commentary Quantifying the language dynamics of bilingual communities Felicity Meakins University of Queensland The diversity of the world’s languages is truly breathtaking but under great threat. Without intervention, language loss could triple in 40 years, equivalent to one lan- guage lost per month for the rest of this century (Bromham et al., 2021). There is an increasing urgency to understand the drivers of language change to stem the catastrophic rate of language loss globally and to improve language vitality. In their EPI article, Grenoble and Osipov (2023) are right to note that much of this change is occurring in bilingual and multilingual settings. In this respect, it is important to account for the use of all languages in ecologies of change, as Greno- ble and Osipov suggest, and use quantitative methods to better understand the vitality of heritage languages in these shif situations. Nonetheless, their methods continue to assess how well a person speaks their heritage language as opposed to how they speak this language alongside other languages in the broader language ecology and what factors drive its use. Their paper also continues a long tradi- tion of making generalisations based on a small number of linguistic features (e.g., general state of play in Variationist Sociolinguistics). Yet studies of single variables are limited in their capacity to map language change and to generalise across dif- ferent aspects of language. BayesVarbrul 1 is a new multivariate analysis of language change which com- bines Wright–Fisher models and the logic behind Varbrul analyses under a Bayesian framework. Wright-Fisher models are generally used in population genetics for describing a serial sampling process of genetic variants from one timestep to the next. Here Hua (2022) adapts Wright–Fisher models for language change, mapping the uptake of linguistic variants across diferent generations. BayesVarbrul models the efect of linguistic and social factors on the uptake of these variants and also how some social groups use these variants diferently from other groups. It is designed for datasets with multiple variables and multiple speakers https://doi.org/./lab..mea Linguistic Approaches to Bilingualism ISSN - | E‑ISSN - © John Benjamins Publishing Company 1. The code and the instructions are implemented in R and available at https://github.com /huaxia1985/BayesVarbrul.