Reserve selection research has not accounted for potential species\' range shifts associated to climate change. It has provided algorithms that are able to prioritise area-sets to achieve given persistence goals in a stable world. However, climate change threatens to reduce effectiveness of such approaches, because projected changes will force species beyond current distributions. Empirical models of species occurrences allow projecting species future distributions according to climate scenarios. This information could be critical in assessing the robustness of current conservation area networks and in guiding management decisions in the future. However, no protocolexists by which range shifts can be incorporated into reserve selection algorithms. The reasons are that
) both range-shift modelling and reserve-selection are complex problems that have been addressed separately; and
2)until recently, regional climate change data were not available at scales and timeframes applicable to reserve selection. But, regional climate modelling makes it now possible to generate projections of range shifts with climate data at temporal and spatial scales useful in reserve selection. Key questions include:
i) what species will either gain or loose range under climate change scenarios?;
ii) how can empirical models of current and projected distributions be brought together with information on dispersal to prioritise reserves that are more robust to climate change, and identify new sites which will be important in the future?;
iii) how can uncertainty be quantified in a way that can help increasing the robustness of area selection decisions for the future? In this project we shall address these problems by making use of the most extensive species distribution data available for Europe.
Finer grain case studies will be developed for the United Kingdom.
Field of science
- /natural sciences/earth and related environmental sciences/atmospheric sciences/climatology/climatic changes
Call for proposal
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