- S. Shennan & K. Edinborough, Prehistoric population history: from the Late Glacial to the Late Neolithic in Central and Northern Europe (Journal of Archaeological Science, 2007).
- Mark Collard et al., Radiocarbon evidence indicates that migrants introduced farming to Britain. Antiquity, 2009.

# Category Archives: demographics

## Revisiting the demographics of Northern and Central Europe in the Neolithic and Chalcolithic periods

## Reconstructing human demographic history from IBS segments

Figure 1. An eight base-pair tract of identity by state (IBS). |

**Kelley Harris & Rasmus Nielsen,**[doi:10.1371/journal.pgen.1003521]

*Inferring Demographic History from a Spectrum of Shared Haplotype Lengths*. PLoS Genetics 2013. Open access → LINKAbstract

There has been much recent excitement about the use of genetics to elucidate ancestral history and demography. Whole genome data from humans and other species are revealing complex stories of divergence and admixture that were left undiscovered by previous smaller data sets. A central challenge is to estimate the timing of past admixture and divergence events, for example the time at which Neanderthals exchanged genetic material with humans and the time at which modern humans left Africa. Here, we present a method for using sequence data to jointly estimate the timing and magnitude of past admixture events, along with population divergence times and changes in effective population size. We infer demography from a collection of pairwise sequence alignments by summarizing their length distribution of tracts of identity by state (IBS) and maximizing an analytic composite likelihood derived from a Markovian coalescent approximation. Recent gene flow between populations leaves behind long tracts of identity by descent (IBD), and these tracts give our method power by influencing the distribution of shared IBS tracts. In simulated data, we accurately infer the timing and strength of admixture events, population size changes, and divergence times over a variety of ancient and recent time scales. Using the same technique, we analyze deeply sequenced trio parents from the 1000 Genomes project. The data show evidence of extensive gene flow between Africa and Europe after the time of divergence as well as substructure and gene flow among ancestral hominids. In particular, we infer that recent African-European gene flow and ancient ghost admixture into Europe are both necessary to explain the spectrum of IBS sharing in the trios, rejecting simpler models that contain less population structure.

**Update:** even Dienekes agrees, on his own well documented reasoning, with a x2 mutation rate being necessary for the above graph.

## How hunter-gatherers slowed farmers’ advance.

**Neus Isern and Joaquim Fort,**

*Anisotropic dispersion, space competition and the slowdown of the Neolithic transition*. New Journal of Physics, 2010. Open access.We can see from equation (9) that if the Mesolithic (indigenous) population density

Mincreases along the directiony, then the probability of Neolithic invaders to jump forward (θ = π/2) is minimum and the probability to jump backwards (θ = 3π/2) is maximum.

*y*is the main vector of Neolithic expansion, drawn along the Morava-Danube axis in SE-NW direction.

From equation (22), we see that if the Mesolithic population density increases with

y, then the front speed decreases because of two effects: (i) the higher the gradient of the reduced Mesolithic densitym, the higher the correction on the front speed; (ii) the speed also changes if there is less available space for the Neolithic population, i.e. for lower values ofs= (1–m(y)) (ifs= 1, this second effect disappears).

Fig. 3 (legend below) |

**Figure 3.**Curves: relative Neolithic front speed predicted by a model with the dispersion and growth processes dependent on the presence of Mesolithic populations, equation (25). Symbols: observed front speeds calculated from archaeological data [9].

A_{1}= 0.999/1300,B_{1}= 0;A_{2}= –0.1 = –B_{2}=A_{3}=B_{3}, τ_{2}= –ln(10.99)/1300 = –τ_{3};A_{4}= 0.99,B_{4}= 42, τ_{4}= 1/0.007.

Comparing the results from equation (25) to those from archaeological data in figure 3, we see that, even though none of the four test functions reproduce exactly the behavior of the archaeological data (which is not surprising for such a complex phenomenon), they do give a good approximation to the general behavior (especially

m_{4}). Thus, a simple physical model can explain qualitatively the decrease in the front speed during the Neolithic expansion range in Europe. Therefore, physical models are useful to explain not only the average Neolithic front speed [8] , but also its gradual slowdown in space.

## Revisiting Bocquet-Appel 2005: the population of Europe in the Paleolithic.

*Estimates of Upper Palaeolithic meta-population size in Europe from archaeological data*. Journal of Archaeological Sciences 2005. (PDF).

Fig. 5 (2nd part). Population estimates for LGM (top) and Late UP (bottom) |