基于表层及温跃层环境变量的南太平洋长鳍金枪鱼栖息地适应性指数模型比较

郭刚刚; 张胜茂; 樊伟; 张衡; 杨胜龙

基于表层及温跃层环境变量的南太平洋长鳍金枪鱼栖息地适应性指数模型比较

1.
中国水产科学研究院东海水产研究所农业部东海与远洋渔业资源开发利用重点实验室, 上海 200090;上海海洋大学海洋科学学院, 上海 201306
2.
中国水产科学研究院东海水产研究所农业部东海与远洋渔业资源开发利用重点实验室, 上海 200090

基金项目: 国家科技支撑计划项目（2013BAD13B01）；上海市自然科学基金（14ZR1449900）；中央级公益性科研院所基本科研业务费专项资金项目（2015M07）

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出版历程
- 收稿日期: 2016-04-20

Comparative research on habitat suitability index models of albacore tuna (Thunnus alalunga) based on surface and thermocline environmental variables in the South Pacific Ocean

1.
Key Lab 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;College of Marine Sciences, Shanghai Ocean University, Shanghai 201306, China
2.
Key Lab 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

摘要

摘要: 为了量化比较海表层环境及温跃层环境对南太平洋长鳍金枪鱼渔场分布的影响程度；本研究采用2010-2012年南太平洋长鳍金枪鱼延绳钓渔船实际生产统计数据；结合卫星遥感所获取的海表面温度（sea surface temperature；SST）和海表面高度（sea surface height；SSH）数据以及Argo浮标所获取的温跃层上、下界水温和深度数据；运用外包络法分别构建了基于海表层环境变量、温跃层上界环境变量以及温跃层下界环境变量的3种栖息地适应性指数（habitat suitability index；HSI）模型。模型验证结果显示；基于海表层环境变量的HSI模型；HSI>0.6时所占产量比重为70.04%；投钩数量比重为70.86%；HSI>0.8时所占产量比重为24.92%；投钩数量比重为25.79%；基于温跃层上界环境变量的HSI模型；HSI>0.6时所占产量比重为82.17%；投钩数量比重为80.95%；HSI>0.8时所占产量比重为33.24%；投钩数量比重为32.69%；基于温跃层下界环境变量的HSI模型；HSI>0.6时所占产量比重为81.01%；投钩数量比重为81.54%；HSI>0.8时所占产量比重为43.51%；投钩数量比重为43.73%。研究发现；基于温跃层上界和下界环境变量的两个HSI模型预报精度明显高于基于表层环境变量的HSI模型；且基于温跃层下界环境变量的HSI模型预报精度高于基于温跃层上界环境变量的HSI模型。研究结果表明；相较于海表层环境；温跃层环境；尤其是温跃层下界环境特征对南太平洋长鳍金枪鱼资源分布的影响更为显著。
- 长鳍金枪鱼 /
- 表层 /
- 温跃层 /
- 栖息地适应性指数
Abstract: In order to compare the influence degree of surface and thermocline environmental factors on the distribution of albacore tuna fishing ground in the South Pacific quantifiably, this study adopted fishing statistics data of albacore tuna from 21 Chinese longline vessels in the South Pacific during 2010-2012, sea surface temperature (SST)and sea surface height (SSH) data from satellite remote sensing, and upper-bounds and bottom-bounds temperature and depth data of thermocline from Argo buoys, using the outer envelope method to construct three kinds of habitat suitability index (HSI) models based on above environmental variables. Model validation results shows that, HSI model based on sea surface environmental variables, when HSI value is higher than 0.6, the percentage of catch accounting for 70.04% and the percentage of hook numbers accounting for 70.86%, when HSI is higher than 0.8, the percentage of catch accounting for 24.92% and the percentage of hook numbers accounting for 25.79%; HSI model based on the thermocline upper-bounds environmental variables, when HSI value is higher than 0.6, the percentage of catch accounting for 82.17% and the percentage of hook numbers accounting for 80.95%, when HSI value is higher than 0.8, the percentage of catch accounting for 33.24% and the percentage of hook numbers accounting for 32.69%; HSI model based on the thermocline bottom-bounds environmental variables, when HSI value is higher than 0.6, the percentage of catch accounting for 81.01% and the percentage of hook numbers accounted for 81.54%, when HSI value is higher than 0.8, the percentage of catch accounting for 43.51%and the percentage of hook numbers accounted for 43.73%. The analysis shows that, compared to the sea surface environment, the thermocline environment, especially the effect of the thermocline bottom-bounds environmental characteristics is more significant to the distribution of South Pacific albacore tuna resource.
- albacore tuna /
- surface /
- thermocline /
- habitat suitability index

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