Our empirical evidence comes from the Rice Archaeological Database (RAD). The first version of this database was used for a synthesis of rice dispersal by Fuller et al. (2010), a slightly expanded dataset (version 1.1) was used to model the dispersal of rice, land area under wet rice cultivation and associated methane emissions from 5000–1000 BP (Fuller et al., 2011). The present dataset (version 2) was used in a previous analysis of the origins of rice domestication (Silva et al., 2015). The database records sites and chronological phases within sites where rice has been reported, including whether rice was identified from plant macroremains, phytoliths or impressions in ceramics. Ages are recorded as the start and end date of each phase, and a median age of the phase is then used for analysis. Dating is based on radiocarbon evidence (…)
Our approach expands on previous efforts to model the geographical origins, and subsequent spread, of japonica rice (Silva et al., 2015). The methodology is based on the explicit modelling of dispersal hypotheses using the Fast Marching algorithm, which computes the cost-distance of an expanding front at each point of a discrete lattice or raster from the source(s) of diffusion (Sethian, 1996; Silva and Steele, 2012, 2014). Sites in the RAD database are then queried for their cost-distance, the distance from the source(s) of dispersal along the cost-surface that represents the hypothesis being modelled (see Connolly and Lake, 2006; Douglas, 1994; Silva et al., 2015; Silva and Steele, 2014 for more on this approach) and, together with the site’s dating, used for regression analysis. (…)
Model and results
The ‘Inner Asia Mountain Corridor’ hypothesis (H2) therefore predicts japonica rice to arrive first in northwest India via a route that starts in the Yellow river valley, travels west via the well-known Hexi corridor, then just south of the Inner Asian Mountains and thence to India.
The results also show that the addition of the Inner Asia Mountain Corridor significantly improves the model’s fit to the data, particularly model H2 where rice is introduced to the Indian subcontinent exclusively via a trade route that circumvents the Tibetan plateau. This agrees with independent archaeological evidence that sees millets spread westwards along this corridor perhaps as early as 3000 BC (e.g. Boivin et al., 2012; Kohler-Schneider and Canepelle, 2009; Rassamakin, 1999) and certainly by 2500–2000 BC (Frachetti et al., 2010; Spengler 2015; Stevens et al., 2016), that is, in the same time frame as that predicted for rice in model H2. The arrival of western livestock (sheep, cattle) into central China, 2500–2000 BC (Fuller et al., 2011; Yuan and Campbell, 2009), and wheat, ca. 2000 BC (Betts et al., 2014; Flad et al., 2010; Stevens et al., 2016; Zhao, 2015), add evidence for the role of the Inner Asia Mountain Corridor for domesticated species dispersal in this period.
Through a combination of explicit spatial modelling and simulation, we have demonstrated the high likelihood that dispersal of rice via traders in Central Asia introduced japonica rice into South Asia. Only slightly less likely is a combination of introduction via two routes including a Central Asia to Pakistan/northwestern India route as well as introduction to northeastern India directly from China/Myanmar. However, there is a very low probability that current archaeological evidence for rice fits with a single introduction of japonica into India via the northeast. We have also simulated the minimum amount of archaeobotanical sampling from the Neolithic (to Bronze Age) period in the regions of northeastern India and Myanmar that will be necessary to strengthen support for the combined introduction (model H3) or a single Central Asian introduction (model H2).
The rapid diffusion of farming technologies in the western Mediterranean raises questions about the mechanisms that drove the development of intensive contact networks and circulation routes between incoming Neolithic communities. Using a statistical method to analyze a brand-new set of cultural and chronological data, we document the large-scale processes that led to variations between Mediterranean archaeological cultures, and micro-scale processes responsible for the transmission of cultural practices within farming communities. The analysis of two symbolic productions, pottery decorations and personal ornaments, shed light on the complex interactions developed by Early Neolithic farmers in the western Mediterranean area. Pottery decoration diversity correlates with local processes of circulation and exchange, resulting in the emergence and the persistence of stylistic and symbolic boundaries between groups, while personal ornaments reflect extensive networks and the high level of mobility of Early Neolithic farmers. The two symbolic productions express different degrees of cultural interaction that may have facilitated the successful and rapid expansion of early farming societies in the western Mediterranean.
