Use of airborne lidar data to improve plant species richness and diversity monitoring in lowland and mountain forests.

ABSTRACT: We explored the potential of airborne laser scanner (ALS) data to improve Bayesian models linking biodiversity indicators of the understory vegetation to environmental factors. Biodiversity was studied at plot level and models were built to investigate species abundance for the most abundant plants found on each study site, and for ecological group richness based on light preference. The usual abiotic explanatory factors related to climate, topography and soil properties were used in the models. ALS data, available for two contrasting study sites, were used to provide biotic factors related to forest structure, which was assumed to be a key driver of understory biodiversity. Several ALS variables were found to have significant effects on biodiversity indicators. However, the responses of b

SUBMITTER: Bouvier M 

PROVIDER: S-EPMC5597197 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature