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R package for live extraction, preparation, visualisation and analysis of TERN Ecosystem Surveillance monitoring data (AusPlots data).

(See bottom of page for troubleshooting help)

Through ausplotsR, users can now directly access plot-based data on vegetation and soils across Australia, with simple function calls to extract the data and merge them into species occurrence matrices for analysis or to calculate things like basal area and fractional cover.

The data have been collected by TERN’s Ecosystem Surveillance platform via field surveys and sampling across a national network of plots and transects. Follow the links for more information on the research infrastructure provided by the Terrestrial Ecosystem Research Network (TERN), an Australian Government NCRIS-enabled project, and its Ecosystem Surveillance platform.

New features in ausplotsR version 1.2

Update to the latest package version to make use of new features:

  1. Demonstration maps and graphical vegetation attributes in a single call.
  2. Additional standardised plant taxonomic fields making it easy to clean species occurrence data or filter or search data by plant family.
  3. Simple species lists for sites.
  4. Revamped help files and manual.
  5. Detailed metadata for all data modules.
  6. Additional options for calculating vegetation cover by plant growth form, e.g., cumulative by species versus absolute cover; cover by strata.
  7. Corrected implementation of Importance Value Index (IVI) calculation as measure of species importance.
  8. Optimisation of plot selection to maximise species accumulation.

Using ausplotsR

You have two options for using the package:

  1. in the cloud via EcoCloud
  2. installed on your computer

ausplotsR on EcoCloud

EcoCloud allows you to get started very quickly with AusplotsR. When you start a new RStudio instance on EcoCloud, AusplotsR is already installed for you so you can get into playing with the data right away. Follow the official guide to get started on EcoCloud and be sure to create an RStudio instance.

NOTE EcoCloud is no longer being updated, pending launch of the new EcoCommons online resource, and so only an older version of ausplotsR is available.

ausplotsR on your computer

ausplotsR is now available on CRAN, meaning it can be installed using the 'install packages' command or menu in an R or RStudio session.

ausplotsR requires the following packages: 'Depends': vegan, maps, mapdata; 'Imports': plyr, R.utils, simba, httr, jsonlite, sp, maptools, ggplot2, gtools, jose, betapart, curl; 'Suggests' (needed to build the package vignette if 'build_vignettes' is set to TRUE below): knitr, rmarkdown.

The most current ausplotsR can be installed directly from github to get the latest developments and patches using the devtools package, which must be installed first.

To install the package, use:

# if you have problems, see the troubleshooting section at the bottom of this document
install_github("ternaustralia/ausplotsR", build_vignettes = TRUE, dependencies = TRUE)

To get started:


To download AusPlots data, start with:


Or, to simply grab all vegetation point intercept and voucher data plus basic site info for all available plots, use:

library(ausplotsR) <- get_ausplots()


A suggested citation is automatically generated in the following format when you extract TERN AusPlots data via ausplotsR:

TERN ("year") AusPlots ecosystem surveillance monitoring dataset (URL: Obtained via the ausplotsR R package (URL:, accessed "day month year".

To print the citation of our package:


Please include appropriate citation in published papers/reports/theses that use the data and R functions.

Repeatability with older versions of the package

If you need to install an older version of the package for repeatability, you can do so by supplying the specific version to the install_github call. The version to install can be obtained from the citation string you obtained when you first used the package (see above).

As an example, the output from the citation function call might look like:

... R package version 1.0 commit SHA=559e0eb77ca3d42a7276351695db42331ef170b4.

The piece of information we need is the commit ID/SHA, which in this example is 559e0eb77ca3d42a7276351695db42331ef170b4. We would then use this to install this specific version of the package with:

install_github("ternaustralia/ausplotsR", build_vignettes = TRUE, ref = '559e0eb77ca3d42a7276351695db42331ef170b4')

Authors: Greg Guerin, Tom Saleeba, Samantha Munroe, Irene Martín-Forés, Bernardo Blanco-Martin, Andrew Tokmakoff


These packages have more recent versions available

When you try to install AusplotsR, you might see a notice like the following.

These packages have more recent versions available.
Which would you like to update?

 1:   All
 2:   CRAN packages only
 3:   None
 4:   backports   (1.1.4  -> 1.1.5 ) [CRAN]
 5:   callr       (3.2.0  -> 3.4.2 ) [CRAN]

AusplotsR has a list of other packages, and their versions, that it needs to work. R is being helpful and telling you that it can install the newest versions of those packages rather than the versions that AusplotsR has asked for.

The safest choice is to select 3: None, which means the exact versions AusplotsR asks for will be installed. You're free to install newer versions of packages if you would like but beware that AusplotsR may not work with these newer packages.

Rcmd.exe not found

We've seen this error when trying to install AusplotsR on Windows in RStudio.

Error in rethrow_call(c_processx_exec, command, c(command, args), stdin, :
Command 'C:/some/path/to/R/R-3.6.3/bin/x64/Rcmd.exe' not found @win/processx.c:98

It seems to be an issue with your R installation. There an official FAQ that seems related but the instructions on how to fix it aren't related to RStudio. So we'll add our own here.

  1. make sure you have R itself installed. You can get the latest version from
  2. Open RStudio
  3. Open the Tools -> Global Options menu item
  4. Click the Change button for the R version
  5. Make sure it's set to Use your machine's default version of R64 (64-bit) screenshot showing how to configure RStudio to use the default R on your machine
  6. Click OK