{"pageNumber":"772","pageRowStart":"19275","pageSize":"25","recordCount":46865,"records":[{"id":97589,"text":"fs20093019 - 2009 - SPARROW MODELING - Enhancing Understanding of the Nation's Water Quality","interactions":[],"lastModifiedDate":"2012-02-02T00:14:32","indexId":"fs20093019","displayToPublicDate":"2009-06-11T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2009-3019","title":"SPARROW MODELING - Enhancing Understanding of the Nation's Water Quality","docAbstract":"The information provided here is intended to assist water-resources managers with interpretation of the U.S. Geological Survey (USGS) SPARROW model and its products. SPARROW models can be used to explain spatial patterns in monitored stream-water quality in relation to human activities and natural processes as defined by detailed geospatial information. Previous SPARROW applications have identified the sources and transport of nutrients in the Mississippi River basin, Chesapeake Bay watershed, and other major drainages of the United States. New SPARROW models with improved accuracy and interpretability are now being developed by the USGS National Water Quality Assessment (NAWQA) Program for six major regions of the conterminous United States. These new SPARROW models are based on updated geospatial data and stream-monitoring records from local, State, and other federal agencies.","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/fs20093019","usgsCitation":"Preston, S.D., Alexander, R.B., Woodside, M., and Hamilton, P.A., 2009, SPARROW MODELING - Enhancing Understanding of the Nation's Water Quality: U.S. Geological Survey Fact Sheet 2009-3019, 6 p., https://doi.org/10.3133/fs20093019.","productDescription":"6 p.","costCenters":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"links":[{"id":124765,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs_2009_3019.jpg"},{"id":12733,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2009/3019/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a0ee4b07f02db5fe15d","contributors":{"authors":[{"text":"Preston, Stephen D. 0000-0003-1515-6692 spreston@usgs.gov","orcid":"https://orcid.org/0000-0003-1515-6692","contributorId":1463,"corporation":false,"usgs":true,"family":"Preston","given":"Stephen","email":"spreston@usgs.gov","middleInitial":"D.","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":302605,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Alexander, Richard B. 0000-0001-9166-0626 ralex@usgs.gov","orcid":"https://orcid.org/0000-0001-9166-0626","contributorId":541,"corporation":false,"usgs":true,"family":"Alexander","given":"Richard","email":"ralex@usgs.gov","middleInitial":"B.","affiliations":[{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":302603,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Woodside, Michael D. mdwoodsi@usgs.gov","contributorId":2903,"corporation":false,"usgs":true,"family":"Woodside","given":"Michael D.","email":"mdwoodsi@usgs.gov","affiliations":[{"id":503,"text":"Office of Water Quality","active":true,"usgs":true}],"preferred":true,"id":302606,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hamilton, Pixie A. pahamilt@usgs.gov","contributorId":1068,"corporation":false,"usgs":true,"family":"Hamilton","given":"Pixie","email":"pahamilt@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":302604,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70197559,"text":"70197559 - 2009 - An integrated approach to benthic habitat mapping using remote sensing and GIS: An example from the Hawaiian Islands","interactions":[],"lastModifiedDate":"2018-06-27T16:02:10","indexId":"70197559","displayToPublicDate":"2009-06-11T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"An integrated approach to benthic habitat mapping using remote sensing and GIS: An example from the Hawaiian Islands","docAbstract":"<p>This chapter documents our effort to map benthic habitats within the KalokoHonokohau National Historic Park, Hawai`i, USA. We produce detailed benthichabitat maps by using a combination of color aerial photography, high-resolution bathymetry, and georeferenced underwater video and still photography. We classify individual habitat polygons using five basic attributes and additional information regarding geology, morphology, and coral species. Derivative data sets including isobaths, hillshades, and slope maps are also generated. The mapping shows that benthic habitat and seafloor morphology varies greatly throughout the study area. Nearly 73% of the study area consists of a hardbottom structure that is potentially available for coral habitation; the remaining 27% includes unconsolidated sediment and artificial or historical features. Coral cover is generally low and increases with water depth. The offshore geology is predominantly composed of smooth to undulating pahoehoe-type basalt flows that form flat to gently sloping benches, vertical walls, and steep escarpments. In some locations the basalt surface is irregular and mounded into ridges, pinnacles, and arches. Large rounded basaltic boulders and smaller scattered rocks are common throughout the marine portions of the park. Coral or accreted carbonate reef obscures the underlying volcanic surface in only a few areas. The underlying geologic framework and morphology of the submerged volcanic flows within Kaloko-Honokohau National Historical Park provide the primary control on benthic habitats within the park. The habitat maps and associated data can be used as a stand-alone product or in a GIS to provide useful baseline information to scientists, managers and the general public.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Remote sensing and geospatial technologies for coastal ecosystem assessment and management: Lecture Notes in Geoinformation and Cartography","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer-Verlag Press","doi":"10.1007/978-3-540-88183-4_9","usgsCitation":"Gibbs, A.E., and Cochran, S., 2009, An integrated approach to benthic habitat mapping using remote sensing and GIS: An example from the Hawaiian Islands, chap. <i>of</i> Remote sensing and geospatial technologies for coastal ecosystem assessment and management: Lecture Notes in Geoinformation and Cartography, p. 211-231, https://doi.org/10.1007/978-3-540-88183-4_9.","productDescription":"21 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E.","contributorId":54229,"corporation":false,"usgs":true,"family":"Gibbs","given":"A.","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":737664,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cochran, Susan A. 0000-0002-2442-8787 scochran@usgs.gov","orcid":"https://orcid.org/0000-0002-2442-8787","contributorId":2062,"corporation":false,"usgs":true,"family":"Cochran","given":"Susan A.","email":"scochran@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":737665,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70198248,"text":"70198248 - 2009 - New and revised 14C dates for Hawaiian surface lava flows: Paleomagnetic and geomagnetic implications","interactions":[],"lastModifiedDate":"2018-07-31T08:54:22","indexId":"70198248","displayToPublicDate":"2009-06-10T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"subseriesTitle":"Solid Earth","title":"New and revised 14C dates for Hawaiian surface lava flows: Paleomagnetic and geomagnetic implications","docAbstract":"<p><span>Radiocarbon dates have been obtained for 30 charcoal samples corresponding to 27 surface lava flows from the Mauna Loa and Kilauea volcanoes on the Island of Hawaii. The submitted charcoal was a mixture of fresh and archived material. Preparation and analysis was undertaken at the NERC Radiocarbon Laboratory in Glasgow, Scotland, and the associated SUERC Accelerator Mass Spectrometry facility. The resulting dates range from 390 years B.P. to 12,910 years B.P. with corresponding error bars an order of magnitude smaller than previously obtained using the gas‐counting method. The new and revised&nbsp;</span><sup>14</sup><span>C data set can aid hazard and risk assessment on the island. The data presented here also have implications for geomagnetic modelling, which at present is limited by large dating errors.</span></p>","language":"English","publisher":"AGU","doi":"10.1029/2009GL037792","usgsCitation":"Pressling, N., Trusdell, F., and Gubbins, D., 2009, New and revised 14C dates for Hawaiian surface lava flows: Paleomagnetic and geomagnetic implications: Geophysical Research Letters, v. 36, no. 11, L11306; 5 p., https://doi.org/10.1029/2009GL037792.","productDescription":"L11306; 5 p.","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":476076,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2009gl037792","text":"Publisher Index Page"},{"id":355905,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -156.51123046874997,\n              18.760712758499565\n            ],\n            [\n              -154.566650390625,\n              18.760712758499565\n            ],\n            [\n              -154.566650390625,\n              20.416716988945712\n            ],\n            [\n              -156.51123046874997,\n              20.416716988945712\n            ],\n            [\n              -156.51123046874997,\n              18.760712758499565\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"36","issue":"11","noUsgsAuthors":false,"publicationDate":"2009-06-10","publicationStatus":"PW","scienceBaseUri":"5b98b9d4e4b0702d0e84523c","contributors":{"authors":[{"text":"Pressling, Nicola","contributorId":43963,"corporation":false,"usgs":true,"family":"Pressling","given":"Nicola","email":"","affiliations":[],"preferred":false,"id":740728,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Trusdell, Frank A. 0000-0002-0681-0528 trusdell@usgs.gov","orcid":"https://orcid.org/0000-0002-0681-0528","contributorId":754,"corporation":false,"usgs":true,"family":"Trusdell","given":"Frank A.","email":"trusdell@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":740729,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gubbins, David","contributorId":72998,"corporation":false,"usgs":true,"family":"Gubbins","given":"David","email":"","affiliations":[],"preferred":false,"id":740730,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":97584,"text":"ds435 - 2009 - Global Positioning System surveys of storm-surge sensors deployed during Hurricane Ike, Seadrift, Texas, to Lake Charles, Louisiana, 2008","interactions":[],"lastModifiedDate":"2022-08-18T17:51:04.341594","indexId":"ds435","displayToPublicDate":"2009-06-10T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"435","title":"Global Positioning System surveys of storm-surge sensors deployed during Hurricane Ike, Seadrift, Texas, to Lake Charles, Louisiana, 2008","docAbstract":"<p>The U.S. Geological Survey installed a network of pressure sensors at 65 sites along the Gulf Coast from Seadrift, Texas, northeast to Lake Charles, Louisiana, to record the timing, areal extent, and magnitude of inland storm surge and coastal flooding caused by Hurricane Ike in September 2008. A Global Positioning System was used to obtain elevations of reference marks near each sensor. A combination of real-time kinematic (RTK) and static Global Positioning System surveys were done to obtain elevations of reference marks. Leveling relative to reference marks was done to obtain elevations of sensor orifices above the reference marks. This report summarizes the Global Positioning System data collected and processed to obtain reference mark and storm-sensor-orifice elevations for 59 storm-surge sensors recovered from the original 65 installed as a necessary prelude to computation of storm-surge elevations. National Geodetic Survey benchmarks were used for RTK surveying. Where National Geodetic Survey benchmarks were not within 12 kilometers of a sensor site, static surveying was done. Additional control points for static surveying were in the form of newly established benchmarks or reestablished existing benchmarks. RTK surveying was used to obtain positions and elevations of reference marks for 29 sensor sites. Static surveying was used to obtain positions and elevations of reference marks for 34 sensor sites; four sites were surveyed using both methods. Multiple quality checks on the RTK-survey and static-survey data were applied. The results of all quality checks indicate that the desired elevation accuracy for the surveys of this report, less than 0.1-meter error, was achieved.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds435","usgsCitation":"Payne, J., Woodward, B.K., and Storm, J.B., 2009, Global Positioning System surveys of storm-surge sensors deployed during Hurricane Ike, Seadrift, Texas, to Lake Charles, Louisiana, 2008: U.S. Geological Survey Data Series 435, Report: iv, 17 p., Appendixes, https://doi.org/10.3133/ds435.","productDescription":"Report: iv, 17 p., Appendixes","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2008-09-01","temporalEnd":"2008-09-30","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":195200,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds435.gif"},{"id":405312,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_86717.htm","linkFileType":{"id":5,"text":"html"}},{"id":12727,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/435/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Louisiana, Texas","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -97,27 ], [ -97,31 ], [ -92,31 ], [ -92,27 ], [ -97,27 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4abee4b07f02db674bb2","contributors":{"authors":[{"text":"Payne, Jason  0000-0003-4294-7924 jdpayne@usgs.gov","orcid":"https://orcid.org/0000-0003-4294-7924","contributorId":1062,"corporation":false,"usgs":true,"family":"Payne","given":"Jason ","email":"jdpayne@usgs.gov","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":false,"id":302567,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Woodward, Brenda K.","contributorId":106985,"corporation":false,"usgs":true,"family":"Woodward","given":"Brenda","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":302569,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Storm, John B. 0000-0002-5657-536X jbstorm@usgs.gov","orcid":"https://orcid.org/0000-0002-5657-536X","contributorId":3684,"corporation":false,"usgs":true,"family":"Storm","given":"John","email":"jbstorm@usgs.gov","middleInitial":"B.