{"pageNumber":"609","pageRowStart":"15200","pageSize":"25","recordCount":40828,"records":[{"id":70168816,"text":"70168816 - 2014 - Controls on methane released through ebullition in peatlands affected by permafrost degradation","interactions":[],"lastModifiedDate":"2016-03-04T10:31:50","indexId":"70168816","displayToPublicDate":"2014-03-28T11:30:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2320,"text":"Journal of Geophysical Research: Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"Controls on methane released through ebullition in peatlands affected by permafrost degradation","docAbstract":"

Permafrost thaw in peat plateaus leads to the flooding of surface soils and the formation of collapse scar bogs, which have the potential to be large emitters of methane (CH4) from surface peat as well as deeper, previously frozen, permafrost carbon (C). We used a network of bubble traps, permanently installed 20 cm and 60 cm beneath the moss surface, to examine controls on ebullition from three collapse bogs in interior Alaska. Overall, ebullition was dominated by episodic events that were associated with changes in atmospheric pressure, and ebullition was mainly a surface process regulated by both seasonal ice dynamics and plant phenology. The majority (>90%) of ebullition occurred in surface peat layers, with little bubble production in deeper peat. During periods of peak plant biomass, bubbles contained acetate-derived CH4 dominated (>90%) by modern C fixed from the atmosphere following permafrost thaw. Post-senescence, the contribution of CH4 derived from thawing permafrost C was more variable and accounted for up to 22% (on average 7%), in the most recently thawed site. Thus, the formation of thermokarst features resulting from permafrost thaw in peatlands stimulates ebullition and CH4 release both by creating flooded surface conditions conducive to CH4 production and bubbling as well as by exposing thawing permafrost C to mineralization.

","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Geophysical Research: Biogeosciences","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"American Geophysical Union","publisherLocation":"Richmond, VA","doi":"10.1002/2013JG002441","usgsCitation":"Klapstein, S.J., Turetsky, M.R., McGuire, A.D., Harden, J.W., Czimczik, C., Xu, X., Chanton, J., and Waddington, J.M., 2014, Controls on methane released through ebullition in peatlands affected by permafrost degradation: Journal of Geophysical Research: Biogeosciences, v. 119, no. 3, p. 418-431, https://doi.org/10.1002/2013JG002441.","productDescription":"14 p.","startPage":"418","endPage":"431","numberOfPages":"14","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-049471","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":473090,"rank":0,"type":{"id":41,"text":"Open Access External Repository 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The assessment of Great Lakes prey fish stocks have been conducted annually with bottom trawls since the 1970s by the Great Lakes Science Center, sometimes assisted by partner agencies. These stock assessments provide data on the status and trends of prey fish that are consumed by important commercial and recreational fishes. Although all these annual surveys are conducted using bottom trawls, they differ among the lakes in the proportion of the lake covered, seasonal timing, trawl gear used, and the manner in which the trawl is towed (across or along bottom contours). Because each assessment is unique, population indices were standardized to the highest value for a time series within each lake for the following prey species: Cisco (Coregonus artedi), Bloater (C. hoyi), Rainbow Smelt (Osmerus mordax), Alewife (Alosa pseudoharengus), and Round Goby (Neogobius melanostomus). In this report, standardized indices are presented in graphical form along with synopses to provide a short, informal cross-basin summary of the status and trends of principal prey fishes. There was basin-wide agreement in the trends of age-1 and older biomass for all prey species, with the highest concordance occurring for coregonids and Rainbow Smelt, and weaker concordance for Alewife. For coregonids, the highest biomass occurred from the mid-1980s to the mid-1990s. Rainbow Smelt biomass declined slowly and erratically during the last quarter century. Alewife biomass was generally higher from the early 1980s through 1990s across the Great Lakes, but since the early 1990s, trends have been divergent across the lakes, though there has been a downward trend in all lakes since 2005. Recently, Lake Huron has shown resurgence in biomass of Bloater, achieving 75% of its maximum record in 2012 due to recruitment of a succession of strong and moderate year classes that appeared in 2005-2011. Also, strong recruitment of the 2010 year class of Alewife has led to a sharp increase in biomass of Alewife in Lake Michigan. In general, trends in year-class strengths were less concordant across the basin and only coregonids showed statistical agreement across the upper Great Lakes. The appearance of strong and moderate year-classes of Bloater in Lake Huron in 2005- 2011 countered the trend of continuing weak year-classes of coregonids in Lakes Michigan and Superior. Not shown in our analysis is the appearance of the 2013 year-class of Bloater in Huron, the largest to date. There was no agreement in cross-basin trends in year-class strengths for Rainbow Smelt and Alewife, although there was agreement between pairs of lakes. Although there was statistical agreement in trends of age-0 and older Round Goby biomass among lakes where this species has successfully invaded (Michigan, Huron, Erie and Ontario), temporal patterns of biomass in each lake were different. Round Goby may be approaching equilibrium in Lake Erie, peaking in Lake Huron, and expanding in Lake Michigan. The trend in Lake Ontario remains unclear. Declining abundance in Lake Erie has corresponded with evidence that Round Goby have become increasingly incorporated into piscivore diets, e.g., Lake Trout, Walleye, Smallmouth Bass, Yellow Perch, and Burbot in Lakes Michigan, Huron, Erie, and Ontario. Round Goby continue to be absent from spring bottom trawl assessments in Lake Superior, but their presence in the harbors and embayments of Duluth and Thunder Bay (U.S. Geological Survey and Ontario Ministry of Natural Resources, unpublished data), suggests that there is potential for future colonization.

