{"pageNumber":"513","pageRowStart":"12800","pageSize":"25","recordCount":68899,"records":[{"id":70175239,"text":"70175239 - 2015 - Glacier-derived August runoff in northwest Montana","interactions":[],"lastModifiedDate":"2016-08-03T09:30:10","indexId":"70175239","displayToPublicDate":"2015-02-03T10:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":899,"text":"Arctic, Antarctic, and Alpine Research","active":true,"publicationSubtype":{"id":10}},"title":"Glacier-derived August runoff in northwest Montana","docAbstract":"<p><span>The second largest concentration of glaciers in the U.S. Rocky Mountains is located in Glacier National Park (GNP), Montana. The total glacier-covered area in this region decreased by &sim;35% over the past 50 years, which has raised substantial concern about the loss of the water derived from glaciers during the summer. We used an innovative weather station design to collect in situ measurements on five remote glaciers, which are used to parameterize a regional glacier melt model. This model offered a first-order estimate of the summer meltwater production by glaciers. We find, during the normally dry month of August, glaciers in the region produce approximately 25 &times; 10</span><sup>6</sup><span>&nbsp;m</span><sup>3</sup><span>&nbsp;of potential runoff. We then estimated the glacier runoff component in five gaged streams sourced from GNP basins containing glaciers. Glacier-melt contributions range from 5% in a basin only 0.12% glacierized to &gt;90% in a basin 28.5% glacierized. Glacier loss would likely lead to lower discharges and warmer temperatures in streams draining basins &gt;20% glacier-covered. Lower flows could even be expected in streams draining basins as little as 1.4% glacierized if glaciers were to disappear.</span></p>","language":"English","publisher":"Institute of Arctic and Alpine Research","publisherLocation":"Boulder, CO","doi":"10.1657/AAAR0014-033","usgsCitation":"Clark, A., Harper, J.T., and Fagre, D.B., 2015, Glacier-derived August runoff in northwest Montana: Arctic, Antarctic, and Alpine Research, v. 47, no. 1, p. 1-16, https://doi.org/10.1657/AAAR0014-033.","startPage":"1","endPage":"16","numberOfPages":"16","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059157","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":472292,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://www.bioone.org/doi/10.1657/AAAR0014-033","text":"External Repository"},{"id":326012,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","otherGeospatial":"Glacier National Park","volume":"47","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-05","publicationStatus":"PW","scienceBaseUri":"57a315c3e4b006cb45558ad3","contributors":{"authors":[{"text":"Clark, Adam","contributorId":173391,"corporation":false,"usgs":false,"family":"Clark","given":"Adam","affiliations":[{"id":16951,"text":"Department of Geosciences, University of Montana, Missoula, MT 59812, USA","active":true,"usgs":false}],"preferred":false,"id":644491,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Harper, Joel T.","contributorId":173392,"corporation":false,"usgs":false,"family":"Harper","given":"Joel","email":"","middleInitial":"T.","affiliations":[{"id":16951,"text":"Department of Geosciences, University of Montana, Missoula, MT 59812, USA","active":true,"usgs":false}],"preferred":false,"id":644492,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fagre, Daniel B. 0000-0001-8552-9461 dan_fagre@usgs.gov","orcid":"https://orcid.org/0000-0001-8552-9461","contributorId":2036,"corporation":false,"usgs":true,"family":"Fagre","given":"Daniel","email":"dan_fagre@usgs.gov","middleInitial":"B.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":644490,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70139779,"text":"ofr20151020 - 2015 - Mercury and selenium contamination in waterbird eggs and risk to avian reproduction at Great Salt Lake, Utah","interactions":[],"lastModifiedDate":"2020-04-30T11:37:38.243248","indexId":"ofr20151020","displayToPublicDate":"2015-02-02T16:45:00","publicationYear":"2015","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":"2015-1020","title":"Mercury and selenium contamination in waterbird eggs and risk to avian reproduction at Great Salt Lake, Utah","docAbstract":"<p>The wetlands of the Great Salt Lake ecosystem are recognized regionally, nationally, and hemispherically for their importance as breeding, wintering, and migratory habitat for diverse groups of waterbirds. Bear River Migratory Bird Refuge is the largest freshwater component of the Great Salt Lake ecosystem and provides critical breeding habitat for more than 60 bird species. However, the Great Salt Lake ecosystem also has a history of both mercury and selenium contamination, and this pollution could reduce the health and reproductive success of waterbirds. The overall objective of this study was to evaluate the risk of mercury and selenium contamination to birds breeding within Great Salt Lake, especially at Bear River Migratory Bird Refuge, and to identify the waterbird species and areas at greatest risk to contamination. We sampled eggs from 33 species of birds breeding within wetlands of Great Salt Lake during 2010 ̶ 2012 and focused on American avocets (<i>Recurvirostra americana</i>), black-necked stilts (<i>Himantopus mexicanus</i>), Forster&rsquo;s terns (<i>Sterna forsteri</i>), white-faced ibis (<i>Plegadis chihi</i>), and marsh wrens (<i>Cistothorus palustris</i>) for additional studies of the effects of contaminants on reproduction.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151020","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Ackerman, J., Herzog, M., Hartman, C.A., Isanhart, J., Herring, G., Vaughn, S., Cavitt, J.F., Eagles-Smith, C.A., Browers, H., Cline, C., and Vest, J., 2015, Mercury and selenium contamination in waterbird eggs and risk to avian reproduction at Great Salt Lake, Utah: U.S. Geological Survey Open-File Report 2015-1020, Report: x, 164 p.; Data Release, https://doi.org/10.3133/ofr20151020.","productDescription":"Report: x, 164 p.; Data Release","numberOfPages":"178","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-061800","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":297692,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20151020.jpg"},{"id":297691,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1020/pdf/ofr2015-1020.pdf","text":"Report","size":"15.5 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":297690,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2015/1020/"},{"id":374389,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9H4US4N","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Mercury and selenium concentrations in bird eggs at Great Salt Lake, Utah"}],"country":"United States","state":"Utah","otherGeospatial":"Great Salt Lake","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -113.18115234375,\n              41.705728515237524\n            ],\n            [\n              -112.82958984375,\n              41.80407814427234\n            ],\n            [\n              -112.21435546875,\n              41.590796851056005\n            ],\n            [\n              -111.99462890625,\n              41.44272637767212\n            ],\n            [\n              -111.8408203125,\n              40.96330795307353\n            ],\n            [\n              -112.17041015625,\n              40.56389453066509\n            ],\n            [\n              -112.939453125,\n              40.88029480552824\n            ],\n            [\n          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ceagles-smith@usgs.gov","orcid":"https://orcid.org/0000-0003-1329-5285","contributorId":505,"corporation":false,"usgs":true,"family":"Eagles-Smith","given":"Collin","email":"ceagles-smith@usgs.gov","middleInitial":"A.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":539729,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Browers, Howard","contributorId":139010,"corporation":false,"usgs":false,"family":"Browers","given":"Howard","email":"","affiliations":[],"preferred":false,"id":539730,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Cline, Chris","contributorId":139011,"corporation":false,"usgs":false,"family":"Cline","given":"Chris","email":"","affiliations":[],"preferred":false,"id":539731,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Vest, Josh","contributorId":24240,"corporation":false,"usgs":false,"family":"Vest","given":"Josh","affiliations":[],"preferred":false,"id":539732,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70139777,"text":"ofr20151017 - 2015 - A framework for modeling anthropogenic impacts on waterbird habitats: addressing future uncertainty in conservation planning","interactions":[],"lastModifiedDate":"2017-02-08T13:32:17","indexId":"ofr20151017","displayToPublicDate":"2015-02-02T14:30:00","publicationYear":"2015","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":"2015-1017","title":"A framework for modeling anthropogenic impacts on waterbird habitats: addressing future uncertainty in conservation planning","docAbstract":"<p><span>The amount and quality of natural resources available for terrestrial and aquatic wildlife habitats are expected to decrease throughout the world in areas that are intensively managed for urban and agricultural uses. Changes in climate and management of increasingly limited water supplies may further impact water resources essential for sustaining habitats. In this report, we document adapting a Water Evaluation and Planning (WEAP) system model for the Central Valley of California. We demonstrate using this adapted model (WEAP-CV</span><sub>wh</sub><span>) to evaluate impacts produced from plausible future scenarios on agricultural and wetland habitats used by waterbirds and other wildlife. Processed output from WEAP-CV</span><sub>wh</sub><span>&nbsp;indicated varying levels of impact caused by projected climate, urbanization, and water supply management in scenarios used to exemplify this approach. Among scenarios, the NCAR-CCSM3 A2 climate projection had a greater impact than the CNRM-CM3 B1 climate projection, whereas expansive urbanization had a greater impact than strategic urbanization, on annual availability of waterbird habitat. Scenarios including extensive rice-idling or substantial instream flow requirements on important water supply sources produced large impacts on annual availability of waterbird habitat. In the year corresponding with the greatest habitat reduction for each scenario, the scenario including instream flow requirements resulted in the greatest decrease in habitats throughout all months of the wintering period relative to other scenarios. This approach provides a new and useful tool for habitat conservation planning in the Central Valley and a model to guide similar research investigations aiming to inform conservation, management, and restoration of important wildlife habitats.</span></p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151017","collaboration":"Prepared in cooperation with the California Landscape Conservation Cooperative, California Department of Fish and Wildlife, and U.S. Fish and Wildlife Service","usgsCitation":"Matchett, E., Fleskes, J.P., Young, C., and Purkey, D.R., 2015, A framework for modeling anthropogenic impacts on waterbird habitats: addressing future uncertainty in conservation planning: U.S. Geological Survey Open-File Report 2015-1017, vi, 40 p., https://doi.org/10.3133/ofr20151017.","productDescription":"vi, 40 p.","numberOfPages":"50","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-053267","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":334995,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7H13050","text":"Data for projected impacts of climate, urbanization, water management, and wetland restoration on waterbird habitat in California’s Central Valley"},{"id":297683,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2015/1017/"},{"id":297684,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20151017.PNG"},{"id":297685,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1017/pdf/ofr2015-1017.pdf","text":"Report","size":"3.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"country":"United States","state":"California","otherGeospatial":"Central Valley","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -124.16748046874999,\n              34.59704151614417\n            ],\n            [\n              -124.16748046874999,\n              40.68063802521456\n            ],\n            [\n              -119.68505859375,\n              40.68063802521456\n            ],\n            [\n              -119.68505859375,\n              34.59704151614417\n            ],\n            [\n              -124.16748046874999,\n              34.59704151614417\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2a4ae4b08de9379b2fc4","contributors":{"authors":[{"text":"Matchett, Elliott 0000-0001-5095-2884 ematchett@usgs.gov","orcid":"https://orcid.org/0000-0001-5095-2884","contributorId":5541,"corporation":false,"usgs":true,"family":"Matchett","given":"Elliott","email":"ematchett@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":539694,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fleskes, Joseph P. 0000-0001-5388-6675 joe_fleskes@usgs.gov","orcid":"https://orcid.org/0000-0001-5388-6675","contributorId":1889,"corporation":false,"usgs":true,"family":"Fleskes","given":"Joseph","email":"joe_fleskes@usgs.gov","middleInitial":"P.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":539695,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Young, Charles A.","contributorId":139008,"corporation":false,"usgs":false,"family":"Young","given":"Charles A.","affiliations":[],"preferred":false,"id":539698,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Purkey, David R.","contributorId":139005,"corporation":false,"usgs":false,"family":"Purkey","given":"David","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":539696,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70123191,"text":"ds877 - 2015 - Wetland paleoecological study of southwest coastal Louisiana: sediment cores and diatom calibration dataset","interactions":[],"lastModifiedDate":"2015-02-02T12:50:59","indexId":"ds877","displayToPublicDate":"2015-02-02T12:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"877","title":"Wetland paleoecological study of southwest coastal Louisiana: sediment cores and diatom calibration dataset","docAbstract":"<p><span>Wetland sediment data were collected in 2009 and 2010 throughout the southwest Louisiana Chenier Plain as part of a pilot study to develop a diatom-based proxy for past wetland water chemistry and the identification of sediment deposits from tropical storms. The complete dataset includes forty-six surface sediment samples and nine sediment cores. The surface sediment samples were collected in fresh, intermediate, and brackish marsh and are located coincident with Coastwide Reference Monitoring System (CRMS) sites. The nine sediment cores were collected at the Rockefeller Wildlife Refuge (RWR) located in Grand Chenier, La.</span></p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds877","usgsCitation":"Smith, K.E., Flocks, J.G., Steyer, G.D., and Piazza, S.C., 2015, Wetland paleoecological study of southwest coastal Louisiana: sediment cores and diatom calibration dataset: U.S. Geological Survey Data Series 877, HTML Document, https://doi.org/10.3133/ds877.","productDescription":"HTML Document","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-052587","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":297680,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds877.PNG"},{"id":297678,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0877/"},{"id":297679,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0877/html/ds877_abstract.html","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"Report"}],"country":"United States","state":"Louisiana","city":"Grand Chenier","otherGeospatial":"Chenier Plain, Rockefeller Wildlife Refuge","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -93.85894775390625,\n              29.508939763268394\n            ],\n            [\n              -93.85894775390625,\n              30.071470887901302\n            ],\n            [\n              -91.96929931640624,\n              30.071470887901302\n            ],\n            [\n              -91.96929931640624,\n              29.508939763268394\n            ],\n            [\n              -93.85894775390625,\n              29.508939763268394\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2ad0e4b08de9379b321c","contributors":{"authors":[{"text":"Smith, Kathryn E. L. kelsmith@usgs.gov","contributorId":3242,"corporation":false,"usgs":true,"family":"Smith","given":"Kathryn","email":"kelsmith@usgs.gov","middleInitial":"E. L.","affiliations":[],"preferred":false,"id":519342,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Flocks, James G. 0000-0002-6177-7433 jflocks@usgs.gov","orcid":"https://orcid.org/0000-0002-6177-7433","contributorId":816,"corporation":false,"usgs":true,"family":"Flocks","given":"James","email":"jflocks@usgs.gov","middleInitial":"G.