Journal of Dalian Ocean University  2023, Vol. 38 Issue (6): 1063-1071 DOI: 10.16535/j.cnki.dlhyxb.2023-041 |
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| Impact of vertical structure of water temperature during different fishing seasons on CPUE of neon flying squid (Ommastrephes bartramii) in the Northwest Pacific Ocean using GAM and BRT models |
| LIU Yue，CHEN Xinjun*，WANG Jintao
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| 1.College of Marine Sciences，Shanghai Ocean University，Shanghai 201306，China；2.Key Laboratory of Oceanic Fisheries Exploration，Ministry of Agriculture and Rural Affairs，Shanghai 201306，China；3.National Engineering Research Center for Oceanic Fisheries，Shanghai 201306，China；4.Key Laboratory of Sustainable Exploitation of Oceanic Fisheries Resources，Ministry of Education，Shanghai 201306，China |
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Abstract To explore the effect of water temperature at different depths and vertical structure of water temperature on catch per unit effort (CPUE) of neon flying squid (Ommastrephes bartramii) and to provide a guidance for the improvement of neon flying squid production efficiency, the influence of 0-300 m water temperature and vertical structure at different depths on the CPUE were analyzed based on the fishery data from May to November from 2015 to 2019, combined with the marine environmental data of the same period, the generalized additive model (GAM) and the boosting regression tree (BRT) during different fishing seasons. The stability and accuracy of the two models were evaluated using repeated ten-fold cross-validation. The results showed that the key factors screened by the GAM model based on the magnitude of deviation explained were found to be latitude (Lat), 150 m layer temperature (T150), 50-100 m water temperature gradient (G50-100), longitude (Lon), and 100-150 m water temperature gradient (G100-150) during the early fishing season (May to July). The BRT model screened factors in order of contribution rate were shown to be sea surface temperature (T0), 0-50 m water temperature gradient (G0-50), 50 m layer temperature (T50), Lat, and G50-100. During the main fishing season (August to November), however, the key factors selected by the GAM model based on the magnitude of deviation explained were Lat, Lon, T0, G0-50, and G50-100. The BRT model selected factors in order of contribution rate were G0-50, Lon, T0, Lat, and T50. The comparison of the two models indicated that BRT was better than the GAM to analyse the actual fishing data, with different key factors affecting CPUE in different stages of fishing season. The great influence on CPUE was observed in the upper-middle water temperature in the early fishing season, and great contribution to CPUE was found in the shallow water temperature in the main fishing season.
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Published: 18 January 2024
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