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The U.S. Geological Survey, in cooperation with the Missouri Department of Natural Resources, maintains a statewide group of stations known as the Ambient Water-Quality Monitoring Network, which includes selected streams and springs in Missouri. During water year 2021 (October 1, 2020, through September 30, 2021), the U.S. Geological Survey collected water-quality data at 72 stations: 70 Ambient Water-Quality Monitoring Network stations and 2 U.S. Geological Survey National Water Quality Network stations. Four of the stations have data from additional sampling completed in cooperation with the U.S. Army Corps of Engineers. Water-quality data provided in this report include dissolved oxygen, specific conductance, water temperature, suspended solids, suspended sediment, Escherichia coli bacteria, fecal coliform bacteria, dissolved nitrate plus nitrite as nitrogen, total phosphorus, dissolved and total recoverable lead and zinc, and selected pesticide compounds. Monitoring stations have been classified based on the physiographic province or primary land use in the drainage basin or based on the unique hydrologic characteristics of the waterbodies (springs, large rivers) monitored. A summary of hydrologic conditions, including peak streamflows, monthly mean streamflows, and 7-day low flows, also is provided for representative streamgages in the State.

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Director, Central Midwest Water Science Center
U.S. Geological Survey
1400 Independence Road
Rolla, MO 65401

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","tableOfContents":"","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2023-06-12","noUsgsAuthors":false,"publicationDate":"2023-06-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Markland, Kendra M. 0000-0002-0276-8684 kmarkland@usgs.gov","orcid":"https://orcid.org/0000-0002-0276-8684","contributorId":306212,"corporation":false,"usgs":true,"family":"Markland","given":"Kendra","email":"kmarkland@usgs.gov","middleInitial":"M.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":875084,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70247381,"text":"70247381 - 2023 - Attenuation of barium, strontium, cobalt, and nickel plumes formed during microbial iron-reduction in a crude-oil-contaminated aquifer","interactions":[],"lastModifiedDate":"2023-07-31T16:33:42.381524","indexId":"70247381","displayToPublicDate":"2023-06-09T11:11:16","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5615,"text":"ACS Earth and Space Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Attenuation of barium, strontium, cobalt, and nickel plumes formed during microbial iron-reduction in a crude-oil-contaminated aquifer","docAbstract":"

We assessed the spatial distribution of 35 elements in aquifer sediments and groundwater of a crude-oil-contaminated aquifer and show evidence of the dissolution of barium (Ba), strontium (Sr), cobalt (Co), and nickel (Ni) during hydrocarbon oxidation coupled to historic microbial Fe(III)-reduction near the oil. Trace element plumes occur in the crude-oil-contaminated aquifer, where 50% Co, 47% Ni, 24% Ba, and 15% Sr have been mobilized from the sediment near the oil into groundwater, resulting in dissolved masses >33, 18, three, and two times greater than estimated dissolved masses prior to contamination, respectively. Ba2+ and Ni2+ concentrations exceeded the World Health Organization’s drinking-water guidelines of 700 and 20 μg/L, respectively. Sediments attenuate trace element plumes in two geochemically distinct zones, resulting in <0.01% total trace element masses dissolved in groundwater, despite the substantial mobilization near the oil body. Geochemical modeling of the modern Fe(III)-reducing zone suggests trace elements are likely attenuated via coprecipitation with/without sorption on iron carbonate precipitates. In the suboxic transition zone at the leading edge of the plume, Fe(III)-hydroxides sorb Ba2+, Sr2+, Co2+, and Ni2+. This study emphasizes that slow but persistent biogeochemical activity can substantially alter aquifer chemistry over decadal timeframes, a phenomenon we term biogeochemical gradualism.

","language":"English","doi":"10.1021/acsearthspacechem.2c00387","usgsCitation":"Jones, K., Ziegler, B., Davis, A., and Cozzarelli, I.M., 2023, Attenuation of barium, strontium, cobalt, and nickel plumes formed during microbial iron-reduction in a crude-oil-contaminated aquifer: ACS Earth and Space Chemistry, v. 7, no. 7, p. 1322-1336, https://doi.org/10.1021/acsearthspacechem.2c00387.","productDescription":"15 p.","startPage":"1322","endPage":"1336","ipdsId":"IP-133249","costCenters":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":443133,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1021/acsearthspacechem.2c00387","text":"Publisher Index Page"},{"id":419447,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota","city":"Bemidji","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.98779296875,\n 47.416937456635445\n ],\n [\n -94.7900390625,\n 47.416937456635445\n ],\n [\n -94.7900390625,\n 47.537601245618134\n ],\n [\n -94.98779296875,\n 47.537601245618134\n ],\n [\n -94.98779296875,\n 47.416937456635445\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"7","issue":"7","noUsgsAuthors":false,"publicationDate":"2023-06-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Jones, Katherine","contributorId":317827,"corporation":false,"usgs":false,"family":"Jones","given":"Katherine","affiliations":[{"id":69164,"text":"Trinity University, San Antonio Texas; current address University of Texas, Austin","active":true,"usgs":false}],"preferred":false,"id":879383,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ziegler, Brady","contributorId":317828,"corporation":false,"usgs":false,"family":"Ziegler","given":"Brady","affiliations":[{"id":69165,"text":"Trinity University, San Antonio Texas","active":true,"usgs":false}],"preferred":false,"id":879384,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Davis, Audrey","contributorId":317829,"corporation":false,"usgs":false,"family":"Davis","given":"Audrey","email":"","affiliations":[{"id":69166,"text":"Trinity University, San Antonio, Texas","active":true,"usgs":false}],"preferred":false,"id":879385,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cozzarelli, Isabelle M. 0000-0002-5123-1007 icozzare@usgs.gov","orcid":"https://orcid.org/0000-0002-5123-1007","contributorId":1693,"corporation":false,"usgs":true,"family":"Cozzarelli","given":"Isabelle","email":"icozzare@usgs.gov","middleInitial":"M.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"preferred":true,"id":879386,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70247750,"text":"70247750 - 2023 - The relative importance of cisco (Coregonus artedi) in the diets of common loons (Gavia immer) among a set of cisco refuge lakes in Minnesota","interactions":[],"lastModifiedDate":"2023-11-07T15:30:25.34369","indexId":"70247750","displayToPublicDate":"2023-06-09T06:59:44","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1176,"text":"Canadian Journal of Zoology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"The relative importance of cisco (Coregonus artedi) in the diets of common loons (Gavia immer) among a set of cisco refuge lakes in Minnesota","title":"The relative importance of cisco (Coregonus artedi) in the diets of common loons (Gavia immer) among a set of cisco refuge lakes in Minnesota","docAbstract":"
Common loon (Gavia immer (Brünnich, 1764)) foraging patterns and the relative importance of cisco (Coregonus artedi Lesueur, 1818) in the diets of loons were evaluated for the Whitefish Chain of Lakes, a set of coldwater cisco refuge lakes in Minnesota, USA. Environmental DNA metabarcoding of loon fecal samples detected 15 fish species. Yellow perch (Perca flavescens (Mitchill, 1814)), mimic shiner (Notropis volucellus (Cope, 1865)), and cisco were the most prominent prey detected across the study lakes. We observed a shift in fish species consumed, with increases in detections of mimic shiner and cisco DNA among loon fecal samples collected in August and September. In some locations, suitable oxythermal habitat became restricted throughout the summer, forcing cisco into surface waters, which potentially increased their vulnerability to loon predation. Conversely, large foraging aggregations of loons were observed during late summer through fall at locations with ample oxythermal habitat and abundant cisco populations. We hypothesize that cisco were sought by loons as a high-calorie prey resource prior to migration. Conservation efforts directed at preserving water quality in important cisco refuge lakes are likely to benefit common loons through enhancement of both the forage base, for resident and migrating birds, and breeding habitat suitability.
","language":"English","publisher":"National Research Council of Canada","doi":"10.1139/cjz-2022-0189","usgsCitation":"Kenow, K.P., Lor, Y., Holbrook, B.V., Fara, L., Houdek, S.C., Tajjioui, T., Gray, B.R., and Jacobson, P.C., 2023, The relative importance of cisco (Coregonus artedi) in the diets of common loons (Gavia immer) among a set of cisco refuge lakes in Minnesota: Canadian Journal of Zoology, v. 101, no. 11, p. 1004-1016, https://doi.org/10.1139/cjz-2022-0189.","productDescription":"13 p.","startPage":"1004","endPage":"1016","ipdsId":"IP-146907","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":501000,"rank":3,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/1807/129019","text":"External Repository"},{"id":435290,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P96EXO3V","text":"USGS data release","linkHelpText":"Environmental DNA metabarcoding results of fish prey DNA in common loon (Gavia immer) fecal and cloacal swab samples from the Whitefish Chain of Lakes, Crow Wing County, Minnesota"},{"id":419878,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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brgray@usgs.gov","orcid":"https://orcid.org/0000-0001-7682-9550","contributorId":2615,"corporation":false,"usgs":true,"family":"Gray","given":"Brian","email":"brgray@usgs.gov","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":880270,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Jacobson, Peter C.","contributorId":177331,"corporation":false,"usgs":false,"family":"Jacobson","given":"Peter","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":880271,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70244312,"text":"70244312 - 2023 - Snow surface roughness across spatio-temporal scales","interactions":[],"lastModifiedDate":"2023-06-13T12:00:07.84478","indexId":"70244312","displayToPublicDate":"2023-06-09T06:51:58","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Snow surface roughness across spatio-temporal scales","docAbstract":"
The snow surface is at the interface between the atmosphere and Earth. The surface of the snowpack changes due to its interaction with precipitation, wind, humidity, short- and long-wave radiation, underlying terrain characteristics, and land cover. These connections create a dynamic snow surface that impacts the energy and mass balance of the snowpack, blowing snow potential, and other snowpack processes. Despite this, the snow surface is generally considered a constant parameter in many Earth system models. Data from the National Aeronautics and Space Administration (NASA) Cold Land Processes Experiment (CLPX) collected in 2002 and 2003 across northern Colorado were used to investigate the spatial and temporal variability of snow surface roughness. The random roughness (RR) and fractal dimension (D) metrics used in this investigation are well correlated. However, roughness is not correlated across scales, computed here from snow roughness boards at a millimeter resolution and airborne lidar at a meter resolution. Process scale differences were found based on land cover at each of the two measurement scales, as appraised through measurements in the forest and alpine.
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University","active":true,"usgs":false}],"preferred":false,"id":875338,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70244223,"text":"fs20233010 - 2023 - Availability of groundwater from the volcanic aquifers of the Hawaiian Islands","interactions":[],"lastModifiedDate":"2026-02-06T21:53:20.527216","indexId":"fs20233010","displayToPublicDate":"2023-06-08T09:02:46","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-3010","displayTitle":"Availability of Groundwater from the Volcanic Aquifers of the Hawaiian Islands","title":"Availability of groundwater from the volcanic aquifers of the Hawaiian Islands","docAbstract":"

The islands of Hawaiʻi were built by basaltic shield volcanoes in the Pacific Ocean. These volcanoes formed aquifers that supply hundreds of millions of gallons of fresh water per day to the islands’ residents and diverse industries. Groundwater discharge from the volcanic aquifers to streams and the coast also supports traditional practices and ecosystems. The aquifers' capacity to yield fresh groundwater is limited, however, by limitations placed on the consequences of groundwater withdrawal, such as water-table depression, rise of saltwater, and reduction of groundwater to streams, springs, and the ocean. The magnitude of these consequences will change if groundwater recharge changes as a result of climate and land-use changes. This fact sheet summarizes groundwater availability and its relation to the consequences of groundwater withdrawals in the volcanic aquifers of Hawaiʻi. This topic was addressed in detail in the Hawaiʻi Volcanic Aquifer Study (https://doi.org/10.3133/pp1876).

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\"}}]}","contact":"

Director,
Pacific Islands Water Science Center
U.S. Geological Survey
Inouye Regional Center
1845 Wasp Blvd., B176
Honolulu, HI 96818

","tableOfContents":"","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2023-06-08","noUsgsAuthors":false,"publicationDate":"2023-06-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Izuka, Scot K. 0000-0002-8758-9414 skizuka@usgs.gov","orcid":"https://orcid.org/0000-0002-8758-9414","contributorId":2645,"corporation":false,"usgs":true,"family":"Izuka","given":"Scot","email":"skizuka@usgs.gov","middleInitial":"K.","affiliations":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"preferred":true,"id":874922,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rotzoll, Kolja 0000-0002-5910-888X kolja@usgs.gov","orcid":"https://orcid.org/0000-0002-5910-888X","contributorId":3325,"corporation":false,"usgs":true,"family":"Rotzoll","given":"Kolja","email":"kolja@usgs.gov","affiliations":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"preferred":false,"id":874923,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70244231,"text":"70244231 - 2023 - Witnessing history: Comparison of a century of sedimentary and written records in a California protected area","interactions":[],"lastModifiedDate":"2023-06-08T13:53:37.834142","indexId":"70244231","displayToPublicDate":"2023-06-08T08:43:45","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3242,"text":"Regional Environmental Change","active":true,"publicationSubtype":{"id":10}},"title":"Witnessing history: Comparison of a century of sedimentary and written records in a California protected area","docAbstract":"

We use a combination of proxy records from a high-resolution analysis of sediments from Searsville Lake and adjacent Upper Lake Marsh and historical records to document over one and a half centuries of vegetation and socio-ecological change—relating to logging, agricultural land use change, dam construction, chemical applications, recreation, and other drivers—on the San Francisco Peninsula. A relatively open vegetation with minimal oak (Quercus) and coast redwood (Sequoia sempervirens) in the late 1850s reflects widespread logging and grazing during the nineteenth century. Forest and woodland expansion occurred in the early twentieth century, with forests composed of coast redwood and oak, among other taxa, as both logging and grazing declined. Invasive species include those associated with pasturage (Rumex, Plantago), landscape disturbance (Urtica, Amaranthaceae), planting for wood production and wind barriers (Eucalyptus), and agriculture. Agricultural species, including wheat, rye, and corn, were more common in the early twentieth century than subsequently. Wetland and aquatic pollen and fungal spores document a complex hydrological history, often associated with fluctuating water levels, application of algaecides, raising of Searsville Dam, and construction of a levee. By pairing the paleoecological and historical records of both lakes, we have been able to reconstruct the previously undocumented impacts of socio-ecological influences on this drainage, all of which overprinted known climate changes. Recognizing the ecological manifestations of these impacts puts into perspective the extent to which people have interacted with and transformed the environment in the transition into the Anthropocene.

