3D Habitat characterisation for targeted bat conservation in the Vienna Woods Biosphere Reserve

Forest management shapes forest structure and thereby the habitat for wildlife. One group that relies on forests during at least part of its life cycle is European insectivorous bats. In the context of climate change, diversification of forest stands is increasingly promoted as a management strategy. However, robust and quantitative tools to evaluate the structural outcomes of different management regimes and their ecological consequences on forest-dwelling bats remain limited. Traditional forest habitat assessments rely largely on field surveys that are time-consuming and observer-dependent. Such surveys are unable to capture complex three-dimensional structural properties such as gap volume or foliage distribution.

In this study, we present a novel three-dimensional LiDAR-based forest habitat characterisation approach and assess how vegetation structure parameters relate to bat activity and bat species richness. High-resolution 3D point clouds were acquired using a handheld mobile laser scanner in beech and mixed forest stands under managed and unmanaged regimes in the Vienna Woods Biosphere Reserve, Austria. Unlike commonly used 2.5D raster-based methods, our approach exploits the full three-dimensionality of point clouds to quantitatively describe vegetation structure. For habitat characterisation, we calculated the number of potential habitat trees, gap availability (gap ratio), and foliage height diversity (FHD). To illustrate the ecological relevance of these structural parameters, we combined the 3D characterisation with acoustic monitoring of bat echolocation calls across 40 sampling plots. Activity data were collected in May and June 2024 and analysed in relation to forest type, management type, and the calculated vegetation structure parameters.

We found clear differences in vegetation structure between beech and mixed stands. Further, stand type and the three vegetation structure parameters (i.e. number of potential habitat trees, gap ratio, and FHD) significantly affected the activity of foraging groups (e.g. open-space foragers) and taxonomic groups (e.g. Myotis and the Nyctaloid group). In contrast, we did not detect significant effects of stand type, management type, or vegetation structure parameters on species richness. Our results suggest that forest structure primarily influences the intensity of habitat use rather than species presence in the Vienna Woods Biosphere Reserve.

Overall, this study demonstrates the added value of full 3D point cloud analysis for linking forest management practices to habitat characterisation. The proposed workflow, implemented in R and applicable across forested ecosystems, provides forest managers and researchers with a tool to assess and guide management decisions aimed at balancing timber production, climate adaptation, and biodiversity goals. The information gained from the habitat characterisation approach can support ongoing efforts within the Vienna Woods Biosphere Reserve and beyond. Improving forest conditions for bats will contribute to the long-term conservation of these mammals.