Sample records for species distribution modelling
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Hierarchical species distribution models
Hefley, Trevor J.; Hooten, Mevin B.
2016-01-01
Determining the distribution pattern of a species is important to increase scientific knowledge, inform management decisions, and conserve biodiversity. To infer spatial and temporal patterns, species distribution models have been developed for use with many sampling designs and types of data. Recently, it has been shown that count, presence-absence, and presence-only data can be conceptualized as arising from a point process distribution. Therefore, it is important to understand properties of the point process distribution. We examine how the hierarchical species distribution modeling framework has been used to incorporate a wide array of regression and theory-based components while accounting for the data collection process and making use of auxiliary information. The hierarchical modeling framework allows us to demonstrate how several commonly used species distribution models can be derived from the point process distribution, highlight areas of potential overlap between different models, and suggest areas where further research is needed.
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Confronting species distribution model predictions with species functional traits.
Wittmann, Marion E; Barnes, Matthew A; Jerde, Christopher L; Jones, Lisa A; Lodge, David M
2016-02-01
Species distribution models are valuable tools in studies of biogeography, ecology, and climate change and have been used to inform conservation and ecosystem management. However, species distribution models typically incorporate only climatic variables and species presence data. Model development or validation rarely considers functional components of species traits or other types of biological data. We implemented a species distribution model (Maxent) to predict global climate habitat suitability for Grass Carp (Ctenopharyngodon idella). We then tested the relationship between the degree of climate habitat suitability predicted by Maxent and the individual growth rates of both wild (N = 17) and stocked (N = 51) Grass Carp populations using correlation analysis. The Grass Carp Maxent model accurately reflected the global occurrence data (AUC = 0.904). Observations of Grass Carp growth rate covered six continents and ranged from 0.19 to 20.1 g day(-1). Species distribution model predictions were correlated (r = 0.5, 95% CI (0.03, 0.79)) with observed growth rates for wild Grass Carp populations but were not correlated (r = -0.26, 95% CI (-0.5, 0.012)) with stocked populations. Further, a review of the literature indicates that the few studies for other species that have previously assessed the relationship between the degree of predicted climate habitat suitability and species functional traits have also discovered significant relationships. Thus, species distribution models may provide inferences beyond just where a species may occur, providing a useful tool to understand the linkage between species distributions and underlying biological mechanisms.
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Bounding species distribution models
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Thomas J. STOHLGREN, Catherine S. JARNEVICH, Wayne E. ESAIAS,Jeffrey T. MORISETTE
2011-10-01
Full Text Available Species distribution models are increasing in popularity for mapping suitable habitat for species of management concern. Many investigators now recognize that extrapolations of these models with geographic information systems (GIS might be sensitive to the environmental bounds of the data used in their development, yet there is no recommended best practice for “clamping” model extrapolations. We relied on two commonly used modeling approaches: classification and regression tree (CART and maximum entropy (Maxent models, and we tested a simple alteration of the model extrapolations, bounding extrapolations to the maximum and minimum values of primary environmental predictors, to provide a more realistic map of suitable habitat of hybridized Africanized honey bees in the southwestern United States. Findings suggest that multiple models of bounding, and the most conservative bounding of species distribution models, like those presented here, should probably replace the unbounded or loosely bounded techniques currently used [Current Zoology 57 (5: 642–647, 2011].
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Bounding Species Distribution Models
Stohlgren, Thomas J.; Jarnevich, Cahterine S.; Morisette, Jeffrey T.; Esaias, Wayne E.
2011-01-01
Species distribution models are increasing in popularity for mapping suitable habitat for species of management concern. Many investigators now recognize that extrapolations of these models with geographic information systems (GIS) might be sensitive to the environmental bounds of the data used in their development, yet there is no recommended best practice for "clamping" model extrapolations. We relied on two commonly used modeling approaches: classification and regression tree (CART) and maximum entropy (Maxent) models, and we tested a simple alteration of the model extrapolations, bounding extrapolations to the maximum and minimum values of primary environmental predictors, to provide a more realistic map of suitable habitat of hybridized Africanized honey bees in the southwestern United States. Findings suggest that multiple models of bounding, and the most conservative bounding of species distribution models, like those presented here, should probably replace the unbounded or loosely bounded techniques currently used [Current Zoology 57 (5): 642-647, 2011].
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New trends in species distribution modelling
Zimmermann, Niklaus E.; Edwards, Thomas C.; Graham, Catherine H.; Pearman, Peter B.; Svenning, Jens-Christian
2010-01-01
Species distribution modelling has its origin in the late 1970s when computing capacity was limited. Early work in the field concentrated mostly on the development of methods to model effectively the shape of a species' response to environmental gradients (Austin 1987, Austin et al. 1990). The methodology and its framework were summarized in reviews 10–15 yr ago (Franklin 1995, Guisan and Zimmermann 2000), and these syntheses are still widely used as reference landmarks in the current distribution modelling literature. However, enormous advancements have occurred over the last decade, with hundreds – if not thousands – of publications on species distribution model (SDM) methodologies and their application to a broad set of conservation, ecological and evolutionary questions. With this special issue, originating from the third of a set of specialized SDM workshops (2008 Riederalp) entitled 'The Utility of Species Distribution Models as Tools for Conservation Ecology', we reflect on current trends and the progress achieved over the last decade.
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How can model comparison help improving species distribution models?
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Emmanuel Stephan Gritti
Full Text Available Today, more than ever, robust projections of potential species range shifts are needed to anticipate and mitigate the impacts of climate change on biodiversity and ecosystem services. Such projections are so far provided almost exclusively by correlative species distribution models (correlative SDMs. However, concerns regarding the reliability of their predictive power are growing and several authors call for the development of process-based SDMs. Still, each of these methods presents strengths and weakness which have to be estimated if they are to be reliably used by decision makers. In this study we compare projections of three different SDMs (STASH, LPJ and PHENOFIT that lie in the continuum between correlative models and process-based models for the current distribution of three major European tree species, Fagussylvatica L., Quercusrobur L. and Pinussylvestris L. We compare the consistency of the model simulations using an innovative comparison map profile method, integrating local and multi-scale comparisons. The three models simulate relatively accurately the current distribution of the three species. The process-based model performs almost as well as the correlative model, although parameters of the former are not fitted to the observed species distributions. According to our simulations, species range limits are triggered, at the European scale, by establishment and survival through processes primarily related to phenology and resistance to abiotic stress rather than to growth efficiency. The accuracy of projections of the hybrid and process-based model could however be improved by integrating a more realistic representation of the species resistance to water stress for instance, advocating for pursuing efforts to understand and formulate explicitly the impact of climatic conditions and variations on these processes.
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BAYESIAN MODELS FOR SPECIES DISTRIBUTION MODELLING WITH ONLY-PRESENCE RECORDS
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Bartolo de Jesús Villar-Hernández
2015-08-01
Full Text Available One of the central issues in ecology is the study of geographical distribution of species of flora and fauna through Species Distribution Models (SDM. Recently, scientific interest has focused on presence-only records. Two recent approaches have been proposed for this problem: a model based on maximum likelihood method (Maxlike and an inhomogeneous poisson process model (IPP. In this paper we discussed two bayesian approaches called MaxBayes and IPPBayes based on Maxlike and IPP model, respectively. To illustrate these proposals, we implemented two study examples: (1 both models were implemented on a simulated dataset, and (2 we modeled the potencial distribution of genus Dalea in the Tehuacan-Cuicatlán biosphere reserve with both models, the results was compared with that of Maxent. The results show that both models, MaxBayes and IPPBayes, are viable alternatives when species distribution are modeled with only-presence records. For simulated dataset, MaxBayes achieved prevalence estimation, even when the number of records was small. In the real dataset example, both models predict similar potential distributions like Maxent does. Â
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Wisz, Mary Susanne; Pottier, Julien; Kissling, W Daniel; Pellissier, Loïc; Lenoir, Jonathan; Damgaard, Christian F; Dormann, Carsten F; Forchhammer, Mads C; Grytnes, John-Arvid; Guisan, Antoine; Heikkinen, Risto K; Høye, Toke T; Kühn, Ingolf; Luoto, Miska; Maiorano, Luigi; Nilsson, Marie-Charlotte; Normand, Signe; Öckinger, Erik; Schmidt, Niels M; Termansen, Mette; Timmermann, Allan; Wardle, David A; Aastrup, Peter; Svenning, Jens-Christian
2013-02-01
Predicting which species will occur together in the future, and where, remains one of the greatest challenges in ecology, and requires a sound understanding of how the abiotic and biotic environments interact with dispersal processes and history across scales. Biotic interactions and their dynamics influence species' relationships to climate, and this also has important implications for predicting future distributions of species. It is already well accepted that biotic interactions shape species' spatial distributions at local spatial extents, but the role of these interactions beyond local extents (e.g. 10 km(2) to global extents) are usually dismissed as unimportant. In this review we consolidate evidence for how biotic interactions shape species distributions beyond local extents and review methods for integrating biotic interactions into species distribution modelling tools. Drawing upon evidence from contemporary and palaeoecological studies of individual species ranges, functional groups, and species richness patterns, we show that biotic interactions have clearly left their mark on species distributions and realised assemblages of species across all spatial extents. We demonstrate this with examples from within and across trophic groups. A range of species distribution modelling tools is available to quantify species environmental relationships and predict species occurrence, such as: (i) integrating pairwise dependencies, (ii) using integrative predictors, and (iii) hybridising species distribution models (SDMs) with dynamic models. These methods have typically only been applied to interacting pairs of species at a single time, require a priori ecological knowledge about which species interact, and due to data paucity must assume that biotic interactions are constant in space and time. To better inform the future development of these models across spatial scales, we call for accelerated collection of spatially and temporally explicit species data. Ideally
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Incorporating Context Dependency of Species Interactions in Species Distribution Models.
Lany, Nina K; Zarnetske, Phoebe L; Gouhier, Tarik C; Menge, Bruce A
2017-07-01
Species distribution models typically use correlative approaches that characterize the species-environment relationship using occurrence or abundance data for a single species. However, species distributions are determined by both abiotic conditions and biotic interactions with other species in the community. Therefore, climate change is expected to impact species through direct effects on their physiology and indirect effects propagated through their resources, predators, competitors, or mutualists. Furthermore, the sign and strength of species interactions can change according to abiotic conditions, resulting in context-dependent species interactions that may change across space or with climate change. Here, we incorporated the context dependency of species interactions into a dynamic species distribution model. We developed a multi-species model that uses a time-series of observational survey data to evaluate how abiotic conditions and species interactions affect the dynamics of three rocky intertidal species. The model further distinguishes between the direct effects of abiotic conditions on abundance and the indirect effects propagated through interactions with other species. We apply the model to keystone predation by the sea star Pisaster ochraceus on the mussel Mytilus californianus and the barnacle Balanus glandula in the rocky intertidal zone of the Pacific coast, USA. Our method indicated that biotic interactions between P. ochraceus and B. glandula affected B. glandula dynamics across >1000 km of coastline. Consistent with patterns from keystone predation, the growth rate of B. glandula varied according to the abundance of P. ochraceus in the previous year. The data and the model did not indicate that the strength of keystone predation by P. ochraceus varied with a mean annual upwelling index. Balanus glandula cover increased following years with high phytoplankton abundance measured as mean annual chlorophyll-a. M. californianus exhibited the same
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Schipper, Aafke M; Posthuma, Leo; de Zwart, Dick; Huijbregts, Mark A J
2014-12-16
Quantitative relationships between species richness and single environmental factors, also called species sensitivity distributions (SSDs), are helpful to understand and predict biodiversity patterns, identify environmental management options and set environmental quality standards. However, species richness is typically dependent on a variety of environmental factors, implying that it is not straightforward to quantify SSDs from field monitoring data. Here, we present a novel and flexible approach to solve this, based on the method of stacked species distribution modeling. First, a species distribution model (SDM) is established for each species, describing its probability of occurrence in relation to multiple environmental factors. Next, the predictions of the SDMs are stacked along the gradient of each environmental factor with the remaining environmental factors at fixed levels. By varying those fixed levels, our approach can be used to investigate how field-based SSDs for a given environmental factor change in relation to changing confounding influences, including for example optimal, typical, or extreme environmental conditions. This provides an asset in the evaluation of potential management measures to reach good ecological status.
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Incorporating uncertainty in predictive species distribution modelling.
Beale, Colin M; Lennon, Jack J
2012-01-19
Motivated by the need to solve ecological problems (climate change, habitat fragmentation and biological invasions), there has been increasing interest in species distribution models (SDMs). Predictions from these models inform conservation policy, invasive species management and disease-control measures. However, predictions are subject to uncertainty, the degree and source of which is often unrecognized. Here, we review the SDM literature in the context of uncertainty, focusing on three main classes of SDM: niche-based models, demographic models and process-based models. We identify sources of uncertainty for each class and discuss how uncertainty can be minimized or included in the modelling process to give realistic measures of confidence around predictions. Because this has typically not been performed, we conclude that uncertainty in SDMs has often been underestimated and a false precision assigned to predictions of geographical distribution. We identify areas where development of new statistical tools will improve predictions from distribution models, notably the development of hierarchical models that link different types of distribution model and their attendant uncertainties across spatial scales. Finally, we discuss the need to develop more defensible methods for assessing predictive performance, quantifying model goodness-of-fit and for assessing the significance of model covariates.
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Regional climate model downscaling may improve the prediction of alien plant species distributions
Liu, Shuyan; Liang, Xin-Zhong; Gao, Wei; Stohlgren, Thomas J.
2014-12-01
Distributions of invasive species are commonly predicted with species distribution models that build upon the statistical relationships between observed species presence data and climate data. We used field observations, climate station data, and Maximum Entropy species distribution models for 13 invasive plant species in the United States, and then compared the models with inputs from a General Circulation Model (hereafter GCM-based models) and a downscaled Regional Climate Model (hereafter, RCM-based models).We also compared species distributions based on either GCM-based or RCM-based models for the present (1990-1999) to the future (2046-2055). RCM-based species distribution models replicated observed distributions remarkably better than GCM-based models for all invasive species under the current climate. This was shown for the presence locations of the species, and by using four common statistical metrics to compare modeled distributions. For two widespread invasive taxa ( Bromus tectorum or cheatgrass, and Tamarix spp. or tamarisk), GCM-based models failed miserably to reproduce observed species distributions. In contrast, RCM-based species distribution models closely matched observations. Future species distributions may be significantly affected by using GCM-based inputs. Because invasive plants species often show high resilience and low rates of local extinction, RCM-based species distribution models may perform better than GCM-based species distribution models for planning containment programs for invasive species.
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A simple model for skewed species-lifetime distributions
Murase, Yohsuke
2010-06-11
A simple model of a biological community assembly is studied. Communities are assembled by successive migrations and extinctions of species. In the model, species are interacting with each other. The intensity of the interaction between each pair of species is denoted by an interaction coefficient. At each time step, a new species is introduced to the system with randomly assigned interaction coefficients. If the sum of the coefficients, which we call the fitness of a species, is negative, the species goes extinct. The species-lifetime distribution is found to be well characterized by a stretched exponential function with an exponent close to 1/2. This profile agrees not only with more realistic population dynamics models but also with fossil records. We also find that an age-independent and inversely diversity-dependent mortality, which is confirmed in the simulation, is a key mechanism accounting for the distribution. © IOP Publishing Ltd and Deutsche Physikalische Gesellschaft.
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Species distribution model transferability and model grain size - finer may not always be better.
Manzoor, Syed Amir; Griffiths, Geoffrey; Lukac, Martin
2018-05-08
Species distribution models have been used to predict the distribution of invasive species for conservation planning. Understanding spatial transferability of niche predictions is critical to promote species-habitat conservation and forecasting areas vulnerable to invasion. Grain size of predictor variables is an important factor affecting the accuracy and transferability of species distribution models. Choice of grain size is often dependent on the type of predictor variables used and the selection of predictors sometimes rely on data availability. This study employed the MAXENT species distribution model to investigate the effect of the grain size on model transferability for an invasive plant species. We modelled the distribution of Rhododendron ponticum in Wales, U.K. and tested model performance and transferability by varying grain size (50 m, 300 m, and 1 km). MAXENT-based models are sensitive to grain size and selection of variables. We found that over-reliance on the commonly used bioclimatic variables may lead to less accurate models as it often compromises the finer grain size of biophysical variables which may be more important determinants of species distribution at small spatial scales. Model accuracy is likely to increase with decreasing grain size. However, successful model transferability may require optimization of model grain size.
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Species distribution models of tropical deep-sea snappers.
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Céline Gomez
Full Text Available Deep-sea fisheries provide an important source of protein to Pacific Island countries and territories that are highly dependent on fish for food security. However, spatial management of these deep-sea habitats is hindered by insufficient data. We developed species distribution models using spatially limited presence data for the main harvested species in the Western Central Pacific Ocean. We used bathymetric and water temperature data to develop presence-only species distribution models for the commercially exploited deep-sea snappers Etelis Cuvier 1828, Pristipomoides Valenciennes 1830, and Aphareus Cuvier 1830. We evaluated the performance of four different algorithms (CTA, GLM, MARS, and MAXENT within the BIOMOD framework to obtain an ensemble of predicted distributions. We projected these predictions across the Western Central Pacific Ocean to produce maps of potential deep-sea snapper distributions in 32 countries and territories. Depth was consistently the best predictor of presence for all species groups across all models. Bathymetric slope was consistently the poorest predictor. Temperature at depth was a good predictor of presence for GLM only. Model precision was highest for MAXENT and CTA. There were strong regional patterns in predicted distribution of suitable habitat, with the largest areas of suitable habitat (> 35% of the Exclusive Economic Zone predicted in seven South Pacific countries and territories (Fiji, Matthew & Hunter, Nauru, New Caledonia, Tonga, Vanuatu and Wallis & Futuna. Predicted habitat also varied among species, with the proportion of predicted habitat highest for Aphareus and lowest for Etelis. Despite data paucity, the relationship between deep-sea snapper presence and their environments was sufficiently strong to predict their distribution across a large area of the Pacific Ocean. Our results therefore provide a strong baseline for designing monitoring programs that balance resource exploitation and
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Species Distribution Modeling: Comparison of Fixed and Mixed Effects Models Using INLA
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Lara Dutra Silva
2017-12-01
Full Text Available Invasive alien species are among the most important, least controlled, and least reversible of human impacts on the world’s ecosystems, with negative consequences affecting biodiversity and socioeconomic systems. Species distribution models have become a fundamental tool in assessing the potential spread of invasive species in face of their native counterparts. In this study we compared two different modeling techniques: (i fixed effects models accounting for the effect of ecogeographical variables (EGVs; and (ii mixed effects models including also a Gaussian random field (GRF to model spatial correlation (Matérn covariance function. To estimate the potential distribution of Pittosporum undulatum and Morella faya (respectively, invasive and native trees, we used geo-referenced data of their distribution in Pico and São Miguel islands (Azores and topographic, climatic and land use EGVs. Fixed effects models run with maximum likelihood or the INLA (Integrated Nested Laplace Approximation approach provided very similar results, even when reducing the size of the presences data set. The addition of the GRF increased model adjustment (lower Deviance Information Criterion, particularly for the less abundant tree, M. faya. However, the random field parameters were clearly affected by sample size and species distribution pattern. A high degree of spatial autocorrelation was found and should be taken into account when modeling species distribution.
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Finessing atlas data for species distribution models
Niamir, A.; Skidmore, A.K.; Toxopeus, A.G.; Munoz, A.R.; Real, R.
2011-01-01
Aim The spatial resolution of species atlases and therefore resulting model predictions are often too coarse for local applications. Collecting distribution data at a finer resolution for large numbers of species requires a comprehensive sampling effort, making it impractical and expensive. This
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Robinson, Jason L; Fordyce, James A
2017-01-01
Among the greatest challenges facing the conservation of plants and animal species in protected areas are threats from a rapidly changing climate. An altered climate creates both challenges and opportunities for improving the management of protected areas in networks. Increasingly, quantitative tools like species distribution modeling are used to assess the performance of protected areas and predict potential responses to changing climates for groups of species, within a predictive framework. At larger geographic domains and scales, protected area network units have spatial geoclimatic properties that can be described in the gap analysis typically used to measure or aggregate the geographic distributions of species (stacked species distribution models, or S-SDM). We extend the use of species distribution modeling techniques in order to model the climate envelope (or "footprint") of individual protected areas within a network of protected areas distributed across the 48 conterminous United States and managed by the US National Park System. In our approach we treat each protected area as the geographic range of a hypothetical endemic species, then use MaxEnt and 5 uncorrelated BioClim variables to model the geographic distribution of the climatic envelope associated with each protected area unit (modeling the geographic area of park units as the range of a species). We describe the individual and aggregated climate envelopes predicted by a large network of 163 protected areas and briefly illustrate how macroecological measures of geodiversity can be derived from our analysis of the landscape ecological context of protected areas. To estimate trajectories of change in the temporal distribution of climatic features within a protected area network, we projected the climate envelopes of protected areas in current conditions onto a dataset of predicted future climatic conditions. Our results suggest that the climate envelopes of some parks may be locally unique or have
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Sample sizes and model comparison metrics for species distribution models
B.B. Hanberry; H.S. He; D.C. Dey
2012-01-01
Species distribution models use small samples to produce continuous distribution maps. The question of how small a sample can be to produce an accurate model generally has been answered based on comparisons to maximum sample sizes of 200 observations or fewer. In addition, model comparisons often are made with the kappa statistic, which has become controversial....
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Applications of species distribution modeling to paleobiology
DEFF Research Database (Denmark)
Svenning, Jens-Christian; Fløjgaard, Camilla; Marske, Katharine Ann
2011-01-01
-Pleistocene megafaunal extinctions, past community assembly, human paleobiogeography, Holocene paleoecology, and even deep-time biogeography (notably, providing insights into biogeographic dynamics >400 million years ago). We discuss important assumptions and uncertainties that affect the SDM approach to paleobiology......Species distribution modeling (SDM: statistical and/or mechanistic approaches to the assessment of range determinants and prediction of species occurrence) offers new possibilities for estimating and studying past organism distributions. SDM complements fossil and genetic evidence by providing (i......) quantitative and potentially high-resolution predictions of the past organism distributions, (ii) statistically formulated, testable ecological hypotheses regarding past distributions and communities, and (iii) statistical assessment of range determinants. In this article, we provide an overview...
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Species Distribution modeling as a tool to unravel determinants of palm distribution in Thailand
DEFF Research Database (Denmark)
Tovaranonte, Jantrararuk; Barfod, Anders S.; Balslev, Henrik
2011-01-01
As a consequence of the decimation of the forest cover in Thailand from 50% to ca. 20 % since the 1950ies, it is difficult to gain insight in the drivers behind past, present and future distribution ranges of plant species. Species distribution modeling allows visualization of potential species...... distribution under specific sets of assumptions. In this study we used maximum entropy to map potential distributions of 103 species of palms for which more than 5 herbarium records exist. Palms constitute key-stone plant group from both an ecological, economical and conservation perspective. The models were......) and the Area Under the Curve (AUC). All models performed well with AUC scores above 0.95. The predicted distribution ranges showed high suitability for palms in the southern region of Thailand. It also shows that spatial predictor variables are important in cases where historical processes may explain extant...
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Infusing considerations of trophic dependencies into species distribution modelling.
Trainor, Anne M; Schmitz, Oswald J
2014-12-01
Community ecology involves studying the interdependence of species with each other and their environment to predict their geographical distribution and abundance. Modern species distribution analyses characterise species-environment dependency well, but offer only crude approximations of species interdependency. Typically, the dependency between focal species and other species is characterised using other species' point occurrences as spatial covariates to constrain the focal species' predicted range. This implicitly assumes that the strength of interdependency is homogeneous across space, which is not generally supported by analyses of species interactions. This discrepancy has an important bearing on the accuracy of inferences about habitat suitability for species. We introduce a framework that integrates principles from consumer-resource analyses, resource selection theory and species distribution modelling to enhance quantitative prediction of species geographical distributions. We show how to apply the framework using a case study of lynx and snowshoe hare interactions with each other and their environment. The analysis shows how the framework offers a spatially refined understanding of species distribution that is sensitive to nuances in biophysical attributes of the environment that determine the location and strength of species interactions. © 2014 John Wiley & Sons Ltd/CNRS.
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Updating known distribution models for forecasting climate change impact on endangered species.
Muñoz, Antonio-Román; Márquez, Ana Luz; Real, Raimundo
2013-01-01
To plan endangered species conservation and to design adequate management programmes, it is necessary to predict their distributional response to climate change, especially under the current situation of rapid change. However, these predictions are customarily done by relating de novo the distribution of the species with climatic conditions with no regard of previously available knowledge about the factors affecting the species distribution. We propose to take advantage of known species distribution models, but proceeding to update them with the variables yielded by climatic models before projecting them to the future. To exemplify our proposal, the availability of suitable habitat across Spain for the endangered Bonelli's Eagle (Aquila fasciata) was modelled by updating a pre-existing model based on current climate and topography to a combination of different general circulation models and Special Report on Emissions Scenarios. Our results suggested that the main threat for this endangered species would not be climate change, since all forecasting models show that its distribution will be maintained and increased in mainland Spain for all the XXI century. We remark on the importance of linking conservation biology with distribution modelling by updating existing models, frequently available for endangered species, considering all the known factors conditioning the species' distribution, instead of building new models that are based on climate change variables only.
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Thematic and spatial resolutions affect model-based predictions of tree species distribution.
Liang, Yu; He, Hong S; Fraser, Jacob S; Wu, ZhiWei
2013-01-01
Subjective decisions of thematic and spatial resolutions in characterizing environmental heterogeneity may affect the characterizations of spatial pattern and the simulation of occurrence and rate of ecological processes, and in turn, model-based tree species distribution. Thus, this study quantified the importance of thematic and spatial resolutions, and their interaction in predictions of tree species distribution (quantified by species abundance). We investigated how model-predicted species abundances changed and whether tree species with different ecological traits (e.g., seed dispersal distance, competitive capacity) had different responses to varying thematic and spatial resolutions. We used the LANDIS forest landscape model to predict tree species distribution at the landscape scale and designed a series of scenarios with different thematic (different numbers of land types) and spatial resolutions combinations, and then statistically examined the differences of species abundance among these scenarios. Results showed that both thematic and spatial resolutions affected model-based predictions of species distribution, but thematic resolution had a greater effect. Species ecological traits affected the predictions. For species with moderate dispersal distance and relatively abundant seed sources, predicted abundance increased as thematic resolution increased. However, for species with long seeding distance or high shade tolerance, thematic resolution had an inverse effect on predicted abundance. When seed sources and dispersal distance were not limiting, the predicted species abundance increased with spatial resolution and vice versa. Results from this study may provide insights into the choice of thematic and spatial resolutions for model-based predictions of tree species distribution.
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Modeling the Distribution of Rare or Cryptic Bird Species of Taiwan
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Tsai-Yu Wu
2012-12-01
Full Text Available For the study of the macroecology and conservation of Taiwan’s birds, there was an urgent need to develop distribution models of bird species whose distribution had never before been modeled. Therefore, we here model the distributions of 27 mostly rare and cryptic breeding bird species using a statistical approach which has been shown to be especially reliable for modeling species with a low sample size of presence localities, namely the maximum entropy (Maxent modeling technique. For this purpose, we began with a dedicated attempt to collate as much high-quality distributional data as possible, assembling databases from several scientific reports, contacting individual data recorders and searching publicly accessible database, the internet and the available literature. This effort resulted in 2022 grid cells of 1 × 1 km size being associated with a presence record for one of the 27 species. These records and 10 pre-selected environmental variables were then used to model each species’ probability distribution which we show here with all grid cells below the lowest presence threshold being converted to zeros. We then in detail discuss the interpretation and applicability of these distributions, whereby we pay close attention to habitat requirements, the intactness and fragmentation of their habitat, the general detectability of the species and data reliability. This study is another one in an ongoing series of studies which highlight the usefulness of using large electronic databases and modern analytical methods to help with the monitoring and assessment of Taiwan’s bird species.
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Species Distribution Modelling: Contrasting presence-only models with plot abundance data.
Gomes, Vitor H F; IJff, Stéphanie D; Raes, Niels; Amaral, Iêda Leão; Salomão, Rafael P; de Souza Coelho, Luiz; de Almeida Matos, Francisca Dionízia; Castilho, Carolina V; de Andrade Lima Filho, Diogenes; López, Dairon Cárdenas; Guevara, Juan Ernesto; Magnusson, William E; Phillips, Oliver L; Wittmann, Florian; de Jesus Veiga Carim, Marcelo; Martins, Maria Pires; Irume, Mariana Victória; Sabatier, Daniel; Molino, Jean-François; Bánki, Olaf S; da Silva Guimarães, José Renan; Pitman, Nigel C A; Piedade, Maria Teresa Fernandez; Mendoza, Abel Monteagudo; Luize, Bruno Garcia; Venticinque, Eduardo Martins; de Leão Novo, Evlyn Márcia Moraes; Vargas, Percy Núñez; Silva, Thiago Sanna Freire; Manzatto, Angelo Gilberto; Terborgh, John; Reis, Neidiane Farias Costa; Montero, Juan Carlos; Casula, Katia Regina; Marimon, Beatriz S; Marimon, Ben-Hur; Coronado, Euridice N Honorio; Feldpausch, Ted R; Duque, Alvaro; Zartman, Charles Eugene; Arboleda, Nicolás Castaño; Killeen, Timothy J; Mostacedo, Bonifacio; Vasquez, Rodolfo; Schöngart, Jochen; Assis, Rafael L; Medeiros, Marcelo Brilhante; Simon, Marcelo Fragomeni; Andrade, Ana; Laurance, William F; Camargo, José Luís; Demarchi, Layon O; Laurance, Susan G W; de Sousa Farias, Emanuelle; Nascimento, Henrique Eduardo Mendonça; Revilla, Juan David Cardenas; Quaresma, Adriano; Costa, Flavia R C; Vieira, Ima Célia Guimarães; Cintra, Bruno Barçante Ladvocat; Castellanos, Hernán; Brienen, Roel; Stevenson, Pablo R; Feitosa, Yuri; Duivenvoorden, Joost F; Aymard C, Gerardo A; Mogollón, Hugo F; Targhetta, Natalia; Comiskey, James A; Vicentini, Alberto; Lopes, Aline; Damasco, Gabriel; Dávila, Nállarett; García-Villacorta, Roosevelt; Levis, Carolina; Schietti, Juliana; Souza, Priscila; Emilio, Thaise; Alonso, Alfonso; Neill, David; Dallmeier, Francisco; Ferreira, Leandro Valle; Araujo-Murakami, Alejandro; Praia, Daniel; do Amaral, Dário Dantas; Carvalho, Fernanda Antunes; de Souza, Fernanda Coelho; Feeley, Kenneth; Arroyo, Luzmila; Pansonato, Marcelo Petratti; Gribel, Rogerio; Villa, Boris; Licona, Juan Carlos; Fine, Paul V A; Cerón, Carlos; Baraloto, Chris; Jimenez, Eliana M; Stropp, Juliana; Engel, Julien; Silveira, Marcos; Mora, Maria Cristina Peñuela; Petronelli, Pascal; Maas, Paul; Thomas-Caesar, Raquel; Henkel, Terry W; Daly, Doug; Paredes, Marcos Ríos; Baker, Tim R; Fuentes, Alfredo; Peres, Carlos A; Chave, Jerome; Pena, Jose Luis Marcelo; Dexter, Kyle G; Silman, Miles R; Jørgensen, Peter Møller; Pennington, Toby; Di Fiore, Anthony; Valverde, Fernando Cornejo; Phillips, Juan Fernando; Rivas-Torres, Gonzalo; von Hildebrand, Patricio; van Andel, Tinde R; Ruschel, Ademir R; Prieto, Adriana; Rudas, Agustín; Hoffman, Bruce; Vela, César I A; Barbosa, Edelcilio Marques; Zent, Egleé L; Gonzales, George Pepe Gallardo; Doza, Hilda Paulette Dávila; de Andrade Miranda, Ires Paula; Guillaumet, Jean-Louis; Pinto, Linder Felipe Mozombite; de Matos Bonates, Luiz Carlos; Silva, Natalino; Gómez, Ricardo Zárate; Zent, Stanford; Gonzales, Therany; Vos, Vincent A; Malhi, Yadvinder; Oliveira, Alexandre A; Cano, Angela; Albuquerque, Bianca Weiss; Vriesendorp, Corine; Correa, Diego Felipe; Torre, Emilio Vilanova; van der Heijden, Geertje; Ramirez-Angulo, Hirma; Ramos, José Ferreira; Young, Kenneth R; Rocha, Maira; Nascimento, Marcelo Trindade; Medina, Maria Natalia Umaña; Tirado, Milton; Wang, Ophelia; Sierra, Rodrigo; Torres-Lezama, Armando; Mendoza, Casimiro; Ferreira, Cid; Baider, Cláudia; Villarroel, Daniel; Balslev, Henrik; Mesones, Italo; Giraldo, Ligia Estela Urrego; Casas, Luisa Fernanda; Reategui, Manuel Augusto Ahuite; Linares-Palomino, Reynaldo; Zagt, Roderick; Cárdenas, Sasha; Farfan-Rios, William; Sampaio, Adeilza Felipe; Pauletto, Daniela; Sandoval, Elvis H Valderrama; Arevalo, Freddy Ramirez; Huamantupa-Chuquimaco, Isau; Garcia-Cabrera, Karina; Hernandez, Lionel; Gamarra, Luis Valenzuela; Alexiades, Miguel N; Pansini, Susamar; Cuenca, Walter Palacios; Milliken, William; Ricardo, Joana; Lopez-Gonzalez, Gabriela; Pos, Edwin; Ter Steege, Hans
2018-01-17
Species distribution models (SDMs) are widely used in ecology and conservation. Presence-only SDMs such as MaxEnt frequently use natural history collections (NHCs) as occurrence data, given their huge numbers and accessibility. NHCs are often spatially biased which may generate inaccuracies in SDMs. Here, we test how the distribution of NHCs and MaxEnt predictions relates to a spatial abundance model, based on a large plot dataset for Amazonian tree species, using inverse distance weighting (IDW). We also propose a new pipeline to deal with inconsistencies in NHCs and to limit the area of occupancy of the species. We found a significant but weak positive relationship between the distribution of NHCs and IDW for 66% of the species. The relationship between SDMs and IDW was also significant but weakly positive for 95% of the species, and sensitivity for both analyses was high. Furthermore, the pipeline removed half of the NHCs records. Presence-only SDM applications should consider this limitation, especially for large biodiversity assessments projects, when they are automatically generated without subsequent checking. Our pipeline provides a conservative estimate of a species' area of occupancy, within an area slightly larger than its extent of occurrence, compatible to e.g. IUCN red list assessments.
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Mainali, Kumar P; Warren, Dan L; Dhileepan, Kunjithapatham; McConnachie, Andrew; Strathie, Lorraine; Hassan, Gul; Karki, Debendra; Shrestha, Bharat B; Parmesan, Camille
2015-12-01
Modeling the distributions of species, especially of invasive species in non-native ranges, involves multiple challenges. Here, we developed some novel approaches to species distribution modeling aimed at reducing the influences of such challenges and improving the realism of projections. We estimated species-environment relationships for Parthenium hysterophorus L. (Asteraceae) with four modeling methods run with multiple scenarios of (i) sources of occurrences and geographically isolated background ranges for absences, (ii) approaches to drawing background (absence) points, and (iii) alternate sets of predictor variables. We further tested various quantitative metrics of model evaluation against biological insight. Model projections were very sensitive to the choice of training dataset. Model accuracy was much improved using a global dataset for model training, rather than restricting data input to the species' native range. AUC score was a poor metric for model evaluation and, if used alone, was not a useful criterion for assessing model performance. Projections away from the sampled space (i.e., into areas of potential future invasion) were very different depending on the modeling methods used, raising questions about the reliability of ensemble projections. Generalized linear models gave very unrealistic projections far away from the training region. Models that efficiently fit the dominant pattern, but exclude highly local patterns in the dataset and capture interactions as they appear in data (e.g., boosted regression trees), improved generalization of the models. Biological knowledge of the species and its distribution was important in refining choices about the best set of projections. A post hoc test conducted on a new Parthenium dataset from Nepal validated excellent predictive performance of our 'best' model. We showed that vast stretches of currently uninvaded geographic areas on multiple continents harbor highly suitable habitats for parthenium
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The effects of model and data complexity on predictions from species distributions models
DEFF Research Database (Denmark)
García-Callejas, David; Bastos, Miguel
2016-01-01
How complex does a model need to be to provide useful predictions is a matter of continuous debate across environmental sciences. In the species distributions modelling literature, studies have demonstrated that more complex models tend to provide better fits. However, studies have also shown...... that predictive performance does not always increase with complexity. Testing of species distributions models is challenging because independent data for testing are often lacking, but a more general problem is that model complexity has never been formally described in such studies. Here, we systematically...
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Five (or so) challenges for species distribution modelling
DEFF Research Database (Denmark)
Bastos Araujo, Miguel; Guisan, Antoine
2006-01-01
Species distribution modelling is central to both fundamental and applied research in biogeography. Despite widespread use of models, there are still important conceptual ambiguities as well as biotic and algorithmic uncertainties that need to be investigated in order to increase confidence in mo...
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Implications of movement for species distribution models - Rethinking environmental data tools.
Bruneel, Stijn; Gobeyn, Sacha; Verhelst, Pieterjan; Reubens, Jan; Moens, Tom; Goethals, Peter
2018-07-01
Movement is considered an essential process in shaping the distributions of species. Nevertheless, most species distribution models (SDMs) still focus solely on environment-species relationships to predict the occurrence of species. Furthermore, the currently used indirect estimates of movement allow to assess habitat accessibility, but do not provide an accurate description of movement. Better proxies of movement are needed to assess the dispersal potential of individual species and to gain a more practical insight in the interconnectivity of communities. Telemetry techniques are rapidly evolving and highly capable to provide explicit descriptions of movement, but their usefulness for SDMs will mainly depend on the ability of these models to deal with hitherto unconsidered ecological processes. More specifically, the integration of movement is likely to affect the environmental data requirements as the connection between environmental and biological data is crucial to provide reliable results. Mobility implies the occupancy of a continuum of space, hence an adequate representation of both geographical and environmental space is paramount to study mobile species distributions. In this context, environmental models, remote sensing techniques and animal-borne environmental sensors are discussed as potential techniques to obtain suitable environmental data. In order to provide an in-depth review of the aforementioned methods, we have chosen to use the modelling of fish distributions as a case study. The high mobility of fish and the often highly variable nature of the aquatic environment generally complicate model development, making it an adequate subject for research. Furthermore, insight into the distribution of fish is of great interest for fish stock assessments and water management worldwide, underlining its practical relevance. Copyright © 2018 Elsevier B.V. All rights reserved.
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Directory of Open Access Journals (Sweden)
Thibaud Rougier
Full Text Available Species can respond to climate change by tracking appropriate environmental conditions in space, resulting in a range shift. Species Distribution Models (SDMs can help forecast such range shift responses. For few species, both correlative and mechanistic SDMs were built, but allis shad (Alosa alosa, an endangered anadromous fish species, is one of them. The main purpose of this study was to provide a framework for joint analyses of correlative and mechanistic SDMs projections in order to strengthen conservation measures for species of conservation concern. Guidelines for joint representation and subsequent interpretation of models outputs were defined and applied. The present joint analysis was based on the novel mechanistic model GR3D (Global Repositioning Dynamics of Diadromous fish Distribution which was parameterized on allis shad and then used to predict its future distribution along the European Atlantic coast under different climate change scenarios (RCP 4.5 and RCP 8.5. We then used a correlative SDM for this species to forecast its distribution across the same geographic area and under the same climate change scenarios. First, projections from correlative and mechanistic models provided congruent trends in probability of habitat suitability and population dynamics. This agreement was preferentially interpreted as referring to the species vulnerability to climate change. Climate change could not be accordingly listed as a major threat for allis shad. The congruence in predicted range limits between SDMs projections was the next point of interest. The difference, when noticed, required to deepen our understanding of the niche modelled by each approach. In this respect, the relative position of the northern range limit between the two methods strongly suggested here that a key biological process related to intraspecific variability was potentially lacking in the mechanistic SDM. Based on our knowledge, we hypothesized that local
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Predicting weed problems in maize cropping by species distribution modelling
Directory of Open Access Journals (Sweden)
Bürger, Jana
2014-02-01
Full Text Available Increasing maize cultivation and changed cropping practices promote the selection of typical maize weeds that may also profit strongly from climate change. Predicting potential weed problems is of high interest for plant production. Within the project KLIFF, experiments were combined with species distribution modelling for this task in the region of Lower Saxony, Germany. For our study, we modelled ecological and damage niches of nine weed species that are significant and wide spread in maize cropping in a number of European countries. Species distribution models describe the ecological niche of a species, these are the environmental conditions under which a species can maintain a vital population. It is also possible to estimate a damage niche, i.e. the conditions under which a species causes damage in agricultural crops. For this, we combined occurrence data of European national data bases with high resolution climate, soil and land use data. Models were also projected to simulated climate conditions for the time horizon 2070 - 2100 in order to estimate climate change effects. Modelling results indicate favourable conditions for typical maize weed occurrence virtually all over the study region, but only a few species are important in maize cropping. This is in good accordance with the findings of an earlier maize weed monitoring. Reaction to changing climate conditions is species-specific, for some species neutral (E. crus-galli, other species may gain (Polygonum persicaria or loose (Viola arvensis large areas of suitable habitats. All species with damage potential under present conditions will remain important in maize cropping, some more species will gain regional importance (Calystegia sepium, Setara viridis.
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Species distribution modeling based on the automated identification of citizen observations.
Botella, Christophe; Joly, Alexis; Bonnet, Pierre; Monestiez, Pascal; Munoz, François
2018-02-01
A species distribution model computed with automatically identified plant observations was developed and evaluated to contribute to future ecological studies. We used deep learning techniques to automatically identify opportunistic plant observations made by citizens through a popular mobile application. We compared species distribution modeling of invasive alien plants based on these data to inventories made by experts. The trained models have a reasonable predictive effectiveness for some species, but they are biased by the massive presence of cultivated specimens. The method proposed here allows for fine-grained and regular monitoring of some species of interest based on opportunistic observations. More in-depth investigation of the typology of the observations and the sampling bias should help improve the approach in the future.
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Mechanistic species distribution modelling as a link between physiology and conservation.
Evans, Tyler G; Diamond, Sarah E; Kelly, Morgan W
2015-01-01
Climate change conservation planning relies heavily on correlative species distribution models that estimate future areas of occupancy based on environmental conditions encountered in present-day ranges. The approach benefits from rapid assessment of vulnerability over a large number of organisms, but can have poor predictive power when transposed to novel environments and reveals little in the way of causal mechanisms that define changes in species distribution or abundance. Having conservation planning rely largely on this single approach also increases the risk of policy failure. Mechanistic models that are parameterized with physiological information are expected to be more robust when extrapolating distributions to future environmental conditions and can identify physiological processes that set range boundaries. Implementation of mechanistic species distribution models requires knowledge of how environmental change influences physiological performance, and because this information is currently restricted to a comparatively small number of well-studied organisms, use of mechanistic modelling in the context of climate change conservation is limited. In this review, we propose that the need to develop mechanistic models that incorporate physiological data presents an opportunity for physiologists to contribute more directly to climate change conservation and advance the field of conservation physiology. We begin by describing the prevalence of species distribution modelling in climate change conservation, highlighting the benefits and drawbacks of both mechanistic and correlative approaches. Next, we emphasize the need to expand mechanistic models and discuss potential metrics of physiological performance suitable for integration into mechanistic models. We conclude by summarizing other factors, such as the need to consider demography, limiting broader application of mechanistic models in climate change conservation. Ideally, modellers, physiologists and
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Using species abundance distribution models and diversity indices for biogeographical analyses
Fattorini, Simone; Rigal, François; Cardoso, Pedro; Borges, Paulo A. V.
2016-01-01
We examine whether Species Abundance Distribution models (SADs) and diversity indices can describe how species colonization status influences species community assembly on oceanic islands. Our hypothesis is that, because of the lack of source-sink dynamics at the archipelago scale, Single Island Endemics (SIEs), i.e. endemic species restricted to only one island, should be represented by few rare species and consequently have abundance patterns that differ from those of more widespread species. To test our hypothesis, we used arthropod data from the Azorean archipelago (North Atlantic). We divided the species into three colonization categories: SIEs, archipelagic endemics (AZEs, present in at least two islands) and native non-endemics (NATs). For each category, we modelled rank-abundance plots using both the geometric series and the Gambin model, a measure of distributional amplitude. We also calculated Shannon entropy and Buzas and Gibson's evenness. We show that the slopes of the regression lines modelling SADs were significantly higher for SIEs, which indicates a relative predominance of a few highly abundant species and a lack of rare species, which also depresses diversity indices. This may be a consequence of two factors: (i) some forest specialist SIEs may be at advantage over other, less adapted species; (ii) the entire populations of SIEs are by definition concentrated on a single island, without possibility for inter-island source-sink dynamics; hence all populations must have a minimum number of individuals to survive natural, often unpredictable, fluctuations. These findings are supported by higher values of the α parameter of the Gambin mode for SIEs. In contrast, AZEs and NATs had lower regression slopes, lower α but higher diversity indices, resulting from their widespread distribution over several islands. We conclude that these differences in the SAD models and diversity indices demonstrate that the study of these metrics is useful for
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Martin-StPaul, N. K.; Ay, J. S.; Guillemot, J.; Doyen, L.; Leadley, P.
2014-12-01
Species distribution models (SDMs) are widely used to study and predict the outcome of global changes on species. In human dominated ecosystems the presence of a given species is the result of both its ecological suitability and human footprint on nature such as land use choices. Land use choices may thus be responsible for a selection bias in the presence/absence data used in SDM calibration. We present a structural modelling approach (i.e. based on structural equation modelling) that accounts for this selection bias. The new structural species distribution model (SSDM) estimates simultaneously land use choices and species responses to bioclimatic variables. A land use equation based on an econometric model of landowner choices was joined to an equation of species response to bioclimatic variables. SSDM allows the residuals of both equations to be dependent, taking into account the possibility of shared omitted variables and measurement errors. We provide a general description of the statistical theory and a set of applications on forest trees over France using databases of climate and forest inventory at different spatial resolution (from 2km to 8km). We also compared the outputs of the SSDM with outputs of a classical SDM (i.e. Biomod ensemble modelling) in terms of bioclimatic response curves and potential distributions under current climate and climate change scenarios. The shapes of the bioclimatic response curves and the modelled species distribution maps differed markedly between SSDM and classical SDMs, with contrasted patterns according to species and spatial resolutions. The magnitude and directions of these differences were dependent on the correlations between the errors from both equations and were highest for higher spatial resolutions. A first conclusion is that the use of classical SDMs can potentially lead to strong miss-estimation of the actual and future probability of presence modelled. Beyond this selection bias, the SSDM we propose represents
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DEFF Research Database (Denmark)
Eskildsen, Anne; LeRoux, Peter C.; Heikkinen, Risto K.
2013-01-01
changes at expanding range margins can be predicted accurately. Location. Finland. Methods. Using 10-km resolution butterfly atlas data from two periods, 1992–1999 (t1) and 2002–2009 (t2), with a significant between-period temperature increase, we modelled the effects of climatic warming on butterfly...... butterfly distributions under climate change. Model performance was lower with independent compared to non-independent validation and improved when land cover and soil type variables were included, compared to climate-only models. SDMs performed less well for highly mobile species and for species with long......Aim. To quantify whether species distribution models (SDMs) can reliably forecast species distributions under observed climate change. In particular, to test whether the predictive ability of SDMs depends on species traits or the inclusion of land cover and soil type, and whether distributional...
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Lany, Nina K; Zarnetske, Phoebe L; Schliep, Erin M; Schaeffer, Robert N; Orians, Colin M; Orwig, David A; Preisser, Evan L
2018-05-01
A species' distribution and abundance are determined by abiotic conditions and biotic interactions with other species in the community. Most species distribution models correlate the occurrence of a single species with environmental variables only, and leave out biotic interactions. To test the importance of biotic interactions on occurrence and abundance, we compared a multivariate spatiotemporal model of the joint abundance of two invasive insects that share a host plant, hemlock woolly adelgid (HWA; Adelges tsugae) and elongate hemlock scale (EHS; Fiorina externa), to independent models that do not account for dependence among co-occurring species. The joint model revealed that HWA responded more strongly to abiotic conditions than EHS. Additionally, HWA appeared to predispose stands to subsequent increase of EHS, but HWA abundance was not strongly dependent on EHS abundance. This study demonstrates how incorporating spatial and temporal dependence into a species distribution model can reveal the dependence of a species' abundance on other species in the community. Accounting for dependence among co-occurring species with a joint distribution model can also improve estimation of the abiotic niche for species affected by interspecific interactions. © 2018 by the Ecological Society of America.
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Current state of the art for statistical modeling of species distributions [Chapter 16
Troy M. Hegel; Samuel A. Cushman; Jeffrey Evans; Falk Huettmann
2010-01-01
Over the past decade the number of statistical modelling tools available to ecologists to model species' distributions has increased at a rapid pace (e.g. Elith et al. 2006; Austin 2007), as have the number of species distribution models (SDM) published in the literature (e.g. Scott et al. 2002). Ten years ago, basic logistic regression (Hosmer and Lemeshow 2000)...
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Mechanistic species distribution modeling reveals a niche shift during invasion.
Chapman, Daniel S; Scalone, Romain; Štefanić, Edita; Bullock, James M
2017-06-01
Niche shifts of nonnative plants can occur when they colonize novel climatic conditions. However, the mechanistic basis for niche shifts during invasion is poorly understood and has rarely been captured within species distribution models. We quantified the consequence of between-population variation in phenology for invasion of common ragweed (Ambrosia artemisiifolia L.) across Europe. Ragweed is of serious concern because of its harmful effects as a crop weed and because of its impact on public health as a major aeroallergen. We developed a forward mechanistic species distribution model based on responses of ragweed development rates to temperature and photoperiod. The model was parameterized and validated from the literature and by reanalyzing data from a reciprocal common garden experiment in which native and invasive populations were grown within and beyond the current invaded range. It could therefore accommodate between-population variation in the physiological requirements for flowering, and predict the potentially invaded ranges of individual populations. Northern-origin populations that were established outside the generally accepted climate envelope of the species had lower thermal requirements for bud development, suggesting local adaptation of phenology had occurred during the invasion. The model predicts that this will extend the potentially invaded range northward and increase the average suitability across Europe by 90% in the current climate and 20% in the future climate. Therefore, trait variation observed at the population scale can trigger a climatic niche shift at the biogeographic scale. For ragweed, earlier flowering phenology in established northern populations could allow the species to spread beyond its current invasive range, substantially increasing its risk to agriculture and public health. Mechanistic species distribution models offer the possibility to represent niche shifts by varying the traits and niche responses of individual
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Using Environmental DNA to Improve Species Distribution Models for Freshwater Invaders
Directory of Open Access Journals (Sweden)
Teja P. Muha
2017-12-01
Full Text Available Species Distribution Models (SDMs have been reported as a useful tool for the risk assessment and modeling of the pathways of dispersal of freshwater invasive alien species (IAS. Environmental DNA (eDNA is a novel tool that can help detect IAS at their early stage of introduction and additionally improve the data available for a more efficient management. SDMs rely on presence and absence of the species in the study area to infer the predictors affecting species distributions. Presence is verified once a species is detected, but confirmation of absence can be problematic because this depends both on the detectability of the species and the sampling strategy. eDNA is a technique that presents higher detectability and accuracy in comparison to conventional sampling techniques, and can effectively differentiate between presence or absence of specific species or entire communities by using a barcoding or metabarcoding approach. However, a number of potential bias can be introduced during (i sampling, (ii amplification, (iii sequencing, or (iv through the usage of bioinformatics pipelines. Therefore, it is important to report and conduct the field and laboratory procedures in a consistent way, by (i introducing eDNA independent observations, (ii amplifying and sequencing control samples, (iii achieving quality sequence reads by appropriate clean-up steps, (iv controlling primer amplification preferences, (v introducing PCR-free sequence capturing, (vi estimating primer detection capabilities through controlled experiments and/or (vii post-hoc introduction of “site occupancy-detection models.” With eDNA methodology becoming increasingly routine, its use is strongly recommended to retrieve species distributional data for SDMs.
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Species Distribution Modelling of Aedes aegypti in two dengue-endemic regions of Pakistan.
Fatima, Syeda Hira; Atif, Salman; Rasheed, Syed Basit; Zaidi, Farrah; Hussain, Ejaz
2016-03-01
Statistical tools are effectively used to determine the distribution of mosquitoes and to make ecological inferences about the vector-borne disease dynamics. In this study, we utilised species distribution models to understand spatial patterns of Aedes aegypti in two dengue-prevalent regions of Pakistan, Lahore and Swat. Species distribution models can potentially indicate the probability of suitability of Ae. aegypti once introduced to new regions like Swat, where invasion of this species is a recent phenomenon. The distribution of Ae. aegypti was determined by applying the MaxEnt algorithm on a set of potential environmental factors and species sample records. The ecological dependency of species on each environmental variable was analysed using response curves. We quantified the statistical performance of the models based on accuracy assessment and spatial predictions. Our results suggest that Ae. aegypti is widely distributed in Lahore. Human population density and urban infrastructure are primarily responsible for greater probability of mosquito occurrence in this region. In Swat, Ae. aegypti has clumped distribution, where urban patches provide refuge to the species in an otherwise hostile heterogeneous environment and road networks are assumed to have facilitated in passive-mediated dispersal of species. In Pakistan, Ae. aegypti is expanding its range northwards; this could be associated with rapid urbanisation, trade and travel. The main implication of this expansion is that more people are at risk of dengue fever in the northern highlands of Pakistan. © 2016 John Wiley & Sons Ltd.
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Aguirre-Gutiérrez, Jesús; Carvalheiro, Luísa G; Polce, Chiara; van Loon, E Emiel; Raes, Niels; Reemer, Menno; Biesmeijer, Jacobus C
2013-01-01
Understanding species distributions and the factors limiting them is an important topic in ecology and conservation, including in nature reserve selection and predicting climate change impacts. While Species Distribution Models (SDM) are the main tool used for these purposes, choosing the best SDM algorithm is not straightforward as these are plentiful and can be applied in many different ways. SDM are used mainly to gain insight in 1) overall species distributions, 2) their past-present-future probability of occurrence and/or 3) to understand their ecological niche limits (also referred to as ecological niche modelling). The fact that these three aims may require different models and outputs is, however, rarely considered and has not been evaluated consistently. Here we use data from a systematically sampled set of species occurrences to specifically test the performance of Species Distribution Models across several commonly used algorithms. Species range in distribution patterns from rare to common and from local to widespread. We compare overall model fit (representing species distribution), the accuracy of the predictions at multiple spatial scales, and the consistency in selection of environmental correlations all across multiple modelling runs. As expected, the choice of modelling algorithm determines model outcome. However, model quality depends not only on the algorithm, but also on the measure of model fit used and the scale at which it is used. Although model fit was higher for the consensus approach and Maxent, Maxent and GAM models were more consistent in estimating local occurrence, while RF and GBM showed higher consistency in environmental variables selection. Model outcomes diverged more for narrowly distributed species than for widespread species. We suggest that matching study aims with modelling approach is essential in Species Distribution Models, and provide suggestions how to do this for different modelling aims and species' data
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Species Distribution Modelling: Contrasting presence-only models with plot abundance data
Gomes, Vitor H.F.; Ijff, Stéphanie D.; Raes, Niels; Amaral, Iêda Leão; Salomão, Rafael P.; Coelho, Luiz De Souza; Matos, Francisca Dionízia De Almeida; Castilho, Carolina V.; Filho, Diogenes De Andrade Lima; López, Dairon Cárdenas; Guevara, Juan Ernesto; Magnusson, William E.; Phillips, Oliver L.; Wittmann, Florian; Carim, Marcelo De Jesus Veiga; Martins, Maria Pires; Irume, Mariana Victória; Sabatier, Daniel; Molino, Jean François; Bánki, Olaf S.; Guimarães, José Renan Da Silva; Pitman, Nigel C.A.; Piedade, Maria Teresa Fernandez; Mendoza, Abel Monteagudo; Luize, Bruno Garcia; Venticinque, Eduardo Martins; Novo, Evlyn Márcia Moraes De Leão; Vargas, Percy Núñez; Silva, Thiago Sanna Freire; Manzatto, Angelo Gilberto; Terborgh, John; Reis, Neidiane Farias Costa; Montero, Juan Carlos; Casula, Katia Regina; Marimon, Beatriz S.; Marimon, Ben Hur; Coronado, Euridice N.Honorio; Feldpausch, Ted R.; Duque, Alvaro; Zartman, Charles Eugene; Arboleda, Nicolás Castaño; Killeen, Timothy J.; Mostacedo, Bonifacio; Vasquez, Rodolfo; Schöngart, Jochen; Assis, Rafael L.; Medeiros, Marcelo Brilhante; Simon, Marcelo Fragomeni; Andrade, Ana; Laurance, William F.; Camargo, José Luís; Demarchi, Layon O.; Laurance, Susan G.W.; Farias, Emanuelle De Sousa; Nascimento, Henrique Eduardo Mendonça; Revilla, Juan David Cardenas; Quaresma, Adriano; Costa, Flavia R.C.; Vieira, Ima Célia Guimarães; Cintra, Bruno Barçante Ladvocat; Castellanos, Hernán; Brienen, Roel; Stevenson, Pablo R.; Feitosa, Yuri; Duivenvoorden, Joost F.; Aymard, Gerardo A.C.; Mogollón, Hugo F.; Targhetta, Natalia; Comiskey, James A.; Vicentini, Alberto; Lopes, Aline; Damasco, Gabriel; Dávila, Nállarett; García-Villacorta, Roosevelt; Levis, Carolina; Schietti, Juliana; Souza, Priscila; Emilio, Thaise; Alonso, Alfonso; Neill, David; Dallmeier, Francisco; Ferreira, Leandro Valle; Araujo-Murakami, Alejandro; Praia, Daniel; Do Amaral, Dário Dantas; Carvalho, Fernanda Antunes; De Souza, Fernanda Coelho; Feeley, Kenneth; Arroyo, Luzmila; Pansonato, Marcelo Petratti; Gribel, Rogerio; Villa, Boris; Licona, Juan Carlos; Fine, Paul V.A.; Cerón, Carlos; Baraloto, Chris; Jimenez, Eliana M.; Stropp, Juliana; Engel, Julien; Silveira, Marcos; Mora, Maria Cristina Peñuela; Petronelli, Pascal; Maas, Paul; Thomas-Caesar, Raquel; Henkel, Terry W.; Daly, Doug; Paredes, Marcos Ríos; Baker, Tim R.; Fuentes, Alfredo; Peres, Carlos A.; Chave, Jerome; Pena, Jose Luis Marcelo; Dexter, Kyle G.; Silman, Miles R.; Jørgensen, Peter Møller; Pennington, Toby; Di Fiore, Anthony; Valverde, Fernando Cornejo; Phillips, Juan Fernando; Rivas-Torres, Gonzalo; Von Hildebrand, Patricio; Van Andel, Tinde R.; Ruschel, Ademir R.; Prieto, Adriana; Rudas, Agustín; Hoffman, Bruce; Vela, César I.A.; Barbosa, Edelcilio Marques; Zent, Egleé L.; Gonzales, George Pepe Gallardo; Doza, Hilda Paulette Dávila; Miranda, Ires Paula De Andrade; Guillaumet, Jean Louis; Pinto, Linder Felipe Mozombite; Bonates, Luiz Carlos De Matos; Silva, Natalino; Gómez, Ricardo Zárate; Zent, Stanford; Gonzales, Therany; Vos, Vincent A.; Malhi, Yadvinder; Oliveira, Alexandre A.; Cano, Angela; Albuquerque, Bianca Weiss; Vriesendorp, Corine; Correa, Diego Felipe; Torre, Emilio Vilanova; Van Der Heijden, Geertje; Ramirez-Angulo, Hirma; Ramos, José Ferreira; Young, Kenneth R.; Rocha, Maira; Nascimento, Marcelo Trindade; Medina, Maria Natalia Umaña; Tirado, Milton; Wang, Ophelia; Sierra, Rodrigo; Torres-Lezama, Armando; Mendoza, Casimiro; Ferreira, Cid; Baider, Cláudia; Villarroel, Daniel; Balslev, Henrik; Mesones, Italo; Giraldo, Ligia Estela Urrego; Casas, Luisa Fernanda; Reategui, Manuel Augusto Ahuite; Linares-Palomino, Reynaldo; Zagt, Roderick; Cárdenas, Sasha; Farfan-Rios, William; Sampaio, Adeilza Felipe; Pauletto, Daniela; Sandoval, Elvis H.Valderrama; Arevalo, Freddy Ramirez; Huamantupa-Chuquimaco, Isau; Garcia-Cabrera, Karina; Hernandez, Lionel; Gamarra, Luis Valenzuela; Alexiades, Miguel N.; Pansini, Susamar; Cuenca, Walter Palacios; Milliken, William; Ricardo, Joana; Lopez-Gonzalez, Gabriela; Pos, Edwin; Ter Steege, Hans
2018-01-01
Species distribution models (SDMs) are widely used in ecology and conservation. Presence-only SDMs such as MaxEnt frequently use natural history collections (NHCs) as occurrence data, given their huge numbers and accessibility. NHCs are often spatially biased which may generate inaccuracies in SDMs.
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Yilmaz, Hatice; Yilmaz, Osman Yalçın; Akyüz, Yaşar Feyza
2017-02-01
Species distribution modeling was used to determine factors among the large predictor candidate data set that affect the distribution of Muscari latifolium , an endemic bulbous plant species of Turkey, to quantify the relative importance of each factor and make a potential spatial distribution map of M. latifolium . Models were built using the Boosted Regression Trees method based on 35 presence and 70 absence records obtained through field sampling in the Gönen Dam watershed area of the Kazdağı Mountains in West Anatolia. Large candidate variables of monthly and seasonal climate, fine-scale land surface, and geologic and biotic variables were simplified using a BRT simplifying procedure. Analyses performed on these resources, direct and indirect variables showed that there were 14 main factors that influence the species' distribution. Five of the 14 most important variables influencing the distribution of the species are bedrock type, Quercus cerris density, precipitation during the wettest month, Pinus nigra density, and northness. These variables account for approximately 60% of the relative importance for determining the distribution of the species. Prediction performance was assessed by 10 random subsample data sets and gave a maximum the area under a receiver operating characteristic curve (AUC) value of 0.93 and an average AUC value of 0.8. This study provides a significant contribution to the knowledge of the habitat requirements and ecological characteristics of this species. The distribution of this species is explained by a combination of biotic and abiotic factors. Hence, using biotic interaction and fine-scale land surface variables in species distribution models improved the accuracy and precision of the model. The knowledge of the relationships between distribution patterns and environmental factors and biotic interaction of M. latifolium can help develop a management and conservation strategy for this species.
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Jeffrey E. Schneiderman; Hong S. He; Frank R. Thompson; William D. Dijak; Jacob S. Fraser
2015-01-01
Tree species distribution and abundance are affected by forces operating across a hierarchy of ecological scales. Process and species distribution models have been developed emphasizing forces at different scales. Understanding model agreement across hierarchical scales provides perspective on prediction uncertainty and ultimately enables policy makers and managers to...
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DEFF Research Database (Denmark)
Guisan, Antoine; Rahbek, Carsten
2011-01-01
Two different approaches currently prevail for predicting spatial patterns of species assemblages. The first approach (macroecological modelling, MEM) focuses directly on realized properties of species assemblages, whereas the second approach (stacked species distribution modelling, S-SDM) starts...
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Directory of Open Access Journals (Sweden)
Hyeyeong Choe
Full Text Available Accurate information on the distribution of existing species is crucial to assess regional biodiversity. However, data inventories are insufficient in many areas. We examine the ability of Multivariate Adaptive Regression Splines (MARS multi-response species distribution model to overcome species' data limitations and portray plant species distribution patterns for 199 South Korean plant species. The study models species with two or more observations, examines their contribution to national patterns of species richness, provides a sensitivity analysis of different range threshold cutoff approaches for modeling species' ranges, and presents considerations for species modeling at fine spatial resolution. We ran MARS models for each species and tested four threshold methods to transform occurrence probabilities into presence or absence range maps. Modeled occurrence probabilities were extracted at each species' presence points, and the mean, median, and one standard deviation (SD calculated to define data-driven thresholds. A maximum sum of sensitivity and specificity threshold was also calculated, and the range maps from the four cutoffs were tested using independent plant survey data. The single SD values were the best threshold tested for minimizing omission errors and limiting species ranges to areas where the associated occurrence data were correctly classed. Eight individual species range maps for rare plant species were identified that are potentially affected by resampling predictor variables to fine spatial scales. We portray spatial patterns of high species richness by assessing the combined range maps from three classes of species: all species, endangered and endemic species, and range-size rarity of all species, which could be used in conservation planning for South Korea. The MARS model is promising for addressing the common problem of few species occurrence records. However, projected species ranges are highly dependent on the
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Directory of Open Access Journals (Sweden)
Pelayo Acevedo
Full Text Available The application of species distribution models (SDMs in ecology and conservation biology is increasing and assuming an important role, mainly because they can be used to hindcast past and predict current and future species distributions. However, the accuracy of SDMs depends on the quality of the data and on appropriate theoretical frameworks. In this study, comprehensive data on the current distribution of the Iberian hare (Lepus granatensis were used to i determine the species' ecogeographical constraints, ii hindcast a climatic model for the last glacial maximum (LGM, relating it to inferences derived from molecular studies, and iii calibrate a model to assess the species future distribution trends (up to 2080. Our results showed that the climatic factor (in its pure effect and when it is combined with the land-cover factor is the most important descriptor of the current distribution of the Iberian hare. In addition, the model's output was a reliable index of the local probability of species occurrence, which is a valuable tool to guide species management decisions and conservation planning. Climatic potential obtained for the LGM was combined with molecular data and the results suggest that several glacial refugia may have existed for the species within the major Iberian refugium. Finally, a high probability of occurrence of the Iberian hare in the current species range and a northward expansion were predicted for future. Given its current environmental envelope and evolutionary history, we discuss the macroecology of the Iberian hare and its sensitivity to climate change.
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Acevedo, Pelayo; Melo-Ferreira, José; Real, Raimundo; Alves, Paulo Célio
2012-01-01
The application of species distribution models (SDMs) in ecology and conservation biology is increasing and assuming an important role, mainly because they can be used to hindcast past and predict current and future species distributions. However, the accuracy of SDMs depends on the quality of the data and on appropriate theoretical frameworks. In this study, comprehensive data on the current distribution of the Iberian hare (Lepus granatensis) were used to i) determine the species' ecogeographical constraints, ii) hindcast a climatic model for the last glacial maximum (LGM), relating it to inferences derived from molecular studies, and iii) calibrate a model to assess the species future distribution trends (up to 2080). Our results showed that the climatic factor (in its pure effect and when it is combined with the land-cover factor) is the most important descriptor of the current distribution of the Iberian hare. In addition, the model's output was a reliable index of the local probability of species occurrence, which is a valuable tool to guide species management decisions and conservation planning. Climatic potential obtained for the LGM was combined with molecular data and the results suggest that several glacial refugia may have existed for the species within the major Iberian refugium. Finally, a high probability of occurrence of the Iberian hare in the current species range and a northward expansion were predicted for future. Given its current environmental envelope and evolutionary history, we discuss the macroecology of the Iberian hare and its sensitivity to climate change.
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Franklin, J.; Wejnert, K.E.; Hathaway, S.A.; Rochester, C.J.; Fisher, R.N.
2009-01-01
Aim: Several studies have found that more accurate predictive models of species' occurrences can be developed for rarer species; however, one recent study found the relationship between range size and model performance to be an artefact of sample prevalence, that is, the proportion of presence versus absence observations in the data used to train the model. We examined the effect of model type, species rarity class, species' survey frequency, detectability and manipulated sample prevalence on the accuracy of distribution models developed for 30 reptile and amphibian species. Location: Coastal southern California, USA. Methods: Classification trees, generalized additive models and generalized linear models were developed using species presence and absence data from 420 locations. Model performance was measured using sensitivity, specificity and the area under the curve (AUC) of the receiver-operating characteristic (ROC) plot based on twofold cross-validation, or on bootstrapping. Predictors included climate, terrain, soil and vegetation variables. Species were assigned to rarity classes by experts. The data were sampled to generate subsets with varying ratios of presences and absences to test for the effect of sample prevalence. Join count statistics were used to characterize spatial dependence in the prediction errors. Results: Species in classes with higher rarity were more accurately predicted than common species, and this effect was independent of sample prevalence. Although positive spatial autocorrelation remained in the prediction errors, it was weaker than was observed in the species occurrence data. The differences in accuracy among model types were slight. Main conclusions: Using a variety of modelling methods, more accurate species distribution models were developed for rarer than for more common species. This was presumably because it is difficult to discriminate suitable from unsuitable habitat for habitat generalists, and not as an artefact of the
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Modelling the potential spatial distribution of mosquito species using three different techniques
Cianci, D.; Hartemink, N.; Ibáñez-Justicia, A.
2015-01-01
Background: Models for the spatial distribution of vector species are important tools in the assessment of the risk of establishment and subsequent spread of vector-borne diseases. The aims of this study are to define the environmental conditions suitable for several mosquito species through species
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DEFF Research Database (Denmark)
Swab, Rebecca Marie; Regan, Helen M.; Matthies, Diethart
2015-01-01
Organisms are projected to shift their distribution ranges under climate change. The typical way to assess range shifts is by species distribution models (SDMs), which predict species’ responses to climate based solely on projected climatic suitability. However, life history traits can impact...... species’ responses to shifting habitat suitability. Additionally, it remains unclear if differences in vital rates across populations within a species can offset or exacerbate the effects of predicted changes in climatic suitability on population viability. In order to obtain a fuller understanding...... of the response of one species to projected climatic changes, we coupled demographic processes with predicted changes in suitable habitat for the monocarpic thistle Carlina vulgaris across northern Europe. We first developed a life history model with species-specific average fecundity and survival rates...
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Crase, Beth; Liedloff, Adam; Vesk, Peter A; Fukuda, Yusuke; Wintle, Brendan A
2014-08-01
Species distribution models (SDMs) are widely used to forecast changes in the spatial distributions of species and communities in response to climate change. However, spatial autocorrelation (SA) is rarely accounted for in these models, despite its ubiquity in broad-scale ecological data. While spatial autocorrelation in model residuals is known to result in biased parameter estimates and the inflation of type I errors, the influence of unmodeled SA on species' range forecasts is poorly understood. Here we quantify how accounting for SA in SDMs influences the magnitude of range shift forecasts produced by SDMs for multiple climate change scenarios. SDMs were fitted to simulated data with a known autocorrelation structure, and to field observations of three mangrove communities from northern Australia displaying strong spatial autocorrelation. Three modeling approaches were implemented: environment-only models (most frequently applied in species' range forecasts), and two approaches that incorporate SA; autologistic models and residuals autocovariate (RAC) models. Differences in forecasts among modeling approaches and climate scenarios were quantified. While all model predictions at the current time closely matched that of the actual current distribution of the mangrove communities, under the climate change scenarios environment-only models forecast substantially greater range shifts than models incorporating SA. Furthermore, the magnitude of these differences intensified with increasing increments of climate change across the scenarios. When models do not account for SA, forecasts of species' range shifts indicate more extreme impacts of climate change, compared to models that explicitly account for SA. Therefore, where biological or population processes induce substantial autocorrelation in the distribution of organisms, and this is not modeled, model predictions will be inaccurate. These results have global importance for conservation efforts as inaccurate
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Ice age distriutions of European small mammals: insights from species distribution modelling
DEFF Research Database (Denmark)
Fløjgaard, Camilla; Normand, Signe; Skov, Flemming
2009-01-01
limits corresponding to the limits of temperate or boreal forest or arctic tundra were used in the analysis. We developed predictive distribution models based on the species present-day European distributions and validated these against their present-day Siberian ranges. The models with the best...... lemmus and Microtus oeconomus), suitable climate was predicted from the Atlantic coast eastward across central Europe and into Russia. Main conclusions. Our results support the idea of more northerly refuge areas in Europe, indicating that boreal species would have found suitable living conditions over...
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Ay, Jean-Sauveur; Guillemot, Joannès; Martin-StPaul, Nicolas K.; Doyen, Luc; Leadley, Paul
2015-04-01
Species distribution models (SDMs) are widely used to study and predict the outcome of global change on species. In human dominated ecosystems the presence of a given species is the result of both its ecological suitability and human footprint on nature such as land use choices. Land use choices may thus be responsible for a selection bias in the presence/absence data used in SDM calibration. We present a structural modelling approach (i.e. based on structural equation modelling) that accounts for this selection bias. The new structural species distribution model (SSDM) estimates simultaneously land use choices and species responses to bioclimatic variables. A land use equation based on an econometric model of landowner choices was joined to an equation of species response to bioclimatic variables. SSDM allows the residuals of both equations to be dependent, taking into account the possibility of shared omitted variables and measurement errors. We provide a general description of the statistical theory and a set of application on forested trees over France using databases of climate and forest inventory at different spatial resolution (from 2km to 8 km). We also compared the output of the SSDM with outputs of a classical SDM in term of bioclimatic response curves and potential distribution under current climate. According to the species and the spatial resolution of the calibration dataset, shapes of bioclimatic response curves the modelled species distribution maps differed markedly between the SSDM and classical SDMs. The magnitude and directions of these differences were dependent on the correlations between the errors from both equations and were highest for higher spatial resolutions. A first conclusion is that the use of classical SDMs can potentially lead to strong miss-estimation of the actual and future probability of presence modelled. Beyond this selection bias, the SSDM we propose represents a crucial step to account for economic constraints on tree
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Relating species abundance distributions to species-area curves in two Mediterranean-type shrublands
Keeley, Jon E.
