{"pageNumber":"557","pageRowStart":"13900","pageSize":"25","recordCount":46856,"records":[{"id":70049005,"text":"sim3278 - 2013 - Flood-inundation maps for a 6.5-mile reach of the Kentucky River at Frankfort, Kentucky","interactions":[],"lastModifiedDate":"2014-01-03T10:44:30","indexId":"sim3278","displayToPublicDate":"2014-01-03T10:27:48","publicationYear":"2013","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":"3278","title":"Flood-inundation maps for a 6.5-mile reach of the Kentucky River at Frankfort, Kentucky","docAbstract":"Digital flood-inundation maps for a 6.5-mile reach of Kentucky River at Frankfort, Kentucky, were created by the U.S. Geological Survey (USGS) in cooperation with the City of Frankfort Office of Emergency Management. The inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_inundation/, depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage Kentucky River at Lock 4 at Frankfort, Kentucky (station no. 03287500). Current conditions for the USGS streamgage may be obtained online at the USGS National Water Information System site (http://waterdata.usgs.gov/nwis/inventory?agency_code=USGS&site_no=03287500). In addition, the information has been provided to the National Weather Service (NWS) for incorporation into their Advanced Hydrologic Prediction Service (AHPS) flood warning system (http:/water.weather.gov/ahps/). The NWS forecasts flood hydrographs at many places that are often colocated at USGS streamgages. The forecasted peak-stage information, also available on the Internet, may be used in conjunction with the maps developed in this study to show predicted areas of flood inundation. In this study, flood profiles were computed for the Kentucky River reach by using HEC–RAS, a one-dimensional step-backwater model developed by the U.S. Army Corps of Engineers. The hydraulic model was calibrated by using the most current (2013) stage-discharge relation for the Kentucky River at Lock 4 at Frankfort, Kentucky, in combination with streamgage and high-water-mark measurements collected for a flood event in May 2010. The calibrated model was then used to calculate 26 water-surface profiles for a sequence of flood stages, at 1-foot intervals, referenced to the streamgage datum and ranging from a stage near bankfull to the elevation that breached the levees protecting the City of Frankfort. To delineate the flooded area at each interval flood stage, the simulated water-surface profiles were combined with a digital elevation model (DEM) of the study area by using geographic information system software. The DEM consisted of bare-earth elevations within the study area and was derived from a Light Detection And Ranging (LiDAR) dataset having a 5.0-foot horizontal resolution and an accuracy of 0.229 foot. The availability of these maps, along with Internet information regarding current stages from USGS streamgages and forecasted stages from the NWS, provides emergency management personnel and local residents with critical information for flood response activities such as evacuations, road closures, and postflood recovery efforts.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3278","collaboration":"Prepared in cooperation with City of Frankfort, Kentucky, Office of Emergency Management","usgsCitation":"Lant, J.G., 2013, Flood-inundation maps for a 6.5-mile reach of the Kentucky River at Frankfort, Kentucky: U.S. Geological Survey Scientific Investigations Map 3278, Report: vi, 10 p.; Low Resolution and High Resolution Map Sheets; Downloads Directory, https://doi.org/10.3133/sim3278.","productDescription":"Report: vi, 10 p.; Low Resolution and High Resolution Map Sheets; Downloads Directory","numberOfPages":"20","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-045182","costCenters":[{"id":354,"text":"Kentucky Water Science Center","active":true,"usgs":true}],"links":[{"id":280591,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3278/"},{"id":280592,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3278/pdf/sim3278.pdf"},{"id":280593,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3278/PDF-mapSheets/"},{"id":280594,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sim/3278/downloads/"},{"id":280595,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sim3278.jpg"}],"projection":"Lambert Conformal Conic","datum":"North American Datum of 1983","country":"United States","state":"Kentucky","city":"Fankfort","otherGeospatial":"Kentucky River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -84.916,38.15 ], [ -84.916,38.233 ], [ -84.816,38.233 ], [ -84.816,38.15 ], [ -84.916,38.15 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52c7dbe1e4b0a753c7d3e375","contributors":{"authors":[{"text":"Lant, Jeremiah G. 0000-0001-6688-4820 jlant@usgs.gov","orcid":"https://orcid.org/0000-0001-6688-4820","contributorId":4912,"corporation":false,"usgs":true,"family":"Lant","given":"Jeremiah","email":"jlant@usgs.gov","middleInitial":"G.","affiliations":[{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true},{"id":354,"text":"Kentucky Water Science Center","active":true,"usgs":true}],"preferred":true,"id":485986,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70055737,"text":"ofr20131255 - 2013 - seawaveQ: an R package providing a model and utilities for analyzing trends in chemical concentrations in streams with a seasonal wave (seawave) and adjustment for streamflow (Q) and other ancillary variables","interactions":[],"lastModifiedDate":"2017-10-12T20:16:54","indexId":"ofr20131255","displayToPublicDate":"2014-01-03T09:30:00","publicationYear":"2013","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":"2013-1255","title":"seawaveQ: an R package providing a model and utilities for analyzing trends in chemical concentrations in streams with a seasonal wave (seawave) and adjustment for streamflow (Q) and other ancillary variables","docAbstract":"The seawaveQ R package fits a parametric regression model (seawaveQ) to pesticide concentration data from streamwater samples to assess variability and trends. The model incorporates the strong seasonality and high degree of censoring common in pesticide data and users can incorporate numerous ancillary variables, such as streamflow anomalies. The model is fitted to pesticide data using maximum likelihood methods for censored data and is robust in terms of pesticide, stream location, and degree of censoring of the concentration data. This R package standardizes this methodology for trend analysis, documents the code, and provides help and tutorial information, as well as providing additional utility functions for plotting pesticide and other chemical concentration data.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131255","collaboration":"National Water-Quality Assessment Program","usgsCitation":"Ryberg, K.R., and Vecchia, A.V., 2013, seawaveQ: an R package providing a model and utilities for analyzing trends in chemical concentrations in streams with a seasonal wave (seawave) and adjustment for streamflow (Q) and other ancillary variables: U.S. Geological Survey Open-File Report 2013-1255, Report: iv, 13 p.; Downloads Directory, https://doi.org/10.3133/ofr20131255.","productDescription":"Report: iv, 13 p.; Downloads Directory","numberOfPages":"22","onlineOnly":"Y","ipdsId":"IP-049192","costCenters":[{"id":478,"text":"North Dakota Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":280584,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131255.jpg"},{"id":280570,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1255/"},{"id":280582,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1255/pdf/ofr13-1255.pdf.pdf"},{"id":280583,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2013/1255/Downloads/"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52c7dc0ee4b0a753c7d3e47d","contributors":{"authors":[{"text":"Ryberg, Karen R. 0000-0002-9834-2046 kryberg@usgs.gov","orcid":"https://orcid.org/0000-0002-9834-2046","contributorId":1172,"corporation":false,"usgs":true,"family":"Ryberg","given":"Karen","email":"kryberg@usgs.gov","middleInitial":"R.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":486257,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vecchia, Aldo V. 0000-0002-2661-4401","orcid":"https://orcid.org/0000-0002-2661-4401","contributorId":41810,"corporation":false,"usgs":true,"family":"Vecchia","given":"Aldo","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":486258,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70056151,"text":"sir20135214 - 2013 - An update of hydrologic conditions and distribution of selected constituents in water, eastern Snake River Plain aquifer and perched groundwater zones, Idaho National Laboratory, Idaho, emphasis 2009–11","interactions":[],"lastModifiedDate":"2014-01-02T13:21:37","indexId":"sir20135214","displayToPublicDate":"2014-01-02T12:49:29","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-5214","title":"An update of hydrologic conditions and distribution of selected constituents in water, eastern Snake River Plain aquifer and perched groundwater zones, Idaho National Laboratory, Idaho, emphasis 2009–11","docAbstract":"Since 1952, wastewater discharged to infiltration ponds (also called percolation ponds) and disposal wells at the Idaho National Laboratory (INL) has affected water quality in the eastern Snake River Plain (ESRP) aquifer and perched groundwater zones underlying the INL. The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Energy, maintains groundwater monitoring networks at the INL to determine hydrologic trends, and to delineate the movement of radiochemical and chemical wastes in the aquifer and in perched groundwater zones. This report presents an analysis of water-level and water-quality data collected from aquifer, multilevel monitoring system (MLMS), and perched groundwater wells in the USGS groundwater monitoring networks during 2009–11. Water in the ESRP aquifer primarily moves through fractures and interflow zones in basalt, generally flows southwestward, and eventually discharges at springs along the Snake River. The aquifer primarily is recharged from infiltration of irrigation water, infiltration of streamflow, groundwater inflow from adjoining mountain drainage basins, and infiltration of precipitation. From March–May 2009 to March–May 2011, water levels in wells generally declined in the northern part of the INL. Water levels generally rose in the central and eastern parts of the INL. Detectable concentrations of radiochemical constituents in water samples from aquifer wells or MLMS equipped wells in the ESRP aquifer at the INL generally decreased or remained constant during 2009–11. Decreases in concentrations were attributed to radioactive decay, changes in waste-disposal methods, and dilution from recharge and underflow. In 2011, concentrations of tritium in groundwater from 50 of 127 aquifer wells were greater than or equal to the reporting level and ranged from 200±60 to 7,000±260 picocuries per liter. Tritium concentrations from one or more discrete zones from four wells equipped with MLMS were greater than or equal to reporting levels in water samples collected at various depths. Tritium concentrations in water from wells completed in shallow perched groundwater at the Advanced Test Reactor Complex (ATR Complex) were less than the reporting levels. Tritium concentrations in deep perched groundwater at the ATR Complex equaled or exceeded the reporting level in 12 wells during at least one sampling event during 2009–11 at the ATR Complex. Concentrations of strontium-90 in water from 20 of 76 aquifer wells sampled during April or October 2011 exceeded the reporting level. Strontium-90 was not detected within the ESRP aquifer beneath the ATR Complex. During at least one sampling event during 2009–11, concentrations of strontium-90 in water from 10 wells completed in deep perched groundwater at the ATR Complex equaled or exceeded the reporting levels. During 2009–11, concentrations of plutonium-238, and plutonium-239, -240 (undivided), and americium-241 were less than the reporting level in water samples from all aquifer wells and in all wells equipped with MLMS. Concentrations of cesium-137 were equal to or slightly above the reporting level in 8 aquifer wells and from 2 wells equipped with MLMS. The concentration of chromium in water from one well south of the ATR Complex was 97 micrograms per liter (μg/L) in April 2011, just less than the maximum contaminant level (MCL) of 100 μg/L. Concentrations of chromium in water samples from 69 other wells sampled ranged from 0.8 μg/L to 25 μg/L. During 2009–11, dissolved chromium was detected in water from 15 wells completed in perched groundwater at the ATR Complex. In 2011, concentrations of sodium in water from most wells in the southern part of the INL were greater than the background concentration of 10 milligrams per liter (mg/L); the highest concentrations were at or near the Idaho Nuclear Engineering and Technology Center (INTEC). After the newpercolation ponds were put into service in 2002 southwest of the INTEC, concentrations of sodium in water samples from the Rifle Range well rose steadily until 2008, when the concentrations generally began decreasing. The increases and decreases were attributed to disposal variability in the new percolation ponds. Concentrations of sodium in most wells equipped with MLMS generally were consistent with depth. During 2011, dissolved sodium concentrations in water from 17 wells completed in deep perched groundwater at the ATR Complex ranged from 6 to 146 mg/L. In 2011, concentrations of chloride in most water samples from aquifer wells south of the INTEC and at the Central Facilities Area exceeded the background concentrations of 15 mg/L, but were less than the secondary MCL of 250 mg/L. Chloride concentrations in water from wells south of the INTEC have generally increased because of increased chloride disposal to the old percolation ponds since 1984 when discharge of wastewater to the INTEC disposal well was discontinued. After the new percolation ponds were put into service in 2002 southwest of the INTEC, concentrations of chloride in water samples from one well rose steadily until 2008 then began decreasing. Chloride concentrations in water from all but one well completed in the ESRP aquifer at or near the ATR Complex were less than background and ranged between 10 and 14 mg/L during 2011, similar to concentrations detected during the 2006–08 reporting period. During 2011, chloride concentrations in water from two aquifer wells at the Radioactive Waste Management Complex (RWMC) were slightly greater than concentrations detected during the 2006–08 reporting period. The vertical distribution of chloride concentrations in wells equipped with MLMS were generally consistent within zones during 2009–11 and ranged from about 8 to 20 mg/L. During April 2011, dissolved chloride concentrations in shallow perched groundwater at the ATR Complex ranged from 7 to 13 mg/L in water from three wells. Dissolved chloride concentrations in deep perched groundwater at the ATR Complex during 2011 ranged from 4 to 54 mg/L. In 2011, sulfate concentrations in water samples from 11 aquifer wells in the south-central part of the INL equaled or exceeded the background concentration of sulfate and ranged from 40 to 167 mg/L. The greater-than-background concentrations in water from these wells probably resulted from sulfate disposal at the ATR Complex infiltration ponds or the old INTEC percolation ponds. In 2011, sulfate concentrations in water samples from two wells near the RWMC were greater than background levels and could have resulted from well construction techniques and (or) waste disposal at the RWMC. The vertical distribution of sulfate concentrations in three wells near the southern boundary of the INL was generally consistent with depth, and ranged between 19 and 25 mg/L. The maximum dissolved sulfate concentration in shallow perched groundwater near the ATR Complex was 400 mg/L in well CWP 1 in April 2011. During 2009–11, the maximum concentration of dissolved sulfate in deep perched groundwater at the ATR Complex was 1,550 mg/L in a well located west of the chemical-waste pond. In 2011, concentrations of nitrate in water from most wells at and near the INTEC exceeded the regional background concentrations of 1 mg/L and ranged from 1.6 to 5.95 mg/L. Concentrations of nitrate in wells south of INTEC and farther away from the influence of disposal areas and the Big Lost River show a general decrease in nitrate concentrations through time. During 2009–11, water samples from 30 wells were collected and analyzed for volatile organic compounds (VOCs). Six VOCs were detected. At least one and up to five VOCs were detected in water samples from 10 wells. The primary VOCs detected include carbon tetrachloride, chloroform, tetrachloroethylene, 1,1,1-trichloroethane, and trichloroethylene. In 2011, concentrations for all VOCs were less than their respective MCL for drinking water, except carbon tetrachloride in water from two wells. During 2009–11, variability and bias were evaluated from 56 replicate and 16 blank quality-assurance samples. Results from replicate analyses were investigated to evaluate sample variability. Constituents with acceptable reproducibility were stable isotope ratios, major ions, nutrients, and VOCs. All radiochemical constituents and trace metals had acceptable reproducibility except for gross beta-particle radioactivity, aluminum, antimony, and cobalt. Bias from sample contamination was evaluated from equipment, field, container, and source-solution blanks. No detectable constituent concentrations were reported for equipment blanks of the thief samplers and sampling pipes or for the source-solution and field blanks. Equipment blanks of bailers had detectable concentrations of strontium-90, sodium, chloride, and sulfate, and the container blank had a detectable concentration of dichloromethane.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135214","collaboration":"Prepared in cooperation with the U.S. Department of Energy","usgsCitation":"Davis, L.C., Bartholomay, R.C., and Rattray, G.W., 2013, An update of hydrologic conditions and distribution of selected constituents in water, eastern Snake River Plain aquifer and perched groundwater zones, Idaho National Laboratory, Idaho, emphasis 2009–11: U.S. Geological Survey Scientific Investigations Report 2013-5214, x, 89 p., https://doi.org/10.3133/sir20135214.","productDescription":"x, 89 p.","numberOfPages":"206","onlineOnly":"Y","ipdsId":"IP-045208","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":280581,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":280580,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5214/pdf/sir20135214.pdf"},{"id":280574,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5214/"}],"projection":"Universal Transverse Mercator projection, Zone 12","datum":"North American Datum of 1927","country":"United States","state":"Idaho","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -113.75,43.25 ], [ -113.75,44.5 ], [ -112.25,44.5 ], [ -112.25,43.25 ], [ -113.75,43.25 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52c68a5ee4b06d2ed1226481","contributors":{"authors":[{"text":"Davis, Linda C. lcdavis@usgs.gov","contributorId":2539,"corporation":false,"usgs":true,"family":"Davis","given":"Linda","email":"lcdavis@usgs.gov","middleInitial":"C.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":486352,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bartholomay, Roy C. 0000-0002-4809-9287 rcbarth@usgs.gov","orcid":"https://orcid.org/0000-0002-4809-9287","contributorId":1131,"corporation":false,"usgs":true,"family":"Bartholomay","given":"Roy","email":"rcbarth@usgs.gov","middleInitial":"C.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":486350,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rattray, Gordon W. 0000-0002-1690-3218 grattray@usgs.gov","orcid":"https://orcid.org/0000-0002-1690-3218","contributorId":2521,"corporation":false,"usgs":true,"family":"Rattray","given":"Gordon","email":"grattray@usgs.gov","middleInitial":"W.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":486351,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70154884,"text":"70154884 - 2013 - What happens in an estuary doesn't stay there: patterns of biotic connectivity resulting from long term ecological research","interactions":[],"lastModifiedDate":"2015-07-15T14:08:36","indexId":"70154884","displayToPublicDate":"2014-01-01T12:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2929,"text":"Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"What happens in an estuary doesn't stay there: patterns of biotic connectivity resulting from long term ecological research","docAbstract":"

