Predicting extinction risks under climate change: coupling stochastic population models with dynamic bioclimatic habitat models
Identifieur interne : 008564 ( Main/Exploration ); précédent : 008563; suivant : 008565Predicting extinction risks under climate change: coupling stochastic population models with dynamic bioclimatic habitat models
Auteurs : David A. Keith [Australie] ; H. Resit Akçakaya [États-Unis] ; Wilfried Thuiller [France] ; Guy F. Midgley [Afrique du Sud] ; Richard G. Pearson [États-Unis] ; Steven J. Phillips [États-Unis] ; Helen M. Regan [États-Unis] ; Miguel B. Araújo [Espagne] ; Tony G. Rebelo [Afrique du Sud]Source :
- Biology Letters [ 1744-9561 ] ; 2008.
Abstract
Species responses to climate change may be influenced by changes in available habitat, as well as population processes, species interactions and interactions between demographic and landscape dynamics. Current methods for assessing these responses fail to provide an integrated view of these influences because they deal with habitat change or population dynamics, but rarely both. In this study, we linked a time series of habitat suitability models with spatially explicit stochastic population models to explore factors that influence the viability of plant species populations under stable and changing climate scenarios in South African fynbos, a global biodiversity hot spot. Results indicate that complex interactions between life history, disturbance regime and distribution pattern mediate species extinction risks under climate change. Our novel mechanistic approach allows more complete and direct appraisal of future biotic responses than do static bioclimatic habitat modelling approaches, and will ultimately support development of more effective conservation strategies to mitigate biodiversity losses due to climate change.
Url:
DOI: 10.1098/rsbl.2008.0049
PubMed: 18664424
PubMed Central: 2610061
Affiliations:
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Le document en format XML
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<front><div type="abstract" xml:lang="en"><p>Species responses to climate change may be influenced by changes in available habitat, as well as population processes, species interactions and interactions between demographic and landscape dynamics. Current methods for assessing these responses fail to provide an integrated view of these influences because they deal with habitat change or population dynamics, but rarely both. In this study, we linked a time series of habitat suitability models with spatially explicit stochastic population models to explore factors that influence the viability of plant species populations under stable and changing climate scenarios in South African fynbos, a global biodiversity hot spot. Results indicate that complex interactions between life history, disturbance regime and distribution pattern mediate species extinction risks under climate change. Our novel mechanistic approach allows more complete and direct appraisal of future biotic responses than do static bioclimatic habitat modelling approaches, and will ultimately support development of more effective conservation strategies to mitigate biodiversity losses due to climate change.</p>
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