Modeling Ancient Population Structures and Movement in Linguistics

Nichols, Johanna

doi:10.1146/annurev.anthro.26.1.359

Cited by 124 publications

(82 citation statements)

References 52 publications

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“…Although the database may contain unidentified loan words, our analysis is based on items of basic vocabulary that are more resistant to being borrowed (52). Moreover, the most likely source of loan words is a language's sister (2,53), the effect of which would be to weaken the signal in our data rather than create false patterns. Simulation studies of borrowing suggest that any unidentified loan words would make the sister languages seem more similar than they actually are by masking innovations or losses (53).…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Rate of language evolution is affected by population size

Bromham

Hua

Fitzpatrick

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

101

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The effect of population size on patterns and rates of language evolution is controversial. Do languages with larger speaker populations change faster due to a greater capacity for innovation, or do smaller populations change faster due to more efficient diffusion of innovations? Do smaller populations suffer greater loss of language elements through founder effects or drift, or do languages with more speakers lose features due to a process of simplification? Revealing the influence of population size on the tempo and mode of language evolution not only will clarify underlying mechanisms of language change but also has practical implications for the way that language data are used to reconstruct the history of human cultures. Here, we provide, to our knowledge, the first empirical, statistically robust test of the influence of population size on rates of language evolution, controlling for the evolutionary history of the populations and formally comparing the fit of different models of language evolution. We compare rates of gain and loss of cognate words for basic vocabulary in Polynesian languages, an ideal test case with a well-defined history. We demonstrate that larger populations have higher rates of gain of new words whereas smaller populations have higher rates of word loss. These results show that demographic factors can influence rates of language evolution and that rates of gain and loss are affected differently. These findings are strikingly consistent with general predictions of evolutionary models. language evolution | sister-pair comparison | Austronesian | lexical change | Poisson regression P opulation size can play a crucial role in the evolution of languages and cultures (1). However, opinions differ on both the possible mechanisms and the expected patterns (2-7). It has been suggested that larger populations will generate more innovations and are less prone to random loss of cultural elements (8-10), but may have less efficient diffusion of innovations than smaller populations (4). Alternatively, languages spoken by small isolated populations of speakers may have lower rates of loss if they maintain tighter cultural norms that improve transmission and resist change (11). Rates of change might be accelerated by founder effects when a new population is started from a small number of colonists, which could result in loss of elements from the ancestral language (11-13). Population size might also influence language complexity if small populations can develop greater linguistic complexity (11), whereas large, widespread languages that are often learned by adults may become simplified (14). Conversely, it has been suggested that the average rate of word turnover is essentially the same in all languages (15-17), or that it is determined primarily by other factors such as language contact (6, 18).Uncovering systematic patterns of rates of language change may reveal underlying mechanisms of language evolution (13,19). In particular, investigating rates of language change can demonstrate whether langua...

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Section: Methodsmentioning

confidence: 99%

“…However, opinions differ on both the possible mechanisms and the expected patterns (2)(3)(4)(5)(6)(7). It has been suggested that larger populations will generate more innovations and are less prone to random loss of cultural elements (8)(9)(10), but may have less efficient diffusion of innovations than smaller populations (4).…”

mentioning

confidence: 99%

Rate of language evolution is affected by population size

Bromham

Hua

Fitzpatrick

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

101

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“…The expansion of Bantu-speaking peoples is not only debated with regard to the underlying events and the route(s) taken, but also whether the spread of the languages took place as the result of 'demic diffusion' via an actual movement of people [1], or whether it was rather a cultural diffusion involving the movement of languages via 'language shift' [14] without concomitant gene flow. Genetic studies have highlighted the strong demographic impact of the Bantu migration on the gene pool of Sub-Saharan African populations for mtDNA [15,16], the Y chromosome [17,18] and autosomes [19,20].…”