Our results shed light on the cultural mechanisms responsible for the complex cultural geography of the western Mediterranean during the transition to farming. Pottery decorations participated in restrained networks in which geographical proximity and local processes of transmission played an influential role. Bead-type associations were used to tell multiple stories about social identities, were especially resistant to change and are characterized by a greater stability through time and space. The high level of cultural connection between the early farming communities favored movement, interaction and exploration and likely represented a successful strategy for their rapid expansion in the western Mediterranean. Cultural boundaries persisted despite a flow of individuals and symbolic transfer across them.
Genetic studies indicate that the last foragers and the first farmers developed social and cultural relationships more closely tied than previously indicated through components of the material culture . Biological data and chronological models support a pattern of diffusion implying geographically discontinuous contacts between local foragers and incoming farmers, but repeated in time [9,140,141]. This process of diffusion conjointly occurred with changes in material culture, including pottery decorations and personal ornaments. Pottery production represents a technological innovation mostly associated with the Neolithic way of life in the western Mediterranean. Pottery decorations were likely particularly sensitive to interactions, leading to their high variability in time and space in order to reinforce group membership. Conversely, personal ornaments were less inclined to change in space and time. Their production by both local foragers and incoming farmers implies different cultural readjustments that led to a completely different pattern of variation in time and space.The preservation of the foragers’ personal ornament styles (and likely also meanings) within emerging farming communities [20,58] has probably contributed to the maintenance of their stability through time and space.
The two symbolic productions appear as a polythetic set of cultural behaviors dedicated to mediating early farmer identities in many ways, and personal ornaments likely reflected the most entrenched and lasting facets of farmers’ ethnicity.
This research is similar to the recent one by Kılınç et al. (2018) studying the same processes initially in Anatolia and the Aegean. With this one it may also be concluded that Archaeology is necessary to assess meaningful cultural (and thus potential ethnolinguistic) change, beyond gross genetic inflows, even in the case of the Near Eastern farmer expansion waves.
Supervised clustering or projection analysis is a staple technique in population genetic analysis. The utility of this technique depends critically on the reference panel. The most commonly used reference panel in the analysis of ancient DNA to date is based on the Human Origins array. We previously described a larger reference panel that captures more ancestries on the global level. Here, I reanalyzed DNA data from 279 ancient Eurasians using our reference panel, finding substantially more ancestral heterogeneity than has been reported. This reanalysis provides evidence against a resurgence of Western hunter-gatherer ancestry in the Middle to Late Neolithic and evidence for a common ancestor of farmers characterized by Western Asian ancestry, a transition of the spread of agriculture from demic to cultural diffusion, at least two migrations between the Pontic-Caspian steppes and Bronze Age Europe, and a sub-Saharan African component in Natufians that localizes to present-day southern Ethiopia.
Excerpt (emphasis mine)
Early to Middle Bronze Age Steppe Peoples
Third, we considered the Eurasian steppe peoples (See figure). The Eneolithic Samara sample had 64.4% Northern European, 18.2% Southern Asian, 8.8% Circumpolar, 4.3% Amerindian, and 4.3% Southern European ancestries. The 27 Early to Middle Bronze Age steppe individuals (Yamnaya from Kalmykia, Yamnaya from Samara, Afanasievo, Poltavka, and Potapovka) averaged 54.7% Northern European, 27.8% Southern Asian, 7.9% Southern European, 4.7% Kalash, 4.2% Amerindian, and 0.8% Western Asian ancestries. We included the Potapovka sample here because the sum of absolute differences in ancestry was greater post-Potapovka rather than post-Poltavka. The increases in Southern Asian and Southern European ancestries do not fit with a European hunter-gatherer source and more broadly do not fit with any of the samples, suggesting an unknown source population. Currently, Southern Asian ancestry co-localizes with Y DNA haplogroup L and correlates with Indo-Iranian languages.
