{"pageNumber":"582","pageRowStart":"14525","pageSize":"25","recordCount":46700,"records":[{"id":70044978,"text":"70044978 - 2013 - Avian influenza in shorebirds: experimental infection of ruddy turnstones (Arenaria interpres) with avian influenza virus","interactions":[],"lastModifiedDate":"2018-01-03T14:41:36","indexId":"70044978","displayToPublicDate":"2013-04-10T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1990,"text":"Influenza and Other Respiratory Viruses","active":true,"publicationSubtype":{"id":10}},"title":"Avian influenza in shorebirds: experimental infection of ruddy turnstones (Arenaria interpres) with avian influenza virus","docAbstract":"Background: Low pathogenic avian influenza viruses (LPAIV) have been reported in shorebirds, especially at Delaware Bay, USA, during spring migration. However, data on patterns of virus excretion, minimal infectious doses, and clinical outcome are lacking. The ruddy turnstone (Arenaria interpres) is the shorebird species with the highest prevalence of influenza virus at Delaware Bay.\n\nObjectives: The primary objective of this study was to experimentally assess the patterns of influenza virus excretion, minimal infectious doses, and clinical outcome in ruddy turnstones.\n\nMethods: We experimentally challenged ruddy turnstones using a common LPAIV shorebird isolate, an LPAIV waterfowl isolate, or a highly pathogenic H5N1 avian influenza virus. Cloacal and oral swabs and sera were analyzed from each bird.\n\nResults: Most ruddy turnstones had pre-existing antibodies to avian influenza virus, and many were infected at the time of capture. The infectious doses for each challenge virus were similar (103·6–104·16 EID50), regardless of exposure history. All infected birds excreted similar amounts of virus and showed no clinical signs of disease or mortality. Influenza A-specific antibodies remained detectable for at least 2 months after inoculation.\n\nConclusions: These results provide a reference for interpretation of surveillance data, modeling, and predicting the risks of avian influenza transmission and movement in these important hosts.","language":"English","publisher":"Wiley","publisherLocation":"Hoboken, NJ","doi":"10.1111/j.1750-2659.2012.00358.x","usgsCitation":"Hall, J.S., Krauss, S., Franson, J., TeSlaa, J.L., Nashold, S.W., Stallknecht, D.E., Webby, R., and Webster, R.G., 2013, Avian influenza in shorebirds: experimental infection of ruddy turnstones (Arenaria interpres) with avian influenza virus: Influenza and Other Respiratory Viruses, v. 7, no. 1, p. 85-92, https://doi.org/10.1111/j.1750-2659.2012.00358.x.","productDescription":"8 p.","startPage":"85","endPage":"92","ipdsId":"IP-029445","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":473881,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/j.1750-2659.2012.00358.x","text":"Publisher Index Page"},{"id":270800,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":270799,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/j.1750-2659.2012.00358.x"}],"volume":"7","issue":"1","noUsgsAuthors":false,"publicationDate":"2012-04-12","publicationStatus":"PW","scienceBaseUri":"51667bd8e4b0bba30b388ba6","contributors":{"authors":[{"text":"Hall, Jeffrey S. 0000-0001-5599-2826 jshall@usgs.gov","orcid":"https://orcid.org/0000-0001-5599-2826","contributorId":2254,"corporation":false,"usgs":true,"family":"Hall","given":"Jeffrey","email":"jshall@usgs.gov","middleInitial":"S.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":476557,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Krauss, Scott","contributorId":43250,"corporation":false,"usgs":true,"family":"Krauss","given":"Scott","affiliations":[],"preferred":false,"id":476561,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Franson, J. Christian 0000-0002-0251-4238","orcid":"https://orcid.org/0000-0002-0251-4238","contributorId":95002,"corporation":false,"usgs":true,"family":"Franson","given":"J. Christian","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":false,"id":476564,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"TeSlaa, Joshua L. 0000-0001-7802-3454 jteslaa@usgs.gov","orcid":"https://orcid.org/0000-0001-7802-3454","contributorId":46813,"corporation":false,"usgs":true,"family":"TeSlaa","given":"Joshua","email":"jteslaa@usgs.gov","middleInitial":"L.","affiliations":[],"preferred":false,"id":476562,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nashold, Sean W. 0000-0002-8869-6633 snashold@usgs.gov","orcid":"https://orcid.org/0000-0002-8869-6633","contributorId":3611,"corporation":false,"usgs":true,"family":"Nashold","given":"Sean","email":"snashold@usgs.gov","middleInitial":"W.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":false,"id":476558,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stallknecht, David E.","contributorId":20230,"corporation":false,"usgs":true,"family":"Stallknecht","given":"David","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":476560,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Webby, Richard J.","contributorId":80156,"corporation":false,"usgs":true,"family":"Webby","given":"Richard J.","affiliations":[],"preferred":false,"id":476563,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Webster, Robert G.","contributorId":11089,"corporation":false,"usgs":true,"family":"Webster","given":"Robert","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":476559,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70169084,"text":"70169084 - 2013 - Characterizing the thermal suitability of instream habitat for salmonids: A cautionary example from the Rocky Mountains","interactions":[],"lastModifiedDate":"2016-03-16T13:05:07","indexId":"70169084","displayToPublicDate":"2013-04-09T14:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Characterizing the thermal suitability of instream habitat for salmonids: A cautionary example from the Rocky Mountains","docAbstract":"<p><span>Understanding a species&rsquo; thermal niche is becoming increasingly important for management and conservation within the context of global climate change, yet there have been surprisingly few efforts to compare assessments of a species&rsquo; thermal niche across methods. To address this uncertainty, we evaluated the differences in model performance and interpretations of a species&rsquo; thermal niche when using different measures of stream temperature and surrogates for stream temperature. Specifically, we used a logistic regression modeling framework with three different indicators of stream thermal conditions (elevation, air temperature, and stream temperature) referenced to a common set of Brook Trout&nbsp;</span><i>Salvelinus fontinalis</i><span>&nbsp;distribution data from the Boise River basin, Idaho. We hypothesized that stream temperature predictions that were contemporaneous with fish distribution data would have stronger predictive performance than composite measures of stream temperature or any surrogates for stream temperature. Across the different indicators of thermal conditions, the highest measure of accuracy was found for the model based on stream temperature predictions that were contemporaneous with fish distribution data (percent correctly classified = 71%). We found considerable differences in inferences across models, with up to 43% disagreement in the amount of stream habitat that was predicted to be suitable. The differences in performance between models support the growing efforts in many areas to develop accurate stream temperature models for investigations of species&rsquo; thermal niches.</span></p>","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Transactions of the American Fisheries Socitey","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"American Fisheries Society","publisherLocation":"Lawrence, KS","doi":"10.1080/00028487.2013.778900","usgsCitation":"Al-Chokhachy, R.K., Wegner, S.J., Isaak, D.J., and Kershner, J.L., 2013, Characterizing the thermal suitability of instream habitat for salmonids: A cautionary example from the Rocky Mountains: Transactions of the American Fisheries Society, v. 142, no. 3, p. 793-801, https://doi.org/10.1080/00028487.2013.778900.","productDescription":"9 p.","startPage":"793","endPage":"801","numberOfPages":"9","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-033925","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":318912,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"Boise River basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -116.4111328125,\n              43.24520272203356\n            ],\n            [\n              -116.4111328125,\n              45.5679096098613\n            ],\n            [\n              -112.91748046874999,\n              45.5679096098613\n            ],\n            [\n              -112.91748046874999,\n              43.24520272203356\n            ],\n            [\n              -116.4111328125,\n              43.24520272203356\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"142","issue":"3","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2013-04-09","publicationStatus":"PW","scienceBaseUri":"56ea83abe4b0f59b85d90cd2","contributors":{"authors":[{"text":"Al-Chokhachy, Robert K. 0000-0002-2136-5098 ral-chokhachy@usgs.gov","orcid":"https://orcid.org/0000-0002-2136-5098","contributorId":1674,"corporation":false,"usgs":true,"family":"Al-Chokhachy","given":"Robert","email":"ral-chokhachy@usgs.gov","middleInitial":"K.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":622832,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wegner, Seth J.","contributorId":167607,"corporation":false,"usgs":false,"family":"Wegner","given":"Seth","email":"","middleInitial":"J.","affiliations":[{"id":24776,"text":"Trout Unlimited, 322 East Front Street, Suite 401, Boise, ID","active":true,"usgs":false}],"preferred":false,"id":622834,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Isaak, Daniel J.","contributorId":57202,"corporation":false,"usgs":true,"family":"Isaak","given":"Daniel","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":622833,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kershner, Jeffrey L. 0000-0002-7093-9860 jkershner@usgs.gov","orcid":"https://orcid.org/0000-0002-7093-9860","contributorId":310,"corporation":false,"usgs":true,"family":"Kershner","given":"Jeffrey","email":"jkershner@usgs.gov","middleInitial":"L.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":622831,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70043720,"text":"70043720 - 2013 - Automated cloud and shadow detection and filling using two-date Landsat imagery in the United States","interactions":[],"lastModifiedDate":"2013-04-09T20:09:58","indexId":"70043720","displayToPublicDate":"2013-04-09T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2068,"text":"International Journal of Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Automated cloud and shadow detection and filling using two-date Landsat imagery in the United States","docAbstract":"A simple, efficient, and practical approach for detecting cloud and shadow areas in satellite imagery and restoring them with clean pixel values has been developed. Cloud and shadow areas are detected using spectral information from the blue, shortwave infrared, and thermal infrared bands of Landsat Thematic Mapper or Enhanced Thematic Mapper Plus imagery from two dates (a target image and a reference image). These detected cloud and shadow areas are further refined using an integration process and a false shadow removal process according to the geometric relationship between cloud and shadow. Cloud and shadow filling is based on the concept of the Spectral Similarity Group (SSG), which uses the reference image to find similar alternative pixels in the target image to serve as replacement values for restored areas. Pixels are considered to belong to one SSG if the pixel values from Landsat bands 3, 4, and 5 in the reference image are within the same spectral ranges. This new approach was applied to five Landsat path/rows across different landscapes and seasons with various types of cloud patterns. Results show that almost all of the clouds were captured with minimal commission errors, and shadows were detected reasonably well. Among five test scenes, the lowest producer's accuracy of cloud detection was 93.9% and the lowest user's accuracy was 89%. The overall cloud and shadow detection accuracy ranged from 83.6% to 99.3%. The pixel-filling approach resulted in a new cloud-free image that appears seamless and spatially continuous despite differences in phenology between the target and reference images. Our methods offer a straightforward and robust approach for preparing images for the new 2011 National Land Cover Database production.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"International Journal of Remote Sensing","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Taylor & Francis","publisherLocation":"Philadelphia, PA","doi":"10.1080/01431161.2012.720045","usgsCitation":"Jin, S., Homer, C.G., Yang, L., Xian, G., Fry, J., Danielson, P., and Townsend, P., 2013, Automated cloud and shadow detection and filling using two-date Landsat imagery in the United States: International Journal of Remote Sensing, v. 34, no. 5, p. 1540-1560, https://doi.org/10.1080/01431161.2012.720045.","productDescription":"21 p.","startPage":"1540","endPage":"1560","ipdsId":"IP-024783","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":270762,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":270761,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1080/01431161.2012.720045"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 172.5,18.9 ], [ 172.5,71.4 ], [ -66.9,71.4 ], [ -66.9,18.9 ], [ 172.5,18.9 ] ] ] } } ] }","volume":"34","issue":"5","noUsgsAuthors":false,"publicationDate":"2012-10-16","publicationStatus":"PW","scienceBaseUri":"51652a5de4b077fa94dadf43","contributors":{"authors":[{"text":"Jin, Suming 0000-0001-9919-8077 sjin@usgs.gov","orcid":"https://orcid.org/0000-0001-9919-8077","contributorId":4397,"corporation":false,"usgs":true,"family":"Jin","given":"Suming","email":"sjin@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":474167,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Homer, Collin G. 0000-0003-4755-8135 homer@usgs.gov","orcid":"https://orcid.org/0000-0003-4755-8135","contributorId":2262,"corporation":false,"usgs":true,"family":"Homer","given":"Collin","email":"homer@usgs.gov","middleInitial":"G.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":474163,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yang, Limin 0000-0002-2843-6944 lyang@usgs.gov","orcid":"https://orcid.org/0000-0002-2843-6944","contributorId":4305,"corporation":false,"usgs":true,"family":"Yang","given":"Limin","email":"lyang@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":474166,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Xian, George 0000-0001-5674-2204","orcid":"https://orcid.org/0000-0001-5674-2204","contributorId":76589,"corporation":false,"usgs":true,"family":"Xian","given":"George","affiliations":[],"preferred":false,"id":474169,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fry, Joyce 0000-0002-8466-9582 jfry@usgs.gov","orcid":"https://orcid.org/0000-0002-8466-9582","contributorId":3147,"corporation":false,"usgs":true,"family":"Fry","given":"Joyce","email":"jfry@usgs.gov","affiliations":[],"preferred":true,"id":474164,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Danielson, Patrick 0000-0002-2990-2783 pdanielson@usgs.gov","orcid":"https://orcid.org/0000-0002-2990-2783","contributorId":3551,"corporation":false,"usgs":true,"family":"Danielson","given":"Patrick","email":"pdanielson@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":474165,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Townsend, Philip A.","contributorId":47664,"corporation":false,"usgs":true,"family":"Townsend","given":"Philip A.","affiliations":[],"preferred":false,"id":474168,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70044142,"text":"70044142 - 2013 - Assessment of spectral band impact on intercalibration over desert sites using simulation based on EO-1 Hyperion data","interactions":[],"lastModifiedDate":"2013-04-09T13:47:15","indexId":"70044142","displayToPublicDate":"2013-04-09T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1944,"text":"IEEE Transactions on Geoscience and Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Assessment of spectral band impact on intercalibration over desert sites using simulation based on EO-1 Hyperion data","docAbstract":"Since the beginning of the 1990s, stable desert sites have been used for the calibration monitoring of many different sensors. Many attempts at sensor intercalibration have been also conducted using these stable desert sites. As a result, site characterization techniques and the quality of intercalibration techniques have gradually improved over the years. More recently, the Committee on Earth Observation Satellites has recommended a list of reference pseudo-invariant calibration sites for frequent image acquisition by multiple agencies. In general, intercalibration should use well-known or spectrally flat reference. The reflectance profile of desert sites, however, might not be flat or well characterized (from a fine spectral point of view). The aim of this paper is to assess the expected accuracy that can be reached when using desert sites for intercalibration. In order to have a well-mastered estimation of different errors or error sources, this study is performed with simulated data from a hyperspectral sensor. Earth Observing-1 Hyperion images are chosen to provide the simulation input data. Two different cases of intercalibration are considered, namely, Landsat 7 Enhanced Thematic Mapper Plus with Terra Moderate Resolution Imaging Spectroradiometer (MODIS) and Environmental Satellite MEdium Resolution Imaging Spectrometer (MERIS) with Aqua MODIS. The simulation results have confirmed that intercalibration accuracy of 1% to 2% can be achieved between sensors, provided there are a sufficient number of available measurements. The simulated intercalibrations allow explaining results obtained during real intercalibration exercises and to establish some recommendations for the use of desert sites for intercalibration.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"IEEE Transactions on Geoscience and Remote Sensing","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"IEEE","publisherLocation":"Washington, D.C.","doi":"10.1109/TGRS.2012.2228210","usgsCitation":"Henry, P., Chander, G., Fougnie, B., Thomas, C., and Xiong, X., 2013, Assessment of spectral band impact on intercalibration over desert sites using simulation based on EO-1 Hyperion data: IEEE Transactions on Geoscience and Remote Sensing, v. 51, no. 3, p. 1297-1308, https://doi.org/10.1109/TGRS.2012.2228210.","productDescription":"12 p.","startPage":"1297","endPage":"1308","ipdsId":"IP-040537","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":270700,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1109/TGRS.2012.2228210"},{"id":270701,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"51","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51652a52e4b077fa94dadf3b","contributors":{"authors":[{"text":"Henry, P.","contributorId":91599,"corporation":false,"usgs":true,"family":"Henry","given":"P.","email":"","affiliations":[],"preferred":false,"id":474889,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chander, G.","contributorId":51449,"corporation":false,"usgs":true,"family":"Chander","given":"G.","affiliations":[],"preferred":false,"id":474888,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fougnie, B.","contributorId":12346,"corporation":false,"usgs":true,"family":"Fougnie","given":"B.","email":"","affiliations":[],"preferred":false,"id":474886,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thomas, C.","contributorId":7443,"corporation":false,"usgs":true,"family":"Thomas","given":"C.","affiliations":[],"preferred":false,"id":474885,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Xiong, Xiaoxiong","contributorId":15088,"corporation":false,"usgs":true,"family":"Xiong","given":"Xiaoxiong","email":"","affiliations":[],"preferred":false,"id":474887,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70045305,"text":"ofr20131012 - 2013 - Simplified stratigraphic cross sections of the Eocene Green River Formation in the Piceance Basin, northwestern Colorado","interactions":[],"lastModifiedDate":"2013-04-09T09:45:33","indexId":"ofr20131012","displayToPublicDate":"2013-04-09T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-1012","title":"Simplified stratigraphic cross sections of the Eocene Green River Formation in the Piceance Basin, northwestern Colorado","docAbstract":"Thirteen stratigraphic cross sections of the Eocene Green River Formation in the Piceance Basin of northwestern Colorado are presented in this report. Originally published in a much larger and more detailed form by Self and others (2010), they are shown here in simplified, page-size versions that are easily accessed and used for presentation purposes. Modifications to the original versions include the elimination of the detailed lithologic columns and oil-yield histograms from Fischer assay data and the addition of ground-surface lines to give the depth of the various oil shale units shown on the cross section.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131012","usgsCitation":"Dietrich, J.D., and Johnson, R.C., 2013, Simplified stratigraphic cross sections of the Eocene Green River Formation in the Piceance Basin, northwestern Colorado: U.S. Geological Survey Open-File Report 2013-1012, iii, 20 p., https://doi.org/10.3133/ofr20131012.","productDescription":"iii, 20 p.","numberOfPages":"23","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":270682,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131012.gif"},{"id":270680,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1012/"},{"id":270681,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1012/OF13-1012.pdf"}],"country":"United States","state":"Colorado","otherGeospatial":"Piceance Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -109.0,37.0 ], [ -109.0,41.0 ], [ -102.0,41.0 ], [ -102.0,37.0 ], [ -109.0,37.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51652a5fe4b077fa94dadf53","contributors":{"authors":[{"text":"Dietrich, John D.","contributorId":53841,"corporation":false,"usgs":true,"family":"Dietrich","given":"John","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":477204,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Ronald C. 0000-0002-6197-5165 rcjohnson@usgs.gov","orcid":"https://orcid.org/0000-0002-6197-5165","contributorId":1550,"corporation":false,"usgs":true,"family":"Johnson","given":"Ronald","email":"rcjohnson@usgs.gov","middleInitial":"C.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":477203,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70045337,"text":"ds69Z - 2013 - Map of assessed shale gas in the United States, 2012","interactions":[],"lastModifiedDate":"2013-04-09T19:52:53","indexId":"ds69Z","displayToPublicDate":"2013-04-09T00:00:00","publicationYear":"2013","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":"69","chapter":"Z","title":"Map of assessed shale gas in the United States, 2012","docAbstract":"The U.S. Geological Survey has compiled a map of shale-gas assessments in the United States that were completed by 2012 as part of the National Assessment of Oil and Gas Project. Using a geology-based assessment methodology, the U.S. Geological Survey quantitatively estimated potential volumes of undiscovered gas within shale-gas assessment units. These shale-gas assessment units are mapped, and square-mile cells are shown to represent proprietary shale-gas wells. The square-mile cells include gas-producing wells from shale intervals. In some cases, shale-gas formations contain gas in deeper parts of a basin and oil at shallower depths (for example, the Woodford Shale and the Eagle Ford Shale). Because a discussion of shale oil is beyond the scope of this report, only shale-gas assessment units and cells are shown. The map can be printed as a hardcopy map or downloaded for interactive analysis in a Geographic Information System data package using the ArcGIS map document (file extension MXD) and published map file (file extension PMF). Also available is a publications access table with hyperlinks to current U.S. Geological Survey shale gas assessment publications and web pages. Assessment results and geologic reports are available as completed at the U.S. Geological Survey Energy Resources Program Web Site, http://energy.usgs.gov/OilGas/AssessmentsData/NationalOilGasAssessment.aspx. A historical perspective of shale gas activity in the United States is documented and presented in a video clip included as a PowerPoint slideshow.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds69Z","collaboration":"National Assessment of Oil and Gas Project","usgsCitation":"U.S. Geological Survey National Assessment of Oil and Gas Resources Team, and Biewick, L., 2013, Map of assessed shale gas in the United States, 2012: U.S. Geological Survey Data Series 69, iii, 16 p.; Map: 1 Sheet: 37 x 27 inches; Table 1; Shale Gas Slideshow 2012; Downloads Directory, https://doi.org/10.3133/ds69Z.","productDescription":"iii, 16 p.; Map: 1 Sheet: 37 x 27 inches; Table 1; Shale Gas Slideshow 2012; Downloads Directory","additionalOnlineFiles":"Y","temporalStart":"2012-01-01","temporalEnd":"2012-12-31","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":270760,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds69z.gif"},{"id":270756,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov//dds/dds-069/dds-069-z/downloads/DDS-69-Z_plate1.pdf"},{"id":270757,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov//dds/dds-069/dds-069-z/downloads/Table1.pdf"},{"id":270754,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov//dds/dds-069/dds-069-z/"},{"id":270755,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov//dds/dds-069/dds-069-z/DDS-69-Z_pamphlet.pdf"},{"id":270758,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov//dds/dds-069/dds-069-z/downloads/DDS-69-Z_ShaleGasSlideshow2012.pps"},{"id":270759,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov//dds/dds-069/dds-069-z/downloads/"}],"otherGeospatial":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 172.5,18.9 ], [ 172.5,71.4 ], [ -66.9,71.4 ], [ -66.9,18.9 ], [ 172.5,18.9 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51652a5fe4b077fa94dadf4f","contributors":{"authors":[{"text":"U.S. Geological Survey National Assessment of Oil and Gas Resources Team","contributorId":128233,"corporation":true,"usgs":false,"organization":"U.S. Geological Survey National Assessment of Oil and Gas Resources Team","id":535481,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Biewick, Laura R. H. (compiler) lbiewick@usgs.gov","contributorId":92561,"corporation":false,"usgs":true,"family":"Biewick","given":"Laura R. H.","suffix":"(compiler)","email":"lbiewick@usgs.gov","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":477264,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70042906,"text":"70042906 - 2013 - An isotope-dilution standard GC/MS/MS method for steroid hormones in water","interactions":[],"lastModifiedDate":"2021-05-27T16:01:28.036606","indexId":"70042906","displayToPublicDate":"2013-04-08T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"An isotope-dilution standard GC/MS/MS method for steroid hormones in water","docAbstract":"An isotope-dilution quantification method was developed for 20 natural and synthetic steroid hormones and additional compounds in filtered and unfiltered water. Deuterium- or carbon-13-labeled isotope-dilution standards (IDSs) are added to the water sample, which is passed through an octadecylsilyl solid-phase extraction (SPE) disk. Following extract cleanup using Florisil SPE, method compounds are converted to trimethylsilyl derivatives and analyzed by gas chromatography with tandem mass spectrometry. Validation matrices included reagent water, wastewater-affected surface water, and primary (no biological treatment) and secondary wastewater effluent. Overall method recovery for all analytes in these matrices averaged 100%; with overall relative standard deviation of 28%. Mean recoveries of the 20 individual analytes for spiked reagent-water samples prepared along with field samples analyzed in 2009–2010 ranged from 84–104%, with relative standard deviations of 6–36%. Detection levels estimated using ASTM International’s D6091–07 procedure range from 0.4 to 4 ng/L for 17 analytes. Higher censoring levels of 100 ng/L for bisphenol A and 200 ng/L for cholesterol and 3-beta-coprostanol are used to prevent bias and false positives associated with the presence of these analytes in blanks. Absolute method recoveries of the IDSs provide sample-specific performance information and guide data reporting. Careful selection of labeled compounds for use as IDSs is important because both inexact IDS-analyte matches and deuterium label loss affect an IDS’s ability to emulate analyte performance. Six IDS compounds initially tested and applied in this method exhibited deuterium loss and are not used in the final method.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Evaluating Veterinary Pharmaceutical Behavior in the Environment: ACS Symposium Series","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"ACS Publications","publisherLocation":"Washington, D.C.","doi":"10.1021/bk-2013-1126.ch004","usgsCitation":"Foreman, W., Gray, J.L., ReVello, R., Lindley, C.E., and Losche, S.A., 2013, An isotope-dilution standard GC/MS/MS method for steroid hormones in water, chap. <i>of</i> Evaluating Veterinary Pharmaceutical Behavior in the Environment: ACS Symposium Series, v. 1126, p. 57-136, https://doi.org/10.1021/bk-2013-1126.ch004.","productDescription":"80 p.","startPage":"57","endPage":"136","ipdsId":"IP-038162","costCenters":[{"id":140,"text":"Branch of Analytical Serv (National Water Quality Laboratory)","active":false,"usgs":true},{"id":452,"text":"National Water Quality Laboratory","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":270671,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":270670,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1021/bk-2013-1126.ch004"}],"volume":"1126","noUsgsAuthors":false,"publicationDate":"2013-03-14","publicationStatus":"PW","scienceBaseUri":"5163d8dae4b0b7010f820135","contributors":{"authors":[{"text":"Foreman, William T. wforeman@usgs.gov","contributorId":1473,"corporation":false,"usgs":true,"family":"Foreman","given":"William T.","email":"wforeman@usgs.gov","affiliations":[{"id":452,"text":"National Water Quality Laboratory","active":true,"usgs":true}],"preferred":false,"id":472561,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gray, James L. 0000-0002-0807-5635 jlgray@usgs.gov","orcid":"https://orcid.org/0000-0002-0807-5635","contributorId":1253,"corporation":false,"usgs":true,"family":"Gray","given":"James","email":"jlgray@usgs.gov","middleInitial":"L.","affiliations":[{"id":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true},{"id":452,"text":"National Water Quality Laboratory","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":472560,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"ReVello, Rhiannon C. rcrevell@usgs.gov","contributorId":4128,"corporation":false,"usgs":true,"family":"ReVello","given":"Rhiannon C.","email":"rcrevell@usgs.gov","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":472563,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lindley, Chris E. clindley@usgs.gov","contributorId":2337,"corporation":false,"usgs":true,"family":"Lindley","given":"Chris","email":"clindley@usgs.gov","middleInitial":"E.","affiliations":[],"preferred":true,"id":472562,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Losche, Scott A. salosche@usgs.gov","contributorId":4694,"corporation":false,"usgs":true,"family":"Losche","given":"Scott","email":"salosche@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":472564,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70045265,"text":"ds756 - 2013 - A compilation of U.S. Geological Survey pesticide concentration data for water and sediment in the Sacramento–San Joaquin Delta region: 1990–2010","interactions":[],"lastModifiedDate":"2015-07-07T07:21:40","indexId":"ds756","displayToPublicDate":"2013-04-05T00:00:00","publicationYear":"2013","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":"756","title":"A compilation of U.S. Geological Survey pesticide concentration data for water and sediment in the Sacramento–San Joaquin Delta region: 1990–2010","docAbstract":"<p>Beginning around 2000, abundance indices of four pelagic fishes (delta smelt, striped bass, longfin smelt, and threadfin shad) within the San Francisco Bay and Sacramento&ndash;San Joaquin Delta began to decline sharply (Sommer and others, 2007). These declines collectively became known as the pelagic organism decline (POD). No single cause has been linked to this decline, and current theories suggest that combinations of multiple stressors are likely to blame. Contaminants (including current-use pesticides) are one potential stressor being investigated for its role in the POD (Anderson, 2007). Pesticide concentration data collected by the U.S. Geological Survey (USGS) at multiple sites in the delta region over the past two decades are critical to understanding the potential effects of current-use pesticides on species of concern as well as the overall health of the delta ecosystem. In April 2010, a compilation of contaminant data for the delta region was published by the State Water Resources Control Board (Johnson and others, 2010). Pesticide occurrence was the major focus of this report, which concluded that &ldquo;there was insufficient high quality data available to make conclusions about the potential role of specific contaminants in the POD.