{"pageNumber":"563","pageRowStart":"14050","pageSize":"25","recordCount":46856,"records":[{"id":70112522,"text":"70112522 - 2013 - Changes in surfzone morphodynamics driven by multi-decadal contraction of a large ebb-tidal delta","interactions":[],"lastModifiedDate":"2020-06-05T13:55:39.88378","indexId":"70112522","displayToPublicDate":"2013-11-01T14:16:00","publicationYear":"2013","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":"Changes in surfzone morphodynamics driven by multi-decadal contraction of a large ebb-tidal delta","docAbstract":"

The impact of multi-decadal, large-scale deflation (76 million m3 of sediment loss) and contraction (~ 1 km) of a 150 km2 ebb-tidal delta on hydrodynamics and sediment transport at adjacent Ocean Beach in San Francisco, CA (USA), is examined using a coupled wave and circulation model. The model is forced with representative wave and tidal conditions using recent (2005) and historic (1956) ebb-tidal delta bathymetry data sets. Comparison of the simulations indicates that along north/south trending Ocean Beach the contraction and deflation of the ebb-tidal delta have resulted in significant differences in the flow and sediment dynamics. Between 1956 and 2005 the transverse bar (the shallow attachment point of the ebb-tidal delta to the shoreline) migrated northward ~ 1 km toward the inlet while a persistent alongshore flow and transport divergence point migrated south by ~ 500 m such that these features now overlap. A reduction in tidal prism and sediment supply over the last century has resulted in a net decrease in offshore tidal current-generated sediment transport at the mouth of San Francisco Bay, and a relative increase in onshore-directed wave-driven transport toward the inlet, accounting for the observed contraction of the ebb-tidal delta. Alongshore migration of the transverse bar and alongshore flow divergence have resulted in an increasing proportion of onshore migrating sediment from the ebb-tidal delta to be transported north along the beach in 2005 versus south in 1956. The northerly migrating sediment is then trapped by Pt. Lobos, a rocky headland at the northern extreme of the beach, consistent with the observed shoreline accretion in this area. Conversely, alongshore migration of the transverse bar and divergence point has decreased the sediment supply to southern Ocean Beach, consistent with the observed erosion of the shoreline in this area. This study illustrates the utility of applying a high-resolution coupled circulation-wave model for understanding coastal response to large-scale bathymetric changes over multi-decadal timescales, common to many coastal systems adjacent to urbanized estuaries and watersheds worldwide.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.margeo.2013.07.005","usgsCitation":"Hansen, J., Elias, E., and Barnard, P., 2013, Changes in surfzone morphodynamics driven by multi-decadal contraction of a large ebb-tidal delta: Marine Geology, v. 345, p. 221-234, https://doi.org/10.1016/j.margeo.2013.07.005.","productDescription":"14 p.","startPage":"221","endPage":"234","numberOfPages":"14","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":288647,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -123.2546,37.333 ], [ -123.2546,38.2598 ], [ -121.9279,38.2598 ], [ -121.9279,37.333 ], [ -123.2546,37.333 ] ] ] } } ] }","volume":"345","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53ae7652e4b0abf75cf2bf24","contributors":{"editors":[{"text":"Barnard, P.L.","contributorId":20527,"corporation":false,"usgs":true,"family":"Barnard","given":"P.L.","email":"","affiliations":[],"preferred":false,"id":509886,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Jaffe, B.E.","contributorId":112487,"corporation":false,"usgs":true,"family":"Jaffe","given":"B.E.","email":"","affiliations":[],"preferred":false,"id":509888,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Schoellhamer, D. H. 0000-0001-9488-7340","orcid":"https://orcid.org/0000-0001-9488-7340","contributorId":85624,"corporation":false,"usgs":true,"family":"Schoellhamer","given":"D. H.","affiliations":[],"preferred":false,"id":509887,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"Hansen, Jeff E.","contributorId":60339,"corporation":false,"usgs":true,"family":"Hansen","given":"Jeff E.","affiliations":[],"preferred":false,"id":494830,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Elias, Edwin","contributorId":50615,"corporation":false,"usgs":true,"family":"Elias","given":"Edwin","affiliations":[],"preferred":false,"id":494828,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barnard, Patrick L.","contributorId":54936,"corporation":false,"usgs":true,"family":"Barnard","given":"Patrick L.","affiliations":[],"preferred":false,"id":494829,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70059023,"text":"70059023 - 2013 - Atmospheric deposition and critical loads for nitrogen and metals in Arctic Alaska: Review and current status","interactions":[],"lastModifiedDate":"2016-10-20T14:57:40","indexId":"70059023","displayToPublicDate":"2013-11-01T14:09:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2950,"text":"Open Journal of Air Pollution","active":true,"publicationSubtype":{"id":10}},"title":"Atmospheric deposition and critical loads for nitrogen and metals in Arctic Alaska: Review and current status","docAbstract":"To protect important resources under their bureau’s purview, the United States National Park Service’s (NPS) Arctic Network (ARCN) has developed a series of “vital signs” that are to be periodically monitored. One of these vital signs focuses on wet and dry deposition of atmospheric chemicals and further, the establishment of critical load (CL) values (thresholds for ecological effects based on cumulative depositional loadings) for nitrogen (N), sulfur, and metals. As part of the ARCN terrestrial monitoring programs, samples of the feather moss Hylocomium splendens are being col- lected and analyzed as a cost-effective means to monitor atmospheric pollutant deposition in this region. Ultimately, moss data combined with refined CL values might be used to help guide future regulation of atmospheric contaminant sources potentially impacting Arctic Alaska. But first, additional long-term studies are needed to determine patterns of contaminant deposition as measured by moss biomonitors and to quantify ecosystem responses at particular loadings/ ranges of contaminants within Arctic Alaska. Herein we briefly summarize 1) current regulatory guidance related to CL values 2) derivation of CL models for N and metals, 3) use of mosses as biomonitors of atmospheric deposition and loadings, 4) preliminary analysis of vulnerabilities and risks associated with CL estimates for N, 5) preliminary analysis of existing data for characterization of CL values for N for interior Alaska and 6) implications for managers and future research needs.","language":"English","publisher":"Scientific Research","doi":"10.4236/ojap.2013.24010","usgsCitation":"Linder, G.L., Brumbaugh, W.G., Neitlich, P., and Little, E., 2013, Atmospheric deposition and critical loads for nitrogen and metals in Arctic Alaska: Review and current status: Open Journal of Air Pollution, v. 2, p. 76-99, https://doi.org/10.4236/ojap.2013.24010.","productDescription":"24 p.","startPage":"76","endPage":"99","ipdsId":"IP-045962","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":473454,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.4236/ojap.2013.24010","text":"Publisher Index Page"},{"id":281392,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":281390,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.4236/ojap.2013.24010"}],"country":"United States","state":"Alaska","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -167.15,66.71 ], [ -167.15,70.73 ], [ -147.05,70.73 ], [ -147.05,66.71 ], [ -167.15,66.71 ] ] ] } } ] }","volume":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd4e68e4b0b290850f2145","contributors":{"authors":[{"text":"Linder, Greg L. linder2@usgs.gov","contributorId":1766,"corporation":false,"usgs":true,"family":"Linder","given":"Greg","email":"linder2@usgs.gov","middleInitial":"L.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":false,"id":487428,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brumbaugh, William G. 0000-0003-0081-375X bbrumbaugh@usgs.gov","orcid":"https://orcid.org/0000-0003-0081-375X","contributorId":493,"corporation":false,"usgs":true,"family":"Brumbaugh","given":"William","email":"bbrumbaugh@usgs.gov","middleInitial":"G.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":487427,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Neitlich, Peter","contributorId":64562,"corporation":false,"usgs":true,"family":"Neitlich","given":"Peter","email":"","affiliations":[],"preferred":false,"id":487429,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Little, Edward","contributorId":90638,"corporation":false,"usgs":true,"family":"Little","given":"Edward","affiliations":[],"preferred":false,"id":487430,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70048765,"text":"fs20133071 - 2013 - Research on pathogens at Great Lakes beaches: sampling, influential factors, and potential sources","interactions":[],"lastModifiedDate":"2013-11-14T17:36:27","indexId":"fs20133071","displayToPublicDate":"2013-11-01T14:09:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-3071","title":"Research on pathogens at Great Lakes beaches: sampling, influential factors, and potential sources","docAbstract":"The overall mission of this work is to provide science-based information and methods that will allow beach managers to more accurately make beach closure and advisory decisions, understand the sources and physical processes affecting beach contaminants, and understand how science-based information can be used to mitigate and restore beaches and protect the public.\n\nThe U.S. Geological Survey (USGS), in collaboration with many Federal, State, and local agencies and universities, has conducted research on beach health issues in the Great Lakes Region for more than a decade. The work consists of four science elements that align with the USGS Beach Health Initiative Mission: real-time assessments of water quality; coastal processes; pathogens and source tracking; and data analysis, interpretation, and communication. The ongoing or completed research for the pathogens and source tracking topic is described in this fact sheet.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20133071","usgsCitation":"Water Resources Division, U.S. Geological Survey, 2013, Research on pathogens at Great Lakes beaches: sampling, influential factors, and potential sources: U.S. Geological Survey Fact Sheet 2013-3071, 4 p., https://doi.org/10.3133/fs20133071.","productDescription":"4 p.","numberOfPages":"4","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true}],"links":[{"id":278650,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20133071.gif"},{"id":278646,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2013/3071/pdf/fs2013-3071.pdf"},{"id":278645,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2013/3071/"}],"state":"Michigan;New York;Ohio;Wisconsin","otherGeospatial":"Great Lakes;Lake Erie;Lake Huron;Lake Michigan","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -88.18,41.34 ], [ -88.18,46.53 ], [ -78.73,46.53 ], [ -78.73,41.34 ], [ -88.18,41.34 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5274c67fe4b089748f071330","contributors":{"authors":[{"text":"Water Resources Division, U.S. Geological Survey","contributorId":128075,"corporation":true,"usgs":false,"organization":"Water Resources Division, U.S. Geological Survey","id":535605,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70048759,"text":"fs20133068 - 2013 - Tools for beach health data management, data processing, and predictive model implementation","interactions":[],"lastModifiedDate":"2013-11-14T17:33:35","indexId":"fs20133068","displayToPublicDate":"2013-11-01T13:59:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-3068","title":"Tools for beach health data management, data processing, and predictive model implementation","docAbstract":"This fact sheet describes utilities created for management of recreational waters to provide efficient data management, data aggregation, and predictive modeling as well as a prototype geographic information system (GIS)-based tool for data visualization and summary. All of these utilities were developed to assist beach managers in making decisions to protect public health. The Environmental Data Discovery and Transformation (EnDDaT) Web service identifies, compiles, and sorts environmental data from a variety of sources that help to define climatic, hydrologic, and hydrodynamic characteristics including multiple data sources within the U.S. Geological Survey and the National Oceanic and Atmospheric Administration. The Great Lakes Beach Health Database (GLBH-DB) and Web application was designed to provide a flexible input, export, and storage platform for beach water quality and sanitary survey monitoring data to compliment beach monitoring programs within the Great Lakes. A real-time predictive modeling strategy was implemented by combining the capabilities of EnDDaT and the GLBH-DB for timely, automated prediction of beach water quality. The GIS-based tool was developed to map beaches based on their physical and biological characteristics, which was shared with multiple partners to provide concepts and information for future Web-accessible beach data outlets.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20133068","usgsCitation":"Water Resources Division, U.S. Geological Survey, 2013, Tools for beach health data management, data processing, and predictive model implementation: U.S. Geological Survey Fact Sheet 2013-3068, 6 p., https://doi.org/10.3133/fs20133068.","productDescription":"6 p.","numberOfPages":"6","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true}],"links":[{"id":278643,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20133068.gif"},{"id":278641,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2013/3068/"},{"id":278642,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2013/3068/pdf/fs2013-3068.pdf"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5274c67fe4b089748f071333","contributors":{"authors":[{"text":"Water Resources Division, U.S. Geological Survey","contributorId":128075,"corporation":true,"usgs":false,"organization":"Water Resources Division, U.S. Geological Survey","id":535602,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70093195,"text":"70093195 - 2013 - Scientific results of the Second Gas Hydrate Drilling Expedition in the Ulleung Basin (UBGH2)","interactions":[],"lastModifiedDate":"2018-08-28T15:24:48","indexId":"70093195","displayToPublicDate":"2013-11-01T13:56:00","publicationYear":"2013","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":"Scientific results of the Second Gas Hydrate Drilling Expedition in the Ulleung Basin (UBGH2)","docAbstract":"As a part of Korean National Gas Hydrate Program, the Second Ulleung Basin Gas Hydrate Drilling Expedition (UBGH2) was conducted from 9 July to 30 September, 2010 in the Ulleung Basin, East Sea, offshore Korea using the D/V Fugro Synergy. The UBGH2 was performed to understand the distribution of gas hydrates as required for a resource assessment and to find potential candidate sites suitable for a future offshore production test, especially targeting gas hydrate-bearing sand bodies in the basin. The UBGH2 sites were distributed across most of the basin and were selected to target mainly sand-rich turbidite deposits. The 84-day long expedition consisted of two phases. The first phase included logging-while-drilling/measurements-while-drilling (LWD/MWD) operations at 13 sites. During the second phase, sediment cores were collected from 18 holes at 10 of the 13 LWD/MWD sites. Wireline logging (WL) and vertical seismic profile (VSP) data were also acquired after coring operations at two of these 10 sites. In addition, seafloor visual observation, methane sensing, as well as push-coring and sampling using a Remotely Operated Vehicle (ROV) were conducted during both phases of the expedition. Recovered gas hydrates occurred either as pore-filling medium associated with discrete turbidite sand layers, or as fracture-filling veins and nodules in muddy sediments. Gas analyses indicated that the methane within the sampled gas hydrates is primarily of biogenic origin.\n\nThis paper provides a summary of the operational and scientific results of the UBGH2 expedition as described in 24 papers that make up this special issue of the Journal of Marine and Petroleum Geology.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Marine and Petroleum Geology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.marpetgeo.2013.07.007","usgsCitation":"Ryu, B., Collett, T.S., Riedel, M., Kim, G., Chun, J., Bahk, J., Lee, J., Kim, J., and Yoo, D., 2013, Scientific results of the Second Gas Hydrate Drilling Expedition in the Ulleung Basin (UBGH2): Marine and Petroleum Geology, v. 47, p. 1-20, https://doi.org/10.1016/j.marpetgeo.2013.07.007.","productDescription":"20 p.","startPage":"1","endPage":"20","numberOfPages":"20","ipdsId":"IP-050115","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":282034,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":281994,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.marpetgeo.2013.07.007"}],"country":"Korea","otherGeospatial":"East Sea Of Korea;Ulleung Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 129.0,35.0 ], [ 129.0,38.0 ], [ 133.0,38.0 ], [ 133.0,35.0 ], [ 129.0,35.0 ] ] ] } } ] }","volume":"47","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd7187e4b0b29085107bde","contributors":{"authors":[{"text":"Ryu, Byong-Jae","contributorId":6375,"corporation":false,"usgs":true,"family":"Ryu","given":"Byong-Jae","email":"","affiliations":[],"preferred":false,"id":489949,"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":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":489948,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Riedel, Michael","contributorId":7518,"corporation":false,"usgs":true,"family":"Riedel","given":"Michael","email":"","affiliations":[],"preferred":false,"id":489950,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kim, Gil-Young","contributorId":45220,"corporation":false,"usgs":true,"family":"Kim","given":"Gil-Young","email":"","affiliations":[],"preferred":false,"id":489952,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chun, Jong-Hwa","contributorId":107611,"corporation":false,"usgs":true,"family":"Chun","given":"Jong-Hwa","affiliations":[],"preferred":false,"id":489956,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bahk, Jang-Jun","contributorId":12781,"corporation":false,"usgs":true,"family":"Bahk","given":"Jang-Jun","email":"","affiliations":[],"preferred":false,"id":489951,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lee, Joo Yong","contributorId":82222,"corporation":false,"usgs":true,"family":"Lee","given":"Joo Yong","affiliations":[],"preferred":false,"id":489953,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kim, Ji-Hoon","contributorId":105547,"corporation":false,"usgs":true,"family":"Kim","given":"Ji-Hoon","email":"","affiliations":[],"preferred":false,"id":489955,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Yoo, Dong-Geun","contributorId":99044,"corporation":false,"usgs":true,"family":"Yoo","given":"Dong-Geun","email":"","affiliations":[],"preferred":false,"id":489954,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70093193,"text":"70093193 - 2013 - Scale-dependent gas hydrate saturation estimates in sand reservoirs in the Ulleung Basin, East Sea of Korea","interactions":[],"lastModifiedDate":"2014-02-05T13:54:41","indexId":"70093193","displayToPublicDate":"2013-11-01T13:52:00","publicationYear":"2013","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":"Scale-dependent gas hydrate saturation estimates in sand reservoirs in the Ulleung Basin, East Sea of Korea","docAbstract":"Through the use of 2-D and 3-D seismic data, several gas hydrate prospects were identified in the Ulleung Basin, East Sea of Korea and thirteen drill sites were established and logging-while-drilling (LWD) data were acquired from each site in 2010. Sites UBGH2–6 and UBGH2–10 were selected to test a series of high amplitude seismic reflections, possibly from sand reservoirs. LWD logs from the UBGH2–6 well indicate that there are three significant sand reservoirs with varying thickness. Two upper sand reservoirs are water saturated and the lower thinly bedded sand reservoir contains gas hydrate with an average saturation of 13%, as estimated from the P-wave velocity. The well logs at the UBGH2–6 well clearly demonstrated the effect of scale-dependency on gas hydrate saturation estimates. Gas hydrate saturations estimated from the high resolution LWD acquired ring resistivity (vertical resolution of about 5–8 cm) reaches about 90% with an average saturation of 28%, whereas gas hydrate saturations estimated from the low resolution A40L resistivity (vertical resolution of about 120 cm) reaches about 25% with an average saturation of 11%. However, in the UBGH2–10 well, gas hydrate occupies a 5-m thick sand reservoir near 135 mbsf with a maximum saturation of about 60%. In the UBGH2–10 well, the average and a maximum saturation estimated from various well logging tools are comparable, because the bed thickness is larger than the vertical resolution of the various logging tools. High resolution wireline log data further document the role of scale-dependency on gas hydrate calculations.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Marine and Petroleum Geology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.marpetgeo.2012.09.004","usgsCitation":"Lee, M.W., and Collett, T.S., 2013, Scale-dependent gas hydrate saturation estimates in sand reservoirs in the Ulleung Basin, East Sea of Korea: Marine and Petroleum Geology, v. 47, p. 195-203, https://doi.org/10.1016/j.marpetgeo.2012.09.004.","productDescription":"9 p.","startPage":"195","endPage":"203","numberOfPages":"9","ipdsId":"IP-038671","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":473455,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.marpetgeo.2012.09.004","text":"Publisher Index Page"},{"id":281992,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.marpetgeo.2012.09.004"},{"id":282033,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Korea","otherGeospatial":"East Sea Of Korea;Ulleung Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 129.0,35.0 ], [ 129.0,38.0 ], [ 133.0,38.0 ], [ 133.0,35.0 ], [ 129.0,35.0 ] ] ] } } ] }","volume":"47","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd7178e4b0b29085107b2a","contributors":{"authors":[{"text":"Lee, Myung Woong","contributorId":15114,"corporation":false,"usgs":true,"family":"Lee","given":"Myung","email":"","middleInitial":"Woong","affiliations":[],"preferred":false,"id":489945,"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":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},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":489944,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70047732,"text":"70047732 - 2013 - Microbial source tracking as a tool for TMDL development, Little Blue River in Independence, Missouri","interactions":[],"lastModifiedDate":"2017-11-21T16:31:47","indexId":"70047732","displayToPublicDate":"2013-11-01T13:44:00","publicationYear":"2013","noYear":false,"publicationType":{"id":4,"text":"Book"},"publicationSubtype":{"id":12,"text":"Conference publication"},"title":"Microbial source tracking as a tool for TMDL development, Little Blue River in Independence, Missouri","docAbstract":"