2003-01-01
Based on both theoretical and empirical studies there is evidence that different species abundance distributions underlie different species-area relationships. Here I show that Australian and Californian shrubland communities (at the scale from 1 to 1000 m2) exhibit different species-area relationships and different species abundance patterns. The species-area relationship in Australian heathlands best fits an exponential model and species abundance (based on both density and cover) follows a narrow log normal distribution. In contrast, the species-area relationship in Californian shrublands is best fit with the power model and, although species abundance appears to fit a log normal distribution, the distribution is much broader than in Australian heathlands. I hypothesize that the primary driver of these differences is the abundance of small-stature annual species in California and the lack of annuals in Australian heathlands. Species-area is best fit by an exponential model in Australian heathlands because the bulk of the species are common and thus the species-area curves initially rise rapidly between 1 and 100 m2. Annuals in Californian shrublands generate very broad species abundance distributions with many uncommon or rare species. The power function is a better model in these communities because richness increases slowly from 1 to 100 m2 but more rapidly between 100 and 1000 m2due to the abundance of rare or uncommon species that are more likely to be encountered at coarser spatial scales. The implications of this study are that both the exponential and power function models are legitimate representations of species-area relationships in different plant communities. Also, structural differences in community organization, arising from different species abundance distributions, may lead to different species-area curves, and this may be tied to patterns of life form distribution.
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Directory of Open Access Journals (Sweden)
Elizabeth A. Becker
2016-02-01
Full Text Available Species distribution models are now widely used in conservation and management to predict suitable habitat for protected marine species. The primary sources of dynamic habitat data have been in situ and remotely sensed oceanic variables (both are considered “measured data”, but now ocean models can provide historical estimates and forecast predictions of relevant habitat variables such as temperature, salinity, and mixed layer depth. To assess the performance of modeled ocean data in species distribution models, we present a case study for cetaceans that compares models based on output from a data assimilative implementation of the Regional Ocean Modeling System (ROMS to those based on measured data. Specifically, we used seven years of cetacean line-transect survey data collected between 1991 and 2009 to develop predictive habitat-based models of cetacean density for 11 species in the California Current Ecosystem. Two different generalized additive models were compared: one built with a full suite of ROMS output and another built with a full suite of measured data. Model performance was assessed using the percentage of explained deviance, root mean squared error (RMSE, observed to predicted density ratios, and visual inspection of predicted and observed distributions. Predicted distribution patterns were similar for models using ROMS output and measured data, and showed good concordance between observed sightings and model predictions. Quantitative measures of predictive ability were also similar between model types, and RMSE values were almost identical. The overall demonstrated success of the ROMS-based models opens new opportunities for dynamic species management and biodiversity monitoring because ROMS output is available in near real time and can be forecast.
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Weather, not climate, defines distributions of vagile bird species.
Directory of Open Access Journals (Sweden)
April E Reside
Full Text Available BACKGROUND: Accurate predictions of species distributions are essential for climate change impact assessments. However the standard practice of using long-term climate averages to train species distribution models might mute important temporal patterns of species distribution. The benefit of using temporally explicit weather and distribution data has not been assessed. We hypothesized that short-term weather associated with the time a species was recorded should be superior to long-term climate measures for predicting distributions of mobile species. METHODOLOGY: We tested our hypothesis by generating distribution models for 157 bird species found in Australian tropical savannas (ATS using modelling algorithm Maxent. The variable weather of the ATS supports a bird assemblage with variable movement patterns and a high incidence of nomadism. We developed "weather" models by relating climatic variables (mean temperature, rainfall, rainfall seasonality and temperature seasonality from the three month, six month and one year period preceding each bird record over a 58 year period (1950-2008. These weather models were compared against models built using long-term (30 year averages of the same climatic variables. CONCLUSIONS: Weather models consistently achieved higher model scores than climate models, particularly for wide-ranging, nomadic and desert species. Climate models predicted larger range areas for species, whereas weather models quantified fluctuations in habitat suitability across months, seasons and years. Models based on long-term climate averages over-estimate availability of suitable habitat and species' climatic tolerances, masking species potential vulnerability to climate change. Our results demonstrate that dynamic approaches to distribution modelling, such as incorporating organism-appropriate temporal scales, improves understanding of species distributions.
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On the Mass Distribution of Animal Species
Redner, Sidney; Clauset, Aaron; Schwab, David
2009-03-01
We develop a simple diffusion-reaction model to account for the broad and asymmetric distribution of adult body masses for species within related taxonomic groups. The model assumes three basic evolutionary features that control body mass: (i) a fixed lower limit that is set by metabolic constraints, (ii) a species extinction risk that is a weakly increasing function of body mass, and (iii) cladogenetic diffusion, in which daughter species have a slight tendency toward larger mass. The steady-state solution for the distribution of species masses in this model can be expressed in terms of the Airy function. This solution gives mass distributions that are in good agreement with data on 4002 terrestrial mammal species from the late Quaternary and 8617 extant bird species.
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Modeling of the spatial distribution of ten endangered bird species in jurisdiction of Corantioquia
International Nuclear Information System (INIS)
Gomez M, Ana Maria; Alvarez, Esteban
2006-01-01
Recently, thanks to advances made in Geographic Information Systems (GIS), techniques have been developed for the construction of models that predict the spatial distribution of species and other attributes of biodiversity. These methods have allowed for the development of objective criteria that are fundamental for making decisions regarding the creation of protected areas systems throughout the world. In this research, the spatial distribution of ten endangered species of birds found within the jurisdiction of CORANTIOQUIA (JDC from here on) was modelled, using GIS techniques. The JDC was divided into 177 squares of 15 x 10 Km and the following variables were quantified within each one: presence or absence of endangered species of birds, rainfall, temperature, sun brightness, relative humidity, day duration, altitude, vegetal cover, slope and primary net productivity. With the help of logistic regression were made predictive models. Based on logistic regressions techniques predictive models were made. These models allow to explain a percentage between 24% and 80% of spatial distribution variability of these species. Those results can help in the identification of valuable zones for the biodiversity conservation. In places where there are neither the time or the economic resources to carry out exhaustive analyses of biodiversity, the models can predict the probable presence of this endangered species
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Chunco, Amanda J.; Phimmachak, Somphouthone; Sivongxay, Niane; Stuart, Bryan L.
2013-01-01
The Lao newt (Laotriton laoensis) is a recently described species currently known only from northern Laos. Little is known about the species, but it is threatened as a result of overharvesting. We integrated field survey results with climate and altitude data to predict the geographic distribution of this species using the niche modeling program Maxent, and we validated these predictions by using interviews with local residents to confirm model predictions of presence and absence. The results of the validated Maxent models were then used to characterize the environmental conditions of areas predicted suitable for L. laoensis. Finally, we overlaid the resulting model with a map of current national protected areas in Laos to determine whether or not any land predicted to be suitable for this species is coincident with a national protected area. We found that both area under the curve (AUC) values and interview data provided strong support for the predictive power of these models, and we suggest that interview data could be used more widely in species distribution niche modeling. Our results further indicated that this species is mostly likely geographically restricted to high altitude regions (i.e., over 1,000 m elevation) in northern Laos and that only a minute fraction of suitable habitat is currently protected. This work thus emphasizes that increased protection efforts, including listing this species as endangered and the establishment of protected areas in the region predicted to be suitable for L. laoensis, are urgently needed. PMID:23555808
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Fithian, William; Elith, Jane; Hastie, Trevor; Keith, David A
2015-04-01
Presence-only records may provide data on the distributions of rare species, but commonly suffer from large, unknown biases due to their typically haphazard collection schemes. Presence-absence or count data collected in systematic, planned surveys are more reliable but typically less abundant.We proposed a probabilistic model to allow for joint analysis of presence-only and survey data to exploit their complementary strengths. Our method pools presence-only and presence-absence data for many species and maximizes a joint likelihood, simultaneously estimating and adjusting for the sampling bias affecting the presence-only data. By assuming that the sampling bias is the same for all species, we can borrow strength across species to efficiently estimate the bias and improve our inference from presence-only data.We evaluate our model's performance on data for 36 eucalypt species in south-eastern Australia. We find that presence-only records exhibit a strong sampling bias towards the coast and towards Sydney, the largest city. Our data-pooling technique substantially improves the out-of-sample predictive performance of our model when the amount of available presence-absence data for a given species is scarceIf we have only presence-only data and no presence-absence data for a given species, but both types of data for several other species that suffer from the same spatial sampling bias, then our method can obtain an unbiased estimate of the first species' geographic range.
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Sheppard, Christine S; Burns, Bruce R; Stanley, Margaret C
2014-09-01
Climate change may facilitate alien species invasion into new areas, particularly for species from warm native ranges introduced into areas currently marginal for temperature. Although conclusions from modelling approaches and experimental studies are generally similar, combining the two approaches has rarely occurred. The aim of this study was to validate species distribution models by conducting field trials in sites of differing suitability as predicted by the models, thus increasing confidence in their ability to assess invasion risk. Three recently naturalized alien plants in New Zealand were used as study species (Archontophoenix cunninghamiana, Psidium guajava and Schefflera actinophylla): they originate from warm native ranges, are woody bird-dispersed species and of concern as potential weeds. Seedlings were grown in six sites across the country, differing both in climate and suitability (as predicted by the species distribution models). Seedling growth and survival were recorded over two summers and one or two winter seasons, and temperature and precipitation were monitored hourly at each site. Additionally, alien seedling performances were compared to those of closely related native species (Rhopalostylis sapida, Lophomyrtus bullata and Schefflera digitata). Furthermore, half of the seedlings were sprayed with pesticide, to investigate whether enemy release may influence performance. The results showed large differences in growth and survival of the alien species among the six sites. In the more suitable sites, performance was frequently higher compared to the native species. Leaf damage from invertebrate herbivory was low for both alien and native seedlings, with little evidence that the alien species should have an advantage over the native species because of enemy release. Correlations between performance in the field and predicted suitability of species distribution models were generally high. The projected increase in minimum temperature and reduced
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What do we gain from simplicity versus complexity in species distribution models?
Merow, Cory; Smith, Matthew J.; Edwards, Thomas C.; Guisan, Antoine; McMahon, Sean M.; Normand, Signe; Thuiller, Wilfried; Wuest, Rafael O.; Zimmermann, Niklaus E.; Elith, Jane
2014-01-01
Species distribution models (SDMs) are widely used to explain and predict species ranges and environmental niches. They are most commonly constructed by inferring species' occurrence–environment relationships using statistical and machine-learning methods. The variety of methods that can be used to construct SDMs (e.g. generalized linear/additive models, tree-based models, maximum entropy, etc.), and the variety of ways that such models can be implemented, permits substantial flexibility in SDM complexity. Building models with an appropriate amount of complexity for the study objectives is critical for robust inference. We characterize complexity as the shape of the inferred occurrence–environment relationships and the number of parameters used to describe them, and search for insights into whether additional complexity is informative or superfluous. By building ‘under fit’ models, having insufficient flexibility to describe observed occurrence–environment relationships, we risk misunderstanding the factors shaping species distributions. By building ‘over fit’ models, with excessive flexibility, we risk inadvertently ascribing pattern to noise or building opaque models. However, model selection can be challenging, especially when comparing models constructed under different modeling approaches. Here we argue for a more pragmatic approach: researchers should constrain the complexity of their models based on study objective, attributes of the data, and an understanding of how these interact with the underlying biological processes. We discuss guidelines for balancing under fitting with over fitting and consequently how complexity affects decisions made during model building. Although some generalities are possible, our discussion reflects differences in opinions that favor simpler versus more complex models. We conclude that combining insights from both simple and complex SDM building approaches best advances our knowledge of current and future species
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Moraitis, Manos L; Tsikopoulou, Irini; Geropoulos, Antonios; Dimitriou, Panagiotis D; Papageorgiou, Nafsika; Giannoulaki, Marianna; Valavanis, Vasilis D; Karakassis, Ioannis
2018-05-24
Marine habitat assessment using indicator species through Species Distribution Modeling (SDM) was investigated. The bivalves: Corbula gibba and Flexopecten hyalinus were the indicator species characterizing disturbed and undisturbed areas respectively in terms of chlorophyll a concentration in Greece. The habitat suitability maps of these species reflected the overall ecological status of the area. The C. gibba model successfully predicted the occurrence of this species in areas with increased physical disturbance driven by chlorophyll a concentration, whereas the habitat map for F. hyalinus showed an increased probability of occurrence in chlorophyll-poor areas, affected mainly by salinity. We advocate the use of C. gibba as a proxy for eutrophication and the incorporation of this species in monitoring studies through SDM methods. For the Mediterranean Sea we suggest the use of F. hyalinus in SDM as an indicator of environmental stability and a possible forecasting tool for salinity fluctuations. Copyright © 2018 Elsevier Ltd. All rights reserved.
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Cai, X.; Simons, J.; Carollo, C.; Sterba-Boatwright, B.; Sadovski, A.
2016-02-01
Ecosystem based fisheries management has been broadly recognized throughout the world as a way to achieve better conservation. Therefore, there is a strong need for mapping of multi-species interactions or spatial distributions. Species distribution models are widely applied since information regarding the presence of species is usually only available for limited locations due to the high cost of fisheries surveys. Instead of regular presence and absence records, a large proportion of the fisheries survey data have only presence records. This makes the modeling problem one of one-class classification (presence only), which is much more complex than the regular two-class classification (presence/absence). In this study, four different presence-only species distribution algorithms (Bioclim, Domain, Mahal and Maxent) were applied using 13 environmental parameters (e.g., depth, DO, bottom types) as predictors to model the distribution of king mackerel (Scomberomorus cavalla) and its 31 prey species in the Gulf of Mexico (a total of 13625 georeferenced presence records from OBIS and GBIF were used). Five-fold cross validations were applied for each of the 128 (4 algorithms × 32 species) models. Area under curve (AUC) and correlation coefficient (R) were used to evaluate the model performances. The AUC of the models based on these four algorithms were 0.83±0.14, 0.77±0.16, 0.94±0.06 and 0.94±0.06, respectively; while R for the models were 0.47±0.27, 0.43±0.24, 0.27±0.16 and 0.76±0.16, respectively. Post hoc with Tukey's test showed that AUC for the Maxent-based models were significantly (pMexico to help managers better manage related fisheries resources.
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Community structure informs species geographic distributions
Montesinos-Navarro, Alicia
2018-05-23
Understanding what determines species\\' geographic distributions is crucial for assessing global change threats to biodiversity. Measuring limits on distributions is usually, and necessarily, done with data at large geographic extents and coarse spatial resolution. However, survival of individuals is determined by processes that happen at small spatial scales. The relative abundance of coexisting species (i.e. \\'community structure\\') reflects assembly processes occurring at small scales, and are often available for relatively extensive areas, so could be useful for explaining species distributions. We demonstrate that Bayesian Network Inference (BNI) can overcome several challenges to including community structure into studies of species distributions, despite having been little used to date. We hypothesized that the relative abundance of coexisting species can improve predictions of species distributions. In 1570 assemblages of 68 Mediterranean woody plant species we used BNI to incorporate community structure into Species Distribution Models (SDMs), alongside environmental information. Information on species associations improved SDM predictions of community structure and species distributions moderately, though for some habitat specialists the deviance explained increased by up to 15%. We demonstrate that most species associations (95%) were positive and occurred between species with ecologically similar traits. This suggests that SDM improvement could be because species co-occurrences are a proxy for local ecological processes. Our study shows that Bayesian Networks, when interpreted carefully, can be used to include local conditions into measurements of species\\' large-scale distributions, and this information can improve the predictions of species distributions.
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Soultan, Alaaeldin; Safi, Kamran
2017-01-01
Digitized species occurrence data provide an unprecedented source of information for ecologists and conservationists. Species distribution model (SDM) has become a popular method to utilise these data for understanding the spatial and temporal distribution of species, and for modelling biodiversity patterns. Our objective is to study the impact of noise in species occurrence data (namely sample size and positional accuracy) on the performance and reliability of SDM, considering the multiplicative impact of SDM algorithms, species specialisation, and grid resolution. We created a set of four 'virtual' species characterized by different specialisation levels. For each of these species, we built the suitable habitat models using five algorithms at two grid resolutions, with varying sample sizes and different levels of positional accuracy. We assessed the performance and reliability of the SDM according to classic model evaluation metrics (Area Under the Curve and True Skill Statistic) and model agreement metrics (Overall Concordance Correlation Coefficient and geographic niche overlap) respectively. Our study revealed that species specialisation had by far the most dominant impact on the SDM. In contrast to previous studies, we found that for widespread species, low sample size and low positional accuracy were acceptable, and useful distribution ranges could be predicted with as few as 10 species occurrences. Range predictions for narrow-ranged species, however, were sensitive to sample size and positional accuracy, such that useful distribution ranges required at least 20 species occurrences. Against expectations, the MAXENT algorithm poorly predicted the distribution of specialist species at low sample size.
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Species distribution modeling in regions of high need and limited data: waterfowl of China
Prosser, Diann J.; Ding, Changqing; Erwin, R. Michael; Mundkur, Taej; Sullivan, Jeffery D.; Ellis, Erle C.
2018-01-01
BackgroundA number of conservation and societal issues require understanding how species are distributed on the landscape, yet ecologists are often faced with a lack of data to develop models at the resolution and extent desired, resulting in inefficient use of conservation resources. Such a situation presented itself in our attempt to develop waterfowl distribution models as part of a multi-disciplinary team targeting the control of the highly pathogenic H5N1 avian influenza virus in China.MethodsFaced with limited data, we built species distribution models using a habitat suitability approach for China’s breeding and non-breeding (hereafter, wintering) waterfowl. An extensive review of the literature was used to determine model parameters for habitat modeling. Habitat relationships were implemented in GIS using land cover covariates. Wintering models were validated using waterfowl census data, while breeding models, though developed for many species, were only validated for the one species with sufficient telemetry data available.ResultsWe developed suitability models for 42 waterfowl species (30 breeding and 39 wintering) at 1 km resolution for the extent of China, along with cumulative and genus level species richness maps. Breeding season models showed highest waterfowl suitability in wetlands of the high-elevation west-central plateau and northeastern China. Wintering waterfowl suitability was highest in the lowland regions of southeastern China. Validation measures indicated strong performance in predicting species presence. Comparing our model outputs to China’s protected areas indicated that breeding habitat was generally better covered than wintering habitat, and identified locations for which additional research and protection should be prioritized.ConclusionsThese suitability models are the first available for many of China’s waterfowl species, and have direct utility to conservation and habitat planning and prioritizing management of critically
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Fontaine, Joseph J.; Jorgensen, Christopher; Stuber, Erica F.; Gruber, Lutz F.; Bishop, Andrew A.; Lusk, Jeffrey J.; Zach, Eric S.; Decker, Karie L.
2017-01-01
We know economic and social policy has implications for ecosystems at large, but the consequences for a given geographic area or specific wildlife population are more difficult to conceptualize and communicate. Species distribution models, which extrapolate species-habitat relationships across ecological scales, are capable of predicting population changes in distribution and abundance in response to management and policy, and thus, are an ideal means for facilitating proactive management within a larger policy framework. To illustrate the capabilities of species distribution modeling in scenario planning for wildlife populations, we projected an existing distribution model for ring-necked pheasants (Phasianus colchicus) onto a series of alternative future landscape scenarios for Nebraska, USA. Based on our scenarios, we qualitatively and quantitatively estimated the effects of agricultural policy decisions on pheasant populations across Nebraska, in specific management regions, and at wildlife management areas.
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Lambert, Amaury
2011-07-01
We consider a general, neutral, dynamical model of biodiversity. Individuals have i.i.d. lifetime durations, which are not necessarily exponentially distributed, and each individual gives birth independently at constant rate λ. Thus, the population size is a homogeneous, binary Crump-Mode-Jagers process (which is not necessarily a Markov process). We assume that types are clonally inherited. We consider two classes of speciation models in this setting. In the immigration model, new individuals of an entirely new species singly enter the population at constant rate μ (e.g., from the mainland into the island). In the mutation model, each individual independently experiences point mutations in its germ line, at constant rate θ. We are interested in the species abundance distribution, i.e., in the numbers, denoted I(n)(k) in the immigration model and A(n)(k) in the mutation model, of species represented by k individuals, k = 1, 2, . . . , n, when there are n individuals in the total population. In the immigration model, we prove that the numbers (I(t)(k); k ≥ 1) of species represented by k individuals at time t, are independent Poisson variables with parameters as in Fisher's log-series. When conditioning on the total size of the population to equal n, this results in species abundance distributions given by Ewens' sampling formula. In particular, I(n)(k) converges as n → ∞ to a Poisson r.v. with mean γ/k, where γ : = μ/λ. In the mutation model, as n → ∞, we obtain the almost sure convergence of n (-1) A(n)(k) to a nonrandom explicit constant. In the case of a critical, linear birth-death process, this constant is given by Fisher's log-series, namely n(-1) A(n)(k) converges to α(k)/k, where α : = λ/(λ + θ). In both models, the abundances of the most abundant species are briefly discussed.
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Directory of Open Access Journals (Sweden)
Christopher L. Coxen
2017-07-01
Full Text Available Species distribution models can provide critical baseline distribution information for the conservation of poorly understood species. Here, we compared the performance of band-tailed pigeon (Patagioenas fasciata species distribution models created using Maxent and derived from two separate presence-only occurrence data sources in New Mexico: 1 satellite tracked birds and 2 observations reported in eBird basic data set. Both models had good accuracy (test AUC > 0.8 and True Skill Statistic > 0.4, and high overlap between suitability scores (I statistic 0.786 and suitable habitat patches (relative rank 0.639. Our results suggest that, at the state-wide level, eBird occurrence data can effectively model similar species distributions as satellite tracking data. Climate change models for the band-tailed pigeon predict a 35% loss in area of suitable climate by 2070 if CO2 emissions drop to 1990 levels by 2100, and a 45% loss by 2070 if we continue current CO2 emission levels through the end of the century. These numbers may be conservative given the predicted increase in drought, wildfire, and forest pest impacts to the coniferous forests the species inhabits in New Mexico. The northern portion of the species’ range in New Mexico is predicted to be the most viable through time.
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Coxen, Christopher L.; Frey, Jennifer K.; Carleton, Scott A.; Collins, Daniel P.
2017-01-01
Species distribution models can provide critical baseline distribution information for the conservation of poorly understood species. Here, we compared the performance of band-tailed pigeon (Patagioenas fasciata) species distribution models created using Maxent and derived from two separate presence-only occurrence data sources in New Mexico: 1) satellite tracked birds and 2) observations reported in eBird basic data set. Both models had good accuracy (test AUC > 0.8 and True Skill Statistic > 0.4), and high overlap between suitability scores (I statistic 0.786) and suitable habitat patches (relative rank 0.639). Our results suggest that, at the state-wide level, eBird occurrence data can effectively model similar species distributions as satellite tracking data. Climate change models for the band-tailed pigeon predict a 35% loss in area of suitable climate by 2070 if CO2 emissions drop to 1990 levels by 2100, and a 45% loss by 2070 if we continue current CO2 emission levels through the end of the century. These numbers may be conservative given the predicted increase in drought, wildfire, and forest pest impacts to the coniferous forests the species inhabits in New Mexico. The northern portion of the species’ range in New Mexico is predicted to be the most viable through time.
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Exploring similarities among many species distributions
Simmerman, Scott; Wang, Jingyuan; Osborne, James; Shook, Kimberly; Huang, Jian; Godsoe, William; Simons, Theodore R.
2012-01-01
Collecting species presence data and then building models to predict species distribution has been long practiced in the field of ecology for the purpose of improving our understanding of species relationships with each other and with the environment. Due to limitations of computing power as well as limited means of using modeling software on HPC facilities, past species distribution studies have been unable to fully explore diverse data sets. We build a system that can, for the first time to our knowledge, leverage HPC to support effective exploration of species similarities in distribution as well as their dependencies on common environmental conditions. Our system can also compute and reveal uncertainties in the modeling results enabling domain experts to make informed judgments about the data. Our work was motivated by and centered around data collection efforts within the Great Smoky Mountains National Park that date back to the 1940s. Our findings present new research opportunities in ecology and produce actionable field-work items for biodiversity management personnel to include in their planning of daily management activities.
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Vanreusel, Wouter; Maes, Dirk; Van Dyck, Hans
2007-02-01
Numerous models for predicting species distribution have been developed for conservation purposes. Most of them make use of environmental data (e.g., climate, topography, land use) at a coarse grid resolution (often kilometres). Such approaches are useful for conservation policy issues including reserve-network selection. The efficiency of predictive models for species distribution is usually tested on the area for which they were developed. Although highly interesting from the point of view of conservation efficiency, transferability of such models to independent areas is still under debate. We tested the transferability of habitat-based predictive distribution models for two regionally threatened butterflies, the green hairstreak (Callophrys rubi) and the grayling (Hipparchia semele), within and among three nature reserves in northeastern Belgium. We built predictive models based on spatially detailed maps of area-wide distribution and density of ecological resources. We used resources directly related to ecological functions (host plants, nectar sources, shelter, microclimate) rather than environmental surrogate variables. We obtained models that performed well with few resource variables. All models were transferable--although to different degrees--among the independent areas within the same broad geographical region. We argue that habitat models based on essential functional resources could transfer better in space than models that use indirect environmental variables. Because functional variables can easily be interpreted and even be directly affected by terrain managers, these models can be useful tools to guide species-adapted reserve management.
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EVALUATING THE NOVEL METHODS ON SPECIES DISTRIBUTION MODELING IN COMPLEX FOREST
Directory of Open Access Journals (Sweden)
C. H. Tu
2012-07-01
Full Text Available The prediction of species distribution has become a focus in ecology. For predicting a result more effectively and accurately, some novel methods have been proposed recently, like support vector machine (SVM and maximum entropy (MAXENT. However, high complexity in the forest, like that in Taiwan, will make the modeling become even harder. In this study, we aim to explore which method is more applicable to species distribution modeling in the complex forest. Castanopsis carlesii (long-leaf chinkapin, LLC, growing widely in Taiwan, was chosen as the target species because its seeds are an important food source for animals. We overlaid the tree samples on the layers of altitude, slope, aspect, terrain position, and vegetation index derived from SOPT-5 images, and developed three models, MAXENT, SVM, and decision tree (DT, to predict the potential habitat of LLCs. We evaluated these models by two sets of independent samples in different site and the effect on the complexity of forest by changing the background sample size (BSZ. In the forest with low complex (small BSZ, the accuracies of SVM (kappa = 0.87 and DT (0.86 models were slightly higher than that of MAXENT (0.84. In the more complex situation (large BSZ, MAXENT kept high kappa value (0.85, whereas SVM (0.61 and DT (0.57 models dropped significantly due to limiting the habitat close to samples. Therefore, MAXENT model was more applicable to predict species’ potential habitat in the complex forest; whereas SVM and DT models would tend to underestimate the potential habitat of LLCs.
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The predictive skill of species distribution models for plankton in a changing climate
DEFF Research Database (Denmark)
Brun, Philipp Georg; Kiørboe, Thomas; Licandro, Priscilla
2016-01-01
Statistical species distribution models (SDMs) are increasingly used to project spatial relocations of marine taxa under future climate change scenarios. However, tests of their predictive skill in the real-world are rare. Here, we use data from the Continuous Plankton Recorder program, one...... null models, is essential to assess the robustness of projections of marine planktonic species under climate change...
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Predictive models of threatened plant species distribution in the Iberian arid south-east
Benito, Blas M.
2013-01-01
Poster on the distribution of three rare, endemic and endangered annual plants of arid zones in the south-eastern Iberian peninsula. Presented in the workshop "Predictive Modelling of Species Distribution: New Tools for the XXI Century (Baeza, Spain, november 2005).
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Eckhart, V M; Geber, M A; Morris, W F; Fabio, E S; Tiffin, P; Moeller, D A
2011-10-01
Potential causes of species' geographic distribution limits fall into two broad classes: (1) limited adaptation across spatially variable environments and (2) limited opportunities to colonize unoccupied areas. Combining demographic studies, analyses of demographic responses to environmental variation, and species distribution models, we investigated the causes of range limits in a model system, the eastern border of the California annual plant Clarkia xantiana ssp. xantiana. Vital rates of 20 populations varied with growing season temperature and precipitation: fruit number and overwinter survival of 1-year-old seeds declined steeply, while current-year seed germination increased modestly along west-to-east gradients in decreasing temperature, decreasing mean precipitation, and increasing variation in precipitation. Long-term stochastic finite rate of increase, λ(s), exhibited a fourfold range and varied among geologic surface materials as well as with temperature and precipitation. Growth rate declined significantly toward the eastern border, falling below 1 in three of the five easternmost populations. Distribution models employing demographically important environmental variables predicted low habitat favorability beyond the eastern border. Models that filtered or weighted population presences by λ(s) predicted steeper eastward declines in favorability and assigned greater roles in setting the distribution to among-year variation in precipitation and to geologic surface material. These analyses reveal a species border likely set by limited adaptation to declining environmental quality.
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Using maximum topology matching to explore differences in species distribution models
Poco, Jorge; Doraiswamy, Harish; Talbert, Marian; Morisette, Jeffrey; Silva, Claudio
2015-01-01
Species distribution models (SDM) are used to help understand what drives the distribution of various plant and animal species. These models are typically high dimensional scalar functions, where the dimensions of the domain correspond to predictor variables of the model algorithm. Understanding and exploring the differences between models help ecologists understand areas where their data or understanding of the system is incomplete and will help guide further investigation in these regions. These differences can also indicate an important source of model to model uncertainty. However, it is cumbersome and often impractical to perform this analysis using existing tools, which allows for manual exploration of the models usually as 1-dimensional curves. In this paper, we propose a topology-based framework to help ecologists explore the differences in various SDMs directly in the high dimensional domain. In order to accomplish this, we introduce the concept of maximum topology matching that computes a locality-aware correspondence between similar extrema of two scalar functions. The matching is then used to compute the similarity between two functions. We also design a visualization interface that allows ecologists to explore SDMs using their topological features and to study the differences between pairs of models found using maximum topological matching. We demonstrate the utility of the proposed framework through several use cases using different data sets and report the feedback obtained from ecologists.
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Dalmaris, Eleftheria; Ramalho, Cristina E; Poot, Pieter; Veneklaas, Erik J; Byrne, Margaret
2015-11-01
A worldwide increase in tree decline and mortality has been linked to climate change and, where these represent foundation species, this can have important implications for ecosystem functions. This study tests a combined approach of phylogeographic analysis and species distribution modelling to provide a climate change context for an observed decline in crown health and an increase in mortality in Eucalyptus wandoo, an endemic tree of south-western Australia. Phylogeographic analyses were undertaken using restriction fragment length polymorphism analysis of chloroplast DNA in 26 populations across the species distribution. Parsimony analysis of haplotype relationships was conducted, a haplotype network was prepared, and haplotype and nucleotide diversity were calculated. Species distribution modelling was undertaken using Maxent models based on extant species occurrences and projected to climate models of the last glacial maximum (LGM). A structured pattern of diversity was identified, with the presence of two groups that followed a climatic gradient from mesic to semi-arid regions. Most populations were represented by a single haplotype, but many haplotypes were shared among populations, with some having widespread distributions. A putative refugial area with high haplotype diversity was identified at the centre of the species distribution. Species distribution modelling showed high climatic suitability at the LGM and high climatic stability in the central region where higher genetic diversity was found, and low suitability elsewhere, consistent with a pattern of range contraction. Combination of phylogeography and paleo-distribution modelling can provide an evolutionary context for climate-driven tree decline, as both can be used to cross-validate evidence for refugia and contraction under harsh climatic conditions. This approach identified a central refugial area in the test species E. wandoo, with more recent expansion into peripheral areas from where it had
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West, Amanda M; Evangelista, Paul H; Jarnevich, Catherine S; Young, Nicholas E; Stohlgren, Thomas J; Talbert, Colin; Talbert, Marian; Morisette, Jeffrey; Anderson, Ryan
2016-10-11
Early detection of invasive plant species is vital for the management of natural resources and protection of ecosystem processes. The use of satellite remote sensing for mapping the distribution of invasive plants is becoming more common, however conventional imaging software and classification methods have been shown to be unreliable. In this study, we test and evaluate the use of five species distribution model techniques fit with satellite remote sensing data to map invasive tamarisk (Tamarix spp.) along the Arkansas River in Southeastern Colorado. The models tested included boosted regression trees (BRT), Random Forest (RF), multivariate adaptive regression splines (MARS), generalized linear model (GLM), and Maxent. These analyses were conducted using a newly developed software package called the Software for Assisted Habitat Modeling (SAHM). All models were trained with 499 presence points, 10,000 pseudo-absence points, and predictor variables acquired from the Landsat 5 Thematic Mapper (TM) sensor over an eight-month period to distinguish tamarisk from native riparian vegetation using detection of phenological differences. From the Landsat scenes, we used individual bands and calculated Normalized Difference Vegetation Index (NDVI), Soil-Adjusted Vegetation Index (SAVI), and tasseled capped transformations. All five models identified current tamarisk distribution on the landscape successfully based on threshold independent and threshold dependent evaluation metrics with independent location data. To account for model specific differences, we produced an ensemble of all five models with map output highlighting areas of agreement and areas of uncertainty. Our results demonstrate the usefulness of species distribution models in analyzing remotely sensed data and the utility of ensemble mapping, and showcase the capability of SAHM in pre-processing and executing multiple complex models.
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West, Amanda M.; Evangelista, Paul H.; Jarnevich, Catherine S.; Young, Nicholas E.; Stohlgren, Thomas J.; Talbert, Colin; Talbert, Marian; Morisette, Jeffrey; Anderson, Ryan
2016-01-01
Early detection of invasive plant species is vital for the management of natural resources and protection of ecosystem processes. The use of satellite remote sensing for mapping the distribution of invasive plants is becoming more common, however conventional imaging software and classification methods have been shown to be unreliable. In this study, we test and evaluate the use of five species distribution model techniques fit with satellite remote sensing data to map invasive tamarisk (Tamarix spp.) along the Arkansas River in Southeastern Colorado. The models tested included boosted regression trees (BRT), Random Forest (RF), multivariate adaptive regression splines (MARS), generalized linear model (GLM), and Maxent. These analyses were conducted using a newly developed software package called the Software for Assisted Habitat Modeling (SAHM). All models were trained with 499 presence points, 10,000 pseudo-absence points, and predictor variables acquired from the Landsat 5 Thematic Mapper (TM) sensor over an eight-month period to distinguish tamarisk from native riparian vegetation using detection of phenological differences. From the Landsat scenes, we used individual bands and calculated Normalized Difference Vegetation Index (NDVI), Soil-Adjusted Vegetation Index (SAVI), and tasseled capped transformations. All five models identified current tamarisk distribution on the landscape successfully based on threshold independent and threshold dependent evaluation metrics with independent location data. To account for model specific differences, we produced an ensemble of all five models with map output highlighting areas of agreement and areas of uncertainty. Our results demonstrate the usefulness of species distribution models in analyzing remotely sensed data and the utility of ensemble mapping, and showcase the capability of SAHM in pre-processing and executing multiple complex models.
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Alan K. Swanson; Solomon Z. Dobrowski; Andrew O. Finley; James H. Thorne; Michael K. Schwartz
2013-01-01
The uncertainty associated with species distribution model (SDM) projections is poorly characterized, despite its potential value to decision makers. Error estimates from most modelling techniques have been shown to be biased due to their failure to account for spatial autocorrelation (SAC) of residual error. Generalized linear mixed models (GLMM) have the ability to...
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Moreno-Amat, Elena; Rubiales, Juan Manuel; Morales-Molino, César; García-Amorena, Ignacio
2017-08-01
The increasing development of species distribution models (SDMs) using palaeodata has created new prospects to address questions of evolution, ecology and biogeography from wider perspectives. Palaeobotanical data provide information on the past distribution of taxa at a given time and place and its incorporation on modelling has contributed to advancing the SDM field. This has allowed, for example, to calibrate models under past climate conditions or to validate projected models calibrated on current species distributions. However, these data also bear certain shortcomings when used in SDMs that may hinder the resulting ecological outcomes and eventually lead to misleading conclusions. Palaeodata may not be equivalent to present data, but instead frequently exhibit limitations and biases regarding species representation, taxonomy and chronological control, and their inclusion in SDMs should be carefully assessed. The limitations of palaeobotanical data applied to SDM studies are infrequently discussed and often neglected in the modelling literature; thus, we argue for the more careful selection and control of these data. We encourage authors to use palaeobotanical data in their SDMs studies and for doing so, we propose some recommendations to improve the robustness, reliability and significance of palaeo-SDM analyses.
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Fieberg, John R.; Forester, James D.; Street, Garrett M.; Johnson, Douglas H.; ArchMiller, Althea A.; Matthiopoulos, Jason
2018-01-01
“Species distribution modeling” was recently ranked as one of the top five “research fronts” in ecology and the environmental sciences by ISI's Essential Science Indicators (Renner and Warton 2013), reflecting the importance of predicting how species distributions will respond to anthropogenic change. Unfortunately, species distribution models (SDMs) often perform poorly when applied to novel environments. Compounding on this problem is the shortage of methods for evaluating SDMs (hence, we may be getting our predictions wrong and not even know it). Traditional methods for validating SDMs quantify a model's ability to classify locations as used or unused. Instead, we propose to focus on how well SDMs can predict the characteristics of used locations. This subtle shift in viewpoint leads to a more natural and informative evaluation and validation of models across the entire spectrum of SDMs. Through a series of examples, we show how simple graphical methods can help with three fundamental challenges of habitat modeling: identifying missing covariates, non-linearity, and multicollinearity. Identifying habitat characteristics that are not well-predicted by the model can provide insights into variables affecting the distribution of species, suggest appropriate model modifications, and ultimately improve the reliability and generality of conservation and management recommendations.
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West, Amanda M.; Evangelista, Paul H.; Jarnevich, Catherine S.; Young, Nicholas E.; Stohlgren, Thomas J.; Talbert, Colin; Talbert, Marian; Morisette, Jeffrey; Anderson, Ryan
2016-01-01
Early detection of invasive plant species is vital for the management of natural resources and protection of ecosystem processes. The use of satellite remote sensing for mapping the distribution of invasive plants is becoming more common, however conventional imaging software and classification methods have been shown to be unreliable. In this study, we test and evaluate the use of five species distribution model techniques fit with satellite remote sensing data to map invasive tamarisk (Tama...
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Sangermano, Florencia
2009-12-01
The world is suffering from rapid changes in both climate and land cover which are the main factors affecting global biodiversity. These changes may affect ecosystems by altering species distributions, population sizes, and community compositions, which emphasizes the need for a rapid assessment of biodiversity status for conservation and management purposes. Current approaches on monitoring biodiversity rely mainly on long term observations of predetermined sites, which require large amounts of time, money and personnel to be executed. In order to overcome problems associated with current field monitoring methods, the main objective of this dissertation is the development of framework for inferential monitoring of the impact of global change on biodiversity based on remotely sensed data coupled with species distribution modeling techniques. Several research pieces were performed independently in order to fulfill this goal. First, species distribution modeling was used to identify the ranges of 6362 birds, mammals and amphibians in South America. Chapter 1 compares the power of different presence-only species distribution methods for modeling distributions of species with different response curves to environmental gradients and sample sizes. It was found that there is large variability in the power of the methods for modeling habitat suitability and species ranges, showing the importance of performing, when possible, a preliminary gradient analysis of the species distribution before selecting the method to be used. Chapter 2 presents a new methodology for the redefinition of species range polygons. Using a method capable of establishing the uncertainty in the definition of existing range polygons, the automated procedure identifies the relative importance of bioclimatic variables for the species, predicts their ranges and generates a quality assessment report to explore prediction errors. Analysis using independent validation data shows the power of this
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Species distribution modelling for conservation of an endangered endemic orchid.
Wang, Hsiao-Hsuan; Wonkka, Carissa L; Treglia, Michael L; Grant, William E; Smeins, Fred E; Rogers, William E
2015-04-21
Concerns regarding the long-term viability of threatened and endangered plant species are increasingly warranted given the potential impacts of climate change and habitat fragmentation on unstable and isolated populations. Orchidaceae is the largest and most diverse family of flowering plants, but it is currently facing unprecedented risks of extinction. Despite substantial conservation emphasis on rare orchids, populations continue to decline. Spiranthes parksii (Navasota ladies' tresses) is a federally and state-listed endangered terrestrial orchid endemic to central Texas. Hence, we aimed to identify potential factors influencing the distribution of the species, quantify the relative importance of each factor and determine suitable habitat for future surveys and targeted conservation efforts. We analysed several geo-referenced variables describing climatic conditions and landscape features to identify potential factors influencing the likelihood of occurrence of S. parksii using boosted regression trees. Our model classified 97 % of the cells correctly with regard to species presence and absence, and indicated that probability of existence was correlated with climatic conditions and landscape features. The most influential variables were mean annual precipitation, mean elevation, mean annual minimum temperature and mean annual maximum temperature. The most likely suitable range for S. parksii was the eastern portions of Leon and Madison Counties, the southern portion of Brazos County, a portion of northern Grimes County and along the borders between Burleson and Washington Counties. Our model can assist in the development of an integrated conservation strategy through: (i) focussing future survey and research efforts on areas with a high likelihood of occurrence, (ii) aiding in selection of areas for conservation and restoration and (iii) framing future research questions including those necessary for predicting responses to climate change. Our model could also
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Energy Technology Data Exchange (ETDEWEB)
Olivero, J.; Toxopeus, A.G.; Skidmore, A.K.; Real, R.
2016-07-01
Statistical downscaling is used to improve the knowledge of spatial distributions from broad–scale to fine–scale maps with higher potential for conservation planning. We assessed the effectiveness of downscaling in two commonly used species distribution models: Maximum Entropy (MaxEnt) and the Favourability Function (FF). We used atlas data (10 x 10 km) of the fire salamander Salamandra salamandra distribution in southern Spain to derive models at a 1 x 1 km resolution. Downscaled models were assessed using an independent dataset of the species’ distribution at 1 x 1 km. The Favourability model showed better downscaling performance than the MaxEnt model, and the models that were based on linear combinations of environmental variables performed better than models allowing higher flexibility. The Favourability model minimized model overfitting compared to the MaxEnt model. (Author)
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Directory of Open Access Journals (Sweden)
M. Williams-Tripp
2012-01-01
Full Text Available The endemic Pyrenean Desman (Galemys pyrenaicus is an elusive, rare, and vulnerable species declining over its entire and narrow range (Spain, Portugal, France, and Andorra. The principal set of conservation measures in France is a 5-years National Action Plan based on 25 conservation actions. Priority is given to update its present distribution and develop tools for predictive distribution models. We aim at building the first species distribution model and map for the northern edge of the range of the Desman and confronting the outputs of the model to target conservation efforts in the context of environmental change. Contrasting to former comparable studies, we derive a simpler model emphasizing the importance of factors linked to precipitation and not to the temperature. If temperature is one of the climate change key factors, depicted shrinkage in Desman distribution could be lower or null at the northern (French edge suggesting thus a major role for this northern population in terms of conservation of the species. Finally, we question the applied issue of temporal and spatial transferability for such environmental favourability models when it is made at the edge of the distribution range.
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Wang, Wen J; He, Hong S; Thompson, Frank R; Spetich, Martin A; Fraser, Jacob S
2018-09-01
Demographic processes (fecundity, dispersal, colonization, growth, and mortality) and their interactions with environmental changes are not well represented in current climate-distribution models (e.g., niche and biophysical process models) and constitute a large uncertainty in projections of future tree species distribution shifts. We investigate how species biological traits and environmental heterogeneity affect species distribution shifts. We used a species-specific, spatially explicit forest dynamic model LANDIS PRO, which incorporates site-scale tree species demography and competition, landscape-scale dispersal and disturbances, and regional-scale abiotic controls, to simulate the distribution shifts of four representative tree species with distinct biological traits in the central hardwood forest region of United States. Our results suggested that biological traits (e.g., dispersal capacity, maturation age) were important for determining tree species distribution shifts. Environmental heterogeneity, on average, reduced shift rates by 8% compared to perfect environmental conditions. The average distribution shift rates ranged from 24 to 200myear -1 under climate change scenarios, implying that many tree species may not able to keep up with climate change because of limited dispersal capacity, long generation time, and environmental heterogeneity. We suggest that climate-distribution models should include species demographic processes (e.g., fecundity, dispersal, colonization), biological traits (e.g., dispersal capacity, maturation age), and environmental heterogeneity (e.g., habitat fragmentation) to improve future predictions of species distribution shifts in response to changing climates. Copyright © 2018 Elsevier B.V. All rights reserved.
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Aguirre-Gutiérrez, J.; Carvalheiro, L.G.; Polce, C.; van Loon, E.E.; Raes, N.; Reemer, M.; Biesmeijer, J.C.
2013-01-01
Understanding species distributions and the factors limiting them is an important topic in ecology and conservation, including in nature reserve selection and predicting climate change impacts. While Species Distribution Models (SDM) are the main tool used for these purposes, choosing the best SDM
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Directory of Open Access Journals (Sweden)
Olivero, J.
2016-03-01
Full Text Available Statistical downscaling is used to improve the knowledge of spatial distributions from broad–scale to fine–scale maps with higher potential for conservation planning. We assessed the effectiveness of downscaling in two commonly used species distribution models: Maximum Entropy (MaxEnt and the Favourability Function (FF. We used atlas data (10 x 10 km of the fire salamander Salamandra salamandra distribution in southern Spain to derive models at a 1 x 1 km resolution. Downscaled models were assessed using an independent dataset of the species’ distribution at 1 x 1 km. The Favourability model showed better downscaling performance than the MaxEnt model, and the models that were based on linear combinations of environmental variables performed better than models allowing higher flexibility. The Favourability model minimized model overfitting compared to the MaxEnt model.
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Directory of Open Access Journals (Sweden)
Lorena Ribeiro de A Carneiro
Full Text Available Species-distribution models (SDM are tools with potential to inform environmental-impact studies (EIA. However, they are not always appropriate and may result in improper and expensive mitigation and compensation if their limitations are not understood by decision makers. Here, we examine the use of SDM for frogs that were used in impact assessment using data obtained from the EIA of a hydroelectric project located in the Amazon Basin in Brazil. The results show that lack of knowledge of species distributions limits the appropriate use of SDM in the Amazon region for most target species. Because most of these targets are newly described and their distributions poorly known, data about their distributions are insufficient to be effectively used in SDM. Surveys that are mandatory for the EIA are often conducted only near the area under assessment, and so models must extrapolate well beyond the sampled area to inform decisions made at much larger spatial scales, such as defining areas to be used to offset the negative effects of the projects. Using distributions of better-known species in simulations, we show that geographical-extrapolations based on limited information of species ranges often lead to spurious results. We conclude that the use of SDM as evidence to support project-licensing decisions in the Amazon requires much greater area sampling for impact studies, or, alternatively, integrated and comparative survey strategies, to improve biodiversity sampling. When more detailed distribution information is unavailable, SDM will produce results that generate uncertain and untestable decisions regarding impact assessment. In many cases, SDM is unlikely to be better than the use of expert opinion.
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Equilibrium of global amphibian species distributions with climate
DEFF Research Database (Denmark)
Munguía, Mariana; Rahbek, Carsten; Rangel, Thiago F.
2012-01-01
A common assumption in bioclimatic envelope modeling is that species distributions are in equilibrium with contemporary climate. A number of studies have measured departures from equilibrium in species distributions in particular regions, but such investigations were never carried out for a compl...
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Duscher Tanja; Nopp-Mayr Ursula
2017-01-01
Species distribution models are important tools for wildlife management planning, particularly in the case of invasive species. We employed a recent framework for niche-based invasive species distribution modeling to predict the probability of presence for the invasive raccoon dog (Nyctereutes procyonoides) in Austria. The raccoon dog is an adaptive, mobile and highly reproductive Asiatic canid that has successfully invaded many parts of Europe. It is known...
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Crase, Beth; Vesk, Peter A; Liedloff, Adam; Wintle, Brendan A
2015-08-01
Dominant species influence the composition and abundance of other species present in ecosystems. However, forecasts of distributional change under future climates have predominantly focused on changes in species distribution and ignored possible changes in spatial and temporal patterns of dominance. We develop forecasts of spatial changes for the distribution of species dominance, defined in terms of basal area, and for species occurrence, in response to sea level rise for three tree taxa within an extensive mangrove ecosystem in northern Australia. Three new metrics are provided, indicating the area expected to be suitable under future conditions (Eoccupied ), the instability of suitable area (Einstability ) and the overlap between the current and future spatial distribution (Eoverlap ). The current dominance and occurrence were modelled in relation to a set of environmental variables using boosted regression tree (BRT) models, under two scenarios of seedling establishment: unrestricted and highly restricted. While forecasts of spatial change were qualitatively similar for species occurrence and dominance, the models of species dominance exhibited higher metrics of model fit and predictive performance, and the spatial pattern of future dominance was less similar to the current pattern than was the case for the distributions of species occurrence. This highlights the possibility of greater changes in the spatial patterning of mangrove tree species dominance under future sea level rise. Under the restricted seedling establishment scenario, the area occupied by or dominated by a species declined between 42.1% and 93.8%, while for unrestricted seedling establishment, the area suitable for dominance or occurrence of each species varied from a decline of 68.4% to an expansion of 99.5%. As changes in the spatial patterning of dominance are likely to cause a cascade of effects throughout the ecosystem, forecasting spatial changes in dominance provides new and
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Hällfors, Maria Helena; Liao, Jishan; Dzurisin, Jason D. K.; Grundel, Ralph; Hyvärinen, Marko; Towle, Kevin; Wu, Grace C.; Hellmann, Jessica J.
2016-01-01
Species distribution models (SDMs) have been criticized for involving assumptions that ignore or categorize many ecologically relevant factors such as dispersal ability and biotic interactions. Another potential source of model error is the assumption that species are ecologically uniform in their climatic tolerances across their range. Typically, SDMs to treat a species as a single entity, although populations of many species differ due to local adaptation or other genetic differentiation. Not taking local adaptation into account, may lead to incorrect range prediction and therefore misplaced conservation efforts. A constraint is that we often do not know the degree to which populations are locally adapted, however. Lacking experimental evidence, we still can evaluate niche differentiation within a species' range to promote better conservation decisions. We explore possible conservation implications of making type I or type II errors in this context. For each of two species, we construct three separate MaxEnt models, one considering the species as a single population and two of disjunct populations. PCA analyses and response curves indicate different climate characteristics in the current environments of the populations. Model projections into future climates indicate minimal overlap between areas predicted to be climatically suitable by the whole species versus population-based models. We present a workflow for addressing uncertainty surrounding local adaptation in SDM application and illustrate the value of conducting population-based models to compare with whole-species models. These comparisons might result in more cautious management actions when alternative range outcomes are considered.
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Gogol-Prokurat, Melanie
2011-01-01
If species distribution models (SDMs) can rank habitat suitability at a local scale, they may be a valuable conservation planning tool for rare, patchily distributed species. This study assessed the ability of Maxent, an SDM reported to be appropriate for modeling rare species, to rank habitat suitability at a local scale for four edaphic endemic rare plants of gabbroic soils in El Dorado County, California, and examined the effects of grain size, spatial extent, and fine-grain environmental predictors on local-scale model accuracy. Models were developed using species occurrence data mapped on public lands and were evaluated using an independent data set of presence and absence locations on surrounding lands, mimicking a typical conservation-planning scenario that prioritizes potential habitat on unsurveyed lands surrounding known occurrences. Maxent produced models that were successful at discriminating between suitable and unsuitable habitat at the local scale for all four species, and predicted habitat suitability values were proportional to likelihood of occurrence or population abundance for three of four species. Unfortunately, models with the best discrimination (i.e., AUC) were not always the most useful for ranking habitat suitability. The use of independent test data showed metrics that were valuable for evaluating which variables and model choices (e.g., grain, extent) to use in guiding habitat prioritization for conservation of these species. A goodness-of-fit test was used to determine whether habitat suitability values ranked habitat suitability on a continuous scale. If they did not, a minimum acceptable error predicted area criterion was used to determine the threshold for classifying habitat as suitable or unsuitable. I found a trade-off between model extent and the use of fine-grain environmental variables: goodness of fit was improved at larger extents, and fine-grain environmental variables improved local-scale accuracy, but fine-grain variables
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Illoldi-Rangel, Patricia; Rivaldi, Chissa-Louise; Sissel, Blake; Trout Fryxell, Rebecca; Gordillo-Pérez, Guadalupe; Rodríguez-Moreno, Angel; Williamson, Phillip; Montiel-Parra, Griselda; Sánchez-Cordero, Víctor; Sarkar, Sahotra
2012-01-01
Species distribution models were constructed for ten Ixodes species and Amblyomma cajennense for a region including Mexico and Texas. The model was based on a maximum entropy algorithm that used environmental layers to predict the relative probability of presence for each taxon. For Mexico, species geographic ranges were predicted by restricting the models to cells which have a higher probability than the lowest probability of the cells in which a presence record was located. There was spatial nonconcordance between the distributions of Amblyomma cajennense and the Ixodes group with the former restricted to lowlands and mainly the eastern coast of Mexico and the latter to montane regions with lower temperature. The risk of Lyme disease is, therefore, mainly present in the highlands where some Ixodes species are known vectors; if Amblyomma cajennense turns out to be a competent vector, the area of risk also extends to the lowlands and the east coast.
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Directory of Open Access Journals (Sweden)
Patricia Illoldi-Rangel
2012-01-01
Full Text Available Species distribution models were constructed for ten Ixodes species and Amblyomma cajennense for a region including Mexico and Texas. The model was based on a maximum entropy algorithm that used environmental layers to predict the relative probability of presence for each taxon. For Mexico, species geographic ranges were predicted by restricting the models to cells which have a higher probability than the lowest probability of the cells in which a presence record was located. There was spatial nonconcordance between the distributions of Amblyomma cajennense and the Ixodes group with the former restricted to lowlands and mainly the eastern coast of Mexico and the latter to montane regions with lower temperature. The risk of Lyme disease is, therefore, mainly present in the highlands where some Ixodes species are known vectors; if Amblyomma cajennense turns out to be a competent vector, the area of risk also extends to the lowlands and the east coast.
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Sindt, Anthony R.; Pierce, Clay; Quist, Michael C.
2012-01-01
Effective conservation of fish species of greatest conservation need (SGCN) requires an understanding of species–habitat relationships and distributional trends. Thus, modeling the distribution of fish species across large spatial scales may be a valuable tool for conservation planning. Our goals were to evaluate the status of 10 fish SGCN in wadeable Iowa streams and to test the effectiveness of Iowa Aquatic Gap Analysis Project (IAGAP) species distribution models. We sampled fish assemblages from 86 wadeable stream segments in the Mississippi River drainage of Iowa during 2009 and 2010 to provide contemporary, independent fish species presence–absence data. The frequencies of occurrence in stream segments where species were historically documented varied from 0.0% for redfin shiner Lythrurus umbratilis to 100.0% for American brook lampreyLampetra appendix, with a mean of 53.0%, suggesting that the status of Iowa fish SGCN is highly variable. Cohen's kappa values and other model performance measures were calculated by comparing field-collected presence–absence data with IAGAP model–predicted presences and absences for 12 fish SGCN. Kappa values varied from 0.00 to 0.50, with a mean of 0.15. The models only predicted the occurrences of banded darterEtheostoma zonale, southern redbelly dace Phoxinus erythrogaster, and longnose daceRhinichthys cataractae more accurately than would be expected by chance. Overall, the accuracy of the twelve models was low, with a mean correct classification rate of 58.3%. Poor model performance probably reflects the difficulties associated with modeling the distribution of rare species and the inability of the large-scale habitat variables used in IAGAP models to explain the variation in fish species occurrences. Our results highlight the importance of quantifying the confidence in species distribution model predictions with an independent data set and the need for long-term monitoring to better understand the
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Near term climate projections for invasive species distributions
Jarnevich, C.S.; Stohlgren, T.J.
2009-01-01
Climate change and invasive species pose important conservation issues separately, and should be examined together. We used existing long term climate datasets for the US to project potential climate change into the future at a finer spatial and temporal resolution than the climate change scenarios generally available. These fine scale projections, along with new species distribution modeling techniques to forecast the potential extent of invasive species, can provide useful information to aide conservation and invasive species management efforts. We created habitat suitability maps for Pueraria montana (kudzu) under current climatic conditions and potential average conditions up to 30 years in the future. We examined how the potential distribution of this species will be affected by changing climate, and the management implications associated with these changes. Our models indicated that P. montana may increase its distribution particularly in the Northeast with climate change and may decrease in other areas. ?? 2008 Springer Science+Business Media B.V.
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Heuner, Maike; Weber, Arnd; Schröder, Uwe; Kleinschmit, Birgit; Schröder, Boris
2016-09-15
The European Water Framework Directive requires a good ecological potential for heavily modified water bodies. This standard has not been reached for most large estuaries by 2015. Management plans for estuaries fall short in linking implementations between restoration measures and underlying spatial analyses. The distribution of emergent macrophytes - as an indicator of habitat quality - is here used to assess the ecological potential. Emergent macrophytes are capable of settling on gentle tidal flats where hydrodynamic stress is comparatively low. Analyzing their habitats based on spatial data, we set up species distribution models with 'elevation relative to mean high water', 'mean bank slope', and 'length of bottom friction' from shallow water up to the vegetation belt as key predictors representing hydrodynamic stress. Effects of restoration scenarios on habitats were assessed applying these models. Our findings endorse species distribution models as crucial spatial planning tools for implementing restoration measures in modified estuaries. Copyright © 2016 Elsevier Ltd. All rights reserved.
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Uncertainty of future projections of species distributions in mountainous regions.
Directory of Open Access Journals (Sweden)
Ying Tang
Full Text Available Multiple factors introduce uncertainty into projections of species distributions under climate change. The uncertainty introduced by the choice of baseline climate information used to calibrate a species distribution model and to downscale global climate model (GCM simulations to a finer spatial resolution is a particular concern for mountainous regions, as the spatial resolution of climate observing networks is often insufficient to detect the steep climatic gradients in these areas. Using the maximum entropy (MaxEnt modeling framework together with occurrence data on 21 understory bamboo species distributed across the mountainous geographic range of the Giant Panda, we examined the differences in projected species distributions obtained from two contrasting sources of baseline climate information, one derived from spatial interpolation of coarse-scale station observations and the other derived from fine-spatial resolution satellite measurements. For each bamboo species, the MaxEnt model was calibrated separately for the two datasets and applied to 17 GCM simulations downscaled using the delta method. Greater differences in the projected spatial distributions of the bamboo species were observed for the models calibrated using the different baseline datasets than between the different downscaled GCM simulations for the same calibration. In terms of the projected future climatically-suitable area by species, quantification using a multi-factor analysis of variance suggested that the sum of the variance explained by the baseline climate dataset used for model calibration and the interaction between the baseline climate data and the GCM simulation via downscaling accounted for, on average, 40% of the total variation among the future projections. Our analyses illustrate that the combined use of gridded datasets developed from station observations and satellite measurements can help estimate the uncertainty introduced by the choice of baseline
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Directory of Open Access Journals (Sweden)
Victor Aguilar-Soto
2015-03-01
Full Text Available Species distribution models (SDMs help identify areas for the development of populations or communities to prevent extinctions, especially in the face of the global environmental change. This study modeled the potential distribution of the tree Picea chihuahuana Martínez, a species in danger of extinction, using the maximum entropy modeling method (MaxEnt at three scales: local, state and national. We used a total of 38 presence data from the Sierra Madre Occidental. At the local scale, we compared MaxEnt with the reclassification and overlay method integrated in a geographic information system. MaxEnt generated maps with a high predictive capability (AUC > 0.97. The distribution of P. chihuahuana is defined by vegetation type and minimum temperature at national and state scales. At the local scale, both models calculated similar areas for the potential distribution of the species; the variables that better defined the species distribution were vegetation type, aspect and distance to water flows. Populations of P. chihuahuana have always been small, but our results show potential habitat greater than the area of the actual distribution. These results provide an insight into the availability of areas suitable for the species’ regeneration, possibly through assisted colonization.
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A simple model for skewed species-lifetime distributions
Murase, Yohsuke; Shimada, Takashi; Ito, Nobuyasu
2010-01-01
A simple model of a biological community assembly is studied. Communities are assembled by successive migrations and extinctions of species. In the model, species are interacting with each other. The intensity of the interaction between each pair
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How much does climate change threaten European forest tree species distributions?
Dyderski, Marcin K; Paź, Sonia; Frelich, Lee E; Jagodziński, Andrzej M
2018-03-01
Although numerous species distribution models have been developed, most were based on insufficient distribution data or used older climate change scenarios. We aimed to quantify changes in projected ranges and threat level by the years 2061-2080, for 12 European forest tree species under three climate change scenarios. We combined tree distribution data from the Global Biodiversity Information Facility, EUFORGEN, and forest inventories, and we developed species distribution models using MaxEnt and 19 bioclimatic variables. Models were developed for three climate change scenarios-optimistic (RCP2.6), moderate (RCP4.5), and pessimistic (RPC8.5)-using three General Circulation Models, for the period 2061-2080. Our study revealed different responses of tree species to projected climate change. The species may be divided into three groups: "winners"-mostly late-successional species: Abies alba, Fagus sylvatica, Fraxinus excelsior, Quercus robur, and Quercus petraea; "losers"-mostly pioneer species: Betula pendula, Larix decidua, Picea abies, and Pinus sylvestris; and alien species-Pseudotsuga menziesii, Quercus rubra, and Robinia pseudoacacia, which may be also considered as "winners." Assuming limited migration, most of the species studied would face a significant decrease in suitable habitat area. The threat level was highest for species that currently have the northernmost distribution centers. Ecological consequences of the projected range contractions would be serious for both forest management and nature conservation. © 2017 John Wiley & Sons Ltd.
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Schlemm, Eckhard
2015-09-01
The Bak-Sneppen model is an abstract representation of a biological system that evolves according to the Darwinian principles of random mutation and selection. The species in the system are characterized by a numerical fitness value between zero and one. We show that in the case of five species the steady-state fitness distribution can be obtained as a solution to a linear differential equation of order five with hypergeometric coefficients. Similar representations for the asymptotic fitness distribution in larger systems may help pave the way towards a resolution of the question of whether or not, in the limit of infinitely many species, the fitness is asymptotically uniformly distributed on the interval [fc, 1] with fc ≳ 2/3. Copyright © 2015 Elsevier Inc. All rights reserved.
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Directory of Open Access Journals (Sweden)
Duscher Tanja
2017-01-01
Full Text Available Species distribution models are important tools for wildlife management planning, particularly in the case of invasive species. We employed a recent framework for niche-based invasive species distribution modeling to predict the probability of presence for the invasive raccoon dog (Nyctereutes procyonoides in Austria. The raccoon dog is an adaptive, mobile and highly reproductive Asiatic canid that has successfully invaded many parts of Europe. It is known to occur in Austria since 1963 and is now widespread in the northern and eastern parts of the country, but its population density remains low. With the help of a species distribution model we identified focal areas for future monitoring and management actions, and we address some management implications for the raccoon dog in Austria. We also determined the environmental predictors of raccoon dog distribution in this alpine country. Its distribution seems to be mainly limited by climatic factors (snow depth, duration of snow cover, winter precipitation and mean annual temperature and is thus linked to elevation. Consequently, we assumed the Alps to be a barrier for the spread of the invasive raccoon dog in Europe; however, its ecological permeability is expected to increase with ongoing climate change.
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Directory of Open Access Journals (Sweden)
Maria da Salete Gurgel Costa
2014-08-01
Full Text Available Phacellodomus Reichenbach, 1853, comprises nine species of Furnariids that occur in South America in open and generally dry areas. This study estimated the geographic distributions of Phacellodomus species in South America by ecological niche modeling. Applying maximum entropy method, models were produced for eight species based on six climatic variables and 949 occurrence records. Since highest climatic suitability for Phacellodomus species has been estimated in open and dry areas, the Amazon rainforest areas are not very suitable for these species. Annual precipitation and minimum temperature of the coldest month are the variables that most influence the models. Phacellodomus species occurred in 35 ecoregions of South America. Chaco and Uruguayan savannas were the ecoregions with the highest number of species. Despite the overall connection of Phacellodomus species with dry areas, species such as P. ruber, P. rufifrons, P. ferrugineigula and P. erythrophthalmus occurred in wet forests and wetland ecoregions.
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Directory of Open Access Journals (Sweden)
Chunrong Mi
2017-01-01
Full Text Available Species distribution models (SDMs have become an essential tool in ecology, biogeography, evolution and, more recently, in conservation biology. How to generalize species distributions in large undersampled areas, especially with few samples, is a fundamental issue of SDMs. In order to explore this issue, we used the best available presence records for the Hooded Crane (Grus monacha, n = 33, White-naped Crane (Grus vipio, n = 40, and Black-necked Crane (Grus nigricollis, n = 75 in China as three case studies, employing four powerful and commonly used machine learning algorithms to map the breeding distributions of the three species: TreeNet (Stochastic Gradient Boosting, Boosted Regression Tree Model, Random Forest, CART (Classification and Regression Tree and Maxent (Maximum Entropy Models. In addition, we developed an ensemble forecast by averaging predicted probability of the above four models results. Commonly used model performance metrics (Area under ROC (AUC and true skill statistic (TSS were employed to evaluate model accuracy. The latest satellite tracking data and compiled literature data were used as two independent testing datasets to confront model predictions. We found Random Forest demonstrated the best performance for the most assessment method, provided a better model fit to the testing data, and achieved better species range maps for each crane species in undersampled areas. Random Forest has been generally available for more than 20 years and has been known to perform extremely well in ecological predictions. However, while increasingly on the rise, its potential is still widely underused in conservation, (spatial ecological applications and for inference. Our results show that it informs ecological and biogeographical theories as well as being suitable for conservation applications, specifically when the study area is undersampled. This method helps to save model-selection time and effort, and allows robust and rapid
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Mi, Chunrong; Huettmann, Falk; Guo, Yumin; Han, Xuesong; Wen, Lijia
2017-01-01
Species distribution models (SDMs) have become an essential tool in ecology, biogeography, evolution and, more recently, in conservation biology. How to generalize species distributions in large undersampled areas, especially with few samples, is a fundamental issue of SDMs. In order to explore this issue, we used the best available presence records for the Hooded Crane ( Grus monacha , n = 33), White-naped Crane ( Grus vipio , n = 40), and Black-necked Crane ( Grus nigricollis , n = 75) in China as three case studies, employing four powerful and commonly used machine learning algorithms to map the breeding distributions of the three species: TreeNet (Stochastic Gradient Boosting, Boosted Regression Tree Model), Random Forest, CART (Classification and Regression Tree) and Maxent (Maximum Entropy Models). In addition, we developed an ensemble forecast by averaging predicted probability of the above four models results. Commonly used model performance metrics (Area under ROC (AUC) and true skill statistic (TSS)) were employed to evaluate model accuracy. The latest satellite tracking data and compiled literature data were used as two independent testing datasets to confront model predictions. We found Random Forest demonstrated the best performance for the most assessment method, provided a better model fit to the testing data, and achieved better species range maps for each crane species in undersampled areas. Random Forest has been generally available for more than 20 years and has been known to perform extremely well in ecological predictions. However, while increasingly on the rise, its potential is still widely underused in conservation, (spatial) ecological applications and for inference. Our results show that it informs ecological and biogeographical theories as well as being suitable for conservation applications, specifically when the study area is undersampled. This method helps to save model-selection time and effort, and allows robust and rapid
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Directory of Open Access Journals (Sweden)
Mark Baah-Acheamfour
Full Text Available There are a number of overarching questions and debate in the scientific community concerning the importance of biotic interactions in species distribution models at large spatial scales. In this paper, we present a framework for revising the potential distribution of tree species native to the Western Ecoregion of Nova Scotia, Canada, by integrating the long-term effects of interspecific competition into an existing abiotic-factor-based definition of potential species distribution (PSD. The PSD model is developed by combining spatially explicit data of individualistic species' response to normalized incident photosynthetically active radiation, soil water content, and growing degree days. A revised PSD model adds biomass output simulated over a 100-year timeframe with a robust forest gap model and scaled up to the landscape using a forestland classification technique. To demonstrate the method, we applied the calculation to the natural range of 16 target tree species as found in 1,240 provincial forest-inventory plots. The revised PSD model, with the long-term effects of interspecific competition accounted for, predicted that eastern hemlock (Tsuga canadensis, American beech (Fagus grandifolia, white birch (Betula papyrifera, red oak (Quercus rubra, sugar maple (Acer saccharum, and trembling aspen (Populus tremuloides would experience a significant decline in their original distribution compared with balsam fir (Abies balsamea, black spruce (Picea mariana, red spruce (Picea rubens, red maple (Acer rubrum L., and yellow birch (Betula alleghaniensis. True model accuracy improved from 64.2% with original PSD evaluations to 81.7% with revised PSD. Kappa statistics slightly increased from 0.26 (fair to 0.41 (moderate for original and revised PSDs, respectively.
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Directory of Open Access Journals (Sweden)
Thomas J Matthews
2014-06-01
Full Text Available A species abundance distribution (SAD characterises patterns in the commonness and rarity of all species within an ecological community. As such, the SAD provides the theoretical foundation for a number of other biogeographical and macroecological patterns, such as the species–area relationship, as well as being an interesting pattern in its own right. While there has been resurgence in the study of SADs in the last decade, less focus has been placed on methodology in SAD research, and few attempts have been made to synthesise the vast array of methods which have been employed in SAD model evaluation. As such, our review has two aims. First, we provide a general overview of SADs, including descriptions of the commonly used distributions, plotting methods and issues with evaluating SAD models. Second, we review a number of recent advances in SAD model fitting and comparison. We conclude by providing a list of recommendations for fitting and evaluating SAD models. We argue that it is time for SAD studies to move away from many of the traditional methods available for fitting and evaluating models, such as sole reliance on the visual examination of plots, and embrace statistically rigorous techniques. In particular, we recommend the use of both goodness-of-fit tests and model-comparison analyses because each provides unique information which one can use to draw inferences.
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Directory of Open Access Journals (Sweden)
David W Redding
Full Text Available Statistical approaches for inferring the spatial distribution of taxa (Species Distribution Models, SDMs commonly rely on available occurrence data, which is often clumped and geographically restricted. Although available SDM methods address some of these factors, they could be more directly and accurately modelled using a spatially-explicit approach. Software to fit models with spatial autocorrelation parameters in SDMs are now widely available, but whether such approaches for inferring SDMs aid predictions compared to other methodologies is unknown. Here, within a simulated environment using 1000 generated species' ranges, we compared the performance of two commonly used non-spatial SDM methods (Maximum Entropy Modelling, MAXENT and boosted regression trees, BRT, to a spatial Bayesian SDM method (fitted using R-INLA, when the underlying data exhibit varying combinations of clumping and geographic restriction. Finally, we tested how any recommended methodological settings designed to account for spatially non-random patterns in the data impact inference. Spatial Bayesian SDM method was the most consistently accurate method, being in the top 2 most accurate methods in 7 out of 8 data sampling scenarios. Within high-coverage sample datasets, all methods performed fairly similarly. When sampling points were randomly spread, BRT had a 1-3% greater accuracy over the other methods and when samples were clumped, the spatial Bayesian SDM method had a 4%-8% better AUC score. Alternatively, when sampling points were restricted to a small section of the true range all methods were on average 10-12% less accurate, with greater variation among the methods. Model inference under the recommended settings to account for autocorrelation was not impacted by clumping or restriction of data, except for the complexity of the spatial regression term in the spatial Bayesian model. Methods, such as those made available by R-INLA, can be successfully used to account
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Redding, David W; Lucas, Tim C D; Blackburn, Tim M; Jones, Kate E
2017-01-01
Statistical approaches for inferring the spatial distribution of taxa (Species Distribution Models, SDMs) commonly rely on available occurrence data, which is often clumped and geographically restricted. Although available SDM methods address some of these factors, they could be more directly and accurately modelled using a spatially-explicit approach. Software to fit models with spatial autocorrelation parameters in SDMs are now widely available, but whether such approaches for inferring SDMs aid predictions compared to other methodologies is unknown. Here, within a simulated environment using 1000 generated species' ranges, we compared the performance of two commonly used non-spatial SDM methods (Maximum Entropy Modelling, MAXENT and boosted regression trees, BRT), to a spatial Bayesian SDM method (fitted using R-INLA), when the underlying data exhibit varying combinations of clumping and geographic restriction. Finally, we tested how any recommended methodological settings designed to account for spatially non-random patterns in the data impact inference. Spatial Bayesian SDM method was the most consistently accurate method, being in the top 2 most accurate methods in 7 out of 8 data sampling scenarios. Within high-coverage sample datasets, all methods performed fairly similarly. When sampling points were randomly spread, BRT had a 1-3% greater accuracy over the other methods and when samples were clumped, the spatial Bayesian SDM method had a 4%-8% better AUC score. Alternatively, when sampling points were restricted to a small section of the true range all methods were on average 10-12% less accurate, with greater variation among the methods. Model inference under the recommended settings to account for autocorrelation was not impacted by clumping or restriction of data, except for the complexity of the spatial regression term in the spatial Bayesian model. Methods, such as those made available by R-INLA, can be successfully used to account for spatial
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Wen J. Wang; Hong S. He; Frank R. Thompson; Martin A. Spetich; Jacob S. Fraser
2018-01-01
Demographic processes (fecundity, dispersal, colonization, growth, and mortality) and their interactions with environmental changes are notwell represented in current climate-distribution models (e.g., niche and biophysical process models) and constitute a large uncertainty in projections of future tree species distribution shifts.We investigate how species biological...