Although there are no L haplogroups in any of these Early to Middle Bronze Age steppe individuals, the correlation with Indo-Iranian languages strengthens the connection between Early to Middle Bronze Age steppe peoples and the introduction of Indo-European languages into Europe. In the Early to Middle Bronze Age steppe peoples, 83.3% of Y DNA haplogroups were R1b and 85.2% of mitochondrial haplogroups were H, J, T, or U. Thus, Northern European ancestry was primarily associated with R1b in these peoples, rather than with I2 as in the European hunter-gatherers, while the mitochondrial lineages were more diverse than in the European hunter-gatherers but less diverse than in the Early Neolithic peoples.
It is an interesting new approach, in that it takes into account more than just adxmiture components and PCA to assess ancestral populations.
As simplistic and wrong some conclusions may seem from your point of view, you have to take into account what Iain Mathieson had to (sadly) expressly state recently:
Beginning with the new year, I wanted to commit myself to some predictions, as I did last year, even though they constantly change with new data.
I recently read Proto-Indo-European homelands – ancient genetic clues at last?, by Edward Pegler, which is a good summary of the current state of the art in the Indo-European question for many geneticists – and thus a great example of how well Genetics can influence Indo-European studies, and how badly it can be used to interpret actual cultural events – although more time is necessary for some to realize it. Notice for example the distribution of ‘Yamnaya’ in 3000 BC, all the way to Latvia (based on the initial findings of Mathieson et al. 2017), and the map of 2000 BC with ‘Corded Ware’, both suggesting communities linked by admixture and unrelated to actual cultures.
Some people – especially those interested in keeping a simplistic picture of Europe, either divided into admixture groups or simplistic R1b-Vasconic / R1a-Indo-European / N1c-Uralic (or any combination thereof) – want (others) to believe that I am linking ‘Indo-Europeans’ with haplogroup R1b. That is simply not true. In fact, my model dismisses such simplistic identifications of the reconstructible proto-languages with any modern peoples, admixtures, or haplogroups.
The beauty of the model lies, therefore, precisely in that if you take any modern group speaking Indo-European languages, none can trace back their combination of language, admixture, and/or haplogroup to a common Indo-European-speaking people. All our ancestral lines have no doubt changed language families (and indeed cultures), they have admixed, and our European regions’ paternal lines have changed, so that any dreams of ‘purity’ or linguistic/cultural/regional continuity become absurd.
That conclusion, which should be obvious to all, has been denied for a long time in blogs and forums alike, and is behind the effort of many of those involved in amateur genetics.
Main linguistic aim
The main consequence of the model, as the title of the paper suggests, is that reconstructible Indo-European proto-languages expanded with people, i.e. with actual communities, which is what we can assert with the help of Genomics. From a personal (or ethnic, or political) point of view genomics is useless, but from an anthropological (and thus linguistic) point of view, genomics can be a very useful tool to decide between alternative models of language diffusion, which has given lots of headaches to those of us involved in Indo-European studies.
The demic diffusion theory for the three main stages of the proto-language expansion was originally, therefore, a dismissal of impossible-to-prove cultural diffusion models for the proto-language – e.g. the adoption of Late Proto-Indo-European by Corded Ware groups due to a patron-client relationship (as proposed by Anthony), or a long-lasting connection between cultures (as proposed by Kristiansen, and favoured by “constellation analogy” proponents like Clackson, who negated the existence of common proto-languages). It also means the acceptance of the easiest anthropological model for language change: migration and – consequently – replacement.
Before the famous 2015 papers (and even after them, if we followed their interpretation), we were left to wonder why the supposed vector of expansion of Indo-European languages, Corded Ware migrants – represented by R1a-Z645 subclades, and supposedly continued unchanged into modern populations in its ‘original’ ancestral territories, Balto-Slavic and Indo-Iranian – , were precisely the (phonetically) most divergent Indo-European languages – relative to the parent Late Indo-European proto-language.
My paper implied therefore the dismissal of an unlikely Indo-Slavonic group, as proposed by Kortlandt, and of a still less factible Germano-Slavonic, or Germano-Indo-Slavonic (?) group, as loosely implied by some in the past, and maybe supported in certain archaeological models (viz. Kristiansen or partially Anthony), and presently by some geneticists since their simplistic 2015 papers on “massive migrations from the steppe“, and amateur genetic fans with infinite pet theories, indeed.
