Abstract
There is an urgent need to develop effective vulnerability assessments for evaluating the conservation status of species in a changing climate1. Several new assessment approaches have been proposed for evaluating the vulnerability of species to climate change2,3,4,5 based on the expectation that established assessments such as the IUCN Red List6 need revising or superseding in light of the threat that climate change brings. However, although previous studies have identified ecological and life history attributes that characterize declining species or those listed as threatened7,8,9, no study so far has undertaken a quantitative analysis of the attributes that cause species to be at high risk of extinction specifically due to climate change. We developed a simulation approach based on generic life history types to show here that extinction risk due to climate change can be predicted using a mixture of spatial and demographic variables that can be measured in the present day without the need for complex forecasting models. Most of the variables we found to be important for predicting extinction risk, including occupied area and population size, are already used in species conservation assessments, indicating that present systems may be better able to identify species vulnerable to climate change than previously thought. Therefore, although climate change brings many new conservation challenges, we find that it may not be fundamentally different from other threats in terms of assessing extinction risks.
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Acknowledgements
Financial support was provided by NASA (Biodiversity Program grant NNX09AK19G). The Australian Research Council supported D.A.F. (grants LP0989420, DP1096427and FS110200051). J. Palmer, S. Phillips, J. Ray, A. Sonneborn helped with analyses, G. Mace provided comments on a draft manuscript, and B. Young, NatureServe and its Natural Heritage member programmes provided data.
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R.G.P. and H.R.A. designed the study, analysed data and led writing the manuscript; R.G.P. ran ENMs; H.R.A. developed GLH models; J.C.S. selected variables for ENM and linked ENM and GLH models; J.C.S. and H.Y.R. collated demographic data and ran metapopulation simulations; K.T.S. led BRT and RF analyses; M.E.A.-L. sampled models from GLH and extracted simulation results; P.J.E. and N.H. developed ENM input data; D.A.F. led climate analyses; C.J.R. helped with species selection, variable selection and demographic data; J.M. collated species data; all authors discussed results and contributed to writing the manuscript.
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Pearson, R., Stanton, J., Shoemaker, K. et al. Life history and spatial traits predict extinction risk due to climate change. Nature Clim Change 4, 217–221 (2014). https://doi.org/10.1038/nclimate2113
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DOI: https://doi.org/10.1038/nclimate2113
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