{"pageNumber":"681","pageRowStart":"17000","pageSize":"25","recordCount":46666,"records":[{"id":70046772,"text":"70046772 - 2011 - A Digital Hydrologic Network Supporting NAWQA MRB SPARROW Modeling--MRB_E2RF1WS","interactions":[],"lastModifiedDate":"2013-07-02T15:40:17","indexId":"70046772","displayToPublicDate":"2011-01-01T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":6,"text":"USGS Unnumbered Series"},"title":"A Digital Hydrologic Network Supporting NAWQA MRB SPARROW Modeling--MRB_E2RF1WS","docAbstract":"A digital hydrologic network was developed to support SPAtially Referenced Regression on Watershed attributes (SPARROW) models within selected regions of the United States. These regions correspond with the U.S. Geological Survey's National Water Quality Assessment (NAWQA) Program Major River Basin (MRB) study units 2, 3, 4, 5, and 7 (Preston and others, 2009).  MRB2, covers the South Atlantic-Gulf and Tennessee River basins.  MRB3, covers the Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy River basins.  MRB4, covers the Missouri River basins.  MRB5, covers the Lower Mississippi, Arkansas-White-Red, and Texas-Gulf River basins.  MRB7, covers the Pacific Northwest River basins. The digital hydrologic network described here represents surface-water pathways (MRB_E2RF1) and associated catchments (MRB_E2RF1WS). It serves as the fundamental framework to spatially reference and summarize explanatory information supporting nutrient SPARROW models (Brakebill and others, 2011; Wieczorek and LaMotte, 2011). The principal geospatial dataset used to support this regional effort was based on an enhanced version of a 1:500,000 scale digital stream-reach network (ERF1_2) (Nolan et al., 2002). Enhancements included associating over 3,500 water-quality monitoring sites to the reach network, improving physical locations of stream reaches at or near monitoring locations, and generating drainage catchments based on 100m elevation data. A unique number (MRB_ID) identifies each reach as a single unit. This unique number is also shared by the catchment area drained by the reach, thus spatially linking the hydrologically connected streams and the respective drainage area characteristics. In addition, other relevant physical, environmental, and monitoring information can be associated to the common network and accessed using the unique identification number.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Baltimore, MA","doi":"10.3133/70046772","usgsCitation":"Brakebill, J., and Terziotti, S., 2011, A Digital Hydrologic Network Supporting NAWQA MRB SPARROW Modeling--MRB_E2RF1WS (Version 1.0), Dataset, https://doi.org/10.3133/70046772.","productDescription":"Dataset","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[],"links":[{"id":274444,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":274443,"type":{"id":16,"text":"Metadata"},"url":"https://water.usgs.gov/GIS/metadata/usgswrd/XML/mrb_e2rf1ws.xml"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -128.290499,23.033207 ], [ -128.290499,52.450082 ], [ -64.959844,52.450082 ], [ -64.959844,23.033207 ], [ -128.290499,23.033207 ] ] ] } } ] }","edition":"Version 1.0","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51d3f662e4b09630fbdc526e","contributors":{"authors":[{"text":"Brakebill, J. W.","contributorId":48206,"corporation":false,"usgs":true,"family":"Brakebill","given":"J. W.","affiliations":[],"preferred":false,"id":480204,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Terziotti, S.E.","contributorId":6287,"corporation":false,"usgs":true,"family":"Terziotti","given":"S.E.","email":"","affiliations":[],"preferred":false,"id":480203,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70156865,"text":"70156865 - 2011 - Management case study: Tampa Bay, Florida","interactions":[],"lastModifiedDate":"2022-11-07T17:48:51.435963","indexId":"70156865","displayToPublicDate":"2011-01-01T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"3","title":"Management case study: Tampa Bay, Florida","docAbstract":"<p id=\"sp9110\">Tampa Bay, Florida, USA, is a shallow, subtropical estuary that experienced severe cultural eutrophication between the 1940s and 1980s, a period when the human population of its watershed quadrupled. In response, citizen action led to the formation of a public- and private-sector partnership (the Tampa Bay Estuary Program), which adopted a number of management objectives to support the restoration and protection of the bay’s living resources. These included numeric chlorophyll<span>&nbsp;</span><i>a</i><span>&nbsp;</span>and water-clarity targets, as well as long-term goals addressing the spatial extent of seagrasses and other selected habitat types, to support estuarine-dependent faunal guilds.</p><p id=\"sp0005\">Over the past three decades, nitrogen controls involving sources such as wastewater treatment plants, stormwater conveyance systems, fertilizer manufacturing and shipping operations, and power plants have been undertaken to meet these and other management objectives. Cumulatively, these controls have resulted in a 60% reduction in annual total nitrogen (TN) loads relative to earlier worse-case (latter 1970s) conditions. As a result, annual water-clarity and chlorophyll<span>&nbsp;</span><i>a</i><span>&nbsp;</span>targets are currently met in most years, and seagrass cover measured in 2008 was the highest recorded since 1950.</p><p id=\"sp0010\">Factors that have contributed to the observed improvements in Tampa Bay over the past several decades include the following: (1) Development of numeric, science-based water-quality targets to meet a long-term goal of restoring seagrass acreage to 1950s levels. Empirical and mechanistic models found that annual average chlorophyll<span>&nbsp;</span><i>a</i><span>&nbsp;</span>concentrations were a primary manageable factor affecting light attenuation. The models also quantified relationships between TN loads, chlorophyll<span>&nbsp;</span><i>a</i><span>&nbsp;</span>concentrations, light attenuation, and fluctuations in seagrass cover. The availability of long-term monitoring data, and a systematic process for using the data to evaluate the effectiveness of management actions, has allowed managers to track progress and make adaptive changes when needed. (2) Citizen involvement, that is, the initial reductions in TN loads, which occurred in the late 1970s and early 1980s, was a result of state regulations that were developed in response to citizens’ call for action. Improved water clarity and better fishing and swimming conditions were identified as primary goals by citizens again in the early 1990s, and led to development of numeric water-quality targets and seagrass restoration goals. More recent citizen actions, from pet waste campaigns to support of reductions in residential fertilizer use, are important elements of the nitrogen management strategy. (3) Collaborative actions, that is, in addition to numerous other collaborative ventures that have benefitted Tampa Bay, the public/private Nitrogen Management Consortium, which includes more than 40 participating organizations, has implemented over 250 nutrient-reduction projects. These projects have addressed stormwater treatment, fertilizer manufacturing and shipping, agricultural practices, reclaimed water use, and atmospheric emissions from local power stations, providing more than 300 tons of TN load reductions since 1995. (4) State and federal regulatory programs, that is, regulatory requirements, such as state statutes and rules requiring compliance with advanced wastewater treatment standards by municipal sewerage works, have played a key role in Tampa Bay management efforts. The technical basis and implementation plan of the Tampa Bay nitrogen management strategy have been developed in cooperation with state and federal regulatory agencies, and the strategy has been recognized by them as an appropriate tool for meeting water-quality standards, including federally mandated total maximum daily loads.</p><p id=\"sp0015\">Subsequent management efforts have focused on maintaining and extending those improvements in Tampa Bay’s environmental resources by addressing water and sediment quality and habitat protection and restoration. Implementation of a collaborative, watershed-based management process, driven by an integrated science approach, has played a central role in supporting progress toward the achievement of science-based estuary management goals.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Management of Estuaries and Coasts","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Academic Press","doi":"10.1016/B978-0-12-374711-2.01104-9","usgsCitation":"Morrison, G., Greening, H., and Yates, K.K., 2011, Management case study: Tampa Bay, Florida, chap. 3 <i>of</i> Management of Estuaries and Coasts, v. 11, p. 31-76, https://doi.org/10.1016/B978-0-12-374711-2.01104-9.","productDescription":"46 p.","startPage":"31","endPage":"76","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science 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,{"id":70036932,"text":"70036932 - 2011 - Growth rate and age distribution of deep-sea black corals in the Gulf of Mexico","interactions":[],"lastModifiedDate":"2013-06-02T20:08:01","indexId":"70036932","displayToPublicDate":"2011-01-01T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2663,"text":"Marine Ecology Progress Series","active":true,"publicationSubtype":{"id":10}},"title":"Growth rate and age distribution of deep-sea black corals in the Gulf of Mexico","docAbstract":"Black corals (order Antipatharia) are important long-lived, habitat-forming, sessile, benthic suspension feeders that are found in all oceans and are usually found in water depths greater than 30 m. Deep-water black corals are some of the slowest-growing, longest-lived deep-sea corals known. Previous age dating of a limited number of black coral samples in the Gulf of Mexico focused on extrapolated ages and growth rates based on skeletal <sup>210</sup>Pb dating. Our results greatly expand the age and growth rate data of black corals from the Gulf of Mexico. Radiocarbon analysis of the oldest Leiopathes sp. specimen from the upper De Soto Slope at 300 m water depth indicates that these animals have been growing continuously for at least the last 2 millennia, with growth rates ranging from 8 to 22 µm yr<sup>–1</sup>. Visual growth ring counts based on scanning electron microscopy images were in good agreement with the <sup>14</sup>C-derived ages, suggestive of annual ring formation. The presence of bomb-derived <sup>14</sup>C in the outermost samples confirms sinking particulate organic matter as the dominant carbon source and suggests a link between the deep-sea and surface ocean. There was a high degree of reproducibility found between multiple discs cut from the base of each specimen, as well as within duplicate subsamples. Robust <sup>14</sup>C-derived chronologies and known surface ocean <sup>14</sup>C reservoir age constraints in the Gulf of Mexico provided reliable calendar ages with future application to the development of proxy records.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Marine Ecology Progress Series","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Inter-Research","doi":"10.3354/meps08953","issn":"01718630","usgsCitation":"Prouty, N., Roark, E., Buster, N., and Ross, S.W., 2011, Growth rate and age distribution of deep-sea black corals in the Gulf of Mexico: Marine Ecology Progress Series, v. 423, p. 101-115, https://doi.org/10.3354/meps08953.","productDescription":"15 p.","startPage":"101","endPage":"115","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":475286,"rank":10000,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/meps08953","text":"Publisher Index Page"},{"id":217865,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.3354/meps08953"},{"id":245837,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Gulf Of Mexico","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -97.9,18.2 ], [ -97.9,30.4 ], [ -81.0,30.4 ], [ -81.0,18.2 ], [ -97.9,18.2 ] ] ] } } ] }","volume":"423","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a2dffe4b0c8380cd5c1f5","contributors":{"authors":[{"text":"Prouty, N.G.","contributorId":36766,"corporation":false,"usgs":true,"family":"Prouty","given":"N.G.","email":"","affiliations":[],"preferred":false,"id":458525,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Roark, E.B.","contributorId":30076,"corporation":false,"usgs":true,"family":"Roark","given":"E.B.","email":"","affiliations":[],"preferred":false,"id":458524,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Buster, N.A.","contributorId":105518,"corporation":false,"usgs":true,"family":"Buster","given":"N.A.","affiliations":[],"preferred":false,"id":458527,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ross, Steve W.","contributorId":72543,"corporation":false,"usgs":false,"family":"Ross","given":"Steve","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":458526,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70036903,"text":"70036903 - 2011 - In-situ gas hydrate hydrate saturation estimated from various well logs at the Mount Elbert Gas Hydrate Stratigraphic Test Well, Alaska North Slope","interactions":[],"lastModifiedDate":"2020-12-17T19:30:54.671568","indexId":"70036903","displayToPublicDate":"2011-01-01T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2682,"text":"Marine and Petroleum Geology","active":true,"publicationSubtype":{"id":10}},"title":"In-situ gas hydrate hydrate saturation estimated from various well logs at the Mount Elbert Gas Hydrate Stratigraphic Test Well, Alaska North Slope","docAbstract":"<p id=\"abspara0010\">In 2006, the U.S. Geological Survey (USGS) completed detailed analysis and interpretation of available 2-D and 3-D seismic data and proposed a viable method for identifying sub-permafrost gas hydrate prospects within the gas hydrate stability zone in the Milne Point area of northern Alaska. To validate the predictions of the USGS and to acquire critical reservoir data needed to develop a long-term production testing program, a well was drilled at the Mount Elbert prospect in February, 2007. Numerous well log data and cores were acquired to estimate in-situ gas hydrate saturations and reservoir properties.