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":302568,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":97585,"text":"ofr20091100 - 2009 - High-Resolution Seismic-Reflection and Marine Magnetic Data Along the Hosgri Fault Zone, Central California","interactions":[],"lastModifiedDate":"2012-02-10T00:11:47","indexId":"ofr20091100","displayToPublicDate":"2009-06-10T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2009-1100","title":"High-Resolution Seismic-Reflection and Marine Magnetic Data Along the Hosgri Fault Zone, Central California","docAbstract":"The U.S. Geological Survey (USGS) collected high-resolution shallow seismic-reflection and marine magnetic data in June 2008 in the offshore areas between the towns of Cayucos and Pismo Beach, Calif., from the nearshore (~6-m depth) to just west of the Hosgri Fault Zone (~200-m depth). These data are in support of the California State Waters Mapping Program and the Cooperative Research and Development Agreement (CRADA) between the Pacific Gas & Electric Co. and the U.S. Geological Survey. \r\n\r\nSeismic-reflection and marine magnetic data were acquired aboard the R/V Parke Snavely, using a SIG 2Mille minisparker seismic source and a Geometrics G882 cesium-vapor marine magnetometer. More than 550 km of seismic and marine magnetic data was collected simultaneously along shore-perpendicular transects spaced 800 m apart, with an additional 220 km of marine magnetometer data collected across the Hosgri Fault Zone, resulting in spacing locally as smallas 400 m. \r\n\r\nThis report includes maps of the seismic-survey sections, linked to Google Earth software, and digital data files showing images of each transect in SEG-Y, JPEG, and TIFF formats, as well as preliminary gridded marine-magnetic-anomaly and residual-magnetic-anomaly (shallow magnetic source) maps.","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/ofr20091100","collaboration":"2009, revised 2010","usgsCitation":"Sliter, R.W., Triezenberg, P., Hart, P.E., Watt, J.T., Johnson, S.Y., and Scheirer, D., 2009, High-Resolution Seismic-Reflection and Marine Magnetic Data Along the Hosgri Fault Zone, Central California: U.S. Geological Survey Open-File Report 2009-1100, Available online only, https://doi.org/10.3133/ofr20091100.","productDescription":"Available online only","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2008-06-10","temporalEnd":"2008-06-26","costCenters":[{"id":645,"text":"Western Coastal and Marine Geology","active":false,"usgs":true}],"links":[{"id":195470,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":12729,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2009/1100/","linkFileType":{"id":5,"text":"html"}}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -121.08333333333333,35 ], [ -121.08333333333333,35.5 ], [ -120.58333333333333,35.5 ], [ -120.58333333333333,35 ], [ -121.08333333333333,35 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a61e4b07f02db635858","contributors":{"authors":[{"text":"Sliter, Ray W. 0000-0003-0337-3454 rsliter@usgs.gov","orcid":"https://orcid.org/0000-0003-0337-3454","contributorId":1992,"corporation":false,"usgs":true,"family":"Sliter","given":"Ray","email":"rsliter@usgs.gov","middleInitial":"W.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":302570,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Triezenberg, Peter J.","contributorId":32625,"corporation":false,"usgs":true,"family":"Triezenberg","given":"Peter J.","affiliations":[],"preferred":false,"id":302575,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hart, Patrick E. 0000-0002-5080-1426 hart@usgs.gov","orcid":"https://orcid.org/0000-0002-5080-1426","contributorId":2879,"corporation":false,"usgs":true,"family":"Hart","given":"Patrick","email":"hart@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":302573,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Watt, Janet T. 0000-0002-4759-3814","orcid":"https://orcid.org/0000-0002-4759-3814","contributorId":8564,"corporation":false,"usgs":true,"family":"Watt","given":"Janet","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":302574,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Johnson, Samuel Y. 0000-0001-7972-9977 sjohnson@usgs.gov","orcid":"https://orcid.org/0000-0001-7972-9977","contributorId":2607,"corporation":false,"usgs":true,"family":"Johnson","given":"Samuel","email":"sjohnson@usgs.gov","middleInitial":"Y.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":302572,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Scheirer, Daniel S. dscheirer@usgs.gov","contributorId":2325,"corporation":false,"usgs":true,"family":"Scheirer","given":"Daniel S.","email":"dscheirer@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":302571,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":97586,"text":"pp1761 - 2009 - Geophysical Interpretations of the Southern Espanola Basin, New Mexico, That Contribute to Understanding Its Hydrogeologic Framework","interactions":[],"lastModifiedDate":"2012-02-10T00:11:54","indexId":"pp1761","displayToPublicDate":"2009-06-10T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":331,"text":"Professional Paper","code":"PP","onlineIssn":"2330-7102","printIssn":"1044-9612","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1761","title":"Geophysical Interpretations of the Southern Espanola Basin, New Mexico, That Contribute to Understanding Its Hydrogeologic Framework","docAbstract":"The southern Espanola basin consists of a westward- and northward-thickening wedge of rift fill, composed primarily of Santa Fe Group sediments, that serves as an important aquifer for the city of Santa Fe and surrounding areas.  Detailed aeromagnetic surveys were flown to better understand ground-water resources in this aquifer.  This report presents a synthesis of these data with gravity data and other constraints.  The interpretations were accomplished using qualitative interpretation, state-of-art data analysis techniques, and two- and three-dimensional modeling.  The results depict the presence of and depth to many geologic features that have hydrogeologic significance, including shallow faults, different types of igneous units, and basement rocks.  The results are presented as map interpretations, geophysical profile models, and a digital surface that represents the base and thickness of Santa Fe Group sediments, as well as vector files of some volcanic features and faults.","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/pp1761","isbn":"9781411323650","collaboration":"Prepared in cooperation with the New Mexico Office of the State Engineer","usgsCitation":"Grauch, V.J., Phillips, J.D., Koning, D., Johnson, P.S., and Bankey, V., 2009, Geophysical Interpretations of the Southern Espanola Basin, New Mexico, That Contribute to Understanding Its Hydrogeologic Framework: U.S. Geological Survey Professional Paper 1761, Report: vi, 88 p.; 2 Plates: Plate 1 - 23 x 37.5 inches, Plate 2 - 23 x 38 inches; Also available on CD-ROM, https://doi.org/10.3133/pp1761.","productDescription":"Report: vi, 88 p.; 2 Plates: Plate 1 - 23 x 37.5 inches, Plate 2 - 23 x 38 inches; Also available on CD-ROM","additionalOnlineFiles":"Y","costCenters":[{"id":212,"text":"Crustal Imaging and Characterization","active":false,"usgs":true}],"links":[{"id":197774,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/pp1761.gif"},{"id":12730,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/pp/1761/","linkFileType":{"id":5,"text":"html"}}],"scale":"1","projection":"Universal Transverse Mercator","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -106.28416666666666,35.3675 ], [ -106.28416666666666,36.1175 ], [ -105.86749999999999,36.1175 ], [ -105.86749999999999,35.3675 ], [ -106.28416666666666,35.3675 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4ac9e4b07f02db67c468","contributors":{"authors":[{"text":"Grauch, V. J. S. 0000-0002-0761-3489","orcid":"https://orcid.org/0000-0002-0761-3489","contributorId":34125,"corporation":false,"usgs":true,"family":"Grauch","given":"V.","email":"","middleInitial":"J. S.","affiliations":[],"preferred":false,"id":302578,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Phillips, Jeffrey D. 0000-0002-6459-2821 jeff@usgs.gov","orcid":"https://orcid.org/0000-0002-6459-2821","contributorId":1572,"corporation":false,"usgs":true,"family":"Phillips","given":"Jeffrey","email":"jeff@usgs.gov","middleInitial":"D.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":false,"id":302577,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Koning, Daniel","contributorId":58355,"corporation":false,"usgs":true,"family":"Koning","given":"Daniel","email":"","affiliations":[],"preferred":false,"id":302579,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Johnson, Peggy S.","contributorId":85689,"corporation":false,"usgs":true,"family":"Johnson","given":"Peggy","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":302580,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bankey, Viki viki@usgs.gov","contributorId":1238,"corporation":false,"usgs":true,"family":"Bankey","given":"Viki","email":"viki@usgs.gov","affiliations":[],"preferred":true,"id":302576,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":97580,"text":"ofr20091073 - 2009 - The framework of a coastal hazards model: A tool for predicting the impact of severe storms","interactions":[],"lastModifiedDate":"2022-06-28T21:23:20.449234","indexId":"ofr20091073","displayToPublicDate":"2009-06-10T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2009-1073","title":"The framework of a coastal hazards model: A tool for predicting the impact of severe storms","docAbstract":"The U.S. Geological Survey (USGS) Multi-Hazards Demonstration Project in Southern California (Jones and others, 2007) is a five-year project (FY2007-FY2011) integrating multiple USGS research activities with the needs of external partners, such as emergency managers and land-use planners, to produce products and information that can be used to create more disaster-resilient communities. The hazards being evaluated include earthquakes, landslides, floods, tsunamis, wildfires, and coastal hazards.\r\n\r\nFor the Coastal Hazards Task of the Multi-Hazards Demonstration Project in Southern California, the USGS is leading the development of a modeling system for forecasting the impact of winter storms threatening the entire Southern California shoreline from Pt. Conception to the Mexican border. The modeling system, run in real-time or with prescribed scenarios, will incorporate atmospheric information (that is, wind and pressure fields) with a suite of state-of-the-art physical process models (that is, tide, surge, and wave) to enable detailed prediction of currents, wave height, wave runup, and total water levels. Additional research-grade predictions of coastal flooding, inundation, erosion, and cliff failure will also be performed. Initial model testing, performance evaluation, and product development will be focused on a severe winter-storm scenario developed in collaboration with the Winter Storm Working Group of the USGS Multi-Hazards Demonstration Project in Southern California. Additional offline model runs and products will include coastal-hazard hindcasts of selected historical winter storms, as well as additional severe winter-storm simulations based on statistical analyses of historical wave and water-level data. The coastal-hazards model design will also be appropriate for simulating the impact of storms under various sea level rise and climate-change scenarios. The operational capabilities of this modeling system are designed to provide emergency planners with the critical information they need to respond quickly and efficiently and to increase public safety and mitigate damage associated with powerful coastal storms. For instance, high resolution local models will predict detailed wave heights, breaking patterns, and current strengths for use in warning systems for harbor-mouth navigation and densely populated coastal regions where beach safety is threatened. The offline applications are intended to equip coastal managers with the information needed to manage and allocate their resources effectively to protect sections of coast that may be most vulnerable to future severe storms.","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/ofr20091073","usgsCitation":"Barnard, P., O’Reilly, B., van Ormondt, M., Elias, E., Ruggiero, P., Erikson, L., Hapke, C., Collins, B., Guza, R.T., Adams, P.N., and Thomas, J., 2009, The framework of a coastal hazards model: A tool for predicting the impact of severe storms (Version 1.0): U.S. Geological Survey Open-File Report 2009-1073, iv, 21 p., https://doi.org/10.3133/ofr20091073.","productDescription":"iv, 21 p.","onlineOnly":"Y","costCenters":[{"id":645,"text":"Western Coastal and Marine Geology","active":false,"usgs":true}],"links":[{"id":195861,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":402650,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_86720.htm","linkFileType":{"id":5,"text":"html"}},{"id":12723,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2009/1073/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"California","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -120.5914306640625,\n              32.722598604044066\n            ],\n            [\n              -116.65283203124999,\n              32.722598604044066\n            ],\n            [\n              -116.65283203124999,\n              34.66032236481892\n            ],\n            [\n              -120.5914306640625,\n              34.66032236481892\n            ],\n            [\n              -120.5914306640625,\n              32.722598604044066\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","edition":"Version 1.0","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4ac9e4b07f02db67c761","contributors":{"authors":[{"text":"Barnard, Patrick L.","contributorId":54936,"corporation":false,"usgs":true,"family":"Barnard","given":"Patrick L.","affiliations":[],"preferred":false,"id":302553,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"O’Reilly, Bill","contributorId":11299,"corporation":false,"usgs":true,"family":"O’Reilly","given":"Bill","email":"","affiliations":[],"preferred":false,"id":302549,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"van Ormondt, Maarten","contributorId":50181,"corporation":false,"usgs":true,"family":"van Ormondt","given":"Maarten","affiliations":[],"preferred":false,"id":302551,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Elias, Edwin","contributorId":50615,"corporation":false,"usgs":true,"family":"Elias","given":"Edwin","affiliations":[],"preferred":false,"id":302552,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ruggiero, Peter","contributorId":15709,"corporation":false,"usgs":false,"family":"Ruggiero","given":"Peter","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":302550,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Erikson, Li H.","contributorId":10880,"corporation":false,"usgs":true,"family":"Erikson","given":"Li H.","affiliations":[],"preferred":false,"id":302548,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hapke, Cheryl","contributorId":89846,"corporation":false,"usgs":true,"family":"Hapke","given":"Cheryl","affiliations":[],"preferred":false,"id":302557,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Collins, Brian D.","contributorId":71641,"corporation":false,"usgs":true,"family":"Collins","given":"Brian D.","affiliations":[],"preferred":false,"id":302555,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Guza, Robert T.","contributorId":74095,"corporation":false,"usgs":true,"family":"Guza","given":"Robert","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":302556,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Adams, Peter N.","contributorId":64361,"corporation":false,"usgs":true,"family":"Adams","given":"Peter","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":302554,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Thomas, Julie","contributorId":107007,"corporation":false,"usgs":true,"family":"Thomas","given":"Julie","email":"","affiliations":[],"preferred":false,"id":302558,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":5211458,"text":"5211458 - 2009 - One size does not fit all: Adapting mark-recapture and occupancy models for state uncertainty","interactions":[],"lastModifiedDate":"2012-02-02T00:15:26","indexId":"5211458","displayToPublicDate":"2009-06-09T09:23:20","publicationYear":"2009","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"seriesNumber":"3","title":"One size does not fit all: Adapting mark-recapture and occupancy models for state uncertainty","docAbstract":"Multistate capture?recapture models continue to be employed with greater frequency to test hypotheses about metapopulation dynamics and life history, and more recently disease dynamics.  