How to interpret past human mobility patterns

celtic-europe-national-geographic

New paper (behind paywall), Interpreting Past Human Mobility Patterns: A Model, by Reiter and Frei Eur J Archaeol (2019).

Interesting excerpts (modified for clarity; emphasis mine):

Present investigations of mobility can be divided into two main groups: 1) individual mobility, and 2) group mobility.

Research approach

(…) it is arguable that, ‘the reality of a mobile existence is far more complex than the ordering principles used to describe it’ (Wendrich & Barnard, 2008: 15). It seems that the most accurate means of modelling mobility is through a thorough examination of a variety of phenomena in combination with archaeological context. Notable examples of these defining criteria include:

  1. Mobility (length of time, season);
  2. Number of journeys;
  3. Segment of the population which moved (as defined by gender, age, health, occupation, or social position);
  4. General socio-political organization;
  5. Logistics and available modes of transport.

means-identifying-individual-vs-group-mobility

In an ideal world, these five categories should be investigated via multiple samples from multiple individuals from a site, region, and culture group who represent the full gamut of ages, sexes, and social levels. Unfortunately, the fragmentary nature of the archaeological record rarely includes material suitable for covering all parameters.

A mobility model

Thirty years ago, David Anthony criticized archaeologists for their approach to migration: ‘instead of developing the needed tools, archaeologists have avoided the subject’ (Anthony, 1990: 895).

Although there are (and always will be) holes in the record, we propose a mobility model composed of four over-arching mobility patterns which we have named as follows:

NOTE. Cases explored in the paper are within brackets.

  1. Non-migratory [no mobility: The Case of Singen (Germany)];
  2. Point-to-point migratory [The Case of the Skrydstrup Woman (Denmark)];
  3. Back-and-forth [The case of Haraldskaer Woman (Denmark)];
  4. Repeated mobility, subdivided into
    • Cyclical mobility [The cases of Nieder-Mörlen (Germany) and Ötzi (Italy)]
    • Non-cyclical mobility [The cases of the medieval Silk Road, Roman York, Viking Age Trelleborg, and La Tène Bohemia]

human-mobility-model

All told, the mobility patterns identified in the present model cleave to three overarching kinds of mobility: non-mobility, single mobility/migration, and multiple movements. The causes of non-mobility and different types of mobility can be manifold.

Non-mobility may include lack of sufficient funds or surplus, social obligations, health status, age, and social standing (serf, slave, landed gentry).

Single, unidirectional movements may have been caused by marriage alliances; family movements; social, political, or economic instability; violence (enslavement, kidnapping); or health issues.

By contrast, individuals who show evidence of multiple movement were likely to have been moving because mobility formed part of their employment, beliefs (ritual), or lifestyle. Although a warrior or soldier, herder, trader, or traveller within an extensive kinship network may present very different mobility patterns, they are all unified by the fact that their chosen occupation or social group(s) exhibit some form of mobility mandate.

The causes of back-and-forth mobility are difficult to define as different reasons could spur a single to-and-from journey to a specific place of cultural, religious, or personal importance.

Repeated mobility, be it cyclical or more irregular (non-cyclical), can also be closely related to social status. For example, a peddler, small-scale trader, or migrant worker’s identity and integration (or nonintegration) into the society (or societies) with which they have contact can be defined by their transitory lifestyles. (…) both the profession and its mobile nature removed metalworkers from ‘normal’ society; in many cases, they formed a separate social category (Neipert, 2006). This could also be the case with warriors. Although contact with migratory workers or specialists was necessary for temporary collaboration, prolonged contact might involve severe social change (Neaher, 1979; Bollig, 1987).

Related

The father tongue and mother tongue hypotheses in Indo-European populations

New paper (behind paywall) Reconciling the father tongue and mother tongue hypotheses in Indo-European populations, by Zhang et al. National Science Review (2018) nwy083.

