人类判断与生态资源管理的理论模型
Human judgment vs. theoretical models for the management of ecological resources
摘要：
尽管在自然资源管理的量化方法方面取得了重大进展，但在管理生态种群的实际实践中使用这些工具一直存在阻力。给定一个管理系统和一组假设，转化为一个模型，优化方法可以用来解决最具成本效益的管理措施。然而，当基本假设不满足时，这种方法可能会导致糟糕的决策。管理者根据过去的经验和判断制定决策，而不需要数学模型的帮助，可以潜在地了解系统并制定灵活的管理策略。然而，这些战略往往是基于主观标准和同样无效的，往往是未说明的假设。鉴于这两种方法的缺点，目前还不清楚是否简单的定量模型改善环境决策专家的意见。在本文中，我们探讨如何以及学生，利用他们的经验和判断，管理模拟渔业种群在网上电脑游戏，并比较他们的管理成果的性能模型为基础的决策。我们认为收获决策产生四种不同的定量模型：1。用于产生游戏中观察到的模拟种群动力学的模型，所有基本参数值已知[对照]，2.相同的模型，但参数值未知，必须在游戏期间根据观察到的数据进行估计，3.结构上不同于用于模拟种群动力学的模型; 4.一个忽略年龄结构的模型在案例1 - 3中，人类的平均表现比模型差得多。当模型忽略年龄结构时，他们产生了表现不佳的管理决策，但在66%的时间里，他们仍然优于使用经验和判断的学生。
英文摘要：
Despite major advances in quantitative approaches to natural resource management, there has been resistance to using these tools in the actual practice of managing ecological populations. Given a managed system and a set of assumptions, translated into a model, optimization methods can be used to solve for the most cost effective management actions. However, when the underlying assumptions are not met, such methods can potentially lead to poor decisions. Managers who develop decisions based on past experience and judgment, without the aid of mathematical models, can potentially learn about the system and develop flexible management strategies. However, these strategies are often based on subjective criteria and equally invalid and often unstated assumptions. Given the drawbacks of both methods, it is unclear whether simple quantitative models improve environmental decision making over expert opinion. In this paper, we explore how well students, using their experience and judgment, manage simulated fishery populations in an online computer game and compare their management outcomes to the performance of model-based decisions. We consider harvest decisions generated using four different quantitative models: 1. the model used to produce the simulated population dynamics observed in the game, with all underlying parameter values known [a control], 2. the same model, but with unknown parameter values that must be estimated during the game from observed data, 3. models that are structurally different from those used to simulate the population dynamics and 4. a model that ignores age structure. Humans on average performed much worse than the models in cases 1 - 3. When the models ignored age structure, they generated poorly performing management decisions, but still outperformed students using experience and judgment 66 percent of the time.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
