Abstract
Overfishing and climate change have led to the depletion of fishery resources in the offshore South China Sea. The purpleback flying squid (Sthenoteuthis oualaniensis) has emerged as a promising alternative due to its ecological and economic value. However, information on its preferred habitat conditions remains scarce. This study integrates geostatistical and fisheries oceanographic approaches to explore optimal spatial-temporal scales for habitat modeling and to assess habitat changes under warming scenarios. Utilizing fishery data from 2013 to 2017, environmental variables including SST, sea surface temperature anomaly (SSTA), and chlorophyll-a concentration (CHL) were analyzed. Fishing effort data revealed significant seasonal differences, with the highest vessel numbers in summer and the lowest in autumn. Among the six modeling schemes, the combination of 0.5° × 0.5° spatial resolution and seasonal temporal resolution yielded the highest HSI model accuracy (84.02%). Optimal environmental ranges varied by season. Simulations of SST deviations (±0.2 °C, ±0.5 °C, and ±1 °C) showed that extreme warming or cooling could eliminate suitable habitats. These findings highlight the vulnerability of squid habitats to thermal shifts and support adaptive fishery strategies in the South China Sea.