The claim in one paragraph
Fluctuations in a pulled wave fall only logarithmically with the number of individuals per site, , because a few individuals at the tip control the wave. A naive expectation is that pushed waves average fluctuations like any large population, so their fluctuations should fall as . The paper finds that this holds only for fully pushed waves. In semi-pushed waves, with , the front wandering and the rate of diversity loss both fall as a power of with an exponent between and .
The evidence comes in two parts: simulations of a stepping-stone model across cooperativity and population density, and a perturbation theory that explains where the scaling breaks down. The claim of universality, that the boundary depends only on the speed ratio, rests on three different growth laws collapsing onto one curve.
Source: G. Birzu
Where to look first
Read Eq. (3) and Fig. 1 together: the growth law with cooperativity , and the speed rising above the Fisher speed beyond . The Methods section gives the simulation, Eq. (11), as dispersal followed by growth and multinomial resampling in each deme. That is the model the Lab runs.
Fig. 5 carries the claim about diversity. Panel A shows the heterozygosity decaying exponentially, panel B its rate against on log-log axes, and panel C the fitted exponent against . Eqs. (6) and (7) give the boundary between the two pushed classes. The supplementary information holds the derivations and the closed forms.
Source: G. Birzu
How the rate is measured
The supplementary section on the duration of simulations is short and worth reading closely. Heterozygosity is averaged over the demes of the simulation box and then over independent runs. The fit of against time ends at the last time when at least runs still hold both alleles. Its start is chosen to maximise the quality of the fit, with a window of at least generations. The exponents are fitted only for , because the power laws are asymptotic.
Two consequences matter for a reader. The early, non-exponential part of the decay is excluded by design. And a fitted exponent over a finite range of need not equal its asymptotic value: Fig. 5B shows pulled waves with an effective exponent near although the theory gives a logarithmic law, which corresponds to an exponent of zero. For front wandering, van Saarloos’s review records the same kind of law, a front diffusion constant falling as , and notes that Brunet and Derrida needed a special method to reach large enough to see it.
Source: G. Birzu · W. van Saarloos
Reading Eq. (5)
Eq. (5) is the perturbative rate of diversity loss. The prefactor is the central-limit scaling. The ratio of integrals weighs each position in the front: the denominator counts ancestry, with the same weight as in chapter 6, and the numerator counts where drift acts.
At the tip , so the numerator integrand behaves as . It converges only if , which holds when exceeds . Below it the integral diverges, a cutoff at low density is needed, and the cutoff brings in a power of other than . For the cooperative growth law with , SI Eq. (S122) gives the integral in closed form.
Source: G. Birzu
Worked example: reproducing one rate
Problem. Take , , , and . Predict and compare with the Lab model.
Closed form. , and . The product is , and dividing by gives per generation. Evaluating Eq. (5) with the lattice front profile instead of the continuum one gives .
Simulation. seeded runs were warmed up for generations, the two alleles were then remixed :, and the heterozygosity was averaged over the demes from ten behind to three ahead of the front. A straight-line fit of between generations and gives , with a jackknife error over runs. The ratio to the perturbative value is .
Second point. At the measurement is against , standard errors low. Between the two sizes the rate falls by , against for an exact law.
Answer. For a fully pushed wave the Lab model reproduces both the size of and its scaling within the errors of a few hundred runs.
Source: G. Birzu
What this reproduction does not show
For pulled waves the Lab finds at and at . The ratio is far from the factor of that a law would give, but also below the of the asymptotic law. As an effective exponent it is , close to the value in Fig. 5B, though our range of is lower than the paper’s, so the agreement may be partly coincidental.
The Lab run differs from the paper in several ways: a few hundred runs instead of a thousand, a window ending at live runs instead of , heterozygosity over fourteen demes near the front rather than the whole box, and well below . We did not measure the semi-pushed exponents, the front diffusion constant or the collapse of three growth laws in Fig. 6. Those are the paper’s central new results, and checking them would need much larger runs. A follow-up by Birzu, Matin, Hallatschek and Korolev reports that dispersal which increases with density suppresses drift at the edge, so the classes depend on how individuals move as well as how they grow. The Lab keeps dispersal fixed.