Regional Mountain Conference

Mountain forests provide essential ecosystem services, including protection against snow avalanches. However, high-severity natural disturbances such as windthrow and bark beetle outbreaks can substantially alter forest structure, often resulting in large amounts of standing and lying deadwood, which may modify their protective effect. As climate change increases the frequency and severity of such disturbances while management resources remain limited, there is a growing need to prioritize post-disturbance management in protective forests at large scales. 

Recently, a 3D point cloud-based tool was developed to assess the protective effect of increased surface roughness from lying deadwood on snow avalanche release. The tool was calibrated using 3D point clouds acquired from unmanned aerial vehicle (UAV)-based photogrammetry. However, UAV surveys are feasible only over relatively small areas. For regional prioritization of post-disturbance management, ALS data provide a promising alternative. Nevertheless, their applicability for detecting deadwood structures linked to a potential protective effect against snow avalanches has not yet been investigated. Using the new framework, we evaluate how and when surface roughness from lying deadwood becomes progressively buried by increasing snow depth, thereby allowing potential avalanche release. 

A comparison between UAV- and ALS-based assessments shows that ALS analyses reproduce key patterns identified in UAV-derived data, confirming transferability. Results from ALS data acquired in 2019 (one year after Storm Vaia) demonstrate that lying deadwood structures are detectable and that quantified surface roughness is comparable to UAV-based results. A sensitivity analysis was conducted to evaluate the influence of critical thresholds of key parameters. Applying the calibrated parameters shows that the protective effect within windthrow areas is often sufficient for snow depths up to 1.5 m, but this threshold varies depending on pre-disturbance forest conditions, deadwood displacement, terrain characteristics, and remaining standing forest elements. The approach is further demonstrated for a test site (3 km²) affected by high-severity disturbance from Storm Vaia. 

The framework provides a novel decision-support tool for practitioners and policymakers, enabling rapid prioritization of post-disturbance management over large areas and highlighting the potential of lying deadwood as a nature-based solution in avalanche-protective mountain forests.