Showing papers by "Stephen Shennan published in 2015"

Early farmers from across Europe directly descended from Neolithic Aegeans

Abstract: Farming and sedentism first appear in southwest Asia during the early Holocene and later spread to neighboring regions, including Europe, along multiple dispersal routes. Conspicuous uncertainties remain about the relative roles of migration, cultural diffusion and admixture with local foragers in the early Neolithisation of Europe. Here we present paleogenomic data for five Neolithic individuals from northwestern Turkey and northern Greece, spanning the time and region of the earliest spread of farming into Europe. We observe striking genetic similarity both among Aegean early farmers and with those from across Europe. Our study demonstrates a direct genetic link between Mediterranean and Central European early farmers and those of Greece and Anatolia, extending the European Neolithic migratory chain all the way back to southwestern Asia.

Size Reduction in Early European Domestic Cattle Relates to Intensification of Neolithic Herding Strategies.

Abstract: Our analysis of over 28,000 osteometric measurements from fossil remains dating between c. 5600 and 1500 BCE reveals a substantial reduction in body mass of 33% in Neolithic central European domestic cattle. We investigate various plausible explanations for this phenotypic adaptation, dismissing climatic change as a causal factor, and further rejecting the hypothesis that it was caused by an increase in the proportion of smaller adult females in the population. Instead we find some support for the hypothesis that the size decrease was driven by a demographic shift towards smaller newborns from sub-adult breeding as a result of intensifying meat production strategies during the Neolithic.

Transition to farming more likely for small, conservative groups with property rights, but increased productivity is not essential.

Abstract: Theories for the origins of agriculture are still debated, with a range of different explanations offered. Computational models can be used to test these theories and explore new hypotheses; Bowles and Choi [Bowles S, Choi J-K (2013) Proc Natl Acad Sci USA 110(22):8830–8835] have developed one such model. Their model shows the coevolution of farming and farming-friendly property rights, and by including climate variability, replicates the timings for the emergence of these events seen in the archaeological record. Because the processes modeled occurred a long time ago, it can be difficult to justify exact parameter values; hence, we propose a fitting to idealized outcomes (FIO) method to explore the model’s parameter space in more detail. We have replicated the model of Bowles and Choi, and used the FIO method to identify complexities and interactions of the model previously unidentified. Our results indicate that the key parameters for the emergence of farming are group structuring, group size, conservatism, and farming-friendly property rights (lending further support to Bowles and Choi’s original proposal). We also find that although advantageous, it is not essential that farming productivity be greater than foraging productivity for farming to emerge. In addition, we highlight how model behaviors can be missed when gauging parameter sensitivity via a fix-all-but-one variation approach.

A generative inference framework for analysing patterns of cultural change in sparse population data with evidence for fashion trends in LBK culture

Abstract: Cultural change can be quantified by temporal changes in frequency of different cultural artefacts and it is a central question to identify what underlying cultural transmission processes could have caused the observed frequency changes. Observed changes, however, often describe the dynamics in samples of the population of artefacts, whereas transmission processes act on the whole population. Here we develop a modelling framework aimed at addressing this inference problem. To do so, we firstly generate population structures from which the observed sample could have been drawn randomly and then determine theoretical samples at a later time t2 produced under the assumption that changes in frequencies are caused by a specific transmission process. Thereby we also account for the potential effect of time-averaging processes in the generation of the observed sample. Subsequent statistical comparisons (e.g. using Bayesian inference) of the theoretical and observed samples at t2 can establish which processes could have produced the observed frequency data. In this way, we infer underlying transmission processes directly from available data without any equilibrium assumption. We apply this framework to a dataset describing pottery from settlements of some of the first farmers in Europe (the LBK culture) and conclude that the observed frequency dynamic of different types of decorated pottery is consistent with age-dependent selection, a preference for 'young' pottery types which is potentially indicative of fashion trends.

Demography and Cultural Evolution

Abstract: Trying to explain the increase in cultural complexity over the long term of human history has long been an interest of anthropology and of historical social sciences more generally. In recent years, interest has grown rapidly in the idea that a key factor in accounting for it might be the size of the human population itself and the extent of interaction between people, because of the effect these have on the innovation rates in populations and on the success with which innovations are transmitted. An important driver of this growth of interest has been the emergence of the new interdisciplinary field of cultural evolution, which makes extensive use of mathematical techniques, especially methods derived from population genetics. The result has been the development of a range of analytical and computer simulation models that make various predictions about the way in which population size influences cultural change, and in particular the growth of cumulative culture, including the processes that have led from the very simple forms of culture possessed by other great apes to those characteristic of Homo sapiens. The aim of this review is to distinguish them, so that future work can focus on evaluating their strengths and weaknesses and the circumstances in which they are useful. Keywords: cultural evolution; cumulative culture; cultural complexity; effective population size; transmission fidelity; innovation; cultural loss; demography; population growth

Simulating Geographical Variation in Material Culture: Were Early Modern Humans in Europe Ethnically Structured?

