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Moreover, the results highlight the utility of craniometric data for assessing patterns of past population dispersal and gene flow.
Our results illustrate the utility of craniometric data for assessing past population history and highlight the importance of testing hypotheses within a population genetics framework.
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Principal components analysis of craniometric data clearly distinguishes the mid-Holocene population at Gobero (Gob-m) from all other sampled populations, including the early Holocene population at Gobero, Iberomaurusian and Capsian populations from the Maghreb, "Mechtoids" from Mali and Mauritania, as well as much older Aterian samples (Figure 6).
Based on a multivariate analysis of craniometric data Taylor et al. [ 13] included R. fuscipes and R. leucopus within a clade containing New Guinean native rat species whereas the other Australian native rat species (R. sordidus, R. tunneyi and R. lutreolus) formed a separate but deeper clade.
Here, we employed partial Mantel correlations to assess the fit of the craniometric data to the six alternative models based on a null model of geographic distance, while correcting for temporal distance.
Furthermore, the craniometric data of the Mesolithic and Neolithic skull from Southwest Asia and Europe also suggest that the spread of farming into Europe was mainly due to the active dispersal of people from Southwest Asia [ 7].
Of the alternative scenarios modelled, all variants of the continuous dispersal models were significantly correlated with the craniometric data, regardless of whether the dispersals were modelled as originating in Anatolia or in the Levant, and regardless of which geographic parameter was employed to model dispersal (500, 1000 or 1500 km).
We have already seen impressive examples for the social utility of big data, from predicting flue epidemics to diagnosing cancer.
increase the utility of the data.
However, our findings do highlight the utility of registry data.
What is clear is the utility of mutation data.
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