基于GAM模型分析印度洋大眼金枪鱼和黄鳍金枪鱼渔场分布与不同环境因子关系

徐国强; 朱文斌; 张洪亮; 周永东; 陈峰

doi:10.3969/j.issn.0253-4193.2018.12.008

基于GAM模型分析印度洋大眼金枪鱼和黄鳍金枪鱼渔场分布与不同环境因子关系

doi: 10.3969/j.issn.0253-4193.2018.12.008

浙江省海洋水产研究所, 浙江舟山 316021;农业部重点渔场渔业资源观测实验站, 浙江舟山 316021;浙江省海洋渔业资源可持续利用技术研究重点实验室, 浙江舟山 316021

基金项目: 浙江省科学技术厅2018年度重点研发计划项目（2018C02026）；农业基础性长期性科技工作国家渔业科学数据中心观测监测任务（ZX08S120357）；农业部基础性长期性科技工作——远洋渔场及关键渔业资源调查监测（ZX08S120363）。

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出版历程
- 收稿日期: 2018-03-05
- 修回日期: 2018-07-01

Relationship between fishing grounds of Thunnus obesus and Thunnus albacores with environmental factors in the Indian Ocean based on generalized additive model

Marine Fisheries Research Institute of Zhejiang Province, Zhoushan 316021, China;Scientific Observing and Experimental Station of Fishery Resources for Key Fishing Grounds, Ministry of Agriculture, Zhoushan 316021, China;Key Laboratory of Sustainable Utilization of Technology Research for Fishery Resource of Zhejiang Province, Zhoushan 316021, China

摘要

摘要: 印度洋金枪鱼延绳钓渔业作为我国重要的远洋渔业之一，探究其渔场时空变动及与环境因子之间的关系十分必要。本文根据2016年1—6月收集的印度洋金枪鱼渔业生产数据，并结合卫星遥感获取的环境因子数据，运用ArcGIS和GAM模型分析了印度洋大眼金枪鱼和黄鳍金枪鱼渔场时空变动及与环境因子之间的关系。研究结果表明：大眼金枪鱼和黄鳍金枪鱼1—6月CPUE均呈现先减小后增加的趋势，4月均达最高值，分别为2.45尾/千钩和3.56尾/千钩，各月CPUE均存在显著性差异（P<0.001）；大眼金枪鱼和黄鳍金枪鱼渔场时空变动基本趋于一致，均为先向东北移动，后向西北移动，最后再向东北移动的趋势；GAM模型分析显示，大眼金枪鱼CPUE与模型因子的解释率为32.1%，纬度和250 m水深温度影响最显著，黄鳍金枪鱼CPUE与模型因子的解释率为37.2%，200 m水深温度影响最显著；协同分析表明，1—6月，印度洋金枪鱼延绳钓中心渔场分布于1°S~9.5°N，47°~64°E，且海表温度在29.3~30.8℃的海域。
- 印度洋 /
- 金枪鱼延绳钓 /
- 时空变动 /
- GAM模型 /
- 中心渔场
Abstract: As one of the important offshore fisheries in China, the tuna longline fishery in the Indian Ocean is indispensable to explore the spatial and temporal changes in fisheries and their relationship with different environmental factors. Based on the Indian Ocean tuna fishery production data collected from January to June of 2016, combined with the data of environmental factors obtained by satellite remote sensing, ArcGIS and GAM models were used to analyze the temporal and spatial changes of Thunnus obesus and Thunnus albacares fishing grounds in the Indian Ocean and their relationship with different environmental factors. The results showed that:CPUE values of T. obesus and T. albacares were first decreased and then increased from January to June, reaching the highest values in April, with 2.45 ind/thousand hooks and 3.56 ind/thousand hooks respectively. There was significant difference in each month's CPUE (P <0.001); the temporal and spatial changes of T. obesus and T. albacares fishing grounds tended to be the same. They were the first to the northeast, the latter to the northwest, and finally to the northeast; GAM model analysis showed that the interpretation rate of CPUE and model factors was 32.1% for T. obesus, and latitude and 250 m water depth temperature had the most significant effect. The interpretation rate of CPUE and model factors for T. albacares was 37.2%, and the temperature at 200 m depth was the most significant; according to the collaborative analysis, from January to June, the tuna longline fishing center in the Indian Ocean distributed in 1°S~9.5°N, 47°~64°E, and the sea surface temperature was in the sea area 29.3~30.8℃.
- Indian Ocean /
- tuna longline /
- spatio-temporal change /
- GAM model /
- central fishing ground

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