基于多尺度渔业数据的印度洋大眼金枪鱼CPUE标准化研究  

CPUE standardization for Thunnus obesus in the Indian Ocean based on multi-scale fisheries data

作　　者：张天蛟 信佳 宋利明[2,3] 袁红春 宋博[4] ZHANG Tianjiao;XIN Jia;SONG Liming;YUAN Hongchun;SONG Bo(College of Information Technology,Shanghai Ocean University,Shanghai 201306,China;College of Marine Living Resource Sciences and Management,Shanghai Ocean University,Shanghai 201306,China;National Engineering Research Center for Oceanic Fisheries,Shanghai 201306,China;China Institute of FTZ Supply Chain,Shanghai Maritime University,Shanghai 201306,China)

机构地区：[1]上海海洋大学信息学院,上海2201306 [2]上海海洋大学海洋生物资源与管理学院,上海210306 [3]国家远洋渔业工程技术研究中心,上海每201306 [4]上海海事大学中国(上海)自贸区供应链研究院,上海210306

出　　处：《海洋渔业》2025年第2期129-140,共12页Marine Fisheries

基　　金：国家自然科学基金(项目编号:32403031);国家重点研发计划(项目编号:2023YFD2401301);“远洋渔业资源可持续开发”重点实验室开放基金(项目编号:A1-2006-23-200207)。

摘　　要：为了解不同空间尺度、环境因子及捕捞策略对大眼金枪鱼(Thunnus obesus)的单位捕捞努力量渔获量(CPUE)标准化的影响,基于3种空间分辨率的渔业数据:印度洋金枪鱼委员会(IOTC)5°×5°、1°×1°数据以及我国延绳钓渔业0.1°×0.1°的统计数据,针对我国延绳钓捕捞渔船在印度洋的作业区域,对比分析了海洋立体环境因子(包括0~500 m水深的温度、盐度、溶解氧浓度和温跃层深度)以及不同捕捞策略下的物种组成等因子对大眼金枪鱼CPUE标准化的影响。在标准化模型中,将5°、1°以及0.1°网格的地理面积作为模型权重。结果表明,在3种空间分辨率下,增加海洋立体环境因子、物种组成因子、采用网格面积作为模型权重能够显著提高CPUE标准化模型的拟合度;其中,温跃层深度和240 m深度的溶解氧浓度在CPUE标准化模型中的重要性较高;物种组成因子从空间上区分了不同捕捞策略下的物种关系,能够提高CPUE标准化的准确性;使用网格面积作为模型权重,可以适应不断变化的捕捞努力量和鱼群丰度,应在CPUE标准化模型中加以考虑。研究结果可为精准评估金枪鱼渔业资源提供科学参考。Research on the standardization of catch-per-unit-effort(CPUE)for Thunnus obesus is important for the conservation and sustainable management of its fishery resources.The challenge lies in the dynamic nature of fishing strategies,which can lead to variations in vertical environmental factors and species composition clusters,ultimately influencing CPUE standardization outcomes across diverse spatial scales.To gain a comprehensive understanding of these interactions,fishery data from three distinct spatial resolutions was collected:5°×5°and 1°×1°datasets from the Indian Ocean Tuna Commission(IOTC),and a high-resolution 0.1°×0.1°dataset from China's longline fishery.The focus was on the operational areas of Chinese longline fishing vessels in the Indian Ocean.We meticulously examined the influence of vertical environmental factors,including temperature,salinity,dissolved oxygen concentration,and thermocline depth within a water depth range of 0-500 m.Additionally,we considered species composition clusters,which reflected the complex interactions between Thunnus obesus and other species within the ecosystem.To enhance the robustness and reliability of our model,we incorporated the geographical area of the 5°,1°,and 0.1°grids as model weights.By incorporating these weights,we aimed to create a more accurate and representative model of CPUE standardization for Thunnus obesus.The findings offered several key insights into the factors influencing CPUE standardization for Thunnus obesus.Firstly,the thermocline depth and dissolved oxygen concentration at a depth of 240 m emerged as significant factors in the CPUE standardized model.These parameters likely played a crucial role in determining the habitat preferences and distribution patterns of Thunnus obesus in the Indian Ocean.Secondly,the inclusion of species composition clusters significantly improved the accuracy of standardized CPUE.This suggested that considering the interactions between Thunnus obesus and other species within the ecosystem was essential

关 键 词：大眼金枪鱼 多尺度渔业数据集 CPUE标准化 海洋立体环境因子 物种组成因子 网格面积 

分 类 号：S931[农业科学—渔业资源]