Multi-scale environmental geodiversity: data for the National Ecological Observatory Network (NEON) with an adaptable...

Spatial variability in environmental conditions is fundamental to explaining and predicting patterns of biodiversity. However, most models explaining patterns of biodiversity use mean values collected at one scale rather than measures of spatial heterogeneity, or "geodiversity", of environmental drivers across multiple scales. Furthermore, accessing and using large, high resolution environmental data sets is often challenging for researchers not trained in supercomputing. To help overcome this barrier, we present an open, reproducible, and adaptable workflow to extract and summarize environmental geodiversity at varying spatial scales. We also provide ready-to-use data on climate and elevation geodiversity metrics and mean values at plot, site, and domain scales for National Ecological Observatory Network (NEON) sites across the United States. The final data set contains over 20,400 tabular values organized into 13 spatial layers. These analysis-ready data, and associated R workflow, will offer opportunities to examine the multiscalar effects of climate and elevation geodiversity on ecological processes.