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 stars
extrapol_mess(x, ...)
# 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.
terra::SpatRaster, stars, terra::SpatRasterDataset or
data.frame
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.