The Little Blue River in Jackson County, Missouri has been listed by the Missouri Department of Natural Resources as impaired by bacteria for the protection of aquatic life and contact recreation from urban point and nonpoint sources. The Clean Water Act requires that a total maximum daily load (TMDL) for Escherichia coli (E. coli) be developed. Over a 5-year period, 108 base-flow, 87 stormflow, 48 fecal source, and 12 sewage influent samples were collected and analyzed for E. coli and Bacteroides general and host-associated microbial source tracking (MST) genetic markers. Less than half of the main-stem base-flow samples exceeded the E. coli state standard, whereas, all of the stormflow samples exceeded the standard during the recreation season (April through October). Both E. coli and MST markers were detected more frequently and at higher concentrations in stormflow samples. Only 14 percent of samples with E. coli detections greater than the Missouri state standard of 206 colonies per 100 milliliters had the human-associated Bacteroides marker as the only identified marker; therefore, Little Blue River TMDL development may require a broader scope beyond the municipal separate storm sewer system if bacteria sources are to be identified and addressed. Fecal samples showed a greater specificity with the human-associated marker than the dog- or ruminant-associated Bacteroides markers; however, false positives were at least one order of magnitude lower than true positives. MST data may be a useful tool for identifying probable sources of contamination and directing TMDL strategies.

","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the Water Environment Federation","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"WEFTEC: The Water Quality Event","conferenceLocation":"Chicago, IL","language":"English","publisher":"Water Environment Federation","publisherLocation":"Alexandria, VA","doi":"10.2175/193864713813726920","usgsCitation":"Christensen, E.D., Bushon, R.N., and Brady, A., 2013, Microbial source tracking as a tool for TMDL development, Little Blue River in Independence, Missouri, 4 p., https://doi.org/10.2175/193864713813726920.","productDescription":"4 p.","startPage":"7218","endPage":"7221","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-049632","costCenters":[],"links":[{"id":289439,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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Eric D. echriste@usgs.gov","contributorId":4230,"corporation":false,"usgs":true,"family":"Christensen","given":"Eric","email":"echriste@usgs.gov","middleInitial":"D.","affiliations":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true}],"preferred":true,"id":482845,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bushon, Rebecca N. rnbushon@usgs.gov","contributorId":2304,"corporation":false,"usgs":true,"family":"Bushon","given":"Rebecca","email":"rnbushon@usgs.gov","middleInitial":"N.","affiliations":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"preferred":true,"id":482844,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brady, Amie M. G.","contributorId":29774,"corporation":false,"usgs":true,"family":"Brady","given":"Amie M. G.","affiliations":[],"preferred":false,"id":482846,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70112504,"text":"70112504 - 2013 - The use of modeling and suspended sediment concentration measurements for quantifying net suspended sediment transport through a large tidally dominated inlet","interactions":[],"lastModifiedDate":"2020-06-05T14:52:04.442498","indexId":"70112504","displayToPublicDate":"2013-11-01T13:41:00","publicationYear":"2013","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":"The use of modeling and suspended sediment concentration measurements for quantifying net suspended sediment transport through a large tidally dominated inlet","docAbstract":"

