{"pageNumber":"605","pageRowStart":"15100","pageSize":"25","recordCount":46681,"records":[{"id":70041960,"text":"ofr20121254 - 2012 - Vitrinite reflectance data for Cretaceous marine shales and coals in the Bighorn Basin, north-central Wyoming and south-central Montana","interactions":[],"lastModifiedDate":"2012-12-19T16:05:43","indexId":"ofr20121254","displayToPublicDate":"2012-12-19T00:00:00","publicationYear":"2012","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":"2012-1254","title":"Vitrinite reflectance data for Cretaceous marine shales and coals in the Bighorn Basin, north-central Wyoming and south-central Montana","docAbstract":"The Bighorn Basin is a large Laramide (Late Cretaceous through Eocene) structural and sedimentary basin that encompasses about 10,400 square miles in north-central Wyoming and south-central Montana. The purpose of this report is to present new vitrinite reflectance data collected from Cretaceous marine shales and coals in the Bighorn Basin to better characterize the thermal maturity and petroleum potential of these rocks. Ninety-eight samples from Lower Cretaceous and lowermost Upper Cretaceous strata were collected from well cuttings from wells stored at the U.S. Geological Survey (USGS) Core Research Center in Lakewood, Colorado.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121254","usgsCitation":"Pawlewicz, M.J., and Finn, T.M., 2012, Vitrinite reflectance data for Cretaceous marine shales and coals in the Bighorn Basin, north-central Wyoming and south-central Montana: U.S. Geological Survey Open-File Report 2012-1254, iii, 11 p.; col. ill.; map (col.), https://doi.org/10.3133/ofr20121254.","productDescription":"iii, 11 p.; col. ill.; map (col.)","startPage":"i","endPage":"11","numberOfPages":"14","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":264655,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1254.gif"},{"id":264653,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1254/"},{"id":264654,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1254/OF12-1254.pdf"}],"country":"United States","state":"Wyoming;Montana","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -116.05,40.9947 ], [ -116.05,49.0 ], [ -104.04,49.0 ], [ -104.04,40.9947 ], [ -116.05,40.9947 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50d391e2e4b062c7914ebda9","contributors":{"authors":[{"text":"Pawlewicz, Mark J. pawlewicz@usgs.gov","contributorId":752,"corporation":false,"usgs":true,"family":"Pawlewicz","given":"Mark","email":"pawlewicz@usgs.gov","middleInitial":"J.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":470478,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Finn, Thomas M. 0000-0001-6396-9351 finn@usgs.gov","orcid":"https://orcid.org/0000-0001-6396-9351","contributorId":778,"corporation":false,"usgs":true,"family":"Finn","given":"Thomas","email":"finn@usgs.gov","middleInitial":"M.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":470479,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70041934,"text":"sir20125122 - 2012 - Simulation of groundwater flow and hydrologic effects of groundwater withdrawals from the Kirkwood-Cohansey aquifer system in the Pinelands of southern New Jersey","interactions":[],"lastModifiedDate":"2012-12-19T13:01:59","indexId":"sir20125122","displayToPublicDate":"2012-12-19T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-5122","title":"Simulation of groundwater flow and hydrologic effects of groundwater withdrawals from the Kirkwood-Cohansey aquifer system in the Pinelands of southern New Jersey","docAbstract":"The Kirkwood-Cohansey aquifer system is an important source of present and future water supply in southern New Jersey. Because this unconfined aquifer system also supports sensitive wetland and aquatic habitats within the New Jersey Pinelands (Pinelands), water managers and policy makers need up-to-date information, data, and projections that show the effects of potential increases in groundwater withdrawals on these habitats. Finite-difference groundwater flow models (MODFLOW) were constructed for three drainage basins (McDonalds Branch Basin, 14.3 square kilometers (km<sup>2</sup>); Morses Mill Stream Basin, 21.63 km<sup>2</sup>; and Albertson Brook Basin, 52.27 km<sup>2</sup>) to estimate the effects of potential increases in groundwater withdrawals on water levels and the base-flow portion of streamflow, in wetland and aquatic habitats. Three models were constructed for each drainage basin: a transient model consisting of twenty-four 1-month stress periods (October 2004 through September 2006); a transient model to simulate the 5- to 10-day aquifer tests that were performed as part of the study; and a high-resolution, steady-state model used to assess long-term effects of increased groundwater withdrawals on water levels in wetlands and on base flow. All models were constructed with the same eight-layer structure. The smallest horizontal cell dimensions among the three model areas were 150 meters (m) for the 24-month transient models, 10 m for the steady-state models, and 3 m for the transient aquifer-test models. Boundary flows of particular interest to this study and represented separately are those for wetlands, streams, and evapotranspiration. The final variables calibrated from both transient models were then used in steady-state models to assess the long-term effects of increased groundwater withdrawals on water levels in wetlands and on base flow. Results of aquifer tests conducted in the three study areas illustrate the effects of withdrawals on water levels in wetlands and on base flow. Pumping stresses at aquifer-test sites resulted in measurable drawdown in each observation well installed for the tests. The magnitude of drawdown in shallow wetland observation wells at the end of pumping ranged from 5.5 to 16.7 centimeters (cm). The stresses induced by the respective tests reduced the flow of the smallest stream (McDonalds Branch) by 75 percent and slightly reduced flow in a side channel of Morses Mill Stream, but did not measurably affect the flow of Morses Mill Stream or Albertson Brook. Results of aquifer-test simulations were used to refine the estimates of hydraulic properties used in the models and to confirm the ability of the model to replicate observed hydrologic responses to pumping. Steady-state sensitivity simulation results for a variety of single well locations and depths were used to define overall “best-case” (smallest effect on wetland water levels and base flow) and “worst-case” (greatest effect on wetland water levels and base flow) groundwater withdrawal configurations. “Best-case” configurations are those for which the extent of the wetland areas within a 1-kilometer (km) radius of the withdrawal well is minimized, the well is located at least 100 m and as far from wetland boundaries as possible, and the withdrawal is from a deep well (50–90 m deep). “Worst-case” configurations are those for which the extent of wetlands within a 1-km radius of the withdrawal well is maximized, the well is located 100 m or less from a wetland boundary, and the withdrawal is from a relatively shallow well (30–67 m deep). “Best-” and “worst-case” simulations were applied by locating hypothetical wells across the study areas and assigning groundwater withdrawals so that the sum of the withdrawals for the basin is equal to 5, 10, 15, and 30 percent of overall recharge. The results were compared to the results of simulations of no groundwater withdrawals. Results for withdrawals of 5 percent of recharge show that the area of wetland water-level decline that exceeded 15 cm was as much as 1.5 percent of the total wetland area for the “best-case” simulations and as much as 9.7 percent of the total wetland area for the “worst-case” simulations. For the same withdrawals, base-flow reduction was as much as 5.1 percent for the “best-case” simulations and as much as 8.6 percent for the “worst-case” simulations. Results for withdrawals of 30 percent of recharge show that the area of wetland water-level decline that exceeded 15 cm was as much as 70 percent of the total wetland area for the “best-case” simulations and as much as 84 percent of the total wetland area for the “worst-case” simulations. For the same withdrawals, base-flow reduction was as much as 30 percent for the “best-case” simulations and as much as 51 percent for the “worst-case” simulations. Results for withdrawals of 10 and 15 percent of recharge show decreased water levels and base flow that are intermediate between those simulated for 5 and 30 percent of recharge. Several approaches for applying the results of this study to other parts of the Pinelands were explored. An analytical-modeling technique based on the Thiem equation and image-well theory was developed to estimate local drawdown distributions resulting from withdrawals in other areas within the Pinelands. Results of example applications of this technique were compared with those of the numerical simulations used in this study and were shown to be useful. Differences among the three basins in the simulated percentage of basin wetlands affected by drawdown were found to be related to the proximity of wetlands to streams, the proximity of wetlands to pumped wells, and the vertical conductance of the aquifer system. These factors formed the basis for an index of wetland vulnerability to drawdown. An empirically-derived model based on the Gompertz function and the wetland vulnerability index was developed, tested, and shown to be an effective means to evaluate potential drawdown in wetlands at a basin scale throughout the Pinelands. Base-flow reduction can be estimated from generalized results of the numerical models, estimates of evapotranspiration reduction, or available regional groundwater flow models. These approaches could be used to evaluate alternative water-supply strategies and, in conjunction with ecological-modeling results, to determine maximum basin withdrawal rates within the limits of acceptable ecological change.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125122","collaboration":"Prepared in cooperation with the New Jersey Pinelands Commission","usgsCitation":"Charles, E.G., and Nicholson, R.S., 2012, Simulation of groundwater flow and hydrologic effects of groundwater withdrawals from the Kirkwood-Cohansey aquifer system in the Pinelands of southern New Jersey: U.S. Geological Survey Scientific Investigations Report 2012-5122, xviii, 219 p.; col. ill.; maps (col.); Apendices: 1-2, https://doi.org/10.3133/sir20125122.","productDescription":"xviii, 219 p.; col. ill.; maps (col.); Apendices: 1-2","startPage":"i","endPage":"219","numberOfPages":"242","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":264138,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5122.png"},{"id":264136,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5122/"},{"id":264137,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5122/support/sir2012-5122.pdf"}],"country":"United States","state":"New Jersey","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -75.5598,38.9286 ], [ -75.5598,41.3574 ], [ -73.9025,41.3574 ], [ -73.9025,38.9286 ], [ -75.5598,38.9286 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50d391d5e4b062c7914ebd9d","contributors":{"authors":[{"text":"Charles, Emmanuel G. 0000-0002-3338-4958 echarles@usgs.gov","orcid":"https://orcid.org/0000-0002-3338-4958","contributorId":4280,"corporation":false,"usgs":true,"family":"Charles","given":"Emmanuel","email":"echarles@usgs.gov","middleInitial":"G.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":470411,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nicholson, Robert S. rnichol@usgs.gov","contributorId":2283,"corporation":false,"usgs":true,"family":"Nicholson","given":"Robert","email":"rnichol@usgs.gov","middleInitial":"S.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":470410,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70041944,"text":"70041944 - 2012 - Comparison of five modelling techniques to predict the spatial distribution and abundance of seabirds","interactions":[],"lastModifiedDate":"2012-12-19T16:04:24","indexId":"70041944","displayToPublicDate":"2012-12-19T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Comparison of five modelling techniques to predict the spatial distribution and abundance of seabirds","docAbstract":"Knowledge about the spatial distribution of seabirds at sea is important for conservation.  During marine conservation planning, logistical constraints preclude seabird surveys covering the complete area of interest and spatial distribution of seabirds is frequently inferred from predictive statistical models.  Increasingly complex models are available to relate the distribution and abundance of pelagic seabirds to environmental variables, but a comparison of their usefulness for delineating protected areas for seabirds is lacking.  Here we compare the performance of five modelling techniques (generalised linear models, generalised additive models, Random Forest, boosted regression trees, and maximum entropy) to predict the distribution of Balearic Shearwaters (<i>Puffinus mauretanicus</i>) along the coast of the western Iberian Peninsula.  We used ship transect data from 2004 to 2009 and 13 environmental variables to predict occurrence and density, and evaluated predictive performance of all models using spatially segregated test data.  Predicted distribution varied among the different models, although predictive performance varied little.  An ensemble prediction that combined results from all five techniques was robust and confirmed the existence of marine important bird areas for Balearic Shearwaters in Portugal and Spain.  Our predictions suggested additional areas that would be of high priority for conservation and could be proposed as protected areas.  Abundance data were extremely difficult to predict, and none of five modelling techniques provided a reliable prediction of spatial patterns.  We advocate the use of ensemble modelling that combines the output of several methods to predict the spatial distribution of seabirds, and use these predictions to target separate surveys assessing the abundance of seabirds in areas of regular use.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Biological Conservation","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.biocon.2011.11.013","usgsCitation":"O’Connell, A.F., Gardner, B., Oppel, S., Meirinho, A., Ramírez, I., Miller, P.I., and Louzao, M., 2012, Comparison of five modelling techniques to predict the spatial distribution and abundance of seabirds: Biological Conservation, v. 156, p. 94-104, https://doi.org/10.1016/j.biocon.2011.11.013.","productDescription":"11 p.","startPage":"94","endPage":"104","ipdsId":"IP-034010","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":474198,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/10508/8494","text":"External Repository"},{"id":264652,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":264651,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.biocon.2011.11.013"}],"country":"Portugal;Spain","volume":"156","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50d391c0e4b062c7914ebd8a","contributors":{"authors":[{"text":"O’Connell, Allan F. 0000-0001-7032-7023 aoconnell@usgs.gov","orcid":"https://orcid.org/0000-0001-7032-7023","contributorId":471,"corporation":false,"usgs":true,"family":"O’Connell","given":"Allan","email":"aoconnell@usgs.gov","middleInitial":"F.