WorldWideScience

Sample records for modelling species distribution

  1. 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].

  2. 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].

  3. Bounding species distribution models

    Institute of Scientific and Technical Information of China (English)

    Thomas J. STOHLGREN; Catherine S. JARNEVICH; Wayne E. ESAIAS; Jeffrey T. MORISETTE

    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. 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 stu

  5. 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

  6. Confronting species distribution model predictions with species functional traits.

    Science.gov (United States)

    Wittmann, Marion E; Barnes, Matthew A; Jerde, Christopher L; Jones, Lisa A; Lodge, David M

    2016-02-01

    Species distribution models are valuable tools in studies of biogeography, ecology, and climate change and have been used to inform conservation and ecosystem management. However, species distribution models typically incorporate only climatic variables and species presence data. Model development or validation rarely considers functional components of species traits or other types of biological data. We implemented a species distribution model (Maxent) to predict global climate habitat suitability for Grass Carp (Ctenopharyngodon idella). We then tested the relationship between the degree of climate habitat suitability predicted by Maxent and the individual growth rates of both wild (N = 17) and stocked (N = 51) Grass Carp populations using correlation analysis. The Grass Carp Maxent model accurately reflected the global occurrence data (AUC = 0.904). Observations of Grass Carp growth rate covered six continents and ranged from 0.19 to 20.1 g day(-1). Species distribution model predictions were correlated (r = 0.5, 95% CI (0.03, 0.79)) with observed growth rates for wild Grass Carp populations but were not correlated (r = -0.26, 95% CI (-0.5, 0.012)) with stocked populations. Further, a review of the literature indicates that the few studies for other species that have previously assessed the relationship between the degree of predicted climate habitat suitability and species functional traits have also discovered significant relationships. Thus, species distribution models may provide inferences beyond just where a species may occur, providing a useful tool to understand the linkage between species distributions and underlying biological mechanisms.

  7. Applications of species distribution modeling to paleobiology

    DEFF Research Database (Denmark)

    Svenning, J.-C.; Fløjgaard, Camilla; A. Marske, Katharine

    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. Pseudoabsence generation strategies for species distribution models.

    Directory of Open Access Journals (Sweden)

    Brice B Hanberry

    Full Text Available BACKGROUND: Species distribution models require selection of species, study extent and spatial unit, statistical methods, variables, and assessment metrics. If absence data are not available, another important consideration is pseudoabsence generation. Different strategies for pseudoabsence generation can produce varying spatial representation of species. METHODOLOGY: We considered model outcomes from four different strategies for generating pseudoabsences. We generating pseudoabsences randomly by 1 selection from the entire study extent, 2 a two-step process of selection first from the entire study extent, followed by selection for pseudoabsences from areas with predicted probability <25%, 3 selection from plots surveyed without detection of species presence, 4 a two-step process of selection first for pseudoabsences from plots surveyed without detection of species presence, followed by selection for pseudoabsences from the areas with predicted probability <25%. We used Random Forests as our statistical method and sixteen predictor variables to model tree species with at least 150 records from Forest Inventory and Analysis surveys in the Laurentian Mixed Forest province of Minnesota. CONCLUSIONS: Pseudoabsence generation strategy completely affected the area predicted as present for species distribution models and may be one of the most influential determinants of models. All the pseudoabsence strategies produced mean AUC values of at least 0.87. More importantly than accuracy metrics, the two-step strategies over-predicted species presence, due to too much environmental distance between the pseudoabsences and recorded presences, whereas models based on random pseudoabsences under-predicted species presence, due to too little environmental distance between the pseudoabsences and recorded presences. Models using pseudoabsences from surveyed plots produced a balance between areas with high and low predicted probabilities and the strongest

  9. Incorporating Context Dependency of Species Interactions in Species Distribution Models.

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    Lany, Nina K; Zarnetske, Phoebe L; Gouhier, Tarik C; Menge, Bruce A

    2017-07-01

    Species distribution models typically use correlative approaches that characterize the species-environment relationship using occurrence or abundance data for a single species. However, species distributions are determined by both abiotic conditions and biotic interactions with other species in the community. Therefore, climate change is expected to impact species through direct effects on their physiology and indirect effects propagated through their resources, predators, competitors, or mutualists. Furthermore, the sign and strength of species interactions can change according to abiotic conditions, resulting in context-dependent species interactions that may change across space or with climate change. Here, we incorporated the context dependency of species interactions into a dynamic species distribution model. We developed a multi-species model that uses a time-series of observational survey data to evaluate how abiotic conditions and species interactions affect the dynamics of three rocky intertidal species. The model further distinguishes between the direct effects of abiotic conditions on abundance and the indirect effects propagated through interactions with other species. We apply the model to keystone predation by the sea star Pisaster ochraceus on the mussel Mytilus californianus and the barnacle Balanus glandula in the rocky intertidal zone of the Pacific coast, USA. Our method indicated that biotic interactions between P. ochraceus and B. glandula affected B. glandula dynamics across >1000 km of coastline. Consistent with patterns from keystone predation, the growth rate of B. glandula varied according to the abundance of P. ochraceus in the previous year. The data and the model did not indicate that the strength of keystone predation by P. ochraceus varied with a mean annual upwelling index. Balanus glandula cover increased following years with high phytoplankton abundance measured as mean annual chlorophyll-a. M. californianus exhibited the same

  10. Improving species distribution models: the value of data on abundance

    National Research Council Canada - National Science Library

    Howard, Christine; Stephens, Philip A; Pearce‐Higgins, James W; Gregory, Richard D; Willis, Stephen G; McPherson, Jana

    2014-01-01

    Species distribution models (SDMs) are important tools for forecasting the potential impacts of future environmental changes but debate remains over the most robust modelling approaches for making projections...

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

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    Gritti, Emmanuel Stephan; Gaucherel, Cédric; Crespo-Perez, Maria-Veronica; Chuine, Isabelle

    2013-01-01

    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.

  12. Population distribution models: species distributions are better modeled using biologically relevant data partitions.

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    Gonzalez, Sergio C; Soto-Centeno, J Angel; Reed, David L

    2011-09-19

    Predicting the geographic distribution of widespread species through modeling is problematic for several reasons including high rates of omission errors. One potential source of error for modeling widespread species is that subspecies and/or races of species are frequently pooled for analyses, which may mask biologically relevant spatial variation within the distribution of a single widespread species. We contrast a presence-only maximum entropy model for the widely distributed oldfield mouse (Peromyscus polionotus) that includes all available presence locations for this species, with two composite maximum entropy models. The composite models either subdivided the total species distribution into four geographic quadrants or by fifteen subspecies to capture spatially relevant variation in P. polionotus distributions. Despite high Area Under the ROC Curve (AUC) values for all models, the composite species distribution model of P. polionotus generated from individual subspecies models represented the known distribution of the species much better than did the models produced by partitioning data into geographic quadrants or modeling the whole species as a single unit. Because the AUC values failed to describe the differences in the predictability of the three modeling strategies, we suggest using omission curves in addition to AUC values to assess model performance. Dividing the data of a widespread species into biologically relevant partitions greatly increased the performance of our distribution model; therefore, this approach may prove to be quite practical and informative for a wide range of modeling applications.

  13. Comparing the performance of species distribution models of

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    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;

  14. 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.

  15. Dynamic species distribution models from categorical survey data.

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    Mieszkowska, Nova; Milligan, Gregg; Burrows, Michael T; Freckleton, Rob; Spencer, Matthew

    2013-11-01

    1. Species distribution models are static models for the distribution of a species, based on Hutchinson's niche concept. They make probabilistic predictions about the distribution of a species, but do not have a temporal interpretation. In contrast, density-structured models based on categorical abundance data make it possible to incorporate population dynamics into species distribution modelling. 2. Using dynamic species distribution models, temporal aspects of a species' distribution can be investigated, including the predictability of future abundance categories and the expected persistence times of local populations, and how these may respond to environmental or anthropogenic drivers. 3. We built density-structured models for two intertidal marine invertebrates, the Lusitanian trochid gastropods Phorcus lineatus and Gibbula umbilicalis, based on 9 years of field data from around the United Kingdom. Abundances were recorded on a categorical scale, and stochastic models for year-to-year changes in abundance category were constructed with winter mean sea surface temperature (SST) and wave fetch (a measure of the exposure of a shore) as explanatory variables. 4. Both species were more likely to be present at sites with high SST, but differed in their responses to wave fetch. Phorcus lineatus had more predictable future abundance and longer expected persistence times than G. umbilicalis. This is consistent with the longer lifespan of P. lineatus. 5. Where data from multiple time points are available, dynamic species distribution models of the kind described here have many applications in population and conservation biology. These include allowing for changes over time when combining historical and contemporary data, and predicting how climate change might alter future abundance conditional on current distributions.

  16. Species distribution modelling in fisheries science

    OpenAIRE

    Paradinas, Iosu

    2017-01-01

    Latest fisheries directives propose adopting an ecosystem approach to manage fisheries \\citep{FAO-EAFM}. Such an approach aims to protect important ecosystems based on the principle that healthy ecosystems produce more and thus enhance sustainability. Unfortunately, quantifying the importance of an ecosystem is a difficult task to do due the immense number of interactions involved in marine systems. This PhD dissertation relies on the fact that good fisheries distribution maps could play ...

  17. 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 model results. We identify and discuss five areas of enquiry that are of high importance for species distribution modelling: (1) clarification of the niche concept; (2) improved designs for sampling data for building models; (3) improved parameterization; (4) improved model selection and predictor...

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

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    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.

  19. Predicting weed problems in maize cropping by species distribution modelling

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    Bürger, Jana

    2014-02-01

    Full Text Available Increasing maize cultivation and changed cropping practices promote the selection of typical maize weeds that may also profit strongly from climate change. Predicting potential weed problems is of high interest for plant production. Within the project KLIFF, experiments were combined with species distribution modelling for this task in the region of Lower Saxony, Germany. For our study, we modelled ecological and damage niches of nine weed species that are significant and wide spread in maize cropping in a number of European countries. Species distribution models describe the ecological niche of a species, these are the environmental conditions under which a species can maintain a vital population. It is also possible to estimate a damage niche, i.e. the conditions under which a species causes damage in agricultural crops. For this, we combined occurrence data of European national data bases with high resolution climate, soil and land use data. Models were also projected to simulated climate conditions for the time horizon 2070 - 2100 in order to estimate climate change effects. Modelling results indicate favourable conditions for typical maize weed occurrence virtually all over the study region, but only a few species are important in maize cropping. This is in good accordance with the findings of an earlier maize weed monitoring. Reaction to changing climate conditions is species-specific, for some species neutral (E. crus-galli, other species may gain (Polygonum persicaria or loose (Viola arvensis large areas of suitable habitats. All species with damage potential under present conditions will remain important in maize cropping, some more species will gain regional importance (Calystegia sepium, Setara viridis.

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

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    Céline Gomez

    Full Text Available Deep-sea fisheries provide an important source of protein to Pacific Island countries and territories that are highly dependent on fish for food security. However, spatial management of these deep-sea habitats is hindered by insufficient data. We developed species distribution models using spatially limited presence data for the main harvested species in the Western Central Pacific Ocean. We used bathymetric and water temperature data to develop presence-only species distribution models for the commercially exploited deep-sea snappers Etelis Cuvier 1828, Pristipomoides Valenciennes 1830, and Aphareus Cuvier 1830. We evaluated the performance of four different algorithms (CTA, GLM, MARS, and MAXENT within the BIOMOD framework to obtain an ensemble of predicted distributions. We projected these predictions across the Western Central Pacific Ocean to produce maps of potential deep-sea snapper distributions in 32 countries and territories. Depth was consistently the best predictor of presence for all species groups across all models. Bathymetric slope was consistently the poorest predictor. Temperature at depth was a good predictor of presence for GLM only. Model precision was highest for MAXENT and CTA. There were strong regional patterns in predicted distribution of suitable habitat, with the largest areas of suitable habitat (> 35% of the Exclusive Economic Zone predicted in seven South Pacific countries and territories (Fiji, Matthew & Hunter, Nauru, New Caledonia, Tonga, Vanuatu and Wallis & Futuna. Predicted habitat also varied among species, with the proportion of predicted habitat highest for Aphareus and lowest for Etelis. Despite data paucity, the relationship between deep-sea snapper presence and their environments was sufficiently strong to predict their distribution across a large area of the Pacific Ocean. Our results therefore provide a strong baseline for designing monitoring programs that balance resource exploitation and

  1. Using genetic data to improve species distribution models.

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    Bouyer, Jérémy; Lancelot, Renaud

    2017-03-23

    Tsetse flies (Diptera, Glossinidae) transmit human and animal trypanosomoses in Africa, respectively a neglected human disease (sleeping sickness) and the most important constraint to cattle production in infested countries (nagana). We recently developed a methodology to map landscape friction (i.e. resistance to movement) for tsetse in West Africa. The goal was to identify natural barriers to tsetse dispersal, and potentially isolated tsetse populations for targeting elimination programmes. Most species distribution models neglect landscape functional connectivity whereas environmental factors affecting suitability or abundance are not necessarily the same as those influencing gene flows. Geographic distributions of a given species can be seen as the intersection between biotic (B), abiotic (A) and movement (M) factors (BAM diagram). Here we show that the suitable habitat for Glossina palpalis gambiensis as modelled by Maxent can be corrected by landscape functional connectivity (M) extracted from our friction analysis. This procedure did not degrade the specificity of the distribution model (P=0.751) whereas the predicted distribution area was reduced. The added value of this approach is that it reveals unconnected habitat patches. The approach we developed on tsetse to inform landscape connectivity (M) is reproducible and does not rely on expert knowledge. It can be applied to any species: we call for a generalization of the use of M to improve distribution models. Copyright © 2017. Published by Elsevier B.V.

  2. Predicting fish species distribution in estuaries: Influence of species' ecology in model accuracy

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    França, Susana; Cabral, Henrique N.

    2016-10-01

    Current threats to biodiversity, combined with limited data availability, have made for species distribution models (SDMs) to be increasingly used due to their ability to predict species' potential distribution, by relating species occurrence with environmental estimates. Often used in ecology, conservation biology and environmental management, SDMs have been informing conservation strategies, and thus it is becoming crucial to understand how trustworthy their predictions are. Uncertainty in model predictions is expected, but knowing the origin of prediction errors may help reducing it. Indeed, uncertainty may be related not only with data quality and the modelling algorithm used, but also with species ecological characteristics. To investigate whether the performance of SDM's may vary with species' ecological characteristics, distribution models for 21 fish species occurring in estuaries from the Portuguese coast were examined. These models were built at two distinct spatial resolutions and seven environmental explanatory variables were used as predictors. SDMs' accuracy was assessed with the area under the curve (AUC) of receiver operating characteristics (ROC) plots, sensitivity and specificity. Relationships between each measure of accuracy and species ecological characteristics were then examined. SDMs of the fish species presented small differences between the considered scales, and predictors as latitude, temperature and salinity were often selected at both scales. Measures of model accuracy presented differences between species and scales, but generally higher accuracy was obtained at smaller spatial scales. Among the ecological traits tested, species feeding mode and estuarine use functional groups were the most influential on the performance of distribution models. Habitat tolerance (number of habitat types frequented), species abundance, body size and spawning period also showed some effect. This analyses will contribute to distinguish, based on species

  3. Historical Species Distribution Models Predict Species Limits in Western Plethodon Salamanders.

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    Pelletier, Tara A; Crisafulli, Charlie; Wagner, Steve; Zellmer, Amanda J; Carstens, Bryan C

    2015-11-01

    Allopatry is commonly used to predict boundaries in species delimitation investigations under the assumption that currently allopatric distributions are indicative of reproductive isolation; however, species ranges are known to change over time. Incorporating a temporal perspective of geographic distributions should improve species delimitation; to explore this, we investigate three species of western Plethodon salamanders that have shifted their ranges since the end of the Pleistocene. We generate species distribution models (SDM) of the current range, hindcast these models onto a climatic model 21 Ka, and use three molecular approaches to delimit species in an integrated fashion. In contrast to expectations based on the current distribution, we detect no independent lineages in species with allopatric and patchy distributions (Plethodon vandykei and Plethodon larselli). The SDMs indicate that probable habitat is more expansive than their current range, especially during the last glacial maximum (LGM) (21 Ka). However, with a contiguous distribution, two independent lineages were detected in Plethodon idahoensis, possibly due to isolation in multiple glacial refugia. Results indicate that historical SDMs are a better predictor of species boundaries than current distributions, and strongly imply that researchers should incorporate SDM and hindcasting into their investigations and the development of species hypotheses. © The Author(s) 2014. Published by Oxford University Press, on behalf of the Society of Systematic Biologists. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  4. Considerations for building climate-based species distribution models

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    Bucklin, David N.; Basille, Mathieu; Romanach, 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.

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

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    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.

  7. Mechanistic species distribution modeling reveals a niche shift during invasion.

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    Chapman, Daniel S; Scalone, Romain; Štefanić, Edita; Bullock, James M

    2017-06-01

    Niche shifts of nonnative plants can occur when they colonize novel climatic conditions. However, the mechanistic basis for niche shifts during invasion is poorly understood and has rarely been captured within species distribution models. We quantified the consequence of between-population variation in phenology for invasion of common ragweed (Ambrosia artemisiifolia L.) across Europe. Ragweed is of serious concern because of its harmful effects as a crop weed and because of its impact on public health as a major aeroallergen. We developed a forward mechanistic species distribution model based on responses of ragweed development rates to temperature and photoperiod. The model was parameterized and validated from the literature and by reanalyzing data from a reciprocal common garden experiment in which native and invasive populations were grown within and beyond the current invaded range. It could therefore accommodate between-population variation in the physiological requirements for flowering, and predict the potentially invaded ranges of individual populations. Northern-origin populations that were established outside the generally accepted climate envelope of the species had lower thermal requirements for bud development, suggesting local adaptation of phenology had occurred during the invasion. The model predicts that this will extend the potentially invaded range northward and increase the average suitability across Europe by 90% in the current climate and 20% in the future climate. Therefore, trait variation observed at the population scale can trigger a climatic niche shift at the biogeographic scale. For ragweed, earlier flowering phenology in established northern populations could allow the species to spread beyond its current invasive range, substantially increasing its risk to agriculture and public health. Mechanistic species distribution models offer the possibility to represent niche shifts by varying the traits and niche responses of individual

  8. Missing in action: Species competition is a neglected predictor variable in species distribution modelling.

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    Mpakairi, Kudzai Shaun; Ndaimani, Henry; Tagwireyi, Paradzayi; Gara, Tawanda Winmore; Zvidzai, Mark; Madhlamoto, Daphine

    2017-01-01

    The central role of species competition in shaping community structure in ecosystems is well appreciated amongst ecologists. However species competition is a consistently missing variable in Species Distribution Modelling (SDM). This study presents results of our attempt to incorporate species competition in SDMs. We used a suit of predictor variables including Soil Adjusted Vegetation Index (SAVI), as well as distance from roads, settlements and water, fire frequency and distance from the nearest herbivore sighting (of selected herbivores) to model individual habitat preferences of five grazer species (buffalo, warthog, waterbuck, wildebeest and zebra) with the Ensemble SDM algorithm for Gonarezhou National Park, Zimbabwe. Our results showed that distance from the nearest animal sighting (a proxy for competition among grazers) was the best predictor of the potential distribution of buffalo, wildebeest and zebra but the second best predictor for warthog and waterbuck. Our findings provide evidence to that competition is an important predictor of grazer species' potential distribution. These findings suggest that species distribution modelling that neglects species competition may be inadequate in explaining the potential distribution of species. Therefore our findings encourage the inclusion of competition in SDM as well as potentially igniting discussions that may lead to improving the predictive power of future SDM efforts.

  9. Species Distribution modeling as a tool to unravel determinants of palm distribution in Thailand

    DEFF Research Database (Denmark)

    Tovaranonte, Jantrararuk; Barfod, Anders S.; Balslev, Henrik

    2011-01-01

    As a consequence of the decimation of the forest cover in Thailand from 50% to ca. 20 % since the 1950ies, it is difficult to gain insight in the drivers behind past, present and future distribution ranges of plant species. Species distribution modeling allows visualization of potential species...... distribution under specific sets of assumptions. In this study we used maximum entropy to map potential distributions of 103 species of palms for which more than 5 herbarium records exist. Palms constitute key-stone plant group from both an ecological, economical and conservation perspective. The models were......) and the Area Under the Curve (AUC). All models performed well with AUC scores above 0.95. The predicted distribution ranges showed high suitability for palms in the southern region of Thailand. It also shows that spatial predictor variables are important in cases where historical processes may explain extant...

  10. 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 (pMAXENT, 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.

  11. 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.

  12. 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

  13. Projecting future expansion of invasive species: comparing and improving methodologies for species distribution modeling.

    Science.gov (United States)

    Mainali, Kumar P; Warren, Dan L; Dhileepan, Kunjithapatham; McConnachie, Andrew; Strathie, Lorraine; Hassan, Gul; Karki, Debendra; Shrestha, Bharat B; Parmesan, Camille

    2015-12-01

    Modeling the distributions of species, especially of invasive species in non-native ranges, involves multiple challenges. Here, we developed some novel approaches to species distribution modeling aimed at reducing the influences of such challenges and improving the realism of projections. We estimated species-environment relationships for Parthenium hysterophorus L. (Asteraceae) with four modeling methods run with multiple scenarios of (i) sources of occurrences and geographically isolated background ranges for absences, (ii) approaches to drawing background (absence) points, and (iii) alternate sets of predictor variables. We further tested various quantitative metrics of model evaluation against biological insight. Model projections were very sensitive to the choice of training dataset. Model accuracy was much improved using a global dataset for model training, rather than restricting data input to the species' native range. AUC score was a poor metric for model evaluation and, if used alone, was not a useful criterion for assessing model performance. Projections away from the sampled space (i.e., into areas of potential future invasion) were very different depending on the modeling methods used, raising questions about the reliability of ensemble projections. Generalized linear models gave very unrealistic projections far away from the training region. Models that efficiently fit the dominant pattern, but exclude highly local patterns in the dataset and capture interactions as they appear in data (e.g., boosted regression trees), improved generalization of the models. Biological knowledge of the species and its distribution was important in refining choices about the best set of projections. A post hoc test conducted on a new Parthenium dataset from Nepal validated excellent predictive performance of our 'best' model. We showed that vast stretches of currently uninvaded geographic areas on multiple continents harbor highly suitable habitats for parthenium

  14. 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

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

    Science.gov (United States)

    Rougier, Thibaud; Lassalle, Géraldine; Drouineau, Hilaire; Dumoulin, Nicolas; Faure, Thierry; Deffuant, Guillaume; Rochard, Eric; Lambert, Patrick

    2015-01-01

    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 adaptations to cold

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

    Science.gov (United States)

    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

  17. 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

  18. 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......) and the Area Under the Curve (AUC). All models performed well with AUC scores above 0.95. The predicted distribution ranges showed high suitability for palms in the southern region of Thailand. It also shows that spatial predictor variables are important in cases where historical processes may explain extant...

  19. 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

    study contradicts the widely held view that the complexity of species distributions models has significant effects in their predictive ability while findings support for previous observations that the properties of species distributions data and their relationship with the environment are strong...

  20. 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

  1. 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.

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

    Science.gov (United States)

    Rodríguez-Castañeda, Genoveva; Hof, Anouschka R; Jansson, Roland; Harding, Larisa E

    2012-01-01

    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.

  3. U.S. Geological Survey Gap Analysis Program Species Distribution Models

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — GAP distribution models represent the areas where species are predicted to occur based on habitat associations. GAP distribution models are the spatial arrangement...

  4. Modeling the Current and Future Distribution of Treeline Species in the Nepal Himalaya

    Science.gov (United States)

    Chhetri, P. K.; Cairns, D. M.

    2015-12-01

    Knowledge of the current distribution of treeline species is important for predicting their future distribution in the landscape. Many studies have indicated that treeline will advance with climate change. Treeline advance will result in a loss of alpine biodiversity because the advancing treeline will fragment alpine ecosystems. A species distribution modeling approach using predicted climate data can increase our understanding of how treeline species will expand their range in the future. We used the Maxent model to predict the current and future distributions of three dominant treeline species, Abies spectabilis, Betula utilis, and Pinus wallichiana, of the Nepal Himalaya. The Maxent model predicted that the distribution of treeline species will change significantly under future climate change scenarios. The range of these treeline species will expand northward or upslope in response to future climate change. The model also indicated that temperature-related climatic variables are the most important determinants of the distribution of treeline species.

  5. Squares of different sizes: effect of geographical projection on model parameter estimates in species distribution modeling.

    Science.gov (United States)

    Budic, Lara; Didenko, Gregor; Dormann, Carsten F

    2016-01-01

    In species distribution analyses, environmental predictors and distribution data for large spatial extents are often available in long-lat format, such as degree raster grids. Long-lat projections suffer from unequal cell sizes, as a degree of longitude decreases in length from approximately 110 km at the equator to 0 km at the poles. Here we investigate whether long-lat and equal-area projections yield similar model parameter estimates, or result in a consistent bias. We analyzed the environmental effects on the distribution of 12 ungulate species with a northern distribution, as models for these species should display the strongest effect of projectional distortion. Additionally we choose four species with entirely continental distributions to investigate the effect of incomplete cell coverage at the coast. We expected that including model weights proportional to the actual cell area should compensate for the observed bias in model coefficients, and similarly that using land coverage of a cell should decrease bias in species with coastal distribution. As anticipated, model coefficients were different between long-lat and equal-area projections. Having progressively smaller and a higher number of cells with increasing latitude influenced the importance of parameters in models, increased the sample size for the northernmost parts of species ranges, and reduced the subcell variability of those areas. However, this bias could be largely removed by weighting long-lat cells by the area they cover, and marginally by correcting for land coverage. Overall we found little effect of using long-lat rather than equal-area projections in our analysis. The fitted relationship between environmental parameters and occurrence probability differed only very little between the two projection types. We still recommend using equal-area projections to avoid possible bias. More importantly, our results suggest that the cell area and the proportion of a cell covered by land should be

  6. 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

    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...... limits corresponding to the limits of temperate or boreal forest or arctic tundra were used in the analysis. We developed predictive distribution models based on the species present-day European distributions and validated these against their present-day Siberian ranges. The models with the best...... 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...

  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. 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)...

  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 t

  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. 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

  12. Equivalence of MAXENT and Poisson point process models for species distribution modeling in ecology.

    Science.gov (United States)

    Renner, Ian W; Warton, David I

    2013-03-01

    Modeling the spatial distribution of a species is a fundamental problem in ecology. A number of modeling methods have been developed, an extremely popular one being MAXENT, a maximum entropy modeling approach. In this article, we show that MAXENT is equivalent to a Poisson regression model and hence is related to a Poisson point process model, differing only in the intercept term, which is scale-dependent in MAXENT. We illustrate a number of improvements to MAXENT that follow from these relations. In particular, a point process model approach facilitates methods for choosing the appropriate spatial resolution, assessing model adequacy, and choosing the LASSO penalty parameter, all currently unavailable to MAXENT. The equivalence result represents a significant step in the unification of the species distribution modeling literature. Copyright © 2013, The International Biometric Society.

  13. Numerical modeling of temperature and species distributions in hydrocarbon reservoirs

    Science.gov (United States)

    Bolton, Edward W.; Firoozabadi, Abbas

    2014-01-01

    We examine bulk fluid motion and diffusion of multicomponent hydrocarbon species in porous media in the context of nonequilibrium thermodynamics, with particular focus on the phenomenology induced by horizontal thermal gradients at the upper and lower horizontal boundaries. The problem is formulated with respect to the barycentric (mass-averaged) frame of reference. Thermally induced convection, with fully time-dependent temperature distributions, can lead to nearly constant hydrocarbon composition, with minor unmixing due to thermal gradients near the horizontal boundaries. Alternately, the composition can be vertically segregated due to gravitational effects. Independent and essentially steady solutions have been found to depend on how the compositions are initialized in space and may have implications for reservoir history. We also examine injection (to represent filling) and extraction (to represent leakage) of hydrocarbons at independent points and find a large distortion of the gas-oil contact for low permeability.

  14. Predicting species distributions from checklist data using site-occupancy models

    Science.gov (United States)

    Kery, M.; Gardner, B.; Monnerat, C.

    2010-01-01

    Aim: (1) To increase awareness of the challenges induced by imperfect detection, which is a fundamental issue in species distribution modelling; (2) to emphasize the value of replicate observations for species distribution modelling; and (3) to show how 'cheap' checklist data in faunal/floral databases may be used for the rigorous modelling of distributions by site-occupancy models. Location: Switzerland. Methods: We used checklist data collected by volunteers during 1999 and 2000 to analyse the distribution of the blue hawker, Aeshna cyanea (Odonata, Aeshnidae), a common dragonfly in Switzerland. We used data from repeated visits to 1-ha pixels to derive 'detection histories' and apply site-occupancy models to estimate the 'true' species distribution, i.e. corrected for imperfect detection. We modelled blue hawker distribution as a function of elevation and year and its detection probability of elevation, year and season. Results: The best model contained cubic polynomial elevation effects for distribution and quadratic effects of elevation and season for detectability. We compared the site-occupancy model with a conventional distribution model based on a generalized linear model, which assumes perfect detectability (p = 1). The conventional distribution map looked very different from the distribution map obtained using site-occupancy models that accounted for the imperfect detection. The conventional model underestimated the species distribution by 60%, and the slope parameters of the occurrence-elevation relationship were also underestimated when assuming p = 1. Elevation was not only an important predictor of blue hawker occurrence, but also of the detection probability, with a bell-shaped relationship. Furthermore, detectability increased over the season. The average detection probability was estimated at only 0.19 per survey. Main conclusions: Conventional species distribution models do not model species distributions per se but rather the apparent

  15. 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...

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

    NARCIS (Netherlands)

    Cobben, M.M.P.; Treuren, van R.; Castaneda-Alvarez, N.P.; Khoury, C.K.; Kik, C.; Hintum, van 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 collec

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

    NARCIS (Netherlands)

    Cobben, M.M.P.; Treuren, van R.; Castaneda-Alvarez, N.P.; Khoury, C.K.; Kik, C.; Hintum, van 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

  18. Thematic and spatial resolutions affect model-based predictions of tree species distribution.

    Directory of Open Access Journals (Sweden)

    Yu Liang

    Full Text Available Subjective decisions of thematic and spatial resolutions in characterizing environmental heterogeneity may affect the characterizations of spatial pattern and the simulation of occurrence and rate of ecological processes, and in turn, model-based tree species distribution. Thus, this study quantified the importance of thematic and spatial resolutions, and their interaction in predictions of tree species distribution (quantified by species abundance. We investigated how model-predicted species abundances changed and whether tree species with different ecological traits (e.g., seed dispersal distance, competitive capacity had different responses to varying thematic and spatial resolutions. We used the LANDIS forest landscape model to predict tree species distribution at the landscape scale and designed a series of scenarios with different thematic (different numbers of land types and spatial resolutions combinations, and then statistically examined the differences of species abundance among these scenarios. Results showed that both thematic and spatial resolutions affected model-based predictions of species distribution, but thematic resolution had a greater effect. Species ecological traits affected the predictions. For species with moderate dispersal distance and relatively abundant seed sources, predicted abundance increased as thematic resolution increased. However, for species with long seeding distance or high shade tolerance, thematic resolution had an inverse effect on predicted abundance. When seed sources and dispersal distance were not limiting, the predicted species abundance increased with spatial resolution and vice versa. Results from this study may provide insights into the choice of thematic and spatial resolutions for model-based predictions of tree species distribution.

  19. Thematic and spatial resolutions affect model-based predictions of tree species distribution.

    Science.gov (United States)

    Liang, Yu; He, Hong S; Fraser, Jacob S; Wu, ZhiWei

    2013-01-01

    Subjective decisions of thematic and spatial resolutions in characterizing environmental heterogeneity may affect the characterizations of spatial pattern and the simulation of occurrence and rate of ecological processes, and in turn, model-based tree species distribution. Thus, this study quantified the importance of thematic and spatial resolutions, and their interaction in predictions of tree species distribution (quantified by species abundance). We investigated how model-predicted species abundances changed and whether tree species with different ecological traits (e.g., seed dispersal distance, competitive capacity) had different responses to varying thematic and spatial resolutions. We used the LANDIS forest landscape model to predict tree species distribution at the landscape scale and designed a series of scenarios with different thematic (different numbers of land types) and spatial resolutions combinations, and then statistically examined the differences of species abundance among these scenarios. Results showed that both thematic and spatial resolutions affected model-based predictions of species distribution, but thematic resolution had a greater effect. Species ecological traits affected the predictions. For species with moderate dispersal distance and relatively abundant seed sources, predicted abundance increased as thematic resolution increased. However, for species with long seeding distance or high shade tolerance, thematic resolution had an inverse effect on predicted abundance. When seed sources and dispersal distance were not limiting, the predicted species abundance increased with spatial resolution and vice versa. Results from this study may provide insights into the choice of thematic and spatial resolutions for model-based predictions of tree species distribution.

  20. 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

  1. 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 ...

  2. 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 ...

