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7.9 Example: Tasmanian meiofauna
Another clear generalisation is to a 2-way rather than 1-way layout, illustrated by the 16 meiofa...
7.8 Species contributions to sample (dis)similarities – SIMPER
Dissimilarity breakdown between groups The fundamental information on the multivariate structure ...
7.7 Example: Ekofisk oil-field macrofauna
The 39 sites sampled for benthic infauna at different distances from an oil-field in the N Sea we...
7.6 Example: Garroch Head macrofauna
An example where the biotic sample axis could have sensibly been ordered according to an a prior...
7.5 Example: Bristol Channel zooplankton
This example, last seen in Chapter 3, consists of 24 (seasonally-averaged) zooplankton net sample...
7.4 Shade plots
An alternative to line plots, and a technique that can often be even more useful, in terms of the...
7.3 Example: Amoco-Cadiz oil spill
A second example of deriving sets of coherent species curves, this time temporal rather than spat...
7.2 Type 2 and type 3 SIMPROF tests
describe in full detail a range of useful SIMPROF tests, which they classify as Types 1, 2 and 3...
7.1 Species clustering
Chapter 2 (page 2.4) describes how the original data matrix can be used to define similarities be...
3.3 Mechanics of PCO
To construct axes that maximise fitted variation (or minimise residual variation) in the cloud of...
0.5 Using this manual
Typographic conventions The typographic conventions for this manual follow those used by for PRI...
0.2 Contact details and installation of the PERMANOVA+ software
Getting in touch with us PERMANOVA+ for PRIMER was produced as a collaborative effort between Pro...
A4 Index to data sets used in examples
Below is an index to the data sets used in examples, listed in order of appearance in the text. W...
5.1 General description
Key references Method: , CAP is a routine for performing canonical analysis of principal co...
A2 References
Akaike (1973) Akaike H. 1973. ‘Information theory as an extension of the maximum l...
5.16 (Hunting spiders)
A study by explored the relationships between two sets of variables: the abundances of hunting s...
5.13 Sphericising variables
It was previously stated that CAP effectively “sphericises” the data clouds as part of the proces...
5.12 Canonical correlation: multiple X’s
In some cases, interest lies in finding axes through the cloud of points so as to maximise correl...
5.11 Canonical correlation: single gradient (Fal estuary biota)
So far, the focus has been on hypotheses concerning groups and the use of CAP for discriminant an...
5.10 Adding new samples
A new utility of the windows-based version of the CAP routine in PERMANOVA+ is the ability to pla...