This article presents and discusses research with the aim of developing a stand-level management scheduling model for short-rotation coppice systems that may take into account the risk of wildfire. The use of the coppice regeneration method requires the definition of both the optimal harvest age in each cycle and the optimal number of coppice cycles within a full rotation. The scheduling of other forest operations such as stool thinning and fuel treatments (e.g., shrub removals) must be further addressed. In this article, a stochastic dynamic programming approach is developed to determine the policy (e.g., fuel treatment, stool thinning, coppice cycles, and rotation length) that maximizes expected net revenues. Stochastic dynamic programming stages are defined by the number of harvests, and state variables correspond to the number of years since the stand was planted. Wildfire occurrence and damage probabilities are introduced in the model to analyze the impact of the wildfire risk on the optimal stand management schedule policy. For that purpose, alternative wildfire occurrence and postfire mortality scenarios were considered at each stage. A typical Eucalyptus globulus Labill. stand in Central Portugal was used as a test case. Results suggest that the proposed approach may help integrate wildfire risk in short-rotation coppice systems management scheduling. They confirm that the maximum expected discounted revenue decreases with and is very sensitive to the discount rate and further suggest that the number of cycles within a full rotation is not sensitive to wildfire risk. Nevertheless, the expected rotation length decreases when wildfire risk is considered. FOR. SCI. 58(4):353-365.

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The paper presents and discusses research aiming at the development of a forested landscape management scheduling model that may address the risk of wildfires. A general indicator is built from wildfire occurrence and damage probabilities to assess stand-level resistance to wildfires. This indicator is developed to further address the specificity of each stand configuration (e.g., shape and size) and spatial context (neighboring stands characteristics). The usefulness of the development of such an indicator is tested within a mixed integer programming (MIP) approach to find the location and timing of management options (e.g., fuel treatment, thinning, clearcut) that may maximize the forested landscape expected net revenues. The Leiria National Forest, a Portuguese forest in central Portugal, was used as a case study. Results suggest that the proposed approach may help integrate wildfire risk in forested landscape management planning and assess its impact on the optimal plan. Results further show that prescriptions that include fuel treatments are often chosen over others that do not include them, thus highlighting the importance of wildfire management efforts. Finally, they provide interesting insights about the role of thinnings and fuel treatment in mitigating wildfire risk.

The aim of this paper is to present approaches to optimize stand-level, short-rotation coppice management planning, taking into account uncertainty in stand growth due to climate change. The focus is on addressing growth uncertainty through a range of climate scenarios so that an adaptive capacity may be possible and the vulnerability of the stand to climate change may be reduced. The optimization encompasses finding both the harvest age in each cycle and the number of coppice cycles within a full rotation that maximize net present revenue. The innovation lies in the combination of the process-based model (Glob3PG) with two dynamic programming (DP) approaches. The former is able to project growth of eucalypt stands under climate change scenarios. The innovative approaches are thus influential to define the management policy (e.g., stool thinning, number of coppice cycles, and cycle length) that maximizes net present revenue taking into account uncertainty in forest growth due to climate change. In both approaches, the state of the system is defined by the number of years since plantation, whereas DP stages are defined by the cumulative number of harvests. The first approach proposes the optimal policy under each climate change scenario at each state. The second approach addresses further situations when the climate scenario is unknown at the beginning of the planning horizon. Both help address uncertainty in an adaptive framework, as a set of readily available options is proposed for each scenario. Results of an application to a typical Eucalyptus globulus Labill. stand in central Portugal are discussed.