In arid and semiarid environments, evapotranspiration (ET) is the primary discharge component in the water balance, with potential ET exceeding precipitation. For this reason, reliable estimates of ET are needed to construct accurate water budgets in these environments. Remote sensing affords the ability to provide fast, accurate, field-scale ET estimates, but these methods have largely been restricted to deep rooted (phreatophytic) plant communities underlain by shallow groundwater. We used 13 years of data from a 3-ha drainage lysimeter in a semiarid sagebrush steppe and Landsat normalized difference vegetation index (NDVI) data to calibrate a generalized least squares model capable of predicting vadose zone ET in a high elevation upland ecosystem. Annual precipitation was the best predictor of annual ET, as they were nearly balanced every year analysed (mean difference = 3 mm). We incorporated reference crop ET and a linear combination of NDVI and precipitation to capably predict ET on a subannual, lag-determined interval of 48 days, with a mean error of only 9.92% across all observations. To our knowledge, this is the first vegetation index-ET algorithm calibrated in a semiarid upland plant community using field-scale lysimetry. Vadose zone ET is particularly important at waste disposal sites in the Desert Southwest, where accurate and spatially explicit ET estimates are needed for monitoring potential mobilization and transport of contaminants past the root zone into local aquifers and for monitoring and modelling effects of recharge on flow and transport of contaminants in underlying aquifers.
Understanding interactions among biogeochemical cycles is increasingly important as anthropogenic alterations of global climate and of carbon (C), nitrogen (N), and phosphorus (P) cycles interactively affect the Earth system. Ecosystem processes in the dryland biome, which makes up over 40% of Earth's terrestrial surface, are often distinctively sensitive to small changes in resource availability, likely because levels of many resources are low. However, data also suggest that simultaneous changes in the availability of multiple resources may be necessary to affect a response in these low-resource systems, offering an opportunity to test patterns and controls of co-limitation, serial limitation, and individual limitation in soil environments. While drylands may play a governing role in key aspects of Earth's C cycle, and while an improved understanding of resource limitation could substantially improve our forecasts of dryland responses to change, our understanding of interacting controls on soil C cycle processes remains notably poor in these dry systems. Here, we address multiple fundamental hypotheses of resource controls over ecosystem function to test how water, C, N, and P regulate soil C cycling individually and interactively in a dryland ecosystem on the Colorado Plateau. Using a series of laboratory incubations, we found that, while water, C, and N limited C cycling through serial limitation, water alone resulted in an extremely small respiratory response from target organisms, whereas water + C resulted in a dramatic increase in soil C cycling, suggesting a degree of functional co-limitation. Nitrogen additions alone resulted in no changes to soil C cycling, but when N was added in concert with water and C, N greatly increased soil C cycling rates relative to additions of water and C without N. Phosphorus additions had no effect on the C cycle either alone or synergistically. These patterns were consistent with the stoichiometry of the system and interactions among resources were surprising in ways that inform our understanding of critical theories in ecology, such as the Transient Maxima Hypothesis, supporting the suggestion that multiple resource limitation explains pulse-dynamic C cycling in drylands better than water limitation alone.
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University","active":true,"usgs":false}],"preferred":false,"id":845240,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reed, Sasha C. 0000-0002-8597-8619 screed@usgs.gov","orcid":"https://orcid.org/0000-0002-8597-8619","contributorId":462,"corporation":false,"usgs":true,"family":"Reed","given":"Sasha","email":"screed@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":845241,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tucker, Colin 0000-0002-4539-7780 ctucker@usgs.gov","orcid":"https://orcid.org/0000-0002-4539-7780","contributorId":167487,"corporation":false,"usgs":true,"family":"Tucker","given":"Colin","email":"ctucker@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":845242,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70229978,"text":"70229978 - 2022 - What drought means for southwestern landscapes","interactions":[],"lastModifiedDate":"2025-03-14T15:12:55.049862","indexId":"70229978","displayToPublicDate":"2022-03-01T11:48:27","publicationYear":"2022","noYear":false,"publicationType":{"id":25,"text":"Newsletter"},"publicationSubtype":{"id":30,"text":"Newsletter"},"seriesTitle":{"id":8569,"text":"Boatman's Quarterly Review","active":true,"publicationSubtype":{"id":30}},"title":"What drought means for southwestern landscapes","docAbstract":"Introduction Each year, more than 20,000 people raft the Grand Canyon, many of whom will experience this iconic landscape for the first and only time. Visitors to our region for their once-in-a-lifetime Grand Canyon experience might be surprised to see forests and wetlands in addition to deserts. While locals are seeing changes to the Colorado Plateau woodlands, many visitors may not be able to distinguish between our normal desert landscapes (we have cactus!) and the increasingly dry and hot conditions we have experienced in recent decades. Helping visitors see these drought impacts could help communicate that climate change is not a problem for future generations but something affecting us now. The southwestern US (“Southwest”) is one of many dry regions around the world located within about 30 degrees of the equator. As global temperatures rise, these dry zones are getting drier and are likely expanding1. Dryland expansion and aridification alters water availability, which touches our lives and ecosystem health in the Southwest. This essay focuses on drought impacts on ecosystems across the Four-Corners region and Grand Canyon, with particular attention to the forests and woodlands that contribute, in part, to Colorado River flows.
","language":"English","publisher":"Grand Canyon River Guides","usgsCitation":"Samuels-Crow, K., Ogle, K., and Palmquist, E.C., 2022, What drought means for southwestern landscapes: Boatman's Quarterly Review, v. 35, no. 1, p. 16-19.","productDescription":"4 p.","startPage":"16","endPage":"19","ipdsId":"IP-137479","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":407799,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":483349,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://www.gcrg.org/bqr","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Arizona, California, Nevada","otherGeospatial":"Colorado River, Grand Canyon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.85107421875,\n 34.415973384481866\n ],\n [\n -111.24755859375,\n 34.415973384481866\n ],\n [\n -111.24755859375,\n 36.94989178681327\n ],\n [\n -114.85107421875,\n 36.94989178681327\n ],\n [\n -114.85107421875,\n 34.415973384481866\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"35","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Samuels-Crow, Kimberly","contributorId":289104,"corporation":false,"usgs":false,"family":"Samuels-Crow","given":"Kimberly","email":"","affiliations":[{"id":62051,"text":"School of Informatics, Computing, and Cyber Systems; Northern Arizona University, Flagstaff, AZ","active":true,"usgs":false}],"preferred":false,"id":838550,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ogle, Kiona","contributorId":248351,"corporation":false,"usgs":false,"family":"Ogle","given":"Kiona","email":"","affiliations":[],"preferred":false,"id":838551,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Palmquist, Emily C. 0000-0003-1069-2154 epalmquist@usgs.gov","orcid":"https://orcid.org/0000-0003-1069-2154","contributorId":5669,"corporation":false,"usgs":true,"family":"Palmquist","given":"Emily","email":"epalmquist@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":838552,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70229135,"text":"70229135 - 2022 - Pharmaceutical pollution of the world’s rivers","interactions":[],"lastModifiedDate":"2022-03-01T17:37:55.020596","indexId":"70229135","displayToPublicDate":"2022-03-01T10:21:01","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3164,"text":"Proceedings of the National Academy of Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Pharmaceutical pollution of the world’s rivers","docAbstract":"Environmental exposure to active pharmaceutical ingredients (APIs) can have negative effects on the health of ecosystems and humans. While numerous studies have monitored APIs in rivers, these employ different analytical methods, measure different APIs, and have ignored many of the countries of the world. This makes it difficult to quantify the scale of the problem from a global perspective. Furthermore, comparison of the existing data, generated for different studies/regions/continents, is challenging due to the vast differences between the analytical methodologies employed. Here, we present a global-scale study of API pollution in 258 of the world’s rivers, representing the environmental influence of 471.4 million people across 137 geographic regions. Samples were obtained from 1,052 locations in 104 countries (representing all continents and 36 countries not previously studied for API contamination) and analyzed for 61 APIs. Highest cumulative API concentrations were observed in sub-Saharan Africa, south Asia, and South America. The most contaminated sites were in low- to middle-income countries and were associated with areas with poor wastewater and waste management infrastructure and pharmaceutical manufacturing. The most frequently detected APIs were carbamazepine, metformin, and caffeine (a compound also arising from lifestyle use), which were detected at over half of the sites monitored. Concentrations of at least one API at 25.7% of the sampling sites were greater than concentrations considered safe for aquatic organisms, or which are of concern in terms of selection for antimicrobial resistance. Therefore, pharmaceutical pollution poses a global threat to environmental and human health, as well as to delivery of the United Nations Sustainable Development Goals.
","language":"English","publisher":"National Academy of Sciences","doi":"10.1073/pnas.2113947119","usgsCitation":"Wilkinson, J., Boxall, A.B., Kolpin, D., Leung, K.M., Lai, R.W., Galban-Malagon, C., Adell, A.D., Mondon, J., Metian, M., Marchant, R., Bouzas-Monroy, A., Cuni-Sanchez, A., Coors, A., P., C., Rojo, M., Gordon, C., Cara, M., Moermond, M., Luarte, T., Petrosyan, V., Perikhanyan, Y., Mahon, C.S., McGurk, C.J., Hofmann, T., Kormoker, T., Iniguez, V., Guzman-Otazo, J., Tavares, J.L., de Figueiredo, F.G., Razzolini, M.T., Dougnon, V., Gbaguidi, G., Traore, O., Blais, J., Kimpe, L.E., Wong, M., Wong, D., Ntchantcho, R., Pizarro, J., Ying, G., Chen, C., Paez, M., Martinez-Lara, J., Otamonga, J., Pote, J., Ifo, S.A., Wilson, P.J., Echeverria-Saenz, S., Udikovic-Kolic, N., Milakovic, M., Fatta-Kassinos, D., Ioannou-Ttofa, L., Belusova, V., Vymazal, J., Cardenas-Bustamante, M., Kassa, B.A., Garric, J., Chaumot, A., Gibba, P., Kunchulia, I., S., S., Lyberatos, G., Halldórsson, H., Melling, M., Shashidhar, T., Lamba, M., Nastiti, A., Supriatin, A., Pourang, N., Abedini, A., Abdullah, O., Gharbia, S.S., Pilla, F., Chefetz, B., Topaz, T., Yao, K.M., Aubakirova, B., Beisenova, R., Olaka, L., Mulu, J., Chatanga, P., Ntuli, V., Blama, N.T., Sherif, S., Aris, A.Z., Looi, L.J., Niang, M., Traore, S.T., Oldenkamp, R., Ogunbanwo, O., Ashfaq, M., Iqbal, M., Abdeen, Z., O’Dea, A., Morales-Saldana, J.M., Custodio, M., de la Cruz, H., Navarrete, I., Carvalho, F., Gogra, A.B., Koroma, B.M., Cerkvenik-Flajs, V., Gombac, M., Thwala, M., Choi, K., Kang, H., Celestino Ladu, J.L., Rico, A., Amerashinghe, P., Sobek, A., Horlitz, G., Zenker, A.K., King, A.C., Jiang, J., Kariuki, R., Tumbo, M., Tezel, U., Onay, T.T., Lejju, J.B., Vystavna, Y., Vergeles, Y., Heinzen, H., Perez-Parada, A., Sims, D.B., Figy, M., Good, D., and Teta, C., 2022, Pharmaceutical pollution of the world’s rivers: Proceedings of the National Academy of Sciences, v. 119, no. 8, p. 1-10, https://doi.org/10.1073/pnas.2113947119.","productDescription":"e2113947119, 10 p.","startPage":"1","endPage":"10","ipdsId":"IP-129923","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":448650,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1073/pnas.2113947119","text":"Publisher Index Page"},{"id":396606,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Earth","volume":"119","issue":"8","noUsgsAuthors":false,"publicationDate":"2022-02-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Wilkinson, John L.","contributorId":287305,"corporation":false,"usgs":false,"family":"Wilkinson","given":"John L.","affiliations":[{"id":35536,"text":"University of York","active":true,"usgs":false}],"preferred":false,"id":836613,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boxall, Alistair B. A.","contributorId":218103,"corporation":false,"usgs":false,"family":"Boxall","given":"Alistair","email":"","middleInitial":"B. A.","affiliations":[{"id":35536,"text":"University of York","active":true,"usgs":false}],"preferred":false,"id":836614,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kolpin, Dana W. 0000-0002-3529-6505","orcid":"https://orcid.org/0000-0002-3529-6505","contributorId":204154,"corporation":false,"usgs":true,"family":"Kolpin","given":"Dana W.","affiliations":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"preferred":true,"id":836615,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Leung, Kenneth M. Y.","contributorId":287307,"corporation":false,"usgs":false,"family":"Leung","given":"Kenneth","email":"","middleInitial":"M. Y.","affiliations":[{"id":55550,"text":"University of Hong Kong","active":true,"usgs":false}],"preferred":false,"id":836616,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lai, Racliffe W. S.","contributorId":287490,"corporation":false,"usgs":false,"family":"Lai","given":"Racliffe","email":"","middleInitial":"W. 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These data are available at 1-degree grids along the U.S. coastline and downscaled specifically at NOAA tide-gauge locations. Estimates of flood exposure are assessed using contemporary U.S. coastal flood-severity thresholds for current conditions (e.g., sea levels and infrastructure footprint) and for the next 30 years (out to year 2050), assuming no additional risk reduction measures are enacted.