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":470420,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gardner, Beth","contributorId":91612,"corporation":false,"usgs":false,"family":"Gardner","given":"Beth","affiliations":[{"id":13553,"text":"University of Washington-Seattle","active":true,"usgs":false}],"preferred":false,"id":470426,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Oppel, Steffen","contributorId":44432,"corporation":false,"usgs":true,"family":"Oppel","given":"Steffen","affiliations":[],"preferred":false,"id":470424,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Meirinho, Ana","contributorId":54480,"corporation":false,"usgs":true,"family":"Meirinho","given":"Ana","email":"","affiliations":[],"preferred":false,"id":470425,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ramírez, Iván","contributorId":16724,"corporation":false,"usgs":true,"family":"Ramírez","given":"Iván","affiliations":[],"preferred":false,"id":470421,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Miller, Peter I.","contributorId":31645,"corporation":false,"usgs":true,"family":"Miller","given":"Peter","email":"","middleInitial":"I.","affiliations":[],"preferred":false,"id":470423,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Louzao, Maite","contributorId":30884,"corporation":false,"usgs":true,"family":"Louzao","given":"Maite","email":"","affiliations":[],"preferred":false,"id":470422,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70041865,"text":"ofr20121196 - 2012 - Groundwater, surface-water, and water-chemistry data from C-aquifer monitoring program, northeastern Arizona, 2005-11","interactions":[],"lastModifiedDate":"2021-07-14T21:11:24.234624","indexId":"ofr20121196","displayToPublicDate":"2012-12-18T00:00:00","publicationYear":"2012","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":"2012-1196","displayTitle":"Groundwater, Surface-Water, and Water-Chemistry Data from C-aquifer Monitoring Program, Northeastern Arizona, 2005-11","title":"Groundwater, surface-water, and water-chemistry data from C-aquifer monitoring program, northeastern Arizona, 2005-11","docAbstract":"<p>The C aquifer is a regionally extensive multiple-aquifer system supplying water for municipal, agricultural, and industrial use in northeastern Arizona, northwestern New Mexico, and southeastern Utah. An increase in groundwater withdrawals from the C aquifer coupled with ongoing drought conditions in the study area increase the potential for drawdown within the aquifer. A decrease in the water table and potentiometric surface of C aquifer is illustrated locally by the drying up of Obed Meadows, a natural peat deposit, and Hugo Meadows, a natural wetland, both south of Joseph City, Arizona. Continual increase in water use from the C aquifer, including a planned increase in pumpage by the City of Flagstaff, is justification for continued monitoring of the C-aquifer system in order to quantify physical and chemical responses to pumping stresses.</p>\n<p>Fifteen of the 35 C-aquifer wells analyzed had water-level data sufficient for percentage difference calculation for 2005&ndash;11. Change in water level as a percentage of the initial water-level measurement for these 15 wells ranged from about -0.2 to about -0.5 percent. For historical water-level data, changes in water levels were greatest around pumping centers, as indicated by a -97.0 feet (percentage difference of -16.5 percent) change over the period of record (1962&ndash;2005) for the Lake Mary 1 Well near Flagstaff, Arizona. In more rural areas of the C aquifer, water levels showed less change for both the temporal focus of this report (2005&ndash;11) and for historical values.</p>\n<p>Continuous records of surface-water discharge from 2005 to 2007 for three discontinued streamflow-gaging stations (Clear Creek near Winslow, AZ, 09399000; Clear Creek below McHood Lake near Winslow, AZ, 09399100; and Chevelon Creek near Winslow, AZ, 09398000) were tabulated. For the period of record, Clear Creek near Winslow, AZ, and Chevelon Creek near Winslow, AZ, showed seasonal discharge distributions indicative of natural streams in the southwestern United States. Clear Creek below McHood Lake near Winslow, AZ, showed discharge distribution indicative of perennial spring flow with little variation annually.</p>\n<p>Physical and chemical data collected during four baseflow investigations (summer 2005, summer 2006, summer 2008, and winter 2010) conducted on Clear Creek, Chevelon Creek, and a portion of the Little Colorado River were compiled and analyzed. Data from 7 sampling sites established on the Little Colorado River, 11 sites along Chevelon Creek, and 14 sites along Clear Creek were included. For the four baseflow investigations presented, a 2,000&ndash;3,000 microsiemens per centimeter increase in specific conductance was measured in Chevelon Creek from near its headwaters to the confluence with the Little Colorado River because of the contribution of highly conductive spring discharge. Clear Creek showed a less consistent pattern of increase in specific conductance with distance, but still exhibited changes on the order of 5,000 microsiemens per centimeter over just a few river miles.</p>\n<p>Water-chemistry data for selected wells and baseflow investigations sites are presented. No well samples analyzed exceeded the U.S. Environmental Protection Agency Maximum Contaminant Level standards for drinking water, but several samples exceeded Secondary Maximum Contaminant Level standards for chloride, fluoride, sulfate, iron, and total dissolved solids.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121196","collaboration":"Prepared in cooperation with the Bureau of Indian Affairs","usgsCitation":"Brown, C.R., and Macy, J.P., 2012, Groundwater, surface-water, and water-chemistry data from C-aquifer monitoring program, northeastern Arizona, 2005-11 (Version 1.0: Originally posted December 2012; Version 1.1: March 2013): U.S. Geological Survey Open-File Report 2012-1196, vi, 38 p., https://doi.org/10.3133/ofr20121196.","productDescription":"vi, 38 p.","numberOfPages":"46","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":264092,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1196.gif"},{"id":269267,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1196/"},{"id":269268,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1196/of2012-1196.pdf"}],"scale":"100000","projection":"Lambert Conformal Conic projection","country":"United States","state":"Arizona","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -111.7913818359375,\n              34.384246040152206\n            ],\n            [\n              -111.7913818359375,\n              35.98245135784044\n            ],\n            [\n              -109.1766357421875,\n              35.98245135784044\n            ],\n            [\n              -109.1766357421875,\n              34.384246040152206\n            ],\n            [\n              -111.7913818359375,\n              34.384246040152206\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","edition":"Version 1.0: Originally posted December 2012; Version 1.1: March 2013","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50d20b86e4b08b071e771b19","contributors":{"authors":[{"text":"Brown, Christopher R. crbrown@usgs.gov","contributorId":4751,"corporation":false,"usgs":true,"family":"Brown","given":"Christopher","email":"crbrown@usgs.gov","middleInitial":"R.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":470263,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Macy, Jamie P. 0000-0003-3443-0079 jpmacy@usgs.gov","orcid":"https://orcid.org/0000-0003-3443-0079","contributorId":2173,"corporation":false,"usgs":true,"family":"Macy","given":"Jamie","email":"jpmacy@usgs.gov","middleInitial":"P.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":470262,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70041860,"text":"70041860 - 2012 - Predominant-period site classification for response spectra prediction equations in Italy","interactions":[],"lastModifiedDate":"2012-12-18T10:46:56","indexId":"70041860","displayToPublicDate":"2012-12-18T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":960,"text":"BSSA","active":true,"publicationSubtype":{"id":10}},"title":"Predominant-period site classification for response spectra prediction equations in Italy","docAbstract":"We propose a site‐classification scheme based on the predominant period of the site, as determined from the average horizontal‐to‐vertical (H/V) spectral ratios of ground motion. Our scheme extends Zhao <i>et al.</i> (2006) classifications by adding two classes, the most important of which is defined by flat H/V ratios with amplitudes less than 2. The proposed classification is investigated by using 5%‐damped response spectra from Italian earthquake records. We select a dataset of 602 three‐component analog and digital recordings from 120 earthquakes recorded at 214 seismic stations within a hypocentral distance of 200 km. Selected events are in the moment‐magnitude range 4.0≤M<sub>w</sub>≤6.8 and focal depths from a few kilometers to 46 km. We computed H/V ratios for these data and used them to classify each site into one of six classes. We then investigate the impact of this classification scheme on empirical ground‐motion prediction equations (GMPEs) by comparing its performance with that of the conventional rock/soil classification. Although the adopted approach results in only a small reduction of the overall standard deviation, the use of H/V spectral ratios in site classification does capture the signature of sites with flat frequency‐response, as well as deep and shallow‐soil profiles, characterized by long‐ and short‐period resonance, respectively; in addition, the classification scheme is relatively quick and inexpensive, which is an advantage over schemes based on measurements of shear‐wave velocity.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"BSSA","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Seismological Society of America","publisherLocation":"El Cerrito, CA","doi":"10.1785/0120110084","usgsCitation":"Di Alessandro, C., Bonilla, L.F., Boore, D.M., Rovelli, A., and Scotti, O., 2012, Predominant-period site classification for response spectra prediction equations in Italy: BSSA, p. 680-695, https://doi.org/10.1785/0120110084.","productDescription":"16 p.","startPage":"680","endPage":"695","additionalOnlineFiles":"Y","ipdsId":"IP-029087","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":264094,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":264093,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1785/0120110084"}],"country":"Italy","noUsgsAuthors":false,"publicationDate":"2012-03-29","publicationStatus":"PW","scienceBaseUri":"50d20bb0e4b08b071e771b38","contributors":{"authors":[{"text":"Di Alessandro, Carola","contributorId":43436,"corporation":false,"usgs":true,"family":"Di Alessandro","given":"Carola","email":"","affiliations":[],"preferred":false,"id":470255,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bonilla, Luis Fabian","contributorId":17894,"corporation":false,"usgs":true,"family":"Bonilla","given":"Luis","email":"","middleInitial":"Fabian","affiliations":[],"preferred":false,"id":470253,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Boore, David M. boore@usgs.gov","contributorId":2509,"corporation":false,"usgs":true,"family":"Boore","given":"David","email":"boore@usgs.gov","middleInitial":"M.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":false,"id":470252,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rovelli, Antonio","contributorId":79378,"corporation":false,"usgs":false,"family":"Rovelli","given":"Antonio","email":"","affiliations":[{"id":12533,"text":"Istituto Nazionale di Geofisica e Vulcanologia – Sezione di Palermo- Via Ugo La Malfa, 153,  90146 Palermo, Italy","active":true,"usgs":false}],"preferred":false,"id":470256,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Scotti, Oona","contributorId":38873,"corporation":false,"usgs":true,"family":"Scotti","given":"Oona","email":"","affiliations":[],"preferred":false,"id":470254,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70041920,"text":"sir20125236 - 2012 - Numerical simulation of groundwater movement and managed aquifer recharge from Sand Hollow Reservoir, Hurricane Bench area, Washington County, Utah","interactions":[],"lastModifiedDate":"2017-01-04T10:28:36","indexId":"sir20125236","displayToPublicDate":"2012-12-18T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-5236","title":"Numerical simulation of groundwater movement and managed aquifer recharge from Sand Hollow Reservoir, Hurricane Bench area, Washington County, Utah","docAbstract":"<p>The Hurricane Bench area of Washington County, Utah, is a 70 square-mile area extending south from the Virgin River and encompassing Sand Hollow basin. Sand Hollow Reservoir, located on Hurricane Bench, was completed in March 2002 and is operated primarily as a managed aquifer recharge project by the Washington County Water Conservancy District. The reservoir is situated on a thick sequence of the Navajo Sandstone and Kayenta Formation. Total recharge to the underlying Navajo aquifer from the reservoir was about 86,000 acre-feet from 2002 to 2009. Natural recharge as infiltration of precipitation was approximately 2,100 acre-feet per year for the same period. Discharge occurs as seepage to the Virgin River, municipal and irrigation well withdrawals, and seepage to drains at the base of reservoir dams. Within the Hurricane Bench area, unconfined groundwater-flow conditions generally exist throughout the Navajo Sandstone. Navajo Sandstone hydraulic-conductivity values from regional aquifer testing range from 0.8 to 32 feet per day. The large variability in hydraulic conductivity is attributed to bedrock fractures that trend north-northeast across the study area.