WorldWideScience

Sample records for modelling species distribution

  1. Hierarchical species distribution models

    Science.gov (United States)

    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.

  2. Bounding species distribution models

    Directory of Open Access Journals (Sweden)

    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].

  3. Bounding Species Distribution Models

    Science.gov (United States)

    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].

  4. Species Distribution Modelling

    DEFF Research Database (Denmark)

    Gomes, Vitor H. F.; Ijff, Stephanie D.; Raes, Niels

    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 SD...

  5. New trends in species distribution modelling

    Science.gov (United States)

    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.

  6. Finessing atlas data for species distribution models

    NARCIS (Netherlands)

    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

  7. Applications of species distribution modeling to paleobiology

    DEFF Research Database (Denmark)

    Svenning, Jens-Christian; Fløjgaard, Camilla; Marske, Katharine Ann

    2011-01-01

    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...... the role of Pleistocene glacial refugia in biogeography and evolution, especially in Europe, but also in many other regions. SDM-based approaches are also beginning to contribute to a suite of other research questions, such as historical constraints on current distributions and diversity patterns, the end...

  8. How can model comparison help improving species distribution models?

    Directory of Open Access Journals (Sweden)

    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.

  9. Challenges and perspectives for species distribution modelling in the neotropics

    OpenAIRE

    Kamino, Luciana H. Y.; Stehmann, João Renato; Amaral, Silvana; De Marco, Paulo; Rangel, Thiago F.; de Siqueira, Marinez F.; De Giovanni, Renato; Hortal, Joaquín

    2011-01-01

    The workshop ‘Species distribution models: applications, challenges and perspectives’ held at Belo Horizonte (Brazil), 29–30 August 2011, aimed to review the state-of-the-art in species distribution modelling (SDM) in the neotropical realm. It brought together researchers in ecology, evolution, biogeography and conservation, with different backgrounds and research interests. The application of SDM in the megadiverse neotropics—where data on species occurrences are scarce—presents several chal...

  10. Species distribution modelling for plant communities: Stacked single species or multivariate modelling approaches?

    Science.gov (United States)

    Emilie B. Henderson; Janet L. Ohmann; Matthew J. Gregory; Heather M. Roberts; Harold S.J. Zald

    2014-01-01

    Landscape management and conservation planning require maps of vegetation composition and structure over large regions. Species distribution models (SDMs) are often used for individual species, but projects mapping multiple species are rarer. We compare maps of plant community composition assembled by stacking results from many SDMs with multivariate maps constructed...

  11. Comparing the performance of species distribution models of

    NARCIS (Netherlands)

    Valle , M.; van Katwijk, M.M.; de Jong, D.J.; Bouma, T.; Schipper, A.M.; Chust, G.; Benito, B.M.; Garmendia, J.M.; Borja, A.

    2013-01-01

    Intertidal seagrasses show high variability in their extent and location, with local extinctions and (re-)colonizations being inherent in their population dynamics. Suitable habitats are identified usually using Species Distribution Models (SDM), based upon the overall distribution of the species;

  12. Reserve selection using nonlinear species distribution models.

    Science.gov (United States)

    Moilanen, Atte

    2005-06-01

    Reserve design is concerned with optimal selection of sites for new conservation areas. Spatial reserve design explicitly considers the spatial pattern of the proposed reserve network and the effects of that pattern on reserve cost and/or ability to maintain species there. The vast majority of reserve selection formulations have assumed a linear problem structure, which effectively means that the biological value of a potential reserve site does not depend on the pattern of selected cells. However, spatial population dynamics and autocorrelation cause the biological values of neighboring sites to be interdependent. Habitat degradation may have indirect negative effects on biodiversity in areas neighboring the degraded site as a result of, for example, negative edge effects or lower permeability for animal movement. In this study, I present a formulation and a spatial optimization algorithm for nonlinear reserve selection problems in grid-based landscapes that accounts for interdependent site values. The method is demonstrated using habitat maps and nonlinear habitat models for threatened birds in the Netherlands, and it is shown that near-optimal solutions are found for regions consisting of up to hundreds of thousands grid cells, a landscape size much larger than those commonly attempted even with linear reserve selection formulations.

  13. A simple model for skewed species-lifetime distributions

    KAUST Repository

    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.

  14. Do Stacked Species Distribution Models Reflect Altitudinal Diversity Patterns?

    Science.gov (United States)

    Mateo, Rubén G.; Felicísimo, Ángel M.; Pottier, Julien; Guisan, Antoine; Muñoz, Jesús

    2012-01-01

    The objective of this study was to evaluate the performance of stacked species distribution models in predicting the alpha and gamma species diversity patterns of two important plant clades along elevation in the Andes. We modelled the distribution of the species in the Anthurium genus (53 species) and the Bromeliaceae family (89 species) using six modelling techniques. We combined all of the predictions for the same species in ensemble models based on two different criteria: the average of the rescaled predictions by all techniques and the average of the best techniques. The rescaled predictions were then reclassified into binary predictions (presence/absence). By stacking either the original predictions or binary predictions for both ensemble procedures, we obtained four different species richness models per taxa. The gamma and alpha diversity per elevation band (500 m) was also computed. To evaluate the prediction abilities for the four predictions of species richness and gamma diversity, the models were compared with the real data along an elevation gradient that was independently compiled by specialists. Finally, we also tested whether our richness models performed better than a null model of altitudinal changes of diversity based on the literature. Stacking of the ensemble prediction of the individual species models generated richness models that proved to be well correlated with the observed alpha diversity richness patterns along elevation and with the gamma diversity derived from the literature. Overall, these models tend to overpredict species richness. The use of the ensemble predictions from the species models built with different techniques seems very promising for modelling of species assemblages. Stacking of the binary models reduced the over-prediction, although more research is needed. The randomisation test proved to be a promising method for testing the performance of the stacked models, but other implementations may still be developed. PMID

  15. 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...... contribution; and (5) improved model evaluation. The challenges discussed in this essay do not preclude the need for developments of other areas of research in this field. However, they are critical for allowing the science of species distribution modelling to move forward.......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...

  16. Where is positional uncertainty a problem for species distribution modelling?

    NARCIS (Netherlands)

    Naimi, N.; Hamm, N.A.S.; Groen, T.A.; Skidmore, A.K.; Toxopeus, A.G.

    2014-01-01

    Species data held in museum and herbaria, survey data and opportunistically observed data are a substantial information resource. A key challenge in using these data is the uncertainty about where an observation is located. This is important when the data are used for species distribution modelling

  17. Can fire atlas data improve species distribution model projections?

    Science.gov (United States)

    Crimmins, Shawn M; Dobrowski, Solomon Z; Mynsberge, Alison R; Safford, Hugh D

    2014-07-01

    Correlative species distribution models (SDMs) are widely used in studies of climate change impacts, yet are often criticized for failing to incorporate disturbance processes that can influence species distributions. Here we use two temporally independent data sets of vascular plant distributions, climate data, and fire atlas data to examine the influence of disturbance history on SDM projection accuracy through time in the mountain ranges of California, USA. We used hierarchical partitioning to examine the influence of fire occurrence on the distribution of 144 vascular plant species and built a suite of SDMs to examine how the inclusion of fire-related predictors (fire occurrence and departure from historical fire return intervals) affects SDM projection accuracy. Fire occurrence provided the least explanatory power among predictor variables for predicting species' distributions, but provided improved explanatory power for species whose regeneration is tied closely to fire. A measure of the departure from historic fire return interval had greater explanatory power for calibrating modern SDMs than fire occurrence. This variable did not improve internal model accuracy for most species, although it did provide marginal improvement to models for species adapted to high-frequency fire regimes. Fire occurrence and fire return interval departure were strongly related to the climatic covariates used in SDM development, suggesting that improvements in model accuracy may not be expected due to limited additional explanatory power. Our results suggest that the inclusion of coarse-scale measures of disturbance in SDMs may not be necessary to predict species distributions under climate change, particularly for disturbance processes that are largely mediated by climate.

  18. Species distribution models of tropical deep-sea snappers.

    Directory of Open Access Journals (Sweden)

    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

  19. A Species Distribution Modeling Informed Conservation Assessment of Bog Spicebush

    Science.gov (United States)

    2016-09-14

    ERDC develops innovative solutions in civil and military engineering, geospatial sciences, water resources, and environmental sciences for the Army...Natural Resources Program. This work was conducted by the Ecological Processes Branch (CNN), In- stallations Division (CN), Construction Engineering...declining number of Bog Spicebush populations, as well as limited information about the species’ ecology , indicate species distribution modeling would

  20. 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

    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......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...

  1. Challenges and perspectives for species distribution modelling in the neotropics

    Science.gov (United States)

    Kamino, Luciana H. Y.; Stehmann, João Renato; Amaral, Silvana; De Marco, Paulo; Rangel, Thiago F.; de Siqueira, Marinez F.; De Giovanni, Renato; Hortal, Joaquín

    2012-01-01

    The workshop ‘Species distribution models: applications, challenges and perspectives’ held at Belo Horizonte (Brazil), 29–30 August 2011, aimed to review the state-of-the-art in species distribution modelling (SDM) in the neotropical realm. It brought together researchers in ecology, evolution, biogeography and conservation, with different backgrounds and research interests. The application of SDM in the megadiverse neotropics—where data on species occurrences are scarce—presents several challenges, involving acknowledging the limitations imposed by data quality, including surveys as an integral part of SDM studies, and designing the analyses in accordance with the question investigated. Specific solutions were discussed, and a code of good practice in SDM studies and related field surveys was drafted. PMID:22031720

  2. Considerations for building climate-based species distribution models

    Science.gov (United States)

    Bucklin, David N.; Basille, Mathieu; Romañach, Stephanie; Brandt, Laura A.; Mazzotti, Frank J.; Watling, James I.

    2016-01-01

    Climate plays an important role in the distribution of species. A given species may adjust to new conditions in-place, move to new areas with suitable climates, or go extinct. Scientists and conservation practitioners use mathematical models to predict the effects of future climate change on wildlife and plan for a biodiverse future. This 8-page fact sheet written by David N. Bucklin, Mathieu Basille, Stephanie S. Romañach, Laura A. Brandt, Frank J. Mazzotti, and James I. Watling and published by the Department of Wildlife Ecology and Conservation explains how, with a better understanding of species distribution models, we can predict how species may respond to climate change. The models alone cannot tell us how a certain species will actually respond to changes in climate, but they can inform conservation planning that aims to allow species to both adapt in place and (for those that are able to) move to newly suitable areas. Such planning will likely minimize loss of biodiversity due to climate change.

  3. The predictive performance and stability of six species distribution models.

    Science.gov (United States)

    Duan, Ren-Yan; Kong, Xiao-Quan; Huang, Min-Yi; Fan, Wei-Yi; Wang, Zhi-Gao

    2014-01-01

    Predicting species' potential geographical range by species distribution models (SDMs) is central to understand their ecological requirements. However, the effects of using different modeling techniques need further investigation. In order to improve the prediction effect, we need to assess the predictive performance and stability of different SDMs. We collected the distribution data of five common tree species (Pinus massoniana, Betula platyphylla, Quercus wutaishanica, Quercus mongolica and Quercus variabilis) and simulated their potential distribution area using 13 environmental variables and six widely used SDMs: BIOCLIM, DOMAIN, MAHAL, RF, MAXENT, and SVM. Each model run was repeated 100 times (trials). We compared the predictive performance by testing the consistency between observations and simulated distributions and assessed the stability by the standard deviation, coefficient of variation, and the 99% confidence interval of Kappa and AUC values. The mean values of AUC and Kappa from MAHAL, RF, MAXENT, and SVM trials were similar and significantly higher than those from BIOCLIM and DOMAIN trials (pSDMs (MAHAL, RF, MAXENT, and SVM) had higher prediction accuracy, smaller confidence intervals, and were more stable and less affected by the random variable (randomly selected pseudo-absence points). According to the prediction performance and stability of SDMs, we can divide these six SDMs into two categories: a high performance and stability group including MAHAL, RF, MAXENT, and SVM, and a low performance and stability group consisting of BIOCLIM, and DOMAIN. We highlight that choosing appropriate SDMs to address a specific problem is an important part of the modeling process.

  4. Niche variability and its consequences for species distribution modeling.

    Science.gov (United States)

    Michel, Matt J; Knouft, Jason H

    2012-01-01

    When species distribution models (SDMs) are used to predict how a species will respond to environmental change, an important assumption is that the environmental niche of the species is conserved over evolutionary time-scales. Empirical studies conducted at ecological time-scales, however, demonstrate that the niche of some species can vary in response to environmental change. We use habitat and locality data of five species of stream fishes collected across seasons to examine the effects of niche variability on the accuracy of projections from Maxent, a popular SDM. We then compare these predictions to those from an alternate method of creating SDM projections in which a transformation of the environmental data to similar scales is applied. The niche of each species varied to some degree in response to seasonal variation in environmental variables, with most species shifting habitat use in response to changes in canopy cover or flow rate. SDMs constructed from the original environmental data accurately predicted the occurrences of one species across all seasons and a subset of seasons for two other species. A similar result was found for SDMs constructed from the transformed environmental data. However, the transformed SDMs produced better models in ten of the 14 total SDMs, as judged by ratios of mean probability values at known presences to mean probability values at all other locations. Niche variability should be an important consideration when using SDMs to predict future distributions of species because of its prevalence among natural populations. The framework we present here may potentially improve these predictions by accounting for such variability.

  5. Niche variability and its consequences for species distribution modeling.

    Directory of Open Access Journals (Sweden)

    Matt J Michel

    Full Text Available When species distribution models (SDMs are used to predict how a species will respond to environmental change, an important assumption is that the environmental niche of the species is conserved over evolutionary time-scales. Empirical studies conducted at ecological time-scales, however, demonstrate that the niche of some species can vary in response to environmental change. We use habitat and locality data of five species of stream fishes collected across seasons to examine the effects of niche variability on the accuracy of projections from Maxent, a popular SDM. We then compare these predictions to those from an alternate method of creating SDM projections in which a transformation of the environmental data to similar scales is applied. The niche of each species varied to some degree in response to seasonal variation in environmental variables, with most species shifting habitat use in response to changes in canopy cover or flow rate. SDMs constructed from the original environmental data accurately predicted the occurrences of one species across all seasons and a subset of seasons for two other species. A similar result was found for SDMs constructed from the transformed environmental data. However, the transformed SDMs produced better models in ten of the 14 total SDMs, as judged by ratios of mean probability values at known presences to mean probability values at all other locations. Niche variability should be an important consideration when using SDMs to predict future distributions of species because of its prevalence among natural populations. The framework we present here may potentially improve these predictions by accounting for such variability.

  6. Integrating species distribution models (SDMs) and phylogeography for two species of Alpine Primula.

    Science.gov (United States)

    Schorr, G; Holstein, N; Pearman, P B; Guisan, A; Kadereit, J W

    2012-06-01

    The major intention of the present study was to investigate whether an approach combining the use of niche-based palaeodistribution modeling and phylo-geography would support or modify hypotheses about the Quaternary distributional history derived from phylogeographic methods alone. Our study system comprised two closely related species of Alpine Primula. We used species distribution models based on the extant distribution of the species and last glacial maximum (LGM) climate models to predict the distribution of the two species during the LGM. Phylogeographic data were generated using amplified fragment length polymorphisms (AFLPs). In Primula hirsuta, models of past distribution and phylogeographic data are partly congruent and support the hypothesis of widespread nunatak survival in the Central Alps. Species distribution models (SDMs) allowed us to differentiate between alpine regions that harbor potential nunatak areas and regions that have been colonized from other areas. SDMs revealed that diversity is a good indicator for nunataks, while rarity is a good indicator for peripheral relict populations that were not source for the recolonization of the inner Alps. In P. daonensis, palaeo-distribution models and phylogeographic data are incongruent. Besides the uncertainty inherent to this type of modeling approach (e.g., relatively coarse 1-km grain size), disagreement of models and data may partly be caused by shifts of ecological niche in both species. Nevertheless, we demonstrate that the combination of palaeo-distribution modeling with phylogeographical approaches provides a more differentiated picture of the distributional history of species and partly supports (P. hirsuta) and partly modifies (P. daonensis and P. hirsuta) hypotheses of Quaternary distributional history. Some of the refugial area indicated by palaeodistribution models could not have been identified with phylogeographic data.

  7. An extensive comparison of species-abundance distribution models.

    Science.gov (United States)

    Baldridge, Elita; Harris, David J; Xiao, Xiao; White, Ethan P

    2016-01-01

    A number of different models have been proposed as descriptions of the species-abundance distribution (SAD). Most evaluations of these models use only one or two models, focus on only a single ecosystem or taxonomic group, or fail to use appropriate statistical methods. We use likelihood and AIC to compare the fit of four of the most widely used models to data on over 16,000 communities from a diverse array of taxonomic groups and ecosystems. Across all datasets combined the log-series, Poisson lognormal, and negative binomial all yield similar overall fits to the data. Therefore, when correcting for differences in the number of parameters the log-series generally provides the best fit to data. Within individual datasets some other distributions performed nearly as well as the log-series even after correcting for the number of parameters. The Zipf distribution is generally a poor characterization of the SAD.

  8. An extensive comparison of species-abundance distribution models

    Directory of Open Access Journals (Sweden)

    Elita Baldridge

    2016-12-01

    Full Text Available A number of different models have been proposed as descriptions of the species-abundance distribution (SAD. Most evaluations of these models use only one or two models, focus on only a single ecosystem or taxonomic group, or fail to use appropriate statistical methods. We use likelihood and AIC to compare the fit of four of the most widely used models to data on over 16,000 communities from a diverse array of taxonomic groups and ecosystems. Across all datasets combined the log-series, Poisson lognormal, and negative binomial all yield similar overall fits to the data. Therefore, when correcting for differences in the number of parameters the log-series generally provides the best fit to data. Within individual datasets some other distributions performed nearly as well as the log-series even after correcting for the number of parameters. The Zipf distribution is generally a poor characterization of the SAD.

  9. Impacts of Species Misidentification on Species Distribution Modeling with Presence-Only Data

    Directory of Open Access Journals (Sweden)

    Hugo Costa

    2015-11-01

    Full Text Available Spatial records of species are commonly misidentified, which can change the predicted distribution of a species obtained from a species distribution model (SDM. Experiments were undertaken to predict the distribution of real and simulated species using MaxEnt and presence-only data “contaminated” with varying rates of misidentification error. Additionally, the difference between the niche of the target and contaminating species was varied. The results show that species misidentification errors may act to contract or expand the predicted distribution of a species while shifting the predicted distribution towards that of the contaminating species. Furthermore the magnitude of the effects was positively related to the ecological distance between the species’ niches and the size of the error rates. Critically, the magnitude of the effects was substantial even when using small error rates, smaller than common average rates reported in the literature, which may go unnoticed while using a standard evaluation method, such as the area under the receiver operating characteristic curve. Finally, the effects outlined were shown to impact negatively on practical applications that use SDMs to identify priority areas, commonly selected for various purposes such as management. The results highlight that species misidentification should not be neglected in species distribution modeling.

  10. 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

    by their geometrical properties. Tests involved analysis of models' ability to predict virtual species distributions in the same region and the same time as used for training the models, and to project distributions in different times under climate change. Of the eight species distribution models analyzed five (Random...

  11. Improving the assessment and reporting on rare and endangered species through species distribution models

    Directory of Open Access Journals (Sweden)

    Rita Sousa-Silva

    2014-12-01

    The objective was to highlight the potential of SDMs for the assessment of threatened species within the periodical report on their conservation status. We used a spatially explicit modeling approach, which predicts species distributions by spatially combining two SDMs: one fitted with climate data alone and the other fitted solely with landscape variables. A comparison between the modeled distribution and the range obtained by classical methods (minimum convex polygon and Range Tool is also presented. Our results show that while data-based approaches only consider the species known distribution, model-based methods allow a more complete evaluation of species distributions and their dynamics, as well as of the underlying pressures. This will ultimately improve the accuracy and usefulness of assessments in the context of EU reporting obligations.

  12. The role of biotic interactions in shaping distributions and realised assemblages of species: implications for species distribution modelling

    Science.gov (United States)

    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

    2013-01-01

    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 km2 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

  13. The predictive performance and stability of six species distribution models.

    Directory of Open Access Journals (Sweden)

    Ren-Yan Duan

    Full Text Available Predicting species' potential geographical range by species distribution models (SDMs is central to understand their ecological requirements. However, the effects of using different modeling techniques need further investigation. In order to improve the prediction effect, we need to assess the predictive performance and stability of different SDMs.We collected the distribution data of five common tree species (Pinus massoniana, Betula platyphylla, Quercus wutaishanica, Quercus mongolica and Quercus variabilis and simulated their potential distribution area using 13 environmental variables and six widely used SDMs: BIOCLIM, DOMAIN, MAHAL, RF, MAXENT, and SVM. Each model run was repeated 100 times (trials. We compared the predictive performance by testing the consistency between observations and simulated distributions and assessed the stability by the standard deviation, coefficient of variation, and the 99% confidence interval of Kappa and AUC values.The mean values of AUC and Kappa from MAHAL, RF, MAXENT, and SVM trials were similar and significantly higher than those from BIOCLIM and DOMAIN trials (p<0.05, while the associated standard deviations and coefficients of variation were larger for BIOCLIM and DOMAIN trials (p<0.05, and the 99% confidence intervals for AUC and Kappa values were narrower for MAHAL, RF, MAXENT, and SVM. Compared to BIOCLIM and DOMAIN, other SDMs (MAHAL, RF, MAXENT, and SVM had higher prediction accuracy, smaller confidence intervals, and were more stable and less affected by the random variable (randomly selected pseudo-absence points.According to the prediction performance and stability of SDMs, we can divide these six SDMs into two categories: a high performance and stability group including MAHAL, RF, MAXENT, and SVM, and a low performance and stability group consisting of BIOCLIM, and DOMAIN. We highlight that choosing appropriate SDMs to address a specific problem is an important part of the modeling process.

  14. Regional climate model downscaling may improve the prediction of alien plant species distributions

    Science.gov (United States)

    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.

  15. Species distribution modelling for conservation of an endangered endemic orchid.

    Science.gov (United States)

    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

  16. Modeled distributions of 12 tree species in New York

    Science.gov (United States)

    Rachel I. Riemann; Barry T. Wilson; Andrew J. Lister; Oren Cook; Sierra. Crane-Murdoch

    2014-01-01

    These maps depict the distribution of 12 tree species across the state of New York. The maps show where these trees do not occur (gray), occasionally occur (pale green), are a minor component (medium green), are a major component (dark green), or are the dominant species (black) in the forest, as determined by that species' total basal area. Basal area is the area...

  17. Past and present potential distribution of the Iberian Abies species: A phytogeographic approach using pollen data and species distribution models

    OpenAIRE

    López-Sáez, JA; Benito de Pando, B; Linares, JC; Nieto-Lugilde, D; López-Merino, L

    2010-01-01

    This is the accepted version of the following article: Alba-Sánchez, F., López-Sáez, J. A., Pando, B. B.-d., Linares, J. C., Nieto-Lugilde, D. and López-Merino, L. (2010), Past and present potential distribution of the Iberian Abies species: a phytogeographic approach using fossil pollen data and species distribution models. Diversity and Distributions, 16: 214–228, which has been published in final form at http://onlinelibrary.wiley.com/doi/10.1111/j.1472-4642.2010.00636.x/abstract. Aim -...

  18. The Combined Use of Correlative and Mechanistic Species Distribution Models Benefits Low Conservation Status Species.

    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

  19. Species-free species distribution models describe macroecological properties of protected area networks.

    Science.gov (United States)

    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

  20. On the dangers of model complexity without ecological justification in species distribution modeling

    Science.gov (United States)

    David M. Bell; Daniel R. Schlaepfer

    2016-01-01

    Although biogeographic patterns are the product of complex ecological processes, the increasing com-plexity of correlative species distribution models (SDMs) is not always motivated by ecological theory,but by model fit. The validity of model projections, such as shifts in a species’ climatic niche, becomesquestionable particularly during extrapolations, such as for...

  1. More than the sum of the parts: forest climate response from joint species distribution models

    Science.gov (United States)

    James S. Clark; Alan E. Gelfand; Christopher W. Woodall; Kai. Zhu

    2014-01-01

    The perceived threat of climate change is often evaluated from species distribution models that are fitted to many species independently and then added together. This approach ignores the fact that species are jointly distributed and limit one another. Species respond to the same underlying climatic variables, and the abundance of any one species can be constrained by...

  2. Likelihood analysis of species occurrence probability from presence-only data for modelling species distributions

    Science.gov (United States)

    Royle, J. Andrew; Chandler, Richard B.; Yackulic, Charles; Nichols, James D.

    2012-01-01

    1. Understanding the factors affecting species occurrence is a pre-eminent focus of applied ecological research. However, direct information about species occurrence is lacking for many species. Instead, researchers sometimes have to rely on so-called presence-only data (i.e. when no direct information about absences is available), which often results from opportunistic, unstructured sampling. MAXENT is a widely used software program designed to model and map species distribution using presence-only data. 2. We provide a critical review of MAXENT as applied to species distribution modelling and discuss how it can lead to inferential errors. A chief concern is that MAXENT produces a number of poorly defined indices that are not directly related to the actual parameter of interest – the probability of occurrence (ψ). This focus on an index was motivated by the belief that it is not possible to estimate ψ from presence-only data; however, we demonstrate that ψ is identifiable using conventional likelihood methods under the assumptions of random sampling and constant probability of species detection. 3. The model is implemented in a convenient r package which we use to apply the model to simulated data and data from the North American Breeding Bird Survey. We demonstrate that MAXENT produces extreme under-predictions when compared to estimates produced by logistic regression which uses the full (presence/absence) data set. We note that MAXENT predictions are extremely sensitive to specification of the background prevalence, which is not objectively estimated using the MAXENT method. 4. As with MAXENT, formal model-based inference requires a random sample of presence locations. Many presence-only data sets, such as those based on museum records and herbarium collections, may not satisfy this assumption. However, when sampling is random, we believe that inference should be based on formal methods that facilitate inference about interpretable ecological quantities

  3. Predicting the fate of biodiversity using species' distribution models: enhancing model comparability and repeatability.

    Directory of Open Access Journals (Sweden)

    Genoveva Rodríguez-Castañeda

    Full Text Available Species distribution modeling (SDM is an increasingly important tool to predict the geographic distribution of species. Even though many problems associated with this method have been highlighted and solutions have been proposed, little has been done to increase comparability among studies. We reviewed recent publications applying SDMs and found that seventy nine percent failed to report methods that ensure comparability among studies, such as disclosing the maximum probability range produced by the models and reporting on the number of species occurrences used. We modeled six species of Falco from northern Europe and demonstrate that model results are altered by (1 spatial bias in species' occurrence data, (2 differences in the geographic extent of the environmental data, and (3 the effects of transformation of model output to presence/absence data when applying thresholds. Depending on the modeling decisions, forecasts of the future geographic distribution of Falco ranged from range contraction in 80% of the species to no net loss in any species, with the best model predicting no net loss of habitat in Northern Europe. The fact that predictions of range changes in response to climate change in published studies may be influenced by decisions in the modeling process seriously hampers the possibility of making sound management recommendations. Thus, each of the decisions made in generating SDMs should be reported and evaluated to ensure conclusions and policies are based on the biology and ecology of the species being modeled.

  4. Distribution models and species discovery: the story of a new Solanum species from the Peruvian Andes

    Science.gov (United States)

    Särkinen, Tiina; Gonzáles, Paúl; Knapp, Sandra

    2013-01-01

    Abstract A new species of Solanum sect. Solanum from Peru is described here. Solanum pseudoamericanum Särkinen, Gonzáles & S.Knapp sp. nov. is a member of the Morelloid clade of Solanum, and is characterized by the combination of mostly forked inflorescences, flowers with small stamens 2.5 mm long including the filament, and strongly exerted styles with capitate stigmas. The species was first thought to be restricted to the seasonally dry tropical forests of southern Peru along the dry valleys of Río Pampas and Río Apurímac. Results from species distribution modelling (SDM) analysis with climatic predictors identified further potential suitable habitat areas in northern and central Peru. These areas were visited during field work in 2013. A total of 17 new populations across the predicted distribution were discovered using the model-based sampling method, and five further collections were identified amongst herbarium loans. Although still endemic to Peru, Solanum pseudoamericanum is now known from across northern, central and southern Peru. Our study demonstrates the usefulness of SDM for predicting new occurrences of rare plants, especially in the Andes where collection densities are still low in many areas and where many new species remain to be discovered. PMID:24399901

  5. Distribution models and species discovery: the story of a new Solanum species from the Peruvian Andes

    Directory of Open Access Journals (Sweden)

    Tiina Sarkinen

    2013-12-01

    Full Text Available A new species of Solanum sect. Solanum from Peru is described here. Solanum pseudoamericanum Särkinen, Gonzáles & S.Knapp sp. nov. is a member of the Morelloid clade of Solanum, and is characterized by the combination of mostly forked inflorescences, flowers with small stamens 2.5 mm long including the filament, and strongly exerted styles with capitate stigmas. The species was first thought to be restricted to the seasonally dry tropical forests of southern Peru along the dry valleys of Río Pampas and Río Apurímac. Results from species distribution modelling (SDM analysis with climatic predictors identified further potential suitable habitat areas in northern and central Peru. These areas were visited during field work in 2013. A total of 17 new populations across the predicted distribution were discovered using the model-based sampling method, and five further collections were identified amongst herbarium loans. Although still endemic to Peru, S. pseudoamericanum is now known from across northern, central and southern Peru. Our study demonstrates the usefulness of SDM for predicting new occurrences of rare plants, especially in the Andes where collection densities are still low in many areas and where many new species remain to be discovered.

  6. Can species distribution models really predict the expansion of invasive species?

    Science.gov (United States)

    Barbet-Massin, Morgane; Rome, Quentin; Villemant, Claire; Courchamp, Franck

    2018-01-01

    Predictive studies are of paramount importance for biological invasions, one of the biggest threats for biodiversity. To help and better prioritize management strategies, species distribution models (SDMs) are often used to predict the potential invasive range of introduced species. Yet, SDMs have been regularly criticized, due to several strong limitations, such as violating the equilibrium assumption during the invasion process. Unfortunately, validation studies-with independent data-are too scarce to assess the predictive accuracy of SDMs in invasion biology. Yet, biological invasions allow to test SDMs usefulness, by retrospectively assessing whether they would have accurately predicted the latest ranges of invasion. Here, we assess the predictive accuracy of SDMs in predicting the expansion of invasive species. We used temporal occurrence data for the Asian hornet Vespa velutina nigrithorax, a species native to China that is invading Europe with a very fast rate. Specifically, we compared occurrence data from the last stage of invasion (independent validation points) to the climate suitability distribution predicted from models calibrated with data from the early stage of invasion. Despite the invasive species not being at equilibrium yet, the predicted climate suitability of validation points was high. SDMs can thus adequately predict the spread of V. v. nigrithorax, which appears to be-at least partially-climatically driven. In the case of V. v. nigrithorax, SDMs predictive accuracy was slightly but significantly better when models were calibrated with invasive data only, excluding native data. Although more validation studies for other invasion cases are needed to generalize our results, our findings are an important step towards validating the use of SDMs in invasion biology.

  7. Adaptive invasive species distribution models: A framework for modeling incipient invasions

    Science.gov (United States)

    Uden, Daniel R.; Allen, Craig R.; Angeler, David G.; Corral, Lucia; Fricke, Kent A.

