Periodic Reporting for period 1 - CyclesOfLife (HOW DO SEASONAL CYCLES SHAPE LIFE CYCLES? A UNIFYING FRAMEWORK TO UNDERSTAND VARIATIONS ACROSS THE GLOBE AND PREDICT SHIFTS IN A CHANGING WORLD)
Reporting period: 2021-10-26 to 2023-10-25
Climate change is altering the patterns of physical seasons around the world, mainly in how long the 'growing season' is within a year. This expansion has complex and counterintuitive consequences on how organisms should, evolutionarily speaking, make use of their time. In this work I developed the mathematical theory of how growing season length should exactly influence the optimal timings of landmark life cycle events, such as flowering or breeding. Knowledge of how changing seasonality should change the timing of biological activity is a universal and general biological puzzle, but it is also highly relevant for human societies that depend on such timing patterns, e.g. agriculture. Timing of life cycle events is also deeply associated with population dynamics and evolutionary fitness, therefore understanding and predicting change is highly relevant for the conservation of natural populations.
I developed mathematical models that relate how the seasonality of environments exactly relate to the expected seasonal timing of key life cycle events of organisms, given a few measurable and standard parameters of those organisms. I found that this relationship is often counterintuitive and nonlinear, but mathematically tractable. In many cases, simple change in the length of the growing season can have a bigger impact on the dynamics of natural selection than environmental variability overall. I then tested theoretical predictions in real-world empirical situations: two plant species across a latitudinal range of Sweden, and bird and caterpillar populations in a model woodland system in Oxford, England. These empirical systems, while noisier than the clean mathematical predictions, still do remarkably follow the predictions made from the simple models. These results are partially published and preprinted so far, with 2 or more to be published soon.
No work to date has developed and tested the relationships between growing season length and the evolution of seasonal timing patterns of organisms. Using the knowledge from the theoretical and empirical work, I am also producing mechanistic predictions of how seasonal patterns might continue to change under climate change scenarios in the natural systems I studied with my collaborators. These predictions will be used scientifically as testable hypotheses as more data are gathered in those systems in the future, as well as improve our forecasting power in the field of phenology which to date is largely extrapolated from correlations, not based on eco-evolutionary theory.