This effort builds upon the 2017 Task Force report (Sweet et al., 2017). In particular, the set of global mean sea level rise scenarios from that report are updated and downscaled with output directly from the United Nations Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6; IPCC, 2021a), through the efforts of the NASA Sea Level Change Team; updates include adjustments to the temporal trajectories and exceedance probabilities of these scenarios based upon end-of-century global temperatures. As with the 2017 report, these global mean sea level rise scenarios are regionalized for the U.S. coastline. In addition, methodology supporting the U.S. Department of Defense Regional Sea Level (DRSL) database (Hall et al., 2016) is adapted for the extreme water level dataset newly developed for this report.
This report will be a key technical input for the Fifth National Climate Assessment (NCA5). These data and information are being incorporated into current and planned agency tools and services, such as NOAA’s Sea Level Rise Viewer and Inundation Dashboard, NASA’s Sea Level Change Portal, and others. Although the intent of this report is not to provide authoritative guidance or design specifications for a specific project, it is intended to help inform Federal agencies, state and local governments, and stakeholders in coastal communities about current and future sea level rise to help contextualize its effects for decision-making purposes.
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The deposit is hosted in the Taconian (approximately 480 – 450 Ma) Martinsville igneous complex, which consists of the Ordovician Leatherwood Granite (granodiorite) and Silurian Rich Acres Formation (diorite). The host rock was metamorphosed to orthogneiss during the Alleghanian orogeny (approximately 325 – 260 Ma) when it also underwent dextral strike-slip movement along the Brookneal shear zone. During the Triassic, extensional tectonics led to the development of the Dan River Basin that lies east of Coles Hill. The mineralized zone is hosted in brittle structures in the footwall of the Triassic Chatham fault that forms the western edge of the basin. Within brittle fracture zones, uranium silicate and uranium-bearing fluorapatite with traces of brannerite form veins and breccia fill with chlorite, quartz, calcite, titanium oxide, pyrite, and calcite. Uranium silicates also coat and replace primary titanite, zircon, ilmenite, and sulfides. Sodium metasomatism preceded and accompanied uranium mineralization, pervasively altering host rock, and forming albite from primary feldspar, depositing limpid albite rims on feldspar, altering titanite to titanium oxide and calcite and forming riebeckite. Various geothermometers suggest temperatures of less than approximately ~200°C during mineralization. In situ U-Pb analyses of titanite, Ti-oxide, and apatite, and Rb/Sr and U/Pb isotope-systematics of whole rock samples resolve the timing of geologic processes affecting Coles Hill. The host Leatherwood granite containing primary euhedral titanite is dated at 450 – 445 Ma, in agreement with previously obtained ages from zircon in the Martinsville igneous complex. A regional metamorphic event at 330 – 310 Ma formed anhedral titanite and some apatite, re-equilibrated whole rock Rb/Sr and U-Pb isotopes and is interpreted to have coincided with movement along the Brookneal shear zone. During shearing and metamorphism primary refractory uranium-bearing minerals including titanite, zircon, and uranothorite were recrystallized and uranium was liberated and incorporated locally into hematite, clay, and other fine-grained minerals. Uranium mineralization was accompanied by a metasomatic episode between 250 and 200 Ma that reset the Rb-Sr and U-Pb isotope systems, forming titanite and apatite that are associated and in places intimately intergrown with uranium silicate dating mineralization. This event coincides with rifting that formed the Dan River Basin and was a precursor to the breakup of Pangea. Based on the close spatial and temporal association of uranium with apatite, we conclude that uranium was carried as a uranyl-phosphate complex. The release of calcium during sodium metasomatic alteration of primary calcic feldspar and titanite in the host rock initiated successive reactions in which uranium and phosphate in mineralizing fluids combined with calcium to form U-enriched fluorapatite. Excess uranium was locally reduced by coupled redox reactions involving ferrous iron and sulfide minerals in the host rock, forming uranium silicates. Based on the deposit mineralogy, oxygen isotope geochemistry and trace element characteristics of uranium silicate and gangue minerals the primary mineralizing fluids likely included connate and/or meteoric water sourced from the local Dan River Basin. High heat flow related to Mesozoic rifting may have driven these (P-Na-F-rich) brines through local aquifers and into basin margin faults, transporting uranium from the basin or mobilizing uranium from previously formed U-minerals in the Brookneal shear zone, or from U-enriched older basement rock.
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Center","active":true,"usgs":true}],"preferred":true,"id":850832,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Breit, G.N.","contributorId":296172,"corporation":false,"usgs":false,"family":"Breit","given":"G.N.","email":"","affiliations":[{"id":63998,"text":"Former USGS volunteer","active":true,"usgs":false}],"preferred":false,"id":850833,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Zielinski, Robert A. 0000-0002-4047-5129 rzielinski@usgs.gov","orcid":"https://orcid.org/0000-0002-4047-5129","contributorId":1593,"corporation":false,"usgs":true,"family":"Zielinski","given":"Robert","email":"rzielinski@usgs.gov","middleInitial":"A.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":850834,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Aylor, G. J. Jr.","contributorId":296174,"corporation":false,"usgs":false,"family":"Aylor","given":"G.","suffix":"Jr.","email":"","middleInitial":"J.","affiliations":[{"id":27992,"text":"Virginia Museum of Natural History","active":true,"usgs":false}],"preferred":false,"id":850835,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70237201,"text":"70237201 - 2022 - USGS invasive carp database management and integration support","interactions":[],"lastModifiedDate":"2022-10-04T14:55:20.0136","indexId":"70237201","displayToPublicDate":"2022-03-01T09:47:50","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":3,"text":"Organization Series"},"title":"USGS invasive carp database management and integration support","docAbstract":"Bigheaded carps (Bighead Carp and Silver Carp) tracking, monitoring, and contracted removal will continue throughout the Illinois River and Upper Mississippi River as part of an adaptive management effort to mitigate, control, and contain bigheaded carps. Other fish will also be tracked to maintain a holistic view of the transmitter distribution in the Upper Illinois River Waterway. To facilitate these actions, a need to compile and analyze invasive carp-related data from all agencies exists. Invasive carp-related data include all data sources that could inform the MRWG objectives or projects. These data, often in disparate formats, must be integrated into a common format that allows all agencies the opportunity to assess invasive carp monitoring, control, and removal efforts. Ensuring the interoperability of these datasets allows for their use in various analyzes and modeling efforts. Implementing an interoperable data management framework provides the mechanisms for end users to find and use integrated data. Integrating data for use in modeling and analysis furthers the partnership’s collective understanding of bigheaded carp life history, distribution, and movement and can be used to facilitate adaptive management actions (e.g., directing monitoring, sampling, and removal efforts, assessing invasive carp abundance to support modeling efforts, informing deployment of control actions, etc.). An effective data management strategy will streamline the data update process, providing all agencies with timely data and analyses in support of informed decision-making processes.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"2021 Invasive carp interim summary report","largerWorkSubtype":{"id":3,"text":"Organization Series"},"language":"English","publisher":"Invasive Carp Regional Coordinating Committee","usgsCitation":"Harrison, T.J., Brey, M.K., and Stone, J., 2022, USGS invasive carp database management and integration support, 4 p.","productDescription":"4 p.","startPage":"109","endPage":"112","ipdsId":"IP-139244","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":407860,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":407845,"type":{"id":15,"text":"Index Page"},"url":"https://invasivecarp.us/PlansReports.html","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Illinois, Iowa, Minnesota, Missouri, Wisconsin","otherGeospatial":"Illinois River, upper Mississippi River system","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.14306640625,\n 36.421282443649496\n ],\n [\n -88.11035156249999,\n 40.6306300839918\n ],\n [\n -87.73681640625,\n 41.95131994679697\n ],\n [\n -88.681640625,\n 43.644025847699496\n ],\n [\n -89.12109375,\n 46.118941506107056\n ],\n [\n -91.0986328125,\n 46.51351558059737\n ],\n [\n -93.1640625,\n 46.483264729155586\n ],\n [\n -93.80126953124999,\n 47.754097979680026\n ],\n [\n -94.833984375,\n 48.06339653776211\n ],\n [\n -96.3720703125,\n 46.73986059969267\n ],\n [\n -96.26220703125,\n 44.809121700077355\n ],\n [\n -94.8779296875,\n 42.21224516288584\n ],\n [\n -92.548828125,\n 39.57182223734374\n ],\n [\n -91.1865234375,\n 37.37015718405753\n ],\n [\n -90.10986328125,\n 36.98500309285596\n ],\n [\n -90.28564453124999,\n 36.63316209558658\n ],\n [\n -89.80224609374999,\n 36.12012758978146\n ],\n [\n -89.14306640625,\n 36.421282443649496\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Harrison, Travis J. 0000-0002-9195-738X","orcid":"https://orcid.org/0000-0002-9195-738X","contributorId":213966,"corporation":false,"usgs":true,"family":"Harrison","given":"Travis","email":"","middleInitial":"J.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":853617,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brey, Marybeth K. 0000-0003-4403-9655 mbrey@usgs.gov","orcid":"https://orcid.org/0000-0003-4403-9655","contributorId":187651,"corporation":false,"usgs":true,"family":"Brey","given":"Marybeth","email":"mbrey@usgs.gov","middleInitial":"K.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":853659,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stone, Jayme 0000-0002-0512-3072","orcid":"https://orcid.org/0000-0002-0512-3072","contributorId":251712,"corporation":false,"usgs":false,"family":"Stone","given":"Jayme","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":false,"id":853618,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70264283,"text":"70264283 - 2022 - Wind River subbasin restoration: Annual Report of U.S. Geological Survey activities January 2020 through December 2020","interactions":[],"lastModifiedDate":"2025-03-10T15:02:41.714948","indexId":"70264283","displayToPublicDate":"2022-03-01T09:41:36","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Wind River subbasin restoration: Annual Report of U.S. Geological Survey activities January 2020 through December 2020","docAbstract":"We sampled juvenile wild Steelhead Trout Oncorhynchus mykiss in headwater streams of the Wind River, WA, to characterize population attributes and investigate life-history metrics, particularly migratory patterns, and early life-stage survival. We used passive integrated transponder (PIT) tagging and a series of instream PIT-tag interrogation systems (PTISs) to track juveniles and adults. The Wind River subbasin is considered a wild Steelhead refuge by Washington Department of Fish and Wildlife (WDFW). No hatchery Steelhead Trout have been released in the Wind River subbasin since 1997, and hatchery adults are estimated at less than one percent of spawners in most years. Over twenty years of Steelhead Trout status and trend monitoring and research in the subbasin is contributing to understanding of population response to numerous restoration actions in the subbasin, including removal of Hemlock Dam from Trout Creek in 2009, which had an outdated adult ladder and contributed to increased water temperatures reducing performance of juvenile Steelhead Trout.
