Study Of Albacore Tuna (Thunnus alalunga) Abundance Using Regional Ocean Modeling System (ROMS) Data In Indian Ocean

Abstract

First, we analysed alabcore catch data based on time, positions, and layer alabcore caught and ROMS result data monthly climatology data for temperature, salinity. current velocity, and sea surface height for 2005–2008. Then, we analyzed the relationship between catch data and ROMS data by combining the statistical method of regression trogh origin (RTO) and geographic information system (GIS). Three model RTO were generated with the abundance of albacore tuna as a response variable, and temperature, salinity. current velocity, and sea surface height as predictor variables. All of the predictors of temperature, salinity. current velocity, and sea surface height were highly significant (P < 0.001) to the number of albacore tuna. Values of temperature, salinity. current velocity, and sea surface height in albacore tuna preferences ranged from 220 to 230 C, 34.79 to 34.84 Psu, 0.01 to 0.03 m/s and 0.66 to 0.70 m, respectively. Validation of the predicted number ofalbacore tuna with the observed value was significant (P < 0.05, r2 = 0.60). sea surface height was the most important environmental variable to the number of albacore tuna caught, followed by temperature, salinity and current velocity.

Role of Sub Surface Temperature, Salinity and Chlorophyll to Albacore Tuna Abundance in Indian Ocean

“…Different result of previous research shows that most ALB were caught at salinity > 34.6 psu (e.g. Roberts, 1980;Chen et al, 2005;Arrizabalaga et al, 2015;Novianto, 2016). Different results between this study and previous study are allegedly time period to analysis, fisheries data classification method and environmental variables data.…”