Interesting excerpts:

Here, we reassessed the correlation between genetic and linguistic characteristics in 34 modern IE populations (Fig. 1a), for which all four types of datasets (lexicon, phonemes, Y-chromosomal composition, and mitochondrial DNA (mtDNA) composition) are available. We assembled compositions of the Y-chromosomal and mtDNA haplogroups or paragroups from the corresponding IE populations, which reflect paternal and maternal lines, respectively (…)

Neighbour-Nets were constructed to delineate the differences between 34 IE population groups clustering at the genetic and linguistic levels (Fig. 2). The reticulations within each net reflect conflicting signals against tree-like structures and support incompatible groupings [21]. These structures are likely produced by potential horizontal transmissions between populations or languages such as admixture, and potential parallel evolution in linguistics as well [22]. The Neighbour-Net for Y-chromosomes with substantial reticulations shows complicated relationships among IE populations (Fig. 2a), indicating a substantial historical population contact and admixture among the males. In contrast, the Neighbour-Net for mtDNA in Fig. 2b clearly illustrates an East-West geographic polarization, indicating two major IE populations in matrilineages: Indo-Iranian and European. (…)

y-dna-mtdna-phoneme-lexicon
Neighbour-Nets of 34 Indo-European populations calculated from the Euclidean distance matrices using (a) Y-chromosomal haplogroups and (b) mtDNA haplogroups; Neighbour-Nets of IE languages calculated from the Hamming distance matrices using (c) lexicon and (d) phonemes. The colours in the legend correspond to the language groups.

The language learning by local women could constitute the reason for unbalanced correlation of mtDNA to lexicon and phonemes. Due to the social prestige of male immigrants, their local spouses have to adopt the language of their husbands and pass it to future generations [6, 10, 15]. This process is second language acquisition and easily develops language fossilization [31]. The language fossilization is a linguistic mechanism that a learner of a second language tends to preserve some linguistic features of the first language, and develops a form of inter-language [31]. Under this circumstance, women can easily replace the lexicon from another [21], but attempt to retain local accents influenced by their native language [32]. In other words, women change to adopt the same word usage as their husbands in daily life but still speak using their own pronunciation. In mixed-language marriages with these male immigrants, women prefer to pass down their inter-languages to offspring [10, 33]. As a result, it yields the correlation between mtDNA and phonemes we observed. Hence, we courageously proposed a hypothetical scenario in Indo-European populations that lexical system of language dominated by their father, while the phonemic system of language determined by their mother.

I am not a fan of this kind of statistical studies for Comparative Grammar, and there are many pitfalls just by looking at this paper superficially: use of modern languages and modern haplogroup distributions, improper classification of phonemes – as is usual in glottochronological studies – , etc… Which render their results ipso facto unacceptable.

But just yesterday I was discussing where the Copenhagen group and their fans were going to end up when Yamna samples turn out not to be the origin of haplogroup R1a-Z645 expansion, and Anthony’s proposal of a patron-client relationship came up. Since the Danish workgroup is always one step behind, such a reactionary view seems like a reasonable assumption for the future.

This mother tongue vs. father tongue theory is another good possibility for what we are going to see, then, when they use e.g. the exogamy of eastern Corded Ware groups with Yamna to explain the adoption of the language. Maybe that’s what Kristiansen’s invented Yamna → Corded Ware arrows mean… Anything to prove that Corded Ware peoples were Indo-European speakers.

Related

Close inbreeding and low genetic diversity in Inner Asian human populations despite geographical exogamy

turko-mongol-indo-iranian

Open access Close inbreeding and low genetic diversity in Inner Asian human populations despite geographical exogamy, by Marchi et al. Scientific Reports (2018) 8:9397.

