Wilderness areas in the United States are preserved for their untrammeled naturalness and opportunities for unconfined recreation. The Boundary Waters Canoe Area Wilderness has these qualities, but long-term recreation visitation pressures on campsites can cause significant ecological changes. This article explores changes on campsites, specifically examining non-native plant ecology over 3 decades. The research replicates a 1982 study analyzing vegetation composition and cover on campsites and environmentally paired controls. Camping activities have removed substantial tree cover on campsites, altering their ecological conditions and perceived wilderness character. Over the span of 32 years, the number of non-native plant species found on campsites has not risen, although their mean relative cover has increased significantly and they have spread to more sites. Of the 23 non-native herbs and grasses found on the campsites, only Cirsium arvense is considered a noxious weed by the state of Minnesota. Other noninvasive, non-native plants fall into a gray area in the context of \"naturalness\" for an area protected as Wilderness because they provide some positive ecological services even as they degrade wilderness character. Thus, wilderness managers face a difficult challenge in coping with the long-term impacts of visitor use on wilderness conditions and character.
","language":"English","publisher":"Oxford","doi":"10.5849/FS-2017-078","usgsCitation":"Eagleston, H., and Marion, J.L., 2018, “Naturalness” in designated Wilderness: Long-term changes in non-native plant dynamics on campsites, Boundary Waters, Minnesota: Forest Science, v. 64, no. 1, p. 50-56, https://doi.org/10.5849/FS-2017-078.","productDescription":"7 p.","startPage":"50","endPage":"56","ipdsId":"IP-088103","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":461057,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/10919/99355","text":"External Repository"},{"id":355527,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":355510,"type":{"id":15,"text":"Index Page"},"url":"https://academic.oup.com/forestscience/article/64/1/50/4804514"}],"country":"United States","state":"Minnesota","otherGeospatial":"Boundary Waters","volume":"64","issue":"1","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b46e5d2e4b060350a15d214","contributors":{"authors":[{"text":"Eagleston, Holly","contributorId":173611,"corporation":false,"usgs":false,"family":"Eagleston","given":"Holly","email":"","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":739637,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Marion, Jeffrey L. 0000-0003-2226-689X jeff_marion@usgs.gov","orcid":"https://orcid.org/0000-0003-2226-689X","contributorId":3614,"corporation":false,"usgs":true,"family":"Marion","given":"Jeffrey","email":"jeff_marion@usgs.gov","middleInitial":"L.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":739580,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70196845,"text":"70196845 - 2018 - Estimating wetland connectivity to streams in the Prairie Pothole Region: An isotopic and remote sensing approach","interactions":[],"lastModifiedDate":"2018-05-04T10:36:11","indexId":"70196845","displayToPublicDate":"2018-02-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Estimating wetland connectivity to streams in the Prairie Pothole Region: An isotopic and remote sensing approach","docAbstract":"Understanding hydrologic connectivity between wetlands and perennial streams is critical to understanding the reliance of stream flow on inputs from wetlands. We used the isotopic evaporation signal in water and remote sensing to examine wetland‐stream hydrologic connectivity within the Pipestem Creek watershed, North Dakota, a watershed dominated by prairie‐pothole wetlands. Pipestem Creek exhibited an evaporated‐water signal that had approximately half the isotopic‐enrichment signal found in most evaporatively enriched prairie‐pothole wetlands. Groundwater adjacent to Pipestem Creek had isotopic values that indicated recharge from winter precipitation and had no significant evaporative enrichment, indicating that enriched surface water did not contribute significantly to groundwater discharging into Pipestem Creek. The estimated surface water area necessary to generate the evaporation signal within Pipestem Creek was highly dynamic, varied primarily with the amount of discharge, and was typically greater than the immediate Pipestem Creek surface water area, indicating that surficial flow from wetlands contributed to stream flow throughout the summer. We propose a dynamic range of spilling thresholds for prairie‐pothole wetlands across the watershed allowing for wetland inputs even during low‐flow periods. Combining Landsat estimates with the isotopic approach allowed determination of potential (Landsat) and actual (isotope) contributing areas in wetland‐dominated systems. This combined approach can give insights into the changes in location and magnitude of surface water and groundwater pathways over time. This approach can be used in other areas where evaporation from wetlands results in a sufficient evaporative isotopic signal.
","language":"English","publisher":"AGU","doi":"10.1002/2017WR021016","usgsCitation":"Brooks, J.R., Mushet, D.M., Vanderhoof, M.K., Leibowitz, S.G., Christensen, J.R., Neff, B., Rosenberry, D.O., Rugh, W.D., and Alexander, L., 2018, Estimating wetland connectivity to streams in the Prairie Pothole Region: An isotopic and remote sensing approach: Water Resources Research, v. 54, no. 2, p. 955-977, https://doi.org/10.1002/2017WR021016.","productDescription":"23 p.","startPage":"955","endPage":"977","ipdsId":"IP-086197","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":469082,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/5903587","text":"Publisher Index Page"},{"id":353957,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Dakota","volume":"54","issue":"2","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2018-02-09","publicationStatus":"PW","scienceBaseUri":"5afee740e4b0da30c1bfc1cb","contributors":{"authors":[{"text":"Brooks, J. 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R.","contributorId":204686,"corporation":false,"usgs":false,"family":"Christensen","given":"J.","email":"","middleInitial":"R.","affiliations":[{"id":36974,"text":"U.S. Environmental Protection Agency, National Exposure Research Laboratory, Las Vegas, NV","active":true,"usgs":false}],"preferred":false,"id":734684,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Neff, Brian 0000-0003-3718-7350 bneff@usgs.gov","orcid":"https://orcid.org/0000-0003-3718-7350","contributorId":198885,"corporation":false,"usgs":true,"family":"Neff","given":"Brian","email":"bneff@usgs.gov","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":734685,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rosenberry, Donald O. 0000-0003-0681-5641 rosenber@usgs.gov","orcid":"https://orcid.org/0000-0003-0681-5641","contributorId":1312,"corporation":false,"usgs":true,"family":"Rosenberry","given":"Donald","email":"rosenber@usgs.gov","middleInitial":"O.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":734687,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Rugh, W. D.","contributorId":204687,"corporation":false,"usgs":false,"family":"Rugh","given":"W.","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":734688,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Alexander, L.C.","contributorId":204056,"corporation":false,"usgs":false,"family":"Alexander","given":"L.C.","email":"","affiliations":[{"id":36812,"text":"U.S. EPA, Office of Research and Development","active":true,"usgs":false}],"preferred":false,"id":734689,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70192339,"text":"70192339 - 2018 - An open source high-performance solution to extract surface water drainage networks from diverse terrain conditions","interactions":[],"lastModifiedDate":"2018-04-02T13:53:09","indexId":"70192339","displayToPublicDate":"2018-02-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1191,"text":"Cartography and Geographic Information Science","active":true,"publicationSubtype":{"id":10}},"title":"An open source high-performance solution to extract surface water drainage networks from diverse terrain conditions","docAbstract":"This paper describes a workflow for automating the extraction of elevation-derived stream lines using open source tools with parallel computing support and testing the effectiveness of procedures in various terrain conditions within the conterminous United States. Drainage networks are extracted from the US Geological Survey 1/3 arc-second 3D Elevation Program elevation data having a nominal cell size of 10 m. This research demonstrates the utility of open source tools with parallel computing support for extracting connected drainage network patterns and handling depressions in 30 subbasins distributed across humid, dry, and transitional climate regions and in terrain conditions exhibiting a range of slopes. Special attention is given to low-slope terrain, where network connectivity is preserved by generating synthetic stream channels through lake and waterbody polygons. Conflation analysis compares the extracted streams with a 1:24,000-scale National Hydrography Dataset flowline network and shows that similarities are greatest for second- and higher-order tributaries.