Predicting present spatial distribution and habitat preferences of commercial fishes using a maximum entropy approach.

The knowledge of the geographical distribution and habitat preferences of marine species is the key to protecting marine ecosystems. Modeling the distribution of marine species through environmental variables is an essential step to understanding and reducing climate change effects on marine biodiversity and related human populations. In this study, the present distributions of commercial fishes including Acanthopagrus latus, Planiliza klunzingeri, and Pomadasys kaakan were modeled using the maximum entropy (MaxEnt) modeling technique and a set of 22 environmental variables. In total, 1531 geographical records belonging to three species were extracted from online databases Ocean Biodiversity Information System (OBIS, 829 records, 54%), Global Biodiversity Information Facility (GBIF, 17 records, 1%), and literature (685 records, 45%) during September to December 2022. The findings showed the values of area under the receiver operating characteristic (ROC) curve (AUC) above 0.99 for all species indicating the high performance of this technique to reflect the actual distribution of species. Environmental factors such as depth (19.68%), sea surface temperature (SST) (19.40%), and wave height (20.71%) were the strongest environmental predictors determining the present distribution and habitat preferences of the three commercial fish species. The Persian Gulf, Iranian coasts of the Sea of Oman, North Arabian Sea, North-East areas of the Indian Ocean, and North coasts of Australia are among the areas with ideal environmental conditions for the species. For all species, the percentage of habitats with high suitability (13.35%) was higher compared to habitats with low suitability (6.56%). However, a high percentage of species occurrence habitats had unsuitable conditions (68.58%) showing the vulnerability of these commercial fishes. Significant management strategies are needed to protect preferred habitats to minimize the effect of fishery and climate change on the population stocks of these commercial fishes. [ABSTRACT FROM AUTHOR]