Stock assessment using Bayesian state-space surplus production models: the case of bonga shad, Ethmalosa fimbriata (Bowdich, 1825), in the Eastern Central Atlantic Ocean

Abstract

Abstract Ethmalosa fimbriata is a crucial fish classified as either fully exploited or overfished, requiring closer monitoring. The Committee for Eastern Central Atlantic Fisheries (CECAF) manages shared stocks in the Eastern Central Atlantic Ocean (ECAO). CECAF’s reported CPUE (1995–2017) and archived regional catch data (1970–2021) in the FAO Fishstatj database were used in this study. The objectives were to evaluate the northern E. fimbriata stock south of ECAO and conduct convergence diagnostics of input data using Bayesian state-space surplus production models (SPMs). The applied SPMs CMSY++ (catch-only), AMSY (CPUE-only), BSM, and JABBA (comparing Schaefer, Fox, and Pella-Tomlison functions). The results may help dispel uncertainty about its state in the region. All models produced robust diagnostic results and a reasonable fit to the data, with significant improvement in posterior perceptions from prior knowledge at very low variance ratios (PPVR < 0.3). The Schaefer model in JABBA showed a better prediction effect on the data (RMSE = 16.9%, DIC = -382.7) than the Fox (RMSE = 17%, DIC = -382.4) and Pella-Tomlinson (RMSE = 17%, DIC = -382) models. All the SPMs suggested that the current fishing mortality rate of the assessed stock has either reached or exceeded the FMSY and that the biomass level has either fallen below or approached the BMSY. The Schaefer model in JABBA predicted a catch limit of 100,000 tons, effective in 2024. By implication, the assessed stock may be unsustainable, requiring catch limits. The Schaefer model proved most effective for evaluating the study species.