{"pageNumber":"1376","pageRowStart":"34375","pageSize":"25","recordCount":184743,"records":[{"id":70106988,"text":"sir20145098 - 2014 - Completion summary for boreholes USGS 140 and USGS 141 near the Advanced Test Reactor Complex, Idaho National Laboratory, Idaho","interactions":[],"lastModifiedDate":"2014-06-10T15:30:36","indexId":"sir20145098","displayToPublicDate":"2014-06-10T15:16:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-5098","title":"Completion summary for boreholes USGS 140 and USGS 141 near the Advanced Test Reactor Complex, Idaho National Laboratory, Idaho","docAbstract":"<p>In 2013, the U.S. Geological Survey, in cooperation with the U.S. Department of Energy, drilled and constructed boreholes USGS 140 and USGS 141 for stratigraphic framework analyses and long-term groundwater monitoring of the eastern Snake River Plain aquifer at the Idaho National Laboratory in southeast Idaho. Borehole USGS 140 initially was cored to collect continuous geologic data, and then re-drilled to complete construction as a monitor well. Borehole USGS 141 was drilled and constructed as a monitor well without coring. Boreholes USGS 140 and USGS 141 are separated by about 375 feet (ft) and have similar geologic layers and hydrologic characteristics based on geophysical and aquifer test data collected. The final construction for boreholes USGS 140 and USGS 141 required 6-inch (in.) diameter carbon-steel well casing and 5-in. diameter stainless-steel well screen; the screened monitoring interval was completed about 50 ft into the eastern Snake River Plain aquifer, between 496 and 546 ft below land surface (BLS) at both sites. Following construction and data collection, dedicated pumps and water-level access lines were placed to allow for aquifer testing, for collecting periodic water samples, and for measuring water levels.</p>\n<br/>\n<p>Borehole USGS 140 was cored continuously, starting from land surface to a depth of 543 ft BLS. Excluding surface sediment, recovery of basalt and sediment core at borehole USGS 140 was about 98 and 65 percent, respectively. Based on visual inspection of core and geophysical data, about 32 basalt flows and 4 sediment layers were collected from borehole USGS 140 between 34 and 543 ft BLS. Basalt texture for borehole USGS 140 generally was described as aphanitic, phaneritic, and porphyritic; rubble zones and flow mold structure also were described in recovered core material. Sediment layers, starting near 163 ft BLS, generally were composed of fine-grained sand and silt with a lesser amount of clay; however, between 223 and 228 ft BLS, silt with gravel was described. Basalt flows generally ranged in thickness from 3 to 76 ft (average of 14 ft) and varied from highly fractured to dense with high to low vesiculation.</p>\n<br/>\n<p>Geophysical and borehole video logs were collected during certain stages of the drilling and construction process at boreholes USGS 140 and USGS 141. Geophysical logs were examined synergistically with the core material for borehole USGS 140; additionally, geophysical data were examined to confirm geologic and hydrologic similarities between boreholes USGS 140 and USGS 141 because core was not collected for borehole USGS 141. Geophysical data suggest the occurrence of fractured and (or) vesiculated basalt, dense basalt, and sediment layering in both the saturated and unsaturated zones in borehole USGS 141. Omni-directional density measurements were used to assess the completeness of the grout annular seal behind 6-in. diameter well casing. Furthermore, gyroscopic deviation measurements were used to measure horizontal and vertical displacement at all depths in boreholes USGS 140 and USGS 141.</p>\n<br/>\n<p>Single-well aquifer tests were done following construction at wells USGS 140 and USGS 141 and data examined after the tests were used to provide estimates of specific-capacity, transmissivity, and hydraulic conductivity. The specific capacity, transmissivity, and hydraulic conductivity for well USGS 140 were estimated at 2,370 gallons per minute per foot [(gal/min)/ft)], 4.06 × 105 feet squared per day (ft<sup>2</sup>/d), and 740 feet per day (ft/d), respectively. The specific capacity, transmissivity, and hydraulic conductivity for well USGS 141 were estimated at 470 (gal/min)/ft, 5.95 × 104 ft<sup>2</sup>/d, and 110 ft/d, respectively. Measured flow rates remained relatively constant in well USGS 140 with averages of 23.9 and 23.7 gal/min during the first and second aquifer tests, respectively, and in well USGS 141 with an average of 23.4 gal/min.</p>\n<br/>\n<p>Water samples were analyzed for cations, anions, metals, nutrients, volatile organic compounds, stable isotopes, and radionuclides. Water samples from both wells indicated that concentrations of tritium, sulfate, and chromium were affected by wastewater disposal practices at the Advanced Test Reactor Complex. Most constituents in water from wells USGS 140 and USGS 141 had concentrations similar to concentrations in well USGS 136, which is upgradient from wells USGS 140 and USGS 141.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145098","collaboration":"DOE/ID-22229. Prepared in cooperation with the U.S. Department of Energy","usgsCitation":"Twining, B.V., Bartholomay, R.C., and Hodges, M., 2014, Completion summary for boreholes USGS 140 and USGS 141 near the Advanced Test Reactor Complex, Idaho National Laboratory, Idaho: U.S. Geological Survey Scientific Investigations Report 2014-5098, Report: vii, 39 p.; Appendixes A-C, https://doi.org/10.3133/sir20145098.","productDescription":"Report: vii, 39 p.; Appendixes A-C","numberOfPages":"52","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-051163","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":288220,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145098.jpg"},{"id":288216,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5098/pdf/sir20145098.pdf"},{"id":288217,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5098/pdf/sir20145098_AppendixA.pdf"},{"id":288218,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5098/pdf/sir20145098_AppendixB.pdf"},{"id":288219,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5098/pdf/sir20145098_AppendixC.pdf"},{"id":288215,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5098/"}],"projection":"Universal Transverse Mercator projection, Zone 12","datum":"North American Datum of 1927","country":"United States","state":"Idaho","otherGeospatial":"Snake River Plain","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -113.4019,43.2995 ], [ -113.4019,44.0971 ], [ -112.347,44.0971 ], [ -112.347,43.2995 ], [ -113.4019,43.2995 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53981ad0e4b09e5ae91f9d96","contributors":{"authors":[{"text":"Twining, Brian V. 0000-0003-1321-4721 btwining@usgs.gov","orcid":"https://orcid.org/0000-0003-1321-4721","contributorId":2387,"corporation":false,"usgs":true,"family":"Twining","given":"Brian","email":"btwining@usgs.gov","middleInitial":"V.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":493830,"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":493829,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hodges, Mary K.V.","contributorId":66848,"corporation":false,"usgs":true,"family":"Hodges","given":"Mary K.V.","affiliations":[],"preferred":false,"id":493831,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70110751,"text":"ofr20141107 - 2014 - National Land Imaging Requirements (NLIR) Pilot Project summary report: Summary of moderate resolution imaging user requirements","interactions":[],"lastModifiedDate":"2020-06-05T12:08:01.026438","indexId":"ofr20141107","displayToPublicDate":"2014-06-10T14:58:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-1107","title":"National Land Imaging Requirements (NLIR) Pilot Project summary report: Summary of moderate resolution imaging user requirements","docAbstract":"<p>Under the National Land Imaging Requirements (NLIR) Project, the U.S. Geological Survey (USGS) is developing a functional capability to obtain, characterize, manage, maintain and prioritize all Earth observing (EO) land remote sensing user requirements. The goal is a better understanding of community needs that can be supported with land remote sensing resources, and a means to match needs with appropriate solutions in an effective and efficient way.</p><p>The NLIR Project is composed of two components. The first component is focused on the development of the Earth Observation Requirements Evaluation System (EORES) to capture, store and analyze user requirements, whereas, the second component is the mechanism and processes to elicit and document the user requirements that will populate the EORES.</p><p>To develop the second component, the requirements elicitation methodology was exercised and refined through a pilot project conducted from June to September 2013. The pilot project focused specifically on applications and user requirements for moderate resolution imagery (5–120 meter resolution) as the test case for requirements development.</p><p>The purpose of this summary report is to provide a high-level overview of the requirements elicitation process that was exercised through the pilot project and an early analysis of the moderate resolution imaging user requirements acquired to date to support ongoing USGS sustainable land imaging study needs.</p><p>The pilot project engaged a limited set of Federal Government users from the operational and research communities and therefore the information captured represents only a subset of all land imaging user requirements. However, based on a comparison of results, trends, and analysis, the pilot captured a strong baseline of typical applications areas and user needs for moderate resolution imagery.</p><p>Because these results are preliminary and represent only a sample of users and application areas, the information from this report should only be used to indicate general user needs for the applications covered. Users of the information are cautioned that use of specific numeric results may be inappropriate without additional research. Any information used or cited from this report should specifically be cited as preliminary findings.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141107","usgsCitation":"Vadnais, C., and Stensaas, G.L., 2014, National Land Imaging Requirements (NLIR) Pilot Project summary report: Summary of moderate resolution imaging user requirements: U.S. Geological Survey Open-File Report 2014-1107, vi, 46 p., https://doi.org/10.3133/ofr20141107.","productDescription":"vi, 46 p.","numberOfPages":"52","onlineOnly":"Y","ipdsId":"IP-054641","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":288212,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1107/","linkFileType":{"id":5,"text":"html"}},{"id":288213,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1107/pdf/ofr2014-1107.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":375352,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2014/1107/images/coverthb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53981ad5e4b09e5ae91f9dae","contributors":{"authors":[{"text":"Vadnais, Carolyn","contributorId":21069,"corporation":false,"usgs":true,"family":"Vadnais","given":"Carolyn","affiliations":[],"preferred":false,"id":494140,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stensaas, Gregory L. 0000-0001-6679-2416 stensaas@usgs.gov","orcid":"https://orcid.org/0000-0001-6679-2416","contributorId":2551,"corporation":false,"usgs":true,"family":"Stensaas","given":"Gregory","email":"stensaas@usgs.gov","middleInitial":"L.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":494141,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70115106,"text":"70115106 - 2014 - Chesapeake Bay hypoxic volume forecasts and results: June 10, 2014","interactions":[],"lastModifiedDate":"2023-02-13T18:33:59.403058","indexId":"70115106","displayToPublicDate":"2014-06-10T13:14:01","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":3,"text":"Organization Series"},"title":"Chesapeake Bay hypoxic volume forecasts and results: June 10, 2014","docAbstract":"<p>The 2014 Forecast - Given the average Jan-May 2014 total nitrogen load of 200,165 kg/day, this summer’s hypoxia volume forecast is 8.2 km<sup>3</sup>, slightly larger than average size for the period of record and the observed size last year.</p>","language":"English","publisher":"University of Michigan","publisherLocation":"Ann Arbor, MI","usgsCitation":"Scavia, D., and Evans, M.A., 2014, Chesapeake Bay hypoxic volume forecasts and results: June 10, 2014, 7 p.","productDescription":"7 p.","numberOfPages":"7","ipdsId":"IP-057486","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":289432,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Chesapeake Bay","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -76.4633,36.9078 ], [ -76.4633,37.9656 ], [ -75.6353,37.9656 ], [ -75.6353,36.9078 ], [ -76.4633,36.9078 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53b67b6ce4b014fc094d545e","contributors":{"authors":[{"text":"Scavia, Donald","contributorId":19068,"corporation":false,"usgs":true,"family":"Scavia","given":"Donald","affiliations":[],"preferred":false,"id":495546,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Evans, Mary Anne 0000-0002-1627-7210 maevans@usgs.gov","orcid":"https://orcid.org/0000-0002-1627-7210","contributorId":4883,"corporation":false,"usgs":true,"family":"Evans","given":"Mary","email":"maevans@usgs.gov","middleInitial":"Anne","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":495545,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70111271,"text":"sir20145075 - 2014 - Land subsidence, groundwater levels, and geology in the Coachella Valley, California, 1993-2010","interactions":[],"lastModifiedDate":"2014-06-10T11:17:22","indexId":"sir20145075","displayToPublicDate":"2014-06-10T11:02:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-5075","title":"Land subsidence, groundwater levels, and geology in the Coachella Valley, California, 1993-2010","docAbstract":"<p>Land subsidence associated with groundwater-level declines has been investigated by the U.S. Geological Survey in the Coachella Valley, California, since 1996. Groundwater has been a major source of agricultural, municipal, and domestic supply in the valley since the early 1920s. Pumping of groundwater resulted in water-level declines as much as 15 meters (50 feet) through the late 1940s. In 1949, the importation of Colorado River water to the southern Coachella Valley began, resulting in a reduction in groundwater pumping and a recovery of water levels during the 1950s through the 1970s. Since the late 1970s, demand for water in the valley has exceeded deliveries of imported surface water, resulting in increased pumping and associated groundwater-level declines and, consequently, an increase in the potential for land subsidence caused by aquifer-system compaction.</p>\n<br/>\n<p>Global Positioning System (GPS) surveying and Interferometric Synthetic Aperture Radar (InSAR) methods were used to determine the location, extent, and magnitude of the vertical land-surface changes in the southern Coachella Valley during 1993–2010. The GPS measurements taken at 11 geodetic monuments in 1996 and in 2010 in the southern Coachella Valley indicated that the elevation of the land surface changed –136 to –23 millimeters (mm) ±54 mm (–0.45 to –0.08 feet (ft) ±0.18 ft) during the 14-year period. Changes at 6 of the 11 monuments exceeded the maximum expected uncertainty of ±54 mm (±0.18 ft) at the 95-percent confidence level, indicating that subsidence occurred at these monuments between June 1996 and August 2010. GPS measurements taken at 17 geodetic monuments in 2005 and 2010 indicated that the elevation of the land surface changed –256 to +16 mm ±28 mm (–0.84 to +0.05 ft ±0.09 ft) during the 5-year period. Changes at 5 of the 17 monuments exceeded the maximum expected uncertainty of ±28 mm (±0.09 ft) at the 95-percent confidence level, indicating that subsidence occurred at these monuments between August 2005 and August 2010. At each of these five monuments, subsidence rates were about the same between 2005 and 2010 as between 2000 and 2005.