Jallow M. S. auteur aut IRD Baldé B. S. auteur aut IRD Sidibeh M. auteur aut IRD Brehmer Patrice auteur aut IRD text journalArticle eng text/pdf born digital access The stock status in many small scale fisheries is often unknown, usually because of limited or absence of data, particularly in the global south. Many data-limited assessments are oriented toward an assessment of fishing pressure. Assessments are often limited by the processes involved in quantifying the uncertainties associated with process and observation errors. Using catch and length data, we evaluated and compared the performance of stock assessment models for Ethmalosa fimbriata in The Gambia. As catch-based models, we used an extension of the Maximum Sustainable Yield "MSY" catch (CMSY++) and a Bayesian length-based model (LBB). Both LBB and CMSY++ models provided good results. Indeed, this case study provides guidelines to consider when using length- and catch-based pseudo-cohort models for data-poor fisheries. Consequently, the indicators estimated for E. fimbriata in The Gambia can be used for sustainable management. Both models showed that the E. fimbriata stock was in a state of recovery with reduced fishing pressure. Reducing fishing efforts could, therefore, help improve stock management. Finally, we advocate further investigation of simple empirical management procedures, irrespective of data limitations, because of their ability to achieve fisheries management objectives when the data context requires such an approach. specialized Small pelagics Small scale fisheries Length-Based Bayesian Data limited fisheries West Africa GAMBIE 040 78 103786 [10 ] 2024 2352-4855 https://www.documentation.ird.fr/hor/fdi:010091325 10.1016/j.rsma.2024.103786 2352-4855 [F B010091325] https://www.documentation.ird.fr/hor/fdi:010091325 https://www.documentation.ird.fr/intranet/publi/2024-10/010091325.pdf Accès réservé (Intranet de l'IRD) IRD - Base Horizon / Pleins textes 2024-10-23 2025-11-06 fdi:010091325 fre