Statistical models of nitrate occurrence in the glacial aquifer system of the northern United States, developed by the U.S. Geological Survey, use observed relations between nitrate concentrations and sets of explanatory variables—representing well-construction, environmental, and source characteristics— to predict the probability that nitrate, as nitrogen, will exceed a threshold concentration. However, the models do not explicitly account for the processes that control the transport of nitrogen from surface sources to a pumped well and use area-weighted mean spatial variables computed from within a circular buffer around the well as a simplified source-area conceptualization. The use of models that explicitly represent physical-transport processes can inform and, potentially, improve these statistical models. Specifically, groundwater-flow models simulate advective transport—predominant in many surficial aquifers— and can contribute to the refinement of the statistical models by (1) providing for improved, physically based representations of a source area to a well, and (2) allowing for more detailed estimates of environmental variables.
\nA source area to a well, known as a contributing recharge area, represents the area at the water table that contributes recharge to a pumped well; a well pumped at a volumetric rate equal to the amount of recharge through a circular buffer will result in a contributing recharge area that is the same size as the buffer but has a shape that is a function of the hydrologic setting. These volume-equivalent contributing recharge areas will approximate circular buffers in areas of relatively flat hydraulic gradients, such as near groundwater divides, but in areas with steep hydraulic gradients will be elongated in the upgradient direction and agree less with the corresponding circular buffers.
\nThe degree to which process-model-estimated contributing recharge areas, which simulate advective transport and therefore account for local hydrologic settings, would inform and improve the development of statistical models can be implicitly estimated by evaluating the differences between explanatory variables estimated from the contributing recharge areas and the circular buffers used to develop existing statistical models. The larger the difference in estimated variables, the more likely that statistical models would be changed, and presumably improved, if explanatory variables estimated from contributing recharge areas were used in model development. Comparing model predictions from the two sets of estimated variables would further quantify—albeit implicitly—how an improved, physically based estimate of explanatory variables would be reflected in model predictions. Differences between the two sets of estimated explanatory variables and resultant model predictions vary spatially; greater differences are associated with areas of steep hydraulic gradients. A direct comparison, however, would require the development of a separate set of statistical models using explanatory variables from contributing recharge areas.
\nArea-weighted means of three environmental variables—silt content, alfisol content, and depth to water from the U.S. Department of Agriculture State Soil Geographic (STATSGO) data—and one nitrogen-source variable (fertilizer-application rate from county data mapped to Enhanced National Land Cover Data 1992 (NLCDe 92) agricultural land use) can vary substantially between circular buffers and volume-equivalent contributing recharge areas and among contributing recharge areas for different sets of well variables. The differences in estimated explanatory variables are a function of the same factors affecting the contributing recharge areas as well as the spatial resolution and local distribution of the underlying spatial data. As a result, differences in estimated variables between circular buffers and contributing recharge areas are complex and site specific as evidenced by differences in estimated variables for circular buffers and contributing recharge areas of existing public-supply and network wells in the Great Miami River Basin. Large differences in areaweighted mean environmental variables are observed at the basin scale, determined by using the network of uniformly spaced hypothetical wells; the differences have a spatial pattern that generally is similar to spatial patterns in the underlying STATSGO data. Generally, the largest differences were observed for area-weighted nitrogen-application rate from county and national land-use data; the basin-scale differences ranged from -1,600 (indicating a larger value from within the volume-equivalent contributing recharge area) to 1,900 kilograms per year (kg/yr); the range in the underlying spatial data was from 0 to 2,200 kg/yr. Silt content, alfisol content, and nitrogen-application rate are defined by the underlying spatial data and are external to the groundwater system; however, depth to water is an environmental variable that can be estimated in more detail and, presumably, in a more physically based manner using a groundwater-flow model than using the spatial data. Model-calculated depths to water within circular buffers in the Great Miami River Basin differed substantially from values derived from the spatial data and had a much larger range.
\nDifferences in estimates of area-weighted spatial variables result in corresponding differences in predictions of nitrate occurrence in the aquifer. In addition to the factors affecting contributing recharge areas and estimated explanatory variables, differences in predictions also are a function of the specific set of explanatory variables used and the fitted slope coefficients in a given model. For models that predicted the probability of exceeding 1 and 4 milligrams per liter as nitrogen (mg/L as N), predicted probabilities using variables estimated from circular buffers and contributing recharge areas generally were correlated but differed significantly at the local and basin scale. The scale and distribution of prediction differences can be explained by the underlying differences in the estimated variables and the relative weight of the variables in the statistical models. Differences in predictions of exceeding 1 mg/L as N, which only includes environmental variables, generally correlated with the underlying differences in STATSGO data, whereas differences in exceeding 4 mg/L as N were more spatially extensive because that model included environmental and nitrogen-source variables. Using depths to water from within circular buffers derived from the spatial data and depths to water within the circular buffers calculated from the groundwater-flow model, restricted to the same range, resulted in large differences in predicted probabilities. The differences in estimated explanatory variables between contributing recharge areas and circular buffers indicate incorporation of physically based contributing recharge area likely would result in a different set of explanatory variables and an improved set of statistical models.
