The U.S. Army Corps of Engineers (USACE), Chicago District, is responsible for monitoring and computation of the quantity of Lake Michigan water diverted by the State of Illinois. As part of this effort, the USACE uses the Hydrological Simulation Program–FORTRAN (HSPF) with measured meteorological data inputs to estimate runoff from the Lake Michigan diversion special contributing areas (SCAs), the North Branch Chicago River above Niles and the Little Calumet River above South Holland gaged basins, and the Lower Des Plaines and the Calumet ungaged that historically drained to Lake Michigan. These simulated runoffs are used for estimating the total runoff component from the diverted Lake Michigan watershed, which is accountable to the total diversion by the State of Illinois. The runoff is simulated from three interpreted land cover types in the HSPF models: impervious, grass, and forest. The three land cover data types currently in use were derived from aerial photographs acquired in the early 1990s.
\nThis study used the National Land Cover Dataset (NLCD) and developed an automated process for determining the area of the three land cover types, thereby allowing faster updating of future models, and for evaluating land cover changes by use of historical NLCD datasets. The study also carried out a raingage partitioning analysis so that the segmentation of land cover and rainfall in each modeled unit is directly applicable to the HSPF modeling. Historical and existing impervious, grass, and forest land acreages partitioned by percentages covered by two sets of raingages for the Lake Michigan diversion SCAs, gaged basins, and ungaged basins are presented.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141258","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers, Chicago District","usgsCitation":"Sharpe, J.B., and Soong, D.T., 2015, Lake Michigan Diversion Accounting land cover change estimation by use of the National Land Cover Dataset and raingage network partitioning analysis: U.S. Geological Survey Open-File Report 2014-1258, Report: iv, 12 p.; Downloads Directory, https://doi.org/10.3133/ofr20141258.","productDescription":"Report: iv, 12 p.; Downloads Directory","numberOfPages":"20","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-060110","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":297727,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141258.jpg"},{"id":297724,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1258/"},{"id":297725,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1258/pdf/ofr2014-1258.pdf","text":"Report","size":"2.12 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":297726,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2014/1258/downloads/ofr2014-1258_tables5-20.xlsx","text":"Downloads Directory","description":"Downloads Directory","linkHelpText":"Contains: Excel spreadsheets of tables 5 through 20."}],"projection":"Albers Equal-Area Conic Projection","country":"United States","state":"Illinois","otherGeospatial":"Calumet River, Lake Michigan, Little Calumet River, Lower Des Plaines River, North Branch Chicago River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.989501953125,\n 41.3500103516271\n ],\n [\n -87.989501953125,\n 42.370720143531955\n ],\n [\n -87.286376953125,\n 42.370720143531955\n ],\n [\n -87.286376953125,\n 41.3500103516271\n ],\n [\n -87.989501953125,\n 41.3500103516271\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2a8de4b08de9379b30ee","contributors":{"authors":[{"text":"Sharpe, Jennifer B. 0000-0002-5192-7848 jbsharpe@usgs.gov","orcid":"https://orcid.org/0000-0002-5192-7848","contributorId":2825,"corporation":false,"usgs":true,"family":"Sharpe","given":"Jennifer","email":"jbsharpe@usgs.gov","middleInitial":"B.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":539829,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Soong, David T. dsoong@usgs.gov","contributorId":2230,"corporation":false,"usgs":true,"family":"Soong","given":"David","email":"dsoong@usgs.gov","middleInitial":"T.","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":false,"id":539830,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70139655,"text":"ofr20141238 - 2015 - Maps showing the change in modern sediment thickness on the Inner Continental Shelf offshore of Fire Island, New York, between 1996-97 and 2011","interactions":[],"lastModifiedDate":"2015-02-03T11:45:19","indexId":"ofr20141238","displayToPublicDate":"2015-02-03T11:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-1238","title":"Maps showing the change in modern sediment thickness on the Inner Continental Shelf offshore of Fire Island, New York, between 1996-97 and 2011","docAbstract":"The U.S. Geological Survey mapped approximately 336 square kilometers of the lower shoreface and inner continental shelf offshore of Fire Island, New York, in 1996 and 1997, using high-resolution sidescan-sonar and seismic-reflection systems, and again in 2011, using interferometric sonar and high-resolution chirp seismic-reflection systems. This report presents a comparison of sediment thickness and distribution as mapped during these two investigations. These spatial data support research on the Quaternary evolution of the Fire Island coastal system and provide baseline information for research on coastal processes along southern Long Island.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141238","usgsCitation":"Schwab, W.C., Baldwin, W.E., and Denny, J.F., 2015, Maps showing the change in modern sediment thickness on the Inner Continental Shelf offshore of Fire Island, New York, between 1996-97 and 2011: U.S. Geological Survey Open-File Report 2014-1238, Report: HTML Document; Report: v, 8 p., https://doi.org/10.3133/ofr20141238.","productDescription":"Report: HTML Document; Report: v, 8 p.","numberOfPages":"17","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"1996-01-01","temporalEnd":"2011-12-31","ipdsId":"IP-058163","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":297710,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141238.JPG"},{"id":297709,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1238/pdf/ofr2014-1238.pdf","text":"Report (PDF format)","size":"2.42 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":297707,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1238/"},{"id":297708,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1238/ofr2014-1238-title_page.html","text":"Report (HTML format)","linkFileType":{"id":5,"text":"html"}}],"projection":"Universal Transverse Mercator projection","datum":"World Geodetic System 1984","country":"United States","state":"New York","otherGeospatial":"Fire Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.3392333984375,\n 40.64521960545374\n ],\n [\n -72.43560791015625,\n 40.887562618139405\n ],\n [\n -72.41912841796875,\n 40.63375667842965\n ],\n [\n -73.32412719726562,\n 40.42395127765169\n ],\n [\n -73.3392333984375,\n 40.64521960545374\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2a95e4b08de9379b3115","contributors":{"authors":[{"text":"Schwab, William C. 0000-0001-9274-5154 bschwab@usgs.gov","orcid":"https://orcid.org/0000-0001-9274-5154","contributorId":417,"corporation":false,"usgs":true,"family":"Schwab","given":"William","email":"bschwab@usgs.gov","middleInitial":"C.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":539498,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baldwin, Wayne E. 0000-0001-5886-0917 wbaldwin@usgs.gov","orcid":"https://orcid.org/0000-0001-5886-0917","contributorId":1321,"corporation":false,"usgs":true,"family":"Baldwin","given":"Wayne","email":"wbaldwin@usgs.gov","middleInitial":"E.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":539499,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Denny, Jane F. 0000-0002-3472-618X jdenny@usgs.gov","orcid":"https://orcid.org/0000-0002-3472-618X","contributorId":418,"corporation":false,"usgs":true,"family":"Denny","given":"Jane","email":"jdenny@usgs.gov","middleInitial":"F.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":539500,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70137562,"text":"sir20145242 - 2015 - Low-flow characteristics for selected streams in Indiana","interactions":[],"lastModifiedDate":"2015-02-03T10:35:00","indexId":"sir20145242","displayToPublicDate":"2015-02-03T11:00:00","publicationYear":"2015","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":"2014-5242","title":"Low-flow characteristics for selected streams in Indiana","docAbstract":"The management and availability of Indiana’s water resources increase in importance every year. Specifically, information on low-flow characteristics of streams is essential to State water-management agencies. These agencies need low-flow information when working with issues related to irrigation, municipal and industrial water supplies, fish and wildlife protection, and the dilution of waste. Industrial, municipal, and other facilities must obtain National Pollutant Discharge Elimination System (NPDES) permits if their discharges go directly to surface waters. The Indiana Department of Environmental Management (IDEM) requires low-flow statistics in order to administer the NPDES permit program. Low-flow-frequency characteristics were computed for 272 continuous-record stations. The information includes low-flow-frequency analysis, flow-duration analysis, and harmonic mean for the continuous-record stations. For those stations affected by some form of regulation, low-flow frequency curves are based on the longest period of homogeneous record under current conditions. Low-flow-frequency values and harmonic mean flow (if sufficient data were available) were estimated for the 166 partial-record stations. Partial-record stations are ungaged sites where streamflow measurements were made at base flow.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145242","collaboration":"Prepared in cooperation with the Indiana Department of Environmental Management","usgsCitation":"Fowler, K.K., and Wilson, J.T., 2015, Low-flow characteristics for selected streams in Indiana: U.S. Geological Survey Scientific Investigations Report 2014-5242, Report: iv, 353 p.; 2 Tables, https://doi.org/10.3133/sir20145242.","productDescription":"Report: iv, 353 p.; 2 Tables","numberOfPages":"361","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-051143","costCenters":[{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":297704,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145242.jpg"},{"id":297699,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5242/"},{"id":297701,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5242/pdf/sir2014-5242.pdf","text":"Report","size":"9.36 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2014-5242 Report"},{"id":297702,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2014/5242/table/sir2014-5242_table1.xlsx","text":"Table 1","size":"72.4 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2014-5242 Table","linkHelpText":"Continuous-record stations."},{"id":297703,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2014/5242/table/sir2014-5242_table2.xlsx","text":"Table 2","size":"87.2 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2014-5242 Table","linkHelpText":"Partial-record stations."}],"country":"United States","state":"Indiana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.528076171875,\n 41.7631174470059\n ],\n [\n -84.803466796875,\n 41.77950486590359\n ],\n [\n -84.7705078125,\n 38.74551518488265\n ],\n [\n -85.36376953125,\n 38.65119833229951\n ],\n [\n -85.36376953125,\n 38.47939467327645\n ],\n [\n -85.968017578125,\n 37.87485339352928\n ],\n [\n -86.33056640625,\n 37.98750437106374\n ],\n [\n -86.59423828125,\n 37.74465712069939\n ],\n [\n -86.802978515625,\n 37.85750715625203\n ],\n [\n -87.0556640625,\n 37.68382032669382\n ],\n [\n -88.05541992187499,\n 37.727280276860036\n ],\n [\n -88.187255859375,\n 37.87485339352928\n ],\n [\n -88.0224609375,\n 38.272688535980976\n ],\n [\n -87.60498046875,\n 38.762650338334154\n ],\n [\n -87.681884765625,\n 39.14710270770074\n ],\n [\n -87.6708984375,\n 39.317300373271024\n ],\n [\n -87.528076171875,\n 39.36827914916014\n ],\n [\n -87.528076171875,\n 41.7631174470059\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2a94e4b08de9379b310c","contributors":{"authors":[{"text":"Fowler, Kathleen K. 0000-0002-0107-3848 kkfowler@usgs.gov","orcid":"https://orcid.org/0000-0002-0107-3848","contributorId":2439,"corporation":false,"usgs":true,"family":"Fowler","given":"Kathleen","email":"kkfowler@usgs.gov","middleInitial":"K.","affiliations":[{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true},{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":539754,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wilson, John T. 0000-0001-6752-4069 jtwilson@usgs.gov","orcid":"https://orcid.org/0000-0001-6752-4069","contributorId":1954,"corporation":false,"usgs":true,"family":"Wilson","given":"John","email":"jtwilson@usgs.gov","middleInitial":"T.","affiliations":[{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":false,"id":539756,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70148570,"text":"70148570 - 2015 - Status and trends of prey fish populations in Lake Michigan, 2013","interactions":[],"lastModifiedDate":"2019-07-16T10:40:14","indexId":"70148570","displayToPublicDate":"2015-02-03T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"seriesTitle":{"id":5651,"text":"Great Lakes Fishery Commission, Committee Meeting Report","active":true,"publicationSubtype":{"id":4}},"title":"Status and trends of prey fish populations in Lake Michigan, 2013","docAbstract":"The U.S. Geological Survey Great Lakes Science Center has conducted lake-wide surveys of the fish community in Lake Michigan each fall since 1973 using standard 12-m bottom trawls towed along contour at depths of 9 to 110 m at each of seven index transects. The resulting data on relative abundance, size and age structure, and condition of individual fishes are used to estimate various population parameters that are in turn used by state and tribal agencies in managing Lake Michigan fish stocks. All seven established index transects of the survey were completed in 2013. The survey provides relative abundance and biomass estimates between the 5-m and 114-m depth contours of the lake (herein, lake-wide) for prey fish populations, as well as burbot, yellow perch, and the introduced dreissenid mussels. Lake-wide biomass of alewives in 2013 was estimated at 29 kilotonnes (kt, 1 kt = 1000 metric tonnes), which was more than three times the 2012 estimate. However, the unusually high standard error associated with the 2013 estimate indicated no significant increase in lake-wide biomass between 2012 and 2013. Moreover, the age distribution of alewives remained truncated with no alewife exceeding an age of 5. The population of age-1 and older alewives was dominated (i.e., 88%) by the 2010 and 2012 year-classes. Record low biomass was observed for deepwater sculpin (1.3 kt) and ninespine stickleback (0.004 kt) in 2013, while bloater (1.6 kt) and rainbow smelt (0.2 kt) biomasses remained at low levels. Slimy sculpin lake-wide biomass was 0.32 kt in 2013, marking the fourth consecutive year of a decline. The 2013 biomass of round goby was estimated at 10.9 kt, which represented the peak estimate to date. Burbot lake-wide biomass (0.4 kt in 2013) has remained below 3 kt since 2001. Numeric density of age-0 yellow perch (i.e., < 100 mm) was only 1 fish per ha, which is indicative of a relatively poor year-class. Lake-wide biomass estimate of dreissenid mussels in 2013 was 23.2 kt. Overall, the total lake-wide prey fish biomass estimate (sum of alewife, bloater, rainbow smelt, deepwater sculpin, slimy sculpin, round goby, and ninespine stickleback) in 2013 was 43 kt, with alewives and round gobies constituting 92% of this total.
