[R-sig-eco] Fwd: how to calculate "axis variance" in metaMDS, pakage vegan?

[Gavin Simpson]

On Tue, 2009-12-08 at 17:09 +0100, Carsten Dormann wrote:
> Dear disputants.

I'm not sure anyone is disagreeing here?

> 
> If this is a poll, I'd like to second Gabriel's email, with respect to 
> his comments on the usefulness of the R-sig-ecology mailing list AND his 
> comments on (n)MDS + adonis AND his point on slowly developing the 
> standard of your research field, rather than immediately dwarfing 
> publication chances by using more "appropriate" but revolutionising 
> methods in the field.
> My own experiences are that 1. reviewers become ever more statistically 
> literate (so I guess one should have no problems in moving from a PCA to 
> a PCoA/MDS); and 2. ecological patterns are relatively robust to the 
> ordination method (so not much is lost by using more, well, traditional 
> approaches).

My critique was aimed at the switch to *DCA* when nMDS wasn't working as
the OP thought, because that was what the OP had seen used a lot in
publications in his field. That's all.

DCA has it's uses (if you must use CA but have a single strong gradient
in your data so an arch crops up), but it is my experience that many
people jump straight to using DCA without doing CA and without really
understanding the monstrous things it is doing to their data to get rid
of the arch. If there isn't an arch (arising from the problem with CA)
what DCA does to axis 2 scores etc would make me question using it
blindly.

nMDS is an established method in ecology so I wouldn't expect any
problems with using that.

Ciao,

G

> 
> Cheers,
> 
> Carsten
> 
> gabriel singer wrote:
> > Hi Gian and others,
> >
> > I think we better stop worrying about subjective interpretations of 
> > emotional backgrounds of what in other aspects are absolutely helpful 
> > discussion threads... I guess part of the challenge on this mailing 
> > list is to span the whole range of expertise with useful 
> > discussion/output/help for everyone, be it a student or an expert. I 
> > found this mailing list very helpful many times for my own questions, 
> > but also very informative when just following the threads on other 
> > questions...
> >
> > Gian, in my opinion, 2 dimensions are absolutely ok, especially if 
> > they do visualize an (obvious) effect in your study. In other words, 
> > if 2 dimensions show you an effect of "Host" but not of "Area", the 
> > effect is obviously strong enough. Then I would not worry about stress 
> > too much. However, there may still be an effect of "Area", maybe 
> > visible in more dimensions, but it´s obviously of minor importance.
> >
> > I personally like a combination of NMDS with the permutational MANOVA 
> > approach (by Marti Anderson) implemented in the function adonis() in 
> > vegan. You can use the same dissimilarity measure (Bray-Curtis) used 
> > for the NMDS and can test the "Area" vs. the "Host" effect on parasite 
> > (was it?) composition. I think that could be a very useful complement 
> > to an NMDS-derived ordination plot and then you may also regard 
> > high-stress "representations" (and that´s what all the low-dimensional 
> > ordination plots really ARE!) in a different light.
> >
> > Complementations like the permanova are in my opinion better than 
> > trying the full spectrum of ordination methods until finally some kind 
> > of pattern gets uncovered (comes quite close to the much too often 
> > encountered data-fishing expeditions....). And though copying analysis 
> > strategies is probably not quite like throwing yourself in front of a 
> > bus, there is some benefit in using what people working in a specific 
> > field regard their "standard" methods (wait for the reviews to 
> > discover this). In any case, a responsible choice for a type of 
> > analysis is oriented along the study design and the data at hand.
> >
> > cheers, gabriel
> >
> 
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