Evenness Profiles

Compute species evenness across sites using Hill-based, Pielou, or Simpson evenness measures.

Usage

evenness(
  x,
  q = seq(0.1, 3, by = 0.1),
  type = c("hill", "pielou", "simpson"),
  coords = NULL
)

Arguments

x: A site-by-species matrix (abundance data).
q: Numeric vector. Orders of diversity for Hill evenness. Default seq(0.1, 3, by = 0.1). Note: q = 0 is excluded by default because Hill evenness at q = 0 is trivially S/S = 1.
type: Character. Evenness type: "hill" (Hill evenness E_q = D_q / D_0, default), "pielou" (Pielou's J = log(D_1) / log(S)), or "simpson" (Simpson evenness = (1/D_2) / S).
coords: Optional data.frame with columns x and y for spatial mapping. When provided, enables plot(type = "map").

Value

An object of class spacc_evenness containing:

per_site: Matrix or vector of per-site evenness values
regional: Regional (pooled) evenness
q: Orders used (for Hill type)
type: Evenness type
coords: Coordinates if provided
n_sites: Number of sites
n_species: Number of species

Details

All evenness measures are bounded in $[0, 1]$:

0 = maximally uneven (one dominant species)
1 = perfectly even (all species equally abundant)

Hill evenness (Jost 2010): $$E_q = D_q / D_0$$ This divides the effective number of species at order q by species richness.

Pielou's J (Pielou 1966): $$J = \frac{\log(D_1)}{\log(S)} = \frac{H'}{\log(S)}$$

Simpson evenness: $$E_{1/D} = \frac{1}{D_2 \cdot S}$$

References

Jost, L. (2010). The relation between evenness and diversity. Diversity, 2, 207-232.

Pielou, E.C. (1966). The measurement of diversity in different types of biological collections. Journal of Theoretical Biology, 13, 131-144.

Examples

species <- matrix(rpois(50 * 30, 2), nrow = 50)

# Hill evenness profile
ev <- evenness(species)
print(ev)

# Pielou's J
ev_j <- evenness(species, type = "pielou")
print(ev_j)