Influenza A viruses (IAVs) are maintained in wild waterbirds and have the potential to infect a broad range of species, including wild mammals. The Arctic Coastal Plain of Alaska supports a diverse suite of species, including waterfowl that are common hosts of IAVs. Mammals co-occur with geese and other migratory waterbirds during the summer breeding season, providing a plausible mechanism for interclass transmission of IAVs. To estimate IAV seroprevalence and identify the subtypes to which geese, loons, Arctic foxes (Vulpes lagopus), caribou (Rangifer tarandus), and polar bears (Ursus maritimus) are potentially exposed, we used a blocking enzyme-linked immunosorbent assay (bELISA) and a hemagglutination inhibition (HI) assay to screen for antibodies to IAVs in samples collected during spring and summer of 2012–16. Apparent IAV seroprevalence using the bELISA was 50.7% in geese (range by species: 46.1–52.8%), 9.2% in loons, (range by species: 3.4–20.0%), and 0.4% in Arctic foxes. We found no evidence for exposure to IAVs in polar bears or caribou by either assay. Among geese, we estimated detection probability from replicate bELISA analyses to be 0.92 and also found good concordance (>85%) between results from bELISA and HI assays, which identified antibodies reactive to H1, H6, and H9 subtype IAVs. In contrast, the HI assay detected antibodies in only one of seven loon samples that were positive by bELISA; that sample had low titers to both H4 and H5 IAV subtypes. Our results provide evidence that a relatively high proportion of waterbirds breeding on the Arctic Coastal Plain are exposed to IAVs, although it is unknown whether such exposure occurs locally or on staging or wintering grounds. In contrast, seroprevalence of IAVs in concomitant mammals is apparently low.
","language":"English","publisher":"Wildlife Disease Association","doi":"10.7589/2018-05-128","usgsCitation":"Van Hemert, C.R., Spivey, T.J., Uher-Koch, B.D., Atwood, T.C., Sinnett, D.R., Meixell, B.W., Hupp, J.W., Jiang, K., Adams, L., Gustine, D.D., Ramey, A.M., and Wan, X., 2018, Survey of Arctic Alaskan wildlife for influenza A antibodies: Limited evidence for exposure of mammals: Journal of Wildlife Diseases, v. 55, no. 2, p. 387-398, https://doi.org/10.7589/2018-05-128.","productDescription":"12 p.","startPage":"387","endPage":"398","ipdsId":"IP-097920","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":437650,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9FPXQTP","text":"USGS data release","linkHelpText":"Serological Data on Influenza A from Birds and Mammals on the Arctic Coastal Plain of Northern Alaska, 2011-2017"},{"id":360442,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Arctic Coastal Plain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -160,\n 69\n ],\n [\n -149.5,\n 69\n ],\n [\n -149.5,\n 71.5\n ],\n [\n -160,\n 71.5\n ],\n [\n -160,\n 69\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"55","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c1a1531e4b0708288c23520","contributors":{"authors":[{"text":"Van Hemert, Caroline R. 0000-0002-6858-7165 cvanhemert@usgs.gov","orcid":"https://orcid.org/0000-0002-6858-7165","contributorId":3592,"corporation":false,"usgs":true,"family":"Van 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bmeixell@usgs.gov","orcid":"https://orcid.org/0000-0002-6738-0349","contributorId":138716,"corporation":false,"usgs":true,"family":"Meixell","given":"Brandt","email":"bmeixell@usgs.gov","middleInitial":"W.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":754483,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hupp, Jerry W. 0000-0002-6439-3910 jhupp@usgs.gov","orcid":"https://orcid.org/0000-0002-6439-3910","contributorId":127803,"corporation":false,"usgs":true,"family":"Hupp","given":"Jerry","email":"jhupp@usgs.gov","middleInitial":"W.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":754484,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Jiang, Kaijun","contributorId":211603,"corporation":false,"usgs":false,"family":"Jiang","given":"Kaijun","email":"","affiliations":[],"preferred":false,"id":754485,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Adams, Layne G. 0000-0001-6212-2896 ladams@usgs.gov","orcid":"https://orcid.org/0000-0001-6212-2896","contributorId":2776,"corporation":false,"usgs":true,"family":"Adams","given":"Layne G.","email":"ladams@usgs.gov","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":754486,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Gustine, David D. 0000-0003-1087-1937","orcid":"https://orcid.org/0000-0003-1087-1937","contributorId":201734,"corporation":false,"usgs":false,"family":"Gustine","given":"David","email":"","middleInitial":"D.","affiliations":[{"id":36245,"text":"NPS","active":true,"usgs":false}],"preferred":false,"id":754487,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Ramey, Andrew M. 0000-0002-3601-8400 aramey@usgs.gov","orcid":"https://orcid.org/0000-0002-3601-8400","contributorId":1872,"corporation":false,"usgs":true,"family":"Ramey","given":"Andrew","email":"aramey@usgs.gov","middleInitial":"M.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":754488,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Wan, Xiu-Feng","contributorId":173959,"corporation":false,"usgs":false,"family":"Wan","given":"Xiu-Feng","email":"","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":754489,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70201673,"text":"70201673 - 2018 - Storm surge propagation and flooding in small tidal rivers during events of mixed coastal and fluvial influence","interactions":[],"lastModifiedDate":"2018-12-20T15:36:37","indexId":"70201673","displayToPublicDate":"2018-12-17T15:36:30","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2380,"text":"Journal of Marine Science and Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Storm surge propagation and flooding in small tidal rivers during events of mixed coastal and fluvial influence","docAbstract":"The highly urbanized estuary of San Francisco Bay is an excellent example of a location susceptible to flooding from both coastal and fluvial influences. As part of developing a forecast model that integrates fluvial and oceanic drivers, a case study of the Napa River and its interactions with the San Francisco Bay was performed. For this application we utilize Delft3D-FM, a hydrodynamic model that computes conservation of mass and momentum on a flexible mesh grid, to calculate water levels that account for tidal forcing, storm surge generated by wind and pressure fields, and river flows. We simulated storms with realistic atmospheric pressure, river discharge, and tidal forcing to represent a realistic joint fluvial and coastal storm event. Storm conditions were applied to both a realistic field-scale Napa river drainage as well as an idealized geometry. With these scenarios, we determine how the extent, level, and duration of flooding is dependent on these atmospheric and hydrologic parameters. Unsurprisingly, the model indicates that maximal water levels will occur in a tidal river when high tides, storm surge, and large fluvial discharge events are coincident. Model results also show that large tidal amplitudes diminish storm surge propagation upstream and that phasing between peak fluvial discharges and high tide is important for predicting when and where the highest water levels will occur. The interactions between tides, river discharge, and storm surge are not simple, indicating the need for more integrated flood forecasting models in the future.
","language":"English","publisher":"MDPI","doi":"10.3390/jmse6040158","usgsCitation":"Herdman, L.M., Erikson, L.H., and Barnard, P., 2018, Storm surge propagation and flooding in small tidal rivers during events of mixed coastal and fluvial influence: Journal of Marine Science and Engineering, v. 6, no. 4, p. 1-26, https://doi.org/10.3390/jmse6040158.","productDescription":"Article 158; 26 p.","startPage":"1","endPage":"26","ipdsId":"IP-100898","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":468183,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/jmse6040158","text":"Publisher Index Page"},{"id":360648,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay, Napa River watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.5,\n 36.5\n ],\n [\n -121,\n 36.5\n ],\n [\n -121,\n 39\n ],\n [\n -124.5,\n 39\n ],\n [\n -124.5,\n 36.5\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"6","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-12-17","publicationStatus":"PW","scienceBaseUri":"5c1cb860e4b0708288c83827","contributors":{"authors":[{"text":"Herdman, Liv M. 0000-0002-5444-6441 lherdman@usgs.gov","orcid":"https://orcid.org/0000-0002-5444-6441","contributorId":149964,"corporation":false,"usgs":true,"family":"Herdman","given":"Liv","email":"lherdman@usgs.gov","middleInitial":"M.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":754831,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Erikson, Li H. 0000-0002-8607-7695 lerikson@usgs.gov","orcid":"https://orcid.org/0000-0002-8607-7695","contributorId":149963,"corporation":false,"usgs":true,"family":"Erikson","given":"Li","email":"lerikson@usgs.gov","middleInitial":"H.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":754833,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barnard, Patrick L. 0000-0003-1414-6476 pbarnard@usgs.gov","orcid":"https://orcid.org/0000-0003-1414-6476","contributorId":147147,"corporation":false,"usgs":true,"family":"Barnard","given":"Patrick L.","email":"pbarnard@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":754832,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70202371,"text":"70202371 - 2018 - Regeneration and expansion of Quercus tomentella (island oak) groves on Santa Rosa Island","interactions":[],"lastModifiedDate":"2019-02-26T15:06:57","indexId":"70202371","displayToPublicDate":"2018-12-17T15:06:50","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3746,"text":"Western North American Naturalist","onlineIssn":"1944-8341","printIssn":"1527-0904","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Regeneration and expansion of Quercus tomentella (island oak) groves on Santa Rosa Island","title":"Regeneration and expansion of Quercus tomentella (island oak) groves on Santa Rosa Island","docAbstract":"Quercus tomentella (island oak) is an endemic species that plays a key functional role in Channel Island ecosystems. Growing in groves on highland ridges, Q. tomentella captures fog and increases water inputs, stabilizes soils, and provides habitat for flora and fauna. This cloud forest system has been impacted by a long history of ranching, and restoration efforts are underway that include erosion control, leaf litter capture, fog capture, and reforestation. To inform retoration efforts, we explored tree regeneration and the potential for Q. tomentella grove expansion on Santa Rosa Island. We delineated current and historic groves at Black Mountain by comparing stand maps from 1989 and aerial photographs from 1994 and 2015. We evaluated regeneration in the outlying areas by recording the location, diameter at breast height, number of trunks, height class, percent crown mortality, nurse plant species (if present), and reproductive status for all 4355 outlying seedlings, saplings, and mature trees. We defined outliers as individuals that were 15 m outside of the canopy of island oak groves. There are 14 groves at Black Mountain, and grove size expanded by an average of 36.9% (SD 18.5%) between 1994 and 2015. Nurse plants correlated positively with outlier tree height and reduced percent crown mortality. This effect is potentially due to increased fog drip from nurse plant species such as Quercus pacifica (island scrub oak), Heteromeles arbutifolia (toyon), and Baccharis pilularis (coyote brush). These results indicate that Q. tomentella is regenerating and that nurse plants can serve as catalysts for ecosystem restoration.
