A risk-based forecast of extreme mortality events in small cetaceans: Using stranding data to inform conservation practice
2019
Bouchard, Colin | Bracken, Cameron | Dabin, Willy | van Canneyt, Olivier | Ridoux, Vincent | Spitz, Jérôme | Authier, Matthieu | Ecologie Comportementale et Biologie des Populations de Poissons (ECOBIOP) ; Institut National de la Recherche Agronomique (INRA)-Université de Pau et des Pays de l'Adour (UPPA) | Observatoire pour la Conservation de la Mégafaune Marine (PELAGIS) ; LIttoral ENvironnement et Sociétés (LIENSs) ; Institut national des sciences de l'Univers (INSU - CNRS)-La Rochelle Université (ULR)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-La Rochelle Université (ULR)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS) | La Rochelle Université (ULR) | Centre National de la Recherche Scientifique (CNRS) | Bonneville Power Administration | Centre d'Études Biologiques de Chizé - UMR 7372 (CEBC) ; Institut National de la Recherche Agronomique (INRA)-La Rochelle Université (ULR)-Centre National de la Recherche Scientifique (CNRS) | ADERA | The authors thank the French Ministry of Ecology (“Ministère de la Transition Ecologique et Solidaire”) for financial support
International audience
Mostrar más [+] Menos [-]Inglés. Effective conservation requires monitoring and pro-active risk assessments.We studied the effects of at-sea mortality events (ASMEs) in marine mammals over two decades (1990–2012) and built a risk-based indicator for the European Union's Marine Strategy Framework Directive. Strandings of harbor porpoises (Phocoena phocoena), short-beaked common dolphins (Delphinus delphis), and striped dolphins (Stenella coeruleoalba) along French coastlines were analyzed using Extreme Value Theory (EVT). EVT operationalizes what is an extreme ASME, and allows the probabilistic forecasting of the expected maximum number of dead animals assuming constant pressures. For the period 2013–2018, we forecast the strandings of 80 harbor porpoises, 860 common dolphins, and 57 striped dolphins in extreme ASMEs. Comparison of these forecasts with observed strandings informs whether pressures are increasing, decreasing, or stable. Applying probabilistic methods to stranding data facilitates the building of risk-based indicators, required under the Marine Strategy Framework Directive, to monitor the effect of pressures on marine mammals.
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