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Schirrmann, Michael; Joschko, Monika; Gebbers, Robin; Kramer, Eckart; Zörner, Mirjam; Barkusky, Dietmar; Timmer, Jens
2016-01-01
Earthworms are important for maintaining soil ecosystem functioning and serve as indicators of soil fertility. However, detection of earthworms is time-consuming, which hinders the assessment of earthworm abundances with high sampling density over entire fields. Recent developments of mobile terrestrial sensor platforms for proximal soil sensing (PSS) provided new tools for collecting dense spatial information of soils using various sensing principles. Yet, the potential of PSS for assessing earthworm habitats is largely unexplored. This study investigates whether PSS data contribute to the spatial prediction of earthworm abundances in species distribution models of agricultural soils. Proximal soil sensing data, e.g., soil electrical conductivity (EC), pH, and near infrared absorbance (NIR), were collected in real-time in a field with two management strategies (reduced tillage / conventional tillage) and sandy to loam soils. PSS was related to observations from a long-term (11 years) earthworm observation study conducted at 42 plots. Earthworms were sampled from 0.5 x 0.5 x 0.2 m³ soil blocks and identified to species level. Sensor data were highly correlated with earthworm abundances observed in reduced tillage but less correlated with earthworm abundances observed in conventional tillage. This may indicate that management influences the sensor-earthworm relationship. Generalized additive models and state-space models showed that modelling based on data fusion from EC, pH, and NIR sensors produced better results than modelling without sensor data or data from just a single sensor. Regarding the individual earthworm species, particular sensor combinations were more appropriate than others due to the different habitat requirements of the earthworms. Earthworm species with soil-specific habitat preferences were spatially predicted with higher accuracy by PSS than more ubiquitous species. Our findings suggest that PSS contributes to the spatial modelling of
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Directory of Open Access Journals (Sweden)
Michael Schirrmann
Full Text Available Earthworms are important for maintaining soil ecosystem functioning and serve as indicators of soil fertility. However, detection of earthworms is time-consuming, which hinders the assessment of earthworm abundances with high sampling density over entire fields. Recent developments of mobile terrestrial sensor platforms for proximal soil sensing (PSS provided new tools for collecting dense spatial information of soils using various sensing principles. Yet, the potential of PSS for assessing earthworm habitats is largely unexplored. This study investigates whether PSS data contribute to the spatial prediction of earthworm abundances in species distribution models of agricultural soils.Proximal soil sensing data, e.g., soil electrical conductivity (EC, pH, and near infrared absorbance (NIR, were collected in real-time in a field with two management strategies (reduced tillage / conventional tillage and sandy to loam soils. PSS was related to observations from a long-term (11 years earthworm observation study conducted at 42 plots. Earthworms were sampled from 0.5 x 0.5 x 0.2 m³ soil blocks and identified to species level. Sensor data were highly correlated with earthworm abundances observed in reduced tillage but less correlated with earthworm abundances observed in conventional tillage. This may indicate that management influences the sensor-earthworm relationship. Generalized additive models and state-space models showed that modelling based on data fusion from EC, pH, and NIR sensors produced better results than modelling without sensor data or data from just a single sensor. Regarding the individual earthworm species, particular sensor combinations were more appropriate than others due to the different habitat requirements of the earthworms. Earthworm species with soil-specific habitat preferences were spatially predicted with higher accuracy by PSS than more ubiquitous species.Our findings suggest that PSS contributes to the spatial
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Ibañez-Justicia, Adolfo; Cianci, Daniela
2015-05-01
Landscape modifications, urbanization or changes of use of rural-agricultural areas can create more favourable conditions for certain mosquito species and therefore indirectly cause nuisance problems for humans. This could potentially result in mosquito-borne disease outbreaks when the nuisance is caused by mosquito species that can transmit pathogens. Anopheles plumbeus is a nuisance mosquito species and a potential malaria vector. It is one of the most frequently observed species in the Netherlands. Information on the distribution of this species is essential for risk assessments. The purpose of the study was to investigate the potential spatial distribution of An. plumbeus in the Netherlands. Random forest models were used to link the occurrence and the abundance of An. plumbeus with environmental features and to produce distribution maps in the Netherlands. Mosquito data were collected using a cross-sectional study design in the Netherlands, from April to October 2010-2013. The environmental data were obtained from satellite imagery and weather stations. Statistical measures (accuracy for the occurrence model and mean squared error for the abundance model) were used to evaluate the models performance. The models were externally validated. The maps show that forested areas (centre of the Netherlands) and the east of the country were predicted as suitable for An. plumbeus. In particular high suitability and high abundance was predicted in the south-eastern provinces Limburg and North Brabant. Elevation, precipitation, day and night temperature and vegetation indices were important predictors for calculating the probability of occurrence for An. plumbeus. The probability of occurrence, vegetation indices and precipitation were important for predicting its abundance. The AUC value was 0.73 and the error in the validation was 0.29; the mean squared error value was 0.12. The areas identified by the model as suitable and with high abundance of An. plumbeus, are
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Directory of Open Access Journals (Sweden)
Orien M W Richmond
Full Text Available Species distribution models (SDMs are increasingly used for extrapolation, or predicting suitable regions for species under new geographic or temporal scenarios. However, SDM predictions may be prone to errors if species are not at equilibrium with climatic conditions in the current range and if training samples are not representative. Here the controversial "Pleistocene rewilding" proposal was used as a novel example to address some of the challenges of extrapolating modeled species-climate relationships outside of current ranges. Climatic suitability for three proposed proxy species (Asian elephant, African cheetah and African lion was extrapolated to the American southwest and Great Plains using Maxent, a machine-learning species distribution model. Similar models were fit for Oryx gazella, a species native to Africa that has naturalized in North America, to test model predictions. To overcome biases introduced by contracted modern ranges and limited occurrence data, random pseudo-presence points generated from modern and historical ranges were used for model training. For all species except the oryx, models of climatic suitability fit to training data from historical ranges produced larger areas of predicted suitability in North America than models fit to training data from modern ranges. Four naturalized oryx populations in the American southwest were correctly predicted with a generous model threshold, but none of these locations were predicted with a more stringent threshold. In general, the northern Great Plains had low climatic suitability for all focal species and scenarios considered, while portions of the southern Great Plains and American southwest had low to intermediate suitability for some species in some scenarios. The results suggest that the use of historical, in addition to modern, range information and randomly sampled pseudo-presence points may improve model accuracy. This has implications for modeling range shifts of
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Multi-scale approach for predicting fish species distributions across coral reef seascapes.
Directory of Open Access Journals (Sweden)
Simon J Pittman
Full Text Available Two of the major limitations to effective management of coral reef ecosystems are a lack of information on the spatial distribution of marine species and a paucity of data on the interacting environmental variables that drive distributional patterns. Advances in marine remote sensing, together with the novel integration of landscape ecology and advanced niche modelling techniques provide an unprecedented opportunity to reliably model and map marine species distributions across many kilometres of coral reef ecosystems. We developed a multi-scale approach using three-dimensional seafloor morphology and across-shelf location to predict spatial distributions for five common Caribbean fish species. Seascape topography was quantified from high resolution bathymetry at five spatial scales (5-300 m radii surrounding fish survey sites. Model performance and map accuracy was assessed for two high performing machine-learning algorithms: Boosted Regression Trees (BRT and Maximum Entropy Species Distribution Modelling (MaxEnt. The three most important predictors were geographical location across the shelf, followed by a measure of topographic complexity. Predictor contribution differed among species, yet rarely changed across spatial scales. BRT provided 'outstanding' model predictions (AUC = >0.9 for three of five fish species. MaxEnt provided 'outstanding' model predictions for two of five species, with the remaining three models considered 'excellent' (AUC = 0.8-0.9. In contrast, MaxEnt spatial predictions were markedly more accurate (92% map accuracy than BRT (68% map accuracy. We demonstrate that reliable spatial predictions for a range of key fish species can be achieved by modelling the interaction between the geographical location across the shelf and the topographic heterogeneity of seafloor structure. This multi-scale, analytic approach is an important new cost-effective tool to accurately delineate essential fish habitat and support
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Oke, Tobi A; Hager, Heather A
2017-01-01
The fate of Northern peatlands under climate change is important because of their contribution to global carbon (C) storage. Peatlands are maintained via greater plant productivity (especially of Sphagnum species) than decomposition, and the processes involved are strongly mediated by climate. Although some studies predict that warming will relax constraints on decomposition, leading to decreased C sequestration, others predict increases in productivity and thus increases in C sequestration. We explored the lack of congruence between these predictions using single-species and integrated species distribution models as proxies for understanding the environmental correlates of North American Sphagnum peatland occurrence and how projected changes to the environment might influence these peatlands under climate change. Using Maximum entropy and BIOMOD modelling platforms, we generated single and integrated species distribution models for four common Sphagnum species in North America under current climate and a 2050 climate scenario projected by three general circulation models. We evaluated the environmental correlates of the models and explored the disparities in niche breadth, niche overlap, and climate suitability among current and future models. The models consistently show that Sphagnum peatland distribution is influenced by the balance between soil moisture deficit and temperature of the driest quarter-year. The models identify the east and west coasts of North America as the core climate space for Sphagnum peatland distribution. The models show that, at least in the immediate future, the area of suitable climate for Sphagnum peatland could expand. This result suggests that projected warming would be balanced effectively by the anticipated increase in precipitation, which would increase Sphagnum productivity.
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[Effects of sampling plot number on tree species distribution prediction under climate change].
Liang, Yu; He, Hong-Shi; Wu, Zhi-Wei; Li, Xiao-Na; Luo, Xu
2013-05-01
Based on the neutral landscapes under different degrees of landscape fragmentation, this paper studied the effects of sampling plot number on the prediction of tree species distribution at landscape scale under climate change. The tree species distribution was predicted by the coupled modeling approach which linked an ecosystem process model with a forest landscape model, and three contingent scenarios and one reference scenario of sampling plot numbers were assumed. The differences between the three scenarios and the reference scenario under different degrees of landscape fragmentation were tested. The results indicated that the effects of sampling plot number on the prediction of tree species distribution depended on the tree species life history attributes. For the generalist species, the prediction of their distribution at landscape scale needed more plots. Except for the extreme specialist, landscape fragmentation degree also affected the effects of sampling plot number on the prediction. With the increase of simulation period, the effects of sampling plot number on the prediction of tree species distribution at landscape scale could be changed. For generalist species, more plots are needed for the long-term simulation.
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Engler, J O; Rödder, D; Elle, O; Hochkirch, A; Secondi, J
2013-11-01
Climate is a major factor delimiting species' distributions. However, biotic interactions may also be prominent in shaping geographical ranges, especially for parapatric species forming hybrid zones. Determining the relative effect of each factor and their interaction of the contact zone location has been difficult due to the lack of broad scale environmental data. Recent developments in species distribution modelling (SDM) now allow disentangling the relative contributions of climate and species' interactions in hybrid zones and their responses to future climate change. We investigated the moving hybrid zone between the breeding ranges of two parapatric passerines in Europe. We conducted SDMs representing the climatic conditions during the breeding season. Our results show a large mismatch between the realized and potential distributions of the two species, suggesting that interspecific interactions, not climate, account for the present location of the contact zone. The SDM scenarios show that the southerly distributed species, Hippolais polyglotta, might lose large parts of its southern distribution under climate change, but a similar gain of novel habitat along the hybrid zone seems unlikely, because interactions with the other species (H. icterina) constrain its range expansion. Thus, whenever biotic interactions limit range expansion, species may become 'trapped' if range loss due to climate change is faster than the movement of the contact zone. An increasing number of moving hybrid zones are being reported, but the proximate causes of movement often remain unclear. In a global context of climate change, we call for more interest in their interactions with climate change. © 2013 The Authors. Journal of Evolutionary Biology © 2013 European Society For Evolutionary Biology.
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Bettina Ohse; Falk Huettmann; Stefanie M. Ickert-Bond; Glenn P. Juday
2009-01-01
Most wilderness areas still lack accurate distribution information on tree species. We met this need with a predictive GIS modeling approach, using freely available digital data and computer programs to efficiently obtain high-quality species distribution maps. Here we present a digital map with the predicted distribution of white spruce (Picea glauca...
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Energy Technology Data Exchange (ETDEWEB)
Cui, Xiaohui [ORNL; Potok, Thomas E [ORNL
2006-01-01
The Flocking model, first proposed by Craig Reynolds, is one of the first bio-inspired computational collective behavior models that has many popular applications, such as animation. Our early research has resulted in a flock clustering algorithm that can achieve better performance than the Kmeans or the Ant clustering algorithms for data clustering. This algorithm generates a clustering of a given set of data through the embedding of the highdimensional data items on a two-dimensional grid for efficient clustering result retrieval and visualization. In this paper, we propose a bio-inspired clustering model, the Multiple Species Flocking clustering model (MSF), and present a distributed multi-agent MSF approach for document clustering.
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Brown, Jason L; Bennett, Joseph R; French, Connor M
2017-01-01
SDMtoolbox 2.0 is a software package for spatial studies of ecology, evolution, and genetics. The release of SDMtoolbox 2.0 allows researchers to use the most current ArcGIS software and MaxEnt software, and reduces the amount of time that would be spent developing common solutions. The central aim of this software is to automate complicated and repetitive spatial analyses in an intuitive graphical user interface. One core tenant facilitates careful parameterization of species distribution models (SDMs) to maximize each model's discriminatory ability and minimize overfitting. This includes carefully processing of occurrence data, environmental data, and model parameterization. This program directly interfaces with MaxEnt, one of the most powerful and widely used species distribution modeling software programs, although SDMtoolbox 2.0 is not limited to species distribution modeling or restricted to modeling in MaxEnt. Many of the SDM pre- and post-processing tools have 'universal' analogs for use with any modeling software. The current version contains a total of 79 scripts that harness the power of ArcGIS for macroecology, landscape genetics, and evolutionary studies. For example, these tools allow for biodiversity quantification (such as species richness or corrected weighted endemism), generation of least-cost paths and corridors among shared haplotypes, assessment of the significance of spatial randomizations, and enforcement of dispersal limitations of SDMs projected into future climates-to only name a few functions contained in SDMtoolbox 2.0. Lastly, dozens of generalized tools exists for batch processing and conversion of GIS data types or formats, which are broadly useful to any ArcMap user.
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Mistaking geography for biology: inferring processes from species distributions.
Warren, Dan L; Cardillo, Marcel; Rosauer, Dan F; Bolnick, Daniel I
2014-10-01
Over the past few decades, there has been a rapid proliferation of statistical methods that infer evolutionary and ecological processes from data on species distributions. These methods have led to considerable new insights, but they often fail to account for the effects of historical biogeography on present-day species distributions. Because the geography of speciation can lead to patterns of spatial and temporal autocorrelation in the distributions of species within a clade, this can result in misleading inferences about the importance of deterministic processes in generating spatial patterns of biodiversity. In this opinion article, we discuss ways in which patterns of species distributions driven by historical biogeography are often interpreted as evidence of particular evolutionary or ecological processes. We focus on three areas that are especially prone to such misinterpretations: community phylogenetics, environmental niche modelling, and analyses of beta diversity (compositional turnover of biodiversity). Crown Copyright © 2014. Published by Elsevier Ltd. All rights reserved.
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Staniczenko, Phillip P A; Sivasubramaniam, Prabu; Suttle, K Blake; Pearson, Richard G
2017-06-01
Macroecological models for predicting species distributions usually only include abiotic environmental conditions as explanatory variables, despite knowledge from community ecology that all species are linked to other species through biotic interactions. This disconnect is largely due to the different spatial scales considered by the two sub-disciplines: macroecologists study patterns at large extents and coarse resolutions, while community ecologists focus on small extents and fine resolutions. A general framework for including biotic interactions in macroecological models would help bridge this divide, as it would allow for rigorous testing of the role that biotic interactions play in determining species ranges. Here, we present an approach that combines species distribution models with Bayesian networks, which enables the direct and indirect effects of biotic interactions to be modelled as propagating conditional dependencies among species' presences. We show that including biotic interactions in distribution models for species from a California grassland community results in better range predictions across the western USA. This new approach will be important for improving estimates of species distributions and their dynamics under environmental change. © 2017 The Authors. Ecology Letters published by CNRS and John Wiley & Sons Ltd.
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Zhang, Keliang; Yao, Linjun; Meng, Jiasong; Tao, Jun
2018-09-01
Paeonia (Paeoniaceae), an economically important plant genus, includes many popular ornamentals and medicinal plant species used in traditional Chinese medicine. Little is known about the properties of the habitat distribution and the important eco-environmental factors shaping the suitability. Based on high-resolution environmental data for current and future climate scenarios, we modeled the present and future suitable habitat for P. delavayi and P. rockii by Maxent, evaluated the importance of environmental factors in shaping their distribution, and identified distribution shifts under climate change scenarios. The results showed that the moderate and high suitable areas for P. delavayi and P. rockii encompassed ca. 4.46×10 5 km 2 and 1.89×10 5 km 2 , respectively. Temperature seasonality and isothermality were identified as the most critical factors shaping P. delavayi distribution, and UVB-4 and annual precipitation were identified as the most critical for shaping P. rockii distribution. Under the scenario with a low concentration of greenhouse gas emissions (RCP2.6), the range of both species increased as global warming intensified; however, under the scenario with higher concentrations of emissions (RCP8.5), the suitable habitat range of P. delavayi decreased while P. rockii increased. Overall, our prediction showed that a shift in distribution of suitable habitat to higher elevations would gradually become more significant. The information gained from this study should provide a useful reference for implementing long-term conservation and management strategies for these species. Copyright © 2018. Published by Elsevier B.V.
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Directory of Open Access Journals (Sweden)
Armenteras Dolors
2010-12-01
Full Text Available The results in this study illustrate the methods of using the existing species' presentrecords and environmental data to produce a niche-based model based on Mahalanobis distances, and also to predict the distribution of a number of tree species in order to apply it on a national scale to a tropical country such as Colombia. The technique applied is based on the Mahalanobis distance, a generalised squared distance statistic. We used environmental data integrated into a GIS, and a georeferenced collection of localities of Palicourea angustifolia and Palicourea guianensis to produce and test the predictive models. We used record data for Warszewiczia coccinea to validate the model. The two Palicourea species show largely complementary potential ranges. P. angustifolia shows a clear Andean distribution with a presence in lower and upper mountain areas but not in the highlands or in the inter-Andean valleys. P. guianensis was predicted throughout most of the lowland areas of Colombia including lowland Amazonian forests, and most of the tropical savannas of Orinoquia. The model predicted an overlapping distribution of the two species of 93.9 km2. The Mahalanobian approach contributes to the development of biogeographically oriented modelling that makes the best use of the available data in data-scarce regions (such as most of the tropics. The technique provides key information about the environmental niche of the species being modelled, and allows comparisons between the species. The prediction achieved for the two species was considered satisfactory.
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Zhang, Ming-Gang; Slik, J. W. Ferry; Ma, Ke-Ping
2016-03-01
The millions of plant specimens that have been collected and stored in Chinese herbaria over the past ~110 years have recently been digitized and geo-referenced. Here we use this unique collection data set for species distribution modeling exercise aiming at mapping & explaining the botanical richness; delineating China’s phytogeographical regions and investigating the environmental drivers of the dissimilarity patterns. We modeled distributions of 6,828 woody plants using MaxEnt and remove the collection bias using null model. The continental China was divided into different phytogeographical regions based on the dissimilarity patterns. An ordination and Getis-Ord Gi* hotspot spatial statistics were used to analysis the environmental drivers of the dissimilarity patterns. We found that the annual precipitation and temperature stability were responsible for observed species diversity. The mechanisms causing dissimilarity pattern seems differ among biogeographical regions. The identified environmental drivers of the dissimilarity patterns for southeast, southwest, northwest and northeast are annual precipitation, topographic & temperature stability, water deficit and temperature instability, respectively. For effective conservation of China’s plant diversity, identifying the historical refuge and protection of high diversity areas in each of the identified floristic regions and their subdivisions will be essential.
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Bonnet-Lebrun, Anne-Sophie
2017-03-17
Community characteristics reflect past ecological and evolutionary dynamics. Here, we investigate whether it is possible to obtain realistically shaped modelled communities - i.e., with phylogenetic trees and species abundance distributions shaped similarly to typical empirical bird and mammal communities - from neutral community models. To test the effect of gene flow, we contrasted two spatially explicit individual-based neutral models: one with protracted speciation, delayed by gene flow, and one with point mutation speciation, unaffected by gene flow. The former produced more realistic communities (shape of phylogenetic tree and species-abundance distribution), consistent with gene flow being a key process in macro-evolutionary dynamics. Earlier models struggled to capture the empirically observed branching tempo in phylogenetic trees, as measured by the gamma statistic. We show that the low gamma values typical of empirical trees can be obtained in models with protracted speciation, in pre-equilibrium communities developing from an initially abundant and widespread species. This was even more so in communities sampled incompletely, particularly if the unknown species are the youngest. Overall, our results demonstrate that the characteristics of empirical communities that we have studied can, to a large extent, be explained through a purely neutral model under pre-equilibrium conditions. This article is protected by copyright. All rights reserved.
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Bonnet-Lebrun, Anne-Sophie; Manica, Andrea; Eriksson, Anders; Rodrigues, Ana S.L.
2017-01-01
Community characteristics reflect past ecological and evolutionary dynamics. Here, we investigate whether it is possible to obtain realistically shaped modelled communities - i.e., with phylogenetic trees and species abundance distributions shaped similarly to typical empirical bird and mammal communities - from neutral community models. To test the effect of gene flow, we contrasted two spatially explicit individual-based neutral models: one with protracted speciation, delayed by gene flow, and one with point mutation speciation, unaffected by gene flow. The former produced more realistic communities (shape of phylogenetic tree and species-abundance distribution), consistent with gene flow being a key process in macro-evolutionary dynamics. Earlier models struggled to capture the empirically observed branching tempo in phylogenetic trees, as measured by the gamma statistic. We show that the low gamma values typical of empirical trees can be obtained in models with protracted speciation, in pre-equilibrium communities developing from an initially abundant and widespread species. This was even more so in communities sampled incompletely, particularly if the unknown species are the youngest. Overall, our results demonstrate that the characteristics of empirical communities that we have studied can, to a large extent, be explained through a purely neutral model under pre-equilibrium conditions. This article is protected by copyright. All rights reserved.
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Directory of Open Access Journals (Sweden)
Rubén G Mateo
Full Text Available The definition of biogeographic regions provides a fundamental framework for a range of basic and applied questions in biogeography, evolutionary biology, systematics and conservation. Previous research suggested that environmental forcing results in highly congruent regionalization patterns across taxa, but that the size and number of regions depends on the dispersal ability of the taxa considered. We produced a biogeographic regionalization of European bryophytes and hypothesized that (1 regions defined for bryophytes would differ from those defined for other taxa due to the highly specific eco-physiology of the group and (2 their high dispersal ability would result in the resolution of few, large regions. Species distributions were recorded using 10,000 km2 MGRS pixels. Because of the lack of data across large portions of the area, species distribution models employing macroclimatic variables as predictors were used to determine the potential composition of empty pixels. K-means clustering analyses of the pixels based on their potential species composition were employed to define biogeographic regions. The optimal number of regions was determined by v-fold cross-validation and Moran's I statistic. The spatial congruence of the regions identified from their potential bryophyte assemblages with large-scale vegetation patterns is at odds with our primary hypothesis. This reinforces the notion that post-glacial migration patterns might have been much more similar in bryophytes and vascular plants than previously thought. The substantially lower optimal number of clusters and the absence of nested patterns within the main biogeographic regions, as compared to identical analyses in vascular plants, support our second hypothesis. The modelling approach implemented here is, however, based on many assumptions that are discussed but can only be tested when additional data on species distributions become available, highlighting the substantial
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Skowronek, Sandra; Van De Kerchove, Ruben; Rombouts, Bjorn; Aerts, Raf; Ewald, Michael; Warrie, Jens; Schiefer, Felix; Garzon-Lopez, Carol; Hattab, Tarek; Honnay, Olivier; Lenoir, Jonathan; Rocchini, Duccio; Schmidtlein, Sebastian; Somers, Ben; Feilhauer, Hannes
2018-06-01
Remote sensing is a promising tool for detecting invasive alien plant species. Mapping and monitoring those species requires accurate detection. So far, most studies relied on models that are locally calibrated and validated against available field data. Consequently, detecting invasive alien species at new study areas requires the acquisition of additional field data which can be expensive and time-consuming. Model transfer might thus provide a viable alternative. Here, we mapped the distribution of the invasive alien bryophyte Campylopus introflexus to i) assess the feasibility of spatially transferring locally calibrated models for species detection between four different heathland areas in Germany and Belgium and ii) test the potential of combining calibration data from different sites in one species distribution model (SDM). In a first step, four different SDMs were locally calibrated and validated by combining field data and airborne imaging spectroscopy data with a spatial resolution ranging from 1.8 m to 4 m and a spectral resolution of about 10 nm (244 bands). A one-class classifier, Maxent, which is based on the comparison of probability densities, was used to generate all SDMs. In a second step, each model was transferred to the three other study areas and the performance of the models for predicting C. introflexus occurrences was assessed. Finally, models combining calibration data from three study areas were built and tested on the remaining fourth site. In this step, different combinations of Maxent modelling parameters were tested. For the local models, the area under the curve for a test dataset (test AUC) was between 0.57-0.78, while the test AUC for the single transfer models ranged between 0.45-0.89. For the combined models the test AUC was between 0.54-0.9. The success of transferring models calibrated in one site to another site highly depended on the respective study site; the combined models provided higher test AUC values than the locally
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Directory of Open Access Journals (Sweden)
Loïc ePellissier
2013-12-01
Full Text Available The distribution of plants along environmental gradients is constrained by abiotic and biotic factors. Cumulative evidence attests of the impact of abiotic factors on plant distributions, but only few studies discuss the role of belowground communities. Soil fungi, in particular, are thought to play an important role in how plant species assemble locally into communities. We first review existing evidence, and then test the effect of the number of soil fungal operational taxonomic units (OTUs on plant species distributions using a recently collected dataset of plant and metagenomic information on soil fungi in the Western Swiss Alps. Using species distribution models, we investigated whether the distribution of individual plant species is correlated to the number of OTUs of two important soil fungal classes known to interact with plants: the Glomeromycetes, that are obligatory symbionts of plants, and the Agaricomycetes, that may be facultative plant symbionts, pathogens, or wood decayers. We show that including the fungal richness information in the models of plant species distributions improves predictive accuracy. Number of fungal OTUs is especially correlated to the distribution of high elevation plant species. We suggest that high elevation soil show greater variation in fungal assemblages that may in turn impact plant turnover among communities. We finally discuss how to move beyond correlative analyses, through the design of field experiments manipulating plant and fungal communities along environmental gradients.
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Dempsey, Steven J; Gese, Eric M; Kluever, Bryan M; Lonsinger, Robert C; Waits, Lisette P
2015-01-01
Development and evaluation of noninvasive methods for monitoring species distribution and abundance is a growing area of ecological research. While noninvasive methods have the advantage of reduced risk of negative factors associated with capture, comparisons to methods using more traditional invasive sampling is lacking. Historically kit foxes (Vulpes macrotis) occupied the desert and semi-arid regions of southwestern North America. Once the most abundant carnivore in the Great Basin Desert of Utah, the species is now considered rare. In recent decades, attempts have been made to model the environmental variables influencing kit fox distribution. Using noninvasive scat deposition surveys for determination of kit fox presence, we modeled resource selection functions to predict kit fox distribution using three popular techniques (Maxent, fixed-effects, and mixed-effects generalized linear models) and compared these with similar models developed from invasive sampling (telemetry locations from radio-collared foxes). Resource selection functions were developed using a combination of landscape variables including elevation, slope, aspect, vegetation height, and soil type. All models were tested against subsequent scat collections as a method of model validation. We demonstrate the importance of comparing multiple model types for development of resource selection functions used to predict a species distribution, and evaluating the importance of environmental variables on species distribution. All models we examined showed a large effect of elevation on kit fox presence, followed by slope and vegetation height. However, the invasive sampling method (i.e., radio-telemetry) appeared to be better at determining resource selection, and therefore may be more robust in predicting kit fox distribution. In contrast, the distribution maps created from the noninvasive sampling (i.e., scat transects) were significantly different than the invasive method, thus scat transects may be
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Elizabeth A. Freeman; Gretchen G. Moisen; Tracy S. Frescino
2012-01-01
Random Forests is frequently used to model species distributions over large geographic areas. Complications arise when data used to train the models have been collected in stratified designs that involve different sampling intensity per stratum. The modeling process is further complicated if some of the target species are relatively rare on the landscape leading to an...
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Directory of Open Access Journals (Sweden)
Jason L. Brown
2017-12-01
Full Text Available SDMtoolbox 2.0 is a software package for spatial studies of ecology, evolution, and genetics. The release of SDMtoolbox 2.0 allows researchers to use the most current ArcGIS software and MaxEnt software, and reduces the amount of time that would be spent developing common solutions. The central aim of this software is to automate complicated and repetitive spatial analyses in an intuitive graphical user interface. One core tenant facilitates careful parameterization of species distribution models (SDMs to maximize each model’s discriminatory ability and minimize overfitting. This includes carefully processing of occurrence data, environmental data, and model parameterization. This program directly interfaces with MaxEnt, one of the most powerful and widely used species distribution modeling software programs, although SDMtoolbox 2.0 is not limited to species distribution modeling or restricted to modeling in MaxEnt. Many of the SDM pre- and post-processing tools have ‘universal’ analogs for use with any modeling software. The current version contains a total of 79 scripts that harness the power of ArcGIS for macroecology, landscape genetics, and evolutionary studies. For example, these tools allow for biodiversity quantification (such as species richness or corrected weighted endemism, generation of least-cost paths and corridors among shared haplotypes, assessment of the significance of spatial randomizations, and enforcement of dispersal limitations of SDMs projected into future climates—to only name a few functions contained in SDMtoolbox 2.0. Lastly, dozens of generalized tools exists for batch processing and conversion of GIS data types or formats, which are broadly useful to any ArcMap user.
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Angelieri, Cintia Camila Silva; Adams-Hosking, Christine; Ferraz, Katia Maria Paschoaletto Micchi de Barros; de Souza, Marcelo Pereira; McAlpine, Clive Alexander
2016-01-01
A mosaic of intact native and human-modified vegetation use can provide important habitat for top predators such as the puma (Puma concolor), avoiding negative effects on other species and ecological processes due to cascade trophic interactions. This study investigates the effects of restoration scenarios on the puma's habitat suitability in the most developed Brazilian region (São Paulo State). Species Distribution Models incorporating restoration scenarios were developed using the species' occurrence information to (1) map habitat suitability of pumas in São Paulo State, Southeast, Brazil; (2) test the relative contribution of environmental variables ecologically relevant to the species habitat suitability and (3) project the predicted habitat suitability to future native vegetation restoration scenarios. The Maximum Entropy algorithm was used (Test AUC of 0.84 ± 0.0228) based on seven environmental non-correlated variables and non-autocorrelated presence-only records (n = 342). The percentage of native vegetation (positive influence), elevation (positive influence) and density of roads (negative influence) were considered the most important environmental variables to the model. Model projections to restoration scenarios reflected the high positive relationship between pumas and native vegetation. These projections identified new high suitability areas for pumas (probability of presence >0.5) in highly deforested regions. High suitability areas were increased from 5.3% to 8.5% of the total State extension when the landscapes were restored for ≥ the minimum native vegetation cover rule (20%) established by the Brazilian Forest Code in private lands. This study highlights the importance of a landscape planning approach to improve the conservation outlook for pumas and other species, including not only the establishment and management of protected areas, but also the habitat restoration on private lands. Importantly, the results may inform environmental
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ESUSA: US endangered species distribution file
Energy Technology Data Exchange (ETDEWEB)
Nagy, J.; Calef, C.E.
1979-10-01
This report describes a file containing distribution data on endangered species of the United States of Federal concern pursuant to the Endangered Species Act of 1973. Included for each species are (a) the common name, (b) the scientific name, (c) the family, (d) the group (mammal, bird, etc.), (e) Fish and Wildlife Service (FWS) listing and recovery priorities, (f) the Federal legal status, (g) the geographic distribution by counties or islands, (h) Federal Register citations and (i) the sources of the information on distribution of the species. Status types are endangered, threatened, proposed, formally under review, candidate, deleted, and rejected. Distribution is by Federal Information Processing Standard (FIPS) county code and is of four types: designated critical habitat, present range, potential range, and historic range.
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Fajardo, Javier; Lessmann, Janeth; Bonaccorso, Elisa; Devenish, Christian; Muñoz, Jesús
2014-01-01
Conservation planning is crucial for megadiverse countries where biodiversity is coupled with incomplete reserve systems and limited resources to invest in conservation. Using Peru as an example of a megadiverse country, we asked whether the national system of protected areas satisfies biodiversity conservation needs. Further, to complement the existing reserve system, we identified and prioritized potential conservation areas using a combination of species distribution modeling, conservation planning and connectivity analysis. Based on a set of 2,869 species, including mammals, birds, amphibians, reptiles, butterflies, and plants, we used species distribution models to represent species' geographic ranges to reduce the effect of biased sampling and partial knowledge about species' distributions. A site-selection algorithm then searched for efficient and complementary proposals, based on the above distributions, for a more representative system of protection. Finally, we incorporated connectivity among areas in an innovative post-hoc analysis to prioritize those areas maximizing connectivity within the system. Our results highlight severe conservation gaps in the Coastal and Andean regions, and we propose several areas, which are not currently covered by the existing network of protected areas. Our approach helps to find areas that contribute to creating a more representative, connected and efficient network. PMID:25479411
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Predicting the geographical distribution of two invasive termite species from occurrence data.
Tonini, Francesco; Divino, Fabio; Lasinio, Giovanna Jona; Hochmair, Hartwig H; Scheffrahn, Rudolf H
2014-10-01
Predicting the potential habitat of species under both current and future climate change scenarios is crucial for monitoring invasive species and understanding a species' response to different environmental conditions. Frequently, the only data available on a species is the location of its occurrence (presence-only data). Using occurrence records only, two models were used to predict the geographical distribution of two destructive invasive termite species, Coptotermes gestroi (Wasmann) and Coptotermes formosanus Shiraki. The first model uses a Bayesian linear logistic regression approach adjusted for presence-only data while the second one is the widely used maximum entropy approach (Maxent). Results show that the predicted distributions of both C. gestroi and C. formosanus are strongly linked to urban development. The impact of future scenarios such as climate warming and population growth on the biotic distribution of both termite species was also assessed. Future climate warming seems to affect their projected probability of presence to a lesser extent than population growth. The Bayesian logistic approach outperformed Maxent consistently in all models according to evaluation criteria such as model sensitivity and ecological realism. The importance of further studies for an explicit treatment of residual spatial autocorrelation and a more comprehensive comparison between both statistical approaches is suggested.
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Luo, Shao-Ming; Chen, Ping; He, Xiao; Guo, Wei; Li, Bailian
2018-01-01
There are a few common species and many rare species in a biological community or a multi-species collection in given space and time. This hollow distribution curve is called species abundance distribution (SAD). Few studies have examined the patterns and dynamics of SADs during the succession of forest communities by model selection. This study explored whether the communities in different successional stages followed different SAD models and whether there existed a best SAD model to reveal their intrinsic quantitative features of structure and dynamics in succession. The abundance (the number of individuals) of each vascular plant was surveyed by quadrat sampling method from the tree, shrub and herb layers in two typical communities (i.e., the evergreen needle- and broad-leaved mixed forest and the monsoon evergreen broad-leaved forest) in southern subtropical Dinghushan Biosphere Reserve, South China. The sites of two forest communities in different successional stages are both 1 ha in area. We collected seven widely representative SAD models with obviously different function forms and transformed them into the same octave (log2) scale. These models are simultaneously confronted with eight datasets from four layers of two communities, and their goodness-of-fits to the data were evaluated by the chi-squared test, the adjusted coefficient of determination and the information criteria. The results indicated that: (1) the logCauchy model followed all the datasets and was the best among seven models; (2) the fitness of each model to the data was not directly related to the successional stage of forest community; (3) according to the SAD curves predicted by the best model (i.e., the logCauchy), the proportion of rare species decreased but that of common ones increased in the upper layers with succession, while the reverse was true in the lower layers; and (4) the difference of the SADs increased between the upper and the lower layers with succession. We concluded that
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Germaine, Stephen S.; Ignizio, Drew; Keinath, Doug; Copeland, Holly
2014-01-01
Species distribution models are an important component of natural-resource conservation planning efforts. Independent, external evaluation of their accuracy is important before they are used in management contexts. We evaluated the classification accuracy of two species distribution models designed to predict the distribution of pygmy rabbit Brachylagus idahoensis habitat in southwestern Wyoming, USA. The Nature Conservancy model was deductive and based on published information and expert opinion, whereas the Wyoming Natural Diversity Database model was statistically derived using historical observation data. We randomly selected 187 evaluation survey points throughout southwestern Wyoming in areas predicted to be habitat and areas predicted to be nonhabitat for each model. The Nature Conservancy model correctly classified 39 of 77 (50.6%) unoccupied evaluation plots and 65 of 88 (73.9%) occupied plots for an overall classification success of 63.3%. The Wyoming Natural Diversity Database model correctly classified 53 of 95 (55.8%) unoccupied plots and 59 of 88 (67.0%) occupied plots for an overall classification success of 61.2%. Based on 95% asymptotic confidence intervals, classification success of the two models did not differ. The models jointly classified 10.8% of the area as habitat and 47.4% of the area as nonhabitat, but were discordant in classifying the remaining 41.9% of the area. To evaluate how anthropogenic development affected model predictive success, we surveyed 120 additional plots among three density levels of gas-field road networks. Classification success declined sharply for both models as road-density level increased beyond 5 km of roads per km-squared area. Both models were more effective at predicting habitat than nonhabitat in relatively undeveloped areas, and neither was effective at accounting for the effects of gas-energy-development road networks. Resource managers who wish to know the amount of pygmy rabbit habitat present in an
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Beauregard, Frieda; de Blois, Sylvie
2014-01-01
Both climatic and edaphic conditions determine plant distribution, however many species distribution models do not include edaphic variables especially over large geographical extent. Using an exceptional database of vegetation plots (n = 4839) covering an extent of ∼55,000 km2, we tested whether the inclusion of fine scale edaphic variables would improve model predictions of plant distribution compared to models using only climate predictors. We also tested how well these edaphic variables could predict distribution on their own, to evaluate the assumption that at large extents, distribution is governed largely by climate. We also hypothesized that the relative contribution of edaphic and climatic data would vary among species depending on their growth forms and biogeographical attributes within the study area. We modelled 128 native plant species from diverse taxa using four statistical model types and three sets of abiotic predictors: climate, edaphic, and edaphic-climate. Model predictive accuracy and variable importance were compared among these models and for species' characteristics describing growth form, range boundaries within the study area, and prevalence. For many species both the climate-only and edaphic-only models performed well, however the edaphic-climate models generally performed best. The three sets of predictors differed in the spatial information provided about habitat suitability, with climate models able to distinguish range edges, but edaphic models able to better distinguish within-range variation. Model predictive accuracy was generally lower for species without a range boundary within the study area and for common species, but these effects were buffered by including both edaphic and climatic predictors. The relative importance of edaphic and climatic variables varied with growth forms, with trees being more related to climate whereas lower growth forms were more related to edaphic conditions. Our study identifies the potential
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High-resolution pattern of mangrove species distribution is controlled by surface elevation
Leong, Rick C.; Friess, Daniel A.; Crase, Beth; Lee, Wei Kit; Webb, Edward L.
2018-03-01
Mangrove vegetation species respond to multiple environmental gradients, and an enhanced understanding of how mangrove species are distributed across these gradients will facilitate conservation and management. Many environmental gradients correlate with tidal inundation; however small-scale inundation patterns resulting from microtopographical changes are difficult to capture empirically. In contrast, surface elevation is often a suitable, measurable and cost-effective proxy for inundation. This study investigated the relationships between species distribution and surface elevation in a mangrove forest in northwest Singapore. Through high-resolution land surveying, we developed a digital elevation model (DEM) and conducted a comprehensive survey of 4380 trees with a stem diameter ≥ 5 cm. A total of 15 species were encountered, and elevation envelopes were generated for 12. Species envelopes were distributed along an elevation continuum, with most species overlapping within the continuum. Spatial autocorrelation (SAC) was present for nine of the 15 species, and when taken into account, species ordering was modified across the elevation continuum. The presence of SAC strongly reinforces the need for research to control for SAC: classical spatial description of mangrove species distribution should be revised to account for ecological factors. This study suggests that (1) surface elevation applies strong controls on species distribution and (2) most mangroves at our study site have similar physiological tolerances.
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Biotic and abiotic variables show little redundancy in explaining tree species distributions
DEFF Research Database (Denmark)
Meier, Elaine S.; Kienast, Felix; Pearman, Peter B.
2010-01-01
Abiotic factors such as climate and soil determine the species fundamental niche, which is further constrained by biotic interactions such as interspecific competition. To parameterize this realized niche, species distribution models (SDMs) most often relate species occurrence data to abiotic var...
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Working toward integrated models of alpine plant distribution.
Carlson, Bradley Z; Randin, Christophe F; Boulangeat, Isabelle; Lavergne, Sébastien; Thuiller, Wilfried; Choler, Philippe
2013-10-01
Species distribution models (SDMs) have been frequently employed to forecast the response of alpine plants to global changes. Efforts to model alpine plant distribution have thus far been primarily based on a correlative approach, in which ecological processes are implicitly addressed through a statistical relationship between observed species occurrences and environmental predictors. Recent evidence, however, highlights the shortcomings of correlative SDMs, especially in alpine landscapes where plant species tend to be decoupled from atmospheric conditions in micro-topographic habitats and are particularly exposed to geomorphic disturbances. While alpine plants respond to the same limiting factors as plants found at lower elevations, alpine environments impose a particular set of scale-dependent and hierarchical drivers that shape the realized niche of species and that require explicit consideration in a modelling context. Several recent studies in the European Alps have successfully integrated both correlative and process-based elements into distribution models of alpine plants, but for the time being a single integrative modelling framework that includes all key drivers remains elusive. As a first step in working toward a comprehensive integrated model applicable to alpine plant communities, we propose a conceptual framework that structures the primary mechanisms affecting alpine plant distributions. We group processes into four categories, including multi-scalar abiotic drivers, gradient dependent species interactions, dispersal and spatial-temporal plant responses to disturbance. Finally, we propose a methodological framework aimed at developing an integrated model to better predict alpine plant distribution.
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Citizen science contributes to our knowledge of invasive plant species distributions
Crall, Alycia W.; Jarnevich, Catherine S.; Young, Nicholas E.; Panke, Brendon; Renz, Mark; Stohlgren, Thomas
2015-01-01
Citizen science is commonly cited as an effective approach to expand the scale of invasive species data collection and monitoring. However, researchers often hesitate to use these data due to concerns over data quality. In light of recent research on the quality of data collected by volunteers, we aimed to demonstrate the extent to which citizen science data can increase sampling coverage, fill gaps in species distributions, and improve habitat suitability models compared to professionally generated data sets used in isolation. We combined data sets from professionals and volunteers for five invasive plant species (Alliaria petiolata, Berberis thunbergii, Cirsium palustre, Pastinaca sativa, Polygonum cuspidatum) in portions of Wisconsin. Volunteers sampled counties not sampled by professionals for three of the five species. Volunteers also added presence locations within counties not included in professional data sets, especially in southern portions of the state where professional monitoring activities had been minimal. Volunteers made a significant contribution to the known distribution, environmental gradients sampled, and the habitat suitability of P. cuspidatum. Models generated with professional data sets for the other four species performed reasonably well according to AUC values (>0.76). The addition of volunteer data did not greatly change model performance (AUC > 0.79) but did change the suitability surface generated by the models, making them more realistic. Our findings underscore the need to merge data from multiple sources to improve knowledge of current species distributions, and to predict their movement under present and future environmental conditions. The efficiency and success of these approaches require that monitoring efforts involve multiple stakeholders in continuous collaboration via established monitoring networks.
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Allman, Elizabeth S; Degnan, James H; Rhodes, John A
2011-06-01
Gene trees are evolutionary trees representing the ancestry of genes sampled from multiple populations. Species trees represent populations of individuals-each with many genes-splitting into new populations or species. The coalescent process, which models ancestry of gene copies within populations, is often used to model the probability distribution of gene trees given a fixed species tree. This multispecies coalescent model provides a framework for phylogeneticists to infer species trees from gene trees using maximum likelihood or Bayesian approaches. Because the coalescent models a branching process over time, all trees are typically assumed to be rooted in this setting. Often, however, gene trees inferred by traditional phylogenetic methods are unrooted. We investigate probabilities of unrooted gene trees under the multispecies coalescent model. We show that when there are four species with one gene sampled per species, the distribution of unrooted gene tree topologies identifies the unrooted species tree topology and some, but not all, information in the species tree edges (branch lengths). The location of the root on the species tree is not identifiable in this situation. However, for 5 or more species with one gene sampled per species, we show that the distribution of unrooted gene tree topologies identifies the rooted species tree topology and all its internal branch lengths. The length of any pendant branch leading to a leaf of the species tree is also identifiable for any species from which more than one gene is sampled.
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What are the most crucial soil factors for predicting the distribution of alpine plant species?
Buri, A.; Pinto-Figueroa, E.; Yashiro, E.; Guisan, A.
2017-12-01
Nowadays the use of species distribution models (SDM) is common to predict in space and time the distribution of organisms living in the critical zone. The realized environmental niche concept behind the development of SDM imply that many environmental factors must be accounted for simultaneously to predict species distributions. Climatic and topographic factors are often primary included, whereas soil factors are frequently neglected, mainly due to the paucity of soil information available spatially and temporally. Furthermore, among existing studies, most included soil pH only, or few other soil parameters. In this study we aimed at identifying what are the most crucial soil factors for explaining alpine plant distributions and, among those identified, which ones further improve the predictive power of plant SDMs. To test the relative importance of the soil factors, we performed plant SDMs using as predictors 52 measured soil properties of various types such as organic/inorganic compounds, chemical/physical properties, water related variables, mineral composition or grain size distribution. We added them separately to a standard set of topo-climatic predictors (temperature, slope, solar radiation and topographic position). We used ensemble forecasting techniques combining together several predictive algorithms to model the distribution of 116 plant species over 250 sites in the Swiss Alps. We recorded the variable importance for each model and compared the quality of the models including different soil proprieties (one at a time) as predictors to models having only topo-climatic variables as predictors. Results show that 46% of the soil proprieties tested become the second most important variable, after air temperature, to explain spatial distribution of alpine plants species. Moreover, we also assessed that addition of certain soil factors, such as bulk soil water density, could improve over 80% the quality of some plant species models. We confirm that soil p
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Directory of Open Access Journals (Sweden)
Giovanni Rapacciuolo
Full Text Available Conservation planners often wish to predict how species distributions will change in response to environmental changes. Species distribution models (SDMs are the primary tool for making such predictions. Many methods are widely used; however, they all make simplifying assumptions, and predictions can therefore be subject to high uncertainty. With global change well underway, field records of observed range shifts are increasingly being used for testing SDM transferability. We used an unprecedented distribution dataset documenting recent range changes of British vascular plants, birds, and butterflies to test whether correlative SDMs based on climate change provide useful approximations of potential distribution shifts. We modelled past species distributions from climate using nine single techniques and a consensus approach, and projected the geographical extent of these models to a more recent time period based on climate change; we then compared model predictions with recent observed distributions in order to estimate the temporal transferability and prediction accuracy of our models. We also evaluated the relative effect of methodological and taxonomic variation on the performance of SDMs. Models showed good transferability in time when assessed using widespread metrics of accuracy. However, models had low accuracy to predict where occupancy status changed between time periods, especially for declining species. Model performance varied greatly among species within major taxa, but there was also considerable variation among modelling frameworks. Past climatic associations of British species distributions retain a high explanatory power when transferred to recent time--due to their accuracy to predict large areas retained by species--but fail to capture relevant predictors of change. We strongly emphasize the need for caution when using SDMs to predict shifts in species distributions: high explanatory power on temporally-independent records
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Wiegand, Thorsten; Lehmann, Sebastian; Huth, Andreas; Fortin, Marie‐Josée
2016-01-01
Abstract Aim It has been recently suggested that different ‘unified theories of biodiversity and biogeography’ can be characterized by three common ‘minimal sufficient rules’: (1) species abundance distributions follow a hollow curve, (2) species show intraspecific aggregation, and (3) species are independently placed with respect to other species. Here, we translate these qualitative rules into a quantitative framework and assess if these minimal rules are indeed sufficient to predict multiple macroecological biodiversity patterns simultaneously. Location Tropical forest plots in Barro Colorado Island (BCI), Panama, and in Sinharaja, Sri Lanka. Methods We assess the predictive power of the three rules using dynamic and spatial simulation models in combination with census data from the two forest plots. We use two different versions of the model: (1) a neutral model and (2) an extended model that allowed for species differences in dispersal distances. In a first step we derive model parameterizations that correctly represent the three minimal rules (i.e. the model quantitatively matches the observed species abundance distribution and the distribution of intraspecific aggregation). In a second step we applied the parameterized models to predict four additional spatial biodiversity patterns. Results Species‐specific dispersal was needed to quantitatively fulfil the three minimal rules. The model with species‐specific dispersal correctly predicted the species–area relationship, but failed to predict the distance decay, the relationship between species abundances and aggregations, and the distribution of a spatial co‐occurrence index of all abundant species pairs. These results were consistent over the two forest plots. Main conclusions The three ‘minimal sufficient’ rules only provide an incomplete approximation of the stochastic spatial geometry of biodiversity in tropical forests. The assumption of independent interspecific placements is most
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Directory of Open Access Journals (Sweden)
Guisan Antoine
2009-04-01
Full Text Available Abstract Background Multiple logistic regression is precluded from many practical applications in ecology that aim to predict the geographic distributions of species because it requires absence data, which are rarely available or are unreliable. In order to use multiple logistic regression, many studies have simulated "pseudo-absences" through a number of strategies, but it is unknown how the choice of strategy influences models and their geographic predictions of species. In this paper we evaluate the effect of several prevailing pseudo-absence strategies on the predictions of the geographic distribution of a virtual species whose "true" distribution and relationship to three environmental predictors was predefined. We evaluated the effect of using a real absences b pseudo-absences selected randomly from the background and c two-step approaches: pseudo-absences selected from low suitability areas predicted by either Ecological Niche Factor Analysis: (ENFA or BIOCLIM. We compared how the choice of pseudo-absence strategy affected model fit, predictive power, and information-theoretic model selection results. Results Models built with true absences had the best predictive power, best discriminatory power, and the "true" model (the one that contained the correct predictors was supported by the data according to AIC, as expected. Models based on random pseudo-absences had among the lowest fit, but yielded the second highest AUC value (0.97, and the "true" model was also supported by the data. Models based on two-step approaches had intermediate fit, the lowest predictive power, and the "true" model was not supported by the data. Conclusion If ecologists wish to build parsimonious GLM models that will allow them to make robust predictions, a reasonable approach is to use a large number of randomly selected pseudo-absences, and perform model selection based on an information theoretic approach. However, the resulting models can be expected to have
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Directory of Open Access Journals (Sweden)
Irene D. Alabia
2016-11-01
Full Text Available The understanding of the spatio-temporal distributions of the species habitat in the marine environment is central to effectual resource management and conservation. Here, we examined the potential habitat distributions of Japanese common squid (Todarodes pacificus in the Sea of Japan during a four-year period. The seasonal patterns of preferential habitat were inferred from species distribution models, built using squid occurrences detected from night-time visible images and remotely-sensed environmental factors. The predicted squid habitat (i.e., areas with high habitat suitability revealed strong seasonal variability, characterized by a reduction of potential habitat, confined off of the southern part of the basin during the winter–spring period (December–May. Apparent expansion of preferential habitat occurred during summer–autumn months (June–November, concurrent with the formation of highly suitable habitat patches in certain regions of the Sea of Japan. These habitat distribution patterns were in response to changes in oceanographic conditions and synchronous with seasonal migration of squid. Moreover, the most important variables regulating the spatio-temporal patterns of suitable habitat were sea surface temperature, depth, sea surface height anomaly, and eddy kinetic energy. These variables could affect the habitat distributions through their impacts on growth and survival of squid, local nutrient transport, and the availability of favorable spawning and feeding grounds.
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Directory of Open Access Journals (Sweden)
Frieda Beauregard
Full Text Available Both climatic and edaphic conditions determine plant distribution, however many species distribution models do not include edaphic variables especially over large geographical extent. Using an exceptional database of vegetation plots (n = 4839 covering an extent of ∼55,000 km2, we tested whether the inclusion of fine scale edaphic variables would improve model predictions of plant distribution compared to models using only climate predictors. We also tested how well these edaphic variables could predict distribution on their own, to evaluate the assumption that at large extents, distribution is governed largely by climate. We also hypothesized that the relative contribution of edaphic and climatic data would vary among species depending on their growth forms and biogeographical attributes within the study area. We modelled 128 native plant species from diverse taxa using four statistical model types and three sets of abiotic predictors: climate, edaphic, and edaphic-climate. Model predictive accuracy and variable importance were compared among these models and for species' characteristics describing growth form, range boundaries within the study area, and prevalence. For many species both the climate-only and edaphic-only models performed well, however the edaphic-climate models generally performed best. The three sets of predictors differed in the spatial information provided about habitat suitability, with climate models able to distinguish range edges, but edaphic models able to better distinguish within-range variation. Model predictive accuracy was generally lower for species without a range boundary within the study area and for common species, but these effects were buffered by including both edaphic and climatic predictors. The relative importance of edaphic and climatic variables varied with growth forms, with trees being more related to climate whereas lower growth forms were more related to edaphic conditions. Our study
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An exactly solvable coarse-grained model for species diversity
Suweis, Samir; Rinaldo, Andrea; Maritan, Amos
2012-07-01
We present novel analytical results concerning ecosystem species diversity that stem from a proposed coarse-grained neutral model based on birth-death processes. The relevance of the problem lies in the urgency for understanding and synthesizing both theoretical results from ecological neutral theory and empirical evidence on species diversity preservation. The neutral model of biodiversity deals with ecosystems at the same trophic level, where per capita vital rates are assumed to be species independent. Closed-form analytical solutions for the neutral theory are obtained within a coarse-grained model, where the only input is the species persistence time distribution. Our results pertain to: the probability distribution function of the number of species in the ecosystem, both in transient and in stationary states; the n-point connected time correlation function; and the survival probability, defined as the distribution of time spans to local extinction for a species randomly sampled from the community. Analytical predictions are also tested on empirical data from an estuarine fish ecosystem. We find that emerging properties of the ecosystem are very robust and do not depend on specific details of the model, with implications for biodiversity and conservation biology.
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An exactly solvable coarse-grained model for species diversity
International Nuclear Information System (INIS)
Suweis, Samir; Maritan, Amos; Rinaldo, Andrea
2012-01-01
We present novel analytical results concerning ecosystem species diversity that stem from a proposed coarse-grained neutral model based on birth–death processes. The relevance of the problem lies in the urgency for understanding and synthesizing both theoretical results from ecological neutral theory and empirical evidence on species diversity preservation. The neutral model of biodiversity deals with ecosystems at the same trophic level, where per capita vital rates are assumed to be species independent. Closed-form analytical solutions for the neutral theory are obtained within a coarse-grained model, where the only input is the species persistence time distribution. Our results pertain to: the probability distribution function of the number of species in the ecosystem, both in transient and in stationary states; the n-point connected time correlation function; and the survival probability, defined as the distribution of time spans to local extinction for a species randomly sampled from the community. Analytical predictions are also tested on empirical data from an estuarine fish ecosystem. We find that emerging properties of the ecosystem are very robust and do not depend on specific details of the model, with implications for biodiversity and conservation biology. (paper)
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Huang, Qiongyu; Sauer, John R.; Swatantran, Anu; Dubayah, Ralph
2016-01-01
Drastic shifts in species distributions are a cause of concern for ecologists. Such shifts pose great threat to biodiversity especially under unprecedented anthropogenic and natural disturbances. Many studies have documented recent shifts in species distributions. However, most of these studies are limited to regional scales, and do not consider the abundance structure within species ranges. Developing methods to detect systematic changes in species distributions over their full ranges is critical for understanding the impact of changing environments and for successful conservation planning. Here, we demonstrate a centroid model for range-wide analysis of distribution shifts using the North American Breeding Bird Survey. The centroid model is based on a hierarchical Bayesian framework which models population change within physiographic strata while accounting for several factors affecting species detectability. Yearly abundance-weighted range centroids are estimated. As case studies, we derive annual centroids for the Carolina wren and house finch in their ranges in the U.S. We further evaluate the first-difference correlation between species’ centroid movement and changes in winter severity, total population abundance. We also examined associations of change in centroids from sub-ranges. Change in full-range centroid movements of Carolina wren significantly correlate with snow cover days (r = −0.58). For both species, the full-range centroid shifts also have strong correlation with total abundance (r = 0.65, and 0.51 respectively). The movements of the full-range centroids of the two species are correlated strongly (up to r = 0.76) with that of the sub-ranges with more drastic population changes. Our study demonstrates the usefulness of centroids for analyzing distribution changes in a two-dimensional spatial context. Particularly it highlights applications that associate the centroid with factors such as environmental stressors, population characteristics
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Boiffin, Juliette; Badeau, Vincent; Bréda, Nathalie
2017-03-01
Species distribution models (SDMs), which statistically relate species occurrence to climatic variables, are widely used to identify areas suitable for species growth under future climates and to plan for assisted migration. When SDMs are projected across times or spaces, it is assumed that species climatic requirements remain constant. However, empirical evidence supporting this assumption is rare, and SDM predictions could be biased. Historical human-aided movements of tree species can shed light on the reliability of SDM predictions in planning for assisted migration. We used Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco), a North American conifer introduced into Europe during the mid-19th century, as a case-study to test niche conservatism. We combined transcontinental data sets of Douglas-fir occurrence and climatic predictors to compare the realized niches between native and introduced ranges. We calibrated a SDM in the native range and compared areas predicted to be climatically suitable with observed presences. The realized niches in the native and introduced ranges showed very limited overlap. The SDM calibrated in North America had very high predictive power in the native range, but failed to predict climatic suitability in Europe where Douglas-fir grows in climates that have no analogue in the native range. We review the ecological mechanisms and silvicultural practices that can trigger such shifts in realized niches. Retrospective analysis of tree species introduction revealed that the assumption of niche conservatism is erroneous. As a result, distributions predicted by SDM are importantly biased. There is a high risk that assisted migration programs may be misdirected and target inadequate species or introduction zones. © 2016 by the Ecological Society of America.
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Miller, Brian W.; Frid, Leonardo; Chang, Tony; Piekielek, N. B.; Hansen, Andrew J.; Morisette, Jeffrey T.
2015-01-01
State-and-transition simulation models (STSMs) are known for their ability to explore the combined effects of multiple disturbances, ecological dynamics, and management actions on vegetation. However, integrating the additional impacts of climate change into STSMs remains a challenge. We address this challenge by combining an STSM with species distribution modeling (SDM). SDMs estimate the probability of occurrence of a given species based on observed presence and absence locations as well as environmental and climatic covariates. Thus, in order to account for changes in habitat suitability due to climate change, we used SDM to generate continuous surfaces of species occurrence probabilities. These data were imported into ST-Sim, an STSM platform, where they dictated the probability of each cell transitioning between alternate potential vegetation types at each time step. The STSM was parameterized to capture additional processes of vegetation growth and disturbance that are relevant to a keystone species in the Greater Yellowstone Ecosystem—whitebark pine (Pinus albicaulis). We compared historical model runs against historical observations of whitebark pine and a key disturbance agent (mountain pine beetle, Dendroctonus ponderosae), and then projected the simulation into the future. Using this combination of correlative and stochastic simulation models, we were able to reproduce historical observations and identify key data gaps. Results indicated that SDMs and STSMs are complementary tools, and combining them is an effective way to account for the anticipated impacts of climate change, biotic interactions, and disturbances, while also allowing for the exploration of management options.
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Directory of Open Access Journals (Sweden)
Marwa Waseem Halmy
2015-12-01
Full Text Available The application of species distribution modeling in deserts is a useful tool for mapping species and assessing the impact of human induced changes on individual species. Such applications are still rare, and this may be attributed to the fact that much of the arid lands and deserts around the world are located in inaccessible areas. Few studies have conducted spatially explicit modeling of plant species distribution in Egypt. The random forest modeling approach was applied to climatic and land-surface parameters to predict the distribution of ten important plant species in an arid landscape in the northwestern coastal desert of Egypt. The impact of changes in land use and climate on the distribution of the plant species was assessed. The results indicate that the changes in land use in the area have resulted in habitat loss for all the modeled species. Projected future changes in land use reveals that all the modeled species will continue to suffer habitat loss. The projected impact of modeled climate scenarios (A1B, A2A and B2A on the distribution of the modeled species by 2040 varied. Some of the species were projected to be adversely affected by the changes in climate, while other species are expected to benefit from these changes. The combined impact of the changes in land use and climate pose serious threats to most of the modeled species. The study found that all the species are expected to suffer loss in habitat, except Gymnocarpos decanderus. The study highlights the importance of assessing the impact of land use/climate change scenarios on other species of restricted distribution in the area and can help shape policy and mitigation measures directed toward biodiversity conservation in Egypt.
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Directory of Open Access Journals (Sweden)
Daniele Porretta
Full Text Available BACKGROUND: The tiger mosquito, Aedes albopictus, is one of the 100 most invasive species in the world and a vector of human diseases. In the last 30 years, it has spread from its native range in East Asia to Africa, Europe, and the Americas. Although this modern invasion has been the focus of many studies, the history of the species' native populations remains poorly understood. Here, we aimed to assess the role of Pleistocene climatic changes in shaping the current distribution of the species in its native range. METHODOLOGY/PRINCIPAL FINDINGS: We investigated the phylogeography, historical demography, and species distribution of Ae. albopictus native populations at the Last Glacial Maximum (LGM. Individuals from 16 localities from East Asia were analyzed for sequence variation at two mitochondrial genes. No phylogeographic structure was observed across the study area. Demographic analyses showed a signature of population expansion that started roughly 70,000 years BP. The occurrence of a continuous and climatically suitable area comprising Southeast China, Indochinese Peninsula, and Sundaland during LGM was indicated by species distribution modelling. CONCLUSIONS/SIGNIFICANCE: Our results suggest an evolutionary scenario in which, during the last glacial phase, Ae. albopictus did not experience a fragmentation phase but rather persisted in interconnected populations and experienced demographic growth. The wide ecological flexibility of the species probably played a crucial role in its response to glacial-induced environmental changes. Currently, there is little information on the impact of Pleistocene climatic changes on animal species in East Asia. Most of the studies focused on forest-associated species and suggested cycles of glacial fragmentation and post-glacial expansion. The case of Ae. albopictus, which exhibits a pattern not previously observed in the study area, adds an important piece to our understanding of the Pleistocene history
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Hu, Zhongjun; Guo, Ke; Jin, Shulan; Pan, Huahua
2018-01-01
The issue that climatic change has great influence on species distribution is currently of great interest in field of biogeography. Six typical Kobresia species are selected from alpine grassland of Tibetan Plateau (TP) as research objects which are the high-quality forage for local husbandry, and their distribution changes are modeled in four periods by using MaxEnt model and GIS technology. The modeling results have shown that the distribution of these six typical Kobresia species in TP was strongly affected by two factors of "the annual precipitation" and "the precipitation in the wettest and driest quarters of the year". The modeling results have also shown that the most suitable habitats of K. pygmeae were located in the area around Qinghai Lake, the Hengduan-Himalayan mountain area, and the hinterland of TP. The most suitable habitats of K. humilis were mainly located in the area around Qinghai Lake and the hinterland of TP during the Last Interglacial period, and gradually merged into a bigger area; K. robusta and K. tibetica were located in the area around Qinghai Lake and the hinterland of TP, but they did not integrate into one area all the time, and K. capillifolia were located in the area around Qinghai Lake and extended to the southwest of the original distributing area, whereas K. macrantha were mainly distributed along the area of the Himalayan mountain chain, which had the smallest distribution area among them, and all these six Kobresia species can be divided into four types of "retreat/expansion" styles according to the changes of suitable habitat areas during the four periods; all these change styles are the result of long-term adaptations of the different species to the local climate changes in regions of TP and show the complexity of relationships between different species and climate. The research results have positive reference value to the protection of species diversity and sustainable development of the local husbandry in TP.
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Marcus V. Warwell; Gerald E. Rehfeldt; Nicholas L. Crookston
2010-01-01
The Random Forests multiple regression tree was used to develop an empirically based bioclimatic model of the presence-absence of species occupying small geographic distributions in western North America. The species assessed were subalpine larch (Larix lyallii), smooth Arizona cypress (Cupressus arizonica ssp. glabra...
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de Almeida, Paulo Silva; de Andrade, Andrey José; Sciamarelli, Alan; Raizer, Josué; Menegatti, Jaqueline Aparecida; Hermes, Sandra Cristina Negreli Moreira; de Carvalho, Maria do Socorro Laurentino; Gurgel-Gonçalves, Rodrigo
2015-01-01
This study updates the geographic distributions of phlebotomine species in Central-West Brazil and analyses the climatic factors associated with their occurrence. The data were obtained from the entomology services of the state departments of health in Central-West Brazil, scientific collections and a literature review of articles from 1962-2014. Ecological niche models were produced for sandfly species with more than 20 occurrences using the Maxent algorithm and eight climate variables. In all, 2,803 phlebotomine records for 127 species were analysed. Nyssomyia whitmani, Evandromyia lenti and Lutzomyia longipalpis were the species with the greatest number of records and were present in all the biomes in Central-West Brazil. The models, which were produced for 34 species, indicated that the Cerrado areas in the central and western regions of Central-West Brazil were climatically more suitable to sandflies. The variables with the greatest influence on the models were the temperature in the coldest months and the temperature seasonality. The results show that phlebotomine species in Central-West Brazil have different geographical distribution patterns and that climate conditions in essentially the entire region favour the occurrence of at least one Leishmania vector species, highlighting the need to maintain or intensify vector control and surveillance strategies. PMID:26018450
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Vaginal drug distribution modeling.
Katz, David F; Yuan, Andrew; Gao, Yajing
2015-09-15
This review presents and applies fundamental mass transport theory describing the diffusion and convection driven mass transport of drugs to the vaginal environment. It considers sources of variability in the predictions of the models. It illustrates use of model predictions of microbicide drug concentration distribution (pharmacokinetics) to gain insights about drug effectiveness in preventing HIV infection (pharmacodynamics). The modeling compares vaginal drug distributions after different gel dosage regimens, and it evaluates consequences of changes in gel viscosity due to aging. It compares vaginal mucosal concentration distributions of drugs delivered by gels vs. intravaginal rings. Finally, the modeling approach is used to compare vaginal drug distributions across species with differing vaginal dimensions. Deterministic models of drug mass transport into and throughout the vaginal environment can provide critical insights about the mechanisms and determinants of such transport. This knowledge, and the methodology that obtains it, can be applied and translated to multiple applications, involving the scientific underpinnings of vaginal drug distribution and the performance evaluation and design of products, and their dosage regimens, that achieve it. Copyright © 2015 Elsevier B.V. All rights reserved.
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Bustamante, Javier; Seoane, Javier
2004-01-01
Aim To test the effectiveness of statistical models based on explanatory environmental variables vs. existing distribution information (maps and breeding atlas), for predicting the distribution of four species of raptors (family Accipitridae): common buzzard Buteo buteo (Linnaeus, 1758), short-toed eagle Circaetus gallicus (Gmelin, 1788), booted eagle Hieraaetus pennatus (Gmelin, 1788) and black kite Milvus migrans (Boddaert, 1783). Location Andalusia, southe...
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Wilting, Andreas; Cord, Anna; Hearn, Andrew J; Hesse, Deike; Mohamed, Azlan; Traeholdt, Carl; Cheyne, Susan M; Sunarto, Sunarto; Jayasilan, Mohd-Azlan; Ross, Joanna; Shapiro, Aurélie C; Sebastian, Anthony; Dech, Stefan; Breitenmoser, Christine; Sanderson, Jim; Duckworth, J W; Hofer, Heribert
2010-03-17
The flat-headed cat (Prionailurus planiceps) is one of the world's least known, highly threatened felids with a distribution restricted to tropical lowland rainforests in Peninsular Thailand/Malaysia, Borneo and Sumatra. Throughout its geographic range large-scale anthropogenic transformation processes, including the pollution of fresh-water river systems and landscape fragmentation, raise concerns regarding its conservation status. Despite an increasing number of camera-trapping field surveys for carnivores in South-East Asia during the past two decades, few of these studies recorded the flat-headed cat. In this study, we designed a predictive species distribution model using the Maximum Entropy (MaxEnt) algorithm to reassess the potential current distribution and conservation status of the flat-headed cat. Eighty-eight independent species occurrence records were gathered from field surveys, literature records, and museum collections. These current and historical records were analysed in relation to bioclimatic variables (WorldClim), altitude (SRTM) and minimum distance to larger water resources (Digital Chart of the World). Distance to water was identified as the key predictor for the occurrence of flat-headed cats (>50% explanation). In addition, we used different land cover maps (GLC2000, GlobCover and SarVision LLC for Borneo), information on protected areas and regional human population density data to extract suitable habitats from the potential distribution predicted by the MaxEnt model. Between 54% and 68% of suitable habitat has already been converted to unsuitable land cover types (e.g. croplands, plantations), and only between 10% and 20% of suitable land cover is categorised as fully protected according to the IUCN criteria. The remaining habitats are highly fragmented and only a few larger forest patches remain. Based on our findings, we recommend that future conservation efforts for the flat-headed cat should focus on the identified remaining key
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Directory of Open Access Journals (Sweden)
Andreas Wilting
Full Text Available BACKGROUND: The flat-headed cat (Prionailurus planiceps is one of the world's least known, highly threatened felids with a distribution restricted to tropical lowland rainforests in Peninsular Thailand/Malaysia, Borneo and Sumatra. Throughout its geographic range large-scale anthropogenic transformation processes, including the pollution of fresh-water river systems and landscape fragmentation, raise concerns regarding its conservation status. Despite an increasing number of camera-trapping field surveys for carnivores in South-East Asia during the past two decades, few of these studies recorded the flat-headed cat. METHODOLOGY/PRINCIPAL FINDINGS: In this study, we designed a predictive species distribution model using the Maximum Entropy (MaxEnt algorithm to reassess the potential current distribution and conservation status of the flat-headed cat. Eighty-eight independent species occurrence records were gathered from field surveys, literature records, and museum collections. These current and historical records were analysed in relation to bioclimatic variables (WorldClim, altitude (SRTM and minimum distance to larger water resources (Digital Chart of the World. Distance to water was identified as the key predictor for the occurrence of flat-headed cats (>50% explanation. In addition, we used different land cover maps (GLC2000, GlobCover and SarVision LLC for Borneo, information on protected areas and regional human population density data to extract suitable habitats from the potential distribution predicted by the MaxEnt model. Between 54% and 68% of suitable habitat has already been converted to unsuitable land cover types (e.g. croplands, plantations, and only between 10% and 20% of suitable land cover is categorised as fully protected according to the IUCN criteria. The remaining habitats are highly fragmented and only a few larger forest patches remain. CONCLUSION/SIGNIFICANCE: Based on our findings, we recommend that future conservation
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Pont, Didier; Logez, M; Carrel, G; Rogers, C; Haidvogl, G
Species distributions models (SDM) that rely on estimated relationships between present environmental conditions and species presence-absence are widely used to forecast changes of species distributions caused by global warming but far less to reconstruct historical assemblages. By compiling historical fish data from the turn to the middle of the twentieth century in a similar way for several European catchments (Rhône, Danube), and using already published SDMs based on current observations, we: (1) tested the predictive accuracy of such models for past climatic conditions, (2) compared observed and expected cumulated historical species occurrences at sub-catchment level, and (3) compared the annual variability in the predictions within one sub-catchment (Salzach) under a future climate scenario to the long-term variability of occurrences reconstructed during an extended historical period (1800-2000). We finally discuss the potential of these SDMs to define a "reference condition", the possibility of a shift in baseline condition in relation with anthropogenic pressures, and past and future climate variability. The results of this study clearly highlight the potential of SDM to reconstruct the past composition of European fish assemblages and to analyze the historical ecological status of European rivers. Assessing the uncertainty associated with species distribution projections is of primary importance before evaluating and comparing the past and future distribution of species within a given catchment.
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Directory of Open Access Journals (Sweden)
Brian W. Miller
2015-05-01
Full Text Available State-and-transition simulation models (STSMs are known for their ability to explore the combined effects of multiple disturbances, ecological dynamics, and management actions on vegetation. However, integrating the additional impacts of climate change into STSMs remains a challenge. We address this challenge by combining an STSM with species distribution modeling (SDM. SDMs estimate the probability of occurrence of a given species based on observed presence and absence locations as well as environmental and climatic covariates. Thus, in order to account for changes in habitat suitability due to climate change, we used SDM to generate continuous surfaces of species occurrence probabilities. These data were imported into ST-Sim, an STSM platform, where they dictated the probability of each cell transitioning between alternate potential vegetation types at each time step. The STSM was parameterized to capture additional processes of vegetation growth and disturbance that are relevant to a keystone species in the Greater Yellowstone Ecosystem—whitebark pine (Pinus albicaulis. We compared historical model runs against historical observations of whitebark pine and a key disturbance agent (mountain pine beetle, Dendroctonus ponderosae, and then projected the simulation into the future. Using this combination of correlative and stochastic simulation models, we were able to reproduce historical observations and identify key data gaps. Results indicated that SDMs and STSMs are complementary tools, and combining them is an effective way to account for the anticipated impacts of climate change, biotic interactions, and disturbances, while also allowing for the exploration of management options.
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Rödder, Dennis; Nekum, Sven; Cord, Anna F.; Engler, Jan O.
2016-07-01
Climate change and anthropogenic habitat fragmentation are considered major threats for global biodiversity. As a direct consequence, connectivity is increasingly disrupted in many species, which might have serious consequences that could ultimately lead to the extinction of populations. Although a large number of reserves and conservation sites are designated and protected by law, potential habitats acting as inter-population connectivity corridors are, however, mostly ignored in the common practice of environmental planning. In most cases, this is mainly caused by a lack of quantitative measures of functional connectivity available for the planning process. In this study, we highlight the use of fine-scale potential connectivity models (PCMs) derived from multispectral satellite data for the quantification of spatially explicit habitat corridors for matrix-sensitive species of conservation concern. This framework couples a species distribution model with a connectivity model in a two-step framework, where suitability maps from step 1 are transformed into maps of landscape resistance in step 2 filtered by fragmentation thresholds. We illustrate the approach using the sand lizard ( Lacerta agilis L.) in the metropolitan area of Cologne, Germany, as a case study. Our model proved to be well suited to identify connected as well as completely isolated populations within the study area. Furthermore, due to its fine resolution, the PCM was also able to detect small linear structures known to be important for sand lizards' inter-population connectivity such as railroad embankments. We discuss the applicability and possible implementation of PCMs to overcome shortcomings in the common practice of environmental impact assessments.
