期刊
JOURNAL OF STATISTICAL PHYSICS
卷 172, 期 1, 页码 3-43出版社
SPRINGER
DOI: 10.1007/s10955-017-1900-1
关键词
Stochastic models; Population genetics; Time-scale separation; Effective models; Noise-induced selection; Population dynamics
资金
- Finnish Center for Excellence in Biological Interactions
- Leverhulme Early Career Fellowship by the Leverhulme Trust for funding
We describe a continuous-time modelling framework for biological population dynamics that accounts for demographic noise. In the spirit of the methodology used by statistical physicists, transitions between the states of the system are caused by individual events while the dynamics are described in terms of the time-evolution of a probability density function. In general, the application of the diffusion approximation still leaves a description that is quite complex. However, in many biological applications one or more of the processes happen slowly relative to the system's other processes, and the dynamics can be approximated as occurring within a slow low-dimensional subspace. We review these time-scale separation arguments and analyse the more simple stochastic dynamics that result in a number of cases. We stress that it is important to retain the demographic noise derived in this way, and emphasise this point by showing that it can alter the direction of selection compared to the prediction made from an analysis of the corresponding deterministic model.
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