Theory, Examples & Exercises
rda- this function calculates RDA if matrix of environmental variables is supplied (if not, it calculates PCA). Two types of syntax are available:
RDA = rda (Y, X, W), where
Yis the response matrix (species composition),
Xis the explanatory matrix (environmental factors) and
Wis the matrix of covariables
RDA = rda (Y ~ var1 + factorA + var2*var3 + Condition (var4), data = XW)- as explanatory are used: quantitative variable
var1, categorical variable
factorA, interaction term between
var4is used as covariable and hence partialled out.
cca- this function calculates CCA if matrix of environmental variables is supplied (if not, it calculates CA).
RsquareAdj- in case of CCA, it extracts only the value of R2, while values of adjusted R2 are not available (these need to be calculated by permutations and it is not available in R yet).
anova.cca- tests the significance of the variation in species composition explained by explanatory variables, using Monte Carlo permutation test.