Radiocarbon test for demographic events in written and oral history

Abstract

We extend an established simulation-based method to test for significant short-duration (1-2 centuries) demographic events known from one documented historical and one oral historical context. Case study 1 extrapolates population data from the Western historical tradition using historically derived demographic data from the catastrophic European Black Death/bubonic plague (). We find a corresponding statistically significant drop in absolute population using an extended version of a previously published simulation method. Case study 2 uses this refined simulation method to test for a settlement gap identified in oral historical records of descendant Tsimshian First Nations communities from the Prince Rupert Harbour region of the Pacific Northwest region of British Columbia, Canada. Using a regional database of = 523 radiocarbon dates, we find a significant drop in relative population using the extended simulation-based method consistent with Tsimshian oral records. We conclude that our technical refinement extends the utility of radiocarbon simulation methods and can provide a rigorous test of demographic predictions derived from a range of historical sources.

On Applications of Space–Time Modelling with Open-Source 14C Age Calibration

“…This was one of the case studies used by Contreras and Meadows (2014) to illustrate the difficulties in identifying such events in radiocarbon data; they concluded that the consequence of the Black Death, a 30% drop in population, is difficult to Bsee^even when randomly sampling calendar dates from the population curve, and virtually impossible when viewed through the heavy fog of the calibration process. However, as Edinborough et al (2017) point out, such demographic events can be positively associated with changes in simulated summed radiocarbon probability distributions by deploying a hypothesis-testing approach-if, of course, there really is a direct link between demography and the production rate of materials destined to become 14 C samples, which is another debate entirely. To test whether the Gaussian KDE can resolve the Black Death Bevent^under a similar set of assumptions, the historic demographic data were used to simulate various numbers of calendar dates whose frequency distribution in time was randomly sampled from the demographic data supplied by Contreras and Meadows (2014) for the period AD 1000 to 1700.…”

“…Gaining momentum is what Edinborough et al (2017) call the BUniversity College London (UCL) method^, where simulation and back-calibration are used to generate a null hypothesis, which can also factor the expected rates of both population growth and taphonomic loss of archaeological materials through time. Through comparison of summed radiocarbon to the simulated model, signals of activity that are significantly weaker or stronger than usual can be identified.…”

“…Drawing inspiration from the Bmodified UCL^method (Edinborough et al 2017) in summed radiocarbon studies, it is possible to set up a null hypothesis model using bootstrapped radiocarbon Gaussian KDE models calculated using the above-mentioned steps and formally test whether the archaeological data significantly deviate from a trajectory that would be expected if all things were equal. To do this, the process is run on both simulated radiocarbon data (the null hypothesis) and the archaeological data (the radiocarbon date catalogue).…”

“…For example, at the time of writing, recent months have seen papers presenting syntheses of millennia of human history in Central Italy (Palmisano et al 2017), the Balkans (Porčić et al 2016), Britain and Ireland , western USA (Zahid et al 2016), the Pacific Northwest (Edinborough et al 2017), Eastern Japan (Crema et al 2016), and Korea (Oh et al 2017). These studies build on pioneering continental-scale studies also published in recent years (e.g.…”

Early and mid-Holocene coastal settlement and demography in southeastern Norway: Comparing distribution of radiocarbon dates and shoreline-dated sites, 8500–2000 cal. BCE

“…During the last decade population dynamics and demographic variation in Mesolithic and Neolithic societies have been thoroughly investigated by using summed radiocarbon probability plots as a population proxy (Apel et al, 2017;Edinborough, 2009;Hinz et al, 2012;Shennan et al, 2013;Shennan and Edinborough, 2007;Timpson et al, 2014). The scopes of the studies are impressive and the methods and models applied to investigate demographic variation are becoming increasingly complex (Edinborough et al, 2017: 1-2 for overview of development; Shennan et al, 2013;Timpson et al, 2014). Basically, reconstructions of prehistoric demography are based on temporal distribution of radiocarbon dates, which are used as a proxy of variation in human activity through time.…”