The paucity of data on migratory connections and an incomplete understanding of how mobile organisms use geographically separate areas have been obstacles to understanding coastal dynamics. Research on acoustically tagged striped bass (Morone saxatilis) at the Plum Island Ecosystems (PIE) Long Term Ecological Research site, Massachusetts, documents intriguing patterns of biotic connectivity (i.e., long-distance migration between geographically distinct areas). First, the striped bass tagged at PIE migrated southward along the coast using different routes. Second, these tagged fish exhibited strong fidelity and specificity to PIE. For example, across multiple years, tagged striped bass resided in PIE waters for an average of 1.5-2.5 months per year (means: 51-72 days; range 2-122 days), left this estuary in fall, then returned in subsequent years. Third, this specificity and fidelity connected PIE to other locations. The fish exported nutrients and energy to at least three other coastal locations through biomass added as growth. These results demonstrate that what happens in an individual estuary can affect other estuaries. Striped bass that use tightly connected routes to feed in specific estuaries should have greater across-system impacts than fish that are equally likely to go anywhere. Consequently, variations in when, where, and how fish migrate can alter across-estuary impacts.

","language":"English","publisher":"The Oceanography Society","publisherLocation":"Rockville, MD","doi":"10.5670/oceanog.2013.60","usgsCitation":"Mather, M.E., Finn, J.T., Kennedy, C., Deegan, L.A., and Smith, J.M., 2013, What happens in an estuary doesn't stay there: patterns of biotic connectivity resulting from long term ecological research: Oceanography, v. 26, no. 3, p. 168-179, https://doi.org/10.5670/oceanog.2013.60.","productDescription":"12 p.","startPage":"168","endPage":"179","numberOfPages":"12","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"2005-01-01","temporalEnd":"2010-12-31","ipdsId":"IP-045506","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":473370,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5670/oceanog.2013.60","text":"Publisher Index Page"},{"id":305767,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Massachusetts","otherGeospatial":"Plum Island Ecosystems Long Term Ecological Research site","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -70.543212890625,\n 42.01665183556825\n ],\n [\n -70.1806640625,\n 42.17154633452751\n ],\n [\n -69.521484375,\n 41.549700145132725\n ],\n [\n -69.90600585937499,\n 41.15384235711447\n ],\n [\n -74.915771484375,\n 38.75408327579141\n ],\n [\n -75.11352539062499,\n 39.33429742980725\n ],\n [\n -74.20166015624999,\n 40.84706035607122\n ],\n [\n -73.026123046875,\n 41.45919537950706\n ],\n [\n -70.543212890625,\n 42.01665183556825\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"26","issue":"3","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55a7843ae4b0183d66e45e9a","contributors":{"authors":[{"text":"Mather, Martha E. 0000-0003-3027-0215 mather@usgs.gov","orcid":"https://orcid.org/0000-0003-3027-0215","contributorId":2580,"corporation":false,"usgs":true,"family":"Mather","given":"Martha","email":"mather@usgs.gov","middleInitial":"E.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":564311,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Finn, John T.","contributorId":78302,"corporation":false,"usgs":true,"family":"Finn","given":"John","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":564876,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kennedy, Christina G.","contributorId":145646,"corporation":false,"usgs":false,"family":"Kennedy","given":"Christina G.","affiliations":[{"id":6932,"text":"University of Massachusetts, Amherst","active":true,"usgs":false}],"preferred":false,"id":564877,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Deegan, Linda A.","contributorId":34094,"corporation":false,"usgs":false,"family":"Deegan","given":"Linda","email":"","middleInitial":"A.","affiliations":[{"id":27818,"text":"The Ecosystems Center, Marine Biological Laboratory. Woods Hole, MA 02543.","active":true,"usgs":false}],"preferred":false,"id":564878,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Smith, Joseph M.","contributorId":106712,"corporation":false,"usgs":false,"family":"Smith","given":"Joseph","email":"","middleInitial":"M.","affiliations":[{"id":17855,"text":"School of Aquatic and Fishery Sciences, University of Washington, Seattle, WA","active":true,"usgs":false},{"id":6932,"text":"University of Massachusetts, Amherst","active":true,"usgs":false}],"preferred":false,"id":564879,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70093890,"text":"70093890 - 2013 - Blind test of methods for obtaining 2-D near-surface seismic velocity models from first-arrival traveltimes","interactions":[],"lastModifiedDate":"2017-11-07T10:30:12","indexId":"70093890","displayToPublicDate":"2014-01-01T08:43:07","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3928,"text":"Journal of Environmental & Engineering Geophysics","printIssn":"1083-1363","active":true,"publicationSubtype":{"id":10}},"title":"Blind test of methods for obtaining 2-D near-surface seismic velocity models from first-arrival traveltimes","docAbstract":"Seismic refraction methods are used in environmental and engineering studies to image the shallow subsurface. We present a blind test of inversion and tomographic refraction analysis methods using a synthetic first-arrival-time dataset that was made available to the community in 2010. The data are realistic in terms of the near-surface velocity model, shot-receiver geometry and the data's frequency and added noise. Fourteen estimated models were determined by ten participants using eight different inversion algorithms, with the true model unknown to the participants until it was revealed at a session at the 2011 SAGEEP meeting. The estimated models are generally consistent in terms of their large-scale features, demonstrating the robustness of refraction data inversion in general, and the eight inversion algorithms in particular. When compared to the true model, all of the estimated models contain a smooth expression of its two main features: a large offset in the bedrock and the top of a steeply dipping low-velocity fault zone. The estimated models do not contain a subtle low-velocity zone and other fine-scale features, in accord with conventional wisdom. Together, the results support confidence in the reliability and robustness of modern refraction inversion and tomographic methods.","language":"English","publisher":"Journal of Environmental and Engineering Geophysics","doi":"10.2113/JEEG18.3.183","usgsCitation":"Zelt, C.A., Haines, S., Powers, M.H., Sheehan, J., Rohdewald, S., Link, C., Hayashi, K., Zhao, D., Zhou, H., Burton, B., Petersen, U.K., Bonal, N.D., and Doll, W.E., 2013, Blind test of methods for obtaining 2-D near-surface seismic velocity models from first-arrival traveltimes: Journal of Environmental & Engineering Geophysics, v. 18, no. 3, p. 183-194, https://doi.org/10.2113/JEEG18.3.183.","productDescription":"12 p.","startPage":"183","endPage":"194","ipdsId":"IP-043837","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":282370,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.2113/JEEG18.3.183"},{"id":282371,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"18","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd4fa1e4b0b290850f2d42","contributors":{"authors":[{"text":"Zelt, Colin A.","contributorId":99461,"corporation":false,"usgs":true,"family":"Zelt","given":"Colin","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":490258,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haines, Seth 0000-0003-2611-8165","orcid":"https://orcid.org/0000-0003-2611-8165","contributorId":97814,"corporation":false,"usgs":true,"family":"Haines","given":"Seth","affiliations":[],"preferred":false,"id":490257,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Powers, Michael H. 0000-0002-4480-7856 mhpowers@usgs.gov","orcid":"https://orcid.org/0000-0002-4480-7856","contributorId":851,"corporation":false,"usgs":true,"family":"Powers","given":"Michael","email":"mhpowers@usgs.gov","middleInitial":"H.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":490246,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sheehan, Jacob","contributorId":75059,"corporation":false,"usgs":true,"family":"Sheehan","given":"Jacob","email":"","affiliations":[],"preferred":false,"id":490256,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rohdewald, Siegfried","contributorId":64554,"corporation":false,"usgs":true,"family":"Rohdewald","given":"Siegfried","email":"","affiliations":[],"preferred":false,"id":490255,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Link, Curtis","contributorId":6368,"corporation":false,"usgs":true,"family":"Link","given":"Curtis","email":"","affiliations":[],"preferred":false,"id":490248,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hayashi, Koichi","contributorId":22675,"corporation":false,"usgs":true,"family":"Hayashi","given":"Koichi","email":"","affiliations":[],"preferred":false,"id":490251,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Zhao, Don","contributorId":58182,"corporation":false,"usgs":true,"family":"Zhao","given":"Don","email":"","affiliations":[],"preferred":false,"id":490254,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Zhou, Hua-wei","contributorId":11504,"corporation":false,"usgs":true,"family":"Zhou","given":"Hua-wei","email":"","affiliations":[],"preferred":false,"id":490249,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Burton, Bethany L. 0000-0001-5011-7862 blburton@usgs.gov","orcid":"https://orcid.org/0000-0001-5011-7862","contributorId":1341,"corporation":false,"usgs":true,"family":"Burton","given":"Bethany L.","email":"blburton@usgs.gov","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":false,"id":490247,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Petersen, Uni K.","contributorId":34037,"corporation":false,"usgs":true,"family":"Petersen","given":"Uni","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":490253,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Bonal, Nedra D.","contributorId":26620,"corporation":false,"usgs":true,"family":"Bonal","given":"Nedra","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":490252,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Doll, William E.","contributorId":20249,"corporation":false,"usgs":true,"family":"Doll","given":"William","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":490250,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70171458,"text":"70171458 - 2013 - Emulating natural disturbances for declining late-successional species: A case study of the consequences for Cerulean Warblers (Setophaga cerulea)","interactions":[],"lastModifiedDate":"2016-05-31T15:39:54","indexId":"70171458","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Emulating natural disturbances for declining late-successional species: A case study of the consequences for Cerulean Warblers (Setophaga cerulea)","docAbstract":"