Data from our study, and companion work by Washington Department of Fish and Wildlife, are contributing to Bonneville Power Administration’s (BPA) Research, Monitoring, and Evaluation (RM&E) Program Strategy of Fish Population Status Monitoring (https://www.cbfish.org/ProgramStrategy.mvc/Index). Specifically, this work addresses the substrategies of 1) Assessing the Status and Trends of Diversity of Natural Origin Fish Populations and Uncertainties Research regarding differing life histories of a wild Steelhead Trout population, 2) Assessing the Status and Trend of Adult Natural Origin Fish Populations, and 3) Monitoring and Evaluating the Effectiveness of Tributary Habitat Actions Relative to Environmental, Physical, or Biological Performance Objectives.
During summer and fall 2020, we PIT-tagged 1,415 Steelhead parr (age-0 and age-1) in the Trout Creek and upper Wind River watersheds. Recaptures and detections of PIT-tagged Steelhead Trout parr happened through repeat headwater sampling, smolt trap operations, and instream PTISs and Columbia River PIT-tag detection infrastructure. Throughout the year, we maintained a series of six instream PTISs to monitor movement of tagged Steelhead Trout parr, smolts, and adults, providing data to population assessments, and life-cycle research and modeling.
Detection data from PIT-tagged adult Steelhead Trout at PTISs allow assessment of adult escapement to tributary watersheds within the Wind River subbasin. Adult Steelhead Trout detection efficiency estimates at our primary PTIS in Trout Creek have been greater than 92 percent during eight of the past nine years and have exceeded 90% at our primary PTIS in the Wind River the past three years. Adult escapement estimates to tributary watersheds are helping evaluate the efficacy of the 2009 removal of Hemlock Dam from rkm 2.0 of Trout Creek. The dam had potential negative effects on Steelhead Trout populations in Trout Creek due to hydrologic impairment, increased temperatures, and adult passage issues. Hemlock Dam was laddered for adult passage, but not to modern standards, which likely resulted in avoidance by some adult Steelhead Trout.
We continue to improve our PTISs in the Wind River subbasin. The improvements in siting and addition of grid power to the upper Wind River PTIS (site code WRU, rkm 27.6) during 2016 and 2017, and the addition of the Mine Reach site (site code MIN, rkm 36.0) have much improved PIT-tagged fish monitoring in the upper Wind River watershed. The paired PTIS design in the upper Wind River watershed (sites WRU and MIN), matches that in the Trout Creek watershed (sites TRC and TC4) and will allow comparisons of Steelhead Trout population metrics between the two watersheds as response to Hemlock Dam removal continues and future restoration efforts occur in Trout Creek. We installed two new PTISs during 2020. Both were installed downstream of our primary interrogation sites on Trout Creek and in the mainstem Wind River. We hope the two new sites will provide interrogations information that will allow us to better estimate detection efficiencies of downstream moving juvenile Steelhead Trout at the primary interrogation sites. The additional interrogations will be particularly important for those fish tagged with 9-mm PIT tags as less information from downstream locations is available from them. These sites and other status and trend data will allow evaluation of further planned restoration within the watershed, particularly that proposed for the headwaters of Trout Creek.
Detections at the instream PTISs have demonstrated trends of age-0 and age-1 parr emigration from natal areas during summer and fall, in addition to the expected movement of parr and smolts in spring. We have estimated that from 15 to 51% of parr tagged as age-0 fish in headwater areas make downstream migrations at age 1 for additional rearing during both spring and fall. We have estimated that up to 27% of Steelhead Trout parr, tagged as age-1 fish, make downstream migrations during fall. These findings raise questions about where parr most successfully rear and whether migrations are density or habitat quality driven. Broader monitoring programs would give a more comprehensive understanding of juvenile Steelhead Trout production and rearing and productivity contribution.
Repeat sampling at consistent locations in the subbasin has enabled assessment of juvenile Steelhead Trout growth patterns. Growth rates (relative change in weight) of age-0 PITtagged parr during summer were similar across the subbasin but lower for age-1 parr in the Trout Creek watershed than the upper Wind River watershed. Yearly relative growth for parr tagged at age-0 is similar across the subbasin.
Non-native Brook Trout Salvelinus confluentus are present in the subbasin, chiefly the Trout Creek watershed, and repeat sampling has allowed us to index their prevalence. Mean percent-of-catch that is Brook Trout, at four sample sites in Trout Creek, has declined from the period 1998 – 2003 to the period 2011 – 2020. Percent-of-catch and number of Brook Trout at the Trout Creek sites from 2011 through 2020 declined, though both metrics increased in 2018.
Evaluation and planning of restoration efforts are critical to ensure efficient use of resources. Assessing Steelhead Trout life history variation in the Wind River subbasin will inform research and tracking of many populations and help inform habitat restoration and water allocation planning. Movement of Steelhead Trout parr from natal areas to other rearing areas raises questions regarding juvenile abundance, origin, and habitat use within watersheds. Improved PTISs and focused PIT tagging of age-0 and age-1 Steelhead Trout parr allow investigation of such questions. Increasingly detailed viable salmonid population information, such as that provided by PIT-tagging and instream PTIS networks like those in the Wind River can provide data to inform fisheries policy and management and understand life-history strategies and limiting factors. Such efforts also provide assessment of long-term effects of habitat restoration actions such as the removal of Hemlock Dam on Trout Creek, and the proposed Stage-0 restoration effort for upper Trout Creek, which would be a large-scale effort to reset sections of stream within their floodplain, restoring connectivity and interaction with surrounding landscape.
","language":"English","publisher":"Bonneville Power Administration","usgsCitation":"Jezorek, I., 2022, Wind River subbasin restoration: Annual Report of U.S. Geological Survey activities January 2020 through December 2020, 71 p.","productDescription":"71 p.","ipdsId":"IP-137356","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":483143,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":483119,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.cbfish.org/Document.mvc/Viewer/P190880","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Washington","otherGeospatial":"Wind River subbasin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.1275,\n 46\n ],\n [\n -122.1275,\n 45.75\n ],\n [\n -121.8,\n 45.75\n ],\n [\n -121.8,\n 46\n ],\n [\n -122.1275,\n 46\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Jezorek, Ian 0000-0002-3842-3485","orcid":"https://orcid.org/0000-0002-3842-3485","contributorId":217811,"corporation":false,"usgs":true,"family":"Jezorek","given":"Ian","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":930257,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70237373,"text":"70237373 - 2022 - Modeling functional flows in California rivers","interactions":[],"lastModifiedDate":"2022-10-12T14:30:29.820543","indexId":"70237373","displayToPublicDate":"2022-03-01T09:17:10","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5738,"text":"Frontiers in Environmental Science","active":true,"publicationSubtype":{"id":10}},"title":"Modeling functional flows in California rivers","docAbstract":"Environmental flows are critical to the recovery and conservation of freshwater ecosystems worldwide. However, estimating\ndesired ranges of environmental flows across large, diverse landscapes is challenging. To advance protections of environmental flows for streams in California, USA, we developed a statewide modeling approach focused on functional components of the natural flow regime. Functional flow components in California streams—fall pulse flows, wet season peak flows and base flows, the spring flow recession, and dry season baseflows—support essential physical and ecological processes in riverine ecosystems. These functional flow components can be represented by functional flow metrics (FFMs) and quantified by their magnitude, timing, frequency, duration, and rate-of-change from daily streamflow records. After quantifying FFMs at reference-quality streamflow gages in California, we used machine-learning methods to estimate their natural range of values for all stream reaches in the state based on physical watershed characteristics and climatic factors. We found that the models performed well in predicting FFMs in streams across a diversity of landscape and climate contexts, according to several model performance criteria. Using the predicted FFM values, we established initial estimates of ecological flows that are expected to support critical functions and are broadly protective of ecosystem health. Modeling functional flows statewide offers a pathway for increasing the pace and scale of environmental flow protections in California and beyond.","language":"English","publisher":"Frontiers in Environmental Science","doi":"10.3389/fenvs.2022.787473","usgsCitation":"Grantham, T.E., Carlisle, D.M., Howard, J., Lane, B., Lusardi, R., Obester, A., Sandoval-Solis, S., Stanford, B., Stein, E.D., Taniguchi-Quan, K.T., Yarnell, S.M., and Zimmerman, J.K., 2022, Modeling functional flows in California rivers: Frontiers in Environmental Science, v. 10, 787473, 11 p., https://doi.org/10.3389/fenvs.2022.787473.","productDescription":"787473, 11 p.","ipdsId":"IP-132706","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":448653,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fenvs.2022.787473","text":"Publisher Index Page"},{"id":435941,"rank":0,"type":{"id":30,"text":"Data 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California--Davis","active":true,"usgs":false}],"preferred":false,"id":854318,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Zimmerman, Julie K. 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Here, we used a data-driven approach to identify regional patterns and exogenous controls on P–Q interactions. We applied an information flow analysis, which quantifies uncertainty reduction, to a daily time series of P and Q from 671 watersheds across the conterminous United States. We first demonstrated that information transfer from P to Q primarily reflects the quickflow component of water-budgets, based on a watershed model. Readily quantifiable information flows show a functional relationship with model parameters, suggesting utility for model calibration. Second, applied to real watersheds, P–Q information flows exhibit seasonally varying behavior within regions in a manner consistent with dominant runoff generation mechanisms. However, the timing and the magnitude of information flows also reflect considerable subregional heterogeneity, likely attributable to differences in watershed size, baseflow contributions, and variation in aerial coverage of preferential flow paths. A regression analysis showed that a combination of climate and watershed characteristics are predictive of P–Q information flows. Though information flows cannot, in most cases, uniquely determine dominant runoff mechanisms, they provide a means to quantify the heterogeneous outcomes of those mechanisms within regions, thereby serving as a benchmarking tool for models developed at the regional scale. Last, information flows characterize regionally specific ways in which catchment connectivity changes from the wet to dry season.