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

Fernández-López de Pablo, Javier, Gutiérrez-Roig, Mario, Gómez-Puche, Madalena, McLaughlin, Rowan, Silva, Fabio, Lozano, Sergi·2019·Nature Communications
DOI 10.1038/s41467-019-09833-3PMC PMC6478856
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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.

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Fig. 1 Distribution of archaeological sites with radiocarbon dates analyzed in this study. The colours represent the different regional subsets analyzed. The background map has been generated in ArcGIS 10.3 using 1 arc second SRTM raster data (available from https://earthdata.nasa.gov/) to represent terrain via a hillshade model
Fig. 1 Distribution of archaeological sites with radiocarbon dates analyzed in this study. The colours represent the different regional subsets analyzed. The background map has been generated in ArcGIS 10.3 using 1 arc second SRTM raster data (available from https://earthdata.nasa.gov/) to represent terrain via a hillshade modelCC BY · PubMed Central
Fig. 2 SPD inferred population density changes between 18,000 and 7500 cal BP for Iberia. a, b Palaeoclimatic framework of the Last Glacial-Interglacial transition. a The green curve represents the variation of 18O from the NGRIP ice-core record with the Greenland stratotype chronology77. b The blue line depicts the reconstruction of Sea Surface Temperature based on the deep-sea core MD95-2043 in the Alborán sea, considered as a palaeoclimatic proxy specific to the Iberian Peninsula56. c Summed Probability Distribution (SPD) of the calibrated radiocarbon dates after applying bootstrap simulations on the taphonomically corrected SPD curve (in black) (seeMethods). d Population proxy (in red) plotted against a bootstrapped null model of exponential growth. Light red and light blue shaded regions denote positive and negative deviations from the null model of exponential demographic growth respectively. The global p value is calculated using the computational method of Timpson et al.8 for a set of simulated SPDs and express the global significance of the curve's departure from the exponential null model
Fig. 2 SPD inferred population density changes between 18,000 and 7500 cal BP for Iberia. a, b Palaeoclimatic framework of the Last Glacial-Interglacial transition. a The green curve represents the variation of 18O from the NGRIP ice-core record with the Greenland stratotype chronology77. b The blue line depicts the reconstruction of Sea Surface Temperature based on the deep-sea core MD95-2043 in the Alborán sea, considered as a palaeoclimatic proxy specific to the Iberian Peninsula56. c Summed Probability Distribution (SPD) of the calibrated radiocarbon dates after applying bootstrap simulations on the taphonomically corrected SPD curve (in black) (seeMethods). d Population proxy (in red) plotted against a bootstrapped null model of exponential growth. Light red and light blue shaded regions denote positive and negative deviations from the null model of exponential demographic growth respectively. The global p value is calculated using the computational method of Timpson et al.8 for a set of simulated SPDs and express the global significance of the curve's departure from the exponential null modelCC BY · PubMed Central
Fig. 3 SPD inferred population density changes between 18,000 and 7500 cal BP for each regional subset. The black bold line represents the population proxy based on the median of the taphonomically corrected SPD after applying bootstrap resampling. For each regional subset is compared with a null model of exponential demographic growth (in gray). The vertical pink and blue bands represent periods of significantly higher and lower population densities respectively compared to the null exponential model. The global p values are calculated using the computational method of Timpson et al.8 for a set of simulated SPDs and express the global significance of the curve's departure from the null model
Fig. 3 SPD inferred population density changes between 18,000 and 7500 cal BP for each regional subset. The black bold line represents the population proxy based on the median of the taphonomically corrected SPD after applying bootstrap resampling. For each regional subset is compared with a null model of exponential demographic growth (in gray). The vertical pink and blue bands represent periods of significantly higher and lower population densities respectively compared to the null exponential model. The global p values are calculated using the computational method of Timpson et al.8 for a set of simulated SPDs and express the global significance of the curve's departure from the null modelCC BY · PubMed Central
Fig. 4 Demographic models tested using an information-theoretic based model selection approach. The black curve depicts the empirical SPD population proxy whereas the red curves represents the model fits with best fitting thresholds for each model. The vertical gray dashed lines represent the highest likelihood breakpoint values
Fig. 4 Demographic models tested using an information-theoretic based model selection approach. The black curve depicts the empirical SPD population proxy whereas the red curves represents the model fits with best fitting thresholds for each model. The vertical gray dashed lines represent the highest likelihood breakpoint valuesCC BY · PubMed Central
Fig. 5 Regression fits and demographic growth rates of the best-fitting model. Top: Population proxy (in black) and regression fits of the best-fitting model of demographic dynamics. Bottom: Comparison of inferred annual growth rates derived from the best-fitting model with those derived from other case studies of prehistoric foragers in Wyoming & Colorado2 and the Western Mediterranean Mesolithic38. In both plots, the blue, red and green thick lines and the associated lighter-color shaded areas represent respectively the running mean values and the corresponding 95.4% uncertainties, whereas the grey shaded areas represent the range of breakpoint values considered
Fig. 5 Regression fits and demographic growth rates of the best-fitting model. Top: Population proxy (in black) and regression fits of the best-fitting model of demographic dynamics. Bottom: Comparison of inferred annual growth rates derived from the best-fitting model with those derived from other case studies of prehistoric foragers in Wyoming & Colorado2 and the Western Mediterranean Mesolithic38. In both plots, the blue, red and green thick lines and the associated lighter-color shaded areas represent respectively the running mean values and the corresponding 95.4% uncertainties, whereas the grey shaded areas represent the range of breakpoint values consideredCC BY · PubMed Central

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Authors
Fernández-López de Pablo, J., Gutiérrez-Roig, M., Gómez-Puche, M., McLaughlin, R., Silva, F., & Lozano, S.
Venue
Nature Communications
Publisher
Springer Science and Business Media LLC
Published
2019-04-23
Volume
10
Issue
1
ISSN
2041-1723
DOI
10.1038/s41467-019-09833-3
PMC
PMC6478856
Cited by
69
References
4
Language
en
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Fernández-López de Pablo, J., Gutiérrez-Roig, M., Gómez-Puche, M., McLaughlin, R., Silva, F., & Lozano, S. (2019). Palaeodemographic modelling supports a population bottleneck during the Pleistocene-Holocene transition in Iberia. Nature Communications. https://doi.org/10.1038/s41467-019-09833-3