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A Goldberg

A Modi

A Olivieri

A Szécsényi-Nagy

A Timpson

A Williams

AJ Ammerman

B Horejs

BS Arbuckle

C Gamba

C Perlès

CJ Stevens

D Orton

ER Crema

F Silva

G Brandt

HJ Zahid

I Lazaridis

I Mathieson

J Fort

J-F Berger

J-P Bocquet-Appel

JB Pereira

JW Rick

K Manning

L Sørensen

LM Cassidy

M Collard

M Gkiasta

M Porčić

M Porčić

M Rivollat

M Zeder

M Zvelebil

NJ Whitehouse

NN Johannsen

P Flohr

P González-Sampériz

P Skoglund

PJ Reimer

R Bollongino

R Pinhasi

S Forenbaher

S Shennan

T Günther

TA Surovell

TR McLaughlin

W Haak

Y Pailler

Z Hofmanová

Ç Çilingiroğlu

AbstractLarge radiocarbon datasets have been analysed statistically to identify, on the one hand, the dynamics and tempo of dispersal processes and, on the other, demographic change. This is particularly true for the spread of farming practices in Neolithic Europe. Here we combine the two approaches and apply them to a new, extensive dataset of 14,535 radiocarbon dates for the Mesolithic and Neolithic periods across the Near East and Europe. The results indicate three distinct demographic regimes: one observed in or around the centre of farming innovation and involving a boost in carrying capacity; a second appearing in regions where Mesolithic populations were well established; and a third corresponding to large-scale migrations into previously essentially unoccupied territories, where the travelling front is readily identified. This spatio-temporal patterning linking demographic change with dispersal dynamics, as displayed in the amplitude of the travelling front, correlates and predicts levels of genetic admixture among European early farmers.</jats:p

Fabio Silva

Marc Vander Linden

Crossref

Scientific Reports

Amplitude of travelling front as inferred from 14C predicts levels of genetic admixture among European early farmers

Large radiocarbon datasets have been analysed statistically to identify, on the one hand, the dynamics and tempo of dispersal processes and, on the other, demographic change. This is particularly true for the spread of farming practices in Neolithic Europe. Here we combine the two approaches and apply them to a new, extensive dataset of 14,535 radiocarbon dates for the Mesolithic and Neolithic periods across the Near East and Europe. The results indicate three distinct demographic regimes: one observed in or around the centre of farming innovation and involving a boost in carrying capacity; a second appearing in regions where Mesolithic populations were well established; and a third corresponding to large-scale migrations into previously essentially unoccupied territories, where the travelling front is readily identified. This spatio-temporal patterning linking demographic change with dispersal dynamics, as displayed in the amplitude of the travelling front, correlates and predicts levels of genetic admixture among European early farmers

Silva, Fabio

Vander Linden, M.

Bournemouth University Research Online

Amplitude of travelling front as inferred from 14C predicts levels of genetic admixture among European early farmers.

Silva, F

Linden, MV

UCL Discovery

1SCIEnTIFIC REPORtS |  (2018) 8:12809  | DOI:10.1038/s41598-018-30976-8www.nature.com/scientificreportsAuthor Correction: Amplitude of travelling front as inferred from 14C predicts levels of genetic admixture among European early farmersFabio Silva  1,2 & Marc Vander Linden3Correction to: Scientific Reports https://doi.org/10.1038/s41598-017-12318-2, published online 20 September 2017In this Article we uncritically employed the terms ‘travelling wave’ and ‘travelling wave-front’ to describe the spread of the Neolithic. There is, however, a distinction between these terms which relate to two different models of dispersal. In Archaeology, the term ‘wave-front’ has been largely associated with the demic diffusion model of Ammerman and Cavalli-Sorza (1971) where the population of previously occupied territories is kept at carrying capacity even after the wave-front passes through them. By contrast, in a travelling wave model the population of previously occupied territories would decrease back to neutral growth levels once the wave moves out of those territories.As a result, in the Conclusion section,“However, contrary to its interpretation as episodes of population growth and sudden collapse, their sequential staggering through time and space, identified here for the first time, suggests that they rather correspond to the demographic signature of a travelling wave-front. In this interpretation, the ‘boom’ is linked to the arrival of new people, whilst the ‘bust’ must be understood as due to outgoing migrants, resuming their spread into a new region. This interpretation is consistent with the expected properties of demic diffusion, as only the wave-front experiences a noticeable demographic pressure, whilst the meta-population follows a neutral growth curve3, as indicated by the SPD across the entire research area.”should read:“However, contrary to its interpretation as episodes of population growth and sudden collapse, their sequential staggering through time and space, identified here for the first time, suggests that they rather correspond to the demographic signature of a travelling wave. In this interpretation, the ‘boom’ is linked to the arrival of new peo-ple, whilst the ‘bust’ must be understood as due to outgoing migrants, resuming their spread into a new region. This interpretation is not consistent with the expected properties of demic diffusion, as only the regions being passed by the travelling wave experience a noticeable demographic pressure, whilst the meta-population follows a neutral growth curve3, as indicated by the SPD across the entire research area.”The conclusions of the Article are unaffected by this change. The authors apologise for the error and any confu-sion caused.1IPHES, Institut Català de Paleoecologia Humana i Evolucio ́ Social, Tarragona, Spain and Àrea de Prehistòria, Universitat Rovira i Virgili (URV), Zona Educacional, 4 – Campus Sescelades URV (Edifici W3), 43007, Tarragona, Spain. 2Faculty of Humanities & Performing Arts, University of Wales Trinity Saint David, Lampeter Campus, Ceredigion, SA48 7ED, United Kingdom. 3UCL Institute of Archaeology, University College London, 31-34 Gordon Square, London, WC1H 0PY, United Kingdom. Correspondence and requests for materials should be addressed to F.S. (email: fsilva@iphes.cat)Published: xx xx xxxxOPENwww.nature.com/scientificreports/2SCIEnTIFIC REPORtS |  (2018) 8:12809  | DOI:10.1038/s41598-018-30976-8Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Cre-ative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not per-mitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. © The Author(s) 2018

