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利用黄海代理CPUE指标加强数据有限渔业中基于渔获量的资源评估。

Enhancing catch-based stock assessment in data-limited fisheries with proxy CPUE indicators in the Yellow Sea.

作者信息

Wang Kun, Li Qi, Zhang Chongliang, Xu Binduo, Ren Yiping

机构信息

Fisheries College, Ocean University of China, 5# Yushan Road, Qingdao, 266003, China.

School of Aquatic and Fishery Sciences, University of Washington, Box 355020, Seattle, WA, 98195, USA.

出版信息

Sci Rep. 2025 Apr 1;15(1):11043. doi: 10.1038/s41598-025-95092-w.

Abstract

Catch-based methods are widely used in marine fisheries management, particularly for assessing fish stock status in data-limited fisheries. However, their reliability remains controversial, especially when only catch data are available. In fisheries with inadequate monitoring, Catch Per Unit Effort (CPUE) data are often unavailable, despite the potential availability of total fishing effort records for entire areas. Here, we evaluate the potential of a proposed proxy-CPUE indicator, defined as the ratio of total catch to total fishing effort metrics, as a substitute for CPUE to enhance catch-based methods. Using chub mackerel (Scomber japonicus) in the Yellow Sea as a case study, we developed proxy-CPUE indicators using three types of large-scale effort metrics: Gross Vessel Count (GVC), Gross Vessel Power (GVP), and Target Vessel Count (TVC). These indicators were incorporated into a Bayesian state-space Schaefer surplus production model (BSM) and their performance was compared to catch-only methods (CMSY) across key evaluation criteria, including robustness of estimation, reliability in retrospective analyses, and performance when encountering catch observation errors. Additionally, we conducted simulations to assess the impact of dynamic catchability, demonstrating that proxy-CPUE methods remain robust even when catchability varies over time. Results indicate that proxy-CPUE substantially improves the robustness of stock status estimates, especially by mitigating the impact of high catch observation errors-reducing estimate variations by 50% compared to catch-only methods. Both GVC-based and GVP-based proxy-CPUE demonstrated reliable performance in retrospective analyses. This study provides a practical and scalable solution for the management of fisheries facing similar data constraints.

摘要

基于渔获量的方法在海洋渔业管理中被广泛应用,特别是用于评估数据有限的渔业中的鱼类资源状况。然而,其可靠性仍存在争议,尤其是在仅有渔获量数据可用的情况下。在监测不足的渔业中,尽管整个区域可能有总捕捞努力量记录,但单位捕捞努力量(CPUE)数据往往不可得。在此,我们评估一种提议的代理CPUE指标的潜力,该指标定义为总渔获量与总捕捞努力量指标的比率,作为CPUE的替代指标以增强基于渔获量的方法。以黄海的鲐鱼(Scomber japonicus)为例,我们使用三种类型的大规模努力量指标:总船只数量(GVC)、总船只功率(GVP)和目标船只数量(TVC)来开发代理CPUE指标。这些指标被纳入贝叶斯状态空间Schaefer剩余产量模型(BSM),并根据关键评估标准将其性能与仅基于渔获量的方法(CMSY)进行比较,这些标准包括估计的稳健性、回顾性分析中的可靠性以及遇到渔获量观测误差时的性能。此外,我们进行了模拟以评估动态可捕性的影响,结果表明即使可捕性随时间变化,代理CPUE方法仍保持稳健。结果表明,代理CPUE显著提高了资源状况估计的稳健性,特别是通过减轻高渔获量观测误差的影响——与仅基于渔获量的方法相比,估计变化减少了50%。基于GVC和基于GVP的代理CPUE在回顾性分析中均表现出可靠的性能。本研究为面临类似数据限制的渔业管理提供了一种实用且可扩展的解决方案。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4503/11961763/071f187f304c/41598_2025_95092_Fig1_HTML.jpg

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