div_similarity: Similarity-Based Diversity of a Community

In divent: Entropy Partitioning to Measure Diversity

Similarity-Based Diversity of a Community

Description

Estimate the diversity of species from abundance or probability data and a similarity matrix between species. Several estimators are available to deal with incomplete sampling. Bias correction requires the number of individuals.

Usage

div_similarity(x, similarities, q = 1, ...)

## S3 method for class 'numeric'
div_similarity(
  x,
  similarities = diag(length(x)),
  q = 1,
  estimator = c("UnveilJ", "Max", "ChaoShen", "MarconZhang", "UnveilC", "UnveiliC",
    "naive"),
  probability_estimator = c("Chao2015", "Chao2013", "ChaoShen", "naive"),
  unveiling = c("geometric", "uniform", "none"),
  jack_alpha = 0.05,
  jack_max = 10,
  coverage_estimator = c("ZhangHuang", "Chao", "Turing", "Good"),
  sample_coverage = NULL,
  as_numeric = FALSE,
  ...,
  check_arguments = TRUE
)

## S3 method for class 'species_distribution'
div_similarity(
  x,
  similarities = diag(sum(!colnames(x) %in% non_species_columns)),
  q = 1,
  estimator = c("UnveilJ", "Max", "ChaoShen", "MarconZhang", "UnveilC", "UnveiliC",
    "naive"),
  probability_estimator = c("Chao2015", "Chao2013", "ChaoShen", "naive"),
  unveiling = c("geometric", "uniform", "none"),
  jack_alpha = 0.05,
  jack_max = 10,
  coverage_estimator = c("ZhangHuang", "Chao", "Turing", "Good"),
  gamma = FALSE,
  as_numeric = FALSE,
  ...,
  check_arguments = TRUE
)

Arguments

x	An object, that may be a numeric vector containing abundances or probabilities, or an object of class abundances or probabilities. If it is a numeric vector, then its length must equal the dimensions of the similarities matrix: species are assumed to be in the same order.
similarities	a similarity matrix, that can be obtained by fun_similarity. Its default value is the identity matrix.
q	a number: the order of diversity.
...	Unused.
estimator	An estimator of asymptotic diversity.
probability_estimator	a string containing one of the possible estimators of the probability distribution (see probabilities). Used only for extrapolation.
unveiling	a string containing one of the possible unveiling methods to estimate the probabilities of the unobserved species (see probabilities). Used only for extrapolation.
jack_alpha	the risk level, 5% by default, used to optimize the jackknife order.
jack_max	the highest jackknife order allowed. Default is 10.
coverage_estimator	an estimator of sample coverage used by coverage.
sample_coverage	the sample coverage of x calculated elsewhere. Used to calculate the gamma diversity of meta-communities, see details.
as_numeric	if TRUE, a number or a numeric vector is returned rather than a tibble.
check_arguments	if TRUE, the function arguments are verified. Should be set to FALSE to save time when the arguments have been checked elsewhere.
gamma	if TRUE, \gamma diversity, i.e. diversity of the metacommunity, is computed.

Details

All species of the species_distribution must be found in the matrix of similarities if it is named. If it is not, its size must equal the number of species. Then, the order of species is assumed to be the same as that of the species_distribution.

Similarity-Based diversity can't be interpolated of extrapolated as of the state of the art.

Value

A tibble with the site names, the estimators used and the estimated diversity.

Examples

# Similarity matrix
Z <- fun_similarity(paracou_6_fundist)
# Diversity of each community
div_similarity(paracou_6_abd, similarities = Z, q = 2)
# gamma diversity
div_similarity(paracou_6_abd, similarities = Z, q = 2, gamma = TRUE)

divent documentation built on April 3, 2025, 7:40 p.m.