  3. Mapping National Plant Biodiversity Patterns in South Korea with the MARS Species Distribution Model.

    Directory of Open Access Journals (Sweden)

    Hyeyeong Choe

    Full Text Available Accurate information on the distribution of existing species is crucial to assess regional biodiversity. However, data inventories are insufficient in many areas. We examine the ability of Multivariate Adaptive Regression Splines (MARS multi-response species distribution model to overcome species' data limitations and portray plant species distribution patterns for 199 South Korean plant species. The study models species with two or more observations, examines their contribution to national patterns of species richness, provides a sensitivity analysis of different range threshold cutoff approaches for modeling species' ranges, and presents considerations for species modeling at fine spatial resolution. We ran MARS models for each species and tested four threshold methods to transform occurrence probabilities into presence or absence range maps. Modeled occurrence probabilities were extracted at each species' presence points, and the mean, median, and one standard deviation (SD calculated to define data-driven thresholds. A maximum sum of sensitivity and specificity threshold was also calculated, and the range maps from the four cutoffs were tested using independent plant survey data. The single SD values were the best threshold tested for minimizing omission errors and limiting species ranges to areas where the associated occurrence data were correctly classed. Eight individual species range maps for rare plant species were identified that are potentially affected by resampling predictor variables to fine spatial scales. We portray spatial patterns of high species richness by assessing the combined range maps from three classes of species: all species, endangered and endemic species, and range-size rarity of all species, which could be used in conservation planning for South Korea. The MARS model is promising for addressing the common problem of few species occurrence records. However, projected species ranges are highly dependent on the

  4. Mapping National Plant Biodiversity Patterns in South Korea with the MARS Species Distribution Model.

    Science.gov (United States)

    Choe, Hyeyeong; Thorne, James H; Seo, Changwan

    2016-01-01

    Accurate information on the distribution of existing species is crucial to assess regional biodiversity. However, data inventories are insufficient in many areas. We examine the ability of Multivariate Adaptive Regression Splines (MARS) multi-response species distribution model to overcome species' data limitations and portray plant species distribution patterns for 199 South Korean plant species. The study models species with two or more observations, examines their contribution to national patterns of species richness, provides a sensitivity analysis of different range threshold cutoff approaches for modeling species' ranges, and presents considerations for species modeling at fine spatial resolution. We ran MARS models for each species and tested four threshold methods to transform occurrence probabilities into presence or absence range maps. Modeled occurrence probabilities were extracted at each species' presence points, and the mean, median, and one standard deviation (SD) calculated to define data-driven thresholds. A maximum sum of sensitivity and specificity threshold was also calculated, and the range maps from the four cutoffs were tested using independent plant survey data. The single SD values were the best threshold tested for minimizing omission errors and limiting species ranges to areas where the associated occurrence data were correctly classed. Eight individual species range maps for rare plant species were identified that are potentially affected by resampling predictor variables to fine spatial scales. We portray spatial patterns of high species richness by assessing the combined range maps from three classes of species: all species, endangered and endemic species, and range-size rarity of all species, which could be used in conservation planning for South Korea. The MARS model is promising for addressing the common problem of few species occurrence records. However, projected species ranges are highly dependent on the threshold and scale

  5. 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. PMID:23840330

  6. 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.

  7. On a link between a species survival time in an evolution model and the Bessel distributions

    CERN Document Server

    Guiol, Herve; Schinazi, Rinaldo B

    2011-01-01

    We consider a stochastic model for species evolution. A new species is born at rate lambda and a species dies at rate mu. A random number, sampled from a given distribution F, is associated with each new species at the time of birth. Every time there is a death event, the species that is killed is the one with the smallest fitness. We consider the (random) survival time of a species with a given fitness f. We show that the survival time distribution depends crucially on whether ff_c where f_c is a critical fitness that is computed explicitly.

  8. Effects of biotic interactions on modeled species' distribution can be masked by environmental gradients.

    Science.gov (United States)

    Godsoe, William; Franklin, Janet; Blanchet, F Guillaume

    2017-01-01

    A fundamental goal of ecology is to understand the determinants of species' distributions (i.e., the set of locations where a species is present). Competition among species (i.e., interactions among species that harms each of the species involved) is common in nature and it would be tremendously useful to quantify its effects on species' distributions. An approach to studying the large-scale effects of competition or other biotic interactions is to fit species' distributions models (SDMs) and assess the effect of competitors on the distribution and abundance of the species of interest. It is often difficult to validate the accuracy of this approach with available data. Here, we simulate virtual species that experience competition. In these simulated datasets, we can unambiguously identify the effects that competition has on a species' distribution. We then fit SDMs to the simulated datasets and test whether we can use the outputs of the SDMs to infer the true effect of competition in each simulated dataset. In our simulations, the abiotic environment influenced the effects of competition. Thus, our SDMs often inferred that the abiotic environment was a strong predictor of species abundance, even when the species' distribution was strongly affected by competition. The severity of this problem depended on whether the competitor excluded the focal species from highly suitable sites or marginally suitable sites. Our results highlight how correlations between biotic interactions and the abiotic environment make it difficult to infer the effects of competition using SDMs.

  9. 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.

  10. 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

  11. 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

  12. Modelling the potential spatial distribution of mosquito species using three different techniques

    NARCIS (Netherlands)

    Cianci, D.; Hartemink, N.; Ibáñez-Justicia, A.

    2015-01-01

    Background: Models for the spatial distribution of vector species are important tools in the assessment of the risk of establishment and subsequent spread of vector-borne diseases. The aims of this study are to define the environmental conditions suitable for several mosquito species through species

  13. Modelling the potential spatial distribution of mosquito species using three different techniques

    NARCIS (Netherlands)

    Cianci, Daniela; Hartemink, Nienke; Ibáñez-Justicia, Adolfo

    2015-01-01

    BACKGROUND: Models for the spatial distribution of vector species are important tools in the assessment of the risk of establishment and subsequent spread of vector-borne diseases. The aims of this study are to define the environmental conditions suitable for several mosquito species through species

  14. 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

  15. Determining the factors affecting the distribution of Muscari 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.

  16. Using the Maxent program for species distribution modelling to assess invasion risk

    Science.gov (United States)

    Jarnevich, Catherine S.; Young, Nicholas E.; Venette, R.C

    2015-01-01

    MAXENT is a software package used to relate known species occurrences to information describing the environment, such as climate, topography, anthropogenic features or soil data, and forecast the presence or absence of a species at unsampled locations. This particular method is one of the most popular species distribution modelling techniques because of its consistent strong predictive performance and its ease to implement. This chapter discusses the decisions and techniques needed to prepare a correlative climate matching model for the native range of an invasive alien species and use this model to predict the potential distribution of this species in a potentially invaded range (i.e. a novel environment) by using MAXENT for the Burmese python (Python molurus bivittatus) as a case study. The chapter discusses and demonstrates the challenges that are associated with this approach and examines the inherent limitations that come with using MAXENT to forecast distributions of invasive alien species.

  17. 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

    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 spe...

  18. Does including physiology improve species distribution model predictions of responses to recent climate change?

    Science.gov (United States)

    Buckley, Lauren B; Waaser, Stephanie A; MacLean, Heidi J; Fox, Richard

    2011-12-01

    Thermal constraints on development are often invoked to predict insect distributions. These constraints tend to be characterized in species distribution models (SDMs) by calculating development time based on a constant lower development temperature (LDT). Here, we assessed whether species-specific estimates of LDT based on laboratory experiments can improve the ability of SDMs to predict the distribution shifts of six U.K. butterflies in response to recent climate warming. We find that species-specific and constant (5 degrees C) LDT degree-day models perform similarly at predicting distributions during the period of 1970-1982. However, when the models for the 1970-1982 period are projected to predict distributions in 1995-1999 and 2000-2004, species-specific LDT degree-day models modestly outperform constant LDT degree-day models. Our results suggest that, while including species-specific physiology in correlative models may enhance predictions of species' distribution responses to climate change, more detailed models may be needed to adequately account for interspecific physiological differences.

  19. A mechanistic niche model for measuring species' distributional responses to seasonal temperature gradients.

    Directory of Open Access Journals (Sweden)

    William B Monahan

    Full Text Available Niche theory is central to understanding how species respond geographically to climate change. It defines a species' realized niche in a biological community, its fundamental niche as determined by physiology, and its potential niche--the fundamental niche in a given environment or geographic space. However, most predictions of the effects of climate change on species' distributions are limited to correlative models of the realized niche, which assume that species are in distributional equilibrium with respect to the variables or gradients included in the model. Here, I present a mechanistic niche model that measures species' responses to major seasonal temperature gradients that interact with the physiology of the organism. I then use lethal physiological temperatures to parameterize the model for bird species in North and South America and show that most focal bird species are not in direct physiological equilibrium with the gradients. Results also show that most focal bird species possess broad thermal tolerances encompassing novel climates that could become available with climate change. I conclude with discussion of how mechanistic niche models may be used to (i gain insights into the processes that cause species to respond to climate change and (ii build more accurate correlative distribution models in birds and other species.

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

    Science.gov (United States)

    2016-09-14

    suitability of occupied sites is spatially and temporally dynamic. Additional information about Bog Spicebush habitat requirements and potential distribution...A language and environment for statistical computing. R Foundation for Statistical Computing. Vienna, Austria: The R foundation, http://www.R...varying disturbance dependence, suggesting the habitat suitability of occupied sites is spatially and temporally dynamic. Additional information

  1. Combining niche and dispersal in a simple model (NDM) of species distribution.

    Science.gov (United States)

    Génard, Michel; Lescourret, Françoise

    2013-01-01

    Predicting the distribution of species has become a crucial issue in biodiversity research. Two kinds of model address this question: niche models, which are usually based on static approaches linking species distribution to habitat characteristics, and dispersal models, which are usually dynamic and process-based. We propose a model (NDM: niche and dispersal model) that considers the local presence of a species to result from a dynamic balance between extinction (based on the niche concept) and immigration (based on the dispersal concept), at a given moment in time, in a spatially explicit context. We show that NDM correctly predicts observed bird species and community distributions at different scales. NDM helps to reconcile the contrasting paradigms of metacommunity theory. It shows that sorting and mass effects are the factors determining bird species distribution. One of the most interesting features of NDM is its ability to predict well known properties of communities, such as decreasing species richness with decreasing patch size and increasing distance to the mainland, and the mid-domain effect at the regional scale, contrasting with predictions of much smaller effects at the local scale. NDM shows that habitat destruction in the matrix around patches of forest can affect the forest bird community, principally by decreasing the occurrence of typical matrix birds within the forest. This model could be used as the starting point for applied ecological studies on the management of species and community distributions.

  2. Incorporating evolutionary adaptation in species distribution modelling reduces projected vulnerability to climate change.

    Science.gov (United States)

    Bush, Alex; Mokany, Karel; Catullo, Renee; Hoffmann, Ary; Kellermann, Vanessa; Sgrò, Carla; McEvey, Shane; Ferrier, Simon

    2016-12-01

    Based on the sensitivity of species to ongoing climate change, and numerous challenges they face tracking suitable conditions, there is growing interest in species' capacity to adapt to climatic stress. Here, we develop and apply a new generic modelling approach (AdaptR) that incorporates adaptive capacity through physiological limits, phenotypic plasticity, evolutionary adaptation and dispersal into a species distribution modelling framework. Using AdaptR to predict change in the distribution of 17 species of Australian fruit flies (Drosophilidae), we show that accounting for adaptive capacity reduces projected range losses by up to 33% by 2105. We identify where local adaptation is likely to occur and apply sensitivity analyses to identify the critical factors of interest when parameters are uncertain. Our study suggests some species could be less vulnerable than previously thought, and indicates that spatiotemporal adaptive models could help improve management interventions that support increased species' resilience to climate change. © 2016 John Wiley & Sons Ltd/CNRS.

  3. 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.

  4. 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

    distributions with boosted regression trees (BRTs) and generalized additive models (GAMs). We evaluated model performance by using the split-sample approach with data from t1 ("non-independent validation"), and then compared model projections based on data from t1 with species’ observed distributions in t2...... ("independent validation"). We compared climate-only SDMs to SDMs including land cover, soil type, or both. Finally, we related model performance to species traits and compared observed and predicted distributional shifts at northern range margins. Results. SDMs showed fair to good model fits when modelling...

  5. Road Resources Distribution and Evolution Analysis Using a Species Competition Model for Improving Road Equity

    Institute of Scientific and Technical Information of China (English)

    YING Xiwen; SHI Jing

    2008-01-01

    The paper analyzes the equity of road resources distribution in urban areas by modeling the competitive relationship among different road users.A logistic model is used to describe the development of different traffic modes in the transportation network.The system is similar to the species competition model,so a two-species model is used to analyze the relationship between users based on the stability of the equilibrium points.The Lotka-Volterra model is then used to describe the multi-species cases with numerical examples,showing that this model can describe the effects of the road space distribution on the competitive user relationships.Policy makers must ensure the equity of road resources distribution so that each urban transportation mode is properly developed for sustainable social development.

  6. Modelling plant species distribution in alpine grasslands using airborne imaging spectroscopy.

    Science.gov (United States)

    Pottier, Julien; Malenovský, Zbyněk; Psomas, Achilleas; Homolová, Lucie; Schaepman, Michael E; Choler, Philippe; Thuiller, Wilfried; Guisan, Antoine; Zimmermann, Niklaus E

    2014-07-01

    Remote sensing using airborne imaging spectroscopy (AIS) is known to retrieve fundamental optical properties of ecosystems. However, the value of these properties for predicting plant species distribution remains unclear. Here, we assess whether such data can add value to topographic variables for predicting plant distributions in French and Swiss alpine grasslands. We fitted statistical models with high spectral and spatial resolution reflectance data and tested four optical indices sensitive to leaf chlorophyll content, leaf water content and leaf area index. We found moderate added-value of AIS data for predicting alpine plant species distribution. Contrary to expectations, differences between species distribution models (SDMs) were not linked to their local abundance or phylogenetic/functional similarity. Moreover, spectral signatures of species were found to be partly site-specific. We discuss current limits of AIS-based SDMs, highlighting issues of scale and informational content of AIS data. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

  7. 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.

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

    Directory of Open Access Journals (Sweden)

    Chiara Polce

    Full Text Available 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.

  9. The Distribution and Abundance of Bird Species: Towards a Satellite, Data Driven Avian Energetics and Species Richness Model

    Science.gov (United States)

    Smith, James A.

    2003-01-01

    This paper addresses the fundamental question of why birds occur where and when they do, i.e., what are the causative factors that determine the spatio-temporal distributions, abundance, or richness of bird species? In this paper we outline the first steps toward building a satellite, data-driven model of avian energetics and species richness based on individual bird physiology, morphology, and interaction with the spatio-temporal habitat. To evaluate our model, we will use the North American Breeding Bird Survey and Christmas Bird Count data for species richness, wintering and breeding range. Long term and current satellite data series include AVHRR, Landsat, and MODIS.

  10. Predicting plant invasions under climate change: are species distribution models validated by field trials?

    Science.gov (United States)

    Sheppard, Christine S; Burns, Bruce R; Stanley, Margaret C

    2014-09-01

    Climate change may facilitate alien species invasion into new areas, particularly for species from warm native ranges introduced into areas currently marginal for temperature. Although conclusions from modelling approaches and experimental studies are generally similar, combining the two approaches has rarely occurred. The aim of this study was to validate species distribution models by conducting field trials in sites of differing suitability as predicted by the models, thus increasing confidence in their ability to assess invasion risk. Three recently naturalized alien plants in New Zealand were used as study species (Archontophoenix cunninghamiana, Psidium guajava and Schefflera actinophylla): they originate from warm native ranges, are woody bird-dispersed species and of concern as potential weeds. Seedlings were grown in six sites across the country, differing both in climate and suitability (as predicted by the species distribution models). Seedling growth and survival were recorded over two summers and one or two winter seasons, and temperature and precipitation were monitored hourly at each site. Additionally, alien seedling performances were compared to those of closely related native species (Rhopalostylis sapida, Lophomyrtus bullata and Schefflera digitata). Furthermore, half of the seedlings were sprayed with pesticide, to investigate whether enemy release may influence performance. The results showed large differences in growth and survival of the alien species among the six sites. In the more suitable sites, performance was frequently higher compared to the native species. Leaf damage from invertebrate herbivory was low for both alien and native seedlings, with little evidence that the alien species should have an advantage over the native species because of enemy release. Correlations between performance in the field and predicted suitability of species distribution models were generally high. The projected increase in minimum temperature and reduced

  11. Incorporating spatial autocorrelation into species distribution models alters forecasts of climate-mediated range shifts.

    Science.gov (United States)

    Crase, Beth; Liedloff, Adam; Vesk, Peter A; Fukuda, Yusuke; Wintle, Brendan A

    2014-08-01

    Species distribution models (SDMs) are widely used to forecast changes in the spatial distributions of species and communities in response to climate change. However, spatial autocorrelation (SA) is rarely accounted for in these models, despite its ubiquity in broad-scale ecological data. While spatial autocorrelation in model residuals is known to result in biased parameter estimates and the inflation of type I errors, the influence of unmodeled SA on species' range forecasts is poorly understood. Here we quantify how accounting for SA in SDMs influences the magnitude of range shift forecasts produced by SDMs for multiple climate change scenarios. SDMs were fitted to simulated data with a known autocorrelation structure, and to field observations of three mangrove communities from northern Australia displaying strong spatial autocorrelation. Three modeling approaches were implemented: environment-only models (most frequently applied in species' range forecasts), and two approaches that incorporate SA; autologistic models and residuals autocovariate (RAC) models. Differences in forecasts among modeling approaches and climate scenarios were quantified. While all model predictions at the current time closely matched that of the actual current distribution of the mangrove communities, under the climate change scenarios environment-only models forecast substantially greater range shifts than models incorporating SA. Furthermore, the magnitude of these differences intensified with increasing increments of climate change across the scenarios. When models do not account for SA, forecasts of species' range shifts indicate more extreme impacts of climate change, compared to models that explicitly account for SA. Therefore, where biological or population processes induce substantial autocorrelation in the distribution of organisms, and this is not modeled, model predictions will be inaccurate. These results have global importance for conservation efforts as inaccurate

  12. Characterizing species abundance distributions across taxa and ecosystems using a simple maximum entropy model.

    Science.gov (United States)

    White, Ethan P; Thibault, Katherine M; Xiao, Xiao

    2012-08-01

    The species abundance distribution (SAD) is one of themost studied patterns in ecology due to its potential insights into commonness and rarity, community assembly, and patterns of biodiversity. It is well established that communities are composed of a few common and many rare species, and numerous theoretical models have been proposed to explain this pattern. However, no attempt has been made to determine how well these theoretical characterizations capture observed taxonomic and global-scale spatial variation in the general form of the distribution. Here, using data of a scope unprecedented in community ecology, we show that a simple maximum entropy model produces a truncated log-series distribution that can predict between 83% and 93% of the observed variation in the rank abundance of species across 15 848 globally distributed communities including birds, mammals, plants, and butterflies. This model requires knowledge of only the species richness and total abundance of the community to predict the full abundance distribution, which suggests that these factors are sufficient to understand the distribution for most purposes. Since geographic patterns in richness and abundance can often be successfully modeled, this approach should allow the distribution of commonness and rarity to be characterized, even in locations where empirical data are unavailable.

  13. The influence of life history characteristics on flea (Siphonaptera) species distribution models.

    Science.gov (United States)

    van der Mescht, Luther; le Roux, Peter C; Matthee, Conrad A; Raath, Morgan J; Matthee, Sonja

    2016-03-29

    Ectoparasites exhibit pronounced variation in life history characteristics such as time spent on the host and host range. Since contemporary species distribution (SD) modelling does not account for differences in life history, the accuracy of predictions of current and future species' ranges could differ significantly between life history groups. SD model performance was compared between 21 flea species that differ in microhabitat preferences and level of host specificity. Distribution models generally performed well, with no significant differences in model performance based on either microhabitat preferences or host specificity. However, the relative importance of predictor variables was significantly related to host specificity, with the distribution of host-opportunistic fleas strongly limited by thermal conditions and host-specific fleas more associated with conditions that restrict their hosts' distribution. The importance of temperature was even more pronounced when considering microhabitat preference, with the distribution of fur fleas being strongly limited by thermal conditions and nest fleas more associated with variables that affect microclimatic conditions in the host nest. Contemporary SD modelling, that includes climate and landscape variables, is a valuable tool to study the biogeography and future distributions of fleas and other parasites taxa. However, consideration of life history characteristics is cautioned as species may be differentially sensitive to environmental conditions.

  14. Effects of Dispersal-Related Factors on Species Distribution Model Accuracy for Boreal Lake Ecosystems

    Directory of Open Access Journals (Sweden)

    Simon Hallstan

    2013-05-01

    Full Text Available Species distribution modeling is used in applied ecology; for example in predicting the consequences of global change. However, questions still remain about the robustness of model predictions. Here we estimate effects of landscape spatial configuration and organism flight ability—factors related to dispersal—on the accuracy of species distribution models. Distribution models were developed for 129 phytoplankton taxa, 164 littoral invertebrate taxa and 44 profundal invertebrate taxa sampled in 105 Swedish lakes, using six different modeling techniques (generalized linear models (GLM, multivariate adaptive regression splines (MARS, classification tree analysis (CTA, mixture discriminant analysis (MDA, generalized boosting models (GBM and random forests (RF. Model accuracy was not affected by dispersal ability (i.e., invertebrate flight ability, but the accuracy of phytoplankton assemblage predictions and, to a lesser extent, littoral invertebrate assemblages were related to ecosystem size and connectivity. Although no general pattern across species or spatial configuration was evident from our study, we recommend that dispersal and spatial configuration of ecosystems should be considered when developing species distribution models.

  15. Addressing potential local adaptation in species distribution models: implications for conservation under climate change

    Science.gov (United States)

    Hällfors, Maria Helena; Liao, Jishan; Dzurisin, Jason D. K.; Grundel, Ralph; Hyvärinen, Marko; Towle, Kevin; Wu, Grace C.; Hellmann, Jessica J.

    2016-01-01

    Species distribution models (SDMs) have been criticized for involving assumptions that ignore or categorize many ecologically relevant factors such as dispersal ability and biotic interactions. Another potential source of model error is the assumption that species are ecologically uniform in their climatic tolerances across their range. Typically, SDMs to treat a species as a single entity, although populations of many species differ due to local adaptation or other genetic differentiation. Not taking local adaptation into account, may lead to incorrect range prediction and therefore misplaced conservation efforts. A constraint is that we often do not know the degree to which populations are locally adapted, however. Lacking experimental evidence, we still can evaluate niche differentiation within a species' range to promote better conservation decisions. We explore possible conservation implications of making type I or type II errors in this context. For each of two species, we construct three separate MaxEnt models, one considering the species as a single population and two of disjunct populations. PCA analyses and response curves indicate different climate characteristics in the current environments of the populations. Model projections into future climates indicate minimal overlap between areas predicted to be climatically suitable by the whole species versus population-based models. We present a workflow for addressing uncertainty surrounding local adaptation in SDM application and illustrate the value of conducting population-based models to compare with whole-species models. These comparisons might result in more cautious management actions when alternative range outcomes are considered.

  16. Addressing potential local adaptation in species distribution models: implications for conservation under climate change.

    Science.gov (United States)

    Hällfors, Maria Helena; Liao, Jishan; Dzurisin, Jason; Grundel, Ralph; Hyvärinen, Marko; Towle, Kevin; Wu, Grace C; Hellmann, Jessica J

    2016-06-01

    Species distribution models (SDMs) have been criticized for involving assumptions that ignore or categorize many ecologically relevant factors such as dispersal ability and biotic interactions. Another potential source of model error is the assumption that species are ecologically uniform in their climatic tolerances across their range. Typically, SDMs treat a species as a single entity, although populations of many species differ due to local adaptation or other genetic differentiation. Not taking local adaptation into account may lead to incorrect range prediction and therefore misplaced conservation efforts. A constraint is that we often do not know the degree to which populations are locally adapted. Lacking experimental evidence, we still can evaluate niche differentiation within a species' range to promote better conservation decisions. We explore possible conservation implications of making type I or type II errors in this context. For each of two species, we construct three separate Max-Ent models, one considering the species as a single population and two of disjunct populations. Principal component analyses and response curves indicate different climate characteristics in the current environments of the populations. Model projections into future climates indicate minimal overlap between areas predicted to be climatically suitable by the whole species vs. population-based models. We present a workflow for addressing uncertainty surrounding local adaptation in SDM application and illustrate the value of conducting population-based models to compare with whole-species models. These comparisons might result in more cautious management actions when alternative range outcomes are considered.

  17. 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.

  18. 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

  19. 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

  20. 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.

  1. Species sensitivity distribution for chlorpyrifos to aquatic organisms: Model choice and sample size.

    Science.gov (United States)

    Zhao, Jinsong; Chen, Boyu

    2016-03-01

    Species sensitivity distribution (SSD) is a widely used model that extrapolates the ecological risk to ecosystem levels from the ecotoxicity of a chemical to individual organisms. However, model choice and sample size significantly affect the development of the SSD model and the estimation of hazardous concentrations at the 5th centile (HC5). To interpret their effects, the SSD model for chlorpyrifos, a widely used organophosphate pesticide, to aquatic organisms is presented with emphases on model choice and sample size. Three subsets of median effective concentration (EC50) with different sample sizes were obtained from ECOTOX and used to build SSD models based on parametric distribution (normal, logistic, and triangle distribution) and nonparametric bootstrap. The SSD models based on the triangle distribution are superior to the normal and logistic distributions according to several goodness-of-fit techniques. Among all parametric SSD models, the one with the largest sample size based on the triangle distribution gives the most strict HC5 with 0.141μmolL(-1). The HC5 derived from the nonparametric bootstrap is 0.159μmol L(-1). The minimum sample size required to build a stable SSD model is 11 based on parametric distribution and 23 based on nonparametric bootstrap. The study suggests that model choice and sample size are important sources of uncertainty for application of the SSD model. Copyright © 2015 Elsevier Inc. All rights reserved.

  2. Modelling the potential spatial distribution of mosquito species using three different techniques.

    Science.gov (United States)

    Cianci, Daniela; Hartemink, Nienke; Ibáñez-Justicia, Adolfo

    2015-02-27

    Models for the spatial distribution of vector species are important tools in the assessment of the risk of establishment and subsequent spread of vector-borne diseases. The aims of this study are to define the environmental conditions suitable for several mosquito species through species distribution modelling techniques, and to compare the results produced with the different techniques. Three different modelling techniques, i.e., non-linear discriminant analysis, random forest and generalised linear model, were used to investigate the environmental suitability in the Netherlands for three indigenous mosquito species (Culiseta annulata, Anopheles claviger and Ochlerotatus punctor). Results obtained with the three statistical models were compared with regard to: (i) environmental suitability maps, (ii) environmental variables associated with occurrence, (iii) model evaluation. The models indicated that precipitation, temperature and population density were associated with the occurrence of Cs. annulata and An. claviger, whereas land surface temperature and vegetation indices were associated with the presence of Oc. punctor. The maps produced with the three different modelling techniques showed consistent spatial patterns for each species, but differences in the ranges of the predictions. Non-linear discriminant analysis had lower predictions than other methods. The model with the best classification skills for all the species was the random forest model, with specificity values ranging from 0.89 to 0.91, and sensitivity values ranging from 0.64 to 0.95. We mapped the environmental suitability for three mosquito species with three different modelling techniques. For each species, the maps showed consistent spatial patterns, but the level of predicted environmental suitability differed; NLDA gave lower predicted probabilities of presence than the other two methods. The variables selected as important in the models were in agreement with the existing knowledge about

  3. 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....... Plankton may be particularly challenging to model, due to its short life span and the dispersive effects of constant water movements on all spatial scales, however there are few other studies against which to compare these results. We conclude that rigorous model validation, including comparison against...

  4. Modeling plant species distributions under future climates: how fine scale do climate projections need to be?

    Science.gov (United States)

    Franklin, Janet; Davis, Frank W; Ikegami, Makihiko; Syphard, Alexandra D; Flint, Lorraine E; Flint, Alan L; Hannah, Lee

    2013-02-01

    Recent studies suggest that species distribution models (SDMs) based on fine-scale climate data may provide markedly different estimates of climate-change impacts than coarse-scale models. However, these studies disagree in their conclusions of how scale influences projected species distributions. In rugged terrain, coarse-scale climate grids may not capture topographically controlled climate variation at the scale that constitutes microhabitat or refugia for some species. Although finer scale data are therefore considered to better reflect climatic conditions experienced by species, there have been few formal analyses of how modeled distributions differ with scale. We modeled distributions for 52 plant species endemic to the California Floristic Province of different life forms and range sizes under recent and future climate across a 2000-fold range of spatial scales (0.008-16 km(2) ). We produced unique current and future climate datasets by separately downscaling 4 km climate models to three finer resolutions based on 800, 270, and 90 m digital elevation models and deriving bioclimatic predictors from them. As climate-data resolution became coarser, SDMs predicted larger habitat area with diminishing spatial congruence between fine- and coarse-scale predictions. These trends were most pronounced at the coarsest resolutions and depended on climate scenario and species' range size. On average, SDMs projected onto 4 km climate data predicted 42% more stable habitat (the amount of spatial overlap between predicted current and future climatically suitable habitat) compared with 800 m data. We found only modest agreement between areas predicted to be stable by 90 m models generalized to 4 km grids compared with areas classified as stable based on 4 km models, suggesting that some climate refugia captured at finer scales may be missed using coarser scale data. These differences in projected locations of habitat change may have more serious implications than net

  5. Mechanistic species distribution modelling as a link between physiology and conservation.

    Science.gov (United States)

    Evans, Tyler G; Diamond, Sarah E; Kelly, Morgan W

    2015-01-01

    Climate change conservation planning relies heavily on correlative species distribution models that estimate future areas of occupancy based on environmental conditions encountered in present-day ranges. The approach benefits from rapid assessment of vulnerability over a large number of organisms, but can have poor predictive power when transposed to novel environments and reveals little in the way of causal mechanisms that define changes in species distribution or abundance. Having conservation planning rely largely on this single approach also increases the risk of policy failure. Mechanistic models that are parameterized with physiological information are expected to be more robust when extrapolating distributions to future environmental conditions and can identify physiological processes that set range boundaries. Implementation of mechanistic species distribution models requires knowledge of how environmental change influences physiological performance, and because this information is currently restricted to a comparatively small number of well-studied organisms, use of mechanistic modelling in the context of climate change conservation is limited. In this review, we propose that the need to develop mechanistic models that incorporate physiological data presents an opportunity for physiologists to contribute more directly to climate change conservation and advance the field of conservation physiology. We begin by describing the prevalence of species distribution modelling in climate change conservation, highlighting the benefits and drawbacks of both mechanistic and correlative approaches. Next, we emphasize the need to expand mechanistic models and discuss potential metrics of physiological performance suitable for integration into mechanistic models. We conclude by summarizing other factors, such as the need to consider demography, limiting broader application of mechanistic models in climate change conservation. Ideally, modellers, physiologists and

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

    OpenAIRE

    2016-01-01

    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...

  7. Ditch the niche - is the niche a useful concept in ecology or species distribution modelling?

    NARCIS (Netherlands)

    McInerny, Greg J.; Etienne, Rampal S.

    2012-01-01

    In this first of three papers we examine the use of niche concepts in ecology and especially in species distribution modelling (SDM). This paper deliberately focuses on the lack of clarity found in the term niche. Because its meanings are so diverse, the term niche tends to create confusion and

  8. 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.

  9. 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...... butterfly distributions under climate change. Model performance was lower with independent compared to non-independent validation and improved when land cover and soil type variables were included, compared to climate-only models. SDMs performed less well for highly mobile species and for species with long...

  10. Species-environment relationships and potential for distribution modelling in coastal waters

    Science.gov (United States)

    Snickars, M.; Gullström, M.; Sundblad, G.; Bergström, U.; Downie, A.-L.; Lindegarth, M.; Mattila, J.

    2014-01-01

    Due to increasing pressure on the marine environment there is a growing need to understand species-environment relationships. To provide background for prioritising among variables (predictors) for use in distribution models, the relevance of predictors for benthic species was reviewed using the coastal Baltic Sea as a case-study area. Significant relationships for three response groups (fish, macroinvertebrates, macrovegetation) and six predictor categories (bottom topography, biotic features, hydrography, wave exposure, substrate and spatiotemporal variability) were extracted from 145 queried peer-reviewed field-studies covering three decades and six subregions. In addition, the occurrence of interaction among predictors was analysed. Hydrography was most often found in significant relationships, had low level of interaction with other predictors, but also had the most non-significant relationships. Depth and wave exposure were important in all subregions and are readily available, increasing their applicability for cross-regional modelling efforts. Otherwise, effort to model species distributions may prove challenging at larger scale as the relevance of predictors differed among both response groups and regions. Fish and hard bottom macrovegetation have the largest modelling potential, as they are structured by a set of predictors that at the same time are accurately mapped. A general importance of biotic features implies that these need to be accounted for in distribution modelling, but the mapping of most biotic features is challenging, which currently lowers the applicability. The presence of interactions suggests that predictive methods allowing for interactive effects are preferable. Detailing these complexities is important for future distribution modelling.

  11. Dispersal leads to spatial autocorrelation in species distributions: A simulation model

    Science.gov (United States)

    Bahn, V.; Krohn, W.B.; O'Connor, R.J.

