Ungulate browsing is a major driver of forest regeneration dynamics and habitat structure in managed temperate forests, influencing species composition, regeneration success, and long-term stand development. Traditional assessments of browsing impacts often rely on field-based indicators such as regeneration density or visual cover, but these metrics provide limited insight into three-dimensional habitat structure. Mobile handheld LiDAR offers highly detailed measurements of forest structure, enabling objective and reproducible quantification of structural complexity that complements and extends conventional field-based methods. In this study, we applied handheld LiDAR as an innovative indicator for habitat structure within the ungulate browsing zone (<2 m height) to evaluate structural development across sites differing in management context. Paired fenced and unfenced plots (12 × 12 m) were surveyed within the WiWaldI project framework in 2019 and 2023 and compared across three hunting regimes representing different degrees of ungulate population management. Structural complexity was quantified by deriving box-counting dimensions from LiDAR point clouds, providing a measure of spatial arrangement and density relevant to ungulate–vegetation interactions. To support interpretation and ecological context, we complemented LiDAR indicators with streamlined field assessments. Based on this framework, we assessed whether forest structural complexity and visual cover differ among regions and over time, and whether ungulate browsing induces detectable structural differences between fenced whether structural differences between fenced and unfenced plots are detectable. We further examined the relative importance of tree species composition, plant architecture, and hunting regime as drivers of three-dimensional habitat structure. A simplified octant method characterized the spatial distribution of woody regeneration, while a silhouette-based approach quantified visual cover from the perspective of a standard ungulate profile. These auxiliary measures contextualize visual and spatial aspects of structure that LiDAR metrics capture with minimal observer bias. LiDAR studies have previously demonstrated potential for linking high-resolution structural data to ungulate habitat use, and our approach extends this by focusing on structural complexity as a habitat indicator. Results show a consistent increase in LiDAR-derived structural complexity between 2019 and 2023 across all regions. This increase occurred across management contexts and was not consistently explained by fencing or hunting regime effects, suggesting that site conditions, forest composition, and successional processes were dominant drivers during the observation period. Hunting regime showed no statistically significant and no consistent effect on structural complexity across regions or years. Visual cover metrics varied strongly among regions and species and declined over time. These findings suggest that three-dimensional habitat structure information has the potential to enhance the evaluation of ungulate impacts and may support evidence-based forest and wildlife management, particularly when interpreted in the context of site conditions and successional dynamics. Beyond ungulate impact assessment, the presented handheld LiDAR approach provides a scalable remote sensing framework for precision forestry by capturing three-dimensional structural attributes that are directly linked to forest stability, resilience, growth dynamics, and stand-level species mixing, thereby supporting evidence-based forest management recommendations.
Jordan-Fragstein et al. (Thu,) studied this question.