\nThe use of a groundwater-flow model to improve representations of source areas or to provide more-detailed estimates of specific explanatory variables includes a number of limitations and technical considerations. An assumption in these analyses is that (1) there is a state of mass balance between recharge and pumping, and (2) transport to a pumped well is under a steady state flow field. Comparison of volumeequivalent contributing recharge areas under steady-state and transient transport conditions at a location in the southeastern part of the basin shows the steady-state contributing recharge area is a reasonable approximation of the transient contributing recharge area after between 10 and 20 years of pumping. The first assumption is a more important consideration for this analysis. A gradient effect refers to a condition where simulated pumping from a well is less than recharge through the corresponding contributing recharge area. This generally takes place in areas with steep hydraulic gradients, such as near discharge locations, and can be mitigated using a finer model discretization. A boundary effect refers to a condition where recharge through the contributing recharge area is less than pumping. This indicates other sources of water to the simulated well and could reflect a real hydrologic process. In the Great Miami River Basin, large gradient and boundary effects—defined as the balance between pumping and recharge being less than half—occurred in 5 and 14 percent of the basin, respectively. The agreement between circular buffers and volume-equivalent contributing recharge areas, differences in estimated variables, and the effect on statisticalmodel predictions between the population of wells with a balance between pumping and recharge within 10 percent and the population of all wells were similar. This indicated process-model limitations did not affect the overall findings in the Great Miami River Basin; however, this would be model specific, and prudent use of a process model needs to entail a limitations analysis and, if necessary, alterations to the model.
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Minerals","active":true,"usgs":true}],"preferred":true,"id":479006,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shew, Nora B. 0000-0003-0025-7220 nshew@usgs.gov","orcid":"https://orcid.org/0000-0003-0025-7220","contributorId":3382,"corporation":false,"usgs":true,"family":"Shew","given":"Nora","email":"nshew@usgs.gov","middleInitial":"B.","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":479005,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gamble, Bruce M. bgamble@usgs.gov","contributorId":560,"corporation":false,"usgs":true,"family":"Gamble","given":"Bruce","email":"bgamble@usgs.gov","middleInitial":"M.","affiliations":[],"preferred":true,"id":479003,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Labay, Keith A. 0000-0002-6763-3190 klabay@usgs.gov","orcid":"https://orcid.org/0000-0002-6763-3190","contributorId":2097,"corporation":false,"usgs":true,"family":"Labay","given":"Keith A.","email":"klabay@usgs.gov","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":false,"id":479007,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70046134,"text":"70046134 - 2013 - Marsh wrens as bioindicators of mercury in wetlands of Great Salt Lake: do blood and feathers reflect site-specific exposure risk to bird reproduction?","interactions":[],"lastModifiedDate":"2017-07-01T17:25:38","indexId":"70046134","displayToPublicDate":"2013-05-28T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Marsh wrens as bioindicators of mercury in wetlands of Great Salt Lake: do blood and feathers reflect site-specific exposure risk to bird reproduction?","docAbstract":"Nonlethal sampling of bird blood and feathers are among the more common ways of estimating the risk of mercury exposure to songbird reproduction. The implicit assumption is that mercury concentrations in blood or feathers of individuals captured in a given area are correlated with mercury concentrations in eggs from the same area. Yet, this assumption is rarely tested. We evaluated mercury concentrations in blood, feathers, and eggs of marsh wrens in wetlands of Great Salt Lake, Utah, and, at two spatial scales, specifically tested the assumption that mercury concentrations in blood and feather samples from birds captured in a defined area were predictive of mercury concentrations in eggs collected in the same area. Mercury concentrations in blood were not correlated with mercury concentrations in eggs collected within the same wetland unit, and were poorly correlated with mercury concentrations in eggs collected at the smaller home range spatial scale of analysis. Moreover, mercury exposure risk, as estimated via tissue concentrations, differed among wetland units depending upon whether blood or egg mercury concentrations were sampled. Mercury concentrations in feathers also were uncorrelated with mercury concentrations in eggs, and were poorly correlated with mercury concentrations in blood. These results demonstrate the potential for contrasting management actions that may be implemented based solely on the specific avian tissue that is sampled, and highlight the importance of developing avian tissues as biomonitoring tools for assessing local risk of mercury exposure to bird reproduction.