</p><p>A numerical groundwater-flow model was developed to simulate groundwater movement in the Hurricane Bench area and to simulate the movement of managed aquifer recharge from Sand Hollow Reservoir through the groundwater system. The model was calibrated to combined steady- and transient-state conditions. The steady-state portion of the simulation was developed and calibrated by using hydrologic data that represented average conditions for 1975. The transient-state portion of the simulation was developed and calibrated by using hydrologic data collected from 1976 to 2009. Areally, the model grid was 98 rows by 76 columns with a variable cell size ranging from about 1.5 to 25 acres. Smaller cells were used to represent the reservoir to accurately simulate the reservoir bathymetry and nearby monitoring wells; larger cells were used in the northern and southern portions of the model where water-level data were limited. Vertically, the aquifer system was divided into 10 layers, which incorporated the Navajo Sandstone and Kayenta Formation. The model simulated recharge to the groundwater system as natural infiltration of precipitation and as infiltration of managed aquifer recharge from Sand Hollow Reservoir. Groundwater discharge was simulated as well withdrawals, shallow drains at the base of reservoir dams, and seepage to the Virgin River. During calibration, variables were adjusted within probable ranges to minimize differences among model-simulated and observed water levels, groundwater travel times, drain discharges, and monthly estimated reservoir recharge.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125236","collaboration":"Prepared in cooperation with the Washington County Water Conservancy District","usgsCitation":"Marston, T.M., and Heilweil, V.M., 2012, Numerical simulation of groundwater movement and managed aquifer recharge from Sand Hollow Reservoir, Hurricane Bench area, Washington County, Utah: U.S. Geological Survey Scientific Investigations Report 2012-5236, vi, 34 p., https://doi.org/10.3133/sir20125236.","productDescription":"vi, 34 p.","numberOfPages":"44","costCenters":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":264131,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5236.jpg"},{"id":264129,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5236/"},{"id":264130,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5236/pdf/sir20125236.pdf"}],"country":"United States","state":"Utah","county":"Washington County","otherGeospatial":"Sand Hollow Reservoir","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -113.39374,37.101658 ], [ -113.39374,37.127394 ], [ -113.35936,37.127394 ], [ -113.35936,37.101658 ], [ -113.39374,37.101658 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50d20bace4b08b071e771b34","contributors":{"authors":[{"text":"Marston, Thomas M. 0000-0003-1053-4172 tmarston@usgs.gov","orcid":"https://orcid.org/0000-0003-1053-4172","contributorId":3272,"corporation":false,"usgs":true,"family":"Marston","given":"Thomas","email":"tmarston@usgs.gov","middleInitial":"M.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":470384,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Heilweil, Victor M. heilweil@usgs.gov","contributorId":837,"corporation":false,"usgs":true,"family":"Heilweil","given":"Victor","email":"heilweil@usgs.gov","middleInitial":"M.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":470383,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70041946,"text":"70041946 - 2012 - Large-scale monitoring of shorebird populations using count data and N-mixture models: Black Oystercatcher (<i>Haematopus bachmani</i>) surveys by land and sea","interactions":[],"lastModifiedDate":"2017-11-21T15:46:12","indexId":"70041946","displayToPublicDate":"2012-12-18T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3544,"text":"The Auk","onlineIssn":"1938-4254","printIssn":"0004-8038","active":true,"publicationSubtype":{"id":10}},"title":"Large-scale monitoring of shorebird populations using count data and N-mixture models: Black Oystercatcher (<i>Haematopus bachmani</i>) surveys by land and sea","docAbstract":"Large-scale monitoring of bird populations is often based on count data collected across spatial scales that may include multiple physiographic regions and habitat types. Monitoring at large spatial scales may require multiple survey platforms (e.g., from boats and land when monitoring coastal species) and multiple survey methods. It becomes especially important to explicitly account for detection probability when analyzing count data that have been collected using multiple survey platforms or methods. We evaluated a new analytical framework, <i>N</i>-mixture models, to estimate actual abundance while accounting for multiple detection biases. During May 2006, we made repeated counts of Black Oystercatchers (<i>Haematopus bachmani</i>) from boats in the Puget Sound area of Washington (<i>n</i> = 55 sites) and from land along the coast of Oregon (<i>n</i> = 56 sites). We used a Bayesian analysis of N-mixture models to (1) assess detection probability as a function of environmental and survey covariates and (2) estimate total Black Oystercatcher abundance during the breeding season in the two regions. Probability of detecting individuals during boat-based surveys was 0.75 (95% credible interval: 0.42–0.91) and was not influenced by tidal stage. Detection probability from surveys conducted on foot was 0.68 (0.39–0.90); the latter was not influenced by fog, wind, or number of observers but was ~35% lower during rain. The estimated population size was 321 birds (262–511) in Washington and 311 (276–382) in Oregon. N-mixture models provide a flexible framework for modeling count data and covariates in large-scale bird monitoring programs designed to understand population change.","language":"English","publisher":"American Ornithological Society","doi":"10.1525/auk.2012.11253","usgsCitation":"Lyons, J., Andrew, R.J., Thomas, S.M., Elliott-Smith, E., Evenson, J.R., Kelly, E.G., Milner, R.L., Nysewander, D.R., and Andres, B.A., 2012, Large-scale monitoring of shorebird populations using count data and N-mixture models: Black Oystercatcher (<i>Haematopus bachmani</i>) surveys by land and sea: The Auk, v. 129, no. 4, p. 645-652, https://doi.org/10.1525/auk.2012.11253.","productDescription":"8 p.","startPage":"645","endPage":"652","ipdsId":"IP-037900","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":474201,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1525/auk.2012.11253","text":"Publisher Index Page"},{"id":264669,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon;Washington","volume":"129","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50d4cc56e4b0c6073c90208e","contributors":{"authors":[{"text":"Lyons, James E.","contributorId":35461,"corporation":false,"usgs":true,"family":"Lyons","given":"James E.","affiliations":[],"preferred":false,"id":470435,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Andrew, Royle J.","contributorId":69800,"corporation":false,"usgs":true,"family":"Andrew","given":"Royle","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":470439,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thomas, Susan M.","contributorId":15452,"corporation":false,"usgs":true,"family":"Thomas","given":"Susan","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":470433,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Elliott-Smith, Elise eelliott-smith@usgs.gov","contributorId":3645,"corporation":false,"usgs":true,"family":"Elliott-Smith","given":"Elise","email":"eelliott-smith@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":470432,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Evenson, Joseph R.","contributorId":62481,"corporation":false,"usgs":true,"family":"Evenson","given":"Joseph","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":470437,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kelly, Elizabeth G.","contributorId":99847,"corporation":false,"usgs":true,"family":"Kelly","given":"Elizabeth","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":470440,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Milner, Ruth L.","contributorId":48061,"corporation":false,"usgs":true,"family":"Milner","given":"Ruth","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":470436,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Nysewander, David R.","contributorId":23036,"corporation":false,"usgs":true,"family":"Nysewander","given":"David","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":470434,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Andres, Brad A.","contributorId":68811,"corporation":false,"usgs":true,"family":"Andres","given":"Brad","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":470438,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70041864,"text":"70041864 - 2012 - Fixed bed sorption of phosphorus from wastewater using iron oxide-based media derived from acid mine drainage","interactions":[],"lastModifiedDate":"2013-02-19T07:53:38","indexId":"70041864","displayToPublicDate":"2012-12-18T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3728,"text":"Water, Air, & Soil Pollution","onlineIssn":"1573-2932","printIssn":"0049-6979","active":true,"publicationSubtype":{"id":10}},"title":"Fixed bed sorption of phosphorus from wastewater using iron oxide-based media derived from acid mine drainage","docAbstract":"Phosphorus (P) releases to the environment have been implicated in the eutrophication of important water bodies worldwide. Current technology for the removal of P from wastewaters consists of treatment with aluminum (Al) or iron (Fe) salts, but is expensive. The neutralization of acid mine drainage (AMD) generates sludge rich in Fe and Al oxides that has hitherto been considered a waste product, but these sludges could serve as an economical adsorption media for the removal of P from wastewaters. Therefore, we have evaluated an AMD-derived media as a sorbent for P in fixed bed sorption systems. The homogenous surface diffusion model (HSDM) was used to analyze fixed bed test data and to determine the value of related sorption parameters. The surface diffusion modulus Ed was found to be a useful predictor of sorption kinetics. Values of Ed < 0.2 were associated with early breakthrough of P, while more desirable S-shaped breakthrough curves resulted when 0.2 < Ed < 0.5. Computer simulations of the fixed bed process with the HSDM confirmed that if Ed was known, the shape of the breakthrough curve could be calculated. The surface diffusion coefficient D s was a critical factor in the calculation of Ed and could be estimated based on the sorption test conditions such as media characteristics, and influent flow rate and concentration. Optimal test results were obtained with a relatively small media particle size (average particle radius 0.028 cm) and resulted in 96 % removal of P from the influent over 46 days of continuous operation. These results indicate that fixed bed sorption of P would be a feasible option for the utilization of AMD residues, thus helping to decrease AMD treatment costs while at the same time ameliorating the impacts of P contamination.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Water, Air, and Soil Pollution","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","publisherLocation":"Amsterdam, Netherlands","doi":"10.1007/s11270-012-1262-x","usgsCitation":"Sibrell, P.L., and Tucker, T., 2012, Fixed bed sorption of phosphorus from wastewater using iron oxide-based media derived from acid mine drainage: Water, Air, & Soil Pollution, v. 223, no. 8, p. 5105-5117, https://doi.org/10.1007/s11270-012-1262-x.","productDescription":"13 p.","startPage":"5105","endPage":"5117","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":264091,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":264090,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s11270-012-1262-x"}],"country":"United States","state":"Pennsylvania","city":"Brandy Camp","otherGeospatial":"Blue Valley","volume":"223","issue":"8","noUsgsAuthors":false,"publicationDate":"2012-07-19","publicationStatus":"PW","scienceBaseUri":"50d20b82e4b08b071e771b15","contributors":{"authors":[{"text":"Sibrell, Philip L. psibrell@usgs.gov","contributorId":2006,"corporation":false,"usgs":true,"family":"Sibrell","given":"Philip","email":"psibrell@usgs.gov","middleInitial":"L.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":470260,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tucker, T.W.","contributorId":85409,"corporation":false,"usgs":true,"family":"Tucker","given":"T.W.","email":"","affiliations":[],"preferred":false,"id":470261,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70041889,"text":"70041889 - 2012 - Mapping anuran habitat suitability to estimate effects of grassland and wetland conservation programs","interactions":[],"lastModifiedDate":"2018-01-04T12:08:46","indexId":"70041889","displayToPublicDate":"2012-12-18T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1337,"text":"Copeia","active":true,"publicationSubtype":{"id":10}},"title":"Mapping anuran habitat suitability to estimate effects of grassland and wetland conservation programs","docAbstract":"The conversion of the Northern Great Plains of North America to a landscape favoring agricultural commodity production has negatively impacted wildlife habitats. To offset impacts, conservation programs have been implemented by the U.S. Department of Agriculture and other agencies to restore grassland and wetland habitat components. To evaluate effects of these efforts on anuran habitats, we used call survey data and environmental data in ecological niche factor analyses implemented through the program Biomapper to quantify habitat suitability for five anuran species within a 196 km<sup>2</sup> study area. Our amphibian call surveys identified Northern Leopard Frogs (<i>Lithobates pipiens</i>), Wood Frogs (<i>Lithobates sylvaticus</i>), Boreal Chorus Frogs (<i>Pseudacris maculata</i>), Great Plains Toads (<i>Anaxyrus cognatus</i>), and Woodhouse’s Toads (<i>Anaxyrus woodhousii</i>) occurring within the study area. Habitat suitability maps developed for each species revealed differing patterns of suitable habitat among species. The most significant findings of our mapping effort were 1) the influence of deep-water overwintering wetlands on suitable habitat for all species encountered except the Boreal Chorus Frog; 2) the lack of overlap between areas of core habitat for both the Northern Leopard Frog and Wood Frog compared to the core habitat for both toad species; and 3) the importance of conservation programs in providing grassland components of Northern Leopard Frog and Wood Frog habitat. The differences in habitats suitable for the five species we studied in the Northern Great Plains, i.e., their ecological niches, highlight the importance of utilizing an ecosystem based approach that considers the varying needs of multiple species in the development of amphibian conservation and management plans.