A common Corded Ware substrate to Balto-Slavic and Indo-Iranian, and common also partially between Balto-Slavic and Germanic (as supported by Kortlandt, too, albeit with different linguistic connotations), would explain their common features. The Corded Ware culture (and Uralic, tentatively proposed by me as the group’s main language family) is a strong potential connection between them, further supported by phylogeography, too.
Interpretations in my paper help thus dismiss the simplistic Yamna -> Corded Ware -> Bell Beaker migration model implied with phylogeography in the 2000s, and revived again by geneticists and Kristiansen’s workgroup based on the famous 2015 papers, whereby – due to the “Yamnaya ancestral component” – the Yamna culture would have been composed of communities of R1a-M417 and R1b-M269 lineages which remained against all odds ‘related but separated’ for more than two thousand years, sharing a common unitary language (why? and how?), and which expanded from Yamna (mainly R1b-L23) into Corded Ware (mainly R1a-M417) and then into Bell Beaker (mainly R1b-L51), in imaginary migration waves whose traces Archaeology has not found, or Anthropology described, before.
While phylogeography (especially the distribution of ancient samples of certain R1b and R1a subclades) was the main genetic aspect I used in combination with Archaeology and Anthropology to challenge the reliability of the “Yamnaya ancestral component” in assessing migrations – and thus Kristiansen’s now-popular-again modified Kurgan model – , my main aim was to prove a recent expansion of Late Proto-Indo-European from the steppe, and a still more recent expansion of a common group of speakers of North-West Indo-European, the language ancestral to Italo-Celtic, Germanic, and probably Balto-Slavic (or ‘Temematic’, the NWIE substrate of Balto-Slavic, according to some linguists).
My arguments serve for this purpose, and modern distributions of haplogroups or admixture are fully irrelevant: I am ready to change my view at any time, regarding the role of any haplogroup, or ancestral component, archaeological data, or anthropological migration model, to the extent that it supports the soundest linguistic model.
Gimbutas’ old theory of sudden and recent expansion served well to support a real community of Proto-Indo-European speakers, as did later the Yamna -> Corded Ware -> Bell Beaker theory that circulated in the 2000s based on modern phylogeography, and as did later partially Anthony’s updated steppe theory (2007). On the other hand, Kristiansen’s long-lasting connections among north-west Pontic steppe cultures and Globular Amphorae and Trypillian cultures, did not fit well with a close community expanding rapidly – although recent genetic data on Trypillia and Globular Amphorae might be compelling him to improve his migration theory.
So, if data turns out to be not as I expect now, I will reflect that in future versions of the paper. I have no problem saying I am wrong. I have been wrong many times before, and something I am certain is that I am wrong now in many details, and I am going to be in the future.
If, for example, R1b-L23(xZ2105) is demonstrated to come from Hungary and not the steppe (as supported by Balanovsky) or R1a-M417 samples are proved to have expanded with West Yamna settlers (as recently proposed by Anthony, see below the Balto-Slavic question), I would support the same model from a linguistic point of view, but modified to reflect these facts. Or if a direct migration link is found in Archaeology from Yamna to Corded Ware, and from Corded Ware to Bell Beaker (as proposed in the 2015 papers), I will revise that too (again, see the image below). Or, if – as Lazaridis et al. (2017) paper on Minoans and Mycenaeans suggested – the Anatolian hypothesis (that is, one of the multiple ones proposed) turns out to be somehow right, I will support it.
Haplogroups are the least important aspect of the whole model, they are just another data that has to be taken into account for a throrough explanation of migrations. It has become essential today because of the apparent lack of vision on the part of geneticists, who failed to use them to adjust their findings of admixture with findings of haplogroup expansions, favouring thus a marginal theory of long-lasting steppe expansion instead of the mainstream anthropological models.
Since many of these alternative scenarios seem less and less likely with each new paper, it is probably more efficient to talk about which developments are most likely to challenge my model.
My main predictions – based mostly on language guesstimates, archaeological cultures, and anthropological models of migration -, even with the scarce genomic data we had, have been proven right until know with new samples from Mathieson et al. (2017) and Olalde et al. (2017), among other papers of this past year. These were my original assumptions:
(1) A Middle Proto-Indo-European expansion defined by the appearance of steppe ancestry + reduction in haplogroup diversity and expansion of (mainly) R1b-M269 and R1b-L23 lineages;
The expansion of Corded Ware peoples, associated with steppe ancestry + reduction in haplogroup diversity and expansion of (mainly) R1a-Z645 subclades, represents thus a different migration, which is compatible with the different nature of the Corded Ware culture, unrelated to Yamna and without migration waves from one to the other (although there were certainly contacts in neighbouring regions).