</p><p id=\"abspara0015\">Gas hydrate saturations were estimated from various well logs such as nuclear magnetic resonance (NMR), P- and S-wave velocity, and electrical resistivity logs along with pore-water salinity. Gas hydrate saturations from the NMR log agree well with those estimated from P- and S-wave velocity data. Because of the low salinity of the connate water and the low formation temperature, the resistivity of connate water is comparable to that of shale. Therefore, the effect of clay should be accounted for to accurately estimate gas hydrate saturations from the resistivity data. Two highly gas hydrate-saturated intervals are identified – an upper ∼43 ft zone with an average gas hydrate saturation of 54% and a lower ∼53 ft zone with an average gas hydrate saturation of 50%; both zones reach a maximum of about 75% saturation.</p>","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Marine and Petroleum Geology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.1016/j.marpetgeo.2009.06.007","issn":"02648172","usgsCitation":"Lee, M.W., and Collett, T.S., 2011, In-situ gas hydrate hydrate saturation estimated from various well logs at the Mount Elbert Gas Hydrate Stratigraphic Test Well, Alaska North Slope: Marine and Petroleum Geology, v. 28, no. 2, p. 439-449, https://doi.org/10.1016/j.marpetgeo.2009.06.007.","productDescription":"11 p.","startPage":"439","endPage":"449","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":245864,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":217891,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.marpetgeo.2009.06.007"}],"country":"United States","state":"Alaska","otherGeospatial":"Mount Elbert Gas Hydrate Stratigraphic Test Well","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -161.3671875,\n              70.28911664330674\n            ],\n            [\n              -159.169921875,\n              68.65655498475735\n            ],\n            [\n              -154.775390625,\n              67.60922060496382\n            ],\n            [\n              -140.44921875,\n              68.26938680456564\n            ],\n            [\n              -139.921875,\n              70.11048478105927\n            ],\n            [\n              -153.28125,\n              72.58082870324515\n            ],\n            [\n              -159.609375,\n              71.88357830131248\n            ],\n            [\n              -161.3671875,\n              70.28911664330674\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"28","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a39c2e4b0c8380cd61a2d","contributors":{"authors":[{"text":"Lee, Myung W. mlee@usgs.gov","contributorId":779,"corporation":false,"usgs":true,"family":"Lee","given":"Myung","email":"mlee@usgs.gov","middleInitial":"W.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":458412,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Collett, Timothy S. 0000-0002-7598-4708 tcollett@usgs.gov","orcid":"https://orcid.org/0000-0002-7598-4708","contributorId":1698,"corporation":false,"usgs":true,"family":"Collett","given":"Timothy","email":"tcollett@usgs.gov","middleInitial":"S.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":458413,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70036902,"text":"70036902 - 2011 - Geologic controls on gas hydrate occurrence in the Mount Elbert prospect, Alaska North Slope","interactions":[],"lastModifiedDate":"2020-12-17T19:51:02.165658","indexId":"70036902","displayToPublicDate":"2011-01-01T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2682,"text":"Marine and Petroleum Geology","active":true,"publicationSubtype":{"id":10}},"title":"Geologic controls on gas hydrate occurrence in the Mount Elbert prospect, Alaska North Slope","docAbstract":"<p><span>Data acquired at the BPXA-DOE-USGS Mount Elbert Gas Hydrate Stratigraphic Test Well, drilled in the Milne Point area of the Alaska North Slope in February, 2007, indicates two zones of high gas hydrate saturation within the Eocene Sagavanirktok Formation. Gas hydrate is observed in two separate sand reservoirs (the D and C units), in the stratigraphically highest portions of those sands, and is not detected in non-sand lithologies. In the younger D unit, gas hydrate appears to fill much of the available reservoir space at the top of the unit. The degree of vertical fill with the D unit is closely related to the unit reservoir quality. A thick, low-permeability clay-dominated unit serves as an upper seal, whereas a subtle transition to more clay-rich, and interbedded sand, silt, and clay units is associated with the base of gas hydrate occurrence. In the underlying C unit, the reservoir is similarly capped by a clay-dominated section, with gas hydrate filling the relatively lower-quality sands at the top of the unit leaving an underlying thick section of high-reservoir quality sands devoid of gas hydrate. Evaluation of well log, core, and seismic data indicate that the gas hydrate occurs within complex combination stratigraphic/structural traps. Structural trapping is provided by a four-way fold closure augmented by a large western bounding fault. Lithologic variation is also a likely strong control on lateral extent of the reservoirs, particularly in the D unit accumulation, where gas hydrate appears to extend beyond the limits of the structural closure. Porous and permeable zones within the C unit sand are only partially charged due most likely to limited structural trapping in the reservoir lithofacies during the period of primary charging. The occurrence of the gas hydrate within the sands in the upper portions of both the C and D units and along the crest of the fold is consistent with an interpretation that these deposits are converted free gas accumulations formed prior to the imposition of gas hydrate stability conditions.</span></p>","largerWorkTitle":"Marine and Petroleum Geology","language":"English","publisher":"Elsevier","doi":"10.1016/j.marpetgeo.2009.12.004","issn":"02648172","usgsCitation":"Boswell, R., Rose, K., Collett, T.S., Lee, M.W., Winters, W.J., Lewis, K.A., and Agena, W.F., 2011, Geologic controls on gas hydrate occurrence in the Mount Elbert prospect, Alaska North Slope: Marine and Petroleum Geology, v. 28, no. 2, p. 589-607, https://doi.org/10.1016/j.marpetgeo.2009.12.004.","productDescription":"19 p.","startPage":"589","endPage":"607","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":475172,"rank":10000,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hdl.handle.net/1912/4387","text":"External Repository"},{"id":245863,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":217890,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.marpetgeo.2009.12.004"}],"country":"United States","state":"Alaska","otherGeospatial":"The Mount Elbert well","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -161.3671875,\n              70.28911664330674\n            ],\n            [\n              -159.169921875,\n              68.65655498475735\n            ],\n            [\n             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K.","contributorId":43594,"corporation":false,"usgs":true,"family":"Rose","given":"K.","email":"","affiliations":[],"preferred":false,"id":458407,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Collett, Timothy S. 0000-0002-7598-4708 tcollett@usgs.gov","orcid":"https://orcid.org/0000-0002-7598-4708","contributorId":1698,"corporation":false,"usgs":true,"family":"Collett","given":"Timothy","email":"tcollett@usgs.gov","middleInitial":"S.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":458409,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lee, Myung W. mlee@usgs.gov","contributorId":779,"corporation":false,"usgs":true,"family":"Lee","given":"Myung","email":"mlee@usgs.gov","middleInitial":"W.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":458405,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Winters, William J. bwinters@usgs.gov","contributorId":522,"corporation":false,"usgs":true,"family":"Winters","given":"William","email":"bwinters@usgs.gov","middleInitial":"J.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":458410,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lewis, Kristen A. 0000-0003-4991-3399 klewis@usgs.gov","orcid":"https://orcid.org/0000-0003-4991-3399","contributorId":4120,"corporation":false,"usgs":true,"family":"Lewis","given":"Kristen","email":"klewis@usgs.gov","middleInitial":"A.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":458411,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Agena, Warren F. wagena@usgs.gov","contributorId":3181,"corporation":false,"usgs":true,"family":"Agena","given":"Warren","email":"wagena@usgs.gov","middleInitial":"F.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":458408,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70036869,"text":"70036869 - 2011 - Development and application of a pollen-based paleohydrologic reconstruction from the lower Roanoke River Basin, North Carolina, USA","interactions":[],"lastModifiedDate":"2013-04-24T22:06:16","indexId":"70036869","displayToPublicDate":"2011-01-01T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3562,"text":"The Holocene","active":true,"publicationSubtype":{"id":10}},"title":"Development and application of a pollen-based paleohydrologic reconstruction from the lower Roanoke River Basin, North Carolina, USA","docAbstract":"We used pollen assemblages to reconstruct late-Holocene paleohydrologic patterns in floodplain deposits from the lower Roanoke River basin (North Carolina, southeastern USA). Using 120 surface samples from 38 transects, we documented statistical relationships between pollen assemblages, vegetation, and landforms. Backswamp pollen assemblages (long hydroperiods) are dominated by Nyssa (tupelo) and Taxodium (cypress) and have high pollen concentrations. Sediments from elevated levees and seasonally flooded forests (shorter hydroperiods) are characterized by dominant Pinus (pine) pollen, variable abundance of hardwood taxa, and low pollen concentrations. We apply the calibration data set to interpret past vegetation and paleohydrology. Pollen from a radiocarbon-dated sediment core collected in a tupelo-cypress backswamp indicates centennial-scale fluctuations in forest composition during the last 2400 years. Backswamp vegetation has occupied the site since land clearance began ~300 years ago. Recent dam emplacement affected sedimentation rates, but vegetation changes are small compared with those caused by pre-Colonial climate variability. The occurrence of wetter conditions from ~2200 to 1800 cal. yr BP, ~1100 to 750 cal. yr BP, and ~400 to 250 cal. yr BP may indicate changes in cyclonic circulation patterns related to shifts in the position of the Bermuda High and jet stream.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"The Holocene","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Sage Journals","doi":"10.1177/0959683610378876","issn":"09596836","usgsCitation":"Willard, D., Bernhardt, C., Brown, R., Landacre, B., and Townsend, P., 2011, Development and application of a pollen-based paleohydrologic reconstruction from the lower Roanoke River Basin, North Carolina, USA: The Holocene, v. 21, no. 2, p. 305-317, https://doi.org/10.1177/0959683610378876.","productDescription":"13 p.","startPage":"305","endPage":"317","costCenters":[],"links":[{"id":217829,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1177/0959683610378876"},{"id":245801,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"21","issue":"2","noUsgsAuthors":false,"publicationDate":"2010-10-08","publicationStatus":"PW","scienceBaseUri":"505a0019e4b0c8380cd4f5b6","contributors":{"authors":[{"text":"Willard, D. 0000-0003-4878-0942","orcid":"https://orcid.org/0000-0003-4878-0942","contributorId":67676,"corporation":false,"usgs":true,"family":"Willard","given":"D.","affiliations":[],"preferred":false,"id":458205,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bernhardt, C. 0000-0003-0082-4731","orcid":"https://orcid.org/0000-0003-0082-4731","contributorId":104307,"corporation":false,"usgs":true,"family":"Bernhardt","given":"C.","affiliations":[],"preferred":false,"id":458208,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brown, R.","contributorId":101419,"corporation":false,"usgs":true,"family":"Brown","given":"R.","affiliations":[],"preferred":false,"id":458207,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Landacre, B.","contributorId":11037,"corporation":false,"usgs":true,"family":"Landacre","given":"B.","affiliations":[],"preferred":false,"id":458204,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Townsend, P.","contributorId":83366,"corporation":false,"usgs":true,"family":"Townsend","given":"P.","email":"","affiliations":[],"preferred":false,"id":458206,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70036865,"text":"70036865 - 2011 - Documenting channel features associated with gas hydrates in the Krishna-Godavari Basin, offshore India","interactions":[],"lastModifiedDate":"2020-12-18T18:04:37.819215","indexId":"70036865","displayToPublicDate":"2011-01-01T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2667,"text":"Marine Geology","active":true,"publicationSubtype":{"id":10}},"title":"Documenting channel features associated with gas hydrates in the Krishna-Godavari Basin, offshore India","docAbstract":"<p><span>During the India National Gas Hydrate Program (NGHP) Expedition 01 in 2006 significant sand and gas hydrate were recovered at Site NGHP-01-15 within the Krishna–Godavari Basin, East Coast off India. At the drill site NGHP-01-15, a 5–8</span><span>&nbsp;</span><span>m thick interval was found that is characterized by higher sand content than anywhere else at the site and within the KG Basin. Gas hydrate concentrations were determined to be 20–40% of the pore volume using wire-line electrical resistivity data as well as core-derived pore-fluid freshening trends. The gas hydrate-bearing interval was linked to a prominent seismic reflection observed in the 3D seismic data. This reflection event, mapped for about 1</span><span>&nbsp;</span><span>km</span><sup>2</sup><span>&nbsp;south of the drill site, is bound by a fault at its northern limit that may act as migration conduit for free gas to enter the gas hydrate stability zone (GHSZ) and subsequently charge the sand-rich layer. On 3D and additional regional 2D seismic data a prominent channel system was imaged mainly by using the seismic instantaneous amplitude attribute. The channel can be clearly identified by changes in the seismic character of the channel fill (sand-rich) and pronounced levees (less sand content than in the fill, but higher than in surrounding mud-dominated sediments). The entire channel sequence (channel fill and levees) has been subsequently covered and back-filled with a more mud-prone sediment sequence. Where the levees intersect the base of the GHSZ, their reflection strengths are significantly increased to 5- to 6-times the surrounding reflection amplitudes. Using the 3D seismic data these high-amplitude reflection edges where linked to the gas hydrate-bearing layer at Site NGHP-01-15. Further south along the channel the same reflection elements representing the levees do not show similarly large reflection amplitudes. However, the channel system is still characterized by several high-amplitude reflection events (a few hundred meters wide and up to ~</span><span>&nbsp;</span><span>1</span><span>&nbsp;</span><span>km in extent) interpreted as gas hydrate-bearing sand intervals along the length of the channel.