Data and materials for Nesslage et al. 2024 - Hydrologically informed estimation of plant species richness across a vernal pool complex using drone-mounted LiDAR

The repository is organized in terms of the data used in the Nesslage et al. 2024 study titled Hydrologically informed estimation of plant species richness across a vernal pool complex using drone-mounted LiDAR, the outputs from the statistical analyses performed, and the scripts used to perform the analyses on the data. We reasoned that as hydrology is an important driver of the distribution of plant communities across vernal pools, we should be able to use digital elevation models obtained over vernal pool complexes with drone-based LiDAR to generate hydrological proxies that enable prediction of plant spatial patterns. We generated high resolution (1m) hydrologic proxies related to hydroperiod, hydrologic connectivity, and soil moisture from drone-mounted LiDAR and created models to estimate the number of total plant species, as well as the number of forbs and grasses across a vernal pool complex. We found that models using drone-mounted LiDAR derived parameters enabled spatial predictions of plant species richness to within 2-3 species. Herein, we provide the data, outputs of the statistical analysis, and the scripts to enable reproduction of the results obtained.