Application of Data-Poor Stock Assessment Methods to Atlantic Sharks

We compared stock status obtained in stock assessments of a suite of Atlantic shark stocks with predictions from a method that calculates biological reference points analytically based on biological data on maturity, fecundity, and natural mortality. In addition to biological information, this method only requires a single index of abundance, but no other fisheries data, making it attractive for application to data-poor fisheries or stocks. Predictions from this method on the overfished status of the stock agreed very well with those from the existing stock assessment models. We also applied three additional data-poor methods: DCAC (Depletion-Corrected Average Catch), AIM (An Index Method), and SEINE (Survival Estimation in Non-Equilibrium Situations) to two shark species with contrasting life histories and compared predictions from these methods with those obtained in the latest stock assessment for these stocks. We discuss the assumptions of the methods used and their sensitivity to inputs as well as their applicability to Atlantic and other shark stocks.