Spatial Endemism Accumulation

Compute the number of endemic species (species found only within the accumulated area) as sites are added spatially. Complements the standard SAC by tracking species unique to each spatial extent.

Usage

spaccEndemism(
  x,
  coords,
  n_seeds = 50L,
  method = "knn",
  distance = c("euclidean", "haversine"),
  map = FALSE,
  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.
n_seeds: Integer. Number of random starting points. Default 50.
method: Character. Accumulation method. Default "knn".
distance: Character. Distance method: "euclidean" or "haversine".
map: Logical. If TRUE, compute per-site endemism by running accumulation from each site as seed. Stores a site_values data.frame enabling plot(type = "map") and as_sf(). Default FALSE.
parallel: Logical. Use parallel processing? Default TRUE.
n_cores: Integer. Number of cores.
progress: Logical. Show progress? Default TRUE.
seed: Integer. Random seed.

Value

An object of class spacc_endemism containing:

richness: Matrix of cumulative richness (n_seeds x n_sites)
endemism: Matrix of endemic species count (n_seeds x n_sites)
site_values: Per-site endemism data.frame (if map = TRUE)
coords, n_seeds, n_sites, method: Parameters used

Details

At each accumulation step k, an endemic species is one that is present in the accumulated sites (1..k) but absent from all remaining unvisited sites (k+1..n). This tracks how many species are unique to the area sampled so far.

The endemism curve typically starts low (few endemics at small areas), increases as the region grows, and eventually equals total richness when all sites are included.

References

Kier, G., Kreft, H., Lee, T.M., et al. (2009). A global assessment of endemism and species richness across island and mainland regions. Proceedings of the National Academy of Sciences, 106, 9322-9327.

May, F., Gerstner, K., McGlinn, D.J., et al. (2018). mobsim: an R package for the simulation and measurement of biodiversity across spatial scales. Methods in Ecology and Evolution, 9, 1401-1408.

Examples

# \donttest{
coords <- data.frame(x = runif(50), y = runif(50))
species <- matrix(rbinom(50 * 30, 1, 0.3), nrow = 50)

end <- spaccEndemism(species, coords, n_seeds = 30)
plot(end)
# }