{"pageNumber":"645","pageRowStart":"16100","pageSize":"25","recordCount":46677,"records":[{"id":70046653,"text":"70046653 - 2012 - Upper Klamath Basin Landsat Image for July 25, 2006: Path 45 Rows 30 and 31","interactions":[],"lastModifiedDate":"2013-06-18T11:53:58","indexId":"70046653","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":6,"text":"USGS Unnumbered Series"},"title":"Upper Klamath Basin Landsat Image for July 25, 2006: Path 45 Rows 30 and 31","docAbstract":"This image is a mosaic of Landsat-5 images of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-5 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-5 on March 1, 1984 marks the addition of the fifth satellite to the Landsat series. The Landsat-5 satellite carries the Thematic Mapper (TM) sensor. More information on the Landsat program can be found online at http://landsat.usgs.gov/.","language":"English","publisher":"U.S. Geological Service","publisherLocation":"Reston, VA","doi":"10.3133/70046653","usgsCitation":"Snyder, D.T., 2012, Upper Klamath Basin Landsat Image for July 25, 2006: Path 45 Rows 30 and 31, Dataset, https://doi.org/10.3133/70046653.","productDescription":"Dataset","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[],"links":[{"id":273923,"type":{"id":16,"text":"Metadata"},"url":"https://water.usgs.gov/GIS/metadata/usgswrd/XML/l5045030_03120060725_klamath_nad83.xml"},{"id":273924,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"}],"country":"United States","state":"Oregon","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -123.382600,41.991760 ], [ -123.382600,43.492919 ], [ -120.601579,43.492919 ], [ -120.601579,41.991760 ], [ -123.382600,41.991760 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51c1816ee4b0dd0e00d92225","contributors":{"authors":[{"text":"Snyder, Daniel T. dtsnyder@usgs.gov","contributorId":820,"corporation":false,"usgs":true,"family":"Snyder","given":"Daniel","email":"dtsnyder@usgs.gov","middleInitial":"T.","affiliations":[],"preferred":true,"id":479934,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70046656,"text":"70046656 - 2012 - Upper Klamath Basin Landsat Image for September 27, 2006: Path 45 Rows 30 and 31","interactions":[],"lastModifiedDate":"2013-06-18T12:56:07","indexId":"70046656","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":6,"text":"USGS Unnumbered Series"},"title":"Upper Klamath Basin Landsat Image for September 27, 2006: Path 45 Rows 30 and 31","docAbstract":"This image is a mosaic of Landsat-5 images of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-5 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-5 on March 1, 1984 marks the addition of the fifth satellite to the Landsat series. The Landsat-5 satellite carries the Thematic Mapper (TM) sensor. More information on the Landsat program can be found online at http://landsat.usgs.gov/.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/70046656","usgsCitation":"Snyder, D.T., 2012, Upper Klamath Basin Landsat Image for September 27, 2006: Path 45 Rows 30 and 31, Dataset, https://doi.org/10.3133/70046656.","productDescription":"Dataset","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[],"links":[{"id":273933,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":273932,"type":{"id":16,"text":"Metadata"},"url":"https://water.usgs.gov/GIS/metadata/usgswrd/XML/l5045030_03120060927_klamath_nad83.xml"}],"country":"United States","state":"Oregon","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -123.382600,41.991760 ], [ -123.382600,43.492919 ], [ -120.601579,43.492919 ], [ -120.601579,41.991760 ], [ -123.382600,41.991760 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51c18170e4b0dd0e00d9223d","contributors":{"authors":[{"text":"Snyder, Daniel T. dtsnyder@usgs.gov","contributorId":820,"corporation":false,"usgs":true,"family":"Snyder","given":"Daniel","email":"dtsnyder@usgs.gov","middleInitial":"T.","affiliations":[],"preferred":true,"id":479941,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70046657,"text":"70046657 - 2012 - Upper Klamath Basin Landsat Image for October 29, 2006: Path 45 Rows 30 and 31","interactions":[],"lastModifiedDate":"2013-06-18T13:06:58","indexId":"70046657","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":6,"text":"USGS Unnumbered Series"},"title":"Upper Klamath Basin Landsat Image for October 29, 2006: Path 45 Rows 30 and 31","docAbstract":"This image is a mosaic of Landsat-5 images of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-5 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-5 on March 1, 1984 marks the addition of the fifth satellite to the Landsat series. The Landsat-5 satellite carries the Thematic Mapper (TM) sensor. More information on the Landsat program can be found online at http://landsat.usgs.gov/.","language":"English","publisher":"U.S. Geological Service","publisherLocation":"Reston, VA","doi":"10.3133/70046657","usgsCitation":"Snyder, D.T., 2012, Upper Klamath Basin Landsat Image for October 29, 2006: Path 45 Rows 30 and 31, Dataset, https://doi.org/10.3133/70046657.","productDescription":"Dataset","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[],"links":[{"id":273937,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":273936,"type":{"id":16,"text":"Metadata"},"url":"https://water.usgs.gov/GIS/metadata/usgswrd/XML/l5045030_03120061029_klamath_nad83.xml"}],"country":"United States","state":"Oregon","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -123.382600,41.991760 ], [ -123.382600,43.492919 ], [ -120.601579,43.492919 ], [ -120.601579,41.991760 ], [ -123.382600,41.991760 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51c18170e4b0dd0e00d92239","contributors":{"authors":[{"text":"Snyder, Daniel T. dtsnyder@usgs.gov","contributorId":820,"corporation":false,"usgs":true,"family":"Snyder","given":"Daniel","email":"dtsnyder@usgs.gov","middleInitial":"T.","affiliations":[],"preferred":true,"id":479942,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70046658,"text":"70046658 - 2012 - Upper Klamath Basin Landsat Image for April 28, 2006: Path 45 Rows 30 and 31","interactions":[],"lastModifiedDate":"2013-06-18T13:27:22","indexId":"70046658","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":6,"text":"USGS Unnumbered Series"},"title":"Upper Klamath Basin Landsat Image for April 28, 2006: Path 45 Rows 30 and 31","docAbstract":"This image is a mosaic of Landsat-7 images of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-7 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-7 on April 15, 1999 marks the addition of the latest satellite to the Landsat series. The Landsat-7 satellite carries the Enhanced Thematic Mapper Plus (ETM+) sensor.  A mechanical failure of the ETM+ Scan Line Corrector (SLC) occurred on May 31, 2003, with the result that all Landsat 7 scenes acquired from July 14, 2003 to present have been collected in 'SLC-off' mode. More information on the Landsat program can be found online at http://landsat.usgs.gov/.","language":"English","publisher":"U.S. Geological Service","publisherLocation":"Reston, VA","doi":"10.3133/70046658","usgsCitation":"Snyder, D.T., 2012, Upper Klamath Basin Landsat Image for April 28, 2006: Path 45 Rows 30 and 31, Dataset, https://doi.org/10.3133/70046658.","productDescription":"Dataset","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[],"links":[{"id":273939,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":273938,"type":{"id":16,"text":"Metadata"},"url":"https://water.usgs.gov/GIS/metadata/usgswrd/XML/l71045030_03120060428_klamath_nad83.xml"}],"country":"United States","state":"Oregon","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -123.382600,41.991760 ], [ -123.382600,43.492919 ], [ -120.601579,43.492919 ], [ -120.601579,41.991760 ], [ -123.382600,41.991760 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51c1816ee4b0dd0e00d92221","contributors":{"authors":[{"text":"Snyder, Daniel T. dtsnyder@usgs.gov","contributorId":820,"corporation":false,"usgs":true,"family":"Snyder","given":"Daniel","email":"dtsnyder@usgs.gov","middleInitial":"T.","affiliations":[],"preferred":true,"id":479943,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70046659,"text":"70046659 - 2012 - Upper Klamath Basin Landsat Image for May 30, 2006: Path 45 Rows 30 and 31","interactions":[],"lastModifiedDate":"2013-06-18T14:24:04","indexId":"70046659","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":6,"text":"USGS Unnumbered Series"},"title":"Upper Klamath Basin Landsat Image for May 30, 2006: Path 45 Rows 30 and 31","docAbstract":"This image is a mosaic of Landsat-7 images of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-7 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-7 on April 15, 1999 marks the addition of the latest satellite to the Landsat series. The Landsat-7 satellite carries the Enhanced Thematic Mapper Plus (ETM+) sensor.  A mechanical failure of the ETM+ Scan Line Corrector (SLC) occurred on May 31, 2003, with the result that all Landsat 7 scenes acquired from July 14, 2003 to present have been collected in 'SLC-off' mode. More information on the Landsat program can be found online at http://landsat.usgs.gov/.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/70046659","usgsCitation":"Snyder, D.T., 2012, Upper Klamath Basin Landsat Image for May 30, 2006: Path 45 Rows 30 and 31, Dataset, https://doi.org/10.3133/70046659.","productDescription":"Dataset","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[],"links":[{"id":273941,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":273940,"type":{"id":16,"text":"Metadata"},"url":"https://water.usgs.gov/GIS/metadata/usgswrd/XML/l71045030_03120060530_klamath_nad83.xml"}],"country":"United States","state":"Oregon","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -123.382600,41.991760 ], [ -123.382600,43.492919 ], [ -120.601579,43.492919 ], [ -120.601579,41.991760 ], [ -123.382600,41.991760 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51c1816fe4b0dd0e00d92231","contributors":{"authors":[{"text":"Snyder, Daniel T. dtsnyder@usgs.gov","contributorId":820,"corporation":false,"usgs":true,"family":"Snyder","given":"Daniel","email":"dtsnyder@usgs.gov","middleInitial":"T.","affiliations":[],"preferred":true,"id":479944,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70032658,"text":"70032658 - 2012 - Verifiable metamodels for nitrate losses to drains and groundwater in the Corn Belt, USA","interactions":[],"lastModifiedDate":"2017-11-21T15:18:55","indexId":"70032658","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Verifiable metamodels for nitrate losses to drains and groundwater in the Corn Belt, USA","docAbstract":"<p><span>Nitrate leaching in the unsaturated zone poses a risk to groundwater, whereas nitrate in tile drainage is conveyed directly to streams. We developed metamodels (MMs) consisting of artificial neural networks to simplify and upscale mechanistic fate and transport models for prediction of nitrate losses by drains and leaching in the Corn Belt, USA. The two final MMs predicted nitrate concentration and flux, respectively, in the shallow subsurface. Because each MM considered both tile drainage and leaching, they represent an integrated approach to vulnerability assessment. The MMs used readily available data comprising farm fertilizer nitrogen (N), weather data, and soil properties as inputs; therefore, they were well suited for regional extrapolation. The MMs effectively related the outputs of the underlying mechanistic model (Root Zone Water Quality Model) to the inputs (R</span><sup>2</sup><span><span>&nbsp;</span>= 0.986 for the nitrate concentration MM). Predicted nitrate concentration was compared with measured nitrate in 38 samples of recently recharged groundwater, yielding a Pearson’s<span>&nbsp;</span></span><i>r</i><span><span>&nbsp;</span>of 0.466 (</span><i>p</i><span><span>&nbsp;</span>= 0.003). Predicted nitrate generally was higher than that measured in groundwater, possibly as a result of the time-lag for modern recharge to reach well screens, denitrification in groundwater, or interception of recharge by tile drains. In a qualitative comparison, predicted nitrate concentration also compared favorably with results from a previous regression model that predicted total N in streams.