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The ICES Workshop on ICES reference points (WKREF1) was tasked to provide a thorough review of the ICES reference points system as a basis to re-evaluate the process for estimating, updating and communicating reference points in the context of the ICES advice. As part of the preparation leading to WKREF1 a large database of the most recent assessment outputs for 78 Category 1 stocks were collated in the form `FLStock` objects, which formed the basis for several components of the presented analyses.The first part of the meeting involved a detailed overview of the history and basis of the ICES references points system, which was aligned with the results of an empirical review of the procedures and choices made to derive ICES reference points for category 1 stocks. The ICES procedures were then contrasted with those used in the USA, Canada, New Zealand and across tuna Regional Fishery Management Organizations. A limitation in terms of transparency of the ICES procedures is a lack of complete documentation of the settings used for deriving reference points using, e.g., the EQSIM software. In comparison to other international standards, the main differences identified include the absence of a target biomass reference point and inconsistent estimates of the limit biomass reference point Blim, which is estimated to be below 10% of the unfished biomass (B0) for a high proportion of analysed stocks (around 50%). In addition, an important difference is that direct estimates of FMSY are used in ICES (which can be unreliable), whereas elsewhere FMSY is often replaced by more conservative biological proxies, such as Fspr% and FB%.The second part focused on the robustness evaluation of the current ICES reference point system. Work presented included examples that demonstrate differences in reference point estimates between standard ICES procedures (EQSIM) and full Management Strategy Evaluation (MSE) simulations, and a study that highlighted the considerable uncertainty in estimating Blim, with guidance on how to quantify uncertainty depending on length and contrast in the time-series. A large simulation experiment was conducted by applying a short-cut MSE approach to 68 Category 1 stocks, which revealed that the ICES MSY advice rule is the least robust of all tested generic approaches if assumptions about the typically highly uncertain stock recruitment relationship are violated. This led to poor performance of the ICES MSY advice rule associated with the lowest long-term yields, highest risks to fall below limit reference points and lowest probabilities of attaining biomass levels at MSY. Contributing factors to the poor performance were combinations of comparably high FMSY estimates and low Blim (trigger (lim > 10% B0), performance improved notably. Results from a backtest using hindcasting with forecasts of 1-5 years reinforced the need to re-estimate reference points regularly at benchmark assessments, and that short-term forecasts should not exceed a three-year time span to account for time-varying biological traits. Finally, presented work highlighted the advantages (in terms of high consistency and accuracy) of estimating the stock-recruitment relationship or reference points internally in the assessment model, which was illustrated for Stock Synthesis and SAM, and supported by a comprehensive simulation study.The key recommendations of WKREF1 were to: i) revise and simplify how Blim is derived. An absolute Blim should only be specified empirically in cases where there is sufficient contrast in the stock-recruit data to estimate a well-defined break-point. Alternatively, it is suggested that Blim should be determined as a plausible ratio of B0 based on biological principles and the life history of the stock (e.g. 10-25% B0 depending on the stocks characteristic; Section 7). ; ii) FP.05 should be calculated without Btrigger; iii) to use biological proxies (Fbrp) for deriving FMSY, and the resultant FMSY proxy must not exceed FP.05; iv) to report biomass target (Btrg) that corresponds to the FMSY proxy; and v) to set Btrigger as either a fraction of Btrg or multiplier of Blim. Specifications of setting reference points (e.g. Fbrp) or Btrigger should be informed through further simulation testing to be presented at WKREF2.