    2008-01-01

    Compared to population growth regulated by local conditions, dispersal has been underappreciated as a central process shaping the spatial distribution of populations. This paper asks: (a) which conditions increase the importance of dispersers relative to local recruits in determining population sizes? and (b) how does dispersal influence the spatial distribution patterns of abundances among connected populations? We approached these questions with a simulation model of populations on a coupled lattice with cells of continuously varying habitat quality expressed as carrying capacities. Each cell contained a population with the basic dynamics of density-regulated growth, and was connected to other populations by immigration and emigration. The degree to which dispersal influenced the distribution of population sizes depended most strongly on the absolute amount of dispersal, and then on the potential population growth rate. Dispersal decaying in intensity with distance left close neighbours more alike in population size than distant populations, leading to an increase in spatial autocorrelation. The spatial distribution of species with low potential growth rates is more dependent on dispersal than that of species with high growth rates; therefore, distribution modelling for species with low growth rates requires particular attention to autocorrelation, and conservation management of these species requires attention to factors curtailing dispersal, such as fragmentation and dispersal barriers. ?? 2007 Elsevier B.V. All rights reserved.

  12. The predictive skill of species distribution models for plankton in a changing climate.

    Science.gov (United States)

    Brun, Philipp; Kiørboe, Thomas; Licandro, Priscilla; Payne, Mark R

    2016-09-01

    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 of the longest running and most extensive marine biological monitoring programs, to investigate the reliability of predicted plankton distributions. We apply three commonly used SDMs to 20 representative plankton species, including copepods, diatoms, and dinoflagellates, all found in the North Atlantic and adjacent seas. We fit the models to decadal subsets of the full (1958-2012) dataset, and then use them to predict both forward and backward in time, comparing the model predictions against the corresponding observations. The probability of correctly predicting presence was low, peaking at 0.5 for copepods, and model skill typically did not outperform a null model assuming distributions to be constant in time. The predicted prevalence increasingly differed from the observed prevalence for predictions with more distance in time from their training dataset. More detailed investigations based on four focal species revealed that strong spatial variations in skill exist, with the least skill at the edges of the distributions, where prevalence is lowest. Furthermore, the scores of traditional single-value model performance metrics were contrasting and some implied overoptimistic conclusions about model skill. Plankton may be particularly challenging to model, due to its short life span and the dispersive effects of constant water movements on all spatial scales, however there are few other studies against which to compare these results. We conclude that rigorous model validation, including comparison against null models, is essential to assess the robustness of projections of marine planktonic species under climate change. © 2016 John Wiley & Sons Ltd.

  13. Unpacking the mechanisms captured by a correlative species distribution model to improve predictions of climate refugia.

    Science.gov (United States)

    Briscoe, Natalie J; Kearney, Michael R; Taylor, Chris A; Wintle, Brendan A

    2016-07-01

    Climate refugia are regions that animals can retreat to, persist in and potentially then expand from under changing environmental conditions. Most forecasts of climate change refugia for species are based on correlative species distribution models (SDMs) using long-term climate averages, projected to future climate scenarios. Limitations of such methods include the need to extrapolate into novel environments and uncertainty regarding the extent to which proximate variables included in the model capture processes driving distribution limits (and thus can be assumed to provide reliable predictions under new conditions). These limitations are well documented; however, their impact on the quality of climate refugia predictions is difficult to quantify. Here, we develop a detailed bioenergetics model for the koala. It indicates that range limits are driven by heat-induced water stress, with the timing of rainfall and heat waves limiting the koala in the warmer parts of its range. We compare refugia predictions from the bioenergetics model with predictions from a suite of competing correlative SDMs under a range of future climate scenarios. SDMs were fitted using combinations of long-term climate and weather extremes variables, to test how well each set of predictions captures the knowledge embedded in the bioenergetics model. Correlative models produced broadly similar predictions to the bioenergetics model across much of the species' current range - with SDMs that included weather extremes showing highest congruence. However, predictions in some regions diverged significantly when projecting to future climates due to the breakdown in correlation between climate variables. We provide unique insight into the mechanisms driving koala distribution and illustrate the importance of subtle relationships between the timing of weather events, particularly rain relative to hot-spells, in driving species-climate relationships and distributions. By unpacking the mechanisms

  14. Phenotypic distribution models corroborate species distribution models: A shift in the role and prevalence of a dominant prairie grass in response to climate change.

    Science.gov (United States)

    Smith, Adam B; Alsdurf, Jacob; Knapp, Mary; Baer, Sara G; Johnson, Loretta C

    2017-10-01

    Phenotypic distribution within species can vary widely across environmental gradients but forecasts of species' responses to environmental change often assume species respond homogenously across their ranges. We compared predictions from species and phenotype distribution models under future climate scenarios for Andropogon gerardii, a widely distributed, dominant grass found throughout the central United States. Phenotype data on aboveground biomass, height, leaf width, and chlorophyll content were obtained from 33 populations spanning a ~1000 km gradient that encompassed the majority of the species' environmental range. Species and phenotype distribution models were trained using current climate conditions and projected to future climate scenarios. We used permutation procedures to infer the most important variable for each model. The species-level response to climate was most sensitive to maximum temperature of the hottest month, but phenotypic variables were most sensitive to mean annual precipitation. The phenotype distribution models predict that A. gerardii could be largely functionally eliminated from where this species currently dominates, with biomass and height declining by up to ~60% and leaf width by ~20%. By the 2070s, the core area of highest suitability for A. gerardii is projected to shift up to ~700 km northeastward. Further, short-statured phenotypes found in the present-day short grass prairies on the western periphery of the species' range will become favored in the current core ~800 km eastward of their current location. Combined, species and phenotype models predict this currently dominant prairie grass will decline in prevalence and stature. Thus, sourcing plant material for grassland restoration and forage should consider changes in the phenotype that will be favored under future climate conditions. Phenotype distribution models account for the role of intraspecific variation in determining responses to anticipated climate change and

  15. 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

    2017-09-06

    Fluvial fishes face increased imperilment from anthropogenic activities, but the specific factors contributing most to range declines are often poorly understood. For example, the shoal bass (Micropterus cataractae) is a fluvial-specialist species experiencing continual range loss, yet how perceived threats have contributed to range loss is largely unknown. We employed species distribution models (SDMs) to disentangle which factors are contributing most to shoal bass range loss by estimating a potential distribution based on natural abiotic factors and by estimating a series of current, occupied distributions that also incorporated variables characterizing land cover, non-native species, and fragmentation intensity (no fragmentation, dams only, and dams and large impoundments). Model construction allowed for 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 current occupied distribution illustrated increased range loss as fragmentation intensified. Response curves from current occupied models 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 free-flowing fragment lengths of > 100 km were necessary to support shoal bass presence. Model evaluation, including an independent validation, suggested models had favorable predictive and discriminative abilities. Similar approaches that use readily-available, diverse geospatial datasets may deliver insights into the biology and conservation needs of other fluvial species facing similar threats. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

  16. Tackling intraspecific genetic structure in distribution models better reflects species geographical range.

    Science.gov (United States)

    Marcer, Arnald; Méndez-Vigo, Belén; Alonso-Blanco, Carlos; Picó, F Xavier

    2016-04-01

    Genetic diversity provides insight into heterogeneous demographic and adaptive history across organisms' distribution ranges. For this reason, decomposing single species into genetic units may represent a powerful tool to better understand biogeographical patterns as well as improve predictions of the effects of GCC (global climate change) on biodiversity loss. Using 279 georeferenced Iberian accessions, we used classes of three intraspecific genetic units of the annual plant Arabidopsis thaliana obtained from the genetic analyses of nuclear SNPs (single nucleotide polymorphisms), chloroplast SNPs, and the vernalization requirement for flowering. We used SDM (species distribution models), including climate, vegetation, and soil data, at the whole-species and genetic-unit levels. We compared model outputs for present environmental conditions and with a particularly severe GCC scenario. SDM accuracy was high for genetic units with smaller distribution ranges. Kernel density plots identified the environmental variables underpinning potential distribution ranges of genetic units. Combinations of environmental variables accounted for potential distribution ranges of genetic units, which shrank dramatically with GCC at almost all levels. Only two genetic clusters increased their potential distribution ranges with GCC. The application of SDM to intraspecific genetic units provides a detailed picture on the biogeographical patterns of distinct genetic groups based on different genetic criteria. Our approach also allowed us to pinpoint the genetic changes, in terms of genetic background and physiological requirements for flowering, that Iberian A. thaliana may experience with a GCC scenario applying SDM to intraspecific genetic units.

  17. 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

  18. 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.

  19. Impact Assessment of Pine Wilt Disease Using the Species Distribution Model and the CLIMEX Model

    Science.gov (United States)

    KIM, J. U.; Jung, H.

    2016-12-01

    The plant disease triangle consists of the host plant, pathogen and environment, but their interaction has not been considered in climate change adaptation policy. Our objectives are to predict the changes of a coniferous forest, pine wood nematodes (Bursaphelenchus xylophilus) and pine sawyer beetles (Monochamus spp.), which is a cause of pine wilt disease in the Republic of Korea. We analyzed the impact of pine wilt disease on climate change by using the species distribution model (SDM) and the CLIMEX model. Area of coniferous forest will decline and move to northern and high-altitude area. But pine wood nematodes and pine sawyer beetles are going to spread because they are going to be in a more favorable environment in the future. Coniferous forests are expected to have high vulnerability because of the decrease in area and the increase in the risk of pine wilt disease. Such changes to forest ecosystems will greatly affect climate change in the future. If effective and appropriate prevention and control policies are not implemented, coniferous forests will be severely damaged. An adaptation policy should be created in order to protect coniferous forests from the viewpoint of biodiversity. Thus we need to consider the impact assessment of climate change for establishing an effective adaptation policy. The impact assessment of pine wilt disease using a plant disease triangle drew suitable results to support climate change adaptation policy.

  20. 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.

  1. Evaluating how species niche modelling is affected by partial distributions with an empirical case

    Science.gov (United States)

    Carretero, Miguel A.; Sillero, Neftalí

    2016-11-01

    Ecological niche models (ENMs) will successfully identify a species' ecological niche, provided that important assumptions are fulfilled, namely environment equilibrium and niche equality across the distribution. Violations may seriously affect ENM reliability, leading to erroneous biogeographic conclusions and inappropriate conservation prioritisation. We evaluate the robustness of ENMs against incomplete knowledge of distribution with a real example, the threatened Iberian lizard Podarcis carbonelli, whose distribution was gradually discovered over a long time period. We used several ENM methods for presence-only data (Maxent, ENFA, Bioclim, and Domain) to infer the realised ecological niche at two spatial resolutions (1 km and 200 m). The distribution data were split into four partial datasets corresponding to separate subranges: Central System (CS); Viseu-Aveiro (VA); Atlantic coast (AC); and Doñana (DO). We then accumulated the datasets following the species discovery sequence: CS + VA, CS + VA + AC, and CS + VA + AC + DO. Niche equivalence and similarity between partial models were compared using Ecospat. ENMs were strongly affected by the violation of niche equilibrium; only the VA subrange forecasts the complete species range. ENMs were also sensitive to the violation of niche equality: only VA models were similar to the Iberian model, altitude being the most important variable followed by annual precipitation, maximum temperature in July, and annual radiation. When the ENMs were applied only to the first subrange discovered (CS), only the VA area was predicted, while the other subranges might have remained unknown, thus compromising conservation strategies. As assumptions of niche equilibrium and equality were violated, likely owing to the species' ecological multimodality, the models generated were biased and of limited predictive value. ENMs are useful tools in biogeography and conservation, but only if their basal assumptions are achieved. Partial

  2. Modelling the spatial distribution of the nuisance mosquito species Anopheles plumbeus (Diptera: Culicidae) in the Netherlands.

    Science.gov (United States)

    Ibañez-Justicia, Adolfo; Cianci, Daniela

    2015-05-01

    Landscape modifications, urbanization or changes of use of rural-agricultural areas can create more favourable conditions for certain mosquito species and therefore indirectly cause nuisance problems for humans. This could potentially result in mosquito-borne disease outbreaks when the nuisance is caused by mosquito species that can transmit pathogens. Anopheles plumbeus is a nuisance mosquito species and a potential malaria vector. It is one of the most frequently observed species in the Netherlands. Information on the distribution of this species is essential for risk assessments. The purpose of the study was to investigate the potential spatial distribution of An. plumbeus in the Netherlands. Random forest models were used to link the occurrence and the abundance of An. plumbeus with environmental features and to produce distribution maps in the Netherlands. Mosquito data were collected using a cross-sectional study design in the Netherlands, from April to October 2010-2013. The environmental data were obtained from satellite imagery and weather stations. Statistical measures (accuracy for the occurrence model and mean squared error for the abundance model) were used to evaluate the models performance. The models were externally validated. The maps show that forested areas (centre of the Netherlands) and the east of the country were predicted as suitable for An. plumbeus. In particular high suitability and high abundance was predicted in the south-eastern provinces Limburg and North Brabant. Elevation, precipitation, day and night temperature and vegetation indices were important predictors for calculating the probability of occurrence for An. plumbeus. The probability of occurrence, vegetation indices and precipitation were important for predicting its abundance. The AUC value was 0.73 and the error in the validation was 0.29; the mean squared error value was 0.12. The areas identified by the model as suitable and with high abundance of An. plumbeus, are

  3. 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)

  4. 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

  5. Fit-for-purpose: species distribution model performance depends on evaluation criteria - Dutch Hoverflies as a case study.

    Science.gov (United States)

    Aguirre-Gutiérrez, Jesús; Carvalheiro, Luísa G; Polce, Chiara; van Loon, E Emiel; Raes, Niels; Reemer, Menno; Biesmeijer, Jacobus C

    2013-01-01

    Understanding species distributions and the factors limiting them is an important topic in ecology and conservation, including in nature reserve selection and predicting climate change impacts. While Species Distribution Models (SDM) are the main tool used for these purposes, choosing the best SDM algorithm is not straightforward as these are plentiful and can be applied in many different ways. SDM are used mainly to gain insight in 1) overall species distributions, 2) their past-present-future probability of occurrence and/or 3) to understand their ecological niche limits (also referred to as ecological niche modelling). The fact that these three aims may require different models and outputs is, however, rarely considered and has not been evaluated consistently. Here we use data from a systematically sampled set of species occurrences to specifically test the performance of Species Distribution Models across several commonly used algorithms. Species range in distribution patterns from rare to common and from local to widespread. We compare overall model fit (representing species distribution), the accuracy of the predictions at multiple spatial scales, and the consistency in selection of environmental correlations all across multiple modelling runs. As expected, the choice of modelling algorithm determines model outcome. However, model quality depends not only on the algorithm, but also on the measure of model fit used and the scale at which it is used. Although model fit was higher for the consensus approach and Maxent, Maxent and GAM models were more consistent in estimating local occurrence, while RF and GBM showed higher consistency in environmental variables selection. Model outcomes diverged more for narrowly distributed species than for widespread species. We suggest that matching study aims with modelling approach is essential in Species Distribution Models, and provide suggestions how to do this for different modelling aims and species' data

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

    Science.gov (United States)

    van der Maaten, Ernst; Hamann, Andreas; van der Maaten-Theunissen, Marieke; Bergsma, Aldo; Hengeveld, Geerten; van Lammeren, Ron; Mohren, Frits; Nabuurs, Gert-Jan; Terhürne, Renske; Sterck, Frank

    2017-04-01

    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 investigate whether climate suitability predictions correlate to tree growth, measured in permanent inventory plots and inferred from tree-ring records. We use the ensemble classifier RandomForest and species occurrence data from ~200,000 inventory plots to build species distribution models for four important European forestry species: Norway spruce, Scots pine, European beech, and pedunculate oak. We then correlate climate-based habitat suitability with volume measurements from ~50-year-old stands, available from ~11,000 inventory plots. Secondly, habitat projections based on annual historical climate are compared with ring width from ~300 tree-ring chronologies. Our working hypothesis is that habitat suitability projections from species distribution models should to some degree be associated with temporal or spatial variation in these growth records. We find that the habitat projections are uncorrelated with spatial growth records (inventory plot data), but they do predict interannual variation in tree-ring width, with an average correlation of .22. Correlation coefficients for individual chronologies range from values as high as .82 or as low as -.31. We conclude that tree responses to projected climate change are highly site-specific and that local suitability of a species for reforestation is difficult to predict. That said, projected increase or decrease in climatic suitability may be interpreted as an average expectation of increased or reduced growth over larger geographic scales.

  7. Feeding habitat quality and behavioral trade-offs in chimpanzees: a case for species distribution models.

    Science.gov (United States)

    Foerster, Steffen; Zhong, Ying; Pintea, Lilian; Murray, Carson M; Wilson, Michael L; Mjungu, Deus C; Pusey, Anne E

    2016-01-01

    The distribution and abundance of food resources are among the most important factors that influence animal behavioral strategies. Yet, spatial variation in feeding habitat quality is often difficult to assess with traditional methods that rely on extrapolation from plot survey data or remote sensing. Here, we show that maximum entropy species distribution modeling can be used to successfully predict small-scale variation in the distribution of 24 important plant food species for chimpanzees at Gombe National Park, Tanzania. We combined model predictions with behavioral observations to quantify feeding habitat quality as the cumulative dietary proportion of the species predicted to occur in a given location. This measure exhibited considerable spatial heterogeneity with elevation and latitude, both within and across main habitat types. We used model results to assess individual variation in habitat selection among adult chimpanzees during a 10-year period, testing predictions about trade-offs between foraging and reproductive effort. We found that nonswollen females selected the highest-quality habitats compared with swollen females or males, in line with predictions based on their energetic needs. Swollen females appeared to compromise feeding in favor of mating opportunities, suggesting that females rather than males change their ranging patterns in search of mates. Males generally occupied feeding habitats of lower quality, which may exacerbate energetic challenges of aggression and territory defense. Finally, we documented an increase in feeding habitat quality with community residence time in both sexes during the dry season, suggesting an influence of familiarity on foraging decisions in a highly heterogeneous landscape.

  8. 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...

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

    Science.gov (United States)

    Poco, Jorge; Doraiswamy, Harish; Talbert, Marian K.; 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.

  10. A coupled phylogeographical and species distribution modelling approach recovers the demographical history of a Neotropical seasonally dry forest tree species.

    Science.gov (United States)

    Collevatti, Rosane G; Terribile, Levi Carina; Lima-Ribeiro, Matheus S; Nabout, João C; de Oliveira, Guilherme; Rangel, Thiago F; Rabelo, Suelen G; Diniz-Filho, Jose A F

    2012-12-01

    We investigated here the demographical history of Tabebuia impetiginosa (Bignoniaceae) to understand the dynamics of the disjunct geographical distribution of South American seasonally dry forests (SDFs), based on coupling an ensemble approach encompassing hindcasting species distribution modelling and statistical phylogeographical analysis. We sampled 17 populations (280 individuals) in central Brazil and analysed the polymorphisms at chloroplast (trnS-trnG, psbA-trnH, and ycf6-trnC intergenic spacers) and nuclear (ITS nrDNA) genomes. Phylogenetic analyses based on median-joining network showed no haplotype sharing among population but strong evidence of incomplete lineage sorting. Coalescent analyses showed historical constant populations size, negligible gene flow among populations, and an ancient time to most recent common ancestor dated from ~4.7 ± 1.1 Myr BP. Most divergences dated from the Lower Pleistocene, and no signal of important population size reduction was found in coalescent tree and tests of demographical expansion. Demographical scenarios were built based on past geographical range dynamic models, using two a priori biogeographical hypotheses ('Pleistocene Arc' and 'Amazonian SDF expansion') and on two additional hypotheses suggested by the palaeodistribution modelling built with several algorithms for distribution modelling and palaeoclimatic data. The simulation of these demographical scenarios showed that the pattern of diversity found so far for T. impetiginosa is in consonance with a palaeodistribution expansion during the last glacial maximum (LGM, 21 kyr BP), strongly suggesting that the current disjunct distribution of T. impetiginosa in SDFs may represent a climatic relict of a once more wide distribution.

  11. A spatial model for sporadic tree species distribution in support of tree oriented silviculture

    Directory of Open Access Journals (Sweden)

    Davide Melini

    2013-12-01

    Full Text Available This technical note describes how a spatial model for sporadic tree species distribution in the territory of the Unione di Comuni Montana Colline Metallifere (UCMCM was built using the Random Forest (RF algorithm and 48 predictors, including reflectance values from ground cover - provided by satellite sensors - and ecological factors. The  P.Pro.SPO.T. project - Policy and Protection of Sporadic tree species in Tuscany forest (LIFE 09 ENV/IT/000087 is currently carried out in this area with the purpose of initiating the implementation of tree oriented silviculture in the Tuscany forests. Tree oriented silviculture aims at obtaining both forest biodiversity protection and local production of valuable timber. After creating a map showing the probability of presence of sporadic tree species, it was possible to identify the most suitable areas for sporadic tree species which are under protection according to the regulation of the Tuscany Region.Using data and software provided free of charge, and applying the RF algorithm, distribution models could be developed in order to identify the most suitable areas for the application of tree oriented silviculture. This can provide a support to forestry planning that includes tree oriented silviculture, thus reducing its implementation cost.

  12. Assessment of Forest Conservation Value Using a Species Distribution Model and Object-based Image Analysis

    Science.gov (United States)

    Jin, Y.; Lee, D. K.; Jeong, S. G.

    2015-12-01

    The ecological and social values of forests have recently been highlighted. Assessments of the biodiversity of forests, as well as their other ecological values, play an important role in regional and national conservation planning. The preservation of habitats is linked to the protection of biodiversity. For mapping habitats, species distribution model (SDM) is used for predicting suitable habitat of significant species, and such distribution modeling is increasingly being used in conservation science. However, the pixel-based analysis does not contain contextual or topological information. In order to provide more accurate habitats predictions, a continuous field view that assumes the real world is required. Here we analyze and compare at different scales, habitats of the Yellow Marten's(Martes Flavigula), which is a top predator and also an umbrella species in South Korea. The object-scale, which is a group of pixels that have similar spatial and spectral characteristics, and pixel-scale were used for SDM. Our analysis using the SDM at different scales suggests that object-scale analysis provides a superior representation of continuous habitat, and thus will be useful in forest conservation planning as well as for species habitat monitoring.

  13. Fitting and comparing competing models of the species abundance distribution: assessment and prospect

    Directory of Open Access Journals (Sweden)

    Thomas J Matthews

    2014-06-01

    Full Text Available A species abundance distribution (SAD characterises patterns in the commonness and rarity of all species within an ecological community. As such, the SAD provides the theoretical foundation for a number of other biogeographical and macroecological patterns, such as the species–area relationship, as well as being an interesting pattern in its own right. While there has been resurgence in the study of SADs in the last decade, less focus has been placed on methodology in SAD research, and few attempts have been made to synthesise the vast array of methods which have been employed in SAD model evaluation. As such, our review has two aims. First, we provide a general overview of SADs, including descriptions of the commonly used distributions, plotting methods and issues with evaluating SAD models. Second, we review a number of recent advances in SAD model fitting and comparison. We conclude by providing a list of recommendations for fitting and evaluating SAD models. We argue that it is time for SAD studies to move away from many of the traditional methods available for fitting and evaluating models, such as sole reliance on the visual examination of plots, and embrace statistically rigorous techniques. In particular, we recommend the use of both goodness-of-fit tests and model-comparison analyses because each provides unique information which one can use to draw inferences.

  14. 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.

  15. 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

  16. 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.

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

    Science.gov (United States)

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

    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 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 for the

  18. Integrating multiple data sources in species distribution modeling: a framework for data fusion.

    Science.gov (United States)

    Pacifici, Krishna; Reich, Brian J; Miller, David A W; Gardner, Beth; Stauffer, Glenn; Singh, Susheela; McKerrow, Alexa; Collazo, Jaime A

    2017-03-01

    The last decade has seen a dramatic increase in the use of species distribution models (SDMs) to characterize patterns of species' occurrence and abundance. Efforts to parameterize SDMs often create a tension between the quality and quantity of data available to fit models. Estimation methods that integrate both standardized and non-standardized data types offer a potential solution to the tradeoff between data quality and quantity. Recently several authors have developed approaches for jointly modeling two sources of data (one of high quality and one of lesser quality). We extend their work by allowing for explicit spatial autocorrelation in occurrence and detection error using a Multivariate Conditional Autoregressive (MVCAR) model and develop three models that share information in a less direct manner resulting in more robust performance when the auxiliary data is of lesser quality. We describe these three new approaches ("Shared," "Correlation," "Covariates") for combining data sources and show their use in a case study of the Brown-headed Nuthatch in the Southeastern U.S. and through simulations. All three of the approaches which used the second data source improved out-of-sample predictions relative to a single data source ("Single"). When information in the second data source is of high quality, the Shared model performs the best, but the Correlation and Covariates model also perform well. When the information quality in the second data source is of lesser quality, the Correlation and Covariates model performed better suggesting they are robust alternatives when little is known about auxiliary data collected opportunistically or through citizen scientists. Methods that allow for both data types to be used will maximize the useful information available for estimating species distributions. © 2016 The Authors. Ecology, published by Wiley Periodicals, Inc., on behalf of the Ecological Society of America.

  19. 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

  20. 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

  1. 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

  2. Modeling "habitat suitability" for a herbicide resistant weed using a species distribution model and presence-only data

    Science.gov (United States)

    Herbicide resistant weeds are like invasive weeds: prompt management is needed to prevent their spread. For invasive weeds, first reports of a weed's occurrence are often analyzed with species distribution models (SDM) to prioritize detection and treatment. Suitability of other areas as habitat for ...

  3. The OH distribution in cometary atmospheres - A collisional Monte Carlo model for heavy species

    Science.gov (United States)

    Combi, Michael R.; Bos, Brent J.; Smyth, William H.

    1993-01-01

    The study presents an extension of the cometary atmosphere Monte Carlo particle trajectory model formalism which makes it both physically correct for heavy species and yet computationally reasonable. The derivation accounts for the collision path and scattering redirection of a heavy radical traveling through a fluid coma with a given radial distribution in outflow speed and temperature. The revised model verifies that the earlier fast-H atom approximations used in earlier work are valid, and it is applied to a case where the heavy radical formalism is necessary: the OH distribution. It is found that a steeper variation of water production rate with heliocentric distance is required for a water coma which is consistent with the velocity-resolved observations of Comet P/Halley.

  4. Fit-for-purpose: species distribution model performance depends on evaluation criteria -Dutch hoverflies as a case study

    NARCIS (Netherlands)

    Aguirre-Gutiérrez, J.; Carvalheiro, L.G.; Polce, C.; van Loon, E.E.; Raes, N.; Reemer, M.; Biesmeijer, J.C.

    2013-01-01

    Understanding species distributions and the factors limiting them is an important topic in ecology and conservation, including in nature reserve selection and predicting climate change impacts. While Species Distribution Models (SDM) are the main tool used for these purposes, choosing the best SDM a

  5. Fit-for-purpose: species distribution model performance depends on evaluation criteria -Dutch hoverflies as a case study

    NARCIS (Netherlands)

    Aguirre-Gutiérrez, J.; Carvalheiro, L.G.; Polce, C.; van Loon, E.E.; Raes, N.; Reemer, M.; Biesmeijer, J.C.

    2013-01-01

    Understanding species distributions and the factors limiting them is an important topic in ecology and conservation, including in nature reserve selection and predicting climate change impacts. While Species Distribution Models (SDM) are the main tool used for these purposes, choosing the best SDM

  6. 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

  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. A Centroid Model of Species Distribution to Analyize Multi-directional Climate Change Finger Print in Avian Distribution in North America

    Science.gov (United States)

    Huang, Q.; Sauer, J.; Dubayah, R.

    2015-12-01

    Species distribution shift (or referred to as "fingerprint of climate change") as a primary mechanism to adapt climate change has been of great interest to ecologists and conservation practitioners. Recent meta-analyses have concluded that a wide range of animal and plant species are already shifting their distribution. However majority of the literature has focused on analyzing recent poleward and elevationally upward shift of species distribution. However if measured only in poleward shifts, the fingerprint of climate change will be underestimated significantly. In this study, we demonstrate a centroid model for range-wide analysis of distribution shifts using the North American Breeding Bird Survey. The centroid model is based on a hierarchical Bayesian framework which models population change within physiographic strata while accounting for several factors affecting species detectability. We used the centroid approach to examine large number of species permanent resident species in North America and evaluated the dreiction and magnitude of their shifting distribution. To examine the inferential ability of mean temperature and precipitation, we test a hypothesis based on climate velocity theory that species would be more likely to shift their distribution or would shift with greater magnitude in in regions with high climate change velocity. For species with significant shifts of distribution, we establish a precipitation model and a temperature model to explain their change of abundance at the strata level. Two models which are composed of mean and extreme climate indices respectively are also established to test the influences of changes in gradual and extreme climate trends.

  9. Cross-validation of species distribution models: removing spatial sorting bias and calibration with a null model.

    Science.gov (United States)

    Hijmans, Robert J

    2012-03-01

    Species distribution models are usually evaluated with cross-validation. In this procedure evaluation statistics are computed from model predictions for sites of presence and absence that were not used to train (fit) the model. Using data for 226 species, from six regions, and two species distribution modeling algorithms (Bioclim and MaxEnt), I show that this procedure is highly sensitive to "spatial sorting bias": the difference between the geographic distance from testing-presence to training-presence sites and the geographic distance from testing-absence (or testing-background) to training-presence sites. I propose the use of pairwise distance sampling to remove this bias, and the use of a null model that only considers the geographic distance to training sites to calibrate cross-validation results for remaining bias. Model evaluation results (AUC) were strongly inflated: the null model performed better than MaxEnt for 45% and better than Bioclim for 67% of the species. Spatial sorting bias and area under the receiver-operator curve (AUC) values increased when using partitioned presence data and random-absence data instead of independently obtained presence-absence testing data from systematic surveys. Pairwise distance sampling removed spatial sorting bias, yielding null models with an AUC close to 0.5, such that AUC was the same as null model calibrated AUC (cAUC). This adjustment strongly decreased AUC values and changed the ranking among species. Cross-validation results for different species are only comparable after removal of spatial sorting bias and/or calibration with an appropriate null model.

  10. 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.

  11. Modeling the Potential Distribution of Picea chihuahuana Martínez, an Endangered Species at the Sierra Madre Occidental, Mexico

    OpenAIRE

    2015-01-01

    Species distribution models (SDMs) help identify areas for the development of populations or communities to prevent extinctions, especially in the face of the global environmental change. This study modeled the potential distribution of the tree Picea chihuahuana Martínez, a species in danger of extinction, using the maximum entropy modeling method (MaxEnt) at three scales: local, state and national. We used a total of 38 presence data from the Sierra Madre Occidental. At the local scale, we...

  12. Regional data refine local predictions: modeling the distribution of plant species abundance on a portion of the central plains.

    Science.gov (United States)

    Young, Nicholas E; Stohlgren, Thomas J; Evangelista, Paul H; Kumar, Sunil; Graham, Jim; Newman, Greg

    2012-09-01

    Species distribution models are frequently used to predict species occurrences in novel conditions, yet few studies have examined the consequences of extrapolating locally collected data to regional landscapes. Similarly, the process of using regional data to inform local prediction for species distribution models has not been adequately evaluated. Using boosted regression trees, we examined errors associated with extrapolating models developed with locally collected abundance data to regional-scale spatial extents and associated with using regional data for predictions at a local extent for a native and non-native plant species across the northeastern central plains of Colorado. Our objectives were to compare model results and accuracy between those developed locally and extrapolated regionally, those developed regionally and extrapolated locally, and to evaluate extending species distribution modeling from predicting the probability of presence to predicting abundance. We developed models to predict the spatial distribution of plant species abundance using topographic, remotely sensed, land cover and soil taxonomic predictor variables. We compared model predicted mean and range abundance values to observed values between local and regional. We also evaluated model prediction performance based on Pearson's correlation coefficient. We show that: (1) extrapolating local models to regional extents may restrict predictions, (2) regional data can help refine and improve local predictions, and (3) boosted regression trees can be useful to model and predict plant species abundance. Regional sampling designed in concert with large sampling frameworks such as the National Ecological Observatory Network may improve our ability to monitor changes in local species abundance.

  13. a Plugin to Interface Openmodeller from Qgis for SPECIES' Potential Distribution Modelling

    Science.gov (United States)

    Becker, Daniel; Willmes, Christian; Bareth, Georg; Weniger, Gerd-Christian

    2016-06-01

    This contribution describes the development of a plugin for the geographic information system QGIS to interface the openModeller software package. The aim is to use openModeller to generate species' potential distribution models for various archaeological applications (site catchment analysis, for example). Since the usage of openModeller's command-line interface and configuration files can be a bit inconvenient, an extension of the QGIS user interface to handle these tasks, in combination with the management of the geographic data, was required. The implementation was realized in Python using PyQGIS and PyQT. The plugin, in combination with QGIS, handles the tasks of managing geographical data, data conversion, generation of configuration files required by openModeller and compilation of a project folder. The plugin proved to be very helpful with the task of compiling project datasets and configuration files for multiple instances of species occurrence datasets and the overall handling of openModeller. In addition, the plugin is easily extensible to take potential new requirements into account in the future.

  14. Modeling Spatial Distribution of a Rare and Endangered Plant Species (Brainea insignis) in Central Taiwan

    Science.gov (United States)

    Wang, W.-C.; Lo, N.-J.; Chang, W.-I.; Huang, K.-Y.

    2012-07-01

    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.

  15. 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

  16. 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.

  17. 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 K.; 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.

  18. 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.

  19. Ecophysiology of wetland plant roots: A modelling comparison of aeration in relation to species distribution

    Science.gov (United States)

    Sorrell, B.K.; Mendelssohn, I.A.; McKee, K.L.; Woods, R.A.