In recent years efforts have begun to adjust these models for cases where there is uncertainty about an animal?s state upon capture.  These efforts can be categorized into models that permit misclassification between two states to occur in either direction or one direction, where state is certain for a subset of individuals or is always uncertain, and where estimation is based on one sampling occasion per period of interest or multiple sampling occasions per period.  State uncertainty also arises in modeling patch occupancy dynamics.  I consider several case studies involving bird and marine mammal studies that illustrate how misclassified states can arise, and outline model structures for properly utilizing the data that are produced.  In each case misclassification occurs in only one direction (thus there is a subset of individuals or patches where state is known with certainty), and there are multiple sampling occasions per period of interest.  For the cases involving capture?recapture data I allude to a general model structure that could include each example as a special case.  However, this collection of cases also illustrates how difficult it is to develop a model structure that can be directly useful for answering every ecological question of interest and account for every type of data from the field.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Modeling demographic processes in marked populations","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"Springer","publisherLocation":"New York and London","collaboration":"Proceedings of the 2007 EURING Technical Meeting and Workshop held January 14-20, 2007 in Dunedin, New Zealand.  OCLC: 213382236  PDF on file: 7058_Kendall.pdf","usgsCitation":"Kendall, W., 2009, One size does not fit all: Adapting mark-recapture and occupancy models for state uncertainty, chap. <i>of</i> Modeling demographic processes in marked populations, p. 765-780.","productDescription":"xxiv, 1136","startPage":"765","endPage":"780","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":203032,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4af3e4b07f02db691a10","contributors":{"editors":[{"text":"Thomson, David L.","contributorId":114050,"corporation":false,"usgs":true,"family":"Thomson","given":"David","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":508173,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Cooch, Evan G.","contributorId":100673,"corporation":false,"usgs":true,"family":"Cooch","given":"Evan","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":508172,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Conroy, Michael J.","contributorId":20871,"corporation":false,"usgs":false,"family":"Conroy","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":13266,"text":"Warnell School of Forestry and Natural Resources, The University of Georgia","active":true,"usgs":false}],"preferred":false,"id":508171,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"Kendall, W. L. 0000-0003-0084-9891","orcid":"https://orcid.org/0000-0003-0084-9891","contributorId":32880,"corporation":false,"usgs":true,"family":"Kendall","given":"W. L.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":331118,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":5211455,"text":"5211455 - 2009 - Inference about species richness and community structure using species-specific occupancy models in the National Swiss Breeding Bird Survey MUB","interactions":[],"lastModifiedDate":"2012-02-02T00:15:27","indexId":"5211455","displayToPublicDate":"2009-06-09T09:23:20","publicationYear":"2009","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"seriesNumber":"3","title":"Inference about species richness and community structure using species-specific occupancy models in the National Swiss Breeding Bird Survey MUB","docAbstract":"Species richness is the most widely used biodiversity measure.  Virtually always, it cannot be observed but needs to be estimated because some species may be present but remain undetected.  This fact is commonly ignored in ecology and management, although it will bias estimates of species richness and related parameters such as occupancy, turnover or extinction rates.  We describe a species community modeling strategy based on species-specific models of occurrence, from which estimates of important summaries of community structure, e.g., species richness, occupancy, or measures of similarity among species or sites, are derived by aggregating indicators of occurrence for all species observed in the sample, and for the estimated complement of unobserved species.  We use data augmentation for an efficient Bayesian approach to estimation and prediction under this model based on MCMC in WinBUGS.  For illustration, we use the Swiss breeding bird survey (MHB) that conducts 2?3 territory-mapping surveys in a systematic sample of 267 1 km2 units on quadrat-specific routes averaging 5.1 km to obtain species-specific estimates of occupancy, and estimates of species richness of all diurnal species free of distorting effects of imperfect detectability.  We introduce into our model species-specific covariates relevant to occupancy (elevation, forest cover, route length) and sampling (season, effort).  From 1995 to 2004, 185 diurnal breeding bird species were known in Switzerland, and an additional 13 bred 1?3 times since 1900.  134 species were observed during MHB surveys in 254 quadrats surveyed in 2001, and our estimate of 169.9 (95% CI 151?195) therefore appeared sensible.  The observed number of species ranged from 4 to 58 (mean 32.8), but with an estimated 0.7?11.2 (mean 2.6) further, unobserved species, the estimated proportion of detected species was 0.48?0.98 (mean 0.91).  As is well known, species richness declined at higher elevation and fell above the timberline, and most species showed some preferred elevation.  Route length had clear effects on occupancy, suggesting it is a proxy for the size of the effectively sampled area.  Detection probability of most species showed clear seasonal patterns and increased with greater survey effort; these are important results for the planning of focused surveys.  The main benefit of our model, and its implementation in WinBUGS for which we provide code, is its conceptual simplicity.  Species richness is naturally expressed as the sum of occurrences of individual species.  Information about species is combined across sites, which yields greater efficiency or may even enable estimation for sites with very few observed species in the first place.  At the same time, species detections are clearly segregated into a true state process (occupancy) and an observation process (detection, given occupancy), and covariates can be readily introduced, which provides for efficient introduction of such additional information as well as sharp testing of such relationships. ","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Modeling demographic processes in marked populations","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"Springer","publisherLocation":"New York and London","collaboration":"Proceedings of the 2007 EURING Technical Meeting and Workshop held January 14-20, 2007 in Dunedin, New Zealand.  OCLC: 213382236  PDF on file: 7055_Kery.pdf","usgsCitation":"Kery, M., and Royle, J., 2009, Inference about species richness and community structure using species-specific occupancy models in the National Swiss Breeding Bird Survey MUB, chap. <i>of</i> Modeling demographic processes in marked populations, p. 639-656.","productDescription":"xxiv, 1136","startPage":"639","endPage":"656","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":202992,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e49f1e4b07f02db5ee81a","contributors":{"editors":[{"text":"Thomson, David L.","contributorId":114050,"corporation":false,"usgs":true,"family":"Thomson","given":"David","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":508164,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Cooch, Evan G.","contributorId":100673,"corporation":false,"usgs":true,"family":"Cooch","given":"Evan","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":508163,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Conroy, Michael J.","contributorId":20871,"corporation":false,"usgs":false,"family":"Conroy","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":13266,"text":"Warnell School of Forestry and Natural Resources, The University of Georgia","active":true,"usgs":false}],"preferred":false,"id":508162,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"Kery, M.","contributorId":46637,"corporation":false,"usgs":true,"family":"Kery","given":"M.","affiliations":[],"preferred":false,"id":331108,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Royle, J. Andrew 0000-0003-3135-2167","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":96221,"corporation":false,"usgs":true,"family":"Royle","given":"J. Andrew","affiliations":[],"preferred":false,"id":331109,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":5211453,"text":"5211453 - 2009 - A generalized mixed effects model of abundance for mark-resight data when sampling is without replacement","interactions":[],"lastModifiedDate":"2012-02-02T00:15:27","indexId":"5211453","displayToPublicDate":"2009-06-09T09:23:20","publicationYear":"2009","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"seriesNumber":"3","title":"A generalized mixed effects model of abundance for mark-resight data when sampling is without replacement","docAbstract":"In recent years, the mark-resight method for estimating abundance when the number of marked individuals is known has become increasingly popular.  By using field-readable bands that may be resighted from a distance, these techniques can be applied to many species, and are particularly useful for relatively small, closed populations.  However, due to the different assumptions and general rigidity of the available estimators, researchers must often commit to a particular model without rigorous quantitative justification for model selection based on the data.  Here we introduce a nonlinear logit-normal mixed effects model addressing this need for a more generalized framework.  Similar to models available for mark-recapture studies, the estimator allows a wide variety of sampling conditions to be parameterized efficiently under a robust sampling design.  Resighting rates may be modeled simply or with more complexity by including fixed temporal and random individual heterogeneity effects.  Using information theory, the model(s) best supported by the data may be selected from the candidate models proposed.  Under this generalized framework, we hope the uncertainty associated with mark-resight model selection will be reduced substantially.  We compare our model to other mark-resight abundance estimators when applied to mainland New Zealand robin (Petroica australis) data recently collected in Eglinton Valley, Fiordland National Park and summarize its performance in simulation experiments. ","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Modeling demographic processes in marked populations","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"Springer","publisherLocation":"New York and London","collaboration":"Proceedings of the 2007 EURING Technical Meeting and Workshop held January 14-20, 2007 in Dunedin, New Zealand.  OCLC: 213382236  PDF on file: 7052_McClintock.pdf","usgsCitation":"McClintock, B., White, G.C., Burnham, K., and Pryde, M., 2009, A generalized mixed effects model of abundance for mark-resight data when sampling is without replacement, chap. <i>of</i> Modeling demographic processes in marked populations, p. 271-289.","productDescription":"xxiv, 1136","startPage":"271","endPage":"289","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":202989,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b24e4b07f02db6aea2f","contributors":{"editors":[{"text":"Thomson, David L.","contributorId":114050,"corporation":false,"usgs":true,"family":"Thomson","given":"David","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":508158,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Cooch, Evan G.","contributorId":100673,"corporation":false,"usgs":true,"family":"Cooch","given":"Evan","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":508157,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Conroy, Michael J.","contributorId":20871,"corporation":false,"usgs":false,"family":"Conroy","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":13266,"text":"Warnell School of Forestry and Natural Resources, The University of Georgia","active":true,"usgs":false}],"preferred":false,"id":508156,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"McClintock, B.T.","contributorId":29108,"corporation":false,"usgs":true,"family":"McClintock","given":"B.T.","email":"","affiliations":[],"preferred":false,"id":331103,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"White, Gary C.","contributorId":26256,"corporation":false,"usgs":true,"family":"White","given":"Gary","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":331102,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Burnham, K.P.","contributorId":63760,"corporation":false,"usgs":true,"family":"Burnham","given":"K.P.","email":"","affiliations":[],"preferred":false,"id":331105,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pryde, M.A.","contributorId":47894,"corporation":false,"usgs":true,"family":"Pryde","given":"M.A.","email":"","affiliations":[],"preferred":false,"id":331104,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":5211456,"text":"5211456 - 2009 - Exploring extensions to multi-state models with multiple unobservable states","interactions":[],"lastModifiedDate":"2012-02-02T00:15:23","indexId":"5211456","displayToPublicDate":"2009-06-09T09:23:20","publicationYear":"2009","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"seriesNumber":"3","title":"Exploring extensions to multi-state models with multiple unobservable states","docAbstract":"Many biological systems include a portion of the target population that is unobservable during certain life history stages.  