","language":"English","publisher":"Springer","doi":"10.1007/s10113-023-02056-9","usgsCitation":"Anderson, R., Stegner, M.A., La Selle, S., Sherrod, B.L., Barnosky, A.D., and Hadly, E.A., 2023, Witnessing history: Comparison of a century of sedimentary and written records in a California protected area: Regional Environmental Change, v. 23, 65, 18 p., https://doi.org/10.1007/s10113-023-02056-9.","productDescription":"65, 18 p.","ipdsId":"IP-147736","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":443145,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10113-023-02056-9","text":"Publisher Index Page"},{"id":417945,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Jasper Ridge Biological Preserve","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.23418768300823,\n 37.3930404399613\n ],\n [\n -122.20397178645686,\n 37.40170883665597\n ],\n [\n -122.209679233583,\n 37.404509181302004\n ],\n [\n -122.21387588588198,\n 37.406109331254214\n ],\n [\n -122.21773680599699,\n 37.4091761898071\n ],\n [\n -122.21857613645665,\n 37.411576252406434\n ],\n [\n -122.22109412783595,\n 37.4118429212817\n ],\n [\n -122.22176559220381,\n 37.41424289844102\n ],\n [\n -122.24123805887044,\n 37.4121095892076\n ],\n [\n -122.2456025772612,\n 37.408376151853375\n ],\n [\n -122.2459383094448,\n 37.406776050314505\n ],\n [\n -122.24543471116908,\n 37.403842442069205\n ],\n [\n -122.24778483645659,\n 37.403842442069205\n ],\n [\n -122.24963136346803,\n 37.40264229649942\n ],\n [\n -122.2494634973759,\n 37.3998418820846\n ],\n [\n -122.23418768300823,\n 37.3930404399613\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"23","noUsgsAuthors":false,"publicationDate":"2023-04-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Anderson, R. Scott","contributorId":6983,"corporation":false,"usgs":false,"family":"Anderson","given":"R. Scott","affiliations":[{"id":7034,"text":"School of Earth Sciences and Environmental Sustainability at Northern Arizona University, in Flagstaff","active":true,"usgs":false}],"preferred":false,"id":874942,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stegner, M. Allison","contributorId":197658,"corporation":false,"usgs":false,"family":"Stegner","given":"M.","email":"","middleInitial":"Allison","affiliations":[],"preferred":false,"id":874943,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"La Selle, SeanPaul 0000-0002-4500-7885 slaselle@usgs.gov","orcid":"https://orcid.org/0000-0002-4500-7885","contributorId":181565,"corporation":false,"usgs":true,"family":"La Selle","given":"SeanPaul","email":"slaselle@usgs.gov","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":874944,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sherrod, Brian L. 0000-0002-4492-8631 bsherrod@usgs.gov","orcid":"https://orcid.org/0000-0002-4492-8631","contributorId":2834,"corporation":false,"usgs":true,"family":"Sherrod","given":"Brian","email":"bsherrod@usgs.gov","middleInitial":"L.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":874945,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Barnosky, Anthony D.","contributorId":197553,"corporation":false,"usgs":false,"family":"Barnosky","given":"Anthony","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":874946,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hadly, Elizabeth A.","contributorId":197554,"corporation":false,"usgs":false,"family":"Hadly","given":"Elizabeth","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":874947,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70244225,"text":"70244225 - 2023 - Multi-scale relationships in thermal limits within and between two cold-water frog species uncover different trends in physiological vulnerability","interactions":[],"lastModifiedDate":"2023-06-28T15:27:18.499421","indexId":"70244225","displayToPublicDate":"2023-06-08T08:38:32","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1696,"text":"Freshwater Biology","active":true,"publicationSubtype":{"id":10}},"title":"Multi-scale relationships in thermal limits within and between two cold-water frog species uncover different trends in physiological vulnerability","docAbstract":"

1. Critical thermal limits represent an important component of an organism's capacity to cope with future temperature changes. Understanding the drivers of variation in these traits may uncover patterns in physiological vulnerability to climate change. Local temperature extremes have emerged as a major driver of thermal limits, although their effects can be mediated by the exploitation of fine-scale spatial variation in temperature through behavioural thermoregulation.

2. Here, we investigated thermal limits along elevation gradients within and between two cold-water frog species (Ascaphus spp.), one with a coastal distribution (A. truei) and the other with a continental range (A. montanus). We quantified thermal limits for over 700 tadpoles, representing multiple populations from each species. We combined local temporal and fine-scale spatial temperature data to quantify local thermal landscapes (i.e., thermalscapes), including the opportunity for behavioural thermoregulation.

3. Lower thermal limits for either species could not be reached experimentally without the water freezing, suggesting that cold tolerance is <0.3°C. By contrast, upper thermal limits varied among populations, but this variation only reflected local temperature extremes in A. montanus, perhaps as a consequence of the greater variation in stream temperatures across its range. Lastly, we found minimal fine-scale spatial variability in temperature, suggesting limited opportunity for behavioural thermoregulation and thus increased vulnerability to warming for all populations.

4. By quantifying local thermalscapes, we uncovered different trends in the relative vulnerability of populations across elevation for each species. In A. truei, physiological vulnerability decreased with elevation, whereas in A. montanus, all populations were equally physiologically vulnerable. These results highlight how similar environments can differentially shape physiological tolerance and patterns of vulnerability of species, and in turn impact their vulnerability to future warming.

","language":"English","publisher":"Wiley","doi":"10.1111/fwb.14102","usgsCitation":"Cicchino, A.S., Shah, A.A., Forester, B.R., Dunham, J., Ghalambor, C.K., and Funk, W., 2023, Multi-scale relationships in thermal limits within and between two cold-water frog species uncover different trends in physiological vulnerability: Freshwater Biology, v. 68, no. 7, p. 1267-1278, https://doi.org/10.1111/fwb.14102.","productDescription":"12 p.","startPage":"1267","endPage":"1278","ipdsId":"IP-144903","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":443148,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/fwb.14102","text":"Publisher Index Page"},{"id":417941,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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Brenna R.","contributorId":261215,"corporation":false,"usgs":false,"family":"Forester","given":"Brenna","email":"","middleInitial":"R.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":874927,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dunham, Jason 0000-0002-6268-0633","orcid":"https://orcid.org/0000-0002-6268-0633","contributorId":220078,"corporation":false,"usgs":true,"family":"Dunham","given":"Jason","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":874928,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ghalambor, Cameron K.","contributorId":93722,"corporation":false,"usgs":false,"family":"Ghalambor","given":"Cameron","email":"","middleInitial":"K.","affiliations":[{"id":6998,"text":"Department of Biology, Colorado State 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Chris 0000-0002-9254-6718","orcid":"https://orcid.org/0000-0002-9254-6718","contributorId":189580,"corporation":false,"usgs":false,"family":"Funk","given":"W. Chris","affiliations":[],"preferred":false,"id":874930,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70244238,"text":"70244238 - 2023 - The influence of large woody debris on post-wildfire debris flow sediment storage","interactions":[],"lastModifiedDate":"2023-06-08T13:08:51.42943","indexId":"70244238","displayToPublicDate":"2023-06-08T08:00:03","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2824,"text":"Natural Hazards and Earth System Sciences","active":true,"publicationSubtype":{"id":10}},"title":"The influence of large woody debris on post-wildfire debris flow sediment storage","docAbstract":"Debris flows transport large quantities of water and granular material, such as sediment and wood, and this mixture can have devastating impacts on life and infrastructure. The proportion of large woody debris (LWD) incorporated into debris flows can be enhanced in forested areas recently burned by wildfire, because wood recruitment into channels accelerates in burned forests. In this study, we explored how LWD transported in post-wildfire debris flows acts to retain sediment within small headwater channels. We found that the largest amount of debris flow sediment is stored in channel reaches with a ratio of LWD length to channel width between 0.25 and 1. Moreover, the largest debris flow deposits forced by LWD were found in low-angle channel reaches. We examined two models for debris flow volume estimation: (1) the current volume prediction model used in U.S. Geological Survey debris flow hazard assessments, and (2) a regional model developed to predict the sediment yield associated with debris-laden flows. We found that the regional model better matched the magnitude of the observed sediment at the terminal fan, suggesting the utility of regionally calibrated parameters for debris flow volume prediction. However, large wood created sediment storage upstream of the terminal fan, and this volume was of the same magnitude as the total volume at the terminal fans. Finally, we demonstrate a method for estimating debris flow velocity based on estimates of the critical velocity required to break wood, which can be used in future field studies to estimate minimum debris flow velocity values.","language":"English","publisher":"European Geosciences Union","doi":"10.5194/nhess-23-2075-2023","usgsCitation":"Rengers, F.K., McGuire, L.A., Barnhart, K.R., Youberg, A., Cadol, D., Gorr, A., Hoch, O.J., Beers, R., and Kean, J.W., 2023, The influence of large woody debris on post-wildfire debris flow sediment storage: Natural Hazards and Earth System Sciences, v. 23, no. 6, p. 2075-2088, https://doi.org/10.5194/nhess-23-2075-2023.","productDescription":"14 p.","startPage":"2075","endPage":"2088","ipdsId":"IP-145338","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":443153,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index 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0000-0002-4408-8548","orcid":"https://orcid.org/0000-0002-4408-8548","contributorId":306176,"corporation":false,"usgs":false,"family":"Cadol","given":"Daniel","email":"","affiliations":[{"id":7026,"text":"New Mexico Tech","active":true,"usgs":false}],"preferred":false,"id":874968,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gorr, Alexander 0000-0002-3239-7773","orcid":"https://orcid.org/0000-0002-3239-7773","contributorId":294389,"corporation":false,"usgs":false,"family":"Gorr","given":"Alexander","email":"","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":874969,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hoch, Olivia J. 0000-0002-1327-7100","orcid":"https://orcid.org/0000-0002-1327-7100","contributorId":306177,"corporation":false,"usgs":true,"family":"Hoch","given":"Olivia","email":"","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science 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Modeling System (PRMS) to simulate the streamflows and water balance of the Red River Basin, 1980–2016","interactions":[],"lastModifiedDate":"2026-02-23T19:28:22.014039","indexId":"sir20225105","displayToPublicDate":"2023-06-08T08:00:00","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-5105","displayTitle":"Application of the Precipitation-Runoff Modeling System (PRMS) to Simulate the Streamflows and Water Balance of the Red River Basin, 1980–2016","title":"Application of the Precipitation-Runoff Modeling System (PRMS) to simulate the streamflows and water balance of the Red River Basin, 1980–2016","docAbstract":"

The Precipitation-Runoff Modeling System (PRMS) was used to develop and calibrate a streamflow and water balance model for the Red River Basin as part of the U.S. Geological Survey National Water Census, a research effort focused on developing innovative water accounting tools and conducting assessments of water use and availability at regional and national spatial scales. The PRMS is a deterministic model that simulates the effects of climate, land cover, and water use on watershed hydrology on the basis of physical processes and spatial attributes of the watershed. The model was used to estimate streamflow at daily and monthly temporal scales for the 1980–2016 period and to evaluate the impacts of natural and anthropogenic influences on streamflow and water budget components.

Sixty-three percent of streamgages were calibrated successfully for the monthly time step and 43 percent of streamgages were successfully calibrated for the daily time step. Some of the challenges of calibrating streamgages included estimating low amounts of streamflow in dry areas of the basin and accurately representing watershed characteristics related to evapotranspiration in the basin, among other factors. The model estimated streamflow with some accuracy for 42 percent and 29 percent of the 73 streamgages used to evaluate the model at monthly and daily time steps, respectively. Relative to no-water-use conditions, water use increased streamflow volumes (that is, return flow from reservoir releases) the most on the main stem of the Red River, the North Fork of the Red River, and the Ouachita River. Water withdrawal decreased streamflow volumes most in the Red River near the outlet of the basin and in Caney Creek. Streamflow volumes on the North Fork of the Red River changed most as a result of water use. The Red River Basin PRMS model provided estimates of streamflow that were limited in their accuracy by (1) the availability of accurate water-use data; (2) the coarse resolution of spatial parameters (such as those for impervious area or plant canopy), which leads to the homogenization of physical features in small watersheds in the model domain; and (3) the accuracy of spatial patterns of precipitation distribution across the model domain. Improvements in the quality and quantity of available water-use data and finer resolution spatial parameter and climate data could lead to the development of better-informed models in the future that are capable of making more accurate estimates of streamflow, because they are more representative of physical and hydrologic conditions in the Red River Basin. 

