Drinking water supply wells can be contaminated by a broad range of waterborne pathogens. However, groundwater assessments frequently measure microbial indicators or a single pathogen type, which provides a limited characterization of potential health risk. This study assessed contamination of wells by testing for viral, bacterial, and protozoan pathogens and fecal markers. Wells supplying groundwater to community and noncommunity public water systems in Minnesota, USA (n = 145) were sampled every other month over one or two years and tested using 23 qPCR assays. Eighteen genetic targets were detected at least once, and microbiological contamination was widespread (96% of 145 wells, 58% of 964 samples). The sewage-associated microbial indicators HF183 and pepper mild mottle virus were detected frequently. Human or zoonotic pathogens were detected in 70% of wells and 21% of samples by qPCR, with Salmonella and Cryptosporidium detected more often than viruses. Samples positive by qPCR for adenovirus (HAdV), enterovirus, or Salmonella were analyzed by culture and for genotype or serotype. qPCR-positive Giardia and Cryptosporidium samples were analyzed by immunofluorescent assay (IFA), and IFA and qPCR concentrations were correlated. Comparisons of indicator and pathogen occurrence at the time of sampling showed that total coliforms, HF183, and Bacteroidales-like HumM2 had high specificity and negative predictive values but generally low sensitivity and positive predictive values. Pathogen-HF183 ratios in sewage have been used to estimate health risks from HF183 concentrations in surface water, but in our groundwater samples Cryptosporidium oocyst:HF183 and HAdV:HF183 ratios were approximately 10,000 times higher than ratios reported for sewage. qPCR measurements provided a robust characterization of microbiological water quality, but interpretation of qPCR data in a regulatory context is challenging because few studies link qPCR measurements to health risk.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.watres.2020.115814","collaboration":"","usgsCitation":"Stokdyk, J.P., Firnstahl, A.D., Walsh, J.F., Spencer, S.K., de Lambert, J.R., Anderson, A., Rezania, L.W., Kieke, B.A., and Borchardt, M.A., 2020, Viral, bacterial, and protozoan pathogens and fecal markers in wells supplying groundwater to public water systems in Minnesota, USA: Water Research, v. 178, 115814, 10 p., https://doi.org/10.1016/j.watres.2020.115814.","productDescription":"115814, 10 p.","ipdsId":"IP-114409","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":374158,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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Water Science Center","active":true,"usgs":true}],"preferred":true,"id":787507,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Walsh, James F.","contributorId":214333,"corporation":false,"usgs":false,"family":"Walsh","given":"James","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":787508,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Spencer, Susan K.","contributorId":210972,"corporation":false,"usgs":false,"family":"Spencer","given":"Susan","email":"","middleInitial":"K.","affiliations":[{"id":38162,"text":"United States Department of Agriculture Agricultural Research Service","active":true,"usgs":false}],"preferred":false,"id":787509,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"de Lambert, Jane R.","contributorId":214334,"corporation":false,"usgs":false,"family":"de 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0000-0002-6471-2627","orcid":"https://orcid.org/0000-0002-6471-2627","contributorId":151033,"corporation":false,"usgs":false,"family":"Borchardt","given":"Mark","email":"","middleInitial":"A.","affiliations":[{"id":6684,"text":"USDA Forest Service, Southern Research Station, Aiken, SC","active":true,"usgs":false}],"preferred":false,"id":787514,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70206370,"text":"ofr20191115 - 2020 - A decision framework to analyze tide-gate options for restoration of the Herring River Estuary, Massachusetts","interactions":[],"lastModifiedDate":"2024-03-04T19:21:20.997009","indexId":"ofr20191115","displayToPublicDate":"2020-04-10T09:00:00","publicationYear":"2020","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":"2019-1115","displayTitle":"A Decision Framework to Analyze Tide-Gate Options for Restoration of the Herring River Estuary, Massachusetts","title":"A decision framework to analyze tide-gate options for restoration of the Herring River Estuary, Massachusetts","docAbstract":"The collective set of decisions involved with the restoration of degraded wetlands is often more complex than considering only ecological responses and outcomes. Restoration is commonly driven by a complex interaction of social, economic, and ecological factors representing the mandate of resource stewards and the values of stakeholders. The authors worked with the Herring River Restoration Committee (HRRC) to develop a decision framework to understand the implications of complex tradeoffs and to guide decision making for the restoration of the 1,100-acre Herring River estuary within Cape Cod National Seashore, which has been restricted from tidal influence for more than 100 years. The HRRC represents decision maker and stakeholder interests in the restoration process. For a 25-year planning horizon, decisions involve the rate at which newly constructed water-control structures allow tidal exchange, and the timing and location of implementing numerous secondary management options. Decisions affect multiple stakeholders, including residents of two adjacent towns who value the watershed for numerous benefits and whose economy relies on seasonal activities and aquaculture. System response to management decisions is characterized by a high degree of uncertainty and risk with positive and negative outcomes possible. Decision policies will affect biophysical (for example, sediment transport, discharge of fecal coliform bacteria) and ecological (for example, vegetation response, fish passage, effects on shellfish) processes, as well as socioeconomic interests (for example, effects on property, viewscapes, recreation). The framework provides a structured approach for evaluating tradeoffs among multiple objectives (ecological and social) while appropriately characterizing relevant uncertainties and accounting for levels of risk tolerances and the values of decision makers and stakeholders. Consequences of tide-gate management options are predicted using a range of methods from quantitative physical process models to elicited expert judgement. The decision framework is presented, and the software developed to implement the tradeoff analysis is introduced. The results from an initial prototype analysis using a software application developed for analyses of tradeoffs and of sensitivity of the decision to risk and uncertainty are presented. The next step is to use the decision-support application to analyze options using improved predictions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191115","collaboration":"Prepared in cooperation with National Park Service and U.S. Fish and Wildlife Service","usgsCitation":"Smith, D.R., Eaton, M.J., Gannon, J.J., Smith, T.P., Derleth, E.L., Katz, J., Bosma, K.F., and Leduc, E., 2020, A decision framework to analyze tide-gate options for restoration of the Herring River Estuary, Massachusetts: U.S. Geological Survey Open-File Report 2019–1115, 42 p., https://doi.org/10.3133/ofr20191115.","productDescription":"viii, 42 p.","numberOfPages":"54","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-101813","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":373779,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1115/ofr20191115.pdf","text":"Report","size":"3.52 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1115"},{"id":373778,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1115/coverthb.jpg"}],"country":"United States","state":"Massachusetts","otherGeospatial":"Herring River Estuary","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -70.07286071777344,\n 41.92961289444422\n ],\n [\n -70.02462387084961,\n 41.92961289444422\n ],\n [\n -70.02462387084961,\n 41.96357478222518\n ],\n [\n -70.07286071777344,\n 41.96357478222518\n ],\n [\n -70.07286071777344,\n 41.92961289444422\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Eastern Ecological Science Center
U.S. Geological Survey
11649 Leetown Road
Kearneysville, WV 25430
Volcanic eruptions can affect landscapes in many ways and consequently alter erosion and the fluxes of water and sediment. Hydrologic and geomorphic responses to volcanic disturbances are varied in both space and time, and, in some instances, can persist for decades to centuries. Understanding the broad context of how landscapes respond to eruptions can help inform how they may evolve, and therefore provides context for managing and mitigating hazards associated with future volcanic and hydrologic events. Here, we assess the geomorphic evolution of the upper North Fork Toutle River valley, the valley most heavily affected by the Mount St. Helens May 18 and later 1980s eruptions. By doing so, we provide context for the landscape changes caused by the eruptions as they relate to potential hydrological hazards associated with Spirit Lake, an iconic landform at the northern foot of the volcano. The Spirit Lake basin was transformed by the cataclysmic 1980 eruption and had its outlet blocked. The analyses presented provide context for considerations of potential outlets for Spirit Lake, a landform which might be viewed as a “sleeping giant” on this landscape: a giant capable of causing catastrophic downstream consequences if water is released uncontrollably from the lake.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205027","collaboration":"Prepared in cooperation with the U.S. Department of Agriculture, U.S. Forest Service, Gifford Pinchot National Forest","usgsCitation":"Major, J.J., Grant, G.E., Sweeney, K., and Mosbrucker, A.R., 2020, A multidecade analysis of fluvial geomorphic evolution of the Spirit Lake blockage, Mount St. Helens, Washington: U.S. Geological Survey Scientific Investigations Report 2020-5027, 54 p., https://doi.org/10.3133/sir20205027.","productDescription":"vii, 54 p.","onlineOnly":"Y","ipdsId":"IP-109211","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":373866,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5027/sir20205027.pdf","text":"Report","size":"9.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5027"},{"id":373905,"rank":3,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/sir/2020/5027/sir20205027_SupplementalDataFile_DF1.xlsx","text":"Supplemental data file DF1","size":"1.9 MB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2020-5027 Supplemental Data File DF1","linkHelpText":"Estimated long-term daily flow hydrology from North Fork Toutle River, WA, below SRS"},{"id":373865,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5027/coverthb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Mount St. Helens","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.36984252929688,\n 46.081804301792545\n ],\n [\n -122.01965332031249,\n 46.081804301792545\n ],\n [\n -122.01965332031249,\n 46.39998810407942\n ],\n [\n -122.36984252929688,\n 46.39998810407942\n ],\n [\n -122.36984252929688,\n 46.081804301792545\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Volcano Science Center
Cascades Volcano Observatory
U.S. Geological Survey
1300 SE Cardinal Court
Vancouver, WA, 98683
The Vermont Department of Health and the U.S. Geological Survey analyzed the concentrations of chloride in groundwater samples collected from 4,319 domestic wells across Vermont between 2011 and 2018. Ninety of these wells were sampled twice and the remaining 4,229 were sampled once. This sample size represents approximately 4 percent of all wells in the State of Vermont. More than half of the wells sampled statewide had groundwater chloride concentrations less than 5 milligrams per liter, whereas more than 1 percent had groundwater concentrations greater than 250 milligrams per liter. Statistical analysis of this dataset revealed distinct patterns in the distribution of chloride in domestic wells. Wells closer (less than 100 meters) to a paved road had significantly higher concentrations of chloride than wells farther ( more than 100 meters) away. Also, wells in urban and in high population density areas, particularly Chittenden and Grand Isle Counties, had significantly higher concentrations of chloride and exhibited greater change in concentrations of chloride over time than wells in less populated areas. This evaluation addresses the distribution of chloride concentrations across the State, which may have adverse health impacts from water infrastructure corrosion and implications for deicing salt application at the State and local levels.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191148","collaboration":"Prepared in cooperation with the Vermont Department of Health","usgsCitation":"Levitt, J.P., and Larsen, S.L., 2020, Groundwater chloride concentrations in domestic wells and proximity to roadways in Vermont, 2011–2018: U.S. Geological Survey Open-File Report 2019–1148, 12 p., https://doi.org/10.3133/ofr20191148.","productDescription":"Report: 12 p.; Data Release","numberOfPages":"12","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-104230","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":373835,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1148/ofr20191148.pdf","text":"Report","size":"77.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1148"},{"id":373355,"rank":3,"type":{"id":30,"text":"Data 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\"}}]}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
Because groundwater recharge in dry regions is generally low, arid and semiarid environments have been considered well‐suited for long‐term isolation of hazardous materials (e.g., radioactive waste). In these dry regions, water lost (transpired) by plants and evaporated from the soil surface, collectively termed evapotranspiration (ET), is usually the primary discharge component in the water balance. Therefore, vegetation can potentially affect groundwater flow and contaminant transport at waste disposal sites. We studied vegetation health and ET dynamics at a Uranium Mill Tailings Radiation Control Act (UMTRCA) disposal site in Shiprock, New Mexico, where a floodplain alluvial aquifer was contaminated by mill effluent. Vegetation on the floodplain was predominantly deep‐rooted, non‐native tamarisk shrubs (Tamarix sp.). After the introduction of the tamarisk beetle (Diorhabda sp.) as a biocontrol agent, the health of the invasive tamarisk on the Shiprock floodplain declined. We used Landsat normalized difference vegetation index (NDVI) data to measure greenness and a remote sensing algorithm to estimate landscape‐scale ET along the floodplain of the UMTRCA site in Shiprock prior to (2000–2009) and after (2010–2018) beetle establishment. Using groundwater level data collected from 2011 to 2014, we also assessed the role of ET in explaining seasonal variations in depth to water of the floodplain. Growing season scaled NDVI decreased 30% (p < .001), while ET decreased 26% from the pre‐ to post‐beetle period and seasonal ET estimates were significantly correlated with groundwater levels from 2011 to 2014 (r2 = .71; p = .009). Tamarisk greenness (a proxy for health) was significantly affected by Diorhabda but has partially recovered since 2012. Despite this, increased ET demand in the summer/fall period might reduce contaminant transport to the San Juan River during this period.
