Age and Growth Estimation of Bigeye Tuna, Thunnus obesus (Lowe, 1839) in the Eastern Indian Ocean Deduced from Otolith Microstructure

Age-based stock assessment of globally important species, like bigeye tuna Thunnus obesus (Lowe, 1839), is urgently required to develop appropriate management plans for fisheries sustainability. This study aimed to estimate age and growth parameters using annual increments count of sectioned-otolit...

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Bibliographic Details
Main Authors: Arief Wujdi, Suciadi Catur Nugroho, Raymon Rahmanov Zedta, Hety Hartaty, Masayu Rahmia Anwar Putri, Fathur Rochman, Prawira Atmaja Rintar Pandapotan Tampubolon, Roy Kurniawan, Yesika Nanda Pramurdya, Bram Setyadji
Format: Article
Language:English
Published: Bogor Agricultural University 2023-04-01
Series:Hayati Journal of Biosciences
Online Access:https://journal.ipb.ac.id/index.php/hayati/article/view/43005
Description
Summary:Age-based stock assessment of globally important species, like bigeye tuna Thunnus obesus (Lowe, 1839), is urgently required to develop appropriate management plans for fisheries sustainability. This study aimed to estimate age and growth parameters using annual increments count of sectioned-otoliths, which effectively employed for age determination of tunas. Samples were collected from Indonesian tuna longline catch landed in the Port of Benoa from March until December 2017. Multi-models were employed to obtain robust growth parameters, and Akaike Information Criterion (AIC) was relied for the best fit model selection among those evaluated. Growth band formation was validated using marginal analysis (MI), indicating that one ring is deposited yearly and slow growth peaked during July (Australian winter). The von Bertalanffy growth model was selected as the best model fitting growth parameters from raw age data, as expressed as Lt = 183.49 (1-e-0.134(t+2.991)). Large variances in growth were detected at the same age, with the oldest age of 15. Over 50% of fish in the Indonesian catch were <5 years old, that may have implications for fisheries sustainability.
ISSN:1978-3019
2086-4094