Abstract (emphasis mine):

When closely related individuals mate, they produce inbred offspring, which often have lower fitness than outbred ones. Geographical exogamy, by favouring matings between distant individuals, is thought to be an inbreeding avoidance mechanism; however, no data has clearly tested this prediction. Here, we took advantage of the diversity of matrimonial systems in humans to explore the impact of geographical exogamy on genetic diversity and inbreeding. We collected ethno-demographic data for 1,344 individuals in 16 populations from two Inner Asian cultural groups with contrasting dispersal behaviours (Turko-Mongols and Indo-Iranians) and genotyped genome-wide single nucleotide polymorphisms in 503 individuals. We estimated the population exogamy rate and confirmed the expected dispersal differences: Turko-Mongols are geographically more exogamous than Indo-Iranians. Unexpectedly, across populations, exogamy patterns correlated neither with the proportion of inbred individuals nor with their genetic diversity. Even more surprisingly, among Turko-Mongols, descendants from exogamous couples were significantly more inbred than descendants from endogamous couples, except for large distances (>40 km). Overall, 37% of the descendants from exogamous couples were closely inbred. This suggests that in Inner Asia, geographical exogamy is neither efficient in increasing genetic diversity nor in avoiding inbreeding, which might be due to kinship endogamy despite the occurrence of dispersal.

Interesting excerpts:

Two cultural groups, which matrimonial systems are reported to differ, coexist in Inner Asia: Turko-Mongols are described as mainly exogamous while Indo-Iranians are thought to be mainly endogamous45. However, it is not always clear if exogamy refers to clan (ethnic) or village (geographical) exogamy. Here, we used a dataset of 16 populations representing 11 different ethnic groups from both cultural groups and we quantified geographical exogamy rates and distances in each population. Using an empirical threshold of 4 km, we confirmed that matrimonial behaviours differ as described in the literature, even though we found some exceptions: three Turko-Mongol populations (out of 14) have less than 50% exogamy, whereas one Indo-Iranian population (out of four) has more than 50% exogamy.(…).

geographic-distance-turko-mongols-indo-iranian
Geographical distances between the birth places of couples in Turko-Mongols and Indo-Iranians. The geographical distances are plotted in log scale (km). Their densities are represented by population (dashed lines) or for the Indo-Iranian and Turko-Mongol groups (solid lines). We represented the average distances within couples per population using a Kernel’s density estimate implemented in R with a smoothing bandwidth of 0.2. See Supplementary Table 1B for population codes.

An additional important result of our study is that geographical distances are not negatively correlated with inbreeding, as could have been expected under an isolation-by-distance model65. Interestingly, a recent study based on a large genealogical dataset, collected across Western Europe and North America, and including birth places information, similarly found an absence of correlation between relatedness and the distance between couples, for the cohorts born before 185066. Our analyses within present-day Turko-Mongols reveal more specifically that the structure of the relationship between geographical distance and mating choice inbreeding is not linear, but rather tends to be bell-shaped, and thus cannot be correctly assessed with a single correlation test. Indeed, descendants from parents born 4 to 40 km apart are more inbred than descendants from endogamous couples (≤4 km) or from long-range exogamous ones (>40 km). As a consequence, close inbreeding exists despite geographical exogamy, and about a third of descendants from exogamous couples are inbred.

These results, in addition to those obtained by [Kaplanis et al. 2018]66, highlight the importance of using geographic distances rather than exogamy rates to characterize the impact of exogamy on inbreeding, as already described when studying patrilocality67. Indeed, when we compare mating choice inbreeding patterns for descendants from exogamous and endogamous couples defined for thresholds of 4, 10, 20 and 30 km, we find no significant differences (for number and total length of class C-ROHs and F-Median coefficient: MWU test p-values > 0.1). We only detect significantly lower values in descendants from exogamous couples for larger distances above 40 and 50 km (p-values < 0.03).

genetic-diversity-turko-mongol-indo-iranian
Genetic diversity (A) and inbreeding patterns (B,C) within populations. Grey lines in (B) represent inbreeding values corresponding to second-cousins and first-cousins. The grey line in (C) represents the homozygosity population baseline expected under panmixia. The number of samples per population is indicated between parentheses. See Supplementary Table 1B for population codes.

