Historical inference is at its most powerful when independent lines of evidence can be integrated into a coherent account. Dating linguistic and cultural lineages can potentially play a vital role in the inte- gration of evidence from linguistics, anthropology, archaeology and genetics. Unfortunately, although the comparative method in historical linguistics can provide a relative chronology, it cannot provide absolute date estimates and an alternative approach, called glottochronology, is fundamentally flawed. In this paper we outline how computational phylogenetic methods can reliably estimate language divergence dates and thus help resolve long-standing debates about human prehistory ranging from the origin of the Indo-European language family to the peopling of the Pacific.

In this paper we outline two debates about the nature of human cultural history. The first focuses on the extent to which human history is treelike (its shape), and the second on the unity of that history (its fabric).

Proponents of cultural phylogenetics are often accused of assuming that human history has been both highly tree-like and consists of tightly linked lineages. Critics have pointed out obvious exceptions to these assumptions.

Instead of a priori dichotomous disputes about the validity of cultural phylogenetics phylogenies, we suggest that the debate is better conceptualized as involving positions along continuous dimensions. The challenge for empirical research is therefore to determine where particular aspects of culture lie on these dimensions.

We discuss the ability of current computational methods derived from evolutionary biology to address these questions. These methods are then used to compare the extent to which lexical evolution is treelike in different parts of the world and to evaluate the coherence of cultural and linguistic lineages.

Phylogenetic comparative methods (PCMs) provide a potentially powerful toolkit for testing hypotheses about cultural evolution. Here we build on previous simulation work by Nunn et al. (2006) to assess the effect horizontal transmission between cultures has on the ability of both phylogenetic and non-phylogenetic methods to make inferences about trait evolution.

We found that the mode of horizontal transmission of traits has important consequences for both methods. Where traits were horizontally transmitted separately PCMs accurately reported when trait evolution was not correlated even at the highest levels of horizontal transmission.

In contrast, linear regression analyses often incorrectly concluded that traits were correlated. Where simulated trait evolution was not correlated and traits were horizontally transmitted as a pair both methods showed increased levels of positive correlation with increasing horizontal transmission.

Where simulated trait evolution was correlated increasing rates of separate horizontal transmission led to decreasing levels of correlation for both methods, but that increasing rates of paired horizontal transmission did not. Furthermore, the PCM was also able to make accurate inferences about the ancestral state of traits.

These results suggest that under certain conditions PCMs can be robust to the effects of horizontal transmission. We discuss ways that future work can investigate the mode and tempo of horizontal transmission of cultural traits.

There are approximately 7000 languages spoken in the world today. This diversity reflects the legacy of thousands of years of cultural evolution. How far back we can trace this history depends largely on the rate at which the different components of language evolve. Rates of lexical evolution are widely thought to impose an upper limit of 6-10 thousand years on reliably identifying language relationships. In contrast, it has been argued that certain structural elements of language are much more stable. Just as biologists use highly conserved genes to uncover the deepest branches in the tree of life, highly stable linguistic features hold the promise of identifying deep relationships between the world’s languages.
Here we present the first global network of languages based on this typological information. We evaluate the relative evolutionary rates of both typological and lexical features in the Austronesian and Indo-European language families. The first indications are that typological features evolve at similar rates to basic vocabulary but their evolution is substantially less treelike. Our results suggest that, whilst rates of vocabulary change are correlated between the two language families, the rates of evolution of typological features and structural sub-types show no consistent relationship across families.

You can download a preprint of this paper here.

A network showing the relationships between 99 languages across the world. This network is built from structural information about language properties (phonology, morphology, grammar and lexicon). The length of the branches is proportional to the amount of divergence between the languages, and the box-like structures on the network show conflicting signal due to borrowing between languages and chance similarity.