As you can see, neither of the 3+1 expansion models imply that no other haplogroup can be found in the culture or regions involved (others have in fact been found, and still the models remain valid): these migrations imply a reduction of haplogroup diversity, and the expansion of certain subclades as is common in population expansions throughout history. While we all accept this general idea, some people have difficulties accepting just those cases not compatible with their dreams of autochthonous continuity.
Nevertheless, there are still voids in genetic investigation.
In my humble opinion, these are potential conflict periods and the most likely areas of change for the future of the theory:
1. When and how did R1b-M269 lineages become “chiefs” in the steppe?
Based on scarce data from Khvalynsk, it seems that during the Neolithic there were many haplogroups in the North Pontic and North Caspian steppes. A reduction to R1b-M269 subclades must have happened either just before or (as I support) during (the migrations that caused) the Suvorovo-Novodanilovka expansion among Sredni Stog, probably coinciding also with the expansion (or one of the expansions) of CHG ancestry (and thus the appearance of ‘Steppe component’ in the steppe). My theory was based initially on Anthony’s account and TMRCA of haplogroups of modern populations (both ca. 4200-4000 BC), but recent samples of the Balkans (R1b-M269 and steppe ancestry) seem to trace the population expansion some centuries back.
If my assessment is correct, then modern populations of haplogroup R1b-M269* and R1b-L23* in the Balkans probably reflect that ancient expansion, and samples related to Proto-Anatolian cultures in the Balkans will most likely be of R1b-M269 subclades and R1b-L23*. After admixture in the Balkans, posterior migrations of Anatolian languages into Anatolia might be associated with a different admixture component and haplogroups, we don’t have enough data yet.
If the haplogroup reduction and expansion in Khvalynsk happened later than the Suvorovo-Novodanilovka expansion, then we might find the expansion of Pre- or Proto-Anatolian associated with many different haplogroups, such as R1b (xM269), R1a, I, J, or G2, and more or less associated with steppe ancestry in the Balkans.
Another reason for finding such variety of haplogroups in ancient samples from the Balkans would be that this Khvalynsk group of “chiefs” traversed – and mixed with – the Sredni Stog population. Nevertheless, if we suppose homogeneity in haplogroups in Khvalynsk during the expansion, a high proportion of different haplogroups explained by admixture with the local population of Sredni Stog would challenge the whole “chief domination” explanation by Anthony, and we would have to return to the “different culture” theory by Rassamakin and potentially an older migration from Khvalynsk. In any case, both researchers show clear links of the Suvorovo-Novodanilovka phenomenon to Khvalynsk, and a differentiation with the surrounding Sredni Stog culture.
A less likely model would support the identification of the whole Eneolithic Pontic-Caspian steppe as a loose Indo-Hittite-speaking community, which would be in my opinion too big a territory and too loose a cultural bond to justify such a long-lasting close linguistic connection. This will probably be the refuge of certain people looking desperately for R1a-IE connections. However, the nature of the western steppe will remain distinct from Late Proto-Indo-European, which must have developed in the Yamna culture, so autochthonous continuity is not on the table anymore, in any case…
2. How did R1a-M417 (and especially R1a-Z645) haplogroups came to dominate over the Corded Ware cultures?
If I am right (again, based on TMRCA of modern populations), then it is precisely at the time of the potential expansion of Proto-Corded Ware from the Dnieper-Dniester forest, forest-steppe, and steppe regions, ca 3300-3000. Furholt’s recent radiocarbon analysis and suggestions of a Lesser Poland origin of the third or A-horizon, on which disparate archaeologists such as Anthony or Klejn rely now, seem to suggest also that Corded Ware was a cultural complex rather than a compact culture reflecting a migration of peoples – similar thus to the Bell Beaker complex.