","language":"English","publisher":"Monte L. Bean Life Science Museum (Brigham Young University)","doi":"10.3398/064.078.0415","usgsCitation":"Woolsey, J., Hanna, C., McEachern, K., Anderson, S., and Hartman, B.D., 2018, Regeneration and expansion of Quercus tomentella (island oak) groves on Santa Rosa Island: Western North American Naturalist, v. 78, no. 4, p. 758-767, https://doi.org/10.3398/064.078.0415.","productDescription":"10 p.","startPage":"758","endPage":"767","ipdsId":"IP-087991","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":361561,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Santa Rosa Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.25497436523436,\n 33.88922749934704\n ],\n [\n -119.96315002441408,\n 33.88922749934704\n ],\n [\n -119.96315002441408,\n 34.048108084909835\n ],\n [\n -120.25497436523436,\n 34.048108084909835\n ],\n [\n -120.25497436523436,\n 33.88922749934704\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"78","issue":"4","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Woolsey, Jay","contributorId":213580,"corporation":false,"usgs":false,"family":"Woolsey","given":"Jay","email":"","affiliations":[{"id":38803,"text":"CSU Channel Islands","active":true,"usgs":false}],"preferred":false,"id":758056,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hanna, Cause","contributorId":69035,"corporation":false,"usgs":false,"family":"Hanna","given":"Cause","affiliations":[{"id":13013,"text":"Department of Environmental Science, Policy and Management, University of California, Berkeley","active":true,"usgs":false}],"preferred":false,"id":758057,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McEachern, Kathryn 0000-0003-2631-8247 kathryn_mceachern@usgs.gov","orcid":"https://orcid.org/0000-0003-2631-8247","contributorId":146324,"corporation":false,"usgs":true,"family":"McEachern","given":"Kathryn","email":"kathryn_mceachern@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":758055,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Anderson, Sean","contributorId":213581,"corporation":false,"usgs":false,"family":"Anderson","given":"Sean","affiliations":[{"id":38803,"text":"CSU Channel Islands","active":true,"usgs":false}],"preferred":false,"id":758058,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hartman, Brett D.","contributorId":213582,"corporation":false,"usgs":false,"family":"Hartman","given":"Brett","email":"","middleInitial":"D.","affiliations":[{"id":38803,"text":"CSU Channel Islands","active":true,"usgs":false}],"preferred":false,"id":758059,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70200497,"text":"ofr20181169 - 2018 - User guide for the Massachusetts Sustainable-Yield Estimator (MA SYE—version 2.0) computer program","interactions":[],"lastModifiedDate":"2018-12-17T13:26:20","indexId":"ofr20181169","displayToPublicDate":"2018-12-17T11:00:00","publicationYear":"2018","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":"2018-1169","displayTitle":"User Guide for the Massachusetts Sustainable-Yield Estimator (MA SYE—Version 2.0) Computer Program","title":"User guide for the Massachusetts Sustainable-Yield Estimator (MA SYE—version 2.0) computer program","docAbstract":"This report is a user guide for the Massachusetts Sustainable-Yield Estimator (MA SYE) computer program (version 2.0). The MA SYE was developed by the U.S. Geological Survey in cooperation with the Massachusetts Department of Environmental Protection to provide a planning-level decision-support tool designed to help decision makers estimate daily mean streamflows and selected streamflow statistics to assess sustainable water use at ungaged sites in Massachusetts. The MA SYE provides estimates of unaltered streamflow (which is assumed to occur in the absence of any water withdrawals or wastewater discharges and with minimal human development), net streamflow alterations caused by water use, water-use-adjusted streamflow, streamflow yields (estimated unaltered streamflow minus user-defined flow targets), and estimates of the accuracy and uncertainty of estimated unaltered streamflow. The MA SYE uses basin characteristics and water-use volumes (water withdrawals and wastewater-return flows) obtained from the U.S. Geological Survey online StreamStats application to estimate the unaltered and water-use-adjusted streamflows. The MA SYE is a database application with a graphical user interface developed by using Visual Basic for Applications with the 32-bit version of Microsoft Access. The graphical user interface is designed include full documentation for users: an introductory instruction form and onscreen help within each interactive form, including explanation buttons, context-sensitive help buttons, and tool-tip and status-bar messages.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181169","collaboration":"Prepared in cooperation with the Massachusetts Department of Environmental Protection","usgsCitation":"Granato, G.E., and Levin, S.B., 2018, User guide for the Massachusetts Sustainable-Yield Estimator (MA SYE—version 2.0) computer program: U.S. Geological Survey Open-File Report 2018–1169, 7 p., https://doi.org/10.3133/ofr20181169.\n\n","productDescription":"Report: vi, 7 p.; Software release","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-098957","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":358596,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P95VX5AX","text":"USGS software release","description":"USGS software release","linkHelpText":"Massachusetts Sustainable-Yield Estimator (MASYE) application software (version 2.0) 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\"}}]}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
The Massachusetts Sustainable-Yield Estimator is a decision support tool that provides estimates of daily unaltered streamflow, water-use-adjusted streamflow, and water availability for ungaged, user-defined basins in Massachusetts. Daily streamflow at the ungaged site is estimated for unaltered (no water use) and water-use scenarios. The procedure for estimating streamflow was developed previously and has been implemented with minor changes and updated water-use data in version 2.0 of the Massachusetts Sustainable-Yield Estimator. Unaltered streamflow at selected exceedance probabilities is estimated by previously published regression equations. Streamflow is interpolated between the regressed quantiles to produce a continuous flow duration curve. A daily streamflow time series is produced for the ungaged site by relating the estimated flow duration curve at the ungaged site to a flow duration curve at a gaged reference site and then transferring the dates from the reference site to the ungaged site.
Minor refinements were made to the previously published methods to estimate unaltered and water-use-adjusted streamflow, including a procedure to enforce the monotonic structure of the regression-based unaltered flow quantiles, improvements to the interpolation method used for computing the estimated flow duration curve, and updates to the methods used to compute time-lagged stream alterations from groundwater pumping or discharges. Additionally, a procedure was developed to estimate prediction intervals for daily and monthly unregulated streamflow time series at an ungaged site.
The Massachusetts Sustainable-Yield Estimator computes water-use-adjusted streamflow using water-use data provided by the Massachusetts Department of Environmental Protection. Available water-use data included monthly withdrawal and wastewater discharge volumes from 2010 to 2014 for surface-water and groundwater sources. Water-use-adjusted streamflow represents the potential effect of current water use on natural streamflow in the basin over the range of historical hydrologic conditions. Georeferenced water withdrawal and discharge volumes were incorporated into the Massachusetts StreamStats web application for use in version 2.0 of the Massachusetts Sustainable-Yield Estimator. To compute water-use-adjusted streamflow, mean daily withdrawals and discharges within a user-defined basin are subtracted and added to the unaltered time series, respectively. Surface-water volumes are applied directly to the equation. Time-lagged streamflow alterations from groundwater withdrawal or wastewater discharge sources are estimated by using a response-coefficient method developed from results of previously published, calibrated groundwater models in Massachusetts.
The Massachusetts Sustainable-Yield Estimator was updated to version 2.0 to improve software stability and usability. The version 2.0 software application was developed in Microsoft Access with a graphical user interface. All geoprocessing steps, including basin delineation and compilation of basin characteristics and water use within the basin, were completed in the Massachusetts StreamStats web application and exported for use by the Massachusetts Sustainable-Yield Estimator version 2.0.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185146","collaboration":"Prepared in cooperation with the Massachusetts Department of Environmental Protection","usgsCitation":"Levin, S.B., and Granato, G.E., 2018, Methods used to estimate daily streamflow and water availability in the Massachusetts Sustainable-Yield Estimator version 2.0: U.S. Geological Survey Scientific Investigations Report 2018–5146, 16 p., https://doi.org/10.3133/sir20185146.","productDescription":"Report: vi, 16 p.; Software release","ipdsId":"IP-087736","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":360268,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5146/coverthb.jpg"},{"id":360271,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P95VX5AX ","text":"USGS software release","description":"USGS software 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\"}}]}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
Occupancy models provide a reliable method of estimating species distributions while accounting for imperfect detectability. The cost of accounting for false absences is that detection and nondetection surveys typically require repeated visits to a site or multiple-observer techniques. More efficient methods of collecting data to estimate detection probabilities would allow additional sites to be surveyed for the same amount of effort, which would support more precise estimation of covariate effects to improve inference about underlying ecological processes. Time-to-detection surveys allow the estimation of detection probability based on a single site visit by one observer, and therefore might be an efficient technique for herpetological occupancy studies. We evaluated the use of time-to-detection surveys to estimate the occupancy of pond-breeding amphibians at Point Reyes National Seashore, California, USA, including variables that affected detection rates and the probability of occurrence. We found that detection times were short enough, and occupancy was high enough, to estimate reliably the probability of occurrence of three pond-breeding amphibians at Point Reyes National Seashore, and that survey and site conditions had species-specific effects on detection rates. In particular, pond characteristics affected detection times of all commonly detected species. Probability of occurrence of Sierran Treefrogs (Hyliola sierra) and Rough-Skinned Newts (Taricha granulosa) was negatively related to the detection of fish and pond area. Time-to-detection surveys can provide an efficient method for estimating detection probabilities and accounting for false absences in occupancy studies of reptiles and amphibians.
","language":"English","publisher":"The Society for the Study of Amphibians and Reptiles","doi":"10.1670/18-049","usgsCitation":"Halstead, B., Kleeman, P.M., and Rose, J.P., 2018, Time-to-detection occupancy modeling: An efficient method for analyzing the occurrence of amphibians and reptiles: Journal of Herpetology, v. 52, no. 4, p. 415-424, https://doi.org/10.1670/18-049.","productDescription":"10 p.; Data Release","startPage":"415","endPage":"424","ipdsId":"IP-098079","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":437651,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9A9LA1O","text":"USGS data release","linkHelpText":"Time to detection data for Point Reyes pond-breeding amphibians, 2017"},{"id":360358,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Point Reyes National Seashore","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.03451538085939,\n 37.92578434712101\n ],\n [\n -122.68913269042967,\n 37.92578434712101\n ],\n [\n -122.68913269042967,\n 38.24842651622814\n ],\n [\n -123.03451538085939,\n 38.24842651622814\n ],\n [\n -123.03451538085939,\n 37.92578434712101\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"52","issue":"4","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c18c423e4b006c4f856acce","contributors":{"authors":[{"text":"Halstead, Brian J. 0000-0002-5535-6528 bhalstead@usgs.gov","orcid":"https://orcid.org/0000-0002-5535-6528","contributorId":3051,"corporation":false,"usgs":true,"family":"Halstead","given":"Brian J.","email":"bhalstead@usgs.gov","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":754352,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kleeman, Patrick M. 0000-0001-6567-3239 pkleeman@usgs.gov","orcid":"https://orcid.org/0000-0001-6567-3239","contributorId":3948,"corporation":false,"usgs":true,"family":"Kleeman","given":"Patrick","email":"pkleeman@usgs.gov","middleInitial":"M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":754353,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rose, Jonathan P. 0000-0003-0874-9166 jprose@usgs.gov","orcid":"https://orcid.org/0000-0003-0874-9166","contributorId":199339,"corporation":false,"usgs":true,"family":"Rose","given":"Jonathan","email":"jprose@usgs.gov","middleInitial":"P.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":754354,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70198668,"text":"sir20185109 - 2018 - The Puʻu ʻŌʻō eruption of Kīlauea Volcano, Hawai‘i—Episode 21 through early episode 48, June 1984–April 1987","interactions":[],"lastModifiedDate":"2018-12-17T16:03:44","indexId":"sir20185109","displayToPublicDate":"2018-12-17T09:17:00","publicationYear":"2018","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":"2018-5109","displayTitle":"The Pu‘u ‘Ō‘ō Eruption of Kīlauea Volcano, Hawai‘i—Episode 21 Through Early Episode 48, June 1984–April 1987","title":"The Puʻu ʻŌʻō eruption of Kīlauea Volcano, Hawai‘i—Episode 21 through early episode 48, June 1984–April 1987","docAbstract":"The Pu‘u ‘Ō‘ō eruption from the middle East Rift Zone of Kīlauea Volcano began in January 1983 with intermittent activity along several fissures. By June 1983, the eruption had localized at the Pu‘u ‘Ō‘ō vent and the activity settled into an increasingly regular pattern of brief eruptive episodes characterized by high lava fountains. The first 18 months of the eruption (episodes 1–20) are chronicled in previous publications.
