It seems this paper is an attempt to bat down critics of 1.0 with an expanded timeframe from 10k to 4k bp. It cover almost 14,000k dates in 12 regions that mostly show a bust pattern after the Early Neolithic.
What I find interesting is that there are catastrophic declines in Europe throughout the third millennium, even after the arrival of Bell Beakers in the relevant regions. Of course, dates end at 2,000 B.C., which is frustrating and very relevant for this blog. I would imagine an increase occurred everywhere after this date.
There is, however, a massive population spike with the arrival of Maritime Bell Beakers in Bohemia and Moravia. The population of Britain more than doubles and the population of Ireland nearly quadruples with the arrival of Beakers (1.0 paper). The population of the Czech Republic almost triples and quadruples at the end of the millennium.
Putting this in context is more interesting. It's not surprising to see the population of Britain expanding during this time, as it would appear to have been the subject of ongoing Beaker immigration from everywhere (Iberia, Lower Rhine and Central Europe).
However, the Moravian and Bohemian numbers are simply jaw dropping. Not only did it defy the continental trend from the sampled areas, it was likely the baby factory that sent immigrants to other parts of Europe, such as Little Poland, Hungary and Wessex. So it wasn't just 3-4 times expansion.
It's also worth pointing out that the longevity and infant mortality estimates of several of the Moravian and Bohemian cemeteries are almost unrealistically modern. Beakers in this region appear to have lived long and healthy lives. To me this indicates the early establishment of political stability and rule of law.
In a previous study we presented a new method that used summed probability distributions (SPD) of radiocarbon dates as a proxy for population levels, and Monte-Carlo simulation to test the significance of the observed fluctuations in the context of uncertainty in the calibration curve and archaeological sampling. The method allowed us to identify periods of significant short-term population change, caveated with the fact that around 5% of these periods were false positives. In this study we present an improvement to the method by applying a criterion to remove these false positives from both the simulated and observed distributions, resulting in a substantial improvement
to both its sensitivity and specificity. We also demonstrate that the method is extremely robust in the face of small sample sizes. Finally we apply this improved method to radiocarbon datasets from European regions, covering the period 8000 to 4000 BP. As in our previous study, the results reveal a boom-bust pattern for most regions, with population levels rising rapidly after the local arrival of farming, followed by a crash to levels much lower than the peak. The prevalence of this phenomenon, combined with the dissimilarity and lack of synchronicity in the general shapes of the regional SPDs, supports the hypothesis of endogenous causes.