&rdquo; The report cited multiple sources; however, data collected by the USGS were not included in the publication even though these data met all criteria listed for inclusion in the report. What follows is a summary of publicly available USGS data for pesticide concentrations in surface water and sediments within the Sacramento&ndash;San Joaquin Delta region from the years 1990 through 2010. Data were retrieved though the USGS National Water Information System (NWIS) database, a publicly available online-data repository (U.S. Geological Survey, 1998), and from published USGS reports (also available online at http://pubs.er.usgs.gov/). The majority of the data were collected in support of two long term USGS monitoring programs&mdash;National Water Quality Assessment Program (NAWQA; http://water.usgs.gov/ nawqa/) and National Stream Quality Accounting Network (NASQAN; http://water.usgs.gov/nasqan/)&mdash;and through projects associated with the USGS Toxics Substances Hydrology Program (http://toxics.usgs.gov/). In addition, data were collected during multiple research projects that were supported by various federal, state, and local agencies. Although these data have been previously published in some form, it is hoped that by focusing on samples collected within the delta region and presenting these data in a concise format, they will be a valuable resource for scientists, resource managers, and members of the public working to understand the role of pesticides in the POD and their potential effects on the overall health of the delta ecosystem.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds756","usgsCitation":"Orlando, J., 2013, A compilation of U.S. Geological Survey pesticide concentration data for water and sediment in the Sacramento–San Joaquin Delta region: 1990–2010: U.S. Geological Survey Data Series 756, Report: v, 48 p.; Appendixes, https://doi.org/10.3133/ds756.","productDescription":"Report: v, 48 p.; Appendixes","numberOfPages":"55","onlineOnly":"N","additionalOnlineFiles":"Y","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":270596,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds756.jpg"},{"id":270595,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/756/ds756_appendixes.xlsx"},{"id":270593,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/756/"},{"id":270594,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/756/pdf/ds756.pdf"}],"country":"United States","state":"California","otherGeospatial":"Sacramento-san Joaquin Delta Region","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.47695922851562,\n              37.80327385185868\n            ],\n            [\n              -122.47695922851562,\n              38.381498197198816\n            ],\n            [\n              -121.48818969726561,\n              38.591113776147445\n            ],\n            [\n              -121.05697631835938,\n              38.052416771864834\n            ],\n            [\n              -121.53762817382814,\n              37.80327385185868\n            ],\n            [\n              -122.47695922851562,\n              37.80327385185868\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"515fe720e4b03707eea09cfd","contributors":{"authors":[{"text":"Orlando, James L. 0000-0002-0099-7221","orcid":"https://orcid.org/0000-0002-0099-7221","contributorId":95954,"corporation":false,"usgs":true,"family":"Orlando","given":"James L.","affiliations":[],"preferred":false,"id":477162,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70045266,"text":"sir20125229 - 2013 - The development and application of a decision support system for land management in the Lake Tahoe Basin—The Land Use Simulation Model","interactions":[],"lastModifiedDate":"2013-04-05T10:25:18","indexId":"sir20125229","displayToPublicDate":"2013-04-05T00:00:00","publicationYear":"2013","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":"2012-5229","title":"The development and application of a decision support system for land management in the Lake Tahoe Basin—The Land Use Simulation Model","docAbstract":"This report describes and applies the Land Use Simulation Model (LUSM), the final modeling product for the long-term decision support project funded by the Southern Nevada Public Land Management Act and developed by the U.S. Geological Survey’s Western Geographic Science Center for the Lake Tahoe Basin. Within the context of the natural-resource management and anthropogenic issues of the basin and in an effort to advance land-use and land-cover change science, this report addresses the problem of developing the LUSM as a decision support system. It includes consideration of land-use modeling theory, fire modeling and disturbance in the wildland-urban interface, historical land-use change and its relation to active land management, hydrologic modeling and the impact of urbanization as related to the Lahontan Regional Water Quality Control Board’s recently developed Total Maximum Daily Load report for the basin, and biodiversity in urbanizing areas. The LUSM strives to inform land-management decisions in a complex regulatory environment by simulating parcel-based, land-use transitions with a stochastic, spatially constrained, agent-based model. The tool is intended to be useful for multiple purposes, including the multiagency Pathway 2007 regional planning effort, the Tahoe Regional Planning Agency (TRPA) Regional Plan Update, and complementary research endeavors and natural-resource-management efforts. The LUSM is an Internet-based, scenario-generation decision support tool for allocating retired and developed parcels over the next 20 years. Because USGS staff worked closely with TRPA staff and their “Code of Ordinances” and analyzed datasets of historical management and land-use practices, this report accomplishes the task of providing reasonable default values for a baseline scenario that can be used in the LUSM. One result from the baseline scenario for the model suggests that all vacant parcels could be allocated within 12 years. Results also include: assessment of model functionality, brief descriptions of the 7 basic output tables, assessment of the rate of change in land-use allocation pools over time, locations and amounts of the spatially explicit probabilities of land-use transitions by real estate commodity, and analysis of the state change from today’s existing land cover to potential land uses in the future. Assumptions and limitations of the model are presented. This report concludes with suggested next steps to support the continued utility of the LUSM and additional research avenues.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125229","usgsCitation":"Forney, W.M., Oldham, I.B., and Crescenti, N., 2013, The development and application of a decision support system for land management in the Lake Tahoe Basin—The Land Use Simulation Model: U.S. Geological Survey Scientific Investigations Report 2012-5229, vi, 54 p., https://doi.org/10.3133/sir20125229.","productDescription":"vi, 54 p.","numberOfPages":"62","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":270599,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20125229.gif"},{"id":270597,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5229/"},{"id":270598,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5229/sir2012-5229.pdf"}],"country":"United States","state":"Nevada","otherGeospatial":"Lake Tahoe Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -120.25,38.66 ], [ -120.25,39.33 ], [ -119.83,39.33 ], [ -119.83,38.66 ], [ -120.25,38.66 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"515fe728e4b03707eea09d01","contributors":{"authors":[{"text":"Forney, William M.","contributorId":43490,"corporation":false,"usgs":true,"family":"Forney","given":"William","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":477163,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Oldham, I. Benson","contributorId":101377,"corporation":false,"usgs":true,"family":"Oldham","given":"I.","email":"","middleInitial":"Benson","affiliations":[],"preferred":false,"id":477165,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Crescenti, Neil","contributorId":86239,"corporation":false,"usgs":true,"family":"Crescenti","given":"Neil","email":"","affiliations":[],"preferred":false,"id":477164,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70045263,"text":"ofr20131045 - 2013 - Soil data from fire and permafrost-thaw chronosequences in upland Picea mariana stands near Hess Creek and Tok, interior Alaska","interactions":[],"lastModifiedDate":"2013-04-04T17:50:50","indexId":"ofr20131045","displayToPublicDate":"2013-04-04T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-1045","title":"Soil data from fire and permafrost-thaw chronosequences in upland Picea mariana stands near Hess Creek and Tok, interior Alaska","docAbstract":"Soils of the Northern Circumpolar Permafrost region harbor 1,672 petagrams (Pg) (1 Pg = 1,000,000,000 kilograms) of organic carbon (OC), nearly 50 percent of the global belowground OC pool (Tarnocai and others, 2009). Of that soil OC, nearly 88 percent is presently stored in perennially frozen ground. Recent climate warming at northern latitudes has resulted in warming and thawing of permafrost in many regions (Osterkamp, 2007), which might mobilize OC stocks from associated soil reservoirs via decomposition, leaching, or erosion. Warming also has increased the magnitude and severity of wildfires in the boreal region (Turetsky and others, 2011), which might exacerbate rates of permafrost degradation relative to warming alone. Given the size and vulnerability of the soil OC pool in permafrost soils, permafrost thaw will likely function as a strong positive feedback to the climate system (Koven and others, 2011; Schaefer and others, 2011).\n\nIn this report, we report soil OC inventories from two upland fire chronosequences located near Hess Creek and Tok in Interior Alaska. We sampled organic and mineral soils in the top 2 meters (m) across a range of stand ages to evaluate the effects of wildfire and permafrost thaw on soil C dynamics. These data were used to parameterize a simple process-based fire-permafrost-carbon model, which is described in detail by O’Donnell and others (2011a, b). Model simulations examine long-term changes in soil OC storage in response to fire, permafrost thaw, and climate change. These data also have been used in other papers, including Harden and others (2012), which examines C recovery post-fire, and Johnson and others (2011), which synthesizes data within the Alaska Soil Carbon Database. Findings from these studies highlight the importance of climate and disturbance (wildfire, permafrost thaw) on soil C storage, and loss of soil C from high-latitude ecosystems.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131045","usgsCitation":"O’Donnell, J.A., Harden, J.W., Manies, K.L., Jorgenson, M., Kanevskiy, M., and Xu, X., 2013, Soil data from fire and permafrost-thaw chronosequences in upland Picea mariana stands near Hess Creek and Tok, interior Alaska: U.S. Geological Survey Open-File Report 2013-1045, iii, 16 p., https://doi.org/10.3133/ofr20131045.","productDescription":"iii, 16 p.","numberOfPages":"22","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":555,"text":"Soil Biogeochemistry Group","active":false,"usgs":true}],"links":[{"id":270592,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131045.gif"},{"id":270591,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2013/1045/data"},{"id":270589,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1045/"},{"id":270590,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1045/of2013-1045_text.pdf"}],"country":"United States","state":"Alaska","city":"Hess Creek;Tok","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 172.5,51.2 ], [ 172.5,71.4 ], [ -130.0,71.4 ], [ -130.0,51.2 ], [ 172.5,51.2 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"515e92f7e4b088aa2258092a","contributors":{"authors":[{"text":"O’Donnell, Jonathan A.","contributorId":84138,"corporation":false,"usgs":true,"family":"O’Donnell","given":"Jonathan","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":477161,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Harden, Jennifer W. 0000-0002-6570-8259 jharden@usgs.gov","orcid":"https://orcid.org/0000-0002-6570-8259","contributorId":1971,"corporation":false,"usgs":true,"family":"Harden","given":"Jennifer","email":"jharden@usgs.gov","middleInitial":"W.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":477156,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Manies, Kristen L. 0000-0003-4941-9657 kmanies@usgs.gov","orcid":"https://orcid.org/0000-0003-4941-9657","contributorId":2136,"corporation":false,"usgs":true,"family":"Manies","given":"Kristen","email":"kmanies@usgs.gov","middleInitial":"L.