</span></p>","language":"English","publisher":"ACS","doi":"10.1021/es202875e","issn":"0013936X","usgsCitation":"Nolan, B.T., Malone, R.W., Gronberg, J., Thorp, K., and Ma, L., 2012, Verifiable metamodels for nitrate losses to drains and groundwater in the Corn Belt, USA: Environmental Science & Technology, v. 46, no. 2, p. 901-908, https://doi.org/10.1021/es202875e.","productDescription":"8 p.","startPage":"901","endPage":"908","numberOfPages":"8","ipdsId":"IP-031037","costCenters":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"links":[{"id":241524,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":213859,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1021/es202875e"}],"volume":"46","issue":"2","noUsgsAuthors":false,"publicationDate":"2011-12-22","publicationStatus":"PW","scienceBaseUri":"505bc218e4b08c986b32a905","contributors":{"authors":[{"text":"Nolan, Bernard T. 0000-0002-6945-9659 btnolan@usgs.gov","orcid":"https://orcid.org/0000-0002-6945-9659","contributorId":2190,"corporation":false,"usgs":true,"family":"Nolan","given":"Bernard","email":"btnolan@usgs.gov","middleInitial":"T.","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"preferred":true,"id":437321,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Malone, Robert W.","contributorId":10347,"corporation":false,"usgs":false,"family":"Malone","given":"Robert","email":"","middleInitial":"W.","affiliations":[{"id":6622,"text":"US Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":437325,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gronberg, Jo Ann M.","contributorId":18342,"corporation":false,"usgs":true,"family":"Gronberg","given":"Jo Ann M.","affiliations":[],"preferred":false,"id":437324,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thorp, K.R.","contributorId":38370,"corporation":false,"usgs":true,"family":"Thorp","given":"K.R.","email":"","affiliations":[],"preferred":false,"id":437323,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ma, Liwang","contributorId":29140,"corporation":false,"usgs":true,"family":"Ma","given":"Liwang","email":"","affiliations":[],"preferred":false,"id":437322,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70044132,"text":"70044132 - 2012 - Digital outcrop model of stratigraphy and breccias of the southern Franklin Mountains, El Paso, Texas","interactions":[],"lastModifiedDate":"2020-09-11T18:41:20.076485","indexId":"70044132","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"seriesTitle":{"id":606,"text":"AAPG Memoir","active":true,"publicationSubtype":{"id":10}},"title":"Digital outcrop model of stratigraphy and breccias of the southern Franklin Mountains, El Paso, Texas","docAbstract":"<p>This chapter reviews and synthesizes the lithostratigraphy, biostratigraphy, chronostratigraphy, and breccia types of the southwestern part of the great American carbonate bank in the southern Franklin Mountains (SFM), El Paso, Texas. Primary stratigraphic units of focus are the Lower Ordovician El Paso and Upper Ordovician Montoya Groups. These groups preserve breccias formed by collapse of a paleocave system. Precambrian and Silurian units are discussed in the context of breccia clast composition and relative timing of breccia emplacement. Specific attention is paid to the juxtaposition of the top-Sauk second-order supersequence unconformity between the El Paso and Montoya Groups and its relationship to breccias above and below it. The unconformity represents a 10-m.y. exposure event that separates Upper and Lower Ordovician carbonates. The top-Sauk exposure has been previously documented as a significant karst horizon across much of North America.</p><p>The breccias of the SFM were previously described as the result of collapsed paleocaves that formed during subaerial exposure related to the Sauk-Tippecanoe unconformity. A new approach in this work uses traditional field mapping combined with high-resolution (<img src=\"http://archives.datapages.com/data/specpubs/memoir98/CHAPTER36/IMAGES/LT.JPG\" alt=\"lt\" data-mce-src=\"http://archives.datapages.com/data/specpubs/memoir98/CHAPTER36/IMAGES/LT.JPG\">1-m [<img src=\"http://archives.datapages.com/data/specpubs/memoir98/CHAPTER36/IMAGES/LT.JPG\" alt=\"lt\" data-mce-src=\"http://archives.datapages.com/data/specpubs/memoir98/CHAPTER36/IMAGES/LT.JPG\">3.3-ft] point spacing) airborne light detection and ranging (LIDAR) data over 24 km<sup>2</sup><span>&nbsp;</span>(9 mi<sup>2</sup>) to map breccia and relevant stratal surfaces. Airborne LIDAR data were used to create a digital outcrop model of the SFM from which a detailed (1:2000 scale) geologic map was created. The geologic map includes formation, fault, and breccia contacts. The digital outcrop model was used to interpret three-dimensional spatial relationships of breccia bodies with respect to the current understanding of the tectonic and stratigraphic evolution of the SFM. The data presented here are used to discuss potential stratigraphic, temporal, and tectonic controls on the formation of caves within the study area that eventually collapsed to form the breccias currently exposed in outcrop.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"The great American carbonate bank: The geology and economic resources of the Cambrian-Ordovician Sauk megasequence of Laurentia","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"AAPG","publisherLocation":"Tulsa, OK","doi":"10.1306/13331521M983516","usgsCitation":"Bellian, J.A., Kerans, C., and Repetski, J.E., 2012, Digital outcrop model of stratigraphy and breccias of the southern Franklin Mountains, El Paso, Texas, chap. <i>of</i> The great American carbonate bank: The geology and economic resources of the Cambrian-Ordovician Sauk megasequence of Laurentia: AAPG Memoir, v. 98, p. 909-939, https://doi.org/10.1306/13331521M983516.","productDescription":"31 p.","startPage":"909","endPage":"939","numberOfPages":"31","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-042949","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":270970,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":298191,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://archives.datapages.com/data/specpubs/memoir98/CHAPTER36/CHAPTER36.HTM"}],"country":"United States","state":"Texas","city":"El Paso","otherGeospatial":"Franklin Mountains","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -106.56944274902344,\n              31.766121200173643\n            ],\n            [\n              -106.56944274902344,\n              31.99875937194732\n            ],\n            [\n              -106.43074035644531,\n              31.99875937194732\n            ],\n            [\n              -106.43074035644531,\n              31.766121200173643\n            ],\n            [\n              -106.56944274902344,\n              31.766121200173643\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"98","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"516e64d8e4b00154e4368b5b","contributors":{"editors":[{"text":"Derby, James R.","contributorId":68207,"corporation":false,"usgs":false,"family":"Derby","given":"James","email":"","middleInitial":"R.","affiliations":[{"id":13326,"text":"The University of Tulsa","active":true,"usgs":false}],"preferred":false,"id":509234,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Fritz, R.D.","contributorId":113600,"corporation":false,"usgs":true,"family":"Fritz","given":"R.D.","email":"","affiliations":[],"preferred":false,"id":509237,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Longacre, S.A.","contributorId":112394,"corporation":false,"usgs":true,"family":"Longacre","given":"S.A.","email":"","affiliations":[],"preferred":false,"id":509235,"contributorType":{"id":2,"text":"Editors"},"rank":3},{"text":"Morgan, W.A.","contributorId":21228,"corporation":false,"usgs":true,"family":"Morgan","given":"W.A.","email":"","affiliations":[],"preferred":false,"id":509233,"contributorType":{"id":2,"text":"Editors"},"rank":4},{"text":"Sternbach, C.A.","contributorId":113505,"corporation":false,"usgs":true,"family":"Sternbach","given":"C.A.","email":"","affiliations":[],"preferred":false,"id":509236,"contributorType":{"id":2,"text":"Editors"},"rank":5}],"authors":[{"text":"Bellian, Jerome A.","contributorId":139515,"corporation":false,"usgs":false,"family":"Bellian","given":"Jerome","email":"","middleInitial":"A.","affiliations":[{"id":12430,"text":"University of Texas at Austin","active":true,"usgs":false}],"preferred":false,"id":541613,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kerans, Charles","contributorId":75838,"corporation":false,"usgs":false,"family":"Kerans","given":"Charles","email":"","affiliations":[{"id":12430,"text":"University of Texas at Austin","active":true,"usgs":false}],"preferred":false,"id":474848,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Repetski, John E. 0000-0002-2298-7120 jrepetski@usgs.gov","orcid":"https://orcid.org/0000-0002-2298-7120","contributorId":2596,"corporation":false,"usgs":true,"family":"Repetski","given":"John","email":"jrepetski@usgs.gov","middleInitial":"E.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":474847,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70032224,"text":"70032224 - 2012 - Distribution and geochemistry of selected trace elements in the Sacramento River near Keswick Reservoir","interactions":[],"lastModifiedDate":"2020-12-03T22:46:11.980694","indexId":"70032224","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1213,"text":"Chemical Geology","active":true,"publicationSubtype":{"id":10}},"title":"Distribution and geochemistry of selected trace elements in the Sacramento River near Keswick Reservoir","docAbstract":"<p id=\"sp0005\">The effect of heavy metals from the Iron Mountain Mines (IMM) Superfund site on the upper Sacramento River is examined using data from water and bed sediment samples collected during 1996–97. Relative to surrounding waters, aluminum, cadmium, cobalt, copper, iron, lead, manganese, thallium, zinc and the rare-earth elements (REE) were all present in high concentrations in effluent from Spring Creek Reservoir (SCR), which enters into the Sacramento River in the Spring Creek Arm of Keswick Reservoir. SCR was constructed in part to regulate the flow of acidic, metal-rich waters draining the IMM Superfund site. Although virtually all of these metals exist in SCR in the dissolved form, upon entering Keswick Reservoir they at least partially converted via precipitation and/or adsorption to the particulate phase. In spite of this, few of the metals settled out; instead the vast majority was transported colloidally down the Sacramento River at least to Bend Bridge, 67&nbsp;km from Keswick Dam.</p><p id=\"sp0010\">The geochemical influence of IMM on the upper Sacramento River was variable, chiefly dependent on the flow of Spring Creek. Although the average flow of the Sacramento River at Keswick Dam is 250&nbsp;m<sup>3</sup>/s (cubic meters per second), even flows as low as 0.3&nbsp;m<sup>3</sup>/s from Spring Creek were sufficient to account for more than 15% of the metals loading at Bend Bridge, and these proportions increased with increasing Spring Creek flow.</p><p id=\"sp0015\">The dissolved proportion of the total bioavailable load was dependent on the element but steadily decreased for all metals, from near 100% in Spring Creek to values (for some elements) of less than 1% at Bend Bridge; failure to account for the suspended sediment load in assessments of the effect of metals transport in the Sacramento River can result in estimates which are low by as much as a factor of 100.