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Environmental Science and Technology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"ACS Publications","doi":"10.1021/es400910x","usgsCitation":"Hartman, C., Ackerman, J., Herring, G., Isanhart, J., and Herzog, M., 2013, Marsh wrens as bioindicators of mercury in wetlands of Great Salt Lake: do blood and feathers reflect site-specific exposure risk to bird reproduction?: Environmental Science & Technology, v. 47, no. 12, p. 6597-6605, https://doi.org/10.1021/es400910x.","productDescription":"9 p.","startPage":"6597","endPage":"6605","ipdsId":"IP-037566","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":272923,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1021/es400910x"},{"id":272925,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -113.1395,40.6046 ], [ -113.1395,41.7094 ], [ -111.8671,41.7094 ], [ -111.8671,40.6046 ], [ -113.1395,40.6046 ] ] ] } } ] }","volume":"47","issue":"12","noUsgsAuthors":false,"publicationDate":"2013-05-21","publicationStatus":"PW","scienceBaseUri":"51a5c3e5e4b0605bc571ef6a","contributors":{"authors":[{"text":"Hartman, C. Alex","contributorId":48851,"corporation":false,"usgs":true,"family":"Hartman","given":"C. Alex","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":479000,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ackerman, Joshua T. 0000-0002-3074-8322 jackerman@usgs.gov","orcid":"https://orcid.org/0000-0002-3074-8322","contributorId":147078,"corporation":false,"usgs":true,"family":"Ackerman","given":"Joshua T.","email":"jackerman@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":479001,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Herring, Garth 0000-0003-1106-4731 gherring@usgs.gov","orcid":"https://orcid.org/0000-0003-1106-4731","contributorId":4403,"corporation":false,"usgs":true,"family":"Herring","given":"Garth","email":"gherring@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":478997,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Isanhart, John","contributorId":35625,"corporation":false,"usgs":true,"family":"Isanhart","given":"John","affiliations":[],"preferred":false,"id":478999,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Herzog, Mark P. mherzog@usgs.gov","contributorId":127823,"corporation":false,"usgs":true,"family":"Herzog","given":"Mark P.","email":"mherzog@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":478998,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70046129,"text":"ofr20131081 - 2013 - Final report for sea-level rise response modeling for San Francisco Bay estuary tidal marshes","interactions":[],"lastModifiedDate":"2017-10-30T12:19:43","indexId":"ofr20131081","displayToPublicDate":"2013-05-28T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-1081","title":"Final report for sea-level rise response modeling for San Francisco Bay estuary tidal marshes","docAbstract":"The International Panel on Climate Change has identified coastal ecosystems as areas that will be disproportionally affected by climate change. Current sea-level rise projections range widely with 0.57 to 1.9 meters increase in mea sea level by 2100. The expected accelerated rate of sea-level rise through the 21st century will put many coastal ecosystems at risk, especially those in topographically low-gradient areas.\n\nWe assessed marsh accretion and plant community state changes through 2100 at 12 tidal salt marshes around San Francisco Bay estuary with a sea-level rise response model. Detailed ground elevation, vegetation, and water level data were collected at all sites between 2008 and 2011 and used as model inputs. Sediment cores (taken by Callaway and others, 2012) at four sites around San Francisco Bay estuary were used to estimate accretion rates. A modification of the Callaway and others (1996) model, the Wetland Accretion Rate Model for Ecosystem Resilience (WARMER), was utilized to run sea-level rise response models for all sites. With a mean sea level rise of 1.24 m by 2100, WARMER projected that the vast majority, 95.8 percent (1,942 hectares), of marsh area in our study will lose marsh plant communities by 2100 and to transition to a relative elevation range consistent with mudflat habitat. Three marshes were projected to maintain marsh vegetation to 2100, but they only composed 4.2 percent (85 hectares) of the total marsh area surveyed.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131081","collaboration":"Prepared in cooperation with U.S. Fish and Wildlife Service","usgsCitation":"Takekawa, J.Y., Thorne, K.M., Buffington, K., Spragens, K., Swanson, K., Drexler, J., Schoellhamer, D., Overton, C.T., and Casazza, M.L., 2013, Final report for sea-level rise response modeling for San Francisco Bay estuary tidal marshes: U.S. Geological Survey Open-File Report 2013-1081, x, 161 p., https://doi.org/10.3133/ofr20131081.","productDescription":"x, 161 p.","numberOfPages":"171","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":552,"text":"San Francisco Bay-Delta","active":false,"usgs":true}],"links":[{"id":272882,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131081.jpg"},{"id":272881,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1081/pdf/ofr20131081.pdf"},{"id":272880,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1081/"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.498478,37.447658 ], [ -122.498478,37.964872 ], [ -122.041878,37.964872 ], [ -122.041878,37.447658 ], [ -122.498478,37.447658 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51a5c3e3e4b0605bc571ef5e","contributors":{"authors":[{"text":"Takekawa, John Y. 0000-0003-0217-5907 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kbuffington@usgs.gov","orcid":"https://orcid.org/0000-0001-9741-1241","contributorId":4775,"corporation":false,"usgs":true,"family":"Buffington","given":"Kevin","email":"kbuffington@usgs.gov","middleInitial":"J.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":478980,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Spragens, Kyle A.","contributorId":98452,"corporation":false,"usgs":true,"family":"Spragens","given":"Kyle A.","affiliations":[],"preferred":false,"id":478983,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Swanson, Kathleen M.","contributorId":11289,"corporation":false,"usgs":true,"family":"Swanson","given":"Kathleen M.","affiliations":[],"preferred":false,"id":478982,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Drexler, Judith Z. 0000-0002-0127-3866","orcid":"https://orcid.org/0000-0002-0127-3866","contributorId":8941,"corporation":false,"usgs":true,"family":"Drexler","given":"Judith Z.","affiliations":[],"preferred":false,"id":478981,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Schoellhamer, David H. 0000-0001-9488-7340 dschoell@usgs.gov","orcid":"https://orcid.org/0000-0001-9488-7340","contributorId":631,"corporation":false,"usgs":true,"family":"Schoellhamer","given":"David H.","email":"dschoell@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":478975,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Overton, Cory T. 0000-0002-5060-7447 coverton@usgs.gov","orcid":"https://orcid.org/0000-0002-5060-7447","contributorId":3262,"corporation":false,"usgs":true,"family":"Overton","given":"Cory","email":"coverton@usgs.gov","middleInitial":"T.