","language":"English","publisher":"Wiley","doi":"10.1002/hyp.13772","usgsCitation":"Jarchow, C.J., Waugh, W.J., Didan, K., Barreto-Munoz, A., Herrmann, S.M., and Nagler, P.L., 2020, Vegetation‐groundwater dynamics at a former uranium mill site following invasion of a biocontrol agent: A time series analysis of Landsat normalized difference vegetation index data: Hydrological Processes, v. 34, no. 12, p. 2739-2749, https://doi.org/10.1002/hyp.13772.","productDescription":"11 p.","startPage":"2739","endPage":"2749","ipdsId":"IP-112673","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":489705,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/hyp.13772","text":"Publisher Index Page"},{"id":378391,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","city":"Shiprock","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.71383666992188,\n 36.766667073939736\n ],\n [\n -108.66302490234375,\n 36.766667073939736\n ],\n [\n -108.66302490234375,\n 36.806261006694555\n ],\n [\n -108.71383666992188,\n 36.806261006694555\n ],\n [\n -108.71383666992188,\n 36.766667073939736\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"34","issue":"12","noUsgsAuthors":false,"publicationDate":"2020-04-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Jarchow, Christopher J. 0000-0002-0424-4104 cjarchow@usgs.gov","orcid":"https://orcid.org/0000-0002-0424-4104","contributorId":5813,"corporation":false,"usgs":true,"family":"Jarchow","given":"Christopher","email":"cjarchow@usgs.gov","middleInitial":"J.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":false,"id":798690,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Waugh, William J.","contributorId":196107,"corporation":false,"usgs":false,"family":"Waugh","given":"William","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":798691,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Didan, Kamel","contributorId":130999,"corporation":false,"usgs":false,"family":"Didan","given":"Kamel","email":"","affiliations":[{"id":7204,"text":"University of Arizona, Electrical and Computer Engineering","active":true,"usgs":false}],"preferred":false,"id":798692,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barreto-Munoz, Armando","contributorId":131000,"corporation":false,"usgs":false,"family":"Barreto-Munoz","given":"Armando","email":"","affiliations":[{"id":7204,"text":"University of Arizona, Electrical and Computer Engineering","active":true,"usgs":false}],"preferred":false,"id":798693,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Herrmann, Stefanie M. 0000-0002-4069-2019","orcid":"https://orcid.org/0000-0002-4069-2019","contributorId":20234,"corporation":false,"usgs":true,"family":"Herrmann","given":"Stefanie","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":798694,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nagler, Pamela L. 0000-0003-0674-103X pnagler@usgs.gov","orcid":"https://orcid.org/0000-0003-0674-103X","contributorId":1398,"corporation":false,"usgs":true,"family":"Nagler","given":"Pamela","email":"pnagler@usgs.gov","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":798634,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70209557,"text":"70209557 - 2020 - Testing ecosystem accounting in the United States: A case study for the Southeast","interactions":[],"lastModifiedDate":"2020-09-01T19:55:33.306925","indexId":"70209557","displayToPublicDate":"2020-04-08T07:05:35","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1477,"text":"Ecosystem Services","active":true,"publicationSubtype":{"id":10}},"title":"Testing ecosystem accounting in the United States: A case study for the Southeast","docAbstract":"Ecosystem accounts, as formalized by the System of Environmental-Economic Accounting Experimental Ecosystem Accounts (SEEA EEA), have been compiled in a number of countries, yet there have been few attempts to develop them for the U.S. We explore the potential for U.S. ecosystem accounting by compiling ecosystem extent, condition, and ecosystem services supply and use accounts for a ten-state region in the Southeast. The pilot accounts address air quality, water quality, biodiversity, carbon storage, recreation, and pollination for selected years from 2001 to 2015. Results illustrate how information from ecosystem accounts can contribute to policy and decision-making. Using an example from Atlanta, we also show how ecosystem accounts can be considered alongside other SEEA accounts to give a more complete picture of a local area’s environmental-economic trends. The process by which we determined where to place metrics within the accounting framework, which was strongly informed by the National Ecosystem Services Classification System (NESCS), can provide guidance for future ecosystem accounts in the U.S. and other countries. Finally, we identify knowledge gaps that limit the inclusion of certain ecosystem services in the accounts and suggest future research that can close these gaps and improve future U.S. ecosystem accounts.","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecoser.2020.101099","usgsCitation":"Warnell, K., Russell, M.J., Rhodes, C., Bagstad, K.J., Olander, L.P., Nowak, D., Poudel, R., Glynn, P.D., Hass, J.L., Hiribayashi, S., Ingram, J.C., Matuszak, J., Oleson, K.L., Posner, S.M., and Villa, F., 2020, Testing ecosystem accounting in the United States: A case study for the Southeast: Ecosystem Services, v. 43, 101099, 18 p., https://doi.org/10.1016/j.ecoser.2020.101099.","productDescription":"101099, 18 p.","ipdsId":"IP-108492","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and 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\"}}]}","volume":"43","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Warnell, Katie","contributorId":224044,"corporation":false,"usgs":false,"family":"Warnell","given":"Katie","email":"","affiliations":[{"id":12643,"text":"Duke University","active":true,"usgs":false}],"preferred":false,"id":786847,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Russell, Marc J.","contributorId":191375,"corporation":false,"usgs":false,"family":"Russell","given":"Marc","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":786848,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rhodes, Charles","contributorId":211873,"corporation":false,"usgs":false,"family":"Rhodes","given":"Charles","affiliations":[{"id":38338,"text":"U.S. EPA-ORISE Fellow","active":true,"usgs":false}],"preferred":false,"id":786849,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bagstad, Kenneth J. 0000-0001-8857-5615 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L.","contributorId":211867,"corporation":false,"usgs":false,"family":"Hass","given":"Julie","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":786855,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Hiribayashi, Satoshi 0000-0003-4259-2748","orcid":"https://orcid.org/0000-0003-4259-2748","contributorId":224046,"corporation":false,"usgs":false,"family":"Hiribayashi","given":"Satoshi","email":"","affiliations":[{"id":40823,"text":"Davey Institute","active":true,"usgs":false}],"preferred":false,"id":786856,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Ingram, Jane Carter","contributorId":211862,"corporation":false,"usgs":false,"family":"Ingram","given":"Jane","email":"","middleInitial":"Carter","affiliations":[{"id":38334,"text":"Ernst and Young","active":true,"usgs":false}],"preferred":false,"id":786857,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Matuszak, John","contributorId":211869,"corporation":false,"usgs":false,"family":"Matuszak","given":"John","email":"","affiliations":[{"id":38336,"text":"U.S. Department of State","active":true,"usgs":false}],"preferred":false,"id":786858,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Oleson, Kirsten L. L. 0000-0002-7992-5051","orcid":"https://orcid.org/0000-0002-7992-5051","contributorId":211871,"corporation":false,"usgs":false,"family":"Oleson","given":"Kirsten","email":"","middleInitial":"L. L.","affiliations":[{"id":36402,"text":"University of Hawaii","active":true,"usgs":false}],"preferred":false,"id":786859,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Posner, Stephen M.","contributorId":211872,"corporation":false,"usgs":false,"family":"Posner","given":"Stephen","email":"","middleInitial":"M.","affiliations":[{"id":38335,"text":"COMPASS","active":true,"usgs":false}],"preferred":false,"id":786860,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Villa, Ferdinando 0000-0002-5114-3007","orcid":"https://orcid.org/0000-0002-5114-3007","contributorId":208486,"corporation":false,"usgs":false,"family":"Villa","given":"Ferdinando","email":"","affiliations":[{"id":32916,"text":"Basque Centre for Climate Change","active":true,"usgs":false}],"preferred":false,"id":786861,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}} ,{"id":70209466,"text":"70209466 - 2020 - Describing historical habitat use of a native fish-Cisco (Coregonus artedi)-In Lake Michigan between 1930 and 1932","interactions":[],"lastModifiedDate":"2020-07-09T14:47:53.051322","indexId":"70209466","displayToPublicDate":"2020-04-08T07:04:27","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Describing historical habitat use of a native fish-Cisco (Coregonus artedi)-In Lake Michigan between 1930 and 1932","title":"Describing historical habitat use of a native fish-Cisco (Coregonus artedi)-In Lake Michigan between 1930 and 1932","docAbstract":"With the global-scale loss of biodiversity, current restoration programs have been often required as part of conservation plans for species richness and ecosystem integrity. The restoration of pelagic-oriented cisco (Coregonus artedi) has been an interest of Lake Michigan managers because it may increase the diversity and resilience of the fish assemblages and conserve the integrity of the ecosystems in a changing environment. To inform restoration, we described historical habitat use of cisco by analyzing a unique fishery-independent dataset collected in 1930–1932 by the U.S. Bureau of Fisheries’ first research vessel Fulmar and a commercial catch dataset reported by the State of Michigan in the same period, both based on gear fished on the bottom. Our results confirmed that the two major embayments, Green Bay and Grand Traverse Bay, were important habitats for cisco and suggest that cisco could complete the entire lifecycle within either of the Bays as there was no lack of summer feeding and fall spawning habitats. Seasonally, our results showed that cisco stayed in nearshore waters in spring, migrated to offshore waters in summer, and then migrated back to nearshore waters in fall for spawning. The results also suggest that in summer, most ciscoes were in waters with bottom depths of 20–70 m, but the highest cisco density occurred in waters with a bottom depth around 40 m. We highlight the importance of embayment habitats to cisco restoration and the seasonal migration pattern of cisco identified in this study, which suggests that a restored cisco population can diversify the food web by occupying different habitats from the exotic fishes that now dominate the pelagic waters of Lake Michigan.
