Empirical data for: Extending phylogenetic regression models for comparing within-species patterns across the Tree of Life

Biologists use phylogenetic comparative methods to characterize
macroevolutionary trends of phenotypic change across species.
Within-species variation can complicate such investigations, and
procedures incorporating nonstructured (random) intraspecific variation
have been developed. However, intraspecific variation can also be
structured (sex-specific differences, allometric trends), and biologists
often wish to compare such intraspecific patterns across taxa.
Unfortunately, current analytical approaches cannot interrogate
within-species patterns while simultaneously accounting for phylogenetic
nonindependence. Thus, deciphering how intraspecific trends evolve remains
a challenge. We introduce an extended phylogenetic generalized least
squares (E-PGLS) procedure which facilitates comparisons of within-species
patterns across species while accounting for phylogenetic nonindependence.
Our method uses an expanded phylogenetic covariance matrix, a hierarchical
linear model, and permutation methods to obtain empirical sampling
distributions and effect sizes for model effects that can evaluate
differences in intraspecific trends across species for both univariate and
multivariate data while conditioning them on the phylogeny. The method has
appropriate statistical properties and obtains evolutionary covariance
estimates that reflect those from existing approaches for nonstructured
(random) intraspecific variation. Additionally, E-PGLS can detect
differences in structured intraspecific patterns across species when such
trends are present. Thus, E-PGLS extends the reach of phylogenetic
comparative methods into the intraspecific comparative realm, by providing
the ability to evaluate within-species trends across species while
simultaneously accounting for shared evolutionary history.