    2015-01-01

    The utilization of species distribution model(s) (SDM) for approximating, explaining, and predicting changes in species’ geographic locations is increasingly promoted for proactive ecological management. Although frameworks for modeling non-invasive species distributions are relatively well developed, their counterparts for invasive species—which may not be at equilibrium within recipient environments and often exhibit rapid transformations—are lacking. Additionally, adaptive ecological management strategies address the causes and effects of biological invasions and other complex issues in social-ecological systems. We conducted a review of biological invasions, species distribution models, and adaptive practices in ecological management, and developed a framework for adaptive, niche-based, invasive species distribution model (iSDM) development and utilization. This iterative, 10-step framework promotes consistency and transparency in iSDM development, allows for changes in invasive drivers and filters, integrates mechanistic and correlative modeling techniques, balances the avoidance of type 1 and type 2 errors in predictions, encourages the linking of monitoring and management actions, and facilitates incremental improvements in models and management across space, time, and institutional boundaries. These improvements are useful for advancing coordinated invasive species modeling, management and monitoring from local scales to the regional, continental and global scales at which biological invasions occur and harm native ecosystems and economies, as well as for anticipating and responding to biological invasions under continuing global change.

  8. BAYESIAN MODELS FOR SPECIES DISTRIBUTION MODELLING WITH ONLY-PRESENCE RECORDS

    Directory of Open Access Journals (Sweden)

    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

  9. Minimum required number of specimen records to develop accurate species distribution models

    NARCIS (Netherlands)

    Proosdij, van A.S.J.; Sosef, M.S.M.; Wieringa, J.J.; Raes, N.

    2016-01-01

    Species distribution models (SDMs) are widely used to predict the occurrence of species. Because SDMs generally use presence-only data, validation of the predicted distribution and assessing model accuracy is challenging. Model performance depends on both sample size and species’ prevalence, being

  10. Minimum required number of specimen records to develop accurate species distribution models

    NARCIS (Netherlands)

    Proosdij, van A.S.J.; Sosef, M.S.M.; Wieringa, Jan; Raes, N.

    2015-01-01

    Species Distribution Models (SDMs) are widely used to predict the occurrence of species. Because SDMs generally use presence-only data, validation of the predicted distribution and assessing model accuracy is challenging. Model performance depends on both sample size and species’ prevalence, being

  11. Current state of the art for statistical modeling of species distributions [Chapter 16

    Science.gov (United States)

    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)...

  12. Invasive Species Distribution Modeling (iSDM): Are absence data and dispersal constraints needed to predict actual distributions?

    Science.gov (United States)

    Tomáš Václavík; Ross K. Meentemeyer

    2009-01-01

    Species distribution models (SDMs) based on statistical relationships between occurrence data and underlying environmental conditions are increasingly used to predict spatial patterns of biological invasions and prioritize locations for early detection and control of invasion outbreaks. However, invasive species distribution models (iSDMs) face special challenges...

  13. Robustness and accuracy of Maxent niche modelling for Lactuca species distributions in light of collecting expeditions

    NARCIS (Netherlands)

    Cobben, M.M.P.; van Treuren, R.; Castañeda-Álvarez, N.P.; Khoury, C.K.; Kik, C.; van Hintum, T.J.L.

    2015-01-01

    Niche modelling software can be used to assess the probability of detecting a population of a plant species at a certain location. In this study, we used the distribution of the wild relatives of lettuce (Lactuca spp.) to investigate the applicability of Maxent species distribution models for

  14. SESAM – a new framework integrating macroecological and species distribution models for predicting spatio-temporal patterns of species assemblages

    DEFF Research Database (Denmark)

    Guisan, Antoine; Rahbek, Carsten

    2011-01-01

    , and ecological assembly rules to constrain predictions of the richness and composition of species assemblages obtained by stacking predictions of individual species distributions. We believe that such a framework could prove useful in many theoretical and applied disciplines of ecology and evolution, both......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...... with constituent species to approximate the properties of assemblages. Here, we propose to unify the two approaches in a single ‘spatially explicit species assemblage modelling’ (SESAM) framework. This framework uses relevant designations of initial species source pools for modelling, macroecological variables...

  15. Selection bias in species distribution models: An econometric approach on forest trees based on structural modeling

    Science.gov (United States)

    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

  16. Species Distribution Modelling: Contrasting presence-only models with plot abundance data

    NARCIS (Netherlands)

    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; de Leão Novo, E.M.M.; Vargas, Percy Núñez; Silva, Thiago Sanna Freire; Manzatto, Angelo Gilberto; Terborgh, John; Reis, Neidiane Farias Costa; Montero, Juan Carlos; Montero, Juan Carlos; Casula, Katia Regina; Marimon, Beatriz S.; Marimon, Ben Hur; Honorio Coronado, Euridice N.; 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; 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; Levis, Carolina; Schietti, Juliana; Souza, Priscila; Emilio, Thaise; Alonso, Alfonso; Neill, David; Dallmeier, Francisco; Ferreira, Leandro Valle; Araujo-Murakami, Alejandro; Praia, Daniel; Amaral, Do Dário Dantas; Carvalho, Fernanda Antunes; Souza, De Fernanda Coelho

    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.

  17. Lithologic data improve plant species distribution models based on coarse-grained occurrence data

    Energy Technology Data Exchange (ETDEWEB)

    Gaston, A.; Soriano, C.; Gomez-Miguel, V.

    2009-07-01

    The aim of this study was to assess the improvement of plant species distribution models based on coarse-grained occurrence data when adding lithologic data to climatic models. The distributions of 40 woody plant species from continental Spain were modelled. A logistic regression model with climatic predictors was fitted for each species and compared to a second model with climatic and lithologic predictors. Improvements on model likelihood and prediction accuracy on validation sub samples were assessed, as well as the effect of calcicole calcifuge habit on model improvement. Climatic models had reasonable mean prediction accuracy, but adding lithologic data improved model likelihood in most cases and increased mean prediction accuracy. Therefore, we recommend utilizing lithologic data for species distribution models based on coarse-grained occurrence data. Our data did not support the hypothesis that calcicole calcifuge habit may explain model improvement when adding lithologic data to climatic models, but further research is needed. (Author) 31 refs.

  18. Species Distribution Modelling: Contrasting presence-only models with plot abundance data.

    Science.gov (United States)

    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.

  19. Updating known distribution models for forecasting climate change impact on endangered species.

    Science.gov (United States)

    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.

  20. Do species distribution models predict species richness in urban and natural green spaces? A case study using amphibians

    Science.gov (United States)

    Urban green spaces are potentially important to biodiversity conservation because they represent habitat islands in a mosaic of development, and could harbor high biodiversity or provide connectivity to nearby habitat. Presence only species distribution models (SDMs) represent a ...

  1. 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

    that areas with a suitable LGM climate for the three temperate species (Apodemus flavicollis, Apodemus sylvaticus and Microtus arvalis) were largely restricted to the traditionally recognized southern refuge areas, i.e. mainly in the Mediterranean region, but also southernmost France and southern parts...... evidence. Our aim was to investigate the potential refuge locations using species distribution modelling to estimate the geographical distribution of suitable climatic conditions for selected rodent species during the LGM. Location Eurasia. Methods Presence/absence data for seven rodent species with range...... predictors of the species distributions across Siberia were projected onto LGM climate simulations to assess the distribution of climatically suitable areas. Results.The best distribution models provided good predictions of the present-day Siberian ranges of the study species. Their LGM projections showed...

  2. Dealing with noisy absences to optimize species distribution models: an iterative ensemble modelling approach.

    Directory of Open Access Journals (Sweden)

    Christine Lauzeral

    Full Text Available Species distribution models (SDMs are widespread in ecology and conservation biology, but their accuracy can be lowered by non-environmental (noisy absences that are common in species occurrence data. Here we propose an iterative ensemble modelling (IEM method to deal with noisy absences and hence improve the predictive reliability of ensemble modelling of species distributions. In the IEM approach, outputs of a classical ensemble model (EM were used to update the raw occurrence data. The revised data was then used as input for a new EM run. This process was iterated until the predictions stabilized. The outputs of the iterative method were compared to those of the classical EM using virtual species. The IEM process tended to converge rapidly. It increased the consensus between predictions provided by the different methods as well as between those provided by different learning data sets. Comparing IEM and EM showed that for high levels of non-environmental absences, iterations significantly increased prediction reliability measured by the Kappa and TSS indices, as well as the percentage of well-predicted sites. Compared to EM, IEM also reduced biases in estimates of species prevalence. Compared to the classical EM method, IEM improves the reliability of species predictions. It particularly deals with noisy absences that are replaced in the data matrices by simulated presences during the iterative modelling process. IEM thus constitutes a promising way to increase the accuracy of EM predictions of difficult-to-detect species, as well as of species that are not in equilibrium with their environment.

  3. VBORNET gap analysis: Mosquito vector distribution models utilised to identify areas of potential species distribution in areas lacking records.

    Directory of Open Access Journals (Sweden)

    Francis Schaffner

    2016-12-01

    Full Text Available This is the second of a number of planned data papers presenting modelled vector distributions produced originally during the ECDC funded VBORNET project. This work continues under the VectorNet project now jointly funded by ECDC and EFSA. Further data papers will be published after sampling seasons when more field data will become available allowing further species to be modelled or validation and updates to existing models.  The data package described here includes those mosquito species first modelled in 2013 & 2014 as part of the VBORNET gap analysis work which aimed to identify areas of potential species distribution in areas lacking records. It comprises three species models together with suitability masks based on land class and environmental limits. The species included as part of this phase are the mosquitoes 'Aedes vexans', 'Anopheles plumbeus' and 'Culex modestus'. The known distributions of these species within the area covered by the project (Europe, the ­Mediterranean Basin, North Africa, and Eurasia are currently incomplete to a greater or lesser degree. The models are designed to fill the gaps with predicted distributions, to provide a assistance in ­targeting surveys to collect distribution data for those areas with no field validated information, and b a first indication of the species distributions within the project areas.

  4. VBORNET Gap Analysis: Sand Fly Vector Distribution Models Utilised to Identify Areas of Potential Species Distribution in Areas Lacking Records

    Directory of Open Access Journals (Sweden)

    Bulent Alten

    2016-12-01

    Full Text Available This is the first of a number of planned data papers presenting modelled vector distributions, the models in this paper were produced during the ECDC funded VBORNET project. This work continues under the VectorNet project now jointly funded by ECDC and EFSA. This data paper contains the sand fly model outputs produced as part of the VBORNET project. Further data papers will be published after sampling seasons when more field data will become available allowing further species to be modelled or validation and updates to existing models. The data package described here includes those sand fly species first modelled in 2013 and 2014 as part of the VBORNET gap analysis work which aimed to identify areas of potential species distribution in areas lacking records. It comprises four species models together with suitability masks based on land class and environmental limits. The species included within this paper are 'Phlebotomus ariasi', 'Phlebotomus papatasi', 'Phlebotomus perniciosus' and 'Phlebotomus tobbi'. The known distributions of these species within the project area (Europe, the Mediterranean Basin, North Africa, and Eurasia are currently incomplete to a greater or lesser degree. The models are designed to fill the gaps with predicted distributions, to provide a assistance in targeting surveys to collect ­distribution data for those areas with no field validated information, and b a first indication of project wide distributions.

  5. Biotic modifiers, environmental modulation and species distribution models

    NARCIS (Netherlands)

    Linder, H. Peter; Bykova, Olga; Dyke, James; Etienne, Rampal S.; Hickler, Thomas; Kuehn, Ingolf; Marion, Glenn; Ohlemueller, Ralf; Schymanski, Stanislaus J.; Singer, Alexander

    2012-01-01

    The ability of species to modulate environmental conditions and resources has long been of interest. In the past three decades the impacts of these biotic modifiers have been investigated as ecosystem engineers, niche constructors, facilitators and keystone species. This environmental modulation can

  6. Effect of species rarity on the accuracy of species distribution models for reptiles and amphibians in southern California

    Science.gov (United States)

    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

  7. Androctonus genus species in arid regions: Ecological niche models, geographical distributions, and envenomation risk

    Directory of Open Access Journals (Sweden)

    Moulay Abdelmonaim El Hidan

    2018-03-01

    Full Text Available Aim: The objective of this study was to establish environmental factors related to scorpion species occurrence and their current potential geographic distributions in Morocco, to produce a current envenomation risk map and also to assess the human population at risk of envenomation. Materials and Methods: In this study, 71 georeferenced points for all scorpion species and nine environmental indicators were used to generate species distribution models in Maxent (maximum entropy modeling of species geographic distributions version 3.3.3k. 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 and envenomation risk maps were produced using the "ESRI® ArcGIS 10.2.2 for Desktop" software. Results: The models had high predictive success (AUC >0.95±0.025. Altitude, slope and five bioclimatic attributes were found to play a significant role in determining Androctonus scorpion species distribution. Ecological niche models (ENMs showed high concordance with the known distribution of the species. Produced risk map identified broad risk areas for Androctonus scorpion envenomation, extending along Marrakech-Tensift-Al Haouz, Souss-Massa-Draa, and some areas of Doukkala-Abda and Oriental regions. Conclusion: Considering these findings ENMs could be useful to afford important information on distributions of medically important scorpion species as well as producing scorpion envenomation risk maps.

  8. Past, present and future distributions of an Iberian Endemic, Lepus granatensis: ecological and evolutionary clues from species distribution models.

    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.

  9. 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...

  10. Species distribution models predict temporal but not spatial variation in forest growth

    NARCIS (Netherlands)

    Maaten, van der Ernest; Hamann, A.; Maaten-Theunissen, van der M.; Bergsma, A.R.; Hengeveld, G.M.; Lammeren, van R.J.A.; Mohren, G.M.J.; Nabuurs, G.J.; Terhürne, R.L.; Sterck, F.J.

    2017-01-01

    Bioclimate envelope models have been widely used to illustrate the discrepancy between current species distributions and their potential habitat under climate change. However, the realism and correct interpretation of such projections has been the subject of considerable discussion. Here, we

  11. Modeling the Distribution of Rare or Cryptic Bird Species of Taiwan

    Directory of Open Access Journals (Sweden)

    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.

  12. Species Distribution Modelling of Aedes aegypti in two dengue-endemic regions of Pakistan.

    Science.gov (United States)

    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.

  13. Modeling species distribution and change using random forest [Chapter 8

    Science.gov (United States)

    Jeffrey S. Evans; Melanie A. Murphy; Zachary A. Holden; Samuel A. Cushman

    2011-01-01

    Although inference is a critical component in ecological modeling, the balance between accurate predictions and inference is the ultimate goal in ecological studies (Peters 1991; De’ath 2007). Practical applications of ecology in conservation planning, ecosystem assessment, and bio-diversity are highly dependent on very accurate spatial predictions of...

  14. Predicting Environmental Suitability for a Rare and Threatened Species (Lao Newt, Laotriton laoensis) Using Validated Species Distribution Models

    Science.gov (United States)

    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

  15. Predicting environmental suitability for a rare and threatened species (Lao newt, Laotriton laoensis using validated species distribution models.

    Directory of Open Access Journals (Sweden)

    Amanda J Chunco

    Full Text Available 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.

  16. The importance of data quality for generating reliable distribution models for rare, elusive, and cryptic species

    Science.gov (United States)

    Keith B. Aubry; Catherine M. Raley; Kevin S. McKelvey

    2017-01-01

    The availability of spatially referenced environmental data and species occurrence records in online databases enable practitioners to easily generate species distribution models (SDMs) for a broad array of taxa. Such databases often include occurrence records of unknown reliability, yet little information is available on the influence of data quality on SDMs generated...

  17. Species distribution models for crop pollination: a modelling framework applied to Great Britain.

    Science.gov (United States)

    Polce, Chiara; Termansen, Mette; Aguirre-Gutiérrez, Jesus; Boatman, Nigel D; Budge, Giles E; Crowe, Andrew; Garratt, Michael P; Pietravalle, Stéphane; Potts, Simon G; Ramirez, Jorge A; Somerwill, Kate E; Biesmeijer, Jacobus C

    2013-01-01

    Insect pollination benefits over three quarters of the world's major crops. There is growing concern that observed declines in pollinators may impact on production and revenues from animal pollinated crops. Knowing the distribution of pollinators is therefore crucial for estimating their availability to pollinate crops; however, in general, we have an incomplete knowledge of where these pollinators occur. We propose a method to predict geographical patterns of pollination service to crops, novel in two elements: the use of pollinator records rather than expert knowledge to predict pollinator occurrence, and the inclusion of the managed pollinator supply. We integrated a maximum entropy species distribution model (SDM) with an existing pollination service model (PSM) to derive the availability of pollinators for crop pollination. We used nation-wide records of wild and managed pollinators (honey bees) as well as agricultural data from Great Britain. We first calibrated the SDM on a representative sample of bee and hoverfly crop pollinator species, evaluating the effects of different settings on model performance and on its capacity to identify the most important predictors. The importance of the different predictors was better resolved by SDM derived from simpler functions, with consistent results for bees and hoverflies. We then used the species distributions from the calibrated model to predict pollination service of wild and managed pollinators, using field beans as a test case. The PSM allowed us to spatially characterize the contribution of wild and managed pollinators and also identify areas potentially vulnerable to low pollination service provision, which can help direct local scale interventions. This approach can be extended to investigate geographical mismatches between crop pollination demand and the availability of pollinators, resulting from environmental change or policy scenarios.

  18. Species distribution models as a tool to estimate reproductive parameters: a case study with a passerine bird species.

    Science.gov (United States)

    Brambilla, Mattia; Ficetola, Gentile F

    2012-07-01

    1. Correlative species distribution models (SDMs) assess relationships between species distribution data and environmental features, to evaluate the environmental suitability (ES) of a given area for a species, by providing a measure of the probability of presence. If the output of SDMs represents the relationships between habitat features and species performance well, SDM results can be related also to other key parameters of populations, including reproductive parameters. To test this hypothesis, we evaluated whether SDM results can be used as a proxy of reproductive parameters (breeding output, territory size) in red-backed shrikes (Lanius collurio). 2. The distribution of 726 shrike territories in Northern Italy was obtained through multiple focused surveys; for a subset of pairs, we also measured territory area and number of fledged juveniles. We used Maximum Entropy modelling to build a SDM on the basis of territory distribution. We used generalized least squares and spatial generalized mixed models to relate territory size and number of fledged juveniles to SDM suitability, while controlling for spatial autocorrelation. 3. Species distribution models predicted shrike distribution very well. Territory size was negatively related to suitability estimated through SDM, while the number of fledglings significantly increased with the suitability of the territory. This was true also when SDM was built using only spatially and temporally independent data. 4. Results show a clear relationship between ES estimated through presence-only SDMs and two key parameters related to species' reproduction, suggesting that suitability estimated by SDM, and habitat quality determining reproduction parameters in our model system, are correlated. Our study shows the potential use of SDMs to infer important fitness parameters; this information can have great importance in management and conservation. © 2012 The Authors. Journal of Animal Ecology © 2012 British Ecological

  19. Predictive models of threatened plant species distribution in the Iberian arid south-east

    OpenAIRE

    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).

  20. Species distribution modeling in the tropics: problems, potentialities, and the role of biological data for effective species conservation

    NARCIS (Netherlands)

    Cayuela, L.; Golicher, J.D.; Newton, A.C.; Kolb, M.; Alburquerque, de F.S.; Arets, E.J.M.M.; Alkemade, J.R.M.; Pérez, A.M.

    2009-01-01

    In this paper we aim to investigate the problems and potentialities of species distribution modeling (SDM) as a tool for conservation planning and policy development and implementation in tropical regions. We reviewed 123 studies published between 1995 and 2007 in five of the leading journals in

  1. Species distribution modeling in regions of high need and limited data: waterfowl of China

    Science.gov (United States)

    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

  2. Climate suitability for European ticks: assessing species distribution models against null models and projection under AR5 climate.

    Science.gov (United States)

    Williams, Hefin Wyn; Cross, Dónall Eoin; Crump, Heather Louise; Drost, Cornelis Jan; Thomas, Christopher James

    2015-08-28

    There is increasing evidence that the geographic distribution of tick species is changing. Whilst correlative Species Distribution Models (SDMs) have been used to predict areas that are potentially suitable for ticks, models have often been assessed without due consideration for spatial patterns in the data that may inflate the influence of predictor variables on species distributions. This study used null models to rigorously evaluate the role of climate and the potential for climate change to affect future climate suitability for eight European tick species, including several important disease vectors. We undertook a comparative assessment of the performance of Maxent and Mahalanobis Distance SDMs based on observed data against those of null models based on null species distributions or null climate data. This enabled the identification of species whose distributions demonstrate a significant association with climate variables. Latest generation (AR5) climate projections were subsequently used to project future climate suitability under four Representative Concentration Pathways (RCPs). Seven out of eight tick species exhibited strong climatic signals within their observed distributions. Future projections intimate varying degrees of northward shift in climate suitability for these tick species, with the greatest shifts forecasted under the most extreme RCPs. Despite the high performance measure obtained for the observed model of Hyalomma lusitanicum, it did not perform significantly better than null models; this may result from the effects of non-climatic factors on its distribution. By comparing observed SDMs with null models, our results allow confidence that we have identified climate signals in tick distributions that are not simply a consequence of spatial patterns in the data. Observed climate-driven SDMs for seven out of eight species performed significantly better than null models, demonstrating the vulnerability of these tick species to the effects of

  3. Species Distribution Models and Ecological Suitability Analysis for Potential Tick Vectors of Lyme Disease in Mexico

    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.

  4. Species distribution models for a migratory bird based on citizen science and satellite tracking data

    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.

  5. Species distribution models for a migratory bird based on citizen science and satellite tracking data

    Science.gov (United States)

    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.

  6. Combining food web and species distribution models for improved community projections.

    Science.gov (United States)

    Pellissier, Loïc; Rohr, Rudolf P; Ndiribe, Charlotte; Pradervand, Jean-Nicolas; Salamin, Nicolas; Guisan, Antoine; Wisz, Mary

    2013-11-01

    The ability to model biodiversity patterns is of prime importance in this era of severe environmental crisis. Species assemblage along environmental gradients is subject to the interplay of biotic interactions in complement to abiotic filtering and stochastic forces. Accounting for complex biotic interactions for a wide array of species remains so far challenging. Here, we propose using food web models that can infer the potential interaction links between species as a constraint in species distribution models. Using a plant-herbivore (butterfly) interaction dataset, we demonstrate that this combined approach is able to improve species distribution and community forecasts. The trophic interaction network between butterfly larvae and host plant was phylogenetically structured and driven by host plant nitrogen content allowing forecasting the food web model to unknown interactions links. This combined approach is very useful in rendering models of more generalist species that have multiple potential interaction links, where gap in the literature may occur. Our combined approach points toward a promising direction for modeling the spatial variation in entire species interaction networks.

  7. Why inputs matter: Selection of climatic variables for species distribution modelling in the Himalayan region

    Science.gov (United States)

    Bobrowski, Maria; Schickhoff, Udo

    2017-04-01

    Betula utilis is a major constituent of alpine treeline ecotones in the western and central Himalayan region. The objective of this study is to provide first time analysis of the potential distribution of Betula utilis in the subalpine and alpine belts of the Himalayan region using species distribution modelling. Using Generalized Linear Models (GLM) we aim at examining climatic factors controlling the species distribution under current climate conditions. Furthermore we evaluate the prediction ability of climate data derived from different statistical methods. GLMs were created using least correlated bioclimatic variables derived from two different climate models: 1) interpolated climate data (i.e. Worldclim, Hijmans et al., 2005) and 2) quasi-mechanistical statistical downscaling (i.e. Chelsa; Karger et al., 2016). Model accuracy was evaluated by the ability to predict the potential species distribution range. We found that models based on variables of Chelsa climate data had higher predictive power, whereas models using Worldclim climate data consistently overpredicted the potential suitable habitat for Betula utilis. Although climatic variables of Worldclim are widely used in modelling species distribution, our results suggest to treat them with caution when remote regions like the Himalayan mountains are in focus. Unmindful usage of climatic variables for species distribution models potentially cause misleading projections and may lead to wrong implications and recommendations for nature conservation. References: Hijmans, R.J., Cameron, S.E., Parra, J.L., Jones, P.G. & Jarvis, A. (2005) Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology, 25, 1965-1978. Karger, D.N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R.W., Zimmermann, N., Linder, H.P. & Kessler, M. (2016) Climatologies at high resolution for the earth land surface areas. arXiv:1607.00217 [physics].

  8. Using species abundance distribution models and diversity indices for biogeographical analyses

    Science.gov (United States)

    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

  9. Moving Towards Dynamic Ocean Management: How Well Do Modeled Ocean Products Predict Species Distributions?

    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.

  10. The geography of demography: long-term demographic studies and species distribution models reveal a species border limited by adaptation.

    Science.gov (United States)

    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.

  11. 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

  12. Implications of movement for species distribution models - Rethinking environmental data tools.

    Science.gov (United States)

    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.

  13. A framework for using niche models to estimate impacts of climate change on species distributions.

    Science.gov (United States)

    Anderson, Robert P

    2013-09-01

    Predicting species geographic distributions in the future is an important yet exceptionally challenging endeavor. Overall, it requires a two-step process: (1) a niche model characterizing suitability, applied to projections of future conditions and linked to (2) a dispersal/demographic simulation estimating the species' future occupied distribution. Despite limitations, for the vast majority of species, correlative approaches are the most feasible avenue for building niche models. In addition to myriad technical issues regarding model building, researchers should follow critical principles for selecting predictor variables and occurrence data, demonstrating effective performance in prediction across space, and extrapolating into nonanalog conditions. Many of these principles relate directly to the niche space, dispersal/demographic noise, biotic noise, and human noise assumptions defined here. Issues requiring progress include modeling interactions between abiotic variables, integrating biotic variables, considering genetic heterogeneity, and quantifying uncertainty. Once built, the niche model identifying currently suitable conditions must be processed to approximate the areas that the species occupies. That estimate serves as a seed for the simulation of persistence, dispersal, and establishment in future suitable areas. The dispersal/demographic simulation also requires data regarding the species' dispersal ability and demography, scenarios for future land use, and the capability of considering multiple interacting species simultaneously. © 2013 New York Academy of Sciences.

  14. Species abundance distributions in neutral models with immigration or mutation and general lifetimes.

    Science.gov (United States)

    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.

  15. Predicting geographic distributions of Phacellodomus species (Aves: Furnariidae in South America based on ecological niche modeling

    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.

  16. What do we gain from simplicity versus complexity in species distribution models?

    Science.gov (United States)

    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

  17. Legume diversity patterns in West Central Africa: influence of species biology on distribution models.

    Science.gov (United States)

    de la Estrella, Manuel; Mateo, Rubén G; Wieringa, Jan J; Mackinder, Barbara; Muñoz, Jesús

    2012-01-01

    Species Distribution Models (SDMs) are used to produce predictions of potential Leguminosae diversity in West Central Africa. Those predictions are evaluated subsequently using expert opinion. The established methodology of combining all SDMs is refined to assess species diversity within five defined vegetation types. Potential species diversity is thus predicted for each vegetation type respectively. The primary aim of the new methodology is to define, in more detail, areas of species richness for conservation planning. Using Maxent, SDMs based on a suite of 14 environmental predictors were generated for 185 West Central African Leguminosae species, each categorised according to one of five vegetation types: Afromontane, coastal, non-flooded forest, open formations, or riverine forest. The relative contribution of each environmental variable was compared between different vegetation types using a nonparametric Kruskal-Wallis analysis followed by a post-hoc Kruskal-Wallis Paired Comparison contrast. Legume species diversity patterns were explored initially using the typical method of stacking all SDMs. Subsequently, five different ensemble models were generated by partitioning SDMs according to vegetation category. Ecological modelers worked with legume specialists to improve data integrity and integrate expert opinion in the interpretation of individual species models and potential species richness predictions for different vegetation types. Of the 14 environmental predictors used, five showed no difference in their relative contribution to the different vegetation models. Of the nine discriminating variables, the majority were related to temperature variation. The set of variables that played a major role in the Afromontane species diversity model differed significantly from the sets of variables of greatest relative important in other vegetation categories. The traditional approach of stacking all SDMs indicated overall centers of diversity in the region but the

  18. Legume Diversity Patterns in West Central Africa: Influence of Species Biology on Distribution Models

    Science.gov (United States)

    de la Estrella, Manuel; Mateo, Rubén G.; Wieringa, Jan J.; Mackinder, Barbara; Muñoz, Jesús

    2012-01-01

    Objectives Species Distribution Models (SDMs) are used to produce predictions of potential Leguminosae diversity in West Central Africa. Those predictions are evaluated subsequently using expert opinion. The established methodology of combining all SDMs is refined to assess species diversity within five defined vegetation types. Potential species diversity is thus predicted for each vegetation type respectively. The primary aim of the new methodology is to define, in more detail, areas of species richness for conservation planning. Methodology Using Maxent, SDMs based on a suite of 14 environmental predictors were generated for 185 West Central African Leguminosae species, each categorised according to one of five vegetation types: Afromontane, coastal, non-flooded forest, open formations, or riverine forest. The relative contribution of each environmental variable was compared between different vegetation types using a nonparametric Kruskal-Wallis analysis followed by a post-hoc Kruskal-Wallis Paired Comparison contrast. Legume species diversity patterns were explored initially using the typical method of stacking all SDMs. Subsequently, five different ensemble models were generated by partitioning SDMs according to vegetation category. Ecological modelers worked with legume specialists to improve data integrity and integrate expert opinion in the interpretation of individual species models and potential species richness predictions for different vegetation types. Results/Conclusions Of the 14 environmental predictors used, five showed no difference in their relative contribution to the different vegetation models. Of the nine discriminating variables, the majority were related to temperature variation. The set of variables that played a major role in the Afromontane species diversity model differed significantly from the sets of variables of greatest relative important in other vegetation categories. The traditional approach of stacking all SDMs indicated overall

  19. 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.

  20. Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling (SAHM)

    OpenAIRE

    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...

  1. Incorporating fragmentation and non-native species into distribution models to inform fluvial fish conservation.

    Science.gov (United States)

    Taylor, Andrew T; Papeş, Monica; Long, James M

    2018-02-01

    Fluvial fishes face increased imperilment from anthropogenic activities, but the specific factors contributing most to range declines are often poorly understood. For example, the range of the fluvial-specialist shoal bass (Micropterus cataractae) continues to decrease, yet how perceived threats have contributed to range loss is largely unknown. We used species distribution models to determine which factors contributed most to shoal bass range loss. We estimated a potential distribution based on natural abiotic factors and a series of currently occupied distributions that incorporated variables characterizing land cover, non-native species, and river fragmentation intensity (no fragmentation, dams only, and dams and large impoundments). We allowed interspecific relationships between non-native congeners and shoal bass to vary across fragmentation intensities. Results from the potential distribution model estimated shoal bass presence throughout much of their native basin, whereas models of currently occupied distribution showed that range loss increased as fragmentation intensified. Response curves from models of currently occupied distribution indicated a potential interaction between fragmentation intensity and the relationship between shoal bass and non-native congeners, wherein non-natives may be favored at the highest fragmentation intensity. Response curves also suggested that >100 km of interconnected, free-flowing stream fragments were necessary to support shoal bass presence. Model evaluation, including an independent validation, suggested that models had favorable predictive and discriminative abilities. Similar approaches that use readily available, diverse, geospatial data sets may deliver insights into the biology and conservation needs of other fluvial species facing similar threats. © 2017 Society for Conservation Biology.

  2. Predicting climate change effects on wetland ecosystem services using species distribution modeling and plant functional traits.

    Science.gov (United States)

    Moor, Helen; Hylander, Kristoffer; Norberg, Jon

    2015-01-01

    Wetlands provide multiple ecosystem services, the sustainable use of which requires knowledge of the underlying ecological mechanisms. Functional traits, particularly the community-weighted mean trait (CWMT), provide a strong link between species communities and ecosystem functioning. We here combine species distribution modeling and plant functional traits to estimate the direction of change of ecosystem processes under climate change. We model changes in CWMT values for traits relevant to three key services, focusing on the regional species pool in the Norrström area (central Sweden) and three main wetland types. Our method predicts proportional shifts toward faster growing, more productive and taller species, which tend to increase CWMT values of specific leaf area and canopy height, whereas changes in root depth vary. The predicted changes in CWMT values suggest a potential increase in flood attenuation services, a potential increase in short (but not long)-term nutrient retention, and ambiguous outcomes for carbon sequestration.

