Construction and verification of a habitat suitability index model for the Indian Ocean albacore tuna

Abstract:

Because of its economic value and wide distribution, albacore tuna (Thunnus alalonga) has become one of the main fishing targets in the world’s marine fisheries. Prediction of albacore tuna can improve fishing efficiency and yield, and provide scientific basis for fishery production.The production data of albacore tuna in the Indian Ocean from 2006 to 2014 and three environmental factors of temperature, salinity and chlorophyll a concentration in the surface layer of the ocean were used in this study. The single-factor Suitability Index (SI) of Indian Ocean albacore tuna with various environmental factors was established monthly by using the single-variable non-linear index model. Then the arithmetic average method was used to obtain the comprehensive Habitat Suitability Index (HSI) model. Using the 2016 Indian ocean albacore tuna production data and the corresponding marine environment data, furthermore, the HSI model was verified based on the ArcGIS platform. The results show that the accuracy of the monthly fishing ground forecast is about 90.56% and the overall forecast accuracy for each HSI grade is 87.46%. Moreover, for the central fishing ground with I_HSI>0.5, the average accuracy rate is 71.82%. Considering that the average yield ratio of I_HSI>0.5 is 69.35%, it can be concluded that the established HSI model had a promising forecast effect for the Indian Ocean albacore tuna.