spaccBetaFunc: Functional Beta Diversity Accumulation

In spacc: Fast Spatial Species Accumulation Curves

Functional Beta Diversity Accumulation

Description

Compute spatial accumulation of functional beta diversity, partitioned into turnover and nestedness components. Measures how functional trait space composition changes as sites are accumulated spatially.

Usage

spaccBetaFunc(
  x,
  coords,
  traits,
  n_seeds = 50L,
  method = "knn",
  index = c("sorensen", "jaccard"),
  distance = c("euclidean", "haversine"),
  parallel = TRUE,
  n_cores = NULL,
  progress = TRUE,
  seed = NULL
)

Arguments

x	A site-by-species matrix (presence/absence or abundance).
coords	A data.frame with columns x and y, or a spacc_dist object.
traits	A species-by-traits matrix. Row names should match species.
n_seeds	Integer. Number of random starting points. Default 50.
method	Character. Accumulation method. Default "knn".
index	Character. Dissimilarity index: "sorensen" (default) or "jaccard".
distance	Character. Distance method. Default "euclidean".
parallel	Logical. Use parallel processing? Default TRUE.
n_cores	Integer. Number of cores.
progress	Logical. Show progress? Default TRUE.
seed	Integer. Random seed.

Details

Functional beta diversity quantifies the turnover of functional traits across space. At each accumulation step, beta is computed based on the overlap of trait ranges (functional space) between the accumulated pool and the newly added site.

Value

An object of class spacc_beta with additional attribute beta_type = "functional".

References

Baselga, A. (2012). The relationship between species replacement, dissimilarity derived from nestedness, and nestedness. Global Ecology and Biogeography, 21, 1223-1232.

Cardoso, P., Rigal, F. & Carvalho, J.C. (2015). BAT – Biodiversity Assessment Tools. Methods in Ecology and Evolution, 6, 232-236.

See Also

spaccBeta(), spaccBetaPhylo()

Examples

coords <- data.frame(x = runif(50), y = runif(50))
species <- matrix(rbinom(50 * 20, 1, 0.3), nrow = 50)
traits <- matrix(rnorm(20 * 3), nrow = 20)
rownames(traits) <- colnames(species) <- paste0("sp", 1:20)

beta_func <- spaccBetaFunc(species, coords, traits)
plot(beta_func)

spacc documentation built on June 20, 2026, 5:07 p.m.