Forest cover in the eastern United States has increased over the past century and while some late-successional species have benefited from this process as expected, others have experienced population declines. These declines may be in part related to contemporary reductions in small-scale forest interior disturbances such as fire, windthrow, and treefalls. To mitigate the negative impacts of disturbance alteration and suppression on some late-successional species, strategies that emulate natural disturbance regimes are often advocated, but large-scale evaluations of these practices are rare. Here, we assessed the consequences of experimental disturbance (using partial timber harvest) on a severely declining late-successional species, the cerulean warbler (Setophaga cerulea), across the core of its breeding range in the Appalachian Mountains. We measured numerical (density), physiological (body condition), and demographic (age structure and reproduction) responses to three levels of disturbance and explored the potential impacts of disturbance on source-sink dynamics. Breeding densities of warblers increased one to four years after all canopy disturbances (vs. controls) and males occupying territories on treatment plots were in better condition than those on control plots. However, these beneficial effects of disturbance did not correspond to improvements in reproduction; nest success was lower on all treatment plots than on control plots in the southern region and marginally lower on light disturbance plots in the northern region. Our data suggest that only habitats in the southern region acted as sources, and interior disturbances in this region have the potential to create ecological traps at a local scale, but sources when viewed at broader scales. Thus, cerulean warblers would likely benefit from management that strikes a landscape-level balance between emulating natural disturbances in order to attract individuals into areas where current structure is inappropriate, and limiting anthropogenic disturbance in forests that already possess appropriate structural attributes in order to maintain maximum productivity.

","language":"English","publisher":"PLoS","doi":"10.1371/journal.pone.0052107","usgsCitation":"Boves, T.J., Buehler, D.A., Sheehan, J., Wood, P.B., Rodewald, A.D., Larkin, J.L., Keyser, P.D., Newell, F.L., George, G.A., Bakermans, M.H., Evans, A., Beachy, T.A., McDermott, M., Perkins, K.A., White, M., and Wigley, T.B., 2013, Emulating natural disturbances for declining late-successional species: A case study of the consequences for Cerulean Warblers (Setophaga cerulea): PLoS ONE, v. 8, no. 1, p. 1-13, https://doi.org/10.1371/journal.pone.0052107.","productDescription":"e52107; 13 p.","startPage":"1","endPage":"13","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-037905","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":473374,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0052107","text":"Publisher Index Page"},{"id":321945,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2013-01-04","publicationStatus":"PW","scienceBaseUri":"574eb5c4e4b0ee97d51a83b2","contributors":{"authors":[{"text":"Boves, Than J.","contributorId":169750,"corporation":false,"usgs":false,"family":"Boves","given":"Than","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":631075,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Buehler, David A.","contributorId":169746,"corporation":false,"usgs":false,"family":"Buehler","given":"David","email":"","middleInitial":"A.","affiliations":[{"id":12716,"text":"University of Tennessee","active":true,"usgs":false}],"preferred":false,"id":631072,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sheehan, James","contributorId":169745,"corporation":false,"usgs":false,"family":"Sheehan","given":"James","email":"","affiliations":[],"preferred":false,"id":631073,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wood, Petra Bohall pbwood@usgs.gov","contributorId":1791,"corporation":false,"usgs":true,"family":"Wood","given":"Petra","email":"pbwood@usgs.gov","middleInitial":"Bohall","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":631070,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rodewald, Amanda D.","contributorId":169748,"corporation":false,"usgs":false,"family":"Rodewald","given":"Amanda","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":631071,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Larkin, Jeffrey L.","contributorId":169747,"corporation":false,"usgs":false,"family":"Larkin","given":"Jeffrey","email":"","middleInitial":"L.","affiliations":[{"id":17929,"text":"American Bird Conservancy","active":true,"usgs":false},{"id":34542,"text":"Department of Biology. Indiana University of Pennsylvania","active":true,"usgs":false}],"preferred":false,"id":631074,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Keyser, Patrick D.","contributorId":146945,"corporation":false,"usgs":false,"family":"Keyser","given":"Patrick","email":"","middleInitial":"D.","affiliations":[{"id":12716,"text":"University of Tennessee","active":true,"usgs":false}],"preferred":false,"id":631109,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Newell, Felicity L.","contributorId":169755,"corporation":false,"usgs":false,"family":"Newell","given":"Felicity","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":631110,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"George, Gregory A.","contributorId":169751,"corporation":false,"usgs":false,"family":"George","given":"Gregory","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":631111,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Bakermans, Marja H.","contributorId":169752,"corporation":false,"usgs":false,"family":"Bakermans","given":"Marja","email":"","middleInitial":"H.","affiliations":[{"id":33354,"text":"Worcester Polytechnic Institute","active":true,"usgs":false}],"preferred":false,"id":631112,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Evans, Andrea","contributorId":169754,"corporation":false,"usgs":false,"family":"Evans","given":"Andrea","email":"","affiliations":[],"preferred":false,"id":631113,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Beachy, Tiffany A.","contributorId":169753,"corporation":false,"usgs":false,"family":"Beachy","given":"Tiffany","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":631114,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"McDermott, Molly E. 0000-0002-0000-0831","orcid":"https://orcid.org/0000-0002-0000-0831","contributorId":169743,"corporation":false,"usgs":false,"family":"McDermott","given":"Molly E.","affiliations":[],"preferred":false,"id":631115,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Perkins, Kelly A.","contributorId":169756,"corporation":false,"usgs":false,"family":"Perkins","given":"Kelly","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":631116,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"White, Matthew","contributorId":169757,"corporation":false,"usgs":false,"family":"White","given":"Matthew","email":"","affiliations":[],"preferred":false,"id":631117,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Wigley, T. Bently","contributorId":169749,"corporation":false,"usgs":false,"family":"Wigley","given":"T.","email":"","middleInitial":"Bently","affiliations":[],"preferred":false,"id":631118,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}} ,{"id":70171457,"text":"70171457 - 2013 - Comparison of point counts and territory mapping for detecting effects of forest management on songbirds","interactions":[],"lastModifiedDate":"2016-05-31T15:45:42","indexId":"70171457","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2284,"text":"Journal of Field Ornithology","active":true,"publicationSubtype":{"id":10}},"title":"Comparison of point counts and territory mapping for detecting effects of forest management on songbirds","docAbstract":"

Point counts are commonly used to assess changes in bird abundance, including analytical approaches such as distance sampling that estimate density. Point-count methods have come under increasing scrutiny because effects of detection probability and field error are difficult to quantify. For seven forest songbirds, we compared fixed-radii counts (50 m and 100 m) and density estimates obtained from distance sampling to known numbers of birds determined by territory mapping. We applied point-count analytic approaches to a typical forest management question and compared results to those obtained by territory mapping. We used a before–after control impact (BACI) analysis with a data set collected across seven study areas in the central Appalachians from 2006 to 2010. Using a 50-m fixed radius, variance in error was at least 1.5 times that of the other methods, whereas a 100-m fixed radius underestimated actual density by >3 territories per 10 ha for the most abundant species. Distance sampling improved accuracy and precision compared to fixed-radius counts, although estimates were affected by birds counted outside 10-ha units. In the BACI analysis, territory mapping detected an overall treatment effect for five of the seven species, and effects were generally consistent each year. In contrast, all point-count methods failed to detect two treatment effects due to variance and error in annual estimates. Overall, our results highlight the need for adequate sample sizes to reduce variance, and skilled observers to reduce the level of error in point-count data. Ultimately, the advantages and disadvantages of different survey methods should be considered in the context of overall study design and objectives, allowing for trade-offs among effort, accuracy, and power to detect treatment effects.

","language":"English","publisher":"Wiley","doi":"10.1111/jofo.12026","usgsCitation":"Newell, F.L., Sheehan, J., Wood, P.B., Rodewald, A.D., Buehler, D.A., Keyser, P.D., Larkin, J.L., Beachy, T.A., Bakermans, M.H., Boves, T.J., Evans, A., George, G.A., McDermott, M., Perkins, K.A., White, M., and Wigley, T.B., 2013, Comparison of point counts and territory mapping for detecting effects of forest management on songbirds: Journal of Field Ornithology, v. 84, no. 3, p. 270-286, https://doi.org/10.1111/jofo.12026.","productDescription":"17 p.","startPage":"270","endPage":"286","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-038461","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":321946,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"84","issue":"3","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2013-08-23","publicationStatus":"PW","scienceBaseUri":"574eb5bae4b0ee97d51a83a2","contributors":{"authors":[{"text":"Newell, Felicity L.","contributorId":169755,"corporation":false,"usgs":false,"family":"Newell","given":"Felicity","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":631121,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sheehan, James","contributorId":169745,"corporation":false,"usgs":false,"family":"Sheehan","given":"James","email":"","affiliations":[],"preferred":false,"id":631122,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wood, Petra Bohall pbwood@usgs.gov","contributorId":1791,"corporation":false,"usgs":true,"family":"Wood","given":"Petra","email":"pbwood@usgs.gov","middleInitial":"Bohall","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":631123,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rodewald, Amanda D.","contributorId":169748,"corporation":false,"usgs":false,"family":"Rodewald","given":"Amanda","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":631124,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Buehler, David A.","contributorId":169746,"corporation":false,"usgs":false,"family":"Buehler","given":"David","email":"","middleInitial":"A.","affiliations":[{"id":12716,"text":"University of Tennessee","active":true,"usgs":false}],"preferred":false,"id":631125,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Keyser, Patrick D.","contributorId":146945,"corporation":false,"usgs":false,"family":"Keyser","given":"Patrick","email":"","middleInitial":"D.","affiliations":[{"id":12716,"text":"University of Tennessee","active":true,"usgs":false}],"preferred":false,"id":631126,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Larkin, Jeffrey L.","contributorId":169747,"corporation":false,"usgs":false,"family":"Larkin","given":"Jeffrey","email":"","middleInitial":"L.","affiliations":[{"id":34542,"text":"Department of Biology. Indiana University of Pennsylvania","active":true,"usgs":false},{"id":17929,"text":"American Bird Conservancy","active":true,"usgs":false}],"preferred":false,"id":631127,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Beachy, Tiffany A.","contributorId":169753,"corporation":false,"usgs":false,"family":"Beachy","given":"Tiffany","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":631128,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Bakermans, Marja H.","contributorId":169752,"corporation":false,"usgs":false,"family":"Bakermans","given":"Marja","email":"","middleInitial":"H.","affiliations":[{"id":33354,"text":"Worcester Polytechnic Institute","active":true,"usgs":false}],"preferred":false,"id":631129,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Boves, Than J.","contributorId":169750,"corporation":false,"usgs":false,"family":"Boves","given":"Than","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":631130,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Evans, Andrea","contributorId":169754,"corporation":false,"usgs":false,"family":"Evans","given":"Andrea","email":"","affiliations":[],"preferred":false,"id":631131,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"George, Gregory A.","contributorId":169751,"corporation":false,"usgs":false,"family":"George","given":"Gregory","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":631132,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"McDermott, Molly E. 0000-0002-0000-0831","orcid":"https://orcid.org/0000-0002-0000-0831","contributorId":169743,"corporation":false,"usgs":false,"family":"McDermott","given":"Molly E.","affiliations":[],"preferred":false,"id":631133,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Perkins, Kelly A.","contributorId":169756,"corporation":false,"usgs":false,"family":"Perkins","given":"Kelly","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":631134,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"White, Matthew","contributorId":169757,"corporation":false,"usgs":false,"family":"White","given":"Matthew","email":"","affiliations":[],"preferred":false,"id":631135,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Wigley, T. Bently","contributorId":169749,"corporation":false,"usgs":false,"family":"Wigley","given":"T.","email":"","middleInitial":"Bently","affiliations":[],"preferred":false,"id":631136,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}} ,{"id":70155070,"text":"70155070 - 2013 - Quantitative and qualitative approaches to identifying migration chronology in a continental migrant","interactions":[],"lastModifiedDate":"2015-08-05T13:01:35","indexId":"70155070","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Quantitative and qualitative approaches to identifying migration chronology in a continental migrant","docAbstract":"

