Combining correlative and mechanistic habitat suitability models to improve ecological compensation
2014
Meineri, Eric | Deville, Anne‐sophie | Grémillet, David | Gauthier-Clerc, Michel | Béchet, Arnaud | Institut méditerranéen de biodiversité et d'écologie marine et continentale (IMBE) ; Avignon Université (AU)-Aix Marseille Université (AMU)-Institut de recherche pour le développement [IRD] : UMR237-Centre National de la Recherche Scientifique (CNRS) | Percy FitzPatrick Institute of African Ornithology ; University of Cape Town | Centre d’Ecologie Fonctionnelle et Evolutive (CEFE) ; Université Paul-Valéry - Montpellier 3 (UPVM)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-École Pratique des Hautes Études (EPHE) ; Université Paris Sciences et Lettres (PSL)-Université Paris Sciences et Lettres (PSL)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [Occitanie])-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro) | Centre de recherche de la Tour du Valat (CRTV) | Laboratoire Chrono-environnement (UMR 6249) (LCE) ; Centre National de la Recherche Scientifique (CNRS)-Université de Franche-Comté (UFC) ; Université Bourgogne Franche-Comté [COMUE] (UBFC)-Université Bourgogne Franche-Comté [COMUE] (UBFC) | Foundation MAVA Salinalgue Reegion Provence-Alpes-Cote d'Azur (South of France) French Fond Unique Interministeriel (FUI)
International audience
Afficher plus [+] Moins [-]anglais. Only a few studies have shown positive impacts of ecological compensation on species dynamics affected by human activities. We argue that this is due to inappropriate methods used to forecast required compensation in environmental impact assessments. These assessments are mostly descriptive and only valid at limited spatial and temporal scales. However, habitat suitability models developed to predict the impacts of environmental changes on potential species' distributions should provide rigorous science-based tools for compensation planning. Here we describe the two main classes of predictive models: correlative models and individual-based mechanistic models. We show how these models can be used alone or synoptically to improve compensation planning. While correlative models are easier to implement, they tend to ignore underlying ecological processes and lack accuracy. On the contrary, individual-based mechanistic models can integrate biological interactions, dispersal ability and adaptation. Moreover, among mechanistic models, those considering animal energy balance are particularly efficient at predicting the impact of foraging habitat loss. However, mechanistic models require more field data compared to correlative models. Hence we present two approaches which combine both methods for compensation planning, especially in relation to the spatial scale considered. We show how the availability of biological databases and software enabling fast and accurate population projections could be advantageously used to assess ecological compensation requirement efficiently in environmental impact assessments.
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