Karen, I suggest you step back and ask two questions: 1) what are you trying to do? (i.e. what is the real goal?) 2) what do you do it to? (i.e. what's the appropriate data?)
Do you want to construct a model or estimate correlations? Your detailed questions suggest that your real interest is the correlations. If so, you don't need an explicit model. Just estimate the correlation. You get to choose how to define correlation. The four most common choices are Pearson correlation on the original scale, Pearson correlation on some transformed scale, Spearman (rank) correlation, or Kendall's (tau) correlation.
I presume the 0's arise from species that are absent from a site, i.e. a (0,0) pair of (abundance, cover). Is it appropriate to include these? You could define correlation in three ways: 1) conditional on a species present at a site. That eliminates all the (0,0). 2) conditional on a species present in the regional species pool. This MAY be the same as conditional on a species present in your data set. You clearly have the second. The BIG issue is whether 'in your data' is an adequate representation of 'in the regional species pool'. 3) conditional on all extant species in your taxonomic group. That adds additional (0,0) pairs for all species present in other regions.
If you really want to model the relationship, this issue is still important. Best wishes, Philip Dixon _______________________________________________ R-sig-ecology mailing list R-sig-ecology@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-ecology
