I am analyzing a data set concerning intertidal communities. The data are percent cover (of seaweed, barnacles, mussels, etc) in quadrats. I am used to thinking about correspondence analysis (CA) in terms of species counts, and principle component analysis (PCA) as something more useful for linear environmental (not species) trends. I haven't really had any luck figuring out if PCA or CA would be a better fit for percent cover (can't find any papers), and I'm not even sure how something that is capped up to 100% would be distributed?
I am familiar with the rough guideline that if the length of the first detrended correspondence analysis (DCA) axis is greater than 2, then you can safely assume that CA should be used. The length of DCA axis 1 was 2.17, which I don't find helpful.