REVIEW: Predictive ecology in a changing world

作者：Nicolas Mouquet, Yvan Lagadeuc, Vincent Devictor, Luc Doyen, Anne Duputié, Damien Eveillard, Denis Faure, Éric Garnier, Olivier Giménez, Philippe Huneman, Franck Jabot, Philippe Jarne, Dominique Joly, Romain Julliard, Sonia Kéfi, Gaël J. Kergoat, Sandra Lavorel, Line Le Gall, Laurence Meslin, Sergé Morand, Xavier Morin, Hélène Morlon, Gilles Pinay, Roger Pradel, Frank M. Schurr, Wilfried Thuiller, Michel Loreau · 发表于：Journal of Applied Ecology · 年份：2015 · DOI：10.1111/1365-2664.12482 · 被引用次数：334 · 研究领域：Species Distribution and Climate Change、Ecosystem dynamics and resilience、Ecology and Vegetation Dynamics Studies

Summary In a rapidly changing world, ecology has the potential to move from empirical and conceptual stages to application and management issues. It is now possible to make large‐scale predictions up to continental or global scales, ranging from the future distribution of biological diversity to changes in ecosystem functioning and services. With these recent developments, ecology has a historical opportunity to become a major actor in the development of a sustainable human society. With this opportunity, however, also comes an important responsibility in developing appropriate predictive models, correctly interpreting their outcomes and communicating their limitations. There is also a danger that predictions grow faster than our understanding of ecological systems, resulting in a gap between the scientists generating the predictions and stakeholders using them (conservation biologists, environmental managers, journalists, policymakers). Here, we use the context provided by the current surge of ecological predictions on the future of biodiversity to clarify what prediction means, and to pinpoint the challenges that should be addressed in order to improve predictive ecological models and the way they are understood and used. Synthesis and applications. Ecologists face several challenges to ensure the healthy development of an operational predictive ecological science: (i) clarity on the distinction between explanatory and anticipatory predictions; (ii) developing new theories ...