Modelling the influence of biotic factors on species distribution patterns

Biotic interactions can have large effects on species distributions yet their role in shaping species ranges is seldom explored due to historical difficulties in incorporating biotic factors into models without a priori knowledge on interspecific interactions. Improved SDMs, which account for biotic factors and do not require a priori knowledge on species interactions, are needed to fully understand species distributions. Here, we model the influence of abiotic and biotic factors on species distribution patterns and explore the robustness of distributions under future climate change. We fit hierarchical spatial models using Integrated Nested Laplace Approximation (INLA) for lagomorph species throughout Europe and test the predictive ability of models containing only abiotic factors against models containing abiotic and biotic factors. We account for residual spatial autocorrelation using a conditional autoregressive (CAR) model. Model outputs are used to estimate areas in which abiotic and biotic factors determine species’ ranges. INLA models containing both abiotic and biotic factors had substantially better predictive ability than models containing abiotic factors only, for all but one of the four species. In models containing abiotic and biotic factors, both appeared equally important as determinants of lagomorph ranges, but the influences were spatially heterogeneous. Parts of widespread lagomorph ranges highly influenced by biotic factors will be less robust to future changes in climate, whereas parts of more localised species ranges highly influenced by the environment may be less robust to future climate. SDMs that do not explicitly include biotic factors are potentially misleading and omit a very important source of variation. For the field of species distribution modelling to advance, biotic factors must be taken into account in order to improve the reliability of predicting species distribution patterns both presently and under future climate change.

[1]  C. Gouveia Predicting the Impacts of Climate Change on Protected Areas: A Case Study of Land Snails in Madeira Island , 2015 .

[2]  Laura J. Pollock,et al.  Understanding co‐occurrence by modelling species simultaneously with a Joint Species Distribution Model (JSDM) , 2014 .

[3]  Jorge Soberón,et al.  Niches and distributional areas: Concepts, methods, and assumptions , 2009, Proceedings of the National Academy of Sciences.

[4]  D. Bell,et al.  Habitat correlates of European rabbit (Oryctolagus cuniculus) distribution after the spread of RVHD in Cadiz Province, Spain , 1999 .

[5]  P. Amarasekare Competitive coexistence in spatially structured environments: a synthesis , 2003 .

[6]  J. Domínguez,et al.  Modelling habitat use by Iberian hare Lepus granatensis and European wild rabbit Oryctolagus cuniculus in a mountainous area in northwestern Spain , 2010, Acta Theriologica.

[7]  C. Gortázar,et al.  A Large-scale Survey of Brown Hare Lepus Europaeus and Iberian Hare L. Granatensis Populations at the Limit of Their Ranges , 2007 .

[8]  Antoine Guisan,et al.  Species distribution models reveal apparent competitive and facilitative effects of a dominant species on the distribution of tundra plants , 2010 .

[9]  J. Flux A Review of Competition between Rabbits (Oryctolagus cuniculus) and Hares (Lepus europaeus) , 2008 .

[10]  Catherine H. Graham,et al.  A comparison of methods for mapping species ranges and species richness , 2006 .

[11]  M. Araújo,et al.  The importance of biotic interactions for modelling species distributions under climate change , 2007 .

[12]  N. Reid,et al.  IS NATURALISATION OF THE BROWN HARE IN IRELAND A THREAT TO THE ENDEMIC IRISH HARE? , 2022, Biology and Environment: Proceedings of the Royal Irish Academy.

[13]  H. Rue,et al.  Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations , 2009 .

[14]  S. Martino Approximate Bayesian Inference for Latent Gaussian Models , 2007 .

[15]  J. Elith,et al.  Species Distribution Models: Ecological Explanation and Prediction Across Space and Time , 2009 .

[16]  N. Reid,et al.  Biogeography, macroecology and species' traits mediate competitive interactions in the order Lagomorpha , 2015 .

[17]  Anni Arponen,et al.  Projecting Global Biodiversity Indicators under Future Development Scenarios , 2016 .

[18]  H. Possingham,et al.  A Climatic Stability Approach to Prioritizing Global Conservation Investments , 2010, PloS one.

[19]  T. Dawson,et al.  Predicting the impacts of climate change on the distribution of species: are bioclimate envelope models useful? , 2003 .

[20]  D. Rosauer,et al.  Integrating species traits with extrinsic threats: closing the gap between predicting and preventing species declines , 2011, Proceedings of the Royal Society B: Biological Sciences.

[21]  J. Lennon,et al.  A new statistical framework for the quantification of covariate associations with species distributions , 2014 .

[22]  S. Lavorel,et al.  Generalized models vs. classification tree analysis: Predicting spatial distributions of plant species at different scales , 2003 .

[23]  Håvard Rue,et al.  Hierarchical analysis of spatially autocorrelated ecological data using integrated nested Laplace approximation , 2012 .

[24]  C. Thulin The distribution of mountain hares Lepus timidus in Europe: a challenge from brown hares L. europaeus? , 2003 .

[25]  David J. Harris Generating realistic assemblages with a joint species distribution model , 2015 .

[26]  Omri Allouche,et al.  Assessing the accuracy of species distribution models: prevalence, kappa and the true skill statistic (TSS) , 2006 .

[27]  A. Cameron,et al.  Expertly Validated Models and Phylogenetically-Controlled Analysis Suggests Responses to Climate Change Are Related to Species Traits in the Order Lagomorpha , 2015, PloS one.

