A comparative study on forecasting model of the stock abundance index for the winter-spawning cohort of Todarodes pacificus in the Pacific Ocean based on the factor of SST

Todarodes pacificus is one of important resources of the ocean economic Ommastrephidae in the world. In order to forecast the stock abundance of winter-spawning cohort, the catch per unit effort (CPUE) as abundance index from T. pacificus stock assessment report of Japan in 2013 is used to establish the forecasting model in this study. The correlation analysis between sea surface temperature (SST) in the spawning areas of 28°N–40°N and 125°E–140°E and CPUE from January to March during 2000—2010 was carried out respectively to select the significantly affecting factors in statistics. The multivariate linear model and BP neural network model forecasting abundance index of T. pacificus winter-spawning population were established and compared, and the actual CPUE in 2011 and 2012 was used for validation. The results showed that the spawning areas with high correlation coefficient between CPUE and SST in Jan. to Mar. are S1 (30.5° N, 136.5° E) and S2 (31.5° N, 136.5° E) in January, the correlation coefficient are 0.71 and 0.70 respectively; S3 (30.5° N, 137.5° E) and S4 (30.5° N, 135.5° E)in February, and the correlation coefficient are 0.87 and 0.84, respectively; S5 (37.5° N, 129.5° E) and S6 (37.5° N, 130.5° E) in March, and the correlation coefficient are 0.72 and 0.70, respectively. Total of five forecasting models including multivariate linear model and BP neural network model with different structure are established and compared. The BP 6-4-1 neural network model is the best, and the average prediction accuracy of the CPUE value during 2011—2012 attained 98%. This study suggests that the model can be used as the forecasting model of the stock abundance for T. pacificus winter-spawning cohort.