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Calculate Multivariate Environmental Similarity

Source: R/mess.R
mess.Rd

Calculate Multivariate Environmental Similarity and most dissimilar/similar variables with respect to a reference dataset, for a set of environmental variables.

Usage

mess(x, ref, full = FALSE, filename = "", ...)

# S3 method for class 'Raster'
mess(x, ref, full = FALSE, filename = "", ...)

# S3 method for class 'SpatRaster'
mess(x, ref, full = FALSE, filename = "", ...)

# S3 method for class 'data.frame'
mess(x, ref, full = FALSE, ...)

# S3 method for class 'matrix'
mess(x, ref, full = FALSE, ...)

Arguments

x

Climate (or environmental) data as a terra::SpatRaster, raster::Raster*, list, data.frame, or matrix where each layer/element/column represents focal values of an environmental variable.

ref

A data.frame, matrix, or list where each column/element represents reference values for an environmental variable (corresponding to those given in x).

full

Logical to indicate whether similarity values should be returned for all variables. If FALSE (the default), then only the minimum similarity scores across variables will be returned.

filename

Optional filename for writing spatial raster output (i.e., the mess raster only). Default is "".

...

Additional parameters.

Value

If x is a SpatRaster or Raster* object, this function returns a list containing:

  • mess: a SpatRaster layer giving the minimum similarity value across all variables for each location (i.e. the MESS);

  • mess_by_variable: a SpatRaster giving the environmental similarities for each variable in x (only included when full=TRUE);

  • mod: a factor SpatRaster layer indicating which variable was most dissimilar to its reference range (i.e. the MoD map, Elith et al. 2010); and

  • mos: a factor SpatRaster layer indicating which variable was most similar to its reference range.

If x is a list, matrix or data.frame, the function will return a list as above, but with multilayer and single layer SpatRaster objects replaced by matrix and vector objects, respectively.

Details

mess uses the MESS algorithm described in Appendix S3 of Elith et al. 2010.

References

Elith, J., Kearney, M., and Phillips, S. (2010). The art of modelling range-shifting species. Methods in Ecology and Evolution, 1: 330-342. doi:10.1111/j.2041-210X.2010.00036.x

Examples

if (FALSE) { # \dontrun{
library(geodata)
library(terra)
bio <- worldclim_global("bio", res = 10, path = tempdir())
aus <- gadm("AUS", level = 0, resolution = 2, path = tempdir())
occ <- spatSample(aus, size = 100, method = "random")
ref <- terra::extract(bio, occ, ID = FALSE)
m <- mess(bio, ref, full = TRUE)

# Plot outputs
plot(m)
plot(m, which = "mod")
plot(m, which = "mos")
} # }