Our results also challenge the intuition that exogamy necessarily increases the genetic diversity within a population and therefore reduces drift inbreeding. Indeed, we found that Turko-Mongol populations have a lower genetic diversity (as measured by the mean haplotypic heterozygosity) and more intermediate ROHs associated with drift inbreeding than those of Indo-Iranians despite higher exogamous rates. (…)

Overall, this research sheds light on mating choice preferences: we showed that two thirds of partners that have not dispersed did mate with unrelated individuals, and that drift and mating choice inbreeding is variable, even among close-by populations. We also provide new insights into the relationship between dispersal and inbreeding in humans, based on genetic data, and demonstrate that geographical exogamy is not necessarily negatively associated with mating choice inbreeding, but rather can have a more complex non-linear relationship. Contrary to the common situation in many animals, this finding suggests that Inner Asian human populations who practise exogamy at small geographical scales might be focused on alliance strategies that result in kinship endogamy. (…)

Related:

Post-Neolithic Y-chromosome bottleneck explained by cultural hitchhiking and competition between patrilineal clans

Open access study Cultural hitchhiking and competition between patrilineal kin groups explain the post-Neolithic Y-chromosome bottleneck, by Zeng, Aw, and Feldman, Nature Communications (2018).

Abstract (emphasis mine):

In human populations, changes in genetic variation are driven not only by genetic processes, but can also arise from cultural or social changes. An abrupt population bottleneck specific to human males has been inferred across several Old World (Africa, Europe, Asia) populations 5000–7000 BP. Here, bringing together anthropological theory, recent population genomic studies and mathematical models, we propose a sociocultural hypothesis, involving the formation of patrilineal kin groups and intergroup competition among these groups. Our analysis shows that this sociocultural hypothesis can explain the inference of a population bottleneck. We also show that our hypothesis is consistent with current findings from the archaeogenetics of Old World Eurasia, and is important for conceptions of cultural and social evolution in prehistory.

Relevant excerpts:

y-dna-bottleneck
Tree of Y-chromosome genotypes from samples found among cultures with hunter-gatherer subsistence, and agropastoralist subsistence. The blue background represents hunter-gatherer subsistence while the green background represents agropastoralist subsistence. Letters in red circles match individuals from sites with their archaeological context. Note that R1b-P321 is synonymous with R1b-S116. Adapted from Figs. 3, 4, 5 and 6 of Kivisild67, with addition of information from Olalde et al.64. The vertical axis represents time; the position of branch points represent the ages of branch-defining mutations, with nomenclature and age from yfull (https://www.yfull.com/tree/)

Our hypothesis explains the bottleneck as a consequence of intergroup competition between patrilineal kin groups, which caused cultural hitchhiking between Y-chromosomes and cultural groups and reduction in Y-chromosomal diversity. Competition between demes can dramatically reduce genetic diversity within a population1, especially if the population is structured such that variation is greater between demes than within demes. Culturally transmitted kinship ideals and norms can cause homophilous sorting and limit interdemic gene flow, creating homogeneous demes that differ strongly from one another. Patrilineal corporate kin groups, with coresiding male group members descending from a common male ancestor, would produce such an effect on Y-chromosomes only, as patrilineal corporate kin groups generally coexist with female exogamy40, which would homogenize the mitochondrial gene pools of different groups41,42.

With intergroup competition between patrilineal corporate kin groups, two mechanisms would operate to reduce Y-chromosomal diversity. First, patrilineal corporate kin groups produce high levels of Y-chromosomal homogeneity within each social group due to common descent, as well as high levels of between-group variation. Second, the presence of such groups results in violent intergroup competition preferentially taking place between members of male descent groups, instead of between unrelated individuals. Casualties from intergroup competition then tend to cluster among related males, and group extinction is effectively the extinction of lineages.

