Onwards from 1900 there has been a dramatic increase in urban land use and ~66% of the worlds population will live in urban areas by the year 2050. While urban systems generate the bulk of carbon emissions, urban green areas (e.g., lawns, parks, roof gardens) have the potential to sequester significant amounts of carbon and influence the global carbon cycle. Urban lawns are of particular relevance due to their high carbon density and expansive footprinturban lawns represent three-times more total acreage than any other cultivar in the U.S. The proposed project is therefore motivated by the idea that pursuing fundamental knowledge of the interactions among urban lawns, the associated microbiome, and biogeochemical function will generate new process knowledge of plant-microbiome interactions that may lead to improved management practices that maximize the carbon storage capacity of urban green spaces. The project is timely as there is relatively little known about lawn-associated microbiomes; studies have focused more on vertical profiles and temporal trajectories of C/N. To the best of our knowledge no study has leveraged advanced molecular-based tools to investigate lawn microbiomes; while 16S rRNA gene surveys have been conducted, no metagenome or metaproteome yet exists for lawn microbiomes. This precludes our ability to directly link lawn biogeochemical function to underlying metabolic processes. Given the key role played by lawns in the carbon-cycle of urban green spaces and the substantial knowledge gap related to the processes governing lawn-microbiome interactions and associated biogeochemical function, we propose to combine JGI and EMSL capabilities to characterize this coupled system while revealing impacts of hydrologic setting and multi-decadal variation in time-since-establishment. The project will specifically use metagenomes (JGI) to interpret metatranscriptomes (JGI), metaproteomes (EMSL), and metabolomes (EMSL) across key biogeochemical transitions. These analyses will be coupled with more targeted analyses of specific metabolic pathways relevant to carbon and nutrient cycling, as well as greenhouse gas emissions. Data generated by JGI and EMSL will be interpreted within the context of broader characterization of the associated lawn systems, based on a number of high throughput assays (e.g., 16S rRNA gene and ITS sequencing, bulk nutrients, microbial biomass, etc.). The project will make use of existing lawns on the campus of the Pacific Northwest National Laboratory; the campus lawns provide an opportunity to sample across existing hydrologic gradients (in and out of bioswales) and across a continuum of lawn ages (spanning 0-46 years since establishment). The sampling design and proposed use of JGI/EMSL capabilities have been optimized to enable evaluation of specific a priori hypotheses. More broadly, the proposed project represents a hypothesis-driven investigation of the coupled lawn-soil-microbiome system and is designed to generate fundamental knowledge needed to build process-based predictive models of carbon/nutrient cycling within an expanding ecosystem that represents the largest cultivar in the U.S.