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首页> 外文期刊>ICES Journal of Marine Science >Simulation-based management strategy evaluation: ignorance disguised as mathematics?
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Simulation-based management strategy evaluation: ignorance disguised as mathematics?

机译：基于模拟的管理策略评估：无知伪装成数学？

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Simulation-based management strategy evaluations are increasingly developed and used for science advice in support of fisheries management, along with risk evaluation and decision analysis. These methods tackle the problem of uncertainty in fisheries systems and data by modelling uncertainty in two ways. For quantities that are difficult to measure accurately or are inherently variable, variables are replaced by probability distributions, and system dynamics are simulated by Monte Carlo simulations, drawing numbers from these distributions. For processes that are not fully understood, arrays of model formulations that might underlie the observed patterns are developed, each is assumed successively, and the results of the corresponding arrays of model results are then combined. We argue that these approaches have several paradoxical features. Stochastic modelling of uncertainty is paradoxical, because it implies knowing more than deterministic approaches: to know the distribution of a quantity requires more information than only estimating its expected value. To combine the results of Monte Carlo simulations with different model formulations may be paradoxical if outcomes of concern are unlikely under some formulations but very likely under others, whereas the reported uncertainty from combined results may produce a risk level that does not occur under any plausible assumed formulation. Moreover, risk estimates of the probability of undesirable outcomes are often statements about likelihood of events that were seldom observed and lie in the tails of the simulated distributions, where the results of Monte Carlo simulation are the least reliable. These potential paradoxes lead us to suggest that greater attention be given to alternative methods to evaluate risks or management strategies, such as qualitative methods and empirical post hoc analyses.
机译：基于仿真的管理策略评估正在不断发展，并用于科学建议，以支持渔业管理以及风险评估和决策分析。这些方法通过两种方式对不确定性进行建模，从而解决了渔业系统和数据不确定性的问题。对于难以精确测量或固有变量的数量，将变量替换为概率分布，并通过蒙特卡洛模拟对系统动力学进行仿真，并从这些分布中提取数字。对于尚未完全理解的过程，开发了可能是观察到的模式基础的模型公式阵列，每个模型都相继假定，然后合并相应模型结果阵列的结果。我们认为这些方法具有几个矛盾的特征。不确定性的随机建模是自相矛盾的，因为它意味着要了解的不仅仅是确定性的方法：要了解数量的分布，不仅需要估计其预期值，还需要更多的信息。如果某些公式不太可能关注结果，而其他公式很可能将蒙特卡罗模拟的结果与不同的模型公式结合起来，这可能是自相矛盾的，而所报告的合并结果的不确定性可能会产生在任何合理假设下都不会发生的风险水平公式。此外，不良结果概率的风险估计通常是关于很少观察到的事件可能性的陈述，这些事件位于模拟分布的尾部，而蒙特卡洛模拟的结果最不可靠。这些潜在的悖论使我们建议更加重视评估风险或管理策略的替代方法，例如定性方法和事后事后分析。

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