Abstract: A high degree of structuring is seen in the spatial distribution of symbolic artefact types associated with the Aurignacian culture in Upper Palaeolithic Europe, particularly the degree of sharing of ornament types across archaeological sites. Multivariate analyses of these distributions have been interpreted as indicating ethno-linguistic differentiation (Vanhaeren and d’Errico 2006), although simpler explanations such as isolation-by-distance have not been formally discounted. In this study we have developed a spatiotemporally explicit cultural transmission simulation model that generates expectations of a range of spatial statistics describing the distribution of shared ornament types. We compare these simulated spatial statistics to those observed from archaeological data for Aurignacian Europe—using Approximate Bayesian Computation—in order to test and compare a range of hypotheses concerning group interaction dynamics for the period. Among the set of hypotheses examined, we include ones where material culture does or does not drive group interaction dynamics.

An ABC of lithic arrowheads: A case study from south-eastern France

Abstract: If archaeology is to take a leading role in the social sciences, new theoretical and methodological advances emerging from the natural sciences cannot be ignored. This requires considerable retooling for archaeology as a discipline at a population scale of analysis. Such an approach is not easy to carry through, especially owing to historically contingent regional traditions; however, the knowledge gained by directly addressing these problems head-on is well worth the effort. This paper shows how population level processes driving cultural evolution can be better understood if mathematical and computational methods, often with a strong element of simulation, are applied to archaeological datasets. We use computational methods to study patterns and process of temporal variation in the frequency of cultural variants. More specifically, we will explore how lineages of lithic technologies are transmitted over time using a well-analysed and chronologically fine-grained assemblage of Central European Neolithic armatures from the French Jura. We look for sharp cultural transitions in the frequency of armature types by trying to detect significant mismatches between predictions dictated by an unbiased transmission model and observed empirical data. A simple armature classification scheme based on morphology is introduced. The results have considerable implications for analysing and understanding cultural transmission pathways not only for Neolithic armatures, but also for the evolution of lithic technology more generally in different spatiotemporal contexts.

On the relevance of the European Neolithic

Abstract: Sustainability, culture change, inequality and global health are among the much-discussed challenges of our time, and rightly so, given the drastic effects such variables can have on modern populations. Yet with many populations today living in tightly connected geographic communities—cities, for example—or in highly networked electronic communities, can we still learn anything about societal challenges by studying simple farming communities from many thousands of years ago? We think there is much to learn, be it Malthusian pressures and ancient societal collapse, the devastating effects of European diseases on indigenous New World populations or endemic violence in pre-state societies (e.g. Pinker 2012). By affording a simpler, ‘slow motion’ view of processes that are greatly accelerated in this century, the detailed, long-term record of the European Neolithic can offer insight into many of these fundamental issues. These include: human adaptations to environmental change (Palmer & Smith 2014), agro-pastoral innovation, human population dynamics, biological and cultural development, hereditary inequality, specialised occupations and private ownership.

Technology, Evolution of

Abstract: An evolutionary approach to the history of technology starts from the position that technologies change as a result of processes of ‘descent with modification’ in Darwin's famous term; it is in this sense that technology is cumulative. Taking this perspective makes it possible to go beyond the tautology that superior technologies spread because they are superior. It introduces a range of transmission mechanisms with different consequences and an array of different forces that affect what is transmitted. These are described and their implications are illustrated by means of examples.

The Cultural Evolution of Neolithic Europe. EUROEVOL Dataset

Abstract: This dataset comprises the primary data collected for the Cultural Evolution of Neolithic Europe project (EUROEVOL), led by Professor Stephen Shennan, UCL. The dataset offers the largest repository of archaeological site and radiocarbon data from Neolithic Europe (4,757 sites and 14,131 radiocarbon samples), dating between the late Mesolithic and Early Bronze Age, as well as the largest collections of archaeobotanical data (>8300 records for 729 different species, genera and families, and the largest collection of animal bone data with >3 million NISP counts and >36,000 biometrics.