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基于灰色系统西南大西洋阿根廷滑柔鱼资源丰度预测模型的构建
引用本文:王言丰,陈新军,陈芃,余景.基于灰色系统西南大西洋阿根廷滑柔鱼资源丰度预测模型的构建[J].海洋学报,2019,41(4):64-73.
作者姓名:王言丰  陈新军  陈芃  余景
作者单位:上海海洋大学 海洋科学学院,上海 201306;中国水产科学研究院 南海水产研究所,广东 广州 510300;上海海洋大学 海洋科学学院,上海 201306;农业农村部大洋渔业开发重点实验室,上海 201306;上海海洋大学国家远洋渔业工程技术研究中心,上海 201306;大洋渔业资源可持续开发教育部重点实验室,上海 201306;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 海洋科学学院,上海,201306;中国水产科学研究院 南海水产研究所,广东 广州,510300
基金项目:海洋局公益性行业专项(20155014),上海市科技创新行动计划(14DZ1205000)。
摘    要:阿根廷滑柔鱼(Illex argentinus)是西南大西洋鱿钓渔业的主要作业鱼种,对资源丰度进行准确的预测可指导企业合理安排渔业生产。因此,本研究根据2000-2016年我国西南大西洋阿根廷滑柔鱼的生产数据,以单位捕捞努力量的渔获量(Catch per unit effort, CPUE)为阿根廷滑柔鱼资源丰度的指标,利用灰色绝对关联分析和灰色预测建模的方法(GM(0, N)),计算2001-2015年CPUE的时间序列值与产卵期(6-8月)产卵场海表面温度(Sea surface temperature, SST)时间序列值的灰色绝对关联度,选取产卵场海域中灰色绝对关联度大于0.90的海区SST建立资源丰度预测模型,并用2016年实际CPUE进行验证。灰色绝对关联分析表明,6-8月,30°~40°S,45°~60°W海域内存在若干海区的SST与次年对数CPUE时间序列呈现较强的关联度,可作为预报因子。GM(0, N)模型结果表明,以6-8月产卵场SST作为环境因子建立的模型4能较好地拟合出阿根廷滑柔鱼资源丰度变动趋势,与2016年真实值相比,相对误差为7%,该模型可较好地作为阿根廷滑柔鱼资源丰度的预测模型。相反,包含6月和7月SST的模型1效果优于不包含6月SST的模型2或不包含7月SST的模型3,拟合得到的2016年的数据与真实值相比,相对误差分别为128%和289%,这说明6月和7月是西南大西洋阿根廷滑柔鱼的主要产卵月份。

关 键 词:阿根廷滑柔鱼  西南大西洋  灰色绝对关联分析  灰色预测GM(0  N)模型  产卵场
收稿时间:2018/3/22 0:00:00
修稿时间:2018/11/6 0:00:00

Prediction of abundance index of Argentine shortfin squid in the Southwest Atlantic Ocean based on grey system model
Wang Yanfeng,Chen Xinjun,Chen Peng and Yu Jing.Prediction of abundance index of Argentine shortfin squid in the Southwest Atlantic Ocean based on grey system model[J].Acta Oceanologica Sinica (in Chinese),2019,41(4):64-73.
Authors:Wang Yanfeng  Chen Xinjun  Chen Peng and Yu Jing
Institution:College of Marine Sciences, Shanghai Ocean University, Shanghai 201306, China;South China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Guangzhou 510300, China,College of Marine Sciences, Shanghai Ocean University, Shanghai 201306, China;Key Laboratory of Oceanic Fisheries Exploration, Ministry of Agriculture and Rural Affairs, Shanghai 201306, China;National Engineering Research Center for Oceanic Fisheries, Shanghai Ocean University, Shanghai 201306, China;Key Laboratory of Sustainable Exploitation of Oceanic Fisheries Resources, Ministry of Education, Shanghai 201306, China;Scientific Observing and Experimental Station of Oceanic Fishery Resources, Ministry of Agriculture and Rural Affairs, Shanghai 201306,College of Marine Sciences, Shanghai Ocean University, Shanghai 201306, China and South China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Guangzhou 510300, China
Abstract:Illex argentinus is the main fishing target in the southwest Atlantic. The accurate prediction of resource abundance can guide enterprises to arrange fishery production rationally. In this study, based on the fishing data of Illex argentinus in southwest Atlantic from 2001-2016, we computed the grey absolute correlation degree between the logarithmic CPUE sequence in the following year and SST sequence in the spawning ground from June to August . And we selected the points which the grey absolute correlation index was greater than 0.90 as the forecasting factors, and then a CPUE forecast of Illex argentinus in southwest Atlantic was established, and used the actual CPUE in 2016 to verify the model. The grey correlation analysis shows that there are a large number of points have strong grey correlation index between SST and CPUE sequence from June to August in the region 30°~40°S,45°~60°W. Results suggest that GM (0, 4) model, which includes average SST from June to August, has the best model effect. The relative error is 7%,which can be used in the prediction of resources abundance of Illex argentinus in the southwest Atlantic. In contrast, the GM (0, 3) does not include the spawning area''s mean SST in June and in July, which relative errors are 128% and 289% respectively. This suggests June and July are the main spawning months for Illex argentinus in Southwest Atlantic Ocean.
Keywords:Illex argentinus  Southwest Atlantic Ocean  grey absolute correlation index  GM (0  N) model  spawning grounds
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