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225105","issn":"2328-0328","programNote":"Water Availability and Use Science Program","usgsCitation":"Roland, V.L., II, 2023, Application of the Precipitation-Runoff Modeling System (PRMS) to simulate the streamflows and water balance of the Red River Basin, 1980–2016: U.S. Geological Survey Scientific Investigations Report 2022–5105, 37 p., https://doi.org/10.3133/sir20225105.","productDescription":"Report: viii, 37 p.; Data Release","numberOfPages":"50","onlineOnly":"Y","ipdsId":"IP-091577","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":417622,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5105/coverthb.jpg"},{"id":500454,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114764.htm","linkFileType":{"id":5,"text":"html"}},{"id":417790,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ZI5IVX","text":"USGS data release—Model input and output from Precipitation Runoff Modeling System (PRMS) simulation of the Red River Basin 1981–2016"},{"id":417789,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5105/images/"},{"id":417921,"rank":4,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/sir20225105/full","linkFileType":{"id":5,"text":"html"},"description":"SIR 2022-5105 HTML"},{"id":417787,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5105/sir20225105.XML","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2022-5105 XML"},{"id":417786,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5105/sir20225105.pdf","size":"16.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5105"}],"country":"United States","state":"Arkansas, Louisiana, Texas, Oklahoma","otherGeospatial":"Red River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -103.48949921760368,\n 36.13692959102481\n ],\n [\n -103.48949921760368,\n 31.242144043970583\n ],\n [\n -89.91622130795812,\n 31.242144043970583\n ],\n [\n -89.91622130795812,\n 36.13692959102481\n ],\n [\n -103.48949921760368,\n 36.13692959102481\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"

For more information about this publication, contact

Director, Lower Mississippi-Gulf Water Science Center
U.S. Geological Survey
640 Grassmere Park, Suite 100
Nashville, TN 37211 
https://www.usgs.gov/centers/lmg-water/

Contact Pubs Warehouse
","tableOfContents":"","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2023-06-08","noUsgsAuthors":false,"publicationDate":"2023-06-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Roland, Victor L. II 0000-0002-6260-9351 vroland@usgs.gov","orcid":"https://orcid.org/0000-0002-6260-9351","contributorId":212248,"corporation":false,"usgs":true,"family":"Roland","given":"Victor","suffix":"II","email":"vroland@usgs.gov","middleInitial":"L.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":874361,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70244268,"text":"70244268 - 2023 - Modeled predictions of human-associated and fecal-indicator bacteria concentrations and loadings in the Menomonee River, Wisconsin using in-situ optical sensors","interactions":[],"lastModifiedDate":"2023-06-12T11:31:14.028063","indexId":"70244268","displayToPublicDate":"2023-06-08T06:25:18","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Modeled predictions of human-associated and fecal-indicator bacteria concentrations and loadings in the Menomonee River, Wisconsin using in-situ optical sensors","docAbstract":"

Human sewage contamination of waterways is a major issue in the United States and throughout the world. Models were developed for estimation of two human-associated fecal-indicator and three general fecal-indicator bacteria (HIB and FIB) using in situ optical field-sensor data for estimating concentrations and loads of HIB and FIB and the extent of sewage contamination in the Menomonee River in Milwaukee, Wisconsin. Three commercially available optical sensor platforms were installed into an unfiltered custom-designed flow-through system along with a refrigerated automatic sampler at the Menomonee River sampling location. Ten-minute optical sensor measurements were made from November 2017 to December 2018 along with the collection of 153 flow-weighted discrete water samples (samples) for HIB, FIB, dissolved organic carbon (DOC), and optical properties of water. Of those 153 samples, 119 samples were from event-runoff periods, and 34 were collected during low-flow periods. Of the 119 event-runoff samples, 43 samples were from event-runoff combined sewer overflow (CSO) influenced periods (event-CSO periods). Models included optical sensor measurements as explanatory variables with a seasonal variable as an interaction term. In some cases, separate models for event-CSO periods and non CSO-periods generally improved model performance, as compared to using all the data combined for estimates of FIB and HIB. Therefore, the CSO and non-CSO models were used in final estimations for CSO and non-CSO time periods, respectively. Estimated continuous concentrations for all bacteria markers varied over six orders of magnitude during the study period. The greatest concentrations, loads, and proportion of sewage contamination occurred during event-runoff and event-CSO periods. Comparison to water quality standards and microbial risk assessment benchmarks indicated that estimated bacteria levels exceeded recreational water quality criteria between 34 and 96% of the entire monitoring period, highlighting the benefits of high-frequency monitoring compared to traditional grab sample collection. The application of optical sensors for estimation of HIB and FIB markers provided a thorough assessment of bacterial presence and human health risk in the Menomonee River.

","language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pone.0286851","usgsCitation":"Lenaker, P.L., Corsi, S., DeCicco, L.A., Olds, H., Dila, D.K., Danz, M., McLellan, S.L., and Rutter, T., 2023, Modeled predictions of human-associated and fecal-indicator bacteria concentrations and loadings in the Menomonee River, Wisconsin using in-situ optical sensors: PLoS ONE, v. 18, no. 6, e0286851, 25 p., https://doi.org/10.1371/journal.pone.0286851.","productDescription":"e0286851, 25 p.","ipdsId":"IP-141458","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":443160,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0286851","text":"Publisher Index Page"},{"id":417996,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","county":"Milwaukee","otherGeospatial":"Menomonee River watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -88.24750205696151,\n 43.32105916069608\n ],\n [\n -88.24750205696151,\n 43.0287481129935\n ],\n [\n -87.94276220098,\n 43.0287481129935\n ],\n [\n -87.94276220098,\n 43.32105916069608\n ],\n [\n -88.24750205696151,\n 43.32105916069608\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"18","issue":"6","noUsgsAuthors":false,"publicationDate":"2023-06-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Lenaker, Peter L. 0000-0002-9469-6285 plenaker@usgs.gov","orcid":"https://orcid.org/0000-0002-9469-6285","contributorId":5572,"corporation":false,"usgs":true,"family":"Lenaker","given":"Peter","email":"plenaker@usgs.gov","middleInitial":"L.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":875095,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Corsi, Steven R. 0000-0003-0583-5536 srcorsi@usgs.gov","orcid":"https://orcid.org/0000-0003-0583-5536","contributorId":172002,"corporation":false,"usgs":true,"family":"Corsi","given":"Steven R.","email":"srcorsi@usgs.gov","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":875096,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DeCicco, Laura A. 0000-0002-3915-9487 ldecicco@usgs.gov","orcid":"https://orcid.org/0000-0002-3915-9487","contributorId":174716,"corporation":false,"usgs":true,"family":"DeCicco","given":"Laura","email":"ldecicco@usgs.gov","middleInitial":"A.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":5054,"text":"Office of Water Information","active":true,"usgs":true},{"id":160,"text":"Center for Integrated Data Analytics","active":false,"usgs":true}],"preferred":true,"id":875097,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Olds, Hayley T. 0000-0002-6701-6459 htemplar@usgs.gov","orcid":"https://orcid.org/0000-0002-6701-6459","contributorId":5002,"corporation":false,"usgs":true,"family":"Olds","given":"Hayley T.","email":"htemplar@usgs.gov","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":false,"id":875098,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dila, Debra K.","contributorId":306214,"corporation":false,"usgs":false,"family":"Dila","given":"Debra","email":"","middleInitial":"K.","affiliations":[{"id":13324,"text":"University of Wisconsin Milwaukee","active":true,"usgs":false}],"preferred":false,"id":875099,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Danz, Mari 0000-0002-4716-0170 medanz@usgs.gov","orcid":"https://orcid.org/0000-0002-4716-0170","contributorId":219227,"corporation":false,"usgs":true,"family":"Danz","given":"Mari","email":"medanz@usgs.gov","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":875100,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McLellan, Sandra L. 0000-0003-3283-1151","orcid":"https://orcid.org/0000-0003-3283-1151","contributorId":210968,"corporation":false,"usgs":false,"family":"McLellan","given":"Sandra","email":"","middleInitial":"L.","affiliations":[{"id":7200,"text":"University of Wisconsin-Milwaukee","active":true,"usgs":false}],"preferred":false,"id":875101,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Rutter, Troy D. 0000-0001-5130-204X","orcid":"https://orcid.org/0000-0001-5130-204X","contributorId":306215,"corporation":false,"usgs":true,"family":"Rutter","given":"Troy D.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":875102,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70244183,"text":"sir20235048 - 2023 - Historical changes to channel planform and bed elevations downstream from dams along Fall Creek and Middle Fork Willamette River, Oregon, 1926–2016","interactions":[],"lastModifiedDate":"2026-03-09T16:05:13.977815","indexId":"sir20235048","displayToPublicDate":"2023-06-07T12:32:35","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-5048","displayTitle":"Historical Changes to Channel Planform and Bed Elevations Downstream from Dams Along Fall Creek and Middle Fork Willamette River, Oregon, 1926–2016","title":"Historical changes to channel planform and bed elevations downstream from dams along Fall Creek and Middle Fork Willamette River, Oregon, 1926–2016","docAbstract":"

Operation of large, multipurpose dams within the Middle Fork Willamette River Basin, Oregon, including the Fall Creek sub-basin, have disrupted natural streamflow and sediment transport regimes and fish passage along the river corridors. Documenting channel morphology, including channel planform, landforms, vegetation cover, and river channel elevations at multiple points in time spanning the 20th and early 21st centuries, is useful for characterizing net changes occurring in response to construction and operation of these dams. The U.S. Geological Survey assessed historical channel changes that occurred within the past century in response to the construction and operation of flood-control dams by evaluating planimetric datasets (from 1926 plan and profile surveys and 1936 and 2016 aerial photographs) and elevation datasets (from 1926 plan and profile surveys and 2015 light detection and ranging [lidar]). This study specifically focuses on the lower 27.3 kilometers (km) of the Middle Fork Willamette River and the lower 11.5 km of Fall Creek, or the reaches downstream from the U.S. Army Corps of Engineers Dexter Dam and Fall Creek Dam, to the confluence with Coast Fork Willamette River. Altogether, compilation and evaluation of datasets for Fall Creek and the Middle Fork Willamette River downstream from the dams provide a foundation for understanding:

  1. channel morphology and patterns of geomorphic stability prior to dam construction in 1926 and 1936;
  2. channel morphology and patterns of lateral and vertical stability of the early 21st century that reflect present-day (post-dam) streamflow and sediment regimes as of 2015–16; and
  3. geomorphic transformations of the river corridors in the decades following dam construction, including changes in planform and bed elevation (determined from water-surface elevations).

Findings from this study can be used to provide historical and geomorphic context for geomorphic responses to deep reservoir drawdowns on Fall Creek Lake that mobilize reservoir sediment downstream and informing other restoration and river-management activities; this report summarizes one component of a larger research effort to document the magnitude and spatial distribution of geomorphic responses to sediment releases from draining Fall Creek Lake.

As of 2016, the modern Fall Creek flows through a narrow, semi-alluvial channel that efficiently conveys water and sediment at typical streamflows downstream from Fall Creek Dam. This channel planform, including the positions and distributions of bars and secondary water features (side channels, alcoves, and ponds), generally reflects pre-dam conditions in 1936, suggesting relatively modest morphological adjustments resulted from reductions in sediment supply and alterations to peak streamflow after dam construction. The most substantial morphologic change detected over this period was a reduction in unvegetated gravel bars.

As of 2016, the modern Middle Fork Willamette River is a large, gravel-bed river that, despite substantial transformations in channel morphology and reduction in lateral dynamism following the construction of multiple upstream dams, remains a dominantly alluvial river. Prior to dam construction in 1926 and 1936, the reaches of the Middle Fork Willamette River downstream from Dexter Dam were laterally active with multi-thread and single-thread channels flanked by large, shifting gravel bars. Since streamflow regulation and other channel modifications in the mid-20th century, these reaches have become less laterally active and encompass a narrower floodplain corridor as abundant former gravel bars were converted to low-elevation floodplains colonized by young, dense forests. The Middle Fork Willamette River downstream from Dexter Dam has remained mostly vertically stable between 1926 and 2015, although localized segments possibly decreased in elevation as much as 2.3 meters.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235048","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Keith, M.K., Wallick, J.R., Gordon, G.W., and Bervid, H.D., 2023, Historical changes to channel planform and bed elevations downstream from dams along Fall Creek and Middle Fork Willamette River, Oregon, 1926–2016: U.S. Geological Survey Scientific Investigations Report 2023–5048, 34 p., https://doi.org/10.3133/sir20235048.","productDescription":"Report: viii, 34 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-136568","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":500925,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114772.htm","linkFileType":{"id":5,"text":"html"}},{"id":417882,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5048/sir20235048.XML"},{"id":417881,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5048/images"},{"id":417880,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9THIZD6","text":"USGS data release","description":"USGS data release.","linkHelpText":"Fall Creek and Middle Fork Willamette Geomorphic Mapping Geodatabase"},{"id":417877,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5048/coverthb.jpg"},{"id":417878,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5048/sir20235048.pdf","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Oregon","otherGeospatial":"Fall Creek, Middle Fork Willamette River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -123,\n 44\n ],\n [\n -123,\n 43.916667\n ],\n [\n -122.75,\n 43.916667\n ],\n [\n -122.75,\n 44\n ],\n [\n -123,\n 44\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"

Director, Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201

","tableOfContents":"","publishedDate":"2023-06-07","noUsgsAuthors":false,"publicationDate":"2023-06-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Keith, Mackenzie K. 0000-0002-7239-0576 mkeith@usgs.gov","orcid":"https://orcid.org/0000-0002-7239-0576","contributorId":196963,"corporation":false,"usgs":true,"family":"Keith","given":"Mackenzie","email":"mkeith@usgs.gov","middleInitial":"K.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":874789,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wallick, J. Rose 0000-0002-9392-272X rosewall@usgs.gov","orcid":"https://orcid.org/0000-0002-9392-272X","contributorId":3583,"corporation":false,"usgs":true,"family":"Wallick","given":"J. Rose","email":"rosewall@usgs.gov","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":874790,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gordon, Gabriel W. 0000-0001-6866-0302 ggordon@usgs.gov","orcid":"https://orcid.org/0000-0001-6866-0302","contributorId":269773,"corporation":false,"usgs":true,"family":"Gordon","given":"Gabriel W.","email":"ggordon@usgs.gov","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":874791,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bervid, Heather D. 0000-0001-9632-885X","orcid":"https://orcid.org/0000-0001-9632-885X","contributorId":176732,"corporation":false,"usgs":true,"family":"Bervid","given":"Heather","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":874792,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70247447,"text":"70247447 - 2023 - Quantifying ecosystem states and state transitions of the Upper Mississippi River System using topological data analysis","interactions":[],"lastModifiedDate":"2023-08-08T11:54:18.370372","indexId":"70247447","displayToPublicDate":"2023-06-07T06:52:13","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5727,"text":"PLOS Computational Biology","active":true,"publicationSubtype":{"id":10}},"title":"Quantifying ecosystem states and state transitions of the Upper Mississippi River System using topological data analysis","docAbstract":"

Aquatic systems worldwide can exist in multiple ecosystem states (i.e., a recurring collection of biological and chemical attributes), and effectively characterizing multidimensionality will aid protection of desirable states and guide rehabilitation. The Upper Mississippi River System is composed of a large floodplain river system spanning 2200 km and multiple federal, state, tribal and local governmental units. Multiple ecosystem states may occur within the system, and characterization of the variables that define these ecosystem states could guide river rehabilitation. We coupled a long-term (30-year) highly dimensional water quality monitoring dataset with multiple topological data analysis (TDA) techniques to classify ecosystem states, identify state variables, and detect state transitions over 30 years in the river to guide conservation. Across the entire system, TDA identified five ecosystem states. State 1 was characterized by exceptionally clear, clean, and cold-water conditions typical of winter (i.e., a clear-water state); State 2 had the greatest range of environmental conditions and contained most the data (i.e., a status-quo state); and States 3, 4, and 5 had extremely high concentrations of suspended solids (i.e., turbid states, with State 5 as the most turbid). The TDA mapped clear patterns of the ecosystem states across several riverine navigation reaches and seasons that furthered ecological understanding. State variables were identified as suspended solids, chlorophyll a, and total phosphorus, which are also state variables of shallow lakes worldwide. The TDA change detection function showed short-term state transitions based on seasonality and episodic events, and provided evidence of gradual, long-term changes due to water quality improvements over three decades. These results can inform decision making and guide actions for regulatory and restoration agencies by assessing the status and trends of this important river and provide quantitative targets for state variables. The TDA change detection function may serve as a new tool for predicting the vulnerability to undesirable state transitions in this system and other ecosystems with sufficient data. Coupling ecosystem state concepts and TDA tools can be transferred to any ecosystem with large data to help classify states and understand their vulnerability to state transitions.