The ICES Workshop on ICES reference points (WKREF2) was tasked review the WKREF1 report and based on the outcome develop updated guidelines for the ICES reference points system and recommendations for ACOM consideration. The WKREF1 report has suggested 5 key recom- mendations to simplify and harmonise the ICES reference points framework representing a ma- jor change to the current guidelines. At WKREF2, we detailed discussions and four key concerns were raised about the proposed approach. The first related to the simplification of rules to define Blim. Around two thirds of category 1 stocks would end up as WKREF1 “Blim Type 2” where Blim would be set as a fraction of B0. The Allee effect or “depensation” maybe more important than previously thought and should be furthered explored for ICES stocks since it has important consequences for Blim. A number of challenges and issues around defining Blim using the current guidelines were documented. Some suggestions on improvement criteria were discussed including using classifiers to define spas- modic stocks and using change point algorithms to address non-stationary productivity regimes. However, further work is need to make these approaches operational and there was no consen- sus that the WKREF1 Blim types should replace the current guidelines. WKREF1 recommended that the FMSY proxy should be based on a biological proxies and should be less than the deterministic FMSY. It was pointed out that the stochastic FMSY estimated in EqSim for example, is lower than the deterministic FMSY and that the current guidelines ensure that the FMSY should not pose a more than 5% risk to Blim. A large amount of work described in WD 1 was carried out to develop an MSE framework to consistency and robustness test a candidate refer- ence point system for North East Atlantic stocks. However, WKREF2 recommended that further work needs to be carried out to condition and test the simulation framework before the conclu- sions could be adopted by ICES and incorporated into the guidelines. A number of considerations for defining MSY related reference points were discussed including using model validation and prediction skill to ensure that ICES provide robust and credible ad- vice. There is evidence that density dependence (DD) is important in the majority of ICES stocks (68% in recruitment and 54% in growth). The correct prediction of the shape and strength of density-dependence in productivity is key to predicting future stock development and providing the best possible long-term fisheries management advice. A suggested approach to use surplus production models (SPMs) to account for DD in FMSY was suggested and discussed but there was no consensus on whether that approach was appropriate. There was consensus that the FECO approach as a means of adapting target fishing mortality to medium-term changes in productiv- ity should be included in the guidelines subject to a benchmark and ACOM approval. While WKREF1 and 2 focused mainly on Category 1 stocks ToR c) called for a “simplified and harmonised set of guidelines for estimating MSY and precautionary reference points applicable in the advice framework across various ICES stock categories.” Ideally the ICES assessment cat- egories should provide equivalent risk across all stocks. This issue was discussed but no recom- mendations emerged. There was no consensus a revised reference point framework was proposed at WKREF2. How- ever, it was agreed that it should be presented here for further discussion at ACOM and other fora. The key feature of the suggested approach is that the stock status evaluation is treated in- dependent of the Advice Rule (AR). The main feature of the system is that the biomass trigger is not linked to a stock status evaluation, it is linked to the expected biomass when fishing at the target fishing mortality, in contrast to the current ICES approach. It also entailed that FMSY would also become an upper limit of fishing mortality and that the advised fishing mortality would be set at or lower than that level. WKREF2 did not discuss what to do in situations where SSB< Blim or alternative forms of HCR for the advice rule. Building community understanding and con- sensus around simplified and harmonised guidelines has yet to be achieved. A further workshop WKREF3 will be required to achieve that aim. The report includes 6 recommendations for ACOM consideration. ICES The main objective of the workshop was to review the recommendations of WKREF1 and con- sider how these might feed into a new reference points framework and guidelines for ICES. There were a number of presentations on the wider issues of best practice for reference points, the Allee effect, density dependence and the WKIRISH approach. The starting point was to try and develop a set of simplified and harmonised guidelines based on the WKREF1 report rather than evolving the current guidelines to include the WKREF1 conclusions. A key aspect of the meeting was to allow for discussions in order to build a shared understanding of the strengths and weakness of the current framework and of the new framework emerging from WKREF1. Published Non Refereed

The ICES Workshop on ICES reference points (WKREF2) was tasked review the WKREF1 report and based on the outcome develop updated guidelines for the ICES reference points system and recommendations for ACOM consideration. The WKREF1 report has suggested 5 key recommendations to simplify and harmonise the ICES reference points framework representing a major change to the current guidelines. At WKREF2, we detailed discussions and four key concerns were raised about the proposed approach. The first related to the simplification of rules to define Blim. Around two thirds of category 1 stocks would end up as WKREF1 “Blim Type 2” where Blim would be set as a fraction of B0. The Allee effect or “depensation” maybe more important than previously thought and should be furthered explored for ICES stocks since it has important consequences for Blim. A number of challenges and issues around defining Blim using the current guidelines were documented. Some suggestions on improvement criteria were discussed including using classifiers to define spasmodic stocks and using change point algorithms to address non-stationary productivity regimes. However, further work is need to make these approaches operational and there was no consensus that the WKREF1 Blim types should replace the current guidelines. WKREF1 recommended that the FMSY proxy should be based