{"pageNumber":"661","pageRowStart":"16500","pageSize":"25","recordCount":165296,"records":[{"id":70206536,"text":"ofr20191129 - 2019 - Peak streamflow and stages at selected streamgages on the Arkansas River in Oklahoma and Arkansas, May to June 2019","interactions":[],"lastModifiedDate":"2019-11-21T12:57:42","indexId":"ofr20191129","displayToPublicDate":"2019-11-20T16:32:35","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-1129","displayTitle":"Peak Streamflow and Stages at Selected Streamgages on the Arkansas River in Oklahoma and Arkansas, May to June 2019","title":"Peak streamflow and stages at selected streamgages on the Arkansas River in Oklahoma and Arkansas, May to June 2019","docAbstract":"

As much as 22 inches of rain fell in Oklahoma in May 2019, resulting in historic flooding along the Arkansas River in Oklahoma and Arkansas. The flooding along the Arkansas River and its tributaries that began in May continued into June 2019. Peaks of record were measured at 12 U.S. Geological Survey (USGS) streamgages on various streams in eastern and northeastern Oklahoma. This report documents the peak streamflows and stages for seven selected streamgages along the Arkansas River in Oklahoma and Arkansas. Most of the flood peaks occurred from May 26 to June 4, 2019. The historic flooding caused homes to fall into the river as a result of bank erosion, forced some towns to be evacuated, and resulted in the highest flood depths in Tulsa, Oklahoma, since 1986. Along the Arkansas River, peak streamflows were recorded at six of the seven selected USGS streamgages, with the seventh streamgage on the Arkansas River having the second highest peak of record at that site since regulation began.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191129","collaboration":"Prepared in cooperation with the Federal Emergency Management Agency and the U.S. Army Corps of Engineers","usgsCitation":"Lewis, J.M., and Trevisan, A.R., 2019, Peak streamflow and stages at selected streamgages on the Arkansas River in Oklahoma and Arkansas, May to June 2019: U.S. Geological Survey Open-File Report 2019–1129, 10 p., https://doi.org/10.3133/ofr20191129.","productDescription":"iv, 10 p.","numberOfPages":"18","onlineOnly":"Y","ipdsId":"IP-112483","costCenters":[{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true}],"links":[{"id":369335,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1129/ofr20191129.pdf","text":"Report","size":"4.04 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 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\"}}]}","contact":"

Director, Oklahoma-Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, Texas 78754–4501

","tableOfContents":"","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2019-11-20","noUsgsAuthors":false,"publicationDate":"2019-11-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Lewis, Jason M. 0000-0001-5337-1890 jmlewis@usgs.gov","orcid":"https://orcid.org/0000-0001-5337-1890","contributorId":3854,"corporation":false,"usgs":true,"family":"Lewis","given":"Jason","email":"jmlewis@usgs.gov","middleInitial":"M.","affiliations":[{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true}],"preferred":true,"id":774902,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Trevisan, A.R. 0000-0002-7295-145X","orcid":"https://orcid.org/0000-0002-7295-145X","contributorId":220399,"corporation":false,"usgs":true,"family":"Trevisan","given":"A.R.","email":"","affiliations":[{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true}],"preferred":true,"id":774903,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70207193,"text":"70207193 - 2019 - Using component ratios to detect metadata and instrument problems of seismic stations: Examples from 18 years of GEOSCOPE data","interactions":[],"lastModifiedDate":"2020-01-08T14:22:39","indexId":"70207193","displayToPublicDate":"2019-11-20T14:53:24","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Using component ratios to detect metadata and instrument problems of seismic stations: Examples from 18 years of GEOSCOPE data","docAbstract":"Replacement or deterioration of seismic instruments and the evolution of the installation conditions and sites can alter the seismic signal in very subtle ways, so it is notoriously difficult to monitor the signal quality of permanent seismic stations. We present a simple tool, energy ratios between each pair of the three recorded components, aimed at characterizing and monitoring signal quality, as a complement to existing methods. To calculate stable daily energy ratios over a large frequency range (0.01 Hz – 5 Hz), we use the daily median energy ratio over all 5-minute windows within the day. The method is applied to all GEOSCOPE stations, for continuous BH channel data collected since 2001. We show applications to identify past gain problems (stations ROCAM and CRZF), to provide feedback after field interventions at remote sites (Antarctic station DRV), and to shed light on complex instrument problems (stations ECH and KIP). Our results show that component energy ratios have excellent time resolution and that they are visually simple for identification of problems. They can be used both for ongoing continuous monitoring of the signal quality, or as a tool to identify past problems. The associated python codes are available on GitHub.","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220190180","usgsCitation":"Pedersen, H.A., Leroy, N., Zigone, D., Vallee, M., Ringler, A.T., and Wilson, D.C., 2019, Using component ratios to detect metadata and instrument problems of seismic stations: Examples from 18 years of GEOSCOPE data: Seismological Research Letters, v. 91, no. 1, p. 272-286, https://doi.org/10.1785/0220190180.","productDescription":"15 p.","startPage":"272","endPage":"286","ipdsId":"IP-112065","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":370182,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"91","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-11-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Pedersen, Helle A.","contributorId":221155,"corporation":false,"usgs":false,"family":"Pedersen","given":"Helle","email":"","middleInitial":"A.","affiliations":[{"id":40340,"text":"Univ. Grenoble Alpes, Univ. Savoie Mont Blanc, CNRS, IRD, IFSTTAR, ISTerre, 38000 Grenoble, France","active":true,"usgs":false}],"preferred":false,"id":777231,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Leroy, Nicolas","contributorId":221156,"corporation":false,"usgs":false,"family":"Leroy","given":"Nicolas","email":"","affiliations":[{"id":40341,"text":"Institut de Physique du Globe de Paris, Sorbonne Paris Cité, Université Paris Diderot, CNRS, France","active":true,"usgs":false}],"preferred":false,"id":777232,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zigone, Dimitri","contributorId":221157,"corporation":false,"usgs":false,"family":"Zigone","given":"Dimitri","email":"","affiliations":[{"id":40342,"text":"Institut de Physique du Globe de Strasbourg, UMR 7516, Université de Strasbourg/EOST, CNRS, Strasbourg, France","active":true,"usgs":false}],"preferred":false,"id":777233,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vallee, Martin","contributorId":221158,"corporation":false,"usgs":false,"family":"Vallee","given":"Martin","email":"","affiliations":[{"id":40341,"text":"Institut de Physique du Globe de Paris, Sorbonne Paris Cité, Université Paris Diderot, CNRS, France","active":true,"usgs":false}],"preferred":false,"id":777234,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ringler, Adam T. 0000-0002-9839-4188 aringler@usgs.gov","orcid":"https://orcid.org/0000-0002-9839-4188","contributorId":145576,"corporation":false,"usgs":true,"family":"Ringler","given":"Adam","email":"aringler@usgs.gov","middleInitial":"T.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":777235,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wilson, David C. 0000-0003-2582-5159 dwilson@usgs.gov","orcid":"https://orcid.org/0000-0003-2582-5159","contributorId":145580,"corporation":false,"usgs":true,"family":"Wilson","given":"David","email":"dwilson@usgs.gov","middleInitial":"C.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":777236,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70205819,"text":"ofr20191109 - 2019 - Chronic wasting disease—Research by the U.S. Geological Survey and partners","interactions":[],"lastModifiedDate":"2021-02-04T00:28:22.935686","indexId":"ofr20191109","displayToPublicDate":"2019-11-20T13:35:00","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-1109","displayTitle":"Chronic Wasting Disease—Research by the U.S. Geological Survey and Partners","title":"Chronic wasting disease—Research by the U.S. Geological Survey and partners","docAbstract":"

Introduction

Chronic wasting disease (CWD) is the only transmissible spongiform encephalopathy, a class of invariably fatal neurodegenerative mammalian diseases associated with a misfolded cellular prion protein found in wild free-ranging animals. Because it has a long incubation period, affected animals in Cervidae (the deer family; referred to as “cervids”) may not show signs of disease for several years. While signs are not specific to CWD, affected cervids (deer, elk, moose, and reindeer) show changes in appearance (such as progressive weight loss) and changes in behavior such as stumbling, tremors, and teeth grinding. CWD can be transmitted by direct contact or through a contaminated environment. The causative prion agent is highly resistant to degradation.

In recent decades, CWD has transitioned from a novel, obscure prion disease of cervids with limited geographical distribution, to a disease that poses substantial ecological, agricultural, and economic risks across large regions of North America. Since its discovery in free-ranging elk and deer populations in the western United States in the 1980s, CWD has been reported in captive or free-ranging cervid populations in 26 States, 3 Canadian Provinces, the Republic of South Korea, Finland, Sweden, and Norway. In addition, the proportion of CWD-infected animals is increasing in many areas where the disease is already established. In some heavily affected areas, total cervid numbers have decreased over time due to CWD, which suggests that these cervid populations may not be sustainable in the long-term.

The U.S. Geological Survey (USGS) conducts wildlife disease surveillance and research to support management of CWD-affected species and their habitats. The scientific information is relevant to governmental agencies that manage wildlife and their habitats including the U.S. Fish and Wildlife Service, the National Park Service, the U.S. Department of Agriculture, and other Federal, State, and Tribal agencies as well as conservation partners (non-governmental organizations, businesses, and private landowners). Each project description in this report (1–30) includes the non-USGS collaborators (Federal, State, Tribal agencies, universities) and a USGS point of contact (principal investigator). If there are USGS publications associated with the project, a publication list is provided at the end of each project description.

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Associate Director, Ecosystems
U.S. Geological Survey
954 National Center
12201 Sunrise Valley Drive
Reston, VA 20192

","tableOfContents":"","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2019-10-23","revisedDate":"2019-11-20","noUsgsAuthors":false,"publicationDate":"2019-10-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Hopkins, M. Camille 0000-0003-1465-6038","orcid":"https://orcid.org/0000-0003-1465-6038","contributorId":219531,"corporation":false,"usgs":true,"family":"Hopkins","given":"M. Camille","affiliations":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"preferred":true,"id":772480,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carlson, Christina M. 0000-0002-4950-8273","orcid":"https://orcid.org/0000-0002-4950-8273","contributorId":219532,"corporation":false,"usgs":true,"family":"Carlson","given":"Christina M.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":772481,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cross, Paul C. 0000-0001-8045-5213","orcid":"https://orcid.org/0000-0001-8045-5213","contributorId":219533,"corporation":false,"usgs":true,"family":"Cross","given":"Paul C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":772482,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Johnson, Christopher J. 0000-0003-4539-2581 cjjohnson@usgs.gov","orcid":"https://orcid.org/0000-0003-4539-2581","contributorId":219534,"corporation":false,"usgs":true,"family":"Johnson","given":"Christopher","email":"cjjohnson@usgs.gov","middleInitial":"J.","affiliations":[{"id":501,"text":"Office of Science Quality and Integrity","active":true,"usgs":true}],"preferred":true,"id":772483,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Richards, Bryan J. 0000-0001-9955-2523","orcid":"https://orcid.org/0000-0001-9955-2523","contributorId":219535,"corporation":false,"usgs":true,"family":"Richards","given":"Bryan","email":"","middleInitial":"J.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":772484,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Russell, Robin E. 0000-0001-8726-7303","orcid":"https://orcid.org/0000-0001-8726-7303","contributorId":219536,"corporation":false,"usgs":true,"family":"Russell","given":"Robin E.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":772485,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Samuel, Michael D.","contributorId":219537,"corporation":false,"usgs":true,"family":"Samuel","given":"Michael D.","affiliations":[],"preferred":true,"id":772486,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sargeant, Glen A. 0000-0003-3845-8503","orcid":"https://orcid.org/0000-0003-3845-8503","contributorId":219538,"corporation":false,"usgs":true,"family":"Sargeant","given":"Glen A.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":772487,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Walsh, Daniel P. 0000-0002-7772-2445","orcid":"https://orcid.org/0000-0002-7772-2445","contributorId":219539,"corporation":false,"usgs":true,"family":"Walsh","given":"Daniel","email":"","middleInitial":"P.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":772488,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Walter, W. David 0000-0003-3068-1073","orcid":"https://orcid.org/0000-0003-3068-1073","contributorId":219540,"corporation":false,"usgs":true,"family":"Walter","given":"W. David","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":772489,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70216024,"text":"70216024 - 2019 - The (mythical) M8.2 off coast of Peru earthquake of 12 December 1908","interactions":[],"lastModifiedDate":"2020-11-03T17:21:36.431251","indexId":"70216024","displayToPublicDate":"2019-11-20T11:18:47","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"title":"The (mythical) M8.2 off coast of Peru earthquake of 12 December 1908","docAbstract":"

Global earthquake catalogs covering the early twentieth century differ in their listings of a large earthquake, or earthquakes, on 12 December 1908. Some catalogs list an M∼7\">M∼7M∼7 earthquake originating in northern Myanmar (Burma) at ∼12:55\">∼12:55∼12:55 UTC on that date. Other catalogs do not list the Myanmar origin but list an earthquake with magnitude 8.2 originating in or near Peru at 12:08 UTC on the date. Some catalogs list both origins, but sometimes with additional evidence suggesting that the 1908 M 8.2 Peru origin may be “mythical.” In a review of arrival times of phases reported in seismic bulletins of 1908, conducted specifically to identify data that might be consistent with the sometimes‐cataloged Peru origin, we do not find a coherent set of such data. Many bulletin arrival times reported for 12 December 1908, however, are mutually consistent with the cataloged Myanmar origin. Comparisons of seismograms recorded at the Seismological Observatory of Göttingen in Germany (station GTT) on 12 December 1908 with seismograms obtained on the same instruments for later large earthquakes that are reliably located in Myanmar and Peru, respectively, are consistent with the implication of the bulletin arrival‐time observations. We conclude that a major earthquake did indeed occur in or near northern Myanmar on 12 December 1908 but that there was not on that date a great earthquake near Peru that would correspond to the sometimes‐cataloged M 8.2 Peru origin.

