{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,3]],"date-time":"2026-09-03T04:46:17Z","timestamp":1788410777659,"version":"build-2803163510"},"reference-count":62,"publisher":"Public Library of Science (PLoS)","issue":"9","license":[{"start":{"date-parts":[[2024,9,24]],"date-time":"2024-09-24T00:00:00Z","timestamp":1727136000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/publicdomain\/zero\/1.0\/"}],"funder":[{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["EAR 1836768"],"award-info":[{"award-number":["EAR 1836768"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["1840243"],"award-info":[{"award-number":["1840243"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["www.plosone.org"],"crossmark-restriction":false},"short-container-title":["PLoS ONE"],"abstract":"<jats:p>Accurate characterization of the movement of water through catchments, particularly during precipitation event response, is critical for hydrological efforts such as contaminant transport modeling or prediction of extreme flows. Abiotic hydrogeochemical tracers are commonly used to track sources and ages of surface waters but provide limited details about transit pathways or the spatial dynamics of water storage and release. Alternatively, biotic material in streams is derived from thousands of taxa originating from a variety of environments within watersheds, including groundwater, sediment, and upslope terrestrial environments, and this material can be characterized with genetic sequencing and bioinformatics. We analyzed the stable water isotopes (\u03b4<jats:sup>18<\/jats:sup>O and \u03b4<jats:sup>2<\/jats:sup>H) and microbiome composition (16S rRNA gene amplicon sequencing) of the Marys River of western Oregon, USA during an early season storm to describe the processes, storage, and flowpaths that shape surface water hydrology. Stable water isotopes (\u03b4<jats:sup>18<\/jats:sup>O and \u03b4<jats:sup>2<\/jats:sup>H) typified an event response in which stream water is composed largely of \u2018old\u2019 water introduced to the catchment before the storm, a common though not well understood phenomenon. In contrast, microbial biodiversity spiked during the storm, consisting of early- and late-event communities clearly distinguishable from pre-event communities. We applied concentration-discharge (cQ) analysis to individual microbial taxa and found that most <jats:italic>Alphaproteobacteria<\/jats:italic> sequences were positively correlated (i.e., were mobilized) with discharge, whereas most sequences from phyla <jats:italic>Gammaproteobacteria<\/jats:italic> and <jats:italic>Bacteroidota<\/jats:italic> were negatively correlated with discharge (i.e., were diluted). Source predictions using the prokaryote habitat preference database ProkAtlas found that freshwater-associated microbes composed a smaller fraction of the microbial community during the stream rise and a larger fraction during the recession, while soil and biofilm-associated microbes increased during the storm and remained high during recession. This suggests that the \u201cold\u201d water discharged during the storm was likely stored and released from, or passed through, soil- and biofilm-rich environments, demonstrating that this approach adds new, biologically derived tracer information about the hydrologic pathways active during and after this event. Overall, this study demonstrates an approach for integrating information-rich DNA into water resource investigations, incorporating tools from both hydrology and microbiology to demonstrate that microbial DNA is useful not only as an indicator of biodiversity but also functions as an innovative hydrologic tracer.<\/jats:p>","DOI":"10.1371\/journal.pone.0306896","type":"journal-article","created":{"date-parts":[[2024,9,24]],"date-time":"2024-09-24T17:25:46Z","timestamp":1727198746000},"page":"e0306896","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":9,"title":["Microbial community storm dynamics signal sources of \u201cold\u201d stream water"],"prefix":"10.1371","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1901-0471","authenticated-orcid":true,"given":"Dawn R.","family":"URycki","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4363-1577","authenticated-orcid":true,"given":"Stephen P.","family":"Good","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Byron C.","family":"Crump","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2260-8426","authenticated-orcid":true,"given":"Natalie C.","family":"Ceperley","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"J. 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