on a biological proxies and should be less than the deterministic FMSY. It was pointed out that the stochastic FMSY estimated in EqSim for example, is lower than the deterministic FMSY and that the current guidelines ensure that the FMSY should not pose a more than 5% risk to Blim. A large amount of work described in WD 1 was carried out to develop an MSE framework to consistency and robustness test a candidate reference point system for North East Atlantic stocks. However, WKREF2 recommended that further work needs to be carried out to condition and test the simulation framework before the conclusions could be adopted by ICES and incorporated into the guidelines. A number of considerations for defining MSY related reference points were discussed including using model validation and prediction skill to ensure that ICES provide robust and credible advice. There is evidence that density dependence (DD) is important in the majority of ICES stocks (68% in recruitment and 54% in growth). The correct prediction of the shape and strength of density-dependence in productivity is key to predicting future stock development and providing the best possible long-term fisheries management advice. A suggested approach to use surplus production models (SPMs) to account for DD in FMSY was suggested and discussed but there was no consensus on whether that approach was appropriate. There was consensus that the FECO approach as a means of adapting target fishing mortality to medium-term changes in productivity should be included in the guidelines subject to a benchmark and ACOM approval. While WKREF1 and 2 focused mainly on Category 1 stocks ToR c) called for a “simplified and harmonised set of guidelines for estimating MSY and precautionary reference points applicable in the advice framework across various ICES stock categories.” Ideally the ICES assessment categories should provide equivalent risk across all stocks. This issue was discussed but no recommendations emerged. There was no consensus a revised reference point framework was proposed at WKREF2. However, it was agreed that it should be presented here for further discussion at ACOM and other fora. The key feature of the suggested approach is that the stock status evaluation is treated independent of the Advice Rule (AR). The main feature of the system is that the biomass trigger is not linked to a stock status evaluation, it is linked to the expected biomass when fishing at the target fishing mortality, in contrast to the current ICES approach. It also entailed that FMSY would also become an upper limit of fishing mortality and that the advised fishing mortality would be set at or lower than that level. WKREF2 did not discuss what to do in situations where SSB< Blim or alternative forms of HCR for the advice rule. Building community understanding and consensus around simplified and harmonised guidelines has yet to be achieved. A further workshop WKREF3 will be required to achieve that aim. The report includes 6 recommendations for ACOM consideration. nonPeerReviewed

The Workshop on the Review and Future of State Space Stock Assessment Models in ICES focused on future directions of state-space assessment models for ICES stocks (WKRFSAM), utilising recent advances in fisheries modelling research to help define best practises. State-space models consist of a process model for unobserved quantities (e.g. true stock abundances) and an observation model for observed quantities (e.g. catches or survey data). Standard statistical asassessment models do not include stochastic population processes. Prediction is a natural part of the state-space model formulation which is a more practical advantage of the approach for stock assessment.Lognormal observation error models for survey indices can be parameterized such that the mean or median is proportional to the true stock abundance, but this makes little difference on assessment results. Empirical results for 14 stocks indicated that this is also the case for catch observation models. There is no practical difference whether the mean or median of fishing mortality rates (F’s) are constant for the data period, but there are important differences if F is projected into the future.Including random deviations in the natural mortality rate (M) leads to convergence issues for some stocks, and similar assessment results for other stocks, but this depends on the details of how this is implemented. Including time- and age-varying M increases model flexibility and potential confounding of F, M, and stock size index catchability, Q. When model parameters are confounded then we can anticipate less robustness. Including external variances and correlations that are reliably estimated will be more relevant and useful in situations where these differ substantially over time, such as when a survey in some year has a large set, or poor coverage, etc.Two general criteria to select between alternative models are Goodness-of-it and Out-of-sample prediction. Minimizing out-of-sample prediction error (e.g. Akaike Information Criterion, AIC) is increasingly seen as a better approach for model selection.The main tool for model validation are residuals. However, for state-space models, Pearson are not independent because of the dependence structure of the unobserved states. One-observationahead and one-step-ahead residuals are preferred. These can be formulated to be independent and Gaussian distributed.Key research recommendations involve when and how M can be estimated, how to include information about the precision of model inputs, and improved usage of diagnostics and model selection criteria.

We use a novel proxy (growth rates of long-lived deep water fish, orange roughy) to reconstruct inferred water temperatures of intermediate water masses in both Northern and Southern Hemispheres since the mid-1800s. The data are consistent with instrumental records showing long-term warming in the Northern Hemisphere but also indicate decadal variability of intermediate depth temperatures that is coherent across the two hemispheres. This variability correlates with the dominant subpolar annular mode in each hemisphere and implies a bihemispheric oceanic response to external forcing that influences the properties of intermediate depth water masses. Key Points Growth rates of deep-sea fish proxy intermediate depth water temperature Long-term warming in North Atlantic but variable temperatures in South Pacific Parallel variability implies hemispheres respond simultaneously to forcing