The degree to which extrinsic factors influence migration chronology in North American waterfowl has not been quantified, particularly for dabbling ducks. Previous studies have examined waterfowl migration using various methods, however, quantitative approaches to define avian migration chronology over broad spatio-temporal scales are limited, and the implications for using different approaches have not been assessed. We used movement data from 19 female adult mallards (Anas platyrhynchos) equipped with solar-powered global positioning system satellite transmitters to evaluate two individual level approaches for quantifying migration chronology. The first approach defined migration based on individual movements among geopolitical boundaries (state, provincial, international), whereas the second method modeled net displacement as a function of time using nonlinear models. Differences in migration chronologies identified by each of the approaches were examined with analysis of variance. The geopolitical method identified mean autumn migration midpoints at 15 November 2010 and 13 November 2011, whereas the net displacement method identified midpoints at 15 November 2010 and 14 November 2011. The mean midpoints for spring migration were 3 April 2011 and 20 March 2012 using the geopolitical method and 31 March 2011 and 22 March 2012 using the net displacement method. The duration, initiation date, midpoint, and termination date for both autumn and spring migration did not differ between the two individual level approaches. Although we did not detect differences in migration parameters between the different approaches, the net displacement metric offers broad potential to address questions in movement ecology for migrating species. Ultimately, an objective definition of migration chronology will allow researchers to obtain a comprehensive understanding of the extrinsic factors that drive migration at the individual and population levels. As a result, targeted conservation plans can be developed to support planning for habitat management and evaluation of long-term climate effects.

","language":"English","publisher":"Public Library of Science","publisherLocation":"San Francisco, CA","doi":"10.1371/journal.pone.0075673","usgsCitation":"Beatty, W.S., Kesler, D.C., Webb, E.B., Raedeke, A.H., Naylor, L.W., and Humburg, D.D., 2013, Quantitative and qualitative approaches to identifying migration chronology in a continental migrant: PLoS ONE, p. 1-9, https://doi.org/10.1371/journal.pone.0075673.","productDescription":"e75673; 9 p.","startPage":"1","endPage":"9","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2010-09-01","temporalEnd":"2012-12-31","ipdsId":"IP-045956","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":473373,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0075673","text":"Publisher Index Page"},{"id":306440,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2013-10-09","publicationStatus":"PW","scienceBaseUri":"57f7f1d6e4b0bc0bec0a0024","contributors":{"authors":[{"text":"Beatty, William S. 0000-0003-0013-3113","orcid":"https://orcid.org/0000-0003-0013-3113","contributorId":146301,"corporation":false,"usgs":false,"family":"Beatty","given":"William","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":567383,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kesler, Dylan C.","contributorId":14358,"corporation":false,"usgs":false,"family":"Kesler","given":"Dylan","email":"","middleInitial":"C.","affiliations":[{"id":6769,"text":"University of Missouri, Columbia, MO","active":true,"usgs":false}],"preferred":false,"id":567384,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Webb, Elisabeth B. 0000-0003-3851-6056 ewebb@usgs.gov","orcid":"https://orcid.org/0000-0003-3851-6056","contributorId":3981,"corporation":false,"usgs":true,"family":"Webb","given":"Elisabeth","email":"ewebb@usgs.gov","middleInitial":"B.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":564764,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Raedeke, Andrew H.","contributorId":94083,"corporation":false,"usgs":true,"family":"Raedeke","given":"Andrew","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":567385,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Naylor, Luke W.","contributorId":145840,"corporation":false,"usgs":false,"family":"Naylor","given":"Luke","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":567386,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Humburg, Dale D.","contributorId":79357,"corporation":false,"usgs":false,"family":"Humburg","given":"Dale","email":"","middleInitial":"D.","affiliations":[{"id":13073,"text":"Ducks Unlimited, Inc.","active":true,"usgs":false}],"preferred":false,"id":567387,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70173625,"text":"70173625 - 2013 - Landsat imagery reveals declining clarity of Maine’s lakes during 1995-2010","interactions":[],"lastModifiedDate":"2016-06-09T15:10:12","indexId":"70173625","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1699,"text":"Freshwater Science","active":true,"publicationSubtype":{"id":10}},"title":"Landsat imagery reveals declining clarity of Maine’s lakes during 1995-2010","docAbstract":"

Water clarity is a strong indicator of regional water quality. Unlike other common water-quality metrics, such as chlorophyll a, total P, or trophic status, clarity can be accurately and efficiently estimated remotely on a regional scale. Satellite-based remote sensing is useful in regions with many lakes where traditional field-sampling techniques may be prohibitively expensive. Repeated sampling of easily accessed lakes can lead to spatially irregular, nonrandom samples of a region. Remote sensing remedies this problem. We applied a remote monitoring protocol we had previously developed for Maine lakes >8 ha based on Landsat satellite data recorded during 1995–2010 to identify spatial and temporal patterns in Maine lake clarity. We focused on the overlapping region of Landsat paths 11 and 12 to increase availability of cloud-free images in August and early September, a period of relative lake stability and seasonal poor-clarity conditions well suited for annual monitoring. We divided Maine into 3 regions (northeastern, south-central, western) based on morphometric and chemical lake features. We found a general decrease in average statewide lake clarity from 4.94 to 4.38 m during 1995–2010. Water clarity ranged from 4 to 6 m during 1995–2010, but it decreased consistently during 2005–2010. Clarity in both the northeastern and western lake regions has decreased from 5.22 m in 1995 to 4.36 and 4.21 m, respectively, in 2010, whereas lake clarity in the south-central lake region (4.50 m) has not changed since 1995. Climate change, timber harvesting, or watershed morphometry may be responsible for regional water-clarity decline. Remote sensing of regional water clarity provides a more complete spatial perspective of lake water quality than existing, interest-based sampling. However, field sampling done under existing monitoring programs can be used to calibrate accurate models designed to estimate water clarity remotely.

","language":"English","publisher":"The University of Chicago Press","doi":"10.1899/12-070.1","usgsCitation":"McCullough, I.M., Loftin, C., and Sader, S., 2013, Landsat imagery reveals declining clarity of Maine’s lakes during 1995-2010: Freshwater Science, v. 32, no. 3, p. 741-752, https://doi.org/10.1899/12-070.1.","productDescription":"12 p.","startPage":"741","endPage":"752","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"1995-01-01","ipdsId":"IP-036854","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":323411,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"32","issue":"3","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"575a9333e4b04f417c275162","contributors":{"authors":[{"text":"McCullough, Ian M.","contributorId":149952,"corporation":false,"usgs":false,"family":"McCullough","given":"Ian","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":638297,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Loftin, Cynthia S. 0000-0001-9104-3724 cyndy_loftin@usgs.gov","orcid":"https://orcid.org/0000-0001-9104-3724","contributorId":2167,"corporation":false,"usgs":true,"family":"Loftin","given":"Cynthia S.","email":"cyndy_loftin@usgs.gov","affiliations":[],"preferred":true,"id":637416,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sader, Steven A.","contributorId":112282,"corporation":false,"usgs":true,"family":"Sader","given":"Steven A.","affiliations":[],"preferred":false,"id":638298,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70173432,"text":"70173432 - 2013 - Accuracy of stream habitat interpolations across spatial scales","interactions":[],"lastModifiedDate":"2016-06-21T16:13:26","indexId":"70173432","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5095,"text":"Journal of Geographic Information System","active":true,"publicationSubtype":{"id":10}},"title":"Accuracy of stream habitat interpolations across spatial scales","docAbstract":"

Stream habitat data are often collected across spatial scales because relationships among habitat, species occurrence, and management plans are linked at multiple spatial scales. Unfortunately, scale is often a factor limiting insight gained from spatial analysis of stream habitat data. Considerable cost is often expended to collect data at several spatial scales to provide accurate evaluation of spatial relationships in streams. To address utility of single scale set of stream habitat data used at varying scales, we examined the influence that data scaling had on accuracy of natural neighbor predictions of depth, flow, and benthic substrate. To achieve this goal, we measured two streams at gridded resolution of 0.33 × 0.33 meter cell size over a combined area of 934 m2 to create a baseline for natural neighbor interpolated maps at 12 incremental scales ranging from a raster cell size of 0.11 m2 to 16 m2 . Analysis of predictive maps showed a logarithmic linear decay pattern in RMSE values in interpolation accuracy for variables as resolution of data used to interpolate study areas became coarser. Proportional accuracy of interpolated models (r2 ) decreased, but it was maintained up to 78% as interpolation scale moved from 0.11 m2 to 16 m2 . Results indicated that accuracy retention was suitable for assessment and management purposes at various scales different from the data collection scale. Our study is relevant to spatial modeling, fish habitat assessment, and stream habitat management because it highlights the potential of using a single dataset to fulfill analysis needs rather than investing considerable cost to develop several scaled datasets.