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dataset","interactions":[],"lastModifiedDate":"2015-02-02T12:50:59","indexId":"ds877","displayToPublicDate":"2015-02-02T12:45:00","publicationYear":"2015","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":"877","title":"Wetland paleoecological study of southwest coastal Louisiana: sediment cores and diatom calibration dataset","docAbstract":"Wetland sediment data were collected in 2009 and 2010 throughout the southwest Louisiana Chenier Plain as part of a pilot study to develop a diatom-based proxy for past wetland water chemistry and the identification of sediment deposits from tropical storms. The complete dataset includes forty-six surface sediment samples and nine sediment cores. The surface sediment samples were collected in fresh, intermediate, and brackish marsh and are located coincident with Coastwide Reference Monitoring System (CRMS) sites. The nine sediment cores were collected at the Rockefeller Wildlife Refuge (RWR) located in Grand Chenier, La.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds877","usgsCitation":"Smith, K.E., Flocks, J.G., Steyer, G.D., and Piazza, S.C., 2015, Wetland paleoecological study of southwest coastal Louisiana: sediment cores and diatom calibration dataset: U.S. Geological Survey Data Series 877, HTML Document, https://doi.org/10.3133/ds877.","productDescription":"HTML Document","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-052587","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":297680,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds877.PNG"},{"id":297678,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0877/"},{"id":297679,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0877/html/ds877_abstract.html","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"Report"}],"country":"United States","state":"Louisiana","city":"Grand Chenier","otherGeospatial":"Chenier Plain, Rockefeller Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.85894775390625,\n 29.508939763268394\n ],\n [\n -93.85894775390625,\n 30.071470887901302\n ],\n [\n -91.96929931640624,\n 30.071470887901302\n ],\n [\n -91.96929931640624,\n 29.508939763268394\n ],\n [\n -93.85894775390625,\n 29.508939763268394\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2ad0e4b08de9379b321c","contributors":{"authors":[{"text":"Smith, Kathryn E. L. kelsmith@usgs.gov","contributorId":3242,"corporation":false,"usgs":true,"family":"Smith","given":"Kathryn","email":"kelsmith@usgs.gov","middleInitial":"E. L.","affiliations":[],"preferred":false,"id":519342,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Flocks, James G. 0000-0002-6177-7433 jflocks@usgs.gov","orcid":"https://orcid.org/0000-0002-6177-7433","contributorId":816,"corporation":false,"usgs":true,"family":"Flocks","given":"James","email":"jflocks@usgs.gov","middleInitial":"G.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":539675,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Steyer, Gregory D. 0000-0001-7231-0110 steyerg@usgs.gov","orcid":"https://orcid.org/0000-0001-7231-0110","contributorId":2856,"corporation":false,"usgs":true,"family":"Steyer","given":"Gregory","email":"steyerg@usgs.gov","middleInitial":"D.","affiliations":[{"id":5064,"text":"Southeast Regional Director's Office","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":5062,"text":"Office of the Chief Scientist for Ecosystems","active":true,"usgs":true}],"preferred":true,"id":539676,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Piazza, Sarai C. 0000-0001-6962-9008 piazzas@usgs.gov","orcid":"https://orcid.org/0000-0001-6962-9008","contributorId":466,"corporation":false,"usgs":true,"family":"Piazza","given":"Sarai","email":"piazzas@usgs.gov","middleInitial":"C.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":false,"id":539677,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70133604,"text":"ds901 - 2015 - Mount St. Helens: Controlled-source audio-frequency magnetotelluric (CSAMT) data and inversions","interactions":[],"lastModifiedDate":"2016-02-08T14:09:10","indexId":"ds901","displayToPublicDate":"2015-02-02T12:30:00","publicationYear":"2015","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":"901","title":"Mount St. Helens: Controlled-source audio-frequency magnetotelluric (CSAMT) data and inversions","docAbstract":"This report describes a series of geoelectrical soundings carried out on and near Mount St. Helens volcano, Washington, in 2010–2011. These soundings used a controlled-source audio-frequency magnetotelluric (CSAMT) approach (Zonge and Hughes, 1991; Simpson and Bahr, 2005). We chose CSAMT for logistical reasons: It can be deployed by helicopter, has an effective depth of penetration of as much as 1 kilometer, and requires less wire than a Schlumberger sounding.
\nThis Data Series provides the edited data for these CSAMT soundings as well as several different types of 1-D inversions (where the signal data are converted to conductivity-versus-depth models). In addition, we include a map showing station locations on and around the volcano and the Pumice Plain to the north.
\nThe apparent conductivity (or its inverse, apparent resistivity) measured by a geoelectrical system is caused by several factors. The most important of these are water-filled rock porosity and the presence of water-filled fractures; however, rock type and minerals (for instance, sulfides and clay content) also contribute to apparent conductivity. In situations with little recharge (for instance, in arid regions), variations in ionic content of water occupying pore space and fractures sampled by the measurement system must also be factored in (Wynn, 2006). Variations in ionic content may also be present in hydrothermal fluids surrounding volcanoes in wet regions. In unusual cases, temperature may also affect apparent conductivity (Keller, 1989; Palacky, 1989). There is relatively little hydrothermal alteration (and thus fewer clay minerals that might add to the apparent conductivity) in the eruptive products of Mount St. Helens (Reid and others, 2010), so conductors observed in the Fischer, Occam, and Marquardt inversion results later in this report are thus believed to map zones with significant water content. Geoelectrical surveys thus have the potential to reveal subsurface regions with significant groundwater content, including perched and regional aquifers. Reid and others (2001) and Reid (2004) have suggested that groundwater involvement may figure in both the scale and the character of some if not all volcanic edifice collapse events. Ongoing research by the U.S. Geological Survey (USGS) and others aims to better understand the contribution of groundwater to both edifice pore pressure and rock alteration as well as its direct influence on eruption processes by violent interaction with magma (Schmincke, 1998).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds901","usgsCitation":"Wynn, J., and Pierce, H., 2015, Mount St. Helens: Controlled-source audio-frequency magnetotelluric (CSAMT) data and inversions: U.S. Geological Survey Data Series 901, HTML Document, https://doi.org/10.3133/ds901.","productDescription":"HTML Document","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-044700","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":297677,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds901.gif"},{"id":316600,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0901/ds901.pdf","text":"Report","size":"3.8 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":297676,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0901/cover.html","text":"Report","linkFileType":{"id":5,"text":"html"}}],"projection":"Universal Transverse Mercator projection, Zone 10N","datum":"World Geodetic System 1984","country":"United States","state":"Washington","otherGeospatial":"Mount St. Helens","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.28675842285158,\n 46.150107913663334\n ],\n [\n -122.28675842285158,\n 46.27388525189855\n ],\n [\n -122.09415435791016,\n 46.27388525189855\n ],\n [\n -122.09415435791016,\n 46.150107913663334\n ],\n [\n -122.28675842285158,\n 46.150107913663334\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2a9ce4b08de9379b3137","contributors":{"authors":[{"text":"Wynn, Jeff 0000-0002-8102-3882 jwynn@usgs.gov","orcid":"https://orcid.org/0000-0002-8102-3882","contributorId":2803,"corporation":false,"usgs":true,"family":"Wynn","given":"Jeff","email":"jwynn@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":539674,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pierce, Herbert A.","contributorId":83093,"corporation":false,"usgs":true,"family":"Pierce","given":"Herbert A.","affiliations":[],"preferred":false,"id":539673,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70148078,"text":"70148078 - 2015 - Mapping migratory flyways in Asia using dynamic Brownian bridge movement models","interactions":[],"lastModifiedDate":"2017-07-26T17:13:27","indexId":"70148078","displayToPublicDate":"2015-02-02T11:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2792,"text":"Movement Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Mapping migratory flyways in Asia using dynamic Brownian bridge movement models","docAbstract":"Background
\nIdentifying movement routes and stopover sites is necessary for developing effective management and conservation strategies for migratory animals. In the case of migratory birds, a collection of migration routes, known as a flyway, is often hundreds to thousands of kilometers long and can extend across political boundaries. Flyways encompass the entire geographic range between the breeding and non-breeding areas of a population, species, or a group of species, and they provide spatial frameworks for management and conservation across international borders. Existing flyway maps are largely qualitative accounts based on band returns and survey data rather than observed movement routes. In this study, we use satellite and GPS telemetry data and dynamic Brownian bridge movement models to build upon existing maps and describe waterfowl space use probabilistically in the Central Asian and East Asian-Australasian Flyways.
\nResults
\nOur approach provided new information on migratory routes that was not easily attainable with existing methods to describe flyways. Utilization distributions from dynamic Brownian bridge movement models identified key staging and stopover sites, migration corridors and general flyway outlines in the Central Asian and East Asian-Australasian Flyways. A map of space use from ruddy shelducks depicted two separate movement corridors within the Central Asian Flyway, likely representing two distinct populations that show relatively strong connectivity between breeding and wintering areas. Bar-headed geese marked at seven locations in the Central Asian Flyway showed heaviest use at several stopover sites in the same general region of high-elevation lakes along the eastern Qinghai-Tibetan Plateau. Our analysis of data from multiple Anatidae species marked at sites throughout Asia highlighted major movement corridors across species and confirmed that the Central Asian and East Asian-Australasian Flyways were spatially distinct.
\nConclusions
\nThe dynamic Brownian bridge movement model improves our understanding of flyways by estimating relative use of regions in the flyway while providing detailed, quantitative information on migration timing and population connectivity including uncertainty between locations. This model effectively quantifies the relative importance of different migration corridors and stopover sites and may help prioritize specific areas in flyways for conservation of waterbird populations.