This cultural complex interpretation of Corded Ware contrasts with the quite homogeneous late samples we have, suggesting clear migration waves in northern Europe, at least at some point in time, so Genomics will be a great tool to ascertain when and from where approximately did Corded Ware peoples expand. Right now, it seems that Eneolithic Ukraine populations are the closest to its origin, so the traditional interpretation of its regional origin by Kristiansen or Anthony remains valid.
3. How was Indo-Iranian adopted by Corded Ware invaders?
As for what some Indians – and other people willing to confront them – are looking for, regarding R1a-M417 and/or Indo-European origins in India, I don’t see the point, we already know a) that the origin of the expansion is in the steppe and b) that Hindu nationalist biggots will not accept results from research that oppose their views. I don’t expect huge surprises there, just more fruitless discussions (fomented by those who live from trolling or conspiracies)…
4. Yamna settlers from Hungary
Anthony’s new theory – and the nature of Balto-Slavic – hinges on the presence of R1a-M417 subclades (associated with later Corded Ware samples) in Yamna settlers of Hungary, potentially originally from the North Pontic area, where the oldest sample has been found.
My ‘modified’ version of Anthony’s new model (the only I deem just remotely factible) includes the expansion of a Proto-Corded Ware from Lesser Poland, but (given the overwhelming R1b found in East Bell Beaker), with R1a-M417 being associated with the region. How to explain this language change with objective data? Well, we have Bell Beaker expanding to these areas at a later time, so we would need to find R1b-L23 settlers in Lesser Poland, and then a resurge of R1a-M417 haplogroup. If not, resorting yet again to cultural diffusion Yamna “patrons” to Corded Ware “clients” of Lesser Poland would bring us to square one, now with the ‘steppe ancestry’ controversy included…
Since some Eastern Europeans are (for no obvious reason whatsoever) putting their hopes on that IE-R1a-CWC association, let’s hope some samples of R1a-M417 in Yamna or Hungary give them a break, so that they can begin accepting something closer to mainstream anthropological models. We could then work from there a Yamna-> Bell Beaker / North-West Indo-European association truce, and from there keep accepting that no single haplogroup from Yamna settlers is linked with modern languages, cultures or ethnic groups.
5. How and when was Balto-Slavic associated with haplogroup R1a?
On the other hand, if it is a Northern dialect related closely to Germanic and Italo-Celtic (in a North-West Indo-European group), then its origin has to be found in the initial expansion of East Bell Beakers, and its development into either the Únětice culture (of Balkan and thus potentially “Southern IE” influence), or the Mierzanowice-Nitra culture (of Corded Ware and thus potentially Uralic influence), or maybe from both, given the intermediate substrate found in Germanic and Balto-Slavic.
It is my opinion that the association of Balto-Slavic with haplogroup R1a is quite early after the East Bell Beaker expansion, probably initially with the subclade typically associated with West Slavic, R1a-M458. I have not much data to support this (apart from the most common linguistic model), just modern haplogroup distribution maps and common TMRCA, and highly hypothetical archaeological-anthropological models. Genetics will hopefully bring more data.
Let’s see also what information on ancient haplogroups we can obtain from the Tollense valley (already showing a close cluster with modern West Slavic populations) and steppe regions.
The expansion of Celtic seems to be associated with chiefdoms, untraceable today in terms of haplogroups, and it seems thus different from previous expansions. New studies might tell how that happened, if it was actually in successive ways, as proposed, or maybe we don’t have enough data yet to reach conclusions.
We don’t know either how Italic expanded into the Italian Peninsula, or whether Latin expanded with peoples from Italy, if at all, or it was mostly a cultural diffusion event, as it seems.
Regarding Etruscan, while I think it is a controversy initiated based on fantastic accounts, and ignited with few finds of Middle Eastern ancestry (that seem logical from the point of view of regional contacts), it will be important for Italian linguists and archaeologists, also to accept the most likely scenario.
