I am looking at a zooplankton community assemblages using hierarchical cluster analysis, indicator species analysis, and non-metric multidimensional scaling based on Bray-Curtis dissimilarities. My input is a species abundance (log10(n+0.01)+1 transformed) by sample matrix.
My question relates to the input for the hierarchical cluster analysis. Can I use the Bray-Curtis dissimilarity output for my hierarchical cluster analysis with Ward’s (ward.D2) as the method or does the fact that Bray-Curtis is non Euclidean violate a list of assumptions I haven’t gotten my head wrapped around yet?
Using Bray-Curtis with the HCA and ISV produces results that make quite a bit of ecological sense, but I want to make sure I haven't tricked myself into thinking I know something I don't actually know (a la Pirsig).
Here is my R code.
# Get dissimilarity matrix from vegan's Bray-Curtis d <- vegdist(pwslog) # Vegan cluster analysis hpws <- hclust(d, method = "ward.D2") # Define 6 groups from the HCA groups.6 <- cutree(hpws, 6) # Run indicspecies' Indicator Species Analysis and look at results indval = multipatt(pwslog, (cutree(hpws, 6)), duleg = TRUE, control = how(nperm = 999)) summary(indval)
Thank you for your time and suggestions.