","language":"English","publisher":"Minerva Center for Movement Ecology","publisherLocation":"London","doi":"10.1186/s40462-015-0029-6","usgsCitation":"Palm, E., Newman, S.H., Prosser, D.J., Xiao, X., Luo, Z., Batbayar, N., Balachandran, S., and Takekawa, J.Y., 2015, Mapping migratory flyways in Asia using dynamic Brownian bridge movement models: Movement Ecology, v. 3, no. 1, p. 1-10, https://doi.org/10.1186/s40462-015-0029-6.","productDescription":"10 p.","startPage":"1","endPage":"10","numberOfPages":"10","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-062254","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":472293,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s40462-015-0029-6","text":"Publisher Index Page"},{"id":300545,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"3","issue":"1","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2015-02-02","publicationStatus":"PW","scienceBaseUri":"555c5eb6e4b0a92fa7eacc02","contributors":{"authors":[{"text":"Palm, E.C.","contributorId":40708,"corporation":false,"usgs":true,"family":"Palm","given":"E.C.","email":"","affiliations":[],"preferred":false,"id":547228,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Newman, S. H.","contributorId":21888,"corporation":false,"usgs":false,"family":"Newman","given":"S.","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":547229,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Prosser, Diann J. 0000-0002-5251-1799 dprosser@usgs.gov","orcid":"https://orcid.org/0000-0002-5251-1799","contributorId":2389,"corporation":false,"usgs":true,"family":"Prosser","given":"Diann","email":"dprosser@usgs.gov","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":547230,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Xiao, Xiangming","contributorId":67212,"corporation":false,"usgs":true,"family":"Xiao","given":"Xiangming","affiliations":[],"preferred":false,"id":547231,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Luo, Ze","contributorId":41307,"corporation":false,"usgs":true,"family":"Luo","given":"Ze","affiliations":[],"preferred":false,"id":547232,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Batbayar, Nyambayar","contributorId":40338,"corporation":false,"usgs":true,"family":"Batbayar","given":"Nyambayar","affiliations":[],"preferred":false,"id":547233,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Balachandran, Sivananinthaperumal","contributorId":20593,"corporation":false,"usgs":true,"family":"Balachandran","given":"Sivananinthaperumal","affiliations":[],"preferred":false,"id":547234,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Takekawa, John Y. 0000-0003-0217-5907 john_takekawa@usgs.gov","orcid":"https://orcid.org/0000-0003-0217-5907","contributorId":176168,"corporation":false,"usgs":true,"family":"Takekawa","given":"John","email":"john_takekawa@usgs.gov","middleInitial":"Y.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":547235,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70135892,"text":"sir20145232 - 2015 - Potentiometric surfaces and water-level trends in the Cockfield (upper Claiborne) aquifer in southern Arkansas and the Wilcox (lower Wilcox) aquifer of northeastern and southern Arkansas, 2012","interactions":[],"lastModifiedDate":"2015-04-20T14:25:03","indexId":"sir20145232","displayToPublicDate":"2015-02-02T09:00:00","publicationYear":"2015","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":"2014-5232","title":"Potentiometric surfaces and water-level trends in the Cockfield (upper Claiborne) aquifer in southern Arkansas and the Wilcox (lower Wilcox) aquifer of northeastern and southern Arkansas, 2012","docAbstract":"The Cockfield aquifer, located in southern Arkansas, is composed of Eocene-age sand beds found near the base of the Cockfield Formation of Claiborne Group. The Wilcox aquifer, located in northeastern and southern Arkansas, is composed of Paleocene-age sand beds found in the middle to lower part of the Wilcox Group. The Cockfield and Wilcox aquifers are primary sources of groundwater. In 2010, withdrawals from the Cockfield aquifer in Arkansas totaled 19.2 million gallons per day (Mgal/d), and withdrawals from the Wilcox aquifer totaled 36.5 Mgal/d.
\nA study was conducted by the U.S. Geological Survey in cooperation with the Arkansas Natural Resources Commission and the Arkansas Geological Survey to measure water levels associated with the Cockfield aquifer and the Wilcox aquifer in northeastern and southern Arkansas. Water levels were measured at 43 wells completed in the Cockfield aquifer and 47 wells completed in the Wilcox aquifer in February and March 2012. Measurements from 2012 are presented as potentiometric-surface maps and in combination with measurements from 2006 as water-level difference maps. Trends in water-level change over time within the Cockfield and Wilcox aquifers were determined using the water-level difference maps and selected well hydrographs.
\nThe Cockfield aquifer study area in southern Arkansas is bounded on the east by the Mississippi River and on the west by the area that contains outcrops and subcrops of the Cockfield Formation. The northern boundary of the Cockfield aquifer study area is defined by the area that contains observation wells completed in the Cockfield aquifer and the southern boundary is the Louisiana State line.
\nThe Wilcox aquifer study area in northeastern Arkansas is bounded on the east by the Mississippi River and on the north by the Missouri State line. The southern and western boundaries are defined by areas containing observation wells completed in the Wilcox aquifer or by outcrop areas on or near Crowleys Ridge. The Wilcox aquifer study area in southern Arkansas is defined by observation wells completed in the Wilcox aquifer or by areas that contain outcrops of the Wilcox Group, or both.
\nThe potentiometric-surface map of the Cockfield aquifer shows the regional direction of groundwater flow was generally toward the east-southeast, except in areas of intense groundwater withdrawals such as southwestern Ashley County, where groundwater flows toward the town of Crossett. The highest water-level altitude measured was 350 feet (ft) above National Geodetic Vertical Datum of 1929 (NGVD 29) in central Columbia County. The lowest water-level altitude measured was 40 ft above NGVD 29 in southeastern Lincoln County.
\nThe water-level difference map for the Cockfield aquifer in Arkansas was constructed using 42 water-level measurements made during 2006 and 2012. The difference in water levels for the Cockfield aquifer ranged from 27.4 ft to -10.4 ft. The largest water-level rise was in Calhoun County, and the largest water-level decline was 10.4 ft in Union County. Of the 42 wells, 13 wells had a rise in water level, and the remaining 29 wells had a decline in water level.
\nHydrographs for 32 wells in the Cockfield aquifer with historical water-level data were evaluated using linear regression to calculate the annual rise or decline for each well. These data were aggregated by county and statistically evaluated for the range, mean, and median of water-level change in each county. Hydrographs for Bradley, Calhoun, Chicot, Columbia, and Union Counties indicated both rising and declining water levels. The mean annual water-level rise or decline for Calhoun County was 0.00 foot per year (ft/yr) or unchanged. The mean annual water-level for Ashley, Bradley, Chicot, Cleveland, Columbia, Lincoln, and Union Counties show declines ranging from -0.02 to -1.10 ft/yr.
\nTwo potentiometric-surface maps, one for the southern area and one for the northeastern area, were constructed to show the altitude of the water surface in the Wilcox aquifer. The direction of groundwater flow in the northeastern area was generally towards the south-southwest except for some areas immediately adjacent to the Mississippi River where the flow was more eastward towards the river. The highest water-level altitude was 219 ft in northern Mississippi County, and the lowest water-level altitude was 123 ft near West Memphis in Crittenden County. The direction of groundwater flow in the northern part of the southern area was generally towards the southwest. The direction of groundwater flow in the southern part was in all directions because of two cones of depression and two water-level mounds. The highest water-level altitude measured was 394 ft at the center of a water-level mound in eastern Hot Spring County and a water-level mound in southwestern Hempstead County. The lowest water-level altitude measured was 145 ft at the center of the cone of depression in Clark County.
\nWater-level difference maps for the Wilcox aquifer in Arkansas were constructed using 47 water-level measurements made during 2006 and 2012. The difference in water levels for the Wilcox aquifer in the northeastern area ranged from 22.0 ft to -17.9 ft. The largest rise in water level occurred in Crittenden County, and the largest decline occurred in Lee County. Twenty-one wells had rising water levels, and 10 wells had declining water levels. The difference in water levels for the Wilcox aquifer in the southern area ranged from 18.1 ft to -4.2 ft. The largest rise and the largest decline in water level occurred in Nevada County. Twelve wells had rising water levels, and 4 wells had declining water levels.
\nLinear regression analysis of long-term hydrographs was used to determine the mean annual water-level rise and decline in the Wilcox aquifer in the northeastern and southern areas of Arkansas. In the northeastern area, the mean annual water level declined in all seven counties. The mean annual declines ranged from -0.55 ft/yr in Craighead County to -1.46 ft/yr in St. Francis County. In the southern area, the annual rise and decline calculations for wells with over 20 years of records indicate rising and declining water levels in Clark, Hot Spring, and Nevada Counties. The mean annual water level declined in all counties except Hot Spring County.
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Basin","docAbstract":"In 2009, the U.S. Geological Survey (USGS) developed a Spatially Referenced Regressions on Watershed Attributes (SPARROW) surface-water quality model for the Upper Colorado River Basin (UCRB) relating dissolved-solids sources and transport in the 1991 water year to upstream catchment characteristics. The SPARROW model focused on geologic and agricultural sources of dissolved solids in the UCRB and was calibrated using water-year 1991 dissolved-solids loads from 218 monitoring sites. A new UCRB SPARROW model is planned that will update the investigation of dissolved-solids sources and transport in the basin to circa 2010 conditions and will improve upon the 2009 model by incorporating more detailed information about agricultural-irrigation and rangeland-management practices, among other improvements. Geospatial datasets relating to circa 2010 rangeland conditions are required for the new UCRB SPARROW modeling effort. This study compiled geospatial datasets for the UCRB that relate to the biotic alterations and rangeland conditions of grazing, fire and other land disturbance, and vegetation type and cover. Datasets representing abiotic alterations of access control (off-highway vehicles) and sediment generation and transport in general, were also compiled. These geospatial datasets may be tested in the upcoming SPARROW model to better understand the potential contribution of rangelands to dissolved-solids loading in UCRB streams.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151007","collaboration":"Prepared in cooperation with the U.S. Bureau of Reclamation","usgsCitation":"Tillman, F., Flynn, M., and Anning, D.W., 2015, Geospatial datasets for assessing the effects of rangeland conditions on dissolved-solids yields in the Upper Colorado River Basin: U.S. Geological Survey Open-File Report 2015-1007, Report: v, 21 p.; 6 Geospatial Datasets, https://doi.org/10.3133/ofr20151007.","productDescription":"Report: v, 21 p.; 6 Geospatial Datasets","numberOfPages":"32","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-060100","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":297671,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20151007.gif"},{"id":297670,"rank":9,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/of/2015/1007/downloads/datasets/UCRB_R-factor.zip","text":"Rainfall-Runoff Erosivity","size":"962 kB","description":"Geospatial dataset","linkHelpText":"This tabular dataset presents the 1971–2000 average annual rainfall-runoff erosivity factor (R-factor) for the UCRB. 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The 2010 existing vegetation cover (EVC) layer represents the vertically projected percent cover of the live canopy layer. The 2010 existing vegetation type (EVT) layer represents the species composition. Spatially, both grids cover the entire UCRB and have a 30-meter pixel resolution."},{"id":297664,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1007/downloads/OFR2015-1007.pdf","text":"Report","size":"5.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":297666,"rank":5,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/of/2015/1007/downloads/datasets/2010_UCRB_USFS_Grazing_projected.zip","text":"U.S. Forest Service Grazing","size":"3.8 MB","description":"Geospatial dataset","linkHelpText":"The shapefile contains 444 polygons of USFS grazing allotments within or bordering the UCRB (fig. 4). 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The Vehicular Trail (4WD) attribute presents potential UCRB locations of off-highway vehicle use—an activity directly related to the \"access controls\" abiotic alteration in Weltz and others (2014) (table 5; fig. 7). The 2010 roads layer covers the entire UCRB."},{"id":297665,"rank":4,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/of/2015/1007/downloads/datasets/2010_UCRB_BLM_Grazing_projected.zip","text":"Bureau of Land Management Grazing","size":"12.9 MB","description":"Geospatial dataset","linkHelpText":"The shapefile contains 2,367 polygons of BLM grazing allotments within or bordering the UCRB (fig. 4). 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In turn, this information can be used to shape policy related to food and water from commodity markets to humanitarian relief efforts. New data alone, however, do not translate to improvements in drought and yield forecasts. New tools will be needed to transform SMAP data into agriculturally meaningful products. The objective of this study is to evaluate the possibility and efficiency of replacing the rainfall-derived soil moisture component of a crop water stress index with SMAP data. The approach is demonstrated with 0.1°-resolution, ~10-day microwave soil moisture from the European Space Agency and simulated soil moisture from the Famine Early Warning Systems Network Land Data Assimilation System. Over a West Africa domain, the approach is evaluated by comparing the different soil moisture estimates and their resulting Water Requirement Satisfaction Index values from 2000 to 2010. This study highlights how the ensemble of indices performs during wet versus dry years, over different land-cover types, and the correlation with national-level millet yields. The new approach is a feasible and useful way to quantitatively assess how satellite-derived rainfall and soil moisture track agricultural water deficits. Given the importance of soil moisture in many applications, ranging from agriculture to public health to fire, this study should inspire other modeling communities to reformulate existing tools to take advantage of SMAP data.