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.chemgeo.2011.12.025","issn":"00092541","usgsCitation":"Antweiler, R.C., Taylor, H.E., and Alpers, C.N., 2012, Distribution and geochemistry of selected trace elements in the Sacramento River near Keswick Reservoir: Chemical Geology, v. 298-299, p. 70-78, https://doi.org/10.1016/j.chemgeo.2011.12.025.","productDescription":"9 p.","startPage":"70","endPage":"78","numberOfPages":"9","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":242543,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":214792,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.chemgeo.2011.12.025"}],"country":"United States","state":"California","otherGeospatial":"Sacramento River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -123.20068359374999,\n              40.317231732315236\n            ],\n            [\n              -121.72302246093749,\n              40.317231732315236\n            ],\n            [\n              -121.72302246093749,\n              41.47566020027821\n            ],\n            [\n              -123.20068359374999,\n              41.47566020027821\n            ],\n            [\n              -123.20068359374999,\n              40.317231732315236\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"298-299","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a028de4b0c8380cd500ce","contributors":{"authors":[{"text":"Antweiler, Ronald C. 0000-0001-5652-6034 antweil@usgs.gov","orcid":"https://orcid.org/0000-0001-5652-6034","contributorId":1481,"corporation":false,"usgs":true,"family":"Antweiler","given":"Ronald","email":"antweil@usgs.gov","middleInitial":"C.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":435115,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Taylor, Howard E. hetaylor@usgs.gov","contributorId":1551,"corporation":false,"usgs":true,"family":"Taylor","given":"Howard","email":"hetaylor@usgs.gov","middleInitial":"E.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":435114,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Alpers, Charles N. 0000-0001-6945-7365 cnalpers@usgs.gov","orcid":"https://orcid.org/0000-0001-6945-7365","contributorId":411,"corporation":false,"usgs":true,"family":"Alpers","given":"Charles","email":"cnalpers@usgs.gov","middleInitial":"N.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":435116,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70042461,"text":"70042461 - 2012 - Appendix A: other methods for estimating trends of Arctic birds","interactions":[],"lastModifiedDate":"2015-01-16T11:18:45","indexId":"70042461","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Appendix A: other methods for estimating trends of Arctic birds","docAbstract":"<p>The Arctic PRISM was designed to determine shorebird population size and trend. During an extensive peer review of PRISM, some reviewers suggested that measuring demographic rates or monitoring shorebirds on migration would be more appropriate than estimating population size on the breeding grounds. However, each method has its own limitations. For demographic monitoring, an unbiased estimate based on a large sample of first-year survivorship would be extremely difficult for shorebirds in the arctic because the needed sample size would be unobtainable (in Canada at least) and the level of effort that would need to be expended (both financial and human resource-wise) would far exceed that of the current Arctic PRISM methodology. For migration monitoring, issues such as changes in use of monitored to non-monitored sites, residency times, and detection rates introduce bias that has not yet been resolved. While we believe demographic and migration monitoring are very valuable and are already components of the PRISM approach (e.g., Tier 2 sites focus on the collection of demographic data), we do not believe that either is likely to achieve the PRISM accuracy target of an 80% power to detect a 50% decline.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Arctic shorebirds in North America: a decade of monitoring","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"University of California Press","publisherLocation":"Berkeley, CA","usgsCitation":"Bart, J., Brown, S., Morrison, R., and Smith, P., 2012, Appendix A: other methods for estimating trends of Arctic birds, chap. <i>of</i> Arctic shorebirds in North America: a decade of monitoring, v. 44, p. 245-251.","productDescription":"7 p.","startPage":"245","endPage":"251","numberOfPages":"7","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-025683","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":268355,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":297339,"type":{"id":15,"text":"Index Page"},"url":"https://www.ucpress.edu/book.php?isbn=9780520273108"}],"volume":"44","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd4d8ee4b0b290850f18e4","contributors":{"editors":[{"text":"Bart, Jonathan jon_bart@usgs.gov","contributorId":57025,"corporation":false,"usgs":true,"family":"Bart","given":"Jonathan","email":"jon_bart@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":false,"id":509163,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Johnston, Victoria","contributorId":90185,"corporation":false,"usgs":true,"family":"Johnston","given":"Victoria","affiliations":[],"preferred":false,"id":509164,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"Bart, Jonathan jon_bart@usgs.gov","contributorId":57025,"corporation":false,"usgs":true,"family":"Bart","given":"Jonathan","email":"jon_bart@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":false,"id":471591,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brown, Stephen","contributorId":40096,"corporation":false,"usgs":true,"family":"Brown","given":"Stephen","affiliations":[],"preferred":false,"id":471589,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Morrison, R.I. Guy","contributorId":52003,"corporation":false,"usgs":true,"family":"Morrison","given":"R.I. Guy","affiliations":[],"preferred":false,"id":471590,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, Paul A.","contributorId":73477,"corporation":false,"usgs":true,"family":"Smith","given":"Paul A.","affiliations":[],"preferred":false,"id":471592,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70173603,"text":"70173603 - 2012 - Native rainbow smelt and nonnative alewife distribution related to temperature and light gradients in Lake Champlain","interactions":[],"lastModifiedDate":"2016-06-07T16:04:12","indexId":"70173603","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Native rainbow smelt and nonnative alewife distribution related to temperature and light gradients in Lake Champlain","docAbstract":"<p><span>Alewife (</span><i>Alosa pseudoharengus</i><span>) recently became established in Lake Champlain and may compete with native rainbow smelt (</span><i>Osmerus mordax</i><span>) for food or consume larval rainbow smelt. The strength of this effect depends partly on the spatial and temporal overlap of different age groups of the two species; therefore, we need a better understanding of factors affecting alewife and rainbow smelt distributions in Lake Champlain. We used hydroacoustics, trawls, and gill nets to document vertical fish distribution, and recorded environmental data during 16&nbsp;day&ndash;night surveys over two years. Temperature, temperature change, and light were all predictors of adult and age-0 rainbow smelt distribution, and temperature and light were predictors of age-0 alewives' distribution (based on GAMM models evaluated with AIC). Adult alewives were 5&ndash;30&nbsp;m shallower and age-0 alewives were 2&ndash;15&nbsp;m shallower than their rainbow smelt counterparts. Adult rainbow smelt distribution overlapped with age-0 rainbow smelt and age-0 alewives near the thermocline (10&ndash;25&nbsp;m), whereas adult alewives were shallower (0&ndash;6&nbsp;m) and overlapped with age-0 alewives and rainbow smelt in the epilimnion. Adult rainbow smelt were in water &lt;&nbsp;10&ndash;12&nbsp;&deg;C, whereas age-0 rainbow smelt were in 10&ndash;20&nbsp;&deg;C, and adult and age-0 alewives were in 15&ndash;22&nbsp;&deg;C water. Predicting these species distributions is necessary for quantifying the strength of predatory and competitive interactions between alewife and rainbow smelt, as well as between alewife and other fish species in Lake Champlain.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2011.06.002","usgsCitation":"Parrish, D.L., Simonin, P.W., Rudstam, L.G., Sullivan, P., and Pientka, B., 2012, Native rainbow smelt and nonnative alewife distribution related to temperature and light gradients in Lake Champlain: Journal of Great Lakes Research, v. 38, no. 1, p. 115-122, https://doi.org/10.1016/j.jglr.2011.06.002.","productDescription":"8 p.","startPage":"115","endPage":"122","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-025329","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":323221,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Vermont","otherGeospatial":"Lake Champlain","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -73.22250366210938,\n              44.457309801319305\n            ],\n            [\n              -73.29391479492188,\n              44.46025037930627\n            ],\n            [\n              -73.33511352539062,\n              44.3670601700202\n            ],\n            [\n              -73.21563720703125,\n              44.37196862007497\n            ],\n            [\n              -73.21975708007812,\n              44.449467536006935\n            ],\n            [\n              -73.22250366210938,\n              44.457309801319305\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"38","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5757f062e4b04f417c24dcf6","contributors":{"authors":[{"text":"Parrish, Donna L. 0000-0001-9693-6329 dparrish@usgs.gov","orcid":"https://orcid.org/0000-0001-9693-6329","contributorId":138661,"corporation":false,"usgs":true,"family":"Parrish","given":"Donna","email":"dparrish@usgs.gov","middleInitial":"L.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":637392,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Simonin, Paul W.","contributorId":171499,"corporation":false,"usgs":false,"family":"Simonin","given":"Paul","email":"","middleInitial":"W.","affiliations":[{"id":18160,"text":"Rubenstein School of Environment and Natural Resources, University of Vermont","active":true,"usgs":false}],"preferred":false,"id":637741,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rudstam, Lars G.","contributorId":56609,"corporation":false,"usgs":false,"family":"Rudstam","given":"Lars","email":"","middleInitial":"G.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":637742,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sullivan, Patrick J.","contributorId":97813,"corporation":false,"usgs":true,"family":"Sullivan","given":"Patrick J.","affiliations":[],"preferred":false,"id":637743,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pientka, Bernard","contributorId":171500,"corporation":false,"usgs":false,"family":"Pientka","given":"Bernard","email":"","affiliations":[],"preferred":false,"id":637744,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70044174,"text":"70044174 - 2012 - Magnetostratigraphy susceptibility for the Guadalupian Series GSSPs (Middle Permian) in Guadalupe Mountains National Park and adjacent areas in West Texas","interactions":[],"lastModifiedDate":"2013-04-22T10:44:52","indexId":"70044174","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1791,"text":"Geological Society, London, Special Publications","active":true,"publicationSubtype":{"id":10}},"title":"Magnetostratigraphy susceptibility for the Guadalupian Series GSSPs (Middle Permian) in Guadalupe Mountains National Park and adjacent areas in West Texas","docAbstract":"Here we establish a magnetostratigraphy susceptibility zonation for the three Middle Permian Global boundary Stratotype Sections and Points (GSSPs) that have recently been defined, located in Guadalupe Mountains National Park, West Texas, USA. These GSSPs, all within the Middle Permian Guadalupian Series, define (1) the base of the Roadian Stage (base of the Guadalupian Series), (2) the base of the Wordian Stage and (3) the base of the Capitanian Stage. Data from two additional stratigraphic successions in the region, equivalent in age to the Kungurian–Roadian and Wordian–Capitanian boundary intervals, are also reported. Based on low-field, mass specific magnetic susceptibility (χ) measurements of 706 closely spaced samples from these stratigraphic sections and time-series analysis of one of these sections, we (1) define the magnetostratigraphy susceptibility zonation for the three Guadalupian Series Global boundary Stratotype Sections and Points; (2) demonstrate that χ datasets provide a proxy for climate cyclicity; (3) give quantitative estimates of the time it took for some of these sediments to accumulate; (4) give the rates at which sediments were accumulated; (5) allow more precise correlation to equivalent sections in the region; (6) identify anomalous stratigraphic horizons; and (7) give estimates for timing and duration of geological events within sections.