Similarity Percentage analysis (SIMPER) for measure species indicator value?

You can overlay a biplot of species correlations with the CAP axes. If you are using the PERMANOVA+ software, you can choose to use Spearman or Pearson correlations and set the level of correlation (default is 0.4). Alternatively you can manually choose which species to display. A word of warning: CAP will give you statistical correlations of species with the canonical axes, whether or not that is biologically meaningful. In other words you can obtain very strong correlations from species that are very rare but occur in only one treatment (for example). This may be meaningful or may not. As a rule of thumb, you should independently check the frequency of occurrence of species - I tend to discount correlations of species that occur in fewer than 15% of samples, or at least look closely at them to be sure the correlations are not merely statistical artefacts.

MDS is somewhat different. It is an unconstrained ordination technique that places samples in multivariate space in the most parsimonious arrangement (relative to each other). Unlike CAP, there are no a priori hypotheses. CAP ordinations come in handy when there is more going on in higher dimensions than can be accurately placed on a 2D MDS plot (in general when the stress value exceeds 0.2). Ideally you should do both if using CAP - plot an unconstrained MDS or PCO ordination too to see the "real" variation among samples.

All that said, if seeking to look at a species x samples matrix versus some suite of environmental variables, you should maybe look at a distance -based multiple regression technique like dbRDA. Again you can get biplots of species correlations with the RDA axes, but it also can run a sequential analysis that drops out the colinear predictor variables - very handy.

Seriation with replication is described in Somerfield, P. J., Clarke K. R., Olsgard, F. (2002) A comparison of the power of categorical and correlational tests applied to community ecology data from gradient studies. J. Anim. Ecol. 71:581-593.

The original question, concerning an alleged problem with SIMPER, is based on a flawed understanding. There is no issue with SIMPER being sensitive to species abundance. The issue is really about using appropriate combinations of resemblance measure and transformation to reflect the aspects of community variation you are interested in. However, SIMPER is about contributions to similarities among groups of samples, and it looks to me like you are more interested in correlations.

A new method of looking at variables which may be relevant is Somerfield, P. J., Clarke, K. R. (2013) Inverse analysis in non-parametric multivariate analyses: distinguishing of groups of associated species which covary coherently across samples. J. Exp. Mar. Biol. Ecol. 449: 261–273. DOI:10.1016/j.jembe.2013.10.002.

Souce: NovoPro    2018-04-03