Quickest Detection of Ecological Regimes for Natural Resource Management

Neha Deopa, Daniele Rinaldo
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Abstract

We study the stochastic dynamics of natural resources under the threat of ecological regime shifts. We establish a Pareto optimal framework of regime shift detection under uncertainty that minimizes the delay with which economic agents become aware of the shift. We integrate ecosystem surveillance in the formation of optimal resource extraction policies. We fully solve the case of a profit-maximizing monopolist, study its response to regime shift detection and show the generality of our framework by extending our results to other decision makers and functional forms. We apply our framework to the case of the Cantareira water reservoir in São Paulo, Brazil, and study the events that led to its depletion and the consequent water supply crisis.

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为自然资源管理快速检测生态制度
我们研究了在生态位移威胁下自然资源的随机动态变化。我们建立了一个不确定条件下的帕累托最优制度转变检测框架,该框架能最大限度地减少经济行为主体意识到制度转变的延迟时间。我们在制定最优资源开采政策时整合了生态系统监控。我们完全解决了利润最大化垄断者的案例,研究了其对制度变迁检测的反应,并通过将我们的结果扩展到其他决策者和函数形式,展示了我们框架的通用性。我们将框架应用于巴西圣保罗的坎塔雷拉水库,并研究了导致水库枯竭和随之而来的供水危机的事件。
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