Transition to and from an unobservable state may be of primary interest in many ecological studies and such movements are easily incorporated into multi-state models.  Several authors have investigated properties of open-population multi-state mark-recapture models with unobservable states, and determined the scope and constraints under which parameters are identifiable (or, conversely, are redundant), but only in the context of a single observable and a single unobservable state (Schmidt et al. 2002; Kendall and Nichols 2002; Schaub et al. 2004; Kendall 2004).  Some of these constraints can be relaxed if data are collected under a version of the robust design (Kendall and Bjorkland 2001; Kendall and Nichols 2002; Kendall 2004; Bailey et al. 2004), which entails >1 capture period per primary period of interest (e.g., 2 sampling periods within a breeding season).  The critical assumption shared by all versions of the robust design is that the state of the individual (e.g. observable or unobservable) remains static for the duration of the primary period (Kendall 2004).  In this paper, we extend previous work by relaxing this assumption to allow movement among observable states within primary periods while maintaining static observable or unobservable states.  Stated otherwise, both demographic and geographic closure assumptions are relaxed, but all individuals are either observable or unobservable within primary periods.  Within these primary periods transitions are possible among multiple observable states, but transitions are not allowed among the corresponding unobservable states.  Our motivation for this work is exploring potential differences in population parameters for pond-breeding amphibians, where the quality of habitat surrounding the pond is not spatially uniform.  The scenario is an example of a more general case where individuals move between habitats both during the breeding season (within primary periods; transitions among observable states only) and during the non-breeding season (between primary periods; transitions between observable and unobservable states).  Presumably, habitat quality affects demographic parameters (e.g. survival and breeding probabilities).  Using this model we are able to test this prediction for amphibians and determine if individuals move to more favorable habitats to increase survival and breeding probabilities.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Modeling demographic processes in marked populations","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"Springer","publisherLocation":"New York and London","collaboration":"Proceedings of the 2007 EURING Technical Meeting and Workshop held January 14-20, 2007 in Dunedin, New Zealand.  OCLC: 213382236  PDF on file: 7056_Bailey.pdf","usgsCitation":"Bailey, L., Kendall, W., and Church, D., 2009, Exploring extensions to multi-state models with multiple unobservable states, chap. <i>of</i> Modeling demographic processes in marked populations, p. 693-709.","productDescription":"xxiv, 1136","startPage":"693","endPage":"709","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":203011,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a0be4b07f02db5fbee4","contributors":{"editors":[{"text":"Thomson, David L.","contributorId":114050,"corporation":false,"usgs":true,"family":"Thomson","given":"David","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":508167,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Cooch, Evan G.","contributorId":100673,"corporation":false,"usgs":true,"family":"Cooch","given":"Evan","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":508166,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Conroy, Michael J.","contributorId":20871,"corporation":false,"usgs":false,"family":"Conroy","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":13266,"text":"Warnell School of Forestry and Natural Resources, The University of Georgia","active":true,"usgs":false}],"preferred":false,"id":508165,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"Bailey, L.L. 0000-0002-5959-2018","orcid":"https://orcid.org/0000-0002-5959-2018","contributorId":61006,"corporation":false,"usgs":true,"family":"Bailey","given":"L.L.","affiliations":[],"preferred":false,"id":331112,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kendall, W. L. 0000-0003-0084-9891","orcid":"https://orcid.org/0000-0003-0084-9891","contributorId":32880,"corporation":false,"usgs":true,"family":"Kendall","given":"W. L.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":331110,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Church, D.R.","contributorId":51884,"corporation":false,"usgs":true,"family":"Church","given":"D.R.","email":"","affiliations":[],"preferred":false,"id":331111,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":5211457,"text":"5211457 - 2009 - A traditional and a less-invasive robust design: choices in optimizing effort allocation for seabird population studies","interactions":[],"lastModifiedDate":"2016-08-16T13:57:00","indexId":"5211457","displayToPublicDate":"2009-06-09T09:23:20","publicationYear":"2009","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"A traditional and a less-invasive robust design: choices in optimizing effort allocation for seabird population studies","docAbstract":"<p>For many animal populations, one or more life stages are not accessible to sampling, and therefore an unobservable state is created. For colonially-breeding populations, this unobservable state could represent the subset of adult breeders that have foregone breeding in a given year. This situation applies to many seabird populations, notably albatrosses, where skipped breeders are either absent from the colony, or are present but difficult to capture or correctly assign to breeding state. Kendall et al. have proposed design strategies for investigations of seabird demography where such temporary emigration occurs, suggesting the use of the robust design to permit the estimation of time-dependent parameters and to increase the precision of estimates from multi-state models. A traditional robust design, where animals are subject to capture multiple times in a sampling season, is feasible in many cases. However, due to concerns that multiple captures per season could cause undue disturbance to animals, Kendall et al. developed a less-invasive robust design (LIRD), where initial captures are followed by an assessment of the ratio of marked-to-unmarked birds in the population or sampled plot. This approach has recently been applied in the Northwestern Hawaiian Islands to populations of Laysan (Phoebastria immutabilis) and black-footed (P. nigripes) albatrosses. In this paper, we outline the LIRD and its application to seabird population studies. We then describe an approach to determining optimal allocation of sampling effort in which we consider a non-robust design option (nRD), and variations of both the traditional robust design (RD), and the LIRD. Variations we considered included the number of secondary sampling occasions for the RD and the amount of total effort allocated to the marked-to-unmarked ratio assessment for the LIRD. We used simulations, informed by early data from the Hawaiian study, to address optimal study design for our example cases. We found that the LIRD performed as well or nearly as well as certain variations of the RD in terms of root mean square error, especially when relatively little of the total effort was allocated to the assessment of the marked-to-unmarked ratio versus to initial captures. For the RD, we found no clear benefit of using 2, 4, or 6 secondary sampling occasions per year, though this result will depend on the relative effort costs of captures versus recaptures and on the length of the study. We also found that field-readable bands, which may be affixed to birds in addition to standard metal bands, will be beneficial in longer-term studies of albatrosses in the Northwestern Hawaiian Islands. Field-readable bands reduce the effort cost of recapturing individuals, and in the long-term this cost reduction can offset the additional effort expended in affixing the bands. Finally, our approach to determining optimal study design can be generally applied by researchers, with little seed data, to design their studies at the outset.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Modeling demographic processes in marked populations","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","usgsCitation":"Converse, S.J., Kendall, W., Doherty, P., Naughton, M., and Hines, J., 2009, A traditional and a less-invasive robust design: choices in optimizing effort allocation for seabird population studies, chap. <i>of</i> Modeling demographic processes in marked populations, p. 727-744.","productDescription":"xxiv, 1131 p.","startPage":"727","endPage":"744","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":203012,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b16e4b07f02db6a556c","contributors":{"editors":[{"text":"Thomson, David L.","contributorId":114050,"corporation":false,"usgs":true,"family":"Thomson","given":"David","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":508170,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Cooch, Evan G.","contributorId":100673,"corporation":false,"usgs":true,"family":"Cooch","given":"Evan","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":508169,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Conroy, Michael J.","contributorId":20871,"corporation":false,"usgs":false,"family":"Conroy","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":13266,"text":"Warnell School of Forestry and Natural Resources, The University of Georgia","active":true,"usgs":false}],"preferred":false,"id":508168,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"Converse, S. J.","contributorId":43475,"corporation":false,"usgs":true,"family":"Converse","given":"S.","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":331115,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kendall, W. L. 0000-0003-0084-9891","orcid":"https://orcid.org/0000-0003-0084-9891","contributorId":32880,"corporation":false,"usgs":true,"family":"Kendall","given":"W. L.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":331113,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Doherty, P.F. Jr.","contributorId":74096,"corporation":false,"usgs":true,"family":"Doherty","given":"P.F.","suffix":"Jr.","email":"","affiliations":[],"preferred":false,"id":331116,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Naughton, M.B.","contributorId":104194,"corporation":false,"usgs":true,"family":"Naughton","given":"M.B.","email":"","affiliations":[],"preferred":false,"id":331117,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hines, J.E. 0000-0001-5478-7230","orcid":"https://orcid.org/0000-0001-5478-7230","contributorId":36885,"corporation":false,"usgs":true,"family":"Hines","given":"J.E.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":331114,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":5211448,"text":"5211448 - 2009 - Filling a void: abundance estimation of North American populations of arctic geese using hunter recoveries","interactions":[],"lastModifiedDate":"2012-02-02T00:15:23","indexId":"5211448","displayToPublicDate":"2009-06-09T09:23:20","publicationYear":"2009","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"seriesNumber":"3","title":"Filling a void: abundance estimation of North American populations of arctic geese using hunter recoveries","docAbstract":"We consider use of recoveries of marked birds harvested by hunters, in conjunction with continental harvest estimates, for drawing inferences about continental abundance of a select number of goose species.  We review assumptions of this method, a version of the Lincoln?Petersen approach, and consider its utility as a tool for making decisions about harvest management in comparison to current sources of information.  Finally, we compare such estimates with existing count data, photographic estimates, or other abundance estimates.  In most cases, Lincoln estimates are far higher than abundances assumed or perhaps accepted by many waterfowl biologists and managers.  Nevertheless, depending on the geographic scope of inference, we suggest that this approach for abundance estimation of arctic geese may have usefulness for retrospective purposes or to assist with harvest management decisions for some species.  Lincoln?s estimates may be as close or closer to truth than count, index, or photo data, and can be used with marking efforts currently in place for estimation of survival and harvest rates.  Although there are bias issues associated with estimates of both harvest and harvest rate, some of the latter can be addressed with proper allocation of marks to spatially structured populations if subpopulations show heterogeneity in harvest rates.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Modeling demographic processes in marked populations","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"Springer","publisherLocation":"New York and London","collaboration":"Proceedings of the 2007 EURING Technical Meeting and Workshop held January 14-20, 2007 in Dunedin, New Zealand.  