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":539675,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Steyer, Gregory D. 0000-0001-7231-0110 steyerg@usgs.gov","orcid":"https://orcid.org/0000-0001-7231-0110","contributorId":2856,"corporation":false,"usgs":true,"family":"Steyer","given":"Gregory","email":"steyerg@usgs.gov","middleInitial":"D.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":5062,"text":"Office of the Chief Scientist for Ecosystems","active":true,"usgs":true},{"id":5064,"text":"Southeast Regional Director's Office","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":539676,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Piazza, Sarai C. 0000-0001-6962-9008 piazzas@usgs.gov","orcid":"https://orcid.org/0000-0001-6962-9008","contributorId":466,"corporation":false,"usgs":true,"family":"Piazza","given":"Sarai","email":"piazzas@usgs.gov","middleInitial":"C.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":false,"id":539677,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70133604,"text":"ds901 - 2015 - Mount St. Helens: Controlled-source audio-frequency magnetotelluric (CSAMT) data and inversions","interactions":[],"lastModifiedDate":"2016-02-08T14:09:10","indexId":"ds901","displayToPublicDate":"2015-02-02T12:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"901","title":"Mount St. Helens: Controlled-source audio-frequency magnetotelluric (CSAMT) data and inversions","docAbstract":"<p>This report describes a series of geoelectrical soundings carried out on and near Mount St. Helens volcano, Washington, in 2010&ndash;2011. These soundings used a controlled-source audio-frequency magnetotelluric (CSAMT) approach (Zonge and Hughes, 1991; Simpson and Bahr, 2005). We chose CSAMT for logistical reasons: It can be deployed by helicopter, has an effective depth of penetration of as much as 1 kilometer, and requires less wire than a Schlumberger sounding.</p>\n<p>This Data Series provides the edited data for these CSAMT soundings as well as several different types of 1-D inversions (where the signal data are converted to conductivity-versus-depth models). In addition, we include a map showing station locations on and around the volcano and the Pumice Plain to the north.</p>\n<p>The apparent conductivity (or its inverse, apparent resistivity) measured by a geoelectrical system is caused by several factors. The most important of these are water-filled rock porosity and the presence of water-filled fractures; however, rock type and minerals (for instance, sulfides and clay content) also contribute to apparent conductivity. In situations with little recharge (for instance, in arid regions), variations in ionic content of water occupying pore space and fractures sampled by the measurement system must also be factored in (Wynn, 2006). Variations in ionic content may also be present in hydrothermal fluids surrounding volcanoes in wet regions. In unusual cases, temperature may also affect apparent conductivity (Keller, 1989; Palacky, 1989). There is relatively little hydrothermal alteration (and thus fewer clay minerals that might add to the apparent conductivity) in the eruptive products of Mount St. Helens (Reid and others, 2010), so conductors observed in the Fischer, Occam, and Marquardt inversion results later in this report are thus believed to map zones with significant water content. Geoelectrical surveys thus have the potential to reveal subsurface regions with significant groundwater content, including perched and regional aquifers. Reid and others (2001) and Reid (2004) have suggested that groundwater involvement may figure in both the scale and the character of some if not all volcanic edifice collapse events. Ongoing research by the U.S. Geological Survey (USGS) and others aims to better understand the contribution of groundwater to both edifice pore pressure and rock alteration as well as its direct influence on eruption processes by violent interaction with magma (Schmincke, 1998).</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds901","usgsCitation":"Wynn, J., and Pierce, H., 2015, Mount St. Helens: Controlled-source audio-frequency magnetotelluric (CSAMT) data and inversions: U.S. Geological Survey Data Series 901, HTML Document, https://doi.org/10.3133/ds901.","productDescription":"HTML Document","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-044700","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":297677,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds901.gif"},{"id":316600,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0901/ds901.pdf","text":"Report","size":"3.8 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":297676,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0901/cover.html","text":"Report","linkFileType":{"id":5,"text":"html"}}],"projection":"Universal Transverse Mercator projection, Zone 10N","datum":"World Geodetic System 1984","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              -122.28675842285158,\n              46.150107913663334\n            ],\n            [\n              -122.28675842285158,\n              46.27388525189855\n            ],\n            [\n              -122.09415435791016,\n              46.27388525189855\n            ],\n            [\n              -122.09415435791016,\n              46.150107913663334\n            ],\n            [\n              -122.28675842285158,\n              46.150107913663334\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2a9ce4b08de9379b3137","contributors":{"authors":[{"text":"Wynn, Jeff 0000-0002-8102-3882 jwynn@usgs.gov","orcid":"https://orcid.org/0000-0002-8102-3882","contributorId":2803,"corporation":false,"usgs":true,"family":"Wynn","given":"Jeff","email":"jwynn@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":539674,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pierce, Herbert A.","contributorId":83093,"corporation":false,"usgs":true,"family":"Pierce","given":"Herbert A.","affiliations":[],"preferred":false,"id":539673,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70148078,"text":"70148078 - 2015 - Mapping migratory flyways in Asia using dynamic Brownian bridge movement models","interactions":[],"lastModifiedDate":"2017-07-26T17:13:27","indexId":"70148078","displayToPublicDate":"2015-02-02T11:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2792,"text":"Movement Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Mapping migratory flyways in Asia using dynamic Brownian bridge movement models","docAbstract":"<p>Background</p>\n<p>Identifying movement routes and stopover sites is necessary for developing effective management and conservation strategies for migratory animals. In the case of migratory birds, a collection of migration routes, known as a flyway, is often hundreds to thousands of kilometers long and can extend across political boundaries. Flyways encompass the entire geographic range between the breeding and non-breeding areas of a population, species, or a group of species, and they provide spatial frameworks for management and conservation across international borders. Existing flyway maps are largely qualitative accounts based on band returns and survey data rather than observed movement routes. In this study, we use satellite and GPS telemetry data and dynamic Brownian bridge movement models to build upon existing maps and describe waterfowl space use probabilistically in the Central Asian and East Asian-Australasian Flyways.</p>\n<p>Results</p>\n<p>Our approach provided new information on migratory routes that was not easily attainable with existing methods to describe flyways. Utilization distributions from dynamic Brownian bridge movement models identified key staging and stopover sites, migration corridors and general flyway outlines in the Central Asian and East Asian-Australasian Flyways. A map of space use from ruddy shelducks depicted two separate movement corridors within the Central Asian Flyway, likely representing two distinct populations that show relatively strong connectivity between breeding and wintering areas. Bar-headed geese marked at seven locations in the Central Asian Flyway showed heaviest use at several stopover sites in the same general region of high-elevation lakes along the eastern Qinghai-Tibetan Plateau. Our analysis of data from multiple Anatidae species marked at sites throughout Asia highlighted major movement corridors across species and confirmed that the Central Asian and East Asian-Australasian Flyways were spatially distinct.</p>\n<p>Conclusions</p>\n<p>The dynamic Brownian bridge movement model improves our understanding of flyways by estimating relative use of regions in the flyway while providing detailed, quantitative information on migration timing and population connectivity including uncertainty between locations. This model effectively quantifies the relative importance of different migration corridors and stopover sites and may help prioritize specific areas in flyways for conservation of waterbird populations.</p>","language":"English","publisher":"Minerva Center for Movement Ecology","publisherLocation":"London","doi":"10.1186/s40462-015-0029-6","usgsCitation":"Palm, E., Newman, S.H., Prosser, D.J., Xiao, X., Luo, Z., Batbayar, N., Balachandran, S., and Takekawa, J.Y., 2015, Mapping migratory flyways in Asia using dynamic Brownian bridge movement models: Movement Ecology, v. 3, no. 1, p. 1-10, https://doi.org/10.1186/s40462-015-0029-6.","productDescription":"10 p.","startPage":"1","endPage":"10","numberOfPages":"10","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-062254","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":472293,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s40462-015-0029-6","text":"Publisher Index Page"},{"id":300545,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"3","issue":"1","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2015-02-02","publicationStatus":"PW","scienceBaseUri":"555c5eb6e4b0a92fa7eacc02","contributors":{"authors":[{"text":"Palm, E.C.","contributorId":40708,"corporation":false,"usgs":true,"family":"Palm","given":"E.C.","email":"","affiliations":[],"preferred":false,"id":547228,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Newman, S. H.","contributorId":21888,"corporation":false,"usgs":false,"family":"Newman","given":"S.","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":547229,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Prosser, Diann J. 0000-0002-5251-1799 dprosser@usgs.gov","orcid":"https://orcid.org/0000-0002-5251-1799","contributorId":2389,"corporation":false,"usgs":true,"family":"Prosser","given":"Diann","email":"dprosser@usgs.gov","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":547230,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Xiao, Xiangming","contributorId":67212,"corporation":false,"usgs":true,"family":"Xiao","given":"Xiangming","affiliations":[],"preferred":false,"id":547231,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Luo, Ze","contributorId":41307,"corporation":false,"usgs":true,"family":"Luo","given":"Ze","affiliations":[],"preferred":false,"id":547232,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Batbayar, Nyambayar","contributorId":40338,"corporation":false,"usgs":true,"family":"Batbayar","given":"Nyambayar","affiliations":[],"preferred":false,"id":547233,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Balachandran, Sivananinthaperumal","contributorId":20593,"corporation":false,"usgs":true,"family":"Balachandran","given":"Sivananinthaperumal","affiliations":[],"preferred":false,"id":547234,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Takekawa, John Y. 0000-0003-0217-5907 john_takekawa@usgs.gov","orcid":"https://orcid.org/0000-0003-0217-5907","contributorId":176168,"corporation":false,"usgs":true,"family":"Takekawa","given":"John","email":"john_takekawa@usgs.gov","middleInitial":"Y.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":547235,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70135892,"text":"sir20145232 - 2015 - Potentiometric surfaces and water-level trends in the Cockfield (upper Claiborne) aquifer in southern Arkansas and the Wilcox (lower Wilcox) aquifer of northeastern and southern Arkansas, 2012","interactions":[],"lastModifiedDate":"2015-04-20T14:25:03","indexId":"sir20145232","displayToPublicDate":"2015-02-02T09:00:00","publicationYear":"2015","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":"2014-5232","title":"Potentiometric surfaces and water-level trends in the Cockfield (upper Claiborne) aquifer in southern Arkansas and the Wilcox (lower Wilcox) aquifer of northeastern and southern Arkansas, 2012","docAbstract":"<p>The Cockfield aquifer, located in southern Arkansas, is composed of Eocene-age sand beds found near the base of the Cockfield Formation of Claiborne Group. The Wilcox aquifer, located in northeastern and southern Arkansas, is composed of Paleocene-age sand beds found in the middle to lower part of the Wilcox Group. The Cockfield and Wilcox aquifers are primary sources of groundwater. In 2010, withdrawals from the Cockfield aquifer in Arkansas totaled 19.2 million gallons per day (Mgal/d), and withdrawals from the Wilcox aquifer totaled 36.5 Mgal/d.</p>\n<p>A study was conducted by the U.S. Geological Survey in cooperation with the Arkansas Natural Resources Commission and the Arkansas Geological Survey to measure water levels associated with the Cockfield aquifer and the Wilcox aquifer in northeastern and southern Arkansas. Water levels were measured at 43 wells completed in the Cockfield aquifer and 47 wells completed in the Wilcox aquifer in February and March 2012. Measurements from 2012 are presented as potentiometric-surface maps and in combination with measurements from 2006 as water-level difference maps. Trends in water-level change over time within the Cockfield and Wilcox aquifers were determined using the water-level difference maps and selected well hydrographs.</p>\n<p>The Cockfield aquifer study area in southern Arkansas is bounded on the east by the Mississippi River and on the west by the area that contains outcrops and subcrops of the Cockfield Formation. The northern boundary of the Cockfield aquifer study area is defined by the area that contains observation wells completed in the Cockfield aquifer and the southern boundary is the Louisiana State line.</p>\n<p>The Wilcox aquifer study area in northeastern Arkansas is bounded on the east by the Mississippi River and on the north by the Missouri State line. The southern and western boundaries are defined by areas containing observation wells completed in the Wilcox aquifer or by outcrop areas on or near Crowleys Ridge. The Wilcox aquifer study area in southern Arkansas is defined by observation wells completed in the Wilcox aquifer or by areas that contain outcrops of the Wilcox Group, or both.</p>\n<p>The potentiometric-surface map of the Cockfield aquifer shows the regional direction of groundwater flow was generally toward the east-southeast, except in areas of intense groundwater withdrawals such as southwestern Ashley County, where groundwater flows toward the town of Crossett. The highest water-level altitude measured was 350 feet (ft) above National Geodetic Vertical Datum of 1929 (NGVD 29) in central Columbia County. The lowest water-level altitude measured was 40 ft above NGVD 29 in southeastern Lincoln County.