Re: [R] Abundance data ordination in R

From: José Rafael Ferrer Paris <>
Date: Sun 01 Apr 2007 - 18:40:13 GMT

There are many ways to do this, really. For example if you use constrained (~ canonical) correspondence analysis the distance measure between sites is Chi-square and absences are not informative to the analysis. Or you can use an ecological distance measure (similarity indices like Soerensen, Bray-Curtis, Jaccard, and others) and perform principal coordinates (=multidimensional scaling), etc. Read the documentation and tutorials for the packages vegan, ade4 and labdsv.

You might start your search at the page of Jari Oksanen: or the one from Dave Roberts . The vegan tutorial was useful for me to learn to use vegan: If you need more indeep mathemathical details, you should take a look at Daniel Chessels site:  There are plenty of pdfs available for download (however, some are suited for beginners, others require more background knowledge) . Be warned: there is a large variety of techniques for multivariate analysis with different properties and weaknesses, sometimes the most popular analysis are not the most appropriate. Be sure of what you want and what you are doing before you perform the analysis, the interpretation will depend on the techniques applied.

I personally find ade4 implements many different techniques but is poorly documented and some functionalities are somehow "hidden", while vegan provides more information about the functions and is perfect for getting started. I haven't used labdsv yet.  

hope this help


El dom, 01-04-2007 a las 09:20 -0700, Milton Cezar Ribeiro escribió:
> Dear R-gurus
> I have a data.frame with abundance data for species and sites which looks like:
> mydf<-data.frame(
> sp1=sample(0:10,5,replace=T),
> sp2=sample(0:20,5,replace=T),
> sp3=sample(0:4,5,replace=T),
> sp4=sample(0:2,5,replace=T))
> rownames(mydf)<-paste("sites",1:5,sep="")
> I would like make an ordination analysis of these data and my worries is about the "zeros" (absence of species) into the matrix. Up to I read (Gotelli - A primir of ecological statistics, 2004), when I have abundance data I cant compute Euclidian Distances because the zeros have the meaning of absence of the species and not as zero counting. Gotelli suggests one make "principal coordinates analysis". I would like to here from you what you think about and what is the best packages and functions to I compute my distance matrices and do my ordination analysis. Can I considere zero as NA on my data.frame? Is there a good PDF book available about Multivariate Analysis for abundance data available on the web?
> Kind regards
> Miltinho
> Brazil
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> and provide commented, minimal, self-contained, reproducible code. mailing list PLEASE do read the posting guide and provide commented, minimal, self-contained, reproducible code. Received on Mon Apr 02 04:47:41 2007

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