[28]  Colin M Beale,et al.  Regression analysis of spatial data. , 2010, Ecology letters.

[29]  Sumio Watanabe,et al.  Asymptotic Equivalence of Bayes Cross Validation and Widely Applicable Information Criterion in Singular Learning Theory , 2010, J. Mach. Learn. Res..

[30]  F. Maestre,et al.  Do biotic interactions modulate ecosystem functioning along stress gradients? Insights from semi-arid plant and biological soil crust communities , 2010, Philosophical Transactions of the Royal Society B: Biological Sciences.

[31]  Robert D Holt,et al.  A framework for community interactions under climate change. , 2010, Trends in ecology & evolution.

[32]  A. Pitman,et al.  Impacts of climate change on the world's most exceptional ecoregions , 2011, Proceedings of the National Academy of Sciences.

[33]  Range expansion and comparative habitat use of insular, congeneric lagomorphs: invasive European hares Lepus europaeus and endemic Irish hares Lepus timidus hibernicus , 2015, Biological Invasions.

[34]  Bradley P. Carlin,et al.  Bayesian measures of model complexity and fit , 2002 .

[35]  P. Legendre Spatial Autocorrelation: Trouble or New Paradigm? , 1993 .

[36]  J. Andrew Royle,et al.  HIERARCHICAL SPATIAL MODELS OF ABUNDANCE AND OCCURRENCE FROM IMPERFECT SURVEY DATA , 2007 .

[37]  Carsten F. Dormann,et al.  Towards novel approaches to modelling biotic interactions in multispecies assemblages at large spatial extents , 2012 .

[38]  R. Real,et al.  Parapatric species and the implications for climate change studies: a case study on hares in Europe , 2012 .

[39]  Jack J. Lennon,et al.  Red-shifts and red herrings in geographical ecology , 2000 .

[40]  J. Wiens The niche, biogeography and species interactions , 2011, Philosophical Transactions of the Royal Society B: Biological Sciences.

[41]  James E. M. Watson,et al.  Mapping vulnerability and conservation adaptation strategies under climate change , 2013 .

[42]  W. D. Kissling,et al.  The role of biotic interactions in shaping distributions and realised assemblages of species: implications for species distribution modelling , 2012, Biological reviews of the Cambridge Philosophical Society.

[43]  Kjersti Aas,et al.  Norges Teknisk-naturvitenskapelige Universitet Estimating Stochastic Volatility Models Using Integrated Nested Laplace Approximations Estimating Stochastic Volatility Models Using Integrated Nested Laplace Approximations , 2022 .

[44]  C. Nilsson,et al.  How biotic interactions may alter future predictions of species distributions: future threats to the persistence of the arctic fox in Fennoscandia , 2012 .

[45]  Robert A. Boria,et al.  Can biotic interactions cause allopatry? Niche models, competition, and distributions of South American mouse opossums , 2014 .

[46]  M. Plummer Penalized loss functions for Bayesian model comparison. , 2008, Biostatistics.

[47]  P. Kareiva,et al.  Projected climate-induced faunal change in the Western Hemisphere. , 2009, Ecology.

[48]  I. Hiscock Communities and Ecosystems , 1970, The Yale Journal of Biology and Medicine.

[49]  P. Alves,et al.  Environmental factors have little influence on the reproductive activity of the Iberian hare (Lepus granatensis) , 2003 .

[50]  Neil Reid,et al.  An invasive‐native mammalian species replacement process captured by camera trap survey random encounter models , 2016 .

[51]  Steven J. Phillips,et al.  Aligning Conservation Priorities Across Taxa in Madagascar with High-Resolution Planning Tools , 2008, Science.

[52]  A. Townsend Peterson,et al.  Novel methods improve prediction of species' distributions from occurrence data , 2006 .

[53]  S. Harris,et al.  Modelling the distribution of badgers Meles meles: comparing predictions from field-based and remotely derived habitat data , 2007 .

[54]  Aki Vehtari,et al.  Understanding predictive information criteria for Bayesian models , 2013, Statistics and Computing.

[55]  Eduardo Pineda,et al.  Assessing the accuracy of species distribution models to predict amphibian species richness patterns. , 2009, The Journal of animal ecology.

[56]  Heidi K. Mod,et al.  Biotic interactions boost spatial models of species richness , 2015 .

[57]  Mevin B. Hooten,et al.  Hierarchical Spatial Models , 2008, Encyclopedia of GIS.

[58]  David Jablonski,et al.  Biotic Interactions and Macroevolution: Extensions and Mismatches Across Scales and Levels , 2008, Evolution; international journal of organic evolution.

[59]  J. Lawton,et al.  Species interactions, local and regional processes, and limits to the richness of ecological communities : a theoretical perspective , 1992 .

[60]  Heiko G. Rödel,et al.  Influence of weather factors on population dynamics of two lagomorph species based on hunting bag records , 2012, European Journal of Wildlife Research.

[61]  H. Possingham,et al.  How robust are global conservation priorities to climate change , 2013 .

[62]  M. Austin Spatial prediction of species distribution: an interface between ecological theory and statistical modelling , 2002 .

[63]  N. Reid European hare (Lepus europaeus) invasion ecology: implication for the conservation of the endemic Irish hare (Lepus timidus hibernicus) , 2011, Biological Invasions.

[64]  Wilfried Thuiller,et al.  BioMove – an integrated platform simulating the dynamic response of species to environmental change , 2010 .

[65]  C. Bull Ecology of Parapatric Distributions , 1991 .