","language":"English","publisher":"PLoS ONE","doi":"10.1371/journal.pone.0231420","usgsCitation":"Kao, Y., Bunnell, D., Eshenroder, R.L., and Murray, D.N., 2020, Describing historical habitat use of a native fish-Cisco (Coregonus artedi)-In Lake Michigan between 1930 and 1932: PLoS ONE, v. 15, no. 4, e0231420, 21 p., https://doi.org/10.1371/journal.pone.0231420.","productDescription":"e0231420, 21 p.","ipdsId":"IP-112754","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":457149,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0231420","text":"Publisher Index Page"},{"id":437032,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9JMLWER","text":"USGS data release","linkHelpText":"1930-1932 Gill net data from Lake Michigan"},{"id":373854,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Lake Michigan","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.1875,\n 41.541477666790286\n ],\n [\n -86.46240234375,\n 41.83682786072714\n ],\n [\n -85.97900390625,\n 42.79540065303723\n ],\n [\n -86.4404296875,\n 43.67581809328341\n ],\n [\n -85.869140625,\n 44.74673324024678\n ],\n [\n -85.4736328125,\n 44.63739123445585\n ],\n [\n -84.52880859375,\n 45.82879925192134\n ],\n [\n -85.18798828125,\n 46.27103747280261\n ],\n [\n -86.0888671875,\n 46.13417004624326\n ],\n [\n -87.38525390624999,\n 45.78284835197676\n ],\n [\n -87.978515625,\n 45.01141864227728\n ],\n [\n -88.1982421875,\n 44.449467536006935\n ],\n [\n -88.06640625,\n 44.402391829093915\n ],\n [\n -87.451171875,\n 44.933696389694674\n ],\n [\n -87.099609375,\n 45.182036837015886\n ],\n [\n -87.4951171875,\n 44.512176171071054\n ],\n [\n -87.7587890625,\n 43.8028187190472\n ],\n [\n -88.00048828124999,\n 42.94033923363181\n ],\n [\n -87.890625,\n 42.407234661551875\n ],\n [\n -87.71484375,\n 41.902277040963696\n ],\n [\n -87.1875,\n 41.541477666790286\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"15","issue":"4","noUsgsAuthors":false,"publicationDate":"2020-04-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Kao, Yu-Chun","contributorId":35626,"corporation":false,"usgs":false,"family":"Kao","given":"Yu-Chun","affiliations":[{"id":6649,"text":"University of Michigan, School of Natural Resources and Environment","active":true,"usgs":false}],"preferred":false,"id":786603,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bunnell, David 0000-0003-3521-7747","orcid":"https://orcid.org/0000-0003-3521-7747","contributorId":217344,"corporation":false,"usgs":true,"family":"Bunnell","given":"David","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":786604,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Eshenroder, Randy L.","contributorId":177867,"corporation":false,"usgs":false,"family":"Eshenroder","given":"Randy","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":786605,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Murray, Devin N. 0000-0003-1429-6669","orcid":"https://orcid.org/0000-0003-1429-6669","contributorId":223909,"corporation":false,"usgs":false,"family":"Murray","given":"Devin","email":"","middleInitial":"N.","affiliations":[{"id":37387,"text":"University of Michigan","active":true,"usgs":false}],"preferred":false,"id":786606,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70206191,"text":"sir20195120 - 2020 - Rio Grande transboundary integrated hydrologic model and water-availability analysis, New Mexico and Texas, United States, and northern Chihuahua, Mexico","interactions":[{"subject":{"id":70197406,"text":"ofr20181091 - 2018 - Rio Grande transboundary integrated hydrologic model and water-availability analysis, New Mexico and Texas, United States, and Northern Chihuahua, Mexico","indexId":"ofr20181091","publicationYear":"2018","noYear":false,"title":"Rio Grande transboundary integrated hydrologic model and water-availability analysis, New Mexico and Texas, United States, and Northern Chihuahua, Mexico"},"predicate":"SUPERSEDED_BY","object":{"id":70206191,"text":"sir20195120 - 2020 - Rio Grande transboundary integrated hydrologic model and water-availability analysis, New Mexico and Texas, United States, and northern Chihuahua, Mexico","indexId":"sir20195120","publicationYear":"2020","noYear":false,"title":"Rio Grande transboundary integrated hydrologic model and water-availability analysis, New Mexico and Texas, United States, and northern Chihuahua, Mexico"},"id":1}],"lastModifiedDate":"2022-04-25T19:02:23.235988","indexId":"sir20195120","displayToPublicDate":"2020-04-07T14:58:16","publicationYear":"2020","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":"2019-5120","displayTitle":"Rio Grande Transboundary Integrated Hydrologic Model and Water-Availability Analysis, New Mexico and Texas, United States, and Northern Chihuahua, Mexico","title":"Rio Grande transboundary integrated hydrologic model and water-availability analysis, New Mexico and Texas, United States, and northern Chihuahua, Mexico","docAbstract":"Changes in population, agricultural development and practices (including shifts to more water-intensive crops), and climate variability are increasing demands on available water resources, particularly groundwater, in one of the most productive agricultural regions in the Southwest—the Rincon and Mesilla Valley parts of Rio Grande Valley, Doña Ana and Sierra Counties, New Mexico, and El Paso County, Texas. The goal of this study was to produce an integrated hydrological simulation model to help evaluate water-management strategies, including conjunctive use of surface water and groundwater for historical conditions, and to support long-term planning for the Rio Grande Project. This report describes model construction and applications by the U.S. Geological Survey, working in cooperation and collaboration with the Bureau of Reclamation.
This model, the Rio Grande Transboundary Integrated Hydrologic Model, simulates the most important natural and human components of the hydrologic system, including selected components related to variations in climate, thereby providing a reliable assessment of surface-water and groundwater conditions and processes that can inform water users and help improve planning for future conditions and sustained operations of the Rio Grande Project (RGP) by the Bureau of Reclamation. Model development included a revision of the conceptual model of the flow system, construction of a Transboundary Rio Grande Watershed Model (TRGWM) water-balance model using the Basin Characterization Model, and construction of an integrated hydrologic flow model with MODFLOW-One-Water Hydrologic Flow Model version 2 (referred to as MF-OWHM2). The hydrologic models were developed for and calibrated to historical conditions of water and land use, and parameters were adjusted so that simulated values closely matched available measurements (calibration). The calibrated model was then used to assess the use and movement of water in the Rincon Valley, Mesilla Basin, and northern part of the Conejos-Médanos Basin, with the entire region referred to as the “Transboundary Rio Grande” or TRG. These tools provide a means to understand hydrologic system response to the evolution of water use in the region, its availability, and potential operational constraints of the RGP.
The conceptual model identified surface-water and groundwater inflows and outflows that included the movement and use of water both in natural and in anthropogenic systems. The groundwater-flow system is characterized by a layered geologic sedimentary sequence combined with the effects of groundwater pumping, operation of the RGP, natural runoff and recharge, and the application of irrigation water at the land surface that is captured and reused in an extensive network of canals and drains as part of the conjunctive use of water in the region.
Historical groundwater-level fluctuations followed a cyclic pattern that were aligned with climate cycles, which collectively resulted in alternating periods of wet or dry years. Periods of drought that persisted for one or more years are associated with low surface-water availability that resulted in higher rates of groundwater-level decline. Rates of groundwater-level decline also increased during periods of agricultural intensification, which necessitated increasing use of groundwater as a source of irrigation water. Agriculture in the area was initially dominated by alfalfa and cotton, but since 1970 more water-intensive pecan orchards and vegetable production have become more common. Groundwater levels substantially declined in subregions where drier climate combined with increased demand, resulting in periods of reduced streamflows.
Most of the groundwater was recharged in the Rio Grande Valley floor, and most of the pumpage and aquifer storage depletion was in Mesilla Basin agricultural subregions. A cyclic imbalance between inflows and outflows resulted in the modeled cyclic depletion (groundwater withdrawals in excess of natural recharge) of the groundwater basin during the 75-year simulation period of 1940–2014. Changes in groundwater storage can vary considerably from year to year, depending on land use, pumpage, and climate conditions. Climatic drivers of wet and dry years can greatly affect all inflows, outflows, and water use. Although streamflow and, to a minor extent, precipitation during inter-decadal wet-year periods replenished the groundwater historically, contemporary water use and storage depletion could have reduced the effects of these major recharge events. The average net groundwater flow-rate deficit for 1953–2014 was estimated to be about 1,090 acre-feet per year.
Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
Groundwater in eastern Abu Dhabi in the United Arab Emirates is an important resource that is widely used for irrigation and domestic supplies in rural areas. The U.S. Geological Survey and the Environment Agency—Abu Dhabi cooperated on an investigation to integrate existing hydrogeologic information and to answer questions about regional groundwater resources in Abu Dhabi by developing a numerical groundwater flow model based on MODFLOW–2005 software. The groundwater flow model developed in this investigation provides an improved understanding of groundwater conditions in the eastern region of the Emirate of Abu Dhabi. The flow model simulates steady-state predevelopment conditions from before the rapid growth of modern pumping in the 1980s and was calibrated with 1,342 groundwater-level observations by use of automated and manual calibration techniques. The calibrated model provides good accuracy, with a mean error of 0.50 meters and a standard error of 5.92 meters for simulated groundwater levels. The results of the regional water budget simulation show that gap recharge, which is groundwater inflow through mountain-front gap alluvium, is the greatest source of water to the aquifer. In the base simulation scenario, gap recharge represents 80 percent of total inflow (119,470 of 149,403 cubic meters per day) and the greatest outflow from the aquifer is from evapotranspiration (93 percent of total outflow). Model scenario and sensitivity results reveal a need for data that more thoroughly and more accurately describe aquifer hydraulic conductivity, inflow to the aquifer from the Oman Mountains, and recharge from precipitation on the piedmont. Additional long-term aquifer pumping test observations would improve understanding of aquifer hydraulic conductivity, which would also improve model accuracy. Future studies can modify the model to understand the effect of land-use change and water use on groundwater supplies and simulate more complex groundwater flow conditions in a predictive mode.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185158","collaboration":"Prepared in cooperation with the Environment Agency—Abu Dhabi","usgsCitation":"Eggleston, J.R., Mack, T.J., Imes, J.L., Kress, W., Woodward, D.W., and Bright, D.J., 2020, Hydrogeologic framework and simulation of predevelopment groundwater flow, eastern Abu Dhabi Emirate, United Arab Emirates: U.S. Geological Survey Scientific Investigations Report 2018–5158, 48 p., https://doi.org/10.3133/sir20185158.","productDescription":"Report: viii, 48 p.; Data Release","numberOfPages":"60","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-088658","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":373295,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5158/coverthb.jpg"},{"id":373296,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5158/sir20185158.pdf","text":"Report","size":"6.17 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5158"},{"id":373297,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ZWZISB","text":"USGS data release","description":"USGS data release","linkHelpText":"MODFLOW-2005 Groundwater Flow Model to Simulate Predevelopment Groundwater Flow in the Eastern Abu Dhabi Emirate, United Arab Emirates"}],"country":"United Arab Emirates","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[51.57952,24.2455],[51.75744,24.29407],[51.79439,24.01983],[52.57708,24.17744],[53.40401,24.15132],[54.008,24.12176],[54.69302,24.79789],[55.43902,25.43915],[56.07082,26.05546],[56.26104,25.71461],[56.39685,24.92473],[55.88623,24.92083],[55.80412,24.2696],[55.98121,24.13054],[55.52863,23.9336],[55.52584,23.52487],[55.23449,23.11099],[55.20834,22.70833],[55.0068,22.49695],[52.00073,23.00115],[51.61771,24.01422],[51.57952,24.2455]]]},\"properties\":{\"name\":\"United Arab Emirates\"}}]}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
The U.S. Geological Survey’s (USGS) Modular Ground-Water Flow Model (MODFLOW-2005) is a computer program that simulates groundwater flow by using finite differences. The MODFLOW-2005 framework uses a modular design that allows for the easy development and incorporation of new features called processes and packages that work with or modify inputs to the groundwater-flow equation. A process solves a flow equation or set of equations. For example, the central part of MODFLOW is the groundwater-flow process that solves the groundwater-flow equation; the surface-water routing process is an additional process that solves the surface-water flow equation. Packages are code related to the groundwater-flow process. For example, the subsidence package modifies the groundwater-flow process by including aquifer compaction effects on flow. With the development of new packages and processes, the MODFLOW-2005 base framework diverged into multiple independent versions designed for specific simulation needs. This divergence limited each independent MODFLOW release to its specific purpose, so that there was no longer a single, comprehensive, general-purpose hydraulic-simulation framework.
The MODFLOW One-Water Hydrologic Flow Model (MF-OWHM, also informally known as OneWater) is an integrated hydrologic flow model that combines multiple MODFLOW-2005 variants in one cohesive simulation software; changes were made to enable multiple capabilities in one code. This fusion of the MODFLOW-2005 versions resulted in a simulation software that can be used to address and analyze a wide class of conjunctive-use, water-management, water-food-security, and climate-crop-water scenarios. As a second core version of MODFLOW-2005, MF-OWHM maintains backward compatibility with existing MODFLOW-2005 versions, with features that include the following:
MF-OWHM is a MODFLOW-2005 based integrated hydrologic model that can simulate and analyze varying environmental conditions to allow for the evaluation of management options from many components of human and natural water movement through a physically based, supply and demand framework. The term “integrated,” in the context of this report, refers to the tight coupling of groundwater flow, surface-water flow, landscape processes, aquifer compaction and subsidence, reservoir operations, and conduit (karst) flow. Another benefit of this integrated hydrologic model is that models developed to run by MODFLOW-2005, MODFLOW-NWT, MODFLOW-CFP, or MODFLOW-FMP can also be simulated with MF-OWHM. At the time of this report’s publication, MF-OWHM version 2 (MF-OWHM2) does not include a direct internal simulation of snowmelt, advanced mountainous watershed rainfall-runoff simulation, detailed shallow soil-moisture accounting, or atmospheric moisture content. Atmospheric moisture may be accounted for indirectly by, optionally, specifying a pan-evaporation rate, reference evapotranspiration, and precipitation. These features are not included to ensure that simulation runtime remains short enough to enable the use of automated methods of calibrating model parameters to field observations, which typically require many simulation model runs. The MF-OWHM approach is to include as much detail as possible to simulate hydrological processes, providing the simulation runtimes remain reasonable enough to allow for robust parameter estimation and model calibration.
To represent both natural and human-influenced flow, MF-OWHM integrates physically based flow processes derived from MODFLOW-2005 in a supply and demand framework. From this integration, the physically based movement of groundwater, surface water, imported water, and precipitation serve as supply to meet consumptive demands associated with irrigated and non-irrigated agriculture, natural vegetation, and urban water uses. Water consumption is determined by balancing the available water supply with water demand, leading to the concept of a demand-driven, supply-constrained simulation.
The MF-OWHM Supply-and-Demand Framework is especially useful for the analysis of agricultural water use, where there are often few data available to describe changes in land-use through time, such as crop type and distribution, and the associated changes in groundwater pumpage. This framework attempts to satisfy each land-use water demand with available water supplies—that is, groundwater uptake, precipitation, and irrigation. An option provided in MF-OWHM2 is to automatically increase groundwater pumping for irrigation, which often is unknown, by the calculated residual between demand and the other available sources of supply. From large- to small-scale applications, the physically based supply and demand framework provides key capabilities for simulating and analyzing historical, current, and future conjunctive-use of surface water and groundwater.
To achieve the physically based supply and demand framework, the MODFLOW-2005 standard of no inter-package and -process communication was relaxed for MF-OWHM2. Traditional MODFLOW simulation models required that all packages and processes interact through the groundwater-flow equation or by removing the water flow from the simulation domain. For example, the MODFLOW-2005 representation of a groundwater well extracts water from the groundwater-flow equation (by subtraction) and removes it from the simulation domain. This feature is available in the MF-OWHM framework, but options have been added to allow the specification of a use or destination of pumped groundwater within the model domain, for example, it can be used for irrigation, managed aquifer recharge, or return-flow to streams.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm6A60","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Boyce, S.E., Hanson, R.T., Ferguson, I., Schmid, W., Henson, W., Reimann, T., Mehl, S.M., and Earll, M.M., 2020, One-Water Hydrologic Flow Model: A MODFLOW based conjunctive-use simulation software: U.S. Geological Survey Techniques and Methods 6–A60, 435 p., https://doi.org/10.3133/tm6A60.","productDescription":"Report: xvii, 435 p.; Application Site","numberOfPages":"435","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-071159","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":437036,"rank":14,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9K2IQ6Y","text":"USGS data release","linkHelpText":"Batteries Included Fortran Library (BiF-lib), version 1.0.0"},{"id":437035,"rank":14,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9P8I8GS","text":"USGS data release","linkHelpText":"MODFLOW One-Water Hydrologic Flow Model (MF-OWHM) Conjunctive Use and Integrated Hydrologic Flow Modeling Software"},{"id":374113,"rank":13,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/tm/06/a60/tm6A60_appendix8.pdf","text":"Appendix 8","size":"300 KB","linkFileType":{"id":1,"text":"pdf"},"description":"Techniques and Methods A6-60","linkHelpText":"- Conduit Flow Process (CFP2) Input File Documentation for New Capabilities of CFP2 Mode 1—Discrete Conduits"},{"id":374112,"rank":12,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/tm/06/a60/tm6A60_appendix7.pdf","text":"Appendix 7","size":"1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Techniques and Methods A6-60","linkHelpText":"- Conduit Flow Process Updates and Upgrades (CFP2)"},{"id":374111,"rank":11,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/tm/06/a60/tm6A60_appendix6.pdf","text":"Appendix 6","size":"7.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Techniques and Methods A6-60","linkHelpText":"- Farm Process Version 4 (FMP)"},{"id":374110,"rank":10,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/tm/06/a60/tm6A60_appendix5.pdf","text":"Appendix 5","size":"2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Techniques and Methods A6-60","linkHelpText":"- Landscape and Root-Zone Processes and Water Demand and Supply"},{"id":374109,"rank":9,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/tm/06/a60/tm6A60_appendix4.pdf","text":"Appendix 4","size":"1.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Techniques and Methods A6-60","linkHelpText":"- Consumptive Use and Evapotranspiration in the Farm Process"},{"id":374108,"rank":8,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/tm/06/a60/tm6A60_appendix3.pdf","text":"Appendix 3","size":"4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Techniques and Methods A6-60","linkHelpText":"- Modflow Upgrades and Updates"},{"id":374107,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/tm/06/a60/tm6A60_appendix2.pdf","text":"Appendix 2","size":"2.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Techniques and Methods A6-60","linkHelpText":"- Separation of Spatial and Temporal Input Options"},{"id":374106,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/tm/06/a60/tm6A60_appendix1.pdf","text":"Appendix 1","size":"2.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Techniques and Methods A6-60","linkHelpText":"- New Input Formats and Utilities"},{"id":374105,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/tm/06/a60/tm6A60_appendix0.pdf","text":"Appendix 0","size":"500 KB","linkFileType":{"id":1,"text":"pdf"},"description":"Techniques and Methods A6-60","linkHelpText":"- Report Syntax Highlighting and Custom Font Styles"},{"id":374104,"rank":4,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/06/a60/tm6A60_body.pdf","text":"Main body","size":"3 MB - Main body","linkFileType":{"id":1,"text":"pdf"},"description":"Techniques and Methods A6-60 Main body"},{"id":373682,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/06/a60/coverthb.jpg"},{"id":373683,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/06/a60/tm6A60.pdf","text":"Full report","size":"30 MB - Full report","linkFileType":{"id":1,"text":"pdf"},"description":"Techniques and Methods A6-60 Full report"},{"id":373696,"rank":3,"type":{"id":4,"text":"Application Site"},"url":"https://www.usgs.gov/software/modflow-owhm-one-water-hydrologic-flow-model"}],"contact":"Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
Despite decades of research into air and stream temperature dynamics, paired air-water annual temperature signals have been underutilized to characterize watershed processes. Annual stream temperature dynamics are useful in classifying fundamental thermal regimes and can enhance process-based interpretation of stream temperature controls, including deep and shallow groundwater discharge, when paired with air signals. In this study, we investigated multi-scale variability in annual paired air-water temperature patterns using sine-wave linear regressions of multi-year daily temperature data from streams of various sizes. A total of 311 sites from two spatially intensive regional datasets (Shenandoah National Park and Olympic Experimental State Forest) and a spatially extensive national dataset spanning the contiguous United States (U.S. Geological Survey gages) were evaluated. We calculated three annual air-water thermal metrics (mean ratio, phase lag, and amplitude ratio) to deduce the influence of groundwater and other watershed processes on stream thermal regimes at multiple spatial scales. Site-specific values of the three annual air-water thermal metrics ranged from 0.69 to 5.29 (mean ratio), −9 to 40 days (phase lag), and 0.29 to 1.12 (amplitude ratio). Regional patterns in the annual thermal metrics revealed persistent yet spatially variable influences of shallow groundwater discharge and high levels of thermal variability within watersheds, indicating the importance of local hydrogeological controls on stream temperature. Furthermore, annual thermal metric patterns from the regional datasets were generally concordant with the national dataset suggesting the utility of these annual thermal metrics for analysis at multiple scales. Analysis of the national dataset showed that previously defined thermal regimes based on water temperature alone could be further refined using air-water metrics and these metrics were related to physiographic watershed characteristics such as contributing area, elevation, and slope. This research demonstrates the importance of spatial scale and heterogeneity for inferring hydrological process in streams and provides guidance for the interpretation of annual air-water temperature metrics that can be efficiently applied to the growing database of multi-year temperature records. Results from this research can aid in the prediction of future thermal habitat suitability for coldwater-adapted species at ecologically and management-relevant spatial scales with readily available data.
