Watershed Rules of Life
(NSF-DEB 1840243)
Title: Watershed Rules of Life
P.I.s: Peter Raymond, Byron C. Crump, Colin Gleason
Postdoctoral scientist: Taylor Maavara
Graduate Students: Ted Bambakidis, Laura Logozzo, Craig Brinkerhoff
Undergraduate Students: Shawn Doran, Marilee Hoyle
Overview: Rivers are the circulatory systems of the continents, and they function as potent reactor sites where terrestrial nutrients, organic matter, and pollutants are removed or transformed during transport from land to ocean. Microbial communities are the engines of these reactors with the capacity to remove or alter important elements (e.g., C, N, P, Hg, As), produce greenhouse gasses (CO2, N2O, CH4) and support food webs. There is a growing body of knowledge that postulates that within drainage networks the microbial engine shifts from the sediments to the water column as you move from small streams to large rivers due to changing physical hydrology and geomorphology. Thus, we argue that the physiological traits that underlie the capacities of planktonic microbes to maintain function in river ecosystems are emergent properties of the dynamic nature of river environments, and that given enough time distinct planktonic microbial communities develop in rivers. This has important implications for the conceptualization of watersheds as reactors because water column communities have different metabolic efficiencies and capabilities and may experience different disturbance regimes with hydrologic events and major confluences. We propose to determine the “Rules of Life” that govern the establishment of this water column community. Excitingly, we believe these rules can be built off of foundational work in hydrologic scaling and therefore be generalizable. We have proposed a set of hypotheses that builds microbial ecology into the scaffolding of hydrology and geomorphology in order to research our Watershed Rules of Life. We also argue that recent advances in bioinformatics, DNA sequencing technology, drainage network conceptual models, and geospatial data sets, will allow for transformative progress at the intersection between hydrology, ecosystem science, geomorphology, and microbial ecology.
Intellectual Merit : The proposed research will develop mathematical expressions that relate microbial indices to stream order, stream hydraulics (e.g., velocity and depth), flow variability, and temperature using several indices for the development and activity of planktonic microbial communities. These indices will be based on metagenomics for genomic diversity, metatranscriptomics for gene expression, and microbial 16S rRNA gene amplicon sequencing for phylogenetic diversity in riverine samples. Microbial indices will be compared to modeled estimates of the time scale for water column microbial community development (i.e., residence time) and microbial metabolic rates (e.g., denitrification). It is hypothesized that geomorphology (e.g., depth, velocity), discharge variability, and temperature are the main sources of variation to these time scales and therefore the determinants of when and where distinct planktonic microbial riverine communities emerge in the water column of river networks. If successful, the determination of these relationships will lend to scaling and prediction of riverine microbial community activity and diversity in other temperate regions of the world.
Broader Impacts: PIs will interact with the Yale New Haven Promise Internship program, which provides internships for students from New Haven interested in STEM. Raymond also proposed to interact with students at the Crested Butte Community School. This project will also train graduate and undergraduate students at UMass, OSU and Yale. Findings will be incorporated into courses taught by the PIs. All data will be archived appropriately following metadata standards.
Publications
Brinkerhoff, C. B., C. J. Gleason, and D. W. Ostendorf. 2019. Reconciling at‐a‐Station and at‐Many‐Stations Hydraulic Geometry Through River‐Wide Geomorphology. Geophysical Research Letters. doi:10.1029/2019GL084529
Good, S. P., D. R. URycki, and B. C. Crump. 2018. Predicting Hydrologic Function With Aquatic Gene Fragments. Water Resour. Res. 54: 2424–2435.
