Summary

The R Modular Analysis of Vegetation Information System (RMAVIS) is an R Shiny application for the assignment of vegetation sample plot data to British National Vegetation Classification (NVC) communities.

RMAVIS is the latest in a series of computer programs for NVC assignment, beginning with TABLEFIT, then MATCH, and most recently MAVIS - for which it is the successor.

At present RMAVIS provides the following functionality:

  • Calculate similarities and assign vegetation sample plot data to GB NVC communities, with a new set of Scottish oceanic wet grassland communities provided by the Floodplain Meadows Partnership.
  • Retrieve the habitats associated with the top-fitting NVC communities from alternative habitat classifications.
  • Composes floristic tables from the survey data and views the NVC floristic tables side-by-side.
  • Compiles a frequency table containing the occurrence of each species present in the vegetation sample plots over time.
  • Calculates mean environmental indicator values, at present the Hill-Ellenberg moisture, light, nitrogen, reaction, and salinity scores.
  • Calculates a range of diversity metrics.
  • Performs a multivariate analysis, facilitating the visualisation of the sample plots in an ordination space.
  • Provides the facility to download the results of an RMAVIS session as a xlsx file or generate a pdf report.

 

The MVA module of `RMAVIS`, showing the trajectory of all sample plots from the Leith Hill Wood example dataset in the ordination spaces over time.

 

Accessing RMAVIS

RMAVIS is hosted on the UKCEH Posit Connect server.

Access RMAVIS

 

Feedback

Feedback on RMAVIS is welcome and can be submitted via a form, by creating a Github issue, or by contacting Zeke Marshall.

Feedback form

Github issue

 

Recommended citation

The code which constitutes RMAVIS is stored and versioned using Zenodo. To cite RMAVIS use either the DOI for all versions as follows:

DOI

Marshall, Z., Smart, S. M., Harrower, C., & Marrs, R. (2024). RMAVIS. Zenodo. https://zenodo.org/doi/10.5281/zenodo.10818640

or the DOI associated with a particular release.

Acknowledgements

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.

We would like to thank Lindsay Maskell, Lucy Ridding, Barry Jobson, Colin Conroy, Andy McMullen, John Handley, Michael Tso, Simon Rolph, Cristina Martin Hernandez, and George Linney for testing RMAVIS.

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.