","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220190232","usgsCitation":"Di Giacomo, D., and Dewey, J.W., 2019, The (mythical) M8.2 off coast of Peru earthquake of 12 December 1908, v. 91, no. 1, p. 488-498, https://doi.org/10.1785/0220190232.","productDescription":"11 p.","startPage":"488","endPage":"498","ipdsId":"IP-112350","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":380081,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Myanmar (Burma)","otherGeospatial":"Northern Myanmar (Burma)","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 95.712890625,\n 21.779905342529645\n ],\n [\n 99.31640625,\n 21.779905342529645\n ],\n [\n 99.31640625,\n 28.69058765425071\n ],\n [\n 95.712890625,\n 28.69058765425071\n ],\n [\n 95.712890625,\n 21.779905342529645\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"91","issue":"1","noUsgsAuthors":false,"publicationDate":"2019-11-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Di Giacomo, Domenico","contributorId":244334,"corporation":false,"usgs":false,"family":"Di Giacomo","given":"Domenico","affiliations":[{"id":48894,"text":"International Seismological Centre, Pipers Lane, Thatcham, RG19 4NS, UK","active":true,"usgs":false}],"preferred":false,"id":803786,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dewey, James W. 0000-0001-8838-2450 jdewey@usgs.gov","orcid":"https://orcid.org/0000-0001-8838-2450","contributorId":5819,"corporation":false,"usgs":true,"family":"Dewey","given":"James","email":"jdewey@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":803787,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70207583,"text":"70207583 - 2019 - Remote sensing of tracer dye concentrations to support dispersion studies in river channels","interactions":[],"lastModifiedDate":"2019-12-30T11:23:49","indexId":"70207583","displayToPublicDate":"2019-11-20T11:17:18","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5513,"text":"Journal of Ecohydraulics","active":true,"publicationSubtype":{"id":10}},"title":"Remote sensing of tracer dye concentrations to support dispersion studies in river channels","docAbstract":"In river channels the flow field influences the dispersion of biota, contaminants, and other suspended or dissolved materials. Insight on patterns and rates of dispersion can be gained by injecting a pulse of visible dye and observing spatial and temporal variations in dye concentration as the pulse moves downstream. We evaluated the potential of passive optical remote sensing to enhance such tracer experiments by providing spatially distributed concentration information. During tests performed in both an experimental flume facility and a large natural channel, we made field measurements of Rhodamine WT dye concentration and above-water spectral reflectance. At Korea's River Experiment Center, a small unmanned aircraft system (sUAS) was used to acquire hyperspectral images of a sinuous outdoor flume. On the Kootenai River in northern Idaho, USA, field spectra were collected from a boat and hyperspectral image data and high resolution aerial photographs were obtained from manned aircraft. We modified an Optimal Band Ratio Analysis (OBRA) algorithm to identify wavelength combinations that yielded strong correlations between a spectrally based quantity X and dye concentration C. For both the flume and field tests, we obtained very strong (R^2 from 0.94 to 0.99) relationships between X and C across a broad range of visible wavelengths. On the Kootenai, we found that X vs. C relations derived from field spectra could be applied to airborne hyperspectral images and that dye concentrations could be estimated nearly as reliably from relatively simple three-band images as from hyperspectral data. These results imply that remote sensing could become a powerful tool for mapping dye patterns. Such a capability would advance our understanding of dispersion processes by enabling more rigorous testing of numerical flow models.","language":"English","publisher":"Taylor & Francis","doi":"10.1080/24705357.2019.1662339","usgsCitation":"Legleiter, C.J., McDonald, R.R., Nelson, J.M., Kinzel, P.J., Perroy, R.L., Baek, D., and Seo, I.W., 2019, Remote sensing of tracer dye concentrations to support dispersion studies in river channels: Journal of Ecohydraulics, v. 4, no. 2, p. 131-146, https://doi.org/10.1080/24705357.2019.1662339.","productDescription":"15 p.","startPage":"131","endPage":"146","ipdsId":"IP-106338","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":437280,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9CV4XEO","text":"USGS data release","linkHelpText":"Remotely sensed data and field measurements from a tracer dye experiment on the Kootenai River, ID, September 25-27, 2017"},{"id":437279,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9V3Y334","text":"USGS data release","linkHelpText":"Hyperspectral image data and Rhodamine WT dye concentrations from a tracer study at the River Experiment Center, Korea, in May 2017"},{"id":370852,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"South Korea","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[128.34972,38.61224],[129.21292,37.43239],[129.46045,36.78419],[129.4683,35.63214],[129.09138,35.08248],[128.18585,34.89038],[127.38652,34.47567],[126.48575,34.39005],[126.37392,34.93456],[126.55923,35.68454],[126.1174,36.72548],[126.86014,36.89392],[126.17476,37.74969],[126.23734,37.84038],[126.68372,37.80477],[127.07331,38.25611],[127.78004,38.30454],[128.20575,38.3704],[128.34972,38.61224]]]},\"properties\":{\"name\":\"South Korea\"}}]}","volume":"4","issue":"2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-11-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Legleiter, Carl J. 0000-0003-0940-8013 cjl@usgs.gov","orcid":"https://orcid.org/0000-0003-0940-8013","contributorId":169002,"corporation":false,"usgs":true,"family":"Legleiter","given":"Carl","email":"cjl@usgs.gov","middleInitial":"J.","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":778610,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McDonald, Richard R. 0000-0002-0703-0638 rmcd@usgs.gov","orcid":"https://orcid.org/0000-0002-0703-0638","contributorId":2428,"corporation":false,"usgs":true,"family":"McDonald","given":"Richard","email":"rmcd@usgs.gov","middleInitial":"R.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":778611,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nelson, Jonathan M. 0000-0002-7632-8526 jmn@usgs.gov","orcid":"https://orcid.org/0000-0002-7632-8526","contributorId":2812,"corporation":false,"usgs":true,"family":"Nelson","given":"Jonathan","email":"jmn@usgs.gov","middleInitial":"M.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":778612,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kinzel, Paul J. 0000-0002-6076-9730 pjkinzel@usgs.gov","orcid":"https://orcid.org/0000-0002-6076-9730","contributorId":743,"corporation":false,"usgs":true,"family":"Kinzel","given":"Paul","email":"pjkinzel@usgs.gov","middleInitial":"J.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":778613,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Perroy, Ryan L. 0000-0002-4210-3281","orcid":"https://orcid.org/0000-0002-4210-3281","contributorId":205505,"corporation":false,"usgs":false,"family":"Perroy","given":"Ryan","email":"","middleInitial":"L.","affiliations":[{"id":37113,"text":"University of Hawaii - Hilo","active":true,"usgs":false}],"preferred":false,"id":778614,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Baek, Donghae","contributorId":214366,"corporation":false,"usgs":false,"family":"Baek","given":"Donghae","email":"","affiliations":[{"id":37780,"text":"Seoul National University","active":true,"usgs":false}],"preferred":false,"id":778615,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Seo, Il Won","contributorId":214367,"corporation":false,"usgs":false,"family":"Seo","given":"Il","email":"","middleInitial":"Won","affiliations":[{"id":37780,"text":"Seoul National University","active":true,"usgs":false}],"preferred":false,"id":778616,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70215266,"text":"70215266 - 2019 - Phenotypic plasticity or a reproductive dead end? Primnoa pacifica (Cnidaria: Alcyonacea) in the southeastern Alaska region","interactions":[],"lastModifiedDate":"2020-10-15T13:25:55.053368","indexId":"70215266","displayToPublicDate":"2019-11-20T09:08:22","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3912,"text":"Frontiers in Marine Science","onlineIssn":"2296-7745","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Phenotypic plasticity or a reproductive dead end? Primnoa pacifica (Cnidaria: Alcyonacea) in the southeastern Alaska region","title":"Phenotypic plasticity or a reproductive dead end? Primnoa pacifica (Cnidaria: Alcyonacea) in the southeastern Alaska region","docAbstract":"

Red tree corals (Primnoa pacifica) are abundant in the eastern Gulf of Alaska, from the glacial fjords of Southeast Alaska where they emerge to as shallow as 6 m, to the continental shelf edge and seamounts where they are more commonly found at depths greater than 150 – 500 m. This keystone species forms large thickets, creating habitat for many associated species, including economically valuable fishes and crabs, and so are important benthic suspension feeders in this region. Though the reproductive periodicity of this species was reported in 2014 from a shallow fjord (Tracy Arm), this study examined reproductive ecologies from 8 sites – two within Glacier Bay National Park and Preserve, three on the continental shelf edge, one within Endicott Arm (Holkham Bay) and two time points from the Tracy Arm (Holkham Bay) study. Male reproductive traits were similar at all sites but there were distinct differences in oogenesis. Though per polyp fecundity mostly showed no significant difference between sites, there was a non-significant trend of increasing number of oocytes with depth. In addition, the average oocyte size from Tracy Arm (the shallowest site) was 105 μm, whereas from Shutter Ridge (one of the deepest sites) the average size was 309 μm. Moreover, the maximum oocyte size at Endicott Arm was 221 μm and at Tracy Arm was 802 μm (both shallow sites), whereas at Dixon Entrance (a deep site) it was 2120 μm, a difference not usually observed within a single species. We propose two theories to explain the observed differences, (a) this species shows great phenotypic plasticity in reproductive ecology, adjusting to different environmental variables based on energetic need and potentially demonstrating micro-evolution; or (b) the fjord sites are at a reproductive dead end, with the stress of shallow-water conditions effectively preventing gametogenesis reaching full potential and likely limiting successful reproductive events from occurring, at least on a regular basis.

