Applying length-based assessment methods to fishery resources in the Bay of Biscay and Iberian Coast ecoregion: Stock status and parameter sensitivity

Length-based methods have been widely applied to estimate biological parameters and understand the dynamics of marine resource populations within data-limited stocks. However, date few studies tested sensitivity in length-based examining stocks with different traits fishery contexts. In Bay Biscay Iberian Coast ecoregion, SE Europe (International Council for Exploration Sea - ICES, Divisions 8 9a), many commercial resources are considered data-limited, either little is known about their fisheries stock statuses or gaps remain currently available assessments. Therefore, this study focuses on two most used methods, which ICES considers be appropriate evaluate stocks, namely indicators (LBI) spawning potential ratio (LBSPR). Both assess various relevant species area, such as: small-spotted catshark (Scyliorhinus canicula), European anchovy (Engraulis encrasicolus), blackspot seabream (Pagellus bogaraveo), pouting (Trisopterus luscus), pollack (Pollachius pollachius), Norway lobster (Nephrops norvegicus). For each stock, model results were compared knowledge current status. Furthermore, paper discusses whether unexpected related violations main assumptions (constant total mortality recruitment, logistic selectivity) a lack representativeness length composition. A analysis was conducted important input parameters: L? (von Bertalanffy asymptotic average maximum body size) M/k (ratio natural von growth rate). This concluded that variation/misspecification both (M/k L?) had considerable impact given by effect more significant case parameter, thus highlighting importance its accuracy assessment. indicated that, among LBI LBSPR indicators, least robust indicator Pmega indicator. The remaining method can than when there uncertainty life history L?). Among SPR affected F/M (relative fishing mortality) parameter L?, whereas under variation perform similarly. it consider very rough measures statuses, describe explicitly. Thus, together obtain precision estimating Nevertheless, critical uncertain (e.g., contradict one another, exception Pmega, trustworthy indicators.