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Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":814788,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Snyder, Craig D. 0000-0002-3448-597X csnyder@usgs.gov","orcid":"https://orcid.org/0000-0002-3448-597X","contributorId":2568,"corporation":false,"usgs":true,"family":"Snyder","given":"Craig","email":"csnyder@usgs.gov","middleInitial":"D.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":814789,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hitt, Nathaniel P. 0000-0002-1046-4568 nhitt@usgs.gov","orcid":"https://orcid.org/0000-0002-1046-4568","contributorId":4435,"corporation":false,"usgs":true,"family":"Hitt","given":"Nathaniel","email":"nhitt@usgs.gov","middleInitial":"P.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":814790,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hare, 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seeps","interactions":[],"lastModifiedDate":"2020-05-20T12:40:04.192663","indexId":"70210189","displayToPublicDate":"2020-04-04T07:26:57","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2315,"text":"Journal of Geophysical Research C: Oceans","active":true,"publicationSubtype":{"id":10}},"title":"Surface methane concentrations along the mid-Atlantic bight driven by aerobic subsurface production rather than seafloor gas seeps","docAbstract":"Relatively minor amounts of methane, a potent greenhouse gas, are currently emitted from the oceans to the atmosphere, but such methane emissions have been hypothesized to increase as oceans warm. Here, we investigate the source, distribution, and fate of methane released from the upper continental slope of the U.S. Mid-Atlantic Bight, where hundreds of gas seeps have been discovered between the shelf-break and ~1600 m water depth. Using physical, chemical, and isotopic analyses, we identify two main sources of methane in the water column: seafloor gas seeps and in situ aerobic methanogenesis which primarily occurs at 100 – 200 m depth in the water column. Stable isotopic analyses reveal that water samples collected at all depths were significantly impacted by aerobic methane oxidation, the dominant methane sink in this region, with more than 50% of the methane being oxidized, on average. Due to methane oxidation in the deeper water column, below 200 m depth, surface concentrations of methane are influenced more by methane sources found near the surface (0 – 10 m depth) and in the subsurface (10 - 200 m depth), rather than seafloor emissions at greater depths.","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2019JC015989","usgsCitation":"Leonte, M., Ruppel, C.D., Ruiz-Angelo, A., and Kessler, J.D., 2020, Surface methane concentrations along the mid-Atlantic bight driven by aerobic subsurface production rather than seafloor gas seeps: Journal of Geophysical Research C: Oceans, v. 125, no. 5, e2019JC015989, 13 p., https://doi.org/10.1029/2019JC015989.","productDescription":"e2019JC015989, 13 p.","ipdsId":"IP-114697","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":457161,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1029/2019jc015989","text":"External Repository"},{"id":374952,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Atlantic margin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.76220703125,\n 39.232253141714885\n ],\n [\n -74.794921875,\n 37.71859032558816\n ],\n [\n -75.1904296875,\n 35.7286770448517\n ],\n [\n -76.22314453125,\n 34.27083595165\n ],\n [\n -76.11328125,\n 34.17999758688084\n ],\n [\n -75.322265625,\n 33.99802726234877\n ],\n [\n -73.916015625,\n 33.97980872872457\n ],\n [\n -72.333984375,\n 36.03133177633187\n ],\n [\n -71.56494140625,\n 38.565347844885466\n ],\n [\n -71.47705078125,\n 39.842286020743394\n ],\n [\n -73.14697265625,\n 39.50404070558415\n ],\n [\n -73.76220703125,\n 39.232253141714885\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"125","issue":"5","noUsgsAuthors":false,"publicationDate":"2020-05-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Leonte, Mihai 0000-0003-1582-5606","orcid":"https://orcid.org/0000-0003-1582-5606","contributorId":224782,"corporation":false,"usgs":false,"family":"Leonte","given":"Mihai","email":"","affiliations":[{"id":40676,"text":"University of Rochester, NY","active":true,"usgs":false}],"preferred":false,"id":789479,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ruppel, Carolyn D. 0000-0003-2284-6632 cruppel@usgs.gov","orcid":"https://orcid.org/0000-0003-2284-6632","contributorId":195778,"corporation":false,"usgs":true,"family":"Ruppel","given":"Carolyn","email":"cruppel@usgs.gov","middleInitial":"D.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":789480,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ruiz-Angelo, Angel","contributorId":224783,"corporation":false,"usgs":false,"family":"Ruiz-Angelo","given":"Angel","email":"","affiliations":[{"id":40940,"text":"Icelandic Meteorological Office","active":true,"usgs":false}],"preferred":false,"id":789481,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kessler, John D. 0000-0003-1097-6800","orcid":"https://orcid.org/0000-0003-1097-6800","contributorId":184241,"corporation":false,"usgs":false,"family":"Kessler","given":"John","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":789482,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70209420,"text":"70209420 - 2020 - Thermal heterogeneity, migration, and consequences for spawning potential of female bull trout in a river-reservoir system","interactions":[],"lastModifiedDate":"2020-06-04T17:09:46.699712","indexId":"70209420","displayToPublicDate":"2020-04-03T08:18:18","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Thermal heterogeneity, migration, and consequences for spawning potential of female bull trout in a river-reservoir system","docAbstract":"The likelihood that fish will initiate spawning, spawn successfully, or skip spawning in a given year is conditioned in part on availability of energy reserves. We evaluated the consequences of spatial heterogeneity in thermal conditions on the energy accumulation and spawning potential of migratory bull trout (Salvelinus confluentus) in a regulated river–reservoir system. Based on existing data, we identified a portfolio of thermal exposures and migratory patterns and then estimated their influence on energy reserves of female bull trout with a bioenergetics model. Spawning by females was assumed to be possible if postspawning energy reserves equaled or exceeded 4 kJ/g. Given this assumption, results suggested up to 70% of the simulated fish could spawn each year. Fish that moved seasonally between a cold river segment and a warmer reservoir downstream had a greater growth rate and higher propensity to spawn in a given year (range: 40%–70%) compared with fish that resided solely in the cold river segment (25%–40%). On average, fish that spawned lost 30% of their energy content relative to their prespawn energy. In contrast, fish that skipped spawning accumulated, on average, 16% energy gains that could be used toward future gamete production. Skipped spawning occurred when water temperatures were relatively low or high, and if upstream migration occurred relatively late (mid-July or later) or early (early-May or earlier). Overall, our modeling effort suggests the configuration of thermal exposures, and the ability of bull trout to exploit this spatially and temporally variable thermal conditions can strongly influence energy reserves and likelihood of successful spawning.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.6184","usgsCitation":"Benjamin, J.R., Vidergar, D., and Dunham, J.B., 2020, Thermal heterogeneity, migration, and consequences for spawning potential of female bull trout in a river-reservoir system: Ecology and Evolution, v. 10, no. 9, p. 4128-4142, https://doi.org/10.1002/ece3.6184.","productDescription":"15 p.","startPage":"4128","endPage":"4142","ipdsId":"IP-111770","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":457165,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/ece3.6184","text":"External Repository"},{"id":373838,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"Boise River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.4111328125,\n 42.97250158602597\n ],\n [\n -113.99414062499999,\n 42.97250158602597\n ],\n [\n -113.99414062499999,\n 44.4808302785626\n ],\n [\n -116.4111328125,\n 44.4808302785626\n ],\n [\n -116.4111328125,\n 42.97250158602597\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"10","issue":"9","noUsgsAuthors":false,"publicationDate":"2020-04-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Benjamin, Joseph R. 0000-0003-3733-6838 jbenjamin@usgs.gov","orcid":"https://orcid.org/0000-0003-3733-6838","contributorId":3999,"corporation":false,"usgs":true,"family":"Benjamin","given":"Joseph","email":"jbenjamin@usgs.gov","middleInitial":"R.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":786443,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vidergar, Dmitri T","contributorId":223858,"corporation":false,"usgs":false,"family":"Vidergar","given":"Dmitri T","affiliations":[{"id":6696,"text":"BLM","active":true,"usgs":false}],"preferred":false,"id":786444,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dunham, Jason B. 0000-0002-6268-0633 jdunham@usgs.gov","orcid":"https://orcid.org/0000-0002-6268-0633","contributorId":147808,"corporation":false,"usgs":true,"family":"Dunham","given":"Jason","email":"jdunham@usgs.gov","middleInitial":"B.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":786445,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70209443,"text":"70209443 - 2020 - Long-term trends of Lake Michigan benthos with emphasis on the southern basin","interactions":[],"lastModifiedDate":"2020-06-04T17:08:34.997292","indexId":"70209443","displayToPublicDate":"2020-04-03T07:50:28","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Long-term trends of Lake Michigan benthos with emphasis on the southern basin","docAbstract":"Lake Michigan benthic macrofauna have been studied for almost a century, allowing for a unique analysis of long-term changes in community structure. We examined changes in abundances of three major taxonomic groups of benthic macroinvertebrates (Diporeia, Oligochaeta, and Sphaeriidae) in southern Lake Michigan from 1931-2015, and identified the most likely causes for these changes. Abundances of all three groups increased during 1931-1980, with the bulk of these increases occurring in nearshore (≤ 50 m) waters and coincident with increasing loading of phosphorus (P) to the lake. Abundances of all three taxa declined during 1980-2000 again mostly in nearshore waters and coincident with decreased P loading. The quagga mussel (Dreissena rostriformis bugensis) invasion was associated with a further decline in phytoplankton primary production during 2000-2015. Both Diporeia and Sphaeriidae declined in abundance during that time, with Diporeia exhibiting the more pronounced decrease of the two groups. In contrast, Oligochaeta increased in abundance during 2000-2015. The quagga mussel has become, by far, the most abundant benthic macroinvertebrate species in terms of density and biomass. Overall, the primary driver of changes in the abundances of the three major taxa during this 85-year period appeared to be changes in phytoplankton primary production due to changing P loadings and, later in the time series, Dreissena filtering. The dreissenid mussel invasions coincided with a rapid decline of Diporeia abundance, but the mechanism of this negative effect remains unidentified. In contrast, Oligochaeta likely benefitted from the quagga mussel invasion; perhaps via quagga-generated food supplies.","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2020.03.011","usgsCitation":"Mehler, K., Burlakova, L.E., Karatayev, A.Y., Elgin, A.K., Nalepa, T.F., Madenjian, C.P., and Hinchey, E.K., 2020, Long-term trends of Lake Michigan benthos with emphasis on the southern basin: Journal of Great Lakes Research, v. 46, no. 3, p. 528-537, https://doi.org/10.1016/j.jglr.2020.03.011.","productDescription":"10 p.","startPage":"528","endPage":"537","ipdsId":"IP-111303","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":457166,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jglr.2020.03.011","text":"Publisher Index Page"},{"id":373836,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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State","active":true,"usgs":false}],"preferred":false,"id":786497,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Karatayev, Alexander Y.","contributorId":150923,"corporation":false,"usgs":false,"family":"Karatayev","given":"Alexander","email":"","middleInitial":"Y.","affiliations":[{"id":18141,"text":"SUNY Buffalo State","active":true,"usgs":false}],"preferred":false,"id":786498,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Elgin, Ashley K.","contributorId":216170,"corporation":false,"usgs":false,"family":"Elgin","given":"Ashley","email":"","middleInitial":"K.","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":786499,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nalepa, Thomas F.","contributorId":211819,"corporation":false,"usgs":false,"family":"Nalepa","given":"Thomas","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":786500,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Madenjian, Charles P. 0000-0002-0326-164X cmadenjian@usgs.gov","orcid":"https://orcid.org/0000-0002-0326-164X","contributorId":2200,"corporation":false,"usgs":true,"family":"Madenjian","given":"Charles","email":"cmadenjian@usgs.gov","middleInitial":"P.