In the two years following episode 20, Pu‘u ‘Ō‘ō produced another 27 high-fountaining episodes. Episodes 21–47 lasted an average of 12.9 hours and were separated by inter-episode periods averaging 26.5 days. The lava fountains, which reached as high as 510 meters (m), fed lava flows (mostly channelized ʻaʻā) that brought the total area covered by the eruption to 40 square kilometers (km2) by the end of episode 47. Flow thickness measurements obtained for episodes 21–40 averaged 3.4 m; lava volumes for episodes 21–47 averaged 8.0×106 m3 per episode (including the 16-day fissure outbreak of episode 35).
The Pu‘u ‘Ō‘ō cone—a composite of pyroclastic material and lava flows—reached its maximum height of 255 m above the pre-eruption surface during episode 43 and maintained that height through episode 47. Short-lived eruptive fissures and vents at or near the base of the Pu‘u ‘Ō‘ō cone accompanied episodes 21, 25, 29, 35, 39, and 44. Episode 35 was unusual in that a fissure on the uprift flank of the cone erupted early in the episode, and then reactivated and extended 2.5 km uprift after the high fountaining was over and erupted for the next 16 days.
The volcano was primed for the 48th episode of high fountaining on July 18, 1986, when the conduit beneath Pu‘u ‘Ō‘ō ruptured again and magma erupted through new fissures at the base of the cone on both its uprift and downrift sides. These fissures were active for only 21 hours, but a third fissure, which opened 3 km downrift from Pu‘u ‘Ō‘ō on July 20, persisted and evolved into a single vent, later named Kupaianaha. Kupaianaha erupted almost continuously for the next 5.5 years (the main part of episode 48). The onset of episode 48 marked the end of episodic high fountaining and the transition to nearly continuous effusion. A lava lake developed over the Kupaianaha vent, and overflows from the lake built a broad, low shield that reached a relatively stable height of 45 m by November 1986.
After weeks of continuous eruption, the main lava channel leading from the lake gradually roofed over, forming a lava tube. By November 1986, the tube had extended from the lake to the ocean, 12 km southeast, closing the coastal highway. Tube-fed flows overran 28 houses in the coastal communities of Kapa‘ahu and Kalapana over the next month.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185109","usgsCitation":"Orr, T.R., Ulrich, G.E., Heliker, C., DeSmither, L.G., and Hoffmann, J.P., 2018, The Pu‘u ‘Ō‘ō eruption of Kīlauea Volcano, Hawai‘i—Episode 21 through early episode 48, June 1984–April 1987: U.S. Geological Survey Scientific Investigations Report 2018–5109, 107 p., https://doi.org/10.3133/sir20185109.","productDescription":"x, 107 p.","onlineOnly":"Y","ipdsId":"IP-087464","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":360340,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5109/sir20185109.pdf","text":"Report ","size":"50 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Scientific Investigations Report 2018–5109"},{"id":360339,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5109/coverthb.jpg"}],"country":"United States","state":"Hawai'i","otherGeospatial":"Kīlauea Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.30685424804688,\n 19.250218840825706\n ],\n [\n -154.9504852294922,\n 19.250218840825706\n ],\n [\n -154.9504852294922,\n 19.44652177370614\n ],\n [\n -155.30685424804688,\n 19.44652177370614\n ],\n [\n -155.30685424804688,\n 19.250218840825706\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Contact,
Hawaiian Volcano Observatory
U.S. Geological Survey
P.O. Box 51
Hawaiʻi Volcanoes National Park, HI 96718-0051
Retrieving accurate volcanic sulfur dioxide (SO2) gas emission rates is important for a variety of purposes. It is an indicator of shallow subsurface magma, and thus may signal impending eruption or unrest. SO2 emission rates are significant for accurately assessing climate impact, and providing context for assessing environmental, agricultural, and human health effects during volcanic eruptions. The U.S. Geological Survey Hawaiian Volcano Observatory uses an array of ten fixed, upward-looking ultraviolet spectrometer systems to measure SO2 emission rates at 10-s sample intervals from the Kīlauea summit. We present Kīlauea SO2 emission rates from the volcano’s summit and middle East Rift Zone during 2014–2017 and discuss the major sources of error for these measurements. Due to the wide range of SO2 emissions encountered at the summit vent, we used a variable wavelength spectral analysis range to accurately quantify both high and low SO2 column densities. We compare measured emission rates from the fixed spectrometer array to independent road and helicopter-based traverse measurements and evaluate the magnitudes and sources of uncertainties for each method. To address the challenge of obtaining accurate plume speed measurements, we examine ground-based wind-speed, plume speed tracking via spectrometer, and SO2 camera derived plume speeds. Our analysis shows that: (1) the summit array column densities calculated using a dual fit window, are within -6 to +22% of results obtained with a variety of other conventional and experimental retrieval methods; (2) emission rates calculated from the summit array located ∼3 km downwind provide the best, practical estimate of summit SO2 release under normal trade wind conditions; (3) ground-based anemometer wind speeds are 22% less than plume speeds determined by cross-correlation of plume features; (4) our best estimate of average Kīlauea SO2 release for 2014–2017 is 5100 t/d, which is comparable to the space-based OMI emissions of 5518 t/d; and (5) short-term variability of SO2 emissions reflects Kīlauea lava lake dynamics.
The reintroduction of extirpated salmonids to historically occupied areas is becoming increasingly common as a conservation and recovery strategy. Often, reintroductions are implemented after the factors that originally led to species extirpation have been reduced, eliminated, or mitigated. For anadromous Oncorhynchus spp. (Pacific salmon) and O. mykiss (steelhead), addressing barriers to migration, which have been a primary factor in the decline and extirpation of many populations, has been an integral component of recovery efforts. Mitigation has included barrier removal, developing fish passage opportunities, and (or) actively trapping and hauling juvenile and adult anadromous salmonids around barriers.
With any reintroduction, there are a number of concerns regarding the ecological impact of the reintroduction efforts. Three of the main tenets to consider when assessing reintroductions are (1) the potential benefits if reintroduction is successful, (2) the biological risk through interactions of reintroduced strains with existing populations, and (3) the factors potentially limiting a successful reintroduction. This report focuses on information and data to address the second and third factors as they apply to the upper Lewis River in Washington.
The upper Lewis River historically contained wild populations of O. tshawytscha (Chinook salmon), O. kisutch (coho salmon), and steelhead. These populations were extirpated after completion of hydropower facilities on Lake Merwin in 1932, Yale Lake in 1953, and Swift Reservoir in 1958, which prevented fish from migrating to and from ocean environments. However, recent licenses issued by the Federal Energy Regulatory Commission require the installation and operation of an upstream fish passage facility at Lake Merwin and a downstream fish passage facility at Swift Reservoir. The licenses were developed in consultation with the National Marine Fisheries Service and the U.S. Fish and Wildlife Service. The overarching goal of this fish reintroduction project is to establish viable, self-sustaining, naturally reproducing, harvestable populations of spring Chinook salmon, winter steelhead, and coho salmon at levels higher than minimum viable populations.
This report uses a combination of field data and existing information to address six key objectives related to the reintroduction in order to inform decisions about passage at the Yale Lake and Lake Merwin hydropower projects. The objectives are (1) a review of information relevant to anadromous fish reintroduction and full fish passage; (2) a habitat assessment of tributaries to Swift Reservoir, Yale Lake, and Lake Merwin; (3) a field study to assess adult potential for spawning success; (4) an assessment of juvenile production and outmigration success; (5) a Lake Merwin predator impact study; and (6) a set of studies assessing interactions between anadromous and resident fish.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181190","collaboration":"Prepared in cooperation with PacifiCorp","usgsCitation":"Al-Chokhachy, R., Clark, C.L., Sorel, M.H., and Beauchamp, D.A., 2018, Development of new information to inform fish passage decisions at the Yale and Merwin hydro projects on the Lewis River, Washington—Final report, 2018: U.S. Geological Survey Open-File Report 2018–1190, 206 p., https://doi.org/10.3133/ofr20181190.","productDescription":"xv, 206 p.","onlineOnly":"Y","ipdsId":"IP-078496","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":360226,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1190/coverthb.jpg"},{"id":360227,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1190/ofr20181190.pdf","text":"Report","size":"12.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1190"}],"country":"United States","state":"Washington","otherGeospatial":"Lewis River","contact":"Director, Northern Rocky Mountain Science Center
U.S. Geological Survey
2327 University Way, Suite 2
Bozeman, MT 59715
We present an exploratory study examining the use of airborne remote-sensing observations to detect ecological responses to elevated CO2emissions from active volcanic systems. To evaluate these ecosystem responses, existing spectroscopic, thermal, and lidar data acquired over forest ecosystems on Mammoth Mountain volcano, California, were exploited, along with in situ measurements of persistent volcanic soil CO2fluxes. The elevated CO2 response was used to statistically model ecosystem structure, composition, and function, evaluated via data products including biomass, plant foliar traits and vegetation indices, and evapotranspiration (ET). Using regression ensemble models, we found that soil CO2 flux was a significant predictor for ecological variables, including canopy greenness (normalized vegetation difference index, NDVI), canopy nitrogen, ET, and biomass. With increasing CO2, we found a decrease in ET and an increase in canopy nitrogen, both consistent with theory, suggesting more water- and nutrient-use-efficient canopies. However, we also observed a decrease in NDVI with increasing CO2 (a mean NDVI of 0.27 at 200 g m−2 d−1 CO2 reduced to a mean NDVI of 0.10 at 800 g m−2 d−1 CO2). This is inconsistent with theory though consistent with increased efficiency of fewer leaves. We found a decrease in above-ground biomass with increasing CO2, also inconsistent with theory, but we did also find a decrease in biomass variance, pointing to a long-term homogenization of structure with elevated CO2. Additionally, the relationships between ecological variables changed with elevated CO2, suggesting a shift in coupling/decoupling among ecosystem structure, composition, and function synergies. For example, ET and biomass were significantly correlated for areas without elevated CO2 flux but decoupled with elevated CO2 flux. This study demonstrates that (a) volcanic systems show great potential as a means to study the properties of ecosystems and their responses to elevated CO2 emissions and (b) these ecosystem responses are measurable using a suite of airborne remotely sensed data.
