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Evolutionary dynamics of language systems

  1. Russell D. Grayb,h
  1. aARC Centre of Excellence for the Dynamics of Language, Australian National University, Canberra, ACT 0200, Australia;
  2. bDepartment of Linguistic and Cultural Evolution, Max Planck Institute for the Science of Human History, 07745 Jena, Germany;
  3. cDepartment of Statistics, University of Oxford, Oxford OX1 3LB, United Kingdom;
  4. dMacroevolution and Macroecology, Division of Ecology, Evolution, and Genetics, Research School of Biology, Australian National University, Canberra, ACT 0200 Australia;
  5. eDepartment of Linguistics and Philology, Uppsala University, 75238 Uppsala, Sweden;
  6. fMax Planck Institute for Psycholinguistics, 6525 XD, Nijmegen, The Netherlands;
  7. gComparative Linguistics, Radboud University Nijmegen, 6525 HP, Nijmegen, The Netherlands;
  8. hSchool of Psychology, University of Auckland, Auckland, New Zealand
  1. Edited by Tomoko Ohta, National Institute of Genetics, Mishima, Japan, and approved July 11, 2017 (received for review January 8, 2017)


Do different aspects of language evolve in different ways? Here, we infer the rates of change in lexical and grammatical data from 81 languages of the Pacific. We show that, in general, grammatical features tend to change faster and have higher amounts of conflicting signal than basic vocabulary. We suggest that subsystems of language show differing patterns of dynamics and propose that modeling this rate variation may allow us to extract more signal, and thus trace language history deeper than has been previously possible.


Understanding how and why language subsystems differ in their evolutionary dynamics is a fundamental question for historical and comparative linguistics. One key dynamic is the rate of language change. While it is commonly thought that the rapid rate of change hampers the reconstruction of deep language relationships beyond 6,000–10,000 y, there are suggestions that grammatical structures might retain more signal over time than other subsystems, such as basic vocabulary. In this study, we use a Dirichlet process mixture model to infer the rates of change in lexical and grammatical data from 81 Austronesian languages. We show that, on average, most grammatical features actually change faster than items of basic vocabulary. The grammatical data show less schismogenesis, higher rates of homoplasy, and more bursts of contact-induced change than the basic vocabulary data. However, there is a core of grammatical and lexical features that are highly stable. These findings suggest that different subsystems of language have differing dynamics and that careful, nuanced models of language change will be needed to extract deeper signal from the noise of parallel evolution, areal readaptation, and contact.


  • ?1To whom correspondence should be addressed. Email: simon.greenhill{at}anu.edu.au.
  • Author contributions: S.J.G., C.-H.W., M.D., S.C.L., and R.D.G. designed research; S.J.G., C.-H.W., X.H., M.D., S.C.L., and R.D.G. performed research; M.D. and S.C.L. contributed new reagents/analytic tools; S.J.G., C.-H.W., and X.H. analyzed data; and S.J.G., C.-H.W., M.D., S.C.L., and R.D.G. wrote the paper.

  • The authors declare no conflict of interest.

  • This article is a PNAS Direct Submission.

  • This article contains supporting information online at www.danielhellerman.com/lookup/suppl/doi:10.1073/pnas.1700388114/-/DCSupplemental.

This is an open access article distributed under the PNAS license.

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