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.margeo.2010.10.008","issn":"00253227","usgsCitation":"Riedel, M., Collett, T.S., and Shankar, U., 2011, Documenting channel features associated with gas hydrates in the Krishna-Godavari Basin, offshore India: Marine Geology, v. 279, no. 1-4, p. 1-11, https://doi.org/10.1016/j.margeo.2010.10.008.","productDescription":"11 p.","startPage":"1","endPage":"11","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":245739,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":217773,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.margeo.2010.10.008"}],"country":"India","otherGeospatial":"Krishna–Godavari Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              80.9912109375,\n              15.114552871944115\n            ],\n            [\n              81.82617187499999,\n              13.66733825965496\n            ],\n            [\n              84.990234375,\n              15.580710739162123\n            ],\n            [\n              83.671875,\n              16.804541076383455\n            ],\n            [\n              80.9912109375,\n              15.114552871944115\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"279","issue":"1-4","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a0387e4b0c8380cd50506","contributors":{"authors":[{"text":"Riedel, M.","contributorId":65268,"corporation":false,"usgs":true,"family":"Riedel","given":"M.","email":"","affiliations":[],"preferred":false,"id":458191,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Collett, Timothy S. 0000-0002-7598-4708 tcollett@usgs.gov","orcid":"https://orcid.org/0000-0002-7598-4708","contributorId":1698,"corporation":false,"usgs":true,"family":"Collett","given":"Timothy","email":"tcollett@usgs.gov","middleInitial":"S.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":458193,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shankar, Ude","contributorId":80033,"corporation":false,"usgs":false,"family":"Shankar","given":"Ude","email":"","affiliations":[],"preferred":false,"id":458192,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70036864,"text":"70036864 - 2011 - Co-occurrence patterns of trees along macro-climatic gradients and their potential influence on the present and future distribution of Fagus sylvatica L.","interactions":[],"lastModifiedDate":"2020-12-18T18:15:21.920437","indexId":"70036864","displayToPublicDate":"2011-01-01T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2193,"text":"Journal of Biogeography","active":true,"publicationSubtype":{"id":10}},"title":"Co-occurrence patterns of trees along macro-climatic gradients and their potential influence on the present and future distribution of Fagus sylvatica L.","docAbstract":"<p><span>During recent and future climate change, shifts in large-scale species ranges are expected due to the hypothesized major role of climatic factors in regulating species distributions. The stress-gradient hypothesis suggests that biotic interactions may act as major constraints on species distributions under more favourable growing conditions, while climatic constraints may dominate under unfavourable conditions. We tested this hypothesis for one focal tree species having three major competitors using broad-scale environmental data. We evaluated the variation of species co-occurrence patterns in climate space and estimated the influence of these patterns on the distribution of the focal species for current and projected future climates. Location: Europe. Methods: We used ICP Forest Level 1 data as well as climatic, topographic and edaphic variables. First, correlations between the relative abundance of European beech (Fagus sylvatica) and three major competitor species (Picea abies, Pinus sylvestris and Quercus robur) were analysed in environmental space, and then projected to geographic space. Second, a sensitivity analysis was performed using generalized additive models (GAM) to evaluate where and how much the predicted F. sylvatica distribution varied under current and future climates if potential competitor species were included or excluded. We evaluated if these areas coincide with current species co-occurrence patterns. Results: Correlation analyses supported the stress-gradient hypothesis: towards favourable growing conditions of F. sylvatica, its abundance was strongly linked to the abundance of its competitors, while this link weakened towards unfavourable growing conditions, with stronger correlations in the south and at low elevations than in the north and at high elevations. The sensitivity analysis showed a potential spatial segregation of species with changing climate and a pronounced shift of zones where co-occurrence patterns may play a major role. Main conclusions: Our Results: demonstrate the importance of species co-occurrence patterns for calibrating improved species distribution models for use in projections of climate effects. The correlation approach is able to localize European areas where inclusion of biotic predictors is effective. The climateinduced spatial segregation of the major tree species could have ecological and economic consequences.</span></p>","language":"English","publisher":"Blackwell Publishing","doi":"10.1111/j.1365-2699.2010.02405.x","issn":"03050270","usgsCitation":"Meier, E., Edwards, T.C., Kienast, F., Dobbertin, M., and Zimmermann, N., 2011, Co-occurrence patterns of trees along macro-climatic gradients and their potential influence on the present and future distribution of Fagus sylvatica L.: Journal of Biogeography, v. 38, no. 2, p. 371-382, https://doi.org/10.1111/j.1365-2699.2010.02405.x.","productDescription":"12 p.","startPage":"371","endPage":"382","ipdsId":"IP-024915","costCenters":[],"links":[{"id":488972,"rank":10000,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://zenodo.org/record/3436519","text":"External Repository"},{"id":245710,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":217747,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/j.1365-2699.2010.02405.x"}],"otherGeospatial":"Europe","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -10.1953125,\n              36.31512514748051\n            ],\n            [\n              0.703125,\n              37.16031654673677\n            ],\n            [\n              5.712890625,\n              38.06539235133249\n            ],\n            [\n              9.404296875,\n              38.34165619279595\n            ],\n            [\n              14.677734375000002,\n              35.02999636902566\n            ],\n            [\n              29.091796875,\n              34.66935854524543\n            ],\n            [\n              29.443359375,\n              36.527294814546245\n            ],\n            [\n              26.279296875,\n              40.245991504199026\n            ],\n            [\n              32.16796875,\n              45.9511496866914\n            ],\n            [\n              40.25390625,\n              47.57652571374621\n            ],\n            [\n              40.25390625,\n              49.724479188712984\n            ],\n            [\n              33.57421875,\n              52.482780222078226\n            ],\n            [\n              29.970703124999996,\n              51.998410382390325\n            ],\n            [\n              32.431640625,\n              53.64463782485651\n            ],\n            [\n              30.673828125,\n              55.727110085045986\n            ],\n            [\n              28.652343749999996,\n              56.70450561416937\n            ],\n            [\n              30.937499999999996,\n              60.58696734225869\n            ],\n            [\n              30.937499999999996,\n              64.62387720204688\n            ],\n            [\n              29.53125,\n              69.41124235697256\n            ],\n            [\n              31.289062500000004,\n              71.85622888185527\n            ],\n            [\n              21.09375,\n              71.63599288330609\n            ],\n            [\n              8.0859375,\n              67.06743335108298\n            ],\n            [\n              -12.65625,\n              60.75915950226991\n            ],\n            [\n              -13.7109375,\n              54.36775852406841\n            ],\n            [\n              -10.1953125,\n              36.31512514748051\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"38","issue":"2","noUsgsAuthors":false,"publicationDate":"2010-10-29","publicationStatus":"PW","scienceBaseUri":"5059f67ae4b0c8380cd4c7b7","contributors":{"authors":[{"text":"Meier, E.S.","contributorId":102713,"corporation":false,"usgs":true,"family":"Meier","given":"E.S.","email":"","affiliations":[],"preferred":false,"id":458190,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Edwards, Thomas C. 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,{"id":70192763,"text":"70192763 - 2011 - Coal resources for the Chemard Lake (Naborton No. 2) coal zone of the lower Wilcox group (Paleocene), northwestern Louisiana","interactions":[],"lastModifiedDate":"2020-10-22T16:44:00.587484","indexId":"70192763","displayToPublicDate":"2011-01-01T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"seriesTitle":{"id":5382,"text":"AAPG Studies in Geology","active":false,"publicationSubtype":{"id":24}},"chapter":"6","title":"Coal resources for the Chemard Lake (Naborton No. 2) coal zone of the lower Wilcox group (Paleocene), northwestern Louisiana","docAbstract":"<p><span>The lower part of the Wilcox Group of northwest Louisiana contains shallow (less than 500 ft) coal deposits that are mined for use in mine-mouth electric power-generating plants. The coal deposits, which are lignite A in apparent rank (Pierce et al., 2011), occur on the eastern part of the Sabine uplift (Figure 1). The coal zones and associated strata in the assessment area generally dip away from the axis of the Red River-Bull Bayou dome that is located in the north-central part of the Louisiana Sabine assessment area (Figure 1). This assessment area includes parts of four parishes: De Soto, Red River, Natchitoches, and Sabine (Figure 2). The assessment area was selected because of its proximity to current mining areas and the availability of stratigraphic data in the area. The assessment area is roughly 60 miles long and 15 miles wide and generally extends across the central-eastern part of the Sabine uplift in northwest Louisiana (Figure 2). More than 950 stratigraphic records from rotary and core drill holes were used to assess the coal resources of the Louisiana Sabine area. Of these, 210 are public data points and are located in or near the areas that have been permitted or proposed for surface mining (Figure 2; Appendix 1). Most of the stratigraphic data used for this assessment were provided to the U.S. Geological Survey (USGS) on a confidential basis by various coal companies for use in regional studies.</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Geologic assessment of coal in the Gulf of Mexico coastal plain","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"American Association of Petroleum Geologists","usgsCitation":"Warwick, P.D., Podwysocki, S.M., and Schultz, A.C., 2011, Coal resources for the Chemard Lake (Naborton No. 2) coal zone of the lower Wilcox group (Paleocene), northwestern Louisiana, chap. 6 <i>of</i> Geologic assessment of coal in the Gulf of Mexico coastal plain: AAPG Studies in Geology, v. 62, p. 109-127.","productDescription":"19 p.","startPage":"109","endPage":"127","ipdsId":"IP-020033","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and 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pwarwick@usgs.gov","orcid":"https://orcid.org/0000-0002-3152-7783","contributorId":762,"corporation":false,"usgs":true,"family":"Warwick","given":"Peter","email":"pwarwick@usgs.gov","middleInitial":"D.