Evolutionary games on cycles with strong selection
arXiv:1701.06615 · doi:10.1103/PhysRevE.95.022407
Abstract
Evolutionary games on graphs describe how strategic interactions and population structure determine evolutionary success, quantified by the probability that a single mutant takes over a population. Graph structures, compared to the well-mixed case, can act as amplifiers or suppressors of selection by increasing or decreasing the fixation probability of a beneficial mutant. Properties of the associated mean fixation times can be more intricate, especially when selection is strong. The intuition is that fixation of a beneficial mutant happens fast (in a dominance game), that fixation takes very long (in a coexistence game), and that strong selection eliminates demographic noise. Here we show that these intuitions can be misleading in structured populations. We analyze mean fixation times on the cycle graph under strong frequency-dependent selection for two different microscopic evolutionary update rules (death-birth and birth-death). We establish exact analytical results for fixation times under strong selection, and show that there are coexistence games in which fixation occurs in time polynomial in population size. Depending on the underlying game, we observe inherence of demographic noise even under strong selection, if the process is driven by random death before selection for birth of an offspring (death-birth update). In contrast, if selection for an offspring occurs before random removal (birth-death update), strong selection can remove demographic noise almost entirely.
arXiv comment5 Figures. Accepted for publication (Physical Review E)
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- Effects of Stochastic Games on Evolutionary Dynamics in Structured Populations
- Asymptotic absorption-time distributions in extinction-prone Markov processes
- Close spatial arrangement of mutants favors and disfavors fixation
- An Evolutionary Theory for the Variability Hypothesis
- Cooperation in Microbial Populations: Theory and Experimental Model Systems
- Role of the effective payoff function in evolutionary game dynamics