Evaluating the Accuracy of Data-Poor Stock Assessment Methods in the Southeast United States

Many fish stocks in the Southeast do not have sufficient data to allow for traditional stock assessments. For these ‘data-poor’ stocks it is difficult to determine annual catch limits (ACLs) and other reference points legally required for every fished stock. Data-poor fisheries are prevalent in the Southeast, where 75% of stocks and stock complexes assessed for ACLs have data consisting only of catch history. Alternative data-poor methods to calculate catch limits in such cases exist, but their effectiveness is subject to question. This study compares MSY estimates from SEDAR stock assessments to those of data-poor methods for the same stocks in order to determine the accuracy of the data-poor estimates for fisheries in the Southeast. Three forms each of DCAC and DB-SRA were tested. It was found that DCAC tended to precisely but inaccurately estimate SEDAR MSY estimates, while DB-SRA estimates were accurate but very imprecise. No method stood out for any life history or region. However, when the parameter values recommended by each method’s original literature were used in the models, MSY estimates from DCAC methods tended to accurately estimate the MSY values produced for those same methods when they were informed by parameters taken from the SEDAR assessments.