Titre
Forecasting the effects of global warming on biodiversity
Type
article
Institution
UNIL/CHUV/Unisanté + institutions partenaires
Périodique
Auteur(s)
Botkin, D. B.
Auteure/Auteur
Saxe, H.
Auteure/Auteur
Araujo, M. B.
Auteure/Auteur
Betts, R.
Auteure/Auteur
Bradshaw, R. H. W.
Auteure/Auteur
Cedhagen, T.
Auteure/Auteur
Chesson, P.
Auteure/Auteur
Dawson, T. P.
Auteure/Auteur
Etterson, J. R.
Auteure/Auteur
Faith, D. P.
Auteure/Auteur
Ferrier, S.
Auteure/Auteur
Guisan, A.
Auteure/Auteur
Hansen, A. S.
Auteure/Auteur
Hilbert, D. W.
Auteure/Auteur
Loehle, C.
Auteure/Auteur
Margules, C.
Auteure/Auteur
New, M.
Auteure/Auteur
Sobel, M. J.
Auteure/Auteur
Stockwell, D. R. B.
Auteure/Auteur
Liens vers les personnes
Liens vers les unités
ISSN
0006-3568
Statut éditorial
Publié
Date de publication
2007
Volume
57
Numéro
3
Première page
227
Dernière page/numéro d’article
236
Peer-reviewed
Oui
Langue
anglais
Résumé
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) specics-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.
PID Serval
serval:BIB_7DBAAC6DFFFC
Open Access
Oui
Date de création
2008-01-24T18:06:02.505Z
Date de création dans IRIS
2025-05-20T23:04:10Z