</p>\n<br/>\n<p>InSAR measurements taken between June 27, 1995, and September 19, 2010, indicated that the land surface subsided from about 220 to 600 mm (0.72 to 1.97 ft) in three areas of the Coachella Valley: near Palm Desert, Indian Wells, and La Quinta. In Palm Desert, the average subsidence rates increased from about 39 millimeters per year (mm/yr), or 0.13 foot per year (ft/yr), during 1995–2000 to about 45 mm/yr (0.15 ft/yr) during 2003–10. In Indian Wells, average subsidence rates for two subsidence maxima were fairly steady at about 34 and 26 mm/yr (0.11 and 0.09 ft/yr) during both periods; for the third maxima, average subsidence rates increased from about 14 to 19 mm/yr (0.05 to 0.06 ft/yr) from the first to the second period. In La Quinta, average subsidence rates for five selected locations ranged from about 17 to 37 mm/yr (0.06 to 0.12 ft/yr) during 1995–2000; three of the locations had similar rates during 2003–mid-2009, while the other two locations had increased subsidence rates. Decreased subsidence rates were calculated throughout the La Quinta subsidence area during mid-2009–10, however, and uplift was observed during 2010 near the southern extent of this area.</p>\n<br/>\n<p>Water-level measurements taken at wells near the subsiding monuments and in the three subsiding areas shown by InSAR generally indicated that the water levels fluctuated seasonally and declined annually from the early 1990s, or earlier, to 2010; some water levels in 2010 were at the lowest levels in their recorded histories. An exception to annually declining water levels in and near subsiding areas was observed beginning in mid-2009 in the La Quinta subsidence area, where recovering water levels coincided with increased recharge operations at the Thomas E. Levy Recharge Facility; decreased pumpage also could cause groundwater levels to recover. Subsidence concomitant with declining water levels and land-surface uplift concomitant with recovering water levels indicate that aquifer-system compaction could be causing subsidence. If the stresses imposed by the historically lowest water levels exceeded the preconsolidation stress, the aquifer-system compaction and associated land subsidence could be permanent.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145075","collaboration":"Prepared in cooperation with the Coachella Valley Water District","usgsCitation":"Sneed, M., Brandt, J.T., and Solt, M., 2014, Land subsidence, groundwater levels, and geology in the Coachella Valley, California, 1993-2010: U.S. Geological Survey Scientific Investigations Report 2014-5075, viii, 62 p., https://doi.org/10.3133/sir20145075.","productDescription":"viii, 62 p.","numberOfPages":"75","onlineOnly":"Y","ipdsId":"IP-043650","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":288211,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145075.jpg"},{"id":288210,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5075/pdf/sir2014-5075.pdf"},{"id":288209,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5075"}],"datum":"North American Datum 1927","country":"United States","state":"California","otherGeospatial":"Coachella Valley","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -117.2406,32.9971 ], [ -117.2406,34.1959 ], [ -115.4443,34.1959 ], [ -115.4443,32.9971 ], [ -117.2406,32.9971 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53981ad2e4b09e5ae91f9d9e","contributors":{"authors":[{"text":"Sneed, Michelle 0000-0002-8180-382X micsneed@usgs.gov","orcid":"https://orcid.org/0000-0002-8180-382X","contributorId":155,"corporation":false,"usgs":true,"family":"Sneed","given":"Michelle","email":"micsneed@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":494317,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brandt, Justin T. 0000-0002-9397-6824","orcid":"https://orcid.org/0000-0002-9397-6824","contributorId":28326,"corporation":false,"usgs":true,"family":"Brandt","given":"Justin","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":494318,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Solt, Mike","contributorId":88258,"corporation":false,"usgs":true,"family":"Solt","given":"Mike","email":"","affiliations":[],"preferred":false,"id":494319,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70111960,"text":"70111960 - 2014 - Reducing fatigue damage for ships in transit through structured decision making","interactions":[],"lastModifiedDate":"2014-06-10T10:43:53","indexId":"70111960","displayToPublicDate":"2014-06-10T10:32:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2677,"text":"Marine Structures","active":true,"publicationSubtype":{"id":10}},"title":"Reducing fatigue damage for ships in transit through structured decision making","docAbstract":"Research in structural monitoring has focused primarily on drawing inference about the health of a structure from the structure’s response to ambient or applied excitation. Knowledge of the current state can then be used to predict structural integrity at a future time and, in principle, allows one to take action to improve safety, minimize ownership costs, and/or increase the operating envelope. While much time and effort has been devoted toward data collection and system identification, research to-date has largely avoided the question of how to choose an optimal maintenance plan. This work describes a structured decision making (SDM) process for taking available information (loading data, model output, etc.) and producing a plan of action for maintaining the structure. SDM allows the practitioner to specify his/her objectives and then solves for the decision that is optimal in the sense that it maximizes those objectives. To demonstrate, we consider the problem of a Naval vessel transiting a fixed distance in varying sea-state conditions. The physics of this problem are such that minimizing transit time increases the probability of fatigue failure in the structural supports. It is shown how SDM produces the optimal trip plan in the sense that it minimizes both transit time and probability of failure in the manner of our choosing (i.e., through a user-defined cost function). The example illustrates the benefit of SDM over heuristic approaches to maintaining the vessel.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Marine Structures","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.marstruc.2014.04.002","usgsCitation":"Nichols, J., Fackler, P., Pacifici, K., Murphy, K., and Nichols, J., 2014, Reducing fatigue damage for ships in transit through structured decision making: Marine Structures, v. 38, p. 18-43, https://doi.org/10.1016/j.marstruc.2014.04.002.","productDescription":"26 p.","startPage":"18","endPage":"43","numberOfPages":"26","ipdsId":"IP-054791","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":288208,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":288207,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.marstruc.2014.04.002"}],"volume":"38","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53981ad5e4b09e5ae91f9db6","contributors":{"authors":[{"text":"Nichols, J.M.","contributorId":18080,"corporation":false,"usgs":true,"family":"Nichols","given":"J.M.","email":"","affiliations":[],"preferred":false,"id":494550,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fackler, P.L.","contributorId":30859,"corporation":false,"usgs":true,"family":"Fackler","given":"P.L.","email":"","affiliations":[],"preferred":false,"id":494551,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pacifici, K.","contributorId":71667,"corporation":false,"usgs":true,"family":"Pacifici","given":"K.","email":"","affiliations":[],"preferred":false,"id":494553,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Murphy, K.D.","contributorId":50004,"corporation":false,"usgs":true,"family":"Murphy","given":"K.D.","email":"","affiliations":[],"preferred":false,"id":494552,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nichols, J.D. 0000-0002-7631-2890","orcid":"https://orcid.org/0000-0002-7631-2890","contributorId":14332,"corporation":false,"usgs":true,"family":"Nichols","given":"J.D.","affiliations":[],"preferred":false,"id":494549,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70111909,"text":"70111909 - 2014 - Pluvial lakes in the Great Basin of the western United States: a view from the outcrop","interactions":[],"lastModifiedDate":"2014-06-10T10:01:04","indexId":"70111909","displayToPublicDate":"2014-06-10T09:53:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3219,"text":"Quaternary Science Reviews","active":true,"publicationSubtype":{"id":10}},"title":"Pluvial lakes in the Great Basin of the western United States: a view from the outcrop","docAbstract":"<p>Paleo-lakes in the western United States provide geomorphic and hydrologic records of climate and drainage-basin change at multiple time scales extending back to the Miocene. Recent reviews and studies of paleo-lake records have focused on interpretations of proxies in lake sediment cores from the northern and central parts of the Great Basin. In this review, emphasis is placed on equally important studies of lake history during the past ∼30 years that were derived from outcrop exposures and geomorphology, in some cases combined with cores. Outcrop and core records have different strengths and weaknesses that must be recognized and exploited in the interpretation of paleohydrology and paleoclimate. Outcrops and landforms can yield direct evidence of lake level, facies changes that record details of lake-level fluctuations, and geologic events such as catastrophic floods, drainage-basin changes, and isostatic rebound. Cores can potentially yield continuous records when sampled in stable parts of lake basins and can provide proxies for changes in lake level, water temperature and chemistry, and ecological conditions in the surrounding landscape. However, proxies such as stable isotopes may be influenced by several competing factors the relative effects of which may be difficult to assess, and interpretations may be confounded by geologic events within the drainage basin that were unrecorded or not recognized in a core. The best evidence for documenting absolute lake-level changes lies within the shore, nearshore, and deltaic sediments that were deposited across piedmonts and at the mouths of streams as lake level rose and fell. We review the different shorezone environments and resulting deposits used in such reconstructions and discuss potential estimation errors.</p>\n<br/>\n<p>Lake-level studies based on deposits and landforms have provided paleohydrologic records ranging from general changes during the past million years to centennial-scale details of fluctuations during the late Pleistocene and Holocene. Outcrop studies have documented the integration histories of several important drainage basins, including the Humboldt, Amargosa, Owens, and Mojave river systems, that have evolved since the Miocene within the active tectonic setting of the Great Basin; these histories have influenced lake levels in terminal basins. Many pre-late Pleistocene lakes in the western Great Basin were significantly larger and record wetter conditions than the youngest lakes. Outcrop-based lake-level data provide important checks on core-based proxy interpretations; we discuss four such comparisons. In some cases, such as for Lakes Owens and Manix, outcrop and core data synthesis yields stronger and more complete records; in other cases, such as for Bonneville and Lahontan, conflicts point toward reconsideration of confounding factors in interpretation of core-based proxies.</p>","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Quaternary Science Reviews","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.quascirev.2014.04.012","usgsCitation":"Reheis, M., Adams, K., Oviatt, C., and Bacon, S.N., 2014, Pluvial lakes in the Great Basin of the western United States: a view from the outcrop: Quaternary Science Reviews, v. 97, p. 33-57, https://doi.org/10.1016/j.quascirev.2014.04.012.","productDescription":"25 p.","startPage":"33","endPage":"57","numberOfPages":"25","ipdsId":"IP-044438","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":288206,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":288205,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.quascirev.2014.04.012"}],"country":"United States","otherGeospatial":"Great Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -121.38,32.36 ], [ -121.38,44.81 ], [ -110.35,44.81 ], [ -110.35,32.36 ], [ -121.38,32.36 ] ] ] } } ] }","volume":"97","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53981ad5e4b09e5ae91f9db2","contributors":{"authors":[{"text":"Reheis, Marith C. 0000-0002-8359-323X","orcid":"https://orcid.org/0000-0002-8359-323X","contributorId":101244,"corporation":false,"usgs":true,"family":"Reheis","given":"Marith C.","affiliations":[],"preferred":false,"id":494540,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Adams, Kenneth D.","contributorId":75586,"corporation":false,"usgs":true,"family":"Adams","given":"Kenneth D.","affiliations":[],"preferred":false,"id":494538,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Oviatt, Charles G.","contributorId":13503,"corporation":false,"usgs":true,"family":"Oviatt","given":"Charles G.","affiliations":[],"preferred":false,"id":494537,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bacon, Steven N.","contributorId":93391,"corporation":false,"usgs":true,"family":"Bacon","given":"Steven","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":494539,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70111934,"text":"70111934 - 2014 - Modeling Hawaiian ecosystem degradation due to invasive plants under current and future climates","interactions":[],"lastModifiedDate":"2014-06-10T09:37:24","indexId":"70111934","displayToPublicDate":"2014-06-10T09:14:00","publicationYear":"2014","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":"Modeling Hawaiian ecosystem degradation due to invasive plants under current and future climates","docAbstract":"Occupation of native ecosystems by invasive plant species alters their structure and/or function. In Hawaii, a subset of introduced plants is regarded as extremely harmful due to competitive ability, ecosystem modification, and biogeochemical habitat degradation. By controlling this subset of highly invasive ecosystem modifiers, conservation managers could significantly reduce native ecosystem degradation. To assess the invasibility of vulnerable native ecosystems, we selected a proxy subset of these invasive plants and developed robust ensemble species distribution models to define their respective potential distributions. The combinations of all species models using both binary and continuous habitat suitability projections resulted in estimates of species richness and diversity that were subsequently used to define an invasibility metric. The invasibility metric was defined from species distribution models with <0.7 niche overlap (Warrens I) and relatively discriminative distributions (Area Under the Curve >0.8; True Skill Statistic >0.75) as evaluated per species. Invasibility was further projected onto a 2100 Hawaii regional climate change scenario to assess the change in potential habitat degradation. The distribution defined by the invasibility metric delineates areas of known and potential invasibility under current climate conditions and, when projected into the future, estimates potential reductions in native ecosystem extent due to climate-driven invasive incursion. We have provided the code used to develop these metrics to facilitate their wider use (Code S1). This work will help determine the vulnerability of native-dominated ecosystems to the combined threats of climate change and invasive species, and thus help prioritize ecosystem and species management actions.