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¹ Urmia University, Artemia & Aquaculture Research Institute, Department of Ecology & Aquatic Stocks Management, P.O. Box: 57179-44514, Urmia, Iran.
² National Taiwan Ocean University, Department of Environmental Biology Fisheries Science, 2 Pei-Ning Rd. Keelung 20224, Taiwan.
³ National Taiwan Ocean University, Center of Excellence for Ocean Engineering, Keelung 20224, Taiwan
⁴ National Taiwan Ocean University, Doctoral Degree Program in Ocean Resource and Environmental Changes, Keelung DOI : 10.4194/TRJFAS19107 Viewed : 1721 - Downloaded : 1900 Skipjack tuna (SKJ) is one of the most targeted fish species globally, especially in the Indian Ocean. SKJ fishery data from Iranian purse seiners and multisatellite remote sensing data were used for hotspot habitat modeling from 2010 to 2018. Spatial and temporal variables were the most important predictors in the generalized additive model (GAM), and 58.6% of the variance was explained. In the MaxEnt model, sea surface temperature (SST), eddy kinetic energy (EKE), and sea surface height (SSH) were the most important predictors of SKJ hotspot habitat suitability in the tropical Indian Ocean between 2°S and 2°N. Furthermore, of the total studied area in the Indian Ocean defined as optimal habitat (habitat suitability index>0.6), 6.8% and 5.3% exhibited ordinary habitat suitability (AUC=0.934, P<0.01) and hotspot habitat suitability (AUC=0.952, P<0.01), respec tively. Iranian purse seiners are distributed mainly in tropical areas, and in the present study, SKJ habitat was affected by environmental variables, as determined using multisatellite remote sensing data. In general, for effective regional monitoring and management strategies to ensure sustainable fisheries, diverse datasets compiled using satellite datasets and habitat modeling can help identify potential hotspot habitats, thereby enabling more accurate suitable habitat zone predictions and more efficient stock management. Keywords : Skipjack tuna Habitat modeling Tropical Indian Ocean Multisatellite remote sensing Fisheries management