","language":"English","publisher":"European Biogeosciences Union","doi":"10.5194/bg-15-7403-2018","usgsCitation":"Cawse-Nicholson, K., Fisher, J.B., Famiglietti, C.A., Braverman, A., Schwandner, F.M., Lewicki, J.L., Townsend, P.A., Schimel, D.S., Pavlick, R., Bormann, K., Ferraz, A., Kang, E.L., Ma, P., Bogue, R.R., Youmans, T., and Pieri, D.C., 2018, Ecosystem responses to elevated CO2 using airborne remote sensing at Mammoth Mountain, California: Biogeosciences, v. 15, p. 7403-7418, https://doi.org/10.5194/bg-15-7403-2018.","productDescription":"16 p.","startPage":"7403","endPage":"7418","ipdsId":"IP-094903","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":468185,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/bg-15-7403-2018","text":"Publisher Index Page"},{"id":360330,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Mammoth Mountain","volume":"15","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-12-14","publicationStatus":"PW","scienceBaseUri":"5c14cfb4e4b006c4f8545d1c","contributors":{"authors":[{"text":"Cawse-Nicholson, Kerry","contributorId":211502,"corporation":false,"usgs":false,"family":"Cawse-Nicholson","given":"Kerry","email":"","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":754298,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fisher, Joshua B.","contributorId":211503,"corporation":false,"usgs":false,"family":"Fisher","given":"Joshua","email":"","middleInitial":"B.","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":754299,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Famiglietti, Caroline A.","contributorId":211504,"corporation":false,"usgs":false,"family":"Famiglietti","given":"Caroline","email":"","middleInitial":"A.","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":754300,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Braverman, Amy","contributorId":211505,"corporation":false,"usgs":false,"family":"Braverman","given":"Amy","email":"","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":754301,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schwandner, Florian M.","contributorId":211506,"corporation":false,"usgs":false,"family":"Schwandner","given":"Florian","email":"","middleInitial":"M.","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":754302,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lewicki, Jennifer L. 0000-0003-1994-9104 jlewicki@usgs.gov","orcid":"https://orcid.org/0000-0003-1994-9104","contributorId":5071,"corporation":false,"usgs":true,"family":"Lewicki","given":"Jennifer","email":"jlewicki@usgs.gov","middleInitial":"L.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":754297,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Townsend, Philip A.","contributorId":211507,"corporation":false,"usgs":false,"family":"Townsend","given":"Philip","email":"","middleInitial":"A.","affiliations":[{"id":16925,"text":"University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":754303,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Schimel, David S.","contributorId":211508,"corporation":false,"usgs":false,"family":"Schimel","given":"David","email":"","middleInitial":"S.","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":754304,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Pavlick, Ryan","contributorId":211509,"corporation":false,"usgs":false,"family":"Pavlick","given":"Ryan","email":"","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":754305,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Bormann, Kathryn J.","contributorId":211510,"corporation":false,"usgs":false,"family":"Bormann","given":"Kathryn J.","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":754306,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Ferraz, Antonio","contributorId":211511,"corporation":false,"usgs":false,"family":"Ferraz","given":"Antonio","email":"","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":754307,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Kang, Emily L.","contributorId":211512,"corporation":false,"usgs":false,"family":"Kang","given":"Emily","email":"","middleInitial":"L.","affiliations":[{"id":38260,"text":"University of Cincinnnati","active":true,"usgs":false}],"preferred":false,"id":754308,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Ma, Pulong","contributorId":211513,"corporation":false,"usgs":false,"family":"Ma","given":"Pulong","email":"","affiliations":[{"id":38260,"text":"University of Cincinnnati","active":true,"usgs":false}],"preferred":false,"id":754309,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Bogue, Robert R.","contributorId":211528,"corporation":false,"usgs":false,"family":"Bogue","given":"Robert","email":"","middleInitial":"R.","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":754334,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Youmans, Thomas","contributorId":211529,"corporation":false,"usgs":false,"family":"Youmans","given":"Thomas","email":"","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":754335,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Pieri, David C.","contributorId":211514,"corporation":false,"usgs":false,"family":"Pieri","given":"David","email":"","middleInitial":"C.","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":754310,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}} ,{"id":70201189,"text":"ofr20131024D - 2018 - Lithostratigraphic framework in boreholes from Goldstone Lake and Nelson Lake Basins, Fort Irwin, California","interactions":[{"subject":{"id":70201189,"text":"ofr20131024D - 2018 - Lithostratigraphic framework in boreholes from Goldstone Lake and Nelson Lake Basins, Fort Irwin, California","indexId":"ofr20131024D","publicationYear":"2018","noYear":false,"chapter":"D","title":"Lithostratigraphic framework in boreholes from Goldstone Lake and Nelson Lake Basins, Fort Irwin, California"},"predicate":"IS_PART_OF","object":{"id":70201192,"text":"ofr20131024 - 2014 - Geology and geophysics applied to groundwater hydrology at Fort Irwin, California","indexId":"ofr20131024","publicationYear":"2014","noYear":false,"title":"Geology and geophysics applied to groundwater hydrology at Fort Irwin, California"},"id":1}],"isPartOf":{"id":70201192,"text":"ofr20131024 - 2014 - Geology and geophysics applied to groundwater hydrology at Fort Irwin, California","indexId":"ofr20131024","publicationYear":"2014","noYear":false,"title":"Geology and geophysics applied to groundwater hydrology at Fort Irwin, California"},"lastModifiedDate":"2024-06-26T15:40:52.511787","indexId":"ofr20131024D","displayToPublicDate":"2018-12-14T12:31:47","publicationYear":"2018","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":"2013-1024","chapter":"D","title":"Lithostratigraphic framework in boreholes from Goldstone Lake and Nelson Lake Basins, Fort Irwin, California","docAbstract":"In 2011 and 2012, the sedimentary basins in the Fort Irwin National Training Center, California, were evaluated for groundwater resources using a variety of techniques, including drilling of boreholes. This study summarizes lithostratigraphic features and deposits in 8 of 10 boreholes drilled in 2 basins located in the western part of Fort Irwin. The western part of Fort Irwin straddles the eastern edge of the Miocene Eagle Crags volcanic field; therefore, many of the rocks penetrated in the boreholes are primary volcanic deposits (lava flow, pyroclastic flow, and fallout tephra deposits) and tuffaceous or lithic-rich sedimentary rocks (siltstone to cobble conglomerates) deposited in alluvial, fluvial, lacustrine, and possibly groundwater discharge environments. Boreholes were drilled with mud-rotary techniques that result in cuttings samples, and only two to four cores ranging in length from 3 to 5 feet (ft) were collected in each borehole.
Correlation of lithostratigraphic features to borehole geophysical logs (especially gamma and resistivity) helps to establish properties of the rock and enables identification of depositional sequences of similar rock types. Lithostratigraphic features and resistivity in boreholes compare reasonably well to nearby time-domain electromagnetic sounding (resistivity) model results.