","language":"English","publisher":"Frontiers","doi":"10.3389/fmars.2019.00709","usgsCitation":"Waller, R.G., Stone, R.P., Rice, L., Johnstone, J., Rossin, A.M., Hartill, E., Feehan, K., and Morrison, C., 2019, Phenotypic plasticity or a reproductive dead end? Primnoa pacifica (Cnidaria: Alcyonacea) in the southeastern Alaska region: Frontiers in Marine Science, v. 6, 709, 14 p., https://doi.org/10.3389/fmars.2019.00709.","productDescription":"709, 14 p.","ipdsId":"IP-109052","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":459144,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fmars.2019.00709","text":"Publisher Index Page"},{"id":379359,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -142.20703125,\n 54.470037612805754\n ],\n [\n -128.671875,\n 54.470037612805754\n ],\n [\n -128.671875,\n 60.50052541051131\n ],\n [\n -142.20703125,\n 60.50052541051131\n ],\n [\n -142.20703125,\n 54.470037612805754\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"6","noUsgsAuthors":false,"publicationDate":"2019-11-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Waller, Rhian G.","contributorId":195852,"corporation":false,"usgs":false,"family":"Waller","given":"Rhian","email":"","middleInitial":"G.","affiliations":[{"id":16143,"text":"University of Hawaii at Manoa, Honolulu, Hawaii","active":true,"usgs":false}],"preferred":false,"id":801391,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stone, Robert P.","contributorId":190569,"corporation":false,"usgs":false,"family":"Stone","given":"Robert","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":801392,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rice, Lauren","contributorId":243033,"corporation":false,"usgs":false,"family":"Rice","given":"Lauren","email":"","affiliations":[{"id":48620,"text":"Darling Marine Center, University of Maine and Oregon Institute of Marine Biology, University of Oregon","active":true,"usgs":false}],"preferred":false,"id":801393,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Johnstone, Julia","contributorId":243034,"corporation":false,"usgs":false,"family":"Johnstone","given":"Julia","email":"","affiliations":[{"id":48621,"text":"Darling Marine Center, University of Maine","active":true,"usgs":false}],"preferred":false,"id":801394,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rossin, Ashley M.","contributorId":243035,"corporation":false,"usgs":false,"family":"Rossin","given":"Ashley","email":"","middleInitial":"M.","affiliations":[{"id":48622,"text":"Darling Marine Center, University of Maine and University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":801395,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hartill, Elise","contributorId":243036,"corporation":false,"usgs":false,"family":"Hartill","given":"Elise","email":"","affiliations":[{"id":48621,"text":"Darling Marine Center, University of Maine","active":true,"usgs":false}],"preferred":false,"id":801396,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Feehan, Keri","contributorId":243037,"corporation":false,"usgs":false,"family":"Feehan","given":"Keri","email":"","affiliations":[{"id":48621,"text":"Darling Marine Center, University of Maine","active":true,"usgs":false}],"preferred":false,"id":801397,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Morrison, Cheryl 0000-0001-9425-691X cmorrison@usgs.gov","orcid":"https://orcid.org/0000-0001-9425-691X","contributorId":202644,"corporation":false,"usgs":true,"family":"Morrison","given":"Cheryl","email":"cmorrison@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":801398,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70228480,"text":"70228480 - 2019 - Identification of a novel Adélie penguin circovirus at Cape Crozier (Ross Island, Antarctica)","interactions":[],"lastModifiedDate":"2022-02-11T15:09:30.923331","indexId":"70228480","displayToPublicDate":"2019-11-20T08:57:45","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3700,"text":"Viruses","active":true,"publicationSubtype":{"id":10}},"title":"Identification of a novel Adélie penguin circovirus at Cape Crozier (Ross Island, Antarctica)","docAbstract":"Understanding the causes of disease in Antarctic wildlife is crucial as many of these species are already threatened by environmental changes brought about by climate change. In recent years, Antarctic penguins have been showing signs of an unknown pathology: a feather disorder characterised by missing feathers resulting in exposed skin. During the 2018-19 austral summer breeding season at Cape Crozier colony on Ross Island, Antarctica, for the first time we observed an Adlie penguin chick missing down over most of its body. A guano sample was collected from the nest of the featherless chick and, using high throughput sequencing we identified a novel circovirus. Using abutting primers, we amplified the full genome, which we cloned, and Sanger sequenced to determine the complete genome of the circovirus. The Adlie penguin guano-associated circovirus genome shares <67% genome-wide nucleotide identity to other circoviruses, representing a new species of circovirus, therefore we named it penguin circovirus (PenCV). Using the same primer pair, we screened 25 previously collected cloacal swabs taken at Cape Crozier from known-age adult Adlie penguins during the 2014-15 season displaying no clinical signs of feather-loss disorder. Three of the 25 samples (12%) were positive for a PenCV, whose genome shared >99% pairwise identity to the one identified in 2018-19. This is the first report of a circovirus associated with a penguin species and could be a possible etiological agent of the feather-loss disorder in Antarctic penguins.","language":"English","publisher":"MDPI","doi":"10.3390/v11121088","usgsCitation":"Morandini, V., Dugger, K., Ballard, G., Elrod, M., Schmidt, A., Ruoppolo, V., Lescroël, A., Jongsomjit, D., Massaro, M., Pennycook, J., Schmidlin, K., Kraberger, S., Ainley, D., and Varsani, A., 2019, Identification of a novel Adélie penguin circovirus at Cape Crozier (Ross Island, Antarctica): Viruses, v. 11, no. 12, 1088, 10 p., https://doi.org/10.3390/v11121088.","productDescription":"1088, 10 p.","ipdsId":"IP-111478","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":459147,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/v11121088","text":"Publisher Index Page"},{"id":395843,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Antarctica, Cape Crozier, Ross Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 165.56396484375,\n -77.91566898632583\n ],\n [\n 170.00244140625,\n -77.91566898632583\n ],\n [\n 170.00244140625,\n -77.05911588252368\n ],\n [\n 165.56396484375,\n -77.05911588252368\n ],\n [\n 165.56396484375,\n -77.91566898632583\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","issue":"12","noUsgsAuthors":false,"publicationDate":"2019-11-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Morandini, 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Amélie","contributorId":275898,"corporation":false,"usgs":false,"family":"Lescroël","given":"Amélie","affiliations":[{"id":48619,"text":"pbcs","active":true,"usgs":false}],"preferred":false,"id":834398,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Jongsomjit, Dennis","contributorId":275900,"corporation":false,"usgs":false,"family":"Jongsomjit","given":"Dennis","affiliations":[{"id":48619,"text":"pbcs","active":true,"usgs":false}],"preferred":false,"id":834399,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Massaro, Melanie","contributorId":275902,"corporation":false,"usgs":false,"family":"Massaro","given":"Melanie","affiliations":[{"id":13606,"text":"CSU","active":true,"usgs":false}],"preferred":false,"id":834400,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Pennycook, Jean","contributorId":275904,"corporation":false,"usgs":false,"family":"Pennycook","given":"Jean","email":"","affiliations":[{"id":56908,"text":"ht assoc","active":true,"usgs":false}],"preferred":false,"id":834401,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Schmidlin, Kara","contributorId":275905,"corporation":false,"usgs":false,"family":"Schmidlin","given":"Kara","email":"","affiliations":[{"id":12431,"text":"ASU","active":true,"usgs":false}],"preferred":false,"id":834402,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Kraberger, Simona","contributorId":275906,"corporation":false,"usgs":false,"family":"Kraberger","given":"Simona","affiliations":[{"id":12431,"text":"ASU","active":true,"usgs":false}],"preferred":false,"id":834403,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Ainley, David G.","contributorId":275908,"corporation":false,"usgs":false,"family":"Ainley","given":"David G.","affiliations":[{"id":56908,"text":"ht assoc","active":true,"usgs":false}],"preferred":false,"id":834404,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Varsani, Arvind","contributorId":275911,"corporation":false,"usgs":false,"family":"Varsani","given":"Arvind","affiliations":[{"id":12431,"text":"ASU","active":true,"usgs":false}],"preferred":false,"id":834405,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}} ,{"id":70206984,"text":"70206984 - 2019 - Shallow-water foraminifera and other microscopic biota of Clipperton Island, tropical eastern Pacific","interactions":[],"lastModifiedDate":"2019-12-03T08:35:52","indexId":"70206984","displayToPublicDate":"2019-11-20T08:33:18","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":930,"text":"Atoll Research Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"Shallow-water foraminifera and other microscopic biota of Clipperton Island, tropical eastern Pacific","docAbstract":"The recent foraminiferal fauna and associated microbiota of Clipperton Island (10.2833°N, 109.2167°W) were investigated at 20 sites collected in the intertidal zone around the perimeter of the island and from the edge of the inner brackish-water lagoon. Due to the island’s geographic location in a low productivity zone, a lack of variable habitats on and surrounding the island, and heavy surf that pounds the exposed land, a depauperate fauna was recovered although mixed biogeographic affinities are represented. The shallow-water foraminiferal assemblage has no endemics but primarily tropical Indo-Pacific and eastern Pacific (Panamic) affinities, as well as one species of Caribbean affinity. The most abundant species are Sorites spp. and Quinqueloculina spp. Noticeably absent are any species of Amphistegina, despite the fact that they are considered ubiquitous in the tropical Pacific. The molluscan fauna has Clipperton Island endemics, a tropical Pacific/Inter-Island endemic, and tropical eastern Pacific oceanic islands/Panamic Molluscan affinities. The ostracods included endemics found restricted to Clipperton Island lagoon, as well as Indo-Pacific and Panamic Province species. The foraminifera, mollusks, and ostracods are thought to disperse to Clipperton Island by way of the North Equatorial Countercurrent and North Equatorial Current, suggesting that the island is indeed a stepping-stone for migration both east and west across the Eastern Pacific Barrier.","language":"English","publisher":"Smithsonian Scholarly Press","doi":"10.5479/si.10329962.v1","usgsCitation":"McGann, M., Schmieder, R.W., and Loncke, L., 2019, Shallow-water foraminifera and other microscopic biota of Clipperton Island, tropical eastern Pacific: Atoll Research Bulletin, v. 626, vi, 28 p., https://doi.org/10.5479/si.10329962.v1.","productDescription":"vi, 28 p.","ipdsId":"IP-102022","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":459149,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.5479/si.10329962.v1","text":"External Repository"},{"id":369854,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Clipperton Island","volume":"626","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"McGann, Mary 0000-0002-3057-2945 mmcgann@usgs.gov","orcid":"https://orcid.org/0000-0002-3057-2945","contributorId":169540,"corporation":false,"usgs":true,"family":"McGann","given":"Mary","email":"mmcgann@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":776461,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schmieder, Robert W","contributorId":220981,"corporation":false,"usgs":false,"family":"Schmieder","given":"Robert","email":"","middleInitial":"W","affiliations":[{"id":40303,"text":"Cordell Expeditions","active":true,"usgs":false}],"preferred":false,"id":776462,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Loncke, Louis-Philippe","contributorId":220982,"corporation":false,"usgs":false,"family":"Loncke","given":"Louis-Philippe","email":"","affiliations":[{"id":40304,"text":"BelgianAdventurer","active":true,"usgs":false}],"preferred":false,"id":776463,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70208193,"text":"70208193 - 2019 - Optical wave gauging using deep neural networks","interactions":[],"lastModifiedDate":"2020-01-29T19:33:09","indexId":"70208193","displayToPublicDate":"2019-11-19T19:27:15","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1262,"text":"Coastal Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Optical wave gauging using deep neural networks","docAbstract":"