","language":"English","publisher":"American Meteorological Society","publisherLocation":"Boston, MA","doi":"10.1175/JHM-D-14-0049.1","collaboration":"Amy McNally; Gregory J. Husak; Molly Brown; Mark Carroll; Chris Funk; Joel Michaelsen; Soni Yatheendradas; Kristi Arsenault, Christa Peters-Lidard; James P. Verdin","usgsCitation":"McNally, A., Gregory J. Husak, Brown, M., Carroll, M.L., Funk, C.C., Soni Yatheendradas, Arsenault, K., Christa Peters-Lidard, and Verdin, J., 2015, Calculating crop water requirement satisfaction in the West Africa Sahel with remotely sensed soil moisture: Journal of Hydrometeorology, v. 16, no. 1, p. 295-305, https://doi.org/10.1175/JHM-D-14-0049.1.","productDescription":"11 p.","startPage":"295","endPage":"305","numberOfPages":"11","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-055181","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":472295,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1175/jhm-d-14-0049.1","text":"Publisher Index Page"},{"id":306506,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"16","issue":"1","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2015-02-04","publicationStatus":"PW","scienceBaseUri":"57f7ef86e4b0bc0bec09f1a4","contributors":{"authors":[{"text":"McNally, Amy","contributorId":145810,"corporation":false,"usgs":false,"family":"McNally","given":"Amy","email":"","affiliations":[{"id":16236,"text":"UCSB Climate Hazards Group","active":true,"usgs":false}],"preferred":false,"id":565400,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gregory J. Husak","contributorId":145824,"corporation":false,"usgs":false,"family":"Gregory J. Husak","affiliations":[{"id":16245,"text":"Department of Geography and Climate Hazards Group, University of California, Santa Barbara, CA, USA","active":true,"usgs":false}],"preferred":false,"id":565401,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brown, Molly","contributorId":145825,"corporation":false,"usgs":false,"family":"Brown","given":"Molly","affiliations":[{"id":16246,"text":"Biospheric Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD, USA","active":true,"usgs":false}],"preferred":false,"id":565402,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Carroll, Mark L.","contributorId":145826,"corporation":false,"usgs":false,"family":"Carroll","given":"Mark","email":"","middleInitial":"L.","affiliations":[{"id":16246,"text":"Biospheric Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD, USA","active":true,"usgs":false},{"id":16247,"text":"Sigma Space Corp, NASA Goddard Space Flight Center, Greenbelt, MD, USA","active":true,"usgs":false},{"id":7239,"text":"Science Systems and Applications, Inc.","active":true,"usgs":false}],"preferred":false,"id":565403,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Funk, Christopher C. 0000-0002-9254-6718 cfunk@usgs.gov","orcid":"https://orcid.org/0000-0002-9254-6718","contributorId":721,"corporation":false,"usgs":true,"family":"Funk","given":"Christopher","email":"cfunk@usgs.gov","middleInitial":"C.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":565404,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Soni Yatheendradas","contributorId":145828,"corporation":false,"usgs":false,"family":"Soni Yatheendradas","affiliations":[{"id":16248,"text":"Hydrologic Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD, USA","active":true,"usgs":false}],"preferred":false,"id":565406,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Arsenault, Kristi","contributorId":145829,"corporation":false,"usgs":false,"family":"Arsenault","given":"Kristi","email":"","affiliations":[{"id":16248,"text":"Hydrologic Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD, USA","active":true,"usgs":false}],"preferred":false,"id":565407,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Christa Peters-Lidard","contributorId":116524,"corporation":false,"usgs":true,"family":"Christa Peters-Lidard","affiliations":[],"preferred":false,"id":565408,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Verdin, James 0000-0003-0238-9657 verdin@usgs.gov","orcid":"https://orcid.org/0000-0003-0238-9657","contributorId":145830,"corporation":false,"usgs":true,"family":"Verdin","given":"James","email":"verdin@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":565409,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70157523,"text":"70157523 - 2015 - An integrated Riverine Environmental Flow Decision Support System (REFDSS) to evaluate the ecological effects of alternative flow scenarios on river ecosystems","interactions":[],"lastModifiedDate":"2017-07-21T14:50:38","indexId":"70157523","displayToPublicDate":"2015-02-01T12:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5004,"text":"Fundamental and Applied Limnology","active":true,"publicationSubtype":{"id":10}},"title":"An integrated Riverine Environmental Flow Decision Support System (REFDSS) to evaluate the ecological effects of alternative flow scenarios on river ecosystems","docAbstract":"In regulated rivers, managers must evaluate competing flow release scenarios that attempt to balance both human and natural needs. Meeting these natural flow needs is complex due to the myriad of interacting physical and hydrological factors that affect ecosystems. Tools that synthesize the voluminous scientific data and models on these factors will facilitate management of these systems. Here, we present the Riverine Environmental Flow Decision Support System (REFDSS), a tool that enables evaluation of competing flow scenarios and other variables on instream habitat. We developed a REFDSS for the Upper Delaware River, USA, a system that is regulated by three headwater reservoirs. This version of the REFDSS has the ability to integrate any set of spatially explicit data and synthesizes modeled discharge for three competing management scenarios, flow-specific 2-D hydrodynamic modeled estimates of local hydrologic conditions (e.g., depth, velocity, shear stress, etc.) at a fine pixel-scale (1 m2), and habitat suitability criteria (HSC) for a variety of taxa. It contains all individual model outputs, computationally integrates these data, and outputs the amount of potentially available habitat for a suite of species of interest under each flow release scenario. Users have the flexibility to change the time period of interest and vary the HSC. The REFDSS was developed to enable side-by-side evaluation of different flow management scenarios and their effects on potential habitat availability, allowing managers to make informed decisions on the best flow scenarios. An exercise comparing two alternative flow scenarios to a baseline scenario for several key species is presented. The Upper Delaware REFDSS was robust to minor changes in HSC (± 10 %). The general REFDSS platform was developed as a user-friendly Windows desktop application that was designed to include other potential parameters of interest (e.g., temperature) and for transferability to other riverine systems.
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boreal winter","docAbstract":"Southwestern Asia, defined here as the domain bounded by 20°–40°N and 40°–70°E, which includes the nations of Iraq, Iran, Afghanistan, and Pakistan, is a water-stressed and semiarid region that receives roughly 75% of its annual rainfall during November–April. The November–April climate of southwestern Asia is strongly influenced by tropical Indo-Pacific variability on intraseasonal and interannual time scales, much of which can be attributed to sea surface temperature (SST) variations. The influences of lower-frequency SST variability on southwestern Asia climate during November–April Pacific decadal SST (PDSST) variability and the long-term trend in SST (LTSST) is examined. The U.S. Climate Variability and Predictability Program (CLIVAR) Drought Working Group forced global atmospheric climate models with PDSST and LTSST patterns, identified using empirical orthogonal functions, to show the steady atmospheric response to these modes of decadal to multidecadal SST variability. During November–April, LTSST forces an anticyclone over southwestern Asia, which results in reduced precipitation and increases in surface temperature. The precipitation and tropospheric circulation influences of LTSST are corroborated by independent observed precipitation and circulation datasets during 1901–2004. The decadal variations of southwestern Asia precipitation may be forced by PDSST variability, with two of the three models indicating that the cold phase of PDSST forces an anticyclone and precipitation reductions. However, there are intermodel circulation variations to PDSST that influence subregional precipitation patterns over the Middle East, southwestern Asia, and subtropical Asia. Changes in wintertime temperature and precipitation over southwestern Asia forced by LTSST and PDSST imply important changes to the land surface hydrology during the spring and summer.
","language":"English","publisher":"American Meteorological Society","publisherLocation":"Boston, MA","doi":"10.1175/JCLI-D-14-00344.1","usgsCitation":"Hoell, A., Funk, C.C., and Barlow, M., 2015, The forcing of southwestern Asia teleconnections by low-frequency sea surface temperature variability during boreal winter: Journal of Climate, v. 28, no. 4, p. 1511-1526, https://doi.org/10.1175/JCLI-D-14-00344.1.","productDescription":"16 p.","startPage":"1511","endPage":"1526","numberOfPages":"16","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-058649","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":472296,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1175/jcli-d-14-00344.1","text":"Publisher Index Page"},{"id":306490,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"28","issue":"4","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2015-02-11","publicationStatus":"PW","scienceBaseUri":"57f7ef86e4b0bc0bec09f1a6","contributors":{"authors":[{"text":"Hoell, Andrew","contributorId":145805,"corporation":false,"usgs":false,"family":"Hoell","given":"Andrew","affiliations":[{"id":16236,"text":"UCSB Climate Hazards Group","active":true,"usgs":false}],"preferred":false,"id":565418,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Funk, Christopher C. 0000-0002-9254-6718 cfunk@usgs.gov","orcid":"https://orcid.org/0000-0002-9254-6718","contributorId":721,"corporation":false,"usgs":true,"family":"Funk","given":"Christopher","email":"cfunk@usgs.gov","middleInitial":"C.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":565417,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barlow, Mathew","contributorId":145832,"corporation":false,"usgs":false,"family":"Barlow","given":"Mathew","email":"","affiliations":[{"id":16249,"text":"UMASS Lowel","active":true,"usgs":false}],"preferred":false,"id":565419,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70148672,"text":"70148672 - 2015 - Sources of endocrine-disrupting compounds in North Carolina waterways: a geographic information systems approach","interactions":[],"lastModifiedDate":"2015-06-19T10:52:23","indexId":"70148672","displayToPublicDate":"2015-02-01T12:00:00","publicationYear":"2015","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":"Sources of endocrine-disrupting compounds in North Carolina waterways: a geographic information systems approach","docAbstract":"The presence of endocrine-disrupting compounds (EDCs), particularly estrogenic compounds, in the environment has drawn public attention across the globe, yet a clear understanding of the extent and distribution of estrogenic EDCs in surface waters and their relationship to potential sources is lacking. The objective of the present study was to identify and examine the potential input of estrogenic EDC sources in North Carolina water bodies using a geographic information system (GIS) mapping and analysis approach. Existing data from state and federal agencies were used to create point and nonpoint source maps depicting the cumulative contribution of potential sources of estrogenic EDCs to North Carolina surface waters. Water was collected from 33 sites (12 associated with potential point sources, 12 associated with potential nonpoint sources, and 9 reference), to validate the predictive results of the GIS analysis. Estrogenicity (measured as 17β-estradiol equivalence) ranged from 0.06 ng/L to 56.9 ng/L. However, the majority of sites (88%) had water 17β-estradiol concentrations below 1 ng/L. Sites associated with point and nonpoint sources had significantly higher 17β-estradiol levels than reference sites. The results suggested that water 17β-estradiol was reflective of GIS predictions, confirming the relevance of landscape-level influences on water quality and validating the GIS approach to characterize such relationships.