","language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pcbi.1011147","usgsCitation":"Larson, D.M., Bungula, W., McKean, C., Stockdill, A., Lee, A., Miller, F., and Davis, K., 2023, Quantifying ecosystem states and state transitions of the Upper Mississippi River System using topological data analysis: PLOS Computational Biology, v. 19, no. 6, e1011147, 18 p., https://doi.org/10.1371/journal.pcbi.1011147.","productDescription":"e1011147, 18 p.","ipdsId":"IP-145761","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":443165,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pcbi.1011147","text":"Publisher Index Page"},{"id":435291,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P976O6PP","text":"USGS data release","linkHelpText":"Data to quantify ecosystem states and state transitions of the Upper Mississippi River using topological data analysis"},{"id":419588,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"19","issue":"6","noUsgsAuthors":false,"publicationDate":"2023-06-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Larson, Danelle M. 0000-0001-6349-6267","orcid":"https://orcid.org/0000-0001-6349-6267","contributorId":228838,"corporation":false,"usgs":true,"family":"Larson","given":"Danelle","email":"","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":879673,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bungula, Wako","contributorId":315367,"corporation":false,"usgs":false,"family":"Bungula","given":"Wako","email":"","affiliations":[{"id":68293,"text":"University of Wisconsin La Crosse","active":true,"usgs":false}],"preferred":false,"id":879674,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McKean, Casey","contributorId":315369,"corporation":false,"usgs":false,"family":"McKean","given":"Casey","email":"","affiliations":[{"id":68293,"text":"University of Wisconsin La Crosse","active":true,"usgs":false}],"preferred":false,"id":879675,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stockdill, Alaina","contributorId":315368,"corporation":false,"usgs":false,"family":"Stockdill","given":"Alaina","email":"","affiliations":[{"id":68293,"text":"University of Wisconsin La Crosse","active":true,"usgs":false}],"preferred":false,"id":879676,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lee, Amber","contributorId":244743,"corporation":false,"usgs":false,"family":"Lee","given":"Amber","email":"","affiliations":[],"preferred":false,"id":879677,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Miller, Frederick","contributorId":315370,"corporation":false,"usgs":false,"family":"Miller","given":"Frederick","email":"","affiliations":[{"id":68293,"text":"University of Wisconsin La Crosse","active":true,"usgs":false}],"preferred":false,"id":879678,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Davis, Killian","contributorId":315371,"corporation":false,"usgs":false,"family":"Davis","given":"Killian","email":"","affiliations":[{"id":68293,"text":"University of Wisconsin La Crosse","active":true,"usgs":false}],"preferred":false,"id":879679,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70244132,"text":"fs20233014 - 2023 - River water quality in the Delaware River Basin—Concentrations and trends through 2018","interactions":[],"lastModifiedDate":"2026-02-06T22:00:50.572526","indexId":"fs20233014","displayToPublicDate":"2023-06-06T13:44:10","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-3014","displayTitle":"River Water Quality in the Delaware River Basin—Concentrations and Trends Through 2018","title":"River water quality in the Delaware River Basin—Concentrations and trends through 2018","docAbstract":"

Introduction

The Delaware River Basin provides drinking water to 13.3 million people and supports endangered species, provides recreational opportunities, and is an essential resource to regional industries. The efforts of Federal and State governments have substantially improved overall water quality in the basin, which had been severely degraded prior to the mid-20th century. Recent trend analyses of water-quality data reveal negative and positive changes: increasing rates of salinization and improvements in nutrient conditions.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20233014","issn":"2327-6932","programNote":"Water Availability and Use Science Program","usgsCitation":"Shoda, M., Gain, E.G., and Murphy, J.C., 2023, River water quality in the Delaware River Basin—Concentrations and trends through 2018: U.S. Geological Survey Fact Sheet 2023–3014, 4 p., https://doi.org/10.3133/fs20233014.","productDescription":"Report: 4 p., 2 Data Releases","numberOfPages":"4","onlineOnly":"Y","ipdsId":"IP-133306","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":417697,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2023/3014/images/"},{"id":417699,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9PX8LZO","text":"USGS—Multisource surface-water-quality data and U.S. Geological Survey streamgage match for the Delaware River Basin"},{"id":417695,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2023/3014/fs20233014.XML","linkFileType":{"id":8,"text":"xml"},"description":"FS 2023-3014 XML"},{"id":417694,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2023/3014/fs20233014.pdf","size":"5.94 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2023-3014"},{"id":417693,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2023/3014/coverthb.jpg"},{"id":417698,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9KMWNJ5","text":"USGS—Water-quality trends for rivers and streams in the Delaware River Basin using Weighted Regressions on Time, Discharge, and Season (WRTDS) models, Seasonal Kendall Trend (SKT) tests, and multisource data, water year 1978–2018"},{"id":417700,"rank":8,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20225097","text":"USGS SIR 2022–5097"},{"id":417696,"rank":4,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/fs20233014/full","linkFileType":{"id":5,"text":"html"},"description":"FS 2023-3014 HTML"},{"id":499664,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114765.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Delaware, New Jersey, New York, Pennsylvania","otherGeospatial":"Delaware River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -75.67732588371656,\n 38.47315961720821\n ],\n [\n -74.18382604899824,\n 38.47315961720821\n ],\n [\n -74.18382604899824,\n 42.626372631803235\n ],\n [\n -75.67732588371656,\n 42.626372631803235\n ],\n [\n -75.67732588371656,\n 38.47315961720821\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"

For more information about this publication, contact
Program Coordinator
U.S. Geological Survey
Water Availability and Use Science Program
National Water Quality Program
Email: wausp-info@usgs.gov

For additional information, visit
https://www.usgs.gov/programs/national-water-quality-program

Contact Pubs Warehouse
","tableOfContents":"","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2023-06-06","noUsgsAuthors":false,"publicationDate":"2023-06-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Shoda, Megan E. 0000-0002-5343-9717 meshoda@usgs.gov","orcid":"https://orcid.org/0000-0002-5343-9717","contributorId":4352,"corporation":false,"usgs":true,"family":"Shoda","given":"Megan","email":"meshoda@usgs.gov","middleInitial":"E.","affiliations":[{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":874560,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gain, Emily G 0000-0002-7834-2145","orcid":"https://orcid.org/0000-0002-7834-2145","contributorId":293625,"corporation":false,"usgs":true,"family":"Gain","given":"Emily","email":"","middleInitial":"G","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":874561,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Murphy, Jennifer C. 0000-0002-0881-0919 jmurphy@usgs.gov","orcid":"https://orcid.org/0000-0002-0881-0919","contributorId":4281,"corporation":false,"usgs":true,"family":"Murphy","given":"Jennifer","email":"jmurphy@usgs.gov","middleInitial":"C.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":874562,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70244185,"text":"70244185 - 2023 - Neonicotinoid sunflower seed treatment, while not detected in pollen and nectar, still impacts wild bees and crop yield","interactions":[],"lastModifiedDate":"2023-06-07T14:21:55.839005","indexId":"70244185","displayToPublicDate":"2023-06-06T09:19:00","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":14460,"text":"Agrochemicals","active":true,"publicationSubtype":{"id":10}},"title":"Neonicotinoid sunflower seed treatment, while not detected in pollen and nectar, still impacts wild bees and crop yield","docAbstract":"Neonicotinoid seed treatments are commonly used in agricultural production even though their benefit to crop yield and their impact on pollinators, particularly wild bees, remains unclear. Using an on-farm matched pair design in which half of each field was sown with thiamethoxam treated seed and half without, we assessed honey bee and wild bee exposure to pesticides in sunflower fields by analyzing pesticide residues in field soil, sunflower pollen and nectar, pollen-foraging and nec-tar-foraging honey bees, and a sunflower specialist wild bee (Melissodes agilis). We also quantified the effects of thiamethoxam-treated seed on wild bee biodiversity and crop yield. M. agilis abundance was significantly lower with thiamethoxam treatment and overall wild bee abundance trending lower but was not significantly different. Furthermore, crop yield was significantly lower in plots with thiamethoxam treatment, even though thiamethoxam was only detected at low concentrations in one soil sample (and its primary metabolite, clothianidin, was never detected). Conversely, wild bee richness was significantly higher and diversity was marginally higher with thiamethoxam treatment. Nectar volumes harvested from the nectar-foraging honey bees were also significantly higher with thiamethoxam treatment. Several pesticides that were not used in the sunflower fields were detected in our samples, some of which are known to be deleterious to bee health, highlighting the importance of the landscape scale in the assessment of pesticide exposure for bees. Overall, our results suggest that thiamethoxam seed treatments may negatively impact wild bee pollination services in sunflower. Importantly, this study highlights the advantages of the inclusion of other metrics, such as biodiversity or behavior, in pesticide risk analysis, as pesticide residue analysis, as an independent metric, may erroneously miss the impacts of field realistic pesticide exposure on bees.","language":"English","publisher":"MDPI","doi":"10.3390/agrochemicals2020018","usgsCitation":"Ward, L.T., Hladik, M.L., Guzman, A., Bautista, A., and Mills, N., 2023, Neonicotinoid sunflower seed treatment, while not detected in pollen and nectar, still impacts wild bees and crop yield: Agrochemicals, v. 2, no. 2, p. 279-295, https://doi.org/10.3390/agrochemicals2020018.","productDescription":"17 p.","startPage":"279","endPage":"295","ipdsId":"IP-132034","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":443172,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/agrochemicals2020018","text":"Publisher Index Page"},{"id":435292,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9X3SP7F","text":"USGS data release","linkHelpText":"Pesticide concentrations in bees and other matrices collected from sunflower fields (with and without a neonicotinoid seed treatment) near Sacramento, California"},{"id":417913,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"Sacramento","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.75836841779504,\n 38.795715176727754\n ],\n [\n -121.75836841779504,\n 38.3032820529848\n ],\n [\n -121.16999959773764,\n 38.3032820529848\n ],\n [\n -121.16999959773764,\n 38.795715176727754\n ],\n [\n -121.75836841779504,\n 38.795715176727754\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"2","issue":"2","noUsgsAuthors":false,"publicationDate":"2023-06-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Ward, Laura T.","contributorId":289488,"corporation":false,"usgs":false,"family":"Ward","given":"Laura","email":"","middleInitial":"T.","affiliations":[{"id":36942,"text":"University of California, Berkeley","active":true,"usgs":false}],"preferred":false,"id":874806,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hladik, Michelle L. 0000-0002-0891-2712","orcid":"https://orcid.org/0000-0002-0891-2712","contributorId":221229,"corporation":false,"usgs":true,"family":"Hladik","given":"Michelle","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":874807,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Guzman, Aidee","contributorId":289489,"corporation":false,"usgs":false,"family":"Guzman","given":"Aidee","email":"","affiliations":[{"id":36942,"text":"University of California, Berkeley","active":true,"usgs":false}],"preferred":false,"id":874808,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bautista, Ariana","contributorId":289494,"corporation":false,"usgs":false,"family":"Bautista","given":"Ariana","email":"","affiliations":[{"id":36942,"text":"University of California, Berkeley","active":true,"usgs":false}],"preferred":false,"id":874809,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mills, Nicholas","contributorId":289500,"corporation":false,"usgs":false,"family":"Mills","given":"Nicholas","email":"","affiliations":[{"id":36942,"text":"University of California, Berkeley","active":true,"usgs":false}],"preferred":false,"id":874810,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70244187,"text":"70244187 - 2023 - Combining field observations and high-resolution numerical modeling to demonstrate the effect of coral reef roughness on turbulence and its implications for reef restoration design","interactions":[],"lastModifiedDate":"2023-06-07T14:17:43.502323","indexId":"70244187","displayToPublicDate":"2023-06-06T09:13:59","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1262,"text":"Coastal Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Combining field observations and high-resolution numerical modeling to demonstrate the effect of coral reef roughness on turbulence and its implications for reef restoration design","docAbstract":"