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Geological Society, London, Special Publications","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"The Geological Society","publisherLocation":"London, UK","doi":"10.1144/SP373.1","usgsCitation":"Wardlaw, B.R., Ellwood, B.B., Lambert, L.L., Tomkin, J.H., Bell, G.L., and Nestell, G.P., 2012, Magnetostratigraphy susceptibility for the Guadalupian Series GSSPs (Middle Permian) in Guadalupe Mountains National Park and adjacent areas in West Texas: Geological Society, London, Special Publications, v. 373, p. 21-21, https://doi.org/10.1144/SP373.1.","startPage":"21","endPage":"21","numberOfPages":"1","additionalOnlineFiles":"N","ipdsId":"IP-034315","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":271339,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":271338,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1144/SP373.1"}],"country":"United States","state":"Texas","volume":"373","noUsgsAuthors":false,"publicationDate":"2012-08-14","publicationStatus":"PW","scienceBaseUri":"51765beae4b0f989f99e00fb","contributors":{"authors":[{"text":"Wardlaw, Bruce R. bwardlaw@usgs.gov","contributorId":266,"corporation":false,"usgs":true,"family":"Wardlaw","given":"Bruce","email":"bwardlaw@usgs.gov","middleInitial":"R.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":474985,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ellwood, Brooks B.","contributorId":44814,"corporation":false,"usgs":false,"family":"Ellwood","given":"Brooks","email":"","middleInitial":"B.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":474988,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lambert, Lance L.","contributorId":9550,"corporation":false,"usgs":true,"family":"Lambert","given":"Lance","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":474986,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tomkin, Jonathan H.","contributorId":85860,"corporation":false,"usgs":true,"family":"Tomkin","given":"Jonathan","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":474990,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bell, Gordon L.","contributorId":69639,"corporation":false,"usgs":true,"family":"Bell","given":"Gordon","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":474989,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nestell, Galina P.","contributorId":22651,"corporation":false,"usgs":false,"family":"Nestell","given":"Galina","email":"","middleInitial":"P.","affiliations":[{"id":12734,"text":"University of Texas at Arlington","active":true,"usgs":false}],"preferred":false,"id":474987,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70043839,"text":"70043839 - 2012 - Molecular characterization and comparison of shale oils generated by different pyrolysis methods","interactions":[],"lastModifiedDate":"2013-02-26T15:17:11","indexId":"70043839","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1506,"text":"Energy & Fuels","active":true,"publicationSubtype":{"id":10}},"title":"Molecular characterization and comparison of shale oils generated by different pyrolysis methods","docAbstract":"Shale oils generated using different laboratory pyrolysis methods have been studied using standard oil characterization methods as well as Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) with electrospray ionization (ESI) and atmospheric photoionization (APPI) to assess differences in molecular composition. The pyrolysis oils were generated from samples of the Mahogany zone oil shale of the Eocene Green River Formation collected from outcrops in the Piceance Basin, Colorado, using three pyrolysis systems under conditions relevant to surface and in situ retorting approaches. Significant variations were observed in the shale oils, particularly the degree of conjugation of the constituent molecules and the distribution of nitrogen-containing compound classes. Comparison of FT-ICR MS results to other oil characteristics, such as specific gravity; saturate, aromatic, resin, asphaltene (SARA) distribution; and carbon number distribution determined by gas chromatography, indicated correspondence between higher average double bond equivalence (DBE) values and increasing asphaltene content. The results show that, based on the shale oil DBE distributions, highly conjugated species are enriched in samples produced under low pressure, high temperature conditions, and under high pressure, moderate temperature conditions in the presence of water. We also report, for the first time in any petroleum-like substance, the presence of N<sub>4</sub> class compounds based on FT-ICR MS data. Using double bond equivalence and carbon number distributions, structures for the N<sub>4</sub> class and other nitrogen-containing compounds are proposed.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Energy & Fuels","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"ACS Publications","publisherLocation":"Washington, D.C.","doi":"10.1021/ef201517a","usgsCitation":"Birdwell, J.E., Jin, J.M., and Kim, S., 2012, Molecular characterization and comparison of shale oils generated by different pyrolysis methods: Energy & Fuels, v. 26, https://doi.org/10.1021/ef201517a.","numberOfPages":"32","ipdsId":"IP-033210","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":268411,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":268410,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1021/ef201517a"}],"volume":"26","noUsgsAuthors":false,"publicationDate":"2012-01-13","publicationStatus":"PW","scienceBaseUri":"53cd6808e4b0b29085101c5d","contributors":{"authors":[{"text":"Birdwell, Justin E. 0000-0001-8263-1452 jbirdwell@usgs.gov","orcid":"https://orcid.org/0000-0001-8263-1452","contributorId":3302,"corporation":false,"usgs":true,"family":"Birdwell","given":"Justin","email":"jbirdwell@usgs.gov","middleInitial":"E.","affiliations":[{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":474298,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jin, Jang Mi","contributorId":28877,"corporation":false,"usgs":true,"family":"Jin","given":"Jang","email":"","middleInitial":"Mi","affiliations":[],"preferred":false,"id":474299,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kim, Sunghwan","contributorId":108376,"corporation":false,"usgs":true,"family":"Kim","given":"Sunghwan","affiliations":[],"preferred":false,"id":474300,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70035366,"text":"70035366 - 2012 - Monitoring on Xi'an ground fissures deformation with TerraSAR-X data","interactions":[],"lastModifiedDate":"2012-03-12T17:21:56","indexId":"70035366","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3798,"text":"Wuhan Daxue Xuebao (Xinxi Kexue Ban)/Geomatics and Information Science of Wuhan University","active":true,"publicationSubtype":{"id":10}},"title":"Monitoring on Xi'an ground fissures deformation with TerraSAR-X data","docAbstract":"Owing to the fine resolution of TerraSAR-X data provided since 2007, this paper applied 6 TerraSAR data (strip mode) during 3rd Dec. 2009 to 23rd Mar. 2010 to detect and monitor the active fissures over Xi'an region. Three themes have been designed for high precision detection and monitoring of Xi'an-Chang'an fissures, as small baseline subsets (SBAS) to test the atmospheric effects of differential interferograms pair stepwise, 2-pass differential interferogram with very short baseline perpendicular to generate the whole deformation map with 44 days interval, and finally, corner reflector (CR) technique was used to closely monitor the relative deformation time series between two CRs settled crossing two ground fissures. Results showed that TerraSAR data are a good choice for small-scale ground fissures detection and monitoring, while special considerations should be taken for their great temporal and baseline decorrelation. Secondly, ground fissures in Xi'an were mostly detected at the joint section of stable and deformable regions. Lastly, CR-InSAR had potential ability to monitor relative deformation crossing fissures with millimeter precision.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Wuhan Daxue Xuebao (Xinxi Kexue Ban)/Geomatics and Information Science of Wuhan University","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"Chinese","issn":"16718860","usgsCitation":"Zhao, C., Zhang, Q., Zhu, W., and Lu, Z., 2012, Monitoring on Xi'an ground fissures deformation with TerraSAR-X data: Wuhan Daxue Xuebao (Xinxi Kexue Ban)/Geomatics and Information Science of Wuhan University, v. 37, no. 1, p. 81-85.","startPage":"81","endPage":"85","numberOfPages":"5","costCenters":[],"links":[{"id":243011,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"37","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a5dd0e4b0c8380cd705f0","contributors":{"authors":[{"text":"Zhao, C.","contributorId":14655,"corporation":false,"usgs":true,"family":"Zhao","given":"C.","email":"","affiliations":[],"preferred":false,"id":450351,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zhang, Q.","contributorId":84163,"corporation":false,"usgs":true,"family":"Zhang","given":"Q.","email":"","affiliations":[],"preferred":false,"id":450353,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zhu, W.","contributorId":27686,"corporation":false,"usgs":true,"family":"Zhu","given":"W.","email":"","affiliations":[],"preferred":false,"id":450352,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lu, Z.","contributorId":106241,"corporation":false,"usgs":true,"family":"Lu","given":"Z.","affiliations":[],"preferred":false,"id":450354,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70042820,"text":"70042820 - 2012 - Physical setting and natural sources of exposure to carcinogenic trace elements and radionuclides in Lahontan Valley, Nevada","interactions":[],"lastModifiedDate":"2013-03-12T16:00:08","indexId":"70042820","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1219,"text":"Chemico-Biological Interactions","active":true,"publicationSubtype":{"id":10}},"title":"Physical setting and natural sources of exposure to carcinogenic trace elements and radionuclides in Lahontan Valley, Nevada","docAbstract":"In Lahontan Valley, Nevada, arsenic, cobalt, tungsten, uranium, radon, and polonium-210 are carcinogens that occur naturally in sediments and groundwater. Arsenic and cobalt are principally derived from erosion of volcanic rocks in the local mountains and tungsten and uranium are derived from erosion of granitic rocks in headwater reaches of the Carson River. Radon and 210Po originate from radioactive decay of uranium in the sediments. Arsenic, aluminum, cobalt, iron, and manganese concentrations in household dust suggest it is derived from the local soils. Excess zinc and chromium in the dust are probably derived from the vacuum cleaner used to collect the dust, or household sources such as the furnace. Some samples have more than 5 times more cobalt in the dust than in the local soil, but whether the source of the excess cobalt is anthropogenic or natural cannot be determined with the available data. Cobalt concentrations are low in groundwater, but arsenic, uranium, radon, and <sup>210</sup>Po concentrations often exceed human-health standards, and sometime greatly exceed them. Exposure to radon and its decay products in drinking water can vary significantly depending on when during the day that the water is consumed. Although the data suggests there have been no long term changes in groundwater chemistry that corresponds to the Lahontan Valley leukemia cluster, the occurrence of the very unusual leukemia cluster in an area with numerous <sup>210</sup>Po and arsenic contaminated wells is striking, particularly in conjunction with the exceptionally high levels of urinary tungsten in Lahontan Valley residents. Additional research is needed on potential exposure pathways involving food or inhalation, and on synergistic effects of mixtures of these natural contaminants on susceptibility to development of leukemia.