Author Correction: Amplitude of

travelling front as inferred from 14C

predicts levels of genetic admixture

among European early farmers

Author Correction: Amplitude of travelling front as inferred from 14C predicts levels of genetic admixture among European early farmers.

Author Correction: Amplitude of travelling front as inferred from 14C predicts levels of genetic admixture among European early farmers

 1 Supplementary Information for Amplitude of travelling front as inferred from 14C predicts levels of genetic admixture among European early farmers Fabio Silva and Marc Vander Linden  Convex Hull Area 10,900 BP9,100 BP8,100 BP7,800 BP7,200 BP6,400 BPyears BPChange in Area14000 12000 10000 8000 6000 4000 Supplementary Figure S1 – Heuristic analysis of the changes in Neolithic diffusion area through time, showing the area of the convex hull (top) and the change in area (bottom). The latter shows distinct periods of expansion interspersed with pauses. The vertical lines show the onset of the major expansion episodes into new territories.  12000 10000 8000 6000 4000 20000.000.020.040.060.080.10Uncorrectedyears BPAnnual Growth Rate (%)PerosGoldewijkZahidShennanIIIIIIIVaIVbVaVbVIaVIbVIIaVIIbALL12000 10000 8000 6000 4000 20000.000.020.040.060.080.10Correctedyears BPAnnual Growth Rate (%)PerosGoldewijkZahidShennanIIIIIIIVaIVbVaVbVIaVIbVIIaVIIbALL Supplementary Figure S2 – Observed growth rates (coloured bars) of the null models which were fitted to the local Mesolithic SPDs both uncorrected (left) and corrected for taphonomic bias (right), compared to other values found in the literature (grey bars). The width of each bar represents one standard deviation, and each bar extends over the period in which the null model was fitted.    2  III: Aegean N=100 p=0.5634years BP12000 11000 10000 9000 8000 7000 6000 5000 4000N=1116years BP12000 11000 10000 9000 8000 7000 6000 5000 4000N=984years BP12000 11000 10000 9000 8000 7000 6000 5000 4000N=274years BP12000 11000 10000 9000 8000 7000 6000 5000 4000N=100Va: Central Europe N=984 p<0.0001VIIb: UK & Ireland N=1116 p<0.0001IVa: Balkans N=274 p<0.0001 Supplementary Figure S3 – Sum of Radiocarbon Probability Densities (SPD) for the Balkans, Central Europe and United Kingdom & Ireland regions, with overlaid 500-year intervals (vertical dotted lines) to emphasize their spatio-temporal staggering. For example the dip around 7,500 cal BP in the Balkans matches the expansion of farming into Central Europe. The latter slowly falls down to null model values by about 6,000 cal BP, which matches the expansion into the United Kingdom & Ireland.  3   Database Number of 14C dates MCSPD p-value Growth Rate Growth Rate corrected for taphonomic bias I - Levant 1,530 <0.0001 0.00354 ± 0.00028 0.00186 ± 0.00026 II - Anatolia 1,098 <0.0001 0.01088 ± 0.00206 0.00312 ± 0.00212 III - Aegean 567 0.5634 0.06431 ± 0.00200 0.05375 ± 0.00195 IVa - Balkans 1,219 <0.0001 0.05546 ± 0.00080 0.04451 ± 0.00079 IVb - Adriatic 315 <0.0001 0.01790 ± 0.00098 0.00702 ± 0.00097 Va - Central Europe 2,359 <0.0001 0.04066 ± 0.00059 0.03288 ± 0.00062 Vb - Western Med 2,289 0.0006 0.05549 ± 0.00049 0.04599 ± 0.00051 VIa - Northern Europe 910 0.21192 0.04969 ± 0.00051 0.04109 ± 0.00052 VIb - Atlantic Façade 243 0.35876 0.06849 ± 0.00126 0.05795 ± 0.00124 VIIa - Southern Scandinavia 757 0.0012 0.03076 ± 0.00052 0.02206 ± 0.00055 VIIb - UK & Ireland 3,244 <0.0001 0.03761 ± 0.00035 0.02780 ± 0.00037 Entire Dataset 14,535 <0.0001 0.04381 ± 0.00019 0.03392 ± 0.00020 Supplementary Table S1 – Table showing the number of 14C dates used, obtained MCSPD p-value and growth rates, including their uncertainty, both uncorrected and corrected for taphonomic bias (see main text), for each region and for the entire dataset.  

Amplitude of travelling front as inferred from C-14 predicts levels of genetic admixture among European early farmers

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Author Correction: Amplitude of travelling front as inferred from 14C predicts levels of genetic admixture among European early farmers.

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