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"PLoS ONE","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Public Library of Science","publisherLocation":"San Francisco, CA","doi":"10.1371/journal.pone.0095427","usgsCitation":"Vorsino, A.E., Fortini, L., Amidon, F.A., Miller, S.E., Jacobi, J.D., Price, J.P., `Ohukani`ohi`a Gon, S., and Koob, G.A., 2014, Modeling Hawaiian ecosystem degradation due to invasive plants under current and future climates: PLoS ONE, v. 9, no. 5, 18 p., https://doi.org/10.1371/journal.pone.0095427.","productDescription":"18 p.","numberOfPages":"18","ipdsId":"IP-054741","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":472944,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0095427","text":"Publisher Index Page"},{"id":288204,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":288198,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1371/journal.pone.0095427"}],"country":"United States","state":"Hawai'i","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -159.9917,18.7288 ], [ -159.9917,22.4876 ], [ -154.4937,22.4876 ], [ -154.4937,18.7288 ], [ -159.9917,18.7288 ] ] ] } } ] }","volume":"9","issue":"5","noUsgsAuthors":false,"publicationDate":"2014-05-07","publicationStatus":"PW","scienceBaseUri":"53981ad4e4b09e5ae91f9daa","contributors":{"authors":[{"text":"Vorsino, Adam E.","contributorId":71102,"corporation":false,"usgs":true,"family":"Vorsino","given":"Adam","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":494547,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fortini, Lucas B.","contributorId":10693,"corporation":false,"usgs":true,"family":"Fortini","given":"Lucas B.","affiliations":[],"preferred":false,"id":494543,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Amidon, Fred A.","contributorId":107200,"corporation":false,"usgs":true,"family":"Amidon","given":"Fred","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":494548,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Miller, Stephen E.","contributorId":31683,"corporation":false,"usgs":true,"family":"Miller","given":"Stephen","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":494544,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jacobi, James D. 0000-0003-2313-7862 jjacobi@usgs.gov","orcid":"https://orcid.org/0000-0003-2313-7862","contributorId":3705,"corporation":false,"usgs":true,"family":"Jacobi","given":"James","email":"jjacobi@usgs.gov","middleInitial":"D.","affiliations":[{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true},{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":494541,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Price, Jonathan P.","contributorId":8736,"corporation":false,"usgs":true,"family":"Price","given":"Jonathan","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":494542,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"`Ohukani`ohi`a Gon, Sam III","contributorId":60961,"corporation":false,"usgs":true,"family":"`Ohukani`ohi`a Gon","given":"Sam","suffix":"III","email":"","affiliations":[],"preferred":false,"id":494545,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Koob, Gregory A.","contributorId":61752,"corporation":false,"usgs":true,"family":"Koob","given":"Gregory","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":494546,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70111837,"text":"70111837 - 2014 - Methodological developments in US state-level Genuine Progress Indicators: toward GPI 2.0","interactions":[],"lastModifiedDate":"2014-06-10T08:46:22","indexId":"70111837","displayToPublicDate":"2014-06-10T08:35:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Methodological developments in US state-level Genuine Progress Indicators: toward GPI 2.0","docAbstract":"The Genuine Progress Indicator (GPI) has emerged as an important monetary measure of economic well-being. Unlike mainstream economic indicators, primarily Gross Domestic Product (GDP), the GPI accounts for both the benefits and costs of economic production across diverse economic, social, and environmental domains in a more comprehensive manner. Recently, the GPI has gained traction in subnational policy in the United States, with GPI studies being conducted in a number of states and with their formal adoption by several state governments. As the GPI is applied in different locations, new methods are developed, different data sources are available, and new issues of policy relevance are addressed using its component indicators. This has led to a divergence in methods, reducing comparability between studies and yielding results that are of varying methodological sophistication. In this study, we review the “state of the art” in recent US state-level GPI studies, focusing on those from Hawaii, Maryland, Ohio, Utah, and Vermont. Through adoption of a consistent approach, these and future GPI studies could utilize a framework that supports more uniform, comparable, and accurate measurements of progress. We also identify longer-term issues, particularly related to treatment of nonrenewable resource depletion, government spending, income inequality, and ecosystem services. As these issues are successfully addressed and disseminated, a “GPI 2.0” will emerge that better measures economic well-being and has greater accuracy and policy relevance than past GPI measurements. As the GPI expands further into mainstream policy analysis, a more formal process by which methods could be updated, standardized, and applied is needed.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ecological Indicators","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2014.05.005","usgsCitation":"Bagstad, K.J., Berik, G., and Gaddis, E.J., 2014, Methodological developments in US state-level Genuine Progress Indicators: toward GPI 2.0: Ecological Indicators, v. 45, p. 474-485, https://doi.org/10.1016/j.ecolind.2014.05.005.","productDescription":"12 p.","startPage":"474","endPage":"485","numberOfPages":"12","ipdsId":"IP-053091","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":288203,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":288202,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.ecolind.2014.05.005"}],"country":"United States","state":"Hawai'i;Maryl;Ohio;Utah;Vermont","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 144.616667,13.233333 ], [ 144.616667,71.833333 ], [ -64.566667,71.833333 ], [ -64.566667,13.233333 ], [ 144.616667,13.233333 ] ] ] } } ] }","volume":"45","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53981ad3e4b09e5ae91f9da6","contributors":{"authors":[{"text":"Bagstad, Kenneth J. 0000-0001-8857-5615 kjbagstad@usgs.gov","orcid":"https://orcid.org/0000-0001-8857-5615","contributorId":3680,"corporation":false,"usgs":true,"family":"Bagstad","given":"Kenneth","email":"kjbagstad@usgs.gov","middleInitial":"J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":494476,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Berik, Gunseli","contributorId":32829,"corporation":false,"usgs":true,"family":"Berik","given":"Gunseli","email":"","affiliations":[],"preferred":false,"id":494477,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gaddis, Erica J. Brown","contributorId":41345,"corporation":false,"usgs":true,"family":"Gaddis","given":"Erica","email":"","middleInitial":"J. Brown","affiliations":[],"preferred":false,"id":494478,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70107013,"text":"ofr20141089 - 2014 - Landscape consequences of natural gas extraction in Bedford, Blair, Cambria, Centre, Clearfield, Clinton, Columbia, Huntingdon, and Luzerne counties, Pennsylvania, 2004-2010","interactions":[],"lastModifiedDate":"2016-08-19T18:23:48","indexId":"ofr20141089","displayToPublicDate":"2014-06-10T08:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-1089","title":"Landscape consequences of natural gas extraction in Bedford, Blair, Cambria, Centre, Clearfield, Clinton, Columbia, Huntingdon, and Luzerne counties, Pennsylvania, 2004-2010","docAbstract":"<p>Increased demands for cleaner burning energy, coupled with the relatively recent technological advances in accessing unconventional hydrocarbon-rich geologic formations, have led to an intense effort to find and extract natural gas from various underground sources around the country. One of these sources, the Marcellus Shale, located in the Allegheny Plateau, is currently undergoing extensive drilling and production. The technology used to extract gas in the Marcellus Shale is known as hydraulic fracturing and has garnered much attention because of its use of large amounts of fresh water, its use of proprietary fluids for the hydraulic-fracturing process, its potential to release contaminants into the environment, and its potential effect on water resources. Nonetheless, development of natural gas extraction wells in the Marcellus Shale is only part of the overall natural gas story in this area of Pennsylvania. Conventional natural gas wells, which sometimes use the same technique, are commonly located in the same general area as the Marcellus Shale and are frequently developed in clusters across the landscape. The combined effects of these two natural gas extraction methods create potentially serious patterns of disturbance on the landscape. This document quantifies the landscape changes and consequences of natural gas extraction for Bedford, Blair, Cambria, Centre, Clearfield, Clinton, Columbia, Huntingdon, and Luzerne Counties in Pennsylvania between 2004 and 2010. Patterns of landscape disturbance related to natural gas extraction activities were collected and digitized using National Agriculture Imagery Program (NAIP) imagery for 2004, 2005/2006, 2008, and 2010. The disturbance patterns were then used to measure changes in land cover and land use using the National Land Cover Database (NLCD) of 2001. A series of landscape metrics is also used to quantify these changes and is included in this publication. In this region, natural gas development disturbed approximately 943 hectares of land in which forest sustained three times the amount of disturbance as agricultural land. One-quarter of that total disturbance was from Marcellus natural gas development.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141089","usgsCitation":"Slonecker, E., Milheim, L., Roig-Silva, C., and Winters, S., 2014, Landscape consequences of natural gas extraction in Bedford, Blair, Cambria, Centre, Clearfield, Clinton, Columbia, Huntingdon, and Luzerne counties, Pennsylvania, 2004-2010: U.S. Geological Survey Open-File Report 2014-1089, v, 49 p., https://doi.org/10.3133/ofr20141089.","productDescription":"v, 49 p.","numberOfPages":"55","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2004-01-01","temporalEnd":"2010-12-31","ipdsId":"IP-052469","costCenters":[{"id":242,"text":"Eastern Geographic Science 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S.G.","contributorId":99898,"corporation":false,"usgs":true,"family":"Winters","given":"S.G.","email":"","affiliations":[],"preferred":false,"id":493853,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70189960,"text":"70189960 - 2014 - H-binding of size- and polarity-fractionated soil and lignite humic acids after removal of metal and ash components","interactions":[],"lastModifiedDate":"2017-07-31T07:57:10","indexId":"70189960","displayToPublicDate":"2014-06-10T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1564,"text":"Environmental Science and Pollution Research","active":true,"publicationSubtype":{"id":10}},"title":"H-binding of size- and polarity-fractionated soil and lignite humic acids after removal of metal and ash components","docAbstract":"<p><span>A fractionation technique, combining dialysis removal of metal and ash components with hydrofluoric acid and pH 10 citrate buffer followed by chromatography of dialysis permeate on XAD-8 resin at decreasing pH values, has been applied to lignite humic acid (lignite-HA) and soil humic acid (soil-HA). H-binding data and non ideal competitive adsorption-Donnan model parameters were obtained for the HA fractions by theoretical analysis of H-binding data which reveal a significant increase of the carboxyl and the phenolic charge for the lignite-HA fractions vs. the parental lignite humic acid (L</span><sub>Parental</sub><span>HA). The fractionated lignite-HA material consisted mainly of permeate fractions, some of which were fulvic acid-like. The fractionated soil-HA material consisted mainly of large macromolecular structures that did not permeate the dialysis membrane during deashing. Chargeable groups had comparable concentrations in soil-HA fractions and parental soil humic acid (S</span><sub>Parental</sub><span>HA), indicating minimal interference of ash components with carboxyl and phenolic (and/or enolic) groups. Fractionation of HA, combined with theoretical analysis of H-binding, can distinguish the supramolecular vs. macromolecular nature of fractions within the same parental HA.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s11356-013-2302-9","usgsCitation":"Drosos, M., Leenheer, J.A., Avgeropoulos, A., and Deligiannakis, Y., 2014, H-binding of size- and polarity-fractionated soil and lignite humic acids after removal of metal and ash components: Environmental Science and Pollution Research, v. 21, no. 5, p. 3963-3971, https://doi.org/10.1007/s11356-013-2302-9.","productDescription":"9 p.","startPage":"3963","endPage":"3971","ipdsId":"IP-025378","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":344450,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"21","issue":"5","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2013-12-03","publicationStatus":"PW","scienceBaseUri":"5980419ce4b0a38ca278935f","contributors":{"authors":[{"text":"Drosos, Marios","contributorId":195372,"corporation":false,"usgs":false,"family":"Drosos","given":"Marios","email":"","affiliations":[],"preferred":false,"id":706896,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Leenheer, Jerry A.","contributorId":72420,"corporation":false,"usgs":true,"family":"Leenheer","given":"Jerry","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":706895,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Avgeropoulos, Apostolos","contributorId":195398,"corporation":false,"usgs":false,"family":"Avgeropoulos","given":"Apostolos","email":"","affiliations":[],"preferred":false,"id":706948,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Deligiannakis, Yiannis","contributorId":195373,"corporation":false,"usgs":false,"family":"Deligiannakis","given":"Yiannis","email":"","affiliations":[],"preferred":false,"id":706897,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}}
