This report summarizes and interprets results of the work in the Ahankashan Area of Interest in northwestern Afghanistan and four study areas—the Ahankashan Prospect Area, Syahsang-Kushkak, Taghab-Soni, and Zakak-e ‘Olya—delineated for their potential undiscovered mineral occurrences with specific emphasis on porphyry copper and related occurrence types. The Area of Interest is underlain by rocks of three different geologic domains that cross from east to west—the Band-e-Bayan Block/Central Pamirs Domain in the south, the Hindu Kush Domain in the Paropamisus Mountains, and the Afghan Turkestan Domain in the north. The domains are sutured remnants of Tethyan tectonic elements. Interpretation of the geologic maps indicates the presence of thrust faults, strike-slip faults, and granitic intrusions emplaced in ground prepared by faulting. Thrust faulting was followed by strike-slip faulting and then followed by magmatic intrusions. Advanced Spaceborne Thermal Emission and Reflection Radiometer data were used to map minerals that have been altered by hydrothermal fluids typically associated with mineralization to delineate new potential occurrences of copper, gold, and silver. Propylitic-, argillic-, and phyllic-altered intrusive rocks are found in the area, as well as very minor amounts of hydrothermal silica-rich rocks. This area of interest is vastly underexplored and contains only seven known mineral occurrences, of which the Ahankashan copper (gold) skarn occurrence is the best known. Gold has been found in stream sediments near the Ahankashan skarn, in the Taghab-Soni study area, and possibly other parts of the Area of Interest, suggesting potential for at least small-scale placer occurrences.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151040","usgsCitation":"Drew, L.J., Sutphin, D.M., Mars, J.C., and Bogdanow, A.K., 2015, Summary of the Ahankashan area of interest: U.S. Geological Survey Open-File Report 2015–1040, 26 p., https://dx.doi.org/10.3133/ofr20151040.","productDescription":"iv, 26 p.","numberOfPages":"31","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-051081","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":308094,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1040/ofr20151040.pdf","text":"Report","size":"4.40 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1040"},{"id":308092,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1040/coverthb.jpg"}],"country":"Afghanistan","otherGeospatial":"Ahankashan Area of Interest","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 63.19335937499999,\n 34.20725938207231\n ],\n [\n 63.19335937499999,\n 34.71452466170392\n ],\n [\n 64.83032226562499,\n 34.71452466170392\n ],\n [\n 64.83032226562499,\n 34.20725938207231\n ],\n [\n 63.19335937499999,\n 34.20725938207231\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Mineral Resources Program
U.S. Geological Survey
12201 Sunrise Valley Dr.
Reston, VA 20192
http://minerals.usgs.gov
The purpose of this application, under Article 23.9.3, is to conserve current usage of the well-established genus-group name Cryptodacus Hendel, 1914 for a genus of Neotropical fruit flies by suppression of the earlier, unused name Cryptodacus Gundlach, 1862, currently a junior synonym of Arrhyton Günther, 1858, a genus of snakes, under the plenary power of the Commission, in the interest of nomenclatural stability. Cryptodacus Gundlach has not been used as a valid name since 1883, whereas Cryptodacus Hendel has been used in a significant body of literature relating to fruit fly systematics, morphology and phylogeny and is the currently used name in various name and molecular databases.
","language":"English","publisher":"International Trust for Zoological Nomenclature","doi":"10.21805/bzn.v72i3.a12","usgsCitation":"Norrbom, A.L., McDiarmid, R.W., Chen, X., David, J., De Meyer, M., Freidberg, A., Han, H., Hancock, D., Steck, G.J., Thompson, F.R., White, I., and Zucchi, R.A., 2015, Case 3693 Cryptodacus Hendel, 1914 (Insecta: Diptera: Tephritidae): Proposed suppression of Cryptodacus Gundlach, 1862 (Reptilia, Serpentes, Colubridae): Bulletin of Zoological Nomenclature, v. 72, no. 3, p. 204-208, https://doi.org/10.21805/bzn.v72i3.a12.","productDescription":"5 p.","startPage":"204","endPage":"208","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-067106","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":471793,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.biodiversitylibrary.org/part/378187","text":"External Repository"},{"id":326303,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"72","issue":"3","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57aafeeae4b05e859be0f082","contributors":{"authors":[{"text":"Norrbom, Allen L.","contributorId":173559,"corporation":false,"usgs":false,"family":"Norrbom","given":"Allen","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":645082,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McDiarmid, Roy W. 0000-0002-7649-1796 rmcdiarmid@usgs.gov","orcid":"https://orcid.org/0000-0002-7649-1796","contributorId":3603,"corporation":false,"usgs":true,"family":"McDiarmid","given":"Roy","email":"rmcdiarmid@usgs.gov","middleInitial":"W.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":645076,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chen, Xiao-Lin","contributorId":173560,"corporation":false,"usgs":false,"family":"Chen","given":"Xiao-Lin","email":"","affiliations":[],"preferred":false,"id":645083,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"David, J.","contributorId":60915,"corporation":false,"usgs":true,"family":"David","given":"J.","email":"","affiliations":[],"preferred":false,"id":645084,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"De Meyer, Marc","contributorId":173561,"corporation":false,"usgs":false,"family":"De Meyer","given":"Marc","email":"","affiliations":[],"preferred":false,"id":645085,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Freidberg, Amnon","contributorId":173562,"corporation":false,"usgs":false,"family":"Freidberg","given":"Amnon","email":"","affiliations":[],"preferred":false,"id":645086,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Han, Ho-Yeon","contributorId":173563,"corporation":false,"usgs":false,"family":"Han","given":"Ho-Yeon","email":"","affiliations":[],"preferred":false,"id":645087,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hancock, David","contributorId":245825,"corporation":false,"usgs":false,"family":"Hancock","given":"David","email":"","affiliations":[],"preferred":false,"id":807070,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Steck, Gary J.","contributorId":173564,"corporation":false,"usgs":false,"family":"Steck","given":"Gary","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":645088,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Thompson, Frank R. III","contributorId":173565,"corporation":false,"usgs":false,"family":"Thompson","given":"Frank","suffix":"III","email":"","middleInitial":"R.","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":645089,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"White, Ian M.","contributorId":173566,"corporation":false,"usgs":false,"family":"White","given":"Ian M.","affiliations":[],"preferred":false,"id":645090,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Zucchi, Roberto A.","contributorId":173567,"corporation":false,"usgs":false,"family":"Zucchi","given":"Roberto","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":645091,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70159975,"text":"70159975 - 2015 - Prospective HyspIRI global observations of tidal wetlands","interactions":[],"lastModifiedDate":"2015-12-07T13:18:57","indexId":"70159975","displayToPublicDate":"2015-09-15T02:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"Prospective HyspIRI global observations of tidal wetlands","docAbstract":"Tidal wetlands are highly productive and act as critical habitat for a wide variety of plants, fish, shellfish, and other wildlife. These ecotones between aquatic and terrestrial environments also provide protection from storm damage, run-off filtering, and recharge of aquifers. Many wetlands along coasts have been exposed to stress-inducing alterations globally, including dredge and fill operations, hydrologic modifications, pollutants, impoundments, fragmentation by roads/ditches, and sea level rise. For wetland protection and sensible coastal development, there is a need to monitor these ecosystems at global and regional scales. Recent advances in satellite sensor design and data analysis are providing practical methods for monitoring natural and man-made changes in wetlands. However, available satellite remote sensors have been limited to mapping primarily wetland location and extent. This paper describes how the HyspIRI hyperspectral and thermal infrared sensors can be used to study and map key ecological properties, such as species composition, biomass, hydrology, and evapotranspiration of tidal salt and brackish marshes and mangroves, and perhaps other major wetland types, including freshwater marshes and wooded/shrub wetlands.
","language":"English","publisher":"American Elsevier Pub. Co","publisherLocation":"New York, NY","doi":"10.1016/j.rse.2015.05.008","usgsCitation":"Kevin Turpie, Klemas, V., Byrd, K.B., Kelly, M., and Jo, Y., 2015, Prospective HyspIRI global observations of tidal wetlands: Remote Sensing of Environment, v. 167, p. 206-217, https://doi.org/10.1016/j.rse.2015.05.008.","productDescription":"12 p.","startPage":"206","endPage":"217","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059690","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":471794,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://escholarship.org/uc/item/2hw3t446","text":"External Repository"},{"id":312010,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"167","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5666bbece4b06a3ea36c8b40","contributors":{"authors":[{"text":"Kevin Turpie","contributorId":150358,"corporation":false,"usgs":false,"family":"Kevin Turpie","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":581399,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Klemas, Victor","contributorId":150359,"corporation":false,"usgs":false,"family":"Klemas","given":"Victor","email":"","affiliations":[{"id":13359,"text":"University of Delaware","active":true,"usgs":false}],"preferred":false,"id":581400,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Byrd, Kristin B. 0000-0002-5725-7486 kbyrd@usgs.gov","orcid":"https://orcid.org/0000-0002-5725-7486","contributorId":3814,"corporation":false,"usgs":true,"family":"Byrd","given":"Kristin","email":"kbyrd@usgs.gov","middleInitial":"B.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":581398,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kelly, Maggi","contributorId":150360,"corporation":false,"usgs":false,"family":"Kelly","given":"Maggi","email":"","affiliations":[{"id":7102,"text":"University of California, Berkeley, Dept. of Civil & Envir. Engineering","active":true,"usgs":false}],"preferred":false,"id":581401,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jo, Young-Heon","contributorId":150361,"corporation":false,"usgs":false,"family":"Jo","given":"Young-Heon","email":"","affiliations":[{"id":18010,"text":"Pusan National University, Busan, South Korea","active":true,"usgs":false}],"preferred":false,"id":581402,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70155523,"text":"ds948 - 2015 - U.S. conterminous wall-to-wall anthropogenic land use trends (NWALT), 1974–2012","interactions":[],"lastModifiedDate":"2015-09-17T10:12:03","indexId":"ds948","displayToPublicDate":"2015-09-14T17:15:00","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":"948","title":"U.S. conterminous wall-to-wall anthropogenic land use trends (NWALT), 1974–2012","docAbstract":"This dataset provides a U.S. national 60-meter, 19-class mapping of anthropogenic land uses for five time periods: 1974, 1982, 1992, 2002, and 2012. The 2012 dataset is based on a slightly modified version of the National Land Cover Database 2011 (NLCD 2011) that was recoded to a schema of land uses, and mapped back in time to develop datasets for the four earlier eras. The time periods coincide with U.S. Department of Agriculture (USDA) Census of Agriculture data collection years. Changes are derived from (a) known changes in water bodies from reservoir construction or removal; (b) housing unit density changes; (c) regional mining/extraction trends; (d) for 1999–2012, timber and forestry activity based on U.S. Geological Survey (USGS) Landscape Fire and Resource Management Planning Tools (Landfire) data; (e) county-level USDA Census of Agriculture change in cultivated land; and (f) establishment dates of major conservation areas. The data are compared to several other published studies and datasets as validation. Caveats are provided about limitations of the data for some classes. The work was completed as part of the USGS National Water-Quality Assessment (NAWQA) Program and termed the NAWQA Wall-to-Wall Anthropogenic Land Use Trends (NWALT) dataset. The associated datasets include five 60-meter geospatial rasters showing anthropogenic land use for the years 1974, 1982, 1992, 2002, and 2012, and 14 rasters showing the annual extent of timber clearcutting and harvest from 1999 to 2012.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds948","usgsCitation":"Falcone, J.A., 2015, U.S. conterminous wall-to-wall anthropogenic land use trends (NWALT), 1974–2012: U.S. Geological Survey Data Series 948, 33 p. plus appendixes 3–6 as separate files, https://dx.doi.org/10.3133/ds948.","productDescription":"Report: viii, 33 p.; Appendixes 3-6; Spatial Data","numberOfPages":"45","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-066108","costCenters":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"links":[{"id":308093,"rank":7,"type":{"id":23,"text":"Spatial Data"},"url":"https://water.usgs.gov/GIS/metadata/usgswrd/XML/ds948_NWALT.xml","text":"DS 948 NWALT","description":"DS 948"},{"id":308002,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0948/ds948.pdf","text":"Report","size":"8.29 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 948"},{"id":308001,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/0948/cover.jpg"},{"id":308003,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/0948/appendix/ds948_appendix3.pdf","text":"DS 948 - Appendix 3","size":"106 KB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 948"},{"id":308004,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/0948/appendix/ds948_appendix4.pdf","text":"DS 948 - Appendix 4","size":"161 KB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 948"},{"id":308005,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/0948/appendix/ds948_appendix5.pdf","text":"DS 948 - Appendix 5","size":"8.44 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 948"},{"id":308006,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/0948/appendix/ds948_appendix6.xlsx","text":"DS 948 - Appendix 6","size":"97.6 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"DS 948"}],"country":"United States","contact":"Chief, Office of Water Quality
U.S. Geological Survey
412 National Center
Reston, VA 20192
http://water.usgs.gov/owq/
The U.S. Geological Survey (USGS) conducts baseline and storm response photography missions to document and understand the changes in vulnerability of the Nation's coasts to extreme storms (Morgan, 2009). On September 5-6, 2014, the USGS conducted an oblique aerial photographic survey from Key Largo, Florida, to the Florida/Georgia border (Figure 1), aboard a Cessna 182 at an altitude of 500 feet (ft) and approximately 1,200 ft offshore (Figure 2). This mission was flown to collect baseline data for assessing incremental changes since the last survey, flown October 1998, and the data can be used in the assessment of future coastal change.
