Detection potential fishing zones of Longtail tuna (Thunnus tonggol) using fisheries and remotely sensed data in the waters around Madura Island

Abstract

In situ data of Longtail tuna fishing location and satellite-based oceanographic data of chlorophyll-a concentration (chl-a), sea-surface temperature (SST), and salinity were employed to figure out the impacts of oceanographic condition on the pattern of potential fishing zones for Longtail tuna in waters around Madura Island. The relation of those parameters to the dissemination of Longtail tuna was analyzed with a maximum entropy (Maxent). The predictive model performance was estimated using the area under the curve (AUC). The jackknife test was then employed to examine each parameter's model contribution. The results from the Maxent model exhibited a high predictive success of the model with AUC value of 0.932. Maxent prediction showed a high probability occurrence of Longtail tuna occurred in the offshore area of the Java Sea. The results also revealed that the Longtail tuna habitat selection was significantly controlled by the salinity ranges from 32.3-32.5 ppt, SST ranges from 29.5-30.5°C, and chl-a ranges from 0.2-0.4 mg/m3. Besides, among the set of oceanographic variables utilized (SST and chl-a), salinity exhibited the highest value of the jackknife test. Therefore salinity expressed to be the most significant factor in the geographic dissemination of Longtail tuna in the waters Madura Island.