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Robust fisheries management strategies under deep uncertainty.
Conradt, Jan; Funk, Steffen; Sguotti, Camilla; Voss, Rudi; Blenckner, Thorsten; Möllmann, Christian.
Afiliação
  • Conradt J; Institute of Marine Ecosystem and Fishery Science, Universität Hamburg, Große Elbstraße 133, 22767, Hamburg, Germany. jan.conradt@uni-hamburg.de.
  • Funk S; Institute of Marine Ecosystem and Fishery Science, Universität Hamburg, Große Elbstraße 133, 22767, Hamburg, Germany.
  • Sguotti C; Institute of Marine Ecosystem and Fishery Science, Universität Hamburg, Große Elbstraße 133, 22767, Hamburg, Germany.
  • Voss R; Department of Biology, University of Padova, Via U. Bassi 58/B, 85121, Padova, Italy.
  • Blenckner T; German Centre for Integrative Biodiversity Research (iDiv), Puschstraße 4, 04103, Leipzig, Germany.
  • Möllmann C; Center for Ocean and Society (CeOS), Christian-Albrechts-University Kiel, Neufeldtstraße 10, 24118, Kiel, Germany.
Sci Rep ; 14(1): 16863, 2024 07 23.
Article em En | MEDLINE | ID: mdl-39043856
ABSTRACT
Fisheries worldwide face uncertain futures as climate change manifests in environmental effects of hitherto unseen strengths. Developing climate-ready management strategies traditionally requires a good mechanistic understanding of stock response to climate change in order to build projection models for testing different exploitation levels. Unfortunately, model-based projections of fish stocks are severely limited by large uncertainties in the recruitment process, as the required stock-recruitment relationship is usually not well represented by data. An alternative is to shift focus to improving the decision-making process, as postulated by the decision-making under deep uncertainty (DMDU) framework. Robust Decision Making (RDM), a key DMDU concept, aims at identifying management decisions that are robust to a vast range of uncertain scenarios. Here we employ RDM to investigate the capability of North Sea cod to support a sustainable and economically viable fishery under future climate change. We projected the stock under 40,000 combinations of exploitation levels, emission scenarios and stock-recruitment parameterizations and found that model uncertainties and exploitation have similar importance for model outcomes. Our study revealed that no management strategy exists that is fully robust to the uncertainty in relation to model parameterization and future climate change. We instead propose a risk assessment that accounts for the trade-offs between stock conservation and profitability under deep uncertainty.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Mudança Climática / Conservação dos Recursos Naturais / Pesqueiros Limite: Animals Idioma: En Revista: Sci Rep Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Mudança Climática / Conservação dos Recursos Naturais / Pesqueiros Limite: Animals Idioma: En Revista: Sci Rep Ano de publicação: 2024 Tipo de documento: Article