Forecasting effects of global warming on Biodiversity

Botkin, D.B., Saxe, H., Araújo, M.B., Betts, R., Bradshaw, R., Cedhagen, T., Chesson, P., Davis, M.B., Dawson, T.P., Etterson, J., Faith, D.P., Ferrier, S., Guisan, A., Skjoldborg, A., Hansen, D.H., Kareiva, P., Loehle, M.C., New, M., Skov, F., Sobel, M.J., Stockwell, D. and Svenning, J-C. (2007) Forecasting effects of global warming on Biodiversity. BioScience, 57, (3), 227-236. (doi:10.1641/B570306).


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The demand for accurate forecasting of the effects of global warming on biodiversity is growing, but current methods for forecasting have limitations.
In this article, we compare and discuss the different uses of four forecasting methods: (1) models that consider species individually, (2) niche-theory
models that group species by habitat (more specifically, by environmental conditions under which a species can persist or does persist), (3) general
circulation models and coupled ocean–atmosphere–biosphere models, and (4) species–area curve models that consider all species or large aggregates
of species. After outlining the different uses and limitations of these methods, we make eight primary suggestions for improving forecasts.We find that
greater use of the fossil record and of modern genetic studies would improve forecasting methods.We note a Quaternary conundrum: While current
empirical and theoretical ecological results suggest that many species could be at risk from global warming, during the recent ice ages surprisingly few
species became extinct. The potential resolution of this conundrum gives insights into the requirements for more accurate and reliable forecasting. Our
eight suggestions also point to constructive synergies in the solution to the different problems.

Item Type: Article
Digital Object Identifier (DOI): doi:10.1641/B570306
ISSNs: 0006-3568 (print)
Related URLs:
Keywords: biodiversity, forecasting, global warming, modeling, Quaternary conundrum
Subjects: G Geography. Anthropology. Recreation > G Geography (General)
G Geography. Anthropology. Recreation > GE Environmental Sciences
G Geography. Anthropology. Recreation > GB Physical geography
Divisions : University Structure - Pre August 2011 > School of Geography > Remote Sensing and Spatial Analysis
ePrint ID: 58440
Accepted Date and Publication Date:
March 2007Published
Date Deposited: 14 Aug 2008
Last Modified: 31 Mar 2016 12:39

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