NOTE: Although mostly unrelated, linguistic questions may also be somehow altered with a change of migration models. For example, our current Corded Ware Substrate Hypothesis – strongly contested by Kortlandt and others – implies that Uralic was potentially the language spoken by Eneolithic Ukraine / Proto-Corded Ware peoples, therefore early Uralic languages were spoken by Corded Ware peoples, as a substrate for Germanic and Balto-Slavic, and Balto-Slavic and Indo-Iranian. If an Indo-Hittite branch different from Late PIE is accepted for Eneolithic Ukraine (thus suggesting a millennia-long cultural-historical community in the steppe), then the model still stands (e.g. Ger. and BSl. *-mos/-mus, as stated by Kortlandt, would correspond to the oldest morphological IE layer). As you can read in the different versions of our model, the different possibilities for the common substrate are stated, and the most likely one selected. But the most likely a priori option sometimes turns out to be wrong…
NOTE 2: You can comment whatever you want here, but I opened a specific thread in our forum if you want serious comments on the model to stuck and be further discussed.
How do migration and acculturation affect within- and between-group cultural variation? Classic models from population genetics show that migration rapidly breaks down between-group genetic structure. However, in the case of cultural evolution, migrants (or their children) can acculturate to local cultural behaviors via social learning processes such as conformity, potentially preventing migration from eliminating between-group cultural variation. To explore this verbal claim formally, here I present models that quantify the effect of migration and acculturation on between-group cultural variation, first for a neutral trait and then for an individually-costly cooperative trait. I also review the empirical literature on the strength of migrant acculturation. The models show that surprisingly little conformist acculturation is required to maintain plausible amounts of between-group cultural diversity. Acculturation is countered by assortation, the tendency for individuals to preferentially interact with culturally-similar others. Cooperative traits may also be maintained by payoff-biased social learning but only in the presence of strong sanctioning institutions. While these models provide insight into the potential dynamics of acculturation and migration in cultural evolution, they also highlight the need for more empirical research into the individual-level learning biases that underlie migrant acculturation.
Included is my first sketch of the genetic history of Europe, as I interpret it in light of Genetic research (especially from outputs of qpGraph published to date), but also Archaeology (and, to some extent, Linguistics).
I have also taken this opportunity to upload some drafts I had been preparing in September while working on the Third Edition, that I have sadly not been able to complete as I would have wanted to. The drafts are posted in the section Human Ancestry. I post them as they are, in the hope that they can help others.
Indonesia, an island nation as large as continental Europe, hosts a sizeable proportion of global human diversity, yet remains surprisingly under-characterized genetically. Here, we substantially expand on existing studies by reporting genome-scale data for nearly 500 individuals from 25 populations in Island Southeast Asia, New Guinea and Oceania, notably including previously unsampled islands across the Indonesian archipelago. We use high-resolution analyses of haplotype diversity to reveal fine detail of regional admixture patterns, with a particular focus on the Holocene. We find that recent population history within Indonesia is complex, and that populations from the Philippines made important genetic contributions in the early phases of the Austronesian expansion. Different, but interrelated processes, acted in the east and west. The Austronesian migration took several centuries to spread across the eastern part of the archipelago, where genetic admixture postdates the archeological signal. As with the Neolithic expansion further east in Oceania and in Europe, genetic mixing with local inhabitants in eastern Indonesia lagged behind the arrival of farming populations. In contrast, western Indonesia has a more complicated admixture history shaped by interactions with mainland Asian and Austronesian newcomers, which for some populations occurred more than once. Another layer of complexity in the west was introduced by genetic contact with maritime travelers from South Asia and strong demographic events in isolated local groups.
Among its results (emphasis is mine):
Most eastern Indonesian populations show traces of admixture that appear to reflect an expansion of AN speakers (Figure 4B, S3). There is a striking similarity between inferred events – each admixed population includes both a Philippine non-Kankanaey and western Indonesian-like source likely representing Holocene movements of Asian farming groups, as well as a Papuan-like source representing local indigenous ancestry. One reason for the lack of clear Taiwanese sources may be because the aboriginal populations of Taiwan were heavily affected by post-AN movements from mainland East Asia, most recently sinicization by Han Chinese, and thus no longer depict the ancestral AN gene pool (Mörseburg, et al. 2016). However, this notable pattern could equally be explained by the dominance of language and culture transfers during early phases of the Neolithic expansion from Taiwan into the Philippines, followed by people with predominantly Philippine ancestry driving later demic diffusion into the Indonesian archipelago. Interestingly, Mörseburg, et al. (2016), by using a different sample set and genotype-based analytical toolkit, indicated that the Kankanaey ethnic group from the Philippines is likely the closest living proxy of the source population that gave rise to the AN expansion. We did not detect this population among sources of admixture in eastern Indonesia, and therefore suggest that the place of individual Philippine groups in the AN expansion needs to be further addressed by better sampling in the Philippine archipelago.
