On the comparison of the strength of morphological integration across morphometric datasets
0106 biological sciences
0301 basic medicine
570
Models, Genetic
Evolution
Ecology and Evolutionary Biology
610
Datasets as Topic
Genetic Variation
Lizards
01 natural sciences
6. Clean water
Statistical Methodology
Evolution, Molecular
03 medical and health sciences
Animals
Body Size
Least-Squares Analysis
10. No inequality
Algorithms
DOI:
10.1111/evo.13045
Publication Date:
2016-09-05T05:53:09Z
AUTHORS (2)
ABSTRACT
Evolutionary morphologists frequently wish to understand the extent to which organisms are integrated, and whether the strength of morphological integration among subsets of phenotypic variables differ among taxa or other groups. However, comparisons of the strength of integration across datasets are difficult, in part because the summary measures that characterize these patterns (RV coefficient and rPLS ) are dependent both on sample size and on the number of variables. As a solution to this issue, we propose a standardized test statistic (a z-score) for measuring the degree of morphological integration between sets of variables. The approach is based on a partial least squares analysis of trait covariation, and its permutation-based sampling distribution. Under the null hypothesis of a random association of variables, the method displays a constant expected value and confidence intervals for datasets of differing sample sizes and variable number, thereby providing a consistent measure of integration suitable for comparisons across datasets. A two-sample test is also proposed to statistically determine whether levels of integration differ between datasets, and an empirical example examining cranial shape integration in Mediterranean wall lizards illustrates its use. Some extensions of the procedure are also discussed.
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