,{"id":70192979,"text":"70192979 - 2014 - Population trends of smallmouth bass in the upper Colorado River basin with an evaluation of removal effects","interactions":[],"lastModifiedDate":"2017-12-21T10:28:54","indexId":"70192979","displayToPublicDate":"2014-06-10T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"seriesNumber":"Project 161","title":"Population trends of smallmouth bass in the upper Colorado River basin with an evaluation of removal effects","docAbstract":"<p>Smallmouth bass <i>Micropterus dolomieu</i> were rare in the upper Colorado River basin until the early 1990’s when their abundance dramatically increased in the Yampa River sub-basin. Increased abundance was due primarily to colonization from Elkhead Reservoir, which was rapidly drawn down twice, first to make improvements to the dam (1992) and a second time for reservoir expansion (2005), and allowed escapement of resident bass to the river through an unscreened outlet. Elkhead Reservoir is located on Elkhead Creek, a tributary of the Yampa River. The rapid Elkhead Reservoir drawdown in 1992 was followed by a period of drought years with low, early runoff in the Yampa River sub-basin that benefitted smallmouth bass reproduction. This combination of factors allowed smallmouth bass to establish a self-sustaining population in the Yampa River. Subsequently, successful recruitment allowed smallmouth bass to disperse upstream and downstream in the Yampa River and eventually move into the downstream Green River. Smallmouth bass were also likely introduced, by unknown means, into the upper Colorado River and have since dispersed in this sub-basin. The rapid increase of smallmouth bass in the upper Colorado River basin overlapped with significant reductions in native fish populations in some locations. The threat to these native fishes initiated intensive mechanical removal of smallmouth bass by the Upper Colorado River Endangered Fish Recovery Program.</p><p>In general, three factors explain fluctuating patterns in smallmouth bass density in the upper Colorado River basin in the last decade: reductions due to electrofishing removal, bass recovery after exploitation due to recruitment and immigration, and changes due to environmental factors not related to electrofishing and other management actions. Our analyses indicated that smallmouth bass densities were substantially reduced in most years by 7 electrofishing removal efforts. Less often, but dramatically in some cases, environmental effects were also responsible for significant declines in smallmouth bass densities in some reaches. Abundant year classes of young smallmouth bass produced in low flow and warm years such as 2007 have potential to overwhelm removal efforts, and the year class persists for one or more years. Nonetheless, it appears that increased electrofishing removal efforts from 2007 to 2011 resulted in sustained reductions in density of smallmouth bass sub-adults and adults throughout the upper basin despite environmental conditions that favored smallmouth bass reproduction in some years (e.g. 2007 and 2009), subsequent recruitment into sub-adult and adult age classes, and movement of smallmouth bass which previously (prior to increases in electrofishing removal efforts) allowed densities to recover in some reaches.</p><p>We recommend that removal efforts continue in most areas of the upper basin but that the Recovery Program consider allocating effort based on population trends and suspected areas of highest smallmouth bass reproduction. For instance, reproduction, recruitment, and movement of smallmouth bass allowed densities to recover in some reaches, particularly Little Yampa Canyon. Smallmouth bass population recovery implies that areas such as Little Yampa Canyon itself or adjacent reaches (especially upstream), may provide important habitat for age-0 production. We recommend continued assessment of smallmouth bass populations in reaches where reproduction or age-1 nurseries are suspected, such as Little Yampa Canyon and the adjacent upstream reach. It may also be necessary to expand monitoring to areas surrounding suspected sources of smallmouth bass reproduction and increase electrofishing removal effort in these reaches.</p>","language":"English","publisher":"Upper Colorado River Endangered Fish Recovery Program","usgsCitation":"Breton, A., Winkelman, D.L., Hawkins, J.A., and Bestgen, K.R., 2014, Population trends of smallmouth bass in the upper Colorado River basin with an evaluation of removal effects, 95 p.","productDescription":"95 p.","ipdsId":"IP-054928","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":350148,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":350147,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.coloradoriverrecovery.org/documents-publications/technical-reports/nonnative-fish-management.html"}],"country":"United States","state":"Colorado, Utah","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -106.58935546875,\n              40.72228267283148\n            ],\n            [\n              -106.76513671875,\n              40.79717741518766\n            ],\n            [\n              -107.347412109375,\n              40.79717741518766\n            ],\n            [\n              -108.58337402343749,\n              40.622291783092706\n            ],\n            [\n              -109.566650390625,\n              40.37584377696013\n            ],\n            [\n              -109.918212890625,\n              40.271143686084194\n            ],\n            [\n              -110.379638671875,\n              40.04023218690451\n            ],\n            [\n              -110.577392578125,\n              39.614152077002664\n            ],\n            [\n              -110.643310546875,\n              39.20671884491848\n            ],\n            [\n              -110.4949951171875,\n              38.586820096127674\n            ],\n            [\n              -110.2972412109375,\n              38.21660403859855\n            ],\n            [\n              -110.1324462890625,\n              38.00049145082287\n            ],\n            [\n              -109.786376953125,\n              38.013476231041935\n            ],\n            [\n              -109.09423828125,\n              38.23386541556985\n            ],\n            [\n              -107.9681396484375,\n              38.989302551359515\n            ],\n            [\n              -107.07824707031249,\n              39.25352462727606\n            ],\n            [\n              -106.54541015625,\n              39.62261494094297\n            ],\n            [\n              -106.468505859375,\n              39.93922484079194\n            ],\n            [\n              -106.58935546875,\n              40.72228267283148\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a61008de4b06e28e9c253e8","contributors":{"authors":[{"text":"Breton, André R.","contributorId":47682,"corporation":false,"usgs":false,"family":"Breton","given":"André R.","affiliations":[],"preferred":false,"id":725286,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Winkelman, Dana L. 0000-0002-5247-0114 danaw@usgs.gov","orcid":"https://orcid.org/0000-0002-5247-0114","contributorId":4141,"corporation":false,"usgs":true,"family":"Winkelman","given":"Dana","email":"danaw@usgs.gov","middleInitial":"L.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":717513,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hawkins, John A.","contributorId":50076,"corporation":false,"usgs":true,"family":"Hawkins","given":"John","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":725287,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bestgen, Kevin R. 0000-0001-8691-2227","orcid":"https://orcid.org/0000-0001-8691-2227","contributorId":171573,"corporation":false,"usgs":false,"family":"Bestgen","given":"Kevin","email":"","middleInitial":"R.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":725288,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70106999,"text":"ofr20141100 - 2014 - Influences of the Tamarisk Leaf Beetle (<i>Diorhabda carinulata</i>) on the diet of insectivorous birds along the Dolores River in Southwestern Colorado","interactions":[],"lastModifiedDate":"2017-11-25T13:44:11","indexId":"ofr20141100","displayToPublicDate":"2014-06-09T14:46:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-1100","title":"Influences of the Tamarisk Leaf Beetle (<i>Diorhabda carinulata</i>) on the diet of insectivorous birds along the Dolores River in Southwestern Colorado","docAbstract":"We examined the effects of a biologic control agent, the tamarisk leaf beetle (Diorhabda carinulata), on native avifauna in southwestern Colorado, specifically, addressing whether and to what degree birds eat tamarisk leaf beetles. In 2010, we documented avian foraging behavior, characterized the arthropod community, sampled bird diets, and undertook an experiment to determine whether tamarisk leaf beetles are palatable to birds. We observed that tamarisk leaf beetles compose 24.0 percent (95-percent-confidence interval, 19.9-27.4 percent) and 35.4 percent (95-percent-confidence interval, 32.4-45.1 percent) of arthropod abundance and biomass in the study area, respectively. Birds ate few tamarisk leaf beetles, despite a superabundance of D. carinulata in the environment. The frequency of occurrence of tamarisk leaf beetles in bird diets was 2.1 percent (95-percent-confidence interval, 1.3- 2.9 percent) by abundance and 3.4 percent (95-percent-confidence interval, 2.6-4.2 percent) by biomass. Thus, tamarisk leaf beetles probably do not contribute significantly to the diets of birds in areas where biologic control of tamarisk is being applied.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141100","issn":"2331-1258","usgsCitation":"Puckett, S., and van Riper, C., 2014, Influences of the Tamarisk Leaf Beetle (<i>Diorhabda carinulata</i>) on the diet of insectivorous birds along the Dolores River in Southwestern Colorado: U.S. Geological Survey Open-File Report 2014-1100, iv, 49 p., https://doi.org/10.3133/ofr20141100.","productDescription":"iv, 49 p.","numberOfPages":"53","onlineOnly":"Y","ipdsId":"IP-044426","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":288180,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1100/"},{"id":288182,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141100.PNG"},{"id":288181,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1100/pdf/ofr2014-1100.pdf"}],"country":"United States","state":"Colorado;Utah","otherGeospatial":"Dolores River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -109.2803,37.4408 ], [ -109.2803,38.8276 ], [ -107.9266,38.8276 ], [ -107.9266,37.4408 ], [ -109.2803,37.4408 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5396c953e4b0f7580bc0a8c3","contributors":{"authors":[{"text":"Puckett, Sarah L.","contributorId":34046,"corporation":false,"usgs":true,"family":"Puckett","given":"Sarah L.","affiliations":[],"preferred":false,"id":493847,"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":493848,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70102224,"text":"70102224 - 2014 - Use of genetic data to infer population-specific ecological and phenotypic traits from mixed aggregations","interactions":[],"lastModifiedDate":"2018-04-21T13:19:15","indexId":"70102224","displayToPublicDate":"2014-06-09T13:58:00","publicationYear":"2014","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":"Use of genetic data to infer population-specific ecological and phenotypic traits from mixed aggregations","docAbstract":"Many applications in ecological genetics involve sampling individuals from a mixture of multiple biological populations and subsequently associating those individuals with the populations from which they arose. Analytical methods that assign individuals to their putative population of origin have utility in both basic and applied research, providing information about population-specific life history and habitat use, ecotoxins, pathogen and parasite loads, and many other non-genetic ecological, or phenotypic traits. Although the question is initially directed at the origin of individuals, in most cases the ultimate desire is to investigate the distribution of some trait among populations. Current practice is to assign individuals to a population of origin and study properties of the trait among individuals within population strata as if they constituted independent samples. It seemed that approach might bias population-specific trait inference. In this study we made trait inferences directly through modeling, bypassing individual assignment. We extended a Bayesian model for population mixture analysis to incorporate parameters for the phenotypic trait and compared its performance to that of individual assignment with a minimum probability threshold for assignment. The Bayesian mixture model outperformed individual assignment under some trait inference conditions. However, by discarding individuals whose origins are most uncertain, the individual assignment method provided a less complex analytical technique whose performance may be adequate for some common trait inference problems. Our results provide specific guidance for method selection under various genetic relationships among populations with different trait distributions.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"PLoS ONE","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Public Library of Science","publisherLocation":"San Francisco, CA","doi":"10.1371/journal.pone.0098470","usgsCitation":"Moran, P., Bromaghin, J.F., and Masuda, M., 2014, Use of genetic data to infer population-specific ecological and phenotypic traits from mixed aggregations: PLoS ONE, v. 9, no. 6, 13 p., https://doi.org/10.1371/journal.pone.0098470.","productDescription":"13 p.","numberOfPages":"13","onlineOnly":"Y","ipdsId":"IP-050953","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"links":[{"id":472945,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0098470","text":"Publisher Index Page"},{"id":288179,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":288178,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1371/journal.pone.0098470"}],"volume":"9","issue":"6","noUsgsAuthors":false,"publicationDate":"2014-06-06","publicationStatus":"PW","scienceBaseUri":"5396c953e4b0f7580bc0a8c7","contributors":{"authors":[{"text":"Moran, Paul","contributorId":42140,"corporation":false,"usgs":true,"family":"Moran","given":"Paul","email":"","affiliations":[],"preferred":false,"id":492862,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bromaghin, Jeffrey F. 0000-0002-7209-9500 jbromaghin@usgs.gov","orcid":"https://orcid.org/0000-0002-7209-9500","contributorId":139899,"corporation":false,"usgs":true,"family":"Bromaghin","given":"Jeffrey","email":"jbromaghin@usgs.gov","middleInitial":"F.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":492860,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Masuda, Michele","contributorId":24280,"corporation":false,"usgs":true,"family":"Masuda","given":"Michele","email":"","affiliations":[],"preferred":false,"id":492861,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70107925,"text":"fs20143043 - 2014 - Water resources of Acadia Parish, Louisiana","interactions":[],"lastModifiedDate":"2014-06-09T11:41:11","indexId":"fs20143043","displayToPublicDate":"2014-06-09T11:32:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-3043","title":"Water resources of Acadia Parish, Louisiana","docAbstract":"Information concerning the availability, use, and quality of water in Acadia Parish, Louisiana, is critical for proper water-supply management. The purpose of this fact sheet is to present information that can be used by water managers, parish residents, and others for stewardship of this vital resource. Information on the availability, past and current use, use trends, and water quality from groundwater and surface-water sources in the parish is presented. Previously published reports and data stored in the U.S. Geological Survey’s National Water Information System (<a href=\"http://waterdata.usgs.gov/nwis\">http://waterdata.usgs.gov/nwis</a>) are the primary sources of the information presented here.