Directly modelling population dynamics in the South American Arid Diagonal using 14C dates

Frequent disturbances enhanced the resilience of past human populations

The record of past human adaptations provides crucial lessons for guiding responses to crises in the future1-3. To date, there have been no systematic global comparisons of humans' ability to absorb and recover from disturbances through time4,5. Here we synthesized resilience across a broad sample of prehistoric population time-frequency data, spanning 30,000 years of human history. Cross-sectional and longitudinal analyses of population decline show that frequent disturbances enhance a population's capacity to resist and recover from later downturns. Land-use patterns are important mediators of the strength of this positive association: farming and herding societies are more vulnerable but also more resilient overall. The results show that important trade-offs exist when adopting new or alternative land-use strategies.

Earliest directly dated rock art from Patagonia reveals socioecological resilience to mid-Holocene climate

The timing for the evolution of the capacity to inscribe the landscape with rock art has global relevance. While this was an in-built capacity when Homo sapiens first colonized the Americas, the heterogeneous distribution of rock art shows that it was a facultative behavior arising under unknown socioecological conditions. Patagonia was the last region to be explored by humans. While its rock art is globally important, it remains largely undated by absolute methods. We report the earliest set of directly radiocarbon-dated rock art motifs from the archaeological site Cueva Huenul 1 (northwestern Patagonia, Argentina), starting at 8.2 thousand years before the present (ka B.P.), predating previous records by several millennia, and encompassing over 3 ka (~130 human generations). This mid-Holocene "rock art emergence" phase overlaps with extremely arid conditions and a human demographic stasis. We suggest that this diachronic rock art emerged as part of a resilient response to ecological stress by highly mobile and low-density populations.

Towards understanding human-environment feedback loops: the Atacama Desert case

The overall trajectory for the human-environment interaction has been punctuated by demographic boom-and-bust cycles, phases of growth/overshooting as well as of expansion/contraction in productivity. Although this pattern has been explained in terms of an interplay between population growth, social upscaling, ecosystem engineering and climate variability, the evoked demographic-resource-complexity mechanisms have not been empirically tested. By integrating proxy data for population sizes, palaeoclimate and internal societal factors into empirical modelling approaches from the population dynamic theory, we evaluated how endogenous (population sizes, warfare and social upscaling) and exogenous (climate) variables module the dynamic in past agrarian societies. We focused on the inland Atacama Desert, where populations developed agriculture activities by engineering arid and semi-arid landscapes during the last 2000 years. Our modelling approach indicates that these populations experienced a boom-and-bust dynamic over the last millennia, which was coupled to structure feedback between population sizes, hydroclimate, social upscaling, warfare and ecosystem engineering. Thus, the human-environment loop appears closely linked with cooperation, competition, limiting resources and the ability of problem-solving. This article is part of the theme issue 'Evolution and sustainability: gathering the strands for an Anthropocene synthesis'.

Descent, marriage, and residence practices of a 3,800-year-old pastoral community in Central Eurasia

Our understanding of prehistoric societal organization at the family level is still limited. Here, we generated genome data from 32 individuals from an approximately 3,800-y-old burial mound attributed to the Bronze Age Srubnaya-Alakul cultural tradition at the site of Nepluyevsky, located in the Southern Ural region of Central Eurasia. We found that life expectancy was generally very low, with adult males living on average 8 y longer than females. A total of 35 first-degree, 40 second-degree, and 48 third-degree biological relationships connected 23 of the studied individuals, allowing us to propose a family tree spanning three generations with six brothers at its center. The oldest of these brothers had eight children with two women and the most children overall, whereas the other relationships were monogamous. Notably, related female children above the age of five were completely absent from the site, and adult females were more genetically diverse than males. These results suggest that biological relationships between male siblings played a structural role in society and that descent group membership was based on patrilineality. Women originated from a larger mating network and moved to join the men, with whom they were buried. Finally, the oldest brother likely held a higher social position, which was expressed in terms of fertility.

Formal Tests for Resistance-Resilience in Archaeological Time Series

The study of resilience is a common pathway for scientific data to inform policy and practice towards impending climate change. Consequently, understanding the mechanisms and features that contribute towards building resilience is a key goal of much research on coupled socio-environmental systems. In parallel, archaeology has developed the ambition to contribute to this agenda through its unique focus on cultural dynamics that occur over the very long term. This paper argues that archaeological studies of resilience are limited in scope and potential impact by incomplete operational definitions of resilience, itself a multifaceted and contested concept. This lack of interdisciplinary engagement fundamentally limits archaeology’s ability to contribute meaningfully to understanding factors behind the emergence and maintenance of long-term societal resilience, a topic of significant interest that the field is in theory ideally positioned to address. Here, we introduce resilience metrics drawn from ecology and develop case studies to illustrate their potential utility for archaeological studies. We achieve this by extending methods for formally measuring resistance, the capacity of a system to absorb disturbances; and resilience, its capacity to recover from disturbances, with a novel significance test for palaeodemographic data. Building on statistical permutation and post-hoc tests available in the rcarbon package in the R statistical environment, we apply our adapted resilience-resistance framework to summed probability distributions of calibrated radiocarbon dates drawn from the Atlantic Forest of eastern Brazil. We deploy these methods to investigate cross-sectional trends across three recognised biogeographical zones of the Atlantic Forest domain, against the backdrop of prehistoric phases of heightened hydroclimatic variability. Our analysis uncovers novel centennial-scale spatial structure in the resilience of palaeodemographic growth rates. In addition to the case-specific findings, we suggest that adapting formal metrics can help archaeology create impact and engagement beyond relatively narrow disciplinary concerns. To this end, we supply code and data to replicate our palaeodemographic analyses to enable their use and adaptation to other archaeological problems.

