Collaborative Research: RoL: Impacts of plants and communities on soil microbial composition and function across phylogenetic scales

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Soils provide critical ecosystem services that support agriculture, determine nutrient and carbon cycles, maintain clean air and water, and sustain biodiversity. These services are controlled by microorganisms, including bacteria and fungi. Plants can manipulate these microbial communities through the chemicals they release—root exudates—with subsequent consequences for soil functions. Characterizing root exudates and their relationships with other plant traits will improve understanding of plant effects on microbial communities and the ecosystem services that they provide. This project will use laboratory, greenhouse, field, and computational approaches to evaluate the effects of plant root exudates on soil microbial composition and function. The work will be conducted in the context of restored tallgrass American prairies, an endangered ecosystem, and deliver our results directly to land owners and natural resource managers responsible for the creation and maintenance of this landscape. Additionally, the project provides educational opportunities for members of the public ranging from high school students to retired adults and will train early-career scientists in cutting-edge techniques. This project will develop a predictive, mechanistic framework to understand how phylogenetic and functional characteristics of plants and plant communities influence soil microbial communities and the ecosystem functions via root exudates. It will combine exometabolomic plant measurements, sampling in a biodiversity experiment, functional microbial characterizations, and machine learning approaches to forecast microbial community structure and function in a field setting. Exudate characterizations from a taxonomically and functionally diverse pool of plants will greatly advance knowledge of plant biochemistry. The use of exudates in mesocosm incubation and metabolic characterization experiments will demonstrate their direct impacts on microbial community structure and function. The project will also sample soil microbes in a biodiversity experiment and use machine learning computational approaches to build predictive models of plant community impacts on soil microbes. These models will be tested in a field setting using large-scale tallgrass prairie restorations to produce generalizable conclusions that span molecular- to landscape-scales.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.