","language":"English","publisher":"Scientific Research","doi":"10.4236/jgis.2013.56057","usgsCitation":"Sheehan, K.R., and Welsh, S., 2013, Accuracy of stream habitat interpolations across spatial scales: Journal of Geographic Information System, v. 5, p. 606-612, https://doi.org/10.4236/jgis.2013.56057.","productDescription":"7 p.","startPage":"606","endPage":"612","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-033558","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":473384,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.4236/jgis.2013.56057","text":"Publisher Index Page"},{"id":324171,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"5","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"576a652fe4b07657d1a11cee","contributors":{"authors":[{"text":"Sheehan, Kenneth R.","contributorId":146541,"corporation":false,"usgs":false,"family":"Sheehan","given":"Kenneth","email":"","middleInitial":"R.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":637126,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Welsh, Stuart A. 0000-0003-0362-054X swelsh@usgs.gov","orcid":"https://orcid.org/0000-0003-0362-054X","contributorId":152088,"corporation":false,"usgs":true,"family":"Welsh","given":"Stuart A.","email":"swelsh@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":637125,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70192303,"text":"70192303 - 2013 - Fifty years after Welles and Welles: Distribution and genetic structure of Desert Bighorn Sheep in Death Valley National Park","interactions":[],"lastModifiedDate":"2018-02-27T11:20:41","indexId":"70192303","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Fifty years after Welles and Welles: Distribution and genetic structure of Desert Bighorn Sheep in Death Valley National Park","docAbstract":"The status of desert bighorn sheep (Ovis canadensis nelsoni) populations in the mountains around Death Valley was first evaluated in 1938, shortly after designation of Death Valley National Monument. However, the most comprehensive evaluation of bighorn sheep in the region was conducted by Ralph and Florence Welles during 1955-1961. They documented patterns of use at water sources and other focal areas around Death Valley and roughly estimated numbers of bighorn sheep from observational data. Data collection on bighorn sheep in the area since that time has\nlacked a regional approach needed to address metapopulation questions.From 2011-2013, we evaluated bighorn activity at important water sources and other likely locations around Death Valley using remote cameras and observations of tracks, beds, sign, and bighorn sheep, and non-invasively collected genetic samples (fecal pellets and bones).\nWhere possible, we revisited many of the water sources and other locations originally investigated by Welles and Welles (1961) and earlier researchers. We extracted DNA from fecal pellets, carcass tissue samples, and blood samples archived from earlier captures and genotyped them using highly variable genetic markers (15 microsatellite loci) with sufficient power to distinguish individuals and characterize gene flow and genetic structure. We also analyzed DNA samples collected from other bighorn sheep populations extending north to the White Mountains, west to the Inyo Mountains, south to the Avawatz Mountains, and southeast to the Clark Mountain Range, Kingston Range, and Spring Mountains of Nevada. We estimated genetic structure and recent gene flow among nearly all known populations of bighorn sheep in and around Death Valley National Park (DEVA), and used assignment tests to evaluate individual and population-level genetic structure to infer connectivity across the region. We found that bighorn sheep are still widely distributed in mountain ranges throughout DEVA, including many of the areas described by Welles and Welles (1961), although some use patterns appear to have changed and other areas still require resurvey. Gene flow was relatively high through some sections of fairly continuous habitat, such as the Grapevine and Funeral Mountains along the eastern side of Death Valley, but other populations were more isolated. Genetic diversity was relatively high throughout the park. Although southern Death Valley populations were genetically distinct from populations to the southeast, population assignment tests and recent gene flow estimates suggested that individuals occasionally migrate between those regions, indicating the potential for the recent outbreak of respiratory disease in the southern Mojave Desert to spread into the Death Valley system. We recommend careful monitoring of bighorn sheep using remote cameras to check for signs of respiratory disease in southeastern DEVA and ground surveys in the still-understudied southwestern part of DEVA.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"1st Death Valley Natural History Conference Proceedings","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"Death Valley National History Association","usgsCitation":"Epps, C.W., Wehausen, J.D., Sloan, W.B., Holt, S., Creech, T.G., Crowhurst, R.S., Jaeger, J.R., Longshore, K.M., and Monello, R.J., 2013, Fifty years after Welles and Welles: Distribution and genetic structure of Desert Bighorn Sheep in Death Valley National Park, in 1st Death Valley Natural History Conference Proceedings.","ipdsId":"IP-056088","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":352068,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":347251,"type":{"id":15,"text":"Index Page"},"url":"https://dvnha.org/opencart/index.php?route=product/product&product_id=768&search=proceedings+Death+Valley+Natural+History+Conference"}],"publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afeefd7e4b0da30c1bfc798","contributors":{"authors":[{"text":"Epps, Clinton W.","contributorId":198148,"corporation":false,"usgs":false,"family":"Epps","given":"Clinton","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":715207,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wehausen, John D.","contributorId":198149,"corporation":false,"usgs":false,"family":"Wehausen","given":"John","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":715208,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sloan, William B.","contributorId":198150,"corporation":false,"usgs":false,"family":"Sloan","given":"William","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":715209,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Holt, Stacy","contributorId":198151,"corporation":false,"usgs":false,"family":"Holt","given":"Stacy","email":"","affiliations":[],"preferred":false,"id":715210,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Creech, Tyler G.","contributorId":198152,"corporation":false,"usgs":false,"family":"Creech","given":"Tyler","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":715211,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Crowhurst, Rachel S.","contributorId":198153,"corporation":false,"usgs":false,"family":"Crowhurst","given":"Rachel","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":715212,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jaeger, Jef R.","contributorId":198154,"corporation":false,"usgs":false,"family":"Jaeger","given":"Jef","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":715213,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Longshore, Kathleen M. 0000-0001-6621-1271 longshore@usgs.gov","orcid":"https://orcid.org/0000-0001-6621-1271","contributorId":2677,"corporation":false,"usgs":true,"family":"Longshore","given":"Kathleen","email":"longshore@usgs.gov","middleInitial":"M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":715206,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Monello, Ryan J.","contributorId":184143,"corporation":false,"usgs":false,"family":"Monello","given":"Ryan","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":715214,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70192414,"text":"70192414 - 2013 - Rapid chemical evolution of tropospheric volcanic emissions from Redoubt Volcano, Alaska, based on observations of ozone and halogen-containing gases","interactions":[],"lastModifiedDate":"2017-10-25T15:11:01","indexId":"70192414","displayToPublicDate":"2013-12-31T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Rapid chemical evolution of tropospheric volcanic emissions from Redoubt Volcano, Alaska, based on observations of ozone and halogen-containing gases","docAbstract":"

We report results from an observational and modeling study of reactive chemistry in the tropospheric plume emitted by Redoubt Volcano, Alaska. Our measurements include the first observations of Br and I degassing from an Alaskan volcano, the first study of O3 evolution in a volcanic plume, as well as the first detection of BrO in the plume of a passively degassing Alaskan volcano. This study also represents the first detailed spatially-resolved comparison of measured and modeled O3 depletion in a volcanic plume. The composition of the plume was measured on June 20, 2010 using base-treated filter packs (for F, Cl, Br, I, and S) at the crater rim and by an instrumented fixed-wing aircraft on June 21 and August 19, 2010. The aircraft was used to track the chemical evolution of the plume up to ~ 30 km downwind (2 h plume travel time) from the volcano and was equipped to make in situ observations of O3, water vapor, CO2, SO2, and H2S during both flights plus remote spectroscopic observations of SO2 and BrO on the August 19th flight. The airborne data from June 21 reveal rapid chemical O3 destruction in the plume as well as the strong influence chemical heterogeneity in background air had on plume composition. Spectroscopic retrievals from airborne traverses made under the plume on August 19 show that BrO was present ~ 6 km downwind (20 min plume travel time) and in situ measurements revealed several ppbv of O3 loss near the center of the plume at a similar location downwind. Simulations with the PlumeChem model reproduce the timing and magnitude of the observed O3 deficits and suggest that autocatalytic release of reactive bromine and in-plume formation of BrO were primarily responsible for the observed O3 destruction in the plume. The measurements are therefore in general agreement with recent model studies of reactive halogen formation in volcanic plumes, but also show that field studies must pay close attention to variations in the composition of ambient air entrained into volcanic plumes in order to unambiguously attribute observed O3 anomalies to specific chemical or dynamic processes. Our results suggest that volcanic eruptions in Alaska are sources of reactive halogen species to the subarctic troposphere.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2012.04.023","usgsCitation":"Werner, C.A., Kelly, P.J., Kern, C., Roberts, T., and Aluppe, A., 2013, Rapid chemical evolution of tropospheric volcanic emissions from Redoubt Volcano, Alaska, based on observations of ozone and halogen-containing gases: Journal of Volcanology and Geothermal Research, v. 259, p. 317-333, https://doi.org/10.1016/j.jvolgeores.2012.04.023.","productDescription":"17 p.","startPage":"317","endPage":"333","ipdsId":"IP-035796","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":473392,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/10447/99077","text":"External Repository"},{"id":347388,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Redoubt Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -154,\n 59\n ],\n [\n -149,\n 59\n ],\n [\n -149,\n 62\n ],\n [\n -154,\n 62\n ],\n [\n -154,\n 59\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"259","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59f1a2a9e4b0220bbd9d9fa8","contributors":{"authors":[{"text":"Werner, Cynthia A. cwerner@usgs.gov","contributorId":2540,"corporation":false,"usgs":true,"family":"Werner","given":"Cynthia","email":"cwerner@usgs.gov","middleInitial":"A.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":715744,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kelly, Peter J. 0000-0002-3868-1046 pkelly@usgs.gov","orcid":"https://orcid.org/0000-0002-3868-1046","contributorId":5931,"corporation":false,"usgs":true,"family":"Kelly","given":"Peter","email":"pkelly@usgs.gov","middleInitial":"J.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":715747,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Kern, Christoph 0000-0002-8920-5701 ckern@usgs.gov","orcid":"https://orcid.org/0000-0002-8920-5701","contributorId":3387,"corporation":false,"usgs":true,"family":"Kern","given":"Christoph","email":"ckern@usgs.gov","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":715746,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Roberts, T.J.","contributorId":198344,"corporation":false,"usgs":false,"family":"Roberts","given":"T.J.","email":"","affiliations":[],"preferred":false,"id":715748,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Aluppe, A.","contributorId":198341,"corporation":false,"usgs":false,"family":"Aluppe","given":"A.","email":"","affiliations":[],"preferred":false,"id":715745,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}} ,{"id":70192301,"text":"70192301 - 2013 - Black bear density in Glacier National Park, Montana","interactions":[],"lastModifiedDate":"2017-10-26T09:57:40","indexId":"70192301","displayToPublicDate":"2013-12-31T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3779,"text":"Wildlife Society Bulletin","onlineIssn":"1938-5463","printIssn":"0091-7648","active":true,"publicationSubtype":{"id":10}},"title":"Black bear density in Glacier National Park, Montana","docAbstract":"

We report the first abundance and density estimates for American black bears (Ursus americanus) in Glacier National Park (NP),Montana, USA.We used data from 2 independent and concurrent noninvasive genetic sampling methods—hair traps and bear rubs—collected during 2004 to generate individual black bear encounter histories for use in closed population mark–recapture models. We improved the precision of our abundance estimate by using noninvasive genetic detection events to develop individual-level covariates of sampling effort within the full and one-half mean maximum distance moved (MMDM) from each bear’s estimated activity center to explain capture probability heterogeneity and inform our estimate of the effective sampling area.Models including the one-halfMMDMcovariate received overwhelming Akaike’s Information Criterion support suggesting that buffering our study area by this distance would be more appropriate than no buffer or the full MMDM buffer for estimating the effectively sampled area and thereby density. Our modelaveraged super-population abundance estimate was 603 (95% CI¼522–684) black bears for Glacier NP. Our black bear density estimate (11.4 bears/100 km2, 95% CI¼9.9–13.0) was consistent with published estimates for populations that are sympatric with grizzly bears (U. arctos) and without access to spawning salmonids. Published 2013. This article is a U.S. Government work and is in the public domain in the USA.