</p>\n<p>The water-level difference map for the Cockfield aquifer in Arkansas was constructed using 42 water-level measurements made during 2006 and 2012. The difference in water levels for the Cockfield aquifer ranged from 27.4 ft to -10.4 ft. The largest water-level rise was in Calhoun County, and the largest water-level decline was 10.4 ft in Union County. Of the 42 wells, 13 wells had a rise in water level, and the remaining 29 wells had a decline in water level.</p>\n<p>Hydrographs for 32 wells in the Cockfield aquifer with historical water-level data were evaluated using linear regression to calculate the annual rise or decline for each well. These data were aggregated by county and statistically evaluated for the range, mean, and median of water-level change in each county. Hydrographs for Bradley, Calhoun, Chicot, Columbia, and Union Counties indicated both rising and declining water levels. The mean annual water-level rise or decline for Calhoun County was 0.00 foot per year (ft/yr) or unchanged. The mean annual water-level for Ashley, Bradley, Chicot, Cleveland, Columbia, Lincoln, and Union Counties show declines ranging from -0.02 to -1.10 ft/yr.</p>\n<p>Two potentiometric-surface maps, one for the southern area and one for the northeastern area, were constructed to show the altitude of the water surface in the Wilcox aquifer. The direction of groundwater flow in the northeastern area was generally towards the south-southwest except for some areas immediately adjacent to the Mississippi River where the flow was more eastward towards the river. The highest water-level altitude was 219 ft in northern Mississippi County, and the lowest water-level altitude was 123 ft near West Memphis in Crittenden County. The direction of groundwater flow in the northern part of the southern area was generally towards the southwest. The direction of groundwater flow in the southern part was in all directions because of two cones of depression and two water-level mounds. The highest water-level altitude measured was 394 ft at the center of a water-level mound in eastern Hot Spring County and a water-level mound in southwestern Hempstead County. The lowest water-level altitude measured was 145 ft at the center of the cone of depression in Clark County.</p>\n<p>Water-level difference maps for the Wilcox aquifer in Arkansas were constructed using 47 water-level measurements made during 2006 and 2012. The difference in water levels for the Wilcox aquifer in the northeastern area ranged from 22.0 ft to -17.9 ft. The largest rise in water level occurred in Crittenden County, and the largest decline occurred in Lee County. Twenty-one wells had rising water levels, and 10 wells had declining water levels. The difference in water levels for the Wilcox aquifer in the southern area ranged from 18.1 ft to -4.2 ft. The largest rise and the largest decline in water level occurred in Nevada County. Twelve wells had rising water levels, and 4 wells had declining water levels.</p>\n<p>Linear regression analysis of long-term hydrographs was used to determine the mean annual water-level rise and decline in the Wilcox aquifer in the northeastern and southern areas of Arkansas. In the northeastern area, the mean annual water level declined in all seven counties. The mean annual declines ranged from -0.55 ft/yr in Craighead County to -1.46 ft/yr in St. Francis County. In the southern area, the annual rise and decline calculations for wells with over 20 years of records indicate rising and declining water levels in Clark, Hot Spring, and Nevada Counties. The mean annual water level declined in all counties except Hot Spring County.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145232","collaboration":"Prepared in cooperation with the Arkansas Natural Resources Commission and the Arkansas Geological Survey","usgsCitation":"Rodgers, K.D., 2015, Potentiometric surfaces and water-level trends in the Cockfield (upper Claiborne) aquifer in southern Arkansas and the Wilcox (lower Wilcox) aquifer of northeastern and southern Arkansas, 2012: U.S. Geological Survey Scientific Investigations Report 2014-5232, v, 46 p., https://doi.org/10.3133/sir20145232.","productDescription":"v, 46 p.","numberOfPages":"55","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-056679","costCenters":[{"id":129,"text":"Arkansas Water Science 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Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":129,"text":"Arkansas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":536978,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70137956,"text":"ofr20151007 - 2015 - Geospatial datasets for assessing the effects of rangeland conditions on dissolved-solids yields in the Upper Colorado River Basin","interactions":[],"lastModifiedDate":"2016-04-12T17:29:26","indexId":"ofr20151007","displayToPublicDate":"2015-02-02T08:30:00","publicationYear":"2015","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":"2015-1007","title":"Geospatial datasets for assessing the effects of rangeland conditions on dissolved-solids yields in the Upper Colorado River Basin","docAbstract":"<p><span>In 2009, the U.S. Geological Survey (USGS) developed a Spatially Referenced Regressions on Watershed Attributes (SPARROW) surface-water quality model for the Upper Colorado River Basin (UCRB) relating dissolved-solids sources and transport in the 1991 water year to upstream catchment characteristics. The SPARROW model focused on geologic and agricultural sources of dissolved solids in the UCRB and was calibrated using water-year 1991 dissolved-solids loads from 218 monitoring sites. A new UCRB SPARROW model is planned that will update the investigation of dissolved-solids sources and transport in the basin to circa 2010 conditions and will improve upon the 2009 model by incorporating more detailed information about agricultural-irrigation and rangeland-management practices, among other improvements. Geospatial datasets relating to circa 2010 rangeland conditions are required for the new UCRB SPARROW modeling effort. This study compiled geospatial datasets for the UCRB that relate to the biotic alterations and rangeland conditions of grazing, fire and other land disturbance, and vegetation type and cover. Datasets representing abiotic alterations of access control (off-highway vehicles) and sediment generation and transport in general, were also compiled. These geospatial datasets may be tested in the upcoming SPARROW model to better understand the potential contribution of rangelands to dissolved-solids loading in UCRB streams.</span></p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151007","collaboration":"Prepared in cooperation with the U.S. Bureau of Reclamation","usgsCitation":"Tillman, F., Flynn, M., and Anning, D.W., 2015, Geospatial datasets for assessing the effects of rangeland conditions on dissolved-solids yields in the Upper Colorado River Basin: U.S. Geological Survey Open-File Report 2015-1007, Report: v, 21 p.; 6 Geospatial Datasets, https://doi.org/10.3133/ofr20151007.","productDescription":"Report: v, 21 p.; 6 Geospatial Datasets","numberOfPages":"32","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-060100","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":297671,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20151007.gif"},{"id":297670,"rank":9,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/of/2015/1007/downloads/datasets/UCRB_R-factor.zip","text":"Rainfall-Runoff Erosivity","size":"962 kB","description":"Geospatial dataset","linkHelpText":"This tabular dataset presents the 1971–2000 average annual rainfall-runoff erosivity factor (R-factor) for the UCRB. The R-factor is a measure of the cumulative erosive force of individual precipitation events (Daly and Taylor, 2002). All other factors being constant, sediment generation from precipitation is directly proportional to the product of the total kinetic energy of a storm and the storm’s maximum 30-minute intensity. The mean annual R-factor is a sum of this product for all storms in a year, averaged over all years of record (Daly and Taylor, 2002)."},{"id":297663,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2015/1007/"},{"id":297668,"rank":7,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/of/2015/1007/downloads/datasets/2010_UCRB_VegTypeCover.zip","text":"Existing Vegetation Type and Cover","size":"540 MB","description":"Geospatial dataset","linkHelpText":"These layers include information on the vegetation type and vegetation cover in 2010 in the UCRB. The 2010 existing vegetation cover (EVC) layer represents the vertically projected percent cover of the live canopy layer. The 2010 existing vegetation type (EVT) layer represents the species composition. Spatially, both grids cover the entire UCRB and have a 30-meter pixel resolution."},{"id":297664,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1007/downloads/OFR2015-1007.pdf","text":"Report","size":"5.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":297666,"rank":5,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/of/2015/1007/downloads/datasets/2010_UCRB_USFS_Grazing_projected.zip","text":"U.S. Forest Service Grazing","size":"3.8 MB","description":"Geospatial dataset","linkHelpText":"The shapefile contains 444 polygons of USFS grazing allotments within or bordering the UCRB (fig. 4). Attributes for the allotment polygons include the allotment name (RMU_NAME) and number (RMU_CN), the authorized number of animal unit months for the allotment (AUTH_AUMS), and the area of the allotment in both acres (AREA_acres) and square kilometers (AREA_km2). USFS-billed grazing is referred to as the \"authorized\" amount and is equivalent to BLM’s \"billed\" grazing (U.S. Government Accountability Office, 2005)."},{"id":297669,"rank":8,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/of/2015/1007/downloads/datasets/2010_UCRB_Roads.zip","text":"2010 Roads","size":"172 MB","description":"Geospatial dataset","linkHelpText":"This layer contains information about the location and type of roads in the UCRB in 2010. One value in the MAF/TIGER Feature Class Code (MTFCC) attribute field in the roads layer is S1500, named \"Vehicular Trail (4WD)\", and is described as \"an unpaved dirt trail where a four-wheel drive vehicle is required\" (table 5). The Vehicular Trail (4WD) attribute presents potential UCRB locations of off-highway vehicle use—an activity directly related to the \"access controls\" abiotic alteration in Weltz and others (2014) (table 5; fig. 7). The 2010 roads layer covers the entire UCRB."},{"id":297665,"rank":4,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/of/2015/1007/downloads/datasets/2010_UCRB_BLM_Grazing_projected.zip","text":"Bureau of Land Management Grazing","size":"12.9 MB","description":"Geospatial dataset","linkHelpText":"The shapefile contains 2,367 polygons of BLM grazing allotments within or bordering the UCRB (fig. 4). Attributes for the allotment polygons include the allotment name (ALLOT_NAME) and number (ST_ALLOT), the authorized number of \"animal unit months\" for the allotment (AUTH_AUMS), and the area of the allotment in both acres (AREA_acres) and square kilometers (AREA_km2)."},{"id":297667,"rank":6,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/of/2015/1007/downloads/datasets/1999-2010_UCRB_LandDisturbance.zip","text":"Land Disturbance","size":"26 MB","description":"Geospatial dataset","linkHelpText":"These layers include temporal and spatial information on disturbances to the landscape as a result of management activities or natural events. Two types of grids are presented: yearly disturbance grids for 1999–2010 and a composite grid of the yearly disturbance grids that summarizes vegetation disturbance for 1999–2010. Spatially, all grids cover the entire UCRB and have a 30-meter pixel resolution."}],"datum":"North American Datum of 1983","country":"United States","state":"Arizona, Colorado, New Mexico, Utah, Wyoming","otherGeospatial":"Upper Colorado River Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -111.69937133789062,\n              36.730079507078415\n            ],\n            [\n              -111.68083190917969,\n              36.730079507078415\n            ],\n            [\n              -111.64581298828125,\n              36.72677751526221\n            ],\n            [\n              -111.4068603515625,\n              36.67723060234619\n            ],\n            [\n              -111.181640625,\n              36.54936246839778\n            ],\n            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dwanning@usgs.gov","contributorId":432,"corporation":false,"usgs":true,"family":"Anning","given":"David","email":"dwanning@usgs.gov","middleInitial":"W.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":539658,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70168684,"text":"70168684 - 2015 - River mainstem thermal regimes influence population structuring within an Appalachian brook trout population","interactions":[],"lastModifiedDate":"2019-12-14T06:14:04","indexId":"70168684","displayToPublicDate":"2015-02-01T14:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1324,"text":"Conservation Genetics","active":true,"publicationSubtype":{"id":10}},"title":"River mainstem thermal regimes influence population structuring within an Appalachian brook trout population","docAbstract":"<p>Brook trout (<i>Salvelinus fontinalis</i>) often exist as highly differentiated populations, even at small spatial scales, due either to natural or anthropogenic sources of isolation and low rates of dispersal. In this study, we used molecular approaches to describe the unique population structure of brook trout inhabiting the Shavers Fork watershed, located in eastern West Virginia, and contrast it to nearby populations in tributaries of the upper Greenbrier River and North Fork South Branch Potomac Rivers. Bayesian and maximum likelihood clustering methods identified minimal population structuring among 14 collections of brook trout from throughout the mainstem and tributaries of Shavers Fork, highlighting the role of the cold-water mainstem for connectivity and high rates of effective migration among tributaries. In contrast, the Potomac and Greenbrier River collections displayed distinct levels of population differentiation among tributaries, presumably resulting from tributary isolation by warm-water mainstems. Our results highlight the importance of protecting and restoring cold-water mainstem habitats as part of region-wide brook trout conservation efforts. In addition, our results from Shavers Fork provide a contrast to previous genetic studies that characterize Appalachian brook trout as fragmented isolates rather than well-mixed populations. Additional study is needed to determine whether the existence of brook trout as genetically similar populations among tributaries is truly unique and whether connectivity among brook trout populations can potentially be restored within other central Appalachian watersheds.</p>","language":"English","publisher":"Springer","doi":"10.1007/s10592-014-0636-6","usgsCitation":"Aunins, A.W., Petty, J.T., King, T.L., Schilz, M., and Mazik, P.M., 2015, River mainstem thermal regimes influence population structuring within an Appalachian brook trout population: Conservation Genetics, v. 16, no. 1, p. 15-29, https://doi.org/10.1007/s10592-014-0636-6.","productDescription":"15 p.","startPage":"15","endPage":"29","numberOfPages":"15","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-052856","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":318369,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"West Virginia","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -80.079345703125,\n              38.09998264736481\n            ],\n            [\n              -79.420166015625,\n              38.03078569382294\n            ],\n            [\n              -78.299560546875,\n              39.308800296002914\n            ],\n            [\n              -78.760986328125,\n              39.470125122358176\n            ],\n            [\n              -79.1015625,\n              39.35978526869001\n            ],\n            [\n              -80.079345703125,\n              38.09998264736481\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"16","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2014-07-27","publicationStatus":"PW","scienceBaseUri":"56cee27be4b015c306ec5f01","contributors":{"authors":[{"text":"Aunins, Aaron W. 0000-0001-5240-1453 aaunins@usgs.gov","orcid":"https://orcid.org/0000-0001-5240-1453","contributorId":5863,"corporation":false,"usgs":true,"family":"Aunins","given":"Aaron","email":"aaunins@usgs.gov","middleInitial":"W.