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/15230406.2017.1337524","usgsCitation":"Stanislawski, L.V., Survila, K., Wendel, J., Liu, Y., and Buttenfield, B., 2018, An open source high-performance solution to extract surface water drainage networks from diverse terrain conditions: Cartography and Geographic Information Science, v. 45, no. 4, p. 319-328, https://doi.org/10.1080/15230406.2017.1337524.","productDescription":"10 p.","startPage":"319","endPage":"328","ipdsId":"IP-077833","costCenters":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"links":[{"id":350964,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"45","issue":"4","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2017-07-04","publicationStatus":"PW","scienceBaseUri":"5a7586d8e4b00f54eb1d81f2","contributors":{"authors":[{"text":"Stanislawski, Larry V. 0000-0002-9437-0576 lstan@usgs.gov","orcid":"https://orcid.org/0000-0002-9437-0576","contributorId":3386,"corporation":false,"usgs":true,"family":"Stanislawski","given":"Larry","email":"lstan@usgs.gov","middleInitial":"V.","affiliations":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true},{"id":404,"text":"NGTOC Rolla","active":true,"usgs":true}],"preferred":true,"id":715438,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Survila, Kornelijus 0000-0003-4851-6084","orcid":"https://orcid.org/0000-0003-4851-6084","contributorId":196791,"corporation":false,"usgs":false,"family":"Survila","given":"Kornelijus","email":"","affiliations":[],"preferred":false,"id":715439,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wendel, Jeffrey 0000-0003-0294-0250 jwendel@usgs.gov","orcid":"https://orcid.org/0000-0003-0294-0250","contributorId":196792,"corporation":false,"usgs":true,"family":"Wendel","given":"Jeffrey","email":"jwendel@usgs.gov","affiliations":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":715441,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Liu, Yan 0000-0003-2298-4728","orcid":"https://orcid.org/0000-0003-2298-4728","contributorId":196790,"corporation":false,"usgs":false,"family":"Liu","given":"Yan","email":"","affiliations":[],"preferred":false,"id":715442,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Buttenfield, Barbara P.","contributorId":145538,"corporation":false,"usgs":false,"family":"Buttenfield","given":"Barbara P.","affiliations":[{"id":16144,"text":"University of Colorado-Boulder","active":true,"usgs":false}],"preferred":false,"id":715440,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70194932,"text":"70194932 - 2018 - Mineral commodity summaries 2018","interactions":[],"lastModifiedDate":"2018-06-08T09:10:46","indexId":"70194932","displayToPublicDate":"2018-01-31T15:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":6,"text":"USGS Unnumbered Series"},"seriesTitle":{"id":368,"text":"Mineral Commodity Summaries","active":false,"publicationSubtype":{"id":6}},"title":"Mineral commodity summaries 2018","docAbstract":"This report is the earliest Government publication to furnish estimates covering 2017 nonfuel mineral industry data. Data sheets contain information on the domestic industry structure, Government programs, tariffs, and 5-year salient statistics for more than 90 individual minerals and materials.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/70194932","usgsCitation":"U.S. Geological Survey, 2018, Mineral commodity summaries 2018: U.S. Geological Survey, 200 p., https://doi.org/10.3133/70194932.","productDescription":"200 p.","numberOfPages":"204","ipdsId":"IP-094560","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":350834,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/graphics/minerals-commodity-2018.jpg"},{"id":350835,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://minerals.usgs.gov/minerals/pubs/mcs/","text":"Mineral Commodity Summaries Index Page","linkFileType":{"id":5,"text":"html"},"description":"Link to page with all USGS Mineral Commodities Summaries"}],"contact":"Director, National Minerals Information Center
U.S. Geological Survey
12201 Sunrise Valley Drive
988 National Center
Reston, VA 20192
Email: nmicrecordsmgt@usgs.gov
Digital flood-inundation maps for a 12.6-mile reach of the Withlacoochee River from Skipper Bridge Road to St. Augustine Road (Georgia State Route 133) were developed to depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the U.S. Geological Survey (USGS) streamgage at Withlacoochee River at Skipper Bridge Road, near Bemiss, Ga. (023177483). Real-time stage information from this streamgage can be used with these maps to estimate near real-time areas of inundation. The forecasted peak-stage information for the USGS streamgage at Withlacoochee River at Skipper Bridge Road, near Bemiss, Ga. (023177483), can be used in conjunction with the maps developed for this study to show predicted areas of flood inundation.
A one-dimensional step-backwater model was developed using the U.S. Army Corps of Engineers Hydrologic Engineer-ing Center’s River Analysis System (HEC–RAS) software for the Withlacoochee River and was used to compute flood profiles for a 12.6-mile reach of the Withlacoochee River. The hydraulic model was then used to simulate 23 water-surface profiles at 1.0-foot (ft) intervals at the Withlacoochee River near the Bemiss streamgage. The profiles ranged from the National Weather Service action stage of 10.7 ft, which is 131.0 ft above the North American Vertical Datum of 1988 (NAVD 88), to a stage of 32.7 ft, which is 153.0 ft above NAVD 88. The simulated water-surface profiles were then combined with a geographic information system digital elevation model—derived from light detection and ranging (lidar) data having a 4.0-ft horizontal resolution—to delineate the area flooded at each 1.0-ft interval of stream stage.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185011","collaboration":"Prepared in cooperation with the City of Valdosta, Georgia, and Lowndes County, Georgia","usgsCitation":"Musser, J.W., 2018, Flood-inundation maps for the Withlacoochee River from Skipper Bridge Road to St. Augustine Road, within the City of Valdosta, Georgia, and Lowndes County, Georgia: U.S. Geological Survey Scientific Investigations Report 2018–5011, 15 p., https://doi.org/10.3133/sir20185011.","productDescription":"Report: viii, 18 p.; Data release","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-087876","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":350785,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5011/coverthb.jpg"},{"id":350787,"rank":3,"type":{"id":30,"text":"Data 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South Atlantic Water Science Center
U.S. Geological Survey
720 Gracern Road
Columbia, SC 29210
Two identical Radar Stage Sensors from Forest Technology Systems were evaluated to determine if they are suitable for U.S. Geological Survey (USGS) hydrologic data collection. The sensors were evaluated in laboratory conditions to evaluate the distance accuracy of the sensor over the manufacturer’s specified operating temperatures and distance to water ranges. Laboratory results were compared to the manufacturer’s accuracy specification of ±0.007 foot (ft) and the USGS Office of Surface Water (OSW) policy requirement that water-level sensors have a measurement uncertainty of no more than 0.01 ft or 0.20 percent of the indicated reading. Both of the sensors tested were within the OSW policy requirement in both laboratory tests and within the manufacturer’s specification in the distance to water test over tested distances from 3 to 15 ft. In the temperature chamber test, both sensors were within the manufacturer’s specification for more than 90 percent of the data points collected over a temperature range of –40 to +60 degrees Celsius at a fixed distance of 8 ft. One sensor was subjected to an SDI-12 communication test, which it passed. A field test was conducted on one sensor at a USGS field site near Landon, Mississippi, from February 5 to March 29, 2016. Water-level measurements made by the radar during the field test were in agreement with those made by the Sutron Accubar Constant Flow Bubble Gauge.
Upon the manufacturer’s release of updated firmware version 1.09, additional SDI-12 and temperature testing was performed to evaluate added SDI-12 functions and verify that performance was unaffected by the update. At this time, an Axiom data logger is required to perform a firmware update on this sensor. The data confirmed the results of the original test. Based on the test results, the Radar Stage Sensor is a suitable choice for USGS hydrologic data collection.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171085","usgsCitation":"Kunkle, G.A., 2018, Evaluation of the Radar Stage Sensor manufactured by Forest Technology Systems—Results of laboratory and field testing: U.S. Geological Survey Open-File Report 2017–1085, 12 p., https://doi.org/10.3133/ofr20171085.","productDescription":"Report: iv, 12 p.; Data Release","numberOfPages":"20","onlineOnly":"Y","ipdsId":"IP-083860","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":350803,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F71C1VSR","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Evaluation of the Radar Stage Sensor Manufactured by Forest Technology Systems, Incorporated—Results of Laboratory and Field Testing"},{"id":350800,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1085/ofr20171085.pdf","text":"Report","size":"918 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017–1085"},{"id":350799,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1085/coverthb.jpg"}],"contact":"Chief, Hydrologic Instrumentation Facility
U.S. Geological Survey
Building 2101
Stennis Space Center, MS 39529
