南海北部渔业生物声学密度的底表层间差异及与多类非生物因子的相关性分析  

Difference in the fishery resource density between the bottom and surface layers and an analysis of multiple types of related factor importance in the Northern South China Sea

作　　者：孙铭帅[1] 蔡研聪[1] 张魁[1] 许友伟[1] 杨玉滔 陈作志[1,2] SUN Mingshuai;CAI Yancong;ZHANG Kui;XU Youwei;YANG Yutao;CHEN Zuozhi(South China Sea Fisheries Research Institute,Chinese Academy of Fishery Sciences,Key Laboratory for Sustainable Utilization of Open-Sea Fishery,Ministry of Agriculture and Rural Affairs,Guangzhou 510300,China;Guangdong Provincial Key Laboratory of Fishery Ecology and Environment,Guangzhou 510300,China)

机构地区：[1]中国水产科学研究院南海水产研究所,农业农村部外海渔业可持续利用重点实验室,广东广州510300 [2]广东省渔业生态环境重点实验室,广东广州510300

出　　处：《中国水产科学》2024年第5期602-612,共11页Journal of Fishery Sciences of China

基　　金：广东省重点研发计划项目(2020B11111030001);中国水产科学研究院中央公益性科研机构基础研究基金项目(2023TD05);中国水产科学研究院中央级公益性科研院所基本科研业务费专项资金资助项目(2021SD01).

摘　　要：本研究旨在分析南海北部渔业生物在不同水层(表层混合层和底层冷水层)间声学密度的差异,并探讨这种差异与41种非生物因子的相关关系,以期为南海北部渔业资源的有效管理和保护提供科学依据。研究采用渔业声学方法,使用Simrad EY60分裂波束科学探鱼仪在南海北部进行声学数据采集。通过Echoview渔业声学数据处理系统分析声学数据,计算表层和底层的声学密度(NASC)。采用极限梯度提升算法(XGBoost)和随机森林算法(random forest)建模分析41种非生物因子对声学密度差异的影响,并评估因子的重要性。研究发现,底层渔业生物声学密度明显高于表层,底层平均值为106.00 m^(2)/nmi^(2),表层为43.39 m^(2)/nmi^(2)。极限梯度提升算法和随机森林算法的建模效果相似,重要性分析显示,温度因素(底层2 m温度、表–底温度差、表层2 m温度)和水深是影响声学密度差异的最关键因素。南海北部渔业资源的表层多、底层少的负值区域主要分布在海南岛周边。温度和水深是影响渔业生物分布差异的主要因素,而人类活动对磷酸盐、叶绿素等因子的调节也可能对声学密度差异产生影响。这些发现为南海北部渔业资源的管理和保护提供了重要科学依据。This study aims to analyze the differences in acoustic density of fishery resources between surface and bottom layers(surface mixed layer and bottom cold water layer)in the northern South China Sea and to explore the relationship between these differences and 41 abiotic factors.This research provides a scientific basis for the effective management and conservation of fishery resources in the northern South China Sea.The northern offshore area of the South China Sea is a crucial traditional fishing ground and an important spawning and feeding ground for marine fish.In recent years,fishery resources in this region have shown significant declines in age,size,and quality,attracting significant attention from both academia and fishery management authorities.Fishery acoustic methods were employed,using a Simrad EY60 split-beam scientific echosounder to collect acoustic data in the northern South China Sea.Acoustic data were analyzed using the Echoview fishery acoustic data processing system to calculate the acoustic density(NASC)of surface and bottom layers.Extreme Gradient Boosting(XGBoost)and Random Forest algorithms were utilized to model the influence of 41 abiotic factors on the differences in acoustic density and to assess the importance of these factors.Results indicated that the bottom layer had significantly higher acoustic density than the surface layer,with mean values of 106.00 m²/nmi²and 43.39 m²/nmi²,respectively.Both XGBoost and Random Forest models performed similarly,with temperature factors(bottom 2 m temperature,surface-bottom temperature difference,and surface 2 m temperature)and water depth identified as the most critical factors affecting acoustic density differences.The negative value region,where surface density exceeds bottom density,is primarily distributed around Hainan Island.The study concluded that temperature and water depth are the primary factors influencing the distribution differences of fishery resources,while human activities may also contribute by altering the concentrations of

关 键 词：非生物因子 极限梯度提升算法(XGBoost) 随机森林(Random Forest) 渔业声学 南海北部 

分 类 号：S931[农业科学—渔业资源]