Abstract

Geometric morphometrics (GM) is a powerful analytical approach for evaluating phenotypic variation relevant to taxonomy and systematics, and as with any statistical methodology, requires adherence to fundamental assumptions for inferences to be strictly valid. An important consideration for GM is how landmark configurations, which represent sets of anatomical loci for evaluating shape variation through Cartesian coordinates, relate to underlying homology (Zelditch et al. 1995; Polly 2008). Perhaps more so than with traditional morphometrics, anatomical homology is a crucial assumption for GM because of the mathematical and biological interpretations associated with shape change depicted by deformation grids, such as the thin plate spline (Klingenberg 2008; Zelditch et al. 2012). GM approaches are often used to analyze shapes or outlines of structures, which are not necessarily related to common ancestry, and in this respect GM approaches that use linear semi-landmarks and related methods are particularly amenable to evaluating primary homology, or raw similarity between structures (De Pinna 1991; Palci Lee 2019). This relaxed interpretation of homology that focuses more on recognizable and repeatable landmarks is defensible so long as authors are clear regarding the purpose of the analyses and in defining their landmark configurations (Palci Lee 2019). Secondary homology, or similarity due to common ancestry, can also be represented with GM methods and is often assumed to be reflected in fixed Type 1 (juxtaposition of tissues) or Type 2 (self-evident geometry) landmarks (Bookstein 1991).

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