Does horizontal transmission invalidate cultural phylogenies?

Greenhill, Simon J.; Currie, Thomas E.; Gray, Russell D.

doi:10.1098/rspb.2008.1944

Cited by 141 publications

(95 citation statements)

References 51 publications

(57 reference statements)

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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%

Rate of language evolution is affected by population size

Bromham

Hua

Fitzpatrick

et al. 2015

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

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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%

Rate of language evolution is affected by population size

Bromham

Hua

Fitzpatrick

et al. 2015

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

Self Cite

101

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“…Greenhill et al (89) simulated language phylogenies with different tree topologies, different borrowing scenarios, and different levels of borrowing. The results show that tree topologies constructed with Bayesian phylogenetic methods are robust to realistic levels of borrowing.…”

Section: Statedmentioning

confidence: 99%

Cultural macroevolution matters

Gray

Watts

2017

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

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Evolutionary thinking can be applied to both cultural microevolution and macroevolution. However, much of the current literature focuses on cultural microevolution. In this article, we argue that the growing availability of large cross-cultural datasets facilitates the use of computational methods derived from evolutionary biology to answer broad-scale questions about the major transitions in human social organization. Biological methods can be extended to human cultural evolution. We illustrate this argument with examples drawn from our recent work on the roles of Big Gods and ritual human sacrifice in the evolution of large, stratified societies. These analyses show that, although the presence of Big Gods is correlated with the evolution of political complexity, in Austronesian cultures at least, they do not play a causal role in ratcheting up political complexity. In contrast, ritual human sacrifice does play a causal role in promoting and sustaining the evolution of stratified societies by maintaining and legitimizing the power of elites. We briefly discuss some common objections to the application of phylogenetic modeling to cultural evolution and argue that the use of these methods does not require a commitment to either gene-like cultural inheritance or to the view that cultures are like vertebrate species. We conclude that the careful application of these methods can substantially enhance the prospects of an evolutionary science of human history. cultural evolution | macroevolution | phylogenetics | religion | Big Gods D arwin's On the Origin of the Species ends with the poetic phrase, "From so simple a beginning endless forms most beautiful and most wonderful have been, and are being, evolved" (1). The central challenge for evolutionary biology is to explain this diversity of endless forms. Evolutionary biologists tackle this task by studying both microevolution (changes in gene frequency within a population) and macroevolution (changes between species over much longer time periods). The aim is to have a mechanistic understanding of the evolution of biological diversity that integrates microlevel processes and macrolevel patterns. This work examines ways in which evolutionary thinking and methods can be extended into the realm of culture, extending the scope of biology to include questions that have traditionally been restricted to the humanities and social sciences. Human cultures also display a vast variety of most beautiful and most wonderful forms. We speak ∼7,000 different languages, engage in hundreds of different religious practices, build many different types of houses, exploit different resources for subsistence, use numerous different kinship systems, and abide by a striking array of marital, sexual, and child-rearing norms (2). The cultural processes that produce such striking cultural diversity must be explained. The field of cultural evolution is currently beginning to blossom (Fig. 1). There is a new cultural evolution society, a proposed journal, and an inaugural conference (3). However,...

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“…They propose techniques for distinguishing the two processes and conclude that, if used cautiously, cultural data can help answer questions about the location of ancestral homelands, the order of cultural divergence, factors affecting cultural rates of change, ancestral states of traits and adaptive cultural responses. Taking the discussion a step further, Greenhill et al (2009) simulate language evolution with realistic levels of borrowing, and then use phylogenetic techniques to see if they can reconstruct the history despite the presence of horizontal exchange; the answer is yes. Meanwhile, archaeologists are already using population genetic and phylogenetic approaches to learn much about the evolution of material culture and of the populations associated with these artefacts (Shennan & Wilkinson 2001;O'Brien & Lyman 2003;Bentley et al 2004;Buchanan & Collard 2007;Mesoudi & O'Brien 2008;O'Brien 2008;Hamilton & Buchanan 2009;Lycett 2009).…”

Section: Introductionmentioning

confidence: 99%

Inferring population histories using cultural data

2009

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The question as to whether cultures evolve in a manner analogous to that of genetic evolution can be addressed by attempting to reconstruct population histories using cultural data. As others have argued, this can only succeed if cultures are isolated enough to maintain and pass on a central core of traditions that can be modified over time. In this study we used a set of cultural data (canoe design traits from Polynesia) to look for the kinds of patterns and relationships normally found in population genetic studies. After developing new techniques to accommodate the peculiarities of cultural data, we were able to infer an ancestral region (Fiji) and a sequence of cultural origins for these Polynesian societies. In addition, we found evidence of cultural exchange, migration and a serial founder effect. Results were stronger when analyses were based on functional traits (presumably subject to natural selection and convergence) rather than symbolic or stylistic traits (probably subject to cultural selection for rapid divergence). These patterns strongly suggest that cultural evolution, while clearly affected by cultural exchange, is also subject to some of the same processes and constraints as genetic evolution.

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Does horizontal transmission invalidate cultural phylogenies?

Cited by 141 publications

References 51 publications

Rate of language evolution is affected by population size

Rate of language evolution is affected by population size

Cultural macroevolution matters

Inferring population histories using cultural data

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