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It may sometimes be easier to use the sample numbers, here Select>Samples>•Sample numbers> 1,2,5,6,11,12,15,16, though this is more likely to be useful where such numerical lists are output in results (e.g. by the BEST routine, Section 13), and can be copied a...

Any of the options for selecting samples are also available for selecting variables, e.g. selecting by variable numbers or by levels of an indicator, the latter as seen in the example of the previous section, in which the Tasmanian copepods of ‘Undetermined ta...

There are, however, three other selection methods under Select>Variables that are specific to selecting species (or other taxon-type) variables, in which matrix entries are positive ‘amounts’ of that species (counts, biomass, area cover etc). The idea of the f...

Looking ahead to Section 5, when the active window is a (triangular) resemblance matrix, selection can take place just as for a (rectangular) datasheet, by Select>Highlighted or Select>Samples>(•Sample numbers) or (•Factor levels). Another option is provided i...

How the data are treated, prior to computation of a resemblance matrix (e.g. similarities), can have an important influence on the final analysis, and such decisions often depend on the practical context rather than any statistical considerations. For example,...

Several of the routines in PRIMER 7 also incorporate a check box for sending summary statistics used in that routine to a further worksheet. Here, this results in a second sheet (probably named Data4), which is just a single column of totals across prey specie...

Pre-treatment>Standardise can also be used to standardise the matrix on the variables axis, e.g. to ensure that each species is given equal weight in any ensuing similarity calculation by making their totals across samples all add to 100, with (Standardise•Var...

Transformation is usually applied to all the entries in an assemblage matrix of counts, biomass, % area cover etc, in order to downweight the contributions of quantitatively dominant species to the similarities calculated between samples (see Chapters 2 and 9 ...

A major new feature in PRIMER 7 is the large number of additional plotting routines, one of the conceptually simplest but most powerful being Shade Plots, which are simple visualisations of the data matrix, with darker (or different colour) shades in each cell...

Transformations may be appropriate for environmental variables too, though usually for a different reason (e.g. in order to justify using Euclidean distance as a dissimilarity measure on normalised variables). However, these are usually selective transformati...

Temporarily deselect the Distance (as in Section 3), and run Plots>Draftsman Plot on the other 9 variables; also Plots>Histogram Plot (a new plotting feature in PRIMER 7). The latter leads to an example of another new feature, a Multi-plot (see Section 7), in ...

Both the Draftsman and Histogram Plots show that several of the Ekofisk abiotic variables are highly right-skewed (tail to the right), and it would be wise, if we are to limit the distorting effects of outliers and normalise the data to a desired common measur...

It is typical of a suite of physico-chemical variables (or biomarkers, water-quality indices etc) that they are not on comparable measurement scales, unlike assemblage abundances. All multivariate analysis methods are based on resemblances between samples that...

When variables are on different measurement scales, there is little viable alternative to normalising each variable (as above) thus equalising, in effect, their contributions to the multivariate analysis. When variables are (ostensibly) on the same scale, e.g...

Sediment copepod assemblages (and other fauna) from five creeks of the Fal estuary, SW England, were analysed by Somerfield PJ, Gee JM, Warwick RM 1994, Mar Ecol Prog Ser 105: 79-88. The sediments of this estuary are characterised by high and varying concentr...

There are other cases in which variables (species) might need prior weighting, e.g. when a species is known to be often misidentified, its contribution (and those of the species it is mistaken for) can be reduced by multiplying the entries in the two species t...

Another example might be in attempting to reconcile two different types of data in the same matrix, e.g. counts of motile organisms and area cover of colonial species. These cases can be problematic. One solution is to use a similarity measure such as the Gowe...

Pre-treatment>Variability Weighting is a new option in PRIMER 7, which bears similarities to the idea of Dispersion Weighting. This was introduced by Hallett CS, Valesini FJ, Clarke KR 2012, Ecol Indicat 19: 240-252 in a context where the variables were ‘healt...

The directory C:\Examples v7\N Sea biomarkers holds a data sheet N Sea flounder biomarkers(.pri) of biochemical and histological biomarkers measured concurrently on flounder caught at 5 North Sea sites (labelled S3, S5, S6, S7 and S9), running on a putative co...

The remaining option on the Pre-treatment menu is Cumulate samples, which successively adds up the entries across variables, separately for each sample. It is only appropriate when all variables share a common measurement scale, and when the order in which the...