\nThe photographs provided here are Joint Photographic Experts Group (JPEG) images. ExifTool was used to add the following to the header of each photo: time of collection, Global Positioning System (GPS) latitude, GPS longitude, keywords, credit, artist (photographer), caption, copyright, and contact information. The photograph locations are an estimate of the position of the aircraft and do not indicate the location of any feature in the images (see the Navigation Data page). These photographs document the state of the barrier islands and other coastal features at the time of the survey. Pages containing thumbnail images of the photographs, referred to as contact sheets, were created in 5-minute segments of flight time. These segments can be found on the Photos and Maps page. Photographs can be opened directly with any JPEG-compatible image viewer by clicking on a thumbnail on the contact sheet.
\nTable 1 provides detailed information about the GPS location, image name, date, and time of each of the 3,892 photographs taken along with links to each photograph.
\nIn addition to the photographs, a Google Earth Keyhole Markup Language (KML) file is provided and can be used to view the images by clicking on the marker and then clicking on either the thumbnail or the link above the thumbnail. The KML files were created using the photographic navigation files. These KML files can be found in the kml folder.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds953","usgsCitation":"Morgan, K.L.M., 2015, Baseline coastal oblique aerial photographs collected from Key Largo, Florida, to the Florida/Georgia border, September 5-6, 2014: U.S. Geological Survey Data Series 953, https://dx.doi.org/10.3133/ds953.","productDescription":"HTML document","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2014-09-05","temporalEnd":"2015-09-06","ipdsId":"IP-065621","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":307882,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/0953/coverthb.jpg"},{"id":307883,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0953/index.html","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"DS 953"}],"country":"United States","state":"Florida","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.573486328125,\n 25.334096684794456\n ],\n [\n -81.573486328125,\n 30.713503990354965\n ],\n [\n -79.9365234375,\n 30.713503990354965\n ],\n [\n -79.9365234375,\n 25.334096684794456\n ],\n [\n -81.573486328125,\n 25.334096684794456\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"St. Petersburg Coastal and Marine Science Center
600 4th Street South
St. Petersburg, FL 33701
(727) 502-8000
http://coastal.er.usgs.gov/
Decisionmakers need information about the quality and quantity of stormwater runoff, the risk for adverse effects of runoff on receiving waters, and the potential effectiveness of mitigation measures to reduce these risks. The Stochastic Empirical Loading and Dilution Model (SELDM) uses Monte Carlo methods to generate stormflows, concentrations, and loads from a highway site and an upstream basin to provide needed risk-based information. SELDM was designed to help inform water-management decisions for streams and lakes receiving runoff from a highway or other land-use site. The purpose of this paper is to provide a brief description of SELDM and a hypothetical case study demonstrating the type of risk-based information that SELDM can provide. Total nitrogen (TN) and total phosphorus (TP) were selected as example constituents because nutrients are a common concern throughout the Nation and data for receiving waters, highway runoff, and the performance of best management practices (BMPs) are readily available for these constituents.
\nThe case study is hypothetical, but was formulated by using actual data from selected monitoring sites in New England. Data representing streamflow and water-quality were collected at U.S. Geological Survey (USGS) streamgage 01208950 Sasco Brook near Southport, CT, which has a drainage area of 7.38 square miles. In this hypothetical case study a 4-lane highway would replace the current 2-lane road and would have a contributing area of 2.2 acres between the topographic basin divides. Concentrations of TN and TP in highway runoff were simulated with data from USGS highway-runoff monitoring station 423027071291301 along State Route 2 in Littleton Massachusetts. Results of a highway-runoff analysis are shown in relation to three hypothetical discharge criteria for TN and two hypothetical discharge criteria for TP. The risks for exceeding TN discharge criteria of 3, 5, and 8 mg/L for highway runoff are 7.4, 0.83, and 0.13 percent of 1,721 runoff events that may occur during a stochastic 30-year simulation. If a grassy swale is used to treat the runoff, the risks for TN exceedances are reduced to 3.2, 0.33 and 0.03 percent, respectively. The risks for exceeding TP discharge criteria of 0.1 and 0.5 mg/L for highway runoff are 49 and 1.2 percent, respectively. If a grassy swale is used to treat the runoff, the risks for TP exceedances are 57 and 0.8 percent, respectively. The risks for the 0.1 mg/L criterion increase because swales can be a source of TP if pavement concentrations are low. The risks for the 0.5 mg/L criterion decrease because the swale is effective for reducing high TP concentrations. Although the results are mixed for storm-event concentrations, the grassy swale effectively reduces annual loads. Annual loads from the swale are, on average, about 49 percent of highway loads for TN and 62 percent of highway loads of TP because the swale reduces high runoff concentrations and stormflow volumes. Analysis of upstream and downstream concentrations indicates that runoff from the site of interest does not have a substantial effect on instream stormflow concentrations in this example simulation.
","conferenceTitle":"StormCon","conferenceDate":"08/6/2015","conferenceLocation":"Austin, TX","language":"English","publisher":"Forester Media Inc.","publisherLocation":"Santa Barbara, CA","collaboration":"Federal Highway Administration","usgsCitation":"Granato, G.E., and Jones, S.C., 2015, A case study demonstrating analysis of stormflows, concentrations, and loads of nutrients in highway runoff and swale discharge with the Stochastic Empirical Loading and Dilution Model (SELDM), StormCon, Austin, TX, 08/6/2015, p. 1-10.","productDescription":"10 p.","startPage":"1","endPage":"10","numberOfPages":"10","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063178","costCenters":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true}],"links":[{"id":308099,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":307902,"type":{"id":11,"text":"Document"},"url":"https://webdmamrl.er.usgs.gov/g1/FHWA/Presentations/GranatoJones2015StormCon.pdf"}],"publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55f7e19ee4b05d6c4e4fa951","contributors":{"authors":[{"text":"Granato, Gregory E. 0000-0002-2561-9913 ggranato@usgs.gov","orcid":"https://orcid.org/0000-0002-2561-9913","contributorId":147346,"corporation":false,"usgs":true,"family":"Granato","given":"Gregory","email":"ggranato@usgs.gov","middleInitial":"E.","affiliations":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":false,"id":571336,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jones, Susan C. 0000-0002-5891-5209","orcid":"https://orcid.org/0000-0002-5891-5209","contributorId":64716,"corporation":false,"usgs":false,"family":"Jones","given":"Susan","email":"","middleInitial":"C.","affiliations":[{"id":34302,"text":"Federal Highway Administration (United States)","active":true,"usgs":false}],"preferred":false,"id":571337,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70155913,"text":"ofr20151143 - 2015 - Biological and geochemical data along Indian Point, Vermilion Bay, Louisiana","interactions":[],"lastModifiedDate":"2025-05-13T16:54:08.808533","indexId":"ofr20151143","displayToPublicDate":"2015-09-14T10:15:00","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":"2015-1143","title":"Biological and geochemical data along Indian Point, Vermilion Bay, Louisiana","docAbstract":"Scientists from the U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center collected shallow sediment cores and surface samples from a coastal salt marsh environment next to Vermilion Bay in southwest Louisiana in January 2013. The sampling was part of a larger USGS study to gather data for assessing environmental changes over the past 150 years. The objective of the study was to expand upon the historical context of sea level and storms affecting coastal systems and how these systems might change under persistent or varying conditions. The data from this report add to a regional environmental change database that aids with the continuing effort to understand the evolution of coastal systems.
\nThis report serves as an archive for sedimentological, radiochemical, and microbiological data derived from the sediment cores. Data are available for January 2013. Downloadable data are available as Excel spreadsheets and as JPEG files. Additional files include ArcGIS shapefiles of the sampling sites, detailed results of sediment analyses, and formal Federal Geographic Data Committee metadata.
\nThe authors thank Nancy DeWitt, B.J. Reynolds, Christopher Reich (USGS, St. Petersburg Coastal and Marine Science Center), for help with sample collection and processing; Michael Ball, Sarai Piazza, and Gregory Steyer (USGS, Coastal Restoration Assessment Branch) for assistance accessing CRMS Site 541; and Darrell Anders and Phillip Turnipseed (USGS National Wetlands Research Center) for technical support while in the field. We would also like to thank Caitlyn Reynolds and Nicholas Zaremba for their pre-release commentary and peer review.
\nThis publication was prepared by an agency of the United States Government. Although these data were processed successfully on a computer system at the U.S. Geological Survey, no warranty expressed or implied is made regarding the display or utility of the data on any other system, or for general or scientific purposes, nor shall the act of distribution imply any such warranty. The U.S. Geological Survey shall not be held liable for improper or incorrect use of the data described and (or) contained herein. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151143","usgsCitation":"Richwine, K.A., Marot, M.E., Smith, C.G., Osterman, L.E., and Adams, C.S., 2015, Biological and geochemical data along Indian Point, Vermilion Bay, Louisiana: U.S. Geological Survey Open-File Report 2015-1143, https://dx.doi.org/10.3133/ofr20151143.","productDescription":"Report: HTML Document; Downloads Directory","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-059007","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":307119,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2015/1143/downloads","text":"Biological and Geochemical Data","description":"OFR 2015-1143"},{"id":307094,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1143/coverthb.jpg"},{"id":307095,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2015/1143/index.html","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2015-1143"}],"country":"United States","state":"Louisiana","otherGeospatial":"Indian Point, Vermilion Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.05787658691406,\n 29.608088257406806\n ],\n [\n -92.05787658691406,\n 29.6361427369564\n ],\n [\n -92.00363159179688,\n 29.6361427369564\n ],\n [\n -92.00363159179688,\n 29.608088257406806\n ],\n [\n -92.05787658691406,\n 29.608088257406806\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, St. Petersburg Coastal and Marine Science Center
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(727) 502-8000
http://coastal.er.usgs.gov/
Despite being protected by both international and national regulations, pangolins are threatened by illegal trade. Here we report mitochondrial DNA identification and haplotype richness estimation, using 239 pangolin scale samples from two confiscations in Hong Kong. We found a total of 13 genetically distinct cytochrome c oxidase I (COI) haplotypes in two confiscations (13 and ten haplotypes respectively, with ten shared haplotypes between confiscations). These haplotypes clustered in two distinct clades with one clade representing the Sunda pangolin (Manisjavanica). The other clade did not match with any known Asian pangolin sequences, and likely represented a cryptic pangolin lineage in Asia. By fitting sample coverage and rarefaction/regression models to our sample data, we predicted that the total number of COI haplotypes in two confiscations were 14.86 and 11.06 respectively, suggesting that our sampling caught the majority of haplotypes and that we had adequately characterized each confiscation. We detected substantial sequence divergence among the seized scales, likely evidencing that the Sunda pangolins were harvested over wide geographical areas across Southeast Asia. Our study illustrates the value of applying DNA forensics for illegal wildlife trade monitoring.