  3. Predicting habitat suitability for rare plants at local spatial scales using a species distribution model.

    Science.gov (United States)

    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

  4. The role of demography, intra-species variation, and species distribution models in species’ projections under climate change

    DEFF Research Database (Denmark)

    Swab, Rebecca Marie; Regan, Helen M.; Matthies, Diethart

    2015-01-01

    and linked it to a SDM that predicted changes in habitat suitability through time with changes in climatic variables. We then varied the demographic parameters based upon observed vital rates of local populations from a translocation experiment. Despite the fact that the SDM alone predicted C. vulgaris......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...

  5. Development of Species Sensitivity Distributions for Wildlife Using Interspecies Toxicity Correlation Models

    Science.gov (United States)

    Species sensitivity distributions (SSD) are cumulative distributions of chemical toxicity of multiple species and have had limited application in wildlife risk assessment because of relatively small datasets of wildlife toxicity values. Interspecies correlation estimation (ICE) m...

  6. How Useful Are Species Distribution Models for Managing Biodiversity under Future Climates?

    Directory of Open Access Journals (Sweden)

    Steve J. Sinclair

    2010-03-01

    Full Text Available Climate change presents unprecedented challenges for biological conservation. Agencies are increasingly looking to modeled projections of species' distributions under future climates to inform management strategies. As government scientists with a responsibility to communicate the best available science to our policy colleagues, we question whether current modeling approaches and outputs are practically useful. Here, we synthesize conceptual problems with species distribution models (SDMs associated with interspecific interactions, dispersal, ecological equilibria and time lags, evolution, and the sampling of niche space. Although projected SDMs have undoubtedly been critical in alerting us to the magnitude of climate change impacts, we conclude that until they offer insights that are more precise than what we can derive from basic ecological theory, we question their utility in deciding how to allocate scarce funds to large-scale conservation projects.

  7. Testing the efficacy of downscaling in species distribution modelling: a comparison between MaxEnt and Favourability Function models

    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)

  8. Testing the efficacy of downscaling in species distribution modelling: a comparison between MaxEnt and Favourability Function models

    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.

  9. Proximal Soil Sensing - A Contribution for Species Habitat Distribution Modelling of Earthworms in Agricultural Soils?

    Science.gov (United States)

    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

  10. Incorporating plant fossil data into species distribution models is not straightforward: Pitfalls and possible solutions

    Science.gov (United States)

    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.

  11. Spatial autocorrelation in predictors reduces the impact of positional uncertainty in occurrence data on species distribution modelling

    NARCIS (Netherlands)

    Naimi, B.; Skidmore, A.K.; Groen, T.A.; Hamm, N.A.S.

    2011-01-01

    Aim To investigate the impact of positional uncertainty in species occurrences on the predictions of seven commonly used species distribution models (SDMs), and explore its interaction with spatial autocorrelation in predictors. Methods A series of artificial datasets covering 155 scenarios

  12. Inferential monitoring of global change impact on biodiversity through remote sensing and species distribution modeling

    Science.gov (United States)

    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

  13. Scale effects in species distribution models: implications for conservation planning under climate change.

    Science.gov (United States)

    Seo, Changwan; Thorne, James H; Hannah, Lee; Thuiller, Wilfried

    2009-02-23

    Predictions of future species' ranges under climate change are needed for conservation planning, for which species distribution models (SDMs) are widely used. However, global climate model-based (GCM) output grids can bias the area identified as suitable when these are used as SDM predictor variables, because GCM outputs, typically at least 50x50 km, are biologically coarse. We tested the assumption that species ranges can be equally well portrayed in SDMs operating on base data of different grid sizes by comparing SDM performance statistics and area selected by four SDMs run at seven grid sizes, for nine species of contrasting range size. Area selected was disproportionately larger for SDMs run on larger grid sizes, indicating a cut-off point above which model results were less reliable. Up to 2.89 times more species range area was selected by SDMs operating on grids above 50x50 km, compared to SDMs operating at 1 km2. Spatial congruence between areas selected as range also diverged as grid size increased, particularly for species with ranges between 20000 and 90000 km2. These results indicate the need for caution when using such data to plan future protected areas, because an overly large predicted range could lead to inappropriate reserve location selection.

  14. Effects of sample survey design on the accuracy of classification tree models in species distribution models

    Science.gov (United States)

    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...

  15. Using maximum topology matching to explore differences in species distribution models

    Science.gov (United States)

    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.

  16. The Application of Spaceborne Remote Sensing Datasets for Species Distribution Modeling in South America

    Science.gov (United States)

    McDonald, K. C.; Carnaval, A.; Waltari, E.; Schroeder, R.

    2012-12-01

    For the last 40 years, the fields of evolutionary biogeography and conservation biology witnessed substantial improvement and usage of correlative species distribution in studies of biodiversity patterns and their underlying processes Thanks to a suite of new algorithms and the integration of maximum entropy concepts into the biological sciences, field scientists are now able to better predict species ranges from environmental surrogates. To date, biologists have been relying on a single major set of global environmental grids for the purpose of both delimiting species environmental envelopes and projecting envelopes through space and time. The data set, also known as the WorldClim database, relies on measurements of elevation, precipitation, mean, maximum and minimum temperature collected from weather-stations across the world. These data were used to derive worldwide grids, at 1 km resolution, through interpolation of average monthly climate data from stations. Nineteen bioclimatic grids have been derived from the air temperature and precipitation values and have been used extensively in predictive studies. Although these WorldClim grids have been successfully applied to a suite of ecological and evolutionary research questions, their performance can be suboptimal especially in topographically complex areas where interpolation methods fail to capture true variation in local climate, in biological systems impacted by environmental phenomena occurring at finer temporal or spatial scales, and in regions with few weather stations. The objective of this work is to assess the utility of remote sensing data sets for providing environmental fields to derive novel bioclimatic grids relative to the WorldClim dataset, and test the associated improvement to species distribution models in a topographically complex tropical area. We generate a novel set of bioclimatic grids for biodiversity analysis from such sources as MODIS, AMSR-E, TRMM and MERRA. Using these grids, we

  17. A mixed modeling approach to predict the effect of environmental modification on species distributions.

    Directory of Open Access Journals (Sweden)

    Francesco Cozzoli

    Full Text Available Human infrastructures can modify ecosystems, thereby affecting the occurrence and spatial distribution of organisms, as well as ecosystem functionality. Sustainable development requires the ability to predict responses of species to anthropogenic pressures. We investigated the large scale, long term effect of important human alterations of benthic habitats with an integrated approach combining engineering and ecological modelling. We focused our analysis on the Oosterschelde basin (The Netherlands, which was partially embanked by a storm surge barrier (Oosterscheldekering, 1986. We made use of 1 a prognostic (numerical environmental (hydrodynamic model and 2 a novel application of quantile regression to Species Distribution Modeling (SDM to simulate both the realized and potential (habitat suitability abundance of four macrozoobenthic species: Scoloplos armiger, Peringia ulvae, Cerastoderma edule and Lanice conchilega. The analysis shows that part of the fluctuations in macrozoobenthic biomass stocks during the last decades is related to the effect of the coastal defense infrastructures on the basin morphology and hydrodynamics. The methodological framework we propose is particularly suitable for the analysis of large abundance datasets combined with high-resolution environmental data. Our analysis provides useful information on future changes in ecosystem functionality induced by human activities.

  18. 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.

  19. Distribution Modeling of three screwworm species in the ecologically diverse landscape of North West Pakistan.

    Science.gov (United States)

    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

  20. Proximal Soil Sensing - A Contribution for Species Habitat Distribution Modelling of Earthworms in Agricultural Soils?

    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

  1. Predicting habitat suitability of Coptotermes gestroi (Isoptera: Rhinotermitidae) with species distribution models.

    Science.gov (United States)

    Li, Hou-Feng; Fujisaki, Ikuko; Su, Nan-Yao

    2013-02-01

    Coptotermes gestroi (Wasmann) is an important structural pest reported from Asia, Pacific islands, North America, Caribbean islands, South America, and Indian Ocean islands. This study summarized previous records of C. gestroi and its synonyms, presenting 184 infested counties from 24 countries. Based on the geo-references occurrence locations and global raster data of climate, geography, and human population, C. gestroi were found most commonly in warm, high precipitation, low altitude, and human populated areas. By using species distribution models, we predicted its current infested area (model 1), habitat suitability (model 2), and probability of introduction (model 3) on a global scale. The results showed its recorded locations and the predicted distribution of the present day are similar, but the suitable habitat is larger than its current distribution. The patterns of the introduction frequency (model 3) and habitat suitability (model 2) are inconsistent. Temperate cities with high introduction risk are located in Europe, United Sates, northeastern China, and Japan where habitat suitability is low and hence successful colonization is unlikely. In tropics and subtropics, habitat suitability of C. gestroi is high. We speculate that continuous urbanization and increasing human population will increase its introduction frequency and cause further extension in fast developing tropical and subtropical countries.

  2. Modeling species distributions from heterogeneous data for the biogeographic regionalization of the European bryophyte flora.

    Science.gov (United States)

    Mateo, Rubén G; Vanderpoorten, Alain; Muñoz, Jesús; Laenen, Benjamin; Désamoré, Aurélie

    2013-01-01

    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 importance of developing

  3. Modeling species distributions from heterogeneous data for the biogeographic regionalization of the European bryophyte flora.

    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

  4. Accounting for selection bias in species distribution models: An econometric approach on forested trees based on structural modeling

    Science.gov (United States)

    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

  5. Evaluating Bayesian spatial methods for modelling species distributions with clumped and restricted occurrence data.

    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

  6. Climate refugia: joint inference from fossil records, species distribution models and phylogeography.

    Science.gov (United States)

    Gavin, Daniel G; Fitzpatrick, Matthew C; Gugger, Paul F; Heath, Katy D; Rodríguez-Sánchez, Francisco; Dobrowski, Solomon Z; Hampe, Arndt; Hu, Feng Sheng; Ashcroft, Michael B; Bartlein, Patrick J; Blois, Jessica L; Carstens, Bryan C; Davis, Edward B; de Lafontaine, Guillaume; Edwards, Mary E; Fernandez, Matias; Henne, Paul D; Herring, Erin M; Holden, Zachary A; Kong, Woo-seok; Liu, Jianquan; Magri, Donatella; Matzke, Nicholas J; McGlone, Matt S; Saltré, Frédérik; Stigall, Alycia L; Tsai, Yi-Hsin Erica; Williams, John W

    2014-10-01

    Climate refugia, locations where taxa survive periods of regionally adverse climate, are thought to be critical for maintaining biodiversity through the glacial-interglacial climate changes of the Quaternary. A critical research need is to better integrate and reconcile the three major lines of evidence used to infer the existence of past refugia - fossil records, species distribution models and phylogeographic surveys - in order to characterize the complex spatiotemporal trajectories of species and populations in and out of refugia. Here we review the complementary strengths, limitations and new advances for these three approaches. We provide case studies to illustrate their combined application, and point the way towards new opportunities for synthesizing these disparate lines of evidence. Case studies with European beech, Qinghai spruce and Douglas-fir illustrate how the combination of these three approaches successfully resolves complex species histories not attainable from any one approach. Promising new statistical techniques can capitalize on the strengths of each method and provide a robust quantitative reconstruction of species history. Studying past refugia can help identify contemporary refugia and clarify their conservation significance, in particular by elucidating the fine-scale processes and the particular geographic locations that buffer species against rapidly changing climate. © 2014 The Authors. New Phytologist © 2014 New Phytologist Trust.

  7. A Distributed Agent Implementation of Multiple Species Flocking Model for Document Partitioning Clustering

    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.

  8. Using species distribution modeling to delineate the botanical richness patterns and phytogeographical regions of China

    Science.gov (United States)

    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.

  9. MODELING SPATIAL DISTRIBUTION OF A RARE AND ENDANGERED PLANT SPECIES (Brainea insignis IN CENTRAL TAIWAN

    Directory of Open Access Journals (Sweden)

    W.-C. Wang

    2012-07-01

    Full Text Available With an increase in the rate of species extinction, we should choose right methods that are sustainable on the basis of appropriate science and human needs to conserve ecosystems and rare species. Species distribution modeling (SDM uses 3S technology and statistics and becomes increasingly important in ecology. Brainea insignis (cycad-fern, CF has been categorized a rare, endangered plant species, and thus was chosen as a target for the study. Five sampling schemes were created with different combinations of CF samples collected from three sites in Huisun forest station and one site, 10 km farther north from Huisun. Four models, MAXENT, GARP, generalized linear models (GLM, and discriminant analysis (DA, were developed based on topographic variables, and were evaluated by five sampling schemes. The accuracy of MAXENT was the highest, followed by GLM and GARP, and DA was the lowest. More importantly, they can identify the potential habitat less than 10% of the study area in the first round of SDM, thereby prioritizing either the field-survey area where microclimatic, edaphic or biotic data can be collected for refining predictions of potential habitat in the later rounds of SDM or search areas for new population discovery. However, it was shown unlikely to extend spatial patterns of CFs from one area to another with a big separation or to a larger area by predictive models merely based on topographic variables. Follow-up studies will attempt to incorporate proxy indicators that can be extracted from hyperspectral images or LIDAR DEM and substitute for direct parameters to make predictive models applicable on a broader scale.

  10. Continuous gene flow contributes to low global species abundance and distribution of a marine model diatom

    KAUST Repository

    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.

  11. Using Species Distribution Models to Predict Potential Landscape Restoration Effects on Puma Conservation.

    Science.gov (United States)

    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

  12. Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling (SAHM).

    Science.gov (United States)

    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.

  13. Integrating remote sensing with species distribution models; Mapping tamarisk invasions using the Software for Assisted Habitat Modeling (SAHM)

    Science.gov (United States)

    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.

  14. The importance of data quality for generating reliable distribution models for rare, elusive, and cryptic species.

    Directory of Open Access Journals (Sweden)

    Keith B Aubry

    Full Text Available The availability of spatially referenced environmental data and species occurrence records in online databases enable practitioners to easily generate species distribution models (SDMs for a broad array of taxa. Such databases often include occurrence records of unknown reliability, yet little information is available on the influence of data quality on SDMs generated for rare, elusive, and cryptic species that are prone to misidentification in the field. We investigated this question for the fisher (Pekania pennanti, a forest carnivore of conservation concern in the Pacific States that is often confused with the more common Pacific marten (Martes caurina. Fisher occurrence records supported by physical evidence (verifiable records were available from a limited area, whereas occurrence records of unknown quality (unscreened records were available from throughout the fisher's historical range. We reserved 20% of the verifiable records to use as a test sample for both models and generated SDMs with each dataset using Maxent. The verifiable model performed substantially better than the unscreened model based on multiple metrics including AUCtest values (0.78 and 0.62, respectively, evaluation of training and test gains, and statistical tests of how well each model predicted test localities. In addition, the verifiable model was consistent with our knowledge of the fisher's habitat relations and potential distribution, whereas the unscreened model indicated a much broader area of high-quality habitat (indices > 0.5 that included large expanses of high-elevation habitat that fishers do not occupy. Because Pacific martens remain relatively common in upper elevation habitats in the Cascade Range and Sierra Nevada, the SDM based on unscreened records likely reflects primarily a conflation of marten and fisher habitat. Consequently, accurate identifications are far more important than the spatial extent of occurrence records for generating reliable SDMs

  15. Identifying Reliable Opportunistic Data for Species Distribution Modeling: A Benchmark Data Optimization Approach

    Directory of Open Access Journals (Sweden)

    Yu-Pin Lin

    2017-11-01

    Full Text Available The purpose of this study is to increase the number of species occurrence data by integrating opportunistic data with Global Biodiversity Information Facility (GBIF benchmark data via a novel optimization technique. The optimization method utilizes Natural Language Processing (NLP and a simulated annealing (SA algorithm to maximize the average likelihood of species occurrence in maximum entropy presence-only species distribution models (SDM. We applied the Kruskal–Wallis test to assess the differences between the corresponding environmental variables and habitat suitability indices (HSI among datasets, including data from GBIF, Facebook (FB, and data from optimally selected FB data. To quantify uncertainty in SDM predictions, and to quantify the efficacy of the proposed optimization procedure, we used a bootstrapping approach to generate 1000 subsets from five different datasets: (1 GBIF; (2 FB; (3 GBIF plus FB; (4 GBIF plus optimally selected FB; and (5 GBIF plus randomly selected FB. We compared the performance of simulated species distributions based on each of the above subsets via the area under the curve (AUC of the receiver operating characteristic (ROC. We also performed correlation analysis between the average benchmark-based SDM outputs and the average dataset-based SDM outputs. Median AUCs of SDMs based on the dataset that combined benchmark GBIF data and optimally selected FB data were generally higher than the AUCs of other datasets, indicating the effectiveness of the optimization procedure. Our results suggest that the proposed approach increases the quality and quantity of data by effectively extracting opportunistic data from large unstructured datasets with respect to benchmark data.

  16. Species distribution modeling techniques as a tool in preliminary assessment of special nature reserve ,,Goč-Gvozdac’’

    Directory of Open Access Journals (Sweden)

    Čubrić, T.

    2016-09-01

    Full Text Available Effective conservation actions such as defining new nature reserve require accurate estimates of the spatial distributions of the target species. Species distribution models provide habitat suitability maps for studied species. In this paper we used Maxent software to estimate the distribution and extent of potential suitable habitat of five amphibian and reptilian species (Mesotriton alpestris, Bombina variegata, Testudo hermanni, Lacerta viridis and Vipera ammodytes in the special nature reserve “Goč-Gvozdac” (Central Serbia in order to assess how much of the potential habitats is included in this reserve. Comparing produced suitable habitat maps of the species with a map of the special nature reserve “Goč – Gvozdac” we concluded that the reserve boundaries do not coincide with the proposed distribution of suitable habitats for M. alpestris, T. hermanni, L. viridis and V. ammodytes, and therefore this reserve does not contribute much to the protection of local populations of these species.

  17. A Systematic Review of Marine-Based Species Distribution Models (SDMs with Recommendations for Best Practice

    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.

  18. 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.

  19. Assessing historical fish community composition using surveys, historical collection data, and species distribution models.

    Directory of Open Access Journals (Sweden)

    Ben Labay

    Full Text Available 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

  20. Fish species of greatest conservation need in wadeable Iowa streams: current status and effectiveness of Aquatic Gap Program distribution models

    Science.gov (United States)

    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

  1. Determining the factors affecting the distribution ofMuscari latifolium, an endemic plant of Turkey, and a mapping species distribution model.

    Science.gov (United States)

    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.

  2. Novel three-step pseudo-absence selection technique for improved species distribution modelling.

    Directory of Open Access Journals (Sweden)

    Senait D Senay

    Full Text Available Pseudo-absence selection for spatial distribution models (SDMs is the subject of ongoing investigation. Numerous techniques continue to be developed, and reports of their effectiveness vary. Because the quality of presence and absence data is key for acceptable accuracy of correlative SDM predictions, determining an appropriate method to characterise pseudo-absences for SDM's is vital. The main methods that are currently used to generate pseudo-absence points are: 1 randomly generated pseudo-absence locations from background data; 2 pseudo-absence locations generated within a delimited geographical distance from recorded presence points; and 3 pseudo-absence locations selected in areas that are environmentally dissimilar from presence points. There is a need for a method that considers both geographical extent and environmental requirements to produce pseudo-absence points that are spatially and ecologically balanced. We use a novel three-step approach that satisfies both spatial and ecological reasons why the target species is likely to find a particular geo-location unsuitable. Step 1 comprises establishing a geographical extent around species presence points from which pseudo-absence points are selected based on analyses of environmental variable importance at different distances. This step gives an ecologically meaningful explanation to the spatial range of background data, as opposed to using an arbitrary radius. Step 2 determines locations that are environmentally dissimilar to the presence points within the distance specified in step one. Step 3 performs K-means clustering to reduce the number of potential pseudo-absences to the desired set by taking the centroids of clusters in the most environmentally dissimilar class identified in step 2. By considering spatial, ecological and environmental aspects, the three-step method identifies appropriate pseudo-absence points for correlative SDMs. We illustrate this method by predicting the New

  3. Is the climate right for pleistocene rewilding? Using species distribution models to extrapolate climatic suitability for mammals across continents.

    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

  4. Developing MODIS-based cloud climatologies to aid species distribution modeling and conservation activities

    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

  5. Used-habitat calibration plots: A new procedure for validating species distribution, resource selection, and step-selection models

    Science.gov (United States)

    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.

  6. A climate change context for the decline of a foundation tree species in south-western Australia: insights from phylogeography and species distribution modelling.

    Science.gov (United States)

    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

  7. Species distribution modeling for the invasive raccoon dog (Nyctereutes procyonoides in Austria and first range predictions for alpine environments

    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.

  8. Modeling Rare Species Distribution at the Edge: The Case for the Vulnerable Endemic Pyrenean Desman in France

    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.

  9. Climate-based species distribution models for Armillaria solidipes in Wyoming: A preliminary assessment

    Science.gov (United States)

    John W. Hanna; James T. Blodgett; Eric W. I. Pitman; Sarah M. Ashiglar; John E. Lundquist; Mee-Sook Kim; Amy L. Ross-Davis; Ned B. Klopfenstein

    2014-01-01

    As part of an ongoing project to predict Armillaria root disease in the Rocky Mountain zone, this project predicts suitable climate space (potential distribution) for A. solidipes in Wyoming and associated forest areas at risk to disease caused by this pathogen. Two bioclimatic models are being developed. One model is based solely on verified locations of A. solidipes...

  10. Balancing energy development and conservation: A method utilizing species distribution models

    Science.gov (United States)

    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).

  11. Modelling planktic foraminifer growth and distribution using an ecophysiological multi-species approach

    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.

  12. Why choose Random Forest to predict rare species distribution with few samples in large undersampled areas? Three Asian crane species models provide supporting evidence

    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

  13. Why choose Random Forest to predict rare species distribution with few samples in large undersampled areas? Three Asian crane species models provide supporting evidence.

    Science.gov (United States)

    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

  14. Species distribution models contribute to determine the effect of climate and interspecific interactions in moving hybrid zones.

    Science.gov (United States)

    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.

  15. Using Citizen Science Observations to Model Species Distributions Over Space, Through Time, and Across Scales

    Science.gov (United States)

    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.

  16. Evolutionary history of the grey-faced Sengi, Rhynchocyon udzungwensis, from Tanzania: a molecular and species distribution modelling approach.

    Directory of Open Access Journals (Sweden)

    Lucinda P Lawson

    Full Text Available Rhynchocyon udzungwensis is a recently described and poorly understood sengi (giant elephant-shrew endemic to two small montane forests in Southern Tanzania, and surrounded in lower forests by R. cirnei reichardi. In this study, we investigate the molecular genetic relationship between R. udzungwensis and R. c. reichardi, and the possible role that shifting species distributions in response to climate fluctuations may have played in shaping their evolutionary history. Rhynchocyon udzungwensis and R. c. reichardi individuals were sampled from five localities for genetic analyses. Three mitochondrial and two nuclear loci were used to construct species trees for delimitation and to determine whether introgression was detectable either from ancient or ongoing hybridization. All species-tree results show R. udzungwensis and R. c. reichardi as distinct lineages, though mtDNA shows evidence of introgression in some populations. Nuclear loci of each species were monophyletic, implying introgression is exclusively historical. Because we found evidence of introgression, we used distribution data and species distribution modelling for present, glacial, and interglacial climate cycles to predict how shifting species distributions may have facilitated hybridization in some populations. Though interpretations are affected by the limited range of these species, a likely scenario is that the mtDNA introgression found in eastern mid-elevation populations was facilitated by low numbers of R. udzungwensis that expanded into lowland heavily occupied R. c. reichardi areas during interglacial climate cycles. These results imply that relationships within the genus Rhynchocyon may be confounded by porous species boundaries and introgression, even if species are not currently sympatric.

  17. Incorporating interspecific competition into species-distribution mapping by upward scaling of small-scale model projections to the landscape.

    Science.gov (United States)

    Baah-Acheamfour, Mark; Bourque, Charles P-A; Meng, Fan-Rui; Swift, D Edwin

    2017-01-01

    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.

  18. Incorporating interspecific competition into species-distribution mapping by upward scaling of small-scale model projections to the landscape.

    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.

  19. Coupling genetic and species distribution models to examine the response of the Hainan Partridge (Arborophila ardens to late quaternary climate.

    Directory of Open Access Journals (Sweden)

    Jiang Chang

    Full Text Available Understanding the historical dynamics of animal species is critical for accurate prediction of their response to climate changes. During the late Quaternary period, Southeast Asia had a larger land area than today due to lower sea levels, and its terrestrial landscape was covered by extensive forests and savanna. To date, however, the distribution fluctuation of vegetation and its impacts on genetic structure and demographic history of local animals during the Last Glacial Maximum (LGM are still disputed. In addition, the responses of animal species on Hainan Island, located in northern Southeast Asia, to climate changes during the LGM are poorly understood. Here, we combined phylogeographic analysis, paleoclimatic evidence, and species distribution models to examine the response of the flightless Hainan Partridge (Arborophila ardens to climate change. We concluded that A. ardens survived through LGM climate changes, and its current distribution on Hainan Island was its in situ refuge. Range model results indicated that A. ardens once covered a much larger area than its current distribution. Demographic history described a relatively stable pattern during and following the LGM. In addition, weak population genetic structure suggests a role in promoting gene flow between populations with climate-induced elevation shifts. Human activities must be considered in conservation planning due to their impact on fragmented habitats. These first combined data for Hainan Partridge demonstrate the value of paired genetic and SDMs study. More related works that might deepen our understanding of the responses of the species in Southeast Asia to late Quaternary Climate are needed.

  20. Limitations to the Use of Species-Distribution Models for Environmental-Impact Assessments in the Amazon.

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    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.

  1. Empirical phylogenies and species abundance distributions are consistent with pre-equilibrium dynamics of neutral community models with gene flow

    KAUST Repository

    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.

  2. Modeling the distribution of colonial species to improve estimation of plankton concentration in ballast water

    Science.gov (United States)

    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.

  3. Predicting geographic and ecological distributions of triatomine species in the southern Mexican state of Puebla using ecological niche modeling.

    Science.gov (United States)

    Sandoval-Ruiz, C A; Zumaquero-Rios, J L; Rojas-Soto, O R

    2008-05-01

    We analyzed the geographic distribution using ecological niche modeling of three species of triatomines distributed in the Mexican state of Puebla. Punctual records were gathered for a period of 5 yr of fieldwork sampling. We used the genetic algorithm for rule-set production (GARP) to achieve the potential distribution of the ecological niche of triatomines. The models showed that Triatoma barberi and Meccus pallidipennis are sympatric and widely distributed in the central-southern part of the state, whereas T. dimidata is restricted to the northern mountains of the state with no overlapping among other species, M. bassolsae was not modeled because of the scarce number of locality records. We highlighted the warm and dry conditions in southern Puebla as important potential areas for triatomine presence. Finally, we correlated the species potential presence with the human population at risk of acquiring Chagas disease by vector-borne transmission; it is showed that M. pallidipennis presents the highest values of both ecological and poverty risk scenarios representing the main potential vector in the state.

  4. Modelling planktic foraminifer growth and distribution using an ecophysiological multi-species approach

    DEFF Research Database (Denmark)

    Lombard, Fabien; Labeyrie, L.; Michel, E.

    2011-01-01

    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...... 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...

  5. The effects of sampling bias and model complexity on the predictive performance of MaxEnt species distribution models.

    Directory of Open Access Journals (Sweden)

    Mindy M Syfert

    Full Text Available 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.

  6. The effects of sampling bias and model complexity on the predictive performance of MaxEnt species distribution models.

    Science.gov (United States)

    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.

  7. Efficient modelling of foliage distribution and crown dynamics in monolayer tree species.

    Science.gov (United States)

    Beyer, Robert

    2017-12-01

    In response to the computational limitations of individual leaf-based tree growth models, this article presents a new approach for the efficient characterisation of the spatial distribution of foliage in monolayered trees in terms of 2D foliage surfaces. Much like the recently introduced 3D leaf area density, this concept accommodates local crown plasticity, which is a common weak point in large-scale growth models. Recognizing phototropism as the predominant driver of spatial crown expansion, we define the local light gradient on foliage surfaces. We consider the partial differential equation describing the evolution of a curve expanding along the light gradient and present an explicit solution. The article concludes with an illustration of the incorporation of foliage surfaces in a simple tree growth model for European beech (Fagus sylvatica L.), and discusses perspectives for applications in functional-structural models.

  8. Evaluating the significance of paleophylogeographic species distribution models in reconstructing quaternary range-shifts of nearctic chelonians.

    Directory of Open Access Journals (Sweden)

    Dennis Rödder

    Full Text Available The climatic cycles of the Quaternary, during which global mean annual temperatures have regularly changed by 5-10°C, provide a special opportunity for studying the rate, magnitude, and effects of geographic responses to changing climates. During the Quaternary, high- and mid-latitude species were extirpated from regions that were covered by ice or otherwise became unsuitable, persisting in refugial retreats where the environment was compatible with their tolerances. In this study we combine modern geographic range data, phylogeny, Pleistocene paleoclimatic models, and isotopic records of changes in global mean annual temperature, to produce a temporally continuous model of geographic changes in potential habitat for 59 species of North American turtles over the past 320 Ka (three full glacial-interglacial cycles. These paleophylogeographic models indicate the areas where past climates were compatible with the modern ranges of the species and serve as hypotheses for how their geographic ranges would have changed in response to Quaternary climate cycles. We test these hypotheses against physiological, genetic, taxonomic and fossil evidence, and we then use them to measure the effects of Quaternary climate cycles on species distributions. Patterns of range expansion, contraction, and fragmentation in the models are strongly congruent with (i phylogeographic differentiation; (ii morphological variation; (iii physiological tolerances; and (iv intraspecific genetic variability. Modern species with significant interspecific differentiation have geographic ranges that strongly fluctuated and repeatedly fragmented throughout the Quaternary. Modern species with low genetic diversity have geographic distributions that were highly variable and at times exceedingly small in the past. Our results reveal the potential for paleophylogeographic models to (i reconstruct past geographic range modifications, (ii identify geographic processes that result in

  9. Wrong, but useful: regional species distribution models may not be improved by range-wide data under biased sampling.

    Science.gov (United States)

    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

  10. Species Distribution Model for Management of an Invasive Vine in Forestlands of Eastern Texas

    Directory of Open Access Journals (Sweden)

    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.

  11. Forest vegetation in western Romania in relation to climate variables: Does community composition reflect modelled tree species distribution?

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    S. Heinrichs

    2016-12-01

    Full Text Available European beech (Fagus sylvatica L. is the prevailing tree species of mesic forests in Central Europe. Increasing summer temperatures and decreasing precipitation, as climate change scenarios predict, may, however, negatively influence beech growth and induce a shift to more thermophilous forest communities. Temperatures as expected in the future for western Central Europe are currently found in parts of western Romania. In light of this climate analogy we investigated forest vegetation as an indicator for future vegetation changes in five regions of western Romania representing a climatic gradient. We related species composition to climate variables and examined if tree and understorey species composition respond similarly to the climatic gradient. We further analysed if tree species occurrences correspond with their modelled distance to the rear niche edge. We found evidence for climatic effects on vegetation composition among regions as well as within deciduous and pine forests, respectively. This underlines that vegetation composition is a useful indicator for environmental change. Tree and understorey species compositions were closely linked showing that community-based characterization of forest stands can provide additional information on tree species suitability along environmental gradients. Both, vegetation composition and a climatic marginality index demonstrate the rear niche edge occurrence of beech in the studied sites of Romania and can predict the site suitability for different tree species. While vegetation surveys indicate Quercus petraea to be associated to moderately mesic forests, the marginality index suggested an inner niche position of sessile oak along the climatic gradient. Phytosociological relevés that differentiate between subspecies (or microspecies of sessile oak with differing habitat requirements should be considered to complement national forest inventories and species distribution maps when modelling rear

  12. Anticipating potential biodiversity conflicts for future biofuel crops in South Africa: Incorporating land cover information with Species Distribution Models

    CSIR Research Space (South Africa)

    Blanchard, R

    2012-10-01

    Full Text Available % of biodiversity importance. Anticipating potential biodiversity confl icts for future biofuel crops in South Africa: Incorporating land cover information with Species Distribution Models R BLANCHARD1, DR P O?FARRELL1 AND PROF. D RICHARDSON2 1CSIR Natural... Resources and the Environment, PO Box 320, Stellenbosch, 7599, South Africa 2Centre for Invasion Biology, Department of Botany and Zoology, Stellenbosch University, Private Bag X1, Matieland 7602, South Africa Email: rblanchard@csir.co.za ? www...