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":716852,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Podwysocki, Steven M.","contributorId":90352,"corporation":false,"usgs":true,"family":"Podwysocki","given":"Steven","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":716853,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schultz, Adam C.","contributorId":82752,"corporation":false,"usgs":true,"family":"Schultz","given":"Adam","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":716854,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70157248,"text":"70157248 - 2011 - Swallows as a sentinel species for contaminant exposure and effect studies","interactions":[],"lastModifiedDate":"2021-11-09T17:36:53.636876","indexId":"70157248","displayToPublicDate":"2011-01-01T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Swallows as a sentinel species for contaminant exposure and effect studies","docAbstract":"<p><span>Tree swallows are an important model species to study the effects of contaminants in wild bird populations and have been used extensively in studies across North America. The advantages of swallows compared to other avian species are detailed. Three case histories are provided where swallows have been successfully used in Natural Resource Damage and Ecological Risk Assessments. The final two sections of this chapter are for individuals who want more in-depth information and include a summary of the chemical classes for which there are swallow data, including effect levels when known. Information provided in this section can be used to put exposure to most classes of contaminants into context with other sites across North America. Finally, commonly used endpoints, ranging from population-level down to cellular and genetic endpoints, are discussed including considerations and pitfalls, and when further work is needed to more fully understand the role of environmental and biological variation in interpreting these endpoints.</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Wildlife ecotoxicology: Forensic approaches","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","publisherLocation":"New York, NY","doi":"10.1007/978-0-387-89432-4_3","usgsCitation":"Custer, C.M., 2011, Swallows as a sentinel species for contaminant exposure and effect studies, chap. <i>of</i> Wildlife ecotoxicology: Forensic approaches, p. 45-91, https://doi.org/10.1007/978-0-387-89432-4_3.","productDescription":"47 p.","startPage":"45","endPage":"91","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-015056","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":308137,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2011-05-31","publicationStatus":"PW","scienceBaseUri":"55f94142e4b05d6c4e5013a9","contributors":{"editors":[{"text":"Elliott, John G. jelliott@usgs.gov","contributorId":832,"corporation":false,"usgs":true,"family":"Elliott","given":"John","email":"jelliott@usgs.gov","middleInitial":"G.","affiliations":[],"preferred":true,"id":572406,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Bishop, Christine Annette","contributorId":147717,"corporation":false,"usgs":false,"family":"Bishop","given":"Christine","email":"","middleInitial":"Annette","affiliations":[],"preferred":false,"id":572407,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Morrissey, Christy A.","contributorId":147718,"corporation":false,"usgs":false,"family":"Morrissey","given":"Christy","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":572408,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"Custer, Christine M. 0000-0003-0500-1582 ccuster@usgs.gov","orcid":"https://orcid.org/0000-0003-0500-1582","contributorId":1143,"corporation":false,"usgs":true,"family":"Custer","given":"Christine","email":"ccuster@usgs.gov","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":572409,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70036414,"text":"70036414 - 2011 - Changes in monoterpene mixing ratios during summer storms in rural New Hampshire (USA)","interactions":[],"lastModifiedDate":"2021-01-12T17:54:49.252301","indexId":"70036414","displayToPublicDate":"2011-01-01T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":922,"text":"Atmospheric Chemistry and Physics","active":true,"publicationSubtype":{"id":10}},"title":"Changes in monoterpene mixing ratios during summer storms in rural New Hampshire (USA)","docAbstract":"<p><span>Monoterpenes are an important class of biogenic hydrocarbons that influence ambient air quality and are a principle source of secondary organic aerosol (SOA). Emitted from vegetation, monoterpenes are a product of photosynthesis and act as a response to a variety of environmental factors. Most parameterizations of monoterpene emissions are based on clear weather models that do not take into account episodic conditions that can drastically change production and release rates into the atmosphere. Here, the monoterpene dataset from the rural Thompson Farm measurement site in Durham, New Hampshire is examined in the context of a set of known severe storm events. While some storm systems had a negligible influence on ambient monoterpene mixing ratios, the average storm event increased mixing ratios by 0.59 ± 0.21 ppbv, a factor of 93% above pre-storm levels. In some events, mixing ratios reached the 10's of ppbv range and persisted overnight. These mixing ratios correspond to increases in the monoterpene emission rate, ranging from 120 to 1240 g km</span><sup>−2</sup><span>&nbsp;h</span><sup>−1</sup><span>&nbsp;compared to an estimated clear weather rate of 116 to 193 g km</span><sup>−2</sup><span>&nbsp;h</span><sup>−1</sup><span>. Considering the regularity of storm events over most forested areas, this could be an important factor to consider when modeling global monoterpene emissions and their resulting influence on the formation of organic aerosols.</span></p>","language":"English","publisher":"Copernicus Publications","publisherLocation":"Göttingen, Germany","doi":"10.5194/acp-11-11465-2011","issn":"16807316","usgsCitation":"Haase, K.B., Jordan, C., Mentis, E., Cottrell, L., Mayne, H., Talbot, R., and Sive, B., 2011, Changes in monoterpene mixing ratios during summer storms in rural New Hampshire (USA): Atmospheric Chemistry and Physics, v. 11, no. 22, p. 11465-11476, https://doi.org/10.5194/acp-11-11465-2011.","productDescription":"9 p.","startPage":"11465","endPage":"11476","costCenters":[{"id":146,"text":"Branch of Regional Research-Eastern Region","active":false,"usgs":true}],"links":[{"id":475112,"rank":10000,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/acp-11-11465-2011","text":"Publisher Index Page"},{"id":246256,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":218261,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.5194/acp-11-11465-2011"}],"country":"United States","state":"New Hampshire","otherGeospatial":"Thompson Farm","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -71.35345458984375,\n              42.92626291864936\n            ],\n            [\n              -70.740966796875,\n              42.92626291864936\n            ],\n            [\n              -70.740966796875,\n              43.329173667843904\n            ],\n            [\n              -71.35345458984375,\n              43.329173667843904\n            ],\n            [\n              -71.35345458984375,\n              42.92626291864936\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"11","issue":"22","noUsgsAuthors":false,"publicationDate":"2011-11-17","publicationStatus":"PW","scienceBaseUri":"5059f41ce4b0c8380cd4bb4b","contributors":{"authors":[{"text":"Haase, Karl B. 0000-0002-6897-6494 khaase@usgs.gov","orcid":"https://orcid.org/0000-0002-6897-6494","contributorId":3405,"corporation":false,"usgs":true,"family":"Haase","given":"Karl","email":"khaase@usgs.gov","middleInitial":"B.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":456018,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jordan, C.","contributorId":17454,"corporation":false,"usgs":true,"family":"Jordan","given":"C.","email":"","affiliations":[],"preferred":false,"id":456019,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mentis, E.","contributorId":62441,"corporation":false,"usgs":true,"family":"Mentis","given":"E.","email":"","affiliations":[],"preferred":false,"id":456021,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cottrell, L.","contributorId":64925,"corporation":false,"usgs":true,"family":"Cottrell","given":"L.","email":"","affiliations":[],"preferred":false,"id":456022,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mayne, H.R.","contributorId":21016,"corporation":false,"usgs":true,"family":"Mayne","given":"H.R.","email":"","affiliations":[],"preferred":false,"id":456020,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Talbot, R.","contributorId":67758,"corporation":false,"usgs":true,"family":"Talbot","given":"R.","email":"","affiliations":[],"preferred":false,"id":456024,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sive, B.C.","contributorId":66518,"corporation":false,"usgs":true,"family":"Sive","given":"B.C.","email":"","affiliations":[],"preferred":false,"id":456023,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70174864,"text":"70174864 - 2011 - Inland surface water: Chapter 18","interactions":[],"lastModifiedDate":"2018-02-21T16:14:08","indexId":"70174864","displayToPublicDate":"2011-01-01T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":32,"text":"General Technical Report","active":false,"publicationSubtype":{"id":1}},"seriesNumber":"NRS-80","title":"Inland surface water: Chapter 18","docAbstract":"<p>Freshwater aquatic ecosystems include rivers and streams, large and small lakes, reservoirs, and ephemeral ponds. Wetlands are defi ned and discussed in Chapter 17 of this report. It is estimated that there are 123,400 lakes with a surface area greater than 4 ha in the United States. Most lakes, however, are smaller than 4 ha; small lakes account for the majority of lake surface area both globally and in the United States (Table 18.1; Downing et al. 2006). Th e density of lakes varies greatly by region of the country, from 8.4 lakes per 100 km2 in the upper Midwest and 7.8 lakes per 100 km2 in Florida, to much lower values in other areas of the country (e.g., mid-Atlantic, Southeast, and West &lt;1.0 lakes per 100 km2 ) ( Eilers and Selle 1991). Th e cumulative surface area of these lakes is approximately 9.5 million ha. Th e U.S. Geologic Survey's National Hydrographic Dataset (NHD) estimates that there are approximately 1.1 million km of perennial fl owing streams in the United States. Of these about 91 percent are fi rst through fourth order (&ldquo;wadeable&rdquo;) (US EPA 2006).</p>","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Assessment of N deposition effects and empirical critical loads of N for ecoregions of the United States","largerWorkSubtype":{"id":1,"text":"Federal Government Series"},"language":"English","publisher":"U.S. Department of Agriculture, Forest Service, Northern Research Station","usgsCitation":"Baron, J., Driscoll, C.T., and Stoddard, J., 2011, Inland surface water: Chapter 18: General Technical Report NRS-80, 19 p.","productDescription":"19 p.","startPage":"209","endPage":"227","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-022968","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":325428,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":325427,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.treesearch.fs.fed.us/pubs/38109"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"578f4f2de4b0ad6235cf001e","contributors":{"authors":[{"text":"Baron, Jill 0000-0002-5902-6251 jill_baron@usgs.gov","orcid":"https://orcid.org/0000-0002-5902-6251","contributorId":194124,"corporation":false,"usgs":true,"family":"Baron","given":"Jill","email":"jill_baron@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":642877,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Driscoll, C. T.","contributorId":47530,"corporation":false,"usgs":false,"family":"Driscoll","given":"C.","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":642878,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stoddard, J.L.","contributorId":75709,"corporation":false,"usgs":true,"family":"Stoddard","given":"J.L.","email":"","affiliations":[],"preferred":false,"id":642879,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70193259,"text":"70193259 - 2011 - Radiotelemetry to estimate stream life of adult chum salmon in the McNeil River, Alaska","interactions":[],"lastModifiedDate":"2017-11-15T14:50:33","indexId":"70193259","displayToPublicDate":"2011-01-01T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Radiotelemetry to estimate stream life of adult chum salmon in the McNeil River, Alaska","docAbstract":"<p><span>Estimating salmon escapement is one of the fundamental steps in managing salmon populations. The area-under-the-curve (AUC) method is commonly used to convert periodic aerial survey counts into annual salmon escapement indices. The AUC requires obtaining accurate estimates of stream life (SL) for target species. Traditional methods for estimating SL (e.g., mark–recapture) are not feasible for many populations. Our objective in this study was to determine the average SL of chum salmon&nbsp;</span><i>Oncorhynchus keta</i><span><span>&nbsp;</span>in the McNeil River, Alaska, through radiotelemetry. During the 2005 and 2006 runs, 155 chum salmon were fitted with mortality-indicating radio tags as they entered the McNeil River and tracked until they died. A combination of remote data loggers, aerial surveys, and foot surveys were used to determine the location of fish and provide an estimate of time of death. Higher predation resulted in tagged fish below McNeil Falls having a significantly shorter SL (12.6 d) than those above (21.9 d). The streamwide average SL (13.8 d) for chum salmon at the McNeil River was lower than the regionwide value (17.5 d) previously used to generate AUC indices of chum salmon escapement for the McNeil River. We conclude that radiotelemetry is an effective tool for estimating SL in rivers not well suited to other methods.