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":621314,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Petty, J. Todd","contributorId":166749,"corporation":false,"usgs":false,"family":"Petty","given":"J.","email":"","middleInitial":"Todd","affiliations":[{"id":24497,"text":"West Virginia University, Morgantown, WV","active":true,"usgs":false}],"preferred":false,"id":621315,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"King, Tim L. tlking@usgs.gov","contributorId":3520,"corporation":false,"usgs":true,"family":"King","given":"Tim","email":"tlking@usgs.gov","middleInitial":"L.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":621316,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schilz, Mariya","contributorId":167176,"corporation":false,"usgs":false,"family":"Schilz","given":"Mariya","email":"","affiliations":[],"preferred":false,"id":621317,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mazik, Patricia M. 0000-0002-8046-5929 pmazik@usgs.gov","orcid":"https://orcid.org/0000-0002-8046-5929","contributorId":2318,"corporation":false,"usgs":true,"family":"Mazik","given":"Patricia","email":"pmazik@usgs.gov","middleInitial":"M.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":621262,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70155258,"text":"70155258 - 2015 - A Bayesian kriging approach for blending satellite and ground precipitation observations","interactions":[],"lastModifiedDate":"2022-11-15T15:07:01.784075","indexId":"70155258","displayToPublicDate":"2015-02-01T13:00:00","publicationYear":"2015","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 Bayesian kriging approach for blending satellite and ground precipitation observations","docAbstract":"<p><span>Drought and flood management practices require accurate estimates of precipitation. Gauge observations, however, are often sparse in regions with complicated terrain, clustered in valleys, and of poor quality. Consequently, the spatial extent of wet events is poorly represented. Satellite-derived precipitation data are an attractive alternative, though they tend to underestimate the magnitude of wet events due to their dependency on retrieval algorithms and the indirect relationship between satellite infrared observations and precipitation intensities. Here we offer a Bayesian kriging approach for blending precipitation gauge data and the Climate Hazards Group Infrared Precipitation satellite-derived precipitation estimates for Central America, Colombia, and Venezuela. First, the gauge observations are modeled as a linear function of satellite-derived estimates and any number of other variables&mdash;for this research we include elevation. Prior distributions are defined for all model parameters and the posterior distributions are obtained simultaneously via Markov chain Monte Carlo sampling. The posterior distributions of these parameters are required for spatial estimation, and thus are obtained prior to implementing the spatial kriging model. This functional framework is applied to model parameters obtained by sampling from the posterior distributions, and the residuals of the linear model are subject to a spatial kriging model. Consequently, the posterior distributions and uncertainties of the blended precipitation estimates are obtained. We demonstrate this method by applying it to pentadal and monthly total precipitation fields during 2009. The model's performance and its inherent ability to capture wet events are investigated. We show that this blending method significantly improves upon the satellite-derived estimates and is also competitive in its ability to represent wet events. This procedure also provides a means to estimate a full conditional distribution of the &ldquo;true&rdquo; observed precipitation value at each grid cell.</span></p>","language":"English","publisher":"American Geophysical Union","publisherLocation":"Washington, D.C.","doi":"10.1002/2014WR015963","usgsCitation":"Verdin, A.P., Rajagopalan, B., Kleiber, W., and Funk, C.C., 2015, A Bayesian kriging approach for blending satellite and ground precipitation observations: Water Resources Research, v. 51, no. 2, p. 908-921, https://doi.org/10.1002/2014WR015963.","productDescription":"14 p.","startPage":"908","endPage":"921","numberOfPages":"14","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059780","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":472294,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2014wr015963","text":"Publisher Index 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Boulder","active":true,"usgs":false}],"preferred":false,"id":565398,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kleiber, William","contributorId":145814,"corporation":false,"usgs":false,"family":"Kleiber","given":"William","email":"","affiliations":[{"id":16240,"text":"U of Colorado, Boulder","active":true,"usgs":false}],"preferred":false,"id":565399,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Funk, Christopher C. 0000-0002-9254-6718 cfunk@usgs.gov","orcid":"https://orcid.org/0000-0002-9254-6718","contributorId":721,"corporation":false,"usgs":true,"family":"Funk","given":"Christopher","email":"cfunk@usgs.gov","middleInitial":"C.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":565396,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70155259,"text":"70155259 - 2015 - Calculating crop water requirement satisfaction in the West Africa Sahel with remotely sensed soil moisture","interactions":[],"lastModifiedDate":"2017-01-18T10:06:09","indexId":"70155259","displayToPublicDate":"2015-02-01T13:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2344,"text":"Journal of Hydrometeorology","active":true,"publicationSubtype":{"id":10}},"title":"Calculating crop water requirement satisfaction in the West Africa Sahel with remotely sensed soil moisture","docAbstract":"<p><span>The Soil Moisture Active Passive (SMAP) mission will provide soil moisture data with unprecedented accuracy, resolution, and coverage, enabling models to better track agricultural drought and estimate yields. In turn, this information can be used to shape policy related to food and water from commodity markets to humanitarian relief efforts. New data alone, however, do not translate to improvements in drought and yield forecasts. New tools will be needed to transform SMAP data into agriculturally meaningful products. The objective of this study is to evaluate the possibility and efficiency of replacing the rainfall-derived soil moisture component of a crop water stress index with SMAP data. The approach is demonstrated with 0.1&deg;-resolution, ~10-day microwave soil moisture from the European Space Agency and simulated soil moisture from the Famine Early Warning Systems Network Land Data Assimilation System. Over a West Africa domain, the approach is evaluated by comparing the different soil moisture estimates and their resulting Water Requirement Satisfaction Index values from 2000 to 2010. This study highlights how the ensemble of indices performs during wet versus dry years, over different land-cover types, and the correlation with national-level millet yields. The new approach is a feasible and useful way to quantitatively assess how satellite-derived rainfall and soil moisture track agricultural water deficits. Given the importance of soil moisture in many applications, ranging from agriculture to public health to fire, this study should inspire other modeling communities to reformulate existing tools to take advantage of SMAP data.</span></p>","language":"English","publisher":"American Meteorological Society","publisherLocation":"Boston, MA","doi":"10.1175/JHM-D-14-0049.1","collaboration":"Amy McNally; Gregory J. Husak; Molly Brown; Mark Carroll; Chris Funk; Joel Michaelsen; Soni Yatheendradas; Kristi Arsenault, Christa Peters-Lidard; James P. Verdin","usgsCitation":"McNally, A., Gregory J. Husak, Brown, M., Carroll, M.L., Funk, C.C., Soni Yatheendradas, Arsenault, K., Christa Peters-Lidard, and Verdin, J., 2015, Calculating crop water requirement satisfaction in the West Africa Sahel with remotely sensed soil moisture: Journal of Hydrometeorology, v. 16, no. 1, p. 295-305, https://doi.org/10.1175/JHM-D-14-0049.1.","productDescription":"11 p.","startPage":"295","endPage":"305","numberOfPages":"11","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-055181","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":472295,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1175/jhm-d-14-0049.1","text":"Publisher Index Page"},{"id":306506,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"16","issue":"1","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2015-02-04","publicationStatus":"PW","scienceBaseUri":"57f7ef86e4b0bc0bec09f1a4","contributors":{"authors":[{"text":"McNally, Amy","contributorId":145810,"corporation":false,"usgs":false,"family":"McNally","given":"Amy","email":"","affiliations":[{"id":16236,"text":"UCSB Climate Hazards Group","active":true,"usgs":false}],"preferred":false,"id":565400,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gregory J. Husak","contributorId":145824,"corporation":false,"usgs":false,"family":"Gregory J. Husak","affiliations":[{"id":16245,"text":"Department of Geography and Climate Hazards Group, University of California, Santa Barbara, CA, USA","active":true,"usgs":false}],"preferred":false,"id":565401,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brown, Molly","contributorId":145825,"corporation":false,"usgs":false,"family":"Brown","given":"Molly","affiliations":[{"id":16246,"text":"Biospheric Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD, USA","active":true,"usgs":false}],"preferred":false,"id":565402,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Carroll, Mark L.","contributorId":145826,"corporation":false,"usgs":false,"family":"Carroll","given":"Mark","email":"","middleInitial":"L.","affiliations":[{"id":7239,"text":"Science Systems and Applications, Inc.","active":true,"usgs":false},{"id":16247,"text":"Sigma Space Corp, NASA Goddard Space Flight Center, Greenbelt, MD, USA","active":true,"usgs":false},{"id":16246,"text":"Biospheric Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD, USA","active":true,"usgs":false}],"preferred":false,"id":565403,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Funk, Christopher C. 0000-0002-9254-6718 cfunk@usgs.gov","orcid":"https://orcid.org/0000-0002-9254-6718","contributorId":721,"corporation":false,"usgs":true,"family":"Funk","given":"Christopher","email":"cfunk@usgs.gov","middleInitial":"C.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":565404,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Soni Yatheendradas","contributorId":145828,"corporation":false,"usgs":false,"family":"Soni Yatheendradas","affiliations":[{"id":16248,"text":"Hydrologic Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD, USA","active":true,"usgs":false}],"preferred":false,"id":565406,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Arsenault, Kristi","contributorId":145829,"corporation":false,"usgs":false,"family":"Arsenault","given":"Kristi","email":"","affiliations":[{"id":16248,"text":"Hydrologic Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD, USA","active":true,"usgs":false}],"preferred":false,"id":565407,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Christa Peters-Lidard","contributorId":116524,"corporation":false,"usgs":true,"family":"Christa Peters-Lidard","affiliations":[],"preferred":false,"id":565408,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Verdin, James 0000-0003-0238-9657 verdin@usgs.gov","orcid":"https://orcid.org/0000-0003-0238-9657","contributorId":145830,"corporation":false,"usgs":true,"family":"Verdin","given":"James","email":"verdin@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":565409,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70155262,"text":"70155262 - 2015 - The forcing of southwestern Asia teleconnections by low-frequency sea surface temperature variability during boreal winter","interactions":[],"lastModifiedDate":"2017-01-18T10:06:49","indexId":"70155262","displayToPublicDate":"2015-02-01T12:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2216,"text":"Journal of Climate","active":true,"publicationSubtype":{"id":10}},"title":"The forcing of southwestern Asia teleconnections by low-frequency sea surface temperature variability during boreal winter","docAbstract":"<p><span>Southwestern Asia, defined here as the domain bounded by 20&deg;&ndash;40&deg;N and 40&deg;&ndash;70&deg;E, which includes the nations of Iraq, Iran, Afghanistan, and Pakistan, is a water-stressed and semiarid region that receives roughly 75% of its annual rainfall during November&ndash;April. The November&ndash;April climate of southwestern Asia is strongly influenced by tropical Indo-Pacific variability on intraseasonal and interannual time scales, much of which can be attributed to sea surface temperature (SST) variations. The influences of lower-frequency SST variability on southwestern Asia climate during November&ndash;April Pacific decadal SST (PDSST) variability and the long-term trend in SST (LTSST) is examined. The U.S. Climate Variability and Predictability Program (CLIVAR) Drought Working Group forced global atmospheric climate models with PDSST and LTSST patterns, identified using empirical orthogonal functions, to show the steady atmospheric response to these modes of decadal to multidecadal SST variability. During November&ndash;April, LTSST forces an anticyclone over southwestern Asia, which results in reduced precipitation and increases in surface temperature. The precipitation and tropospheric circulation influences of LTSST are corroborated by independent observed precipitation and circulation datasets during 1901&ndash;2004. The decadal variations of southwestern Asia precipitation may be forced by PDSST variability, with two of the three models indicating that the cold phase of PDSST forces an anticyclone and precipitation reductions. However, there are intermodel circulation variations to PDSST that influence subregional precipitation patterns over the Middle East, southwestern Asia, and subtropical Asia. Changes in wintertime temperature and precipitation over southwestern Asia forced by LTSST and PDSST imply important changes to the land surface hydrology during the spring and summer.</span></p>","language":"English","publisher":"American Meteorological Society","publisherLocation":"Boston, MA","doi":"10.1175/JCLI-D-14-00344.1","usgsCitation":"Hoell, A., Funk, C.C., and Barlow, M., 2015, The forcing of southwestern Asia teleconnections by low-frequency sea surface temperature variability during boreal winter: Journal of Climate, v. 28, no. 4, p. 1511-1526, https://doi.org/10.1175/JCLI-D-14-00344.1.","productDescription":"16 p.","startPage":"1511","endPage":"1526","numberOfPages":"16","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-058649","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":472296,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1175/jcli-d-14-00344.1","text":"Publisher Index Page"},{"id":306490,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"28","issue":"4","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2015-02-11","publicationStatus":"PW","scienceBaseUri":"57f7ef86e4b0bc0bec09f1a6","contributors":{"authors":[{"text":"Hoell, Andrew","contributorId":145805,"corporation":false,"usgs":false,"family":"Hoell","given":"Andrew","affiliations":[{"id":16236,"text":"UCSB Climate Hazards Group","active":true,"usgs":false}],"preferred":false,"id":565418,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Funk, Christopher C. 0000-0002-9254-6718 cfunk@usgs.gov","orcid":"https://orcid.org/0000-0002-9254-6718","contributorId":721,"corporation":false,"usgs":true,"family":"Funk","given":"Christopher","email":"cfunk@usgs.gov","middleInitial":"C.