Nonequilibrium Theory for Adaptive Systems in Varying Environments.

Area of Science:

• Physics
• Biology
• Ecology

Background:

• Biological organisms must adapt to unpredictable environmental changes to survive and thrive.
• Understanding the physical basis of adaptivity is crucial for fields ranging from evolutionary biology to medicine.

Purpose of the Study:

• To develop a physical theory of adaptivity by analyzing the components of biological fitness in fluctuating environments.
• To determine the optimal adaptive strategies for organisms and the optimal environmental control strategies for external agents.

Main Methods:

• Application of nonequilibrium physics principles to model organismal fitness.
• Computation of fitness components, including static generalist and dynamic nonequilibrium tracking.
• Derivation of optimal adaptive and environmental control strategies.

Main Results:

• Fitness comprises a static generalist component and a dynamic nonequilibrium tracking component.
• Environmental changes require specific rates and magnitudes to be worth tracking; not all changes are beneficial to track.
• Anticipatory tracking in coherent environments significantly enhances fitness.
• Optimal strategies such as bet hedging and phenotypic memory were computed and explained.
• Optimal environmental control strategies, applicable to drug regimen design, were also computed.

Conclusions:

• A unified physical framework for adaptivity connects fitness, adaptive strategy, and environmental variability.
• The study provides a quantitative understanding of how biological systems adapt to dynamic environments.
• The findings have implications for understanding evolution, ecology, and designing interventions in biological systems.