</span></p>","language":"English","publisher":"Taylor & Francis","doi":"10.1080/02755947.2011.574080","usgsCitation":"Peirce, J., Otis, E.O., Wipfli, M.S., and Follmann, E., 2011, Radiotelemetry to estimate stream life of adult chum salmon in the McNeil River, Alaska: North American Journal of Fisheries Management, v. 31, no. 2, p. 315-322, https://doi.org/10.1080/02755947.2011.574080.","productDescription":"8 p.","startPage":"315","endPage":"322","ipdsId":"IP-013106","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":348914,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"McNeil River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -154.2978286743164,\n              59.0957028026867\n            ],\n            [\n              -154.2037582397461,\n              59.0957028026867\n            ],\n            [\n              -154.2037582397461,\n              59.13843678215489\n            ],\n            [\n              -154.2978286743164,\n              59.13843678215489\n            ],\n            [\n              -154.2978286743164,\n              59.0957028026867\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"31","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2011-05-02","publicationStatus":"PW","scienceBaseUri":"5a6107fce4b06e28e9c25632","contributors":{"authors":[{"text":"Peirce, Joshua","contributorId":42510,"corporation":false,"usgs":true,"family":"Peirce","given":"Joshua","email":"","affiliations":[],"preferred":false,"id":722265,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Otis, Edward O.","contributorId":19065,"corporation":false,"usgs":true,"family":"Otis","given":"Edward","email":"","middleInitial":"O.","affiliations":[],"preferred":false,"id":722266,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wipfli, Mark S. 0000-0002-4856-6068 mwipfli@usgs.gov","orcid":"https://orcid.org/0000-0002-4856-6068","contributorId":1425,"corporation":false,"usgs":true,"family":"Wipfli","given":"Mark","email":"mwipfli@usgs.gov","middleInitial":"S.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":718461,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Follmann, Erich H.","contributorId":75049,"corporation":false,"usgs":true,"family":"Follmann","given":"Erich H.","affiliations":[],"preferred":false,"id":722267,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70176225,"text":"70176225 - 2011 - A review of the lignite resources of Arkansas","interactions":[],"lastModifiedDate":"2020-10-16T16:58:56.51936","indexId":"70176225","displayToPublicDate":"2011-01-01T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"seriesTitle":{"id":5382,"text":"AAPG Studies in Geology","active":false,"publicationSubtype":{"id":24}},"chapter":"17","title":"A review of the lignite resources of Arkansas","docAbstract":"<p><span>This review of the lignite resources of Arkansas is a part of the U.S. Geological Survey's (USGS) National Coal Resource Assessment (NCRA) of the Gulf Coastal Plain Coal Province, which also includes coal-bearing areas in the states of Texas, Louisiana, Alabama, Mississippi, Tennessee, and Kentucky (see&nbsp;</span><a class=\"link link-ref link-reveal xref-bibr\" data-open=\"ch17r53\">Ruppert et al., 2002</a><span>;&nbsp;</span><a class=\"link link-ref link-reveal xref-bibr\" data-open=\"ch17r16\">Dennen, 2009</a><span>; and other chapters of this publication). Lignite mining is not planned in Arkansas in the immediate future, and the lignite resources of the state were not assessed in detail as part of the NCRA. This chapter includes reviews of the geology of the lignite-bearing units, historical mining, previous investigations of lignite resources, and coal quality. Palynological data for lignite samples collected in Arkansas as part of this work are presented in Table&nbsp;</span><a class=\"link link-reveal link-table xref-fig\" data-open=\"ch17tbl1\">1</a><span>.</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Geologic assessment of coal in the Gulf of Mexico coastal plain: AAPG Studies in Geology vol. 62","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"American Association of Petroleum Geologists","usgsCitation":"Hackley, P.C., Willett, J.C., Warwick, P.D., Law, S., and Nichols, D.J., 2011, A review of the lignite resources of Arkansas, chap. 17 <i>of</i> Geologic assessment of coal in the Gulf of Mexico coastal plain: AAPG Studies in Geology vol. 62: AAPG Studies in Geology, v. 62, p. 313-325.","productDescription":"13 p.","startPage":"313","endPage":"325","ipdsId":"IP-020070","costCenters":[{"id":241,"text":"Eastern Energy Resources Science 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,{"id":70046785,"text":"70046785 - 2011 - A Digital Hydrologic Network Supporting NAWQA MRB SPARROW Modeling--MRB_E2RF1WS","interactions":[],"lastModifiedDate":"2013-07-08T13:04:35","indexId":"70046785","displayToPublicDate":"2011-01-01T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":6,"text":"USGS Unnumbered Series"},"seriesTitle":{"id":361,"text":"General Information","active":false,"publicationSubtype":{"id":6}},"title":"A Digital Hydrologic Network Supporting NAWQA MRB SPARROW Modeling--MRB_E2RF1WS","docAbstract":"A digital hydrologic network was developed to support SPAtially Referenced Regression on Watershed attributes (SPARROW) models within selected regions of the United States. These regions correspond with the U.S. Geological Survey's National Water Quality Assessment (NAWQA) Program Major River Basin (MRB) study units 2, 3, 4, 5, and 7 (Preston and others, 2009).  MRB2, covers the South Atlantic-Gulf and Tennessee River basins.  MRB3, covers the Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy River basins.  MRB4, covers the Missouri River basins.  MRB5, covers the Lower Mississippi, Arkansas-White-Red, and Texas-Gulf River basins.  MRB7, covers the Pacific Northwest River basins. The digital hydrologic network described here represents surface-water pathways (MRB_E2RF1) and associated catchments (MRB_E2RF1WS). It serves as the fundamental framework to spatially reference and summarize explanatory information supporting nutrient SPARROW models (Brakebill and others, 2011; Wieczorek and LaMotte, 2011). The principal geospatial dataset used to support this regional effort was based on an enhanced version of a 1:500,000 scale digital stream-reach network (ERF1_2) (Nolan et al., 2002). Enhancements included associating over 3,500 water-quality monitoring sites to the reach network, improving physical locations of stream reaches at or near monitoring locations, and generating drainage catchments based on 100m elevation data. A unique number (MRB_ID) identifies each reach as a single unit. This unique number is also shared by the catchment area drained by the reach, thus spatially linking the hydrologically connected streams and the respective drainage area characteristics. In addition, other relevant physical, environmental, and monitoring information can be associated to the common network and accessed using the unique identification number.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/70046785","usgsCitation":"Brakebill, J., and Terziotti, S., 2011, A Digital Hydrologic Network Supporting NAWQA MRB SPARROW Modeling--MRB_E2RF1WS (1.0): General Information, Dataset, https://doi.org/10.3133/70046785.","productDescription":"Dataset","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[],"links":[{"id":274631,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":274629,"type":{"id":16,"text":"Metadata"},"url":"https://water.usgs.gov/GIS/metadata/usgswrd/XML/mrb_e2rf1ws.xml"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -128.290499,23.033207 ], [ -128.290499,52.450082 ], [ -64.959844,52.450082 ], [ -64.959844,23.033207 ], [ -128.290499,23.033207 ] ] ] } } ] }","edition":"1.0","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51dbdf64e4b0f81004b77c9f","contributors":{"authors":[{"text":"Brakebill, J. W.","contributorId":48206,"corporation":false,"usgs":true,"family":"Brakebill","given":"J. W.","affiliations":[],"preferred":false,"id":480249,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Terziotti, S.E.","contributorId":6287,"corporation":false,"usgs":true,"family":"Terziotti","given":"S.E.","email":"","affiliations":[],"preferred":false,"id":480248,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70159146,"text":"70159146 - 2011 - Chapter 39 The Edwardsburg Formation and related rocks, Windermere Supergroup, central Idaho, USA","interactions":[],"lastModifiedDate":"2015-10-15T16:34:22","indexId":"70159146","displayToPublicDate":"2011-01-01T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2711,"text":"Memoir of the Geological Society of America","active":true,"publicationSubtype":{"id":10}},"title":"Chapter 39 The Edwardsburg Formation and related rocks, Windermere Supergroup, central Idaho, USA","docAbstract":"<p><span>In central Idaho, Neoproterozoic stratified rocks are engulfed by the Late Cretaceous Idaho batholith and by Eocene volcanic and plutonic rocks of the Challis event. Studied sections in the Gospel Peaks and Big Creek areas of west-central Idaho are in roof pendants of the Idaho batholith. A drill core section studied from near Challis, east-central Idaho, lies beneath the Challis Volcanic Group and is not exposed at the surface. Metamorphic and deformational overprinting, as well as widespread dismembering by the younger igneous rocks, conceals many primary details. Despite this, these rocks provide important links for regional correlations and have produced critical geochronological data for two Neoproterozoic glacial periods in the North American Cordillera. At the base of the section, the more than 700-m-thick Edwardsburg Formation (Fm.) contains interlayered diamictite and volcanic rocks. There are two diamictite-bearing members in the Edwardsburg Fm. that are closely related in time. Each of the diamictites is associated with intermediate composition tuff or flow rocks and the diamictites are separated by mafic volcanic rocks. SHRIMP U&ndash;Pb dating indicates that the lower diamictite is about 685&plusmn;7 Ma, whereas the upper diamictite is 684&plusmn;4 Ma. The diamictite units are part of a cycle of rocks from coarse clastic, to fine clastic, to carbonate rocks that, by correlation to better preserved sections, are thought to record an older Cryogenian glacial to interglacial period in the northern US Cordillera. The more than 75-m-thick diamictite of Daugherty Gulch is dated at 664&plusmn;6 Ma. This unit is preserved only in drill core and the palaeoenvironmental interpretation and local stratigraphic relations are non-unique. Thus, the date for this diamictite may provide a date for a newly recognized glaciogenic horizon or may be a minimum age for the diamictite in the Edwardsburg Fm. The c. 1000-m-thick Moores Lake Fm. is an amphibolite facies diamictite in which glacial features have not been observed. However, it is part of a sedimentary cycle from unsorted siliclastic deposits to mud and carbonate deposits. Using lithostratigraphy and available geochronology, the Moores Lake Fm. is correlated with a younger succession of Cryogenian glaciogenic rocks in southeastern Idaho. Traditional correlations of Neoproterozoic rocks in the Cordillera recognize two levels of Cryogenian diamictites. The Edwardsburg and Moores Lake diamictites along the middle Cordillera fit well into the scenario of two glacial events. Because of the correlations, dates that provide ages for the diamictites in central Idaho (and corroborated in southeastern Idaho, Link &amp; Fanning 2008) could constrain the age of correlated glaciogenic deposits elsewhere in the Cordillera. However, in the absence of dates for the glaciogenic diamictites in Canadian and southern US Cordilleran sections, the correlations are considered possible but uncertain.