Palaeodemographic modelling supports a population bottleneck during the Pleistocene-Holocene transition in Iberia

Abstract

Demographic change lies at the core of debates on genetic inheritance and resilience to climate change of prehistoric hunter-gatherers. Here we analyze the radiocarbon record of Iberia to reconstruct long-term changes in population levels and test different models of demographic growth during the Last Glacial-Interglacial transition. Our best fitting demographic model is composed of three phases. First, we document a regime of exponential population increase during the Late Glacial warming period (c.16.6-12.9 kya). Second, we identify a phase of sustained population contraction and stagnation, beginning with the cold episode of the Younger Dryas and continuing through the first half of the Early Holocene (12.9-10.2 kya). Finally, we report a third phase of density-dependent logistic growth (10.2-8 kya), with rapid population increase followed by stabilization. Our results support a population bottleneck hypothesis during the Last Glacial-Interglacial transition, providing a demographic context to interpret major shifts of prehistoric genetic groups in south-west Europe.

Late Glacial and Early Holocene human demographic responses to climatic and environmental change in Atlantic Iberia

“…We compiled a database of 62 archaeological sites and 371 radiocarbon dates, updating upon a synthesis previously published [ 4 ]. The data were subjected to two rounds of data screening, where dates with excessive error terms (greater than 200 years) were filtered from the database to reduce noise, as were dates where the archaeological association with human activity was not clear.…”

“…Dates from closed sites (caves and rockshelters) were then added to this SPD without any taphonomic correction. A confidence interval for the SPD was calculated using the bootstrapping method of [ 4 ].…”

“…Null hypotheses of exponential population growth were tested by fitting an exponential curve to the SPD and bootstrapping a confidence interval [ 4 ], and the periods of significant departure from this null model identified by comparing the bootstrapped confidence intervals of both curves. Adopting the rcarbon visual syntax, those areas of the bootstrapped SPD whose 95.4% confidence interval were above or below the confidence interval of 95.4% of the exponential null model were, respectively, shaded in blue and red, to denote statistically significant departures from the null model.…”

Inference From Large Sets of Radiocarbon Dates: Software and Methods

“…a logistic model) to name just a few of the most common (e.g. Shennan et al 2013;Crema et al 2016;Bevan et al 2017, Fernández-López de Pablo et al 2019. The usual workflow involves (1) fitting such a theoretical model to the observed SPD, (2) drawing s dates proportional to the shape of this fitted model (where s matches the number of observed dates or the number of bins if the dates have been binned), (3) back-calibrating individual dates from calendar time to 14 C age, and assigning an error to each by randomly sampling (with replacement) the observed 14 C age errors in the input data, (4) generating a theoretical SPD from the simulated data obtained in steps 2 and 3, (5) repeating steps 2-4 n times and generating a critical (e.g.…”

Re-Evaluation of World Population Figures: Politics and Forecasting Mechanics

“…While the changes in demographics were relatively small till the first half of the 20th century, the population growth expanded unprecedentedly at the later end of the century (Shobande, 2018). There is wide consensus in literature that the world will experience population explosion in few decades from now with the African continent leading the pack with the highest growth rate (Dumont, 2018;Fernández-López de Pablo et al, 2019;Marshall et al, 2017).…”