We develop a remote wave gauging technique to estimate wave height and period from imagery of waves in the surf zone. In this proof-of-concept study, we apply the same framework to three datasets: the first, a set of close-range monochrome infrared (IR) images of individual nearshore waves at Duck, NC, USA; the second, a set of visible (i.e. RGB) band orthomosaics of a larger nearshore area near Santa Cruz, CA, USA; and the third, a set of oblique (unrectified) images from the same site. The network is trained using coincident images and in situ wave measurements. The optical wave gauge (OWG) consists of a deep convolutional neural network (CNN) to extract features from imagery — called a ‘base model’, with additional layers to distill the feature information into lower dimensional spaces, and a final layer of dense neurons to predict continuously varying quantities. Four base models are compared. The OWG is trained for both individual wave height and period, and statistical quantities like significant wave height and peak wave period. The best performing OWG on the IR dataset achieved RMS errors of 0.14 m and 0.41 s for height and period, respectively, capturing up to 98% of the variance in these quantities. The best performing OWG on the visible band rectified dataset achieved RMS errors of 0.08 m and 0.79 s, respectively, for height and period. The same values for the oblique RGB imagery were 0.11 m and 0.81 s for height and period, respectively. Overall, wave height and period accuracy is sensitive to choice of base model; OWGs built upon MobilenetV2 tend to perform worst and those built on Inception-ResnetV2 have the smallest RMS error. The presence or otherwise of residual layers in the model makes little systematic difference to the final OWG accuracy. Smaller batch sizes used in model training tend to result in more accurate OWGs. An out-of-calibration validation, using images associated with wave heights or periods outside the range of values represented in the training data, showed that the ability for OWGs to predict the bottom 5% of low wave heights and the top 5% of high wave heights was reasonably good, but the same was not generally true of wave period. The same framework, not optimized for either dataset, predicts both quantities with high accuracy when trained on imagery, despite the differences in electromagnetic band, perspective, and scale. The OWG estimates wave properties from an image in less than 100 ms on a modestly sized CPU, allowing for the possibility of continuous real-time wave estimates.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.coastaleng.2019.103593","usgsCitation":"Buscombe, D.D., Carini, R.J., Harrison, S., Chickadel, C.C., and Warrick, J.A., 2019, Optical wave gauging using deep neural networks: Coastal Engineering, v. 155, 103593, 18 p., https://doi.org/10.1016/j.coastaleng.2019.103593.","productDescription":"103593, 18 p.","ipdsId":"IP-106980","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":459152,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.coastaleng.2019.103593","text":"Publisher Index Page"},{"id":371746,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, North Carolina","county":"Santa Cruz, Duck","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.80978393554688,\n 36.27527883184338\n ],\n [\n -75.7562255859375,\n 36.07851703597173\n ],\n [\n -75.69374084472656,\n 36.08295654486136\n ],\n [\n -75.77545166015625,\n 36.274725267505474\n ],\n [\n -75.80978393554688,\n 36.27527883184338\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.19818115234375,\n 36.97183825093165\n ],\n [\n -122.06634521484374,\n 36.92793899776678\n ],\n [\n -121.96197509765625,\n 36.934525498514894\n ],\n [\n -121.93450927734375,\n 36.95647639022989\n ],\n [\n -121.90704345703124,\n 36.98500309285596\n ],\n [\n -121.95098876953125,\n 37.06613594074314\n ],\n [\n -122.05261230468751,\n 37.055177106660814\n ],\n [\n -122.21466064453125,\n 37.04421668967971\n ],\n [\n -122.19818115234375,\n 36.97183825093165\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"155","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Buscombe, Daniel D. 0000-0001-6217-5584","orcid":"https://orcid.org/0000-0001-6217-5584","contributorId":198817,"corporation":false,"usgs":false,"family":"Buscombe","given":"Daniel","middleInitial":"D.","affiliations":[],"preferred":false,"id":780897,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carini, Roxanne J 0000-0001-9682-890X","orcid":"https://orcid.org/0000-0001-9682-890X","contributorId":221996,"corporation":false,"usgs":false,"family":"Carini","given":"Roxanne","email":"","middleInitial":"J","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":780898,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Harrison, Shawn 0000-0002-8711-4427","orcid":"https://orcid.org/0000-0002-8711-4427","contributorId":221997,"corporation":false,"usgs":true,"family":"Harrison","given":"Shawn","email":"","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":780899,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chickadel, C Chris 0000-0002-0770-7725","orcid":"https://orcid.org/0000-0002-0770-7725","contributorId":221998,"corporation":false,"usgs":false,"family":"Chickadel","given":"C","email":"","middleInitial":"Chris","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":780900,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Warrick, Jonathan A. 0000-0002-0205-3814 jwarrick@usgs.gov","orcid":"https://orcid.org/0000-0002-0205-3814","contributorId":167736,"corporation":false,"usgs":true,"family":"Warrick","given":"Jonathan","email":"jwarrick@usgs.gov","middleInitial":"A.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":780896,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70206744,"text":"70206744 - 2019 - A parametric numerical analysis of factors controlling ground ruptures caused by groundwater pumping","interactions":[],"lastModifiedDate":"2020-01-03T10:41:12","indexId":"70206744","displayToPublicDate":"2019-11-19T15:52:39","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"A parametric numerical analysis of factors controlling ground ruptures caused by groundwater pumping","docAbstract":"A modeling analysis is used to investigate the relative susceptibility of various hydrogeologic configurations to aseismic rupture generation due to deformation of aquifer systems accompanying groundwater pumping. An advanced numerical model (GEPS3D) is used to simulate rupture generation and propagation for three typical processes: (i) reactivation of a preexisting fault, (ii) differential compaction due to variations in thickness of aquifer/aquitard layers constituting the aquifer system, and (iii) tensile fracturing above a bedrock ridge that forms the base of the aquifer system. A sensitivity analysis is developed to address the relative importance of various factors, including aquifer depletion, aquifer thickness, the possible uneven distribution and depth below land surface of the aquifer/aquitard layers susceptible to aquifer-system compaction, and the height of bedrock ridges beneath the aquifer system which contributes to thinning of the aquifer system. The rupture evolution is classified in two occurrences. In one, the rupture develops at the top of the aquifer or at land surface and does not propagate. In the other, the developed rupture propagates from the aquifer top toward the land surface and/or from the land surface downward. The aquifer depth is the most important factor controlling rupture evolution. Specifically, the probability of a significant rupture propagation is higher when the aquifer top is near land surface. The numerical results are processed by a statistical regression analysis to provide a general methodology for a preliminary evaluation of possible ruptures development in exploited aquifer systems susceptible to aquifer-system compaction and accompanying land subsidence. A comparison with a few representative case studies in Arizona, USA, China, and Mexico supports the study outcomes.","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2019WR025034","usgsCitation":"Frigo, M., Ferronato, M., Yu, J., Ye, S., Galloway, D., Carreon-Freyre, D., and Teatini, P., 2019, A parametric numerical analysis of factors controlling ground ruptures caused by groundwater pumping: Water Resources Research, v. 55, no. 11, p. 9500-9518, https://doi.org/10.1029/2019WR025034.","productDescription":"19 p.","startPage":"9500","endPage":"9518","ipdsId":"IP-113487","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":369361,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"China, Mexico, United States","state":"Arizona","volume":"55","issue":"11","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-11-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Frigo, Matteo","contributorId":220754,"corporation":false,"usgs":false,"family":"Frigo","given":"Matteo","email":"","affiliations":[{"id":40265,"text":"Department of Civil, Architectural and Environmental Engineering, University of Padova, Padova, Italy","active":true,"usgs":false}],"preferred":false,"id":775626,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ferronato, Massimiliano","contributorId":220755,"corporation":false,"usgs":false,"family":"Ferronato","given":"Massimiliano","email":"","affiliations":[{"id":40265,"text":"Department of Civil, Architectural and Environmental Engineering, University of Padova, Padova, Italy","active":true,"usgs":false}],"preferred":false,"id":775627,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yu, Jun","contributorId":220756,"corporation":false,"usgs":false,"family":"Yu","given":"Jun","email":"","affiliations":[{"id":40266,"text":"Key Laboratory of Earth Fissures Geological Disaster, Ministry of Land and Resources, Geological Survey of Jiangsu Province, Nanjing, China","active":true,"usgs":false}],"preferred":false,"id":775628,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ye, Shujun","contributorId":203532,"corporation":false,"usgs":false,"family":"Ye","given":"Shujun","email":"","affiliations":[{"id":36646,"text":"Dept. of Hydrosciences, School of Earth Sciences and Engineering, Nanjing University, Nanjing P. R. China","active":true,"usgs":false}],"preferred":false,"id":775629,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Galloway, Devin 0000-0003-0904-5355","orcid":"https://orcid.org/0000-0003-0904-5355","contributorId":215888,"corporation":false,"usgs":true,"family":"Galloway","given":"Devin","email":"","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":775625,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Carreon-Freyre, Dora","contributorId":203530,"corporation":false,"usgs":false,"family":"Carreon-Freyre","given":"Dora","email":"","affiliations":[{"id":36644,"text":"Centro de Geociencias, Universidad Nacional Autónoma de México, Campus Juriquilla, Queretaro, Mexico","active":true,"usgs":false}],"preferred":false,"id":775630,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Teatini, Pietro","contributorId":203529,"corporation":false,"usgs":false,"family":"Teatini","given":"Pietro","email":"","affiliations":[{"id":36643,"text":"Department of Civil, Environmental and Architectural Engineering, University of Padova, Padova, Italy","active":true,"usgs":false}],"preferred":false,"id":775631,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70206737,"text":"70206737 - 2019 - Geospatial scaling of runoff and erosion modeling in the Chihuahuan Desert","interactions":[],"lastModifiedDate":"2019-11-19T15:39:57","indexId":"70206737","displayToPublicDate":"2019-11-19T15:39:47","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":833,"text":"Applied Engineering in Agriculture","active":true,"publicationSubtype":{"id":10}},"title":"Geospatial scaling of runoff and erosion modeling in the Chihuahuan Desert","docAbstract":"

Large-scale assessments of rangeland runoff and erosion require methods to extend plot-scale parameterizations to large areas. In this study, Rangeland Hydrology and Erosion Model (RHEM) parameters were developed from plot-scale foliar and ground-cover transect data for an arid, grass-shrub rangeland in southern New Mexico, and a method was assessed to upscale transect-plot parameters to a large landscape. The transect-plot data compared favorably to corresponding cell data generated from publicly available geospatial data for total foliar cover but less favorably for litter cover and poorly for rock cover. The RHEM effective hydraulic conductivity (Ke) parameter was comparable between transect-plot and geospatial-cell methods, but the splash and sheet erosion factor (Kss) had poor agreement between the two methods. Simulated runoff and erosion reflected differences in transect-plot and geospatial-cell-based RHEM parameterizations, with low error and very good agreement for runoff but high error and poor agreement for soil loss. These results demonstrate that Ke parameters developed using geospatial data calibrated to plot data can be extrapolated to large spatial areas and provide reasonable simulation of runoff using RHEM. However, these same geospatial methods do not provide reasonable estimation of Kss or simulation of soil loss. Poor representation of litter and rock cover variables, which are highly spatially heterogeneous at the plot scale, was inadequate to accurately represent Kss or soil loss using RHEM. High resolution ground cover data, such as from unmanned aerial systems, may improve parameterization of Kss, and, ultimately, arid rangeland soil erosion simulation.

","language":"English","publisher":"American Society of Agricultural and Biological Engineers","doi":"10.13031/aea.13275","usgsCitation":"Ball, G., and Douglas-Mankin, K., 2019, Geospatial scaling of runoff and erosion modeling in the Chihuahuan Desert: Applied Engineering in Agriculture, v. 5, no. 35, p. 733-743, https://doi.org/10.13031/aea.13275.","productDescription":"11 p.","startPage":"733","endPage":"743","ipdsId":"IP-104120","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":369346,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","otherGeospatial":"Chihuahuan Desert","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.732421875,\n 34.88593094075317\n ],\n [\n -105.13916015625,\n 33.60546961227188\n ],\n [\n -105.2490234375,\n 32.861132322810946\n ],\n [\n -105.75439453125,\n 32.491230287947594\n ],\n [\n -106.9189453125,\n 34.34343606848294\n ],\n [\n -107.1826171875,\n 33.970697997361626\n ],\n [\n -107.698974609375,\n 32.80574473290688\n ],\n [\n -109.09423828125,\n 33.19273094190692\n ],\n [\n -109.10522460937499,\n 31.325486676506983\n ],\n [\n -108.226318359375,\n 31.325486676506983\n ],\n [\n -108.204345703125,\n 31.774877618507386\n ],\n [\n -106.578369140625,\n 31.765537409484374\n ],\n [\n -106.644287109375,\n 31.970803930433096\n ],\n [\n -103.11767578124999,\n 32.01739159980399\n ],\n [\n -103.084716796875,\n 34.994003757575776\n ],\n [\n -105.732421875,\n 34.88593094075317\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"5","issue":"35","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ball, Grady 0000-0003-3030-055X","orcid":"https://orcid.org/0000-0003-3030-055X","contributorId":220746,"corporation":false,"usgs":true,"family":"Ball","given":"Grady","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":775597,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Douglas-Mankin, Kyle R. 0000-0002-3155-3666","orcid":"https://orcid.org/0000-0002-3155-3666","contributorId":200849,"corporation":false,"usgs":false,"family":"Douglas-Mankin","given":"Kyle R.","affiliations":[],"preferred":false,"id":775598,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70206053,"text":"sim3444 - 2019 - Potentiometric surface of groundwater-level altitudes near the planned Highway 270 bypass, east of Hot Springs, Arkansas, July–August 2017","interactions":[],"lastModifiedDate":"2019-11-19T17:19:14","indexId":"sim3444","displayToPublicDate":"2019-11-19T13:49:10","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3444","displayTitle":"Potentiometric Surface of Groundwater-Level Altitudes Near the Planned Highway 270 Bypass, East of Hot Springs, Arkansas, July–August 2017","title":"Potentiometric surface of groundwater-level altitudes near the planned Highway 270 bypass, east of Hot Springs, Arkansas, July–August 2017","docAbstract":"

The Ouachita Mountains aquifer system potentiometric-surface map is one component of the Hot Springs Bypass Groundwater Monitoring Project. The potentiometric-surface map provides a baseline assessment of shallow groundwater levels and flow directions before the construction of the Arkansas Department of Transportation planned extension of the Highway 270 bypass, east of Hot Springs, Arkansas. The map provides data regarding status of groundwater levels and potential effects on the recharge area in the Hot Springs National Park and to groundwater that supplies water to domestic users near the Highway 270 bypass.

Groundwater levels from 66 wells were measured in July–August 2017. Fifty nine of the 66 groundwater-level altitudes measured, along with select surface-water features and springs, were used to construct the Ouachita Mountains aquifer system potentiometric-surface map. The potentiometric surface, a two-dimensional representation, shows groundwater-level altitudes ranging from a maximum of 766 ft above the North American Vertical Datum of 1988 (NAVD 88) to a minimum of 443 ft NAVD 88. The spring altitudes on the potentiometric-surface map range from 534 ft to 927 ft above NAVD 88. The study area, located in the Ouachita Mountains physiographic section of the Ouachita physiographic province, comprises narrow valleys and high ridges of Stanley Shale, Hot Springs Sandstone, Arkansas Novaculite, Missouri Mountain-Polk Creek Shale, and Bigfork Chert. The highest groundwater-level altitudes observed were in the Hot Springs Sandstone, Arkansas Novaculite, and Missouri Mountain-Polk Creek Shale. The springs discharge in outcrop areas of the Stanley Shale, Bigfork Chert, and Arkansas novaculite. The planned Highway 270 bypass will cut across ridges and valleys comprising these formations and, very importantly, across areas with elevations above 660 ft above NAVD 88 that define the hot springs recharge zone.