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021WR030186","usgsCitation":"Moges, E., Ruddell, B., Zhang, L., Driscoll, J.M., and Larsen, L., 2022, Strength and memory of precipitation's control over streamflow across the conterminous United States: Water Resources Research, v. 58, no. 3, e2021WR030186, 20 p., https://doi.org/10.1029/2021WR030186.","productDescription":"e2021WR030186, 20 p.","ipdsId":"IP-128702","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":448657,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2021wr030186","text":"Publisher Index Page"},{"id":397106,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"conterminous United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n 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Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":837995,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Larsen, Laurel","contributorId":190106,"corporation":false,"usgs":false,"family":"Larsen","given":"Laurel","affiliations":[],"preferred":false,"id":837996,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70229540,"text":"70229540 - 2022 - Identification of fresh submarine groundwater off the coast of San Diego, USA, using electromagnetic methods","interactions":[],"lastModifiedDate":"2022-05-13T14:53:35.170768","indexId":"70229540","displayToPublicDate":"2022-03-01T09:01:59","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1923,"text":"Hydrogeology Journal","active":true,"publicationSubtype":{"id":10}},"title":"Identification of fresh submarine groundwater off the coast of San Diego, USA, using electromagnetic methods","docAbstract":"Climate change has a pronounced effect on water resources in many semiarid climates, causing populated areas such as San Diego County (USA), to become more vulnerable to water shortages in the coming decades. To prepare for decreased water supply, San Diego County is adopting policies to decrease water use and to develop additional local sources of water. One new local source of freshwater is produced by a desalination facility that purifies brackish groundwater from the coastal San Diego Formation. This formation has been studied extensively onshore, but little is known about the geology or groundwater quality offshore in the adjacent continental shelf. Because most groundwater systems are interconnected and complex, further analysis is needed to identify offshore geology, possible sequestration of freshwater in the shelf, and potential pathways for saltwater intrusion. This comprehensive understanding is important because seawater intrusion may limit use of the San Diego Formation and longevity of desalination facilities. Controlled-source electromagnetic methods are uniquely suited to detecting offshore groundwater as they are sensitive to changes in pore fluids such as the transition from fresh to brackish groundwater. This paper describes results from surface-towed electromagnetic surveys that mapped the pore-fluid salinity and possible fluid pathways in the continental shelf off the coast of San Diego. The results indicate a considerable volume of fresh-to-brackish groundwater sequestered in the shelf, both in continuous lenses and isolated pockets, that appear influenced by fault systems and shallow stratigraphy.
","language":"English","publisher":"Springer Link","doi":"10.1007/s10040-022-02463-y","usgsCitation":"King, R.B., Danskin, W.R., Constable, S., and Maloney, J.M., 2022, Identification of fresh submarine groundwater off the coast of San Diego, USA, using electromagnetic methods: Hydrogeology Journal, v. 30, p. 965-973, https://doi.org/10.1007/s10040-022-02463-y.","productDescription":"9 p,","startPage":"965","endPage":"973","ipdsId":"IP-132993","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":448661,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10040-022-02463-y","text":"Publisher Index Page"},{"id":396992,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Baja California, California","city":"San Diego","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.333984375,\n 32.400834826722196\n ],\n [\n -116.97967529296874,\n 32.442567075075075\n ],\n [\n -116.43035888671875,\n 32.11980111179328\n ],\n [\n -116.180419921875,\n 32.001088607540446\n ],\n [\n -116.11175537109376,\n 32.05231681645636\n ],\n [\n -116.14196777343749,\n 32.20815332547324\n ],\n [\n -116.45233154296874,\n 32.669436832605314\n ],\n [\n -116.71874999999999,\n 33.05932046347212\n ],\n [\n -116.82586669921874,\n 33.123750829710225\n ],\n [\n -117.1307373046875,\n 32.960281958039836\n ],\n [\n -117.41638183593749,\n 32.76880048488168\n ],\n [\n -117.49053955078125,\n 32.74339241542703\n ],\n [\n -117.333984375,\n 32.400834826722196\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"30","noUsgsAuthors":false,"publicationDate":"2022-03-01","publicationStatus":"PW","contributors":{"authors":[{"text":"King, Roslynn B. 0000-0001-9944-2463","orcid":"https://orcid.org/0000-0001-9944-2463","contributorId":288371,"corporation":false,"usgs":false,"family":"King","given":"Roslynn","email":"","middleInitial":"B.","affiliations":[{"id":61739,"text":"Scripps Institution of Oceanography, University of California San Diego and Department of Geological Sciences, San Diego State University","active":true,"usgs":false}],"preferred":false,"id":837801,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Danskin, Wesley R. 0000-0001-8672-5501 wdanskin@usgs.gov","orcid":"https://orcid.org/0000-0001-8672-5501","contributorId":1034,"corporation":false,"usgs":true,"family":"Danskin","given":"Wesley","email":"wdanskin@usgs.gov","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":837802,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Constable, Steven","contributorId":9178,"corporation":false,"usgs":false,"family":"Constable","given":"Steven","email":"","affiliations":[{"id":16196,"text":"Scripps Institution of Oceanography, La Jolla, CA","active":true,"usgs":false}],"preferred":false,"id":837803,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Maloney, Jillian M. 0000-0001-8223-4676","orcid":"https://orcid.org/0000-0001-8223-4676","contributorId":261208,"corporation":false,"usgs":false,"family":"Maloney","given":"Jillian","email":"","middleInitial":"M.","affiliations":[{"id":6608,"text":"San Diego State University","active":true,"usgs":false}],"preferred":false,"id":837804,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70241168,"text":"70241168 - 2022 - Real-time telemetry and multi-state modeling","interactions":[],"lastModifiedDate":"2023-03-14T13:46:09.843378","indexId":"70241168","displayToPublicDate":"2022-03-01T08:39:37","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":3,"text":"Organization Series"},"title":"Real-time telemetry and multi-state modeling","docAbstract":"This project will result in real-time data and other invasive carp movement information to inform realtime management decisions and refine the SEICarP model. FY 2022 funding will produce final transition probability estimates from the newly-developed Bayesian multi-state model, continue the maintenance of real-time telemetry to inform contingency actions, and produce a study plan to refine fishing mortality estimates using telemetry data.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"2022 Invasive Carp Action Plan","largerWorkSubtype":{"id":3,"text":"Organization Series"},"language":"English","publisher":"Invasive Carp Regional Coordinating Committee","usgsCitation":"Brey, M.K., Knights, B.C., Jackson, P.R., Stanton, J.C., Appel, D., Duncker, J.J., and Fritts, A.K., 2022, Real-time telemetry and multi-state modeling, 2 p.","productDescription":"2 p.","startPage":"49","endPage":"50","ipdsId":"IP-138045","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":414093,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":414092,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://invasivecarp.us/PlansReports.html"}],"country":"United States","state":"Illinois","otherGeospatial":"Illinois River, Mississippi River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -87.53510308013573,\n 42.06797711967815\n ],\n [\n -91.44414970929891,\n 42.06797711967815\n ],\n [\n -91.44414970929891,\n 38.91562899040929\n ],\n [\n -87.53510308013573,\n 38.91562899040929\n ],\n [\n -87.53510308013573,\n 42.06797711967815\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Brey, Marybeth K. 0000-0003-4403-9655 mbrey@usgs.gov","orcid":"https://orcid.org/0000-0003-4403-9655","contributorId":187651,"corporation":false,"usgs":true,"family":"Brey","given":"Marybeth","email":"mbrey@usgs.gov","middleInitial":"K.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":866332,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Knights, Brent C. 0000-0001-8526-8468 bknights@usgs.gov","orcid":"https://orcid.org/0000-0001-8526-8468","contributorId":2906,"corporation":false,"usgs":true,"family":"Knights","given":"Brent","email":"bknights@usgs.gov","middleInitial":"C.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":866333,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jackson, P. Ryan 0000-0002-3154-6108 pjackson@usgs.gov","orcid":"https://orcid.org/0000-0002-3154-6108","contributorId":194529,"corporation":false,"usgs":true,"family":"Jackson","given":"P.","email":"pjackson@usgs.gov","middleInitial":"Ryan","affiliations":[{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":true,"id":866334,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stanton, Jessica C. 0000-0002-6225-3703 jcstanton@usgs.gov","orcid":"https://orcid.org/0000-0002-6225-3703","contributorId":5634,"corporation":false,"usgs":true,"family":"Stanton","given":"Jessica","email":"jcstanton@usgs.gov","middleInitial":"C.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":866335,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Appel, Douglas 0000-0001-8775-1058","orcid":"https://orcid.org/0000-0001-8775-1058","contributorId":268159,"corporation":false,"usgs":true,"family":"Appel","given":"Douglas","email":"","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":866336,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Duncker, James J. 0000-0001-5464-7991 jduncker@usgs.gov","orcid":"https://orcid.org/0000-0001-5464-7991","contributorId":4316,"corporation":false,"usgs":true,"family":"Duncker","given":"James","email":"jduncker@usgs.gov","middleInitial":"J.","affiliations":[{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":true,"id":866337,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Fritts, Andrea K. 0000-0003-2142-3339","orcid":"https://orcid.org/0000-0003-2142-3339","contributorId":204594,"corporation":false,"usgs":true,"family":"Fritts","given":"Andrea","email":"","middleInitial":"K.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":866338,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70230685,"text":"70230685 - 2022 - Natural and anthropogenic influences on benthic cyanobacteria in streams of the northeastern United States","interactions":[],"lastModifiedDate":"2022-05-13T15:16:03.306357","indexId":"70230685","displayToPublicDate":"2022-03-01T06:53:35","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Natural and anthropogenic influences on benthic cyanobacteria in streams of the northeastern United States","docAbstract":"Benthic cyanobacteria are widespread in streams and rivers and have the potential to release toxins. In large numbers, these microorganisms and their toxins present a risk to human health. Cyanobacterial abundance in stream biofilms is typically related to single or a limited set of environmental factors, mainly light availability, water temperature, and nutrient concentrations. However, these factors may act synergistically with watershed characteristics and other stressors, such as anthropogenic pollutants, to affect cyanobacteria. We investigated the influence of multiple regional and local variables on the abundance of benthic cyanobacterial genera in streams using all subsets generalized additive modeling. We examined watershed factors (topography, geology, and climate) alongside in-stream factors (geomorphology, hydrology, pH, specific conductance, nutrients, organic contaminants, and dissolved metals) from 76 sites along an urban gradient in the northeast United States. Each genus responded to a distinct combination of environmental variables, demonstrating strong intergeneric variation in environmental selection of realized niches. Four of the 7 potentially toxigenic genera that we modeled were positively influenced by water temperature or nutrients. Nonetheless, watershed characteristics, streamflow, and/or other water quality pollutants were equally or more influential for the potentially toxigenic genera. Additionally, the relationships between cyanobacterial abundance and environmental factors varied in shape and direction across many genera. In particular, with increasing concentrations of herbicides, polychlorinated biphenyls, or metals, the abundance of roughly half of the affected genera decreased, while the others increased. These results likely demonstrate novel toxic effects of the pollutants on cyanobacterial genera in the environment, while indicating that unmeasured biotic interactions may lead to positive responses for other genera. Our results emphasize the need to consider variables beyond those that are most frequently measured or implicated (e.g., water temperature and nutrients) to more fully understand the environmental conditions that influence the distributions and abundance of potentially harmful cyanobacteria.
