The promise of geometric morphometrics
Open Access
- 13 December 2002
- journal article
- review article
- Published by Wiley in American Journal of Physical Anthropology
- Vol. 119 (S35) , 63-91
- https://doi.org/10.1002/ajpa.10174
Abstract
Nontraditional or geometric morphometric methods have found wide application in the biological sciences, especially in anthropology, a field with a strong history of measurement of biological form. Controversy has arisen over which method is the “best” for quantifying the morphological difference between forms and for making proper statistical statements about the detected differences. This paper explains that many of these arguments are superfluous to the real issues that need to be understood by those wishing to apply morphometric methods to biological data. Validity, the ability of a method to find the correct answer, is rarely discussed and often ignored. We explain why demonstration of validity is a necessary step in the evaluation of methods used in morphometrics. Focusing specifically on landmark data, we discuss the concepts of size and shape, and reiterate that since no unique definition of size exists, shape can only be recognized with reference to a chosen surrogate for size. We explain why only a limited class of information related to the morphology of an object can be known when landmark data are used. This observation has genuine consequences, as certain morphometric methods are based on models that require specific assumptions, some of which exceed what can be known from landmark data. We show that orientation of an object with reference to other objects in a sample can never be known, because this information is not included in landmark data. Consequently, a descriptor of form difference that contains information on orientation is flawed because that information does not arise from evidence within the data, but instead is a product of a chosen orientation scheme. To illustrate these points, we apply superimposition, deformation, and linear distance‐based morphometric methods to the analysis of a simulated data set for which the true differences are known. This analysis demonstrates the relative efficacy of various methods to reveal the true difference between forms. Our discussion is intended to be fair, but it will be obvious to the reader that we favor a particular approach. Our bias comes from the realization that morphometric methods should operate with a definition of form and form difference consistent with the limited class of information that can be known from landmark data. Answers based on information that can be known from the data are of more use to biological inquiry than those based on unjustifiable assumptions. Yrbk Phys Anthropol 45:63–91, 2002.Keywords
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