entropart (version 1.2.0)

DivEst: Diversity Estimation of a metacommunity

Description

Estimates diversity of a metacommunity.

Usage

DivEst(q = 0, MC, Biased = TRUE, Correction = "Best", Tree = NULL, 
  Normalize = TRUE, Z = NULL, Simulations = 100, CheckArguments = TRUE)
## S3 method for class 'DivEst':
plot(x, \dots, main = NULL, Which = "All")
## S3 method for class 'DivEst':
summary(object, \dots)

Arguments

q

A number: the order of diversity.

MC

A MetaCommunity object.

Biased

Logical; if FALSE, a bias correction is appplied.

Correction

A string containing one of the possible corrections. The correction must be accepted by DivPart. "Best" is the default value.

Tree

An object of class hclust or phylog. The tree must be ultrametric.

Normalize

If TRUE (default), diversity is not affected by the height of the tree.. If FALSE, diversity is proportional to the height of the tree.

Z

A relatedness matrix, i.e. a square matrix whose terms are all positive, strictly positive on the diagonal. Generally, the matrix is a similarity matrix, i.e. the diagonal terms equal 1 and other terms are between 0 and 1.

Simulations

The number of simulations to build confidence intervals.

CheckArguments

Logical; if TRUE, the function arguments are verified. Should be set to FALSE to save time when the arguments have been checked elsewhere.

x

An object to be tested or plotted.

main

The title of the plot.

Which

May be "Alpha", "Beta" or "Gamma" to respectively plot the metacommunity's alpha, beta or gamma diversity. If "All" (default), all three plots are shown.

object

A MCdiversity object to be summarized.

...

Additional arguments to be passed to the generic methods.

Value

• A Divest object which is a DivPart object with an additional item in its list:
• SimulatedDiversity
  A matrix containing the simulated values of alpha, beta and gamma diversity.
• Divest objects can be summarized and plotted.

Details

Divest estimates the diversity of the metacommunity and partitions it into alpha and beta components. If Tree is provided, the phylogenetic diversity is calculated else if Z is not NULL, then similarity-based entropy is calculated. Confidence intervals are calculated by Monte-Carlo simulations, drawing simulated communities from a multinomial law following observed frequencies (Marcon et al, 2012 ; 2014)

References

Marcon, E., Herault, B., Baraloto, C. and Lang, G. (2012). The Decomposition of Shannon's Entropy and a Confidence Interval for Beta Diversity. Oikos 121(4): 516-522. Marcon, E., Scotti, I., Herault, B., Rossi, V. and Lang, G. (2014). Generalization of the partitioning of Shannon diversity. PLOS One 9(3): e90289. Marcon, E., Herault, B. (2014). Decomposing Phylodiversity. HAL hal-00946177(version 1). Marcon, E. and Zhang, Z. (2014). The decomposition of similarity-based diversity and its bias correction. HAL hal-00989454(version 1).

See Also

DivPart

Examples

# Load Paracou data (number of trees per species in two 1-ha plot of a tropical forest)
  data(Paracou618)
  # Estimate Shannon diversity.
  Estimation <- DivEst(q = 1, Paracou618.MC, Biased = FALSE, Correction = "Best", 
    Simulations = 1000)
  plot(Estimation)
  summary(Estimation)