Searching for Pareto Fronts for Forest Stand Wind Stability by Incorporating Timber and Biodiversity Values

Abstract

Selecting a variant of forest regeneration cuttings that would ensure fulfilling multiple, frequently conflicting forest functions is a challenging task for forest management planning. The aim of this work is to present an efficient and complex analysis of the impact of different forest management scenarios on stand wind stability, timber production (economy), and biodiversity of a secondary mixed temperate forest in Central Europe. We evaluated four different harvest-regeneration systems: clear-cutting, shelter-wood, selection cutting, and no-cutting using theSIBYLA growth simulator. We simulated forest stand development over time and applied 450 variants of 4 harvest-regeneration systems. The selected outputs from the simulator were used as indicators of the fulfilment of wood-production and non-wood-production functions. The calculated indicators were forest stability (height/diameter ratio), economic efficiency (soil expectation value, SEV), and tree species diversity (Shannon index). These indicators were used as inputs for multi-criteria a posteriori decision analysis using the weighted summation method and Pareto fronts. The results revealed substantial trade-offs among the three investigated criteria. The decision space was highly sensitive to their weighting system and included all regeneration systems. The Pareto fronts for wind stability revealed that the maximum stability could be achieved with shelter-wood based on target diameter. This variant, however, fulfils the other two examined functions only to a limited extent (SEV and diversity only to 9% and 27% of their absolute maxima). Other similar variants achieve high stability by sacrificing the diversity and increasing SEV, simultaneously. If a high diversity level is favoured, optimal stability could be achieved by the selection system. The proposed approach enables objective testing of a large number of variants, and an objective assessment of stand management planning since it provides us with the complex multi-dimensional picture about the impact of criteria weights on the selection of optimal variants, and the relative fulfilment of individual criteria.

Forest Regeneration Patterns Differ Considerably between Sites with and without Windthrow Wood Logging in the High Tatra Mountains

“…The risk of wind disturbance in forests increases not only with the increasing severity of the harmful agent (a consequence of climate change [6]), but also with decreasing forest stability, i.e., resistance to wind destruction [7][8][9]. The risk of disturbance is increased with accumulating aboveground biomass stock in forest stands, and at the same time, more wood volume per hectare is obviously damaged in a single disturbance episode [10].…”

Management of Multiple Ecosystem Services under Climate Change, Bioeconomy and Participation

“…Furthermore, Merganic et al [19] analyzed the impact of four forest management scenarios (clear-cutting, shelter-wood, selection cutting, and no-cutting) on wind stability, timber production, and biodiversity in stands as management criteria/objectives. They inte-grated stand level simulation (SIBYLA) with a MCDA tool (OPTIMUS) to construct Pareto frontiers for assessing compromises in forest management.…”

Modelling Future Growth of Mountain Forests Under Changing Environments

“…Predictions by growth models are the best available source of information to optimise forest management and to assess the potential adaptation of the forests to climate change and the mitigation of climate change by the forests. Forest growth models have the potential to test many different variants of forest management, including various species compositions and silvicultural systems, from stand to regional or landscape levels (Fontes et al 2010;Kramer et al 2010;Merganič et al 2020). Example applications of growth models include prediction of future yields, exploration of silvicultural options, preparing resource forecasts, providing insights into stand dynamics, etc.…”