</span></p>","language":"English","publisher":"The Geological Society","usgsCitation":"Lund, K., Evans, K.V., and Alienikoff, J.N., 2011, Chapter 39 The Edwardsburg Formation and related rocks, Windermere Supergroup, central Idaho, USA: Memoir of the Geological Society of America, v. 36, p. 437-448.","productDescription":"12 p.","startPage":"437","endPage":"448","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[],"links":[{"id":309968,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"Central Idaho","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -116.98242187499999,\n              46.17983040759436\n            ],\n            [\n              -114.43359375,\n              46.10370875598026\n            ],\n            [\n              -112.8955078125,\n              44.402391829093915\n            ],\n            [\n              -113.02734374999999,\n              44.02442151965934\n            ],\n            [\n              -117.04833984375001,\n              43.78695837311561\n            ],\n            [\n              -116.96044921875,\n              44.18220395771566\n            ],\n            [\n              -117.20214843749999,\n              44.37098696297173\n            ],\n            [\n              -117.00439453125,\n              44.77793589631623\n            ],\n            [\n              -116.806640625,\n              45.24395342262324\n            ],\n            [\n              -116.78466796875,\n              45.521743896993634\n            ],\n            [\n              -117.04833984375001,\n              46.08847179577592\n            ],\n            [\n              -116.98242187499999,\n              46.17983040759436\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"36","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5620ce57e4b06217fc478acd","contributors":{"authors":[{"text":"Lund, Karen 0000-0002-4249-3582 klund@usgs.gov","orcid":"https://orcid.org/0000-0002-4249-3582","contributorId":1235,"corporation":false,"usgs":true,"family":"Lund","given":"Karen","email":"klund@usgs.gov","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"preferred":true,"id":577699,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Evans, Karl V. kvevans@usgs.gov","contributorId":194,"corporation":false,"usgs":true,"family":"Evans","given":"Karl","email":"kvevans@usgs.gov","middleInitial":"V.","affiliations":[],"preferred":true,"id":577700,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Alienikoff, John N.","contributorId":85078,"corporation":false,"usgs":true,"family":"Alienikoff","given":"John","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":577701,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70192887,"text":"70192887 - 2011 - The relative importance of physicochemical factors to stream biological condition in urbanizing basins: Evidence from multimodel inference","interactions":[],"lastModifiedDate":"2017-11-12T18:09:25","indexId":"70192887","displayToPublicDate":"2011-01-01T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1699,"text":"Freshwater Science","active":true,"publicationSubtype":{"id":10}},"title":"The relative importance of physicochemical factors to stream biological condition in urbanizing basins: Evidence from multimodel inference","docAbstract":"<p>Many physicochemical factors potentially impair stream ecosystems in urbanizing basins, but few studies have evaluated their relative importance simultaneously, especially in different environmental settings. We used data collected in 25 to 30 streams along a gradient of urbanization in each of 6 metropolitan areas (MAs) to evaluate the relative importance of 11 physicochemical factors on the condition of algal, macroinvertebrate, and fish assemblages. For each assemblage, biological condition was quantified using 2 separate metrics, nonmetric multidimensional scaling ordination site scores and the ratio of observed/expected taxa, both derived in previous studies. Separate linear regression models with 1 or 2 factors as predictors were developed for each MA and assemblage metric. Model parsimony was evaluated based on Akaike’s Information Criterion for small sample size (AICc) and Akaike weights, and variable importance was estimated by summing the Akaike weights across models containing each stressor variable. Few of the factors were strongly correlated (Pearson |<i>r</i>| &gt; 0.7) within MAs. Physicochemical factors explained 17 to 81% of variance in biological condition. Most (92 of 118) of the most plausible models contained 2 predictors, and generally more variance could be explained by the additive effects of 2 factors than by any single factor alone. None of the factors evaluated was universally important for all MAs or biological assemblages. The relative importance of factors varied for different measures of biological condition, biological assemblages, and MA. Our results suggest that the suite of physicochemical factors affecting urban stream ecosystems varies across broad geographic areas, along gradients of urban intensity, and among basins within single MAs.</p>","language":"English","publisher":"University of Chicago Press","doi":"10.1899/10-131.1","usgsCitation":"Carlisle, D.M., and Bryant, W., 2011, The relative importance of physicochemical factors to stream biological condition in urbanizing basins: Evidence from multimodel inference: Freshwater Science, v. 31, no. 1, p. 154-166, https://doi.org/10.1899/10-131.1.","productDescription":"13 p.","startPage":"154","endPage":"166","ipdsId":"IP-011790","costCenters":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"links":[{"id":488743,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://www.bioone.org/doi/10.1899/10-131.1","text":"External Repository"},{"id":348633,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"31","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a096bb3e4b09af898c94155","contributors":{"authors":[{"text":"Carlisle, Daren M. 0000-0002-7367-348X dcarlisle@usgs.gov","orcid":"https://orcid.org/0000-0002-7367-348X","contributorId":513,"corporation":false,"usgs":true,"family":"Carlisle","given":"Daren","email":"dcarlisle@usgs.gov","middleInitial":"M.","affiliations":[{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"preferred":true,"id":717302,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bryant, Wade L. Jr. wbbryant@usgs.gov","contributorId":1777,"corporation":false,"usgs":true,"family":"Bryant","given":"Wade L.","suffix":"Jr.","email":"wbbryant@usgs.gov","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":false,"id":717303,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70175392,"text":"70175392 - 2011 - Chapter 8: Occurrence of large and medium-sized mammals: Occurrence but not count models predict pronghorn distribution","interactions":[{"subject":{"id":70175392,"text":"70175392 - 2011 - Chapter 8: Occurrence of large and medium-sized mammals: Occurrence but not count models predict pronghorn distribution","indexId":"70175392","publicationYear":"2011","noYear":false,"chapter":"8","title":"Chapter 8: Occurrence of large and medium-sized mammals: Occurrence but not count models predict pronghorn distribution"},"predicate":"IS_PART_OF","object":{"id":70118768,"text":"70118768 - 2011 - Sagebrush ecosystem conservation and management: Ecoregional assessment tools and models for the Wyoming Basins","indexId":"70118768","publicationYear":"2011","noYear":false,"title":"Sagebrush ecosystem conservation and management: Ecoregional assessment tools and models for the Wyoming Basins"},"id":1}],"isPartOf":{"id":70118768,"text":"70118768 - 2011 - Sagebrush ecosystem conservation and management: Ecoregional assessment tools and models for the Wyoming Basins","indexId":"70118768","publicationYear":"2011","noYear":false,"title":"Sagebrush ecosystem conservation and management: Ecoregional assessment tools and models for the Wyoming Basins"},"lastModifiedDate":"2020-08-31T14:30:51.708526","indexId":"70175392","displayToPublicDate":"2011-01-01T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"8","title":"Chapter 8: Occurrence of large and medium-sized mammals: Occurrence but not count models predict pronghorn distribution","docAbstract":"<p>Management of medium to large-sized terrestrial mammals (Antilocapridae, Canidae, Cervidae, Leporidae, Mustelidae, Ochotonidae) in the western United States is multifaceted and complex. Species in this group generally are charismatic and provide economic opportunities, although others are considered a nuisance at one extreme or are listed as species of conservation concern at the other. Understanding the relative influence of land cover, habitat fragmentation, and human land use on their distribution during the breeding season is imperative to inform management decisions on land use and conservation planning for these species. We surveyed medium to large-sized sagebrush (<i>Artemisia</i> spp.)-associated mammal species in 2005 and 2006 on 141 random transects (mean length = 1.1 km) in the Wyoming Basins, an area undergoing rapid land cover transformation due to human actions including energy development. Overall, we observed 10 species but only obtained enough observations of pronghorn (<i>Antilocapra americana</i>) to develop spatially explicit distribution models. For pronghorn, occurrence related positively to proportion of sagebrush land cover within 0.27 km, mixed shrubland land cover within 3 km, riparian land cover within 5 km, Normalized Difference Vegetation Index (NDVI) within 0.27 km, road density within 5 km, and decay distance to power line corridors at 1 km, but negatively to salt-desert shrubland cover within 18 km and an interaction between sagebrush and NDVI within 0.27 km. We found excellent predictive capability of this model when evaluated with independent test data. The model provides a basis for assessing the effects of proposed development on pronghorn and can aid planning efforts to avoid or mitigate adverse effects on pronghorn.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Sagebrush ecosystem conservation and management: Ecoregional assessment tools and models for the Wyoming Basins","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Allen Press","publisherLocation":"Lawrence, Kansas","isbn":"978-0-615-55530-0","usgsCitation":"Leu, M., Hanser, S.E., Aldridge, C.L., Nielsen, S.E., Suring, L.H., and Knick, S.T., 2011, Chapter 8: Occurrence of large and medium-sized mammals: Occurrence but not count models predict pronghorn distribution, chap. 8 <i>of</i> Sagebrush ecosystem conservation and management: Ecoregional assessment tools and models for the Wyoming Basins, p. 315-336.","productDescription":"22 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Science Center","active":false,"usgs":true}],"preferred":true,"id":797694,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Aldridge, Cameron L. 0000-0003-3926-6941 aldridgec@usgs.gov","orcid":"https://orcid.org/0000-0003-3926-6941","contributorId":191773,"corporation":false,"usgs":true,"family":"Aldridge","given":"Cameron","email":"aldridgec@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":797695,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nielsen, Scott E.","contributorId":65190,"corporation":false,"usgs":true,"family":"Nielsen","given":"Scott","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":797696,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Suring, Lowell H.","contributorId":172229,"corporation":false,"usgs":false,"family":"Suring","given":"Lowell","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":797697,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Knick, Steven T. 0000-0003-4025-1704 steve_knick@usgs.gov","orcid":"https://orcid.org/0000-0003-4025-1704","contributorId":159,"corporation":false,"usgs":true,"family":"Knick","given":"Steven","email":"steve_knick@usgs.gov","middleInitial":"T.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":797698,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70032389,"text":"70032389 - 2011 - Episodic soil succession on basaltic lava fields in a cool, dry environment","interactions":[],"lastModifiedDate":"2016-03-08T08:43:06","indexId":"70032389","displayToPublicDate":"2011-01-01T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3420,"text":"Soil Science Society of America Journal","active":true,"publicationSubtype":{"id":10}},"title":"Episodic soil succession on basaltic lava fields in a cool, dry environment","docAbstract":"<p><span>Holocene- to late Pleistocene-aged lava flows at Craters of the Moon National Monument and Preserve provide an ideal setting to examine the early stages of soil formation under cool, dry conditions. Transects were used to characterize the amount and nature of soil cover on across basaltic lava flows ranging in age from 2.1 to 18.4 ka. Results indicate that on flows &lt;13 ka, very shallow organic soils (Folists in Soil Taxonomy) are the dominant soil type, providing an areal coverage of up to &sim;25%. On flows &ge;13.9 ka, deeper mineral soils including Entisols, Aridisols, and Mollisols become dominant and the areal extent increases to &ge;95% on flows older than 18.4 ka. These data suggest there are two distinct pedogenic pathways associated with lava flows of the region. The first pathway is illustrated by the younger flows, where Folists dominate. In the absence of a major source of loess, relatively little mineral material accumulates and soils provide only minor coverage of the lava flows. Our results indicate that this pathway of soil development has not changed appreciably over the past &sim;10 ka. The second pedogenic pathway is illustrated by the flows older than 13.9 ka. These flows have been subject to deposition of large quantities of loess during and after the last regional glaciation, resulting in almost complete coverage. Subsequent pedogenesis has given rise to Aridisols and Mollisols with calcic and cambic horizons and mollic epipedons. This research highlights the importance of regional climate change on the evolution of Craters of the Moon soilscapes.</span></p>","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Soil Science Society of America Journal","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.2136/sssaj2010.0341","issn":"03615995","usgsCitation":"Vaughan, K., McDaniel, P., and Phillips, W., 2011, Episodic soil succession on basaltic lava fields in a cool, dry environment: Soil Science Society of America Journal, v. 75, no. 4, p. 1462-1470, https://doi.org/10.2136/sssaj2010.0341.","productDescription":"9 p.","startPage":"1462","endPage":"1470","numberOfPages":"9","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[],"links":[{"id":241473,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"Craters of the Moon National Monument and Preserve, Eastern Snake River Plain","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -113,\n              42.5\n            ],\n            [\n              -113,\n              44\n            ],\n            [\n              -114,\n              44\n            ],\n            [\n              -114,\n              42.5\n            ],\n            [\n              -113,\n              42.5\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"75","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a0a14e4b0c8380cd521c0","contributors":{"authors":[{"text":"Vaughan, K.L.","contributorId":107512,"corporation":false,"usgs":true,"family":"Vaughan","given":"K.L.","email":"","affiliations":[],"preferred":false,"id":435920,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McDaniel, P.A.","contributorId":14129,"corporation":false,"usgs":true,"family":"McDaniel","given":"P.A.","email":"","affiliations":[],"preferred":false,"id":435918,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Phillips, W.M.","contributorId":49332,"corporation":false,"usgs":true,"family":"Phillips","given":"W.M.","email":"","affiliations":[],"preferred":false,"id":435919,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70046614,"text":"70046614 - 2011 - Solid sample locations for Fanno Creek, Oregon","interactions":[],"lastModifiedDate":"2013-06-17T08:45:39","indexId":"70046614","displayToPublicDate":"2011-01-01T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":6,"text":"USGS Unnumbered Series"},"title":"Solid sample locations for Fanno Creek, Oregon","docAbstract":"Fanno Creek is a tributary to the Tualatin River and flows though parts of the southwest Portland metropolitan area. The stream is heavily influenced by urban runoff and shows characteristic flashy streamflow and poor water quality commonly associated with urban streams. This data set represents the locations where solid samples were collected.