• Digital Humanities and Cultural Heritage
• Open Access close
• Publications close
• Research data close
• Research software close
• Other research products close
• Article close
• European Commission close
• EUROEVOL close
• EU close

AbstractA long tradition of cultural evolutionary studies has developed a rich repertoire of mathematical models of social learning. Early studies have laid the foundation of more recent endeavours to infer patterns of cultural transmission from observed frequencies of a variety of cultural data, from decorative motifs on potsherds to baby names and musical preferences. While this wide range of applications provides an opportunity for the development of generalisable analytical workflows, archaeological data present new questions and challenges that require further methodological and theoretical discussion. Here we examine the decorative motifs of Neolithic pottery from an archaeological assemblage in Western Germany, and argue that the widely used (and relatively undiscussed) assumption that observed frequencies are the result of a system in equilibrium conditions is unwarranted, and can lead to incorrect conclusions. We analyse our data with a simulation-based inferential framework that can overcome some of the intrinsic limitations in archaeological data, as well as handle both equilibrium conditions and instances where the mode of cultural transmission is time-variant. Results suggest that none of the models examined can produce the observed pattern under equilibrium conditions, and suggest. instead temporal shifts in the patterns of cultural transmission.

Ecosystems on the verge of major reorganization-regime shift-may exhibit declining resilience, which can be detected using a collection of generic statistical tests known as early warning signals (EWSs). This study explores whether EWSs anticipated human population collapse during the European Neolithic. It analyzes recent reconstructions of European Neolithic (8-4 kya) population trends that reveal regime shifts from a period of rapid growth following the introduction of agriculture to a period of instability and collapse. We find statistical support for EWSs in advance of population collapse. Seven of nine regional datasets exhibit increasing autocorrelation and variance leading up to collapse, suggesting that these societies began to recover from perturbation more slowly as resilience declined. We derive EWS statistics from a prehistoric population proxy based on summed archaeological radiocarbon date probability densities. We use simulation to validate our methods and show that sampling biases, atmospheric effects, radiocarbon calibration error, and taphonomic processes are unlikely to explain the observed EWS patterns. The implications of these results for understanding the dynamics of Neolithic ecosystems are discussed, and we present a general framework for analyzing societal regime shifts using EWS at large spatial and temporal scales. We suggest that our findings are consistent with an adaptive cycling model that highlights both the vulnerability and resilience of early European populations. We close by discussing the implications of the detection of EWS in human systems for archaeology and sustainability science.

The datasets described in this paper comprises the animal bone data collected as part of the Cultural Evolution of Neolithic Europe project (EUROEVOL), led by Professor Stephen Shennan, UCL, representing the largest collection of animal bone data for the European Neolithic ( Figure 1 ) with >3 million NISP counts and >36,000 biometric measurements. This is one of three datasets resulting from the EUROEVOL project; the other two comprising the core spatial and temporal structure of the project, including all radiocarbon dates (EUROEVOL Dataset 1) and archaeobotanical data (EUROEVOL Dataset 3) - http://discovery.ucl.ac.uk/1469811/ .

The datasets described in this paper comprises the animal bone data collected as part of the Cultural Evolution of Neolithic Europe project (EUROEVOL), led by Professor Stephen Shennan, UCL, representing the largest collection of animal bone data for the European Neolithic (Figure 1) with >3 million NISP counts and >36,000 biometric measurements. This is one of three datasets resulting from the EUROEVOL project; the other two comprising the core spatial and temporal structure of the project, including all radiocarbon dates (EUROEVOL Dataset 1) and archaeobotanical data (EUROEVOL Dataset 3) - http://discovery.ucl.ac.uk/1469811/.

The datasets described in this paper comprise the core spatial and temporal structure of the Cultural Evolution of Neolithic Europe project (EUROEVOL), led by Professor Stephen Shennan, UCL. This is one of three datasets resulting from the EUROEVOL project, the other two comprising the faunal (EUROEVOL Dataset 2) and archaeobotanical (EUROEVOL Dataset 3) data ( http://discovery.ucl.ac.uk/1469811/ ). The dataset offers the largest repository of archaeological site and radiocarbon data from Neolithic Europe (4,757 sites and 14,053 radiocarbon samples), dating between the late Mesolithic and Early Bronze Age (Figure 1). It also offers the core archaeological information structured at the site and phase level, which provide the primary links between the datasets.

The datasets described in this paper comprise the core spatial and temporal structure of the Cultural Evolution of Neolithic Europe project (EUROEVOL), led by Professor Stephen Shennan, UCL. This is one of three datasets resulting from the EUROEVOL project, the other two comprising the faunal (EUROEVOL Dataset 2) and archaeobotanical (EUROEVOL Dataset 3) data (http://discovery.ucl.ac.uk/1469811/). The dataset offers the largest repository of archaeological site and radiocarbon data from Neolithic Europe (4,757 sites and 14,053 radiocarbon samples), dating between the late Mesolithic and Early Bronze Age (Figure 1). It also offers the core archaeological information structured at the site and phase level, which provide the primary links between the datasets.

The collection of this dataset was carried out under the auspices of the Cultural Evolution of Neolithic Europe project (EUROEVOL) led by Professor Stephen Shennan, UCL. The dataset represents one of the largest collections of archaeobotanical data for the Neolithic of Europe (Figure 1), comprising c.8300 records for c.1500 different species, genera and families and representing over a million identified items. This is one of three datasets resulting from the EUROEVOL project; the other two comprising the core spatial and temporal structure of the project, including all radiocarbon dates (EUROEVOL Dataset 1) and zooarchaeological data (EUROEVOL Dataset 2) – http://discovery.ucl.ac.uk/1469811/.

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. This research was funded by the European Research Council by an Advanced Grant (# 249390) to Stephen Shennan for the EUROEVOL Project. We are grateful to Eva Fairnell and Rebecca Rennell for assistance with the data input, and to all those who provided source data, to Sue Colledge for her insights on soil productivity and pasture conditions, and to Mark G Thomas for his useful statistical advice.