[R-sig-eco] Relating abundance and cover data

[Karen Kotschy]

Dear list

This seems like something I really should know by now, but I'm getting so 
confused, I'd really appreciate a little help!

I am trying to model the relationship between relative abundance (%) and 
relative cover (%) data for plant species. I want to know to 
what extent the 2 measures correlate, and to compare the extent of this 
correlation at different sites. Obviously, both sets of data are 
zero-inflated and highly skewed.

The "traditional" thing to do would be to log-transform both of them and 
use lm(). However, a recent paper (O'Hara & Kotze, 2010) argues that a 
much better approach is to use glm() and to specify Poisson or negative 
binomial models, rather than using transformations. This does make a lot 
of sense, I think!

I have tried using "quasipoisson" and "quasibinomial" families in glm(), 
but I am left with a number of questions: 

1) Should relative abundance and relative cover be treated as "count" 
data, given that the values are not actually integers but rather 
percentages?

2) Which parts of the output of glm(...family=quasipoisson(link=log)) do I 
use to evaluate the fit? Just residual deviance and the p value?

3) How do I plot the data so as to graphically represent the model? If I 
am using a log link should I use log axes for x and y?

Thanks so much for any help!
Karen

---
Karen Kotschy
Centre for Water in the Environment
University of the Witwatersrand, Johannesburg
Tel: +2711 717-6425

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