As human populations grow, decisions regarding use of the world's finite land base become increasingly complex. We adopted a land use–conflict scenario involving renewable energy to illustrate one potential cause of these conflicts and resulting tradeoff decisions. Renewable energy industries wishing to expand operations in the United States are limited by multijurisdictional regulations in finding developable land. Interest groups entreat industries to avoid land for various reasons, including avoidance of prime wildlife habitat in accordance with an “avoidance-first” mitigation strategy. By applying a uniform set of rules for renewable energy facilities to the Prairie Pothole Region and portions of the Northern Great Plains, we evaluated the effects of regulations and avoidance of prime wildlife habitat on the amount of land available for development. In our scenario, existing regulations excluded 39% of the project area from potential development, with human infrastructure accounting for 30% (10–66% among states), whereas federally protected species accounted for < 1% at project area and state levels. Unregulated lands accounted for 61% of the project area, with conservation areas predicted as high-quality sites for breeding grassland birds and waterfowl and for migrating whooping cranes Grus americana accounting for 19% within the project area (6–27% among states). This model demonstrated a limited land base available for new development when accounting for regulations and concerns of a subset of societal interest groups. Additional interest groups likely will have different and competing concerns, further emphasizing the complexity of future land-use decisions as the available land base for development diminishes.
","language":"English","publisher":"U.S. Fish and Wildlife Service","doi":"10.3996/JFWM-21-036","usgsCitation":"Shaffer, J.A., Niemuth, N.D., Loesch, C.R., Derby, C.E., Pearse, A.T., Barnes, K.W., Shaffer, T.L., and Ryba, A.J., 2022, Limited land base and competing land uses force societal tradeoffs when siting energy development: Journal of Fish and Wildlife Management, v. 13, no. 1, p. 106-123, https://doi.org/10.3996/JFWM-21-036.","productDescription":"18 p.","startPage":"106","endPage":"123","ipdsId":"IP-122448","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":448664,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/jfwm-21-036","text":"Publisher Index Page"},{"id":405160,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","issue":"1","noUsgsAuthors":false,"publicationDate":"2022-02-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Shaffer, Jill A. 0000-0003-3172-0708 jshaffer@usgs.gov","orcid":"https://orcid.org/0000-0003-3172-0708","contributorId":3184,"corporation":false,"usgs":true,"family":"Shaffer","given":"Jill","email":"jshaffer@usgs.gov","middleInitial":"A.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":848973,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Niemuth, Neal D. 0009-0006-9637-5588","orcid":"https://orcid.org/0009-0006-9637-5588","contributorId":204334,"corporation":false,"usgs":false,"family":"Niemuth","given":"Neal","email":"","middleInitial":"D.","affiliations":[{"id":36919,"text":"U.S. Fish and Wildlife Service Habitat and Population Evaluation Team","active":true,"usgs":false}],"preferred":false,"id":848974,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Loesch, Charles R. 0000-0003-3090-1566","orcid":"https://orcid.org/0000-0003-3090-1566","contributorId":213437,"corporation":false,"usgs":false,"family":"Loesch","given":"Charles","email":"","middleInitial":"R.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":848975,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Derby, Clayton E.","contributorId":295253,"corporation":false,"usgs":false,"family":"Derby","given":"Clayton","email":"","middleInitial":"E.","affiliations":[{"id":38051,"text":"Western EcoSystems Technology, Inc.","active":true,"usgs":false}],"preferred":false,"id":848976,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pearse, Aaron T. 0000-0002-6137-1556 apearse@usgs.gov","orcid":"https://orcid.org/0000-0002-6137-1556","contributorId":1772,"corporation":false,"usgs":true,"family":"Pearse","given":"Aaron","email":"apearse@usgs.gov","middleInitial":"T.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":848977,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Barnes, Kevin W.","contributorId":295254,"corporation":false,"usgs":false,"family":"Barnes","given":"Kevin","email":"","middleInitial":"W.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":848978,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Shaffer, Terry L. 0000-0001-6950-8951 tshaffer@usgs.gov","orcid":"https://orcid.org/0000-0001-6950-8951","contributorId":3192,"corporation":false,"usgs":true,"family":"Shaffer","given":"Terry","email":"tshaffer@usgs.gov","middleInitial":"L.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":848979,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ryba, Adam J.","contributorId":204335,"corporation":false,"usgs":false,"family":"Ryba","given":"Adam","email":"","middleInitial":"J.","affiliations":[{"id":36919,"text":"U.S. Fish and Wildlife Service Habitat and Population Evaluation Team","active":true,"usgs":false}],"preferred":false,"id":848980,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70229031,"text":"ofr20221015 - 2022 - Floods of June 21–July 1, 2018, in the Floyd River and Little Sioux River Basins, northwestern Iowa","interactions":[],"lastModifiedDate":"2026-03-27T19:52:19.500576","indexId":"ofr20221015","displayToPublicDate":"2022-02-28T13:24:18","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-1015","displayTitle":"Floods of June 21–July 1, 2018, in the Floyd River and Little Sioux River Basins, Northwestern Iowa","title":"Floods of June 21–July 1, 2018, in the Floyd River and Little Sioux River Basins, northwestern Iowa","docAbstract":"The Floyd River and Little Sioux River Basins in northwestern Iowa flooded on June 21–July 1, 2018, after sustained rainfall on June 14–27, 2018. Within the Floyd River Basin, rainfall totals from June 14 to 21 preceding flooding were 3.01 inches (in.) at Le Mars, 4.50 in. at Orange City, and 7.44 in. at Sheldon. Within the Little Sioux River Basin, rainfall amounts for the 2-week period from June 14 to 27 preceding flooding were 11.29 in. at Lake Park, 12.95 in. at Milford, 5.56 in. at Spencer, 7.71 in. at Sioux Rapids, and 6.13 in. at Cherokee. Flooding in the Floyd River Basin resulted in a recorded maximum peak discharge of 14,300 cubic feet per second (ft3/s; annual exceedance probability [AEP] estimate between 4 and 10 percent) at the U.S. Geological Survey (USGS) streamgage Floyd River at Alton, Iowa (06600100), and a recorded maximum peak discharge of 9,180 ft3/s (AEP estimate greater than 10 percent) at the USGS streamgage Floyd River at James, Iowa (06600500). Flooding in the Little Sioux River Basin resulted in a recorded maximum peak discharge of 16,300 ft3/s (AEP estimate between 4 and 10 percent) at the USGS streamgage Little Sioux River at Linn Grove, Iowa (06605850), and maximum peak discharges of 18,700 ft3/s (AEP estimate greater than 10 percent) and 20,000 ft3/s (AEP estimate greater than 10 percent) were recorded at the USGS streamgages Little Sioux River at Correctionville, Iowa (06606600), and Little Sioux River near Turin, Iowa (06607500), respectively. High-water mark elevations were surveyed at 19 locations along the Floyd River and 22 locations along the Little Sioux River to develop 2 flood profiles: a 52.5-mile profile along the Floyd River from State Highway 3 at Le Mars to U.S. Highway 18 at Sheldon that includes the USGS streamgage Floyd River at Alton and a 101-mile profile along the Little Sioux River from U.S. Highway 59 at Cherokee to U.S. Highway 18 north of Spencer that includes the USGS streamgage Little Sioux River at Linn Grove.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221015","collaboration":"Prepared in cooperation with the Iowa Department of Transportation and the Iowa Highway Research Board (Project HR–140)","usgsCitation":"O’Shea, P.S., Wilson, J.L., Vegrzyn, J.C., and Barnes, K.K., 2022, Floods of June 21–July 1, 2018, in the Floyd River and Little Sioux River Basins, northwestern Iowa: U.S. Geological Survey Open-File Report 2022–1015, 35 p., https://doi.org/10.3133/ofr20221015.","productDescription":"Report: ix, 35 p.; 2 Data Releases; Dataset","numberOfPages":"48","onlineOnly":"N","ipdsId":"IP-111461","costCenters":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":396505,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1015/coverthb.jpg"},{"id":396510,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9V8NO0H","text":"USGS data release","linkHelpText":"Peak-flow frequency analysis for seven selected U.S. Geological Survey streamgages in the Floyd and Little Sioux River Basins, Iowa, based on data through water year 2019"},{"id":396508,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1015/images"},{"id":396507,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1015/ofr20221015.XML","size":"189 kB","linkFileType":{"id":8,"text":"xml"},"description":"OFR 2022–1015 XML"},{"id":396506,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1015/ofr20221015.pdf","text":"Report","size":"9.39 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022–1015"},{"id":501760,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112527.htm","linkFileType":{"id":5,"text":"html"}},{"id":396512,"rank":7,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":396511,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9W7VP64","text":"USGS data release","linkHelpText":"Peak-flow frequency analysis for three selected streamgages in the Cedar and Little Sioux River Basins, Iowa, based on data through water year 2019"}],"country":"United States","state":"Iowa","otherGeospatial":"Floyd River and Little Sioux River Basins","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96.6192626953125,\n 42.407234661551875\n ],\n [\n -95.701904296875,\n 42.407234661551875\n ],\n [\n -95.701904296875,\n 43.5326204268101\n ],\n [\n -96.6192626953125,\n 43.5326204268101\n ],\n [\n -96.6192626953125,\n 42.407234661551875\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
400 South Clinton Street, Suite 269
Iowa City, IA 52240
Treatment wetlands utilize various physical and biological processes to reduce levels of organic contaminants, metals, bacteria, and suspended solids. Silver nanoparticles (AgNPs) are one type of contaminant that can enter treatment wetlands and impact the overall treatment efficacy. Grazing by filter-feeding zooplankton, such as Daphnia magna, is critical to treatment wetland functioning; but the effects of AgNPs on zooplankton are not fully understood, especially at environmentally relevant concentrations. We characterized the bioaccumulation kinetics of dissolved and nanoparticulate (citrate-coated) 109Ag in D. magna exposed to environmentally relevant 109Ag concentrations (i.e., 0.2–23 nmol L−1 Ag) using a stable isotope as a tracer of Ag. Both aqueous and nanoparticulate forms of 109Ag were bioavailable to D. magna after exposure. Water chemistry affected 109Ag influx from 109AgNP but not from 109AgNO3. Silver retention was greater for citrate-coated 109AgNP than dissolved 109Ag, indicating a greater potential for bioaccumulation from nanoparticulate Ag. Feeding inhibition was observed at higher dietary 109Ag concentrations, which could lead to reduced treatment wetland performance. Our results illustrate the importance of using environmentally relevant concentrations and media compositions when predicting Ag bioaccumulation and provide insight into potential effects on filter feeders critical to the function of treatment wetlands.