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Copeia","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"American Society of Ichthyologists and Herpetologists","publisherLocation":"Lawrence, KS","doi":"10.1643/CH-11-119","usgsCitation":"Mushet, D.M., Euliss, N.H., and Stockwell, C., 2012, Mapping anuran habitat suitability to estimate effects of grassland and wetland conservation programs: Copeia, v. 2012, no. 2, p. 321-330, https://doi.org/10.1643/CH-11-119.","productDescription":"10 p.","startPage":"321","endPage":"330","ipdsId":"IP-030690","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":264133,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":264132,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1643/CH-11-119"}],"volume":"2012","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50d20ba7e4b08b071e771b30","contributors":{"authors":[{"text":"Mushet, David M. 0000-0002-5910-2744 dmushet@usgs.gov","orcid":"https://orcid.org/0000-0002-5910-2744","contributorId":1299,"corporation":false,"usgs":true,"family":"Mushet","given":"David","email":"dmushet@usgs.gov","middleInitial":"M.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":470316,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Euliss, Ned H. Jr. ceuliss@usgs.gov","contributorId":2916,"corporation":false,"usgs":true,"family":"Euliss","given":"Ned","suffix":"Jr.","email":"ceuliss@usgs.gov","middleInitial":"H.","affiliations":[],"preferred":false,"id":470317,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stockwell, Craig A.","contributorId":55257,"corporation":false,"usgs":true,"family":"Stockwell","given":"Craig A.","affiliations":[],"preferred":false,"id":470318,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70041900,"text":"ds715 - 2012 - Hydrologic and geochemical data collected near Skewed Reservoir, an impoundment for coal-bed natural gas produced water, Powder River Basin, Wyoming","interactions":[],"lastModifiedDate":"2012-12-18T17:35:33","indexId":"ds715","displayToPublicDate":"2012-12-18T00:00:00","publicationYear":"2012","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":"715","title":"Hydrologic and geochemical data collected near Skewed Reservoir, an impoundment for coal-bed natural gas produced water, Powder River Basin, Wyoming","docAbstract":"The Powder River Structural Basin is one of the largest producers of coal-bed natural gas (CBNG) in the United States. An important environmental concern in the Basin is the fate of groundwater that is extracted during CBNG production. Most of this produced water is disposed of in unlined surface impoundments. A 6-year study of groundwater flow and subsurface water and soil chemistry was conducted at one such impoundment, Skewed Reservoir. Hydrologic and geochemical data collected as part of that study are contained herein. Data include chemistry of groundwater obtained from a network of 21 monitoring wells and three suction lysimeters and chemical and physical properties of soil cores including chemistry of water/soil extracts, particle-size analyses, mineralogy, cation-exchange capacity, soil-water content, and total carbon and nitrogen content of soils.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds715","collaboration":"Prepared in cooperation with the Bureau of Land Management.  The Downloads Directory contains 16 appendixes, numbering 1-5, 6A-6F, 7-11.  Please see the \"View companion files\" link above for access to these appendixes.","usgsCitation":"Healy, R.W., Rice, C.A., and Bartos, T.T., 2012, Hydrologic and geochemical data collected near Skewed Reservoir, an impoundment for coal-bed natural gas produced water, Powder River Basin, Wyoming: U.S. Geological Survey Data Series 715, Report: iv, 6 p.; Downloads Directory, https://doi.org/10.3133/ds715.","productDescription":"Report: iv, 6 p.; Downloads Directory","numberOfPages":"13","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2003-07-01","temporalEnd":"2005-05-31","costCenters":[{"id":440,"text":"National Research Program Water Resources","active":false,"usgs":true}],"links":[{"id":264124,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds_715.gif"},{"id":264121,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/715/"},{"id":264123,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/715/downloads/"},{"id":264122,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/715/DS715_508.pdf"}],"country":"United States","state":"Wyoming","otherGeospatial":"Poweder River;Skewed Reservoir","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -106.120833,44.113611 ], [ -106.120833,44.120833 ], [ -106.113889,44.120833 ], [ -106.113889,44.113611 ], [ -106.120833,44.113611 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50d20b8ee4b08b071e771b1d","contributors":{"authors":[{"text":"Healy, Richard W. 0000-0002-0224-1858 rwhealy@usgs.gov","orcid":"https://orcid.org/0000-0002-0224-1858","contributorId":658,"corporation":false,"usgs":true,"family":"Healy","given":"Richard","email":"rwhealy@usgs.gov","middleInitial":"W.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":470340,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rice, Cynthia A.","contributorId":87140,"corporation":false,"usgs":true,"family":"Rice","given":"Cynthia","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":470342,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bartos, Timothy T. 0000-0003-1803-4375 ttbartos@usgs.gov","orcid":"https://orcid.org/0000-0003-1803-4375","contributorId":1826,"corporation":false,"usgs":true,"family":"Bartos","given":"Timothy","email":"ttbartos@usgs.gov","middleInitial":"T.","affiliations":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"preferred":true,"id":470341,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70041897,"text":"70041897 - 2012 - Comparing seasonal dynamics of the Lake Huron zooplankton community between 1983-1984 and 2007 and revisiting the impact of <i>Bythotrephes</i> planktivory","interactions":[],"lastModifiedDate":"2012-12-19T15:42:09","indexId":"70041897","displayToPublicDate":"2012-12-18T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Comparing seasonal dynamics of the Lake Huron zooplankton community between 1983-1984 and 2007 and revisiting the impact of <i>Bythotrephes</i> planktivory","docAbstract":"Zooplankton community composition can be influenced by lake productivity as well as planktivory by fish or invertebrates. Previous analyses based on long-term Lake Huron zooplankton data from August reported a shift in community composition between the 1980s and 2000s: proportional biomass of calanoid copepods increased while that of cyclopoid copepods and herbivorous cladocerans decreased. Herein, we used seasonally collected data from Lake Huron in 1983–1984 and 2007 and reported similar shifts in proportional biomass. We also used a series of generalized additive models to explore differences in seasonal abundance by species and found that all three cyclopoid copepod species (<i>Diacyclops thomasi, Mesocylops edax, Tropocyclops prasinus mexicanus</i>) exhibited higher abundance in 1983–1984 than in 2007. Surprisingly, only one (<i>Epischura lacustris</i>) of seven calanoid species exhibited higher abundance in 2007. The results for cladocerans were also mixed with <i>Bosmina</i> spp. exhibiting higher abundance in 1983–1984, while <i>Daphnia galeata mendotae</i> reached a higher level of abundance in 2007. We used a subset of the 2007 data to estimate not only the vertical distribution of <i>Bythotrephes longimanus</i> and their prey, but also the consumption by <i>Bythotrephes</i> in the top 20 m of water. This epilimnetic layer was dominated by copepod copepodites and nauplii, and consumption either exceeded (Hammond Bay site) or equaled 65% (Detour site) of epilimnetic zooplankton production. The lack of spatial overlap between <i>Bythotrephes</i> and herbivorous cladocerans and cyclopoid copepod prey casts doubt on the hypothesis that <i>Bythotrephes</i> planktivory was the primary driver underlying the community composition changes in the 2000s.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Great Lakes Research","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.jglr.2012.04.007","usgsCitation":"Bunnell, D., Keeler, K.M., Puchala, E.A., Davis, B.M., and Pothoven, S.A., 2012, Comparing seasonal dynamics of the Lake Huron zooplankton community between 1983-1984 and 2007 and revisiting the impact of <i>Bythotrephes</i> planktivory: Journal of Great Lakes Research, v. 38, no. 3, p. 451-462, https://doi.org/10.1016/j.jglr.2012.04.007.","productDescription":"12 p.","startPage":"451","endPage":"462","ipdsId":"IP-038228","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":264638,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":264637,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.jglr.2012.04.007"}],"country":"United States;Canada","otherGeospatial":"Lake Huron","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -83.6431,42.9928 ], [ -83.6431,45.9218 ], [ -81.2795,45.9218 ], [ -81.2795,42.9928 ], [ -83.6431,42.9928 ] ] ] } } ] }","volume":"38","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50d9742ce4b07a5aecdeb8d6","contributors":{"authors":[{"text":"Bunnell, David B.","contributorId":14360,"corporation":false,"usgs":true,"family":"Bunnell","given":"David B.","affiliations":[],"preferred":false,"id":470332,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Keeler, Kevin M. 0000-0002-8118-0060 kkeeler@usgs.gov","orcid":"https://orcid.org/0000-0002-8118-0060","contributorId":4377,"corporation":false,"usgs":true,"family":"Keeler","given":"Kevin","email":"kkeeler@usgs.gov","middleInitial":"M.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":470331,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Puchala, Elizabeth A.","contributorId":38862,"corporation":false,"usgs":true,"family":"Puchala","given":"Elizabeth","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":470333,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Davis, Bruce M. bmdavis@usgs.gov","contributorId":4227,"corporation":false,"usgs":true,"family":"Davis","given":"Bruce","email":"bmdavis@usgs.gov","middleInitial":"M.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":470330,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pothoven, Steven A.","contributorId":92998,"corporation":false,"usgs":false,"family":"Pothoven","given":"Steven","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":470334,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70041880,"text":"ofr20121251 - 2012 - Updates to watershed modeling in the Potholes Reservoir basin, Washington-a supplement to Scientific Investigation Report 2009-5081","interactions":[],"lastModifiedDate":"2012-12-18T14:27:18","indexId":"ofr20121251","displayToPublicDate":"2012-12-18T00:00:00","publicationYear":"2012","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":"2012-1251","title":"Updates to watershed modeling in the Potholes Reservoir basin, Washington-a supplement to Scientific Investigation Report 2009-5081","docAbstract":"A previous collaborative effort between the U.S. Geological Survey and the Bureau of Reclamation resulted in a watershed model for four watersheds that discharge into Potholes Reservoir, Washington. Since the model was constructed, two new meteorological sites have been established that provide more reliable real-time information. The Bureau of Reclamation was interested in incorporating this new information into the existing watershed model developed in 2009, and adding measured snowpack information to update simulated results and to improve forecasts of runoff. This report includes descriptions of procedures to aid a user in making model runs, including a description of the Object User Interface for the watershed model with details on specific keystrokes to generate model runs for the contributing basins. A new real-time, data-gathering computer program automates the creation of the model input files and includes the new meteorological sites. The 2009 watershed model was updated with the new sites and validated by comparing simulated results to measured data. As in the previous study, the updated model (2012 model) does a poor job of simulating individual storms, but a reasonably good job of simulating seasonal runoff volumes. At three streamflow-gaging stations, the January 1 to June 30 retrospective forecasts of runoff volume for years 2010 and 2011 were within 40 percent of the measured runoff volume for five of the six comparisons, ranging from -39.4 to 60.3 percent difference. A procedure for collecting measured snowpack data and using the data in the watershed model for forecast model runs, based on the Ensemble Streamflow Prediction method, is described, with an example that uses 2004 snow-survey data.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121251","collaboration":"For additional information see <a href=\"http://pubs.er.usgs.gov/publication/sir20095081\" target=\"_blank\">SIR 2009-5081</a>.","usgsCitation":"Mastin, M., 2012, Updates to watershed modeling in the Potholes Reservoir basin, Washington-a supplement to Scientific Investigation Report 2009-5081: U.S. Geological Survey Open-File Report 2012-1251, vii, 52 p., https://doi.org/10.3133/ofr20121251.","productDescription":"vii, 52 p.","numberOfPages":"59","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":264116,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1251.jpg"},{"id":264114,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1251/"},{"id":264115,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1251/pdf/ofr20121251.pdf"}],"country":"United States","state":"Washington","otherGeospatial":"Potholes Reservoir Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -119.50,47.83 ], [ -119.50,48.16 ], [ -117.83,48.16 ], [ -117.83,47.83 ], [ -119.50,47.83 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50d20bb4e4b08b071e771b3c","contributors":{"authors":[{"text":"Mastin, Mark","contributorId":41312,"corporation":false,"usgs":true,"family":"Mastin","given":"Mark","affiliations":[],"preferred":false,"id":470286,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70041849,"text":"ofr20121217 - 2012 - Quaternary geologic map of the Glasgow 1° x 2° quadrangle, Montana","interactions":[],"lastModifiedDate":"2012-12-26T14:47:22","indexId":"ofr20121217","displayToPublicDate":"2012-12-17T00:00:00","publicationYear":"2012","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":"2012-1217","title":"Quaternary geologic map of the Glasgow 1° x 2° quadrangle, Montana","docAbstract":"The Glasgow quadrangle encompasses approximately 16,084 km<sup>2</sup> (6,210 mi<sup>2</sup>). The northern boundary is the Montana/Saskatchewan (U.S./Canada) boundary. The quadrangle is in the Northern Plains physiographic province and it includes the Boundary Plateau, Peerless Plateau, and Larb Hills. The primary river is the Milk River.