Wan Lijun, Cheng Tianfei, Fan Wei, Shi Yongchuang, Zhang Heng, Zhang Shengmao, Yu Linlin, Dai Yang, Yang Shenglong
School of Navigation and Naval Architecture, Dalian Ocean University, Dalian, 116023, China.
Key Laboratory of East China Sea & Oceanic Fishery Resources Exploitation and Utilization, Ministry of Agriculture, East China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Shanghai, 200090, China.
Heliyon. 2024 Apr 1;10(7):e28953. doi: 10.1016/j.heliyon.2024.e28953. eCollection 2024 Apr 15.
Ecological fishery management requires high-precision fishery information to support resource management and marine spatial planning. In this paper, the Automatic Identification System (AIS) was adopted to extract the spatial information on the fishing grounds of light purse seine vessels in the Northwest Pacific Ocean. The spatial distributions of fishing grounds mapped by the data mining, kernel density analysis and hotspot analysis methods were compared. The spatial similarity index was applied to determine the spatial consistency between the computed spatial information and fisheries resource information. Finally, the spatial information derived by the best method was used to investigate the characteristics of fishing activity. The results showed that: the speed of light purse seine vessels related to operations was lower than 1.6 knots. The spatial information extracted by the three methods was consistent with the catch data distribution, and the spatial similarity between the fishing effort and catch data was the highest. The spatial variation in fishing activity was similar to that in the chub mackerel migration route. AIS data could be used to provide high-resolution fishery information. Light purse seine fishing vessels typically operate and travel along the exclusive economic zone boundary, and increased attention must be given to fishing vessel operation supervision. A comprehensive supervision system can be employed to monitor the operations of fishing vessels more effectively. The results of this study can provide technical support for the management of fishing activities and conservation of marine resources in this region using AIS data.
生态渔业管理需要高精度的渔业信息来支持资源管理和海洋空间规划。本文采用自动识别系统（AIS）提取西北太平洋海域灯光围网渔船渔场的空间信息。比较了通过数据挖掘、核密度分析和热点分析方法绘制的渔场空间分布。应用空间相似性指数来确定计算出的空间信息与渔业资源信息之间的空间一致性。最后，使用最佳方法得出的空间信息来研究捕捞活动的特征。结果表明：与作业相关的灯光围网渔船速度低于1.6节。三种方法提取的空间信息与渔获数据分布一致，捕捞努力量与渔获数据之间的空间相似性最高。捕捞活动的空间变化与鲐鱼洄游路线的空间变化相似。AIS数据可用于提供高分辨率的渔业信息。灯光围网渔船通常在专属经济区边界沿线作业和航行，必须更加重视对渔船作业的监管。可采用综合监管系统更有效地监测渔船作业。本研究结果可为利用AIS数据管理该区域捕捞活动和保护海洋资源提供技术支持。