","language":"English","publisher":"Wiley","doi":"10.1002/wsb.356","usgsCitation":"Stetz, J.B., Kendall, K.C., and Macleod, A.C., 2013, Black bear density in Glacier National Park, Montana: Wildlife Society Bulletin, v. 38, no. 1, p. 60-70, https://doi.org/10.1002/wsb.356.","productDescription":"11 p.","startPage":"60","endPage":"70","ipdsId":"IP-045361","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":500011,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doaj.org/article/bbe229248951484a85366b0798f527ef","text":"External Repository"},{"id":347347,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","otherGeospatial":"Glacier National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.0543212890625,\n 49.001843917978526\n ],\n [\n -114.993896484375,\n 48.929717630629554\n ],\n [\n -114.884033203125,\n 48.89722676235673\n ],\n [\n -114.72473144531251,\n 48.8936153614802\n ],\n [\n -114.72473144531251,\n 48.79600890414036\n ],\n [\n -114.697265625,\n 48.72358515157852\n ],\n [\n -114.47753906249999,\n 48.56024979174329\n ],\n [\n -114.3182373046875,\n 48.46199462233164\n ],\n [\n -114.1644287109375,\n 48.46563710044979\n ],\n [\n -114.0216064453125,\n 48.50932644976633\n ],\n [\n -113.93920898437499,\n 48.50932644976633\n ],\n [\n -113.8128662109375,\n 48.44013426398058\n ],\n [\n -113.7744140625,\n 48.40367941865281\n ],\n [\n -113.69750976562499,\n 48.334343174592014\n ],\n [\n -113.65905761718749,\n 48.26491251331118\n ],\n [\n -113.521728515625,\n 48.25759852914997\n ],\n [\n -113.31298828125,\n 48.29781249243716\n ],\n [\n -113.258056640625,\n 48.425555463221066\n ],\n [\n -113.41735839843749,\n 48.69096039092549\n ],\n [\n -113.4283447265625,\n 48.73807825631017\n ],\n [\n -113.48876953125,\n 48.76343113791796\n ],\n [\n -113.62060546875,\n 48.94415123418794\n ],\n [\n -113.609619140625,\n 48.99463598353405\n ],\n [\n -115.0543212890625,\n 49.001843917978526\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"38","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2013-11-08","publicationStatus":"PW","scienceBaseUri":"59f1a2a9e4b0220bbd9d9fb9","contributors":{"authors":[{"text":"Stetz, Jeff B.","contributorId":198142,"corporation":false,"usgs":false,"family":"Stetz","given":"Jeff","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":715190,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kendall, Katherine C. 0000-0002-4831-2287 kkendall@usgs.gov","orcid":"https://orcid.org/0000-0002-4831-2287","contributorId":3081,"corporation":false,"usgs":true,"family":"Kendall","given":"Katherine","email":"kkendall@usgs.gov","middleInitial":"C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":715188,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Macleod, Amy C.","contributorId":198141,"corporation":false,"usgs":false,"family":"Macleod","given":"Amy","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":715189,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70059790,"text":"70059790 - 2013 - Conflation and aggregation of spatial data improve predictive models for species with limited habitats: a case of the threatened yellow-billed cuckoo in Arizona, USA","interactions":[],"lastModifiedDate":"2018-09-18T16:29:07","indexId":"70059790","displayToPublicDate":"2013-12-30T14:56:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":836,"text":"Applied Geography","active":true,"publicationSubtype":{"id":10}},"title":"Conflation and aggregation of spatial data improve predictive models for species with limited habitats: a case of the threatened yellow-billed cuckoo in Arizona, USA","docAbstract":"Riparian vegetation provides important wildlife habitat in the Southwestern United States, but limited distributions and spatial complexity often leads to inaccurate representation in maps used to guide conservation. We test the use of data conflation and aggregation on multiple vegetation/land-cover maps to improve the accuracy of habitat models for the threatened western yellow-billed cuckoo (Coccyzus americanus occidentalis). We used species observations (n = 479) from a state-wide survey to develop habitat models from 1) three vegetation/land-cover maps produced at different geographic scales ranging from state to national, and 2) new aggregate maps defined by the spatial agreement of cover types, which were defined as high (agreement = all data sets), moderate (agreement ≥ 2), and low (no agreement required). Model accuracies, predicted habitat locations, and total area of predicted habitat varied considerably, illustrating the effects of input data quality on habitat predictions and resulting potential impacts on conservation planning. Habitat models based on aggregated and conflated data were more accurate and had higher model sensitivity than original vegetation/land-cover, but this accuracy came at the cost of reduced geographic extent of predicted habitat. Using the highest performing models, we assessed cuckoo habitat preference and distribution in Arizona and found that major watersheds containing high-probably habitat are fragmented by a wide swath of low-probability habitat. Focus on riparian restoration in these areas could provide more breeding habitat for the threatened cuckoo, offset potential future habitat losses in adjacent watershed, and increase regional connectivity for other threatened vertebrates that also use riparian corridors.","language":"English","publisher":"Elsevier","doi":"10.1016/j.apgeog.2013.12.003","usgsCitation":"Villarreal, M., van Riper, C., and Petrakis, R., 2013, Conflation and aggregation of spatial data improve predictive models for species with limited habitats: a case of the threatened yellow-billed cuckoo in Arizona, USA: Applied Geography, v. 47, p. 57-69, https://doi.org/10.1016/j.apgeog.2013.12.003.","productDescription":"13 p.","startPage":"57","endPage":"69","numberOfPages":"13","ipdsId":"IP-048880","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":280568,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":280567,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.apgeog.2013.12.003"}],"country":"United States","state":"Arizona","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -114.8184,31.3322 ], [ -114.8184,37.0043 ], [ -109.0452,37.0043 ], [ -109.0452,31.3322 ], [ -114.8184,31.3322 ] ] ] } } ] }","volume":"47","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52c29607e4b040b25da903da","contributors":{"authors":[{"text":"Villarreal, Miguel L.","contributorId":107012,"corporation":false,"usgs":true,"family":"Villarreal","given":"Miguel L.","affiliations":[],"preferred":false,"id":487828,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"van Riper, Charles III 0000-0003-1084-5843 charles_van_riper@usgs.gov","orcid":"https://orcid.org/0000-0003-1084-5843","contributorId":169488,"corporation":false,"usgs":true,"family":"van Riper","given":"Charles","suffix":"III","email":"charles_van_riper@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":false,"id":487826,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Petrakis, Roy E.","contributorId":46868,"corporation":false,"usgs":true,"family":"Petrakis","given":"Roy E.","affiliations":[],"preferred":false,"id":487827,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70056564,"text":"sir20105070G - 2013 - Descriptive and geoenvironmental model for Co-Cu-Au deposits in metasedimentary rocks","interactions":[],"lastModifiedDate":"2022-12-12T23:19:59.000786","indexId":"sir20105070G","displayToPublicDate":"2013-12-30T13:46:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2010-5070","chapter":"G","title":"Descriptive and geoenvironmental model for Co-Cu-Au deposits in metasedimentary rocks","docAbstract":"

Introduction

This report is a revised model for a specific type of cobalt-copper-gold (Co-Cu-Au) deposit that will be evaluated in the next U.S. Geological Survey (USGS) assessment of undiscovered mineral resources in the United States (see Ferrero and others, 2012). Emphasis is on providing an up-to-date deposit model that includes both geologic and geoenvironmental aspects. The new model presented here supersedes previous USGS models by Earhart (1986) and Evans and others (1995), which are based solely on deposits in the Blackbird mining district of central Idaho. This report is a broader synthesis of information on 19 Co-Cu-Au deposits occurring in predominantly metasedimentary successions worldwide (table 1–1) that generally share common geologic, mineralogical, and geochemical features; preliminary summary versions were presented in Slack and others (2010) and Slack and others (2011), which are superseded by this report. As defined herein, the individual Co-Cu-Au deposits are located more than 500 meters from similar deposits and contain 0.1 percent or more by weight of Co in ore or mineralized rock; some deposits included in the database lack reported average Co grades, but they contain high Co concentrations, at least locally. Most of the deposits also have high As contents, present in Co arsenide and sulfarsenide minerals. Type examples of the Co-Cu-Au deposits are those in the Blackbird district, Skuterud in Norway, and Kouvervarra and Juomasuo in Finland. Some deposits in the database have low grades for Cu (for example, NICO in Canada) or Au (for example, Lemmonlampi in Finland), but these deposits are included because their geological, mineralogical, and alteration features are similar to those of the type examples. Several deposits included in the model are partly hosted by metavolcanic or metaigneous rocks (including granite), but regionally these deposits are within metasedimentary successions; no deposits are wholly within granite or other plutonic igneous intrusions.

Despite having a lower average Co grade, the Mt. Cobalt deposit in Australia is included here because it has past Co production from higher-grade ore zones (Nisbet and others, 1983). The Black Pine deposit in the Idaho cobalt belt is included because it contains mineable Co- and Au-rich lenses within Cu-rich mineralized zones (Formation Metals, Inc., 2012). Six deposits that lack data for average Co grades are also included because each reportedly contains abundant Co (>0.1 weight percent Co), at least locally. Many of the deposits are noteworthy as possible resources of Ag, Bi, W, Ni, Y, REE, and (or) U. Detailed data on the deposits listed in table 1–1, including references, are available in appendix 1. Significantly, the grouping in this report of Co-Cu-Au deposits in metasedimentary rocks into a single model includes deposits that other workers have previously classified in different ways. For background information, a global overview of different types of Co deposits worldwide is given in Smith (2001).

Additional geologically and compositionally similar deposits are known, but have average Co grades less than 0.1 percent. Most of these deposits contain cobalt-rich pyrite and lack appreciable amounts of distinct Co sulfide and (or) sulfarsenide minerals. Such deposits are not discussed in detail in the following sections, but these deposits may be relevant to the descriptive and genetic models presented below. Examples include the Scadding Au-Co-Cu deposit in Ontario, Canada; the Vähäjoki Co-Cu-Au deposit in Finland; the Tuolugou Co-Au deposit in Qinghai Province, China; the Lala Co-Cu-UREE deposit in Sichuan Province, China; the Guelb Moghrein Cu-Au-Co deposit in Mauritania; and the Great Australia Co-Cu, Greenmount Cu-Au-Co, and Monakoff Cu-Au-Co-UAg deposits in Queensland, Australia. Detailed information on these deposits is presented in appendix 2.

