Forests are prone to direct and indirect effects of climate change. Adaptation strategies have been developed to increase the resistance of forests towards climate change and to reduce the associated risks. However, the direction and degree of climate change remain deeply uncertain. This deep uncertainty is often neglected in forest management. Thus, alternative approaches such as robust decision-making are needed to deal with this deep uncertainty. The aim of this paper is to review current studies on adaptive forest management and improve the understanding of how robust decision-making approaches can help to evaluate and enhance adaptive forest management strategies. An extensive literature review explores the concepts of deep uncertainty and robust decision-making and adapts both to the context of adaptive forest management. We conduct a comprehensive meta-analysis of current studies (42 papers) that provide quantitative outputs for alternative forest management scenarios across various climate scenarios. In addition to the general characteristics of included studies and characterizations of adaptive forest management measures, we focus on the quality and type of stated recommended strategies within studies. We demonstrate the application of two robustness criteria - ‘maximin’ and ‘safety-first’ - to identify robust strategies that, respectively, maximize outcome at the worst case or safeguard a minimum outcome regardless of scenario. Based on this assessment, we compared the overall robustness of proposed adaptive forest management scenarios within studies with the identified robust strategy. We found that the vast majority of studies (40 out of 42) provided no unique recommended strategy for adaptive forest management. 68% of proposed adaptive management scenarios included resistance-type strategies (mostly recommended thinning, prescribed burning, and decreased rotation length), and 28% applied management scenarios with resilience-oriented strategies (mostly recommended species composition changes). We identified robust strategies among recommended adaptation scenarios made in the literature and regarding multiple forest goods and services including timber production, biodiversity, net present value (NPV) and carbon values. None of the recommended scenarios were robust to climate change if more than a single objective were considered. Surprisingly, most of the recommended scenarios were robust enough to guarantee a minimum level of outcome (safety-first) for timber and carbon values. By visually demonstrating the identification process of robust scenarios, we managed to explain the rather abstract concept of robustness. Robust decision-making offers a promising approach to identify robust management strategies that can cope with uncertainties stemming from climate-change-induced deep uncertainty.

中文翻译：

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通过稳健性分析审查适应性森林管理战略的绩效

森林容易受到气候变化的直接和间接影响。已经制定了适应战略以增加森林对气候变化的抵抗力并减少相关风险。然而，气候变化的方向和程度仍然存在很大的不确定性。这种深刻的不确定性在森林管理中经常被忽视。因此，需要诸如稳健决策之类的替代方法来处理这种严重的不确定性。本文的目的是回顾当前关于适应性森林管理的研究，并加深对稳健决策方法如何有助于评估和加强适应性森林管理战略的理解。广泛的文献综述探讨了深度不确定性和稳健决策的概念，并适用于适应性森林管理的背景。我们对当前的研究（42 篇论文）进行了全面的荟萃分析，这些研究为各种气候情景中的替代森林管理情景提供了定量输出。除了纳入研究的一般特征和适应性森林管理措施的特征外，我们还关注研究中陈述的推荐策略的质量和类型。我们展示了两个稳健性标准的应用——“最大化”和“安全第一”——以确定稳健的策略，分别在最坏情况下最大化结果或在任何情况下保护最小结果。基于此评估，我们将研究中提议的适应性森林管理方案的整体稳健性与确定的稳健策略进行了比较。我们发现绝大多数研究（42 项中的 40 项）没有为适应性森林管理提供独特的推荐策略。68% 提出的适应性管理方案包括抗性策略（主要是推荐的间伐、规定的燃烧和减少轮作长度），28% 的应用管理方案具有以弹性为导向的策略（主要是推荐的物种组成变化）。我们在文献中推荐的适应情景中确定了稳健的策略，这些策略涉及多种森林产品和服务，包括木材生产、生物多样性、净现值 (NPV) 和碳值。如果考虑的目标不止一个，那么所有推荐的情景都无法应对气候变化。出奇，大多数推荐的情景都足以保证木材和碳价值的最低水平结果（安全第一）。通过直观地展示稳健场景的识别过程，我们设法解释了相当抽象的稳健性概念。稳健的决策为确定稳健的管理策略提供了一种有前途的方法，这些策略可以应对由气候变化引起的深度不确定性引起的不确定性。