Life on Earth has evolved under regular environmental rhythms, including the daily cycle of light and darkness. Many organisms, from bacteria to humans, have therefore developed internal timing mechanisms known as biological clocks. These clocks coordinate processes such as metabolism, DNA repair, and cell division so that they occur at appropriate times. Because these processes influence growth and reproduction, biological clocks are closely related to organismal function. However, the precise relationship between clock dynamics and biological performance is still not fully understood.

In evolutionary biology, growth and reproduction are often summarized by the idea of fitness. Fitness measures the reproductive success of an organism in a given environment. Variation in fitness across organismal traits and environmental conditions can be represented as a landscape. This project examines how properties of biological clocks, including their timing relative to environmental cycles, shape fitness landscapes.

Biological clocks generate rhythmic dynamics that can be analyzed using theoretical approaches from physics. Time-dependent processes are often studied using the framework of dynamical systems, which describes how systems evolve over time. Within this framework, biological clocks can be modeled as nonlinear oscillators that produce regular rhythms. This approach provides a general way to analyze how internal rhythms interact with environmental cycles.

The project also includes experimental studies using cyanobacteria, microorganisms that possess well-characterized biological clocks. These systems provide a tractable setting for examining how clock dynamics relate to fitness. Experimental measurements allow predictions from theoretical models to be tested and help refine these models. In turn, theoretical analysis can guide the interpretation of experimental results and suggest additional experiments. This combination of theory and experiment helps clarify how biological timing contributes to the structure of fitness landscapes. More broadly, these results may improve understanding of how temporal organization influences evolutionary processes.