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Chemico-Biological Interactions","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.cbi.2011.04.004","usgsCitation":"Seiler, R.L., 2012, Physical setting and natural sources of exposure to carcinogenic trace elements and radionuclides in Lahontan Valley, Nevada: Chemico-Biological Interactions, v. 196, no. 3, p. 79-86, https://doi.org/10.1016/j.cbi.2011.04.004.","productDescription":"8 p.","startPage":"79","endPage":"86","numberOfPages":"8","additionalOnlineFiles":"N","ipdsId":"IP-023222","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":269184,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":269183,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.cbi.2011.04.004"}],"country":"United States","state":"Nevada","otherGeospatial":"Lahontan Valley","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -119.127414,39.463302 ], [ -119.127414,39.766719 ], [ -118.724621,39.766719 ], [ -118.724621,39.463302 ], [ -119.127414,39.463302 ] ] ] } } ] }","volume":"196","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51404e8ae4b089809dbf44b9","contributors":{"authors":[{"text":"Seiler, Ralph L.","contributorId":13609,"corporation":false,"usgs":true,"family":"Seiler","given":"Ralph","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":472326,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70035458,"text":"70035458 - 2012 - Geochemical constraints on adakites of different origins and copper mineralization","interactions":[],"lastModifiedDate":"2020-11-13T20:05:13.127307","indexId":"70035458","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2309,"text":"Journal of Geology","active":true,"publicationSubtype":{"id":10}},"title":"Geochemical constraints on adakites of different origins and copper mineralization","docAbstract":"<p><span>The petrogenesis of adakites holds important clues to the formation of the continental crust and copper ± gold porphyry mineralization. However, it remains highly debated as to whether adakites form by slab melting, by partial melting of the lower continental crust, or by fractional crystallization of normal arc magmas. Here, we show that to form adakitic signature, partial melting of a subducting oceanic slab would require high pressure at depths of &gt;50 km, whereas partial melting of the lower continental crust would require the presence of plagioclase and thus shallower depths and additional water. These two types of adakites can be discriminated using geochemical indexes. Compiled data show that adakites from circum-Pacific regions, which have close affinity to subduction of young hot oceanic plate, can be clearly discriminated from adakites from the Dabie Mountains and the Tibetan Plateau, which have been attributed to partial melting of continental crust, in Sr/Y-versus-La/Yb diagram. Given that oceanic crust has copper concentrations about two times higher than those in the continental crust, whereas the high oxygen fugacity in the subduction environment promotes the release of copper during partial melting, slab melting provides the most efficient mechanism to concentrate copper and gold; slab melts would be more than two times greater in copper (and also gold) concentrations than lower continental crust melts and normal arc magmas. Thus, identification of slab melt adakites is important for predicting exploration targets for copper- and gold-porphyry ore deposits. This explains the close association of ridge subduction with large porphyry copper deposits because ridge subduction is the most favorable place for slab melting.</span></p>","language":"English","publisher":"The University of Chicago Press Books","doi":"10.1086/662736","issn":"00221376","usgsCitation":"Sun, W., Ling, M., Chung, S., Ding, X., Yang, X., Liang, H., Fan, W., Goldfarb, R., and Yin, Q., 2012, Geochemical constraints on adakites of different origins and copper mineralization: Journal of Geology, v. 120, no. 1, p. 105-120, https://doi.org/10.1086/662736.","productDescription":"16 p.","startPage":"105","endPage":"120","costCenters":[],"links":[{"id":243369,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":215557,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1086/662736"}],"country":"China","otherGeospatial":"Dabie Mountains and the Tibetan Plateau","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              101.513671875,\n              22.43134015636061\n            ],\n            [\n              108.720703125,\n              25.958044673317843\n            ],\n            [\n              107.57812499999999,\n              30.600093873550072\n            ],\n            [\n              102.65625,\n              31.50362930577303\n            ],\n            [\n              99.49218749999999,\n              29.152161283318915\n            ],\n            [\n              99.580078125,\n              25.64152637306577\n            ],\n            [\n              101.513671875,\n              22.43134015636061\n            ]\n          ]\n        ]\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      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X.","contributorId":49990,"corporation":false,"usgs":true,"family":"Ding","given":"X.","email":"","affiliations":[],"preferred":false,"id":450764,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Yang, X.-Y.","contributorId":9489,"corporation":false,"usgs":true,"family":"Yang","given":"X.-Y.","email":"","affiliations":[],"preferred":false,"id":450760,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Liang, H.-Y.","contributorId":88576,"corporation":false,"usgs":true,"family":"Liang","given":"H.-Y.","email":"","affiliations":[],"preferred":false,"id":450767,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Fan, W.-M.","contributorId":100217,"corporation":false,"usgs":true,"family":"Fan","given":"W.-M.","email":"","affiliations":[],"preferred":false,"id":450768,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Goldfarb, R.","contributorId":43113,"corporation":false,"usgs":true,"family":"Goldfarb","given":"R.","email":"","affiliations":[],"preferred":false,"id":450763,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Yin, Q.-Z.","contributorId":64056,"corporation":false,"usgs":true,"family":"Yin","given":"Q.-Z.","email":"","affiliations":[],"preferred":false,"id":450765,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70173757,"text":"70173757 - 2012 - Spatio-temporal variation in male white-tailed deer harvest rates in Pennsylvania: Implications for estimating abundance","interactions":[],"lastModifiedDate":"2016-08-24T12:28:25","indexId":"70173757","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Spatio-temporal variation in male white-tailed deer harvest rates in Pennsylvania: Implications for estimating abundance","docAbstract":"<p><span>The performance of 2 popular methods that use age-at-harvest data to estimate abundance of white-tailed deer is contingent on assumptions about variation in estimates of subadult (1.5&thinsp;yr old) and adult (&ge;2.5&thinsp;yr old) male harvest rates. Auxiliary data (e.g., estimates of survival or harvest rates from radiocollared animals) can be used to relax some assumptions, but unless these population parameters exhibit limited temporal or spatial variation, these auxiliary data may not improve accuracy. Unfortunately maintaining sufficient sample sizes of radiocollared deer for parameter estimation in every wildlife management unit (WMU) is not feasible for most state agencies. We monitored the fates of 397 subadult and 225 adult male white-tailed deer across 4 WMUs from 2002 to 2008 using radio telemetry. We investigated spatial and temporal variation in harvest rates and investigated covariates related to the patterns observed. We found that most variation in harvest rates was explained spatially and that adult harvest rates (0.36&ndash;0.69) were more variable among study areas than subadult harvest rates (0.26&ndash;0.42). We found that hunter effort during the archery and firearms season best explained variation in harvest rates of adult males among WMUs, whereas hunter effort during only the firearms season best explained harvest rates for subadult males. From a population estimation perspective, it is advantageous that most variation was spatial and explained by a readily obtained covariate (hunter effort). However, harvest rates may vary if hunting regulations or hunter behavior change, requiring additional field studies to obtain accurate estimates of harvest rates.&nbsp;</span></p>","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.249","usgsCitation":"Norton, A.S., Diefenbach, D.R., Wallingford, B.D., and Rosenberry, C.S., 2012, Spatio-temporal variation in male white-tailed deer harvest rates in Pennsylvania: Implications for estimating abundance: Journal of Wildlife Management, v. 76, no. 1, p. 136-143, https://doi.org/10.1002/jwmg.249.","productDescription":"8 p.","startPage":"136","endPage":"143","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-025517","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":323319,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Pennsylvania","county":"Armstrong County, Centre County, Clearfield County, Clinton County, Cumberland County, Juniata County, Perry 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,{"id":70042453,"text":"70042453 - 2012 - Shorebird surveys in western Alaska","interactions":[],"lastModifiedDate":"2022-12-21T16:48:44.16649","indexId":"70042453","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"3","title":"Shorebird surveys in western Alaska","docAbstract":"<p>Surveys for breeding shorebirds were conducted during 2001-2002 in four National Wildlife Refuges (NWRs) in western Alaska - Alaska Maritime, Alaska Peninsula, Yukon Delta and Selawik. The sizes of our study areas on and adjacent to these four refuges were 9,243 km<sup>2</sup>, 24,493 km<sup>2</sup>, 853 km<sup>2</sup>, and 15,170 km<sup>2</sup>, respectively. Eleven sites were selected non-randomly, 3 in the Alaska Maritime NWR, 6 in the Alaska Peninsula, and one each in the other two NWRs. Survey and analytic methods are described in Chapter 2. Rapid surveys were conducted on 224 plots; 2,163 indicated pairs of shorebirds were recorded of which 1,485 were judged to be nesting in the surveyed plots. Detection ratios were estimated using intensive plot data from northern Alaska as well as from two plots on the Yukon Delta NWR. The highest estimated densities (shorebirds/km<sup>2</sup>) were on the Yukon Delta Study Area: 416 in wetlands and 300 in moist areas. The estimated densities on the Alaska Peninsula Study Area were 118 in wetlands and 62 in uplands. Other densities were markedly lower. Estimated numbers of shorebirds were 62,000 (CV = 0.58), 1,804,000 (CV = 0.32), 310,000 (CV = 0.11), and 390,000 (CV = 0.35), in the Alaska Maritime, Alaska Peninsula, Yukon Delta, and Selawik study areas, respectively. The former two estimates were affected by selection bias of unknown magnitude and so should be regarded with caution. A small estimate was generated for the Yukon Delta Study Area because it covered only about 1% of the Yukon Delta NWR. We identify several species-specific estimates from our study which appear inconsistent with previous continental estimates. This pilot study provides preliminary estimates of species composition and density in the surveyed areas. By incorporating several region-specific modifications to the sampling protocols for future surveys, we believe that the Arctic PRISM method is suitable for covering large areas in western Alaska.