Functional groups of communities
We calculated fuzzy-weighted species composition to reflect the
functional relatedness among communities (Pillar et al. 2009;
Duarte et al. 2016), using the matrix.x function of
package SYNCSA (Debastiani & Pillar 2012). For that we considered only
the effect traits, thus, not including the life forms. Next, based on
Euclidean distances between plots, we submitted the fuzzy-weighted
species composition to cluster analysis using Ward’s method. For the
derived classifications up to five functional groups of plots, we tested
group partition sharpness by using the bootstrap resampling procedure
(Pillar 1999). Further, for a synthetic view of the functional patterns
across communities we submitted the fuzzy-weighted community composition
matrix to covariance-based Principal Components Analysis (PCA) and
tested the significance of the ordination axes (Pillar 1999). For these
analyses we used the functions Cluster and Ordination in
MULTIV software (available at http://ecoqua.ecologia.ufrgs.br).