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20143043","issn":"2327-6932","collaboration":"Prepared in cooperation with the Louisiana Department of Transportation and Development","usgsCitation":"Prakken, L., and White, V.E., 2014, Water resources of Acadia Parish, Louisiana: U.S. Geological Survey Fact Sheet 2014-3043, 6 p., https://doi.org/10.3133/fs20143043.","productDescription":"6 p.","numberOfPages":"6","onlineOnly":"N","ipdsId":"IP-055417","costCenters":[{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"links":[{"id":288175,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20143043.jpg"},{"id":288173,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2014/3043/"},{"id":288174,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2014/3043/pdf/fs2014-3043.pdf"}],"projection":"Albers Equal-Area Conic projection","datum":"North American Datum of 1983","country":"United States","state":"Louisiana","county":"Acadia Parish","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -92.666667,30.0 ], [ -92.666667,30.5 ], [ -92.166667,30.5 ], [ -92.166667,30.0 ], [ -92.666667,30.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5396c954e4b0f7580bc0a8cb","contributors":{"authors":[{"text":"Prakken, Larry B.","contributorId":86673,"corporation":false,"usgs":true,"family":"Prakken","given":"Larry B.","affiliations":[],"preferred":false,"id":493934,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"White, Vincent E. 0000-0002-1660-0102 vwhite@usgs.gov","orcid":"https://orcid.org/0000-0002-1660-0102","contributorId":5388,"corporation":false,"usgs":true,"family":"White","given":"Vincent","email":"vwhite@usgs.gov","middleInitial":"E.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":493933,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70111747,"text":"70111747 - 2014 - Hawaiian forest bird trends: using log-linear models to assess long-term trends is supported by model diagnostics and assumptions (reply to Freed and Cann 2013)","interactions":[],"lastModifiedDate":"2014-06-09T10:37:25","indexId":"70111747","displayToPublicDate":"2014-06-09T10:27:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1318,"text":"Condor","active":true,"publicationSubtype":{"id":10}},"title":"Hawaiian forest bird trends: using log-linear models to assess long-term trends is supported by model diagnostics and assumptions (reply to Freed and Cann 2013)","docAbstract":"Freed and Cann (2013) criticized our use of linear models to assess trends in the status of Hawaiian forest birds through time (Camp et al. 2009a, 2009b, 2010) by questioning our sampling scheme, whether we met model assumptions, and whether we ignored short-term changes in the population time series. In the present paper, we address these concerns and reiterate that our results do not support the position of Freed and Cann (2013) that the forest birds in the Hakalau Forest National Wildlife Refuge (NWR) are declining, or that the federally listed endangered birds are showing signs of imminent collapse. On the contrary, our data indicate that the 21-year long-term trends for native birds in Hakalau Forest NWR are stable to increasing, especially in areas that have received active management.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Condor","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Cooper Ornithological Society","doi":"10.1650/CONDOR-13-089.1","usgsCitation":"Camp, R., Pratt, T.K., Gorresen, P.M., Woodworth, B., and Jeffrey, J.J., 2014, Hawaiian forest bird trends: using log-linear models to assess long-term trends is supported by model diagnostics and assumptions (reply to Freed and Cann 2013): Condor, v. 116, no. 1, p. 97-101, https://doi.org/10.1650/CONDOR-13-089.1.","productDescription":"5 p.","startPage":"97","endPage":"101","numberOfPages":"5","ipdsId":"IP-052204","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":472946,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1650/condor-13-089.1","text":"Publisher Index Page"},{"id":288171,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":288161,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1650/CONDOR-13-089.1"}],"country":"United States","state":"Hawai'i","otherGeospatial":"Hakalau Forest National Wildlife Refuge","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -155.85876,19.363457 ], [ -155.85876,19.922001 ], [ -155.223499,19.922001 ], [ -155.223499,19.363457 ], [ -155.85876,19.363457 ] ] ] } } ] }","volume":"116","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5396c952e4b0f7580bc0a8bf","contributors":{"authors":[{"text":"Camp, Richard J.","contributorId":27392,"corporation":false,"usgs":true,"family":"Camp","given":"Richard J.","affiliations":[],"preferred":false,"id":494460,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pratt, Thane K. tkpratt@usgs.gov","contributorId":5495,"corporation":false,"usgs":true,"family":"Pratt","given":"Thane","email":"tkpratt@usgs.gov","middleInitial":"K.","affiliations":[{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"preferred":true,"id":494459,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gorresen, P. Marcos mgorresen@usgs.gov","contributorId":37020,"corporation":false,"usgs":true,"family":"Gorresen","given":"P.","email":"mgorresen@usgs.gov","middleInitial":"Marcos","affiliations":[],"preferred":false,"id":494461,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Woodworth, Bethany L.","contributorId":66797,"corporation":false,"usgs":true,"family":"Woodworth","given":"Bethany L.","affiliations":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"preferred":false,"id":494463,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jeffrey, John J.","contributorId":55256,"corporation":false,"usgs":true,"family":"Jeffrey","given":"John","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":494462,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70128991,"text":"70128991 - 2014 - Hierarchical spatial genetic structure in a distinct population segment of greater sage-grouse","interactions":[],"lastModifiedDate":"2016-12-14T12:11:21","indexId":"70128991","displayToPublicDate":"2014-06-07T09:51:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1324,"text":"Conservation Genetics","active":true,"publicationSubtype":{"id":10}},"title":"Hierarchical spatial genetic structure in a distinct population segment of greater sage-grouse","docAbstract":"<p>Greater sage-grouse (<em>Centrocercus urophasianus</em>) within the Bi-State Management Zone (area along the border between Nevada and California) are geographically isolated on the southwestern edge of the species&rsquo; range. Previous research demonstrated that this population is genetically unique, with a high proportion of unique mitochondrial DNA (mtDNA) haplotypes and with significant differences in microsatellite allele frequencies compared to populations across the species&rsquo; range. As a result, this population was considered a distinct population segment (DPS) and was recently proposed for listing as threatened under the U.S. Endangered Species Act. A more comprehensive understanding of the boundaries of this genetically unique population (where the Bi-State population begins) and an examination of genetic structure within the Bi-State is needed to help guide effective management decisions. We collected DNA from eight sampling locales within the Bi-State (N = 181) and compared those samples to previously collected DNA from the two most proximal populations outside of the Bi-State DPS, generating mtDNA sequence data and amplifying 15 nuclear microsatellites. Both mtDNA and microsatellite analyses support the idea that the Bi-State DPS represents a genetically unique population, which has likely been separated for thousands of years. Seven mtDNA haplotypes were found exclusively in the Bi-State population and represented 73 % of individuals, while three haplotypes were shared with neighboring populations. In the microsatellite analyses both STRUCTURE and FCA separate the Bi-State from the neighboring populations. We also found genetic structure within the Bi-State as both types of data revealed differences between the northern and southern part of the Bi-State and there was evidence of isolation-by-distance. STRUCTURE revealed three subpopulations within the Bi-State consisting of the northern Pine Nut Mountains (PNa), mid Bi-State, and White Mountains (WM) following a north&ndash;south gradient. This genetic subdivision within the Bi-State is likely the result of habitat loss and fragmentation that has been exacerbated by recent human activities and the encroachment of singleleaf pinyon (<em>Pinus monophylla</em>) and juniper (<em>Juniperus</em> spp.) trees. While genetic concerns may be only one of many priorities for the conservation and management of the Bi-State greater sage-grouse, we believe that they warrant attention along with other issues (e.g., quality of sagebrush habitat, preventing future loss of habitat). Management actions that promote genetic connectivity, especially with respect to WM and PNa, may be critical to the long-term viability of the Bi-State DPS.</p>","language":"English","publisher":"Springer","doi":"10.1007/s10592-014-0618-8","usgsCitation":"Oyler-McCance, S.J., Casazza, M.L., Fike, J.A., and Coates, P.S., 2014, Hierarchical spatial genetic structure in a distinct population segment of greater sage-grouse: Conservation Genetics, v. 15, no. 6, p. 1299-1311, https://doi.org/10.1007/s10592-014-0618-8.","productDescription":"13 p.","startPage":"1299","endPage":"1311","numberOfPages":"13","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-052505","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":295364,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":295348,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s10592-014-0618-8"}],"country":"United States","state":"California, Nevada","volume":"15","issue":"6","noUsgsAuthors":false,"publicationDate":"2014-06-07","publicationStatus":"PW","scienceBaseUri":"5440de2de4b0b0a643c732db","contributors":{"authors":[{"text":"Oyler-McCance, Sara J. 0000-0003-1599-8769 sara_oyler-mccance@usgs.gov","orcid":"https://orcid.org/0000-0003-1599-8769","contributorId":1973,"corporation":false,"usgs":true,"family":"Oyler-McCance","given":"Sara","email":"sara_oyler-mccance@usgs.gov","middleInitial":"J.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":503266,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Casazza, Michael L. 0000-0002-5636-735X mike_casazza@usgs.gov","orcid":"https://orcid.org/0000-0002-5636-735X","contributorId":2091,"corporation":false,"usgs":true,"family":"Casazza","given":"Michael","email":"mike_casazza@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":503267,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fike, Jennifer A. fikej@usgs.gov","contributorId":4564,"corporation":false,"usgs":true,"family":"Fike","given":"Jennifer","email":"fikej@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":503269,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Coates, Peter S. 0000-0003-2672-9994 pcoates@usgs.gov","orcid":"https://orcid.org/0000-0003-2672-9994","contributorId":3263,"corporation":false,"usgs":true,"family":"Coates","given":"Peter","email":"pcoates@usgs.gov","middleInitial":"S.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":503268,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70102827,"text":"ofr20141083 - 2014 - Using a Bayesian Network to predict shore-line change vulnerability to sea-level rise for the coasts of the United States","interactions":[],"lastModifiedDate":"2014-06-06T15:53:08","indexId":"ofr20141083","displayToPublicDate":"2014-06-06T15:50:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-1083","title":"Using a Bayesian Network to predict shore-line change vulnerability to sea-level rise for the coasts of the United States","docAbstract":"Sea-level rise is an ongoing phenomenon that is expected to continue and is projected to have a wide range of effects on coastal environments and infrastructure during the 21st century and beyond. Consequently, there is a need to assemble relevant datasets and to develop modeling or other analytical approaches to evaluate the likelihood of particular sea-level rise impacts, such as coastal erosion, and to inform coastal management decisions with this information. This report builds on previous work that compiled oceanographic and geomorphic data as part of the U.S. Geological Survey’s Coastal Vulnerability Index (CVI) for the U.S. Atlantic coast, and developed a Bayesian Network to predict shoreline-change rates based on sea-level rise plus variables that describe the hydrodynamic and geologic setting. This report extends the previous analysis to include the Gulf and Pacific coasts of the continental United States and Alaska and Hawaii, which required using methods applied to the USGS CVI dataset to extract data for these regions. The Bayesian Network converts inputs that include observations of local rates of relative sea-level change, mean wave height, mean tide range, a geomorphic classification, coastal slope, and observed shoreline-change rates to calculate the probability of the shoreline-erosion rate exceeding a threshold level of 1 meter per year for the coasts of the United States. The calculated probabilities were compared to the historical observations of shoreline change to evaluate the hindcast success rate of the most likely probability of shoreline change. Highest accuracy was determined for the coast of Hawaii (98 percent success rate) and lowest accuracy was determined for the Gulf of Mexico (34 percent success rate). The minimum success rate rose to nearly 80 percent (Atlantic and Gulf coasts) when success included shoreline-change outcomes that were adjacent to the most likely outcome. Additionally, the probabilistic approach determines the confidence in calculated outcomes as the probability of the most likely outcome. The confidence was highest along the Pacific coast and it was lowest along the Alaskan coast.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141083","issn":"2331-1258","usgsCitation":"Gutierrez, B.T., Plant, N.G., Pendleton, E., and Thieler, E.R., 2014, Using a Bayesian Network to predict shore-line change vulnerability to sea-level rise for the coasts of the United States: U.S. Geological Survey Open-File Report 2014-1083, v, 26 p., https://doi.org/10.3133/ofr20141083.","productDescription":"v, 26 p.","numberOfPages":"32","onlineOnly":"Y","ipdsId":"IP-053816","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":288160,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141083.jpg"},{"id":288158,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1083/"},{"id":288159,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1083/pdf/ofr2014-1083.pdf"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -130.0,20.0 ], [ -130.0,50.0 ], [ -60.0,50.0 ], [ -60.0,20.0 ], [ -130.0,20.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53ae789ce4b0abf75cf2da90","contributors":{"authors":[{"text":"Gutierrez, Benjamin T.","contributorId":58670,"corporation":false,"usgs":true,"family":"Gutierrez","given":"Benjamin","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":493044,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Plant, Nathaniel G. 0000-0002-5703-5672 nplant@usgs.gov","orcid":"https://orcid.org/0000-0002-5703-5672","contributorId":3503,"corporation":false,"usgs":true,"family":"Plant","given":"Nathaniel","email":"nplant@usgs.gov","middleInitial":"G.