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
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.ProbaVector), and plotted.
Phylogenetic entropy and diversity can be calculated if a phylogenetic (or functional), ultrametric tree is provided. See
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.
Metacommunities are addressed by more specialized functions. The simplest way to import such 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.
The second file should contain the community weights and be organized as follows:
Files can be read and data imported by code such as:
1 2 3 4
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).
A full documentation is available in the vignette. Type:
vignette("entropart"). A quick introuction is in
Eric Marcon, Bruno Herault
Grabchak, M., Marcon, E., Lang, G., and Zhang, Z. (2017). The Generalized Simpson's Entropy is a Measure of Biodiversity. Plos One, 12(3): e0173305.
Marcon, E. (2015) Practical Estimation of Diversity from Abundance Data. HAL 01212435: 1-27.
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 3).
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