    2000-01-01

    This study examined the potential for inter-specific differences in root aeration to determine wetland plant distribution in nature. We compared aeration in species that differ in the type of sediment and depth of water they colonize. Differences in root anatomy, structure and physiology were applied to aeration models that predicted the maximum possible aerobic lengths and development of anoxic zones in primary adventitious roots. Differences in anatomy and metabolism that provided higher axial fluxes of oxygen allowed deeper root growth in species that favour more reducing sediments and deeper water. Modelling identified factors that affected growth in anoxic soils through their effects on aeration. These included lateral root formation, which occurred at the expense of extension of the primary root because of the additional respiratory demand they imposed, reducing oxygen fluxes to the tip and stele, and the development of stelar anoxia. However, changes in sediment oxygen demand had little detectable effect on aeration in the primary roots due to their low wall permeability and high surface impedance, but appeared to reduce internal oxygen availability by accelerating loss from laterals. The development of pressurized convective gas flow in shoots and rhizomes was also found to be important in assisting root aeration, as it maintained higher basal oxygen concentrations at the rhizome-root junctions in species growing into deep water. (C) 2000 Annals of Botany Company.

  20. [Distribution model of aluminum species in drinking water basing on the reaction kinetics].

    Science.gov (United States)

    Wang, Wen-dong; Yang, Hong-wei; Wang, Xiao-chang; Jiang, Jing; Zhu, Wan-peng; Jiang, Zhan-peng

    2010-04-01

    The effects of excess aluminum on water distribution system and human health were mainly attributable to the presences of some aluminum species in drinking water. A prediction model for the concentrations of aluminum species was developed using three-layer front feedback artificial neural network method. Results showed that the reaction rates of both inorganic monomeric aluminum and soluble aluminum varied with reaction time and water quality parameters, such as water temperature, pH, total aluminum, fluoride, phosphate and silicate. Their reaction orders were both three. The reaction kinetic parameters of inorganic monomeric aluminum and soluble aluminum could be predicted effectively applying artificial neural network; the correlation coefficients of k and 1/C0(2) between calculated value and predicted value were both greater than 0.999. Aluminum species prediction results in the drinking water of City M showed that when the concentration of total aluminum was less than 0.05 mg x L(-1), the relative prediction error was large for inorganic monomeric aluminum. When the concentration of total aluminum was above 0.05 mg x L(-1), the model could predict inorganic monomeric aluminum and soluble aluminum concentrations effectively, with relative prediction errors of +/- 15% and +/- 10% respectively.

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

    Science.gov (United States)

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

    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 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 for the

  2. Integrating mechanistic and empirical model projections to assess climate impacts on tree species distributions in northwestern North America.

    Science.gov (United States)

    Case, Michael J; Lawler, Joshua J

    2017-05-01

    Empirical and mechanistic models have both been used to assess the potential impacts of climate change on species distributions, and each modeling approach has its strengths and weaknesses. Here, we demonstrate an approach to projecting climate-driven changes in species distributions that draws on both empirical and mechanistic models. We combined projections from a dynamic global vegetation model (DGVM) that simulates the distributions of biomes based on basic plant functional types with projections from empirical climatic niche models for six tree species in northwestern North America. These integrated model outputs incorporate important biological processes, such as competition, physiological responses of plants to changes in atmospheric CO2 concentrations, and fire, as well as what are likely to be species-specific climatic constraints. We compared the integrated projections to projections from the empirical climatic niche models alone. Overall, our integrated model outputs projected a greater climate-driven loss of potentially suitable environmental space than did the empirical climatic niche model outputs alone for the majority of modeled species. Our results also show that refining species distributions with DGVM outputs had large effects on the geographic locations of suitable habitat. We demonstrate one approach to integrating the outputs of mechanistic and empirical niche models to produce bioclimatic projections. But perhaps more importantly, our study reveals the potential for empirical climatic niche models to over-predict suitable environmental space under future climatic conditions. © 2016 John Wiley & Sons Ltd.

  3. 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.

  4. Development of an invasive species distribution model with fine-resolution remote sensing

    Science.gov (United States)

    Diao, Chunyuan; Wang, Le

    2014-08-01

    Saltcedar (Tamarix spp.) is recognized as one of the most aggressively invasive species throughout the Western United States. Mapping its suitable habitat is of paramount importance to effective management, and thus, becomes a high priority for conservation practitioners. In previous studies, species distribution models (SDMs) have been applied to predicting the suitable habitats of saltcedar at national scale, but at coarser spatial resolution (1 km). Although such studies achieved some success, they are lacking of capability to accommodate fine-scale resolution environmental variables, and therefore, fail to uncover detailed spatial pattern of habitats. The objective of this study was to develop a remote sensing driven SDM so as to characterize suitable habitats of saltcedar at very fine spatial scale (30 m). We exploited several fine-scale environmental predictors through remote sensing images, and utilized the logistic regression model to analyze the species-habitat relationship by identifying influential factors with subset selection criteria. We also incorporated the spatial autocorrelation with regression kriging method. Our results indicated that the model incorporating spatial autocorrelation achieved a higher accuracy than that of regression only model. Among 10 environmental variables, the distance to the river and the phenological attributes summarized by the harmonic analysis were regarded as the most significant in predicting the invasive potential of saltcedar. We conclude that remote sensing driven SDM has potential to identify the suitable habitat of saltcedar at a fine scale and locate appropriate areas at high risk of saltcedar infestation, which could benefit the early control and proactive management strategies to a large extent.

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

    National Research Council Canada - National Science Library

    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...

  6. Updating Known Distribution Models for Forecasting Climate Change Impact on Endangered Species: e65462

    National Research Council Canada - National Science Library

    Antonio-Román Muñoz; Ana Luz Márquez; Raimundo Real

    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...

  7. Evaluation of Species Distribution Model Algorithms For Fine-Scale Container Breeding Mosquito Risk Prediction

    Science.gov (United States)

    Khatchikian, C.; Sangermano, F.; Kendell, D.; Livdahl, T.

    2010-01-01

    The present work evaluates the use of species distribution model (SDM) algorithms to classify high density of small container Aedes mosquitoes at a fine scale, in the Bermuda islands. Weekly ovitrap data collected by the Health Department of Bermuda (UK) for the years 2006 and 2007 were used for the models. The models evaluated included the following algorithms: Bioclim, Domain, GARP, logistic regression, and MaxEnt. Models were evaluated according to performance and robustness. The area Receiver Operating Characteristic (ROC) curve was used to evaluate each model’s performance, and robustness was assessed considering the spatial correlation between classification risks for the two datasets. Relative to the other algorithms, logistic regression was the best model for classifying high risk areas, and the maximum entropy approach (MaxEnt) presented the second best performance. We report the importance of covariables for these two models, and discuss the utility of SDMs for vector control efforts and the potential for the development of scripts that automate the task of creating risk assessment maps. PMID:21198711

  8. A model for habitat selection and species distribution derived from central place foraging theory.

    Science.gov (United States)

    Olsson, Ola; Bolin, Arvid

    2014-06-01

    We have developed a habitat selection model based on central place foraging theory. An individual's decision to include a patch in its habitat depends on the marginal fitness contribution of that patch, which is characterized by its quality and distance to the central place. The essence of the model we have developed is a fitness isocline which is a function of patch quality and travel time to the patch. It has two parameters: the maximum travel distance to a patch of infinite quality and a coefficient that appropriately scales quality by travel time. Patches falling below the isocline will have positive marginal fitness values and should be included in the habitat. The maximum travel distance depends on the availability and quality of patches, as well as on the forager's life history, whereas the scaling parameter mostly depends on life history properties. Using the model, we derived a landscape quality metric (which can be thought of as a connectivity measure) that sums the values of available habitat in the landscape around a central place. We then fitted the two parameters to foraging data on breeding white storks (Ciconia ciconia) and estimated landscape quality, which correlated strongly with reproductive success. Landscape quality was then calculated for a larger region where re-introduction of the species is currently going on in order to demonstrate how this model can also be regarded as a species distribution model. In conclusion, we have built a general habitat selection model for central place foragers and a novel way of estimating landscape quality based on a behaviorally scaled connectivity metric.

  9. 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

  10. 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

  11. Testing Three Species Distribution Modelling Strategies to Define Fish Assemblage Reference Conditions for Stream Bioassessment and Related Applications.

    Science.gov (United States)

    Rose, Peter M; Kennard, Mark J; Moffatt, David B; Sheldon, Fran; Butler, Gavin L

    2016-01-01

    Species distribution models are widely used for stream bioassessment, estimating changes in habitat suitability and identifying conservation priorities. We tested the accuracy of three modelling strategies (single species ensemble, multi-species response and community classification models) to predict fish assemblages at reference stream segments in coastal subtropical Australia. We aimed to evaluate each modelling strategy for consistency of predictor variable selection; determine which strategy is most suitable for stream bioassessment using fish indicators; and appraise which strategies best match other stream management applications. Five models, one single species ensemble, two multi-species response and two community classification models, were calibrated using fish species presence-absence data from 103 reference sites. Models were evaluated for generality and transferability through space and time using four external reference site datasets. Elevation and catchment slope were consistently identified as key correlates of fish assemblage composition among models. The community classification models had high omission error rates and contributed fewer taxa to the 'expected' component of the taxonomic completeness (O/E50) index than the other strategies. This potentially decreases the model sensitivity for site impact assessment. The ensemble model accurately and precisely modelled O/E50 for the training data, but produced biased predictions for the external datasets. The multi-species response models afforded relatively high accuracy and precision coupled with low bias across external datasets and had lower taxa omission rates than the community classification models. They inherently included rare, but predictable species while excluding species that were poorly modelled among all strategies. We suggest that the multi-species response modelling strategy is most suited to bioassessment using freshwater fish assemblages in our study area. At the species level

  12. Modelling diameter distributions of two-cohort forest stands with various proportions of dominant species: a two-component mixture model approach.

    Science.gov (United States)

    Rafal Podlaski; Francis Roesch

    2014-01-01

    In recent years finite-mixture models have been employed to approximate and model empirical diameter at breast height (DBH) distributions. We used two-component mixtures of either the Weibull distribution or the gamma distribution for describing the DBH distributions of mixed-species, two-cohort forest stands, to analyse the relationships between the DBH components,...

  13. Species Distribution Modeling between Abies koreana and Abies nephrolepis According to the RCP Scenarios in South Korea

    Science.gov (United States)

    Lee, S. G.; Kim, I. S.; Lee, W. K.; Kwon, H. J.; Byeon, J. G.; Yun, J. E.

    2016-12-01

    Vulnerable plant that includes species in crisis of extinction is shown by environment, competition between various species. The climate is one of the main factor that affect to the plant distribution. The most essential particular to make species distribution model is distribution data, and secondly environmental factors. 179 taxon plant classified according to the distribution, it consist of characteristic and regional distribution criteria. In case of climate data, 1960-1990 period made by World Clim Data is applied which has 0.86㎢ spatial resolution. It separates temperature and precipitation factor. To predict potential distribution, Maxent(Maximum Entropy Model) is applied that is widely known as suitable model in case of presence distributional data only. Among the target species, Abies koreana and Abies nephrolepis have no clearly key to identify, so their differences of distribution and environmental fator information could act useful. In order to know the distinction according to the classifying species, Abies koreana and Abies nephrolepis are typically selected. Abies koreana distributes at high mountain in Southern part of Korean Peninsula, otherwise Abies nephrolepis is at high mountain in from Middle latitude(over the 37°) in South Korea. These species has been the center of controversy recently, because the classification key of these species is not scientifically clear yet. In this perspective these species predicted potential distribution depend on whether these are same species or not. In the result of considering these species are same, entire predicted distribution area is wider, especially Jiri-san mountain(latitude : 35°) which is the highest latitude of the Abies koreana distributed point. On the other side, result of considering different species is shown that Abies koreana could climatically survive near by Soerak-san mountain(latitude : 37°), but Abies nephrolepis could not live in Halla-san mountan(33°) in Jeju-island which is the

  14. Modelling both dominance and species distribution provides a more complete picture of changes to mangrove ecosystems under climate change.

    Science.gov (United States)

    Crase, Beth; Vesk, Peter A; Liedloff, Adam; Wintle, Brendan A

    2015-08-01

    Dominant species influence the composition and abundance of other species present in ecosystems. However, forecasts of distributional change under future climates have predominantly focused on changes in species distribution and ignored possible changes in spatial and temporal patterns of dominance. We develop forecasts of spatial changes for the distribution of species dominance, defined in terms of basal area, and for species occurrence, in response to sea level rise for three tree taxa within an extensive mangrove ecosystem in northern Australia. Three new metrics are provided, indicating the area expected to be suitable under future conditions (Eoccupied ), the instability of suitable area (Einstability ) and the overlap between the current and future spatial distribution (Eoverlap ). The current dominance and occurrence were modelled in relation to a set of environmental variables using boosted regression tree (BRT) models, under two scenarios of seedling establishment: unrestricted and highly restricted. While forecasts of spatial change were qualitatively similar for species occurrence and dominance, the models of species dominance exhibited higher metrics of model fit and predictive performance, and the spatial pattern of future dominance was less similar to the current pattern than was the case for the distributions of species occurrence. This highlights the possibility of greater changes in the spatial patterning of mangrove tree species dominance under future sea level rise. Under the restricted seedling establishment scenario, the area occupied by or dominated by a species declined between 42.1% and 93.8%, while for unrestricted seedling establishment, the area suitable for dominance or occurrence of each species varied from a decline of 68.4% to an expansion of 99.5%. As changes in the spatial patterning of dominance are likely to cause a cascade of effects throughout the ecosystem, forecasting spatial changes in dominance provides new and

  15. 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 includin

  16. Ecological risk assessment of nonylphenol in coastal waters of China based on species sensitivity distribution model.

    Science.gov (United States)

    Gao, Pei; Li, Zhengyan; Gibson, Mark; Gao, Huiwang

    2014-06-01

    Nonylphenol (NP) is an endocrine disruptor and causes feminization and carcinogenesis in various organisms. Consequently, the environmental distribution and ecological risks of NP have received wide concern. China accounts for approximately 10% of the total NP usage in the world, but the water quality criteria of NP have not been established in China and the ecological risks of this pollutant cannot be properly assessed. This study thus aims to determine the predicted no effect concentration (PNEC) of NP and to assess the ecological risks of NP in coastal waters of China with the PNEC as water quality criteria. To obtain the HC5 (hazardous concentration for 5% of biological species) and PNEC estimates, the species sensitivity distributions (SSDs) models were built with chronic toxicity data of NP on aquatic organisms screened from the US Environmental Protection Agency (USEPA) ECOTOX database. The results showed that the PNEC for NP in freshwater and seawater was 0.48 μg L(-1) and 0.28 μg L(-1), respectively. The RQ (risk quotient) values of NP in coastal waters of China ranged from 0.01 to 69.7. About 60% of the reported areas showed a high ecological risk with an RQ value ≥ 1.00. NP therefore exists ubiquitously in coastal waters of China and it poses various risks to aquatic ecosystems in the country. This study demonstrates that the SSD methodology can provide a feasible tool for the establishment of water quality criteria for emergent new pollutants when sufficient toxicity data is available. Copyright © 2013 Elsevier Ltd. All rights reserved.

  17. 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.

  18. 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

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

    Science.gov (United States)

    Richmond, Orien M W; McEntee, Jay P; Hijmans, Robert J; Brashares, Justin S

    2010-09-22

    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 organisms in response

  20. Predicting the spatiotemporal distributions of marine fish species utilizing earth system data in a maximum entropy modeling framework

    Science.gov (United States)

    Wang, L.; Kerr, L. A.; Bridger, E.

    2016-12-01

    Changes in species distributions have been widely associated with climate change. Understanding how ocean conditions influence marine fish distributions is critical for elucidating the role of climate in ecosystem change and forecasting how fish may be distributed in the future. Species distribution models (SDMs) can enable estimation of the likelihood of encountering species in space or time as a function of environmental conditions. Traditional SDMs are applied to scientific-survey data that include both presences and absences. Maximum entropy (MaxEnt) models are promising tools as they can be applied to presence-only data, such as those collected from fisheries or citizen science programs. We used MaxEnt to relate the occurrence records of marine fish species (e.g. Atlantic herring, Atlantic mackerel, and butterfish) from NOAA Northeast Fisheries Observer Program to environmental conditions. Environmental variables from earth system data, such as sea surface temperature (SST), sea bottom temperature (SBT), Chlorophyll-a, bathymetry, North Atlantic oscillation (NAO), and Atlantic multidecadal oscillation (AMO), were matched with species occurrence for MaxEnt modeling the fish distributions in Northeast Shelf area. We developed habitat suitability maps for these species, and assessed the relative influence of environmental factors on their distributions. Overall, SST and Chlorophyll-a had greatest influence on their monthly distributions, with bathymetry and SBT having moderate influence and climate indices (NAO and AMO) having little influence. Across months, Atlantic herring distribution was most related to SST 10th percentile, and Atlantic mackerel and butterfish distributions were most related to previous month SST. The fish distributions were most affected by previous month Chlorophyll-a in summer months, which may indirectly indicate the accumulative impact of primary productivity. Results highlighted the importance of spatial and temporal scales when using

  1. Deriving the species richness distribution of Geotrupinae (Coleoptera: Scarabaeoidea) in Mexico from the overlap of individual model predictions.

    Science.gov (United States)

    Trotta-Moreu, Nuria; Lobo, Jorge M

    2010-02-01

    Predictions from individual distribution models for Mexican Geotrupinae species were overlaid to obtain a total species richness map for this group. A database (GEOMEX) that compiles available information from the literature and from several entomological collections was used. A Maximum Entropy method (MaxEnt) was applied to estimate the distribution of each species, taking into account 19 climatic variables as predictors. For each species, suitability values ranging from 0 to 100 were calculated for each grid cell on the map, and 21 different thresholds were used to convert these continuous suitability values into binary ones (presence-absence). By summing all of the individual binary maps, we generated a species richness prediction for each of the considered thresholds. The number of species and faunal composition thus predicted for each Mexican state were subsequently compared with those observed in a preselected set of well-surveyed states. Our results indicate that the sum of individual predictions tends to overestimate species richness but that the selection of an appropriate threshold can reduce this bias. Even under the most optimistic prediction threshold, the mean species richness error is 61% of the observed species richness, with commission errors being significantly more common than omission errors (71 +/- 29 versus 18 +/- 10%). The estimated distribution of Geotrupinae species richness in Mexico in discussed, although our conclusions are preliminary and contingent on the scarce and probably biased available data.

  2. Modeling the Potential Distribution of Picea chihuahuana Martínez, an Endangered Species at the Sierra Madre Occidental, Mexico

    Directory of Open Access Journals (Sweden)

    Victor Aguilar-Soto

    2015-03-01

    Full Text Available Species distribution models (SDMs help identify areas for the development of populations or communities to prevent extinctions, especially in the face of the global environmental change. This study modeled the potential distribution of the tree Picea chihuahuana Martínez, a species in danger of extinction, using the maximum entropy modeling method (MaxEnt at three scales: local, state and national. We used a total of 38 presence data from the Sierra Madre Occidental. At the local scale, we compared MaxEnt with the reclassification and overlay method integrated in a geographic information system. MaxEnt generated maps with a high predictive capability (AUC > 0.97. The distribution of P. chihuahuana is defined by vegetation type and minimum temperature at national and state scales. At the local scale, both models calculated similar areas for the potential distribution of the species; the variables that better defined the species distribution were vegetation type, aspect and distance to water flows. Populations of P. chihuahuana have always been small, but our results show potential habitat greater than the area of the actual distribution. These results provide an insight into the availability of areas suitable for the species’ regeneration, possibly through assisted colonization.

  3. Combining citizen science species distribution models and stable isotopes reveals migratory connectivity in the secretive Virginia rail

    Science.gov (United States)

    Fournier, Auriel M. V.; Sullivan, Alexis R.; Bump, Joseph K.; Perkins, Marie; Shieldcastle, Mark C.; King, Sammy L.

    2017-01-01

    Stable hydrogen isotope (δD) methods for tracking animal movement are widely used yet often produce low resolution assignments. Incorporating prior knowledge of abundance, distribution or movement patterns can ameliorate this limitation, but data are lacking for most species. We demonstrate how observations reported by citizen scientists can be used to develop robust estimates of species distributions and to constrain δD assignments.We developed a Bayesian framework to refine isotopic estimates of migrant animal origins conditional on species distribution models constructed from citizen scientist observations. To illustrate this approach, we analysed the migratory connectivity of the Virginia rail Rallus limicola, a secretive and declining migratory game bird in North America.Citizen science observations enabled both estimation of sampling bias and construction of bias-corrected species distribution models. Conditioning δD assignments on these species distribution models yielded comparably high-resolution assignments.Most Virginia rails wintering across five Gulf Coast sites spent the previous summer near the Great Lakes, although a considerable minority originated from the Chesapeake Bay watershed or Prairie Pothole region of North Dakota. Conversely, the majority of migrating Virginia rails from a site in the Great Lakes most likely spent the previous winter on the Gulf Coast between Texas and Louisiana.Synthesis and applications. In this analysis, Virginia rail migratory connectivity does not fully correspond to the administrative flyways used to manage migratory birds. This example demonstrates that with the increasing availability of citizen science data to create species distribution models, our framework can produce high-resolution estimates of migratory connectivity for many animals, including cryptic species. Empirical evidence of links between seasonal habitats will help enable effective habitat management, hunting quotas and population monitoring and

  4. Species Distribution Models for Crop Pollination: A Modelling Framework Applied to Great Britain

    NARCIS (Netherlands)

    Polce, C.; Termansen, M.; Aguirre-Gutiérrez, J.; Boatman, N.D.; Budge, G.E.; Crowe, A.; Garratt, M.P.; Pietravalle, S.; Potts, S.G.; Ramirez, J. A.; Somerwill, K.E.; Biesmeijer, J.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

  5. Species Distribution Models for Crop Pollination: A Modelling Framework Applied to Great Britain

    NARCIS (Netherlands)

    C. Polce; M. Termansen; J. Aguirre-Gutiérrez; N.D. Boatman; G.E. Budge; A. Crowe; M.P. Garratt; S. Pietravalle; S.G. Potts; J. A. Ramirez; K.E. Somerwill; J.C. Biesmeijer

    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 availabilit

  6. 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

    2017-01-01

    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.

  7. Species Distribution Model using Hyperspectral Data Application in Peatland, Central Kalimantan

    Science.gov (United States)

    Dayuf Jusuf, Muhammad

    2016-11-01

    Tumih / Parepat (Combretocarpus-rotundatus Mig. Dencer) of the family Anisophylleaceae and Meranti (Shorea Belangerang, ShoreaTeysmanniana Dyer ex. Brandis) of Dipterocarpaceae are groups of species of vegetation that is modeled for the designation of its spread. Pioneer species are predicted as an indicator of ecosystem restoration succession of wet tropical peatland characteristic (unique) and very susceptible (fragile) in an endemic Sundaland hotspot. Projected climate change and conservation planning a topic of heated discussion. the analysis of alternative approaches and the development of a combination of search algorithm projection models within the fabric of the diffusion of the species to attain this through a geospatial information system technology. Model approach used to work out problems in research on this vegetation species level based machine learning is a method (hybrid). which is a combination of wavelet and neural network. Often the approach to field data into general use in the management of natural resources and biodiversity assessment. Expression of the hybrid models provides encouraging results. to decide the classification of the species Tumih / Parepat and Meranti through mapping of vegetation species that are backed up by the pattern of the spectral curve of the field spectrometer.

  8. Species distribution modelling for Rhipicephalus microplus (Acari: Ixodidae) in Benin, West Africa: comparing datasets and modelling algorithms.

    Science.gov (United States)

    De Clercq, E M; Leta, S; Estrada-Peña, A; Madder, M; Adehan, S; Vanwambeke, S O

    2015-01-01

    Rhipicephalus microplus is one of the most widely distributed and economically important ticks, transmitting Babesia bigemina, B. bovis and Anaplasma marginale. It was recently introduced to West Africa on live animals originating from Brazil. Knowing the precise environmental suitability for the tick would allow veterinary health officials to draft vector control strategies for different regions of the country. To test the performance of modelling algorithms and different sets of environmental explanatory variables, species distribution models for this tick species in Benin were developed using generalized linear models, linear discriminant analysis and random forests. The training data for these models were a dataset containing reported absence or presence in 104 farms, randomly selected across Benin. These farms were sampled at the end of the rainy season, which corresponds with an annual peak in tick abundance. Two environmental datasets for the country of Benin were compared: one based on interpolated climate data (WorldClim) and one based on remotely sensed images (MODIS). The pixel size for both environmental datasets was 1 km. Highly suitable areas occurred mainly along the warmer and humid coast extending northwards to central Benin. The northern hot and drier areas were found to be unsuitable. The models developed and tested on data from the entire country were generally found to perform well, having an AUC value greater than 0.92. Although statistically significant, only small differences in accuracy measures were found between the modelling algorithms, or between the environmental datasets. The resulting risk maps differed nonetheless. Models based on interpolated climate suggested gradual variations in habitat suitability, while those based on remotely sensed data indicated a sharper contrast between suitable and unsuitable areas, and a patchy distribution of the suitable areas. Remotely sensed data yielded more spatial detail in the predictions. When

  9. 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

    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....... 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...

  10. Comparison of Geostatistical Methods to Determine the Best Bioclimatic Data Interpolation Method for Modelling Species Distribution in Central Iran

    Directory of Open Access Journals (Sweden)

    R. Khosravi

    2014-09-01

    Full Text Available Climatic change can impose physiological constraints on species and can therefore affect species distribution. Bioclimatic predictors, including annual trends, regimes, thresholds and bio-limiting factors are the most important independent variables in species distribution models. Water and temperature are the most limiting factors in arid ecosystem in central Iran. Therefore, mapping of climatic factors in species distribution models seems necessary. In this study, we describe the extraction of 20 important bioclimatic variables from climatic data and compare different interpolation methods including inverse distance weighting, ordinary kriging, kriging with external trend, cokriging, and five radial basis functions. Normal climatic data (1950-2010 in 26 synoptic stations in central Iran were used to extract bioclimatic data. Spatial correlation, heterogeneity and trend in data were evaluated using three models of semivariogram (spherical, exponential and Gaussian and the best model was selected using cross validation. The optimum model for bioclimatic variables was assessed based on the root mean square error and mean bias error. Exponential model was considered to be the best fit mathematical model to empirical semivariogram. IDW and cokriging were recognised as the best interpolating methods for average annual temperature and annual precipitation, respectively. Use of elevation as an auxiliary variable appeared to be necessary for optimizing interpolation methods of climatic and bioclimatic variables.

  11. A comparison of absolute performance of different correlative and mechanistic species distribution models in an independent area.

    Science.gov (United States)

    Shabani, Farzin; Kumar, Lalit; Ahmadi, Mohsen

    2016-08-01

    To investigate the comparative abilities of six different bioclimatic models in an independent area, utilizing the distribution of eight different species available at a global scale and in Australia. Global scale and Australia. We tested a variety of bioclimatic models for eight different plant species employing five discriminatory correlative species distribution models (SDMs) including Generalized Linear Model (GLM), MaxEnt, Random Forest (RF), Boosted Regression Tree (BRT), Bioclim, together with CLIMEX (CL) as a mechanistic niche model. These models were fitted using a training dataset of available global data, but with the exclusion of Australian locations. The capabilities of these techniques in projecting suitable climate, based on independent records for these species in Australia, were compared. Thus, Australia is not used to calibrate the models and therefore it is as an independent area regarding geographic locations. To assess and compare performance, we utilized the area under the receiver operating characteristic (ROC) curves (AUC), true skill statistic (TSS), and fractional predicted areas for all SDMs. In addition, we assessed satisfactory agreements between the outputs of the six different bioclimatic models, for all eight species in Australia. The modeling method impacted on potential distribution predictions under current climate. However, the utilization of sensitivity and the fractional predicted areas showed that GLM, MaxEnt, Bioclim, and CL had the highest sensitivity for Australian climate conditions. Bioclim calculated the highest fractional predicted area of an independent area, while RF and BRT were poor. For many applications, it is difficult to decide which bioclimatic model to use. This research shows that variable results are obtained using different SDMs in an independent area. This research also shows that the SDMs produce different results for different species; for example, Bioclim may not be good for one species but works better

  12. 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.

  13. Integrating phylogeography and species distribution models: cryptic distributional responses to past climate change in an endemic rodent from the central Chile hotspot.

    Science.gov (United States)

    Gutiérrez-Tapia, Pablo; Palma, R Eduardo

    2016-06-01

    Biodiversity losses under the species level may have been severely underestimated in future global climate change scenarios. Therefore, it is important to characterize the diversity units at this level, as well as to understand their ecological responses to climatic forcings. We have chosen an endemic rodent from a highly endangered ecogeographic area as a model to look for distributional responses below the species level: Phyllotis darwini. The central Chile biodiversity hotspot: This area harbours a high number of endemic species, and it is known to have experienced vegetational displacements between two mountain systems during and after the Last Glacial Maximum. We have characterized cryptic lineages inside P. darwini in a classic phylogeographic approach; those intraspecific lineages were considered as relevant units to construct distribution models at Last Glacial Maximum and at present, as border climatic conditions. Differences in distribution between border conditions for each lineage were interpreted as distributional responses to post-glacial climate change. The species is composed of two major phylogroups: one of them has a broad distribution mainly across the valley but also in mountain ranges, whereas the other displays a disjunct distribution across both mountain ranges and always above 1500 m. The lineage distribution model under LGM climatic conditions suggests that both lineages were co-distributed in the southern portion of P. darwini's current geographic range, mainly at the valley and at the coast. Present distribution of lineages in P. darwini is the consequence of a cryptic distributional response to climate change after LGM: postglacial northward colonization, with strict altitudinal segregation of both phylogroups.

  14. 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...

  15. 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).

  16. A differential equation for the asymptotic fitness distribution in the Bak-Sneppen model with five species.

    Science.gov (United States)

    Schlemm, Eckhard

    2015-09-01

    The Bak-Sneppen model is an abstract representation of a biological system that evolves according to the Darwinian principles of random mutation and selection. The species in the system are characterized by a numerical fitness value between zero and one. We show that in the case of five species the steady-state fitness distribution can be obtained as a solution to a linear differential equation of order five with hypergeometric coefficients. Similar representations for the asymptotic fitness distribution in larger systems may help pave the way towards a resolution of the question of whether or not, in the limit of infinitely many species, the fitness is asymptotically uniformly distributed on the interval [fc, 1] with fc ≳ 2/3. Copyright © 2015 Elsevier Inc. All rights reserved.

  17. 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

  18. 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.

  19. 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.

  20. 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.

  1. 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.

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

    Directory of Open Access Journals (Sweden)

    Lorena Ribeiro de A Carneiro

    Full Text Available Species-distribution models (SDM are tools with potential to inform environmental-impact studies (EIA. However, they are not always appropriate and may result in improper and expensive mitigation and compensation if their limitations are not understood by decision makers. Here, we examine the use of SDM for frogs that were used in impact assessment using data obtained from the EIA of a hydroelectric project located in the Amazon Basin in Brazil. The results show that lack of knowledge of species distributions limits the appropriate use of SDM in the Amazon region for most target species. Because most of these targets are newly described and their distributions poorly known, data about their distributions are insufficient to be effectively used in SDM. Surveys that are mandatory for the EIA are often conducted only near the area under assessment, and so models must extrapolate well beyond the sampled area to inform decisions made at much larger spatial scales, such as defining areas to be used to offset the negative effects of the projects. Using distributions of better-known species in simulations, we show that geographical-extrapolations based on limited information of species ranges often lead to spurious results. We conclude that the use of SDM as evidence to support project-licensing decisions in the Amazon requires much greater area sampling for impact studies, or, alternatively, integrated and comparative survey strategies, to improve biodiversity sampling. When more detailed distribution information is unavailable, SDM will produce results that generate uncertain and untestable decisions regarding impact assessment. In many cases, SDM is unlikely to be better than the use of expert opinion.

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

    Science.gov (United States)

    Carneiro, Lorena Ribeiro de A; Lima, Albertina P; Machado, Ricardo B; Magnusson, William E

    2016-01-01

    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.

  4. 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.

  5. Integrated species distribution models: combining presence-background data and site-occupancy data with imperfect detection

    Science.gov (United States)

    Koshkina, Vira; Wang, Yang; Gordon, Ascelin; Dorazio, Robert; White, Matthew; Stone, Lewi

    2017-01-01

    Two main sources of data for species distribution models (SDMs) are site-occupancy (SO) data from planned surveys, and presence-background (PB) data from opportunistic surveys and other sources. SO surveys give high quality data about presences and absences of the species in a particular area. However, due to their high cost, they often cover a smaller area relative to PB data, and are usually not representative of the geographic range of a species. In contrast, PB data is plentiful, covers a larger area, but is less reliable due to the lack of information on species absences, and is usually characterised by biased sampling. Here we present a new approach for species distribution modelling that integrates these two data types.We have used an inhomogeneous Poisson point process as the basis for constructing an integrated SDM that fits both PB and SO data simultaneously. It is the first implementation of an Integrated SO–PB Model which uses repeated survey occupancy data and also incorporates detection probability.The Integrated Model's performance was evaluated, using simulated data and compared to approaches using PB or SO data alone. It was found to be superior, improving the predictions of species spatial distributions, even when SO data is sparse and collected in a limited area. The Integrated Model was also found effective when environmental covariates were significantly correlated. Our method was demonstrated with real SO and PB data for the Yellow-bellied glider (Petaurus australis) in south-eastern Australia, with the predictive performance of the Integrated Model again found to be superior.PB models are known to produce biased estimates of species occupancy or abundance. The small sample size of SO datasets often results in poor out-of-sample predictions. Integrated models combine data from these two sources, providing superior predictions of species abundance compared to using either data source alone. Unlike conventional SDMs which have restrictive

  6. 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.