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Hong Kong SAR","active":true,"usgs":false}],"preferred":false,"id":579689,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chan, Ki","contributorId":149819,"corporation":false,"usgs":false,"family":"Chan","given":"Ki","email":"","affiliations":[{"id":17833,"text":"Kadoorie Farm and Botanic Garden, Lam Kam Road, Tai Po, N.T. Hong Kong SAR","active":true,"usgs":false}],"preferred":false,"id":579690,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gaubert, Philippe 0000-0002-1375-9935","orcid":"https://orcid.org/0000-0002-1375-9935","contributorId":149820,"corporation":false,"usgs":false,"family":"Gaubert","given":"Philippe","email":"","affiliations":[{"id":17834,"text":"Institut des Sciences de l'Evolution de Montpellier (ISEM) – UM2-CNRS-IRD, Université de Montpellier, Montpellier Cedex 05, France","active":true,"usgs":false}],"preferred":false,"id":579691,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ades, Gary","contributorId":149821,"corporation":false,"usgs":false,"family":"Ades","given":"Gary","email":"","affiliations":[{"id":17833,"text":"Kadoorie Farm and Botanic Garden, Lam Kam Road, Tai Po, N.T. Hong Kong SAR","active":true,"usgs":false}],"preferred":false,"id":579692,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Fischer, Gunter A.","contributorId":149822,"corporation":false,"usgs":false,"family":"Fischer","given":"Gunter","email":"","middleInitial":"A.","affiliations":[{"id":17833,"text":"Kadoorie Farm and Botanic Garden, Lam Kam Road, Tai Po, N.T. Hong Kong SAR","active":true,"usgs":false}],"preferred":false,"id":579693,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70155942,"text":"sir20155113 - 2015 - Hydrogeology and simulation of groundwater flow in fractured-rock aquifers of the Piedmont and Blue Ridge Physiographic Provinces, Bedford County, Virginia","interactions":[],"lastModifiedDate":"2015-11-02T09:44:16","indexId":"sir20155113","displayToPublicDate":"2015-09-11T10:45:00","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":"2015-5113","title":"Hydrogeology and simulation of groundwater flow in fractured-rock aquifers of the Piedmont and Blue Ridge Physiographic Provinces, Bedford County, Virginia","docAbstract":"An annual groundwater budget was computed as part of a hydrogeologic characterization and monitoring effort of fractured-rock aquifers in Bedford County, Virginia, a growing 764-square-mile (mi2) rural area between the cities of Roanoke and Lynchburg, Virginia. Data collection in Bedford County began in the 1930s when continuous stream gages were installed on Goose Creek and Big Otter River, the two major tributaries of the Roanoke River within the county. Between 2006 and 2014, an additional 2 stream gages, 3 groundwater monitoring wells, and 12 partial-record stream gages were operated. Hydrograph separation methods were used to compute base-flow recharge rates from the continuous data collected from the continuous stream gages. Mean annual base-flow recharge ranged from 8.3 inches per year (in/yr) for the period 1931–2012 at Goose Creek near Huddleston (drainage area 188 mi2) to 9.3 in/yr for the period 1938–2012 at Big Otter River near Evington (drainage area 315 mi2). Mean annual base-flow recharge was estimated to be 6.5 in/yr for the period 2007–2012 at Goose Creek at Route 747 near Bunker Hill (drainage area 125 mi2) and 8.9 in/yr for the period 2007–2012 at Big Otter River at Route 221 near Bedford (drainage area 114 mi2). Base-flow recharge computed from the partial-record data ranged from 5.0 in/yr in the headwaters of Goose Creek to 10.5 in/yr in the headwaters of Big Otter River.
\nA steady-state groundwater-flow simulation for Bedford County was developed to test the conceptual understanding of flow in the fractured-rock aquifers and to compute a groundwater budget for the four major drainages: James River, Smith Mountain and Leesville Lakes, Goose Creek, and Big Otter River. Model results indicate that groundwater levels mimic topography and that minimal differences in aquifer properties exist between the Proterozoic basement crystalline rocks and Late Proterozoic-Cambrian cover crystalline rocks. The Big Otter River receives 40.8 percent of the total daily groundwater outflow from fractured-rock aquifers in Bedford County; Goose Creek receives 25.8 percent, the James River receives 18.2 percent, and Smith Mountain and Leesville Lakes receive 15.2 percent. The remaining percentage of outflow is attributed to pumping from the aquifer (consumptive use).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155113","issn":"2328-031X","isbn":"978-1-4113-3965-1","usgsCitation":"McCoy, K.J., White, B.A., Yager, R.M., and Harlow, G.E., Jr., 2015, Hydrogeology and simulation of groundwater flow in fractured-rock aquifers of the Piedmont and Blue Ridge Physiographic Provinces, Bedford County, Virginia: U.S. Geological Survey Scientific Investigations Report 2015–5113, 54 p., https://dx.doi.org/10.3133/sir20155113.","productDescription":"viii, 54 p.","numberOfPages":"68","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-039535","costCenters":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true}],"links":[{"id":308064,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5113/sir20155113.pdf","text":"Report","size":"4.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5113"},{"id":308063,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5113/coverthb.jpg"}],"country":"United States","state":"Virginia","county":"Bedford County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -79.9365234375,\n 36.97622678464096\n ],\n [\n -79.9365234375,\n 37.666429212090605\n ],\n [\n -79.1015625,\n 37.666429212090605\n ],\n [\n -79.1015625,\n 36.97622678464096\n ],\n [\n -79.9365234375,\n 36.97622678464096\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Virginia Water Science Center
U.S. Geological Survey
1730 East Parham Road
Richmond, Virginia 23228
http://va.water.usgs.gov/
Geographic information system (GIS) information may facilitate energy studies, which in turn provide input for energy policy decisions. The U.S. Geological Survey (USGS) has compiled GIS data representing coal mines, deposits (including those with and without coal mines), occurrences, areas, basins, and provinces of Mongolia as of 2009. These data are now available for download, and may be used in a GIS for a variety of energy resource and environmental studies of Mongolia. Chemical data for 37 coal samples from a previous USGS study of Mongolia (Tewalt and others, 2010) are included in a downloadable GIS point shapefile and shown on the map of Mongolia. A brief report summarizes the methodology used for creation of the shapefiles and the chemical analyses run on the samples.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151144","usgsCitation":"Trippi, M.H., and Belkin, H.E., comps., 2015, USGS compilation of geographic information system (GIS) data representing coal mines and coal-bearing areas of Mongolia: U.S. Geological Survey Open-File Report 2015–1144, 18 p., https://dx.doi.org/10.3133/ofr20151144.","productDescription":"Report: v, 18 p.; Metadata; Spatial data","numberOfPages":"24","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-051260","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":307735,"rank":7,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/of/2015/1144/downloads/ofr20151144_mongolia-coal-deposits-metadata.html","text":"Mongolia Coal Deposits Metadata","size":"35.4 KB","linkFileType":{"id":5,"text":"html"},"description":"OFR 2015-1144"},{"id":307731,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1144/coverthb.jpg"},{"id":307740,"rank":4,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/of/2015/1144/downloads/ofr20151144_mongolia-coal-areas-basins-provinces.zip","text":"Mongolia Coal Areas, Basins, and Provinces Shape Files","size":"203 KB","linkFileType":{"id":6,"text":"zip"},"description":"OFR 2015-1144"},{"id":307732,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1144/ofr20151144.pdf","text":"Report","size":"4.07 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1144"},{"id":307733,"rank":3,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/of/2015/1144/downloads/ofr20151144_mongolia-allshapefiles-metadata.zip","text":"All Mongolia Shape Files and Metadata","size":"294 KB","linkFileType":{"id":6,"text":"zip"},"description":"OFR 2015-1144"},{"id":307734,"rank":5,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/of/2015/1144/downloads/ofr20151144_mongolia-coal-areas-basins-provinces-metadata.html","text":"Mongolia Coal Areas, Basins, and Provinces Metadata","size":"20.9 KB","linkFileType":{"id":5,"text":"html"},"description":"OFR 2015-1144"},{"id":307737,"rank":9,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/of/2015/1144/downloads/ofr20151144_mongolia-analytical-data-metadata.html","text":"Mongolia Anaytical Data Metadata","size":"100 KB","linkFileType":{"id":5,"text":"html"},"description":"OFR 2015-1144"},{"id":307738,"rank":6,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/of/2015/1144/downloads/ofr20151144_mongolia-coal-deposits.zip","text":"Mongolia Coal Deposit Shape File","size":"24.6 KB","linkFileType":{"id":6,"text":"zip"},"description":"OFR 2015-1144"},{"id":307739,"rank":8,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/of/2015/1144/downloads/ofr20151144_mongolia-analytical-data.zip","text":"Mongolia Analytical Data Shape File","size":"43.6 KB","linkFileType":{"id":6,"text":"zip"},"description":"OFR 2015-1144"}],"country":"Mongolia","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[87.75126,49.2972],[88.80557,49.47052],[90.71367,50.33181],[92.23471,50.80217],[93.10422,50.49529],[94.14757,50.48054],[94.81595,50.01343],[95.81403,49.97747],[97.25973,49.72606],[98.23176,50.4224],[97.82574,51.011],[98.86149,52.04737],[99.98173,51.63401],[100.88948,51.51686],[102.06522,51.25992],[102.25591,50.51056],[103.67655,50.08997],[104.62155,50.27533],[105.88659,50.40602],[106.8888,50.2743],[107.86818,49.79371],[108.47517,49.28255],[109.40245,49.29296],[110.66201,49.13013],[111.58123,49.37797],[112.89774,49.54357],[114.36246,50.2483],[114.96211,50.14025],[115.4857,49.80518],[116.6788,49.88853],[116.1918,49.1346],[115.48528,48.13538],[115.74284,47.72654],[116.30895,47.85341],[117.29551,47.69771],[118.06414,48.06673],[118.86657,47.74706],[119.77282,47.04806],[119.66327,46.69268],[118.87433,46.80541],[117.4217,46.67273],[116.71787,46.3882],[115.9851,45.72724],[114.46033,45.33982],[113.46391,44.80889],[112.43606,45.01165],[111.87331,45.10208],[111.34838,44.45744],[111.66774,44.07318],[111.82959,43.74312],[111.12968,43.40683],[110.4121,42.87123],[109.2436,42.51945],[107.74477,42.48152],[106.12932,42.13433],[104.96499,41.59741],[104.52228,41.90835],[103.31228,41.90747],[101.83304,42.51487],[100.84587,42.6638],[99.51582,42.52469],[97.45176,42.74889],[96.3494,42.72564],[95.76245,43.31945],[95.30688,44.24133],[94.68893,44.35233],[93.48073,44.97547],[92.13389,45.11508],[90.94554,45.28607],[90.58577,45.71972],[90.97081,46.88815],[90.28083,47.69355],[88.8543,48.06908],[88.01383,48.59946],[87.75126,49.2972]]]},\"properties\":{\"name\":\"Mongolia\"}}]}","contact":"Eastern Energy Resources Science Center
U.S. Geological Survey
954 National Center
12201 Sunrise Valley Drive
Reston, Virginia 20192
http://energy.usgs.gov/GeneralInfo/
ScienceCenters/Eastern.aspx
Greater sage-grouse (Centrocercus urophasianus; hereinafter, sage-grouse) are a sagebrush obligate species that has declined concomitantly with the loss and fragmentation of sagebrush ecosystems across most of its geographical range. The species currently is listed as a candidate for federal protection under the Endangered Species Act (ESA). Increasing wildfire frequency and changing climate frequently are identified as two environmental drivers that contribute to the decline of sage-grouse populations, yet few studies have rigorously quantified their effects on sage-grouse populations across broad spatial scales and long time periods. To help inform a threat assessment within the Great Basin for listing sage-grouse in 2015 under the ESA, we conducted an extensive analysis of wildfire and climatic effects on sage-grouse population growth derived from 30 years of lek-count data collected across the hydrographic Great Basin of Western North America. Annual (1984–2013) patterns of wildfire were derived from an extensive dataset of remotely sensed 30-meter imagery and precipitation derived from locally downscaled spatially explicit data. In the sagebrush ecosystem, underlying soil conditions also contribute strongly to variation in resilience to disturbance and resistance to plant community changes (R&R). Thus, we developed predictions from models of post-wildfire recovery and chronic effects of wildfire based on three spatially explicit R&R classes derived from soil moisture and temperature regimes. We found evidence of an interaction between the effects of wildfire (chronically affected burned area within 5 kilometers of a lek) and climatic conditions (spring through fall precipitation) after accounting for a consistent density-dependent effect. Specifically, burned areas near leks nullifies population growth that normally follows years with relatively high precipitation. In models, this effect results in long-term population declines for sage-grouse despite cyclic periods of high precipitation. Based on 30-year projections of burn and recovery rates, our population model predicted steady and substantial long-term declines in population size across the Great Basin. Further, example management scenarios that may help offset adverse wildfire effects are provided by models of varying levels of fire suppression and post-wildfire restoration that focus on areas especially important to sage-grouse populations. These models illustrate how sage-grouse population persistence likely will be compromised as sagebrush ecosystems and sage-grouse habitat are degraded by wildfire, especially in a warmer and drier climate, and by invasion of annual grasses that can increase wildfire frequency and size in the Great Basin.