ComIndexMulti {cati} R Documentation

Computing multitraits metrics to test and quantify the non-random assembly of communities

Description

Computing multitraits metrics to test and quantify the non-random assembly of communities

Usage


ComIndexMulti(traits = NULL, index = NULL, by.factor = NULL,
nullmodels = NULL, ind.plot = NULL, sp = NULL, com = NULL,
SE = 0, namesindex = NULL, reg.pool = NULL, SE.reg.pool = NULL,
nperm = 99, printprogress = TRUE, independantTraits = TRUE,
type.sp.val = "count")

## S3 method for class 'ComIndexMulti'
plot(x, type = "normal",
col.index = c("red", "purple", "olivedrab3"), add.conf = TRUE,
color.cond = TRUE, val.quant = c(0.025, 0.975), ...)

## S3 method for class 'ComIndexMulti'
print(x, ...)

## S3 method for class 'ComIndexMulti'
summary(object, ...)



Arguments

 traits Individual Matrix of traits with traits in column (or species matrix when using "com" instead of "ind.plot"). index A vector of functions to apply to traits vectors in the form "mean(x, na.rm = TRUE)" or "range(x)". by.factor A factor to split the Matrix of traits and compute index for each subset eg for each site. nullmodels A vector of names corresponding to null models tu use for each index. local (or 1) corresponds to a randomization of individual values within a given community. regional.ind (or 2) corresponds to randomization of individual values within region, ie within all the dataset. A value of regional.pop (or 2sp) corresponds to randomization of population values (each individual value are replaced by the mean value of it population) within region. Finally a value of regional.pop.prab (or 2sp.prab) mirror null model regional.pop but without taking indo account species abundance. For example, if nullmodels = c("local", "regional.ind"), the first index will be calculated on the null model local and the second index on the null model regional.ind. If only one value is given, all the the null model will be determined by this value. ind.plot Factor defining the name of the plot (site or community) in which the individual is. sp Factor defining the species which the individual belong to. com Community data matrix with species (or populations) in rows and sites in column. Use only if ind.plot = NULL. "traits" matrix and "com" matrix must have the same number of rows. SE A single value or vector of standard errors associated with each traits. Especially allow to handle measurement errors. Not used with populational null model. namesindex A vector of names for metrics. reg.pool Regional pool data for traits. If not informed, traits is considere as the regional pool. This matrix need to be larger (more rows) than the matrix "traits". Use only for null model 2. SE.reg.pool A single value or vector of standard errors associated with each traits in each regional pool. Use only if reg.pool is used. Need to have the same dimension as reg.pool. nperm Number of permutations. If NULL, only observed values are returned. printprogress Logical value; print progress during the calculation or not. independantTraits Logical value (default: TRUE). If independantTraits is true (default), each traits is sample independently in null models, if not, each lines of the matrix are randomized, keeping the relation (and trade-off) among traits. type.sp.val Only if ind.plot = NULL. Either "count" or "abundance". Use abundance when all values in the com matrix are not superior to one. x An object of class ComIndexMulti. object An object of class ComIndexMulti. type Type of plot. Possible type = "simple", "simple_range", "normal", "barplot" and "bytraits". col.index Vector of colors for index. add.conf Logical value; Add confidence intervals or not. color.cond Logical value; If color.cond = TRUE, color points indicate T-statistics values significatively different from the null model and grey points are not different from null model. val.quant Numeric vectors of length 2, giving the quantile to calculate confidence interval. By default val.quant = c(0.025,0.975) for a bilateral test with alpha = 5%. ... Any additional arguments are passed to the plot, print or summary function creating the core of the plot and can be used to adjust the look of resulting graph. See plot.listofindex for more arguments.

Details

This function implement four null models which keep unchanged the number of individual per community. Model local (1) corresponds to randomization of individual values within community. Model regional.ind (2) corresponds to randomization of individual values within region. Model regional.pop (2sp) corresponds to randomization of population values within region. Model regional.pop.prab (2sp.prab) corresponds to randomization of population values within region but whitout taking into account for abundance.

S3 method plot for class listofindex:

-Normal type plot means, standard deviations, ranges and confidence intervals of T-statistics.

-Simple_range type plot means, standard deviations and range of T-statistics

-Simple type plot T-statistics for each site and traits and the mean confidence intervals by traits

-Barplot type plot means, standard deviations and confidence intervals of T-statistics in a barplot fashion

-Bysites type plot each metrics for each sites

-Bytraits type plot each metrics for each traits

Value

A list of lists:

 $obs List of observed values for each trait in each community. Each component of the list correspond to a matrix containing the result for each custom function. $null List of null values for each trait in each community. Each component of the list correspond to an array containing the result of the permutations for each custom function. $sites_richness Number of species per site. $namestraits Names of traits. $traits traits data $ind.plot name of the plot in which the individual is $sp groups (e.g. species) which the individual belong to $nullmodels List of null models used for each indices. $call call of the function Tstats $list.index List of index values and associate null models. Internal use in other function. Traits in columns. \$list.index.t List of index values and associate null models. Internal use in other function. Traits in rows.

Author(s)

ComIndex; plot.listofindex; ses

Examples

data(finch.ind)

## Not run:
#For most multivariate functions we need to replace (or exclude) NA values.
#For this example, we use the package mice to complete the data.

comm<-t(table(ind.plot.finch,1:length(ind.plot.finch)))

library(mice)
traits = traits.finch
mice<-mice(traits.finch)
traits.finch.mice<-complete(mice)

#A simple example to illustrate the concept of the function ComIndexMulti

n_sp_plot<-as.factor(paste(sp.finch, ind.plot.finch, sep = "_"))
res.sum.1<-ComIndexMulti(traits.finch,
index = c("sum(scale(x), na.rm = T)", "sum(x, na.rm = T)"),
by.factor = n_sp_plot, nullmodels = "regional.ind",
ind.plot = ind.plot.finch, nperm = 9, sp = sp.finch)
res.sum.1

#A more interesting example using the function hypervolume
library(hypervolume)

hv<-hypervolume(traits.finch.mice,
reps = 100,bandwidth = 0.2,
verbose = F, warnings = F)
plot(hv)

hv.1<-ComIndexMulti(traits.finch.mice,
index = c("as.numeric(try(hypervolume(na.omit(x), reps = 100,
bandwidth = 0.2, verbose = F, warnings = F)@Volume))"),
by.factor = rep(1,length(n_sp_plot)), nullmodels = "regional.ind",
ind.plot = ind.plot.finch, nperm = 9, sp = sp.finch)

hv.1

## End(Not run)


[Package cati version 0.99.4 Index]