title: Spinning a laser web: predicting spider distributions using LiDAR.
abstract: LiDAR remote sensing has been used to examine relationships between vertebrate diversity and environmental characteristics, but its application to invertebrates has been limited. Our objectives were to determine whether LiDAR-derived variables could be used to accurately describe single-species distributions and community characteristics of spiders in remote forested and mountainous terrain. We collected over 5300 spiders across multiple transects in the Bavarian National Park (Germany) using pitfall traps. We examined spider community characteristics (species richness, the Shannon index, the Simpson index, community composition, mean body size, and abundance) and single-species distribution and abundance with LiDAR variables and ground-based measurements. We used the R2 and partial R2 provided by variance partitioning to evaluate the predictive power of LiDAR-derived variables compared to ground measurements for each of the community characteristics. The total adjusted R2 for species richness, the Shannon index, community species composition, and body size had a range of 25-57%. LiDAR variables and ground measurements both contributed >80% to the total predictive power. For species composition, the explained variance was approximately 32%, which was significantly greater than expected by chance. The predictive power of LiDAR-derived variables was comparable or superior to that of the ground-based variables for examinations of single-species distributions, and it explained up to 55% of the variance. The predictability of species distributions was higher for species that had strong associations with shade in open-forest habitats, and this niche position has been well documented across the European continent for spider species. The similar statistical performance between LiDAR and ground-based measures at our field sites indicated that deriving spider community and species distribution information using LiDAR data can provide not only high predictive power at relatively low cost, but may also allow unprecedented mapping of community- and species-level spider information at scales ranging from stands to landscapes. Therefore, LiDAR is a viable tool to assist species-specific conservation as well as broader biodiversity planning efforts not only for a growing list of vertebrates, but for invertebrates as well.
authors.affiliation: Department of Fish and Wildlife Resources, University of Idaho, Box 441136, Moscow, Idaho 83844-1136, USA. kerriv@uidaho.edu
authors.forename: K T
authors.initials: KT
authors.lastname: Vierling
authors.forename: C
authors.initials: C
authors.lastname: Bässler
authors.forename: R
authors.initials: R
authors.lastname: Brandl
authors.forename: L A
authors.initials: LA
authors.lastname: Vierling
authors.forename: I
authors.initials: I
authors.lastname: Weiss
authors.forename: J
authors.initials: J
authors.lastname: Müller
mesh_terms: D000818:Animals; D003710:Demography; D017753:Ecosystem; D005858:Germany; D007834:Lasers; D058998:Remote Sensing Technology / Q000191:economics / Q000379:methods*; D013112:Spiders / Q000502:physiology*; D014197:Trees