BetaEntropy {entropart} | R Documentation |
Calculates the reduced-bias beta entropy of order q
between communities.
BetaEntropy(MC, q = 1, Correction = "Best", Tree = NULL, Normalize = TRUE,
Z = NULL, CheckArguments = TRUE)
MC |
A |
q |
A number: the order of diversity. Default is 1 for Shannon entropy. |
Correction |
A string containing one of the possible corrections accepted by the bias-corrected entropy function (see details) or |
Tree |
An object of class |
Normalize |
If |
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. |
CheckArguments |
Logical; if |
If Tree
is not NULL
, then phylogenetic entropy is calculated by bcPhyloBetaEntropy
; else, if Z
is not NULL
, then similarity-based entropy is calculated by bcHqzBeta
; else, neutral entropy is calculated by bcTsallisBeta
.
The reduced-bias beta entropy of each community is calculated and summed according to community weights.
Note that beta entropy is related to alpha entropy (if q
is not 1) and cannot be compared accross communities (Jost, 2007). Do rather calculate the BetaDiversity
of the metacommunity.
An MCentropy
object containing entropy values of each community and of the metacommunity.
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. (2015). Decomposing Phylodiversity. Methods in Ecology and Evolution 6(3): 333-339.
Marcon, E., Zhang, Z. and Herault, B. (2014). The decomposition of similarity-based diversity and its bias correction. HAL hal-00989454(version 3).
# Load Paracou data (number of trees per species in two 1-ha plot of a tropical forest)
data(Paracou618)
# Estimate Shannon beta entropy
summary(BetaEntropy(Paracou618.MC, 1))
# Compare without correction
summary(BetaEntropy(Paracou618.MC, 1, Correction = "None"))
# Estimate phylogenetic Shannon beta entropy
summary(BetaEntropy(Paracou618.MC, 1, Tree = Paracou618.Taxonomy) -> e)
plot(e)