A branching process model for dormancy and seed banks in randomly fluctuating environments

Area of Science:

• Evolutionary biology
• Theoretical ecology
• Mathematical modeling

Background:

• Environmental fluctuations pose challenges to microbial population survival.
• Dormant seed banks are a strategy to persist through harsh conditions.
• Understanding the evolutionary benefits of dormancy requires quantitative models.

Purpose of the Study:

• To explore the evolutionary advantages of maintaining dormant seed banks in microbial populations.
• To quantitatively assess strategies for switching between active and dormant states.
• To understand population dynamics in fluctuating environments.

Main Methods:

• Utilizing a '2-type' branching process model.
• Simulating populations with individuals switching between active and dormant states.
• Analyzing a random environment oscillating between healthy and harsh states.
• Employing a 'fair comparison' method for reproductive costs.
• Calculating maximal Lyapunov exponents to determine fitness.

Main Results:

• Developed a model for microbial populations with dormancy strategies.
• Introduced a method for comparing different switching strategies fairly.
• Generated a 'fitness map' illustrating strategy effectiveness across environmental regimes.
• Identified specific environmental conditions favoring unique switching strategies.

Conclusions:

• Dormant seed banks provide significant evolutionary benefits for microbial populations.
• The optimal strategy for dormancy depends on the environmental regime.
• Mathematical modeling, specifically branching processes, is crucial for understanding evolutionary strategies.