Languages and weaving methods are passed down generation to generation, allowing both of them to have relatively clear phylogenies. These researchers use a Bayesian approach with Markov chain Monte Carlo methods to uncover similar but independent phylogenies for Kra-Dai languages and weaving technologies. Evolutionary differences between the two are most likely due to different rates of change: smooth change (language) and periods of burst and stasis (weaving). This study found that language phylogenies were not efficient at predicting phylogenies of technologies.

Languages and weaving methods are passed down generation to generation, allowing both of them to have relatively clear phylogenies. These researchers use a Bayesian approach with Markov chain Monte Carlo methods to uncover similar but independent phylogenies for Kra-Dai languages and weaving technologies. Evolutionary differences between the two are most likely due to different rates of change: smooth change (language) and periods of burst and stasis (weaving). This study found that language phylogenies were not efficient at predicting phylogenies of technologies.

Languages and weaving methods are passed down generation to generation, allowing both of them to have relatively clear phylogenies. These researchers use a Bayesian approach with Markov chain Monte Carlo methods to uncover similar but independent phylogenies for Kra-Dai languages and weaving technologies. Evolutionary differences between the two are most likely due to different rates of change: smooth change (language) and periods of burst and stasis (weaving). This study found that language phylogenies were not efficient at predicting phylogenies of technologies.

Languages and weaving methods are passed down generation to generation, allowing both of them to have relatively clear phylogenies. These researchers use a Bayesian approach with Markov chain Monte Carlo methods to uncover similar but independent phylogenies for Kra-Dai languages and weaving technologies. Evolutionary differences between the two are most likely due to different rates of change: smooth change (language) and periods of burst and stasis (weaving). This study found that language phylogenies were not efficient at predicting phylogenies of technologies.

Languages and weaving methods are passed down generation to generation, allowing both of them to have relatively clear phylogenies. These researchers use a Bayesian approach with Markov chain Monte Carlo methods to uncover similar but independent phylogenies for Kra-Dai languages and weaving technologies. Evolutionary differences between the two are most likely due to different rates of change: smooth change (language) and periods of burst and stasis (weaving). This study found that language phylogenies were not efficient at predicting phylogenies of technologies.

Ikat and warp weaving techniques have a long history in Southeastern Asia and tend to be the most geographically widespread in the region. This researcher uses Bayesian and Neighbornet techniques to create models of phylogenetic descent and distribution of SE Asian weaving traditions. These findings do not support the theory of late Bronze Age Dong-Son descent.

Ikat and warp weaving techniques have a long history in Southeastern Asia and tend to be the most geographically widespread in the region. This researcher uses Bayesian and Neighbornet techniques to create models of phylogenetic descent and distribution of SE Asian weaving traditions. These findings do not support the theory of late Bronze Age Dong-Son descent.

Ikat and warp weaving techniques have a long history in Southeastern Asia and tend to be the most geographically widespread in the region. This researcher uses Bayesian and Neighbornet techniques to create models of phylogenetic descent and distribution of SE Asian weaving traditions. These findings do not support the theory of late Bronze Age Dong-Son descent.

Ikat and warp weaving techniques have a long history in Southeastern Asia and tend to be the most geographically widespread in the region. This researcher uses Bayesian and Neighbornet techniques to create models of phylogenetic descent and distribution of SE Asian weaving traditions. These findings do not support the theory of late Bronze Age Dong-Son descent.

By testing relationships between musical, geographic, genetic, and linguistic distance among nine indigenous groups in Taiwan, the researchers aim to quantitatively evaluate a developing theory of coevolution between these traits. An especially strong correlation between musical variability and genetic distance suggests that music may possess worldwide time depth, diversity, and universality equal to or greater than that of language, and could thus serve as a complementary marker for reconstruction of long-term population shifts.