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]\n}","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"566ff64fe4b09cfe53ca799b","contributors":{"authors":[{"text":"Gorman, Owen T. 0000-0003-0451-110X otgorman@usgs.gov","orcid":"https://orcid.org/0000-0003-0451-110X","contributorId":2888,"corporation":false,"usgs":true,"family":"Gorman","given":"Owen","email":"otgorman@usgs.gov","middleInitial":"T.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":542169,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Weidel, Brian 0000-0001-6095-2773 bweidel@usgs.gov","orcid":"https://orcid.org/0000-0001-6095-2773","contributorId":2485,"corporation":false,"usgs":true,"family":"Weidel","given":"Brian","email":"bweidel@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":542170,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70073968,"text":"ofr20141003 - 2014 - Hydrologic Drought Decision Support System (HyDroDSS)","interactions":[],"lastModifiedDate":"2014-03-27T14:22:43","indexId":"ofr20141003","displayToPublicDate":"2014-03-27T14:06:00","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":"2014-1003","title":"Hydrologic Drought Decision Support System (HyDroDSS)","docAbstract":"

The hydrologic drought decision support system (HyDroDSS) was developed by the U.S. Geological Survey (USGS) in cooperation with the Rhode Island Water Resources Board (RIWRB) for use in the analysis of hydrologic variables that may indicate the risk for streamflows to be below user-defined flow targets at a designated site of interest, which is defined herein as data-collection site on a stream that may be adversely affected by pumping. Hydrologic drought is defined for this study as a period of lower than normal streamflows caused by precipitation deficits and (or) water withdrawals. The HyDroDSS is designed to provide water managers with risk-based information for balancing water-supply needs and aquatic-habitat protection goals to mitigate potential effects of hydrologic drought.

\n
\n

This report describes the theory and methods for retrospective streamflow-depletion analysis, rank correlation analysis, and drought-projection analysis. All three methods are designed to inform decisions made by drought steering committees and decisionmakers on the basis of quantitative risk assessment. All three methods use estimates of unaltered streamflow, which is the measured or modeled flow without major withdrawals or discharges, to approximate a natural low-flow regime.

\n
\n

Retrospective streamflow-depletion analysis can be used by water-resource managers to evaluate relations between withdrawal plans and the potential effects of withdrawal plans on streams at one or more sites of interest in an area. Retrospective streamflow-depletion analysis indicates the historical risk of being below user-defined flow targets if different pumping plans were implemented for the period of record. Retrospective streamflow-depletion analysis also indicates the risk for creating hydrologic drought conditions caused by use of a pumping plan. Retrospective streamflow-depletion analysis is done by calculating the net streamflow depletions from withdrawals and discharges and applying these depletions to a simulated record of unaltered streamflow.

\n
\n

Rank correlation analysis in the HyDroDSS indicates the persistence of hydrologic measurements from month to month for the prediction of developing hydrologic drought conditions and quantitatively indicates which hydrologic variables may be used to indicate the onset of hydrologic drought conditions. Rank correlation analysis also indicates the potential use of each variable for estimating the monthly minimum unaltered flow at a site of interest for use in the drought-projection analysis. Rank correlation analysis in the HyDroDSS is done by calculating Spearman’s rho for paired samples and the 95-percent confidence limits of this rho value. Rank correlation analysis can be done by using precipitation, groundwater levels, measured streamflows, and estimated unaltered streamflows. Serial correlation analysis, which indicates relations between current and future values, can be done for a single site. Cross correlation analysis, which indicates relations among current values at one site and current and future values at a second site, also can be done.

\n
\n

Drought-projection analysis in the HyDroDSS indicates the risk for being in a hydrologic drought condition during the current month and the five following months with and without pumping. Drought-projection analysis also indicates the potential effectiveness of water-conservation methods for mitigating the effect of withdrawals in the coming months on the basis of the amount of depletion caused by different pumping plans and on the risk of unaltered flows being below streamflow targets. Drought-projection analysis in the HyDroDSS is done with Monte Carlo methods by using the position analysis method. In this method the initial value of estimated unaltered streamflows is calculated by correlation to a measured hydrologic variable (monthly precipitation, groundwater levels, or streamflows from an index station identified with the rank correlation analysis). Then a pseudorandom number generator is used to create 251 six-month-long flow traces by using a bootstrap method. Serial correlation of the estimated unaltered monthly minimum streamflows determined from the rank correlation analysis is preserved within each flow trace. The sample of unaltered streamflows indicates the risk of being below flow targets in the coming months under simulated natural conditions (without historic withdrawals). The streamflow-depletion algorithms are then used to estimate risks of flow being below targets if selected pumping plans are used.

\n
\n

This report also describes the implementation of the HyDroDSS. The HyDroDSS was developed as a Microsoft Access® database application to facilitate storage, handling, and use of hydrologic datasets with a simple graphical user interface. The program is implemented in the database by using the Visual Basic for Applications® (VBA) programming language. Program source code for the analytical techniques is provided in the HyDroDSS and in electronic text files accompanying this report. Program source code for the graphical user interface and for data-handling code, which is specific to Microsoft Access® and the HyDroDSS, is provided in the database. An installation package with a run-time version of the software is available with this report for potential users who do not have a compatible copy of Microsoft Access®. Administrative rights are needed to install this version of the HyDroDSS.

