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Challenges in identifying and interpreting organizational modules in morphology

Esteve-Altava, B


B Esteve-Altava


Form is a rich concept that agglutinates information about the proportions and topological arrangement of body parts. Modularity is readily measurable in both features, the variation of proportions (variational modules) and the organization of topology (organizational modules). The study of variational modularity and of organizational modularity faces similar challenges regarding the identification of meaningful modules and the validation of generative processes; however, most studies in morphology focus solely on variational modularity, while organizational modularity is much less understood. A possible cause for this bias is the successful development in the last twenty years of morphometrics, and specially geometric morphometrics, to study patters of variation. This contrasts with the lack of a similar mathematical framework to deal with patterns of organization. Recently, a new mathematical framework has been proposed to study the organization of gross anatomy using tools from Network Theory, so‐called Anatomical Network Analysis (AnNA). In this essay, I explore the potential use of this new framework—and the challenges it faces in identifying and validating biologically meaningful modules in morphological systems—by providing working examples of a complete analysis of modularity of the human skull and upper limb. Finally, I suggest further directions of research that may bridge the gap between variational and organizational modularity studies, and discuss how alternative modeling strategies of morphological systems using networks can benefit from each other.


Esteve-Altava, B. (2017). Challenges in identifying and interpreting organizational modules in morphology. Journal of Morphology, 278(7), 960-974.

Journal Article Type Article
Acceptance Date Apr 4, 2017
Publication Date May 2, 2017
Deposit Date May 6, 2017
Publicly Available Date May 29, 2018
Print ISSN 0362-2525
Publisher Wiley
Peer Reviewed Peer Reviewed
Volume 278
Issue 7
Pages 960-974
Public URL


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