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":478978,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"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":478977,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70046132,"text":"fs20133024 - 2013 - A conceptual hydrogeologic model for the hydrogeologic framework, geochemistry, and groundwater-flow system of the Edwards-Trinity and related aquifers in the Pecos County region, Texas","interactions":[],"lastModifiedDate":"2016-08-05T14:01:32","indexId":"fs20133024","displayToPublicDate":"2013-05-28T00:00:00","publicationYear":"2013","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":"2013-3024","title":"A conceptual hydrogeologic model for the hydrogeologic framework, geochemistry, and groundwater-flow system of the Edwards-Trinity and related aquifers in the Pecos County region, Texas","docAbstract":"The Edwards-Trinity aquifer is a vital groundwater resource for agricultural, industrial, and municipal uses in the Trans-Pecos region of west Texas. A conceptual model of the hydrogeologic framework, geochemistry, and groundwater-flow system in the 4,700 square-mile study area was developed by the U.S. Geological Survey (USGS) in cooperation with the Middle Pecos Groundwater Conservation District, Pecos County, City of Fort Stockton, Brewster County, and Pecos County Water Control and Improvement District No. 1. The model was developed to gain a better understanding of the groundwater system and to establish a scientific foundation for resource-management decisions. Data and information were collected or obtained from various sources to develop the model. Lithologic information obtained from well reports and geophysical data were used to describe the hydrostratigraphy and structural features of the groundwater system, and aquifer-test data were used to estimate aquifer hydraulic properties. Groundwater-quality data were used to evaluate groundwater-flow paths, water and rock interaction, aquifer interaction, and the mixing of water from different sources. Groundwater-level data also were used to evaluate aquifer interaction as well as to develop a potentiometric-surface map, delineate regional groundwater divides, and describe regional groundwater-flow paths.
\nSeveral previous studies have been done to compile or collect physical and chemical data, describe the hydrogeologic processes, and develop conceptual and numerical groundwater-flow models of the Edwards-Trinity aquifer in the Trans-Pecos region. Documented methods were used to compile and collect groundwater, surface-water, geochemical, geophysical, and geologic information that subsequently were used to develop this conceptual model.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20133024","collaboration":"Prepared in cooperation with the Middle Pecos Groundwater Conservation District, Pecos County, City of Fort Stockton, Brewster County, and Pecos County Water Control and Improvement District No. 1","usgsCitation":"Thomas, J.V., Stanton, G.P., Bumgarner, J.R., Pearson, D., Teeple, A., Houston, N.A., Payne, J., and Musgrove, M., 2013, A conceptual hydrogeologic model for the hydrogeologic framework, geochemistry, and groundwater-flow system of the Edwards-Trinity and related aquifers in the Pecos County region, Texas: U.S. Geological Survey Fact Sheet 2013-3024, 6 p., https://doi.org/10.3133/fs20133024.","productDescription":"6 p.","numberOfPages":"6","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":272903,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20133024.gif"},{"id":272902,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2013/3024/pdf/fs2013-3024.pdf"},{"id":272901,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2013/3024/"}],"projection":"Albers Equal Area","datum":"North American Datum of 1983","country":"United States","state":"Texas","county":"Pecos County","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -104,30.08 ], [ -104,31.30 ], [ -102,31.30 ], [ -102,30.08 ], [ -104,30.08 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51a5c3d2e4b0605bc571ef52","contributors":{"authors":[{"text":"Thomas, Jonathan V. 0000-0003-0903-9713 jvthomas@usgs.gov","orcid":"https://orcid.org/0000-0003-0903-9713","contributorId":2194,"corporation":false,"usgs":true,"family":"Thomas","given":"Jonathan","email":"jvthomas@usgs.gov","middleInitial":"V.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":478993,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stanton, Gregory P. 0000-0001-8622-0933 gstanton@usgs.gov","orcid":"https://orcid.org/0000-0001-8622-0933","contributorId":1583,"corporation":false,"usgs":true,"family":"Stanton","given":"Gregory","email":"gstanton@usgs.gov","middleInitial":"P.","affiliations":[],"preferred":true,"id":478991,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bumgarner, Johnathan R. jbumgarner@usgs.gov","contributorId":5378,"corporation":false,"usgs":true,"family":"Bumgarner","given":"Johnathan","email":"jbumgarner@usgs.gov","middleInitial":"R.","affiliations":[],"preferred":true,"id":478994,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pearson, Daniel K.","contributorId":52014,"corporation":false,"usgs":true,"family":"Pearson","given":"Daniel K.","affiliations":[],"preferred":false,"id":478996,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Teeple, Andrew 0000-0003-1781-8354 apteeple@usgs.gov","orcid":"https://orcid.org/0000-0003-1781-8354","contributorId":1399,"corporation":false,"usgs":true,"family":"Teeple","given":"Andrew ","email":"apteeple@usgs.gov","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":false,"id":478990,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Houston, Natalie A. 0000-0002-6071-4545 nhouston@usgs.gov","orcid":"https://orcid.org/0000-0002-6071-4545","contributorId":1682,"corporation":false,"usgs":true,"family":"Houston","given":"Natalie","email":"nhouston@usgs.gov","middleInitial":"A.