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":477157,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jorgenson, M. Torre","contributorId":40486,"corporation":false,"usgs":true,"family":"Jorgenson","given":"M. Torre","affiliations":[],"preferred":false,"id":477159,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kanevskiy, Mikhail","contributorId":60511,"corporation":false,"usgs":true,"family":"Kanevskiy","given":"Mikhail","affiliations":[],"preferred":false,"id":477160,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Xu, Xiaomei","contributorId":32055,"corporation":false,"usgs":true,"family":"Xu","given":"Xiaomei","affiliations":[],"preferred":false,"id":477158,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70045259,"text":"sir20135034 - 2013 - Groundwater withdrawals 1976, 1990, and 2000--10 and land-surface-elevation changes 2000--10 in Harris, Galveston, Fort Bend, Montgomery, and Brazoria Counties, Texas","interactions":[],"lastModifiedDate":"2017-06-14T14:45:41","indexId":"sir20135034","displayToPublicDate":"2013-04-04T00:00:00","publicationYear":"2013","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":"2013-5034","title":"Groundwater withdrawals 1976, 1990, and 2000--10 and land-surface-elevation changes 2000--10 in Harris, Galveston, Fort Bend, Montgomery, and Brazoria Counties, Texas","docAbstract":"<p>The study area comprising Harris County and parts of Galveston, Fort Bend, Montgomery, and Brazoria Counties in southeastern Texas forms part of one of the largest areas of land-surface-elevation change in the United States. Land-surface-elevation change in the study area primarily is caused by the withdrawal of groundwater. Groundwater withdrawn from the Chicot and Evangeline aquifers has been the primary source of water for municipal supply, industrial and commercial use, and irrigation in the study area. Groundwater withdrawals cause compaction of clay and silt layers abundant in the aquifers, which has in turn resulted in the widespread, substantial land-surface-elevation changes in the region with increased flooding. To estimate land-surface-elevation changes, the U.S. Geological Survey (USGS), in cooperation with the Harris-Galveston Subsidence District (HGSD), documented land-surface-elevation changes in the study area that occurred during 2000&ndash;10 and 2005&ndash;10 based on elevation data measured by 11 USGS borehole-extensometer sites, a National Geodetic Survey Continuously Operating Reference Station, and Global Positioning System Port-A-Measure (PAM) sites operated by the HGSD and the Fort Bend Subsidence District. Groundwater withdrawals in the study area also were documented for 1976, 1990, and 2000&ndash;10.</p>\n<p>In 1976, about 428.9 million gallons per day (Mgal/d) were withdrawn from the aquifer system in Harris County, but by 2000, because of HGSD regulation, withdrawals had decreased to about 337.8 Mgal/d, or about a 21-percent reduction since 1976. By 2010, withdrawals had decreased to about 227.1 Mgal/d, or about a 47-percent reduction since 1976. Among the counties in the study area, the largest decrease in groundwater withdrawals has occurred in Galveston County since 1976. In 1976, about 27.4 Mgal/d were withdrawn from the aquifer system, and by 2000, withdrawals had decreased to about 4.12 Mgal/d, or about an 85-percent reduction since 1976. By 2010, withdrawals had decreased to about 0.626 Mgal/d, or about a 98-percent decrease since 1976.</p>\n<p>Since the mid-1970s, Fort Bend and Montgomery Counties have undergone extensive urban development and corresponding large increases in groundwater withdrawals. Total groundwater withdrawal for Fort Bend County in 1976 was about 16.0 Mgal/d, and by 2000, withdrawals had increased to about 86.5 Mgal/d, or about a 441-percent increase since 1976. By 2010, withdrawals in Fort Bend County had increased to about 99.8 Mgal/d, or about a 524-percent increase since 1976. Total groundwater withdrawal for Montgomery County in 1976 was about 7.84 Mgal/d, and by 2000, withdrawals had increased to about 43.6 Mgal/d, or about a 456-percent increase since 1976. By 2010, withdrawals in Montgomery County had increased to about 64.2 Mgal/d, or about a 719-percent increase since 1976. Total groundwater withdrawal in Brazoria County in 1976 was about 18.0 Mgal/d, and by 2000, withdrawals had increased to about 26.0 Mgal/d, or about a 44-percent increase. By 2010, withdrawals in Brazoria County had increased to about 24.7 Mgal/d, or about a 37-percent increase since 1976.</p>\n<p>Measured land-surface-elevation changes from December 31, 2000, to December 31, 2010, ranged from an elevation increase of 0.06 feet (ft), or an average increase in elevation of 0.006 ft per year, at the Seabrook borehole extensometer located near Seabrook, Tex., to an elevation decrease of 1.28 ft, or an average decrease in elevation of 0.128 ft per year, at a PAM station north of Jersey Village, Tex. (PAM 07). Measured land-surface-elevation changes from December 31, 2005, to December 31, 2010, ranged from an elevation increase of 0.07 ft, or an average increase in elevation of 0.014 ft per year, at PAM 09 in far northeastern Harris County to an elevation decrease of 0.51 ft, or an average decrease in elevation of 0.102 ft per year, at PAM 07.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135034","collaboration":"Prepared in cooperation with the Harris-Galveston Subsidence District","usgsCitation":"Kasmarek, M.C., and Johnson, M., 2013, Groundwater withdrawals 1976, 1990, and 2000--10 and land-surface-elevation changes 2000--10 in Harris, Galveston, Fort Bend, Montgomery, and Brazoria Counties, Texas: U.S. Geological Survey Scientific Investigations Report 2013-5034, iv, 17 p., https://doi.org/10.3133/sir20135034.","productDescription":"iv, 17 p.","numberOfPages":"25","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"1976-01-01","temporalEnd":"2010-12-31","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":270588,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135034.gif"},{"id":270587,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5034/pdf/sir2013-5034.pdf","text":"Report","size":"2.06 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":270586,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5034/"}],"country":"United States","state":"Texas","county":"Brazoria County, Fort Bend County, Galveston County, Harris County, Montgomery County","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -96.125,28.95 ], [ -96.125,29.216667 ], [ -95.6,29.216667 ], [ -95.6,28.95 ], [ -96.125,28.95 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"515e92f7e4b088aa22580926","contributors":{"authors":[{"text":"Kasmarek, Mark C. 0000-0003-2808-2506 mckasmar@usgs.gov","orcid":"https://orcid.org/0000-0003-2808-2506","contributorId":1968,"corporation":false,"usgs":true,"family":"Kasmarek","given":"Mark","email":"mckasmar@usgs.gov","middleInitial":"C.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":477155,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Michaela R. 0000-0001-6133-0247 mrjohns@usgs.gov","orcid":"https://orcid.org/0000-0001-6133-0247","contributorId":1013,"corporation":false,"usgs":true,"family":"Johnson","given":"Michaela R.","email":"mrjohns@usgs.gov","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":477154,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70045247,"text":"ofr20131080 - 2013 - Detection of environmental DNA of Bigheaded Carps in samples collected from selected locations in the St. Croix River and in the Mississippi River","interactions":[],"lastModifiedDate":"2013-04-04T10:29:27","indexId":"ofr20131080","displayToPublicDate":"2013-04-04T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-1080","title":"Detection of environmental DNA of Bigheaded Carps in samples collected from selected locations in the St. Croix River and in the Mississippi River","docAbstract":"The use of molecular methods, such as the detection of environmental deoxyribonucleic acid (eDNA), have become an increasingly popular tool in surveillance programs that monitor for the presence of invasive species in aquatic systems. One early application of these methods in aquatic systems was surveillance for DNA of Asian carps (specifically bighead carp Hypophthalmichthys nobilis and silver carp H. molitrix) in water samples taken from the Chicago Area Waterway System. The ability to identify DNA of a species in an environmental sample presents a potentially powerful tool because these sensitive analyses can presumably detect the presence of DNA in water even when the species is not abundant or are difficult to catch or monitor with traditional gear. Prior to research presented in this report, an initial eDNA surveillance effort was completed in selected locations in the Upper Mississippi and St. Croix Rivers in 2011 after the capture of a bighead carp in the St. Croix River near Prescott, WI. Data presented in this report were developed to duplicate the 2011 monitoring results from the Upper Mississippi and St. Croix Rivers and to provide critical insight into the technique to inform future work in these locations. We specifically sought to understand the potential confounding effects of other pathways of eDNA movement (e.g., fish-eating birds, watercraft) on the variation in background DNA by collecting water samples from (1) sites within the St. Croix River and the upper Mississippi River where the DNA of silver carp was previously detected, (2) sites considered to be free of Asian carp, and (3) a site known to have a large population of Asian carp. We also sought to establish a baseline Asian carp eDNA signature to which future eDNA sampling efforts could be compared. All samples taken as part of this effort were processed using conventional polymerase chain reaction (PCR) according to procedures outlined in the U.S. Army Corps of Engineers Quality Assurance Project Plan with minor deviations designed to enhance the rigor of our data. Presence of DNA in PCR-positive samples was confirmed by Sanger sequencing (forward and reverse) and sequences were considered positive only if sequences (forward and reverse) of ≥150 base pairs had a match of ≥95% to those of published sequences for bighead carp or silver carp. The DNA of bighead carp and silver carp was not detected in environmental samples collected above and below St. Croix Falls Dam on the St. Croix River, above and below the Coon Rapids Dam and below Lock and Dam 1 on the Upper Mississippi River, and from two negative control lakes, Square Lake and Lake Riley. The DNA of silver carp was detected in environmental samples collected below Lock and Dam 19 at Keokuk, Iowa, a reach of the river with high silver carp abundance. The portion (68%) of environmental samples taken below Lock and Dam 19 that were determined to contain the DNA of silver carp was similar to that reported in the scientific literature for other abundant species. The DNA of bighead carp, however, was not detected in environmental samples collected below Lock and Dam 19, a reach of the river known to have bighead carp. Previous reported detections of the DNA of silver carp in samples collected in 2011 were not replicated in this study. Additional analyses are planned for the DNA extracted from the samples collected in 2012. Those analyses may provide additional information regarding the lack of amplification of bighead carp DNA and the lengths of the sequences of silver carp DNA present in samples taken below Lock and Dam 19. These additional analyses may help inform the use of eDNA monitoring in large, complex systems like the Mississippi River.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131080","collaboration":"Prepared in collaboration with the University of Minnesota","usgsCitation":"Amberg, J., McCalla, S., Miller, L., Sorensen, P., and Gaikowski, M.P., 2013, Detection of environmental DNA of Bigheaded Carps in samples collected from selected locations in the St. Croix River and in the Mississippi River: U.S. Geological Survey Open-File Report 2013-1080, iv, 44 p., https://doi.org/10.3133/ofr20131080.","productDescription":"iv, 44 p.","numberOfPages":"52","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":270564,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131080.gif"},{"id":270562,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1080/"},{"id":270563,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1080/pdf/OFR2013-1080.pdf"}],"country":"United States","otherGeospatial":"St. Croix River;Mississippi River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 172.5,18.9 ], [ 172.5,71.4 ], [ -66.9,71.4 ], [ -66.9,18.9 ], [ 172.5,18.9 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"515e92f3e4b088aa22580916","contributors":{"authors":[{"text":"Amberg, Jon J. jamberg@usgs.gov","contributorId":797,"corporation":false,"usgs":true,"family":"Amberg","given":"Jon J.","email":"jamberg@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":false,"id":477134,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCalla, S. Grace smccalla@usgs.gov","contributorId":4897,"corporation":false,"usgs":true,"family":"McCalla","given":"S. Grace","email":"smccalla@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":false,"id":477135,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miller, Loren","contributorId":52058,"corporation":false,"usgs":true,"family":"Miller","given":"Loren","affiliations":[],"preferred":false,"id":477137,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sorensen, Peter","contributorId":9935,"corporation":false,"usgs":true,"family":"Sorensen","given":"Peter","affiliations":[],"preferred":false,"id":477136,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gaikowski, Mark P. 0000-0002-6507-9341 mgaikowski@usgs.gov","orcid":"https://orcid.org/0000-0002-6507-9341","contributorId":796,"corporation":false,"usgs":true,"family":"Gaikowski","given":"Mark","email":"mgaikowski@usgs.gov","middleInitial":"P.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":false,"id":477133,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70045242,"text":"70045242 - 2013 - The effects of juvenile American shad planktivory on zooplankton production in Columbia River food webs","interactions":[],"lastModifiedDate":"2016-05-04T15:32:18","indexId":"70045242","displayToPublicDate":"2013-04-03T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"The effects of juvenile American shad planktivory on zooplankton production in Columbia River food webs","docAbstract":"<p>Columbia River reservoirs support a large population of nonnative American Shad <i>Alosa sapidissima</i> that consume the zooplankton that native fishes also rely on. We hypothesized that the unprecedented biomass of juvenile American Shad in John Day Reservoir is capable of altering the zooplankton community if these fish consume a large portion of the zooplankton production. We derived taxon-specific estimates of zooplankton production using field data and a production model from the literature. Empirical daily ration was estimated for American Shad and expanded to population-level consumption using abundance and biomass data from hydroacoustic surveys. <i>Daphnia</i> spp. production was high in early summer but declined to near zero by September as shad abundance increased. American Shad sequentially consumed <i>Daphnia</i> spp., copepods, and <i>Bosmina</i> spp., which tracked the production trends of these taxa. American Shad evacuation rates ranged from 0.09 to 0.24/h, and daily rations ranged from 0.008 to 0.045&nbsp;g&middot;g<sup>&minus;1</sup>&middot;d<sup>&minus;1</sup> (dry weight) over all years. We observed peak American Shad biomass (45.2&nbsp;kg/ha) in 1994, and daily consumption (1.6&nbsp;kg/ha) approached 30% (5.3&nbsp;kg/ha) of zooplankton production. On average, American Shad consumed 23.6% of the available zooplankton production (range, &lt;1&ndash;83%). The changes in the zooplankton community are consistent with a top-down effect of planktivory by American Shad associated with their unprecedented biomass and consumption, but the effects are likely constrained by temperature, nutrient flux, and the seasonal production patterns of zooplankton in John Day Reservoir. American Shad add to the planktivory exerted by other species like <i>Neomysis mercedis</i> to reduce the capacity of the reservoir to support other planktivorous fishes. The introduction of American Shad and other nonnative species will continue to alter the food web in John Day Reservoir, potentially affecting native fishes, including Pacific salmon <i>Oncorhynchus</i> spp.