Entropy Partitioning to Measure Diversity


Functions to calculate alpha, beta and gamma diversity of communities, including phylogenetic and functional diversity.

Estimation-bias corrections are available.


In the entropart package, individuals of different "species" are counted in several "communities" which are agregated to define a "metacommunity". In the metacommunity, the probability to find a species in the weighted average of probabilities in communities.

This is a naming convention, which may correspond to plots in a forest inventory or any data organized the same way.

The simplest way to import data is to organize it into two text files. The first file should contain abundance data: the first column named Species for species names, and a column for each community.

Species NameOfCommunity1 NameOfCommunity2
NameOfSpecies1 1 5
NameOfSpecies2 4 2
... ... ...

The second file should contain the community weights and be organized as follows:

Communities Weights
NameOfCommunity1 3
NameOfCommunity2 1

Files can be read and data imported by code such as:

  Abundances <- read.csv(file="Abundances.csv")
  Weights <- read.csv(file="Weights.csv")
  MC <- MetaCommunity(Abundances, Weights)

The last line of the code calls the MetaCommunity function to create an object that will be used by all metacommunity functions, such as DivPart (to partition diversity), DivEst (to partition diversity and calculate confidence interval of its estimation) or DivProfile (to compute diversity profiles).

The package also provides community functions to calculate entropy or diversity with bias correction from a vector of probabilities or abundances, such as bcShannon (to calculate the reduced-bias estimator of Shannon entropy of a community) or Diversity (to calculate the true diversity of a community).

Phylogenetic entropy and diversity can be calculated if a phylogenetic (or functional), ultrametric tree is provided. See PhyloEntropy, Rao for examples of entropy and bcPhyloDiversity to calculate phylodiversity, with bias correction. Similarity-based diversity is calculated with Dqz or (with bias correction) bcDqz, based on a similarity matrix.


Eric Marcon, Bruno Herault


Marcon, E. and Herault, B. (2015). entropart: An R Package to Measure and Partition Diversity. Journal of Statistical Software, 67(8): 1-26.

Marcon, E., Herault, B. (2015). Decomposing Phylodiversity. Methods in Ecology and Evolution 6(3): 333-339.

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., Zhang, Z. and Herault, B. (2014). The decomposition of similarity-based diversity and its bias correction. HAL hal-00989454(version 1).

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