Bayesian analyses question the role of climate in Chulmun demography

We investigate the relationship between climatic and demographic events in Korea during the Chulmun period (10,000-3,500 cal. BP) by analyzing paleoenvironmental proxies and 14C dates. We focus on testing whether a cooling climate, and its potential negative impact on millet productivity around the mid 5th-millennium cal. BP, triggered the population decline suggested by the archaeological record. We employ a Bayesian approach that estimates the temporal relationship between climatic events and change-points in the rate of growth in human population as inferred from radiocarbon time frequency data. Our results do not support the climate-induced population decline hypothesis for three reasons. First, our Bayesian analyses suggest that the cooling event occurred after the start of the population decline inferred from the radiocarbon time-frequency record. Second, we did not find evidence showing a significant reduction of millet-associated dates occurring during the cooling climate. Third, we detected different magnitudes of decline in the radiocarbon time-frequency data in the inland and coastal regions, indicating that the even if cooling episodes were ultimately responsible of these population 'busts', their impact was most likely distinct between these regions. We discuss our results highlighting the long tradition of mobility-based subsistence strategy in coastal regions as a potential factor contributing to the regional differences we were able to detect.

Approximate Bayesian Computation of radiocarbon and paleoenvironmental record shows population resilience on Rapa Nui (Easter Island)

Examining how past human populations responded to environmental and climatic changes is a central focus of the historical sciences. The use of summed probability distributions (SPD) of radiocarbon dates as a proxy for estimating relative population sizes provides a widely applicable method in this research area. Paleodemographic reconstructions and modeling with SPDs, however, are stymied by a lack of accepted methods for model fitting, tools for assessing the demographic impact of environmental or climatic variables, and a means for formal multi-model comparison. These deficiencies severely limit our ability to reliably resolve crucial questions of past human-environment interactions. We propose a solution using Approximate Bayesian Computation (ABC) to fit complex demographic models to observed SPDs. Using a case study from Rapa Nui (Easter Island), a location that has long been the focus of debate regarding the impact of environmental and climatic changes on its human population, we find that past populations were resilient to environmental and climatic challenges. Our findings support a growing body of evidence showing stable and sustainable communities on the island. The ABC framework offers a novel approach for exploring regions and time periods where questions of climate-induced demographic and cultural change remain unresolved.

Summed probability distributions of radiocarbon dates can be used to estimate past demography, but methods to test for associations with environmental change are lacking. Here, DiNapoli et al. propose an approach using Approximate Bayesian Computation and illustrate it in a case study of Rapa Nui.

A Bayesian approach for fitting and comparing demographic growth models of radiocarbon dates: A case study on the Jomon-Yayoi transition in Kyushu (Japan)

Large sets of radiocarbon dates are increasingly used as proxies for inferring past population dynamics and the last few years, in particular, saw an increase in the development of new statistical techniques to overcome some of the key challenges imposed by this kind of data. These include: 1) null hypothesis significance testing approaches based on Monte-Carlo simulations or mark permutations; 2) non-parametric Bayesian modelling approaches, and 3) the use of more traditional techniques such as correlation, regression, and AIC-based model comparison directly on the summed probability distribution of radiocarbon dates (SPD). While the range of opportunities offered by these solutions is unquestionably appealing, they often do not consider the uncertainty and the biases arising from calibration effects or sampling error. Here we introduce a novel Bayesian approach and nimbleCarbon, an R package that offers model fitting and comparison for population growth models based on the temporal frequency data of radiocarbon dates. We evaluate the robustness of the proposed approach on a range of simulated scenarios and illustrate its application on a case study focused on the demographic impact of the introduction of wet-rice farming in prehistoric Japan during the 1st millennium BCE.

Archaeology, demography and life history theory together can help us explain past and present population patterns

Population matters. Demographic patterns are both a cause and a consequence of human behaviour in other important domains, such as subsistence, cooperation, politics and culture. Demographers interested in contemporary and recent historical populations have rich data at their fingertips; the importance of demography means many interested parties have gathered demographic data, much of which is now readily available for all to explore. Those interested in the demography of the distant past are not so fortunate, given the lack of written records. Nevertheless, the emergence in recent years of a new interest in the demography of ancient populations has seen the development of a range of new methods for piecing together archaeological, skeletal and DNA evidence to reconstruct past population patterns. These efforts have found evidence in support of the view that the relatively low long-term population growth rates of prehistoric human populations, albeit ultimately conditioned by carrying capacities, may have been owing to 'boom-bust' cycles at the regional level; rapid population growth, followed by population decline. In fact, this archaeological research may have come to the same conclusion as some contemporary demographers: that demography can be remarkably hard to predict, at least in the short term. It also fits with evidence from biology that primates, and particularly humans, may be adapted to environmental variability, leading to associated demographic stochasticity. This evidence of the fluctuating nature of human demographic patterns may be of considerable significance in understanding our species' evolution, and of understanding what our species future demographic trajectories might be. This article is part of the theme issue 'Cross-disciplinary approaches to prehistoric demography'.