The purpose of the prediction grids for selected redox constituents—dissolved oxygen and dissolved manganese—are intended to provide an understanding of groundwater-quality conditions at the domestic and public-supply drinking water depths. The chemical quality of groundwater and the fate of many contaminants is influenced by redox processes in all aquifers, and understanding the redox conditions horizontally and vertically is critical in evaluating groundwater quality. The redox condition of groundwater—whether oxic (oxygen present) or anoxic (oxygen absent)—strongly influences the oxidation state of a chemical in groundwater. The anoxic dissolved oxygen thresholds of <0.5 milligram per liter (mg/L), <1.0 mg/L, and <2.0 mg/L were selected to apply broadly to regional groundwater-quality investigations. Although the presence of dissolved manganese in groundwater indicates strongly reducing (anoxic) groundwater conditions, it is also considered a “nuisance” constituent in drinking water, making drinking water undesirable with respect to taste, staining, or scaling. Three dissolved manganese thresholds, <50 micrograms per liter (µg/L), <150 µg/L, and <300 µg/L, were selected to create predicted probabilities of exceedances in depth zones used by domestic and public-supply water wells. The 50 µg/L event threshold represents the secondary maximum contaminant level (SMCL) benchmark for manganese (U.S. Environmental Protection Agency, 2017; California Division of Drinking Water, 2014), whereas the 300 µg/L event threshold represents the U.S. Geological Survey (USGS) health-based screening level (HBSL) benchmark, used to put measured concentrations of drinking-water contaminants into a human-health context (Toccalino and others, 2014). The 150 µg/L event threshold represents one-half the USGS HBSL. The resultant dissolved oxygen and dissolved manganese prediction grids may be of interest to water-resource managers, water-quality researchers, and groundwater modelers concerned with the occurrence of natural and anthropogenic contaminants related to anoxic conditions. Prediction grids for selected redox constituents and thresholds were created by the USGS National Water-Quality Assessment (NAWQA) modeling and mapping team.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3397","usgsCitation":"Rosecrans, C.Z., Nolan, B.T., and Gronberg, J.M., 2018, Maps showing predicted probabilities for selected dissolved oxygen and dissolved manganese threshold events in depth zones used by the domestic and public drinking water supply wells, Central Valley, California: U.S. Geological Survey Scientific Investigations Map 3397, 2 sheets, various scales, https://doi.org/10.3133/sim3397.","productDescription":"2 Sheets: 18.99 x 24.04 inches and 18.99 x 23.75 inches; Data Release","onlineOnly":"Y","ipdsId":"IP-083513","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":350545,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7T151S1","linkHelpText":"Probability distribution grids of dissolved oxygen and dissolved manganese concentrations at selected thresholds in drinking water depth zones, Central Valley, California"},{"id":350705,"rank":3,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3397/sim3397_plate1_.pdf","text":"Plate 1","size":"4.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3397","linkHelpText":" - Spatial Distribution of Predicted Probabilities for Selected Dissolved Oxygen Threshold Events"},{"id":350544,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3397/coverthb_.jpg"},{"id":350706,"rank":4,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3397/sim3397_plate2.pdf","text":"Plate 2","size":"4.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3397","linkHelpText":" - Spatial Distribution of Predicted Probabilities for Selected Dissolved Manganese Threshold Events"}],"country":"United States","state":"California","otherGeospatial":"Central Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.354736328125,\n 40.17887331434696\n ],\n [\n -122.2119140625,\n 38.02213147353745\n ],\n [\n -119.46533203125,\n 34.858890491257796\n ],\n [\n -118.54248046874999,\n 34.93097858831627\n ],\n [\n -118.57543945312501,\n 35.29943548054545\n ],\n [\n -118.93798828125,\n 36.465471886798134\n ],\n [\n -119.5751953125,\n 36.94989178681327\n ],\n [\n -120.487060546875,\n 37.70120736474139\n ],\n [\n -120.92651367187499,\n 38.05674222065296\n ],\n [\n -121.11328124999999,\n 38.676933444637925\n ],\n [\n -121.47583007812501,\n 39.39375459224348\n ],\n [\n -121.53076171875,\n 39.64799732373418\n ],\n [\n -121.871337890625,\n 39.977120098439634\n ],\n [\n -122.1240234375,\n 40.212440718286466\n ],\n [\n -122.310791015625,\n 40.212440718286466\n ],\n [\n -122.354736328125,\n 40.17887331434696\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
California Water Science Center
6000 J Street, Placer Hall
Sacramento, CA 95819
The U.S. Geological Survey (USGS) maintains and operates more than 8,200 continuous streamgages nationwide. Types of data that may be collected, computed, and stored for streamgages include streamgage height (water-surface elevation), streamflow, and water quality. The streamflow data allow scientists and engineers to calculate streamflow statistics, such as the 1-percent annual exceedance probability flood (also known as the 100-year flood), the mean flow, and the 7-day, 10-year low flow, which are used by managers to make informed water resource management decisions, at each streamgage location. Researchers, regulators, and managers also commonly need physical characteristics (basin characteristics) that describe the unique properties of a basin. Common uses for streamflow statistics and basin characteristics include hydraulic design, water-supply management, water-use appropriations, and flood-plain mapping for establishing flood-insurance rates and land-use zones. The USGS periodically publishes reports that update the values of basin characteristics and streamflow statistics at selected gaged locations (locations with streamgages), but these studies usually only update a subset of streamgages, making data retrieval difficult. Additionally, streamflow statistics and basin characteristics are most often needed at ungaged locations (locations without streamgages) for which published streamflow statistics and basin characteristics do not exist.
Missouri StreamStats is a web-based geographic information system that was created by the USGS in cooperation with the Missouri Department of Natural Resources to provide users with access to an assortment of tools that are useful for water-resources planning and management. StreamStats allows users to easily obtain the most recent published streamflow statistics and basin characteristics for streamgage locations and to automatically calculate selected basin characteristics and estimate streamflow statistics at ungaged locations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20183003","collaboration":"Prepared in cooperation with the Missouri Department of Natural Resources","usgsCitation":"Ellis, J.T., 2018, Missouri StreamStats—A water-resources web application: U.S. Geological Survey Fact Sheet 2018–3003, 6 p., https://doi.org/10.3133/fs20183003.","productDescription":"6 p.","onlineOnly":"N","ipdsId":" IP-091212","costCenters":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true}],"links":[{"id":350829,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2018/3003/coverthb.jpg"},{"id":350830,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2018/3003/fs20183003.pdf","text":"Report","size":"8.50 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2018–3003"}],"country":"United 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\"}}]}","contact":"Director, Missouri Water Science Center
U.S. Geological Survey
1400 Independence Road
Rolla, MO 65401
In Autumn 2015, USA National Phenology Network (USA-NPN) staff implemented new U.S. Geological Survey (USGS) data-management policies intended to ensure that the results of Federally funded research are made available to the public. The effort aimed both to improve USA-NPN data releases and to provide a model for similar programs within the USGS. This report provides an overview of the steps taken to ensure compliance, following the USGS Science Data Lifecycle, and provides lessons learned about the data-release process for USGS program leaders and data managers.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181007","usgsCitation":"Rosemartin, A., Langseth, M.L., Crimmins, T.M., and Weltzin, J.F., 2018, Development and release of phenological data products—A case study in compliance with federal open data policy: U.S. Geological Survey Open-File Report 2018–1007, 13 p., https://doi.org/10.3133/ofr20181007.","productDescription":"iv, 13 p.","numberOfPages":"18","onlineOnly":"Y","ipdsId":"IP-090322","costCenters":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true},{"id":37226,"text":"Core Science Analytics, Synthesis, and Libraries","active":true,"usgs":true}],"links":[{"id":350850,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1007/coverthb.jpg"},{"id":350851,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1007/ofr20181007.pdf","text":"Report","size":"350 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1007"}],"contact":"Ecosystems Mission Area
U.S. Geological Survey
12201 Sunrise Valley Dr., MS 300
Reston, VA 20192
Demand for high-volume, short duration water withdrawals could create water stress to aquatic organisms in Fayetteville Shale streams sourced for hydraulic fracturing fluids. We estimated potential water stress using permitted water withdrawal volumes and actual water withdrawals compared to monthly median, low, and high streamflows. Risk for biological stress was considered at 20% of long-term median and 10% of high- and low-flow thresholds. Future well build-out projections estimated potential for continued stress. Most water was permitted from small, free-flowing streams and “frack” ponds (dammed streams). Permitted 12-h pumping volumes exceeded median streamflow at 50% of withdrawal sites in June, when flows were low. Daily water usage, from operator disclosures, compared to median streamflow showed possible water stress in 7–51% of catchments from June–November, respectively. If 100% of produced water was recycled, per-well water use declined by 25%, reducing threshold exceedance by 10%. Future water stress was predicted to occur in fewer catchments important for drinking water and species of conservation concern due to the decline in new well installations and increased use of recycled water. Accessible and precise withdrawal and streamflow data are critical moving forward to assess and mitigate water stress in streams that experience high-volume withdrawals.
