Baggio / TESAF

FS 26.107

Impacts of natural disturbances in Alpine forests

Session status: Accepted

Content last updated: 2026-04-16 00:06:27

Online available since: 2025-12-16 17:07:47

Details

Full Title
Natural disturbances in Alpine forests: implications for natural hazard protection, other ecosystem services, and their management
Scheduled
TBA
TBA
Chair
Teich, Michaela
Co-chair(s)
Bührle, Leon; Baggio, Tommaso; Bottero, Alessandra; Lingua, Emanuele; and Moos, Christine
Thematic Focus
Adaption, Ecosystems, Modeling, Monitoring, Natural Hazards
Keywords
pre- and post-disturbance management, protective forest, risk management, modeling, climate change

Abstract/Description

The content was (partly) adapted by AI

Mountain forests in the European Alps are increasingly affected by natural disturbances such as windthrow events, insect outbreaks, and wildfires. While these disturbances are a fundamental component of forest ecosystems, their recent increase in frequency, magnitude, and severity is significantly impacting the provision of critical ecosystem services, including protection against natural hazards such as snow avalanches, rockfall, landslides, and debris flows—a service that is essential for both livelihoods and the economy in the Alpine region.

Shifts in natural disturbance regimes are often driven by climate change and past land management legacies. Consequently, sustainable forest and natural hazard risk management that balances multiple societal demands has become increasingly important under changing climatic conditions, but also in the face of societal growth and evolving needs as well as limited financial, human, and operational resources. Sharing experiences on pre- and post-disturbance management across the Alps is therefore essential to foster mutual learning and develop resilient strategies that provide optimal protection from natural hazards while maintaining other key ecosystem services, such as timber production, freshwater and habitat provision, and space for recreational activities.

This session provides a platform for presenting and discussing the latest research on pre- and post-disturbance management in Alpine forests; the influence of management strategies on disturbance predisposition and recovery; their link to natural hazard protection (including compound events) and other ecosystem services; and related synergies and trade-offs. It also welcomes innovative approaches to quantifying ecosystem services, such as the protective effects of disturbed forests against natural hazards, as well as methods for detecting and monitoring natural disturbances. Contributions may include case studies, management concepts, methodological advances, literature reviews, policy adaptations, and examples in which management interventions did not achieve the intended outcomes. By bringing together researchers, practitioners, and policymakers, the session aims to foster knowledge exchange on effective forest management strategies to mitigate natural hazard risks and maintain ecosystem services under rapidly changing disturbance regimes in mountain forests.

Registered Abstracts

ID: 3.7

Influence of forest compositional naturalness on climate change vulnerability and disturbance risks in Alpine mountain landscapes

Marco Mina
Marzini, Sebastian; Crespi, Alice; Tasser, Erich; Wellstein, Camilla; Albrich, Katharina

Abstract/Description

Forests of the European Alps have been strongly shaped by past human activities, which have influenced their structure and composition. Assessing the natural tree-species composition of current forest landscapes is essential for evaluating their biodiversity potential and for informing management prioritization. High levels of compositional naturalness are often associated with greater ecosystem functioning, but it remains unclear whether forest landscapes that are closer to their potential forest composition are also less vulnerable to future climate change and natural disturbances. Using the process-based landscape model iLand, we quantified the naturalness and the vulnerability to natural disturbances across a large forest landscape in South Tyrol, Italy. We developed a spatially-explicit index to evaluate how closely current tree species composition matches potential forest composition. We then simulated future forest dynamics under multiple climate change and disturbance scenarios (wind and bark beetle), using two different initial vegetation conditions on the same landscape – potential vs. current forest – and compared their future vulnerability based on changes in species dominance, vegetation structure, and height heterogeneity.

Results indicate that current forests exhibit generally low naturalness compared with their potential forest composition, reflecting historical management practices. The naturalness score varied depending on elevation across the landscape, with low- and high-elevation forests showing low naturalness, while mid-elevation forests medium to high naturalness. Vulnerability to natural disturbances under climate change differed between the two initial vegetation conditions. Current forest was more susceptible to bark beetle outbreaks, driven by past promotion of Norway spruce and further amplified by warming. In contrast, the potential forest was more vulnerable to wind disturbance, likely due to old-growth characteristics, such as greater height heterogeneity and canopy roughness, that increase blowdown susceptibility. Given the projected intensification of natural disturbances under future climates, our findings suggest that promoting more natural forest conditions alone may not guarantee higher resilience to climate-induced disturbances. Instead, management approaches should aim at increasing landscape-level structural and compositional heterogeneity in a balanced manner to minimizing future disturbance vulnerability.

