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.
Forecasting effects of global warming on Biodiversity
BioScience, 57, (3), . (doi:10.1641/B570306).
Full text not available from this repository.
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.
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