Extinction risk from climate change
Chris D. Thomas,Alison Cameron,Rhys E. Green,Rhys E. Green,Michel Bakkenes,Linda J. Beaumont,Yvonne C. Collingham,Barend F.N. Erasmus,Marinez Ferreira de Siqueira,Alan Grainger,Lee Hannah,Lesley Hughes,Brian Huntley,Albert S. van Jaarsveld,Guy F. Midgley,Lera Miles,Lera Miles,Miguel A. Ortega-Huerta,A. Townsend Peterson,Oliver L. Phillips,Stephen E. Williams +20 more
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Estimates of extinction risks for sample regions that cover some 20% of the Earth's terrestrial surface show the importance of rapid implementation of technologies to decrease greenhouse gas emissions and strategies for carbon sequestration.Abstract:
Climate change over the past approximately 30 years has produced numerous shifts in the distributions and abundances of species and has been implicated in one species-level extinction. Using projections of species' distributions for future climate scenarios, we assess extinction risks for sample regions that cover some 20% of the Earth's terrestrial surface. Exploring three approaches in which the estimated probability of extinction shows a power-law relationship with geographical range size, we predict, on the basis of mid-range climate-warming scenarios for 2050, that 15-37% of species in our sample of regions and taxa will be 'committed to extinction'. When the average of the three methods and two dispersal scenarios is taken, minimal climate-warming scenarios produce lower projections of species committed to extinction ( approximately 18%) than mid-range ( approximately 24%) and maximum-change ( approximately 35%) scenarios. These estimates show the importance of rapid implementation of technologies to decrease greenhouse gas emissions and strategies for carbon sequestration.read more
Citations
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Incorporating uncertainty in predictive species distribution modelling
Colin M. Beale,Jack J. Lennon +1 more
TL;DR: It is concluded that uncertainty in SDMs has often been underestimated and a false precision assigned to predictions of geographical distribution, and areas where development of new statistical tools will improve predictions from distribution models are identified.
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Selecting from correlated climate variables: a major source of uncertainty for predicting species distributions under climate change
TL;DR: This article used four highly correlated climate variables together with a constant set of landscape variables in order to predict current (2010) and future (2050) distributions of four mountain bird species in central Europe.
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How many tree species are there in the Amazon and how many of them will go extinct
Stephen P. Hubbell,Stephen P. Hubbell,Fangliang He,Richard Condit,Richard Condit,Luís Borda-de-Água,Luís Borda-de-Água,James R. Kellner,Hans ter Steege +8 more
TL;DR: This work uses neutral theory to estimate the number, relative abundance, and range size of tree species in the Amazon metacommunity and estimate likely tree-species extinctions under published optimistic and nonoptimistic Amazon scenarios.
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How can a knowledge of the past help to conserve the future? Biodiversity conservation and the relevance of long-term ecological studies.
Katherine J. Willis,Miguel B. Araújo,Keith Bennett,Blanca Blanca Figueroa-Rangel,Cynthia A. Froyd,Norman Myers +5 more
TL;DR: It is concluded that often inclusion of a long-term ecological perspective can provide a more scientifically defensible basis for conservation decisions than the one based only on contemporary records.
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Potential impacts of climatic change upon geographical distributions of birds
Brian Huntley,Yvonne C. Collingham,Rhys E. Green,Geoffrey M. Hilton,Carsten Rahbek,Stephen G. Willis +5 more
TL;DR: In this paper, the potential impacts of anthropogenic climatic changes upon avian species richness in the two continents of Europe and Africa have been assessed for a range of general circulation model projections of late 21st century climate lead to the conclusion that the impacts upon birds are likely to be substantial.
References
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