College of Marine Sciences, Shanghai Ocean University, Shanghai, 201306, China.
Key Laboratory of Sustainable Exploitation of Oceanic Fisheries Resources, Ministry of Education, Shanghai, 201306, China.
Sci Rep. 2023 Sep 15;13(1):15290. doi: 10.1038/s41598-023-42521-3.
Most sophisticated stock assessment models often need a large amount of data to assess fish stocks, yet this data is often lacking for most fisheries worldwide, resulting in the increasing demand for data-limited stock assessment methods. To estimate fish stock status, one class of these data-limited methods uses simply catch time series data and, in other instances, life history information or fishery characteristics. These catch-only methods (COMs) built differently are known to make assumptions about changes in fishing effort and may perform differently under various fishing scenarios. As a case study, this paper used European anchovy (Engraulis encrasicolus) caught in the northwest African waters, though very economically and ecologically important, but still unassessed. Our study investigated the performance of five COMs under different fishing scenarios using as a reference the life-history information of the European anchovy captured in this region of the Atlantic. Hence, the present study developed a simulation approach to evaluate the performance of the five COMs in inferring the stock biomass status (B/B) with consideration of different fishing scenarios under prior information true to anchovy. All five COMs mostly underestimated B/B throughout the simulation period, especially under constant fishing mortality, and in the last five years of the simulation during all fishing scenarios. Overall, these COMs were generally poor classifiers of stock status, however, the state-space COM (SSCOM) generally performed better than the other COMs as it showed possibilities of recovering an overfished stock. When these methods were explored using actual anchovy catch data collected in the northwest African waters, SSCOM yielded results that were deferred from the other COMs. This study being the first to assess this species' stock in this area using a suite of COMs, presents more insights into the species stock status, and what needs to be considered before scientifically putting in place management measures of the stock in the area.
大多数复杂的渔业资源评估模型通常需要大量的数据来评估鱼类种群，但全球大多数渔业都缺乏这些数据，因此对数据有限的渔业资源评估方法的需求日益增加。为了评估鱼类种群状况，一类数据有限的方法仅使用渔获时间序列数据，在其他情况下，则使用生命史信息或渔业特征。这些仅基于渔获量的方法（COMs）在构建时存在假设，认为捕捞努力量会发生变化，并且在不同的捕捞场景下可能表现不同。作为案例研究，本文使用在西北非海域捕捞的欧洲无须鳕（Engraulis encrasicolus），尽管它们在经济和生态上都非常重要，但仍未得到评估。我们的研究使用在大西洋该区域捕获的欧洲无须鳕的生命史信息，调查了在不同捕捞场景下使用的五种 COMs 的性能。因此，本研究开发了一种模拟方法，以评估在考虑到与欧洲无须鳕相符的先验信息下，在不同捕捞场景下五种 COMs 推断种群生物量状况（B/B）的性能。在整个模拟期间，所有五种 COMs 都普遍低估了 B/B，尤其是在恒定的捕捞死亡率下，以及在所有捕捞场景的最后五年模拟期间。总体而言，这些 COMs 通常是种群状况的较差分类器，但是状态空间 COMs（SSCOMs）总体上表现优于其他 COMs，因为它显示出恢复过度捕捞种群的可能性。当使用在西北非海域收集的实际无须鳕渔获数据探索这些方法时，SSCOM 得出的结果与其他 COMs 不同。本研究是首次在该地区使用一系列 COMs 评估该物种的种群，为了解该物种的种群状况提供了更多的信息，并为在该地区科学制定种群管理措施之前需要考虑的因素提供了更多的信息。