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":565417,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barlow, Mathew","contributorId":145832,"corporation":false,"usgs":false,"family":"Barlow","given":"Mathew","email":"","affiliations":[{"id":16249,"text":"UMASS Lowel","active":true,"usgs":false}],"preferred":false,"id":565419,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70148672,"text":"70148672 - 2015 - Sources of endocrine-disrupting compounds in North Carolina waterways: a geographic information systems approach","interactions":[],"lastModifiedDate":"2015-06-19T10:52:23","indexId":"70148672","displayToPublicDate":"2015-02-01T12:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1571,"text":"Environmental Toxicology and Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Sources of endocrine-disrupting compounds in North Carolina waterways: a geographic information systems approach","docAbstract":"<p>The presence of endocrine-disrupting compounds (EDCs), particularly estrogenic compounds, in the environment has drawn public attention across the globe, yet a clear understanding of the extent and distribution of estrogenic EDCs in surface waters and their relationship to potential sources is lacking. The objective of the present study was to identify and examine the potential input of estrogenic EDC sources in North Carolina water bodies using a geographic information system (GIS) mapping and analysis approach. Existing data from state and federal agencies were used to create point and nonpoint source maps depicting the cumulative contribution of potential sources of estrogenic EDCs to North Carolina surface waters. Water was collected from 33 sites (12 associated with potential point sources, 12 associated with potential nonpoint sources, and 9 reference), to validate the predictive results of the GIS analysis. Estrogenicity (measured as 17&beta;-estradiol equivalence) ranged from 0.06 ng/L to 56.9 ng/L. However, the majority of sites (88%) had water 17&beta;-estradiol concentrations below 1 ng/L. Sites associated with point and nonpoint sources had significantly higher 17&beta;-estradiol levels than reference sites. The results suggested that water 17&beta;-estradiol was reflective of GIS predictions, confirming the relevance of landscape-level influences on water quality and validating the GIS approach to characterize such relationships.</p>","language":"English","publisher":"Elsevier Science","publisherLocation":"Amsterdam","doi":"10.1002/etc.2797","collaboration":"North Carolina Wildlife Resources Commission (NCWRC); North Carolina State University; US Geological Survey; US Fish and Wildlife Service; Wildlife Management Institute","usgsCitation":"Sackett, D.K., Pow, C.L., Rubino, M.J., Aday, D., Cope, W., Kullman, S.W., Rice, J., Kwak, T.J., and Law, L.M., 2015, Sources of endocrine-disrupting compounds in North Carolina waterways: a geographic information systems approach: Environmental Toxicology and Chemistry, v. 34, no. 2, p. 437-445, https://doi.org/10.1002/etc.2797.","productDescription":"9 p.","startPage":"437","endPage":"445","numberOfPages":"9","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-055607","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":301357,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"34","issue":"2","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2014-11-05","publicationStatus":"PW","scienceBaseUri":"55853d5be4b023124e8f5b47","contributors":{"authors":[{"text":"Sackett, Dana K.","contributorId":141232,"corporation":false,"usgs":false,"family":"Sackett","given":"Dana","email":"","middleInitial":"K.","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":549008,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pow, Crystal Lee","contributorId":141233,"corporation":false,"usgs":false,"family":"Pow","given":"Crystal","email":"","middleInitial":"Lee","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":549009,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rubino, Matthew J. 0000-0003-0651-3053","orcid":"https://orcid.org/0000-0003-0651-3053","contributorId":141234,"corporation":false,"usgs":false,"family":"Rubino","given":"Matthew","email":"","middleInitial":"J.","affiliations":[{"id":39327,"text":"North Carolina Cooperative Fish and Wildlife Research Unit, Department of Applied Ecology, North Carolina State Univ.","active":true,"usgs":false}],"preferred":false,"id":549010,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Aday, D.D.","contributorId":75356,"corporation":false,"usgs":true,"family":"Aday","given":"D.D.","email":"","affiliations":[],"preferred":false,"id":549011,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cope, W. Gregory","contributorId":70353,"corporation":false,"usgs":true,"family":"Cope","given":"W. Gregory","affiliations":[],"preferred":false,"id":549012,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kullman, Seth W.","contributorId":62516,"corporation":false,"usgs":true,"family":"Kullman","given":"Seth","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":549013,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rice, J. A.","contributorId":101217,"corporation":false,"usgs":true,"family":"Rice","given":"J.","middleInitial":"A.","affiliations":[],"preferred":false,"id":549014,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kwak, Thomas J. 0000-0002-0616-137X tkwak@usgs.gov","orcid":"https://orcid.org/0000-0002-0616-137X","contributorId":834,"corporation":false,"usgs":true,"family":"Kwak","given":"Thomas","email":"tkwak@usgs.gov","middleInitial":"J.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":549015,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Law, LeRoy M.","contributorId":104603,"corporation":false,"usgs":true,"family":"Law","given":"LeRoy","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":549016,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70164451,"text":"70164451 - 2015 - Seasonal patterns in stream periphyton fatty acids and community benthic algal composition in six high quality headwater streams","interactions":[],"lastModifiedDate":"2017-07-21T14:54:16","indexId":"70164451","displayToPublicDate":"2015-02-01T11:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1919,"text":"Hydrobiologia","onlineIssn":"1573-5117","printIssn":"0018-8158","active":true,"publicationSubtype":{"id":10}},"title":"Seasonal patterns in stream periphyton fatty acids and community benthic algal composition in six high quality headwater streams","docAbstract":"<p>Fatty acids are integral components of periphyton and differ among algal taxa. We examined seasonal patterns in periphyton fatty acids in six minimally disturbed headwater streams in Pennsylvania&rsquo;s Appalachian Mountains, USA. Environmental data and periphyton were collected across four seasons for fatty acid and algal taxa content. Non-metric multidimensional scaling ordination suggested significant seasonal differences in fatty acids; an ordination on algal composition revealed similar seasonal patterns, but with slightly weaker separation of summer and fall. Summer and fall fatty acid profiles were driven by temperature, overstory cover, and conductivity and winter profiles by measures of stream size. Ordination on algal composition suggested that summer and fall communities were driven by overstory and temperature, whereas winter communities were driven by velocity. The physiologically important fatty acid 18:3&omega;6 was highest in summer and fall. Winter samples had the highest 20:3&omega;3. Six saturated fatty acids differed among the seasons. Periphyton fatty acids profiles appeared to reflect benthic algal species composition. This suggests that periphyton fatty acid composition can be useful in characterizing basal food resources and stream water quality.</p>","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Hydrobiologia","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Kluwer","publisherLocation":"Dordrecht","doi":"10.1007/s10750-014-2054-7","usgsCitation":"Honeyfield, D.C., and Maloney, K.O., 2015, Seasonal patterns in stream periphyton fatty acids and community benthic algal composition in six high quality headwater streams: Hydrobiologia, v. 744, no. 1, p. 35-47, https://doi.org/10.1007/s10750-014-2054-7.","productDescription":"13 p.","startPage":"35","endPage":"47","numberOfPages":"13","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-051650","costCenters":[{"id":199,"text":"Coop Res Unit 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kmaloney@usgs.gov","orcid":"https://orcid.org/0000-0003-2304-0745","contributorId":4636,"corporation":false,"usgs":true,"family":"Maloney","given":"Kelly","email":"kmaloney@usgs.gov","middleInitial":"O.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":597440,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70156795,"text":"70156795 - 2015 - An early to mid-Pleistocene deep Arctic Ocean ostracode fauna with North Atlantic affinities","interactions":[],"lastModifiedDate":"2018-02-08T12:49:20","indexId":"70156795","displayToPublicDate":"2015-02-01T11:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2996,"text":"Palaeogeography, Palaeoclimatology, Palaeoecology","printIssn":"0031-0182","active":true,"publicationSubtype":{"id":10}},"title":"An early to mid-Pleistocene deep Arctic Ocean ostracode fauna with North Atlantic affinities","docAbstract":"<p><span>An early to middle Pleistocene ostracode fauna was discovered in sediment core P1-93-AR-23 (P23, 76.95&deg;N, 155.07&deg;W) from 951&nbsp;meter water depth from the Northwind Ridge, western Arctic Ocean. Piston core P23 yielded more than 30,000 specimens and a total of about 30 species. Several early to mid-Pleistocene species in the genera&nbsp;</span><i>Krithe</i><span>,</span><i>Echinocythereis</i><span>,&nbsp;</span><i>Pterygocythereis</i><span>, and&nbsp;</span><i>Arcacythere</i><span>&nbsp;are now extinct in the Arctic and show taxonomic affinities to North Atlantic Ocean species. Our results suggest that there was a major ostracode faunal turnover during the global climate transitions known as the Mid-Pleistocene Transition (MPT, ~&nbsp;1.2 to 0.7&nbsp;Ma) and the Mid-Brunhes Event (MBE, ~&nbsp;400&nbsp;ka) reflecting the development of perennial sea ice during interglacial periods and large ice shelves during glacial periods over the last 400,000&nbsp;years.</span></p>","language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam","doi":"10.1016/j.palaeo.2014.07.026","usgsCitation":"DeNinno, L.H., Cronin, T.M., Rodriquez-Lazaro, J., and Brenner, A.R., 2015, An early to mid-Pleistocene deep Arctic Ocean ostracode fauna with North Atlantic affinities: Palaeogeography, Palaeoclimatology, Palaeoecology, v. 419, p. 90-99, https://doi.org/10.1016/j.palaeo.2014.07.026.","productDescription":"10 p.","startPage":"90","endPage":"99","numberOfPages":"10","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057946","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":307825,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"419","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55e81daae4b0dacf699e6650","chorus":{"doi":"10.1016/j.palaeo.2014.07.026","url":"http://dx.doi.org/10.1016/j.palaeo.2014.07.026","publisher":"Elsevier BV","authors":"DeNinno L.H., Cronin T.M., Rodriguez-Lazaro J., Brenner A.","journalName":"Palaeogeography, Palaeoclimatology, Palaeoecology","publicationDate":"2/2015","auditedOn":"11/1/2014"},"contributors":{"authors":[{"text":"DeNinno, Lauren H. ldeninno@usgs.gov","contributorId":5312,"corporation":false,"usgs":true,"family":"DeNinno","given":"Lauren","email":"ldeninno@usgs.gov","middleInitial":"H.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":570572,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cronin, Thomas M. 0000-0002-2643-0979 tcronin@usgs.gov","orcid":"https://orcid.org/0000-0002-2643-0979","contributorId":2579,"corporation":false,"usgs":true,"family":"Cronin","given":"Thomas","email":"tcronin@usgs.gov","middleInitial":"M.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":570573,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rodriquez-Lazaro, J.","contributorId":147163,"corporation":false,"usgs":false,"family":"Rodriquez-Lazaro","given":"J.","email":"","affiliations":[{"id":16801,"text":"Universidad Pais Vasco","active":true,"usgs":false}],"preferred":false,"id":570574,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brenner, Alec R. abrenner@usgs.gov","contributorId":5315,"corporation":false,"usgs":true,"family":"Brenner","given":"Alec","email":"abrenner@usgs.gov","middleInitial":"R.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":570575,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70141757,"text":"70141757 - 2015 - Influence of hardness on the bioavailability of silver to a freshwater snail after waterborne exposure to silver nitrate and silver nanoparticles","interactions":[],"lastModifiedDate":"2018-09-04T16:26:28","indexId":"70141757","displayToPublicDate":"2015-02-01T11:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2809,"text":"Nanotoxicology","active":true,"publicationSubtype":{"id":10}},"title":"Influence of hardness on the bioavailability of silver to a freshwater snail after waterborne exposure to silver nitrate and silver nanoparticles","docAbstract":"<p>The release of Ag nanoparticles (AgNPs) into the aquatic environment is likely, but the influence of water chemistry on their impacts and fate remains unclear. Here, we characterize the bioavailability of Ag from AgNO<sub>3</sub> and from AgNPs capped with polyvinylpyrrolidone (PVP AgNP) and thiolated polyethylene glycol (PEG AgNP) in the freshwater snail, <i>Lymnaea stagnalis</i>, after short waterborne exposures. Results showed that water hardness, AgNP capping agents, and metal speciation affected the uptake rate of Ag from AgNPs. Comparison of the results from organisms of similar weight showed that water hardness affected the uptake of Ag from AgNPs, but not that from AgNO<sub>3</sub>. Transformation (dissolution and aggregation) of the AgNPs was also influenced by water hardness and the capping agent. Bioavailability of Ag from AgNPs was, in turn, correlated to these physical changes. Water hardness increased the aggregation of AgNPs, especially for PEG AgNPs, reducing the bioavailability of Ag from PEG AgNPs to a greater degree than from PVP AgNPs. Higher dissolved Ag concentrations were measured for the PVP AgNPs (15%) compared to PEG AgNPs (3%) in moderately hard water, enhancing Ag bioavailability of the former. Multiple drivers of bioavailability yielded differences in Ag influx between very hard and deionized water where the uptake rate constants (<i>k</i><sub>uw</sub>, l g<sup>-1</sup> d<sup>-1</sup> &plusmn; SE) varied from 3.1&thinsp;&plusmn;&thinsp;0.7 to 0.2&thinsp;&plusmn;&thinsp;0.01 for PEG AgNPs and from 2.3&thinsp;&plusmn;&thinsp;0.02 to 1.3&thinsp;&plusmn;&thinsp;0.01 for PVP AgNPs. Modeling bioavailability of Ag from NPs revealed that Ag influx into&nbsp;<i>L. stagnalis</i><span>&nbsp;comprised uptake from the NPs themselves and from newly dissolved Ag.