\n\nThe map units are surficial deposits and materials, not landforms. Deposits that comprise some constructional landforms (for example, ground-moraine deposits, end-moraine deposits, and stagnation-moraine deposits, all composed of till) are distinguished for purposes of reconstruction of glacial history. Surficial deposits and materials are assigned to 23 map units on the basis of genesis, age, lithology or composition, texture or particle size, and other physical, chemical, and engineering characteristics. It is not a map of soils that are recognized in pedology or agronomy. Rather, it is a generalized map of soils recognized in engineering geology, or of substrata or parent materials in which pedologic or agronomic soils are formed. Glaciotectonic (ice-thrust) structures and deposits are mapped separately, represented by a symbol. The surficial deposits are glacial, ice-contact, glaciofluvial, alluvial, lacustrine, eolian, colluvial, and mass-movement deposits. Residuum, a surficial material, also is mapped. \n\nTill of late Wisconsin age is represented by three map units. Till of Illinoian age is also represented locally but is widespread in the subsurface.\n\nThis map was prepared to serve as a database for compilation of a Quaternary geologic map of the United States and Canada (scale 1:1,000,000). Letter symbols for the map units are those used for the same units in the Quaternary Geologic Atlas of the United States map series.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121217","collaboration":"Prepared in cooperation with the Montana Bureau of Mines and Geology","usgsCitation":"Fullerton, D.S., Colton, R.B., and Bush, C.A., 2012, Quaternary geologic map of the Glasgow 1° x 2° quadrangle, Montana: U.S. Geological Survey Open-File Report 2012-1217, Map: 52 x 36 inches; Downloads Directory, https://doi.org/10.3133/ofr20121217.","productDescription":"Map: 52 x 36 inches; Downloads Directory","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":264794,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1217.gif"},{"id":264085,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2012/1217/downloads/"},{"id":264083,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1217/"},{"id":264084,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1217/OF12_1217_508.pdf"}],"scale":"250000","country":"United States","state":"Montana","otherGeospatial":"Milk River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -108.0,48.0 ], [ -108.0,49.0 ], [ -106.0,49.0 ], [ -106.0,48.0 ], [ -108.0,48.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50e4989ae4b0e8fec6cd9d2a","contributors":{"authors":[{"text":"Fullerton, David S. fullerton@usgs.gov","contributorId":448,"corporation":false,"usgs":true,"family":"Fullerton","given":"David","email":"fullerton@usgs.gov","middleInitial":"S.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":470249,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Colton, Roger B.","contributorId":17967,"corporation":false,"usgs":true,"family":"Colton","given":"Roger","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":470251,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bush, Charles A. cbush@usgs.gov","contributorId":1258,"corporation":false,"usgs":true,"family":"Bush","given":"Charles","email":"cbush@usgs.gov","middleInitial":"A.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":470250,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70041821,"text":"ofr20121257 - 2012 - Reconnaissance soil geochemistry at the Riverton Uranium Mill Tailings Remedial Action Site, Fremont County, Wyoming","interactions":[],"lastModifiedDate":"2025-05-14T19:21:42.065777","indexId":"ofr20121257","displayToPublicDate":"2012-12-17T00:00:00","publicationYear":"2012","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":"2012-1257","title":"Reconnaissance soil geochemistry at the Riverton Uranium Mill Tailings Remedial Action Site, Fremont County, Wyoming","docAbstract":"Soil samples were collected and chemically analyzed from the Riverton Uranium Mill Tailings Remedial Action Site, which lies within the Wind River Indian Reservation in Fremont County, Wyoming. Nineteen soil samples from a depth of 0 to 5 centimeters were collected in August 2011 from the site. The samples were sieved to less than 2 millimeters and analyzed for 44 major and trace elements following a near-total multi-acid extraction. Soil pH was also determined. The geochemical data were compared to a background dataset consisting of 160 soil samples previously collected from the same depth throughout the State of Wyoming as part of another ongoing study by the U.S. Geological Survey. Risk from potentially toxic elements in soil from the site to biologic receptors and humans was estimated by comparing the concentration of these elements with soil screening values established by the U.S. Environmental Protection Agency. All 19 samples exceeded the carcinogenic human health screening level for arsenic in residential soils of 0.39 milligrams per kilogram (mg/kg), which represents a one-in-one-million cancer risk (median arsenic concentration in the study area is 2.7 mg/kg). All 19 samples also exceeded the lead and vanadium screening levels for birds. Eighteen of the 19 samples exceeded the manganese screening level for plants, 13 of the 19 samples exceeded the antimony screening level for mammals, and 10 of 19 samples exceeded the zinc screening level for birds. However, these exceedances are also found in soils at most locations in the Wyoming Statewide soil database, and elevated concentrations alone are not necessarily cause for alarm. Uranium and thorium, two other elements of environmental concern, are elevated in soils at the site as compared to the Wyoming dataset, but no human or ecological soil screening levels have been established for these elements.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121257","usgsCitation":"Smith, D., and Sweat, M.J., 2012, Reconnaissance soil geochemistry at the Riverton Uranium Mill Tailings Remedial Action Site, Fremont County, Wyoming: U.S. Geological Survey Open-File Report 2012-1257, Report: iv, 23 p.; 1 Appendix, https://doi.org/10.3133/ofr20121257.","productDescription":"Report: iv, 23 p.; 1 Appendix","numberOfPages":"27","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2011-08-01","temporalEnd":"2011-08-31","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":264080,"rank":4,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1257.gif"},{"id":264079,"rank":1,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2012/1257/Appendix%201.xlsx"},{"id":264078,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1257/OF12-1257.pdf"},{"id":264077,"rank":3,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1257/"}],"country":"United States","state":"Wyoming","county":"Fremont","otherGeospatial":"Riverton Uranium Mill","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -108.420833,42.975 ], [ -108.420833,43.25 ], [ -108.383333,43.25 ], [ -108.383333,42.975 ], [ -108.420833,42.975 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50d0498ce4b0d83991d15696","contributors":{"authors":[{"text":"Smith, David B. 0000-0001-8396-9105 dsmith@usgs.gov","orcid":"https://orcid.org/0000-0001-8396-9105","contributorId":1274,"corporation":false,"usgs":true,"family":"Smith","given":"David B.","email":"dsmith@usgs.gov","affiliations":[{"id":218,"text":"Denver Federal Center","active":false,"usgs":true}],"preferred":false,"id":470239,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sweat, Michael J. mjsweat@usgs.gov","contributorId":356,"corporation":false,"usgs":true,"family":"Sweat","given":"Michael","email":"mjsweat@usgs.gov","middleInitial":"J.","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":470238,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70040393,"text":"70040393 - 2012 - Temporal variations of geyser water chemistry in the Upper Geyser Basin, Yellowstone National Park, USA","interactions":[],"lastModifiedDate":"2019-05-30T12:35:05","indexId":"70040393","displayToPublicDate":"2012-12-13T09:04:47","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1757,"text":"Geochemistry, Geophysics, Geosystems","active":true,"publicationSubtype":{"id":10}},"title":"Temporal variations of geyser water chemistry in the Upper Geyser Basin, Yellowstone National Park, USA","docAbstract":"Geysers are rare features that reflect a delicate balance between an abundant supply of water and heat and a unique geometry of fractures and porous rocks. Between April 2007 and September 2008, we sampled Old Faithful, Daisy, Grand, Oblong, and Aurum geysers in Yellowstone National Park's Upper Geyser Basin and characterized temporal variations in major element chemistry and water isotopes (δ<sup>18</sup>O, δD, <sup>3</sup>H). We compare these temporal variations with temporal trends of Geyser Eruption Intervals (GEI). SiO<sub>2</sub> concentrations and geothermometry indicate that the geysers are fed by waters ascending from a reservoir with temperatures of ∼190 to 210°C. The studied geysers display small and complex chemical and isotopic seasonal variations, and geysers with smaller volume display larger seasonal variations than geysers with larger volumes. Aurum and Oblong Geysers contain detectable tritium concentrations, suggesting that erupted water contains some modern meteoric water. We propose that seasonal GEI variations result from varying degrees of evaporation, meteoric water recharge, water table fluctuations, and possible hydraulic interaction with the adjacent Firehole River. We demonstrate that the concentrations of major dissolved species in Old Faithful Geyser have remained nearly constant since 1884 despite large changes in Old Faithful's eruption intervals, suggesting that no major changes have occurred in the hydrothermal system of the Upper Geyser Basin for >120 years. Our data set provides a baseline for monitoring future changes in geyser activity that might result from varying climate, earthquakes, and changes in heat flow from the underlying magmatic system.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Geochemistry, Geophysics, Geosystems","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"American Geophysical Union","publisherLocation":"Washington, D.C.","doi":"10.1029/2012GC004388","usgsCitation":"Hurwitz, S., Hunt, A.G., and Evans, W.C., 2012, Temporal variations of geyser water chemistry in the Upper Geyser Basin, Yellowstone National Park, USA: Geochemistry, Geophysics, Geosystems, v. 13, no. 12, 19 p., https://doi.org/10.1029/2012GC004388.","productDescription":"19 p.","numberOfPages":"19","ipdsId":"IP-041584","costCenters":[{"id":148,"text":"Branch of Regional Research-Western Region","active":false,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"links":[{"id":280954,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1029/2012GC004388"},{"id":280955,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Firehole River;Upper Geyser Basin;Yellowstone National Park","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -111.156,44.1313 ], [ -111.156,45.109 ], [ -109.8255,45.109 ], [ -109.8255,44.1313 ], [ -111.156,44.1313 ] ] ] } } ] }","volume":"13","issue":"12","noUsgsAuthors":false,"publicationDate":"2012-12-13","publicationStatus":"PW","scienceBaseUri":"53cd768de4b0b2908510af70","contributors":{"authors":[{"text":"Hurwitz, Shaul 0000-0001-5142-6886 shaulh@usgs.gov","orcid":"https://orcid.org/0000-0001-5142-6886","contributorId":2169,"corporation":false,"usgs":true,"family":"Hurwitz","given":"Shaul","email":"shaulh@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":468259,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hunt, Andrew G. 0000-0002-3810-8610 ahunt@usgs.gov","orcid":"https://orcid.org/0000-0002-3810-8610","contributorId":1582,"corporation":false,"usgs":true,"family":"Hunt","given":"Andrew","email":"ahunt@usgs.gov","middleInitial":"G.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":468258,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Evans, William C. 0000-0001-5942-3102 wcevans@usgs.gov","orcid":"https://orcid.org/0000-0001-5942-3102","contributorId":2353,"corporation":false,"usgs":true,"family":"Evans","given":"William","email":"wcevans@usgs.gov","middleInitial":"C.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":468260,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70041457,"text":"70041457 - 2012 - Geology and <sup>40</sup>Ar/<sup>39</sup>Ar geochronology of the medium- to high-K Tanaga volcanic cluster, western Aleutians","interactions":[],"lastModifiedDate":"2019-05-30T12:39:52","indexId":"70041457","displayToPublicDate":"2012-12-13T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1786,"text":"Geological Society of America Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"Geology and <sup>40</sup>Ar/<sup>39</sup>Ar geochronology of the medium- to high-K Tanaga volcanic cluster, western Aleutians","docAbstract":"We used geologic mapping and geochemical data augmented by <sup>40</sup>Ar/<sup>39</sup>Ar dating to establish an eruptive chronology for the Tanaga volcanic cluster in the western Aleutian arc. The Tanaga volcanic cluster is unique in comparison to other central and western Aleutian volcanoes in that it consists of three closely spaced, active, volumetrically significant edifices (Sajaka, Tanaga, and Takawangha), the eruptive products of which have unusually high K<sub>2</sub>O contents. Thirty-five new <sup>40</sup>Ar/<sup>39</sup>Ar ages obtained in two different laboratories constrain the duration of Pleistocene–Holocene subaerial volcanism to younger than 295 ka. The eruptive activity has been mostly continuous for the last 150 k.y., unlike most other well-characterized arc volcanoes, which tend to grow in discrete pulses. More than half of the analyzed Tanaga volcanic cluster lavas are basalts that have erupted throughout the lifetime of the cluster, although a considerable amount of basaltic andesite and basaltic trachyandesite has also been produced since 200 ka. Major- and trace-element variations suggest that magmas from Sajaka and Tanaga volcanoes are likely to have crystallized pyroxene and/or amphibole at greater depths than the older Takawangha magmas, which experienced a larger percentage of plagioclase-dominated fractionation at shallower depths. Magma output from Takawangha has declined over the last 86 k.y. At ca. 19 ka, the focus of magma flux shifted to the west beneath Tanaga and Sajaka volcanoes, where hotter, more mafic magma erupted.