Unravelling the structure of species extinction risk for predictive conservation science

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Unravelling the structure of species extinction risk for predictive conservation science
Publication Type Journal Article
Year of Publication 2011
Authors Lee, Tien Ming, and Jetz Walter
Journal Proceedings of the Royal Society B-Biological Sciences
Volume 278
Pagination 1329-1338
Abstract Extinction risk varies across species and space owing to the combined and interactive effects of ecology/life history and geography. For predictive conservation science to be effective, large datasets and integrative models that quantify the relative importance of potential factors and separate rapidly changing from relatively static threat drivers are urgently required. Here, we integrate and map in space the relative and joint effects of key correlates of The International Union for Conservation of Nature-assessed extinction risk for 8700 living birds. Extinction risk varies significantly with species’ broad-scale environmental niche, geographical range size, and life-history and ecological traits such as body size, developmental mode, primary diet and foraging height. Even at this broad scale, simple quantifications of past human encroachment across species’ ranges emerge as key in predicting extinction risk, supporting the use of land-cover change projections for estimating future threat in an integrative setting. A final joint model explains much of the interspecific variation in extinction risk and provides a remarkably strong prediction of its observed global geography. Our approach unravels the species-level structure underlying geographical gradients in extinction risk and offers a means of disentangling static from changing components of current and future threat. This reconciliation of intrinsic and extrinsic, and of past and future extinction risk factors may offer a critical step towards a more continuous, forward-looking assessment of species’ threat status based on geographically explicit environmental change projections, potentially advancing global predictive conservation science.
Media ECN, Yale Bulletin
URL http://rspb.royalsocietypublishing.org/content/early/2010/10/12/rspb.2010.1877.full
DOI 10.1098/rspb.2010.1877
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