It is quite clear how our present is shaped by the recent Prehistory. Today, most of our present socio-economic politics are grounded on a Neolithic way of living (demography, production, ownership, residential mobility, etc.); human images, extremely rare during Paleolithic, spread during Neolithic times and represent today our main subject of interest; most of modern Europeans belong to the haplogroup H (ca 40%) inherited partly from Middle and Late Neolithic migrations; etc. Investigations on gene-culture coevolution have become a major issue of prehistoric studies. Until recently, narratives on ancient societies were the prerogative of archaeologists and prehistorians but the development of ancient DNA (aDNA), haplogroup (hg) studies, isotopes analysis, paleoenvironmental and climatic sciences have opened a fertile dialogue about the recognition of ancient cultures, their interactions, their environmental adaptation and their evolution. To this day, gene-culture coevolution studies benefit from a large amount of data and models yearly renewed or refined (e.g. hg characterizations, climatic models, radiocarbon calibration curves and dating) stored in databases or in scientific publications. Prehistory itself has evolved by integrating these scientific advances and by giving more importance to databases, statistics and spatial analysis. This situation permits to go further in the study of forces (genetic, cultural, environmental) that shape our modern societies.
On the base of single-nucleotide polymorphisms (SNPs) study, the neutral hypothesis (H0, i.e. a population continuity with few random genetic drifts) can be rejected (H1 accepted) and factors like mutation, selection and migration can be supposed. At the time scale we investigate (Recent Prehistory), only the migration factor could explain observed significant changes in the genetic of populations. Differences between populations can be detected by different means but the determination of groups (e.g. indigenous, immigrants) is mostly based on the study of the SNPs or discrete haplogroup (hg) frequencies [11]. Each individual belongs to a hg. Individual sharing a common hg have also a common ancestor. Genetic traits are considered in terms of presence/absence, relative quantities and correlations of hg. A hg can be shared (in different proportions), or not, by different groups (see here). The R packages ape and pegas, among others, permit to perform analysis of Molecular Variance (AMOVA), genetic mapping (e.g. phylogenetic trees, haplotype network, median-joining network) and cluster analysis (multidimensional scaling, dendrogram, etc.)
To describe gene-culture coevolution, two global dimensions of social groups can be distinguished: its genetic identity ('Who ?') and its cultural identity ('What ?')
The identity of a social group is the conjunction of its cultural and genetic identities. In traditional societies, the language barrier and the cost of transport are the main factors to explain why genetic and cultural transmissions are mostly vertical (between generations, on the spot). Over time, autocorrelations appear between genetics, culture and geography, for example:
- a new generation inherits its parents' language (mother tongue) as it inherits its genes; two populations are all the more genetically similar they are geographically close
- the geographical extension of a social group is the area where the association of its genetic and cultural traits is higher than anywhere outside this area
- genetic and cultural distances between social groups will be all the more important as these groups are separated by time and space
- etc.
The map of present European nations is also the map of their genomic proximities [1]: there are generally gradual differences (i.e. linear gradient) between neighboring countries in terms of: genetics, languages, kinship systems, etc. This 'continuity principle' permits to ground gene-culture coevolution studies on parsimonious models: tendencies (i.e. mean, median, standard deviations) of cultural and genetic traits, community detetction population continuity, spatial friction, cultural consensus theories, seriations, etc. Exceptions to this 'continuity principle' are very few. Maybe the Basque population should be the best example [2]. Beside the importance of vertical transmission, some horizontal transmissions could have been major triggers of social changes. In this way, diffusion and adoption of innovations, with its new animal breeds, vegetal landraces, weaving or ploughing techniques, prestigious goods, etc., are only the most visible. All along the Neolithic, cultural diffusion and trait-adoptions became increasingly significant, leading to Bronze Age highly hierarchised societies and globalized economy [2].
For example, last Mesolithic sites are preferentially located in the mountain -- maybe because of the Neolithic pressure created by the arrival of first farmers -- while early farming sites occupied fertile lands: soils of the Balkans flood plains during Painted Pottery complex (PPC) diffusion, loessic soils of Central Europe and morainic soils of the Northern Alps during LBK diffusion (id. in the Southern Alps during Cardial diffusion). Spatial statistics have various indexes or models able to describe and explain spatial distributions. For example, we will calculate cost-weighted time of walk buffers from site locations (site catchment analysis) to study both site environmental context (site supply, repository of raw materials, land cover and arable lands, local climate, etc.) and inter-site connections. For traditional societies, a terrestrial 50/60 km radius, corresponding roughly to a day's walk, would be a theoretically good threshold below which principal genetic and cultural traits (marriage, language, economic exchanges, etc.) are optimal. Map algebra between land cover, slopes, climatic model, etc., will be used to evaluate the attractiveness of soils. Spatial statistics (e.g. semi-variograms), indexes (e.g., autocorrelation Moran's I, location quotient) or pattern distribution (e.g. Ripley's K function, Kernel density) will permit to characterize social groups' spatial distributions [10]. Geographic models (e.g. core-periphery, down-the-line, directional trade) will permit to match past observations with present ones (ethnographic, economic). To reduce the variability of the dataset, sites will be clustered according to their own specificities (e.g. category, size) and their inter-relations (e.g. geographical or network distances, genetic and cultural differences of their inhabitants). Beside geographical analysis, network analysis will be performed when qualitative "connections" between "nodes" (these terms are contextually-defined) will be observed.
A current model for these diffusion/differentiation processes follows these three phases:
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taking possession of a new territory: founder effect (loss of genetic diversity); opposition indigenous/incomers; incomers maintain links with their region of origin, perceptible, in particular, in common styles and long-distance exchanges;
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rooting and withdrawal: contacts with indigenous populations increase (admixture); selection of some cultural traits from indigenous and incomers backgrounds; contacts with the area of origin decrease, styles tends to lean towards regionalization;
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development and identity affirmation: a new social group appears; styles autonomy; the potential of the new territory is really exploited; long-distance exchanges restart;
[1] Novembre, J., Johnson, T., Bryc, K., Kutalik, Z., Boyko, A. R., Auton, A., ... & Bustamante, C. D. (2008). Genes mirror geography within Europe. Nature, 456(7218), 98-101.
[2] Günther, T., Valdiosera, C., Malmström, H., Ureña, I., Rodriguez-Varela, R., Sverrisdóttir, Ó. O., ... & Jakobsson, M. (2015). Ancient genomes link early farmers from Atapuerca in Spain to modern-day Basques. Proceedings of the National Academy of Sciences, 112(38), 11917-11922.
[3] Kristiansen, K., Allentoft, M. E., Frei, K. M., Iversen, R., Johannsen, N. N., Kroonen, G., ... & Willerslev, E. (2017). Re-theorising mobility and the formation of culture and language among the Corded Ware Culture in Europe. antiquity, 91(356), 334-347.