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Geological Society of America Bulletin","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Geological Society of America","publisherLocation":"Boulder, CO","doi":"10.1130/B30472.1","usgsCitation":"Jicha, B.R., Coombs, M.L., Calvert, A.T., and Singer, B., 2012, Geology and <sup>40</sup>Ar/<sup>39</sup>Ar geochronology of the medium- to high-K Tanaga volcanic cluster, western Aleutians: Geological Society of America Bulletin, v. 124, no. 5-6, p. 842-856, https://doi.org/10.1130/B30472.1.","productDescription":"15 p.","startPage":"842","endPage":"856","ipdsId":"IP-027482","costCenters":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":264035,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":264034,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1130/B30472.1"}],"country":"United States","state":"Alaska","otherGeospatial":"Tanaga Island;Aleutian Islands","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -178.228701,51.593733 ], [ -178.228701,51.918986 ], [ -177.613314,51.918986 ], [ -177.613314,51.593733 ], [ -178.228701,51.593733 ] ] ] } } ] }","volume":"124","issue":"5-6","noUsgsAuthors":false,"publicationDate":"2012-03-09","publicationStatus":"PW","scienceBaseUri":"50cb5776e4b09e092d6f03e1","contributors":{"authors":[{"text":"Jicha, Brian R.","contributorId":44062,"corporation":false,"usgs":true,"family":"Jicha","given":"Brian","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":469765,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coombs, Michelle L. 0000-0002-6002-6806 mcoombs@usgs.gov","orcid":"https://orcid.org/0000-0002-6002-6806","contributorId":2809,"corporation":false,"usgs":true,"family":"Coombs","given":"Michelle","email":"mcoombs@usgs.gov","middleInitial":"L.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":469764,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Calvert, Andrew T. 0000-0001-5237-2218 acalvert@usgs.gov","orcid":"https://orcid.org/0000-0001-5237-2218","contributorId":2694,"corporation":false,"usgs":true,"family":"Calvert","given":"Andrew","email":"acalvert@usgs.gov","middleInitial":"T.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":469763,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Singer, Brad S.","contributorId":50425,"corporation":false,"usgs":true,"family":"Singer","given":"Brad S.","affiliations":[],"preferred":false,"id":469766,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70041781,"text":"sir20125216 - 2012 - Evaluation of water-quality characteristics and sampling design for streams in North Dakota, 1970–2008","interactions":[],"lastModifiedDate":"2017-10-14T11:23:39","indexId":"sir20125216","displayToPublicDate":"2012-12-13T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-5216","title":"Evaluation of water-quality characteristics and sampling design for streams in North Dakota, 1970–2008","docAbstract":"In response to the need to examine the large amount of historic water-quality data comprehensively across North Dakota and evaluate the efficiency of the State-wide sampling programs, a study was done by the U.S. Geological Survey in cooperation with the North Dakota State Water Commission and the North Dakota Department of Health to describe the water-quality data collected for the various programs and determine an efficient State-wide sampling design for monitoring future water-quality conditions. Although data collected for the North Dakota State Water Commission High-Low Sampling Program, the North Dakota Department of Health Ambient Water-Quality Network, and other projects and programs provide valuable information on the quality of water in streams in North Dakota, the objectives vary among the programs, some of the programs overlap spatially and temporally, and the various sampling designs may not be the most efficient or relevant to the objectives of the individual programs as they have changed through time.\n\nOne objective of a State-wide sampling program was to evaluate ways to describe the spatial variability of water-quality conditions across the State in the most efficient manner. Weighted least-squares regression analysis was used to relate the average absolute difference between paired downstream and upstream concentrations, expressed as a percent of the average downstream concentration, to the average absolute difference in daily flow between the downstream and upstream pairs, expressed as a percent of the average downstream flow. The analysis showed that a reasonable spatial network would consist of including the most downstream sites in large basins first, followed by the next upstream site(s) that roughly bisect the downstream flows at the first sites, followed by the next upstream site(s) that roughly bisect flows for the second sites. Sampling sites to be included in a potential State-wide network were prioritized into 3 design levels: level 1 (highest priority), level 2 (second priority), and level 3 (third priority).\n\nGiven the spatial distribution and priority designation (levels 1–3) of sites in the potential spatial network, the next consideration was to determine the appropriate temporal sampling frequency to use for monitoring future water-quality conditions. The time-series model used to detect concentration trends for this report also was used to evaluate sampling designs to monitor future water-quality trends. Sampling designs were evaluated with regard to their sensitivity to detect seasonal trends that occurred during three 4-month seasons—March through June, July through October, and November through February.\n\nFor the 34 level-1 sites, samples would be collected for major ions, trace metals, nutrients, bacteria, and sediment eight times per year, with samples in January, April (2 samples),May, June, July, August, and October. For the 21 level-2 sites, samples would be collected for major ions, trace metals, and nutrients six times per year (January, April, May, June, August, and October), and for the 26 level-3 sites, samples would be collected for these constituents four times per year (April, June, August, and October).","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125216","collaboration":"Prepared in cooperation with the North Dakota State Water Commission and the North Dakota Department of Health","usgsCitation":"Galloway, J.M., Vecchia, A.V., Vining, K.C., Densmore, B.K., and Lundgren, R.F., 2012, Evaluation of water-quality characteristics and sampling design for streams in North Dakota, 1970–2008: U.S. Geological Survey Scientific Investigations Report 2012-5216, Report: viii, 301 p.; Appendix 3, https://doi.org/10.3133/sir20125216.","productDescription":"Report: viii, 301 p.; Appendix 3","numberOfPages":"316","onlineOnly":"Y","temporalStart":"1970-01-01","temporalEnd":"2008-12-31","costCenters":[{"id":478,"text":"North Dakota Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":264016,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5216.gif"},{"id":264014,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5216/"},{"id":264015,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2012/5216/downloads/appendix3.xlsx"},{"id":264057,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5216/sir12-5216.pdf"}],"country":"United States","state":"North Dakota","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -104.05,45.9351 ], [ -104.05,49.0007 ], [ -96.5545,49.0007 ], [ -96.5545,45.9351 ], [ -104.05,45.9351 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50cb5769e4b09e092d6f03d5","contributors":{"authors":[{"text":"Galloway, Joel M. 0000-0002-9836-9724 jgallowa@usgs.gov","orcid":"https://orcid.org/0000-0002-9836-9724","contributorId":1562,"corporation":false,"usgs":true,"family":"Galloway","given":"Joel","email":"jgallowa@usgs.gov","middleInitial":"M.","affiliations":[{"id":478,"text":"North Dakota Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":470212,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vecchia, Aldo V. 0000-0002-2661-4401","orcid":"https://orcid.org/0000-0002-2661-4401","contributorId":41810,"corporation":false,"usgs":true,"family":"Vecchia","given":"Aldo","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":470215,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vining, Kevin C. 0000-0001-5738-3872 kcvining@usgs.gov","orcid":"https://orcid.org/0000-0001-5738-3872","contributorId":308,"corporation":false,"usgs":true,"family":"Vining","given":"Kevin","email":"kcvining@usgs.gov","middleInitial":"C.","affiliations":[{"id":478,"text":"North Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":470211,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Densmore, Brenda K. 0000-0003-2429-638X bdensmore@usgs.gov","orcid":"https://orcid.org/0000-0003-2429-638X","contributorId":4896,"corporation":false,"usgs":true,"family":"Densmore","given":"Brenda","email":"bdensmore@usgs.gov","middleInitial":"K.","affiliations":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"preferred":true,"id":470214,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lundgren, Robert F. 0000-0001-7669-0552 rflundgr@usgs.gov","orcid":"https://orcid.org/0000-0001-7669-0552","contributorId":1657,"corporation":false,"usgs":true,"family":"Lundgren","given":"Robert","email":"rflundgr@usgs.gov","middleInitial":"F.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":470213,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70041777,"text":"70041777 - 2012 - Waste rice seed in conventional and stripper-head harvested fields in California: Implications for wintering waterfowl","interactions":[],"lastModifiedDate":"2012-12-13T20:09:08","indexId":"70041777","displayToPublicDate":"2012-12-13T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Waste rice seed in conventional and stripper-head harvested fields in California: Implications for wintering waterfowl","docAbstract":"Waste rice seed is an important food for wintering waterfowl and current estimates of its availability are needed to determine the carrying capacity of rice fields and guide habitat conservation. We used a line-intercept method to estimate mass-density of rice seed remaining after harvest during 2010 in the Sacramento Valley (SACV) of California and compared results with estimates from previous studies in the SACV and Mississippi Alluvial Valley (MAV). Posterior mean (95% credible interval) estimates of total waste rice seed mass-density for the SACV in 2010 were 388 (336–449) kg/ha in conventionally harvested fields and 245 (198–307) kg/ha in stripper-head harvested fields; the 2010 mass-density is nearly identical to the mid-1980s estimate for conventionally harvested fields but 36% lower than the mid-1990s estimate for stripped fields. About 18% of SACV fields were stripper-head harvested in 2010 vs. 9–15% in the mid-1990s and 0% in the mid-1980s; but due to a 50% increase in planted rice area, total mass of waste rice seed in SACV remaining after harvest in 2010 was 43% greater than in the mid-1980s. However, total mass of seed-eating waterfowl also increased 82%, and the ratio of waste rice seed to seed-eating waterfowl mass was 21% smaller in 2010 than in the mid-1980s. Mass-densities of waste rice remaining after harvest in SACV fields are within the range reported for MAV fields. However, because there is a lag between harvest and waterfowl use in the MAV but not in the SACV, seed loss is greater in the MAV and estimated waste seed mass-density available to wintering waterfowl in SACV fields is about 5–30 times recent MAV estimates. Waste rice seed remains an abundant food source for waterfowl wintering in the SACV, but increased use of stripper-head harvesters would reduce this food. To provide accurate data on carrying capacities of rice fields necessary for conservation planning, trends in planted rice area, harvest method, and postharvest field treatment should be tracked and impacts of postharvest field treatment and other farming practices on waste rice seed availability should be investigated.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Fish and Wildlife Management","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"U.S. Fish and Wildlife Service","publisherLocation":"Arlington, VA","doi":"10.3996/022012-JFWM-014","usgsCitation":"Fleskes, J.P., Halstead, B., Casazza, M.L., Coates, P.S., Kohl, J.D., and Skalos, D.A., 2012, Waste rice seed in conventional and stripper-head harvested fields in California: Implications for wintering waterfowl: Journal of Fish and Wildlife Management, v. 3, no. 2, p. 266-275, https://doi.org/10.3996/022012-JFWM-014.","productDescription":"10 p.; map","startPage":"266","endPage":"275","ipdsId":"IP-035176","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":474206,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/022012-jfwm-014","text":"Publisher Index Page"},{"id":264018,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":264017,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.3996/022012-JFWM-014"}],"country":"United States","state":"California","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.41,32.53 ], [ -124.41,42.01 ], [ -114.13,42.01 ], [ -114.13,32.53 ], [ -124.41,32.53 ] ] ] } } ] }","volume":"3","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50cb5783e4b09e092d6f03ed","contributors":{"authors":[{"text":"Fleskes, Joseph P. 0000-0001-5388-6675 joe_fleskes@usgs.gov","orcid":"https://orcid.org/0000-0001-5388-6675","contributorId":1889,"corporation":false,"usgs":true,"family":"Fleskes","given":"Joseph","email":"joe_fleskes@usgs.gov","middleInitial":"P.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":470205,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Halstead, Brian J. 0000-0002-5535-6528 bhalstead@usgs.gov","orcid":"https://orcid.org/0000-0002-5535-6528","contributorId":3051,"corporation":false,"usgs":true,"family":"Halstead","given":"Brian J.","email":"bhalstead@usgs.gov","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":470207,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Casazza, Michael L. 0000-0002-5636-735X mike_casazza@usgs.gov","orcid":"https://orcid.org/0000-0002-5636-735X","contributorId":2091,"corporation":false,"usgs":true,"family":"Casazza","given":"Michael","email":"mike_casazza@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":470206,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Coates, Peter S. 0000-0003-2672-9994 pcoates@usgs.gov","orcid":"https://orcid.org/0000-0003-2672-9994","contributorId":3263,"corporation":false,"usgs":true,"family":"Coates","given":"Peter","email":"pcoates@usgs.gov","middleInitial":"S.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":470208,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kohl, Jeffrey D.","contributorId":79773,"corporation":false,"usgs":true,"family":"Kohl","given":"Jeffrey","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":470210,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Skalos, Daniel A.","contributorId":64123,"corporation":false,"usgs":true,"family":"Skalos","given":"Daniel","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":470209,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70041790,"text":"fs20123061 - 2012 - United States Geological Survey (USGS) Natural Hazards Response","interactions":[],"lastModifiedDate":"2012-12-14T09:53:27","indexId":"fs20123061","displayToPublicDate":"2012-12-13T00:00:00","publicationYear":"2012","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":"2012-3061","title":"United States Geological Survey (USGS) Natural Hazards Response","docAbstract":"The primary goal of U.S. Geological Survey (USGS) Natural Hazards Response is to ensure that the disaster response community has access to timely, accurate, and relevant geospatial products, imagery, and services during and after an emergency event. To accomplish this goal, products and services provided by the National Geospatial Program (NGP) and Land Remote Sensing (LRS) Program serve as a geospatial framework for mapping activities of the emergency response community. Post-event imagery and analysis can provide important and timely information about the extent and severity of an event. USGS Natural Hazards Response will also support the coordination of remotely sensed data acquisitions, image distribution, and authoritative geospatial information production as required for use in disaster preparedness, response, and recovery operations.