This potentiometric-surface map defines the status of the shallow groundwater potentiometric surface near the Highway 270 bypass prior to initiation of construction activities. A post-construction potentiometric map is planned. It must be noted that shallow groundwater levels are also subject to climatic effects including changes in amount and timing of precipitation and changes in temperature.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3444","collaboration":"Prepared in cooperation with the Arkansas Department of Transportation and the National Park Service","usgsCitation":"Nottmeier, A.M., and Hays, P.D., 2019, Potentiometric surface of groundwater-level altitudes near the planned Highway 270 bypass, east of Hot Springs, Arkansas, July–August 2017: U.S. Geological Survey Scientific Investigations Map 3444, 13 p., 1 sheet, https://doi.org/10.3133/sim3444.","productDescription":"Pamphlet: v, 13 p.; Sheet: 22 x 28 inches; Data Release","numberOfPages":"24","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-092242","costCenters":[{"id":129,"text":"Arkansas Water Science Center","active":true,"usgs":true},{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":369331,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7TD9WK0","text":"USGS data release ","description":"USGS Data Release","linkHelpText":"Datasets of the Potentiometric Surface of Groundwater-Level Altitudes Near the Planned Highway 270 Bypass, East of Hot Springs, Arkansas, July–August 2017"},{"id":369328,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3444/coverthb.jpg"},{"id":369329,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3444/sim3444.pdf","text":"Sheet ","size":"2.16 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3444 ","linkHelpText":"– Potentiometric-surface map for the Ouachita Mountains aquifer, July–August 2017"},{"id":369330,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3444/sim3444_pamphlet.pdf","text":"Pamphlet","size":"3.27 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3444 Pamphlet"}],"country":"United States","state":"Arkansas","county":"Garland County","city":"Hot Springs","otherGeospatial":"Highway 270 Bypass","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.01935195922852,\n 34.50542493789137\n ],\n [\n -92.94931411743164,\n 34.50542493789137\n ],\n [\n -92.94931411743164,\n 34.5710371883746\n ],\n [\n -93.01935195922852,\n 34.5710371883746\n ],\n [\n -93.01935195922852,\n 34.50542493789137\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Lower Mississippi-Gulf Water Science Center
U.S. Geological Survey
640 Grassmere Park, Suite 100
Nashville, TN 37211

","tableOfContents":"","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2019-11-19","noUsgsAuthors":false,"publicationDate":"2019-11-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Nottmeier, Anna M. 0000-0002-0205-0955 anottmeier@usgs.gov","orcid":"https://orcid.org/0000-0002-0205-0955","contributorId":5283,"corporation":false,"usgs":true,"family":"Nottmeier","given":"Anna","email":"anottmeier@usgs.gov","middleInitial":"M.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":773429,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hays, Phillip D. 0000-0001-5491-9272 pdhays@usgs.gov","orcid":"https://orcid.org/0000-0001-5491-9272","contributorId":4145,"corporation":false,"usgs":true,"family":"Hays","given":"Phillip","email":"pdhays@usgs.gov","middleInitial":"D.","affiliations":[{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":129,"text":"Arkansas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":773430,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70208703,"text":"70208703 - 2019 - Heterogeneity in hyporheic flow, pore water chemistry, and microbial community composition in an alpine streambed","interactions":[],"lastModifiedDate":"2020-02-25T12:27:59","indexId":"70208703","displayToPublicDate":"2019-11-19T12:25:49","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2320,"text":"Journal of Geophysical Research: Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"Heterogeneity in hyporheic flow, pore water chemistry, and microbial community composition in an alpine streambed","docAbstract":"The hyporheic zone, where surface water and groundwater mix, is an important microbial habitat where biogeochemical reactions influence water quality. We show that spatial variability in hyporheic flow in the East River near Crested Butte, Colorado, drives heterogeneity in streambed geochemical conditions and microbial community assemblages, but the diversity of assemblages remains nearly constant throughout the reach. In July 2018, we collected approximately 100 pore water samples at 20 cm depth and analyzed them for anions, cations, dissolved organic carbon, dissolved organic matter (DOM) quality, and basic water quality parameters. Vertical hydraulic head gradients were also measured to assess the potential for upward or downward flow, and heat tracing was used to quantify vertical flux rates at a subset of locations. We found that regions of the streambed that are more groundwater-dominated contain less dissolved oxygen, higher concentrations of reduced metals, and more microbially-processed, recalcitrant DOM, while more surface water-dominated locations contain higher dissolved oxygen concentrations and terrestrially-derived, labile DOM. 16S rRNA gene sequencing of extracted DNA revealed that microbial community composition varies with geochemical gradients related to hyporheic flow. These findings provide a better understanding of hyporheic controls on streambed biogeochemistry during the baseflow season, which is expected to lengthen with climate change in alpine watersheds due to earlier snowmelt onset and reduced snowpack.","language":"English","publisher":"Wiley","doi":"10.1029/2019JG005226","usgsCitation":"Nelson, A., Sawyer, A., Gabor, R., Saup, C., Bryant, S., Harris, K., Briggs, M.A., Williams, K., and Wilkins, M.J., 2019, Heterogeneity in hyporheic flow, pore water chemistry, and microbial community composition in an alpine streambed: Journal of Geophysical Research: Biogeosciences, v. 124, no. 11, p. 3465-3478, https://doi.org/10.1029/2019JG005226.","productDescription":"14 p.","startPage":"3465","endPage":"3478","ipdsId":"IP-113191","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":459156,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index 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University","active":true,"usgs":false}],"preferred":false,"id":783096,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Briggs, Martin A. 0000-0003-3206-4132 mbriggs@usgs.gov","orcid":"https://orcid.org/0000-0003-3206-4132","contributorId":4114,"corporation":false,"usgs":true,"family":"Briggs","given":"Martin","email":"mbriggs@usgs.gov","middleInitial":"A.","affiliations":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true}],"preferred":true,"id":783090,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Williams, Kenneth ","contributorId":222682,"corporation":false,"usgs":false,"family":"Williams","given":"Kenneth ","affiliations":[{"id":38900,"text":"Lawrence Berkeley National 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J.","contributorId":176779,"corporation":false,"usgs":false,"family":"Wilkins","given":"M.","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":783098,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70215182,"text":"70215182 - 2019 - Using morphological measurements to predict subspecies of Midcontinent sandhill cranes","interactions":[],"lastModifiedDate":"2020-10-09T13:08:18.959986","indexId":"70215182","displayToPublicDate":"2019-11-19T08:06:02","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3779,"text":"Wildlife Society Bulletin","onlineIssn":"1938-5463","printIssn":"0091-7648","active":true,"publicationSubtype":{"id":10}},"title":"Using morphological measurements to predict subspecies of Midcontinent sandhill cranes","docAbstract":"

The Midcontinent population of sandhill cranes (Antigone canadensis) has historically been classified into 3 putative subspecies, but genetic analyses have identified only 2 genetically distinct subspecies. Previous studies have successfully used morphometrics in combination with an individual's sex to differentiate subspecies of sandhill cranes that had been inferred based on breeding area, but no study has used a sample of genetically determined subspecies to discriminate and develop predictive models. Using measurements from 843 adult sandhill cranes captured throughout their range and annual cycle (in 4 States and 1 Canadian province during 1998–2007), we used linear discriminant analysis to classify genetically identified A. c. canadensis (lesser) and A. c. tabida (greater) sandhill crane subspecies, and developed a field‐ready tool to predict subspecies using common morphometric measurements without determination of an individual's sex. Our top‐ranked model was 89.5% accurate overall, and used flattened wing chord, total culmen, and tarsometatarsus lengths to correctly identify 93.1% of A. c. canadensis and 82.8% of A. c. tabida subspecies. Additionally, we identified measurement thresholds based on posterior probabilities of correct classification to aid in subspecies determination when the linear discriminant procedure provided equivocal results. We also investigated whether sex determination could increase accuracy of our top‐ranked model, and found that accuracy increased <1% when including this information. We suggest collection of the morphometric measurements used in our top‐ranked model to determine subspecies of adult Midcontinent sandhill cranes. Our method does not require determining sex of the individual to correctly classify subspecies, allows for accurate and rapid subspecies determination, and can largely avoid additional costs and time associated with genetic analyses to determine subspecies. © 2019 The Wildlife Society.

","language":"English","publisher":"Wildlife Society","doi":"10.1002/wsb.1020","usgsCitation":"VonBank, J., Brandt, D.A., Pearse, A.T., Wester, D.B., and Ballard, B.M., 2019, Using morphological measurements to predict subspecies of Midcontinent sandhill cranes: Wildlife Society Bulletin, v. 4, no. 43, p. 737-744, https://doi.org/10.1002/wsb.1020.","productDescription":"8 p.","startPage":"737","endPage":"744","ipdsId":"IP-102356","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":499861,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doaj.org/article/d19b606702144f31add6ec00ffc7b42d","text":"External Repository"},{"id":379271,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"4","issue":"43","noUsgsAuthors":false,"publicationDate":"2019-11-19","publicationStatus":"PW","contributors":{"authors":[{"text":"VonBank, Jay A","contributorId":242902,"corporation":false,"usgs":false,"family":"VonBank","given":"Jay A","affiliations":[{"id":13724,"text":"Texas A&M University-Kingsville","active":true,"usgs":false}],"preferred":false,"id":801074,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brandt, David A. 0000-0001-9786-307X dbrandt@usgs.gov","orcid":"https://orcid.org/0000-0001-9786-307X","contributorId":149929,"corporation":false,"usgs":true,"family":"Brandt","given":"David","email":"dbrandt@usgs.gov","middleInitial":"A.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":801075,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pearse, Aaron T. 0000-0002-6137-1556 apearse@usgs.gov","orcid":"https://orcid.org/0000-0002-6137-1556","contributorId":1772,"corporation":false,"usgs":true,"family":"Pearse","given":"Aaron","email":"apearse@usgs.gov","middleInitial":"T.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":801076,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wester, David B.","contributorId":200945,"corporation":false,"usgs":false,"family":"Wester","given":"David","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":801077,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ballard, Bart M","contributorId":242903,"corporation":false,"usgs":false,"family":"Ballard","given":"Bart","email":"","middleInitial":"M","affiliations":[{"id":13724,"text":"Texas A&M University-Kingsville","active":true,"usgs":false}],"preferred":false,"id":801078,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70206691,"text":"70206691 - 2019 - Santa Barbara area coastal ecosystem vulnerability assessment","interactions":[],"lastModifiedDate":"2019-11-19T08:06:37","indexId":"70206691","displayToPublicDate":"2019-11-19T08:05:16","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Santa Barbara area coastal ecosystem vulnerability assessment","docAbstract":"The Santa Barbara Area Coastal Ecosystem Vulnerability Assessment (SBA CEVA)\nis a multidisciplinary research project that investigates future changes to southern\nSanta Barbara County climate, beaches, watersheds, wetland habitats and beach\necosystems. The target audience is local land use planners and decision makers.\nThe main objective is to provide information that assists the Cities of Santa Barbara,\nCarpinteria, and Goleta, the County of Santa Barbara, and UC Santa Barbara in\nclimate adaptation planning with a clear focus on coastal ecosystems.\nLed by California Sea Grant, SBA CEVA was developed from the work of three\nof the state’s leading ecological and climatological research programs: UCSB’s\nSanta Barbara Coastal Long-Term Ecological Research (LTER) Program, the UCSD\nScripps Institution of Oceanography (SIO) and their activities within the California\nand Nevada Applications Program Regional Integrated Science and Assessment\n(CNAP RISA), the California 4th Climate Assessment and the Southwest Climate\nScience Center Program, and USGS Coastal Storm Modeling System (CoSMoS)","language":"English","publisher":"California Sea Grant","collaboration":"CA Sea Grant, NOAA, County of Santa Barbara, Cities of Goleta, Carpinteria and Santa Barbara","usgsCitation":"Myers, M., Cayan, D., Iacobellis, S., Melack, J., Beighley, R., Barnard, P., Dugan, J., and Page, H., 2019, Santa Barbara area coastal ecosystem vulnerability assessment (CASG-17-009), 207 p.","productDescription":"207 p.","ipdsId":"IP-111905","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":369323,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":369279,"type":{"id":15,"text":"Index Page"},"url":"https://caseagrant.ucsd.edu/sites/default/files/SBA-CEVA-final-0917_0.pdf"}],"country":"United States","state":"California","city":"Santa Barbara","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.33325195312499,\n 34.14363482031264\n ],\n [\n -119.06982421874999,\n 34.14363482031264\n ],\n [\n -119.06982421874999,\n 34.59704151614417\n ],\n [\n -120.33325195312499,\n 34.59704151614417\n ],\n [\n -120.33325195312499,\n 34.14363482031264\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"CASG-17-009","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Myers, M.R.","contributorId":220701,"corporation":false,"usgs":false,"family":"Myers","given":"M.R.","email":"","affiliations":[{"id":39996,"text":"California Sea Grant","active":true,"usgs":false}],"preferred":false,"id":775469,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cayan, D.R.","contributorId":25961,"corporation":false,"usgs":false,"family":"Cayan","given":"D.R.","email":"","affiliations":[{"id":16196,"text":"Scripps Institution of Oceanography, La Jolla, CA","active":true,"usgs":false}],"preferred":false,"id":775470,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Iacobellis, S.F.","contributorId":220702,"corporation":false,"usgs":false,"family":"Iacobellis","given":"S.F.","email":"","affiliations":[{"id":37799,"text":"SCRIPPS","active":true,"usgs":false}],"preferred":false,"id":775471,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Melack, J.M.","contributorId":220703,"corporation":false,"usgs":false,"family":"Melack","given":"J.M.","email":"","affiliations":[{"id":36524,"text":"University of California, Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":775472,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Beighley, R.E.","contributorId":220704,"corporation":false,"usgs":false,"family":"Beighley","given":"R.E.","email":"","affiliations":[{"id":38331,"text":"Northeastern University","active":true,"usgs":false}],"preferred":false,"id":775473,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"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":775468,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dugan, J.E.","contributorId":220705,"corporation":false,"usgs":false,"family":"Dugan","given":"J.E.","email":"","affiliations":[{"id":36524,"text":"University of California, Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":775474,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Page, H.M.","contributorId":220706,"corporation":false,"usgs":false,"family":"Page","given":"H.M.","email":"","affiliations":[{"id":36524,"text":"University of California, Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":775475,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70206645,"text":"sir20175022E - 2019 - Field trip guide to Mount St. Helens, Washington—Recent and ancient volcaniclastic processes and deposits","interactions":[{"subject":{"id":70206645,"text":"sir20175022E - 2019 - Field trip guide to Mount St. Helens, Washington—Recent and ancient volcaniclastic processes and deposits","indexId":"sir20175022E","publicationYear":"2019","noYear":false,"chapter":"E","displayTitle":"Field Trip Guide to Mount St. Helens, Washington—Recent and Ancient Volcaniclastic Processes and Deposits","title":"Field trip guide to Mount St. Helens, Washington—Recent and ancient volcaniclastic processes and deposits"},"predicate":"IS_PART_OF","object":{"id":70188710,"text":"sir20175022 - 2017 - Field-trip guides to selected volcanoes and volcanic landscapes of the western United States","indexId":"sir20175022","publicationYear":"2017","noYear":false,"title":"Field-trip guides to selected volcanoes and volcanic landscapes of the western United States"},"id":1}],"isPartOf":{"id":70188710,"text":"sir20175022 - 2017 - Field-trip guides to selected volcanoes and volcanic landscapes of the western United States","indexId":"sir20175022","publicationYear":"2017","noYear":false,"title":"Field-trip guides to selected volcanoes and volcanic landscapes of the western United States"},"lastModifiedDate":"2019-11-19T06:39:36","indexId":"sir20175022E","displayToPublicDate":"2019-11-18T18:08:01","publicationYear":"2019","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":"2017-5022","chapter":"E","displayTitle":"Field Trip Guide to Mount St. Helens, Washington—Recent and Ancient Volcaniclastic Processes and Deposits","title":"Field trip guide to Mount St. Helens, Washington—Recent and ancient volcaniclastic processes and deposits","docAbstract":"

This field guide explores volcanic effusions, sediments, and landforms at Mount St. Helens in Washington. A detailed synopsis outlines the eruptive history of Mount St. Helens from about 300,000 years ago through 1980 and beyond.