OCLC: 213382236   Section V, Wildlife and Conservation Management   PDF on file: 7053_Alisauskas.pdf","usgsCitation":"Alisauskas, R., Drake, K., and Nichols, J., 2009, Filling a void: abundance estimation of North American populations of arctic geese using hunter recoveries, chap. <i>of</i> Modeling demographic processes in marked populations, p. 463-489.","productDescription":"xxiv, 1136","startPage":"463","endPage":"489","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":203010,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e49fbe4b07f02db5f4894","contributors":{"editors":[{"text":"Thomson, David L.","contributorId":114050,"corporation":false,"usgs":true,"family":"Thomson","given":"David","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":508144,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Cooch, Evan G.","contributorId":100673,"corporation":false,"usgs":true,"family":"Cooch","given":"Evan","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":508143,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Conroy, Michael J.","contributorId":20871,"corporation":false,"usgs":false,"family":"Conroy","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":13266,"text":"Warnell School of Forestry and Natural Resources, The University of Georgia","active":true,"usgs":false}],"preferred":false,"id":508142,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"Alisauskas, R.T.","contributorId":89645,"corporation":false,"usgs":true,"family":"Alisauskas","given":"R.T.","affiliations":[],"preferred":false,"id":331087,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Drake, K.L.","contributorId":10005,"corporation":false,"usgs":true,"family":"Drake","given":"K.L.","email":"","affiliations":[],"preferred":false,"id":331085,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nichols, J.D. 0000-0002-7631-2890","orcid":"https://orcid.org/0000-0002-7631-2890","contributorId":14332,"corporation":false,"usgs":true,"family":"Nichols","given":"J.D.","affiliations":[],"preferred":false,"id":331086,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":5211446,"text":"5211446 - 2009 - Inferences about landbird abundance from count data: recent advances and future directions","interactions":[],"lastModifiedDate":"2012-02-02T00:15:28","indexId":"5211446","displayToPublicDate":"2009-06-09T09:23:20","publicationYear":"2009","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"seriesNumber":"3","title":"Inferences about landbird abundance from count data: recent advances and future directions","docAbstract":"We summarize results of a November 2006 workshop dealing with recent research on the estimation of landbird abundance from count data.  Our conceptual framework includes a decomposition of the probability of detecting a bird potentially exposed to sampling efforts into four separate probabilities.  Primary inference methods are described and include distance sampling, multiple observers, time of detection, and repeated counts.  The detection parameters estimated by these different approaches differ, leading to different interpretations of resulting estimates of density and abundance.  Simultaneous use of combinations of these different inference approaches can not only lead to increased precision but also provides the ability to decompose components of the detection process.  Recent efforts to test the efficacy of these different approaches using natural systems and a new bird radio test system provide sobering conclusions about the ability of observers to detect and localize birds in auditory surveys.  Recent research is reported on efforts to deal with such potential sources of error as bird misclassification, measurement error, and density gradients.  Methods for inference about spatial and temporal variation in avian abundance are outlined.  Discussion topics include opinions about the need to estimate detection probability when drawing inference about avian abundance, methodological recommendations based on the current state of knowledge and suggestions for future research.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Modeling demographic processes in marked populations","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"Springer","publisherLocation":"New York and London","collaboration":"Proceedings of the 2007 EURING Technical Meeting and Workshop held January 14-20, 2007 in Dunedin, New Zealand.  OCLC: 213382236  PDF on file: 7051_Nichols.pdf","usgsCitation":"Nichols, J., Thomas, L., and Conn, P., 2009, Inferences about landbird abundance from count data: recent advances and future directions, chap. <i>of</i> Modeling demographic processes in marked populations, p. 201-235.","productDescription":"xxiv, 1136","startPage":"201","endPage":"235","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":202887,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4abae4b07f02db6720f8","contributors":{"editors":[{"text":"Thomson, David L.","contributorId":114050,"corporation":false,"usgs":true,"family":"Thomson","given":"David","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":508138,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Cooch, Evan G.","contributorId":100673,"corporation":false,"usgs":true,"family":"Cooch","given":"Evan","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":508137,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Conroy, Michael J.","contributorId":20871,"corporation":false,"usgs":false,"family":"Conroy","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":13266,"text":"Warnell School of Forestry and Natural Resources, The University of Georgia","active":true,"usgs":false}],"preferred":false,"id":508136,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"Nichols, J.D. 0000-0002-7631-2890","orcid":"https://orcid.org/0000-0002-7631-2890","contributorId":14332,"corporation":false,"usgs":true,"family":"Nichols","given":"J.D.","affiliations":[],"preferred":false,"id":331079,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thomas, L.","contributorId":37678,"corporation":false,"usgs":true,"family":"Thomas","given":"L.","affiliations":[],"preferred":false,"id":331080,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Conn, P.B.","contributorId":73974,"corporation":false,"usgs":true,"family":"Conn","given":"P.B.","email":"","affiliations":[],"preferred":false,"id":331081,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":97574,"text":"pp1760C - 2009 - The Longview/Lakeview barite deposits, southern National Petroleum Reserve, Alaska (NPRA) — Potential-field models and preliminary size estimates","interactions":[{"subject":{"id":97574,"text":"pp1760C - 2009 - The Longview/Lakeview barite deposits, southern National Petroleum Reserve, Alaska (NPRA) — Potential-field models and preliminary size estimates","indexId":"pp1760C","publicationYear":"2009","noYear":false,"chapter":"C","title":"The Longview/Lakeview barite deposits, southern National Petroleum Reserve, Alaska (NPRA) — Potential-field models and preliminary size estimates"},"predicate":"IS_PART_OF","object":{"id":97266,"text":"pp1760 - 2009 - Studies by the U.S. Geological Survey in Alaska, 2007","indexId":"pp1760","publicationYear":"2009","noYear":false,"title":"Studies by the U.S. Geological Survey in Alaska, 2007"},"id":1}],"isPartOf":{"id":97266,"text":"pp1760 - 2009 - Studies by the U.S. Geological Survey in Alaska, 2007","indexId":"pp1760","publicationYear":"2009","noYear":false,"title":"Studies by the U.S. Geological Survey in Alaska, 2007"},"lastModifiedDate":"2021-12-15T20:08:17.853189","indexId":"pp1760C","displayToPublicDate":"2009-06-05T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":331,"text":"Professional Paper","code":"PP","onlineIssn":"2330-7102","printIssn":"1044-9612","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1760","chapter":"C","title":"The Longview/Lakeview barite deposits, southern National Petroleum Reserve, Alaska (NPRA) — Potential-field models and preliminary size estimates","docAbstract":"Longview and Lakeview are two of the larger stratiform barite deposits hosted in Mississippian Akmalik Chert in the Cutaway Basin area (Howard Pass C-3 quadrangle) of the southern National Petroleum Reserve, Alaska (NPRA). Geologic studies for the South NPRA Integrated Activity Plan and Environmental Impact Statement process included an attempt to evaluate the possible size of barite resources at Longview and Lakeview by using potential-field geophysical methods (gravity and magnetics). \r\n\r\nGravity data from 227 new stations measured by the U.S. Geological Survey, sparse regional gravity data, and new, high-resolution aeromagnetic data were forward modeled simultaneously along seven profiles perpendicular to strike and two profiles along strike of the Longview and Lakeview deposits. \r\n\r\nThese models indicate details of the size and shape of the barite deposits and suggest thicknesses of 15 to 24 m, and 9 to 24 m for the Longview and Lakeview deposits, respectively. Two groups of outcrops span 1.8 km of strike length and are likely connected below the surface by barite as much as 10 m thick. Barite of significant thickness (>-5 m) is unlikely to occur north of the presently known exposures of the Longview deposit. The barite bodies have irregular (nonplanar) bases suggestive of folding; northwest-trending structures of small apparent offset cross strike at several locations. Dip of the barite is 10 to 25 degrees to the southeast. True width of the bodies (the least certain dimension) is estimated to be 160 to 200 m for Longview and 220 to 260 m for Lakeview. The two bodies contain a minimum of 4.5 million metric tons of barite and more than 38 million metric tons are possible. \r\n\r\nGrades of the barite are relatively high, with high specific gravities and low impurities. The potential for the Cutaway Basin to host economically minable quantities of barite is uncertain. Heavy-mineral concentrate samples from streams in the area, trace-element analyses, and physicalproperty measurements of bulk samples derived from trenching or drilling would be valuable for future assessment work.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Studies by the U.S. Geological Survey in Alaska, 2007","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/pp1760C","collaboration":"Prepared in cooperation with the U.S. Bureau of Land Management","usgsCitation":"Schmidt, J.M., Glen, J., and Morin, R.L., 2009, The Longview/Lakeview barite deposits, southern National Petroleum Reserve, Alaska (NPRA) — Potential-field models and preliminary size estimates (Version 1.0): U.S. Geological Survey Professional Paper 1760, iv, 29 p., https://doi.org/10.3133/pp1760C.","productDescription":"iv, 29 p.","onlineOnly":"Y","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"links":[{"id":196037,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/pp1760c.jpg"},{"id":392962,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_86706.htm"},{"id":12717,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/pp/1760/c/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Alaska","otherGeospatial":"Longview/Lakeview barite deposits, southern National Petroleum Reserve","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -157.6167,\n              68.5583\n            ],\n            [\n              -157.4,\n              68.5583\n            ],\n            [\n              -157.4,\n              68.6333\n            ],\n            [\n              -157.6167,\n              68.6333\n            ],\n            [\n              -157.6167,\n              68.5583\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","edition":"Version 1.0","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4ac8e4b07f02db67bab4","contributors":{"authors":[{"text":"Schmidt, Jeanine M. jschmidt@usgs.gov","contributorId":3138,"corporation":false,"usgs":true,"family":"Schmidt","given":"Jeanine","email":"jschmidt@usgs.gov","middleInitial":"M.","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":302532,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Glen, Jonathan M. G.","contributorId":45756,"corporation":false,"usgs":true,"family":"Glen","given":"Jonathan M. G.","affiliations":[],"preferred":false,"id":302533,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Morin, Robert L.","contributorId":82671,"corporation":false,"usgs":true,"family":"Morin","given":"Robert","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":302534,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":97573,"text":"gip87 - 2009 - Sea Floor off San Diego, California","interactions":[],"lastModifiedDate":"2012-02-02T00:15:04","indexId":"gip87","displayToPublicDate":"2009-06-05T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":315,"text":"General Information Product","code":"GIP","onlineIssn":"2332-354X","printIssn":"2332-3531","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"87","title":"Sea Floor off San Diego, California","docAbstract":"Ocean-floor image generated from multibeam-bathymetry data acquired by the U.S. Geological Survey (USGS); Woods Hole Oceanographic Institution; Scripps Institution of Oceanography; California State University, Monterey Bay; and Fugro Pelagos. To learn more, visit http://pubs.usgs.gov/sim/2007/2959/.","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/gip87","usgsCitation":"Dartnell, P., and Gibbons, H., 2009, Sea Floor off San Diego, California (Version 1.0): U.S. Geological Survey General Information Product 87, Postcard: 2 sided, https://doi.org/10.3133/gip87.","productDescription":"Postcard: 2 sided","costCenters":[{"id":645,"text":"Western Coastal and Marine Geology","active":false,"usgs":true}],"links":[{"id":126278,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/gip_87.jpg"},{"id":12716,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/gip/87/","linkFileType":{"id":5,"text":"html"}}],"edition":"Version 1.0","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a0ce4b07f02db5fc6a1","contributors":{"authors":[{"text":"Dartnell, Peter 0000-0002-9554-729X pdartnell@usgs.gov","orcid":"https://orcid.org/0000-0002-9554-729X","contributorId":2688,"corporation":false,"usgs":true,"family":"Dartnell","given":"Peter","email":"pdartnell@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":302531,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gibbons, Helen hgibbons@usgs.gov","contributorId":912,"corporation":false,"usgs":true,"family":"Gibbons","given":"Helen","email":"hgibbons@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":302530,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":97576,"text":"ofr20091105 - 2009 - Klamath River Water Quality Data from Link River Dam to Keno Dam, Oregon, 2008","interactions":[],"lastModifiedDate":"2012-03-08T17:16:31","indexId":"ofr20091105","displayToPublicDate":"2009-06-05T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2009-1105","title":"Klamath River Water Quality Data from Link River Dam to Keno Dam, Oregon, 2008","docAbstract":"This report documents sampling and analytical methods and presents field data from a second year of an ongoing study on the Klamath River from Link River Dam to Keno Dam in south central Oregon; this dataset will form the basis of a hydrodynamic and water quality model. Water quality was sampled weekly at six mainstem and two tributary sites from early April through early November, 2008. Constituents reported herein include field-measured water-column parameters (water temperature, pH, dissolved oxygen concentration, specific conductance); total nitrogen and phosphorus; particulate carbon and nitrogen; total iron; filtered orthophosphate, nitrite, nitrite plus nitrate, ammonia, organic carbon, and iron; specific UV absorbance at 254 nanometers; chlorophyll a; phytoplankton and zooplankton enumeration and species identification; and bacterial abundance and morphological subgroups. Sampling program results indicated:\r\n\r\n*Most nutrient and carbon concentrations were lowest in spring, increased starting in mid-June, remained elevated in the summer, and decreased in fall. Dissolved nitrite plus nitrate had a different