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/70046614","usgsCitation":"Sobieszczyk, S., 2011, Solid sample locations for Fanno Creek, Oregon, Dataset, https://doi.org/10.3133/70046614.","productDescription":"Dataset","additionalOnlineFiles":"N","costCenters":[],"links":[{"id":273758,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":273757,"type":{"id":16,"text":"Metadata"},"url":"https://water.usgs.gov/GIS/metadata/usgswrd/XML/fannoCk_solid_samples.xml"}],"country":"United States","state":"Oregon","otherGeospatial":"Fanno Creek","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -129.351779,39.745375 ], [ -129.351779,55.265926 ], [ -109.448056,55.265926 ], [ -109.448056,39.745375 ], [ -129.351779,39.745375 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51c02ff7e4b0ee1529ed3d64","contributors":{"authors":[{"text":"Sobieszczyk, Steven 0000-0002-0834-8437 ssobie@usgs.gov","orcid":"https://orcid.org/0000-0002-0834-8437","contributorId":885,"corporation":false,"usgs":true,"family":"Sobieszczyk","given":"Steven","email":"ssobie@usgs.gov","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":479869,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70046615,"text":"70046615 - 2011 - Stream Centerline for Fanno Creek, Oregon","interactions":[],"lastModifiedDate":"2013-06-17T08:56:05","indexId":"70046615","displayToPublicDate":"2011-01-01T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":6,"text":"USGS Unnumbered Series"},"title":"Stream Centerline for Fanno Creek, Oregon","docAbstract":"Fanno Creek is a tributary to the Tualatin River and flows though parts of the southwest Portland metropolitan area. The stream is heavily influenced by urban runoff and shows characteristic flashy streamflow and poor water quality commonly associated with urban streams. This data set represents the stream centerline of the current active channel as derived from light detection and ranging (LiDAR) data and aerial photographic imagery.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/70046615","usgsCitation":"Sobieszczyk, S., 2011, Stream Centerline for Fanno Creek, Oregon, Dataset, https://doi.org/10.3133/70046615.","productDescription":"Dataset","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[],"links":[{"id":273760,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":273759,"type":{"id":16,"text":"Metadata"},"url":"https://water.usgs.gov/GIS/metadata/usgswrd/XML/fannoCk_stm_cntr_ln.xml"}],"country":"United States","state":"Oregon","otherGeospatial":"Fanno Creek","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -129.351779,39.745375 ], [ -129.351779,55.265926 ], [ -109.448056,55.265926 ], [ -109.448056,39.745375 ], [ -129.351779,39.745375 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51c02ff8e4b0ee1529ed3d6f","contributors":{"authors":[{"text":"Sobieszczyk, Steven 0000-0002-0834-8437 ssobie@usgs.gov","orcid":"https://orcid.org/0000-0002-0834-8437","contributorId":885,"corporation":false,"usgs":true,"family":"Sobieszczyk","given":"Steven","email":"ssobie@usgs.gov","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":479870,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70033914,"text":"70033914 - 2011 - Multi-scale temporal and spatial variation in genotypic composition of Cladophora-borne Escherichia coli populations in Lake Michigan","interactions":[],"lastModifiedDate":"2013-06-28T10:06:47","indexId":"70033914","displayToPublicDate":"2011-01-01T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3716,"text":"Water Research","onlineIssn":"1879-2448","printIssn":"0043-1354","active":true,"publicationSubtype":{"id":10}},"title":"Multi-scale temporal and spatial variation in genotypic composition of Cladophora-borne Escherichia coli populations in Lake Michigan","docAbstract":"High concentrations of Escherichia coli in mats of Cladophora in the Great Lakes have raised concern over the continued use of this bacterium as an indicator of microbial water quality. Determining the impacts of these environmentally abundant E. coli, however, necessitates a better understanding of their ecology. In this study, the population structure of 4285 Cladophora-borne E. coli isolates, obtained over multiple three day periods from Lake Michigan Cladophora mats in 2007-2009, was examined by using DNA fingerprint analyses. In contrast to previous studies that have been done using isolates from attached Cladophora obtained over large time scales and distances, the extensive sampling done here on free-floating mats over successive days at multiple sites provided a large dataset that allowed for a detailed examination of changes in population structure over a wide range of spatial and temporal scales. While Cladophora-borne E. coli populations were highly diverse and consisted of many unique isolates, multiple clonal groups were also present and accounted for approximately 33% of all isolates examined. Patterns in population structure were also evident. At the broadest scales, E. coli populations showed some temporal clustering when examined by year, but did not show good spatial distinction among sites. E. coli population structure also showed significant patterns at much finer temporal scales. Populations were distinct on an individual mat basis at a given site, and on individual days within a single mat. Results of these studies indicate that Cladophora-borne E. coli populations consist of a mixture of stable, and possibly naturalized, strains that persist during the life of the mat, and more unique, transient strains that can change over rapid time scales. It is clear that further study of microbial processes at fine spatial and temporal scales is needed, and that caution must be taken when interpolating short term microbial dynamics from results obtained from weekly or monthly samples.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Water Research","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.watres.2010.08.041","issn":"00431354","usgsCitation":"Badgley, B., Ferguson, J., Heuvel, A., Kleinheinz, G., McDermott, C., Sandrin, T., Kinzelman, J., Junion, E., Byappanahalli, M., Whitman, R., and Sadowsky, M., 2011, Multi-scale temporal and spatial variation in genotypic composition of Cladophora-borne Escherichia coli populations in Lake Michigan: Water Research, v. 45, no. 2, p. 721-731, https://doi.org/10.1016/j.watres.2010.08.041.","productDescription":"11 p.","startPage":"721","endPage":"731","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":214571,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.watres.2010.08.041"},{"id":242306,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Lake Michigan","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -87.91,41.61 ], [ -87.91,46.1 ], [ -84.74,46.1 ], [ -84.74,41.61 ], [ -87.91,41.61 ] ] ] } } ] }","volume":"45","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a5fc5e4b0c8380cd71111","contributors":{"authors":[{"text":"Badgley, B.D.","contributorId":82546,"corporation":false,"usgs":true,"family":"Badgley","given":"B.D.","email":"","affiliations":[],"preferred":false,"id":443153,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ferguson, J.","contributorId":31907,"corporation":false,"usgs":true,"family":"Ferguson","given":"J.","email":"","affiliations":[],"preferred":false,"id":443149,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Heuvel, A.V.","contributorId":9882,"corporation":false,"usgs":true,"family":"Heuvel","given":"A.V.","email":"","affiliations":[],"preferred":false,"id":443145,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kleinheinz, G.T.","contributorId":11021,"corporation":false,"usgs":true,"family":"Kleinheinz","given":"G.T.","affiliations":[],"preferred":false,"id":443146,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McDermott, C.M.","contributorId":59643,"corporation":false,"usgs":true,"family":"McDermott","given":"C.M.","email":"","affiliations":[],"preferred":false,"id":443151,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sandrin, T.R.","contributorId":97339,"corporation":false,"usgs":true,"family":"Sandrin","given":"T.R.","email":"","affiliations":[],"preferred":false,"id":443154,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kinzelman, J.","contributorId":43584,"corporation":false,"usgs":true,"family":"Kinzelman","given":"J.","affiliations":[],"preferred":false,"id":443150,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Junion, E.A.","contributorId":105138,"corporation":false,"usgs":true,"family":"Junion","given":"E.A.","email":"","affiliations":[],"preferred":false,"id":443155,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Byappanahalli, M.N.","contributorId":11384,"corporation":false,"usgs":true,"family":"Byappanahalli","given":"M.N.","email":"","affiliations":[],"preferred":false,"id":443147,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Whitman, R.L.","contributorId":69750,"corporation":false,"usgs":true,"family":"Whitman","given":"R.L.","email":"","affiliations":[],"preferred":false,"id":443152,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Sadowsky, M.J.","contributorId":19337,"corporation":false,"usgs":true,"family":"Sadowsky","given":"M.J.","email":"","affiliations":[],"preferred":false,"id":443148,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70034132,"text":"70034132 - 2011 - Changes in agricultural cropland areas between a water-surplus year and a water-deficit year impacting food security, determined using MODIS 250 m time-series data and spectral matching techniques, in the Krishna river basin (India)","interactions":[],"lastModifiedDate":"2018-02-22T16:16:51","indexId":"70034132","displayToPublicDate":"2011-01-01T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2068,"text":"International Journal of Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Changes in agricultural cropland areas between a water-surplus year and a water-deficit year impacting food security, determined using MODIS 250 m time-series data and spectral matching techniques, in the Krishna river basin (India)","docAbstract":"<p>The objective of this study was to investigate the changes in cropland areas as a result of water availability using Moderate Resolution Imaging Spectroradiometer (MODIS) 250 m time-series data and spectral matching techniques (SMTs). The study was conducted in the Krishna River basin in India, a very large river basin with an area of 265 752 km<sup>2</sup><span>&nbsp;</span>(26 575 200 ha), comparing a water-surplus year (2000–2001) and a water-deficit year (2002–2003). The MODIS 250&nbsp;m time-series data and SMTs were found ideal for agricultural cropland change detection over large areas and provided fuzzy classification accuracies of 61–100% for various land‐use classes and 61–81% for the rain-fed and irrigated classes. The most mixing change occurred between rain-fed cropland areas and informally irrigated (e.g. groundwater and small reservoir) areas. Hence separation of these two classes was the most difficult. The MODIS 250 m-derived irrigated cropland areas for the districts were highly correlated with the Indian Bureau of Statistics data, with<span>&nbsp;</span><i>R</i><span>&nbsp;</span><sup>2</sup>-values between 0.82 and 0.86.</p><p>The change in the net area irrigated was modest, with an irrigated area of 8&nbsp;669&nbsp;881 ha during the water-surplus year, as compared with 7&nbsp;718&nbsp;900 ha during the water-deficit year. However, this is quite misleading as most of the major changes occurred in cropping intensity, such as changing from higher intensity to lower intensity (e.g. from double crop to single crop). The changes in cropping intensity of the agricultural cropland areas that took place in the water-deficit year (2002–2003) when compared with the water-surplus year (2000–2001) in the Krishna basin were: (a) 1&nbsp;078&nbsp;564 ha changed from double crop to single crop, (b) 1&nbsp;461&nbsp;177 ha changed from continuous crop to single crop, (c) 704&nbsp;172 ha changed from irrigated single crop to fallow and (d) 1&nbsp;314&nbsp;522 ha changed from minor irrigation (e.g. tanks, small reservoirs) to rain-fed. These are highly significant changes that will have strong impact on food security. Such changes may be expected all over the world in a changing climate.</p>","language":"English","publisher":"Taylor & Francis","doi":"10.1080/01431161003749485","issn":"01431161","usgsCitation":"Gumma, M., Thenkabail, P.S., Muralikrishna, I., Velpuri, N.M., Gangadhararao, P., Dheeravath, V., Biradar, C., Nalan, S., and Gaur, A., 2011, Changes in agricultural cropland areas between a water-surplus year and a water-deficit year impacting food security, determined using MODIS 250 m time-series data and spectral matching techniques, in the Krishna river basin (India): International Journal of Remote Sensing, v. 32, no. 12, p. 3495-3520, https://doi.org/10.1080/01431161003749485.","productDescription":"26 p.","startPage":"3495","endPage":"3520","numberOfPages":"26","costCenters":[],"links":[{"id":216904,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1080/01431161003749485"},{"id":244805,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"32","issue":"12","noUsgsAuthors":false,"publicationDate":"2011-06-28","publicationStatus":"PW","scienceBaseUri":"5059f409e4b0c8380cd4bad7","contributors":{"authors":[{"text":"Gumma, Murali Krishna","contributorId":50426,"corporation":false,"usgs":true,"family":"Gumma","given":"Murali Krishna","affiliations":[],"preferred":false,"id":444246,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thenkabail, Prasad S. 0000-0002-2182-8822 pthenkabail@usgs.gov","orcid":"https://orcid.org/0000-0002-2182-8822","contributorId":570,"corporation":false,"usgs":true,"family":"Thenkabail","given":"Prasad","email":"pthenkabail@usgs.gov","middleInitial":"S.