","language":"English","publisher":"Elsevier Science","publisherLocation":"Amsterdam","doi":"10.1002/etc.2797","collaboration":"North Carolina Wildlife Resources Commission (NCWRC); North Carolina State University; US Geological Survey; US Fish and Wildlife Service; Wildlife Management Institute","usgsCitation":"Sackett, D.K., Pow, C.L., Rubino, M.J., Aday, D., Cope, W., Kullman, S.W., Rice, J., Kwak, T.J., and Law, L.M., 2015, Sources of endocrine-disrupting compounds in North Carolina waterways: a geographic information systems approach: Environmental Toxicology and Chemistry, v. 34, no. 2, p. 437-445, https://doi.org/10.1002/etc.2797.","productDescription":"9 p.","startPage":"437","endPage":"445","numberOfPages":"9","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-055607","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":301357,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"34","issue":"2","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2014-11-05","publicationStatus":"PW","scienceBaseUri":"55853d5be4b023124e8f5b47","contributors":{"authors":[{"text":"Sackett, Dana K.","contributorId":141232,"corporation":false,"usgs":false,"family":"Sackett","given":"Dana","email":"","middleInitial":"K.","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":549008,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pow, Crystal Lee","contributorId":141233,"corporation":false,"usgs":false,"family":"Pow","given":"Crystal","email":"","middleInitial":"Lee","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":549009,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rubino, Matthew J. 0000-0003-0651-3053","orcid":"https://orcid.org/0000-0003-0651-3053","contributorId":141234,"corporation":false,"usgs":false,"family":"Rubino","given":"Matthew","email":"","middleInitial":"J.","affiliations":[{"id":39327,"text":"North Carolina Cooperative Fish and Wildlife Research Unit, Department of Applied Ecology, North Carolina State Univ.","active":true,"usgs":false}],"preferred":false,"id":549010,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Aday, D.D.","contributorId":75356,"corporation":false,"usgs":true,"family":"Aday","given":"D.D.","email":"","affiliations":[],"preferred":false,"id":549011,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cope, W. Gregory","contributorId":70353,"corporation":false,"usgs":true,"family":"Cope","given":"W. Gregory","affiliations":[],"preferred":false,"id":549012,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kullman, Seth W.","contributorId":62516,"corporation":false,"usgs":true,"family":"Kullman","given":"Seth","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":549013,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rice, J. A.","contributorId":101217,"corporation":false,"usgs":true,"family":"Rice","given":"J.","middleInitial":"A.","affiliations":[],"preferred":false,"id":549014,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kwak, Thomas J. 0000-0002-0616-137X tkwak@usgs.gov","orcid":"https://orcid.org/0000-0002-0616-137X","contributorId":834,"corporation":false,"usgs":true,"family":"Kwak","given":"Thomas","email":"tkwak@usgs.gov","middleInitial":"J.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":549015,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Law, LeRoy M.","contributorId":104603,"corporation":false,"usgs":true,"family":"Law","given":"LeRoy","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":549016,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70164451,"text":"70164451 - 2015 - Seasonal patterns in stream periphyton fatty acids and community benthic algal composition in six high quality headwater streams","interactions":[],"lastModifiedDate":"2017-07-21T14:54:16","indexId":"70164451","displayToPublicDate":"2015-02-01T11:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1919,"text":"Hydrobiologia","onlineIssn":"1573-5117","printIssn":"0018-8158","active":true,"publicationSubtype":{"id":10}},"title":"Seasonal patterns in stream periphyton fatty acids and community benthic algal composition in six high quality headwater streams","docAbstract":"Fatty acids are integral components of periphyton and differ among algal taxa. We examined seasonal patterns in periphyton fatty acids in six minimally disturbed headwater streams in Pennsylvania’s Appalachian Mountains, USA. Environmental data and periphyton were collected across four seasons for fatty acid and algal taxa content. Non-metric multidimensional scaling ordination suggested significant seasonal differences in fatty acids; an ordination on algal composition revealed similar seasonal patterns, but with slightly weaker separation of summer and fall. Summer and fall fatty acid profiles were driven by temperature, overstory cover, and conductivity and winter profiles by measures of stream size. Ordination on algal composition suggested that summer and fall communities were driven by overstory and temperature, whereas winter communities were driven by velocity. The physiologically important fatty acid 18:3ω6 was highest in summer and fall. Winter samples had the highest 20:3ω3. Six saturated fatty acids differed among the seasons. Periphyton fatty acids profiles appeared to reflect benthic algal species composition. This suggests that periphyton fatty acid composition can be useful in characterizing basal food resources and stream water quality.
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Heaton","interactions":[],"lastModifiedDate":"2015-05-05T10:06:26","indexId":"70147363","displayToPublicDate":"2015-02-01T11:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Comment on “Models of stochastic, spatially varying stress in the crust compatible with focal‐mechanism data, and how stress inversions can be biased toward the stress rate” by Deborah Elaine Smith and Thomas H. Heaton","docAbstract":"Smith and Heaton (2011) propose a model in which stress in the crust is fractal‐like and highly variable on a range of length scales, including short length‐scales of ~1 km. Smith and Heaton (2011) motivate the need for stress heterogeneity on short length‐scales by citing observations such as short length‐scale changes in stress directions inferred from borehole breakouts, short length‐scale changes in earthquake slip, and the success of numerical models that include short‐wavelength stress heterogeneity. The heterogeneous part of the stress field in their model is more than twice as large as the homogeneous part. The stress field in this model frequently reverses itself over short distances, as can be seen in figure14 a of Smith and Heaton (2011). The modeled stress field contains at least 10 areas of reversed shear stress direction over the length of a 100 km long profile, with the length of the reversed areas ranging from <1 to ~5 km.
\nThis model makes specific predictions about the orientations and heterogeneity of earthquake focal mechanisms. Smith and Heaton (2011) attempt to validate this heterogeneous stress model using observations of earthquake focal‐mechanism variability from Hardebeck (2006). They then demonstrate that the model predicts a bias in the orientations of earthquake focal mechanisms, which are biased away from the background stress and toward the stressing rate. They suggest the focal‐mechanism bias in this model invalidates the large body of work over the last several decades, that has inferred stress orientations from the inversion of earthquake focal mechanisms. The question of whether or not the Smith and Heaton (2011) model is applicable to the real Earth is therefore important not only for understanding spatial stress variability but also for evaluating the numerous studies that have inferred crustal stress orientations from earthquake focal mechanisms (e.g., as compiled by Heidbach et al., 2008).
","language":"English","publisher":"Seismological Society of America","publisherLocation":"Stanford, CA","doi":"10.1785/0120130127","usgsCitation":"Hardebeck, J.L., 2015, Comment on “Models of stochastic, spatially varying stress in the crust compatible with focal‐mechanism data, and how stress inversions can be biased toward the stress rate” by Deborah Elaine Smith and Thomas H. Heaton: Bulletin of the Seismological Society of America, v. 105, no. 1, p. 447-451, https://doi.org/10.1785/0120130127.","productDescription":"5 p.","startPage":"447","endPage":"451","numberOfPages":"5","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-045509","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":300085,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"105","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-01-13","publicationStatus":"PW","scienceBaseUri":"5549e9b4e4b064e4207ca432","contributors":{"authors":[{"text":"Hardebeck, Jeanne L. 0000-0002-6737-7780 jhardebeck@usgs.gov","orcid":"https://orcid.org/0000-0002-6737-7780","contributorId":841,"corporation":false,"usgs":true,"family":"Hardebeck","given":"Jeanne","email":"jhardebeck@usgs.gov","middleInitial":"L.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":true,"id":545856,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70141763,"text":"70141763 - 2015 - Ephemeral stream reaches preserve the evolutionary and distributional history of threespine stickleback in the Santa Clara and Ventura River watersheds of southern California","interactions":[],"lastModifiedDate":"2015-02-23T09:32:27","indexId":"70141763","displayToPublicDate":"2015-02-01T10:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1324,"text":"Conservation Genetics","active":true,"publicationSubtype":{"id":10}},"title":"Ephemeral stream reaches preserve the evolutionary and distributional history of threespine stickleback in the Santa Clara and Ventura River watersheds of southern California","docAbstract":"Much remains to be understood about the evolutionary history and contemporary landscape genetics of unarmored threespine stickleback in southern California, where populations collectively referred to as Gasterosteus aculeatus williamsoni have severely declined over the past 70+ years and are now endangered. We used mitochondrial sequence and microsatellite data to assess the population genetics and phylogeography of unarmored populations sampled immediately downstream from the type locality of G. a. williamsoni in the upper Santa Clara River, and assessed their distinctiveness with respect to low-armor populations in the downstream sections of the river and the adjacent Ventura River. We also characterized the geographic limits of different plate morphs and evaluated the congruence of those boundaries with barriers to dispersal in both river systems and to neutral genetic variation. We show substantial population structuring within the upper reach of the Santa Clara River, but little partitioning between the lower Santa Clara and Ventura Rivers—we attribute these patterns to different ancestry between spatially subdivided populations within the same drainage, a predominance of downstream gene flow, and ability for coastal dispersal between the Santa Clara and Ventura Rivers. We also show that alleles from introduced low-plate stock have infiltrated a native population in at least one upper Santa Clara River tributary, causing this formerly unarmored population to become gradually low-plated over a 30 + year time period. Measures of genetic diversity, census surveys, and severe habitat disturbance all indicate that unarmored stickleback near the type locality are currently at high risk of extinction.