  13. Applying surrogate species presences to correct sample bias in species distribution models: a case study using the Pilbara population of the Northern Quoll

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    Shaun W. Molloy

    2017-05-01

    Full Text Available The management of populations of threatened species requires the capacity to identify areas of high habitat value. We developed a high resolution species distribution model (SDM for the endangered Pilbara northern quoll Dasyurus hallucatus, population using MaxEnt software and a combined suite of bioclimatic and landscape variables. Once common throughout much of northern Australia, this marsupial carnivore has recently declined throughout much of its former range and is listed as endangered by the IUCN. Other than the potential threats presented by climate change, and the invasive cane toad Rhinella marina (which has not yet arrived in the Pilbara. The Pilbara population is also impacted by introduced predators, pastoral and mining activities. To account for sample bias resulting from targeted surveys unevenly spread through the region, a pseudo-absence bias layer was developed from presence records of other critical weight-range non-volant mammals. The resulting model was then tested using the biomod2 package which produces ensemble models from individual models created with different algorithms. This ensemble model supported the distribution determined by the bias compensated MaxEnt model with a covariance of of 86% between models with both models largely identifying the same areas as high priority habitat. The primary product of this exercise is a high resolution SDM which corroborates and elaborates on our understanding of the ecology and habitat preferences of the Pilbara Northern Quoll population thereby improving our capacity to manage this population in the face of future threats.

  14. Key issues for the development and application of the species sensitivity distribution (SSD) model for ecological risk assessment

    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...... fractions (msPAFs) for the joint ecological risk assessment of multiple pollutants. Among the above mentioned four steps, the first two steps are paramount. In the present study, the following six key issues are discussed: (1) how to select the appropriate species, (2) how to preprocess the toxicity data...... for invertebrates. The concentration addition or response addition were discussed to calculate msPAF according to the toxic model of action (TMoA). The uncertainties of the SSD models for five heavy metals and for eight polycyclic aromatic hydrocarbons (PAHs) were performed. The comparison of the coefficients...

  15. Strengthening the link between climate, hydrological and species distribution modeling to assess the impacts of climate change on freshwater biodiversity.

    Science.gov (United States)

    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.

  16. Glacial History of a Modern Invader: Phylogeography and Species Distribution Modelling of the Asian Tiger Mosquito Aedes albopictus

    Science.gov (United States)

    Porretta, Daniele; Mastrantonio, Valentina; Bellini, Romeo; Somboon, Pradya; Urbanelli, Sandra

    2012-01-01

    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 of East Asian biota

  17. Incorporating Field Studies into Species Distribution and Climate Change Modelling: A Case Study of the Koomal Trichosurus vulpecula hypoleucus (Phalangeridae.

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    Shaun W Molloy

    Full Text Available Species distribution models (SDMs are an effective way of predicting the potential distribution of species and their response to environmental change. Most SDMs apply presence data to a relatively generic set of predictive variables such as climate. However, this weakens the modelling process by overlooking the responses to more cryptic predictive variables. In this paper we demonstrate a means by which data gathered from an intensive animal trapping study can be used to enhance SDMs by combining field data with bioclimatic modelling techniques to determine the future potential distribution for the koomal (Trichosurus vulpecula hypoleucus. The koomal is a geographically isolated subspecies of the common brushtail possum, endemic to south-western Australia. Since European settlement this taxon has undergone a significant reduction in distribution due to its vulnerability to habitat fragmentation, introduced predators and tree/shrub dieback caused by a virulent group of plant pathogens of the genus Phytophthora. An intensive field study found: 1 the home range for the koomal rarely exceeded 1 km in in length at its widest point; 2 areas heavily infested with dieback were not occupied; 3 gap crossing between patches (>400 m was common behaviour; 4 koomal presence was linked to the extent of suitable vegetation; and 5 where the needs of koomal were met, populations in fragments were demographically similar to those found in contiguous landscapes. We used this information to resolve a more accurate SDM for the koomal than that created from bioclimatic data alone. Specifically, we refined spatial coverages of remnant vegetation and dieback, to develop a set of variables that we combined with selected bioclimatic variables to construct models. We conclude that the utility value of an SDM can be enhanced and given greater resolution by identifying variables that reflect observed, species-specific responses to landscape parameters and incorporating these

  18. Forestry trial data can be used to evaluate climate-based species distribution models in predicting tree invasions

    Directory of Open Access Journals (Sweden)

    Rethabile Motloung

    2014-01-01

    Full Text Available Climate is frequently used to predict the outcome of species introductions based on the results from species distribution models (SDMs. However, despite the widespread use of SDMs for pre- and post-border risk assessments, data that can be used to validate predictions is often not available until after an invasion has occurred. Here we explore the potential for using historical forestry trials to assess the performance of climate-based SDMs. SDMs were parameterized based on the native range distribution of 36 Australian acacias, and predictions were compared against both the results of 150 years of government forestry trials, and current invasive distribution in southern Africa using true skill statistic, sensitivity and specificity. Classification tree analysis was used to evaluate why some Australian acacias failed in trials while others were successful. Predicted suitability was significantly related to the invaded range (sensitivity = 0.87 and success in forestry trials (sensitivity = 0.80, but forestry trial failures were under-predicted (specificity = 0.35. Notably, for forestry trials, the success in trials was greater for species invasive somewhere in the world. SDM predictions also indicate a considerable invasion potential of eight species that are currently naturalized but not yet widespread. Forestry trial data clearly provides a useful additional source of data to validate and refine SDMs in the context of risk assessment. Our study identified the climatic factors required for successful invasion of acacias, and accentuates the importance of integration of status elsewhere for risk assessment.

  19. Using potential distributions to explore environmental correlates of bat species richness in southern Africa: Effects of model selection and taxonomy

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    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].

  20. Seasonal Habitat Patterns of Japanese Common Squid (Todarodes Pacificus Inferred from Satellite-Based Species Distribution Models

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    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.

  1. Comparative ecology of widely distributed pelagic fish species in the North Atlantic: Implications for modelling climate and fisheries impacts

    Science.gov (United States)

    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.

  2. Combining state-and-transition simulations and species distribution models to anticipate the effects of climate change

    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.

  3. Combining state-and-transition simulations and species distribution models to anticipate the effects of climate change

    Science.gov (United States)

    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.

  4. Modeling impacts of human footprint and soil variability on the potential distribution of invasive plant species in different biomes

    Science.gov (United States)

    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.

  5. Poor transferability of species distribution models for a pelagic predator, the grey petrel, indicates contrasting habitat preferences across ocean basins.

    Science.gov (United States)

    Torres, Leigh G; Sutton, Philip J H; Thompson, David R; Delord, Karine; Weimerskirch, Henri; Sagar, Paul M; Sommer, Erica; Dilley, Ben J; Ryan, Peter G; Phillips, Richard A

    2015-01-01

    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 efforts. Although

  6. Poor transferability of species distribution models for a pelagic predator, the grey petrel, indicates contrasting habitat preferences across ocean basins.

    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

  7. Multiple glacial refugia of the low-dispersal ground beetle Carabus irregularis: molecular data support predictions of species distribution models.

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    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.

  8. The challenge of modelling and mapping the future distribution and impact of invasive alien species

    Science.gov (United States)

    Robert C. Venette

    2015-01-01

    Invasions from alien species can jeopardize the economic, environmental or social benefits derived from biological systems. Biosecurity measures seek to protect those systems from accidental or intentional introductions of species that might become injurious. Pest risk maps convey how the probability of invasion by an alien species or the potential consequences of that...

  9. Predicting species' tolerance to salinity and alkalinity using distribution data and geochemical modelling: a case study using Australian grasses.

    Science.gov (United States)

    Saslis-Lagoudakis, C Haris; Hua, Xia; Bui, Elisabeth; Moray, Camile; Bromham, Lindell

    2015-02-01

    Salt tolerance has evolved many times independently in different plant groups. One possible explanation for this pattern is that it builds upon a general suite of stress-tolerance traits. If this is the case, then we might expect a correlation between salt tolerance and other tolerances to different environmental stresses. This association has been hypothesized for salt and alkalinity tolerance. However, a major limitation in investigating large-scale patterns of these tolerances is that lists of known tolerant species are incomplete. This study explores whether species' salt and alkalinity tolerance can be predicted using geochemical modelling for Australian grasses. The correlation between taxa found in conditions of high predicted salinity and alkalinity is then assessed. Extensive occurrence data for Australian grasses is used together with geochemical modelling to predict values of pH and electrical conductivity to which species are exposed in their natural distributions. Using parametric and phylogeny-corrected tests, the geochemical predictions are evaluated using a list of known halophytes as a control, and it is determined whether taxa that occur in conditions of high predicted salinity are also found in conditions of high predicted alkalinity. It is shown that genera containing known halophytes have higher predicted salinity conditions than those not containing known halophytes. Additionally, taxa occurring in high predicted salinity tend to also occur in high predicted alkalinity. Geochemical modelling using species' occurrence data is a potentially useful approach to predict species' relative natural tolerance to challenging environmental conditions. The findings also demonstrate a correlation between salinity tolerance and alkalinity tolerance. Further investigations can consider the phylogenetic distribution of specific traits involved in these ecophysiological strategies, ideally by incorporating more complete, finer-scale geochemical information, as

  10. Predicting Species Distributions Using Record Centre Data: Multi-Scale Modelling of Habitat Suitability for Bat Roosts.

    Science.gov (United States)

    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

  11. Spatial patterns of distribution, abundance, and species diversity of small odontocetes estimated using density surface modeling with line transect sampling

    Science.gov (United States)

    Kanaji, Yu; Okazaki, Makoto; Miyashita, Tomio

    2017-06-01

    Spatial patterns of distribution, abundance, and species diversity of small odontocetes including species in the Delphinidae and Phocoenidae families were investigated using long-term dedicated sighting survey data collected between 1983 and 2006 in the North Pacific. Species diversity indices were calculated from abundance estimated using density surface modeling of line-transect data. The estimated abundance ranged from 19,521 individuals in killer whale to 1,886,022 in pantropical spotted dolphin. The predicted density maps showed that the habitats of small odontocetes corresponded well with distinct oceanic domains. Species richness was estimated to be highest between 30 and 40°N where warm- and cold-water currents converge. Simpson's Diversity Index showed latitudinal diversity gradients of decreasing species numbers toward the poles. Higher diversity was also estimated in the coastal areas and the zonal areas around 35-42°N. Coastal-offshore gradients and latitudinal gradients are known for many taxa. The zonal areas around 35°N and 40°N coincide with the Kuroshio Current and its extension and the subarctic boundary, respectively. These results suggest that the species diversity of small odontocetes primarily follows general patterns of latitudinal and longitudinal gradients, while the confluence of faunas originating in distinct water masses increases species diversify in frontal waters around 30-40°N. Population densities tended to be higher for the species inhabiting higher latitudes, but were highest for intermediate latitudes at approximately 35-40°N. According to latitudinal gradients in water temperature and biological productivity, the costs for thermoregulation will decrease in warmer low latitudes, while feeding efficiency will increase in colder high latitudes. These trade-offs could optimize population density in intermediate latitudes.

  12. Evaluating effectiveness of down-sampling for stratified designs and unbalanced prevalence in Random Forest models of tree species distributions in Nevada

    Science.gov (United States)

    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...

  13. Acid base characterization of the surface of mixed species of algae Spirulin by potentiometric titration and discrete site distribution model

    OpenAIRE

    Lima, Elizabete C. de; Masini, Jorge C.

    1999-01-01

    Acid base properties of mixed species of the microalgae Spirulina were studied by potentiometric titration in medium of 0.01 and 0.10 mols L-1 NaNO3 at 25.0±0.10 C using modified Gran functions or nonlinear regression techniques for data fitting. The discrete site distribution model was used, permitting the characterization of five classes of ionizable sites in both ionic media. This fact suggests that the chemical heterogeneity of the ionizable sites on the cell surface plays a major role on...

  14. Advances in global sensitivity analyses of demographic-based species distribution models to address uncertainties in dynamic landscapes

    Directory of Open Access Journals (Sweden)

    Ilona Naujokaitis-Lewis

    2016-07-01

    Full Text Available Developing a rigorous understanding of multiple global threats to species persistence requires the use of integrated modeling methods that capture processes which influence species distributions. Species distribution models (SDMs coupled with population dynamics models can incorporate relationships between changing environments and demographics and are increasingly used to quantify relative extinction risks associated with climate and land-use changes. Despite their appeal, uncertainties associated with complex models can undermine their usefulness for advancing predictive ecology and informing conservation management decisions. We developed a computationally-efficient and freely available tool (GRIP 2.0 that implements and automates a global sensitivity analysis of coupled SDM-population dynamics models for comparing the relative influence of demographic parameters and habitat attributes on predicted extinction risk. Advances over previous global sensitivity analyses include the ability to vary habitat suitability across gradients, as well as habitat amount and configuration of spatially-explicit suitability maps of real and simulated landscapes. Using GRIP 2.0, we carried out a multi-model global sensitivity analysis of a coupled SDM-population dynamics model of whitebark pine (Pinus albicaulis in Mount Rainier National Park as a case study and quantified the relative influence of input parameters and their interactions on model predictions. Our results differed from the one-at-time analyses used in the original study, and we found that the most influential parameters included the total amount of suitable habitat within the landscape, survival rates, and effects of a prevalent disease, white pine blister rust. Strong interactions between habitat amount and survival rates of older trees suggests the importance of habitat in mediating the negative influences of white pine blister rust. Our results underscore the importance of considering habitat

  15. Seasonally-Dynamic Presence-Only Species Distribution Models for a Cryptic Migratory Bat Impacted by Wind Energy Development.

    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.

  16. Seasonally-Dynamic Presence-Only Species Distribution Models for a Cryptic Migratory Bat Impacted by Wind Energy Development.

    Science.gov (United States)

    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.

  17. Seasonally-dynamic presence-only species distribution models for a cryptic migratory bat impacted by wind energy development

    Science.gov (United States)

    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.

  18. 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...

  19. Modelling the species distribution of flat-headed cats (Prionailurus planiceps, an endangered South-East Asian small felid.

    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

  20. Improving environmental assessments by integrating Species Sensitivity Distributions into environmental modeling: examples with two hypothetical oil spills.

    Science.gov (United States)

    Bejarano, Adriana C; Mearns, Alan J

    2015-04-15

    A three dimensional (3D) trajectory model was used to simulate oil mass balance and environmental concentrations of two 795,000 L hypothetical oil spills modeled under physical and chemical dispersion scenarios. Species Sensitivity Distributions (SSD) for Total Hydrocarbon Concentrations (THCs) were developed, and Hazard Concentrations (HC) used as levels of concern. Potential consequences to entrained water column organisms were characterized by comparing model outputs with SSDs, and obtaining the proportion of species affected (PSA) and areas with oil concentrations exceeding HC5s (Area ⩾ HC5). Under the physically-dispersed oil scenario ⩽ 77% of the oil remains on the water surface and strands on shorelines, while with the chemically-dispersed oil scenario ⩽ 67% of the oil is entrained in the water column. For every 10% increase in chemical dispersion effectiveness, the average PSA and Area ⩾ HC5 increases (range: 0.01-0.06 and 0.50-2.9 km(2), respectively), while shoreline oiling decreases (⩽ 2919 L/km). Integrating SSDs into modeling may improve understanding of scales of potential impacts to water column organisms, while providing net environmental benefit comparison of oil spill response options. Copyright © 2015 Elsevier Ltd. All rights reserved.

  1. Comparative interpretation of count, presence-absence and point methods for species distribution models

    NARCIS (Netherlands)

    Aarts, G.M; Fieberg, J.; Matthiopoulos, J.

    2012-01-01

    1.The need to understand the processes shaping population distributions has resulted in a vast increase in the diversity of spatial wildlife data, leading to the development of many novel analytical techniques that are fit-for-purpose. One may aggregate location data into spatial units (e.g. grid

  2. Coupling Satellite Data with Species Distribution and Connectivity Models as a Tool for Environmental Management and Planning in Matrix-Sensitive Species.

    Science.gov (United States)

    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.

  3. Coupling Satellite Data with Species Distribution and Connectivity Models as a Tool for Environmental Management and Planning in Matrix-Sensitive Species

    Science.gov (United States)

    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.

  4. Contribution of climate, soil, and MODIS predictors when modeling forest inventory invasive species distribution using forest inventory data

    Science.gov (United States)

    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-...

  5. Using species distribution model to estimate the wintering population size of the endangered scaly-sided merganser in China.

    Science.gov (United States)

    Zeng, Qing; Zhang, Yamian; Sun, Gongqi; Duo, Hairui; Wen, Li; Lei, Guangchun

    2015-01-01

    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.

  6. Using species distribution model to estimate the wintering population size of the endangered scaly-sided merganser in China.

    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.

  7. Testing species distribution models across space and time: high latitude butterflies and recent warming

    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...

  8. Modeling species’ realized climatic niche space and predicting their response to global warming for several western forest species with small geographic distributions

    Science.gov (United States)

    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...

  9. Effects of global changes on the climatic niche of the tick Ixodes ricinus inferred by species distribution modelling.

    Science.gov (United States)

    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

  10. Effects of global changes on the climatic niche of the tick Ixodes ricinus inferred by species distribution modelling

    Science.gov (United States)

    2013-01-01

    Background 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. Methods 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. Results 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. Conclusions 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

  11. Exploring similarities among many species distributions

    Science.gov (United States)

    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.

  12. MODELLING THE POTENTIAL DISTRIBUTION OF TREE SPECIES ON A NATIONAL SCALE IN COLOMBIA: APPLICATION TO PALICOUREA ANGUSTIFOLIA KUNTH AND PALICOUREA GUIANENSIS AUBL.

    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.

  13. Explanative power of variables used in species distribution modelling: an issue of general model transferability or niche shift in the invasive Greenhouse frog ( Eleutherodactylus planirostris)

    Science.gov (United States)

    Rödder, Dennis; Lötters, Stefan

    2010-09-01

    The use of species distribution models (SDMs) to predict potential distributions of species is steadily increasing. A necessary assumption when projecting models throughout space or time is that climatic niches are conservative, but recent findings of niche shifts during biological invasion of particular plant and animal species have indicated that this assumption is not categorically valid. One reason for observed shifts may relate to variable selection for modelling. In this study, we assess differences in climatic niches in the native and invasive ranges of the Greenhouse frog ( Eleutherodactylus planirostris). We analyze which variables are more ‘conserved’ in comparison to more ‘relaxed’ variables (i.e. subject to niche shift) and how they influence transferability of SDMs developed with Maxent on the basis of ten bioclimatic layers best describing the climatic requirements of the target species. We focus on degrees of niche similarity and conservatism using Schoener's index and Hellinger distance. Significance of results are tested with null models. Results indicate that the degrees of niche similarity and conservatism vary greatly among the predictive variables. Some shifts can be attributed to active habitat selection, whereas others apparently reflect variation in the availability of climate conditions or biotic interactions between the frogs' native and invasive ranges. Patterns suggesting active habitat selection also vary among variables. Our findings evoke considerable implications on the transferability of SDMs over space and time, which is strongly affected by the choice and number of predictors. The incorporation of ‘relaxed’ predictors not or only indirectly correlated with biologically meaningful predictors may lead to erroneous predictions when projecting SDMs. We recommend thorough assessments of invasive species' ecology for the identification biologically meaningful predictors facilitating transferability.

  14. Ecological and spatial modeling : mapping ecosystems, landscape changes, and plant species distribution in Llanos del Orinoco, Venezuela

    NARCIS (Netherlands)

    Moreno, E.J.C.

    2007-01-01

    The transformation of Llanos del Orinoco, focused on the flooding savanna, is evaluated in terms of the change and replacement of the savanna ecosystem and the plant species distribution under a Landscape Ecological approach. This research is carried out at three spatial scales: sub-continental,

  15. The influence of climatic changes on distribution pattern of six typical Kobresia species in Tibetan Plateau based on MaxEnt model and geographic information system

    Science.gov (United States)

    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.

  16. Big data of tree species distributions

    DEFF Research Database (Denmark)

    Serra-Diaz, Josep M.; Enquist, Brian J.; Maitner, Brian

    2018-01-01

    are currently available in big databases, several challenges hamper their use, notably geolocation problems and taxonomic uncertainty. Further, we lack a complete picture of the data coverage and quality assessment for open/public databases of tree occurrences. Methods: We combined data from five major......Background: Trees play crucial roles in the biosphere and societies worldwide, with a total of 60,065 tree species currently identified. Increasingly, a large amount of data on tree species occurrences is being generated worldwide: from inventories to pressed plants. While many of these data...... aggregators of occurrence data (e.g. Global Biodiversity Information Facility, Botanical Information and Ecological Network v.3, DRYFLOR, RAINBIO and Atlas of Living Australia) by creating a workflow to integrate, assess and control data quality of tree species occurrences for species distribution modeling...

  17. Species distribution models and impact factor growth in environmental journals: methodological fashion or the attraction of global change science.

    Directory of Open Access Journals (Sweden)

    Lluís Brotons

    Full Text Available In this work, I evaluate the impact of species distribution models (SDMs on the current status of environmental and ecological journals by asking the question to which degree development of SDMs in the literature is related to recent changes in the impact factors of ecological journals. The hypothesis evaluated states that research fronts are likely to attract research attention and potentially drive citation patterns, with journals concentrating papers related to the research front receiving more attention and benefiting from faster increases in their impact on the ecological literature. My results indicate a positive relationship between the number of SDM related articles published in a journal and its impact factor (IF growth during the period 2000-09. However, the percentage of SDM related papers in a journal was strongly and positively associated with the percentage of papers on climate change and statistical issues. The results support the hypothesis that global change science has been critical in the development of SDMs and that interest in climate change research in particular, rather than the usage of SDM per se, appears as an important factor behind journal IF increases in ecology and environmental sciences. Finally, our results on SDM application in global change science support the view that scientific interest rather than methodological fashion appears to be the major driver of research attraction in the scientific literature.

  18. Impacts of pesticide mixtures in European rivers as predicted by the Species Sensitivity Distribution (SSD) models and SPEAR bioindication

    Science.gov (United States)

    Jesenska, Sona; Liess, Mathias; Schäfer, Ralf; Beketov, Mikhail; Blaha, Ludek

    2013-04-01

    Species sensitivity distribution (SSD) is statistical method broadly used in the ecotoxicological risk assessment of chemicals. Originally it has been used for prospective risk assessment of single substances but nowadays it is becoming more important also in the retrospective risk assessment of mixtures, including the catchment scale. In the present work, SSD predictions (impacts of mixtures consisting of 25 pesticides; data from several catchments in Germany, France and Finland) were compared with SPEAR-pesticides, which a bioindicator index based on biological traits responsive to the effects of pesticides and post-contamination recovery. The results showed statistically significant correlations (Pearson's R, ppesticides (based on field biomonitoring observations). Comparisons of the thresholds established for the SSD and SPEAR approaches (SPEAR-pesticides=45%, i.e. LOEC level, and msPAF = 0.05 for SSD, i.e. HC5) showed that use of chronic toxicity data significantly improved the agreement between the two methods but the SPEAR-pesticides index was still more sensitive. Taken together, the validation study shows good potential of SSD models in predicting the real impacts of micropollutant mixtures on natural communities of aquatic biota.

  19. Equilibrium of Global Amphibian Species Distributions with Climate

    Science.gov (United States)

    Munguía, Mariana; Rahbek, Carsten; Rangel, Thiago F.; Diniz-Filho, Jose Alexandre F.; Araújo, Miguel B.

    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 complete lineage across its entire distribution. We measure departures of equilibrium with contemporary climate for the distributions of the world amphibian species. Specifically, we fitted bioclimatic envelopes for 5544 species using three presence-only models. We then measured the proportion of the modeled envelope that is currently occupied by the species, as a metric of equilibrium of species distributions with climate. The assumption was that the greater the difference between modeled bioclimatic envelope and the occupied distribution, the greater the likelihood that species distribution would not be at equilibrium with contemporary climate. On average, amphibians occupied 30% to 57% of their potential distributions. Although patterns differed across regions, there were no significant differences among lineages. Species in the Neotropic, Afrotropics, Indo-Malay, and Palaearctic occupied a smaller proportion of their potential distributions than species in the Nearctic, Madagascar, and Australasia. We acknowledge that our models underestimate non equilibrium, and discuss potential reasons for the observed patterns. From a modeling perspective our results support the view that at global scale bioclimatic envelope models might perform similarly across lineages but differently across regions. PMID:22511938

  20. Predicting species distributions for conservation decisions.

    Science.gov (United States)

    Guisan, Antoine; Tingley, Reid; Baumgartner, John B; Naujokaitis-Lewis, Ilona; Sutcliffe, Patricia R; Tulloch, Ayesha I T; Regan, Tracey J; Brotons, Lluis; McDonald-Madden, Eve; Mantyka-Pringle, Chrystal; Martin, Tara G; Rhodes, Jonathan R; Maggini, Ramona; Setterfield, Samantha A; Elith, Jane; Schwartz, Mark W; Wintle, Brendan A; Broennimann, Olivier; Austin, Mike; Ferrier, Simon; Kearney, Michael R; Possingham, Hugh P; Buckley, Yvonne M

    2013-12-01

    Species distribution models (SDMs) are increasingly proposed to support conservation decision making. However, evidence of SDMs supporting solutions for on-ground conservation problems is still scarce in the scientific literature. Here, we show that successful examples exist but are still largely hidden in the grey literature, and thus less accessible for analysis and learning. Furthermore, the decision framework within which SDMs are used is rarely made explicit. Using case studies from biological invasions, identification of critical habitats, reserve selection and translocation of endangered species, we propose that SDMs may be tailored to suit a range of decision-making contexts when used within a structured and transparent decision-making process. To construct appropriate SDMs to more effectively guide conservation actions, modellers need to better understand the decision process, and decision makers need to provide feedback to modellers regarding the actual use of SDMs to support conservation decisions. This could be facilitated by individuals or institutions playing the role of 'translators' between modellers and decision makers. We encourage species distribution modellers to get involved in real decision-making processes that will benefit from their technical input; this strategy has the potential to better bridge theory and practice, and contribute to improve both scientific knowledge and conservation outcomes. © 2013 The Authors. Ecology Letters published by John Wiley & Sons Ltd and CNRS.

  1. Assessing environmental attributes and effects of climate change on Sphagnum peatland distributions in North America using single- and multi-species models.

    Science.gov (United States)

    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.

  2. Use of Anecdotal Occurrence Data in Species Distribution Models: An Example Based on the White-Nosed Coati (Nasua narica in the American Southwest

    Directory of Open Access Journals (Sweden)

    James N. Stuart

    2013-04-01

    Full Text Available Species distributions are usually inferred from occurrence records. However, these records are prone to errors in spatial precision and reliability. Although influence of spatial errors has been fairly well studied, there is little information on impacts of poor reliability. Reliability of an occurrence record can be influenced by characteristics of the species, conditions during the observation, and observer’s knowledge. Some studies have advocated use of anecdotal data, while others have advocated more stringent evidentiary standards such as only accepting records verified by physical evidence, at least for rare or elusive species. Our goal was to evaluate the influence of occurrence records with different reliability on species distribution models (SDMs of a unique mammal, the white-nosed coati (Nasua narica in the American Southwest. We compared SDMs developed using maximum entropy analysis of combined bioclimatic and biophysical variables and based on seven subsets of occurrence records that varied in reliability and spatial precision. We found that the predicted distribution of the coati based on datasets that included anecdotal occurrence records were similar to those based on datasets that only included physical evidence. Coati distribution in the American Southwest was predicted to occur in southwestern New Mexico and southeastern Arizona and was defined primarily by evenness of climate and Madrean woodland and chaparral land-cover types. Coati distribution patterns in this region suggest a good model for understanding the biogeographic structure of range margins. We concluded that occurrence datasets that include anecdotal records can be used to infer species distributions, providing such data are used only for easily-identifiable species and based on robust modeling methods such as maximum entropy. Use of a reliability rating system is critical for using anecdotal data.

  3. Not to put too fine a point on it - does increasing precision of geographic referencing improve species distribution models for a wide-ranging migratory bat?

    Science.gov (United States)

    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.

  4. Evaluation of Scat Deposition Transects versus Radio Telemetry for Developing a Species Distribution Model for a Rare Desert Carnivore, the Kit Fox.

    Directory of Open Access Journals (Sweden)

    Steven J Dempsey

    Full Text Available 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

  5. 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.

  6. Modelling and mapping the local distribution of representative species on the Le Danois Bank, El Cachucho Marine Protected Area (Cantabrian Sea)

    Science.gov (United States)

    García-Alegre, Ana; Sánchez, Francisco; Gómez-Ballesteros, María; Hinz, Hilmar; Serrano, Alberto; Parra, Santiago

    2014-08-01

    The management and protection of potentially vulnerable species and habitats require the availability of detailed spatial data. However, such data are often not readily available in particular areas that are challenging for sampling by traditional sampling techniques, for example seamounts. Within this study habitat modelling techniques were used to create predictive maps of six species of conservation concern for the Le Danois Bank (El Cachucho Marine Protected Area in the South of the Bay of Biscay). The study used data from ECOMARG multidisciplinary surveys that aimed to create a representative picture of the physical and biological composition of the area. Classical fishing gear (otter trawl and beam trawl) was used to sample benthic communities that inhabit sedimentary areas, and non-destructive visual sampling techniques (ROV and photogrammetric sled) were used to determine the presence of epibenthic macrofauna in complex and vulnerable habitats. Multibeam echosounder data, high-resolution seismic profiles (TOPAS system) and geological data from box-corer were used to characterize the benthic terrain. ArcGIS software was used to produce high-resolution maps (75×75 m2) of such variables in the entire area. The Maximum Entropy (MAXENT) technique was used to process these data and create Habitat Suitability maps for six species of special conservation interest. The model used seven environmental variables (depth, rugosity, aspect, slope, Bathymetric Position Index (BPI) in fine and broad scale and morphosedimentary characteristics) to identify the most suitable habitats for such species and indicates which environmental factors determine their distribution. The six species models performed highly significantly better than random (pthe Curve (AUC) values were tested. This indicates that the environmental variables chosen are relevant to distinguish the distribution of these species. The Jackknife test estimated depth to be the key factor structuring their

  7. Plant Species Sensitivity Distributions for ozone exposure

    International Nuclear Information System (INIS)

    Goethem, T.M.W.J. van; Azevedo, L.B.; Zelm, R. van; Hayes, F.; Ashmore, M.R.; Huijbregts, M.A.J.

