Grand challenges for archaeology

Kintigh, Keith; Altschul, Jeffrey H.; Beaudry, Mary C.; Drennan, Robert D.; Kinzig, Ann P.; Kohler, Timothy A.; Limp, W. Frederick; Maschner, Herbert D. G.; Michener, William K.; Paüketat, Timothy R.; Peregrine, Peter N.; Sabloff, Jeremy A.; Wilkinson, T. J.; Wright, Henry T.; Zeder, Melinda A.

doi:10.1073/pnas.1324000111

Cited by 213 publications

(192 citation statements)

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“…The rate and scale of contemporary climate change are unprecedented at a hemispheric level; however, past agrarian populations have had to adapt to rapid, dramatic changes in their local environments. Archaeological knowledgeanalysed in the context of reconstructed environments-is essential in understanding the dynamics and operation of coupled human and natural systems 35 . The experience in the Ancestral Pueblo SWUS suggests that, when faced with changing environments, humans will first seek alternative habitats that do not require them to change behaviour-such as the Pajarito Plateau-and only once those are unavailable will they develop or adopt alternative strategies.…”

Section: Discussionmentioning

confidence: 99%

A 2,000-year reconstruction of the rain-fed maize agricultural niche in the US Southwest

Bocinsky

Kohler

2014

Nat Commun

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Section: Discussionmentioning

confidence: 99%

A 2,000-year reconstruction of the rain-fed maize agricultural niche in the US Southwest

Bocinsky

Kohler

2014

Nat Commun

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“…Although regime shifts are well documented in human-dominated ecosystems (9)(10)(11)(12)(13), the degree to which EWSs anticipate them remains largely unexamined due to data limitations at requisite spatial and temporal scales. However, recent advances in the integration of large-scale archaeological data (14)(15)(16) are narrowing the gap between theory and data. This study presents what we believe to be the first statistical evidence for EWSs of regime shifts in human population dynamics.…”

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confidence: 99%

European Neolithic societies showed early warning signals of population collapse

Downey

Haas

Shennan

2016

Proc. Natl. Acad. Sci. U.S.A.

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Ecosystems on the verge of major reorganization-regime shiftmay 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.archaeology | early warning signs | human paleodemography | Neolithic Europe | resilience A 2012 Special Issue in PNAS debates how analysis of historical collapse in ancient societies can contribute to sustainability science (1). Key themes include accounting for complexity and multicausality in instances of collapse, modeling, and predicting both short-and long-term environmental change and the importance of historical and archaeological case studies. Although significant progress has been made in measuring ecosystem resilience and predicting collapse (2), quantifying the resilience of human societies presents a major challenge for social science research (3, 4). Further, the use of archaeological data and EWS methods to predict known periods of collapse in ancient human societies (i.e., retrodiction) (5) remains largely unexplored. Resilience as we use the concept here is defined as the ability of a system to absorb change and recover from disturbance while maintaining relationships between populations or state variables (6). Recent developments in ecology point to a promising new direction that follows from the observation that ecosystem resilience tends to decrease in advance of regime shifts-major transitions among qualitatively distinct ecosystem states (7). Theoretical and empirical studies of nonhuman systems reveal that decreasing resilience is detectable via time series statistics term...

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“…Digital datasets are often highly variable, of poor quality, and incompatible. Deficiencies like these inhibit reuse of primary data and the aggregation of datasets from multiple studies for large-scale research [4,7,1].…”

Section: Motivation and Significancementioning

confidence: 99%

FAIMS Mobile: Flexible, open-source software for field research

Ballsun-Stanton¹,

Ross²,

Sobotková³

et al. 2017

Preprint

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FAIMS Mobile is a native Android application supported by an Ubuntu server facilitating human-mediated field research across disciplines. It consists of 'core' Java and Ruby software providing a platform for data capture, which can be deeply customised using 'definition packets' consisting of XML documents (data schema and UI) and Beanshell scripts (automation). Definition packets can also be generated using an XML-based domain-specific language, making customisation easier. FAIMS Mobile includes features allowing rich and efficient data capture tailored to the needs of fieldwork. It also promotes synthetic research and improves transparency and reproducibility through the production of comprehensive datasets that can be mapped to vocabularies or ontologies as they are created.

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Grand challenges for archaeology

Cited by 213 publications

References 1 publication

A 2,000-year reconstruction of the rain-fed maize agricultural niche in the US Southwest

A 2,000-year reconstruction of the rain-fed maize agricultural niche in the US Southwest

European Neolithic societies showed early warning signals of population collapse

FAIMS Mobile: Flexible, open-source software for field research

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