Sediment exchange at large energetic inlets is often difficult to quantify due complex flows, massive amounts of water and sediment exchange, and environmental conditions limiting long-term data collection. In an effort to better quantify such exchange this study investigated the use of suspended sediment concentrations (SSC) measured at an offsite location as a surrogate for sediment exchange at the tidally dominated Golden Gate inlet in San Francisco, CA. A numerical model was calibrated and validated against water and suspended sediment flux measured during a spring–neap tide cycle across the Golden Gate. The model was then run for five months and net exchange was calculated on a tidal time-scale and compared to SSC measurements at the Alcatraz monitoring site located in Central San Francisco Bay ~ 5 km from the Golden Gate. Numerically modeled tide averaged flux across the Golden Gate compared well (r2 = 0.86, p-value < 0.05) with 25 h low-pass filtered (tide averaged) SSCs measured at Alcatraz over the five month simulation period (January through April 2008). This formed a basis for the development of a simple equation relating the advective flux at Alcatraz with suspended sediment flux across the Golden Gate. Utilization of the equation with all available Alcatraz SSC data resulted in an average export rate of 1.2 Mt/yr during water years 2004 through 2010. While the rate is comparable to estimated suspended sediment inflow rates from sources within the Bay over the same time period (McKee et al., 2013-this issue), there was little variation from year to year. Exports were computed to be greatest during the wettest water year analyzed but only marginally so.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.margeo.2013.06.001","usgsCitation":"Erikson, L., Wright, S., Elias, E., Hanes, D.M., Schoellhamer, D., and Largier, J., 2013, The use of modeling and suspended sediment concentration measurements for quantifying net suspended sediment transport through a large tidally dominated inlet: Marine Geology, v. 345, p. 96-112, https://doi.org/10.1016/j.margeo.2013.06.001.","productDescription":"17 p.","startPage":"96","endPage":"112","numberOfPages":"17","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":552,"text":"San Francisco Bay-Delta","active":false,"usgs":true}],"links":[{"id":288632,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.559719,37.681583 ], [ -122.559719,37.994051 ], [ -122.249249,37.994051 ], [ -122.249249,37.681583 ], [ -122.559719,37.681583 ] ] ] } } ] }","volume":"345","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53ae7871e4b0abf75cf2d559","contributors":{"editors":[{"text":"Barnard, Patrick L. 0000-0003-1414-6476 pbarnard@usgs.gov","orcid":"https://orcid.org/0000-0003-1414-6476","contributorId":147147,"corporation":false,"usgs":true,"family":"Barnard","given":"Patrick L.","email":"pbarnard@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":509868,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Jaffe, Bruce E. 0000-0002-8816-5920 bjaffe@usgs.gov","orcid":"https://orcid.org/0000-0002-8816-5920","contributorId":2049,"corporation":false,"usgs":true,"family":"Jaffe","given":"Bruce","email":"bjaffe@usgs.gov","middleInitial":"E.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":509870,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Schoellhamer, David H. 0000-0001-9488-7340 dschoell@usgs.gov","orcid":"https://orcid.org/0000-0001-9488-7340","contributorId":631,"corporation":false,"usgs":true,"family":"Schoellhamer","given":"David H.","email":"dschoell@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":509869,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"Erikson, Li H.","contributorId":10880,"corporation":false,"usgs":true,"family":"Erikson","given":"Li H.","affiliations":[],"preferred":false,"id":494790,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wright, Scott 0000-0002-0387-5713 sawright@usgs.gov","orcid":"https://orcid.org/0000-0002-0387-5713","contributorId":1536,"corporation":false,"usgs":true,"family":"Wright","given":"Scott","email":"sawright@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":494789,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Elias, Edwin","contributorId":50615,"corporation":false,"usgs":true,"family":"Elias","given":"Edwin","affiliations":[],"preferred":false,"id":494791,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hanes, Daniel M.","contributorId":96360,"corporation":false,"usgs":true,"family":"Hanes","given":"Daniel","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":494793,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schoellhamer, David H. 0000-0001-9488-7340 dschoell@usgs.gov","orcid":"https://orcid.org/0000-0001-9488-7340","contributorId":631,"corporation":false,"usgs":true,"family":"Schoellhamer","given":"David H.","email":"dschoell@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":494788,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Largier, John","contributorId":85257,"corporation":false,"usgs":true,"family":"Largier","given":"John","email":"","affiliations":[],"preferred":false,"id":494792,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70093197,"text":"70093197 - 2013 - Large-scale depositional characteristics of the Ulleung Basin and its impact on electrical resistivity and Archie-parameters for gas hydrate saturation estimates","interactions":[],"lastModifiedDate":"2018-08-28T15:25:18","indexId":"70093197","displayToPublicDate":"2013-11-01T13:37:00","publicationYear":"2013","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":"Large-scale depositional characteristics of the Ulleung Basin and its impact on electrical resistivity and Archie-parameters for gas hydrate saturation estimates","docAbstract":"Gas hydrate saturation estimates were obtained from an Archie-analysis of the Logging-While-Drilling (LWD) electrical resistivity logs under consideration of the regional geological framework of sediment deposition in the Ulleung Basin, East Sea, of Korea. Porosity was determined from the LWD bulk density log and core-derived values of grain density. In situ measurements of pore-fluid salinity as well as formation temperature define a background trend for pore-fluid resistivity at each drill site. The LWD data were used to define sets of empirical Archie-constants for different depth-intervals of the logged borehole at all sites drilled during the second Ulleung Basin Gas Hydrate Drilling Expedition (UBGH2). A clustering of data with distinctly different trend-lines is evident in the cross-plot of porosity and formation factor for all sites drilled during UBGH2. The reason for the clustering is related to the difference between hemipelagic sediments (mostly covering the top ∼100 mbsf) and mass-transport deposits (MTD) and/or the occurrence of biogenic opal. For sites located in the north-eastern portion of the Ulleung Basin a set of individual Archie-parameters for a shallow depth interval (hemipelagic) and a deeper MTD zone was achieved. The deeper zone shows typically higher resistivities for the same range of porosities seen in the upper zone, reflecting a shift in sediment properties. The presence of large amounts of biogenic opal (up to and often over 50% as defined by XRD data) was especially observed at Sites UBGH2-2_1 and UBGH2-2_2 (as well as UBGH1-9 from a previous drilling expedition in 2007). The boundary between these two zones can also easily be identified in gamma-ray logs, which also show unusually low readings in the opal-rich interval. Only by incorporating different Archie-parameters for the different zones a reasonable estimate of gas hydrate saturation was achieved that also matches results from other techniques such as pore-fluid freshening, velocity-based calculations, and pressure-core degassing experiments. Seismically, individual boundaries between zones were determined using a grid of regional 2D seismic data. Zoning from the Archie-analysis for sites in the south-western portion of the Ulleung Basin was also observed, but at these sites it is linked to individually stacked MTDs only and does not reflect a mineralogical occurrence of biogenic opal or hemipelagic sedimentation. The individual MTD events represent differently compacted material often associated with a strong decrease in porosity (and increase in density), warranting a separate set of empirical Archie-parameters.","language":"English","publisher":"Elsevier","doi":"10.1016/j.marpetgeo.2013.03.014","usgsCitation":"Riedel, M., Collett, T.S., Kim, H., Bahk, J., Kim, J., Ryu, B., and Kim, G., 2013, Large-scale depositional characteristics of the Ulleung Basin and its impact on electrical resistivity and Archie-parameters for gas hydrate saturation estimates: Marine and Petroleum Geology, v. 47, p. 222-235, https://doi.org/10.1016/j.marpetgeo.2013.03.014.","productDescription":"14 p.","startPage":"222","endPage":"235","numberOfPages":"14","ipdsId":"IP-040872","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":282028,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":281996,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.marpetgeo.2013.03.014"}],"country":"Korea","otherGeospatial":"East Sea Of Korea;Ulleung Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 129.0,35.0 ], [ 129.0,38.0 ], [ 133.0,38.0 ], [ 133.0,35.0 ], [ 129.0,35.0 ] ] ] } } ] }","volume":"47","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd641ce4b0b290850ff3e6","contributors":{"authors":[{"text":"Riedel, Michael","contributorId":7518,"corporation":false,"usgs":true,"family":"Riedel","given":"Michael","email":"","affiliations":[],"preferred":false,"id":489967,"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":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"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}],"preferred":true,"id":489966,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kim, H.-S.","contributorId":46874,"corporation":false,"usgs":true,"family":"Kim","given":"H.-S.","email":"","affiliations":[],"preferred":false,"id":489969,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bahk, J.-J.","contributorId":99891,"corporation":false,"usgs":true,"family":"Bahk","given":"J.-J.","affiliations":[],"preferred":false,"id":489972,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kim, J.-H.","contributorId":26395,"corporation":false,"usgs":true,"family":"Kim","given":"J.-H.","email":"","affiliations":[],"preferred":false,"id":489968,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ryu, B.-J.","contributorId":59348,"corporation":false,"usgs":true,"family":"Ryu","given":"B.-J.","email":"","affiliations":[],"preferred":false,"id":489970,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kim, G.-Y.","contributorId":77454,"corporation":false,"usgs":true,"family":"Kim","given":"G.-Y.","email":"","affiliations":[],"preferred":false,"id":489971,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70093196,"text":"70093196 - 2013 - Characterization of gas hydrate reservoirs by integration of core and log data in the Ulleung Basin, East Sea","interactions":[],"lastModifiedDate":"2018-08-28T15:25:34","indexId":"70093196","displayToPublicDate":"2013-11-01T12:46:00","publicationYear":"2013","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":"Characterization of gas hydrate reservoirs by integration of core and log data in the Ulleung Basin, East Sea","docAbstract":"Examinations of core and well-log data from the Second Ulleung Basin Gas Hydrate Drilling Expedition (UBGH2) drill sites suggest that Sites UBGH2-2_2 and UBGH2-6 have relatively good gas hydrate reservoir quality in terms of individual and total cumulative thicknesses of gas-hydrate-bearing sand (HYBS) beds. In both of the sites, core sediments are generally dominated by hemipelagic muds which are intercalated with turbidite sands. The turbidite sands are usually thin-to-medium bedded and mainly consist of well sorted coarse silt to fine sand. Anomalies in infrared core temperatures and porewater chlorinity data and pressure core measurements indicate that “gas hydrate occurrence zones” (GHOZ) are present about 68–155 mbsf at Site UBGH2-2_2 and 110–155 mbsf at Site UBGH2-6. In both the GHOZ, gas hydrates are preferentially associated with many of the turbidite sands as “pore-filling” type hydrates. The HYBS identified in the cores from Site UBGH2-6 are medium-to-thick bedded particularly in the lower part of the GHOZ and well coincident with significant high excursions in all of the resistivity, density, and velocity logs. Gas-hydrate saturations in the HYBS range from 12% to 79% with an average of 52% based on pore-water chlorinity. In contrast, the HYBS from Site UBGH2-2_2 are usually thin-bedded and show poor correlations with both of the resistivity and velocity logs owing to volume averaging effects of the logging tools on the thin HYBS beds. Gas-hydrate saturations in the HYBS range from 15% to 65% with an average of 37% based on pore-water chlorinity. In both of the sites, large fluctuations in biogenic opal contents have significant effects on the sediment physical properties, resulting in limited usage of gamma ray and density logs in discriminating sand reservoirs.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Marine and Petroleum Geology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.marpetgeo.2013.05.007","usgsCitation":"Bahk, J., Kim, G., Chun, J., Kim, J., Lee, J., Ryu, B., Lee, J., Son, B., and Collett, T.S., 2013, Characterization of gas hydrate reservoirs by integration of core and log data in the Ulleung Basin, East Sea: Marine and Petroleum Geology, v. 47, p. 30-42, https://doi.org/10.1016/j.marpetgeo.2013.05.007.","productDescription":"13 p.","startPage":"30","endPage":"42","numberOfPages":"13","ipdsId":"IP-049786","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":282021,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":281995,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.marpetgeo.2013.05.007"}],"country":"Korea","otherGeospatial":"East Sea Of Korea;Ulleung Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 129.0,35.0 ], [ 129.0,38.0 ], [ 133.0,38.0 ], [ 133.0,35.0 ], [ 129.0,35.0 ] ] ] } } ] }","volume":"47","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd50b6e4b0b290850f37f3","contributors":{"authors":[{"text":"Bahk, J.-J.","contributorId":99891,"corporation":false,"usgs":true,"family":"Bahk","given":"J.-J.","affiliations":[],"preferred":false,"id":489965,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kim, G.-Y.","contributorId":77454,"corporation":false,"usgs":true,"family":"Kim","given":"G.-Y.","email":"","affiliations":[],"preferred":false,"id":489962,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chun, J.-H.","contributorId":97421,"corporation":false,"usgs":true,"family":"Chun","given":"J.-H.","email":"","affiliations":[],"preferred":false,"id":489964,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kim, J.-H.","contributorId":26395,"corporation":false,"usgs":true,"family":"Kim","given":"J.-H.","email":"","affiliations":[],"preferred":false,"id":489959,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lee, J.Y.","contributorId":20061,"corporation":false,"usgs":true,"family":"Lee","given":"J.Y.","email":"","affiliations":[],"preferred":false,"id":489958,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ryu, B.-J.","contributorId":59348,"corporation":false,"usgs":true,"family":"Ryu","given":"B.-J.","email":"","affiliations":[],"preferred":false,"id":489960,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lee, J.-H.","contributorId":77047,"corporation":false,"usgs":true,"family":"Lee","given":"J.-H.","email":"","affiliations":[],"preferred":false,"id":489961,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Son, B.-K.","contributorId":95798,"corporation":false,"usgs":true,"family":"Son","given":"B.-K.","email":"","affiliations":[],"preferred":false,"id":489963,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"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":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"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}],"preferred":true,"id":489957,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70093194,"text":"70093194 - 2013 - Characteristics and interpretation of fracture-filled gas hydrate: an example from the Ulleung Basin, East Sea of Korea","interactions":[],"lastModifiedDate":"2018-08-28T15:25:50","indexId":"70093194","displayToPublicDate":"2013-11-01T12:36:00","publicationYear":"2013","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":"Characteristics and interpretation of fracture-filled gas hydrate: an example from the Ulleung Basin, East Sea of Korea","docAbstract":"Through the use of 2-D and 3-D seismic data, a total of thirteen sites were selected and drilled in the East Sea of Korea in 2010. A suite of logging-while-drilling (LWD) logs was acquired at each site. LWD logs from the UBGH2-3A well indicate significant gas hydrate in clay-bearing sediments including several zones with massive gas hydrate with a bulk density less than 1.0 g/m3 for depths between 5 and 103 m below the sea floor. The UBGH2-3A well was drilled on a seismically identified chimney structure with a mound feature at the sea floor. Average gas hydrate saturations estimated from the isotropic analysis of ring resistivity and P-wave velocity logs are 80 ± 13% and 47 ± 16%, respectively, whereas they are 46 ± 17% and 45 ± 16%, respectively from the anisotropic analysis. Modeling indicates that the upper part of chimney (between 5 and 45 m below sea floor [mbsf]) is characterized by gas hydrate filling near horizontal fractures (7° dip) and the lower part of chimney (between 45 and 103 mbsf) is characterized by gas hydrate filling high angle fractures on the basis of ring resistivity and P-wave velocity. The anisotropic analysis using P40H resistivity (phase shift resistivity at 32 mHz with 40 inch spacing) and the P-wave velocity yields a gas hydrate saturation of 46 ± 15% and 46 ± 15% respectively, similar to those estimated using ring resistivity and P-wave velocity, but with quite different fracture dip angles. Differences in vertical resolution, depth of investigation, and a finite fracture dimension relative to the tool separation appear to contribute to this discrepancy. Forward modeling of anisotropic resistivity and velocity are essential to identify gas hydrate in fractures and to estimate accurate gas hydrate amounts.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Marine and Petroleum Geology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.marpetgeo.2012.09.003","usgsCitation":"Lee, M.W., and Collett, T.S., 2013, Characteristics and interpretation of fracture-filled gas hydrate: an example from the Ulleung Basin, East Sea of Korea: Marine and Petroleum Geology, v. 47, p. 168-181, https://doi.org/10.1016/j.marpetgeo.2012.09.003.","productDescription":"14 p.","startPage":"168","endPage":"181","numberOfPages":"14","ipdsId":"IP-038690","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":281993,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.marpetgeo.2012.09.003"},{"id":282020,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Korea","otherGeospatial":"East Sea Of Korea;Ulleung Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 129.0,35.0 ], [ 129.0,38.0 ], [ 133.0,38.0 ], [ 133.0,35.0 ], [ 129.0,35.0 ] ] ] } } ] }","volume":"47","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd509ee4b0b290850f3727","contributors":{"authors":[{"text":"Lee, Myung Woong","contributorId":15114,"corporation":false,"usgs":true,"family":"Lee","given":"Myung","email":"","middleInitial":"Woong","affiliations":[],"preferred":false,"id":489947,"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":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":489946,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70039673,"text":"70039673 - 2013 - Measuring suspended sediment","interactions":[],"lastModifiedDate":"2022-12-13T17:01:08.367467","indexId":"70039673","displayToPublicDate":"2013-11-01T11:43:00","publicationYear":"2013","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"1.10","title":"Measuring suspended sediment","docAbstract":"