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Tisseuil, C; Vrac, M; Grenouillet, G; Wade, A J; Gevrey, M; Oberdorff, T; Grodwohl, J-B; Lek, S
2012-05-01
To understand the resilience of aquatic ecosystems to environmental change, it is important to determine how multiple, related environmental factors, such as near-surface air temperature and river flow, will change during the next century. This study develops a novel methodology that combines statistical downscaling and fish species distribution modeling, to enhance the understanding of how global climate changes (modeled by global climate models at coarse-resolution) may affect local riverine fish diversity. The novelty of this work is the downscaling framework developed to provide suitable future projections of fish habitat descriptors, focusing particularly on the hydrology which has been rarely considered in previous studies. The proposed modeling framework was developed and tested in a major European system, the Adour-Garonne river basin (SW France, 116,000 km(2)), which covers distinct hydrological and thermal regions from the Pyrenees to the Atlantic coast. The simulations suggest that, by 2100, the mean annual stream flow is projected to decrease by approximately 15% and temperature to increase by approximately 1.2 °C, on average. As consequence, the majority of cool- and warm-water fish species is projected to expand their geographical range within the basin while the few cold-water species will experience a reduction in their distribution. The limitations and potential benefits of the proposed modeling approach are discussed. Copyright © 2012 Elsevier B.V. All rights reserved.
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Model uncertainties do not affect observed patterns of species richness in the Amazon
Sales, Lilian Patrícia; Neves, Olívia Viana; De Marco, Paulo
2017-01-01
Background Climate change is arguably a major threat to biodiversity conservation and there are several methods to assess its impacts on species potential distribution. Yet the extent to which different approaches on species distribution modeling affect species richness patterns at biogeographical scale is however unaddressed in literature. In this paper, we verified if the expected responses to climate change in biogeographical scale—patterns of species richness and species vulnerability to climate change—are affected by the inputs used to model and project species distribution. Methods We modeled the distribution of 288 vertebrate species (amphibians, birds and mammals), all endemic to the Amazon basin, using different combinations of the following inputs known to affect the outcome of species distribution models (SDMs): 1) biological data type, 2) modeling methods, 3) greenhouse gas emission scenarios and 4) climate forecasts. We calculated uncertainty with a hierarchical ANOVA in which those different inputs were considered factors. Results The greatest source of variation was the modeling method. Model performance interacted with data type and modeling method. Absolute values of variation on suitable climate area were not equal among predictions, but some biological patterns were still consistent. All models predicted losses on the area that is climatically suitable for species, especially for amphibians and primates. All models also indicated a current East-western gradient on endemic species richness, from the Andes foot downstream the Amazon river. Again, all models predicted future movements of species upwards the Andes mountains and overall species richness losses. Conclusions From a methodological perspective, our work highlights that SDMs are a useful tool for assessing impacts of climate change on biodiversity. Uncertainty exists but biological patterns are still evident at large spatial scales. As modeling methods are the greatest source of
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Balancing energy development and conservation: A method utilizing species distribution models
Jarnevich, C.S.; Laubhan, M.K.
2011-01-01
Alternative energy development is increasing, potentially leading to negative impacts on wildlife populations already stressed by other factors. Resource managers require a scientifically based methodology to balance energy development and species conservation, so we investigated modeling habitat suitability using Maximum Entropy to develop maps that could be used with other information to help site energy developments. We selected one species of concern, the Lesser Prairie-Chicken (LPCH; Tympanuchus pallidicinctus) found on the southern Great Plains of North America, as our case study. LPCH populations have been declining and are potentially further impacted by energy development. We used LPCH lek locations in the state of Kansas along with several environmental and anthropogenic parameters to develop models that predict the probability of lek occurrence across the landscape. The models all performed well as indicated by the high test area under the curve (AUC) scores (all >0.9). The inclusion of anthropogenic parameters in models resulted in slightly better performance based on AUC values, indicating that anthropogenic features may impact LPCH lek habitat suitability. Given the positive model results, this methodology may provide additional guidance in designing future survey protocols, as well as siting of energy development in areas of marginal or unsuitable habitat for species of concern. This technique could help to standardize and quantify the impacts various developments have upon at-risk species. ?? 2011 Springer Science+Business Media, LLC (outside the USA).
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Bellamy, Chloe; Altringham, John
2015-01-01
Conservation increasingly operates at the landscape scale. For this to be effective, we need landscape scale information on species distributions and the environmental factors that underpin them. Species records are becoming increasingly available via data centres and online portals, but they are often patchy and biased. We demonstrate how such data can yield useful habitat suitability models, using bat roost records as an example. We analysed the effects of environmental variables at eight spatial scales (500 m - 6 km) on roost selection by eight bat species (Pipistrellus pipistrellus, P. pygmaeus, Nyctalus noctula, Myotis mystacinus, M. brandtii, M. nattereri, M. daubentonii, and Plecotus auritus) using the presence-only modelling software MaxEnt. Modelling was carried out on a selection of 418 data centre roost records from the Lake District National Park, UK. Target group pseudoabsences were selected to reduce the impact of sampling bias. Multi-scale models, combining variables measured at their best performing spatial scales, were used to predict roosting habitat suitability, yielding models with useful predictive abilities. Small areas of deciduous woodland consistently increased roosting habitat suitability, but other habitat associations varied between species and scales. Pipistrellus were positively related to built environments at small scales, and depended on large-scale woodland availability. The other, more specialist, species were highly sensitive to human-altered landscapes, avoiding even small rural towns. The strength of many relationships at large scales suggests that bats are sensitive to habitat modifications far from the roost itself. The fine resolution, large extent maps will aid targeted decision-making by conservationists and planners. We have made available an ArcGIS toolbox that automates the production of multi-scale variables, to facilitate the application of our methods to other taxa and locations. Habitat suitability modelling has the
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Hayes, Mark A.; Ozenberger, Katharine; Cryan, Paul M.; Wunder, Michael B.
2015-01-01
Bat specimens held in natural history museum collections can provide insights into the distribution of species. However, there are several important sources of spatial error associated with natural history specimens that may influence the analysis and mapping of bat species distributions. We analyzed the importance of geographic referencing and error correction in species distribution modeling (SDM) using occurrence records of hoary bats (Lasiurus cinereus). This species is known to migrate long distances and is a species of increasing concern due to fatalities documented at wind energy facilities in North America. We used 3,215 museum occurrence records collected from 1950–2000 for hoary bats in North America. We compared SDM performance using five approaches: generalized linear models, multivariate adaptive regression splines, boosted regression trees, random forest, and maximum entropy models. We evaluated results using three SDM performance metrics (AUC, sensitivity, and specificity) and two data sets: one comprised of the original occurrence data, and a second data set consisting of these same records after the locations were adjusted to correct for identifiable spatial errors. The increase in precision improved the mean estimated spatial error associated with hoary bat records from 5.11 km to 1.58 km, and this reduction in error resulted in a slight increase in all three SDM performance metrics. These results provide insights into the importance of geographic referencing and the value of correcting spatial errors in modeling the distribution of a wide-ranging bat species. We conclude that the considerable time and effort invested in carefully increasing the precision of the occurrence locations in this data set was not worth the marginal gains in improved SDM performance, and it seems likely that gains would be similar for other bat species that range across large areas of the continent, migrate, and are habitat generalists.
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Directory of Open Access Journals (Sweden)
Johannes Bergsten
2017-06-01
Full Text Available The species status of Hyphydrus anatolicus Guignot, 1957 and H. sanctus Sharp, 1882, previously often confused with the widespread H. ovatus (Linnaeus, 1760, are tested with molecular and morphological characters. Cytochrome c oxidase subunit 1 (CO1 was sequenced for 32 specimens of all three species. Gene-trees were inferred with parsimony, time-free bayesian and strict clock bayesian analyses. The GMYC model was used to estimate species limits. All three species were reciprocally monophyletic with CO1 and highly supported. The GMYC species delimitation analysis unequivocally delimited the three species with no other than the three species solution included in the confidence interval. A likelihood ratio test rejected the one-species null model. Important morphological characters distinguishing the species are provided and illustrated. New distributional data are given for the following species: Hyphydrus anatolicus from Slovakia and Ukraine, and H. aubei Ganglbauer, 1891, and H. sanctus from Turkey.
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Uncovering the drivers of host-associated microbiota with joint species distribution modelling.
Björk, Johannes R; Hui, Francis K C; O'Hara, Robert B; Montoya, Jose M
2018-06-01
In addition to the processes structuring free-living communities, host-associated microbiota are directly or indirectly shaped by the host. Therefore, microbiota data have a hierarchical structure where samples are nested under one or several variables representing host-specific factors, often spanning multiple levels of biological organization. Current statistical methods do not accommodate this hierarchical data structure and therefore cannot explicitly account for the effect of the host in structuring the microbiota. We introduce a novel extension of joint species distribution models (JSDMs) which can straightforwardly accommodate and discern between effects such as host phylogeny and traits, recorded covariates such as diet and collection site, among other ecological processes. Our proposed methodology includes powerful yet familiar outputs seen in community ecology overall, including (a) model-based ordination to visualize and quantify the main patterns in the data; (b) variance partitioning to assess how influential the included host-specific factors are in structuring the microbiota; and (c) co-occurrence networks to visualize microbe-to-microbe associations. © 2018 John Wiley & Sons Ltd.
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Tree species distribution in temperate forests is more influenced by soil than by climate.
Walthert, Lorenz; Meier, Eliane Seraina
2017-11-01
Knowledge of the ecological requirements determining tree species distributions is a precondition for sustainable forest management. At present, the abiotic requirements and the relative importance of the different abiotic factors are still unclear for many temperate tree species. We therefore investigated the relative importance of climatic and edaphic factors for the abundance of 12 temperate tree species along environmental gradients. Our investigations are based on data from 1,075 forest stands across Switzerland including the cold-induced tree line of all studied species and the drought-induced range boundaries of several species. Four climatic and four edaphic predictors represented the important growth factors temperature, water supply, nutrient availability, and soil aeration. The climatic predictors were derived from the meteorological network of MeteoSwiss, and the edaphic predictors were available from soil profiles. Species cover abundances were recorded in field surveys. The explanatory power of the predictors was assessed by variation partitioning analyses with generalized linear models. For six of the 12 species, edaphic predictors were more important than climatic predictors in shaping species distribution. Over all species, abundances depended mainly on nutrient availability, followed by temperature, water supply, and soil aeration. The often co-occurring species responded similar to these growth factors. Drought turned out to be a determinant of the lower range boundary for some species. We conclude that over all 12 studied tree species, soil properties were more important than climate variables in shaping tree species distribution. The inclusion of appropriate soil variables in species distribution models allowed to better explain species' ecological niches. Moreover, our study revealed that the ecological requirements of tree species assessed in local field studies and in experiments are valid at larger scales across Switzerland.
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Hierarchical spatial models for predicting pygmy rabbit distribution and relative abundance
Wilson, T.L.; Odei, J.B.; Hooten, M.B.; Edwards, T.C.
2010-01-01
Conservationists routinely use species distribution models to plan conservation, restoration and development actions, while ecologists use them to infer process from pattern. These models tend to work well for common or easily observable species, but are of limited utility for rare and cryptic species. This may be because honest accounting of known observation bias and spatial autocorrelation are rarely included, thereby limiting statistical inference of resulting distribution maps. We specified and implemented a spatially explicit Bayesian hierarchical model for a cryptic mammal species (pygmy rabbit Brachylagus idahoensis). Our approach used two levels of indirect sign that are naturally hierarchical (burrows and faecal pellets) to build a model that allows for inference on regression coefficients as well as spatially explicit model parameters. We also produced maps of rabbit distribution (occupied burrows) and relative abundance (number of burrows expected to be occupied by pygmy rabbits). The model demonstrated statistically rigorous spatial prediction by including spatial autocorrelation and measurement uncertainty. We demonstrated flexibility of our modelling framework by depicting probabilistic distribution predictions using different assumptions of pygmy rabbit habitat requirements. Spatial representations of the variance of posterior predictive distributions were obtained to evaluate heterogeneity in model fit across the spatial domain. Leave-one-out cross-validation was conducted to evaluate the overall model fit. Synthesis and applications. Our method draws on the strengths of previous work, thereby bridging and extending two active areas of ecological research: species distribution models and multi-state occupancy modelling. Our framework can be extended to encompass both larger extents and other species for which direct estimation of abundance is difficult. ?? 2010 The Authors. Journal compilation ?? 2010 British Ecological Society.
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Directory of Open Access Journals (Sweden)
Nicolas Casajus
Full Text Available An impressive number of new climate change scenarios have recently become available to assess the ecological impacts of climate change. Among these impacts, shifts in species range analyzed with species distribution models are the most widely studied. Whereas it is widely recognized that the uncertainty in future climatic conditions must be taken into account in impact studies, many assessments of species range shifts still rely on just a few climate change scenarios, often selected arbitrarily. We describe a method to select objectively a subset of climate change scenarios among a large ensemble of available ones. Our k-means clustering approach reduces the number of climate change scenarios needed to project species distributions, while retaining the coverage of uncertainty in future climate conditions. We first show, for three biologically-relevant climatic variables, that a reduced number of six climate change scenarios generates average climatic conditions very close to those obtained from a set of 27 scenarios available before reduction. A case study on potential gains and losses of habitat by three northeastern American tree species shows that potential future species distributions projected from the selected six climate change scenarios are very similar to those obtained from the full set of 27, although with some spatial discrepancies at the edges of species distributions. In contrast, projections based on just a few climate models vary strongly according to the initial choice of climate models. We give clear guidance on how to reduce the number of climate change scenarios while retaining the central tendencies and coverage of uncertainty in future climatic conditions. This should be particularly useful during future climate change impact studies as more than twice as many climate models were reported in the fifth assessment report of IPCC compared to the previous one.
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Casajus, Nicolas; Périé, Catherine; Logan, Travis; Lambert, Marie-Claude; de Blois, Sylvie; Berteaux, Dominique
2016-01-01
An impressive number of new climate change scenarios have recently become available to assess the ecological impacts of climate change. Among these impacts, shifts in species range analyzed with species distribution models are the most widely studied. Whereas it is widely recognized that the uncertainty in future climatic conditions must be taken into account in impact studies, many assessments of species range shifts still rely on just a few climate change scenarios, often selected arbitrarily. We describe a method to select objectively a subset of climate change scenarios among a large ensemble of available ones. Our k-means clustering approach reduces the number of climate change scenarios needed to project species distributions, while retaining the coverage of uncertainty in future climate conditions. We first show, for three biologically-relevant climatic variables, that a reduced number of six climate change scenarios generates average climatic conditions very close to those obtained from a set of 27 scenarios available before reduction. A case study on potential gains and losses of habitat by three northeastern American tree species shows that potential future species distributions projected from the selected six climate change scenarios are very similar to those obtained from the full set of 27, although with some spatial discrepancies at the edges of species distributions. In contrast, projections based on just a few climate models vary strongly according to the initial choice of climate models. We give clear guidance on how to reduce the number of climate change scenarios while retaining the central tendencies and coverage of uncertainty in future climatic conditions. This should be particularly useful during future climate change impact studies as more than twice as many climate models were reported in the fifth assessment report of IPCC compared to the previous one.
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Directory of Open Access Journals (Sweden)
Brady J Mattsson
Full Text Available Understanding interactions between mobile species distributions and landcover characteristics remains an outstanding challenge in ecology. Multiple factors could explain species distributions including endogenous evolutionary traits leading to conspecific clustering and endogenous habitat features that support life history requirements. Birds are a useful taxon for examining hypotheses about the relative importance of these factors among species in a community. We developed a hierarchical Bayes approach to model the relationships between bird species occupancy and local landcover variables accounting for spatial autocorrelation, species similarities, and partial observability. We fit alternative occupancy models to detections of 90 bird species observed during repeat visits to 316 point-counts forming a 400-m grid throughout the Patuxent Wildlife Research Refuge in Maryland, USA. Models with landcover variables performed significantly better than our autologistic and null models, supporting the hypothesis that local landcover heterogeneity is important as an exogenous driver for species distributions. Conspecific clustering alone was a comparatively poor descriptor of local community composition, but there was evidence for spatial autocorrelation in all species. Considerable uncertainty remains whether landcover combined with spatial autocorrelation is most parsimonious for describing bird species distributions at a local scale. Spatial structuring may be weaker at intermediate scales within which dispersal is less frequent, information flows are localized, and landcover types become spatially diversified and therefore exhibit little aggregation. Examining such hypotheses across species assemblages contributes to our understanding of community-level associations with conspecifics and landscape composition.
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Forms and genesis of species abundance distributions
Directory of Open Access Journals (Sweden)
Evans O. Ochiaga
2015-12-01
Full Text Available Species abundance distribution (SAD is one of the most important metrics in community ecology. SAD curves take a hollow or hyperbolic shape in a histogram plot with many rare species and only a few common species. In general, the shape of SAD is largely log-normally distributed, although the mechanism behind this particular SAD shape still remains elusive. Here, we aim to review four major parametric forms of SAD and three contending mechanisms that could potentially explain this highly skewed form of SAD. The parametric forms reviewed here include log series, negative binomial, lognormal and geometric distributions. The mechanisms reviewed here include the maximum entropy theory of ecology, neutral theory and the theory of proportionate effect.
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Directory of Open Access Journals (Sweden)
F Andrew Jones
Full Text Available Plants interact with each other, nutrients, and microbial communities in soils through extensive root networks. Understanding these below ground interactions has been difficult in natural systems, particularly those with high plant species diversity where morphological identification of fine roots is difficult. We combine DNA-based root identification with a DNA barcode database and above ground stem locations in a floristically diverse lowland tropical wet forest on Barro Colorado Island, Panama, where all trees and lianas >1 cm diameter have been mapped to investigate richness patterns below ground and model rooting distributions.DNA barcode loci, particularly the cpDNA locus trnH-psba, can be used to identify fine and small coarse roots to species. We recovered 33 species of roots from 117 fragments sequenced from 12 soil cores. Despite limited sampling, we recovered a high proportion of the known species in the focal hectare, representing approximately 14% of the measured woody plant richness. This high value is emphasized by the fact that we would need to sample on average 13 m(2 at the seedling layer and 45 m(2 for woody plants >1 cm diameter to obtain the same number of species above ground. Results from inverse models parameterized with the locations and sizes of adults and the species identifications of roots and sampling locations indicates a high potential for distal underground interactions among plants.DNA barcoding techniques coupled with modeling approaches should be broadly applicable to studying root distributions in any mapped vegetation plot. We discuss the implications of our results and outline how second-generation sequencing technology and environmental sampling can be combined to increase our understanding of how root distributions influence the potential for plant interactions in natural ecosystems.
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Do predictions from Species Sensitivity Distributions match with field data?
International Nuclear Information System (INIS)
Smetanová, S.; Bláha, L.; Liess, M.; Schäfer, R.B.; Beketov, M.A.
2014-01-01
Species Sensitivity Distribution (SSD) is a statistical model that can be used to predict effects of contaminants on biological communities, but only few comparisons of this model with field studies have been conducted so far. In the present study we used measured pesticides concentrations from streams in Germany, France, and Finland, and we used SSD to calculate msPAF (multiple substance potentially affected fraction) values based on maximum toxic stress at localities. We compared these SSD-based predictions with the actual effects on stream invertebrates quantified by the SPEAR pesticides bioindicator. The results show that the msPAFs correlated well with the bioindicator, however, the generally accepted SSD threshold msPAF of 0.05 (5% of species are predicted to be affected) severely underestimated the observed effects (msPAF values causing significant effects are 2–1000-times lower). These results demonstrate that validation with field data is required to define the appropriate thresholds for SSD predictions. - Highlights: • We validated the statistical model Species Sensitivity Distribution with field data. • Good correlation was found between the model predictions and observed effects. • But, the generally accepted threshold msPAF 0.05 severely underestimated the effects. - Comparison of the SSD-based prediction with the field data evaluated with the SPEAR pesticides index shows that SSD threshold msPAF of 0.05 severely underestimates the effects observed in the field
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El-Gabbas, Ahmed; Dormann, Carsten F
2018-02-01
Species distribution modeling (SDM) is an essential method in ecology and conservation. SDMs are often calibrated within one country's borders, typically along a limited environmental gradient with biased and incomplete data, making the quality of these models questionable. In this study, we evaluated how adequate are national presence-only data for calibrating regional SDMs. We trained SDMs for Egyptian bat species at two different scales: only within Egypt and at a species-specific global extent. We used two modeling algorithms: Maxent and elastic net, both under the point-process modeling framework. For each modeling algorithm, we measured the congruence of the predictions of global and regional models for Egypt, assuming that the lower the congruence, the lower the appropriateness of the Egyptian dataset to describe the species' niche. We inspected the effect of incorporating predictions from global models as additional predictor ("prior") to regional models, and quantified the improvement in terms of AUC and the congruence between regional models run with and without priors. Moreover, we analyzed predictive performance improvements after correction for sampling bias at both scales. On average, predictions from global and regional models in Egypt only weakly concur. Collectively, the use of priors did not lead to much improvement: similar AUC and high congruence between regional models calibrated with and without priors. Correction for sampling bias led to higher model performance, whatever prior used, making the use of priors less pronounced. Under biased and incomplete sampling, the use of global bats data did not improve regional model performance. Without enough bias-free regional data, we cannot objectively identify the actual improvement of regional models after incorporating information from the global niche. However, we still believe in great potential for global model predictions to guide future surveys and improve regional sampling in data
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Assessing distributions of two invasive species of contrasting habits in future climate.
Panda, Rajendra Mohan; Behera, Mukunda Dev; Roy, Partha Sarathi
2018-05-01
Understanding the impact of climate change on species invasion is crucial for sustainable biodiversity conservation. Through this study, we try to answer how species differing in phenological cycles, specifically Cassia tora and Lantana camara, differ in the manner in which they invade new regions in India in the future climate. Since both species occupy identical niches, exploring their invasive potential in different climate change scenarios will offer critical insights into invasion and inform ecosystem management. We use three modelling protocols (i.e., maximum entropy, generalised linear model and generalised additive model) to predict the current distribution. Projections are made for both moderate (A1B) and extreme (A2) IPCC (Intergovernmental Panel on Climate Change) scenarios for the year 2050 and 2100. The study reveals that the distributions of C. tora (annual) and L. camara (perennial) would depend on the precipitation of the warmest quarter and moisture availability. C. tora may demonstrate physiological tolerance to the mean diurnal temperature range and L. camara to the solar radiation. C. tora may invade central India, while L. camara may invade the Western Himalaya, parts of the Eastern Himalaya and the Western Ghats. The distribution ranges of both species could shift in the northern and north-eastern directions in India, owing to changes in moisture availability. The possible alterations in precipitation regimes could lead to water stress, which might have cascading effects on species invasion. L. camara might adapt to climate change better compared with C. tora. This comparative analysis of the future distributions of two invasive plants with contrasting habits demonstrates that temporal complementarity would prevail over the competition. Copyright © 2017 Elsevier Ltd. All rights reserved.
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Directory of Open Access Journals (Sweden)
Néstor M. Robinson
2017-12-01
Full Text Available In the marine environment Species Distribution Models (SDMs have been used in hundreds of papers for predicting the present and future geographic range and environmental niche of species. We have analyzed ways in which SDMs are being applied to marine species in order to recommend best practice in future studies. This systematic review was registered as a protocol on the Open Science Framework: https://osf.io/tngs6/. The literature reviewed (236 papers was published between 1992 and July 2016. The number of papers significantly increased through time (R2 = 0.92, p < 0.05. The studies were predominantly carried out in the Temperate Northern Atlantic (45% followed by studies of global scale (11% and studies in Temperate Australasia (10%. The majority of studies reviewed focused on theoretical ecology (37% including investigations of biological invasions by non-native organisms, conservation planning (19%, and climate change predictions (17%. Most of the studies were published in ecological, multidisciplinary, or biodiversity conservation journals. Most of the studies (94% failed to report the amount of uncertainty derived from data deficiencies and model parameters. Best practice recommendations are proposed here to ensure that novice and advanced SDM users can (a understand the main elements of SDMs, (b reproduce standard methods and analysis, and (c identify potential limitations with their data. We suggest that in the future, studies of marine SDMs should report on key features of the approaches employed, data deficiencies, the selection of the best explanatory model, and the approach taken to validate the SDM results. In addition, based on the literature reviewed, we suggest that future marine SDMs should account for uncertainty levels as part of the modeling process.
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Energy Technology Data Exchange (ETDEWEB)
Obregon, R.; Fernandez Haeger, J.; Jordano, D.
2016-07-01
Knowledge of the spatial distribution of rare or endangered species is of key importance to assess conservation status at different geographic scales and to develop conservation and recovery programs. In this paper we review and update the distribution of three species of Lycaenid butterflies in Andalusia (southern Spain): Cupido carswelli, C. lorquinii, and C. osiris. Cupido carswelli is endemic in south east Spain and is considered a vulnerable species in the Red Book of Invertebrates of Andalusia. Cupido lorquinii is an Iberian–Maghrebian endemism, found in the southern half of the Iberian peninsula. Cupido osiris, widely distributed in Europe and Central Asia, has its southern limit of distribution in Andalusia. We modeled the potential current distribution of these species in Andalusia, using Maxent. Their potential distribution was mainly conditioned by the presence of their host plants and, to a lesser extent, by climatic variables: rainfall during the warmest and coldest quarters of the year and annual mean temperature. AUC test values, sensitivity, and specificity for the three models were high, confirming the accuracy of the models and their high predictive values. We also modeled the potential future distributions of the three species under the climate change scenario A2a. Our results predict a significant reduction in the potential distribution for C. lorquinii —which has a wider distribution in Andalusia than the other two species— and for the more localized species, C. osiris and C. carswelli. This expected decline in the south of the Iberian peninsula highlights the pressing need to design and implement specific conservation plans for these species. (Author)
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Modelling the potential distribution of Betula utilis in the Himalaya
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Maria Bobrowski
2017-07-01
Full Text Available Developing sustainable adaptation pathways under climate change conditions in mountain regions requires accurate predictions of treeline shifts and future distribution ranges of treeline species. Here, we model for the first time the potential distribution of Betula utilis, a principal Himalayan treeline species, to provide a basis for the analysis of future range shifts. Our target species Betula utilis is widespread at alpine treelines in the Himalayan mountains, the distribution range extends across the Himalayan mountain range. Our objective is to model the potential distribution of B. utilis in relation to current climate conditions. We generated a dataset of 590 occurrence records and used 24 variables for ecological niche modelling. We calibrated Generalized Linear Models using the Akaike Information Criterion (AIC and evaluated model performance using threshold-independent (AUC, Area Under the Curve and threshold-dependent (TSS, True Skill Statistics characteristics as well as visual assessments of projected distribution maps. We found two temperature-related (Mean Temperature of the Wettest Quarter, Temperature Annual Range and three precipitation-related variables (Precipitation of the Coldest Quarter, Average Precipitation of March, April and May and Precipitation Seasonality to be useful for predicting the potential distribution of B. utilis. All models had high predictive power (AUC ≥ 0.98 and TSS ≥ 0.89. The projected suitable area in the Himalayan mountains varies considerably, with most extensive distribution in the western and central Himalayan region. A substantial difference between potential and real distribution in the eastern Himalaya points to decreasing competitiveness of B. utilis under more oceanic conditions in the eastern part of the mountain system. A comparison between the vegetation map of Schweinfurth (1957 and our current predictions suggests that B. utilis does not reach the upper elevational limit in
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Fire, humans, and climate: modeling distribution dynamics of boreal forest waterbirds.
Börger, Luca; Nudds, Thomas D
2014-01-01
Understanding the effects of landscape change and environmental variability on ecological processes is important for evaluating resource management policies, such as the emulation of natural forest disturbances. We analyzed time series of detection/nondetection data using hierarchical models in a Bayesian multi-model inference framework to decompose the dynamics of species distributions into responses to environmental variability, spatial variation in habitat conditions, and population dynamics and interspecific interactions, while correcting for observation errors and variation in sampling regimes. We modeled distribution dynamics of 14 waterbird species (broadly defined, including wetland and riparian species) using data from two different breeding bird surveys collected in the Boreal Shield ecozone within Ontario, Canada. Temporal variation in species occupancy (2000-2006) was primarily driven by climatic variability. Only two species showed evidence of consistent temporal trends in distribution: Ring-necked Duck (Aythya collaris) decreased, and Red-winged Blackbird (Agelaius phoeniceus) increased. The models had good predictive ability on independent data over time (1997-1999). Spatial variation in species occupancy was strongly related to the distribution of specific land cover types and habitat disturbance: Fire and forest harvesting influenced occupancy more than did roads, settlements, or mines. Bioclimatic and habitat heterogeneity indices and geographic coordinates exerted negligible influence on most species distributions. Estimated habitat suitability indices had good predictive ability on spatially independent data (Hudson Bay Lowlands ecozone). Additionally, we detected effects of interspecific interactions. Species responses to fire and forest harvesting were similar for 13 of 14 species; thus, forest-harvesting practices in Ontario generally appeared to emulate the effects of fire for waterbirds over timescales of 10-20 years. Extrapolating to all
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Labay, Ben; Cohen, Adam E; Sissel, Blake; Hendrickson, Dean A; Martin, F Douglas; Sarkar, Sahotra
2011-01-01
Accurate establishment of baseline conditions is critical to successful management and habitat restoration. We demonstrate the ability to robustly estimate historical fish community composition and assess the current status of the urbanized Barton Creek watershed in central Texas, U.S.A. Fish species were surveyed in 2008 and the resulting data compared to three sources of fish occurrence information: (i) historical records from a museum specimen database and literature searches; (ii) a nearly identical survey conducted 15 years earlier; and (iii) a modeled historical community constructed with species distribution models (SDMs). This holistic approach, and especially the application of SDMs, allowed us to discover that the fish community in Barton Creek was more diverse than the historical data and survey methods alone indicated. Sixteen native species with high modeled probability of occurrence within the watershed were not found in the 2008 survey, seven of these were not found in either survey or in any of the historical collection records. Our approach allowed us to more rigorously establish the true baseline for the pre-development fish fauna and then to more accurately assess trends and develop hypotheses regarding factors driving current fish community composition to better inform management decisions and future restoration efforts. Smaller, urbanized freshwater systems, like Barton Creek, typically have a relatively poor historical biodiversity inventory coupled with long histories of alteration, and thus there is a propensity for land managers and researchers to apply inaccurate baseline standards. Our methods provide a way around that limitation by using SDMs derived from larger and richer biodiversity databases of a broader geographic scope. Broadly applied, we propose that this technique has potential to overcome limitations of popular bioassessment metrics (e.g., IBI) to become a versatile and robust management tool for determining status of
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Using Historical Atlas Data to Develop High-Resolution Distribution Models of Freshwater Fishes.
Directory of Open Access Journals (Sweden)
Jian Huang
Full Text Available Understanding the spatial pattern of species distributions is fundamental in biogeography, and conservation and resource management applications. Most species distribution models (SDMs require or prefer species presence and absence data for adequate estimation of model parameters. However, observations with unreliable or unreported species absences dominate and limit the implementation of SDMs. Presence-only models generally yield less accurate predictions of species distribution, and make it difficult to incorporate spatial autocorrelation. The availability of large amounts of historical presence records for freshwater fishes of the United States provides an opportunity for deriving reliable absences from data reported as presence-only, when sampling was predominantly community-based. In this study, we used boosted regression trees (BRT, logistic regression, and MaxEnt models to assess the performance of a historical metacommunity database with inferred absences, for modeling fish distributions, investigating the effect of model choice and data properties thereby. With models of the distribution of 76 native, non-game fish species of varied traits and rarity attributes in four river basins across the United States, we show that model accuracy depends on data quality (e.g., sample size, location precision, species' rarity, statistical modeling technique, and consideration of spatial autocorrelation. The cross-validation area under the receiver-operating-characteristic curve (AUC tended to be high in the spatial presence-absence models at the highest level of resolution for species with large geographic ranges and small local populations. Prevalence affected training but not validation AUC. The key habitat predictors identified and the fish-habitat relationships evaluated through partial dependence plots corroborated most previous studies. The community-based SDM framework broadens our capability to model species distributions by innovatively
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SPECIES DISTRIBUTIONS, SURROGACY, AND IMPORTANT CONSERVATION REGIONS IN CANADA
Conservation actions could be more efficient if there is congruence among taxa in the distribution of species. Patterns in the geographic distribution of species of six taxa were used to identify nationally important sites for conservation in Canada. Species richness and a meas...
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Sun, Fu; Chen, Ji-ning; Zeng, Si-yu
2008-12-01
A conceptual multi-species water quality model for water distribution systems was developed on the basis of the toolkit of the EPANET-MSX software. The model divided the pipe segment into four compartments including pipe wall, biofilm, boundary layer and bulk liquid. The involved processes were substrate utilization and microbial growth, decay and inactivation of microorganisms, mass transfer of soluble components through the boundary layer, adsorption and desorption of particular components between bulk liquid and biofilm, oxidation and halogenation of organic matter by residual chlorine, and chlorine consumption by pipe wall. The fifteen simulated variables included the seven common variables both in the biofilm and in the bulk liquid, i.e. soluble organic matter, particular organic matter, ammonia nitrogen, residual chlorine, heterotrophic bacteria, autotrophic bacteria and inert solids, as well as biofilm thickness on the pipe wall. The model was validated against the data from a series of pilot experiments, and the simulation accuracy for residual chlorine and turbidity were 0.1 mg/L and 0.3 NTU respectively. A case study showed that the model could reasonably reflect the dynamic variation of residual chlorine and turbidity in the studied water distribution system, while Monte Carlo simulation, taking into account both the variability of finished water from the waterworks and the uncertainties of model parameters, could be performed to assess the violation risk of water quality in the water distribution system.
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Rudi, Gabrielle; Bailly, Jean-Stéphane; Vinatier, Fabrice
2018-01-01
To optimize ecosystem services provided by agricultural drainage networks (ditches) in headwater catchments, we need to manage the spatial distribution of plant species living in these networks. Geomorphological variables have been shown to be important predictors of plant distribution in other ecosystems because they control the water regime, the sediment deposition rates and the sun exposure in the ditches. Whether such variables may be used to predict plant distribution in agricultural drainage networks is unknown. We collected presence and absence data for 10 herbaceous plant species in a subset of a network of drainage ditches (35 km long) within a Mediterranean agricultural catchment. We simulated their spatial distribution with GLM and Maxent model using geomorphological variables and distance to natural lands and roads. Models were validated using k-fold cross-validation. We then compared the mean Area Under the Curve (AUC) values obtained for each model and other metrics issued from the confusion matrices between observed and predicted variables. Based on the results of all metrics, the models were efficient at predicting the distribution of seven species out of ten, confirming the relevance of geomorphological variables and distance to natural lands and roads to explain the occurrence of plant species in this Mediterranean catchment. In particular, the importance of the landscape geomorphological variables, ie the importance of the geomorphological features encompassing a broad environment around the ditch, has been highlighted. This suggests that agro-ecological measures for managing ecosystem services provided by ditch plants should focus on the control of the hydrological and sedimentological connectivity at the catchment scale. For example, the density of the ditch network could be modified or the spatial distribution of vegetative filter strips used for sediment trapping could be optimized. In addition, the vegetative filter strips could constitute
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Wenger, Seth J; Freeman, Mary C
2008-10-01
Researchers have developed methods to account for imperfect detection of species with either occupancy (presence absence) or count data using replicated sampling. We show how these approaches can be combined to simultaneously estimate occurrence, abundance, and detection probability by specifying a zero-inflated distribution for abundance. This approach may be particularly appropriate when patterns of occurrence and abundance arise from distinct processes operating at differing spatial or temporal scales. We apply the model to two data sets: (1) previously published data for a species of duck, Anas platyrhynchos, and (2) data for a stream fish species, Etheostoma scotti. We show that in these cases, an incomplete-detection zero-inflated modeling approach yields a superior fit to the data than other models. We propose that zero-inflated abundance models accounting for incomplete detection be considered when replicate count data are available.
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Zaidi, Farrah; Fatima, Syeda Hira; Khisroon, Muhammad; Gul, Ayesha
2016-10-01
North West Pakistan (NWP) is characterized by four eco-zones: Northern Montane Region, North Western Hills, Submontane Region and Indus Plains. Present study identified 1037 cases of traumatic myiasis in the region during 2012-2015. Screw worm larvae were classified as 12 species: Chrysomya bezziana (Villeneuve), Chryomya megacephala (Fabricius), Chrysomya rufifacies (Macquart), Lucilia cuprina (Wiedemann), Lucilia sericata (Meigen), Lucilia illustris (Meigen), Lucilia porphyrina (Walker), Hemipyrellia ligguriens (Wiedemann), Calliphora vicina (Robineau-Desvoidy), Wohlfahrtia magnifica (Schiner), Sarcophaga crassipalpalis (Macquart), Sarchophaga species. Among these C. bezziana, L. cuprina and W. magnifica with approximately 882 case reports were the principal agents of traumatic myiasis. The species W. magnifica is a first report from Pakistan. In order to investigate spatial distribution of these dominant species we used MaxEnt niche model. Our results revealed a well-established occurrence of C. bezziana and L. cuprina in the four eco-regions while W. magnifica is currently contained in the Submontane Region. Several hot spot areas of infestation were detected all characterized by high human population density showing synanthropic nature of these species. Wohlfahrtia magnifica was excluded from Northern Montane Region with severe winters and Southern Indus Plains with harsh summers revealing that invasive species are initially sensitive to extreme of temperatures. Presence of L. cuprina in the wet areas of North Humid Belt (Maximum annual precipitation: 1641mm) depicted a moisture preference of the species. In perspective of changing climate and future predictions of severe events such as droughts and flooding in NWP, W. magnifica can potentially alter the species composition. Considering these findings in an eco-geographically dynamic region of Pakistan we predict that two factors (1) Growing human population (2) Climatic conditions, equally contribute to range
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PDEAR model prediction of Protea species in years 2070-2100
Guo, Danni; Guo, Renkuan; Midgley, Guy F.; Rebelo, A. G.
2009-10-01
Global warming and climate changes are changing the environment and therefore changing the distribution and behaviour of the plant species. Plant species often move and change their distributions as they find their original habitats are no longer suitable to their needs. It is therefore important to establish a statistical model to catch up the movement and patterns of the endangered species in order to effectively manage environmental protection under the inevitable biodiversity changes that are taking place. In this paper, we are focusing on the population category of rare Proteas that has an estimated population size from 1 to 10 per sample site, which is very small. We used the partial differential equation associated regression (PDEAR) model, which merges the partial differential equation theory, (statistical) linear model theory and random fuzzy variable theory together into a efficient small-sample oriented model, for the spatial pattern changing analysis. The regression component in a PDEAR model is in nature a special random fuzzy multivariate regression model. We developed a bivariate model for investigating the impacts from rainfall and temperature on the Protea species in average sense in the population size of 1 to 10, in the Cape Floristic Region, from 1992 to 2002, South Africa. Under same the average biodiversity structure assumptions, we explore the future spatial change patterns of Protea species in the population size of 1 to 10 with future (average) predicted rainfall and temperature. The spatial distribution and patterns are clearly will help us to explore global climate changing impacts on endangered species.
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Directory of Open Access Journals (Sweden)
Michael William Douglas
2016-10-01
Full Text Available WorldClim (Hijmans et al. 2005 has been the de-facto source of basic climatological analyses for most species distribution modeling research and conservation science applications because of its global coverage and fine (<1 km spatial resolution. However, it has been recognized since its development that there are limitations in data-poor regions, especially with regard to the precipitation analyses. Here we describe procedures to develop a satellite-based daytime cloudiness climatology that better reflects the variations in vegetation cover in many regions of the globe than do the WorldClim precipitation products. Moderate Resolution Imaging Spectroradiometer (MODIS imagery from the National Aeronautics and Space Administration (NASA Terra and Aqua sun-synchronous satellites have recently been used to develop multi-year climatologies of cloudiness. Several procedures exist for developing such climatologies. We first discuss a simple procedure that uses brightness thresholds to identify clouds. We compare these results with those from a more complex procedure: the MODIS Cloud Mask product, recently averaged into climatological products by Wilson and Jetz (2016. We discuss advantages and limitations of both approaches. We also speculate on further work that will be needed to improve the usefulness of these MODIS-based climatologies of cloudiness. Despite limitations of current MODIS-based climatology products, they have the potential to greatly improve our understanding of the distribution of biota across the globe. We show examples from oceanic islands and arid coastlines in the subtropics and tropics where the MODIS products should be of special value in predicting the observed vegetation cover. Some important applications of reliable climatologies based on MODIS imagery products will include 1 helping to restore long-degraded cloud-impacted environments; 2 improving estimations of the spatial distribution of cloud
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Directory of Open Access Journals (Sweden)
Obregón, R.
2016-03-01
Full Text Available Knowledge of the spatial distribution of rare or endangered species is of key importance to assess conservation status at different geographic scales and to develop conservation and recovery programs. In this paper we review and update the distribution of three species of Lycaenid butterflies in Andalusia (southern Spain: Cupido carswelli, C. lorquinii, and C. osiris. Cupido carswelli is endemic in south east Spain and is considered a vulnerable species in the Red Book of Invertebrates of Andalusia. Cupido lorquinii is an Iberian–Maghrebian endemism, found in the southern half of the Iberian peninsula. Cupido osiris, widely distributed in Europe and Central Asia, has its southern limit of distribution in Andalusia. We modeled the potential current distribution of these species in Andalusia, using Maxent. Their potential distribution was mainly conditioned by the presence of their host plants and, to a lesser extent, by climatic variables: rainfall during the warmest and coldest quarters of the year and annual mean temperature. AUC test values, sensitivity, and specificity for the three models were high, confirming the accuracy of the models and their high predictive values. We also modeled the potential future distributions of the three species under the climate change scenario A2a. Our results predict a significant reduction in the potential distribution for C. lorquinii —which has a wider distribution in Andalusia than the other two species— and for the more localized species, C. osiris and C. carswelli. This expected decline in the south of the Iberian peninsula highlights the pressing need to design and implement specific conservation plans for these species.
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Directory of Open Access Journals (Sweden)
F. Lombard
2011-04-01
Full Text Available We present an eco-physiological model reproducing the growth of eight foraminifer species (Neogloboquadrina pachyderma, Neogloboquadrina incompta, Neogloboquadrina dutertrei, Globigerina bulloides, Globigerinoides ruber, Globigerinoides sacculifer, Globigerinella siphonifera and Orbulina universa. By using the main physiological rates of foraminifers (nutrition, respiration, symbiotic photosynthesis, this model estimates their growth as a function of temperature, light availability, and food concentration. Model parameters are directly derived or calibrated from experimental observations and only the influence of food concentration (estimated via Chlorophyll-a concentration was calibrated against field observations. Growth rates estimated from the model show positive correlation with observed abundance from plankton net data suggesting close coupling between individual growth and population abundance. This observation was used to directly estimate potential abundance from the model-derived growth. Using satellite data, the model simulate the dominant foraminifer species with a 70.5% efficiency when compared to a data set of 576 field observations worldwide. Using outputs of a biogeochemical model of the global ocean (PISCES instead of satellite images as forcing variables gives also good results, but with lower efficiency (58.9%. Compared to core tops observations, the model also correctly reproduces the relative worldwide abundance and the diversity of the eight species when using either satellite data either PISCES results. This model allows prediction of the season and water depth at which each species has its maximum abundance potential. This offers promising perspectives for both an improved quantification of paleoceanographic reconstructions and for a better understanding of the foraminiferal role in the marine carbon cycle.
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Directory of Open Access Journals (Sweden)
Elizabeth A. Becker
2017-05-01
Full Text Available Managing marine species effectively requires spatially and temporally explicit knowledge of their density and distribution. Habitat-based density models, a type of species distribution model (SDM that uses habitat covariates to estimate species density and distribution patterns, are increasingly used for marine management and conservation because they provide a tool for assessing potential impacts (e.g., from fishery bycatch, ship strikes, anthropogenic sound over a variety of spatial and temporal scales. The abundance and distribution of many pelagic species exhibit substantial seasonal variability, highlighting the importance of predicting density specific to the season of interest. This is particularly true in dynamic regions like the California Current, where significant seasonal shifts in cetacean distribution have been documented at coarse scales. Finer scale (10 km habitat-based density models were previously developed for many cetacean species occurring in this region, but most models were limited to summer/fall. The objectives of our study were two-fold: (1 develop spatially-explicit density estimates for winter/spring to support management applications, and (2 compare model-predicted density and distribution patterns to previously developed summer/fall model results in the context of species ecology. We used a well-established Generalized Additive Modeling framework to develop cetacean SDMs based on 20 California Cooperative Oceanic Fisheries Investigations (CalCOFI shipboard surveys conducted during winter and spring between 2005 and 2015. Models were fit for short-beaked common dolphin (Delphinus delphis delphis, Dall's porpoise (Phocoenoides dalli, and humpback whale (Megaptera novaeangliae. Model performance was evaluated based on a variety of established metrics, including the percentage of explained deviance, ratios of observed to predicted density, and visual inspection of predicted and observed distributions. Final models were
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Mechanisms controlling the distribution of two invasive Bromus species
Directory of Open Access Journals (Sweden)
Olga Bykova
2014-03-01
Full Text Available In order to predict future range shifts for invasive species it is important to explore their ability to acclimate to the new environment and understand physiological and reproductive constraints controlling their distribution. My dissertation studied mechanisms by which temperature may affect the distribution of two aggressive plant invaders in North America, Bromus tectorum and Bromus rubens. I first evaluated winter freezing tolerance of Bromus species and demonstrated that the mechanism explaining their distinct northern range limits is different acquisition time of freezing tolerance. While B. rubens has a slower rate of freezing acclimation that leads to intolerance of sudden, late-autumn drops in temperature below -12°C, B. tectorum rapidly hardens and so is not impacted by the sudden onset of severe late-autumn cold. In addition, the analysis of male reproductive development and seed production showed that neither species produces seed at or above 36°C, due to complete pollen sterility, which might trigger climate-mediated range contractions at B. tectorum and B. rubens southern margins. Finally, a detailed gas-exchange analysis combined with biochemical modelling demonstrated that both species acclimate to a broad range of temperatures and photosynthetic response to temperature does not explain their current range separation.
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Gridded Species Distribution, Version 1: Global Amphibians Presence Grids
National Aeronautics and Space Administration — The Global Amphibians Presence Grids of the Gridded Species Distribution, Version 1 is a reclassified version of the original grids of amphibian species distribution...
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Directory of Open Access Journals (Sweden)
Matthew W. Luizza
2016-03-01
Full Text Available The threats posed by invasive plants span ecosystems and economies worldwide. Local knowledge of biological invasions has proven beneficial for invasive species research, but to date no work has integrated this knowledge with species distribution modeling for invasion risk assessments. In this study, we integrated pastoral knowledge with Maxent modeling to assess the suitable habitat and potential impacts of invasive Cryptostegia grandiflora Robx. Ex R.Br. (rubber vine in Ethiopia's Afar region. We conducted focus groups with seven villages across the Amibara and Awash-Fentale districts. Pastoral knowledge revealed the growing threat of rubber vine, which to date has received limited attention in Ethiopia, and whose presence in Afar was previously unknown to our team. Rubber vine occurrence points were collected in the field with pastoralists and processed in Maxent with MODIS-derived vegetation indices, topographic data, and anthropogenic variables. We tested model fit using a jackknife procedure and validated the final model with an independent occurrence data set collected through participatory mapping activities with pastoralists. A Multivariate Environmental Similarity Surface analysis revealed areas with novel environmental conditions for future targeted surveys. Model performance was evaluated using area under the receiver-operating characteristic curve (AUC and showed good fit across the jackknife models (average AUC = 0.80 and the final model (test AUC = 0.96. Our results reveal the growing threat rubber vine poses to Afar, with suitable habitat extending downstream of its current known location in the middle Awash River basin. Local pastoral knowledge provided important context for its rapid expansion due to acute changes in seasonality and habitat alteration, in addition to threats posed to numerous endemic tree species that provide critical provisioning ecosystem services. This work demonstrates the utility of integrating local
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Di Marco, Moreno; Buchanan, Graeme M; Szantoi, Zoltan; Holmgren, Milena; Grottolo Marasini, Gabriele; Gross, Dorit; Tranquilli, Sandra; Boitani, Luigi; Rondinini, Carlo
2014-01-01
Although conservation intervention has reversed the decline of some species, our success is outweighed by a much larger number of species moving towards extinction. Extinction risk modelling can identify correlates of risk and species not yet recognized to be threatened. Here, we use machine learning models to identify correlates of extinction risk in African terrestrial mammals using a set of variables belonging to four classes: species distribution state, human pressures, conservation response and species biology. We derived information on distribution state and human pressure from satellite-borne imagery. Variables in all four classes were identified as important predictors of extinction risk, and interactions were observed among variables in different classes (e.g. level of protection, human threats, species distribution ranges). Species biology had a key role in mediating the effect of external variables. The model was 90% accurate in classifying extinction risk status of species, but in a few cases the observed and modelled extinction risk mismatched. Species in this condition might suffer from an incorrect classification of extinction risk (hence require reassessment). An increased availability of satellite imagery combined with improved resolution and classification accuracy of the resulting maps will play a progressively greater role in conservation monitoring.
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Climatic zoning of chia (Salvia hispanica L. in Chile using a species distribution model
Directory of Open Access Journals (Sweden)
Daniela Cortés
2017-12-01
Full Text Available Salvia hispanica L., known as chia, is a plant species originally from tropical and subtropical Mesoamerica. It is economically important because its seeds produce omega-3, thus its demand has increased in Chile and internationally. As there is no commercial production in Chile, we investigated the places in the country where this species could be cultivated in order to satisfy at the least the national demand. The aim of the study was to quantify the main climatic requirements of chia and to produce a climatic aptitude map for chia cultivation in Chile. The methodology was based on the Maxent species distribution model. We used 78 georeferenced data points where chia is grown throughout the world, mostly from the GBIF database, along with raster climatic layers from the Worldclim project. We estimated the performance curves of annual precipitation and temperature along with their respective optimal and critical values, in analogy with the Ecocrop method. The maps used two scenarios for crops in different conditions, with and without irrigation. The results indicated that the intermediate depression and coastal edge of mainly the Arica y Parinacota, Tarapacá, Antofagasta and Atacama regions have optimum conditions for irrigated crops, but it would be impossible in rainfed conditions. We conclude that chia’s cultivation niche is reduced due to its tropical climate requirements; however, it can be cultivated under irrigation in northern Chile.
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Climatic zoning of chia (Salvia hispanica L.) in Chile using a species distribution model
International Nuclear Information System (INIS)
Cortés, D.; Silva, H.; Baginsky, C.; Morales, L.
2017-01-01
Salvia hispanica L., known as chia, is a plant species originally from tropical and subtropical Mesoamerica. It is economically important because its seeds produce omega-3, thus its demand has increased in Chile and internationally. As there is no commercial production in Chile, we investigated the places in the country where this species could be cultivated in order to satisfy at the least the national demand. The aim of the study was to quantify the main climatic requirements of chia and to produce a climatic aptitude map for chia cultivation in Chile. The methodology was based on the Maxent species distribution model. We used 78 georeferenced data points where chia is grown throughout the world, mostly from the GBIF database, along with raster climatic layers from the Worldclim project. We estimated the performance curves of annual precipitation and temperature along with their respective optimal and critical values, in analogy with the Ecocrop method. The maps used two scenarios for crops in different conditions, with and without irrigation. The results indicated that the intermediate depression and coastal edge of mainly the Arica y Parinacota, Tarapacá, Antofagasta and Atacama regions have optimum conditions for irrigated crops, but it would be impossible in rainfed conditions. We conclude that chia’s cultivation niche is reduced due to its tropical climate requirements; however, it can be cultivated under irrigation in northern Chile.
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Climatic zoning of chia (Salvia hispanica L.) in Chile using a species distribution model
Energy Technology Data Exchange (ETDEWEB)
Cortés, D.; Silva, H.; Baginsky, C.; Morales, L.
2017-07-01
Salvia hispanica L., known as chia, is a plant species originally from tropical and subtropical Mesoamerica. It is economically important because its seeds produce omega-3, thus its demand has increased in Chile and internationally. As there is no commercial production in Chile, we investigated the places in the country where this species could be cultivated in order to satisfy at the least the national demand. The aim of the study was to quantify the main climatic requirements of chia and to produce a climatic aptitude map for chia cultivation in Chile. The methodology was based on the Maxent species distribution model. We used 78 georeferenced data points where chia is grown throughout the world, mostly from the GBIF database, along with raster climatic layers from the Worldclim project. We estimated the performance curves of annual precipitation and temperature along with their respective optimal and critical values, in analogy with the Ecocrop method. The maps used two scenarios for crops in different conditions, with and without irrigation. The results indicated that the intermediate depression and coastal edge of mainly the Arica y Parinacota, Tarapacá, Antofagasta and Atacama regions have optimum conditions for irrigated crops, but it would be impossible in rainfed conditions. We conclude that chia’s cultivation niche is reduced due to its tropical climate requirements; however, it can be cultivated under irrigation in northern Chile.
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DEFF Research Database (Denmark)
Lombard, Fabien; Labeyrie, L.; Michel, E.
2011-01-01
We present an eco-physiological model reproducing the growth of eight foraminifer species (Neogloboquadrina pachyderma, Neogloboquadrina incompta, Neogloboquadrina dutertrei, Globigerina bulloides, Globigerinoides ruber, Globigerinoides sacculifer, Globigerinella siphonifera and Orbulina universa...... in the marine carbon cycle....... ocean (PISCES) instead of satellite images as forcing variables gives also good results, but with lower efficiency (58.9%). Compared to core tops observations, the model also correctly reproduces the relative worldwide abundance and the diversity of the eight species when using either satellite data...
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A biogeographical perspective on species abundance distributions
DEFF Research Database (Denmark)
Matthews, Thomas J.; Borges, Paulo A. V.; de Azevedo, Eduardo Brito
2017-01-01
It has become increasingly recognized that multiple processes can generate similar shapes of species abundance distributions (SADs), with the result that the fit of a given SAD model cannot unambiguously provide evidence in support of a given theory or model. An alternative approach to comparing...... the fit of different SAD models to data from a single site is to collect abundance data from a variety of sites, and then build models to analyse how different SAD properties (e.g. form, skewness) vary with different predictor variables. Such a biogeographical approach to SAD research is potentially very...... revealing, yet there has been a general lack of interest in SADs in the biogeographical literature. In this Perspective, we address this issue by highlighting findings of recent analyses of SADs that we consider to be of intrinsic biogeographical interest. We use arthropod data drawn from the Azorean...
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Rastogi, Achal
2017-08-15
Unlike terrestrial ecosystems where geographical isolation often leads to a restricted gene flow between species, genetic admixing in aquatic micro-eukaryotes is likely to be frequent. Diatoms inhabit marine ecosystems since the Mesozoic period and presently constitute one of the major primary producers in the world ocean. They are a highly diversified group of eukaryotic phytoplankton with estimates of up to 200,000 species. Since decades, Phaeodactylum tricornutum is used as a model diatom species to characterize the functional pathways, physiology and evolution of diatoms in general. In the current study, using whole genome sequencing of ten P. tricornutum strains, sampled at broad geospatial and temporal scales, we show a continuous dispersal and genetic admixing between geographically isolated strains. We also describe a very high level of heterozygosity and propose it to be a consequence of frequent ancestral admixture. Our finding that P. tricornutum sequences are plausibly detectable at low but broadly distributed levels in the world ocean further suggests that high admixing between geographically isolated strains may create a significant bottleneck, thus influencing their global abundance and distribution in nature. Finally, in an attempt to understand the functional implications of genetic diversity between different P. tricornutum ecotypes, we show the effects of domestication in inducing changes in the selection pressure on many genes and metabolic pathways. We propose these findings to have significant implications for understanding the genetic structure of diatom populations in nature and provide a framework to assess the genomic underpinnings of their ecological success.
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Rastogi, Achal; Deton-Cabanillas, Anne-Flore; Rocha Jimenez Vieira, Fabio; Veluchamy, Alaguraj; Cantrel, Catherine; Wang, Gaohong; Vanormelingen, Pieter; Bowler, Chris; Piganeau, Gwenael; Tirichine, Leila; Hu, Hanhua
2017-01-01
Unlike terrestrial ecosystems where geographical isolation often leads to a restricted gene flow between species, genetic admixing in aquatic micro-eukaryotes is likely to be frequent. Diatoms inhabit marine ecosystems since the Mesozoic period and presently constitute one of the major primary producers in the world ocean. They are a highly diversified group of eukaryotic phytoplankton with estimates of up to 200,000 species. Since decades, Phaeodactylum tricornutum is used as a model diatom species to characterize the functional pathways, physiology and evolution of diatoms in general. In the current study, using whole genome sequencing of ten P. tricornutum strains, sampled at broad geospatial and temporal scales, we show a continuous dispersal and genetic admixing between geographically isolated strains. We also describe a very high level of heterozygosity and propose it to be a consequence of frequent ancestral admixture. Our finding that P. tricornutum sequences are plausibly detectable at low but broadly distributed levels in the world ocean further suggests that high admixing between geographically isolated strains may create a significant bottleneck, thus influencing their global abundance and distribution in nature. Finally, in an attempt to understand the functional implications of genetic diversity between different P. tricornutum ecotypes, we show the effects of domestication in inducing changes in the selection pressure on many genes and metabolic pathways. We propose these findings to have significant implications for understanding the genetic structure of diatom populations in nature and provide a framework to assess the genomic underpinnings of their ecological success.
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Ratola, Nuno; Jiménez-Guerrero, Pedro
2015-04-01
A strategy designed to combine the features of field-based experiments and modelling approaches is presented in this work to assess air-vegetation distribution of benzo(a)pyrene (BaP) in the Iberian Peninsula (IP). Given the lack of simultaneous data in both environmental matrices, a methodology with two main steps was employed. First, evaluating the simulations with the chemistry transport model (CTM) WRF (Weather Research and Forecasting) + CHIMERE data against the European Monitoring and Evaluation Programme (EMEP) network, to test the aptitude of the CTM to replicate the respective atmospheric levels. Then, using modelled concentrations and a method to estimate air levels of BaP from biomonitoring data to compare the performance of different pine species (Pinus pinea, Pinus pinaster, Pinus nigra and Pinus halepensis) to describe the atmospheric evidences. The comparison of modelling vs. biomonitoring has a higher dependence on the location of the sampling points, rather than on the pine species, as some tend to overestimate and others to underestimate BaP concentrations, in most cases regardless of the season. The climatology of the canopy levels of BaP was successfully validated with the concentrations in pine needles (most biases below 26%), however, the model was unable to distinguish between species. This should be taken into consideration in future studies, as biases can rise up to 48%, especially in summer and autumn, the. The comparison with biomonitoring data showed a similar pattern, but with the best results in the warmer months.
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Directory of Open Access Journals (Sweden)
Jessica L. Beckham
2017-08-01
Full Text Available Texas is the second largest state in the United States of America, and the largest state in the contiguous USA at nearly 700,000 sq. km. Several Texas bumble bee species have shown evidence of declines in portions of their continental ranges, and conservation initiatives targeting these species will be most effective if species distributions are well established. To date, statewide bumble bee distributions for Texas have been inferred primarily from specimen records housed in natural history collections. To improve upon these maps, and help inform conservation decisions, this research aimed to (1 update existing Texas bumble bee presence databases to include recent (2007–2016 data from citizen science repositories and targeted field studies, (2 model statewide species distributions of the most common bumble bee species in Texas using MaxEnt, and (3 identify conservation target areas for the state that are most likely to contain habitat suitable for multiple declining species. The resulting Texas bumble bee database is comprised of 3,580 records, to include previously compiled museum records dating from 1897, recent field survey data, and vetted records from citizen science repositories. These data yielded an updated state species list that includes 11 species, as well as species distribution models (SDMs for the most common Texas bumble bee species, including two that have shown evidence of range-wide declines: B. fraternus (Smith, 1854 and B. pensylvanicus (DeGeer, 1773. Based on analyses of these models, we have identified conservation priority areas within the Texas Cross Timbers, Texas Blackland Prairies, and East Central Texas Plains ecoregions where suitable habitat for both B. fraternus and B. pensylvanicus are highly likely to co-occur.
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Distribution and diversity of twelve Curcuma species in China.
Zhang, Lanyue; Wei, Jingwen; Yang, Zhiwen; Chen, Feng; Xian, Qiqiu; Su, Ping; Pan, Wanyi; Zhang, Kun; Zheng, Xi; Du, Zhiyun
2018-02-01
Genus Curcuma a wild species presents an important source of valuable characters for improving the cultivated Curcuma varieties. Based on the collected germplasms, herbariums, field surveys and other literatures, the ecogeographical diversity of Genus Curcuma and its potential distributions under the present and future climate are analysed by DIVA-GIS. The results indicate Genus Curcuma is distributed over 17 provinces in China, and particularly abundant in Guangxi and Guangdong provinces. The simulated current distributions are close to the actual distribution regions. In the future climate, the suitable areas for four Curcuma species will be extended, while for other three species the regions will be significantly decreased, and thus these valuable resources need protecting.
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Maxent modelling for predicting the potential distribution of Thai Palms
DEFF Research Database (Denmark)
Tovaranonte, Jantrararuk; Barfod, Anders S.; Overgaard, Anne Blach
2011-01-01
on presence data. The aim was to identify potential hot spot areas, assess the determinants of palm distribution ranges, and provide a firmer knowledge base for future conservation actions. We focused on a relatively small number of climatic, environmental and spatial variables in order to avoid...... overprediction of species distribution ranges. The models with the best predictive power were found by calculating the area under the curve (AUC) of receiver-operating characteristic (ROC). Here, we provide examples of contrasting predicted species distribution ranges as well as a map of modeled palm diversity...
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Distribution of crayfish species in Hungarian waters
Mercédesz, Ludányi; Peeters, E.T.H.M.; Kiss, B.; Roessink, I.
2016-01-01
Three native crayfish species, i.e.~Astacus astacus, Astacus leptodactylus and Austropotamobius torrentium, occur in Hungary. Lately, however, non-indigenous crustaceans have also invaded the country Their most recent distribution and impact on the occurrences of the native species is not clear.
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Book review: A new view on the species abundance distribution
DeAngelis, Donald L.
2018-01-01
The sampled relative abundances of species of a taxonomic group, whether birds, trees, or moths, in a natural community at a particular place vary in a way that suggests a consistent underlying pattern, referred to as the species abundance distribution (SAD). Preston [1] conjectured that the numbers of species, plotted as a histogram of logarithmic abundance classes called octaves, seemed to fit a lognormal distribution; that is, the histograms look like normal distributions, although truncated on the left-hand, or low-species-abundance, end. Although other specific curves for the SAD have been proposed in the literature, Preston’s lognormal distribution is widely cited in textbooks and has stimulated attempts at explanation. An important aspect of Preston’s lognormal distribution is the ‘veil line’, a vertical line drawn exactly at the point of the left-hand truncation in the distribution, to the left of which would be species missing from the sample. Dewdney rejects the lognormal conjecture. Instead, starting with the long-recognized fact that the number of species sampled from a community, when plotted as histograms against population abundance, resembles an inverted J, he presents a mathematical description of an alternative that he calls the ‘J distribution’, a hyperbolic density function truncated at both ends. When multiplied by species richness, R, it becomes the SAD of the sample.
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Snyder, Marcia; Freeman, Mary C.; Purucker, S. Thomas; Pringle, Catherine M.
2016-01-01
Freshwater shrimps are an important biotic component of tropical ecosystems. However, they can have a low probability of detection when abundances are low. We sampled 3 of the most common freshwater shrimp species, Macrobrachium olfersii, Macrobrachium carcinus, and Macrobrachium heterochirus, and used occupancy modeling and logistic regression models to improve our limited knowledge of distribution of these cryptic species by investigating both local- and landscape-scale effects at La Selva Biological Station in Costa Rica. Local-scale factors included substrate type and stream size, and landscape-scale factors included presence or absence of regional groundwater inputs. Capture rates for 2 of the sampled species (M. olfersii and M. carcinus) were sufficient to compare the fit of occupancy models. Occupancy models did not converge for M. heterochirus, but M. heterochirus had high enough occupancy rates that logistic regression could be used to model the relationship between occupancy rates and predictors. The best-supported models for M. olfersii and M. carcinus included conductivity, discharge, and substrate parameters. Stream size was positively correlated with occupancy rates of all 3 species. High stream conductivity, which reflects the quantity of regional groundwater input into the stream, was positively correlated with M. olfersii occupancy rates. Boulder substrates increased occupancy rate of M. carcinus and decreased the detection probability of M. olfersii. Our models suggest that shrimp distribution is driven by factors that function at local (substrate and discharge) and landscape (conductivity) scales.
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Luke, Denneko; McLaren, Kurt
2018-05-01
In situ measurements of leaf level photosynthetic response to light were collected from seedlings of ten tree species from a tropical montane wet forest, the John Crow Mountains, Jamaica. A model-based recursive partitioning ('mob') algorithm was then used to identify species associations based on their fitted photosynthetic response curves. Leaf area dark respiration (RD) and light saturated maximum photosynthetic (Amax) rates were also used as 'mob' partitioning variables, to identify species associations based on seedling demographic patterns (from June 2007 to May 2010) following a hurricane (Aug. 2007) and the spatiotemporal distribution patterns of stems in 2006 and 2012. RD and Amax rates ranged from 1.14 to 2.02 μmol (CO2) m-2s-1 and 2.97-5.87 μmol (CO2) m-2s-1, respectively, placing the ten species in the range of intermediate shade tolerance. Several parsimonious species 'mob' groups were formed based on 1) interspecific differences among species response curves, 2) variations in post-hurricane seedling demographic trends and 3) RD rates and species spatiotemporal distribution patterns at aspects that are more or less exposed to hurricanes. The composition of parsimonious groupings based on photosynthetic curves was not concordant with the groups based on demographic trends but was partially concordant with the RD - species spatiotemporal distribution groups. Our results indicated that the influence of photosynthetic characteristics on demographic traits and species distributions was not straightforward. Rather, there was a complex pattern of interaction between ecophysiological and demographic traits, which determined species successional status, post-hurricane response and ultimately, species distribution at our study site.
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Directory of Open Access Journals (Sweden)
M. Corrie SCHOEMAN, F. P. D. (Woody COTTERILL, Peter J. TAYLOR, Ara MONADJEM
2013-06-01
Full Text Available We tested the prediction that at coarse spatial scales, variables associated with climate, energy, and productivity hypotheses should be better predictor(s of bat species richness than those associated with environmental heterogeneity. Distribution ranges of 64 bat species were estimated with niche-based models informed by 3629 verified museum specimens. The influence of environmental correlates on bat richness was assessed using ordinary least squares regression (OLS, simultaneous autoregressive models (SAR, conditional autoregressive models (CAR, spatial eigenvector-based filtering models (SEVM, and Classification and Regression Trees (CART. To test the assumption of stationarity, Geographically Weighted Regression (GWR was used. Bat species richness was highest in the eastern parts of southern Africa, particularly in central Zimbabwe and along the western border of Mozambique. We found support for the predictions of both the habitat heterogeneity and climate/productivity/ energy hypotheses, and as we expected, support varied among bat families and model selection. Richness patterns and predictors of Miniopteridae and Pteropodidae clearly differed from those of other bat families. Altitude range was the only independent variable that was significant in all models and it was most often the best predictor of bat richness. Standard coefficients of SAR and CAR models were similar to those of OLS models, while those of SEVM models differed. Although GWR indicated that the assumption of stationarity was violated, the CART analysis corroborated the findings of the curve-fitting models. Our results identify where additional data on current species ranges, and future conservation action and ecological work are needed [Current Zoology 59 (3: 279–293, 2013].
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Environmental niche divergence among three dune shrub sister species with parapatric distributions.
Chozas, Sergio; Chefaoui, Rosa M; Correia, Otília; Bonal, Raúl; Hortal, Joaquín
2017-05-01
The geographical distributions of species are constrained by their ecological requirements. The aim of this work was to analyse the effects of environmental conditions, historical events and biogeographical constraints on the diversification of the three species of the western Mediterranean shrub genus Stauracanthus , which have a parapatric distribution in the Iberian Peninsula. Ecological niche factor analysis and generalized linear models were used to measure the response of all Stauracanthus species to the environmental gradients and map their potential distributions in the Iberian Peninsula. The bioclimatic niche overlap between the three species was determined by using Schoener's index. The genetic differentiation of the Iberian and northern African populations of Stauracanthus species was characterized with GenalEx. The effects on genetic distances of the most important environmental drivers were assessed through Mantel tests and non-metric multidimensional scaling. The three Stauracanthus species show remarkably similar responses to climatic conditions. This supports the idea that all members of this recently diversified clade retain common adaptations to climate and consequently high levels of climatic niche overlap. This contrasts with the diverse edaphic requirements of Stauracanthus species. The populations of the S. genistoides-spectabilis clade grow on Miocene and Pliocene fine-textured sedimentary soils, whereas S. boivinii , the more genetically distant species, occurs on older and more coarse-textured sedimentary substrates. These patterns of diversification are largely consistent with a stochastic process of geographical range expansion and fragmentation coupled with niche evolution in the context of spatially complex environmental fluctuations. : The combined analysis of the distribution, realized environmental niche and phylogeographical relationships of parapatric species proposed in this work allows integration of the biogeographical
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Trenkel, V. M.; Huse, G.; MacKenzie, B. R.; Alvarez, P.; Arrizabalaga, H.; Castonguay, M.; Goñi, N.; Grégoire, F.; Hátún, H.; Jansen, T.; Jacobsen, J. A.; Lehodey, P.; Lutcavage, M.; Mariani, P.; Melvin, G. D.; Neilson, J. D.; Nøttestad, L.; Óskarsson, G. J.; Payne, M. R.; Richardson, D. E.; Senina, I.; Speirs, D. C.
2014-12-01
This paper reviews the current knowledge on the ecology of widely distributed pelagic fish stocks in the North Atlantic basin with emphasis on their role in the food web and the factors determining their relationship with the environment. We consider herring (Clupea harengus), mackerel (Scomber scombrus), capelin (Mallotus villosus), blue whiting (Micromesistius poutassou), and horse mackerel (Trachurus trachurus), which have distributions extending beyond the continental shelf and predominantly occur on both sides of the North Atlantic. We also include albacore (Thunnus alalunga), bluefin tuna (Thunnus thynnus), swordfish (Xiphias gladius), and blue marlin (Makaira nigricans), which, by contrast, show large-scale migrations at the basin scale. We focus on the links between life history processes and the environment, horizontal and vertical distribution, spatial structure and trophic role. Many of these species carry out extensive migrations from spawning grounds to nursery and feeding areas. Large oceanographic features such as the North Atlantic subpolar gyre play an important role in determining spatial distributions and driving variations in stock size. Given the large biomasses of especially the smaller species considered here, these stocks can exert significant top-down pressures on the food web and are important in supporting higher trophic levels. The review reveals commonalities and differences between the ecology of widely distributed pelagic fish in the NE and NW Atlantic basins, identifies knowledge gaps and modelling needs that the EURO-BASIN project attempts to address.
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Buckland, Steeves; Cole, Nik C; Aguirre-Gutiérrez, Jesús; Gallagher, Laura E; Henshaw, Sion M; Besnard, Aurélien; Tucker, Rachel M; Bachraz, Vishnu; Ruhomaun, Kevin; Harris, Stephen
2014-01-01
The invasion of the giant Madagascar day gecko Phelsuma grandis has increased the threats to the four endemic Mauritian day geckos (Phelsuma spp.) that have survived on mainland Mauritius. We had two main aims: (i) to predict the spatial distribution and overlap of P. grandis and the endemic geckos at a landscape level; and (ii) to investigate the effects of P. grandis on the abundance and risks of extinction of the endemic geckos at a local scale. An ensemble forecasting approach was used to predict the spatial distribution and overlap of P. grandis and the endemic geckos. We used hierarchical binomial mixture models and repeated visual estimate surveys to calculate the abundance of the endemic geckos in sites with and without P. grandis. The predicted range of each species varied from 85 km2 to 376 km2. Sixty percent of the predicted range of P. grandis overlapped with the combined predicted ranges of the four endemic geckos; 15% of the combined predicted ranges of the four endemic geckos overlapped with P. grandis. Levin's niche breadth varied from 0.140 to 0.652 between P. grandis and the four endemic geckos. The abundance of endemic geckos was 89% lower in sites with P. grandis compared to sites without P. grandis, and the endemic geckos had been extirpated at four of ten sites we surveyed with P. grandis. Species Distribution Modelling, together with the breadth metrics, predicted that P. grandis can partly share the equivalent niche with endemic species and survive in a range of environmental conditions. We provide strong evidence that smaller endemic geckos are unlikely to survive in sympatry with P. grandis. This is a cause of concern in both Mauritius and other countries with endemic species of Phelsuma.
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Directory of Open Access Journals (Sweden)
Steeves Buckland
Full Text Available The invasion of the giant Madagascar day gecko Phelsuma grandis has increased the threats to the four endemic Mauritian day geckos (Phelsuma spp. that have survived on mainland Mauritius. We had two main aims: (i to predict the spatial distribution and overlap of P. grandis and the endemic geckos at a landscape level; and (ii to investigate the effects of P. grandis on the abundance and risks of extinction of the endemic geckos at a local scale. An ensemble forecasting approach was used to predict the spatial distribution and overlap of P. grandis and the endemic geckos. We used hierarchical binomial mixture models and repeated visual estimate surveys to calculate the abundance of the endemic geckos in sites with and without P. grandis. The predicted range of each species varied from 85 km2 to 376 km2. Sixty percent of the predicted range of P. grandis overlapped with the combined predicted ranges of the four endemic geckos; 15% of the combined predicted ranges of the four endemic geckos overlapped with P. grandis. Levin's niche breadth varied from 0.140 to 0.652 between P. grandis and the four endemic geckos. The abundance of endemic geckos was 89% lower in sites with P. grandis compared to sites without P. grandis, and the endemic geckos had been extirpated at four of ten sites we surveyed with P. grandis. Species Distribution Modelling, together with the breadth metrics, predicted that P. grandis can partly share the equivalent niche with endemic species and survive in a range of environmental conditions. We provide strong evidence that smaller endemic geckos are unlikely to survive in sympatry with P. grandis. This is a cause of concern in both Mauritius and other countries with endemic species of Phelsuma.
