European mountain forests have been shaped by human activities, affecting their structure and composition. Using a process-based forest landscape model in the Italian Alps, we assessed how current tree species composition compares to potential natural composition and examined vulnerability to disturbances under climate change. Results show that current forests generally have low naturalness, especially at low and high elevations, and are more prone to bark beetle outbreaks, while potential forests are more susceptible to wind disturbance due to old-growth traits. Our findings highlight that simply promoting natural forest conditions may not ensure resilience to climate-induced disturbances; instead, management should focus on enhancing structural and compositional heterogeneity to reduce future vulnerability.

Simulation models are important tools to study the impacts of climate change and natural disturbances on forest ecosystems. Being able to track tree demographic processes in a spatially explicit manner, process-based forest landscape models are considered the most suitable to provide robust projections that can aid decision-making in forest management. However, landscape models are challenging to parameterize and setting up new study areas for application studies largely depends on data availability. The aim of this study is to demonstrate the parameterization process, including model testing and evaluation, for setting up a study area in the Italian Alps in a process-based forest landscape model using available data. We processed soil, climate, carbon pools, vegetation, disturbances and forest management data, and ran iterative spin-up simulations to generate a virtual landscape best resembling current conditions. Our results demonstrated the feasibility of initializing forest landscape models with data that are typically available from forest management plans and national forest inventories, as well as openly available mapping products. Evaluation tests proved the ability of the model to capture the environmental constraints driving regeneration dynamics and inter-specific competition in forests of the Italian Alps, as well as to simulate natural disturbances and carbon dynamics. The model can subsequently be applied to investigate forest landscape development under a suite of future scenarios and provide recommendations for adapting forest management decisions.