Introduction
Theory, R functions & Examples
Section: Ordination analysis
varpart
(library vegan
) - variation partitioning (using RDA, CCA or db-RDA) among up to four matrices of environmental variables. First argument (Y
) is dependent variable, usually the matrix of species composition (the function calculates RDA, or, if chisquare = TRUE
, CCA), but could be also only a single variable (in that case it calculates linear regression) or distance matrix (applying db-RDA using the function capscale
). Further arguments (up to four) are (groups of) explanatory variables. The function uses either formula interface (with ~, see examples) or matrices. The interpretation should be based on adjusted R2, although raw R2 is also reported (for CCA, adjusted R2 is calculated by permutation method of Peres-Neto et al. 2006 and may slightly vary between re-analyses of the same data; the argument permutations
specifies the number of permutations used to calculate adjusted R2 in CCA).plot.varpart
(library vegan
) - draws Venn's diagram with fractions of explained variation. In default setting it doesn't show negative values of explained variation (argument cutoff = 0
). The function can use arguments of showvarparts
below, e.g. to add the labels for individual (groups of) variables (Xnames
), or colors of the fractions (bg
). Consult ?plot.varpart
for more details.showvarparts
(library vegan
) - draws schema of Venn's diagram with codes of individual fractions.