\n
\n

A case study, to demonstrate the use of HyDroDSS and interpretation of results for a site of interest, is detailed for the USGS streamgage on the Hunt River (station 01117000) near East Greenwich in central Rhode Island. The Hunt River streamgage was used because it has a long record of streamflow and is in a well-studied basin with a substantial amount of hydrologic and water-use data including groundwater pumping for municipal water supply.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141003","collaboration":"Prepared in cooperation with the Rhode Island Water Resources Board","usgsCitation":"Granato, G., 2014, Hydrologic Drought Decision Support System (HyDroDSS): U.S. Geological Survey Open-File Report 2014-1003, Report: x, 91 p.; Make CD by ISO package, https://doi.org/10.3133/ofr20141003.","productDescription":"Report: x, 91 p.; Make CD by ISO package","numberOfPages":"118","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-042923","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":285061,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141003.jpg"},{"id":285059,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2014/1003/ofr2014-1003_CDROM.iso"},{"id":285057,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1003/"},{"id":285058,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1003/pdf/ofr2014-1003.pdf"}],"projection":"Rhode Island state plane projection","country":"United States","state":"Rhode Island","city":"East Greenwich","otherGeospatial":"Hunt River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -71.575284,41.507592 ], [ -71.575284,41.674953 ], [ -71.426104,41.674953 ], [ -71.426104,41.507592 ], [ -71.575284,41.507592 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53517047e4b05569d805a262","contributors":{"authors":[{"text":"Granato, Gregory E. 0000-0002-2561-9913 ggranato@usgs.gov","orcid":"https://orcid.org/0000-0002-2561-9913","contributorId":1692,"corporation":false,"usgs":true,"family":"Granato","given":"Gregory E.","email":"ggranato@usgs.gov","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":false,"id":489307,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70093764,"text":"sir20145029 - 2014 - Hydrogeologic framework and salinity distribution of the Floridan aquifer system of Broward County, Florida","interactions":[],"lastModifiedDate":"2014-03-27T10:09:44","indexId":"sir20145029","displayToPublicDate":"2014-03-27T09:58:00","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":"2014-5029","title":"Hydrogeologic framework and salinity distribution of the Floridan aquifer system of Broward County, Florida","docAbstract":"

Concerns about water-level decline and seawater intrusion in the surficial Biscayne aquifer, currently the principal source of water supply to Broward County, prompted a study to refine the hydrogeologic framework of the underlying Floridan aquifer system to evaluate its potential as an alternative source of supply. This report presents cross sections that illustrate the stratigraphy and hydrogeology in eastern Broward County; maps of the upper surfaces and thicknesses of several geologic formations or units within the Floridan aquifer system; and maps of two of the potentially productive water-bearing zones within the system, the Upper Floridan aquifer and the Avon Park permeable zone.

\n
\n

An analysis of data on rock depositional textures, associated pore networks, and flow zones in the Floridan aquifer system shows that groundwater moves through the system in two ways. These data support a conceptual, dual-porosity model of the system wherein groundwater moves either as concentrated flow in discrete, thin bedding-plane vugs or zones of vuggy megaporosity, or as diffuse flow through rocks with primarily interparticle and moldic-particle porosity. Because considerable exchange of groundwater may occur between the zones of vuggy and matrix-dominated porosity, understanding the distribution of that porosity and flow zone types is important to evaluating the suitability of the several units within the Floridan aquifer system for managing the water through practices such as aquifer storage and recovery (ASR).

\n
\n

The salinity of the water in the Floridan aquifer system is highest in the central part of the study area, and lower toward the north and south. Although salinity generally increases with depth, in the western part of the study area a zone of relatively high saline water is perched above water of lower salinity in the underlying Avon Park permeable zone. Overall, the areas of highest salinity in the aquifer system coincide with those with the lowest estimated transmissivity, so that the occurrence of perched saline water in the system may be the consequence of incompletely flushed connate water or intruded seawater.

