Analysis of multi-scale effects and spatial heterogeneity of environmental factors influencing purse seine tuna fishing activities in the Western and Central Pacific Ocean
Wei Wang,
Wei Fan,
Linlin Yu,
Fei Wang,
Zuli Wu,
Jiashu Shi,
Xuesen Cui,
Tianfei Cheng,
Weiguo Jin,
Guolai Wang,
Yang Dai,
Shenglong Yang
Affiliations
Wei Wang
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; Key and Open Laboratory of Remote Sensing Information Technology in Fishing Resource, Chinese Academy of Fishery Sciences, Shanghai, 200090, China; College of Information, Shanghai Ocean University, Shanghai, 201306, China
Wei Fan
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; Key and Open Laboratory of Remote Sensing Information Technology in Fishing Resource, Chinese Academy of Fishery Sciences, Shanghai, 200090, China
Linlin Yu
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; Key and Open Laboratory of Remote Sensing Information Technology in Fishing Resource, Chinese Academy of Fishery Sciences, Shanghai, 200090, China; College of Information, Shanghai Ocean University, Shanghai, 201306, China
Fei Wang
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; Key and Open Laboratory of Remote Sensing Information Technology in Fishing Resource, Chinese Academy of Fishery Sciences, Shanghai, 200090, China
Zuli Wu
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; Key and Open Laboratory of Remote Sensing Information Technology in Fishing Resource, Chinese Academy of Fishery Sciences, Shanghai, 200090, China
Jiashu Shi
School of Navigation and Naval Architecture, Dalian Ocean University, Dalian, 116023, China
Xuesen Cui
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; Key and Open Laboratory of Remote Sensing Information Technology in Fishing Resource, Chinese Academy of Fishery Sciences, Shanghai, 200090, China
Tianfei Cheng
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; Key and Open Laboratory of Remote Sensing Information Technology in Fishing Resource, Chinese Academy of Fishery Sciences, Shanghai, 200090, China
Weiguo Jin
Shanghai Kaichuang Deep Sea Fisheries Co.Ltd, Shanghai, 200131, China
Guolai Wang
Shanghai Kaichuang Deep Sea Fisheries Co.Ltd, Shanghai, 200131, China
Yang Dai
Laoshan Laboratory, Qingdao, 266237, China
Shenglong Yang
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; Key and Open Laboratory of Remote Sensing Information Technology in Fishing Resource, Chinese Academy of Fishery Sciences, Shanghai, 200090, China; Corresponding author.
Understanding the spatial fishing activity distribution characteristics is important for the sustainable development of fisheries. Spatial nonstationarity is always present, especially in marine ecosystems. To explore how marine environmental factors affect the fishing effort of tuna purse seine vessels, data from 2015 to 2020 on the fishing activities of these fleets and environmental variables in the Western and Central Pacific Ocean (WCPO) were analyzed. A Generalized Additive Model (GAM), Geographically Weighted Regression model (GWR), and Multi-Scale Geographically Weighted Regression (MGWR) model were applied to explore the drivers of fishing activity and the impacts of environmental factors on spatial heterogeneity. The results indicate that: (1) The MGWR models has the highest prediction accuracy and effectively reflects the spatial heterogeneity and multi-scale effects of environmental factors in a year. (2) Environmental factors exhibit significant multi-scale effects and spatial heterogeneity on the fishing activities of purse seine tuna vessels. Sea floor depth, salinity at 200 m depth and sea surface temperature show the greatest spatial heterogeneity in their impact on fishing activities. (3) Sea surface temperature, distance to port, and primary productivity and salinity at 200 m depth are key variables influencing the fishing activities of purse seine tuna vessels. These findings are expected to provide scientific and effective guidance for fishery management and sustainable development by assessing the spatial variations in fishing activities at multiple scales.
