Identification of Commercial Tuna Hotspot in the Southern Waters of Java-Bali Through Satellite Remote Sensing Data

Tuna are mesopredators in oceanic food webs which play an essential role in pelagic communities and high sea ecosystems service. Hence, understanding the environmental preference of commercial tuna species is necessary to project the hot spot and to characterize its habitat. This study used generalized additive models (GAMs) to determine the relationship between the environmental variables derived from satellite data and the abundance of commercial tuna species. We used three environmental data as predictor variables and built seven GAMs models for each tuna species. The result stated that all environmental variables, namely sea surface temperature(SST), sea surface chlorophyll (SSC), and sea surface height (SSH) gave a significant influence on the existence of commercial tuna (
$\mathrm{P} < 0.01$
) in the study area. Also, we found different spatial patterns among three types of commercial tuna. Bigeye tuna prefers to stay in lower SST, while yellowfin tuna and albacore tuna prefer to stay in a certain SST range. Furthermore, they also have a different pattern of SSH where albacore and bigeye tuna prefer to stay in the higher SSH while yellowfin tuna prefers to stay between 0.49-0.65 m. However, three species have a similar range of SSC.