Areas of Research: Evolution, Genetics-and-Genomics, Modeling-and-Computation
- Ecology and Evolutionary Biology
207 Eno Hall
Understanding and managing complex adaptive systems (CAS)—characterized by emergent patterns at scales larger than those of the interacting parts—has crystallized as one of the most pressing problems of our time, from biology to sociology, from medicine to financial markets. Faced with a range of challenges throughout evolutionary history that have led to a diversity of hierarchical, modular, and robust solutions, biological systems are ideal for the study of CAS, and solutions inferred from biology have successfully been applied to system design and management in other fields. It is therefore imperative not only to study individual biological CAS but also to compare the organizing principles and emergent properties of diverse CAS.
A natural dimension with which to categorize the diversity of CAS is offered by the level at which selection acts: because evolution can act at multiple spatiotemporal scales, CAS range from tightly integrated units subject to evolution as a whole (evolved CAS, such as multicellular organisms or eusocial insect colonies), to intermediately integrated ones in which evolution acts strongly on both the individual units and the whole (evolved and self-organized CAS, such as multicellular aggregates as seen in slime molds), to little-integrated ones in which evolution acting only on the parts shapes the emergent properties of the whole (self-organized CAS, such as communities or ecosystems). How the underlying organizing principles and emergent properties of CAS vary along this continuum arises therefore as an immediate and fundamental question and constitutes the overarching theme guiding the work in our lab.