Consistency and robustness testing of candidate reference point systems for North East Atlantic stocks
2022
Winker, Henning | Cardinale, Massimiliano | Mosqueira, I. | Kell, Laurence T. | Konrad, Christoph | Gras, Michael | Sharma, Rishi | Lordan, Colm
Recently, the ICES Workshop on ICES reference points (WKREF1, 2021) 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. The key recommendations of WKREF1were to: i) revise and simplify how Blim is derived, including the possibility to determine Blim as a fraction of B0 based on biological principles and international best practice; ii) FP.05 should be calculated without Btrigger;iii) to use biological proxies for deriving FMSY, and the FMSY proxy must not exceed FP.05 consistent with ICES Precautionary Approach (PA) ; iv) to report a biomass target (Btrg) that corresponds to the FMSY proxy; and v) to set Btrigger as either a fraction of Btrg or multiplier of Blim. In this paper, we conduct a large-scale simulation testing experiment with feedback control for 64 ICES Category 1 stocks, with the aim to evaluate the consistency and robustness of candidate reference point systems. In accordance with the objectives of ICES advice framework, the evaluation criteria for testing consistency are based on the following objects: (1) to not exceed a 5% probability of SSB falling below Blim , (2) to achieve high long-term yields that correspond to at least 95% of the median yield at constant FMSY (MSY), (3) to attain a high probability that SSB is above the FAO threshold of 80% of the Btrg proxy for BMSY. By considering stock-specific productivity and taxonomic grouping, we then put forward the best performing candidate reference point systems for further robustness testing under alternative misspecifications of the stock recruitment relationship . Based on our simulation results, we present straightforward and transparent guidelines for setting optimal reference points depending on the stock’s productivity characteristics. We align this new reference point system with a status classification system that is intended to facilitate clear and unambiguous interpretation of the stock status.
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