Fishing for more data: Exploratory stock assessment of the data-limited brown crab (Cancer pagurus) stock in Norway
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Formal stock assessment is a key step in managing fisheries sustainably and preventing overexploitation (Hilborn, 2011). However, the majority of the world’s exploited stocks are considered data-limited and lack formal stock assessments (Ovando et al., 2021). Several attempts to find simple, low-cost, and generic solutions for the assessment of data-limited stocks have been made, still, individual adjustments are required to provide useful information for management purposes (Dowling et al., 2019). To date, there has not been any systematic quantification of stock size of brown crab (Cancer pagurus) in Norway. The present study has therefore evaluated the applicability of data on brown crab in Norway in describing the stock development qualitatively or quantitatively, providing the potential basis for a formal assessment. Data from the reference fishery (Woll et al. 2006), landings data and fisheries-independent data were standardized using statistical models to derive indices that provide indicators of stock development. The indices also serve as inputs for stock assessment models. The available data were applied to stock assessment designed for data-limited stocks and their applicability was evaluated. The following methods were tested: (i) length -based indicators, (ii) length-based spawning potential ratio (LBSPR), and (iii) Surplus production in continuous time (SPiCT). Few major spatial differences among the trends in length structures or abundance were found. Overall, the available data and the tested methods indicate stable trends, suggesting that the brown crab fishery has been sustainable. Vestlandet emerges as an exception with indications of overfishing, as the assessment unit does not meet the length- specific targets and the relative abundance has been abruptly declining since 2015. Despite relatively long time series, the applicability of the data in LBSPR and SPiCT is strictly limited. This highlights that data-limited methods have specific data demands, both quantitatively and qualitatively, that can make them unsuitable for specific cases, such as non-conventional shellfish fisheries. Furthermore, each method comes with specific assumptions that need to be fulfilled and often require sufficient contrast in time series, constraining their utility for stocks with stable trends. This underlines the challenges with the application of generic stock assessment methods, and a need for easily adjustable methods for shellfish and particularly decapods.