Modeling the Habitat Distribution of <i>Acanthopagrus schlegelii</i> in the Coastal Waters of the Eastern Taiwan Strait Using MAXENT with Fishery and Remote Sensing Data

Abstract

Black sea bream, Acanthopagrus schlegelii, is among the most commercially valuable species in the coastal fishery industry and marine ecosystems. Catch data comprising capture locations for the gillnet fisheries, remotely sensed environmental data (i.e., sea surface temperature, chlorophyll-a concentration, and current velocity), and topography (bathymetry) from 2015 to 2018 were used to construct a spatial habitat distribution of black sea bream. This species is concentrated in coastal waters (<3 nm) from December to April (spawning season). The maximum entropy (MaxEnt) method and corresponding habitat suitability index among seasons were used to clarify the species’ spatial distribution and identify the seasonal variations in habitat selection. The patterns corresponded closely to the changes in oceanographic conditions, and the species exhibited synchronous trends with the marine environment’s seasonal dynamics. Chlorophyll-a concentration and bathymetry substantially influenced (80.1–92.9%) black sea bream’s habitat selection. By applying the MaxEnt model, the optimal habitats were identified with four variables including depth and satellite-derived temperature, current velocity and chlorophyll-a concentration, which provides a foundation for the scientific assessment and management of black sea bream in coastal waters of the Eastern Taiwan Strait.

Keywords

• habitat selection
• environmental variation
• habitat suitability index
• maximum entropy