    2013-01-01

    This study derived Species Sensitivity Distributions (SSD), representing a cumulative stressor-response distribution based on single-species sensitivity data, for ozone exposure on natural vegetation. SSDs were constructed for three species groups, i.e. trees, annual grassland and perennial grassland species, using species-specific exposure–response data. The SSDs were applied in two ways. First, critical levels were calculated for each species group and compared to current critical levels for ozone exposure. Second, spatially explicit estimates of the potentially affected fraction of plant species in Northwestern Europe were calculated, based on ambient ozone concentrations. We found that the SSD-based critical levels were lower than for the current critical levels for ozone exposure, with conventional critical levels for ozone relating to 8–20% affected plant species. Our study shows that the SSD concept can be successfully applied to both derive critical ozone levels and estimate the potentially affected species fraction of plant communities along specific ozone gradients. -- Highlights: ► Plant Species Sensitivity Distributions were derived for ozone exposure. ► Annual grassland species, as a species assemblage, tend to be most sensitive to ozone. ► Conventional critical levels for ozone relate to 8–20% affected plant species. ► The affected fraction of plant species for current ozone exposure in Northwestern Europe is estimated. -- Species Sensitivity Distributions offer opportunities in ozone risk assessment to both derive critical levels and estimate the affected fraction of a plant community

  8. Spatial statistics for modeling of abundance and distribution of wildlife species in the Masai Mara ecosystem, Kenya

    NARCIS (Netherlands)

    Khaemba, W.M.; Stein, A.

    2001-01-01

    This study illustrates the use of modern statistical procedures for better wildlife management by addressing three key issues: determination of abundance, modeling of animal distributions and variability of diversity in space and time. Prior information in Markov Chain Monte Carlo (MCMC) methods is

  9. Relating species abundance distributions to species-area curves in two Mediterranean-type shrublands

    Science.gov (United States)

    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.

  10. Tiarosporella species: Distribution and significance

    Directory of Open Access Journals (Sweden)

    Karadžić Dragan

    2003-01-01

    Full Text Available The genus Tiarosporella consists of eight species of which four occur on conifers. These fungi differ in conidial size and in the form of appendages that occur on the distal end of the conidia (pycnospore. In Europe only the two species have been recorded. T. parca occurs on the species of the genus Picea (P. abies and P. omorika, while T. durmitorensis infests fir (Abies alba. T. parca can be considered, as an endophyte, and it sporulates only when the needles die due to a stress or old age. T. durmitorensis is a very aggressive pathogen colonizing fir needles of all ages. Together with other fungi, it leads to tree death. So far, T. durmitotensis has been found only in European silver fir stands in the National Park "Durmitor" and in the National Park "Biogradska Gora".

  11. Do pseudo-absence selection strategies influence species distribution models and their predictions? An information-theoretic approach based on simulated data

    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

  12. Integrating local pastoral knowledge, participatory mapping, and species distribution modeling for risk assessment of invasive rubber vine (Cryptostegia grandiflora in Ethiopia's Afar region

    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

  13. Integrating local pastoral knowledge, participatory mapping, and species distribution modeling for risk assessment of invasive rubber vine (Cryptostegia grandiflora) in Ethiopia’s Afar region

    Science.gov (United States)

    Luizza, Matthew; Wakie, Tewodros; Evangelista, Paul; Jarnevich, Catherine S.

    2016-01-01

    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 ecological

  14. Combining a Climatic Niche Model of an Invasive Fungus with Its Host Species Distributions to Identify Risks to Natural Assets: Puccinia psidii Sensu Lato in Australia

    Science.gov (United States)

    Kriticos, Darren J.; Morin, Louise; Leriche, Agathe; Anderson, Robert C.; Caley, Peter

    2013-01-01

    Puccinia psidii sensu lato (s.l.) is an invasive rust fungus threatening a wide range of plant species in the family Myrtaceae. Originating from Central and South America, it has invaded mainland USA and Hawai'i, parts of Asia and Australia. We used CLIMEX to develop a semi-mechanistic global climatic niche model based on new data on the distribution and biology of P. psidii s.l. The model was validated using independent distribution data from recently invaded areas in Australia, China and Japan. We combined this model with distribution data of its potential Myrtaceae host plant species present in Australia to identify areas and ecosystems most at risk. Myrtaceaeous species richness, threatened Myrtaceae and eucalypt plantations within the climatically suitable envelope for P. psidii s.l in Australia were mapped. Globally the model identifies climatically suitable areas for P. psidii s.l. throughout the wet tropics and sub-tropics where moist conditions with moderate temperatures prevail, and also into some cool regions with a mild Mediterranean climate. In Australia, the map of species richness of Myrtaceae within the P. psidii s.l. climatic envelope shows areas where epidemics are hypothetically more likely to be frequent and severe. These hotspots for epidemics are along the eastern coast of New South Wales, including the Sydney Basin, in the Brisbane and Cairns areas in Queensland, and in the coastal region from the south of Bunbury to Esperance in Western Australia. This new climatic niche model for P. psidii s.l. indicates a higher degree of cold tolerance; and hence a potential range that extends into higher altitudes and latitudes than has been indicated previously. The methods demonstrated here provide some insight into the impacts an invasive species might have within its climatically suited range, and can help inform biosecurity policies regarding the management of its spread and protection of valued threatened assets. PMID:23704988

  15. The roots of diversity: below ground species richness and rooting distributions in a tropical forest revealed by DNA barcodes and inverse modeling.

    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.

  16. SDMtoolbox 2.0: the next generation Python-based GIS toolkit for landscape genetic, biogeographic and species distribution model analyses

    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.

  17. Using occupancy modeling and logistic regression to assess the distribution of shrimp species in lowland streams, Costa Rica: Does regional groundwater create favorable habitat?

    Science.gov (United States)

    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.

  18. 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.

  19. Application of Species distribution models and River2D to assess riverine ecosystems: A case of Sicyopterus japonicus in Datuan stream

    Science.gov (United States)

    Chu, Po-Ting

    2017-04-01

    Riverine ecosystems are usually under the risk of anthropogenic contamination and climate change. With an eye to improving this situation, it is imperative to formulate corresponding policies. To provide the government with better policy-making standard, understanding of the future development of the ecosystems is quite necessary. Species distribution models (SDMs) is an ideal tool to understand the relationship between environmental variables and species occurrence.There are various species distribution models (SDMs) that have been developed and used in stream ecology. However, consensus on the selection among different models has not yet been reached. The results of inappropriate model selection include increasing uncertainty and high occurrence of prediction errors. How to choose the model that best fits the scenario among many is, therefore, of paramount importance. This study collects river channel data and Sicyopterus Japonic data in Datuan stream. We uses River2D as an efficient tool for simulating the two-dimensional flow condition of a stream segment. Then we combine six SDMs with the outputs of River2D and quantify the relationship between environmental variables and species occurrence by using six SDMs, which are respectively generalized linear model (GLM), generalized additive model (GAM), random forest model (RF), support vector machine (SVM), artificial neural network model (ANN), and ensemble model (the average of other five SDMs). We randomly split the fish data to train(70%) and validate(30%), and each model repeats this step for 1000 times. Finally, through Akaike information criterion, root-mean-square error and Kullback-Leibler divergence, we can know which model has better performance. The results demonstrated that the accuracy of River2D is greatly affected by measurement , and that Sicyopterus Japonic likes areas where the water is deep. Moreover, through the result, it is observed that ensemble model outperforms the others. Therefore, next

  20. Spatial factor analysis: a new tool for estimating joint species distributions and correlations in species range

    DEFF Research Database (Denmark)

    Thorson, James T.; Scheuerell, Mark D.; Shelton, Andrew O.

    2015-01-01

    1. Predicting and explaining the distribution and density of species is one of the oldest concerns in ecology. Species distributions can be estimated using geostatistical methods, which estimate a latent spatial variable explaining observed variation in densities, but geostatistical methods may...... be imprecise for species with low densities or few observations. Additionally, simple geostatistical methods fail to account for correlations in distribution among species and generally estimate such cross-correlations as a post hoc exercise. 2. We therefore present spatial factor analysis (SFA), a spatial...... model for estimating a low-rank approximation to multivariate data, and use it to jointly estimate the distribution of multiple species simultaneously. We also derive an analytic estimate of cross-correlations among species from SFA parameters. 3. As a first example, we show that distributions for 10...

  1. Species distribution models of two critically endangered deep-sea octocorals reveal fishing impacts on vulnerable marine ecosystems in central Mediterranean Sea.

    Science.gov (United States)

    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.

  2. Ecological effects of the invasive giant madagascar day gecko on endemic mauritian geckos: applications of binomial-mixture and species distribution models.

    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.

  3. Ecological effects of the invasive giant madagascar day gecko on endemic mauritian geckos: applications of binomial-mixture and species distribution models.

    Science.gov (United States)

    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.

  4. Near term climate projections for invasive species distributions

    Science.gov (United States)

    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.

  5. Equilibrium of global amphibian species distributions with climate

    DEFF Research Database (Denmark)

    Munguí­a, Mariana; Rahbek, Carsten; Rangel, Thiago F.

    2012-01-01

    of their potential distributions than species in the Nearctic, Madagascar, and Australasia. We acknowledge that our models underestimate non equilibrium, and discuss potential reasons for the observed patterns. From a modeling perspective our results support the view that at global scale bioclimatic envelope models...

  6. 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

  7. Predicting criteria continuous concentrations of 34 metals or metalloids by use of quantitative ion character-activity relationships–species sensitivity distributions (QICAR–SSD) model

    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

  8. Linking land cover and species distribution models to project potential ranges of malaria vectors: an example using Anopheles arabiensis in Sudan and Upper Egypt

    Directory of Open Access Journals (Sweden)

    Fuller Douglas O

    2012-08-01

    Full Text Available Abstract Background Anopheles arabiensis is a particularly opportunistic feeder and efficient vector of Plasmodium falciparum in Africa and may invade areas outside its normal range, including areas separated by expanses of barren desert. The purpose of this paper is to demonstrate how spatial models can project future irrigated cropland and potential, new suitable habitat for vectors such as An. arabiensis. Methods Two different but complementary spatial models were linked to demonstrate their synergy for assessing re-invasion potential of An. arabiensis into Upper Egypt as a function of irrigated cropland expansion by 2050. The first model (The Land Change Modeler was used to simulate changes in irrigated cropland using a Markov Chain approach, while the second model (MaxEnt uses species occurrence points, land cover and other environmental layers to project probability of species presence. Two basic change scenarios were analysed, one involving a more conservative business-as-usual (BAU assumption and second with a high probability of desert-to-cropland transition (Green Nile to assess a broad range of potential outcomes by 2050. Results The results reveal a difference of 82,000 sq km in potential An. arabiensis range between the BAU and Green Nile scenarios. The BAU scenario revealed a highly fragmented set of small, potential habitat patches separated by relatively large distances (maximum distance = 64.02 km, mean = 12.72 km, SD = 9.92, while the Green Nile scenario produced a landscape characterized by large patches separated by relatively shorter gaps (maximum distance = 49.38, km, mean = 4.51 km, SD = 7.89 that may be bridged by the vector. Conclusions This study provides a first demonstration of how land change and species distribution models may be linked to project potential changes in vector habitat distribution and invasion potential. While gaps between potential habitat patches remained large in the

  9. Linking land cover and species distribution models to project potential ranges of malaria vectors: an example using Anopheles arabiensis in Sudan and Upper Egypt.

    Science.gov (United States)

    Fuller, Douglas O; Parenti, Michael S; Hassan, Ali N; Beier, John C

    2012-08-06

    Anopheles arabiensis is a particularly opportunistic feeder and efficient vector of Plasmodium falciparum in Africa and may invade areas outside its normal range, including areas separated by expanses of barren desert. The purpose of this paper is to demonstrate how spatial models can project future irrigated cropland and potential, new suitable habitat for vectors such as An. arabiensis. Two different but complementary spatial models were linked to demonstrate their synergy for assessing re-invasion potential of An. arabiensis into Upper Egypt as a function of irrigated cropland expansion by 2050. The first model (The Land Change Modeler) was used to simulate changes in irrigated cropland using a Markov Chain approach, while the second model (MaxEnt) uses species occurrence points, land cover and other environmental layers to project probability of species presence. Two basic change scenarios were analysed, one involving a more conservative business-as-usual (BAU) assumption and second with a high probability of desert-to-cropland transition (Green Nile) to assess a broad range of potential outcomes by 2050. The results reveal a difference of 82,000 sq km in potential An. arabiensis range between the BAU and Green Nile scenarios. The BAU scenario revealed a highly fragmented set of small, potential habitat patches separated by relatively large distances (maximum distance = 64.02 km, mean = 12.72 km, SD = 9.92), while the Green Nile scenario produced a landscape characterized by large patches separated by relatively shorter gaps (maximum distance = 49.38, km, mean = 4.51 km, SD = 7.89) that may be bridged by the vector. This study provides a first demonstration of how land change and species distribution models may be linked to project potential changes in vector habitat distribution and invasion potential. While gaps between potential habitat patches remained large in the Green Nile scenario, the models reveal large areas of future

  10. DNA barcodes and species distribution models evaluate threats of global climate changes to genetic diversity: a case study from Nanorana parkeri (Anura: Dicroglossidae).

    Science.gov (United States)

    Zhou, Wei-wei; Zhang, Bao-lin; Chen, Hong-man; Jin, Jie-qiong; Yang, Jun-xiao; Wang, Yun-yu; Jiang, Ke; Murphy, Robert W; Zhang, Ya-ping; Che, Jing

    2014-01-01

    Anthropogenic global climate changes are one of the greatest threats to biodiversity. Distribution modeling can predict the effects of climate changes and potentially their effects on genetic diversity. DNA barcoding quickly identifies patterns of genetic diversity. As a case study, we use DNA barcodes and distribution models to predict threats under climate changes in the frog Nanorana parkeri, which is endemic to the Qinghai-Tibetan Plateau. Barcoding identifies major lineages W and E. Lineage W has a single origin in a refugium and Lineage E derives from three refugia. All refugia locate in river valleys and each greatly contributes to the current level of intraspecific genetic diversity. Species distribution models suggest that global climate changes will greatly influence N. parkeri, especially in the level of genetic diversity, because two former refugia will fail to provide suitable habitat. Our pipeline provides a novel application of DNA barcoding and has important implications for the conservation of biodiversity in southern areas of the Qinghai-Tibetan Plateau.

  11. DNA barcodes and species distribution models evaluate threats of global climate changes to genetic diversity: a case study from Nanorana parkeri (Anura: Dicroglossidae.

    Directory of Open Access Journals (Sweden)

    Wei-wei Zhou

    Full Text Available Anthropogenic global climate changes are one of the greatest threats to biodiversity. Distribution modeling can predict the effects of climate changes and potentially their effects on genetic diversity. DNA barcoding quickly identifies patterns of genetic diversity. As a case study, we use DNA barcodes and distribution models to predict threats under climate changes in the frog Nanorana parkeri, which is endemic to the Qinghai-Tibetan Plateau. Barcoding identifies major lineages W and E. Lineage W has a single origin in a refugium and Lineage E derives from three refugia. All refugia locate in river valleys and each greatly contributes to the current level of intraspecific genetic diversity. Species distribution models suggest that global climate changes will greatly influence N. parkeri, especially in the level of genetic diversity, because two former refugia will fail to provide suitable habitat. Our pipeline provides a novel application of DNA barcoding and has important implications for the conservation of biodiversity in southern areas of the Qinghai-Tibetan Plateau.

  12. Comparative ecology of widely distributed pelagic fish species in the North Atlantic: Implications for modelling climate and fisheries impacts

    DEFF Research Database (Denmark)

    Trenkel, V.M.; Huse, G.; MacKenzie, Brian

    2014-01-01

    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...

  13. Mistaking geography for biology: inferring processes from species distributions.

    Science.gov (United States)

    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.

  14. species composition, relative abundance and distribution

    African Journals Online (AJOL)

    Preferred Customer

    However, wet season had an effect on the avian abundance in eucalyptus plantation. (t=2.952, P <0.05). Eucalyptus plantation, soil ... distribution of bird species in the country is quite complex (Urban, 1980). Most of the the birds that .... size, shape, colour, songs and calls were considered as important parameters (Afework.

  15. Node-based analysis of species distributions

    DEFF Research Database (Denmark)

    Borregaard, Michael Krabbe; Rahbek, Carsten; Fjeldså, Jon

    2014-01-01

    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...

  16. Prioritizing West African medicinal plants for conservation and sustainable extraction studies based on market surveys and species distribution models

    NARCIS (Netherlands)

    van Andel, T.R.; Croft, S.; van Loon, E.E.; Quiroz, D.; Towns, A.M.; Raes, N.

    2015-01-01

    Sub-Saharan African human populations rely heavily on wild-harvested medicinal plants for their health. The trade in herbal medicine provides an income for many West African people, but little is known about the effects of commercial extraction on wild plant populations. Detailed distribution maps

  17. Prioritizing West African medicinal plants for conservation and sustainable extraction studies based on market surveys and species distribution models.

    NARCIS (Netherlands)

    Andel, van T.R.; Croft, S.; Loon, van E.E.; Quiroz Villarreal, D.K.; Towns, A.M.; Raes, N.

    2015-01-01

    Sub-Saharan African human populations rely heavily on wild-harvested medicinal plants for their health. The trade in herbal medicine provides an income for many West African people, but little is known about the effects of commercial extraction on wild plant populations. Detailed distribution maps

  18. Analyzing the hydrological impact of afforestation and tree species in two catchments with contrasting soil properties using the spatially distributed model MIKE SHE SWET

    DEFF Research Database (Denmark)

    Sonnenborg, Torben Obel; Christiansen, Jesper Riis; Pang, Bo

    2017-01-01

    Groundwater depletion occurs at a global scale but requires regional strategies for sustainable management of freshwater resources. In Denmark the groundwater quantity and quality is under pressure, and forested areas are considered to protect groundwater reservoirs. However, little is known on how...... 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...... with an energy-based description of evaporation and transpiration processes (MIKE SHE SWET) was used. Large scale hydrological models were established for two geologically (sandy/clayey) contrasting catchments in Denmark; Skjern and Lejre catchments. Land use scenarios were defined with forest vegetation...

  19. Semi-mechanistic partial buffer approach to modeling pH, the buffer properties, and the distribution of ionic species in complex solutions.

    Science.gov (United States)

    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.

  20. Predicting species distribution combining multi-scale drivers

    Directory of Open Access Journals (Sweden)

    Alice Fournier

    2017-10-01

    Full Text Available Species Distribution Models (SDMs are often used to predict the potential range of invasive species. Unfortunately, most studies do not evaluate variables relevance before selecting them to fit their models. Moreover, multiple variables such as climate and land use may drive species distribution at different spatial scales but most studies either use a single type of drivers, or combine multiple types without respecting their operating scale. We propose a three steps framework to overcome this limitation. First, use SDMs to select the most relevant climatic variables to predict a given species distribution, at continental scale. Then, characterize the species-habitat relationships, at a local scale, to produce species and area specific habitat filters. Finally, combine both information, each obtained at a relevant scale, to refine climatic predictions according to habitat suitability. We illustrate this framework with 14,794 Asian hornet (Vespa velutina nigrithorax records. We show that integrating multiple drivers, while still respecting their scale of effect, produced a potential range 55.9% smaller than that predicted using the climatic model alone, suggesting a systematic overestimation in many published predictions. This general framework illustrated by a well-documented invasive species is applicable to other taxa and scenarios of future climate and land-cover changes.

  1. 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.

  2. How Gaussian competition leads to lumpy or uniform species distributions

    DEFF Research Database (Denmark)

    Pigolotti, Simone; Lopez, Cristóbal; Hernandez-Garcia, Emilio

    2010-01-01

    A central model in theoretical ecology considers the competition of a range of species for a broad spectrum of resources. Recent studies have shown that essentially two different outcomes are possible. Either the species surviving competition are more or less uniformly distributed over the resource...... spectrum, or their distribution is “lumped” (or “clumped”), consisting of clusters of species with similar resource use that are separated by gaps in resource space. Which of these outcomes will occur crucially depends on the competition kernel, which reflects the shape of the resource utilization pattern...... of the competing species. Most models considered in the literature assume a Gaussian competition kernel. This is unfortunate, since predictions based on such a Gaussian assumption are not robust. In fact, Gaussian kernels are a border case scenario, and slight deviations from this function can lead to either...

  3. Anticipating potential biodiversity conflicts for future biofuel crops in South Africa: incorporating spatial filters with species distribution models

    CSIR Research Space (South Africa)

    Blanchard, R

    2014-04-01

    Full Text Available for biodiversity (Evans et al., 2010, Wilcove et al., 2000), as a wider 17 range of land types can be brought into production when compared to conventional 18 agricultural areas (Beringer et al., 2011, Field et al., 2007, Righelato & Spracklen, 2007). 19 One... modelling (SDM) techniques that rely on 3 presence-only records have been shown to provide a useful screening tool to determine 4 suitable climatic environments for potential dedicated energy crops (Evans et al., 2010). The 5 recent use of SDMs...

  4. Predicting criteria continuous concentrations of 34 metals or metalloids by use of quantitative ion character-activity relationships-species sensitivity distributions (QICAR-SSD) model.

    Science.gov (United States)

    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.

  5. Species Composition of Sand Flies (Diptera: Psychodidae) and Modeling the Spatial Distribution of Main Vectors of Cutaneous Leishmaniasis in Hormozgan Province, Southern Iran.

    Science.gov (United States)

    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.

  6. Attenuation of species abundance distributions by sampling

    Science.gov (United States)

    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

  7. Making species distribution models available on the Web for reuse in biodiversity experiments: Euterpe edulis species case study / Modelos de distribuição de espécies disponíveis na Web para reutilização em experimentos de biodiversidade: Estudo de caso com a espécie Euterpe edulis

    Directory of Open Access Journals (Sweden)

    Karla Donato Fook

    2009-04-01

    Full Text Available Currently, biodiversity conservation is one of the most urgent and important themes. Biodiversityresearchers use species distribution models to make inferences about species occurrences and locations.These models are fundamental for fauna and flora preservation, as well as for decision making processesfor urban and regional planning and development. Species distribution modelling tools use largebiodiversity datasets which are globally distributed, can be in different computational platforms, and are hard to access and manipulate. The scientific community needs infrastructures in which biodiversityresearchers can collaborate and share knowledge. In this context, we present a computationalenvironment that supports the collaboration in species distribution modelling network on the Web. Thisenvironment is based on a modelling experiment catalogue and on a set of geoweb services, the WebBiodiversity Collaborative Modelling Services – WBCMS.

  8. DISENTANGLING INTERPOLATION AND EXTRAPOLATION UNCERTAINTIES IN SPECIES DISTRIBUTION MODELS: A NOVEL VISUALIZATION TECHNIQUE FOR THE SPATIAL VARIATION OF PREDICTOR VARIABLE COLINEARITY

    Directory of Open Access Journals (Sweden)

    Dennis Rödder

    2012-08-01

    Full Text Available Abstract. - Species distribution models (SDMs are increasingly used in many scientific fields, with most studies requiring the application of the SDM to predict the likelihood of occurrence and/or environmental suitability in locations and time periods outside the range of the data set used to fit the model. Uncertainty in the quality of SDM predictions caused by errors of interpolation and extrapolation has been acknowledged for a long time, but the explicit consideration of the magnitude of such errors is, as yet, uncommon. Among other issues, the spatial variation in the colinearity of the environmental predictor variables used in the development of SDMs may cause misleading predictions when applying SDMs to novel locations and time periods. In this paper, we provide a framework for the spatially explicit identification of areas prone to errors caused by changes in the inter-correlation structure (i.e. their colinearity of environmental predictors used for SDM development. The proposed method is compatible with all SDM algorithms currently employed, and expands the available toolbox for assessing the uncertainties raising from SDM predictions. We provide an implementation of the analysis as a script for the R statistical platform in an online appendix.

  9. Cartograms tool to represent spatial uncertainty in species distribution

    Directory of Open Access Journals (Sweden)

    Duccio Rocchini

    2017-02-01

    Full Text Available Species distribution models have become an important tool for biodiversity monitoring. Like all statistical modelling techniques developed based on field data, they are prone to uncertainty due to bias in the sampling (e.g. identification, effort, detectability. In this study, we explicitly quantify and map the uncertainty derived from sampling effort bias. With that aim, we extracted data from the widely used GBIF dataset to map this semantic bias using cartograms.

  10. Gridded Species Distribution, Version 1: Global Amphibians Presence Grids

    Data.gov (United States)

    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...

  11. Quantifying the degree of bias from using county-scale data in species distribution modeling: Can increasing sample size or using county-averaged environmental data reduce distributional overprediction?

    Science.gov (United States)

    Collins, Steven D; Abbott, John C; McIntyre, Nancy E

    2017-08-01

    Citizen-science databases have been used to develop species distribution models (SDMs), although many taxa may be only georeferenced to county. It is tacitly assumed that SDMs built from county-scale data should be less precise than those built with more accurate localities, but the extent of the bias is currently unknown. Our aims in this study were to illustrate the effects of using county-scale data on the spatial extent and accuracy of SDMs relative to true locality data and to compare potential compensatory methods (including increased sample size and using overall county environmental averages rather than point locality environmental data). To do so, we developed SDMs in maxent with PRISM-derived BIOCLIM parameters for 283 and 230 species of odonates (dragonflies and damselflies) and butterflies, respectively, for five subsets from the OdonataCentral and Butterflies and Moths of North America citizen-science databases: (1) a true locality dataset, (2) a corresponding sister dataset of county-centroid coordinates, (3) a dataset where the average environmental conditions within each county were assigned to each record, (4) a 50/50% mix of true localities and county-centroid coordinates, and (5) a 50/50% mix of true localities and records assigned the average environmental conditions within each county. These mixtures allowed us to quantify the degree of bias from county-scale data. Models developed with county centroids overpredicted the extent of suitable habitat by 15% on average compared to true locality models, although larger sample sizes (>100 locality records) reduced this disparity. Assigning county-averaged environmental conditions did not offer consistent improvement, however. Because county-level data are of limited value for developing SDMs except for species that are widespread and well collected or that inhabit regions where small, climatically uniform counties predominate, three means of encouraging more accurate georeferencing in citizen

  12. Estimating Invasion Success by Non-Native Trees in a National Park Combining WorldView-2 Very High Resolution Satellite Data and Species Distribution Models

    Directory of Open Access Journals (Sweden)

    Antonio T. Monteiro

    2017-01-01

    Full Text Available Invasion by non-native tree species is an environmental and societal challenge requiring predictive tools to assess invasion dynamics. The frequent scale mismatch between such tools and on-ground conservation is currently limiting invasion management. This study aimed to reduce these scale mismatches, assess the success of non-native tree invasion and determine the environmental factors associated to it. A hierarchical scaling approach combining species distribution models (SDMs and satellite mapping at very high resolution (VHR was developed to assess invasion by Acacia dealbata in Peneda-Gerês National Park, the only national park in Portugal. SDMs were first used to predict the climatically suitable areas for A. dealdata and satellite mapping with the random-forests classifier was then applied to WorldView-2 very-high resolution imagery to determine whether A. dealdata had actually colonized the predicted areas (invasion success. Environmental attributes (topographic, disturbance and canopy-related differing between invaded and non-invaded vegetated areas were then analyzed. The SDM results indicated that most (67% of the study area was climatically suitable for A. dealbata invasion. The onset of invasion was documented to 1905 and satellite mapping highlighted that 12.6% of study area was colonized. However, this species had only colonized 62.5% of the maximum potential range, although was registered within 55.6% of grid cells that were considerable unsuitable. Across these areas, the specific success rate of invasion was mostly below 40%, indicating that A. dealbata invasion was not dominant and effective management may still be possible. Environmental attributes related to topography (slope, canopy (normalized difference vegetation index (ndvi, land surface albedo and disturbance (historical burnt area differed between invaded and non-invaded vegetated area, suggesting that landscape attributes may alter at specific locations with Acacia

  13. Review: Ecological distribution of Dipterocarpaceae species in Indonesia

    Directory of Open Access Journals (Sweden)

    PURWANINGSIH

    2004-07-01

    Full Text Available Dipterocarpaceae is one of the biggest family with >500 species in the world, and most of dipterocarps population are grown in Indonesia which have high economical value of wood. One of the most important value from dipterocarps species is high on endemicities; there are up to 128 species (53.78% from 238 dipterocarps species in Indonesia. Distribution of dipterocarps species would be affected by some factors especially edaphic, climate, and altitude. In Indonesia the dipterocarps species distribution could be shown from islands groups, number of species and forest types. Based on the observation of herbarium collection in Herbarium Bogoriense the distribution of the most dipterocarps species was in the altitude of 0-500 m and 500-1000 m on the dipterocarps forest type. Kalimantan and Sumatra were the two bigger islands with have the dipterocarps species distributed relatively high on population and species.

  14. Rainfall and temperature affect tree species distributions in Ghana

    NARCIS (Netherlands)

    Amissah, L.; Mohren, G.M.J.; Bongers, F.; Hawthorne, W.D.; Poorter, L.

    2014-01-01

    We evaluated the relative importance of annual rainfall, temperature and their seasonality to tree species distribution in Ghana. We used species presence/absence data from 2505 1-ha plots systematically distributed over Ghana's forests. Logistic regression was used to determine species responses to

  15. Predicting the past distribution of species climatic niches

    DEFF Research Database (Denmark)

    Nogues, David Bravo

    2009-01-01

    Predicting past distributions of species climatic niches, hindcasting, by using climate envelope models (CEMs) is emerging as an exciting research area. CEMs are used to examine veiled evolutionary questions about extinctions, locations of past refugia and migration pathways, or to propose...... the theoretical assumptions behind niche modelling and using inadequate methods for hindcasting CEMs may well entail a cascade of errors and naïve ecological and evolutionary inferences. We should also push integrative research lines linking macroecology, physiology, population biology, palaeontology......, evolutionary biology and CEMs for a better understanding of niche dynamics across space and time....

  16. Response of chironomid species (Diptera, Chironomidae to water temperature: effects on species distribution in specific habitats

    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.

  17. Species delimitation of the Hyphydrus ovatus complex in western Palaearctic with an update of species distributions (Coleoptera, Dytiscidae

    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.

  18. 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.

  19. Species composition, abundance, distribution and habitat ...

    African Journals Online (AJOL)

    There were 371 captures of rodents and shrews from live-trapping and 73 captures from snaps. Seven species of rodents (Stenocephalemys albipes, Lophuromys flavopunctatus, Arvicanthis abyssinicus, Desmomys harringtoni, Mastomys natalensis, Mus mahomet and Rattus rattus) and two species of shrews (Crocidura ...

  20. Analyzing fractal property of species abundance distribution and diversity indexes.

    Science.gov (United States)

    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.

  1. Hierarchical analysis of species distributions and abundance across environmental gradients

    Science.gov (United States)

    Jeffery Diez; Ronald H. Pulliam

    2007-01-01

    Abiotic and biotic processes operate at multiple spatial and temporal scales to shape many ecological processes, including species distributions and demography. Current debate about the relative roles of niche-based and stochastic processes in shaping species distributions and community composition reflects, in part, the challenge of understanding how these processes...

  2. 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

    Species abundance distributions (SAD) are central to the description of diversity and have played a major role in the development of theories of biodiversity and biogeography. However, most work on species abundance distributions has focused on one single spatial scale. Here we used data on arthr...

  3. Hyperspectral remote sensing of vegetation species distribution in a saltmarsh

    NARCIS (Netherlands)

    Schmidt, K.S.

    2003-01-01

    The availability of quality empirical data on vegetation species distribution is a major factor limiting the understanding, if not resolution, of many nature conservation issues. Accurate knowledge of the distribution of plant species can form a critical component for managing ecosystems and

  4. Solar system formation and the distribution of volatile species

    Science.gov (United States)

    Lunine, Jonathan I.