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20123061","usgsCitation":"Lamb, R.M., and Jones, B., 2012, United States Geological Survey (USGS) Natural Hazards Response: U.S. Geological Survey Fact Sheet 2012-3061, 4 p., https://doi.org/10.3133/fs20123061.","productDescription":"4 p.","numberOfPages":"4","additionalOnlineFiles":"N","ipdsId":"IP-034620","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":264033,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs_2012_3061.gif"},{"id":264031,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2012/3061/"},{"id":264032,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2012/3061/fs2012-3061.pdf"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50cb577fe4b09e092d6f03e9","contributors":{"authors":[{"text":"Lamb, Rynn M. 0000-0001-6054-4139 lamb@usgs.gov","orcid":"https://orcid.org/0000-0001-6054-4139","contributorId":4038,"corporation":false,"usgs":true,"family":"Lamb","given":"Rynn","email":"lamb@usgs.gov","middleInitial":"M.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":470216,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jones, Brenda K. 0000-0003-4941-5349","orcid":"https://orcid.org/0000-0003-4941-5349","contributorId":60739,"corporation":false,"usgs":true,"family":"Jones","given":"Brenda K.","affiliations":[],"preferred":false,"id":470217,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70041776,"text":"sim3231 - 2012 - Flood-inundation maps for the White River at Newberry, Indiana","interactions":[],"lastModifiedDate":"2012-12-14T10:53:02","indexId":"sim3231","displayToPublicDate":"2012-12-13T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3231","title":"Flood-inundation maps for the White River at Newberry, Indiana","docAbstract":"Digital flood-inundation maps for a 4.9-mile reach of the White River at Newberry, Indiana (Ind.), were created by the U.S. Geological Survey (USGS) in cooperation with the Indiana Office of Community and Rural Affairs. The inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at <a href=\"http://water.usgs.gov/osw/flood_inundation\" target=\"_blank\">http://water.usgs.gov/osw/flood_inundation</a>, depict estimates of the areal extent of flooding corresponding to selected water levels (stages) at USGS streamgage 03360500, White River at Newberry, Ind. Current conditions at the USGS streamgage may be obtained on the Internet (<a href=\"http://waterdata.usgs.gov/in/nwis/uv?site_no=03360500\" target=\"_blank\">http://waterdata.usgs.gov/in/nwis/uv?site_no=03360500</a>). The National Weather Service (NWS) forecasts flood hydrographs at the Newberry streamgage. That forecasted peak-stage information, also available on the Internet, may be used in conjunction with the maps developed in this study to show predicted areas of flood inundation. For this study, flood profiles were computed for the White River reach by means of a one-dimensional step-backwater model developed by the U.S. Army Corps of Engineers. The hydraulic model was calibrated by using the most current stage-discharge relation at USGS streamgage 03360500, White River at Newberry, Ind., and high-water marks from a flood in June 2008.The calibrated hydraulic model was then used to determine 22 water-surface profiles for flood stages a1-foot intervals referenced to the streamgage datum and ranging from bankfull to approximately the highest recorded water level at the streamgage. The simulated water-surface profiles were then combined with a geographic information system digital elevation model (derived from Light Detection and Ranging (LiDAR) data) in order to delineate the area flooded at each water level. The availability of these maps, along with Internet information regarding current stage from the USGS streamgage at Newberry, Ind., and forecasted stream stages from the NWS, provide emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures as well as for post-flood recovery efforts.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3231","collaboration":"Prepared in cooperation with the Indiana Office of Community and Rural Affairs.  These sheets are availalbe in High Resolution PDF or Low Resolution JPG.  See <a href=\"http://pubs.usgs.gov/sim/3231/\" target=\"_blank\">SIM 3231</a> for more information.","usgsCitation":"Fowler, K.K., Kim, M.H., and Menke, C.D., 2012, Flood-inundation maps for the White River at Newberry, Indiana: U.S. Geological Survey Scientific Investigations Map 3231, Pamphlet: vi,8 p.; 22 sheets: 17 x 22 inches or smaller; Downloads Directory, https://doi.org/10.3133/sim3231.","productDescription":"Pamphlet: vi,8 p.; 22 sheets: 17 x 22 inches or smaller; Downloads Directory","numberOfPages":"18","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":264013,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sim_3231.gif"},{"id":263990,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sim/3231/Downloads"},{"id":263988,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3231/"},{"id":263989,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3231/pdf/sim3231-102612.pdf"},{"id":263991,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3231/pdf/Sheet1-473_8ft.pdf"},{"id":263992,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3231/pdf/Sheet10-482_17ft.pdf"},{"id":263993,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3231/pdf/Sheet11-483_18ft.pdf"},{"id":263994,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3231/pdf/Sheet12-484_19ft.pdf"},{"id":263995,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3231/pdf/Sheet13-485_20ft.pdf"},{"id":263996,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3231/pdf/Sheet14-486_21ft.pdf"},{"id":263997,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3231/pdf/Sheet15-487_22ft.pdf"},{"id":263998,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3231/pdf/Sheet16-488_23ft.pdf"},{"id":263999,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3231/pdf/Sheet17-489_24ft.pdf"},{"id":264002,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3231/pdf/Sheet2-474_9ft.pdf"},{"id":264003,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3231/pdf/Sheet20-492_27ft.pdf"},{"id":264000,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3231/pdf/Sheet18-490_25ft.pdf"},{"id":264001,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3231/pdf/Sheet19-491_26ft.pdf"},{"id":264004,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3231/pdf/Sheet21-493_28ft.pdf"},{"id":264005,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3231/pdf/Sheet22-494_29ft.pdf"},{"id":264006,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3231/pdf/Sheet3-475_10ft.pdf"},{"id":264007,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3231/pdf/Sheet4-476_11ft.pdf"},{"id":264008,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3231/pdf/Sheet5-477_12ft.pdf"},{"id":264009,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3231/pdf/Sheet6-478_13ft.pdf"},{"id":264010,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3231/pdf/Sheet8-480_15ft.pdf"},{"id":264011,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3231/pdf/Sheet7-479_14ft.pdf"},{"id":264012,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3231/pdf/Sheet9-481_16ft.pdf"}],"projection":"Transverse Mercator","datum":"North American Datum of 1983","country":"United States","state":"Indiana","city":"Newberry","otherGeospatial":"White River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -87.07,38.90 ], [ -87.07,38.97 ], [ -86.67,38.97 ], [ -86.67,38.90 ], [ -87.07,38.90 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50cb576de4b09e092d6f03d9","contributors":{"authors":[{"text":"Fowler, Kathleen K. 0000-0002-0107-3848 kkfowler@usgs.gov","orcid":"https://orcid.org/0000-0002-0107-3848","contributorId":2439,"corporation":false,"usgs":true,"family":"Fowler","given":"Kathleen","email":"kkfowler@usgs.gov","middleInitial":"K.","affiliations":[{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true},{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":470202,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kim, Moon H. 0000-0002-4328-8409 mkim@usgs.gov","orcid":"https://orcid.org/0000-0002-4328-8409","contributorId":3211,"corporation":false,"usgs":true,"family":"Kim","given":"Moon","email":"mkim@usgs.gov","middleInitial":"H.","affiliations":[{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true}],"preferred":true,"id":470204,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Menke, Chad D. cdmenke@usgs.gov","contributorId":3209,"corporation":false,"usgs":true,"family":"Menke","given":"Chad","email":"cdmenke@usgs.gov","middleInitial":"D.","affiliations":[],"preferred":true,"id":470203,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70041759,"text":"ofr20121239 - 2012 - Producing fractional rangeland component predictions in a sagebrush ecosystem, a Wyoming sensitivity analysis","interactions":[],"lastModifiedDate":"2012-12-12T15:01:41","indexId":"ofr20121239","displayToPublicDate":"2012-12-12T00:00:00","publicationYear":"2012","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":"2012-1239","title":"Producing fractional rangeland component predictions in a sagebrush ecosystem, a Wyoming sensitivity analysis","docAbstract":"Remote sensing information has been widely used to monitor vegetation condition and variations in a variety of ecosystems, including shrublands. Careful application of remotely sensed imagery can provide additional spatially explicit, continuous, and extensive data on the composition and condition of shrubland ecosystems. Historically, the most widely available remote sensing information has been collected by Landsat, which has offered large spatial coverage and moderate spatial resolution data globally for nearly three decades. Such medium-resolution satellite remote sensing information can quantify the distribution and variation of terrestrial ecosystems. Landsat imagery has been frequently used with other high-resolution remote sensing data to classify sagebrush components and quantify their spatial distributions (Ramsey and others, 2004; Seefeldt and Booth, 2004; Stow and others, 2008; Underwood and others, 2007). Modeling algorithms have been developed to use field measurements and satellite remote sensing data to quantify the extent and evaluate the quality of shrub ecosystem components in large geographic areas (Homer and others, 2009). The percent cover of sagebrush ecosystem components, including bare-ground, herbaceous, litter, sagebrush, and shrub, have been quantified for entire western states (Homer and others, 2012). Furthermore, research has demonstrated the use of current measurements with historical archives of Landsat imagery to quantify the variations of these components for the last two decades (Xian and others, 2012). The modeling method used to quantify the extent and spatial distribution of sagebrush components over a large area also has required considerable amounts of training data to meet targeted accuracy requirements. These training data have maintained product accuracy by ensuring that they are derived from good quality field measurements collected during appropriate ecosystem phenology and subsequently maximized by extrapolation on high-resolution remote sensing data (Homer and others, 2012). This method has proven its utility; however, to develop these products across even larger areas will require additional cost efficiencies to ensure that an adequate product can be developed for the lowest cost possible. Given the vast geographic extent of shrubland ecosystems in the western United States, identifying cost efficiencies with optimal training data development and subsequent application to medium resolution satellite imagery provide the most likely areas for methodological efficiency gains. The primary objective of this research was to conduct a series of sensitivity tests to evaluate the most optimal and practical way to develop Landsat scale information for estimating the extent and distribution of sagebrush ecosystem components over large areas in the conterminous United States. An existing dataset of sagebrush components developed from extensive field measurements, high-resolution satellite imagery, and medium resolution Landsat imagery in Wyoming was used as the reference database (Homer and others, 2012). Statistical analysis was performed to analyze the relation between the accuracy of sagebrush components and the amount and distribution of training data on Landsat scenes needed to obtain accurate predictions.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121239","usgsCitation":"Xian, G., Homer, C.G., Granneman, B., and Meyer, D.K., 2012, Producing fractional rangeland component predictions in a sagebrush ecosystem, a Wyoming sensitivity analysis: U.S. Geological Survey Open-File Report 2012-1239, iv, 18 p., https://doi.org/10.3133/ofr20121239.","productDescription":"iv, 18 p.","numberOfPages":"26","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":263980,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1239.gif"},{"id":263978,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1239/"},{"id":263979,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1239/of12-1239.pdf"}],"country":"United States","state":"Wyoming","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -111.0,41.0 ], [ -111.0,45.0 ], [ -104.0,45.0 ], [ -104.0,41.0 ], [ -111.0,41.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50c9a773e4b06bc7a3e933c7","contributors":{"authors":[{"text":"Xian, George 0000-0001-5674-2204","orcid":"https://orcid.org/0000-0001-5674-2204","contributorId":76589,"corporation":false,"usgs":true,"family":"Xian","given":"George","affiliations":[],"preferred":false,"id":470170,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Homer, Collin G. 0000-0003-4755-8135 homer@usgs.gov","orcid":"https://orcid.org/0000-0003-4755-8135","contributorId":2262,"corporation":false,"usgs":true,"family":"Homer","given":"Collin","email":"homer@usgs.gov","middleInitial":"G.