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Multi-Objective Sequential Forest Management Under Risk Using a Markov Decision Process-Pareto Frontier Approach
Environmental Modeling & Assessment ( IF 2.7 ) Pub Date : 2020-11-09 , DOI: 10.1007/s10666-020-09736-4
Stéphane Couture , Marie-Josée Cros , Régis Sabbadin

Forests play an important role in many different cycles (carbon sink, biodiversity, timber) and, consequently, in regulating the global climate system. Moreover, forests are the source of a wide range of goods and services to human societies and, as a result, the decisions made by forest owners affect forest ecosystems. Since forests are currently threatened by climate change, there is a need to provide support to forest owners for managing forests under risk, taking conflicting objectives into account. This study focuses on developing an explicit multiple-objective and sequential forest management model under risk. The multi-objective sequential optimization approach used here is based on the concept of Pareto optimality, and the computation of the Pareto frontier (the set of non-dominated solutions), instead of a single solution. We consider a Markov Decision Process (MDP) model to evaluate forest management policies under different criteria, and to generate the Pareto frontier. The framework is applied to the management of a private forest located in southwestern France. We identify optimal forest management practices for each objective separately and trade-off policies considering all objectives jointly. We analyze the forest management policies located on the Pareto frontier, yielding different trade-offs among the conflicting objectives. Our framework makes it possible to envision all possible trade-offs, and to understand how a trade-off policy takes each objective into account. It is hoped that this information will help in analyzing potential policy implications for forest management, taking the provision of multiple forest ecosystem services into consideration.



中文翻译:

马尔可夫决策过程-Pareto前沿方法在风险下的多目标顺序森林管理

森林在许多不同的循环(碳汇,生物多样性,木材)中起着重要作用,因此在调节全球气候系统中也发挥着重要作用。此外,森林是人类社会广泛的商品和服务的来源,因此,森林所有者的决定影响森林生态系统。由于森林目前正受到气候变化的威胁,因此有必要向森林所有者提供支持,以在考虑到相互矛盾的目标的情况下管理处于危险中的森林。这项研究的重点是在风险下建立一个明确的多目标和顺序森林管理模型。此处使用的多目标顺序优化方法基于帕累托最优性的概念以及帕累托前沿(非支配解集)的计算,而不是单个解。我们考虑使用马尔可夫决策过程(MDP)模型来评估不同标准下的森林管理政策,并产生帕累托边界。该框架适用于法国西南部私人森林的管理。我们分别为每个目标确定最佳的森林管理实践,并共同考虑所有目标的权衡政策。我们分析了位于帕累托边界的森林管理政策,在相互矛盾的目标之间产生了不同的权衡。我们的框架可以预见所有可能的权衡,并了解权衡政策如何考虑每个目标。希望这些信息将有助于分析对森林管理的潜在政策影响,同时考虑提供多种森林生态系统服务。

更新日期:2020-11-09
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