Sumba and Flores, the two westernmost islands to the east of Wallace’s line, display a high proportion of Java and Bali surrogates in their AN admixing source. This suggests that the AN movement into eastern Indonesia, especially for Sumba and Flores, had earlier experienced some degree of genetic contact with western Indonesian groups. In contrast, the sources of AN admixture in Lembata, Alor, Pantar and Timor are dominated by Sulawesi (Figure 4B, S3, Table S3, S5). This generally agrees with expectations from the geography of the region, whereby AN groups exiting the southern Philippines were likely funneled into at least two streams, including a western path through Borneo and a central path through Sulawesi (Blust 2014).
Point estimates of genetic admixture times in eastern Indonesia lie within a narrow timeframe ranging between ca 185 BCE to 360 CE or 75 to 56 generations ago (95% CI 510 BCE – 475 CE or 87–52 generations) (Figure 4B, Table S3). These inferred dates are younger than some previous estimates (120–200 generations ago) (Xu, et al. 2012; Sanderson, et al. 2015; Sedghifar, et al. 2015). A major analysis of admixture in Indonesia estimated the date of AN contact in the eastern part of archipelago to be around 500 to 600 CE (ca 50 generations, CI estimates between 58–42 generations ago) (Lipson, et al. 2014), surprisingly young given the archaeological evidence. However, the study pooled a very small sample of genetically heterogeneous eastern Indonesian islands including, for example, Flores and Alor. As we show here (Figure 2, 4, 5, S3, Table S3, S5, S6), while the wave of AN speakers left a common genetic trace across the whole of eastern Indonesia, the details and dates of this contact vary considerably not only between islands (e.g., Flores and Alor), but also within individual islands (e.g., Flores Rampasasa vs. Flores Bama). The genetic dates, which were obtained here by denser geographical sampling of 8 eastern islands, a much larger number of individuals (28 per island on average) and a greater number of SNPs, are up to 30 generations older, predating the Common Era in many cases.
It therefore took migrants at least half a millennium to proceed from islands around Wallace’s line to the easternmost sampled part of eastern Indonesia. Nevertheless, observed dates for AN contact in eastern Indonesia are still approximately a millennium younger than the earliest Neolithic archaeological evidence in the region, and two explanations seem most likely here. First, the AN migration may have involved several waves of people leaving Taiwan, spanning multiple generations, which would bias date estimates later than the first arrival of the Neolithic archeological assemblage (Sedghifar, et al. 2015). Second, there may have been a substantial time gap between the spread of culture and technological traditions, and the beginning of extensive genetic contact between incoming farming groups and native inhabitants in Indonesia (Lansing, et al. 2011). The lack of considerable admixture with Papuan groups was recently noted in ancient Lapita individuals from Remote Oceania, whose genomes are mostly Asian and carry little to no Papuan ancestry, suggesting limited contact as they moved through Melanesia to previously uninhabited islands in the Pacific (Skoglund, et al. 2016). A lag in admixture between local and incoming Neolithic groups has also been observed in Europe, where hunter-gatherer and farming populations initially co-existed for nearly a thousand years without substantial genetic interaction (Malmström, et al. 2015).
Ancestral genomic components in regional populations. For every K, the modal solution with the highest number of ADMIXTURE runs is shown; individual ancestry proportions were averaged across all runs from the same mode and the number of runs (out of 50) assigned to the presented solution is shown in parentheses. Average cross validation statistics were calculated across all runs from the same mode (insert). The minimum cross-validation score is observed at K=9. Note major ancestry components in Indonesia and ISEA – Papuan (light purple), mainland Asian (light yellow) and AN (light blue) – as well as major differences in the distribution of these three ancestries between eastern and western Indonesia. Populations from the Philippines and Flores are abbreviated as ‘Ph.’ and ‘Fl.’, respectively.
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