Assessing stock status and abundance trends of King Mackerel (Scomberomorus cavalla) using a maturity-based approach: A comparison across local and regional scales

The king mackerel (Scomberomorus cavalla) is one of the most important fishing resources in Northeast Brazil; however, little is known about the status of its stocks, largely due to a limitation of monitoring data. In this context, simple maturity-based approaches to stock status are useful to provide a general panorama of exploitation in the absence of thorough time series. We evaluated abundance (CPUE) trends and stock-status of king mackerel at regional and local scales: the REVIZEE program (1998–2000), covering almost all of Northeast Brazil, and the REPENSAPESCA project (2019–2021), with landings recorded only in the state of Rio Grande do Norte. Both projects followed handline and gillnet fleets. Abundance trends were analyzed through Generalized Additive Models (GAM). Maturity-based stock status was used to categorize size classes into juveniles, adults below optimal catch length (L_opt), adults at L_opt and mega-spawners. Abundance trends reveal the susceptibility of the species to be caught in conditions representing the outer continental shelf, likely due to an habitat preference, and higher catch in the first semester. Stock indicators show that the most frequent maturity class were adults below L_opt, while the proportion of adults within L_opt varied between 21.5 % and 30.6 %.Although gillnetting accounted for a relatively small portion of the total fishing effort, it presented a significant concern due to the high capture rate of juvenile specimens, as this gear type is known for its low selectivity. Increasing the mesh size could help reduce the capture of undersized individuals of this species. In addition, regulating the seasonal use of gillnets by avoiding periods of recruitment in this area could further minimize juvenile bycatch. Possible mega-spawners were caught within sustainable limits. All results were similar at local and regional scales, revealing the usefulness of limited monitoring and its possible application for management at different scales.