State of the Bay Report 2010-Final - Anchor Environmental

9.2.3 Data Analysis
The similarities or dissimilarities among the quadrats from the eight different study sites
were analyzed with multivariate analyses techniques employing the software package PRIMER 6.
These methods are useful for a graphical presentation of the results obtained from the typically large
data sets collected during ecological sampling. The principle aim of these techniques is to discern the
most conspicuous patterns in the community data. Comparisons between intertidal communities are
based on the extent to which they share particular species at similar levels of occurrence. Patterns in
the data are represented graphically through hierarchical clustering (dendrogram) and multidimensional
scaling (MDS) ordination techniques. The former produces a dendrogram in which
samples with the greatest similarity are fused into groups, and these are successively grouped into
clusters as the similarity criteria defining the groups are gradually reduced. MDS techniques
compliment hierarchical clustering methods by more accurately ‘mapping’ the sample groupings
two-dimensionally in such a way that the distances between samples represent their relative
similarities or dissimilarities.
Whether (a priori defined) groups of samples (e.g. sites, treatments, years) are statistically
different is analysed by means of the PERMANOVA routine, contained in the PERMANOVA+ for
PRIMER 6 software package. PERMANOVA is a routine for testing the simultaneous response of one
or more variables to one or more factors in an analysis of variance (ANOVA) experimental design on
the basis of any resemblance measure, using permutation methods (Anderson et al. 2008). In
essence, the routine performs a partitioning of the total sum of squares according to the specified
experimental design, including appropriate treatment of factors that are fixed or random, crossed or
nested, and all interaction terms. A distance-based pseudo-F statistic is calculated in a fashion that is
analogue to the construction of the F statistic for multi-factorial ANOVA models. P-values are
subsequently obtained using an appropriate permutation procedure for each term. Following the
main overall test, pair-wise comparisons are conducted. Significance level for the PERMANOVA
routine is p