    1994-01-01

    To understand how the solar system formed we must understand the compositional distribution of the current system. Volatile species are particularly important in that their stability as condensed phases is limited in temperature-pressure space, and hence variations in their distribution at present potentially contain an imprint of processes by which temperature and pressure varied in the solar nebula. In this talk we restrict ourselves to species more volatile than water ice, and address issues related to processes in the outer solar system and the formation of bodies there; others in this conference will cover volatile species relevant to inner solar system processes. Study of the outer solar system is relevant both to understanding the interface between the solar nebula and the progenitor giant molecular cloud (since the chemical links to present-day observables in molecular clouds are species like methane, carbon monoxide, etc.), as well as the origin of terrestrial planet atmospheres and oceans (the latter to be covered by Owen). The wealth of compositional information on outer solar system bodies which has become available from spacecraft and ground-based observations challenges traditional simplistic views of the composition and hence dynamics of the solar nebula. The basic assumption of thermochemical equilibrium, promulgated in the 1950's, in which methane and ammonia dominate nitrogen- and carbon-bearing species, is demonstrably incorrect on both observational and theoretical grounds. However, the kinetic inhibition model which replaced it, in which carbon monoxide and molecular nitrogen dominate a nebula which is fully mixed and hence cycles outer solar system gases through a hot, chemically active zone near the disk center, is not supported either by observations. Instead, a picture of the outer solar system emerges in which the gas and grains are a mixture of relatively unaltered, or modestly altered, molecular cloud material, along with a fraction

  5. Species Distribution and Antibiotic Resistance in Coagulase ...

    African Journals Online (AJOL)

    Purpose: The antimicrobial susceptibility of 149 coagulase-negative staphylococci (CoNS) isolates from faecal samples of children in Ile-Ife, Nigeria, was evaluated in order to determine their contribution to antimicrobial resistance in the community. Methods: The isolates were identified to the species level by conventional ...

  6. Comprehensive distributed-parameters modeling and experimental validation of microcantilever-based biosensors with an application to ultrasmall biological species detection

    International Nuclear Information System (INIS)

    Faegh, Samira; Jalili, Nader

    2013-01-01

    Nanotechnological advancements have made a great contribution in developing label-free and highly sensitive biosensors. The detection of ultrasmall adsorbed masses has been enabled by such sensors which transduce molecular interaction into detectable physical quantities. More specifically, microcantilever-based biosensors have caught widespread attention for offering a label-free, highly sensitive and inexpensive platform for biodetection. Although there are a lot of studies investigating microcantilever-based sensors and their biological applications, a comprehensive mathematical modeling and experimental validation of such devices providing a closed form mathematical framework is still lacking. In almost all of the studies, a simple lumped-parameters model has been proposed. However, in order to have a precise biomechanical sensor, a comprehensive model is required being capable of describing all phenomena and dynamics of the biosensor. Therefore, in this study, an extensive distributed-parameters modeling framework is proposed for the piezoelectric microcantilever-based biosensor using different methodologies for the purpose of detecting an ultrasmall adsorbed mass over the microcantilever surface. An optimum modeling methodology is concluded and verified with the experiment. This study includes three main parts. In the first part, the Euler–Bernoulli beam theory is used to model the nonuniform piezoelectric microcantilever. Simulation results are obtained and presented. The same system is then modeled as a nonuniform rectangular plate. The simulation results are presented describing model's capability in the detection of an ultrasmall mass. Finally the last part presents the experimental validation verifying the modeling results. It was shown that plate modeling predicts the real situation with a degree of precision of 99.57% whereas modeling the system as an Euler–Bernoulli beam provides a 94.45% degree of precision. The detection of ultrasmall

  7. 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...

  8. How much does climate change threaten European forest tree species distributions?

    Science.gov (United States)

    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.

  9. Predicting the geographic distribution of a species from presence-only data subject to detection errors

    Science.gov (United States)

    Dorazio, Robert M.

    2012-01-01

    Several models have been developed to predict the geographic distribution of a species by combining measurements of covariates of occurrence at locations where the species is known to be present with measurements of the same covariates at other locations where species occurrence status (presence or absence) is unknown. In the absence of species detection errors, spatial point-process models and binary-regression models for case-augmented surveys provide consistent estimators of a species’ geographic distribution without prior knowledge of species prevalence. In addition, these regression models can be modified to produce estimators of species abundance that are asymptotically equivalent to those of the spatial point-process models. However, if species presence locations are subject to detection errors, neither class of models provides a consistent estimator of covariate effects unless the covariates of species abundance are distinct and independently distributed from the covariates of species detection probability. These analytical results are illustrated using simulation studies of data sets that contain a wide range of presence-only sample sizes. Analyses of presence-only data of three avian species observed in a survey of landbirds in western Montana and northern Idaho are compared with site-occupancy analyses of detections and nondetections of these species.

  10. Integrating subsistence practice and species distribution modeling: assessing invasive elodea’s potential impact on Native Alaskan subsistence of Chinook salmon and whitefish

    Science.gov (United States)

    Luizza, Matthew; Evangelista, Paul; Jarnevich, Catherine S.; West, Amanda; Stewart, Heather

    2016-01-01

    Alaska has one of the most rapidly changing climates on earth and is experiencing an accelerated rate of human disturbance, including resource extraction and transportation infrastructure development. Combined, these factors increase the state’s vulnerability to biological invasion, which can have acute negative impacts on ecological integrity and subsistence practices. Of growing concern is the spread of Alaska’s first documented freshwater aquatic invasive plant Elodea spp. (elodea). In this study, we modeled the suitable habitat of elodea using global and state-specific species occurrence records and environmental variables, in concert with an ensemble of model algorithms. Furthermore, we sought to incorporate local subsistence concerns by using Native Alaskan knowledge and available statewide subsistence harvest data to assess the potential threat posed by elodea to Chinook salmon (Oncorhynchus tshawytscha) and whitefish (Coregonus nelsonii) subsistence. State models were applied to future climate (2040–2059) using five general circulation models best suited for Alaska. Model evaluations indicated that our results had moderate to strong predictability, with area under the receiver-operating characteristic curve values above 0.80 and classification accuracies ranging from 66 to 89 %. State models provided a more robust assessment of elodea habitat suitability. These ensembles revealed different levels of management concern statewide, based on the interaction of fish subsistence patterns, known spawning and rearing sites, and elodea habitat suitability, thus highlighting regions with additional need for targeted monitoring. Our results suggest that this approach can hold great utility for invasion risk assessments and better facilitate the inclusion of local stakeholder concerns in conservation planning and management.

  11. Integrating subsistence practice and species distribution modeling: assessing invasive elodea's potential impact on Native Alaskan subsistence of Chinook salmon and whitefish

    Science.gov (United States)

    Luizza, Matthew W.; Evangelista, Paul H.; Jarnevich, Catherine S.; West, Amanda; Stewart, Heather

    2016-07-01

    Alaska has one of the most rapidly changing climates on earth and is experiencing an accelerated rate of human disturbance, including resource extraction and transportation infrastructure development. Combined, these factors increase the state's vulnerability to biological invasion, which can have acute negative impacts on ecological integrity and subsistence practices. Of growing concern is the spread of Alaska's first documented freshwater aquatic invasive plant Elodea spp. (elodea). In this study, we modeled the suitable habitat of elodea using global and state-specific species occurrence records and environmental variables, in concert with an ensemble of model algorithms. Furthermore, we sought to incorporate local subsistence concerns by using Native Alaskan knowledge and available statewide subsistence harvest data to assess the potential threat posed by elodea to Chinook salmon ( Oncorhynchus tshawytscha) and whitefish ( Coregonus nelsonii) subsistence. State models were applied to future climate (2040-2059) using five general circulation models best suited for Alaska. Model evaluations indicated that our results had moderate to strong predictability, with area under the receiver-operating characteristic curve values above 0.80 and classification accuracies ranging from 66 to 89 %. State models provided a more robust assessment of elodea habitat suitability. These ensembles revealed different levels of management concern statewide, based on the interaction of fish subsistence patterns, known spawning and rearing sites, and elodea habitat suitability, thus highlighting regions with additional need for targeted monitoring. Our results suggest that this approach can hold great utility for invasion risk assessments and better facilitate the inclusion of local stakeholder concerns in conservation planning and management.

  12. 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

    Increasingly species distribution models are being used to address questions related to ecology, biogeography and species conservation on global and regional scales. We used the maximum entropy approach implemented in the MAXENT programme to build a habitat suitability model for Thai palms based...... 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...

  13. Distribution system modeling and analysis

    CERN Document Server

    Kersting, William H

    2001-01-01

    For decades, distribution engineers did not have the sophisticated tools developed for analyzing transmission systems-often they had only their instincts. Things have changed, and we now have computer programs that allow engineers to simulate, analyze, and optimize distribution systems. Powerful as these programs are, however, without a real understanding of the operating characteristics of a distribution system, engineers using the programs can easily make serious errors in their designs and operating procedures. Distribution System Modeling and Analysis helps prevent those errors. It gives readers a basic understanding of the modeling and operating characteristics of the major components of a distribution system. One by one, the author develops and analyzes each component as a stand-alone element, then puts them all together to analyze a distribution system comprising the various shunt and series devices for power-flow and short-circuit studies. He includes the derivation of all models and includes many num...

  14. Gridded Species Distribution, Version 1: Global Amphibians Original Grids

    Data.gov (United States)

    National Aeronautics and Space Administration — The Global Amphibians Original Grids of the Gridded Species Distribution, Version 1 are converted 1- kilometer grid cell data available in the Geographic Coordinate...

  15. 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 ...

  16. Determination of horizontal and vertical distribution of tree species in ...

    African Journals Online (AJOL)

    Determination of horizontal and vertical distribution of tree species in Turkey via Shuttle Radar Topography Mission (SRTM) satellite data and geographic information system: the case of Crimean pine ( Pinus nigra )

  17. Gridded Species Distribution, Version 1: Global Amphibians Family Richness Grids

    Data.gov (United States)

    National Aeronautics and Space Administration — Global Amphibians Family Richness Grids of the Gridded Species Distribution, Version 1 are aggregations of the presence grids data at the family level. They are...

  18. The Global Distribution and Drivers of Alien Bird Species Richness

    Science.gov (United States)

    Dyer, Ellie E.; Cassey, Phillip; Redding, David W.; Collen, Ben; Franks, Victoria; Gaston, Kevin J.; Jones, Kate E.; Kark, Salit; Orme, C. David L.; Blackburn, Tim M.

    2017-01-01

    Alien species are a major component of human-induced environmental change. Variation in the numbers of alien species found in different areas is likely to depend on a combination of anthropogenic and environmental factors, with anthropogenic factors affecting the number of species introduced to new locations, and when, and environmental factors influencing how many species are able to persist there. However, global spatial and temporal variation in the drivers of alien introduction and species richness remain poorly understood. Here, we analyse an extensive new database of alien birds to explore what determines the global distribution of alien species richness for an entire taxonomic class. We demonstrate that the locations of origin and introduction of alien birds, and their identities, were initially driven largely by European (mainly British) colonialism. However, recent introductions are a wider phenomenon, involving more species and countries, and driven in part by increasing economic activity. We find that, globally, alien bird species richness is currently highest at midlatitudes and is strongly determined by anthropogenic effects, most notably the number of species introduced (i.e., “colonisation pressure”). Nevertheless, environmental drivers are also important, with native and alien species richness being strongly and consistently positively associated. Our results demonstrate that colonisation pressure is key to understanding alien species richness, show that areas of high native species richness are not resistant to colonisation by alien species at the global scale, and emphasise the likely ongoing threats to global environments from introductions of species. PMID:28081142

  19. 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 ...

  20. 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 ...

  1. Causality of the relationship between geographic distribution and species abundance

    DEFF Research Database (Denmark)

    Borregaard, Michael Krabbe; Rahbek, Carsten

    2010-01-01

    The positive relationship between a species' geographic distribution and its abundance is one of ecology's most well-documented patterns, yet the causes behind this relationship remain unclear. Although many hypotheses have been proposed to account for distribution-abundance relationships none have...

  2. 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.

  3. Hydronic distribution system computer model

    Energy Technology Data Exchange (ETDEWEB)

    Andrews, J.W.; Strasser, J.J.

    1994-10-01

    A computer model of a hot-water boiler and its associated hydronic thermal distribution loop has been developed at Brookhaven National Laboratory (BNL). It is intended to be incorporated as a submodel in a comprehensive model of residential-scale thermal distribution systems developed at Lawrence Berkeley. This will give the combined model the capability of modeling forced-air and hydronic distribution systems in the same house using the same supporting software. This report describes the development of the BNL hydronics model, initial results and internal consistency checks, and its intended relationship to the LBL model. A method of interacting with the LBL model that does not require physical integration of the two codes is described. This will provide capability now, with reduced up-front cost, as long as the number of runs required is not large.

  4. A globally-distributed alien invasive species poses risks to United States imperiled species.

    Science.gov (United States)

    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.

  5. Species Distributions, Quantum Theory, and the Enhancement of Biodiversity Measures.

    Science.gov (United States)

    Real, Raimundo; Barbosa, A Márcia; Bull, Joseph W

    2017-05-01

    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 differently to similar environmental conditions at different places or moments, so their distribution is, in principle, not completely predictable. We argue that this uncertainty exists, and warrants considering species distributions as analogous to coherent quantum objects, whose distributions are better described by a wavefunction rather than by a set of locations. We use this to extend the existing concept of "dark diversity", which incorporates into biodiversity metrics those species that could, but which have not yet been observed to, inhabit a region-thereby developing the idea of "potential 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 eventually be gained through interdisciplinary collaboration between biogeographers and quantum physicists. [Biogeography; favorability; physics; predictability; probability; species occurrence; uncertainty; wavefunction. © The Author(s) 2016. Published by Oxford University Press, on behalf of the Society of Systematic Biologists. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  6. Distribution and diversity of twelve Curcuma species in China.

    Science.gov (United States)

    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.

  7. Linking macroecology and community ecology: refining predictions of species distributions using biotic interaction networks.

    Science.gov (United States)

    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.

  8. Multiple factors and thresholds explaining fish species distributions in lowland streams

    Directory of Open Access Journals (Sweden)

    Cristina Trigal

    2015-07-01

    Full Text Available Appropriate restoration and conservation measures require a good understanding of the factors limiting the distribution of species, the presence of steep changes in the distribution along environmental gradients and the effect of environmental interactions on species distribution. We used 12 environmental variables describing connectivity, hydrology, climate and stream morphology, to model the distributions of 17 fish species from 2005 Swedish stream sites that were sampled between 2000 and 2011. Modeling was performed using boosted regression trees and random forest, two machine learning techniques to assess the relationship between species distributions and their environment. Temperature, width and connectivity (minimum distance to lake or the sea and water discharge, were the most important variables explaining changes in species distribution at large spatial scales. Response curves of fitted occurrence probabilities along predictors often showed abrupt changes, however, clear threshold effects were difficult to detect. Our results show also differences across species and even in the outcomes of the two algorithms, implying that a simultaneous assessment of multiple species may provide a better signal of ecosystem change than the use of surrogate species.

  9. High-resolution pattern of mangrove species distribution is controlled by surface elevation

    Science.gov (United States)

    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.

  10. SAMICS marketing and distribution model

    Science.gov (United States)

    1978-01-01

    A SAMICS (Solar Array Manufacturing Industry Costing Standards) was formulated as a computer simulation model. Given a proper description of the manufacturing technology as input, this model computes the manufacturing price of solar arrays for a broad range of production levels. This report presents a model for computing these marketing and distribution costs, the end point of the model being the loading dock of the final manufacturer.

  11. The effects of global change on the distribution, species richness and life history of European dragonflies

    DEFF Research Database (Denmark)

    Olsen, Kent

    2016-01-01

    Climate change and human land-use strongly impacts ranges and distributional borders of dragonfly (Odonata) species which are therefore a good model group for understanding how the strength of such impacts depend on species specific ecology and functional traits. The specificity of their larvae t...

  12. Biotic Interactions Shape the Ecological Distributions of Staphylococcus Species.

    Science.gov (United States)

    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

  13. Distribution of Gobio species in the Czech Republic

    Czech Academy of Sciences Publication Activity Database

    Lusk, Stanislav; Halačka, Karel; Lusková, Věra; Horák, Václav

    2005-01-01

    Roč. 54, Suppl. 1 (2005), s. 56-64 ISSN 0139-7893. [Distribution, taxonomy and genetic status of the European species of the genus Gobio. Brno, 09.09.2003-11.09.2003] R&D Projects: GA AV ČR(CZ) IAA6045005; GA AV ČR(CZ) IAA6093105 Institutional research plan: CEZ:AV0Z60930519 Keywords : Gobio * distribution Subject RIV: EG - Zoology Impact factor: 0.585, year: 2005

  14. Ecological Effects of the Invasive Giant Madagascar Day Gecko on Endemic Mauritian Geckos: Applications of Binomial-Mixture and Species Distribution Models

    NARCIS (Netherlands)

    Buckland, S.; Cole, N.C.; Aguirre-Gutiérrez, J.; Gallagher, L.E.; Henshaw, S.M.; Besnard, A.; Tucker, R.M.; Bachraz, V.; Ruhomaun, K.; Harris, S.

    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

  15. 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...

  16. Causality of the relationship between geographic distribution and species abundance

    DEFF Research Database (Denmark)

    Borregaard, Michael Krabbe; Rahbek, Carsten

    2010-01-01

    The positive relationship between a species' geographic distribution and its abundance is one of ecology's most well-documented patterns, yet the causes behind this relationship remain unclear. Although many hypotheses have been proposed to account for distribution-abundance relationships none have...... differences in terminology and ecological point of view. Realizing and accounting for these differences facilitates integration, so that the relative contributions of each mechanism may be evaluated. Here, we review all the mechanisms that have been proposed to account for distribution-abundance relationships...

  17. Testing hypotheses on distribution shifts and changes in phenology of imperfectly detectable species

    Science.gov (United States)

    Chambert, Thierry A.; Kendall, William L.; Hines, James E.; Nichols, James D.; Pedrini, Paolo; Waddle, J. Hardin; Tavecchia, Giacomo; Walls, Susan C.; Tenan, Simone

    2015-01-01

    With ongoing climate change, many species are expected to shift their spatial and temporal distributions. To document changes in species distribution and phenology, detection/non-detection data have proven very useful. Occupancy models provide a robust way to analyse such data, but inference is usually focused on species spatial distribution, not phenology.We present a multi-season extension of the staggered-entry occupancy model of Kendall et al. (2013, Ecology, 94, 610), which permits inference about the within-season patterns of species arrival and departure at sampling sites. The new model presented here allows investigation of species phenology and spatial distribution across years, as well as site extinction/colonization dynamics.We illustrate the model with two data sets on European migratory passerines and one data set on North American treefrogs. We show how to derive several additional phenological parameters, such as annual mean arrival and departure dates, from estimated arrival and departure probabilities.Given the extent of detection/non-detection data that are available, we believe that this modelling approach will prove very useful to further understand and predict species responses to climate change.

  18. The Distribution, Feeding and Reproduction of Clarioid Species in ...

    African Journals Online (AJOL)

    The distribution, feeding and reproduction of the members of the sub-genus Clarias (Clarioides) in Epie Creek Floodplain was studied. Four species of the Clarias: C. buthupogon, C. agboyiensis, C. macromystax, and C albopunctatus occurred in the ecosystem. The presence of C. albopunctatus is reported for the first time ...

  19. Fish species composition, size structure and distribution in non ...

    African Journals Online (AJOL)

    Fish diversity studies in littoral non-trawlable areas of Lake Victoria (Tanzania) were undertaken during six systematic surveys (November 2000 to December 2002). Information on fish species composition, size structure as well as spatial and temporal distribution was generated from gill-netting, beach-seining and electric ...

  20. Fish species and size distribution and abundance in different areas ...

    African Journals Online (AJOL)

    Tanzania Journal of Science ... The results show that there were significant differences in catch rates between rainy and dry seasons (F (12, 12) = 2.69; p < 0.05). ... The distribution of the fish species in different areas recorded a significant difference during the dry season (Q = 18.254, df = 8, P < 0.001), while during the rainy ...

  1. fish species and size distribution and abundance in different areas

    African Journals Online (AJOL)

    ABSTRACT. The study was carried out to investigate fish species distribution and abundance in different areas and size structure variations according to depth in Lake Victoria, Tanzania. Data were collected using a bottom trawl net during rainy and dry seasons in 2002. The results show that there were significant ...

  2. Distribution and Molecular Diversity of Arborescent Gossypium Species.

    Science.gov (United States)

    Mexico is a center of diversity of Gossypium. As currently circumscribed, arborescent Gossypium species (Section Erioxylum) are widely distributed in dry deciduous forests located from the central state of Sinaloa at the north of its range to the eastern state of Oaxaca in the south. However, extens...

  3. Sparse Distribution Pattern Of Some Plant Species In Two ...

    African Journals Online (AJOL)

    Mountain forests play major roles in biodiversity; containing many endemics and species of conservation concern. The diversity and distribution patterns of plants in mountain ecosystems are influenced by various environmental and anthropogenic factors that exhibit heterogeneity over space and time. This study analysed ...

  4. The impact of climate on the geographical distribution of phytoplankton species in boreal lakes.

    Science.gov (United States)

    Hallstan, Simon; Trigal, Cristina; Johansson, Karin S L; Johnson, Richard K

    2013-12-01

    Here, we use a novel space-by-time approach to study large-scale changes in phytoplankton species distribution in Swedish boreal lakes in response to climate variability. Using phytoplankton samples from 27 lakes, evenly distributed across Sweden, all relatively unimpacted by anthropogenic disturbance and sampled annually between 1996 and 2010, we found significant shifts in the geographical distribution of 18 species. We also found significant changes in the prevalence of 45 species (33 became more common and 12 less common) over the study period. Using species distribution models and phytoplankton samples from 60 lakes sampled at least twice between 1992 and 2010, we evaluated the importance of climate variability and other environmental variables on species distribution. We found that temperature (e.g., extreme events and the duration of the growing season) was the most important predictor for species detections. Many cyanobacteria, chlorophytes, and, to a lesser extent, diatoms and zygnematophytes, showed congruent and positive responses to temperature. In contrast, precipitation explained little variation and was important only for a few taxa (e.g., Staurodesmus spp., Trachelomonas volvocina). At the community level, our results suggest a change in community composition at temperatures over 20 °C and growing seasons longer than 40 days. We conclude that climate is an important driver of the distributional patterns of individual phytoplankton species and may drive changes in community composition in minimally disturbed boreal lakes.

  5. 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.

  6. Forecasting species distributions with geo-spatial data: R objects that predict from averages of competing statistical models or data mining methods

    Science.gov (United States)

    Salas, L. A.; Veloz, S.; Ballard, G.

    2011-12-01

    Most forecasting approaches based on statistical models and data mining methods share a set of characteristics: all are constructed from train sets and validated against test sets using methods to avoid over-fitting on the training data; standard validation methods are used (e.g., AUC values for binary response data); some form of model averaging is applied when predicting new values from a set of competing models; measurements of error of predictions and goodness-of-fit of each competing model are reported and made spatially explicit. Many packages exist in R to fit statistical models and for data mining, but few include algorithms for forecasting and there are no model-averaging methods. However, results from these packages are commonly reported in R objects (S4 classes) that usually extend from other objects, and so they share methods in common (e.g., "predict", "aic"). Here we illustrate an approach that takes advantages of the abovementioned commonalities to develop a "framework" using objects that fit competing models with algorithms for forecasting and include model averaging methods. These objects can be easily extended to incorporate new kinds of statistical and data mining methods. We illustrate this approach with three types of objects and show how to interact with them to produce weighted averages from competing models, and some tabular and graphic outputs. These objects have been compiled into an R package ("RavianForecasting" - http://data.prbo.org/apps/ravian). We encourage others to use and contribute toward the development of these types of forecasting objects, or to develop alternatives with similar flexibility. We show how these can be easily extended to incorporate new statistical methods, new outputs, new methods to weigh averages, and new methods to validate the models.

  7. Ecological Effects of the Invasive Giant Madagascar Day Gecko on Endemic Mauritian Geckos: Applications of Binomial-Mixture and Species Distribution Models

    OpenAIRE

    Buckland, S.; Cole, N.C.; Aguirre-Gutiérrez, J.; Gallagher, L.E.; Henshaw, S.M.; Besnard, A.; Tucker, R.M.; Bachraz, V.; Ruhomaun, K.; Harris, S.

    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...

  8. Endangered species toxicity extrapolation using ICE models

    Science.gov (United States)

    The National Research Council’s (NRC) report on assessing pesticide risks to threatened and endangered species (T&E) included the recommendation of using interspecies correlation models (ICE) as an alternative to general safety factors for extrapolating across species. ...

  9. Gulf of California species and catch spatial distributions and historical time series - Developing end-to-end models of the Gulf of California

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The purpose of this project is to develop spatially discrete end-to-end models of the northern Gulf of California, linking oceanography, biogeochemistry, food web...

  10. 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.

  11. 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

  12. Modeling utilization distributions in space and time

    Science.gov (United States)

    Keating, K.A.; Cherry, S.

    2009-01-01

    W. Van Winkle defined the utilization distribution (UD) as a probability density that gives an animal's relative frequency of occurrence in a two-dimensional (x, y) plane. We extend Van Winkle's work by redefining the UD as the relative frequency distribution of an animal's occurrence in all four dimensions of space and time. We then describe a product kernel model estimation method, devising a novel kernel from the wrapped Cauchy distribution to handle circularly distributed temporal covariates, such as day of year. Using Monte Carlo simulations of animal movements in space and time, we assess estimator performance. Although not unbiased, the product kernel method yields models highly correlated (Pearson's r - 0.975) with true probabilities of occurrence and successfully captures temporal variations in density of occurrence. In an empirical example, we estimate the expected UD in three dimensions (x, y, and t) for animals belonging to each of two distinct bighorn sheep {Ovis canadensis) social groups in Glacier National Park, Montana, USA. Results show the method can yield ecologically informative models that successfully depict temporal variations in density of occurrence for a seasonally migratory species. Some implications of this new approach to UD modeling are discussed. ?? 2009 by the Ecological Society of America.

  13. Log-grade volume distribution prediction models for tree species in red oak-sweetgum stands on US mid-south minor stream bottoms

    Science.gov (United States)

    George M. Banzhaf; Thomas G. Matney; Emily B. Schultz; James S. Meadows; J. Paul Jeffreys; William C. Booth; Gan Li; Andrew W. Ezell; Theodor D. Leininger

    2016-01-01

    Red oak (Quercus section Labatae)-sweetgum (Liquidambar styraciflua L.) stands growing on mid-south bottomland sites in the United States are well known for producing high-quality grade hardwood logs, but models for estimating the quantity and quality of standing grade wood in these stands have been unavailable. Prediction...

  14. Global potential distribution of an invasive species, the yellow crazy ant (Anoplolepis gracilipes) under climate change.

    Science.gov (United States)

    Chen, Youhua

    2008-09-01

    Changes to the Earth's climate may affect the distribution of countless species. Understanding the potential distribution of known invasive species under an altered climate is vital to predicting impacts and developing management policy. The present study employs ecological niche modeling to construct the global potential distribution range of the yellow crazy ant (Anoplolepis gracilipes) using past, current and future climate scenarios. Three modeling algorithms, GARP, BioClim and Environmental Distance, were used in a comparative analysis. Output from the models suggest firstly that this insect originated from south Asia, expanded into Europe and then into Afrotropical regions, after which it formed its current distribution. Second, the invasive risk of A. gracilipes under future climatic change scenarios will become greater because of an extension of suitable environmental conditions in higher latitudes. Third, when compared to the GARP model, BioClim and Environmental Distance models were better at modeling a species' ancestral distribution. These findings are discussed in light of the predictive accuracy of these models. © 2008 ISZS, Blackwell Publishing and IOZ/CAS.

  15. What are the most crucial soil factors for predicting the distribution of alpine plant species?

    Science.gov (United States)

    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

  16. Implications of human induced changes on the distribution of important plant species in the northwestern coastal desert of Egypt

    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.

  17. Uncertainties in Predicting Species Distributions under Climate Change: A Case Study Using Tetranychus evansi (Acari: Tetranychidae), a Widespread Agricultural Pest

    OpenAIRE

    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 (Tetr...

  18. A model of seasonal foliage dynamics of the subtropical mangrove species Rhizophora stylosa Griff. growing at the northern limit of its distribution

    Directory of Open Access Journals (Sweden)

    Sahadev Sharma

    2014-08-01

    Full Text Available Background Progress of forest production in response to the environment requires a quantitative understanding of leaf area development. Therefore, it is necessary to investigate the dynamics of seasonal crown foliage in order to understand the productivity of mangroves, which play an important role in the subtropical and tropical coastlines of the world. Method Crown foliage dynamics of the mangrove Rhizophora stylosa were studies to reveal patterns of leaf recruitment, survival and seasonal leaf area growth. Results Flushing of leaves occurred throughout the year, but both flushing and leaf area growth pattern of leaves varied with season. Maximum flushing occurred in summer, but leaf areas did not differ significantly with season. The half-expansion period is longer, and the intrinsic rate of increase was lower in winter. Summer flushed leaves grew faster at their initial stage and reached their maximum area over a shorter period of time. The difference in temperature and air vapor pressure deficit (VPD between summer and winter contributed to the present dynamics of foliage patterns. The mean leaf longevity was estimated to be 13.1 month. The crown foliage area was almost stable throughout the year. Conclusions Homeostatic control of the crown foliage area may be accompanied by the existence of ecophysiological mechanisms in R. stylosa. Integrating crown foliage dynamics into forest models represents an important step towards incorporating physiological mechanisms into the models for predicting growth responses to environmental changes and for understanding the complex responses of tree growth and litter production.

  19. Modelling the effect of climate change on species ranges

    NARCIS (Netherlands)

    Nagelkerke, C.J.; Alkemade, J.R.M.

    2003-01-01

    Three main types of models can be used to understand and predict climate-related range shifts. Equilibrium models predict potential future distributions from the current climate envelope of a species, but do not take migration constraints into account. They show that future range changes can be

  20. Seeing the forest and the trees: multilevel models reveal both species and community patterns

    Science.gov (United States)

    Michelle M. Jackson; Monica G. Turner; Scott M. Pearson; Anthony R. Ives

    2012-01-01

    Studies designed to understand species distributions and community assemblages typically use separate analytical approaches (e.g., logistic regression and ordination) to model the distribution of individual species and to relate community composition to environmental variation. Multilevel models (MLMs) offer a promising strategy for integrating species and community-...

  1. Water Distribution and Removal Model

    Energy Technology Data Exchange (ETDEWEB)

    Y. Deng; N. Chipman; E.L. Hardin

    2005-08-26

    The design of the Yucca Mountain high level radioactive waste repository depends on the performance of the engineered barrier system (EBS). To support the total system performance assessment (TSPA), the Engineered Barrier System Degradation, Flow, and Transport Process Model Report (EBS PMR) is developed to describe the thermal, mechanical, chemical, hydrological, biological, and radionuclide transport processes within the emplacement drifts, which includes the following major analysis/model reports (AMRs): (1) EBS Water Distribution and Removal (WD&R) Model; (2) EBS Physical and Chemical Environment (P&CE) Model; (3) EBS Radionuclide Transport (EBS RNT) Model; and (4) EBS Multiscale Thermohydrologic (TH) Model. Technical information, including data, analyses, models, software, and supporting documents will be provided to defend the applicability of these models for their intended purpose of evaluating the postclosure performance of the Yucca Mountain repository system. The WD&R model ARM is important to the site recommendation. Water distribution and removal represents one component of the overall EBS. Under some conditions, liquid water will seep into emplacement drifts through fractures in the host rock and move generally downward, potentially contacting waste packages. After waste packages are breached by corrosion, some of this seepage water will contact the waste, dissolve or suspend radionuclides, and ultimately carry radionuclides through the EBS to the near-field host rock. Lateral diversion of liquid water within the drift will occur at the inner drift surface, and more significantly from the operation of engineered structures such as drip shields and the outer surface of waste packages. If most of the seepage flux can be diverted laterally and removed from the drifts before contacting the wastes, the release of radionuclides from the EBS can be controlled, resulting in a proportional reduction in dose release at the accessible environment. The purposes

  2. Water Distribution and Removal Model

    International Nuclear Information System (INIS)

    Y. Deng; N. Chipman; E.L. Hardin

    2005-01-01

    The design of the Yucca Mountain high level radioactive waste repository depends on the performance of the engineered barrier system (EBS). To support the total system performance assessment (TSPA), the Engineered Barrier System Degradation, Flow, and Transport Process Model Report (EBS PMR) is developed to describe the thermal, mechanical, chemical, hydrological, biological, and radionuclide transport processes within the emplacement drifts, which includes the following major analysis/model reports (AMRs): (1) EBS Water Distribution and Removal (WD and R) Model; (2) EBS Physical and Chemical Environment (P and CE) Model; (3) EBS Radionuclide Transport (EBS RNT) Model; and (4) EBS Multiscale Thermohydrologic (TH) Model. Technical information, including data, analyses, models, software, and supporting documents will be provided to defend the applicability of these models for their intended purpose of evaluating the postclosure performance of the Yucca Mountain repository system. The WD and R model ARM is important to the site recommendation. Water distribution and removal represents one component of the overall EBS. Under some conditions, liquid water will seep into emplacement drifts through fractures in the host rock and move generally downward, potentially contacting waste packages. After waste packages are breached by corrosion, some of this seepage water will contact the waste, dissolve or suspend radionuclides, and ultimately carry radionuclides through the EBS to the near-field host rock. Lateral diversion of liquid water within the drift will occur at the inner drift surface, and more significantly from the operation of engineered structures such as drip shields and the outer surface of waste packages. If most of the seepage flux can be diverted laterally and removed from the drifts before contacting the wastes, the release of radionuclides from the EBS can be controlled, resulting in a proportional reduction in dose release at the accessible environment

  3. Beyond a climate-centric view of plant distribution: edaphic variables add value to distribution models.

    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

  4. Drought tolerance of tropical tree species : functional traits, trade-offs and species distribution

    NARCIS (Netherlands)

    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 one of the

  5. Drought tolerance of tropical tree species : functional traits, trade-offs and species distribution

    NARCIS (Netherlands)

    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

  6. Historical change in fish species distribution: shifting reference conditions and global warming effects.

    Science.gov (United States)

    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.