Coral reefs are effective natural barriers that protect adjacent coastal communities from hazards such as erosion and storm-induced flooding. However, the degradation of coral reefs compromises their ability to protect against these hazards, making degraded reefs a target for restoration. There have been limited field and numerical modeling studies conducted to understand how an increase in coral reef roughness, as would occur due to restoration, can affect wave energy dissipation for a range of real-world wave and water level conditions. To address this knowledge gap, field measurements were collected over adjacent low-roughness and high-roughness reefs off Molokaʻi, Hawaiʻi, USA, subjected to the same oceanographic forcing. Those field data were then used to calibrate and validate OpenFOAM computational fluid dynamics models of the reef. These calibrated models were then used to explore energy dissipation for a range of wave conditions based on measurements from a suite of existing datasets and values from the literature. In general, wave dissipation scales with incident wave conditions, where greater dissipation occurred for shallow depths and shorter-period waves. This tendency for short-period waves to be more readily attenuated is supported by wave energy dissipation factors in the range of 0.1–5, which decline with increasing wave period. Near-bed turbulent kinetic energy dissipation also scales with incident wave conditions, where the greatest difference in dissipation between low and high relief cases occurs for short wave periods. Turbulence becomes less affected by bottom roughness as the wave period increases. Based on this study, wave attenuation and turbulent energy dissipation could be enhanced by 0.5–1 order of magnitude (45% per across-shore meter) if the seabed roughness at the field site were increased by 13%, an achievable goal in coral reef restoration.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.coastaleng.2023.104331","usgsCitation":"Norris, B.K., Storlazzi, C.D., Pomeroy, A.W., Rosenberger, K.J., Logan, J.B., and Cheriton, O.M., 2023, Combining field observations and high-resolution numerical modeling to demonstrate the effect of coral reef roughness on turbulence and its implications for reef restoration design: Coastal Engineering, v. 184, 104331, 18 p., https://doi.org/10.1016/j.coastaleng.2023.104331.","productDescription":"104331, 18 p.","ipdsId":"IP-137643","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":443176,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.coastaleng.2023.104331","text":"Publisher Index Page"},{"id":435295,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P933TO2Q","text":"USGS data release","linkHelpText":"OpenFOAM models of low- and high-relief sites from the coral reef flat off Waiakane, Molokai, Hawaii"},{"id":435294,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9HNLI7Y","text":"USGS data release","linkHelpText":"3D bathymetric surfaces of low- and high-relief sites from the coral reef flat off Waiakane, Molokai"},{"id":435293,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9XZT1FK","text":"USGS data release","linkHelpText":"Aerial imagery and structure-from-motion-derived shallow water bathymetry from a UAS survey of the coral reef off Waiakane, Molokai, Hawaii, June 2018"},{"id":417912,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"184","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Norris, Benjamin K 0000-0002-9133-5935","orcid":"https://orcid.org/0000-0002-9133-5935","contributorId":306089,"corporation":false,"usgs":true,"family":"Norris","given":"Benjamin","email":"","middleInitial":"K","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":874818,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Storlazzi, Curt D. 0000-0001-8057-4490","orcid":"https://orcid.org/0000-0001-8057-4490","contributorId":213610,"corporation":false,"usgs":true,"family":"Storlazzi","given":"Curt","middleInitial":"D.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":874819,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pomeroy, Andrew W. M.","contributorId":304433,"corporation":false,"usgs":false,"family":"Pomeroy","given":"Andrew","email":"","middleInitial":"W. M.","affiliations":[{"id":13336,"text":"University of Melbourne","active":true,"usgs":false}],"preferred":false,"id":874820,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rosenberger, Kurt J. 0000-0002-5185-5776 krosenberger@usgs.gov","orcid":"https://orcid.org/0000-0002-5185-5776","contributorId":140453,"corporation":false,"usgs":true,"family":"Rosenberger","given":"Kurt","email":"krosenberger@usgs.gov","middleInitial":"J.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":874821,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Logan, Joshua B. 0000-0002-6191-4119 jlogan@usgs.gov","orcid":"https://orcid.org/0000-0002-6191-4119","contributorId":2335,"corporation":false,"usgs":true,"family":"Logan","given":"Joshua","email":"jlogan@usgs.gov","middleInitial":"B.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":874822,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cheriton, Olivia M. 0000-0003-3011-9136","orcid":"https://orcid.org/0000-0003-3011-9136","contributorId":204459,"corporation":false,"usgs":true,"family":"Cheriton","given":"Olivia","middleInitial":"M.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":874823,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70248836,"text":"70248836 - 2023 - Progress in reducing nutrient and sediment loads to Chesapeake Bay: Three decades of monitoring data and implications for restoring complex ecosystems","interactions":[],"lastModifiedDate":"2023-09-22T12:09:23.21022","indexId":"70248836","displayToPublicDate":"2023-06-06T07:06:00","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5067,"text":"WIREs Water","active":true,"publicationSubtype":{"id":10}},"title":"Progress in reducing nutrient and sediment loads to Chesapeake Bay: Three decades of monitoring data and implications for restoring complex ecosystems","docAbstract":"

For over three decades, Chesapeake Bay (USA) has been the focal point of a coordinated restoration strategy implemented through a partnership of governmental and nongovernmental entities, which has been a classical model for coastal restoration worldwide. This synthesis aims to provide resource managers and estuarine scientists with a clearer perspective of the magnitude of changes in water quality within the Bay watershed, including nitrogen (N), phosphorus (P), and sediment for the River Input Monitoring (RIM) watershed and the unmonitored below-RIM watershed. The flow-normalized N load from the RIM watershed has declined in the period of 1985–2017, but P and sediment loads have lacked progress. Reductions of riverine N are largely driven by reductions of point sources and atmospheric deposition. Future reductions will require significant progress in managing agricultural nonpoint sources. The below-RIM watershed, which comprises a disproportionately high fraction of inputs to the Bay, has shown long-term declines in major sources, including point sources (N and P), atmospheric deposition (N), manure (N and P) and fertilizer (P), based on a combination of monitoring and modeling assessments. To date, the Bay cleanup efforts have achieved some progress toward reducing nutrients from the watershed, which have resulted in improving water quality in the estuary. However, further reductions are critical to achieve the Chesapeake Bay Total Maximum Daily Load goals, and emerging challenges due to Conowingo Reservoir, legacy nutrients, climate change, and population growth should be considered. Continued monitoring, modeling, and assessment are critically important for informing the restoration of this complex ecosystem.

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0000-0002-8350-8779","orcid":"https://orcid.org/0000-0002-8350-8779","contributorId":330001,"corporation":false,"usgs":false,"family":"Langland","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":12443,"text":"U.S. Geological Survey (retired)","active":true,"usgs":false}],"preferred":false,"id":883842,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70244153,"text":"ofr20231028 - 2023 - Analysis of aquifer framework and properties, North Magee Street well field, Southampton, New York","interactions":[],"lastModifiedDate":"2026-02-11T21:05:56.661721","indexId":"ofr20231028","displayToPublicDate":"2023-06-05T16:25:00","publicationYear":"2023","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":"2023-1028","displayTitle":"Analysis of Aquifer Framework and Properties, North Magee Street Well Field, Southampton, New York","title":"Analysis of aquifer framework and properties, North Magee Street well field, Southampton, New York","docAbstract":"

The U.S. Geological Survey, in cooperation with the Suffolk County Water Authority, evaluated the groundwater-flow characteristics and aquifer properties of the North Magee Street well field north of the village of Southampton, New York. Characteristics and properties included groundwater-flow direction, potential groundwater-contributing areas to the well field production wells, and aquifer transmissivity and storage. The groundwater flow and aquifer properties were also evaluated to allow Suffolk County Water Authority to better assess the potential source of dissolved halocarbons (refrigerants, such as chlorofluorocarbons).

The well field production wells are screened in the upper glacial aquifer and an observation well is screened in the Magothy aquifer. Based on depth and available logs, groundwater from wells screened in the upper glacial aquifer was classified as under water-table (unconfined) conditions, and groundwater from wells screened in the Magothy aquifer was classified as being under semiconfined conditions.

Groundwater flows radially to the well field during production and in a northwesterly direction under the effect of the regional flow regime. A previously published particle tracking analysis identified the following recharge contributing areas nearby the well field: (1) contributing areas to surface-water bodies of the Peconic Estuary, (2) contributing areas to surface-water bodies of the South Shore Estuary Reserve, (3) a contributing area to the Atlantic Ocean, and (4) a contributing area to another Suffolk County Water Authority well field. Five other pumping well contributing areas were identified within the study area, including those of various wells pumped for golf-course irrigation.

Analysis of drawdown and recovery data collected during the multiple-well aquifer test, through the application of a Neuman analytical model, provided estimates of upper glacial aquifer characteristics and properties. Inclusion of lateral aquifer boundaries was not necessary for the analysis to result in satisfactory matches with the observed water-level responses. Aquifer transmissivity was estimated to be 170,000 feet squared per day. Storativity was estimated to be 0.02 (dimensionless), and specific yield was estimated to be 0.08 (dimensionless), consistent with the inferred degree of confinement and well field characteristics.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231028","collaboration":"Prepared in cooperation with the Suffolk County Water Authority","usgsCitation":"Misut, P.E., 2023, Analysis of aquifer framework and properties, North Magee Street well field, Southampton, New York: U.S. Geological Survey Open-File Report 2023–1028, 14 p., https://doi.org/10.3133/ofr20231028.","productDescription":"Report: iv, 14 p.; Dataset","numberOfPages":"14","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-124210","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":499775,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114761.htm","linkFileType":{"id":5,"text":"html"}},{"id":417746,"rank":6,"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":417745,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1028/images/"},{"id":417744,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1028/ofr20231028.XML"},{"id":417743,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231028/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2023-1028"},{"id":417742,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1028/ofr20231028.pdf","text":"Report","size":"2.51 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023-1028"},{"id":417741,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1028/coverthb.jpg"}],"country":"United States","state":"New York","city":"Southampton","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -72.43897301957882,\n 40.91839299249426\n ],\n [\n -72.43897301957882,\n 40.87699855750361\n ],\n [\n -72.37328061868494,\n 40.87699855750361\n ],\n [\n -72.37328061868494,\n 40.91839299249426\n ],\n [\n -72.43897301957882,\n 40.91839299249426\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"

Director, New York Water Science Center
U.S. Geological Survey
425 Jordan Road
Troy, NY 12180–8349

","tableOfContents":"","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"publishedDate":"2023-06-05","noUsgsAuthors":false,"publicationDate":"2023-06-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Misut, Paul E. 0000-0002-6502-5255 pemisut@usgs.gov","orcid":"https://orcid.org/0000-0002-6502-5255","contributorId":1073,"corporation":false,"usgs":true,"family":"Misut","given":"Paul","email":"pemisut@usgs.gov","middleInitial":"E.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":874644,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70244095,"text":"ofr20231022 - 2023 - Distribution of chlorinated volatile organic compounds and per- and polyfluoroalkyl substances in groundwater and surface water at the former Naval Air Warfare Center, West Trenton, New Jersey, 2018","interactions":[],"lastModifiedDate":"2026-02-11T20:59:01.863472","indexId":"ofr20231022","displayToPublicDate":"2023-06-05T12:00:00","publicationYear":"2023","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":"2023-1022","displayTitle":"Distribution of Chlorinated Volatile Organic Compounds and Per- and Polyfluoroalkyl Substances in Groundwater and Surface Water at the former Naval Air Warfare Center, West Trenton, New Jersey, 2018","title":"Distribution of chlorinated volatile organic compounds and per- and polyfluoroalkyl substances in groundwater and surface water at the former Naval Air Warfare Center, West Trenton, New Jersey, 2018","docAbstract":"

Groundwater wells and surface-water storm sewers contaminated with volatile organic compounds (VOCs) and per- and polyfluoroalkyl substances (PFASs) at the former Naval Air Warfare Center (NAWC) site in West Trenton, New Jersey were sampled in 2018 as part of the Navy’s long-term monitoring program. Trichloroethene (TCE), cis-1,2-dichloroethene (cisDCE), and vinyl chloride concentrations were plotted in map view and selected cross sections to elucidate the vertical and horizontal extent and distribution of contamination, along with a tabular comparison between 2018 and previous analytical results. The 2018 data showed that the areas of VOC contamination (>1 microgram per liter) decreased slightly on the north and east sides of the NAWC site from previous sampling dates; these decreases are attributed to the influence of the pump-and-treat system, natural attenuation processes, and various engineered bioaugmentation experiments that have occurred onsite. Off-site groundwater samples indicate the VOC contaminated groundwater is likely hydraulically constrained by the pump-and-treat system and appears to not be moving offsite to the south and west of NAWC. Only one offsite well, 50BR, located along the eastern margin of the site, was found to have detectable TCE and cisDCE concentrations, indicating that VOC contamination continues to migrate a short distance offsite to the east. Detectable VOC contamination was found in wells as deep as 200 and 221 feet on both the east and west sides of the NAWC site. Comparisons of present-day data to data from past sampling efforts indicate that TCE concentrations in most wells have decreased slowly over time.

Results from surface-water samples indicate that VOCs enter surface water predominantly through the West Ditch drainage system. Concentrations and fluxes of VOCs are higher when groundwater levels are higher, indicating contaminated groundwater discharges into the surface water system. Higher VOC concentrations at the Interceptor site relative to other sites in the West Ditch indicate the contamination in the West Ditch system is likely caused by contaminated groundwater discharging to the West Ditch storm sewer near manhole MH-140 when water table levels are high.

