Morphometrics maven: morphometricians must and can do better

booksteinA grizzled morphometrician casts a cold, gleeful eye at his field, and urges himself and his fellow morphometricians to do better. Morphometrics is the the continuing attempt to carefully measure and compare shapes and sizes. This morphometrician’s happy diatribe is in the form of a long, new paper:

The Inappropriate Symmetries of Multivariate Statistical Analysis in Geometric Morphometrics,” by Fred L. Bookstein (pictured here], Evolutionary Biology, epub 2016, pp 1-37. The author, who is at the University of Washington and the University of Vienna, writes, in densely grand language:

“In today’s geometric morphometrics the commonest multivariate statistical procedures, such as principal component analysis or regressions of Procrustes shape coordinates on Centroid Size, embody a tacit roster of symmetries—axioms concerning the homogeneity of the multiple spatial domains or descriptor vectors involved—that do not correspond to actual biological fact. These techniques are hence inappropriate for any application regarding which we have a-priori biological knowledge to the contrary (e.g., genetic/morphogenetic processes common to multiple landmarks, the range of normal in anatomy atlases, the consequences of growth or function for form). But nearly every morphometric investigation is motivated by prior insights of this sort. We therefore need new tools that explicitly incorporate these elements of knowledge, should they be quantitative, to break the symmetries of the classic morphometric approaches. Some of these are already available in our literature but deserve to be known more widely…”

Here’s a bit of flavored detail from the paper:

bookstein-figure