Compute multivariate environmental similarity surfaces (MESS), as described by Elith et al., 2010.
extrapol_mess(x, training, .col, ...)# S3 method for default
extrapol_mess(x, training, ...)
# S3 method for SpatRaster
extrapol_mess(x, training, .col, filename = "", ...)
# S3 method for data.frame
extrapol_mess(x, training, .col, ...)
# S3 method for SpatRasterDataset
extrapol_mess(x, training, .col, ...)
a terra::SpatRaster (data.frame) with
the MESS values.
matrix or data.frame or sf object containing the reference values; each column
should correspond to one layer of the terra::SpatRaster object, with the exception
of the presences column defined in .col (optional).
the column containing the presences (optional). If specified, it is excluded when computing the MESS scores.
additional arguments as for terra::writeRaster()
character. Output filename (optional)
Jean-Pierre Rossi, Robert Hijmans, Paulo van Breugel, Andrea Manica
This function is a modified version of mess in
package predicts, with a method added to work on terra::SpatRasterDataset.
Note that the method for terra::SpatRasterDataset assumes that each variables
is stored as a terra::SpatRaster with time information within x. Time
is also assumed to be in years. If these conditions are not met, it is possible
to manually extract a terra::SpatRaster for each time step, and use
extrapol_mess on those terra::SpatRasters
Elith J., M. Kearney M., and S. Phillips, 2010. The art of modelling range-shifting species. Methods in Ecology and Evolution 1:330-342.