The pump-and-treat extraction wells at the former NAWC site were sampled for per- and polyfluoroalkyl substances (PFAS) in 2018. The suite of reported PFAS include perfluorooctane sulfonate (PFOS), perfluorooctanoic acid (PFOA), perfluorononanoic acid, and perfluorobutane sulfonate. Concentrations were plotted in map view to determine the areal extent of the PFAS contamination at the site. Extraction well 48BR sampled on the eastern half of the site was found to have PFOS and PFOA concentrations greater than the New Jersey Department of Environmental Protection Drinking Water maximum contaminant levels (MCLs), which is consistent with the distribution of highest PFAS concentrations in surface water in the OF-4 storm sewer system that drains that area, as well as previously collected PFAS concentrations in monitoring wells. On the western half of the site, the extraction well 08BR sample exceeded MCLs for PFOA and PFOS and the extraction well 22BR sample exceeded the MCL for PFOA, but samples from all other extraction wells were below the MCLs or other criteria for all PFAS analyzed. Concentrations of PFOA exceeded concentrations of PFOS on the west side of NAWC in both groundwater and surface water, which contrasts with the conditions on the east side of NAWC where PFOS concentrations exceeded PFOA concentrations. However, this observation was based on a limited number of samples on the west side of NAWC from 2018 and previous years, so more PFAS sampling is needed on the west side to assess this further.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231022","collaboration":"Prepared in cooperation with the U.S. Navy","usgsCitation":"Fiore, A.R., Imbrigiotta, T.E., and Wilson, T.P., 2023, Distribution of chlorinated volatile organic compounds and per- and polyfluoroalkyl substances in groundwater and surface water at the former Naval Air Warfare Center, West Trenton, New Jersey, 2018: U.S. Geological Survey Open-File Report 2023–1022, 81 p., https://doi.org/10.3133/ofr20231022.","productDescription":"Report: ix, 81 p.; Data Release","numberOfPages":"81","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-114249","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":417658,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9RCAQ5N","text":"USGS data release","linkHelpText":"Concentrations of chlorinated volatile organic compounds and per- and polyfluoroalkyl substances in groundwater and surface water, former Naval Air Warfare Center, West Trenton, New Jersey"},{"id":417657,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1022/images/"},{"id":417656,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1022/ofr20231022.XML"},{"id":417655,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/ofr20231022/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2023-1022"},{"id":417654,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1022/ofr20231022.pdf","text":"Report","size":"11.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023-1022"},{"id":417653,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1022/coverthb.jpg"},{"id":499772,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114760.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"New Jersey","city":"West Trenton","otherGeospatial":"former Naval Air Warfare Center","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -74.816667,\n 40.275\n ],\n [\n -74.816667,\n 40.2667\n ],\n [\n -74.808333,\n 40.2667\n ],\n [\n -74.808333,\n 40.275\n ],\n [\n -74.816667,\n 40.275\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"

Director, New Jersey Water Science Center
U.S. Geological Survey
3450 Princeton Pike, Suite 110
Lawrenceville, NJ, 08648

Contact Pubs Warehouse

","tableOfContents":"","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"publishedDate":"2023-06-05","noUsgsAuthors":false,"publicationDate":"2023-06-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Fiore, Alex R. 0000-0002-0986-5225 afiore@usgs.gov","orcid":"https://orcid.org/0000-0002-0986-5225","contributorId":4977,"corporation":false,"usgs":true,"family":"Fiore","given":"Alex","email":"afiore@usgs.gov","middleInitial":"R.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":874475,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Imbrigiotta, Thomas E. 0000-0003-1716-4768 timbrig@usgs.gov","orcid":"https://orcid.org/0000-0003-1716-4768","contributorId":152114,"corporation":false,"usgs":true,"family":"Imbrigiotta","given":"Thomas","email":"timbrig@usgs.gov","middleInitial":"E.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":874476,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wilson, Timothy P. 0000-0003-1914-6344","orcid":"https://orcid.org/0000-0003-1914-6344","contributorId":219174,"corporation":false,"usgs":true,"family":"Wilson","given":"Timothy P.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":874477,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70244134,"text":"sir20235049 - 2023 - Comparing domestic and public-supply groundwater quality in the northern San Joaquin Valley, 2019—California GAMA Priority Basin Project","interactions":[],"lastModifiedDate":"2026-03-09T16:07:18.717873","indexId":"sir20235049","displayToPublicDate":"2023-06-05T10:01:50","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-5049","displayTitle":"Comparing Domestic and Public-Supply Groundwater Quality in the Northern San Joaquin Valley, 2019: California GAMA Priority Basin Project","title":"Comparing domestic and public-supply groundwater quality in the northern San Joaquin Valley, 2019—California GAMA Priority Basin Project","docAbstract":"

Groundwater quality in the Northern San Joaquin Valley region of California was studied as part of California State Water Resources Control Board (SWRCB) Groundwater Ambient Monitoring and Assessment Program-Priority Basin Project (GAMA-PBP). The GAMA-PBP made a spatially unbiased assessment of the aquifer system used for domestic drinking-water supply in the study region and compared the results to the aquifer system used for public drinking-water supply. These assessments characterized the quality of raw groundwater to evaluate ambient conditions in regional aquifers and not the quality of treated drinking water. The study included two components: (1) a status assessment presenting study results summarizing the status of groundwater quality used for domestic supply in the Northern San Joaquin Valley and (2) a comparative assessment of groundwater resources used for domestic and public drinking-water supply in the study region.

The status assessment was based on data collected by the GAMA-PBP from 45 sites in the Northern San Joaquin Valley domestic-supply aquifer assessment study unit during 2019. To contextualize water-quality results, concentrations of water-quality constituents in ambient groundwater were compared to regulatory and non-regulatory benchmarks used by the State of California and Federal agencies as health-based or aesthetic standards for public drinking water. A grid-based method to estimate aquifer-scale proportions of groundwater resources with concentrations approaching or exceeding benchmark thresholds was used in the status assessment. This method provides spatially unbiased results and allows inter-comparability with similar groundwater-quality assessments. A spatially weighted method was used to calculate aquifer-scale proportions for public-supply wells within the domestic assessment grid network using contemporaneous regulatory compliance monitoring data. Differences among aquifer-scale proportions for constituents exceeding regulatory and non-regulatory benchmarks in domestic- and public-supply aquifers were quantitatively evaluated. Factors influencing the vertical and lateral distribution of key contaminants of concern (nitrate, fumigants, and arsenic) across overlapping aquifer systems used for domestic and public drinking-water supply were also evaluated.

Status assessment results indicated inorganic and organic constituents with health-based benchmarks were present at high relative concentrations (RCs), meaning they exceeded a benchmark threshold, in 20 and 9 percent of the domestic-supply aquifer system in the Northern San Joaquin Valley, respectively. Inorganic constituents with health-based benchmarks present at high RCs included nitrate and arsenic. The only organic constituents with health-based benchmarks present at high RCs were the fumigants 1,2-dibromo-3-chloropropane (DBCP) and 1,2,3-trichloropropane (1,2,3-TCP). Inorganic constituents with aesthetic-based benchmarks were present at high RCs in 13 percent of the domestic-supply aquifer system in the Northern San Joaquin Valley and included iron and manganese. Microbial indicators (total coliform bacteria and Enterococci) were present in 18 and 2 percent of the domestic-supply aquifer system in the Northern San Joaquin Valley, respectively.

Comparative assessment results indicated inorganic and organic constituents with health-based benchmarks were present at high RCs in 13 and 6 percent of the public-supply aquifer system in the Northern San Joaquin Valley, respectively. Inorganic constituents with aesthetic-based benchmarks were present at high RCs in 22 percent of the public-supply aquifer system in the Northern San Joaquin Valley. There were no significant differences among high RC proportions for individual water-quality constituents, except for nitrate, which was greater in the domestic- compared to public-supply aquifer system in the Northern San Joaquin Valley. The most prevalent constituents with health-based benchmarks contributing to high RC proportions in the public-supply aquifer system were arsenic and fumigants, including DBCP and 1,2,3-TCP.

Analysis of construction data for wells included in the comparative assessment indicated that, although depth to top of perforations are comparable for domestic and public-supply wells in the Northern San Joaquin Valley (median depth about 60 meters [m]), public-supply wells have longer perforation intervals and extend to deeper parts of the aquifer system than domestic wells that typically draw exclusively from the shallower aquifer system in the upper 80 m of unconsolidated sediments. Analysis of the vertical and lateral distribution of constituents of interest (nitrate, fumigants, and arsenic) across domestic- and public-supply aquifers indicated that nitrate is prevalent in shallow aquifers throughout the Northern San Joaquin Valley but is potentially diluted by mixing with deeper, older groundwater at long-screened public-supply wells. Fumigants were prevalent in areas of urban and agricultural land use in the western part of the Northern San Joaquin Valley, particularly in areas near Lodi, California, but 1,2,3-TCP was more widespread than DBCP and was detected in shallow and deeper parts of the aquifer system, potentially because of its recalcitrance in groundwater and ability to be detected at low concentrations. Arsenic was most prevalent in the western part of the Northern San Joaquin Valley with proximity to deltaic sediments and was detected at high RCs in wells tapping shallow and deep parts of the aquifer system.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235049","collaboration":"Prepared in cooperation with the California State Water Resources Control Board","programNote":"A product of the California Groundwater Ambient Monitoring and Assessment (GAMA) Program","usgsCitation":"Bennett, G.L., V, Haugen, E.A., and Levy, Z.F., 2023, Comparing domestic and public-supply groundwater quality in the northern San Joaquin Valley, 2019—California GAMA Priority Basin Project: U.S. Geological Survey Scientific Investigations Report 2023–5049, 44 p., https://doi.org/10.3133/sir20235049.","productDescription":"Report: x, 44 p.; 2 Data Releases","numberOfPages":"44","onlineOnly":"Y","ipdsId":"IP-136374","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":417722,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5049/images"},{"id":417725,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P90OHVIC","text":"Compilation of public-supply well construction depths in California","description":"Levy, Z.F., and Borkovich, J.G., 2022, Compilation of public-supply well construction depths in California: U.S. Geological Survey data release, https://doi.org/10.5066/P90OHVIC."},{"id":417719,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5049/covrthb.jpg"},{"id":417720,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5049/sir20235049.pdf","text":"Report","size":"21 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":417721,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5049/sir20235049.xml"},{"id":417723,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235049/full"},{"id":417724,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9Q083IB","text":"Groundwater-quality data in the Northern San Joaquin Valley Domestic-Supply Aquifer Study Unit, 2019: Results from the California GAMA Priority Basin Project","description":"Balkan, M., Levy, Z.F., Shelton, J.L., Johnson, T.D., and Watson, E., 2021, Groundwater-quality data in the Northern San Joaquin Valley Domestic-Supply Aquifer Study Unit, 2019: Results from the California GAMA Priority Basin Project: U.S. Geological Survey data release, https://doi.org/10.5066/P9Q083IB."},{"id":500927,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114762.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"California","otherGeospatial":"Northern San Joaquin Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.78743448158886,\n 38.35484127947586\n ],\n [\n -121.78743448158886,\n 37.32696097611618\n ],\n [\n -120.59999292604016,\n 37.32696097611618\n ],\n [\n -120.59999292604016,\n 38.35484127947586\n ],\n [\n -121.78743448158886,\n 38.35484127947586\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"

Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819

","tableOfContents":"","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2023-06-05","noUsgsAuthors":false,"publicationDate":"2023-06-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Bennett, George L. V V 0000-0002-6239-1604 georbenn@usgs.gov","orcid":"https://orcid.org/0000-0002-6239-1604","contributorId":1373,"corporation":false,"usgs":true,"family":"Bennett","given":"George","suffix":"V","email":"georbenn@usgs.gov","middleInitial":"L. V","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":874565,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haugen, Emily A. 0000-0002-0263-9911","orcid":"https://orcid.org/0000-0002-0263-9911","contributorId":211480,"corporation":false,"usgs":true,"family":"Haugen","given":"Emily","email":"","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":874566,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Levy, Zeno F. 0000-0003-4580-2309 zflevy@usgs.gov","orcid":"https://orcid.org/0000-0003-4580-2309","contributorId":219572,"corporation":false,"usgs":true,"family":"Levy","given":"Zeno","email":"zflevy@usgs.gov","middleInitial":"F.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":874567,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70254885,"text":"70254885 - 2023 - Habitat selection and water dependency of feral burros in the Mojave Desert, California, USA","interactions":[],"lastModifiedDate":"2024-06-11T11:24:12.755768","indexId":"70254885","displayToPublicDate":"2023-06-05T06:20:16","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Habitat selection and water dependency of feral burros in the Mojave Desert, California, USA","docAbstract":"

Expansion of feral burro (Equus asinus) populations across the southwestern United States is causing human–wildlife conflicts including rangeland degradation, competition with livestock and native species, and burro–vehicle collisions. On the Fort Irwin National Training Center (NTC) in California, feral burros interfere with military training and are involved in vehicle collisions and other conflicts (e.g., burros blocking access to buildings). Limited data on burro movements and resource use poses a challenge for the development of management plans and mitigation strategies. We estimated home range size, second- and third-order seasonal resource selection, and water dependency of 10 adult female feral burros fitted with global positioning system (GPS) collars on the NTC from November 2015 to April 2017. Mean 95% autocorrelated kernel home range size of female burros (253.9 ± 30.7 km2 [SE]) did not differ among seasons or between burros that resided close to or far from urban areas. Burros selected areas closer to water in all seasons and at both spatial scales, but selection was stronger in the dry season and at the landscape scale. When available, burros strongly selected for areas closer to urban areas. Burros consistently selected for areas with green forage and at lower elevations, but selection for other topographical features was variable. Water use patterns were consistent with the resource selection results. Burros visited water sources twice as often (every 22.2 ± 6.3 hr) during the hot-dry season (Apr–Oct) compared to the cool-wet seasons (Nov–Mar; 2015: 45.9 ± 21.0; 2016: 39.7 ± 9.3 hr). Our results suggest that urban areas, and resources therein, and water sources have the biggest influence on burro resource selection, and management plans could focus mitigation programs on these areas.

