Sensitivity of forest model simulations to initial stand conditions, climate and management scenarios based on a novel indicator set

Facing an uncertain future, European forests are expected to fulfill a range of forest ecosystem services (FES), including timber supply, carbon storage or biodiversity. Using criteria and indicators forest managers can evaluate alternative management options and decision support systems (DSS) help them make decisions considering multiple objectives, trade-offs and complex interrelations of forest structure, management and FES. An important tool to support DSSs are modelling tools, that are capable of estimating future forest development under various climate scenarios and management practices and thus define possible development trajectories of European forests. Here we report on the simulation results in the project “OptFor-EU” using the hybrid forest model PICUS v1.5 for three case study areas in Austria, Italy and Romania. We use six different climate inputs (3 RCPs, 2 Regional climate models) and up to nine management alternatives in simulations until year 2099. The initial stand structure was derived using forest inventory data. Validating our results with remote sensing based primary production and leaf area index data, reveals general good agreement, if we consider differences in stand age and stand density. We derive selected indicators from a preliminary set of Essential Forest Mitigation Indicators (EFMI) to evaluate our simulations. Forest carbon, one of the most important regulatory FES, was more sensitive to forest management alternatives than to climate input. Deadwood volume, important not just as carbon storage and water retention, but also habitat to saproxylic organisms, increased under a “no harvesting” management alternative, which may become more frequent in the European Union under the new Nature Restoration law. Other indicators such as multi-layeredness, number of species and the Gini index show an opposite trend over the simulation period. The starting conditions (initial forest structure) overlay the effects of forest management and need prudent consideration, when incorporating simulation results into a DSS, as the outcomes of forest management varies depending on which development phase a forest of interest currently is. We conclude that current simulations using PICUS v1.5 in OptForEU are promising, but further model comparisons are needed to use model outputs for upscaling impacts of climate and management scenarios on a landscape scale.

 

References

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