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Gálvez, Rosa; Musella, Vicenzo; Descalzo, Miguel A; Montoya, Ana; Checa, Rocío; Marino, Valentina; Martín, Oihane; Cringoli, Giuseppe; Rinaldi, Laura; Miró, Guadalupe
2017-09-19
The cat flea, Ctenocephalides felis, is the most prevalent flea species detected on dogs and cats in Europe and other world regions. The status of flea infestation today is an evident public health concern because of their cosmopolitan distribution and the flea-borne diseases transmission. This study determines the spatial distribution of the cat flea C. felis infesting dogs in Spain. Using geospatial tools, models were constructed based on entomological data collected from dogs during the period 2013-2015. Bioclimatic zones, covering broad climate and vegetation ranges, were surveyed in relation to their size. The models builded were obtained by negative binomial regression of several environmental variables to show impacts on C. felis infestation prevalence: land cover, bioclimatic zone, mean summer and autumn temperature, mean summer rainfall, distance to urban settlement and normalized difference vegetation index. In the face of climate change, we also simulated the future distributions of C. felis for the global climate model (GCM) "GFDL-CM3" and for the representative concentration pathway RCP45, which predicts their spread in the country. Predictive models for current climate conditions indicated the widespread distribution of C. felis throughout Spain, mainly across the central northernmost zone of the mainland. Under predicted conditions of climate change, the risk of spread was slightly greater, especially in the north and central peninsula, than for the current situation. The data provided will be useful for local veterinarians to design effective strategies against flea infestation and the pathogens transmitted by these arthropods.
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Directory of Open Access Journals (Sweden)
Katharina Homburg
Full Text Available Classical glacial refugia such as the southern European peninsulas were important for species survival during glacial periods and acted as sources of post-glacial colonisation processes. Only recently, some studies have provided evidence for glacial refugia north of the southern European peninsulas. In the present study, we combined species distribution models (SDMs with phylogeographic analyses (using mitochondrial DNA = mtDNA to investigate if the cold-adapted, stenotopic and flightless ground beetle species, Carabus irregularis, survived the Last Glacial Maximum (LGM in classical and/or other refugia. SDMs (for both a western European and for a Carpathian subgroup were calculated with MAXENT on the basis of 645 species records to predict current and past distribution patterns. Two mtDNA loci (CO1 and ND5, concatenated sequence length: 1785 bp were analyzed from 91 C. irregularis specimens to reconstruct the phylogeography of Central and eastern European populations and to estimate divergence times of the given lineages. Strong intra-specific genetic differentiation (inter-clade ΦST values ranged from 0.92 to 0.99 implied long-term isolation of major clades and subsclades. The high divergence between the nominate subspecies and the Carpathian subspecies C. i. montandoni points to two independent species rather than subspecies (K-2P distance 0.042 ± 0.004; supposed divergence of the maternal lineages dated back 1.6 to 2.5 million years BP differing not only morphologically but also genetically and ecologically from each other. The SDMs also inferred classical as well as other refugia for C. irregularis, especially north of the Alps, in southeastern Europe and in the Carpathians. The coincidences between the results of both methods confirm the assumption of multiple glacial refugia for the studied species and the usefulness of combining methodological approaches for the understanding of the history of low-dispersal insect species.
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Niu, Yu Jie; Yang, Si Wei; Wang, Gui Zhen; Liu, Li; Du, Guo Zhen; Hua, Li Min
2017-12-01
The research selected the alpine meadow located in the northeastern margin of the Qinghai-Tibet Plateau to study the changes of vegetation community and soil properties under different grazing intensities, as well as the quantitative relation between the distribution patterns of plant species and the physical and chemical properties of soil. The results showed that the grazing caused the differentiation of the initial vegetation community with the dominant plants, Elymus nutans and Stipa grandis. In the plots with high and low grazing intensities, the dominant plants had changed to Kobresia humilis and Melissitus ruthenica, and E. nutans and Poa crymophila, respectively. With the increase of grazing intensity, the plant richness, importance value and biomass were significantly decreased. The sequence of plant species importance value in each plot against grazing intensity could be fitted by a logarithmic model. The number of required plant species was reduced while the importance value of the remaining plant species accounted for 50% of the importance value in the whole vegetation community. The available P, available K, soil compaction, soil water content, stable infiltration rate and large aggregate index were significantly changed with grazing intensity, however, the changes were different. The CCA ordination showed that the soil compaction was the key factor affecting the distribution pattern of the plant species under grazing. The variance decomposition indicated that the soil factors together explained 30.5% of the distribution of the plant species, in particular the soil physical properties alone explained 22.8% of the distribution of the plant species, which had the highest rate of contribution to the plant species distribution. The soil physical properties affected the distribution pattern of plant species on grazed alpine meadow.
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Directory of Open Access Journals (Sweden)
Mark A Hayes
Full Text Available Understanding seasonal distribution and movement patterns of animals that migrate long distances is an essential part of monitoring and conserving their populations. Compared to migratory birds and other more conspicuous migrants, we know very little about the movement patterns of many migratory bats. Hoary bats (Lasiurus cinereus, a cryptic, wide-ranging, long-distance migrant, comprise a substantial proportion of the tens to hundreds of thousands of bat fatalities estimated to occur each year at wind turbines in North America. We created seasonally-dynamic species distribution models (SDMs from 2,753 museum occurrence records collected over five decades in North America to better understand the seasonal geographic distributions of hoary bats. We used 5 SDM approaches: logistic regression, multivariate adaptive regression splines, boosted regression trees, random forest, and maximum entropy and consolidated outputs to generate ensemble maps. These maps represent the first formal hypotheses for sex- and season-specific hoary bat distributions. Our results suggest that North American hoary bats winter in regions with relatively long growing seasons where temperatures are moderated by proximity to oceans, and then move to the continental interior for the summer. SDMs suggested that hoary bats are most broadly distributed in autumn-the season when they are most susceptible to mortality from wind turbines; this season contains the greatest overlap between potentially suitable habitat and wind energy facilities. Comparing wind-turbine fatality data to model outputs could test many predictions, such as 'risk from turbines is highest in habitats between hoary bat summering and wintering grounds'. Although future field studies are needed to validate the SDMs, this study generated well-justified and testable hypotheses of hoary bat migration patterns and seasonal distribution.
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Hayes, Mark A; Cryan, Paul M; Wunder, Michael B
2015-01-01
Understanding seasonal distribution and movement patterns of animals that migrate long distances is an essential part of monitoring and conserving their populations. Compared to migratory birds and other more conspicuous migrants, we know very little about the movement patterns of many migratory bats. Hoary bats (Lasiurus cinereus), a cryptic, wide-ranging, long-distance migrant, comprise a substantial proportion of the tens to hundreds of thousands of bat fatalities estimated to occur each year at wind turbines in North America. We created seasonally-dynamic species distribution models (SDMs) from 2,753 museum occurrence records collected over five decades in North America to better understand the seasonal geographic distributions of hoary bats. We used 5 SDM approaches: logistic regression, multivariate adaptive regression splines, boosted regression trees, random forest, and maximum entropy and consolidated outputs to generate ensemble maps. These maps represent the first formal hypotheses for sex- and season-specific hoary bat distributions. Our results suggest that North American hoary bats winter in regions with relatively long growing seasons where temperatures are moderated by proximity to oceans, and then move to the continental interior for the summer. SDMs suggested that hoary bats are most broadly distributed in autumn-the season when they are most susceptible to mortality from wind turbines; this season contains the greatest overlap between potentially suitable habitat and wind energy facilities. Comparing wind-turbine fatality data to model outputs could test many predictions, such as 'risk from turbines is highest in habitats between hoary bat summering and wintering grounds'. Although future field studies are needed to validate the SDMs, this study generated well-justified and testable hypotheses of hoary bat migration patterns and seasonal distribution.
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Hayes, Mark A.; Cryan, Paul M.; Wunder, Michael B.
2015-01-01
Understanding seasonal distribution and movement patterns of animals that migrate long distances is an essential part of monitoring and conserving their populations. Compared to migratory birds and other more conspicuous migrants, we know very little about the movement patterns of many migratory bats. Hoary bats (Lasiurus cinereus), a cryptic, wide-ranging, long-distance migrant, comprise a substantial proportion of the tens to hundreds of thousands of bat fatalities estimated to occur each year at wind turbines in North America. We created seasonally-dynamic species distribution models (SDMs) from 2,753 museum occurrence records collected over five decades in North America to better understand the seasonal geographic distributions of hoary bats. We used 5 SDM approaches: logistic regression, multivariate adaptive regression splines, boosted regression trees, random forest, and maximum entropy and consolidated outputs to generate ensemble maps. These maps represent the first formal hypotheses for sex- and season-specific hoary bat distributions. Our results suggest that North American hoary bats winter in regions with relatively long growing seasons where temperatures are moderated by proximity to oceans, and then move to the continental interior for the summer. SDMs suggested that hoary bats are most broadly distributed in autumn—the season when they are most susceptible to mortality from wind turbines; this season contains the greatest overlap between potentially suitable habitat and wind energy facilities. Comparing wind-turbine fatality data to model outputs could test many predictions, such as ‘risk from turbines is highest in habitats between hoary bat summering and wintering grounds’. Although future field studies are needed to validate the SDMs, this study generated well-justified and testable hypotheses of hoary bat migration patterns and seasonal distribution.
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Lauria, V; Garofalo, G; Fiorentino, F; Massi, D; Milisenda, G; Piraino, S; Russo, T; Gristina, M
2017-08-14
Deep-sea coral assemblages are key components of marine ecosystems that generate habitats for fish and invertebrate communities and act as marine biodiversity hot spots. Because of their life history traits, deep-sea corals are highly vulnerable to human impacts such as fishing. They are an indicator of vulnerable marine ecosystems (VMEs), therefore their conservation is essential to preserve marine biodiversity. In the Mediterranean Sea deep-sea coral habitats are associated with commercially important crustaceans, consequently their abundance has dramatically declined due to the effects of trawling. Marine spatial planning is required to ensure that the conservation of these habitats is achieved. Species distribution models were used to investigate the distribution of two critically endangered octocorals (Funiculina quadrangularis and Isidella elongata) in the central Mediterranean as a function of environmental and fisheries variables. Results show that both species exhibit species-specific habitat preferences and spatial patterns in response to environmental variables, but the impact of trawling on their distribution differed. In particular F. quadrangularis can overlap with fishing activities, whereas I. elongata occurs exclusively where fishing is low or absent. This study represents the first attempt to identify key areas for the protection of soft and compact mud VMEs in the central Mediterranean Sea.
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Directory of Open Access Journals (Sweden)
L Valeria Oppliger
Full Text Available A major determinant of the geographic distribution of a species is expected to be its physiological response to changing abiotic variables over its range. The range of a species often corresponds to the geographic extent of temperature regimes the organism can physiologically tolerate. Many species have very distinct life history stages that may exhibit different responses to environmental factors. In this study we emphasized the critical role of the haploid microscopic stage (gametophyte of the life cycle to explain the difference of edge distribution of two related kelp species. Lessonia nigrescens was recently identified as two cryptic species occurring in parapatry along the Chilean coast: one located north and the other south of a biogeographic boundary at latitude 29-30°S. Six life history traits from microscopic stages were identified and estimated under five treatments of temperature in eight locations distributed along the Chilean coast in order to (1 estimate the role of temperature in the present distribution of the two cryptic L. nigrescens species, (2 compare marginal populations to central populations of the two cryptic species. In addition, we created a periodic matrix model to estimate the population growth rate (λ at the five temperature treatments. Differential tolerance to temperature was demonstrated between the two species, with the gametophytes of the Northern species being more tolerant to higher temperatures than gametophytes from the south. Second, the two species exhibited different life history strategies with a shorter haploid phase in the Northern species contrasted with considerable vegetative growth in the Southern species haploid stage. These results provide strong ecological evidence for the differentiation process of the two cryptic species and show local adaptation of the life cycle at the range limits of the distribution. Ecological and evolutionary implications of these findings are discussed.
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A Bayesian Supertree Model for Genome-Wide Species Tree Reconstruction
De Oliveira Martins, Leonardo; Mallo, Diego; Posada, David
2016-01-01
Current phylogenomic data sets highlight the need for species tree methods able to deal with several sources of gene tree/species tree incongruence. At the same time, we need to make most use of all available data. Most species tree methods deal with single processes of phylogenetic discordance, namely, gene duplication and loss, incomplete lineage sorting (ILS) or horizontal gene transfer. In this manuscript, we address the problem of species tree inference from multilocus, genome-wide data sets regardless of the presence of gene duplication and loss and ILS therefore without the need to identify orthologs or to use a single individual per species. We do this by extending the idea of Maximum Likelihood (ML) supertrees to a hierarchical Bayesian model where several sources of gene tree/species tree disagreement can be accounted for in a modular manner. We implemented this model in a computer program called guenomu whose inputs are posterior distributions of unrooted gene tree topologies for multiple gene families, and whose output is the posterior distribution of rooted species tree topologies. We conducted extensive simulations to evaluate the performance of our approach in comparison with other species tree approaches able to deal with more than one leaf from the same species. Our method ranked best under simulated data sets, in spite of ignoring branch lengths, and performed well on empirical data, as well as being fast enough to analyze relatively large data sets. Our Bayesian supertree method was also very successful in obtaining better estimates of gene trees, by reducing the uncertainty in their distributions. In addition, our results show that under complex simulation scenarios, gene tree parsimony is also a competitive approach once we consider its speed, in contrast to more sophisticated models. PMID:25281847
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A Bayesian Supertree Model for Genome-Wide Species Tree Reconstruction.
De Oliveira Martins, Leonardo; Mallo, Diego; Posada, David
2016-05-01
Current phylogenomic data sets highlight the need for species tree methods able to deal with several sources of gene tree/species tree incongruence. At the same time, we need to make most use of all available data. Most species tree methods deal with single processes of phylogenetic discordance, namely, gene duplication and loss, incomplete lineage sorting (ILS) or horizontal gene transfer. In this manuscript, we address the problem of species tree inference from multilocus, genome-wide data sets regardless of the presence of gene duplication and loss and ILS therefore without the need to identify orthologs or to use a single individual per species. We do this by extending the idea of Maximum Likelihood (ML) supertrees to a hierarchical Bayesian model where several sources of gene tree/species tree disagreement can be accounted for in a modular manner. We implemented this model in a computer program called guenomu whose inputs are posterior distributions of unrooted gene tree topologies for multiple gene families, and whose output is the posterior distribution of rooted species tree topologies. We conducted extensive simulations to evaluate the performance of our approach in comparison with other species tree approaches able to deal with more than one leaf from the same species. Our method ranked best under simulated data sets, in spite of ignoring branch lengths, and performed well on empirical data, as well as being fast enough to analyze relatively large data sets. Our Bayesian supertree method was also very successful in obtaining better estimates of gene trees, by reducing the uncertainty in their distributions. In addition, our results show that under complex simulation scenarios, gene tree parsimony is also a competitive approach once we consider its speed, in contrast to more sophisticated models. © The Author(s) 2014. Published by Oxford University Press on behalf of the Society of Systematic Biologists.
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Biotic Interactions Shape the Ecological Distributions of Staphylococcus Species.
Kastman, Erik K; Kamelamela, Noelani; Norville, Josh W; Cosetta, Casey M; Dutton, Rachel J; Wolfe, Benjamin E
2016-10-18
Many metagenomic sequencing studies have observed the presence of closely related bacterial species or genotypes in the same microbiome. Previous attempts to explain these patterns of microdiversity have focused on the abiotic environment, but few have considered how biotic interactions could drive patterns of microbiome diversity. We dissected the patterns, processes, and mechanisms shaping the ecological distributions of three closely related Staphylococcus species in cheese rind biofilms. Paradoxically, the most abundant species (S. equorum) is the slowest colonizer and weakest competitor based on growth and competition assays in the laboratory. Through in vitro community reconstructions, we determined that biotic interactions with neighboring fungi help resolve this paradox. Species-specific stimulation of the poor competitor by fungi of the genus Scopulariopsis allows S. equorum to dominate communities in vitro as it does in situ Results of comparative genomic and transcriptomic experiments indicate that iron utilization pathways, including a homolog of the S. aureus staphyloferrin B siderophore operon pathway, are potential molecular mechanisms underlying Staphylococcus-Scopulariopsis interactions. Our integrated approach demonstrates that fungi can structure the ecological distributions of closely related bacterial species, and the data highlight the importance of bacterium-fungus interactions in attempts to design and manipulate microbiomes. Decades of culture-based studies and more recent metagenomic studies have demonstrated that bacterial species in agriculture, medicine, industry, and nature are unevenly distributed across time and space. The ecological processes and molecular mechanisms that shape these distributions are not well understood because it is challenging to connect in situ patterns of diversity with mechanistic in vitro studies in the laboratory. Using tractable cheese rind biofilms and a focus on coagulase-negative staphylococcus (CNS
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The integration of DNA-based identification methods into bioassessments could result in more accurate representations of species distributions and species-habitat relationships. DNA-based approaches may be particularly informative for tracking the distributions of rare and/or inv...
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Carlo, Michael A; Riddell, Eric A; Levy, Ofir; Sears, Michael W
2018-01-01
The capacity to tolerate climate change often varies across ontogeny in organisms with complex life cycles. Recently developed species distribution models incorporate traits across life stages; however, these life-cycle models primarily evaluate effects of lethal change. Here, we examine impacts of recurrent sublethal warming on development and survival in ecological projections of climate change. We reared lizard embryos in the laboratory under temperature cycles that simulated contemporary conditions and warming scenarios. We also artificially warmed natural nests to mimic laboratory treatments. In both cases, recurrent sublethal warming decreased embryonic survival and hatchling sizes. Incorporating survivorship results into a mechanistic species distribution model reduced annual survival by up to 24% compared to models that did not incorporate sublethal warming. Contrary to models without sublethal effects, our model suggests that modest increases in developmental temperatures influence species ranges due to effects on survivorship. © 2017 John Wiley & Sons Ltd/CNRS.
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Wilson, William G; Lundberg, Per
2004-09-22
Theoretical interest in the distributions of species abundances observed in ecological communities has focused recently on the results of models that assume all species are identical in their interactions with one another, and rely upon immigration and speciation to promote coexistence. Here we examine a one-trophic level system with generalized species interactions, including species-specific intraspecific and interspecific interaction strengths, and density-independent immigration from a regional species pool. Comparisons between results from numerical integrations and an approximate analytic calculation for random communities demonstrate good agreement, and both approaches yield abundance distributions of nearly arbitrary shape, including bimodality for intermediate immigration rates.
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The origin and distribution of neotropical species of Campylopus
Frahm, Jan-Peter
1990-01-01
Of the 65 species of Campylopus known from tropical America, 33 are andine in distribution, 16 are found only in SE Brazil, 8 have wide ranges through Central and South America, 3 species are disjunct in SE-North America and Brazil, 3 are confined to the Caribbean and one species belongs to the circum-pacific and one to the tethyan element. For different parts of the Neotropics, the composition of phytogeographical elements is calculated. For the first time, bryophyte distributions are compar...
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Porretta, Daniele; Mastrantonio, Valentina; Amendolia, Sara; Gaiarsa, Stefano; Epis, Sara; Genchi, Claudio; Bandi, Claudio; Otranto, Domenico; Urbanelli, Sandra
2013-09-19
Global climate change can seriously impact on the epidemiological dynamics of vector-borne diseases. In this study we investigated how future climatic changes could affect the climatic niche of Ixodes ricinus (Acari, Ixodida), among the most important vectors of pathogens of medical and veterinary concern in Europe. Species Distribution Modelling (SDM) was used to reconstruct the climatic niche of I. ricinus, and to project it into the future conditions for 2050 and 2080, under two scenarios: a continuous human demographic growth and a severe increase of gas emissions (scenario A2), and a scenario that proposes lower human demographic growth than A2, and a more sustainable gas emissions (scenario B2). Models were reconstructed using the algorithm of "maximum entropy", as implemented in the software Maxent 3.3.3e; 4,544 occurrence points and 15 bioclimatic variables were used. In both scenarios an increase of climatic niche of about two times greater than the current area was predicted as well as a higher climatic suitability under the scenario B2 than A2. Such an increase occurred both in a latitudinal and longitudinal way, including northern Eurasian regions (e.g. Sweden and Russia), that were previously unsuitable for the species. Our models are congruent with the predictions of range expansion already observed in I. ricinus at a regional scale and provide a qualitative and quantitative assessment of the future climatically suitable areas for I. ricinus at a continental scale. Although the use of SDM at a higher resolution should be integrated by a more refined analysis of further abiotic and biotic data, the results presented here suggest that under future climatic scenarios most of the current distribution area of I. ricinus could remain suitable and significantly increase at a continental geographic scale. Therefore disease outbreaks of pathogens transmitted by this tick species could emerge in previous non-endemic geographic areas. Further studies will
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Nattier, Romain; Grandcolas, Philippe; Pellens, Roseli; Jourdan, Hervé; Couloux, Arnaud; Poulain, Simon; Robillard, Tony
2013-01-01
The grasshopper genus Caledonula, endemic to New Caledonia, was studied to understand the evolution of species distributions in relation to climate and soil types. Based on a comprehensive sampling of 80 locations throughout the island, the genus was represented by five species, four of which are new to science, of which three are described here. All the species have limited distributions in New Caledonia. Bioclimatic niche modelling shows that all the species were found in association with a wet climate and reduced seasonality, explaining their restriction to the southern half of the island. The results suggest that the genus was ancestrally constrained by seasonality. A molecular phylogeny was reconstructed using two mitochondrial and two nuclear markers. The partially resolved tree showed monophyly of the species found on metalliferous soils, and molecular dating indicated a rather recent origin for the genus. Adaptation to metalliferous soils is suggested by both morphological changes and radiation on these soils. The genus Caledonula is therefore a good model to understand the origin of microendemism in the context of recent and mixed influences of climate and soil type.
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Marshall, Leon; Carvalheiro, Luísa G; Aguirre-Gutiérrez, Jesús; Bos, Merijn; de Groot, G Arjen; Kleijn, David; Potts, Simon G; Reemer, Menno; Roberts, Stuart; Scheper, Jeroen; Biesmeijer, Jacobus C
2015-10-01
Species distribution models (SDM) are increasingly used to understand the factors that regulate variation in biodiversity patterns and to help plan conservation strategies. However, these models are rarely validated with independently collected data and it is unclear whether SDM performance is maintained across distinct habitats and for species with different functional traits. Highly mobile species, such as bees, can be particularly challenging to model. Here, we use independent sets of occurrence data collected systematically in several agricultural habitats to test how the predictive performance of SDMs for wild bee species depends on species traits, habitat type, and sampling technique. We used a species distribution modeling approach parametrized for the Netherlands, with presence records from 1990 to 2010 for 193 Dutch wild bees. For each species, we built a Maxent model based on 13 climate and landscape variables. We tested the predictive performance of the SDMs with independent datasets collected from orchards and arable fields across the Netherlands from 2010 to 2013, using transect surveys or pan traps. Model predictive performance depended on species traits and habitat type. Occurrence of bee species specialized in habitat and diet was better predicted than generalist bees. Predictions of habitat suitability were also more precise for habitats that are temporally more stable (orchards) than for habitats that suffer regular alterations (arable), particularly for small, solitary bees. As a conservation tool, SDMs are best suited to modeling rarer, specialist species than more generalist and will work best in long-term stable habitats. The variability of complex, short-term habitats is difficult to capture in such models and historical land use generally has low thematic resolution. To improve SDMs' usefulness, models require explanatory variables and collection data that include detailed landscape characteristics, for example, variability of crops and
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Directory of Open Access Journals (Sweden)
Leigh G Torres
Full Text Available Species distribution models (SDMs are increasingly applied in conservation management to predict suitable habitat for poorly known populations. High predictive performance of SDMs is evident in validations performed within the model calibration area (interpolation, but few studies have assessed SDM transferability to novel areas (extrapolation, particularly across large spatial scales or pelagic ecosystems. We performed rigorous SDM validation tests on distribution data from three populations of a long-ranging marine predator, the grey petrel Procellaria cinerea, to assess model transferability across the Southern Hemisphere (25-65°S. Oceanographic data were combined with tracks of grey petrels from two remote sub-Antarctic islands (Antipodes and Kerguelen using boosted regression trees to generate three SDMs: one for each island population, and a combined model. The predictive performance of these models was assessed using withheld tracking data from within the model calibration areas (interpolation, and from a third population, Marion Island (extrapolation. Predictive performance was assessed using k-fold cross validation and point biserial correlation. The two population-specific SDMs included the same predictor variables and suggested birds responded to the same broad-scale oceanographic influences. However, all model validation tests, including of the combined model, determined strong interpolation but weak extrapolation capabilities. These results indicate that habitat use reflects both its availability and bird preferences, such that the realized distribution patterns differ for each population. The spatial predictions by the three SDMs were compared with tracking data and fishing effort to demonstrate the conservation pitfalls of extrapolating SDMs outside calibration regions. This exercise revealed that SDM predictions would have led to an underestimate of overlap with fishing effort and potentially misinformed bycatch mitigation
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Megna, Yoandri S; Sánchez-Fernández, David
2014-01-10
A new species, Desmopachria andreae sp. n. is described from Cuba. Diagnostic characters including illustrations of male genitalia are provided and illustrated for the five species of the genus occurring on the island. For these five species both a simple key to adults and maps of their known distribution in Cuba are also provided. Using a Maximun Entropy method (MaxEnt), a distribution model was developed for D. andreae sp.n. Based on the model's predictions, this species has a higher probability of occurring in high altitude forests (above 1000 m a.s.l.), characterised by relatively low temperatures especially during the hottest and wettest seasons, specifically, the mountainous areas of the Macizo de Guamuhaya (Central Cuba), Sierra Maestra (S Cuba) and Nipe-Sagua-Baracoa (NE Cuba). In some of these areas the species has not yet been recorded, and should be searched for in future field surveys.
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A Species Distribution Modeling Informed Conservation Assessment of Bog Spicebush
2016-09-14
Adhikari, Barik , and Upadhaya 2012). These results sug- gest there are many locations potentially suitable for (re)introducing L. subcoriacea across its...References Adhikari, D., S. K. Barik , K. Upadhaya. 2012. Habitat distribution modelling for reintroduction of Ilex khasiana Purk., a critically
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Wan, Ji-Zhong; Wang, Chun-Jing; Yu, Fei-Hai
2017-11-01
Human footprint and soil variability may be important in shaping the spread of invasive plant species (IPS). However, until now, there is little knowledge on how human footprint and soil variability affect the potential distribution of IPS in different biomes. We used Maxent modeling to project the potential distribution of 29 IPS with wide distributions and long introduction histories in China based on various combinations of climatic correlates, soil characteristics and human footprint. Then, we evaluated the relative importance of each type of environmental variables (climate, soil and human footprint) as well as the difference in range and similarity of the potential distribution of IPS between different biomes. Human footprint and soil variables contributed to the prediction of the potential distribution of IPS, and different types of biomes had varying responses and degrees of impacts from the tested variables. Human footprint and soil variability had the highest tendency to increase the potential distribution of IPS in Montane Grasslands and Shrublands. We propose to integrate the assessment in impacts of human footprint and soil variability on the potential distribution of IPS in different biomes into the prevention and control of plant invasion.
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Kelling, S.
2017-12-01
The goal of Biodiversity research is to identify, explain, and predict why a species' distribution and abundance vary through time, space, and with features of the environment. Measuring these patterns and predicting their responses to change are not exercises in curiosity. Today, they are essential tasks for understanding the profound effects that humans have on earth's natural systems, and for developing science-based environmental policies. To gain insight about species' distribution patterns requires studying natural systems at appropriate scales, yet studies of ecological processes continue to be compromised by inadequate attention to scale issues. How spatial and temporal patterns in nature change with scale often reflects fundamental laws of physics, chemistry, or biology, and we can identify such basic, governing laws only by comparing patterns over a wide range of scales. This presentation will provide several examples that integrate bird observations made by volunteers, with NASA Earth Imagery using Big Data analysis techniques to analyze the temporal patterns of bird occurrence across scales—from hemisphere-wide views of bird distributions to the impact of powerful city lights on bird migration.
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Meynard, Christine N; Migeon, Alain; Navajas, Maria
2013-01-01
Many species are shifting their distributions due to climate change and to increasing international trade that allows dispersal of individuals across the globe. In the case of agricultural pests, such range shifts may heavily impact agriculture. Species distribution modelling may help to predict potential changes in pest distributions. However, these modelling strategies are subject to large uncertainties coming from different sources. Here we used the case of the tomato red spider mite (Tetranychus evansi), an invasive pest that affects some of the most important agricultural crops worldwide, to show how uncertainty may affect forecasts of the potential range of the species. We explored three aspects of uncertainty: (1) species prevalence; (2) modelling method; and (3) variability in environmental responses between mites belonging to two invasive clades of T. evansi. Consensus techniques were used to forecast the potential range of the species under current and two different climate change scenarios for 2080, and variance between model projections were mapped to identify regions of high uncertainty. We revealed large predictive variations linked to all factors, although prevalence had a greater influence than the statistical model once the best modelling strategies were selected. The major areas threatened under current conditions include tropical countries in South America and Africa, and temperate regions in North America, the Mediterranean basin and Australia. Under future scenarios, the threat shifts towards northern Europe and some other temperate regions in the Americas, whereas tropical regions in Africa present a reduced risk. Analysis of niche overlap suggests that the current differential distribution of mites of the two clades of T. evansi can be partially attributed to environmental niche differentiation. Overall this study shows how consensus strategies and analysis of niche overlap can be used jointly to draw conclusions on invasive threat
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Directory of Open Access Journals (Sweden)
Christine N Meynard
Full Text Available Many species are shifting their distributions due to climate change and to increasing international trade that allows dispersal of individuals across the globe. In the case of agricultural pests, such range shifts may heavily impact agriculture. Species distribution modelling may help to predict potential changes in pest distributions. However, these modelling strategies are subject to large uncertainties coming from different sources. Here we used the case of the tomato red spider mite (Tetranychus evansi, an invasive pest that affects some of the most important agricultural crops worldwide, to show how uncertainty may affect forecasts of the potential range of the species. We explored three aspects of uncertainty: (1 species prevalence; (2 modelling method; and (3 variability in environmental responses between mites belonging to two invasive clades of T. evansi. Consensus techniques were used to forecast the potential range of the species under current and two different climate change scenarios for 2080, and variance between model projections were mapped to identify regions of high uncertainty. We revealed large predictive variations linked to all factors, although prevalence had a greater influence than the statistical model once the best modelling strategies were selected. The major areas threatened under current conditions include tropical countries in South America and Africa, and temperate regions in North America, the Mediterranean basin and Australia. Under future scenarios, the threat shifts towards northern Europe and some other temperate regions in the Americas, whereas tropical regions in Africa present a reduced risk. Analysis of niche overlap suggests that the current differential distribution of mites of the two clades of T. evansi can be partially attributed to environmental niche differentiation. Overall this study shows how consensus strategies and analysis of niche overlap can be used jointly to draw conclusions on invasive
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Directory of Open Access Journals (Sweden)
L. Marziali
2013-09-01
Full Text Available The response of 443 chironomid species to water temperature was analyzed, with the aim of defining their thermal optimum, tolerance limits and thermal habitat. The database included 4442 samples mainly from Italian river catchments collected from the 1950s up to date. Thermal preferences were calculated separately for larval and pupal specimens and for different habitats: high altitude and lowland lakes in the Alpine ecoregion; lowland lakes in the Mediterranean ecoregion; heavily modified water bodies; kryal, krenal, rhithral and potamal in running waters. Optimum response was calculated as mean water temperature, weighted by species abundances; tolerance as weighted standard deviation; skewness and kurtosis as 3rd and 4th moment statistics. The responses were fitted to normal uni- or plurimodal Gaussian models. Cold stenothermal species showed: i unimodal response, ii tolerance for a narrow temperature range, iii optima closed to their minimum temperature values, iv leptokurtic response. Thermophilous species showed: i optima at different temperature values, ii wider tolerance, iii optima near their maximum temperature values, iv platikurtic response, often fitting a plurimodal model. As expected, lower optima values and narrower tolerance were obtained for kryal and krenal, than for rhithral, potamal and lakes. Thermal response curves were produced for each species and were discussed according to species distribution (i.e. altitudinal range in running water and water depth in lakes, voltinism and phylogeny. Thermal optimum and tolerance limits and the definition of the thermal habitat of species can help predicting the impact of global warming on freshwater ecosystems.
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Probabilistic accounting of uncertainty in forecasts of species distributions under climate change
Seth J. Wenger; Nicholas A. Som; Daniel C. Dauwalter; Daniel J. Isaak; Helen M. Neville; Charles H. Luce; Jason B. Dunham; Michael K. Young; Kurt D. Fausch; Bruce E. Rieman
2013-01-01
Forecasts of species distributions under future climates are inherently uncertain, but there have been few attempts to describe this uncertainty comprehensively in a probabilistic manner. We developed a Monte Carlo approach that accounts for uncertainty within generalized linear regression models (parameter uncertainty and residual error), uncertainty among competing...
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Directory of Open Access Journals (Sweden)
Paulo Vallejos-Garrido
2017-09-01
Full Text Available Background Why biodiversity is not uniformly distributed on the Earth is a major research question of biogeography. One of the most striking patterns of disparity in species distribution are the biodiversity hotspots, which generally do not fit with the distribution of relevant components of the Neotropical biota. In this study, we assess the proximal causes of the species-richness pattern of one of the most conspicuous groups of Neotropical mammals, the New World monkeys the Platyrrhini. We test two complementary hypotheses: (1 there is a historical source-sink dynamic (addressed using macroevolutionary and macroecological approaches; (2 the large number of species in the Amazon basin is due to the constraints imposed by environmental variables occurring outside this area. Methods We first characterize spatial patterns of species richness and biodiversity hotspots using a new, objective protocol based on probabilities. Then we evaluate the source-sink hypothesis using BioGeoBEARS analysis and nestedness analysis of species richness patterns. Complementarily, to measure how often different species pairs appear in the same sites, we used null models to estimate the checkerboard score index (C-score. Finally, we evaluate the relationship between several climatic variables and species richness through ordinary least squares (OLS and spatial autoregressive (SAR models, and the potential environmental constraints on the pattern. Results We found one significant cluster of high values for species richness in the Amazon basin. Most dispersal events occurred from the Amazonian subregion to other Neotropical areas. Temperature (T, discrepancy (BR, and NODF indexes show a significant nesting in the matrix ordered by species richness and available energy. The C-score observed was significantly smaller than the null expectation for all sites in the Neotropics where there are records of platyrrhine species. Ten climatic variables comprised the best
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Place prioritization for biodiversity content using species ecological niche modeling
Víctor Sánchez-Cordero; Verónica Cirelli; Mariana Munguial; Sahotra Sarkar
2005-01-01
Place prioritization for biodiversity representation is essential for conservation planning, particularly in megadiverse countries where high deforestation threatens biodiversity. Given the collecting biases and uneven sampling of biological inventories, there is a need to develop robust models of species’ distributions. By modeling species’ ecological niches using point occurrence data and digitized environmental feature maps, we can predict potential and extant distributions of species in u...
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DEFF Research Database (Denmark)
Sonnenborg, Torben Obel; Christiansen, Jesper Riis; Pang, Bo
2017-01-01
afforestation or forest conversion impacts the water resource at the catchment scale. We hypothesize that the groundwater formation and streamflow is increased when water consuming conifers are replaced with the less consumptive broadleaf tree species. To test this a distributed hydrological model...
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Analyzing fractal property of species abundance distribution and diversity indexes.
Su, Qiang
2016-03-07
Community diversity is usually characterized by numerical indexes; however it indeed depends on the species abundance distribution (SAD). Diversity indexes and SAD are based on the same information but treating as separate themes. Ranking species abundance from largest to smallest, the decreasing pattern can give the information about the SAD. Frontier proposed such SAD might be a fractal structure, and first applied the Zipf-Mandelbrot model to the SAD study. However, this model fails to include the Zipf model, and also fails to ensure an integer rank. In this study, a fractal model of SAD was reconstructed, and tested with 104 community samples from 8 taxonomic groups. The results show that there was a good fit of the presented model. Fractal parameter (p) determines the SAD of a community. The ecological significance of p relates to the "dominance" of a community. The correlation between p and classical diversity indexes show that Shannon index decreases and Simpson index increases as p increases. The main purpose of this paper is not to compare with other SADs models; it simply provides a new interpretation of SAD model construction, and preliminarily integrates diversity indexes and SAD model into a broader perspective of community diversity. Copyright © 2015 Elsevier Ltd. All rights reserved.
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Năpăruş, Magdalena; Kuntner, Matjaž
2012-01-01
Although numerous studies model species distributions, these models are almost exclusively on single species, while studies of evolutionary lineages are preferred as they by definition study closely related species with shared history and ecology. Hermit spiders, genus Nephilengys, represent an ecologically important but relatively species-poor lineage with a globally allopatric distribution. Here, we model Nephilengys global habitat suitability based on known localities and four ecological parameters. We geo-referenced 751 localities for the four most studied Nephilengys species: N. cruentata (Africa, New World), N. livida (Madagascar), N. malabarensis (S-SE Asia), and N. papuana (Australasia). For each locality we overlaid four ecological parameters: elevation, annual mean temperature, annual mean precipitation, and land cover. We used linear backward regression within ArcGIS to select two best fit parameters per species model, and ModelBuilder to map areas of high, moderate and low habitat suitability for each species within its directional distribution. For Nephilengys cruentata suitable habitats are mid elevation tropics within Africa (natural range), a large part of Brazil and the Guianas (area of synanthropic spread), and even North Africa, Mediterranean, and Arabia. Nephilengys livida is confined to its known range with suitable habitats being mid-elevation natural and cultivated lands. Nephilengys malabarensis, however, ranges across the Equator throughout Asia where the model predicts many areas of high ecological suitability in the wet tropics. Its directional distribution suggests the species may potentially spread eastwards to New Guinea where the suitable areas of N. malabarensis largely surpass those of the native N. papuana, a species that prefers dry forests of Australian (sub)tropics. Our model is a customizable GIS tool intended to predict current and future potential distributions of globally distributed terrestrial lineages. Its predictive
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Directory of Open Access Journals (Sweden)
Magdalena Năpăruş
Full Text Available BACKGROUND: Although numerous studies model species distributions, these models are almost exclusively on single species, while studies of evolutionary lineages are preferred as they by definition study closely related species with shared history and ecology. Hermit spiders, genus Nephilengys, represent an ecologically important but relatively species-poor lineage with a globally allopatric distribution. Here, we model Nephilengys global habitat suitability based on known localities and four ecological parameters. METHODOLOGY/PRINCIPAL FINDINGS: We geo-referenced 751 localities for the four most studied Nephilengys species: N. cruentata (Africa, New World, N. livida (Madagascar, N. malabarensis (S-SE Asia, and N. papuana (Australasia. For each locality we overlaid four ecological parameters: elevation, annual mean temperature, annual mean precipitation, and land cover. We used linear backward regression within ArcGIS to select two best fit parameters per species model, and ModelBuilder to map areas of high, moderate and low habitat suitability for each species within its directional distribution. For Nephilengys cruentata suitable habitats are mid elevation tropics within Africa (natural range, a large part of Brazil and the Guianas (area of synanthropic spread, and even North Africa, Mediterranean, and Arabia. Nephilengys livida is confined to its known range with suitable habitats being mid-elevation natural and cultivated lands. Nephilengys malabarensis, however, ranges across the Equator throughout Asia where the model predicts many areas of high ecological suitability in the wet tropics. Its directional distribution suggests the species may potentially spread eastwards to New Guinea where the suitable areas of N. malabarensis largely surpass those of the native N. papuana, a species that prefers dry forests of Australian (subtropics. CONCLUSIONS: Our model is a customizable GIS tool intended to predict current and future potential
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Directory of Open Access Journals (Sweden)
Sonja Preuss
2011-11-01
Full Text Available The development of conservation strategies to mitigate the impact of invasive species requires knowledge of the species ecology and distribution. This is, however, often lacking as collecting biological data may be both time-consuming and resource intensive. Species distribution models can offer a solution to this dilemma by analysing the species-environment relationship with help of Geographic information systems (GIS. In this study, we model the distribution of the non-native bush-cricket Metrioptera roeselii in the agricultural landscape in mid-Sweden where the species has been rapidly expanding in its range since the 1990s. We extract ecologically relevant landscape variables from Swedish CORINE land-cover maps and use species presence-absence data from large-scale surveys to construct a species distribution model (SDM. The aim of the study is to increase the knowledge of the species range expansion pattern by examining how its distribution is affected by landscape composition and structure, and to evaluate SDM performance at two different spatial scales. We found that models including data on a scale of 1 × 1 km were able to explain more of the variation in species distribution than those on the local scale (10 m buffer on each side of surveyed road. The amount of grassland in the landscape, estimated from the area of arable land, pasture and rural settlements, was a good predictor of the presence of the species on both scales. The measurements of landscape structure – linear elements and fragmentation - gave ambivalent results which differed from previous small scaled studies on species dispersal behaviour and occupancy patterns. The models had good predictive ability and showed that areas dominated by agricultural fields and their associated grassland edges have a high probability being colonised by the species. Our study identified important landscape variables that explain the distribution of M. roeselii in Mid-Sweden that may also
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Geographic distribution of wild potato species
Hijmans, R.J.; Spooner, D.M.
2001-01-01
The geographic distribution of wild potatoes (Solanaceae sect. Petota) was analyzed using a database of 6073 georeferenced observations. Wild potatoes occur in 16 countries, but 88% of the observations are from Argentina, Bolivia, Mexico, and Peru. Most species are rare and narrowly endemic: for 77
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Directory of Open Access Journals (Sweden)
Romain Nattier
Full Text Available The grasshopper genus Caledonula, endemic to New Caledonia, was studied to understand the evolution of species distributions in relation to climate and soil types. Based on a comprehensive sampling of 80 locations throughout the island, the genus was represented by five species, four of which are new to science, of which three are described here. All the species have limited distributions in New Caledonia. Bioclimatic niche modelling shows that all the species were found in association with a wet climate and reduced seasonality, explaining their restriction to the southern half of the island. The results suggest that the genus was ancestrally constrained by seasonality. A molecular phylogeny was reconstructed using two mitochondrial and two nuclear markers. The partially resolved tree showed monophyly of the species found on metalliferous soils, and molecular dating indicated a rather recent origin for the genus. Adaptation to metalliferous soils is suggested by both morphological changes and radiation on these soils. The genus Caledonula is therefore a good model to understand the origin of microendemism in the context of recent and mixed influences of climate and soil type.
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Syfert, Mindy M; Smith, Matthew J; Coomes, David A
2013-01-01
Species distribution models (SDMs) trained on presence-only data are frequently used in ecological research and conservation planning. However, users of SDM software are faced with a variety of options, and it is not always obvious how selecting one option over another will affect model performance. Working with MaxEnt software and with tree fern presence data from New Zealand, we assessed whether (a) choosing to correct for geographical sampling bias and (b) using complex environmental response curves have strong effects on goodness of fit. SDMs were trained on tree fern data, obtained from an online biodiversity data portal, with two sources that differed in size and geographical sampling bias: a small, widely-distributed set of herbarium specimens and a large, spatially clustered set of ecological survey records. We attempted to correct for geographical sampling bias by incorporating sampling bias grids in the SDMs, created from all georeferenced vascular plants in the datasets, and explored model complexity issues by fitting a wide variety of environmental response curves (known as "feature types" in MaxEnt). In each case, goodness of fit was assessed by comparing predicted range maps with tree fern presences and absences using an independent national dataset to validate the SDMs. We found that correcting for geographical sampling bias led to major improvements in goodness of fit, but did not entirely resolve the problem: predictions made with clustered ecological data were inferior to those made with the herbarium dataset, even after sampling bias correction. We also found that the choice of feature type had negligible effects on predictive performance, indicating that simple feature types may be sufficient once sampling bias is accounted for. Our study emphasizes the importance of reducing geographical sampling bias, where possible, in datasets used to train SDMs, and the effectiveness and essentialness of sampling bias correction within MaxEnt.
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Species Composition, Relative Abundance and Distribution of the ...
African Journals Online (AJOL)
Species Composition, Relative Abundance and Distribution of the Avian Fauna of Entoto Natural Park and Escarpment, Addis Ababa. ... Eucalyptus plantation, soil erosion, deforestation, habitat fragmentation, settlement and land degradation were the main threats for the distribution of birds in the present study area.
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Evans, M. E.; Merow, C.; Record, S.; Menlove, J.; Gray, A.; Cundiff, J.; McMahon, S.; Enquist, B. J.
2013-12-01
Current attempts to forecast how species' distributions will change in response to climate change suffer under a fundamental trade-off: between modeling many species superficially vs. few species in detail (between correlative vs. mechanistic models). The goals of this talk are two-fold: first, we present a Bayesian multilevel modeling framework, dynamic range modeling (DRM), for building process-based forecasts of many species' distributions at a time, designed to address the trade-off between detail and number of distribution forecasts. In contrast to 'species distribution modeling' or 'niche modeling', which uses only species' occurrence data and environmental data, DRMs draw upon demographic data, abundance data, trait data, occurrence data, and GIS layers of climate in a single framework to account for two processes known to influence range dynamics - demography and dispersal. The vision is to use extensive databases on plant demography, distributions, and traits - in the Botanical Information and Ecology Network, the Forest Inventory and Analysis database (FIA), and the International Tree Ring Data Bank - to develop DRMs for North American trees. Second, we present preliminary results from building the core submodel of a DRM - an integral projection model (IPM) - for a sample of dominant tree species in western North America. IPMs are used to infer demographic niches - i.e., the set of environmental conditions under which population growth rate is positive - and project population dynamics through time. Based on >550,000 data points derived from FIA for nine tree species in western North America, we show IPM-based models of their current and future distributions, and discuss how IPMs can be used to forecast future forest productivity, mortality patterns, and inform efforts at assisted migration.
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Comparing distribution models for small samples of overdispersed counts of freshwater fish
Vaudor, Lise; Lamouroux, Nicolas; Olivier, Jean-Michel
2011-05-01
The study of species abundance often relies on repeated abundance counts whose number is limited by logistic or financial constraints. The distribution of abundance counts is generally right-skewed (i.e. with many zeros and few high values) and needs to be modelled for statistical inference. We used an extensive dataset involving about 100,000 fish individuals of 12 freshwater fish species collected in electrofishing points (7 m 2) during 350 field surveys made in 25 stream sites, in order to compare the performance and the generality of four distribution models of counts (Poisson, negative binomial and their zero-inflated counterparts). The negative binomial distribution was the best model (Bayesian Information Criterion) for 58% of the samples (species-survey combinations) and was suitable for a variety of life histories, habitat, and sample characteristics. The performance of the models was closely related to samples' statistics such as total abundance and variance. Finally, we illustrated the consequences of a distribution assumption by calculating confidence intervals around the mean abundance, either based on the most suitable distribution assumption or on an asymptotical, distribution-free (Student's) method. Student's method generally corresponded to narrower confidence intervals, especially when there were few (≤3) non-null counts in the samples.
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Lima, Robson B DE; Bufalino, Lina; Alves, Francisco T; Silva, José A A DA; Ferreira, Rinaldo L C
2017-01-01
Currently, there is a lack of studies on the correct utilization of continuous distributions for dry tropical forests. Therefore, this work aims to investigate the diameter structure of a brazilian tropical dry forest and to select suitable continuous distributions by means of statistic tools for the stand and the main species. Two subsets were randomly selected from 40 plots. Diameter at base height was obtained. The following functions were tested: log-normal; gamma; Weibull 2P and Burr. The best fits were selected by Akaike's information validation criterion. Overall, the diameter distribution of the dry tropical forest was better described by negative exponential curves and positive skewness. The forest studied showed diameter distributions with decreasing probability for larger trees. This behavior was observed for both the main species and the stand. The generalization of the function fitted for the main species show that the development of individual models is needed. The Burr function showed good flexibility to describe the diameter structure of the stand and the behavior of Mimosa ophthalmocentra and Bauhinia cheilantha species. For Poincianella bracteosa, Aspidosperma pyrifolium and Myracrodum urundeuva better fitting was obtained with the log-normal function.
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Distribution Patterns of Ohio Stoneflies, with an Emphasis on Rare and Uncommon Species
Grubbs, Scott A.; Pessimo, Massimo; DeWalt, R. Edward
2013-01-01
Presently, 102 stonefly species (Plecoptera) have been reported from Ohio. All 9 Nearctic families are represented. Over 90% of the fauna exhibit a combination of broad Nearctic-widespread, eastern Nearctic-widespread, Appalachian, and eastern Nearctic-unglaciated distributions. In contrast, only 2 species display a central Nearctic-Prairie distribution. Seven species of Perlidae are likely no longer present (Acroneuria evoluta Klapálek, A. perplexa Frison, Attaneuria ruralis (Hagen), and Neoperla mainensis Banks) or have experienced marked range reductions (Acroneuria abnormis (Newman), A. frisoni Stark and Brown, and A. filicis Frison). Another nearly 31% of the fauna (32 species) are rare, uncommon, or have highly-limited distributions within the state. Twelve of these species have Appalachian distributions, and an additional 8 have eastern Nearctic-unglaciated distributions. The distributional status for each of the 32 rare/uncommon species is discussed. PMID:24219390
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Modeled ground water age distributions
Woolfenden, Linda R.; Ginn, Timothy R.
2009-01-01
The age of ground water in any given sample is a distributed quantity representing distributed provenance (in space and time) of the water. Conventional analysis of tracers such as unstable isotopes or anthropogenic chemical species gives discrete or binary measures of the presence of water of a given age. Modeled ground water age distributions provide a continuous measure of contributions from different recharge sources to aquifers. A numerical solution of the ground water age equation of Ginn (1999) was tested both on a hypothetical simplified one-dimensional flow system and under real world conditions. Results from these simulations yield the first continuous distributions of ground water age using this model. Complete age distributions as a function of one and two space dimensions were obtained from both numerical experiments. Simulations in the test problem produced mean ages that were consistent with the expected value at the end of the model domain for all dispersivity values tested, although the mean ages for the two highest dispersivity values deviated slightly from the expected value. Mean ages in the dispersionless case also were consistent with the expected mean ages throughout the physical model domain. Simulations under real world conditions for three dispersivity values resulted in decreasing mean age with increasing dispersivity. This likely is a consequence of an edge effect. However, simulations for all three dispersivity values tested were mass balanced and stable demonstrating that the solution of the ground water age equation can provide estimates of water mass density distributions over age under real world conditions.
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Kalwij, Jesse M; Robertson, Mark P; Ronk, Argo; Zobel, Martin; Pärtel, Meelis
2014-01-01
Much ecological research relies on existing multispecies distribution datasets. Such datasets, however, can vary considerably in quality, extent, resolution or taxonomic coverage. We provide a framework for a spatially-explicit evaluation of geographical representation within large-scale species distribution datasets, using the comparison of an occurrence atlas with a range atlas dataset as a working example. Specifically, we compared occurrence maps for 3773 taxa from the widely-used Atlas Florae Europaeae (AFE) with digitised range maps for 2049 taxa of the lesser-known Atlas of North European Vascular Plants. We calculated the level of agreement at a 50-km spatial resolution using average latitudinal and longitudinal species range, and area of occupancy. Agreement in species distribution was calculated and mapped using Jaccard similarity index and a reduced major axis (RMA) regression analysis of species richness between the entire atlases (5221 taxa in total) and between co-occurring species (601 taxa). We found no difference in distribution ranges or in the area of occupancy frequency distribution, indicating that atlases were sufficiently overlapping for a valid comparison. The similarity index map showed high levels of agreement for central, western, and northern Europe. The RMA regression confirmed that geographical representation of AFE was low in areas with a sparse data recording history (e.g., Russia, Belarus and the Ukraine). For co-occurring species in south-eastern Europe, however, the Atlas of North European Vascular Plants showed remarkably higher richness estimations. Geographical representation of atlas data can be much more heterogeneous than often assumed. Level of agreement between datasets can be used to evaluate geographical representation within datasets. Merging atlases into a single dataset is worthwhile in spite of methodological differences, and helps to fill gaps in our knowledge of species distribution ranges. Species distribution
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Improved Predictions of the Geographic Distribution of Invasive Plants Using Climatic Niche Models
Ramírez-Albores, Jorge E.; Bustamante, Ramiro O.
2016-01-01
Climatic niche models for invasive plants are usually constructed with occurrence records taken from literature and collections. Because these data neither discriminate among life-cycle stages of plants (adult or juvenile) nor the origin of individuals (naturally established or man-planted), the resulting models may mispredict the distribution ranges of these species. We propose that more accurate predictions could be obtained by modelling climatic niches with data of naturally established individuals, particularly with occurrence records of juvenile plants because this would restrict the predictions of models to those sites where climatic conditions allow the recruitment of the species. To test this proposal, we focused on the Peruvian peppertree (Schinus molle), a South American species that has largely invaded Mexico. Three climatic niche models were constructed for this species using high-resolution dataset gathered in the field. The first model included all occurrence records, irrespective of the life-cycle stage or origin of peppertrees (generalized niche model). The second model only included occurrence records of naturally established mature individuals (adult niche model), while the third model was constructed with occurrence records of naturally established juvenile plants (regeneration niche model). When models were compared, the generalized climatic niche model predicted the presence of peppertrees in sites located farther beyond the climatic thresholds that naturally established individuals can tolerate, suggesting that human activities influence the distribution of this invasive species. The adult and regeneration climatic niche models concurred in their predictions about the distribution of peppertrees, suggesting that naturally established adult trees only occur in sites where climatic conditions allow the recruitment of juvenile stages. These results support the proposal that climatic niches of invasive plants should be modelled with data of
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Directory of Open Access Journals (Sweden)
Qing Zeng
Full Text Available Scaly-sided Merganser is a globally endangered species restricted to eastern Asia. Estimating its population is difficult and considerable gap exists between populations at its breeding grounds and wintering sites. In this study, we built a species distribution model (SDM using Maxent with presence-only data to predict the potential wintering habitat for Scaly-sided Merganser in China. Area under the receiver operating characteristic curve (AUC method suggests high predictive power of the model (training and testing AUC were 0.97 and 0.96 respectively. The most significant environmental variables included annual mean temperature, mean temperature of coldest quarter, minimum temperature of coldest month and precipitation of driest quarter. Suitable conditions for Scaly-sided Merganser are predicted in the middle and lower reaches of the Yangtze River, especially in Jiangxi, Hunan and Hubei Provinces. The predicted suitable habitat embraces 6,984 km of river. Based on survey results from three consecutive winters (2010-2012 and previous studies, we estimated that the entire wintering population of Scaly-sided Merganser in China to be 3,561 ± 478 individuals, which is consistent with estimate in its breeding ground.
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Model of Peatland Vegetation Species using HyMap Image and Machine Learning
Dayuf Jusuf, Muhammad; Danoedoro, Projo; Muljo Sukojo, Bangun; Hartono
2017-12-01
Species Tumih / Parepat (Combretocarpus-rotundatus Mig. Dancer) family Anisophylleaceae and Meranti (Shorea Belangerang, Shorea Teysmanniana Dyer ex Brandis) family Dipterocarpaceae is a group of vegetation species distribution model. Species pioneer is predicted as an indicator of the succession of ecosystem restoration of tropical peatland characteristics and extremely fragile (unique) in the endemic hot spot of Sundaland. Climate change projections and conservation planning are hot topics of current discussion, analysis of alternative approaches and the development of combinations of species projection modelling algorithms through geospatial information systems technology. Approach model to find out the research problem of vegetation level based on the machine learning hybrid method, wavelet and artificial neural networks. Field data are used as a reference collection of natural resource field sample objects and biodiversity assessment. The testing and training ANN data set iterations times 28, achieve a performance value of 0.0867 MSE value is smaller than the ANN training data, above 50%, and spectral accuracy 82.1 %. Identify the location of the sample point position of the Tumih / Parepat vegetation species using HyMap Image is good enough, at least the modelling, design of the species distribution can reach the target in this study. The computation validation rate above 90% proves the calculation can be considered.
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Modelling the distribution of chickens, ducks, and geese in China
Prosser, Diann J.; Wu, Junxi; Ellis, Erie C.; Gale, Fred; Van Boeckel, Thomas P.; Wint, William; Robinson, Tim; Xiao, Xiangming; Gilbert, Marius
2011-01-01
Global concerns over the emergence of zoonotic pandemics emphasize the need for high-resolution population distribution mapping and spatial modelling. Ongoing efforts to model disease risk in China have been hindered by a lack of available species level distribution maps for poultry. The goal of this study was to develop 1 km resolution population density models for China's chickens, ducks, and geese. We used an information theoretic approach to predict poultry densities based on statistical relationships between poultry census data and high-resolution agro-ecological predictor variables. Model predictions were validated by comparing goodness of fit measures (root mean square error and correlation coefficient) for observed and predicted values for 1/4 of the sample data which were not used for model training. Final output included mean and coefficient of variation maps for each species. We tested the quality of models produced using three predictor datasets and 4 regional stratification methods. For predictor variables, a combination of traditional predictors for livestock mapping and land use predictors produced the best goodness of fit scores. Comparison of regional stratifications indicated that for chickens and ducks, a stratification based on livestock production systems produced the best results; for geese, an agro-ecological stratification produced best results. However, for all species, each method of regional stratification produced significantly better goodness of fit scores than the global model. Here we provide descriptive methods, analytical comparisons, and model output for China's first high resolution, species level poultry distribution maps. Output will be made available to the scientific and public community for use in a wide range of applications from epidemiological studies to livestock policy and management initiatives.
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Amirazodi, S.; Griffin, R.; Flores Cordova, A. I.; Ouko, E.; Omondi, S.; Mugo, R. M.; Farah, H.; Flores Cordova, A. I.; Adams, E. C.
2017-12-01
Invasive species in African savannas pose great threat to the native biodiversity and changes ecosystem functioning. In the forest sector, for instance Acacia species are important sources of fuel-wood, yet at the same time they have increased strain on water resources and shrunken forage spaces for both livestock and wildlife. In recently infested regions, invasive species can progress through the stages of introduction, establishment and dispersal to a full range. Currently there is much worldwide interest in predicting distributions of invasive species, and several organizations are faced with questions of whether and how to tackle such environmental challenges, or how to interpret predictions from the science community. Conservation practioners require mapped estimates of where species could persist in a given region, and this is associated to information about the biotope - i.e. the geographic location of the species' niche. The process of collecting species distribution data for identifying the potential distribution of the invasive species in the invaded ranges has become a challenge both in terms of resource and time allocation. This study highlights innovative approaches in crowdsourcing validation data in mapping and modelling invasive species (Acacia reficiens and Cactus) through involvement of the local communities. The general approach was to model the distribution of A. reficiens and Cactus (Opuntia Spp) using occurrence records from native range, then project the model into new regions to assess susceptibility to invasion using climatic and topographic environmental variables. The models performed better than random prediction (P 0.75.
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Factors influencing non-native tree species distribution in urban landscapes
Wayne C. Zipperer
2010-01-01
Non-native species are presumed to be pervasive across the urban landscape. Yet, we actually know very little about their actual distribution. For this study, vegetation plot data from Syracuse, NY and Baltimore, MD were used to examine non-native tree species distribution in urban landscapes. Data were collected from remnant and emergent forest patches on upland sites...
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A globally-distributed alien invasive species poses risks to United States imperiled species.
McClure, Meredith L; Burdett, Christopher L; Farnsworth, Matthew L; Sweeney, Steven J; Miller, Ryan S
2018-03-28
In the midst of Earth's sixth mass extinction event, non-native species are a driving factor in many imperiled species' declines. One of the most widespread and destructive alien invasive species in the world, wild pigs (Sus scrofa) threaten native species through predation, habitat destruction, competition, and disease transmission. We show that wild pigs co-occur with up to 87.2% of imperiled species in the contiguous U.S. identified as susceptible to their direct impacts, and we project increases in both the number of species at risk and the geographic extent of risks by 2025. Wild pigs may therefore present a severe threat to U.S. imperiled species, with serious implications for management of at-risk species throughout wild pigs' global distribution. We offer guidance for efficient allocation of research effort and conservation resources across species and regions using a simple approach that can be applied to wild pigs and other alien invasive species globally.
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García-Vázquez, Uri; D’Addario, Maristella
2018-01-01
Land use and climate change are affecting the abundance and distribution of species. The Trans-Mexican Volcanic Belt (TMVB) is a very diverse region due to geological history, geographic position, and climate. It is also one of the most disturbed regions in Mexico. Reptiles are particularly sensitive to environmental changes due to their low dispersal capacity and thermal ecology. In this study, we define the important environmental variables (considering climate, topography, and land use) and potential distribution (present and future) of the five Thamnophis species present in TMVB. To do so, we used the maximum entropy modeling software (MAXENT). First, we modeled to select the most important variables to explain the distribution of each species, then we modeled again using only the most important variables and projected these models to the future considering a middle-moderate climate change scenario (rcp45), and land use and vegetation variables for the year 2050 (generated according to land use changes that occurred between years 2002 and 2011). Arid vegetation had an important negative effect on habitat suitability for all species, and minimum temperature of the coldest month was important for four of the five species. Thamnophis cyrtopsis was the species with the lowest tolerance to minimum temperatures. The maximum temperature of the warmest month was important for T. scalaris and T. cyrtopsis. Low percentages of agriculture were positive for T. eques and T. melanogaster but, at higher values, agriculture had a negative effect on habitat suitability for both species. Elevation was the most important variable to explain T. eques and T. melanogaster potential distribution while distance to Abies forests was the most important variable for T. scalaris and T. scaliger. All species had a high proportion of their potential distribution in the TMVB. However, according to our models, all Thamnophis species will experience reductions in their potential
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Modelling survival: exposure pattern, species sensitivity and uncertainty.
Ashauer, Roman; Albert, Carlo; Augustine, Starrlight; Cedergreen, Nina; Charles, Sandrine; Ducrot, Virginie; Focks, Andreas; Gabsi, Faten; Gergs, André; Goussen, Benoit; Jager, Tjalling; Kramer, Nynke I; Nyman, Anna-Maija; Poulsen, Veronique; Reichenberger, Stefan; Schäfer, Ralf B; Van den Brink, Paul J; Veltman, Karin; Vogel, Sören; Zimmer, Elke I; Preuss, Thomas G
2016-07-06
The General Unified Threshold model for Survival (GUTS) integrates previously published toxicokinetic-toxicodynamic models and estimates survival with explicitly defined assumptions. Importantly, GUTS accounts for time-variable exposure to the stressor. We performed three studies to test the ability of GUTS to predict survival of aquatic organisms across different pesticide exposure patterns, time scales and species. Firstly, using synthetic data, we identified experimental data requirements which allow for the estimation of all parameters of the GUTS proper model. Secondly, we assessed how well GUTS, calibrated with short-term survival data of Gammarus pulex exposed to four pesticides, can forecast effects of longer-term pulsed exposures. Thirdly, we tested the ability of GUTS to estimate 14-day median effect concentrations of malathion for a range of species and use these estimates to build species sensitivity distributions for different exposure patterns. We find that GUTS adequately predicts survival across exposure patterns that vary over time. When toxicity is assessed for time-variable concentrations species may differ in their responses depending on the exposure profile. This can result in different species sensitivity rankings and safe levels. The interplay of exposure pattern and species sensitivity deserves systematic investigation in order to better understand how organisms respond to stress, including humans.
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Continental-wide distribution of crayfish species in Europe: update and maps
Directory of Open Access Journals (Sweden)
Kouba A.
2014-01-01
Full Text Available Recently published astacological studies substantially improved available data on distribution of crayfish in various European regions. At the same time, spread of invasive species has been recorded, additional non-indigenous species became established in various countries, and losses of populations of native species due to crayfish plague and other negative factors were observed. We overview recent advances in this knowledge, and provide updated colour maps of the distribution of all crayfish species present in Europe. These maps are originally based on the data from the Atlas of Crayfish in Europe published in 2006 as a result of the CRAYNET project, and were further updated from more recently published reports, grey literature, and especially thanks to contributions and feedback of over 70 specialists from 32 countries. Separate maps are available for all indigenous crayfish species in Europe as well as for three most widespread non-indigenous crayfish species. Additionally, two maps give locations of known findings of crayfish species introduced to Europe after 1980. These newly established alien species have so far restricted distributions; however, the frequency of recent reports suggests that findings of such species resulting from releases of aquarium pets will further increase.
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Freeman, Benjamin G.; Class Freeman, Alexandra M.
2014-01-01
Temperate-zone species have responded to warming temperatures by shifting their distributions poleward and upslope. Thermal tolerance data suggests that tropical species may respond to warming temperatures even more strongly than temperate-zone species, but this prediction has yet to be tested. We addressed this data gap by conducting resurveys to measure distributional responses to temperature increases in the elevational limits of the avifaunas of two geographically and faunally independent New Guinean mountains, Mt. Karimui and Karkar Island, 47 and 44 y after they were originally surveyed. Although species richness is roughly five times greater on mainland Mt. Karimui than oceanic Karkar Island, distributional shifts at both sites were similar: upslope shifts averaged 113 m (Mt. Karimui) and 152 m (Karkar Island) for upper limits and 95 m (Mt. Karimui) and 123 m (Karkar Island) for lower limits. We incorporated these results into a metaanalysis to compare distributional responses of tropical species with those of temperate-zone species, finding that average upslope shifts in tropical montane species match local temperature increases significantly more closely than in temperate-zone montane species. That tropical species appear to be strong responders has global conservation implications and provides empirical support to hitherto untested models that predict widespread extinctions in upper-elevation tropical endemics with small ranges. PMID:24550460
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Predictive modeling of deep-sea fish distribution in the Azores
Parra, Hugo E.; Pham, Christopher K.; Menezes, Gui M.; Rosa, Alexandra; Tempera, Fernando; Morato, Telmo
2017-11-01
Understanding the link between fish and their habitat is essential for an ecosystem approach to fisheries management. However, determining such relationship is challenging, especially for deep-sea species. In this study, we applied generalized additive models (GAMs) to relate presence-absence and relative abundance data of eight economically-important fish species to environmental variables (depth, slope, aspect, substrate type, bottom temperature, salinity and oxygen saturation). We combined 13 years of catch data collected from systematic longline surveys performed across the region. Overall, presence-absence GAMs performed better than abundance models and predictions made for the observed data successfully predicted the occurrence of the eight deep-sea fish species. Depth was the most influential predictor of all fish species occurrence and abundance distributions, whereas other factors were found to be significant for some species but did not show such a clear influence. Our results predicted that despite the extensive Azores EEZ, the habitats available for the studied deep-sea fish species are highly limited and patchy, restricted to seamounts slopes and summits, offshore banks and island slopes. Despite some identified limitations, our GAMs provide an improved knowledge of the spatial distribution of these commercially important fish species in the region.
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VisTrails SAHM: visualization and workflow management for species habitat modeling
Morisette, Jeffrey T.; Jarnevich, Catherine S.; Holcombe, Tracy R.; Talbert, Colin B.; Ignizio, Drew A.; Talbert, Marian; Silva, Claudio; Koop, David; Swanson, Alan; Young, Nicholas E.
2013-01-01
The Software for Assisted Habitat Modeling (SAHM) has been created to both expedite habitat modeling and help maintain a record of the various input data, pre- and post-processing steps and modeling options incorporated in the construction of a species distribution model through the established workflow management and visualization VisTrails software. This paper provides an overview of the VisTrails:SAHM software including a link to the open source code, a table detailing the current SAHM modules, and a simple example modeling an invasive weed species in Rocky Mountain National Park, USA.
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Thomas C. Edwards; D. Richard Cutler; Niklaus E. Zimmermann; Linda Geiser; Gretchen G. Moisen
2006-01-01
We evaluated the effects of probabilistic (hereafter DESIGN) and non-probabilistic (PURPOSIVE) sample surveys on resultant classification tree models for predicting the presence of four lichen species in the Pacific Northwest, USA. Models derived from both survey forms were assessed using an independent data set (EVALUATION). Measures of accuracy as gauged by...
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Fernández-Mazuecos, Mario; Vargas, Pablo
2013-06-01
· The role of Quaternary climatic shifts in shaping the distribution of Linaria elegans, an Iberian annual plant, was investigated using species distribution modelling and molecular phylogeographical analyses. Three hypotheses are proposed to explain the Quaternary history of its mountain ring range. · The distribution of L. elegans was modelled using the maximum entropy method and projected to the last interglacial and to the last glacial maximum (LGM) using two different paleoclimatic models: the Community Climate System Model (CCSM) and the Model for Interdisciplinary Research on Climate (MIROC). Two nuclear and three plastid DNA regions were sequenced for 24 populations (119 individuals sampled). Bayesian phylogenetic, phylogeographical, dating and coalescent-based population genetic analyses were conducted. · Molecular analyses indicated the existence of northern and southern glacial refugia and supported two routes of post-glacial recolonization. These results were consistent with the LGM distribution as inferred under the CCSM paleoclimatic model (but not under the MIROC model). Isolation between two major refugia was dated back to the Riss or Mindel glaciations, > 100 kyr before present (bp). · The Atlantic distribution of inferred refugia suggests that the oceanic (buffered)-continental (harsh) gradient may have played a key and previously unrecognized role in determining Quaternary distribution shifts of Mediterranean plants. © 2013 The Authors. New Phytologist © 2013 New Phytologist Trust.
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Evaluating the combined effects of climate and land-use change on tree species distributions
DEFF Research Database (Denmark)
Garcia-Valdes, Raul; Svenning, Jens-Christian; Zavala, Miguel A.
2015-01-01
Summary: A large proportion of the world's biodiversity is reportedly threatened by habitat loss and climate change. However, there are few studies that investigate the interaction between these two threats using empirical data. Here, we investigate interactions between climate change and land-use...... change in the future distribution of 23 dominant tree species in mainland Spain. We simulated changes up to year 2100 using a climate-dependent Stochastic Patch Occupancy Model, parameterized with colonization and extinction events recorded in 46 596 survey plots. We estimated that the distribution of 17......% of the habitat, was estimated to reduce species occupancies (relative to baseline projections) by an average of 23% if habitat loss was spatially clumped, and by 35% if it was scattered. If habitat loss occurred in areas already impacted by human activities, species occupancies would be reduced by 26%. Land-use...
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Controlled comparison of species- and community-level models across novel climates and communities
Maguire, Kaitlin C.; Blois, Jessica L.; Fitzpatrick, Matthew C.; Williams, John W.; Ferrier, Simon; Lorenz, David J.
2016-01-01
Species distribution models (SDMs) assume species exist in isolation and do not influence one another's distributions, thus potentially limiting their ability to predict biodiversity patterns. Community-level models (CLMs) capitalize on species co-occurrences to fit shared environmental responses of species and communities, and therefore may result in more robust and transferable models. Here, we conduct a controlled comparison of five paired SDMs and CLMs across changing climates, using palaeoclimatic simulations and fossil-pollen records of eastern North America for the past 21 000 years. Both SDMs and CLMs performed poorly when projected to time periods that are temporally distant and climatically dissimilar from those in which they were fit; however, CLMs generally outperformed SDMs in these instances, especially when models were fit with sparse calibration datasets. Additionally, CLMs did not over-fit training data, unlike SDMs. The expected emergence of novel climates presents a major forecasting challenge for all models, but CLMs may better rise to this challenge by borrowing information from co-occurring taxa. PMID:26962143
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Abundance, distribution and species composition of fish larvae in ...
African Journals Online (AJOL)
improving our knowledge of the abundance, distribution and species diversity ... banks as well as in the mid-channel, thus eliminating any bias that might have .... cond method (Table 2) may bias the importance of a single species due to one, ...
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Directory of Open Access Journals (Sweden)
GR. Winck
Full Text Available In this study we attempted to access further information on the geographical distribution of the endangered lizard Liolaemus lutzae, estimating its potential distribution through the maximum entropy algorithm. For this purpose, we related its points of occurrence with matrices of environmental variables. After examining the correlation between environmental matrices, we selected 10 for model construction. The main variables influencing the current geographic distribution of L. lutzae were the diurnal temperature range and altitude. The species endemism seemed to be a consequence of a reduction of the original distribution area. Alternatively, the resulting model may reflect the geographic distribution of an ancestral lineage, since the model selected areas of occurrence of the two other species of Liolaemus from Brazil (L. arambarensis and L. occipitalis, all living in sand dune habitats and having psamophilic habits. Due to the high loss rate of habitat occupied by the species, the conservation and recovery of the remaining areas affected by human actions is essential.
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Fish species composition, density-distribution patterns, and impingement during upwelling
International Nuclear Information System (INIS)
Spigarelli, S.A.; Sharma, R.K.
1975-01-01
The effects of cooling system intakes and discharges on Lake Michigan fishes are highly dependent on inshore species composition and spatial distribution which, in turn, are affected by natural hydrological conditions. Significant (5 to 10 C) short-term decreases in water temperature (due to upwelling) could cause cold shock in fish equilibrated to either ambient or plume temperatures; substantial changes in distribution due to avoidance or attraction responses; and resultant changes in susceptibility to impingement. The objectives of this study are to characterize the changes in fish species composition, density, and thermal distribution as a result of natural upwellings, and to relate these factors to intake and discharge effects. Day and night sampling was conducted in ambient (reference) and thermal plume waters near the Zion Nuclear Plant on four occasions between 17 July and 11 September 1975. Density-distribution patterns and species composition of fish were determined by means of gill nets, bottom trawls, seines, and a sonic fish locater
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High Resolution Habitat Suitability Modelling For Restricted-Range Hawaiian Alpine Arthropod Species
Stephenson, N. M.