Historical linguistics has never been particularly intimate with computers. The first wave of computational historical linguistics—lexicostatistics—was developed in the 1950s and quickly applied to language groups around the world from Indo-European to Austronesian. However, critics were quick to point out the problems caused by assuming a single constant rate of lexical replacement and repeatedly noted the erroneous results that this produced. As a consequence of these critiques lexicostatistics has been widely rejected by mainstream historical linguists. The last few years have seen a second wave of computational approaches entering historical linguistics: phylogenetic methods. These techniques, drawn from evolutionary biology, have been used to investigate some provocative and controversial claims about human prehistory. Given the combination of strong claims, new techniques, and the high-profile reporting of results, it is not surprising that these studies are often controversial. Sadly many of these criticisms are mired in misunderstanding.

Computational phylogenetic methods are not just lexicostatistics redux, but a powerful supplement to the comparative method used in historical linguistics. Here we will focus on one of the great battlegrounds between lexicostatistics and the traditional comparative method: the Austronesian language family. First, we will describe how Bayesian phylogenetic methods work, and then give a step-by-step explanation of an analysis of a large lexical dataset for 400 Austronesian languages.

Phylogenetic methods have recently been applied to studies of cultural evolution. However, it has been claimed that the large amount of horizontal transmission that sometimes occurs between cultural groups invalidates the use of these methods. Here, we use a natural model of linguistic evolution to simulate borrowing between languages. The results show that tree topologies constructed with Bayesian phylogenetic methods are robust to realistic levels of borrowing. Inferences about divergence dates are slightly less robust and show a tendency to underestimate dates. Our results demonstrate that realistic levels of reticulation between cultures do not invalidate a phylogenetic approach to cultural and linguistic evolution.

The nature of social life in human prehistory is elusive, yet knowing how kinship systems evolve is critical for understanding population history and cultural diversity. Post-marital residence rules specify sex-specific dispersal and kin association, influencing the pattern of genetic markers across populations. Cultural phylogenetics allows us to practise ‘virtual archaeology’ on these aspects of social life that leave no trace in the archaeological record. Here we show that early Austronesian societies practised matrilocal post-marital residence. Using a Markov-chain Monte Carlo comparative method implemented in a Bayesian phylogenetic framework, we estimated the type of residence at each ancestral node in a sample of Austronesian language trees spanning 135 Pacific societies. Matrilocal residence has been hypothesized for proto-Oceanic society (ca 3500 BP), but we find strong evidence that matrilocality was predominant in earlier Austronesian societies ca 5000–4500 BP, at the root of the language family and its early branches. Our results illuminate the divergent patterns of mtDNA and Y-chromosome markers seen in the Pacific. The analysis of present-day cross-cultural data in this way allows us to directly address cultural evolutionary and life-history processes in prehistory.

Phylogenetic methods have revolutionised evolutionary biology and have recently been applied to studies of linguistic and cultural evolution. However, the basic comparative data on the languages of the world required for these analyses is often widely dispersed in hard to obtain sources. Here we outline how our Austronesian Basic Vocabulary Database (ABVD) helps remedy this situation by collating wordlists from over 500 languages into one web-accessible database. We describe the technology underlying the ABVD and discuss the benefits that an evolutionary bioinformatic approach can provide. These include facilitating computational comparative linguistic research, answering questions about human prehistory, enabling syntheses with genetic data, and safe-guarding fragile linguistic information.

Phylogenetic tree thinking is beginning to revolutionise studies of linguistic and cultural evolution. However, linguistic and cultural traits are easily transmitted horizontally (“borrowed”) between cultures. Indeed, well over 95% of the words in the Oxford English Dictionary aren’t English. A loud and persistent debate has centered around the issue of borrowing and whether it invalidates cultural phylogenies or not. Here, we use a natural model of linguistic evolution to simulate borrowing between languages. The results show that tree topologies constructed with Bayesian phylogenetic methods are relatively robust to the effects of realistic levels of borrowing. Inferences about time depth are slightly less robust.