Recruitment in age-structured stock assessment models can be forecasted using a variety of algorithms to provide advice on the anticipated consequences of different possible management actions. Selecting one method over another usually involves some subjectivity, yet can be consequential to the provision of advice. Extensive case-specific testing is not always feasible. We evaluated the forecast skill in 3-, 5- and 10-year forecasts of 16 recruitment forecasting methods under various circumstances to provide a broad evaluation and general guidelines on the reliability of forecasts. We used 31 operating models based on existing stock assessment models applied to a diversity of stocks with empirical data, which we show to be generally representative of assessed stocks worldwide. Although no single best-performing method could be identified, we found that time-series methods were most likely to perform poorly. Both forecast skill across all methods and forecast sensitivity to the selected method were linked to the properties of the stock or assessment: age at maturity and recruitment autocorrelation in 3-year forecasts and previous long-term recruitment variability in 10-year forecasts. In some situations, all forecasting methods resulted in systematic over- or underestimation of spawning stock biomass. The simulation approach employed here to assess forecast performance, rooted directly in the predictions of existing stock assessment models, can be a complementary tool to existing simulation approaches which generate alternative sets of population dynamics or observations and we discussed the advantages and limitations.

中文翻译：

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预测年龄结构人口模型中的鱼类补充

可以使用各种算法预测年龄结构股票评估模型中的招募，以提供有关不同可能管理行动的预期后果的建议。选择一种方法而不是另一种方法通常涉及一些主观性，但可能会导致提供建议。广泛的针对特定案例的测试并不总是可行的。我们评估了 16 种招聘预测方法在不同情况下的 3 年、5 年和 10 年预测的预测技巧，为预测的可靠性提供广泛的评估和一般指导。我们使用了 31 个基于现有库存评估模型的操作模型，这些模型应用于具有经验数据的各种股票，我们表明这些模型普遍代表了全球评估的股票。尽管无法确定单一的最佳执行方法，我们发现时间序列方法最有可能表现不佳。所有方法的预测技能和所选方法的预测敏感性都与股票或评估的属性相关：成熟年龄和 3 年预测中的招聘自相关以及 10 年预测中以前的长期招聘可变性。在某些情况下，所有预测方法都会导致对产卵种群生物量的系统性高估或低估。此处用于评估预测性能的模拟方法直接植根于现有种群评估模型的预测，可以作为现有模拟方法的补充工具，可生成替代的种群动态或观察结果集，我们讨论了其优点和局限性。所有方法的预测技能和所选方法的预测敏感性都与股票或评估的属性相关：成熟年龄和 3 年预测中的招聘自相关以及 10 年预测中以前的长期招聘可变性。在某些情况下，所有预测方法都会导致对产卵种群生物量的系统性高估或低估。此处用于评估预测性能的模拟方法直接植根于现有种群评估模型的预测，可以作为现有模拟方法的补充工具，可生成替代的种群动态或观察结果集，我们讨论了其优点和局限性。所有方法的预测技能和所选方法的预测敏感性都与股票或评估的属性相关：成熟年龄和 3 年预测中的招聘自相关以及 10 年预测中以前的长期招聘可变性。在某些情况下，所有预测方法都会导致对产卵种群生物量的系统性高估或低估。此处用于评估预测性能的模拟方法直接植根于现有种群评估模型的预测，可以作为现有模拟方法的补充工具，可生成替代的种群动态或观察结果集，我们讨论了其优点和局限性。