  7. 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.

  8. Combining physiological threshold knowledge to species distribution models is key to improving forecasts of the future niche for macroalgae.

    Science.gov (United States)

    Martínez, Brezo; Arenas, Francisco; Trilla, Alba; Viejo, Rosa M; Carreño, Francisco

    2015-04-01

    Species distribution models (SDM) are a useful tool for predicting species range shifts in response to global warming. However, they do not explore the mechanisms underlying biological processes, making it difficult to predict shifts outside the environmental gradient where the model was trained. In this study, we combine correlative SDMs and knowledge on physiological limits to provide more robust predictions. The thermal thresholds obtained in growth and survival experiments were used as proxies of the fundamental niches of two foundational marine macrophytes. The geographic projections of these species' distributions obtained using these thresholds and existing SDMs were similar in areas where the species are either absent-rare or frequent and where their potential and realized niches match, reaching consensus predictions. The cold-temperate foundational seaweed Himanthalia elongata was predicted to become extinct at its southern limit in northern Spain in response to global warming, whereas the occupancy of southern-lusitanic Bifurcaria bifurcata was expected to increase. Combined approaches such as this one may also highlight geographic areas where models disagree potentially due to biotic factors. Physiological thresholds alone tended to over-predict species prevalence, as they cannot identify absences in climatic conditions within the species' range of physiological tolerance or at the optima. Although SDMs tended to have higher sensitivity than threshold models, they may include regressions that do not reflect causal mechanisms, constraining their predictive power. We present a simple example of how combining correlative and mechanistic knowledge provides a rapid way to gain insight into a species' niche resulting in consistent predictions and highlighting potential sources of uncertainty in forecasted responses to climate change. © 2014 John Wiley & Sons Ltd.

  9. Survival and Stationary Distribution Analysis of a Stochastic Competitive Model of Three Species in a Polluted Environment.

    Science.gov (United States)

    Zhao, Yu; Yuan, Sanling; Ma, Junling

    2015-07-01

    In this paper, we develop and study a stochastic model for the competition of three species with a generalized dose-response function in a polluted environment. We first carry out the survival analysis and obtain sufficient conditions for the extinction, non-persistence, weak persistence in the mean, strong persistence in the mean and stochastic permanence. The threshold between weak persistence in the mean and extinction is established for each species. Then, using Hasminskii's methods and a Lyapunov function, we derive sufficient conditions for the existence of stationary distribution for each population. Numerical simulations are carried out to support our theoretical results, and some biological significance is presented.

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

    Directory of Open Access Journals (Sweden)

    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.

  12. 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.

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

    Science.gov (United States)

    Molloy, Shaun W; Davis, Robert A; van Etten, Eddie J B

    2016-01-01

    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 responses

  14. [Predicting the dispersal routes of alpine plant Pedicularis longiflora (Orobanchaceae) based on GIS and species distribution models].

    Science.gov (United States)

    Yu, Hai-In; Zhang, Yi-Li; Li, Shi-Cheng; Qi, Wei; Hu, Zhong-Jun

    2014-06-01

    Pedicularis longiflora experienced extensive populations' expansion in Quaternary, but the dispersal corridors were still unclear. According to the distribution patterns of haplotypes based on chloroplast DNA variation, the dispersal routes were predicted using species distribution models (MXENT) and the least-cost path method. Two possible dispersal routes from the southeastern part of Tibetan Plateau (TP) to interior were identified. The populations of East Himalayas-Hengduan Mountains region expanded to the western part of TP along with the Yarlung Zangbo River valley and the lower altitudes of the north slope of Himalayas. The expansion trend was also proved by SDMs based on two historical periods containing the Last Interglacial and the Last Glacial Maximum. In conclusion, identification of dispersal routes is significant to the evolutionary history of alpine plants and the protection of special species in TP.

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

    Institute of Scientific and Technical Information of China (English)

    M.Corrie SCHOEMAN; F.P.D.(Woody) COTTERILL; Peter J.TAYLOR; Ara MONADJEM

    2013-01-01

    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].

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

    Directory of Open Access Journals (Sweden)

    M. Corrie SCHOEMAN, F. P. D. (Woody COTTERILL, Peter J. TAYLOR, Ara MONADJEM

    2013-06-01

    Full Text Available We tested the prediction that at coarse spatial scales, variables associated with climate, energy, and productivity hypotheses should be better predictor(s of bat species richness than those associated with environmental heterogeneity. Distribution ranges of 64 bat species were estimated with niche-based models informed by 3629 verified museum specimens. The influence of environmental correlates on bat richness was assessed using ordinary least squares regression (OLS, simultaneous autoregressive models (SAR, conditional autoregressive models (CAR, spatial eigenvector-based filtering models (SEVM, and Classification and Regression Trees (CART. To test the assumption of stationarity, Geographically Weighted Regression (GWR was used. Bat species richness was highest in the eastern parts of southern Africa, particularly in central Zimbabwe and along the western border of Mozambique. We found support for the predictions of both the habitat heterogeneity and climate/productivity/ energy hypotheses, and as we expected, support varied among bat families and model selection. Richness patterns and predictors of Miniopteridae and Pteropodidae clearly differed from those of other bat families. Altitude range was the only independent variable that was sig­nificant in all models and it was most often the best predictor of bat richness. Standard coefficients of SAR and CAR models were similar to those of OLS models, while those of SEVM models differed. Although GWR indicated that the assumption of stationa­rity was violated, the CART analysis corroborated the findings of the curve-fitting models. Our results identify where additional data on current species ranges, and future conservation action and ecological work are needed [Current Zoology 59 (3: 279–293, 2013].

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

    Directory of Open Access Journals (Sweden)

    Irene D. Alabia

    2016-11-01

    Full Text Available The understanding of the spatio-temporal distributions of the species habitat in the marine environment is central to effectual resource management and conservation. Here, we examined the potential habitat distributions of Japanese common squid (Todarodes pacificus in the Sea of Japan during a four-year period. The seasonal patterns of preferential habitat were inferred from species distribution models, built using squid occurrences detected from night-time visible images and remotely-sensed environmental factors. The predicted squid habitat (i.e., areas with high habitat suitability revealed strong seasonal variability, characterized by a reduction of potential habitat, confined off of the southern part of the basin during the winter–spring period (December–May. Apparent expansion of preferential habitat occurred during summer–autumn months (June–November, concurrent with the formation of highly suitable habitat patches in certain regions of the Sea of Japan. These habitat distribution patterns were in response to changes in oceanographic conditions and synchronous with seasonal migration of squid. Moreover, the most important variables regulating the spatio-temporal patterns of suitable habitat were sea surface temperature, depth, sea surface height anomaly, and eddy kinetic energy. These variables could affect the habitat distributions through their impacts on growth and survival of squid, local nutrient transport, and the availability of favorable spawning and feeding grounds.

  18. 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.

  19. 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

  20. 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...... collected from the ecotoxicity database, (3) how to transform the acute toxicity data into chronic data, (4) how to best fit the toxicity data, (5) how to calculate the msPAF of multiple pollutants, and (6) how to determine the uncertainty of the SSD model”. In response to these questions, several...

  1. 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.

  2. 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...

  3. [Development and application of a multi-species water quality model for water distribution systems with EPANET-MSX].

    Science.gov (United States)

    Sun, Fu; Chen, Ji-ning; Zeng, Si-yu

    2008-12-01

    A conceptual multi-species water quality model for water distribution systems was developed on the basis of the toolkit of the EPANET-MSX software. The model divided the pipe segment into four compartments including pipe wall, biofilm, boundary layer and bulk liquid. The involved processes were substrate utilization and microbial growth, decay and inactivation of microorganisms, mass transfer of soluble components through the boundary layer, adsorption and desorption of particular components between bulk liquid and biofilm, oxidation and halogenation of organic matter by residual chlorine, and chlorine consumption by pipe wall. The fifteen simulated variables included the seven common variables both in the biofilm and in the bulk liquid, i.e. soluble organic matter, particular organic matter, ammonia nitrogen, residual chlorine, heterotrophic bacteria, autotrophic bacteria and inert solids, as well as biofilm thickness on the pipe wall. The model was validated against the data from a series of pilot experiments, and the simulation accuracy for residual chlorine and turbidity were 0.1 mg/L and 0.3 NTU respectively. A case study showed that the model could reasonably reflect the dynamic variation of residual chlorine and turbidity in the studied water distribution system, while Monte Carlo simulation, taking into account both the variability of finished water from the waterworks and the uncertainties of model parameters, could be performed to assess the violation risk of water quality in the water distribution system.

  4. Predicting the spatial and temporal distributions of marine fish species utilizing earth system data in a MaxEnt model framework

    Science.gov (United States)

    Wang, L.; Kerr, L. A.; Bridger, E.

    2016-02-01

    Changes in species distributions have been widely associated with climate change. Understanding how ocean temperatures influence species distributions is critical for elucidating the role of climate in ecosystem change as well as for forecasting how species may be distributed in the future. As such, species distribution modeling (SDM) is increasingly useful in marine ecosystems research, as it can enable estimation of the likelihood of encountering marine fish in space or time as a function of a set of environmental and ecosystem conditions. Many traditional SDM approaches are applied to species data collected through standardized methods that include both presence and absence records, but are incapable of using presence-only data, such as those collected from fisheries or through citizen science programs. Maximum entropy (MaxEnt) models provide promising tools as they can predict species distributions from incomplete information (presence-only data). We developed a MaxEnt framework to relate the occurrence records of several marine fish species (e.g. Atlantic herring, Atlantic mackerel, and butterfish) to environmental conditions. Environmental variables derived from remote sensing, such as monthly average sea surface temperature (SST), are matched with fish species data, and model results indicate the relative occurrence rate of the species as a function of the environmental variables. The results can be used to provide hindcasts of where species might have been in the past in relation to historical environmental conditions, nowcasts in relation to current conditions, and forecasts of future species distributions. In this presentation, we will assess the relative influence of several environmental factors on marine fish species distributions, and evaluate the effects of data coverage on these presence-only models. We will also discuss how the information from species distribution forecasts can support climate adaptation planning in marine fisheries.

  5. 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

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

    Science.gov (United States)

    Naujokaitis-Lewis, Ilona; Curtis, Janelle M R

    2016-01-01

    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 attributes along

  7. Modelling diameter distributions of two-cohort forest stands with various proportions of dominant species: a two-component mixture model approach.

    Science.gov (United States)

    Podlaski, Rafał; Roesch, Francis A

    2014-03-01

    In recent years finite-mixture models have been employed to approximate and model empirical diameter at breast height (DBH) distributions. We used two-component mixtures of either the Weibull distribution or the gamma distribution for describing the DBH distributions of mixed-species, two-cohort forest stands, to analyse the relationships between the DBH components, age cohorts and dominant species, and to assess the significance of differences between the mixture distributions and the kernel density estimates. The data consisted of plots from the Świętokrzyski National Park (Central Poland) and areas close to and including the North Carolina section of the Great Smoky Mountains National Park (USA; southern Appalachians). The fit of the mixture Weibull model to empirical DBH distributions had a precision similar to that of the mixture gamma model, slightly less accurate estimate was obtained with the kernel density estimator. Generally, in the two-cohort, two-storied, multi-species stands in the southern Appalachians, the two-component DBH structure was associated with age cohort and dominant species. The 1st DBH component of the mixture model was associated with the 1st dominant species sp1 occurred in young age cohort (e.g., sweetgum, eastern hemlock); and to a lesser degree, the 2nd DBH component was associated with the 2nd dominant species sp2 occurred in old age cohort (e.g., loblolly pine, red maple). In two-cohort, partly multilayered, stands in the Świętokrzyski National Park, the DBH structure was usually associated with only age cohorts (two dominant species often occurred in both young and old age cohorts). When empirical DBH distributions representing stands of complex structure are approximated using mixture models, the convergence of the estimation process is often significantly dependent on the starting strategies. Depending on the number of DBHs measured, three methods for choosing the initial values are recommended: min.k/max.k, 0.5/1.5/mean

  8. 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.

  9. 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.

  10. 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

  11. Modelling the Species Distribution of Flat-Headed Cats (Prionailurus planiceps), an Endangered South-East Asian Small Felid

    Science.gov (United States)

    Hearn, Andrew J.; Hesse, Deike; Mohamed, Azlan; Traeholdt, Carl; Cheyne, Susan M.; Sunarto, Sunarto; Jayasilan, Mohd-Azlan; Ross, Joanna; Shapiro, Aurélie C.; Sebastian, Anthony; Dech, Stefan; Breitenmoser, Christine; Sanderson, Jim; Duckworth, J. W.; Hofer, Heribert

    2010-01-01

    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 efforts for

  12. Rarity in large data sets: Singletons, model values and the location of the species abundance distribution

    NARCIS (Netherlands)

    Straatsma, G.; Egli, S.

    2012-01-01

    Species abundance data in 12 large data sets, holding 10 × 103 to 125 × 106 individuals in 350 to 10 × 103 samples, were studied. Samples and subsets, for instance the summarized data of samples over years, and whole sets were analysed. Two methods of the binning of data, assigning abundance values

  13. Rarity in large data sets: Singletons, model values and the location of the species abundance distribution

    NARCIS (Netherlands)

    Straatsma, G.; Egli, S.

    2012-01-01

    Species abundance data in 12 large data sets, holding 10 × 103 to 125 × 106 individuals in 350 to 10 × 103 samples, were studied. Samples and subsets, for instance the summarized data of samples over years, and whole sets were analysed. Two methods of the binning of data, assigning abundance values

  14. 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.

  15. Using species distribution models to optimize vector control in the framework of the tsetse eradication campaign in Senegal.

    Science.gov (United States)

    Dicko, Ahmadou H; Lancelot, Renaud; Seck, Momar T; Guerrini, Laure; Sall, Baba; Lo, Mbargou; Vreysen, Marc J B; Lefrançois, Thierry; Fonta, William M; Peck, Steven L; Bouyer, Jérémy

    2014-07-15

    Tsetse flies are vectors of human and animal trypanosomoses in sub-Saharan Africa and are the target of the Pan African Tsetse and Trypanosomiasis Eradication Campaign (PATTEC). Glossina palpalis gambiensis (Diptera: Glossinidae) is a riverine species that is still present as an isolated metapopulation in the Niayes area of Senegal. It is targeted by a national eradication campaign combining a population reduction phase based on insecticide-treated targets (ITTs) and cattle and an eradication phase based on the sterile insect technique. In this study, we used species distribution models to optimize control operations. We compared the probability of the presence of G. p. gambiensis and habitat suitability using a regularized logistic regression and Maxent, respectively. Both models performed well, with an area under the curve of 0.89 and 0.92, respectively. Only the Maxent model predicted an expert-based classification of landscapes correctly. Maxent predictions were therefore used throughout the eradication campaign in the Niayes to make control operations more efficient in terms of deployment of ITTs, release density of sterile males, and location of monitoring traps used to assess program progress. We discuss how the models' results informed about the particular ecology of tsetse in the target area. Maxent predictions allowed optimizing efficiency and cost within our project, and might be useful for other tsetse control campaigns in the framework of the PATTEC and, more generally, other vector or insect pest control programs.

  16. 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.

  17. Evaluating Connectivity for two mid-sized mammals Across Riparian Corridors using Wildlife Crossing Monitoring and Species Distribution Modeling

    Science.gov (United States)

    Jeong, S.

    2016-12-01

    The movement of wildlife can be constrained by river renovation projects owing to the presence of artificial structures. This study evaluates lateral connectivity, the ability to cross from habitat on one side of the river, through riparian vegetation, embankments, and the river to the other, of two mammal species, the leopard cat (Felis bengalensis euptilura) and water deer (Hydropotes inermis). We used 34 months of monitoring on 250 m stream segments on the Seom river, in South Korea to model the lateral connectivity of the stream between suitable habitats on either side of the steam. Habitat suitability within the landscape was determined using species distribution modelingand was used to determine where we thought the animals would want to pass across the river. We compared the predicted crossing locations to observed crossings.We assessed lateral connectivity suitability with maximum entropy and logistic regression models, and species' presences detected from snow tracking, heat sensor cameras, and scat or other signs, as well as landscape variables. Leopard cats prefer upland forest, while water deer prefer the forest edge and riparian corridor. For both target species, the best riparian habitats were characterized by the presence of vegetation cover on the embankment and by at least one side of an embankment being adjacent to farmland or forest cover. The lateral connectivity for the two target species showed different requirements. Water deer cross through large culverts with an openness ratio of 0.7 or under bridges, whereas leopard cats utilized drainage pipes and culvert boxes with a much smaller openness ratio. Stream reaches located close to a river tributary had the highest connectivity values, and areas modeled as good habitat for both species thatlink watershed and riparian habitats showed high connectivity values. Artifacts such as steep banks, concrete embankments, and adjacent roads were found to degrade the lateral connectivity of wildlife

  18. A sampling and analytical approach to develop spatial distribution models for sagebrush-associated species: Chapter 4

    Science.gov (United States)

    Leu, Matthias; Hanser, Steven E.; Aldridge, Cameron L.; Nielsen, Scott E.; Cade, Brian S.; Knick, Steven T.; Hanser, Steven E.; Leu, Matthias; Knick, Steven T.; Aldridge, Cameron L.

    2011-01-01

    Understanding multi-scale floral and faunal responses to human land use is crucial for informing natural resource management and conservation planning. However, our knowledge on how land use influences sagebrush (Artemisia spp.) ecosystems is limited primarily to site-specific studies. To fill this void, studies across large regions are needed that address how species are distributed relative to type, extent, and intensity of land use. We present a study design for the Wyoming Basin Ecoregional Assessment (WBEA) to sample sagebrush-associated flora and fauna along a land cover-human land use gradient. To minimize field costs, we sampled various taxonomic groups simultaneously on transects (ungulates and lagomorphs), point counts (song birds), and area-searches of 7.29-ha survey blocks (pellet counts, burrow counts, reptile surveys, medium-sized mammals, ant mounds, rodent trapping, and vegetation sampling of native and exotic plants). We then present an exploratory approach to develop species occurrence and abundance models when a priori model building is not an option. Our study design has broad applications for large-scale evaluations of arid ecosystems.

  19. 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.

  20. 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.

  1. The study and applications of photochemical-dynamical gravity wave model Ⅱ-- The effects of stable gravity wave on chemical species distribution in mesosphere

    Institute of Scientific and Technical Information of China (English)

    XU; Jiyao(徐寄遥); MA; Ruiping(马瑞平); A.K.Smith

    2002-01-01

    A nonlinear, compressible, non-isothermal gravity wave model that involves photochemistry is used to study the effects of gravity wave on atmospheric chemical species distributions in this paper. The changes in the distributions of oxygen compound and hydrogen compound density induced by gravity wave propagation are simulated. The results indicate that when a gravity wave propagates through a mesopause region, even if it does not break, it can influence the background distributions of chemical species. The effect of gravity wave on chemical species at night is larger than in daytime.

  2. Equilibrium of global amphibian species distributions with climate

    DEFF Research Database (Denmark)

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

    2012-01-01

    A common assumption in bioclimatic envelope modeling is that species distributions are in equilibrium with contemporary climate. A number of studies have measured departures from equilibrium in species distributions in particular regions, but such investigations were never carried out...... for a 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...

  3. 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...

  4. Application of Species Distribution Modeling for Avian Influenza surveillance in the United States considering the North America Migratory Flyways

    Science.gov (United States)

    Belkhiria, Jaber; Alkhamis, Moh A.; Martínez-López, Beatriz

    2016-09-01

    Highly Pathogenic Avian Influenza (HPAI) has recently (2014–2015) re-emerged in the United States (US) causing the largest outbreak in US history with 232 outbreaks and an estimated economic impact of $950 million. This study proposes to use suitability maps for Low Pathogenic Avian Influenza (LPAI) to identify areas at high risk for HPAI outbreaks. LPAI suitability maps were based on wild bird demographics, LPAI surveillance, and poultry density in combination with environmental, climatic, and socio-economic risk factors. Species distribution modeling was used to produce high-resolution (cell size: 500m x 500m) maps for Avian Influenza (AI) suitability in each of the four North American migratory flyways (NAMF). Results reveal that AI suitability is heterogeneously distributed throughout the US with higher suitability in specific zones of the Midwest and coastal areas. The resultant suitability maps adequately predicted most of the HPAI outbreak areas during the 2014–2015 epidemic in the US (i.e. 89% of HPAI outbreaks were located in areas identified as highly suitable for LPAI). Results are potentially useful for poultry producers and stakeholders in designing risk-based surveillance, outreach and intervention strategies to better prevent and control future HPAI outbreaks in the US.

  5. Tropospheric Distribution of Trace Species during the Oxidation Mechanism Observations (OMO-2015) campaign: Model Evaluation and sensitivity simulations

    Science.gov (United States)

    Ojha, Narendra; Pozzer, Andrea; Jöckel, Patrick; Fischer, Horst; Zahn, Andreas; Tomsche, Laura; Lelieveld, Jos

    2017-04-01

    The Asian monsoon convection redistributes trace species, affecting the tropospheric chemistry and radiation budget over Asia and downwind as far as the Mediterranean. It remains challenging to model these impacts due to uncertainties, e.g. associated with the convection parameterization and input emissions. Here, we perform a series of numerical experiments using the global ECHAM5/MESSy atmospheric chemistry model (EMAC) to investigate the tropospheric distribution of O3 and related tracers measured during the Oxidation Mechanism Observations (OMO) conducted during July-August 2015. The reference simulation can reproduce the spatio-temporal variations to some extent (e.g. r2 = 0.7 for O3, 0.6 for CO). However, this simulation underestimates mean CO in the lower troposphere by about 30 ppbv and overestimates mean O3 up to 35 ppbv, especially in the middle-upper troposphere. Interestingly, sensitivity simulations with 50% higher biofuel emissions of CO over South Asia had insignificant effect on CO underestimation, pointing to sources upwind of South Asia. Use of an alternative convection parameterization is found to significantly improve simulated O3. The study reveals the abilities as well as the limitations of the model to reproduce observations and study atmospheric chemistry and climate implications of the monsoon.

  6. Integrating species distributional, conservation planning, and individual based population models: A case study in critical habitat evaluation for the Northern Spotted Owl

    Science.gov (United States)

    Background / Question / Methods As part of the ongoing northern spotted owl recovery planning effort, we evaluated a series of alternative potential critical habitat scenarios using a species-distribution model (MaxEnt), a conservation-planning model (Zonation), and an individua...

  7. 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, reg

  8. 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.

  9. Common garden test of range limits as predicted by a species distribution model in the annual plant Mimulus bicolor.

    Science.gov (United States)

    Dixon, Andrea L; Busch, Jeremiah W

    2017-06-01

    Direct tests of a species distribution model (SDM) were used to evaluate the hypothesis that the northern and southern edges of Mimulus bicolor's geographical range are limited by temperature and precipitation. Climatic suitability was predicted using an SDM informed only by temperature and precipitation variables. These predictions were tested by growing plants in growth chambers with temperature and watering treatments informed by weather stations characteristic of environments at the geographic center, edges, and outside the range. An Aster analysis was used to assess whether treatments significantly affected lifetime flower production and to test for local adaptation. The relationship between climatic suitability and lifetime flower number in the growth chambers was also evaluated. The temperature and watering treatments significantly affected lifetime flower number, although local adaptation was not detected. Flower production was significantly lower under the two edge treatments compared to the central treatment. While no flowers were produced under the beyond-south treatments, flower production was greatest under the beyond-north treatment. These results suggest a hard abiotic limit at the southern edge, and suitable temperature and precipitation conditions beyond the northern edge. While predicted climatic suitability was significantly lower at the range edges, there was no correlation between the climatic suitability of the weather stations' locations and flower production. These results suggest that temperature and precipitation play a significant role in defining the distribution of M. bicolor, but also indicate that dispersal limitation or metapopulation dynamics are likely important factors restricting access to habitable sites beyond the northern range limit. © 2017 Botanical Society of America.

  10. 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, p<0.01) between SSD (predicted msPAF values) and values of SPEAR-pesticides (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.

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

    Science.gov (United States)

    Brotons, Lluís

    2014-01-01

    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.

  12. Competitive exclusion over broad spatial extents is a slow process: Evidence and implications for species distribution modeling

    Science.gov (United States)

    Yackulic, Charles B.

    2016-01-01

    There is considerable debate about the role of competition in shaping species distributions over broad spatial extents. This debate has practical implications because predicting changes in species' geographic ranges in response to ongoing environmental change would be simpler if competition could be ignored. While this debate has been the subject of many reviews, recent literature has not addressed the rates of relevant processes. This omission is surprising in that ecologists hypothesized decades ago that regional competitive exclusion is a slow process. The goal of this review is to reassess the debate under the hypothesis that competitive exclusion over broad spatial extents is a slow process.Available evidence, including simulations presented for the first time here, suggests that competitive exclusion over broad spatial extents occurs slowly over temporal extents of many decades to millennia. Ecologists arguing against an important role for competition frequently study modern patterns and/or range dynamics over periods of decades, while much of the evidence for competition shaping geographic ranges at broad spatial extents comes from paleoecological studies over time scales of centuries or longer. If competition is slow, as evidence suggests, the geographic distributions of some, perhaps many species, would continue to change over time scales of decades to millennia, even if environmental conditions did not continue to change. If the distributions of competing species are at equilibrium it is possible to predict species distributions based on observed species–environment relationships. However, disequilibrium is widespread as a result of competition and many other processes. Studies whose goal is accurate predictions over intermediate time scales (decades to centuries) should focus on factors associated with range expansion (colonization) and loss (local extinction), as opposed to current patterns. In general, understanding of modern range dynamics would be

  13. A centroid model of species distribution with applications to the Carolina wren Thryothorus ludovicianus and house finch Haemorhous mexicanus in the United States

    Science.gov (United States)

    Huang, Qiongyu; Sauer, John R.; Swatantran, Anu; Dubayah, Ralph

    2016-01-01

    Drastic shifts in species distributions are a cause of concern for ecologists. Such shifts pose great threat to biodiversity especially under unprecedented anthropogenic and natural disturbances. Many studies have documented recent shifts in species distributions. However, most of these studies are limited to regional scales, and do not consider the abundance structure within species ranges. Developing methods to detect systematic changes in species distributions over their full ranges is critical for understanding the impact of changing environments and for successful conservation planning. Here, we demonstrate a centroid model for range-wide analysis of distribution shifts using the North American Breeding Bird Survey. The centroid model is based on a hierarchical Bayesian framework which models population change within physiographic strata while accounting for several factors affecting species detectability. Yearly abundance-weighted range centroids are estimated. As case studies, we derive annual centroids for the Carolina wren and house finch in their ranges in the U.S. We further evaluate the first-difference correlation between species’ centroid movement and changes in winter severity, total population abundance. We also examined associations of change in centroids from sub-ranges. Change in full-range centroid movements of Carolina wren significantly correlate with snow cover days (r = −0.58). For both species, the full-range centroid shifts also have strong correlation with total abundance (r = 0.65, and 0.51 respectively). The movements of the full-range centroids of the two species are correlated strongly (up to r = 0.76) with that of the sub-ranges with more drastic population changes. Our study demonstrates the usefulness of centroids for analyzing distribution changes in a two-dimensional spatial context. Particularly it highlights applications that associate the centroid with factors such as environmental stressors, population characteristics

  14. 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 distribution models, land cover, land capability and various biodiversity conservation data to identify natural areas with (i) a potentially high risk of transformation for biofuel production and (ii) potential impact to biodiversity conservation areas...

  15. 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.

  16. 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.

  17. 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.

  18. 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.

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

    Science.gov (United States)

    Dempsey, Steven J; Gese, Eric M; Kluever, Bryan M; Lonsinger, Robert C; Waits, Lisette P

    2015-01-01

    Development and evaluation of noninvasive methods for monitoring species distribution and abundance is a growing area of ecological research. While noninvasive methods have the advantage of reduced risk of negative factors associated with capture, comparisons to methods using more traditional invasive sampling is lacking. Historically kit foxes (Vulpes macrotis) occupied the desert and semi-arid regions of southwestern North America. Once the most abundant carnivore in the Great Basin Desert of Utah, the species is now considered rare. In recent decades, attempts have been made to model the environmental variables influencing kit fox distribution. Using noninvasive scat deposition surveys for determination of kit fox presence, we modeled resource selection functions to predict kit fox distribution using three popular techniques (Maxent, fixed-effects, and mixed-effects generalized linear models) and compared these with similar models developed from invasive sampling (telemetry locations from radio-collared foxes). Resource selection functions were developed using a combination of landscape variables including elevation, slope, aspect, vegetation height, and soil type. All models were tested against subsequent scat collections as a method of model validation. We demonstrate the importance of comparing multiple model types for development of resource selection functions used to predict a species distribution, and evaluating the importance of environmental variables on species distribution. All models we examined showed a large effect of elevation on kit fox presence, followed by slope and vegetation height. However, the invasive sampling method (i.e., radio-telemetry) appeared to be better at determining resource selection, and therefore may be more robust in predicting kit fox distribution. In contrast, the distribution maps created from the noninvasive sampling (i.e., scat transects) were significantly different than the invasive method, thus scat transects may be

  20. Combined Use of Systematic Conservation Planning, Species Distribution Modelling, and Connectivity Analysis Reveals Severe Conservation Gaps in a Megadiverse Country (Peru)

    Science.gov (United States)

    Fajardo, Javier; Lessmann, Janeth; Bonaccorso, Elisa; Devenish, Christian; Muñoz, Jesús

    2014-01-01

    Conservation planning is crucial for megadiverse countries where biodiversity is coupled with incomplete reserve systems and limited resources to invest in conservation. Using Peru as an example of a megadiverse country, we asked whether the national system of protected areas satisfies biodiversity conservation needs. Further, to complement the existing reserve system, we identified and prioritized potential conservation areas using a combination of species distribution modeling, conservation planning and connectivity analysis. Based on a set of 2,869 species, including mammals, birds, amphibians, reptiles, butterflies, and plants, we used species distribution models to represent species' geographic ranges to reduce the effect of biased sampling and partial knowledge about species' distributions. A site-selection algorithm then searched for efficient and complementary proposals, based on the above distributions, for a more representative system of protection. Finally, we incorporated connectivity among areas in an innovative post-hoc analysis to prioritize those areas maximizing connectivity within the system. Our results highlight severe conservation gaps in the Coastal and Andean regions, and we propose several areas, which are not currently covered by the existing network of protected areas. Our approach helps to find areas that contribute to creating a more representative, connected and efficient network. PMID:25479411

  1. 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 (p<0.0001; Mann-Whitney test) when Area Under the 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

  2. Time-dependent species sensitivity distributions.

    Science.gov (United States)

    Fox, David R; Billoir, Elise

    2013-02-01

    Time is a central component of toxicity assessments. However, current ecotoxicological practice marginalizes time in concentration-response (C-R) modeling and species sensitivity distribution (SSD) analyses. For C-R models, time is invariably fixed, and toxicity measures are estimated from a function fitted to the data at that time. The estimated toxicity measures are used as inputs to the SSD modeling phase, which similarly avoids explicit recognition of the temporal component. The present study extends some commonly employed probability models for SSDs to derive theoretical results that characterize the time-dependent nature of hazardous concentration (HCx) values. The authors' results show that even from very simple assumptions, more complex patterns in the SSD time dependency can be revealed.

  3. A biogeographical perspective on species abundance distributions

    DEFF Research Database (Denmark)

    Matthews, Thomas J.; Borges, Paulo A. V.; de Azevedo, Eduardo Brito

    2017-01-01

    It has become increasingly recognized that multiple processes can generate similar shapes of species abundance distributions (SADs), with the result that the fit of a given SAD model cannot unambiguously provide evidence in support of a given theory or model. An alternative approach to comparing...... the fit of different SAD models to data from a single site is to collect abundance data from a variety of sites, and then build models to analyse how different SAD properties (e.g. form, skewness) vary with different predictor variables. Such a biogeographical approach to SAD research is potentially very...... revealing, yet there has been a general lack of interest in SADs in the biogeographical literature. In this Perspective, we address this issue by highlighting findings of recent analyses of SADs that we consider to be of intrinsic biogeographical interest. We use arthropod data drawn from the Azorean...

  4. Modeling the Spatial Distribution and Fruiting Pattern of a Key Tree Species in a Neotropical Forest : Methodology and Potential Applications

    NARCIS (Netherlands)

    Caillaud, Damien; Crofoot, Margaret C.; Scarpino, Samuel V.; Jansen, Patrick A.; Garzon-Lopez, Carol X.; Winkelhagen, Annemarie J. S.; Bohlman, Stephanie A.; Walsh, Peter D.

    2010-01-01

    Background: The movement patterns of wild animals depend crucially on the spatial and temporal availability of resources in their habitat. To date, most attempts to model this relationship were forced to rely on simplified assumptions about the spatiotemporal distribution of food resources. Here we

  5. 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".