  7. Species Diversity and Distributional Pattern of Cockroaches in Lahore, Pakistan

    Directory of Open Access Journals (Sweden)

    Hafsa Memona

    2017-06-01

    Full Text Available Background: Cockroaches are found as the most common urban pests of tropical countries, prompting economic and serious health risk problem for humans by carrying microbes and allergens, acting as vector for various patho­gens of diseases. The present study was conducted from April 2013 to March 2014 in various human dwelling local­ities of urban area of district Lahore, Pakistan.Methods: Cockroaches were collected randomly by hand, food baited and sticky traps throughout the year. Four species of cockroaches (Periplaneta Americana (P. amercana, Blattella germanica (B. germanica, Blatta orientalis (B. orientalis, and Blatta lateralis (B. lateralis were collected and identified from the study site.Results: B. germanica was the most dominant indoor species with highest diversity indices in study areas. Overall cockroach species diversity was highest in July–September, 2013 with highest Simpson index of diversity and Shan­non index as well. P. americana was found second broadly distributed in the study area followed by B. orientalis and B. lateralis were intermediately distributed in residential areas and narrowly distributed in hospitals. Residential ar­eas and hospitals were highly infested with B. germanica followed by P. americana. Population index of B. ger­manica for hospitals was double than residential areas. B. lateralis was observed as displacing B. orientalis in out­door habitat through competing with its habitat and food sources.Conclusion: The infestation rate of different species depends on availability of food sources, sanitary conditions and climatic conditions. Cockroach infestation can be controlled with knowledge about their biology and behavior, at­tention to sanitation and effective use of commercial insecticides.

  8. Estimating the spatial and temporal distribution of species richness within Sequoia and Kings Canyon National Parks.

    Science.gov (United States)

    Wathen, Steve; Thorne, James H; Holguin, Andrew; Schwartz, Mark W

    2014-01-01

    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.

  9. Estimating the spatial and temporal distribution of species richness within Sequoia and Kings Canyon National Parks.

    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.

  10. Ising model for distribution networks

    Science.gov (United States)

    Hooyberghs, H.; Van Lombeek, S.; Giuraniuc, C.; Van Schaeybroeck, B.; Indekeu, J. O.

    2012-01-01

    An elementary Ising spin model is proposed for demonstrating cascading failures (breakdowns, blackouts, collapses, avalanches, etc.) that can occur in realistic networks for distribution and delivery by suppliers to consumers. A ferromagnetic Hamiltonian with quenched random fields results from policies that maximize the gap between demand and delivery. Such policies can arise in a competitive market where firms artificially create new demand, or in a solidarity environment where too high a demand cannot reasonably be met. Network failure in the context of a policy of solidarity is possible when an initially active state becomes metastable and decays to a stable inactive state. We explore the characteristics of the demand and delivery, as well as the topological properties, which make the distribution network susceptible of failure. An effective temperature is defined, which governs the strength of the activity fluctuations which can induce a collapse. Numerical results, obtained by Monte Carlo simulations of the model on (mainly) scale-free networks, are supplemented with analytic mean-field approximations to the geometrical random field fluctuations and the thermal spin fluctuations. The role of hubs versus poorly connected nodes in initiating the breakdown of network activity is illustrated and related to model parameters.

  11. Confronting different models of community structure to species-abundance data : a Bayesian model comparison

    NARCIS (Netherlands)

    Etienne, RS; Olff, H

    Species abundances are undoubtedly the most widely available macroecological data, but can we use them to distinguish among several models of community structure? Here we present a Bayesian analysis of species-abundance data that yields a full joint probability distribution of each model's

  12. Confronting different models of community structure to species-abundance data: a Bayesian model comparison

    NARCIS (Netherlands)

    Etienne, R.S.; Olff, H.

    2005-01-01

    Species abundances are undoubtedly the most widely available macroecological data, but can we use them to distinguish among several models of community structure? Here we present a Bayesian analysis of species-abundance data that yields a full joint probability distribution of each model's

  13. Stochastic species abundance models involving special copulas

    Science.gov (United States)

    Huillet, Thierry E.

    2018-01-01

    Copulas offer a very general tool to describe the dependence structure of random variables supported by the hypercube. Inspired by problems of species abundances in Biology, we study three distinct toy models where copulas play a key role. In a first one, a Marshall-Olkin copula arises in a species extinction model with catastrophe. In a second one, a quasi-copula problem arises in a flagged species abundance model. In a third model, we study completely random species abundance models in the hypercube as those, not of product type, with uniform margins and singular. These can be understood from a singular copula supported by an inflated simplex. An exchangeable singular Dirichlet copula is also introduced, together with its induced completely random species abundance vector.

  14. 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)

  15. Probabilistic accounting of uncertainty in forecasts of species distributions under climate change

    Science.gov (United States)

    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...

  16. Climate controls the distribution of a widespread invasive species: Implications for future range expansion

    Science.gov (United States)

    McDowell, W.G.; Benson, A.J.; Byers, J.E.

    2014-01-01

    1. Two dominant drivers of species distributions are climate and habitat, both of which are changing rapidly. Understanding the relative importance of variables that can control distributions is critical, especially for invasive species that may spread rapidly and have strong effects on ecosystems. 2. Here, we examine the relative importance of climate and habitat variables in controlling the distribution of the widespread invasive freshwater clam Corbicula fluminea, and we model its future distribution under a suite of climate scenarios using logistic regression and maximum entropy modelling (MaxEnt). 3. Logistic regression identified climate variables as more important than habitat variables in controlling Corbicula distribution. MaxEnt modelling predicted Corbicula's range expansion westward and northward to occupy half of the contiguous United States. By 2080, Corbicula's potential range will expand 25–32%, with more than half of the continental United States being climatically suitable. 4. Our combination of multiple approaches has revealed the importance of climate over habitat in controlling Corbicula's distribution and validates the climate-only MaxEnt model, which can readily examine the consequences of future climate projections. 5. Given the strong influence of climate variables on Corbicula's distribution, as well as Corbicula's ability to disperse quickly and over long distances, Corbicula is poised to expand into New England and the northern Midwest of the United States. Thus, the direct effects of climate change will probably be compounded by the addition of Corbicula and its own influences on ecosystem function.

  17. Geographic distribution of phlebotomine sandfly species (Diptera: Psychodidae) in Central-West Brazil

    Science.gov (United States)

    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

  18. An Objective Approach to Select Climate Scenarios when Projecting Species Distribution under Climate Change

    Science.gov (United States)

    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. PMID:27015274

  19. An Objective Approach to Select Climate Scenarios when Projecting Species Distribution under Climate Change.

    Science.gov (United States)

    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.

  20. Using geomorphological variables to predict the spatial distribution of plant species in agricultural drainage networks.

    Science.gov (United States)

    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

  1. A new species and karyotype variation in the bordering distribution of Mepraia spinolai (Porter) and Mepraia gajardoi Frías et al (Hemiptera: Reduviidae: Triatominae) in Chile and its parapatric model of speciation.

    Science.gov (United States)

    Frías-Lasserre, Daniel

    2010-01-01

    In the present study, the morphology, color pattern, chromosomal complement and aspects of meiosis in natural populations at the borders of the distributions of Mepraia gajardoi Frías et al and Mepraia spinolai (Porter) are described. The males of these bordering populations are brachypterous or macropterous, while females are always micropterous. Morphological and cytogenetic data indicated that the populations that border the distributions of M. gajardoi and M. spinolai, belong to a different species of parapatric origin.

  2. Effects of urbanization on carnivore species distribution and richness

    Science.gov (United States)

    Ordenana, Miguel A.; Crooks, Kevin R.; Boydston, Erin E.; Fisher, Robert N.; Lyren, Lisa M.; Siudyla, Shalene; Haas, Christopher D.; Harris, Sierra; Hathaway, Stacie A.; Turschak, Greta M.; Miles, A. Keith; Van Vuren, Dirk H.

    2010-01-01

    Urban development can have multiple effects on mammalian carnivore communities. We conducted a meta-analysis of 7,929 photographs from 217 localities in 11 camera-trap studies across coastal southern California to describe habitat use and determine the effects of urban proximity (distance to urban edge) and intensity (percentage of area urbanized) on carnivore occurrence and species richness in natural habitats close to the urban boundary. Coyotes (Canis latrans) and bobcats (Lynx rufus) were distributed widely across the region. Domestic dogs (Canis lupus familiaris), striped skunks (Mephitis mephitis), raccoons (Procyon lotor), gray foxes (Urocyon cinereoargenteus), mountain lions (Puma concolor), and Virginia opossums (Didelphis virginiana) were detected less frequently, and long-tailed weasels (Mustela frenata), American badgers (Taxidea taxus), western spotted skunks (Spilogale gracilis), and domestic cats (Felis catus) were detected rarely. Habitat use generally reflected availability for most species. Coyote and raccoon occurrence increased with both proximity to and intensity of urbanization, whereas bobcat, gray fox, and mountain lion occurrence decreased with urban proximity and intensity. Domestic dogs and Virginia opossums exhibited positive and weak negative relationships, respectively, with urban intensity but were unaffected by urban proximity. Striped skunk occurrence increased with urban proximity but decreased with urban intensity. Native species richness was negatively associated with urban intensity but not urban proximity, probably because of the stronger negative response of individual species to urban intensity.

  3. Distribution of atmospheric mercury species near ground. [Tampa Bay, Florida

    Energy Technology Data Exchange (ETDEWEB)

    Johnson, D.L.; Braman, R.S.

    1974-01-01

    A recently developed technique makes possible the routine analysis of atmospheric samples for particulate and volatile mercury. The volatile fraction can be analyzed for several chemical species. This work presents the results of some Tampb Bay area analyses and diurnal studies of atmospheric mercury speciation. The mercury in air in the area investigated was primarily volatile (>90%) and was composed of significant proportions of mercury (II)-type compounds, methylmercury (II)-type compounds, and elemental mercury. Dimethylmercury was rarely observed. Results were quite variable suggesting a variety of sources and irregular wind transport processes. The data indicate that background mercury concentrations and the percentage distribution of mercury species in air in a local area may be established by mercury emanations from the ground or from adjacent bodies of water.

  4. Distribution of Plasmids in Distinct Leptospira Pathogenic Species.

    Directory of Open Access Journals (Sweden)

    Yanzhuo Wang

    2015-11-01

    Full Text Available 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

  5. Distribution of Plasmids in Distinct Leptospira Pathogenic Species.

    Science.gov (United States)

    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

  6. Distribution of Pu Species in Sea Water of Ujung Lemahabang

    International Nuclear Information System (INIS)

    Syarbaini

    2000-01-01

    Distribution of Pu related to its oxidation state in Ujung Lemahabang Sea water has been investigated by using 242 Pu isotop. The objective of this research is to study a species of Pu in Ujung Lemahabang marine environment. The 242 Pu isotop was added into sea water samples, mixed well and allow to stand for several weeks. Furthermore, oxidation state of Pu in sea water was determined by using coprecipitation method with NdF 3 . Activity of Pu in precipitate was measured by using GSM α/β counter. The result showed that Pu in sea water of Ujung Lemahabang is distributed in the form of Pu (III, IV) and Pu (V,VI) in the value of 9 % and 61 % respectively. The Pu in Sea water was also found about 27 % in particulate matter with diameter> 0.22 μm. (author)

  7. Climatic associations of British species distributions show good transferability in time but low predictive accuracy for range change.

    Science.gov (United States)

    Rapacciuolo, Giovanni; Roy, David B; Gillings, Simon; Fox, Richard; Walker, Kevin; Purvis, Andy

    2012-01-01

    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--as assessed using

  8. Climatic associations of British species distributions show good transferability in time but low predictive accuracy for range change.

    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

  9. Species distribution and susceptibility profile of Candida species in a Brazilian public tertiary hospital

    Directory of Open Access Journals (Sweden)

    Montelli Augusto

    2010-01-01

    Full Text Available Abstract Background Species identification and antifungal susceptibility tests were carried out on 212 Candida isolates obtained from bloodstream infections, urinary tract infections and dialysis-associated peritonitis, from cases attended at a Brazilian public tertiary hospital from January 1998 to January 2005. Findings Candida albicans represented 33% of the isolates, Candida parapsilosis 31.1%, Candida tropicalis 17.9%,Candida glabrata 11.8%, and others species 6.2%. In blood culture, C. parapsilosis was the most frequently encountered species (48%. The resistance levels to the antifungal azoles were relatively low for the several species, except for C. tropicalis and C. glabrata. Amphotericin B resistance was observed in 1 isolate of C. parapsilosis. Conclusions The species distribution and antifungal susceptibility herein observed presented several epidemiological features common to other tertiary hospitals in Latin American countries. It also exhibited some peculiarity, such as a very high frequency of C. parapsilosis both in bloodstream infections and dialysis-associated peritonitis. C. albicans also occurred in an important number of case infections, in all evaluated clinical sources. C. glabrata presented a high proportion of resistant isolates. The data emphasize the necessity to carry out the correct species identification accompanied by the susceptibility tests in all tertiary hospitals.

  10. Using habitat suitability models to target invasive plant species surveys.

    Science.gov (United States)

    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 habitat suitability models can be highly useful tools for guiding invasive species monitoring

  11. Metalaxyl toxicity, uptake, and distribution in several ornamental plant species.

    Science.gov (United States)

    Wilson, P C; Whitwell, T; Klaine, S J

    2001-01-01

    Phytoremediation depends on the ability of plants to tolerate and assimilate contaminants. This research characterized the interaction between several ornamental plant species and the fungicidal active ingredient, metalaxyl [N-(2,6-dimethylphenyl)-N-(methoxyacetyl)alanine methyl ester]. Species evaluated included sweetflag (Acorus gramineus Sol. ex Aiton), canna (Canna hybrida L. 'Yellow King Humbert'), parrotfeather [Myriophyllum aquaticum (Vell.) Verdc.], and pickerelweed (Pontederia cordata L.). Metalaxyl tolerance levels for each species were determined by exposing plants for 7 d to solutions containing 0, 5, 10, 25, 50, 75, or 100 mg metalaxyl L-1 aqueous nutrient media. Response endpoints included fresh mass production after 7 d exposure and 7 d post-exposure and quantum efficiency using dark-adapted (Fv/Fm) and light-adapted (fluorescence yields) plants. Metalaxyl uptake and distribution within the plant was determined by growing plants in aqueous nutrient media containing 1.18 x 10(6) Bq L-1 [14C]metalaxyl (0.909 mg L-1) for 1, 3, 5, or 7 d. Plant tissues were combusted and analyzed by liquid scintillation counting. Metalaxyl had no effects on the endpoints measured, except for fresh mass production of sweetflag at the 75 and 100 mg L-1 treatment levels. However, leaf necrosis was apparent in most species after 5 d exposure to concentrations greater than 25 mg L-1. Metalaxyl removal from the spiked nutrient media ranged from 15 to 60% during the 7-d exposure period. The majority of metalaxyl removed from the solution was detected within individual plants. In nearly all cases, activity from the radiolabeled pesticide accumulated in the leaves. Uptake of metalaxyl was correlated with water uptake throughout the 7 d. These results suggest that all species examined may be good candidates for incorporation into a phytoremediation scheme for metalaxyl.

  12. Climate, soil or both? Which variables are better predictors of the distributions of Australian shrub species?

    Directory of Open Access Journals (Sweden)

    Yasmin Hageer

    2017-06-01

    Full Text Available Background Shrubs play a key role in biogeochemical cycles, prevent soil and water erosion, provide forage for livestock, and are a source of food, wood and non-wood products. However, despite their ecological and societal importance, the influence of different environmental variables on shrub distributions remains unclear. We evaluated the influence of climate and soil characteristics, and whether including soil variables improved the performance of a species distribution model (SDM, Maxent. Methods This study assessed variation in predictions of environmental suitability for 29 Australian shrub species (representing dominant members of six shrubland classes due to the use of alternative sets of predictor variables. Models were calibrated with (1 climate variables only, (2 climate and soil variables, and (3 soil variables only. Results The predictive power of SDMs differed substantially across species, but generally models calibrated with both climate and soil data performed better than those calibrated only with climate variables. Models calibrated solely with soil variables were the least accurate. We found regional differences in potential shrub species richness across Australia due to the use of different sets of variables. Conclusions Our study provides evidence that predicted patterns of species richness may be sensitive to the choice of predictor set when multiple, plausible alternatives exist, and demonstrates the importance of considering soil properties when modeling availability of habitat for plants.

  13. Marine species distribution shifts on the U.S. Northeast Continental Shelf under continued ocean warming

    Science.gov (United States)

    Kleisner, Kristin M.; Fogarty, Michael J.; McGee, Sally; Hare, Jonathan A.; Moret, Skye; Perretti, Charles T.; Saba, Vincent S.

    2017-04-01

    The U.S. Northeast Continental Shelf marine ecosystem has warmed much faster than the global ocean and it is expected that this enhanced warming will continue through this century. Complex bathymetry and ocean circulation in this region have contributed to biases in global climate model simulations of the Shelf waters. Increasing the resolution of these models results in reductions in the bias of future climate change projections and indicates greater warming than suggested by coarse resolution climate projections. Here, we used a high-resolution global climate model and historical observations of species distributions from a trawl survey to examine changes in the future distribution of suitable thermal habitat for various demersal and pelagic species on the Shelf. Along the southern portion of the shelf (Mid-Atlantic Bight and Georges Bank), a projected 4.1 °C (surface) to 5.0 °C (bottom) warming of ocean temperature from current conditions results in a northward shift of the thermal habitat for the majority of species. While some southern species like butterfish and black sea bass are projected to have moderate losses in suitable thermal habitat, there are potentially significant increases for many species including summer flounder, striped bass, and Atlantic croaker. In the north, in the Gulf of Maine, a projected 3.7 °C (surface) to 3.9 °C (bottom) warming from current conditions results in substantial reductions in suitable thermal habitat such that species currently inhabiting this region may not remain in these waters under continued warming. We project a loss in suitable thermal habitat for key northern species including Acadian redfish, American plaice, Atlantic cod, haddock, and thorney skate, but potential gains for some species including spiny dogfish and American lobster. We illustrate how changes in suitable thermal habitat of important commercially fished species may impact local fishing communities and potentially impact major fishing ports

  14. Real-time modeling of heat distributions

    Energy Technology Data Exchange (ETDEWEB)

    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.

  15. Reactive oxygen species at phospholipid bilayers: distribution, mobility and permeation.

    Science.gov (United States)

    Cordeiro, Rodrigo M

    2014-01-01

    Reactive oxygen species (ROS) are involved in biochemical processes such as redox signaling, aging, carcinogenesis and neurodegeneration. Although biomembranes are targets for reactive oxygen species attack, little is known about the role of their specific interactions. Here, molecular dynamics simulations were employed to determine the distribution, mobility and residence times of various reactive oxygen species at the membrane-water interface. Simulations showed that molecular oxygen (O2) accumulated at the membrane interior. The applicability of this result to singlet oxygen ((1)O2) was discussed. Conversely, superoxide (O2(-)) radicals and hydrogen peroxide (H2O2) remained at the aqueous phase. Both hydroxyl (HO) and hydroperoxyl (HO2) radicals were able to penetrate deep into the lipid headgroups region. Due to membrane fluidity and disorder, these radicals had access to potential peroxidation sites along the lipid hydrocarbon chains, without having to overcome the permeation free energy barrier. Strikingly, HO2 radicals were an order of magnitude more concentrated in the headgroups region than in water, implying a large shift in the acid-base equilibrium between HO2 and O2(-). In comparison with O2, both HO and HO2 radicals had lower lateral mobility at the membrane. Simulations revealed that there were intermittent interruptions in the H-bond network around the HO radicals at the headgroups region. This effect is expected to be unfavorable for the H-transfer mechanism involved in HO diffusion. The implications for lipid peroxidation and for the effectiveness of membrane antioxidants were evaluated. © 2013.

  16. Estimating species occurrence, abundance, and detection probability using zero-inflated distributions.

    Science.gov (United States)

    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.

  17. SPECIES COMPOSITION AND GEOGRAPHICAL DISTRIBUTION OF SPECIES OF LOCUST INHABITING KARACHAY-CHERKESSIA

    Directory of Open Access Journals (Sweden)

    Z. S. Temirlieva

    2015-01-01

    Full Text Available Aim. The aim of this work was to study the characteristics of the fauna of locusts in Karachay-Cherkessia, as some areas of the region's fauna has not been studied for a long time. Locusts (Acrididae can be defined as dominant in numbers and biomass, which makes them an important role as herbivores as well as crop pests, so the modern study of locusts is of great interest. Methods. With observations in nature and conducted experiments in the laboratory we have made tests on behavior for five species of locusts (Omocestus haemorrhoidalis Ch., Chorthippus albomarginatus Deg., Chorthippus bigutullus L., Chorthippus apricarius L., Chorthippus mollis Ch.. Results. As a result, the inventory of species composition of locusts inhabiting the territory of Karachay-Cherkessia revealed 53 species belonging to 31 genera. Conclusions. This work is a modern faunal study of locusts inhabiting KarachayCherkessia. It has been identified 53 species of locusts, and data about the fauna group under study was updated. The faunal information is given in compliance with the current level of taxonomic knowledge of the group, and also presents data on the geographic distribution of all known species of the region. 

  18. Effects of climate change, invasive species, and disease on the distribution of native European crayfishes.

    Science.gov (United States)

    Capinha, César; Larson, Eric R; Tricarico, Elena; Olden, Julian D; Gherardi, Francesca

    2013-08-01

    Climate change will require species to adapt to new conditions or follow preferred climates to higher latitudes or elevations, but many dispersal-limited freshwater species may be unable to move due to barriers imposed by watershed boundaries. In addition, invasive nonnative species may expand into new regions under future climate conditions and contribute to the decline of native species. We evaluated future distributions for the threatened European crayfish fauna in response to climate change, watershed boundaries, and the spread of invasive crayfishes, which transmit the crayfish plague, a lethal disease for native European crayfishes. We used climate projections from general circulation models and statistical models based on Mahalanobis distance to predict climate-suitable regions for native and invasive crayfishes in the middle and at the end of the 21st century. We identified these suitable regions as accessible or inaccessible on the basis of major watershed boundaries and present occurrences and evaluated potential future overlap with 3 invasive North American crayfishes. Climate-suitable areas decreased for native crayfishes by 19% to 72%, and the majority of future suitable areas for most of these species were inaccessible relative to native and current distributions. Overlap with invasive crayfish plague-transmitting species was predicted to increase. Some native crayfish species (e.g., noble crayfish [Astacus astacus]) had no future refugia that were unsuitable for the modeled nonnative species. Our results emphasize the importance of preventing additional introductions and spread of invasive crayfishes in Europe to minimize interactions between the multiple stressors of climate change and invasive species, while suggesting candidate regions for the debatable management option of assisted colonization. © 2013 Society for Conservation Biology.

  19. Projecting future changes in distributions of pelagic fish species of Northeast Pacific shelf seas

    Science.gov (United States)

    Cheung, William W. L.; Brodeur, Richard D.; Okey, Thomas A.; Pauly, Daniel

    2015-01-01

    Marine life is being affected by changes in ocean conditions resulting from changes in climate and chemistry triggered by combustion of fossil fuels. Shifting spatial distributions of fish species is a major observed and predicted impact of these oceanographic changes, and such shifts may modify fish community structure considerably in particular locations and regions. We projected future range shifts of pelagic marine fishes of the Northeast Pacific shelf seas by 2050 relative to the present. We combined published data, expert knowledge, and pelagic fish survey data to predict current species distribution ranges of 28 fish species of the Northeast Pacific shelf seas that occur in the epipelagic zone and are well-represented in pelagic fish surveys. These represent a wide spectrum of sub-tropical to sub-polar species, with a wide range of life history characteristics. Using projected ocean condition changes from three different Earth System Models, we simulated changes in the spatial distribution of each species. We show that Northeast Pacific shelf seas may undergo considerable changes in the structure of its pelagic marine communities by mid-21st century. Ensembles of model projections suggest that the distribution centroids of the studied species are expected to shift poleward at an average rate of 30.1 ± 2.34 (S.E.) km decade-1 under the SRES A2 scenario from 2000 to 2050. The projected species range shifts result in a high rate of range expansion of this group of species into the Gulf of Alaska and the Bering Sea. Rate of range contraction of these species is highest at the Aleutian Islands, and in the California Current Large Marine Ecosystem. We also predict increasing dominance of warmer water species in all regions. The projected changes in species assemblages may have large ecological and socio-economic implications through mismatches of co-evolved species, unexpected trophic effects, and shifts of fishing grounds. These results provide hypotheses of

  20. Sapling performance along resource gradients drives tree species distributions within and across tropical forests

    NARCIS (Netherlands)

    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

  1. Geographical distribution and ecology of the Armillaria species in western Europe.

    NARCIS (Netherlands)

    Guillaumin, J.J.; Mohammed, C.; Anselmi, N.; Courtecuisse, R.; Gregory, S.C.; Holdenrieder, O.; Intini, M.; Lung, B.; Marxmüller, H.; Morrison, D.; Rishbeth, J.; Termorshuizen, A.J.; Tirro, A.; Dam, van B.

    1993-01-01

    Over 4000 records of the six European Armillaria species were compiled to give distribution maps and host lists for each species. Differences in geographical and altitudinal distribution, pathogenicity, dissemination and ecological role are discussed.

  2. Model-based uncertainty in species range prediction

    DEFF Research Database (Denmark)

    Pearson, R. G.; Thuiller, Wilfried; Bastos Araujo, Miguel

    2006-01-01

    algorithm when extrapolating beyond the range of data used to build the model. The effects of these factors should be carefully considered when using this modelling approach to predict species ranges. Main conclusions We highlight an important source of uncertainty in assessments of the impacts of climate......Aim Many attempts to predict the potential range of species rely on environmental niche (or 'bioclimate envelope') modelling, yet the effects of using different niche-based methodologies require further investigation. Here we investigate the impact that the choice of model can have on predictions......, identify key reasons why model output may differ and discuss the implications that model uncertainty has for policy-guiding applications. Location The Western Cape of South Africa. Methods We applied nine of the most widely used modelling techniques to model potential distributions under current...

  3. Geographic distribution, evolution, and disease importance of species within the Neotropical Anopheles albitarsis Group (Diptera, Culicidae).

    Science.gov (United States)

    Foley, Desmond H; Linton, Yvonne-Marie; Ruiz-Lopez, J Freddy; Conn, Jan E; Sallum, Maria Anice M; Póvoa, Marinete M; Bergo, Eduardo S; Oliveira, Tatiane M P; Sucupira, Izis; Wilkerson, Richard C

    2014-06-01

    The Anopheles albitarsis group of mosquitoes comprises eight recognized species and one mitochondrial lineage. Our knowledge of malaria vectorial importance and the distribution and evolution of these taxa is incomplete. We constructed ecological niche models (ENMs) for these taxa and used hypothesized phylogenetic relationships and ENMs to investigate environmental and ecological divergence associated with speciation events. Two major clades were identified, one north (Clade 1) and one south (Clade 2) of the Amazon River that likely is or was a barrier to mosquito movement. Clade 1 species occur more often in higher average temperature locations than Clade 2 species, and taxon splits within Clade 1 corresponded with a greater divergence of variables related to precipitation than was the case within Clade 2. Comparison of the ecological profiles of sympatric species and sister species support the idea that phylogenetic proximity is related to ecological similarity. Anopheles albitarsis I, An. janconnae, and An. marajoara ENMs had the highest percentage of their predicted suitable habitat overlapping distribution models of Plasmodium falciparum and P. vivax, and warrant additional studies of the transmission potential of these species. Phylogenetic proximity may be related to malaria vectorial importance within the Albitarsis Group. © 2014 The Society for Vector Ecology.

  4. Distribution of Studied Insectivorous Bat Species of Myanmar

    International Nuclear Information System (INIS)

    Nyo Nyo

    2005-10-01

    Fourty-five species of insectivourous bats; Craseonycteris thonglongyai, Emballonura monticola, Taphozous melenopongon, T. theobaldi, T. longimanus, Megaderma lyra, M. spasma, Rhinolophus affinis, R. rouxii, R. pusillus, R. lepidus, R. macrotis, R. trifoliatus, R. pearsoni, R. malayanus, R. stheno, R. thomasi, R. shameli, R. acuminatus, R. marshalli, Rhinolophus sp., Hipposideros pomona, H. larvatus, H. armiger, H. lylei, H. ater, H. fulvus, Aselliscus stoliczkanus, Tadarida plicata, Myotis siligorensis, M. muricola, M. horsfieldii, M. hasseltii, M. chinensis, Scotophilus heathii, S. kuhlii, Ia io, Pipistrellus javanicus, P. coromandra, P. pulveratus, P. paterculus, P. affinis, P. ceylonicus, Miniopterus pusillus and M. magnater were distributed in 7 Divisions; Yangon, Bago, Ayeyawady, Taninthayi, Magway, Mandalay and Sagaing Division, and 7 States; Mon, Kayin, Shan, Chin, Kayah, Kachin and Rakhine States of Myanmar.

  5. Comparative Distributions of Hazard Modeling Analysis

    Directory of Open Access Journals (Sweden)

    Rana Abdul Wajid

    2006-07-01

    Full Text Available In this paper we present the comparison among the distributions used in hazard analysis. Simulation technique has been used to study the behavior of hazard distribution modules. The fundamentals of Hazard issues are discussed using failure criteria. We present the flexibility of the hazard modeling distribution that approaches to different distributions.

  6. Citizen science contributes to our knowledge of invasive plant species distributions

    Science.gov (United States)

    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.