</p>","language":"English","publisher":"American Fisheries Society","doi":"10.1080/00028487.2012.728164","usgsCitation":"Haskell, C.A., Tiffan, K.F., and Rondorf, D.W., 2013, The effects of juvenile American shad planktivory on zooplankton production in Columbia River food webs: Transactions of the American Fisheries Society, v. 142, no. 3, p. 606-620, https://doi.org/10.1080/00028487.2012.728164.","productDescription":"15 p.","startPage":"606","endPage":"620","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-036417","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":270553,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Columbia River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.0,45.37 ], [ -124.0,55.0 ], [ -112.8,55.0 ], [ -112.8,45.37 ], [ -124.0,45.37 ] ] ] } } ] }","volume":"142","issue":"3","noUsgsAuthors":false,"publicationDate":"2013-03-21","publicationStatus":"PW","scienceBaseUri":"515d4162e4b0803bd2eec503","contributors":{"authors":[{"text":"Haskell, Craig A. 0000-0002-3604-1758 chaskell@usgs.gov","orcid":"https://orcid.org/0000-0002-3604-1758","contributorId":3458,"corporation":false,"usgs":true,"family":"Haskell","given":"Craig","email":"chaskell@usgs.gov","middleInitial":"A.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":477117,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tiffan, Kenneth F. 0000-0002-5831-2846 ktiffan@usgs.gov","orcid":"https://orcid.org/0000-0002-5831-2846","contributorId":3200,"corporation":false,"usgs":true,"family":"Tiffan","given":"Kenneth","email":"ktiffan@usgs.gov","middleInitial":"F.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":477116,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rondorf, Dennis W. drondorf@usgs.gov","contributorId":2970,"corporation":false,"usgs":true,"family":"Rondorf","given":"Dennis","email":"drondorf@usgs.gov","middleInitial":"W.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":477115,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70043515,"text":"70043515 - 2013 - Whole-coal versus ash basis in coal geochemistry: a mathematical approach to consistent interpretations","interactions":[],"lastModifiedDate":"2013-05-20T13:50:35","indexId":"70043515","displayToPublicDate":"2013-04-03T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2033,"text":"International Journal of Coal Geology","active":true,"publicationSubtype":{"id":10}},"title":"Whole-coal versus ash basis in coal geochemistry: a mathematical approach to consistent interpretations","docAbstract":"Several standard methods require coal to be ashed prior to geochemical analysis. Researchers, however, are commonly interested in the compositional nature of the whole-coal, not its ash. Coal geochemical data for any given sample can, therefore, be reported in the ash basis on which it is analyzed or the whole-coal basis to which the ash basis data are back calculated. Basic univariate (mean, variance, distribution, etc.) and bivariate (correlation coefficients, etc.) measures of the same suite of samples can be very different depending which reporting basis the researcher uses. These differences are not real, but an artifact resulting from the compositional nature of most geochemical data. The technical term for this artifact is subcompositional incoherence. Since compositional data are forced to a constant sum, such as 100% or 1,000,000 ppm, they possess curvilinear properties which make the Euclidean principles on which most statistical tests rely inappropriate, leading to erroneous results. Applying the isometric logratio (ilr) transformation to compositional data allows them to be represented in Euclidean space and evaluated using traditional tests without fear of producing mathematically inconsistent results. When applied to coal geochemical data, the issues related to differences between the two reporting bases are resolved as demonstrated in this paper using major oxide and trace metal data from the Pennsylvanian-age Pond Creek coal of eastern Kentucky, USA. Following ilr transformation, univariate statistics, such as mean and variance, still differ between the ash basis and whole-coal basis, but in predictable and calculated manners. Further, the stability between two different components, a bivariate measure, is identical, regardless of the reporting basis. The application of ilr transformations addresses both the erroneous results of Euclidean-based measurements on compositional data as well as the inconsistencies observed on coal geochemical data reported on different bases.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"International Journal of Coal Geology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.coal.2013.02.008","usgsCitation":"Geboy, N., Engle, M.A., and Hower, J., 2013, Whole-coal versus ash basis in coal geochemistry: a mathematical approach to consistent interpretations: International Journal of Coal Geology, v. 113, no. 1, p. 41-49, https://doi.org/10.1016/j.coal.2013.02.008.","productDescription":"9 p.","startPage":"41","endPage":"49","additionalOnlineFiles":"N","ipdsId":"IP-042334","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":270555,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":270464,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.coal.2013.02.008"}],"volume":"113","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"515d4163e4b0803bd2eec507","contributors":{"authors":[{"text":"Geboy, Nicholas J. ngeboy@usgs.gov","contributorId":3860,"corporation":false,"usgs":true,"family":"Geboy","given":"Nicholas J.","email":"ngeboy@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":473750,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Engle, Mark A. 0000-0001-5258-7374 engle@usgs.gov","orcid":"https://orcid.org/0000-0001-5258-7374","contributorId":584,"corporation":false,"usgs":true,"family":"Engle","given":"Mark","email":"engle@usgs.gov","middleInitial":"A.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":473749,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hower, James C. 0000-0003-4694-2776","orcid":"https://orcid.org/0000-0003-4694-2776","contributorId":34561,"corporation":false,"usgs":false,"family":"Hower","given":"James C.","affiliations":[{"id":16123,"text":"University of Kentucky, Center for Applied Energy Research, 2540 Research Park Drive, Lexington, KY 40511, United States.","active":true,"usgs":false}],"preferred":false,"id":473751,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70045245,"text":"sir20125255 - 2013 - Assessment of historical surface-water quality data in southwestern Colorado, 1990-2005","interactions":[],"lastModifiedDate":"2013-04-04T07:34:01","indexId":"sir20125255","displayToPublicDate":"2013-04-03T00:00:00","publicationYear":"2013","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":"2012-5255","title":"Assessment of historical surface-water quality data in southwestern Colorado, 1990-2005","docAbstract":"The spatial and temporal distribution of selected physical and chemical surface-water-quality characteristics were analyzed at stream sites throughout the Dolores and San Juan River Basins in southwestern Colorado using historical data collected from 1990 through 2005 by various local, State, Tribal, and Federal agencies. Overall, streams throughout the study area were well oxygenated. Values of pH generally were near neutral to slightly alkaline throughout most of the study area with the exception of the upper Animas River Basin near Silverton where acidic conditions existed at some sites because of hydrothermal alteration and(or) historical mining. The highest concentrations of dissolved aluminum, total recoverable iron, dissolved lead, and dissolved zinc were measured at sites located in the upper Animas River Basin. Thirty-two sites throughout the study area had at least one measured concentration of total mercury that exceeded the State chronic aquatic-life criterion of 0.01 μg/L. Concentrations of dissolved selenium at some sites exceeded the State chronic water-quality standard of 4.6 μg/L. Total ammonia, nitrate, nitrite, and total phosphorus concentrations generally were low throughout the study area. Overall, results from the trend analyses indicated improvement in water-quality conditions as a result of operation of the Paradox Valley Unit in the Dolores River Basin and irrigation and water-delivery system improvements made in the McElmo Creek Basin (Lower San Juan River Basin) and Mancos River Valley (Upper San Juan River Basin).","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125255","collaboration":"Prepared in cooperation with the Bureau of Land Management, Bureau of Reclamation, Southwestern Water Conservation District, San Miguel County, and Telluride Power/Water","usgsCitation":"Miller, L.D., Schaffrath, K.R., and Linard, J.I., 2013, Assessment of historical surface-water quality data in southwestern Colorado, 1990-2005: U.S. Geological Survey Scientific Investigations Report 2012-5255, vii, 74 p., https://doi.org/10.3133/sir20125255.","productDescription":"vii, 74 p.","numberOfPages":"85","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"1990-01-01","temporalEnd":"2005-12-31","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":270546,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20125255.gif"},{"id":270544,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5255/"},{"id":270545,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5255/SIR12-5255.pdf"}],"country":"United States","state":"Colorado","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -109.0,37.0 ], [ -109.0,41.0 ], [ -102.0,41.0 ], [ -102.0,37.0 ], [ -109.0,37.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"515d4154e4b0803bd2eec4eb","contributors":{"authors":[{"text":"Miller, Lisa D. 0000-0002-3523-0768 ldmiller@usgs.gov","orcid":"https://orcid.org/0000-0002-3523-0768","contributorId":1125,"corporation":false,"usgs":true,"family":"Miller","given":"Lisa","email":"ldmiller@usgs.gov","middleInitial":"D.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":477122,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schaffrath, Keelin R.","contributorId":7552,"corporation":false,"usgs":true,"family":"Schaffrath","given":"Keelin","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":477124,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Linard, Joshua I. jilinard@usgs.gov","contributorId":1465,"corporation":false,"usgs":true,"family":"Linard","given":"Joshua","email":"jilinard@usgs.gov","middleInitial":"I.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":477123,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70045216,"text":"sir20135039 - 2013 - Water-quality conditions, and constituent loads and yields in the Cambridge drinking-water source area, Massachusetts, water years 2005–07","interactions":[],"lastModifiedDate":"2013-04-02T14:44:31","indexId":"sir20135039","displayToPublicDate":"2013-04-02T00:00:00","publicationYear":"2013","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":"2013-5039","title":"Water-quality conditions, and constituent loads and yields in the Cambridge drinking-water source area, Massachusetts, water years 2005–07","docAbstract":"The source water area for the drinking-water supply of the city of Cambridge, Massachusetts, encompasses major transportation corridors, as well as large areas of light industrial, commercial, and residential land use. Because of ongoing development in the drinking-water source area, the Cambridge water supply has the potential to be affected by a wide variety of contaminants. The U.S. Geological Survey (USGS) has monitored surface-water quality in the Hobbs Brook and Stony Brook Basins, which compose the drinking-water source area, since 1997 (water year 1997) through continuous monitoring and discrete sample collection and, since 2004, through systematic collection of streamwater samples during base-flow and stormflow conditions at five primary sampling stations in the drinking-water source area. Four primary sampling stations are on small tributaries in the Hobbs Brook and Stony Brook Basins; the fifth primary sampling station is on the main stem of Stony Brook and drains about 93 percent of the Cambridge drinking-water source area. Water samples also were collected at six secondary sampling stations, including Fresh Pond Reservoir, the final storage reservoir for the raw water supply. Storm runoff and base-flow concentrations of calcium (Ca), chloride (Cl), sodium (Na), and sulfate (SO<sub>4</sub>) were estimated from continuous records of streamflow and specific conductance for six monitoring stations, which include the five primary sampling stations. These data were used to characterize current water-quality conditions, estimate loads and yields, and describe trends in Cl and Na in the tributaries and main-stem streams in the Hobbs Brook and Stony Brook Basins. These data also were used to describe how streamwater quality is affected by various watershed characteristics and provide information to guide future watershed management. Water samples were analyzed for physical properties and concentrations of Ca, Cl, Na, and SO<sub>4</sub>, total nitrogen (TN), total phosphorus (TP), caffeine, and a suite of 59 polar pesticides. Values of physical properties and constituent concentrations varied widely, particularly in samples from tributaries. Median concentrations of Ca, Cl, Na, and SO4 in samples collected in the Hobbs Brook Basin (39.8, 392, 207, and 21.7 milligrams per liter (mg/L), respectively) were higher than those for the Stony Brook Basin (17.8, 87.7, 49.7, and 14.7 mg/L, respectively). These differences in major ion concentrations are likely related to the low percentages of developed land and impervious area in the Stony Brook Basin. Concentrations of dissolved Cl and Na in samples, and those estimated from continuous records of specific conductance (particularly during base flow), often were greater than the U.S. Environmental Protection Agency (USEPA) secondary drinking-water guideline for Cl (250 mg/L), the chronic aquatic-life guideline for Cl (230 mg/L), and the Commonwealth of Massachusetts, Executive Office of Energy and Environmental Affairs drinking-water guideline for Na (20 mg/L). Mean annual flow-weighted concentrations of Ca, Cl, and Na were generally positively correlated with the area of roadway land use in the subbasins. Correlations between mean annual concentrations of Ca and SO<sub>4</sub> in base flow and total roadway, total impervious, and commercial-industrial land uses were statistically significant. Concentrations of TN (range of 0.42 to 5.13 mg/L in all subbasins) and TP (range of 0.006 to 0.80 mg/L in all subbasins) in tributary samples did not differ substantially between the Hobbs Brook and Stony Brook Basins. Concentrations of TN and TP in samples collected during water years 2004–07 exceeded proposed reference concentrations of 0.57 and 0.024 mg/L, in 94 and 56 percent of the samples, respectively. Correlations between annual flow-weighted concentrations of TN and percentages of recreational land use and water-body area were statistically significant; however, no significant relation was found between TP and available land-use information. The volume of streamflow affected water-quality conditions at the primary sampling stations. Turbidity and concentrations of TP were positively correlated with streamflow. In contrast, concentrations of major ions were negatively correlated with streamflow, indicating that these constituents were diluted during stormflows. Concentrations of TN were not correlated with streamflow. Twenty-five pesticides and caffeine were detected in water samples collected in the drinking-water source area and in raw water collected from the Cambridge water-treatment