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\n

A seismic reflection profile along the Hillsboro Canal, at the northern edge of the study area, shows seven seismic-sag structures that are interpreted as downward deformation of overlying strata into collapsed deep cave systems. These structures may compromise the integrity of the confinement created by the underlying strata by allowing upconing of saline water from depth, which has implications for successful application of ASR and use of the Floridan aquifer system as an alternative water supply.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145029","collaboration":"Prepared in cooperation with Broward County, Florida","usgsCitation":"Reese, R.S., and Cunningham, K.J., 2014, Hydrogeologic framework and salinity distribution of the Floridan aquifer system of Broward County, Florida: U.S. Geological Survey Scientific Investigations Report 2014-5029, Report: vii, 60 p.; Appendix; Plate Directory, https://doi.org/10.3133/sir20145029.","productDescription":"Report: vii, 60 p.; Appendix; Plate Directory","numberOfPages":"72","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-026662","costCenters":[{"id":285,"text":"Florida Water Science Center","active":false,"usgs":true}],"links":[{"id":285022,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145029.jpg"},{"id":285020,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5029/appendix"},{"id":285021,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2014/5029/plates"},{"id":285018,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5029/"},{"id":285019,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5029/pdf/sir2014-5029.pdf"}],"projection":"Albers Equal Area Conic Projection","datum":"North American Datum 1983","country":"United States","state":"Florida","county":"Broward County","otherGeospatial":"Hillsboro Canal","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -80.37981,25.949959 ], [ -80.37981,26.37992 ], [ -80.060996,26.37992 ], [ -80.060996,25.949959 ], [ -80.37981,25.949959 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53517047e4b05569d805a25d","contributors":{"authors":[{"text":"Reese, Ronald S. rsreese@usgs.gov","contributorId":1090,"corporation":false,"usgs":true,"family":"Reese","given":"Ronald","email":"rsreese@usgs.gov","middleInitial":"S.","affiliations":[],"preferred":true,"id":490204,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cunningham, Kevin J. 0000-0002-2179-8686 kcunning@usgs.gov","orcid":"https://orcid.org/0000-0002-2179-8686","contributorId":1689,"corporation":false,"usgs":true,"family":"Cunningham","given":"Kevin","email":"kcunning@usgs.gov","middleInitial":"J.","affiliations":[{"id":269,"text":"FLWSC-Ft. Lauderdale","active":true,"usgs":true}],"preferred":true,"id":490205,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70099773,"text":"70099773 - 2014 - The role of landscape features and density dependence in growth and fledging rates of Piping Plovers in North Dakota, USA","interactions":[],"lastModifiedDate":"2017-08-31T11:01:50","indexId":"70099773","displayToPublicDate":"2014-03-27T09:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":996,"text":"BioOne","active":true,"publicationSubtype":{"id":10}},"title":"The role of landscape features and density dependence in growth and fledging rates of Piping Plovers in North Dakota, USA","docAbstract":"For species with precocial young, survival from hatching to fledging is a key factor influencing recruitment. Furthermore, growth rates of precocial chicks are an indicator of forage quality and habitat suitability of brood-rearing areas. We examined how growth and fledging rates of Piping Plover (Charadrius melodus) chicks were influenced by landscape features, such as hatchling density (hatchlings per hectare of remotely sensed habitat [H ha-1]), island vs. mainland, and wind fetch (exposure to waves) at 2-km segments (n ¼ 15) of Lake Sakakawea, North Dakota, during 2007–2008. Hatchling growth was comparable with published estimates for other habitats. Models for fledging rate (fledged young per segment) assuming density dependence had more support (wi ¼ 96%) than those assuming density independence (wi ¼ 4%). Density-dependent processes appeared to influence fledging rate only at densities .5 H ha-1, which occurred in 19% of the segments we sampled. When areas with densities .5 H ha-1 were excluded, density-dependence and density-independence models were equally supported (wi ¼ 52% and 48%, respectively). Fledging rate declined as the wind fetch of a segment increased. Fledging rate on mainland shorelines was 4.3 times greater than that on islands. Previous work has indicated that plovers prefer islands for nesting, but our results suggest that this preference is not optimal and could lead to an ecological trap for chicks. While other researchers have found nesting-habitat requirements to be gravelly areas on exposed beaches without fine-grain substrates, our results suggest that chicks fledge at lower rates in these habitats. Thus, breeding plovers likely require complexes of these nesting habitats along with protected areas with fine, nutrient-rich substrate for foraging by hatchlings.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"BioOne","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"The Condor","doi":"10.1650/CONDOR-13-001-R1.1","usgsCitation":"Anteau, M.J., Wiltermuth, M.T., Sherfy, M.H., Shaffer, T.L., and Pearse, A.T., 2014, The role of landscape features and density dependence in growth and fledging rates of Piping Plovers in North Dakota, USA: BioOne, v. 116, no. 2, p. 195-204, https://doi.org/10.1650/CONDOR-13-001-R1.1.","productDescription":"10 p.","startPage":"195","endPage":"204","ipdsId":"IP-041459","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":473091,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1650/condor-13-001-r1.1","text":"Publisher Index Page"},{"id":285024,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":284952,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1650/CONDOR-13-001-R1.1"}],"country":"United States","state":"North Dakota","otherGeospatial":"Lake Sakakawea","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -103.5771,47.4491 ], [ -103.5771,48.1718 ], [ -101.2537,48.1718 ], [ -101.2537,47.4491 ], [ -103.5771,47.4491 ] ] ] } } ] }","volume":"116","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53517069e4b05569d805a403","contributors":{"authors":[{"text":"Anteau, Michael J. 0000-0002-5173-5870 manteau@usgs.gov","orcid":"https://orcid.org/0000-0002-5173-5870","contributorId":3427,"corporation":false,"usgs":true,"family":"Anteau","given":"Michael","email":"manteau@usgs.gov","middleInitial":"J.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":492021,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wiltermuth, Mark T. 0000-0002-8871-2816 mwiltermuth@usgs.gov","orcid":"https://orcid.org/0000-0002-8871-2816","contributorId":708,"corporation":false,"usgs":true,"family":"Wiltermuth","given":"Mark","email":"mwiltermuth@usgs.gov","middleInitial":"T.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":492018,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sherfy, Mark H. 0000-0003-3016-4105 msherfy@usgs.gov","orcid":"https://orcid.org/0000-0003-3016-4105","contributorId":125,"corporation":false,"usgs":true,"family":"Sherfy","given":"Mark","email":"msherfy@usgs.gov","middleInitial":"H.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":492017,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shaffer, Terry L. 0000-0001-6950-8951 tshaffer@usgs.gov","orcid":"https://orcid.org/0000-0001-6950-8951","contributorId":3192,"corporation":false,"usgs":true,"family":"Shaffer","given":"Terry","email":"tshaffer@usgs.gov","middleInitial":"L.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":492020,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pearse, Aaron T. 0000-0002-6137-1556 apearse@usgs.gov","orcid":"https://orcid.org/0000-0002-6137-1556","contributorId":1772,"corporation":false,"usgs":true,"family":"Pearse","given":"Aaron","email":"apearse@usgs.gov","middleInitial":"T.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":492019,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70095888,"text":"ofr20141052 - 2014 - Monitoring fine-sediment volume in the Colorado River ecosystem, Arizona: construction and analysis of digital elevation models","interactions":[],"lastModifiedDate":"2014-03-27T08:31:20","indexId":"ofr20141052","displayToPublicDate":"2014-03-27T08:23:00","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":"2014-1052","title":"Monitoring fine-sediment volume in the Colorado River ecosystem, Arizona: construction and analysis of digital elevation models","docAbstract":"

