Free fitness that always increases in evolution.

Area of Science:

• Population Biology
• Evolutionary Dynamics
• Theoretical Ecology

Background:

• Evolutionary processes are often modeled using Markov processes.
• Understanding the balance between systematic forces and random processes is crucial in population biology.

Purpose of the Study:

• Introduce a novel free fitness function for population biology.
• Demonstrate its applicability to various evolutionary and ecological models.
• Clarify the interplay between systematic and disturbing evolutionary forces.

Main Methods:

• Developed a free fitness function that monotonically increases over time.
• Expressed free fitness as an average index plus an entropy term.
• Applied the function to Markov process models with positive steady states.

Main Results:

• The free fitness function reaches its maximum at evolutionary equilibrium.
• The function provides a clear interpretation of evolutionary forces.
• Successfully applied to models of population genetics, quantitative character evolution, molecular evolution, and ecological succession.

Conclusions:

• The free fitness function offers a unified approach to studying evolutionary dynamics.
• It enhances the understanding of the balance between selection, drift, and other evolutionary factors.
• The method is broadly applicable across diverse areas of population biology.