基于AIS的黄渤海捕捞活动时空格局及其环境影响因素研究OA
Spatial and temporal patterns of fishing activities in the Yellow Sea and Bohai Sea and their environmental influencing factors based on AIS
船舶自动识别系统(automatic identification system,AIS)的广泛应用,为大范围、高精度获取渔船捕捞活动信息提供了重要数据支撑.为探究黄渤海捕捞活动的空间分布规律及其环境影响因素,基于 AIS获取的捕捞渔业数据集,量化分析了2014-2019年间黄渤海渔船捕捞努力量的时空动态变化特征,并结合同期海洋环境遥感数据,采用广义加性模型(generalized additive model,GAM)识别海洋环境因子对捕捞活动空间分布格局的影响.结果表明:研究期间,黄渤海渔船捕捞作业的规模结构发生明显变化,拖网类渔船的捕捞努力量占比下降,而刺网类渔船的捕捞努力量占比上升;9-12月为年内捕捞活动集中期,该时段内渔船捕捞努力量占全年的50%以上,且空间分布最为广泛;渔船捕捞活动高度集中于中国近海的渤海湾、辽东半岛南部、山东半岛沿岸、海州湾及韩国西部沿海,离岸60 km以内海域的捕捞努力量占比达88.7%以上;不同渔具类型渔船的捕捞活动空间分布存在明显差异.GAM 模型对黄渤海9-12月份渔船捕捞努力量空间分布的累计偏差解释率为72.5%,其中离岸距离与海表盐度是解释力最高的两个因子.研究结果可为黄渤海渔业捕捞空间管理和近海渔业资源修复提供决策支持.
The widespread application of automatic identification system(AIS)has provided crucial data support for the collection of large-scale,high-precision information on the fishing vessel activities.To investigate the distribution patterns of fishing activities in the Yellow Sea and Bohai Sea of China and their environmental influencing factors,a fishing vessel dataset obtained via AIS was used to quantitatively analyze the spatiotemporal dynamics of fishing effort by fishing vessels from 2014 to 2019.Combined with marine environmental remote sensing data from the same period,generalized additive model(GAM)was employed to simulate and identify the influence of marine environmental factors on the spatial distribution of fishing activities.The results indicate that,during the study period,there were significant changes in the scale and structure of fishing operations in the Yellow Sea and Bohai Sea.The proportion of fishing effort by trawlers decreased,while the proportion of operating time by gillnet vessels increased.The period from September to December was the peak season for fishing activities in that year,with fishing operations distributed most widely across this period,accounting for more than half of the annual fishing effort.Fishing activities were highly concentrated in China's coastal waters,particularly in the Bohai Sea,the southern part of the Liaodong Peninsula,the coast of the Shandong Peninsula,Haizhou Bay and the western coast of South Korea;over 88.7%of the fishing effort was concentrated in waters within 60 km of the coast,and there were marked spatial differences in the distribution of fishing activities among vessels using different types of fishing gears.GAM model explained 72.5%of the variance in the spatial distribution of total fishing effort by fishing vessels in the Yellow and Bohai seas between September and December.Distance from shore and sea surface salinity were the two environmental factors with the highest explanatory power for the spatial distribution of fishing activities.These findings can provide valuable decision support for the spatial management of the fishing industry and the restoration of nearshore fishery resources in the Yellow Sea and Bohai Sea.
张凌霄;吴晓青;陈仁丽;王钰萍
中国科学院烟台海岸带研究所,山东 烟台 264003||中国科学院大学,北京 100049中国科学院烟台海岸带研究所,山东 烟台 264003||山东省海岸带环境过程与生态安全修复实验室,山东 烟台 264003安徽理工大学碳中和科学与工程学院,合肥 231131中国科学院烟台海岸带研究所,山东 烟台 264003||中国科学院大学,北京 100049
农业科技
捕捞活动黄渤海AIS时空格局GAM模型环境因子
fishing activitiesYellow Sea and Bohai SeaAISspatio-temporal patternGAM modelenvironmental factor
《海洋渔业》 2026 (3)
314-328,15
山东省自然科学基金项目(ZR2020MD014)国家重点研发计划项目(2019YFD0900705)
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