</span><span><br /></span></p>","language":"English","publisher":"Informa Healthcare","publisherLocation":"London","doi":"10.3109/17435390.2014.991772","usgsCitation":"Stoiber, T., Croteau, M.N., Romer, I., Tejamaya, M., Lead, J.R., and Luoma, S.N., 2015, Influence of hardness on the bioavailability of silver to a freshwater snail after waterborne exposure to silver nitrate and silver nanoparticles: Nanotoxicology, v. 9, no. 7, p. 918-927, https://doi.org/10.3109/17435390.2014.991772.","productDescription":"10 p.","startPage":"918","endPage":"927","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-055265","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":472297,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"text":"External Repository"},{"id":298123,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","issue":"7","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-09-10","publicationStatus":"PW","scienceBaseUri":"54edaebee4b02d776a6849ad","contributors":{"authors":[{"text":"Stoiber, Tasha L.","contributorId":91402,"corporation":false,"usgs":false,"family":"Stoiber","given":"Tasha L.","affiliations":[],"preferred":false,"id":541043,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Croteau, Marie Noele 0000-0003-0346-3580 mcroteau@usgs.gov","orcid":"https://orcid.org/0000-0003-0346-3580","contributorId":895,"corporation":false,"usgs":true,"family":"Croteau","given":"Marie","email":"mcroteau@usgs.gov","middleInitial":"Noele","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":541042,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Romer, Isabella","contributorId":139390,"corporation":false,"usgs":false,"family":"Romer","given":"Isabella","email":"","affiliations":[{"id":7157,"text":"University of Birmingham","active":true,"usgs":false}],"preferred":false,"id":541044,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tejamaya, Mila","contributorId":93375,"corporation":false,"usgs":false,"family":"Tejamaya","given":"Mila","email":"","affiliations":[],"preferred":false,"id":541045,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lead, Jamie R.","contributorId":41331,"corporation":false,"usgs":false,"family":"Lead","given":"Jamie","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":541046,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Luoma, Samuel N. 0000-0001-5443-5091 snluoma@usgs.gov","orcid":"https://orcid.org/0000-0001-5443-5091","contributorId":2287,"corporation":false,"usgs":true,"family":"Luoma","given":"Samuel","email":"snluoma@usgs.gov","middleInitial":"N.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":541047,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70141763,"text":"70141763 - 2015 - Ephemeral stream reaches preserve the evolutionary and distributional history of threespine stickleback in the Santa Clara and Ventura River watersheds of southern California","interactions":[],"lastModifiedDate":"2015-02-23T09:32:27","indexId":"70141763","displayToPublicDate":"2015-02-01T10:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1324,"text":"Conservation Genetics","active":true,"publicationSubtype":{"id":10}},"title":"Ephemeral stream reaches preserve the evolutionary and distributional history of threespine stickleback in the Santa Clara and Ventura River watersheds of southern California","docAbstract":"<p>Much remains to be understood about the evolutionary history and contemporary landscape genetics of unarmored threespine stickleback in southern California, where populations collectively referred to as <i>Gasterosteus aculeatus williamsoni</i> have severely declined over the past 70+ years and are now endangered. We used mitochondrial sequence and microsatellite data to assess the population genetics and phylogeography of unarmored populations sampled immediately downstream from the type locality of <i>G. a. williamsoni</i> in the upper Santa Clara River, and assessed their distinctiveness with respect to low-armor populations in the downstream sections of the river and the adjacent Ventura River. We also characterized the geographic limits of different plate morphs and evaluated the congruence of those boundaries with barriers to dispersal in both river systems and to neutral genetic variation. We show substantial population structuring within the upper reach of the Santa Clara River, but little partitioning between the lower Santa Clara and Ventura Rivers&mdash;we attribute these patterns to different ancestry between spatially subdivided populations within the same drainage, a predominance of downstream gene flow, and ability for coastal dispersal between the Santa Clara and Ventura Rivers. We also show that alleles from introduced low-plate stock have infiltrated a native population in at least one upper Santa Clara River tributary, causing this formerly unarmored population to become gradually low-plated over a 30 + year time period. Measures of genetic diversity, census surveys, and severe habitat disturbance all indicate that unarmored stickleback near the type locality are currently at high risk of extinction.</p>","language":"English","publisher":"Kluwer Academic Publishers","publisherLocation":"Dordrecht","doi":"10.1007/s10592-014-0643-7","usgsCitation":"Richmond, J.Q., Jacobs, D.K., Backlin, A.R., Swift, C.C., Dellith, C., and Fisher, R.N., 2015, Ephemeral stream reaches preserve the evolutionary and distributional history of threespine stickleback in the Santa Clara and Ventura River watersheds of southern California: Conservation Genetics, v. 16, no. 1, p. 85-101, https://doi.org/10.1007/s10592-014-0643-7.","productDescription":"17 p.","startPage":"85","endPage":"101","numberOfPages":"17","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-058303","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":298096,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"Santa Clara","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.02308654785156,\n              37.21392518793643\n            ],\n            [\n              -122.02308654785156,\n              37.41107339721063\n            ],\n            [\n              -121.85142517089844,\n              37.41107339721063\n            ],\n            [\n              -121.85142517089844,\n              37.21392518793643\n            ],\n            [\n              -122.02308654785156,\n              37.21392518793643\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"16","issue":"1","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2014-08-08","publicationStatus":"PW","scienceBaseUri":"54ec5d41e4b02d776a67daa7","contributors":{"authors":[{"text":"Richmond, Jonathan Q. 0000-0001-9398-4894 jrichmond@usgs.gov","orcid":"https://orcid.org/0000-0001-9398-4894","contributorId":5400,"corporation":false,"usgs":true,"family":"Richmond","given":"Jonathan","email":"jrichmond@usgs.gov","middleInitial":"Q.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":541025,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jacobs, David K.","contributorId":139394,"corporation":false,"usgs":false,"family":"Jacobs","given":"David","email":"","middleInitial":"K.","affiliations":[{"id":12763,"text":"University of California, Los Angeles","active":true,"usgs":false}],"preferred":false,"id":541026,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Backlin, Adam R. 0000-0001-5618-8426 abacklin@usgs.gov","orcid":"https://orcid.org/0000-0001-5618-8426","contributorId":3802,"corporation":false,"usgs":true,"family":"Backlin","given":"Adam","email":"abacklin@usgs.gov","middleInitial":"R.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":541027,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Swift, Camm C.","contributorId":139395,"corporation":false,"usgs":false,"family":"Swift","given":"Camm","email":"","middleInitial":"C.","affiliations":[{"id":12725,"text":"Natural History Museum of Los Angeles County","active":true,"usgs":false}],"preferred":false,"id":541028,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dellith, Chris","contributorId":139396,"corporation":false,"usgs":false,"family":"Dellith","given":"Chris","email":"","affiliations":[{"id":6678,"text":"U.S. Fish and Wildlife Service, Alaska Maritime National Wildlife Refuge","active":true,"usgs":false}],"preferred":false,"id":541029,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fisher, Robert N. 0000-0002-2956-3240 rfisher@usgs.gov","orcid":"https://orcid.org/0000-0002-2956-3240","contributorId":1529,"corporation":false,"usgs":true,"family":"Fisher","given":"Robert","email":"rfisher@usgs.gov","middleInitial":"N.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":541024,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70148424,"text":"70148424 - 2015 - Magmatic gas emissions at Holocene volcanic features near Mono Lake, California, and their relation to regional magmatism","interactions":[],"lastModifiedDate":"2018-09-13T13:39:07","indexId":"70148424","displayToPublicDate":"2015-02-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Magmatic gas emissions at Holocene volcanic features near Mono Lake, California, and their relation to regional magmatism","docAbstract":"<p><span>Silicic lavas have erupted repeatedly in the Mono Basin over the past few thousand years, forming the massive domes and coulees of the Mono Craters chain and the smaller island vents in Mono Lake. We report here on the first systematic study of magmatic CO</span><sub>2</sub><span>&nbsp;emissions from these features, conducted during 2007&ndash;2010. Most notably, a known locus of weak steam venting on the summit of North Coulee is actually enclosed in a large area (~&nbsp;0.25&nbsp;km</span><sup>2</sup><span>) of diffuse gas discharge that emits 10&ndash;14&nbsp;t/d of CO</span><sub>2</sub><span>, mostly at ambient temperature. Subsurface gases sampled here are heavily air-contaminated, but after standard corrections are applied, show average &delta;</span><sup>13</sup><span>C-CO</span><sub>2</sub><span>&nbsp;of &minus;&nbsp;4.72&permil;,&nbsp;</span><sup>3</sup><span>He/</span><sup>4</sup><span>He of 5.89R</span><sub>A</sub><span>, and CO</span><sub>2</sub><span>/</span><sup>3</sup><span>He of 0.77&nbsp;&times;&nbsp;10</span><sup>10</sup><span>, very similar to the values in fumarolic gas from Mammoth Mountain and the Long Valley Caldera immediately to the south of the basin. If these values also characterize the magmatic gas source at Mono Lake, where CO</span><sub>2</sub><span>&nbsp;is captured by the alkaline lake water, a magmatic CO</span><sub>2</sub><span>&nbsp;upflow beneath the lake of ~&nbsp;4&nbsp;t/d can be inferred. Groundwater discharge from the Mono Craters area transports ~&nbsp;13&nbsp;t/d of&nbsp;</span><sup>14</sup><span>C-dead CO</span><sub>2</sub><span>&nbsp;as free gas and dissolved carbonate species, and adding in this component brings the estimated total magmatic CO</span><sub>2</sub><span>&nbsp;output to 29&nbsp;t/d for the two silicic systems in the Mono Basin. If these emissions reflect intrusion and degassing of underlying basalt with 0.5&nbsp;wt.% CO</span><sub>2</sub><span>, a modest intrusion rate of 0.00075&nbsp;km</span><sup>3</sup><span>/yr is indicated. Much higher intrusion rates are required to account for CO</span><sub>2</sub><span>&nbsp;emissions from Mammoth Mountain and the West Moat of the Long Valley Caldera.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2015.01.008","usgsCitation":"Bergfeld, D., Evans, W.C., Howle, J.F., and Hunt, A.G., 2015, Magmatic gas emissions at Holocene volcanic features near Mono Lake, California, and their relation to regional magmatism: Journal of Volcanology and Geothermal Research, v. 292, p. 70-83, https://doi.org/10.1016/j.jvolgeores.2015.01.008.","productDescription":"14 p.","startPage":"70","endPage":"83","numberOfPages":"14","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059936","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":301032,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Long Valley Caldera, Mammoth Mountain, Mono Craters, Mono Lake","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -119.06639099121094,\n              37.44106442458555\n            ],\n            [\n              -119.06639099121094,\n              38.02862223458794\n            ],\n            [\n              -118.76083374023436,\n              38.02862223458794\n            ],\n            [\n              -118.76083374023436,\n              37.44106442458555\n            ],\n            [\n              -119.06639099121094,\n              37.44106442458555\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"292","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"557176b5e4b077dba762a2c5","contributors":{"authors":[{"text":"Bergfeld, D. dbergfel@usgs.gov","contributorId":2069,"corporation":false,"usgs":true,"family":"Bergfeld","given":"D.","email":"dbergfel@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":false,"id":548172,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Evans, William C. 0000-0001-5942-3102 wcevans@usgs.gov","orcid":"https://orcid.org/0000-0001-5942-3102","contributorId":2353,"corporation":false,"usgs":true,"family":"Evans","given":"William","email":"wcevans@usgs.gov","middleInitial":"C.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":548173,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Howle, James F. 0000-0003-0491-6203 jfhowle@usgs.gov","orcid":"https://orcid.org/0000-0003-0491-6203","contributorId":2225,"corporation":false,"usgs":true,"family":"Howle","given":"James","email":"jfhowle@usgs.gov","middleInitial":"F.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":548174,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hunt, Andrew G. 0000-0002-3810-8610 ahunt@usgs.gov","orcid":"https://orcid.org/0000-0002-3810-8610","contributorId":1582,"corporation":false,"usgs":true,"family":"Hunt","given":"Andrew","email":"ahunt@usgs.gov","middleInitial":"G.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":548175,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70141629,"text":"70141629 - 2015 - Flow cytometric method for measuring chromatin fragmentation in fixed sperm from yellow perch (<i>Perca flavescens</i>)","interactions":[],"lastModifiedDate":"2018-08-09T12:54:58","indexId":"70141629","displayToPublicDate":"2015-02-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3594,"text":"Theriogenology","active":true,"publicationSubtype":{"id":10}},"title":"Flow cytometric method for measuring chromatin fragmentation in fixed sperm from yellow perch (<i>Perca flavescens</i>)","docAbstract":"<p><span>Declining harvests of yellow perch,&nbsp;</span><i>Perca flavescens</i><span>, in urbanized watersheds of Chesapeake Bay have prompted investigations of their reproductive fitness. The purpose of this study was to establish a flow cytometric technique for DNA analysis of fixed samples sent from the field to provide reliable gamete quality measurements. Similar to the sperm chromatin structure assay, measures were made on the susceptibility of nuclear DNA to acid-induced denaturation, but used fixed rather than live or thawed cells. Nuclei were best exposed to the acid treatment for 1&nbsp;minute at 37&nbsp;&deg;C followed by the addition of cold (4&nbsp;&deg;C) propidium iodide staining solution before flow cytometry. The rationale for protocol development is presented graphically through cytograms. Field results collected in 2008 and 2009 revealed DNA fragmentation up to 14.5%. In 2008, DNA fragmentation from the more urbanized watersheds was significantly greater than from reference sites (P&nbsp;=&nbsp;0.026) and in 2009, higher percentages of haploid testicular cells were noted from the less urbanized watersheds (P&nbsp;=&nbsp;0.032) indicating better reproductive condition at sites with less urbanization. For both years, total and progressive live sperm motilities by computer-assisted sperm motion analysis ranged from 19.1% to 76.5%, being significantly higher at the less urbanized sites (P&nbsp;&lt;&nbsp;0.05). This flow cytometric method takes advantage of the propensity of fragmented DNA to be denatured under standard conditions, or 1&nbsp;minute at 37&nbsp;&deg;C with 10% buffered formalin&ndash;fixed cells. The study of fixed sperm makes possible the restrospective investigation of germplasm fragmentation, spermatogenic ploidy patterns, and chromatin compaction levels from samples translocated over distance and time. The protocol provides an approach that can be modified for other species across taxa.