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Evolution as statistical physics

L4 · Chapter 7

Reading “Neither pulled nor pushed” and checking its drift claim

Birzu, Hallatschek and Korolev claim that waves of growth and dispersal come in three classes, not two, and that the middle class keeps far less genetic diversity than a pushed wave should. This chapter is a guide to reading the paper with the Lab beside you. It shows where each claim sits, which quantity carries it, and which numbers we could reproduce, which we could not, and why.

The claim in one paragraph

Fluctuations in a pulled wave fall only logarithmically with the number of individuals per site, NN, 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 1/N1/N. The paper finds that this holds only for fully pushed waves. In semi-pushed waves, with 1<v/vF<3/(22)1<v/v_{\mathrm F}<3/(2\sqrt2), the front wandering and the rate of diversity loss both fall as a power of NN with an exponent between 00 and −1-1.

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 1/N1/N 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 BB, and the speed rising above the Fisher speed beyond B=2B=2. 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 HH decaying exponentially, panel B its rate Λ\Lambda against NN on log-log axes, and panel C the fitted exponent αh\alpha_h against BB. Eqs. (6) and (7) give the boundary between the two pushed classes. The supplementary information holds the derivations and the closed forms.

H(t)=⟨2f(1−f)⟩∼e−Λt,Λ∝NαhH(t)=\bigl\langle 2f(1-f)\bigr\rangle\sim e^{-\Lambda t},\qquad \Lambda\propto N^{\alpha_h}
The measured quantity: average heterozygosity at the front, its decay rate, and the exponent that classifies the wave.

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 10001000 independent runs. The fit of ln⁡H\ln H against time ends at the last time when at least 5050 runs still hold both alleles. Its start is chosen to maximise the quality of the fit, with a window of at least 10001000 generations. The exponents are fitted only for N>104N>10^4, 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 NN need not equal its asymptotic value: Fig. 5B shows pulled waves with an effective exponent near −0.33-0.33 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 1/ln⁡3N1/\ln^3N, and notes that Brunet and Derrida needed a special method to reach large enough NN to see it.

Source: G. Birzu · W. van Saarloos

Reading Eq. (5)

Eq. (5) is the perturbative rate of diversity loss. The prefactor 1/N1/N is the central-limit scaling. The ratio of integrals weighs each position in the front: the denominator counts ancestry, with the same weight ρ2evζ/D\rho^2e^{v\zeta/D} as in chapter 6, and the numerator counts where drift acts.

At the tip ρ∼e−kζ\rho\sim e^{-k\zeta}, so the numerator integrand behaves as e(2v/D−3k)ζe^{(2v/D-3k)\zeta}. It converges only if 2v/D<3k2v/D<3k, which holds when v/vFv/v_{\mathrm F} exceeds 3/(22)3/(2\sqrt2). Below it the integral diverges, a cutoff at low density is needed, and the cutoff brings in a power of NN other than −1-1. For the cooperative growth law with B>4B>4, SI Eq. (S122) gives the integral in closed form.

Λ=1N ∫−∞∞γf ρ3(ζ) e2vζ/D dζ[∫−∞∞ρ2(ζ) evζ/D dζ]2\Lambda=\frac{1}{N}\,\frac{\displaystyle\int_{-\infty}^{\infty}\gamma_f\,\rho^3(\zeta)\,e^{2v\zeta/D}\,d\zeta}{\Bigl[\displaystyle\int_{-\infty}^{\infty}\rho^2(\zeta)\,e^{v\zeta/D}\,d\zeta\Bigr]^2}
Eq. (5) of the paper for the rate of diversity loss, with ρ\rho the normalised density profile in the frame moving with the front.
Λ=γf4πNg0B2D (B+4)tan⁡2πB(B>4)\Lambda=\frac{\gamma_f}{4\pi N}\sqrt{\frac{g_0B}{2D}}\,(B+4)\tan\frac{2\pi}{B}\qquad(B>4)
SI Eq. (S122): the same rate for the cooperative growth law, valid for fully pushed waves.

Source: G. Birzu

Worked example: reproducing one rate

Problem. Take B=10B=10, g0=0.01g_0=0.01, D=0.125D=0.125, γf=1\gamma_f=1 and N=300N=300. Predict Λ\Lambda and compare with the Lab model.

Closed form. 0.01×10/0.25=0.632\sqrt{0.01\times10/0.25}=0.632, B+4=14B+4=14 and tan⁡(2π/10)=0.727\tan(2\pi/10)=0.727. The product is 6.436.43, and dividing by 4π×300=37704\pi\times300=3770 gives Λ=1.71×10−3\Lambda=1.71\times10^{-3} per generation. Evaluating Eq. (5) with the lattice front profile instead of the continuum one gives 1.70×10−31.70\times10^{-3}.

Simulation. 320320 seeded runs were warmed up for 15001500 generations, the two alleles were then remixed 5050:5050, and the heterozygosity was averaged over the demes from ten behind to three ahead of the front. A straight-line fit of ln⁡H\ln H between generations 10001000 and 21002100 gives Λ=(1.68±0.20)×10−3\Lambda=(1.68\pm0.20)\times10^{-3}, with a jackknife error over runs. The ratio to the perturbative value is 0.990.99.

Second point. At N=1000N=1000 the measurement is (4.3±0.7)×10−4(4.3\pm0.7)\times10^{-4} against 5.1×10−45.1\times10^{-4}, 1.11.1 standard errors low. Between the two sizes the rate falls by 3.9±0.83.9\pm0.8, against 3.333.33 for an exact 1/N1/N law.

