Abstract
An urgent imperative of the hydrologic community is to accurately characterize hydrologic processes in order to anticipate and mitigate changes to water resources under global environmental change. However, despite decades of research supported by large amounts of highly complex hydrological observations, major gaps in our understanding persist, particularly regarding the storage and movement of water in the catchment. We suggest that a new type of information-rich data that can be easily collected and analyzed might be the key to new insights that propel the field toward a deeper, more fundamental understanding of hydrologic processes. Microbial communities, characterized taxonomically by sequencing the 16S rRNA gene in DNA, are highly diverse and respond dynamically to environmental conditions. To investigate the streamwater microbial community as a novel hydrologic dataset, we collected DNA samples over three years, from 2017-2020, from more than 60 streams across the Willamette, Deschutes, and John Day watersheds in Oregon, USA. I will show how we determined that differences in microbial communities are related to characteristics of the drainage catchment and how we used an information-theoretic approach to show that specific summer community constituents were related to stream discharge metrics at multiple temporal and flow scales. I will then elaborate on a more recent analysis in which we discovered that streamwater microbial diversity exhibited a rich and dynamic response to hydrograph dynamics over a single, isolated precipitation event. I will describe how we leverage published data about microbial taxonomy to identify pathways of water through the catchment, potentially contributing new insights regarding the sources and pathways of streamflow and a new way of characterizing taxa in microbial ecology studies. Overall, results of our research support the continued exploration of the hydrologic information encoded within microbial communities, as well as ways in which the field might best extract and apply this new information to further our understanding of hydrologic systems and contribute fresh insight to unsolved questions in hydrology.
Bio
Dawn URycki earned her PhD from Oregon State University with a dual major in Water Resources Engineering and Biological and Ecological Engineering under the advisement of Dr. Stephen P. Good. As a PhD student, she drove thousands of miles collecting more than 300 DNA samples in all the weather Oregon has to offer. She is currently a postdoctoral fellow at the University of Colorado Denver in the Civil Engineering Department, working with Dr. Allison Goodwell using information-theoretic approaches to investigate the dynamics and causal drivers of uncertainty in evapotranspiration observations. She is a new member and co-chair of the Professional Development Committee of the AGU Hydrology Section Student Subcommittee (H3S). She is also training for her first triathlon.