On Sun, 2009-07-19 at 15:34 +0000, Alexandre F. Souza wrote:
> Hello All,
> 
>   Do anyone has ever performed a constrained NMDS with community data? I
> have read in McCune and Graces' Analysis of Ecological Communities that
> the theory of such analysis already exists (i.e., associating vectors of
> environmental variables to a NMDS ordination) but has seldon been used
> by ecologists. It would be a better alternative to CCA, which has
> stingent premises that ecological data does not match properly most of
> times.
> 
>   I suppose that this could be implemented in R, but I could not find it
> in Vegan or other packages.

If I understand the above, see ?vectorfit ?envfit and ?ordisurf in
vegan, to relate an a priori developed nMDS configuration to associated
covariates.

If you really meant a constrained nMDS, I'm not sure how one would go
about doing it. There are no axes to constrain, and the purpose of the
constraints in RDA/CCA is to express on the first n axes the variance
you can explain with the covariates available; this isn't an issue with
nMDS as you are expressly interested in a low dimensional representation
of the original dissimilarities.

More flexible versions of RDA/CCA include constrained analysis of
principal coordinates (capscale() in vegan) and you can use the kind of
transformation envisaged by Legendre and Gallagher 2001 Oecologia with
RDA.

Alternatively, for a more statistically-based solution, take a look at
the work of Thomas Yee and vector GLMs and GAMs, particularly the
quadratic reduced rank VGLMs or constrained additive ordination. This is
available in the VGAM package for R.

HTH

G

> 
>   Thanks in advance,
> 
>    Alexandre
> 
>   
> 
> Dr. Alexandre F. Souza 
> Programa de Pós-Graduação em Biologia: Diversidade e Manejo da Vida
> Silvestre
> Universidade do Vale do Rio dos Sinos (UNISINOS)
> Av. UNISINOS 950 - C.P. 275, São Leopoldo 93022-000, RS  - Brasil
> Telefone: (051)3590-8477 ramal 1263
> Skype: alexfadigas
> [email protected]
> http://www.unisinos.br/laboratorios/lecopop
> 
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