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true}],"preferred":true,"id":493043,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pendleton, Elizabeth A.","contributorId":101312,"corporation":false,"usgs":true,"family":"Pendleton","given":"Elizabeth A.","affiliations":[],"preferred":false,"id":493045,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thieler, E. Robert 0000-0003-4311-9717 rthieler@usgs.gov","orcid":"https://orcid.org/0000-0003-4311-9717","contributorId":2488,"corporation":false,"usgs":true,"family":"Thieler","given":"E.","email":"rthieler@usgs.gov","middleInitial":"Robert","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":493042,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70098476,"text":"ofr20141060 - 2014 - Quality-assurance and data management plan for groundwater activities by the U.S. Geological Survey in Kansas, 2014","interactions":[],"lastModifiedDate":"2014-06-06T15:10:05","indexId":"ofr20141060","displayToPublicDate":"2014-06-06T15:07:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-1060","title":"Quality-assurance and data management plan for groundwater activities by the U.S. Geological Survey in Kansas, 2014","docAbstract":"<p>As the Nation’s principle earth-science information agency, the U.S. Geological Survey (USGS) is depended on to collect data of the highest quality. This document is a quality-assurance plan for groundwater activities (GWQAP) of the Kansas Water Science Center. The purpose of this GWQAP is to establish a minimum set of guidelines and practices to be used by the Kansas Water Science Center to ensure quality in groundwater activities. Included within these practices are the assignment of responsibilities for implementing quality-assurance activities in the Kansas Water Science Center and establishment of review procedures needed to ensure the technical quality and reliability of the groundwater products. In addition, this GWQAP is intended to complement quality-assurance plans for surface-water and water-quality activities and similar plans for the Kansas Water Science Center and general project activities throughout the USGS.</p>\n<br>\n<p>This document provides the framework for collecting, analyzing, and reporting groundwater data that are quality assured and quality controlled. This GWQAP presents policies directing the collection, processing, analysis, storage, review, and publication of groundwater data. In addition, policies related to organizational responsibilities, training, project planning, and safety are presented. These policies and practices pertain to all groundwater activities conducted by the Kansas Water Science Center, including data-collection programs, interpretive and research projects. This report also includes the data management plan that describes the progression of data management from data collection to archiving and publication.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141060","issn":"2331-1258","usgsCitation":"Putnam, J.E., and Hansen, C.V., 2014, Quality-assurance and data management plan for groundwater activities by the U.S. Geological Survey in Kansas, 2014: U.S. Geological Survey Open-File Report 2014-1060, v, 37 p., https://doi.org/10.3133/ofr20141060.","productDescription":"v, 37 p.","numberOfPages":"48","onlineOnly":"Y","ipdsId":"IP-051485","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":288156,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141060.jpg"},{"id":288154,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1060/"},{"id":288155,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1060/pdf/ofr2014-1060.pdf"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53ae77f9e4b0abf75cf2c668","contributors":{"authors":[{"text":"Putnam, James E. jputnam@usgs.gov","contributorId":2021,"corporation":false,"usgs":true,"family":"Putnam","given":"James","email":"jputnam@usgs.gov","middleInitial":"E.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":false,"id":491730,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hansen, Cristi V. chansen@usgs.gov","contributorId":435,"corporation":false,"usgs":true,"family":"Hansen","given":"Cristi","email":"chansen@usgs.gov","middleInitial":"V.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":false,"id":491729,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70111698,"text":"ds856 - 2014 - Archive of digital chirp subbottom profile data collected during USGS cruise 12BIM03 offshore of the Chandeleur Islands, Louisiana, July 2012","interactions":[],"lastModifiedDate":"2023-01-04T21:51:19.731225","indexId":"ds856","displayToPublicDate":"2014-06-06T14:19:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"856","title":"Archive of digital chirp subbottom profile data collected during USGS cruise 12BIM03 offshore of the Chandeleur Islands, Louisiana, July 2012","docAbstract":"<p>From July 23 - 31, 2012, the U.S. Geological Survey conducted geophysical surveys to investigate the geologic controls on barrier island framework and long-term sediment transport along the oil spill mitigation sand berm constructed at the north end and just offshore of the Chandeleur Islands, La. (figure 1). This effort is part of a broader USGS study, which seeks to better understand barrier island evolution over medium time scales (months to years). This report serves as an archive of unprocessed digital chirp subbottom data, trackline maps, navigation files, Geographic Information System (GIS) files, Field Activity Collection System (FACS) logs, and formal Federal Geographic Data Committee (FGDC) metadata. Gained (showing a relative increase in signal amplitude) digital images of the seismic profiles are also provided. Refer to the Abbreviations page for expansions of acronyms and abbreviations used in this report.</p>\n\n<br>\n\n<p>The USGS St. Petersburg Coastal and Marine Science Center (SPCMSC) assigns a unique identifier to each cruise or field activity. For example, 12BIM03 tells us the data were collected in 2012 during the third field activity for that project in that calendar year and BIM is a generic code, which represents efforts related to Barrier Island Mapping. Refer to http://walrus.wr.usgs.gov/infobank/programs/html/definition/activity.html for a detailed description of the method used to assign the field activity ID.</p>\n\n<br>\n\n<p>All chirp systems use a signal of continuously varying frequency; the EdgeTech SB-424 system used during this survey produces high-resolution, shallow-penetration (typically less than 50 milliseconds (ms)) profile images of sub-seafloor stratigraphy. The towfish contains a transducer that transmits and receives acoustic energy and is typically towed 1 - 2 m below the sea surface. As transmitted acoustic energy intersects density boundaries, such as the seafloor or sub-surface sediment layers, energy is reflected back toward the transducer, received, and recorded by a PC-based seismic acquisition system. This process is repeated at regular time intervals (for example, 0.125 seconds (s)) and returned energy is recorded for a specific duration (for example, 50 ms). In this way, a two-dimensional (2-D) vertical image of the shallow geologic structure beneath the ship track is produced. Figure 2 displays the acquisition geometry. Refer to table 1 for a summary of acquisition parameters and table 2 for trackline statistics.</p>\n\n<br>\n\n<p>The archived trace data are in standard Society of Exploration Geophysicists (SEG) SEG Y rev. 0 format (Barry and others, 1975); the first 3,200 bytes of the card image header are in ASCII format instead of EBCDIC format. The SEG Y files may be downloaded and processed with commercial or public domain software such as Seismic Unix (SU) (Cohen and Stockwell, 2010). See the How To Download SEG Y Data page for download instructions. The web version of this archive does not contain the SEG Y trace files. These files are very large and would require extremely long download times. To obtain the complete DVD archive, contact USGS Information Services at 1-888-ASK-USGS or infoservices@usgs.gov. The printable profiles provided here are GIF images that were processed and gained using SU software and can be viewed from the Profiles page or from links located on the trackline maps; refer to the Software page for links to example SU processing scripts. The SEG Y files are available on the DVD version of this report or on the Web, downloadable via the USGS Coastal and Marine Geoscience Data System (http://cmgds.marine.usgs.gov). The data are also available for viewing using GeoMapApp (http://www.geomapapp.org) and Virtual Ocean (http://www.virtualocean.org) multi-platform open source software.</p>\n\n<br>\n\n<p>Detailed information about the navigation system used can be found in table 1 and the Field Activity Collection System (FACS) logs. To view the trackline maps and navigation files, and for more information about these items, see the Navigation page.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds856","usgsCitation":"Forde, A.S., Miselis, J.L., and Wiese, D.S., 2014, Archive of digital chirp subbottom profile data collected during USGS cruise 12BIM03 offshore of the Chandeleur Islands, Louisiana, July 2012: U.S. Geological Survey Data Series 856, HTML Document, https://doi.org/10.3133/ds856.","productDescription":"HTML Document","onlineOnly":"Y","ipdsId":"IP-054768","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":288153,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds856.jpg"},{"id":288152,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/856/html/ds856_home.html"},{"id":288151,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/856/"}],"country":"United States","state":"Louisiana","otherGeospatial":"Chandeleur Islands","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -88.916378,\n              29.951025\n            ],\n            [\n              -88.916378,\n              30.094522\n            ],\n            [\n              -88.797183,\n              30.094522\n            ],\n            [\n              -88.797183,\n              29.951025\n            ],\n            [\n              -88.916378,\n              29.951025\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5396d760e4b0f7580bc0a8d0","contributors":{"authors":[{"text":"Forde, Arnell S. 0000-0002-5581-2255 aforde@usgs.gov","orcid":"https://orcid.org/0000-0002-5581-2255","contributorId":376,"corporation":false,"usgs":true,"family":"Forde","given":"Arnell","email":"aforde@usgs.gov","middleInitial":"S.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":494440,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Miselis, Jennifer L. 0000-0002-4925-3979 jmiselis@usgs.gov","orcid":"https://orcid.org/0000-0002-4925-3979","contributorId":3914,"corporation":false,"usgs":true,"family":"Miselis","given":"Jennifer","email":"jmiselis@usgs.gov","middleInitial":"L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":494442,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wiese, Dana S. dwiese@usgs.gov","contributorId":2476,"corporation":false,"usgs":true,"family":"Wiese","given":"Dana","email":"dwiese@usgs.gov","middleInitial":"S.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":494441,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70112937,"text":"70112937 - 2014 - Using a network modularity analysis to inform management of a rare endemic plant in the northern Great Plains, USA","interactions":[],"lastModifiedDate":"2018-01-02T12:28:30","indexId":"70112937","displayToPublicDate":"2014-06-06T14:08:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2163,"text":"Journal of Applied Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Using a network modularity analysis to inform management of a rare endemic plant in the northern Great Plains, USA","docAbstract":"<p>1.  Analyses of flower-visitor interaction networks allow application of community-level information to conservation problems, but management recommendations that ensue from such analyses are not well characterized. Results of modularity analyses, which detect groups of species (modules) that interact more with each other than with species outside their module, may be particularly applicable to management concerns.</p>\n<br>\n<p>2.  We conducted modularity analyses of networks surrounding a rare endemic annual plant, <i>Eriogonum visheri</i>, at Badlands National Park, USA, in 2010 and 2011. Plant species visited were determined by pollen on insect bodies and by flower species upon which insects were captured. Roles within modules (network hub, module hub, connector and peripheral, in decreasing order of network structural importance) were determined for each species.</p>\n<br>\n<p>3.  Relationships demonstrated by the modularity analysis, in concert with knowledge of pollen species carried by insects, allowed us to infer effects of two invasive species on <i>E. visheri</i>. Sharing a module increased risk of interspecific pollen transfer to <i>E. visheri</i>. Control of invasive <i>Salsola tragus</i>, which shared a module with <i>E. visheri</i>, is therefore a prudent management objective, but lack of control of invasive <i>Melilotus officinalis</i>, which occupied a different module, is unlikely to negatively affect pollination of <i>E. visheri</i>. <i>Eriogonum pauciflorum</i> may occupy a key position in this network, supporting insects from the <i>E. visheri</i> module when <i>E. visheri</i> is less abundant.</p>\n<br>\n<p>4.  Year-to-year variation in species' roles suggests management decisions must be based on observations over several years. Information on pollen deposition on stigmas would greatly strengthen inferences made from the modularity analysis.</p>\n<br>\n<p>5.  Synthesis and applications: Assessing the consequences of pollination, whether at the community or individual level, is inherently time-consuming. A trade-off exists: rather than an estimate of fitness effects, the network approach provides a broad understanding of the relationships among insect visitors and other plant species that may affect the focal rare plant. Knowledge of such relationships allows managers to detect, target and prioritize control of only the important subset of invasive species present and identify other species that may augment a rare species' population stability, such as <i>E. pauciflorum</i> in our study.</p>","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Applied Ecology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1111/1365-2664.12273","usgsCitation":"Larson, D.L., Droege, S., Rabie, P.A., Larson, J.L., Devalez, J., Haar, M., and McDermott-Kubeczko, M., 2014, Using a network modularity analysis to inform management of a rare endemic plant in the northern Great Plains, USA: Journal of Applied Ecology, v. 51, no. 4, p. 1024-1032, https://doi.org/10.1111/1365-2664.12273.","productDescription":"9 p.","startPage":"1024","endPage":"1032","ipdsId":"IP-052981","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":472947,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2664.12273","text":"Publisher Index Page"},{"id":288828,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":288827,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/1365-2664.12273"}],"country":"United States","state":"South Dakota","otherGeospatial":"Badlands National Park","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -102.9,43.48 ], [ -102.9,43.92 ], [ -101.89,43.92 ], [ -101.89,43.48 ], [ -102.9,43.48 ] ] ] } } ] }","volume":"51","issue":"4","noUsgsAuthors":false,"publicationDate":"2014-06-06","publicationStatus":"PW","scienceBaseUri":"53ae789de4b0abf75cf2daa8","chorus":{"doi":"10.1111/1365-2664.12273","url":"http://dx.doi.org/10.1111/1365-2664.12273","publisher":"Wiley-Blackwell","authors":"Larson Diane L., Droege Sam, Rabie Paul A., Larson Jennifer L., Devalez Jelle, Haar Milton, McDermott-Kubeczko Margaret","journalName":"Journal of Applied Ecology","publicationDate":"6/6/2014"},"contributors":{"authors":[{"text":"Larson, Diane L. 0000-0001-5202-0634 dlarson@usgs.gov","orcid":"https://orcid.org/0000-0001-5202-0634","contributorId":2120,"corporation":false,"usgs":true,"family":"Larson","given":"Diane","email":"dlarson@usgs.gov","middleInitial":"L.