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

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Oct 07, 2024 version files 1.29 MB

Abstract

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.