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These included the highly contaminated (Stege Marsh) and relatively clean (China Camp) marshes in San Francisco Bay and two reference marshes in Tomales Bay. Toxicity potential of contaminants and benthic macroinvertebrate survey showed significant differences between contaminated and reference marshes. Sublethal responses (e.g., apoptotic DNA fragmentation, lipid accumulation, and glycogen depletion) in livers of longjaw mudsucker (Gillichthys mirabilis) and embryo abnormality in lined shore crab (Pachygrapsus crassipes) also clearly distinguished contaminated and reference marshes, while other responses (e.g., cytochrome P450, metallothionein) did not. This study demonstrates that additional chronic sublethal responses in resident species under field exposure conditions can be readily combined with sediment quality triads for an expanded multiple lines of evidence approach. This confirmatory step may be warranted in environments like salt marshes in which natural variables may affect interpretation of toxicity test data. 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Deerlodge Park, east entrance to Dinosaur National Monument, northwest Colorado, 2011","docAbstract":"The Yampa River in northwestern Colorado is the largest, relatively unregulated river system in the upper Colorado River Basin. Water from the Yampa River Basin continues to be sought for a number of municipal, industrial, and energy uses. It is anticipated that future water development within the Yampa River Basin above the amount of water development identified under the Upper Colorado River Endangered Fish Recovery Implementation Program and the Programmatic Biological Opinion may require additional analysis in order to understand the effects on habitat and river function. Water development in the Yampa River Basin could alter the streamflow regime and, consequently, could lead to changes in the transport and storage of sediment in the Yampa River at Deerlodge Park. These changes could affect the physical form of the reach and may impact aquatic and riparian habitat in and downstream from Deerlodge Park.\n\nThe U.S. Geological Survey, in cooperation with the Colorado Water Conservation Board, began a study in 2011 to characterize the current hydrodynamic and sediment-transport conditions for a 2-kilometer reach of the Yampa River in Deerlodge Park. Characterization of channel conditions in the Deerlodge Park reach was completed through topographic surveying, grain-size analysis of streambed sediment, and characterization of streamflow properties. This characterization provides (1) a basis for comparisons of current stream functions (channel geometry, sediment transport, and stream hydraulics) to future conditions and (2) a dataset that can be used to assess channel response to streamflow alteration scenarios indicated from computer modeling of streamflow and sediment-transport conditions.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3273","collaboration":"Prepared in cooperation with the Colorado Water Conservation Board","usgsCitation":"Williams, C.A., 2013, Characterization of hydrodynamic and sediment conditions in the lower Yampa River at Deerlodge Park, east entrance to Dinosaur National Monument, northwest Colorado, 2011: U.S. Geological Survey Scientific Investigations Map 3273, Map: 37.92 inches x 29.17 inches, https://doi.org/10.3133/sim3273.","productDescription":"Map: 37.92 inches x 29.17 inches","additionalOnlineFiles":"N","ipdsId":"IP-049562","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":280530,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3273/"},{"id":280546,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3273/pdf/sim3273.pdf"},{"id":280547,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sim3273.jpg"}],"projection":"2011 Universal Transverse Mercator, Zone 12 North","datum":"North American Datum of 1983","country":"United States","state":"Colorado","otherGeospatial":"Dinosaur National Monument","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -108.519001,40.441199 ], [ -108.519001,40.453087 ], [ -108.499947,40.453087 ], [ -108.499947,40.441199 ], [ -108.519001,40.441199 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52c29607e4b040b25da903d3","contributors":{"authors":[{"text":"Williams, Cory A. 0000-0003-1461-7848 cawillia@usgs.gov","orcid":"https://orcid.org/0000-0003-1461-7848","contributorId":689,"corporation":false,"usgs":true,"family":"Williams","given":"Cory","email":"cawillia@usgs.gov","middleInitial":"A.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":486588,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70058863,"text":"ofr20131295 - 2013 - Preliminary estimates of annual agricultural pesticide use for counties of the conterminous United States, 2010-11","interactions":[],"lastModifiedDate":"2013-12-30T08:25:24","indexId":"ofr20131295","displayToPublicDate":"2013-12-27T15:17:00","publicationYear":"2013","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":"2013-1295","subseriesTitle":"National Water-Quality Assessment Program","title":"Preliminary estimates of annual agricultural pesticide use for counties of the conterminous United States, 2010-11","docAbstract":"This report provides preliminary estimates of annual agricultural use of 374 pesticide compounds in counties of the conterminous United States in 2010 and 2011, compiled by means of methods described in Thelin and Stone (2013). U.S. Department of Agriculture (USDA) county-level data for harvested-crop acreage were used in conjunction with proprietary Crop Reporting District (CRD)-level pesticide-use data to estimate county-level pesticide use. Estimated pesticide use (EPest) values were calculated with both the EPest-high and EPest-low methods. The distinction between the EPest-high method and the EPest-low method is that there are more counties with estimated pesticide use for EPest-high compared to EPest-low, owing to differing assumptions about missing survey data (Thelin and Stone, 2013). Preliminary estimates in this report will be revised upon availability of updated crop acreages in the 2012 Agricultural Census, to be published by the USDA in 2014. In addition, estimates for 2008 and 2009 previously published by Stone (2013) will be updated subsequent to the 2012 Agricultural Census release. Estimates of annual agricultural pesticide use are provided as downloadable, tab-delimited files, which are organized by compound, year, state Federal Information Processing Standard (FIPS) code, county FIPS code, and kg (amount in kilograms).","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131295","usgsCitation":"Baker, N.T., and Stone, W.W., 2013, Preliminary estimates of annual agricultural pesticide use for counties of the conterminous United States, 2010-11: U.S. Geological Survey Open-File Report 2013-1295, Report: iii, 2 p.; Tables: 14 txt files, https://doi.org/10.3133/ofr20131295.","productDescription":"Report: iii, 2 p.; Tables: 14 txt files","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-052139","costCenters":[{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":280542,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131295.jpg"},{"id":280539,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1295/"},{"id":280540,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2013/1295/tables/of2013-1295_tables.zip"},{"id":280541,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1295/pdf/of2013-1295.pdf"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.8,24.5 ], [ -124.8,49.383333 ], [ -66.95,49.383333 ], [ -66.95,24.5 ], [ -124.8,24.5 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52bea162e4b052bfba83a2ed","contributors":{"authors":[{"text":"Baker, Nancy T. 0000-0002-7979-5744 ntbaker@usgs.gov","orcid":"https://orcid.org/0000-0002-7979-5744","contributorId":1955,"corporation":false,"usgs":true,"family":"Baker","given":"Nancy","email":"ntbaker@usgs.gov","middleInitial":"T.","affiliations":[{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"preferred":true,"id":487407,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stone, Wesley W. 0000-0003-0239-2063 wwstone@usgs.gov","orcid":"https://orcid.org/0000-0003-0239-2063","contributorId":1496,"corporation":false,"usgs":true,"family":"Stone","given":"Wesley","email":"wwstone@usgs.gov","middleInitial":"W.","affiliations":[{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true}],"preferred":true,"id":487406,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70059316,"text":"ofr20131301 - 2013 - Monitoring of adult Lost River and shortnose suckers in Clear Lake Reservoir, California, 2008–2010","interactions":[],"lastModifiedDate":"2016-05-04T15:42:46","indexId":"ofr20131301","displayToPublicDate":"2013-12-23T14:53:00","publicationYear":"2013","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":"2013-1301","title":"Monitoring of adult Lost River and shortnose suckers in Clear Lake Reservoir, California, 2008–2010","docAbstract":"

Executive Summary

\n

In collaboration with the Bureau of Reclamation, the U.S. Geological Survey began a consistent monitoring program for endangered Lost River suckers (Deltistes luxatus) and shortnose suckers (Chasmistes brevirostris) in Clear Lake Reservoir, California, in the fall of 2004. The program was intended to develop a more complete understanding of the Clear Lake Reservoir populations because they are important to the recovery efforts for these species. We report results from this ongoing program and include sampling efforts from fall 2008 to spring 2010. We summarize catches and passive integrated transponder (PIT) tagging efforts from trammel net sampling in fall 2008 and fall 2009, as well as detections of PIT-tagged suckers on remote antennas in the spawning tributary, Willow Creek, in spring 2009 and spring 2010.

\n

Trammel net sampling resulted in a relatively low catch of suckers in fall 2008 and a high catch of suckers in fall 2009. We attribute the high catch of suckers to low lake levels in 2009, which concentrated fish. As in previous years, shortnose suckers made up the vast majority of the sucker catch and recaptures of previously PIT-tagged suckers were relatively uncommon. Across the 2 years, we captured and tagged 389 new Lost River suckers and 2,874 new shortnose suckers. Since the program began, we have tagged a total of about 1,200 Lost River suckers and 5,900 shortnose suckers that can be detected on the remote antennas in Willow Creek. Detections of tagged suckers were low in both spring 2009 and spring 2010. The magnitude of the spawning migration was presumably small in both years because of low flows in Willow Creek; detections were similar to a previous low-flow year (spring 2007) and much lower than previous years with higher flows (spring 2006 and spring 2008).

\n

The size composition of fish captured in fall trammel net sampling over time suggests that the Lost River sucker population probably has decreased in abundance from what it was in the early 2000s. Shortnose suckers are smaller than Lost River suckers, and we are unable to infer any trend in abundance for shortnose suckers because it is impossible to separate recruitment of small fish from size selectivity of the trammel nets. Nonetheless, the substantial catch of small shortnose suckers in 2009, especially females, indicates that some new individuals recruited to the population.

\n

Problems with inferring status and population dynamics from size composition data can be overcome by a robust capture-recapture program that follows the histories of PIT-tagged individuals. Inferences from such a program are currently hindered by poor detection rates during spawning seasons with low flows in Willow Creek, which indicate that a key assumption of capture-recapture models is violated. We suggest that the most straightforward solution to this issue would be to collect detection data during the spawning season using remote PIT tag antennas in the strait between the west and east lobes of the lake.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131301","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Hewitt, D.A., and Hayes, B., 2013, Monitoring of adult Lost River and shortnose suckers in Clear Lake Reservoir, California, 2008–2010: U.S. Geological Survey Open-File Report 2013-1301, iv, 18 p., https://doi.org/10.3133/ofr20131301.","productDescription":"iv, 18 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-051993","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":280526,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131301.JPG"},{"id":280524,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1301/pdf/ofr2013-1301.pdf","text":"Report","size":"900 KB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":280525,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1301/"}],"country":"United States","state":"California, Oregon","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.3831,41.78000 ], [ -122.3831,42.7534 ], [ -120.9161,42.7534 ], [ -120.9161,41.78000 ], [ -122.3831,41.78000 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52b95be1e4b0a747b3e7e7a1","contributors":{"authors":[{"text":"Hewitt, David A. 0000-0002-5387-0275 dhewitt@usgs.gov","orcid":"https://orcid.org/0000-0002-5387-0275","contributorId":3767,"corporation":false,"usgs":false,"family":"Hewitt","given":"David","email":"dhewitt@usgs.gov","middleInitial":"A.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":487664,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hayes, Brian S. 0000-0001-8229-4070","orcid":"https://orcid.org/0000-0001-8229-4070","contributorId":37022,"corporation":false,"usgs":true,"family":"Hayes","given":"Brian S.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":false,"id":487665,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70058790,"text":"pp1803 - 2013 - Selenium in ecosystems within the mountaintop coal mining and valley-fill region of southern West Virginia-assessment and ecosystem-scale modeling","interactions":[],"lastModifiedDate":"2013-12-23T14:47:58","indexId":"pp1803","displayToPublicDate":"2013-12-23T14:28:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":331,"text":"Professional Paper","code":"PP","onlineIssn":"2330-7102","printIssn":"1044-9612","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1803","title":"Selenium in ecosystems within the mountaintop coal mining and valley-fill region of southern West Virginia-assessment and ecosystem-scale modeling","docAbstract":"Coal and associated waste rock are among environmental selenium (Se) sources that have the potential to affect reproduction in fish and aquatic birds. Ecosystems of southern West Virginia that are affected by drainage from mountaintop coal mines and valleys filled with waste rock in the Coal, Gauley, and Lower Guyandotte watersheds were assessed during 2010 and 2011. Sampling data from earlier studies in these watersheds (for example, Upper Mud River Reservoir) and other mining-affected watersheds also are included to assess additional hydrologic settings and food webs for comparison. Basin schematics give a comprehensive view of sampled species and Se concentration data specific to location and date. Food-web diagrams document the progression of Se trophic transfer across suspended particulate material, invertebrates, and fish for each site to serve as the basis for developing an ecosystem-scale model to predict Se exposure within the hydrologic conditions and food webs of southern West Virginia. This approach integrates a site-specific predator’s dietary exposure pathway into modeling to ensure an adequate link to Se toxicity and, thus, to species vulnerability.\n\nSite-specific fish abundance and richness data in streams documented various species of chub, shiner, dace, darters, bass, minnow, sunfish, sucker, catfish, and central stoneroller (Campostoma anomalum), mottled sculpin (Cottus bairdii), and least brook lamprey (Lampetra aepyptera). However, Se assessment species for streams, and hence, model species for streams, were limited to creek chub (Semotilus atromaculatus) and central stoneroller. Both of these species of fish are generally considered to have a high tolerance for environmental stress based on traditional comparative fish community assessment, with creek chub being present at all sites. Aquatic insects (mayfly, caddisfly, stonefly, dobsonfly, chironomid) were the main invertebrates sampled in streams. Collection of suspended particulate material acted as an integrator of organic-rich, fine-grained biomass present in streams.\n\nThe base-case food web modeled for streams was suspended particulate material to aquatic insect to creek chub, with comparative modeling of a direct particulate-to-stoneroller food web. Model species for a reservoir setting were based on an earlier study of bluegill sunfish (Lepomis macrochirus), green sunfish (Lepomis cyanellus), and largemouth bass (Micropterus salmoides). Several reservoir food webs were considered based on a variety of invertebrates (insect, snail, clam). For stream and reservoir settings, predicted Se concentrations in exposure scenarios showed a high degree of correlation (r2 = 0.91 for invertebrates and 0.75 for fish) with field observations of Se concentrations when modeling was initiated from suspended-particulate-material Se concentrations and model transfer parameters defined previously in the literature were used. These strong correlations validate the derived site-specific model and establish sufficient confidence that the predictions from the developed model can be quantitatively applied to the ecosystems in southern West Virginia.\n\nAn application of modeling used a metric describing the partitioning of Se between particulate material and dissolved phases (Kd) to allow determination of a dissolved Se concentration that would be necessary to attain a site-specific Se fish body burden. The operationally defined Kd quantifies the complex process of transformation at the base of a food web on a site-specific basis. The magnitude of this metric is known to vary with such factors as Se speciation, particulate-material type, and hydrology. This application (1) ties dissolved Se concentrations to fish tissue concentrations; (2) allows consideration of different choices for intervening site-specific exposure steps that set Se bioaccumulation, partitioning, and bioavailability; and (3) generates implications for management decisions that define protection through different regulatory pathways and guidelines. The range of model outcomes accounts for critical sources of variability and establishes whether site and food-web characterization were adequate to represent the dynamics of the system with certainty. This is especially true in terms of particulate-material phases at the base of the food web and utilization of Kd in different hydrologic settings. For streams, a range of field-derived Kdds were applied to food-web exposure scenarios within a framework of locational and hydrologic variables (area of stream basin; stream gradient and discharge) that may affect the magnitude of Kd. Overlaying even a coarse temporal scale that acknowledges variability in stream dissolved Se and Se speciation, such as through seasonal derivation of Kd, can substantially narrow model uncertainty.\n\nModeling that constrains the place and time of greatest ecosystem Se sensitivity within a specified food web gives insight into Se risk and identifies controlling management alternatives within a watershed or stream basin. If there is a range of hydrologic settings, specificity is needed to establish a hierarchy of in-stream and off-stream habitats for a watershed approach that takes into account Se-enriched water moving through different Kd and food web environments. If there is a range of predator vulnerabilities (measured as a combination of food-web Se biodynamics and response in Se toxicity tests) within the site-specific community of fish species to be protected, then choice of fish species is critical to protection because it determines the food web and, hence, the magnitude of biotransfer through which Se is modeled. Whether creek chub is representative of the vulnerability to Se of all fish species encountered within the study-site ecosystems will require additional species-specific data and analysis. A range of site-specific scenarios illustrated here set model outcomes, but the final quantitative evaluation of alternatives and their implications will be those generated through choices and guidance formulated by state and other agencies in their decisionmaking processes.\n\nProposed additions and refinements to the ecosystem-scale site-specific approach developed here include consideration of:\n\nmeasurement of temporally matched pairs of dissolved and suspended-particulate-material Se concentrations across a broader range of stream sites to expand the stream Kd database and to test the representativeness of a suspended-particulate-material sample within a stream;\ncharacterization of different phases of particulate material across seasons to better define the base of the food web and connect to invertebrate feeding;\nrefinement of model assumptions concerning dietary preferences and composition for fish to develop additional trophic transfer factors (TTFs) (for example, calculation of TTFinvertebrate composite for mixed diets);\nexpansion of modeling of fish species and their food webs to include Se-vulnerable species;\ntemporal characterization of a predator’s life cycle and habitat use as additional model layers to integrate with Se biodynamics in streams;\ninvestigation of the effect of stream gradient on Kd based on a finer scale than presented here in terms of such variables as residence time, watershed dilution, and physical habitat attributes (for example, amount of ponding versus run or riffle within a stream); and\nlinkage to discharge through use of stream gaging to record variability and enable model organization within water-year types and discharge seasons.\nInvestigating the presence and variability of prey and predator species in demographically open systems such as streams also is key to model outcomes given the overall environmental stressors (for example, general landscape change, food-web disruption, recolonization potential) imposed on the composition of biological communities in coal mining and valley-fill affected watersheds","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1803","usgsCitation":"Presser, T.S., 2013, Selenium in ecosystems within the mountaintop coal mining and valley-fill region of southern West Virginia-assessment and ecosystem-scale modeling: U.S. Geological Survey Professional Paper 1803, vi, 86 p., https://doi.org/10.3133/pp1803.","productDescription":"vi, 86 p.","numberOfPages":"96","additionalOnlineFiles":"N","ipdsId":"IP-051155","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":280523,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/pp1803.jpg"},{"id":280521,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/pp/1803/"},{"id":280522,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1803/pdf/pp1803.pdf"}],"country":"United States","state":"West Virginia","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -81.8207,37.4749 ], [ -81.8207,38.6340 ], [ -80.1453,38.6340 ], [ -80.1453,37.4749 ], [ -81.8207,37.4749 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52b95be2e4b0a747b3e7e7aa","contributors":{"authors":[{"text":"Presser, Theresa S. 0000-0001-5643-0147 tpresser@usgs.gov","orcid":"https://orcid.org/0000-0001-5643-0147","contributorId":2467,"corporation":false,"usgs":true,"family":"Presser","given":"Theresa","email":"tpresser@usgs.gov","middleInitial":"S.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":487377,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70059593,"text":"ofr20121024F - 2013 - Geologic framework for the national assessment of carbon dioxide storage resources: Arkoma Basin, Kansas Basins, and Midcontinent Rift Basin study areas","interactions":[{"subject":{"id":70059593,"text":"ofr20121024F - 2013 - Geologic framework for the national assessment of carbon dioxide storage resources: Arkoma Basin, Kansas Basins, and Midcontinent Rift Basin study areas","indexId":"ofr20121024F","publicationYear":"2013","noYear":false,"chapter":"F","title":"Geologic framework for the national assessment of carbon dioxide storage resources: Arkoma Basin, Kansas Basins, and Midcontinent Rift Basin study areas"},"predicate":"IS_PART_OF","object":{"id":70093199,"text":"ofr20121024 - 2012 - Geologic framework for the national assessment of carbon dioxide storage resources","indexId":"ofr20121024","publicationYear":"2012","noYear":false,"title":"Geologic framework for the national assessment of carbon dioxide storage resources"},"id":1}],"isPartOf":{"id":70093199,"text":"ofr20121024 - 2012 - Geologic framework for the national assessment of carbon dioxide storage resources","indexId":"ofr20121024","publicationYear":"2012","noYear":false,"title":"Geologic framework for the national assessment of carbon dioxide storage resources"},"lastModifiedDate":"2019-02-21T11:38:30","indexId":"ofr20121024F","displayToPublicDate":"2013-12-23T12:40:00","publicationYear":"2013","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":"2012-1024","chapter":"F","title":"Geologic framework for the national assessment of carbon dioxide storage resources: Arkoma Basin, Kansas Basins, and Midcontinent Rift Basin study areas","docAbstract":"

