From correlations to explanations: towards a new European prehistory (COREX)
The study of the past is undergoing a dramatic transformation: researchers in the fields of archaeology, genetics, linguistics, history and archaeometry are blurring the lines delimiting their respective fields, and working in increasingly collaborative efforts to understand how history and prehistory unfolded. Recent debates stress the need for new explanatory models which integrate both micro- and macro-level historical processes, and diverse types of datasets. We approach this challenge by applying novel modelling approaches allowing us to move from correlations to explanations of how changes have been shaped by the dynamic interaction of cultural innovation, migration, admixture, population growth and collapse, landscape transformation, dietary change, biological adaptation, social structure, and the emergence of new diseases. To achieve this overall goal the project is built upon four specific aims, which translates into four work packages:
- WP1: Database for C14, cultural and subsistence (including isotope) data, ancient genomes, eDNA sites, fossil pollen datasets and strontium samples
- WP2: Environmental DNA and high- resolution local environments,
- WP3 Exploratory analyses and discriminative models,
- WP4 Generative models and explanations.
Our findings will serve to determine what the impact of the movement of people was on the European landscape, simultaneously on multiple scales: continental, regional and local, providing a research program defying the boundaries of archaeology, genetics and mathematical modelling. Thus, by identifying prehistoric regularities in the interactions of human biology, social and economic organisation, and demography we will be able to compare them to anthropological and historical models of such processes in recent times, to form a more comprehensive understanding of the nature of migration, integration and cultural change, then and now.
Objective: The overall goal of this project is to explain the key processes that formed the genetic and cultural diversity of Europe north of the Mediterranean from the beginning of farming 6000 BCE to the end of the Bronze Age 500 BCE. Through synergies between world-experts in a number of disciplines, we will explore how small-scale processes generate large-scale patterns in genetic and cultural data, and will investigate how the two interact. We will achieve this by applying novel modelling approaches allowing us to move from correlations to explanations of how changes have been shaped by the dynamic interaction of cultural innovation, migration, admixture, population growth and collapse, dietary change, biological adaptation, social structure, and the emergence of new diseases. To achieve this overall goal the project is built upon four specific aims, which translates into four work packages (WPs): WP1: Database for C14, cultural and subsistence (including isotope) data, ancient genomes, eDNA sites, fossil pollen datasets and strontium samples WP2: Environmental DNA and high resolution local environments, WP3 Exploratory analyses and discriminative models WP4 Generative models and explanations.
The DNA revolution and archaeology. The development of methods to sequence ancient genomic DNA and the publication of ever-increasing numbers of ancient genomes has created the greatest revolution in archaeology since the introduction of radiocarbon dating in the 1960s. Like that revolution it has removed a major burden of archaeological interpretation (Kristiansen 2014), as we have moved from invoking migrations based solely on archaeological evidence to an independent information source, ancient DNA. This resolves the problem of circular reasoning, and implies that we no longer have to discuss if migrations took place, but can instead focus on causes and processes. However, many archaeologists remain sceptical of the implications of this new revolution (Furholt 2018; Heyd 2017; Sørensen 2017). This is because genetic studies to date have not been leveraged to systematically explain the patterns that archaeologists identify in material culture data. Also, there are cases where there has been significant material culture change with little change in ancestry, for example, the origin of the Linear Pottery Culture (LBK) in the Carpathian Basin with continuing overwhelmingly high proportions of Anatolian farmer ancestry (Lipson et al. 2017; Mathieson et al. 2018), or the Bell Beaker complex where a Bell Beaker culture package from Iberia was adopted by Corded Ware groups without significant genetic admixture (Olalde et al. 2018).
The challenge: These major advances in understanding the population demographic history of western Eurasia have run far in advance of our capacity to relate them to the empirical archaeological record, except in the vaguest and most general terms. The key challenge that this project will address will be the integration of these revolutionary genomic findings with new archaeological contextual data (WP1), detailed environmental DNA reconstructions (WP2) and quantified palaeo-vegetation data. These high resolution contextual analyses will then be linked to innovative integrated model-based frameworks that can correlate the commonalities and differences among different times and places (WP3). Further we seek to explain those relationships using generative models by considering how local processes lead to global, continent-wide phenomena (WP4). Some work has already been undertaken (Kristiansen et al. 2017; Knipper et al. 2017). Thus, the single most important challenge in archaeology today is to be able to handle, integrate and interpret all the new genetic data with archaeological and environmental data, so that we can compare the cultural relationships with those apparent in the ancient genomes and assess the extent to which genes and cultural information were or were not transmitted in parallel, before going on to model the processes that might have produced the relationships observed.
Our solution: By bringing together three PIs and four senior researchers with a unique combination of complementary disciplinary backgrounds and skills we propose to create a novel, and so far never attempted synergistic understanding of the demographic, social, cultural, ecological and evolutionary processes that shaped European prehistory from the introduction of farming to the end of the Bronze Age. Such an endeavour is well beyond the capacity of any of them individually. Key processes to be considered include demographic ones relating to population growth and decline. At the same time as the explosion in ancient genome research, there has been major growth in the collation of large databases of radiocarbon dates and the use of summed date probabilities and related measures to infer past population size changes. These have been accompanied by statistical methods to evaluate the validity of the inferences being made (e.g. Shennan et al. 2013, Crema et al. 2016, Palmisano et al. 2017, Hannah and McLaughlin 2019) and to correlate them with other proxies, such as anthropogenic impacts on the environment and past vegetation change (e.g. Woodbridge et al. 2014, Berger et al. 2019, Feeser et al. 2019). In WP1 all of these methods will be adopted, and compared with changes in subsistence (cf. Colledge et al. 2019), diet and diseases, so as to create a multi-proxy foundation for assessing and explaining the complex processes of population change throughout later prehistory (WP 3 and 4). cPI Kristiansen Part B1 COREX 3
Research questions: 1) To what extent do changing patterns in the archaeological record, for example, burial practices, correspond to changing patterns in gene flow indicated by data from ancient genomes? Conversely, did adaptation to new environmental conditions lead to changes in economy/subsistence and culture, irrespective of gene flow? 2) How did patterns of mobility change over time? Do different types of migration/mobility lead to different forms of genetic and socio-economic change? 3) Did trade lead to new forms of more sustained population growth and environmental sustainability? 4). How do we explain fluctuations in regional populations? Did decreases in regional demographic density lead to large-scale gene flow from elsewhere (via migration that then resulted in renewed population growth?). Or were increases in population due to inherent growth (perhaps as a result of increased resource availability through changed climate conditions or technological developments, including new crop varieties)? 5). What are the relations between genetic factors (ancestry, frequencies of disease-associated SNPs and haplotypes), environmental factors (climate, ecozones, subsistence strategy and the presence of pathogens) and population responses? 6) How can we explain the emergence of large-scale phenomena such as shared material culture over wide geographic regions, or extensive population movements and replacements, from local-scale processes such as cultural transmission, identity, contact networks and trade?