Suspended sediment in streams and rivers can be measured using traditional instruments and techniques and (or) surrogate technologies. The former, as described herein, consists primarily of both manually deployed isokinetic samplers and their deployment protocols developed by the Federal Interagency Sedimentation Project. They are used on all continents other than Antarctica. The reliability of the typically spatially rich but temporally sparse data produced by traditional means is supported by a broad base of scientific literature since 1940.

\n
\n

However, the suspended sediment surrogate technologies described herein – based on hydroacoustic, nephelometric, laser, and pressure difference principles – tend to produce temporally rich but in some cases spatially sparse datasets. The value of temporally rich data in the accuracy of continuous sediment-discharge records is hard to overstate, in part because such data can often overcome the shortcomings of poor spatial coverage. Coupled with calibration data produced by traditional means, surrogate technologies show considerable promise toward providing the fluvial sediment data needed to increase and bring more consistency to sediment-discharge measurements worldwide.

","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Comprehensive water quality and purification","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Elsevier","doi":"10.1016/B978-0-12-382182-9.00012-8","usgsCitation":"Gray, J.R., and Landers, M.N., 2013, Measuring suspended sediment, chap. 1.10 of Comprehensive water quality and purification, v. 1, p. 157-204, https://doi.org/10.1016/B978-0-12-382182-9.00012-8.","productDescription":"48 p.","startPage":"157","endPage":"204","numberOfPages":"48","ipdsId":"IP-038802","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":284311,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd667ce4b0b29085100c8e","contributors":{"authors":[{"text":"Gray, J. R.","contributorId":63372,"corporation":false,"usgs":true,"family":"Gray","given":"J.","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":466700,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Landers, M. N.","contributorId":63428,"corporation":false,"usgs":true,"family":"Landers","given":"M.","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":466701,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70099269,"text":"70099269 - 2013 - The North American Breeding Bird Survey 1966–2011: Summary analysis and species accounts","interactions":[],"lastModifiedDate":"2015-12-03T13:46:31","indexId":"70099269","displayToPublicDate":"2013-11-01T11:36:06","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2884,"text":"North American Fauna","active":true,"publicationSubtype":{"id":10}},"title":"The North American Breeding Bird Survey 1966–2011: Summary analysis and species accounts","docAbstract":"

The North American Breeding Bird Survey is a roadside, count-based survey conducted by volunteer observers. Begun in 1966, it now is a primary source of information on spatial and temporal patterns of population change for North American birds. We analyze population change for states, provinces, Bird Conservation Regions, and the entire survey within the contiguous United States and southern Canada for 426 species using a hierarchical log-linear model that controls for observer effects in counting. We also map relative abundance and population change for each species using a spatial smoothing of data at the scale of survey routes. We present results in accounts that describe major breeding habitats, migratory status, conservation status, and population trends for each species at several geographic scales. We also present composite results for groups of species categorized by habitats and migratory status. The survey varies greatly among species in percentage of species' range covered and precision of results, but consistent patterns of decline occur among eastern forest, grassland, and aridland obligate birds while generalist bird species are increasing.

