Description Details Author(s) References
Functions to calculate alpha, beta and gamma diversity of communities, including phylogenetic and functional diversity.
Estimationbias 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 stateoftheart estimationbias correction. Similaritybased 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.
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:
1 2 3 4  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).
A full documentation is available in the vignette. Type: vignette("entropart")
. A quick introuction is in vignette("Introduction", "entropart")
.
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: 127.
Marcon, E. and Herault, B. (2015). entropart: An R Package to Measure and Partition Diversity. Journal of Statistical Software, 67(8): 126.
Marcon, E., Herault, B. (2015). Decomposing Phylodiversity. Methods in Ecology and Evolution 6(3): 333339.
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): 516522.
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 similaritybased diversity and its bias correction. HAL hal00989454(version 3).
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