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151165","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Coates, P.S., Ricca, M.A., Prochazka, B.G., Doherty, K.E., Brooks, M.L., and Casazza, M.L., 2015, Long-term effects of wildfire on greater sage-grouse—Integrating population and ecosystem concepts for management in the Great Basin: U.S. Geological Survey Open-File Report 2015–1165, 42 p., https://dx.doi.org/10.3133/ofr20151165.","productDescription":"Report: vi, 42 p.; Dataset","numberOfPages":"52","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-067577","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":438684,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7K35RRS","text":"USGS data release","linkHelpText":"Long-term effects of wildfire on greater sage-grouse - integrating population and ecosystem concepts for management in the Great Basin"},{"id":307537,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1165/ofr20151165.pdf","text":"Report","size":"6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1165 PDF"},{"id":307539,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1165/coverthb.jpg"},{"id":321005,"rank":3,"type":{"id":28,"text":"Dataset"},"url":"https://dx.doi.org/10.5066/F7K35RRS","text":"Data release"}],"country":"United States","state":"California, Idaho, Nevada, Oregon, Utah","otherGeospatial":"Great Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.03881835937499,\n 44.879228141635274\n ],\n [\n -113.97216796875,\n 45.72152152227954\n ],\n [\n -121.5087890625,\n 45.706179285330855\n ],\n [\n -122.49755859375,\n 40.713955826286046\n ],\n [\n -118.69628906249999,\n 35.53222622770337\n ],\n [\n -114.5654296875,\n 34.88593094075317\n ],\n [\n -112.30224609374999,\n 37.020098201368114\n ],\n [\n -110.54443359375,\n 40.9964840143779\n ],\n [\n -111.03881835937499,\n 44.879228141635274\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
http://werc.usgs.gov/
Estimates of the seasonal and interannual exchanges of carbon dioxide (CO2) and methane (CH4) between land ecosystems north of 45°N and the atmosphere are poorly constrained, in part, because of uncertainty in the temporal variability of water-inundated land area. Here we apply a process-based biogeochemistry model to evaluate how interannual changes in wetland inundation extent might have influenced the overall carbon dynamics of the region during the time period 1993–2004. We find that consideration by our model of these interannual variations between 1993 and 2004, on average, results in regional estimates of net methane sources of 67.8 ± 6.2 Tg CH4 yr−1, which is intermediate to model estimates that use two static inundation extent datasets (51.3 ± 2.6 and 73.0 ± 3.6 Tg CH4 yr−1). In contrast, consideration of interannual changes of wetland inundation extent result in regional estimates of the net CO2 sink of −1.28 ± 0.03 Pg C yr−1 with a persistent wetland carbon sink from −0.38 to −0.41 Pg C yr−1 and a upland sink from −0.82 to −0.98 Pg C yr−1. Taken together, despite the large methane emissions from wetlands, the region is a consistent greenhouse gas sink per global warming potential (GWP) calculations irrespective of the type of wetland datasets being used. However, the use of satellite-detected wetland inundation extent estimates a smaller regional GWP sink than that estimated using static wetland datasets. Our sensitivity analysis indicates that if wetland inundation extent increases or decreases by 10% in each wetland grid cell, the regional source of methane increases 13% or decreases 12%, respectively. In contrast, the regional CO2 sink responds with only 7–9% changes to the changes in wetland inundation extent. Seasonally, the inundated area changes result in higher summer CH4 emissions, but lower summer CO2 sinks, leading to lower summer negative greenhouse gas forcing. Our analysis further indicates that wetlands play a disproportionally important role in affecting regional greenhouse gas budgets given that they only occupy approximately 10% of the total land area in the region.
","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Environmental Research Letters","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Institute of Physics Publishing","publisherLocation":"London","doi":"10.1088/1748-9326/10/9/095009","usgsCitation":"Zhuang, Q., Zhu, X., He, Y., Prigent, C., Melillo, J.M., McGuire, A.D., Prinn, R.G., and Kicklighter, D.W., 2015, Influence of changes in wetland inundation extent on net fluxes of carbon dioxide and methane in northern high latitudes from 1993 to 2004: Environmental Research Letters, v. 10, no. 9, 13 p., https://doi.org/10.1088/1748-9326/10/9/095009.","productDescription":"13 p.","numberOfPages":"13","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-044010","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":471798,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/1748-9326/10/9/095009","text":"Publisher Index Page"},{"id":318558,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","issue":"9","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-09-10","publicationStatus":"PW","scienceBaseUri":"56dabfe5e4b015c306f84cb3","contributors":{"authors":[{"text":"Zhuang, Qianlai","contributorId":101975,"corporation":false,"usgs":true,"family":"Zhuang","given":"Qianlai","affiliations":[],"preferred":false,"id":621888,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zhu, Xudong","contributorId":19684,"corporation":false,"usgs":true,"family":"Zhu","given":"Xudong","email":"","affiliations":[],"preferred":false,"id":621889,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"He, Yujie","contributorId":32444,"corporation":false,"usgs":true,"family":"He","given":"Yujie","affiliations":[],"preferred":false,"id":621890,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Prigent, Catherine","contributorId":167345,"corporation":false,"usgs":false,"family":"Prigent","given":"Catherine","email":"","affiliations":[],"preferred":false,"id":621891,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Melillo, Jerry M.","contributorId":87847,"corporation":false,"usgs":false,"family":"Melillo","given":"Jerry","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":621892,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McGuire, A. David 0000-0003-4646-0750 ffadm@usgs.gov","orcid":"https://orcid.org/0000-0003-4646-0750","contributorId":166708,"corporation":false,"usgs":true,"family":"McGuire","given":"A.","email":"ffadm@usgs.gov","middleInitial":"David","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":false,"id":621844,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Prinn, Ronald G.","contributorId":69046,"corporation":false,"usgs":true,"family":"Prinn","given":"Ronald","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":621893,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kicklighter, David W.","contributorId":48872,"corporation":false,"usgs":false,"family":"Kicklighter","given":"David","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":621894,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70157152,"text":"70157152 - 2015 - Slip pulse and resonance of Kathmandu basin during the 2015 Mw 7.8 Gorkha earthquake, Nepal imaged with space geodesy","interactions":[],"lastModifiedDate":"2015-09-28T11:31:42","indexId":"70157152","displayToPublicDate":"2015-09-10T11:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3338,"text":"Science","active":true,"publicationSubtype":{"id":10}},"title":"Slip pulse and resonance of Kathmandu basin during the 2015 Mw 7.8 Gorkha earthquake, Nepal imaged with space geodesy","docAbstract":"Detailed geodetic imaging of earthquake rupture enhances our understanding of earthquake physics and induced ground shaking. The April 25, 2015 Mw 7.8 Gorkha, Nepal earthquake is the first example of a large continental megathrust rupture beneath a high-rate (5 Hz) GPS network. We use GPS and InSAR data to model the earthquake rupture as a slip pulse of ~20 km width, ~6 s duration, and with peak sliding velocity of 1.1 m/s that propagated toward Kathmandu basin at ~3.3 km/s over ~140 km. The smooth slip onset, indicating a large ~5 m slip-weakening distance, caused moderate ground shaking at high >1Hz frequencies (~16% g) and limited damage to regular dwellings. Whole basin resonance at 4-5 s period caused collapse of tall structures, including cultural artifacts.
","language":"English","publisher":"AAAS","doi":"10.1126/science.aac6383","usgsCitation":"Galetzka, J., Melgar, D., Genrich, J., Geng, J., Owen, S., Lindsey, E.O., Xu, X., Bock, Y., Avouac, J., Adhikari, L.B., Upreti, B.N., Pratt-Sitaula, B., Bhattarai, T.N., Sitaula, B.P., Moore, A., Hudnut, K.W., Szeliga, W., Normandeau, J., Fend, M., Flouzat, M., Bollinger, L., Shrestha, P., Koirala, B., Gautam, U., Bhatterai, M., Gupta, R., Kandel, T., Timsina, C., Sapkota, S., Rajaure, S., and Maharjan, N., 2015, Slip pulse and resonance of Kathmandu basin during the 2015 Mw 7.8 Gorkha earthquake, Nepal imaged with space geodesy: Science, v. 349, no. 6252, p. 1091-1095, https://doi.org/10.1126/science.aac6383.","productDescription":"5 p.","startPage":"1091","endPage":"1095","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-067207","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":471799,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.repository.cam.ac.uk/handle/1810/249076","text":"External Repository"},{"id":308054,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Nepal","state":"Gorkha","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 84.22943115234375,\n 27.685960229871625\n ],\n [\n 84.22943115234375,\n 28.096212229438105\n ],\n [\n 84.869384765625,\n 28.096212229438105\n ],\n [\n 84.869384765625,\n 27.685960229871625\n ],\n [\n 84.22943115234375,\n 27.685960229871625\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"349","issue":"6252","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55f29bace4b0dacf699ec69c","contributors":{"authors":[{"text":"Galetzka, John","contributorId":147535,"corporation":false,"usgs":false,"family":"Galetzka","given":"John","email":"","affiliations":[{"id":13711,"text":"Caltech","active":true,"usgs":false}],"preferred":false,"id":571950,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Melgar, D.","contributorId":147565,"corporation":false,"usgs":false,"family":"Melgar","given":"D.","affiliations":[],"preferred":false,"id":572046,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Genrich, J.F.","contributorId":42374,"corporation":false,"usgs":true,"family":"Genrich","given":"J.F.","email":"","affiliations":[],"preferred":false,"id":572047,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Geng, J.","contributorId":147566,"corporation":false,"usgs":false,"family":"Geng","given":"J.","email":"","affiliations":[],"preferred":false,"id":572048,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Owen, S.","contributorId":147567,"corporation":false,"usgs":false,"family":"Owen","given":"S.","email":"","affiliations":[],"preferred":false,"id":572049,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lindsey, E. 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2015 - Linking climate change and health outcomes: Examining the relationship between temperature, precipitation and birth weight in Africa","interactions":[],"lastModifiedDate":"2017-05-16T16:17:28","indexId":"70155252","displayToPublicDate":"2015-09-09T10:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1841,"text":"Global Environmental Change","active":true,"publicationSubtype":{"id":10}},"title":"Linking climate change and health outcomes: Examining the relationship between temperature, precipitation and birth weight in Africa","docAbstract":"This paper examined the relationship between birth weight, precipitation, and temperature in 19 African countries. We matched recorded birth weights from Demographic and Health Surveys covering 1986 through 2010 with gridded monthly precipitation and temperature data derived from satellite and ground-based weather stations. Observed weather patterns during various stages of pregnancy were also used to examine the effect of temperature and precipitation on birth weight outcomes. In our empirical model we allowed the effect of weather factors to vary by the dominant food production strategy (livelihood zone) in a given region as well as by household wealth, mother's education and birth season. This allowed us to determine if certain populations are more or less vulnerable to unexpected weather changes after adjusting for known covariates. Finally we measured effect size by observing differences in birth weight outcomes in women who have one low birth weight experience and at least one healthy birth weight baby. The results indicated that climate does indeed impact birth weight and at a level comparable, in some cases, to the impact of increasing women's education or household electricity status.