","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"North American Fauna","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"U.S. Fish and Wildlife","doi":"10.3996/nafa.79.0001","usgsCitation":"Sauer, J., Link, W., Fallon, J.E., Pardieck, K.L., and Ziolkowski, D., 2013, The North American Breeding Bird Survey 1966–2011: Summary analysis and species accounts: North American Fauna, v. 79, p. 1-32, https://doi.org/10.3996/nafa.79.0001.","productDescription":"32 p.","startPage":"1","endPage":"32","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-052328","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":473461,"rank":2,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://digital.library.unt.edu/ark:/67531/metadc700932/","text":"External 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covariates","interactions":[],"lastModifiedDate":"2014-01-13T11:10:43","indexId":"70047680","displayToPublicDate":"2013-11-01T11:05:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"A hierarchical nest survival model integrating incomplete temporally varying covariates","docAbstract":"Nest success is a critical determinant of the dynamics of avian populations, and nest survival modeling has played a key role in advancing avian ecology and management. Beginning with the development of daily nest survival models, and proceeding through subsequent extensions, the capacity for modeling the effects of hypothesized factors on nest survival has expanded greatly. We extend nest survival models further by introducing an approach to deal with incompletely observed, temporally varying covariates using a hierarchical model. Hierarchical modeling offers a way to separate process and observational components of demographic models to obtain estimates of the parameters of primary interest, and to evaluate structural effects of ecological and management interest. We built a hierarchical model for daily nest survival to analyze nest data from reintroduced whooping cranes (Grus americana) in the Eastern Migratory Population. This reintroduction effort has been beset by poor reproduction, apparently due primarily to nest abandonment by breeding birds. We used the model to assess support for the hypothesis that nest abandonment is caused by harassment from biting insects. We obtained indices of blood-feeding insect populations based on the spatially interpolated counts of insects captured in carbon dioxide traps. However, insect trapping was not conducted daily, and so we had incomplete information on a temporally variable covariate of interest. We therefore supplemented our nest survival model with a parallel model for estimating the values of the missing insect covariates. We used Bayesian model selection to identify the best predictors of daily nest survival. Our results suggest that the black fly Simulium annulus may be negatively affecting nest survival of reintroduced whooping cranes, with decreasing nest survival as abundance of S. annulus increases. The modeling framework we have developed will be applied in the future to a larger data set to evaluate the biting-insect hypothesis and other hypotheses for nesting failure in this reintroduced population; resulting inferences will support ongoing efforts to manage this population via an adaptive management approach. Wider application of our approach offers promise for modeling the effects of other temporally varying, but imperfectly observed covariates on nest survival, including the possibility of modeling temporally varying covariates collected from incubating adults.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ecology and Evolution","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1002/ece3.822","usgsCitation":"Converse, S., Royle, J., Adler, P.H., Urbanek, R.P., and Barzan, J.A., 2013, A hierarchical nest survival model integrating incomplete temporally varying covariates: Ecology and Evolution, v. 3, no. 13, p. 4439-4447, https://doi.org/10.1002/ece3.822.","productDescription":"9 p.","startPage":"4439","endPage":"4447","numberOfPages":"9","ipdsId":"IP-050325","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":473462,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.822","text":"Publisher Index Page"},{"id":280859,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/ece3.822"},{"id":280860,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Necedah National Wildlife Refuge","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -90.188271,44.039059 ], [ -90.188271,44.098374 ], [ -90.087591,44.098374 ], [ -90.087591,44.039059 ], [ -90.188271,44.039059 ] ] ] } } ] }","volume":"3","issue":"13","noUsgsAuthors":false,"publicationDate":"2013-10-10","publicationStatus":"PW","scienceBaseUri":"53cd49efe4b0b290850ef78c","chorus":{"doi":"10.1002/ece3.822","url":"http://dx.doi.org/10.1002/ece3.822","publisher":"Wiley-Blackwell","authors":"Converse Sarah J., Royle J. Andrew, Adler Peter H., Urbanek Richard P., Barzen Jeb A.","journalName":"Ecology and Evolution","publicationDate":"10/10/2013","auditedOn":"4/1/2017","publiclyAccessibleDate":"10/10/2013"},"contributors":{"authors":[{"text":"Converse, Sarah J.","contributorId":85716,"corporation":false,"usgs":true,"family":"Converse","given":"Sarah J.","affiliations":[],"preferred":false,"id":482707,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Royle, J. Andrew 0000-0003-3135-2167","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":80808,"corporation":false,"usgs":true,"family":"Royle","given":"J. Andrew","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":482706,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Adler, Peter H.","contributorId":89797,"corporation":false,"usgs":true,"family":"Adler","given":"Peter","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":482708,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Urbanek, Richard P.","contributorId":38400,"corporation":false,"usgs":true,"family":"Urbanek","given":"Richard","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":482704,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Barzan, Jeb A.","contributorId":59340,"corporation":false,"usgs":true,"family":"Barzan","given":"Jeb","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":482705,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70055623,"text":"70055623 - 2013 - Simulated tsunami inundation for a range of Cascadia megathrust earthquake scenarios at Bandon, Oregon, USA","interactions":[],"lastModifiedDate":"2014-01-08T10:40:20","indexId":"70055623","displayToPublicDate":"2013-11-01T10:31:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1820,"text":"Geosphere","active":true,"publicationSubtype":{"id":10}},"title":"Simulated tsunami inundation for a range of Cascadia megathrust earthquake scenarios at Bandon, Oregon, USA","docAbstract":"Characterizations of tsunami hazards along the Cascadia subduction zone hinge on uncertainties in megathrust rupture models used for simulating tsunami inundation. To explore these uncertainties, we constructed 15 megathrust earthquake scenarios using rupture models that supply the initial conditions for tsunami simulations at Bandon, Oregon. Tsunami inundation varies with the amount and distribution of fault slip assigned to rupture models, including models where slip is partitioned to a splay fault in the accretionary wedge and models that vary the updip limit of slip on a buried fault. Constraints on fault slip come from onshore and offshore paleoseismological evidence. We rank each rupture model using a logic tree that evaluates a model’s consistency with geological and geophysical data. The scenarios provide inputs to a hydrodynamic model, SELFE, used to simulate tsunami generation, propagation, and inundation on unstructured grids with <5–15 m resolution in coastal areas. Tsunami simulations delineate the likelihood that Cascadia tsunamis will exceed mapped inundation lines. Maximum wave elevations at the shoreline varied from ∼4 m to 25 m for earthquakes with 9–44 m slip and Mw 8.7–9.2. Simulated tsunami inundation agrees with sparse deposits left by the A.D. 1700 and older tsunamis. Tsunami simulations for large (22–30 m slip) and medium (14–19 m slip) splay fault scenarios encompass 80%–95% of all inundation scenarios and provide reasonable guidelines for land-use planning and coastal development. The maximum tsunami inundation simulated for the greatest splay fault scenario (36–44 m slip) can help to guide development of local tsunami evacuation zones.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Geosphere","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Geological Society of America","doi":"10.1130/GES00899.1","usgsCitation":"Witter, R., Zhang, Y.J., Wang, K., Priest, G., Goldfinger, C., Stimely, L., English, J.T., and Ferro, P.A., 2013, Simulated tsunami inundation for a range of Cascadia megathrust earthquake scenarios at Bandon, Oregon, USA: Geosphere, v. 9, no. 6, p. 1783-1803, https://doi.org/10.1130/GES00899.1.","productDescription":"21 p.","startPage":"1783","endPage":"1803","numberOfPages":"21","ipdsId":"IP-052081","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":473463,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges00899.1","text":"Publisher Index Page"},{"id":280705,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":280704,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1130/GES00899.1"}],"country":"United States","state":"Oregon","city":"Bandon","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.5,42.0 ], [ -124.5,44.0 ], [ -124.0,44.0 ], [ -124.0,42.0 ], [ -124.5,42.0 ] ] ] } } ] }","volume":"9","issue":"6","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd72cfe4b0b290851088c5","contributors":{"authors":[{"text":"Witter, Robert C. 0000-0002-1721-254X rwitter@usgs.gov","orcid":"https://orcid.org/0000-0002-1721-254X","contributorId":4528,"corporation":false,"usgs":true,"family":"Witter","given":"Robert C.","email":"rwitter@usgs.gov","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":486155,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zhang, Yinglong J.","contributorId":100281,"corporation":false,"usgs":true,"family":"Zhang","given":"Yinglong","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":486161,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wang, Kelin","contributorId":15266,"corporation":false,"usgs":true,"family":"Wang","given":"Kelin","affiliations":[],"preferred":false,"id":486156,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Priest, George R.","contributorId":50950,"corporation":false,"usgs":true,"family":"Priest","given":"George R.","affiliations":[],"preferred":false,"id":486157,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Goldfinger, Chris","contributorId":59460,"corporation":false,"usgs":true,"family":"Goldfinger","given":"Chris","affiliations":[],"preferred":false,"id":486159,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stimely, Laura","contributorId":71092,"corporation":false,"usgs":true,"family":"Stimely","given":"Laura","email":"","affiliations":[],"preferred":false,"id":486160,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"English, John T.","contributorId":100282,"corporation":false,"usgs":true,"family":"English","given":"John","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":486162,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ferro, Paul A.","contributorId":58179,"corporation":false,"usgs":true,"family":"Ferro","given":"Paul","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":486158,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70094651,"text":"70094651 - 2013 - Woody debris volume depletion through decay: implications for biomass and carbon accounting","interactions":[],"lastModifiedDate":"2014-02-24T10:34:13","indexId":"70094651","displayToPublicDate":"2013-11-01T10:29:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1478,"text":"Ecosystems","active":true,"publicationSubtype":{"id":10}},"title":"Woody debris volume depletion through decay: implications for biomass and carbon accounting","docAbstract":"Woody debris decay rates have recently received much attention because of the need to quantify temporal changes in forest carbon stocks. Published decay rates, available for many species, are commonly used to characterize deadwood biomass and carbon depletion. However, decay rates are often derived from reductions in wood density through time, which when used to model biomass and carbon depletion are known to underestimate rate loss because they fail to account for volume reduction (changes in log shape) as decay progresses. We present a method for estimating changes in log volume through time and illustrate the method using a chronosequence approach. The method is based on the observation, confirmed herein, that decaying logs have a collapse ratio (cross-sectional height/width) that can serve as a surrogate for the volume remaining. Combining the resulting volume loss with concurrent changes in wood density from the same logs then allowed us to quantify biomass and carbon depletion for three study species. Results show that volume, density, and biomass follow distinct depletion curves during decomposition. Volume showed an initial lag period (log dimensions remained unchanged), even while wood density was being reduced. However, once volume depletion began, biomass loss (the product of density and volume depletion) occurred much more rapidly than density alone. At the temporal limit of our data, the proportion of the biomass remaining was roughly half that of the density remaining. Accounting for log volume depletion, as demonstrated in this study, provides a comprehensive characterization of deadwood decomposition, thereby improving biomass-loss and carbon-accounting models.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ecosystems","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","doi":"10.1007/s10021-013-9682-z","usgsCitation":"Fraver, S., Milo, A.M., Bradford, J.B., D’Amato, A.W., Kenefic, L., Palik, B.J., Woodall, C.W., and Brissette, J., 2013, Woody debris volume depletion through decay: implications for biomass and carbon accounting: Ecosystems, v. 16, no. 7, p. 1262-1272, https://doi.org/10.1007/s10021-013-9682-z.","productDescription":"11 p.","startPage":"1262","endPage":"1272","numberOfPages":"11","ipdsId":"IP-042518","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":282669,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":282639,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s10021-013-9682-z"}],"country":"United States","state":"Minnesota","otherGeospatial":"Laurentian Mixed Forest Province","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -95.81,45.41 ], [ -95.81,49.38 ], [ -89.49,49.38 ], [ -89.49,45.41 ], [ -95.81,45.41 ] ] ] } } ] }","volume":"16","issue":"7","noUsgsAuthors":false,"publicationDate":"2013-06-08","publicationStatus":"PW","scienceBaseUri":"53cd7dcce4b0b2908510f9b6","contributors":{"authors":[{"text":"Fraver, Shawn","contributorId":91379,"corporation":false,"usgs":false,"family":"Fraver","given":"Shawn","email":"","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":490749,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Milo, Amy M.","contributorId":83441,"corporation":false,"usgs":true,"family":"Milo","given":"Amy","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":490747,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bradford, John B. 0000-0001-9257-6303 jbradford@usgs.gov","orcid":"https://orcid.org/0000-0001-9257-6303","contributorId":611,"corporation":false,"usgs":true,"family":"Bradford","given":"John","email":"jbradford@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":490742,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"D’Amato, Anthony W.","contributorId":28140,"corporation":false,"usgs":false,"family":"D’Amato","given":"Anthony","email":"","middleInitial":"W.","affiliations":[{"id":13478,"text":"Department of Forest Resources, University of Minnesota, St. Paul, Minnesota (Correspondence to: russellm@umn.edu)","active":true,"usgs":false},{"id":6735,"text":"University of Vermont, Rubenstein School of Environment and Natural Resources","active":true,"usgs":false}],"preferred":false,"id":490743,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kenefic, Laura","contributorId":86685,"corporation":false,"usgs":true,"family":"Kenefic","given":"Laura","affiliations":[],"preferred":false,"id":490748,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Palik, Brian J.","contributorId":78619,"corporation":false,"usgs":true,"family":"Palik","given":"Brian","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":490746,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Woodall, Christopher W.","contributorId":53696,"corporation":false,"usgs":false,"family":"Woodall","given":"Christopher","email":"","middleInitial":"W.","affiliations":[{"id":7264,"text":"USDA Forest Service, Northern Research Station, Beltsville, MD 20705","active":true,"usgs":false}],"preferred":false,"id":490745,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Brissette, John","contributorId":50077,"corporation":false,"usgs":true,"family":"Brissette","given":"John","email":"","affiliations":[],"preferred":false,"id":490744,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70132444,"text":"70132444 - 2013 - Spatial contexts for temporal variability in alpine vegetation under ongoing climate change","interactions":[],"lastModifiedDate":"2020-12-31T16:33:48.929098","indexId":"70132444","displayToPublicDate":"2013-11-01T10:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3086,"text":"Plant Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Spatial contexts for temporal variability in alpine vegetation under ongoing climate change","docAbstract":"

A framework to monitor mountain summit vegetation (The Global Observation Research Initiative in Alpine Environments, GLORIA) was initiated in 1997. GLORIA results should be taken within a regional context of the spatial variability of alpine tundra. Changes observed at GLORIA sites in Glacier National Park, Montana, USA are quantified within the context of the range of variability observed in alpine tundra across much of western North America. Dissimilarity is calculated and used in nonmetric multidimensional scaling for repeated measures of vascular species cover at 14 GLORIA sites with 525 nearby sites and with 436 sites in western North America. The lengths of the trajectories of the GLORIA sites in ordination space are compared to the dimensions of the space created by the larger datasets. The absolute amount of change on the GLORIA summits over 5 years is high, but the degree of change is small relative to the geographical context. The GLORIA sites are on the margin of the ordination volumes with the large datasets. The GLORIA summit vegetation appears to be specialized, arguing for the intrinsic value of early observed change in limited niche space.