Digital elevation models (DEMs) of eleven 2–5 kilometer reaches of the Colorado River ecosystem (CRE) in Grand Canyon were constructed from repeat bathymetric and topographic surveys collected between August 2000 and December 2004. The DEMs will be used by researchers to study the effects of Glen Canyon Dam (GCD) operations on the sediment resources of the CRE in Grand Canyon by quantifying morphological changes and sediment transfer within and among the study reaches.

\n
\n

Airborne surveys collected light detection and ranging (lidar) and photogrammetric data, whereas ground topographic and bathymetric data were collected simultaneously on river trips. Surveys were conducted in August 2000, September 2000, May 2002, May 2004, November 2004, and December 2004. The aerial lidar and photogrammetric data were merged with the ground topographic and bathymetric data to create DEMs of the study areas with a grid resolution of 1 meter. For each survey period, the vertical component of uncertainty (specifically, reproducibility or precision) was estimated for each data type (lidar/photogrammetry, ground surveys, bathymetry) and for two different types of bed-surface texture (smooth and rough).

\n
\n

The resulting DEMs from this study are a valuable contribution to ongoing efforts in assessing the effects of GCD operations on the CRE. The DEMs can be used to map the spatial characteristics of geomorphic change within the study reaches and to estimate sediment budgets for different time periods by calculating the difference in sediment volume between surveys. In addition, the DEMs provide essential boundary conditions for numerical models of sediment transport and deposition, as well as help define the spatial distribution of habitat for fisheries investigations.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141052","collaboration":"Prepared in cooperation with Northern Arizona University","usgsCitation":"Kaplinski, M., Hazel, J., Grams, P.E., and Davis, P.A., 2014, Monitoring fine-sediment volume in the Colorado River ecosystem, Arizona: construction and analysis of digital elevation models: U.S. Geological Survey Open-File Report 2014-1052, Report: v, 29 p.; Appendix 1; Digital products, https://doi.org/10.3133/ofr20141052.","productDescription":"Report: v, 29 p.; Appendix 1; Digital products","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-043600","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":285009,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141052.jpg"},{"id":285006,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1052/pdf/ofr2014-1052.pdf"},{"id":285008,"type":{"id":7,"text":"Companion Files"},"url":"https://www.gcmrc.gov/research_areas/sediment_geomorphology/downloads/OFR_2014_1052/"},{"id":285007,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2014/1052/pdf/ofr2014-1052_Appendix.pdf"},{"id":285005,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1052/"}],"projection":"1983 Arizona State Plane","datum":"North American Datum 1983","country":"United States","state":"Arizona","otherGeospatial":"Colorado River;Grand Canyon","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -114.2468,35.003 ], [ -114.2468,37.2631 ], [ -110.6625,37.2631 ], [ -110.6625,35.003 ], [ -114.2468,35.003 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53517056e4b05569d805a339","contributors":{"authors":[{"text":"Kaplinski, Matt","contributorId":65817,"corporation":false,"usgs":true,"family":"Kaplinski","given":"Matt","affiliations":[],"preferred":false,"id":491465,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hazel, Joseph E. Jr.","contributorId":91819,"corporation":false,"usgs":true,"family":"Hazel","given":"Joseph E.","suffix":"Jr.","affiliations":[],"preferred":false,"id":491466,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Grams, Paul E. 0000-0002-0873-0708 pgrams@usgs.gov","orcid":"https://orcid.org/0000-0002-0873-0708","contributorId":1830,"corporation":false,"usgs":true,"family":"Grams","given":"Paul","email":"pgrams@usgs.gov","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":491464,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Davis, Philip A. pdavis@usgs.gov","contributorId":692,"corporation":false,"usgs":true,"family":"Davis","given":"Philip","email":"pdavis@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":491463,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70048989,"text":"sir20135204 - 2014 - Acute and chronic sensitivity of white sturgeon (Acipenser transmontanus) and rainbow trout (Oncorhynchus mykiss) to cadmium, copper, lead, or zinc in laboratory water-only exposures","interactions":[],"lastModifiedDate":"2014-03-26T12:59:41","indexId":"sir20135204","displayToPublicDate":"2014-03-26T12:54:00","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":"2013-5204","title":"Acute and chronic sensitivity of white sturgeon (Acipenser transmontanus) and rainbow trout (Oncorhynchus mykiss) to cadmium, copper, lead, or zinc in laboratory water-only exposures","docAbstract":"

White sturgeon (Acipenser transmontanus) are experiencing poor recruitment in the trans boundary reach of the upper Columbia River in eastern Washington State. Limited toxicity data indicated that early life stages of white sturgeon are sensitive to metals. In acute 4-day (d) exposures with larval white sturgeon, previous studies have reported that the 4-day median lethal concentrations (LC50) based on biotic ligand model (BLM) normalization for copper were below the U.S. Environmental Protection Agency national recommended acute water-quality criterion. In previously published chronic 66-d exposures starting with newly fertilized eggs of white sturgeon, 20-percent lethal effect concentrations (LC20s) for copper, cadmium, or zinc generally were within a factor of two of the chronic values of the most sensitive fish species in the databases of the U.S. Environmental Protection Agency water-quality criteria (WQC) for the three metals. However, there were some uncertainties in the chronic exposures previously performed with white sturgeon, including (1) low control survival (37 percent), (2) more control fish tested in each replicate compared to other treatments, (3) limited replication of treatments (n=2), (4) lack of reported growth data (such as dry weight), and (5) wide dilution factors for exposure concentrations (6- to 8-fold dilutions). The U.S. Environmental Protection Agency concluded that additional studies are needed to generate more toxicity data to better define lethal and sublethal toxicity thresholds for metals for white sturgeon.

