pca or nmds (with which normalization and distance ) for abundance data ?
On Thu, 2012-12-13 at 14:03 -0600, Stephen Sefick wrote:
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My aim was to study how the distribution of species is linked with environmental data. Firstly, I did a PCA (with vegan library), using a Hellinger transformation, with commands like this : acp1<-rda(decostand(myDataSpec[,c(25:62)], "hellinger"))
Is the Hellinger transform done on relative proportions?
The transformation includes division by by the row sum and hence conversion to proportions. As such it can be applied to count data or relative abundance data; with the latter the division by row sum will have no effect and then the transformation collapses to a simple square root transformation of the proportional abundance data. This is one of the reasons for the apparent contradictions over the utility of the chord distance in ecological and palaeoecological disciplines. In the latter we commonly use proportional data whilst count abundances are common in the former. Directly applying the chord distance to count abundances carries with it the baggage of the Euclidean distance (squared differences emphasise the big things). But chord distance applied to proportional data *is* the Hellinger distance and hence palaeoecologists have found the chord distance a useful dissimilarity coefficients in their field. <snip />
a) Which ordination method would be better for my data : PCA knowing that the represented inertia is 35.62% or NMDS with a stress value about 0.22?
My opinion is PCA on hellinger transformed relative proportions "means" more than an NMDS
?? NMDS with Hellinger distances could optimise a k-D PCA with Hellinger transform. Given that NMDS essentially subsumes PCA I'm not sure what you are getting at. G
b) If NMDS is more adapted which one is the better? with Hellinger normalization and Bray-Curtis distance, or with the normalization recommended by Legendre and Legendre and Kulcynski distance ?
I sounds like the normalization you are referring to is relative proportion which is si/sum(s); s is a vector of taxon at a site.
c) Is there other method to apply? I?m going to try co-inertia with ade4 package
I am reading about co-inertia analysis now as it may be useful for some of the things that I am planning on doing. This method looks promising. You are going to have to decide on what type of ordination to use with COIA... HTH, Stephen
Thanks in advance. Cheers. Claire Della Vedova [[alternative HTML version deleted]]
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