","language":"English","publisher":"Kluwer Academic Publishers","publisherLocation":"Dordrecht","doi":"10.1007/s11258-013-0253-3","usgsCitation":"George P. Malanson, and Fagre, D.B., 2013, Spatial contexts for temporal variability in alpine vegetation under ongoing climate change: Plant Ecology, v. 214, no. 11, p. 1309-1319, https://doi.org/10.1007/s11258-013-0253-3.","productDescription":"11 p.","startPage":"1309","endPage":"1319","numberOfPages":"11","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-041204","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":296041,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","otherGeospatial":"Glacier National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.488525390625,\n 48.16974908365419\n ],\n [\n -113.02734374999999,\n 48.16974908365419\n ],\n [\n -113.02734374999999,\n 49.009050809382046\n ],\n [\n -114.488525390625,\n 49.009050809382046\n ],\n [\n -114.488525390625,\n 48.16974908365419\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"214","issue":"11","noUsgsAuthors":false,"publicationDate":"2013-09-26","publicationStatus":"PW","scienceBaseUri":"5465d639e4b04d4b7dbd6686","contributors":{"authors":[{"text":"George P. Malanson","contributorId":127023,"corporation":false,"usgs":false,"family":"George P. Malanson","affiliations":[{"id":6768,"text":"University of Iowa","active":true,"usgs":false}],"preferred":false,"id":522895,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fagre, Daniel B. 0000-0001-8552-9461 dan_fagre@usgs.gov","orcid":"https://orcid.org/0000-0001-8552-9461","contributorId":2036,"corporation":false,"usgs":true,"family":"Fagre","given":"Daniel","email":"dan_fagre@usgs.gov","middleInitial":"B.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":522894,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70106161,"text":"70106161 - 2013 - A sediment budget for the southern reach in San Francisco Bay, CA: Implications for habitat restoration","interactions":[],"lastModifiedDate":"2017-10-30T12:17:17","indexId":"70106161","displayToPublicDate":"2013-11-01T09:21:00","publicationYear":"2013","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":"A sediment budget for the southern reach in San Francisco Bay, CA: Implications for habitat restoration","docAbstract":"The South Bay Salt Pond Restoration Project is overseeing the restoration of about 6000 ha of former commercial salt-evaporation ponds to tidal marsh and managed wetlands in the southern reach of San Francisco Bay (SFB). As a result of regional groundwater overdrafts prior to the 1970s, parts of the project area have subsided below sea-level and will require between 29 and 45 million m3 of sediment to raise the surface of the subsided areas to elevations appropriate for tidal marsh colonization and development. Therefore, a sufficient sediment supply to the far south SFB subembayment is a critical variable for achieving restoration goals. Although both major tributaries to far south SFB have been seasonally gaged for sediment since 2004, the sediment flux at the Dumbarton Narrows, the bayward boundary of far south SFB, has not been quantified until recently. Using daily suspended-sediment flux data from the gages on Guadalupe River and Coyote Creek, combined with continuous suspended-sediment flux data at Dumbarton Narrows, we computed a sediment budget for far south SFB during Water Years 2009–2011. A Monte Carlo approach was used to quantify the uncertainty of the flux estimates. The sediment flux past Dumbarton Narrows from the north dominates the input to the subembayment. However, environmental conditions in the spring can dramatically influence the direction of springtime flux, which appears to be a dominant influence on the net annual flux. It is estimated that up to several millennia may be required for natural tributary sediments to fill the accommodation space of the subsided former salt ponds, whereas supply from the rest of the bay could fill the space in several centuries. Uncertainty in the measurement of sediment flux is large, in part because small suspended-sediment concentration differences between flood and ebb tides can lead to large differences in total mass exchange. Using Monte Carlo simulations to estimate the random error associated with this uncertainty provides a more statistically rigorous method of quantifying this uncertainty than the more typical “sum of errors” approach. The results of this study reinforce the need for measurement of estuarine sediment fluxes over multiple years (multiple hydrologic conditions) to adequately detail the variability in flux. Additionally, the timing of breaching events for the restoration project could be tied to annual hydrologic conditions to capitalize on increased regional sediment supply.","language":"English","publisher":"Elsevier","doi":"10.1016/j.margeo.2013.05.007","usgsCitation":"Shellenbarger, G., Wright, S., and Schoellhamer, D., 2013, A sediment budget for the southern reach in San Francisco Bay, CA: Implications for habitat restoration: Marine Geology, v. 345, p. 281-293, https://doi.org/10.1016/j.margeo.2013.05.007.","productDescription":"13 p.","startPage":"281","endPage":"293","numberOfPages":"13","ipdsId":"IP-006338","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":552,"text":"San Francisco Bay-Delta","active":false,"usgs":true}],"links":[{"id":287278,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.75,37.2509 ], [ -122.75,38.3523 ], [ -121.6589,38.3523 ], [ -121.6589,37.2509 ], [ -122.75,37.2509 ] ] ] } } ] }","volume":"345","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"537b27e6e4b0929ba496ab48","contributors":{"authors":[{"text":"Shellenbarger, Gregory gshellen@usgs.gov","contributorId":1133,"corporation":false,"usgs":true,"family":"Shellenbarger","given":"Gregory","email":"gshellen@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":493821,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wright, Scott 0000-0002-0387-5713 sawright@usgs.gov","orcid":"https://orcid.org/0000-0002-0387-5713","contributorId":1536,"corporation":false,"usgs":true,"family":"Wright","given":"Scott","email":"sawright@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":493822,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schoellhamer, David H. 0000-0001-9488-7340 dschoell@usgs.gov","orcid":"https://orcid.org/0000-0001-9488-7340","contributorId":631,"corporation":false,"usgs":true,"family":"Schoellhamer","given":"David H.","email":"dschoell@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":493820,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70048671,"text":"70048671 - 2013 - High-resolution global maps of 21st-century forest cover change","interactions":[],"lastModifiedDate":"2017-05-16T11:19:01","indexId":"70048671","displayToPublicDate":"2013-11-01T08:43:35","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3338,"text":"Science","active":true,"publicationSubtype":{"id":10}},"title":"High-resolution global maps of 21st-century forest cover change","docAbstract":"Quantification of global forest change has been lacking despite the recognized importance of forest ecosystem services. In this study, Earth observation satellite data were used to map global forest loss (2.3 million square kilometers) and gain (0.8 million square kilometers) from 2000 to 2012 at a spatial resolution of 30 meters. The tropics were the only climate domain to exhibit a trend, with forest loss increasing by 2101 square kilometers per year. Brazil’s well-documented reduction in deforestation was offset by increasing forest loss in Indonesia, Malaysia, Paraguay, Bolivia, Zambia, Angola, and elsewhere. Intensive forestry practiced within subtropical forests resulted in the highest rates of forest change globally. Boreal forest loss due largely to fire and forestry was second to that in the tropics in absolute and proportional terms. These results depict a globally consistent and locally relevant record of forest change.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Science","largerWorkSubtype":{"id":10,"text":"Journal Article"},"doi":"10.1126/science.1244693","usgsCitation":"Hansen, M., Potapov, P., Moore, R., Hancher, M., Turubanova, S., Tyukavina, A., Thau, D., Stehman, S., Goetz, S., Loveland, T., Kommareddy, A., Egorov, A., Chini, L., Justice, C., and Townshend, J., 2013, High-resolution global maps of 21st-century forest cover change: Science, v. 342, no. 6160, p. 850-853, https://doi.org/10.1126/science.1244693.","productDescription":"4 p.","startPage":"850","endPage":"853","ipdsId":"IP-052106","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":279094,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":279093,"type":{"id":10,"text":"Digital Object 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R.","contributorId":50184,"corporation":false,"usgs":true,"family":"Moore","given":"R.","affiliations":[],"preferred":false,"id":485372,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hancher, M.","contributorId":104391,"corporation":false,"usgs":true,"family":"Hancher","given":"M.","affiliations":[],"preferred":false,"id":485378,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Turubanova, S.A.","contributorId":108388,"corporation":false,"usgs":false,"family":"Turubanova","given":"S.A.","email":"","affiliations":[{"id":33433,"text":"University of Maryland, College Park","active":true,"usgs":false}],"preferred":false,"id":485381,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Tyukavina, A.","contributorId":19872,"corporation":false,"usgs":false,"family":"Tyukavina","given":"A.","email":"","affiliations":[{"id":33433,"text":"University of Maryland, College Park","active":true,"usgs":false}],"preferred":false,"id":485369,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Thau, D.","contributorId":50813,"corporation":false,"usgs":true,"family":"Thau","given":"D.","affiliations":[],"preferred":false,"id":485373,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Stehman, S.V.","contributorId":91974,"corporation":false,"usgs":false,"family":"Stehman","given":"S.V.","email":"","affiliations":[{"id":27852,"text":"State University of New York, Syracuse","active":true,"usgs":false}],"preferred":false,"id":485377,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Goetz, S.J.","contributorId":55186,"corporation":false,"usgs":false,"family":"Goetz","given":"S.J.","email":"","affiliations":[{"id":25456,"text":"Woods Hole Research Center, Falmouth, MA, United States","active":true,"usgs":false}],"preferred":false,"id":485374,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Loveland, Thomas R. 0000-0003-3114-6646","orcid":"https://orcid.org/0000-0003-3114-6646","contributorId":106125,"corporation":false,"usgs":true,"family":"Loveland","given":"Thomas R.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":false,"id":485380,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Kommareddy, A.","contributorId":105638,"corporation":false,"usgs":false,"family":"Kommareddy","given":"A.","email":"","affiliations":[{"id":26958,"text":"South Dakota State University, Brookings, SD","active":true,"usgs":false}],"preferred":false,"id":485379,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Egorov, Alexey","contributorId":81719,"corporation":false,"usgs":false,"family":"Egorov","given":"Alexey","email":"","affiliations":[{"id":5089,"text":"South Dakota State University","active":true,"usgs":false}],"preferred":false,"id":485376,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Chini, L.","contributorId":28894,"corporation":false,"usgs":true,"family":"Chini","given":"L.","affiliations":[],"preferred":false,"id":485370,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Justice, C.O.","contributorId":36450,"corporation":false,"usgs":true,"family":"Justice","given":"C.O.","email":"","affiliations":[],"preferred":false,"id":485371,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Townshend, J.R.G.","contributorId":15321,"corporation":false,"usgs":true,"family":"Townshend","given":"J.R.G.","email":"","affiliations":[],"preferred":false,"id":485367,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}} ,{"id":70057370,"text":"70057370 - 2013 - Comparing bacterial community composition between healthy and white plague-like disease states in Orbicella annularis using PhyloChip™ G3 microarrays","interactions":[],"lastModifiedDate":"2016-03-30T11:50:02","indexId":"70057370","displayToPublicDate":"2013-11-01T08:39:22","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Comparing bacterial community composition between healthy and white plague-like disease states in Orbicella annularis using PhyloChip™ G3 microarrays","docAbstract":"

Coral disease is a global problem. Diseases are typically named or described based on macroscopic changes, but broad signs of coral distress such as tissue loss or discoloration are unlikely to be specific to a particular pathogen. For example, there appear to be multiple diseases that manifest the rapid tissue loss that characterizes ‘white plague.’ PhyloChip™ G3 microarrays were used to compare the bacterial community composition of both healthy and white plague-like diseased corals. Samples of lobed star coral (Orbicella annularis, formerly of the genus Montastraea [1]) were collected from two geographically distinct areas, Dry Tortugas National Park and Virgin Islands National Park, to determine if there were biogeographic differences between the diseases. In fact, all diseased samples clustered together, however there was no consistent link to Aurantimonas coralicida, which has been described as the causative agent of white plague type II. The microarrays revealed a large amount of bacterial heterogeneity within the healthy corals and less diversity in the diseased corals. Gram-positive bacterial groups (Actinobacteria, Firmicutes) comprised a greater proportion of the operational taxonomic units (OTUs) unique to healthy samples. Diseased samples were enriched in OTUs from the families Corynebacteriaceae, Lachnospiraceae, Rhodobacteraceae, and Streptococcaceae. Much previous coral disease work has used clone libraries, which seem to be methodologically biased toward recovery of Gram-negative bacterial sequences and may therefore have missed the importance of Gram-positive groups. The PhyloChip™ data presented here provide a broader characterization of the bacterial community changes that occur within Orbicella annularis during the shift from a healthy to diseased state.