\n
\n

The objective of the study was to further evaluate the acute and chronic toxicity of cadmium, copper, lead, or zinc to early life stages of white sturgeon in water-only exposures. Toxicity tests also were performed with commonly tested rainbow trout (Oncorhynchus mykiss) under similar test conditions to determine the relative sensitivity between white sturgeon and rainbow trout to these metals. Toxicity data generated from this study were used to evaluate the sensitivity of early life stages of white sturgeon and rainbow trout relative to data published for other test organisms. Toxicity data generated from this study also were used to evaluate the level of protection of U.S. Environmental Protection Agency WQC or Washington State water-quality standards (WQS) for copper, zinc, cadmium, or lead to white sturgeon inhabiting the upper Columbia River.

\n
\n

Chapter A of this report summarizes the results of acute toxicity tests performed for 4 d with white sturgeon and rainbow trout exposed to copper, cadmium, or zinc. Chapter B of this report summarizes the results of chronic toxicity tests performed for as many as 53 days with white sturgeon or rainbow trout exposed to copper, cadmium, zinc, or lead. Appendixes to the report are available at http://pubs.usgs.gov/sir/2013/5204. Supporting documentation for chapter A toxicity testing is provided in appendix 1. Supporting documentation for chapter B toxicity testing is provided in Appendix 2. Supporting documentation on analysis of water chemistry for chapter A and chapter B is provided in appendix 3 and 4. The rationale for applying corrections to measured copper and zinc values in water samples from some of the toxicity tests performed in chapter A is provided in appendix 5. A summary of dissolved organic carbon measurement variability and implications for biotic ligand model normalization for toxicity data summarized in chapter A and chapter B are provided in appendix 6. An evaluation of an interlaboratory comparison of analyses for dissolved organic carbon in water from the U.S. Geological Survey Columbia Environmental Research Center and University of Saskatchewan is provided in appendix 7. Finally, appendix 8 provides a summary of retesting of white sturgeon in 2012 to determine if improved survival of sturgeon would affect copper effect concentrations in 24-d copper exposures started with newly hatched larvae, and to evaluate the effect of light intensity or temperature on the response of newly hatched larvae during a 25-d study.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135204","issn":"2328-0328","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency and Teck American, Inc.","usgsCitation":"Ingersoll, C.G., Contributions by Wang, N., Calfee, R.D., Beahan, E., Brumbaugh, W.G., Dorman, R.A., Hardesty, D.K., Kunz, J.L., Little, E.E., Mebane, C.A., and Puglis, H.J., 2014, Acute and chronic sensitivity of white sturgeon (Acipenser transmontanus) and rainbow trout (Oncorhynchus mykiss) to cadmium, copper, lead, or zinc in laboratory water-only exposures: U.S. Geological Survey Scientific Investigations Report 2013-5204, Report: viii, 76 p.; Downloads Directory, https://doi.org/10.3133/sir20135204.","productDescription":"Report: viii, 76 p.; Downloads Directory","numberOfPages":"88","onlineOnly":"Y","ipdsId":"IP-042908","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":284956,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5204/"},{"id":284957,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5204/pdf/sir2013-5204.pdf"},{"id":284958,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2013/5204/downloads/"},{"id":284959,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135204.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd4b24e4b0b290850f02f6","contributors":{"authors":[{"text":"Ingersoll, Christopher G. 0000-0003-4531-5949 cingersoll@usgs.gov","orcid":"https://orcid.org/0000-0003-4531-5949","contributorId":2071,"corporation":false,"usgs":true,"family":"Ingersoll","given":"Christopher","email":"cingersoll@usgs.gov","middleInitial":"G.","affiliations":[{"id":192,"text":"Columbia Environmental Research 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Erinn","contributorId":13893,"corporation":false,"usgs":true,"family":"Beahan","given":"Erinn","email":"","affiliations":[],"preferred":false,"id":485947,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brumbaugh, William G. 0000-0003-0081-375X bbrumbaugh@usgs.gov","orcid":"https://orcid.org/0000-0003-0081-375X","contributorId":493,"corporation":false,"usgs":true,"family":"Brumbaugh","given":"William","email":"bbrumbaugh@usgs.gov","middleInitial":"G.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":485941,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dorman, Rebecca A. 0000-0002-5748-7046","orcid":"https://orcid.org/0000-0002-5748-7046","contributorId":28522,"corporation":false,"usgs":true,"family":"Dorman","given":"Rebecca","email":"","middleInitial":"A.","affiliations":[{"id":192,"text":"Columbia Environmental Research 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elittle@usgs.gov","orcid":"https://orcid.org/0000-0003-0034-3639","contributorId":1746,"corporation":false,"usgs":true,"family":"Little","given":"Edward","email":"elittle@usgs.gov","middleInitial":"E.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":485942,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Mebane, Christopher A. 0000-0002-9089-0267 cmebane@usgs.gov","orcid":"https://orcid.org/0000-0002-9089-0267","contributorId":110,"corporation":false,"usgs":true,"family":"Mebane","given":"Christopher","email":"cmebane@usgs.gov","middleInitial":"A.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":485940,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Puglis, Holly J. 0000-0002-3090-6597 hpuglis@usgs.gov","orcid":"https://orcid.org/0000-0002-3090-6597","contributorId":4686,"corporation":false,"usgs":true,"family":"Puglis","given":"Holly","email":"hpuglis@usgs.gov","middleInitial":"J.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":485946,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70099631,"text":"fs20143022 - 2014 - The 3D Elevation Program: summary for Montana","interactions":[],"lastModifiedDate":"2016-08-17T15:46:29","indexId":"fs20143022","displayToPublicDate":"2014-03-25T14:50:00","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":"2014-3022","title":"The 3D Elevation Program: summary for Montana","docAbstract":"

Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, national security, recreation, and many others. For the State of Montana, elevation data are critical for flood risk management, infrastructure and construction management, agriculture and precision farming, geologic resource assessment and hazard mitigation, natural resources conservation, and other business uses. Today, high-density light detection and ranging (lidar) data are the primary sources for deriving elevation models and other datasets. Federal, State, Tribal, and local agencies work in partnership to (1) replace data that are older and of lower quality and (2) provide coverage where publicly accessible data do not exist. A joint goal of State and Federal partners is to acquire consistent, statewide coverage to support existing and emerging applications enabled by lidar data.

\n

The National Enhanced Elevation Assessment evaluated multiple elevation data acquisition options to determine the optimal data quality and data replacement cycle relative to cost to meet the identified requirements of the user community. The evaluation demonstrated that lidar acquisition at quality level 2 for the conterminous United States and quality level 5 ifsar data for Alaska with a 6- to 10-year acquisition cycle provided the highest benefit/cost ratios. The new 3D Elevation Program (3DEP) initiative selected an 8-year acquisition cycle for the respective quality levels. 3DEP, managed by the U.S. Geological Survey (USGS), the Office of Management and Budget Circular A–16 lead agency for terrestrial elevation data, responds to the growing need for high-quality topographic data and a wide range of other 3D representations of the Nation’s natural and constructed features.

