[R-sig-eco] [R] reception of (Vegan) envfit analysis by manuscript reviewers
Gavin Simpson
gavin.simpson at ucl.ac.uk
Thu May 10 13:50:08 CEST 2012
On Thu, 2012-05-10 at 13:17 +0200, Alan Haynes wrote:
> Hi all,
>
> Im using envfit with some decomposition data currently but with a PCA
> result (via vegan:::rda()). Is envfit still valid for PCA results? I
> guess it doesnt make so very much difference, just the interpretation
> is slightly different.
> Or am I barking up the wrong tree by using this approach?
It is perfectly valid and is introduced in Jongman et al alongside PCA
and CA. We (well Jari) wouldn't have written a method for objects of
class "cca" if it wasn't appropriate.
I suggest you look at ordisurf() though; in most of the projects I have
been involved in, the linearity assumption of envfit() is questionable.
If you want a bit more info on what ordisurf() is doing see my blog post
on the function: http://wp.me/pZRQ9-1x
HTH
G
> Cheers,
>
> Alan
>
> --------------------------------------------------
> Email: aghaynes at gmail.com
> Mobile: +41794385586
> Skype: aghaynes
>
>
> On 10 May 2012 12:53, Gavin Simpson <gavin.simpson at ucl.ac.uk> wrote:
> I've removed R-Help from this now...
>
> On Thu, 2012-05-10 at 10:13 +0000, Jari Oksanen wrote:
> > On 10/05/2012, at 11:45 AM, Gavin Simpson wrote:
>
> <snip />
> > > As you provide little or no context I'll explain what
> envfit() does etc.
> > >
> > > The idea goes back a long way (!) and is in my 1995
> edition of Jongman
> > > et al Data Analysis in Community and Landscape Ecology
> (Cambridge
> > > University Press) though most likely was in 1987 version
> too. See
> > > Section 5.4 of the Ordination chapter by Ter Braak in that
> book.
> > >
> > > The idea is to find the direction (in the k-dimensional
> ordination
> > > space) that has maximal correlation with an external
> variable.
> >
> >
> > Hello,
>
>
> <snip />
>
> > Then about Bray-Curtis. The referee may be correct when
> writing that
> > the fitted vectors are not directly related to Bray-Curtis.
> You fit
> > the vectors to the NMDS ordination, and that is a non-linear
> mapping
> > from Bray-Curtis to the metric ordination space. There are
> two points
> > here: non-linearity and stress. Because of these, it is not
> strictly
> > about B-C. Of course, the referee is wrong when writing
> about NMDS
> > axes: the fitted vector has nothing to do with axes (unless
> you rotate
> > your axis parallel to the fitted vector which you can do).
> The NMDS is
> > based on Bray-Curtis, but it is not the same, and the vector
> fitting
> > is based on NMDS. So why not write that is about NMDS? Why
> to insist
> > on Bray-Curtis which is only in the background?
>
>
> Right, agreed. The analysis is one step removed from the B-C
> but the
> point of doing the nMDS was to find a low-d mapping of these
> B-C
> distances so in the sense that *if* the mapping is a good one
> then we
> can talk about correlations between "distances" between sites
> and the
> environmental variables. Whilst it might be strictly more
> correct to
> talk about this from the point of view of the nMDS the
> implication is
> that for significant envfit()s there is a significant linear
> correlation
> between the environmental variable(s) and the approximate
> ranked
> distances between samples.
>
> I mean, if all we talk about is the nMDS who cares? it is the
> implications of this for the system under study that are of
> interest.
>
> That said, B-C is just one of many ways to think of distance
> so to my
> mind I wouldn't even talk about the B-C distance either; the
> interest is
> in differences between sites/samples. The relevance of B-C or
> some other
> coefficient only comes in when considering if they are a good
> descriptor
> of the "distance" between samples for the variables you are
> considering.
>
> Cheers,
>
> G
>
> > Cheers, Jari Oksanen
> >
>
> --
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> Dr. Gavin Simpson [t] +44 (0)20 7679 0522
> ECRC, UCL Geography, [f] +44 (0)20 7679 0565
> Pearson Building, [e]
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Dr. Gavin Simpson [t] +44 (0)20 7679 0522
ECRC, UCL Geography, [f] +44 (0)20 7679 0565
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