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.gloenvcha.2015.06.010","usgsCitation":"Grace, K., Davenport, F., Hanson, H., Funk, C.C., and Shukla, S., 2015, Linking climate change and health outcomes: Examining the relationship between temperature, precipitation and birth weight in Africa: Global Environmental Change, v. 35, p. 125-137, https://doi.org/10.1016/j.gloenvcha.2015.06.010.","productDescription":"13 p.","startPage":"125","endPage":"137","numberOfPages":"13","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064651","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":310208,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Africa","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -19.072265625,\n -32.990235559651055\n ],\n [\n -19.072265625,\n 29.53522956294847\n ],\n [\n 55.8984375,\n 29.53522956294847\n ],\n [\n 55.8984375,\n -32.990235559651055\n ],\n [\n -19.072265625,\n -32.990235559651055\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"35","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5628b730e4b0d158f5926c17","contributors":{"authors":[{"text":"Grace, Kathryn","contributorId":145815,"corporation":false,"usgs":false,"family":"Grace","given":"Kathryn","email":"","affiliations":[{"id":7215,"text":"University of Utah Dept. of Geography","active":true,"usgs":false}],"preferred":false,"id":565375,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Davenport, Frank","contributorId":145816,"corporation":false,"usgs":false,"family":"Davenport","given":"Frank","email":"","affiliations":[{"id":7168,"text":"UCSB","active":true,"usgs":false}],"preferred":false,"id":565376,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hanson, Heidi","contributorId":149327,"corporation":false,"usgs":false,"family":"Hanson","given":"Heidi","email":"","affiliations":[],"preferred":false,"id":577984,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":565374,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Shukla, Shraddhanand","contributorId":140735,"corporation":false,"usgs":false,"family":"Shukla","given":"Shraddhanand","email":"","affiliations":[{"id":13549,"text":"UC Santa Barbara Climate Hazards Group","active":true,"usgs":false}],"preferred":false,"id":565377,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70156556,"text":"ofr20151149 - 2015 - Sea-floor morphology and sedimentary environments in southern Narragansett Bay, Rhode Island","interactions":[],"lastModifiedDate":"2015-09-09T11:53:03","indexId":"ofr20151149","displayToPublicDate":"2015-09-09T10:30:00","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":"2015-1149","title":"Sea-floor morphology and sedimentary environments in southern Narragansett Bay, Rhode Island","docAbstract":"Multibeam echosounder data collected by the National Oceanic and Atmospheric Administration along with sediment samples and still and video photography of the sea floor collected by the U.S. Geological Survey were used to interpret sea-floor features and sedimentary environments in southern Narragansett Bay, Rhode Island, as part of a long-term effort to map the sea floor along the northeastern coast of the United States. Sea-floor features include rocky areas and scour depressions in high-energy environments characterized by erosion or nondeposition, and sand waves and megaripples in environments characterized by coarse-grained bedload transport. Two shipwrecks are also located in the study area. Much of the sea floor is relatively featureless within the resolution of the multibeam data; sedimentary environments in these areas are characterized by processes associated with sorting and reworking. This report releases bathymetric data from the multibeam echosounder, grain-size analyses of sediment samples, and photographs of the sea floor and interpretations of the sea-floor features and sedimentary environments. It provides base maps that can be used for resource management and studies of topics such as benthic ecology, contaminant inventories, and sediment transport.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151149","isbn":"978-1-4113-3933-0","collaboration":"Prepared in cooperation with the National Oceanic and Atmospheric Administration","usgsCitation":"McMullen, K.Y., Poppe, L.J., Blackwood, D.S., Nardi, M.J., and Andring, M.A., 2015, Sea-floor morphology and sedimentary environments in southern Narragansett Bay, Rhode Island: U.S. Geological Survey Open-File Report 2015–1149, 1 DVD-ROM, https://dx.doi.org/10.3133/ofr20151149.","productDescription":"HMTL Document","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2011-06-01","temporalEnd":"2011-09-30","ipdsId":"IP-065057","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":307926,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1149/images/coverthb.jpg"},{"id":307927,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2015/1149/index.html","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2015-1149"}],"country":"United States","state":"Rhode Island","otherGeospatial":"Narragansett Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -71.455078125,\n 41.396384896536276\n ],\n [\n -71.455078125,\n 41.748775021355044\n ],\n [\n -71.26419067382812,\n 41.748775021355044\n ],\n [\n -71.26419067382812,\n 41.396384896536276\n ],\n [\n -71.455078125,\n 41.396384896536276\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Woods Hole Coastal and Marine Science Center
U.S. Geological Survey
384 Woods Hole Road
Quissett Campus
Woods Hole, MA 02543
(508) 548-8700 or (508) 457-2200
http://woodshole.er.usgs.gov/
This report describes the methods and data associated with a reconnaissance study of young of year bluefish and mussel tissue samples as well as bed sediment collected as bluefish habitat indicators during August 2013–April 2014 in New Jersey and New York following Hurricane Sandy in October 2012. This study was funded by the Disaster Relief Appropriations Act of 2013 (PL 113-2) and was conducted by the U.S. Geological Survey (USGS) in cooperation with the National Oceanic and Atmospheric Administration (NOAA).
\nYoung of year Pomatomus saltatrix (bluefish) were collected from nine sites in New Jersey (N.J.) and New York (N.Y.) including Barnegat Bay, N.J., Sandy Hook Bay, N.J., Jamaica Bay, N.Y., and Great South Bay, N.Y., and analyzed for indicators of health and chemical contamination. At each bluefish sampling location, bed sediment was also collected and analyzed for a suite of contaminants. Resident mussels, Mytilus edulis (blue mussels) and (or) Geukensia demissa (ribbed mussels), were collected from 11 historic NOAA Mussel Watch Program sites along the N.J. and N.Y. coastlines in the winter/spring of 2014 and analyzed for contaminants. Individual age of a subset of the mussels sampled was also determined at each site.
\nBed sediment samples were analyzed for a suite of organic contaminants including 34 polychlorinated biphenyl (PCB) congeners, 28 polybrominated diphenyl ether (PBDE) congeners, 24 organochlorine pesticides (OCPs), 53 polycyclic aromatic hydrocarbons (PAHs) and alkylated PAHs, 33 aliphatic hydrocarbons (AHs), and 10 petroleum biomarkers (steranes and hopanes). Bed sediment collected from the Navesink River (Sandy Hook, N.J.), Metedeconk River (Barnegat Bay, N.J.), and Toms River (Barnegat Bay, N.J.) had the highest concentrations of contaminants compared to the other sites.
\nBluefish and mussel tissue collected throughout the study area was analyzed for 34 PCB congeners, 28 PBDE congeners, and 24 OCPs. Thirty-three PCB congeners, 22 PBDE congeners, and 24 OCPs were detected in the bluefish analyzed. The highest median concentrations of total PCBs were present in tissue from Jamaica Bay, N.Y., whereas the highest median concentrations of total PBDEs and total OCPs were present in tissue from Sandy Hook Bay. Of the OCPs detected, p,p’-DDE was found in 99 percent (%) of the tissue samples and at the highest median concentrations compared to the other OCPs.
\nFish health assessments were conducted on 20 fish from the 4 bays. Results indicate that the sex ratio and the mean total length varied by site. Physical fish damage, such as lesions and parasites, was observed in fish from all four bays. The most common parasite observed visually was the presence of Livoneca redmanii, an ectoparasitic gill isopod, which can cause localized gill erosion. The prevalence of the gill isopod infestation ranged from 20% at Great South Bay, N.Y., to 35% at Jamaica Bay, N.Y.
\nTwenty three PCB congeners, 9 PBDE congeners, and 20 OCPs were detected in composite mussel samples collected throughout the study area. The co-eluting PCB congeners 153 and 132, PBDE 47, 99, and 100, and p,p’-DDE were detected in samples from each site. The highest median concentrations of PCBs and PBDEs were present in mussels from Raritan Bay, N.Y., whereas the highest median concentrations of OCPs were present in mussels from Fire Island Inlet, N.Y., and Shark River, N.J. Mytilus edulis (blue mussels) and Geukensia demissa (ribbed mussels) were thin-sectioned and aged. The blue mussels collected ranged in age from 4 to 13 years, and the ribbed mussels ranged in age from 3 to 12 years.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds956","collaboration":"Prepared in cooperation with the National Oceanic and Atmospheric Administration","usgsCitation":"Smalling, K.L., Deshpande, A.D., Blazer, V.S., Galbraith, H., Dockum, B.W., Romanok, K.M., Colella, K., Deetz, A.C., Fisher, I.J., Imbrigiotta, T.E., Sharack, B., Sumner, L, Timmons, D., Trainor, J., Wieczorek, D, Samson, J., Reilly, T.J., and Focazio, M.J., 2015, Chemical and ancillary data associated with bed sediment, young of year bluefish (Pomatomus saltatrix) tissue, and mussel (Mytilus edulis and Geukensia demissa) tissue collected after Hurricane Sandy in bays and estuaries of New Jersey and New York, 2013–14: U.S. Geological Survey Data Series 956, 18 p., https://dx.doi.org/10.3133/ds956.","productDescription":"Report: x, 18 p.; Tables","numberOfPages":"32","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-066280","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":307934,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0956/ds956.pdf","text":"Report","size":"12.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 956"},{"id":307935,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/ds/0956/ds956_tables.xlsx","text":"DS 956 Tables","size":"226 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"DS 956","linkHelpText":"Excel workbook containing tables 1–21"},{"id":307933,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/0956/coverthb.jpg"}],"country":"United States","state":"New Jersey, New York","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.39117431640625,\n 40.065460682065535\n ],\n [\n -74.39117431640625,\n 41.32320110223851\n ],\n [\n -71.88079833984375,\n 41.32320110223851\n ],\n [\n -71.88079833984375,\n 40.065460682065535\n ],\n [\n -74.39117431640625,\n 40.065460682065535\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New Jersey Water Science Center
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The Palos Verdes Fault (PVF) is one of few active faults in Southern California that crosses the shoreline and can be studied using both terrestrial and subaqueous methodologies. To characterize the near-seafloor fault morphology, tectonic influences on continental slope sedimentary processes and late Pleistocene to present slip rate, a grid of high-resolution multibeam bathymetric data, and chirp subbottom profiles were acquired with an autonomous underwater vehicle (AUV) along the main trace of PVF in water depths between 250 and 600 m. Radiocarbon dates were obtained from vibracores collected using a remotely operated vehicle (ROV) and ship-based gravity cores. The PVF is expressed as a well-defined seafloor lineation marked by subtle along-strike bends. Right-stepping transtensional bends exert first-order control on sediment flow dynamics and the spatial distribution of Holocene depocenters; deformed strata within a small pull-apart basin record punctuated growth faulting associated with at least three Holocene surface ruptures. An upper (shallower) landslide scarp, a buried sedimentary mound, and a deeper scarp have been right-laterally offset across the PVF by 55 ± 5, 52 ± 4 , and 39 ± 8 m, respectively. The ages of the upper scarp and buried mound are approximately 31 ka; the age of the deeper scarp is bracketed to 17–24 ka. These three piercing points bracket the late Pleistocene to present slip rate to 1.3–2.8 mm/yr and provide a best estimate of 1.6–1.9 mm/yr. The deformation observed along the PVF is characteristic of strike-slip faulting and accounts for 20–30% of the total right-lateral slip budget accommodated offshore Southern California.