","language":"English","publisher":"Kluwer Academic Publishers","publisherLocation":"Dordrecht","doi":"10.1007/s10592-014-0643-7","usgsCitation":"Richmond, J.Q., Jacobs, D.K., Backlin, A.R., Swift, C.C., Dellith, C., and Fisher, R.N., 2015, Ephemeral stream reaches preserve the evolutionary and distributional history of threespine stickleback in the Santa Clara and Ventura River watersheds of southern California: Conservation Genetics, v. 16, no. 1, p. 85-101, https://doi.org/10.1007/s10592-014-0643-7.","productDescription":"17 p.","startPage":"85","endPage":"101","numberOfPages":"17","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-058303","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":298096,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"Santa Clara","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.02308654785156,\n 37.21392518793643\n ],\n [\n -122.02308654785156,\n 37.41107339721063\n ],\n [\n -121.85142517089844,\n 37.41107339721063\n ],\n [\n -121.85142517089844,\n 37.21392518793643\n ],\n [\n -122.02308654785156,\n 37.21392518793643\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"16","issue":"1","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2014-08-08","publicationStatus":"PW","scienceBaseUri":"54ec5d41e4b02d776a67daa7","contributors":{"authors":[{"text":"Richmond, Jonathan Q. 0000-0001-9398-4894 jrichmond@usgs.gov","orcid":"https://orcid.org/0000-0001-9398-4894","contributorId":5400,"corporation":false,"usgs":true,"family":"Richmond","given":"Jonathan","email":"jrichmond@usgs.gov","middleInitial":"Q.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":541025,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jacobs, David K.","contributorId":139394,"corporation":false,"usgs":false,"family":"Jacobs","given":"David","email":"","middleInitial":"K.","affiliations":[{"id":12763,"text":"University of California, Los Angeles","active":true,"usgs":false}],"preferred":false,"id":541026,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Backlin, Adam R. 0000-0001-5618-8426 abacklin@usgs.gov","orcid":"https://orcid.org/0000-0001-5618-8426","contributorId":3802,"corporation":false,"usgs":true,"family":"Backlin","given":"Adam","email":"abacklin@usgs.gov","middleInitial":"R.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":541027,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Swift, Camm C.","contributorId":139395,"corporation":false,"usgs":false,"family":"Swift","given":"Camm","email":"","middleInitial":"C.","affiliations":[{"id":12725,"text":"Natural History Museum of Los Angeles County","active":true,"usgs":false}],"preferred":false,"id":541028,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dellith, Chris","contributorId":139396,"corporation":false,"usgs":false,"family":"Dellith","given":"Chris","email":"","affiliations":[{"id":6678,"text":"U.S. Fish and Wildlife Service, Alaska Maritime National Wildlife Refuge","active":true,"usgs":false}],"preferred":false,"id":541029,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fisher, Robert N. 0000-0002-2956-3240 rfisher@usgs.gov","orcid":"https://orcid.org/0000-0002-2956-3240","contributorId":1529,"corporation":false,"usgs":true,"family":"Fisher","given":"Robert","email":"rfisher@usgs.gov","middleInitial":"N.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":541024,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70147980,"text":"70147980 - 2015 - Spatial genetic structure of bristle-thighed curlews (Numenius tahitiensis): Breeding area differentiation not reflected on the non-breeding grounds","interactions":[],"lastModifiedDate":"2018-08-21T13:10:04","indexId":"70147980","displayToPublicDate":"2015-02-01T10:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1324,"text":"Conservation Genetics","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Spatial genetic structure of bristle-thighed curlews (Numenius tahitiensis): Breeding area differentiation not reflected on the non-breeding grounds","title":"Spatial genetic structure of bristle-thighed curlews (Numenius tahitiensis): Breeding area differentiation not reflected on the non-breeding grounds","docAbstract":"Migratory birds occupy geographically and ecologically disparate areas during their annual cycle with conditions on breeding and non-breeding grounds playing separate and important roles in population dynamics. We used data from nuclear microsatellite and mitochondrial DNA control region loci to assess the breeding and non-breeding spatial genetic structure of a transoceanic migrant shorebird, the bristle-thighed curlew. We found spatial variance in the distribution of allelic and haplotypic frequencies between the curlew's two breeding areas in Alaska but did not observe this spatial structure throughout its non-breeding range on low-lying tropical and subtropical islands in the Central Pacific (Oceania). This suggests that the two breeding populations do not spatially segregate during the non-breeding season. Lack of migratory connectivity is likely attributable to the species' behavior, as bristle-thighed curlews exhibit differential timing of migration and some individuals move among islands during non-breeding months. Given the detrimental impact of many past and current human activities on island ecosystems, admixture of breeding populations in Oceania may render the bristle-thighed curlew less vulnerable to perturbations there, as neither breeding population will be disproportionally affected by local habitat losses or by stochastic events. Furthermore, lack of migratory connectivity may enable bristle-thighed curlews to respond to changing island ecosystems by altering their non-breeding distribution. However, availability of suitable non-breeding habitat for curlews in Oceania is increasingly limited on both low-lying and high islands by habitat loss, sea level rise, and invasive mammalian predators that pose a threat to flightless and flight-compromised curlews during the molting period.
","language":"English","publisher":"Kluwer Academic Publishers","publisherLocation":"Dordrecht","doi":"10.1007/s10592-014-0654-4","usgsCitation":"Sonsthagen, S.A., Tibbitts, T.L., Gill, R., Williams, I.S., and Talbot, S.L., 2015, Spatial genetic structure of bristle-thighed curlews (Numenius tahitiensis): Breeding area differentiation not reflected on the non-breeding grounds: Conservation Genetics, v. 16, no. 1, p. 223-233, https://doi.org/10.1007/s10592-014-0654-4.","productDescription":"11 p.","startPage":"223","endPage":"233","numberOfPages":"11","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-055300","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":438726,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7WS8RB7","text":"USGS data release","linkHelpText":"Data from Bristle-Thighed Curlews at James Campbell National Wildlife Refuge, O'ahu, Hawaii, 2012-2014"},{"id":300264,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"16","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2014-09-16","publicationStatus":"PW","scienceBaseUri":"5551d2bbe4b0a92fa7e93c0e","contributors":{"authors":[{"text":"Sonsthagen, Sarah A. 0000-0001-6215-5874 ssonsthagen@usgs.gov","orcid":"https://orcid.org/0000-0001-6215-5874","contributorId":3711,"corporation":false,"usgs":true,"family":"Sonsthagen","given":"Sarah","email":"ssonsthagen@usgs.gov","middleInitial":"A.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":546519,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tibbitts, T. Lee 0000-0002-0290-7592 ltibbitts@usgs.gov","orcid":"https://orcid.org/0000-0002-0290-7592","contributorId":140455,"corporation":false,"usgs":true,"family":"Tibbitts","given":"T.","email":"ltibbitts@usgs.gov","middleInitial":"Lee","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":false,"id":546537,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gill, Robert E. Jr. 0000-0002-6385-4500 rgill@usgs.gov","orcid":"https://orcid.org/0000-0002-6385-4500","contributorId":171747,"corporation":false,"usgs":true,"family":"Gill","given":"Robert E.","suffix":"Jr.","email":"rgill@usgs.gov","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":546538,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Williams, Ian S.","contributorId":77439,"corporation":false,"usgs":true,"family":"Williams","given":"Ian","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":546539,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Talbot, Sandra L. 0000-0002-3312-7214 stalbot@usgs.gov","orcid":"https://orcid.org/0000-0002-3312-7214","contributorId":140512,"corporation":false,"usgs":true,"family":"Talbot","given":"Sandra","email":"stalbot@usgs.gov","middleInitial":"L.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":546540,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70145827,"text":"70145827 - 2015 - Integrated survival analysis using an event-time approach in a Bayesian framework","interactions":[],"lastModifiedDate":"2015-04-13T09:31:55","indexId":"70145827","displayToPublicDate":"2015-02-01T10:30:00","publicationYear":"2015","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":"Integrated survival analysis using an event-time approach in a Bayesian framework","docAbstract":"Event-time or continuous-time statistical approaches have been applied throughout the biostatistical literature and have led to numerous scientific advances. However, these techniques have traditionally relied on knowing failure times. This has limited application of these analyses, particularly, within the ecological field where fates of marked animals may be unknown. To address these limitations, we developed an integrated approach within a Bayesian framework to estimate hazard rates in the face of unknown fates. We combine failure/survival times from individuals whose fates are known and times of which are interval-censored with information from those whose fates are unknown, and model the process of detecting animals with unknown fates. This provides the foundation for our integrated model and permits necessary parameter estimation. We provide the Bayesian model, its derivation, and use simulation techniques to investigate the properties and performance of our approach under several scenarios. Lastly, we apply our estimation technique using a piece-wise constant hazard function to investigate the effects of year, age, chick size and sex, sex of the tending adult, and nesting habitat on mortality hazard rates of the endangered mountain plover (Charadrius montanus) chicks. Traditional models were inappropriate for this analysis because fates of some individual chicks were unknown due to failed radio transmitters. Simulations revealed biases of posterior mean estimates were minimal (≤ 4.95%), and posterior distributions behaved as expected with RMSE of the estimates decreasing as sample sizes, detection probability, and survival increased. We determined mortality hazard rates for plover chicks were highest at <5 days old and were lower for chicks with larger birth weights and/or whose nest was within agricultural habitats. Based on its performance, our approach greatly expands the range of problems for which event-time analyses can be used by eliminating the need for having completely known fate data.
","language":"English","publisher":"Blackwell Pub. Ltd.","publisherLocation":"Oxford, England","doi":"10.1002/ece3.1399","usgsCitation":"Walsh, D.P., Dreitz, V., and Heisey, D.M., 2015, Integrated survival analysis using an event-time approach in a Bayesian framework: Ecology and Evolution, v. 5, no. 3, p. 769-780, https://doi.org/10.1002/ece3.1399.","productDescription":"12 p.","startPage":"769","endPage":"780","numberOfPages":"12","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061696","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":472299,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.1399","text":"Publisher Index Page"},{"id":299601,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"5","issue":"3","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2015-01-17","publicationStatus":"PW","scienceBaseUri":"552ce8b8e4b0b22a157f50b5","chorus":{"doi":"10.1002/ece3.1399","url":"http://dx.doi.org/10.1002/ece3.1399","publisher":"Wiley-Blackwell","authors":"Walsh Daniel P., Dreitz Victoria J., Heisey Dennis M.","journalName":"Ecology and Evolution","publicationDate":"1/17/2015","auditedOn":"3/17/2016"},"contributors":{"authors":[{"text":"Walsh, Daniel P. 0000-0002-7772-2445 dwalsh@usgs.gov","orcid":"https://orcid.org/0000-0002-7772-2445","contributorId":4758,"corporation":false,"usgs":true,"family":"Walsh","given":"Daniel","email":"dwalsh@usgs.gov","middleInitial":"P.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":544448,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dreitz, VJ","contributorId":140149,"corporation":false,"usgs":false,"family":"Dreitz","given":"VJ","email":"","affiliations":[{"id":5097,"text":"University of Montana, Division of Biological Sciences","active":true,"usgs":false}],"preferred":false,"id":544449,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Heisey, Dennis M. dheisey@usgs.gov","contributorId":2455,"corporation":false,"usgs":true,"family":"Heisey","given":"Dennis","email":"dheisey@usgs.gov","middleInitial":"M.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":544450,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70148079,"text":"70148079 - 2015 - An open-population hierarchical distance sampling model","interactions":[],"lastModifiedDate":"2015-05-19T09:05:34","indexId":"70148079","displayToPublicDate":"2015-02-01T10:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"An open-population hierarchical distance sampling model","docAbstract":"Modeling population dynamics while accounting for imperfect detection is essential to monitoring programs. Distance sampling allows estimating population size while accounting for imperfect detection, but existing methods do not allow for direct estimation of demographic parameters. We develop a model that uses temporal correlation in abundance arising from underlying population dynamics to estimate demographic parameters from repeated distance sampling surveys. Using a simulation study motivated by designing a monitoring program for island scrub-jays (Aphelocoma insularis), we investigated the power of this model to detect population trends. We generated temporally autocorrelated abundance and distance sampling data over six surveys, using population rates of change of 0.95 and 0.90. We fit the data generating Markovian model and a mis-specified model with a log-linear time effect on abundance, and derived post hoc trend estimates from a model estimating abundance for each survey separately. We performed these analyses for varying number of survey points. Power to detect population changes was consistently greater under the Markov model than under the alternatives, particularly for reduced numbers of survey points. The model can readily be extended to more complex demographic processes than considered in our simulations. This novel framework can be widely adopted for wildlife population monitoring.