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":494950,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Droege, Sam sdroege@usgs.gov","contributorId":3464,"corporation":false,"usgs":true,"family":"Droege","given":"Sam","email":"sdroege@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":494951,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rabie, Paul A. 0000-0003-4364-2268","orcid":"https://orcid.org/0000-0003-4364-2268","contributorId":74328,"corporation":false,"usgs":true,"family":"Rabie","given":"Paul","email":"","middleInitial":"A.","affiliations":[],"preferred":true,"id":494955,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Larson, Jennifer L. 0000-0002-6259-0101","orcid":"https://orcid.org/0000-0002-6259-0101","contributorId":68144,"corporation":false,"usgs":true,"family":"Larson","given":"Jennifer","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":494954,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Devalez, Jelle","contributorId":24690,"corporation":false,"usgs":true,"family":"Devalez","given":"Jelle","email":"","affiliations":[],"preferred":false,"id":494953,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Haar, Milton","contributorId":14302,"corporation":false,"usgs":true,"family":"Haar","given":"Milton","email":"","affiliations":[],"preferred":false,"id":494952,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McDermott-Kubeczko, Margaret","contributorId":91024,"corporation":false,"usgs":true,"family":"McDermott-Kubeczko","given":"Margaret","affiliations":[],"preferred":false,"id":494956,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70111688,"text":"70111688 - 2014 - Natural uranium and strontium isotope tracers of water sources and surface water-groundwater interactions in arid wetlands: Pahranagat Valley, Nevada, USA","interactions":[],"lastModifiedDate":"2014-06-06T11:53:25","indexId":"70111688","displayToPublicDate":"2014-06-06T11:48:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Natural uranium and strontium isotope tracers of water sources and surface water-groundwater interactions in arid wetlands: Pahranagat Valley, Nevada, USA","docAbstract":"Near-surface physical and chemical process can strongly affect dissolved-ion concentrations and stable isotope compositions of water in wetland settings, especially under arid climate conditions.  In contrast, heavy radiogenic isotopes of strontium (<sup>87</sup>Sr/<sup>86</sup>Sr) and uranium (<sup>234</sup>U/<sup>238</sup>U) remain largely unaffected and can be used to help identify unique signatures from different sources and quantify end-member mixing that would otherwise be difficult to determine.  The utility of combined Sr and U isotopes are demonstrated in this study of wetland habitats on the Pahranagat National Wildlife Refuge, which depend on supply from large-volume springs north of the Refuge, and from small-volume springs and seeps within the Refuge.  Water budgets from these sources have not been quantified previously.  Evaporation, transpiration, seasonally variable surface flow, and water management practices complicate the use of conventional methods for determining source contributions and mixing relations.  In contrast, <sup>87</sup>Sr/<sup>86</sup>Sr and <sup>234</sup>U/<sup>238</sup>U remain unfractionated under these conditions, and compositions at a given site remain constant.  Differences in Sr- and U-isotopic signatures between individual sites can be related by simple two- or three-component mixing models.  Results indicate that surface flow constituting the Refuge’s irrigation source consists of a 65:25:10 mixture of water from two distinct regionally sourced carbonate aquifer springs, and groundwater from locally sourced volcanic aquifers.  Within the Refuge, contributions from the irrigation source and local groundwater are readily determined and depend on proximity to those sources as well as water management practices.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Hydrology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2014.05.011","usgsCitation":"Paces, J.B., and Wurster, F.C., 2014, Natural uranium and strontium isotope tracers of water sources and surface water-groundwater interactions in arid wetlands: Pahranagat Valley, Nevada, USA: Journal of Hydrology, v. 517, p. 213-225, https://doi.org/10.1016/j.jhydrol.2014.05.011.","productDescription":"13 p.","startPage":"213","endPage":"225","numberOfPages":"13","ipdsId":"IP-049329","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":288145,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":288135,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.jhydrol.2014.05.011"}],"country":"United States","state":"Nevada","otherGeospatial":"Pahranagat Valley","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -115.313393,37.187186 ], [ -115.313393,37.618914 ], [ -115.025947,37.618914 ], [ -115.025947,37.187186 ], [ -115.313393,37.187186 ] ] ] } } ] }","volume":"517","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53ae7782e4b0abf75cf2c161","contributors":{"authors":[{"text":"Paces, James B. 0000-0002-9809-8493 jbpaces@usgs.gov","orcid":"https://orcid.org/0000-0002-9809-8493","contributorId":2514,"corporation":false,"usgs":true,"family":"Paces","given":"James","email":"jbpaces@usgs.gov","middleInitial":"B.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":494438,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wurster, Frederic C. 0000-0002-5393-2878 fred_wurster@fws.gov","orcid":"https://orcid.org/0000-0002-5393-2878","contributorId":74301,"corporation":false,"usgs":true,"family":"Wurster","given":"Frederic","email":"fred_wurster@fws.gov","middleInitial":"C.","affiliations":[],"preferred":false,"id":494439,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70173453,"text":"70173453 - 2014 - Comparative bioenergetics modeling of two Lake Trout morphotypes","interactions":[],"lastModifiedDate":"2016-06-20T12:20:20","indexId":"70173453","displayToPublicDate":"2014-06-06T06:30:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Comparative bioenergetics modeling of two Lake Trout morphotypes","docAbstract":"<p><span>Efforts to restore Lake Trout&nbsp;</span><i>Salvelinus namaycush</i><span>&nbsp;in the Laurentian Great Lakes have been hampered for decades by several factors, including overfishing and invasive species (e.g., parasitism by Sea Lampreys&nbsp;</span><i>Petromyzon marinus</i><span>&nbsp;and reproductive deficiencies associated with consumption of Alewives&nbsp;</span><i>Alosa pseudoharengus</i><span>). Restoration efforts are complicated by the presence of multiple body forms (i.e., morphotypes) of Lake Trout that differ in habitat utilization, prey consumption, lipid storage, and spawning preferences. Bioenergetics models constitute one tool that is used to help inform management and restoration decisions; however, bioenergetic differences among morphotypes have not been evaluated. The goal of this research was to investigate bioenergetic differences between two actively stocked morphotypes: lean and humper Lake Trout. We measured consumption and respiration rates across a wide range of temperatures (4&ndash;22&deg;C) and size-classes (5&ndash;100&nbsp;g) to develop bioenergetics models for juvenile Lake Trout. Bayesian estimation was used so that uncertainty could be propagated through final growth predictions. Differences between morphotypes were minimal, but when present, the differences were temperature and weight dependent. Basal respiration did not differ between morphotypes at any temperature or size-class. When growth and consumption differed between morphotypes, the differences were not consistent across the size ranges tested. Management scenarios utilizing the temperatures presently found in the Great Lakes (e.g., predicted growth at an average temperature of 11.7&deg;C and 14.4&deg;C during a 30-d period) demonstrated no difference in growth between the two morphotypes. Due to a lack of consistent differences between lean and humper Lake Trout, we developed a model that combined data from both morphotypes. The combined model yielded results similar to those of the morphotype-specific models, suggesting that accounting for morphotype differences may not be necessary in bioenergetics modeling of lean and humper Lake Trout.</span></p>","language":"English","publisher":"American Fisheries Society","doi":"10.1080/00028487.2014.954051","usgsCitation":"Kepler, M.V., Wagner, T., and Sweka, J.A., 2014, Comparative bioenergetics modeling of two Lake Trout morphotypes: Transactions of the American Fisheries Society, v. 143, no. 6, p. 1592-1604, https://doi.org/10.1080/00028487.2014.954051.","productDescription":"13 p.","startPage":"1592","endPage":"1604","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-052962","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":472948,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://figshare.com/articles/journal_contribution/Comparative_Bioenergetics_Modeling_of_Two_Lake_Trout_Morphotypes/1246729","text":"External Repository"},{"id":323990,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"143","issue":"6","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2014-10-30","publicationStatus":"PW","scienceBaseUri":"576913b4e4b07657d19fefed","contributors":{"authors":[{"text":"Kepler, Megan V.","contributorId":172106,"corporation":false,"usgs":false,"family":"Kepler","given":"Megan","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":639792,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wagner, Tyler 0000-0003-1726-016X twagner@usgs.gov","orcid":"https://orcid.org/0000-0003-1726-016X","contributorId":1050,"corporation":false,"usgs":true,"family":"Wagner","given":"Tyler","email":"twagner@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":637147,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sweka, John A.","contributorId":80945,"corporation":false,"usgs":true,"family":"Sweka","given":"John","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":639793,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70132329,"text":"70132329 - 2014 - A new clarification method to visualize biliary degeneration during liver metamorphosis in sea lamprey (<i>Petromyzon marinus</i>)","interactions":[],"lastModifiedDate":"2021-12-09T15:28:15.105111","indexId":"70132329","displayToPublicDate":"2014-06-06T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2498,"text":"Journal of Visualized Experiments","active":true,"publicationSubtype":{"id":10}},"title":"A new clarification method to visualize biliary degeneration during liver metamorphosis in sea lamprey (<i>Petromyzon marinus</i>)","docAbstract":"<p><span>Biliary atresia is a rare disease of infancy, with an estimated 1 in 15,000 frequency in the southeast United States, but more common in East Asian countries, with a reported frequency of 1 in 5,000 in Taiwan. Although much is known about the management of biliary atresia, its pathogenesis is still elusive. The sea lamprey (</span><i>Petromyzon marinus</i><span>) provides a unique opportunity to examine the mechanism and progression of biliary degeneration. Sea lamprey develop through three distinct life stages: larval, parasitic, and adult. During the transition from<span>&nbsp;</span></span>larvae<span><span>&nbsp;</span>to parasitic juvenile, sea lamprey undergo metamorphosis with dramatic reorganization and remodeling in external morphology and internal organs. In the liver, the entire biliary system is lost, including the gall bladder and the biliary tree. A newly-developed method called &ldquo;CLARITY&rdquo; was modified to clarify the entire liver and the junction with the intestine in metamorphic sea lamprey. The process of biliary degeneration was visualized and discerned during sea lamprey metamorphosis by using laser scanning confocal microscopy. This method provides a powerful tool to study biliary atresia in a unique animal model.</span></p>","language":"English","publisher":"JoVE","publisherLocation":"Cambridge, MA","doi":"10.3791/51648","usgsCitation":"Chung-Davidson, Y., Davidson, P.J., Scott, A.M., Walaszczyk, E.J., Brant, C.O., Buchinger, T., Johnson, N.S., and Li, W., 2014, A new clarification method to visualize biliary degeneration during liver metamorphosis in sea lamprey (<i>Petromyzon marinus</i>): Journal of Visualized Experiments, v. 88, e51648, https://doi.org/10.3791/51648.","productDescription":"e51648","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-052484","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":472949,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.3791/51648","text":"External Repository"},{"id":297315,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"88","noUsgsAuthors":false,"publicationDate":"2014-06-06","publicationStatus":"PW","scienceBaseUri":"54dd2b1ee4b08de9379b3255","contributors":{"authors":[{"text":"Chung-Davidson, Yu-Wen","contributorId":126742,"corporation":false,"usgs":false,"family":"Chung-Davidson","given":"Yu-Wen","email":"","affiliations":[{"id":6589,"text":"Department of Fisheries & Wildlife, Michigan State University","active":true,"usgs":false}],"preferred":false,"id":522773,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Davidson, Peter J.","contributorId":126743,"corporation":false,"usgs":false,"family":"Davidson","given":"Peter","email":"","middleInitial":"J.","affiliations":[{"id":6590,"text":"Department of Fisheries and Wildlife, Michigan State University","active":true,"usgs":false}],"preferred":false,"id":522774,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Scott, Anne M.","contributorId":126744,"corporation":false,"usgs":false,"family":"Scott","given":"Anne","email":"","middleInitial":"M.","affiliations":[{"id":6590,"text":"Department of Fisheries and Wildlife, Michigan State University","active":true,"usgs":false}],"preferred":false,"id":522775,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Walaszczyk, Erin J.","contributorId":126745,"corporation":false,"usgs":false,"family":"Walaszczyk","given":"Erin","email":"","middleInitial":"J.","affiliations":[{"id":6590,"text":"Department of Fisheries and Wildlife, Michigan State University","active":true,"usgs":false}],"preferred":false,"id":522776,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brant, Cory O.","contributorId":126746,"corporation":false,"usgs":false,"family":"Brant","given":"Cory","email":"","middleInitial":"O.","affiliations":[{"id":6590,"text":"Department of Fisheries and Wildlife, Michigan State University","active":true,"usgs":false}],"preferred":false,"id":522777,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Buchinger, Tyler","contributorId":126747,"corporation":false,"usgs":false,"family":"Buchinger","given":"Tyler","affiliations":[{"id":6590,"text":"Department of Fisheries and Wildlife, Michigan State University","active":true,"usgs":false}],"preferred":false,"id":522778,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Johnson, Nicholas S. 0000-0002-7419-6013 njohnson@usgs.gov","orcid":"https://orcid.org/0000-0002-7419-6013","contributorId":597,"corporation":false,"usgs":true,"family":"Johnson","given":"Nicholas","email":"njohnson@usgs.gov","middleInitial":"S.