| 不同气候模态下西北太平洋秋刀鱼资源丰度预测模型建立 |
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| 引用本文： | 刘祝楠,陈新军. 不同气候模态下西北太平洋秋刀鱼资源丰度预测模型建立[J]. 海洋学报, 2018, 40(6): 74-82. DOI: 10.3969/j.issn.0253-4193.2018.06.007 |
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| 作者姓名： | 刘祝楠 陈新军 |
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| 作者单位： | 1.上海海洋大学 海洋科学学院, 上海 201306 |
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| 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（15DZ1202200）；海洋二号卫星地面应用系统项目（HY2A-HT-YWY-006）。 |
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| 摘 要： | 秋刀鱼（Cololabis saira）资源对海洋环境因素极为敏感，不同气候模态可能对秋刀鱼资源丰度产生不同的影响。根据1990-2014年西北太平洋日本的秋刀鱼渔业中单位捕捞努力量渔获量（CPUE，以此作为资源丰度），以及相应产卵场、索饵场的海表温（SST）遥感数据，探讨太平洋年际震荡（PDO）指数冷、暖年下，秋刀鱼资源丰度CPUE变化与产卵场、索饵场SST的关系，并分别建立资源丰度的预测模型。研究表明，PDO冷年索饵场4月SST与年CPUE显著相关（P<0.05），PDO暖年索饵场11月的SST与年标准化CPUE显著相关（P<0.05）。PDO冷、暖年的秋刀鱼资源丰度的预测模型中，CPUE均与索饵场11月的SST、索饵场4月SST呈现正相关的关系，统计学上为显著相关（P<0.05）。PDO冷年（2012年）和PDO暖年（2014年）的CPUE预测值与实际值相对误差分别为14.03%、-16.26%，具有较好的拟合效果。研究认为，不同气候模态下，可用于秋刀鱼资源丰度预测的环境因子不同，上述建立资源丰度模型可用于业务化运行。
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| 关 键 词： | 西北太平洋 秋刀鱼 太平洋年代际震荡 海表温 资源丰度 |
| 收稿时间： | 2017-07-18 |
| 修稿时间： | 2017-09-13 |
Forecasting model of abundance index of Cololabis saira in the Northwest Pacific under different climate condition |
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| Liu Zhu''nan and Chen Xinjun. Forecasting model of abundance index of Cololabis saira in the Northwest Pacific under different climate condition[J]. Acta Oceanologica Sinica (in Chinese), 2018, 40(6): 74-82. DOI: 10.3969/j.issn.0253-4193.2018.06.007 |
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| Authors: | Liu Zhu''nan and Chen Xinjun |
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| Affiliation: | College of Marine Sciences, Shanghai Ocean University, Shanghai 201306, China and College of Marine Sciences, Shanghai Ocean University, Shanghai 201306, China;Key Laboratory of Oceanic Fisheries Exploration, Ministry of Agriculture, 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 Ocean University, Shanghai 201306, China;Scientific Observing and Experimental Station of Oceanic Fishery Resources, Ministry of Agriculture, Shanghai 201306, China |
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| Abstract: | Cololabis saira is extremely sensitive to marine environmental factors.Different climate conditions may have different effects on abundance index of Cololabis saira in the Northwest Pacific.We defined the year as cold year or warm year by annual average of Pacific Decadal Oscillation(PDO) index. Based on the data of the CPUE (catch per unit effort) and sea surface temperature (SST) data from remote sensing in the feeding grounds and spawning grounds in the Northwest Pacific from 1990 to 2014, the relationship between CPUE and SST is analyzed, and the forecasting model of abundance index is also established by using the linear regression models for the cold and warm index years.The results show that the SST of feeding ground is significantly related to the CPUE in April during cold years(P<0.05), and this phenomenon may be related to the Kuroshio enhancement in April. The SST of feeding ground is also significantly related to the CPUE in November during warm years(P<0.05), and this phenomenon may be related to the reduction of SST in November. It is also found that the forecasting modelsbetween CPUE and SST in the feeding ground during April and November are built, which is significant in statistics(P<0.05). During the PDO cold times (the year of 2012) and PDO warm times (the year of 2014), the relative error between CPUE predicted value and actual value is 14.03% and -16.26%, respectively, which have better fitting effect. The research shows that under different climate condition, the environmental factors used to forecast abundance index of Cololabis saira different. It is concluded that the forecasting model of abundance index can be used for the operation in the Cololabis saira fishery. |
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| Keywords: | Northwest Pacific Cololabis saira Pacific Decadal Oscillation sea surface temperature resource abundance |
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