Predicting soil microbial alpha diversity at the landscape scale using LiDAR-derived variables

Soil microbial communities serve as key mediators of biophysical and biochemical processes. Their interactions with roots and other soil organisms shape belowground diversity and ecosystem responses to environmental change. Despite their importance, mapping soil microbial diversity remains challenging due to measurement complexity, particularly at large spatial extents. Forest structure influences belowground dynamics and may therefore serve an indirect proxy for predicting soil microbial diversity across landscapes. Accordingly, this study integrates forest structural information and soil microbial profiles to predict soil microbial diversity at the landscape scale. LiDAR-derived forest structural attributes representing tree size, vertical complexity, and lower-canopy structure were combined with soil bacterial and fungal alpha-diversity indices (observed richness, Shannon diversity, and phylogenetic diversity) derived from environmental DNA (eDNA) profiles. Environmental gradients, including forest type, soil pH, stand age, and elevation, were used to evaluate whether spatial patterns in predicted diversity align with known ecological patterns. Gaussian Process Regression (GPR) models were developed using LiDAR-derived variables to predict microbial diversity indices. The results demonstrated that LiDAR variables (with canopy height and upper-canopy return variables being the most important predictors) have the potential to serve as proxies for estimating soil microbial diversity across landscapes. Between 34% and 46% of the variation in soil microbial diversity was explained by LiDAR variables, with richness and phylogenetic diversity showing the strongest predictive performance. Predicted diversity patterns exhibited ecologically consistent responses to key environmental gradients, including forest type, soil pH, stand age, and elevation. This approach provides ecologists and managers with a practical tool for developing conservation strategies that integrate above- and belowground biodiversity at large spatial extents.