","language":"English","publisher":"ACS Publications","doi":"10.1021/acs.est.7b03304","usgsCitation":"Entrekin, S., Trainor, A., Saiers, J., Patterson, L., Maloney, K.O., Fargione, J., Kiesecker, J.M., Baruch-Mordo, S., Konschnik, K.E., Wiseman, H., Nicot, J., and Ryan, J.N., 2018, Water stress from high-volume hydraulic fracturing potentially threatens aquatic biodiversity and ecosystem services in Arkansas, United States: Environmental Science & Technology, v. 52, no. 4, p. 2349-2358, https://doi.org/10.1021/acs.est.7b03304.","productDescription":"10 p.","startPage":"2349","endPage":"2358","ipdsId":"IP-079892","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":352824,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas","volume":"52","issue":"4","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-31","publicationStatus":"PW","scienceBaseUri":"5afee744e4b0da30c1bfc211","contributors":{"authors":[{"text":"Entrekin, Sally","contributorId":147949,"corporation":false,"usgs":false,"family":"Entrekin","given":"Sally","affiliations":[{"id":16964,"text":"University of Central Arkansas","active":true,"usgs":false}],"preferred":false,"id":731854,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Trainor, Anne","contributorId":191831,"corporation":false,"usgs":false,"family":"Trainor","given":"Anne","affiliations":[],"preferred":false,"id":731855,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Saiers, James","contributorId":191832,"corporation":false,"usgs":false,"family":"Saiers","given":"James","affiliations":[],"preferred":false,"id":731856,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Patterson, Lauren","contributorId":203604,"corporation":false,"usgs":false,"family":"Patterson","given":"Lauren","affiliations":[],"preferred":false,"id":731857,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Maloney, Kelly O. 0000-0003-2304-0745 kmaloney@usgs.gov","orcid":"https://orcid.org/0000-0003-2304-0745","contributorId":4636,"corporation":false,"usgs":true,"family":"Maloney","given":"Kelly","email":"kmaloney@usgs.gov","middleInitial":"O.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":731858,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fargione, Joseph","contributorId":191828,"corporation":false,"usgs":false,"family":"Fargione","given":"Joseph","affiliations":[],"preferred":false,"id":731859,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kiesecker, Joseph M.","contributorId":146679,"corporation":false,"usgs":false,"family":"Kiesecker","given":"Joseph","email":"","middleInitial":"M.","affiliations":[{"id":7041,"text":"The Nature Conservancy","active":true,"usgs":false}],"preferred":false,"id":731860,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Baruch-Mordo, Sharon","contributorId":191830,"corporation":false,"usgs":false,"family":"Baruch-Mordo","given":"Sharon","email":"","affiliations":[],"preferred":false,"id":731861,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Konschnik, Katherine E.","contributorId":191826,"corporation":false,"usgs":false,"family":"Konschnik","given":"Katherine","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":731862,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Wiseman, Hannah","contributorId":191827,"corporation":false,"usgs":false,"family":"Wiseman","given":"Hannah","affiliations":[],"preferred":false,"id":731863,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Nicot, Jean-Philippe","contributorId":175575,"corporation":false,"usgs":false,"family":"Nicot","given":"Jean-Philippe","email":"","affiliations":[],"preferred":false,"id":731864,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Ryan, Joseph N.","contributorId":54290,"corporation":false,"usgs":false,"family":"Ryan","given":"Joseph","email":"","middleInitial":"N.","affiliations":[{"id":604,"text":"University of Colorado- Boulder","active":false,"usgs":true}],"preferred":false,"id":731865,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70194632,"text":"ofr20171158 - 2018 - Sea surface temperature estimates for the mid-Piacenzian Indian Ocean—Ocean Drilling Program sites 709, 716, 722, 754, 757, 758, and 763","interactions":[],"lastModifiedDate":"2018-01-31T10:21:02","indexId":"ofr20171158","displayToPublicDate":"2018-01-30T12:45:00","publicationYear":"2018","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":"2017-1158","title":"Sea surface temperature estimates for the mid-Piacenzian Indian Ocean—Ocean Drilling Program sites 709, 716, 722, 754, 757, 758, and 763","docAbstract":"Despite the wealth of global paleoclimate data available for the warm period in the middle of the Piacenzian Stage of the Pliocene Epoch (about 3.3 to 3.0 million years ago [Ma]; Dowsett and others, 2013, and references therein), the Indian Ocean has remained a region of sparse geographic coverage in terms of microfossil analysis. In an effort to characterize the surface Indian Ocean during this interval, we examined the planktic foraminifera from Ocean Drilling Program (ODP) sites 709, 716, 722, 754, 757, 758, and 763, encompassing a wide range of oceanographic conditions. We quantitatively analyzed the data for sea surface temperature (SST) estimation using both the modern analog technique (MAT) and a factor analytic transfer function. The data will contribute to the U.S. Geological Survey (USGS) Pliocene Research, Interpretation and Synoptic Mapping (PRISM) Project’s global SST reconstruction and climate model SST boundary condition for the mid-Piacenzian and will become part of the PRISM verification dataset designed to ground-truth Pliocene climate model simulations (Dowsett and others, 2013).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171158","usgsCitation":"Robinson, M.M., Dowsett, H.J., and Stoll, D.K., 2018, Sea surface temperature estimates for the mid-Piacenzian Indian Ocean—Ocean Drilling Program sites 709, 716, 722, 754, 757, 758, and 763: U.S. Geological Survey Open-File Report 2017–1158, 14 p., https://doi.org/10.3133/ofr20171158.","productDescription":"iv, 14 p.","numberOfPages":"19","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-087996","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":350488,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1158/coverthb.jpg"},{"id":350489,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1158/ofr20171158.pdf","text":"Report","size":"11 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1158"}],"otherGeospatial":"Indian Ocean","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 59.80,\n -30.93\n ],\n [\n 112.21,\n -30.93\n ],\n [\n 112.21,\n 16.62\n ],\n [\n 59.80,\n 16.62\n ],\n [\n 59.80,\n -30.93\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Eastern Geology and Paleoclimate Science Center
U.S. Geological Survey
12201 Sunrise Valley Drive
926A National Center
Reston, VA 20192
Feral horses are widespread in the western United States, with the majority of feral horse herds found in the Great Basin. There is a federal mandate to manage these herds in order to maintain “ecological balance”; however, understanding of the specific effects of feral horse grazing on rangeland plant communities in this region is incomplete. To address this research gap, we utilized long-term grazing exclosures and fenceline contrasts to evaluate the impacts of feral horses on several plant community variables (diversity, richness, dominance, and biomass) and species composition. Because the effects of grazing can vary with site precipitation and productivity, we selected 5 sites from 4 different rangeland types (Great Basin Desert, Colorado Plateau, Rocky Mountain grassland, and mixed grass prairie) that spanned a mean annual precipitation gradient of 229 to 413 mm. Our results did not reveal a significant effect of feral horse grazing on plant community composition, species richness, diversity, evenness, or dominance. In contrast, total aboveground herbaceous biomass and grass biomass were significantly reduced with feral horse grazing, but these effects did not vary with mean annual precipitation. Our results suggest that, at least at the sites we studied, feral horses have affected the plant community by reducing herbaceous biomass but have not caused plant community shifts. Additional multisite studies, preferably with standardized exclosures and larger sample sizes, would increase our understanding of feral horse grazing effects and inform management of feral horse herds in the western United States.
","language":"English","publisher":"BioOne","doi":"10.3398/064.077.0412","usgsCitation":"Baur, L.E., Schoenecker, K.A., and Smith, M.D., 2018, Effects of feral horse herds on plant communities across a precipitation gradient: Western North American Naturalist, v. 77, no. 4, p. 526-539, https://doi.org/10.3398/064.077.0412.","productDescription":"14 p.","startPage":"526","endPage":"539","ipdsId":"IP-081750","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":488902,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://scholarsarchive.byu.edu/wnan/vol77/iss4/11","text":"External Repository"},{"id":373555,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, Montana, Nevada, North Dakota, Utah","otherGeospatial":"Clan Alpine Herd Management Area, Pryor Mountain Wild Horse Range, Spring Creek Basin Herd Management Area, Sulphur Herd Management Area, Theodore Roosevelt National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.7042236328125,\n 37.86292829402713\n ],\n [\n -108.44192504882812,\n 37.86292829402713\n ],\n [\n -108.44192504882812,\n 38.039979682751806\n ],\n [\n -108.7042236328125,\n 38.039979682751806\n ],\n [\n -108.7042236328125,\n 37.86292829402713\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -103.6395263671875,\n 46.85831292242506\n ],\n [\n -103.26873779296875,\n 46.85831292242506\n ],\n [\n -103.26873779296875,\n 47.03082254778662\n ],\n [\n -103.6395263671875,\n 47.03082254778662\n ],\n [\n -103.6395263671875,\n 46.85831292242506\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.39523315429688,\n 45.0034084059808\n ],\n [\n -108.26614379882812,\n 45.0034084059808\n ],\n [\n -108.26614379882812,\n 45.141125276752774\n ],\n [\n -108.39523315429688,\n 45.141125276752774\n ],\n [\n -108.39523315429688,\n 45.0034084059808\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.02847290039062,\n 37.98750437106374\n ],\n [\n -113.66729736328125,\n 37.98750437106374\n ],\n [\n -113.66729736328125,\n 38.591113776147445\n ],\n [\n -114.02847290039062,\n 38.591113776147445\n ],\n [\n -114.02847290039062,\n 37.98750437106374\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.04534912109376,\n 39.4255858195144\n ],\n [\n -117.62512207031251,\n 39.4255858195144\n ],\n [\n -117.62512207031251,\n 39.86758762451019\n ],\n [\n -118.04534912109376,\n 39.86758762451019\n ],\n [\n -118.04534912109376,\n 39.4255858195144\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"77","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Baur, Lauren E.","contributorId":210390,"corporation":false,"usgs":false,"family":"Baur","given":"Lauren","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":785632,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schoenecker, Kathryn A. 0000-0001-9906-911X schoeneckerk@usgs.gov","orcid":"https://orcid.org/0000-0001-9906-911X","contributorId":2001,"corporation":false,"usgs":true,"family":"Schoenecker","given":"Kathryn","email":"schoeneckerk@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":785631,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, Melinda D.","contributorId":223621,"corporation":false,"usgs":false,"family":"Smith","given":"Melinda","email":"","middleInitial":"D.