Abstract
This study evaluates the stock status of Scomberomorus commerson in the southern Arabian Gulf, particularly in Abu Dhabi waters, using length-based models to address data limitations in fisheries assessments. The findings contribute critical insights into management practices using four length-based models, namely, LBI, LBB, LBSPR, and LIME, to analyze length frequency distributions from commercial catches between 2011 and 2023. The results indicate that the stock is overfished, with low proportions of mature and optimal-sized individuals and an excessive harvest of juveniles, as shown by the model estimates of F/M ratios and SPR values below target levels. From 2011 to 2019, the biomass declined sharply, but signs of recovery were evident by 2023 due to management actions, such as a gillnet ban introduced in 2019. The final-year estimates revealed a B/Bmsy ratio of 1.0 and F/M of 1.2, suggesting ongoing but reduced overfishing pressures. These outcomes underscore the importance of ongoing data-limited assessment methods in monitoring exploited stocks, providing evidence that restrictive measures have positively impacted biomass recovery. The convergence of outputs across methods, such as the indication of overfishing in S. commerson stocks, suggests that implementing multiple models enhances the robustness of management recommendations, including the enforcement of minimum size limits or reductions in fishing efforts or restriction of certain fishing methods. Overall, this study highlights the importance of using multiple models and choosing appropriate priors to improve the quality of stock assessments in data-limited fisheries.
| Original language | English |
|---|---|
| Article number | 1492238 |
| Journal | Frontiers in Marine Science |
| Volume | 11 |
| DOIs | |
| Publication status | Published - 2024 |
Keywords
- data limited
- fisheries management
- reference points
- stock assessment
- sustainability
ASJC Scopus subject areas
- Oceanography
- Global and Planetary Change
- Aquatic Science
- Water Science and Technology
- Environmental Science (miscellaneous)
- Ocean Engineering
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