© 2007 Society of Systematic Biologists
The Conceptual and Statistical Relationship between Modularity and Morphological Integration
1 Department of Anthropology, University of Vienna Althanstrasse 14, A-1091, Vienna, Austria E-mail: philipp.mitteroecker{at}univie.ac.at
2 Konrad Lorenz Institute for Evolution and Cognition Research Adolf Lorenz Gasse 2, A-3422, Altenberg, Austria
3 Department of Statistics, University of Washington Padelford B-207, Seattle, WA, 98195-4322, USA
Edited by Norman MacLead
 |
Abstract |
|---|
The modular variation of organismal form during evolution or development can be viewed as the result of dissociated local developmental processes. Whereas studies of modularity often are experimental, morphological integration is a more descriptive concept applying to groups of correlated phenotypic characters. Using simple path models, this paper shows that the classic underlying assumption of modularity (high correlations within modules, lower correlations between modules) is met only when local developmental factors have high effects on the traits relative to all factors' variations of effect (i.e., allometry). Accordingly, many classic approaches to morphological integration are meaningful only when local as well as common growth factors are nearly isometric. We show that morphometric modules might instead be defined more generally as sets of variables with non-zero within-module covariances, even when the covariances due to common factors have been removed, so that the residual between-module covariances are all near zero. Although it is still inherently unreliable to identify modules from phenotypic covariances in nonexperimental data, patterns of integration can sometimes be estimated based on prior identification of the modules themselves. We outline a simple approach for this case using Wright-style factor analysis and demonstrate the relation of its algebra to the more familiar approach via partial least squares.
Keywords: Allometry; correlation pleiades; dissociation; factor analysis; morphometrics; partial least squares; path models
Received December 10, 2006; Revised March 19, 2007; Accepted August 2, 2007
CiteULike 
Connotea 
Del.icio.us What's this?
This article has been cited by other articles:
|
|
 |
|
  P. Mitteroecker and F. L. Bookstein Examining modularity via partial correlations: A rejoinder to a comment by Paul Magwene Syst Biol, July 17, 2009; (2009) syp040v1. [Full Text] [PDF]
|
|
|
|
|
|
P. M. Magwene Statistical Methods for Studying Modularity: A Reply to Mitteroecker and Bookstein Syst Biol, May 22, 2009; (2009) syp007v1. [Full Text] [PDF]
|
|