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基于GAM模型分析水温垂直结构对热带大西洋大眼金枪鱼渔获率的影响
引用本文:杨胜龙,张忭忭,唐宝军,化成君,张胜茂,范秀梅,戴阳,冯春雷.基于GAM模型分析水温垂直结构对热带大西洋大眼金枪鱼渔获率的影响[J].中国水产科学,2017,24(4):875-883.
作者姓名:杨胜龙  张忭忭  唐宝军  化成君  张胜茂  范秀梅  戴阳  冯春雷
作者单位:1. 农业部东海与远洋渔业资源开发利用重点实验室, 上海 200090;中国水产科学研究院 渔业资源与遥感信息技术重点开放实验室, 上海 200090;2. 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:国家自然科学基金项目(41606138),上海市自然科学基金项目(14ZR1449900),国家科技支撑计划项目(2013BAD13B01),上海市科技创新行动计划(15DZ1202201),中央级公益性科研院所基本科研业务费专项(2015M07)
摘    要:通过模型分析环境变量对延绳钓大眼金枪鱼渔获率的影响,评估适宜垂直活动空间对大西洋大眼金枪鱼延绳钓渔获率的作用。首先采用回归分析检验环境变量对延绳钓渔获率(由单位捕捞努力渔获量(catch per unit fishing effort,CPUE)表示)的影响显著性,结合时空变量,采用GAM(generalized additive model)模型分析各变量对大眼金枪鱼CPUE非线性作用。模型结果表明,环境因子和时空变量对热带大西洋延绳钓大眼金枪鱼渔获率空间分布影响明显。大西洋大眼金枪鱼延绳钓的高渔获率月份出现在夏季和冬季,空间上在赤道以北和30?~50?W。12℃等温线深度对大眼金枪鱼延绳钓渔获率的影响表现为抛物线形状,高渔获率出现在深度较浅的250 m水层,随着12℃等温线深度的增加,大眼金枪鱼延绳钓渔获率降低。温跃层下界深度和深度差对大眼金枪鱼延绳钓渔获率的影响都是穹顶状。随着温跃层下界深度值和深度差由小变大至200 m,延绳钓渔获率递增;温跃层下界深度和深度差超过200 m后,延绳钓渔获率变小。温跃层下界深度和深度差对大眼金枪鱼延绳钓渔获率影响显著的水层分别是200 m和50 m。研究结果显示,12℃等温线深度和温跃层对热带大西洋延绳钓大眼金枪鱼渔获率影响是交叉的,在大眼金枪鱼适宜垂直活动水层受限到和延绳钓作业深度相同时,延绳钓渔获率最高;在适宜垂直活动空间过深或者过浅时,延绳钓渔获率都变小,但可以通过改变作业方式提高渔获率。采用延绳钓CPUE进行渔场和资源评估要考虑金枪鱼适宜垂直活动空间。

关 键 词:大眼金枪鱼  GAM模型  Argo  水温垂直结构  渔获率  热带大西洋  CPUE
修稿时间:2017/7/21 0:00:00

Influence of vertical structure of the water temperature on bigeye tuna longline catch rates in the tropical Atlantic Ocean
YANG Shenglong,ZHANG Bianbian,TANG Baojun,HUA Chengjun,ZHANG Shengmao,FAN Xiumei,DAI Yang,FENG Chunlei.Influence of vertical structure of the water temperature on bigeye tuna longline catch rates in the tropical Atlantic Ocean[J].Journal of Fishery Sciences of China,2017,24(4):875-883.
Authors:YANG Shenglong  ZHANG Bianbian  TANG Baojun  HUA Chengjun  ZHANG Shengmao  FAN Xiumei  DAI Yang  FENG Chunlei
Institution:1. Key Laboratory of East China Sea & Oceanic Fishery Resources Exploitation and Utilization, Ministry of Agriculture, Shanghai 200090, China;2. Key and Open Laboratory of Remote Sensing Information Technology in Fishing Resource, East China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Shanghai 200090, China
Abstract:The vertical habitat of tuna has significant effects on the longline catch rates, which are primarily in-fluenced by oceanographic features. In order to support longline operations and fishery management, several key environmental factors were used to evaluate the influence of vertical habitat on longline catch rates in the tropical Atlantic Ocean. Regression model was used to determine the relationship between environment and longline catch rates, expressed as catch per unit fishing effort (CPUE), while generalized additive model (GAM) was used to evaluate the significance of environmental factors on CPUE. The results revealed that the environment and spa-tio-temporal factors had significant effects on catch rates, and the relationships were nonlinear. High catch rates were achieved in the summer and winter to the north of the equator, between 30°-50°W. The shape of the 12℃isolines (open para curves) showed influences on longline catch rates. High catch rates were observed where the depth was lower than 250 m. The hooking rates declined as the depth of 12℃ isolines increased to 400 m. The nonlinear effects of the low depths of thermoclines and relative depths were both like a dome. The longline catch rates increased as the thermocline depth and relative depth increased to 200 m, while at depths greater than 200 m, the catch rates decreased. There were strong relationships between longline catch rates and the thermocline depth and relative depth, which were 200 m and 50 m, respectively. These results suggest that the influences of 12℃isolines and thermoclines were cross. The catch rates reached maximum levels when the vertical habitat was com-pressed consistent with hooking depth and decreased when the vertical habitat depth was too large or too small, but could change by adjusting the depth of hooks. The vertical habitat of tuna should be taken into account in fi-sheries stock assessments and fishing grounds analyses.
Keywords:Thunnus obesus  GAM model  Argo  vertical structure of the water temperature  catch rates  the trop-ical Atlantic Ocean  CPUE
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