","language":"English","publisher":"Ecological Society of America","publisherLocation":"Brooklyn, NY","doi":"10.1890/14-1625.1","usgsCitation":"Sollmann, R., Gardner, B., Chandler, R.B., Royle, J.A., and Sillett, T.S., 2015, An open-population hierarchical distance sampling model: Ecology, v. 96, no. 2, p. 325-331, https://doi.org/10.1890/14-1625.1.","productDescription":"7 p.","startPage":"325","endPage":"331","numberOfPages":"7","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060570","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":472301,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1890/14-1625.1","text":"Publisher Index Page"},{"id":300528,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"96","issue":"2","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"555c5eb0e4b0a92fa7eacbf2","contributors":{"authors":[{"text":"Sollmann, Rachel","contributorId":11909,"corporation":false,"usgs":true,"family":"Sollmann","given":"Rachel","email":"","affiliations":[],"preferred":false,"id":547190,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gardner, Beth","contributorId":140853,"corporation":false,"usgs":true,"family":"Gardner","given":"Beth","email":"","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":547191,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chandler, Richard B rchandler@usgs.gov","contributorId":140854,"corporation":false,"usgs":false,"family":"Chandler","given":"Richard","email":"rchandler@usgs.gov","middleInitial":"B","affiliations":[{"id":13596,"text":"Univ. Georgia","active":true,"usgs":false}],"preferred":false,"id":547192,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":139626,"corporation":false,"usgs":true,"family":"Royle","given":"J.","email":"aroyle@usgs.gov","middleInitial":"Andrew","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":547189,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sillett, T Scott","contributorId":140855,"corporation":false,"usgs":false,"family":"Sillett","given":"T","email":"","middleInitial":"Scott","affiliations":[{"id":13597,"text":"Smithsonian Institude","active":true,"usgs":false}],"preferred":false,"id":547193,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70176621,"text":"70176621 - 2015 - Genetic diversity and host specificity varies across three genera of blood parasites in ducks of the Pacific Americas Flyway","interactions":[],"lastModifiedDate":"2018-08-16T21:28:57","indexId":"70176621","displayToPublicDate":"2015-02-01T00:00:00","publicationYear":"2015","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":"Genetic diversity and host specificity varies across three genera of blood parasites in ducks of the Pacific Americas Flyway","docAbstract":"Birds of the order Anseriformes, commonly referred to as waterfowl, are frequently infected by Haemosporidia of the genera Haemoproteus, Plasmodium, and Leucocytozoon via dipteran vectors. We analyzed nucleotide sequences of the Cytochrome b (Cytb) gene from parasites of these genera detected in six species of ducks from Alaska and California, USA to characterize the genetic diversity of Haemosporidia infecting waterfowl at two ends of the Pacific Americas Flyway. In addition, parasite Cytb sequences were compared to those available on a public database to investigate specificity of genetic lineages to hosts of the order Anseriformes. Haplotype and nucleotide diversity of Haemoproteus Cytb sequences was lower than was detected for Plasmodium and Leucocytozoon parasites. Although waterfowl are presumed to be infected by only a single species of Leucocytozoon, L. simondi, diversity indices were highest for haplotypes from this genus and sequences formed five distinct clades separated by genetic distances of 4.9%–7.6%, suggesting potential cryptic speciation. All Haemoproteus andLeucocytozoon haplotypes derived from waterfowl samples formed monophyletic clades in phylogenetic analyses and were unique to the order Anseriformes with few exceptions. In contrast, waterfowl-origin Plasmodium haplotypes were identical or closely related to lineages found in other avian orders. Our results suggest a more generalist strategy for Plasmodiumparasites infecting North American waterfowl as compared to those of the generaHaemoproteus and Leucocytozoon.
","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0116661","usgsCitation":"Reeves, A.B., Smith, M.M., Meixell, B.W., Fleskes, J.P., and Ramey, A.M., 2015, Genetic diversity and host specificity varies across three genera of blood parasites in ducks of the Pacific Americas Flyway: PLoS ONE, v. 10, no. 2, e0116661; 15 p., https://doi.org/10.1371/journal.pone.0116661.","productDescription":"e0116661; 15 p.","ipdsId":"IP-059454","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":472310,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0116661","text":"Publisher Index Page"},{"id":328891,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","issue":"2","noUsgsAuthors":false,"publicationDate":"2015-02-24","publicationStatus":"PW","scienceBaseUri":"57f7ee45e4b0bc0bec09e977","contributors":{"authors":[{"text":"Reeves, Andrew B. 0000-0002-7526-0726 areeves@usgs.gov","orcid":"https://orcid.org/0000-0002-7526-0726","contributorId":167362,"corporation":false,"usgs":true,"family":"Reeves","given":"Andrew","email":"areeves@usgs.gov","middleInitial":"B.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":649402,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, Matthew M. 0000-0002-2259-5135 mmsmith@usgs.gov","orcid":"https://orcid.org/0000-0002-2259-5135","contributorId":5115,"corporation":false,"usgs":true,"family":"Smith","given":"Matthew","email":"mmsmith@usgs.gov","middleInitial":"M.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":649403,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Meixell, Brandt W. 0000-0002-6738-0349 bmeixell@usgs.gov","orcid":"https://orcid.org/0000-0002-6738-0349","contributorId":138716,"corporation":false,"usgs":true,"family":"Meixell","given":"Brandt","email":"bmeixell@usgs.gov","middleInitial":"W.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":649404,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fleskes, Joseph P. 0000-0001-5388-6675 joe_fleskes@usgs.gov","orcid":"https://orcid.org/0000-0001-5388-6675","contributorId":1889,"corporation":false,"usgs":true,"family":"Fleskes","given":"Joseph","email":"joe_fleskes@usgs.gov","middleInitial":"P.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":649405,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ramey, Andrew M. 0000-0002-3601-8400 aramey@usgs.gov","orcid":"https://orcid.org/0000-0002-3601-8400","contributorId":1872,"corporation":false,"usgs":true,"family":"Ramey","given":"Andrew","email":"aramey@usgs.gov","middleInitial":"M.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":649406,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70148005,"text":"70148005 - 2015 - The cost of reproduction: differential resource specialization in female and male California sea otters","interactions":[],"lastModifiedDate":"2017-11-17T16:43:00","indexId":"70148005","displayToPublicDate":"2015-02-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2932,"text":"Oecologia","active":true,"publicationSubtype":{"id":10}},"title":"The cost of reproduction: differential resource specialization in female and male California sea otters","docAbstract":"Intraspecific variation in behavior and diet can have important consequences for population and ecosystem dynamics. 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Consistent with our hypothesis, increasing population density is associated with increased individual diet specialization by females but not by males. Additionally, we find the amount of coastline in a sea otter’s home range positively related with individual dietary variability, with increased range span resulting in weaker specialization for both males and females. We attribute our results to sex-based differences in movement, with females needing to specialize in their small ranges to maximize energy gain, and posit that the paradigm of individual prey specialization in sea otters with increased intraspecific competition may be a pattern driven largely by females. Our work highlights a potentially broader role of sex in the mechanistic pressures promoting and maintaining diet specialization.
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Tim 0000-0002-3314-839X ttinker@usgs.gov","orcid":"https://orcid.org/0000-0002-3314-839X","contributorId":2796,"corporation":false,"usgs":true,"family":"Tinker","given":"M.","email":"ttinker@usgs.gov","middleInitial":"Tim","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":546737,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70127397,"text":"70127397 - 2015 - Vegetation burn severity mapping using Landsat-8 and WorldView-2","interactions":[],"lastModifiedDate":"2016-07-08T15:05:35","indexId":"70127397","displayToPublicDate":"2015-02-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3052,"text":"Photogrammetric Engineering and Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Vegetation burn severity mapping using Landsat-8 and WorldView-2","docAbstract":"We used remotely sensed data from the Landsat-8 and WorldView-2 satellites to estimate vegetation burn severity of the Creek Fire on the San Carlos Apache Reservation, where wildfire occurrences affect the Tribe's crucial livestock and logging industries. Accurate pre- and post-fire canopy maps at high (0.5-meter) resolution were created from World- View-2 data to generate canopy loss maps, and multiple indices from pre- and post-fire Landsat-8 images were used to evaluate vegetation burn severity. Normalized difference vegetation index based vegetation burn severity map had the highest correlation coefficients with canopy loss map from WorldView-2. Two distinct approaches - canopy loss mapping from WorldView-2 and spectral index differencing from Landsat-8 - agreed well with the field-based burn severity estimates and are both effective for vegetation burn severity mapping. Canopy loss maps created with WorldView-2 imagery add to a short list of accurate vegetation burn severity mapping techniques that can help guide effective management of forest resources on the San Carlos Apache Reservation, and the broader fire-prone regions of the Southwest.
","language":"English","publisher":"Ingenta Connect","doi":"10.14358/PERS.81.2.143","usgsCitation":"Wu, Z., Middleton, B.R., Hetzler, R., Vogel, J.M., and Dye, D.G., 2015, Vegetation burn severity mapping using Landsat-8 and WorldView-2: Photogrammetric Engineering and Remote Sensing, v. 2, p. 143-154, https://doi.org/10.14358/PERS.81.2.143.","productDescription":"12 p.","startPage":"143","endPage":"154","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-055282","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":472311,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.14358/pers.81.2.143","text":"Publisher Index Page"},{"id":324949,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5780cec2e4b0811616822402","contributors":{"authors":[{"text":"Wu, Zhuoting 0000-0001-7393-1832 zwu@usgs.gov","orcid":"https://orcid.org/0000-0001-7393-1832","contributorId":4953,"corporation":false,"usgs":true,"family":"Wu","given":"Zhuoting","email":"zwu@usgs.gov","affiliations":[{"id":498,"text":"Office of Land Remote Sensing (Geography)","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":519606,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Middleton, Barry R. 0000-0001-8924-4121 bmiddleton@usgs.gov","orcid":"https://orcid.org/0000-0001-8924-4121","contributorId":3947,"corporation":false,"usgs":true,"family":"Middleton","given":"Barry","email":"bmiddleton@usgs.gov","middleInitial":"R.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":519604,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hetzler, Robert","contributorId":117299,"corporation":false,"usgs":true,"family":"Hetzler","given":"Robert","affiliations":[],"preferred":false,"id":519607,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vogel, John M. 0000-0002-8226-1188 jvogel@usgs.gov","orcid":"https://orcid.org/0000-0002-8226-1188","contributorId":3167,"corporation":false,"usgs":true,"family":"Vogel","given":"John","email":"jvogel@usgs.gov","middleInitial":"M.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":519603,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dye, Dennis G. 0000-0002-7100-272X ddye@usgs.gov","orcid":"https://orcid.org/0000-0002-7100-272X","contributorId":4233,"corporation":false,"usgs":true,"family":"Dye","given":"Dennis","email":"ddye@usgs.gov","middleInitial":"G.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":519605,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70136575,"text":"70136575 - 2015 - Variations in community exposure to lahar hazards from multiple volcanoes in Washington State (USA)","interactions":[],"lastModifiedDate":"2021-02-11T17:46:39.981725","indexId":"70136575","displayToPublicDate":"2015-02-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3841,"text":"Journal of Applied Volcanology","active":true,"publicationSubtype":{"id":10}},"title":"Variations in community exposure to lahar hazards from multiple volcanoes in Washington State (USA)","docAbstract":"Understanding how communities are vulnerable to lahar hazards provides critical input for effective design and implementation of volcano hazard preparedness and mitigation strategies. Past vulnerability assessments have focused largely on hazards posed by a single volcano, even though communities and officials in many parts of the world must plan for and contend with hazards associated with multiple volcanoes. To better understand community vulnerability in regions with multiple volcanic threats, we characterize and compare variations in community exposure to lahar hazards associated with five active volcanoes in Washington State, USA—Mount Baker, Glacier Peak, Mount Rainier, Mount Adams and Mount St. Helens—each having the potential to generate catastrophic lahars that could strike communities tens of kilometers downstream. We use geospatial datasets that represent various population indicators (e.g., land cover, residents, employees, tourists) along with mapped lahar-hazard boundaries at each volcano to determine the distributions of populations within communities that occupy lahar-prone areas. We estimate that Washington lahar-hazard zones collectively contain 191,555 residents, 108,719 employees, 433 public venues that attract visitors, and 354 dependent-care facilities that house individuals that will need assistance to evacuate. We find that population exposure varies considerably across the State both in type (e.g., residential, tourist, employee) and distribution of people (e.g., urban to rural). We develop composite lahar-exposure indices to identify communities most at-risk and communities throughout the State who share common issues of vulnerability to lahar-hazards. We find that although lahars are a regional hazard that will impact communities in different ways there are commonalities in community exposure across multiple volcanoes. Results will aid emergency managers, local officials, and the public in educating at-risk populations and developing preparedness, mitigation, and recovery plans within and across communities.
