r.mess

r.mess [-mkl] vector_input=name raster_input=names[,names,...] output=name [columns=string] [--overwrite] [--verbose] [--quiet]

Flags:

-m

Most dissimilar variable (MoD)

-k

Calculate MESS_mean - the mean value of the individual

-l

Calculate MESS_median

--overwrite

Allow output files to overwrite existing files

--verbose

Verbose module output

--quiet

Quiet module output

Parameters:

vector_input=name [required]

Reference points

raster_input=names[,names,...] [required]

Input raster map(s)

output=name [required]

Root name of the output MESS data layers

columns=string

Columns with environmental variables

Default: Same names as input layers

DESCRIPTION

r.mess computes the "Multivariate Environmental Similarity Surfaces" (MESS) in GRASS using R as backend. The MESS index was proposed by Elith et al (2010) and is also implemented in the Maxent software. The MESS approach can be described as follows (from Elith et al 2010): "The multivariate environmental similarity surface (MESS) calculation represents how similar a point is to a reference set of points, with respect to a set of predictor variables (V1, V2, ...). The values in the MESS are influenced by the full distribution of the reference points, so that sites within the environmental range of the reference points but in relatively unusual environments will have a smaller value than those in very common environments."

This module will also compute the individual environmental similarity surfaces (IESS), which represents how similar a point is to a set of reference set of points for each of the input variable. MESS is then simply calculated as the minimum of its similarity with respect to each variable.

The IESS can have negative values – these are sites where the variable has a value that is outside the range in the reference set. A negative MESS thus represents sites where at least one variable has a value that is outside the range of environments over the reference set, so these are novel environments.

In addition to the MESS, which is the minimum(IESS), the r.mess function also allows to compute mean and medium of the IESS layers.

SEE ALSO

There is also a similar function implemented for R using the R package raster. See here for more information and the script.

AUTHORS

Contact: Paulo van Breugel

REFERENCES

1. Elith, J., Kearney, M., & Phillips, S. 2010. The art of modelling range-shifting species. Methods in Ecology and Evolution 1: 330–342.