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February 2007 Evolution of discrete populations and the canonical diffusion of adaptive dynamics
Nicolas Champagnat, Amaury Lambert
Ann. Appl. Probab. 17(1): 102-155 (February 2007). DOI: 10.1214/105051606000000628


The biological theory of adaptive dynamics proposes a description of the long-term evolution of a structured asexual population. It is based on the assumptions of large population, rare mutations and small mutation steps, that lead to a deterministic ODE describing the evolution of the dominant type, called the “canonical equation of adaptive dynamics.” Here, in order to include the effect of stochasticity (genetic drift), we consider self-regulated randomly fluctuating populations subject to mutation, so that the number of coexisting types may fluctuate. We apply a limit of rare mutations to these populations, while keeping the population size finite. This leads to a jump process, the so-called “trait substitution sequence,” where evolution proceeds by successive invasions and fixations of mutant types. Then we apply a limit of small mutation steps (weak selection) to this jump process, that leads to a diffusion process that we call the “canonical diffusion of adaptive dynamics,” in which genetic drift is combined with directional selection driven by the gradient of the fixation probability, also interpreted as an invasion fitness. Finally, we study in detail the particular case of multitype logistic branching populations and seek explicit formulae for the invasion fitness of a mutant deviating slightly from the resident type. In particular, second-order terms of the fixation probability are products of functions of the initial mutant frequency, times functions of the initial total population size, called the invasibility coefficients of the resident by increased fertility, defence, aggressiveness, isolation or survival.


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Nicolas Champagnat. Amaury Lambert. "Evolution of discrete populations and the canonical diffusion of adaptive dynamics." Ann. Appl. Probab. 17 (1) 102 - 155, February 2007.


Published: February 2007
First available in Project Euclid: 13 February 2007

zbMATH: 1128.92023
MathSciNet: MR2292582
Digital Object Identifier: 10.1214/105051606000000628

Primary: 92D15

Rights: Copyright © 2007 Institute of Mathematical Statistics


Vol.17 • No. 1 • February 2007
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