A stochastic rate-calibrated method for time-scaling phylogenies of fossil taxa
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SummaryApplying phylogenybased analyses of trait evolution and diversification in the fossil record generally involves transforming an unscaled cladogram into a phylogeny scaled to geologic time. Current methods produce single timescaled phylogenies with no indication of the uncertainty in the temporal relationships and, under some methods, artificial zerolength branches.Here, I present a stochastic algorithm for timescaling phylogenies of fossil taxa by randomly sampling node ages from a constrained distribution, with the ultimate goal of producing large samples of timescaled phylogenies for a given data set as the basis for phylogenybased analyses. I describe how this stochastic approach can be extended to consider potential ancestral relationships and resolve polytomies.The stochastic selection of node ages in this algorithm is weighted by the probability density of the total inferable unobserved evolutionary history at single divergence events in a tree, a distribution dependent on rates of branching, extinction and sampling in the fossil record.The combined timescaling method must be calibrated with explicit estimates of three rates: branching, extinction and sampling, and thus is named the cal3 timescaling method, included in the r library paleotree. I test the timescaling capabilities of the cal3 and older timescaling methods in simulations. cal3 produces samples of timescaled trees that better bracket the uncertainty in the true node ages than existing timescaling methods. This is true even in simulations under a terminaltaxon model of differentiation that violates many of the assumptions of the cal3 method.The cal3 method provides a new approach for timescaling palaeontological cladograms, calibrated to estimated sampling and diversification rates, allowing for better estimates of uncertainty in the phylogenetic timescaling. The cal3 method is robust to relaxation of at least some model assumptions. Additional work is needed to analyse the impact of timescaling approaches on macroevolutionary analyses and to integrate timescaling with phylogenetic inference.
