The impact of extreme disturbance events on the economic attractiveness of stand types: A Monte Carlo simulation-based study

Climate change and the increasing frequency of extreme disturbance events pose major challenges for sustainable forest management. Quantifying the economic impacts of such events is essential for developing adaptive strategies. We present a comparative stand-level assessment framework that evaluates land expectation value (LEV) and conditional value at risk (CVaR, the average of the worst 5% of LEV outcomes) by explicitly integrating rare disturbance events into forest economic simulations. Probabilities for extreme disturbances were estimated using Taylor's law, which links the mean and variance of disturbance rates, and were combined with Monte Carlo simulations for four major Central European tree species and a mixed stand under different climate scenarios. Our analysis distinguishes between background mortality (hazards predicted by established statistical survival models) and extreme disturbances (low-probability, high-impact events), providing a comprehensive economic assessment. Results show that including extreme disturbances substantially reduces LEV and worsens CVaR, with large variation across stand types. Norway spruce is most affected, with additional LEV losses above €3000 ha−1 and CVaR declines up to €7000 ha−1. Douglas fir maintains high mean returns but faces considerable downside risk (CVaR declines up to €3600 ha−1). Silver fir and mixed stand experience moderate impacts, while European beech performs worst, with consistently low or negative returns. By integrating disturbance probabilities into forest economics, this study quantifies both expected and worst-case outcomes. The findings suggest that while Douglas fir remains profitable on average, silver fir and mixed stand tend to provide a more balanced performance under future disturbance regimes, although broader conclusions require landscape-level analysis.