The Proceedings of the Eighth International Conference on Creationism (2018)

Africa, and many Muslim populations are exploding. Arguable all these types of genetic change have been going on for as long as man has existed. Logically, these forces should cause “accelerated drift” (i.e., accelerated allele frequency change). If these forces are ignored, genetic simulations will consistently indicate that populations are older than they really are, and that populations can only change extremely slowly. A major new paper has just been released that demonstrates rapid and massive demographic shifts in the early human population ( Narasimhan et al. 2018). This study, involving 92 scientists, clearly shows the historical reality of massive global demographic shifts. All such major demographic shifts should effective accelerate allele spreading. A simple illustration of how genetic drift might really be operating at a much higher rate, can be seen when we consider a colored liquid carefully added to water. If there is very little initial mixing, the added solution will diffuse very slowly and at a constant rate. But if there is any type stirring, the rate of mixing is much faster and the exact rate becomes unpredictable. Another illustration would be trying to study ocean chemistry or marine biology based on diffusion alone, without taking into account ocean currents. It should be obvious that there are numerous demographic forces that act to “stir” the gene pool of any global population. We propose the term demographic stirring to describe this phenomenon, and we suggest that it is ubiquitous in nature. Any type of demographic stirring should greatly accelerate the rate of genetic drift and should eclipse that special type of drift that is simply diffusion/ sampling error. We suggest all future population modeling and simulation should take into consideration demographic stirring. People doing genetic simulations (including the authors of this paper), have failed to include these important demographic forces in their models for the simple reason that these factors are complicated and challenging to realistically simulate. To take into account demographic stirring, population models and simulations need some type of correction factor. All the simulation experiments recorded in this paper employed a maximal population size of 1000 individuals, instead of the conventionally assumed historical human population size of 10,000 individuals. Our smaller populations help compensate for the complete absence of any natural “demographic stirring” in our simulations. We observe that this “correction factor” very effectively accelerates allele spreading, yielding the distributions we show in Figure 8. It is important to realize that while the rate of classical genetic drift is almost entirely a function of population size, demographic stirring is not directly tied to population size. Therefore, in larger global populations, classical genetic drift is essentially irrelevant, and the only meaningful factors that change allele frequencies are natural selection and other types of demographic stirring. Amajor limitation of numerical simulation is that it lacks the ability to model extremely large populations. In particular, we cannot model the billions of very rare alleles that are now accumulating in our very large population. These nearly countless rare alleles are the un-plotted alleles in the “invisible bin” (frequencies 0–1%) of our histograms and linear graphs. While it is a practical necessity to ignore such alleles in our plots, we cannot ignore them in our thinking. Historical rapid lineage expansions that have happened at the expense of other sub-populations ( Narasimhan et al. 2018), should pull many alleles out of the invisible bin and into higher frequency bins. Our simulations fail to model the vast number of rare alleles that would accumulate as the human population grew rapidly from thousands of people to billions of people. Realistically, any type of demographic stirring would draw large numbers of SNPs into the 1–99% frequency range, helping to explain the large number of actually observed human polymorphisms. Therefore, there is an enormous reservoir of SNPs in the actual human population that Mendel is neither currently simulating or plotting. We acknowledge that reducing population size is not a perfect correction factor – but it seems to us better than entirely ignoring the numerous major demographic factors such as natural selection and lineage expansions. Ideally, all population models and simulations should eventually take into consideration some degree of demographic stirring and should include some type of demographic correction factor to achieve greater biological realism. Despite the complication associated with substituting reduced population size for demographic stirring, we are very encouraged by what our simulations show. We summarize below what we have learned about the three primary mechanisms that help us reconcile a literal Adam and Eve with the observed human allele distribution. 1. Adam and Eve were created heterozygous, followed by population constrictions that accelerated genetic drift. Our preliminary simulations of a heterozygous Adam and Eve were over-simplified (Figures 3a, 3b, 3c, 4a, 4b, 6a) and yielded distributions different from the actually observed allele frequency distribution (Figure 1a). When designed alleles were combined with newly arising mutations, the designed alleles had a humped distribution along the x-axis, while the mutational alleles had a nearly vertical distribution, with almost all mutational alleles being squeezed into the first bin on the far left of the histogram (Figure 6a). Based upon our preliminary simulations, it seemed problematic for us to reconcile the designed diversity model to the observed allele frequency distribution. We found that our results began to approximate the modern allele distributions when we added other key elements to our formula. This included several instances of reduced or constrained population size, and more than one initial allele frequency. Most importantly, we required accelerated genetic drift, which is essential for filling the allele distribution “gap” in the range of 3–20%. It is generally assumed that accelerated genetic drift only happens when a population is relatively small. As soon as the population size reaches 1,000 or more, classical genetic drift grinds to a near standstill (Carter and Powell 2016). Substantial allele spreading required that early in the simulation there must be at least one episode where the population size is very small for a number of generations. Fortunately, the biblical model provides two and perhaps three such episodes: a) the tiny initial population in Eden, consisting of just two people; b) the tiny post-flood population of just six reproducing adults; and c) a possible stall in population growth among the emerging tribes, following the dispersion out of Babel (which may well have been chaotic/violent). We might have simulated a single but more prolonged population bottleneck Sanford et al. ◀ Designed genetic diversity in Adam and Eve ▶ 2018 ICC 211