Substituting model based indicators in Harvest Control Rules by observations using fuzzy logic methodology

• Published in: ICES Journal of Marine Science
• Main Author: Eide, Arne
• Format: Article in Journal/Newspaper
• Language: English
• Published: Oxford University Press 2017
• Subjects: VDP::Agriculture and fishery disciplines: 900::Fisheries science: 920::Catch: 925; VDP::Landbruks- og Fiskerifag: 900::Fiskerifag: 920::Fangst: 925; VDP::Agriculture and fishery disciplines: 900::Fisheries science: 920; VDP::Landbruks- og Fiskerifag: 900::Fiskerifag: 920; Arctic; Arctic cod; Northeast Arctic cod
• Online Access: https://hdl.handle.net/10037/14265; https://doi.org/10.1093/icesjms/fsx227

The accepted manuscript (AM) is the final draft author manuscript, as accepted for publication by a journal, including modifications based on referees’ suggestions, before it has undergone copyediting, typesetting and proof correction. This is sometimes referred to as the post-print version. Source at: http://doi.org/10.1093/icesjms/fsx227 Harvest Control Rules are predefined heuristic decision rules to provide quota advices for managed fisheries. Frequently statistical methods and biological assumptions expressed in mathematical models, are used to provide the Harvest Control Rules with initial information (indicators values). The aim of this article is to investigate a possible way forward of replacing these inputs by quantities of measurable observations, e.g. catch-at-age statistics. The article presents a method by which recruitment indexes and stock biomass indicators are obtained by non-parametric use of annual catch-at-age records, without filtering the raw data (observations) through mathematical models. Two related methods, applied on three empirical cases, are provided: First, showing that recruitment strengths of the Northeast Arctic cod, haddock, and saithe stocks, obtained by fuzzy logic methodology, are satisfactory captures by the use of catch-at-age data. Second, stock size indicators are estimated for the three species by the same catch-at-age data. The second task turns out to be more challenging than the first, but also in the case of stock size evaluation, the suggested procedure provides reasonable results when compared to standard stock assessment methods