Languages, like genes, provide vital clues about human history. The origin of the Indo-European language family is "the most intensively studied, yet still most recalcitrant, problem of historical linguistics". Numerous genetic studies of Indo-European origins have also produced inconclusive results. Here we analyse linguistic data using computational methods derived from evolutionary biology. We test two theories of Indo-European origin: the 'Kurgan expansion' and the 'Anatolian farming' hypotheses. The Kurgan theory centres on possible archaeological evidence for an expansion into Europe and the Near East by Kurgan horsemen beginning in the sixth millennium BP. In contrast, the Anatolian theory claims that Indo-European languages expanded with the spread of agriculture from Anatolia around 8,000-9,500 years bp. In striking agreement with the Anatolian hypothesis, our analysis of a matrix of 87 languages with 2,449 lexical items produced an estimated age range for the initial Indo-European divergence of between 7,800 and 9,800 years bp. These results were robust to changes in coding procedures, calibration points, rooting of the trees and priors in the bayesian analysis.

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...

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Many animals use tools but only humans are generally considered to have the cognitive sophistication required for cumulative technological evolution. Three important characteristics of cumulative technological evolution are: (i) the diversification of tool design; (ii) cumulative change; and (iii) high-fidelity social transmission. We present evidence that crows have diversified and cumulatively changed the design of their pandanus tools. In 2000 we carried out an intensive survey in New Caledonia to establish the geographical variation in the manufacture of these tools. We documented the shapes of 5550 tools from 21 sites throughout the range of pandanus tool manufacture. We found three distinct pandanus tool designs: wide tools, narrow tools and stepped tools. The lack of ecological correlates of the three tool designs and their different, continuous and overlapping geographical distributions make it unlikely that they evolved independently. The similarities in the manufacture method of each design further suggest that pandanus tools have gone through a process of cumulative change from a common historical origin. We propose a plausible scenario for this rudimentary cumulative evolution.

Languages, like molecules, document evolutionary history. Darwin observed that evolutionary change in languages greatly resembled the processes of biological evolution: inheritance from a common ancestor and convergent evolution operate in both. Despite many suggestions, few attempts have been made to apply the phylogenetic methods used in biology to linguistic data. Here we report a parsimony analysis of a large language data set. We use this analysis to test competing hypotheses--the "express-train" and the "entangled-bank" models--for the colonization of the Pacific by Austronesian-speaking peoples. The parsimony analysis of a matrix of 77 Austronesian languages with 5,185 lexical items produced a single most-parsimonious tree. The express-train model was converted into an ordered geographical character and mapped onto the language tree. We found that the topology of the language tree was highly compatible with the express-train model.

The relative timing and size of regional human population growth following our expansion from Africa remain unknown. Human mitochondrial DNA (mtDNA) diversity carries a legacy of our population history. Given a set of sequences, we can use coalescent theory to estimate past population size through time and draw inferences about human population history. However, recent work has challenged the validity of using mtDNA diversity to infer species population sizes. Here we use Bayesian coalescent inference methods, together with a global data set of 357 human mtDNA coding-region sequences, to infer human population sizes through time across 8 major geographic regions. Our estimates of relative population sizes show remarkable concordance with the contemporary regional distribution of humans across Africa, Eurasia, and the Americas, indicating that mtDNA diversity is a good predictor of population size in humans. Plots of population size through time show slow growth in sub-Saharan Africa beginning 143-193 kya, followed by a rapid expansion into Eurasia after the emergence of the first non-African mtDNA lineages 50-70 kya. Outside Africa, the earliest and fastest growth is inferred in Southern Asia approximately 52 kya, followed by a succession of growth phases in Northern and Central Asia (approximately 49 kya), Australia (approximately 48 kya), Europe (approximately 42 kya), the Middle East and North Africa (approximately 40 kya), New Guinea (approximately 39 kya), the Americas (approximately 18 kya), and a second expansion in Europe (approximately 10-15 kya). Comparisons of relative regional population sizes through time suggest that between approximately 45 and 20 kya most of humanity lived in Southern Asia. These findings not only support the use of mtDNA data for estimating human population size but also provide a unique picture of human prehistory and demonstrate the importance of Southern Asia to our recent evolutionary past.

A crucial stage in hominin evolution was the development of metatool use -- the ability to use one tool on another [1, 2]. Although the great apes can solve metatool tasks [3, 4], monkeys have been less successful [5-7]. Here we provide experimental evidence that New Caledonian crows can spontaneously solve a demanding metatool task in which a short tool is used to extract a longer tool that can then be used to obtain meat. Six out of the seven crows initially attempted to extract the long tool with the short tool. Four successfully obtained meat on the first trial. The experiments revealed that the crows did not solve the metatool task by trial-and-error learning during the task or through a previously learned rule. The sophisticated physical cognition shown appears to have been based on analogical reasoning. The ability to reason analogically may explain the exceptional tool-manufacturing skills of New Caledonian crows.