profile_similarity: Similarity-Based Diversity Profile of a Community

In divent: Entropy Partitioning to Measure Diversity

Similarity-Based Diversity Profile of a Community

Description

Calculate the diversity profile of a community, i.e. its similarity-based diversity against its order.

Usage

profile_similarity(
  x,
  similarities,
  orders = seq(from = 0, to = 2, by = 0.1),
  ...
)

## S3 method for class 'numeric'
profile_similarity(
  x,
  similarities = diag(length(x)),
  orders = seq(from = 0, to = 2, by = 0.1),
  estimator = c("UnveilJ", "Max", "ChaoShen", "MarconZhang", "UnveilC", "UnveiliC",
    "naive"),
  probability_estimator = c("Chao2015", "Chao2013", "ChaoShen", "naive"),
  unveiling = c("geometric", "uniform", "none"),
  richness_estimator = c("jackknife", "iChao1", "Chao1", "naive"),
  jack_alpha = 0.05,
  jack_max = 10,
  coverage_estimator = c("ZhangHuang", "Chao", "Turing", "Good"),
  sample_coverage = NULL,
  as_numeric = FALSE,
  n_simulations = 0,
  alpha = 0.05,
  bootstrap = c("Chao2015", "Marcon2012", "Chao2013"),
  show_progress = TRUE,
  ...,
  check_arguments = TRUE
)

## S3 method for class 'species_distribution'
profile_similarity(
  x,
  similarities = diag(sum(!colnames(x) %in% non_species_columns)),
  orders = seq(from = 0, to = 2, by = 0.1),
  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,
  n_simulations = 0,
  alpha = 0.05,
  bootstrap = c("Chao2015", "Marcon2012", "Chao2013"),
  show_progress = TRUE,
  ...,
  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.
similarities	a similarity matrix, that can be obtained by fun_similarity. Its default value is the identity matrix.
orders	The orders of diversity used to build the profile.
...	Unused.
estimator	An estimator of entropy.
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.
richness_estimator	an estimator of richness to evaluate the total number of species, see div_richness. used for interpolation and 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.
n_simulations	The number of simulations used to estimate the confidence envelope of the profile.
alpha	The risk level, 5% by default, of the confidence envelope of the profile.
bootstrap	the method used to obtain the probabilities to generate bootstrapped communities from observed abundances. If "Marcon2012", the probabilities are simply the abundances divided by the total number of individuals \insertCiteMarcon2012adivent. If "Chao2013" or "Chao2015" (by default), a more sophisticated approach is used (see as_probabilities) following \insertCiteChao2013;textualdivent or \insertCiteChao2015;textualdivent.
show_progress	if TRUE, a progress bar is shown during long computations.
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

A bootstrap confidence interval can be produced by simulating communities (their number is n_simulations) with rcommunity and calculating their profiles. Simulating communities implies a downward bias in the estimation: rare species of the actual community may have abundance zero in simulated communities. Simulated diversity values are recentered so that their mean is that of the actual community.

Value

A tibble with the site names, the estimators used and the estimated diversity at each order. This is an object of class "profile" that can be plotted.

References

\insertAllCited

Examples

# Similarity matrix
Z <- fun_similarity(paracou_6_fundist)
# Profile
profile_similarity(paracou_6_abd, similarities = Z, q = 2)

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