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2015JB011938","usgsCitation":"Brothers, D., Conrad, J.E., Maier, K., Paull, C.K., McGann, M., and Caress, D.W., 2015, The Palos Verdes Fault offshore southern California: late Pleistocene to present tectonic geomorphology, seascape evolution and slip rate estimate based on AUV and ROV surveys: Journal of Geophysical Research B: Solid Earth, v. 120, no. 7, p. 4734-4758, https://doi.org/10.1002/2015JB011938.","productDescription":"25 p.","startPage":"4734","endPage":"4758","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063656","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":307951,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Palos Verdes Fault","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.39691162109375,\n 33.30987251398259\n ],\n [\n -118.39691162109375,\n 33.8430453147447\n ],\n [\n -117.75421142578125,\n 33.8430453147447\n ],\n [\n -117.75421142578125,\n 33.30987251398259\n ],\n [\n -118.39691162109375,\n 33.30987251398259\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"120","issue":"7","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-07-30","publicationStatus":"PW","scienceBaseUri":"55eff8a9e4b0dacf699e9fe2","chorus":{"doi":"10.1002/2015jb011938","url":"http://dx.doi.org/10.1002/2015jb011938","publisher":"Wiley-Blackwell","authors":"Brothers Daniel S., Conrad James E., Maier Katherine L., Paull Charles K., McGann Mary, Caress David W.","journalName":"Journal of Geophysical Research: Solid Earth","publicationDate":"7/2015"},"contributors":{"authors":[{"text":"Brothers, Daniel S. dbrothers@usgs.gov","contributorId":140096,"corporation":false,"usgs":true,"family":"Brothers","given":"Daniel S.","email":"dbrothers@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":571527,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conrad, James E. 0000-0001-6655-694X jconrad@usgs.gov","orcid":"https://orcid.org/0000-0001-6655-694X","contributorId":2316,"corporation":false,"usgs":true,"family":"Conrad","given":"James","email":"jconrad@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":571528,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Maier, Katherine L.","contributorId":91411,"corporation":false,"usgs":true,"family":"Maier","given":"Katherine L.","affiliations":[],"preferred":false,"id":571529,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Paull, Charles K. 0000-0001-5940-3443","orcid":"https://orcid.org/0000-0001-5940-3443","contributorId":55825,"corporation":false,"usgs":false,"family":"Paull","given":"Charles","email":"","middleInitial":"K.","affiliations":[{"id":7043,"text":"University of North Carolina","active":true,"usgs":false}],"preferred":true,"id":571530,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McGann, Mary L. 0000-0002-3057-2945 mmcgann@usgs.gov","orcid":"https://orcid.org/0000-0002-3057-2945","contributorId":147188,"corporation":false,"usgs":true,"family":"McGann","given":"Mary L.","email":"mmcgann@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":571531,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Caress, David W.","contributorId":147392,"corporation":false,"usgs":false,"family":"Caress","given":"David","email":"","middleInitial":"W.","affiliations":[{"id":16837,"text":"MBARI","active":true,"usgs":false}],"preferred":false,"id":571532,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70142444,"text":"70142444 - 2015 - Ground motion simulation for the 23 August 2011, Mineral, Virginia earthquake using physics-based and stochastic broadband methods","interactions":[],"lastModifiedDate":"2016-01-29T10:44:48","indexId":"70142444","displayToPublicDate":"2015-09-08T12:45:00","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":"Ground motion simulation for the 23 August 2011, Mineral, Virginia earthquake using physics-based and stochastic broadband methods","docAbstract":"Three broadband simulation methods are used to generate synthetic ground motions for the 2011 Mineral, Virginia, earthquake and compare with observed motions. The methods include a physics‐based model by Hartzell et al. (1999, 2005), a stochastic source‐based model by Boore (2009), and a stochastic site‐based model by Rezaeian and Der Kiureghian (2010, 2012). The ground‐motion dataset consists of 40 stations within 600 km of the epicenter. Several metrics are used to validate the simulations: (1) overall bias of response spectra and Fourier spectra (from 0.1 to 10 Hz); (2) spatial distribution of residuals for GMRotI50 peak ground acceleration (PGA), peak ground velocity, and pseudospectral acceleration (PSA) at various periods; (3) comparison with ground‐motion prediction equations (GMPEs) for the eastern United States. Our results show that (1) the physics‐based model provides satisfactory overall bias from 0.1 to 10 Hz and produces more realistic synthetic waveforms; (2) the stochastic site‐based model also yields more realistic synthetic waveforms and performs superiorly for frequencies greater than about 1 Hz; (3) the stochastic source‐based model has larger bias at lower frequencies (<0.5 Hz) and cannot reproduce the varying frequency content in the time domain. The spatial distribution of GMRotI50 residuals shows that there is no obvious pattern with distance in the simulation bias, but there is some azimuthal variability. The comparison between synthetics and GMPEs shows similar fall‐off with distance for all three models, comparable PGA and PSA amplitudes for the physics‐based and stochastic site‐based models, and systematic lower amplitudes for the stochastic source‐based model at lower frequencies (<0.5 Hz).
","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Bulletin of the Seismological Society of America","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Seismological Society of America","publisherLocation":"El Cerrito","doi":"10.1785/0120140311","usgsCitation":"Sun, X., Hartzell, S.H., and Rezaeian, S., 2015, Ground motion simulation for the 23 August 2011, Mineral, Virginia earthquake using physics-based and stochastic broadband methods: Bulletin of the Seismological Society of America, v. 105, no. 5, p. 2641-2661, https://doi.org/10.1785/0120140311.","productDescription":"21 p.","startPage":"2641","endPage":"2661","numberOfPages":"21","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063943","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":310289,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.5068359375,\n 32.731840896865684\n ],\n [\n -84.5068359375,\n 43.16512263158296\n ],\n [\n -73.5205078125,\n 43.16512263158296\n ],\n [\n -73.5205078125,\n 32.731840896865684\n ],\n [\n -84.5068359375,\n 32.731840896865684\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"105","issue":"5","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-09-08","publicationStatus":"PW","scienceBaseUri":"5628b734e4b0d158f5926c22","contributors":{"authors":[{"text":"Sun, Xiaodan","contributorId":139583,"corporation":false,"usgs":false,"family":"Sun","given":"Xiaodan","email":"","affiliations":[{"id":6672,"text":"former: USGS Southwest Biological Science Center, Colorado Plateau Research Station, Flagstaff, AZ. Current address: TN-SCORE, Univ of Tennessee, Knoxville, TN, e-mail: jennen@gmail.com","active":true,"usgs":false}],"preferred":false,"id":541902,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hartzell, Stephen H. 0000-0003-0858-9043 shartzell@usgs.gov","orcid":"https://orcid.org/0000-0003-0858-9043","contributorId":2594,"corporation":false,"usgs":true,"family":"Hartzell","given":"Stephen","email":"shartzell@usgs.gov","middleInitial":"H.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":541903,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rezaeian, Sanaz 0000-0001-7589-7893 srezaeian@usgs.gov","orcid":"https://orcid.org/0000-0001-7589-7893","contributorId":4395,"corporation":false,"usgs":true,"family":"Rezaeian","given":"Sanaz","email":"srezaeian@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":541904,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70147396,"text":"ofr20151080 - 2015 - Methods for evaluating potential sources of chloride in surface waters and groundwaters of the conterminous United States","interactions":[],"lastModifiedDate":"2018-04-03T11:36:56","indexId":"ofr20151080","displayToPublicDate":"2015-09-04T13:30:00","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":"2015-1080","title":"Methods for evaluating potential sources of chloride in surface waters and groundwaters of the conterminous United States","docAbstract":"Chloride exists as a major ion in most natural waters, but many anthropogenic sources are increasing concentrations of chloride in many receiving waters. Although natural concentrations in continental waters can be as high as 200,000 milligrams per liter, chloride concentrations that are suitable for freshwater ecology, human consumption, and agricultural and industrial water uses commonly are on the order of 10 to 1,000 milligrams per liter. “Road salt” frequently is identified as the sole source of anthropogenic chloride, but only about 30 percent of the salt consumed and released to the environment is used for deicing. Furthermore, several studies in Southern States where the use of deicing salt is minimal also show anthropogenic chloride in rising concentrations and in strong correlation to imperviousness and road density. This is because imperviousness and road density also are strongly correlated to population density. The term “road salt” is a misnomer because deicers applied to parking lots, sidewalks, and driveways can be a substantial source of chloride in some catchments because these land covers are comparable to roadways as a percentage of the total impervious area and commonly receive higher salt application rates than some roadways. Other sources of anthropogenic chloride include wastewater, dust control on unpaved roads, fertilizer, animal waste, irrigation, aquaculture, energy production wastes, and landfill leachates. The assumption that rising chloride concentrations in surface water or groundwater is indicative of contamination by deicing chemicals rather than one or more other potential sources may preclude the identification of toxic, carcinogenic, mutagenic, or endocrine-disrupting contaminants that are associated with many sources of elevated chloride concentrations. Once the sources of anthropogenic chloride in an area of interest have been identified and measured, water and solute budgets can be estimated to guide decisionmakers to identify and apply potential mitigation measures that can reduce the problem.
\nScientists, engineers, regulators, and decisionmakers need information about potential sources of chloride, water and solute budgets, and methods for collecting water-quality data to help identify potential sources. This information is needed to evaluate potential sources of chloride in areas where chloride may have adverse ecological effects or may degrade water supplies used for drinking water, agriculture, or industry. Knowledge of potential sources will help decisionmakers identify the best mitigation measures to reduce the total background chloride load, thereby reducing the potential for water-quality exceedances that occur because of superposition on rising background concentrations. Also, knowledge of potential sources may help decisionmakers identify the potential for the presence of contaminants that have toxic, carcinogenic, mutagenic, or endocrine-disrupting effects at concentrations that are lower by orders of magnitude than the chloride concentrations in the source water. This report is a comprehensive synthesis of relevant information, but it is not the result of an exhaustive search for literature on each topic. The potential adverse effects of chloride on infrastructure and the environment are not discussed in this report because these issues have been extensively documented elsewhere.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151080","collaboration":"Prepared in cooperation with the U.S. Department of Transportation Federal Highway Administration Office of Project Development and Environmental Review","usgsCitation":"Granato, G.E., DeSimone, L.A., Barbaro, J.R., and Jeznach, L.C., 2015, Methods for evaluating potential sources of chloride in surface waters and groundwaters of the conterminous United States: U.S. Geological Survey Open-File Report 2015–1080, 89 p., https://dx.doi.org/10.3133/ofr20151080.","productDescription":"ix, 89 p.","numberOfPages":"104","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-063136","costCenters":[{"id":376,"text":"Massachusetts Water Science 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U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
Or visit our Web site at:
http://newengland.water.usgs.gov
Mount St. Helens began erupting in late 2004 following an 18 year quiescence. Swarms of repeating earthquakes accompanied the extrusion of a mostly solid dacite dome over the next 4 years. In some cases the waveforms from these earthquakes evolved slowly, likely reflecting changes in the properties of the volcano that affect seismic wave propagation. We use coda-wave interferometry to quantify small changes in seismic velocity structure (usually <1%) between two similar earthquakes and employed waveforms from several hundred families of repeating earthquakes together to create a continuous function of velocity change observed at permanent stations operated within 20 km of the volcano. The high rate of earthquakes allowed tracking of velocity changes on an hourly time scale. Changes in velocity were largest near the newly extruding dome and likely related to shallow deformation as magma first worked its way to the surface. We found strong correlation between velocity changes and the inverse of real-time seismic amplitude measurements during the first 3 weeks of activity, suggesting that fluctuations of pressure in the shallow subsurface may have driven both seismicity and velocity changes. Velocity changes during the remainder of the eruption likely result from a complex interplay of multiple effects and are not well explained by any single factor alone, highlighting the need for complementary geophysical data when interpreting velocity changes.
