A Bayesian hierarchical DeLury model for stock assessment of the west winter-spring cohort of neon flying squid (Ommastrephes bartramii) in the northwest Pacific Ocean

DeLury depletion models are commonly used in the stock assessment of short-lived species, such as squid of the family Ommastrephidae. However, this type of model may be misleading if its input data are not informative. Here, we applied and compared both Bayesian hierarchical and non-hierarchical DeLury depletion models to conduct stock assessment of the west winter-spring cohort of neon flying squid, Ommastrephes bartramii (LeSueur, 1821), in the North Pacific Ocean. Fishery data from the Chinese squid jigging fleets from 1996 to 2004 were examined. The Bayesian hierarchical model yielded reasonable estimates, but the Bayesian non-hierarchical model did not successfully estimate the initial abundance for certain years. This suggests that the Bayesian hierarchical DeLury depletion model can produce more reliable estimates than a similar non-hierarchical model, especially because it uses the data more efficiently by combining all sets of time-series data hierarchically in the same model.