","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0079801","usgsCitation":"Kellogg, C.A., Piceno, Y., Tom, L.M., DeSantis, T.Z., Gray, M.A., Zawada, D., and Andersen, G.L., 2013, Comparing bacterial community composition between healthy and white plague-like disease states in Orbicella annularis using PhyloChip™ G3 microarrays: PLoS ONE, v. 8, no. 11, e79801; 10 p., https://doi.org/10.1371/journal.pone.0079801.","productDescription":"e79801; 10 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-050897","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":473464,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0079801","text":"Publisher Index Page"},{"id":279514,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Dry Tortugas National Park, St. John, Virgin Island","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -82.93,18.3 ], [ -82.93,24.64 ], [ -64.66,24.64 ], [ -64.66,18.3 ], [ -82.93,18.3 ] ] ] } } ] }","volume":"8","issue":"11","noUsgsAuthors":false,"publicationDate":"2013-11-20","publicationStatus":"PW","scienceBaseUri":"52908b00e4b0bbdcf23f08d9","contributors":{"authors":[{"text":"Kellogg, Christina A. 0000-0002-6492-9455 ckellogg@usgs.gov","orcid":"https://orcid.org/0000-0002-6492-9455","contributorId":391,"corporation":false,"usgs":true,"family":"Kellogg","given":"Christina","email":"ckellogg@usgs.gov","middleInitial":"A.","affiliations":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":486642,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Piceno, Yvette M.","contributorId":66977,"corporation":false,"usgs":true,"family":"Piceno","given":"Yvette M.","affiliations":[],"preferred":false,"id":486645,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tom, Lauren M.","contributorId":92938,"corporation":false,"usgs":true,"family":"Tom","given":"Lauren","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":486647,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"DeSantis, Todd Z.","contributorId":101158,"corporation":false,"usgs":true,"family":"DeSantis","given":"Todd","email":"","middleInitial":"Z.","affiliations":[],"preferred":false,"id":486648,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gray, Michael A. 0000-0002-3856-5037 mgray@usgs.gov","orcid":"https://orcid.org/0000-0002-3856-5037","contributorId":3532,"corporation":false,"usgs":true,"family":"Gray","given":"Michael","email":"mgray@usgs.gov","middleInitial":"A.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":486644,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Zawada, David G. 0000-0003-4547-4878 dzawada@usgs.gov","orcid":"https://orcid.org/0000-0003-4547-4878","contributorId":1898,"corporation":false,"usgs":true,"family":"Zawada","given":"David G.","email":"dzawada@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":486643,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Andersen, Gary L.","contributorId":68610,"corporation":false,"usgs":true,"family":"Andersen","given":"Gary","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":486646,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70042648,"text":"70042648 - 2013 - Estimating animal resource selection from telemetry data using point process models","interactions":[],"lastModifiedDate":"2013-11-07T14:21:56","indexId":"70042648","displayToPublicDate":"2013-11-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2158,"text":"Journal of Animal Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Estimating animal resource selection from telemetry data using point process models","docAbstract":"Analyses of animal resource selection functions (RSF) using data collected from relocations of individuals via remote telemetry devices have become commonplace. Increasing technological advances, however, have produced statistical challenges in analysing such highly autocorrelated data. Weighted distribution methods have been proposed for analysing RSFs with telemetry data. However, they can be computationally challenging due to an intractable normalizing constant and cannot be aggregated (i.e. collapsed) over time to make space-only inference.\nIn this study, we take a conceptually different approach to modelling animal telemetry data for making RSF inference. We consider the telemetry data to be a realization of a space–time point process. Under the point process paradigm, the times of the relocations are also considered to be random rather than fixed.\nWe show the point process models we propose are a generalization of the weighted distribution telemetry models. By generalizing the weighted model, we can access several numerical techniques for evaluating point process likelihoods that make use of common statistical software. Thus, the analysis methods can be readily implemented by animal ecologists.\nIn addition to ease of computation, the point process models can be aggregated over time by marginalizing over the temporal component of the model. This allows a full range of models to be constructed for RSF analysis at the individual movement level up to the study area level.\nTo demonstrate the analysis of telemetry data with the point process approach, we analysed a data set of telemetry locations from northern fur seals (Callorhinus ursinus) in the Pribilof Islands, Alaska. Both a space–time and an aggregated space-only model were fitted. At the individual level, the space–time analysis showed little selection relative to the habitat covariates. However, at the study area level, the space-only model showed strong selection relative to the covariates.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Animal Ecology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1111/1365-2656.12087","usgsCitation":"Johnson, D., Hooten, M., and Kuhn, C.E., 2013, Estimating animal resource selection from telemetry data using point process models: Journal of Animal Ecology, v. 82, no. 6, p. 1155-1164, https://doi.org/10.1111/1365-2656.12087.","productDescription":"10 p.","startPage":"1155","endPage":"1164","numberOfPages":"10","ipdsId":"IP-039994","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":473466,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2656.12087","text":"Publisher Index Page"},{"id":278937,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":278936,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/1365-2656.12087"}],"country":"United States","state":"Alaska","otherGeospatial":"Pribilof Islands","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -170.42,56.53 ], [ -170.42,57.25 ], [ -169.46,57.25 ], [ -169.46,56.53 ], [ -170.42,56.53 ] ] ] } } ] }","volume":"82","issue":"6","noUsgsAuthors":false,"publicationDate":"2013-06-25","publicationStatus":"PW","scienceBaseUri":"527cc48de4b0850ea050ce5d","contributors":{"authors":[{"text":"Johnson, Devin S.","contributorId":47524,"corporation":false,"usgs":true,"family":"Johnson","given":"Devin S.","affiliations":[],"preferred":false,"id":471984,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hooten, Mevin 0000-0002-1614-723X mhooten@usgs.gov","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":2958,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin","email":"mhooten@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":12963,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO","active":true,"usgs":false}],"preferred":true,"id":471982,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kuhn, Carey E.","contributorId":42128,"corporation":false,"usgs":true,"family":"Kuhn","given":"Carey","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":471983,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70140927,"text":"70140927 - 2013 - Improving sediment-quality guidelines for nickel: development and application of predictive bioavailability models to assess chronic toxicity of nickel in freshwater sediments","interactions":[],"lastModifiedDate":"2016-12-02T14:59:21","indexId":"70140927","displayToPublicDate":"2013-11-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1571,"text":"Environmental Toxicology and Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Improving sediment-quality guidelines for nickel: development and application of predictive bioavailability models to assess chronic toxicity of nickel in freshwater sediments","docAbstract":"

Within the framework of European Union chemical legislations an extensive data set on the chronic toxicity of sediment nickel has been generated. In the initial phase of testing, tests were conducted with 8 taxa of benthic invertebrates in 2 nickel-spiked sediments, including 1 reasonable worst-case sediment with low concentrations of acid-volatile sulfide (AVS) and total organic carbon. The following species were tested: amphipods (Hyalella azteca, Gammarus pseudolimnaeus), mayflies (Hexagenia sp.), oligochaetes (Tubifex tubifex, Lumbriculus variegatus), mussels (Lampsilis siliquoidea), and midges (Chironomus dilutus, Chironomus riparius). In the second phase, tests were conducted with the most sensitive species in 6 additional spiked sediments, thus generating chronic toxicity data for a total of 8 nickel-spiked sediments. A species sensitivity distribution was elaborated based on 10% effective concentrations yielding a threshold value of 94 mg Ni/kg dry weight under reasonable worst-case conditions. Data from all sediments were used to model predictive bioavailability relationships between chronic toxicity thresholds (20% effective concentrations) and AVS and Fe, and these models were used to derive site-specific sediment-quality criteria. Normalization of toxicity values reduced the intersediment variability in toxicity values significantly for the amphipod species Hyalella azteca and G. pseudolimnaeus, but these relationships were less clearly defined for the mayfly Hexagenia sp. Application of the models to prevailing local conditions resulted in threshold values ranging from 126 mg to 281 mg Ni/kg dry weight, based on the AVS model, and 143 mg to 265 mg Ni/kg dry weight, based on the Fe model

","language":"English","publisher":"Wiley","doi":"10.1002/etc.2373","usgsCitation":"Vangheluwe, M.L., Verdonck, F.A., Besser, J.M., Brumbaugh, W.G., Ingersoll, C.G., Schlekat, C.E., and Rogevich Garman, E., 2013, Improving sediment-quality guidelines for nickel: development and application of predictive bioavailability models to assess chronic toxicity of nickel in freshwater sediments: Environmental Toxicology and Chemistry, v. 32, no. 11, p. 2507-2519, https://doi.org/10.1002/etc.2373.","productDescription":"13 p.","startPage":"2507","endPage":"2519","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-045453","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":297915,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"32","issue":"11","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2013-08-24","publicationStatus":"PW","scienceBaseUri":"54dd2bd2e4b08de9379b34f8","contributors":{"authors":[{"text":"Vangheluwe, Marnix L. U.","contributorId":139229,"corporation":false,"usgs":false,"family":"Vangheluwe","given":"Marnix","email":"","middleInitial":"L. U.","affiliations":[{"id":12706,"text":"ARCHE (Assessing Risks of Chemicals), Ghent, Belgium","active":true,"usgs":false}],"preferred":false,"id":540440,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Verdonck, Frederik A. M.","contributorId":139230,"corporation":false,"usgs":false,"family":"Verdonck","given":"Frederik","email":"","middleInitial":"A. M.","affiliations":[{"id":12706,"text":"ARCHE (Assessing Risks of Chemicals), Ghent, Belgium","active":true,"usgs":false}],"preferred":false,"id":540441,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Besser, John M. 0000-0002-9464-2244 jbesser@usgs.gov","orcid":"https://orcid.org/0000-0002-9464-2244","contributorId":2073,"corporation":false,"usgs":true,"family":"Besser","given":"John","email":"jbesser@usgs.gov","middleInitial":"M.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":540437,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brumbaugh, William G. 0000-0003-0081-375X bbrumbaugh@usgs.gov","orcid":"https://orcid.org/0000-0003-0081-375X","contributorId":493,"corporation":false,"usgs":true,"family":"Brumbaugh","given":"William","email":"bbrumbaugh@usgs.gov","middleInitial":"G.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":540435,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ingersoll, Christopher G. 0000-0003-4531-5949 cingersoll@usgs.gov","orcid":"https://orcid.org/0000-0003-4531-5949","contributorId":2071,"corporation":false,"usgs":true,"family":"Ingersoll","given":"Christopher","email":"cingersoll@usgs.gov","middleInitial":"G.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":540436,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schlekat, Christan E.","contributorId":139228,"corporation":false,"usgs":false,"family":"Schlekat","given":"Christan","email":"","middleInitial":"E.","affiliations":[{"id":12705,"text":"Nickel Producers Environmental Research Association, Durham, Nor","active":true,"usgs":false}],"preferred":false,"id":540439,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rogevich Garman, Emily","contributorId":139227,"corporation":false,"usgs":false,"family":"Rogevich Garman","given":"Emily","email":"","affiliations":[{"id":12705,"text":"Nickel Producers Environmental Research Association, Durham, Nor","active":true,"usgs":false}],"preferred":false,"id":540438,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70048745,"text":"ds799 - 2013 - Baseline coastal oblique aerial photographs collected from Pensacola, Florida, to Breton Islands, Louisiana, February 7, 2012","interactions":[],"lastModifiedDate":"2026-05-29T13:32:56.945234","indexId":"ds799","displayToPublicDate":"2013-10-31T16:06:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"799","title":"Baseline coastal oblique aerial photographs collected from Pensacola, Florida, to Breton Islands, Louisiana, February 7, 2012","docAbstract":"

The U.S. Geological Survey (USGS) conducts baseline and storm response photography missions to document and understand the changes in vulnerability of the Nation's coasts to extreme storms (Morgan, 2009). On February 7, 2012, the USGS conducted an oblique aerial photographic survey from Pensacola, Fla., to Breton Islands, La., aboard a Piper Navajo Chieftain at an altitude of 500 feet (ft) and approximately 1,000 ft offshore. This mission was flown to collect baseline data for assessing incremental changes since the last survey, and the data can be used in the assessment of future coastal change. The photographs provided here are Joint Photographic Experts Group (JPEG) images. The photograph locations are an estimate of the position of the aircraft and do not indicate the location of the feature in the images (see the Navigation Data page). These photos document the configuration of the barrier islands and other coastal features at the time of the survey. The header of each photo is populated with time of collection, Global Positioning System (GPS) latitude, GPS longitude, GPS position (latitude and longitude), keywords, credit, artist (photographer), caption, copyright, and contact information using EXIFtools (Subino and others, 2012). Photographs can be opened directly with any JPEG-compatible image viewer by clicking on a thumbnail on the contact sheet. Table 1 provides detailed information about the assigned location, name, data, and time the photograph was taken along with links to the photograph. In addition to the photographs, a Google Earth Keyhole Markup Language (KML) file is provided and can be used to view the images by clicking on the marker and then clicking on either the thumbnail or the link above the thumbnail. The KML files were created using the photographic navigation files (see the Photos and Maps page).