There is no direct age control on the rocks penetrated in the boreholes. The abundance of tuffaceous material as primary or slightly redeposited matrix is used to identify rocks deposited during the activity of the Eagle Crags volcanic field in the Miocene. In contrast, sedimentary rocks composed of detrital and epiclastic grains (only a few of which are tuffaceous rocks as clasts) are inferred to have been deposited during the Quaternary or Pliocene(?). The lithostratigraphic-based estimates of relative age indicate the typical thickness of the Quaternary or Pliocene(?) deposits is 70–170 ft, and that several water-bearing horizons are probable in the Miocene(?) section.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Geology and geophysics applied to groundwater hydrology at Fort Irwin, California","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131024D","usgsCitation":"Buesch, D.C., 2018, Lithostratigraphic framework in boreholes from Goldstone Lake and Nelson Lake Basins, Fort Irwin, California, chap. D of Buesch, D.C., ed., Geology and geophysics applied to groundwater hydrology at Fort Irwin, California: U.S. Geological Survey Open-file Report 2013–1024–D, 133 p., https://doi.org/10.3133/ofr20131024D.","productDescription":"vi, 133 p.","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-079918","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":362164,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2013/1024/d/ofr20131024d_table2.1.xls","text":"Table 2.1","size":"56 KB xls","description":"OFR 2013-1024 Chapter D Table 2.1"},{"id":360342,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1024/d/ofr20131024d.pdf","text":"Report","size":"8.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2013-1024 Chapter D"},{"id":360343,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2013/1024/d/coverthb.jpg"}],"country":"United States","state":"California","county":"San Bernardino County","city":"Fort Irwin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117,\n 35\n ],\n [\n -116,\n 35\n ],\n [\n -116,\n 35.67\n ],\n [\n -117,\n 35.67\n ],\n [\n -117,\n 35\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Contact Information,
Geology, Minerals, Energy, & Geophysics Science Center—Menlo Park
U.S. Geological Survey
345 Middlefield Road
Menlo Park, CA 94025-3591
One important component of continental-scale hydrologic modeling is quantifying the level of uncertainty in long-term hydrologic simulations and providing a range of possible simulated streamflow and/or runoff values for gaged and ungaged locations. In this paper, uncertainty was quantified for simulated streamflow and runoff generated from a monthly water balance model (MWBM) at 1575 streamgages and 109,951 hydrologic response units (HRUs), which span the conterminous United States (CONUS). A stochastic-approach, which incorporated the properties of modeled streamflow residuals back into the simulated model output, was used to create time series of upper and lower uncertainty intervals (UIs) around the simulated monthly time series. This approach was applied to an existing hydrologic regionalization implementation. Metrics used to evaluate the UIs across the CONUS (the coverage ratio, average width index, and interval skill score) indicated that on average the UIs were reliable, skillful, and sharp in being able to both contain measured streamflow observations and reduce estimates of uncertainty based on expected model predictions. These uncertainty evaluation metrics can complement each other in characterizing model skill and uncertainty over large-scale domains.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.advwatres.2018.10.005","usgsCitation":"Bock, A.R., Farmer, W.H., and Hay, L., 2018, Quantifying uncertainty in simulated streamflow and runoff from a continental-scale monthly water balance model: Advances in Water Resources, v. 122, p. 166-175, https://doi.org/10.1016/j.advwatres.2018.10.005.","productDescription":"10 p.","startPage":"166","endPage":"175","ipdsId":"IP-094722","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":360293,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"122","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c14cfb5e4b006c4f8545d26","contributors":{"authors":[{"text":"Bock, Andrew R. 0000-0001-7222-6613 abock@usgs.gov","orcid":"https://orcid.org/0000-0001-7222-6613","contributorId":4580,"corporation":false,"usgs":true,"family":"Bock","given":"Andrew","email":"abock@usgs.gov","middleInitial":"R.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":754251,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Farmer, William H. 0000-0002-2865-2196 wfarmer@usgs.gov","orcid":"https://orcid.org/0000-0002-2865-2196","contributorId":4374,"corporation":false,"usgs":true,"family":"Farmer","given":"William","email":"wfarmer@usgs.gov","middleInitial":"H.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":754253,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hay, Lauren E. 0000-0003-3763-4595","orcid":"https://orcid.org/0000-0003-3763-4595","contributorId":211478,"corporation":false,"usgs":true,"family":"Hay","given":"Lauren E.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":754252,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70199284,"text":"ofr20131024C - 2018 - Cenozoic geology of Fort Irwin and vicinity, California","interactions":[{"subject":{"id":70199284,"text":"ofr20131024C - 2018 - Cenozoic geology of Fort Irwin and vicinity, California","indexId":"ofr20131024C","publicationYear":"2018","noYear":false,"chapter":"C","displayTitle":"Cenozoic Geology of Fort Irwin and Vicinity, California","title":"Cenozoic geology of Fort Irwin and vicinity, California"},"predicate":"IS_PART_OF","object":{"id":70201192,"text":"ofr20131024 - 2014 - Geology and geophysics applied to groundwater hydrology at Fort Irwin, California","indexId":"ofr20131024","publicationYear":"2014","noYear":false,"title":"Geology and geophysics applied to groundwater hydrology at Fort Irwin, California"},"id":1}],"isPartOf":{"id":70201192,"text":"ofr20131024 - 2014 - Geology and geophysics applied to groundwater hydrology at Fort Irwin, California","indexId":"ofr20131024","publicationYear":"2014","noYear":false,"title":"Geology and geophysics applied to groundwater hydrology at Fort Irwin, California"},"lastModifiedDate":"2019-03-18T18:19:25","indexId":"ofr20131024C","displayToPublicDate":"2018-12-14T10:31:31","publicationYear":"2018","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":"2013-1024","chapter":"C","displayTitle":"Cenozoic Geology of Fort Irwin and Vicinity, California","title":"Cenozoic geology of Fort Irwin and vicinity, California","docAbstract":"The geology of the Fort Irwin National Training Center in the north-central Mojave Desert, California, provides insights into the hydrology and water resources of the area. The Fort Irwin area is underlain by rocks ranging in age from Proterozoic to Quaternary that have been deformed by faults as young as Quaternary. Pre-Tertiary sedimentary, igneous, and metamorphic bedrock and Miocene volcanic and sedimentary rocks are exposed in the mountains and ridges, between which are basins containing Quaternary to Pliocene deposits. During the Miocene, in the western part of Fort Irwin, development of the Eagle Crags volcanic field resulted in a complex assemblage of lava flows, pyroclastic flow and fallout tephra deposits, and volcaniclastic sedimentary rocks that were deposited in alluvial, fluvial, and locally lacustrine environments; in the eastern part of Fort Irwin, epiclastic sedimentary rocks and minor tuffaceous rocks were deposited in alluvial, fluvial, and locally lacustrine environments. In the Pliocene and Quaternary, sandstone and conglomerate were deposited in alluvial and fluvial environments, and locally fine-grained materials were deposited in lacustrine, eolian, playa, and groundwater discharge environments. The Fort Irwin area is transected by Neogene to Holocene northwest- and east-striking (and fewer northeast-striking) strike-slip, normal, and locally thrust faults. Structural blocks between faults are broadly warped, and locally rocks adjacent to the faults are folded and sheared. Many of these faults influenced the formation or modification of basins, especially after about 11 million years, when the Eastern California Shear Zone developed in this area. The three-dimensional geologic framework produced by the late Cenozoic stratigraphic and structural history is represented by the continuity or spatial limitations of lithostratigraphic and correlative hydrogeologic properties. The continuity or limitations of rocks and properties influence how water moved (and moves) through the hydrogeologic system.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Geology and geophysics applied to groundwater hydrology at Fort Irwin, California","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131024C","collaboration":"Prepared in cooperation with the U.S. Army, Fort Irwin National Training Center","usgsCitation":"Buesch, D.C., Miller, D.M., and Menges, C.M., 2018, Cenozoic geology of Fort Irwin and vicinity, California, chap. C of Buesch, D.C., ed., Geology and geophysics applied to groundwater hydrology at Fort Irwin, California: U.S. Geological Survey Open-File Report 2013–1024–C, 39 p., https://doi.org/10.3133/ofr20131024C.","productDescription":"Report: iv, 39 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-079524","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":359938,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1024/c/ofr20131024c.pdf","text":"Report","size":"7.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Open-File Report 2013-1024"},{"id":359937,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2013/1024/c/coverthb.jpg"}],"country":"United States","state":"California","county":"San Bernardino County","city":"Fort Irwin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117,\n 35\n ],\n [\n -116,\n 35\n ],\n [\n -116,\n 35.67\n ],\n [\n -117,\n 35.67\n ],\n [\n -117,\n 35\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Contact Information,
Geology, Minerals, Energy, & Geophysics Science Center—Menlo Park
U.S. Geological Survey
345 Middlefield Road
Menlo Park, CA 94025-3591
The Southern Great Plains Rapid Ecoregional Assessment was conducted in partnership with the Bureau of Land Management (BLM) and the Great Plains Landscape Conservation Cooperative. The overall goal of the Rapid Ecoregional Assessments (REAs) is to compile and synthesize regional datasets to facilitate evaluation of the cumulative effects of change agents on priority ecological communities and species. In particular, the REAs identify and map the distribution of communities and wildlife habitats at broad spatial extents and provide assessments of ecological conditions. The REAs also identify where and to what degree ecological resources are currently at risk from change agents, such as development, fire, invasive species, and climate change. The REAs can help managers identify and prioritize potential areas for conservation or restoration, assess cumulative effects as required by the National Environmental Policy Act, and inform landscape-level planning and management decisions for multiple uses of public lands.
Management questions form the basis for the REA framework and were developed in conjunction with the BLM and other stakeholders. Conservation elements are communities and species that are of regional management concern. Core management questions relate to the key ecological attributes and change agents associated with each conservation element. Integrated management questions synthesize the results of the primary core management questions into overall landscape-level ranks for each conservation element.
The ecological communities evaluated as conservation elements are shortgrass, mixed-grass, and sand prairies; all grasslands; riparian and nonplaya wetlands; playa wetlands and saline lakes; and prairie streams and rivers. Species and species assemblages evaluated are the freshwater mussel assemblage, Arkansas River shiner (Notropis girardi), ferruginous hawk (Buteo regalis), lesser prairie chicken (Tympanuchus pallidicinctus), snowy plover (Charadrius nivosus), mountain plover (Charadrius montanus), long-billed curlew (Numenius americanus), interior least tern (Sternula antillarum athalassos), burrowing owl (Athene cunicularia), black-tailed prairie dog (Cynomys ludovicianus), bat assemblage, swift fox (Vulpes velox), and mule deer (Odocoileus hemionus).
The Southern Great Plains REA is summarized in a series of three reports and associated datasets. The pre-assessment report (available online at https://doi.org/10.3133/ofr20151003) summarizes the process used by the REA stakeholders to select management questions, conservation elements, and change agents. It also provides background information for each conservation element. Volume I of the Southern Great Plains REA report addresses the ecological communities (available online at https://doi.org/10.3133/ofr20171100). Volume II (this volume) addresses the species and species assemblages. All source and derived datasets used to produce the maps and graphs for REAs are available online at the BLM Landscape Approach Data Portal (https://landscape.blm.gov/geoportal/catalog/REAs/REAs.page).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181109","collaboration":"Prepared in cooperation with the Bureau of Land Management and the Great Plains Landscape Conservation Cooperative","usgsCitation":"Reese, G.C., Carr, N.B., and Burris, L.E., 2018, Southern Great Plains Rapid Ecoregional Assessment—Volume II. Species and assemblages (ver. 1.1, December 2018): U.S. Geological Survey Open-File Report 2018–1109, 134 p., https://doi.org/10.3133/ofr20181109.","productDescription":"xiii, 134 p.","onlineOnly":"Y","ipdsId":"IP-094978","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":360274,"rank":5,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2018/1109/versionHist.txt","text":"Version History","size":"4.00 KB","linkFileType":{"id":2,"text":"txt"},"description":"Version History"},{"id":359623,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20171100 ","text":"Open-File Report 2017-1100—","linkHelpText":"Southern Great Plains Rapid Ecoregional assessment—Volume I. Ecological communities"},{"id":359620,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1109/coverthb2.jpg"},{"id":359621,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1109/ofr20181109.pdf","text":"Report","size":"9.34 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1109"},{"id":359622,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20151003","text":"Open-File Report 2015–1003—","linkHelpText":"Southern Great Plains Rapid Ecoregional Assessment—Pre-Assessment Report"}],"country":"United States","state":"Colorado, Kansas, Nebraska, New Mexico, Oklahoma, Texas, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.14990234375,\n 30.939924331023445\n ],\n [\n -96.2841796875,\n 30.939924331023445\n ],\n [\n -96.2841796875,\n 43.08493742707592\n ],\n [\n -106.14990234375,\n 43.08493742707592\n ],\n [\n -106.14990234375,\n 30.939924331023445\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.1: December 2018; Version 1.0: November 2018","contact":"Director, Fort Collins Science Center
U.S. Geological Survey
2150 Centre Ave., Building C
Fort Collins, CO 80526-8118
The U.S. Geological Survey has created a hydrogeologic framework for Quaternary sediments in glaciated areas of the conterminous United States that categorizes, maps, and characterizes the glacial sediments at and beneath the land surface. The hydrogeologic framework divides the glaciated United States into 17 distinct hydrogeologic terranes using a geologic approach based on previous mapping, and was characterized using the Glacial Environments and Surficial Sediments geodatabase compiled from the Quaternary Atlas of the United States map series, the Surficial Materials Map of the United States, and several Integrated Geologic Map Databases for the United States; a groundwater use database compiled from public-supply, water-well data; and a lithologic database compiled from State-managed well records and geologic logs. This framework is to be used to assess the occurrence and characteristics of confined and unconfined glacial aquifers, their distribution and extent, and their potential intrinsic susceptibility and vulnerability.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1090","usgsCitation":"Haj, A.E., Soller, D.R., Reddy, J.E., Kauffman, L.J., Yager, R.M., and Buchwald, C.A., 2018, Hydrogeologic framework for characterization and occurrence of confined and unconfined aquifers in quaternary sediments in the glaciated conterminous United States—A digital map compilation and database: U.S. Geological Survey Data Series 1090, 31 p., https://doi.org/10.3133/ds1090.\n\n","productDescription":"Report: vi, 31 p.; Interactive Maps; Data Releases","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-081250","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":359730,"rank":6,"type":{"id":7,"text":"Companion Files"},"url":"https://doi.org/10.3133/sir20185091","text":"Scientific Investigations Report 2018-5091","linkHelpText":"- Characterization and occurrence of confined and unconfined aquifers in Quaternary sediments in the glaciated conterminous United States"},{"id":359725,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1090/coverthb.jpg"},{"id":359729,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7HH6J8X","text":"USGS data release","description":"USGS data release","linkHelpText":"Digital products from a hydrogeologic framework for Quaternary sediments within the glaciated conterminous United States "},{"id":359726,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1090/ds1090.pdf","text":"Report","size":"11.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1090"},{"id":359727,"rank":3,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/ds/1090/ds1090_index.html","linkFileType":{"id":5,"text":"html"},"linkHelpText":"- Index page for oversized, interactive Leaflet maps"},{"id":359728,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F71R6PQG","text":"USGS data release","description":"USGS data release","linkHelpText":"Databases used to develop a hydrogeologic framework for Quaternary sediments in the glaciated conterminous United States"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.969069883,\n 35.090811167\n ],\n [\n -65.343237884,\n 35.090811167\n ],\n [\n -65.343237884,\n 50.932504994\n ],\n [\n -124.969069883,\n 50.932504994\n ],\n [\n -124.969069883,\n 35.090811167\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
400 South Clinton Street
Iowa City, IA 52240
Freshwater streams in Connecticut are subject to many competing demands, including public water supply; agricultural, commercial, and industrial water use; and ecosystem and habitat needs. In recent years, drought has further stressed Connecticut’s water resources. To sustainably allocate and manage water resources among these competing uses, Federal, State, and local water-resource managers require data and modeling tools to estimate the water availability at a variety of temporal and spatial scales for planning purposes. The Connecticut Streamflow and Sustainable Water Use Estimator (CT SSWUE), developed by the U.S. Geological Survey in cooperation with the Connecticut Department of Energy and Environmental Protection, is a decision-support tool for estimating daily unaltered streamflow and sustainable water use at ungaged sites in Connecticut.