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":444252,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Muralikrishna, I.V.","contributorId":31234,"corporation":false,"usgs":true,"family":"Muralikrishna","given":"I.V.","email":"","affiliations":[],"preferred":false,"id":444248,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Velpuri, Naga Manohar 0000-0002-6370-1926 nvelpuri@usgs.gov","orcid":"https://orcid.org/0000-0002-6370-1926","contributorId":4441,"corporation":false,"usgs":true,"family":"Velpuri","given":"Naga","email":"nvelpuri@usgs.gov","middleInitial":"Manohar","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":444251,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gangadhararao, P.T.","contributorId":19406,"corporation":false,"usgs":true,"family":"Gangadhararao","given":"P.T.","email":"","affiliations":[],"preferred":false,"id":444247,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dheeravath, V.","contributorId":55234,"corporation":false,"usgs":true,"family":"Dheeravath","given":"V.","affiliations":[],"preferred":false,"id":444250,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Biradar, C.M.","contributorId":35563,"corporation":false,"usgs":true,"family":"Biradar","given":"C.M.","email":"","affiliations":[],"preferred":false,"id":444249,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Nalan, S.A.","contributorId":7110,"corporation":false,"usgs":true,"family":"Nalan","given":"S.A.","email":"","affiliations":[],"preferred":false,"id":444245,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Gaur, A.","contributorId":74603,"corporation":false,"usgs":true,"family":"Gaur","given":"A.","email":"","affiliations":[],"preferred":false,"id":444253,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70034017,"text":"70034017 - 2011 - Vibrational, X-ray absorption, and Mössbauer spectra of sulfate minerals from the weathered massive sulfide deposit at Iron Mountain, California","interactions":[],"lastModifiedDate":"2018-03-05T17:10:44","indexId":"70034017","displayToPublicDate":"2011-01-01T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1213,"text":"Chemical Geology","active":true,"publicationSubtype":{"id":10}},"title":"Vibrational, X-ray absorption, and Mössbauer spectra of sulfate minerals from the weathered massive sulfide deposit at Iron Mountain, California","docAbstract":"The Iron Mountain Mine Superfund site in California is a prime example of an acid mine drainage (AMD) system with well developed assemblages of sulfate minerals typical for such settings. Here we present and discuss the vibrational (infrared), X-ray absorption, and M??ssbauer spectra of a number of these phases, augmented by spectra of a few synthetic sulfates related to the AMD phases. The minerals and related phases studied in this work are (in order of increasing Fe2O3/FeO): szomolnokite, rozenite, siderotil, halotrichite, r??merite, voltaite, copiapite, monoclinic Fe2(SO4)3, Fe2(SO4)3??5H2O, kornelite, coquimbite, Fe(SO4)(OH), jarosite and rhomboclase. Fourier transform infrared spectra in the region 750-4000cm-1 are presented for all studied phases. Position of the FTIR bands is discussed in terms of the vibrations of sulfate ions, hydroxyl groups, and water molecules. Sulfur K-edge X-ray absorption near-edge structure (XANES) spectra were collected for selected samples. The feature of greatest interest is a series of weak pre-edge peaks whose position is determined by the number of bridging oxygen atoms between Fe3+ octahedra and sulfate tetrahedra. M??ssbauer spectra of selected samples were obtained at room temperature and 80K for ferric minerals jarosite and rhomboclase and mixed ferric-ferrous minerals r??merite, voltaite, and copiapite. Values of Fe2+/[Fe2++Fe3+] determined by M??ssbauer spectroscopy agree well with those determined by wet chemical analysis. The data presented here can be used as standards in spectroscopic work where spectra of well-characterized compounds are required to identify complex mixtures of minerals and related phases. ?? 2011 Elsevier B.V.","language":"English","publisher":"Elsevier","doi":"10.1016/j.chemgeo.2011.03.008","issn":"00092541","usgsCitation":"Majzlan, J., Alpers, C.N., Bender Koch, C., McCleskey, R.B., Myneni, S.B., and Neil, J.M., 2011, Vibrational, X-ray absorption, and Mössbauer spectra of sulfate minerals from the weathered massive sulfide deposit at Iron Mountain, California: Chemical Geology, v. 284, no. 3-4, p. 296-305, https://doi.org/10.1016/j.chemgeo.2011.03.008.","productDescription":"10 p.","startPage":"296","endPage":"305","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[],"links":[{"id":244508,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":216627,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.chemgeo.2011.03.008"}],"country":"United States","state":"California","otherGeospatial":"Iron Mountain","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -119.26208496093751,\n              37.431250501793585\n            ],\n            [\n              -119.26208496093751,\n              37.642509774448754\n            ],\n            [\n              -118.91876220703126,\n              37.642509774448754\n            ],\n            [\n              -118.91876220703126,\n              37.431250501793585\n            ],\n            [\n              -119.26208496093751,\n              37.431250501793585\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"284","issue":"3-4","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505bc256e4b08c986b32aa9d","contributors":{"authors":[{"text":"Majzlan, Juraj","contributorId":127677,"corporation":false,"usgs":false,"family":"Majzlan","given":"Juraj","email":"","affiliations":[{"id":7107,"text":"Univ. of Freiburg, Germany","active":true,"usgs":false}],"preferred":false,"id":443667,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Alpers, Charles N. 0000-0001-6945-7365 cnalpers@usgs.gov","orcid":"https://orcid.org/0000-0001-6945-7365","contributorId":411,"corporation":false,"usgs":true,"family":"Alpers","given":"Charles","email":"cnalpers@usgs.gov","middleInitial":"N.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":443670,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bender Koch, Christian","contributorId":127676,"corporation":false,"usgs":false,"family":"Bender Koch","given":"Christian","email":"","affiliations":[{"id":7106,"text":"Royal Vet. and Ag. Univ, Denmark","active":true,"usgs":false}],"preferred":false,"id":443668,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McCleskey, R. Blaine 0000-0002-2521-8052 rbmccles@usgs.gov","orcid":"https://orcid.org/0000-0002-2521-8052","contributorId":147399,"corporation":false,"usgs":true,"family":"McCleskey","given":"R.","email":"rbmccles@usgs.gov","middleInitial":"Blaine","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true}],"preferred":true,"id":443665,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Myneni, Satish B.C.","contributorId":127678,"corporation":false,"usgs":false,"family":"Myneni","given":"Satish","email":"","middleInitial":"B.C.","affiliations":[{"id":7108,"text":"Princeton Univ.","active":true,"usgs":false}],"preferred":false,"id":443669,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Neil, John M.","contributorId":13957,"corporation":false,"usgs":false,"family":"Neil","given":"John","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":443666,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70034313,"text":"70034313 - 2011 - Predicting breeding habitat for amphibians: A spatiotemporal analysis across Yellowstone National Park","interactions":[],"lastModifiedDate":"2021-04-22T17:01:03.465858","indexId":"70034313","displayToPublicDate":"2011-01-01T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Predicting breeding habitat for amphibians: A spatiotemporal analysis across Yellowstone National Park","docAbstract":"<p><span>The ability to predict amphibian breeding across landscapes is important for informing land management decisions and helping biologists better understand and remediate factors contributing to declines in amphibian populations. We built geospatial models of likely breeding habitats for each of four amphibian species that breed in Yellowstone National Park (YNP). We used field data collected in 2000–2002 from 497 sites among 16 basins and predictor variables from geospatial models produced from remotely sensed data (e.g., digital elevation model, complex topographic index, landform data, wetland probability, and vegetative cover). Except for 31 sites in one basin that were surveyed in both 2000 and 2002, all sites were surveyed once. We used polytomous regression to build statistical models for each species of amphibian from (1) field survey site data only, (2) field data combined with data from geospatial models, and (3) data from geospatial models only. Based on measures of receiver operating characteristic (ROC) scores, models of the second type best explained likely breeding habitat because they contained the most information (ROC values ranged from 0.70 to 0.88). However, models of the third type could be applied to the entire YNP landscape and produced maps that could be verified with reserve field data. Accuracy rates for models built for single years were highly variable, ranging from 0.30 to 0.78. Accuracy rates for models built with data combined from multiple years were higher and less variable, ranging from 0.60 to 0.80. Combining results from the geospatial multiyear models yielded maps of “core” breeding areas (areas with high probability values for all three years) surrounded by areas that scored high for only one or two years, providing an estimate of variability among years. Such information can highlight landscape options for amphibian conservation. For example, our models identify alternative areas that could be protected for each species, including 6828–10 764 ha for tiger salamanders, 971–3017 ha for western toads, 4732–16 696 ha for boreal chorus frogs, and 4940–19 690 ha for Columbia spotted frogs.</span></p>","language":"English","publisher":"Ecological Society of America","doi":"10.1890/10-1261.1","issn":"10510761","usgsCitation":"Bartelt, P.E., Gallant, A.L., Klaver, R.W., Wright, C., Patla, D.A., and Peterson, C.R., 2011, Predicting breeding habitat for amphibians: A spatiotemporal analysis across Yellowstone National Park: Ecological Applications, v. 21, no. 7, p. 2530-2547, https://doi.org/10.1890/10-1261.1.","productDescription":"18 p.","startPage":"2530","endPage":"2547","costCenters":[],"links":[{"id":475420,"rank":10000,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1890/10-1261.1","text":"Publisher Index Page"},{"id":244495,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":216614,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1890/10-1261.1"}],"country":"United States","state":"Wyoming","otherGeospatial":"Yellowstone National Park","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -111.0772705078125,\n              44.18614312298759\n            ],\n            [\n              -109.8907470703125,\n              44.18614312298759\n            ],\n            [\n              -109.8907470703125,\n              45.092913646051144\n            ],\n            [\n              -111.0772705078125,\n              45.092913646051144\n            ],\n            [\n              -111.0772705078125,\n              44.18614312298759\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"21","issue":"7","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a81aae4b0c8380cd7b670","contributors":{"authors":[{"text":"Bartelt, Paul E.","contributorId":18895,"corporation":false,"usgs":true,"family":"Bartelt","given":"Paul","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":445202,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gallant, Alisa L. 0000-0002-3029-6637 gallant@usgs.gov","orcid":"https://orcid.org/0000-0002-3029-6637","contributorId":2940,"corporation":false,"usgs":true,"family":"Gallant","given":"Alisa","email":"gallant@usgs.gov","middleInitial":"L.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":445200,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Klaver, Robert W. 0000-0002-3263-9701 bklaver@usgs.gov","orcid":"https://orcid.org/0000-0002-3263-9701","contributorId":3285,"corporation":false,"usgs":true,"family":"Klaver","given":"Robert","email":"bklaver@usgs.gov","middleInitial":"W.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":445204,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wright, C.K.","contributorId":25780,"corporation":false,"usgs":true,"family":"Wright","given":"C.K.","affiliations":[],"preferred":false,"id":445201,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Patla, Debra A.","contributorId":40059,"corporation":false,"usgs":true,"family":"Patla","given":"Debra","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":445203,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Peterson, Charles R.","contributorId":95738,"corporation":false,"usgs":true,"family":"Peterson","given":"Charles","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":445199,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
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