facility intake at the Fresh Pond Reservoir. Imidacloprid, norflurazon, and siduron were the most frequently detected pesticides with the frequency of detections ranging from about 24 to 41 percent. Caffeine was detected in about 37 percent of water samples at concentrations ranging from 0.003 to 1.82 micrograms per liter (μg/L). Although some of the detected pesticides degrade rapidly, norflurazon and siduron are relatively stable and are able to immigrate though the serial reservoir system. Concentrations of 2,4-D, carbaryl, imazaquin, MCPA (2-methyl-4-chlorophenoxyacetic acid), metsulfuron-methyl, norflurazon, siduron, and caffeine were detected more frequently in stormflow samples than in base-flow samples. Concentrations of pesticides did not exceed USEPA drinking-water guidelines or other health standards and were several orders of magnitude less than the lethal exposure level established for several fish species common to the drinking-water source area. Imidacloprid, an insecticide, was the only pesticide with a concentration exceeding available long-term aquatic-life guidelines. Several pesticides correlated significantly with the amount of recreational, residential, and commercial area in the tributary subbasins. Mean annual base-flow concentrations of caffeine correlated significantly with parking-lot land use. For most tributaries, about 70 percent of the annual loads of Ca, Cl, Na, and SO<sub>4</sub> were associated with base flow. Upward temporal trends in annual loads of Cl and Na were identified on the basis of data for water years 1998 to 2008 for the outlet of the Cambridge Reservoir in the Hobbs Brook Basin; however, similar trends were not identified for the main stem of Stony Brook downstream from the reservoir. The proportions of the TN load attributed to base flow and stormflow were similar in each tributary. In contrast, more than 83 percent of the TP loads in the tributaries and about 73 percent of the TP load in main stem of Stony Brook were associated with stormflow. Mean annual yields of Ca, Cl, Na, and SO<sub>4</sub> in the Stony Brook Reservoir watershed, which represents most of the drinking-water source area, were 14, 85, 46, and 9 metric tons per square kilometer, respectively. Mean annual yields among the individual tributary subbasins varied extensively. Mean annual yields for the respective constituents increased with an increase in roadway and parking-lot area in the tributary subbasins. Mean annual yields of TN in the tributary subbasins ranged from about 740 to more than 1,200 kilograms per square kilometer and exceeded the yield for the main stem of Stony Brook at USGS station 01104460 upstream from the Stony Brook Reservoir. Mean annual yields estimated for the herbicides 2,4-D and imidacloprid ranged from 34 to 310 grams per square kilometer (g/km<sup>2</sup>) and 3 to 170 g/km<sup>2</sup>, respectively. Annual loads for 2,4-D were entirely associated with stormflow. The largest annual load for imidacloprid was estimated for the main stem of Stony Brook; however, the highest annual yield for this pesticide, as well as for benomyl, carbaryl, metalaxyl, and propiconazole, was estimated for a tributary to the Stony Brook Reservoir that drains largely residential and recreational areas. Mean annual yields for the herbicide siduron ranged from 6.9 to 35 g/km<sup>2</sup> with most of the loads associated with stormflow. Mean annual yields for the insecticide diuron ranged from 2.1 to 4.4 g/km<sup>2</sup>. Annual yields of caffeine ranged from 11 to 410 g/km<sup>2</sup>.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135039","collaboration":"Prepared in cooperation with the City of Cambridge, Massachusetts, Water Department","usgsCitation":"Smith, K.P., 2013, Water-quality conditions, and constituent loads and yields in the Cambridge drinking-water source area, Massachusetts, water years 2005–07: U.S. Geological Survey Scientific Investigations Report 2013-5039, xii, 76 p., https://doi.org/10.3133/sir20135039.","productDescription":"xii, 76 p.","numberOfPages":"76","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":270487,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135039.gif"},{"id":270485,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5039/"},{"id":270486,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5039/pdf/sir2013-5039_report_508.pdf"}],"country":"United States","state":"Massachusetts","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -71.20,42.21 ], [ -71.20,42.27 ], [ -71.11,42.27 ], [ -71.11,42.21 ], [ -71.20,42.21 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"515befe0e4b075500ee5ca16","contributors":{"authors":[{"text":"Smith, Kirk P. 0000-0003-0269-474X kpsmith@usgs.gov","orcid":"https://orcid.org/0000-0003-0269-474X","contributorId":1516,"corporation":false,"usgs":true,"family":"Smith","given":"Kirk","email":"kpsmith@usgs.gov","middleInitial":"P.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true}],"preferred":true,"id":477052,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70045212,"text":"gip145 - 2013 - Energy map of southwestern Wyoming - Energy data archived, organized, integrated, and accessible","interactions":[],"lastModifiedDate":"2013-04-04T07:42:48","indexId":"gip145","displayToPublicDate":"2013-04-02T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":315,"text":"General Information Product","code":"GIP","onlineIssn":"2332-354X","printIssn":"2332-3531","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"145","title":"Energy map of southwestern Wyoming - Energy data archived, organized, integrated, and accessible","docAbstract":"The Wyoming Landscape Conservation Initiative (WLCI) focuses on conserving world-class wildlife resources while facilitating responsible energy development in southwestern Wyoming. To further advance the objectives of the WLCI long-term, science-based effort, a comprehensive inventory of energy resource and production data is being published in two parts. Energy maps, data, documentation and spatial data processing capabilities are available in geodatabase, published map file (pmf), ArcMap document (mxd), Adobe Acrobat PDF map, and other digital formats that can be downloaded at the USGS website.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/gip145","usgsCitation":"Biewick, L., Jones, N.R., and Wilson, A.B., 2013, Energy map of southwestern Wyoming - Energy data archived, organized, integrated, and accessible: U.S. Geological Survey General Information Product 145, Report PDF: 21 slides, https://doi.org/10.3133/gip145.","productDescription":"Report PDF: 21 slides","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":270481,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/gip145.gif"},{"id":270479,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/gip/145/"},{"id":270480,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/gip/145/GIP145.pdf"}],"country":"United States","state":"Wyoming","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -111.0333,41.0048 ], [ -111.0333,43.4893 ], [ -105.7269,43.4893 ], [ -105.7269,41.0048 ], [ -111.0333,41.0048 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"515befdde4b075500ee5ca02","contributors":{"authors":[{"text":"Biewick, Laura","contributorId":83148,"corporation":false,"usgs":true,"family":"Biewick","given":"Laura","affiliations":[],"preferred":false,"id":477042,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jones, Nicholas R.","contributorId":14233,"corporation":false,"usgs":true,"family":"Jones","given":"Nicholas","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":477041,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wilson, Anna B. 0000-0002-9737-2614 awilson@usgs.gov","orcid":"https://orcid.org/0000-0002-9737-2614","contributorId":1619,"corporation":false,"usgs":true,"family":"Wilson","given":"Anna","email":"awilson@usgs.gov","middleInitial":"B.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":477040,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70208128,"text":"70208128 - 2013 - Structure and tectonic evolution of the eastern Española Basin, Rio Grande rift, north-central New Mexico","interactions":[],"lastModifiedDate":"2020-01-28T15:08:03","indexId":"70208128","displayToPublicDate":"2013-04-01T14:50:50","publicationYear":"2013","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"8","title":"Structure and tectonic evolution of the eastern Española Basin, Rio Grande rift, north-central New Mexico","docAbstract":"<p><span>We describe the structure of the eastern Española Basin and use stratigraphic and stratal attitude data to interpret its tectonic development. This area consists of a west-dipping half graben in the northern Rio Grande rift that includes several intrabasinal grabens, faults, and folds. The Embudo–Santa Clara–Pajarito fault system, a collection of northeast- and north-striking faults in the center of the Española Basin, defines the western boundary of the half graben and was active throughout rifting. Throw rates near the middle of the fault system (i.e., the Santa Clara and north Pajarito faults) and associated hanging-wall tilt rates progressively increased during the middle Miocene. East of Española, hanging-wall tilt rates decreased after 10–12 Ma, coinciding with increased throw rates on the Cañada del Almagre fault. This fault may have temporarily shunted slip from the north Pajarito fault during ca. 8–11 Ma, resulting in lower strain rates on the Santa Clara fault. East of the Embudo–Santa Clara–Pajarito fault system, deformation of the southern Barrancos monocline and the Cañada Ancha graben peaked during the early–middle Miocene and effectively ceased by the late Pliocene. The north-striking Gabeldon faulted monocline lies at the base of the Sangre de Cristo Mountains, where stratal dip relations indicate late Oligocene and Miocene tilting. Shifting of strain toward the Embudo–Santa Clara–Pajarito fault system culminated during the late Pliocene–Quaternary. Collectively, our data suggest that extensional tectonism in the eastern Española Basin increased in the early Miocene and probably peaked between 14–15 Ma and 9–10 Ma, preceding and partly accompanying major volcanism, and decreased in the Plio-Pleistocene.</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"New perspectives on Rio Grande Rift Basins: From tectonics to groundwater","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Geological Society of America","doi":"10.1130/2013.2494(08)","usgsCitation":"Koning, D., Grauch, V.J., Connell, S.D., Ferguson, J., McIntosh, W., Slate, J.L., Wan, E., and Baldridge, W., 2013, Structure and tectonic evolution of the eastern Española Basin, Rio Grande rift, north-central New Mexico, chap. 8 <i>of</i> New perspectives on Rio Grande Rift Basins: From tectonics to groundwater, v. 494, p. 185-219, https://doi.org/10.1130/2013.2494(08).","productDescription":"35 p.","startPage":"185","endPage":"219","ipdsId":"IP-010011","costCenters":[{"id":308,"text":"Geology and Environmental Change Science Center","active":false,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":371658,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico ","otherGeospatial":"Espanola Basin, Rio Grande Rift","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -106.61132812499999,\n              35.25459097465022\n            ],\n            [\n              -105.677490234375,\n              35.25459097465022\n            ],\n            [\n              -105.677490234375,\n              36.33282808737917\n            ],\n            [\n              -106.61132812499999,\n              36.33282808737917\n            ],\n            [\n              -106.61132812499999,\n              35.25459097465022\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"494","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Koning, Daniel","contributorId":58355,"corporation":false,"usgs":true,"family":"Koning","given":"Daniel","email":"","affiliations":[],"preferred":false,"id":780627,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grauch, V. J. 0000-0002-0761-3489 tien@usgs.gov","orcid":"https://orcid.org/0000-0002-0761-3489","contributorId":152256,"corporation":false,"usgs":true,"family":"Grauch","given":"V.","email":"tien@usgs.gov","middleInitial":"J.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":780628,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Connell, Sean D.","contributorId":7374,"corporation":false,"usgs":true,"family":"Connell","given":"Sean","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":780629,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ferguson, J.","contributorId":31907,"corporation":false,"usgs":true,"family":"Ferguson","given":"J.","email":"","affiliations":[],"preferred":false,"id":780630,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McIntosh, William","contributorId":179358,"corporation":false,"usgs":false,"family":"McIntosh","given":"William","affiliations":[],"preferred":false,"id":780631,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Slate, Janet L. 0000-0002-2870-9068 jslate@usgs.gov","orcid":"https://orcid.org/0000-0002-2870-9068","contributorId":252,"corporation":false,"usgs":true,"family":"Slate","given":"Janet","email":"jslate@usgs.gov","middleInitial":"L.","affiliations":[{"id":501,"text":"Office of Science Quality and Integrity","active":true,"usgs":true}],"preferred":true,"id":780632,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wan, Elmira 0000-0002-9255-112X ewan@usgs.gov","orcid":"https://orcid.org/0000-0002-9255-112X","contributorId":3434,"corporation":false,"usgs":true,"family":"Wan","given":"Elmira","email":"ewan@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":780633,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Baldridge, W.S.","contributorId":63956,"corporation":false,"usgs":true,"family":"Baldridge","given":"W.S.","affiliations":[],"preferred":false,"id":780634,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70098949,"text":"70098949 - 2013 - Selection of hyperspectral narrowbands (HNBs) and composition of hyperspectral twoband vegetation indices (HVIs) for biophysical characterization and discrimination of crop types using field reflectance and Hyperion/EO-1 data","interactions":[],"lastModifiedDate":"2017-02-13T14:53:37","indexId":"70098949","displayToPublicDate":"2013-04-01T14:42:31","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1942,"text":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Selection of hyperspectral narrowbands (HNBs) and composition of hyperspectral twoband vegetation indices (HVIs) for biophysical characterization and discrimination of crop types using field reflectance and Hyperion/EO-1 data","docAbstract":"The overarching goal of this study was to establish optimal hyperspectral vegetation indices (HVIs) and hyperspectral narrowbands (HNBs) that best characterize, classify, model, and map the world's main agricultural crops. The primary objectives were: (1) crop biophysical modeling through HNBs and HVIs, (2) accuracy assessment of crop type discrimination using Wilks' Lambda through a discriminant model, and (3) meta-analysis to select optimal HNBs and HVIs for applications related to agriculture. The study was conducted using two Earth Observing One (EO-1) Hyperion scenes and other surface hyperspectral data for the eight leading worldwide crops (wheat, corn, rice, barley, soybeans, pulses, cotton, and alfalfa) that occupy ~70% of all cropland areas globally. This study integrated data collected from multiple study areas in various agroecosystems of Africa, the Middle East, Central Asia, and India. Data were collected for the eight crop types in six distinct growth stages. These included (a) field spectroradiometer measurements (350-2500 nm) sampled at 1-nm discrete bandwidths, and (b) field biophysical variables (e.g., biomass, leaf area index) acquired to correspond with spectroradiometer measurements. The eight crops were described and classified using ~20 HNBs. The accuracy of classifying these 8 crops using HNBs was around 95%, which was ~ 25% better than the multi-spectral results possible from Landsat-7's Enhanced Thematic Mapper+ or EO-1's Advanced Land Imager. Further, based on this research and meta-analysis involving over 100 papers, the study established 33 optimal HNBs and an equal number of specific two-band normalized difference HVIs to best model and study specific biophysical and biochemical quantities of major agricultural crops of the world. Redundant bands identified in this study will help overcome the Hughes Phenomenon (or “the curse of high dimensionality”) in hyperspectral data for a particular application (e.g., biophysi- al characterization of crops). The findings of this study will make a significant contribution to future hyperspectral missions such as NASA's HyspIRI.","language":"English","publisher":"Institute of Electrical and Electronics Engineers","publisherLocation":"New York, NY","doi":"10.1109/JSTARS.2013.2252601","usgsCitation":"Thenkabail, P., Mariotto, I., Gumma, M., Middleton, E., Landis, D., and Huemmrich, K., 2013, Selection of hyperspectral narrowbands (HNBs) and composition of hyperspectral twoband vegetation indices (HVIs) for biophysical characterization and discrimination of crop types using field reflectance and Hyperion/EO-1 data: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, v. 6, no. 2, p. 427-439, https://doi.org/10.1109/JSTARS.2013.2252601.","productDescription":"13 p.","startPage":"427","endPage":"439","numberOfPages":"13","ipdsId":"IP-037139","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true}],"links":[{"id":473885,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/11603/31506","text":"External Repository"},{"id":284275,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":284273,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1109/JSTARS.2013.2252601"}],"country":"India","otherGeospatial":"Africa;Central Asia;Middle East","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -32.7,-40.6 ], [ -32.7,46.9 ], [ 100.0,46.9 ], [ 100.0,-40.6 ], [ -32.7,-40.6 ] ] ] } } ] }","volume":"6","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd7255e4b0b29085108408","contributors":{"authors":[{"text":"Thenkabail, P.S.","contributorId":66071,"corporation":false,"usgs":true,"family":"Thenkabail","given":"P.S.","email":"","affiliations":[],"preferred":false,"id":491784,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mariotto, I.","contributorId":47285,"corporation":false,"usgs":true,"family":"Mariotto","given":"I.","affiliations":[],"preferred":false,"id":491783,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gumma, M.K.","contributorId":12286,"corporation":false,"usgs":true,"family":"Gumma","given":"M.K.","email":"","affiliations":[],"preferred":false,"id":491781,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Middleton, E.M.","contributorId":107656,"corporation":false,"usgs":true,"family":"Middleton","given":"E.M.","email":"","affiliations":[],"preferred":false,"id":491786,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Landis, D.R.","contributorId":25454,"corporation":false,"usgs":true,"family":"Landis","given":"D.R.","email":"","affiliations":[],"preferred":false,"id":491782,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Huemmrich, K.F.","contributorId":105632,"corporation":false,"usgs":true,"family":"Huemmrich","given":"K.F.","email":"","affiliations":[],"preferred":false,"id":491785,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70059944,"text":"70059944 - 2013 - Vegetation greenness trend (2000 to 2009) and the climate controls in the Qinghai-Tibetan Plateau","interactions":[],"lastModifiedDate":"2014-01-06T14:03:33","indexId":"70059944","displayToPublicDate":"2013-04-01T13:55:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2172,"text":"Journal of Applied Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Vegetation greenness trend (2000 to 2009) and the climate controls in the Qinghai-Tibetan Plateau","docAbstract":"The Qinghai-Tibetan Plateau has been experiencing a distinct warming trend, and climate warming has a direct and quick impact on the alpine grassland ecosystem. We detected the greenness trend of the grasslands in the plateau using Moderate Resolution Imaging Spectroradiometer data from 2000 to 2009. Weather station data were used to explore the climatic drivers for vegetation greenness variations. The results demonstrated that the region-wide averaged normalized difference vegetation index (NDVI) increased at a rate of 0.036  yr<sup>−1</sup>. Approximately 20% of the vegetation areas, which were primarily located in the northeastern plateau, exhibited significant NDVI increase trend (p-value <0.05). Only 4% of the vegetated area showed significant decrease trends, which were mostly in the central and southwestern plateau. A strong positive relationship between NDVI and precipitation, especially in the northeastern plateau, suggested that precipitation was a favorable factor for the grassland NDVI. Negative correlations between NDVI and temperature, especially in the southern plateau, indicated that higher temperature adversely affected the grassland growth. Although a warming climate was expected to be beneficial to the vegetation growth in cold regions, the grasslands in the central and southwestern plateau showed a decrease in trends influenced by increased temperature coupled with decreased precipitation.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Applied Remote Sensing","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"SPIE","doi":"10.1117/1.JRS.7.073572","usgsCitation":"Zhang, L., Guo, H., Ji, L., Lei, L., Wang, C., Yan, D., Li, B., and Li, J., 2013, Vegetation greenness trend (2000 to 2009) and the climate controls in the Qinghai-Tibetan Plateau: Journal of Applied Remote Sensing, v. 7, no. 1, 18 p., https://doi.org/10.1117/1.JRS.7.073572.","productDescription":"18 p.","numberOfPages":"18","onlineOnly":"Y","temporalStart":"2000-01-01","temporalEnd":"2009-12-31","ipdsId":"IP-032689","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":473886,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1117/1.jrs.7.073572","text":"Publisher Index Page"},{"id":280627,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":280626,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1117/1.JRS.7.073572"}],"country":"China","state":"Tibet;Qinghai","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 80.0,25.0 ], [ 80.0,40.0 ], [ 100.0,40.0 ], [ 100.0,25.0 ], [ 80.0,25.0 ] ] ] } } ] }","volume":"7","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd7b02e4b0b2908510ddb5","contributors":{"authors":[{"text":"Zhang, Li","contributorId":98139,"corporation":false,"usgs":true,"family":"Zhang","given":"Li","affiliations":[],"preferred":false,"id":487860,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Guo, Huadong","contributorId":21056,"corporation":false,"usgs":true,"family":"Guo","given":"Huadong","email":"","affiliations":[],"preferred":false,"id":487857,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ji, Lei 0000-0002-6133-1036 lji@usgs.gov","orcid":"https://orcid.org/0000-0002-6133-1036","contributorId":2832,"corporation":false,"usgs":true,"family":"Ji","given":"Lei","email":"lji@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":487854,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lei, Liping","contributorId":31299,"corporation":false,"usgs":true,"family":"Lei","given":"Liping","email":"","affiliations":[],"preferred":false,"id":487858,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wang, Cuizhen","contributorId":16312,"corporation":false,"usgs":true,"family":"Wang","given":"Cuizhen","email":"","affiliations":[],"preferred":false,"id":487856,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Yan, Dongmei","contributorId":100736,"corporation":false,"usgs":true,"family":"Yan","given":"Dongmei","email":"","affiliations":[],"preferred":false,"id":487861,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Li, Bin","contributorId":47684,"corporation":false,"usgs":true,"family":"Li","given":"Bin","email":"","affiliations":[],"preferred":false,"id":487859,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Li, Jing","contributorId":9166,"corporation":false,"usgs":true,"family":"Li","given":"Jing","email":"","affiliations":[],"preferred":false,"id":487855,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70073681,"text":"70073681 - 2013 - Use of NMR logging to obtain estimates of hydraulic conductivity in the High Plains aquifer, Nebraska, USA","interactions":[],"lastModifiedDate":"2014-01-22T13:20:38","indexId":"70073681","displayToPublicDate":"2013-04-01T13:14:00","publicationYear":"2013","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":"Use of NMR logging to obtain estimates of hydraulic conductivity in the High Plains aquifer, Nebraska, USA","docAbstract":"Hydraulic conductivity (K) is one of the most important parameters of interest in groundwater applications because it quantifies the ease with which water can flow through an aquifer material. Hydraulic conductivity is typically measured by conducting aquifer tests or wellbore flow (WBF) logging. Of interest in our research is the use of proton nuclear magnetic resonance (NMR) logging to obtain information about water-filled porosity and pore space geometry, the combination of which can be used to estimate K. In this study, we acquired a suite of advanced geophysical logs, aquifer tests, WBF logs, and sidewall cores at the field site in Lexington, Nebraska, which is underlain by the High Plains aquifer. We first used two empirical equations developed for petroleum applications to predict K from NMR logging data: the Schlumberger Doll Research equation (K<sub>SDR</sub>) and the Timur-Coates equation (K<sub>T-C</sub>), with the standard empirical constants determined for consolidated materials. We upscaled our NMR-derived K estimates to the scale of the WBF-logging K(K<sub>WBF-logging</sub>) estimates for comparison. All the upscaled K<sub>T-C</sub> estimates were within an order of magnitude of K<sub>WBF-logging</sub> and all of the upscaled K<sub>SDR</sub> estimates were within 2 orders of magnitude of K<sub>WBF-logging</sub>. We optimized the fit between the upscaled NMR-derived K and KWBF-logging estimates to determine a set of site-specific empirical constants for the unconsolidated materials at our field site. We conclude that reliable estimates of K can be obtained from NMR logging data, thus providing an alternate method for obtaining estimates of K at high levels of vertical resolution.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Water Resources Research","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1002/wrcr.20151","usgsCitation":"Dlubac, K., Knight, R., Song, Y., Bachman, N., Grau, B., Cannia, J., and Williams, J., 2013, Use of NMR logging to obtain estimates of hydraulic conductivity in the High Plains aquifer, Nebraska, USA: Water Resources Research, v. 49, no. 4, p. 1871-1886, https://doi.org/10.1002/wrcr.20151.","productDescription":"16 p.","startPage":"1871","endPage":"1886","numberOfPages":"16","ipdsId":"IP-041711","costCenters":[{"id":496,"text":"Office of Groundwater-Branch of Geophysics","active":false,"usgs":true}],"links":[{"id":473887,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/wrcr.20151","text":"Publisher Index Page"},{"id":281383,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":281332,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/wrcr.20151"}],"country":"United States","state":"Nebraska","city":"Lexington","otherGeospatial":"High Plains Aquifer","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -99.768037,40.743098 ], [ -99.768037,40.798141 ], [ -99.71096,40.798141 ], [ -99.71096,40.743098 ], [ -99.768037,40.743098 ] ] ] } } ] }","volume":"49","issue":"4","noUsgsAuthors":false,"publicationDate":"2013-04-15","publicationStatus":"PW","scienceBaseUri":"53cd7a7be4b0b2908510d886","contributors":{"authors":[{"text":"Dlubac, Katherine","contributorId":33218,"corporation":false,"usgs":true,"family":"Dlubac","given":"Katherine","email":"","affiliations":[],"preferred":false,"id":489034,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Knight, Rosemary","contributorId":84245,"corporation":false,"usgs":true,"family":"Knight","given":"Rosemary","email":"","affiliations":[],"preferred":false,"id":489037,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Song, Yi-Qiao","contributorId":60534,"corporation":false,"usgs":true,"family":"Song","given":"Yi-Qiao","email":"","affiliations":[],"preferred":false,"id":489036,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bachman, Nate","contributorId":35639,"corporation":false,"usgs":true,"family":"Bachman","given":"Nate","email":"","affiliations":[],"preferred":false,"id":489035,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Grau, Ben","contributorId":96188,"corporation":false,"usgs":true,"family":"Grau","given":"Ben","email":"","affiliations":[],"preferred":false,"id":489038,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cannia, Jim","contributorId":16746,"corporation":false,"usgs":true,"family":"Cannia","given":"Jim","email":"","affiliations":[],"preferred":false,"id":489032,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Williams, John","contributorId":23842,"corporation":false,"usgs":true,"family":"Williams","given":"John","email":"","affiliations":[],"preferred":false,"id":489033,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70047564,"text":"70047564 - 2013 - EO-1 Hyperion reflectance time series at calibration and validation sites: stability and sensitivity to seasonal dynamics","interactions":[],"lastModifiedDate":"2013-08-12T12:59:15","indexId":"70047564","displayToPublicDate":"2013-04-01T12:36:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1942,"text":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"EO-1 Hyperion reflectance time series at calibration and validation sites: stability and sensitivity to seasonal dynamics","docAbstract":"This study evaluated Earth Observing 1 (EO-1) Hyperion reflectance time series at established calibration sites to assess the instrument stability and suitability for monitoring vegetation functional parameters. Our analysis using three pseudo-invariant calibration sites in North America indicated that the reflectance time series are devoid of apparent spectral trends and their stability consistently is within 2.5-5 percent throughout most of the spectral range spanning the 12+ year data record. Using three vegetated sites instrumented with eddy covariance towers, the Hyperion reflectance time series were evaluated for their ability to determine important variables of ecosystem function. A number of narrowband and derivative vegetation indices (VI) closely described the seasonal profiles in vegetation function and ecosystem carbon exchange (e.g., net and gross ecosystem productivity) in three very different ecosystems, including a hardwood forest and tallgrass prairie in North America, and a Miombo woodland in Africa. Our results demonstrate the potential for scaling the carbon flux tower measurements to local and regional landscape levels. The VIs with stronger relationships to the CO<sub>2</sub> parameters were derived using continuous reflectance spectra and included wavelengths associated with chlorophyll content and/or chlorophyll fluorescence. Since these indices cannot be calculated from broadband multispectral instrument data, the opportunity to exploit these spectrometer-based VIs in the future will depend on the launch of satellites such as EnMAP and HyspIRI. This study highlights the practical utility of space-borne spectrometers for characterization of the spectral stability and uniformity of the calibration sites in support of sensor cross-comparisons, and demonstrates the potential of narrowband VIs to track and spatially extend ecosystem functional status as well as carbon processes measured at flux towers.