Stock assessment on fishery-dependent data: Effect of data quality and parametrisation for a red snapper fishery

Data availability, and unreported and unregulated fishing are significant obstacles to evaluating stock status, especially in tropical areas. Limitations in data quantity and quality can lead to model misspecification and erroneous data treatments, potentially causing important changes in model outputs and subsequent management implications. Red snapper Lutjanus purpureus (Poey) in French Guiana provides an example of a stock with a long-time series of fishery-dependent data subject to large uncertainty. A flexible catch-at-age model (Stock Synthesis) was applied to the available data and compared to an historically applied assessment approach. Inter-model variability based on different model specifications and data treatments were compared to identify better the status of the resource. Results showed that a major source of uncertainty in the model was the inclusion of a catch-per-unit-effort abundance index with questionable ability to track abundance. The Stock Synthesis model provided a more flexible and viable method than the virtual population analysis approach. Despite large uncertainty, models depicted a similar trend with a notable stock depletion in the late 1990s but with two distinct biomass trends in more recent years depending on the treatment. To reduce uncertainty and preserve this important economic resource, new data collection programmes and management policies are needed.