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":786501,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hinchey, Elizabeth K.","contributorId":197957,"corporation":false,"usgs":false,"family":"Hinchey","given":"Elizabeth","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":786502,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70263118,"text":"70263118 - 2020 - Investigating population genetics of invasive rainbow smelt in the Great Lakes Region","interactions":[],"lastModifiedDate":"2025-01-30T15:34:14.883877","indexId":"70263118","displayToPublicDate":"2020-04-03T00:00:00","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Investigating population genetics of invasive rainbow smelt in the Great Lakes Region","docAbstract":"Increasing our understanding of invasive species is important because of the negative impacts they can have on the economies and ecosystems of invaded regions. There is growing interest in how environmental variability (e.g. temperature) and stochastic invasion events (e.g. founder effects) affect the genetic composition of populations of invasive species. Rainbow smelt (Osmerus mordax) are a cold-water, planktivorous fish that spread into the Great Lakes basin in the early 1900s. We performed genetic analyses using microsatellites (N = 10) to investigate the influence stochastic invasion events have had on the genetic composition of invasive rainbow smelt populations across a broad geographic range. Genetic analyses were conducted on rainbow smelt populations (N = 30/population) from Lake Ontario, Lake Michigan, Lake Superior, and four inland lakes in Northern Wisconsin. Populations from the Great Lakes were generally less differentiated than inland populations. Additionally, we found evidence of a significant bottleneck in two inland populations and evidence for two distinct genetic strains of rainbow smelt in Lake Ontario. We also performed genetic analyses using microsatellites to determine if a thermally-induced extreme mortality event had an effect on a population of rainbow smelt and found that there was no measurable genetic effect on the population. Overall, this study provides evidence that the genetic structure and diversity of introduced populations can vary significantly, and are likely influenced by factors such as the frequency and magnitude of introductions. Also the resiliency of an invasive species can be high despite a history of bottlenecks and low genetic diversity.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2020.01.016","usgsCitation":"Dobosenski, J., Strasburg, J., Larson, W., and Hrabik, T., 2020, Investigating population genetics of invasive rainbow smelt in the Great Lakes Region: Journal of Great Lakes Research, v. 46, no. 2, p. 382-390, https://doi.org/10.1016/j.jglr.2020.01.016.","productDescription":"9 p.","startPage":"382","endPage":"390","ipdsId":"IP-109675","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":481504,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Great Lakes Region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -91.74064917677558,\n 47.29910280069214\n ],\n [\n -88.72180472353388,\n 45.92694839046345\n ],\n [\n -87.48882297041533,\n 41.600893566227285\n ],\n [\n -80.91070356084862,\n 41.48254481239488\n ],\n [\n -78.20297539830352,\n 42.832826145165996\n ],\n [\n -76.60960173259036,\n 42.98668563895146\n ],\n [\n -75.64453839868747,\n 44.260789106848705\n ],\n [\n -81.81944877789577,\n 46.04033704847711\n ],\n [\n -88.97252426064546,\n 48.19838227578134\n ],\n [\n -90.15695774500598,\n 47.35524992499353\n ],\n [\n -91.74064917677558,\n 47.29910280069214\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"46","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Dobosenski, Jamie A.","contributorId":350280,"corporation":false,"usgs":false,"family":"Dobosenski","given":"Jamie A.","affiliations":[{"id":16117,"text":"Wisconsin DNR","active":true,"usgs":false}],"preferred":false,"id":925612,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Strasburg, Jared L.","contributorId":350281,"corporation":false,"usgs":false,"family":"Strasburg","given":"Jared L.","affiliations":[{"id":34699,"text":"University of Minnesota-Duluth","active":true,"usgs":false}],"preferred":false,"id":925613,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Larson, Wesley 0000-0003-4473-3401 wlarson@usgs.gov","orcid":"https://orcid.org/0000-0003-4473-3401","contributorId":199509,"corporation":false,"usgs":true,"family":"Larson","given":"Wesley","email":"wlarson@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":925611,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hrabik, Thomas R.","contributorId":350283,"corporation":false,"usgs":false,"family":"Hrabik","given":"Thomas R.","affiliations":[{"id":34699,"text":"University of Minnesota-Duluth","active":true,"usgs":false}],"preferred":false,"id":925614,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70210178,"text":"70210178 - 2020 - Low threshold for nitrogen concentration saturation in headwaters increases regional and coastal delivery","interactions":[],"lastModifiedDate":"2020-09-01T13:53:32.395533","indexId":"70210178","displayToPublicDate":"2020-04-02T08:01:50","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1562,"text":"Environmental Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Low threshold for nitrogen concentration saturation in headwaters increases regional and coastal delivery","docAbstract":"River corridors store, convey, and process nutrients from terrestrial and upstream sources, regulating delivery from headwaters to estuaries. A consequence of chronic excess nitrogen loading, as supported by theory and field studies in specific areas, is saturation of the biogeochemically-mediated nitrogen removal processes that weakens the capacity of the river corridor to remove nitrogen. Regional nitrogen models typically assume that removal capacity exhibits first-order behavior, scaling positively and linearly with increasing concentration, which may bias the estimation of where and at what rate nitrogen is removed by river corridors. Here we estimate the nitrogen concentration saturation threshold and its effects on nitrogen export from the Northeastern United States, revealing an average 42% concentration-induced reduction in headwater removal capacity. The weakened capacity caused an average 10% increase in the predicted delivery of riverine nitrogen from urban and agricultural watersheds compared to estimates using first-order process assumptions. Our results suggest that nitrogen removal may fall below a first-order process at a low riverine threshold concentration of 0.5 mg N L-1. Threshold behavior indicates that even modest mitigation of nitrogen concentration in river corridors above the threshold can cause a self-reinforcing boost to nitrogen removal.","language":"English","publisher":"IOP Publishing","doi":"10.1088/1748-9326/ab751b","usgsCitation":"Schmadel, N., Harvey, J., Alexander, R., Boyer, E.W., Schwarz, G.E., Gomez-Velez, J., Scott, D., and Konrad, C., 2020, Low threshold for nitrogen concentration saturation in headwaters increases regional and coastal delivery: Environmental Research Letters, v. 15, no. 4, 044018, 10 p., https://doi.org/10.1088/1748-9326/ab751b.","productDescription":"044018, 10 p.","ipdsId":"IP-114890","costCenters":[{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":457171,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index 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Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-5021","displayTitle":"Effects of Box Culverts on Stream Habitat, Channel Morphology, and Fish and Macroinvertebrate Communities at Selected Sites in South Carolina, 2016–18","title":"Effects of box culverts on stream habitat, channel morphology, and fish and macroinvertebrate communities at selected sites in South Carolina, 2016–18","docAbstract":"Much attention has been placed on the role that under-roadway culverts may have in inhibiting upstream fish movement because of altered hydrology and unsuitable conditions for accessing or swimming through the culvert. Other culvert effects related to habitat alterations or disturbance to macroinvertebrate communities have received relatively little attention. Entities responsible for culverts or other stream crossing structures are required to follow the U.S. Army Corps of Engineers guidelines for compensatory mitigation should any disturbance result from an engineering activity. One factor considered in the scoring of mitigation requirements is culvert length. Except for shading a longer length of stream, it is unknown whether longer culverts result in greater disturbance to stream habitat or the biotic communities than shorter culverts. The U.S. Geological Survey, in cooperation with the South Carolina Department of Transportation, evaluated the role of culverts in altering physical habitat and community structure of fish and macroinvertebrates at 20 sites in South Carolina. Culvert sites were categorized by length (either greater than 30.5 meters or less than or equal to 30.5 meters) and physiographic province (Piedmont or upper Coastal Plain). This study design allowed for a regional assessment to determine if culverts may have different effects on habitat and biotic communities in different physical settings. The results indicated considerable variation in physical habitat characteristics within and among the culvert sites from all categories. A consistent finding was that channel cross-sectional area tended to increase in reaches downstream from culverts in the upper Coastal Plain. The primary dimension of change was vertical, that is, incision of the streambed. This change, however, did not seem to coincide with a deleterious effect on the fish community. Increased habitat complexity and greater taxonomic richness were observed at most sites with downstream incision. Macroinvertebrate communities were highly variable and did not tend to cluster along any of the culvert categories, which may reflect the variability of microhabitats within each site. In contrast, fish communities were largely segregated by physiographic province but did not show any other significant clustering on the basis of upstream or downstream reach or culvert length. Given the small within-group sample size, extrapolation of results should be done carefully, acknowledging the physiographic and group characteristics.