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":522772,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Li, Weiming","contributorId":126748,"corporation":false,"usgs":false,"family":"Li","given":"Weiming","email":"","affiliations":[{"id":6590,"text":"Department of Fisheries and Wildlife, Michigan State University","active":true,"usgs":false}],"preferred":false,"id":522779,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70111602,"text":"sir20145072 - 2014 - Concentrations, loads, and yields of total nitrogen and total phosphorus in the Barnegat Bay-Little Egg Harbor watershed, New Jersey, 1989-2011, at multiple spatial scales","interactions":[],"lastModifiedDate":"2014-06-05T14:55:51","indexId":"sir20145072","displayToPublicDate":"2014-06-05T14:39:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-5072","title":"Concentrations, loads, and yields of total nitrogen and total phosphorus in the Barnegat Bay-Little Egg Harbor watershed, New Jersey, 1989-2011, at multiple spatial scales","docAbstract":"<p>Concentrations, loads, and yields of nutrients (total nitrogen and total phosphorus) were calculated for the Barnegat Bay-Little Egg Harbor (BB-LEH) watershed for 1989–2011 at annual and seasonal (growing and nongrowing) time scales. Concentrations, loads, and yields were calculated at three spatial scales: for each of the 81 subbasins specified by 14-digit hydrologic unit codes (HUC-14s); for each of the three BB-LEH watershed segments, which coincide with segmentation of the BB-LEH estuary; and for the entire BB-LEH watershed. Base-flow and runoff values were calculated separately and were combined to provide total values.</p>\n<br/>\n<p>Available surface-water-quality data for all streams in the BB-LEH watershed for 1980–2011 were compiled from existing datasets and quality assured. Precipitation and streamflow data were used to distinguish between water-quality samples that were collected during base-flow conditions and those that were collected during runoff conditions. Base-flow separation of hydrographs of six streams in the BB-LEH watershed indicated that base flow accounts for about 72 to 94 percent of total flow in streams in the watershed.</p>\n<br/>\n<p>Base-flow mean concentrations (BMCs) of total nitrogen (TN) and total phosphorus (TP) for each HUC-14 subbasin were calculated from relations between land use and measured base-flow concentrations. These relations were developed from multiple linear regression models determined from water-quality data collected at sampling stations in the BB-LEH watershed under base-flow conditions and land-use percentages in the contributing drainage basins. The total watershed base-flow volume was estimated for each year and season from continuous streamflow records for 1989–2011 and relations between precipitation and streamflow during base-flow conditions. For each year and season, the base-flow load and yield were then calculated for each HUC-14 subbasin from the BMCs, total base-flow volume, and drainage area.</p>\n<br/>\n<p>The watershed-loading application PLOAD was used to calculate runoff concentrations, loads, and yields of TN and TP at the HUC-14 scale. Flow-weighted event-mean concentrations (EMCs) for runoff were developed for each major land-use type in the watershed using storm sampling data from four streams in the BB-LEH watershed and three streams outside the watershed. The EMCs were developed separately for the growing and nongrowing seasons, and were typically greater during the growing season. The EMCs, along with annual and seasonal precipitation amounts and percent imperviousness associated with land-use types, were used as inputs to PLOAD to calculate annual and seasonal runoff concentrations, loads, and yields at the HUC-14 scale.</p>\n<br/>\n<p>Over the period of study (1989–2011), total surface-water loads (base flow plus runoff) for the entire BB-LEH watershed for TN ranged from about 455,000 kilograms (kg) as N (1995) to 857,000 kg as N (2010). For TP, total loads for the watershed ranged from about 17,000 (1995) to 32,000 kg as P (2010). On average, the north segment accounted for about 66 percent of the annual TN load and 63 percent of the annual TP load, and the central and south segments each accounted for less than 20 percent of the nutrient loads. Loads and yields were strongly associated with precipitation patterns, ensuing hydrologic conditions, and land use. HUC-14 subbasins with the highest yields of nutrients are concentrated in the northern part of the watershed, and have the highest percentages of urban or agricultural land use. Subbasins with the lowest TN and TP yields are dominated by forest cover.</p>\n<br/>\n<p>Percentages of turf (lawn) cover and nonturf cover were estimated for the watershed. Of the developed land in the watershed, nearly one quarter (24.9 percent) was mapped as turf cover. Because there is a strong relation between percent turf and percent developed land, percent turf in the watershed typically increases with percent development, and the amount of development can be considered a reasonable predictor of the amount of turf cover in the watershed. In the BB-LEH watershed, calculated concentrations of TN and TP were greater for developed–turf areas than for developed–nonturf areas, which, in turn, were greater than those for undeveloped areas.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145072","collaboration":"Prepared in cooperation with the New England Interstate Water Pollution Control Commission","usgsCitation":"Baker, R.J., Wieben, C.M., Lathrop, R.G., and Nicholson, R.S., 2014, Concentrations, loads, and yields of total nitrogen and total phosphorus in the Barnegat Bay-Little Egg Harbor watershed, New Jersey, 1989-2011, at multiple spatial scales: U.S. Geological Survey Scientific Investigations Report 2014-5072, Report: vii, 64 p.; Table 13, https://doi.org/10.3133/sir20145072.","productDescription":"Report: vii, 64 p.; Table 13","numberOfPages":"76","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"1989-01-01","temporalEnd":"2011-12-31","ipdsId":"IP-039063","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":288123,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145072.jpg"},{"id":288120,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5072/"},{"id":288122,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5072/pdf/sir2014-5072.pdf"},{"id":288121,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2014/5072/table/sir2014-5072_table13-loads-huc.xlsx"}],"country":"United States","state":"New Jersey","otherGeospatial":"Barnegat Bay;Little Egg Harbor","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -74.6007,39.4669 ], [ -74.6007,40.2311 ], [ -73.9678,40.2311 ], [ -73.9678,39.4669 ], [ -74.6007,39.4669 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5391834fe4b06f80638265a0","contributors":{"authors":[{"text":"Baker, Ronald J. rbaker@usgs.gov","contributorId":1436,"corporation":false,"usgs":true,"family":"Baker","given":"Ronald","email":"rbaker@usgs.gov","middleInitial":"J.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":494374,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wieben, Christine M. 0000-0001-5825-5119 cwieben@usgs.gov","orcid":"https://orcid.org/0000-0001-5825-5119","contributorId":4270,"corporation":false,"usgs":true,"family":"Wieben","given":"Christine","email":"cwieben@usgs.gov","middleInitial":"M.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":494376,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lathrop, Richard G.","contributorId":63727,"corporation":false,"usgs":true,"family":"Lathrop","given":"Richard","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":494377,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nicholson, Robert S. rnichol@usgs.gov","contributorId":2283,"corporation":false,"usgs":true,"family":"Nicholson","given":"Robert","email":"rnichol@usgs.gov","middleInitial":"S.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":494375,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70103029,"text":"sir20145064 - 2014 - Continuous water-quality monitoring and regression analysis to estimate constituent concentrations and loads in the Red River of the North at Fargo and Grand Forks, North Dakota, 2003-12","interactions":[],"lastModifiedDate":"2017-10-12T20:13:26","indexId":"sir20145064","displayToPublicDate":"2014-06-05T12:51:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-5064","title":"Continuous water-quality monitoring and regression analysis to estimate constituent concentrations and loads in the Red River of the North at Fargo and Grand Forks, North Dakota, 2003-12","docAbstract":"<p>The Red River of the North (hereafter referred to as “Red River”) Basin is an important hydrologic region where water is a valuable resource for the region’s economy. Continuous water-quality monitors have been operated by the U.S. Geological Survey, in cooperation with the North Dakota Department of Health, Minnesota Pollution Control Agency, City of Fargo, City of Moorhead, City of Grand Forks, and City of East Grand Forks at the Red River at Fargo, North Dakota, from 2003 through 2012 and at Grand Forks, N.Dak., from 2007 through 2012. The purpose of the monitoring was to provide a better understanding of the water-quality dynamics of the Red River and provide a way to track changes in water quality. Regression equations were developed that can be used to estimate concentrations and loads for dissolved solids, sulfate, chloride, nitrate plus nitrite, total phosphorus, and suspended sediment using explanatory variables such as streamflow, specific conductance, and turbidity.</p>\n<br/>\n<p>Specific conductance was determined to be a significant explanatory variable for estimating dissolved solids concentrations at the Red River at Fargo and Grand Forks. The regression equations provided good relations between dissolved solid concentrations and specific conductance for the Red River at Fargo and at Grand Forks, with adjusted coefficients of determination of 0.99 and 0.98, respectively. Specific conductance, log-transformed streamflow, and a seasonal component were statistically significant explanatory variables for estimating sulfate in the Red River at Fargo and Grand Forks. Regression equations provided good relations between sulfate concentrations and the explanatory variables, with adjusted coefficients of determination of 0.94 and 0.89, respectively.</p>\n<br/>\n<p>For the Red River at Fargo and Grand Forks, specific conductance, streamflow, and a seasonal component were statistically significant explanatory variables for estimating chloride. For the Red River at Grand Forks, a time component also was a statistically significant explanatory variable for estimating chloride. The regression equations for chloride at the Red River at Fargo provided a fair relation between chloride concentrations and the explanatory variables, with an adjusted coefficient of determination of 0.66 and the equation for the Red River at Grand Forks provided a relatively good relation between chloride concentrations and the explanatory variables, with an adjusted coefficient of determination of 0.77.</p>\n<br/>\n<p>Turbidity and streamflow were statistically significant explanatory variables for estimating nitrate plus nitrite concentrations at the Red River at Fargo and turbidity was the only statistically significant explanatory variable for estimating nitrate plus nitrite concentrations at Grand Forks. The regression equation for the Red River at Fargo provided a relatively poor relation between nitrate plus nitrite concentrations, turbidity, and streamflow, with an adjusted coefficient of determination of 0.46. The regression equation for the Red River at Grand Forks provided a fair relation between nitrate plus nitrite concentrations and turbidity, with an adjusted coefficient of determination of 0.73. Some of the variability that was not explained by the equations might be attributed to different sources contributing nitrates to the stream at different times. Turbidity, streamflow, and a seasonal component were statistically significant explanatory variables for estimating total phosphorus at the Red River at Fargo and Grand Forks. The regression equation for the Red River at Fargo provided a relatively fair relation between total phosphorus concentrations, turbidity, streamflow, and season, with an adjusted coefficient of determination of 0.74. The regression equation for the Red River at Grand Forks provided a good relation between total phosphorus concentrations, turbidity, streamflow, and season, with an adjusted coefficient of determination of 0.87.</p>\n<br/>\n<p>For the Red River at Fargo, turbidity and streamflow were statistically significant explanatory variables for estimating suspended-sediment concentrations. For the Red River at Grand Forks, turbidity was the only statistically significant explanatory variable for estimating suspended-sediment concentration. The regression equation at the Red River at Fargo provided a good relation between suspended-sediment concentration, turbidity, and streamflow, with an adjusted coefficient of determination of 0.95. The regression equation for the Red River at Grand Forks provided a good relation between suspended-sediment concentration and turbidity, with an adjusted coefficient of determination of 0.96.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145064","collaboration":"Prepared in cooperation with the North Dakota Department of Health, Minnesota Pollution Control Agency, City of Fargo, City of Moorhead, City of Grand Forks, and City of East Grand Forks","usgsCitation":"Galloway, J.M., 2014, Continuous water-quality monitoring and regression analysis to estimate constituent concentrations and loads in the Red River of the North at Fargo and Grand Forks, North Dakota, 2003-12: U.S. Geological Survey Scientific Investigations Report 2014-5064, vi, 37 p., https://doi.org/10.3133/sir20145064.","productDescription":"vi, 37 p.","numberOfPages":"48","onlineOnly":"Y","temporalStart":"2003-01-01","temporalEnd":"2012-12-31","ipdsId":"IP-054797","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":288108,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5064/"},{"id":288109,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5064/pdf/sir2014-5064.pdf"},{"id":288110,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145064.jpg"}],"country":"United States","state":"North Dakota","city":"Grand Forks;Fargo","otherGeospatial":"Red River Of The North","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -100.9863,45.4996 ], [ -100.9863,49.0 ], [ -93.8342,49.0 ], [ -93.8342,45.4996 ], [ -100.9863,45.4996 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53918350e4b06f80638265a4","contributors":{"authors":[{"text":"Galloway, Joel M. 0000-0002-9836-9724 jgallowa@usgs.gov","orcid":"https://orcid.org/0000-0002-9836-9724","contributorId":1562,"corporation":false,"usgs":true,"family":"Galloway","given":"Joel","email":"jgallowa@usgs.gov","middleInitial":"M.","affiliations":[{"id":478,"text":"North Dakota Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":493093,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
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