Title: Spatiotemporal dynamic of blue shark (Prionace glauca) associated with longline fishery in the Eastern Indian Ocean.

Fish stock management worldwide is based on stock assessment models. The relative abundance index of the species of interest is one of the most critical inputs in most stock assessment models. The main problem in determining the abundance index occurs in a dependence survey, where the catchability covariates are highly influential on the species abundance index to cover the actual reality in nature. This study used the Vector Autoregressive Spatiotemporal Model (VAST) for blue shark species associated with Indonesian longline tuna fisheries in the Eastern Indian Ocean. The results indicated that the resulting abundance index was better with low residuals, excluded catchability, and included habitat covariates, making the results better than those of the conventional GLM model. The population density is well illustrated in the VAST model, where the VAST model can impute the population density in unfished areas to obtain a weighted area index. This is a distinct advantage, considering the many unfished areas in our research survey. This information is expected to benefit stakeholders in their decision making in the field.