From Genes to Satellites: Uncovering Microbial Drivers of Water Quality and Green House Gas Flux in Southeastern U.S. Reservoirs

Microbial communities are fundamental drivers of the ecology and biogeochemistry of inland waters, yet their composition, functional potential, and spatial distribution remain poorly characterized. Current monitoring often relies on traditional methods like microscopy, which have low spatial resolution and can miss critical microbial "hotspots" or the precise genetic identity of toxin-producing organisms. This gap limits our ability to predict and manage water quality effectively.  To address this challenge, our research integrates field sampling with a suite of advanced technologies: metagenomic sequencing, flow cytometry, high-throughput microscopy, and satellite remote sensing, in key reservoirs of the southeastern U.S. We aim to build a new framework to map microbial communities and their functions at a reservoir-wide scale, and how these spatial gradients map onto harmful agal blooms and associated greenhouse gas concentrations (CH4, N2O, CO2). Our initial findings from Jordan Lake, NC reveal substantial spatial variability in microbial cell abundance, identifying "hotspots" with microbial biomass double that of adjacent areas. This variability extends beyond typical river-to-dam gradients. Furthermore, metagenomic analysis of samples from the Jordan Lake and Haw River systems following a major storm event produced over 80 distinct microbial genomes. Critically, this included the assembled genome of the known toxin-producing cyanobacterium Raphidiopsis brookii.  This integrated approach provides an exceptional view of microbial biodiversity and functional potential. By linking this "on-the-ground" genomic data to satellite-observable parameters, this work is developing a scalable, predictive capacity to assess water quality, identify emerging threats from harmful algal blooms, and provide powerful new tools for in-land water resource managers.

Presentation Preference: Standard Oral (12 Minutes)

Primary Presenter: Scott Gifford, The University of North Carolina at Chapel Hill (sgifford@email.unc.edu)

Authors:

Scott Gifford, The University of North Carolina at Chapel Hill  (sgifford@email.unc.edu)

John Gardner, The University of North Carolina at Chapel Hill  (gardj@unc.edu)

Mary Kate Rinderle, The University of North Carolina at Chapel Hill  (rinderle@unc.edu)

Tamlin Pavelsky, The University of North Carolina at Chapel Hill  (pavelsky@email.unc.edu)

Amanda Del Vecchia, The University of North Carolina at Chapel Hill  (adelvecc@unc.edu)

Nathan Hall, The University of North Carolina at Chapel Hill  (nshall@email.unc.edu)