The CT SSWUE estimates unaltered daily mean streamflow and water-use-adjusted streamflow for the period from October 1, 1960, to September 30, 2015, and the monthly sustainable net withdrawal at ungaged sites in Connecticut. Unaltered streamflow is the estimated daily mean streamflow in a drainage basin in the absence of any water withdrawals or wastewater discharges and with minimal human development. Sustainable net withdrawal is the maximum net withdrawal (withdrawal minus wastewater discharges) that can be drawn from a basin without critically depleting the water available through natural streamflow patterns. Sustainable net withdrawal is defined for this study as the difference between the unaltered daily mean streamflow and a user-defined target minimum streamflow.
Weighted least squares and Tobit regression techniques were used to develop equations for estimating streamflow at ungaged sites at 19 streamflow quantiles with exceedance probabilities ranging from 0.005 to 99.995 percent. Regressions were based on streamflow quantiles and basin characteristics from 36 reference streamgages in and around Connecticut. Four basin characteristics—drainage area, mean of the soil permeability, mean of the average annual precipitation, and ratio of the length of streams that overlay sand and gravel deposits to the total length of streams in the basin—are used as explanatory variables in the equations. At an ungaged site, interpolation between the streamflow quantiles estimated from the regression equations produces a continuous flow-duration curve. A time series of daily mean streamflow at an ungaged site is then estimated by assuming that for each day, the streamflow quantile occurs on the same date at both a reference streamgage and the ungaged site.
In a remove-one cross validation, estimated unaltered daily mean streamflow agreed well with observed values at reference streamgages, with a few exceptions. Nash Sutcliffe efficiency ranged from −0.43 to 0.97 with a median value of 0.88. The normalized root-mean-square error ranged from 16.6 to 120.4 percent with a median value of 34.5 percent.
An empirical method for estimating 95-percent prediction intervals for unaltered daily and monthly mean streamflow was developed and tested by using the cross-validation data. Prediction intervals for unaltered daily mean streamflow at the cross-validation reference streamgages performed well in most cases. Gaged streamflow values from the cross-validation data fell within the prediction intervals a median 96.6 percent of the time for daily mean time series and 93.9 percent of the time for monthly mean time series.
The CT SSWUE computes water-use-adjusted streamflow using spatially referenced water-use information provided by the Connecticut Department of Energy and Environmental Protection. Available water-use information included permitted and registered water withdrawals and permitted wastewater discharges during 1998 to 2015 for the Thames River Basin and central coastal drainage basins. Water-use information was incorporated into the U.S. Geological Survey StreamStats web application for Connecticut and can be used for computing water-use-adjusted streamflow and sustainable net withdrawal at selected points of interest. Altered daily streamflow is computed by applying average daily withdrawals and wastewater discharges to the water balance equation. Average daily surface water withdrawals and wastewater discharges are applied directly to the daily water balance equation. Time-lagged alterations on streamflow from groundwater withdrawals or wastewater discharges are estimated by using a response-coefficient method developed from results of previously published, calibrated groundwater models.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185135","collaboration":"Prepared in cooperation with the Connecticut Department of Energy and Environmental Protection","usgsCitation":"Levin, S.B., Olson, S.A., Nielsen, M.G., and Granato, G.E., 2018, The Connecticut Streamflow and Sustainable Water Use Estimator—A decision-support tool to estimate water availability at ungaged stream locations in Connecticut: U.S. Geological Survey Scientific Investigations Report 2018–5135, 34 p., https://doi.org/10.3133/sir20185135.","productDescription":"Report: vii, 34 p.; Table; Data Release","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-087738","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":360020,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5135/sir20185135.pdf","text":"Report","size":"8.92 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\"}}]}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
This report is a user guide for the Connecticut Streamflow and Sustainable Water Use Estimator (CT SSWUE) computer program (version 1.0). The CT SSWUE was developed by the U.S. Geological Survey in cooperation with the Connecticut Department of Energy and Environmental Protection to provide a planning-level decision-support tool designed to help decision makers estimate daily mean streamflows and selected streamflow statistics to assess sustainable water use at ungaged sites in Connecticut. The CT SSWUE provides estimates of unaltered streamflow (which is assumed to occur in the absence of any water withdrawals or wastewater discharges and with minimal human development), net streamflow alterations caused by water use, water-use-adjusted streamflow, streamflow yields (estimated unaltered streamflow minus user-defined flow targets), and estimates of the accuracy and uncertainty of estimated unaltered streamflow. The CT SSWUE uses basin characteristics and water-use volumes (water withdrawals and wastewater-return flows) obtained from the U.S. Geological Survey online StreamStats application to estimate the unaltered and water-use-adjusted streamflows. The CT SSWUE is a database application with a graphical user interface developed by using Visual Basic for Applications with the 32-bit version of Microsoft Access. The graphical user interface is designed to include full documentation for users: an introductory instruction form and onscreen help within each interactive form, including explanation buttons, context-sensitive help buttons, and tool-tip and status-bar messages.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181163","collaboration":"Prepared in cooperation with the Connecticut Department of Energy and Environmental Protection","usgsCitation":"Granato, G.E., and Levin, S.B., 2018, User guide for the Connecticut Streamflow and Sustainable Water Use Estimator (CT SSWUE—version 1.0) computer program: U.S. Geological Survey Open-File Report 2018–1163, 7 p., https://doi.org/10.3133/ofr20181163.","productDescription":"vi, 7 p.","ipdsId":"IP-098955","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":360048,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9V6ARUS","text":"USGS data release","description":"USGS data release","linkHelpText":"Connecticut Streamflow and Sustainable Water Use Estimator (CT SSWUE) Application Software "},{"id":360046,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1163/ofr20181163.pdf","text":"Report","size":"360 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1163"},{"id":360045,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1163/coverthb.jpg"},{"id":360047,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20185135","text":"Scientific Investigations Report 2018–5135","linkHelpText":"- The Connecticut Streamflow and Sustainable Water Use Estimator: A Decision-Support Tool To Estimate Water Availability at Ungaged Stream Locations in Connecticut"}],"contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
Context
Habitat complexity in rivers is linked to dynamic fluvial conditions acting at various spatial scales. On regulated rivers in the western United States, tributaries are regions of high energy and disturbance, providing important resource inputs for riparian ecosystems.
Objectives
This study investigated spatial patterns and extents of tributary influence on riparian habitat complexity in the near channel zone along regulated reaches of the Colorado (> 200 km) and Dolores Rivers (~ 300 km) in the western United States. Because tributary confluences are regions of increased dynamism, we hypothesized that: (1) geomorphic and land cover complexity would be greatest close to tributary junctions and decrease with distance from tributaries; and (2) patterns in complexity would vary across different sized spatial units.
Methods
Using a combination of remote sensing and spatial analysis, we classified fluvial features and land cover classes to investigate patterns longitudinally at 10-, 25-, and 100-m spatial units in the near channel zone of two regulated rivers.
Results
Using change point analysis and randomization tests, we detected shifts in riparian habitat complexity closer to tributary junctions. Patterns varied across 10-, 25-, and 100-m spatial units in the near channel zone, with significance (p ≤ 0.05) recorded for 10- and 25-m spatial units.
Conclusions
Tributary junctions deliver critical resource inputs on regulated systems, providing for increased geomorphic and land cover diversity upstream and downstream of tributaries. We found that patterns of response were non-linear and discontinuous, varying across spatial units and potentially influenced by the degree of mainstem flow regulation.
Karst subterranean estuaries (KSEs) extend into carbonate platforms along 12% of all coastlines. A recent study has shown that microbial methane (CH4) consumption is an important component of the carbon cycle and food web dynamics within flooded caves that permeate KSEs. In this study, we obtained high‐resolution (~2.5‐day) temporal records of dissolved methane concentrations and its stable isotopic content (δ13C) to evaluate how regional meteorology and hydrology control methane dynamics in KSEs. Our records show that less methane was present in the anoxic fresh water during the wet season (4,361 ± 89 nM) than during the dry season (5,949 ± 132 nM), suggesting that the wet season hydrologic regime enhances mixing of methane and other constituents into the underlying brackish water. The δ13C of the methane (−38.1 ± 1.7‰) in the brackish water was consistently more 13C‐enriched than fresh water methane (−65.4 ± 0.4‰), implying persistent methane oxidation in the cave. Using a hydrologically based mass balance model, we calculate that methane consumption in the KSE was 21–28 mg CH4·m−2·year−1 during the 6‐month dry period, which equates to ~1.4 t of methane consumed within the 102‐ to 138‐km2 catchment basin for the cave. Unless wet season methane consumption is much greater, the magnitude of methane oxidized within KSEs is not likely to affect the global methane budget. However, our estimates constrain the contribution of a critical resource for this widely distributed subterranean ecosystem.
