Habitat suitability modelling of Nemipterus japonicus using MaxEnt in the Makran Sea

The Maximum Entropy Model (MaxEnt) is a high-performance machine learning algorithm that is used to investigate the presence of species and to forecast the possible distribution of a target species according to its maximum entropy under different conditions and to determine the habitat suitability of species. In the present study, habitat suitability modeling for Nemipterus japonicus in the Makoran region (northern shores of the Makran Sea) was performed using the Maximum Entropy Model (MaxEnt). For this purpose, the data obtained from the fishing of Nemipterus japonicus during the period of 2015 to 2019 recorded by the Chabahar Offshore Fisheries Research Center in five areas were used to find points of presence. Based on the results obtained from the model, the variables of sea surface temperature at night and day and chlorophyll a concentration were recognized as the most important parameters in identifying the suitable areas, including the Gowatr bay area. Also, the area under the curve index (AUC) was equal to 0.998, which indicates the high accuracy and efficiency of the model in identifying the most suitable areas of Nemipterus japonicus distribution. The obtained results can be used as an effective tool for effective evaluation of conservation strategies for sustainable yield of Nemipterus japonicus fish stocks.