The five days in the field include about 28 stops and 12 potential stops. Exposures in valleys surrounding Mount St. Helens reveal records of diverse Pleistocene and Holocene processes including debris avalanche, lahar, huge water wave on a nearby lake, pyroclastic density currents (surge and flow), tephra fall, lava flow, the growth of domes, and Pleistocene glaciation. Many of the stops explore effects of the several catastrophes that constituted the 18 May 1980 eruption and made Mount St. Helens famous.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175022E","usgsCitation":"Waitt, R.B., Major, J.J., Hoblitt, R.P., Van Eaton, A.R., and Clynne, M.A., 2019, Field trip guide to Mount St. Helens, Washington—Recent and ancient volcaniclastic processes and deposits: U.S. Geological Survey Scientific Investigations Report 2017–5022–E, 68 p., https://doi.org/10.3133/sir20175022E.","productDescription":"xii, 68 p.","numberOfPages":"84","onlineOnly":"Y","ipdsId":"IP-076026","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":369261,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5022/e/coverthb.jpg"},{"id":369262,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5022/e/sir20175022E.pdf","text":"Report","size":"53.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5022–E"}],"country":"United States","state":"Washington","otherGeospatial":"Mount St. Helens","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.38494873046875,\n 46.12274903582433\n ],\n [\n -122.01141357421875,\n 46.12274903582433\n ],\n [\n -122.01141357421875,\n 46.3886223381617\n ],\n [\n -122.38494873046875,\n 46.3886223381617\n ],\n [\n -122.38494873046875,\n 46.12274903582433\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Volcano Science Center - Menlo Park
U.S. Geological Survey
345 Middlefield Road, MS 910
Menlo Park, CA 94025

","tableOfContents":"","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2019-11-18","noUsgsAuthors":false,"publicationDate":"2019-11-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Waitt, Richard B. 0000-0002-6392-5604 waitt@usgs.gov","orcid":"https://orcid.org/0000-0002-6392-5604","contributorId":2343,"corporation":false,"usgs":true,"family":"Waitt","given":"Richard","email":"waitt@usgs.gov","middleInitial":"B.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":775295,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Major, Jon J. 0000-0003-2449-4466 jjmajor@usgs.gov","orcid":"https://orcid.org/0000-0003-2449-4466","contributorId":439,"corporation":false,"usgs":true,"family":"Major","given":"Jon","email":"jjmajor@usgs.gov","middleInitial":"J.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":775296,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hoblitt, Richard P. 0000-0001-5850-4760","orcid":"https://orcid.org/0000-0001-5850-4760","contributorId":220615,"corporation":false,"usgs":true,"family":"Hoblitt","given":"Richard","email":"","middleInitial":"P.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":775297,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Van Eaton, Alexa R. 0000-0001-6646-4594 avaneaton@usgs.gov","orcid":"https://orcid.org/0000-0001-6646-4594","contributorId":184079,"corporation":false,"usgs":true,"family":"Van Eaton","given":"Alexa","email":"avaneaton@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":775298,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Clynne, Michael A. 0000-0002-4220-2968 mclynne@usgs.gov","orcid":"https://orcid.org/0000-0002-4220-2968","contributorId":2032,"corporation":false,"usgs":true,"family":"Clynne","given":"Michael","email":"mclynne@usgs.gov","middleInitial":"A.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":775299,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70206110,"text":"ofr20191120 - 2019 - Differentiating sediment sources using sediment fingerprinting techniques, in the Sprague River Basin, South-Central Oregon","interactions":[],"lastModifiedDate":"2019-11-19T06:33:51","indexId":"ofr20191120","displayToPublicDate":"2019-11-18T13:59:03","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-1120","displayTitle":"Differentiating Sediment Sources Using Sediment Fingerprinting Techniques, in the Sprague River Basin, South-Central Oregon","title":"Differentiating sediment sources using sediment fingerprinting techniques, in the Sprague River Basin, South-Central Oregon","docAbstract":"

Identifying sources of sediment to streams in the Sprague River Basin, in south-central Oregon, is important for restoration efforts that are focused on reducing sediment erosion and transport. Reducing sediment loads in these streams also contributes to compliance with the total maximum daily load reduction requirements for total phosphorus in this basin. In the Sprague River Basin, phosphorus occurs in surface waters in both dissolved phase and particulate phase, and particulate phosphorus is readily transported in streams on fine-grained suspended sediments, which eventually deposit in Upper Klamath Lake. The lake has seasonal blooms of cyanobacteria that require phosphorus for growth and degrade water-quality conditions, violating State water-quality standards and creating conditions that are stressful to two endangered suckers that reside in the lake. Identifying sources of sediment to the Sprague River could help inform restoration actions by determining the principal locations in the basin contributing fine sediment to the river. The U.S. Geological Survey, in cooperation with the U.S. Fish and Wildlife Service, conducted a proof-of-concept study to determine if sediment fingerprinting can differentiate sources of bank erosion by source material, basin, river reach, and soil horizon. The sediment fingerprinting approach uses properties of streambank and streambed sediment to differentiate between multiple sediment sources by determining a composite signature, or fingerprint. The composite fingerprint is established by combining fingerprint properties from laboratory results of elemental analysis, stable isotopes, and total carbon and nitrogen. The methods for differentiating sediment samples for this study include grouping bank and bed samples by basin, river reach, and soil horizon, and using non-parametric statistics to determine which fingerprint properties could be used to differentiate the sample groups. Results indicate that fingerprint properties differentiated source material, river reach, and basin, and were more successful at differentiating samples grouped by geographic location (basin and reach) compared to source material. Source material (banks, bed, levees) were differentiated with three fingerprint properties—Antimony (Sb), copper (Cu), and manganese (Mn). The basin category (South Fork and main-stem Sprague River) differentiated the South Fork and main stem with stable nitrogen isotopes (δ15N), aluminum (Al), silicon (Si), and vanadium (V). Specific river reaches within the study area were differentiated with 11 different fingerprint properties. These results can be used for apportionment studies using suspended sediment samples and mixing models to determine sediment source contributions within the basin.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191120","collaboration":"Prepared in cooperation with U.S. Fish and Wildlife Service","usgsCitation":"Schenk, L.N., Harden, T.M., and Kelson, J.K., 2019, Differentiating sediment sources using sediment fingerprinting techniques, in the Sprague River Basin, south-central Oregon: U.S. Geological Survey Open-File Report 2019-1120, 25 p., https://doi.org/10.3133/ofr20191120.","productDescription":"Report: vi, 25 p.; 2 Tables; Appendix","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-106755","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":369299,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1120/ofr20191120.pdf","text":"Report","size":"7.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1120"},{"id":369302,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2019/1120/ofr20191120_appendix1.xlsx","text":"Appendix 1 –","size":"41 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2019-1120 Appendix 1","linkHelpText":" Analytical Results and Site Characteristics"},{"id":369298,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1120/coverthb.jpg"},{"id":369300,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2019/1120/ofr20191120_table03.xlsx","text":"Table 3","size":"21 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2019-1120 Table 3"},{"id":369301,"rank":4,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2019/1120/ofr20191120_table05.xlsx","text":"Table 5","size":"28 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2019-1120 Table 5"}],"country":"United States","state":"Oregon","otherGeospatial":"Sprague River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.947998046875,\n 41.95949009892467\n ],\n [\n -119.21264648437499,\n 41.95949009892467\n ],\n [\n -119.21264648437499,\n 44.04811573082351\n ],\n [\n -122.947998046875,\n 44.04811573082351\n ],\n [\n -122.947998046875,\n 41.95949009892467\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

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

","tableOfContents":"","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"publishedDate":"2019-11-18","noUsgsAuthors":false,"publicationDate":"2019-11-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Schenk, Liam N. 0000-0002-2491-0813 lschenk@usgs.gov","orcid":"https://orcid.org/0000-0002-2491-0813","contributorId":4273,"corporation":false,"usgs":true,"family":"Schenk","given":"Liam","email":"lschenk@usgs.gov","middleInitial":"N.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":773614,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Harden, Tessa M. 0000-0001-9854-1347 tharden@usgs.gov","orcid":"https://orcid.org/0000-0001-9854-1347","contributorId":192153,"corporation":false,"usgs":true,"family":"Harden","given":"Tessa","email":"tharden@usgs.gov","middleInitial":"M.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":773615,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kelson, Julia K. 0000-0002-0588-5018","orcid":"https://orcid.org/0000-0002-0588-5018","contributorId":220716,"corporation":false,"usgs":false,"family":"Kelson","given":"Julia K.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":773616,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70205547,"text":"cir1460 - 2019 - Woods Hole Coastal and Marine Science Center—2018 annual report","interactions":[],"lastModifiedDate":"2019-11-19T06:43:46","indexId":"cir1460","displayToPublicDate":"2019-11-18T13:55:00","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":307,"text":"Circular","code":"CIR","onlineIssn":"2330-5703","printIssn":"1067-084X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1460","displayTitle":"Woods Hole Coastal and Marine Science Center—2018 Annual Report","title":"Woods Hole Coastal and Marine Science Center—2018 annual report","docAbstract":"

The 2018 annual report of the U.S. Geological Survey Woods Hole Coastal and Marine Science Center summarizes the work of the center, as well as the work of each of its science groups, highlights accomplishments of 2018, and includes a list of publications published in 2018. This product allows readers to gain a general understanding of the focus areas of the center’s scientific research and learn more about specific projects and progress made throughout 2018, all while enjoying applicable photos taken in the field and of various models, maps, and web pages.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1460","usgsCitation":"Ernst, S., 2019, Woods Hole Coastal and Marine Science Center—2018 annual report: U.S. Geological Survey Circular 1460, 36 p., https://doi.org/10.3133/cir1460.","productDescription":"iv, 36 p.","numberOfPages":"44","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-108282","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":369283,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1460/cir1460.pdf","text":"Report","size":"11.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"CIR 1460"},{"id":368016,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/circ/1460/coverthb.jpg"}],"country":"United States","state":"Massachusetts","city":"Falmouth","otherGeospatial":"Woods Hole Coastal and Marine Science Center","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -70.68672180175781,\n 41.513719082873486\n ],\n [\n -70.61119079589844,\n 41.513719082873486\n ],\n [\n -70.61119079589844,\n 41.55278330492603\n ],\n [\n -70.68672180175781,\n 41.55278330492603\n ],\n [\n -70.68672180175781,\n 41.513719082873486\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Woods Hole Coastal and Marine Science Center
U.S. Geological Survey
384 Woods Hole Road
Quissett Campus
Woods Hole, MA 02543-1598
(508) 548–8700 or (508) 457–2200

","tableOfContents":"","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"publishedDate":"2019-10-07","noUsgsAuthors":false,"publicationDate":"2019-10-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Ernst, Sara 0000-0001-7825-3209","orcid":"https://orcid.org/0000-0001-7825-3209","contributorId":219205,"corporation":false,"usgs":true,"family":"Ernst","given":"Sara","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":771592,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70203902,"text":"cir1456 - 2019 - Yellowstone Volcano Observatory 2017 annual report","interactions":[],"lastModifiedDate":"2025-05-08T15:38:50.359915","indexId":"cir1456","displayToPublicDate":"2019-11-18T13:02:57","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":307,"text":"Circular","code":"CIR","onlineIssn":"2330-5703","printIssn":"1067-084X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1456","displayTitle":"Yellowstone Volcano Observatory 2017 Annual Report","title":"Yellowstone Volcano Observatory 2017 annual report","docAbstract":"

