Community Turnover (Overlap) Indices

R functions for calculating pairwise community turnover (overlap) indices.

The main implementation and detailed API documentation are in turnover.R. Complete runnable examples using Species.csv are in turnover_examples.R.

References:

• Hillebrand et al. (2018), Biodiversity change is uncoupled from species richness trends: Consequences for conservation and monitoring, J Appl Ecol, 55, 169-184.
• Gotelli, Chao & Colwell (2024), Measuring and Estimating Species Richness, Taxonomic and Phylogenetic Diversity, and Related Biotic (Dis)similarity Indices From Sampling Data, 314-339.

Input

Input is an M x N table or matrix X, where rows are community observations and columns are species abundances, frequencies, or presence/absence values.

Optional vectors or data frames can provide observation dates, spatial coordinates, and grouping variables.

Main Functions

turnover(
  X,
  method = "SERr",
  combinations = "i<j",
  dates = NULL,
  locations = NULL,
  measure = "euclidean",
  ext_inv = FALSE,
  groupby = NULL
)

turnover() returns a data frame, usually named turnover_df in examples, with pairwise community turnover values and optional metadata such as dates, time intervals, spatial distances, and group names.

turnover_s(X, method = "SERr", combinations = "i<j")

turnover_s() is a convenience wrapper for species-only calculations. It is equivalent to calling turnover() without dates, locations, ext_inv, or groupby.

Methods

Method	Alias	Meaning
method = "SERr"	method = "U0"	Richness-based turnover for presence/absence data; equivalent to Jaccard dissimilarity / dist(X, method = "binary").
method = "Horn"	method = "U1"	Shannon-entropy-based Horn turnover value for Hill number q = 1.
method = "SERa"		Abundance-based turnover from Hillebrand et al. (2018), the complement of the Wishart similarity ratio.
method = "U2"		Hill-number order q = 2 turnover (overlap) value from the Chao U_q family. Identical communities have U2 = 1.

See the roxygen comments in turnover.R for formulas, returned columns, and method-specific notes.

Minimal Example

source("turnover.R")

data <- read.csv("Species.csv")
SpecColumns <- 4:ncol(data)
X <- data[, SpecColumns]

SERr <- turnover(X, method = "SERr")
U0 <- turnover(X, method = "U0")
Horn <- turnover(X, method = "Horn")
U1 <- turnover(X, method = "U1")
SERa <- turnover(X, method = "SERa")
U2 <- turnover(X, method = "U2")

SampleDates <- as.Date(data$Date, format = "%Y-%m-%d")
XY <- data[, 2:3]

turnover_df <- turnover(X, method = "SERa", dates = SampleDates, locations = XY)
head(turnover_df)

Full Examples

Complete examples are provided in turnover_examples.R and can be run with:

source("turnover_examples.R")