Mechanism Across Scales: A Holistic Modeling Framework Integrating Laboratory and Field Studies for Microbial Ecology - Lui, Lauren M.; Majumder, Erica L.-W.; Smith, Heidi J.; Carlson, Hans K.; von Netzer, Frederick; Fields, Matthew W.; Stahl, David A.; Zhou, Jizhong; Hazen, Terry C.; Baliga, Nitin S.; Adams, Paul D.; Arkin, Adam P. (Frontiers in Microbiology, 2021)
Over the last century, leaps in technology for imaging, sampling, detection, high throughput sequencing and omics analyses have revolutionized microbial ecology to enable rapid acquisition of extensive datasets for microbial communities across ever-increasing temporal and spatial scales. The present challenge is capitalizing on our enhanced abilities of observation and integrating diverse data types from different scales, resolutions and disciplines to reach a causal and mechanistic understanding of how microbial communities transform and respond to perturbations in the environment. This type of causal and mechanistic understanding will make predictions of microbial community behavior more robust and actionable in addressing microbially-mediated global problems. To discern drivers of microbial community assembly and function, we recognize the need for a conceptual, quantitative framework that connects measurements of genomic potential, the environment, and ecological and physical forces to rates of microbial growth at specific locations. We describe the Framework for Integrated, Conceptual, and Systematic Microbial Ecology (FICSME), an experimental design tool to determine the minimum amount of information needed to answer a specific question at a desired resolution. Through iterative cycles that lead to understanding of the coupling between scales and processes can we reliably predict how perturbations to microbial systems impact landscape-scale processes or vice versa. We describe an approach and potential applications for using the FICSME to elucidate the mechanisms of globally important ecological and physical processes; towards attaining the goal of predicting the structure and function of microbial communities in chemically complex natural environments.