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

机译:使用模糊逻辑方法通过观察将基于模型的指标替换为“收获控制规则”

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摘要

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 nonparametric 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.
机译:收获控制规则是预定义的启发式决策规则,可为托管渔业提供配额建议。经常使用数学模型中表示的统计方法和生物学假设为“收获控制规则”提供初始信息(指标值)。本文的目的是研究用大量可测量的观测值代替这些输入的可行方法。 G。捕捞年龄统计。本文提出了一种方法,通过该方法可以通过非参数使用年度捕捞量记录来获取招聘指标和种群生物量指标,而无需通过数学模型过滤原始数据(观测值)。提供了在三个经验案例中应用的两种相关方法:首先,表明通过模糊逻辑方法获得的东北北极鳕鱼,黑线鳕和赛斯羚羊的募集强度通过使用捕捞年龄数据可以令人满意地捕获。 。其次,根据相同的捕捞年龄数据估算这三个物种的种群规模指标。事实证明,第二项任务比第一项更具挑战性,但在库存量评估的情况下,与标准库存评估方法相比,建议的程序可提供合理的结果。

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