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Arctic shorebirds in North America: A decade of monitoring","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"University of California Press","publisherLocation":"Berkeley, CA","usgsCitation":"McCaffery, B.J., Bart, J., Wightman, C., and Krueper, D.J., 2012, Shorebird surveys in western Alaska, chap. 3 <i>of</i> Arctic shorebirds in North America: A decade of monitoring, v. 44, p. 17-36.","productDescription":"10 p.","startPage":"17","endPage":"36","numberOfPages":"10","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-026453","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":268325,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":297331,"type":{"id":15,"text":"Index Page"},"url":"https://www.ucpress.edu/book.php?isbn=9780520273108"}],"country":"United States","state":"Alaska","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -159.83606127608508,\n              67.83094206266881\n            ],\n            [\n              -168.60315969175733,\n              67.31587290572091\n            ],\n            [\n              -168.04564134058197,\n              59.94938901312631\n            ],\n            [\n              -160.65923179948007,\n              57.14283500068541\n            ],\n            [\n              -176.3059056833646,\n              53.361921209719895\n            ],\n            [\n              -178.00466802783237,\n              50.46694403512976\n            ],\n            [\n              -152.1254855949343,\n              57.554123066073885\n            ],\n            [\n              -159.83606127608508,\n              67.83094206266881\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"44","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd72a0e4b0b290851086e9","contributors":{"authors":[{"text":"McCaffery, Brian J.","contributorId":37617,"corporation":false,"usgs":true,"family":"McCaffery","given":"Brian","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":471575,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bart, Jonathan jon_bart@usgs.gov","contributorId":57025,"corporation":false,"usgs":true,"family":"Bart","given":"Jonathan","email":"jon_bart@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":false,"id":471576,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wightman, Catherine","contributorId":66568,"corporation":false,"usgs":true,"family":"Wightman","given":"Catherine","affiliations":[],"preferred":false,"id":471577,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Krueper, David J.","contributorId":103752,"corporation":false,"usgs":true,"family":"Krueper","given":"David","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":471578,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70032294,"text":"70032294 - 2012 - The effect of diagenesis and fluid migration on rare earth element distribution in pore fluids of the northern Cascadia accretionary margin","interactions":[],"lastModifiedDate":"2013-04-25T13:32:35","indexId":"70032294","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1213,"text":"Chemical Geology","active":true,"publicationSubtype":{"id":10}},"title":"The effect of diagenesis and fluid migration on rare earth element distribution in pore fluids of the northern Cascadia accretionary margin","docAbstract":"Analytical challenges in obtaining high quality measurements of rare earth elements (REEs) from small pore fluid volumes have limited the application of REEs as deep fluid geochemical tracers. Using a recently developed analytical technique, we analyzed REEs from pore fluids collected from Sites U1325 and U1329, drilled on the northern Cascadia margin during the Integrated Ocean Drilling Program (IODP) Expedition 311, to investigate the REE behavior during diagenesis and their utility as tracers of deep fluid migration. These sites were selected because they represent contrasting settings on an accretionary margin: a ponded basin at the toe of the margin, and the landward Tofino Basin near the shelf's edge. REE concentrations of pore fluid in the methanogenic zone at Sites U1325 and U1329 correlate positively with concentrations of dissolved organic carbon (DOC) and alkalinity. Fractionations across the REE series are driven by preferential complexation of the heavy REEs. Simultaneous enrichment of diagenetic indicators (DOC and alkalinity) and of REEs (in particular the heavy elements Ho to Lu), suggests that the heavy REEs are released during particulate organic carbon (POC) degradation and are subsequently chelated by DOC. REE concentrations are greater at Site U1325, a site where shorter residence times of POC in sulfate-bearing redox zones may enhance REE burial efficiency within sulfidic and methanogenic sediment zones where REE release ensues.  Cross-plots of La concentrations versus Cl, Li and Sr delineate a distinct field for the deep fluids (z > 75 mbsf) at Site U1329, and indicate the presence of a fluid not observed at the other sites drilled on the Cascadia margin. Changes in REE patterns, the presence of a positive Eu anomaly, and other available geochemical data for this site suggest a complex hydrology and possible interaction with the igneous Crescent Terrane, located east of the drilled transect.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Chemical Geology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.chemgeo.2011.10.010","issn":"00092541","usgsCitation":"Kim, J., Torres, M.E., Haley, B.A., Kastner, M., Pohlman, J., Riedel, M., and Lee, Y., 2012, The effect of diagenesis and fluid migration on rare earth element distribution in pore fluids of the northern Cascadia accretionary margin: Chemical Geology, v. 291, p. 152-165, https://doi.org/10.1016/j.chemgeo.2011.10.010.","productDescription":"14 p.","startPage":"152","endPage":"165","numberOfPages":"14","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":214915,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.chemgeo.2011.10.010"},{"id":242675,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada;United States","city":"Vancouver","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -0.01611111111111111,0.0011111111111111111 ], [ -0.01611111111111111,0.001388888888888889 ], [ -0.01611111111111111,0.001388888888888889 ], [ -0.01611111111111111,0.0011111111111111111 ], [ -0.01611111111111111,0.0011111111111111111 ] ] ] } } ] }","volume":"291","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505bab1fe4b08c986b322c30","contributors":{"authors":[{"text":"Kim, Ji-Hoon","contributorId":105547,"corporation":false,"usgs":true,"family":"Kim","given":"Ji-Hoon","email":"","affiliations":[],"preferred":false,"id":435487,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Torres, Marta E.","contributorId":33546,"corporation":false,"usgs":true,"family":"Torres","given":"Marta","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":435483,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haley, Brian A.","contributorId":43996,"corporation":false,"usgs":true,"family":"Haley","given":"Brian","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":435484,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kastner, Miriam","contributorId":24187,"corporation":false,"usgs":true,"family":"Kastner","given":"Miriam","email":"","affiliations":[],"preferred":false,"id":435482,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pohlman, John W.","contributorId":95288,"corporation":false,"usgs":true,"family":"Pohlman","given":"John W.","affiliations":[],"preferred":false,"id":435486,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Riedel, Michael","contributorId":7518,"corporation":false,"usgs":true,"family":"Riedel","given":"Michael","email":"","affiliations":[],"preferred":false,"id":435481,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lee, Young-Joo","contributorId":82548,"corporation":false,"usgs":true,"family":"Lee","given":"Young-Joo","email":"","affiliations":[],"preferred":false,"id":435485,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70032301,"text":"70032301 - 2012 - Trophic cascades linking wolves (Canis lupus), coyotes (Canis latrans), and small mammals","interactions":[],"lastModifiedDate":"2012-03-12T17:21:29","indexId":"70032301","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1176,"text":"Canadian Journal of Zoology","active":true,"publicationSubtype":{"id":10}},"title":"Trophic cascades linking wolves (Canis lupus), coyotes (Canis latrans), and small mammals","docAbstract":"When large carnivores are extirpated from ecosystems that evolved with apex predators, these systems can change at the herbivore and plant trophic levels. Such changes across trophic levels are called cascading effects and they are very important to conservation. Studies on the effects of reintroduced wolves in Yellowstone National Park have examined the interaction pathway of wolves (Canis lupus L., 1758) to ungulates to plants. This study examines the interaction effects of wolves to coyotes to rodents (reversing mesopredator release in the absence of wolves). Coyotes (Canis latrans Say, 1823) generally avoided areas near a wolf den. However, when in the proximity of a den, they used woody habitats (pine or sage) compared with herbaceous habitats (grass or forb or sedge)- when they were away from the wolf den. Our data suggested a significant increase in rodent numbers, particularly voles (genus Microtus Schrank, 1798), during the 3-year study on plots that were within 3 km of the wolf den, but we did not detect a significant change in rodent numbers over time for more distant plots. Predation by coyotes may have depressed numbers of small mammals in areas away from the wolf den. These factors indicate a top-down effect by wolves on coyotes and subsequently on the rodents of the area. Restoration of wolves could be a powerful tool for regulating predation at lower trophic levels.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Canadian Journal of Zoology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.1139/Z11-115","issn":"00084301","usgsCitation":"Miller, B., Harlow, H., Harlow, T., Biggins, D., and Ripple, W.J., 2012, Trophic cascades linking wolves (Canis lupus), coyotes (Canis latrans), and small mammals: Canadian Journal of Zoology, v. 90, no. 1, p. 70-78, https://doi.org/10.1139/Z11-115.","startPage":"70","endPage":"78","numberOfPages":"9","costCenters":[],"links":[{"id":215040,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1139/Z11-115"},{"id":242809,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"90","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505bb882e4b08c986b3278ca","contributors":{"authors":[{"text":"Miller, B.J.","contributorId":17173,"corporation":false,"usgs":true,"family":"Miller","given":"B.J.","email":"","affiliations":[],"preferred":false,"id":435505,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Harlow, H.J.","contributorId":20178,"corporation":false,"usgs":true,"family":"Harlow","given":"H.J.","email":"","affiliations":[],"preferred":false,"id":435506,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Harlow, T.S.","contributorId":15849,"corporation":false,"usgs":true,"family":"Harlow","given":"T.S.","email":"","affiliations":[],"preferred":false,"id":435504,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Biggins, D.","contributorId":53343,"corporation":false,"usgs":true,"family":"Biggins","given":"D.","affiliations":[],"preferred":false,"id":435508,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ripple, W. J.","contributorId":36333,"corporation":false,"usgs":true,"family":"Ripple","given":"W.","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":435507,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70032316,"text":"70032316 - 2012 - Intelligent estimation of spatially distributed soil physical properties","interactions":[],"lastModifiedDate":"2020-12-02T21:51:46.727938","indexId":"70032316","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1760,"text":"Geoderma","active":true,"publicationSubtype":{"id":10}},"title":"Intelligent estimation of spatially distributed soil physical properties","docAbstract":"<p><span>Spatial analysis of soil samples is often times not possible when measurements are limited in number or clustered. To obviate potential problems, we propose a new approach based on the self-organizing map (SOM) technique. This approach exploits underlying nonlinear relation of the steady-state geomorphic concave–convex nature of hillslopes (from hilltop to bottom of the valley) to spatially limited soil textural data. The topographic features are extracted from Shuttle Radar Topographic Mission elevation data; whereas soil textural (clay, silt, and sand) and hydraulic data were collected in 29 spatially random locations (50 to 75</span><span>&nbsp;</span><span>cm depth). In contrast to traditional principal component analysis, the SOM identifies relations among relief features, such as, slope, horizontal curvature and vertical curvature. Stochastic cross-validation indicates that the SOM is unbiased and provides a way to measure the magnitude of prediction uncertainty for all variables. The SOM cross-component plots of the soil texture reveals higher clay proportions at concave areas with convergent hydrological flux and lower proportions for convex areas with divergent flux. The sand ratio has an opposite pattern with higher values near the ridge and lower values near the valley. Silt has a trend similar to sand, although less pronounced. The relation between soil texture and concave–convex hillslope features reveals that subsurface weathering and transport is an important process that changed from loss-to-gain at the rectilinear hillslope point. These results illustrate that the SOM can be used to capture and predict nonlinear hillslope relations among relief, soil texture, and hydraulic conductivity data.