https://jfmr.ub.ac.id/index.php/jfmr/article/view/519
Fathur Rochman, Ririk Kartika Sulistyaningsih, Gussasta Levi Arnenda
Abstract
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Fathur Rochman, Ririk Kartika Sulistyaningsih, Gussasta Levi Arnenda
Abstract
Open-access reader
Albacore ( Thunnus alalunga ) is sub-tropical tuna that live in the high seas of the Pacific, Atlantic and Indian Ocean. The average catches of albacore from 2013-2017 was 36,235 ton per year. The stock status of the Indian Ocean albacore estimated near overfished. The aims of this study is to provide the CPUE standardization of Indonesian tuna longline operated in the Eastern Indian Ocean. This information is important to give the development indication of albacore fisheries in the Indian Ocean. Data were analyzed from onboard observer program during 2006-2018 consist of 2,811 setting. Data then will be analysis using GLM (Generalized Linear Models) include explanatory variables as supporting variables. The result showed that the explanatory variable give a significant contribution to CPUE standardization except the catch season variable This research suggests that the prepared data must include narrower area data (5 x 5 grids of longitude and latitude) and the addition of explanatory variables such as sea surface temperature, sub-surface temperature, dissolved oxygen and abundance of nutrients.
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Albacore ( Thunnus alalunga ) is sub-tropical tuna that live in the high seas of the Pacific, Atlantic and Indian Ocean. The average catches of albacore from 2013-2017 was 36,235 ton per year. The stock status of the Indian Ocean albacore estimated near overfished. The aims of this study is to provide the CPUE standardization of Indonesian tuna longline operated in the Eastern Indian Ocean. This information is important to give the development indication of albacore fisheries in the Indian Ocean. Data were analyzed from onboard observer program during 2006-2018 consist of 2,811 setting. Data then will be analysis using GLM (Generalized Linear Models) include explanatory variables as supporting variables. The result showed that the explanatory variable give a significant contribution to CPUE standardization except the catch season variable This research suggests that the prepared data must include narrower area data (5 x 5 grids of longitude and latitude) and the addition of explanatory variables such as sea surface temperature, sub-surface temperature, dissolved oxygen and abundance of nutrients.
Key concepts: Albacore, Thunnus, Environmental science, Fishery, Stock assessment, Sea surface temperature, Longitude, Oceanography