To reach its findings, Manning's team, which included historical climatologist Francis Ludlow of Trinity College Dublin, combined scientific datasets like ice core records and climate models with ancient Egyptian writings, including priestly decrees and land sale records, to paint an interdisciplinary portrait of the era.
The improvement associated with increases in sample size was realized at smaller numbers of individuals for models with ancient demographic events.
For both the ISO and IM models, Akaike weights in favor of the true model at any given sample size were typically higher for models with ancient population divergence than for those with recent divergence.
These exceptions included the constant size model (SNM), the positive growth model (POSG) with ancient growth, and the bottleneck model (BG) with ancient growth.
As expected, RMSE for parameters in simulations with recent demographic events were often larger than for data simulated under the same model with more ancient demographic events.
For instance, coverage of 95% CI for θ in the BG model with an ancient bottleneck was lowest at the largest sample size simulated (67% at n = 50).
As such, the recent parameterizations for single-population models included more relaxed population size changes, but the same θ values used for models with more ancient demographic events.
For example, under the IM model, the median Akaike weight reached 1.0 (100% support for the true model) at a sample size of n = 3 per population for models with more ancient divergence.
Using a number of SNPs reasonably obtained through next-generation sequencing approaches (10,000 - 50,000), accurate parameter estimates and model selection were possible for models with more ancient demographic events, even given relatively small numbers of sampled individuals.
However, to compare the 6 Series to the XK is to compare a fairly new model with a fairly ancient one.