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":785633,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70194863,"text":"ds1077 - 2018 - Chirp subbottom profile data collected in 2015 from the northern Chandeleur Islands, Louisiana","interactions":[],"lastModifiedDate":"2018-02-01T11:04:02","indexId":"ds1077","displayToPublicDate":"2018-01-30T11:15:00","publicationYear":"2018","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":"1077","title":"Chirp subbottom profile data collected in 2015 from the northern Chandeleur Islands, Louisiana","docAbstract":"As part of the Barrier Island Evolution Research project, scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted a nearshore geophysical survey around the northern Chandeleur Islands, Louisiana, in September 2015. The objective of the project is to improve the understanding of barrier island geomorphic evolution, particularly storm-related depositional and erosional processes that shape the islands over annual to interannual time scales (1–5 years). Collecting geophysical data can help researchers identify relations between the geologic history of the islands and their present day morphology and sediment distribution. High-resolution geophysical data collected along this rapidly changing barrier island system can provide a unique time-series dataset to further the analyses and geomorphological interpretations of this and other coastal systems, improving our understanding of coastal response and evolution over medium-term time scales (months to years). Subbottom profile data were collected in September 2015 offshore of the northern Chandeleur Islands, during USGS Field Activity Number 2015-331-FA. Data products, including raw digital chirp subbottom data, processed subbottom profile images, survey trackline map, navigation files, geographic information system data files and formal Federal Geographic Data Committee metadata, and Field Activity Collection System and operation logs are available for download.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1077","usgsCitation":"Forde, A.S., DeWitt, N.T., Fredericks, J.J., and Miselis, J.L., 2018, Chirp subbottom profile data collected in 2015 from the northern Chandeleur Islands, Louisiana: U.S. Geological Survey Data Series 1077, https://doi.org/10.3133/ds1077.\n\n","productDescription":"HMTL Report; Data Release","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-091492","costCenters":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"links":[{"id":438048,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9U1WJXM","text":"USGS data release","linkHelpText":"Archive of Chirp Subbottom Profile Data Collected in 2018 From the Northern Chandeleur Islands, Louisiana"},{"id":438047,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9E8VRGO","text":"USGS data release","linkHelpText":"Archive of Chirp Subbottom Profile Data Collected in 2017 From the Northern Chandeleur Islands, Louisiana"},{"id":438046,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9NFK0K4","text":"USGS data release","linkHelpText":"Archive of Chirp Subbottom Profile Data Collected in 2016 From the Northern Chandeleur Islands, Louisiana"},{"id":350561,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1077/coverthb.jpg"},{"id":350562,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1077/index.html","text":"Report HTML","linkFileType":{"id":5,"text":"html"},"description":"DS 1077"},{"id":350842,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7668C5C","text":"USGS data release","description":"USGS data release","linkHelpText":"Archive of Chirp Subbottom Profile Data Collected in 2015 From the Northern Chandeleur Islands, Louisiana"}],"country":"United States","state":"Louisiana","otherGeospatial":"Northern Chandeleur Islands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.8167,\n 30.075\n ],\n [\n -88.8833,\n 30.075\n ],\n [\n -88.8833,\n 30.0167\n ],\n [\n -88.8167,\n 30.0167\n ],\n [\n -88.8167,\n 30.075\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"St. Petersburg Coastal and Marine Science Center
U.S. Geological Survey
600 4th Street South
St. Petersburg, FL 33701
We analyzed light detection and ranging (lidar) data and aerial photography to locate active faults near the south coast of Puerto Rico and excavated paleoseismic trenches across the Salinas fault and the Great Southern Puerto Rico fault zone (GSPRFZ). We document evidence for two Holocene surface‐rupturing earthquakes along both faults. Two earthquakes on the Salinas fault occurred after the deposition of sediments that are 7400–10,400 yrs old. No quantitative ages constrain the timing of the two earthquakes on the southeast GSPRFZ, but we interpret both events to have occurred during the Holocene or latest Pleistocene, based on the similarities in the characteristics of the faulted sediment and the development of soils exposed in both trenches. Stratigraphic and geomorphic evidence suggests components of both vertical and lateral slip on both faults. These results show that onshore active faults in Puerto Rico are more common than previously recognized and highlight the need for additional study to search for Holocene active faults and for an updated seismic hazard analysis for the island.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120170182","usgsCitation":"Piety, L., Redwine, J.R., Derouin, S., Prentice, C.S., Kelson, K.I., Klinger, R.E., and Mahan, S.A., 2018, Holocene surface ruptures on the Salinas Fault and southeastern Great Southern Puerto Rico Fault Zone, South Coastal Plain of Puerto Rico: Bulletin of the Seismological Society of America, v. 108, no. 2, p. 619-638, https://doi.org/10.1785/0120170182.","productDescription":"20 p.","startPage":"619","endPage":"638","ipdsId":"IP-086932","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":482038,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Puerto Rico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -67.46005793365855,\n 18.59919601130781\n ],\n [\n -67.46005793365855,\n 17.690536136611925\n ],\n [\n -65.53344705478513,\n 17.690536136611925\n ],\n [\n -65.53344705478513,\n 18.59919601130781\n ],\n [\n -67.46005793365855,\n 18.59919601130781\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"108","issue":"2","noUsgsAuthors":false,"publicationDate":"2018-01-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Piety, Lucille 0000-0003-0525-0132","orcid":"https://orcid.org/0000-0003-0525-0132","contributorId":350919,"corporation":false,"usgs":false,"family":"Piety","given":"Lucille","affiliations":[{"id":6736,"text":"Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":927311,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Redwine, Joanna R.","contributorId":130966,"corporation":false,"usgs":false,"family":"Redwine","given":"Joanna","email":"","middleInitial":"R.","affiliations":[{"id":7183,"text":"U.S. Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":927312,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Derouin, Sarah 0000-0002-0414-1682","orcid":"https://orcid.org/0000-0002-0414-1682","contributorId":350922,"corporation":false,"usgs":false,"family":"Derouin","given":"Sarah","affiliations":[{"id":6736,"text":"Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":927313,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Prentice, Carol S. 0000-0003-3732-3551 cprentice@usgs.gov","orcid":"https://orcid.org/0000-0003-3732-3551","contributorId":2676,"corporation":false,"usgs":true,"family":"Prentice","given":"Carol","email":"cprentice@usgs.gov","middleInitial":"S.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927314,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kelson, Keith I.","contributorId":192585,"corporation":false,"usgs":false,"family":"Kelson","given":"Keith","email":"","middleInitial":"I.","affiliations":[],"preferred":false,"id":927315,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Klinger, Ralph E.","contributorId":172929,"corporation":false,"usgs":false,"family":"Klinger","given":"Ralph","email":"","middleInitial":"E.","affiliations":[{"id":6736,"text":"Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":927316,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Mahan, Shannon A. 0000-0001-5214-7774 smahan@usgs.gov","orcid":"https://orcid.org/0000-0001-5214-7774","contributorId":147159,"corporation":false,"usgs":true,"family":"Mahan","given":"Shannon","email":"smahan@usgs.gov","middleInitial":"A.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":927317,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70217598,"text":"70217598 - 2018 - Geomorphic response of the Muddy River Basin to the 1980 eruptions of Mount St. Helens, 1980–2000","interactions":[],"lastModifiedDate":"2021-01-22T15:32:52.320112","indexId":"70217598","displayToPublicDate":"2018-01-30T09:24:00","publicationYear":"2018","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Geomorphic response of the Muddy River Basin to the 1980 eruptions of Mount St. Helens, 1980–2000","docAbstract":"The 18 May 1980 eruption of Mount St. Helens produced a mosaic of primary landscape disturbances that decreased in intensity with distance from the volcano across the headwaters of Muddy River and its tributaries. Subsequent geomorphic responses were influenced by evolving hillslope and channel conditions that affected fluxes of water, sediment, and wood, as well as by an exceptional storm in February 1996. Sediment fluxes have generally decreased, but downed wood in channels remains episodically mobile. Geomorphic change and biotic activity in the basin continue to interact in terrestrial, riparian, and aquatic ecosystems and in many cases diversify ecosystem conditions.