seasonal cycle and was below detection or at low concentration in summer. \r\n*Although total nitrogen and total phosphorus concentrations did not show large differences from upstream to downstream, filtered ammonia and orthophosphate concentrations increased in the downstream direction and particulate carbon and particulate nitrogen generally decreased in the downstream direction. \r\n*Large bacterial cells made up most of the bacteria biovolume, though cocci were the most numerous bacteria type. Cocci, with diameters of 0.1 to 0.2 micrometers, were smaller than the filter pore sizes used to separate dissolved from particulate matter. \r\n*Phytoplankton biovolumes were dominated by diatoms in spring and by the blue-green alga Aphanizomenon flos-aquae after mid-June. Another blue-green, Anabaena flos-aquae, was noted in samples from late May to late June. Phytoplankton biovolumes generally were highest at the upstream Link River and Railroad Bridge sites and decreased in the downstream direction. \r\n*Zooplankton densities were largest in late April. Populations were dominated by rotifers and copepods in early spring, and by rotifers and cladocerans in summer, with cladocerans most common at the most upstream site.","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/ofr20091105","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Sullivan, A.B., Deas, M., Asbill, J., Kirshtein, J.D., Butler, K.D., and Vaughn, J., 2009, Klamath River Water Quality Data from Link River Dam to Keno Dam, Oregon, 2008: U.S. Geological Survey Open-File Report 2009-1105, Report: vi, 25 p.; Appendixes (Zip), https://doi.org/10.3133/ofr20091105.","productDescription":"Report: vi, 25 p.; Appendixes (Zip)","additionalOnlineFiles":"Y","temporalStart":"2008-04-01","temporalEnd":"2008-11-30","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":195998,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":12719,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2009/1105/","linkFileType":{"id":5,"text":"html"}}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122,42 ], [ -122,42.333333333333336 ], [ -121.66666666666667,42.333333333333336 ], [ -121.66666666666667,42 ], [ -122,42 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b32e4b07f02db6b47c2","contributors":{"authors":[{"text":"Sullivan, Annett B. 0000-0001-7783-3906 annett@usgs.gov","orcid":"https://orcid.org/0000-0001-7783-3906","contributorId":56317,"corporation":false,"usgs":true,"family":"Sullivan","given":"Annett","email":"annett@usgs.gov","middleInitial":"B.","affiliations":[],"preferred":false,"id":302539,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Deas, Michael L.","contributorId":98830,"corporation":false,"usgs":true,"family":"Deas","given":"Michael L.","affiliations":[],"preferred":false,"id":302541,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Asbill, Jessica","contributorId":79575,"corporation":false,"usgs":true,"family":"Asbill","given":"Jessica","affiliations":[],"preferred":false,"id":302540,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kirshtein, Julie D.","contributorId":26033,"corporation":false,"usgs":true,"family":"Kirshtein","given":"Julie","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":302537,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Butler, Kenna D. kebutler@usgs.gov","contributorId":3283,"corporation":false,"usgs":true,"family":"Butler","given":"Kenna","email":"kebutler@usgs.gov","middleInitial":"D.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":false,"id":302536,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Vaughn, Jennifer","contributorId":33009,"corporation":false,"usgs":true,"family":"Vaughn","given":"Jennifer","email":"","affiliations":[],"preferred":false,"id":302538,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70156667,"text":"70156667 - 2009 - Acid neutralizing capacity and leachate results for igneous rocks, with associated carbon contents of derived soils, Animas River AML site, Silverton, Colorado","interactions":[],"lastModifiedDate":"2021-10-28T16:50:16.312459","indexId":"70156667","displayToPublicDate":"2009-06-05T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Acid neutralizing capacity and leachate results for igneous rocks, with associated carbon contents of derived soils, Animas River AML site, Silverton, Colorado","docAbstract":"<p><span>Mine planning efforts have historically overlooked the possible acid neutralizing capacity (ANC) that local igneous rocks can provide to help neutralize acidmine drainage. As a result, limestone has been traditionally hauled to mine sites for use in neutralizing acid drainage. Local igneous rocks, when used as part of mine life-cycle planning and acid mitigation strategy, may reduce the need to transport limestone to mine sites because these rocks can contain acid neutralizing minerals. Igneous hydrothermal events often introduce moderately altered mineral assemblages peripheral to more intensely altered rocks that host metal-bearing veins and ore bodies. These less altered rocks can contain ANC minerals (calcite-chlorite-epidote) and are referred to as a propylitic assemblage. In addition, the carbon contents of soils in areas of new mining or those areas undergoing restoration have been historically unknown. Soil organic carbon is an important constituent to characterize as a soil recovery benchmark that can be referred to during mine cycle planning and restoration. &lt;br/&gt; This study addresses the mineralogy, ANC, and leachate chemistry of propylitic volcanic rocks that host polymetallic mineralization in the Animas River watershed near the historical Silverton, Colorado, mining area. Acid titration tests on volcanic rocks containing calcite (2 &ndash; 20 wt %) and chlorite (6 &ndash; 25 wt %), have ANC ranging from 4 &ndash; 146 kg/ton CaCO&lt;sub&gt;3&lt;/sub&gt; equivalence. Results from a 6-month duration, kinetic reaction vessel test containing layered pyritic mine waste and underlying ANC volcanic rock (saturated with deionized water) indicate that acid generating mine waste (pH 2.4) has not overwhelmed the ANC of propylitic volcanic rocks (pH 5.8). Sequential leachate laboratory experiments evaluated the concentration of metals liberated during leaching. Leachate concentrations of Cu-Zn-As-Pb for ANC volcanic rock are one-to-three orders of magnitude lower when compared to leached solution from mine waste used in the kinetic reaction vessel test. This finding suggests that mine waste and not ANC rock may generate the majority of leachable metals in a field scenario. &lt;br/&gt; The organic carbon content of naturally reclaimed soils derived from weathering of propylitically-altered andesite was determined in catchments where ANC studies were initiated. Soils were found to have total carbon concentrations (TOC) that exceed global average soil TOC abundances by as much as 1.5 &ndash; 5 times. These data support an environmental management system involving use of ANC rocks as part of life-cycle mine planning to reduce post-mine closure acid mitigation measures. Carbon contents of undisturbed soils in mined catchments can possibly be used to validate post-reclamation success and help quantify carbon sequestration for CO&lt;sub&gt;2&lt;/sub&gt; emission offset trading as carbon markets mature.</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"26th annual meetings of the American Society of Mining and Reclamation and 11th Billings Land Reclamation Symposium 2009 : Billings, Montana, USA, 30 May-5 June 2009","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"Joint Conference of the 26th Annual Meetings of the American Society of Mining and Reclamation and the 11th Billings Land Reclamation Symposium","conferenceDate":"May 30-June 5, 2009","conferenceLocation":"Billings, Montana","language":"English","publisher":"American Society of Mining & Reclamation","usgsCitation":"Yager, D.B., Stanton, M.R., Choate, L.M., and Burchell, A., 2009, Acid neutralizing capacity and leachate results for igneous rocks, with associated carbon contents of derived soils, Animas River AML site, Silverton, Colorado, <i>in</i> 26th annual meetings of the American Society of Mining and Reclamation and 11th Billings Land Reclamation Symposium 2009 : Billings, Montana, USA, 30 May-5 June 2009, Billings, Montana, May 30-June 5, 2009, p. 1662-1697.","productDescription":"37 p.","startPage":"1662","endPage":"1697","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-011792","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":307460,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Silverton area","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -107.830810546875,\n              37.72836644908416\n            ],\n            [\n              -107.457275390625,\n              37.72836644908416\n            ],\n            [\n              -107.457275390625,\n              37.88027325525864\n            ],\n            [\n              -107.830810546875,\n              37.88027325525864\n            ],\n            [\n              -107.830810546875,\n              37.72836644908416\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57fe8449e4b0824b2d148f7d","contributors":{"authors":[{"text":"Yager, Douglas B. 0000-0001-5074-4022 dyager@usgs.gov","orcid":"https://orcid.org/0000-0001-5074-4022","contributorId":798,"corporation":false,"usgs":true,"family":"Yager","given":"Douglas","email":"dyager@usgs.gov","middleInitial":"B.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":569865,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stanton, Mark R. mstanton@usgs.gov","contributorId":1834,"corporation":false,"usgs":true,"family":"Stanton","given":"Mark","email":"mstanton@usgs.gov","middleInitial":"R.","affiliations":[],"preferred":true,"id":569866,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Choate, LaDonna M. 0000-0002-0229-7210 lchoate@usgs.gov","orcid":"https://orcid.org/0000-0002-0229-7210","contributorId":1176,"corporation":false,"usgs":true,"family":"Choate","given":"LaDonna","email":"lchoate@usgs.gov","middleInitial":"M.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":569867,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Burchell, Alison Alison","contributorId":120944,"corporation":false,"usgs":true,"family":"Burchell","given":"Alison","suffix":"Alison","email":"","affiliations":[],"preferred":false,"id":569868,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":97571,"text":"sir20095007 - 2009 - Spatially referenced statistical assessment of dissolved-solids load sources and transport in streams of the Upper Colorado River Basin","interactions":[],"lastModifiedDate":"2017-01-25T11:18:28","indexId":"sir20095007","displayToPublicDate":"2009-06-04T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2009-5007","title":"Spatially referenced statistical assessment of dissolved-solids load sources and transport in streams of the Upper Colorado River Basin","docAbstract":"The Upper Colorado River Basin (UCRB) discharges more than 6 million tons of dissolved solids annually, about 40 to 45 percent of which are attributed to agricultural activities. The U.S. Department of the Interior estimates economic damages related to salinity in excess of $330 million annually in the Colorado River Basin. Salinity in the UCRB, as measured by dissolved-solids load and concentration, has been studied extensively during the past century. Over this period, a solid conceptual understanding of the sources and transport mechanisms of dissolved solids in the basin has been developed. This conceptual understanding was incorporated into the U.S. Geological Survey Spatially Referenced Regressions on Watershed Attributes (SPARROW) surface-water quality model to examine statistically the dissolved-solids supply and transport within the UCRB. Geologic and agricultural sources of dissolved solids in the UCRB were defined and represented in the model. On the basis of climatic and hydrologic conditions along with data availability, water year 1991 was selected for examination with SPARROW. \r\n\r\nDissolved-solids loads for 218 monitoring sites were used to calibrate a dissolved-solids SPARROW model for the UCRB. The calibrated model generally captures the transport mechanisms that deliver dissolved solids to streams of the UCRB as evidenced by R2 and yield R2 values of 0.98 and 0.71, respectively. Model prediction error is approximated at 51 percent. Model results indicate that of the seven geologic source groups, the high-yield sedimentary Mesozoic rocks have the largest yield of dissolved solids, about 41.9 tons per square mile (tons/mi2). Irrigated sedimentary-clastic Mesozoic lands have an estimated yield of 1,180 tons/mi2, and irrigated sedimentary-clastic Tertiary lands have an estimated yield of 662 tons/mi2. Coefficients estimated for the seven landscape transport characteristics seem to agree well with the conceptual understanding of the role they play in the delivery of dissolved solids to streams in the UCRB. \r\n\r\nPredictions of dissolved-solids loads were generated for more than 10,000 stream reaches of the stream network defined in the UCRB. From these estimates, the downstream accumulation of dissolved solids, including natural and agricultural components, were examined in selected rivers. Contributions from each of the 11 dissolved-solids sources were also examined at select locations in the Grand, Green, and San Juan Divisions of the UCRB. At the downstream boundary of the UCRB, the Colorado River at Lees Ferry, Arizona, monitoring site, the dissolved-solids contribution of irrigated agricultural lands and natural sources were about 45 and 57 percent, respectively. Finally, model predictions, including the contributions of natural and agricultural sources for selected locations in the UCRB, were compared with results from two previous studies.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20095007","collaboration":"Prepared in cooperation with the U.S. Department of the Interior - Bureau of Reclamation and Bureau of Land Management","usgsCitation":"Kenney, T.A., Gerner, S.J., Buto, S.G., and Spangler, L.E., 2009, Spatially referenced statistical assessment of dissolved-solids load sources and transport in streams of the Upper Colorado River Basin: U.S. Geological Survey Scientific Investigations Report 2009-5007, Report: viii, 50 p.; Plate Package; ReadMe; Guide, https://doi.org/10.3133/sir20095007.","productDescription":"Report: viii, 50 p.; Plate Package; ReadMe; Guide","additionalOnlineFiles":"Y","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true},{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":124344,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2009_5007.jpg"},{"id":12714,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2009/5007/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Arizona, Colorado, Idaho, New Mexico, Utah, Wyoming","otherGeospatial":"Upper Colorado River Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -114,35 ], [ -114,43 ], [ -105,43 ], [ -105,35 ], [ -114,35 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e49e5e4b07f02db5e6ca4","contributors":{"authors":[{"text":"Kenney, Terry A. 0000-0003-4477-7295 tkenney@usgs.gov","orcid":"https://orcid.org/0000-0003-4477-7295","contributorId":447,"corporation":false,"usgs":true,"family":"Kenney","given":"Terry","email":"tkenney@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":302521,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gerner, Steven J. 0000-0002-5701-1304 sjgerner@usgs.gov","orcid":"https://orcid.org/0000-0002-5701-1304","contributorId":972,"corporation":false,"usgs":true,"family":"Gerner","given":"Steven","email":"sjgerner@usgs.gov","middleInitial":"J.