The Yellowstone Volcano Observatory (YVO) monitors volcanic and hydrothermal activity associated with the Yellowstone magmatic system, conducts research into magmatic processes occurring beneath Yellowstone Caldera, and issues timely warnings and guidance related to potential future geologic hazards. This report summarizes the activities and findings of YVO during the year 2017, focusing on the Yellowstone magmatic system. The most noteworthy event of the year was the Maple Creek earthquake swarm of June–September, about 15 kilometers north-northwest of West Yellowstone, Montana. Over 2,400 earthquakes were located, including a felt magnitude 4.4 earthquake on June 15. Deformation was mostly consistent throughout the year, with uplift of the Norris Geyser Basin area and subsidence of the caldera, both at rates of a few centimeters per year. The only significant interruption in this pattern was an ~2-week period of subsidence at Norris Geyser Basin in early December, after which deformation returned to uplift. Field work in 2017, conducted under research permits granted by the National Park Service, included routine maintenance visits to seismic and geodetic stations as well as deployment of a semipermanent Global Positioning System network during the summer months, installation of Multi-GAS and eddy covariance systems for tracking gas emissions at the Solfatara Plateau thermal area, deployment of a nodal seismic array in Upper Geyser Basin, and collection of gas and water samples from Boundary Creek on the western side of Yellowstone National Park.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1456","usgsCitation":"Yellowstone Volcano Observatory, 2019, Yellowstone Volcano Observatory 2017 annual report: U.S. Geological Survey Circular 1456, 37 p., https://doi.org/10.3133/cir1456.","productDescription":"v, 37 p.","ipdsId":"IP-103262","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":369306,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1456/cir1456.pdf","text":"Report","size":"67.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Circular 1456"},{"id":369305,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/circ/1456/coverthb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Yellowstone Volcano Observatory","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.1431884765625,\n 43.8503744993026\n ],\n [\n -109.4293212890625,\n 43.8503744993026\n ],\n [\n -109.4293212890625,\n 45.0502402697946\n ],\n [\n -111.1431884765625,\n 45.0502402697946\n ],\n [\n -111.1431884765625,\n 43.8503744993026\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Yellowstone Volcano Observatory
U.S. Geological Survey
1300 SE Cardinal Court, Suite 100
Vancouver, WA 98683

Email: yvowebteam@usgs.gov

","tableOfContents":"","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2019-11-18","noUsgsAuthors":false,"publicationDate":"2019-11-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Yellowstone Volcano Observatory","contributorId":127797,"corporation":true,"usgs":false,"organization":"Yellowstone Volcano Observatory","id":764664,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70215106,"text":"70215106 - 2019 - Advances in quantifying streamflow variability across continental scales: 2. Improved model regionalization and prediction uncertainties using hierarchical Bayesian methods","interactions":[],"lastModifiedDate":"2020-10-07T15:26:44.598024","indexId":"70215106","displayToPublicDate":"2019-11-18T10:18:28","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Advances in quantifying streamflow variability across continental scales: 2. Improved model regionalization and prediction uncertainties using hierarchical Bayesian methods","docAbstract":"

The precise estimation of process effects in hydrological models requires applying models to large scales with extensive spatial variability in controlling factors. Despite progress in large‐scale applications of hydrological models in conterminous United States (CONUS) river basins, spatial constraints in model parameters have prevented the interbasin sharing of data, complicating quantification of process effects and limiting the accuracy of model predictions and uncertainties. Hierarchical Bayesian methods enable data sharing between basins and the identification of the causes of model uncertainties, which can improve model accuracy and interpretability; however, computational inefficiencies have been an obstacle to their large‐scale application. We used a new generation of Bayesian methods to develop a hierarchical version of a previous hybrid (statistical‐mechanistic) SPAtially Referenced Regression On Watershed attributes model of long‐term mean annual streamflow in the CONUS. We identified hierarchical (regional) variations in model coefficients and uncertainties and evaluated their effects on model accuracy and interpretability across diverse environments in 16 major CONUS regions. Hierarchical coefficients significantly improved spatial accuracy of model predictions, with the largest improvements in humid eastern regions, where uncertainties were approximately one third of those in arid western regions. Half of the coefficients varied regionally, with the largest variations in coefficients associated with water losses in streams and reservoirs. Our unraveling of the causes of model uncertainties identified a small latent process component of runoff that varies inversely with river size in most CONUS regions. Our study advances the use of hierarchical Bayesian methods to improve the predictive capabilities of hydrological models.

","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2019WR025037","usgsCitation":"Alexander, R.B., Schwarz, G.E., and Boyer, E.W., 2019, Advances in quantifying streamflow variability across continental scales: 2. Improved model regionalization and prediction uncertainties using hierarchical Bayesian methods: Water Resources Research, v. 55, no. 12, p. 11061-11087, https://doi.org/10.1029/2019WR025037.","productDescription":"27 p.","startPage":"11061","endPage":"11087","ipdsId":"IP-105136","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":459161,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2019wr025037","text":"Publisher Index Page"},{"id":379175,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"geometry\": {\n \"type\": \"MultiPolygon\",\n \"coordinates\": [\n [\n [\n [\n -94.81758,\n 49.38905\n ],\n [\n -94.64,\n 48.84\n ],\n [\n -94.32914,\n 48.67074\n ],\n [\n -93.63087,\n 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-107.05,\n 49\n ],\n [\n -104.04826,\n 48.99986\n ],\n [\n -100.65,\n 49\n ],\n [\n -97.22872,\n 49.0007\n ],\n [\n -95.15907,\n 49\n ],\n [\n -95.15609,\n 49.38425\n ],\n [\n -94.81758,\n 49.38905\n ]\n ]\n ]\n ]\n },\n \"properties\": {\n \"name\": \"United States\"\n }\n }\n ]\n}","volume":"55","issue":"12","noUsgsAuthors":false,"publicationDate":"2019-12-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Alexander, Richard B. 0000-0001-9166-0626 ralex@usgs.gov","orcid":"https://orcid.org/0000-0001-9166-0626","contributorId":541,"corporation":false,"usgs":true,"family":"Alexander","given":"Richard","email":"ralex@usgs.gov","middleInitial":"B.","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true}],"preferred":true,"id":800904,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schwarz, Gregory E. 0000-0002-9239-4566 gschwarz@usgs.gov","orcid":"https://orcid.org/0000-0002-9239-4566","contributorId":213621,"corporation":false,"usgs":true,"family":"Schwarz","given":"Gregory","email":"gschwarz@usgs.gov","middleInitial":"E.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":800905,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Boyer, Elizabeth W.","contributorId":44659,"corporation":false,"usgs":false,"family":"Boyer","given":"Elizabeth","email":"","middleInitial":"W.","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":800906,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70241849,"text":"70241849 - 2019 - Population ecology of Roosevelt elk: Conservation and management in Redwood National and State Parks. Butch Weckerly. 2017. University of Nevada Press, Reno, Nevada, USA. 224 pp. $54.95 hardback. ISBN 978- 1943859504.","interactions":[],"lastModifiedDate":"2023-03-29T13:37:48.882262","indexId":"70241849","displayToPublicDate":"2019-11-18T08:34:44","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Population ecology of Roosevelt elk: Conservation and management in Redwood National and State Parks. Butch Weckerly. 2017. University of Nevada Press, Reno, Nevada, USA. 224 pp. $54.95 hardback. ISBN 978- 1943859504.","docAbstract":"

Long-term research on large ungulate populations typically conjures perceptions of extensive (and expensive) animal capture and telemetry work, and subsequent advanced modeling of resource selection and population dynamics that inform management decisions. In contrast, studies lacking a telemetry component are often limited to animal behavior or natural history. Although compelling from a standpoint of advancing understanding of ecological and evolutionary processes, results from the latter can be unfairly labeled as esoteric because they are not easily transferable to resource managers or may not provide exceptional interest to a general public drawn to these charismatic megafuana. Such dichotomies are not predetermined, however, because study conditions exist where dedicated academic researchers on tight budgets can achieve results relevant to ecology and management.

","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.21599","usgsCitation":"Ricca, M.A., 2019, Population ecology of Roosevelt elk: Conservation and management in Redwood National and State Parks. Butch Weckerly. 2017. University of Nevada Press, Reno, Nevada, USA. 224 pp. $54.95 hardback. ISBN 978- 1943859504.: Journal of Wildlife Management, v. 83, p. 243-244, https://doi.org/10.1002/jwmg.21599.","productDescription":"2 p.","startPage":"243","endPage":"244","ipdsId":"IP-101496","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":414892,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"83","noUsgsAuthors":false,"publicationDate":"2018-11-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Ricca, Mark A. 0000-0003-1576-513X mark_ricca@usgs.gov","orcid":"https://orcid.org/0000-0003-1576-513X","contributorId":139103,"corporation":false,"usgs":true,"family":"Ricca","given":"Mark","email":"mark_ricca@usgs.gov","middleInitial":"A.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":867920,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70216137,"text":"70216137 - 2019 - Constraining dissolved organic matter sources and temporal variability in a model sub-Arctic lake","interactions":[],"lastModifiedDate":"2020-11-06T13:57:10.563433","indexId":"70216137","displayToPublicDate":"2019-11-18T07:51:43","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1007,"text":"Biogeochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Constraining dissolved organic matter sources and temporal variability in a model sub-Arctic lake","docAbstract":"

Circumpolar lakes comprise ~ 1.4 million km2 of arctic and subarctic landscapes and are vulnerable to change in vegetation, permafrost distribution, and hydrological conditions in response to climate warming. However, the composition and cycling of dissolved organic matter (DOM) is poorly understood for these lakes because most are remote and unstudied. The goal of this study was to assess timescale and source controls on DOM composition in Canvasback Lake, a shallow, sub-Arctic lake in interior Alaska with similar hydrologic and geomorphic characteristics to about a quarter of circumpolar lake ecosystems. Lake dissolved organic carbon (DOC) concentration varied by as much as 16% from the mean (3.34 mg L−1 change) through diel cycles in spring 2016 to fall 2017 and was accompanied by minor changes in DOM composition. At the seasonal scale, DOC concentration increased from spring through fall to very high concentrations under ice in winter. Decreases in both condensed aromatic and polyphenolic compound classes and lignin carbon-normalized yield, plus increased relative abundance of aliphatic compounds, suggests that DOM composition shifts from a pulse of allochthonous DOM in the spring to more autochthonous under-ice. These changes highlight the seasonally-dynamic nature of DOM in circumpolar lakes that are poorly captured by single-visit lake surveys and underscores the need to measure DOM properties and fate consistently across multiple timescales (i.e. seasonally) to better constrain the role of DOM in lake processes. To further assess DOM sources, a suite of endmember leachates were compared to bulk lake DOM, indicating solely allochthonous inputs are not well reflected in lake DOM, highlighting the role of degradation processes or mixing with autochthonous sources. Thus, Canvasback Lake appears less well connected to terrestrial inputs compared to past studies of northern high-latitude lakes and does not behave as previous boreal lake models suggest.

