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Indigenous Fremont farmers in Cub Creek, a part of northeastern Utah's Dinosaur National Monument, occupied the northern ecological margin of maize cultivation in western North America from A.D. 300 to 1300. Agriculture in Cub Creek was a response to multidecadal precipitation variability, but when precipitation stabilized between A.D. 750 and 1050, agricultural conditions improved and populations expanded to form villages along the floodplains of local dryland streams. Did the very same conditions (i.e., decreased precipitation variability) that allowed the growth of agricultural societies make them simultaneously vulnerable to arroyo formation, a key geomorphic risk to floodplain agriculturalists? Preliminary results from Cub Creek show that rapid sedimentation punctuated by episodic arroyo formation characterized the last 2000 years. We use stratigraphic and chronological evidence formalized in a Bayesian age model to develop a set of working hypotheses that a 2.5 m‐deep discontinuous arroyo formed before either A.D. 1020 or A.D. 1275. The earlier age corresponds with occupation of the Cub Creek village, while the later age corresponds with the end of Fremont agriculture in Cub Creek, and demonstrates regional synchronicity with arroyo formation across the Colorado Plateau. A second arroyo formed before A.D. 1490, indicating rapid alluvial cycling in Cub Creek. We conclude that floodplain instability and arroyo formation combined with the return of the dominant multidecadal precipitation variability regime beginning at A.D. 1050 was a key constraint on the growth potential of local populations. These findings have potential implications for the development of early Indigenous dryland agricultural systems throughout the interior of western North America.

 

The northern American Southwest provides one of the most well-documented cases of human population growth and decline in the world. The geographic extent of this decline in North America is unknown owing to the lack of high-resolution palaeodemographic data from regions across and beyond the greater Southwest, where archaeological radiocarbon data are often the only available proxy for investigating these palaeodemographic processes. Radiocarbon time series across and beyond the greater Southwest suggest widespread population collapses from AD 1300 to 1600. However, radiocarbon data have potential biases caused by variable radiocarbon sample preservation, sample collection and the nonlinearity of the radiocarbon calibration curve. In order to be confident in the wider trends seen in radiocarbon time series across and beyond the greater Southwest, here we focus on regions that have multiple palaeodemographic proxies and compare those proxies to radiocarbon time series. We develop a new method for time series analysis and comparison between dendrochronological data and radiocarbon data. Results confirm a multiple proxy decline in human populations across the Upland US Southwest, Central Mesa Verde and Northern Rio Grande from AD 1300 to 1600. These results lend confidence to single proxy radiocarbon-based reconstructions of palaeodemography outside the Southwest that suggest post-AD 1300 population declines in many parts of North America. This article is part of the theme issue ‘Cross-disciplinary approaches to prehistoric demography’. 

Archaeologists increasingly use large radiocarbon databases to model prehistoric human demography (also termed paleo-demography). Numerous independent projects, funded over the past decade, have assembled such databases from multiple regions of the world. These data provide unprecedented potential for comparative research on human population ecology and the evolution of social-ecological systems across the Earth. However, these databases have been developed using different sample selection criteria, which has resulted in interoperability issues for global-scale, comparative paleo-demographic research and integration with paleoclimate and paleoenvironmental data. We present a synthetic, global-scale archaeological radiocarbon database composed of 180,070 radiocarbon dates that have been cleaned according to a standardized sample selection criteria. This database increases the reusability of archaeological radiocarbon data and streamlines quality control assessments for various types of paleo-demographic research. As part of an assessment of data quality, we conduct two analyses of sampling bias in the global database at multiple scales. This database is ideal for paleo-demographic research focused on dates-as-data, bayesian modeling, or summed probability distribution methodologies.

 

Questions regarding population stability among animals and plants are fundamental to population ecology, yet this has not been a topic studied by archeologists focusing on prehistoric human populations. This is an important knowledge gap. The fluctuation of human populations over decades to centuries – population instability – may constrain the expansion of human economies. A first step toward describing basic patterns of population stability would be to identify sizes of fluctuations through time, since smaller fluctuations are more stable than larger fluctuations. We conduct a biogeographic analysis of the long-term stability of human societies in North America using a continental scale radiocarbon dataset. Our analysis compares the stability of summed calibrated radiocarbon date probability distributions (SPDs) with subsistence strategies and modeled climate stability between 6000 and 300 BP. This coarse-grained analysis reveals general trends regarding the stability of human systems in North America that future studies may build upon. Our results demonstrate that agricultural sequences have more stable SPDs than hunter-gatherer sequences in general, but agricultural sequences also experience rare, extreme increases and decreases in SPDs not seen among hunter-gatherers. We propose that the adoption of agriculture has the unintended consequence of increasing population density and stability over most time scales, but also increases the vulnerability of populations to large, rare changes. Conversely, hunter-gatherer systems remain flexible and less vulnerable to large population changes. Climate stability may have an indirect effect on long-term population stability, and climate shocks may be buffered by other aspects of subsistence strategies prior to affecting human demography. 

Climatic conditions exert an important influence on wildfire activity in the western United States; however, Indigenous farming activity may have also shaped the local fire regimes for millennia. The Fish Lake Plateau is located on the Great Basin–Colorado Plateau boundary, the only region in western North America where maize farming was adopted then suddenly abandoned. Here we integrate sedimentary archives, tree rings, and archeological data to reconstruct the past 1200 years of fire, climate, and human activity. We identify a period of high fire activity during the apex of prehistoric farming between 900 and 1400 CE, and suggest that farming likely obscured the role of climate on the fire regime through the use of frequent low-severity burning. Climatic conditions again became the dominant driver of wildfire when prehistoric populations abandoned farming around 1400 CE. We conclude that Indigenous populations shaped high-elevation mixed-conifer fire regimes on the Fish Lake Plateau through land-use practices.

 

Abstract Over the last decade, archaeologists have turned to large radiocarbon ( 14 C) data sets to infer prehistoric population size and change. An outstanding question concerns just how direct of an estimate 14 C dates are for human populations. In this paper we propose that 14 C dates are a better estimate of energy consumption, rather than an unmediated, proportional estimate of population size. We use a parametric model to describe the relationship between population size, economic complexity and energy consumption in human societies, and then parametrize the model using data from modern contexts. Our results suggest that energy consumption scales sub-linearly with population size, which means that the analysis of a large 14 C time-series has the potential to misestimate rates of population change and absolute population size. Energy consumption is also an exponential function of economic complexity. Thus, the 14 C record could change semi-independent of population as complexity grows or declines. Scaling models are an important tool for stimulating future research to tease apart the different effects of population and social complexity on energy consumption, and explain variation in the forms of 14 C date time-series in different regions.