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":478992,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Payne, Jason 0000-0003-4294-7924 jdpayne@usgs.gov","orcid":"https://orcid.org/0000-0003-4294-7924","contributorId":1062,"corporation":false,"usgs":true,"family":"Payne","given":"Jason ","email":"jdpayne@usgs.gov","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":false,"id":478989,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Musgrove, MaryLynn","contributorId":34878,"corporation":false,"usgs":true,"family":"Musgrove","given":"MaryLynn","affiliations":[],"preferred":false,"id":478995,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70043209,"text":"70043209 - 2013 - Gaussian process regression for sensor networks under localization uncertainty","interactions":[],"lastModifiedDate":"2013-05-28T10:14:22","indexId":"70043209","displayToPublicDate":"2013-05-28T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1947,"text":"IEEE Transactions on Signal Processing","active":true,"publicationSubtype":{"id":10}},"title":"Gaussian process regression for sensor networks under localization uncertainty","docAbstract":"In this paper, we formulate Gaussian process regression with observations under the localization uncertainty due to the resource-constrained sensor networks. In our formulation, effects of observations, measurement noise, localization uncertainty, and prior distributions are all correctly incorporated in the posterior predictive statistics. The analytically intractable posterior predictive statistics are proposed to be approximated by two techniques, viz., Monte Carlo sampling and Laplace's method. Such approximation techniques have been carefully tailored to our problems and their approximation error and complexity are analyzed. Simulation study demonstrates that the proposed approaches perform much better than approaches without considering the localization uncertainty properly. Finally, we have applied the proposed approaches on the experimentally collected real data from a dye concentration field over a section of a river and a temperature field of an outdoor swimming pool to provide proof of concept tests and evaluate the proposed schemes in real situations. In both simulation and experimental results, the proposed methods outperform the quick-and-dirty solutions often used in practice.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"IEEE Transactions on Signal Processing","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"IEEE","doi":"10.1109/TSP.2012.2223695","usgsCitation":"Jadaliha, M., Xu, Y., Choi, J., Johnson, N., and Li, W., 2013, Gaussian process regression for sensor networks under localization uncertainty: IEEE Transactions on Signal Processing, v. 61, no. 2, p. 223-237, https://doi.org/10.1109/TSP.2012.2223695.","productDescription":"15 p.","startPage":"223","endPage":"237","ipdsId":"IP-041065","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":272859,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":272857,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1109/TSP.2012.2223695"}],"volume":"61","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51a5c3e4e4b0605bc571ef66","contributors":{"authors":[{"text":"Jadaliha, M.","contributorId":45210,"corporation":false,"usgs":true,"family":"Jadaliha","given":"M.","email":"","affiliations":[],"preferred":false,"id":473173,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Xu, Yunfei","contributorId":17513,"corporation":false,"usgs":true,"family":"Xu","given":"Yunfei","email":"","affiliations":[],"preferred":false,"id":473172,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Choi, Jongeun","contributorId":84229,"corporation":false,"usgs":true,"family":"Choi","given":"Jongeun","affiliations":[],"preferred":false,"id":473176,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Johnson, N.S.","contributorId":73436,"corporation":false,"usgs":true,"family":"Johnson","given":"N.S.","email":"","affiliations":[],"preferred":false,"id":473175,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Li, Weiming","contributorId":65440,"corporation":false,"usgs":true,"family":"Li","given":"Weiming","affiliations":[],"preferred":false,"id":473174,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70046136,"text":"sim3252 - 2013 - Automated mapping of mineral groups and green vegetation from Landsat Thematic Mapper imagery with an example from the San Juan Mountains, Colorado","interactions":[],"lastModifiedDate":"2013-05-28T14:30:22","indexId":"sim3252","displayToPublicDate":"2013-05-28T00:00:00","publicationYear":"2013","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":"3252","title":"Automated mapping of mineral groups and green vegetation from Landsat Thematic Mapper imagery with an example from the San Juan Mountains, Colorado","docAbstract":"Multispectral satellite data acquired by the ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) and Landsat 7 Enhanced Thematic Mapper Plus (TM) sensors are being used to populate an online Geographic Information System (GIS) of the spatial occurrence of mineral groups and green vegetation across the western conterminous United States and Alaska. These geospatial data are supporting U.S. Geological Survey national-scale mineral deposit database development and other mineral resource and geoenvironmental research as a means of characterizing mineral exposures related to mined and unmined hydrothermally altered rocks and mine waste.\n\nThis report introduces a new methodology for the automated analysis of Landsat TM data that has been applied to more than 180 scenes covering the western United States. A map of mineral groups and green vegetation produced using this new methodology that covers the western San Juan Mountains, Colorado, and the Four Corners Region is presented. The map is provided as a layered GeoPDF and in GIS-ready digital format. TM data analysis results from other well-studied and mineralogically characterized areas with strong hydrothermal alteration and (or) supergene weathering of near-surface sulfide minerals are also shown and compared with results derived from ASTER data analysis.