An empirical review of ICES reference points. (9th November 2022)

• Record Type: Journal Article
• Authors: Silvar-Viladomiu, Paula; Batts, Luke; Minto, Cóilín; Miller, David; Lordan, Colm
• Editors: Poos, Jan Jaap
• Is Part Of: ICES journal of marine science. Volume 79:Number 10(2022)
• Page Start: 2563
• Page End: 2578
• Publication Date: 2022-11-09
• Subjects: ICES region -- limit and target reference points -- maximum sustainable yield -- precautionary approach -- stock population dynamics -- synthesis; Ocean -- Periodicals; Fisheries -- Periodicals; Fishes -- Periodicals; Marine biology -- Bibliography -- Periodicals; 551.4605
• DOI: 10.1093/icesjms/fsac194
• Languages: English
• ISSNs: 1054-3139

Abstract

Abstract: 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.