These files contain data that Menalled et al. (2022) used to test the effects of crop density and mulch biomass on weed suppression and community assembly. The data was generated through a field experiment replicated for four site-years. In each site-year, soybean was planted at five rates from 0 to 74 seeds m-2, and five cereal rye mulch levels were established from 0 to 2 times the ambient cereal rye biomass within each site-year for 25 unique treatments. All treatments were replicated in four blocks for 100 plots per site-year. Approximately 15 weeks after soybean planting, weed biomass, soybean density, and mulch biomass were sampled in each plot. Changes in weed biomass and species abundance were used to assess weed suppression and community composition. We assessed treatment effects on weed life cycle, emergence timing, seed weight, height, and specific leaf area using trait data for each species. Results show that multi-tactic weed management can enhance weed suppression and promote the management of diverse weed functional groups. All analyses and results are reported and discussed in Menalled et al. (2022): “Cereal rye mulch biomass and crop density affect weed suppression and community assembly in no-till planted soybean.”
Code/
├── AnalysisCode.md #markdown of code
└── AnalysisCode.Rmd #code file
Data/
├── BSR_WideMatrix.xlsx #plant species observations
└── FunctionalTraitsCleaned.xlsx #trait data used for analysis
renv/
├── .gitignore
├── activate.R
└── settings.json
.gitignore
.Rprofile
functional-diversity-filters.Rproj
LICENSE
README.md
renv.lock
Version control is done using the renv package. This package maintains a package library within the project folder. It is useful because it automatically restores all package versions that I used during my analysis to the within-project package library on your computer. Don’t worry, all changes will only be within the project and will not affect your R packages outside of this project. The renv package will automatically run when you open the project. Upon your first use of my project, you will have to restore all the packages that I used by running renv::restore() in your R console. To do this, you might have to make sure that your version of R is sufficiently up-to-date. Also, you will need to be connected to the internet. For more information on the renv package, see these wonderful YouTube videos:
If the renv workflow is not working, you can remove the renv folder and renv.lock files from the project and manually install packages. However, this is not recommended as you will not be using the same package versions as I used during my analysis. Finally, please note that the renv package makes note of the R version I used the last time I saved my files (4.5.1, although I was using 4.4.0 during paper writing… results don’t change), but it will not change your R version.
Uploaded to Zenodo for long-term storage:
