Going back to the roots: Evaluating Bayesian phylogeographic models with discrete trait uncertainty

Evaluating the Impact of Anthropogenic Factors on the Dissemination of Contemporary Cosmopolitan, Arctic, and Arctic-like Rabies Viruses

Rabies is a globally prevalent viral zoonosis that causes 59,000 deaths per year and has important economic consequences. Most virus spread is associated with the migration of its primary hosts. Anthropogenic dissemination, mainly via the transportation of rabid dogs, shaped virus ecology a few hundred years ago and is responsible for several current outbreaks. A systematic analysis of aberrant long-distance events in the steppe and Arctic-like groups of rabies virus was performed using statistical (Bayesian) phylogeography and plots of genetic vs. geographic distances. The two approaches produced similar results but had some significant differences and complemented each other. No phylogeographic analysis could be performed for the Arctic group because polar foxes transfer the virus across the whole circumpolar region at high velocity, and there was no correlation between genetic and geographic distances in this virus group. In the Arctic-like group and the steppe subgroup of the cosmopolitan group, a significant number of known sequences (15-20%) was associated with rapid long-distance transfers, which mainly occurred within Eurasia. Some of these events have been described previously, while others have not been documented. Most of the recent long-distance transfers apparently did not result in establishing the introduced virus, but a few had important implications for the phylogeographic history of rabies. Thus, human-mediated long-distance transmission of the rabies virus remains a significant threat that needs to be addressed.

Testing methods of linguistic homeland detection using synthetic data

Two families of quantitative methods have been used to infer geographical homelands of language families: Bayesian phylogeography and the 'diversity method'. Bayesian methods model how populations may have moved using a phylogenetic tree as a backbone, while the diversity method assumes that the geographical area where linguistic diversity is highest likely corresponds to the homeland. No systematic tests of the performances of the different methods in a linguistic context have so far been published. Here, we carry out performance testing by simulating language families, including branching structures and word lists, along with speaker populations moving in space. We test six different methods: two versions of BayesTraits; the relaxed random walk model of BEAST 2; our own RevBayes implementations of a fixed rate and a variable rates random walk model; and the diversity method. As a result of the tests, we propose a hierarchy of performance of the different methods. Factors such as geographical idiosyncrasies, incomplete sampling, tree imbalance and small family sizes all have a negative impact on performance, but mostly across the board, the performance hierarchy generally being impervious to such factors. This article is part of the theme issue 'Reconstructing prehistoric languages'.