2016-12-01
Mapping potentially suitable habitat is critical for effective species conservation and management but can be challenging in areas exhibiting complex heterogeneity. An approach that combines non-intrusive spatial data collection techniques and field data can lead to a better understanding of landscapes and species distributions. Nysius wekiuicola, commonly known as the wēkiu bug, is the most studied arthropod species endemic to the Maunakea summit in Hawai`i, yet details about its geographic distribution and habitat use remain poorly understood. To predict the geographic distribution of N. wekiuicola, MaxEnt habitat suitability models were generated from a diverse set of input variables, including fifteen years of species occurrence data, high resolution digital elevation models, surface mineralogy maps derived from hyperspectral remote sensing, and climate data. Model results indicate that elevation (78.2 percent), and the presence of nanocrystalline hematite surface minerals (13.7 percent) had the highest influence, with lesser contributions from aspect, slope, and other surface mineral classes. Climatic variables were not included in the final analysis due to auto-correlation and coarse spatial resolution. Biotic factors relating to predation and competition also likely dictate wēkiu bug capture patterns and influence our results. The wēkiu bug range and habitat suitability models generated as a result of this study will be directly incorporated into management and restoration goals for the summit region and can also be adapted for other arthropod species present, leading to a more holistic understanding of metacommunity dynamics. Key words: Microhabitat, Structure from Motion, Lidar, MaxEnt, Habitat Suitability
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Ornelas, Juan Francisco; Gándara, Etelvina; Vásquez-Aguilar, Antonio Acini; Ramírez-Barahona, Santiago; Ortiz-Rodriguez, Andrés Ernesto; González, Clementina; Mejía Saules, María Teresa; Ruiz-Sanchez, Eduardo
2016-04-12
Ecological adaptation to host taxa is thought to result in mistletoe speciation via race formation. However, historical and ecological factors could also contribute to explain genetic structuring particularly when mistletoe host races are distributed allopatrically. Using sequence data from nuclear (ITS) and chloroplast (trnL-F) DNA, we investigate the genetic differentiation of 31 Psittacanthus schiedeanus (Loranthaceae) populations across the Mesoamerican species range. We conducted phylogenetic, population and spatial genetic analyses on 274 individuals of P. schiedeanus to gain insight of the evolutionary history of these populations. Species distribution modeling, isolation with migration and Bayesian inference methods were used to infer the evolutionary transition of mistletoe invasion, in which evolutionary scenarios were compared through posterior probabilities. Our analyses revealed shallow levels of population structure with three genetic groups present across the sample area. Nine haplotypes were identified after sequencing the trnL-F intergenic spacer. These haplotypes showed phylogeographic structure, with three groups with restricted gene flow corresponding to the distribution of individuals/populations separated by habitat (cloud forest localities from San Luis Potosí to northwestern Oaxaca and Chiapas, localities with xeric vegetation in central Oaxaca, and localities with tropical deciduous forests in Chiapas), with post-glacial population expansions and potentially corresponding to post-glacial invasion types. Similarly, 44 ITS ribotypes suggest phylogeographic structure, despite the fact that most frequent ribotypes are widespread indicating effective nuclear gene flow via pollen. Gene flow estimates, a significant genetic signal of demographic expansion, and range shifts under past climatic conditions predicted by species distribution modeling suggest post-glacial invasion of P. schiedeanus mistletoes to cloud forests. However, Approximate
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Dougherty, Daniel P; Da Conceicao Neta, Edith Ramos; McFeeters, Roger F; Lubkin, Sharon R; Breidt, Frederick
2006-08-09
In many biological science and food processing applications, it is very important to control or modify pH. However, the complex, unknown composition of biological media and foods often limits the utility of purely theoretical approaches to modeling pH and calculating the distributions of ionizable species. This paper provides general formulas and efficient algorithms for predicting the pH, titration, ionic species concentrations, buffer capacity, and ionic strength of buffer solutions containing both defined and undefined components. A flexible, semi-mechanistic, partial buffering (SMPB) approach is presented that uses local polynomial regression to model the buffering influence of complex or undefined components in a solution, while identified components of known concentration are modeled using expressions based on extensions of the standard acid-base theory. The SMPB method is implemented in a freeware package, (pH)Tools, for use with Matlab. We validated the predictive accuracy of these methods by using strong acid titrations of cucumber slurries to predict the amount of a weak acid required to adjust pH to selected target values.
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Reusser, D.A.; Lee, H.
2008-01-01
Habitat models can be used to predict the distributions of marine and estuarine non-indigenous species (NIS) over several spatial scales. At an estuary scale, our goal is to predict the estuaries most likely to be invaded, but at a habitat scale, the goal is to predict the specific locations within an estuary that are most vulnerable to invasion. As an initial step in evaluating several habitat models, model performance for a suite of benthic species with reasonably well-known distributions on the Pacific coast of the US needs to be compared. We discuss the utility of non-parametric multiplicative regression (NPMR) for predicting habitat- and estuary-scale distributions of native and NIS. NPMR incorporates interactions among variables, allows qualitative and categorical variables, and utilizes data on absence as well as presence. Preliminary results indicate that NPMR generally performs well at both spatial scales and that distributions of NIS are predicted as well as those of native species. For most species, latitude was the single best predictor, although similar model performance could be obtained at both spatial scales with combinations of other habitat variables. Errors of commission were more frequent at a habitat scale, with omission and commission errors approximately equal at an estuary scale. ?? 2008 International Council for the Exploration of the Sea. Published by Oxford Journals. All rights reserved.
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Garnica, Sigisfredo; Spahn, Philipp; Oertel, Bernhard; Ammirati, Joseph; Oberwinkler, Franz
2011-07-19
Cortinarius species in section Calochroi display local, clinal and circumboreal patterns of distribution across the Northern Hemisphere where these ectomycorrhizal fungi occur with host trees throughout their geographical range within a continent, or have disjunct intercontinental distributions, the origins of which are not understood. We inferred evolutionary histories of four species, 1) C. arcuatorum, 2) C. aureofulvus, 3) C. elegantior and 4) C. napus, from populations distributed throughout the Old World, and portions of the New World (Central- and North America) based on genetic variation of 154 haplotype internal transcribed spacer (ITS) sequences from 83 population samples. By describing the population structure of these species across their geographical distribution, we attempt to identify their historical migration and patterns of diversification. Models of population structure from nested clade, demographic and coalescent-based analyses revealed genetically differentiated and geographically structured haplotypes in C. arcuatorum and C. elegantior, while C. aureofulvus showed considerably less population structure and C. napus lacked sufficient genetic differentiation to resolve any population structure. Disjunct populations within C. arcuatorum, C. aureofulvus and C. elegantior show little or no morphological differentiation, whereas in C. napus there is a high level of homoplasy and phenotypic plasticity for veil and lamellae colour. The ITS sequences of the type specimens of C. albobrunnoides and C. albobrunnoides var. violaceovelatus were identical to one another and are treated as one species with a wider range of geographic distribution under C. napus. Our results indicate that each of the Calochroi species has undergone a relatively independent evolutionary history, hypothesised as follows: 1) a widely distributed ancestral population of C. arcuatorum diverged into distinctive sympatric populations in the New World; 2) two divergent lineages in C
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Directory of Open Access Journals (Sweden)
Steve Wathen
Full Text Available Evidence for significant losses of species richness or biodiversity, even within protected natural areas, is mounting. Managers are increasingly being asked to monitor biodiversity, yet estimating biodiversity is often prohibitively expensive. As a cost-effective option, we estimated the spatial and temporal distribution of species richness for four taxonomic groups (birds, mammals, herpetofauna (reptiles and amphibians, and plants within Sequoia and Kings Canyon National Parks using only existing biological studies undertaken within the Parks and the Parks' long-term wildlife observation database. We used a rarefaction approach to model species richness for the four taxonomic groups and analyzed those groups by habitat type, elevation zone, and time period. We then mapped the spatial distributions of species richness values for the four taxonomic groups, as well as total species richness, for the Parks. We also estimated changes in species richness for birds, mammals, and herpetofauna since 1980. The modeled patterns of species richness either peaked at mid elevations (mammals, plants, and total species richness or declined consistently with increasing elevation (herpetofauna and birds. Plants reached maximum species richness values at much higher elevations than did vertebrate taxa, and non-flying mammals reached maximum species richness values at higher elevations than did birds. Alpine plant communities, including sagebrush, had higher species richness values than did subalpine plant communities located below them in elevation. These results are supported by other papers published in the scientific literature. Perhaps reflecting climate change: birds and herpetofauna displayed declines in species richness since 1980 at low and middle elevations and mammals displayed declines in species richness since 1980 at all elevations.
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Directory of Open Access Journals (Sweden)
Mário Ferreira
2015-12-01
Full Text Available Imperfect detection (i.e., failure to detect a species when the species is present is increasingly recognized as an important source of uncertainty and bias in species distribution modeling. Although methods have been developed to solve this problem by explicitly incorporating variation in detectability in the modeling procedure, their use in freshwater systems remains limited. This is probably because most methods imply repeated sampling (≥ 2 of each location within a short time frame, which may be impractical or too expensive in most studies. Here we explore a novel approach to control for detectability based on the time-to-first-detection, which requires only a single sampling occasion and so may find more general applicability in freshwaters. The approach uses a Bayesian framework to combine conventional occupancy modeling with techniques borrowed from parametric survival analysis, jointly modeling factors affecting the probability of occupancy and the time required to detect a species. To illustrate the method, we modeled large scale factors (elevation, stream order and precipitation affecting the distribution of six fish species in a catchment located in north-eastern Portugal, while accounting for factors potentially affecting detectability at sampling points (stream depth and width. Species detectability was most influenced by depth and to lesser extent by stream width and tended to increase over time for most species. Occupancy was consistently affected by stream order, elevation and annual precipitation. These species presented a widespread distribution with higher uncertainty in tributaries and upper stream reaches. This approach can be used to estimate sampling efficiency and provide a practical framework to incorporate variations in the detection rate in fish distribution models.
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DEFF Research Database (Denmark)
Xu, Fu-Liu; Li, Yi-Long; Wang, Yin
2015-01-01
The species sensitivity distribution (SSD) model is one of the most commonly used methods for ecological risk assessment based on the potentially affected fraction (PAF) of and the combined PAF (msPAF) as quantitative indicators. There are usually four steps for the development of SSD models...... and their applications: (1) obtain the toxicity data of the pollutants; (2) fit the SSD curves; (3) calculate the potentially affected fractions (PAFs) of the individual pollutants for the ecological risk assessment of an individual pollutant; and (4) calculate the accumulated multi-substance potentially affected...... collected from the ecotoxicity database, (3) how to transform the acute toxicity data into chronic data, (4) how to best fit the toxicity data, (5) how to calculate the msPAF of multiple pollutants, and (6) how to determine the uncertainty of the SSD model”. In response to these questions, several...
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Dumitru Salajanu; Dennis Jacobs
2010-01-01
Forest inventory and analysis data are used to monitor the presence and extent of certain non-native invasive species. Effective control of its spread requires quality spatial distribution information. There is no clear consensus why some ecosystems are more favorable to non-native species. The objective of this study is to evaluate the reelative contribution of geo-...
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Marshall, L.; Carvalheiro, L.G.; Aguirre-Gutierrez, J.; Bos, M.; Groot, de G.A.; Kleijn, D.; Potts, S.G.; Reemer, M.; Roberts, S.P.M.; Scheper, J.A.; Biesmeijer, J.C.
2015-01-01
Species distribution models (SDM) are increasingly used to understand the factors that regulate variation in biodiversity patterns and to help plan conservation strategies. However, these models are rarely validated with independently collected data and it is unclear whether SDM performance is
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Distribution of metal and adsorbed guest species in zeolites
Energy Technology Data Exchange (ETDEWEB)
Chmelka, B.F.
1989-12-01
Because of their high internal surface areas and molecular-size cavity dimensions, zeolites are used widely as catalysts, shape- selective supports, or adsorbents in a variety of important chemical processes. For metal-catalyzed reactions, active metal species must be dispersed to sites within the zeolite pores that are accessible to diffusing reactant molecules. The distribution of the metal, together with transport and adsorption of reactant molecules in zeolite powders, are crucial to ultimate catalyst performance. The nature of the metal or adsorbed guest distribution is known, however, to be dramatically dependent upon preparatory conditions. Our objective is to understand, at the molecular level, how preparatory treatments influence the distribution of guest species in zeolites, in order that macroscopic adsorption and reaction properties of these materials may be better understood. The sensitivity of xenon to its adsorption environment makes {sup 129}Xe NMR spectroscopy an important diagnostic probe of metal clustering and adsorbate distribution processes in zeolites. The utility of {sup 129}Xe NMR depends on the mobility of the xenon atoms within the zeolite-guest system, together with the length scale of the sample heterogeneity being studied. In large pore zeolites containing dispersed guest species, such as Pt--NaY, {sup 129}Xe NMR is insensitive to fine structural details at room temperature.
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Distribution of metal and adsorbed guest species in zeolites
International Nuclear Information System (INIS)
Chmelka, B.F.
1989-12-01
Because of their high internal surface areas and molecular-size cavity dimensions, zeolites are used widely as catalysts, shape- selective supports, or adsorbents in a variety of important chemical processes. For metal-catalyzed reactions, active metal species must be dispersed to sites within the zeolite pores that are accessible to diffusing reactant molecules. The distribution of the metal, together with transport and adsorption of reactant molecules in zeolite powders, are crucial to ultimate catalyst performance. The nature of the metal or adsorbed guest distribution is known, however, to be dramatically dependent upon preparatory conditions. Our objective is to understand, at the molecular level, how preparatory treatments influence the distribution of guest species in zeolites, in order that macroscopic adsorption and reaction properties of these materials may be better understood. The sensitivity of xenon to its adsorption environment makes 129 Xe NMR spectroscopy an important diagnostic probe of metal clustering and adsorbate distribution processes in zeolites. The utility of 129 Xe NMR depends on the mobility of the xenon atoms within the zeolite-guest system, together with the length scale of the sample heterogeneity being studied. In large pore zeolites containing dispersed guest species, such as Pt--NaY, 129 Xe NMR is insensitive to fine structural details at room temperature
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Modeling of spatial distribution for scorpions of medical importance in the São Paulo State, Brazil
Directory of Open Access Journals (Sweden)
José Brites-Neto
2015-07-01
Full Text Available Aim: In this work, we aimed to develop maps of modeling geographic distribution correlating to environmental suitability for the two species of scorpions of medical importance at São Paulo State and to develop spatial configuration parameters for epidemiological surveillance of these species of venomous animals. Materials and Methods: In this study, 54 georeferenced points for Tityus serrulatus and 86 points for Tityus bahiensis and eight environmental indicators, were used to generate species distribution models in Maxent (maximum entropy modeling of species geographic distributions version 3.3.3k using 70% of data for training (n=38 to T. serrulatus and n=60 to T. bahiensis and 30% to test the models (n=16 for T. serrulatus and n=26 for T. bahiensis. The logistic threshold used to cut models in converting the continuous probability model into a binary model was the “maximum test sensitivity plus specificity,” provided by Maxent, with results of 0.4143 to T. serrulatus and of 0.3401 to T. bahiensis. The models were evaluated by the area under the curve (AUC, using the omission error and the binomial probability. With the data generated by Maxent, distribution maps were produced using the “ESRI® ArcGIS 10.2.2 for Desktop” software. Results: The models had high predictive success (AUC=0.7698±0.0533, omission error=0.2467 and p<0.001 for T. serrulatus and AUC=0.8205±0.0390, omission error=0.1917 and p<0.001 for T. bahiensis and the resultant maps showed a high environmental suitability in the north, central, and southeast of the state, confirming the increasing spread of these species. The environmental variables that mostly contributed to the scorpions species distribution model were rain precipitation (28.9% and tree cover (28.2% for the T. serrulatus and temperature (45.8% and thermal amplitude (12.6% for the T. bahiensis. Conclusion: The distribution model of these species of medical importance scorpions in São Paulo State
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González, Camila; Rebollar-Téllez, Eduardo A.; Ibáñez-Bernal, Sergio; Becker-Fauser, Ingeborg; Martínez-Meyer, Enrique; Peterson, A. Townsend; Sánchez-Cordero, Víctor
2011-01-01
Leishmaniases are a group of vector-borne diseases with different clinical manifestations caused by parasites transmitted by sand fly vectors. In Mexico, the sand fly Lutzomyia olmeca olmeca is the only vector proven to transmit the parasite Leishmania mexicana to humans, which causes leishmaniasis. Other vector species with potential medical importance have been obtained, but their geographic distributions and relation to transmission areas have never been assessed. We modeled the ecological niches of nine sand fly species and projected niches to estimate potential distributions by using known occurrences, environmental coverages, and the algorithms GARP and Maxent. All vector species were distributed in areas with known recurrent transmission, except for Lu. diabolica, which appeared to be related only to areas of occasional transmission in northern Mexico. The distribution of Lu. o. olmeca does not overlap with all reported cutaneous leishmaniasis cases, suggesting that Lu. cruciata and Lu. shannoni are likely also involved as primary vectors in those areas. Our study provides useful information of potential risk areas of leishmaniasis transmission in Mexico. PMID:22049037
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Directory of Open Access Journals (Sweden)
Marcelo A Dias
2011-08-01
Full Text Available Phoneutria bahiensis Simó & Brescovit, 2001 is a large ctenid spider inhabiting the states of Bahia and Espírito Santo, Brazil. Considering that it is probably endemic, this species was included in the Brazilian red book of threatened species. Here, we predict the distribution range of P. bahiensis using 19 bioclimatic variables in the model design. The most septentrional record for this spider was indicated for northern Bahia. The model predicts that the distribution range covers the Atlantic Forest from the state of Paraíba to Rio de Janeiro, with the best suitable area in the Atlantic Forest of the state of Bahia. The bioclimatic variable with the best contribution to the model was precipitation in the driest quarter. Based on collected data, the species inhabits Ombrophilous Forests and Restinga vegetation, two ecosystems of the Atlantic Forest biome. In the best-predicted area of distribution, eleven Conservation Units were included. This information could be considered for future conservation plans of this species.
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The prevalence and distribution of Fusarium species in Norwegian cereals: a survey
DEFF Research Database (Denmark)
Kosiak, B.; Torp, M.; Skjerve, E.
2003-01-01
the regions. A total of 695 grain samples were analysed. The amount of Fusarium infection varied with cereal species and region of origin. The most frequently isolated Fusarium spp. from all samples were F. avenaceum, F. poae, F. tricinctum and F. culmorum. Other important toxigenic Fusarium spp. were F......In the period 1994-1996 a post-harvest survey was conducted in wheat, barley and oats to assess the occurrence and geographic distribution of Fusarium species in Norwegian cereals. The number of samples investigated was adjusted proportionally to the production of each cereal species within...... and F. culmorum demonstrated in this study , corresponded to previously reported DON-distribution, although DON seems to be produced by different species in different regions. Distribution of the isolated Fusarium species and comparison between cereals and locations are discussed....
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Directory of Open Access Journals (Sweden)
Sarah J. Graves
2016-02-01
Full Text Available Mapping species through classification of imaging spectroscopy data is facilitating research to understand tree species distributions at increasingly greater spatial scales. Classification requires a dataset of field observations matched to the image, which will often reflect natural species distributions, resulting in an imbalanced dataset with many samples for common species and few samples for less common species. Despite the high prevalence of imbalanced datasets in multiclass species predictions, the effect on species prediction accuracy and landscape species abundance has not yet been quantified. First, we trained and assessed the accuracy of a support vector machine (SVM model with a highly imbalanced dataset of 20 tropical species and one mixed-species class of 24 species identified in a hyperspectral image mosaic (350–2500 nm of Panamanian farmland and secondary forest fragments. The model, with an overall accuracy of 62% ± 2.3% and F-score of 59% ± 2.7%, was applied to the full image mosaic (23,000 ha at a 2-m resolution to produce a species prediction map, which suggested that this tropical agricultural landscape is more diverse than what has been presented in field-based studies. Second, we quantified the effect of class imbalance on model accuracy. Model assessment showed a trend where species with more samples were consistently over predicted while species with fewer samples were under predicted. Standardizing sample size reduced model accuracy, but also reduced the level of species over- and under-prediction. This study advances operational species mapping of diverse tropical landscapes by detailing the effect of imbalanced data on classification accuracy and providing estimates of tree species abundance in an agricultural landscape. Species maps using data and methods presented here can be used in landscape analyses of species distributions to understand human or environmental effects, in addition to focusing conservation
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Characterization of Quercus species distributed in Jordan using ...
African Journals Online (AJOL)
Characterization of Quercus species distributed in Jordan using morphological and molecular markers. Mohammad S Jawarneh, Mohammad H Brake, Riyadh Muhaidat, Hussein M Migdadi, Jamil N Lahham, Ahmad Ali El-Oqlah ...
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Distribution of Vulpia species (Poaceae in Poland
Directory of Open Access Journals (Sweden)
Ludwik Frey
2011-01-01
Full Text Available The distribution of four species of the genus Vulpia [V. myuros (L. C.C. Gmel., V. bromoides (L. S.F. Gray, V. ciliata Dumort. and V. geniculata (L. Link] reported in Poland has been studied. Currently, V. myuros and especially V. bromoides are very rare species, and their greatest concentration can be found only in the Lower Silesia region. The number of their localities decreased after 1950 and it seems resonable to include both species in the "red list" of threatened plants in Poland: V. myuros in the EN category, V. bromoides in the CR category. V. ciliata and V. geniculata are very rare ephemerophytes and their localities not confirmed during ca 60 years are of historical interest only.
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Directory of Open Access Journals (Sweden)
Katarzyna Szczepańska
2015-12-01
Full Text Available The paper presents models of potential geographical distribution of Xanthoparmelia delisei, X. loxodes, and X. verruculifera in Central Europe. The models were developed with MaxEnt (maximum entropy algorithm based on 224 collection localities and bioclimatic variables. The applied method enabled to identify the areas where climatic conditions are the most suitable for modeled species outside their known localities. According to obtained model, high potential distribution of the X. delisei and X. loxodes was found in the northern and northeastern Poland, when areas most suitable for X. verruculifera were placed in the south, especially in the Carpathians. Model also suggests that potential distribution of X. delisei could be wider than known data on its occurrence and extend to Lithuania, Belarus and the Czech Republic. MaxEnt modeling of X. loxodes showed the widest potential distribution for this species in Central Europe with the best regions in Lithuania. Potential distribution in all models was strongly influenced by precipitation-related variables. All the modelled species prefer areas where precipitation in the coldest quarter is very low.
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West, Amanda M.; Evangelista, Paul H.; Jarnevich, Catherine S.; Kumar, Sunil; Swallow, Aaron; Luizza, Matthew; Chignell, Steve
2017-01-01
Among the most pressing concerns of land managers in post-wildfire landscapes are the establishment and spread of invasive species. Land managers need accurate maps of invasive species cover for targeted management post-disturbance that are easily transferable across space and time. In this study, we sought to develop an iterative, replicable methodology based on limited invasive species occurrence data, freely available remotely sensed data, and open source software to predict the distribution of Bromus tectorum (cheatgrass) in a post-wildfire landscape. We developed four species distribution models using eight spectral indices derived from five months of Landsat 8 Operational Land Imager (OLI) data in 2014. These months corresponded to both cheatgrass growing period and time of field data collection in the study area. The four models were improved using an iterative approach in which a threshold for cover was established, and all models had high sensitivity values when tested on an independent dataset. We also quantified the area at highest risk for invasion in future seasons given 2014 distribution, topographic covariates, and seed dispersal limitations. These models demonstrate the effectiveness of using derived multi-date spectral indices as proxies for species occurrence on the landscape, the importance of selecting thresholds for invasive species cover to evaluate ecological risk in species distribution models, and the applicability of Landsat 8 OLI and the Software for Assisted Habitat Modeling for targeted invasive species management.
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Solvable Catalyzed Birth-Death-Exchange Competition Model of Three Species
International Nuclear Information System (INIS)
Wang Haifeng; Gao Yan; Zhang Heng; Lin Zhenquan
2009-01-01
A competition model of three species in exchange-driven aggregation growth is proposed. In the model, three distinct aggregates grow by exchange of monomers and in parallel, birth of species A is catalyzed by species B and death of species A is catalyzed by species C. The rates for both catalysis processes are proportional to kj ν and kj ω respectively, where ν(Ω) is a parameter reflecting the dependence of the catalysis reaction rate of birth (death) on the catalyst aggregate's size. The kinetic evolution behaviors of the three species are investigated by the rate equation approach based on the mean-field theory. The form of the aggregate size distribution of A-species a k (t) is found to be dependent crucially on the two catalysis rate kernel parameters. The results show that (i) in case of μ ≤ 0, the form of a k (t) mainly depends on the competition between self-exchange of species A and species-C-catalyzed death of species A; (ii) in case of ν > 0, the form of a k (t) mainly depends on the competition between species-B-catalyzed birth of species A and species-C-catalyzed death of species A. (interdisciplinary physics and related areas of science and technology)
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Directory of Open Access Journals (Sweden)
Ammirati Joseph
2011-07-01
Full Text Available Abstract Background Cortinarius species in section Calochroi display local, clinal and circumboreal patterns of distribution across the Northern Hemisphere where these ectomycorrhizal fungi occur with host trees throughout their geographical range within a continent, or have disjunct intercontinental distributions, the origins of which are not understood. We inferred evolutionary histories of four species, 1 C. arcuatorum, 2 C. aureofulvus, 3 C. elegantior and 4 C. napus, from populations distributed throughout the Old World, and portions of the New World (Central- and North America based on genetic variation of 154 haplotype internal transcribed spacer (ITS sequences from 83 population samples. By describing the population structure of these species across their geographical distribution, we attempt to identify their historical migration and patterns of diversification. Results Models of population structure from nested clade, demographic and coalescent-based analyses revealed genetically differentiated and geographically structured haplotypes in C. arcuatorum and C. elegantior, while C. aureofulvus showed considerably less population structure and C. napus lacked sufficient genetic differentiation to resolve any population structure. Disjunct populations within C. arcuatorum, C. aureofulvus and C. elegantior show little or no morphological differentiation, whereas in C. napus there is a high level of homoplasy and phenotypic plasticity for veil and lamellae colour. The ITS sequences of the type specimens of C. albobrunnoides and C. albobrunnoides var. violaceovelatus were identical to one another and are treated as one species with a wider range of geographic distribution under C. napus. Conclusions Our results indicate that each of the Calochroi species has undergone a relatively independent evolutionary history, hypothesised as follows: 1 a widely distributed ancestral population of C. arcuatorum diverged into distinctive sympatric
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Map of Life - A Dashboard for Monitoring Planetary Species Distributions
Jetz, W.
2016-12-01
Geographic information about biodiversity is vital for understanding the many services nature provides and their potential changes, yet remains unreliable and often insufficient. By integrating a wide range of knowledge about species distributions and their dynamics over time, Map of Life supports global biodiversity education, monitoring, research and decision-making. Built on a scalable web platform geared for large biodiversity and environmental data, Map of Life endeavors provides species range information globally and species lists for any area. With data and technology provided by NASA and Google Earth Engine, tools under development use remote sensing-based environmental layers to enable on-the-fly predictions of species distributions, range changes, and early warning signals for threatened species. The ultimate vision is a globally connected, collaborative knowledge- and tool-base for regional and local biodiversity decision-making, education, monitoring, and projection. For currently available tools, more information and to follow progress, go to MOL.org.
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VEGETATIVE MORPHOLOGY FOR SPECIES IDENTIFICATION OF TROPICAL TREES: FAMILY DISTRIBUTION
Directory of Open Access Journals (Sweden)
Peter Hargreaves
2006-03-01
Full Text Available Tree specimens from the ESAL herbarium of the Universidade Federal de Lavras, Minas Gerais, Brazil, were describedby vegetative characteristics using CARipé, a Microsoft Access database application specially developed for this study. Only onespecimen per species was usually described. Thus, 2 observers described 567 herbarium species as a base to test methods ofidentification as part of a larger study. The present work formed part of that study and provides information on the distribution of22 vegetative characters among 16 families having 10 or more species described. The characters are discussed. The study foundmarked differences, even discontinuities, of distributions of characters between those families. Therefore it should be possible toincorporate phylogenetic relationships into the identification process.
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Worthington, Thomas A.; Zhang, T.; Logue, Daniel R.; Mittelstet, Aaron R.; Brewer, Shannon K.
2016-01-01
Truncated distributions of pelagophilic fishes have been observed across the Great Plains of North America, with water use and landscape fragmentation implicated as contributing factors. Developing conservation strategies for these species is hindered by the existence of multiple competing flow regime hypotheses related to species persistence. Our primary study objective was to compare the predicted distributions of one pelagophil, the Arkansas River Shiner Notropis girardi, constructed using different flow regime metrics. Further, we investigated different approaches for improving temporal transferability of the species distribution model (SDM). We compared four hypotheses: mean annual flow (a baseline), the 75th percentile of daily flow, the number of zero-flow days, and the number of days above 55th percentile flows, to examine the relative importance of flows during the spawning period. Building on an earlier SDM, we added covariates that quantified wells in each catchment, point source discharges, and non-native species presence to a structured variable framework. We assessed the effects on model transferability and fit by reducing multicollinearity using Spearman’s rank correlations, variance inflation factors, and principal component analysis, as well as altering the regularization coefficient (β) within MaxEnt. The 75th percentile of daily flow was the most important flow metric related to structuring the species distribution. The number of wells and point source discharges were also highly ranked. At the default level of β, model transferability was improved using all methods to reduce collinearity; however, at higher levels of β, the correlation method performed best. Using β = 5 provided the best model transferability, while retaining the majority of variables that contributed 95% to the model. This study provides a workflow for improving model transferability and also presents water-management options that may be considered to improve the
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Drought tolerance of tropical tree species : functional traits, trade-offs and species distribution
Markesteijn, L.
2010-01-01
KEY-WORDS:
Bolivia, drought tolerance, shade tolerance, functional traits, trade-offs, ecophysiology, species distribution
Tropical forests occur under rainfall regimes that vary greatly in the rainfall pattern and frequency and intensity of drought. Consequently water availability is -
Ecological plant epigenetics: Evidence from model and non-model species, and the way forward.
Richards, Christina L; Alonso, Conchita; Becker, Claude; Bossdorf, Oliver; Bucher, Etienne; Colomé-Tatché, Maria; Durka, Walter; Engelhardt, Jan; Gaspar, Bence; Gogol-Döring, Andreas; Grosse, Ivo; van Gurp, Thomas P; Heer, Katrin; Kronholm, Ilkka; Lampei, Christian; Latzel, Vít; Mirouze, Marie; Opgenoorth, Lars; Paun, Ovidiu; Prohaska, Sonja J; Rensing, Stefan A; Stadler, Peter F; Trucchi, Emiliano; Ullrich, Kristian; Verhoeven, Koen J F
2017-12-01
Growing evidence shows that epigenetic mechanisms contribute to complex traits, with implications across many fields of biology. In plant ecology, recent studies have attempted to merge ecological experiments with epigenetic analyses to elucidate the contribution of epigenetics to plant phenotypes, stress responses, adaptation to habitat, and range distributions. While there has been some progress in revealing the role of epigenetics in ecological processes, studies with non-model species have so far been limited to describing broad patterns based on anonymous markers of DNA methylation. In contrast, studies with model species have benefited from powerful genomic resources, which contribute to a more mechanistic understanding but have limited ecological realism. Understanding the significance of epigenetics for plant ecology requires increased transfer of knowledge and methods from model species research to genomes of evolutionarily divergent species, and examination of responses to complex natural environments at a more mechanistic level. This requires transforming genomics tools specifically for studying non-model species, which is challenging given the large and often polyploid genomes of plants. Collaboration among molecular geneticists, ecologists and bioinformaticians promises to enhance our understanding of the mutual links between genome function and ecological processes. © 2017 The Authors. Ecology Letters published by CNRS and John Wiley & Sons Ltd.
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Louis R Iverson; Anantha M. Prasad; Mark W. Schwartz; Mark W. Schwartz
2005-01-01
We predict current distribution and abundance for tree species present in eastern North America, and subsequently estimate potential suitable habitat for those species under a changed climate with 2 x CO2. We used a series of statistical models (i.e., Regression Tree Analysis (RTA), Multivariate Adaptive Regression Splines (MARS), Bagging Trees (...
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Two-species occupancy modeling accounting for species misidentification and nondetection
Chambert, Thierry; Grant, Evan H. Campbell; Miller, David A. W.; Nichols, James; Mulder, Kevin P.; Brand, Adrianne B,
2018-01-01
1. In occupancy studies, species misidentification can lead to false positive detections, which can cause severe estimator biases. Currently, all models that account for false positive errors only consider omnibus sources of false detections and are limited to single species occupancy. 2. However, false detections for a given species often occur because of the misidentification with another, closely-related species. To exploit this explicit source of false positive detection error, we develop a two-species occupancy model that accounts for misidentifications between two species of interest. As with other false positive models, identifiability is greatly improved by the availability of unambiguous detections at a subset of site-occasions. Here, we consider the case where some of the field observations can be confirmed using laboratory or other independent identification methods (“confirmatory data”). 3. We performed three simulation studies to (1) assess the model’s performance under various realistic scenarios, (2) investigate the influence of the proportion of confirmatory data on estimator accuracy, and (3) compare the performance of this two-species model with that of the single-species false positive model. The model shows good performance under all scenarios, even when only small proportions of detections are confirmed (e.g., 5%). It also clearly outperforms the single-species model.
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The implicit assumption of symmetry and the species abundance distribution
Alonso, D.; Ostling, A.; Etienne, R.S.
2008-01-01
Species abundance distributions (SADs) have played a historical role in the development of community ecology. They summarize information about the number and the relative abundance of the species encountered in a sample from a given community. For years ecologists have developed theory to
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The implicit assumption of symmetry and the species abundance distribution
Alonso, David; Ostling, Annette; Etienne, Rampal S.
Species abundance distributions (SADs) have played a historical role in the development of community ecology. They summarize information about the number and the relative abundance of the species encountered in a sample from a given community. For years ecologists have developed theory to
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New record of the sympatric distribution of two Asian species of the horseshoe crab
Digital Repository Service at National Institute of Oceanography (India)
Chatterji, A.
distribution of two Asian species of the horses... http://www.ias.ac.in/currsci/sep25/articles14.htm 1 of 3 2/11/05 9:47 AM New record of the sympatric distribution of two Asian species of the horseshoe crab The geographical distribution of four extant species...... http://www.ias.ac.in/currsci/sep25/articles14.htm 2 of 3 2/11/05 9:47 AM This species was found breeding actively on relatively clean and sandy beaches. The other species (C. rotundicauda) was not reported in these areas.However, during the survey...
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Node-based analysis of species distributions
DEFF Research Database (Denmark)
Borregaard, Michael Krabbe; Rahbek, Carsten; Fjeldså, Jon
2014-01-01
overrepresentation score (SOS) and the geographic node divergence (GND) score, which together combine ecological and evolutionary patterns into a single framework and avoids many of the problems that characterize community phylogenetic methods in current use.This approach goes through each node in the phylogeny...... with case studies on two groups with well-described biogeographical histories: a local-scale community data set of hummingbirds in the North Andes, and a large-scale data set of the distribution of all species of New World flycatchers. The node-based analysis of these two groups generates a set...... of intuitively interpretable patterns that are consistent with current biogeographical knowledge.Importantly, the results are statistically tractable, opening many possibilities for their use in analyses of evolutionary, historical and spatial patterns of species diversity. The method is implemented...
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Integrating multiple distribution models to guide conservation efforts of an endangered toad
Treglia, Michael L.; Fisher, Robert N.; Fitzgerald, Lee A.
2015-01-01
Species distribution models are used for numerous purposes such as predicting changes in species’ ranges and identifying biodiversity hotspots. Although implications of distribution models for conservation are often implicit, few studies use these tools explicitly to inform conservation efforts. Herein, we illustrate how multiple distribution models developed using distinct sets of environmental variables can be integrated to aid in identification sites for use in conservation. We focus on the endangered arroyo toad (Anaxyrus californicus), which relies on open, sandy streams and surrounding floodplains in southern California, USA, and northern Baja California, Mexico. Declines of the species are largely attributed to habitat degradation associated with vegetation encroachment, invasive predators, and altered hydrologic regimes. We had three main goals: 1) develop a model of potential habitat for arroyo toads, based on long-term environmental variables and all available locality data; 2) develop a model of the species’ current habitat by incorporating recent remotely-sensed variables and only using recent locality data; and 3) integrate results of both models to identify sites that may be employed in conservation efforts. We used a machine learning technique, Random Forests, to develop the models, focused on riparian zones in southern California. We identified 14.37% and 10.50% of our study area as potential and current habitat for the arroyo toad, respectively. Generally, inclusion of remotely-sensed variables reduced modeled suitability of sites, thus many areas modeled as potential habitat were not modeled as current habitat. We propose such sites could be made suitable for arroyo toads through active management, increasing current habitat by up to 67.02%. Our general approach can be employed to guide conservation efforts of virtually any species with sufficient data necessary to develop appropriate distribution models.
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International Nuclear Information System (INIS)
Mu, Yunsong; Wu, Fengchang; Chen, Cheng; Liu, Yuedan; Zhao, Xiaoli; Haiqing Liao; Giesy, John P.
2014-01-01
Criteria continuous concentrations (CCCs) are useful for describing chronic exposure to pollutants and setting water quality standards to protect aquatic life. However, because of financial, practical, or ethical restrictions on toxicity testing, few data are available to derive CCCs. In this study, CCCs for 34 metals or metalloids were derived using quantitative ion character-activity relationships–species sensitivity distributions (QICAR–SSD) and the final acute-chronic ratio (FACR) method. The results showed that chronic toxic potencies were correlated with several physico-chemical properties among eight species chosen, where the softness index was the most predictive characteristic. Predicted CCCs for most of the metals, except for Lead and Iron, were within a range of 10-fold of values recommended by the U.S. EPA. The QICAR–SSD model was superior to the FACR method for prediction of data-poor metals. This would have significance for predicting toxic potencies and criteria thresholds of more metals or metalloids. - Highlights: • We investigate relationships between σp and log-NOEC in eight species. • The QICAR–SSD model, FACR, and CMC/CCC were used to predict CCCs. • They are as a supplement to screening for toxicities, criteria and standards. - CCCs for 34 metals/metalloids were predicted by use of QICAR–SSD model and FACR method
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Distribution characteristics of mineral elements in tree Species from ...
African Journals Online (AJOL)
Tree species populations were 44 in Akyaakrom (AS), 29 in Dopiri (DS), and families were 18 in AS and 16 in DS. Tree densities were 121 and 99 in AS and DS, respectively, in 0.57 ha. In terms of tree species population, diversity and density, AS was superior to DS. The distribution of major mineral elements in the leaves ...
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Dispersal ability determines the scaling properties of species abundance distributions
DEFF Research Database (Denmark)
Borda-De-Água, Luís; Whittaker, Robert James; Cardoso, Pedro
2017-01-01
with computer simulations, low dispersal ability species generate a hump for intermediate abundance classes earlier than the distributions of high dispersal ability species. Importantly, when plotted as function of sample size, the raw moments of the SADs of arthropods have a power law pattern similar...
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Magarey, Roger; Newton, Leslie; Hong, Seung C.; Takeuchi, Yu; Christie, Dave; Jarnevich, Catherine S.; Kohl, Lisa; Damus, Martin; Higgins, Steven I.; Miller, Leah; Castro, Karen; West, Amanda; Hastings, John; Cook, Gericke; Kartesz, John; Koop, Anthony
2018-01-01
This study compares four models for predicting the potential distribution of non-indigenous weed species in the conterminous U.S. The comparison focused on evaluating modeling tools and protocols as currently used for weed risk assessment or for predicting the potential distribution of invasive weeds. We used six weed species (three highly invasive and three less invasive non-indigenous species) that have been established in the U.S. for more than 75 years. The experiment involved providing non-U. S. location data to users familiar with one of the four evaluated techniques, who then developed predictive models that were applied to the United States without knowing the identity of the species or its U.S. distribution. We compared a simple GIS climate matching technique known as Proto3, a simple climate matching tool CLIMEX Match Climates, the correlative model MaxEnt, and a process model known as the Thornley Transport Resistance (TTR) model. Two experienced users ran each modeling tool except TTR, which had one user. Models were trained with global species distribution data excluding any U.S. data, and then were evaluated using the current known U.S. distribution. The influence of weed species identity and modeling tool on prevalence and sensitivity effects was compared using a generalized linear mixed model. Each modeling tool itself had a low statistical significance, while weed species alone accounted for 69.1 and 48.5% of the variance for prevalence and sensitivity, respectively. These results suggest that simple modeling tools might perform as well as complex ones in the case of predicting potential distribution for a weed not yet present in the United States. Considerations of model accuracy should also be balanced with those of reproducibility and ease of use. More important than the choice of modeling tool is the construction of robust protocols and testing both new and experienced users under blind test conditions that approximate operational conditions.
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Directory of Open Access Journals (Sweden)
Tiessen Axel
2012-02-01
Full Text Available Abstract Background The sizes of proteins are relevant to their biochemical structure and for their biological function. The statistical distribution of protein lengths across a diverse set of taxa can provide hints about the evolution of proteomes. Results Using the full genomic sequences of over 1,302 prokaryotic and 140 eukaryotic species two datasets containing 1.2 and 6.1 million proteins were generated and analyzed statistically. The lengthwise distribution of proteins can be roughly described with a gamma type or log-normal model, depending on the species. However the shape parameter of the gamma model has not a fixed value of 2, as previously suggested, but varies between 1.5 and 3 in different species. A gamma model with unrestricted shape parameter described best the distributions in ~48% of the species, whereas the log-normal distribution described better the observed protein sizes in 42% of the species. The gamma restricted function and the sum of exponentials distribution had a better fitting in only ~5% of the species. Eukaryotic proteins have an average size of 472 aa, whereas bacterial (320 aa and archaeal (283 aa proteins are significantly smaller (33-40% on average. Average protein sizes in different phylogenetic groups were: Alveolata (628 aa, Amoebozoa (533 aa, Fornicata (543 aa, Placozoa (453 aa, Eumetazoa (486 aa, Fungi (487 aa, Stramenopila (486 aa, Viridiplantae (392 aa. Amino acid composition is biased according to protein size. Protein length correlated negatively with %C, %M, %K, %F, %R, %W, %Y and positively with %D, %E, %Q, %S and %T. Prokaryotic proteins had a different protein size bias for %E, %G, %K and %M as compared to eukaryotes. Conclusions Mathematical modeling of protein length empirical distributions can be used to asses the quality of small ORFs annotation in genomic releases (detection of too many false positive small ORFs. There is a negative correlation between average protein size and total number of
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Lin, Guojun; Stralberg, Diana; Gong, Guiquan; Huang, Zhongliang; Ye, Wanhui; Wu, Linfang
2013-01-01
Quantifying the relative contributions of environmental conditions and spatial factors to species distribution can help improve our understanding of the processes that drive diversity patterns. In this study, based on tree inventory, topography and soil data from a 20-ha stem-mapped permanent forest plot in Guangdong Province, China, we evaluated the influence of different ecological processes at different spatial scales using canonical redundancy analysis (RDA) at the community level and multiple linear regression at the species level. At the community level, the proportion of explained variation in species distribution increased with grid-cell sizes, primarily due to a monotonic increase in the explanatory power of environmental variables. At the species level, neither environmental nor spatial factors were important determinants of overstory species' distributions at small cell sizes. However, purely spatial variables explained most of the variation in the distributions of understory species at fine and intermediate cell sizes. Midstory species showed patterns that were intermediate between those of overstory and understory species. At the 20-m cell size, the influence of spatial factors was stronger for more dispersal-limited species, suggesting that much of the spatial structuring in this community can be explained by dispersal limitation. Comparing environmental factors, soil variables had higher explanatory power than did topography for species distribution. However, both topographic and edaphic variables were highly spatial structured. Our results suggested that dispersal limitation has an important influence on fine-intermediate scale (from several to tens of meters) species distribution, while environmental variability facilitates species distribution at intermediate (from ten to tens of meters) and broad (from tens to hundreds of meters) scales.
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Identity and distribution of southern African sciaenid fish species of ...
African Journals Online (AJOL)
Two Umbrina species, U. canariensis Valenciennes 1843 and U. robinsoni Gilchrist and Thompson 1908, are recognised from southern Africa. The latter species was hitherto believed to be a synonym of Umbrina ronchus Valenciennes 1843 (type locality Canary Islands). U. canariensis is distributed along the South Africa ...
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Using habitat suitability models to target invasive plant species surveys.
Crall, Alycia W; Jarnevich, Catherine S; Panke, Brendon; Young, Nick; Renz, Mark; Morisette, Jeffrey
2013-01-01
Managers need new tools for detecting the movement and spread of nonnative, invasive species. Habitat suitability models are a popular tool for mapping the potential distribution of current invaders, but the ability of these models to prioritize monitoring efforts has not been tested in the field. We tested the utility of an iterative sampling design (i.e., models based on field observations used to guide subsequent field data collection to improve the model), hypothesizing that model performance would increase when new data were gathered from targeted sampling using criteria based on the initial model results. We also tested the ability of habitat suitability models to predict the spread of invasive species, hypothesizing that models would accurately predict occurrences in the field, and that the use of targeted sampling would detect more species with less sampling effort than a nontargeted approach. We tested these hypotheses on two species at the state scale (Centaurea stoebe and Pastinaca sativa) in Wisconsin (USA), and one genus at the regional scale (Tamarix) in the western United States. These initial data were merged with environmental data at 30-m2 resolution for Wisconsin and 1-km2 resolution for the western United States to produce our first iteration models. We stratified these initial models to target field sampling and compared our models and success at detecting our species of interest to other surveys being conducted during the same field season (i.e., nontargeted sampling). Although more data did not always improve our models based on correct classification rate (CCR), sensitivity, specificity, kappa, or area under the curve (AUC), our models generated from targeted sampling data always performed better than models generated from nontargeted data. For Wisconsin species, the model described actual locations in the field fairly well (kappa = 0.51, 0.19, P guiding invasive species monitoring, and we support the use of an iterative sampling design for
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Rodríguez-Castañeda, G; MacVean, C; Cardona, C; Hof, A R
2017-07-01
Factors limiting distribution range for most species are generally unknown regardless of whether they are native or invasive. We studied factors that could enable or restrict the distribution of two cosmopolitan invasive leafminer fly species, Liriomyza huidobrensis (Blanchard) and Liriomyza sativae (Blanchard) in their native niche. In order to test which ecological and environmental factors affect leafminer distribution we conducted thermal tolerance assays, sampled along elevation gradients and modeled species distribution. Findings from the field and rearing chambers showed a physiological restriction due to high temperatures for L. huidobrensis at 28-29 °C, above which adult emergence is compromised. We also found that maximum temperatures below 22 °C, typical of tropical highlands, favored L. huidobrensis. L. sativae was found across a wider temperature range (i.e., from 21 to 36 °C) in Guatemala. Our finding of a physiological threshold in temperature for L. huidobrensis may enable us to predict its invasive risk when combined with the environmental conditions at horticultural ports of entry and the global agricultural landscape. Further, it strengthens our predictions on shifts in distribution of the leafminer fly under future climate. We also found a temperature mediated competitive exclusion interaction between the two herbivore species, where L. sativae occurred at temperatures < 22 °C only in the absence of L. huidobrensis. We show that parasitoids had a negative effect on the leafminer flies, which varied with host plant. Finally, we show the importance of taking a multiaspect approach when investigating what limits distribution and invasiveness of a species. © The Authors 2017. Published by Oxford University Press on behalf of Entomological Society of America.
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Directory of Open Access Journals (Sweden)
Nathan M Bacheler
Full Text Available Marine fish abundance and distribution often varies across spatial scales for a variety of reasons, and this variability has significant ecological and management consequences. We quantified the distribution of reef-associated fish species along the southeast United States Atlantic coast using underwater video survey samples (N = 4,855 in 2011-2014 to elucidate variability within species across space, depths, and habitats, as well as describe broad-scale patterns in species richness. Thirty-two species were seen at least 10 times on video, and the most commonly observed species were red porgy (Pagrus pagrus; 41.4% of videos, gray triggerfish (Balistes capriscus; 31.0%, black sea bass (Centropristis striata; 29.1%, vermilion snapper (Rhomboplites aurorubens; 27.7%, and red snapper (Lutjanus campechanus; 22.6%. Using generalized additive models, we found that most species were non-randomly distributed across space, depths, and habitats. Most rare species were observed along the continental shelf break, except for goliath grouper (Epinephelus itajara, which was found on the continental shelf in Florida and Georgia. We also observed higher numbers of species in shelf-break habitats from southern North Carolina to Georgia, and fewer in shallower water and at the northern and southern ends of the southeast United States Atlantic coast. Our study provides the first broad-scale description of the spatial distribution of reef fish in the region to be based on fishery-independent data, reinforces the utility of underwater video to survey reef fish, and can help improve the management of reef fish in the SEUS, for example, by improving indices of abundance.
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Climate change and plant distribution: local models predict high-elevation persistence
DEFF Research Database (Denmark)
Randin, Christophe F.; Engler, Robin; Normand, Signe
2009-01-01
Mountain ecosystems will likely be affected by global warming during the 21st century, with substantial biodiversity loss predicted by species distribution models (SDMs). Depending on the geographic extent, elevation range, and spatial resolution of data used in making these models, different rates...
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Are range-size distributions consistent with species-level heritability?
DEFF Research Database (Denmark)
Borregaard, Michael Krabbe; Gotelli, Nicholas; Rahbek, Carsten
2012-01-01
The concept of species-level heritability is widely contested. Because it is most likely to apply to emergent, species-level traits, one of the central discussions has focused on the potential heritability of geographic range size. However, a central argument against range-size heritability has...... been that it is not compatible with the observed shape of present-day species range-size distributions (SRDs), a claim that has never been tested. To assess this claim, we used forward simulation of range-size evolution in clades with varying degrees of range-size heritability, and compared the output...
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Ai, Dexiecuo; Gravel, Dominique; Chu, Chengjin; Wang, Gang
2013-01-01
The correspondence between species distribution and the environment depends on species' ability to track favorable environmental conditions (via dispersal) and to maintain competitive hierarchy against the constant influx of migrants (mass effect) and demographic stochasticity (ecological drift). Here we report a simulation study of the influence of landscape structure on species distribution. We consider lottery competition for space in a spatially heterogeneous environment, where the landscape is represented as a network of localities connected by dispersal. We quantified the contribution of neutrality and species sorting to their spatial distribution. We found that neutrality increases and the strength of species-sorting decreases with the centrality of a community in the landscape when the average dispersal among communities is low, whereas the opposite was found at elevated dispersal. We also found that the strength of species-sorting increases with environmental heterogeneity. Our results illustrate that spatial structure of the environment and of dispersal must be taken into account for understanding species distribution. We stress the importance of spatial geographic structure on the relative importance of niche vs. neutral processes in controlling community dynamics.
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Patterns and causes of species richness: a general simulation model for macroecology
DEFF Research Database (Denmark)
Gotelli, Nicholas J; Anderson, Marti J; Arita, Hector T
2009-01-01
to a mechanistic understanding of the patterns. During the past two decades, macroecologists have successfully addressed technical problems posed by spatial autocorrelation, intercorrelation of predictor variables and non-linearity. However, curve-fitting approaches are problematic because most theoretical models...... in macroecology do not make quantitative predictions, and they do not incorporate interactions among multiple forces. As an alternative, we propose a mechanistic modelling approach. We describe computer simulation models of the stochastic origin, spread, and extinction of species' geographical ranges...... in an environmentally heterogeneous, gridded domain and describe progress to date regarding their implementation. The output from such a general simulation model (GSM) would, at a minimum, consist of the simulated distribution of species ranges on a map, yielding the predicted number of species in each grid cell...
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Liu, He-Ming; Wang, Zhang-Hua; Ma, Zun-Ping; Fang, Xiao-Feng; Zhang, Jian; Wang, Xi-Hua
2016-01-01
The pervasive pattern of aggregated tree distributions in natural communities is commonly explained by the joint effect of two clustering processes: environmental filtering and dispersal limitation, yet little consensus remains on the relative importance of the two clustering processes on tree aggregations. Different life stages of examined species were thought to be one possible explanation of this disagreement, because the effect of environmental filtering and dispersal limitation are expected to increase and decrease with tree life stages, respectively. However, few studies have explicitly tested these expectations. In this study, we evaluated these expectations by three different methods (species-habitat association test based on Poisson Clustering model and spatial point pattern analyses based on Heterogeneous Poisson model and the jointly modeling approach) using 36 species in a 20-ha subtropical forest plot. Our results showed that the percentage of species with significant habitat association increased with life stages, and there were fewer species affected by dispersal limitation in later life stages compared with those in earlier stages. Percentage of variance explained by the environmental filtering and dispersal limitation also increases and decreases with life stages. These results provided a promising alternative explanation on the existing mixed results about the relative importance of the two clustering processes. These findings also highlighted the importance of plant life stages for fully understanding species distributions and species coexistence. PMID:27227538
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[Species composition and distribution of medical mollusca in Shanghai City].
Guo, Yun-hai; Lv, Shan; Gu, Wen-biao; Liu, He-xiang; Wu, Ying; Zhang, Yi
2015-02-01
To investigate the species diversity and distribution of medical mollusca in Shanghai City. From August 2012 to October 2013, all kinds of habitats in 8 districts and counties in Shanghai City, namely Jiading, Qingpu, Baoshan, Minhang, Songjiang, Jinshan, Chongming, Pudong, were selected for the field survey according to the distribution characteristics of the river system, and all the specimens of medical mollusca in the investigation sites were collected and classified by morphological identification. Meanwhile, the species composition, habitats as well as the fauna of the medical mollusca collected were analyzed. A total of 5,211 specimens were collected, which belonged to 2 classes, 14 families, 18 genera and 25 species, including Oncomelania hupensis hupensis, Pomacea canaliculata, Parafossarulus striatulus, Alocinma longicornis, Physa acuta, Galba pervia, Hippeutis cantori, etc. The species numbers of medical mollusca in Chongming, Jinshan, Pudong new area and Qingpu districts (counties) were 22, 22, 21 and 20, respectively, which were more than those of other areas. The habitat analysis suggested that the species numbers in the river and wetland were the most, both of which were 14 species. The main faunas of the medical mollusca in Shanghai were the cosmopolitan and oriental species. The freshwater gastropod species are paucity in Shanghai City, but almost of them can be served as the intermediate hosts of certain parasites to transmit snail-related parasitic diseases, so the surveillance of medical mollusca should be strengthened.
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Neigel, J E; Avise, J C
1993-12-01
In rapidly evolving molecules, such as animal mitochondrial DNA, mutations that delineate specific lineages may not be dispersed at sufficient rates to attain an equilibrium between genetic drift and gene flow. Here we predict conditions that lead to nonequilibrium geographic distributions of mtDNA lineages, test the robustness of these predictions and examine mtDNA data sets for consistency with our model. Under a simple isolation by distance model, the variance of an mtDNA lineage's geographic distribution is expected be proportional to its age. Simulation results indicated that this relationship is fairly robust. Analysis of mtDNA data from natural populations revealed three qualitative distributional patterns: (1) significant departure of lineage structure from equilibrium geographic distributions, a pattern exhibited in three rodent species with limited dispersal; (2) nonsignificant departure from equilibrium expectations, exhibited by two avian and two marine fish species with potentials for relatively long-distance dispersal; and (3) a progression from nonequilibrium distributions for younger lineages to equilibrium distributions for older lineages, a condition displayed by one surveyed avian species. These results demonstrate the advantages of considering mutation and genealogy in the interpretation of mtDNA geographic variation.
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Benchmarking novel approaches for modelling species range dynamics.
Zurell, Damaris; Thuiller, Wilfried; Pagel, Jörn; Cabral, Juliano S; Münkemüller, Tamara; Gravel, Dominique; Dullinger, Stefan; Normand, Signe; Schiffers, Katja H; Moore, Kara A; Zimmermann, Niklaus E
2016-08-01
Increasing biodiversity loss due to climate change is one of the most vital challenges of the 21st century. To anticipate and mitigate biodiversity loss, models are needed that reliably project species' range dynamics and extinction risks. Recently, several new approaches to model range dynamics have been developed to supplement correlative species distribution models (SDMs), but applications clearly lag behind model development. Indeed, no comparative analysis has been performed to evaluate their performance. Here, we build on process-based, simulated data for benchmarking five range (dynamic) models of varying complexity including classical SDMs, SDMs coupled with simple dispersal or more complex population dynamic models (SDM hybrids), and a hierarchical Bayesian process-based dynamic range model (DRM). We specifically test the effects of demographic and community processes on model predictive performance. Under current climate, DRMs performed best, although only marginally. Under climate change, predictive performance varied considerably, with no clear winners. Yet, all range dynamic models improved predictions under climate change substantially compared to purely correlative SDMs, and the population dynamic models also predicted reasonable extinction risks for most scenarios. When benchmarking data were simulated with more complex demographic and community processes, simple SDM hybrids including only dispersal often proved most reliable. Finally, we found that structural decisions during model building can have great impact on model accuracy, but prior system knowledge on important processes can reduce these uncertainties considerably. Our results reassure the clear merit in using dynamic approaches for modelling species' response to climate change but also emphasize several needs for further model and data improvement. We propose and discuss perspectives for improving range projections through combination of multiple models and for making these approaches
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Mori, Gustavo M; Zucchi, Maria I; Sampaio, Iracilda; Souza, Anete P
2015-04-10
Mangrove plants grow in the intertidal zone in tropical and subtropical regions worldwide. The global latitudinal distribution of the mangrove is mainly influenced by climatic and oceanographic features. Because of current climate changes, poleward range expansions have been reported for the major biogeographic regions of mangrove forests in the Western and Eastern Hemispheres. There is evidence that mangrove forests also responded similarly after the last glaciation by expanding their ranges. In this context, the use of genetic tools is an informative approach for understanding how historical processes and factors impact the distribution of mangrove species. We investigated the phylogeographic patterns of two Avicennia species, A. germinans and A. schaueriana, from the Western Hemisphere using nuclear and chloroplast DNA markers. Our results indicate that, although Avicennia bicolor, A. germinans and A. schaueriana are independent lineages, hybridization between A. schaueriana and A. germinans is a relevant evolutionary process. Our findings also reinforce the role of long-distance dispersal in widespread mangrove species such as A. germinans, for which we observed signs of transatlantic dispersal, a process that has, most likely, contributed to the breadth of the distribution of A. germinans. However, along the southern coast of South America, A. schaueriana is the only representative of the genus. The distribution patterns of A. germinans and A. schaueriana are explained by their different responses to past climate changes and by the unequal historical effectiveness of relative gene flow by propagules and pollen. We observed that A. bicolor, A. germinans and A. schaueriana are three evolutionary lineages that present historical and ongoing hybridization on the American continent. We also inferred a new evidence of transatlantic dispersal for A. germinans, which may have contributed to its widespread distribution. Despite the generally wider distribution of A
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Vegetation in Bangalore's Slums: Composition, Species Distribution, Density, Diversity, and History
Gopal, Divya; Nagendra, Harini; Manthey, Michael
2015-06-01
There is widespread acknowledgement of the need for biodiversity and greening to be part of urban sustainability efforts. Yet we know little about greenery in the context of urban poverty, particularly in slums, which constitute a significant challenge for inclusive development in many rapidly growing cities. We assessed the composition, density, diversity, and species distribution of vegetation in 44 slums of Bangalore, India, comparing these to published studies on vegetation diversity in other land-use categories. Most trees were native to the region, as compared to other land-use categories such as parks and streets which are dominated by introduced species. Of the most frequently encountered tree species, Moringa oleifera and Cocos nucifera are important for food, while Ficus religiosa plays a critical cultural and religious role. Tree density and diversity were much lower in slums compared to richer residential neighborhoods. There are also differences in species preferences, with most plant (herb, shrub and vines) species in slums having economic, food, medicinal, or cultural use, while the species planted in richer residential areas are largely ornamental. Historic development has had an impact on species distribution, with older slums having larger sized tree species, while recent slums were dominated by smaller sized tree species with greater economic and food use. Extensive focus on planting trees and plant species with utility value is required in these congested neighborhoods, to provide livelihood support.
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Directory of Open Access Journals (Sweden)
Tai-Chung Wu
2011-11-01
Full Text Available Marsilea, an amphibian fern genus (containing ca. 80 species characterized by their unusual leaves and reproductive structures, is distributed over the five continents. To investigate the adaptation traits of three Marsilea species (M. crenata, M. quadrifolia, and M. schelpiana, distributed in different geographic regions, to terrestrial conditions, we compared morphological features, optical properties and photosynthetic performance of leaflets of the three species grown in terrestrial environment. The results showed that leaflets of the three species had significant differences in some of the ecophysiogical traits. Among the three species, M. quadrifolia (distributed in temperate region where receiving low precipitation had the highest trichome density on its leaflet surface and the highest water use efficiency, M. schelpiana (mainly in southern Africa where accepting high level of solar irradiance had the tallest petiole and the highest leaf dissection index, total stomatal pore area index, PSII electron transport rate and photosaturated photosynthetic rate, M. crenata (mainly in southeastern Asia region where receiving high precipitation and with high humidity had the lowest leaf dissection index and water use efficiency. Accordingly, leaf characteristics of the three Marsilea species reflect the climate pattern of their habitats. The results also suggest that water availability and light intensity are two of the important factors contributing to the geographic distribution of the three species.
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Habitat Modeling of Alien Plant Species at Varying Levels of Occupancy
Directory of Open Access Journals (Sweden)
Jennifer A. Brown
2012-09-01
Full Text Available Distribution models of invasive plants are very useful tools for conservation management. There are challenges in modeling expanding populations, especially in a dynamic environment, and when data are limited. In this paper, predictive habitat models were assessed for three invasive plant species, at differing levels of occurrence, using two different habitat modeling techniques: logistic regression and maximum entropy. The influence of disturbance, spatial and temporal heterogeneity, and other landscape characteristics is assessed by creating regional level models based on occurrence records from the USDA Forest Service’s Forest Inventory and Analysis database. Logistic regression and maximum entropy models were assessed independently. Ensemble models were developed to combine the predictions of the two analysis approaches to obtain a more robust prediction estimate. All species had strong models with Area Under the receiver operator Curve (AUC of >0.75. The species with the highest occurrence, Ligustrum spp., had the greatest agreement between the models (93%. Lolium arundinaceum had the most disagreement between models at 33% and the lowest AUC values. Overall, the strength of integrative modeling in assessing and understanding habitat modeling was demonstrated.
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Nazeri, Mona; Jusoff, Kamaruzaman; Madani, Nima; Mahmud, Ahmad Rodzi; Bahman, Abdul Rani; Kumar, Lalit
2012-01-01
One of the available tools for mapping the geographical distribution and potential suitable habitats is species distribution models. These techniques are very helpful for finding poorly known distributions of species in poorly sampled areas, such as the tropics. Maximum Entropy (MaxEnt) is a recently developed modeling method that can be successfully calibrated using a relatively small number of records. In this research, the MaxEnt model was applied to describe the distribution and identify the key factors shaping the potential distribution of the vulnerable Malayan Sun Bear (Helarctos malayanus) in one of the main remaining habitats in Peninsular Malaysia. MaxEnt results showed that even though Malaysian sun bear habitat is tied with tropical evergreen forests, it lives in a marginal threshold of bio-climatic variables. On the other hand, current protected area networks within Peninsular Malaysia do not cover most of the sun bears potential suitable habitats. Assuming that the predicted suitability map covers sun bears actual distribution, future climate change, forest degradation and illegal hunting could potentially severely affect the sun bear's population.
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Directory of Open Access Journals (Sweden)
Mona Nazeri
Full Text Available One of the available tools for mapping the geographical distribution and potential suitable habitats is species distribution models. These techniques are very helpful for finding poorly known distributions of species in poorly sampled areas, such as the tropics. Maximum Entropy (MaxEnt is a recently developed modeling method that can be successfully calibrated using a relatively small number of records. In this research, the MaxEnt model was applied to describe the distribution and identify the key factors shaping the potential distribution of the vulnerable Malayan Sun Bear (Helarctos malayanus in one of the main remaining habitats in Peninsular Malaysia. MaxEnt results showed that even though Malaysian sun bear habitat is tied with tropical evergreen forests, it lives in a marginal threshold of bio-climatic variables. On the other hand, current protected area networks within Peninsular Malaysia do not cover most of the sun bears potential suitable habitats. Assuming that the predicted suitability map covers sun bears actual distribution, future climate change, forest degradation and illegal hunting could potentially severely affect the sun bear's population.
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Wealth distribution of simple exchange models coupled with extremal dynamics
Bagatella-Flores, N.; Rodríguez-Achach, M.; Coronel-Brizio, H. F.; Hernández-Montoya, A. R.
2015-01-01
Punctuated Equilibrium (PE) states that after long periods of evolutionary quiescence, species evolution can take place in short time intervals, where sudden differentiation makes new species emerge and some species extinct. In this paper, we introduce and study the effect of punctuated equilibrium on two different asset exchange models: the yard sale model (YS, winner gets a random fraction of a poorer player's wealth) and the theft and fraud model (TF, winner gets a random fraction of the loser's wealth). The resulting wealth distribution is characterized using the Gini index. In order to do this, we consider PE as a perturbation with probability ρ of being applied. We compare the resulting values of the Gini index at different increasing values of ρ in both models. We found that in the case of the TF model, the Gini index reduces as the perturbation ρ increases, not showing dependence with the agents number. While for YS we observe a phase transition which happens around ρc = 0.79. For perturbations ρ <ρc the Gini index reaches the value of one as time increases (an extreme wealth condensation state), whereas for perturbations greater than or equal to ρc the Gini index becomes different to one, avoiding the system reaches this extreme state. We show that both simple exchange models coupled with PE dynamics give more realistic results. In particular for YS, we observe a power low decay of wealth distribution.
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Monahan, William B; Pereira, Ricardo J; Wake, David B
2012-03-12
In the mid 20th century, Ernst Mayr and Theodosius Dobzhansky championed the significance of circular overlaps or ring species as the perfect demonstration of speciation, yet in the over 50 years since, only a handful of such taxa are known. We developed a topographic model to evaluate whether the geographic barriers that favor processes leading to ring species are common or rare, and to predict where other candidate ring barriers might be found. Of the 952,147 geographic barriers identified on the planet, only about 1% are topographically similar to barriers associated with known ring taxa, with most of the likely candidates occurring in under-studied parts of the world (for example, marine environments, tropical latitudes). Predicted barriers separate into two distinct categories: (i) single cohesive barriers (barriers - formed by groups of barriers (each 184,000 to 1.7 million km2) in close geographic proximity (totaling 1.9 to 2.3 million km2) - associated with taxa that differentiate at larger spatial scales (birds: Phylloscopus trochiloides and Larus (sp. argentatus and fuscus)). When evaluated globally, we find a large number of cohesive barriers that are topographically similar to those associated with known ring taxa. Yet, compared to cohesive barriers, an order of magnitude fewer composite barriers are similar to those that favor ring divergence in species with higher dispersal. While these findings confirm that the topographic conditions that favor evolutionary processes leading to ring speciation are, in fact, rare, they also suggest that many understudied natural systems could provide valuable demonstrations of continuous divergence towards the formation of new species. Distinct advantages of the model are that it (i) requires no a priori information on the relative importance of features that define barriers, (ii) can be replicated using any kind of continuously distributed environmental variable, and (iii) generates spatially explicit hypotheses of
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Vertical distribution and migration of euphausiid species in the Red Sea
Wiebe, Peter H.
2016-06-01
We addressed how the extreme environmental conditions of the Red Sea impact or alter patterns of vertical distribution and vertical migration of five euphausiid species that are known from other oceans. Euphausia diomedeae was abundant and performed diel vertical migration (DVM) from >200 m in daytime to <100 m at night, similar to its pattern in other ocean regions. Euphausia sibogae and Euphausia sanzoi also showed consistent patterns of DVM across their ranges in the Red Sea and elsewhere. Two species, Stylocheiron affine and Stylocheiron abbreviatum, did not exhibit DVM. DNA barcode sequences for mitochondrial cytochrome oxidase I (COI) were used to confirm species identifications for four species (no previous barcode data exist for E. sanzoi). COI sequence differences averaged 2.8% (SD 3.1%) within species and 16.6% (SD 0.7%) between species, similar to previous studies of euphausiids. Red Sea specimens of S. affine matched morphological descriptions of a western equatorial form and differed 14% from Atlantic and Pacific specimens, suggesting possible cryptic species-level variation within this taxon. Widely distributed species of zooplankton may exhibit broad tolerance ranges for key environmental variables, and have considerable potential to adapt to variable and changing conditions across their geographic range.
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Directory of Open Access Journals (Sweden)
Dexiecuo Ai
Full Text Available The correspondence between species distribution and the environment depends on species' ability to track favorable environmental conditions (via dispersal and to maintain competitive hierarchy against the constant influx of migrants (mass effect and demographic stochasticity (ecological drift. Here we report a simulation study of the influence of landscape structure on species distribution. We consider lottery competition for space in a spatially heterogeneous environment, where the landscape is represented as a network of localities connected by dispersal. We quantified the contribution of neutrality and species sorting to their spatial distribution. We found that neutrality increases and the strength of species-sorting decreases with the centrality of a community in the landscape when the average dispersal among communities is low, whereas the opposite was found at elevated dispersal. We also found that the strength of species-sorting increases with environmental heterogeneity. Our results illustrate that spatial structure of the environment and of dispersal must be taken into account for understanding species distribution. We stress the importance of spatial geographic structure on the relative importance of niche vs. neutral processes in controlling community dynamics.
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de Mendoza, Guillermo; Ventura, Marc; Catalan, Jordi
2015-07-01
Aiming to elucidate whether large-scale dispersal factors or environmental species sorting prevail in determining patterns of Trichoptera species composition in mountain lakes, we analyzed the distribution and assembly of the most common Trichoptera (Plectrocnemia laetabilis, Polycentropus flavomaculatus, Drusus rectus, Annitella pyrenaea, and Mystacides azurea) in the mountain lakes of the Pyrenees (Spain, France, Andorra) based on a survey of 82 lakes covering the geographical and environmental extremes of the lake district. Spatial autocorrelation in species composition was determined using Moran's eigenvector maps (MEM). Redundancy analysis (RDA) was applied to explore the influence of MEM variables and in-lake, and catchment environmental variables on Trichoptera assemblages. Variance partitioning analysis (partial RDA) revealed the fraction of species composition variation that could be attributed uniquely to either environmental variability or MEM variables. Finally, the distribution of individual species was analyzed in relation to specific environmental factors using binomial generalized linear models (GLM). Trichoptera assemblages showed spatial structure. However, the most relevant environmental variables in the RDA (i.e., temperature and woody vegetation in-lake catchments) were also related with spatial variables (i.e., altitude and longitude). Partial RDA revealed that the fraction of variation in species composition that was uniquely explained by environmental variability was larger than that uniquely explained by MEM variables. GLM results showed that the distribution of species with longitudinal bias is related to specific environmental factors with geographical trend. The environmental dependence found agrees with the particular traits of each species. We conclude that Trichoptera species distribution and composition in the lakes of the Pyrenees are governed predominantly by local environmental factors, rather than by dispersal constraints. For
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Decapod larvae distribution and species composition off the southern Portuguese coast
Pochelon, Patricia N.; Pires, Rita F. T.; Dubert, Jesús; Nolasco, Rita; Santos, A. Miguel P.; Queiroga, Henrique; dos Santos, Antonina
2017-12-01
For decapod crustaceans, the larval phase is the main responsible for dispersal, given the direct emission from adult habitats into the water column. Circulation patterns and behavioural mechanisms control the dispersal distance and connectivity between different areas. Information on larval distribution and abundance is required to predict the size and location of breeding populations, and correctly manage marine resources. Spatial distribution and abundance data of decapod larvae, and environmental parameters were assessed in winter surveys off the southern Portuguese coast. To better understand the oceanic structures driving larval distribution patterns, in situ physical parameters were measured and a hydrodynamical model used. Inter-annual, cross-shore and alongshore differences on decapod larvae distribution were found. Brachyuran crabs dominated the samples and similar taxa composition was observed in the most dynamic areas. Coastal taxa dominated the nearshore survey and were almost absent in the more offshore one, that registered much lower abundances. An upwelling front allowed a clear cross-shore species separation, also evident in the abundance values and number of taxa. Hydrodynamical conditions and adult habitats were the main factors explaining the observed patterns. Important missing information to understand the distribution patterns of decapod larval communities and the mechanisms behind them is given for the region.
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Diversity and Distribution of Freshwater Amphipod Species in Switzerland (Crustacea: Amphipoda)
Altermatt, Florian; Alther, Roman; Fišer, Cene; Jokela, Jukka; Konec, Marjeta; Küry, Daniel; Mächler, Elvira; Stucki, Pascal; Westram, Anja Marie
2014-01-01
Amphipods are key organisms in many freshwater systems and contribute substantially to the diversity and functioning of macroinvertebrate communities. Furthermore, they are commonly used as bioindicators and for ecotoxicological tests. For many areas, however, diversity and distribution of amphipods is inadequately known, which limits their use in ecological and ecotoxicological studies and handicaps conservation initiatives. We studied the diversity and distribution of amphipods in Switzerland (Central Europe), covering four major drainage basins, an altitudinal gradient of>2,500 m, and various habitats (rivers, streams, lakes and groundwater). We provide the first provisional checklist and detailed information on the distribution and diversity of all amphipod species from Switzerland. In total, we found 29 amphipod species. This includes 16 native and 13 non-native species, one of the latter (Orchestia cavimana) reported here for the first time for Switzerland. The diversity is compared to neighboring countries. We specifically discuss species of the genus Niphargus, which are often receiving less attention. We also found evidence of an even higher level of hidden diversity, and the potential occurrence of further cryptic species. This diversity reflects the biogeographic past of Switzerland, and suggests that amphipods are ideally suited to address questions on endemism and adaptive radiations, post-glaciation re-colonization and invasion dynamics as well as biodiversity-ecosystem functioning relationships in aquatic systems. PMID:25354099
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Wei, Xiaojing; Savage, Jessica A; Riggs, Charlotte E; Cavender-Bares, Jeannine
2017-05-01
Environmental filtering is an important community assembly process influencing species distributions. Contrasting species abundance patterns along environmental gradients are commonly used to provide evidence for environmental filtering. However, the same abundance patterns may result from alternative or concurrent assembly processes. Experimental tests are an important means to decipher whether species fitness varies with environment, in the absence of dispersal constraints and biotic interactions, and to draw conclusions about the importance of environmental filtering in community assembly. We performed an experimental test of environmental filtering in 14 closely related willow and poplar species (family Salicaceae) by transplanting cuttings of each species into 40 common gardens established along a natural hydrologic gradient in the field, where competition was minimized and herbivory was controlled. We analyzed species fitness responses to the hydrologic environment based on cumulative growth and survival over two years using aster fitness models. We also examined variation in nine drought and flooding tolerance traits expected to contribute to performance based on a priori understanding of plant function in relation to water availability and stress. We found substantial evidence that environmental filtering along the hydrologic gradient played a critical role in determining species distributions. Fitness variation of each species in the field experiment was used to model their water table depth optima. These optima predicted 68% of the variation in species realized hydrologic niches based on peak abundance in naturally assembled communities in the surrounding region. Multiple traits associated with water transport efficiency and water stress tolerance were correlated with species hydrologic niches, but they did not necessarily covary with each other. As a consequence, species occupying similar hydrologic niches had different combinations of trait values
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Directory of Open Access Journals (Sweden)
Ovidiu COPOȚ
2017-12-01
Full Text Available Ganoderma lucidum is one of the most valued mushrooms in the World, because of its medicinal properties. In the context of North-Eastern Region’s development, any forest product could have a valuable contribution. Therefore, it is important to understand the mushroom’s ecology and generate a map of its optimal distribution. For this, we used one of the most performant species distribution models available – Maxent, field occurrences and climatic-topographic-biotic variables. After multi-collinearity testing and step-wise Maxent modelling, we came to an end with a 0.8 final model based on two predictors. Thus, in the region, the optimal habitat distribution is found in oak, beech, riparian or mixed forests bellow approximately 800 m altitude. The species can be found in almost all forests across lowland, colline and submontane regions according to tree host presence. The approach could be promising for other fungal species for the sustainable development of the region.
