Abstract
Time-scaled phylogenetic trees are an ultimate goal of evolutionary biology and a necessary ingredient in comparative studies. The accumulation of genomic data has resolved the tree of life to a great extent, yet timing evolutionary events remains challenging if not impossible without external information such as fossil ages and morphological characters. Methods for incorporating morphology in tree estimation have lagged behind their molecular counter-parts, especially in the case of continuous characters. Despite recent advances, such tools are still direly needed as we approach the limits of what molecules can teach us. Here, we implement a suite of state-of-the-art methods for leveraging continuous morphology in phylogenetics, and by conducting extensive simulation studies we thoroughly validate and explore our methods’ properties. While retaining model generality and scalability, we make it possible to estimate absolute and relative divergence times from multiple continuous characters while accounting for uncertainty. We compile and analyze one of the most data-type diverse data sets to date, comprised of contemporaneous and ancient molecular sequences, and discrete and continuous characters from living and extinct Carnivora taxa. We conclude by synthesizing lessons about our method’s behavior, and suggest future research venues.
Competing Interest Statement
The authors have declared no competing interest.
Footnotes
Re-running the empirical analyses using the best discrete-morphology model partition found in Barrett et al. (2021); Clarifying the parameterization of our model -- specifically our choice of using the upper-triangular decomposition of rate correlation matrix; Doing a new simulation experiment to test an additional type of model misspecification in the updated Fig. 2a-c; Modifying the x-axis in Fig. 2 to show absolute values; Adding several new passages discussing on our modeling assumptions of (a) character independence, and (b) characters sharing evolutionary rates;