CladeDate: Calibration information generator for divergence time estimation

Time‐scaled phylogenetic trees are essential tools in modern biology and node‐based calibrations have been the main approach to time‐tree estimation. But methods for generating the required calibration information are scarce and difficult to parameterize. Here, I present CladeDate, an R package for...

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Bibliographic Details
Published in:Methods in ecology and evolution 2022-11, Vol.13 (11), p.2331-2338
Main Author: Claramunt, Santiago
Format: Article
Language:English
Subjects:
Calibration
calibration densities
divergence time estimation
empirical priors
fossil dating
fossil record
Mathematical models
Phylogeny
Probability density functions
Uncertainty
Upper bounds
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Summary:Time‐scaled phylogenetic trees are essential tools in modern biology and node‐based calibrations have been the main approach to time‐tree estimation. But methods for generating the required calibration information are scarce and difficult to parameterize. Here, I present CladeDate, an R package for the generation of empirical calibration information from the fossil record. CladeDate uses simple mathematical models to estimate the age of a clade and its uncertainty based on fossil times. Using a Monte Carlo approach, CladeDate generates empirical densities representing the uncertainty associated with the age of the clade and fits standard probability density functions that can be used in time‐tree inference software such as BEAST2, MrBayes and MCMCtree. I show with simulations that the calibration information generated with CladeDate produces accurate time‐trees and compares favourably with more complex methods. I demonstrate the use CladeDate for the generation of calibration information, including point estimates, upper bounds and calibration densities, for passerine birds. CladeDate is particularly suited for groups with limited fossil information or when assumptions of more complex methods are not met, and provides a general and practical solution to the problem of generating calibration information for divergence time estimation.
ISSN:2041-210X
2041-210X
DOI:10.1111/2041-210X.13977