Theory of time-averaged neutral dynamics with environmental stochasticity

TL;DR

This paper develops and analyzes two time-averaged neutral models incorporating environmental stochasticity, revealing how nonlinear fitness dependence can stabilize populations and influence species abundance distributions.

Contribution

It introduces two new neutral models with environmental fluctuations and provides analytical solutions for their species abundance distributions.

Findings

Model B exhibits noise-induced stabilization facilitating mutant invasion.

Analytical results accurately fit simulation data.

Environmental stochasticity significantly impacts population dynamics.

Abstract

Competition is the main driver of population dynamics, which shapes the genetic composition of populations and the assembly of ecological communities. Neutral models assume that all the individuals are equivalent and that the dynamics is governed by demographic (shot) noise, with a steady state species abundance distribution (SAD) that reflects a mutation-extinction equilibrium. Recently, many empirical and theoretical studies emphasized the importance of environmental variations that affect coherently the relative fitness of entire populations. Here we consider two generic time-averaged neutral models, in both the relative fitness of each species fluctuates independently in time but its mean is zero. The first (model A) describes a system with local competition and linear fitness-dependence of the birth-death rates, while in the second (model B) the competition is global and the fitness dependence is nonlinear. Due to this nonlinearity, model B admits a noise-induced stabilization mechanism that facilitates the invasion of new mutants. A self-consistent mean-field approach is used to reduce the multi-species problem to two-species dynamics, and the large-$N$ asymptotics of the emerging set of Fokker-Planck equations is presented and solved. Our analytic expressions are shown to fit the SADs obtained from extensive Monte-Carlo simulations and from numerical solutions of the corresponding master equations.