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.theriogenology.2014.11.028","usgsCitation":"Jenkins, J.A., Draugelis-Dale, R.O., Pinkney, A.E., Iwanowicz, L., and Blazer, V., 2015, Flow cytometric method for measuring chromatin fragmentation in fixed sperm from yellow perch (<i>Perca flavescens</i>): Theriogenology, v. 83, no. 5, p. 920-931, https://doi.org/10.1016/j.theriogenology.2014.11.028.","productDescription":"12 p.","startPage":"920","endPage":"931","numberOfPages":"12","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-048922","costCenters":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":298064,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"83","issue":"5","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54e868bce4b02d776a67c5c6","contributors":{"authors":[{"text":"Jenkins, Jill A. 0000-0002-5087-0894 jenkinsj@usgs.gov","orcid":"https://orcid.org/0000-0002-5087-0894","contributorId":2710,"corporation":false,"usgs":true,"family":"Jenkins","given":"Jill","email":"jenkinsj@usgs.gov","middleInitial":"A.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":540913,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Draugelis-Dale, Rassa O. 0000-0001-8532-3287 daler@usgs.gov","orcid":"https://orcid.org/0000-0001-8532-3287","contributorId":20422,"corporation":false,"usgs":true,"family":"Draugelis-Dale","given":"Rassa","email":"daler@usgs.gov","middleInitial":"O.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":540914,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pinkney, Alfred E.","contributorId":14253,"corporation":false,"usgs":false,"family":"Pinkney","given":"Alfred","email":"","middleInitial":"E.","affiliations":[{"id":12750,"text":"U.S. Fish and Wildlife Service, Annapolis, MD","active":true,"usgs":false}],"preferred":false,"id":540915,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Iwanowicz, Luke R. liwanowicz@usgs.gov","contributorId":139215,"corporation":false,"usgs":true,"family":"Iwanowicz","given":"Luke R.","email":"liwanowicz@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":540916,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Blazer, Vicki 0000-0001-6647-9614 vblazer@usgs.gov","orcid":"https://orcid.org/0000-0001-6647-9614","contributorId":792,"corporation":false,"usgs":true,"family":"Blazer","given":"Vicki","email":"vblazer@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":540917,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70141293,"text":"70141293 - 2015 - Differences between main-channel and off-channel food webs in the upper Mississippi River revealed by fatty acid profiles of consumers","interactions":[],"lastModifiedDate":"2020-12-18T12:54:53.344972","indexId":"70141293","displayToPublicDate":"2015-02-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1999,"text":"Inland Waters","active":true,"publicationSubtype":{"id":10}},"title":"Differences between main-channel and off-channel food webs in the upper Mississippi River revealed by fatty acid profiles of consumers","docAbstract":"<p><span>Large river systems are often thought to contain a mosaic of patches with different habitat characteristics driven by differences in flow and mixing environments. Off-channel habitats (e.g., backwater areas, secondary channels) can become semi-isolated from main-channel water inputs, leading to the development of distinct biogeochemical environments. Observations of adult bluegill (</span><i>Lepomis macrochirus</i><span>) in the main channel of the Mississippi River led to speculation that the main channel offered superior food resources relative to off-channel areas. One important aspect of food quality is the quantity and composition of polyunsaturated fatty acids (PUFA). We sampled consumers from main-channel and backwater habitats to determine whether they differed in PUFA content. Main-channel individuals for relatively immobile species (young-of-year bluegill, zebra mussels [</span><i>Dreissena polymorpha</i><span>], and plain pocketbook mussels [</span><i>Lampsilis cardium</i><span>]) had significantly greater PUFA content than off-channel individuals. No difference in PUFA was observed for the more mobile gizzard shad (</span><i>Dorsoma cepedianum</i><span>), which may move between main-channel and off-channel habitats even at early life-history stages. As off-channel habitats become isolated from main-channel waters, flow and water column nitrogen decrease, potentially improving conditions for nitrogen-fixing cyanobacteria and vascular plants that, in turn, have low PUFA content. We conclude that main-channel food webs of the upper Mississippi River provide higher quality food resources for some riverine consumers as compared to food webs in off-channel habitats.</span></p>","language":"English","publisher":"Freshwater Biological Association","doi":"10.5268/IW-5.2.781","usgsCitation":"Larson, J.H., Bartsch, M., Gutreuter, S., Knights, B.C., Bartsch, L., Richardson, W.B., Vallazza, J.M., and Arts, M.T., 2015, Differences between main-channel and off-channel food webs in the upper Mississippi River revealed by fatty acid profiles of consumers: Inland Waters, v. 5, no. 2, p. 101-106, https://doi.org/10.5268/IW-5.2.781.","productDescription":"6 p.","startPage":"101","endPage":"106","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-058306","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences 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Center","active":true,"usgs":true}],"preferred":true,"id":540644,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gutreuter, Steve","contributorId":139279,"corporation":false,"usgs":false,"family":"Gutreuter","given":"Steve","email":"","affiliations":[{"id":6733,"text":"former UMESC employee, USGS","active":true,"usgs":false}],"preferred":false,"id":540645,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Knights, Brent C. 0000-0001-8526-8468 bknights@usgs.gov","orcid":"https://orcid.org/0000-0001-8526-8468","contributorId":2906,"corporation":false,"usgs":true,"family":"Knights","given":"Brent","email":"bknights@usgs.gov","middleInitial":"C.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":540646,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bartsch, Lynn 0000-0002-1483-4845 lbartsch@usgs.gov","orcid":"https://orcid.org/0000-0002-1483-4845","contributorId":3342,"corporation":false,"usgs":true,"family":"Bartsch","given":"Lynn","email":"lbartsch@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":540647,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Richardson, William B. 0000-0002-7471-4394 wrichardson@usgs.gov","orcid":"https://orcid.org/0000-0002-7471-4394","contributorId":3277,"corporation":false,"usgs":true,"family":"Richardson","given":"William","email":"wrichardson@usgs.gov","middleInitial":"B.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":540648,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Vallazza, Jonathan M. jvallazza@usgs.gov","contributorId":3651,"corporation":false,"usgs":true,"family":"Vallazza","given":"Jonathan","email":"jvallazza@usgs.gov","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":false,"id":540649,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Arts, Michael T.","contributorId":139280,"corporation":false,"usgs":false,"family":"Arts","given":"Michael","email":"","middleInitial":"T.","affiliations":[{"id":12720,"text":"Environment of Canada, National Water Research Institute","active":true,"usgs":false}],"preferred":false,"id":540650,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70155114,"text":"70155114 - 2015 - Tectonic activity as a significant source of crustal tetrafluoromethane emissions to the atmosphere: observations in groundwaters along the San Andreas Fault","interactions":[],"lastModifiedDate":"2015-07-30T10:47:27","indexId":"70155114","displayToPublicDate":"2015-02-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1427,"text":"Earth and Planetary Science Letters","active":true,"publicationSubtype":{"id":10}},"title":"Tectonic activity as a significant source of crustal tetrafluoromethane emissions to the atmosphere: observations in groundwaters along the San Andreas Fault","docAbstract":"<p>Tetrafluoromethane (CF4) concentrations were measured in 14 groundwater samples from the Cuyama Valley, Mil Potrero and Cuddy Valley aquifers along the Big Bend section of the San Andreas Fault System (SAFS) in California to assess whether tectonic activity in this region is a significant source of crustal CF4 to the atmosphere. Dissolved CF4 concentrations in all groundwater samples but one were elevated with respect to estimated recharge concentrations including entrainment of excess air during recharge (CreCre; &sim;30 fmol&thinsp;kg&minus;1 H2O), indicating subsurface addition of CF4 to these groundwaters. Groundwaters in the Cuyama Valley contain small CF4 excesses (0.1&ndash;9 times CreCre), which may be attributed to an in situ release from weathering and a minor addition of deep crustal CF4 introduced to the shallow groundwater through nearby faults. CF4 excesses in groundwaters within 200 m of the SAFS are larger (10&ndash;980 times CreCre) and indicate the presence of a deep crustal flux of CF4 that is likely associated with the physical alteration of silicate minerals in the shear zone of the SAFS. Extrapolating CF4 flux rates observed in this study to the full extent of the SAFS (1300 km &times; 20&ndash;100 km) suggests that the SAFS potentially emits (0.3&ndash;1)&times;10&minus;1 kg(0.3&ndash;1)&times;10&minus;1 kg CF4 yr&minus;1 to the Earth's surface. For comparison, the chemical weathering of &sim;7.5&times;104 km2&sim;7.5&times;104 km2 of granitic rock in California is estimated to release (0.019&ndash;3.2)&times;10&minus;1 kg(0.019&ndash;3.2)&times;10&minus;1 kg CF4 yr&minus;1. Tectonic activity is likely an important, and potentially the dominant, driver of natural emissions of CF4 to the atmosphere. Variations in preindustrial atmospheric CF4 as observed in paleo-archives such as ice cores may therefore represent changes in both continental weathering and tectonic activity, including changes driven by variations in continental ice cover during glacial&ndash;interglacial transitions.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.epsl.2014.12.016","usgsCitation":"Deeds, D., Kulongoski, J., Muhle, J., and Weiss, R.F., 2015, Tectonic activity as a significant source of crustal tetrafluoromethane emissions to the atmosphere: observations in groundwaters along the San Andreas Fault: Earth and Planetary Science Letters, v. 412, p. 163-172, https://doi.org/10.1016/j.epsl.2014.12.016.","productDescription":"10 p.","startPage":"163","endPage":"172","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-049276","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":306244,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Cuyama Valley, Mil Potrero and Cuddy Valley","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -119.94873046875,\n              34.43862840686652\n            ],\n            [\n              -119.94873046875,\n              35.07946034047981\n            ],\n            [\n              -118.267822265625,\n              35.07946034047981\n            ],\n            [\n              -118.267822265625,\n              34.43862840686652\n            ],\n            [\n              -119.94873046875,\n              34.43862840686652\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"412","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55b98fc0e4b08f6647be517f","contributors":{"authors":[{"text":"Deeds, Daniel A. ddeeds@usgs.gov","contributorId":5087,"corporation":false,"usgs":true,"family":"Deeds","given":"Daniel A.","email":"ddeeds@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":564809,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kulongoski, Justin T. 0000-0002-3498-4154 kulongos@usgs.gov","orcid":"https://orcid.org/0000-0002-3498-4154","contributorId":919,"corporation":false,"usgs":true,"family":"Kulongoski","given":"Justin T.","email":"kulongos@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":564810,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Muhle, Jens","contributorId":145626,"corporation":false,"usgs":false,"family":"Muhle","given":"Jens","email":"","affiliations":[{"id":12888,"text":"Scripps Institution of Oceanography, Univ of California","active":true,"usgs":false}],"preferred":false,"id":564811,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Weiss, Ray F.","contributorId":145627,"corporation":false,"usgs":false,"family":"Weiss","given":"Ray","email":"","middleInitial":"F.","affiliations":[{"id":12888,"text":"Scripps Institution of Oceanography, Univ of California","active":true,"usgs":false}],"preferred":false,"id":564812,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70150459,"text":"70150459 - 2015 - Reducing nitrogen export from the corn belt to the Gulf of Mexico: agricultural strategies for remediating hypoxia","interactions":[],"lastModifiedDate":"2018-02-06T12:16:11","indexId":"70150459","displayToPublicDate":"2015-02-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"Reducing nitrogen export from the corn belt to the Gulf of Mexico: agricultural strategies for remediating hypoxia","docAbstract":"<p><span>SPAtially Referenced Regression on Watershed models developed for the Upper Midwest were used to help evaluate the nitrogen-load reductions likely to be achieved by a variety of agricultural conservation practices in the Upper Mississippi-Ohio River Basin (UMORB) and to compare these reductions to the 45% nitrogen-load reduction proposed to remediate hypoxia in the Gulf of Mexico (GoM). Our results indicate that nitrogen-management practices (improved fertilizer management and cover crops) fall short of achieving this goal, even if adopted on all cropland in the region. The goal of a 45% decrease in loads to the GoM can only be achieved through the coupling of nitrogen-management practices with innovative nitrogen-removal practices such as tile-drainage treatment wetlands, drainage&ndash;ditch enhancements, stream-channel restoration, and floodplain reconnection. Combining nitrogen-management practices with nitrogen-removal practices can dramatically reduce nutrient export from agricultural landscapes while minimizing impacts to agricultural production. With this approach, it may be possible to meet the 45% nutrient reduction goal while converting less than 1% of cropland in the UMORB to nitrogen-removal practices. Conservationists, policy makers, and agricultural producers seeking a workable strategy to reduce nitrogen export from the Corn Belt will need to consider a combination of nitrogen-management practices at the field scale and diverse nitrogen-removal practices at the landscape scale.</span></p>","language":"English","publisher":"Wiley","doi":"10.1111/jawr.12246","usgsCitation":"McLellan, E., Robertson, D.M., Schilling, K., Tomer, M., Kostel, J., Smith, D.G., and King, K., 2015, Reducing nitrogen export from the corn belt to the Gulf of Mexico: agricultural strategies for remediating hypoxia: Journal of the American Water Resources Association, v. 51, no. 1, p. 263-289, https://doi.org/10.1111/jawr.12246.","productDescription":"27 p.","startPage":"263","endPage":"289","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-050927","costCenters":[{"id":677,"text":"Wisconsin Water Science 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SC","active":true,"usgs":false}],"preferred":false,"id":556915,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kostel, Jill","contributorId":146458,"corporation":false,"usgs":false,"family":"Kostel","given":"Jill","email":"","affiliations":[],"preferred":false,"id":567954,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Smith, Douglas G. dgsmith@usgs.gov","contributorId":1532,"corporation":false,"usgs":true,"family":"Smith","given":"Douglas","email":"dgsmith@usgs.gov","middleInitial":"G.","affiliations":[{"id":476,"text":"North Carolina Water Science Center","active":true,"usgs":true}],"preferred":true,"id":556916,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"King, Kevin","contributorId":143721,"corporation":false,"usgs":false,"family":"King","given":"Kevin","affiliations":[{"id":6684,"text":"USDA Forest Service, Southern Research Station, Aiken, 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,{"id":70159896,"text":"70159896 - 2015 - A method for estimating the diffuse attenuation coefficient (KdPAR)from paired temperature sensors","interactions":[],"lastModifiedDate":"2020-10-16T15:03:42.633049","indexId":"70159896","displayToPublicDate":"2015-02-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2622,"text":"Limnology and Oceanography: Methods","active":true,"publicationSubtype":{"id":10}},"displayTitle":"A method for estimating the diffuse attenuation coefficient (K<sub>dPAR</sub>)from paired temperature sensors","title":"A method for estimating the diffuse attenuation coefficient (KdPAR)from paired temperature sensors","docAbstract":"<p><span>A new method for estimating the diffuse attenuation coefficient for photosynthetically active radiation (</span><i>K</i><sub><i>d</i>PAR</sub><span>) from paired temperature sensors was derived. We show that during cases where the attenuation of penetrating shortwave solar radiation is the dominant source of temperature changes, time series measurements of water temperatures at multiple depths (</span><i>z</i><sub>1</sub><span>&nbsp;and&nbsp;</span><i>z</i><sub>2</sub><span>) are related to one another by a linear scaling factor (</span><i>α</i><span>).