","language":"English","publisher":"American Geophysical Union","publisherLocation":"Washington, D.C.","doi":"10.1002/2015JB012101","usgsCitation":"Hotovec-Ellis, A., Vidale, J., Gomberg, J.S., Thelen, W.A., and Moran, S.C., 2015, Changes in seismic velocity during the first 14 months of the 2004–2008 eruption of Mount St. Helens, Washington: Journal of Geophysical Research B: Solid Earth, v. 120, no. 9, p. 6226-6240, https://doi.org/10.1002/2015JB012101.","productDescription":"15 p.","startPage":"6226","endPage":"6240","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-067267","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":309373,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"120","issue":"9","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-09-04","publicationStatus":"PW","scienceBaseUri":"560d07ade4b058f706e542fb","contributors":{"authors":[{"text":"Hotovec-Ellis, A.J.","contributorId":147946,"corporation":false,"usgs":false,"family":"Hotovec-Ellis","given":"A.J.","affiliations":[{"id":16962,"text":"U. Washington","active":true,"usgs":false}],"preferred":false,"id":573396,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vidale, J.E.","contributorId":55849,"corporation":false,"usgs":true,"family":"Vidale","given":"J.E.","email":"","affiliations":[],"preferred":false,"id":573397,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gomberg, Joan S. 0000-0002-0134-2606 gomberg@usgs.gov","orcid":"https://orcid.org/0000-0002-0134-2606","contributorId":1269,"corporation":false,"usgs":true,"family":"Gomberg","given":"Joan","email":"gomberg@usgs.gov","middleInitial":"S.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":573395,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thelen, Weston A. 0000-0003-2534-5577 wthelen@usgs.gov","orcid":"https://orcid.org/0000-0003-2534-5577","contributorId":4126,"corporation":false,"usgs":true,"family":"Thelen","given":"Weston","email":"wthelen@usgs.gov","middleInitial":"A.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":573398,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Moran, Seth C. 0000-0001-7308-9649 smoran@usgs.gov","orcid":"https://orcid.org/0000-0001-7308-9649","contributorId":548,"corporation":false,"usgs":true,"family":"Moran","given":"Seth","email":"smoran@usgs.gov","middleInitial":"C.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":573399,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70156555,"text":"sir20155117 - 2015 - A conceptual framework and monitoring strategy for movement of saltwater in the coastal plain aquifer system of Virginia","interactions":[],"lastModifiedDate":"2015-09-04T11:18:05","indexId":"sir20155117","displayToPublicDate":"2015-09-04T10:30:00","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":"2015-5117","title":"A conceptual framework and monitoring strategy for movement of saltwater in the coastal plain aquifer system of Virginia","docAbstract":"A conceptual framework synthesizes previous studies to provide an understanding of conditions, processes, and relations of saltwater to groundwater withdrawal in the Virginia Coastal Plain aquifer system. A strategy for monitoring saltwater movement is based on spatial relations between the saltwater-transition zone and 612 groundwater-production wells that were regulated during 2013 by the Virginia Department of Environmental Quality. The vertical position and lateral distance and direction of the bottom of each production well’s screened interval was calculated relative to previously published groundwater chloride iso-concentration surfaces. Spatial analysis identified 81 production wells completed in the Yorktown-Eastover and Potomac aquifers that are positioned in closest proximity to the 250-milligrams-per-liter chloride surface, and from which chloride concentrations are most likely to increase above the U.S. Environmental Protection Agency’s 250-milligrams-per-liter secondary maximum-contaminant level. Observation wells are specified to distinguish vertical upconing from lateral intrusion among individual production wells. To monitor upconing, an observation well is to be collocated with each production well and completed at about the altitude of the 250-milligrams-per-liter chloride iso-concentration surface. To monitor lateral intrusion, a potential location of an observation well is projected from the bottom of each production well’s screened interval, in the lateral direction to the underlying chloride surface to a distance of 1 mile.
\nMonitoring potential withdrawal-induced movement of saltwater in the Virginia Coastal Plain aquifer system is needed to detect increases in chloride concentration before groundwater-production wells become contaminated. An investigation was undertaken during 2014 by the U.S. Geological Survey in cooperation with the Virginia Department of Environmental Quality, to provide a sound scientific understanding of saltwater movement and guidance to implement a monitoring program. Previous studies have theorized that the saltwater originated primarily from seawater repeatedly emplaced within aquifer sediments during the past about 65 million years. Subsequent flushing by fresh groundwater has been impeded across sediments filling the Chesapeake Bay impact crater. The resulting saltwater-transition zone has been mapped to exhibit a warped and steeply mounded dome shape about centered on the impact crater, and flanked by a nearly level and shallow plateau shape to the southeast. Groundwater chloride concentrations have historically fluctuated during periods of weeks to months, probably as a result of localized vertical upconing beneath individual production wells. Lateral intrusion takes several decades or more to horizontally displace groundwater across distances of about 1 mile toward production wells. Upconing is relatively immediate, but reversible, whereas lateral intrusion under the regionally landward hydraulic gradient may slowly, but permanently reposition the saltwater-transition zone. Upconing coupled with lateral intrusion is theorized to produce composite chloride-concentration trends that vary widely over time in response to changing water demands, and evolve dynamically from hydraulic interactions among multiple neighboring production wells.
\nSome aspects of observation-well construction and sampling are of particular importance to monitoring saltwater movement in the Virginia Coastal Plain aquifer system. Observation wells should feature screened intervals generally of no more than 10 feet that isolate distinct parts of the aquifer, and be thoroughly developed for removal of drilling fluid and introduced water. Presample purging should fully displace stratified saltwater in the well casing upward to the pump. Stable flow should be maintained as field parameters are measured and sample containers are filled with filtered water isolated from the atmosphere and unaffected by surface temperature. Groundwater samples from both upconing and lateral-intrusion observation wells should initially be collected four times per year when wells are newly established, but can be more optimally timed with withdrawal once responses in chloride concentrations can be reliably predicted. Concentrations of major ions (1) determine the dominant chemical composition of groundwater at each well, (2) establish the relative position of the well within the saltwater-transition zone, and (3) provide data quality control by calculation of sample charge balance. For these reasons, samples initially collected for the first year from newly established observation wells should be analyzed for calcium, magnesium, sodium, and potassium cations and chloride, bicarbonate, carbonate, sulfate, fluoride, and bromide anions. Inflection-point titration for alkalinity should be completed in the field. Analysis of chloride and field parameters may be adequate on a long-term basis once the dominant chemical composition at each well is established. Specific conductance may also provide a surrogate for chloride concentration depending on regulatory policy.
\nThe saltwater-movement monitoring strategy is limited and constrained. Relative monitoring needs among groundwater-production wells, and construction of observation wells, depend on the accuracy of previously mapped groundwater chloride iso-concentration surfaces. Production wells in similar proximity to saltwater can differ in aquifer hydraulic conductivity, rates of withdrawal, and screened-interval lengths. Only production wells making withdrawals reported to the Virginia Department of Environmental Quality have been accounted for; undocumented production wells can result in spurious changes in groundwater chloride concentration. Upconing observation wells should be as close as possible to corresponding production wells, so long as production wells are not damaged by borehole deviation. Projected locations of some lateral-intrusion observation wells may be precluded and require adjustment. Depths of upconing and lateral-intrusion observation wells may also require adjustment to be within the same aquifer as their corresponding production wells. Existing unused wells can be adapted as observation wells if differences from specified locations and construction are kept to a minimum and are accounted for. Where multiple production wells are in proximity, a modified monitoring approach may be needed to determine their net effect on changes in chloride concentration, and may require more than one lateral-intrusion observation well depending on the vertical positions of production-well screened intervals.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155117","collaboration":"Prepared in cooperation with the Virginia Department of Environmental Quality","usgsCitation":"McFarland, E.R., 2015, A conceptual framework and monitoring strategy for movement of saltwater in the Coastal Plain aquifer system of Virginia: U.S. Geological Survey Scientific Investigations Report 2015–5117, 30 p., 1 pl., https://dx.doi.org/10.3133/sir20155117.","productDescription":"Report: vi, 30 p.; Plate: 24 x 35 inches; Table","numberOfPages":"40","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-062904","costCenters":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true}],"links":[{"id":307898,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5117/coverthb.jpg"},{"id":307899,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5117/sir20155117.pdf","text":"Report","size":"1.30 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5117"},{"id":307900,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2015/5117/sir20155117_attachment1.xlsx","text":"Attachment 1","size":"114 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2015-5117","linkHelpText":"Groundwater-production Wells, Vertical Positions and Lateral Distances and Directions Relative to Chloride Iso-concentration Surfaces, and Projected Locations of Lateral-intrusion Observation Wells"},{"id":307901,"rank":4,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2015/5117/sir20155117_plate1.pdf","text":"Plate 1","size":"399 KB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5117","linkHelpText":"Locations of Groundwater-Production Wells, Projected Locations of Lateral Intrusion Observation Wells, and the Configuration of the 250-Milligrams-Per-Liter Chloride Iso-Concentration Surface"}],"country":"United States","state":"Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -78.24462890625,\n 36.51405119943165\n ],\n [\n -78.24462890625,\n 38.436379603\n ],\n [\n -75.3387451171875,\n 38.436379603\n ],\n [\n -75.3387451171875,\n 36.51405119943165\n ],\n [\n -78.24462890625,\n 36.51405119943165\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Virginia Water Science Center
U.S. Geological Survey
1730 East Parham Road
Richmond, VA 23228
(804) 261-2600
Or visit the Virginia Water Science Center Web site:
http://va.water.usgs.gov/
The Colorado River and its tributaries supply water to more than 35 million people in the United States and 3 million people in Mexico, irrigating more than 4.5 million acres of farmland, and generating about 12 billion kilowatt hours of hydroelectric power annually. The Upper Colorado River Basin, encompassing more than 110,000 square miles (mi2), contains the headwaters of the Colorado River (also known as the River) and is an important source of snowmelt runoff to the River. Groundwater discharge also is an important source of water in the River and its tributaries, with estimates ranging from 21 to 58 percent of streamflow in the upper basin. Planning for the sustainable management of the Colorado River in future climates requires an understanding of the Upper Colorado River Basin groundwater system. This report documents input datasets for a Soil-Water Balance groundwater recharge model that was developed for the Upper Colorado River Basin.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151160","collaboration":"Prepared in cooperation with the Bureau of Reclamation and the USGS Groundwater Resources Program","usgsCitation":"Tillman, F., 2015, Documentation of input datasets for the soil-water balance groundwater recharge model of the Upper Colorado River Basin: U.S. Geological Survey Open-File Report 2015-1160, v, 17 p., https://doi.org/10.3133/ofr20151160.","productDescription":"v, 17 p.","numberOfPages":"26","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-066684","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":307918,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1160/coverthb.jpg"},{"id":307919,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1160/ofr20151160.pdf","text":"Report","size":"3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1160 PDF"},{"id":316699,"rank":3,"type":{"id":28,"text":"Dataset"},"url":"https://water.usgs.gov/lookup/getspatial?ofr_2015_1160_soil-water_balance"}],"country":"Mexico, United States","state":"Arizona, Colorado, New Mexico, Utah, Wyoming","otherGeospatial":"Upper Colorado River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.69937133789062,\n 36.730079507078415\n ],\n [\n -111.68083190917969,\n 36.730079507078415\n ],\n [\n -111.64581298828125,\n 36.72677751526221\n ],\n [\n -111.4068603515625,\n 36.67723060234619\n ],\n [\n -111.181640625,\n 36.54936246839778\n ],\n [\n -110.45654296875,\n 36.46105407505434\n ],\n [\n -109.8687744140625,\n 35.991340960635405\n ],\n [\n -109.5062255859375,\n 35.67068501330236\n ],\n [\n -109.21508789062499,\n 35.48751102385376\n ],\n [\n -108.907470703125,\n 35.34425514918409\n ],\n [\n -107.5286865234375,\n 35.290468565908775\n ],\n [\n -107.2760009765625,\n 35.28150065789119\n ],\n [\n -107.215576171875,\n 35.31736632923788\n ],\n [\n -107.13317871093749,\n 35.460669951495305\n ],\n [\n -106.9793701171875,\n 35.62604706595698\n ],\n [\n -106.94091796875,\n 35.817813158696616\n ],\n [\n -106.875,\n 36.26199220445664\n ],\n [\n -106.842041015625,\n 36.67723060234619\n ],\n [\n -106.864013671875,\n 37.02886944696474\n ],\n [\n -107.0068359375,\n 37.21283151445594\n ],\n [\n -107.33642578124999,\n 37.37015718405753\n ],\n [\n -107.545166015625,\n 37.55328764595765\n ],\n [\n -107.666015625,\n 37.74465712069939\n ],\n [\n -107.42431640625,\n 37.84883250647402\n ],\n [\n -107.07275390625,\n 37.90953361677018\n ],\n [\n -106.6552734375,\n 38.004819966413194\n ],\n [\n -106.666259765625,\n 38.33303882235456\n ],\n [\n -106.69921875,\n 38.685509760012\n ],\n [\n -106.875,\n 39.13006024213511\n ],\n [\n -106.435546875,\n 39.40224434029275\n ],\n [\n -105.9521484375,\n 39.740986355883564\n ],\n [\n -105.908203125,\n 40.34654412118006\n ],\n [\n -105.99609375,\n 40.613952441166596\n ],\n [\n -106.435546875,\n 40.74725696280421\n ],\n [\n -106.69921875,\n 41.64007838467894\n ],\n [\n -107.57812499999999,\n 42.65012181368025\n ],\n [\n -108.10546875,\n 42.84375132629023\n ],\n [\n -108.8525390625,\n 43.13306116240612\n ],\n [\n -109.423828125,\n 43.197167282501276\n ],\n [\n -109.77539062499999,\n 43.42100882994726\n ],\n [\n -109.9072265625,\n 43.67581809328341\n ],\n [\n -110.3466796875,\n 43.83452678223682\n ],\n [\n -110.61035156249999,\n 43.67581809328341\n ],\n [\n -110.74218749999999,\n 43.13306116240612\n ],\n [\n -110.8740234375,\n 42.19596877629178\n ],\n [\n -111.0498046875,\n 41.44272637767212\n ],\n [\n -111.0498046875,\n 41.19518982948959\n ],\n [\n -111.181640625,\n 41.04621681452063\n ],\n [\n -111.37939453125,\n 40.94671366508002\n ],\n [\n -111.533203125,\n 40.613952441166596\n ],\n [\n -111.73095703125,\n 40.245991504199026\n ],\n [\n -111.884765625,\n 39.8928799002948\n ],\n [\n -111.97265625,\n 39.33429742980725\n ],\n [\n -112.2802734375,\n 39.11301365149975\n ],\n [\n -112.43408203124999,\n 38.856820134743636\n ],\n [\n -112.60986328125,\n 38.59970036588819\n ],\n [\n -112.60986328125,\n 38.376115424036016\n ],\n [\n -112.67578124999999,\n 38.22091976683121\n ],\n [\n -112.8955078125,\n 37.87485339352928\n ],\n [\n -113.02734374999999,\n 37.579412513438385\n ],\n [\n -113.02734374999999,\n 37.26530995561875\n ],\n [\n -112.9833984375,\n 37.00255267215955\n ],\n [\n -112.67578124999999,\n 36.756490329505155\n ],\n [\n -112.34619140625,\n 36.5978891330702\n ],\n [\n -111.97265625,\n 36.56260003738548\n ],\n [\n -111.69937133789062,\n 36.730079507078415\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Arizona Water Science Center
U.S. Geological Survey
520 N. Park Avenue
Tucson, AZ 85719
http://az.water.usgs.gov/
Three different geophysical sensor types were used to characterize the underwater pressure waves generated by the underwater firing of a seismic water gun and their suitability for establishing a pressure barrier to potentially direct or prevent the movement of the Asian carps. The sensors used to collect the seismic information were blast rated hydrophones and underwater blast sensors. Specific location information for the water guns and the sensors was obtained using either laser rangefinders or differentially corrected global positioning systems (GPS).
