DivProfile(q.seq = seq(0, 2, 0.1), MC, Biased = TRUE, Correction = "Best", Tree = NULL, Normalize = TRUE, Z = NULL, NumberOfSimulations = 0, Alpha = 0.05, CheckArguments = TRUE)
is.DivProfile(x)
"plot"(x, ..., main = NULL, xlab = "Order of Diversity", ylab = NULL, Which = "All", LineWidth = 2, ShadeColor = "grey75", BorderColor = "red")
"summary"(object, ...)
MetaCommunity
object.
FALSE
, a bias correction is appplied.
AlphaEntropy
, BetaEntropy
and GammaEntropy
. "Best"
is the default value.
TRUE
(default), diversity is not affected by the height of the tree.
If FALSE
, diversity is proportional to the height of the tree.
TRUE
, the function arguments are verified. Should be set to FALSE
to save time when the arguments have been checked elsewhere.
Which = "All"
.
Which = "All"
.
"Communities"
, "Alpha"
, "Beta"
or "Gamma"
to respectively plot the alpha diversity of communities or the metacommunity's alpha, beta or gamma diversity. If "All"
(default), all four plots are shown.
MCdiversity
object to be summarized.
DivProfile
object. It is a list:DivProfile
objects can be summarized and plotted.
Tree
is provided, the phylogenetic diversity is calculated.
DivPart
partitions the diversity of the metacommunity into alpha and beta components. It supports estimation-bias correction.
If Tree
is provided, the phylogenetic diversity is calculated else if Z
is not NULL
, then similarity-based entropy is calculated.
Beta diversity/entropy is calculated from Gamma and Alpha when bias correction is required, so community values are not available.
If NumberOfSimulations
is greater than 0, a bootstrap confidence interval is produced by simulating communities from a multinomial distribution following the observed frequencies (Marcon et al, 2012; 2014) and calculating their profiles.DivPart
# Load Paracou data (number of trees per species in two 1-ha plot of a tropical forest)
data(Paracou618)
# Estimate diversity.
Profile <- DivProfile(q.seq = seq(0, 2, 0.1), Paracou618.MC, Biased = FALSE)
plot(Profile)
summary(Profile)
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