&nbsp;</span><i>K</i><sub><i>d</i>PAR</sub><span>&nbsp;can then be estimated by the simple equation&nbsp;</span><i>K</i><sub><i>d</i>PAR</sub><span>&nbsp;= ln(</span><i>α</i><span>)/(</span><i>z</i><sub>2</sub><span>−</span><i>z</i><sub>1</sub><span>). A suggested workflow is presented that outlines procedures for calculating&nbsp;</span><i>K</i><sub><i>d</i>PAR</sub><span>&nbsp;according to this paired temperature sensor (PTS) method. This method is best suited for conditions when radiative temperature gains are large relative to physical noise. These conditions occur frequently on water bodies with low wind and/or high&nbsp;</span><i>K</i><sub><i>d</i>PAR</sub><span>s but can be used for other types of lakes during time periods of low wind and/or where spatially redundant measurements of temperatures are available. The optimal vertical placement of temperature sensors according to a priori knowledge of&nbsp;</span><i>K</i><sub><i>d</i>PAR</sub><span>&nbsp;is also described. This information can be used to inform the design of future sensor deployments using the PTS method or for campaigns where characterizing sub‐daily changes in temperatures is important. The PTS method provides a novel method to characterize light attenuation in aquatic ecosystems without expensive radiometric equipment or the user subjectivity inherent in Secchi depth measurements. This method also can enable the estimation of&nbsp;</span><i>K</i><sub><i>d</i>PAR</sub><span>&nbsp;at higher frequencies than many manual monitoring programs allow.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/lom3.10006","usgsCitation":"Read, J.S., Rose, K., Winslow, L.A., and Read, E.K., 2015, A method for estimating the diffuse attenuation coefficient (KdPAR)from paired temperature sensors: Limnology and Oceanography: Methods, v. 13, no. 2, p. 53-61, https://doi.org/10.1002/lom3.10006.","productDescription":"9 p.","startPage":"53","endPage":"61","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-051186","costCenters":[],"links":[{"id":472306,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/lom3.10006","text":"Publisher Index Page"},{"id":311836,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","issue":"2","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2015-02-11","publicationStatus":"PW","scienceBaseUri":"566175c1e4b06a3ea36c5677","contributors":{"authors":[{"text":"Read, Jordan S. 0000-0002-3888-6631 jread@usgs.gov","orcid":"https://orcid.org/0000-0002-3888-6631","contributorId":4453,"corporation":false,"usgs":true,"family":"Read","given":"Jordan","email":"jread@usgs.gov","middleInitial":"S.","affiliations":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":160,"text":"Center for Integrated Data Analytics","active":false,"usgs":true}],"preferred":true,"id":580931,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rose, Kevin C.","contributorId":64580,"corporation":false,"usgs":true,"family":"Rose","given":"Kevin C.","affiliations":[],"preferred":false,"id":580933,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Winslow, Luke A. 0000-0002-8602-5510 lwinslow@usgs.gov","orcid":"https://orcid.org/0000-0002-8602-5510","contributorId":5919,"corporation":false,"usgs":true,"family":"Winslow","given":"Luke","email":"lwinslow@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":false,"id":580934,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Read, Emily K. 0000-0002-9617-9433 eread@usgs.gov","orcid":"https://orcid.org/0000-0002-9617-9433","contributorId":5815,"corporation":false,"usgs":true,"family":"Read","given":"Emily","email":"eread@usgs.gov","middleInitial":"K.","affiliations":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true},{"id":160,"text":"Center for Integrated Data Analytics","active":false,"usgs":true}],"preferred":false,"id":580932,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70159420,"text":"70159420 - 2015 - Do shrubs reduce the adverse effects of grazing on soil properties?","interactions":[],"lastModifiedDate":"2019-12-11T15:58:15","indexId":"70159420","displayToPublicDate":"2015-02-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1447,"text":"Ecohydrology","active":true,"publicationSubtype":{"id":10}},"title":"Do shrubs reduce the adverse effects of grazing on soil properties?","docAbstract":"<p>Increases in the density of woody plants are a global phenomenon in drylands, and large aggregations of shrubs, in particular, are regarded as being indicative of dysfunctional ecosystems. There is increasing evidence that overgrazing by livestock reduces ecosystem functions in shrublands, but that shrubs may buffer the negative effects of increasing grazing. We examined changes in water infiltration and nutrient concentrations in soils under shrubs and in their interspaces in shrublands in eastern Australia that varied in the intensity of livestock grazing. We used structural equation modelling to test whether shrubs might reduce the negative effects of overgrazing on infiltration and soil carbon and nitrogen (henceforth &lsquo;soil nutrients&rsquo;). Soils under shrubs and subject to low levels of grazing were more stable and had greater levels of soil nutrients. Shrubs had a direct positive effect on soil nutrients; but, grazing negatively affected nutrients by increasing soil bulk density. Structural equation modelling showed that shrubs had a direct positive effect on water flow under ponded conditions but also enhanced water flow, indirectly, through increased litter cover. Any positive effects of shrubs on water flow under low levels of grazing waned at high levels of grazing. Our results indicate that shrubs may reduce the adverse effects of grazing on soil properties. Specifically, shrubs could restrict access to livestock and therefore protect soils and plants beneath their canopies. Low levels of grazing are likely to ensure the retention of soil water and soil carbon and nitrogen in shrubland soils.</p>","language":"English","publisher":"Wiley","doi":"10.1002/eco.1600","usgsCitation":"Eldridge, D., Beecham, G., and Grace, J.B., 2015, Do shrubs reduce the adverse effects of grazing on soil properties?: Ecohydrology, v. 8, no. 8, p. 1503-1513, https://doi.org/10.1002/eco.1600.","productDescription":"11 p.","startPage":"1503","endPage":"1513","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061846","costCenters":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"links":[{"id":310767,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Australia","city":"Cobar","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              145.26123046875,\n              -31.85889704445453\n            ],\n            [\n              146.260986328125,\n              -31.85889704445453\n            ],\n            [\n              146.260986328125,\n              -31.184609135743237\n            ],\n            [\n              145.26123046875,\n              -31.184609135743237\n            ],\n            [\n              145.26123046875,\n              -31.85889704445453\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"8","issue":"8","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2015-02-18","publicationStatus":"PW","scienceBaseUri":"56334338e4b048076347eec1","contributors":{"authors":[{"text":"Eldridge, David J. 0000-0002-2191-486X","orcid":"https://orcid.org/0000-0002-2191-486X","contributorId":66535,"corporation":false,"usgs":false,"family":"Eldridge","given":"David J.","affiliations":[{"id":27407,"text":"Centre for Ecosystem Science, School of Biological, Earth and Environmental Sciences,  University of New South Wales, Sydney, NSW 2052, Australia","active":true,"usgs":false}],"preferred":false,"id":578516,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Beecham, Genevieve","contributorId":149466,"corporation":false,"usgs":false,"family":"Beecham","given":"Genevieve","email":"","affiliations":[{"id":17744,"text":"University of NSW, Sydney, Australia","active":true,"usgs":false}],"preferred":false,"id":578517,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Grace, James B. 0000-0001-6374-4726 gracej@usgs.gov","orcid":"https://orcid.org/0000-0001-6374-4726","contributorId":884,"corporation":false,"usgs":true,"family":"Grace","given":"James","email":"gracej@usgs.gov","middleInitial":"B.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":578515,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70156348,"text":"70156348 - 2015 - Factors influencing CO<sub>2</sub> and CH<sub>4</sub> emissions from coastal wetlands in the Liaohe Delta, northeast China","interactions":[],"lastModifiedDate":"2015-08-20T12:54:13","indexId":"70156348","displayToPublicDate":"2015-02-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1012,"text":"Biogeosciences Discussions","active":true,"publicationSubtype":{"id":10}},"title":"Factors influencing CO<sub>2</sub> and CH<sub>4</sub> emissions from coastal wetlands in the Liaohe Delta, northeast China","docAbstract":"<p><span>Many factors are known to influence greenhouse gas emissions from coastal wetlands, but it is still unclear which factors are most important under field conditions when they are all acting simultaneously. The objective of this study was to assess the effects of water table, salinity, soil temperature and vegetation on CH</span><span>4</span><span>&nbsp;emissions and ecosystem respiration (</span><i>R</i><span>eco</span><span>) from five coastal wetlands in the Liaohe Delta, northeast China: two&nbsp;</span><i>Phragmites australis</i><span>&nbsp;(common reed) wetlands, two&nbsp;</span><i>Suaeda salsa</i><span>&nbsp;(sea blite) marshes and a rice (</span><i>Oryza sativa</i><span>) paddy. Throughout the growing season, the&nbsp;</span><i>Suaeda</i><span>&nbsp;wetlands were net CH</span><span>4</span><span>&nbsp;sinks whereas the&nbsp;</span><i>Phragmites</i><span>&nbsp;wetlands and the rice paddy were net CH</span><span>4</span><span>sources emitting 1.2&ndash;6.1 g CH</span><span>4</span><span>&nbsp;m</span><span>&minus;2</span><span>&nbsp;y</span><span>&minus;1</span><span>. The&nbsp;</span><i>Phragmites</i><span>&nbsp;wetlands emitted the most CH</span><span>4</span><span>&nbsp;per unit area and the most CH</span><span>4</span><span>&nbsp;relative to CO</span><span>2</span><span>. The main controlling factors for the CH</span><span>4</span><span>&nbsp;emissions were water table, temperature and salinity. The CH</span><span>4</span><span>&nbsp;emission was accelerated at high and constant (or managed) water tables and decreased at water tables below the soil surface. High temperatures enhanced CH</span><span>4</span><span>&nbsp;emissions, and emission rates were consistently low (&lt; 1 mg CH</span><span>4</span><span>&nbsp;m</span><span>&minus;2</span><span>&nbsp;h) at soil temperatures &lt;18 &deg;C. At salinity levels &gt; 18 ppt, the CH</span><span>4</span><span>&nbsp;emission rates were always low (&lt; 1 mg CH</span><span>4</span><span>&nbsp;m</span><span>&minus;2</span><span>&nbsp;h</span><span>&minus;1</span><span>) probably because methanogens were outcompeted by sulphate reducing bacteria. Saline&nbsp;</span><i>Phragmites</i><span>&nbsp;wetlands can, however, emit significant amounts of CH</span><span>4</span><span>&nbsp;as CH</span><span>4</span><span>&nbsp;produced in deep soil layers are transported through the air-space tissue of the plants to the atmosphere. The CH</span><span>4</span><span>&nbsp;emission from coastal wetlands can be reduced by creating fluctuating water tables, including water tables below the soil surface, as well as by occasional flooding by high-salinity water. The effects of water management schemes on the biological communities in the wetlands must, however, be carefully studied prior to the management in order to avoid undesirable effects on the wetland communities.</span></p>","language":"English","publisher":"European Geosciences Union","doi":"10.5194/bg-12-4965-2015","usgsCitation":"Olsson, L., Ye, S., Yu, X., Wei, M., Krauss, K.W., and Brix, H., 2015, Factors influencing CO<sub>2</sub> and CH<sub>4</sub> emissions from coastal wetlands in the Liaohe Delta, northeast China: Biogeosciences Discussions, v. 12, p. 3469-3503, https://doi.org/10.5194/bg-12-4965-2015.","productDescription":"35 p.","startPage":"3469","endPage":"3503","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063447","costCenters":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"links":[{"id":472309,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/bg-12-4965-2015","text":"Publisher Index Page"},{"id":307019,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"China","state":"Liaoning Province","otherGeospatial":"Liaohe Delta","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              122.85736083984375,\n              41.49006348843993\n            ],\n            [\n              122.85736083984375,\n              41.95949009892465\n            ],\n            [\n              124.1180419921875,\n              41.95949009892465\n            ],\n            [\n              124.1180419921875,\n              41.49006348843993\n            ],\n            [\n              122.85736083984375,\n              41.49006348843993\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"12","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2015-08-20","publicationStatus":"PW","scienceBaseUri":"55d6fa32e4b0518e3546bc3c","contributors":{"authors":[{"text":"Olsson, Linda","contributorId":146731,"corporation":false,"usgs":false,"family":"Olsson","given":"Linda","email":"","affiliations":[{"id":13419,"text":"Aarhus University, Denmark","active":true,"usgs":false}],"preferred":false,"id":568816,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ye, Siyuan","contributorId":146732,"corporation":false,"usgs":false,"family":"Ye","given":"Siyuan","email":"","affiliations":[{"id":16739,"text":"Qingdao Institute of Marine Geology, Shandong Province, China","active":true,"usgs":false}],"preferred":false,"id":568817,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yu, Xueyang","contributorId":146733,"corporation":false,"usgs":false,"family":"Yu","given":"Xueyang","email":"","affiliations":[{"id":16739,"text":"Qingdao Institute of Marine Geology, Shandong Province, China","active":true,"usgs":false}],"preferred":false,"id":568818,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wei, Mengjie","contributorId":146734,"corporation":false,"usgs":false,"family":"Wei","given":"Mengjie","email":"","affiliations":[{"id":16739,"text":"Qingdao Institute of Marine Geology, Shandong Province, China","active":true,"usgs":false}],"preferred":false,"id":568819,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Krauss, Ken W. 0000-0003-2195-0729 kraussk@usgs.gov","orcid":"https://orcid.org/0000-0003-2195-0729","contributorId":2017,"corporation":false,"usgs":true,"family":"Krauss","given":"Ken","email":"kraussk@usgs.gov","middleInitial":"W.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":568815,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brix, Hans","contributorId":146735,"corporation":false,"usgs":false,"family":"Brix","given":"Hans","email":"","affiliations":[{"id":13419,"text":"Aarhus University, Denmark","active":true,"usgs":false}],"preferred":false,"id":568820,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
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