2012/02/17 by Eric W. Goolsby, Betsy Palmer · 1 citation
Biochemistry, Genetics and Molecular Biology · Earth and Planetary Sciences · Economics, Econometrics and Finance · Environmental Science · Social Sciences · #American Constitutional Law and Politics #Ecology and Vegetation Dynamics Studies #Evolution and Paleontology Studies #Genetic diversity and population structure #Law, Rights, and Freedoms #Legal and Constitutional Studies
paper · pdf · doi:10.1093/sysbio/syv012
openalex publication_date 2012/02/17 · openalex created_date 2025/10/10 · openalex updated_date 2026/04/28
Phylogenetic comparative methods offer a suite of tools for studying trait evolution. However, most models inherently assume fixed trait values within species. Although some methods can incorporate error around species means, few are capable of accounting for variation driven by environmental or temporal gradients, such as trait responses to abiotic stress or ontogenetic trajectories. Such traits, often referred to as function-valued or infinite-dimensional, are typically expressed as reaction norms, dose-response curves, or time plots and are described by mathematical functions linking independent predictor variables to the trait of interest. Here, I introduce a method for extending ancestral state reconstruction to incorporate function-valued traits in a phylogenetic generalized least squares (PGLS) framework, as well as extensions of this method for testing phylogenetic signal, performing phylogenetic analysis of variance (ANOVA), and testing for correlated trait evolution using recently proposed multivariate PGLS methods. Statistical power of function-valued comparative methods is compared to univariate approaches using data simulations, and the assumptions and challenges of each are discussed in detail.