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#### 5.9 Example: Okura estuary macrofauna

describe macrofauna samples from the Okura estuary {O}, on the northern fringes of urban Aucklan...

#### 5.8 Further nMDS/mMDS developments

Higher dimensional solutions MDS solutions can be sought in higher dimensions and we noted previo...

#### 5.7 MDS strengths and weaknesses

MDS strengths MDS is simple in concept. The numerical algorithm is undeniably complex, but it ...

#### 5.6 Example: Amoco-Cadiz oil spill, Morlaix

Benthic macrofaunal abundances of 251 species were sampled by at 21 times between April 1977 and ...

#### 5.5 Example: Celtic Sea zooplankton

In situations where the samples are strongly grouped, as in Figs. 5.4 and 5.5, both clustering an...

#### 5.4 EXAMPLE: Dosing experiment, Solbergstrand

The nematode abundance data from the dosing experiment {D} at the GEEP Oslo Workshop was previous...

#### 5.3 Diagnostics: Adequacy of MDS representation

Is the stress value small? By definition, stress reduces with increasing dimensionality of the ...

#### 5.2 Non-metric multidimensional scaling (MDS)

The method of non-metric MDS was introduced by and , for application to problems in psychology; ...

#### 5.1 Other ordination methods

Principal Co-ordinates Analysis The two main weaknesses of PCA, identified at the end of Chapter ...

#### 4.5 Example: Dosing experiment, Solbergstrand mesocosm

An example of this final point for a real data set can be seen in Fig. 4.2. This is of nematode ...

#### 4.4 PCA for environmental data

The above example makes it clear that PCA is an unsatisfactory ordination method for biological d...

#### 4.3 Example: Garroch Head macrofauna

Fig. 4.1 shows the result of applying PCA to square-root transformed macrofaunal biomass data fro...

#### 4.2 Principal components analysis

The starting point for PCA is the original data matrix rather than a derived similarity matrix (t...

#### 4.1 Ordinations

An ordination is a map of the samples, usually in two or three dimensions, in which the placement...

#### 3.7 k-R clustering (non-hierarchical)

Another major class of clustering techniques is non-hierarchical, referred to above as flat clust...

#### 3.6 Binary divisive clustering

All discussion so far has been in terms of hierarchical agglomerative clustering, in which sample...

#### 3.5 Similarity profiles (SIMPROF)

Given the form of the dendrogram in Fig. 3.3, with high similarities in apparently tightly define...

#### 3.4 Recommendations

Hierarchical clustering with group-average linking, based on sample similarities or dissimilari...

#### 3.3 Example: Bristol Channel zooplankton

perform hierarchical cluster analyses of zooplankton samples, collected by double oblique net ha...

#### 3.2 Hierarchical agglomerative clustering

The most commonly used clustering techniques are the hierarchical agglomerative methods. These u...