Journal of Marine Sciences ›› 2018, Vol. 36 ›› Issue (4): 60-67.DOI: 10.3969/j.issn.1001-909X.2018.04.008

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The grey predict model construction of abundance forecasting for skipjack tuna (Katsuwonus pelamis) in the Western and Central Pacific Ocean based on different environmental factors

FANG Zhou1,2,3,4, CHEN Yang-yang1, CHEN Xin-jun*1,2,3,4, GUO Li-xin1   

  1. 1. College of Marine Sciences, Shanghai Ocean University, Shanghai 201306, China;
    2. The Key Laboratory of Sustainable Exploitation of Oceanic Fisheries Resources, Ministry of Education, Shanghai 201306, China;
    3. National Engineering Research Center for Oceanic Fisheries, Shanghai 201306, China;
    4. Key Laboratory of Oceanic Fisheries Exploration, Ministry of Agriculture, Shanghai 201306, China
  • Received:2018-08-07 Revised:2018-09-18 Online:2018-12-15 Published:2022-11-18

Abstract: Skipjack tuna (Katsuwonus pelamis) is widely distributed in the tropical and subtropical water of the worlds ocean, and has high abundance in the Western and Central Pacific Ocean. Evaluating the relationship between its abundance and environment factors using forecasting model is pivotal for sustainable exploration of this species. According to the catch data of skipjack tuna in the Western and Central Pacific during 1998-2013, we used catch per unit effort (CPUE) as an indicator of abundance and analyzed the grey correlation between each environmental factor and CPUE. The optimal model was constructed by choosing suitable environmental factor and comparing the prediction of multiple grey forecasting models with different environmental factors. The results showed that the catch of skipjack tuna gradually increased year after year, whereas CPUE fluctuate dramatically within years. The model M1 including four environmental factors, sea surface temperature, sea surface height, chlorophyll-a, and sea surface temperature anomaly in Nino3.4, was the best model among models with multiple environmental factors, the models mean relative error was 6.475 2 and correlation was 0.687 4 between fitting abundance sequence and predict abundance. The model S2 eliminating SST in November and containing that of May and June, was the best model among the models with single environmental factor, the models mean relative error was 7.419 2 and correlation was 0.791 0 between fitting abundance sequence and predict abundance. The model based on single environmental factor showed a stable and high correlation between actual and predict value, comparing with models based on multiple environmental factors. Therefore, the former forecasting model should be used as suitable model for the prediction of skipjack tuna abundance in the Western and Central Pacific Ocean.

Key words: skipjack tuna, environmental factor, grey system, relative abundance, forecasting model

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