Mapping the monthly habitat dynamics of greater amberjack using MaxEnt model in the Taiwan Strait: Implications for sustainable blue transformations

Understanding species-habitat relationships is critical for marine ecosystem management. We applied maximum entropy (MaxEnt) model to assess how marine environmental variables shape the monthly distribution of greater amberjack ( Seriola dumerili ) in the Taiwan Strait (20°N–28°N), using historical (2014–2019) presence data. The models demonstrated strong presence-background discrimination (AUC > 0.9, TSS > 0.75). Map-based interpretation indicates that predicted suitable habitat expands in winter, peaks across Taiwan Strait in summer, and contracts to fragmented southwestern patches by late autumn; these spatial patterns are qualitative rather than quantified area estimates. Dominant environmental contributors shifted seasonally: sea surface height and mixed layer depth in winter-spring, sea surface temperature, and salinity in summer, and mixed layer depth and temperature in autumn, with chlorophyll- a and eddy kinetic energy contributing minimally throughout. Results inform fishery-associated habitat identification and habitat-based fisheries management, within a framework linking distribution patterns to Sustainable Development Goals and blue transformation targets.