","language":"English","publisher":"ACS Publications","doi":"10.1002/etc.5271","usgsCitation":"Lesser, E., Sheikh, F.N., Sikder, M., Croteau, M.N., Franklin, N., Baalousha, M., and Ismail, N.S., 2022, Water chemistry, exposure routes and metal forms determine the bioaccumulation dynamics of silver (ionic and nanoparticulate) in Daphnia magna: Environmental Toxicology and Chemistry, v. 41, no. 3, p. 726-738, https://doi.org/10.1002/etc.5271.","productDescription":"13 p.","startPage":"726","endPage":"738","ipdsId":"IP-131554","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":396548,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"41","issue":"3","noUsgsAuthors":false,"publicationDate":"2021-12-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Lesser, Emma","contributorId":286941,"corporation":false,"usgs":false,"family":"Lesser","given":"Emma","email":"","affiliations":[{"id":47946,"text":"Smith College","active":true,"usgs":false}],"preferred":false,"id":836370,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sheikh, Fatima Noor","contributorId":286942,"corporation":false,"usgs":false,"family":"Sheikh","given":"Fatima","email":"","middleInitial":"Noor","affiliations":[{"id":47946,"text":"Smith College","active":true,"usgs":false}],"preferred":false,"id":836371,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sikder, Mithun 0000-0002-6295-0939","orcid":"https://orcid.org/0000-0002-6295-0939","contributorId":255449,"corporation":false,"usgs":false,"family":"Sikder","given":"Mithun","email":"","affiliations":[{"id":37804,"text":"University of South Carolina","active":true,"usgs":false}],"preferred":false,"id":836372,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Croteau, Marie Noele 0000-0003-0346-3580 mcroteau@usgs.gov","orcid":"https://orcid.org/0000-0003-0346-3580","contributorId":895,"corporation":false,"usgs":true,"family":"Croteau","given":"Marie","email":"mcroteau@usgs.gov","middleInitial":"Noele","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":836373,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Franklin, Natasha","contributorId":286944,"corporation":false,"usgs":false,"family":"Franklin","given":"Natasha","email":"","affiliations":[],"preferred":false,"id":836374,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Baalousha, Mohammed","contributorId":239642,"corporation":false,"usgs":false,"family":"Baalousha","given":"Mohammed","affiliations":[{"id":37804,"text":"University of South Carolina","active":true,"usgs":false}],"preferred":false,"id":836375,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ismail, Niveen S.","contributorId":286947,"corporation":false,"usgs":false,"family":"Ismail","given":"Niveen","email":"","middleInitial":"S.","affiliations":[{"id":47946,"text":"Smith College","active":true,"usgs":false}],"preferred":false,"id":836376,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70230407,"text":"70230407 - 2022 - Rotenone use and subsequent prey loss lowers Osprey fledging rates via brood reduction","interactions":[],"lastModifiedDate":"2022-04-12T12:18:38.286639","indexId":"70230407","displayToPublicDate":"2022-02-28T07:16:26","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2442,"text":"Journal of Raptor Research","active":true,"publicationSubtype":{"id":10}},"title":"Rotenone use and subsequent prey loss lowers Osprey fledging rates via brood reduction","docAbstract":"Fisheries managers used the fish toxicant rotenone to eradicate an undesirable brown bullhead (Ameiurus nebulosus) population and all other fish species at Hyatt Reservoir, Oregon, on 12 October 1989. This 4-yr study (1988–1990, 1992) compared effects of that rotenone project on Ospreys (Pandion haliaetus) nesting at Hyatt Reservoir and nearby Howard Prairie Reservoir (untreated reference)—the latter a reservoir where both brown bullheads and hatchery-released rainbow trout (Oncorhynchus mykiss) prospered. Because Hyatt Reservoir was treated after Osprey fall migration in 1989, the first 2 yr (1988 and 1989) yielded pretreatment information: number of Osprey pairs was unchanged and reproductive rates were similar and consistent at the two reservoirs. Yearling fish (200–250 mm) were restocked at Hyatt Reservoir in the spring of 1990 and Ospreys returned each year following rotenone treatment, with no decline in the number of occupied or active nests. The negative effect of the rotenone treatment on Ospreys was short-term, resulting in reduced reproductive rates (young/occupied nest, young/active nest, and young/successful nest) during the first nesting season posttreatment, although hatching rates were not affected. Osprey dive success and prey delivery rates declined sharply in 1990, leading to competition for food among siblings and brood reduction. Osprey reproductive rates and prey delivery rates at Hyatt Reservoir in both 1990 and 1992 remained below the extremely high pretreatment rates, but within the range required for population stability. Serious adverse effects of the fish loss on Osprey reproduction were minimized by: (1) the delay of the rotenone application until after breeding season, (2) the restocking of the treated reservoir in the following spring with some larger (yearling) fish (though the timing was late), (3) the maintenance of a supplemental feeding program for a nesting pair of Bald Eagles (Haliaeetus leucocephalus), which minimized kleptoparasitism on Ospreys, and perhaps most important (4) the presence of nearby water bodies, where Osprey obtained some fish in the 1990 and 1992 breeding seasons.
High-resolution historical climate grids are readily available and frequently used as inputs for a wide range of regional management and risk assessments, including water supply, ecological processes, and as baseline for climate change impact studies that compare them to future projected conditions. Because historical gridded climates are produced using various methods, their portrayal of landscape conditions differ, which becomes a source of uncertainty when they are applied to subsequent analyses. Here we tested the range of values from five gridded climate datasets. We compared their values to observations from 1231 weather stations, first using each dataset’s native scale, and then after each was rescaled to 270-m resolution. We inputted the downscaled grids to a mechanistic hydrology model and assessed the spatial results of six hydrological variables across California, in 10 ecoregions and 11 large watersheds in the Sierra Nevada. PRISM was most accurate for precipitation, ClimateNA for maximum temperature, and TopoWx for minimum temperature. The single most accurate dataset overall was PRISM due to the best performance for precipitation and low air temperature errors. Hydrological differences ranged up to 70% of the average monthly streamflow with an average of 35% disagreement for all months derived from different historical climate maps. Large differences in minimum air temperature data produced differences in modeled actual evapotranspiration, snowpack, and streamflow. Areas with the highest variability in climate data, including the Sierra Nevada and Klamath Mountains ecoregions, also had the largest spread for snow water equivalent, recharge, and runoff.
","language":"English","publisher":"American Meteorological Society","doi":"10.1175/JHM-D-21-0045.1","usgsCitation":"Stern, M.A., Flint, L.E., Flint, A.L., Boynton, R.M., Stewart, J.A., Wright, J.W., and Thorne, J.H., 2022, Selecting the optimal fine-scale historical climate data for assessing current and future hydrological conditions: Journal of Hydrometeorology, v. 23, no. 3, p. 293-308, https://doi.org/10.1175/JHM-D-21-0045.1.","productDescription":"16 p.","startPage":"293","endPage":"308","ipdsId":"IP-127192","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":448670,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1175/jhm-d-21-0045.1","text":"Publisher Index Page"},{"id":414886,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"23","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Stern, Michelle A. 0000-0003-3030-7065 mstern@usgs.gov","orcid":"https://orcid.org/0000-0003-3030-7065","contributorId":4244,"corporation":false,"usgs":true,"family":"Stern","given":"Michelle","email":"mstern@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":867967,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Flint, Lorraine E. 0000-0002-7868-441X lflint@usgs.gov","orcid":"https://orcid.org/0000-0002-7868-441X","contributorId":1184,"corporation":false,"usgs":true,"family":"Flint","given":"Lorraine","email":"lflint@usgs.gov","middleInitial":"E.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":868014,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Flint, Alan L. 0000-0002-5118-751X aflint@usgs.gov","orcid":"https://orcid.org/0000-0002-5118-751X","contributorId":1492,"corporation":false,"usgs":true,"family":"Flint","given":"Alan","email":"aflint@usgs.gov","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":867968,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Boynton, Ryan M 0000-0002-3952-2573","orcid":"https://orcid.org/0000-0002-3952-2573","contributorId":303743,"corporation":false,"usgs":false,"family":"Boynton","given":"Ryan","email":"","middleInitial":"M","affiliations":[{"id":12711,"text":"UC Davis","active":true,"usgs":false}],"preferred":false,"id":867969,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stewart, Joseph A E","contributorId":247751,"corporation":false,"usgs":false,"family":"Stewart","given":"Joseph","email":"","middleInitial":"A E","affiliations":[{"id":49638,"text":"USGS WERC & UC Davis","active":true,"usgs":false}],"preferred":false,"id":867970,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wright, Jessica W","contributorId":303744,"corporation":false,"usgs":false,"family":"Wright","given":"Jessica","email":"","middleInitial":"W","affiliations":[{"id":36400,"text":"US Forest Service","active":true,"usgs":false}],"preferred":false,"id":867971,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Thorne, James H.","contributorId":139144,"corporation":false,"usgs":false,"family":"Thorne","given":"James","email":"","middleInitial":"H.","affiliations":[{"id":12659,"text":"U C Davis","active":true,"usgs":false}],"preferred":false,"id":867972,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70231893,"text":"70231893 - 2022 - Simple relationships between residence time and annual nutrient retention, export, and loading for estuaries","interactions":[],"lastModifiedDate":"2022-06-01T11:46:06.234257","indexId":"70231893","displayToPublicDate":"2022-02-27T06:42:37","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2620,"text":"Limnology and Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"Simple relationships between residence time and annual nutrient retention, export, and loading for estuaries","docAbstract":"Simple mathematical models are derived from mass balances for water and transported substance to provide insight into the relationships between import, export, transport, and internal removal for nonconservative substances in an estuary. Extending previous work, our models explicitly include water and substance inputs from the ocean and are expressed in terms of timescales (i.e., mean residence time and the timescale for net removal). Steady-state, timescale-based expressions for ratios of export to import, retention to import, and net export to loading, as well as for loading and annually averaged concentration, are provided. The net export:loading model explains the underlying mechanisms for a well-known empirical relationship between fractional net export and residence time derived by other authors. Although our simplified models are first-order approximations, the relative importance of physical and biochemical processes influencing export or retention of a substance can be assessed using mean residence time and the timescale for net removal. Assumptions employed in deriving the simplified models (e.g., well-mixed, dynamic steady state) may not be met for real estuaries. However, model application to Chesapeake Bay for 1985–2012 demonstrates that interannual variations in total nitrogen (TN) net export:loading can be evaluated, and annual nutrient loadings can be well estimated using numerically modeled time-varying mean residence time, observation-based mean concentration, freshwater inflow, and an appropriately estimated removal timescale. Our model shows that net fractional export of TN loading ranges from 0.3 to 0.5 over the 28-yr period. The models can be employed for other substances and water bodies if the underlying assumptions are applicable.
