Abstract:Bigeye tuna (BET), Thunnus obesus is a large epi- and mesopelagic species distributed in tropical and subtropical waters of the Indian Ocean. Its stock status has been the focus of regional tuna fisheries management organizations. Because of a variety of fishing gear and fishing fleet structures, there have some statistical biases in the historical nominal catches of the Indian Ocean BET. However, the impact of this bias on stock assessment has been neglected in recent years. This paper aimed to assess the impact of observation error and statistical bias of catch on the stock assessment of Indian Ocean BET, using Age-Structured Assessment Program (ASAP) based on fishery-specific catch, catch-at-age, and standardized catch-per-unit-effort data. The results showed that the current stock of BET in the Indian Ocean was not overfished. The results of base model and eight sensitivity analysis models showed that the observation error of catch had influences on the stock status evaluation. When the bias of nominal catch was assumed to be 15% (i.e., the historical catch was underestimated), the assessment result was consistent with the base model (i.e. not overfished). When the bias of nominal catch was assumed to be 20%, the stock might be overfished. Therefore, both the observation error and the statistical bias associated with catch data can have significant impacts on the assessment results, with the latter having a greater effect. This study highlights the importance of considering both the assumption of observation error and statistical bias in catch data in tuna fishery stock assessment, which has been neglected recently.
