globalIntegration: Quantify global integration relative to self-similarity

In geomorph: Geometric Morphometric Analyses of 2D and 3D Landmark Data

Quantify global integration relative to self-similarity

Description

Function quantifies the overall level of morphological integration for a set of Procrustes shape variables

Usage

globalIntegration(A, ShowPlot = TRUE)

Arguments

A	3D array (p1 x k x n) containing Procrustes shape variables
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 shape 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). The 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 more extreme than -1.0) correspond to data that are globally integrated, while shallower slopes (between -1 and 0) correspond 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

## Not run: 
data(plethodon) 
Y.gpa <- gpagen(plethodon$land)    #GPA-alignment    

globalIntegration(Y.gpa$coords)

## End(Not run)

geomorph documentation built on June 24, 2024, 5:07 p.m.