Mikhail Tikhonov, University of Washington in St. Louis: Quantifying the Coarse-Grainability of Microbial Ecosystems

Sequencing-based technologies allow resolving the composition of microbial ecosystems to strain-level detail; however, coarser representations are often found to be more reproducible and more predictive of community-level properties. The general principles for selecting an appropriate level of description for modeling remain elusive. I will describe a framework for systematically comparing all possible coarse-grained descriptions by explicitly quantifying their prediction power and information content, allowing us to define the Pareto front of optimal descriptions for a given property of interest. Crucially, this Pareto front depends on ecological context; in particular, a high diversity of strains (while nominally more complex) may, in fact, facilitate coarse grainability. I'll discuss an empirical example of diversity-enhanced coarse-grainability, and show how our framework nuances the notion of "emergent simplicity" in microbial ecology.