Hydropower production is one of the greatest threats to fluvial ecosystems and freshwater biodiversity. Now that we have entered the Anthropocene, there is an opportunity to reflect on what might constitute a ‘sustainable’ Anthropocene in the context of hydropower and riverine fish populations. Considering elements of existing practices that promote favorable social-ecological outcomes (i.e., ‘bright spots’) is timely given that there are plans to expand hydropower capacity in previously undammed rivers, intensify dam development in some of the world's largest river systems, and re-license existing facilities. We approach this from a pragmatic perspective: for the foreseeable future, hydropower will likely remain an important source of renewable electricity. To offer support for moving toward a more ‘sustainable’ Anthropocene, we provide syntheses of best practices during the siting, design, construction, operation, and compensation phases of hydropower development to minimize impacts on inland fish. For each phase, we offer positive examples (or what might be considered ‘bright spots’) pertaining to some of the approaches described within our syntheses, acknowledging that these projects may not be viewed as without ecological and (or) societal detriment by all stakeholders. Our findings underscore the importance of protecting critical habitat and free-flowing river reaches through careful site selection and basin-scale planning, infrastructure designs that minimize reservoir effects and facilitate safe passage of fish, construction of hydropower plants using best practices that minimize long-term damage, operating guidelines that mimic natural flow conditions, and compensation that is lasting, effective, inclusive, and locally relevant. Learning from these ‘bright spots’ may require engagement of diverse stakeholders, professionals, and governments at scales that extend well beyond a given site, river, or even basin. Indeed, environmental planning that integrates hydropower development into broader discussions of conserving regional biodiversity and ecosystem services will be of utmost importance.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.watbs.2022.100009","usgsCitation":"Twardek, W., Cowx, I., Lapointe, N.W., Paukert, C.P., Beard, T., Bennett, E., Browne, D., Carlson, A., Clarke, K.D., Hogan, Z., Lorenzen, K., Lynch, A., McIntyre, P.B., Pompeu, P.S., Rogers, M.W., Sakas, A., Taylor, W., Ward, T.D., Basher, Z., and Cooke, S., 2022, Bright spots for inland fish and fisheries to guide future hydropower development: Water Biology and Security, v. 1, no. 1, 100009, 19 p., https://doi.org/10.1016/j.watbs.2022.100009.","productDescription":"100009, 19 p.","ipdsId":"IP-134471","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":448679,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.watbs.2022.100009","text":"Publisher Index Page"},{"id":433405,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"1","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Twardek, William M.","contributorId":341625,"corporation":false,"usgs":false,"family":"Twardek","given":"William M.","affiliations":[{"id":17786,"text":"Carleton University","active":true,"usgs":false}],"preferred":false,"id":908713,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cowx, Ian G.","contributorId":341626,"corporation":false,"usgs":false,"family":"Cowx","given":"Ian G.","affiliations":[{"id":81763,"text":"Fisheries Institute at the University of Hull","active":true,"usgs":false}],"preferred":false,"id":908714,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lapointe, Nicolas W.R.","contributorId":341627,"corporation":false,"usgs":false,"family":"Lapointe","given":"Nicolas","email":"","middleInitial":"W.R.","affiliations":[{"id":54575,"text":"Canadian Wildlife Federation","active":true,"usgs":false}],"preferred":false,"id":908715,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Paukert, Craig P. 0000-0002-9369-8545","orcid":"https://orcid.org/0000-0002-9369-8545","contributorId":245524,"corporation":false,"usgs":true,"family":"Paukert","given":"Craig","middleInitial":"P.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":908712,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Beard, T. Douglas Jr. 0000-0003-2632-2350","orcid":"https://orcid.org/0000-0003-2632-2350","contributorId":245522,"corporation":false,"usgs":true,"family":"Beard","given":"T. Douglas","suffix":"Jr.","affiliations":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":908716,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bennett, Elena M.","contributorId":341628,"corporation":false,"usgs":false,"family":"Bennett","given":"Elena M.","affiliations":[{"id":6646,"text":"McGill University","active":true,"usgs":false}],"preferred":false,"id":908717,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Browne, David","contributorId":341629,"corporation":false,"usgs":false,"family":"Browne","given":"David","affiliations":[{"id":54575,"text":"Canadian Wildlife Federation","active":true,"usgs":false}],"preferred":false,"id":908718,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Carlson, Andrew K.","contributorId":341630,"corporation":false,"usgs":false,"family":"Carlson","given":"Andrew K.","affiliations":[{"id":6644,"text":"Princeton University","active":true,"usgs":false}],"preferred":false,"id":908719,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Clarke, Keith D.","contributorId":341631,"corporation":false,"usgs":false,"family":"Clarke","given":"Keith","email":"","middleInitial":"D.","affiliations":[{"id":81765,"text":"Ecological Sciences Section Science Branch","active":true,"usgs":false}],"preferred":false,"id":908720,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Hogan, Zeb","contributorId":341632,"corporation":false,"usgs":false,"family":"Hogan","given":"Zeb","affiliations":[{"id":37455,"text":"University of Nevada","active":true,"usgs":false}],"preferred":false,"id":908721,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Lorenzen, Kai","contributorId":169476,"corporation":false,"usgs":false,"family":"Lorenzen","given":"Kai","email":"","affiliations":[{"id":12557,"text":"University of Florida, FLREC","active":true,"usgs":false}],"preferred":false,"id":912022,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Lynch, Abigail 0000-0001-8449-8392","orcid":"https://orcid.org/0000-0001-8449-8392","contributorId":220490,"corporation":false,"usgs":true,"family":"Lynch","given":"Abigail","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":908722,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"McIntyre, Peter B.","contributorId":166828,"corporation":false,"usgs":false,"family":"McIntyre","given":"Peter","email":"","middleInitial":"B.","affiliations":[{"id":24540,"text":"Center for Limnology, University of Wisconsin, Madison, Wisconsin, 53706, USA.","active":true,"usgs":false}],"preferred":false,"id":912023,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Pompeu, Paulo S.","contributorId":203993,"corporation":false,"usgs":false,"family":"Pompeu","given":"Paulo","email":"","middleInitial":"S.","affiliations":[{"id":36790,"text":"Universidad Federal de Lavras, Department de Biologia","active":true,"usgs":false}],"preferred":false,"id":912024,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Rogers, Mark W. 0000-0001-7205-5623","orcid":"https://orcid.org/0000-0001-7205-5623","contributorId":245525,"corporation":false,"usgs":true,"family":"Rogers","given":"Mark","email":"","middleInitial":"W.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":908723,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Sakas, Alexis","contributorId":343802,"corporation":false,"usgs":false,"family":"Sakas","given":"Alexis","email":"","affiliations":[],"preferred":false,"id":912025,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Taylor, William W.","contributorId":49735,"corporation":false,"usgs":false,"family":"Taylor","given":"William W.","affiliations":[],"preferred":false,"id":912026,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Ward, Taylor D.","contributorId":343803,"corporation":false,"usgs":false,"family":"Ward","given":"Taylor","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":912027,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Basher, Zeenatul 0000-0002-6439-8324 zbasher@usgs.gov","orcid":"https://orcid.org/0000-0002-6439-8324","contributorId":48118,"corporation":false,"usgs":true,"family":"Basher","given":"Zeenatul","email":"zbasher@usgs.gov","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":912028,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Cooke, Steven J.","contributorId":340990,"corporation":false,"usgs":false,"family":"Cooke","given":"Steven J.","affiliations":[{"id":17786,"text":"Carleton University","active":true,"usgs":false}],"preferred":false,"id":912029,"contributorType":{"id":1,"text":"Authors"},"rank":20}]}} ,{"id":70262057,"text":"70262057 - 2022 - Taking a macroscale perspective to improve understanding of shallow lake total phosphorus and chlorophyll a","interactions":[],"lastModifiedDate":"2025-01-10T16:15:07.781209","indexId":"70262057","displayToPublicDate":"2022-02-25T10:05:23","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1919,"text":"Hydrobiologia","onlineIssn":"1573-5117","printIssn":"0018-8158","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Taking a macroscale perspective to improve understanding of shallow lake total phosphorus and chlorophyll a","title":"Taking a macroscale perspective to improve understanding of shallow lake total phosphorus and chlorophyll a","docAbstract":"We conducted a macroscale study of 2210 shallow lakes (mean depth ≤ 3 m or a maximum depth ≤ 5 m) in the Upper Midwestern and Northeastern USA. We asked the following: What are the patterns and drivers of shallow lake total phosphorus (TP), chlorophyll a (CHLa), and TP–CHLa relationships at the macroscale, how do these differ from those for 4360 non-shallow lakes, and do results differ by hydrologic connectivity class? Spatial patterns and Bayesian hierarchical models indicated that shallow lakes had higher TP and CHLa than non-shallow lakes, connected shallow lakes were more productive than unconnected shallow lakes, and there was regional variation in these patterns. Important predictors of TP and CHLa included lake-specific watershed:lake area ratio, forested land use/cover, and baseflow; unconnected lakes were more difficult to predict than connected lakes; and region-specific predictors were mostly unimportant. Shallow lake TP–CHLa relationships were less steep than for non-shallow lakes and these relationships varied regionally. Our results, combined with the facts that only 23% of lakes in the study extent have depth data and that shallow and unconnected lakes are undersampled, have important implications for estimates of lake contributions to global cycles that are based mainly on large (and deeper) lakes.