  6. Using Remotely-Sensed Land Cover and Distribution Modeling to Estimate Tree Species Migration in the Pacific Northwest Region of North America

    Directory of Open Access Journals (Sweden)

    Nicholas C. Coops

    2016-01-01

    Full Text Available Understanding future tree species migration is challenging due to the unprecedented rate of climate change combined with the presence of human barriers that may limit or impede species movement. Projected changes in climatic conditions outpace migration rates, and more realistic rates of range expansion are needed to make sound environmental policies. In this paper, we develop a modeling approach that takes into account both the geographic changes in the area suitable for the growth and reproduction of tree species, as well as limits imposed geographically on their potential migration using remotely-sensed land cover information. To do so, we combined a physiologically-based decision tree model with a remotely-sensed-derived diffusion-dispersal model to identify the most likely direction of future migration for 15 native tree species in the Pacific Northwest Region of North America, as well as the degree that landscape fragmentation might limit movement. Although projected changes in climate through to 2080 are likely to create favorable environments for range expansion of the 15 tree species by 65% on average, by limiting the potential movement by previously published migration rates and landscape fragmentation, range expansion will likely be 50%–90% of the potential. The hybrid modeling approach using distribution modeling and remotely-sensed data fills a gap between naïve and more complex approaches to take into account major impediments on the potential migration of native tree species.

  7. Multi-model study of mercury dispersion in the atmosphere: vertical and interhemispheric distribution of mercury species

    Directory of Open Access Journals (Sweden)

    J. Bieser

    2017-06-01

    Full Text Available Atmospheric chemistry and transport of mercury play a key role in the global mercury cycle. However, there are still considerable knowledge gaps concerning the fate of mercury in the atmosphere. This is the second part of a model intercomparison study investigating the impact of atmospheric chemistry and emissions on mercury in the atmosphere. While the first study focused on ground-based observations of mercury concentration and deposition, here we investigate the vertical and interhemispheric distribution and speciation of mercury from the planetary boundary layer to the lower stratosphere. So far, there have been few model studies investigating the vertical distribution of mercury, mostly focusing on single aircraft campaigns. Here, we present a first comprehensive analysis based on various aircraft observations in Europe, North America, and on intercontinental flights. The investigated models proved to be able to reproduce the distribution of total and elemental mercury concentrations in the troposphere including interhemispheric trends. One key aspect of the study is the investigation of mercury oxidation in the troposphere. We found that different chemistry schemes were better at reproducing observed oxidized mercury patterns depending on altitude. High concentrations of oxidized mercury in the upper troposphere could be reproduced with oxidation by bromine while elevated concentrations in the lower troposphere were better reproduced by OH and ozone chemistry. However, the results were not always conclusive as the physical and chemical parameterizations in the chemistry transport models also proved to have a substantial impact on model results.

  8. Multi-model study of mercury dispersion in the atmosphere: vertical and interhemispheric distribution of mercury species

    Science.gov (United States)

    Bieser, Johannes; Slemr, Franz; Ambrose, Jesse; Brenninkmeijer, Carl; Brooks, Steve; Dastoor, Ashu; DeSimone, Francesco; Ebinghaus, Ralf; Gencarelli, Christian N.; Geyer, Beate; Gratz, Lynne E.; Hedgecock, Ian M.; Jaffe, Daniel; Kelley, Paul; Lin, Che-Jen; Jaegle, Lyatt; Matthias, Volker; Ryjkov, Andrei; Selin, Noelle E.; Song, Shaojie; Travnikov, Oleg; Weigelt, Andreas; Luke, Winston; Ren, Xinrong; Zahn, Andreas; Yang, Xin; Zhu, Yun; Pirrone, Nicola

    2017-06-01

    Atmospheric chemistry and transport of mercury play a key role in the global mercury cycle. However, there are still considerable knowledge gaps concerning the fate of mercury in the atmosphere. This is the second part of a model intercomparison study investigating the impact of atmospheric chemistry and emissions on mercury in the atmosphere. While the first study focused on ground-based observations of mercury concentration and deposition, here we investigate the vertical and interhemispheric distribution and speciation of mercury from the planetary boundary layer to the lower stratosphere. So far, there have been few model studies investigating the vertical distribution of mercury, mostly focusing on single aircraft campaigns. Here, we present a first comprehensive analysis based on various aircraft observations in Europe, North America, and on intercontinental flights. The investigated models proved to be able to reproduce the distribution of total and elemental mercury concentrations in the troposphere including interhemispheric trends. One key aspect of the study is the investigation of mercury oxidation in the troposphere. We found that different chemistry schemes were better at reproducing observed oxidized mercury patterns depending on altitude. High concentrations of oxidized mercury in the upper troposphere could be reproduced with oxidation by bromine while elevated concentrations in the lower troposphere were better reproduced by OH and ozone chemistry. However, the results were not always conclusive as the physical and chemical parameterizations in the chemistry transport models also proved to have a substantial impact on model results.

  9. 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

  10. 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

  11. 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

  12. 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.

    Directory of Open Access Journals (Sweden)

    Darren J Kriticos

    Full Text Available 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.

  13. 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 BACKGROUND: 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. METHODOLOGY/PRINCIPAL FINDINGS: 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. CONCLUSIONS: 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.

  14. What role does plant physiology play in limiting species distribution?

    Science.gov (United States)

    De Kauwe, M. G.; Medlyn, B. E.; Beaumont, L.; Duursma, R.; Baumgartner, J.

    2015-12-01

    To predict vulnerability of tree species to changes in climate, we need to understand what processes are currently limiting their distributions. Although the limits to distribution is among the most fundamental of ecological questions, there are few studies that determine quantitatively which processes can explain observed distributions. Focusing on two contrasting Eucalypt species, a fast-growing coastal species (E. saligna) and a slower-growing inland species (E. sideroxylon), we examined to what extent plant physiological characteristics limit species distributions. The ecophysiology of both species has been extensively characterised in both controlled and field environments. We parameterised an ecosystem model (GDAY, Generic Decomposition and Yield) for both species, using the best available experimental data. We then used the model to predict the spatial distribution of productivity for these species in eastern Australia, and compared these predictions with the actual distributions. The results of this comparison allow us to identify where the distributions of these species are limited by physiological constraints on productivity, and consequently their vulnerability to changes in climate.

  15. Global alterations in areas of suitability for maize production from climate change and using a mechanistic species distribution model (CLIMEX).

    Science.gov (United States)

    Ramirez-Cabral, Nadiezhda Y Z; Kumar, Lalit; Shabani, Farzin

    2017-07-19

    At the global level, maize is the third most important crop on the basis of harvested area. Given its importance, an assessment of the variation in regional climatic suitability under climate change is critical. CliMond 10' data were used to model the potential current and future climate distribution of maize at the global level using the CLIMEX distribution model with climate data from two general circulation models, CSIRO-Mk3.0 and MIROC-H, assuming an A2 emissions scenario for 2050 and 2100. The change in area under future climate was analysed at continental level and for major maize-producing countries of the world. Regions between the tropics of Cancer and Capricorn indicate the highest loss of climatic suitability, contrary to poleward regions that exhibit an increase of suitability. South America shows the highest loss of climatic suitability, followed by Africa and Oceania. Asia, Europe and North America exhibit an increase in climatic suitability. This study indicates that globally, large areas that are currently suitable for maize cultivation will suffer from heat and dry stresses that may constrain production. For the first time, a model was applied worldwide, allowing for a better understanding of areas that are suitable and that may remain suitable for maize.

  16. 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.

  17. 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...... uniform or lumped species distributions. Here, we illustrate the non-robustness of the Gaussian assumption by simulating different implementations of the standard competition model with constant carrying capacity. In this scenario, lumped species distributions can come about by secondary ecological...... 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...

  18. 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.

  19. Correlative and dynamic species distribution modelling for ecological predictions in the Antarctic: a cross-disciplinary concept

    Directory of Open Access Journals (Sweden)

    Thomas Saucède

    2012-05-01

    Full Text Available Developments of future scenarios of Antarctic ecosystems are still in their infancy, whilst predictions of the physical environment are recognized as being of global relevance and corresponding models are under continuous development. However, in the context of environmental change simulations of the future of the Antarctic biosphere are increasingly demanded by decision makers and the public, and are of fundamental scientific interest. This paper briefly reviews existing predictive models applied to Antarctic ecosystems before providing a conceptual framework for the further development of spatially and temporally explicit ecosystem models. The concept suggests how to improve approaches to relating species’ habitat description to the physical environment, for which a case study on sea urchins is presented. In addition, the concept integrates existing and new ideas to consider dynamic components, particularly information on the natural history of key species, from physiological experiments and biomolecular analyses. Thereby, we identify and critically discuss gaps in knowledge and methodological limitations. These refer to process understanding of biological complexity, the need for high spatial resolution oceanographic data from the entire water column, and the use of data from biomolecular analyses in support of such ecological approaches. Our goal is to motivate the research community to contribute data and knowledge to a holistic, Antarctic-specific, macroecological framework. Such a framework will facilitate the integration of theoretical and empirical work in Antarctica, improving our mechanistic understanding of this globally influential ecoregion, and supporting actions to secure this biodiversity hotspot and its ecosystem services.

  20. Cocaine distribution in wild Erythroxylum species.

    Science.gov (United States)

    Bieri, Stefan; Brachet, Anne; Veuthey, Jean-Luc; Christen, Philippe

    2006-02-20

    Cocaine distribution was studied in leaves of wild Erythroxylum species originating from Bolivia, Brazil, Ecuador, Paraguay, Peru, Mexico, USA, Venezuela and Mauritius. Among 51 species, 28 had never been phytochemically investigated before. Cocaine was efficiently and rapidly extracted with methanol, using focused microwaves at atmospheric pressure, and analysed without any further purification by capillary gas chromatography coupled to mass spectrometry. Cocaine was reported for the first time in 14 species. Erythroxylum laetevirens was the wild species with the highest cocaine content. Its qualitative chromatographic profile also revealed other characteristic tropane alkaloids. Finally, its cocaine content was compared to those of two cultivated coca plants as well as with a coca tea bag sample.

  1. Combining the least cost path method with population genetic data and species distribution models to identify landscape connectivity during the late Quaternary in Himalayan hemlock.

    Science.gov (United States)

    Yu, Haibin; Zhang, Yili; Liu, Linshan; Qi, Wei; Li, Shicheng; Hu, Zhongjun

    2015-12-01

    Himalayan hemlock (Tsuga dumosa) experienced a recolonization event during the Quaternary period; however, the specific dispersal routes are remain unknown. Recently, the least cost path (LCP) calculation coupled with population genetic data and species distribution models has been applied to reveal the landscape connectivity. In this study, we utilized the categorical LCP method, combining species distribution of three periods (the last interglacial, the last glacial maximum, and the current period) and locality with shared chloroplast, mitochondrial, and nuclear haplotypes, to identify the possible dispersal routes of T. dumosa in the late Quaternary. Then, both a coalescent estimate of migration rates among regional groups and establishment of genetic divergence pattern were conducted. After those analyses, we found that the species generally migrated along the southern slope of Himalaya across time periods and genomic makers, and higher degree of dispersal was in the present and mtDNA haplotype. Furthermore, the direction of range shifts and strong level of gene flow also imply the existence of Himalayan dispersal path, and low area of genetic divergence pattern suggests that there are not any obvious barriers against the dispersal pathway. Above all, we inferred that a dispersal route along the Himalaya Mountains could exist, which is an important supplement for the evolutionary history of T. dumosa. Finally, we believed that this integrative genetic and geospatial method would bring new implications for the evolutionary process and conservation priority of species in the Tibetan Plateau.

  2. Combined field/modelling approaches to represent the air-vegetation distribution of benzo[a]pyrene using different vegetation species

    Science.gov (United States)

    Ratola, Nuno; Jiménez-Guerrero, Pedro

    2015-04-01

    A strategy designed to combine the features of field-based experiments and modelling approaches is presented in this work to assess air-vegetation distribution of benzo(a)pyrene (BaP) in the Iberian Peninsula (IP). Given the lack of simultaneous data in both environmental matrices, a methodology with two main steps was employed. First, evaluating the simulations with the chemistry transport model (CTM) WRF (Weather Research and Forecasting) + CHIMERE data against the European Monitoring and Evaluation Programme (EMEP) network, to test the aptitude of the CTM to replicate the respective atmospheric levels. Then, using modelled concentrations and a method to estimate air levels of BaP from biomonitoring data to compare the performance of different pine species (Pinus pinea, Pinus pinaster, Pinus nigra and Pinus halepensis) to describe the atmospheric evidences. The comparison of modelling vs. biomonitoring has a higher dependence on the location of the sampling points, rather than on the pine species, as some tend to overestimate and others to underestimate BaP concentrations, in most cases regardless of the season. The climatology of the canopy levels of BaP was successfully validated with the concentrations in pine needles (most biases below 26%), however, the model was unable to distinguish between species. This should be taken into consideration in future studies, as biases can rise up to 48%, especially in summer and autumn, the. The comparison with biomonitoring data showed a similar pattern, but with the best results in the warmer months.

  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. A dynamic model of some malaria-transmitting anopheline mosquitoes of the Afrotropical region. II. Validation of species distribution and seasonal variations.

    Science.gov (United States)

    Lunde, Torleif M; Balkew, Meshesha; Korecha, Diriba; Gebre-Michael, Teshome; Massebo, Fekadu; Sorteberg, Asgeir; Lindtjørn, Bernt

    2013-02-25

    The first part of this study aimed to develop a model for Anopheles gambiae s.l. with separate parametrization schemes for Anopheles gambiae s.s. and Anopheles arabiensis. The characterizations were constructed based on literature from the past decades. This part of the study is focusing on the model's ability to separate the mean state of the two species of the An. gambiae complex in Africa. The model is also evaluated with respect to capturing the temporal variability of An. arabiensis in Ethiopia. Before conclusions and guidance based on models can be made, models need to be validated. The model used in this paper is described in part one (Malaria Journal 2013, 12:28). For the validation of the model, a data base of 5,935 points on the presence of An. gambiae s.s. and An. arabiensis was constructed. An additional 992 points were collected on the presence An. gambiae s.l.. These data were used to assess if the model could recreate the spatial distribution of the two species. The dataset is made available in the public domain. This is followed by a case study from Madagascar where the model's ability to recreate the relative fraction of each species is investigated. In the last section the model's ability to reproduce the temporal variability of An. arabiensis in Ethiopia is tested. The model was compared with data from four papers, and one field survey covering two years. Overall, the model has a realistic representation of seasonal and year to year variability in mosquito densities in Ethiopia. The model is also able to describe the distribution of An. gambiae s.s. and An. arabiensis in sub-Saharan Africa. This implies this model can be used for seasonal and long term predictions of changes in the burden of malaria. Before models can be used to improving human health, or guide which interventions are to be applied where, there is a need to understand the system of interest. Validation is an important part of this process. It is also found that one of the main

  5. Forms and genesis of species abundance distributions

    Directory of Open Access Journals (Sweden)

    Evans O. Ochiaga

    2015-12-01

    Full Text Available Species abundance distribution (SAD is one of the most important metrics in community ecology. SAD curves take a hollow or hyperbolic shape in a histogram plot with many rare species and only a few common species. In general, the shape of SAD is largely log-normally distributed, although the mechanism behind this particular SAD shape still remains elusive. Here, we aim to review four major parametric forms of SAD and three contending mechanisms that could potentially explain this highly skewed form of SAD. The parametric forms reviewed here include log series, negative binomial, lognormal and geometric distributions. The mechanisms reviewed here include the maximum entropy theory of ecology, neutral theory and the theory of proportionate effect.

  6. Distribution maps for Midsouth tree species

    Science.gov (United States)

    Roy C. Beltz; Daniel F. Bertelson

    1990-01-01

    The Midsouth is an important timber-producing region, with a wide variety of sites and species. In addition to timber production, increasing demands for non-timber amenities are placed on the region’s forests. These maps indicate the distribution of individual species recorded in surveys of the Midsouth conducted by the U.S. Department of Agriculture, Forest Service....

  7. Species, Distributions and Conservation of Acipenseriformes

    Institute of Scientific and Technical Information of China (English)

    黄大明

    2002-01-01

    A list of the world-wide distribution of Acipenseriformes is given including 32 species and subspecies, their distributions, and conservation levels. Most of the species and subspecies of sturgeons are threatened or endangered in at least some of their habitats. Many are nearing extinction. The threat against sturgeons will continue to grow as the world's population increases. Therefore, the problem of conserving sturgeons and replenishing their stock in the entire range has become urgent for scientists of various countries. Materials given here will be useful for solving this difficult but important problem. The problems concerning the Acipenseridae, such as the investigation of resource classification and biological conservation, are also discussed.

  8. 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...

  9. [Modeling of species distribution using topography and remote sensing data, with vascular plants of the Tukuringra Range low mountain belt (Zeya state Nature Reserve, Amur Region) as a case study].

    Science.gov (United States)

    Dudov, S V

    2016-01-01

    On the basis of maximum entropy method embedded in MaxEnt software, the cartographic models are designed for spatial distribution of 63 species of vascular plants inhabiting low mountain belt of the Tukuringra Range. Initial data for modeling were actual points of a species occurrence, data on remote sensing (multispectral space snapshots by Landsat), and a digital topographic model. It is found out that the structure of factors contributing to the model is related to species ecological amplitude. The distribution of stenotopic species is determined, mainly, by the topography, which thermal and humidity conditions of habitats are associated with. To the models for eurytopic species, variables formed on the basis of remote sensing contribute significantly, those variables encompassing the parameters of the soil-vegetable cover. In course of the obtained models analyzing, three principal groups of species are revealed that have similar distribution pattern. Species of the first group are restricted in their distribution by the slopes of the. River Zeya and River Giluy gorges. Species of the second group are associated with the southern macroslope of the range and with southern slopes of large rivers' valleys. The third group incorporates those species that are distributed over the whole territory under study.

  10. 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).

  11. 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

  12. ESUSA: U. S. endangered species distribution file

    Energy Technology Data Exchange (ETDEWEB)

    Nagy, J; Calef, C E

    1978-05-01

    A file containing distribution data on federally listed or proposed endangered species of the United States is described. Included are (a) the common name, (b) the scientific name, (c) the taxonomic family, (d) the OES/FWS/USDI group (mammal, bird, etc.), (e) the status, (f) the geographic distribution by counties, and (g) Federal Register references. Status types are endangered, threatened, proposed, under review, 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. The file is currently being used in conjunction with similar data on projected future energy facilities to anticipate possible conflicts. However, the file would be useful to any project correlating endangered species with location information expressed by county. An example is as an aid in evaluating Forest Service or Bureau of Land Management proposed wilderness areas.

  13. 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.

  14. 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...

  15. Features and distribution patterns of Chinese endemic seed plant species

    Institute of Scientific and Technical Information of China (English)

    Ji-Hong HUANG; Jian-Hua CHEN; Jun-Sheng YING; Ke-Ping MA

    2011-01-01

    We compiled and identified a list of Chinese. endemic seed plant species based on a large number of published References and expert reviews. The characters of these seed plant species and their distribution patterns were described at length. China is rich in endemic seed plants, with a total of 14 939 species (accounting for 52.1%of its total seed plant species) belonging to 1584 genera and 191 families. Temperate families and genera have a significantly higher proportion of endemism than cosmopolitan and tropical ones. The most primitive and derived groups have significantly higher endemism than the other groups. The endemism of tree, shrub, and liana or vine is higher than that of total species; in contrast, the endemism of herb is lower than that of total species. Geographically,these Chinese endemic plants are mainly distributed in Yunnan and Sichuan provinces, southwest China. Species richness and proportion of these endemic plants decrease with increased latitude and have a unimodal response to altitude. The peak value of proportion of endemism is at higher altitudes than that of total species and endemic species richness. The proportions of endemic shrub, liana or vine, and herb increase with altitude and have a clear unimodal curve. In contrast, the proportion of tree increases with altitude, with a sudden increase at~4000 m and has a completely different model. To date, our study provides the most comprehensive list of Chinese endemic seed plant species and their basic composition and distribution features.

  16. A mistletoe tale: postglacial invasion of Psittacanthus schiedeanus (Loranthaceae) to Mesoamerican cloud forests revealed by molecular data and species distribution modeling.

    Science.gov (United States)

    Ornelas, Juan Francisco; Gándara, Etelvina; Vásquez-Aguilar, Antonio Acini; Ramírez-Barahona, Santiago; Ortiz-Rodriguez, Andrés Ernesto; González, Clementina; Mejía Saules, María Teresa; Ruiz-Sanchez, Eduardo

    2016-04-12

    Ecological adaptation to host taxa is thought to result in mistletoe speciation via race formation. However, historical and ecological factors could also contribute to explain genetic structuring particularly when mistletoe host races are distributed allopatrically. Using sequence data from nuclear (ITS) and chloroplast (trnL-F) DNA, we investigate the genetic differentiation of 31 Psittacanthus schiedeanus (Loranthaceae) populations across the Mesoamerican species range. We conducted phylogenetic, population and spatial genetic analyses on 274 individuals of P. schiedeanus to gain insight of the evolutionary history of these populations. Species distribution modeling, isolation with migration and Bayesian inference methods were used to infer the evolutionary transition of mistletoe invasion, in which evolutionary scenarios were compared through posterior probabilities. Our analyses revealed shallow levels of population structure with three genetic groups present across the sample area. Nine haplotypes were identified after sequencing the trnL-F intergenic spacer. These haplotypes showed phylogeographic structure, with three groups with restricted gene flow corresponding to the distribution of individuals/populations separated by habitat (cloud forest localities from San Luis Potosí to northwestern Oaxaca and Chiapas, localities with xeric vegetation in central Oaxaca, and localities with tropical deciduous forests in Chiapas), with post-glacial population expansions and potentially corresponding to post-glacial invasion types. Similarly, 44 ITS ribotypes suggest phylogeographic structure, despite the fact that most frequent ribotypes are widespread indicating effective nuclear gene flow via pollen. Gene flow estimates, a significant genetic signal of demographic expansion, and range shifts under past climatic conditions predicted by species distribution modeling suggest post-glacial invasion of P. schiedeanus mistletoes to cloud forests. However, Approximate

  17. Calcifying species sensitivity distributions for ocean acidification.

    Science.gov (United States)

    Azevedo, Ligia B; De Schryver, An M; Hendriks, A Jan; Huijbregts, Mark A J

    2015-02-01

    Increasing CO2 atmospheric levels lead to increasing ocean acidification, thereby enhancing calcium carbonate dissolution of calcifying species. We gathered peer-reviewed experimental data on the effects of acidified seawater on calcifying species growth, reproduction, and survival. The data were used to derive species-specific median effective concentrations, i.e., pH50, and pH10, via logistic regression. Subsequently, we developed species sensitivity distributions (SSDs) to assess the potentially affected fraction (PAF) of species exposed to pH declines. Effects on species growth were observed at higher pH than those on species reproduction (mean pH10 was 7.73 vs 7.63 and mean pH50 was 7.28 vs 7.11 for the two life processes, respectively) and the variability in the sensitivity of species increased with increasing number of species available for the PAF (pH10 standard deviation was 0.20, 0.21, and 0.33 for survival, reproduction, and growth, respectively). The SSDs were then applied to two climate change scenarios to estimate the increase in PAF (ΔPAF) by future ocean acidification. In a high CO2 emission scenario, ΔPAF was 3 to 10% (for pH50) and 21 to 32% (for pH10). In a low emission scenario, ΔPAF was 1 to 4% (for pH50) and 7 to 12% (for pH10). Our SSDs developed for the effect of decreasing ocean pH on calcifying marine species assemblages can also be used for comparison with other environmental stressors.

  18. Node-based analysis of species distributions

    DEFF Research Database (Denmark)

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

    2014-01-01

    The integration of species distributions and evolutionary relationships is one of the most rapidly moving research fields today and has led to considerable advances in our understanding of the processes underlying biogeographical patterns. Here, we develop a set of metrics, the specific overrepre......The integration of species distributions and evolutionary relationships is one of the most rapidly moving research fields today and has led to considerable advances in our understanding of the processes underlying biogeographical patterns. Here, we develop a set of metrics, the specific...... with case studies on two groups with well-described biogeographical histories: a local-scale community data set of hummingbirds in the North Andes, and a large-scale data set of the distribution of all species of New World flycatchers. The node-based analysis of these two groups generates a set...... of intuitively interpretable patterns that are consistent with current biogeographical knowledge.Importantly, the results are statistically tractable, opening many possibilities for their use in analyses of evolutionary, historical and spatial patterns of species diversity. The method is implemented...

  19. 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

  20. 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

  1. 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 a

  2. 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 a

  3. Evaluation of Survey Methods and Development of Species Distribution Models for Kit Foxes in the Great Basin Desert

    OpenAIRE

    Dempsey, Stephen J

    2013-01-01

    Historically, kit foxes (Vulpes macrotis) once occupied the desert and semi-arid regions of southwestern North America, ranging from Idaho to central Mexico. Their range-wide decline has warranted the kit fox to be listed as endangered in Colorado, threatened in California and Oregon, and designated as a state sensitive species in Idaho and Utah. Once considered the most abundant carnivore in western Utah, the kit fox has been in steep decline over the past decade, creating a demand to determ...

  4. Distributed generation systems model

    Energy Technology Data Exchange (ETDEWEB)

    Barklund, C.R.

    1994-12-31

    A slide presentation is given on a distributed generation systems model developed at the Idaho National Engineering Laboratory, and its application to a situation within the Idaho Power Company`s service territory. The objectives of the work were to develop a screening model for distributed generation alternatives, to develop a better understanding of distributed generation as a utility resource, and to further INEL`s understanding of utility concerns in implementing technological change.

  5. Using Global and Regional Species Distribution Models (SDM) to Infer the Invasive Stage of Latrodectus geometricus (Araneae: Theridiidae) in the Americas.

    Science.gov (United States)

    Taucare-Ríos, Andrés; Bizama, Gustavo; Bustamante, Ramiro O

    2016-12-01

    The brown widow spider, Latrodectus geometricus C. L. Koch, 1841, is a large spider of the family Theridiidae that belongs to a genus of medical interest owing to its potent neurotoxic venom, which causes severe pain in humans. In America, this alien spider has been found in virtually all countries in the region, mainly associated with human dwellings, but also in agricultural sectors. However, the invasive process and potential distribution of this invasive species across the American continent are completely unknown. In this context, using a combination of both global and regional niche models, it is possible to hypothesize the invasive phase of the species as well as the geographic space where these different phases occur. By comparing the global and regional niches of L. geometricus, we examined its invasive process and potential distribution across the American continent. This work is an innovative approach to understanding the invasion of the brown widow spider in this area and the ecological processes that underlie this invasion. In this context, the global and regional niche comparison constitutes an appropriate tool to account for the complexities of the invasive process, generating different hypotheses amenable to being tested in future studies. © The Authors 2016. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  6. 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.

  7. Multiple peaks of species abundance distributions induced by sparse interactions

    CERN Document Server

    Obuchi, Tomoyuki; Tokita, Kei

    2016-01-01

    We investigate the replicator dynamics with "sparse" symmetric interactions which represent specialist-specialist interactions in ecological communities. By considering a large self interaction $u$, we conduct a perturbative expansion which manifests that the nature of the interactions has a direct impact on the species abundance distribution. The central results are all species coexistence in a realistic range of the model parameters and that a certain discrete nature of the interactions induces multiple peaks in the species abundance distribution, providing the possibility of theoretically explaining multiple peaks observed in various field studies. To get more quantitative information, we also construct a non-perturbative theory which becomes exact on tree-like networks if all the species coexist, providing exact critical values of $u$ below which extinct species emerge. Numerical simulations in various different situations are conducted and they clarify the robustness of the presented mechanism of all spe...

  8. 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...... hypotheses concerning the past population structure of species in phylogeographical studies. CEMs are sensitive to theoretical assumptions, to model classes and to projections in non-analogous climates, among other issues. Studies hindcasting the climatic niches of species often make reference...... time and the equilibrium of species with climate. I also summarize a set of 'recommended practices' to improve hindcasting. The studies reviewed: (1) rarely test the theoretical assumptions behind niche modelling such as the stability of species climatic niches through time and the equilibrium...

  9. How many predictors in species distribution models at the landscape scale? Land use versus LiDAR-derived canopy height

    NARCIS (Netherlands)

    Ficetola, G.F.; Bonardi, A.; Mücher, C.A.; Gilissen, N.L.M.; Padoa-Schioppa, E.

    2014-01-01

    At the local spatial scale, land-use variables are often employed as predictors for ecological niche models (ENMs). Remote sensing can provide additional synoptic information describing vegetation structure in detail. However, there is limited knowledge on which environmental variables and how many

  10. Generalized functional responses for species distributions

    NARCIS (Netherlands)

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

    2011-01-01

    Researchers employing resource selection functions (RSFs) and other related methods aim to detect correlates of space-use and mitigate against detrimental environmental change. However, an empirical model fit to data from one place or time is unlikely to capture species responses under different con

  11. Tests of species-specific models reveal the importance of drought in postglacial range shifts of a Mediterranean-climate tree: insights from integrative distributional, demographic and coalescent modelling and ABC model selection.

    Science.gov (United States)

    Bemmels, Jordan B; Title, Pascal O; Ortego, Joaquín; Knowles, L Lacey

    2016-10-01

    Past climate change has caused shifts in species distributions and undoubtedly impacted patterns of genetic variation, but the biological processes mediating responses to climate change, and their genetic signatures, are often poorly understood. We test six species-specific biologically informed hypotheses about such processes in canyon live oak (Quercus chrysolepis) from the California Floristic Province. These hypotheses encompass the potential roles of climatic niche, niche multidimensionality, physiological trade-offs in functional traits, and local-scale factors (microsites and local adaptation within ecoregions) in structuring genetic variation. Specifically, we use ecological niche models (ENMs) to construct temporally dynamic landscapes where the processes invoked by each hypothesis are reflected by differences in local habitat suitabilities. These landscapes are used to simulate expected patterns of genetic variation under each model and evaluate the fit of empirical data from 13 microsatellite loci genotyped in 226 individuals from across the species range. Using approximate Bayesian computation (ABC), we obtain very strong support for two statistically indistinguishable models: a trade-off model in which growth rate and drought tolerance drive habitat suitability and genetic structure, and a model based on the climatic niche estimated from a generic ENM, in which the variables found to make the most important contribution to the ENM have strong conceptual links to drought stress. The two most probable models for explaining the patterns of genetic variation thus share a common component, highlighting the potential importance of seasonal drought in driving historical range shifts in a temperate tree from a Mediterranean climate where summer drought is common.

  12. Modeled ground water age distributions

    Science.gov (United States)

    Woolfenden, Linda R.; Ginn, Timothy R.

    2009-01-01

    The age of ground water in any given sample is a distributed quantity representing distributed provenance (in space and time) of the water. Conventional analysis of tracers such as unstable isotopes or anthropogenic chemical species gives discrete or binary measures of the presence of water of a given age. Modeled ground water age distributions provide a continuous measure of contributions from different recharge sources to aquifers. A numerical solution of the ground water age equation of Ginn (1999) was tested both on a hypothetical simplified one-dimensional flow system and under real world conditions. Results from these simulations yield the first continuous distributions of ground water age using this model. Complete age distributions as a function of one and two space dimensions were obtained from both numerical experiments. Simulations in the test problem produced mean ages that were consistent with the expected value at the end of the model domain for all dispersivity values tested, although the mean ages for the two highest dispersivity values deviated slightly from the expected value. Mean ages in the dispersionless case also were consistent with the expected mean ages throughout the physical model domain. Simulations under real world conditions for three dispersivity values resulted in decreasing mean age with increasing dispersivity. This likely is a consequence of an edge effect. However, simulations for all three dispersivity values tested were mass balanced and stable demonstrating that the solution of the ground water age equation can provide estimates of water mass density distributions over age under real world conditions.

  13. 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.

  14. Modelling the Distribution of Forest-Dependent Species in Human-Dominated Landscapes: Patterns for the Pine Marten in Intensively Cultivated Lowlands.

    Directory of Open Access Journals (Sweden)

    Alessandro Balestrieri

    Full Text Available In recent years, the "forest-specialist" pine marten Martes martes has been reported to also occur also in largely fragmented, lowland landscapes of north-western Italy. The colonization of such an apparently unsuitable area provided the opportunity for investigating pine marten ecological requirements and predicting its potential south- and eastwards expansion. We collected available pine marten occurrence data in the flood plain of the River Po (N Italy and relate them to 11 environmental variables by developing nine Species Distribution Models. To account for inter-model variability we used average ensemble predictions (EP. EP predicted a total of 482 suitable patches (8.31% of the total study area for the pine marten. The main factors driving pine marten occurrence in the western River Po plain were the distance from watercourses and the distance from woods. EP suggested that the pine marten may further expand in the western lowland, whilst the negligible residual wood cover of large areas in the central and eastern plain makes the habitat unsuitable for the pine marten, except for some riparian corridors and the pine wood patches bordering the Adriatic coast. Based on our results, conservation strategies should seek to preserve remnant forest patches and enhance the functional connectivity provided by riparian corridors.

