ausplotsR: quickstart guide to basic analysis of TERN AusPlots vegetation data

Introduction

TERN AusPlots is a national plot-based terrestrial ecosystem surveillance monitoring method and dataset for Australia (Sparrow et al. 2020). Through ausplotsR, users can directly access AusPlots data collected by on-ground observers on vegetation and soils, including physical sample/voucher details and barcode numbers. The dataset can be downloaded in its entirety or as individual modules, and can be subsetted by geographic bounding box or species name search. The package also includes a series of bespoke functions for working with AusPlots data, including visualisation, creating tables of species composition, and calculation of tree basal area, fractional cover or vegetation cover by growth form/structure/strata and so on.

This is a short guide for getting started with analysis of AusPlots data through the ausplotsR R package. More information on making use of AusPlots data in ausplotsR is available through the package help files and manual. Below, we demonstrate installing the package, accessing some AusPlots data, generating matrices and running simple example analyses.

More comprehensive tutorials on accessing and analysing AusPlots data (Blanco-Martin 2019) are available at: https://github.com/ternaustralia/TERN-Data-Skills/tree/master/EcosystemSurveillance_PlotData

Installing the package and accessing raw data

The latest version of ausplotsR can be installed directly from github using the devtools package, which must be installed first.

library(devtools)
install_github("ternaustralia/ausplotsR", build_vignettes = TRUE, dependencies = TRUE)

Once installed, load the package as follows. Note, packages vegan, maps and mapdata are required for ausplotsR to load, and functions are also imported from packages: plyr, R.utils, simba, httr, jsonlite, sp, maptools, ggplot2, gtools, jose, curl and betapart, while knitr and rmarkdown are required to build this package vignette (i.e., if ‘build_vignettes’ is set to TRUE above).

library(ausplotsR)

We can now access live data, starting here with basic site information and vegetation point-intercept modules and using a bounding box to spatially filter the dataset to central Australia. All data modules are extracted via a single function, get_ausplots:

# See ?get_ausplots to explore all data modules available

my.ausplots.data <- try(get_ausplots(bounding_box = c(125, 140, -40, -10)))

#> Vignette aborted due to database connection issue.