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Ecological responses at Mount St. Helens: Revisited 35 years after the 1980 eruption","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-1-4939-7451-1_3","usgsCitation":"Lisle, T.E., Major, J.J., and Hardison, J.H., 2018, Geomorphic response of the Muddy River Basin to the 1980 eruptions of Mount St. Helens, 1980–2000, chap. of Ecological responses at Mount St. Helens: Revisited 35 years after the 1980 eruption, p. 45-70, https://doi.org/10.1007/978-1-4939-7451-1_3.","productDescription":"26 p.","startPage":"45","endPage":"70","ipdsId":"IP-053962","costCenters":[{"id":157,"text":"Cascades Volcano Observatory","active":false,"usgs":true}],"links":[{"id":382495,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Muddy River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.1954345703125,\n 46.074659663982324\n ],\n [\n -121.95785522460936,\n 46.074659663982324\n ],\n [\n -121.95785522460936,\n 46.18125668339498\n ],\n [\n -122.1954345703125,\n 46.18125668339498\n ],\n [\n -122.1954345703125,\n 46.074659663982324\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2018-01-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Lisle, Thomas E.","contributorId":124570,"corporation":false,"usgs":false,"family":"Lisle","given":"Thomas","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":808790,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Major, Jon J. 0000-0003-2449-4466 jjmajor@usgs.gov","orcid":"https://orcid.org/0000-0003-2449-4466","contributorId":439,"corporation":false,"usgs":true,"family":"Major","given":"Jon","email":"jjmajor@usgs.gov","middleInitial":"J.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":808791,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hardison, J. H. III","contributorId":49543,"corporation":false,"usgs":true,"family":"Hardison","given":"J.","suffix":"III","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":808792,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70254967,"text":"70254967 - 2018 - Hydrologic regime changes in a high-latitude glacierized watershed under future climate conditions","interactions":[],"lastModifiedDate":"2024-06-11T13:31:03.727537","indexId":"70254967","displayToPublicDate":"2018-01-30T08:23:57","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Hydrologic regime changes in a high-latitude glacierized watershed under future climate conditions","docAbstract":"A calibrated conceptual glacio-hydrological monthly water balance model (MWBMglacier) was used to evaluate future changes in water partitioning in a high-latitude glacierized watershed in Southcentral Alaska under future climate conditions. The MWBMglacier was previously calibrated and evaluated against streamflow measurements, literature values of glacier mass balance change, and satellite-based observations of snow covered area, evapotranspiration, and total water storage. Output from five global climate models representing two future climate scenarios (RCP 4.5 and RCP 8.5) was used with the previously calibrated parameters to drive the MWBMglacier at 2 km spatial resolution. Relative to the historical period 1949–2009, precipitation will increase and air temperature in the mountains will be above freezing for an additional two months per year by mid-century which significantly impacts snow/rain partitioning and the generation of meltwater from snow and glaciers. Analysis of the period 1949–2099 reveals that numerous hydrologic regime shifts already occurred or are projected to occur in the study area including glacier accumulation area, snow covered area, and forest vulnerability. By the end of the century, Copper River discharge is projected to increase by 48%, driven by 21% more precipitation and 53% more glacial melt water (RCP 8.5) relative to the historical period (1949–2009).
","language":"English","publisher":"MDPI","doi":"10.3390/w10020128","usgsCitation":"Valentin, M., Hogue, T.S., and Hay, L., 2018, Hydrologic regime changes in a high-latitude glacierized watershed under future climate conditions: Water, v. 10, no. 2, 128, 24 p., https://doi.org/10.3390/w10020128.","productDescription":"128, 24 p.","ipdsId":"IP-088012","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":469085,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w10020128","text":"Publisher Index Page"},{"id":429864,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Copper River watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -148,\n 63.4\n ],\n [\n -148,\n 60.5\n ],\n [\n -140,\n 60.5\n ],\n [\n -140,\n 63.4\n ],\n [\n -148,\n 63.4\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"10","issue":"2","noUsgsAuthors":false,"publicationDate":"2018-01-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Valentin, Melissa","contributorId":202218,"corporation":false,"usgs":false,"family":"Valentin","given":"Melissa","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":902997,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hogue, Terri S.","contributorId":205175,"corporation":false,"usgs":false,"family":"Hogue","given":"Terri","email":"","middleInitial":"S.","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":902998,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hay, Lauren 0000-0003-3763-4595","orcid":"https://orcid.org/0000-0003-3763-4595","contributorId":205020,"corporation":false,"usgs":true,"family":"Hay","given":"Lauren","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":902999,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70194834,"text":"ofr20181001 - 2018 - Updated procedures for using drill cores and cuttings at the Lithologic Core Storage Library, Idaho National Laboratory, Idaho","interactions":[],"lastModifiedDate":"2018-01-31T10:26:59","indexId":"ofr20181001","displayToPublicDate":"2018-01-30T00:00:00","publicationYear":"2018","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":"2018-1001","title":"Updated procedures for using drill cores and cuttings at the Lithologic Core Storage Library, Idaho National Laboratory, Idaho","docAbstract":"In 1990, the U.S. Geological Survey, in cooperation with the U.S. Department of Energy Idaho Operations Office, established the Lithologic Core Storage Library at the Idaho National Laboratory (INL). The facility was established to consolidate, catalog, and permanently store nonradioactive drill cores and cuttings from subsurface investigations conducted at the INL, and to provide a location for researchers to examine, sample, and test these materials.
The facility is open by appointment to researchers for examination, sampling, and testing of cores and cuttings. This report describes the facility and cores and cuttings stored at the facility. Descriptions of cores and cuttings include the corehole names, corehole locations, and depth intervals available.
Most cores and cuttings stored at the facility were drilled at or near the INL, on the eastern Snake River Plain; however, two cores drilled on the western Snake River Plain are stored for comparative studies. Basalt, rhyolite, sedimentary interbeds, and surficial sediments compose most cores and cuttings, most of which are continuous from land surface to their total depth. The deepest continuously drilled core stored at the facility was drilled to 5,000 feet below land surface. This report describes procedures and researchers' responsibilities for access to the facility and for examination, sampling, and return of materials.
","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181001","collaboration":"DOE/ID-22244Director, Idaho Water Science Center
U.S. Geological Survey
230 Collins Road
Boise, Idaho 83702
With the decline of Chinook salmon (Oncorhynchus tshawytscha) and steelhead (O. mykiss), habitat restoration actions in freshwater tributaries have been implemented to improve conditions for juveniles. Typically, physical (for example, hydrologic and engineering) based models are used to design restoration alternatives with the assumption that biological responses will be improved with changes to the physical habitat. Biological models rarely are used. Here, we describe simulations of a food web model, the Aquatic Trophic Productivity (ATP) model, to aid in the design of a restoration project in the Methow River, north-central Washington. The ATP model mechanistically links environmental conditions of the stream to the dynamics of river food webs, and can be used to simulate how alternative river restoration designs influence the potential for river reaches to sustain fish production. Four restoration design alternatives were identified that encompassed varying levels of side channel and floodplain reconnection and large wood addition. Our model simulations suggest that design alternatives focused on reconnecting side channels and the adjacent floodplain may provide the greatest increase in fish capacity. These results were robust to a range of discharge and thermal regimes that naturally occur in the Methow River. Our results suggest that biological models, such as the ATP model, can be used during the restoration planning phase to increase the effectiveness of restoration actions. Moreover, the use of multiple modeling efforts, both physical and biological, when evaluating restoration design alternatives provides a better understanding of the potential outcome of restoration actions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181002","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Benjamin, J.R., Bellmore, J.R., and Dombroski, Daniel, 2018, Using a food web model to inform the design of river restoration—An example at the Barkley Bear Segment, Methow River, north-central Washington: U.S. Geological Survey Open-File Report 2018–1002, 24 p., https://doi.org/10.3133/ofr20181002.","productDescription":"iv, 24 p.","numberOfPages":"32","onlineOnly":"Y","ipdsId":"IP-092102","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":350751,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1002/ofr20181002.pdf","text":"Report","size":"4.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1002"},{"id":350750,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1002/coverthb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Methow River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.497802734375,\n 47.646886969413\n ],\n [\n -119.02587890624999,\n 47.646886969413\n ],\n [\n -119.02587890624999,\n 49.15296965617042\n ],\n [\n -121.497802734375,\n 49.15296965617042\n ],\n [\n -121.497802734375,\n 47.646886969413\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Forest and Rangeland Ecosystem Science Center
U.S. Geological Survey
777 NW 9th St., Suite 400
Corvallis, Oregon 97330
Climate-sensitive Arctic lakes have been identified as conduits for ancient permafrost-carbon (C) emissions and as such accelerate warming. However, the environmental factors that control emission pathways and their sources are unclear; this complicates upscaling, forecasting and climate-impact-assessment efforts. Here we show that current whole-lake CH4 and CO2 emissions from widespread lakes in Arctic Alaska primarily originate from organic matter fixed within the past 3–4 millennia (modern to 3,300 ± 70 years before the present), and not from Pleistocene permafrost C. Furthermore, almost 100% of the annual diffusive C flux is emitted as CO2. Although the lakes mostly processed younger C (89 ± 3% of total C emissions), minor contributions from ancient C sources were two times greater in fine-textured versus coarse-textured Pleistocene sediments, which emphasizes the importance of the underlying geological substrate in current and future emissions. This spatially extensive survey considered the environmental and temporal variability necessary to monitor and forecast the fate of ancient permafrost C as Arctic warming progresses.