  15. Modelling the Distribution of Forest-Dependent Species in Human-Dominated Landscapes: Patterns for the Pine Marten in Intensively Cultivated Lowlands

    Science.gov (United States)

    Balestrieri, Alessandro; Bogliani, Giuseppe; Boano, Giovanni; Ruiz-González, Aritz; Saino, Nicola; Costa, Stefano; Milanesi, Pietro

    2016-01-01

    In recent years, the “forest-specialist” pine marten Martes martes has been reported to also occur also in largely fragmented, lowland landscapes of north-western Italy. The colonization of such an apparently unsuitable area provided the opportunity for investigating pine marten ecological requirements and predicting its potential south- and eastwards expansion. We collected available pine marten occurrence data in the flood plain of the River Po (N Italy) and relate them to 11 environmental variables by developing nine Species Distribution Models. To account for inter-model variability we used average ensemble predictions (EP). EP predicted a total of 482 suitable patches (8.31% of the total study area) for the pine marten. The main factors driving pine marten occurrence in the western River Po plain were the distance from watercourses and the distance from woods. EP suggested that the pine marten may further expand in the western lowland, whilst the negligible residual wood cover of large areas in the central and eastern plain makes the habitat unsuitable for the pine marten, except for some riparian corridors and the pine wood patches bordering the Adriatic coast. Based on our results, conservation strategies should seek to preserve remnant forest patches and enhance the functional connectivity provided by riparian corridors. PMID:27368056

  16. 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

  17. 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

  18. Distributed Parameter Modelling Applications

    DEFF Research Database (Denmark)

    2011-01-01

    Here the issue of distributed parameter models is addressed. Spatial variations as well as time are considered important. Several applications for both steady state and dynamic applications are given. These relate to the processing of oil shale, the granulation of industrial fertilizers and the d......Here the issue of distributed parameter models is addressed. Spatial variations as well as time are considered important. Several applications for both steady state and dynamic applications are given. These relate to the processing of oil shale, the granulation of industrial fertilizers...... sands processing. The fertilizer granulation model considers the dynamics of MAP-DAP (mono and diammonium phosphates) production within an industrial granulator, that involves complex crystallisation, chemical reaction and particle growth, captured through population balances. A final example considers...

  19. 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

  20. ESA species' distribution and critical habitat in Alaska EEZ

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This feature dataset contains feature classes that depict the distribution and critical habitat of species list under the Endangered Species Act which occur in...

  1. Models of distributive justice.

    Science.gov (United States)

    Wolff, Jonathan

    2007-01-01

    Philosophical disagreement about justice rages over at least two questions. The most immediate is a substantial question, concerning the conditions under which particular distributive arrangements can be said to be just or unjust. The second, deeper, question concerns the nature of justice itself. What is justice? Here we can distinguish three views. First, justice as mutual advantage sees justice as essentially a matter of the outcome of a bargain. There are times when two parties can both be better off by making some sort of agreement. Justice, on this view, concerns the distribution of the benefits and burdens of the agreement. Second, justice as reciprocity takes a different approach, looking not at bargaining but at the idea of a fair return or just price, attempting to capture the idea of justice as equal exchange. Finally justice as impartiality sees justice as 'taking the other person's point of view' asking 'how would you like it if it happened to you?' Each model has significantly different consequences for the question of when issues of justice arise and how they should be settled. It is interesting to consider whether any of these models of justice could regulate behaviour between non-human animals.

  2. 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.

  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 preserv

  4. Effects of tree species composition on within-forest distribution of understorey species

    NARCIS (Netherlands)

    Oijen, van D.; Feijen, M.; Hommel, P.W.F.M.; Ouden, den J.; Waal, de R.W.

    2005-01-01

    Question: Do tree species, with different litter qualities, affect the within-forest distribution of forest understorey species on intermediate to base-rich soils? Since habitat loss and fragmentation have caused ancient forest species to decline, those species are the main focus of this study. Loca

  5. Distribution Pattern of Species Richness for Wild Fruit Trees in Xinjiang Based on Species Distribution Modeling%基于物种分布模型的新疆野生果树物种丰富度分布格局

    Institute of Scientific and Technical Information of China (English)

    刘会良; 张玲卫; 张宏祥; 布海丽且姆·阿卜杜热合曼; 张道远; 管开云

    2015-01-01

    【目的】选取新疆56种野生果树为研究对象,利用物种分布区模型模拟其潜在分布区,并分析其与环境因子的关系,为有效保护和管理新疆野生果树资源提供基础资料。【方法】基于物种分布点数据,最终选取13个环境因子确定物种的生态位信息,使用Maxent软件构建分布区模型,获得新疆野生果树物种丰富度分布格局图,并分析其与环境因子的关系。【结果】野生果树在新疆具有广泛的潜在分布区,其面积占全区面积的54.5%;物种丰富度可划分为1~4,5~14,15~24和25~38这4个等级,但物种丰富度大的区域面积比较狭窄,主要分布于伊犁河谷周边的天山山脉、巴尔鲁克山-塔尔巴哈台山和阿尔泰山西部;通过计算物种丰富度格局与13个环境因子之间的相关系数,发现2个降水因子(最湿季降水和最干季降水)、1个气温因子(平均日较差)和1个土壤因子(土壤碳含量)与新疆野生果树分布格局相关性高(R2>0.35),说明最湿季降水、最干季降水、平均日较差气温和土壤碳含量显著影响新疆野生果树的物种丰富度和分布格局。【结论】从物种丰富度水平和物种保护的角度上说,具有高水平野生果树物种丰富度的天山西部的伊犁河谷、巴尔鲁克山-塔尔巴哈台山和阿尔泰山西部山地应该受到优先保护。%[Objective]In this study,we have applied species distribution modeling ( SDM ) to model the potential distributions of 56 species of wild fruit trees,in order to provide baseline data for effective conservation and management of Xinjiang wild fruit tree resources.[Method]Distribution records of wild fruit trees were obtained from the Herbarium and 13 environmental variables were chosen to define the ecological niche for these sample species. The software package Maxen was employed to model species distributions. After overlapping these 56

  6. Species distributions, quantum theory, and the enhancement of biodiversity measures

    DEFF Research Database (Denmark)

    Real, Raimundo; Barbosa, A. Márcia; Bull, Joseph William

    2016-01-01

    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...... 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....

  7. MaxEnt versus MaxLike: empirical comparisons with ant species distributions

    OpenAIRE

    Fitzpatrick, Matthew C.; Gotelli, Nicholas J.; Ellison, Aaron M.

    2013-01-01

    MaxEnt is one of the most widely used tools in ecology, biogeography, and evolution for modeling and mapping species distributions using presence-only occurrence records and associated environmental covariates. Despite its popularity, the exponential model implemented by MaxEnt does not directly estimate occurrence probability, the natural quantity of interest when modeling species distributions. Instead, MaxEnt generates an index of relative habitat suitability. MaxLike, a newly introduced m...

  8. Anticipating species distributions: Handling sampling effort bias under a Bayesian framework.

    Science.gov (United States)

    Rocchini, Duccio; Garzon-Lopez, Carol X; Marcantonio, Matteo; Amici, Valerio; Bacaro, Giovanni; Bastin, Lucy; Brummitt, Neil; Chiarucci, Alessandro; Foody, Giles M; Hauffe, Heidi C; He, Kate S; Ricotta, Carlo; Rizzoli, Annapaola; Rosà, Roberto

    2017-04-15

    Anticipating species distributions in space and time is necessary for effective biodiversity conservation and for prioritising management interventions. This is especially true when considering invasive species. In such a case, anticipating their spread is important to effectively plan management actions. However, considering uncertainty in the output of species distribution models is critical for correctly interpreting results and avoiding inappropriate decision-making. In particular, when dealing with species inventories, the bias resulting from sampling effort may lead to an over- or under-estimation of the local density of occurrences of a species. In this paper we propose an innovative method to i) map sampling effort bias using cartogram models and ii) explicitly consider such uncertainty in the modeling procedure under a Bayesian framework, which allows the integration of multilevel input data with prior information to improve the anticipation species distributions.

  9. 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...

  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. distribution of simulium species and its infection with onchocerca ...

    African Journals Online (AJOL)

    DR. AMINU

    ABSTRACT. A survey of the distribution of Simulium species complex population and its infection rate with ... Statistical analysis using t-test and ANOVA revealed that there was no significant .... B.A. Bissan, Y. (1995): Impact of combined.

  13. MaxEnt versus MaxLike: empirical comparisons with ant species distributions

    National Research Council Canada - National Science Library

    Fitzpatrick, Matthew C; Gotelli, Nicholas J; Ellison, Aaron M

    2013-01-01

    MaxEnt is one of the most widely used tools in ecology, biogeography, and evolution for modeling and mapping species distributions using presence-only occurrence records and associated environmental covariates...

  14. Insecticide species sensitivity distributions: importance of test species selection and relevance to aquatic ecosystems

    NARCIS (Netherlands)

    Maltby, L.; Blake, N.; Brock, T.C.M.; Brink, van den P.J.

    2005-01-01

    Single-species acute toxicity data and (micro)mesocosm data were collated for 16 insecticides. These data were used to investigate the importance of test-species selection in constructing species sensitivity distributions (SSDs) and the ability of estimated hazardous concentrations (HCs) to protect

  15. Prediction of current species distribution of Cheilosia proxima group (Diptera: Syrphidae on the Balkan peninsula

    Directory of Open Access Journals (Sweden)

    Milić Dubravka M.

    2013-01-01

    Full Text Available Predicting species distribution in different climates is most often made by climate models (“climate envelope models” - CEM which are using the current geographical distribution of species and climate characteristics of the area. Hoverflies (Insecta: Diptera: Syrphidae can act as bioindicators and monitors of climate change and habitat quality. Cheilosia Meigen, 1822 is one of the largest hoverflies genera, with about 450 described species. The aim of this study was to model the current potential distribution of six species from Cheilosia proxima group on the Balkan Peninsula (Cheilosia aerea Dufour, 1848, C. balkana Vujić, 1994, C. gigantea Zetterstedt, 1838, C. pascuorum Becker, 1894, C. proxima Zetterstedt, 1843 and C. rufimana Becker, 1894 using maximum entropy modeling (Maxent. It is observed that parameters with highest influence on the analyzed species are Altitude and BIO 15 (Precipitation Seasonality for all species, except C. rufimana. Parameter that also substantially influenced for all species, except C. pascuorum, is BIO 18 (Precipitation of Warmest Quarter. The models of current distribution have shown that the most important area of the Balkan Peninsula, for species from Cheilosia proxima group, is Dinaric mountains. Information obtained in this paper can help in future monitoring of species, as well as for the conservation measures, especially for endemics and rare species. [Projekat Ministarstva nauke Republike Srbije, br. 173002 i br. 43002

  16. 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

  17. 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.

  18. 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......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 arthropods to test predictions obtained with computer simulations on whether dispersal ability influences the rate of change of SADs as a function of sample size. To characterize the change of the shape of the SADs we use the moments of the distributions: the skewness and the raw moments. In agreement...... with computer simulations, low dispersal ability species generate a hump for intermediate abundance classes earlier than the distributions of high dispersal ability species. Importantly, when plotted as function of sample size, the raw moments of the SADs of arthropods have a power law pattern similar...

  19. Entropy Maximization and the Spatial Distribution of Species

    NARCIS (Netherlands)

    Haegeman, Bart; Etienne, Rampal S.

    2010-01-01

    Entropy maximization (EM, also known as MaxEnt) is a general inference procedure that originated in statistical mechanics. It has been applied recently to predict ecological patterns, such as species abundance distributions and species-area relationships. It is well known in physics that the EM resu

  20. Aquatic beetle species and their distributions in Xinjiang, China

    Institute of Scientific and Technical Information of China (English)

    ZHAO Ling; JIA Feng-long; Tursun Dilbar; ZHENG Zhe-min

    2009-01-01

    The species of aquatic beetles and their distributions in lotic and lentic habitats were investigated during July to August of 2005 and 2006 in Xinjiang Uygur Autonomous Region, China. A total of 66 species belonging to 7 beetle families (Dytiscidae, Gyrinidae, Haliplidae, Helophoridae, Noteridae, Hydraenidae, Hydrophilidae) are recorded, of which 16 are new records of aquatic beetles for China.

  1. Entropy Maximization and the Spatial Distribution of Species

    NARCIS (Netherlands)

    Haegeman, Bart; Etienne, Rampal S.

    Entropy maximization (EM, also known as MaxEnt) is a general inference procedure that originated in statistical mechanics. It has been applied recently to predict ecological patterns, such as species abundance distributions and species-area relationships. It is well known in physics that the EM

  2. The implicit assumption of symmetry and the species abundance distribution

    NARCIS (Netherlands)

    Alonso, David; Ostling, Annette; Etienne, Rampal S.

    Species abundance distributions (SADs) have played a historical role in the development of community ecology. They summarize information about the number and the relative abundance of the species encountered in a sample from a given community. For years ecologists have developed theory to

  3. species composition, relative abundance and distribution of the ...

    African Journals Online (AJOL)

    Preferred Customer

    ABSTRACT: A study on avian species composition, relative abundance, diversity and distribution at ... settlement and land degradation were the main threats for the distribution of birds in the present study area. ... Entoto Natural Park and escarpment is located between ..... Mathematical Theory of Communication. The.

  4. Global geographic distribution of Trichinella species and genotypes.

    Science.gov (United States)

    Feidas, Haralambos; Kouam, Marc K; Kantzoura, Vaia; Theodoropoulos, Georgios

    2014-08-01

    Maximum entropy ecological niche modeling was utilized to describe the global geographic distribution of Trichinella species and genotypes and to assess their invasive risk in new areas other than the ones currently known. Also, space-time scan statistic was utilized to identify global spatiotemporal clusters of infection. A database containing 3209 records for 12 species and genotypes identified at the International Trichinella Reference Center (ITRC) as well as climate, elevation, and land cover data extracted from various databases were used. Ecological niche modeling implemented in the Maxent program indicated new potential ranges for T. spiralis (T1), T. nativa (T2), T. britovi (T3), T. pseudospiralis (T4), T. murrelli (T5), T6, T. papuae (T10), and T. zimbabwensis (T11). The area under the curve values for the test data of the models ranged from 0.901 to 0.998, indicating that the models were very good to excellent. The most important bioclimatic factor in modeling the ranges for T. spiralis (T1), T. nativa (T2), T. britovi (T3), T6, and T. zimbabwensis (T11) was temperature, for T. pseudospiralis (T4) and T. papuae (T10) was precipitation, and for T. murrelli (T5) was land cover. T. spiralis (T1), T. britovi (T3), and T. pseudospiralis (T4) had the same primary land cover which was "Grass Crops". The primary land covers were "Conifer Boreal Forest" for T. nativa (T2), "Cool Fields and Woods" for T. murrelli (T5), "Upland Tundra" for T6, "Tropical Rainforest" for T. papuae (T10), and "Crops and Town" for T. zimbabwensis (T11). The scan statistic analyses revealed the presence of significant spatiotemporal clusters (p<0.05) for T. spiralis (T1), T. nativa (T2), T. britovi (T3), T. pseudospiralis (T4), T. murrelli (T5), T6, and T. nelsoni (T7). No significant clusters were found for T. papuae (T10) and T. zimbabwensis (T11).

  5. Is there an optimum scale for predicting bird species' distribution in agricultural landscapes?

    Science.gov (United States)

    Pelosi, Céline; Bonthoux, Sébastien; Castellarini, Fabiana; Goulard, Michel; Ladet, Sylvie; Balent, Gérard

    2014-04-01

    Changes in forest cover in agricultural landscapes affect biodiversity. Its management needs some indications about scale to predict occurrence of populations and communities. In this study we considered a forest cover index to predict bird species and community patterns in agricultural landscapes in south-western France. We used generalized linear models for that purpose with prediction driven by wooded areas' spatial distribution at nine different radii. Using 1064 point counts, we modelled the distribution of 10 bird species whose habitat preferences are spread along a landscape opening gradient. We also modelled the distribution of species richness for farmland species and for forest species. We used satellite images to construct a 'wood/non-wood' map and calculated a forest index, considering the surface area of wooded areas at nine radii from 110m to 910m. The models' predictive quality was determined by the AUC (for predicted presences) and ρ (for predicted species richness) criteria. We found that the forest cover was a good predictor of the distribution of seven bird species in agricultural landscapes (mean AUC for the seven species = 0.74 for the radius 110m). Species richness of farmland and forest birds was satisfactorily predicted by the models (ρ = 0.55 and 0.49, respectively, for the radius 110m). The presence of the studied species and species richness metrics were better predicted at smaller scales (i.e. radii between 110 m and 310 m) within the range tested. These results have implications for bird population management in agricultural landscapes since better pinpointing the scale to predict species distributions will enhance targeting efforts to be made in terms of landscape management.

  6. Vasyliunas-Cairns distribution function for space plasma species

    Science.gov (United States)

    Abid, A. A.; Ali, S.; Du, J.; Mamun, A. A.

    2015-08-01

    A more generalized form of non-Maxwellian distribution function (that can be named as Vasyliunas-Cairns distribution function) is introduced. Its basic properties are numerically analyzed by the variation of two important parameters, namely, α (which shows the amount of energetic particles present in the plasma system) and κ (which shows the superthermality of the plasma species). It has been observed that (i) for α → 0 ( κ → ∞ ), the Vasyliunas-Cairns distribution function reduces to the Vasyliunas or κ (Cairns or nonthermal) distribution function; (ii) for α → 0 and κ → ∞ , it reduces to the Maxwellian distribution function; and (iii) the effect of the parameter α (κ) significantly modifies the basic properties of the Vasyliunas (Cairns) distribution function. The applications of this generalized non-Maxwellian distribution function (Vasyliunas-Cairns distribution function) in different space plasma situations are briefly discussed.

  7. Map of Life - A Dashboard for Monitoring Planetary Species Distributions

    Science.gov (United States)

    Jetz, W.

    2016-12-01

    Geographic information about biodiversity is vital for understanding the many services nature provides and their potential changes, yet remains unreliable and often insufficient. By integrating a wide range of knowledge about species distributions and their dynamics over time, Map of Life supports global biodiversity education, monitoring, research and decision-making. Built on a scalable web platform geared for large biodiversity and environmental data, Map of Life endeavors provides species range information globally and species lists for any area. With data and technology provided by NASA and Google Earth Engine, tools under development use remote sensing-based environmental layers to enable on-the-fly predictions of species distributions, range changes, and early warning signals for threatened species. The ultimate vision is a globally connected, collaborative knowledge- and tool-base for regional and local biodiversity decision-making, education, monitoring, and projection. For currently available tools, more information and to follow progress, go to MOL.org.

  8. 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 ...... in Thailand based on overlays of all species with more than 5 records (n = 103)....

  9. 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.

  10. Predicting species richness and distribution ranges of centipedes at the northern edge of Europe

    Science.gov (United States)

    Georgopoulou, Elisavet; Djursvoll, Per; Simaiakis, Stylianos M.

    2016-07-01

    In recent decades, interest in understanding species distributions and exploring processes that shape species diversity has increased, leading to the development of advanced methods for the exploitation of occurrence data for analytical and ecological purposes. Here, with the use of georeferenced centipede data, we explore the importance and contribution of bioclimatic variables and land cover, and predict distribution ranges and potential hotspots in Norway. We used a maximum entropy analysis (Maxent) to model species' distributions, aiming at exploring centres of distribution, latitudinal spans and northern range boundaries of centipedes in Norway. The performance of all Maxent models was better than random with average test area under the curve (AUC) values above 0.893 and True Skill Statistic (TSS) values above 0.593. Our results showed a highly significant latitudinal gradient of increased species richness in southern grid-cells. Mean temperatures of warmest and coldest quarters explained much of the potential distribution of species. Predictive modelling analyses revealed that south-eastern Norway and the Atlantic coast in the west (inclusive of the major fjord system of Sognefjord), are local biodiversity hotspots with regard to high predictive species co-occurrence. We conclude that our predicted northward shifts of centipedes' distributions in Norway are likely a result of post-glacial recolonization patterns, species' ecological requirements and dispersal abilities.

  11. Distribution of Xiphinema americanum and Related Species in North America.

    Science.gov (United States)

    Robbins, R T

    1993-09-01

    All species of the Xiphinema americanum-group and their synonyms are listed. The North American species reported are listed by state or province. Among these species, X. rivesi has the most widely reported distribution. Six species (X. diffusum, X. floridae, X. laevistriatum, X. luci, X. shell, and X. tarjanense) have been reported from only Florida. The reports of X. pachtaicum, X. sheri, and X. luci did not include morphometrics and need to be confirmed; X. brevicolle from California was identified before Lamberti and Bleve-Zacheo described 15 new species in 1979 and similarly needs to be confirmed. Because of the proliferation of species in this group, reports of X. americanum (sensu stricto) before 1979 are questionable. Extraction techniques for longidorids are discussed.

  12. How dispersal limitation shapes species-body size distributions in local communities

    NARCIS (Netherlands)

    Etienne, R.S.; Olff, H.

    2004-01-01

    A critical but poorly understood pattern in macroecology is the often unimodal species - body size distribution ( also known as body size - diversity relationship) in a local community ( embedded in a much larger regional species pool). Purely neutral community models that assume functional

  13. 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.

  14. Plant species distribution along environmental gradient: do belowground interactions with fungi matter?

    Directory of Open Access Journals (Sweden)

    Loïc ePellissier

    2013-12-01

    Full Text Available The distribution of plants along environmental gradients is constrained by abiotic and biotic factors. Cumulative evidence attests of the impact of abiotic factors on plant distributions, but only few studies discuss the role of belowground communities. Soil fungi, in particular, are thought to play an important role in how plant species assemble locally into communities. We first review existing evidence, and then test the effect of the number of soil fungal operational taxonomic units (OTUs on plant species distributions using a recently collected dataset of plant and metagenomic information on soil fungi in the Western Swiss Alps. Using species distribution models, we investigated whether the distribution of individual plant species is correlated to the number of OTUs of two important soil fungal classes known to interact with plants: the Glomeromycetes, that are obligatory symbionts of plants, and the Agaricomycetes, that may be facultative plant symbionts, pathogens, or wood decayers. We show that including the fungal richness information in the models of plant species distributions improves predictive accuracy. Number of fungal OTUs is especially correlated to the distribution of high elevation plant species. We suggest that high elevation soil show greater variation in fungal assemblages that may in turn impact plant turnover among communities. We finally discuss how to move beyond correlative analyses, through the design of field experiments manipulating plant and fungal communities along environmental gradients.

  15. [Effects of sampling plot number on tree species distribution prediction under climate change].

    Science.gov (United States)

    Liang, Yu; He, Hong-Shi; Wu, Zhi-Wei; Li, Xiao-Na; Luo, Xu

    2013-05-01

    Based on the neutral landscapes under different degrees of landscape fragmentation, this paper studied the effects of sampling plot number on the prediction of tree species distribution at landscape scale under climate change. The tree species distribution was predicted by the coupled modeling approach which linked an ecosystem process model with a forest landscape model, and three contingent scenarios and one reference scenario of sampling plot numbers were assumed. The differences between the three scenarios and the reference scenario under different degrees of landscape fragmentation were tested. The results indicated that the effects of sampling plot number on the prediction of tree species distribution depended on the tree species life history attributes. For the generalist species, the prediction of their distribution at landscape scale needed more plots. Except for the extreme specialist, landscape fragmentation degree also affected the effects of sampling plot number on the prediction. With the increase of simulation period, the effects of sampling plot number on the prediction of tree species distribution at landscape scale could be changed. For generalist species, more plots are needed for the long-term simulation.

  16. A Universal Lifetime Distribution for Multi-Species Systems

    CERN Document Server

    Murase, Yohsuke; Ito, Nobuyasu; Rikvold, Per Arne

    2015-01-01

    Lifetime distributions of social entities, such as enterprises, products, and media contents, are one of the fundamental statistics characterizing the social dynamics. To investigate the lifetime distribution of mutually interacting systems, simple models having a rule for additions and deletions of entities are investigated. We found a quite universal lifetime distribution for various kinds of inter-entity interactions, and it is well fitted by a stretched-exponential function with an exponent close to 1/2. We propose a "modified Red-Queen" hypothesis to explain this distribution. We also review empirical studies on the lifetime distribution of social entities, and discussed the applicability of the model.

  17. Modelling the nuclear parton distributions

    CERN Document Server

    Kulagin, S A

    2016-01-01

    We review a semi-microscopic model of nuclear parton distributions, which takes into account a number of nuclear effects including Fermi motion and nuclear binding, nuclear meson-exchange currents and off-shell corrections to bound nucleon distributions as well as nuclear shadowing effect. We also discuss applications of the model to the lepton-nuclear deep-inelastic scattering, Drell-Yan process and neutrino total cross sections.

  18. 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

  19. Distribution system modeling and analysis

    CERN Document Server

    Kersting, William H

    2002-01-01

    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 re

  20. 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 ha......, in a framework that facilitates a comparison between them. We identify and discuss the central factors governing the individual mechanisms, and elucidate their effect on empirical patterns....

  1. Extending Marine Species Distribution Maps Using Non-Traditional Sources

    Science.gov (United States)

    Moretzsohn, Fabio; Gibeaut, James

    2015-01-01

    Abstract Background Traditional sources of species occurrence data such as peer-reviewed journal articles and museum-curated collections are included in species databases after rigorous review by species experts and evaluators. The distribution maps created in this process are an important component of species survival evaluations, and are used to adapt, extend and sometimes contract polygons used in the distribution mapping process. New information During an IUCN Red List Gulf of Mexico Fishes Assessment Workshop held at The Harte Research Institute for Gulf of Mexico Studies, a session included an open discussion on the topic of including other sources of species occurrence data. During the last decade, advances in portable electronic devices and applications enable 'citizen scientists' to record images, location and data about species sightings, and submit that data to larger species databases. These applications typically generate point data. Attendees of the workshop expressed an interest in how that data could be incorporated into existing datasets, how best to ascertain the quality and value of that data, and what other alternate data sources are available. This paper addresses those issues, and provides recommendations to ensure quality data use. PMID:25941453

  2. Odonata of maharashtra, India with notes on species distribution.

    Science.gov (United States)

    Tiple, Ashish D; Koparde, Pankaj

    2015-01-01

    Odonata are freshwater insects spread world-wide. Tropical areas are high Odonata diversity areas. However, there has not been accumulation of extensive baseline data on spatial distribution of these insects from such places. Maharashtra, the third largest state of India, harbors a variety of land-use and occupies six biogeographic provinces. We carried out Odonata surveys in Maharashtra during 2006-2014. Compilation of all these studies along with other authenticated records resulted in a checklist of 134 species of Odonata belonging to 70 genera representing 11 families. The highest numbers of species were recorded from the Libellulidae (48 species) and Gomphidae (22 species) families. A previous study had reported 99 species of Odonata from the Maharashtra state considering records from early 1900's to 2012. Our observations across the state add 33 species to this list. Maharashtra forms a unique source of Odonata diversity and our observations support the importance of this region in providing valuable habitats for Odonata. Here, we discuss several of the new records, how global surveys might help fill the local gap in species distributions, how secondary data deposited through crowd-sourcing can help and what it offers to conservation.

  3. Tardigrades of Alaska: distribution patterns, diversity and species richness

    Directory of Open Access Journals (Sweden)

    Carl Johansson

    2013-05-01

    Full Text Available During the summer of 2010, a biotic survey of tardigrades was conducted along a latitudinal transect in central Alaska from the Kenai Peninsula, via Fairbanks and the Arctic Circle to the coastal plain. Work was centred at the Toolik and Bonanza Creek Long Term Ecological Research Network sites and supplemented by opportunistic collections from the Kenai Peninsula and Anchorage areas. The 235 samples collected at 20 sites over 10 degrees of latitude yielded 1463 tardigrades representing two classes, three orders, 10 families, 23 genera and 73 species from 142 positive samples. A total of 50 species are new to Alaska, increasing the state's known species richness to 84. Several environmental metrics, such as pH, substrate, elevation, location and habitat were measured, recorded and analysed along the latitudinal gradient. Contrary to expectations, pH did not appear to be a predictor of tardigrade abundance or distribution. Density and species richness were relatively consistent across sites. However, the assemblages were highly variable within and between sites at only 14–20% similarity. We detected no correlation between species diversity and latitudinal or environmental gradients, though this may be affected by a high (59.9% occurrence of single-species samples (containing individuals of only one species. Estimates of species richness were calculated for Alaska (118 and the Arctic (172. Our efforts increased the number of known species in Alaska to 84, and those results led us to question the validity of the estimate numbers.

  4. 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.

  5. A collection of Australian Drosophila datasets on climate adaptation and species distributions.

    Science.gov (United States)

    Hangartner, Sandra B; Hoffmann, Ary A; Smith, Ailie; Griffin, Philippa C

    2015-11-24

    The Australian Drosophila Ecology and Evolution Resource (ADEER) collates Australian datasets on drosophilid flies, which are aimed at investigating questions around climate adaptation, species distribution limits and population genetics. Australian drosophilid species are diverse in climatic tolerance, geographic distribution and behaviour. Many species are restricted to the tropics, a few are temperate specialists, and some have broad distributions across climatic regions. Whereas some species show adaptability to climate changes through genetic and plastic changes, other species have limited adaptive capacity. This knowledge has been used to identify traits and genetic polymorphisms involved in climate change adaptation and build predictive models of responses to climate change. ADEER brings together 103 datasets from 39 studies published between 1982-2013 in a single online resource. All datasets can be downloaded freely in full, along with maps and other visualisations. These historical datasets are preserved for future studies, which will be especially useful for assessing climate-related changes over time.

  6. Species and Distribution of Mangroves in the Fujian Coastal Area

    Institute of Scientific and Technical Information of China (English)

    王文卿; 赵萌莉; 邓传远; 林鹏

    2001-01-01

    On the basis of an investigation on the mangroves in Fujian from November 1998 to January 1999, the species composition, area, distribution, artificial afforestation of mangroves and the factors restricting the development of mangroves in Fujian are discussed in the paper. Some suggestions on how to develop mangroves in Fujian have been put forward.

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

    African Journals Online (AJOL)

    Yomi

    2012-01-24

    Jan 24, 2012 ... tree species in Turkey via Shuttle Radar Topography. Mission ... and 1/100,000 scale Forest Information System database, horizontal and vertical distribution of Pinus .... southern parts of the country, in Thrace, and also near some large ... Initially, infrared aerial photographs of the area at 1/15,000 scale.

  8. 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.

  9. Diversity, distribution and conservation of Chinese seagrass species

    Directory of Open Access Journals (Sweden)

    Fengying Zheng

    2013-09-01

    Full Text Available Seagrass beds are one of the most productive ecosystems on Earth and an important source of ecosystem services. Accurate mapping of spatial patterns of seagrass species diversity are lacking at the national scale in China, while taxonomic information on Chinese seagrass species requires an urgent update. This lack of information hinders national conservation and restoration programs for seagrass biodiversity. In this article we review studies of diversity, distributions and degradation of seagrass in China. A total of 22 seagrass species distributed along China’s coastal regions belong to ten genera and four families, and account for about 30% of known seagrass species worldwide. A check of herbarium material stored in Sun Yat-sen University showed that the seagrass species previously identified as Posidonia australis in Hainan is in fact Enhalus acoroides. From our analyses, two Chinese seagrass biotas are proposed. These include the South China Sea Bioregion (SCSBR and China’s Yellow Sea and Bohai Sea Bioregion (CYSBSBR. The SCSBR includes Hainan, Guangxi, Guangdong, Hongkong, Taiwan and Fujian provinces, and contains 15 seagrass species representing nine genera with Halophila ovalis being most widely distributed. The CYSBSBR includes Shandong, Hebei, Tianjin and Liaonin provinces and contains nine seagrass species belonging to three genera with Zostera marina being most widely distributed. The total distribution area for China’s seagrass meadows is estimated to be 8,765.1 ha, with Hainan, Guangdong and Guangxi provinces accounting for 64%, 11% and 10% of the area, respectively. Both the number and area of seagrass meadows are much higher in the SCSBR than in the CYSBSBR. In the SCSBR, seagrass meadows are mainly located in the eastern Hainan coast, Zhanjiang in Guangdong, Beihai in Guangxi and Dongsha Island in Taiwan, whereas in the CYSBSBR they predominate in Rongcheng in Shandong and Changhai in Liaoning. Halophila ovalis, Thalassia

  10. 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.

  11. 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

  12. Potential distribution of mosquito vector species in a primary malaria endemic region of Colombia.

    Science.gov (United States)

    Altamiranda-Saavedra, Mariano; Arboleda, Sair; Parra, Juan L; Peterson, A Townsend; Correa, Margarita M

    2017-01-01

    Rapid transformation of natural ecosystems changes ecological conditions for important human disease vector species; therefore, an essential task is to identify and understand the variables that shape distributions of these species to optimize efforts toward control and mitigation. Ecological niche modeling was used to estimate the potential distribution and to assess hypotheses of niche similarity among the three main malaria vector species in northern Colombia: Anopheles nuneztovari, An. albimanus, and An. darlingi. Georeferenced point collection data and remotely sensed, fine-resolution satellite imagery were integrated across the Urabá -Bajo Cauca-Alto Sinú malaria endemic area using a maximum entropy algorithm. Results showed that An. nuneztovari has the widest geographic distribution, occupying almost the entire study region; this niche breadth is probably related to the ability of this species to colonize both, natural and disturbed environments. The model for An. darlingi showed that most suitable localities for this species in Bajo Cauca were along the Cauca and Nechí river. The riparian ecosystems in this region and the potential for rapid adaptation by this species to novel environments, may favor the establishment of populations of this species. Apparently, the three main Colombian Anopheles vector species in this endemic area do not occupy environments either with high seasonality, or with low seasonality and high NDVI values. Estimated overlap in geographic space between An. nuneztovari and An. albimanus indicated broad spatial and environmental similarity between these species. An. nuneztovari has a broader niche and potential distribution. Dispersal ability of these species and their ability to occupy diverse environmental situations may facilitate sympatry across many environmental and geographic contexts. These model results may be useful for the design and implementation of malaria species-specific vector control interventions optimized for

  13. 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.

  14. Biotic Interactions Shape the Ecological Distributions of Staphylococcus Species

    Directory of Open Access Journals (Sweden)

    Erik K. Kastman

    2016-10-01

    Full Text Available 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.

  15. 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...