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":302522,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Buto, Susan G. 0000-0002-1107-9549 sbuto@usgs.gov","orcid":"https://orcid.org/0000-0002-1107-9549","contributorId":1057,"corporation":false,"usgs":true,"family":"Buto","given":"Susan","email":"sbuto@usgs.gov","middleInitial":"G.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true},{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":302524,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Spangler, Lawrence E. 0000-0003-3928-8809 spangler@usgs.gov","orcid":"https://orcid.org/0000-0003-3928-8809","contributorId":973,"corporation":false,"usgs":true,"family":"Spangler","given":"Lawrence","email":"spangler@usgs.gov","middleInitial":"E.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":302523,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":97569,"text":"cir1337 - 2009 - Water Quality in the High Plains Aquifer, Colorado, Kansas, Nebraska, New Mexico, Oklahoma, South Dakota, Texas, and Wyoming, 1999-2004","interactions":[],"lastModifiedDate":"2019-09-05T08:32:00","indexId":"cir1337","displayToPublicDate":"2009-06-03T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":307,"text":"Circular","code":"CIR","onlineIssn":"2330-5703","printIssn":"1067-084X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1337","title":"Water Quality in the High Plains Aquifer, Colorado, Kansas, Nebraska, New Mexico, Oklahoma, South Dakota, Texas, and Wyoming, 1999-2004","docAbstract":"This report contains the major findings of a 1999-2004 assessment of water quality in the High Plains aquifer. It is one of a series of reports by the National Water-Quality Assessment (NAWQA) Program that present major findings for principal and other aquifers and major river basins across the Nation. In these reports, water quality is discussed in terms of local, regional, State, and national issues. Conditions in the aquifer system are compared to conditions found elsewhere and to selected national benchmarks, such as those for drinking-water quality.\r\n\r\nThis report is intended for individuals working with water-resource issues in Federal, State, or local agencies, universities, public interest groups, or the private sector. The information will be useful in addressing a number of current issues, such as drinking-water quality, the effects of agricultural practices on water quality, source-water protection, and monitoring and sampling strategies. This report is also for individuals who wish to know more about the quality of ground water in areas near where they live and how that water quality compares to the quality of water in other areas across the region and the Nation.\r\n\r\nThe water-quality conditions in the High Plains aquifer summarized in this report are discussed in greater detail in other reports that can be accessed in Appendix 1 of http://pubs.usgs.gov/pp/1749/. Detailed technical information, data and analyses, collection and analytical methodology, models, graphs, and maps that support the findings presented in this report in addition to reports in this series from other basins can be accessed from the national NAWQA Web site (http://water.usgs.gov/nawqa). This report accompanies the detailed and technical report of water-quality conditions in the High Plains aquifer 'Water-quality assessment of the High Plains aquifer, 1999-2004' (http://pubs.usgs.gov/pp/1749/)","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1337","isbn":"9781411324716","usgsCitation":"Gurdak, J., McMahon, P.B., Dennehy, K., and Qi, S.L., 2009, Water Quality in the High Plains Aquifer, Colorado, Kansas, Nebraska, New Mexico, Oklahoma, South Dakota, Texas, and Wyoming, 1999-2004: U.S. Geological Survey Circular 1337, viii, 64 p., https://doi.org/10.3133/cir1337.","productDescription":"viii, 64 p.","temporalStart":"1999-01-01","temporalEnd":"2004-12-31","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":196036,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":12712,"rank":100,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1337/pdf/C1337.pdf","linkFileType":{"id":5,"text":"html"}}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -109,31 ], [ -109,44 ], [ -96,44 ], [ -96,31 ], [ -109,31 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a0de4b07f02db5fd381","contributors":{"authors":[{"text":"Gurdak, Jason J.","contributorId":65125,"corporation":false,"usgs":true,"family":"Gurdak","given":"Jason J.","affiliations":[],"preferred":false,"id":302516,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McMahon, Peter B. 0000-0001-7452-2379 pmcmahon@usgs.gov","orcid":"https://orcid.org/0000-0001-7452-2379","contributorId":724,"corporation":false,"usgs":true,"family":"McMahon","given":"Peter","email":"pmcmahon@usgs.gov","middleInitial":"B.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":302514,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dennehy, Kevin","contributorId":106222,"corporation":false,"usgs":true,"family":"Dennehy","given":"Kevin","email":"","affiliations":[],"preferred":false,"id":302517,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Qi, Sharon L. 0000-0001-7278-4498 slqi@usgs.gov","orcid":"https://orcid.org/0000-0001-7278-4498","contributorId":1130,"corporation":false,"usgs":true,"family":"Qi","given":"Sharon","email":"slqi@usgs.gov","middleInitial":"L.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":302515,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70168476,"text":"70168476 - 2009 - Biogeography of Iberian freshwater fishes revisited: The roles of historical versus contemporary constraints","interactions":[],"lastModifiedDate":"2016-02-16T12:40:19","indexId":"70168476","displayToPublicDate":"2009-06-03T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2193,"text":"Journal of Biogeography","active":true,"publicationSubtype":{"id":10}},"title":"Biogeography of Iberian freshwater fishes revisited: The roles of historical versus contemporary constraints","docAbstract":"<div class=\"page\" title=\"Page 1\">\n<div class=\"layoutArea\">\n<div class=\"column\">\n<p><strong>Aim&nbsp;</strong>The question of how much of the shared geographical distribution of biota is due to environmental vs. historical constraints remains unanswered. The aim of this paper is to disentangle the contribution of historical vs. contemporary factors to the distribution of freshwater fish species. In addition, it illustrates how quantifying the contribution of each type of factor improves the classification of biogeographical provinces.</p>\n<p><span><strong>Location</strong>&nbsp;</span><span>Iberian Peninsula, south-western Europe (</span><span>c</span><span>. 581,000 km</span><sup><span>2</span></sup><span>).</span></p>\n<p><strong>Methods&nbsp;</strong>We used the most comprehensive data on native fish distributions for the Iberian Peninsula, compiled from Portuguese and Spanish sources on a 20-km grid-cell resolution. Overall, 58 species were analysed after being categorized into three groups according to their ability to disperse through saltwater: (1) species strictly intolerant of saltwater (primary species); (2) species partially tolerant of saltwater, making limited incursions into saltwaters (secondary species); and (3) saltwater-tolerant species that migrate back and forth from sea to freshwaters or have invaded freshwaters recently (peripheral species). Distance-based multivariate analyses were used to test the role of historical (basin formation) vs. contemporary environmental (climate) conditions in explaining current patterns of native fish assemblage composition. Cluster analyses were performed to explore species co-occurrence patterns and redefine biogeographical provinces based on the distributions of fishes.</p>\n<p><strong>Results&nbsp;</strong>River basin boundaries were better at segregating species composition for all species groups than contemporary climate variables. This historical signal was especially evident for primary and secondary freshwater fishes. Eleven biogeographical provinces were delineated. Basins flowing to the Atlantic Ocean north of the Tagus Basin and those flowing to the Mediterranean Sea north of the Mijares Basin were the most dissimilar group. Primary and secondary freshwater species had higher province fidelity than peripheral species.&nbsp;</p>\n<p><strong>Main conclusions&nbsp;</strong>The results support the hypothesis that historical factors exert greater constraints on native freshwater fish assemblages in the Iberian Peninsula than do current environmental factors. After examining patterns of assemblage variation across space, as evidenced by the biogeographical provinces, we discuss the likely dispersal and speciation events that underlie these patterns.&nbsp;</p>\n</div>\n</div>\n</div>","language":"English","publisher":"Blackwell Scientific Publications","publisherLocation":"Oxford, England","doi":"10.1111/j.1365-2699.2009.02154.x","usgsCitation":"Filipe, A.F., Araujo, M.B., Doadrio, I., Angermeier, P.L., and Collares-Pereira, M.J., 2009, Biogeography of Iberian freshwater fishes revisited: The roles of historical versus contemporary constraints: Journal of Biogeography, v. 36, no. 11, p. 2096-2110, https://doi.org/10.1111/j.1365-2699.2009.02154.x.","productDescription":"15 p.","startPage":"2096","endPage":"2110","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-011527","costCenters":[{"id":199,"text":"Coop Res Unit 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,{"id":70156107,"text":"70156107 - 2009 - Is there a basis for preferring characteristic earthquakes over a Gutenberg–Richter distribution in probabilistic earthquake forecasting?","interactions":[],"lastModifiedDate":"2015-08-17T11:22:42","indexId":"70156107","displayToPublicDate":"2009-06-01T12:30:00","publicationYear":"2009","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Is there a basis for preferring characteristic earthquakes over a Gutenberg–Richter distribution in probabilistic earthquake forecasting?","docAbstract":"<p><span>The idea that faults rupture in repeated, characteristic earthquakes is central to most probabilistic earthquake forecasts. The concept is elegant in its simplicity, and if the same event has repeated itself multiple times in the past, we might anticipate the next. In practice however, assembling a fault-segmented characteristic earthquake rupture model can grow into a complex task laden with unquantified uncertainty. We weigh the evidence that supports characteristic earthquakes against a potentially simpler model made from extrapolation of a Gutenberg&ndash;Richter magnitude-frequency law to individual fault zones. We find that the Gutenberg&ndash;Richter model satisfies key data constraints used for earthquake forecasting equally well as a characteristic model. Therefore, judicious use of instrumental and historical earthquake catalogs enables large-earthquake-rate calculations with quantifiable uncertainty that should get at least equal weighting in probabilistic forecasting.</span></p>","language":"English","publisher":"Seismological Society of America","publisherLocation":"Stanford, CA","doi":"10.1785/0120080069","usgsCitation":"Parsons, T.E., and Geist, E.L., 2009, Is there a basis for preferring characteristic earthquakes over a Gutenberg–Richter distribution in probabilistic earthquake forecasting?: Bulletin of the Seismological Society of America, v. 99, no. 3, p. 2012-2019, https://doi.org/10.1785/0120080069.","productDescription":"8 p.","startPage":"2012","endPage":"2019","numberOfPages":"8","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-015082","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":306795,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"99","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2009-06-07","publicationStatus":"PW","scienceBaseUri":"55d305b5e4b0518e35468d04","contributors":{"authors":[{"text":"Parsons, Thomas E. 0000-0002-0582-4338 tparsons@usgs.gov","orcid":"https://orcid.org/0000-0002-0582-4338","contributorId":2314,"corporation":false,"usgs":true,"family":"Parsons","given":"Thomas","email":"tparsons@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":567880,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Geist, Eric L. 0000-0003-0611-1150 egeist@usgs.gov","orcid":"https://orcid.org/0000-0003-0611-1150","contributorId":1956,"corporation":false,"usgs":true,"family":"Geist","given":"Eric","email":"egeist@usgs.gov","middleInitial":"L.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":567879,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70156383,"text":"70156383 - 2009 - An orientation soil survey at the Pebble Cu-Au-Mo porphyry deposit, Alaska","interactions":[],"lastModifiedDate":"2021-10-28T16:44:52.578513","indexId":"70156383","displayToPublicDate":"2009-06-01T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"An orientation soil survey at the Pebble Cu-Au-Mo porphyry deposit, Alaska","docAbstract":"<p><span>Soil samples were collected in 2007 and 2008 along three traverses across the giant Pebble Cu-Au-Mo porphyry deposit. Within each soil pit, four subsamples were collected following recommended protocols for each of ten commonly-used and proprietary leach/digestion techniques. The significance of geochemical patterns generated by these techniques was classified by visual inspection of plots showing individual element concentration by each analytical method along the 2007 traverse. A simple matrix by element versus method, populated with a value based on the significance classification, provides a method for ranking the utility of methods and elements at this deposit. The interpretation of a complex multi-element dataset derived from multiple analytical techniques is challenging. An example of vanadium results from a single leach technique is used to illustrate the several possible interpretations of the data.