Predicting Fishing Grounds of the Offshore and High Seas Longline Fishery of Sri Lanka Using Oceanographic Conditions in the Indian Ocean

Abstract

The fishing grounds of the multiday longline fisheries of Sri Lanka are identified from the remote sensed satellite data measurements. The fisheries catch rates of longlines relevant to the major commercially targeted fish species (Thunnus albacares, Xiphius gladius and Thunnus obesus) in the Indian Ocean was calculated by the Generalized Additive Model (GAM) and the Empirical Cumulative Distribution Function (ECDF) model. The optimum oceanographic conditions of the sea surfaces including the Temperature (SST), Chlorophyll (SSC), Salinity (SSS), Height (SSH), Eddy Kinetic Energy (EKE) and the Mixed Layer Depth (MLD) relevant to the target fish species were analyzed to ascertain the relationship between the catch rates and spatiotemporal distribution of Potential Fishing Zones (PFZ). The Catch Per Unit Effort (CPUE) varied in the South–West and North- East monsoon seasons. Four main regions; Bay of Bengal, Exclusive Economic Zone (EEZ) of Sri Lanka, Eastern and western margins of the Maldives island EEZ, and the East-Central Arabian Sea in the Indian Ocean were observed as highly aggregated PFZ. The best fitting models in the GAM analysis indicates that all the oceanographic parameters influence in different proportions for the abundance of the fish species. It can be concluded that SST is the primary driving force of the fish distribution in the ocean. The SSC and SSS indicate that the fluctuating sensitivities considerably impacts on the fish distribution. Results suggest that the optimum oceanographic conditions derived for the fish species can be useful for tracking and predicting the potential fishing grounds in the Indian Ocean. However, the reliability of model results strictly depends on the fisheries catch data recordings that can cause errors related to the catch rates and the prediction of fishing grounds.