  7. Termite Species Distribution and Flight Periods on Oahu, Hawaii.

    Science.gov (United States)

    Tong, Reina L; Grace, J Kenneth; Mason, Makena; Krushelnycky, Paul D; Spafford, Helen; Aihara-Sasaki, Maria

    2017-06-05

    Termites are economically-important structural pests, costing residents of Hawaii over $100 million annually. On Oahu, the last published termite swarming survey occurred from 1969 to 1971, and the last termite hand-collection survey occurred from 1998 to 2000. To contribute data on termite occurrences on Oahu, a light-trap survey took place from February 2011 to September 2012, and a hand-collection survey occurred from September to November 2012. Formosan subterranean termite, Coptotermes formosanus Shiraki, swarming was compared over the duration of the study, finding peak swarming in May 2011. C. formosanus alate activity density was regressed with environmental factors, finding a negative correlation with average wind speed and a positive correlation with average rainfall. Coptotermes gestroi (Wasmann) alates were observed in April, June, and July 2011 and in June 2012. Four species of termites were found in the hand-collection survey of 44 sites: Incisitermes immigrans (Snyder) ( n = 8/44), C. formosanus ( n = 2/44), Cryptotermes cynocephalus Light ( n = 1/44), and Neotermes sp. ( n = 1/44). This study contributes to distribution data for termite species on Oahu and records alate activity for two important termite pests.

  8. Distribution of positive ion species above a diffuse midnight aurora

    International Nuclear Information System (INIS)

    Moore, T.E.

    1978-01-01

    The origin of the hot plasma in the Earth's magnetosphere is still open to investigation. Mass composition is an indicator of source region, while the distribution functions bear the signatures of transport and energization processes. Only ions identified as H + and He ++ were detected, and the He ++ was statistically marginal. Coincident magnetic storms are likely to play a crucial role in populating the magnetosphere with energized ionospheric ions. The measured proton distribution was nearly isotropic over downcoming pitch angles at all energies and showed a depleted atmospheric source cone. The high-altitude proton energy distribution had a best fit temperature of 4.5 keV and a number density of 0.17 cm- 3 , corresponding to a peak intensity just over 10 5 cm -2 s -1 sr -1 keV -1 . Altitudinal variations are consistent with the theory of charge exchange of a time-steady incident proton population. Simultaneous electron measurements can be interpreted in terms of an incident electron distribution that is also thermal wih a similar number density but a temperature of 2.5 keV. Taken together, the ion and electron data are consistent with the model of diffuse auroras in which plasma convecting in from the magnetospheric tail precipitates due to strong pitch angle diffusion on auroral field lines linking the near Earth plasma sheet

  9. Predicting fine-scale distributions of peripheral aquatic species in headwater streams

    Science.gov (United States)

    DeRolph, Christopher R.; Nelson, S.; Kwak, Thomas J.; Hain, Ernie F.

    2015-01-01

    Headwater species and peripheral populations that occupy habitat at the edge of a species range may hold an increased conservation value to managers due to their potential to maximize intraspecies diversity and species' adaptive capabilities in the context of rapid environmental change. The southern Appalachian Mountains are the southern extent of the geographic range of native Salvelinus fontinalis and naturalized Oncorhynchus mykiss and Salmo trutta in eastern North America. We predicted distributions of these peripheral, headwater wild trout populations at a fine scale to serve as a planning and management tool for resource managers to maximize resistance and resilience of these populations in the face of anthropogenic stressors. We developed correlative logistic regression models to predict occurrence of brook trout, rainbow trout, and brown trout for every interconfluence stream reach in the study area. A stream network was generated to capture a more consistent representation of headwater streams. Each of the final models had four significant metrics in common: stream order, fragmentation, precipitation, and land cover. Strahler stream order was found to be the most influential variable in two of the three final models and the second most influential variable in the other model. Greater than 70% presence accuracy was achieved for all three models. The underrepresentation of headwater streams in commonly used hydrography datasets is an important consideration that warrants close examination when forecasting headwater species distributions and range estimates. Additionally, it appears that a relative watershed position metric (e.g., stream order) is an important surrogate variable (even when elevation is included) for biotic interactions across the landscape in areas where headwater species distributions are influenced by topographical gradients.

  10. Diameter distribution in a Brazilian tropical dry forest domain: predictions for the stand and species.

    Science.gov (United States)

    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.

  11. Assessing distributions of two invasive species of contrasting habits in future climate.

    Science.gov (United States)

    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.

  12. A new species of Desmopachria Babington (Coleoptera: Dytiscidae) from Cuba with a prediction of its geographic distribution and notes on other Cuban species of the genus.

    Science.gov (United States)

    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.

  13. Predictive Modeling and Mapping of Malayan Sun Bear (Helarctos malayanus) Distribution Using Maximum Entropy

    OpenAIRE

    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 ...

  14. Reevaluating species number, distribution and endemism of the coral genus Pocillopora Lamarck, 1816 using species delimitation methods and microsatellites.

    Science.gov (United States)

    Gélin, P; Postaire, B; Fauvelot, C; Magalon, H

    2017-04-01

    Species delimitation methods based on genetic information, notably using single locus data, have been proposed as means of increasing the rate of biodiversity description, but can also be used to clarify complex taxonomies. In this study, we explore the species diversity within the cnidarian genus Pocillopora, widely distributed in the tropical belt of the Indo-Pacific Ocean. From 943 Pocillopora colonies sampled in the Western Indian Ocean, the Tropical Southwestern Pacific and Southeast Polynesia, representing a huge variety of morphotypes, we delineated Primary Species Hypotheses (PSH) applying the Automatic Barcode Gap Discovery method, the Poisson Tree Processes algorithm and the Generalized mixed Yule-coalescent model on two mitochondrial markers (Open Reading Frame and Dloop) and reconstructing a haploweb using one nuclear marker (Internal Transcribed Spacer 2). Then, we confronted identified PSHs to the results of clustering analyses using 13 microsatellites to determine Secondary Species Hypotheses (SSH). Based on the congruence of all methods used and adding sequences from the literature, we defined at least 18 Secondary Species Hypotheses among 14 morphotypes, confirming the high phenotypic plasticity in Pocillopora species and the presence of cryptic lineages. We also identified three new genetic lineages never found to date, which could represent three new putative species. Moreover, the biogeographical ranges of several SSHs were re-assessed in the light of genetic data, which may have direct implications in conservation policies. Indeed, the cryptic diversity within this genus should be taken into account seriously, as neglecting its importance is source of confusion in our understanding of ecosystem functioning. Next generation sequencing, combined with other parameters (i.e. microstructure, zooxanthellae identification, ecology even at a micro-scale, resistance and resilience ability to bleaching) will be the next step towards an integrative

  15. Simplifying biochemical models with intermediate species

    DEFF Research Database (Denmark)

    Feliu, Elisenda; Wiuf, Carsten

    2013-01-01

    Mathematical models are increasingly being used to understand complex biochemical systems, to analyse experimental data and make predictions about unobserved quantities. However, we rarely know how robust our conclusions are with respect to the choice and uncertainties of the model. Using algebraic......-state concentrations of the species in the core model, after suitable matching of parameters. Importantly, our results provide guidelines to the modeller in choosing between models and in distinguishing their properties. Further, our work provides a formal way of comparing models that share a common skeleton....

  16. Climate and soil type together explain the distribution of microendemic species in a biodiversity hotspot.

    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.

  17. Current Knowledge of Leishmania Vectors in Mexico: How Geographic Distributions of Species Relate to Transmission Areas

    OpenAIRE

    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...

  18. Effects of climate change on three species of Cupido (Lepidoptera, Lycaenidae) with different biogeographic distribution in Andalusia, southern Spain

    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)

  19. Effects of climate change on three species of Cupido (Lepidoptera, Lycaenidae with different biogeographic distribution in Andalusia, southern Spain

    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.

  20. Mollusca of the Magellan Region. A checklist of the species and their distribution

    Directory of Open Access Journals (Sweden)

    Katrin Linse

    1999-12-01

    Full Text Available The Molluscan species collected during the Victor Hensen Joint Magellan Campaign 1994 served as the basis for this species list. The list was then completed by literature data on the distribution of molluscs around the Falkland Islands, the other Scotia Arc Islands, Antarctica and the Kerguelen Islands. 397 Magellan species are known: 10 species of Aplacophora, 250 species of Gastropoda, 6 species of Scaphopoda and 131 species of Bivalvia. Polyplacophora and Cephalopoda are not included because both taxa need revision.

  1. Predicting the potential distribution of invasive exotic species using GIS and information-theoretic approaches: A case of ragweed (Ambrosia artemisiifolia L.) distribution in China

    Science.gov (United States)

    Hao, Chen; LiJun, Chen; Albright, Thomas P.

    2007-01-01

    Invasive exotic species pose a growing threat to the economy, public health, and ecological integrity of nations worldwide. Explaining and predicting the spatial distribution of invasive exotic species is of great importance to prevention and early warning efforts. We are investigating the potential distribution of invasive exotic species, the environmental factors that influence these distributions, and the ability to predict them using statistical and information-theoretic approaches. For some species, detailed presence/absence occurrence data are available, allowing the use of a variety of standard statistical techniques. However, for most species, absence data are not available. Presented with the challenge of developing a model based on presence-only information, we developed an improved logistic regression approach using Information Theory and Frequency Statistics to produce a relative suitability map. This paper generated a variety of distributions of ragweed (Ambrosia artemisiifolia L.) from logistic regression models applied to herbarium specimen location data and a suite of GIS layers including climatic, topographic, and land cover information. Our logistic regression model was based on Akaike's Information Criterion (AIC) from a suite of ecologically reasonable predictor variables. Based on the results we provided a new Frequency Statistical method to compartmentalize habitat-suitability in the native range. Finally, we used the model and the compartmentalized criterion developed in native ranges to "project" a potential distribution onto the exotic ranges to build habitat-suitability maps. ?? Science in China Press 2007.

  2. Distributions with given marginals and statistical modelling

    CERN Document Server

    Fortiana, Josep; Rodriguez-Lallena, José

    2002-01-01

    This book contains a selection of the papers presented at the meeting `Distributions with given marginals and statistical modelling', held in Barcelona (Spain), July 17-20, 2000. In 24 chapters, this book covers topics such as the theory of copulas and quasi-copulas, the theory and compatibility of distributions, models for survival distributions and other well-known distributions, time series, categorical models, definition and estimation of measures of dependence, monotonicity and stochastic ordering, shape and separability of distributions, hidden truncation models, diagonal families, orthogonal expansions, tests of independence, and goodness of fit assessment. These topics share the use and properties of distributions with given marginals, this being the fourth specialised text on this theme. The innovative aspect of the book is the inclusion of statistical aspects such as modelling, Bayesian statistics, estimation, and tests.

  3. Modelling community dynamics based on species-level abundance models from detection/nondetection data

    Science.gov (United States)

    Yamaura, Yuichi; Royle, J. Andrew; Kuboi, Kouji; Tada, Tsuneo; Ikeno, Susumu; Makino, Shun'ichi

    2011-01-01

    1. In large-scale field surveys, a binary recording of each species' detection or nondetection has been increasingly adopted for its simplicity and low cost. Because of the importance of abundance in many studies, it is desirable to obtain inferences about abundance at species-, functional group-, and community-levels from such binary data. 2. We developed a novel hierarchical multi-species abundance model based on species-level detection/nondetection data. The model accounts for the existence of undetected species, and variability in abundance and detectability among species. Species-level detection/nondetection is linked to species- level abundance via a detection model that accommodates the expectation that probability of detection (at least one individuals is detected) increases with local abundance of the species. We applied this model to a 9-year dataset composed of the detection/nondetection of forest birds, at a single post-fire site (from 7 to 15 years after fire) in a montane area of central Japan. The model allocated undetected species into one of the predefined functional groups by assuming a prior distribution on individual group membership. 3. The results suggest that 15–20 species were missed in each year, and that species richness of communities and functional groups did not change with post-fire forest succession. Overall abundance of birds and abundance of functional groups tended to increase over time, although only in the winter, while decreases in detectabilities were observed in several species. 4. Synthesis and applications. Understanding and prediction of large-scale biodiversity dynamics partly hinge on how we can use data effectively. Our hierarchical model for detection/nondetection data estimates abundance in space/time at species-, functional group-, and community-levels while accounting for undetected individuals and species. It also permits comparison of multiple communities by many types of abundance-based diversity and similarity

  4. Climate change and the distribution of neotropical red-bellied toads (Melanophryniscus, Anura, Amphibia): how to prioritize species and populations?

    Science.gov (United States)

    Zank, Caroline; Becker, Fernando Gertum; Abadie, Michelle; Baldo, Diego; Maneyro, Raúl; Borges-Martins, Márcio

    2014-01-01

    We used species distribution modeling to investigate the potential effects of climate change on 24 species of Neotropical anurans of the genus Melanophryniscus. These toads are small, have limited mobility, and a high percentage are endangered or present restricted geographical distributions. We looked at the changes in the size of suitable climatic regions and in the numbers of known occurrence sites within the distribution limits of all species. We used the MaxEnt algorithm to project current and future suitable climatic areas (a consensus of IPCC scenarios A2a and B2a for 2020 and 2080) for each species. 40% of the species may lose over 50% of their potential distribution area by 2080, whereas 28% of species may lose less than 10%. Four species had over 40% of the currently known occurrence sites outside the predicted 2080 areas. The effect of climate change (decrease in climatic suitable areas) did not differ according to the present distribution area, major habitat type or phylogenetic group of the studied species. We used the estimated decrease in specific suitable climatic range to set a conservation priority rank for Melanophryniscus species. Four species were set to high conservation priority: M. montevidensis, (100% of its original suitable range and all known occurrence points potentially lost by 2080), M. sp.2, M. cambaraensis, and M. tumifrons. Three species (M. spectabilis, M. stelzneri, and M. sp.3) were set between high to intermediate priority (more than 60% decrease in area predicted by 2080); nine species were ranked as intermediate priority, while eight species were ranked as low conservation priority. We suggest that monitoring and conservation actions should be focused primarily on those species and populations that are likely to lose the largest area of suitable climate and the largest number of known populations in the short-term.

  5. Climate change and the distribution of neotropical red-bellied toads (Melanophryniscus, Anura, Amphibia: how to prioritize species and populations?

    Directory of Open Access Journals (Sweden)

    Caroline Zank

    Full Text Available We used species distribution modeling to investigate the potential effects of climate change on 24 species of Neotropical anurans of the genus Melanophryniscus. These toads are small, have limited mobility, and a high percentage are endangered or present restricted geographical distributions. We looked at the changes in the size of suitable climatic regions and in the numbers of known occurrence sites within the distribution limits of all species. We used the MaxEnt algorithm to project current and future suitable climatic areas (a consensus of IPCC scenarios A2a and B2a for 2020 and 2080 for each species. 40% of the species may lose over 50% of their potential distribution area by 2080, whereas 28% of species may lose less than 10%. Four species had over 40% of the currently known occurrence sites outside the predicted 2080 areas. The effect of climate change (decrease in climatic suitable areas did not differ according to the present distribution area, major habitat type or phylogenetic group of the studied species. We used the estimated decrease in specific suitable climatic range to set a conservation priority rank for Melanophryniscus species. Four species were set to high conservation priority: M. montevidensis, (100% of its original suitable range and all known occurrence points potentially lost by 2080, M. sp.2, M. cambaraensis, and M. tumifrons. Three species (M. spectabilis, M. stelzneri, and M. sp.3 were set between high to intermediate priority (more than 60% decrease in area predicted by 2080; nine species were ranked as intermediate priority, while eight species were ranked as low conservation priority. We suggest that monitoring and conservation actions should be focused primarily on those species and populations that are likely to lose the largest area of suitable climate and the largest number of known populations in the short-term.

  6. Future distribution of Arctic char Salvelinus alpinus in Sweden under climate change: effects of temperature, lake size and species interactions.

    Science.gov (United States)

    Hein, Catherine L; Ohlund, Gunnar; Englund, Göran

    2012-01-01

    Novel communities will be formed as species with a variety of dispersal abilities and environmental tolerances respond individually to climate change. Thus, models projecting future species distributions must account for species interactions and differential dispersal abilities. We developed a species distribution model for Arctic char Salvelinus alpinus, a freshwater fish that is sensitive both to warm temperatures and to species interactions. A logistic regression model using lake area, mean annual air temperature (1961-1990), pike Esox lucius and brown trout Salmo trutta occurrence correctly classified 95 % of 467 Swedish lakes. We predicted that Arctic char will lose 73 % of its range in Sweden by 2100. Predicted extinctions could be attributed both to simulated temperature increases and to projected pike invasions. The Swedish mountains will continue to provide refugia for Arctic char in the future and should be the focus of conservation efforts for this highly valued fish.

  7. Distance distribution in configuration-model networks

    Science.gov (United States)

    Nitzan, Mor; Katzav, Eytan; Kühn, Reimer; Biham, Ofer

    2016-06-01

    We present analytical results for the distribution of shortest path lengths between random pairs of nodes in configuration model networks. The results, which are based on recursion equations, are shown to be in good agreement with numerical simulations for networks with degenerate, binomial, and power-law degree distributions. The mean, mode, and variance of the distribution of shortest path lengths are also evaluated. These results provide expressions for central measures and dispersion measures of the distribution of shortest path lengths in terms of moments of the degree distribution, illuminating the connection between the two distributions.

  8. Current Knowledge of Leishmania Vectors in Mexico: How Geographic Distributions of Species Relate to Transmission Areas

    Science.gov (United States)

    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

  9. Current knowledge of Leishmania vectors in Mexico: how geographic distributions of species relate to transmission areas.

    Science.gov (United States)

    González, Camila; Rebollar-Téllez, Eduardo A; Ibáñez-Bernal, Sergio; Becker-Fauser, Ingeborg; Martínez-Meyer, Enrique; Peterson, A Townsend; Sánchez-Cordero, Víctor

    2011-11-01

    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.

  10. Photovoltaic subsystem marketing and distribution model

    Energy Technology Data Exchange (ETDEWEB)

    None

    1982-04-01

    The purpose of the marketing and distribution model is to estimate the costs of selling and transporting photovoltaic solar energy products from the factory to the factory customer. The model adjusts for inflation and regional differences in marketing and distribution costs. The model consists of three major components: the marketing submodel, the distribution submodel, and the financial submodel. What the model can and cannot do, and what data are required is explained. An example for a power conditioning unit demonstrates the application of the model.

  11. [Species identification of freshwater snail Planorbella trivolvis and analysis of its potential distribution].

    Science.gov (United States)

    Li, Xiao-heng; Gao, Shi-tong; Gu, Wen-biao; Zhang, Yi; Guo, Yun-hai

    2015-06-01

    To identify the species classification of an ornamental Planorbidae from a flower market in Shanghai and analyze its potential distribution in China. In August 2013, six freshwater snail specimens were collected from the Wanshang flower market. The species was identified by morphology and molecular biology. An ecological niche model was constructed based on the native geographic presence occurrence data, and projected onto the whole of China to predict the potential distribution. Their shell external morphology suggested that the specimens belonged to Planorbella trivolvis (Say 1817) of Planorbidae, which is native in North America. The sequence data of a fragment of the mitochondrial cytochrome c oxidase subunit I (COI) confirmed its identification. A total of 2 294 georeferenced occurrence points in North America were carried out from the Global Biodiversity Information Facility databases and 614 records with coordinates were used to produce a North American native niche model by a maximum entropy method (Maxent). The projection on China results suggested high probabilities of occurrence mostly in Henan Province and its borderland with nearby provinces. P. trivolvis is similarly with Biomphalaria species from shell morphology. It is the first records of the species in China, and the field dispersal is not clear.

  12. Distribution patterns of rare earth elements in various plant species

    Energy Technology Data Exchange (ETDEWEB)

    Wyttenbach, A.; Tobler, L.; Furrer, V. [Paul Scherrer Inst. (PSI), Villigen (Switzerland)

    1997-09-01

    The elements La, Ce, Nd, Sm, Eu, Gd, Tb, Yb and Lu have been determined in 6 different plant species by neutron activation analysis. When the concentrations of each species were normalized to Norway spruce, smooth curves were obtained which revealed systematic inter-species differences. (author) 3 figs., 4 refs.

  13. Distribution, animal preference and nutritive value of browse species ...

    African Journals Online (AJOL)

    Local pastoralists are knowledgeable about the ecology and use, and the change in vegetation structure of browse species. Browse species ranking, according to local criteria of use of vegetation species, indicated that Acacia oerfota was ranked first (3.77) followed by A. etbaica (3.88), Balanites aegyptiaca (4.55) and A.

  14. Rapid upslope shifts in New Guinean birds illustrate strong distributional responses of tropical montane species to global warming.

    Science.gov (United States)

    Freeman, Benjamin G; Class Freeman, Alexandra M

    2014-03-25

    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.

  15. Rapid upslope shifts in New Guinean birds illustrate strong distributional responses of tropical montane species to global warming

    Science.gov (United States)

    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

  16. Recurrent sublethal warming reduces embryonic survival, inhibits juvenile growth, and alters species distribution projections under climate change.

    Science.gov (United States)

    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.

  17. Distribution and occupancy of introduced species: a baseline inventory from Phase 3 plots across the country

    Science.gov (United States)

    Bethany K. Schulz; W. Keith. Moser

    2012-01-01

    Invasive plant species have significant negative impacts in many ecosystems and are found in many forests around the world. Although not all introduced species become invasive, there are numerous examples of species escaping cultivation and invading natural ecosystems years or even decades after their initial introduction. Regional distributions of invasive species are...

  18. Gridded Species Distribution, Version 1: Birds of the Americas Presence Grids

    Data.gov (United States)

    National Aeronautics and Space Administration — The Birds of the Americas Family Presence Grids of the Gridded Species Distribution, Version 1 is a reclassified version of the original grids of the bird species...

  19. 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.

  20. Topographic variables improve climate models of forage species abundance in the northeastern United States

    Science.gov (United States)

    Species distribution modeling has most commonly been applied to presence-only data and to woody species, but detailed predicted abundance maps for forage species would be of great value for agricultural management and land use planning. We used field data from 107 farms across the northeastern Unite...

  1. Testing projected wild bee distributions in agricultural habitats: predictive power depends on species traits and habitat type

    NARCIS (Netherlands)

    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

  2. Relating biomarkers to whole-organism effects using species sensitivity distributions: a pilot study for marine species exposed to oil

    NARCIS (Netherlands)

    Smit, M.G.D.; Bechmann, R.K.; Hendriks, A.J.; Skadsheim, A.; Larsen, B.K.

    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

  3. Relating biomarkers to whole-organism effects using species sensitivity distributions : A pilot study for marine species exposed to oil

    NARCIS (Netherlands)

    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

  4. A spatial pattern analysis of the halophytic species distribution in an arid coastal environment.

    Science.gov (United States)

    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.

  5. Topographic and spatial controls of palm species distributions in a montane rain forest, southern Ecuador

    DEFF Research Database (Denmark)

    Svenning, J.-C.; Harlev, D.; Sørensen, M.M.

    2009-01-01

    location as factors controlling species distributions in a palm community in a montane rain forest landscape in the Andes of southern Ecuador (1900-2150 m above sea level). Eleven species were present: Aiphanes verrucosa, Ceroxylon parvifrons, Chamaedorea pinnatifrons, Dictyocaryum lamarckianum, Euterpe......). 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......-association of some species corresponded to their general elevational ranges in southern Ecuador, this was not the case for other species. Based on such considerations, we conclude that elevational climatic gradients are likely to only form part of the explanation for the topographic effects on palm species...

  6. 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... swampy areas. In Orissa (Kirtania, Balramgari, Paradeep, Khairnasi and Gopalpur), the population of the horseshoe crab showed only the presence of Tachypleus gigas (Müller). New record of the sympatric distribution of two Asian species of the horses...

  7. Testing projected wild bee distributions in agricultural habitats: predictive power depends on species traits and habitat type.

    Science.gov (United States)

    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

  8. Distributed modeling for road authorities

    NARCIS (Netherlands)

    Luiten, G.T.; Bõhms, H.M.; Nederveen, S. van; Bektas, E.

    2013-01-01

    A great challenge for road authorities is to improve the effectiveness and efficiency of their core processes by improving data exchange and sharing using new technologies such as building information modeling (BIM). BIM has already been successfully implemented in other sectors, such as

  9. Iodine uptake and distribution in horticultural and fruit tree species

    Directory of Open Access Journals (Sweden)

    Alessandra Caffagni

    2012-07-01

    Full Text Available Iodine is an essential microelement for humans and iodine deficiency disorder (IDD is one of the most widespread nutrient-deficiency diseases in the world. Iodine biofortification of plants provides an attractive opportunity to increase iodine intake in humans and to prevent and control IDD. This study was conducted to investigate the iodine uptake and accumulation in edible portion of two fruit trees: plum and nectarine, and two horticultural crops: tomato and potato. Two type of iodine treatments (soil and foliar spray application, and, for fresh market tomato, two production systems (open field and greenhouse hydroponic culture were tested. The distribution of iodine in potato stem and leaves, and in plum tree fruits, leaves, and branches was investigated. Iodine content of potato tubers after postharvest storage and processing (cooking, and iodine content of nectarine fruits after postharvest storage and processing (peeling were also determined. Differences in iodine accumulation were observed among the four crops, between applications, and between production systems. In open field, the maximum iodine content ranged from 9.5 and 14.3 μg 100 g−1 for plum and nectarine fruit, to 89.4 and 144.0 μg 100 g−1 for potato tuber and tomato fruit, respectively. These results showed that nectarine and plum tree accumulated significantly lower amounts of iodine in their edible tissues, in comparison with potato and tomato. The experiments also indicated hydroponic culture as the most efficient system for iodine uptake in tomato, since its fresh fruits accumulated up to 2423 μg 100 g−1 of iodine. Iodine was stored mainly in the leaves, in all species investigated. Only a small portion of iodine was moved to plum tree branches and fruits, and to potato stems and tubers. No differences in iodine content after fruit peeling was observed. A significant increase in iodine content of potato was observed after baking, whereas a significant decrease was

  10. Endangered Fish Species in Kansas: Historic vs Contemporary Distribution

    Science.gov (United States)

    Background/Question/Methods Kansas state has more freshwater fish species than other states in the west and northern US. Based on recent count, more than 140 fishes have been documented in Kansas rivers. And at least five are categorized as endangered species in Kansas (and thre...

  11. Abundance, distribution and species composition of fish larvae in ...

    African Journals Online (AJOL)

    An attemptwas made to correlate the data with environmental parameters such as temperature, salinity and rainfall. The ichthyoplankton of the Swartkops is dominated by few species. The family Gobiidae (59,44%) and a clupeid species, Gilchristella aestuarius (31,12%), accounted for 90,56% of all the fish larvae sampled.

  12. Ring distributions leading to species formation: a global topographic analysis of geographic barriers associated with ring species.

    Science.gov (United States)

    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

  13. Ring distributions leading to species formation: a global topographic analysis of geographic barriers associated with ring species

    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

  14. Modeling of Species Transport and Macrosegregation in Heavy Steel Ingots

    Science.gov (United States)

    Li, Wensheng; Shen, Houfa; Zhang, Xiong; Liu, Baicheng

    2014-04-01

    In the current study, two significant phenomena involved in heavy steel ingot casting, i.e., species transport and macrosegregation, were numerically simulated. First, a ladle-tundish-mold species transport model describing the entire multiple pouring process of heavy steel ingots was proposed. Carbon distribution and variation in both the tundish and the mold of a 292-ton steel ingot were predicted. Results indicate high carbon concentration in the bottom of the mold while low concentration carbon at the top of mold after the pouring process. Such concentration distribution helps in reducing both negative segregation in the bottom of the solidified ingot and positive segregation at the top. Second, a two-phase multiscale macrosegregation model was used to simulate the solidification process of industrial steel ingots. This model takes into account heat transfer, fluid flow, solute transport, and equiaxed grain motion on a system scale, as well as grain nucleation and growth on a microscopic scale. The model was first used to analyze a three-dimensional industry-scale steel ingot as a benchmark. Then, it was applied to study macrosegregation formation in a 53-ton steel ingot. Macrosegregation predicted by the numerical model was presented and compared with experimental measurements. Typical macrosegregation patterns in heavy steel ingots are found to be well reproduced with the two-phase model.

  15. Ascidians (Tunicata, Ascidiacea: species distribution along the Scotia Arc

    Directory of Open Access Journals (Sweden)

    Marcos Tatiàn

    2005-12-01

    Full Text Available Ascidians are found in all the oceans. The Polar Front is considered a strong barrier, especially for benthic organisms, separating the Southern Ocean from other oceans. Its influence on ascidian species present at the boundary of the Magellan and Antarctic regions along the Scotia Arc and on the species composition at each station is inferred from the samples taken during the “LAMPOS” cruise. Ascidians were collected by Agassiz (AGT and bottom (GSN trawls at depths between 250 and 587 m on different types of substrate. Of 25 identified species/morphospecies one is new and eight were found in new localities, enlarging the known range of five of these species. Muddy bottoms were found to support higher species richness than hard bottoms, and the South Georgia Islands are found to be the northern limit for Antarctic species and the southern limit for Magellan ones. Affinity between the ascidian fauna of the Magellan region and the Antarctic is slightly stronger than was previously considered; there is also a species gradient along the Scotia Arc, which can be regarded as a bridge between the two regions.

  16. Economic Models and Algorithms for Distributed Systems

    CERN Document Server

    Neumann, Dirk; Altmann, Jorn; Rana, Omer F

    2009-01-01

    Distributed computing models for sharing resources such as Grids, Peer-to-Peer systems, or voluntary computing are becoming increasingly popular. This book intends to discover fresh avenues of research and amendments to existing technologies, aiming at the successful deployment of commercial distributed systems

  17. Climate change versus deforestation: Implications for tree species distribution in the dry forests of southern Ecuador.

    Science.gov (United States)

    Manchego, Carlos E; Hildebrandt, Patrick; Cueva, Jorge; Espinosa, Carlos Iván; Stimm, Bernd; Günter, Sven

    2017-01-01

    Seasonally dry forests in the neotropics are heavily threatened by a combination of human disturbances and climate change; however, the severity of these threats is seldom contrasted. This study aims to quantify and compare the effects of deforestation and climate change on the natural spatial ranges of 17 characteristic tree species of southern Ecuador dry deciduous forests, which are heavily fragmented and support high levels of endemism as part of the Tumbesian ecoregion. We used 660 plant records to generate species distribution models and land-cover data to project species ranges for two time frames: a simulated deforestation scenario from 2008 to 2014 with native forest to anthropogenic land-use conversion, and an extreme climate change scenario (CCSM4.0, RCP 8.5) for 2050, which assumed zero change from human activities. To assess both potential threats, we compared the estimated annual rates of species loss (i.e., range shifts) affecting each species. Deforestation loss for all species averaged approximately 71 km2/year, while potential climate-attributed loss was almost 21 km2/year. Moreover, annual area loss rates due to deforestation were significantly higher than those attributed to climate-change (P < 0.01). However, projections into the future scenario show evidence of diverging displacement patterns, indicating the potential formation of novel ecosystems, which is consistent with other species assemblage predictions as result of climate change. Furthermore, we provide recommendations for management and conservation, prioritizing the most threatened species such as Albizia multiflora, Ceiba trichistandra, and Cochlospermum vitifolium.

  18. The roles of competition and habitat in the dynamics of populations and species distributions

    Science.gov (United States)

    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

  19. An updated understanding of Texas bumble bee (Hymenoptera: Apidae species presence and potential distributions in Texas, USA

    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.

  20. Distributed simulation a model driven engineering approach

    CERN Document Server

    Topçu, Okan; Oğuztüzün, Halit; Yilmaz, Levent

    2016-01-01

    Backed by substantive case studies, the novel approach to software engineering for distributed simulation outlined in this text demonstrates the potent synergies between model-driven techniques, simulation, intelligent agents, and computer systems development.

  1. Uncertainties in predicting species distributions under climate change: a case study using Tetranychus evansi (Acari: Tetranychidae), a widespread agricultural pest.

    Science.gov (United States)

    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

  2. Uncertainties in predicting species distributions under climate change: a case study using Tetranychus evansi (Acari: Tetranychidae, a widespread agricultural pest.

    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

  3. The influence of electrohydrodynamic flow on the distribution of chemical species in positive corona

    Science.gov (United States)

    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.

  4. Does scale matter? A systematic review of incorporating biological realism when predicting changes in species distributions.

    Science.gov (United States)

    Record, Sydne; Strecker, Angela; Tuanmu, Mao-Ning; Beaudro