dist_gcms: Distance Between GCMs

In chooseGCM: Selecting General Circulation Models for Species Distribution Modeling

Distance Between GCMs

Description

This function compares future climate projections from multiple General Circulation Models (GCMs) based on their similarity in terms of variables. It calculates distance metrics and plots the results on a heatmap.

Usage

dist_gcms(
  s,
  var_names = c("bio_1", "bio_12"),
  study_area = NULL,
  scale = TRUE,
  method = "euclidean"
)

Arguments

s	A list of stacks of General Circulation Models (GCMs).
var_names	Character. A vector of names of the variables to compare, or 'all' to include all variables.
study_area	An Extent object, or any object from which an Extent object can be extracted. Defines the study area for cropping and masking the rasters.
scale	Logical. Whether to apply centering and scaling to the data. Default is TRUE.
method	Character. The correlation method to use. Default is "euclidean". Possible values are: "euclidean", "maximum", "manhattan", "canberra", "binary", "minkowski", "pearson", "spearman", or "kendall".

Value

A list containing two items: distances (the calculated distances between GCMs) and heatmap (a plot displaying the heatmap).

Author(s)

Luíz Fernando Esser ([e-mail]) https://luizfesser.wordpress.com

See Also

transform_gcms flatten_gcms

Examples

var_names <- c("bio_1", "bio_12")
s <- import_gcms(system.file("extdata", package = "chooseGCM"), var_names = var_names)
study_area <- terra::ext(c(-80, -30, -50, 10)) |> terra::vect(crs="epsg:4326")
dist_gcms(s, var_names, study_area, method = "euclidean")

chooseGCM documentation built on April 3, 2025, 5:27 p.m.