This project is ultimately about why we see the patterns we do in ecology and evolution, and how these patterns may be sensitive to human impacts on the environment at both local and global scales. The project will adapt the physics of non-equilibrium systems to understand what fundamental constraints exist on ecological and evolutionary phenomena. In short: are the emergent patterns we observe in biological systems inevitable, why does the living world look how it does, and can we predict in broad terms how it will it change in the future? This will serve to integrate and interconnect our understanding of life with the physical, non-living universe, while also quantifying the view that simple, emergent patterns can arise from complex underpinnings.
To address this goal, we will develop new mathematical theory and data analysis, centered around life history as a guiding principle. We will organize a working group, bringing together expertise drawing from biology, physics, and information-processing in complex systems, and we will apply to host this working group at either the Santa Fe Institute or the Harvard Radcliffe Institute. Our outputs also include the generation of and publication of new theoretical results, while also testing our theory using diverse datasets, and developing a new synthetic framework for future work. These outputs will help us to understand how patterns and trends emerge, and will inform how living systems process information and resources, how self-regulation impacts pattern formation, and to what extent ecological outcomes are robust to variability and stochasticity.
Our project will provide a much-needed understanding of biodiversity across scales, contributing to both fundamental understanding of the Science of Purpose applied in ecology, and informing future conservation and mitigation of biodiversity loss. Our approach will engage mathematicians, physicists and biologists, creating new links between ecology and other fields.
