论文
论文题目: Analysis of fishing intensity in the South China Sea based on automatic identification system data: A comparison between China and Vietnam
第一作者: Wu Wenzhou, Zhang Peng, Wang Qi, Kang Lu etc.
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发表年度: 2024
摘  要: ObjectiveRecently, the South China Sea has been facing a crisis of depleted fishery resources, primarily due to the impacts of illegal, unreported, and unregulated fishing activities, as well as overfishing. Accurately understanding the fishing activity intensity in the South China Sea holds significant implications for the sustainable management of fisheries resources.MethodsLeveraging the automatic identification system trajectory data from 2018, this paper employs spatial statistical methods and fishing effort indicators to comparatively analyze the spatial variations in fishing intensity between Chinese and Vietnamese fishing vessels.ResultThe results of this study show that (1) in 2018, the total fishing effort of Chinese fishing vessels in the South China Sea was 7.65 times that of Vietnamese vessels, but during China's South China Sea fishing moratorium, the fishing effort exerted by Vietnamese vessels surpassed that of China and (2) the top 10 ports in China and Vietnam support approximately 30% and 55.13% of their respective fishing intensities in the South China Sea.ConclusionThe study highlights significant variations in fishing intensity between Chinese and Vietnamese vessels and the substantial support provided by major ports. These findings offer valuable insights for fisheries resource monitoring and maritime spatial planning, contributing to the sustainable management of the South China Sea's fisheries resources. Impact statement This study sheds light on fishing by Chinese and Vietnamese vessels during the South China Sea fishing ban and the intensity of fishing by vessels supported by ports along the South China Sea. By understanding these patterns, we can better manage fishery resources in the South China Sea and ensure sustainable fishing.
英文摘要:
刊物名称: MARINE AND COASTAL FISHERIES
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论文类别: SCI