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在深度不确定性下的稳健渔业管理策略。

Robust fisheries management strategies under deep uncertainty.

机构信息

Institute of Marine Ecosystem and Fishery Science, Universität Hamburg, Große Elbstraße 133, 22767, Hamburg, Germany.

Department of Biology, University of Padova, Via U. Bassi 58/B, 85121, Padova, Italy.

出版信息

Sci Rep. 2024 Jul 23;14(1):16863. doi: 10.1038/s41598-024-68006-5.

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.

摘要

由于气候变化对环境产生了前所未有的强烈影响,全球渔业的未来充满不确定性。传统上,制定应对气候变化的管理策略需要对种群对气候变化的响应有很好的机械理解,以便为不同的开发水平建立预测模型。不幸的是,由于数据通常无法很好地反映所需的种群补充关系,基于模型的鱼类种群预测受到很大的不确定性限制。另一种方法是将重点转移到改进决策过程,正如深度不确定性下的决策(DMDU)框架所假设的那样。稳健决策(RDM)是 DMDU 的一个关键概念,旨在确定对大量不确定情况具有稳健性的管理决策。在这里,我们运用 RDM 来研究北海鳕鱼在未来气候变化下支持可持续和经济可行渔业的能力。我们根据 40,000 种开发水平、排放情景和种群补充参数化组合来预测种群,发现模型不确定性和捕捞对模型结果具有相似的重要性。我们的研究表明,不存在一种完全能应对模型参数化和未来气候变化不确定性的管理策略。相反,我们提出了一种风险评估,该评估考虑了在深度不确定性下种群保护和盈利能力之间的权衡。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/837e/11266645/c5ab5c275138/41598_2024_68006_Fig1_HTML.jpg

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