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Liu Zhu'nan, Chen Xinjun. Forecasting model of abundance index of Cololabis saira in the Northwest Pacific under different climate condition[J]. Haiyang Xuebao, 2018, 40(6): 74-82. doi: 10.3969/j.issn.0253-4193.2018.06.007
Citation: Liu Zhu'nan, Chen Xinjun. Forecasting model of abundance index of Cololabis saira in the Northwest Pacific under different climate condition[J]. Haiyang Xuebao, 2018, 40(6): 74-82. doi: 10.3969/j.issn.0253-4193.2018.06.007

Forecasting model of abundance index of Cololabis saira in the Northwest Pacific under different climate condition

doi: 10.3969/j.issn.0253-4193.2018.06.007
  • Received Date: 2017-07-18
  • Rev Recd Date: 2017-09-13
  • 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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