","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.22429","usgsCitation":"Karish, T., Roemer, G., Delaney, D.K., Reddell, C.D., and Cain, J.W., 2023, Habitat selection and water dependency of feral burros in the Mojave Desert, California, USA: Journal of Wildlife Management, v. 87, no. 6, e22429, 24 p., https://doi.org/10.1002/jwmg.22429.","productDescription":"e22429, 24 p.","ipdsId":"IP-145476","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":443200,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jwmg.22429","text":"Publisher Index Page"},{"id":429809,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Mojave Desert","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.66803632479731,\n 34.76261213717514\n ],\n [\n -115.85087435686407,\n 34.76261213717514\n ],\n [\n -115.85087435686407,\n 35.909122547186584\n ],\n [\n -117.66803632479731,\n 35.909122547186584\n ],\n [\n -117.66803632479731,\n 34.76261213717514\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"87","issue":"6","noUsgsAuthors":false,"publicationDate":"2023-06-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Karish, Talesha","contributorId":337900,"corporation":false,"usgs":false,"family":"Karish","given":"Talesha","affiliations":[{"id":12628,"text":"New Mexico State University","active":true,"usgs":false}],"preferred":false,"id":902771,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Roemer, Gary W.","contributorId":337901,"corporation":false,"usgs":false,"family":"Roemer","given":"Gary W.","affiliations":[{"id":12628,"text":"New Mexico State University","active":true,"usgs":false}],"preferred":false,"id":902772,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Delaney, David K.","contributorId":337902,"corporation":false,"usgs":false,"family":"Delaney","given":"David","email":"","middleInitial":"K.","affiliations":[{"id":81054,"text":"U.S. Army Construction Engineering Research Laboratory","active":true,"usgs":false}],"preferred":false,"id":902773,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Reddell, Craig D.","contributorId":337904,"corporation":false,"usgs":false,"family":"Reddell","given":"Craig","email":"","middleInitial":"D.","affiliations":[{"id":12628,"text":"New Mexico State University","active":true,"usgs":false}],"preferred":false,"id":902774,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cain, James W. III 0000-0003-4743-516X jwcain@usgs.gov","orcid":"https://orcid.org/0000-0003-4743-516X","contributorId":4063,"corporation":false,"usgs":true,"family":"Cain","given":"James","suffix":"III","email":"jwcain@usgs.gov","middleInitial":"W.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":902775,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70249738,"text":"70249738 - 2023 - Geographic isolation reduces genetic diversity of a wide-ranging terrestrial vertebrate, Canis lupus","interactions":[],"lastModifiedDate":"2023-10-26T12:11:35.260827","indexId":"70249738","displayToPublicDate":"2023-06-04T07:05:59","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Geographic isolation reduces genetic diversity of a wide-ranging terrestrial vertebrate, Canis lupus","docAbstract":"

Genetic diversity is theorized to decrease in populations closer to a species' range edge, where habitat may be suboptimal. Generalist species capable of long-range dispersal may maintain sufficient gene flow to counteract this, though the presence of significant barriers to dispersal (e.g., large water bodies, human-dominated landscapes) may still lead to, and exacerbate, the edge effect. We used microsatellite data for 2421 gray wolves (Canis lupus) from 24 subpopulations (groups) to model how allelic richness and expected heterozygosity varied with mainland–island position and two measures of range edge (latitude and distance from range center) across >7.3 million km2 of northern North America. We expected low genetic diversity both at high latitudes, due to harsh environmental conditions, and on islands, but no change in diversity with distance to the range center due to the species' exceptional dispersal ability and favorable conditions in far eastern and western habitats. We found that allelic richness and expected heterozygosity of island groups were measurably less than that of mainland groups, and that these differences increased with the island's distance to the species' range center in the study area. Our results demonstrate how multiple axes of geographic isolation (distance from range center and island habitation) can act synergistically to erode the genetic diversity of wide-ranging terrestrial vertebrate populations despite the counteracting influence of long-range dispersal ability. These findings emphasize how geographic isolation is a potential threat to the genetic diversity and viability of terrestrial vertebrate populations even among species capable of long-range dispersal.

","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.4536","usgsCitation":"Frevol, S., MacNulty, D.R., Anderson, M.C., Cluff, H.D., Mech, L.D., and Musiani, M., 2023, Geographic isolation reduces genetic diversity of a wide-ranging terrestrial vertebrate, Canis lupus: Ecosphere, v. 14, no. 6, e4536, 13 p., https://doi.org/10.1002/ecs2.4536.","productDescription":"e4536, 13 p.","ipdsId":"IP-141501","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":443205,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.4536","text":"Publisher Index Page"},{"id":422132,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -129.86560219966944,\n 54.047086800415855\n ],\n [\n -92.59997719966954,\n 53.318357166998\n ],\n [\n -76.42810219966938,\n 49.13926253399768\n ],\n [\n -61.3109146996692,\n 49.13926253399768\n ],\n [\n -54.98278969966927,\n 51.93134598198591\n ],\n [\n -58.49841469966904,\n 58.066794430918236\n ],\n [\n -59.55310219966961,\n 64.98865955060353\n ],\n [\n -61.61853188716954,\n 66.93726341113427\n ],\n [\n -63.68396157466947,\n 68.885867271665\n ],\n [\n -71.68200844966942,\n 72.06746073196186\n ],\n [\n -77.13128787964015,\n 75.13539430494208\n ],\n [\n -71.81847807344269,\n 79.62027784056812\n ],\n [\n -63.55675932344245,\n 81.8208107201825\n ],\n [\n -61.97472807344246,\n 82.62864222144114\n ],\n [\n -69.00597807344256,\n 83.21321439167704\n ],\n [\n -79.55285307344245,\n 83.1085546629603\n ],\n [\n -95.72472807344262,\n 81.48920213520432\n ],\n [\n -115.58800932344275,\n 78.55632744792695\n ],\n [\n -128.06847807344298,\n 75.09023680563831\n ],\n [\n -129.47472807344275,\n 70.83778883188734\n ],\n [\n -136.70809238032393,\n 69.64367653654656\n ],\n [\n -156.92293613032413,\n 71.06154516351532\n ],\n [\n -161.14168613032408,\n 69.02334144669882\n ],\n [\n -162.54793613032416,\n 66.21591068059402\n ],\n [\n -160.4385611303242,\n 60.99703349653922\n ],\n [\n -154.81356113032416,\n 59.246167793297815\n ],\n [\n -142.86043613032396,\n 60.3078521983613\n ],\n [\n -136.18074863032396,\n 57.11530816731394\n ],\n [\n -133.544029880324,\n 53.82977420960461\n ],\n [\n -129.86560219966944,\n 54.047086800415855\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"14","issue":"6","noUsgsAuthors":false,"publicationDate":"2023-06-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Frevol, S.A.","contributorId":331192,"corporation":false,"usgs":false,"family":"Frevol","given":"S.A.","email":"","affiliations":[{"id":49963,"text":"Université Paris-Saclay","active":true,"usgs":false}],"preferred":false,"id":886897,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"MacNulty, D. R.","contributorId":331193,"corporation":false,"usgs":false,"family":"MacNulty","given":"D.","email":"","middleInitial":"R.","affiliations":[{"id":79147,"text":"Idaho State U.","active":true,"usgs":false}],"preferred":false,"id":886898,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anderson, M. C.","contributorId":192450,"corporation":false,"usgs":false,"family":"Anderson","given":"M.","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":886899,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cluff, H. D.","contributorId":251696,"corporation":false,"usgs":false,"family":"Cluff","given":"H.","email":"","middleInitial":"D.","affiliations":[{"id":50376,"text":"Government of the Northwest Territories","active":true,"usgs":false}],"preferred":false,"id":886900,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mech, L. David 0000-0003-3944-7769 david_mech@usgs.gov","orcid":"https://orcid.org/0000-0003-3944-7769","contributorId":2518,"corporation":false,"usgs":true,"family":"Mech","given":"L.","email":"david_mech@usgs.gov","middleInitial":"David","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":886901,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Musiani, M.","contributorId":331194,"corporation":false,"usgs":false,"family":"Musiani","given":"M.","email":"","affiliations":[{"id":16660,"text":"University of Calgary","active":true,"usgs":false}],"preferred":false,"id":886902,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70244308,"text":"70244308 - 2023 - Roles of climatic and anthropogenic factors in shaping Holocene vegetation and fire regimes in Great Dismal Swamp, eastern USA","interactions":[],"lastModifiedDate":"2023-06-13T12:07:50.607357","indexId":"70244308","displayToPublicDate":"2023-06-03T07:03:00","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3219,"text":"Quaternary Science Reviews","active":true,"publicationSubtype":{"id":10}},"title":"Roles of climatic and anthropogenic factors in shaping Holocene vegetation and fire regimes in Great Dismal Swamp, eastern USA","docAbstract":"

The Great Dismal Swamp wetland, spanning >400 km2 along the Virginia and North Carolina border, was shaped by a complex combination of geomorphic, climatic, and anthropogenic forcings during the last 14,000 years. Pollen, macrofossils, charcoal, and physical properties from sediment cores at seven sites provide a detailed record of the spatial heterogeneity of the wetland and the roles played by natural hydrologic variability, wildfire, and human modification of drainage in shaping vegetation and habitats. Cold-temperate forests occupied regional uplands from at least 13.5–10.3 cal ka BP. Marshes dominated by grasses and other herbaceous taxa began developing along low-elevation streams as early as 10.3 cal ka BP, resulting in accumulation of organic silts. Long-hydroperiod, peat accumulating marshes, with abundant floating aquatic plants, developed as early as 9.6 cal ka BP, as rapid rates of sea-level rise elevated the water table and facilitated wetland development and peat accumulation along stream courses. By the mid-Holocene (c. 7–6.5 cal ka BP), when local sea-level rise began slowing and reached about 12–15 m below present, shorter hydroperiod, peat-accumulating marshes dominated the landscape, with increased wildfire activity. Great Dismal Swamp vegetation shifted from marshes to peat-accumulating forested wetlands by c. 3.7 cal ka BP; these were dominated by varying combinations of Nyssa (tupelo), Taxodium (cypress), and Chamaecyparis thyoides (Atlantic white cedar). Wildfires were infrequent during this time, and the forested wetlands persisted, with minor compositional changes related to climate-driven fluctuations in stream flow, until colonial ditching and logging began in the swamp during the late 18th century. These activities decreased cypress and cedar populations, and, by the mid-20th century, expanded ditching resulted in even drier conditions and expansion of maple-gum (dominated by Acer and Liquidambar), and pine-pocosin (dominated by Pinus) forests. The distribution of these forests differs from that of the late Holocene and represents a fundamental shift in hydrology, peat structure, vegetation, and fire regime due to landscape alterations of the last few centuries.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.quascirev.2023.108153","usgsCitation":"Willard, D., Jones, M.C., Alder, J.R., Fastovich, D., Hoefke, K., Poirier, R., and Wurster, F.C., 2023, Roles of climatic and anthropogenic factors in shaping Holocene vegetation and fire regimes in Great Dismal Swamp, eastern USA: Quaternary Science Reviews, v. 311, 108153, 20 p., https://doi.org/10.1016/j.quascirev.2023.108153.","productDescription":"108153, 20 p.","ipdsId":"IP-143520","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":443207,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.quascirev.2023.108153","text":"Publisher Index Page"},{"id":418047,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina, Virginia","otherGeospatial":"Great Dismal Swamp","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -76.64913661063176,\n 36.87216995919957\n ],\n [\n -76.64913661063176,\n 36.36536334591281\n ],\n [\n -76.27576165195242,\n 36.36536334591281\n ],\n [\n -76.27576165195242,\n 36.87216995919957\n ],\n [\n -76.64913661063176,\n 36.87216995919957\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"311","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Willard, Debra A. 0000-0003-4878-0942","orcid":"https://orcid.org/0000-0003-4878-0942","contributorId":269840,"corporation":false,"usgs":true,"family":"Willard","given":"Debra A.","affiliations":[],"preferred":true,"id":875318,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jones, Miriam C. 0000-0002-6650-7619","orcid":"https://orcid.org/0000-0002-6650-7619","contributorId":257239,"corporation":false,"usgs":true,"family":"Jones","given":"Miriam","email":"","middleInitial":"C.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":875319,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Alder, Jay R. 0000-0003-2378-2853 jalder@usgs.gov","orcid":"https://orcid.org/0000-0003-2378-2853","contributorId":5118,"corporation":false,"usgs":true,"family":"Alder","given":"Jay","email":"jalder@usgs.gov","middleInitial":"R.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":875320,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fastovich, David","contributorId":225614,"corporation":false,"usgs":false,"family":"Fastovich","given":"David","email":"","affiliations":[],"preferred":false,"id":875321,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hoefke, Kristen 0000-0001-7690-8726 khoefke@usgs.gov","orcid":"https://orcid.org/0000-0001-7690-8726","contributorId":220877,"corporation":false,"usgs":true,"family":"Hoefke","given":"Kristen","email":"khoefke@usgs.gov","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":875322,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Poirier, Robert 0000-0001-5380-4545","orcid":"https://orcid.org/0000-0001-5380-4545","contributorId":261201,"corporation":false,"usgs":true,"family":"Poirier","given":"Robert","email":"","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":875323,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wurster, Fred C.","contributorId":306267,"corporation":false,"usgs":false,"family":"Wurster","given":"Fred","email":"","middleInitial":"C.","affiliations":[{"id":66391,"text":"Great Dismal Swamp NWR","active":true,"usgs":false}],"preferred":false,"id":875324,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70233516,"text":"sir20225036 - 2023 - Groundwater availability, geochemistry, and flow pathways to public-supply wells in the Atlantic Coastal Plain and bedrock aquifers, Aiken County and part of Lexington County, South Carolina, 2015–2019","interactions":[],"lastModifiedDate":"2026-03-06T21:16:33.895313","indexId":"sir20225036","displayToPublicDate":"2023-06-02T14:30:00","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-5036","displayTitle":"Groundwater Availability, Geochemistry, and Flow Pathways to Public-Supply Wells in the Atlantic Coastal Plain and Bedrock Aquifers, Aiken County and Part of Lexington County, South Carolina, 2015–2019","title":"Groundwater availability, geochemistry, and flow pathways to public-supply wells in the Atlantic Coastal Plain and bedrock aquifers, Aiken County and part of Lexington County, South Carolina, 2015–2019","docAbstract":"

Between 2015 and 2019, the U.S. Geological Survey (USGS) studied concerns related to projected increases in demand for groundwater, in collaboration with municipal water providers and county managers within the study area, Aiken County and part of Lexington County, South Carolina. A three-dimensional (3D), numerical groundwater-flow model of the Atlantic Coastal Plain (ACP) aquifers, confining units, and the underlying bedrock aquifer in the study area was constructed using the USGS software program MODFLOW–NWT in conjunction with a groundwater-recharge model using the Soil-Water-Balance (SWB) model. Water budgets for dry (2012) and wet (2015) year conditions, future (2017–2065) groundwater-demand scenarios based on general circulation models (GCMs) of future climates, and future agricultural irrigation demands were simulated. Overall, the GCMs projected increased recharge rates. Simulation of projected increased demand on groundwater by agriculture irrigation indicated little drawdown in the study area.

