The R Modular Analysis of Vegetation Information
System (RMAVIS
) R Shiny web application is a tool to assist in the
assignment of vegetation plot sample data to GB National Vegetation
Classification units, with additional exploratory analyses.
We will update and improve RMAVIS
over time in response to user
feedback and hope it acts as a useful tool for the GB ecology and
conservation community.
There are 8 main sections in RMAVIS
at present.
Home - Provides outlining information.
Data Entry - Facilitates data entry and makes available the
taxonomic information used by RMAVIS
.
NVC Analysis - The core of the RMAVIS
application, containing the
functionality present in the original v1.0 release.
NVC Information - Contains a set of searchable tables for inspecting the NVC community names, taxon names, floristic tables, and community attributes.
Documentation - Provides a more detailed overview of the underlying methods, data sources, and usage instructions.
News - Contains the release log and additional news regarding the
development and maintenance of RMAVIS
.
Additional Information - Contains other useful information.
Privacy - A privacy notice.
In addition to accessing RMAVIS
via the web RMAVIS
can be run on
your personal device and installed as an R package.
To run RMAVIS locally take the following steps.
- Ensure R >= 4.4 is installed.
- Install
RMAVIS
usingremotes::install_github("NERC-CEH/RMAVIS")
- Run
install.packages("tinytex")
thentinytex::install_tinytex()
to install a minimal LaTeX distribution. This is required to generate a pdf report. Note that this is only required if you do not have a LaTeX distribution already installed. - From the R terminal run
RMAVIS::runApp()
.
If you wish to use the NVC-matching functions outside of the RMAVIS
app, these are also made available through the RMAVIS
package.
To reference the core RMAVIS
application please cite the JOSS paper as
follows:
Marshall et al., (2024). RMAVIS v1.0: a Shiny application for the analysis of vegetation survey data and assignment to GB NVC communities. Journal of Open Source Software, 9(100), 6682, https://doi.org/10.21105/joss.06682
To cite a specific version of RMAVIS select the relevant release from Zenodo here.
To report a bug please submit a Github issue here, fill out the feedback form here, or send an email to Zeke Marshall.
The development of this app was partly supported by the UK‐SCAPE programme delivering National Capability (NE/R016429/1) funded by the Natural Environment Research Council.
Special thanks are given to Colin Conroy and Barry Jobson for their ongoing and essential support testing RMAVIS.
We would also like to thank Lindsay Maskell, Lucy Ridding, Andy McMullen, John Handley, Michael Tso, Simon Rolph, Cristina Martin Hernandez, and George Linney for testing RMAVIS.
Lastly, we would also like to thank Rob Marrs for his ongoing collaboration with the development of NVC assignment methodologies and the University of Liverpool for their ongoing support.