Here we provide two datasets, which are used in the paper by Iannone et al. 2018 "Environmental harshness drives spatial heterogeneity in biotic resistance" published in Neobiota. Both are provided as a separate tab in a single Excel spreadsheet. The “Info” tab provides more detail on both.
The first dataset, “FIA_Plot_Data”, was collected as part of the U.S. Forest Inventory Analysis Program (USDA, Forest Service; https://apps.fs.usda.gov/fia/datamart/). It provides locations (e.g. coordinates, ecological sections, States, Counties, etc.), maximum tree height, metrics of native tree diversity (species richness and four separate metrics of evolutionary diversity), native tree biomass and relative density, invasive plant species richness and cover, and an estimate of stand age from 42,626 plots in the eastern United States of America (USA). This geographic area is defined by Iannone et al (In press) and Iannone et al (2016), i.e., the two studies that present and analyze these data.
The second dataset is a compilation of findings from Iannone et al (In press) and a summary of the first dataset. Iannone et al (In press) used a mixed-effects modeling framework to model invasive plant species richness and cover in response to four metrics of native tree evolutionary diversity. This framework allowed independent estimates for model intercepts and slopes for each of the 91 ecological sections contained within the eastern USA. This dataset provides these independent estimates. It also provides mean and SD of maximum tree height and relative tree density, as well as mean Jaccard distance based on absence presence of native tree species, and mean stand age all estimated across plots found in each of the 91 ecological sections of the eastern USA.
Cite this work
Researchers should cite this work as follows:
- Iannone, B., Potter, K., Guo, Q., Jo, I., Oswalt, C., Fei, S. (2018). Data on native tree diversity (species richness and phylogenetic), biomass, relative density, tree height, and invasive plants in forests of the eastern USA. Purdue University Research Repository. doi:10.4231/R7GX48TW