Emergent Controls on Microbial Functional Distributions Across a Mountainous Watershed


Patrick Sorensen1* (posorensen@lbl.gov), Ulas Karaoz1, Nicola Falco1, Fabio Cuilla1, Benjamin Gilbert1, Langlang Li1, Hannah Naughton1, Annie DiGuiseppe1, Nicholas Bouskill1, Shi Wang1, Susan Mullen2, Preston Tasoff2, Jacob West-Roberts2, Jill Banfield1,2, Simon Roux1, Clement Coclet1, Emiley Eloe-Fadrosh1, Tomas Tyml1, Frederik Schulz1, Matthias Sprenger1, Kenneth Williams1, Eoin Brodie1


1Lawrence Berkeley National Laboratory, Berkeley, CA; 2University of California–Berkeley, Berkeley, CA



Watershed traits including topography, vegetation, and soil characteristics are shaped by interacting climate and geologic variability in mountainous watersheds. Energy resources are constrained by these interacting watershed traits, and water availability is central in selecting microbial biogeochemical function. By understanding how watershed traits influence the spatial distribution of microbial functional traits, this research aims to predict how changes in watershed traits influence hydro-biogeochemical process response to disturbance. Researchers have quantified the spatial distribution of genome-inferred microbial functional traits for over nine field campaigns (20 watershed locations). From 724 metagenomes, 91K species were identified, as well as exceptional virus diversity. A database of inferred microbial functional traits has been established using new computational workflows. Machine learning is being used to scale and predict microbial trait distributions to uncover relationships with watershed traits quantified by remote sensing. For example, plant canopy height, leaf mass per area, and elevation are the best predictors of the genomic capacity for nitrogen-mobilizing ammonia oxidation, a process carried out primarily by ureolytic Thaumarcheotal. By contrast, the genomic capacity for nitrate retention (i.e., dissimilatory nitrate reduction to ammonia versus denitrification) is higher in topographic depressions that are occupied by willow shrubs across the watershed. This extends upon observations of floodplains as key nitrogen retention control points. Intensive studies are being completed at finer scale across space (e.g., soil-to-bedrock profiles) and time (e.g., floodplain inundation). For example, shale weathering contributes to both carbon and nitrogen exports, and mycorrhizal fungi have also been observed colonizing tap roots of sagebrush in bedrock fractures 2 m below the surface and may contribute to weathering. Methane off-gassing from Mancos shale bedrock may be an important carbon source in the subsurface of upland soils, evidenced by high gene expression of methane oxidizing Actinobacteria in deep soils and negligible methane fluxes from the soil surface. In surface soils, topography and plant roots interact to create anoxic soil microsites that contribute to soil carbon stabilization and greenhouse gas emissions. In floodplains, methane production is driven by highly fluctuating river discharge; however anaerobic methane oxidation coupled with nitrate reduction may be an important control on overall methane fluxes. These finer scale studies form the basis of mechanistic understanding of microbial influence on biogeochemical cycling from bedrock-to-canopy, and combined with this project’s watershed scale surveys, are informing targeted field sampling campaigns, coupled laboratory experiments, and model development to predict watershed responses to future disturbance.