基于AIS数据的西北太平洋鱿鱼跳汰渔船捕捞区域适宜性评价

IF 2.1 3区 农林科学 Q2 FISHERIES
Fishes Pub Date : 2023-10-23 DOI:10.3390/fishes8100530
Yingjie Fei, Shenglong Yang, Mengya Huang, Xiaomei Wu, Zhenzhen Yang, Jiangyue Zhao, Fenghua Tang, Wei Fan, Sanling Yuan
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引用次数: 0

摘要

了解渔业活动的空间分布和适宜的渔区对改善渔业可持续管理和保护脆弱鱼类资源具有重要意义。为了确定西北太平洋鱿鱼跳汰渔船与气候相关的栖息地变化和捕捞活动分布的变化,采用两种方法(加权算术平均值法,weighted- amm;利用不同深度的海洋环境数据,建立了生境适宜性指数(HSI)模型的加权几何平均方法(weighted geometric mean method,加权gmm)。采用增强回归树(boosting regression tree, BRT)模型获取月度重要环境变量及相应变量的相对影响。结果表明,加权amm比加权gmm具有更好的预测性能。适宜渔区在空间位置和覆盖面积上均表现出明显的季节变化。热点图显示,2012 ~ 2019年全年适合跳鱿鱼渔船的捕捞区域在42°N ~ 44°N、155°E ~ 170°E范围内,提示在渔业管理中应重视跳鱿鱼渔船的高捕捞压力。HSI模型对中国企业渔业数据除6月和7月外均有较好的预测效果。此外,捕鱼努力可以用作渔业研究的替代数据。该研究还表明,渔业数据受到时空分布和捕鱼经验的限制,这可能会使研究结果产生偏差。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Evaluating Suitability of Fishing Areas for Squid-Jigging Vessels in the Northwest Pacific Ocean Derived from AIS Data
Understanding the spatial distribution of fishing activity and suitable fishing areas is important for improving sustainable fisheries management and protecting vulnerable fish stocks. To identify climate-related habitat changes and variations in the distribution of fishing activity for squid-jigging vessels in the Northwest Pacific Ocean, two types (weighted arithmetic mean method, weighted-AMM; weighted geometric mean method, weighted-GMM) of habitat suitability index (HSI) models were developed in this study with marine environmental data at different depths. The boosted regression tree (BRT) model was adopted to access the monthly important environmental variables and the relative influence of the corresponding variables. The results showed that the weighted-AMM has better prediction performance than the weighted-GMM. The suitable fishing areas showed significant seasonal changes in both spatial location and coverage area. The hotspot map showed that the suitable fishing area for squid-jigging vessels was located in the scope of 42∘ N∼44∘ N, 155∘ E∼170∘ E throughout the year during 2012∼2019, which suggests that high squid-jigging fishing pressure should be given more attention in fishery management. The HSI model also had good prediction performance for the fishery data of Chinese companies, except for June and July. Additionally, fishing efforts could be used as alternative data for fishery research. The study has also suggested that fishery data are restricted by spatial and temporal distribution and fishing experience, which probably biases the results of the research.
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Fishes
Fishes Multiple-
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1.90
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311
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