There is evidence that other analogous situations involving gene-culture hitchhiking in culturally-defined social groups may have affected genetic diversity. Central Asian pastoralists, who are organized into patriclans, have high levels of intergroup competition and demonstrate ethnolinguistic and population-genetic turnover down into the historical period59. They also have a markedly lower diversity in Y-chromosomal lineages than nearby agriculturalists42,60. In fact, Central Asians are the only population whose male effective population size has not recovered from the post-Neolithic bottleneck; it remains disproportionately reduced, compared to female estimates using mtDNA4. Central Asians are also the only population to have star-shaped expansions of Y-chromosomes within the historical period, which may be due to competitive processes that led to the disproportionate political success of certain patrilineal clans60.

The simulation offers an interesting graphic. I had been thinking for some time about developing an interactive image with waves of expansion showing how only few haplogroups expand and thus their variability is reduced in successive migration waves, because a lot of people seemed not to be willing to accept this:

y-dna-bottleneck-simulation
Schematic of the steps in the simulation, according to the order described in the algorithm. a (i) Patrilineal (PT) starting conditions, where cultural groups strictly determine haplogroup type. a (ii) The non-patrilineal (NPT) condition where they are perfectly uncorrelated. b The killing step, with a more (PT) and less (NPT) patrilineal starting condition. The number of deaths in each group is inversely related to group size. The blue cultural group goes extinct in both cases. This causes the haplogroup represented by the diamonds to go extinct in PT, but no haplogroup extinction occurs in NPT. c The mutation step, where a small number of individuals in the largest haplogroup change their haplogroup. d The regeneration step, where (i) is a replica of (b) PT (iii), and (d) (ii) shows how the original number of individuals before the killing step is restored by proportionally increasing the number of individuals in all cells. e Group fission step. Where an empty row occurs, the largest cultural group splits, and half the individuals form a new cultural group in the empty row. The step in which we remove cultural groups that are too small—between (c, d) (see Methods)—is not shown

You only have to imagine this process happening in many successive waves of expansion (external as well as internal to each culture) since the first Neolithic expansions in the steppe in the late-6th millennium BC, even before the formation of the Khvalynsk-Sredni Stog cultural-historical community, to understand what happened in the next thousands of years with evolving patrilineal clans and their distinct cultures.

The whole paper is an interesting read. It’s great to see sociology and genetics finally catch up and interact to develop more complex anthropological hypotheses.

The fact that this paper appears in mid-2018 and geneticists are beginning to discuss this only now when their statistical methods fail to explain the obvious (see David Reich’s recent interview) seems anachronistic, though, because all this was quite clear already in 2015 – at least for those who were looking for mainstream Yamna – Bell Beaker connections, instead of inventing new migration pathways to justify the results of certain statistical analyses

Anyway, better late than never.

Also, they use YFull estimates, which vindicates my use of them in the Indo-European demic diffusion model (2017). On the other hand, their use of these estimates right now in 2018 for R1a-M417 and R1b-M269 – when we know of a R1a-Z93 case much older than YFull’s estimated 5,000 YBP for this subclade, and possibly for R1b-L23, too, is the biggest pitfall in their temporal assessment, although the bottlenecks seen in Chalcolithic expansions seem to have indeed began during the Mesolithic-Neolithic transition in the steppe.

So, say goodbye (if you haven’t already) to dat fantasy ‘steppe people’ of mixed R1a/R1b descent cooperating with the same mixed steppe language, all represented by the Yamnaya™ ancestral component, and say hello to distinct, competing ethnolinguistic steppe groups during the Neolithic.

Related:

Immigration and transhumance in the Early Bronze Age Carpathian Basin

Interesting excerpts about local Hungarian groups that had close contacts with Yamna settlers in the Carpathian Basin, from the paper Immigration and transhumance in the Early Bronze Age Carpathian Basin: the occupants of a kurgan, by Gerling, Bánffy, Dani, Köhler, Kulcsár, Pike, Szeverényi & Heyd, Antiquity (2012) 86(334):1097-1111.

