Compute multivariate environmental similarity surfaces (MESS), as described by Elith et al., 2010.
Usage
extrapol_mess(x, training, .col, ...)
# Default S3 method
extrapol_mess(x, training, ...)
# S3 method for class 'stars'
extrapol_mess(x, ...)
# S3 method for class 'SpatRaster'
extrapol_mess(x, training, .col, filename = "", ...)
# S3 method for class 'data.frame'
extrapol_mess(x, training, .col, ...)
# S3 method for class 'SpatRasterDataset'
extrapol_mess(x, training, .col, ...)Arguments
- x
terra::SpatRaster,stars,terra::SpatRasterDatasetordata.frame- training
matrix or data.frame or sf object containing the reference values; each column should correspond to one layer of the
terra::SpatRasterobject, with the exception of the presences column defined in.col(optional).- .col
the column containing the presences (optional). If specified, it is excluded when computing the MESS scores.
- ...
additional arguments as for
terra::writeRaster()- filename
character. Output filename (optional)
Value
a terra::SpatRaster (data.frame) with the MESS values.
Details
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