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When does gene flow facilitate evolutionary rescue?
Matteo Tomasini1,2,3,4, Stephan Peischl1,3
1Interfaculty Bioinformatics Unit, University of Bern, Bern, 3012, Switzerland.
Evolution; International Journal of Organic Evolution
|June 17, 2020
Summary
Gene flow can aid evolutionary rescue in structured populations, especially at intermediate migration rates. This research identifies conditions where gene flow promotes survival rather than hindering adaptation.
Area of Science:
- Ecology and Evolutionary Biology
- Population Genetics
- Mathematical Biology
Background:
- Gene flow's impact on evolutionary rescue in structured habitats is a key area of study.
- Theoretical models and experiments suggest intermediate migration rates can maximize rescue probability in deteriorating environments.
- The role of gene flow in facilitating adaptation contrasts with traditional views of it hindering local adaptation.
Purpose of the Study:
- To identify conditions under which gene flow facilitates evolutionary rescue.
- To resolve the apparent conflict between gene flow aiding survival and hindering local adaptation.
- To develop a tractable model for evolutionary rescue in a two-deme system with gene flow.
Main Methods:
- Development of a simple, analytically tractable mathematical model.
- Simulation of evolutionary rescue in a two-deme population structure with varying gene flow.
- Investigation of asymmetries in gene flow, carrying capacities, density regulation, and local growth rates.
Main Results:
- A simple condition for when migration facilitates evolutionary rescue has been identified.
- Intermediate migration rates were shown to be crucial for maximizing rescue probability.
- Asymmetries in gene flow and carrying capacities, along with density regulation, influence rescue outcomes.
Conclusions:
- Gene flow can be a critical factor promoting the survival of populations facing environmental change.
- Understanding the conditions that enable gene flow to facilitate evolutionary rescue is essential for conservation biology.
- The study provides a theoretical framework for predicting population persistence under environmental stress.
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