ID: 3.49

Early detection of bark beetle infestation by combining remote sensing and scent detection dogs

Alessandra Bottero
Beuchat, Marie-Sarah; Blaser, Simon; Hugentobler, Antonin; Karp, Denise; Loeillot, Tomoki; Lucchinetti, Mario; Stoffel, Andreas

Abstract/Description

Early detection of bark beetle infestation is critical for effective forest management, particularly in mountain forests where steep terrain and limited accessibility often constrain timely interventions. Visual symptoms at canopy level typically appear weeks after host colonization, when control measures are often no longer effective. This study presents a methodological framework that combines drone-based methods with scent detection dogs to improve the detection of early and mostly symptom-free infestation stages of the European spruce bark beetle (Ips typographus).

Multispectral drone imagery is used to spatially prioritize potentially infested trees, while trained detection dogs are deployed for targeted field validation based on pheromone cues. The approach aims to bridge the temporal gap between beetle colonization and visible crown symptoms, while reducing the effort required for extensive ground surveys. Particular emphasis is placed on testing the approach under realistic alpine conditions, including steep terrain, heterogeneous stand structure, and variable meteorological settings.

This contribution focuses on study design, field protocols, and decision workflows relevant for operational forest protection. By systematically integrating remote sensing and biological detection, the proposed framework seeks to support timely decision-making, resource prioritization, and adaptive management in mountain forests facing increasing disturbance pressure under climate change.

ID: 3.50

Optimizing post-bark beetle disturbance management in mountain forests to promote biodiversity and natural tree regeneration under climate change

Alessandra Bottero
Banzer, Theresa; Bugmann, Harald; Garbarino, Matteo; Lingua, Emanuele; Marangon, Davide; Marzano, Raffaella; Mina, Marco

Abstract/Description

The European spruce bark beetle (Ips typographus) has caused considerable damage in many Norway spruce (Picea abies) forests in recent years, due to the dry and warm conditions that have prevailed. As the climate becomes increasingly unfavourable for spruce, at least at low elevations in Europe, and the bark beetle pressure continues to rise, these forests are becoming more vulnerable, posing ecological challenges even in previously unaffected regions at higher elevations.

Prompt removal of infested trees during the early stage of a bark beetle outbreak can protect surrounding trees. However, climate change and increasing beetle populations make timely interventions and large-scale outbreak control increasingly difficult, often shifting management focus to the post-infestation phase. Consequently, effective post-disturbance forest management is becoming essential. Yet, our understanding of ecological advantages and ecosystem service implications of leaving beetle-killed trees in beetle-disturbed areas remains limited.

Our research in spruce-dominated mountain forests in the Swiss and Italian Alps addresses these challenges. We examine the short- to medium-term impacts of post-bark beetle interventions on biodiversity potential and natural tree regeneration by analysing site, forest, and tree characteristics. We distinguish post-disturbance management strategies such as no intervention, partial removal of bark beetle-killed trees with or without release of deadwood on the ground, and salvage logging, and include undisturbed control sites for comparison. At the conference, we will present preliminary results, following field data collection in summer and autumn 2025.

Given the likelihood of increasing frequency and severity of bark beetle disturbance in mountain forests, understanding their impacts and providing practical insights for sustainable post-disturbance management is essential. To effectively address these ecological challenges, efforts should focus on conserving forest biodiversity, enhancing ecosystem resilience, and promoting sustainable forest management under a changing climate.

ID: 3.67

Airborne Laser Scanning (ALS) for assessing the protective effect of lying deadwood on snow avalanche release

Kathrin Holstein
Bührle, Leon J.; Rutzinger, Martin; Winiwarter, Lukas; Baggio, Tommaso; Lingua, Emanuele; Teich, Michaela

Abstract/Description

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.

ID: 3.85

Compound risk in protective forest and natural hazard management

Laura Saxer
Moos, Christine; Teich, Michaela

Abstract/Description

Mountain forests can lower the frequency, magnitude, and intensity of gravity-driven natural hazards such as snow avalanches and rockfall, thereby protecting people, infrastructure, and livelihoods. These so-called protective forests constitute a key nature-based solution (NbS) for Disaster Risk Reduction (DRR), which can be complemented by technical protection measures. However, ongoing climate change increasingly exposes forests to stressors and natural disturbances that reduce their resistance to future impacts and their capacity for recovery.

In this study, we transferred the concept of compound events to protective forests, defining them as multiple, spatially and/or temporally interacting climate-induced stressors and disturbances. Such events can alter forest structure, species composition, and spatial extent, thereby reducing the forests’ protective functions and effects against natural hazards and creating compound risks for people and infrastructure. For example, windthrow and bark beetle infestations can create large forest openings, increasing the likelihood of snow avalanche release.

