Reviewing the performance of adaptive forest management strategies with robustness analysis

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.