Abstract
Language is a hallmark of our species and understanding linguistic
diversity is an area of major interest. Genetic factors influencing
the cultural transmission of language provide a powerful and elegant
explanation for aspects of the present day linguistic diversity and
a window into the emergence and evolution of language. In particular,
it has recently been proposed that linguistic tone-the usage of voice
pitch to convey lexical and grammatical meaning-is biased by two
genes involved in brain growth and development, ASPM and Microcephalin.
This hypothesis predicts that tone is a stable characteristic of
language because of its 'genetic anchoring'. The present paper tests
this prediction using a Bayesian phylogenetic framework applied to
a large set of linguistic features and language families, using multiple
software implementations, data codings, stability estimations, linguistic
classifications and outgroup choices. The results of these different
methods and datasets show a large agreement, suggesting that this
approach produces reliable estimates of the stability of linguistic
data. Moreover, linguistic tone is found to be stable across methods
and datasets, providing suggestive support for the hypothesis of
genetic influences on its distribution.
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