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Coevolutionary interactions between a haploid species and a diploid species
1Department of Mathematics, Claremont Graduate University, Claremont, CA 91711, USA. switkes@jasper.uor.edu
Journal of Mathematical Biology
|March 23, 2001
Summary
This study models coevolution between haploid and diploid populations, revealing complex interactions and potential for multiple stable genetic states. Findings support the geographic mosaic theory, showing diverse local coevolutionary outcomes influenced by migration.
Area of Science:
- Evolutionary Biology
- Population Genetics
- Theoretical Ecology
Background:
- Coevolutionary dynamics are complex, especially involving populations with different ploidies.
- Understanding these interactions is crucial for predicting evolutionary trajectories and biodiversity patterns.
Purpose of the Study:
- To develop and analyze a general mathematical model for coevolution between haploid and diploid populations.
- To determine the equilibrium states and outcomes of these complex interspecific interactions.
- To explore the implications for the geographic mosaic theory of coevolution.
Main Methods:
- A general mathematical model was formulated for a haploid and a diploid population, each with two alleles at a single locus.
- Fitness functions were defined as linear dependencies on the genotype frequencies of the interacting species.
- A semi-symmetric model was constructed for further analytical exploration of outcomes.
Main Results:
- The model demonstrates that coevolution between haploid and diploid populations is significantly more complex than between two haploid populations.
- The analysis identified conditions allowing for the existence of two distinct polymorphic equilibria.
- Even a simplified semi-symmetric model exhibited a wide variety of potential coevolutionary outcomes.
Conclusions:
- The complex dynamics and multiple equilibria observed support the geographic mosaic theory.
- Local populations can evolve to divergent outcomes, creating a dynamic geographic mosaic through inter-population migration and interaction.
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