Groundwater-quality samples were collected from representative public-supply wells (PSWs) and analyzed in the field and laboratory. In general, the groundwater in the ACP aquifers is acidic, dilute, and oxic. Conversely, groundwater in the bedrock aquifer was of neutral pH, mineralized, and anoxic. Total-radium concentrations across all PSWs ranged from 0.55 to 6.69 picocuries per liter (pCi/L). Groundwater from some PSWs contained detectable but low concentrations of commonly and historically used volatile organic compounds, such as chloroform, methyl tert-butyl ether (MTBE), cis-1,2-dichloroethylene (cis-1,2-DCE), 1,1-dichloroethane (1,1-DCA), and 1,1-dichloroethylene (1,1-DCE). The stable isotopes of groundwater sampled from all wells indicate the possibility that groundwater from the bedrock aquifer may discharge into the ACP. Finally, groundwater age-dating results and MODPATH simulations indicate recharge between the 1950s and 1980s for PSWs in the ACP and recharge between the 1940s and 1950s for PSWs in bedrock. Maximum groundwater-flow pathways ranged from 270 to 7,470 feet, with the longest simulated-flow pathway for wells pumped at higher rates.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225036","collaboration":"Prepared in cooperation with Aiken County, City of Aiken, Breezy Hill Water and Sewer Company, Inc., Gilbert-Summit Rural Water District, and Montmorenci-Couchton Water & Sewer District, Inc.","programNote":"Water Availability and Use Science Program","usgsCitation":"Campbell, B.G., and Landmeyer, J.E., 2023, Groundwater availability, geochemistry, and flow pathways to public-supply wells in the Atlantic Coastal Plain and bedrock aquifers, Aiken County and part of Lexington County, South Carolina, 2015–2019: U.S. Geological Survey Scientific Investigations Report 2022–5036, 117 p., https://doi.org/10.3133/sir20225036.","productDescription":"Report: xiv, 117 p.; Data Release","numberOfPages":"117","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-111003","costCenters":[{"id":13634,"text":"South Atlantic Water Science 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Director, South Atlantic Water Science Center
U.S. Geological Survey
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Norcross, GA 30093

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","tableOfContents":"","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2023-06-02","noUsgsAuthors":false,"publicationDate":"2023-06-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Campbell, Bruce G. 0000-0003-4800-6674 bcampbel@usgs.gov","orcid":"https://orcid.org/0000-0003-4800-6674","contributorId":995,"corporation":false,"usgs":true,"family":"Campbell","given":"Bruce","email":"bcampbel@usgs.gov","middleInitial":"G.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true}],"preferred":true,"id":847327,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Landmeyer, James E. 0000-0002-5640-3816","orcid":"https://orcid.org/0000-0002-5640-3816","contributorId":216137,"corporation":false,"usgs":true,"family":"Landmeyer","given":"James","email":"","middleInitial":"E.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":847328,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70245133,"text":"70245133 - 2023 - Evaluating pharmaceuticals and other organic contaminants in the Lac du Flambeau Chain of Lakes using risk-based screening techniques","interactions":[],"lastModifiedDate":"2023-06-16T12:02:15.345932","indexId":"70245133","displayToPublicDate":"2023-06-02T06:58:42","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating pharmaceuticals and other organic contaminants in the Lac du Flambeau Chain of Lakes using risk-based screening techniques","docAbstract":"

In an investigation of pharmaceutical contamination in the Lac du Flambeau Chain of Lakes (hereafter referred to as “the Chain”), few contaminants were detected; only eight pharmaceuticals and one pesticide were identified among the 110 pharmaceuticals and other organic contaminants monitored in surface water samples. This study, conducted in cooperation with the Lac du Flambeau Tribe’s Water Resource Program, investigated these organic contaminants and potential biological effects in channels connecting lakes throughout the Chain, including the Moss Lake Outlet site, adjacent to the wastewater treatment plant lagoon. Of the 6 sites monitored and 24 samples analyzed, sample concentrations and contaminant detection frequencies were greatest at the Moss Lake Outlet site; however, the concentrations and detection frequencies of this study were comparable to other pharmaceutical investigations in basins with similar characteristics. Because established water-quality benchmarks do not exist for the pharmaceuticals detected in this study, alternative screening-level water-quality benchmarks, developed using two U.S. Environmental Protection Agency toxicological resources (ToxCast database and ECOTOX knowledgebase), were used to estimate potential biological effects associated with the observed contaminant concentrations. Two contaminants (caffeine and thiabendazole) exceeded the prioritization threshold according to ToxCast alternative benchmarks, and four contaminants (acetaminophen, atrazine, caffeine, and carbamazepine) exceeded the prioritization threshold according to ECOTOX alternative benchmarks. Atrazine, an herbicide, was the most frequently detected contaminant (79% of samples), and it exhibited the strongest potential for biological effects due to its high estimated potency. Insufficient toxicological information within ToxCast and ECOTOX for gabapentin and methocarbamol (which had the two greatest concentrations in this study) precluded alternative benchmark development. This data gap presents unknown potential environmental impacts. Future research examining the biological effects elicited by these two contaminants as well as the others detected in this study would further elucidate the ecological relevance of the water chemistry results generated though this investigation.

","language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pone.0286571","usgsCitation":"Pronschinske, M.A., Corsi, S., and Hockings, C., 2023, Evaluating pharmaceuticals and other organic contaminants in the Lac du Flambeau Chain of Lakes using risk-based screening techniques: PLoS ONE, v. 18, no. 6, e0286571, 20 p., https://doi.org/10.1371/journal.pone.0286571.","productDescription":"e0286571, 20 p.","ipdsId":"IP-145547","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":443217,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0286571","text":"Publisher Index Page"},{"id":418153,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Lac du Flambeau Chain of Lakes","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -90.03024621076904,\n 46.03671796981226\n ],\n [\n -90.03024621076904,\n 45.85440934115081\n ],\n [\n -89.69256150549272,\n 45.85440934115081\n ],\n [\n -89.69256150549272,\n 46.03671796981226\n ],\n [\n -90.03024621076904,\n 46.03671796981226\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"18","issue":"6","noUsgsAuthors":false,"publicationDate":"2023-06-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Pronschinske, Matthew A. 0000-0001-9787-4545 mpronschinske@usgs.gov","orcid":"https://orcid.org/0000-0001-9787-4545","contributorId":295961,"corporation":false,"usgs":true,"family":"Pronschinske","given":"Matthew","email":"mpronschinske@usgs.gov","middleInitial":"A.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":875631,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Corsi, Steven R. 0000-0003-0583-5536 srcorsi@usgs.gov","orcid":"https://orcid.org/0000-0003-0583-5536","contributorId":172002,"corporation":false,"usgs":true,"family":"Corsi","given":"Steven R.","email":"srcorsi@usgs.gov","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":875632,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hockings, Celeste","contributorId":204077,"corporation":false,"usgs":false,"family":"Hockings","given":"Celeste","email":"","affiliations":[{"id":36828,"text":"Natural Resource Department, Lac du Flambeau Band of Lake Superior Chippewa Indians","active":true,"usgs":false}],"preferred":false,"id":875633,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70244058,"text":"ofr20231023 - 2023 - Calibration of the Trinity River Stream Salmonid Simulator (S3) with extension to the Klamath River, California, 2006–17","interactions":[],"lastModifiedDate":"2023-09-18T19:50:01.76388","indexId":"ofr20231023","displayToPublicDate":"2023-06-02T06:56:34","publicationYear":"2023","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":"2023-1023","displayTitle":"Calibration of the Trinity River Stream Salmonid Simulator (S3) with Extension to the Klamath River, California, 2006–17","title":"Calibration of the Trinity River Stream Salmonid Simulator (S3) with extension to the Klamath River, California, 2006–17","docAbstract":"

The Trinity River is managed in two sections: (1) the upper 64-kilometer (km) “restoration reach” downstream from Lewiston Dam and (2) the 120-km lower Trinity River downstream from the restoration reach. The Stream Salmonid Simulator (S3) has been previously constructed and calibrated for the restoration reach. In this report, we extended and parameterized S3 for the 120-km section of the lower Trinity River to the confluence with the Klamath River and then to the Pacific Ocean in northern California.

S3 is a deterministic life-stage structured-population model that tracks daily growth, movement, and survival of juvenile salmon. A key theme of the model is that river discharge affects habitat availability and capacity, which in turn drives density-dependent population dynamics. To explicitly link population dynamics to habitat quality and quantity, the river environment is constructed as a one-dimensional series of linked habitat units, each of which has an associated daily timeseries of discharge, water temperature, and useable habitat area or carrying capacity. In turn, the physical characteristics of each habitat unit and the number of fish occupying each unit drive (1) survival and growth within each habitat unit and (2) movement of fish among habitat units.

The physical template of the Trinity River was formed by classifying the river into 910 meso-habitat units that were designated into runs, riffles, or pools. For each habitat unit, we developed a timeseries of daily discharge, water temperature, amount of available spawning habitat, and fry and parr carrying capacity. Capacity timeseries were constructed using state-of-the-art models of spatially explicit hydrodynamics and quantitative fish habitat relationships developed for the Trinity River. These variables were then used to drive population dynamics such as egg maturation and survival, and in turn, juvenile movement, growth, and survival.
We estimated key movement and survival parameters by calibrating the model to 12 years (2007–18) of weekly juvenile abundance estimates from two rotary screw traps: (1) the Pear Tree trap near the downstream end of the restoration reach and (2) the Willow Creek trap site is about 40.2 km upriver from the Trinity River’s confluence with the Klamath River. The calibration consisted of replicating historical conditions as closely as possible (for example: flow, temperature, spawner abundance, spawning location and timing, and hatchery releases), and then running the model to predict weekly abundance passing the trap location. We also evaluated four alternative model structures that included either no density-dependence, density-independent movement and survival, density-dependent survival, or density-dependent movement. Akaike information criterion model selection was used to evaluate the strength of evidence for alternative model structures to simulate the observed abundance estimates.

Model selection supported the conclusion that the fully density-dependent model and density-dependent survival model was better supported by the data than the no density-dependence or density-dependent movement model. Because density-dependent movement was favored in past evaluations, we focus on the results from the fully density-dependent model. Parameter estimates from this model indicated that fry were less likely than parr to move downstream and that fry moved slower. Fry had a lower daily survival probability than parr. In contrast, hatchery fish had the highest probability of movement and the lowest daily survival probability.

Fitting the model to both traps individually enabled us to independently compare the fit and performance of S3 at simulating fish abundance, timing, and growth of juvenile salmon in the upper restoration reach and lower Trinity River. We obtained a better fit to the data at the Willow Creek trap site than we obtained at the Pear Tree trap site, regardless of whether we fit the model to the abundances at the Pear Tree trap or Willow Creek trap. This better fit was surprising given that the S3 input data for the upper restoration reach required fewer assumptions than fitting to the Willow Creek trap site that is farther down river. Fitting S3 to weekly abundances at the Willow Creek trap site required making assumptions about (1) extrapolating capacity-flow relationships to unmeasured habitat units; (2) spatially allocating spawners within the lower Trinity River; and (3) approximating the abundance, timing, and size of juveniles entering from tributaries. The model provided better fit to the data at the Willow Creek trap site. In the weekly abundance estimates, in relation to the S3 simulated abundances, several migration years’ (2011, 2015–17) weekly abundance estimates appeared truncated and were near or at peak annual abundances in January, suggesting that a large fraction of juveniles was migrating as early as December at the Pear Tree trap site. Some early life dynamics may not be currently incorporated into S3. For example, the estimation of abundance at the Pear Tree trap may be biased because of size selectivity. Knowing about selectivity at the Pear Tree trap could greatly improve S3’s ability to predict weekly and peak abundances each year.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231023","usgsCitation":"Plumb, J.M., Perry, R.W., Som, N.A., Goodman, D.H., Martin, A.C., Alvarez, J.S., and Hetrick, N.J., 2023, Calibration of the Trinity River Stream Salmonid Simulator (S3) with extension to the Klamath River, California, 2006–17: U.S. Geological Survey Open-File Report 2023–1023, 44 p., https://doi.org/10.3133/ofr20231023.","productDescription":"vi, 44 p.","onlineOnly":"Y","ipdsId":"IP-138474","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":417617,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1023/ofr20231023.XML"},{"id":417615,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231023/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2023-1023"},{"id":417614,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1023/ofr20231023.pdf","text":"Report","size":"7.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023-1023"},{"id":417613,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1023/coverthb.jpg"},{"id":417616,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1023/images"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -124.56822822318722,\n 42.000867977436485\n ],\n [\n -124.56822822318722,\n 40.34781901689766\n ],\n [\n -122.02049321102055,\n 40.34781901689766\n ],\n [\n -122.02049321102055,\n 42.000867977436485\n ],\n [\n -124.56822822318722,\n 42.000867977436485\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"

Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115-5016

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