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State of the Bay Report 2011-Final.pdf - Anchor Environmental

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<strong>State</strong> <strong>of</strong> Saldanha <strong>Bay</strong> & Langebaan Lagoon <strong>2011</strong><br />

Intertidal invertebrates<br />

8.2.3 Data Analysis<br />

The similarities or dissimilarities among <strong>the</strong> quadrats from <strong>the</strong> eight different study sites are<br />

analyzed with multivariate analyses techniques employing <strong>the</strong> s<strong>of</strong>tware package PRIMER 6. These<br />

methods are useful for a graphical presentation <strong>of</strong> <strong>the</strong> results obtained from <strong>the</strong> typically large<br />

data sets collected during ecological sampling. The principle aim <strong>of</strong> <strong>the</strong>se techniques is to discern<br />

<strong>the</strong> most conspicuous patterns in <strong>the</strong> community data. Comparisons between intertidal<br />

communities are based on <strong>the</strong> extent to which <strong>the</strong>y share particular species at similar levels <strong>of</strong><br />

occurrence. Patterns in <strong>the</strong> data are represented graphically through hierarchical clustering<br />

(dendrogram) and multi-dimensional scaling (MDS) ordination techniques. The former produces a<br />

dendrogram in which samples with <strong>the</strong> greatest similarity are fused into groups, and <strong>the</strong>se are<br />

successively grouped into clusters as <strong>the</strong> similarity criteria defining <strong>the</strong> groups are gradually<br />

reduced. MDS techniques compliment hierarchical clustering methods by more accurately<br />

‘mapping’ <strong>the</strong> sample groupings two-dimensionally in such a way that <strong>the</strong> distances between<br />

samples represent <strong>the</strong>ir relative similarities or dissimilarities.<br />

Whe<strong>the</strong>r (a priori defined) groups <strong>of</strong> samples (e.g. sites, treatments, years) are statistically<br />

different is analysed by means <strong>of</strong> PERMANOVA. PERMANOVA is a routine for testing <strong>the</strong><br />

simultaneous response <strong>of</strong> one or more variables to one or more factors in an analysis <strong>of</strong> variance<br />

(ANOVA) experimental design on <strong>the</strong> basis <strong>of</strong> any resemblance measure, using permutation<br />

methods (Anderson et al. 2008). In essence, <strong>the</strong> routine performs a partitioning <strong>of</strong> <strong>the</strong> total sum<br />

<strong>of</strong> squares according to <strong>the</strong> specified experimental design, including appropriate treatment <strong>of</strong><br />

factors that are fixed or random, crossed or nested, and all interaction terms. A distance-based<br />

pseudo-F statistic is calculated in a fashion that is analogue to <strong>the</strong> construction <strong>of</strong> <strong>the</strong> F statistic<br />

for multi-factorial ANOVA models. P-values are subsequently obtained using an appropriate<br />

permutation procedure for each term. Following <strong>the</strong> main overall test, pair-wise comparisons are<br />

conducted. Significance level for <strong>the</strong> PERMANOVA routine is p

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