Planning for bark beetle disturbance in production forests: A regional forest optimization case study in Norway

Increasing disturbance pressure from the spruce bark beetle (Ips typographus) challenges the reliability of timber supply in managed boreal forests. This study evaluates alternative optimization approaches for integrating bark beetle damage into regional forest planning in southern Norway. Using a simulation and optimization process, we compare three alternative optimization approaches: (i) deterministic linear programming ignoring disturbance risk, (ii) robust optimization protecting even-flow constraints against income variability, and (iii) stochastic programming using probabilistic disturbance scenarios. Two planning objectives were examined: maximizing the net present value (NPV) alone, and maximizing NPV subject to a minimum periodic timber harvest requirement. When only NPV was maximized, differences among the solutions were minor. The stochastic solution yielded a slightly higher expected NPV (0.1%) through earlier harvesting. Approximately 22% of deterministic scenarios outperformed the stochastic solution, highlighting the limited economic gains when focused on a purely financial objective. When prioritizing a targeted periodic timber supply the deterministic solution resulted in systematic harvest shortfalls under realized disturbances while the robust solution reduced shortfalls by increasing periodic harvests. The stochastic formulation substantially improved supply reliability, reducing expected harvest shortfalls from 1.9% (deterministic) and 1.1% (robust) to nearly 0% for the stochastic solution, albeit with a moderate reduction in the expected NPV. Results demonstrate that the value of incorporating disturbance uncertainty depends on management objectives. While economic efficiency alone provides limited incentive for risk integration, maintaining stable timber supply under increasing disturbance pressure benefits substantially from stochastic planning approaches.