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.geoderma.2011.11.002","issn":"00167061","usgsCitation":"Iwashita, F., Friedel, M.J., Ribeiro, G., and Fraser, S.J., 2012, Intelligent estimation of spatially distributed soil physical properties: Geoderma, v. 170, p. 1-10, https://doi.org/10.1016/j.geoderma.2011.11.002.","productDescription":"10 p.","startPage":"1","endPage":"10","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":242483,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":214733,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.geoderma.2011.11.002"}],"volume":"170","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a3c98e4b0c8380cd62e87","contributors":{"authors":[{"text":"Iwashita, F.","contributorId":96912,"corporation":false,"usgs":true,"family":"Iwashita","given":"F.","affiliations":[],"preferred":false,"id":435582,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Friedel, Michael J. 0000-0002-5060-3999 mfriedel@usgs.gov","orcid":"https://orcid.org/0000-0002-5060-3999","contributorId":595,"corporation":false,"usgs":true,"family":"Friedel","given":"Michael","email":"mfriedel@usgs.gov","middleInitial":"J.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":435581,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ribeiro, G.F.","contributorId":60032,"corporation":false,"usgs":true,"family":"Ribeiro","given":"G.F.","email":"","affiliations":[],"preferred":false,"id":435579,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fraser, Stephen J.","contributorId":87769,"corporation":false,"usgs":true,"family":"Fraser","given":"Stephen","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":435580,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70032318,"text":"70032318 - 2012 - Experimental determination of soil heat storage for the simulation of heat transport in a coastal wetland","interactions":[],"lastModifiedDate":"2020-12-03T13:01:40.584017","indexId":"70032318","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","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":"Experimental determination of soil heat storage for the simulation of heat transport in a coastal wetland","docAbstract":"<p id=\"sp010\">Two physical experiments were developed to better define the thermal interaction of wetland water and the underlying soil layer. This information is important to numerical models of flow and heat transport that have been developed to support biological studies in the South Florida coastal wetland areas. The experimental apparatus consists of two 1.32&nbsp;m diameter by 0.99&nbsp;m tall, trailer-mounted, well-insulated tanks filled with soil and water. A peat–sand–soil mixture was used to represent the wetland soil, and artificial plants were used as a surrogate for emergent wetland vegetation based on size and density observed in the field. The tanks are instrumented with thermocouples to measure vertical and horizontal temperature variations and were placed in an outdoor environment subject to solar radiation, wind, and other factors affecting the heat transfer. Instruments also measure solar radiation, relative humidity, and wind speed.</p><p id=\"sp015\">Tests indicate that heat transfer through the sides and bottoms of the tanks is negligible, so the experiments represent vertical heat transfer effects only. The temperature fluctuations measured in the vertical profile through the soil and water are used to calibrate a one-dimensional heat-transport model. The model was used to calculate the thermal conductivity of the soil. Additionally, the model was used to calculate the total heat stored in the soil. This information was then used in a lumped parameter model to calculate an effective depth of soil which provides the appropriate heat storage to be combined with the heat storage in the water column. An effective depth, in the model, of 5.1&nbsp;cm of wetland soil represents the heat storage needed to match the data taken in the tank containing 55.9&nbsp;cm of peat/sand/soil mix. The artificial low-density laboratory sawgrass reduced the solar energy absorbed by the 35.6&nbsp;cm of water and 55.9&nbsp;cm of soil at midday by less than 5%. The maximum heat transfer into the underlying peat–sand–soil mix lags behind maximum solar radiation by approximately 2&nbsp;h. A slightly longer temperature lag was observed between the maximum solar radiation and maximum water temperature both with and without soil.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2011.12.036","issn":"00221694","usgsCitation":"Swain, M., Swain, M., Lohmann, M., and Swain, E., 2012, Experimental determination of soil heat storage for the simulation of heat transport in a coastal wetland: Journal of Hydrology, v. 422-423, p. 53-62, https://doi.org/10.1016/j.jhydrol.2011.12.036.","productDescription":"10 p.","startPage":"53","endPage":"62","costCenters":[{"id":269,"text":"FLWSC-Ft. Lauderdale","active":true,"usgs":true}],"links":[{"id":242515,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"422-423","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a0dc5e4b0c8380cd531b0","contributors":{"authors":[{"text":"Swain, Michael","contributorId":79716,"corporation":false,"usgs":true,"family":"Swain","given":"Michael","email":"","affiliations":[],"preferred":false,"id":435586,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Swain, Matthew","contributorId":68126,"corporation":false,"usgs":true,"family":"Swain","given":"Matthew","email":"","affiliations":[],"preferred":false,"id":435585,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lohmann, Melinda 0000-0003-1472-159X mlohmann@usgs.gov","orcid":"https://orcid.org/0000-0003-1472-159X","contributorId":2971,"corporation":false,"usgs":true,"family":"Lohmann","given":"Melinda","email":"mlohmann@usgs.gov","affiliations":[{"id":269,"text":"FLWSC-Ft. Lauderdale","active":true,"usgs":true}],"preferred":true,"id":435583,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Swain, Eric 0000-0001-7168-708X","orcid":"https://orcid.org/0000-0001-7168-708X","contributorId":23347,"corporation":false,"usgs":true,"family":"Swain","given":"Eric","affiliations":[],"preferred":false,"id":435584,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70035364,"text":"70035364 - 2012 - Regulation leads to increases in riparian vegetation, but not direct allochthonous inputs, along the Colorado River in Grand Canyon, Arizona","interactions":[],"lastModifiedDate":"2012-03-12T17:21:56","indexId":"70035364","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3301,"text":"River Research and Applications","active":true,"publicationSubtype":{"id":10}},"title":"Regulation leads to increases in riparian vegetation, but not direct allochthonous inputs, along the Colorado River in Grand Canyon, Arizona","docAbstract":"Dams and associated river regulation have led to the expansion of riparian vegetation, especially nonnative species, along downstream ecosystems. Nonnative saltcedar is one of the dominant riparian plants along virtually every major river system in the arid western United States, but allochthonous inputs have never been quantified along a segment of a large river that is dominated by saltcedar. We developed a novel method for estimating direct allochthonous inputs along the 387km-long reach of the Colorado River downstream of Glen Canyon Dam that utilized a GIS vegetation map developed from aerial photographs, empirical and literature-derived litter production data for the dominant vegetation types, and virtual shorelines of annual peak discharge (566m  3s  -1 stage elevation). Using this method, we estimate that direct allochthonous inputs from riparian vegetation for the entire reach studied total 186metric tonsyear  -1, which represents mean inputs of 470gAFDMm  -1year  -1 of shoreline or 5.17gAFDMm  -2year  -1 of river surface. These values are comparable to allochthonous inputs for other large rivers and systems that also have sparse riparian vegetation. Nonnative saltcedar represents a significant component of annual allochthonous inputs (36% of total direct inputs) in the Colorado River. We also estimated direct allochthonous inputs for 46.8km of the Colorado River prior to closure of Glen Canyon Dam using a vegetation map that was developed from historical photographs. Regulation has led to significant increases in riparian vegetation (270-319% increase in cover, depending on stage elevation), but annual allochthonous inputs appear unaffected by regulation because of the lower flood peaks on the post-dam river. Published in 2010 by John Wiley &amp; Sons, Ltd.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"River Research and Applications","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.1002/rra.1431","issn":"15351459","usgsCitation":"Kennedy, T., and Ralston, B., 2012, Regulation leads to increases in riparian vegetation, but not direct allochthonous inputs, along the Colorado River in Grand Canyon, Arizona: River Research and Applications, v. 28, no. 1, p. 2-12, https://doi.org/10.1002/rra.1431.","startPage":"2","endPage":"12","numberOfPages":"11","costCenters":[],"links":[{"id":242977,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":215194,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/rra.1431"}],"volume":"28","issue":"1","noUsgsAuthors":false,"publicationDate":"2012-01-04","publicationStatus":"PW","scienceBaseUri":"50e4a5f2e4b0e8fec6cdc02e","contributors":{"authors":[{"text":"Kennedy, T.A.","contributorId":86155,"corporation":false,"usgs":true,"family":"Kennedy","given":"T.A.","email":"","affiliations":[],"preferred":false,"id":450341,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ralston, B.E.","contributorId":61662,"corporation":false,"usgs":true,"family":"Ralston","given":"B.E.","email":"","affiliations":[],"preferred":false,"id":450340,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70032500,"text":"70032500 - 2012 - Why farmers adopt best management practice in the United States: A meta-analysis of the adoption literature","interactions":[],"lastModifiedDate":"2013-01-10T14:03:22","indexId":"70032500","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2258,"text":"Journal of Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Why farmers adopt best management practice in the United States: A meta-analysis of the adoption literature","docAbstract":"This meta-analysis of both published and unpublished studies assesses factors believed to influence adoption of agricultural Best Management Practices in the United States. Using an established statistical technique to summarize the adoption literature in the United States, we identified the following variables as having the largest impact on adoption: access to and quality of information, financial capacity, and being connected to agency or local networks of farmers or watershed groups. This study shows that various approaches to data collection affect the results and comparability of adoption studies. In particular, environmental awareness and farmer attitudes have been inconsistently used and measured across the literature. This meta-analysis concludes with suggestions regarding the future direction of adoption studies, along with guidelines for how data should be presented to enhance the adoption of conservation practices and guide research.