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"IEEE Geoscience & Remote Sensing Society","doi":"10.1109/JSTARS.2013.2246139","usgsCitation":"Campbell, P., Middleton, E., Thome, K.J., Kokaly, R., Huemmrich, K., Novick, K., and Brunsell, N., 2013, EO-1 Hyperion reflectance time series at calibration and validation sites: stability and sensitivity to seasonal dynamics: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, v. 6, no. 2, p. 276-290, https://doi.org/10.1109/JSTARS.2013.2246139.","productDescription":"15 p.","startPage":"276","endPage":"290","numberOfPages":"15","ipdsId":"IP-037418","costCenters":[{"id":218,"text":"Denver Federal Center","active":false,"usgs":true}],"links":[{"id":473888,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/11603/28581","text":"External Repository"},{"id":276533,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":276369,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1109/JSTARS.2013.2246139"}],"country":"United States","state":"Nevada","otherGeospatial":"Frenchman Flat;Ivanpah Playa;Railroad Valley Playa","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -118.99,35.0 ], [ -118.99,39.84 ], [ -114.04,39.84 ], [ -114.04,35.0 ], [ -118.99,35.0 ] ] ] } } ] }","volume":"6","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"520a03e6e4b0026c2bc11aff","contributors":{"authors":[{"text":"Campbell, P.K.E.","contributorId":51640,"corporation":false,"usgs":true,"family":"Campbell","given":"P.K.E.","email":"","affiliations":[],"preferred":false,"id":482409,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Middleton, E.M.","contributorId":107656,"corporation":false,"usgs":true,"family":"Middleton","given":"E.M.","email":"","affiliations":[],"preferred":false,"id":482414,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thome, K. J.","contributorId":88099,"corporation":false,"usgs":true,"family":"Thome","given":"K.","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":482411,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kokaly, Raymond F. 0000-0003-0276-7101 raymond@usgs.gov","orcid":"https://orcid.org/0000-0003-0276-7101","contributorId":1785,"corporation":false,"usgs":true,"family":"Kokaly","given":"Raymond F.","email":"raymond@usgs.gov","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":false,"id":482408,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Huemmrich, K.F.","contributorId":105632,"corporation":false,"usgs":true,"family":"Huemmrich","given":"K.F.","email":"","affiliations":[],"preferred":false,"id":482413,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Novick, K.A.","contributorId":93808,"corporation":false,"usgs":true,"family":"Novick","given":"K.A.","email":"","affiliations":[],"preferred":false,"id":482412,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Brunsell, N.A.","contributorId":56144,"corporation":false,"usgs":true,"family":"Brunsell","given":"N.A.","affiliations":[],"preferred":false,"id":482410,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70148175,"text":"70148175 - 2013 - Effects of hydrologic connectivity and environmental nariables on nekton assemblage in a coastal marsh system","interactions":[],"lastModifiedDate":"2015-05-26T11:16:35","indexId":"70148175","displayToPublicDate":"2013-04-01T12:15:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3750,"text":"Wetlands","onlineIssn":"1943-6246","printIssn":"0277-5212","active":true,"publicationSubtype":{"id":10}},"title":"Effects of hydrologic connectivity and environmental nariables on nekton assemblage in a coastal marsh system","docAbstract":"<p>Hydrologic connectivity and environmental variation can influence nekton assemblages in coastal ecosystems. We evaluated the effects of hydrologic connectivity (permanently connected pond: PCP; temporary connected pond: TCP), salinity, vegetation coverage, water depth and other environmental variables on seasonal nekton assemblages in freshwater, brackish, and saline marshes of the Chenier Plain, Louisiana, USA. We hypothesize that 1) nekton assemblages in PCPs have higher metrics (density, biomass, assemblage similarity) than TCPs within all marsh types and 2) no nekton species would be dominant across all marsh types. In throw traps, freshwater PCPs in Fall (36.0 &plusmn; 1.90) and Winter 2009 (43.2 &plusmn; 22.36) supported greater biomass than freshwater TCPs (Fall 2009: 9.1 &plusmn; 4.65; Winter 2009: 8.3 &plusmn; 3.42). In minnow traps, saline TCPs (5.9 &plusmn; 0.85) in Spring 2009 had higher catch per unit effort than saline PCPs (0.7 &plusmn; 0.67). Our data only partially support our first hypothesis as freshwater marsh PCPs had greater assemblage similarity than TCPs. As predicted by our second hypothesis, no nekton species dominated across all marsh types. Nekton assemblages were structured by individual species responses to the salinity gradient as well as pond habitat attributes (submerged aquatic vegetation coverage, dissolved oxygen, hydrologic connectivity).</p>","language":"English","publisher":"Society of Wetland Scientists","publisherLocation":"McClean, VA","doi":"10.1007/s13157-013-0386-0","collaboration":"Louisiana Department of Wildlife and Fisheries; U.S. Fish and Wildlife Service; International Crane Foundation","usgsCitation":"Kang, S., and King, S.L., 2013, Effects of hydrologic connectivity and environmental nariables on nekton assemblage in a coastal marsh system: Wetlands, v. 33, no. 2, p. 321-334, https://doi.org/10.1007/s13157-013-0386-0.","productDescription":"14 p.","startPage":"321","endPage":"334","numberOfPages":"14","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-036540","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":300785,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"33","issue":"2","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2013-02-05","publicationStatus":"PW","scienceBaseUri":"5565993ee4b0d9246a9eb61b","contributors":{"authors":[{"text":"Kang, Sung-Ryong","contributorId":140927,"corporation":false,"usgs":false,"family":"Kang","given":"Sung-Ryong","email":"","affiliations":[],"preferred":false,"id":547609,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"King, Sammy L. 0000-0002-5364-6361 sking@usgs.gov","orcid":"https://orcid.org/0000-0002-5364-6361","contributorId":557,"corporation":false,"usgs":true,"family":"King","given":"Sammy","email":"sking@usgs.gov","middleInitial":"L.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":547533,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70041624,"text":"70041624 - 2013 - Spatial variability of the response to climate change in regional groundwater systems -- examples from simulations in the Deschutes Basin, Oregon","interactions":[],"lastModifiedDate":"2013-11-14T11:31:44","indexId":"70041624","displayToPublicDate":"2013-04-01T11:27:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Spatial variability of the response to climate change in regional groundwater systems -- examples from simulations in the Deschutes Basin, Oregon","docAbstract":"We examine the spatial variability of the response of aquifer systems to climate change in and adjacent to the Cascade Range volcanic arc in the Deschutes Basin, Oregon using downscaled global climate model projections to drive surface hydrologic process and groundwater flow models. Projected warming over the 21st century is anticipated to shift the phase of precipitation toward more rain and less snow in mountainous areas in the Pacific Northwest, resulting in smaller winter snowpack and in a shift in the timing of runoff to earlier in the year. This will be accompanied by spatially variable changes in the timing of groundwater recharge. Analysis of historic climate and hydrologic data and modeling studies show that groundwater plays a key role in determining the response of stream systems to climate change. The spatial variability in the response of groundwater systems to climate change, particularly with regard to flow-system scale, however, has generally not been addressed in the literature. Here we simulate the hydrologic response to projected future climate to show that the response of groundwater systems can vary depending on the location and spatial scale of the flow systems and their aquifer characteristics. Mean annual recharge averaged over the basin does not change significantly between the 1980s and 2080s climate periods given the ensemble of global climate models and emission scenarios evaluated. There are, however, changes in the seasonality of groundwater recharge within the basin. Simulation results show that short-flow-path groundwater systems, such as those providing baseflow to many headwater streams, will likely have substantial changes in the timing of discharge in response changes in seasonality of recharge. Regional-scale aquifer systems with flow paths on the order of many tens of kilometers, in contrast, are much less affected by changes in seasonality of recharge. Flow systems at all spatial scales, however, are likely to reflect interannual changes in total recharge. These results provide insights into the possible impacts of climate change to other regional aquifer systems, and the streams they support, where discharge points represent a range of flow system scales.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Hydrology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2013.01.019","usgsCitation":"Waibel, M.S., Gannett, M.W., Chang, H., and Hulbe, C.L., 2013, Spatial variability of the response to climate change in regional groundwater systems -- examples from simulations in the Deschutes Basin, Oregon: Journal of Hydrology, v. 486, p. 187-201, https://doi.org/10.1016/j.jhydrol.2013.01.019.","productDescription":"15 p.","startPage":"187","endPage":"201","numberOfPages":"15","ipdsId":"IP-040209","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":279076,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":279075,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.jhydrol.2013.01.019"}],"country":"United States","state":"Oregon","otherGeospatial":"Deschutes Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.5,43.0 ], [ -122.5,45.0 ], [ -120.5,45.0 ], [ -120.5,43.0 ], [ -122.5,43.0 ] ] ] } } ] }","volume":"486","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"528607a5e4b00926c21865bf","contributors":{"authors":[{"text":"Waibel, Michael S.","contributorId":19984,"corporation":false,"usgs":true,"family":"Waibel","given":"Michael","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":470001,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gannett, Marshall W. 0000-0003-2498-2427 mgannett@usgs.gov","orcid":"https://orcid.org/0000-0003-2498-2427","contributorId":2942,"corporation":false,"usgs":true,"family":"Gannett","given":"Marshall","email":"mgannett@usgs.gov","middleInitial":"W.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":469999,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chang, Heejun","contributorId":14705,"corporation":false,"usgs":true,"family":"Chang","given":"Heejun","email":"","affiliations":[],"preferred":false,"id":470000,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hulbe, Christina L.","contributorId":93371,"corporation":false,"usgs":true,"family":"Hulbe","given":"Christina","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":470002,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70046394,"text":"70046394 - 2013 - Significance of exchanging SSURGO and STATSGO data when modeling hydrology in diverse physiographic terranes","interactions":[],"lastModifiedDate":"2013-07-25T10:25:57","indexId":"70046394","displayToPublicDate":"2013-04-01T10:19:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3420,"text":"Soil Science Society of America Journal","active":true,"publicationSubtype":{"id":10}},"title":"Significance of exchanging SSURGO and STATSGO data when modeling hydrology in diverse physiographic terranes","docAbstract":"The Water Availability Tool for Environmental Resources (WATER) is a TOPMODEL-based hydrologic model that depends on spatially accurate soils data to function in diverse terranes. In Kentucky, this includes mountainous regions, karstic plateau, and alluvial plains. Soils data are critical because they quantify the space to store water, as well as how water moves through the soil to the stream during storm events. We compared how the model performs using two different sources of soils data--Soil Survey Geographic Database (SSURGO) and State Soil Geographic Database laboratory data (STATSGO)--for 21 basins ranging in size from 17 to 1564 km<sup>2</sup>. Model results were consistently better when SSURGO data were used, likely due to the higher field capacity, porosity, and available-water holding capacity, which cause the model to store more soil-water in the landscape and improve streamflow estimates for both low- and high-flow conditions. In addition, there were significant differences in the conductivity multiplier and scaling parameter values that describe how water moves vertically and laterally, respectively, as quantified by TOPMODEL. We also evaluated whether partitioning areas that drain to streams via sinkholes in karstic basins as separate hydrologic modeling units (HMUs) improved model performance. There were significant differences between HMUs in properties that control soil-water storage in the model, although the effect of partitioning these HMUs on streamflow simulation was inconclusive.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Soil Science Society of America Journal","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Soil Science Society of America","doi":"10.2136/sssaj2012.0069","usgsCitation":"Williamson, T., Taylor, C.J., and Newson, J.K., 2013, Significance of exchanging SSURGO and STATSGO data when modeling hydrology in diverse physiographic terranes: Soil Science Society of America Journal, v. 77, no. 3, p. 877-889, https://doi.org/10.2136/sssaj2012.0069.","productDescription":"13 p.","startPage":"877","endPage":"889","numberOfPages":"13","ipdsId":"IP-036109","costCenters":[{"id":354,"text":"Kentucky Water Science Center","active":true,"usgs":true}],"links":[{"id":275377,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":275376,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.2136/sssaj2012.0069"}],"country":"United States","state":"Kentucky","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -89.5715,36.4972 ], [ -89.5715,39.1475 ], [ -81.965,39.1475 ], [ -81.965,36.4972 ], [ -89.5715,36.4972 ] ] ] } } ] }","volume":"77","issue":"3","noUsgsAuthors":false,"publicationDate":"2013-04-19","publicationStatus":"PW","scienceBaseUri":"51f25422e4b0279fe2e1c026","contributors":{"authors":[{"text":"Williamson, Tanja N. tnwillia@usgs.gov","contributorId":452,"corporation":false,"usgs":true,"family":"Williamson","given":"Tanja N.","email":"tnwillia@usgs.gov","affiliations":[{"id":354,"text":"Kentucky Water Science Center","active":true,"usgs":true}],"preferred":false,"id":479605,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Taylor, Charles J.","contributorId":93100,"corporation":false,"usgs":true,"family":"Taylor","given":"Charles","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":479607,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Newson, Jeremy K. jknewson@usgs.gov","contributorId":4159,"corporation":false,"usgs":true,"family":"Newson","given":"Jeremy","email":"jknewson@usgs.gov","middleInitial":"K.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":false,"id":479606,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
]}