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Simulated SCPD (dark grey, same number of dates at each temporal bin) compared with the IntCal13 calibration curve. https://doi.org/10.1371/journal.pone.0200709.g004

Simulated SCPD (dark grey, same number of dates at each temporal bin) compared with the IntCal13 calibration curve. https://doi.org/10.1371/journal.pone.0200709.g004

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The reconstruction of past demographic patterns is a fundamental step towards a better understanding of human-environment relations, especially in terms of quantifiable anthropic impact and population susceptibility to environmental changes. The recently developed Summed Calibrated Probability Distributions (SCPD) approach, based on large collectio...

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... In a broader archaeological framework, studies on prehistoric demographic trends have exponentially increased over the last 20 years (Shennan & Edinborough, 2007), creating what is termed the "boom-and-bust" theory in prehistoric demography, whose causes are not always easy to disentangle from climate and sociocultural changes (Shennan & Saer, 2021) and human conflicts (Kondor et al., 2022). A specific focus has been on the relationships among environmental trends (Capuzzo et al., 2018) and the correlation between the increase in human population and arboreal pollen percentages, notably tree crops . Roberts et al. (2019;11) note: "The results show that most Mediterranean regions experienced a series of population 'cycles' starting with the first appearance of Neolithic farming societies, but that demographic trends were region-specific rather than pan-Mediterranean." ...
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... In case of dates on charcoal and cremated bone from the same grave, measurements from long-lived samples were excluded, retaining only dates on calcined bone. In this way, a pre-analytic "binning" procedure was applied to filter the data (Capuzzo et al. 2018). ...
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... We have modelized a Sum of Probabilities of 3190 simulated 14 C estimates with the same lab error (20 years), from 14000 to 0 BP, to build the accumulated probability distribution on the assumption of a single date every 5 years using OxCal (Figure 2). Given that the number of dates is uniform within each time interval, a straight line would be expected, and departures from this uniform expectation should be consequences of irregularities in the calibration curve (Capuzzo et al. 2018 to 0 BP to test the effect of the calibration curve shape using the SHCal20 curve. Plotted using PAST (Hammer et al. 2001). ...
... Hemisphere Calibration Curve and that irregularities in the KDE distribution may have been affected by the resulting shape of the calibration curve. However, from 2000 BP onwards, the increasing 14 C signal clearly exceeds possible effects of the calibration curve and the exponential increase in standard taphonomic loss (Surovell et al. 2009;Capuzzo et al. 2018). Moreover, the apparent fall-off around 1000 BP also coincides with irregularities in the calibration curve. ...
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... Such competition is arguably visible in the rapid changes and growing investment in panoplies of weapons at precisely this time. The nature of the Po Valley boom and bust contrasts with other areas of Italy that show more incremental growth and stability throughout the Bronze Age (Blake 2014;Capuzzo et al. 2018;Iacono 2019;Ialongo 2018;Roberts et al. 2019). ...
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... Over the past couple of decades, there has been renewed interest in the study of past demographic patterns, with a view to understanding how population growth and decline do or do not run in step with cultural change, with increase or decrease in social complexity and/or with environmental change Freeman, et al., 2018;Riede, 2009;Roberts, et al., 2019;Shennan, 2000Shennan, , 2001Turchin, et al., 2018;Wigand & McCallum, 2017). In this context, summed probability distributions (SPDs) of calibrated archaeological radiocarbon dates have become particularly popular for inferring demographic trends in prehistory (Rick, 1987;Shennan & Edinborough, 2007;Bocquet-Appel et al., 2009;Shennan et al., 2013;Porčić et al., 2016;de Pablo et al., 2019;Palmisano et al., 2019); and for assessing population response to climate shifts (Weninger et al., 2009;Williams et al., 2010;Fiorentino et al., 2013;Capuzzo et al., 2018;Roberts et al., 2018;Riris & Arroyo-Kalin, 2019). More recently, this approach has benefitted from a series of methodological advances dealing with issues such as the effects of the calibration curve (Weninger et al., 2015;Williams, 2012); taphonomic loss (Surovell et al., 2009); biases in the original archaeological dataset (Brown, 2017;McLaughlin, 2019); and testing statistically spatio-temporal trends in the fluctuations of SPDs of calibrated radiocarbon dates (Timpson et al, 2014;Crema et al., 2016;Crema et al., 2017;Bevan et al., 2017;Edinborough et al., 2017;Palmisano et al., 2017;McLaughlin, 2019;Robinson et al., 2019). ...
... However, over the past two decades, SPDs of archaeological radiocarbon dates have begun to be used to model past demographic trends in prehistory, because they have the potential to document trends at higher levels of resolution. This latter approach has had limited impact in Italy with the exception of rare examples focussing on single regions or well-defined cultural periods (Fiorentino et al., 2013;Palmisano et al., 2017;Palmisano et al., 2018;Capuzzo et al., 2018;Stoddart et al., 2019). The reluctance to use radiocarbon dates as a proxy for past human population reflects a broader preference for using archaeological survey data to estimate past settlement intensity (e.g. ...
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... The challenge is further exacerbated by the growing interest in linking changes observed in SPD curves to paleoenvironmental proxies with various correlation techniques and direct comparisons, e.g., 27,32,[35][36][37][38][39][40][41][42][43][44] . While these studies offer important indications of potential associations between population and climate, there have been only limited attempts to formally model the effect of climatic or environmental changes on SPD-based population proxies, e.g., 15,21,41,45 . ...
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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.