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Evaluating tag-reliant harvest estimators in Chinook salmon mixed-stock fisheries using simulations
Canadian Journal of Fisheries and Aquatic Sciences ( IF 1.9 ) Pub Date : 2021-12-03 , DOI: 10.1139/cjfas-2021-0197
Alexander J Jensen 1 , Benjamin Cox 2 , James T Peterson 3
Affiliation  

Canadian Journal of Fisheries and Aquatic Sciences, Ahead of Print.
Management of mixed-stock Chinook salmon (Oncorhynchus tshawytscha) fisheries requires balancing fishery access and conservation of vulnerable stocks. Although accurate, timely estimates of stock-specific harvest are crucial in achieving competing objectives, limited numbers of stock assignments (e.g., tag recoveries) can diminish the utility of estimates. We used a flexible simulation approach, applied to both a theoretical and real-world fishery case study, to compare the performance of competing monitoring alternatives and estimators for harvest. We sought to improve accuracy for point estimates of harvest and harvest trajectories over time. Bayesian models provided similarly accurate point estimates to existing models at high levels of data aggregation, generally improved estimates of harvest trajectories at intermediate aggregation, and reliable estimates of uncertainty. Incorporation of time-lagged prior information inconsistently improved estimates of harvest trajectories. Among monitoring alternatives yielding equal increases (33%) in coded wire tag recoveries, increasing tagging rates resulted in the greatest decrease in estimate uncertainty for target stocks (37.5% to 45.3%). Variable performances of mixed-stock harvest estimators suggest their use should considered on a stock- and fishery-specific basis, potentially using a simulation-based approach.


中文翻译:

使用模拟评估奇努克鲑鱼混合种群渔业中依赖标签的收获估计器

加拿大渔业和水生科学杂志,印刷前。
混合种群奇努克鲑鱼(Oncorhynchus tshawytscha)渔业的管理需要平衡渔业准入和脆弱种群的保护。尽管准确、及时地估计特定种群的收获对于实现竞争目标至关重要,但有限数量的种群分配(例如,标签回收)可能会降低估计的效用。我们使用了一种灵活的模拟方法,应用于理论和现实世界的渔业案例研究,以比较竞争监测替代方案和收获估计器的性能。我们试图提高随着时间的推移对收获和收获轨迹的点估计的准确性。贝叶斯模型在高水平的数据聚合中提供了与现有模型相似的准确点估计,通常改进了中间聚合中收获轨迹的估计,以及对不确定性的可靠估计。包含时间滞后的先验信息不一致地改进了对收获轨迹的估计。在编码线标签回收率同样增加 (33%) 的监测替代方案中,增加标签率导致目标库存的估计不确定性下降幅度最大 (37.5% 至 45.3%)。混合种群收获估算器的可变性能表明,它们的使用应在种群和渔业特定的基础上考虑,可能使用基于模拟的方法。增加标记率导致目标库存的估计不确定性下降幅度最大(37.5% 至 45.3%)。混合种群收获估算器的可变性能表明,它们的使用应在种群和渔业特定的基础上考虑,可能使用基于模拟的方法。增加标记率导致目标库存的估计不确定性下降幅度最大(37.5% 至 45.3%)。混合种群收获估算器的可变性能表明,它们的使用应在种群和渔业特定的基础上考虑,可能使用基于模拟的方法。
更新日期:2021-12-03
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