  16. Quasispecies distribution of Eigen model

    Institute of Scientific and Technical Information of China (English)

    Chen Jia; Li Sheng; Ma Hong-Ru

    2007-01-01

    We have studied sharp peak landscapes of the Eigen model from a new perspective about how the quasispecies are distributed in the sequence space. To analyse the distribution more carefully, we bring in two tools. One tool is the variance of Hamming distance of the sequences at a given generation. It not only offers us a different avenue for accurately locating the error threshold and illustrates how the configuration of the distribution varies with copying fidelity q in the sequence space, but also divides the copying fidelity into three distinct regimes. The other tool is the similarity network of a certain Hamming distance do, by which we can gain a visual and in-depth result about how the sequences are distributed. We find that there are several local similarity optima around the centre (global similarity optimum) in the distribution of the sequences reproduced near the threshold. Furthermore, it is interesting that the distribution of clustering coefficient C(k) follows lognormal distribution and the curve of clustering coefficient C of the network versus d0 appears to be linear near the threshold.

  17. Quasispecies distribution of Eigen model

    Science.gov (United States)

    Chen, Jia; Li, Sheng; Ma, Hong-Ru

    2007-09-01

    We have studied sharp peak landscapes of the Eigen model from a new perspective about how the quasispecies are distributed in the sequence space. To analyse the distribution more carefully, we bring in two tools. One tool is the variance of Hamming distance of the sequences at a given generation. It not only offers us a different avenue for accurately locating the error threshold and illustrates how the configuration of the distribution varies with copying fidelity q in the sequence space, but also divides the copying fidelity into three distinct regimes. The other tool is the similarity network of a certain Hamming distance d0, by which we can gain a visual and in-depth result about how the sequences are distributed. We find that there are several local similarity optima around the centre (global similarity optimum) in the distribution of the sequences reproduced near the threshold. Furthermore, it is interesting that the distribution of clustering coefficient C(k) follows lognormal distribution and the curve of clustering coefficient C of the network versus d0 appears to be linear near the threshold.

  18. 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...... to habitat type, their amphibious life cycle, and the ease of identification of the adult, combined with the good knowledge of their distribution and ecological requirement, make dragonfly species particularly well suited for studying effects of climate change and human land-use in the short term — which...... species to persist while others decline? In this context, the main objective of my research was to investigate how current climate change and human land-use shape large scale distribution patterns of European dragonflies and whether these macroecological pattern and changes can be linked to functional...

  19. Grinnellian and Eltonian niches and geographic distributions of species.

    Science.gov (United States)

    Soberón, Jorge

    2007-12-01

    In the recent past, availability of large data sets of species presences has increased by orders of magnitude. This, together with developments in geographical information systems and statistical methods, has enabled scientists to calculate, for thousands of species, the environmental conditions of their distributional areas. The profiles thus obtained are obviously related to niche concepts in the Grinnell tradition, and separated from those in Elton's tradition. I argue that it is useful to define Grinnellian and Eltonian niches on the basis of the types of variables used to calculate them, the natural spatial scale at which they can be measured, and the dispersal of the individuals over the environment. I use set theory notation and analogies derived from population ecology theory to obtain formal definitions of areas of distribution and several types of niches. This brings clarity to several practical and fundamental questions in macroecology and biogeography.

  20. LogCauchy, log-sech and lognormal distributions of species abundances in forest communities

    Science.gov (United States)

    Yin, Z.-Y.; Peng, S.-L.; Ren, H.; Guo, Q.; Chen, Z.-H.

    2005-01-01

    Species-abundance (SA) pattern is one of the most fundamental aspects of biological community structure, providing important information regarding species richness, species-area relation and succession. To better describe the SA distribution (SAD) in a community, based on the widely used lognormal (LN) distribution model with exp(-x2) roll-off on Preston's octave scale, this study proposed two additional models, logCauchy (LC) and log-sech (LS), respectively with roll-offs of simple x-2 and e-x. The estimation of the theoretical total number of species in the whole community, S*, including very rare species not yet collected in sample, was derived from the left-truncation of each distribution. We fitted these three models by Levenberg-Marquardt nonlinear regression and measured the model fit to the data using coefficient of determination of regression, parameters' t-test and distribution's Kolmogorov-Smirnov (KS) test. Examining the SA data from six forest communities (five in lower subtropics and one in tropics), we found that: (1) on a log scale, all three models that are bell-shaped and left-truncated statistically adequately fitted the observed SADs, and the LC and LS did better than the LN; (2) from each model and for each community the S* values estimated by the integral and summation methods were almost equal, allowing us to estimate S* using a simple integral formula and to estimate its asymptotic confidence internals by regression of a transformed model containing it; (3) following the order of LC, LS, and LN, the fitted distributions became lower in the peak, less concave in the side, and shorter in the tail, and overall the LC tended to overestimate, the LN tended to underestimate, while the LS was intermediate but slightly tended to underestimate, the observed SADs (particularly the number of common species in the right tail); (4) the six communities had some similar structural properties such as following similar distribution models, having a common

  1. 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...... on presence data. The aim was to identify potential hot spot areas, assess the determinants of palm distribution ranges, and provide a firmer knowledge base for future conservation actions. We focused on a relatively small number of climatic, environmental and spatial variables in order to avoid...... overprediction of species distribution ranges. The models with the best predictive power were found by calculating the area under the curve (AUC) of receiver-operating characteristic (ROC). Here, we provide examples of contrasting predicted species distribution ranges as well as a map of modeled palm diversity...

  2. 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.

  3. pH-distribution of cerium species in aqueous systems

    Institute of Scientific and Technical Information of China (English)

    B.Bouchaud; J.Balmain; G.Bonnet; F.Pedraza

    2012-01-01

    Cerium-based oxide coalings can be obtained through either chemical or electrochemical processes on various conductor and semiconductor substrates.In both cases the films develop through a precipitation mechanism,which strongly depends on the solution chemistry.In the particular case of the electrolytic approach,the elaboration parameters play a key role on the interfacial pH modification thereby leading to an indirect precipitation mechanism.Indeed,the nucleation and growth mechanisms of crystallites and the composition of the resulting layers have been shown to be also strongly affected by the deposition conditions as well as by the substrate composition,which could in turn modify the protectiveness provided by such coatings.Therefore a better fundamental understanding of the system is required,in particular of the distribution of cerium-containing species in aqueous solution.To this end,the present work intended to develop a diagram showing the distribution as well as the relative amount of Ce(Ⅲ)/Ce(Ⅳ) species in aqueous media as a function of the pH range.The resulting pH-distribution diagram turned out to be a useful tool to predict the relevant precipitation mechanisms and species involved during the growth of cerium-containing films and to draw correlations with the characteristics of the as-deposited films.

  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. 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

  6. 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-...

  7. Modelling biological invasions: species traits, species interactions, and habitat heterogeneity.

    Science.gov (United States)

    Cannas, Sergio A; Marco, Diana E; Páez, Sergio A

    2003-05-01

    In this paper we explore the integration of different factors to understand, predict and control ecological invasions, through a general cellular automaton model especially developed. The model includes life history traits of several species in a modular structure interacting multiple cellular automata. We performed simulations using field values corresponding to the exotic Gleditsia triacanthos and native co-dominant trees in a montane area. Presence of G. triacanthos juvenile bank was a determinant condition for invasion success. Main parameters influencing invasion velocity were mean seed dispersal distance and minimum reproductive age. Seed production had a small influence on the invasion velocity. Velocities predicted by the model agreed well with estimations from field data. Values of population density predicted matched field values closely. The modular structure of the model, the explicit interaction between the invader and the native species, and the simplicity of parameters and transition rules are novel features of the model.

  8. Retrieval of Temperature and Species Distributions from Multispectral Image Data of Surface Flame Spread in Microgravity

    Science.gov (United States)

    Annen, K. D.; Conant, John A.; Weiland, Karen J.

    2001-01-01

    Weight, size, and power constraints severely limit the ability of researchers to fully characterize temperature and species distributions in microgravity combustion experiments. A powerful diagnostic technique, infrared imaging spectrometry, has the potential to address the need for temperature and species distribution measurements in microgravity experiments. An infrared spectrum imaged along a line-of-sight contains information on the temperature and species distribution in the imaged path. With multiple lines-of-sight and approximate knowledge of the geometry of the combustion flowfield, a three-dimensional distribution of temperature and species can be obtained from one hyperspectral image of a flame. While infrared imaging spectrometers exist for collecting hyperspectral imagery, the remaining challenge is retrieving the temperature and species information from this data. An initial version of an infrared analysis software package, called CAMEO (Combustion Analysis Model et Optimizer), has been developed for retrieving temperature and species distributions from hyperspectral imaging data of combustion flowfields. CAMEO has been applied to the analysis of multispectral imaging data of flame spread over a PMMA surface in microgravity that was acquired in the DARTFire program. In the next section of this paper, a description of CAMEO and its operation is presented, followed by the results of the analysis of microgravity flame spread data.

  9. 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.

  10. Climatic Control on Forests and Tree Species Distribution in the Forest Region of Northeast China

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    North-east (NE) China covers considerable climatic gradients and all major forests types of NE Asia. In the present study, 10 major forest types across the forest region of NE China were sampled to investigate forest distribution in relation to climate. Canonical correspondence analysis (CCA) revealed that growing season precipitation and energy availability were primary climatic factors for the overall forest pattern of NE China, accounting for 66% of the explanatory power of CCA. Conversely, annual precipitation and winter coldness had minor effects. Generalized additive models revealed that tree species responded to climatic gradients differently and showed three types of response curve: (i) monotonous decline; (ii) monotonous increase; and (iii) a unimodal pattern. Furthermore, tree species showed remarkable differences in limiting climatic factors for their distribution. The power of climate in explaining species distribution declined significantly with decreasing species dominance, suggesting that the distribution of dominant species was primarily controlled by climate, whereas that of subordinate species was more affected by competition from other species.

  11. Modeling utilization distributions in space and time.

    Science.gov (United States)

    Keating, Kim A; Cherry, Steve

    2009-07-01

    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.

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

    OpenAIRE

    Paulo Silva de Almeida; Andrey José de Andrade; Alan Sciamarelli; Josué Raizer; Jaqueline Aparecida Menegatti; Sandra Cristina Negreli Moreira Hermes; Maria do Socorro Laurentino de Carvalho; Rodrigo Gurgel-Gonçalves

    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 a...

  13. 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.

  14. 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.

  15. 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.

  16. Numerical investigation of the spatiotemporal distribution of chemical species in an atmospheric surface barrier-discharge

    Science.gov (United States)

    Hasan, M. I.; Walsh, J. L.

    2016-05-01

    Using a one dimensional time dependent convection-reaction-diffusion model, the temporal and spatial distributions of species propagating downstream of an atmospheric pressure air surface barrier discharge was studied. It was found that the distribution of negatively charged species is more spatially spread compared to positive ions species, which is attributed to the diffusion of electrons that cool down and attach to background gas molecules, creating different negative ions downstream of the discharge region. Given the widespread use of such discharges in applications involving the remote microbial decontamination of surfaces and liquids, the transport of plasma generated reactive species away from the discharge region was studied by implementing mechanical convection through the discharge region. It was shown that increased convection causes the spatial distribution of species density to become uniform. It was also found that many species have a lower density close to the surface of the discharge as convection prevents their accumulation. While for some species, such as NO2, convection causes a general increase in the density due to a reduced residence time close to the discharge region, where it is rapidly lost through reactions with OH. The impact of the applied power was also investigated, and it was found that the densities of most species, whether charged or neutral, are directly proportional to the applied power.

  17. 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

  18. 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

  19. Beyond a Climate-Centric View of Plant Distribution: Edaphic Variables Add Value to Distribution Models

    Science.gov (United States)

    Beauregard, Frieda; de Blois, Sylvie

    2014-01-01

    Both climatic and edaphic conditions determine plant distribution, however many species distribution models do not include edaphic variables especially over large geographical extent. Using an exceptional database of vegetation plots (n = 4839) covering an extent of ∼55000 km2, we tested whether the inclusion of fine scale edaphic variables would improve model predictions of plant distribution compared to models using only climate predictors. We also tested how well these edaphic variables could predict distribution on their own, to evaluate the assumption that at large extents, distribution is governed largely by climate. We also hypothesized that the relative contribution of edaphic and climatic data would vary among species depending on their growth forms and biogeographical attributes within the study area. We modelled 128 native plant species from diverse taxa using four statistical model types and three sets of abiotic predictors: climate, edaphic, and edaphic-climate. Model predictive accuracy and variable importance were compared among these models and for species' characteristics describing growth form, range boundaries within the study area, and prevalence. For many species both the climate-only and edaphic-only models performed well, however the edaphic-climate models generally performed best. The three sets of predictors differed in the spatial information provided about habitat suitability, with climate models able to distinguish range edges, but edaphic models able to better distinguish within-range variation. Model predictive accuracy was generally lower for species without a range boundary within the study area and for common species, but these effects were buffered by including both edaphic and climatic predictors. The relative importance of edaphic and climatic variables varied with growth forms, with trees being more related to climate whereas lower growth forms were more related to edaphic conditions. Our study identifies the potential for

  20. 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

  1. Species clustering in competitive Lotka-Volterra models.

    Science.gov (United States)

    Pigolotti, Simone; López, Cristóbal; Hernández-García, Emilio

    2007-06-22

    We study the properties of general Lotka-Volterra models with competitive interactions. The intensity of the competition depends on the position of species in an abstract niche space through an interaction kernel. We show analytically and numerically that the properties of these models change dramatically when the Fourier transform of this kernel is not positive definite, due to a pattern-forming instability. We estimate properties of the species distributions, such as the steady number of species and their spacings, for different types of interactions, including stretched exponential and constant kernels.

  2. Modeling considerations for using expression data from multiple species.

    Science.gov (United States)

    Siewert, Elizabeth; Kechris, Katerina J

    2013-10-15

    Although genome-wide expression data sets from multiple species are now more commonly generated, there have been few studies on how to best integrate this type of correlated data into models. Starting with a single-species, linear regression model that predicts transcription factor binding sites as a case study, we investigated how best to take into account the correlated expression data when extending this model to multiple species. Using a multivariate regression model, we accounted for the phylogenetic relationships among the species in two ways: (i) a repeated-measures model, where the error term is constrained; and (ii) a Bayesian hierarchical model, where the prior distributions of the regression coefficients are constrained. We show that both multiple-species models improve predictive performance over the single-species model. When compared with each other, the repeated-measures model outperformed the Bayesian model. We suggest a possible explanation for the better performance of the model with the constrained error term. Copyright © 2013 John Wiley & Sons, Ltd.

  3. Functional traits, drought performance, and the distribution of tree species in tropical forests of Ghana

    NARCIS (Netherlands)

    Amissah, L.

    2014-01-01

      Tropical forests occur along a rainfall gradient where annual amount, the length and intensity of dry season vary and water availability shapes therefore strongly the distribution of tree species. Annual rainfall in West Africa has declined at a rate of 4% per decade, and climate change model

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

    Directory of Open Access Journals (Sweden)

    Paulo Silva de Almeida

    2015-06-01

    Full Text Available 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 longipalpiswere 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.

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

    Science.gov (United States)

    Almeida, Paulo Silva de; Andrade, Andrey José de; Sciamarelli, Alan; Raizer, Josué; Menegatti, Jaqueline Aparecida; Hermes, Sandra Cristina Negreli Moreira; Carvalho, Maria do Socorro Laurentino de; Gurgel-Gonçalves, Rodrigo

    2015-06-01

    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.

  6. Environmental niche divergence among three dune shrub sister species with parapatric distributions.

    Science.gov (United States)

    Chozas, Sergio; Chefaoui, Rosa M; Correia, Otília; Bonal, Raúl; Hortal, Joaquín

    2017-05-01

    The geographical distributions of species are constrained by their ecological requirements. The aim of this work was to analyse the effects of environmental conditions, historical events and biogeographical constraints on the diversification of the three species of the western Mediterranean shrub genus Stauracanthus , which have a parapatric distribution in the Iberian Peninsula. Ecological niche factor analysis and generalized linear models were used to measure the response of all Stauracanthus species to the environmental gradients and map their potential distributions in the Iberian Peninsula. The bioclimatic niche overlap between the three species was determined by using Schoener's index. The genetic differentiation of the Iberian and northern African populations of Stauracanthus species was characterized with GenalEx. The effects on genetic distances of the most important environmental drivers were assessed through Mantel tests and non-metric multidimensional scaling. The three Stauracanthus species show remarkably similar responses to climatic conditions. This supports the idea that all members of this recently diversified clade retain common adaptations to climate and consequently high levels of climatic niche overlap. This contrasts with the diverse edaphic requirements of Stauracanthus species. The populations of the S. genistoides-spectabilis clade grow on Miocene and Pliocene fine-textured sedimentary soils, whereas S. boivinii , the more genetically distant species, occurs on older and more coarse-textured sedimentary substrates. These patterns of diversification are largely consistent with a stochastic process of geographical range expansion and fragmentation coupled with niche evolution in the context of spatially complex environmental fluctuations. : The combined analysis of the distribution, realized environmental niche and phylogeographical relationships of parapatric species proposed in this work allows integration of the biogeographical

  7. 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.

  8. Seagrass species distribution, density and coverage at Panggang Island, Jakarta

    Science.gov (United States)

    Wahab, Iswandi; Madduppa, Hawis; Kawaroe, Mujizat

    2017-01-01

    This study aimed to assess species distribution, density and coverage of seagrass in Panggang Island, within Kepulauan Seribu Marine National Park, northern Jakarta. Seagrass sampling was conducted between March to April 2016 at three observation stations in the West, East, and South of Panggang Island. A total of 6 seagrass species was recorded during sampling period, including Cymodocea rotundata, C. serulata, Halodule uninervis, Syiringodium isoetifolium, Enhalus acoroides, and Thalassia hempricii. All species were observed in the South station, while in the West and East station found only three species (C. rotundata, E. acoroides, and T. hemprichii). While, C. rotundata and T. hemprichii were observed at all station. The highest density was observed for C. rotundata (520 ind/m2) and for T. hempricii (619 ind/m2) in the West station and South Station, respectively. The lowest density was observed in South Station for C. serulata (18 ind/m2), Halodule uninervis (20 ind/m2), and Syiringodium isoetifolium (15 ind/m2). Seagrass coverage of Thalassia hempricii was the highest (43.60%) and the lowest observed at Syiringodium isoetifolium (0.40%). This could be basic information for the management of seagrass ecosystem in the Kepulauan Seribu Marine National Park.

  9. 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.

  10. On the statistical mechanics of species abundance distributions.

    Science.gov (United States)

    Bowler, Michael G; Kelly, Colleen K

    2012-09-01

    A central issue in ecology is that of the factors determining the relative abundance of species within a natural community. The proper application of the principles of statistical physics to species abundance distributions (SADs) shows that simple ecological properties could account for the near universal features observed. These properties are (i) a limit on the number of individuals in an ecological guild and (ii) per capita birth and death rates. They underpin the neutral theory of Hubbell (2001), the master equation approach of Volkov et al. (2003, 2005) and the idiosyncratic (extreme niche) theory of Pueyo et al. (2007); they result in an underlying log series SAD, regardless of neutral or niche dynamics. The success of statistical mechanics in this application implies that communities are in dynamic equilibrium and hence that niches must be flexible and that temporal fluctuations on all sorts of scales are likely to be important in community structure.

  11. 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

  12. Rainfall seasonality and pest pressure as determinants of tropical tree species' distributions

    OpenAIRE

    2012-01-01

    Drought and pests are primary abiotic and biotic factors proposed as selective filters acting on species distributions along rainfall gradients in tropical forests and may contribute importantly to species distributional limits, performance, and diversity gradients. Recent research demonstrates linkages between species distributions along rainfall gradients and physiological drought tolerance; corresponding experimental examinations of the contribution of pest pressure to distributional limit...

  13. Ising model for distribution networks

    CERN Document Server

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

    2012-01-01

    An elementary Ising spin model is proposed for demonstrating cascading failures (break-downs, blackouts, collapses, avalanches, ...) 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 solidary 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 t...

  14. Distributed Object Medical Imaging Model

    CERN Document Server

    Noor, Ahmad Shukri Mohd

    2009-01-01

    Digital medical informatics and images are commonly used in hospitals today,. Because of the interrelatedness of the radiology department and other departments, especially the intensive care unit and emergency department, the transmission and sharing of medical images has become a critical issue. Our research group has developed a Java-based Distributed Object Medical Imaging Model(DOMIM) to facilitate the rapid development and deployment of medical imaging applications in a distributed environment that can be shared and used by related departments and mobile physiciansDOMIM is a unique suite of multimedia telemedicine applications developed for the use by medical related organizations. The applications support realtime patients' data, image files, audio and video diagnosis annotation exchanges. The DOMIM enables joint collaboration between radiologists and physicians while they are at distant geographical locations. The DOMIM environment consists of heterogeneous, autonomous, and legacy resources. The Common...

  15. 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.

  16. 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

  17. Are range-size distributions consistent with species-level heritability?

    DEFF Research Database (Denmark)

    Borregaard, Michael Krabbe; Gotelli, Nicholas; Rahbek, Carsten

    2012-01-01

    been that it is not compatible with the observed shape of present-day species range-size distributions (SRDs), a claim that has never been tested. To assess this claim, we used forward simulation of range-size evolution in clades with varying degrees of range-size heritability, and compared the output...... of three different models to the range-size distribution of the South American avifauna. Although there were differences among the models, a moderate-to-high degree of range-size heritability consistently leads to SRDs that were similar to empirical data. These results suggest that range-size heritability......The concept of species-level heritability is widely contested. Because it is most likely to apply to emergent, species-level traits, one of the central discussions has focused on the potential heritability of geographic range size. However, a central argument against range-size heritability has...

  18. 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

  19. 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.

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

    Science.gov (United States)

    Hageer, Yasmin; Esperón-Rodríguez, Manuel; Baumgartner, John B; Beaumont, Linda J

    2017-01-01

    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. 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. 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. 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.

  1. From projected species distribution to food-web structure under climate change.

    Science.gov (United States)

    Albouy, Camille; Velez, Laure; Coll, Marta; Colloca, Francesco; Le Loc'h, François; Mouillot, David; Gravel, Dominique

    2014-03-01

    Climate change is inducing deep modifications in species geographic ranges worldwide. However, the consequences of such changes on community structure are still poorly understood, particularly the impacts on food-web properties. Here, we propose a new framework, coupling species distribution and trophic models, to predict climate change impacts on food-web structure across the Mediterranean Sea. Sea surface temperature was used to determine the fish climate niches and their future distributions. Body size was used to infer trophic interactions between fish species. Our projections reveal that 54 fish species of 256 endemic and native species included in our analysis would disappear by 2080-2099 from the Mediterranean continental shelf. The number of feeding links between fish species would decrease on 73.4% of the continental shelf. However, the connectance of the overall fish web would increase on average, from 0.26 to 0.29, mainly due to a differential loss rate of feeding links and species richness. This result masks a systematic decrease in predator generality, estimated here as the number of prey species, from 30.0 to 25.4. Therefore, our study highlights large-scale impacts of climate change on marine food-web structure with potential deep consequences on ecosystem functioning. However, these impacts will likely be highly heterogeneous in space, challenging our current understanding of climate change impact on local marine ecosystems.

  2. Predators modify biogeographic constraints on species distributions in an insect metacommunity.

    Science.gov (United States)

    Grainger, Tess Nahanni; Germain, Rachel M; Jones, Natalie T; Gilbert, Benjamin

    2017-03-01

    Theory describing the positive effects of patch size and connectivity on diversity in fragmented systems has stimulated a large body of empirical work, yet predicting when and how local species interactions mediate these responses remains challenging. We used insects that specialize on milkweed plants as a model metacommunity to investigate how local predation alters the effects of biogeographic constraints on species distributions. Species-specific dispersal ability and susceptibility to predation were used to predict when patch size and connectivity should shape species distributions, and when these should be modified by local predator densities. We surveyed specialist herbivores and their predators in milkweed patches in two matrix types, a forest and an old field. Predator-resistant species showed the predicted direct positive effects of patch size and connectivity on occupancy rates. For predator-susceptible species, predators consistently altered the impact of biogeographic constraints, rather than acting independently. Finally, differences between matrix types in species' responses and overall occupancy rates indicate a potential role of the inter-patch environment in mediating the joint effects of predators and spatial drivers. Together, these results highlight the importance of local top-down pressure in mediating classic biogeographic relationships, and demonstrate how species-specific responses to local and regional constraints can be used to predict these effects. © 2017 by the Ecological Society of America.

  3. Biodiversity and the Lotka-Volterra theory of species interactions: open systems and the distribution of logarithmic densities.

    Science.gov (United States)

    Wilson, William G; Lundberg, Per

    2004-09-22

    Theoretical interest in the distributions of species abundances observed in ecological communities has focused recently on the results of models that assume all species are identical in their interactions with one another, and rely upon immigration and speciation to promote coexistence. Here we examine a one-trophic level system with generalized species interactions, including species-specific intraspecific and interspecific interaction strengths, and density-independent immigration from a regional species pool. Comparisons between results from numerical integrations and an approximate analytic calculation for random communities demonstrate good agreement, and both approaches yield abundance distributions of nearly arbitrary shape, including bimodality for intermediate immigration rates.

  4. [Biology, species biodiversity and distribution of Trichinella nematodes].

    Science.gov (United States)

    Moskwa, Bozena

    2006-01-01

    From the time of the discovery of Trichinella larvae in 1835 until the middle of the next century it was commonly assumed that all trichinellosis was caused by a single species Trichinella spiralis. This species is an intracellular parasite in both a larva and an adult stage. The L1 larvae live in a modified skeletal muscles. The adult worms occupy a membrane-bound portion of columnar epitelium, living as intramulticellular parasite. More than century later T. spiralis have been reported from more than 150 different naturally or experimentally infected hosts and demonstrated worldwide distribution in domestic and/or sylvatic animals. Up to date, Trichinella genus comprised eight species (T. spiralis, T. nativa, T. britovi, T. murrelli, T. nelsoni, T. pseudospiralis, T. papuae and T. zimbabwensisi) and three additional genotypic variants that have not yet to be taxonomically defined (T6, T8, T9). Molecular markers revealed that Trichinella T6 is related to T. nativa, Trichinella T8 related to T. britovi. Two main clades are recognized in the genus Trichinella: the first encapsulated in host muscle tissue and the second--non-encapsulated. In this paper the history of Trichinella spp. discovery, their life cycle, taxonomy and phylogeny have been reviewed.

  5. [Candidemia in Pediatrics: Species distribution and antifungal susceptibility].

    Science.gov (United States)

    Guzzetti, Luciana B; Vescina, Cecilia M; Gil, M Florencia; Gatti, Blanca M

    2017-07-19

    Serious infections caused by Candida yeasts are frequent in the hospital population. Due to differences in species distribution and antifungal susceptibility testing depending on the geographic area and the type of patient, it is important to study the epidemiology of each institution. For this purpose, we conducted a retrospective, descriptive study on the occurrence of candidemia in the Children's Hospital "Superiora Sor María Ludovica" of the city of La Plata. In a 6-year period (2010-2015), 177 candidemia episodes were recorded. The predominant species were Candida albicans (45%) and Candida parapsilosis (28%). The hospital wards with the highest number of candidemia episodes were the pediatric, neonatal and cardiovascular intensive care units (58%). No resistance to amphotericin B was observed throughout the period whereas resistance to azoles was limited to 4 strains of less frequent species. Copyright © 2017 Asociación Argentina de Microbiología. Publicado por Elsevier España, S.L.U. All rights reserved.

  6. Distributed Object Medical Imaging Model

    Directory of Open Access Journals (Sweden)

    Ahmad Shukri Mohd Noor

    2009-09-01

    Full Text Available Digital medical informatics and images are commonly used in hospitals today. Because of the interrelatedness of the radiology department and other departments, especially the intensive care unit and emergency department, the transmission and sharing of medical images has become a critical issue. Our research group has developed a Java-based Distributed Object Medical Imaging Model(DOMIM to facilitate the rapid development and deployment of medical imaging applications in a distributed environment that can be shared and used by related departments and mobile physiciansDOMIM is a unique suite of multimedia telemedicine applications developed for the use by medical related organizations. The applications support realtime patients' data, image files, audio and video diagnosis annotation exchanges. The DOMIM enables joint collaboration between radiologists and physicians while they are at distant geographical locations. The DOMIM environment consists of heterogeneous, autonomous, and legacy resources. The Common Object Request Broker Architecture (CORBA, Java Database Connectivity (JDBC, and Java language provide the capability to combine the DOMIM resources into an integrated, interoperable, and scalable system. The underneath technology, including IDL ORB, Event Service, IIOP JDBC/ODBC, legacy system wrapping and Java implementation are explored. This paper explores a distributed collaborative CORBA/JDBC based framework that will enhance medical information management requirements and development. It encompasses a new paradigm for the delivery of health services that requires process reengineering, cultural changes, as well as organizational changes.

  7. Species Abundance Distribution of Ectoparasites on Norway rats (Rattus norvegicus from a Localized Area in Southwest China

    Directory of Open Access Journals (Sweden)

    Xian Guo Guo

    2016-01-01

    Full Text Available Background: The species of ectoparasites that live on a specific host in a geographical region form an ectoparasite community. Species abundance distributions describe the number of individuals observed for each different species that is encountered within a community. Based on properties of the species abundance distribution, the expected total number of species present in the community can be estimated.Methods: Preston’s lognormal distribution model was used to fit the expected species abundance distribution curve. Using the expected species abundance distribution curve, we estimated the total number of expected parasite species present and the amount of species that were likely missed by our sampling in the field.Results: In total, 8040 ectoparasites (fleas, sucking lice, gamasid mites and chigger mites were collected from 431 Norway rats (Rattus norvegicus from a localized area in southwest China. These ectoparasites were identified to be 47 species from 26 genera in 10 families. The majority of ectoparasite species were chigger mites (family Trombicu­lidae while the majority of individuals were sucking lice in the family Polyplacidae. The expected species abun­dance distribution curve demonstrated the classic pattern that the majority of ectoparasite species were rare and that there were a few common species. The total expected number of ectoparasite species on R. norvegicus was estimated to be 85 species, and 38 species were likely missed by our sampling in the field.Conclusions: Norway rats harbor a large suite of ectoparasites. Future field investigations should sample large num­bers of host individuals to assess ectoparasite populations.

  8. Incorporating abundance information and guiding variable selection for climate-based ensemble forecasting of species' distributional shifts

    Science.gov (United States)

    2017-01-01

    Ecological niche models (ENMs) have increasingly been used to estimate the potential effects of climate change on species’ distributions worldwide. Recently, predictions of species abundance have also been obtained with such models, though knowledge about the climatic variables affecting species abundance is often lacking. To address this, we used a well-studied guild (temperate North American quail) and the Maxent modeling algorithm to compare model performance of three variable selection approaches: correlation/variable contribution (CVC), biological (i.e., variables known to affect species abundance), and random. We then applied the best approach to forecast potential distributions, under future climatic conditions, and analyze future potential distributions in light of available abundance data and presence-only occurrence data. To estimate species’ distributional shifts we generated ensemble forecasts using four global circulation models, four representative concentration pathways, and two time periods (2050 and 2070). Furthermore, we present distributional shifts where 75%, 90%, and 100% of our ensemble models agreed. The CVC variable selection approach outperformed our biological approach for four of the six species. Model projections indicated species-specific effects of climate change on future distributions of temperate North American quail. The Gambel’s quail (Callipepla gambelii) was the only species predicted to gain area in climatic suitability across all three scenarios of ensemble model agreement. Conversely, the scaled quail (Callipepla squamata) was the only species predicted to lose area in climatic suitability across all three scenarios of ensemble model agreement. Our models projected future loss of areas for the northern bobwhite (Colinus virginianus) and scaled quail in portions of their distributions which are currently areas of high abundance. Climatic variables that influence local abundance may not always scale up to influence

  9. Explaining local-scale species distributions: relative contributions of spatial autocorrelation and landscape heterogeneity for an avian assemblage.

    Science.gov (United States)

    Mattsson, Brady J; Zipkin, Elise F; Gardner, Beth; Blank, Peter J; Sauer, John R; Royle, J Andrew

    2013-01-01

    Understanding interactions between mobile species distributions and landcover characteristics remains an outstanding challenge in ecology. Multiple factors could explain species distributions including endogenous evolutionary traits leading to conspecific clustering and endogenous habitat features that support life history requirements. Birds are a useful taxon for examining hypotheses about the relative importance of these factors among species in a community. We developed a hierarchical Bayes approach to model the relationships between bird species occupancy and local landcover variables accounting for spatial autocorrelation, species similarities, and partial observability. We fit alternative occupancy models to detections of 90 bird species observed during repeat visits to 316 point-counts forming a 400-m grid throughout the Patuxent Wildlife Research Refuge in Maryland, USA. Models with landcover variables performed significantly better than our autologistic and null models, supporting the hypothesis that local landcover heterogeneity is important as an exogenous driver for species distributions. Conspecific clustering alone was a comparatively poor descriptor of local community composition, but there was evidence for spatial autocorrelation in all species. Considerable uncertainty remains whether landcover combined with spatial autocorrelation is most parsimonious for describing bird species distributions at a local scale. Spatial structuring may be weaker at intermediate scales within which dispersal is less frequent, information flows are localized, and landcover types become spatially diversified and therefore exhibit little aggregation. Examining such hypotheses across species assemblages contributes to our understanding of community-level associations with conspecifics and landscape composition.

  10. Explaining local-scale species distributions: relative contributions of spatial autocorrelation and landscape heterogeneity for an avian assemblage.

    Directory of Open Access Journals (Sweden)