2007 Energy Independence and Security Act (Public Law 110–140) directs the U.S. Geological Survey (USGS) to conduct a national assessment of potential geologic storage resources for carbon dioxide (CO2). The methodology used by the USGS for the national CO2 assessment follows that of previous USGS work. This methodology is non-economic and intended to be used at regional to subbasinal scales. This report identifies and contains geologic descriptions of three storage assessment units (SAUs) in Upper Cambrian to Mississippian sedimentary rocks within the Arkoma Basin study area, and two SAUs in Upper Cambrian to Mississippian sedimentary rocks within the Kansas Basins study area. The Arkoma Basin and Kansas Basins are adjacent with very similar geologic units; although the Kansas Basins area is larger, the Arkoma Basin is more structurally complex. The report focuses on the characteristics, specified in the methodology, that influence the potential CO2 storage resource in the SAUs. Specific descriptions of the SAU boundaries as well as their sealing and reservoir units are included. Properties for each SAU, such as depth to top, gross thickness, porosity, permeability, groundwater quality, and structural reservoir traps, are usually provided to illustrate geologic factors critical to the assessment. Although assessment results are not contained in this report, the geologic information herein was employed, as specified in the USGS methodology, to calculate a probabilistic distribution of potential storage resources in each SAU. The Midcontinent Rift Basin study area was not assessed, because no suitable storage formations meeting our size, depth, reservoir quality, and regional seal guidelines were found. Figures in this report show study area boundaries along with the SAU boundaries and cell maps of well penetrations through sealing units into the top of the storage formations. The cell maps show the number of penetrating wells within one-square mile and are derived from interpretations of incompletely attributed well data and from a digital compilation that is known not to include all drilling. The USGS does not expect to know the location of all wells and cannot guarantee the amount of drilling through specific formations in any given cell shown on the cell maps.

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For more information, see Open File Report 2012-1024.","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52b95bc0e4b0a747b3e7e724","contributors":{"authors":[{"text":"Buursink, Marc L. 0000-0001-6491-386X mbuursink@usgs.gov","orcid":"https://orcid.org/0000-0001-6491-386X","contributorId":3362,"corporation":false,"usgs":true,"family":"Buursink","given":"Marc","email":"mbuursink@usgs.gov","middleInitial":"L.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":487705,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Craddock, William H. 0000-0002-4181-4735 wcraddock@usgs.gov","orcid":"https://orcid.org/0000-0002-4181-4735","contributorId":3411,"corporation":false,"usgs":true,"family":"Craddock","given":"William","email":"wcraddock@usgs.gov","middleInitial":"H.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":487706,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Blondes, Madalyn S. 0000-0003-0320-0107 mblondes@usgs.gov","orcid":"https://orcid.org/0000-0003-0320-0107","contributorId":3598,"corporation":false,"usgs":true,"family":"Blondes","given":"Madalyn S.","email":"mblondes@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":487707,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Freeman, Phillip A. 0000-0002-0863-7431","orcid":"https://orcid.org/0000-0002-0863-7431","contributorId":84661,"corporation":false,"usgs":true,"family":"Freeman","given":"Phillip","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":487711,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cahan, Steven M. 0000-0002-4776-3668 scahan@usgs.gov","orcid":"https://orcid.org/0000-0002-4776-3668","contributorId":4529,"corporation":false,"usgs":true,"family":"Cahan","given":"Steven","email":"scahan@usgs.gov","middleInitial":"M.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":487710,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"DeVera, Christina A. 0000-0002-4691-6108 cdevera@usgs.gov","orcid":"https://orcid.org/0000-0002-4691-6108","contributorId":3845,"corporation":false,"usgs":true,"family":"DeVera","given":"Christina","email":"cdevera@usgs.gov","middleInitial":"A.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":487708,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lohr, Celeste D. 0000-0001-6287-9047 clohr@usgs.gov","orcid":"https://orcid.org/0000-0001-6287-9047","contributorId":3866,"corporation":false,"usgs":true,"family":"Lohr","given":"Celeste D.","email":"clohr@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":487709,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70055710,"text":"sim3259 - 2013 - Base of the upper layer of the phase-three Elkhorn-Loup groundwater-flow model, north-central Nebraska","interactions":[],"lastModifiedDate":"2013-12-23T11:24:50","indexId":"sim3259","displayToPublicDate":"2013-12-23T11:01:00","publicationYear":"2013","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":"3259","title":"Base of the upper layer of the phase-three Elkhorn-Loup groundwater-flow model, north-central Nebraska","docAbstract":"The Elkhorn and Loup Rivers in Nebraska provide water for irrigation, recreation, hydropower produc­tion, aquatic life, and municipal water systems for the Omaha and Lincoln metropolitan areas. Groundwater is another important resource in the region and is extracted primarily for agricultural irrigation. Water managers of the area are interested in balancing and sustaining the long-term uses of these essential surface-water and groundwater resources. Thus, a cooperative study was established in 2006 to compile reliable data describing hydrogeologic properties and water-budget components and to improve the understanding of stream-aquifer interactions in the Elkhorn and Loup River Basins. A groundwater-flow model was constructed as part of the first two phases of that study as a tool for under­standing the effect of groundwater pumpage on stream base flow and the effects of management strategies on hydrologically connected groundwater and surface-water supplies. The third phase of the study was implemented to gain additional geologic knowledge and update the ELM with enhanced water-budget information and refined discretization of the model grid and stress periods. As part of that effort, the ELM is being reconstructed to include two vertical model layers, whereas phase-one and phase-two simulations represented the aquifer system using one vertical model layer. This report presents a map of and methods for developing the elevation of the base of the upper model layer for the phase-three ELM. Digital geospatial data of elevation contours and geologic log sites used to esti­mate elevation contours are available as part of this report.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3259","collaboration":"Prepared in cooperation with the Lower Elkhorn, Lower Loup, Lower Platte North, Middle Niobrara, and Upper Elkhorn Natural Resources Districts","usgsCitation":"Stanton, J.S., 2013, Base of the upper layer of the phase-three Elkhorn-Loup groundwater-flow model, north-central Nebraska: U.S. Geological Survey Scientific Investigations Map 3259, Map: 49 inches x 39 inches; Associated Metadata and GIS files, https://doi.org/10.3133/sim3259.","productDescription":"Map: 49 inches x 39 inches; Associated Metadata and GIS files","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-043054","costCenters":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"links":[{"id":280507,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sim3259.gif"},{"id":280504,"type":{"id":16,"text":"Metadata"},"url":"https://water.usgs.gov/GIS/metadata/usgswrd/XML/sim2013-3259_sites.xml"},{"id":280503,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3259/pdf/sim3259.pdf"},{"id":280505,"type":{"id":16,"text":"Metadata"},"url":"https://water.usgs.gov/GIS/metadata/usgswrd/XML/sim2013-3259_contours.xml"},{"id":280506,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3259/"}],"country":"United States","state":"Nebraska","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -102.4640,40.5000 ], [ -102.4640,43.0000 ], [ -97.2839,43.0000 ], [ -97.2839,40.5000 ], [ -102.4640,40.5000 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52b95b5fe4b0a747b3e7e599","contributors":{"authors":[{"text":"Stanton, Jennifer S. 0000-0002-2520-753X jstanton@usgs.gov","orcid":"https://orcid.org/0000-0002-2520-753X","contributorId":830,"corporation":false,"usgs":true,"family":"Stanton","given":"Jennifer","email":"jstanton@usgs.gov","middleInitial":"S.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"preferred":true,"id":486231,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ]}