Predictive Modeling of Eastern Little Tuna (<i>Euthynnus affinis</i>) Catches in the Makassar Strait Using the Generalized Additive Model

Abstract

The Makassar Strait (MS) is characterized by water mass from the Pacific Ocean and is one of the ITF (Indonesia Throughflow) branches. It carries warm water masses from the Pacific Ocean to the Indian Ocean. This research aims to analyze the relationship between CPUE of Eastern Little Tuna (Euthynnus affinis) and oceanographic variables, likewise predict the fishing area using the Generalized Additive Model (GAM). The research method used is spatial and temporal analysis. The data was used from 2015 to 2020. The data processed were sea surface temperature, chlorophyll-a, salinity, currents, sea level as predictor variables, and Eastern Little Tuna production as a response. Eastern Little Tuna catch data were normalized into Catch per Unit Effort, while the oceanographic data were extracted using ArcGIS. Based on the results of the GAM model, it was found that the model with five variables is the most suitable predictive model, with 16.4% CDE. Salinity is the most influential parameter on the catch of Eastern Little Tuna with a significance value of −16 ***. The optimum value for SST is 30–31 °C, chlorophyll-a is 1–2 mg/m3, salinity is 29–30 ppt, current velocity is 0.3–0.5 m/s and sea level is between 0.6–0.7 m. Based on the GAM prediction results, a high CPUE value will be obtained in the southwest monsoon (March to May). Fishing activity carried out in the best season will implement the adoption of harvest control measures.

Keywords

• catch per unit effort
• optimum value
• predictors
• response
• significance value