","language":"English","publisher":"AGU","doi":"10.1029/2018GB006026","usgsCitation":"Brankovits, D., Pohlman, J.W., Ganju, N., Iliffe, T., Lowell, N., Roth, E., Sylva, S., Emmert, J., and Lapham, L.L., 2018, Hydrologic controls of methane dynamics in karst subterranean estuaries: Global Biogeochemical Cycles, v. 32, no. 12, p. 1759-1775, https://doi.org/10.1029/2018GB006026.","productDescription":"17 p.","startPage":"1759","endPage":"1775","ipdsId":"IP-102700","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":468186,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2018gb006026","text":"Publisher Index Page"},{"id":360248,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"32","issue":"12","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2018-12-07","publicationStatus":"PW","scienceBaseUri":"5c137dd2e4b006c4f8514874","contributors":{"authors":[{"text":"Brankovits, David 0000-0002-0863-5698","orcid":"https://orcid.org/0000-0002-0863-5698","contributorId":210617,"corporation":false,"usgs":true,"family":"Brankovits","given":"David","email":"","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":753870,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pohlman, John W. 0000-0002-3563-4586 jpohlman@usgs.gov","orcid":"https://orcid.org/0000-0002-3563-4586","contributorId":145771,"corporation":false,"usgs":true,"family":"Pohlman","given":"John","email":"jpohlman@usgs.gov","middleInitial":"W.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":753871,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ganju, Neil K. 0000-0002-1096-0465","orcid":"https://orcid.org/0000-0002-1096-0465","contributorId":202878,"corporation":false,"usgs":true,"family":"Ganju","given":"Neil K.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":753872,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Iliffe, T.M.","contributorId":201287,"corporation":false,"usgs":false,"family":"Iliffe","given":"T.M.","email":"","affiliations":[],"preferred":false,"id":753873,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lowell, N.","contributorId":211383,"corporation":false,"usgs":false,"family":"Lowell","given":"N.","email":"","affiliations":[{"id":38240,"text":"Lowell Instruments","active":true,"usgs":false}],"preferred":false,"id":753874,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Roth, E.","contributorId":90499,"corporation":false,"usgs":true,"family":"Roth","given":"E.","affiliations":[],"preferred":false,"id":753875,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sylva, S.P.","contributorId":211384,"corporation":false,"usgs":false,"family":"Sylva","given":"S.P.","email":"","affiliations":[{"id":36711,"text":"Woods Hole Oceanographic Institution","active":true,"usgs":false}],"preferred":false,"id":753876,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Emmert, J.A.","contributorId":211385,"corporation":false,"usgs":false,"family":"Emmert","given":"J.A.","email":"","affiliations":[{"id":38241,"text":"Moody Gardens Aquarium","active":true,"usgs":false}],"preferred":false,"id":753877,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Lapham, L. L.","contributorId":140085,"corporation":false,"usgs":false,"family":"Lapham","given":"L.","email":"","middleInitial":"L.","affiliations":[{"id":13383,"text":"University of Maryland Center for Environmental Science, Chesapeake Biological Laboratory, 6 Solomons, Maryland 20688","active":true,"usgs":false}],"preferred":false,"id":753878,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70201798,"text":"70201798 - 2018 - Book review: Analytical groundwater mechanics","interactions":[],"lastModifiedDate":"2019-01-30T14:04:43","indexId":"70201798","displayToPublicDate":"2018-12-13T14:04:36","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3825,"text":"Groundwater","active":true,"publicationSubtype":{"id":10}},"title":"Book review: Analytical groundwater mechanics","docAbstract":"Encapsulating almost 50 years of experience applying mathematics to groundwater flow problems, this latest textbook from Otto Strack (2017) is a tour de force for analytical groundwater approaches. It is comprised of 10 chapters, spanning topics from the basics of groundwater mechanics, to steady state, three‐dimensional, and transient flow, as well as particle tracking and solute transport. The book concludes with a chapter on finite‐difference and finite‐element methods, but the treatment is cursory, focusing on basic principles. The book is high quality, especially with respect to the presentation, due perhaps in no small part to the keen eye of the author's longtime publication resource (and clearly supportive wife) Andrine!
","language":"English","publisher":"Wiley","doi":"10.1111/gwat.12843","usgsCitation":"Hunt, R., 2018, Book review: Analytical groundwater mechanics: Groundwater, v. 57, no. 1, p. 85-85, https://doi.org/10.1111/gwat.12843.","productDescription":"1 p.","startPage":"85","endPage":"85","ipdsId":"IP-102643","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":360826,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"57","issue":"1","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2018-12-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Hunt, Randall J. 0000-0001-6465-9304","orcid":"https://orcid.org/0000-0001-6465-9304","contributorId":16118,"corporation":false,"usgs":true,"family":"Hunt","given":"Randall J.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":755402,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70202360,"text":"70202360 - 2018 - Intensive oyster aquaculture can reduce disease impacts on sympatric wild oysters","interactions":[],"lastModifiedDate":"2019-02-25T13:33:46","indexId":"70202360","displayToPublicDate":"2018-12-13T13:33:37","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5806,"text":"Aquaculture Environment Interactions","active":true,"publicationSubtype":{"id":10}},"title":"Intensive oyster aquaculture can reduce disease impacts on sympatric wild oysters","docAbstract":"Risks associated with disease spread from fish and shellfish farming have plagued the growth and public perception of aquaculture worldwide. However, by processing nutrients and organic material from the water column, the culture of many suspension-feeding bivalves has been proposed as a novel solution toward mitigating problems facing coastal water quality, including the removal of disease-causing parasites. Here we developed and simulated an epidemiological model describing sympatric oyster Crassostrea virginica populations in aquaculture and the wild impacted by the protozoan parasite Perkinsus marinus. Our model captured the indirect interaction between wild and cultured populations that occurs through sharing water-borne P. marinus transmission stages, and we hypothesized that oyster aquaculture can enhance wild oyster populations through reduced parasitism as long as cultured oysters are harvested prior to spreading disease. We found that the density of oysters in aquaculture, which is commonly thought to lead to the spread of disease through farms and out to nearby populations in the wild, has only indirect effects on P. marinustransmission through its interaction with the rate of aquaculture harvests. Sufficient aquaculture harvest, which varies with the susceptibility of farmed oysters to P. marinus infection and their lifespan once infected, reduces disease by diluting parasites in the environment. Our modeling results offer new insights toward the broader epidemiological implications of oyster aquaculture and effective disease management.
","language":"English","publisher":"Inter-Research","doi":"10.3354/aei00290","usgsCitation":"Ben-Horin, T., Burge, C.A., Bushek, D., Groner, M.L., Proestou, D.A., Huey, L.I., Bidegain, G., and Carnegie, R.B., 2018, Intensive oyster aquaculture can reduce disease impacts on sympatric wild oysters: Aquaculture Environment Interactions, v. 10, p. 557-567, https://doi.org/10.3354/aei00290.","productDescription":"11 p.","startPage":"557","endPage":"567","ipdsId":"IP-098954","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":468187,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/aei00290","text":"Publisher Index Page"},{"id":361500,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ben-Horin, Tal","contributorId":58137,"corporation":false,"usgs":false,"family":"Ben-Horin","given":"Tal","email":"","affiliations":[],"preferred":false,"id":757989,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burge, Colleen A.","contributorId":213539,"corporation":false,"usgs":false,"family":"Burge","given":"Colleen","email":"","middleInitial":"A.","affiliations":[{"id":38781,"text":"Institute of Marine and Environmental Technology, University of Maryland Baltimore County, Baltimore, MD 21202","active":true,"usgs":false}],"preferred":false,"id":757990,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bushek, David","contributorId":213540,"corporation":false,"usgs":false,"family":"Bushek","given":"David","email":"","affiliations":[{"id":38782,"text":"Haskin Shellfish Research Laboratory, Rutgers University, Port Norris, NJ 08349","active":true,"usgs":false}],"preferred":false,"id":757991,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Groner, Maya L. 0000-0002-3381-6415","orcid":"https://orcid.org/0000-0002-3381-6415","contributorId":213541,"corporation":false,"usgs":true,"family":"Groner","given":"Maya","email":"","middleInitial":"L.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":757992,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Proestou, Dina A.","contributorId":213542,"corporation":false,"usgs":false,"family":"Proestou","given":"Dina","email":"","middleInitial":"A.","affiliations":[{"id":38783,"text":"National Cold Water Marine Aquaculture Center, U.S. Department of Agriculture Agricultural Research Service, Kingston, RI 02881","active":true,"usgs":false}],"preferred":false,"id":757993,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Huey, Lauren I.","contributorId":213543,"corporation":false,"usgs":false,"family":"Huey","given":"Lauren","email":"","middleInitial":"I.","affiliations":[{"id":38784,"text":"Virginia Institute of Marine Science, College of William & Mary, P.O. Box 1346, Gloucester Point, VA 23062","active":true,"usgs":false}],"preferred":false,"id":757994,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bidegain, Gorka","contributorId":167008,"corporation":false,"usgs":false,"family":"Bidegain","given":"Gorka","email":"","affiliations":[{"id":13403,"text":"University of Southern Mississippi, Department of Biological Sciences, Hattiesburg, Mississippi, USA","active":true,"usgs":false}],"preferred":false,"id":757995,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Carnegie, Ryan B.","contributorId":213544,"corporation":false,"usgs":false,"family":"Carnegie","given":"Ryan","email":"","middleInitial":"B.","affiliations":[{"id":38784,"text":"Virginia Institute of Marine Science, College of William & Mary, P.O. Box 1346, Gloucester Point, VA 23062","active":true,"usgs":false}],"preferred":false,"id":757996,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70201462,"text":"70201462 - 2018 - Accuracies achieved in classifying five leading world crop types and their growth stages using optimal Earth Observing-1 Hyperion hyperspectral narrowbands on Google Earth Engine","interactions":[],"lastModifiedDate":"2018-12-14T10:46:19","indexId":"70201462","displayToPublicDate":"2018-12-13T10:46:13","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Accuracies achieved in classifying five leading world crop types and their growth stages using optimal Earth Observing-1 Hyperion hyperspectral narrowbands on Google Earth Engine","docAbstract":"As the global population increases, we face increasing demand for food and nutrition. Remote sensing can help monitor food availability to assess global food security rapidly and accurately enough to inform decision-making. However, advances in remote sensing technology are still often limited to multispectral broadband sensors. Although these sensors have many applications, they can be limited in studying agricultural crop characteristics such as differentiating crop types and their growth stages with a high degree of accuracy and detail. In contrast, hyperspectral data contain continuous narrowbands that provide data in terms of spectral signatures rather than a few data points along the spectrum, and hence can help advance the study of crop characteristics. To better understand and advance this idea, we conducted a detailed study of five leading world crops (corn, soybean, winter wheat, rice, and cotton) that occupy 75% and 54% of principal crop areas in the United States and the world respectively. The study was conducted in seven agroecological zones of the United States using 99 Earth Observing-1 (EO-1) Hyperion hyperspectral images from 2008–2015 at 30 m resolution. The authors first developed a first-of-its-kind comprehensive Hyperion-derived Hyperspectral Imaging Spectral Library of Agricultural crops (HISA) of these crops in the US based on USDA Cropland Data Layer (CDL) reference data. Principal Component Analysis was used to eliminate redundant bands by using factor loadings to determine which bands most influenced the first few principal components. This resulted in the establishment of 30 optimal hyperspectral narrowbands (OHNBs) for the study of agricultural crops. The rest of the 242 Hyperion HNBs were redundant, uncalibrated, or noisy. Crop types and crop growth stages were classified using linear discriminant analysis (LDA) and support vector machines (SVM) in the Google Earth Engine cloud computing platform using the 30 optimal HNBs (OHNBs). The best overall accuracies were between 75% to 95% in classifying crop types and their growth stages, which were achieved using 15–20 HNBs in the majority of cases. However, in complex cases (e.g., 4 or more crops in a Hyperion image) 25–30 HNBs were required to achieve optimal accuracies. Beyond 25–30 bands, accuracies asymptote. This research makes a significant contribution towards understanding modeling, mapping, and monitoring agricultural crops using data from upcoming hyperspectral satellites, such as NASA’s Surface Biology and Geology mission (formerly HyspIRI mission) and the recently launched HysIS (Indian Hyperspectral Imaging Satellite, 55 bands over 400–950 nm in VNIR and 165 bands over 900–2500 nm in SWIR), and contributions in advancing the building of a novel, first-of-its-kind global hyperspectral imaging spectral-library of agricultural crops (GHISA: www.usgs.gov/WGSC/GHISA).
