DoctorateOpen Access

Bayesian estimation of growth parameters in fisheries sciences

2016
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Advisor: Yrd. Doç. Dr. Makbule Baylan

Abstract (EN)

This study examines the Bayesian estimation of fish growth parameters. For this purpose, the species Mullus barbatus barbatus (L., 1758), Saurida lessepsianus (Russel, Golani, & Tikochinski, 2015) and Upeneus pori (Ben-Tuvia & Golani, 1989) were collected from the Iskenderun Bay and the von Bertalanffy growth parameters were estimated using the Bayesian method. The estimates were also compared with classical methods. It was determined that for all three species, the Bayesian approach is a more advantageous estimation method for growth parameters both with regards to correlation between parameters and due to offering a more realistic parameter estimation biologically. Especially considering the L_∞ and t_0 estimations, with classic methods, L_∞ was estimated either too high or too low compared to the observed highest value. With the Bayesian method, this estimate was higher than the largest size observed, but more realistic. Similarly the t_0 value, which signifies the time the fish spends in the egg, has to be as close to zero as possible, but with the classic approach, it was noted that this value was estimated as very different from zero. However with the Bayesian method, this parameter was estimated to be very close to zero for all three species. The most important way of making biologically relevant estimations is to use the most appropriate statistical estimation method. This study establishes that the Bayesian method is appropriate and effective for the estimation of the growth parameters of fish.

Author

Sedat Gündoğdu

How to Cite

Sedat Gündoğdu (Doctorate thesis). Bayesian estimation of growth parameters in fisheries sciences, 2016, Çukurova University.

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