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The International Council for the Exploration of the Sea (ICES) has provided scientific stock advice based on reference points to manage fisheries in the North Atlantic Ocean and adjacent seas for decades. ICES advice integrates the precautionary approach with the objective of achieving maximum sustainable yield. Here, we examine ICES reference point evolution over the last 25 yr and provide a comprehensive empirical review of current ICES reference points for data-rich stocks (Category 1; 79 stocks). The consistency of reference point estimation with the ICES guidelines is evaluated. We demonstrate: (1) how the framework has evolved over time in an intergovernmental setting, (2) that multiple precautionary components and sources of stochasticity are included, (3) that the relationship and historical context of stock size and recruitment are crucial for non-proxy reference points, (4) that reference points are reviewed frequently, taking into account fluctuations and multiple sources of variability, (5) that there are occasional inconsistencies with the guidelines, and (6) that more comprehensive and clearer documentation is needed. Simplifying the stock-recruit typology and developing quantitative criteria would assist with this critically important classification. We recommend a well-documented, transparent, and reproducible framework, and periodic syntheses comparing applications across all stocks.

For many environmental indicators, the sustainable status can change because of changes in either the monitored state or the policy goal. Fisheries provide an intensively monitored setting to investigate the relative impacts of such change. Key fisheries sustainability indicators comprise the ratio between fishing pressure or biomass and their respective reference levels. We developed a retrospective database of population status, reference point changes and reported reasons for changes for all data-rich stocks in the ICES region. We derived methods to distinguish the impacts of either source of change (monitored state or policy goal) on sustainable status. We found that reference points changed frequently (64% of populations had reference point changes) with varying magnitudes. Contrary to expectation, reference point changes were often not compensated by changes in the state thus significantly impacting inferred sustainability status and dependent scientific advice. Across a range of life histories and assessments, changes in reference points dominate retrospective revisions in status over the full time series. Overall, status before and after the change of reference point had no significant directional differences that would suggest reference point change effecting movement towards or away from sustainability. Although multiple factors have contributed to reference point changes, our results show that the reference point definition and the technical basis for estimation were the most important reasons for change. Recognizing that reference points are not constant in time but rather form reference series is paramount to quantifying present and historical sustainability. Properly documenting, justifying and quantifying the impacts of such change is an ongoing challenge.

Target and limit reference points are fundamental management components used to define sustainable harvest strategies. Maximum Sustainable Yield (MSY) and the precautionary principle underpin many reference points. Non-proxy reference points based on MSY in age-based single-species assessments depend on the stock–recruitment (SR) relationship, which can display complex variability. Current reference points ignore persistent dynamic change by assuming that the SR relationship is stationary and with constant recruitment parameters over selected time periods. We highlight Peterman's productivity method (PPM), which is capable of tracking temporal dynamics of recruitment productivity via time-varying SR parameters. We show how temporal variability in SR parameters affects fishing mortality and biomass MSY-based reference points. Implementation of PPM allows for integrated dynamic ecosystem influences in tactical management while avoiding overwrought and sometimes ephemeral mechanistic hypotheses tested on small and variable SR datasets. While some of these arguments have been made in individual papers, in our opinion the method has not yet garnered the attention that is due to it.