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Chadin, Ivan; Dalke, Igor; Zakhozhiy, Ilya; Malyshev, Ruslan; Madi, Elena; Olga Kuzivanova; Kirillov, Dmitrii; Elsakov, Vladimir
2017-01-01
Occurrences of the invasive plant species Heracleum sosnowskyi Manden. in the Komi Republic (northeastern part of European Russia) were recorded and published in the Global Biodiversity Information Facility (GBIF http://www.gbif.org) using the RIVR information system (http://ib.komisc.ru/add/rivr/en). RIVR stands for "Rasprostranenie Invasionnyh Vidov Rastenij" [Occurrence of Invasion Plant Species]. This citizen science project aims at collecting occurrence data about invasive plant species with the help of citizen scientists. Information can be added by any user after a simple registration (concept) process. However, the data published in GBIF are provided only by professional scientists. The total study area is approximately 19,000 km 2 . The GBIF resource contains 10894 Heracleum sosnowskyi occurrence points, each with their geographical coordinates and photographs of the plants in the locus of growth. The preliminary results of species distribution modelling on the territory of European North-East Russia presented.
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Ensemble forecasting of species distributions.
Araújo, Miguel B; New, Mark
2007-01-01
Concern over implications of climate change for biodiversity has led to the use of bioclimatic models to forecast the range shifts of species under future climate-change scenarios. Recent studies have demonstrated that projections by alternative models can be so variable as to compromise their usefulness for guiding policy decisions. Here, we advocate the use of multiple models within an ensemble forecasting framework and describe alternative approaches to the analysis of bioclimatic ensembles, including bounding box, consensus and probabilistic techniques. We argue that, although improved accuracy can be delivered through the traditional tasks of trying to build better models with improved data, more robust forecasts can also be achieved if ensemble forecasts are produced and analysed appropriately.
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Sterck, F.J.; Markesteijn, L.; Toledo, M.; Schieving, F.; Poorter, L.
2014-01-01
Niche differentiation is a major hypothesized determinant of species distributions, but its practical importance is heavily debated and its underlying mechanisms are poorly understood. Trait-based approaches have been used to infer niche differentiation and predict species distributions. For
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K-distribution models for gas mixtures in hypersonic nonequilibrium flows
Bansal, Ankit
Calculation of nonequilibrium radiation field in plasmas around a spacecraft entering into an atmosphere at hypersonic velocities is a very complicated and computationally expensive task. The objective of this Dissertation is to collect state-of-the art spectroscopic data for the evaluation of spectral absorption and emission coefficients of atomic and molecular gases, develop efficient and accurate spectral models and databases, and study the effect of radiation on wall heat loads and flowfield around the spacecraft. The most accurate simulation of radiative transport in the shock layer requires calculating the gas properties at a large number of wavelengths and solving the Radiative Transfer Equation (RTE) in a line-by-line (LBL) fashion, which is prohibitively expensive for coupled simulations. A number of k-distribution based spectral models are developed for atomic lines, continuum and molecular bands that allow efficient evaluation of radiative properties and heat loads in hypersonic shock layer plasma. Molecular radiation poses very different challenges than atomic radiation. A molecular spectrum is governed by simultaneous electronic, vibrational and rotational transitions, making the spectrum very strongly dependent on wavelength. In contrast to an atomic spectrum, where line wings play a major role in heat transfer, most of the heat transfer in molecular spectra occurs near line centers. As the first step, k-distribution models are developed separately for atomic and molecular species, taking advantage of the fact that in the Earth's atmosphere the radiative field is dominated by atomic species (N and O) and in Titan's and Mars' atmospheres molecular bands of CN and CO are dominant. There are a number of practical applications where both atomic and molecular species are present, for example, the vacuum-ultra-violet spectrum during Earth's reentry conditions is marked by emission from atomic bound-bound lines and continuum and simultaneous absorption by
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Tang, Cindy Q.; Dong, Yi-Fei; Herrando-Moraira, Sonia; Matsui, Tetsuya; Ohashi, Haruka; He, Long-Yuan; Nakao, Katsuhiro; Tanaka, Nobuyuki; Tomita, Mizuki; Li, Xiao-Shuang; Yan, Hai-Zhong; Peng, Ming-Chun; Hu, Jun; Yang, Ruo-Han; Li, Wang-Jun; Yan, Kai; Hou, Xiuli; Zhang, Zhi-Ying; López-Pujol, Jordi
2017-01-01
This study, using species distribution modeling (involving a new approach that allows for uncertainty), predicts the distribution of climatically suitable areas prevailing during the mid-Holocene, the Last Glacial Maximum (LGM), and at present, and estimates the potential formation of new habitats in 2070 of the endangered and rare Tertiary relict tree Davidia involucrata Baill. The results regarding the mid-Holocene and the LGM demonstrate that south-central and southwestern China have been long-term stable refugia, and that the current distribution is limited to the prehistoric refugia. Given future distribution under six possible climate scenarios, only some parts of the current range of D. involucrata in the mid-high mountains of south-central and southwestern China would be maintained, while some shift west into higher mountains would occur. Our results show that the predicted suitable area offering high probability (0.5‒1) accounts for an average of only 29.2% among the models predicted for the future (2070), making D. involucrata highly vulnerable. We assess and propose priority protected areas in light of climate change. The information provided will also be relevant in planning conservation of other paleoendemic species having ecological traits and distribution ranges comparable to those of D. involucrata. PMID:28272437
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A solvable two-species catalysis-driven aggregation model
Ke Jian Hong
2003-01-01
We study the kinetics of a two-species catalysis-driven aggregation system, in which an irreversible aggregation between any two clusters of one species occurs only with the catalytic action of another species. By means of a generalized mean-field rate equation, we obtain the asymptotic solutions of the cluster mass distributions in a simple process with a constant rate kernel. For the case without any consumption of the catalyst, the cluster mass distribution of either species always approaches a conventional scaling law. However, the evolution behaviour of the system in the case with catalyst consumption is complicated and depends crucially on the relative data of the initial concentrations of the two species.
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Taucare-Ríos, Andrés; Bizama, Gustavo; Bustamante, Ramiro O
2016-12-01
The brown widow spider, Latrodectus geometricus C. L. Koch, 1841, is a large spider of the family Theridiidae that belongs to a genus of medical interest owing to its potent neurotoxic venom, which causes severe pain in humans. In America, this alien spider has been found in virtually all countries in the region, mainly associated with human dwellings, but also in agricultural sectors. However, the invasive process and potential distribution of this invasive species across the American continent are completely unknown. In this context, using a combination of both global and regional niche models, it is possible to hypothesize the invasive phase of the species as well as the geographic space where these different phases occur. By comparing the global and regional niches of L. geometricus, we examined its invasive process and potential distribution across the American continent. This work is an innovative approach to understanding the invasion of the brown widow spider in this area and the ecological processes that underlie this invasion. In this context, the global and regional niche comparison constitutes an appropriate tool to account for the complexities of the invasive process, generating different hypotheses amenable to being tested in future studies. © The Authors 2016. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
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Directory of Open Access Journals (Sweden)
Regina Gabriela Medina
2016-11-01
Full Text Available Subtropical dry forests are among the most vulnerable biomes to land transformation at a global scale. Among them, the Dry Chaco suffers an accelerated change due to agriculture expansion and intensification. The Dry Chaco ecoregion is characterized by high levels of endemisms and species diversity, which are the result of a variety of climates and reliefs, allowing a wide variety of environments. The amphibian group exhibits a high richness in the Dry Chaco, which has been barely studied in relation to land cover changes. We used ecological niche models (ENMs to assess the potential geographic distribution of 10 Leptodactylus species (Anura, Leptodactylidae, which are mainly distributed within the Dry Chaco. We characterized these distributions environmentally, analyzed their overlap with land cover classes, and assessed their diversity of ecoregions. Also, we evaluated how these species potential distribution is affected by the transformation of land, and quantified the proportional area of the potential distribution in protected areas. We found that temperature seasonality is the main constraint to the occurrence of the species studied, whose main habitats are savannas, grasslands and croplands. The main threats to these species are the effects of climate change over spatial patterns of seasonality, which could affect their breeding and reproduction mode; the loss of their natural habitat; the exposure to contaminants used by intensive agriculture and their underrepresentation in protected areas.
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Mid-winter European dabbling duck distributions are not linked to species body mass
DEFF Research Database (Denmark)
Dalby, Lars; Delany, Simon; Fox, Anthony David
are likely to play a major role in determining the wintering distribution of short- to medium-distance migratory bird species and its inter-annual variability. As avian thermoregulatory costs scale allometrically with body size, we predicted that the mean mid-winter temperature experienced by six species...... of dabbling ducks wintering in Western Europe would be negatively correlated with body mass. We found no evidence for such a relationship in a large-scale analysis testing for a link between temperature and dabbling duck distributions, suggesting that other factors such as those related to feeding ecology......In order to understand the current changes and to predict future changes in wintering dabbling duck (Anas sp.) distributions in response to climate change, it is important to understand how species distribute themselves on a continental scale in response to temperature. Thermoregulatory costs...
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Directory of Open Access Journals (Sweden)
Ulrik B. Pedersen
2014-05-01
Full Text Available The environment, the on-going global climate change and the ecology of animal species determine the localisation of habitats and the geographical distribution of the various species in nature. The aim of this study was to explore the effects of such changes on snail species not only of interest to naturalists but also of importance to human and animal health. The spatial distribution of freshwater snail intermediate hosts involved in the transmission of schistosomiasis, fascioliasis and paramphistomiasis (i.e. Bulinus globosus, Biomphalaria pfeifferi and Lymnaea natalensis were modelled by the use of a maximum entropy algorithm (Maxent. Two snail observation datasets from Zimbabwe, from 1988 and 2012, were com- pared in terms of geospatial distribution and potential distributional change over this 24-year period investigated. Climate data, from the two years were identified and used in a species distribution modelling framework to produce maps of pre- dicted suitable snail habitats. Having both climate- and snail observation data spaced 24 years in time represent a unique opportunity to evaluate biological response of snails to changes in climate variables. The study shows that snail habitat suit- ability is highly variable in Zimbabwe with foci mainly in the central Highveld but also in areas to the South and West. It is further demonstrated that the spatial distribution of suitable habitats changes with variation in the climatic conditions, and that this parallels that of the predicted climate change.
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Modeling nonbreeding distributions of shorebirds and waterfowl in response to climate change
Reese, Gordon; Skagen, Susan K.
2017-01-01
To identify areas on the landscape that may contribute to a robust network of conservation areas, we modeled the probabilities of occurrence of several en route migratory shorebirds and wintering waterfowl in the southern Great Plains of North America, including responses to changing climate. We predominantly used data from the eBird citizen-science project to model probabilities of occurrence relative to land-use patterns, spatial distribution of wetlands, and climate. We projected models to potential future climate conditions using five representative general circulation models of the Coupled Model Intercomparison Project 5 (CMIP5). We used Random Forests to model probabilities of occurrence and compared the time periods 1981–2010 (hindcast) and 2041–2070 (forecast) in “model space.” Projected changes in shorebird probabilities of occurrence varied with species-specific general distribution pattern, migration distance, and spatial extent. Species using the western and northern portion of the study area exhibited the greatest likelihoods of decline, whereas species with more easterly occurrences, mostly long-distance migrants, had the greatest projected increases in probability of occurrence. At an ecoregional extent, differences in probabilities of shorebird occurrence ranged from −0.015 to 0.045 when averaged across climate models, with the largest increases occurring early in migration. Spatial shifts are predicted for several shorebird species. Probabilities of occurrence of wintering Mallards and Northern Pintail are predicted to increase by 0.046 and 0.061, respectively, with northward shifts projected for both species. When incorporated into partner land management decision tools, results at ecoregional extents can be used to identify wetland complexes with the greatest potential to support birds in the nonbreeding season under a wide range of future climate scenarios.
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Espinoza, Mario; Cappo, Mike; Heupel, Michelle R; Tobin, Andrew J; Simpfendorfer, Colin A
2014-01-01
Quantifying shark distribution patterns and species-specific habitat associations in response to geographic and environmental drivers is critical to assessing risk of exposure to fishing, habitat degradation, and the effects of climate change. The present study examined shark distribution patterns, species-habitat associations, and marine reserve use with baited remote underwater video stations (BRUVS) along the entire Great Barrier Reef Marine Park (GBRMP) over a ten year period. Overall, 21 species of sharks from five families and two orders were recorded. Grey reef Carcharhinus amblyrhynchos, silvertip C. albimarginatus, tiger Galeocerdo cuvier, and sliteye Loxodon macrorhinus sharks were the most abundant species (>64% of shark abundances). Multivariate regression trees showed that hard coral cover produced the primary split separating shark assemblages. Four indicator species had consistently higher abundances and contributed to explaining most of the differences in shark assemblages: C. amblyrhynchos, C. albimarginatus, G. cuvier, and whitetip reef Triaenodon obesus sharks. Relative distance along the GBRMP had the greatest influence on shark occurrence and species richness, which increased at both ends of the sampling range (southern and northern sites) relative to intermediate latitudes. Hard coral cover and distance across the shelf were also important predictors of shark distribution. The relative abundance of sharks was significantly higher in non-fished sites, highlighting the conservation value and benefits of the GBRMP zoning. However, our results also showed that hard coral cover had a large effect on the abundance of reef-associated shark species, indicating that coral reef health may be important for the success of marine protected areas. Therefore, understanding shark distribution patterns, species-habitat associations, and the drivers responsible for those patterns is essential for developing sound management and conservation approaches.
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Model of charge-state distributions for electron cyclotron resonance ion source plasmas
Directory of Open Access Journals (Sweden)
D. H. Edgell
1999-12-01
Full Text Available A computer model for the ion charge-state distribution (CSD in an electron cyclotron resonance ion source (ECRIS plasma is presented that incorporates non-Maxwellian distribution functions, multiple atomic species, and ion confinement due to the ambipolar potential well that arises from confinement of the electron cyclotron resonance (ECR heated electrons. Atomic processes incorporated into the model include multiple ionization and multiple charge exchange with rate coefficients calculated for non-Maxwellian electron distributions. The electron distribution function is calculated using a Fokker-Planck code with an ECR heating term. This eliminates the electron temperature as an arbitrary user input. The model produces results that are a good match to CSD data from the ANL-ECRII ECRIS. Extending the model to 1D axial will also allow the model to determine the plasma and electrostatic potential profiles, further eliminating arbitrary user input to the model.
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Attenuation of species abundance distributions by sampling
Shimadzu, Hideyasu; Darnell, Ross
2015-01-01
Quantifying biodiversity aspects such as species presence/ absence, richness and abundance is an important challenge to answer scientific and resource management questions. In practice, biodiversity can only be assessed from biological material taken by surveys, a difficult task given limited time and resources. A type of random sampling, or often called sub-sampling, is a commonly used technique to reduce the amount of time and effort for investigating large quantities of biological samples. However, it is not immediately clear how (sub-)sampling affects the estimate of biodiversity aspects from a quantitative perspective. This paper specifies the effect of (sub-)sampling as attenuation of the species abundance distribution (SAD), and articulates how the sampling bias is induced to the SAD by random sampling. The framework presented also reveals some confusion in previous theoretical studies. PMID:26064626
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The influence of electrohydrodynamic flow on the distribution of chemical species in positive corona
Pontiga, Francisco; Yanallah, Khelifa; Bouazza, R.; Chen, Junhong
2015-09-01
A numerical simulation of positive corona discharge in air, including the effect of electrohydrodynamic (EHD) motion of the gas, has been carried out. Air flow is assumed to be confined between two parallel plates, and corona discharge is produced around a thin wire, midway between the plates. Therefore, fluid dynamics equations, including electrical forces, have been solved together with the continuity equation of each neutral species. The plasma chemical model included 24 chemical reactions and ten neutral species, in addition to electrons and positive ions. The results of the simulation have shown that the influence of EHD flow on the spatial distributions of the species is quite different depending on the species. Hence, reactive species like atomic oxygen and atomic nitrogen are confined to the vicinity of the wire, and they are weakly affected by the EHD gas motion. In contrast, nitrogen oxides and ozone are efficiently dragged outside the active region of the corona discharge by the EHD flow. This work was supported by the Spanish Government Agency ``Ministerio de Ciencia e Innovación'' under Contract No. FIS2011-25161.
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Directory of Open Access Journals (Sweden)
Mmoto L. Masubelele
2009-09-01
Full Text Available Protected areas globally are threatened by the potential negative impacts that invasive alien plants pose, and Camdeboo National Park (CNP, South Africa, is no exception. Alien plants have been recorded in the CNP since 1981, before it was proclaimed a national park by South African National Parks in 2005. This is the first publication of a list of alien plants in and around the CNP. Distribution maps of some of the first recorded alien plant species are also presented and discussed. To date, 39 species of alien plants have been recorded, of which 13 are invasive and one is a transformer weed. The majority of alien plant species in the park are herbaceous (39% and succulent (24% species. The most widespread alien plant species in the CNP are Atriplex inflata (= A. lindleyi subsp. inflata, Salsola tragus (= S. australis and cacti species, especially Opuntia ficus-indica. Eradication and control measures that have been used for specific problematic alien plant species are described. Conservation implications: This article represents the first step in managing invasive alien plants and includes the collation of a species list and basic information on their distribution in and around the protected area. This is important for enabling effective monitoring of both new introductions and the distribution of species already present. We present the first species list and distribution information for Camdeboo National Park.
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The use of logistic regression in modelling the distributions of bird ...
African Journals Online (AJOL)
The method of logistic regression was used to model the observed geographical distribution patterns of bird species in Swaziland in relation to a set of environmental variables. Reporting rates derived from bird atlas data are used as an index of population densities. This is justified in part by the success of the modelling ...
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Solution of the spatial neutral model yields new bounds on the Amazonian species richness
Shem-Tov, Yahav; Danino, Matan; Shnerb, Nadav M.
2017-02-01
Neutral models, in which individual agents with equal fitness undergo a birth-death-mutation process, are very popular in population genetics and community ecology. Usually these models are applied to populations and communities with spatial structure, but the analytic results presented so far are limited to well-mixed or mainland-island scenarios. Here we combine analytic results and numerics to obtain an approximate solution for the species abundance distribution and the species richness for the neutral model on continuous landscape. We show how the regional diversity increases when the recruitment length decreases and the spatial segregation of species grows. Our results are supported by extensive numerical simulations and allow one to probe the numerically inaccessible regime of large-scale systems with extremely small mutation/speciation rates. Model predictions are compared with the findings of recent large-scale surveys of tropical trees across the Amazon basin, yielding new bounds for the species richness (between 13100 and 15000) and the number of singleton species (between 455 and 690).
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An analysis of plant species distributions on the floodplain of the ...
African Journals Online (AJOL)
Furthermore, several ruderal species were restricted to elevated sites in close proximity to the channel, occurring on recently formed point bars which are the product of fluvial processes. Disturbance in the form of sediment deposition on point bars is thus an important determinant of species distribution on floodplains of the ...
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Directory of Open Access Journals (Sweden)
Monahan William B
2012-03-01
Full Text Available Abstract Background In the mid 20th century, Ernst Mayr and Theodosius Dobzhansky championed the significance of circular overlaps or ring species as the perfect demonstration of speciation, yet in the over 50 years since, only a handful of such taxa are known. We developed a topographic model to evaluate whether the geographic barriers that favor processes leading to ring species are common or rare, and to predict where other candidate ring barriers might be found. Results Of the 952,147 geographic barriers identified on the planet, only about 1% are topographically similar to barriers associated with known ring taxa, with most of the likely candidates occurring in under-studied parts of the world (for example, marine environments, tropical latitudes. Predicted barriers separate into two distinct categories: (i single cohesive barriers (2, associated with taxa that differentiate at smaller spatial scales (salamander: Ensatina eschscholtzii; tree: Acacia karroo; and (ii composite barriers - formed by groups of barriers (each 184,000 to 1.7 million km2 in close geographic proximity (totaling 1.9 to 2.3 million km2 - associated with taxa that differentiate at larger spatial scales (birds: Phylloscopus trochiloides and Larus (sp. argentatus and fuscus. When evaluated globally, we find a large number of cohesive barriers that are topographically similar to those associated with known ring taxa. Yet, compared to cohesive barriers, an order of magnitude fewer composite barriers are similar to those that favor ring divergence in species with higher dispersal. Conclusions While these findings confirm that the topographic conditions that favor evolutionary processes leading to ring speciation are, in fact, rare, they also suggest that many understudied natural systems could provide valuable demonstrations of continuous divergence towards the formation of new species. Distinct advantages of the model are that it (i requires no a priori information on the
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Species composition and geographical distribution of Saharan scorpion fauna, Morocco
Directory of Open Access Journals (Sweden)
Oulaid Touloun
2016-11-01
Full Text Available Objective: To describe the species composition of scorpions and to study its geographical distribution in Laayoune-Sakia El Hamra and Dakhla-Oued Ed Dahab regions in July 2014. Methods: To locate scorpions, the ground was examined through searching the places under the stones, rocks and in burrows. The nocturnal missions were also conducted using portable ultraviolet lamps. The scorpions were subsequently identified in the laboratory. Results: The results of the investigations in these regions showed the presence of five scorpion species, two of which Androctonus gonneti and Buthus bonito were endemic in Morocco. Conclusions: This work is allowed to complete the inventory of the studied scorpion fauna and provides some considerations on the distribution patterns in the study area.
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DEFF Research Database (Denmark)
Svenning, J.-C.; Harlev, D.; Sørensen, M.M.
2009-01-01
The northern Andes harbour a flora that is as species-rich or even richer than the 18-times larger lowland Amazon basin. Gaining an understanding of how the high species richness of the Andean region is generated and maintained is therefore of particular interest. Environmental sorting due......). Mantel tests and indicator species analysis showed that both topography and spatial location imposed strong controls on palm species distributions at the study site. Our results suggest that species distributions in the studied montane forest landscape were partly determined by the species' habitat...... distributions at the study site. Other factors must also be involved, notably wind-exposure and hydrology, as discussed for lowland palm communities. Our results show that to understand plant community assembly in the tropical montane forests of the Andes it is too simple to focus just on environmental sorting...
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Species distributions, quantum theory, and the enhancement of biodiversity measures
DEFF Research Database (Denmark)
Real, Raimundo; Barbosa, A. Márcia; Bull, Joseph William
2017-01-01
Species distributions are typically represented by records of their observed occurrence at a given spatial and temporal scale. Such records are inevitably incomplete and contingent on the spatial–temporal circumstances under which the observations were made. Moreover, organisms may respond...... biodiversity”. We show how conceptualizing species’ distributions in this way could help overcome important weaknesses in current biodiversity metrics, both in theory and by using a worked case study of mammal distributions in Spain over the last decade. We propose that considerable theoretical advances could...
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Directory of Open Access Journals (Sweden)
Victor H. Gonzalez
2017-04-01
Full Text Available In the summer of 2010, two male specimens of the neotropical orchid bee genus Eufriesea Cockerell were collected in the Guadalupe Mountains of western Texas and southeastern New Mexico, USA. We tentatively identified them as E. coerulescens (Lepeletier de Saint Fargeau because of the uncertainty surrounding the limits of this taxon and hypothesized that they were members of a persistent bee population, rather than long-distance transient vagrants. The goals of this paper are to clarify the identity of these specimens, assess the species limits of E. coerulescens, and to evaluate suitability of habitats in the USA for this adventive species. Herein, we revise the species in the coerulescens group using morphological features of both sexes and confirm that the specimens of Eufriesea from the USA are E. coerulescens. We recognize the following six species in the coerulescens group: E. coerulescens, E. micheneri Ayala & Engel, E. simillima (Moure & Michener, which is reinstated from synonym with E. coerulescens, and three new species from Mexico (E. barthelli Gonzalez & Griswold, sp. n., E. engeli Gonzalez & Griswold, sp. n., and E. oliveri Gonzalez & Griswold, sp. n.. To facilitate the identification of these taxa, we present a fully illustrated account of the species, comparative diagnoses, descriptions, and an updated key to all Mexican species of Eufriesea. Our analyses using species distribution modelling show an absence of suitable habitat for E. coerulescens in western Texas and southeastern New Mexico, thus favoring the long-distance dispersal hypothesis. The analyses also suggest high suitability of habitats across the Caribbean and some areas in Florida, as well as in other regions in Mexico and Central America. We discuss the implications of these results and compare them with the predicted distribution available for the other two known adventive orchid bee species in the USA.
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Directory of Open Access Journals (Sweden)
Enrique García-Muñoz
2013-12-01
Full Text Available Distribution modelling usually makes inferences correlating species presence and environmental variables but does not take biotic relations into account. Alternative approaches based on a mechanistic understanding of biological processes are now being applied. Regarding lacertid lizards, physiological traits such as preferred body temperature (Tp are well known to correlate with several physiological optima. Much less is known about their water ecology although body temperature and evaporative water loss (Wl may trade-off. Two saxicolous lacertids, Algyroides marchi and Podarcis hispanica ss are sympatric in the Subbetic Mountains (SE Spain were they can be found in syntopy. Previous distribution modelling indicates the first species is associated with mountains, low temperatures; high precipitation and forest cover whereas the second one is more generalistic. Here, we perform two ecophysiological tests with both species: a Tp experiment in thermal gradient and a Wl experiment in sealed chambers. Although both species attained similar body temperatures, A. marchi lost more water and more uniformly in time than P. hispanica ss that displayed an apparent response to dehydration. These results suggest that water loss rather temperature is crucial to explain the distribution patterns of A. marchi in relation to P. hispanica ss, the former risking dehydration in dry areas no matter what temperature is. Ecophysiological traits represent a promising tool to build future mechanistic models for (lacertid lizards. Additionally, the implications for their biogeography and conservation are discussed.
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Palm, Juliane; Klaus, Julian; van Schaik, Loes; Zehe, Erwin; Schröder, Boris
2010-05-01
environmental predictors which explain the distribution and dynamics of different ecological earthworm types can help us to understand where or when these processes are relevant in the landscape. Therefore, we develop species distribution models which are a useful tool to predict spatiotemporal distributions of earthworm occurrence and abundance under changing environmental conditions. On field scale, geostatistical distribution maps have shown that the spatial distribution of earthworms depends on soil parameters such as food supply, soil moisture, bulk density but with different patterns for earthworm stages (adult, juvenile) and ecological types (anecic, endogeic, epigeic). On landscape scales, earthworm distribution seems to be strongly controlled by management/disturbance-related factors. Our study shows different modelling approaches for predicting distribution patterns of earthworms in the Weiherbach area, an agricultural site in Kraichtal (Baden-Württemberg, Germany). We carried out field studies on arable fields differing in soil management practices (conventional, conservational), soil properties (organic matter content, texture, soil moisture), and topography (slope, elevation) in order to identify predictors for earthworm occurrence, abundance and biomass. Our earthworm distribution models consider all ecological groups as well as different life stages, accounting for the fact that the activity of juveniles is sometimes different from those of adults. Within our BIOPORE-project it is our final goal to couple our distribution models with population dynamic models and a preferential flow model to an integrated ecohydrological model to analyse feedbacks between earthworm engineering and transport characteristics affecting the functioning of (agro-) ecosystems.
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Rajakaruna, Harshana; VandenByllaardt, Julie; Kydd, Jocelyn; Bailey, Sarah
2018-03-01
The International Maritime Organization (IMO) has set limits on allowable plankton concentrations in ballast water discharge to minimize aquatic invasions globally. Previous guidance on ballast water sampling and compliance decision thresholds was based on the assumption that probability distributions of plankton are Poisson when spatially homogenous, or negative binomial when heterogeneous. We propose a hierarchical probability model, which incorporates distributions at the level of particles (i.e., discrete individuals plus colonies per unit volume) and also within particles (i.e., individuals per particle) to estimate the average plankton concentration in ballast water. We examined the performance of the models using data for plankton in the size class ≥ 10 μm and test ballast water compliance using the above models.
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A spatial pattern analysis of the halophytic species distribution in an arid coastal environment.
Badreldin, Nasem; Uria-Diez, J; Mateu, J; Youssef, Ali; Stal, Cornelis; El-Bana, Magdy; Magdy, Ahmed; Goossens, Rudi
2015-05-01
Obtaining information about the spatial distribution of desert plants is considered as a serious challenge for ecologists and environmental modeling due to the required intensive field work and infrastructures in harsh and remote arid environments. A new method was applied for assessing the spatial distribution of the halophytic species (HS) in an arid coastal environment. This method was based on the object-based image analysis for a high-resolution Google Earth satellite image. The integration of the image processing techniques and field work provided accurate information about the spatial distribution of HS. The extracted objects were based on assumptions that explained the plant-pixel relationship. Three different types of digital image processing techniques were implemented and validated to obtain an accurate HS spatial distribution. A total of 2703 individuals of the HS community were found in the case study, and approximately 82% were located above an elevation of 2 m. The micro-topography exhibited a significant negative relationship with pH and EC (r = -0.79 and -0.81, respectively, p < 0.001). The spatial structure was modeled using stochastic point processes, in particular a hybrid family of Gibbs processes. A new model is proposed that uses a hard-core structure at very short distances, together with a cluster structure in short-to-medium distances and a Poisson structure for larger distances. This model was found to fit the data perfectly well.
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The roles of competition and habitat in the dynamics of populations and species distributions.
Yackulic, Charles B; Reid, Janice; Nichols, James D; Hines, James E; Davis, Raymond; Forsman, Eric
2014-02-01
The role of competition in structuring biotic communities at fine spatial scales is well known from detailed process-based studies. Our understanding of competition's importance at broader scales is less resolved and mainly based on static species distribution maps. Here, we bridge this gap by examining the joint occupancy dynamics of an invading species (Barred Owl, Strix varia) and a resident species (Northern Spotted Owl, Strix occidentalis caurina) in a 1000-km study area over a 22-year period. Past studies of these competitors have focused on the dynamics of one species at a time, hindering efforts to parse out the roles of habitat and competition and to forecast the future of the resident species. In addition, while these studies accounted for the imperfect detection of the focal species, no multi-season analysis of these species has accounted for the imperfect detection of the secondary species, potentially biasing inference. We analyzed survey data using models that combine the general multistate-multi-season occupancy modeling framework with autologistic modeling, allowing us to account for important aspects of our study system. We found that local extinction probability increases for each species when the other is present; however, the effect of the invader on the resident is greater. Although the species prefer different habitats, these habitats are highly correlated at the patch scale, and the impacts of invader on the resident are greatest in patches that would otherwise be optimal. As a consequence, competition leads to a weaker relationship between habitat and Northern Spotted Owl occupancy. Colonization and extinction rates of the invader are closely related to neighborhood occupancy, and over the first half of the study the availability of colonists limited the rate of population growth. Competition is likely to exclude the resident species, both through its immediate effects on local extinction and by indirectly lowering colonization rates as
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Arana, María V; Gonzalez-Polo, Marina; Martinez-Meier, Alejandro; Gallo, Leonardo A; Benech-Arnold, Roberto L; Sánchez, Rodolfo A; Batlla, Diego
2016-01-01
Seeds integrate environmental cues that modulate their dormancy and germination. Although many mechanisms have been identified in laboratory experiments, their contribution to germination dynamics in existing communities and their involvement in defining species habitats remain elusive. By coupling mathematical models with ecological data we investigated the contribution of seed temperature responses to the dynamics of germination of three Nothofagus species that are sharply distributed across different altitudes in the Patagonian Andes. Seed responsiveness to temperature of the three Nothofagus species was linked to the thermal characteristics of their preferred ecological niche. In their natural distribution range, there was overlap in the timing of germination of the species, which was restricted to mid-spring. By contrast, outside their species distribution range, germination was temporally uncoupled with altitude. This phenomenon was described mathematically by the interplay between interspecific differences in seed population thermal parameters and the range in soil thermic environments across different altitudes. The observed interspecific variations in seed responsiveness to temperature and its environmental regulation, constitute a major determinant of the dynamics of Nothofagus germination across elevations. This phenomenon likely contributes to the maintenance of patterns of species abundance across altitude by placing germinated seeds in a favorable environment for plant growth. © 2015 The Authors. New Phytologist © 2015 New Phytologist Trust.
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González, Camila; Paz, Andrea; Ferro, Cristina
2014-01-01
Visceral leishmaniasis (VL) is caused by the trypanosomatid parasite Leishmania infantum (=Leishmania chagasi), and is epidemiologically relevant due to its wide geographic distribution, the number of annual cases reported and the increase in its co-infection with HIV. Two vector species have been incriminated in the Americas: Lutzomyia longipalpis and Lutzomyia evansi. In Colombia, L. longipalpis is distributed along the Magdalena River Valley while L. evansi is only found in the northern part of the Country. Regarding the epidemiology of the disease, in Colombia the incidence of VL has decreased over the last few years without any intervention being implemented. Additionally, changes in transmission cycles have been reported with urban transmission occurring in the Caribbean Coast. In Europe and North America climate change seems to be driving a latitudinal shift of leishmaniasis transmission. Here, we explored the spatial distribution of the two known vector species of L. infantum in Colombia and projected its future distribution into climate change scenarios to establish the expansion potential of the disease. An updated database including L. longipalpis and L. evansi collection records from Colombia was compiled. Ecological niche models were performed for each species using the Maxent software and 13 Worldclim bioclimatic coverages. Projections were made for the pessimistic CSIRO A2 scenario, which predicts the higher increase in temperature due to non-emission reduction, and the optimistic Hadley B2 Scenario predicting the minimum increase in temperature. The database contained 23 records for L. evansi and 39 records for L. longipalpis, distributed along the Magdalena River Valley and the Caribbean Coast, where the potential distribution areas of both species were also predicted by Maxent. Climate change projections showed a general overall reduction in the spatial distribution of the two vector species, promoting a shift in altitudinal distribution for L
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Architecture and Distribution of Introns in Core Genes of Four Fusarium Species
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Mmatshepho M. Phasha
2017-11-01
Full Text Available Removal of introns from transcribed RNA represents a crucial step during the production of mRNA in eukaryotes. Available whole-genome sequences and expressed sequence tags (ESTs have increased our knowledge of this process and revealed various commonalities among eukaryotes. However, certain aspects of intron structure and diversity are taxon-specific, which can complicate the accuracy of in silico gene prediction methods. Using core genes, we evaluated the distribution and architecture of Fusarium circinatum spliceosomal introns, and linked these characteristics to the accuracy of the predicted gene models of the genome of this fungus. We also evaluated intron distribution and architecture in F. verticillioides, F. oxysporum, and F. graminearum, and made comparisons with F. circinatum. Results indicated that F. circinatum and the three other Fusarium species have canonical 5′ and 3′ splice sites, but with subtle differences that are apparently not shared with those of other fungal genera. The polypyrimidine tract of Fusarium introns was also found to be highly divergent among species and genes. Furthermore, the conserved adenosine nucleoside required during the first step of splicing is contained within unique branch site motifs in certain Fusarium introns. Data generated here show that introns of F. circinatum, as well as F. verticillioides, F. oxysporum, and F. graminearum, are characterized by a number of unique features such as the CTHAH and ACCAT motifs of the branch site. Incorporation of such information into genome annotation software will undoubtedly improve the accuracy of gene prediction methods used for Fusarium species and related fungi.
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Fourcade, Yoan; Engler, Jan O; Rödder, Dennis; Secondi, Jean
2014-01-01
MAXENT is now a common species distribution modeling (SDM) tool used by conservation practitioners for predicting the distribution of a species from a set of records and environmental predictors. However, datasets of species occurrence used to train the model are often biased in the geographical space because of unequal sampling effort across the study area. This bias may be a source of strong inaccuracy in the resulting model and could lead to incorrect predictions. Although a number of sampling bias correction methods have been proposed, there is no consensual guideline to account for it. We compared here the performance of five methods of bias correction on three datasets of species occurrence: one "virtual" derived from a land cover map, and two actual datasets for a turtle (Chrysemys picta) and a salamander (Plethodon cylindraceus). We subjected these datasets to four types of sampling biases corresponding to potential types of empirical biases. We applied five correction methods to the biased samples and compared the outputs of distribution models to unbiased datasets to assess the overall correction performance of each method. The results revealed that the ability of methods to correct the initial sampling bias varied greatly depending on bias type, bias intensity and species. However, the simple systematic sampling of records consistently ranked among the best performing across the range of conditions tested, whereas other methods performed more poorly in most cases. The strong effect of initial conditions on correction performance highlights the need for further research to develop a step-by-step guideline to account for sampling bias. However, this method seems to be the most efficient in correcting sampling bias and should be advised in most cases.
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Incorporating climate change and exotic species into forecasts of riparian forest distribution.
Directory of Open Access Journals (Sweden)
Dana H Ikeda
Full Text Available We examined the impact climate change (CC will have on the availability of climatically suitable habitat for three native and one exotic riparian species. Due to its increasing prevalence in arid regions throughout the western US, we predicted that an exotic species, Tamarix, would have the greatest increase in suitable habitat relative to native counterparts under CC. We used an ecological niche model to predict range shifts of Populus fremontii, Salix gooddingii, Salix exigua and Tamarix, from present day to 2080s, under five general circulation models and one climate change scenario (A1B. Four major findings emerged. 1 Contrary to our original hypothesis, P. fremontii is projected to have the greatest increase in suitable habitat under CC, followed closely by Tamarix. 2 Of the native species, S. gooddingii and S. exigua showed the greatest loss in predicted suitable habitat due to CC. 3 Nearly 80 percent of future P. fremontii and Salix habitat is predicted to be affected by either CC or Tamarix by the 2080s. 4 By the 2080s, 20 percent of S. gooddingii habitat is projected to be affected by both Tamarix and CC concurrently, followed by S. exigua (19 percent and P. fremontii (13 percent. In summary, while climate change alone will negatively impact both native willow species, Tamarix is likely to affect a larger portion of all three native species' distributions. We discuss these and other results in the context of prioritizing restoration and conservation efforts to optimize future productivity and biodiversity. As we are accounting for only direct effects of CC and Tamarix on native habitat, we present a possible hierarchy of effects- from the direct to the indirect- and discuss the potential for the indirect to outweigh the direct effects. Our results highlight the need to account for simultaneous challenges in the face of CC.
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Record, Sydne; Strecker, Angela; Tuanmu, Mao-Ning; Beaudrot, Lydia; Zarnetske, Phoebe; Belmaker, Jonathan; Gerstner, Beth
2018-01-01
There is ample evidence that biotic factors, such as biotic interactions and dispersal capacity, can affect species distributions and influence species' responses to climate change. However, little is known about how these factors affect predictions from species distribution models (SDMs) with respect to spatial grain and extent of the models. Understanding how spatial scale influences the effects of biological processes in SDMs is important because SDMs are one of the primary tools used by conservation biologists to assess biodiversity impacts of climate change. We systematically reviewed SDM studies published from 2003-2015 using ISI Web of Science searches to: (1) determine the current state and key knowledge gaps of SDMs that incorporate biotic interactions and dispersal; and (2) understand how choice of spatial scale may alter the influence of biological processes on SDM predictions. We used linear mixed effects models to examine how predictions from SDMs changed in response to the effects of spatial scale, dispersal, and biotic interactions. There were important biases in studies including an emphasis on terrestrial ecosystems in northern latitudes and little representation of aquatic ecosystems. Our results suggest that neither spatial extent nor grain influence projected climate-induced changes in species ranges when SDMs include dispersal or biotic interactions. We identified several knowledge gaps and suggest that SDM studies forecasting the effects of climate change should: 1) address broader ranges of taxa and locations; and 1) report the grain size, extent, and results with and without biological complexity. The spatial scale of analysis in SDMs did not affect estimates of projected range shifts with dispersal and biotic interactions. However, the lack of reporting on results with and without biological complexity precluded many studies from our analysis.
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The roles of competition and habitat in the dynamics of populations and species distributions
Yackulic, Charles Brandon; Reid, Janice; Nichols, James D.; Hines, James E.; Davis, Raymond; Forsman, Eric
2014-01-01
The role of competition in structuring biotic communities at fine spatial scales is well known from detailed process-based studies. Our understanding of competition's importance at broader scales is less resolved and mainly based on static species distribution maps. Here, we bridge this gap by examining the joint occupancy dynamics of an invading (barred owl: Strix varia) and a resident species (Northern spotted owl: Strix occidentalis caurina) in a 1000 km2 study area over a 22 - year period. Past studies of these competitors have focused on the dynamics of one species at a time, hindering efforts to parse out the roles of habitat and competition and to forecast the future of the resident species. In addition, while these studies accounted for the imperfect detection of the focal species, no multiseason analysis of these species has accounted for the imperfect detection of the secondary species, potentially biasing inference. We analyze survey data using models that combine the general multistate-multiseason occupancy modeling framework with autologistic modeling - allowing us to account for important aspects of our study system. We find that local extinction probability increases for each species when the other is present; however, the effect of the invader on the resident is greater. Although the species prefer different habitats, these habitats are highly correlated at the patch scale and the impacts of invader on the resident are greatest in patches that would otherwise be optimal. As a consequence, competition leads to a weaker relationship between habitat and Northern spotted owl occupancy. Colonization and extinction rates of the invader are closely related to neighborhood occupancy, and over the first half of the study the availability of colonists limited the rate of population growth. Competition is likely to exclude the resident species both through its immediate effects on local extinction, and by indirectly lowering colonization rates as Northern
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Smit, M.G.D.; Bechmann, R.K.; Hendriks, A.J.; Skadsheim, A.; Larsen, B.K.; Baussant, T.; Bamber, S.; Sannei, S.
2009-01-01
Biomarkers are widely used to measure environmental impacts on marine species. For many biomarkers, it is not clear how the signal levels relate to effects on the whole organism. This paper shows how species sensitivity distributions (SSDs) can be applied to evaluate multiple biomarker responses in
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Antwi, Raymond Agyepong; Owusu, Erasmus Henaku; Attuquayefio, Daniel Korley
2018-02-01
The well-being of a species fundamentally rests on understanding its biology, home range, and distribution. The highly seasonal distribution of kobs poses conservation and management difficulties, particularly because of the capricious nature of the ever-changing ecological and vegetation dynamics of the ecosystem. Assessing the distribution of kobs and their associated vegetation provides insight into the vulnerability and conservation status of the species. Species distribution and habitat suitability maps were developed and created respectively for the management of kobs in the Shai Hills Resource Reserve. Kob presence data collected was analyzed using the spatial analyst and Hawth's tool in the ArcGIS software where the gradients of kob distribution within the protected area landscape were plotted and mapped. Seven environmental variables including location, land cover/use, slope/elevation, nearness to dams and rivers, temperature, and rainfall were considered to have effect on kob distribution pattern and as such used in the development of species distribution and habitat suitability maps. The results indicated that kobs in the Shai Hills Resource Reserve (SHRR) assume a clumped or contagious distribution pattern where individual kobs are aggregated in patches. Rainfall, temperature, nearness to dams and rivers, slope/elevation, and land cover/use had influence in kob distribution. Of all the cataloged habitats, 86, 13, and 1% were moderately suitable, suitable, and unsuitable, respectively. Long-term survival of species depends on adequately large areas of suitable habitats and opportunities for home range activities between such areas. As such, it is recommended that suitable habitats for kobs be dedicated and designated as conservation areas, especially areas along the western boundary.
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Monitoring potential geographical distribution of four wild bird species in China
Dai, S.; Feng, D.; Xu, B.
2015-12-01
The outbreak of highly pathogenic avian influenza (HPAI) of the H5N1 subtype in wild birds and poultry have caught worldwide attention. To explore the association between wild bird migration and avian influenza virus transmission, we monitored potential geographical distribution of four wild bird species that might carry the avian influenza viruses in China. They are Bar-headed geese (Anser indicus), Ruddy Shelduck (Tadorna ferruginea), Whooper Swan (Cygnus cygnus) and Black-headed Gull (Larus ridibundus). They served as major reservoir of the avian influenza viruses. We used bird watching records with the precise latitude/longitude coordinates from January 2002 to August 2014, and environmental variables with a pixel resolution of 5 km × 5 km from 2002 to 2014. The study utilized maximum entropy (MaxEnt) model based on ecological niche model approaches, and got the following results: 1) MaxEnt model have good discriminatory ability with the area under the curve (AUC) of the receiver operating curve (ROC) of 0.86-0.97; 2) The four wild bird species were estimated to concentrate in the North China Plain, the middle and lower region of the Yangtze River, Qinghai Lake, Tianshan Mountain and Tarim Basin, part of Tibet Plateau, and Hengduan Mountains; 3) Radiation and the minimum temperature were found to provide the most significant information. Our findings will help to understand the spread of avian influenza viruses by wild bird migration in China, which benefits for effective monitoring strategies and prevention measures.
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Species Distribution Model for Management of an Invasive Vine in Forestlands of Eastern Texas
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Hsiao-Hsuan Wang
2015-11-01
Full Text Available Invasive plants decrease biodiversity, modify vegetation structure, and inhibit growth and reproduction of native species. Japanese honeysuckle (Lonicera japonica Thunb. is the most prevalent invasive vine in the forestlands of eastern Texas. Hence, we aimed to identify potential factors influencing the distribution of the species, quantify the relative importance of each factor, and test possible management strategies. We analyzed an extensive dataset collected as part of the Forest Inventory and Analysis Program of the United States Department of Agriculture (USDA Forest Service to quantify the range expansion of Japanese honeysuckle in the forestlands of eastern Texas from 2006 to 2011. We then identified potential factors influencing the likelihood of presence of Japanese honeysuckle using boosted regression trees. Our results indicated that the presence of Japanese honeysuckle on sampled plots almost doubled during this period (from 352 to 616 plots, spreading extensively, geographically. The probability of invasion was correlated with variables representing landscape conditions, climatic conditions, forest features, disturbance factors, and forest management activities. Habitats most at risk to invasion under current conditions occurred primarily in northeastern Texas, with a few invasion hotspots in the south. Estimated probabilities of invasion were reduced most by artificial site regeneration, with habitats most at risk again occurring primarily in northeastern Texas.
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Wagner, Tyler; Jefferson T. Deweber,; Jason Detar,; John A. Sweka,
2013-01-01
Predicting the distribution of native stream fishes is fundamental to the management and conservation of many species. Modeling species distributions often consists of quantifying relationships between species occurrence and abundance data at known locations with environmental data at those locations. However, it is well documented that native stream fish distributions can be altered as a result of asymmetric interactions between dominant exotic and subordinate native species. For example, the naturalized exotic Brown Trout Salmo trutta has been identified as a threat to native Brook Trout Salvelinus fontinalis in the eastern United States. To evaluate large-scale patterns of co-occurrence and to quantify the potential effects of Brown Trout presence on Brook Trout occupancy, we used data from 624 stream sites to fit two-species occupancy models. These models assumed that asymmetric interactions occurred between the two species. In addition, we examined natural and anthropogenic landscape characteristics we hypothesized would be important predictors of occurrence of both species. Estimated occupancy for Brook Trout, from a co-occurrence model with no landscape covariates, at sites with Brown Trout present was substantially lower than sites where Brown Trout were absent. We also observed opposing patterns for Brook and Brown Trout occurrence in relation to percentage forest, impervious surface, and agriculture within the network catchment. Our results are consistent with other studies and suggest that alterations to the landscape, and specifically the transition from a forested catchment to one that contains impervious surface or agriculture, reduces the occurrence probability of wild Brook Trout. Our results, however, also suggest that the presence of Brown Trout results in lower occurrence probability of Brook Trout over a range of anthropogenic landscape characteristics, compared with streams where Brown Trout were absent.
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Rodrigues, P M S; Silva, J O; Eisenlohr, P V; Schaefer, C E G R
2015-08-01
The aim of this study was to evaluate the ecological niche models (ENMs) for three specialist trees (Anadenanthera colubrina, Aspidosperma pyrifolium and Myracrodruon urundeuva) in seasonally dry tropical forests (SDTFs) in Brazil, considering present and future pessimist scenarios (2080) of climate change. These three species exhibit typical deciduousness and are widely distributed by SDTF in South America, being important in studies of the historical and evolutionary processes experienced by this ecosystem. The modeling of the potential geographic distribution of species was done by the method of maximum entropy (Maxent).We verified a general expansion of suitable areas for occurrence of the three species in future (c.a., 18%), although there was reduction of areas with high environmental suitability in Caatinga region. Precipitation of wettest quarter and temperature seasonality were the predictor variables that most contributed to our models. Climatic changes can provide more severe and longer dry season with increasing temperature and tree mortality in tropics. On this scenario, areas currently occupied by rainforest and savannas could become more suitable for occurrence of the SDTF specialist trees, whereas regions occupied by Caatinga could not support the future level of unsustainable (e.g., aridity). Long-term multidisciplinary studies are necessary to make reliable predictions of the plant's adaptation strategies and responses to climate changes in dry forest at community level. Based on the high deforestation rate, endemism and threat, public policies to minimize the effects of climate change on the biodiversity found within SDTFs must be undertaken rapidly.
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Zhang, Qian; Zhong, Jin-Xin
2013-05-01
Based on the related published papers, and by using Geographic Information System (ArcGIS 9.3), this paper analyzed the species composition and geographical distribution of threatened fishes in Yunnan Province of Southwest China. There were 83 threatened species living in the Province, belonging to 5 orders, 13 families, and 47 genera. Cypriniformes was absolutely dominant, with 64 species, followed by Siluriformes, with 16 species. Cyprinidae fishes had 51 species, accounting for 79.7% of Cypriniformes. The most species of Cyprinid fishes were of Barbinae (14 species), Cyprininae (10 species), and Cultrinae (10 species). The threatened fishes could be divided into two zoogeographical regions, i. e., Tibetan Plateau region and Oriental region, and their species composition and geographical distribution were resulted from the historical evolution adapted to the related environments. Whatever in rivers and in lakes, the Cyprinid fishes were both absolutely dominant, occupying 36.1% and 31.3% of the total, respectively. The Cyprinid fishes in rivers were mostly of endangered species, while those in lakes were mostly of vulnerable species. The factors affecting the threatened fishes in the Province were discussed from the two aspects of geodynamic evolution and present situation.
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Directory of Open Access Journals (Sweden)
Luis M. Carrascal
2016-07-01
Full Text Available Background. The availability of environmental energy, as measured by temperature, is expected to limit the abundance and distribution of endotherms wintering at temperate latitudes. A prediction of this hypothesis is that birds should attain their highest abundances in warmer areas. However, there may be a spatial mismatch between species preferred habitats and species preferred temperatures, so some species might end-up wintering in sub-optimal thermal environments. Methods. We model the influence of minimum winter temperature on the relative abundance of 106 terrestrial bird species wintering in peninsular Spain, at 10 ×10 km2 resolution, using 95%-quantile regressions. We analyze general trends across species on the shape of the response curves, the environmental preferred temperature (at which the species abundance is maximized, the mean temperature in the area of distribution and the thermal breadth (area under the abundance-temperature curve. Results. Temperature explains a low proportion of variation in abundance. The most significant effect is on limiting the maximum potential abundance of species. Considering this upper-limit response, there is a large interspecific variability on the thermal preferences and specialization of species. Overall, there is a preponderance of positive relationships between species abundance and temperature; on average, species attain their maximum abundances in areas 1.9 °C warmer than the average temperature available in peninsular Spain. The mean temperature in the area of distribution is lower than the thermal preferences of the species. Discussion. Many species prefer the warmest areas to overwinter, which suggests that temperature imposes important restrictions to birds wintering in the Iberian Peninsula. However, one third of species overwinter in locations colder than their thermal preferences, probably reflecting the interaction between habitat and thermal requirements. There is a high inter
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Golicher, J.D.; Cayuela, L.; Alkemade, J.R.M.; González-Espinosa, M.; Ramírez-Marcial, N.
2008-01-01
Aim Predictive species distribution modelling is a useful tool for extracting the maximum amount of information from biological collections and floristic inventories. However, in many tropical regions records are only available from a small number of sites. This can limit the application of
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Kafeshani, Farzaneh Alizadeh; Rajabpour, Ali; Aghajanzadeh, Sirous; Gholamian, Esmaeil; Farkhari, Mohammad
2018-04-02
Aphis spiraecola Patch, Aphis gossypii Glover, and Toxoptera aurantii Boyer de Fonscolombe are three important aphid pests of citrus orchards. In this study, spatial distributions of the aphids on two orange species, Satsuma mandarin and Thomson navel, were evaluated using Taylor's power law and Iwao's patchiness. In addition, a fixed-precision sequential sampling plant was developed for each species on the host plant by Green's model at precision levels of 0.25 and 0.1. The results revealed that spatial distribution parameters and therefore the sampling plan were significantly different according to aphid and host plant species. Taylor's power law provides a better fit for the data than Iwao's patchiness regression. Except T. aurantii on Thomson navel orange, spatial distribution patterns of the aphids were aggregative on both citrus. T. aurantii had regular dispersion pattern on Thomson navel orange. Optimum sample size of the aphids varied from 30-2061 and 1-1622 shoots on Satsuma mandarin and Thomson navel orange based on aphid species and desired precision level. Calculated stop lines of the aphid species on Satsuma mandarin and Thomson navel orange ranged from 0.48 to 19 and 0.19 to 80.4 aphids per 24 shoots according to aphid species and desired precision level. The performance of the sampling plan was validated by resampling analysis using resampling for validation of sampling plans (RVSP) software. This sampling program is useful for IPM program of the aphids in citrus orchards.
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Wu, Jianguo
2016-01-01
It is unclear whether the distributions of snakes have changed in association with climate change over the past years. We detected the distribution changes of snakes over the past 50 years and determined whether the changes could be attributed to recent climate change in China. Long-term records of the distribution of nine snake species in China, grey relationship analysis, fuzzy sets classification techniques, the consistency index, and attributed methods were used. Over the past 50 years, the distributions of snake species have changed in multiple directions, primarily shifting northwards, and most of the changes were related to the thermal index. Driven by climatic factors over the past 50 years, the distribution boundary and distribution centers of some species changed with the fluctuations. The observed and predicted changes in distribution were highly consistent for some snake species. The changes in the northern limits of distributions of nearly half of the species, as well as the southern and eastern limits, and the distribution centers of some snake species can be attributed to climate change.
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Pearce, J; Ferrier, S; Scotts, D
2001-06-01
To use models of species distributions effectively in conservation planning, it is important to determine the predictive accuracy of such models. Extensive modelling of the distribution of vascular plant and vertebrate fauna species within north-east New South Wales has been undertaken by linking field survey data to environmental and geographical predictors using logistic regression. These models have been used in the development of a comprehensive and adequate reserve system within the region. We evaluate the predictive accuracy of models for 153 small reptile, arboreal marsupial, diurnal bird and vascular plant species for which independent evaluation data were available. The predictive performance of each model was evaluated using the relative operating characteristic curve to measure discrimination capacity. Good discrimination ability implies that a model's predictions provide an acceptable index of species occurrence. The discrimination capacity of 89% of the models was significantly better than random, with 70% of the models providing high levels of discrimination. Predictions generated by this type of modelling therefore provide a reasonably sound basis for regional conservation planning. The discrimination ability of models was highest for the less mobile biological groups, particularly the vascular plants and small reptiles. In the case of diurnal birds, poor performing models tended to be for species which occur mainly within specific habitats not well sampled by either the model development or evaluation data, highly mobile species, species that are locally nomadic or those that display very broad habitat requirements. Particular care needs to be exercised when employing models for these types of species in conservation planning.
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Gottschalk, Fadri; Nowack, Bernd
2013-01-01
This article presents a method of probabilistically computing species sensitivity distributions (SSD) that is well-suited to cope with distinct data scarcity and variability. First, a probability distribution that reflects the uncertainty and variability of sensitivity is modeled for each species considered. These single species sensitivity distributions are then combined to create an SSD for a particular ecosystem. A probabilistic estimation of the risk is carried out by combining the probability of critical environmental concentrations with the probability of organisms being impacted negatively by these concentrations. To evaluate the performance of the method, we developed SSD and risk calculations for the aquatic environment exposed to triclosan. The case studies showed that the probabilistic results reflect the empirical information well, and the method provides a valuable alternative or supplement to more traditional methods for calculating SSDs based on averaging raw data and/or on using theoretical distributional forms. A comparison and evaluation with single SSD values (5th-percentile [HC5]) revealed the robustness of the proposed method. Copyright © 2012 SETAC.
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Mu, Yunsong; Wu, Fengchang; Chen, Cheng; Liu, Yuedan; Zhao, Xiaoli; Haiqing Liao; Giesy, John P
2014-05-01
Criteria continuous concentrations (CCCs) are useful for describing chronic exposure to pollutants and setting water quality standards to protect aquatic life. However, because of financial, practical, or ethical restrictions on toxicity testing, few data are available to derive CCCs. In this study, CCCs for 34 metals or metalloids were derived using quantitative ion character-activity relationships-species sensitivity distributions (QICAR-SSD) and the final acute-chronic ratio (FACR) method. The results showed that chronic toxic potencies were correlated with several physico-chemical properties among eight species chosen, where the softness index was the most predictive characteristic. Predicted CCCs for most of the metals, except for Lead and Iron, were within a range of 10-fold of values recommended by the U.S. EPA. The QICAR-SSD model was superior to the FACR method for prediction of data-poor metals. This would have significance for predicting toxic potencies and criteria thresholds of more metals or metalloids. Copyright © 2014 Elsevier Ltd. All rights reserved.
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A Robust Approach to Risk Assessment Based on Species Sensitivity Distributions.
Monti, Gianna S; Filzmoser, Peter; Deutsch, Roland C
2018-05-03
The guidelines for setting environmental quality standards are increasingly based on probabilistic risk assessment due to a growing general awareness of the need for probabilistic procedures. One of the commonly used tools in probabilistic risk assessment is the species sensitivity distribution (SSD), which represents the proportion of species affected belonging to a biological assemblage as a function of exposure to a specific toxicant. Our focus is on the inverse use of the SSD curve with the aim of estimating the concentration, HCp, of a toxic compound that is hazardous to p% of the biological community under study. Toward this end, we propose the use of robust statistical methods in order to take into account the presence of outliers or apparent skew in the data, which may occur without any ecological basis. A robust approach exploits the full neighborhood of a parametric model, enabling the analyst to account for the typical real-world deviations from ideal models. We examine two classic HCp estimation approaches and consider robust versions of these estimators. In addition, we also use data transformations in conjunction with robust estimation methods in case of heteroscedasticity. Different scenarios using real data sets as well as simulated data are presented in order to illustrate and compare the proposed approaches. These scenarios illustrate that the use of robust estimation methods enhances HCp estimation. © 2018 Society for Risk Analysis.
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Marini, C; Fossa, F; Paoli, C; Bellingeri, M; Gnone, G; Vassallo, P
2015-03-01
Habitat modeling is an important tool to investigate the quality of the habitat for a species within a certain area, to predict species distribution and to understand the ecological processes behind it. Many species have been investigated by means of habitat modeling techniques mainly to address effective management and protection policies and cetaceans play an important role in this context. The bottlenose dolphin (Tursiops truncatus) has been investigated with habitat modeling techniques since 1997. The objectives of this work were to predict the distribution of bottlenose dolphin in a coastal area through the use of static morphological features and to compare the prediction performances of three different modeling techniques: Generalized Linear Model (GLM), Generalized Additive Model (GAM) and Random Forest (RF). Four static variables were tested: depth, bottom slope, distance from 100 m bathymetric contour and distance from coast. RF revealed itself both the most accurate and the most precise modeling technique with very high distribution probabilities predicted in presence cells (90.4% of mean predicted probabilities) and with 66.7% of presence cells with a predicted probability comprised between 90% and 100%. The bottlenose distribution obtained with RF allowed the identification of specific areas with particularly high presence probability along the coastal zone; the recognition of these core areas may be the starting point to develop effective management practices to improve T. truncatus protection. Copyright © 2014 Elsevier Ltd. All rights reserved.
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Distribution of Plasmids in Distinct Leptospira Pathogenic Species.
Wang, Yanzhuo; Zhuang, Xuran; Zhong, Yi; Zhang, Cuicai; Zhang, Yan; Zeng, Lingbing; Zhu, Yongzhang; He, Ping; Dong, Ke; Pal, Utpal; Guo, Xiaokui; Qin, Jinhong
2015-11-01
Leptospirosis, caused by pathogenic Leptospira, is a worldwide zoonotic infection. The genus Leptospira includes at least 21 species clustered into three groups--pathogens, non-pathogens, and intermediates--based on 16S rRNA phylogeny. Research on Leptospira is difficult due to slow growth and poor transformability of the pathogens. Recent identification of extrachromosomal elements besides the two chromosomes in L. interrogans has provided new insight into genome complexity of the genus Leptospira. The large size, low copy number, and high similarity of the sequence of these extrachromosomal elements with the chromosomes present challenges in isolating and detecting them without careful genome assembly. In this study, two extrachromosomal elements were identified in L. borgpetersenii serovar Ballum strain 56604 through whole genome assembly combined with S1 nuclease digestion following pulsed-field gel electrophoresis (S1-PFGE) analysis. Further, extrachromosomal elements in additional 15 Chinese epidemic strains of Leptospira, comprising L. borgpetersenii, L. weilii, and L. interrogans, were successfully separated and identified, independent of genome sequence data. Southern blot hybridization with extrachromosomal element-specific probes, designated as lcp1, lcp2 and lcp3-rep, further confirmed their occurrences as extrachromosomal elements. In total, 24 plasmids were detected in 13 out of 15 tested strains, among which 11 can hybridize with the lcp1-rep probe and 11 with the lcp2-rep probe, whereas two can hybridize with the lcp3-rep probe. None of them are likely to be species-specific. Blastp search of the lcp1, lcp2, and lcp3-rep genes with a nonredundant protein database of Leptospira species genomes showed that their homologous sequences are widely distributed among clades of pathogens but not non-pathogens or intermediates. These results suggest that the plasmids are widely distributed in Leptospira species, and further elucidation of their biological
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Energy Technology Data Exchange (ETDEWEB)
Kefford, Ben J., E-mail: ben.kefford@uts.edu.a [School of Applied Sciences, RMIT University, Victoria (Australia); Centre for Environmental Sustainability, Department of Environmental Science, University of Technology Sydney, New South Wales (Australia); Marchant, Richard [Department of Entomology, Museum of Victoria, Victoria (Australia); Schaefer, Ralf B. [School of Applied Sciences, RMIT University, Victoria (Australia); Metzeling, Leon [EPA Victoria, Macleod, Victoria (Australia); Dunlop, Jason E. [Department of Environment and Resource Management, Indooroopilly, Queensland (Australia); National Research Centre for Environmental Toxicology, University of Queensland, Coopers Plains, Queensland (Australia); Choy, Satish C. [Department of Environment and Resource Management, Indooroopilly, Queensland (Australia); Goonan, Peter [South Australia Environment Protection Authority, Adelaide, South Australia (Australia)
2011-01-15
The risk of chemicals for ecological communities is often forecast with species sensitivity distributions (SSDs) which are used to predict the concentration which will protect p% of species (PC{sub p} value). However, at the PC{sub p} value, species richness in nature would not necessary be p% less than at uncontaminated sites. The definition of species richness inherent to SSDs (contaminant category richness) contrasts with species richness typically measured in most field studies (point richness). We determine, for salinity in eastern Australia, whether these definitions of stream macroinvertebrate species richness are commensurable. There were strong relationships (r{sup 2} {>=} 0.87) between mean point species, family and Ephemeroptera, Trichoptera and Plecoptera species richness and their respective contamination category richness. Despite differences in the definition of richness used by SSDs and field biomonitoring, their results in terms of relative species loss from salinity in south-east Australia are similar. We conclude that in our system both definitions are commensurable. - Definitions of species richness inherit in SSDs and biomonitoring are for salinity in south-east Australia commensurable.
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International Nuclear Information System (INIS)
Kefford, Ben J.; Marchant, Richard; Schaefer, Ralf B.; Metzeling, Leon; Dunlop, Jason E.; Choy, Satish C.; Goonan, Peter
2011-01-01
The risk of chemicals for ecological communities is often forecast with species sensitivity distributions (SSDs) which are used to predict the concentration which will protect p% of species (PC p value). However, at the PC p value, species richness in nature would not necessary be p% less than at uncontaminated sites. The definition of species richness inherent to SSDs (contaminant category richness) contrasts with species richness typically measured in most field studies (point richness). We determine, for salinity in eastern Australia, whether these definitions of stream macroinvertebrate species richness are commensurable. There were strong relationships (r 2 ≥ 0.87) between mean point species, family and Ephemeroptera, Trichoptera and Plecoptera species richness and their respective contamination category richness. Despite differences in the definition of richness used by SSDs and field biomonitoring, their results in terms of relative species loss from salinity in south-east Australia are similar. We conclude that in our system both definitions are commensurable. - Definitions of species richness inherit in SSDs and biomonitoring are for salinity in south-east Australia commensurable.
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A species sensitivity distribution (SSD) is a probability model of the variation of species sensitivities to a stressor, in particular chemical exposure. The SSD approach has been used as a decision support tool in environmental protection and management since the 1980s, and the ...
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Patino, Luz H; Mendez, Claudia; Rodriguez, Omaira; Romero, Yanira; Velandia, Daniel; Alvarado, Maria; Pérez, Julie; Duque, Maria Clara; Ramírez, Juan David
2017-08-01
In Colombia, the cutaneous leishmaniasis (CL) is the most common manifestation across the army personnel. Hence, it is mandatory to determine the species associated with the disease as well as the association with the clinical traits. A total of 273 samples of male patients with CL were included in the study and clinical data of the patients was studied. PCR and sequencing analyses (Cytb and HSP70 genes) were performed to identify the species and the intra-specific genetic variability. A georeferenced database was constructed to identify the spatial distribution of Leishmania species isolated. The identification of five species of Leishmania that circulate in the areas where army personnel are deployed is described. Predominant infecting Leishmania species corresponds to L. braziliensis (61.1%), followed by Leishmania panamensis (33.5%), with a high distribution of both species at geographical and municipal level. The species L. guyanensis, L. mexicana and L. lainsoni were also detected at lower frequency. We also showed the identification of different genotypes within L. braziliensis and L. panamensis. In conclusion, we identified the Leishmania species circulating in the areas where Colombian army personnel are deployed, as well as the high intra-specific genetic variability of L. braziliensis and L. panamensis and how these genotypes are distributed at the geographic level.
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McGill, Brian J.; Etienne, Rampal S.; Gray, John S.; Alonso, David; Anderson, Marti J.; Benecha, Habtamu Kassa; Dornelas, Maria; Enquist, Brian J.; Green, Jessica L.; He, Fangliang; Hurlbert, Allen H.; Magurran, Anne E.; Marquet, Pablo A.; Maurer, Brian A.; Ostling, Annette; Soykan, Candan U.; Ugland, Karl I.; White, Ethan P.
2007-01-01
Species abundance distributions (SADs) follow one of ecology's oldest and most universal laws - every community shows a hollow curve or hyperbolic shape on a histogram with many rare species and just a few common species. Here, we review theoretical, empirical and statistical developments in the
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Persiani, Anna Maria; Maggi, Oriana
2013-01-01
Experimental fires, of both low and high intensity, were lit during summer 2000 and the following 2 y in the Castel Volturno Nature Reserve, southern Italy. Soil samples were collected Jul 2000-Jul 2002 to analyze the soil fungal community dynamics. Species abundance distribution patterns (geometric, logarithmic, log normal, broken-stick) were compared. We plotted datasets with information both on species richness and abundance for total, xerotolerant and heat-stimulated soil microfungi. The xerotolerant fungi conformed to a broken-stick model for both the low- and high intensity fires at 7 and 84 d after the fire; their distribution subsequently followed logarithmic models in the 2 y following the fire. The distribution of the heat-stimulated fungi changed from broken-stick to logarithmic models and eventually to a log-normal model during the post-fire recovery. Xerotolerant and, to a far greater extent, heat-stimulated soil fungi acquire an important functional role following soil water stress and/or fire disturbance; these disturbances let them occupy unsaturated habitats and become increasingly abundant over time.
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Jarnevich, Catherine S.; Young, Nicholas E.; Talbert, Marian; Talbert, Colin
2018-01-01
Understanding invasive species distributions and potential invasions often requires broad‐scale information on the environmental tolerances of the species. Further, resource managers are often faced with knowing these broad‐scale relationships as well as nuanced environmental factors related to their landscape that influence where an invasive species occurs and potentially could occur. Using invasive buffelgrass (Cenchrus ciliaris), we developed global models and local models for Saguaro National Park, Arizona, USA, based on location records and literature on physiological tolerances to environmental factors to investigate whether environmental relationships of a species at a global scale are also important at local scales. In addition to correlative models with five commonly used algorithms, we also developed a model using a priori user‐defined relationships between occurrence and environmental characteristics based on a literature review. All correlative models at both scales performed well based on statistical evaluations. The user‐defined curves closely matched those produced by the correlative models, indicating that the correlative models may be capturing mechanisms driving the distribution of buffelgrass. Given climate projections for the region, both global and local models indicate that conditions at Saguaro National Park may become more suitable for buffelgrass. Combining global and local data with correlative models and physiological information provided a holistic approach to forecasting invasive species distributions.
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Directory of Open Access Journals (Sweden)
Yi Zeng
2017-08-01
Full Text Available The forest ecosystem is the largest land vegetation type, which plays the role of unreplacement with its unique value. And in the landscape scale, the research on forest landscape pattern has become the current hot spot, wherein the study of forest canopy structure is very important. They determines the process and the strength of forests energy flow, which influences the adjustments of ecosystem for climate and species diversity to some extent. The extraction of influencing factors of canopy structure and the analysis of the vegetation distribution pattern are especially important. To solve the problems, remote sensing technology, which is superior to other technical means because of its fine timeliness and large-scale monitoring, is applied to the study. Taking Lingkong Mountain as the study area, the paper uses the remote sensing image to analyze the forest distribution pattern and obtains the spatial characteristics of canopy structure distribution, and DEM data are as the basic data to extract the influencing factors of canopy structure. In this paper, pattern of trees distribution is further analyzed by using terrain parameters, spatial analysis tools and surface processes quantitative simulation. The Hydrological Analysis tool is used to build distributed hydrological model, and corresponding algorithm is applied to determine surface water flow path, rivers network and basin boundary. Results show that forest vegetation distribution of dominant tree species present plaque on the landscape scale and their distribution have spatial heterogeneity which is related to terrain factors closely. After the overlay analysis of aspect, slope and forest distribution pattern respectively, the most suitable area for stand growth and the better living condition are obtained.
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International Nuclear Information System (INIS)
Padilla Gil, Dora Nancy
2014-01-01
The work was carried in the marine agricola farm of the Municipality Tumaco, with the objective of studying the distribution of the species of the genus Buenoa in homogeneous environmental conditions regarding temperature, humidity, altitude and aquatic habitats of the freshwater and the others with different grade of conductivity and dedicated to the marine shrimp farming Litopenaeus vannamei (Boone, 1931). The studied lakes were four of freshwater and four with different conductivity, in the months of June to November 2010. The results showed heterogeneous distribution of the species of the genus Buenoa with major diversity in freshwater (5 species) and lower abundance; while in saltwater had lower diversity (4 species) and major abundance. Only Buenoa dactylis Padilla-Gil 2010 was found in both aquatic environments. It is discussed possible ecological implications than can influence this distribution pattern are discussed.
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Moctezuma, Victor; Sánchez-Huerta, José Luis; Halffter, Gonzalo
2018-01-01
Two new species of the genus Ateuchus Weber are described from the region of Los Chimalapas, Oaxaca, Mexico: A. benitojuarezi sp. n. and A. colossus sp. n. A diagnosis for distinguishing these new species from the other species of this genus in North America is included. This paper is illustrated with pictures of the dorsal habitus and the male genitalia of the new species. The evolutionary relationships of the species are discussed, as well as their distribution and ecology. It is considered that the species of the genus Ateuchus present in North and Central America correspond to the Typical Neotropical and Mountain Mesoamerican distribution patterns.
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Distribution and diversity of Arctic-Alpine species in the Balkans
DEFF Research Database (Denmark)
Stevanovic, Vladimir; Vukojicic, Snezana; Sinzar-Sekulic, Jasmina
2009-01-01
The distributions of 77 Arctic-Alpine species in the Balkans are mapped and the centers of their richness and diversity presented. Within the Dinaric Alps these are Mts Vranica, Durmitor, and Prokletije; in the Scardo-Pindhic mountains, Šarplanina-Rudoka-Korab form a continuous chain...
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McGill, B.J.; Etienne, R.S.; Gray, J.S.; Alonso, D.; Anderson, M.J.; Benecha, H.K.
2007-01-01
Species abundance distributions (SADs) follow one of ecology's oldest and most universal laws ¿ every community shows a hollow curve or hyperbolic shape on a histogram with many rare species and just a few common species. Here, we review theoretical, empirical and statistical developments in the
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Ecological relationships of meso-scale distribution in 25 neotropical vertebrate species.