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720 Gracern Road
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Groundwater hydrology and geochemistry within the tidal Anacostia River watershed of Washington, D.C. are related to natural and human influences. The U.S. Geological Survey, in cooperation with the District Department of Energy & Environment, began investigating the hydrogeology and groundwater quality of the watershed in 2002. Lithologic coring, groundwater-level and tidal monitoring, and water-quality sampling have been conducted to improve understanding of the groundwater-flow system, geochemistry, water quality, and the likely interaction between groundwater and the tidal Anacostia River. The flow and interaction of shallow groundwater with the tidal Anacostia River and other area streams are affected by diversions, pumping, land reclamation, and other human activities in this highly urbanized watershed.
The tidal Anacostia River watershed is underlain by a wedge of unconsolidated sediments that is part of the Atlantic Coastal Plain Physiographic Province. These sediments form a system of confined and unconfined aquifers. The coarse sediments of the Potomac Group sand-dominated lithofacies form the Patuxent aquifer. The Patuxent aquifer crops out and subcrops in the northwestern part of the study area, but is confined to the southeast by the overlying Potomac Group clay-dominated lithofacies. Overlying the Potomac Group is a series of interbedded sands and clays that form an unconfined surficial aquifer system. Regional correlation in the unconfined surficial aquifer system is complicated by local heterogeneity in aquifer sediments. Local perched and semi-confined conditions occur in some areas.
Recharge of the confined Patuxent aquifer occurs primarily in the outcrop and subcrop area, although some recharge may also occur through overlying confining units. Recharge to the unconfined surficial aquifer system occurs through infiltration of precipitation and possible artificial recharge from structures such as underground water or sewer pipes. In the Patuxent aquifer, hydraulic gradients indicate downward movement in the outcrop area, whereas hydraulic heads beneath the Anacostia River are higher than land surface, indicating an upward hydraulic gradient. In the unconfined surficial aquifer system, groundwater generally flows from upland recharge areas towards discharge areas near the Anacostia River and its tributaries. Groundwater from the confined part of the Patuxent aquifer also may discharge to the Anacostia River in locations where the overlying clay-dominated lithofacies of the Potomac Group is absent as a result of past geologic and (or) alluvial processes.
Geochemistry and groundwater quality are affected by hydrologic conditions as well as anthropogenic influences. Local variability in groundwater quality reflects local variability in hydrogeologic conditions and sources of chemicals. Groundwater ranges from anoxic and iron- or calcium-bicarbonate type, to oxic with elevated nitrate. The occurrence and distribution of pesticides, volatile organic compounds, and other selected chemical compounds in groundwater reflect the multitude of sources common to urban areas, as well as variable hydrogeologic and geochemical conditions that affect their fate and transport in the environment. Overall, concentrations of only a few of the over 200 chemical constituents included in laboratory analyses exceeded regulatory standards or guidance values. These include tetrachloroethene and arsenic, which were each detected one time in different wells. There were also several detections of iron and manganese that exceeded regulatory standards or guidance values that are associated with reducing conditions in aquifer sediments.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195128","usgsCitation":"Ator, S.W., Denver, J.M., and Dieter, C.A., 2020, Hydrogeology and shallow groundwater quality in the tidal Anacostia River watershed, Washington, D.C.: U.S. Geological Survey Scientific Investigations Report 2019-5128, 93 p., https://doi.org/10.3133/sir20195128.","productDescription":"Report: viii, 93 p.; 6 Appendixes","numberOfPages":"106","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-039169","costCenters":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"links":[{"id":373579,"rank":8,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2019/5128/sir20195128_appendix5.pdf","text":"Appendix 5","size":"10.5 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- South Capitol Street Geotechnical Report, MACTEC Engineering and Consulting, Inc., 2005 (reproduced with permission)"},{"id":399609,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109888.htm"},{"id":373578,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2019/5128/sir20195128_appendix4d.txt","text":"Appendix 4d","size":"1.45 MB","linkFileType":{"id":2,"text":"txt"},"linkHelpText":"- Tide Levels at USGS Station 01651750, Anacostia River Aquatic Gardens at Washington, D.C., 2007"},{"id":373577,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2019/5128/sir20195128_appendix4c.txt","text":"Appendix 4c","size":"1.97 MB","linkFileType":{"id":2,"text":"txt"},"linkHelpText":"- Tide Levels at USGS Station 01651750, Anacostia River Aquatic Gardens at Washington, D.C., 2006"},{"id":373569,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5128/coverthb.jpg"},{"id":373570,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5128/sir20195128.pdf","text":"Report","size":"3.52 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019-5128"},{"id":373575,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2019/5128/sir20195128_appendix4a.txt","text":"Appendix 4a","size":"1.20 MB","linkFileType":{"id":2,"text":"txt"},"linkHelpText":"- Tide Levels at USGS Station 01651750, Anacostia River Aquatic Gardens at Washington, D.C., 2004"},{"id":373576,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2019/5128/sir20195128_appendix4b.txt","text":"Appendix 4b","size":"2.08 MB","linkFileType":{"id":2,"text":"txt"},"linkHelpText":"- Tide Levels at USGS Station 01651750, Anacostia River Aquatic Gardens at Washington, D.C., 2005"},{"id":373574,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2019/5128/sir20195128_appendix3.xlsx","text":"Appendix 3","size":"59.4 KB","linkFileType":{"id":3,"text":"xlsx"},"linkHelpText":"- Instantaneous Groundwater-Level Measurements Collected at Selected Sites in the Anacostia River Watershed, 2002–11"}],"country":"United States","state":"Washington, D.C.","otherGeospatial":"Tidal Anacostia River watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.1185302734375,\n 38.79048618862274\n ],\n [\n -76.93313598632812,\n 38.79048618862274\n ],\n [\n -76.93313598632812,\n 38.93698019310818\n ],\n [\n -77.1185302734375,\n 38.93698019310818\n ],\n [\n -77.1185302734375,\n 38.79048618862274\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, MD-DE-DC Water Science Center
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Determining which traits characterize strategies of coexisting species is important to developing trait‐based models of plant communities. First, global dimensions may not exist locally. Second, the degree to which traits and trait spectra constitute independent dimensions of functional variation at various scales continues to be refined. Finally, traits may be associated with existing categorical groupings.
We assessed trait integration and differentiation across 57 forest understory plant species in Douglas‐fir forests of western Oregon, United States. We combined measurements for a range of traits with literature‐based estimates of seed mass and species groupings. We used network analysis and nonmetric multidimensional scaling ordination (NMS) to determine the degree of integration.
We observed a strong leaf economics spectrum (LES) integrated with stem but not root traits. However, stem traits and intrinsic water‐use efficiency integrated LES and root traits. Network analyses indicated a modest grouping of a priori trait dimensions. NMS indicated that multivariate differences among species were related primarily to (1) rooting depth and plant height vs. specific root length, (2) the LES, and (3) leaf size vs. seed mass. These differences were related to species groupings associated with growth and life form, leaf lifespan and seed dispersal mechanisms.
The strategies of coexisting understory plant species could not be reduced to a single dimension. Yet, species can be characterized efficiently and effectively for trait‐based studies of plant communities by measuring four common traits: plant height, specific leaf area, leaf size, and seed mass.
","language":"English","publisher":"Wiley","doi":"10.1002/ajb2.1451","usgsCitation":"Burton, J.I., Perakis, S.S., Brooks, J.R., and Puettmann, K.J., 2020, Trait integration and functional differentiation among co-existing plant species: American Journal of Botany, v. 107, no. 4, p. 628-638, https://doi.org/10.1002/ajb2.1451.","productDescription":"11 p.","startPage":"628","endPage":"638","ipdsId":"IP-095474","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":457186,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8108537","text":"Publisher Index Page"},{"id":378745,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.1455078125,\n 41.983994270935625\n ],\n [\n -120.25634765624999,\n 41.983994270935625\n ],\n [\n -120.25634765624999,\n 45.78284835197676\n ],\n [\n -124.1455078125,\n 45.78284835197676\n ],\n [\n -124.1455078125,\n 41.983994270935625\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"107","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Burton, Julia I. 0000-0002-3205-8819","orcid":"https://orcid.org/0000-0002-3205-8819","contributorId":192599,"corporation":false,"usgs":false,"family":"Burton","given":"Julia","email":"","middleInitial":"I.","affiliations":[],"preferred":false,"id":799605,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Perakis, Steven S. 0000-0003-0703-9314 sperakis@usgs.gov","orcid":"https://orcid.org/0000-0003-0703-9314","contributorId":145528,"corporation":false,"usgs":true,"family":"Perakis","given":"Steven","email":"sperakis@usgs.gov","middleInitial":"S.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":799606,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brooks, J. 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River temperatures respond to a diverse array of drivers including air temperature, streamflow, and thermal inputs, but the physical template has been shown to play a significant role in structuring spatial and temporal variation in water temperature. How these factors interact to affect water temperature in complex floodplain river habitats such as those present in the Upper Mississippi River System (UMRS) is not well-studied. We used a combination of airborne thermal imagery and continuous temperature loggers deployed across aquatic area types to evaluate spatial and temporal patterns in water temperature in Navigation Pool 8 during the summer and fall of 2017. The mid-wave infrared thermal camera available for this study is not commonly used for thermal imagery acquisition over water, so we discuss accommodations that were made to account for potential interferences and describe considerations for future users interested in using the technology. We quantified thermal metrics from imagery and continuous loggers (e.g., mean, coefficient of variation, range) and compared those to hydrogeomorphic variability across aquatic areas using a Geographic Information System (GIS) dataset. Our findings showed that both temporal and spatial temperature patterns were linked to variation in depth and connectivity of aquatic areas across the pool. Despite some of the technical challenges associated with acquiring this imagery, the method shows promise for characterizing spatial variation in surface temperatures in the UMRS associated with complex physical features such as habitat rehabilitation and enhancement projects.
