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Frequency-dependent growth in class-structured populations: continuous dynamics in the limit of weak selection
Sabin Lessard1, Cíntia Dalila Soares2
1Département de mathématiques et de statistique, Université de Montréal, C.P. 6128, Succursale Centre-ville, Montréal, QC, H3C 3J7, Canada. lessards@dms.umontreal.ca.
This study develops a continuous model for class-structured populations, approximating discrete dynamics under weak selection. Type frequencies follow a replicator equation, influenced by class frequencies and reproductive values.
Area of Science:
- Population Dynamics
- Mathematical Biology
- Evolutionary Theory
Background:
- Discrete-time models are often used to study population dynamics.
- Approximating these discrete models with continuous ones can simplify analysis and provide insights into long-term behavior.
- Understanding frequency-dependent growth is crucial in evolutionary biology.
Purpose of the Study:
- To establish a continuous model that accurately approximates a discrete-time, class-structured population model.
- To analyze the dynamics of frequency-dependent growth in haploid populations with finite class structure.
- To derive the limiting behavior of type frequencies under weak selection.
Main Methods:
- Consideration of infinite haploid populations with finite class structure.
- Analysis in the limit of weak selection, using the inverse of selection intensity as the unit of time.
- Derivation of generalized fecundity parameters with perturbations dependent on class and type frequencies.
- Mathematical analysis of the dynamics as the number of time steps (N) approaches infinity.
Main Results:
- The type frequencies, in the limit, obey the replicator equation.
- Instantaneous growth rates depend on equilibrium class frequencies and reproductive values.
- The model provides an approximation for discrete population dynamics.
Conclusions:
- A continuous model effectively approximates discrete, class-structured population dynamics under weak selection.
- The derived replicator equation offers insights into evolutionary game theory applications.
- The findings are supported by simulation results.
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