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1999—2011年东、黄海鲐资源丰度年间变化分析
引用本文:王从军,邹莉瑾,李纲,陈新军.1999—2011年东、黄海鲐资源丰度年间变化分析[J].水产学报,2014,38(1):56-64.
作者姓名:王从军  邹莉瑾  李纲  陈新军
作者单位:上海海洋大学海洋科学学院, 上海 201306;上海海洋大学海洋科学学院, 上海 201306;上海海洋大学大洋渔业资源可持续开发省部共建教育部重点实验室, 上海 201306;上海海洋大学农业部大洋渔业资源环境科学观测实验站, 上海 201306;上海海洋大学远洋渔业协同创新中心, 上海 201306;上海海洋大学海洋科学学院, 上海 201306;上海海洋大学大洋渔业资源可持续开发省部共建教育部重点实验室, 上海 201306;上海海洋大学农业部大洋渔业资源环境科学观测实验站, 上海 201306;上海海洋大学远洋渔业协同创新中心, 上海 201306;上海海洋大学海洋科学学院, 上海 201306;上海海洋大学大洋渔业资源可持续开发省部共建教育部重点实验室, 上海 201306;上海海洋大学农业部大洋渔业资源环境科学观测实验站, 上海 201306;上海海洋大学远洋渔业协同创新中心, 上海 201306
基金项目:国家“八六三”高技术研究发展计划(2012AA092303);国家发改委产业化专项(2159999);上海市科技创新行动计划(12231203900);国家科技支撑计划(2013BAD13B01)
摘    要:根据1999—2011年我国鲐大型灯光围网渔业数据,使用广义线性模型(generalized linear model,GLM)和广义加性模型(generalized additive model,GAM)估算了影响CPUE的时间(年、月)、空间(经度、纬度)、捕捞性能和环境效应海表面温度(sea surface temperature,SST)、海表面高度、海表面叶绿素浓度],并以年效应作为资源丰度指数,分析了东、黄海鲐资源丰度的年间变化,东、黄海鲐资源丰度指数的年间变化与产卵场海表面温度以及捕捞强度间的关系。GAM结果表明,时间、空间、捕捞和环境变量对CPUE偏差的解释率为11.69%,其中变量年的解释率最大,占总解释率的38%。结果显示,1999—2011年东、黄海鲐鱼资源丰度指数(abundance index,AI)总体上呈下降趋势,2008年以来更是持续下降,丰度指数由2008年的1.22降至2011年的0.82。东、黄海鲐资源丰度指数年间与产卵场呈正相关,关系式为AI=-3.51+0.23SST(P0.05),这表明较高的产卵场SST对鲐资源量增加有利。过高的渔获量以及我国群众围网渔业渔船数量的快速增长是导致近年来鲐鱼资源下降的重要原因。

关 键 词:  丰度指数  年效应  单位捕捞努力量(CPUE)  广义加性模型
收稿时间:2013/5/24 0:00:00
修稿时间:2013/11/12 0:00:00

Analysis of the inter-annual variation of chub mackerel abundance in the East China Sea and Yellow Sea during 1999-2011
WANG Congjun,ZOU Lijin,LI Gang and CHEN Xinjun.Analysis of the inter-annual variation of chub mackerel abundance in the East China Sea and Yellow Sea during 1999-2011[J].Journal of Fisheries of China,2014,38(1):56-64.
Authors:WANG Congjun  ZOU Lijin  LI Gang and CHEN Xinjun
Institution:College of Marine Science, Shanghai Ocean University, Shanghai 201306, China;College of Marine Science, Shanghai Ocean University, Shanghai 201306, China;Key Laboratory of Sustainable Exploitation of Oceanic Fisheries Resources, Ministry of Education, Shanghai Ocean University, Shanghai 201306, China;Scientific Observing and Experimental Station of Oceanic Fishery Resources, Ministry of Agriculture, Shanghai Ocean University, Shanghai 201306, China;Collaborative Innovation Center for Distant-water Fisheries, Shanghai Ocean University, Shanghai 201306, China;College of Marine Science, Shanghai Ocean University, Shanghai 201306, China;Key Laboratory of Sustainable Exploitation of Oceanic Fisheries Resources, Ministry of Education, Shanghai Ocean University, Shanghai 201306, China;Scientific Observing and Experimental Station of Oceanic Fishery Resources, Ministry of Agriculture, Shanghai Ocean University, Shanghai 201306, China;Collaborative Innovation Center for Distant-water Fisheries, Shanghai Ocean University, Shanghai 201306, China;College of Marine Science, Shanghai Ocean University, Shanghai 201306, China;Key Laboratory of Sustainable Exploitation of Oceanic Fisheries Resources, Ministry of Education, Shanghai Ocean University, Shanghai 201306, China;Scientific Observing and Experimental Station of Oceanic Fishery Resources, Ministry of Agriculture, Shanghai Ocean University, Shanghai 201306, China;Collaborative Innovation Center for Distant-water Fisheries, Shanghai Ocean University, Shanghai 201306, China
Abstract:Relative abundance index is often used to measure the level of fisheries resources biomass.Based on chub mackerel(Scomber japonicus)catch data of the large lighting-purse seine fishery from 1999 to 2011,the impacts of temporal(Year,Month),spatial(Longitude,Latitude),environmental factors(Sea surface temperature,Sea surface height and Sea surface chlorophyll-a concentration)and fishing performance(Vessel name)on catch per unit effort(CPUE)were analyzed using generalized linear model(GLM)and generalized additive model(GAM).The Year effect of CPUE,extracted from GAM,was used as the annual abundance index(AI)to reflect the inter-annual variation of chub mackerel abundance in the East China Sea and Yellow Sea.The relationship between AI and SST in the chub mackerel spawning ground and fishing effort was also investigated.The GAM with the eight variables explains 11.69% of the total variance in nominal CPUE,and the impact of Year on CPUE is the foremost factor,contributing to 53.9% of the total reduction in deviance.The extracted Year effect indicates that chub mackerel abundance shows a declining trend over the past 13 years,especially after 2008,and the AI fell from 1.22 in 2008 to 0.82 in 2011.The AI shows a significantly positive relationship with the SST of the spawning ground,and it is expressed as AI=-3.5+023SST(P<0.05).This result indicates that SST of the spawning ground has a positive impact on the abundance of chub mackerel.The decrease of chub mackerel abundance in the East China Sea and Yellow Sea resulted from the rapidly increasing number of purse seine vessels in the recent years.
Keywords:Scomber japonicus  abundance index  year effect  catch per unit effort(CPUE)  generalized additive model(GAM)
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