DivProfile.Rd
Calculate the diversity profiles (alpha, beta, gamma) of a metacommunity.
DivProfile(q.seq = seq(0, 2, 0.1), MC, Biased = TRUE, Correction = "Best",
Tree = NULL, Normalize = TRUE, Z = NULL,
NumberOfSimulations = 0, Alpha = 0.05,
ShowProgressBar = TRUE, CheckArguments = TRUE)
is.DivProfile(x)
# S3 method for DivProfile
plot(x, ..., main = NULL, xlab = "Order of Diversity",
ylab = NULL, Which = "All",
LineWidth = 2, ShadeColor = "grey75", BorderColor = "red")
# S3 method for DivProfile
autoplot(object, ..., main = NULL, xlab = "Order of Diversity",
ylab = NULL, Which = "All", ShadeColor = "grey75", alpha = 0.3, BorderColor = "red",
labels = NULL, font.label = list(size=11, face="plain"),
col = ggplot2::GeomLine$default_aes$colour,
lty = ggplot2::GeomLine$default_aes$linetype,
lwd = ggplot2::GeomLine$default_aes$size)
# S3 method for DivProfile
summary(object, ...)
A numeric vector.
A MetaCommunity
object.
Logical; if FALSE
, a bias correction is appplied.
A string containing one of the possible corrections.
The correction must be accepted by AlphaEntropy
, BetaEntropy
and GammaEntropy
. "Best"
is the default value.
An object of class hclust
, phylo
, phylog
or PPtree
. The tree must be ultrametric.
If TRUE
(default), diversity is not affected by the height of the tree.
If FALSE
, diversity is proportional to the height of the tree.
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.
The number of simulations to run, 0 by default.
The risk level, 5% by default.
If TRUE
(default), a progress bar is shown.
Logical; if TRUE
, the function arguments are verified. Should be set to FALSE
to save time when the arguments have been checked elsewhere.
An object to be tested or plotted.
The main title of the plot. Ignored if Which = "All"
.
The x axis label of the plots.
The y axis label of the plot. Ignored if Which = "All"
.
May be "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.
The width of the line that represents the actual profile.
The color of the shaded confidence envelope.
The color of the bounds of the confidence envelope.
Opacity of the confidence enveloppe, between 0 and 1.
Vector of labels to be added to multiple plots. "auto"
is the same as c("a", "b", "c", "d)"
.
A list of arguments to customize labels. See ggarrange
.
The color of the geom objects. See "Color Specification" in par
.
The type of the lines. See lines
.
The width of the lines. See lines
.
A MCdiversity
object to be summarized or plotted.
Additional arguments to be passed to the generic methods.
If 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.
A DivProfile
object. It is a list:
The name of the MetaCommunity
object containing inventory data.
A vector containing the values of q
.
Logical. If FALSE
, bias corrected values of diversity have been computed.
The estimation bias correction used to calculate diversity. Usually a string, but it may be a list if different corrections have been used in the estimation of phylodiversity.
The method used to calculate entropy ("HCDT", "Similarity-based").
The phylogenetic or functional tree used to calculate phylodiversity.
Logical. Indicates whether phylodiversity is normalized or proportional to the height of the tree.
The matrix used to calculate similarity-based entropy.
A matrix containing the alpha diversity of each community.
A vector containing the alpha diversity of communities for each order.
A vector containing the beta diversity of communities for each order.
A vector containing the gamma diversity of the metacommunity for each order.
A matrix containing the alpha entropy of each community.
A vector containing the alpha entropy of communities for each order.
A vector containing the beta entropy of communities for each order.
A vector containing the gamma entropy of the metacommunity for each order.
Total Alpha, Beta and Gamma Entropy and Diversity may come with a confidence envelope whose value is stored in twelve more vectors named suffixed Low or High, such as GammaEntropyLow
DivProfile
objects can be summarized and plotted.
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., Herault, B. (2015). Decomposing Phylodiversity. Methods in Ecology and Evolution 6(3): 333-339.
# 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)
autoplot(Profile)
summary(Profile)
#> Diversity profile of MetaCommunity Paracou618.MC
#> with correction: UnveilJ
#> Diversity against its order:
#> Order Alpha Diversity Beta Diversity Gamma Diversity
#> UnveilJ 0.0 277.53648 1.293524 359.00000
#> UnveilJ 0.1 253.43317 1.292524 327.56839
#> UnveilJ 0.2 230.43524 1.293933 298.16776
#> UnveilJ 0.3 208.62940 1.298170 270.83648
#> UnveilJ 0.4 188.11846 1.305629 245.61294
#> UnveilJ 0.5 169.01163 1.316623 222.52453
#> UnveilJ 0.6 151.41091 1.331320 201.57635
#> UnveilJ 0.7 135.39585 1.349686 182.74194
#> UnveilJ 0.8 121.00956 1.371445 165.95797
#> UnveilJ 0.9 108.24942 1.396073 151.12409
#> UnveilJ 1.0 97.06467 1.422843 138.10783
#> UnveilJ 1.1 87.36143 1.450904 126.75305
#> UnveilJ 1.2 79.01317 1.479377 116.89026
#> UnveilJ 1.3 71.87395 1.507453 108.34662
#> UnveilJ 1.4 65.79132 1.534463 100.95435
#> UnveilJ 1.5 60.61669 1.559914 94.55679
#> UnveilJ 1.6 56.21256 1.583490 89.01206
#> UnveilJ 1.7 52.45645 1.605040 84.19469
#> UnveilJ 1.8 49.24224 1.624534 79.99569
#> UnveilJ 1.9 46.47987 1.642037 76.32167
#> UnveilJ 2.0 44.09399 1.657672 73.09335