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Linking the performance of a data-limited empirical catch rule to life-history traits
ICES Journal of Marine Science ( IF 3.1 ) Pub Date : 2020-06-12 , DOI: 10.1093/icesjms/fsaa054
Simon H Fischer 1, 2 , José A A De Oliveira 1 , Laurence T Kell 2
Affiliation  

Worldwide, the majorities of fish stocks are data-limited and lack fully quantitative stock assessments. Within ICES, such data-limited stocks are currently managed by setting total allowable catch without the use of target reference points. To ensure that such advice is precautionary, we used management strategy evaluation to evaluate an empirical rule that bases catch advice on recent catches, information from a biomass survey index, catch length frequencies, and MSY reference point proxies. Twenty-nine fish stocks were simulated covering a wide range of life histories. The performance of the rule varied substantially between stocks, and the risk of breaching limit reference points was inversely correlated to the von Bertalanffy growth parameter k. Stocks with k>0.32 year−1 had a high probability of stock collapse. A time series cluster analysis revealed four types of dynamics, i.e. groups with similar terminal spawning stock biomass (collapsed, BMSY, 2BMSY, 3BMSY). It was shown that a single generic catch rule cannot be applied across all life histories, and management should instead be linked to life-history traits, and in particular, the nature of the time series of stock metrics. The lessons learnt can help future work to shape scientific research into data-limited fisheries management and to ensure that fisheries are MSY compliant and precautionary.

中文翻译:

将数据受限的经验捕获规则的性能与生活历史特征联系起来

在世界范围内,大多数鱼类种群数据有限,缺乏全面的定量种群评估。在ICES中,当前通过设置总允许捕捞量而不使用目标参考点来管理此类数据受限的种群。为了确保此类建议是预防性的,我们使用管理策略评估来评估经验规则,该规则基于最近捕获的捕获建议,来自生物量调查指数的信息,捕获长度频率和MSY参考点代理。模拟了29种鱼类,涵盖了广泛的生活史。该规则的表现在股票之​​间有很大的不同,违反限制基准点的风险与冯·贝塔朗菲的增长参数成反比ķ。与股票ķ>0.32 - 1年极有可能发生股票崩盘。时间序列聚类分析揭示了四种类型的动力学,即具有相似的最终产卵种群生物量的组(崩溃,B MSY,2 B MSY,3 B MSY)。结果表明,不能将单个通用捕获规则应用于所有生命历史,而应该将管理与生命历史特征(尤其是股票指标时间序列的性质)联系起来。所汲取的经验教训可以帮助将来开展工作,以将科学研究转变为数据受限的渔业管理,并确保渔业符合MSY标准并采取预防措施。
更新日期:2020-06-12
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