","language":"English","publisher":"Springer","doi":"10.1007/s10533-019-00619-9","usgsCitation":"Johnston, S.E., Bogard, M.J., Rogers, J.A., Butman, D., Striegl, R.G., Dornblaser, M.M., and Spencer, R., 2019, Constraining dissolved organic matter sources and temporal variability in a model sub-Arctic lake: Biogeochemistry, v. 146, p. 271-292, https://doi.org/10.1007/s10533-019-00619-9.","productDescription":"22 p.","startPage":"271","endPage":"292","ipdsId":"IP-114232","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":380253,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Yukon River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -159.3896484375,\n 65.96437717203096\n ],\n [\n -142.1630859375,\n 65.96437717203096\n ],\n [\n -142.1630859375,\n 69.67235784229395\n ],\n [\n -159.3896484375,\n 69.67235784229395\n ],\n [\n -159.3896484375,\n 65.96437717203096\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"146","noUsgsAuthors":false,"publicationDate":"2019-11-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Johnston, Sarah Ellen","contributorId":213256,"corporation":false,"usgs":false,"family":"Johnston","given":"Sarah","email":"","middleInitial":"Ellen","affiliations":[{"id":7092,"text":"Florida State University","active":true,"usgs":false}],"preferred":false,"id":804265,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bogard, Matthew J. 0000-0001-9491-0328","orcid":"https://orcid.org/0000-0001-9491-0328","contributorId":213254,"corporation":false,"usgs":false,"family":"Bogard","given":"Matthew","email":"","middleInitial":"J.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":804266,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rogers, Jennifer A.","contributorId":244616,"corporation":false,"usgs":false,"family":"Rogers","given":"Jennifer","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":804267,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Butman, David 0000-0003-3520-7426 dbutman@usgs.gov","orcid":"https://orcid.org/0000-0003-3520-7426","contributorId":174187,"corporation":false,"usgs":true,"family":"Butman","given":"David","email":"dbutman@usgs.gov","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":804268,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Striegl, Robert G. 0000-0002-8251-4659 rstriegl@usgs.gov","orcid":"https://orcid.org/0000-0002-8251-4659","contributorId":1630,"corporation":false,"usgs":true,"family":"Striegl","given":"Robert","email":"rstriegl@usgs.gov","middleInitial":"G.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true}],"preferred":false,"id":804269,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dornblaser, Mark M. 0000-0002-6298-3757 mmdornbl@usgs.gov","orcid":"https://orcid.org/0000-0002-6298-3757","contributorId":1636,"corporation":false,"usgs":true,"family":"Dornblaser","given":"Mark","email":"mmdornbl@usgs.gov","middleInitial":"M.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":804270,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Spencer, Robert G. M.","contributorId":139731,"corporation":false,"usgs":false,"family":"Spencer","given":"Robert G. M.","affiliations":[{"id":12894,"text":"Department of Land, Air, and Water Resources, University of California, One Shields Avenue, Davis, CA, 95616, USA","active":true,"usgs":false}],"preferred":false,"id":804271,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70206837,"text":"70206837 - 2019 - Historical range and variation (HRV)","interactions":[],"lastModifiedDate":"2021-01-18T22:54:41.544964","indexId":"70206837","displayToPublicDate":"2019-11-18T06:53:37","publicationYear":"2019","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Historical range and variation (HRV)","docAbstract":"Fire-prone landscapes are experiencing rapid and potentially persistent changes as the result of complex and potentially novel interactions of anthropogenic climate changes, shifting fire regimes, exotic plant, insect, and pathogen invasions, and industrial, agricultural, and urban development. Are these landscapes fully departed from historical conditions? Should they be managed as novel environments or as landscapes in transition? Historical range and variation is a benchmark representation of the conditions that describe fully functional, healthy ecosystems or landscapes. The HRV can provide an ecological reference against which contemporary and future conditions can be evaluated to determine status, trend, and magnitude of departure. This text describes the concepts of HRV, methods for developing HRV data sets, and application of HRV for fire management. We discuss the limitations of HRV, and its use under future climates that are no longer representative of historical conditions.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Encyclopedia of Wildfires and Wildland-Urban Interface (WUI) Fires","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-3-319-51727-8_255-1","usgsCitation":"Keane, R., and Loehman, R.A., 2019, Historical range and variation (HRV), chap. of Encyclopedia of Wildfires and Wildland-Urban Interface (WUI) Fires, HTML Document, https://doi.org/10.1007/978-3-319-51727-8_255-1.","productDescription":"HTML Document","ipdsId":"IP-109003","costCenters":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"links":[{"id":369521,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2019-11-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Keane, Robert","contributorId":187606,"corporation":false,"usgs":false,"family":"Keane","given":"Robert","affiliations":[],"preferred":false,"id":776001,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Loehman, Rachel A. 0000-0001-7680-1865 rloehman@usgs.gov","orcid":"https://orcid.org/0000-0001-7680-1865","contributorId":187605,"corporation":false,"usgs":true,"family":"Loehman","given":"Rachel","email":"rloehman@usgs.gov","middleInitial":"A.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"preferred":false,"id":776000,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70206688,"text":"70206688 - 2019 - Dissolved organic matter in the deep TALDICE ice core: A nano-UPLC-nano-ESI-HRMS method","interactions":[],"lastModifiedDate":"2019-11-18T06:42:12","indexId":"70206688","displayToPublicDate":"2019-11-18T06:40:19","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Dissolved organic matter in the deep TALDICE ice core: A nano-UPLC-nano-ESI-HRMS method","docAbstract":"Trace organic compounds in deep ice cores supply important paleoclimatic information. Untargeted analyses of dissolved organic matter provide an overview of molecular species in ice samples however, sample volumes usually required for these analyses are generally not available from deep ice cores. Here, we developed an analytical method using a nano-UPLC-nano-ESI-HRMS to detect major molecular species in ice cores. Samples (4 µL) from the TALos Dome Ice CorE (TALDICE), allowed investigating molecular species across a range of depths including during glacial and interglacial periods. We detected 317 chemical species that were tentatively assigned to fatty acids, hydroxy fatty acids and their degradation products (oxo-fatty acids and dicarboxylic acids), as well as oxidation byproducts of isoprene and monoterpenes. These compounds indicate that the main sources of the organic fraction are microbes as well as primary and secondary aerosols. Interglacial samples encompass a wide range of species including compounds from the oxidation of isoprene and monoterpenes as well as unsaturated fatty acids, while the glacial samples contained less diverse species. This difference may be due to decreased temperatures during the glacial period inhibiting terrestrial vegetation growth and increasing the sea ice extent, thereby weakening the emission sources.","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2019.134432","usgsCitation":"Zangrando, R., Zanella, V., Karroca, O., Barbaro, E., Kehrwald, N., Battistel, D., Gambaro, A., and Barbante, C., 2019, Dissolved organic matter in the deep TALDICE ice core: A nano-UPLC-nano-ESI-HRMS method: Science of the Total Environment, v. 700, 134432, https://doi.org/10.1016/j.scitotenv.2019.134432.","productDescription":"134432","ipdsId":"IP-098635","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":369277,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"700","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Zangrando, Roberta","contributorId":205868,"corporation":false,"usgs":false,"family":"Zangrando","given":"Roberta","email":"","affiliations":[{"id":37182,"text":"Institute for the Dynamics of Environmental Processes -- CNR, Venice, Italy","active":true,"usgs":false}],"preferred":false,"id":775369,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zanella, Veronica","contributorId":220637,"corporation":false,"usgs":false,"family":"Zanella","given":"Veronica","email":"","affiliations":[{"id":38042,"text":"Department of Environmental Sciences, Informatics and Statistics, Ca' Foscari University of Venice","active":true,"usgs":false}],"preferred":false,"id":775370,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Karroca, Ornela","contributorId":220638,"corporation":false,"usgs":false,"family":"Karroca","given":"Ornela","email":"","affiliations":[{"id":38042,"text":"Department of Environmental Sciences, Informatics and Statistics, Ca' Foscari University of Venice","active":true,"usgs":false}],"preferred":false,"id":775371,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barbaro, Elena","contributorId":205867,"corporation":false,"usgs":false,"family":"Barbaro","given":"Elena","email":"","affiliations":[{"id":37181,"text":"Department of Environmental Science, Informatics and Statistics, Ca' Foscari University of Venice, Italy","active":true,"usgs":false}],"preferred":false,"id":775372,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kehrwald, Natalie 0000-0002-9160-2239","orcid":"https://orcid.org/0000-0002-9160-2239","contributorId":220636,"corporation":false,"usgs":true,"family":"Kehrwald","given":"Natalie","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":775368,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Battistel, Dario","contributorId":205865,"corporation":false,"usgs":false,"family":"Battistel","given":"Dario","email":"","affiliations":[{"id":37181,"text":"Department of Environmental Science, Informatics and Statistics, Ca' Foscari University of Venice, Italy","active":true,"usgs":false}],"preferred":false,"id":775373,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gambaro, Andrea","contributorId":205873,"corporation":false,"usgs":false,"family":"Gambaro","given":"Andrea","email":"","affiliations":[{"id":37181,"text":"Department of Environmental Science, Informatics and Statistics, Ca' Foscari University of Venice, Italy","active":true,"usgs":false}],"preferred":false,"id":775374,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Barbante, Carlo","contributorId":202632,"corporation":false,"usgs":false,"family":"Barbante","given":"Carlo","email":"","affiliations":[{"id":36503,"text":"Department of Environmental Sciences, Infomatics, and Statistics, Ca'Foscari University of Venice, Via Torino 155, 30172 Mestre (VE), Italy","active":true,"usgs":false}],"preferred":false,"id":775375,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70215938,"text":"70215938 - 2019 - Fluorescent biomarkers demonstrate prospects for spreadable vaccines to control disease transmission in wild bats","interactions":[],"lastModifiedDate":"2020-11-02T12:26:25.330628","indexId":"70215938","displayToPublicDate":"2019-11-18T06:19:20","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7304,"text":"Nature Ecology and Evotution","active":true,"publicationSubtype":{"id":10}},"title":"Fluorescent biomarkers demonstrate prospects for spreadable vaccines to control disease transmission in wild bats","docAbstract":"

Vaccines that autonomously transfer among individuals have been proposed as a strategy to control infectious diseases within inaccessible wildlife populations. However, rates of vaccine spread and epidemiological efficacy in real-world systems remain elusive. Here, we investigate whether topical vaccines that transfer among individuals through social contacts can control vampire bat rabies—a medically and economically important zoonosis in Latin America. Field experiments in three Peruvian bat colonies, which used fluorescent biomarkers as a proxy for the bat-to-bat transfer and ingestion of an oral vaccine, revealed that vaccine transfer would increase population-level immunity up to 2.6 times beyond the same effort using conventional, non-spreadable vaccines. Mathematical models showed that observed levels of vaccine transfer would reduce the probability, size and duration of rabies outbreaks, even at low but realistically achievable levels of vaccine application. Models further predicted that existing vaccines provide substantial advantages over culling bats—the policy currently implemented in North, Central and South America. Linking field studies with biomarkers to mathematical models can inform how spreadable vaccines may combat pathogens of health and conservation concern before costly investments in vaccine design and testing.

","language":"English","publisher":"Nature Publishing Group","doi":"10.1038/s41559-019-1032-x","usgsCitation":"Bakker, K.M., Rocke, T.E., Osorio, J., Abbott, R.C., Tello, C., Carerra, J., Valderrama, W., Shiva, C., Falcon, N., and Streicker, D.G., 2019, Fluorescent biomarkers demonstrate prospects for spreadable vaccines to control disease transmission in wild bats: Nature Ecology and Evotution, v. 3, p. 1697-1704, https://doi.org/10.1038/s41559-019-1032-x.","productDescription":"8 p.","startPage":"1697","endPage":"1704","ipdsId":"IP-109945","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":459171,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41559-019-1032-x","text":"Publisher Index Page"},{"id":380001,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"3","noUsgsAuthors":false,"publicationDate":"2019-11-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Bakker, Kevin M. 0000-0002-7084-9291","orcid":"https://orcid.org/0000-0002-7084-9291","contributorId":244266,"corporation":false,"usgs":false,"family":"Bakker","given":"Kevin","email":"","middleInitial":"M.","affiliations":[{"id":48876,"text":"Institute of Biodiversity, Animal Health and Comparative Medicine, College of Medical,","active":true,"usgs":false}],"preferred":false,"id":803632,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rocke, Tonie E. 0000-0003-3933-1563 trocke@usgs.gov","orcid":"https://orcid.org/0000-0003-3933-1563","contributorId":2665,"corporation":false,"usgs":true,"family":"Rocke","given":"Tonie","email":"trocke@usgs.gov","middleInitial":"E.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":803631,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Osorio, Jorge E.","contributorId":50392,"corporation":false,"usgs":false,"family":"Osorio","given":"Jorge E.","affiliations":[{"id":13052,"text":"Department of Pathobiological Sciences, School of Veterinary Medicine, University of Wisconsin","active":true,"usgs":false}],"preferred":false,"id":803633,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Abbott, Rachel C. 0000-0003-4820-9295 rabbott@usgs.gov","orcid":"https://orcid.org/0000-0003-4820-9295","contributorId":1183,"corporation":false,"usgs":true,"family":"Abbott","given":"Rachel","email":"rabbott@usgs.gov","middleInitial":"C.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":803634,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Tello, Carlos","contributorId":244267,"corporation":false,"usgs":false,"family":"Tello","given":"Carlos","email":"","affiliations":[{"id":48877,"text":"ILLARIY, Asociaci´on para el Desarrollo y Conservaci´on de los Recursos Naturales Lima, Peru","active":true,"usgs":false}],"preferred":false,"id":803635,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Carerra, Jorge","contributorId":244268,"corporation":false,"usgs":false,"family":"Carerra","given":"Jorge","email":"","affiliations":[{"id":48877,"text":"ILLARIY, Asociaci´on para el Desarrollo y Conservaci´on de los Recursos Naturales Lima, Peru","active":true,"usgs":false}],"preferred":false,"id":803636,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Valderrama, William","contributorId":244269,"corporation":false,"usgs":false,"family":"Valderrama","given":"William","email":"","affiliations":[{"id":48878,"text":"eILLARIY, Asociaci´on para el Desarrollo y Conservaci´on de los Recursos Naturales Lima, Peru","active":true,"usgs":false}],"preferred":false,"id":803637,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Shiva, Carlos","contributorId":244270,"corporation":false,"usgs":false,"family":"Shiva","given":"Carlos","email":"","affiliations":[{"id":48879,"text":"hFaculty of Veterinary Medicine and Zootechnics, Universidad Peruana Cayetano, Lima, Peru","active":true,"usgs":false}],"preferred":false,"id":803638,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Falcon, Nestor","contributorId":244271,"corporation":false,"usgs":false,"family":"Falcon","given":"Nestor","email":"","affiliations":[{"id":48879,"text":"hFaculty of Veterinary Medicine and Zootechnics, Universidad Peruana Cayetano, Lima, Peru","active":true,"usgs":false}],"preferred":false,"id":803639,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Streicker, Daniel G. 0000-0001-7475-2705","orcid":"https://orcid.org/0000-0001-7475-2705","contributorId":152378,"corporation":false,"usgs":false,"family":"Streicker","given":"Daniel","email":"","middleInitial":"G.","affiliations":[{"id":12473,"text":"University of Glasgow","active":true,"usgs":false}],"preferred":false,"id":803640,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ]}