Plot species richness in environmental and geographical space

This function plots species richness in both environmental and geographical space based on the output of lets.envpam. It can optionally highlight species distributions, individual cells, or regions in both spaces.

Usage

lets.plot.envpam(
  x,
  species = NULL,
  cell_id_env = NULL,
  cell_id_geo = NULL,
  geo_plot = TRUE,
  world = TRUE,
  rast_return = FALSE,
  col_rich = NULL,
  ...
)

Arguments

x: The output object from lets.envpam).
species: A character string indicating the species name to be highlighted in both plots.
cell_id_env: An integer or vector of integers indicating environmental space cell(s) to be highlighted.
cell_id_geo: An integer or vector of integers indicating geographic cell(s) to be highlighted.
geo_plot: Logical. Should the geographic richness map also be plotted? Default is TRUE.
world: Logical. If TRUE, plots a base map using the `wrld_simpl` object from the `letsR` package over the geographic raster.
rast_return: Logical. If TRUE, returns the modified raster objects instead of plotting.
col_rich: A custom color ramp palette function to use for plotting richness (e.g., from colorRampPalette).
...: Additional arguments passed to the plot function for rasters.

Details

This function provides a visual summary of species richness across both geographic and environmental dimensions. Users can highlight specific species or environmental/geographical cells. When a highlight is selected, both rasters are modified to display only presences related to the selected species or cells, and all other cells are greyed out.

Author

Bruno Vilela

Examples

if (FALSE) { # \dontrun{
# Load data
data("Phyllomedusa")
data("prec")
data("temp")

prec <- unwrap(prec)
temp <- unwrap(temp)
PAM <- lets.presab(Phyllomedusa, remove.cells = FALSE)
envs <- lets.addvar(PAM, c(temp, prec), onlyvar = TRUE)
colnames(envs) <- c("Temperature", "Preciptation")
wrld_simpl <- get(utils::data("wrld_simpl", package = "letsR"))
PAM <- lets.pamcrop(PAM, vect(wrld_simpl))

# Create environmental PAM
res <- lets.envpam(PAM, envs)

# Plot both spaces
lets.plot.envpam(x = res,
            species = NULL,
            cell_id_env = NULL,
            cell_id_geo = NULL,
            geo_plot = TRUE,
            world = TRUE,
            mar = c(4, 4, 4, 4))

# Highlight a single species
plot.envpam(res, species = "Phyllomedusa_atlantica")
} # }