Debates about human prehistory often center on the role that population expansions play in shaping biological and cultural diversity. Hypotheses on the origin of the Austronesian settlers of the Pacific are divided between a recent "pulse-pause" expansion from Taiwan and an older "slow-boat" diffusion from Wallacea. We used lexical data and Bayesian phylogenetic methods to construct a phylogeny of 400 languages. In agreement with the pulse-pause scenario, the language trees place the Austronesian origin in Taiwan approximately 5230 years ago and reveal a series of settlement pauses and expansion pulses linked to technological and social innovations. These results are robust to assumptions about the rooting and calibration of the trees and demonstrate the combined power of linguistic scholarship, database technologies, and computational phylogenetic methods for resolving questions about human prehistory.

There are two competing hypotheses for the origin of the Indo-European language family. The conventional view places the homeland in the Pontic steppes approximately 6kya. An alternative hypothesis claims the languages spread from Anatolia with the expansion of farming 8–9.5kya. Here we use Bayesian phylogeographic approaches together with basic vocabulary data from 103 ancient and contemporary Indo-European languages to explicitly model the expansion of the family and test between the homeland hypotheses. We find decisive support for an Anatolian over a steppe origin. Both the inferred timing and root location of the Indo-European language trees fit with an agricultural expansion from Anatolia beginning in the 9th millennium BP. These results highlight the critical role phylogeographic inference can play in resolving longstanding debates about human prehistory.

Languages vary widely but not without limit. The central goal of linguistics is to describe the diversity of human languages and explain the constraints on that diversity. Generative linguists following Chomsky have claimed that linguistic diversity must be constrained by innate parameters that are set as a child learns a language 1,2 . In contrast, other linguists following Greenberg have claimed that there are statistical tendencies for co-occurrence of traits reflecting universal systems biases [3][4][5] , rather than absolute constraints or parametric variation. Here we use computational phylogenetic methods to address the nature of constraints on linguistic diversity in an evolutionary framework 6 . First, contrary to the generative account of parameter setting, we show that the evolution of only a few word-order features of languages are strongly correlated. Second, contrary to the Greenbergian generalizations, we show that most observed functional dependencies between traits are lineage-specific rather than universal tendencies. These findings support the view that-at least with respect to word order-cultural evolution is the primary factor that determines linguistic structure, with the current state of a linguistic system shaping and constraining future states.Human language is unique amongst animal communication systems not only for its structural complexity but also for its diversity at every level of structure and meaning. There are about 7,000 extant languages, some with just a dozen contrastive sounds, others with more than 100, some with complex patterns of word formation, others with simple words only, some with the verb at the beginning of the sentence, some in the middle, and some at the end. Understanding this diversity and the systematic constraints on it is the central goal of linguistics. The generative approach to linguistic variation has held that linguistic diversity can be explained by changes in parameter settings. Each of these parameters controls a number of specific linguistic traits. For example, the setting 'heads first' will cause a language both to place verbs before objects ('kick the ball'), and prepositions before nouns ('into the goal') 1,7 . According to this account, language change occurs when child learners simplify or regularize by choosing parameter settings other than those of the parental generation. Across a few generations such changes might work through a population, effecting language change across all the associated traits. Language change should therefore be relatively fast, and the traits set by one parameter must co-vary 8 .In contrast, the statistical approach adopted by Greenbergian linguists samples languages to find empirically co-occurring traits. These cooccurring traits are expected to be statistical tendencies attributable to universal cognitive or systems biases. Among the most robust of these tendencies are the so-called ''word-order universals'' 3 linking the order of elements in a clause. Dryer has tested these generalizations on a worldwide sample...

Many human languages have words for emotions such as “anger” and “fear,” yet it is not clear whether these emotions have similar meanings across languages, or why their meanings might vary. We estimate emotion semantics across a sample of 2474 spoken languages using “colexification”—a phenomenon in which languages name semantically related concepts with the same word. Analyses show significant variation in networks of emotion concept colexification, which is predicted by the geographic proximity of language families. We also find evidence of universal structure in emotion colexification networks, with all families differentiating emotions primarily on the basis of hedonic valence and physiological activation. Our findings contribute to debates about universality and diversity in how humans understand and experience emotion.