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A collection of functions to summarize the Portal Data


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R-CMD-check License Coverage status CRAN downloads

DOI DOI NSF-1929730


The portalr package provides collection of basic functions to summarize the Portal project data on rodents, plants, ants, and weather at our long-term field site in the Chihuahuan Desert. The data begin in 1977 and are continuously updated today. There are functions to summarize rodent abundance, biomass, or energy and by site, plot, or treatment type. There are functions to summarize the weather data collected from our automated weather stations and plant data that is collected each summer and fall.


You can install portalr from CRAN with:


OR from github with:

# install.packages("remotes")


  1. Load all data tables from the PortalData GitHub repo:
data_tables <- load_rodent_data("repo")
  1. Download and generate summaries of rodent abundance and biomass:

rodent_data <- abundance(".") # default grouping is by sampling period

rodent_biomass_by_plot <- biomass(".", level = "plot", type = "granivores", 
shape = "flat", time = "date")
  1. Retrieve weather data:
weatherdata <- weather("Monthly", ".")

For more detailed info, checkout the vignettes associated with the package:


More Information

The data repo contains useful details for issues with data collection, and background on why we handle them the way we do. Of course, it also contains the raw data, if you would like to create more complex data summaries than what is provided here.

Find a list of previous publications using the Portal data at our website.

Follow our blog to get the latest news on what is happening with our project and at the site.


To cite portalr, please refer to either:

  • JOSS publication:

    Erica M. Christensen, Glenda M. Yenni, Hao Ye, Juniper L. Simonis, Ellen K. Bledsoe, Renata M. Diaz, Shawn D. Taylor, Ethan P. White, and S. K. Morgan Ernest. (2019). portalr: an R package for summarizing and using the Portal Project Data. Journal of Open Source Software, 4(33), 1098,

  • or use the most recent release on Zenodo.

Dataset Citation

To cite the Portal dataset, use:

#> To cite the Portal Data in publications, use:
#>   S. K. Morgan Ernest, Glenda M. Yenni, Ginger Allington, Ellen K.
#>   Bledsoe, Erica M. Christensen, Renata M. Diaz, Keith Geluso, Jacob R.
#>   Goheen, Qinfeng Guo, Edward Heske, Douglas Kelt, Joan M. Meiners, Jim
#>   Munger, Carla Restrepo, Douglas A. Samson, Michele R. Schutzenhofer,
#>   Marian Skupski, Sarah R. Supp, Kate Thibault, Shawn Taylor, Ethan
#>   White, Diane W. Davidson, James H. Brown, and Thomas J. Valone.
#>   (2018). The Portal Project: a long-term study of a Chihuahuan desert
#>   ecosystem. bioRxiv,
#> A BibTeX entry for LaTeX users is
#>   @Article{ernest2018portal,
#>     title = {The Portal Project: a long-term study of a Chihuahuan desert ecosystem},
#>     author = {S. K. Morgan Ernest and Glenda M. Yenni and Ginger Allington and Ellen K. Bledsoe and Erica M. Christensen and Renata M. Diaz and Keith Geluso and Jacob R. Goheen and Qinfeng Guo and Edward Heske and Douglas Kelt and Joan M. Meiners and Jim Munger and Carla Restrepo and Douglas A. Samson and Michele R. Schutzenhofer and Marian Skupski and Sarah R. Supp and Kate Thibault and Shawn Taylor and Ethan White and Diane W. Davidson and James H. Brown and Thomas J. Valone},
#>     year = {2018},
#>     journal = {bioRxiv},
#>     doi = {10.1101/332783},
#>   }