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3252","usgsCitation":"Rockwell, B.W., 2013, Automated mapping of mineral groups and green vegetation from Landsat Thematic Mapper imagery with an example from the San Juan Mountains, Colorado: U.S. Geological Survey Scientific Investigations Map 3252, iv, 25 p.; Map: 1 Sheet: 36 x 40 inches; Downloads Directory, https://doi.org/10.3133/sim3252.","productDescription":"iv, 25 p.; Map: 1 Sheet: 36 x 40 inches; Downloads Directory","numberOfPages":"31","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":272912,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sim3252.gif"},{"id":272908,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3252/"},{"id":272909,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3252/downloads/pdfs/SIM3252_pamphlet.pdf"},{"id":272910,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3252/downloads/pdfs/SIM3252_map.pdf"},{"id":272911,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sim/3252/downloads/"}],"country":"United States","state":"Colorado","otherGeospatial":"San Juan Mountains","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -109.0,37.0 ], [ -109.0,41.0 ], [ -102.0,41.0 ], [ -102.0,37.0 ], [ -109.0,37.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51a5c3e2e4b0605bc571ef5a","contributors":{"authors":[{"text":"Rockwell, Barnaby W. 0000-0002-9549-0617 barnabyr@usgs.gov","orcid":"https://orcid.org/0000-0002-9549-0617","contributorId":2195,"corporation":false,"usgs":true,"family":"Rockwell","given":"Barnaby","email":"barnabyr@usgs.gov","middleInitial":"W.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":479002,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70046112,"text":"sir20135104 - 2013 - Organic waste compounds in streams: Occurrence and aquatic toxicity in different stream compartments, flow regimes, and land uses in southeast Wisconsin, 2006–9","interactions":[],"lastModifiedDate":"2013-05-28T08:29:56","indexId":"sir20135104","displayToPublicDate":"2013-05-28T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-5104","title":"Organic waste compounds in streams: Occurrence and aquatic toxicity in different stream compartments, flow regimes, and land uses in southeast Wisconsin, 2006–9","docAbstract":"An assessment of organic chemicals and aquatic toxicity in streams located near Milwaukee, Wisconsin, indicated high potential for adverse impacts on aquatic organisms that could be related to organic waste compounds (OWCs). OWCs used in agriculture, industry, and households make their way into surface waters through runoff, leaking septic-conveyance systems, regulated and unregulated discharges, and combined sewage overflows, among other sources. Many of these compounds are toxic at elevated concentrations and (or) known to have endocrine-disrupting potential, and often they occur as complex mixtures. There is still much to be learned about the chronic exposure effects of these compounds on aquatic populations. During 2006–9, the U.S. Geological Survey, in cooperation with the Milwaukee Metropolitan Sewerage District (MMSD), conducted a study to determine the occurrence and potential toxicity of OWCs in different stream compartments and flow regimes for streams in the Milwaukee area. Samples were collected at 17 sites and analyzed for a suite of 69 OWCs. Three types of stream compartments were represented: water column, streambed pore water, and streambed sediment. Water-column samples were subdivided by flow regime into stormflow and base-flow samples. One or more compounds were detected in all 196 samples collected, and 64 of the 69 compounds were detected at least once. Base-flow samples had the lowest detection rates, with a median of 12 compounds detected per sample. Median detection rates for stormflow, pore-water, and sediment samples were more than double that of base-flow samples. Compounds with the highest detection rates include polycyclic aromatic hydrocarbons (PAHs), insecticides, herbicides, and dyes/pigments. Elevated occurrence and concentrations of some compounds were detected in samples from urban sites, as compared with more rural sites, especially during stormflow conditions. These include the PAHs and the domestic waste-water-indicator compounds, among others. Urban runoff and storm-related leaks of sanitary sewers and (or) septic systems may be important sources of these and other compounds to the streams. The Kinnickinnic River, a highly urbanized site, had the highest detection rates and concentrations of compounds of all the sampled sites. The Milwaukee River near Cedarburg—one of the least urban sites—and the Outer Milwaukee Harbor site had the lowest detection rates and concentrations. Aquatic-toxicity benchmarks were exceeded for 12 of the 25 compounds with known benchmarks. The compounds with the greatest benchmark exceedances were the PAHs, both in terms of exceedance frequency (up to 93 percent for some compounds in sediment samples) and magnitude (concentrations up to 1,024 times greater than the benchmark value). Other compounds with toxicity-benchmark exceedances include Bis(2-ethylhexyl) phthalate (a plasticizer), 2-Methylnapthalene (a component of fuel and oil), phenol (an antimicrobial disinfectant with diverse uses), and 4-Nonylphenol (sum of all isomers; a detergent metabolite, among other uses). Analyzed as a mixture, the suite of PAH compounds were found to be potentially toxic for most non-base-flow samples. Bioassay tests were conducted on samples from 14 streams: Ceriodaphnia dubia in base-flow samples, Ceriodaphnia dubia and Hyallela azteca in pore-water samples, and Hyallela azteca and Chironomus tentans in sediment samples. The greatest adverse effect was observed in tests with Chironomus tentans from sediment samples. The weight of Chironomus tentans after exposure to sediments decreased with increased OWC concentrations. This was most evident in the relation between PAH results and Chironomus tentans bioassay results for the majority of samples; however, solvents and flame retardants appeared to be important for one site each. These results for PAHs were consistent with assessment of PAH potency factors for sediment, indicating that PAHs were likely to have adverse effects on aquatic organisms in many of the streams studied.