","language":"English","publisher":"MDPI","doi":"10.3390/rs10122027","usgsCitation":"Aneece, I., and Thenkabail, P.S., 2018, Accuracies achieved in classifying five leading world crop types and their growth stages using optimal Earth Observing-1 Hyperion hyperspectral narrowbands on Google Earth Engine: Remote Sensing, v. 10, no. 12, p. 1-29, https://doi.org/10.3390/rs10122027.","productDescription":"Article 2027; 29 p.","startPage":"1","endPage":"29","ipdsId":"IP-097093","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":468188,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs10122027","text":"Publisher Index Page"},{"id":360295,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"10","issue":"12","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-12-13","publicationStatus":"PW","scienceBaseUri":"5c14cfb7e4b006c4f8545d30","contributors":{"authors":[{"text":"Aneece, Itiya 0000-0002-1201-5459","orcid":"https://orcid.org/0000-0002-1201-5459","contributorId":211471,"corporation":false,"usgs":true,"family":"Aneece","given":"Itiya","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":754190,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thenkabail, Prasad S. 0000-0002-2182-8822 pthenkabail@usgs.gov","orcid":"https://orcid.org/0000-0002-2182-8822","contributorId":570,"corporation":false,"usgs":true,"family":"Thenkabail","given":"Prasad","email":"pthenkabail@usgs.gov","middleInitial":"S.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":754191,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70199036,"text":"ofr20181143 - 2018 - Indicators of ecosystem structure and function for the Upper Mississippi River System","interactions":[],"lastModifiedDate":"2018-12-13T16:01:11","indexId":"ofr20181143","displayToPublicDate":"2018-12-13T06:50:00","publicationYear":"2018","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":"2018-1143","displayTitle":"Indicators of Ecosystem Structure and Function for the Upper Mississippi River System","title":"Indicators of ecosystem structure and function for the Upper Mississippi River System","docAbstract":"This report documents the development of quantitative measures (indicators) of ecosystem structure and function for use in a Habitat Needs Assessment (HNA) for the Upper Mississippi River System (UMRS). HNAs are led periodically by the U.S. Army Corps of Engineers’ Upper Mississippi River Restoration (UMRR) Program, which is the primary habitat restoration program on the UMRS. The UMRR Program helps determine how Federal, State and nongovernmental agencies can best address environmental issues on one of the world’s largest and most diverse river systems. Each indicator in this report represents at least one management objective developed for the river system. These objectives were developed in a previous planning effort using an ecosystem management conceptual framework (USACE, 2011). The objectives represent five essential ecosystem characteristics: hydraulics and hydrology, biogeochemistry, geomorphology, habitat, and biota. Subsequent to the 2011 planning effort, the UMRR increased its focus on improving the health and resilience of the UMRS. The indicators presented here are based on the five essential ecosystem characteristics and four aspects of ecosystems thought to support general ecosystem resilience (the ability of an ecosystem to adapt and respond to disturbances): (1) connectivity, (2) diversity and redundancy, (3) controlling variables, and (4) slow processes. Thus, we developed indicators that quantify both essential ecosystem characteristics and characteristics of a resilient river system. The indicators documented in this report focus on important aspects of river floodplain hydrogeomorphology, given the fundamental role hydrogeomorphology plays in determining habitat conditions and ecosystem health and resilience at broad geographic scales. The information contained within this report provides a broader scale (for example, system-wide) context for management decisions made at finer scales (for example, within river reaches or at project sites) and is designed for use in the formal system-wide Habitat Needs Assessment II (HNA–II) led by the UMRR Program.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181143","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers’ Upper Mississippi River Restoration Program","usgsCitation":"De Jager, N.R., Rogala, J.T., Rohweder, J.J., Van Appledorn, M., Bouska, K.L., Houser, Jeffrey, N., and Jankowski, K.J., 2018, Indicators of ecosystem structure and function for the Upper Mississippi River System: U.S. Geological Survey Open-File Report 2018–1143, 115 p., including 4 appendixes, https://doi.org/10.3133/ofr20181143.","productDescription":"xiii, 115 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-092913","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":360203,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1143/coverthb2.jpg"},{"id":360204,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1143/ofr20181143.pdf","text":"Report","size":"45.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1143"}],"country":"United States","otherGeospatial":"Upper Mississippi River System","contact":"Director, Upper Midwest Environmental Sciences Center
U.S. Geological Survey
2630 Fanta Reed Road
La Crosse, WI 5460
Elevation data are critical for assessments of sea-level rise (SLR) and coastal flooding exposure. Previous research has demonstrated that the quality of data used in elevation-based assessments must be well understood and applied to properly model potential impacts. The cumulative vertical uncertainty of the input elevation data substantially controls the minimum increments of SLR and the minimum planning horizons that can be effectively used in assessments. For regional, continental, or global assessments, several digital elevation models (DEMs) are available for the required topographic information to project potential impacts of increased coastal water levels, whether a simple inundation model is used or a more complex process-based or probabilistic model is employed. When properly characterized, the vertical accuracy of the DEM can be used to report assessment results with the uncertainty stated in terms of a specific confidence level or likelihood category. An accuracy evaluation has been conducted of global DEMs to quantify their inherent vertical uncertainty to demonstrate how accuracy information should be considered when planning and implementing a SLR or coastal flooding assessment. The evaluation approach includes comparison of the DEMs with high-accuracy geodetic control points as the independent reference data over a variety of coastal relief settings. The global DEMs evaluated include SRTM, ASTER GDEM, ALOS World 3D, TanDEM-X, NASADEM, and MERIT. High-resolution, high-accuracy DEM sources, such as airborne lidar and stereo imagery, are also included to give context to the results from the global DEMs. The accuracy characterization results show that current global DEMs are not adequate for high confidence mapping of exposure to fine increments (<1 m) of SLR or with shorter planning horizons (<100 years) and thus they should not be used for such mapping, but they are suitable for general delineation of low elevation coastal zones. In addition to the best practice of rigorous accounting for vertical uncertainty, other recommended procedures are presented for delineation of different types of impact areas (marine and groundwater inundation) and use of regional relative SLR scenarios. The requirement remains for a freely available, high-accuracy, high-resolution global elevation model that supports quantitative SLR and coastal inundation assessments at high confidence levels.
","language":"English","publisher":"Frontiers","doi":"10.3389/feart.2018.00230","usgsCitation":"Gesch, D.B., 2018, Best practices for elevation-based assessments of sea-level rise and coastal flooding exposure: Frontiers in Earth Science, v. 6, p. 1-19, https://doi.org/10.3389/feart.2018.00230.","productDescription":"Article 230; 19 p.","startPage":"1","endPage":"19","ipdsId":"IP-099709","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":468189,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/feart.2018.00230","text":"Publisher Index Page"},{"id":360254,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2018-12-12","publicationStatus":"PW","scienceBaseUri":"5c137dd3e4b006c4f851487e","contributors":{"authors":[{"text":"Gesch, Dean B. 0000-0002-8992-4933 gesch@usgs.gov","orcid":"https://orcid.org/0000-0002-8992-4933","contributorId":2956,"corporation":false,"usgs":true,"family":"Gesch","given":"Dean","email":"gesch@usgs.gov","middleInitial":"B.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":754063,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70239437,"text":"70239437 - 2018 - Communicating information on nature-related topics: Preferred information channels and trust in sources","interactions":[],"lastModifiedDate":"2023-01-13T13:18:11.190282","indexId":"70239437","displayToPublicDate":"2018-12-12T07:15:19","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Communicating information on nature-related topics: Preferred information channels and trust in sources","docAbstract":"How information is communicated influences the public’s environmental perceptions and behaviors. Information channels and sources both play an important role in the dissemination of information. Trust in a source is often used as a proxy for whether a particular piece of information is credible. To determine preferences for information channels and trust in various sources for information on nature-related topics, a mail-out survey was sent to randomly selected U.S. addresses (n = 1,030). Diverse groups of people may have differing communication preferences. Therefore, we explored differences in channel preferences and trust by demographics using regression models. Overall, the most preferred channels were personal experience, reading online content, and watching visual media online. The most trusted sources were science organizations, universities, and friends/family. Channel preferences varied the most by education level and age, while source trust was most influenced by education, race, age, and size of current residence (rural-urban). The influence of demographics varied depending on the individual channel and source, with some groups preferring certain channels or sources but not others. Results are useful to consider when disseminating information on nature-related topics to a general public audience. More broadly, results also suggest spreading information using different channels and sources depending on the specific audience being targeted.