Data from: Use and categorization of Light Detection and Ranging vegetation metrics in avian diversity and species distribution research

Aim: Vegetation structure is a key determinant of animal diversity and species distributions. The introduction of Light Detection and Ranging (LiDAR) has enabled the collection of massive amounts of point cloud data for quantifying habitat structure at fine resolution. Here, we review the current use of LiDAR-derived vegetation metrics in diversity and distribution research of birds, a key group for understanding animal-habitat relationships. Location: Global. Methods: We review 50 relevant papers and quantify where, in which habitats, at which spatial scales and with what kind of LiDAR data current studies make use of LiDAR metrics. We also harmonize and categorize LiDAR metrics and quantify their current use and effectiveness. Results: Most studies have been conducted at local extents in temperate forests of North America and Europe. Rasterization is currently the main method to derive LiDAR metrics, usually from airborne laser scanning data with low point densities (<10 points/m2) and small footprints (<1 m diameter). Our metric harmonization suggests that 40% of the currently used metric names are redundant. A categorisation scheme allowed to group all metric names into 18 out of 24 theoretically possible classes, defined by vegetation part (total vegetation, single trees, canopy, understory, and other single layers as well as multi-layer) and structural type (cover, height, horizontal variability, vertical variability). Metrics related to canopy cover, canopy height and canopy vertical variability are currently most often used, but not always effective. Main conclusions: LiDAR metrics play an important role in understanding animal space use. Our review and the developed categorization scheme may facilitate future studies in the selection, prioritization and ecological interpretation of LiDAR metrics. The increasing availability of airborne and spaceborne LiDAR data and the development of voxel-based and object-based approaches will further allow novel ecological applications, also for open habitats and other vertebrate and invertebrate taxa.