","language":"English","publisher":"Nature","doi":"10.1038/s41558-017-0066-9","usgsCitation":"Elder, C.D., Xu, X., Walker, J., Schnell, J.L., Hinkel, K.M., Townsend-Small, A., Arp, C.D., Pohlman, J.W., Gaglioti, B., and Czimzik, C.I., 2018, Greenhouse gas emissions from diverse Arctic Alaskan lakes are dominated by young carbon: Nature Climate Change, v. 8, p. 166-171, https://doi.org/10.1038/s41558-017-0066-9.","productDescription":"6 p.","startPage":"166","endPage":"171","ipdsId":"IP-088994","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":469086,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://escholarship.org/uc/item/9q0086pg","text":"External Repository"},{"id":350887,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -158,\n 68.5\n ],\n [\n -149,\n 68.5\n ],\n [\n -149,\n 71.5\n ],\n [\n -158,\n 71.5\n ],\n [\n -158,\n 68.5\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"8","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-29","publicationStatus":"PW","scienceBaseUri":"5a743584e4b0a9a2e9e25ca0","contributors":{"authors":[{"text":"Elder, Clayton D.","contributorId":201542,"corporation":false,"usgs":false,"family":"Elder","given":"Clayton","email":"","middleInitial":"D.","affiliations":[{"id":7023,"text":"Jet Propulsion Laboratory, California Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":726347,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Xu, Xiaomei","contributorId":32055,"corporation":false,"usgs":true,"family":"Xu","given":"Xiaomei","affiliations":[],"preferred":false,"id":726348,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Walker, Jennifer","contributorId":201558,"corporation":false,"usgs":false,"family":"Walker","given":"Jennifer","affiliations":[],"preferred":false,"id":726349,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schnell, Jordan L.","contributorId":201543,"corporation":false,"usgs":false,"family":"Schnell","given":"Jordan","email":"","middleInitial":"L.","affiliations":[{"id":36194,"text":"Department of Earth System Science, University of California, Irvine, CA, 92697, USA.","active":true,"usgs":false}],"preferred":false,"id":726350,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hinkel, Kenneth M.","contributorId":15405,"corporation":false,"usgs":true,"family":"Hinkel","given":"Kenneth","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":726351,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Townsend-Small, Amy","contributorId":201545,"corporation":false,"usgs":false,"family":"Townsend-Small","given":"Amy","email":"","affiliations":[{"id":36196,"text":"Department of Geology, University of Cincinnati, OH, 45221, USA.","active":true,"usgs":false}],"preferred":false,"id":726352,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Arp, Christopher D.","contributorId":17330,"corporation":false,"usgs":false,"family":"Arp","given":"Christopher","email":"","middleInitial":"D.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":726353,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Pohlman, John W. 0000-0002-3563-4586 jpohlman@usgs.gov","orcid":"https://orcid.org/0000-0002-3563-4586","contributorId":145771,"corporation":false,"usgs":true,"family":"Pohlman","given":"John","email":"jpohlman@usgs.gov","middleInitial":"W.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":726346,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Gaglioti, Benjamin V.","contributorId":193129,"corporation":false,"usgs":false,"family":"Gaglioti","given":"Benjamin V.","affiliations":[],"preferred":false,"id":726354,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Czimzik, Claudia I.","contributorId":199102,"corporation":false,"usgs":false,"family":"Czimzik","given":"Claudia","email":"","middleInitial":"I.","affiliations":[],"preferred":false,"id":726355,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70208063,"text":"70208063 - 2018 - Is sensitivity to anticoagulant rodenticides affected by repeated exposure in hawks?","interactions":[],"lastModifiedDate":"2020-01-28T07:25:47","indexId":"70208063","displayToPublicDate":"2018-01-28T07:24:57","publicationYear":"2018","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Is sensitivity to anticoagulant rodenticides affected by repeated exposure in hawks?","docAbstract":"A seminal question in wildlife toxicology is whether exposure to an environmental contaminant, in particular a second-generation anticoagulant rodenticide, can evoke subtle long lasting effects on body condition, physiological function and survival. Many reports indicate that non-target predators often carry residues of several rodenticides, which is indicative of multiple exposures. An often-cited study in laboratory rats demonstrated that exposure to the second-generation anticoagulant rodenticide brodifacoum prolongs blood clotting time for a few days, but weeks later when rats were re-exposed to the first-generation anticoagulant rodenticide warfarin, coagulopathy was more pronounced in brodifacoum-treated rats than naïve rats exposed to warfarin. To further investigate this phenomenon, American kestrels were fed environmentally realistic doses of chlorophacinone or brodifacoum for a week, and following a week-long recovery period, birds were then challenged with a low-level dietary dose of chlorophacinone. In the present study, neither hematocrit nor clotting time (prothrombin time, Russell’s viper venom time) were differentially affected in sequentially exposed kestrels compared to naïve birds fed low-level dietary dose of chlorophacinone. While the present findings do not reveal lasting effects of anticoagulant exposure on blood clotting ability, findings in laboratory rats and other species have demonstrated such effects on blood clotting, and even other molecular pathways associated with immune function and xenobiotic metabolism. Additional studies using an environmentally realistic route of exposure and dose are underway to further test this hypothesis.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the Vertebrate Pest Conference","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"University of California","doi":"10.5070/V42811045","usgsCitation":"Rattner, B., 2018, Is sensitivity to anticoagulant rodenticides affected by repeated exposure in hawks?, in Proceedings of the Vertebrate Pest Conference, p. 247-253, https://doi.org/10.5070/V42811045.","productDescription":"7 p.","startPage":"247","endPage":"253","ipdsId":"IP-096311","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":461069,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5070/v42811045","text":"Publisher Index Page"},{"id":371636,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Rattner, Barnett 0000-0003-3676-2843 brattner@usgs.gov","orcid":"https://orcid.org/0000-0003-3676-2843","contributorId":221814,"corporation":false,"usgs":true,"family":"Rattner","given":"Barnett","email":"brattner@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":780333,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70194519,"text":"sim3392 - 2018 - Quaternary sediment thickness and bedrock topography of the glaciated United States east of the Rocky Mountains","interactions":[],"lastModifiedDate":"2018-01-29T09:58:24","indexId":"sim3392","displayToPublicDate":"2018-01-26T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3392","title":"Quaternary sediment thickness and bedrock topography of the glaciated United States east of the Rocky Mountains","docAbstract":"Beginning roughly 2.6 million years ago, global climate entered a cooling phase known as the Pleistocene Epoch. As snow in northern latitudes compacted into ice several kilometers thick, it flowed as glaciers southward across the North American continent. These glaciers extended across the northern United States, dramatically altering the landscape they covered. East of the Rocky Mountains, the ice coalesced into continental glaciers (called the Laurentide Ice Sheet) that at times blanketed much of the north-central and northeastern United States. To the west of the Laurentide Ice Sheet, glaciers formed in the mountains of western Canada and the United States and coalesced into the Cordilleran ice sheet; this relatively smaller ice mass extended into the conterminous United States in the northernmost areas of western Montana, Idaho, and Washington. Throughout the Pleistocene, landscape alteration occurred by (1) glacial erosion of the rocks and sediments; (2) redeposition of the eroded earth materials in a form substantially different from their source rocks, in terms of texture and overall character; and (3) disruption of preexisting drainage patterns by the newly deposited sediments. In many cases, pre-glacial drainage systems (including, for example, the Mississippi River) were rerouted because their older drainage courses became blocked with glacial sediment.
The continental glaciers advanced and retreated many times across those areas. During each ice advance, or glaciation, erosion and deposition occurred, and the landscape was again altered. Through successive glaciations, the landscape and the bedrock surface gradually came to resemble their present configurations. As continental ice sheets receded and the Pleistocene ended, erosion and deposition of sediment (for example in stream valleys) continued to shape the landscape up to the present day (albeit to a lesser extent than during glaciation). The interval of time since the last recession of the glaciers is called the Holocene and, together with the Pleistocene, constitutes the Quaternary Period of geologic time; this publication characterizes the three-dimensional geometry of the Quaternary sediments and the bedrock surface that lies beneath.
The pre-glacial landscape was underlain mostly by weathered bedrock generally similar in nature to that found in many areas of the non-glaciated United States. Glacial erosion and redeposition of earth materials produced a young, mineral-rich soil that formed the basis for the highly productive agricultural economy in the U.S. midcontinent. Extensive buried sands and gravels within the glacial deposits also provided a stimulus to other economic sectors by serving as high-quality aquifers supplying groundwater to the region’s industry and cities. An understanding of the three-dimensional distribution of these glacial sediments has direct utility for addressing various societal issues including groundwater quality and supply, and landscape and soil response to earthquake-induced shaking.
