Abstract:The big-eye tuna (Thunnus obesus) is the most commercially important tuna species in eastern Pacific Ocean. The fishery of this species has been managed by Inter-American Tropical Tuna Commission (IATTC). IATTC evaluates the stock of big-eye tuna annually using Stock Synthesis 3 (SS3). SS3 is one of the most commonly used models that assess age-structured fishery stock based on biological parameters and fishery data such as the annual catch, the age-composition, the length composition of catch and abundance indices. A recent assessment of the big-eye tuna stock in eastern Pacific Ocean indicated a small recovery of the spawning stock biomass (SSB) and the fishing mortality (F) with respect to biological reference points (BRPs). The integrated model effectively combines multiple data with various sources into single analysis, and propagates the uncertainties associated with model parameters and structures into model outputs such as the biomass time series and BRP. However, it is time-consuming to use full SS3 model to analyze the big-eye tuna stock as it has as many as 23 fisheries. Therefore, model simplification has become necessary to improve the analysis efficiency. In this study, we tried to simplify the SS3 modeling process by using 2 fisheries (purse seine and longline fisheries) instead of 23. Representative abundance index and size composition from the purse seine fisheries and longline fisheries of the full model were used in the simplified one. The outputs of the simplified model were compared to that of the full model to evaluate the performance of the former. The results showed that the simplified model effectively captured the historical trends of stock time series (e.g., recruitments, SSB and F) and estimated FMSY with little interference from the steepness and natural mortality parameters. The reduced interference from steepness allowed the simplified model to correctly analyze the stock status based on the Kobe plot. However, the simplified model increased errors in the estimation of other BRPs. This study implied that selecting BRPs and defining stock status of big-eye tuna could affect the evaluation of the performance of the simplified model. Further studies are needed to achieve a balance between high performance and reduced complexity of the model.