The most interesting of the local people is the occupant of grave 12, which is the earliest grave in the kurgan and the main statistical range of its radiocarbon date clearly predates the arrival of the western Yamnaya groups c. 3000 BC. This is also confirmed by the burial rite, which is not typical for the Yamnaya (Dani 2011: 29–33; Heyd in press), although some heterogeneity may apply in Yamnaya communities too. The migrant group, graves nos. 4, 7, 9 and 11, all occupy late stratigraphic positions in the mound, and have radiocarbon dates in the second quarter of the third millennium BC. It is also noteworthy that they are all adult or mature men. The contextual data, their physical distribution over the space of the whole kurgan, and the variety of burial practices, indicate several generations of burials. The cultural attributes of this group are summarised in Figure 5. Overall, their closest match lies in the Livezile group from the eastern and southern Apuseni Mountains, which is also the likely place of origin of the buried persons.

yamna-settlements-hungary
Cultural geography of the Carpathian Basin in the first half of the third millennium BC (in black: archaeological cultures and groups dating roughly to the first quarter; in red: those dating to the second quarter). Indicated also are regions and sites mentioned in the text.

The key question is, what cultural process could be responsible for attracting these men from their homeland to the Great Hungarian Plain, over several generations? Their sex and age uniformity indicate they are a social sub-set within a larger group, implying that only a portion of their society was on the move. Exogamy can probably be excluded, since one would expect more women than men to move in prehistoric times; not to mention the distance of more than 200km between the places of potential origin and burial.

One hypothesis would see these men involved in the exchange of goods, with long-term relations between the mountain and steppe communities. Normally living in, or next to, the Apuseni, these men would journey for weeks into the plain, returning to the same places and people over many decades. Ethnographic examples of such travels to exchange objects and ideas, and perhaps people, are numerous (e.g. Helms 1988). However, the child’s (grave 7a) local isotopic signature would remain unexplained, and one has to wonder for how many generations an exchange continues for four men to die near the Őrhalom.

A second hypothesis is essentially an economic model of transhumance, with livestock passing the winter and spring in the milder regions of the Great Hungarian Plain, and returning to higher pastures in the warmer months (Arnold & Greenfield 2006). Such systems can endure for centuries, provided the social relations underpinning them are stable. This has the advantage of accounting for relatively long periods of time spent away from home, as herdsmen guarded their animals, and perhaps some women and their children came too, which would account for the child’s presence, and the pottery relations of the Livezile group. Furthermore, regular visits to a region would increase the likelihood of Livezile transhumant herders becoming integrated locally. The second quarter of the third millennium BC was a period when Yamnaya ideology, and thus its internal coherence, might have already diminished. This would likely have resulted in a weakened grip by Yamnaya people on pastures and territory, consequently allowing Livezile herders, and potentially others, to step in and take over locally, perhaps first on a seasonal basis and then permanently.

On West Yamna settlers in Hungary

yamnaya-hungary-globular-amphora
Modified table from Wang et al. (2018) Supplementary materials (in bold, Yamna and related samples; in red, newly reported samples). “Supplementary Table 18. P values of rank=1 and admixture coefficients of modelling the Steppe ancestry populations as a two-way admixture of the Eneolithic_steppe and Globular_Amphora using 14 outgroups. Left populations: Steppe cluster, Eneolithic_steppe, Globular Amphora Right populations: Mbuti.DG, Ust_Ishim.DG, Kostenki14, MA1, Han.DG, Papuan.DG, Onge.DG, Villabruna, Vestonice16, ElMiron, Ethiopia_4500BP.SG, Karitiana.DG, Natufian, Iran_Ganj_Dareh_Neolithic.”

By disclosing very interesting information on (yet unpublished) Yamna samples from Hungary, the latest preprint from the Reich Lab has rendered irrelevant – in a rather surprising turn of events – (what I expected would be) future discussions on West Yamna settlers potentially sharing a similar ancestry with Baltic Late Neolithic / Corded Ware settlers (see here for more details).

