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Science. 2016 Sep 9;353(6304). pii: aad8466. doi: 10.1126/science.aad8466.

Improving the forecast for biodiversity under climate change.

Author information

1
Institute of Biological Risk, Ecology and Evolutionary Biology, University of Connecticut, Storrs, CT, USA. mark.urban@uconn.edu.
2
Institute of Biological and Environmental Sciences, University of Aberdeen, Aberdeen, UK.
3
Redpath Museum, Department of Biology, McGill University, Montreal, Canada.
4
Sorbonne Universités, UPMC Université Paris 06, Muséum National d'Histoire Naturelle, CNRS, CESCO, UMR 7204, Paris, France. Conservation Biology, UFZ-Helmholtz Centre for Environmental Research, Leipzig, Germany.
5
Conservation Biology, UFZ-Helmholtz Centre for Environmental Research, Leipzig, Germany. German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany.
6
German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany. Ecological Modelling, UFZ-Helmholtz Centre for Environmental Research, Leipzig, Germany. Swedish University of Agricultural Sciences, Swedish Species Information Centre, Uppsala, Sweden.
7
School of Biological Sciences, University of Bristol, Bristol, UK.
8
NOAA Fisheries Northwest Fisheries Science Center, Seattle, WA, USA.
9
Laboratory of Aquatic Ecology, Evolution and Conservation, KU Leuven, Leuven, Belgium.
10
Bio-Protection Research Centre, Lincoln University, Lincoln, New Zealand.
11
Biology, McGill University, Montreal, Canada.
12
Institute on the Environment; Ecology, Evolution, and Behavior, University of Minnesota, St. Paul, MN, USA.
13
Biology, University of Florida, Gainesville, FL, USA.
14
Ecological Modelling, UFZ-Helmholtz Centre for Environmental Research, Leipzig, Germany. German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany. Institute for Environmental Systems Research, Department of Mathematics/Computer Science, University of Osnabrück, Osnabrück, Germany.
15
Ecological Modelling, UFZ-Helmholtz Centre for Environmental Research, Leipzig, Germany.
16
Ecologie Systématique Evolution, University Paris-Sud, CNRS, AgroParisTech, Université Paris-Saclay, Orsay, France. DIVERSITAS, Paris, France.
17
Centre d'Ecologie fonctionnelle et Evolutive, UMR 5175 CNRS-Université de Montpellier-EPHE, Montpellier Cedex, France.
18
Conservation Biology, UFZ-Helmholtz Centre for Environmental Research, Leipzig, Germany.
19
Forestry and Natural Resources, Purdue University, West Lafayette, IN, USA.

Abstract

New biological models are incorporating the realistic processes underlying biological responses to climate change and other human-caused disturbances. However, these more realistic models require detailed information, which is lacking for most species on Earth. Current monitoring efforts mainly document changes in biodiversity, rather than collecting the mechanistic data needed to predict future changes. We describe and prioritize the biological information needed to inform more realistic projections of species' responses to climate change. We also highlight how trait-based approaches and adaptive modeling can leverage sparse data to make broader predictions. We outline a global effort to collect the data necessary to better understand, anticipate, and reduce the damaging effects of climate change on biodiversity.

PMID:
27609898
DOI:
10.1126/science.aad8466
[Indexed for MEDLINE]

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