Traditional phylogenetic models are insensitive to variations in the effective population size

A substitution represents the emergence and fixation of an allele in a population or species and is the fundamental event from which phylogenetic models of sequence evolution are devised. Because of the increasing availability of genomic sequences, we are now able to take advantage of intraspecific variability when reconstructing the tree of life. As a result, substitutions can be more realistically modeled as the product of mutation, selection, and genetic drift. However, it is still unclear whether this increased complexity affects our measures of evolutionary times and rates. This study seeks to answer this question by contrasting the traditional substitution model with a population genetic equivalent using data from 4385 individuals distributed across 179 populations and representing 17 species of animals, plants, and fungi. We found that when the population genetics dynamic is modeled via the substitution rates, the evolutionary times and rates of the two models are well correlated, suggesting that the phylogenetic model is able to capture the time and pace of its population counterpart. However, a closer inspection of this result showed that the traditional models largely ignore the effect of the effective population size, even when it is explicitly accounted for in the substitution rates. Our findings suggest that superimposing population-genetics results on the substitution rates is an effective strategy to study mutation and selection biases, while other data sources (e.g., life history traits or polymorphisms) may need to be additionally integrated to make the traditional substitution models sensitive to the impact of genetic drift. When combined with the known effect of ancestral population size on generating phylogenomic incongruence due to incomplete lineage sorting, our findings provide further evidence that unaccounted-for variations in the effective population size may be one of the primary causes of errors in phylogenetic analyses at shorter time scales.