Assessing the Potential of Catch-Only Models to Inform on the State of Global Fisheries and the UN’s SDGs

Catch-only models (COMs) have been the focus of ongoing research into data-poor stock assessment methods. Two most recent that are especially promising (i) CMSY+, latest refined version CMSY has progressed from Catch-MSY, and (ii) SRA+ (Stock Reduction Analysis Plus), one developments in field. Comparing COMs evaluating their relative performance is essential for determining state regional global fisheries may be lacking necessary data would required to run traditional models. In this paper we interrogate how can improved by incorporating additional sources information. We evaluate on a dataset 48 data-rich ICES (International Council Exploration Seas) assessments. As measure performance, consider ability model correctly classify status using FAO’s 3-tier classification also used reporting sustainable development goals UN. Both showed notable bias when with inbuilt default heuristics, but as quality prior information increased, rates terminal year substantially. conclude although further COM refinements show some potential, developing biomass or fishing effort priors order able reliably track majority world’s currently