Last data update: 2014.03.03

R: Quantify global integration relative to self-similarity
globalIntegrationR Documentation

Quantify global integration relative to self-similarity

Description

Function quantifies the overall level of morphological integration for a set of Procrustes-aligned coordinates

Usage

globalIntegration(A, ShowPlot = TRUE)

Arguments

A

3D array (p1 x k x n) containing GPA-aligned coordinates

ShowPlot

A logical value indicating whether or not the plot should be returned

Details

The function quantifies the overall level of morphological integration for a set of Procrustes coordinates. It is assumed that the landmarks have previously been aligned using Generalized Procrustes Analysis (GPA) [e.g., with gpagen]. Based on the set of aligned specimens, the function estimates the set of bending energies at various spatial scales, and plots the log of the variance of the partial warps versus the log of their corresponding bending energies (Bookstein 2015). For slope of a regression of these data provides information regarding the degree of overall morphological integration (or lack thereof).

A slope of negative one corresponds to self-similarity, implying that patterns of shape variation are similar across spatial scales. Steeper slopes (i.e., those larger than -1.0) correspond to data that are globally integrated, while shallower slopes to data that are 'disintegrated (see Bookstein 2015). Isotropic data will have an expected slope of zero.

Author(s)

Dean Adams

References

Bookstein, F. L. 2015. Integration, disintegration, and self-similarity: Characterizing the scales of shape variation in landmark data. Evol. Biol.42(4): 395-426.

Examples

data(plethodon) 
Y.gpa<-gpagen(plethodon$land)    #GPA-alignment    

globalIntegration(Y.gpa$coords)

Results