\nTwo separate studies are discussed in this report. The two studies were completed during September 2012 and July 2013. Both of these studies took place in an earthen testing pond on the campus of Upper Midwest Environmental Sciences Center (UMESC) in La Crosse, Wisconsin.
\nPrevious studies had identified 5 pounds per square inch (lb/in2) as a target value for the successful operation of a water gun barrier. The September 2012 study evaluated the performance of 1-cubic-inch (in3) and 80-in3 water guns. Data from the 1-in3 gun showed that it produces a very planar wave with limited effect on the depths above and below its gun ports. The 1-in3 gun did not produce the 5-lb/in2
\ntarget pressure at a sufficient distance to be considered effective. The 80-in3 gun produced a bowl-shaped pressure field with the 5-lb/in2 target radius at the surface extending to 45 feet.
\nThe July 2013 study consisted of three scenarios: fish behavior, single gun assessment, and experimental barrier evaluation. The fish behavior scenario simulated the pond conditions from previous studies. Two 80-in3 water guns were fired in the south end of the testing pond. Pressures essentially doubled from the testing of the single 80-in3 water gun. The single gun assessment scenario sought to replicate the setup of the 80-in3 scenario in September 2012, but with additional sensors to better define the pressure field. The 5-lb/in2 target pressure field continued to show a radius ranging from 40 to 45 feet, dependent on the pressure of the input air. The final scenario, the experimental barrier evaluation, showed that a two-dimensional continuous plane of 5 lb/in2 can be created between two 80-in3 water guns to a separation of 99 feet and a depth of 6.5 feet with 1,500 lb/in2 of input air.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151130","collaboration":"Prepared in cooperation with U.S. Environmental Protection Agency, Great Lakes Restoration Initiative","usgsCitation":"Adams, R.F., and Morrow, W.S., 2015, Geophysical investigation of the pressure field produced by water guns at a pond site in La Crosse, Wisconsin: U.S. Geological Survey Open-File Report 2015–1130, 24 p., 1 app., https://dx.doi.org/10.3133/ofr20151130.","productDescription":"iv, 56 p.","numberOfPages":"64","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2012-09-01","temporalEnd":"2013-07-31","ipdsId":"IP-053140","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":307792,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1130/coverthb.jpg"},{"id":307793,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1130/ofr20151130.pdf","text":"Report","size":"12.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1130"}],"country":"United States","state":"Wisconsin","city":"La Crosse","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.25677585601807,\n 43.8665583482127\n ],\n [\n -91.25677585601807,\n 43.86934288877363\n ],\n [\n -91.24935150146484,\n 43.86934288877363\n ],\n [\n -91.24935150146484,\n 43.8665583482127\n ],\n [\n -91.25677585601807,\n 43.8665583482127\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Illinois Water Science Center
405 N. Goodwin
Urbana, IL 61801
(217) 328-8747
http://il.water.usgs.gov/
Understanding seasonal distribution and movement patterns of animals that migrate long distances is an essential part of monitoring and conserving their populations. Compared to migratory birds and other more conspicuous migrants, we know very little about the movement patterns of many migratory bats. Hoary bats (Lasiurus cinereus), a cryptic, wide-ranging, long-distance migrant, comprise a substantial proportion of the tens to hundreds of thousands of bat fatalities estimated to occur each year at wind turbines in North America. We created seasonally-dynamic species distribution models (SDMs) from 2,753 museum occurrence records collected over five decades in North America to better understand the seasonal geographic distributions of hoary bats. We used 5 SDM approaches: logistic regression, multivariate adaptive regression splines, boosted regression trees, random forest, and maximum entropy and consolidated outputs to generate ensemble maps. These maps represent the first formal hypotheses for sex- and season-specific hoary bat distributions. Our results suggest that North American hoary bats winter in regions with relatively long growing seasons where temperatures are moderated by proximity to oceans, and then move to the continental interior for the summer. SDMs suggested that hoary bats are most broadly distributed in autumn—the season when they are most susceptible to mortality from wind turbines; this season contains the greatest overlap between potentially suitable habitat and wind energy facilities. Comparing wind-turbine fatality data to model outputs could test many predictions, such as ‘risk from turbines is highest in habitats between hoary bat summering and wintering grounds’. Although future field studies are needed to validate the SDMs, this study generated well-justified and testable hypotheses of hoary bat migration patterns and seasonal distribution.
","language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pone.0132599","collaboration":"Prepared in collaboration with University of Colorado Denver","usgsCitation":"Hayes, M.A., Cryan, P.M., and Wunder, M., 2015, Seasonally-dynamic presence-only species distribution models for a cryptic migratory bat impacted by wind energy development: PLoS ONE, v. 10, no. 7, e0132599; 20 p., https://doi.org/10.1371/journal.pone.0132599.","productDescription":"e0132599; 20 p.","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"1950-01-01","temporalEnd":"2000-12-31","ipdsId":"IP-066454","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":471812,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0132599","text":"Publisher Index 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PSC"},"noUsgsAuthors":false,"publicationDate":"2015-07-24","publicationStatus":"PW","scienceBaseUri":"55e96127e4b0dacf699e785e","contributors":{"authors":[{"text":"Hayes, Mark A. hayesm@usgs.gov","contributorId":147339,"corporation":false,"usgs":true,"family":"Hayes","given":"Mark","email":"hayesm@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":571312,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cryan, Paul M. 0000-0002-2915-8894 cryanp@usgs.gov","orcid":"https://orcid.org/0000-0002-2915-8894","contributorId":2356,"corporation":false,"usgs":true,"family":"Cryan","given":"Paul","email":"cryanp@usgs.gov","middleInitial":"M.","affiliations":[{"id":547,"text":"Rocky Mountain Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":571311,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wunder, Michael B.","contributorId":80599,"corporation":false,"usgs":false,"family":"Wunder","given":"Michael B.","affiliations":[{"id":6674,"text":"Department of Integrative Biology, University of Colorado Denver","active":true,"usgs":false}],"preferred":false,"id":571313,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70157011,"text":"70157011 - 2015 - Using sutures to attach miniature tracking tags to small bats for multimonth movement and behavioral studies","interactions":[],"lastModifiedDate":"2015-09-03T12:03:02","indexId":"70157011","displayToPublicDate":"2015-09-03T13:00:00","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":"Using sutures to attach miniature tracking tags to small bats for multimonth movement and behavioral studies","docAbstract":"1. Determining the detailed movements of individual animals often requires them to carry tracking devices, but tracking broad-scale movement of small bats (< 30g) has been limited by transmitter technology and long-term attachment methods. This limitation inhibits our understanding of bat dispersal and migration, particularly in the context of emerging conservation issues like fatalities at wind turbines and diseases. 2. We tested a novel method of attaching lightweight global positioning system (GPS) tags and geolocating data loggers to small bats. We used monofilament, synthetic, absorbable sutures to secure GPS tags and data loggers to the skin of anesthetized big brown bats (Eptesicus fuscus) in Colorado and hoary bats (Lasiurus cinereus) in California. 3. GPS tags and data loggers were sutured to 17 bats in this study. Three tagged bats were recaptured seven months after initial deployment, with tags still attached; none of these bats showed ill effects from the tag. No severe injuries were apparent upon recapture of 6 additional bats that carried tags up to 26 days after attachment, however one of the bats exhibited skin chafing. 4. Use of absorbable sutures to affix small tracking devices seems to be a safe, effective method for studying movements of bats over multiple months, although additional testing is warranted. This new attachment method has the potential to quickly advance our understanding of small bats, particularly as more-sophisticated miniature tracking devices (e.g., satellite tags) become available.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.1584","collaboration":"Prepared in cooperation with Wildlife Veterinary Consulting; U.S. Forest Service Pacific Southwest Research Station; Bat Conservation International","usgsCitation":"Castle, K.T., Weller, T.J., Cryan, P.M., Hein, C.D., and Schirmacher, M.R., 2015, Using sutures to attach miniature tracking tags to small bats for multimonth movement and behavioral studies: Ecology and Evolution, v. 5, no. 14, p. 2980-2989, https://doi.org/10.1002/ece3.1584.","productDescription":"10 p.","startPage":"2980","endPage":"2989","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"2014-08-01","temporalEnd":"2015-05-31","ipdsId":"IP-066197","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":471813,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.1584","text":"Publisher Index Page"},{"id":307915,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"5","issue":"14","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-07-04","publicationStatus":"PW","scienceBaseUri":"55e9612ae4b0dacf699e7863","contributors":{"authors":[{"text":"Castle, Kevin T.","contributorId":90616,"corporation":false,"usgs":true,"family":"Castle","given":"Kevin","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":571315,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Weller, Theodore J.","contributorId":105961,"corporation":false,"usgs":false,"family":"Weller","given":"Theodore","email":"","middleInitial":"J.","affiliations":[{"id":13261,"text":"USDA Forest Service, Pacific Southwest Research Station, Davis, California","active":true,"usgs":false}],"preferred":false,"id":571316,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cryan, Paul M. 0000-0002-2915-8894 cryanp@usgs.gov","orcid":"https://orcid.org/0000-0002-2915-8894","contributorId":2356,"corporation":false,"usgs":true,"family":"Cryan","given":"Paul","email":"cryanp@usgs.gov","middleInitial":"M.","affiliations":[{"id":547,"text":"Rocky Mountain Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":571314,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hein, Cris D.","contributorId":73910,"corporation":false,"usgs":false,"family":"Hein","given":"Cris","email":"","middleInitial":"D.","affiliations":[{"id":12591,"text":"Bat Conservation International","active":true,"usgs":false}],"preferred":false,"id":571317,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schirmacher, Michael R.","contributorId":76635,"corporation":false,"usgs":false,"family":"Schirmacher","given":"Michael","email":"","middleInitial":"R.","affiliations":[{"id":12591,"text":"Bat Conservation International","active":true,"usgs":false}],"preferred":false,"id":571318,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ]}