| 东海区小黄鱼繁殖模型优化选择及其管理应用研究 |
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| 引用本文： | 张辉,袁兴伟,程家骅.东海区小黄鱼繁殖模型优化选择及其管理应用研究[J].中国水产科学,2010,17(6). |
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| 作者姓名： | 张辉 袁兴伟 程家骅 |
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| 作者单位： | 1. 上海海洋大学,海洋科学学院,上海,201306;中国水产科学研究院,东海水产研究所,农业部海洋与河口渔业重点开放实验室,上海,200090
2. 中国水产科学研究院,东海水产研究所,农业部海洋与河口渔业重点开放实验室,上海,200090 |
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| 基金项目： | 农业部渔业资源动态监测调查项目，中央级公益性科研院所基本科研业务费专项基金(中国水产科学研究院东海水产研究所)资助项目 |
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| 摘 要： | 根据 1999-2008 年东海区渔业资源底拖网大面定点调查获取的小黄鱼(Larimichthys polyactis)渔业生物学资料,利用AIC(Akaike Information Criterion)与BIC(Bayesian Information Criterion),对小黄鱼的Ricker、Beverton-Holt和Cushing繁殖模型进行了拟合优度检验.针对选择的繁殖模型,经单因子相关分析和逐步回归分析,筛选对繁殖模型有重要影响的环境因子,经模型的拟合和检验,确定东海区小黄鱼的适用繁殖模型.结果表明:3种繁殖模型中,Ricker繁殖模型更适合模拟小黄鱼亲体与补充量关系,但吕泗渔场海域3-4月平均海水表温、7月海水表温和5月长江径流量、7-8月长江平均径流量以及当年夏季风速对模型中的补充量有着重要的影响;优化后的Ricker繁殖模型不仅可以提高东海区小黄鱼亲鱼量与补充量的拟合精度,而且可参考该模型修正当年度小黄鱼的资源管理目标,提高资源管理的科学性.
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| 关 键 词： | 东海区 小黄鱼 亲体量 补充量 繁殖模型 |
| 修稿时间： | 2010/11/19 0:00:00 |
Optimizing selection and application of reproduction model of small yellow croaker in the East China Sea |
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| ZHANG Hui,YUAN Xingwei,CHENG Jiahua.Optimizing selection and application of reproduction model of small yellow croaker in the East China Sea[J].Journal of Fishery Sciences of China,2010,17(6). |
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| Authors: | ZHANG Hui YUAN Xingwei CHENG Jiahua |
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| Abstract: | Based on time series of abundances collected from demersal trawling surveys in the East China Sea from 1999 to 2008, the author studied the relationship between stock and recruitment of the small yellow croaker in the East China Sea using Ricker, Beverton-Holt and Cushing reproduction models. The best relationship was selected using AIC (Akaike Information Criterion) and BIC (Bayesian Information Criterion) methods, respectively, which had the advantage of testing the significance of the difference between the functions of different model specifications. The environmental factors influencing the relationship between stock and recruitment, were selected using single factor correlation analysis and stepwise regression analysis. The result indicated that the Ricker reproduction model was the best among the three reproduction models. The environmental factors could obviously influence the average SST from March to April, and Julythe average runoff on May, July and August of Yangzi River and the speed of the summer monsoon in the very year. The optimized model not only increased the precision of predication ability of stock-recruitment model, but also could be used to improve the management objective of the stock. |
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| Keywords: | AIC BIC |
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