How considering multiple criteria, uncertainty scenarios and biological interactions may influence the optimal silvicultural strategy for a mixed forest

Assessing pre-defined strategies remains the status quo for studies supporting silvicultural decision-making for future forest management, yet, such strategies may not fully address decision-makers' preferences and uncertainty attitudes. We develop a continuous stand-level optimisation approach that integrates multiple decision criteria, uncertain input data based on ellipsoidal uncertainty sets and biological interactions. The optimisation aims to derive silvicultural strategies that closely align with the objectives and uncertainty attitudes of decision-makers. The novel approach optimises tree species composition and harvesting regimes simultaneously. In our example, the decision criteria are the soil expectation value (SEV), the volume of timber harvested, the sum of cash flows and the average amount of carbon stored in the forest. We use input data for Norway spruce (Picea abies), Silver fir (Abies alba) and European beech (Fagus sylvatica), and integrate biological stand-level interactions represented by a) enhanced survival of tree species in mixed forests and b) the growth response of trees remaining after partial harvesting. The resulting optimal silvicultural strategies ranged from a clear-cutting system (when maximising SEV and ignoring uncertainty) to continuous cover forestry (maximising SEV and considering uncertainty). Our analyses did not support single species forestry – even the clear-cutting system suggested a mixed rather than pure forest. Silvicultural strategies that consider multiple criteria stored up to 47% more carbon than the clear-cutting system, but their SEVs were up to 39% lower. Biological interactions influence the optimal stand composition and harvesting regime, while establishment costs and the discount rate affect the level achieved for each management criterion. Lower survival due to changes in climate hardly influenced the model results. Our optimisation approach is flexible and may integrate many more and different criteria. It is useful to derive silvicultural strategies to guide science-based recommendations for various forest decision-makers.