","language":"English","publisher":"U.S. Army Corps of Engineers, Upper Mississippi River Restoration Program","usgsCitation":"Jankowski, K.J., Robinson, L.R., Kalas, J., Carhart, A., Lubinski, B.R., and Ruhser, J., 2020, Mapping the thermal landscape of the Upper Mississippi River: Long Term Resource Monitoring Technical Report LTRMP-2017TL2, 27 p.","productDescription":"27 p.","ipdsId":"IP-103180","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":375283,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":375282,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.umesc.usgs.gov/documents/publications/2020/jankowski_a_2020.html"}],"country":"United States","state":"Iowa, Illinois, Minnesota, Wisconsin","otherGeospatial":"Upoper Mississippi River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.3623046875,\n 39.9434364619742\n ],\n [\n -89.736328125,\n 41.86956082699455\n ],\n [\n -90.3076171875,\n 43.004647127794435\n ],\n [\n -91.0546875,\n 44.18220395771566\n ],\n [\n -93.1640625,\n 45.583289756006316\n ],\n [\n -93.515625,\n 46.649436163350245\n ],\n [\n -94.658203125,\n 46.558860303117164\n ],\n [\n -94.04296874999999,\n 45.36758436884978\n ],\n [\n -92.98828125,\n 44.213709909702054\n ],\n [\n -91.97753906249999,\n 43.96119063892024\n ],\n [\n -91.49414062499999,\n 43.61221676817573\n ],\n [\n -91.5380859375,\n 42.94033923363181\n ],\n [\n -91.0546875,\n 42.32606244456202\n ],\n [\n -90.52734374999999,\n 42.09822241118974\n ],\n [\n -91.5380859375,\n 40.713955826286046\n ],\n [\n -91.3623046875,\n 39.9434364619742\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Jankowski, Kathi Jo 0000-0002-3292-4182","orcid":"https://orcid.org/0000-0002-3292-4182","contributorId":207429,"corporation":false,"usgs":true,"family":"Jankowski","given":"Kathi","email":"","middleInitial":"Jo","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":786563,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Robinson, Larry R. 0000-0002-3049-6479 lrobinson@usgs.gov","orcid":"https://orcid.org/0000-0002-3049-6479","contributorId":3136,"corporation":false,"usgs":true,"family":"Robinson","given":"Larry","email":"lrobinson@usgs.gov","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":786564,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kalas, John","contributorId":223883,"corporation":false,"usgs":false,"family":"Kalas","given":"John","affiliations":[{"id":6913,"text":"Wisconsin Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":786565,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Carhart, Alicia 0000-0002-9977-8124","orcid":"https://orcid.org/0000-0002-9977-8124","contributorId":223884,"corporation":false,"usgs":false,"family":"Carhart","given":"Alicia","email":"","affiliations":[{"id":6913,"text":"Wisconsin Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":786566,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lubinski, Brian R.","contributorId":177523,"corporation":false,"usgs":false,"family":"Lubinski","given":"Brian","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":786567,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ruhser, Janis 0000-0001-9987-2578 jruhser@usgs.gov","orcid":"https://orcid.org/0000-0001-9987-2578","contributorId":149646,"corporation":false,"usgs":true,"family":"Ruhser","given":"Janis","email":"jruhser@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":786568,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70209317,"text":"sir20205017 - 2020 - Geophysical surveys, hydrogeologic characterization, and groundwater flow model for the Truxton basin and Hualapai Plateau, northwestern Arizona","interactions":[{"subject":{"id":70208586,"text":"sir20205017A - 2020 - Groundwater availability in the Truxton basin, northwestern Arizona","indexId":"sir20205017A","publicationYear":"2020","noYear":false,"chapter":"A","displayTitle":"Groundwater Availability in the Truxton Basin, Northwestern Arizona","title":"Groundwater availability in the Truxton basin, northwestern Arizona"},"predicate":"IS_PART_OF","object":{"id":70209317,"text":"sir20205017 - 2020 - Geophysical surveys, hydrogeologic characterization, and groundwater flow model for the Truxton basin and Hualapai Plateau, northwestern Arizona","indexId":"sir20205017","publicationYear":"2020","noYear":false,"title":"Geophysical surveys, hydrogeologic characterization, and groundwater flow model for the Truxton basin and Hualapai Plateau, northwestern Arizona"},"id":1},{"subject":{"id":70208636,"text":"sir20205017B - 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These reports document the findings of a comprehensive groundwater study conducted on the reservation and adjacent areas from 2015 through 2018 by the U.S. Geological Survey in cooperation with the Bureau of Reclamation. The first report described the hydrologic framework and characterization of the Truxton aquifer on the Hualapai Indian Reservation (Bills and Macy, 2016). The second report described the hydrogeologic characterization of the Hualapai Plateau part of the reservation (Mason, Macy, and others, 2020).
This report includes five chapters. Chapter A (Mason, Knight, and others, 2020) is a summary of this multichapter volume and briefly describes the study area. Chapter B (Mason, Bills, and Macy, 2020) describes the geology and hydrology of the Truxton basin and Hualapai Plateau. Chapter C (Kennedy, 2020) describes the results of a gravity geophysical survey of the Truxton basin. Chapter D (Ball, 2020) describes the findings of an airborne electromagnetic survey of the Truxton aquifer and Hualapai Plateau. Chapter E (Knight, 2020) describes the results of a transient groundwater model created for the entire Truxton aquifer both on and off the reservation. The groundwater-flow model is used to estimate projected groundwater levels based on future groundwater withdrawal scenarios.
Director,
Arizona Water Science Center
U.S. Geological Survey
520 N. Park Avenue
Tucson, AZ 85719
Respiratory disease is a key factor affecting the conservation and recovery of bighorn sheep (Ovis canadensis ) populations. Innovative, minimally invasive tools such as gene transcription–based diagnostics have the potential to improve our understanding of the broad range of factors that can affect the health of wild sheep. Evaluation of transcript levels for genes representative of multiple internal systems enables measurement of physiological responses of individuals as well as populations to environmental stressors such as pathogens, nutritional deficiency, or contaminants. We developed real‐time polymerase chain reaction assays for 14 genes of interest representing systems including inflammation, cell signaling, detoxification, antiviral, antibacterial, or general stress. Initial results from desert bighorn sheep (O. c. nelsoni ) sampled from the River, Muddy, and Bare mountains as well as from the Pintwater Range, in southern Nevada, USA, indicated unique transcript profiles associated with each population. This initial study provides the framework from which controlled variable or longitudinal studies can be made, thus augmenting the potential to inform management actions in the future.
","language":"English","publisher":"The Wildlife Society","doi":"10.1002/wsb.1078","usgsCitation":"Bowen, L., Longshore, K., Wolff, P., Klinger, R.C., Cox, M., Bullock, S., Waters-Dynes, S.C., and Miles, A.K., 2020, Gene transcript profiling in desert bighorn sheep: Wildlife Society Bulletin, v. 44, no. 2, p. 323-332, https://doi.org/10.1002/wsb.1078.","productDescription":"10 p.","startPage":"323","endPage":"332","ipdsId":"IP-110200","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":499866,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doaj.org/article/786626d02c084267b8ba32305e06594b","text":"External Repository"},{"id":377447,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada","otherGeospatial":"Bare Mountain Range, Muddy Mountains, Pintwater Range, River Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.093017578125,\n 37.57070524233116\n ],\n [\n -117.861328125,\n 37.60552821745789\n ],\n [\n -115.740966796875,\n 35.94243575255426\n ],\n [\n -114.873046875,\n 35.25459097465022\n ],\n [\n -114.81811523437501,\n 36.01356058518153\n ],\n [\n -114.53247070312499,\n 36.26199220445664\n ],\n [\n -114.158935546875,\n 36.1733569352216\n ],\n [\n -114.093017578125,\n 36.1733569352216\n ],\n [\n -114.093017578125,\n 37.57070524233116\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"44","issue":"2","noUsgsAuthors":false,"publicationDate":"2020-03-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Bowen, Lizabeth 0000-0001-9115-4336 lbowen@usgs.gov","orcid":"https://orcid.org/0000-0001-9115-4336","contributorId":4539,"corporation":false,"usgs":true,"family":"Bowen","given":"Lizabeth","email":"lbowen@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":795956,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Longshore, Kathleen 0000-0001-6621-1271","orcid":"https://orcid.org/0000-0001-6621-1271","contributorId":216374,"corporation":false,"usgs":true,"family":"Longshore","given":"Kathleen","email":"","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":795957,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wolff, Peregrine","contributorId":238063,"corporation":false,"usgs":false,"family":"Wolff","given":"Peregrine","affiliations":[{"id":27489,"text":"Nevada Department of Wildlife","active":true,"usgs":false}],"preferred":false,"id":795958,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Klinger, Robert C. 0000-0003-3193-3199 rcklinger@usgs.gov","orcid":"https://orcid.org/0000-0003-3193-3199","contributorId":5395,"corporation":false,"usgs":true,"family":"Klinger","given":"Robert","email":"rcklinger@usgs.gov","middleInitial":"C.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":795959,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cox, Mike","contributorId":198457,"corporation":false,"usgs":false,"family":"Cox","given":"Mike","email":"","affiliations":[],"preferred":false,"id":795960,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bullock, Sarah","contributorId":238064,"corporation":false,"usgs":false,"family":"Bullock","given":"Sarah","email":"","affiliations":[{"id":47694,"text":"USFWS - Desert NWR","active":true,"usgs":false}],"preferred":false,"id":795961,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Waters-Dynes, Shannon C. 0000-0002-9707-4684 swaters@usgs.gov","orcid":"https://orcid.org/0000-0002-9707-4684","contributorId":5826,"corporation":false,"usgs":true,"family":"Waters-Dynes","given":"Shannon","email":"swaters@usgs.gov","middleInitial":"C.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":795962,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Miles, A. Keith 0000-0002-3108-808X keith_miles@usgs.gov","orcid":"https://orcid.org/0000-0002-3108-808X","contributorId":196,"corporation":false,"usgs":true,"family":"Miles","given":"A.","email":"keith_miles@usgs.gov","middleInitial":"Keith","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":795963,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ]}