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135104","collaboration":"Prepared in cooperation with the Milwaukee Metropolitan Sewerage District","usgsCitation":"Baldwin, A.K., Corsi, S., Richards, K.D., Geis, S.W., and Magruder, C., 2013, Organic waste compounds in streams: Occurrence and aquatic toxicity in different stream compartments, flow regimes, and land uses in southeast Wisconsin, 2006–9: U.S. Geological Survey Scientific Investigations Report 2013-5104, vii, 48 p., https://doi.org/10.3133/sir20135104.","productDescription":"vii, 48 p.","numberOfPages":"58","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":272830,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135104.gif"},{"id":272829,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5104/pdf/sir2013-5104.pdf"},{"id":272828,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5104/"}],"country":"United States","state":"Wisconsin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -88.40,42.50 ], [ -88.40,43.50 ], [ -87.40,43.50 ], [ -87.40,42.50 ], [ -88.40,42.50 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51a5c3e6e4b0605bc571ef6e","contributors":{"authors":[{"text":"Baldwin, Austin K. 0000-0002-6027-3823 akbaldwi@usgs.gov","orcid":"https://orcid.org/0000-0002-6027-3823","contributorId":4515,"corporation":false,"usgs":true,"family":"Baldwin","given":"Austin","email":"akbaldwi@usgs.gov","middleInitial":"K.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":478952,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Corsi, Steven R. srcorsi@usgs.gov","contributorId":511,"corporation":false,"usgs":true,"family":"Corsi","given":"Steven R.","email":"srcorsi@usgs.gov","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":false,"id":478951,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Richards, Kevin D. krichard@usgs.gov","contributorId":280,"corporation":false,"usgs":true,"family":"Richards","given":"Kevin","email":"krichard@usgs.gov","middleInitial":"D.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":false,"id":478950,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Geis, Steven W.","contributorId":85868,"corporation":false,"usgs":true,"family":"Geis","given":"Steven","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":478954,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Magruder, Christopher","contributorId":35995,"corporation":false,"usgs":true,"family":"Magruder","given":"Christopher","affiliations":[],"preferred":false,"id":478953,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70046109,"text":"ofr20131093 - 2013 - Solid-phase data from cores at the proposed Dewey Burdock uranium in-situ recovery mine, near Edgemont, South Dakota","interactions":[],"lastModifiedDate":"2013-05-27T20:31:16","indexId":"ofr20131093","displayToPublicDate":"2013-05-27T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-1093","title":"Solid-phase data from cores at the proposed Dewey Burdock uranium in-situ recovery mine, near Edgemont, South Dakota","docAbstract":"This report releases solid-phase data from cores at the proposed Dewey Burdock uranium in-situ recovery site near Edgemont, South Dakota. These cores were collected by Powertech Uranium Corporation, and material not used for their analyses were given to the U.S. Geological Survey for additional sampling and analyses. These additional analyses included total carbon and sulfur, whole rock acid digestion for major and trace elements, 234U/238U activity ratios, X-ray diffraction, thin sections, scanning electron microscopy analyses, and cathodoluminescence. This report provides the methods and data results from these analyses along with a short summary of observations.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131093","collaboration":"In cooperation with the Environmental Protection Agency","usgsCitation":"Johnson, R.H., Diehl, S.F., and Benzel, W., 2013, Solid-phase data from cores at the proposed Dewey Burdock uranium in-situ recovery mine, near Edgemont, South Dakota: U.S. Geological Survey Open-File Report 2013-1093, iii, 13 p.; 2 Tables; 5 Appendixes, https://doi.org/10.3133/ofr20131093.","productDescription":"iii, 13 p.; 2 Tables; 5 Appendixes","numberOfPages":"16","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-042233","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":272820,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131093.gif"},{"id":272813,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2013/1093/Table%201%20all%20solid%20data%20for%20pubs.xls"},{"id":272814,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2013/1093/Table%202%20XRD%20data%20for%20pubs.xlsx"},{"id":272811,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1093/"},{"id":272812,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1093/OF13-1093.pdf"},{"id":272815,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2013/1093/Appendix%20A%20carbon-sulfur/EPA-carbon-sulfur_final.xlsx"},{"id":272816,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2013/1093/Appendix%20C%20Transmitted%20light"},{"id":272817,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2013/1093/Appendix%20D%20SEM%20images"},{"id":272818,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2013/1093/Appendix%20E%20SEM%20Elemental%20Maps"},{"id":272819,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2013/1093/Appendix%20B%20uranium%20isotopes/KettererUrpt%2020Feb2012_final.pdf"}],"country":"United States","state":"South Dakota","city":"Edgemont","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -103.843393,43.289569 ], [ -103.843393,43.30621 ], [ -103.81689,43.30621 ], [ -103.81689,43.289569 ], [ -103.843393,43.289569 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51a47259e4b064a995b7a0c3","contributors":{"authors":[{"text":"Johnson, Raymond H. rhjohnso@usgs.gov","contributorId":707,"corporation":false,"usgs":true,"family":"Johnson","given":"Raymond","email":"rhjohnso@usgs.gov","middleInitial":"H.","affiliations":[],"preferred":true,"id":478935,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Diehl, Sharon F. diehl@usgs.gov","contributorId":1089,"corporation":false,"usgs":true,"family":"Diehl","given":"Sharon","email":"diehl@usgs.gov","middleInitial":"F.