Influence of oceanographic parameters on the seasonal potential fishing grounds of Rastrelliger kanagurta using maximum entropy models and remotely sensed data

Understanding of the spatial distribution of fish habitats is crucial in order to achieve optimum fishing and to increase efficiency of marine resource management. In this study, seasonal potential suitability habitat model for Rastrelliger kanagurta off the east coast of Peninsular Malaysia was derived using maximum entropy (MaxEnt) by utilizing fishing locations and environmental parameters from remotely sensed sea surface temperature (SST) and chl-a concentration (chl-a) data. The influence of environmental parameters on the formation of the potential fishing zones was also determined. The results showed that all the seasonal models performed significantly better than random with AUC > 0.80, which indicated that the constructed models were applicable with ‘good’ to ‘excellent’ predictive accuracy. The model also showed that chl-a influenced R. kanagurta’s potential fishing ground during northeast and intermediate monsoon of October. Meanwhile, SST contributed more in defining the potential fishing grounds during southwest and intermediate monsoon period of April. The seasonal and spatial extents of potential fishing grounds were largely explained by chl-a (0.32-0.42 mg/m3 during northeast, 0.27-0.66 mg/m3 in April, 0.21-0.30 mg/m3 during southwest monsoon and 0.22-0.39 mg/m3 in October) and SST (29.05-29.94oC during northeast monsoon, 31.18-31.47oC in April, 31.17-31.48oC during southwest monsoon and 30.34-31.11oC in October). This indicated that seasonal changes in oceanographic parameters influenced spatial distribution of fish. The results also demonstrated the applicability and potential of MaxEnt in determination of potential fishing grounds and describing the influence of oceanographic factors on the formation of the area