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Environmental Management","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.jenvman.2011.10.006","issn":"03014797","usgsCitation":"Baumgart-Getz, A., Stalker Prokopy, L., and Floress, K., 2012, Why farmers adopt best management practice in the United States: A meta-analysis of the adoption literature: Journal of Environmental Management, v. 96, no. 1, p. 17-25, https://doi.org/10.1016/j.jenvman.2011.10.006.","productDescription":"9 p.","startPage":"17","endPage":"25","numberOfPages":"9","costCenters":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"links":[{"id":214033,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.jenvman.2011.10.006"},{"id":241720,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"96","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505bd0a2e4b08c986b32ef8e","contributors":{"authors":[{"text":"Baumgart-Getz, Adam","contributorId":44365,"corporation":false,"usgs":true,"family":"Baumgart-Getz","given":"Adam","email":"","affiliations":[],"preferred":false,"id":436493,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stalker Prokopy, Linda","contributorId":73419,"corporation":false,"usgs":true,"family":"Stalker Prokopy","given":"Linda","email":"","affiliations":[],"preferred":false,"id":436494,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Floress, Kristin","contributorId":106326,"corporation":false,"usgs":true,"family":"Floress","given":"Kristin","email":"","affiliations":[],"preferred":false,"id":436495,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70032574,"text":"70032574 - 2012 - Regional scale impacts of <i>Tamarix</i> leaf beetles (<i>Diorhabda carinulata</i>) on the water availability of western U.S. rivers as determined by multi-scale remote sensing methods","interactions":[],"lastModifiedDate":"2017-11-25T14:17:42","indexId":"70032574","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"Regional scale impacts of <i>Tamarix</i> leaf beetles (<i>Diorhabda carinulata</i>) on the water availability of western U.S. rivers as determined by multi-scale remote sensing methods","docAbstract":"<i>Tamarix</i> leaf beetles (<i>Diorhabda carinulata</i>) have been widely released on western U.S. rivers to control introduced shrubs in the genus <i>Tamarix</i>. Part of the motivation to control <i>Tamarix</i> is to salvage water for human use. Information is needed on the impact of beetles on <i>Tamarix</i> seasonal leaf production and subsequent water use overwide areas andmultiple cycles of annual defoliation.Herewe combine ground data with high resolution phenocam imagery and moderate resolution (Landsat) and coarser resolution (MODIS) satellite imagery to test the effects of beetles on <i>Tamarix</i> evapotranspiration (ET) and leaf phenology at sites on six western rivers. Satellite imagery covered the period 2000 to 2010 which encompassed years before and after beetle release at each study site. Phenocam images showed that beetles reduced green leaf cover of individual canopies by about 30% during a 6-8 week period in summer, but plants produced new leaves after beetles became dormant in August, and over three years no net reduction in peak summer leaf production was noted. ETwas estimated by vegetation index methods, and both Landsat and MODIS analyses showed that beetles reduced ET markedly in the first year of defoliation, but ET recovered in subsequent years. Over all six sites, ET decreased by 14% to 15% by Landsat and MODIS estimates, respectively. However, resultswere variable among sites, ranging fromno apparent effect on ET to substantial reduction in ET. Baseline ET rates before defoliation were low, 394 mmyr<sup>-1</sup> by Landsat and 314 mm yr<sup>-1</sup> by MODIS estimates (20-25% of potential ET), further constraining the amount of water that could be salvaged. Beetle-<i>Tamarix</i> interactions are in their early stage of development on this continent and it is too soon to predict the eventual extent towhich <i>Tamarix</i> populationswill be reduced. The utility of remote sensing methods for monitoring defoliation was constrained by the small area covered by each phenocamimage, the low temporal resolution of Landsat, and the lowspatial resolution ofMODIS imagery. Even combined image sets did not adequately reveal the details of the defoliation process, and remote sensing data should be combined with ground observations to develop operational monitoring protocols.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Remote Sensing of Environment","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.rse.2011.11.011","issn":"00344257","usgsCitation":"Nagler, P.L., Brown, T., Hultine, K.R., van Riper, C., Bean, D., Dennison, P.E., Murray, R.S., and Glenn, E.P., 2012, Regional scale impacts of <i>Tamarix</i> leaf beetles (<i>Diorhabda carinulata</i>) on the water availability of western U.S. rivers as determined by multi-scale remote sensing methods: Remote Sensing of Environment, v. 118, p. 227-240, https://doi.org/10.1016/j.rse.2011.11.011.","productDescription":"14 p.","startPage":"227","endPage":"240","numberOfPages":"14","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":241759,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":214071,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.rse.2011.11.011"}],"country":"United States","state":"Colorado;Nevada;Utah;Wyoming","otherGeospatial":"Big Horn River;Humbolt River;Lower Delores River;Middle-upper Delores River;Upper Colorado River;Walker River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -120.0800,37.0000 ], [ -120.0800,45.0000 ], [ -106.3000,45.0000 ], [ -106.3000,37.0000 ], [ -120.0800,37.0000 ] ] ] } } ] }","volume":"118","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50788eb2e4b0cfc2d59f5b0d","contributors":{"authors":[{"text":"Nagler, Pamela L. 0000-0003-0674-103X pnagler@usgs.gov","orcid":"https://orcid.org/0000-0003-0674-103X","contributorId":1398,"corporation":false,"usgs":true,"family":"Nagler","given":"Pamela","email":"pnagler@usgs.gov","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":436882,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brown, Tim","contributorId":17841,"corporation":false,"usgs":true,"family":"Brown","given":"Tim","affiliations":[],"preferred":false,"id":436884,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hultine, Kevin R. 0000-0001-9747-6037","orcid":"https://orcid.org/0000-0001-9747-6037","contributorId":23772,"corporation":false,"usgs":true,"family":"Hultine","given":"Kevin","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":436886,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"van Riper, Charles III 0000-0003-1084-5843 charles_van_riper@usgs.gov","orcid":"https://orcid.org/0000-0003-1084-5843","contributorId":169488,"corporation":false,"usgs":true,"family":"van Riper","given":"Charles","suffix":"III","email":"charles_van_riper@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":false,"id":436888,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bean, Daniel W.","contributorId":11016,"corporation":false,"usgs":false,"family":"Bean","given":"Daniel W.","affiliations":[{"id":16124,"text":"Colorado Department of Agriculture, Biological Pest Control","active":true,"usgs":false}],"preferred":false,"id":436883,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dennison, Philip E.","contributorId":105132,"corporation":false,"usgs":true,"family":"Dennison","given":"Philip","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":436889,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Murray, R. Scott","contributorId":64468,"corporation":false,"usgs":true,"family":"Murray","given":"R.","email":"","middleInitial":"Scott","affiliations":[],"preferred":false,"id":436887,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Glenn, Edward P.","contributorId":19289,"corporation":false,"usgs":true,"family":"Glenn","given":"Edward","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":436885,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70032573,"text":"70032573 - 2012 - Ecoregional analysis of nearshore sea-surface temperature in the North Pacific","interactions":[],"lastModifiedDate":"2016-05-03T16:03:45","indexId":"70032573","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Ecoregional analysis of nearshore sea-surface temperature in the North Pacific","docAbstract":"<div class=\"abstract toc-section\">\n<p>The quantification and description of sea surface temperature (SST) is critically important because it can influence the distribution, migration, and invasion of marine species; furthermore, SSTs are expected to be affected by climate change. To better understand present temperature regimes, we assembled a 29-year nearshore time series of mean monthly SSTs along the North Pacific coastline using remotely-sensed satellite data collected with the Advanced Very High Resolution Radiometer (AVHRR) instrument. We then used the dataset to describe nearshore (&lt;20 km offshore) SST patterns of 16 North Pacific ecoregions delineated by the Marine Ecoregions of the World (MEOW) hierarchical schema. Annual mean temperature varied from 3.8&deg;C along the Kamchatka ecoregion to 24.8&deg;C in the Cortezian ecoregion. There are smaller annual ranges and less variability in SST in the Northeast Pacific relative to the Northwest Pacific. Within the 16 ecoregions, 31&ndash;94% of the variance in SST is explained by the annual cycle, with the annual cycle explaining the least variation in the Northern California ecoregion and the most variation in the Yellow Sea ecoregion. Clustering on mean monthly SSTs of each ecoregion showed a clear break between the ecoregions within the Warm and Cold Temperate provinces of the MEOW schema, though several of the ecoregions contained within the provinces did not show a significant difference in mean seasonal temperature patterns. Comparison of these temperature patterns shared some similarities and differences with previous biogeographic classifications and the Large Marine Ecosystems (LMEs). Finally, we provide a web link to the processed data for use by other researchers.</p>\n<p>&nbsp;</p>\n</div>","language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pone.0030105","issn":"19326203","usgsCitation":"Payne, M., Brown, C., Reusser, D., and Lee, H., 2012, Ecoregional analysis of nearshore sea-surface temperature in the North Pacific: PLoS ONE, v. 7, no. 1, e30105, 12 p., https://doi.org/10.1371/journal.pone.0030105.","productDescription":"e30105, 12 p.","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[],"links":[{"id":474745,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0030105","text":"Publisher Index Page"},{"id":241726,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"1","noUsgsAuthors":false,"publicationDate":"2012-01-11","publicationStatus":"PW","scienceBaseUri":"505a0594e4b0c8380cd50e61","contributors":{"authors":[{"text":"Payne, M.C.","contributorId":93271,"corporation":false,"usgs":true,"family":"Payne","given":"M.C.","email":"","affiliations":[],"preferred":false,"id":436881,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brown, C.A.","contributorId":71776,"corporation":false,"usgs":true,"family":"Brown","given":"C.A.","email":"","affiliations":[],"preferred":false,"id":436880,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reusser, D.A.","contributorId":61251,"corporation":false,"usgs":true,"family":"Reusser","given":"D.A.","email":"","affiliations":[],"preferred":false,"id":436879,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lee, H. II","contributorId":9077,"corporation":false,"usgs":true,"family":"Lee","given":"H.","suffix":"II","affiliations":[],"preferred":false,"id":436878,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
]}