Answer. For a fully pushed wave the Lab model reproduces both the size of Λ\Lambda and its 1/N1/N scaling within the errors of a few hundred runs.

Source: G. Birzu

What this reproduction does not show

For pulled waves the Lab finds Λ=(1.96±0.21)×10−3\Lambda=(1.96\pm0.21)\times10^{-3} at N=100N=100 and (0.92±0.11)×10−3(0.92\pm0.11)\times10^{-3} at N=1000N=1000. The ratio 2.1±0.32.1\pm0.3 is far from the factor of 1010 that a 1/N1/N law would give, but also below the 3.43.4 of the asymptotic ln⁡3N\ln^3N law. As an effective exponent it is −0.33±0.07-0.33\pm0.07, close to the value in Fig. 5B, though our range of NN 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 3030 live runs instead of 5050, heterozygosity over fourteen demes near the front rather than the whole box, and NN well below 10410^4. 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.

Source: G. Birzu · G. Birzu

Try it in the Lab

See where the central-limit scaling holds, and where it fails

  1. Choose Fully pushed: the bulk shares ancestry and watch the diversity readout fall. Predict how much more slowly it falls if the carrying capacity rises from one thousand to about three thousand.
  2. Make the change and compare. Then choose Pulled: the tip wins and make the same change. Predict whether the slowdown is as large.
  3. Set the cooperativity to three. Explain, with the tip of the front, why the paper needs a cutoff to estimate drift in this wave.

Exercises with explained answers

  1. Use SI Eq. (S122) to compute Λ\Lambda for B=10B=10 and N=1000N=1000 with the Lab parameters.

    Show the answer

    The rate scales as 1/N1/N, so 1.706×10−3×300/1000=5.12×10−41.706\times10^{-3}\times300/1000=5.12\times10^{-4} per generation. The Lab measures (4.3±0.7)×10−4(4.3\pm0.7)\times10^{-4}.

  2. The supplement quotes the pulled-front transient as v(t)=vF(1−3/(4r0t))v(t)=v_{\mathrm F}\bigl(1-3/(4r_0t)\bigr). Show that this is the same as v∗−3/(2λ∗t)v^*-3/(2\lambda^*t) from chapter 6 for the continuum equation.

    Show the answer

    For the continuum, v∗=vF=2Dr0v^*=v_{\mathrm F}=2\sqrt{Dr_0} and λ∗=r0/D\lambda^*=\sqrt{r_0/D}. Then vF⋅3/(4r0t)=3D/(2r0 t)=3/(2λ∗t)v_{\mathrm F}\cdot3/(4r_0t)=3\sqrt{D}/(2\sqrt{r_0}\,t)=3/(2\lambda^*t). The two formulas agree.

  3. A rate falls by a factor of 2.122.12 when NN grows tenfold. What effective exponent αh\alpha_h does that imply, and what would a ln⁡3N\ln^3N law give between N=100N=100 and 10001000?

    Show the answer

    αh=−log⁡102.12=−0.33\alpha_h=-\log_{10}2.12=-0.33. A ln⁡3N\ln^3N law gives a ratio (ln⁡1000/ln⁡100)3=1.53=3.4(\ln1000/\ln100)^3=1.5^3=3.4, an effective exponent of −0.53-0.53, even though its asymptotic exponent is zero. Effective exponents over one decade say little about asymptotic laws.

Sources and what we recomputed

  1. G. Birzu, O. Hallatschek and K. S. Korolev, Neither pulled nor pushed: genetic drift and front wandering uncover a new class of reaction-diffusion waves, arXiv:1709.01601v2 (2018)

    Version 2, full text. Eq. (2): the Fisher speed. Eq. (3): the cooperative growth law. Eq. (5): perturbative rate of diversity loss. Eqs. (6)-(7): the leading-edge decay and the speed ratio 3/(22)3/(2\sqrt2) that separates semi-pushed from fully pushed waves. Fig. 5: diversity loss in the three classes. Methods, Eq. (11): the simulation model. SI Eq. (S28): ancestry weight; Eq. (S122): closed form of the loss rate; section Duration of simulations and data collection, Eqs. (S149)-(S150).

  2. G. Birzu, S. Matin, O. Hallatschek and K. S. Korolev, Genetic drift in range expansions is very sensitive to density feedback in dispersal and growth, arXiv:1903.11627v1 (2019)

    Version 1, full text. Abstract: dispersal that increases with population density suppresses genetic drift at the edge, and one ratio, the expansion speed over the geometric mean of dispersal and growth at the edge, controls the regimes of diversity loss.

  3. W. van Saarloos, Front propagation into unstable states, arXiv:cond-mat/0308540v2 (2003), Physics Reports

    Version 2, full text. Section 2.2, Eqs. (24)-(27): the linear spreading speed v∗v^* and steepness λ∗\lambda^* from the dispersion relation. Section 2.9.1, Eq. (78): the universal slow approach v(t)=v∗−3/(2λ∗t)v(t)=v^*-3/(2\lambda^*t) of a pulled front. Section 7.1, Eqs. (241)-(246): the cutoff correction to the pulled speed in particle models, proportional to 1/ln⁡2N1/\ln^2N; Eq. (248): the front diffusion constant falling as 1/ln⁡3N1/\ln^3N.

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