Entropy Partitioning to Measure Diversity

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entropart is an R package that provides 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 may (or not) be 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.

Basic functions allow computing diversity of a community. Data is simply a vector of probabilities (summing up to 1) or of abundances (integer values that are numbers of individuals). Calculate entropy with functions such as Tsallis, Shannon, Simpson, Hurlbert or GenSimpson and explicit diversity (i.e. effective number of species) with Diversity and others. By default, the best available estimator of diversity will be used, according to the data.

Communities can be simulated by rCommunity, explicitely declared as a species distribution (as.AbdVector or as.ProbaVector), and plotted.

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


A full documentation is available in the main vignette. In R, type: vignette("entropart"). It is a continuous update of the paper published in the Journal of Statistical Software (Marcon & Hérault, 2015).

A quick introduction is in vignette("docs", "entropart").


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