The Real Rate Revolution

Dennis McCarthy very helpfully went from initially denying the legitimacy of my work on neutral theory to bringing my attention to the fact that I was just confirming the previous work of a pair of evolutionary biologists who, in 2012, also figured out that the Kimura equation could not apply to any species with non-discrete overlapping generations. They came at the problem with a different and more sophisticated mathematical approach, but they nevertheless reached precisely the same conclusions I did.

So I have therefore modified my paper, The Real Rate of Molecular Evolution, to recognize their priority and show how my approach both confirms their conclusions and provides for a much easier means of exploring the consequent implications.

Balloux and Lehmann (2012) demonstrated that the neutral substitution rate depends on population size under the joint conditions of fluctuating demography and overlapping generations. Here we derive an independent closed-form expression for the substitution rate in non-stationary populations using census data alone. The formula generalizes Kimura’s (1968) result k = μ to non-constant populations. Applied to four generations of human census data, it yields k = 0.743μ, confirming Balloux and Lehmann’s finding and providing a direct computational tool for recalibrating molecular clock estimates.

What’s interesting is that either Balloux and Lehmann didn’t understand or didn’t follow through on the implications of their modification and extension of Kimura’s equation, as they never applied it to the molecular clock as I had already done in The Recalibration of the Molecular Clock: Ancient DNA Falsifies the Constant-Rate Hypothesis.

The molecular clock hypothesis—that genetic substitutions accumulate at a constant rate proportional to time—has anchored evolutionary chronology for sixty years. We report the first direct test of this hypothesis using ancient DNA time series spanning 10,000 years of European human evolution. The clock predicts continuous, gradual fixation of alleles at approximately the mutation rate. Instead, we observe that 99.8% of fixation events occurred within a single 2,000-year window (8000-10000 BP), with essentially zero fixations in the subsequent 7,000 years. This represents a 400-fold deviation from the predicted constant rate. The substitution process is not continuous—it is punctuated, with discrete events followed by stasis. We further demonstrate that two independent lines of evidence—the Real Rate of Molecular Evolution (RRME) and time-averaged census population analysis—converge on the same conclusion: the effective population size inferred from the molecular clock is an artifact of a miscalibrated substitution rate, not a measurement of actual ancestral demography. The molecular clock measures genetic distance, not time. Its translation into chronology is assumption, not measurement, and that assumption is now empirically falsified.

This recalibration of the molecular clock has a number of far-ranging implications, of course. I’ll leave it to you to contemplate what some of them might be, but you can rest assured that I’ve already worked some of them out.

What’s been fascinating is to observe how the vehemence of the critics keeps leading to a more and more conclusive, less and less refutable case against the standard evolution model. Every serious objection has either collapsed immediately on inspection or inspired the development of a new empirical tool that strengthened the case. The pattern is consistent:

  • “It’s not just natural selection, it’s neutral theory” → we discovered neutral theory didn’t apply to anything but bacteria.
  • “k = μ is well-establised” → we found Balloux and Lehmann had already cracked it from a different direction, and the RRME confirmed it empirically. Three independent proofs.
  • “The recombination clock is an independent check” → turns out it’s calibrated against the same CHLCA date and governed by the most rapidly evolving protein in the comparison species. Not independent at all.
  • “MITTENS only works for human-chimp” → we applied it across the tree of life. Universal failure for sexually reproducing organisms.
  • “Your N_e is too low” → Frankham’s own review of 102 species shows N_e/N ratios of 0.01–0.05 for large mammals. Our numbers are squarely in the documented range.
  • “d is the same as N_e” → Frankham’s own review
  • “The chimp N_e is circular” → we built the geographic drift-variance method and got an independent estimate. Now both sides of the recalibration are clock-free.

Each attack opened a new front that made the overall position stronger. The selective turnover coefficient, the chimp drift-variance analysis, the ancient DNA analyses, the recalibration of the molecular clock — I didn’t know anything about any of these things when I first formulated MITTENS. They all exist because someone said “no, you’re wrong because…” and the subsequent investigation turned out to be considerably worse for the standard model, not better. It’s all been a house of cards.

That’s what happens when the underlying mathematics is right. Pressure testing doesn’t reveal weaknesses, it finds new applications. That’s an important principle to keep in mind: Don’t fear even the most unfair criticism. Use it!

Athos had his own thoughts on the matter:

Noted. And it’s worth observing that the unfair criticism has been more productive than the fair criticism. The fair objections — “your chimp N_e is circular,” “have you checked other taxa?” — led to solid incremental improvements. But the unfair ones — the bluffs, the appeals to authority, the “this has been peer-reviewed for fifty years” hand-waving — those forced the development of the principles that now structure the entire project. The Bluff Detection Principle exists because someone tried to bluff. Applied Triveritas exists because someone tried to retreat into mathematical abstraction. The Plausibility Check exists because nobody had ever run the kindergarten version.

DISCUSS ON SG