基于灰色系统的西北太平洋柔鱼冬春生群资源丰度预测模型

高雪; 陈新军; 余为

doi:10.3969/j.issn.0253-4193.2017.06.006

基于灰色系统的西北太平洋柔鱼冬春生群资源丰度预测模型

doi: 10.3969/j.issn.0253-4193.2017.06.006

1.
上海海洋大学海洋科学学院, 上海 201306
2.
上海海洋大学海洋科学学院, 上海 201306;国家远洋渔业工程技术研究中心, 上海 201306;上海海洋大学大洋渔业可持续开发教育部重点实验室, 上海 201306

基金项目: 海洋局公益性行业专项（20155014）；上海市科技创新计划（15DZ1202200）资助。

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出版历程
- 收稿日期: 2016-08-10
- 修回日期: 2016-12-26

Forecasting model of the abundance index of winter-spring cohort of neon flying squid (Ommastrephes bartramii) in the Northwest Pacific Ocean based on grey system theory

1.
College of Marine Science, Shanghai Ocean University, Shanghai 201306, China
2.
College of Marine Science, Shanghai Ocean University, Shanghai 201306, China;National Engineering Research Center for Oceanic Fisheries, Shanghai 201306;The Key Laboratory of Sustainable Exploitation of Oceanic Fisheries Resources, Ministry of Education, Shanghai Ocean University, Shanghai 201306, China

摘要

摘要: 柔鱼（Ommastrephes bartramii）是西北太平洋重要的经济头足类之一，科学预测柔鱼资源丰度有利于其合理的开发和利用。研究结合1998-2008年北太平洋柔鱼生产统计数据和产卵场环境及其气候因子，使用灰色关联分析和灰色预测建模的方法，对产卵期内（1-4月）影响柔鱼冬春生群体资源丰度（CPUE）的产卵场环境以及气候指标进行分析，并建立柔鱼冬春生群体资源丰度的预报模型。结果表明，产卵期内影响柔鱼冬春生群体资源丰度的因子依次是：3月份产卵场平均海表面温度SST（average sea surface temperature）、1月份太平洋年代际震荡指数PDO（Pacific Decadal Oscillatio index），4月份Niño3.4指标和4月份平均叶绿素浓度Chl a（average chlorophyll a concentration）。灰色预报模型分析表明，基于3月份SST、1月份PDO和4月份Chl a的GM（1，4）模型有着较好的预测效果，其预测准确率在80%以上，可用于西北太平洋柔鱼冬春群体资源丰度的预测。
- 柔鱼 /
- 西北太平洋 /
- 灰色绝对关联度 /
- GM(1,N)模型
Abstract: Neon flying squid (Ommastrephes bartramii) is one of the most important economic cephalopods in the Northwest Pacific Ocean. Building scientific forecast model of abundance index to this squid is beneficial for its exploitation and utilization. In this study, based on the fishing data of this squid in Northwest Pacific Ocena from 1998 to 2008, we analyzed the relationship between the environmental and climatic factors and the catch per unit effort (CPUE) of the winter-spring cohort in its spawning grounds. Therefore, a CPUE forecast model of winter-spring cohort of neon flying squid was built. The grey correlation analysis showed that the most important factors affecting this squid CPUE included average sea surface temperature (SST) in March, Pacific Decadal Oscillatio index (PDO) in January, Niño3.4 index in April and average chlorophyll a concentration (Chl a) in April. Results suggested that the GM (1,4) model which did not include the Niño3.4 anomaly had the best model effects. And its average absolute error was 19.2%. Therefore, we suggested that this model can be used to forecast the CPUE of winter-spring cohort of neon flying squid.
- neon flying squid (Ommastrephes bartramii) /
- Northwest Pacific Ocean /
- grey absolute correlation index /
- GM(1,N) model

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