Robust management procedures and advice for data limited stocks (RoMA)

Background: The common fisheries policy (CFP) of the EU stipulates that the Maximum Sustainable Yield (MSY) is the best possible objective for fisheries and that scientific advice is the basis for good policy making setting fishing opportunities according to the state and productivity f all managed stocks. Nevertheless, a substantial proportion of EU’s marine living resources are data-limited and still lack a quantitative assessment and, therefore, are not managed appropriately. This increases the risk of overfishing and potentially reduces long-term yield. Therefore, robust quantitative methods need to be developed and harvest control rules need to be implemented and tested that are risk-averse while ensuring high yields and that are applicable for stocks with limited data.

Aims of the project: The project has four main objectives: (i) developing guidelines and advice on good practices for data-limited assessments and, (ii) to further develop assessment methods and provide alternatives to age-based assessments, (iii) to provide new and improve existing quantitative assessments of selected fish stocks of high commercial and ecological importance, and (iv) to disseminate project results to the international scientific and management advisory community.

Results: The RoMA project further developed the surplus production model in continuous time (SPiCT) and facilitated its application for many stocks. Stochastic harvest control rules (HCRs) were introduced to account for uncertainties in maximum sustainable yield (MSY) estimates. These rules, adjusting the Total Allowable Catch (TAC) based on quantified uncertainty, demonstrated robust performance in reducing risk and yield variability across stocks. The approach was implemented in ICES guidelines and applied to multiple stocks. A software tool, SAM2SPICT, was developed that makes a surplus production model assessment for stocks with age-based assessments. This tool provides an alternative assessment for stocks managed with age-based models that can be used as replacement in case of any issues with them. The project also facilitated the assessment and provision of scientific advice for over 20 data limited stocks, contributing to ICES benchmark and assessment working groups. The dissemination of the project was extensive with three scientific publications, presentations at scientific conferences and symposia and involvement in assessment working groups.

Conclusion: The project successfully addressed methodological gaps in stock assessment in the context of data-limited stocks. Most important contributions include, the further development and application of surplus production models, the implementation of stochastic harvest control rules, and the development of the SAM2SPiCT tool. The developments of the RoMA project were adopted in the ICES technical guidelines and were applied in the assessment of various stocks.