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      Language is not isolated from its wider environment: Vocal tract influences on the evolution of speech and language

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      Language & Communication
      Elsevier BV

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          Language Structure Is Partly Determined by Social Structure

          Background Languages differ greatly both in their syntactic and morphological systems and in the social environments in which they exist. We challenge the view that language grammars are unrelated to social environments in which they are learned and used. Methodology/Principal Findings We conducted a statistical analysis of >2,000 languages using a combination of demographic sources and the World Atlas of Language Structures— a database of structural language properties. We found strong relationships between linguistic factors related to morphological complexity, and demographic/socio-historical factors such as the number of language users, geographic spread, and degree of language contact. The analyses suggest that languages spoken by large groups have simpler inflectional morphology than languages spoken by smaller groups as measured on a variety of factors such as case systems and complexity of conjugations. Additionally, languages spoken by large groups are much more likely to use lexical strategies in place of inflectional morphology to encode evidentiality, negation, aspect, and possession. Our findings indicate that just as biological organisms are shaped by ecological niches, language structures appear to adapt to the environment (niche) in which they are being learned and used. As adults learn a language, features that are difficult for them to acquire, are less likely to be passed on to subsequent learners. Languages used for communication in large groups that include adult learners appear to have been subjected to such selection. Conversely, the morphological complexity common to languages used in small groups increases redundancy which may facilitate language learning by infants. Conclusions/Significance We hypothesize that language structures are subjected to different evolutionary pressures in different social environments. Just as biological organisms are shaped by ecological niches, language structures appear to adapt to the environment (niche) in which they are being learned and used. The proposed Linguistic Niche Hypothesis has implications for answering the broad question of why languages differ in the way they do and makes empirical predictions regarding language acquisition capacities of children versus adults.
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            De novo establishment of wild-type song culture in the zebra finch

            What sort of culture would evolve in an island colony of naive founders? This question cannot be studied experimentally in humans. We performed the analogous experiment using socially learned birdsong. Culture is typically viewed as consisting of traits inherited epigenetically, via social learning. However, cultural diversity has species-typical constraints1, presumably of genetic origin. A celebrated, if contentious, example is whether a universal grammar constrains syntactic diversity in human languages2. Oscine songbirds exhibit song learning and provide biologically tractable models of culture: members of a species show individual variation in song3 and geographically separated groups have local song dialects 4,5. Different species exhibit distinct song cultures6,7, suggestive of genetic constraints8,9. Absent such constraints, innovations and copying errors should cause unbounded variation over multiple generations or geographical distance, contrary to observations9. We asked if wild-type song culture might emerge over multiple generations in an isolated colony founded by isolates, and if so, how this might happen and what type of social environment is required10. Zebra finch isolates, unexposed to singing males during development, produce song with characteristics that differ from the wild-type song found in laboratory11 or natural colonies. In tutoring lineages starting from isolate founders, we quantified alterations in song across tutoring generations in two social environments: tutor-pupil pairs in sound-isolated chambers and an isolated semi-natural colony. In both settings, juveniles imitated the isolate tutors, but changed certain characteristics of the songs. These alterations accumulated over learning generations. Consequently, songs evolved toward the wild-type in 3–4 generations. Thus, species-typical song culture can appear de novo. Our study has parallels with language change and evolution12,13. In analogy to models in quantitative genetics14,15, we model song culture as a multi-generational phenotype, partly encoded genetically in an isolate founding population, influenced by environmental variables, and taking multiple generations to emerge.
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              Phonemic diversity supports a serial founder effect model of language expansion from Africa.

              Human genetic and phenotypic diversity declines with distance from Africa, as predicted by a serial founder effect in which successive population bottlenecks during range expansion progressively reduce diversity, underpinning support for an African origin of modern humans. Recent work suggests that a similar founder effect may operate on human culture and language. Here I show that the number of phonemes used in a global sample of 504 languages is also clinal and fits a serial founder-effect model of expansion from an inferred origin in Africa. This result, which is not explained by more recent demographic history, local language diversity, or statistical non-independence within language families, points to parallel mechanisms shaping genetic and linguistic diversity and supports an African origin of modern human languages.
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                Author and article information

                Journal
                Language & Communication
                Language & Communication
                Elsevier BV
                02715309
                May 2017
                May 2017
                : 54
                :
                : 9-20
                Article
                10.1016/j.langcom.2016.10.002
                92a44845-f694-413f-a79c-34be3d3b49d9
                © 2017

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