ArticleJournal of mathematical biology2018
Fixation probabilities in populations under demographic fluctuations.
Article in Journal of mathematical biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Mutant fixation in the presence of a natural enemy.Nature communications · 2023Article
- A stochastic analysis of the interplay between antibiotic dose, mode of action, and bacterial competition in the evolution of antibiotic resistance.PLoS computational biology · 2023Article
- Reproductive variance can drive behavioral dynamics.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- Understanding evolutionary and ecological dynamics using a continuum limit.Ecology and evolution · 2021Review
- Evolutionary bet-hedging in structured populations.Journal of mathematical biology · 2021Article
- Effects of niche overlap on coexistence, fixation and invasion in a population of two interacting species.Royal Society open science · 2020Article
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Authors and funding
2 authors.
Funding
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Abstract
We study the fixation probability of a mutant type when introduced into a resident population. We implement a stochastic competitive Lotka-Volterra model with two types and intra- and interspecific competition. The model further allows for stochastically varying population sizes. The competition coefficients are interpreted in terms of inverse payoffs emerging from an evolutionary game. Since our study focuses on the impact of the competition values, we assume the same net growth rate for both types. In this general framework, we derive a formula for the fixation probability [Formula: see text] of the mutant type under weak selection. We find that the most important parameter deciding over the invasion success of the mutant is its death rate due to competition with the resident. Furthermore, we compare our approximation to results obtained by implementing population size changes deterministically in order to explore the parameter regime of validity of our method. Finally, we put our formula in the context of classical evolutionary game theory and observe similarities and differences to the results obtained in that constant population size setting.
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