Search Results

Anderson MJ, Ellingsen KE, McArdle BH 2006, Ecol Lett 9: 683-693 used Czekanowski’s mean character difference (above) as their preferred distance measure after a specific transformation of the original counts, advocated for its interpretable properties, namely...

L&L also assign $D_{14}$ to Bray-Curtis dissimilarity, the complement of $S_{17}$, defined earlier. This is also provided in the Dissimilarity list since it is (very occasionally) useful to specify a dissimilarity rather than its complementary similarity – tho...

In addition to Bray-Curtis $S_{17}$, and its zero-adjusted modification, PRIMER 7 also calculates: $$ S_{15} = 100 \frac{1}{p} \sum_i \left[ 1 - \frac{ \left| y_{i1} - y_{i2} \right| }{ R_i} \right] \text{, where } R_i=\max_j \left\{ y_{ij} \right\} - \min_j ...

There are numerous similarity measures defined for simple species lists, i.e. when the data consist only of presence (1) or absence (0) of each species in each sample. Any similarity defined between samples 1 and 2 must then be a combination of only four numbe...

It is instructive to draw the other links between quantitative coefficients and the presence/absence measures they reduce to, when calculating them on a P/A matrix. Pure distance measures such as $D_1$, $D_6$, $D_7$ and $D_{10}$, which are not averaged in some...

Returning to the quantitative resemblance coefficients in the •Others list, five further measures given under the ✓Distance/dissimilarity heading are (loosely) based on likelihood-ratio tests. All are motivated by the (usually unrealistic) model in which the i...

Another useful application of multivariate methods was touched on at the end of Section 4, namely the analysis of structured sets of curves or (pseudo-)frequency distributions, generically referred to as sample profiles. These include particle- or body-size an...

An example of a particle-size analysis (PSA) matrix has already been seen for Danish sediments at the end of Section 4, for which the histogram was smoothed by cumulating the size-classes. Here we examine instead an already smooth frequency distribution from C...

A later section (15) discusses univariate diversity indices that can be computed from each sample, including biodiversity measures that are based on the relatedness of the species making up a simple species list (P/A data), see Chapter 17 of CiMC. Though the s...

This concept of taxonomic distinctness can be carried over from a diversity index to a dissimilarity coefficient. Two measures are given under Analyse>Resemblance>(Measure•Other: ✓Taxonomic P/A). Both are presence/absence measures only, indicated by the plus s...

Assemblage data from 93 groundfish species, those that could be reliably sampled and identified in beam-trawl surveys by research vessels from several countries surrounding NW European shelf waters, were analysed by Rogers SI, Clarke KR, Reynolds JD 1999, J An...

Note the alternative means of supplying the variable information, to these dissimilarity measures and the biodiversity indices of Section 15, which is now available in PRIMER 7. In the Variable Relationship dialog box, Type•Resemblance>Details now requires spe...

The introduction above of the concept of ‘distances’ among species raises the issue of how best to compute species similarities – or more generally variable associations – taking the menu option of Analyse>Resemblance>(Analyse between•Variables). Several signi...

One context in which resemblances between variables is often of primary interest is in dealing with environmental variables, biomarkers, morphology etc. Concepts of ignoring joint absences do not apply – in fact zero no longer necessarily means absence (e.g. $...

Use of a correlation matrix between all pairs of variables as input to a multivariate ordination (say), in which points denote variables rather than samples (so that highly correlated variables are placed close together), either requires one of the absolute co...

Returning to the main purpose of resemblance measures, to describe similarity among samples, an important new feature in PRIMER 7, not offered in earlier versions, is that resemblance measures will now be calculated in the presence of missing cells (identified...

File>Save Resem As will save a resemblance matrix in internal binary PRIMER v7 (*.sid) format, though the previous v6 and v5 binary formats (also *.sid) are other options – as is the early DOS text format (*.sim) – all likely to be of limited utility now. More...

PRIMER 7 now carries out a wider range of clustering methods than previously: a) hierarchical agglomerative clustering using one of four linkage methods – single, complete, group average (UPGMA) and flexible beta (a standard WPGMA extension); b) hierarchical (...

All of the clustering methods are able to exploit ‘similarity profile’ (SIMPROF) permutation tests, e.g. for stopping rules for divisive methods or choice of number of groups k in a ‘flat’ clustering. SIMPROF test sequences look for statistically significant e...

The dendrogram itself is rapidly calculated, at least for the agglomerative methods, since no search procedure is involved, and it can thus be constructed for very large numbers of samples – but the SIMPROF routine is highly compute-intensive, given the typica...