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":478936,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Benzel, William 0000-0002-4085-1876 wbenzel@usgs.gov","orcid":"https://orcid.org/0000-0002-4085-1876","contributorId":3594,"corporation":false,"usgs":true,"family":"Benzel","given":"William","email":"wbenzel@usgs.gov","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":478937,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70046106,"text":"70046106 - 2013 - Evidence for extensive methane venting on the southeastern U.S. Atlantic margin","interactions":[],"lastModifiedDate":"2013-07-01T09:52:50","indexId":"70046106","displayToPublicDate":"2013-05-27T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1796,"text":"Geology","active":true,"publicationSubtype":{"id":10}},"title":"Evidence for extensive methane venting on the southeastern U.S. Atlantic margin","docAbstract":"We present the first evidence for widespread seabed methane venting along the southeastern United States Atlantic margin beyond the well-known Blake Ridge diapir seep. Recent ship- and autonomous underwater vehicle (AUV)–collected data resolve multiple water-column anomalies (>1000 m height) and extensive new chemosynthetic seep communities at the Blake Ridge and Cape Fear diapirs. These results indicate that multiple, highly localized fluid conduits punctuate the areally extensive Blake Ridge gas hydrate province, and enable the delivery of significant amounts of methane to the water column. Thus, there appears to be an abundance of seabed fluid flux not previously ascribed to the Atlantic margin of the United States.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Geology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.1130/G34217.1","usgsCitation":"Brothers, L., Van Dover, C., German, C., Kaiser, C., Yoerger, D., Ruppel, C., Lobecker, E., Skarke, A., and Wagner, J., 2013, Evidence for extensive methane venting on the southeastern U.S. Atlantic margin: Geology, v. 41, no. 7, p. 807-810, https://doi.org/10.1130/G34217.1.","productDescription":"4 p.","startPage":"807","endPage":"810","ipdsId":"IP-044454","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":272825,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":272824,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1130/G34217.1"}],"volume":"41","issue":"7","noUsgsAuthors":false,"publicationDate":"2013-05-16","publicationStatus":"PW","scienceBaseUri":"51a47250e4b064a995b7a0bb","contributors":{"authors":[{"text":"Brothers, L.L.","contributorId":17074,"corporation":false,"usgs":true,"family":"Brothers","given":"L.L.","email":"","affiliations":[],"preferred":false,"id":478926,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Van Dover, C.L.","contributorId":104507,"corporation":false,"usgs":true,"family":"Van Dover","given":"C.L.","affiliations":[],"preferred":false,"id":478934,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"German, C.R.","contributorId":24673,"corporation":false,"usgs":true,"family":"German","given":"C.R.","email":"","affiliations":[],"preferred":false,"id":478927,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kaiser, C.L.","contributorId":32434,"corporation":false,"usgs":true,"family":"Kaiser","given":"C.L.","email":"","affiliations":[],"preferred":false,"id":478929,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Yoerger, D.R.","contributorId":54492,"corporation":false,"usgs":true,"family":"Yoerger","given":"D.R.","email":"","affiliations":[],"preferred":false,"id":478930,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ruppel, C.D.","contributorId":64839,"corporation":false,"usgs":true,"family":"Ruppel","given":"C.D.","email":"","affiliations":[],"preferred":false,"id":478932,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lobecker, E.","contributorId":30122,"corporation":false,"usgs":true,"family":"Lobecker","given":"E.","email":"","affiliations":[],"preferred":false,"id":478928,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Skarke, A.D.","contributorId":57752,"corporation":false,"usgs":true,"family":"Skarke","given":"A.D.","affiliations":[],"preferred":false,"id":478931,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Wagner, J.K.S.","contributorId":101970,"corporation":false,"usgs":true,"family":"Wagner","given":"J.K.S.","email":"","affiliations":[],"preferred":false,"id":478933,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70043838,"text":"70043838 - 2013 - Frequent cross-species transmission of parvoviruses among diverse carnivore hosts","interactions":[],"lastModifiedDate":"2015-04-29T14:12:08","indexId":"70043838","displayToPublicDate":"2013-05-27T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2497,"text":"Journal of Virology","active":true,"publicationSubtype":{"id":10}},"title":"Frequent cross-species transmission of parvoviruses among diverse carnivore hosts","docAbstract":"Although parvoviruses are commonly described in domestic carnivores, little is known about their biodiversity in nondomestic species. A phylogenetic analysis of VP2 gene sequences from puma, coyote, gray wolf, bobcat, raccoon, and striped skunk revealed two major groups related to either feline panleukopenia virus (“FPV-like”) or canine parvovirus (“CPV-like”). Cross-species transmission was commonplace, with multiple introductions into each host species but, with the exception of raccoons, relatively little evidence for onward transmission in nondomestic species.
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