Han Qingpeng, Shan Xiujuan, Gorfine Harry, Jin Yue, Wu Qiang, Teng Guangliang
Key Laboratory of Sustainable Development of Marine Fisheries, Ministry of Agriculture and Rural Affairs, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao, 266071, China.
Function Laboratory for Marine Fisheries Science and Food Production Processes, Qingdao Marine Science and Technology Center, Qingdao, 266237, China.
Sci Rep. 2025 Jul 9;15(1):24679. doi: 10.1038/s41598-025-10673-z.
Accurate stock assessment (SA) is an essential basis to ensuring effective fisheries management. The trade-off between data input and output accuracy makes the surplus production model (SPM), which lacks spatial information, a widely used stock assessment model. We coupled species spatio-temporal distribution (STD) with SPM to better understand stock status and facilitate (targeted and spatially refined) fisheries management. In our coupled STD-SA framework, the spatio-temporal model not only provides accurate biomass index for the SPM, but also provides critical habitat assessments to better complement localized spatial information on stock status and factors contributing to the risk of population fluctuation. We demonstrated our framework with a commercially important fish population of Trichiurus lepturus in the Yellow Sea Large Marine Ecosystem (YSLME), which was once on the verge of population collapse. The results suggested that the population size has recovered to an acceptable level since 2017 and is currently in a healthy state (98.2% of probability). But the Bohai Sea still needs to be emphasized for conservation. The population can be further exploited; however, small portions of localized habitat still need to be focused on. Our framework can help to identify and implement targeted interventions to address localized stock fluctuation.
准确的资源评估(SA)是确保有效渔业管理的重要基础。数据输入与输出准确性之间的权衡使得缺乏空间信息的剩余产量模型(SPM)成为广泛使用的资源评估模型。我们将物种时空分布(STD)与SPM相结合,以更好地了解资源状况并促进(有针对性且空间细化的)渔业管理。在我们的STD-SA耦合框架中,时空模型不仅为SPM提供准确的生物量指数,还提供关键栖息地评估,以更好地补充有关资源状况和导致种群波动风险因素的局部空间信息。我们以黄海大海洋生态系统(YSLME)中一种具有商业重要性的鱼类——带鱼为例展示了我们的框架,该种群曾一度濒临种群崩溃。结果表明,自2017年以来种群规模已恢复到可接受水平,目前处于健康状态(概率为98.2%)。但渤海仍需重点保护。该种群可以进一步开发利用;然而,仍需关注局部栖息地的小部分区域。我们的框架有助于识别和实施针对性干预措施,以应对局部资源波动。