</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the 24th International Applied Geochemistry Symposium Volume I","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"The 24th International Applied Geochemistry Symposium","conferenceDate":"June 1-4, 2009","conferenceLocation":"Fredericton, New Brunswick, Canada","language":"English","publisher":"Association of Applied Geochemists","usgsCitation":"Smith, S.M., Eppinger, R.G., Fey, D.L., Kelley, K.D., and Giles, S.A., 2009, An orientation soil survey at the Pebble Cu-Au-Mo porphyry deposit, Alaska, <i>in</i> Proceedings of the 24th International Applied Geochemistry Symposium Volume I, v. 1, Fredericton, New Brunswick, Canada, June 1-4, 2009, p. 393-396.","productDescription":"4 p.","startPage":"393","endPage":"396","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-011998","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":307039,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":307038,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.appliedgeochemists.org/aag-events/24th-international-applied-geochemistry-symposium"}],"country":"United States","state":"Alaska","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -155.35,\n              59.92\n            ],\n            [\n              -155.23,\n              59.92\n            ],\n            [\n              -155.23,\n              59.88\n            ],\n            [\n              -155.35,\n              59.88\n            ],\n            [\n              -155.35,\n              59.92\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55d6fa2fe4b0518e3546bc22","contributors":{"authors":[{"text":"Smith, Steven M. 0000-0003-3591-5377 smsmith@usgs.gov","orcid":"https://orcid.org/0000-0003-3591-5377","contributorId":1460,"corporation":false,"usgs":true,"family":"Smith","given":"Steven","email":"smsmith@usgs.gov","middleInitial":"M.","affiliations":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":568973,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Eppinger, Robert G. eppinger@usgs.gov","contributorId":849,"corporation":false,"usgs":true,"family":"Eppinger","given":"Robert","email":"eppinger@usgs.gov","middleInitial":"G.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":568974,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fey, David L. dfey@usgs.gov","contributorId":713,"corporation":false,"usgs":true,"family":"Fey","given":"David","email":"dfey@usgs.gov","middleInitial":"L.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":568975,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kelley, Karen D. kdkelley@usgs.gov","contributorId":431,"corporation":false,"usgs":true,"family":"Kelley","given":"Karen","email":"kdkelley@usgs.gov","middleInitial":"D.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":568976,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Giles, S. 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,{"id":70156090,"text":"70156090 - 2009 - Recovery distances of nestling Bald Eagles banded in Florida and implications for natal dispersal and philopatry","interactions":[],"lastModifiedDate":"2022-11-11T19:25:46.227643","indexId":"70156090","displayToPublicDate":"2009-06-01T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2442,"text":"Journal of Raptor Research","active":true,"publicationSubtype":{"id":10}},"title":"Recovery distances of nestling Bald Eagles banded in Florida and implications for natal dispersal and philopatry","docAbstract":"<p><span>I used band recovery data to examine distances between banding and recovery locations for 154 nestling Florida Bald Eagles and discuss the implications for understanding natal dispersal and philopatry in this species. Band recoveries occurred in 23 U.S. states and five Canadian provinces between 1931&ndash;2005. Recovery distance from the natal nest averaged longer for the youngest age classes (ANOVA:&nbsp;</span><i>F</i><span>&nbsp; =  3.59; df  =  5, 153;&nbsp;</span><i>P</i><span>&nbsp; =  0.005), for individuals banded in earlier decades (</span><i>F</i><span>&nbsp; =  1.94; df  =  5, 153;&nbsp;</span><i>P</i><span>&nbsp; =  0.093), and for the months of May through October (</span><i>F</i><span>&nbsp; =  3.10; df  =  12, 153;</span><i>P</i><span>&nbsp;&lt; 0.001). Of 35 individuals classed as mature (&ge;3.9 yr old when recovered; range 3.9&ndash;36.5 yr), 31 were located within Florida, which suggested a strong degree of philopatry to the natal state. Among 21 mature eagles of known sex with known banding and recovery locations in Florida, females, particularly younger birds, had longer recovery distances (</span><i>N</i><span>&nbsp; =  9, mean  =  93 km, SE  =  22.4) than did males (</span><i>N</i><span>&nbsp; =  12, mean  =  31 km, SE  =  5.3;&nbsp;</span><i>t</i><span>&nbsp; =  2.67, df  =  19,&nbsp;</span><i>P</i><span>&nbsp; =  0.026). The records examined here suggest a high degree of philopatry and relatively short natal dispersal distances, particularly in male Bald Eagles.</span></p>","language":"English","publisher":"The Raptor Research Foundation","doi":"10.3356/JRR-08-94.1","usgsCitation":"Wood, P.B., 2009, Recovery distances of nestling Bald Eagles banded in Florida and implications for natal dispersal and philopatry: Journal of Raptor Research, v. 43, no. 2, p. 127-133, https://doi.org/10.3356/JRR-08-94.1.","productDescription":"6 p.","startPage":"127","endPage":"133","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-010183","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":306850,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n   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,{"id":97567,"text":"sir20095006 - 2009 - Occurrence and distribution of iron, manganese, and selected trace elements in ground water in the glacial aquifer system of the northern United States","interactions":[],"lastModifiedDate":"2023-09-21T21:29:46.890404","indexId":"sir20095006","displayToPublicDate":"2009-05-30T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2009-5006","title":"Occurrence and distribution of iron, manganese, and selected trace elements in ground water in the glacial aquifer system of the northern United States","docAbstract":"<p>Dissolved trace elements, including iron and manganese, are often an important factor in use of ground water for drinking-water supplies in the glacial aquifer system of the United States. The glacial aquifer system underlies most of New England, extends through the Midwest, and underlies portions of the Pacific Northwest and Alaska. Concentrations of dissolved trace elements in ground water can vary over several orders of magnitude across local well networks as well as across regions of the United States. Characterization of this variability is a step toward a regional screening-level assessment of potential human-health implications. Ground-water sampling, from 1991 through 2003, of the National Water-Quality Assessment (NAWQA) Program of the U.S. Geological Survey determined trace element concentrations in water from 847 wells in the glacial aquifer system. Dissolved iron and manganese concentrations were analyzed in those well samples and in water from an additional 743 NAWQA land-use and major-aquifer survey wells. The samples are from monitoring and water-supply wells. Concentrations of antimony, barium, beryllium, cadmium, chromium, cobalt, copper, iron, lead, manganese, molybdenum, nickel, selenium, strontium, thallium, uranium, and zinc vary as much within NAWQA study units (local scale; ranging in size from a few thousand to tens of thousands of square miles) as over the entire glacial aquifer system.</p><p>Patterns of trace element concentrations in glacial aquifer system ground water were examined by using techniques suitable for a dataset with zero to 80 percent of analytical results reported as below detection. During the period of sampling, the analytical techniques changed, which generally improved the analytical sensitivity. Multiple reporting limits complicated the comparison of detections and concentrations. Regression on Order Statistics was used to model probability distributions and estimate the medians and other quantiles of the trace element concentrations. Strontium and barium were the most frequently detected and usually were present in the highest concentrations. Iron and manganese were the next most commonly detected and next highest in concentrations. Iron concentrations were the most variable with respect to the range of variations (both within local networks and aquifer-wide) and with respect to the disparity between magnitude of concentrations (detections) and the frequency of samples below reporting limits (nondetections). Antimony, beryllium, cadmium, silver, and thallium were detected too infrequently for substantial interpretation of their occurrence or distributions or potential human-health implications.</p><p>For those elements that were more frequently detected, there are some geographic patterns in their occurrence that primarily reflect climate effects. The highest concentrations of several elements were found in the West-Central glacial framework area (High Plains and northern Plains areas). There are few important patterns for any element in relation to land use, well type, or network type. Shallow land-use (monitor) wells had iron concentrations generally lower than the glacial aquifer system wells overall and much lower than major-aquifer survey wells, which comprise mostly private- and public-supply wells. Unlike those for iron, concentration patterns for manganese were similar among shallow land-use wells and major-aquifer survey wells. An apparent relation between low pH and relatively low concentrations of many elements, except lead, may be more indicative of the relatively low dissolved-solids content in wells in the Northeastern United States that comprise the majority of low pH wells, than of a pH dependent pattern.</p><p>Iron and manganese have higher concentrations and larger ranges of concentrations especially under more reducing conditions. Dissolved oxygen and well depth were related to iron and manganese concentrations. Redox conditions also affect several trace elements such as arsenic and copper; however, a comparison of redox categories, based in part on iron and manganese concentrations, indicated that the concentrations of many redox-sensitive elements were not significantly different among redox categories. Some of the redox-related patterns were not what would be expected on the basis of solubility constraints. Furthermore, barium is affected by redox conditions in at least one well network even though it is not a redox-sensitive element. Concentrations of barium in portions of the glacial aquifer system are limited by sulfate, which is strongly affected by redox conditions.</p><p>Few samples had concentrations of any trace element that exceeded drinking-water standards (Maximum Contaminant Levels), for compounds regulated in drinking water or Health-Based Screening Levels for unregulated trace elements. More unregulated trace elements had concentrations greater than benchmarks than regulated trace elements. More samples had manganese concentrations greater its benchmark than any other element in the glacial aquifer system wells. Of the 1,590 wells sampled for manganese, only 556 are for private or public drinking-water supplies, and of those, 9.9 percent (55) exceeded the manganese Lifetime Health Advisory. Concentrations of arsenic, selenium, and uranium less frequently exceeded Maximum Contaminant Levels. There are 29 wells that had 2 element concentrations that exceeded their respective benchmarks. Most concentrations that exceeded a health-based benchmark were from wells in the West-Central area (Iowa, Minnesota, North and South Dakota, Nebraska, and Kansas); however, there is little geographical pattern to the wells with element concentrations of concern.</p>","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/sir20095006","usgsCitation":"Groschen, G.E., Arnold, T., Morrow, W.S., and Warner, K., 2009, Occurrence and distribution of iron, manganese, and selected trace elements in ground water in the glacial aquifer system of the northern United States: U.S. Geological Survey Scientific Investigations Report 2009-5006, xi, 89 p., https://doi.org/10.3133/sir20095006.","productDescription":"xi, 89 p.","temporalStart":"1991-01-01","temporalEnd":"2003-12-31","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":421032,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_86701.htm","linkFileType":{"id":5,"text":"html"}},{"id":12710,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2009/5006/","linkFileType":{"id":5,"text":"html"}},{"id":195959,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"}],"country":"United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -63.90466201228409,\n              48.51275601223605\n            ],\n            [\n              -126.53974492430241,\n              49.21207458339808\n            ],\n            [\n              -127.47398728729782,\n              36.27565543536504\n            ],\n            [\n              -63.603085670560674,\n              36.27565543536504\n            ],\n            [\n              -63.90466201228409,\n              48.51275601223605\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -154.86974304700584,\n              61.85351161170351\n            ],\n            [\n              -154.86974304700584,\n              57.4497276786976\n            ],\n            [\n              -140.41853610687016,\n              57.4497276786976\n            ],\n            [\n              -140.41853610687016,\n              61.85351161170351\n            ],\n            [\n              -154.86974304700584,\n              61.85351161170351\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4afbe4b07f02db69638c","contributors":{"authors":[{"text":"Groschen, George E.","contributorId":99132,"corporation":false,"usgs":true,"family":"Groschen","given":"George","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":302509,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Arnold, Terri 0000-0003-1406-6054 tlarnold@usgs.gov","orcid":"https://orcid.org/0000-0003-1406-6054","contributorId":1598,"corporation":false,"usgs":false,"family":"Arnold","given":"Terri","email":"tlarnold@usgs.gov","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true}],"preferred":false,"id":302507,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Morrow, William S. 0000-0002-2250-3165 wsmorrow@usgs.gov","orcid":"https://orcid.org/0000-0002-2250-3165","contributorId":1886,"corporation":false,"usgs":true,"family":"Morrow","given":"William","email":"wsmorrow@usgs.gov","middleInitial":"S.","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":true,"id":302508,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Warner, Kelly L. klwarner@usgs.gov","contributorId":655,"corporation":false,"usgs":true,"family":"Warner","given":"Kelly L.","email":"klwarner@usgs.gov","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":true,"id":302506,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
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