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Create a presence–absence matrix in environmental space

Source: R/lets_envpam.R
lets.envpam.Rd

Transform a presence–absence matrix (PAM) based on geographic coordinates into a new PAM structured in environmental space. The function rasterizes the environmental variable space (based on two continuous environmental predictors), and assigns species presences to binned environmental conditions, producing a species richness raster in environmental space.

Usage

lets.envpam(
  pam,
  envs,
  n_bins = 30,
  remove.cells = TRUE,
  remove.sp = TRUE,
  count = FALSE
)

Arguments

pam

A `PresenceAbsence` object, typically created using lets.presab.

envs

A two-column matrix or data frame with continuous environmental variables corresponding to the coordinates in the PAM. The first column will be used as the x-axis and the second as the y-axis in the environmental space.

n_bins

Number of bins used to discretize each environmental variable. Default is 30.

remove.cells

Logical. Should cells with no species be removed from the final matrix?

remove.sp

Logical. Should species with no occurrences in environmental space be removed?

count

Logical. If TRUE, displays a progress bar for species processing.

Value

A list with the following elements:

  • Presence_and_Absence_Matrix_env: A matrix of species presences across environmental bins.

  • Presence_and_Absence_Matrix_geo: The original PAM coordinates associated with environmental cells.

  • Env_Richness_Raster: A raster layer of species richness in environmental space.

  • Geo_Richness_Raster: The original species richness raster in geographic space.

Details

This function projects species occurrences into a two-dimensional environmental space, facilitating ecological analyses that depend on environmental gradients. The environmental space is discretized into a regular grid (determined by n_bins), and each cell is assigned the number of species occurring under those environmental conditions.

See also

lets.presab, lets.addvar, lets.plot.envpam

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))

# Run function
res <- lets.envpam(PAM, envs)

# Plot results
lets.plot.envpam(x = res,
            species = NULL,
            cell_id_env = NULL,
            cell_id_geo = NULL,
            T,
            world = TRUE,
            mar = c(4, 4, 4, 4))
} # }