
Hi -

This isn't really an R question (but the analysis is performed in  
R!). Anyway, I'm trying to compute pairwise distances between a set  
of sites, where the site data (habitat) consist of:

(1) Percent cover of various plant groups (eg "shrub", "tussock grass")

and

(2) several additional quantitative (non percentage) metrics, such as  
the volume of dead wood, the mean diameter of shrubs, and the  
"hardness" of the soil at each site.

I'm having a hard time deciding which distance metric is best for  
computing an overall pairwise distance between sites, given this  
mixture of datatypes. I have never seen proportional similarity  
metrics used for such data and am unsure whether they would be  
acceptable - although Bray-Curtis distances seem to accord well with  
my intuition about how I think the data are structured. Actually, I'm  
not familiar with any studies that have computed pairwise distances  
for such mixed data, so don't have much to go on.

Thanks for your help,
~Dan Rabosky





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