Compound risks pose novel challenges for pre- and post-disturbance protective forest and natural hazard management. Given the high level of uncertainty and complexity involved, it is necessary to develop a shared understanding of compound risk. There is also a need to quantitatively assess compound risks to enable the implementation of effective protective forest management and compound risk mitigation strategies.

Based on a systematic literature review, we synthesized existing knowledge on compounding stressors and disturbances affecting protective forests to develop an operational definition of compound risk. To support its assessment and management, we proposed a risk-based decision-making framework grounded in adaptive pathways. We applied this framework to two case studies of compound events in forests protecting against rockfall and snow avalanche hazards. For each case study, vulnerabilities and opportunities were characterised through the development of a range of plausible scenarios. The framework further identified different types of actions to mitigate compound risk and evaluated their effectiveness across the defined scenarios. In an additional step, contingency actions were specified to enable risk-based interventions in response to changes in the system.

Overall, we demonstrate that this framework can support flexible and adaptive decision-making in protective forest and natural hazard management under uncertainty arising from compound risk.

ID: 3.128

High resolution forest wind risk mapping under historical and future climate conditions

Tommaso Baggio
Fosser, Giorgia; Locatelli, Tommaso; Lingua, Emanuele

Abstract/Description

Windstorms are the principal cause of disturbance to forests, and due to climate change their frequency and magnitude are expected to increase by the end of the century. Different studies assessed the risk of forest wind disturbances but most of them were mainly limited by forest vulnerability accuracy or climate data especially in complex terrain like the Alps. In this study, we assessed and mapped at high resolution scale (20×20 m) the forest wind risk under the historical (1996-2005) and the future (2090-2099, Representative Concentration Pathway 8.5) reference periods. The study took advantage of high-resolution remotely sensed data to derive individual tree and stand characteristics for calculating forest vulnerability with ForestGALES, a hybrid mechanistic-empirical forest wind risk model. Wind intensities were derived from an ensemble of high temporal and spatial resolution of Convection-Permitting Models. Combining these two datasets, we derived high resolution mapping of the forest wind risk for the Agordino study, in the Dolomites in North-east Italy (extent of 477 km²). This study firstly assess the forest wind vulnerability and then classifies the forest area into three levels of risk. Thanks to the forest metrics the study quantitatively assesses the relative amount of growing stock at risk for each class. Results show that the relative area at risk respect the total forest area is equal to 5.3% and increasing to 6.3 % under the historical and future reference periods, respectively. The risk maps clearly identified the stands at higher risk, mainly composed of pure Norway spruce trees (11.5% and 13.3% at risk respect the total stand spruce forest area), and provide fundamental insights for management prioritization for improving the forest resistance to wind at the regional scale.

ID: 3.152

Optimizing Multi-Source Remote Sensing-Based Vegetation Height Models for Large-Scale Avalanche Hazard Modelling and Protective Forest Delineation

Elia Stihl
Bühler, Yves; Bebi, Peter; Bottero, Alessandra

Abstract/Description

Large-scale avalanche hazard maps are increasingly being used to identify at-risk areas and designate protective forests across mountainous regions. However, the accuracy of these automated approaches depends heavily on the quality of the input data, particularly the vegetation height models (VHMs) applied to characterise forest structure. The ability of current methods for generating VHMs — including photogrammetry, LiDAR and satellite imagery — to capture vegetation characteristics relevant for avalanche protection assessment, varies considerably. These characteristics include canopy density, gap width and tree height. While high-resolution photogrammetry and LiDAR data are available in well-surveyed regions such as Switzerland, other mountainous countries lack access to such detailed datasets. This makes satellite-derived VHMs a crucial alternative for global hazard assessment. These methodological discrepancies may lead to inconsistent definitions of forests with protective effects and propagate through numerical avalanche simulations. This work aims to evaluate and optimise VHM generation methods to improve the accuracy of large-scale avalanche hazard indication modelling and their resulting delineation of forests with protective effects, while also assessing the viability of satellite-based approaches in regions where survey infrastructure is limited.

VHMs derived from three acquisition methods — airborne photogrammetry, airborne LiDAR and satellite imagery — are compared, and their performance in capturing forest parameters critical for avalanche protection is assessed. Large-scale numerical avalanche simulations are conducted at two test sites in the canton of Grisons: a high-altitude coniferous forest and a mixed coniferous-broadleaf forest at lower elevations. Protective forest extents are computed for each VHM input and the resulting hazard maps are compared to quantify differences in avalanche runout zones and protective forest boundaries.

Preliminary analyses suggest that optimized, higher-resolution VHMs provide more accurate delineations of protective forests. By quantifying the differences in accuracy between the various methods, this work will provide guidance on the acceptable trade-offs when using satellite-derived VHMs in regions where data are scarce, thereby supporting a more effective management of natural hazards in mountainous regions.

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FS 26.107

Impacts of natural disturbances in Alpine forests

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