Interesting excerpts regarding the tight cluster formed by all Yamna samples:

Individuals from the North Caucasian steppe associated with the Yamnaya cultural formation (5300-4400 BP, 3300-2400 calBCE) appear genetically almost identical to previously reported Yamnaya individuals from Kalmykia20 immediately to the north, the middle Volga region19, 27, Ukraine and Hungary, and to other Bronze Age individuals from the Eurasian steppes who share the characteristic ‘steppe ancestry’ profile as a mixture of EHG and CHG/Iranian ancestry23, 28. These individuals form a tight cluster in PCA space (Figure 2) and can be shown formally to be a mixture by significantly negative admixture f3-statistics of the form f3(EHG, CHG; target) (Supplementary Fig. 3).

Using qpAdm with Globular Amphora as a proximate surrogate population (assuming that a related group was the source of the Anatolian farmer-related ancestry), we estimated the contribution of Anatolian farmer-related ancestry into Yamnaya and other steppe groups. We find that Yamnaya individuals from the Volga region (Yamnaya Samara) have 13.2±2.7% and Yamnaya individuals in Hungary 17.1±4.1% Anatolian farmer-related ancestry (Fig.4; Supplementary Table 18)– statistically indistinguishable proportions.

yamna_bell_beaker
Yamna – Bell Beaker migration according to Heyd (2007, 2012)

Before this paper, we had the solidest anthropological models backed by Y-DNA against conflicting data from certain statistical tools applied to a few samples (which some used to contradict what was mainstream in Academia).

NOTE. I have discussed this extensively in this blog, and more than once. See for example my posts on R1a speaking IE (July 2017), on the Eneolithic Ukraine sample (September 2017), or on the “Yamnaya ancestral component” (November 2017).

Today, we have everything – including statistical tools – showing a genetically homogeneous, Late PIE-speaking late Khvalynsk/Yamna community expanding into its known branches, confirming what was described using traditional anthropological disciplines:

  • Late Khvalynsk expanding into Afanasevo ca. 3300-3000 BC with an archaic Late PIE dialect, which was attested much later as Tocharian;
  • East Yamna/Poltavka admixing with Uralic-speaking Abashevo migrants probably ca. 2600-2100 BC to form Proto-Indo-Iranian-speaking Sintashta-Petrovka and Potapovka;
  • and now also Yamna settlers: those in Hungary admixing (probably ca. 2800-2500 BC) with the local population to form North-West Indo-European-speaking East Bell Beakers; those from the Balkans forming other IE-speaking Balkan cultures, including the peoples that admixed in Greece, as seen in Mycenaeans.

If Volker Heyd is right with this and other papers – and he has been right until now in his predictions regarding Yamna, Bell Beaker, and Corded Ware cultures – , the change in ancestry will probably begin to be noticed in Yamna samples from Hungary and the Lower Danube during the second quarter of the 3rd millennium, a period defined by the addition of a more fashionable western Proto-Bell Beaker package to the fading traditional Yamna cultural package.

EDIT (19 MAY 2018): I corrected some sentences and added interesting information.

Related:

Modern Hungarian mtDNA more similar to ancient Europeans than to Hungarian conquerors

middle-ages-europe

New preprint at BioRxiv, MITOMIX, an Algorithm to Reconstruct Population Admixture Histories Indicates Ancient European Ancestry of Modern Hungarians, by Maroti et al. (2018).

hungarian-shared-mtDNA
The estimated age distribution of the shared mt Hgs between Hungarians (Hun), the best hypothetical admix (mixFreq) and the populations contributing to this admix: Belgian/Dutch (BeN), Danish (Dan), Basque (Bsq), Croatian/Serbian (CrS), Baltic Late Bronze Age culture (BalBA), Bell Beaker culture (BellB), Slovakian (Slo). The numbers in parentheses indicate the contributions to the best hypothetical admix.

