Problems and Cautions With Sequence Mismatch Analysis and Bayesian Skyline Plots to Infer Historical Demography

Sequence mismatch analysis (MMA) and Bayesian skyline plots (BSP) are commonly used to reconstruct historical demography. A survey of 173 research articles (2009-2014), which included estimates of historical population sizes from mtDNA or cpDNA, shows a widespread genetic signature of demographic or spatial population expansion in species of all major taxonomic groups. Associating these expansions with climatic events can provide insights into the origins of lineage diversity, range expansions (or contractions), and speciation. However, several variables can introduce error into reconstructions of demographic history, including levels of sequence polymorphism, sampling scheme, sample size, natural selection, and estimates of mutation rate. Most researchers use substitution rates estimated from divergences in phylogenetic trees dated with fossils, or geological events. Recent studies show that molecular clocks calibrated with phylogenetic divergences can overestimate the timings of population-level events by an order of magnitude. Overestimates disconnect historical population reconstructions from climatic history and confound our understanding of the factors influencing genetic variability. If mismatch distributions and BSPs largely reflect demographic history, the widespread signature of population expansion in vertebrate, invertebrate, and plant populations appears to reflect responses to postglacial climate warming.