Application of a delta-generalized additive model to assess the impact of environmental changes on the spatial distribution of bigeye tuna (Thunnus obesus) in the Indian Ocean

Abstract

This study estimated the spatial distribution of bigeye tuna (Thunnus obesus) in the Indian Ocean under changing environmental conditions through habitat suitability modeling. Fisheries data from the Indian Ocean Tuna Commission and environmental satellite data from COPERNICUS were used in a delta-generalized additive model approach. This involved separately modeling the probability of presence or absence using binomial logistic regression and the positive catch using lognormal distribution. Results showed that sea surface temperature, mixed layer depth, and chlorophyll-a significantly influenced the presence of bigeye tuna in the Indian Ocean, whereas sea surface height, mixed layer depth, and chlorophyll-a exerted a substantial impact on their density. Adjusted simulated environmental data from 2020 to 2100 under three climate change scenarios (SSP126, SSP245, and SSP585) from Coupled Model Intercomparison Project Phase 6 were utilized to predict the future spatial distribution pattern of bigeye tuna in the Indian Ocean. Bigeye tuna is expected to variedly shift its spatial distribution under the three different climate change scenarios, with SSP585 having the most pronounced changes. Generally, bigeye tuna is predicted to spread poleward from the equator as a result of tropicalization in the higher latitudes.