Adopting robust decision-making to forest management under climate change
Multi-objective robust decision making is a promising decision-making method in forest management under climate change as it adequately considers deep uncertainties and handles the long-term, inflexible, and multi-objective character of decisions. This paper provides guidance for application and recommendation on the design.
Recent studies have promoted the application of robust decision-making approaches to adequately consider deep uncertainties in natural resource management. Yet, applications have until now hardly addressed the forest management context.
This paper seeks to (i) assemble different definitions of uncertainty and draw recommendation to deal with the different levels in decision making, (ii) outline those applications that adequately deal with deep uncertainty, and (iii) systematically review the applications to natural resources management in order to (iv) propose adoption in forest management.
We conducted a systematic literature review of robust decision-making approaches and their applications in natural resource management. Different levels of uncertainty were categorized depending on available knowledge in order to provide recommendations on dealing with deep uncertainty. Robust decision-making approaches and their applications to natural resources management were evaluated based on different analysis steps. A simplified application to a hypothetical tree species selection problem illustrates that distinct robustness formulations may lead to different conclusions. Finally, robust decision-making applications to forest management under climate change uncertainty were evaluated and recommendations drawn.
Deep uncertainty is not adequately considered in the forest management literature. Yet, the comparison of robust decision-making approaches and their applications to natural resource management provide guidance on applying robust decision making in forest management regarding decision contexts, decision variables, robustness metrics, and how uncertainty is depicted.
As forest management is characterized by long decision horizons, inflexible systems, and multiple objectives, and is subject to deeply uncertain climate change, the application of a robust decision-making framework using a global, so-called satisficing robustness metric is recommended. Further recommendations are distinguished depending on the decision context.