ECOSHAPE · The role of growth rate density-dependence SHAPE in community assembly: ECOlogical experiments and theory

A fundamental challenge in ecology is to understand and predict how diverse microbial communities assemble and persist, a question also relevant for medicine, biotechnology, and ecosystem management. While decades of theory have explored coexistence, predictive models often rely on overly simplified traits, such as maximum growth rate, that fail to capture the dynamic feedback between organisms and their environment. Direct experimental evidence linking functional traits to community-level outcomes remains scarce. This project aims to elucidate how the shape of ecological interactions drives microbial community assembly by combining high-throughput experiments and theoretical models. Recent experimental advances have enabled the precise measurement of growth dynamics in diverse synthetic communities, while theoretical models, inspired by statistical physics, can disentangle interactions and predict community dynamics. I propose to elevate the functional form of growth rate density-dependence to a fundamental ecological trait that integrates resource consumption, inhibition, and facilitation into a single measurable curve. I will use high-throughput techniques to measure the shape of density-dependence profiles for a broad library of microbial isolates, both in monoculture and in pairwise co-cultures under diverse environmental conditions. I will then experimentally assemble multi-species communities and track their composition over time to generate a systematic dataset of assembly outcomes. I will develop a novel theoretical model that incorporates the empirically measured profiles to predict these experimental outcomes. Utilizing statistical physics tools, I will generate predictions capable of interpreting the experiments and scale these insights to complex ecosystems. Beyond developing a new predictive framework for community ecology, this project has the potential to indicate new strategies for engineering microbial consortia relevant for medicine and industry.