Michalski, Lincoln José; Norris, Darren; de Oliveira, Tadeu Gomes; Michalski, Fernanda
2015-01-01
Vertebrates are a vital ecological component of Amazon forest biodiversity. Although vertebrates are a functionally important part of various ecosystem services they continue to be threatened by anthropogenic impacts throughout the Amazon. Here we use a standardized, regularly spaced arrangement of camera traps within 25km2 to provide a baseline assessment of vertebrate species diversity in a sustainable use protected area in the eastern Brazilian Amazon. We examined seasonal differences in the per species encounter rates (number of photos per camera trap and number of cameras with photos). Generalized linear models (GLMs) were then used to examine the influence of five variables (altitude, canopy cover, basal area, distance to nearest river and distance to nearest large river) on the number of photos per species and on functional groups. GLMs were also used to examine the relationships between large predators [Jaguar (Panthera onca) and Puma (Puma concolor)] and their prey. A total of 649 independent photos of 25 species were obtained from 1,800 camera trap days (900 each during wet and dry seasons). Only ungulates and rodents showed significant seasonal differences in the number of photos per camera. The number of photos differed between seasons for only three species (Mazama americana, Dasyprocta leporina and Myoprocta acouchy) all of which were photographed more (3 to 10 fold increase) during the wet season. Mazama americana was the only species where a significant difference was found in occupancy, with more photos in more cameras during the wet season. For most groups and species variation in the number of photos per camera was only explained weakly by the GLMs (deviance explained ranging from 10.3 to 54.4%). Terrestrial birds (Crax alector, Psophia crepitans and Tinamus major) and rodents (Cuniculus paca, Dasyprocta leporina and M. acouchy) were the notable exceptions, with our GLMs significantly explaining variation in the distribution of all species
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Ecological relationships of meso-scale distribution in 25 neotropical vertebrate species.
Directory of Open Access Journals (Sweden)
Lincoln José Michalski
Full Text Available Vertebrates are a vital ecological component of Amazon forest biodiversity. Although vertebrates are a functionally important part of various ecosystem services they continue to be threatened by anthropogenic impacts throughout the Amazon. Here we use a standardized, regularly spaced arrangement of camera traps within 25km2 to provide a baseline assessment of vertebrate species diversity in a sustainable use protected area in the eastern Brazilian Amazon. We examined seasonal differences in the per species encounter rates (number of photos per camera trap and number of cameras with photos. Generalized linear models (GLMs were then used to examine the influence of five variables (altitude, canopy cover, basal area, distance to nearest river and distance to nearest large river on the number of photos per species and on functional groups. GLMs were also used to examine the relationships between large predators [Jaguar (Panthera onca and Puma (Puma concolor] and their prey. A total of 649 independent photos of 25 species were obtained from 1,800 camera trap days (900 each during wet and dry seasons. Only ungulates and rodents showed significant seasonal differences in the number of photos per camera. The number of photos differed between seasons for only three species (Mazama americana, Dasyprocta leporina and Myoprocta acouchy all of which were photographed more (3 to 10 fold increase during the wet season. Mazama americana was the only species where a significant difference was found in occupancy, with more photos in more cameras during the wet season. For most groups and species variation in the number of photos per camera was only explained weakly by the GLMs (deviance explained ranging from 10.3 to 54.4%. Terrestrial birds (Crax alector, Psophia crepitans and Tinamus major and rodents (Cuniculus paca, Dasyprocta leporina and M. acouchy were the notable exceptions, with our GLMs significantly explaining variation in the distribution of all
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Theoretical size distribution of fossil taxa: analysis of a null model
Directory of Open Access Journals (Sweden)
Hughes Barry D
2007-03-01
Full Text Available Abstract Background This article deals with the theoretical size distribution (of number of sub-taxa of a fossil taxon arising from a simple null model of macroevolution. Model New species arise through speciations occurring independently and at random at a fixed probability rate, while extinctions either occur independently and at random (background extinctions or cataclysmically. In addition new genera are assumed to arise through speciations of a very radical nature, again assumed to occur independently and at random at a fixed probability rate. Conclusion The size distributions of the pioneering genus (following a cataclysm and of derived genera are determined. Also the distribution of the number of genera is considered along with a comparison of the probability of a monospecific genus with that of a monogeneric family.
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Stochastic models for the Trojan Y-Chromosome eradication strategy of an invasive species.
Wang, Xueying; Walton, Jay R; Parshad, Rana D
2016-01-01
The Trojan Y-Chromosome (TYC) strategy, an autocidal genetic biocontrol method, has been proposed to eliminate invasive alien species. In this work, we develop a Markov jump process model for this strategy, and we verify that there is a positive probability for wild-type females going extinct within a finite time. Moreover, when sex-reversed Trojan females are introduced at a constant population size, we formulate a stochastic differential equation (SDE) model as an approximation to the proposed Markov jump process model. Using the SDE model, we investigate the probability distribution and expectation of the extinction time of wild-type females by solving Kolmogorov equations associated with these statistics. The results indicate how the probability distribution and expectation of the extinction time are shaped by the initial conditions and the model parameters.
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Modeling Malaria Vector Distribution under Climate Change Scenarios in Kenya
Ngaina, J. N.
2017-12-01
Projecting the distribution of malaria vectors under climate change is essential for planning integrated vector control strategies for sustaining elimination and preventing reintroduction of malaria. However, in Kenya, little knowledge exists on the possible effects of climate change on malaria vectors. Here we assess the potential impact of future climate change on locally dominant Anopheles vectors including Anopheles gambiae, Anopheles arabiensis, Anopheles merus, Anopheles funestus, Anopheles pharoensis and Anopheles nili. Environmental data (Climate, Land cover and elevation) and primary empirical geo-located species-presence data were identified. The principle of maximum entropy (Maxent) was used to model the species' potential distribution area under paleoclimate, current and future climates. The Maxent model was highly accurate with a statistically significant AUC value. Simulation-based estimates suggest that the environmentally suitable area (ESA) for Anopheles gambiae, An. arabiensis, An. funestus and An. pharoensis would increase under all two scenarios for mid-century (2016-2045), but decrease for end century (2071-2100). An increase in ESA of An. Funestus was estimated under medium stabilizing (RCP4.5) and very heavy (RCP8.5) emission scenarios for mid-century. Our findings can be applied in various ways such as the identification of additional localities where Anopheles malaria vectors may already exist, but has not yet been detected and the recognition of localities where it is likely to spread to. Moreover, it will help guide future sampling location decisions, help with the planning of vector control suites nationally and encourage broader research inquiry into vector species niche modeling
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Mukhopadhyay, Anirban; Mondal, Parimal; Barik, Jyotiskona; Chowdhury, S M; Ghosh, Tuhin; Hazra, Sugata
2015-06-01
The composition and assemblage of mangroves in the Bangladesh Sundarbans are changing systematically in response to several environmental factors. In order to understand the impact of the changing environmental conditions on the mangrove forest, species composition maps for the years 1985, 1995 and 2005 were studied. In the present study, 1985 and 1995 species zonation maps were considered as base data and the cellular automata-Markov chain model was run to predict the species zonation for the year 2005. The model output was validated against the actual dataset for 2005 and calibrated. Finally, using the model, mangrove species zonation maps for the years 2025, 2055 and 2105 have been prepared. The model was run with the assumption that the continuation of the current tempo and mode of drivers of environmental factors (temperature, rainfall, salinity change) of the last two decades will remain the same in the next few decades. Present findings show that the area distribution of the following species assemblages like Goran (Ceriops), Sundari (Heritiera), Passur (Xylocarpus), and Baen (Avicennia) would decrease in the descending order, whereas the area distribution of Gewa (Excoecaria), Keora (Sonneratia) and Kankra (Bruguiera) dominated assemblages would increase. The spatial distribution of projected mangrove species assemblages shows that more salt tolerant species will dominate in the future; which may be used as a proxy to predict the increase of salinity and its spatial variation in Sundarbans. Considering the present rate of loss of forest land, 17% of the total mangrove cover is predicted to be lost by the year 2105 with a significant loss of fresh water loving mangroves and related ecosystem services. This paper describes a unique approach to assess future changes in species composition and future forest zonation in mangroves under the 'business as usual' scenario of climate change.
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Directory of Open Access Journals (Sweden)
Patricia Puerta
Full Text Available Populations of the same species can experience different responses to the environment throughout their distributional range as a result of spatial and temporal heterogeneity in habitat conditions. This highlights the importance of understanding the processes governing species distribution at local scales. However, research on species distribution often averages environmental covariates across large geographic areas, missing variability in population-environment interactions within geographically distinct regions. We used spatially explicit models to identify interactions between species and environmental, including chlorophyll a (Chla and sea surface temperature (SST, and trophic (prey density conditions, along with processes governing the distribution of two cephalopods with contrasting life-histories (octopus and squid across the western Mediterranean Sea. This approach is relevant for cephalopods, since their population dynamics are especially sensitive to variations in habitat conditions and rarely stable in abundance and location. The regional distributions of the two cephalopod species matched two different trophic pathways present in the western Mediterranean Sea, associated with the Gulf of Lion upwelling and the Ebro river discharges respectively. The effects of the studied environmental and trophic conditions were spatially variant in both species, with usually stronger effects along their distributional boundaries. We identify areas where prey availability limited the abundance of cephalopod populations as well as contrasting effects of temperature in the warmest regions. Despite distributional patterns matching productive areas, a general negative effect of Chla on cephalopod densities suggests that competition pressure is common in the study area. Additionally, results highlight the importance of trophic interactions, beyond other common environmental factors, in shaping the distribution of cephalopod populations. Our study presents
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Huff, David D; Lindley, Steven T; Wells, Brian K; Chai, Fei
2012-01-01
The green sturgeon (Acipenser medirostris), which is found in the eastern Pacific Ocean from Baja California to the Bering Sea, tends to be highly migratory, moving long distances among estuaries, spawning rivers, and distant coastal regions. Factors that determine the oceanic distribution of green sturgeon are unclear, but broad-scale physical conditions interacting with migration behavior may play an important role. We estimated the distribution of green sturgeon by modeling species-environment relationships using oceanographic and migration behavior covariates with maximum entropy modeling (MaxEnt) of species geographic distributions. The primary concentration of green sturgeon was estimated from approximately 41-51.5° N latitude in the coastal waters of Washington, Oregon, and Vancouver Island and in the vicinity of San Francisco and Monterey Bays from 36-37° N latitude. Unsuitably cold water temperatures in the far north and energetic efficiencies associated with prevailing water currents may provide the best explanation for the range-wide marine distribution of green sturgeon. Independent trawl records, fisheries observer records, and tagging studies corroborated our findings. However, our model also delineated patchily distributed habitat south of Monterey Bay, though there are few records of green sturgeon from this region. Green sturgeon are likely influenced by countervailing pressures governing their dispersal. They are behaviorally directed to revisit natal freshwater spawning rivers and persistent overwintering grounds in coastal marine habitats, yet they are likely physiologically bounded by abiotic and biotic environmental features. Impacts of human activities on green sturgeon or their habitat in coastal waters, such as bottom-disturbing trawl fisheries, may be minimized through marine spatial planning that makes use of high-quality species distribution information.
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Species sensitivity distributions in a context of practical applications for risk-based decisions
Energy Technology Data Exchange (ETDEWEB)
Posthuma, L.; Traas, T.P.; Roelofs, W.; Winterse, A.; Zwart, D. de; Meent, D. van de [RIVM, Bilthoven (Netherlands)
2003-07-01
Different biological species clearly show different sensitivities to toxic compounds present in their habitat. The absence of differences in sensitivity would entail an 'all nothing' response, with all species responding similarly to pollution. Given the sensitivity variation, however, some species show adverse effects, and others flourish. In this sense, variation is 'music for ecotoxicologists'. But it also is a nuisance: ecotoxicologists need to handle the vast diversity of sensitivities in Ecological Risk Assessment (ERA). This contribution addresses a pragmatic, versatile, statistics-based concept to address species sensitivity differences, and shows options for application. In the 1980s, ecotoxicologists have coined the term 'Species Sensitivity Distributions' (SSDs) for the statistical descriptions that can be applied to address sensitivity variation. An SSD is a Probability Density Function (usually bell-shaped) or Cumulative Distribution Function (sigmoid), that relates the environmental concentration (x) to 'risk' (y). Since their original description and use, the concept was further developed, criticised, and tailored to various policy or assessment problems. (orig.)
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Directory of Open Access Journals (Sweden)
J. Bieser
2017-06-01
Full Text Available Atmospheric chemistry and transport of mercury play a key role in the global mercury cycle. However, there are still considerable knowledge gaps concerning the fate of mercury in the atmosphere. This is the second part of a model intercomparison study investigating the impact of atmospheric chemistry and emissions on mercury in the atmosphere. While the first study focused on ground-based observations of mercury concentration and deposition, here we investigate the vertical and interhemispheric distribution and speciation of mercury from the planetary boundary layer to the lower stratosphere. So far, there have been few model studies investigating the vertical distribution of mercury, mostly focusing on single aircraft campaigns. Here, we present a first comprehensive analysis based on various aircraft observations in Europe, North America, and on intercontinental flights. The investigated models proved to be able to reproduce the distribution of total and elemental mercury concentrations in the troposphere including interhemispheric trends. One key aspect of the study is the investigation of mercury oxidation in the troposphere. We found that different chemistry schemes were better at reproducing observed oxidized mercury patterns depending on altitude. High concentrations of oxidized mercury in the upper troposphere could be reproduced with oxidation by bromine while elevated concentrations in the lower troposphere were better reproduced by OH and ozone chemistry. However, the results were not always conclusive as the physical and chemical parameterizations in the chemistry transport models also proved to have a substantial impact on model results.
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Richards-like two species population dynamics model.
Ribeiro, Fabiano; Cabella, Brenno Caetano Troca; Martinez, Alexandre Souto
2014-12-01
The two-species population dynamics model is the simplest paradigm of inter- and intra-species interaction. Here, we present a generalized Lotka-Volterra model with intraspecific competition, which retrieves as particular cases, some well-known models. The generalization parameter is related to the species habitat dimensionality and their interaction range. Contrary to standard models, the species coupling parameters are general, not restricted to non-negative values. Therefore, they may represent different ecological regimes, which are derived from the asymptotic solution stability analysis and are represented in a phase diagram. In this diagram, we have identified a forbidden region in the mutualism regime, and a survival/extinction transition with dependence on initial conditions for the competition regime. Also, we shed light on two types of predation and competition: weak, if there are species coexistence, or strong, if at least one species is extinguished.
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Digital Repository Service at National Institute of Oceanography (India)
Santhakumari, V.; Tiwari, L.R.; Nair, V.R.
Species composition, abundance and distribution of hydromedusae from Dharamtar estuarine system, adjoining Bombay Harbour, Maharashtra, India were investigated during 1984-1985. Twenty six species belonging to 19 genera were obtained from this area...
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Directory of Open Access Journals (Sweden)
Delin Wang
2016-10-01
Full Text Available The vocalization source level distributions and pulse compression gains are estimated for four distinct baleen whale species in the Gulf of Maine: fin, sei, minke and an unidentified baleen whale species. The vocalizations were received on a large-aperture densely-sampled coherent hydrophone array system useful for monitoring marine mammals over instantaneous wide areas via the passive ocean acoustic waveguide remote sensing technique. For each baleen whale species, between 125 and over 1400 measured vocalizations with significantly high Signal-to-Noise Ratios (SNR > 10 dB after coherent beamforming and localized with high accuracies (<10% localization errors over ranges spanning roughly 1 km–30 km are included in the analysis. The whale vocalization received pressure levels are corrected for broadband transmission losses modeled using a calibrated parabolic equation-based acoustic propagation model for a random range-dependent ocean waveguide. The whale vocalization source level distributions are characterized by the following means and standard deviations, in units of dB re 1 μ Pa at 1 m: 181.9 ± 5.2 for fin whale 20-Hz pulses, 173.5 ± 3.2 for sei whale downsweep chirps, 177.7 ± 5.4 for minke whale pulse trains and 169.6 ± 3.5 for the unidentified baleen whale species downsweep calls. The broadband vocalization equivalent pulse-compression gains are found to be 2.5 ± 1.1 for fin whale 20-Hz pulses, 24 ± 10 for the unidentified baleen whale species downsweep calls and 69 ± 23 for sei whale downsweep chirps. These pulse compression gains are found to be roughly proportional to the inter-pulse intervals of the vocalizations, which are 11 ± 5 s for fin whale 20-Hz pulses, 29 ± 18 for the unidentified baleen whale species downsweep calls and 52 ± 33 for sei whale downsweep chirps. The source level distributions and pulse compression gains are essential for determining signal-to-noise ratios and hence detection regions for baleen whale
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Poorter, Hendrik; Jagodzinski, Andrzej M; Ruiz-Peinado, Ricardo; Kuyah, Shem; Luo, Yunjian; Oleksyn, Jacek; Usoltsev, Vladimir A; Buckley, Thomas N; Reich, Peter B; Sack, Lawren
2015-11-01
We compiled a global database for leaf, stem and root biomass representing c. 11 000 records for c. 1200 herbaceous and woody species grown under either controlled or field conditions. We used this data set to analyse allometric relationships and fractional biomass distribution to leaves, stems and roots. We tested whether allometric scaling exponents are generally constant across plant sizes as predicted by metabolic scaling theory, or whether instead they change dynamically with plant size. We also quantified interspecific variation in biomass distribution among plant families and functional groups. Across all species combined, leaf vs stem and leaf vs root scaling exponents decreased from c. 1.00 for small plants to c. 0.60 for the largest trees considered. Evergreens had substantially higher leaf mass fractions (LMFs) than deciduous species, whereas graminoids maintained higher root mass fractions (RMFs) than eudicotyledonous herbs. These patterns do not support the hypothesis of fixed allometric exponents. Rather, continuous shifts in allometric exponents with plant size during ontogeny and evolution are the norm. Across seed plants, variation in biomass distribution among species is related more to function than phylogeny. We propose that the higher LMF of evergreens at least partly compensates for their relatively low leaf area : leaf mass ratio. © 2015 The Authors. New Phytologist © 2015 New Phytologist Trust.
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Thapa, Sunil; Chitale, Vishwas; Rijal, Srijana Joshi; Bisht, Neha; Shrestha, Bharat Babu
2018-01-01
Invasive alien plant species (IAPS) can pose severe threats to biodiversity and stability of native ecosystems, therefore, predicting the distribution of the IAPS plays a crucial role in effective planning and management of ecosystems. In the present study, we use Maximum Entropy (MaxEnt) modelling approach to predict the potential of distribution of eleven IAPS under future climatic conditions under RCP 2.6 and RCP 8.5 in part of Kailash sacred landscape region in Western Himalaya. Based on the model predictions, distribution of most of these invasive plants is expected to expand under future climatic scenarios, which might pose a serious threat to the native ecosystems through competition for resources in the study area. Native scrublands and subtropical needle-leaved forests will be the most affected ecosystems by the expansion of these IAPS. The present study is first of its kind in the Kailash Sacred Landscape in the field of invasive plants and the predictions of potential distribution under future climatic conditions from our study could help decision makers in planning and managing these forest ecosystems effectively.
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DEFF Research Database (Denmark)
Nieto-Lugilde, Diego; Lenoir, Jonathan; Abdulhak, Sylvain
2012-01-01
on the occurrence on light-demanding species via size-asymmetric competition for light, but a facilitative effect on shade-tolerant species. In order to compare the relative importance of tree cover, four models with different combinations of variables (climate, soil and tree cover) were run for each species. Then...... role. Results indicated that high tree cover causes range contraction, especially at the upper limit, for light-demanding species, whereas it causes shade-tolerant species to extend their range upwards and downwards. Tree cover thus drives plant-plant interactions to shape plant species distribution...
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New distribution records for four mammal species, with notes on their taxonomy and ecology
Directory of Open Access Journals (Sweden)
G.N. Bronner
1990-09-01
Full Text Available New distribution records for four small mammal species (Georychus capensis, Galerella pulverulenta, Rhinolophus swinnyi and Amblysomus julianae are presented, along with relevant notes on the taxonomy, karyology and ecology of these species.
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Hu, Zhong-jun; Zhang, Yi-li; Yu, Hai-bin
2015-02-01
The impact of climate change on species distribution is a hot issue in biogeography research. This study utilized the constructive species Stipa purpurea as the research object, which was widely distributed in alpine meadow of the Tibetan Plateau, investigated its distribution in the Tibetan Plateau through the field survey and herbarium search, and used MaxEnt model to simulate its historical, current and future distribution trends to analyze its distribution pattern in each historical period and explore the cause of species distribution changes. Research results showed that diversity of Stipa species in alpine grassland of the Tibetan Plateau was high, its main distribution area was the hinterland of the Tibetan Plateau and areas along the Himalaya, and its distribution was strongly affected by precipitation of warmest quarter, precipitation of wettest quarter and annual precipitation. According to the distribution pattern of S. purpurea in the Last Glacial Maximum, and geographical and geological features of the Tibetan Plateau, this paper proposed that: North Tibet core area of South Qiangtang and Ali region of west Himalaya mountainous area were the core area of the potential distribution for S. purpurea, since these regions could provide more suitable habitats for S. purpurea than other regions and be the refugia where the current S. purpurea was migrated and differentiated from. The presence of refugia may contribute to the understanding of related issues of the alpine plants' origin and differentiation in the Tibetan Plateau.
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Directory of Open Access Journals (Sweden)
Michael Drexler
Full Text Available Spatially explicit ecosystem models of all types require an initial allocation of biomass, often in areas where fisheries independent abundance estimates do not exist. A generalized additive modelling (GAM approach is used to describe the abundance of 40 species groups (i.e. functional groups across the Gulf of Mexico (GoM using a large fisheries independent data set (SEAMAP and climate scale oceanographic conditions. Predictor variables included in the model are chlorophyll a, sediment type, dissolved oxygen, temperature, and depth. Despite the presence of a large number of zeros in the data, a single GAM using a negative binomial distribution was suitable to make predictions of abundance for multiple functional groups. We present an example case study using pink shrimp (Farfantepenaeus duroarum and compare the results to known distributions. The model successfully predicts the known areas of high abundance in the GoM, including those areas where no data was inputted into the model fitting. Overall, the model reliably captures areas of high and low abundance for the large majority of functional groups observed in SEAMAP. The result of this method allows for the objective setting of spatial distributions for numerous functional groups across a modeling domain, even where abundance data may not exist.
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Vertical distribution and migration of euphausiid species in the Red Sea
Wiebe, Peter H.; Bucklin, Ann; Kaartvedt, Stein; Rø stad, Anders; Blanco-Bercial, Leocadio
2016-01-01
We addressed how the extreme environmental conditions of the Red Sea impact or alter patterns of vertical distribution and vertical migration of five euphausiid species that are known from other oceans. Euphausia diomedeae was abundant and performed
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Directory of Open Access Journals (Sweden)
Jens G Froese
Full Text Available Invasive wildlife often causes serious damage to the economy and agriculture as well as environmental, human and animal health. Habitat models can fill knowledge gaps about species distributions and assist planning to mitigate impacts. Yet, model accuracy and utility may be compromised by small study areas and limited integration of species ecology or temporal variability. Here we modelled seasonal habitat suitability for wild pigs, a widespread and harmful invader, in northern Australia. We developed a resource-based, spatially-explicit and regional-scale approach using Bayesian networks and spatial pattern suitability analysis. We integrated important ecological factors such as variability in environmental conditions, breeding requirements and home range movements. The habitat model was parameterized during a structured, iterative expert elicitation process and applied to a wet season and a dry season scenario. Model performance and uncertainty was evaluated against independent distributional data sets. Validation results showed that an expert-averaged model accurately predicted empirical wild pig presences in northern Australia for both seasonal scenarios. Model uncertainty was largely associated with different expert assumptions about wild pigs' resource-seeking home range movements. Habitat suitability varied considerably between seasons, retracting to resource-abundant rainforest, wetland and agricultural refuge areas during the dry season and expanding widely into surrounding grassland floodplains, savanna woodlands and coastal shrubs during the wet season. Overall, our model suggested that suitable wild pig habitat is less widely available in northern Australia than previously thought. Mapped results may be used to quantify impacts, assess risks, justify management investments and target control activities. Our methods are applicable to other wide-ranging species, especially in data-poor situations.
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Jarløv, J O; Højbjerg, T; Busch-Sørensen, C; Scheibel, J; Møller, J K; Kolmos, H J; Wandall, D A
1996-03-01
The distribution and antibiotic susceptibility of coagulase-negative staphylococci (CoNS) isolated from blood cultures was examined in samples from hospitals covering most of Denmark. A total of 499 CoNS isolates were detected in 477 blood cultures from 340 patients and speciated as Staphylococcus epidermidis, 285; Staphylococcus hominis, 61; Staphylococcus haemolyticus, 43; Staphylococcus warneri, 12; Staphylococcus cohnii, 7; Staphylococcus saprophyticus, 4; Staphylococcus capitis, 2 and Staphylococcus lugdunensis, 1. Seventy-eight isolates could not be identified to species level and six were Micrococcus spp. In 108 (22.6%) blood culture sets, more than one CoNS strain were found, as detected by species identification, antibiogram and biotyping. Significantly more blood cultures from patients in university hospitals were drawn from central venous catheters. Comparing university and non-university hospitals, the overall antibiotic susceptibility among CoNS was only slightly different, except for methicillin and amikacin. The prevalence of methicillin-resistant strains was 35.1% in the university hospital strains vs. 25.3% in the non-university hospital strains. The overall prevalence of methicillin resistance was 32%. Great geographic variation in both species distribution and antibiotic resistance was observed. The high prevalence of S. epidermidis makes subtyping of this species important.
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Stationary distribution and ergodicity of a stochastic food-chain model with Lévy jumps
Yu, Jingyi; Liu, Meng
2017-09-01
In this paper, a three-species stochastic food-chain model with Lévy jumps is proposed and analyzed. Sharp sufficient criteria for the existence and uniqueness of an ergodic stationary distribution are established. The effects of Lévy jumps on the existence of the stationary distribution are revealed: in some cases, the Lévy jumps could make the stationary distribution appear, while in some cases, the Lévy jumps could make the stationary distribution disappear. Some numerical simulations are introduced to illustrate the theoretical results.
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Species Abundance in a Forest Community in South China: A Case of Poisson Lognormal Distribution
Institute of Scientific and Technical Information of China (English)
Zuo-Yun YIN; Hai REN; Qian-Mei ZHANG; Shao-Lin PENG; Qin-Feng GUO; Guo-Yi ZHOU
2005-01-01
Case studies on Poisson lognormal distribution of species abundance have been rare, especially in forest communities. We propose a numerical method to fit the Poisson lognormal to the species abundance data at an evergreen mixed forest in the Dinghushan Biosphere Reserve, South China. Plants in the tree, shrub and herb layers in 25 quadrats of 20 m×20 m, 5 m×5 m, and 1 m×1 m were surveyed. Results indicated that: (i) for each layer, the observed species abundance with a similarly small median, mode, and a variance larger than the mean was reverse J-shaped and followed well the zero-truncated Poisson lognormal;(ii) the coefficient of variation, skewness and kurtosis of abundance, and two Poisson lognormal parameters (σ andμ) for shrub layer were closer to those for the herb layer than those for the tree layer; and (iii) from the tree to the shrub to the herb layer, the σ and the coefficient of variation decreased, whereas diversity increased. We suggest that: (i) the species abundance distributions in the three layers reflects the overall community characteristics; (ii) the Poisson lognormal can describe the species abundance distribution in diverse communities with a few abundant species but many rare species; and (iii) 1/σ should be an alternative measure of diversity.
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Hylid frogs from Mount Ayanganna, Guyana: new species, redescriptions, and distributional records
Directory of Open Access Journals (Sweden)
Ross D. MacCulloch
2005-10-01
Full Text Available A new species of Osteocephalus, one species of Hyla, three species of Hypsiboas and one of Myersiohyla were collected on Mount Ayanganna, a sandstone Guiana Shield tepui. Hyla warreni, Hypsiboas roraima, H. sibleszi, Myersiohyla kanaima and the new Osteocephalus were collected in high-tepui forest at 1500 m elevation, while Hypsiboas lemai, H. roraima and M. kanaima were also collected in lower montane forest at 870 m. Supplementary descriptions of adults of all species of Hyla, Hypsiboas and Myersiohyla based on the newly collected specimens are provided. Tadpoles of M. kanaima are described. The specimens from Ayanganna represent significant distributional records for several species. This is the first record of Osteocephalus as a member of the Guiana Shield high-tepui herpetofauna.
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Matthews, Thomas J; Whittaker, Robert J
2014-01-01
Published in 2001, The Unified Neutral Theory of Biodiversity and Biogeography (UNTB) emphasizes the importance of stochastic processes in ecological community structure, and has challenged the traditional niche-based view of ecology. While neutral models have since been applied to a broad range of ecological and macroecological phenomena, the majority of research relating to neutral theory has focused exclusively on the species abundance distribution (SAD). Here, we synthesize the large body of work on neutral theory in the context of the species abundance distribution, with a particular focus on integrating ideas from neutral theory with traditional niche theory. First, we summarize the basic tenets of neutral theory; both in general and in the context of SADs. Second, we explore the issues associated with neutral theory and the SAD, such as complications with fitting and model comparison, the underlying assumptions of neutral models, and the difficultly of linking pattern to process. Third, we highlight the advances in understanding of SADs that have resulted from neutral theory and models. Finally, we focus consideration on recent developments aimed at unifying neutral- and niche-based approaches to ecology, with a particular emphasis on what this means for SAD theory, embracing, for instance, ideas of emergent neutrality and stochastic niche theory. We put forward the argument that the prospect of the unification of niche and neutral perspectives represents one of the most promising future avenues of neutral theory research. PMID:25360266
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Matthews, Thomas J; Whittaker, Robert J
2014-06-01
Published in 2001, The Unified Neutral Theory of Biodiversity and Biogeography (UNTB) emphasizes the importance of stochastic processes in ecological community structure, and has challenged the traditional niche-based view of ecology. While neutral models have since been applied to a broad range of ecological and macroecological phenomena, the majority of research relating to neutral theory has focused exclusively on the species abundance distribution (SAD). Here, we synthesize the large body of work on neutral theory in the context of the species abundance distribution, with a particular focus on integrating ideas from neutral theory with traditional niche theory. First, we summarize the basic tenets of neutral theory; both in general and in the context of SADs. Second, we explore the issues associated with neutral theory and the SAD, such as complications with fitting and model comparison, the underlying assumptions of neutral models, and the difficultly of linking pattern to process. Third, we highlight the advances in understanding of SADs that have resulted from neutral theory and models. Finally, we focus consideration on recent developments aimed at unifying neutral- and niche-based approaches to ecology, with a particular emphasis on what this means for SAD theory, embracing, for instance, ideas of emergent neutrality and stochastic niche theory. We put forward the argument that the prospect of the unification of niche and neutral perspectives represents one of the most promising future avenues of neutral theory research.
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Modelling the growth of Populus species using Ecosystem Demography (ED) model
Wang, D.; Lebauer, D. S.; Feng, X.; Dietze, M. C.
2010-12-01
Hybrid poplar plantations are an important source being evaluated for biomass production. Effective management of such plantations requires adequate growth and yield models. The Ecosystem Demography model (ED) makes predictions about the large scales of interest in above- and belowground ecosystem structure and the fluxes of carbon and water from a description of the fine-scale physiological processes. In this study, we used a workflow management tool, the Predictive Ecophysiological Carbon flux Analyzer (PECAn), to integrate literature data, field measurement and the ED model to provide predictions of ecosystem functioning. Parameters for the ED ensemble runs were sampled from the posterior distribution of ecophysiological traits of Populus species compiled from the literature using a Bayesian meta-analysis approach. Sensitivity analysis was performed to identify the parameters which contribute the most to the uncertainties of the ED model output. Model emulation techniques were used to update parameter posterior distributions using field-observed data in northern Wisconsin hybrid poplar plantations. Model results were evaluated with 5-year field-observed data in a hybrid poplar plantation at New Franklin, MO. ED was then used to predict the spatial variability of poplar yield in the coterminous United States (United States minus Alaska and Hawaii). Sensitivity analysis showed that root respiration, dark respiration, growth respiration, stomatal slope and specific leaf area contribute the most to the uncertainty, which suggests that our field measurements and data collection should focus on these parameters. The ED model successfully captured the inter-annual and spatial variability of the yield of poplar. Analyses in progress with the ED model focus on evaluating the ecosystem services of short-rotation woody plantations, such as impacts on soil carbon storage, water use, and nutrient retention.
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Rosen, G.
1976-01-01
The basic form of a model representation for systems of n interacting biological species is a set of essentially nonlinear autonomous ordinary differential equations. A generic canonical expression for the rate functions in the equations is reported which permits the analytical general solution to be obtained by elementary computation. It is shown that a general analytical solution is directly obtainable for models where the rate functions are prescribed by the generic canonical expression from the outset. Some illustrative examples are given which demonstrate that the generic canonical expression can be used to construct analytically solvable models for two interacting species with limit-cycle dynamics as well as for a three-species interdependence.
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Physico-chemical thresholds in the distribution of fish species among French lakes
Directory of Open Access Journals (Sweden)
Roubeix Vincent
2017-01-01
Full Text Available The management of lakes requires the definition of physico-chemical thresholds to be used for ecosystem preservation or restoration. According to the European Water Framework Directive, the limits between physico-chemical quality classes must be set consistently with biological quality elements. One way to do this consists in analyzing the response of aquatic communities to environmental gradients across monitoring sites and in identifying ecological community thresholds, i.e. zones in the gradients where the species turnover is the highest. In this study, fish data from 196 lakes in France were considered to derive ecological thresholds using the multivariate method of gradient forest. The analysis was performed on 25 species and 36 environmental parameters. The results revealed the highest importance of maximal water temperature in the distribution of fish species. Other important parameters included geographical factors, dissolved organic carbon concentration and water transparency, while nutrients appeared to have low influence. In spite of the diversity of species responses to the gradients, community thresholds were detected in the gradients of the most important physico-chemical parameters and of total phosphorus and nitrate concentrations as well. The thresholds identified in such macroecological study may highlight new patterns of species natural distribution and improve niche characterization. Moreover, when factors that may be influenced by human activities are involved, the thresholds could be used to set environmental standards for lake preservation.
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Distribution of silica species in cooling water system in nuclear power station
International Nuclear Information System (INIS)
Akiba, Kenichi; Onozuka, Teruo; Shindo, Manabu.
1995-01-01
Distribution of silica species was examined by spectrophotometric method based on the formation of molybdosilicic acid species. Ultra-microamounts of ionic (reactive) silica were determined by collection of silicomolybdenum blue compound on a nitrocellulose membrane filter. Total concentrations of silica including nonionic (polymer and colloidal) species were also determined after decomposition of unreactive silica in alkali solutions. Water in the nuclear reactor (Onagawa BWR No.1) contained high concentration of silica (∼600 ppb) and ionic silica was found to be predominant (∼90%). In condensate system, silica contents were of a lower level (2-6 ppb), but the ionic silica contents were comparable to others (20-60%). The silica species appear to be brought and accumulated in the reactor from the condensate system, and then the silica species change to ionic species under high pressure and high temperature. (author)
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Distribution of silica species in cooling water system in nuclear power station
Energy Technology Data Exchange (ETDEWEB)
Akiba, Kenichi [Tohoku Univ., Sendai (Japan). Inst. for Advanced Materials Processing; Onozuka, Teruo; Shindo, Manabu
1995-12-01
Distribution of silica species was examined by spectrophotometric method based on the formation of molybdosilicic acid species. Ultra-microamounts of ionic (reactive) silica were determined by collection of silicomolybdenum blue compound on a nitrocellulose membrane filter. Total concentrations of silica including nonionic (polymer and colloidal) species were also determined after decomposition of unreactive silica in alkali solutions. Water in the nuclear reactor (Onagawa BWR No.1) contained high concentration of silica ({approx}600 ppb) and ionic silica was found to be predominant ({approx}90%). In condensate system, silica contents were of a lower level (2-6 ppb), but the ionic silica contents were comparable to others (20-60%). The silica species appear to be brought and accumulated in the reactor from the condensate system, and then the silica species change to ionic species under high pressure and high temperature. (author).
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Directory of Open Access Journals (Sweden)
Sebastian Dalgarno
2017-12-01
Full Text Available We present a species distribution model (SDM for prediction of Black Oystercatcher (Haematopus bachmani breeding pair occurrence in Haida Gwaii, British Columbia. Boosted regression trees, a machine learning algorithm, was used to fit the model. In total, 14 predictors were selected a priori through development of a conceptual model. Breeding pair occurrence data were compiled from two available surveys conducted in 2005 and 2010 (545 km of shoreline surveyed in total. All data were aggregated to common model units (vector polyline shoreline segments approximately 100 m in length, which approximate breeding territory size. The final model, which included eight predictors (distance to treeline, island area, wave exposure, shoreline type, intertidal area within 50 m, segment length, rat occurrence, and intertidal area within 1000 m, had excellent predictive ability assessed by 10-fold cross-validation (AUC = 0.89. Predictive ability was reduced when the model was trained and tested on spatially (AUC = 0.86 and temporally (AUC = 0.83 independent data. Distance to treeline and island area had greatest influence on the model (RI = 41.5% and RI = 36.7%, respectively; we hypothesized that these predictors are related to avoidance of predators. Partial dependence plots revealed that breeding pairs tended to occur: further from the treeline, on small islands, at high wave exposures, at moderate intertidal area, on bedrock or gravel shoreline types, and on islands without rats. However, breeding pairs tended not to occur on very small islands and at very high wave exposures, which we hypothesize to reflect avoidance of nest washout. Results may inform local conservation and management efforts, i.e., from predictive maps, and eventual development of a high-resolution (~100 m model for prediction of Black Oystercatcher breeding pairs at a regional scale. Further, methods and GIS data sets developed may be used to model distribution of other coastal species
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Distribution patterns of Saccharomyces species in cultural landscapes of Germany.
Brysch-Herzberg, Michael; Seidel, Martin
2017-08-01
The distribution patterns of the three Saccharomyces species, Saccharomyces paradoxus, S. uvarum and S. cerevisiae, were investigated by a culture-dependent approach in order to understand better how these species propagate in the cultural landscape of Germany. Saccharomyces paradoxus, the closest relative of S. cerevisiae, is shown to be a true woodland species. It was frequently found in the soil under conifers indicating that S. paradoxus is an autochthonous member of the microbial community in this habitat. Physiological characteristics of the species like the Crabtree effect and high tolerance against ethanol suggest that the species is adapted to regular supply with considerable amounts of sugars. Additionally, a high proportion of the S. paradoxus strains isolated in this study are shown to have the rare ability to ferment melezitose. For these reasons, it is hypothesized that S. paradoxus may be closely associated with the honeydew system in forests. Saccharomyces cerevisiae was rare in most habitats and only exceeded the frequency of S. paradoxus in habitats characterized by modern agricultural mass production of fruit. Both the landscape structure and the agricultural system heavily influence the frequencies of Saccharomyces species. © FEMS 2017. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
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Directory of Open Access Journals (Sweden)
C. F. Rodrigues
2013-04-01
Full Text Available Previous work in the mud volcanoes from the Gulf of Cadiz (South Iberian Margin revealed a high number of chemosymbiotic species, namely bivalves and siboglinid polychaetes. In this study we give an overview of the distribution and life styles of these species in the Gulf of Cadiz, determine the role of autotrophic symbionts in the nutrition of selected species using stable isotope analyses (δ13C, δ15N and δ34S and investigate the intra-specific variation of isotope signatures within and between study sites. During our studies, we identified twenty siboglinidae and nine bivalve chemosymbiotic species living in fifteen mud volcanoes. Solemyid bivalves and tubeworms of the genus Siboglinum are widespread in the study area, whereas other species were found in a single mud volcano (e.g. "Bathymodiolus" mauritanicus or restricted to deeper mud volcanoes (e.g. Polybrachia sp., Lamelisabella denticulata. Species distribution suggests that different species may adjust their position within the sediment according to their particular needs, and to the intensity and variability of the chemical substrata supply. Tissue stable isotope signatures for selected species are in accordance with values found in other studies, with thiotrophy as the dominant nutritional pathway, and with methanotrophy and mixotrophy emerging as secondary strategies. The heterogeneity in terms of nutrient sources (expressed in the high variance of nitrogen and sulphur values and the ability to exploit different resources by the different species may explain the high diversity of chemosymbiotic species found in the Gulf of Cadiz. This study increases the knowledge on distributional patterns and resource partitioning of chemosymbiotic species and highlights how trophic fuelling varies on spatial scales with direct implications to seep assemblages and potentially to the biodiversity of continental margin.
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Directory of Open Access Journals (Sweden)
Guoqing Li
2014-11-01
Full Text Available Black locust (Robinia pseudoacacia L. is a tree species of high economic and ecological value, but is also considered to be highly invasive. Understanding the global potential distribution and ecological characteristics of this species is a prerequisite for its practical exploitation as a resource. Here, a maximum entropy modeling (MaxEnt was used to simulate the potential distribution of this species around the world, and the dominant climatic factors affecting its distribution were selected by using a jackknife test and the regularized gain change during each iteration of the training algorithm. The results show that the MaxEnt model performs better than random, with an average test AUC value of 0.9165 (±0.0088. The coldness index, annual mean temperature and warmth index were the most important climatic factors affecting the species distribution, explaining 65.79% of the variability in the geographical distribution. Species response curves showed unimodal relationships with the annual mean temperature and warmth index, whereas there was a linear relationship with the coldness index. The dominant climatic conditions in the core of the black locust distribution are a coldness index of −9.8 °C–0 °C, an annual mean temperature of 5.8 °C–14.5 °C, a warmth index of 66 °C–168 °C and an annual precipitation of 508–1867 mm. The potential distribution of black locust is located mainly in the United States, the United Kingdom, Germany, France, the Netherlands, Belgium, Italy, Switzerland, Australia, New Zealand, China, Japan, South Korea, South Africa, Chile and Argentina. The predictive map of black locust, climatic thresholds and species response curves can provide globally applicable guidelines and valuable information for policymakers and planners involved in the introduction, planting and invasion control of this species around the world.
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Q(n) species distribution in K2O.2SiO2 glass by 29Si magic angle flipping NMR.
Davis, Michael C; Kaseman, Derrick C; Parvani, Sahar M; Sanders, Kevin J; Grandinetti, Philip J; Massiot, Dominique; Florian, Pierre
2010-05-06
Two-dimensional magic angle flipping (MAF) was employed to measure the Q((n)) distribution in a (29)Si-enriched potassium disilicate glass (K(2)O.2SiO(2)). Relative concentrations of [Q((4))] = 7.2 +/- 0.3%, [Q((3))] = 82.9 +/- 0.1%, and [Q((2))] = 9.8 +/- 0.6% were obtained. Using the thermodynamic model for Q((n)) species disproportionation, these relative concentrations yield an equilibrium constant k(3) = 0.0103 +/- 0.0008, indicating, as expected, that the Q((n)) species distribution is close to binary in the potassium disilicate glass. A Gaussian distribution of isotropic chemical shifts was observed for each Q((n)) species with mean values of -82.74 +/- 0.03, -91.32 +/- 0.01, and -101.67 +/- 0.02 ppm and standard deviations of 3.27 +/- 0.03, 4.19 +/- 0.01, and 5.09 +/- 0.03 ppm for Q((2)), Q((3)), and Q((4)), respectively. Additionally, nuclear shielding anisotropy values of zeta =-85.0 +/- 1.3 ppm, eta = 0.48 +/- 0.02 for Q((2)) and zeta = -74.9 +/- 0.2 ppm, eta = 0.03 +/- 0.01 for Q((3)) were observed in the potassium disilicate glass.
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International Nuclear Information System (INIS)
Ravva, Srinivasa Rao; Iyer, Kannan N.; Gupta, S.K.; Gaikwad, Avinash J.
2014-01-01
Highlights: • A condensation model based on diffusion was implemented in FLUENT. • Validation of a condensation model for the H 2 distribution studies was performed. • Multi-component diffusion is used in the present work. • Appropriate grid and turbulence model were identified. - Abstract: This paper aims at the implementation details of a condensation model in the CFD code FLUENT and its validation so that it can be used in performing the containment hydrogen distribution studies. In such studies, computational fluid dynamics simulations are necessary for obtaining accurate predictions. While steam condensation plays an important role, commercial CFD codes such as FLUENT do not have an in-built condensation model. Therefore, a condensation model was developed and implemented in the FLUENT code through user defined functions (UDFs) for the sink terms in the mass, momentum, energy and species balance equations together with associated turbulence quantities viz., kinetic energy and dissipation rate. The implemented model was validated against the ISP-47 test of TOSQAN facility using the standard wall functions and enhanced wall treatment approaches. The best suitable grid size and the turbulence model for the low density gas (He) distribution studies are brought out in this paper
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DEFF Research Database (Denmark)
Olsen, Kent
2016-01-01
traits such as taxonomy, habitat specificity, metabolic plasticity, and biogeographic traits such zoogeographical origin. In Paper I we describe how changes in species richness pattern across Europe correlate with range changes in different taxonomic and biogeographic groups of dragonflies. We found...... specialized species adapted to permanent running (perennial lotic) water habitats. We found that species reproducing in temporary water track climate changes better than species adapted to permanent water. In Paper III we explore the relationship between metabolic plasticity (expressed as the ability to shift...... with less metabolic plasticity. We conducted experimental ex-situ measurements of metabolic rates measured as respiration rates at 10°C and 20°C, respectively, of four Scandinavian dragonfly species. We used two species with a northern distribution, one with a southern distribution and one ubiquitous...
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Smetacek, Victor; Klaas, Christine; Menden-Deuer, Susanne; Rynearson, Tatiana A.
The quantitative distribution of dominant phytoplankton species was mapped at high spatial resolution (15 km spacing) during a quasi-synoptic, mesoscale survey of hydrographical, chemical, pigment, and zooplankton fields carried out along the Antarctic Polar Front within a grid 140×130 km 2 during austral summer. A rapid assessment method for quantifying phytoplankton species by microscopy in concentrated samples on board enabled estimation of total biomass and that of dominant species at hourly sampling intervals. The biomass distribution pattern derived from this method was remarkably coherent and correlated very well with chlorophyll concentrations and the location of different water masses covered by the grid. A "background" chlorophyll concentration of 0.5 mg m -3 in the grid could be assigned to the uniformly distributed pico- and nanophytoplankton; all higher values (up to 2.0 mg m -3) were contributed by large diatoms. Three species complexes ( Chaetoceros atlanticus/dichaeta, Pseudo-nitzschia cf. Lineola, and Thalassiothrix antarctica) contributed about one-third each to the biomass. Although all species were found throughout the study area, distinct patterns in abundance emerged: The Thalassiothrix maximum was located north of the frontal jet, Chaetoceros biomass was highest along the jet, and Pseudo-nitzschia was the most uniformly distributed of the three taxa. Since the meridional pattern of biomass and species composition persisted for about 5 weeks, despite heavy grazing pressure of small copepods, we hypothesize that the dominant species reflect the highest degree of grazer protection in the assemblage. This is accomplished by large size, needle-shaped cells, and long spines armed with barbs. We suggest that these persistent species sequester the limiting nutrient—iron—from the assemblage of smaller, less-defended species that must hence have higher turn-over rates.
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Boyd, Charlotte; Castillo, Ramiro; Hunt, George L.; Punt, André E..; VanBlaricom, Glenn R.; Weimerskirch, Henri; Bertrand, Sophie
2015-01-01
Understanding the ecological processes that underpin species distribution patterns is a fundamental goal in spatial ecology. However, developing predictive models of habitat use is challenging for species that forage in marine environments, as both predators and prey are often highly mobile and difficult to monitor. Consequently, few studies have developed resource selection functions for marine predators based directly on the abundance and distribution of their prey.
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On the statistical mechanics of species abundance distributions.
Bowler, Michael G; Kelly, Colleen K
2012-09-01
A central issue in ecology is that of the factors determining the relative abundance of species within a natural community. The proper application of the principles of statistical physics to species abundance distributions (SADs) shows that simple ecological properties could account for the near universal features observed. These properties are (i) a limit on the number of individuals in an ecological guild and (ii) per capita birth and death rates. They underpin the neutral theory of Hubbell (2001), the master equation approach of Volkov et al. (2003, 2005) and the idiosyncratic (extreme niche) theory of Pueyo et al. (2007); they result in an underlying log series SAD, regardless of neutral or niche dynamics. The success of statistical mechanics in this application implies that communities are in dynamic equilibrium and hence that niches must be flexible and that temporal fluctuations on all sorts of scales are likely to be important in community structure. Copyright © 2012 Elsevier Inc. All rights reserved.
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De Visscher, A; Piepers, S; Haesebrouck, F; Supré, K; De Vliegher, S
2017-01-01
Coagulase-negative staphylococci (CNS) have become the main pathogens causing bovine mastitis in recent years. A huge variation in species distribution among herds has been observed in several studies, emphasizing the need to identify subgroup- and species-specific herd-level factors to improve our understanding of the differences in ecological and epidemiological nature between species. The use of bulk milk samples enables the inclusion of a large(r) number of herds needed to identify herd-level risk factors and increases the likelihood of recovering enough isolates per species needed for conducting subgroup- and, eventually, species-specific analyses at the same time. This study aimed to describe the prevalence and distribution of CNS species in bulk milk samples and to identify associated subgroup- and species-specific herd-level factors. Ninety percent of all bulk milk samples yielded CNS. Staphylococcus equorum was the predominant species, followed by Staphylococcus haemolyticus and Staphylococcus epidermidis. A seasonal effect was observed for several CNS species. Bulk milk samples from herds with a loose-pack or a tiestall housing system were more likely to yield CNS species compared with herds with a freestall barn, except for S. epidermidis, Staphylococcus simulans, and Staphylococcus cohnii. In September, herds in which udders were clipped had lower odds of yielding Staphylococcus chromogenes, S. simulans, and Staphylococcus xylosus, the CNS species assumed to be most relevant for udder health, in their bulk milk than herds in which udder clipping was not practiced. Bulk milk of herds participating in a monthly veterinary udder health-monitoring program was more likely to yield these 3 CNS species. Herds always receiving their milk quality premium or predisinfecting teats before attachment of the milking cluster had lower odds of having S. equorum in their bulk milk. Herds not using a single dry cotton or paper towel for each cow during premilking udder
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Directory of Open Access Journals (Sweden)
S. KATSANEVAKIS
2013-03-01
Full Text Available The European Alien Species Information Network (EASIN was created with the aim to provide easy access to accurate information on alien species in Europe. EASIN allows the retrieval of spatial information from existing online data providers in order to produce integrated georeferenced distribution maps of alien species in Europe. In November 2012, a new data provider, the Ellenic Network on Aquatic Invasive Species (ELNAIS, joined EASIN; this has significantly increased the available georeferenced information on marine/estuarine alien species in Greek waters. Here, we use maps created by EASIN to show differences in patterns of distribution in Greece for the most abundant Phyla of marine alien species - Mollusca, Arthropoda, Chordata and Annelida. We also show that the two main pathways of introduction of marine alien species (Lessepsian migration and Shipping are related to different patterns of species spatial distribution in Greece. Overall, the tools provided by EASIN can greatly aid scientists and policy makers in obtaining high quality information on marine alien species in Greece, especially after the association with ELNAIS.
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Does governance play a role in the distribution of invasive alien species?
Evans, Thomas; Zu Ermgassen, Philine; Amano, Tatsuya; Peh, Kelvin S-H
2018-02-01
Invasive alien species (IAS) constitute a major threat to global biological diversity. In order to control their spread, a detailed understanding of the factors influencing their distribution is essential. Although international trade is regarded as a major force structuring spatial patterns of IAS, the role of other social factors remains unclear. Despite studies highlighting the importance of strong governance in slowing drivers of biodiversity loss such as logging, deforestation, and agricultural intensification, no study has yet analyzed its contribution to the issue of IAS. Using estimates of governance quality and comprehensive spatiotemporal IAS data, we performed multiple linear regressions to investigate the effect of governance quality upon the distribution of species listed under "100 of the worst" IAS in 38 Eurasian countries as defined by DASIE. Our model suggested that for countries with higher GDP, stronger governance was associated with a greater number of the worst IAS; in contrast, for the lowest GDP countries under analysis, stronger governance was associated with fewer of these IAS. We elucidate how the quality of governance within a country has implications for trade, tourism, transport, legislation, and economic development, all of which influence the spread of IAS. While our findings support the common assumption that strengthening governance benefits conservation interventions in countries of smaller economy, we find that this effect is not universal. Stronger governance alone cannot adequately address the problem of IAS, and targeted action is required in relatively high-GDP countries in order to stem the influx of IAS associated with high volumes of trade.
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Directory of Open Access Journals (Sweden)
Ismael Martins Pereira
2014-01-01
Full Text Available We have modeled the ecological niche for 12 plant species belonging to the genus Davilla (Dilleniaceae which occur in the Atlantic Forest of Brazil. This group includes endemic species lianas threatened by extinction and is therefore a useful indicator for forest areas requiring conservation. The aims are to compare the distribution and richness of species within the protected areas, assessing the degree of protection and gap analysis of reserves for this group. We used the Maxent algorithm with environmental and occurrence data, and produced geographic distribution maps. The results show that high species richness occurs in forest and coastal forest of Espírito Santo to Bahia states. The endemic species comprise D. flexuosa, D. macrocarpa, D. flexuosa, D. grandifolia, and D. sessilifolia. In the Atlantic Forest of southeastern Brazil, the following endemic species occur: D. tintinnabulata and D. glaziovii, with this latter species being included in the “red list” due habitat loss and predatory extractivism. The indicators of species richness in the coastal region of Bahia correspond with floristic inventories that point to this area having a high biodiversity. Although this region has several protected areas, there are gaps in reserves, which, combined with anthropogenic threats and fragmentation, have caused several problems for biodiversity.
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Ewart, A; Popple, L W; Marshall, D C
2015-08-20
genera are morphologically similar, the calling songs, behaviour and habitats do distinguish them, at least as represented by these species documented. MaxEnt modeling of the species climatic envelope for the widely distributed species Simona erema suggests an association with summer-peak rainfall and diurnal temperature range. Modeling under estimated conditions of the Last Glacial Maximum (22 ky) suggests the possibility of an even more widespread distribution at that time.
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Geographic Distribution of Chagas Disease Vectors in Brazil Based on Ecological Niche Modeling
Directory of Open Access Journals (Sweden)
Rodrigo Gurgel-Gonçalves
2012-01-01
Full Text Available Although Brazil was declared free from Chagas disease transmission by the domestic vector Triatoma infestans, human acute cases are still being registered based on transmission by native triatomine species. For a better understanding of transmission risk, the geographic distribution of Brazilian triatomines was analyzed. Sixteen out of 62 Brazilian species that both occur in >20 municipalities and present synanthropic tendencies were modeled based on their ecological niches. Panstrongylus geniculatus and P. megistus showed broad ecological ranges, but most of the species sort out by the biome in which they are distributed: Rhodnius pictipes and R. robustus in the Amazon; R. neglectus, Triatoma sordida, and T. costalimai in the Cerrado; R. nasutus, P. lutzi, T. brasiliensis, T. pseudomaculata, T. melanocephala, and T. petrocchiae in the Caatinga; T. rubrovaria in the southern pampas; T. tibiamaculata and T. vitticeps in the Atlantic Forest. Although most occurrences were recorded in open areas (Cerrado and Caatinga, our results show that all environmental conditions in the country are favorable to one or more of the species analyzed, such that almost nowhere is Chagas transmission risk negligible.
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Directory of Open Access Journals (Sweden)
M. Saki
2013-03-01
Full Text Available The relationship between plant species and environmental factors has always been a central issue in plant ecology. With rising power of statistical techniques, geo-statistics and geographic information systems (GIS, the development of predictive habitat distribution models of organisms has rapidly increased in ecology. This study aimed to evaluate the ability of Logistic Regression Tree model to create potential habitat map of Astragalus verus. This species produces Tragacanth and has economic value. A stratified- random sampling was applied to 100 sites (50 presence- 50 absence of given species, and produced environmental and edaphic factors maps by using Kriging and Inverse Distance Weighting methods in the ArcGIS software for the whole study area. Relationships between species occurrence and environmental factors were determined by Logistic Regression Tree model and extended to the whole study area. The results indicated species occurrence has strong correlation with environmental factors such as mean daily temperature and clay, EC and organic carbon content of the soil. Species occurrence showed direct relationship with mean daily temperature and clay and organic carbon, and inverse relationship with EC. Model accuracy was evaluated both by Cohen’s kappa statistics (κ and by area under Receiver Operating Characteristics curve based on independent test data set. Their values (kappa=0.9, Auc of ROC=0.96 indicated the high power of LRT to create potential habitat map on local scales. This model, therefore, can be applied to recognize potential sites for rangeland reclamation projects.
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A maximum entropy model for predicting wild boar distribution in Spain
Directory of Open Access Journals (Sweden)
Jaime Bosch
2014-09-01
Full Text Available Wild boar (Sus scrofa populations in many areas of the Palearctic including the Iberian Peninsula have grown continuously over the last century. This increase has led to numerous different types of conflicts due to the damage these mammals can cause to agriculture, the problems they create in the conservation of natural areas, and the threat they pose to animal health. In the context of both wildlife management and the design of health programs for disease control, it is essential to know how wild boar are distributed on a large spatial scale. Given that the quantifying of the distribution of wild species using census techniques is virtually impossible in the case of large-scale studies, modeling techniques have thus to be used instead to estimate animals’ distributions, densities, and abundances. In this study, the potential distribution of wild boar in Spain was predicted by integrating data of presence and environmental variables into a MaxEnt approach. We built and tested models using 100 bootstrapped replicates. For each replicate or simulation, presence data was divided into two subsets that were used for model fitting (60% of the data and cross-validation (40% of the data. The final model was found to be accurate with an area under the receiver operating characteristic curve (AUC value of 0.79. Six explanatory variables for predicting wild boar distribution were identified on the basis of the percentage of their contribution to the model. The model exhibited a high degree of predictive accuracy, which has been confirmed by its agreement with satellite images and field surveys.
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Beck, PSA; Kalmbach, E; Joly, D; Stien, A; Nilsen, L
2005-01-01
Despite the intensive research effort directed at predicting the effects of climate change on plants in the Arctic, the impact of environmental change on species' distributions remains difficult to quantify. Predictive habitat distribution models provide a tool to predict the geographical
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Occurrence and distribution of Indian primates
Karanth, K.K.; Nichols, J.D.; Hines, J.E.
2010-01-01
Global and regional species conservation efforts are hindered by poor distribution data and range maps. Many Indian primates face extinction, but assessments of population status are hindered by lack of reliable distribution data. We estimated the current occurrence and distribution of 15 Indian primates by applying occupancy models to field data from a country-wide survey of local experts. We modeled species occurrence in relation to ecological and social covariates (protected areas, landscape characteristics, and human influences), which we believe are critical to determining species occurrence in India. We found evidence that protected areas positively influence occurrence of seven species and for some species are their only refuge. We found evergreen forests to be more critical for some primates along with temperate and deciduous forests. Elevation negatively influenced occurrence of three species. Lower human population density was positively associated with occurrence of five species, and higher cultural tolerance was positively associated with occurrence of three species. We find that 11 primates occupy less than 15% of the total land area of India. Vulnerable primates with restricted ranges are Golden langur, Arunachal macaque, Pig-tailed macaque, stump-tailed macaque, Phayre's leaf monkey, Nilgiri langur and Lion-tailed macaque. Only Hanuman langur and rhesus macaque are widely distributed. We find occupancy modeling to be useful in determining species ranges, and in agreement with current species ranking and IUCN status. In landscapes where monitoring efforts require optimizing cost, effort and time, we used ecological and social covariates to reliably estimate species occurrence and focus species conservation efforts. ?? Elsevier Ltd.
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Differences in Crossover Frequency and Distribution among Three Sibling Species of Drosophila
True, J. R.; Mercer, J. M.; Laurie, C. C.
1996-01-01
Comparisons of the genetic and cytogenetic maps of three sibling species of Drosophila reveal marked differences in the frequency and cumulative distribution of crossovers during meiosis. The maps for two of these species, Drosophila melanogaster and D. simulans, have previously been described, while this report presents new map data for D. mauritiana, obtained using a set of P element markers. A genetic map covering nearly the entire genome was constructed by estimating the recombination fra...
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Fate modeling of mercury species and fluxes estimation in an urban river
International Nuclear Information System (INIS)
Tong, Yindong; Zhang, Wei; Chen, Cen; Chen, Long; Wang, Wentao; Hu, Xindi; Wang, Huanhuan; Hu, Dan; Ou, Langbo; Wang, Xuejun; Wang, Qiguang
2014-01-01
The fate and transfer of mercury in urban river is an important environmental concern. In this study, QWASI (Quantitative Water–Air–Sediment Interaction) model was selected to estimate the levels of total mercury and three mercury species in water and sediment, and was used to quantify the fluxes of mercury at water/air and sediment/water interfaces of an urban river. The predicted mercury levels in water and sediments were closed to the measured values. Water inflow, re-suspension of sediment and diffusion from sediment to water are major input sources of mercury in water. The net mercury transfer flux from water to air was 0.16 ng/(m 2 h). At the sediment/water interface, a net total mercury transfer of 1.32 ng/(m 2 h) from water to sediment was seen. In addition to the existing dynamic flux chambers measurement, this model method could provide a new perspective to identify the distribution and transfer of mercury in the urban river. -- Highlights: • QWASI could be a good tool to quantify transfer and fate of mercury in environment. • Distribution and flux of mercury species in an urban river was modeled. • Mercury in water mainly came from water inflow, sediment re-suspension and diffusion. • Net mercury transfer from water to air and sediment were 0.16 and 1.32 ng/(m 2 h). -- Quantitative Water–Air–Sediment Interaction model was used to quantify the transfer and fate of mercury in an urban river
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Hanafi-Bojd, Ahmad Ali; Khoobdel, Mehdi; Soleimani-Ahmadi, Moussa; Azizi, Kourosh; Aghaei Afshar, Abbas; Jaberhashemi, Seyed Aghil; Fekri, Sajjad; Safari, Reza
2018-02-28
Cutaneous Leishmaniasis (CL) is one of the main neglected vector-borne diseases in the Middle East, including Iran. This study aimed to map the spatial distribution and species composition of sand flies in Hormozgan Province and to predict the best ecological niches for main CL vectors in this area. A database that included all earlier studies on sand flies in Hormozgan Province was established. Sand flies were also collected from some localities across the province. Prediction maps for main vectors were developed using MaxEnt model. A total of 27 sand fly species were reported from the study area. Phlebotomus papatasi Scopoli, Phlebotomus sergenti s.l. Parrot, Phlebotomus alexandri Sinton, Sergentomyia sintoni Pringle, Sergentomyia clydei Sinton, Sergentomyia tiberiadis Adler, and Sergentomyia baghdadis Adler (Diptera: Psychodidae) had the widest distribution range. The probability of their presence as the main vectors of CL was calculated to be 0.0003-0.9410 and 0.0031-0.8880 for P. papatasi and P. sergenti s.l., respectively. The best ecological niches for P. papatasi were found in the central south, southeast, and a narrow area in southwest, whereas central south to northern area had better niches for P. sergenti s.l. The endemic areas are in Bandar-e Jask, where transmission occurs, whereas in Bastak, the cases were imported from endemic foci of Fars province. In conclusion, proven and suspected vectors of CL and VL were recorded in this study. Due to the existence of endemic foci of CL, and favorite ecological niches for its vectors, there is potential risk of emerging CL in new areas.
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Directory of Open Access Journals (Sweden)
Alessandro Prantoni
2017-12-01
Full Text Available A checklist of all currently accepted species of Grania Southern, 1913 (Annelida, Clitellata, Enchytraeidae is presented. The genus is widespread over the world and comprises 81 species described to date. Remarks on their geographical distribution, habitat, synonymies and museum catalogue numbers are provided.
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Morphometry and Distribution of Senecio Nemorensis agg. Species (Asteraceae in Poland
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Rola Kaja
2014-07-01
Full Text Available A morphometric analysis based on 316 herbarium specimens of Senecio nemorensis agg. indicated the occurrence of the following four species in Poland: S. germanicus Wallr., S. hercynicus Herborg, S. ovatus (G. Gaertn. et al. Willd. and S. ucranicus Hodálová. Principal component analysis (PCA, analysis of variance (ANOVA/Kruskal-Wallis test and canonical discriminant analysis (CDA were applied. Quantitative characters such as supplementary bract length, leaf base width, ligule length and the supplementary/involucral bract length ratio clearly discriminated taxa within S. nemorensis agg. Included is a distribution map of the investigated species based on the examined material, with particular emphasis on the course of the northeastern boundary of S. hercynicus and the northwestern boundary of S. ucranicus. Also given is a determination key for species within S. nemorensis agg. in Poland, together with morphological descriptions of particular species
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Present and potential distribution of Snub-nosed Monkey
DEFF Research Database (Denmark)
Nüchel, Jonas; Bøcher, Peder Klith; Svenning, Jens-Christian
are the Snub-nosed Monkeys (Rhinopithecus), a temperate-subtropical East Asian genus. We use species distribution modeling to assess the following question of key relevancy for conservation management of Rhinopithecus; 1. Which climatic factors determine the present distribution of Rhinopithecus within...... distribution of Rhinopithecus within the region, considering climate, habitat availability and the locations of nature reserves. Keywords: biodiversity, biogeography, conservation, China, snub-nosed monkey, rhinopithecus, primates, species distribution modeling...
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Directory of Open Access Journals (Sweden)
Marija Ivković
2017-12-01
Full Text Available All records of aquatic dance flies (37 species in subfamily Clinocerinae and 10 species in subfamily Hemerodromiinae from the territory of Greece are summarized, including previously unpublished data and data on five newly described species (Chelifera horvati Ivković & Sinclair, sp. n., Wiedemannia iphigeniae Ivković & Sinclair, sp. n., W. ljerkae Ivković & Sinclair, sp. n., W. nebulosa Ivković & Sinclair, sp. n. and W. pseudoberthelemyi Ivković & Sinclair, sp. n.. The new species are described and illustrated, the male terminalia of Clinocera megalatlantica (Vaillant are illustrated and the distributions of all species within Greece are listed. The aquatic Empididae fauna of Greece consists of 47 species, with the following described species reported for the first time: Chelifera angusta Collin, Hemerodromia melangyna Collin, Clinocera megalatlantica, Kowarzia plectrum (Mik, Phaeobalia dimidiata (Loew, W. (Chamaedipsia beckeri (Mik, W. (Philolutra angelieri Vaillant and W. (P. chvali Joost. A key to species of aquatic Empididae of Greece is provided for the first time. Information related to the European Ecoregions in which species were found is given. Compared to the other studied countries in the Balkans, the Greek species assemblage is most similar to that of the Former Yugoslav Republic of Macedonia.
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Directory of Open Access Journals (Sweden)
E. J. OLAYA-MARIN
2015-03-01
Full Text Available Luciobarbus guiraonis (Eastern Iberian barbel is an endemic fish species restricted to Spain, mainly distributed in the Júcar River Basin District. Its study is important because there is little knowledge about its biology and ecology. To improve the knowledge about the species distribution and habitat requirements, nonlinear modelling was carried out to predict the presence/absence and density of the Eastern Iberian barbel, based on 155 sampling sites distributed throughout the Júcar River Basin District (Eastern Iberian Peninsula. We used multilayer feed-forward artificial neural networks (ANN to represent nonlinear relationships between L. guiraonis descriptors and variables regarding the physical habitat and biological components (macroinvertebrates, fish, riparian forest. The gradient descent algorithm was implemented to find the optimal model parameters; the importance of the ANN’s input variables was determined by the partial derivatives method. The predictive power of the model was evaluated with the Cohen’s kappa (k, the correctly classified instances (CCI, and the area under the curve (AUC of the receiver operator characteristic (ROC plots. The best model predicted presence/absence with a high performance (k= 0.66, CCI= 87% and AUC= 0.85; the prediction of density was moderate (CCI = 62%, AUC=0.71 and k= 0.43. The fundamental variables describing the presence/absence were; solar radiation (the highest contribution was observed between 2000 and 4200 WH/m2, drainage area (with the strongest influence between 3000 and 5.000 km2, and the proportion of exotic fish species (with relevant contribution between 50 and 100%. In the density model, the most important variables were the coefficient of variation of mean annual flows (relative importance of 50.5% and the proportion of exotic fish species (24.4%. The models provide important information about the relation of L. guiraonis with biotic and abiotic variables, this new knowledge can
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Real-time modeling of heat distributions
Hamann, Hendrik F.; Li, Hongfei; Yarlanki, Srinivas
2018-01-02
Techniques for real-time modeling temperature distributions based on streaming sensor data are provided. In one aspect, a method for creating a three-dimensional temperature distribution model for a room having a floor and a ceiling is provided. The method includes the following steps. A ceiling temperature distribution in the room is determined. A floor temperature distribution in the room is determined. An interpolation between the ceiling temperature distribution and the floor temperature distribution is used to obtain the three-dimensional temperature distribution model for the room.
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Directory of Open Access Journals (Sweden)
Alessandro Balestrieri
Full Text Available In recent years, the "forest-specialist" pine marten Martes martes has been reported to also occur also in largely fragmented, lowland landscapes of north-western Italy. The colonization of such an apparently unsuitable area provided the opportunity for investigating pine marten ecological requirements and predicting its potential south- and eastwards expansion. We collected available pine marten occurrence data in the flood plain of the River Po (N Italy and relate them to 11 environmental variables by developing nine Species Distribution Models. To account for inter-model variability we used average ensemble predictions (EP. EP predicted a total of 482 suitable patches (8.31% of the total study area for the pine marten. The main factors driving pine marten occurrence in the western River Po plain were the distance from watercourses and the distance from woods. EP suggested that the pine marten may further expand in the western lowland, whilst the negligible residual wood cover of large areas in the central and eastern plain makes the habitat unsuitable for the pine marten, except for some riparian corridors and the pine wood patches bordering the Adriatic coast. Based on our results, conservation strategies should seek to preserve remnant forest patches and enhance the functional connectivity provided by riparian corridors.
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Distribution and diversity of fungal species in and adjacent to the Los Alamos National Laboratory
Energy Technology Data Exchange (ETDEWEB)
Balice, R.G.; Jarmie, N.; Rogers, F.J.
1997-12-01
Fungi have demonstrated their ability to diversify and specialize to take advantage of new environments (Murphy 1996). These species are essential to the normal functioning of ecosystems and the impacts of human activities may be harmful to fungi. There is a need to inventory fungi throughout the range of their environments. Previously archived information representing 43 sample locations was used to perform a preliminary evaluation of the distributions and diversity of fungal species at the Los Alamos National Laboratory and in adjacent environments. Presence-absence data for 71 species of fungi in five habitats, pinon-juniper, canyon-bottom ponderosa pine, ponderosa pine, canyon-bottom mixed conifer, and mixed conifer were analyzed. The results indicate that even though fungi occur in each of the habitats, fungal species are not distributed evenly among these habitats. The richness of fungal species is greater in the canyon-bottom mixed conifer and mixed conifer habitats than in the pinon-juniper, canyon-bottom ponderosa pine or ponderosa pine habitats. All but three of the fungal species were recorded in either the canyon-bottom mixed conifer or the mixed conifer habitats, and all but seven of the fungal species were found in the mixed conifer habitat.
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Distribution and diversity of fungal species in and adjacent to the Los Alamos National Laboratory
International Nuclear Information System (INIS)
Balice, R.G.; Jarmie, N.; Rogers, F.J.
1997-12-01
Fungi have demonstrated their ability to diversify and specialize to take advantage of new environments (Murphy 1996). These species are essential to the normal functioning of ecosystems and the impacts of human activities may be harmful to fungi. There is a need to inventory fungi throughout the range of their environments. Previously archived information representing 43 sample locations was used to perform a preliminary evaluation of the distributions and diversity of fungal species at the Los Alamos National Laboratory and in adjacent environments. Presence-absence data for 71 species of fungi in five habitats, pinon-juniper, canyon-bottom ponderosa pine, ponderosa pine, canyon-bottom mixed conifer, and mixed conifer were analyzed. The results indicate that even though fungi occur in each of the habitats, fungal species are not distributed evenly among these habitats. The richness of fungal species is greater in the canyon-bottom mixed conifer and mixed conifer habitats than in the pinon-juniper, canyon-bottom ponderosa pine or ponderosa pine habitats. All but three of the fungal species were recorded in either the canyon-bottom mixed conifer or the mixed conifer habitats, and all but seven of the fungal species were found in the mixed conifer habitat
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C. H. Flather; M. S Knowles; C. H. Sieg
2011-01-01
This indicator provides information on the number and distribution of forest-associated species at risk of losing genetic variation across their geographic range. Comparing a species' current geographic distribution with its historic distribution is the basis for identifying those species whose range has contracted significantly. Human activities are accelerating...
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Ma, Fei; Na, Xiaofan; Xu, Tingting
2016-05-01
Drought is a major environmental constraint affecting growth and distribution of plants in the desert region of the Inner Mongolia plateau. Caragana microphylla, C. liouana, and C. korshinskii are phylogenetically close but distribute vicariously in Mongolia plateau. To gain a better understanding of the ecological differentiation between these three species, we examined the leaf gas exchange, growth, water use efficiency, biomass accumulation and allocation by subjecting their seedlings to low and high drought treatments in a glasshouse. Increasing drought stress had a significant effect on many aspects of seedling performance in all species, but the physiology and growth varied with species in response to drought. C. korshinskii exhibited lower sensitivity of photosynthetic rate and growth, lower specific leaf area, higher biomass allocation to roots, higher levels of water use efficiency to drought compared with the other two species. Only minor interspecific differences in growth performances were observed between C. liouana and C. microphylla. These results indicated that faster seedling growth rate and more efficient water use of C. korshinskii should confer increased drought tolerance and facilitate its establishment in more severe drought regions relative to C. liouana and C. microphylla.
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Warwick-Evans, Victoria C; Atkinson, Philip W; Robinson, Leonie A; Green, Jonathan A
2016-01-01
During the breeding season seabirds are constrained to coastal areas and are restricted in their movements, spending much of their time in near-shore waters either loafing or foraging. However, in using these areas they may be threatened by anthropogenic activities such as fishing, watersports and coastal developments including marine renewable energy installations. Although many studies describe large scale interactions between seabirds and the environment, the drivers behind near-shore, fine-scale distributions are not well understood. For example, Alderney is an important breeding ground for many species of seabird and has a diversity of human uses of the marine environment, thus providing an ideal location to investigate the near-shore fine-scale interactions between seabirds and the environment. We used vantage point observations of seabird distribution, collected during the 2013 breeding season in order to identify and quantify some of the environmental variables affecting the near-shore, fine-scale distribution of seabirds in Alderney's coastal waters. We validate the models with observation data collected in 2014 and show that water depth, distance to the intertidal zone, and distance to the nearest seabird nest are key predictors in the distribution of Alderney's seabirds. AUC values for each species suggest that these models perform well, although the model for shags performed better than those for auks and gulls. While further unexplained underlying localised variation in the environmental conditions will undoubtedly effect the fine-scale distribution of seabirds in near-shore waters we demonstrate the potential of this approach in marine planning and decision making.