Comparative analysis reveals that hierarchical Bayesian modeling yields higher weight estimates than standard regression in bigeye scad, suggesting potential overestimation in fisheries biomass...
Fisheries management or conservation requires information on length-weight relationship (LWR) for the fishing regulation and biomass estimation. This study aims to assess LWR estimation using two methods, regular and Bayesian hierarchical approached for big-eye Scad (Selar crumenophthalmus). Samples of big eye Scad were collected at several fish landings around Ambon Island from March to August 2020. Length-weight relationship measurement to obtain the parameters of W = a*Lb was tested using generalized linear model and t-test. The parameter b for monthly sampling was not significantly different (F = 0.77, df = 70, P = 0.89) and showed isometric growth b=3 (t = -1.13, df = 4, P = 0.32). Regular measurement resulted parameter log10(a) = -1.99 (±SD = 1.06) dan b = 3.06 (±SD = 0.084). Bayesian method produced parameter log10(a) = -2.07 (±SD = 0.2365) dan parameter b = 3.21 (±SD = 0.1497). Weight measurement from HB approach was significantly higher than the regular method (t = 1.65; df = 405; P <0.0001), and might produce over-estimated of weight from length data. Discrepancy of these methods was overcome by combining all information of LWR to obtain the best estimation on LWR parameters.
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Hutubessy et al. (2021) studied this question.
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