","language":"English","publisher":"Springer Nature","doi":"10.1186/s13617-015-0024-z","usgsCitation":"Diefenbach, A.K., Wood, N.J., and Ewert, J.W., 2015, Variations in community exposure to lahar hazards from multiple volcanoes in Washington State (USA): Journal of Applied Volcanology, v. 4, 4, 14 p., https://doi.org/10.1186/s13617-015-0024-z.","productDescription":"4, 14 p.","numberOfPages":"14","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060701","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":472312,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s13617-015-0024-z","text":"Publisher Index Page"},{"id":297750,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Glacier Peak, Mount Adams, Mount Baker, Mount Rainier, Mount St. Helens","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.73876953125,\n 45.598665689820656\n ],\n [\n -124.73876953125,\n 48.99463598353408\n ],\n [\n -117.0703125,\n 48.99463598353408\n ],\n [\n -117.0703125,\n 45.598665689820656\n ],\n [\n -124.73876953125,\n 45.598665689820656\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"4","noUsgsAuthors":false,"publicationDate":"2015-02-01","publicationStatus":"PW","scienceBaseUri":"54dd2ac9e4b08de9379b3205","contributors":{"authors":[{"text":"Diefenbach, Angela K. 0000-0003-0214-7818 adiefenbach@usgs.gov","orcid":"https://orcid.org/0000-0003-0214-7818","contributorId":1084,"corporation":false,"usgs":true,"family":"Diefenbach","given":"Angela","email":"adiefenbach@usgs.gov","middleInitial":"K.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":false,"id":537544,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wood, Nathan J. 0000-0002-6060-9729 nwood@usgs.gov","orcid":"https://orcid.org/0000-0002-6060-9729","contributorId":3347,"corporation":false,"usgs":true,"family":"Wood","given":"Nathan","email":"nwood@usgs.gov","middleInitial":"J.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":537545,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ewert, John W. 0000-0003-2819-4057 jwewert@usgs.gov","orcid":"https://orcid.org/0000-0003-2819-4057","contributorId":642,"corporation":false,"usgs":true,"family":"Ewert","given":"John","email":"jwewert@usgs.gov","middleInitial":"W.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":537546,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70140578,"text":"70140578 - 2015 - Ground motion observations of the 2014 South Napa earthquake","interactions":[],"lastModifiedDate":"2015-04-03T14:47:21","indexId":"70140578","displayToPublicDate":"2015-02-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Ground motion observations of the 2014 South Napa earthquake","docAbstract":"Ground motions of the South Napa earthquake (24 August 2014; M 6.0) were recorded at 19 stations within 20 km and 292 stations within 100 km of the rupture surface trace, generating peak ground motions in excess of 50%g and 50 cm/s in and near Napa Valley. This large dataset allows us to compare the ground motion from the earthquake to existing ground‐motion prediction equations (GMPEs) in considerable detail.
\nUsing the ground‐motion data compiled and reported by ShakeMap (Wald et al., 2000), we examine the peak ground acceleration (PGA) and peak ground velocity (PGV), as well as the pseudospectral acceleration (PSA) at periods of 0.3, 1.0, and 3.0 s. At the higher frequencies, especially PGA, data recorded at close distances (within ∼20 km) are very consistent with the GMPEs, implying a stress drop for this event similar to the median for California, that is, 5 MPa (Baltay and Hanks, 2014). At all frequencies, the attenuation with distance is stronger than the GMPEs would predict, which suggests the attenuation in the Napa and San Francisco Bay delta region is stronger than the average attenuation in California. The spatial plot of the ground‐motion residuals is positive to the north, in both Napa and Sonoma Valleys, consistent with increases in amplitude expected from both the directivity and basin effects. More interestingly, perhaps, there is strong ground motion to the south in the along‐strike direction, particularly for PSA at 1.0 s. These strongly positive residuals align with an older, Quaternary fault structure associated with the Franklin or Southampton fault, potentially indicating a fault‐zone‐guided wave.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220140232","usgsCitation":"Baltay Sundstrom, A.S., and Boatwright, J., 2015, Ground motion observations of the 2014 South Napa earthquake: Seismological Research Letters, v. 86, no. 2A, p. 355-360, https://doi.org/10.1785/0220140232.","productDescription":"6 p.","startPage":"355","endPage":"360","numberOfPages":"6","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061613","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":299363,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.56323242187499,\n 37.330856613297144\n ],\n [\n -123.56323242187499,\n 38.70265930723801\n ],\n [\n -121.51977539062499,\n 38.70265930723801\n ],\n [\n -121.51977539062499,\n 37.330856613297144\n ],\n [\n -123.56323242187499,\n 37.330856613297144\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"86","issue":"2A","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-03-04","publicationStatus":"PW","scienceBaseUri":"551fb9b8e4b027f0aee3bb0a","contributors":{"authors":[{"text":"Baltay Sundstrom, Annemarie S. 0000-0002-6514-852X abaltay@usgs.gov","orcid":"https://orcid.org/0000-0002-6514-852X","contributorId":4932,"corporation":false,"usgs":true,"family":"Baltay Sundstrom","given":"Annemarie","email":"abaltay@usgs.gov","middleInitial":"S.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":true,"id":540169,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boatwright, John 0000-0002-6931-5241 boat@usgs.gov","orcid":"https://orcid.org/0000-0002-6931-5241","contributorId":1938,"corporation":false,"usgs":true,"family":"Boatwright","given":"John","email":"boat@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":540170,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70155255,"text":"70155255 - 2015 - Evaluation of satellite rainfall estimates for drought and flood monitoring in Mozambique","interactions":[],"lastModifiedDate":"2017-01-18T10:07:16","indexId":"70155255","displayToPublicDate":"2015-02-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of satellite rainfall estimates for drought and flood monitoring in Mozambique","docAbstract":"Satellite derived rainfall products are useful for drought and flood early warning and overcome the problem of sparse, unevenly distributed and erratic rain gauge observations, provided their accuracy is well known. Mozambique is highly vulnerable to extreme weather events such as major droughts and floods and thus, an understanding of the strengths and weaknesses of different rainfall products is valuable. Three dekadal (10-day) gridded satellite rainfall products (TAMSAT African Rainfall Climatology And Time-series (TARCAT) v2.0, Famine Early Warning System NETwork (FEWS NET) Rainfall Estimate (RFE) v2.0, and Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS)) are compared to independent gauge data (2001–2012). This is done using pairwise comparison statistics to evaluate the performance in estimating rainfall amounts and categorical statistics to assess rain-detection capabilities. The analysis was performed for different rainfall categories, over the seasonal cycle and for regions dominated by different weather systems. Overall, satellite products overestimate low and underestimate high dekadal rainfall values. The RFE and CHIRPS products perform as good, generally outperforming TARCAT on the majority of statistical measures of skill. TARCAT detects best the relative frequency of rainfall events, while RFE underestimates and CHIRPS overestimates the rainfall events frequency. Differences in products performance disappear with higher rainfall and all products achieve better results during the wet season. During the cyclone season, CHIRPS shows the best results, while RFE outperforms the other products for lower dekadal rainfall. Products blending thermal infrared and passive microwave imagery perform better than infrared only products and particularly when meteorological patterns are more complex, such as over the coastal, central and south regions of Mozambique, where precipitation is influenced by frontal systems.
","language":"English","publisher":"MDPI AG","doi":"10.3390/rs70201758","usgsCitation":"Tote, C., Patricio, D., Boogaard, H., van der Wijngaart, R., Tarnavsky, E., and Funk, C.C., 2015, Evaluation of satellite rainfall estimates for drought and flood monitoring in Mozambique: Remote Sensing, v. 7, no. 2, p. 1758-1776, https://doi.org/10.3390/rs70201758.","productDescription":"19 p.","startPage":"1758","endPage":"1776","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-062070","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":472308,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs70201758","text":"Publisher Index Page"},{"id":306853,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mozambique","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 32.93701171875,\n -26.88288045572338\n ],\n [\n 32.18994140625,\n -26.843677401113002\n ],\n [\n 32.05810546875,\n -26.056782885778798\n ],\n [\n 31.9482421875,\n -25.859223554761382\n ],\n [\n 31.9921875,\n -24.467150664738977\n ],\n [\n 31.552734374999996,\n -23.443088931121775\n ],\n [\n 31.26708984375,\n -22.41102852155869\n ],\n [\n 32.40966796875,\n -21.309846141087192\n ],\n [\n 32.3876953125,\n -21.105000275382054\n ],\n [\n 32.4755859375,\n -20.509354588714576\n ],\n [\n 33.0029296875,\n -19.746024239625417\n ],\n [\n 32.783203125,\n -19.394067895396613\n ],\n [\n 32.6953125,\n -18.750309813140653\n ],\n [\n 32.93701171875,\n -18.375379094031814\n ],\n [\n 32.958984375,\n -17.455472579972827\n ],\n [\n 32.87109375,\n -16.867633616803836\n ],\n [\n 32.431640625,\n -16.488764934242063\n ],\n [\n 31.640625,\n -16.13026201203474\n ],\n [\n 30.95947265625,\n -16.024695711685304\n ],\n [\n 30.454101562499996,\n -16.003575733881313\n ],\n [\n 30.16845703125,\n -14.987239525774244\n ],\n [\n 33.15673828125,\n -13.966054081318301\n ],\n [\n 33.7060546875,\n -14.541049898060388\n ],\n [\n 34.43115234375,\n -14.349547837185362\n ],\n [\n 34.51904296875,\n -14.626108798876839\n ],\n [\n 34.60693359375,\n -15.347761924346937\n ],\n [\n 34.27734375,\n -15.834535741221552\n ],\n [\n 34.47509765625,\n -16.25686733062344\n ],\n [\n 35.13427734375,\n -16.941214960202647\n ],\n [\n 35.057373046875,\n -17.02527268537679\n ],\n [\n 35.079345703125,\n -17.151288449816732\n ],\n [\n 35.299072265625,\n -17.130291743533746\n ],\n [\n 35.26611328125,\n -16.70986293320658\n ],\n [\n 35.17822265625,\n -16.55196172197251\n ],\n [\n 35.4638671875,\n -16.140815555276024\n ],\n [\n 35.8154296875,\n -15.993014907400758\n ],\n [\n 35.83740234375,\n -14.77488250651626\n ],\n [\n 35.35400390625,\n -14.008696370634658\n ],\n [\n 34.80468749999999,\n -13.47510594433495\n ],\n [\n 34.4970703125,\n -13.47510594433495\n ],\n [\n 34.34326171875,\n -12.103780891645817\n ],\n [\n 34.5849609375,\n -11.5230875068685\n ],\n [\n 35.96923828125,\n -11.480024648555816\n ],\n [\n 37.001953125,\n -11.544616463449655\n ],\n [\n 37.94677734374999,\n -11.24306204194776\n ],\n [\n 38.60595703125,\n -11.329253026617318\n ],\n [\n 40.517578125,\n -10.422988388338242\n ],\n [\n 40.84716796875,\n -14.689881366618762\n ],\n [\n 39.814453125,\n -16.46769474828897\n ],\n [\n 36.93603515625,\n -17.97873309555617\n ],\n [\n 36.25488281249999,\n -18.916679786648565\n ],\n [\n 34.87060546875,\n -19.828725387681168\n ],\n [\n 34.78271484375,\n -20.42701281425737\n ],\n [\n 35.57373046875,\n -22.41102852155869\n ],\n [\n 35.4638671875,\n -24.206889622398023\n ],\n [\n 34.4091796875,\n -24.926294766395593\n ],\n [\n 33.11279296875,\n -25.423431426334233\n ],\n [\n 32.607421875,\n -26.056782885778798\n ],\n [\n 32.93701171875,\n -26.254009699865737\n ],\n [\n 32.93701171875,\n -26.88288045572338\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"7","issue":"2","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2015-02-05","publicationStatus":"PW","scienceBaseUri":"55d45730e4b0518e354694c3","contributors":{"authors":[{"text":"Tote, Carolien","contributorId":145818,"corporation":false,"usgs":false,"family":"Tote","given":"Carolien","email":"","affiliations":[{"id":16241,"text":"Flemish Institute for Technological Research (VITO), Remote Sensing Unit","active":true,"usgs":false}],"preferred":false,"id":565387,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Patricio, Domingos","contributorId":145819,"corporation":false,"usgs":false,"family":"Patricio","given":"Domingos","email":"","affiliations":[{"id":16242,"text":"Instituto Nacional de Meteorologia - 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