","language":"English","publisher":"Springer","doi":"10.1007/s10750-022-04811-1","usgsCitation":"Spence Cheruvelil, K., Webster, K., King, K., Poisson, A., and Wagner, T., 2022, Taking a macroscale perspective to improve understanding of shallow lake total phosphorus and chlorophyll a: Hydrobiologia, v. 849, p. 3663-3677, https://doi.org/10.1007/s10750-022-04811-1.","productDescription":"15 p.","startPage":"3663","endPage":"3677","ipdsId":"IP-130204","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":465993,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Connecticut, Illinois, Indiana, Iowa, Maine, Massachusetts, Michigan, Minnesota, Missouri, New Hampshire, New Jersey, New York, Ohio, Pennsylvania, Rhode Island, Vermont, 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\"}}]}","volume":"849","noUsgsAuthors":false,"publicationDate":"2022-02-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Spence Cheruvelil, Kendra","contributorId":348079,"corporation":false,"usgs":false,"family":"Spence Cheruvelil","given":"Kendra","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":922923,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Webster, Katherine","contributorId":348080,"corporation":false,"usgs":false,"family":"Webster","given":"Katherine","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":922924,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"King, Katelyn","contributorId":348081,"corporation":false,"usgs":false,"family":"King","given":"Katelyn","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":922925,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Poisson, Autumn C.","contributorId":348082,"corporation":false,"usgs":false,"family":"Poisson","given":"Autumn C.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":922926,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wagner, Tyler 0000-0003-1726-016X twagner@usgs.gov","orcid":"https://orcid.org/0000-0003-1726-016X","contributorId":1050,"corporation":false,"usgs":true,"family":"Wagner","given":"Tyler","email":"twagner@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":922922,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70229101,"text":"70229101 - 2022 - Lessons learned from 20 y of monitoring suburban development with distributed stormwater management in Clarksburg, Maryland, USA","interactions":[],"lastModifiedDate":"2022-09-15T14:05:49.817277","indexId":"70229101","displayToPublicDate":"2022-02-25T06:18:11","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1699,"text":"Freshwater Science","active":true,"publicationSubtype":{"id":10}},"title":"Lessons learned from 20 y of monitoring suburban development with distributed stormwater management in Clarksburg, Maryland, USA","docAbstract":"Urban development is a well-known stressor for stream ecosystems, presenting a challenge to managers tasked with mitigating its effects. For the past 20 y, streamflow, water quality, geomorphology, and benthic communities were monitored in 5 watersheds in Montgomery County, Maryland, USA. This study presents a synthesis of multiple studies of monitoring efforts in the study area and new analysis of more recent monitoring data to document the primary lessons learned from monitoring. The monitored watersheds include a forested control, an urban control with centralized stormwater management, and 3 suburban treatment watersheds featuring low-impact development and a high density of infiltration-focused stormwater facilities distributed across the watershed. Treatment watersheds were monitored before development, during construction, and after development. Monitoring was initiated to inform adaptive management of stormwater and impervious cover limits within the study area, with a focus on the impacts of distributed stormwater management. Results from our synthesis indicate that distributed stormwater management is advantageous compared with centralized stormwater management in numerous ways. Hydrologic benefits were greater with distributed stormwater infrastructure, demonstrating the ability to mitigate runoff volumes and peak flows and, for small storms, replicate predevelopment conditions. Baseflow temporarily increased during the construction phase in the treatment watersheds. Water-quality benefits were mixed, with declines in baseflow nitrate concentrations but limited changes to nitrate export and increases in specific conductance after development. Substantial topographic changes occurred during construction in the treatment watersheds, including changes within the riparian zone, despite riparian buffer protections. Ecological monitoring indicated that even though index of biotic integrity scores rebounded in some cases, sensitive benthic macroinvertebrate families did not fully recover in the treatment watersheds. Lessons learned from this synthesis highlight the importance of tracking multiple indicators of stream health and considering past land use and that more stormwater facilities distributed across the watershed is beneficial but cannot mitigate the effects of all urban stressors on aquatic ecosystems.
High fisheries production within estuaries is associated with coastal upwelling, tidal mixing, and land-based runoff facing increasing impacts from climate and human activities. Active river deltas receive large riverine inflows compared to inactive river deltas, providing contrasting estuaries to compare impacts of river inflow on estuarine nekton. We quantified nekton assemblages and stable isotopes (δ13C, δ15N) of commercially important blue crab Callinectes sapidus Rathbun, 1896 within an active and inactive delta in coastal Louisiana to explore the impacts of differing riverine inflow. Crustaceans dominated estuarine assemblages, differing only by season and not delta type, with summer and fall supporting highest densities. Fish density and assemblages differed by the interaction of season and delta due to differences during the 2019 record high spring river inflow. During this period, the active delta supported reduced fish densities and richness compared to the inactive delta. Nekton densities across deltas and seasons reflect a combination of species life history characteristics and habitat conditions. The high spring river discharge in 2019 impacted habitat availability (reduced presence of submerged aquatic vegetation), water conditions (decreased temperature and salinity), and potentially displaced nekton to unsampled habitat areas (i.e. interior marsh surface) within the active delta. While differences in nekton density and assemblages were only evident during the high spring river discharge, δ15N values of blue crabs were approximately 1.5 times higher in the active delta, potentially indicating more terrestrial influence. Understanding how altered inflow impacts environmental variables supporting estuarine nekton production remains critical for supporting management within these hydrologically managed regions.
","language":"English","publisher":"Inter-Research","doi":"10.3354/ab00748","usgsCitation":"Taylor, C.B., Nyman, J.A., and La Peyre, M., 2022, Nekton community dynamics within active and inactive deltas in a major river estuary: Potential implications for altered hydrology regimes: Aquatic Biology, v. 31, p. 1-18, https://doi.org/10.3354/ab00748.","productDescription":"18 p.","startPage":"1","endPage":"18","ipdsId":"IP-132543","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":448690,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/ab00748","text":"Publisher Index Page"},{"id":397188,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Mississippi River Delta Basin, Terrebonne Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.4337158203125,\n 29.16655229520015\n ],\n [\n -89.2694091796875,\n 29.16655229520015\n ],\n [\n -89.2694091796875,\n 30.088107753367257\n ],\n [\n -91.4337158203125,\n 30.088107753367257\n ],\n [\n -91.4337158203125,\n 29.16655229520015\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"31","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Taylor, Caleb B.","contributorId":288505,"corporation":false,"usgs":false,"family":"Taylor","given":"Caleb","email":"","middleInitial":"B.","affiliations":[{"id":61780,"text":"School of Renewable Natural Resources","active":true,"usgs":false}],"preferred":false,"id":838032,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nyman, John Andrew","contributorId":288506,"corporation":false,"usgs":false,"family":"Nyman","given":"John","email":"","middleInitial":"Andrew","affiliations":[{"id":61780,"text":"School of Renewable Natural Resources","active":true,"usgs":false}],"preferred":false,"id":838033,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"La Peyre, Megan K. 0000-0001-9936-2252","orcid":"https://orcid.org/0000-0001-9936-2252","contributorId":264343,"corporation":false,"usgs":true,"family":"La Peyre","given":"Megan K.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":838031,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70228909,"text":"ofr20221018 - 2022 - December 23, 2021, Red Hill synoptic groundwater-level survey, Hālawa area, O‘ahu, Hawai‘i","interactions":[],"lastModifiedDate":"2026-03-27T19:57:12.180137","indexId":"ofr20221018","displayToPublicDate":"2022-02-24T08:33:58","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-1018","displayTitle":"December 23, 2021, Red Hill Synoptic Groundwater-Level Survey, Hālawa Area, O‘ahu, Hawai‘i","title":"December 23, 2021, Red Hill synoptic groundwater-level survey, Hālawa area, O‘ahu, Hawai‘i","docAbstract":"On December 23, 2021, groundwater levels were measured in selected wells in the Hālawa area, O‘ahu, Hawai‘i, constituting a synoptic groundwater-level survey (shortened herein to “synoptic survey”) of the area. Groundwater levels were measured mainly from 9:00 a.m. to 12:00 p.m. (times listed in Hawai‘i standard time) and provide a snapshot of groundwater levels during the survey period. Following a reported fuel release that affected groundwater quality in the Red Hill area, several production wells were shut down in the weeks prior to the synoptic survey. These wells include the Red Hill Shaft (shut down on November 28, 2021) and the Hālawa Shaft (shut down on December 3, 2021, except for weekly, short-duration operations for water-quality sampling). Groundwater levels measured in wells during the synoptic survey ranged from 16.34 to 19.77 feet above mean sea level.
The groundwater levels collected during the multiagency synoptic survey contain uncertainty because of several potential sources of error associated with (1) the accuracy of the measuring tapes used, (2) the accuracy of the measuring-point altitude at the top of each well, (3) well plumbness and alignment, (4) human error, and (5) changing conditions during the survey period. Because of these potential sources of error, comparability of groundwater-level measurements may be affected. Some of the sources of uncertainty can be addressed and lead to improved accuracy and comparability of the groundwater levels. For example, uncertainty associated with the measuring-point altitudes can be addressed by resurveying measuring-point altitudes to a common vertical datum using consistent surveying methods.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221018","collaboration":"Prepared in cooperation with the U.S. Navy","usgsCitation":"Nakama, R.K., Mitchell, J.N., and Oki, D.S., 2022, December 23, 2021, Red Hill synoptic groundwater-level survey, Hālawa area, O‘ahu, Hawai‘i: U.S. Geological Survey Open-File Report 2022–1018, 10 p., https://doi.org/10.3133/ofr20221018.","productDescription":"Report: v, 10 p.; Data Release","numberOfPages":"10","onlineOnly":"Y","ipdsId":"IP-137125","costCenters":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"links":[{"id":396393,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1018/covrthb.jpg"},{"id":396394,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1018/ofr20221018.pdf","text":"Report","size":"8 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":401563,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20221048","text":"Open-File Report 2022-1048","description":"Nakama, R.K., Mitchell, J.N., and Oki, D.S., 2022, January 18, 2022, Red Hill synoptic groundwater-level survey, Hālawa area, O‘ahu, Hawai‘i: U.S. Geological Survey Open-File Report 2022–1048, 11 p., https://doi.org/10.3133/ofr20221048.","linkHelpText":"- January 18, 2022, Red Hill Synoptic Groundwater-Level Survey, Hālawa Area, O‘ahu, Hawai‘i"},{"id":396395,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS water data for the nation","description":"U.S. Geological Survey, 2022, USGS water data for the nation: U.S. Geological Survey National Water Information database, https://doi.org/10.5066/F7P55KJN"},{"id":501763,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112526.htm","linkFileType":{"id":5,"text":"html"}},{"id":404438,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20221069","text":"Open-File Report 2022-1069","description":"Nakama, R.K., Mitchell, J.N., and Oki, D.S., 2022, Groundwater-level monitoring from January 17 to March 3, 2022, Hālawa area, O‘ahu, Hawai‘i: U.S. Geological Survey Open-File Report 2022–1069, 29 p., https://doi.org/10.3133/ofr20221069.","linkHelpText":"- Groundwater-Level Monitoring from January 17 to March 3, 2022, Hālawa Area, O‘ahu, Hawai‘i"}],"country":"United States","state":"Hawaii","otherGeospatial":"O‘ahu, Hālawa area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -157.95867919921875,\n 21.332873489271286\n ],\n [\n -157.86117553710938,\n 21.332873489271286\n ],\n [\n -157.86117553710938,\n 21.410883719938866\n ],\n [\n -157.95867919921875,\n 21.410883719938866\n ],\n [\n -157.95867919921875,\n 21.332873489271286\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Pacific Islands Water Science Center
U.S. Geological Survey
Inouye Regional Center
1845 Wasp Blvd., B176
Honolulu, HI 96818