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":470168,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Granneman, Brian 0000-0002-1910-0955","orcid":"https://orcid.org/0000-0002-1910-0955","contributorId":96174,"corporation":false,"usgs":true,"family":"Granneman","given":"Brian","affiliations":[],"preferred":false,"id":470171,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Meyer, Debra K. 0000-0002-8841-697X dkmeyer@usgs.gov","orcid":"https://orcid.org/0000-0002-8841-697X","contributorId":3145,"corporation":false,"usgs":true,"family":"Meyer","given":"Debra","email":"dkmeyer@usgs.gov","middleInitial":"K.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":470169,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70041581,"text":"70041581 - 2012 - One year of migration data for a western yellow-billed cuckoo","interactions":[],"lastModifiedDate":"2013-11-15T10:31:25","indexId":"70041581","displayToPublicDate":"2012-12-12T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3743,"text":"Western Birds","active":true,"publicationSubtype":{"id":10}},"title":"One year of migration data for a western yellow-billed cuckoo","docAbstract":"In 2009, we studied the migration of the Western Yellow-billed Cuckoo by capturing 13 breeding birds on the middle Rio Grande, New Mexico, and attaching a 1.5-g Mk 14-S British Antarctic Survey geolocator to each bird. In 2010, we recaptured one of the cuckoos, enabling us to download its geolocation data. The cuckoo had flown approximately 9500 km during its southward migration, traveling through Central America to winter in portions of Bolivia, Brazil, Paraguay, and Argentina. The spring migration route differed somewhat from the fall route, with the cuckoo bypassing Central America to migrate through the Caribbean. Additionally, it moved between New Mexico and Mexico at the end of summer in 2009 and again in 2010 before being recaptured at its breeding site. Our results, albeit from one individual, hint at a dynamic migration strategy and have broad implications for the ecology and conservation of the Western Yellow-billed Cuckoo, a species of conservation concern.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Western Birds","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Western Field Ornithologists","publisherLocation":"http://www.westernfieldornithologists.org/","usgsCitation":"Sechrist, J.D., Paxton, E.H., Ahlers, D.D., Doster, R.H., and Ryan, V.M., 2012, One year of migration data for a western yellow-billed cuckoo: Western Birds, v. 43, no. 1, p. 2-11.","productDescription":"10 p.","startPage":"2","endPage":"11","ipdsId":"IP-031415","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":263974,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":263973,"type":{"id":1,"text":"Abstract"},"url":"https://www.westernfieldornithologists.org/docs/abstracts/43-1.pdf"}],"volume":"43","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50c9a766e4b06bc7a3e933c3","contributors":{"authors":[{"text":"Sechrist, Juddson D.","contributorId":52472,"corporation":false,"usgs":true,"family":"Sechrist","given":"Juddson","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":469942,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Paxton, Eben H. 0000-0001-5578-7689","orcid":"https://orcid.org/0000-0001-5578-7689","contributorId":19640,"corporation":false,"usgs":true,"family":"Paxton","given":"Eben","email":"","middleInitial":"H.","affiliations":[{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"preferred":true,"id":469941,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ahlers, Darrell D.","contributorId":92563,"corporation":false,"usgs":true,"family":"Ahlers","given":"Darrell","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":469945,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Doster, Robert H.","contributorId":55710,"corporation":false,"usgs":true,"family":"Doster","given":"Robert","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":469943,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ryan, Vicky M.","contributorId":65742,"corporation":false,"usgs":true,"family":"Ryan","given":"Vicky","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":469944,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70041619,"text":"70041619 - 2012 - Redox reaction rates in shallow aquifers: Implications for nitrate transport in groundwater and streams","interactions":[],"lastModifiedDate":"2013-03-17T19:52:58","indexId":"70041619","displayToPublicDate":"2012-12-11T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":18,"text":"Abstract or summary"},"title":"Redox reaction rates in shallow aquifers: Implications for nitrate transport in groundwater and streams","docAbstract":"Groundwater age and water chemistry data along flow paths from recharge areas to streams were used to evaluate the trends and transformations of agricultural chemicals. Results from this analysis indicate that median nitrate recharge concentrations in these agricultural areas have increased markedly over the last 50 years from 4 mg N/L in samples collected prior to 1983 to 7.5 mg N/L in samples collected since 1983. The effect that nitrate accumulation in shallow aquifers will have on drinking water quality and stream ecosystems is dependent on the rate of redox reactions along flow paths and on the age distribution of nitrate discharging to supply wells and streams.","largerWorkTitle":"Abstracts with Programs, Geological Society of America Annual Meeting","language":"English","publisher":"Geological Society of America","publisherLocation":"Boulder, CO","usgsCitation":"Tesoriero, A., 2012, Redox reaction rates in shallow aquifers: Implications for nitrate transport in groundwater and streams, <i>in</i> Abstracts with Programs, Geological Society of America Annual Meeting, v. 44, no. 7, p. 208-208.","productDescription":"1 p.","startPage":"208","endPage":"208","ipdsId":"IP-025488","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":263925,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":263924,"type":{"id":11,"text":"Document"},"url":"https://gsa.confex.com/gsa/2012AM/finalprogram/abstract_210158.htm"}],"volume":"44","issue":"7","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50c85626e4b03bc63bd679b6","contributors":{"authors":[{"text":"Tesoriero, Anthony J.","contributorId":40207,"corporation":false,"usgs":true,"family":"Tesoriero","given":"Anthony J.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":false,"id":469989,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70041419,"text":"70041419 - 2012 - Rapid, low-cost photogrammetry to monitor volcanic eruptions: An example from Mount St. Helens, Washington, USA","interactions":[],"lastModifiedDate":"2021-02-11T20:39:24.649597","indexId":"70041419","displayToPublicDate":"2012-12-11T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1109,"text":"Bulletin of Volcanology","active":true,"publicationSubtype":{"id":10}},"title":"Rapid, low-cost photogrammetry to monitor volcanic eruptions: An example from Mount St. Helens, Washington, USA","docAbstract":"<p><span>We describe a low-cost application of digital photogrammetry using commercially available photogrammetric software and oblique photographs taken with an off-the-shelf digital camera to create sequential digital elevation models (DEMs) of a lava dome that grew during the 2004–2008 eruption of Mount St. Helens (MSH) volcano. Renewed activity at MSH provided an opportunity to devise and test this method, because it could be validated against other observations of this well-monitored volcano. The datasets consist of oblique aerial photographs (snapshots) taken from a helicopter using a digital single-lens reflex camera. Twelve sets of overlapping digital images of the dome taken during 2004–2007 were used to produce DEMs and to calculate lava dome volumes and extrusion rates. Analyses of the digital images were carried out using photogrammetric software to produce three-dimensional coordinates of points identified in multiple photos. The evolving morphology of the dome was modeled by comparing successive DEMs. Results were validated by comparison to volume measurements derived from traditional vertical photogrammetric surveys by the US Geological Survey Cascades Volcano Observatory. Our technique was significantly less expensive and required less time than traditional vertical photogrammetric techniques; yet, it consistently yielded volume estimates within 5% of the traditional method. This technique provides an inexpensive, rapid assessment tool for tracking lava dome growth or other topographic changes at restless volcanoes.</span></p>","language":"English","publisher":"Springer","publisherLocation":"Amsterdam, Netherlands","doi":"10.1007/s00445-011-0548-y","usgsCitation":"Diefenbach, A., Crider, J.G., Schilling, S.P., and Dzurisin, D., 2012, Rapid, low-cost photogrammetry to monitor volcanic eruptions: An example from Mount St. Helens, Washington, USA: Bulletin of Volcanology, v. 74, no. 2, p. 579-587, https://doi.org/10.1007/s00445-011-0548-y.","productDescription":"9 p.","startPage":"579","endPage":"587","ipdsId":"IP-029276","costCenters":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":263928,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Mount St. Helens","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.22993850708006,\n              46.166754488708506\n            ],\n            [\n              -122.14702606201172,\n              46.166754488708506\n            ],\n            [\n              -122.14702606201172,\n              46.231034280827245\n            ],\n            [\n              -122.22993850708006,\n              46.231034280827245\n            ],\n            [\n              -122.22993850708006,\n              46.166754488708506\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"74","issue":"2","noUsgsAuthors":false,"publicationDate":"2011-10-21","publicationStatus":"PW","scienceBaseUri":"50c85622e4b03bc63bd679b2","contributors":{"authors":[{"text":"Diefenbach, Angela K. 0000-0003-0214-7818","orcid":"https://orcid.org/0000-0003-0214-7818","contributorId":36650,"corporation":false,"usgs":true,"family":"Diefenbach","given":"Angela K.","affiliations":[],"preferred":false,"id":469688,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Crider, Juliet G.","contributorId":78580,"corporation":false,"usgs":true,"family":"Crider","given":"Juliet","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":469689,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schilling, Steve P. sschilli@usgs.gov","contributorId":634,"corporation":false,"usgs":true,"family":"Schilling","given":"Steve","email":"sschilli@usgs.gov","middleInitial":"P.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":469687,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dzurisin, Daniel 0000-0002-0138-5067 dzurisin@usgs.gov","orcid":"https://orcid.org/0000-0002-0138-5067","contributorId":538,"corporation":false,"usgs":true,"family":"Dzurisin","given":"Daniel","email":"dzurisin@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":469686,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70041489,"text":"70041489 - 2012 - Remote sensing of sagebrush canopy nitrogen","interactions":[],"lastModifiedDate":"2012-12-11T10:46:53","indexId":"70041489","displayToPublicDate":"2012-12-11T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"Remote sensing of sagebrush canopy nitrogen","docAbstract":"This paper presents a combination of techniques suitable for remotely sensing foliar Nitrogen (N) in semiarid shrublands – a capability that would significantly improve our limited understanding of vegetation functionality in dryland ecosystems. The ability to estimate foliar N distributions across arid and semi-arid environments could help answer process-driven questions related to topics such as controls on canopy photosynthesis, the influence of N on carbon cycling behavior, nutrient pulse dynamics, and post-fire recovery. Our study determined that further exploration into estimating sagebrush canopy N concentrations from an airborne platform is warranted, despite remote sensing challenges inherent to open canopy systems. Hyperspectral data transformed using standard derivative analysis were capable of quantifying sagebrush canopy N concentrations using partial least squares (PLS) regression with an <i>R<sup>2</sup></i> value of 0.72 and an <i>R<sup>2</sup></i> predicted value of 0.42 (<i>n</i> = 35). Subsetting the dataset to minimize the influence of bare ground (n = 19) increased <i>R<sup>2</sup></i> to 0.95 (<i>R<sup>2</sup></i> predicted = 0.56). Ground-based estimates of canopy N using leaf mass per unit area measurements (LMA) yielded consistently better model fits than ground-based estimates of canopy N using cover and height measurements. The LMA approach is likely a method that could be extended to other semiarid shrublands. Overall, the results of this study are encouraging for future landscape scale N estimates and represent an important step in addressing the confounding influence of bare ground, which we found to be a major influence on predictions of sagebrush canopy N from an airborne platform.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Remote Sensing of Environment","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.rse.2012.05.002","usgsCitation":"Mitchell, J.J., Glenn, N.F., Sankey, T., Derryberry, D., and Germino, M., 2012, Remote sensing of sagebrush canopy nitrogen: Remote Sensing of Environment, v. 124, p. 217-223, https://doi.org/10.1016/j.rse.2012.05.002.","productDescription":"7 p.","startPage":"217","endPage":"223","ipdsId":"IP-038733","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":263920,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":263919,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.rse.2012.05.002"}],"volume":"124","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50c8562ce4b03bc63bd679ba","contributors":{"authors":[{"text":"Mitchell, Jessica J.","contributorId":81772,"corporation":false,"usgs":true,"family":"Mitchell","given":"Jessica","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":469836,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Glenn, Nancy F.","contributorId":95321,"corporation":false,"usgs":true,"family":"Glenn","given":"Nancy","email":"","middleInitial":"F.","affiliations":[{"id":16201,"text":"Boise State University","active":true,"usgs":false}],"preferred":false,"id":469837,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sankey, Temuulen T.","contributorId":38863,"corporation":false,"usgs":true,"family":"Sankey","given":"Temuulen T.","affiliations":[],"preferred":false,"id":469834,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Derryberry, DeWayne R.","contributorId":99016,"corporation":false,"usgs":true,"family":"Derryberry","given":"DeWayne R.","affiliations":[],"preferred":false,"id":469838,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Germino, Matthew J.","contributorId":50029,"corporation":false,"usgs":true,"family":"Germino","given":"Matthew J.","affiliations":[],"preferred":false,"id":469835,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
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