This function asses the effects of taxonomic uncertainty on the R2 coefficients and the p-values of a permutational multivariate analysis of variance using distance matrices.
adonis_pertables(formula = X ~ ., data, permutations = 5, method = "bray")
# S3 method for adonis_pertables
plot(x, ...)adonis_pertables returns an object of classadonis_pertables, basically a list with the following components:
An object of class adonis, i.e. the results of applying mantel to the original biological data table without the unidentified species. This includes p-values for each explanatory variable showing the probability of obtaining the same F statistic under different scenarios of taxonomic uncertainty.
A list with the results of the simulation: F, i.e. a data.frame with all the simulated pseudo-F (columns) for each explanatory variable (rows); R2, i.e. a data.frame with all the simulated R2 coefficients (columns) for each explanatory variable (rows); pvalue, i.e. a data.frame with all the simulated p-values (columns) for each explanatory variable (rows); R2.quant, i.e. a data.frame with the summary of R2 by quantiles; p.quant,, i.e. a data.frame with the summary of pvalue by quantiles.
The objects of class adonis_pertables have print and plot S3 methods for a simple access to results. See the examples.
A typical model formula such as 'Y ~ A + B*C', but where 'Y' is a pertables object (i.e. a list of simulated community data matrices obtained with pertables; 'A', 'B', and 'C' may be factors or continuous variables.
The data frame from which 'A', 'B', and 'C' would be drawn.
Number of replicate permutations used for the hypothesis tests (F tests) for each simulated community data matrices obtained with pertables.
The name of any method used in 'vegdist' to calculate pairwise distances.
adonis_pertables object to plot.
Additional graphical parameters passed to plot.
Luis Cayuela and Marcelino de la Cruz
Cayuela, L., De la Cruz, M. and Ruokolainen, K. (2011). A method to incorporate the effect of taxonomic uncertainty on multivariate analyses of ecological data. Ecography, 34: 94-102. http://dx.doi.org/10.1111/j.1600-0587.2009.05899.x.
pertables, adonis
data(Amazonia)
data(soils)
# Define a new index that includes the terms used in the \code{Amazonia} dataset to define
# undetermined taxa at different taxonomic levels
index.Amazon <- c(paste("sp.", rep(1:20), sep=""), "Indet.", "indet.")
# Generate a pertables object (i.e. a list of biological data tables simulated from taxonomic
# uncertainty)
if (FALSE) {
Amazonia100 <- pertables(Amazonia, index=index.Amazon, nsim=100)
# Assess the effects of taxonomic uncertainty on a PERMANOVA (i.e., adonis) test:
Amazonia.adonis <- adonis_pertables(Amazonia100 ~ Ca + K + Mg + Na, data=soils)
Amazonia.adonis
plot(Amazonia.adonis)
}
# Fast example for Rcheck
Amazonia4.p2 <- pertables.p2(Amazonia[1:50,], index=index.Amazon, nsim=4, ncl=2, iseed=4)
set.seed(2)
Amazonia.adonis <- adonis_pertables(Amazonia4.p2 ~ Ca + K + Mg + Na, data=soils)
Amazonia.adonis
plot(Amazonia.adonis)
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