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Discard management: A spatial multi-criteria approach
Institution:1. Instituto Español de Oceanografía, Centro Oceanográfico de Murcia, C/ Varadero 1, San Pedro del Pinatar, 30740 Murcia, Spain;2. Instituto Español de Oceanografía, Centro Oceanográfico de Vigo, Subida a Radio Faro, 50-52, Vigo, 36390 Vigo, Spain;1. Institut de Recherche pour le Développement - France (IRD), UMR Lemar, BP 1386, Dakar, Senegal;2. Institut de Recherche pour le Développement - France (IRD), UMR Marbec, Sète, France;3. University of Kiel (CAU), Department of Economics, Wilhelm-Seelig-Platz 1, 24118, Kiel, Germany;4. Université Cheikh Anta Diop (UCAD), Institut Universitaire de Pêche et d’Aquaculture, UCAD II, BP 45784, Dakar, Senegal;5. Institut Sénégalais de Recherche Agricole (ISRA), Centre de Recherche Océanographique de Dakar-Thiaroye (CRODT), BP 2241, Centre PRH, Dakar, Senegal;1. European Commission, Joint Research Centre Institute for the Protection and Security of the Citizen, Ispra, Italy;2. Swedish Agency for Marine and Water management, Gothenburg, Sweden;1. European Commission Joint Research Centre, Institute for the Protection and Security of the Citizen (IPSC), Via Enrico Fermi 2749, 21027 Ispra, VA, Italy;2. Swedish University of Agricultural Sciences, Department of Aquatic Resources, Institute of Marine Research, Turistgatan 5, S-453 30 Lysekil, Sweden;3. Marine Scotland Science, Freshwater Laboratory, Faskally, Pitlochry , Perthshire, PH16 5LB, UK;1. IMARES, Institute for Marine Resources and Ecosystem Studies, P.O. Box 68, 1970 AB IJmuiden, The Netherlands;2. Aquaculture and Fisheries Group, Wageningen University, P.O. Box 338, 6700 AH Wageningen, The Netherlands;3. Agricultural Economics Research Institute (LEI), PO Box 29703, 2502 LS Den Haag, The Netherlands
Abstract:Discard management needs to draw on scientific research and advice, usually supported by specific statistical modeling analysis. A wide range of statistical analysis methods were applied to fishery data in an attempt to distinguish factors that influence the species discard composition. While such approaches are important, they are still incomplete for disaggregating the economic and spatial-temporal factors for analyzing of this process and obtain a whole view of this issue. Our study aims to fill this gap by identifying, describing, and quantifying factors that influence discards of trawl fisheries using a multivariate approach based on five complementary aspects: “economic”, “vessel characteristics”, “spatial”, “temporal” and “environmental”. In addition, a spatial multi-criteria approach were used to investigate discard hot-spot areas using ecological criteria such as vulnerability and resilience of the discarded species. Using these ecological criteria will concentrate conservation efforts on the most relevant sites minimizing discards of a variety of potentially vulnerable species. This approach was applied to a case study of a multi-species demersal bottom trawl fisheries in north Spain, Cantabrian Sea (ICES area VIIIc). Results showed how spatial and economic factors highly affect species discard composition, identifying specific spatial-temporal discard hot-spots to be preferentially avoided by fishers. Mitigation measures for future fisheries management strategies should be implemented at multiple stages of the discarding process, both in the selection of the fishing grounds and the economic valorization of the discarded species.
Keywords:Bayesian models  Cantabrian Sea  Discard drivers  Fishery management
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