Section: Introductionmentioning

confidence: 99%

Bringing together linguistic and genetic evidence to test the Bantu expansion

et al. 2012

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The expansion of Bantu languages represents one of the most momentous events in the history of Africa. While it is well accepted that Bantu languages spread from their homeland (Cameroon/Nigeria) approximately 5000 years ago (ya), there is no consensus about the timing and geographical routes underlying this expansion. Two main models of Bantu expansion have been suggested: The 'early-split' model claims that the most recent ancestor of Eastern languages expanded north of the rainforest towards the Great Lakes region approximately 4000 ya, while the 'late-split' model proposes that Eastern languages diversified from Western languages south of the rainforest approximately 2000 ya. Furthermore, it is unclear whether the language dispersal was coupled with the movement of people, raising the question of language shift versus demic diffusion. We use a novel approach taking into account both the spatial and temporal predictions of the two models and formally test these predictions with linguistic and genetic data. Our results show evidence for a demic diffusion in the genetic data, which is confirmed by the correlations between genetic and linguistic distances. While there is little support for the early-split model, the late-split model shows a relatively good fit to the data. Our analyses demonstrate that subsequent contact among languages/populations strongly affected the signal of the initial migration via isolation by distance.

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“…It is useful to borrow the term 'spread' from historical-comparative linguistics (Nichols, 1997), because the spread of the Upper Palaeolithic has many of the characteristics of a language spread. The source area appears to have been in the Negev (Marks, 1990) and probably the north-eastern corner of Africa, the lower Nile Valley and Cyrenaica (McBurney, 1967).…”

Section: Out Of Africamentioning

confidence: 99%

“…A language in the modern sense would be necessary to explain the meaning of symbols held in common. Click languages are unique to this part of Africa and probably had their origins here (Nichols, 1997). It is entirely possible they were spoken in an ancestral form in the Late Pleistocene.…”

Section: The Emergence Of Modern Behaviourmentioning

confidence: 99%

Humanity from African Naissance to Coming Millennia

Tobias¹,

Raath²,

Moggi‐Cecchi³

et al. 2001

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The first 2.5 million years of hominid history is characterized by limited dispersals similar to those of the living great apes whose home range sizes very little between years. Unlike our closest relative Pan, who are particulary vulnerable during dispersal because the distribution of their resources is highly habitat specific and predation takes a relatively higher toll than it does in r-selected animals, hominids are widely dispersed after 1.8 Ma. Hominid dispersal must have entailed either a shift in the types of resources exploited or a technological advance to ensure resource availability or both. Using data from ecology, geochronology, morphology, and paleontology we assess the initial hominid dispersal from Africa and the relationship to patterns of dispersal in nonhuman primates and large mammals of both 'widely dispersing' and 'non-dispersing' species. The dispersal rates of Plio/Pleistocene hominids differ from those of nonhuman primates and are typical of widely-dispersing large mammals. In fact, H. erectus first appears in Java almost immediately after its appearence in Africa, yet its first appearence in Java is contemporaneous with that of Colobus, Macaca, and Pongo that had already inhabited mainland Asia for millions of years. Although the timing of the first hominid dispersal pre-dates significant technological advances, the energy required by larger hominid body/brain sizes suggest a shift to exploitation of highprotein packages that, according to correlation between faunal and chronometric sequences, is itself dispersing. These data suggest that it is at the origin of H. erectus (sensu lato) that our uniquely human dispersal capabilities began to emerge and that this dispersal is not primarily due to the technological innovation of the Acheulean tradition. IntroductionThe global distribution of Homo sapiens contrasts with the restricted ranges of our closest living primate relative, Pan. Yet for some three million years after our lineages diverged, both were apparently exclusively African phenomena, as Pan remains today. These current biogeographic differences are reflected in home range (HR) sizes that are some 15 to 100 times greater in recent human huntergatherers than in Pan. (23 hectares in Pan, 330-2600 in humans; Leonard and Robertson, 2000). Although an extensive literature considers the significance of the behavioral repertoire that allows the final, relatively late, dispersal of Homo sapiens into Australasia, North and South America, and Siberia (e.g., Lindly & Clark, 1990;Roberts et al., 1991; Davidson & Noble, 1992; Jelinek, 1994; Waters et al., 1997), the origin of this difference in dispersal patterns is not well understood.The original hominid dispersal from Africa has been viewed as a largely hominid (technologically) driven rather than ecologically driven phenomenon. Such scenarios are based on the idea that widely dispersed ex-African hominids are not found before 1.0 ma (Pope, 1983) or are not found before the development of the Acheulean (Wolpoff, 1999), and thus that th...

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Modeling Ancient Population Structures and Movement in Linguistics

Cited by 124 publications

References 52 publications

Rate of language evolution is affected by population size

Rate of language evolution is affected by population size

Bringing together linguistic and genetic evidence to test the Bantu expansion

Humanity from African Naissance to Coming Millennia

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