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds799","usgsCitation":"Morgan, K., Krohn, M.D., Doran, K., and Guy, K.K., 2013, Baseline coastal oblique aerial photographs collected from Pensacola, Florida, to Breton Islands, Louisiana, February 7, 2012: U.S. Geological Survey Data Series 799, HTML Document, https://doi.org/10.3133/ds799.","productDescription":"HTML Document","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":278621,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0799/"},{"id":278622,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0799/title.html"},{"id":278623,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds799.gif"},{"id":504824,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_99274.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Alabama, Florida, Louisiana, Mississippi","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.93408203124999,\n 28.998531814051795\n ],\n [\n -89.93408203124999,\n 30.751277776257812\n ],\n [\n -86.781005859375,\n 30.751277776257812\n ],\n [\n -86.781005859375,\n 28.998531814051795\n ],\n [\n -89.93408203124999,\n 28.998531814051795\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52736dd3e4b097f32ac3dadd","contributors":{"authors":[{"text":"Morgan, Karen L.M. 0000-0002-2994-5572","orcid":"https://orcid.org/0000-0002-2994-5572","contributorId":95553,"corporation":false,"usgs":true,"family":"Morgan","given":"Karen L.M.","affiliations":[],"preferred":false,"id":485535,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Krohn, M. Dennis dkrohn@usgs.gov","contributorId":3378,"corporation":false,"usgs":true,"family":"Krohn","given":"M.","email":"dkrohn@usgs.gov","middleInitial":"Dennis","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":485532,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Doran, Kara 0000-0001-8050-5727","orcid":"https://orcid.org/0000-0001-8050-5727","contributorId":56550,"corporation":false,"usgs":true,"family":"Doran","given":"Kara","affiliations":[],"preferred":false,"id":485534,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Guy, Kristy K. kguy@usgs.gov","contributorId":3546,"corporation":false,"usgs":true,"family":"Guy","given":"Kristy","email":"kguy@usgs.gov","middleInitial":"K.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":485533,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70048715,"text":"sir20135174 - 2013 - Refinement of regression models to estimate real-time concentrations of contaminants in the Menomonee River drainage basin, southeast Wisconsin, 2008-11","interactions":[],"lastModifiedDate":"2018-02-06T12:25:47","indexId":"sir20135174","displayToPublicDate":"2013-10-31T09:36:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-5174","title":"Refinement of regression models to estimate real-time concentrations of contaminants in the Menomonee River drainage basin, southeast Wisconsin, 2008-11","docAbstract":"In 2008, the U.S. Geological Survey and the Milwaukee Metropolitan Sewerage District initiated a study to develop regression models to estimate real-time concentrations and loads of chloride, suspended solids, phosphorus, and bacteria in streams near Milwaukee, Wisconsin. To collect monitoring data for calibration of models, water-quality sensors and automated samplers were installed at six sites in the Menomonee River drainage basin. The sensors continuously measured four potential explanatory variables: water temperature, specific conductance, dissolved oxygen, and turbidity. Discrete water-quality samples were collected and analyzed for five response variables: chloride, total suspended solids, total phosphorus, Escherichia coli bacteria, and fecal coliform bacteria. Using the first year of data, regression models were developed to continuously estimate the response variables on the basis of the continuously measured explanatory variables. Those models were published in a previous report. In this report, those models are refined using 2 years of additional data, and the relative improvement in model predictability is discussed. In addition, a set of regression models is presented for a new site in the Menomonee River Basin, Underwood Creek at Wauwatosa.\n\nThe refined models use the same explanatory variables as the original models. The chloride models all used specific conductance as the explanatory variable, except for the model for the Little Menomonee River near Freistadt, which used both specific conductance and turbidity. Total suspended solids and total phosphorus models used turbidity as the only explanatory variable, and bacteria models used water temperature and turbidity as explanatory variables.\n\nAn analysis of covariance (ANCOVA), used to compare the coefficients in the original models to those in the refined models calibrated using all of the data, showed that only 3 of the 25 original models changed significantly. Root-mean-squared errors (RMSEs) calculated for both the original and refined models using the entire dataset showed a median improvement in RMSE of 2.1 percent, with a range of 0.0–13.9 percent. Therefore most of the original models did almost as well at estimating concentrations during the validation period (October 2009–September 2011) as the refined models, which were calibrated using those data.\n\nApplication of these refined models can produce continuously estimated concentrations of chloride, total suspended solids, total phosphorus, E. coli bacteria, and fecal coliform bacteria that may assist managers in quantifying the effects of land-use changes and improvement projects, establish total maximum daily loads, and enable better informed decision making in the future.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135174","collaboration":"Prepared in cooperation with the Milwaukee Metropolitan Sewerage District","usgsCitation":"Baldwin, A.K., Robertson, D.M., Saad, D.A., and Magruder, C., 2013, Refinement of regression models to estimate real-time concentrations of contaminants in the Menomonee River drainage basin, southeast Wisconsin, 2008-11: U.S. Geological Survey Scientific Investigations Report 2013-5174, vii, 113 p., https://doi.org/10.3133/sir20135174.","productDescription":"vii, 113 p.","numberOfPages":"125","onlineOnly":"Y","temporalStart":"2008-01-01","temporalEnd":"2011-12-31","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":278596,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135174.gif"},{"id":278594,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5174/"},{"id":278595,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5174/pdf/sir2013-5174.pdf"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Menomonee River Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -88.25,42.833333 ], [ -88.25,43.333333 ], [ -87.833333,43.333333 ], [ -87.833333,42.833333 ], [ -88.25,42.833333 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52736dfee4b097f32ac3dae6","contributors":{"authors":[{"text":"Baldwin, Austin K. 0000-0002-6027-3823 akbaldwi@usgs.gov","orcid":"https://orcid.org/0000-0002-6027-3823","contributorId":4515,"corporation":false,"usgs":true,"family":"Baldwin","given":"Austin","email":"akbaldwi@usgs.gov","middleInitial":"K.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":485477,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Robertson, Dale M. 0000-0001-6799-0596 dzrobert@usgs.gov","orcid":"https://orcid.org/0000-0001-6799-0596","contributorId":150760,"corporation":false,"usgs":true,"family":"Robertson","given":"Dale","email":"dzrobert@usgs.gov","middleInitial":"M.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":485475,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Saad, David A. dasaad@usgs.gov","contributorId":121,"corporation":false,"usgs":true,"family":"Saad","given":"David","email":"dasaad@usgs.gov","middleInitial":"A.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":485476,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Magruder, Christopher","contributorId":35995,"corporation":false,"usgs":true,"family":"Magruder","given":"Christopher","affiliations":[],"preferred":false,"id":485478,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70048712,"text":"sir20135051 - 2013 - Groundwater and surface-water interaction within the upper Smith River Watershed, Montana 2006-2010","interactions":[],"lastModifiedDate":"2014-01-30T14:30:20","indexId":"sir20135051","displayToPublicDate":"2013-10-31T08:34:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-5051","title":"Groundwater and surface-water interaction within the upper Smith River Watershed, Montana 2006-2010","docAbstract":"

The 125-mile long Smith River, a tributary of the Missouri River, is highly valued as an agricultural resource and for its many recreational uses. During a drought starting in about 1999, streamflow was insufficient to meet all of the irrigation demands, much less maintain streamflow needed for boating and viable fish habitat. In 2006, the U.S. Geological Survey, in cooperation with the Meagher County Conservation District, initiated a multi-year hydrologic investigation of the Smith River watershed. This investigation was designed to increase understanding of the water resources of the upper Smith River watershed and develop a detailed description of groundwater and surface-water interactions. A combination of methods, including miscellaneous and continuous groundwater-level, stream-stage, water-temperature, and streamflow monitoring was used to assess the hydrologic system and the spatial and temporal variability of groundwater and surface-water interactions. Collectively, data are in agreement and show: (1) the hydraulic connectedness of groundwater and surface water, (2) the presence of both losing and gaining stream reaches, (3) dynamic changes in direction and magnitude of water flow between the stream and groundwater with time, (4) the effects of local flood irrigation on groundwater levels and gradients in the watershed, and (5) evidence and timing of irrigation return flows to area streams.

\n
\n

Groundwater flow within the alluvium and older (Tertiary) basin-fill sediments generally followed land-surface topography from the uplands to the axis of alluvial valleys of the Smith River and its tributaries. Groundwater levels were typically highest in the monitoring wells located within and adjacent to streams in late spring or early summer, likely affected by recharge from snowmelt and local precipitation, leakage from losing streams and canals, and recharge from local flood irrigation. The effects of flood irrigation resulted in increased hydraulic gradients (increased groundwater levels relative to stream stage) or even reversed gradient direction at several monitoring sites coincident with the onset of nearby flood irrigation. Groundwater-level declines in mid-summer were due to groundwater withdrawals and reduced recharge from decreased precipitation, increased evapotranspiration, and reduced leakage in some area streams during periods of low flow. Groundwater levels typically rebounded in late summer, a result of decreased evapotranspiration, decreased groundwater use for irrigation, increased flow in losing streams, and the onset of late-season flood irrigation at some sites.

\n
\n

The effect of groundwater and surface-water interactions is most apparent along the North and South Forks of the Smith River where the magnitude of streamflow losses and gains can be greater than the magnitude of flow within the stream. Net gains consistently occurred over the lower 15 miles of the South Fork Smith River. A monitoring site near the mouth of the South Fork Smith River gained (flow from the groundwater to the stream) during all seasons, with head gradients towards the stream. Two upstream sites on the South Fork Smith River exhibited variable conditions that ranged from gaining during the spring, losing (flowing from the stream to the groundwater) during most of the summer as groundwater levels declined, and then approached or returned to gaining conditions in late summer. Parts of the South Fork Smith River became dry during periods of losing conditions, thus classifying this tributary as intermittent. The North Fork Smith River is highly managed at times through reservoir releases. The North Fork Smith River was perennial throughout the study period although irrigation diversions removed a large percentage of streamflow at times and losing conditions persisted along a lower reach. The lowermost reach of the North Fork Smith River near its mouth transitioned from a losing reach to a gaining reach throughout the study period.

\n
\n

Groundwater and surface-water interactions occur downstream from the confluence of the North and South Fork Smith Rivers, but are less discernible compared to the overall magnitude of the main-stem streamflow. The Smith River was perennial throughout the study. Monitoring sites along the Smith River generally displayed small head gradients between the stream and the groundwater, while one site consistently showed strongly gaining conditions. Synoptic streamflow measurements during periods of limited irrigation diversion in 2007 and 2008 consistently showed gains over the upper 41.4 river miles of the main stem Smith River where net gains ranged from 13.0 to 28.9 cubic feet per second. Continuous streamflow data indicated net groundwater discharge and small-scale tributary inflow contributions of around 25 cubic feet per second along the upper 10-mile reach of the Smith River for most of the 2010 record. A period of intense irrigation withdrawal during the last two weeks in May was followed by a period (early June 2010 to mid-July 2010) with the largest net increase (an average of 71.1 cubic feet per second) in streamflow along this reach of the Smith River. This observation is likely due to increased groundwater discharge to the Smith River resulting from irrigation return flow. By late July, the apparent effects of return flows receded, and the net increase in streamflow returned to about 25 cubic feet per second.

\n
\n

Two-dimensional heat and solute transport VS2DH models representing selected stream cross sections were used to constrain the hydraulic properties of the Quaternary alluvium and estimate temporal water-flux values through model boundaries. Hydraulic conductivity of the Quaternary alluvium of the modeled sections ranged from 3x10-6 to 4x10-5 feet per second. The models showed reasonable approximations of the streambed and shallow aquifer environment, and the dynamic changes in water flux between the stream and the groundwater through different model boundaries.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135051","collaboration":"Prepared in cooperation with Meagher County Conservation District","usgsCitation":"Caldwell, R.R., and Eddy-Miller, C., 2013, Groundwater and surface-water interaction within the upper Smith River Watershed, Montana 2006-2010: U.S. Geological Survey Scientific Investigations Report 2013-5051, xi, 88 p., https://doi.org/10.3133/sir20135051.","productDescription":"xi, 88 p.","numberOfPages":"104","costCenters":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"links":[{"id":278592,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135051.gif"},{"id":278591,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5051/pdf/sir2013-5051.pdf"},{"id":279219,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5051/"}],"scale":"100000","projection":"Lambert Conformal Conic Projection","datum":"North American Datum of 1983","country":"United States","state":"Montana","otherGeospatial":"Smith River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -112.0,46.0 ], [ -112.0,47.5 ], [ -110.5,47.5 ], [ -110.5,46.0 ], [ -112.0,46.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52736dfce4b097f32ac3dae0","contributors":{"authors":[{"text":"Caldwell, Rodney R. 0000-0002-2588-715X caldwell@usgs.gov","orcid":"https://orcid.org/0000-0002-2588-715X","contributorId":2577,"corporation":false,"usgs":true,"family":"Caldwell","given":"Rodney","email":"caldwell@usgs.gov","middleInitial":"R.","affiliations":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"preferred":true,"id":485472,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Eddy-Miller, Cheryl A.","contributorId":86755,"corporation":false,"usgs":true,"family":"Eddy-Miller","given":"Cheryl A.","affiliations":[],"preferred":false,"id":485473,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ]}