Fitness versus longevity in age-structured population dynamics.

Area of Science:

• Population dynamics
• Evolutionary biology
• Mathematical modeling

Background:

• Investigating age-structured population models is crucial for understanding demographic stability.
• The impact of mutations on life expectancy and population characteristics requires further exploration.
• Mutational bias can significantly influence evolutionary trajectories and population traits.

Purpose of the Study:

• To analyze the dynamics of an age-structured population model with variable offspring life expectancy.
• To investigate how mutational bias affects population fitness and age structure.
• To elucidate the relationship between mutation, fitness, and average population age.

Main Methods:

• Analytical study of underlying rate equations.
• Numerical simulations of population dynamics.
• Examination of steady-state conditions and time-dependent behavior.

Main Results:

• Total population reaches a steady state regardless of mutational bias.
• Favoring deleterious mutations leads to steady average fitness but decreasing average age.
• Favoring advantageous mutations results in linearly growing average fitness with time-independent average age.
• No mutational bias shows average fitness growing as t^(2/3).

Conclusions:

• Mutational bias has counter-intuitive effects on population fitness and age structure.
• Deleterious mutation bias can paradoxically lead to stable average fitness.
• Advantageous mutation bias drives population fitness growth over time.
• The interplay between mutation, age, and fitness is complex and depends on mutation direction.