Quantifying the risk mitigation efficiency of changing silvicultural systems under storm risk throughout history

Abstract

Silvicultural adaptations throughout history resulted in an increasing mitigation efficiency towards storm risk, quantifiable through an increasing conditional value at risk and decreasing average damage loss. Recently recommended silvicultural systems for spruce stands in Central Europe, like the group selection system, showed the highest mitigation efficiency towards storm, compared to past thinning from below or thinning from above systems. Storms may affect forests and their productivity. Silvicultural systems adapted throughout history to maintain economic performance of forests under storm risk. This paper aims to (i) determine the conditional value at risk (CVaR) as the expected value of the lower 5% quantile of the simulated economic performance distribution of different silvicultural systems under storm risk, (ii) demonstrate the effect of historical cost and price changes on their performance, and (iii) assess their performance considering revenues from multiple ecosystem services. We used an individual-tree growth model to simulate three silvicultural systems, namely thinning from below, thinning from above and group selection. An additive land expectation value is introduced to reflect long-term timber and carbon sequestration revenues. The performance of silvicultural systems under storm risk is assessed, using an empirical storm model combined with Monte Carlo simulations. The group selection system showed the highest CVaR and therefore highest mitigation efficiency towards storm risk. Moreover, it showed the least sensitivity towards historical cost and price changes. Inclusion of other ecosystem services (carbon sequestration) showed minor sensitivity to storm risk. Silvicultural adaptations throughout history resulted in increasing mitigation efficiency towards storm risk. Integration of silvicultural adaptation is crucial in the further development of forest management, especially approaching risks from climate change.