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Map species-level attributes over the attribute-space grid

Source: R/lets_maplizer_attr.R
lets.maplizer.attr.Rd

Summarizes species attributes (e.g., trait values, description year) within each attribute-space cell of a presence–absence matrix produced by lets.attrpam. A summary function is applied across the attributes of species present in each cell, producing a per-cell attribute surface and an optional raster for visualization.

Usage

lets.maplizer.attr(x, y, z, func = mean, ras = TRUE, weighted = FALSE)

Arguments

x

An object returned by lets.attrpam, containing the attribute-space PAM (matrix) and its raster.

y

A numeric vector with species attributes to summarize (one value per species in z). If y is a factor, it is coerced to numeric by level codes.

z

A character vector of species names corresponding to y. These names must match the species columns in the attribute-space PAM within x.

func

A function to summarize attributes across species within each cell (e.g., mean, median, sum). Must return a single numeric value.

ras

Logical; if TRUE, include the attribute map as a SpatRaster in the output.

weighted

If TRUE, argument func is ignored, and weighted mean is calculated. Weights are attributed to each species according to 1/N cells that the species occur.

Value

A list with:

  • Matrix_attr: matrix/data.frame with summarized attribute values per attribute cell (first columns are the cell ID and the two attribute axes).

  • Attr_Raster: SpatRaster with the summarized attribute mapped in attribute space.

Details

Map species attributes in attribute space

Internally, the function multiplies each species presence column by its attribute value in y (matched by name via z), sets zeros to NA so that summary functions ignore absences, applies func across species for each cell, and rasterizes the resulting per-cell summaries onto the attribute raster template. Cells with no species remain as NA.

See also

lets.attrpam, lets.plot.attrpam, lets.attrcells

Author

Bruno Vilela

Examples

if (FALSE) { # \dontrun{
# Simulate a dataset of 2000 species with two traits
n <- 2000
Species <- paste0("sp", 1:n)
trait_a <- rnorm(n)
trait_b <- trait_a * 0.2 + rnorm(n)
df <- data.frame(Species, trait_a, trait_b)

# Build attribute-space PAM
x <- lets.attrpam(df, n_bins = 30)

# Map species-level attribute (here, trait_b) by cell using the mean
res <- lets.maplizer.attr(x, y = trait_b, z = Species)

# Plot attribute raster
lets.plot.attrpam(res)
} # }