The Quaternary sediment thickness map and bedrock topographic map shown here provide a regional overview and are intended to supplement the more detailed work on which they are based. Detailed mapping is particularly useful in populated areas for site-specific planning. In contrast, regional maps such as these serve to place local, detailed mapping in context; to permit the extrapolation of data into unmapped areas; and to depict large-scale regional geologic features and patterns that are beyond the scope of local, detailed mapping. They also can enhance the reader’s general understanding of the region’s landscape and geologic history and provide a source of information for regional decision making that could benefit by improved predictability of bedrock depth beneath the unconsolidated Quaternary sediments. To enable these maps to be analyzed in conjunction with other types of information, this publication also includes the map data in GIS compatible format.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3392","usgsCitation":"Soller, D.R., and Garrity, C.P., 2018, Quaternary sediment thickness and bedrock topography of the glaciated United States east of the Rocky Mountains: U.S. Geological Survey Scientific Investigations Map 3392, 2 sheets, scale 1:5,000,000. https://doi.org/10.3133/sim3392.","productDescription":"2 Sheets: 42.5 x 23.0 inches; Metadata; Read Me; Spatial Data","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-084769","costCenters":[{"id":5061,"text":"National Cooperative Geologic Mapping and Landslide Hazards","active":true,"usgs":true}],"links":[{"id":350668,"rank":5,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sim/3392/sim3392_spatialdata.zip","text":"Spatial Data","size":"16 MB","linkFileType":{"id":6,"text":"zip"},"description":"SIM 3392","linkHelpText":"– Contains raster image files, layer file, and 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KB","linkFileType":{"id":6,"text":"zip"},"description":"SIM 3392","linkHelpText":" - Zip file of Sheet 1 and 2 metatdata"},{"id":350658,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3392/coverthb_.jpg"},{"id":350663,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3392/sim3392_sheet1.pdf","text":"Sheet 1","size":"10 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3392","linkHelpText":" – Map of Quaternary Sediment Thickness"},{"id":350664,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3392/sim3392_sheet2.pdf","text":"Sheet 2","size":"13 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3392","linkHelpText":" – Map of Bedrock Topography"},{"id":350667,"rank":4,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sim/3392/sim3392_readme.txt","text":"Read Me","size":"2 KB","linkFileType":{"id":2,"text":"txt"},"description":"SIM 3392"}],"country":"United 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\"}}]}","contact":"National Cooperative Geologic Mapping Program
U.S. Geological Survey
12201 Sunrise Valley Drive Mail Stop 908
Reston, VA 20192
Fax: (703) 648-6937
The Jan Mayen Microcontinent encompasses a rectangular, mostly submarine fragment of continental crust that lies north of Iceland in the middle of the North Atlantic Ocean. These continental rocks were rifted away from the eastern margin of Greenland as a consequence of a westward jump of spreading centers from the now-extinct Aegir Ridge to the currently active Kolbeinsey Ridge in the Oligocene and early Miocene. The microcontinent is composed of the high-standing Jan Mayen Ridge and a series of smaller ridges that diminish southward in elevation and includes several deep basins that are underlain by strongly attenuated continental crust. The geology of this area is known principally from a loose collection of seismic reflection and refraction lines and several deep-sea scientific drill cores.
The Jan Mayen Microcontinent petroleum province encompasses the entire area of the microcontinent and was defined as a single assessment unit (AU). Although its geology is poorly known, the microcontinent is thought to consist of late Paleozoic and Mesozoic rift basin stratigraphic sequences similar to those of the highly prospective Norwegian, North Sea, and Greenland continental margins. The prospectivity of the AU may be greatly diminished, however, by pervasive extensional deformation, basaltic magmatism, and exhumation that accompanied two periods of continental rifting and breakup in the Paleogene and early Neogene. The overall probability of at least one petroleum accumulation of >50 million barrels of oil equivalent was judged to be 5.6 percent. As a consequence of the low level of probability, a quantitative assessment of this AU was not conducted.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1824L","usgsCitation":"Moore, T.E., and Pitman, J.K., 2018, Geology and assessment of undiscovered oil and gas resources of the Jan Mayen Microcontinent Province, 2008, chap. L of Moore, T.E., and Gautier, D.L., eds., The 2008 Circum-Arctic Resource Appraisal: U.S. Geological Survey Professional Paper 1824, 18 p., https://doi.org/10.3133/pp1824L.","productDescription":"Report: vi, 18 p.; Appendix","numberOfPages":"27","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-028951","costCenters":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"links":[{"id":350678,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1824/l/coverthb.jpg"},{"id":350681,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1824/l/pp1824L.pdf","text":"Report","size":"4.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1824 Chapter L"},{"id":350682,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/pp/1824/l/pp1824L_appendix.xls","size":"36 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"PP 1824 Chapter L"}],"otherGeospatial":"Jan Mayen Microcontinent Province","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -15,\n 66\n ],\n [\n 7,\n 66\n ],\n [\n 7,\n 72\n ],\n [\n -15,\n 72\n ],\n [\n -15,\n 66\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Contact Information, Geology, Minerals, Energy, & Geophysics Science Center—Menlo Park
U.S. Geological Survey
345 Middlefield Road
Menlo Park, CA 94025-3591
FAX 650-329-4936
Flood-damage reduction in the United States has been a longstanding but elusive societal goal. The national strategy for reducing flood damage has shifted over recent decades from a focus on construction of flood-control dams and levee systems to a three-pronged strategy to (1) improve the design and operation of such structures, (2) provide more accurate and accessible flood forecasting, and (3) shift the Federal Emergency Management Agency (FEMA) National Flood Insurance Program to a more balanced, less costly flood-insurance paradigm. Expanding the availability and use of high-quality, three-dimensional (3D) elevation information derived from modern light detection and ranging (lidar) technologies to provide essential terrain data poses a singular opportunity to dramatically enhance the effectiveness of all three components of this strategy. Additionally, FEMA, the National Weather Service, and the U.S. Geological Survey (USGS) have developed tools and joint program activities to support the national strategy.
The USGS 3D Elevation Program (3DEP) has the programmatic infrastructure to produce and provide essential terrain data. This infrastructure includes (1) data acquisition partnerships that leverage funding and reduce duplicative efforts, (2) contracts with experienced private mapping firms that ensure acquisition of consistent, low-cost 3D elevation data, and (3) the technical expertise, standards, and specifications required for consistent, edge-to-edge utility across multiple collection platforms and public access unfettered by individual database designs and limitations.
High-quality elevation data, like that collected through 3DEP, are invaluable for assessing and documenting flood risk and communicating detailed information to both responders and planners alike. Multiple flood-mapping programs make use of USGS streamflow and 3DEP data. Flood insurance rate maps, flood documentation studies, and flood-inundation map libraries are products of these programs.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20173081","usgsCitation":"Carswell, W.J., Jr., and Lukas, Vicki, 2018, The 3D Elevation Program—Flood risk management: U.S. Geological Survey Fact Sheet 2017-3081, 6 p., https://doi.org/10.3133/fs20173081.","productDescription":"6 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-073000","costCenters":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"links":[{"id":350200,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2017/3081/coverthb2.jpg"},{"id":350201,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2017/3081/fs20173081.pdf","text":"Report","size":"4.14 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2017-3081"}],"contact":"Director, National Geospatial Program
U.S. Geological Survey, MS 511
12201 Sunrise Valley Drive
Reston, VA 20192
A U.S. Navy SEAL (an acronym for sea, air, land) carries gear containing at least 23 nonfuel mineral commodities for which the United States is greater than 50 percent net import reliant. The graphics display the leading world producers of selected nonfuel mineral commodities used to manufacture U.S. Navy SEAL gear. SEALs are members of the U.S. Navy's special operations forces.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/gip183","usgsCitation":"Brainard, Jamie, Nassar, N.T., Gambogi, Joseph, Baker, M.S., and Jarvis, M.T., 2018, Globally sourced mineral commodities used in U.S. Navy SEAL gear—An illustration of U.S. net import reliance (ver. 2.0, January 2018): U.S. Geological Survey General Information Product 183, 2 p., https://doi.org/10.3133/gip183.","productDescription":"2 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-093066","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":350473,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/gip/0183/coverthb4.jpg"},{"id":350854,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/gip/0183/versionHist.txt","size":"1 MB","linkFileType":{"id":2,"text":"txt"}},{"id":350853,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/gip/0183/gip183.pdf","text":"Report","size":"19.7 MB","linkFileType":{"id":1,"text":"pdf"}}],"edition":"Version 1.0: Originally posted January 25, 2018; Version 2.0: January 31, 2018","contact":"Director, National Minerals Information Center
U.S. Geological Survey
12201 Sunrise Valley Drive
988 National Center
Reston, VA 20192