Abstract (emphasis mine)

By making use of the increasing number of available mitogenomes we propose a novel population genetic distance metric, named Shared Haplogroup Distance (SHD). Unlike FST, SHD is a true mathematical distance that complies with all metric axioms, which enables our new algorithm (MITOMIX) to detect population-level admixture based on SHD minimum optimization. In order to demonstrate the effectiveness of our methodology we analyzed the relation of 62 modern and 25 ancient Eurasian human populations, and compared our results with the most widely used FST calculation. We also sequenced and performed an in-depth analysis of 272 modern Hungarian mtDNA genomes to shed light on the genetic composition of modern Hungarians. MITOMIX analysis showed that in general admixture occurred between neighboring populations, but in some cases it also indicated admixture with migrating populations. SHD and MITOMIX analysis comply with known genetic data and shows that in case of closely related and/or admixing populations, SHD gives more realistic results and provides better resolution than FST. Our results suggest that the majority of modern Hungarian maternal lineages have Late Neolith/Bronze Age European origins (partially shared also with modern Danish, Belgian/Dutch and Basque populations), and a smaller fraction originates from surrounding (Serbian, Croatian, Slovakian, Romanian) populations. However only a minor genetic contribution (<3%) was identified from the IXth Hungarian Conquerors whom are deemed to have brought Hungarians to the Carpathian Basin. Our analysis shows that SHD and MITOMIX can augment previous methods by providing novel insights into past population processes.

hungarian-hierarchic-cluster
Unrooted hierarchic cluster of modern and archaic populations based on the SHD matrix.

It is interesting to keep receiving data as to how language does not correlate well with Genomics, whether admixture or haplogroups, even though it is already known to happen in regions such as Anatolia, the Baltic, South-Eastern or Northern Europe.

Thorough anthropological models of migration or cultural diffusion are necessary for a proper interpretation of genetic data. There is no shortcut to that.

hungarian-mtdna
Co-occurrence of Hungarian Bronze Age mt Hgs Distribution of mt Hgs found in Hungarian Bronze Age archaic samples in the analyzed populations. The fixation dates are based on Behar et al [6].

Images made available under a CC-BY-NC-ND 4.0 International license.
See also:

Ancient Phoenician mtDNA from Sardinia, Lebanon reflects settlement, genetic diversity, and female mobility

phoenicia-settlements-genetics

New article at PLOS One, Ancient mitogenomes of Phoenicians from Sardinia and Lebanon: A story of settlement, integration, and female mobility, by Matisoo-Smith et al. (2018).

Abstract:

The Phoenicians emerged in the Northern Levant around 1800 BCE and by the 9th century BCE had spread their culture across the Mediterranean Basin, establishing trading posts, and settlements in various European Mediterranean and North African locations. Despite their widespread influence, what is known of the Phoenicians comes from what was written about them by the Greeks and Egyptians. In this study, we investigate the extent of Phoenician integration with the Sardinian communities they settled. We present 14 new ancient mitogenome sequences from pre-Phoenician (~1800 BCE) and Phoenician (~700–400 BCE) samples from Lebanon (n = 4) and Sardinia (n = 10) and compare these with 87 new complete mitogenomes from modern Lebanese and 21 recently published pre-Phoenician ancient mitogenomes from Sardinia to investigate the population dynamics of the Phoenician (Punic) site of Monte Sirai, in southern Sardinia. Our results indicate evidence of continuity of some lineages from pre-Phoenician populations suggesting integration of indigenous Sardinians in the Monte Sirai Phoenician community. We also find evidence of the arrival of new, unique mitochondrial lineages, indicating the movement of women from sites in the Near East or North Africa to Sardinia, but also possibly from non-Mediterranean populations and the likely movement of women from Europe to Phoenician sites in Lebanon. Combined, this evidence suggests female mobility and genetic diversity in Phoenician communities, reflecting the inclusive and multicultural nature of Phoenician society.

phoenician-mtdna
Haplogroup assignments, dates, locations and Genbank accession details of all aDNA samples included in analyses.

Featured image, from the article: Map showing phoenician maritime expansions across the Mediterranean starting from around 800 BCE. Arrows indicate maritime movement. Blue dots indicate coastal sites and pink shaded areas indicate the extent of Phoenician settlements. https://doi.org/10.1371/journal.pone.0190169.g001

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