Dear morphometricians,

I have a basic question that some quick literature searches havent answered
yet, but which I believe will be answered quickly from the collective
knowledge here.

I wish to compare pairwise distances among specimens in PCA space derived
from a) a suite of linear measurements and b) a 3D landmark-based approach.
The goal is simply to ask whether one of the two approaches to describing
shape provides "higher resolution" (i.e., more discriminating power).
However, I dont think that raw (Euclidean or Mahalanobis) distances from
the separate PCAs are comparable, since they explain different amounts of
total variation.

Is there a way to scale the among-specimen distances from each so they are
comparable between the PCAs?
OR - is there a totally different (eg non-PCA-based) way of approaching
this simple question?

Thanks in advance,
Bryan

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