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William J. Jr. carswell@usgs.gov","contributorId":1787,"corporation":false,"usgs":true,"family":"Carswell","given":"William J.","suffix":"Jr.","email":"carswell@usgs.gov","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":false,"id":491994,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70099605,"text":"70099605 - 2014 - Land cover and topography affect the land transformation caused by wind facilities","interactions":[],"lastModifiedDate":"2014-03-25T11:25:28","indexId":"70099605","displayToPublicDate":"2014-03-25T11:22:00","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":"Land cover and topography affect the land transformation caused by wind facilities","docAbstract":"Land transformation (ha of surface disturbance/MW) associated with wind facilities shows wide variation in its reported values. In addition, no studies have attempted to explain the variation across facilities. We digitized land transformation at 39 wind facilities using high resolution aerial imagery. We then modeled the effects of turbine size, configuration, land cover, and topography on the levels of land transformation at three spatial scales. The scales included strings (turbines with intervening roads only), sites (strings with roads connecting them, buried cables and other infrastructure), and entire facilities (sites and the roads or transmission lines connecting them to existing infrastructure). An information theoretic modeling approach indicated land cover and topography were well-supported variables affecting land transformation, but not turbine size or configuration. Tilled landscapes, despite larger distances between turbines, had lower average land transformation, while facilities in forested landscapes generally had the highest land transformation. At site and string scales, flat topographies had the lowest land transformation, while facilities on mesas had the largest. The results indicate the landscape in which the facilities are placed affects the levels of land transformation associated with wind energy. This creates opportunities for optimizing wind energy production while minimizing land cover change. In addition, the results indicate forecasting the impacts of wind energy on land transformation should include the geographic variables affecting land transformation reported here.","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.0088914","usgsCitation":"Diffendorfer, J.E., and Compton, R.W., 2014, Land cover and topography affect the land transformation caused by wind facilities: PLoS ONE, v. 9, no. 2, 7 p., https://doi.org/10.1371/journal.pone.0088914.","productDescription":"7 p.","numberOfPages":"7","ipdsId":"IP-049019","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":473092,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0088914","text":"Publisher Index Page"},{"id":284859,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":284841,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1371/journal.pone.0088914"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 173.0,16.916667 ], [ 173.0,71.833333 ], [ -66.95,71.833333 ], [ -66.95,16.916667 ], [ 173.0,16.916667 ] ] ] } } ] }","volume":"9","issue":"2","noUsgsAuthors":false,"publicationDate":"2014-02-18","publicationStatus":"PW","scienceBaseUri":"53517051e4b05569d805a2fb","contributors":{"authors":[{"text":"Diffendorfer, Jay E. 0000-0003-1093-6948 jediffendorfer@usgs.gov","orcid":"https://orcid.org/0000-0003-1093-6948","contributorId":55137,"corporation":false,"usgs":true,"family":"Diffendorfer","given":"Jay","email":"jediffendorfer@usgs.gov","middleInitial":"E.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":false,"id":491978,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Compton, Roger W. rwcompton@usgs.gov","contributorId":2780,"corporation":false,"usgs":true,"family":"Compton","given":"Roger","email":"rwcompton@usgs.gov","middleInitial":"W.","affiliations":[],"preferred":true,"id":491977,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70099278,"text":"70099278 - 2014 - 1DTempPro: analyzing temperature profiles for groundwater/surface-water exchange","interactions":[],"lastModifiedDate":"2018-09-14T16:04:54","indexId":"70099278","displayToPublicDate":"2014-03-25T10:06:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1861,"text":"Ground Water","active":true,"publicationSubtype":{"id":10}},"title":"1DTempPro: analyzing temperature profiles for groundwater/surface-water exchange","docAbstract":"A new computer program, 1DTempPro, is presented for the analysis of vertical one-dimensional (1D) temperature profiles under saturated flow conditions. 1DTempPro is a graphical user interface to the U.S. Geological Survey code Variably Saturated 2-Dimensional Heat Transport (VS2DH), which numerically solves the flow and heat-transport equations. Pre- and postprocessor features allow the user to calibrate VS2DH models to estimate vertical groundwater/surface-water exchange and also hydraulic conductivity for cases where hydraulic head is known.","language":"English","publisher":"National Ground Water Association","doi":"10.1111/gwat.12051","usgsCitation":"Voytek, E.B., Drenkelfuss, A., Day-Lewis, F.D., Healy, R., Lane, J.W., and Werkema, D.D., 2014, 1DTempPro: analyzing temperature profiles for groundwater/surface-water exchange: Ground Water, v. 52, no. 2, p. 298-302, https://doi.org/10.1111/gwat.12051.","productDescription":"5 p.","startPage":"298","endPage":"302","numberOfPages":"5","ipdsId":"IP-042740","costCenters":[{"id":496,"text":"Office of Groundwater-Branch of Geophysics","active":false,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":284767,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":284376,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/gwat.12051"}],"volume":"52","issue":"2","noUsgsAuthors":false,"publicationDate":"2013-04-02","publicationStatus":"PW","scienceBaseUri":"53516eb1e4b05569d8059d05","contributors":{"authors":[{"text":"Voytek, Emily B. 0000-0003-0981-453X ebvoytek@usgs.gov","orcid":"https://orcid.org/0000-0003-0981-453X","contributorId":3575,"corporation":false,"usgs":true,"family":"Voytek","given":"Emily","email":"ebvoytek@usgs.gov","middleInitial":"B.","affiliations":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true}],"preferred":true,"id":491941,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Drenkelfuss, Anja","contributorId":9954,"corporation":false,"usgs":true,"family":"Drenkelfuss","given":"Anja","email":"","affiliations":[],"preferred":false,"id":491942,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Day-Lewis, Frederick D. 0000-0003-3526-886X daylewis@usgs.gov","orcid":"https://orcid.org/0000-0003-3526-886X","contributorId":1672,"corporation":false,"usgs":true,"family":"Day-Lewis","given":"Frederick","email":"daylewis@usgs.gov","middleInitial":"D.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true}],"preferred":true,"id":491939,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Healy, Richard","contributorId":60947,"corporation":false,"usgs":true,"family":"Healy","given":"Richard","affiliations":[],"preferred":false,"id":491944,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lane, John W. Jr. jwlane@usgs.gov","contributorId":1738,"corporation":false,"usgs":true,"family":"Lane","given":"John","suffix":"Jr.","email":"jwlane@usgs.gov","middleInitial":"W.","affiliations":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true}],"preferred":false,"id":491940,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Werkema, Dale D.","contributorId":40488,"corporation":false,"usgs":false,"family":"Werkema","given":"Dale","email":"","middleInitial":"D.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":491943,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70099347,"text":"70099347 - 2014 - Quantifying restoration effectiveness using multi-scale habitat models: implications for sage-grouse in the Great Basin","interactions":[],"lastModifiedDate":"2014-03-25T09:13:06","indexId":"70099347","displayToPublicDate":"2014-03-24T16:20:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Quantifying restoration effectiveness using multi-scale habitat models: implications for sage-grouse in the Great Basin","docAbstract":"A recurrent challenge in the conservation of wide-ranging, imperiled species is understanding which habitats to protect and whether we are capable of restoring degraded landscapes. For Greater Sage-grouse (Centrocercus urophasianus), a species of conservation concern in the western United States, we approached this problem by developing multi-scale empirical models of occupancy in 211 randomly located plots within a 40 million ha portion of the species' range. We then used these models to predict sage-grouse habitat quality at 826 plots associated with 101 post-wildfire seeding projects implemented from 1990 to 2003. We also compared conditions at restoration sites to published habitat guidelines. Sage-grouse occupancy was positively related to plot- and landscape-level dwarf sagebrush (Artemisia arbuscula, A. nova, A. tripartita) and big sagebrush steppe prevalence, and negatively associated with non-native plants and human development. The predicted probability of sage-grouse occupancy at treated plots was low on average (0.09) and not substantially different from burned areas that had not been treated. Restoration sites with quality habitat tended to occur at higher elevation locations with low annual temperatures, high spring precipitation, and high plant diversity. Of 313 plots seeded after fire, none met all sagebrush guidelines for breeding habitats, but approximately 50% met understory guidelines, particularly for perennial grasses. This pattern was similar for summer habitat. Less than 2% of treated plots met winter habitat guidelines. Restoration actions did not increase the probability of burned areas meeting most guideline criteria. The probability of meeting guidelines was influenced by a latitudinal gradient, climate, and topography. Our results suggest that sage-grouse are relatively unlikely to use many burned areas within 20 years of fire, regardless of treatment. Understory habitat conditions are more likely to be adequate than overstory conditions, but in most climates, establishing forbs and reducing cheatgrass dominance is unlikely. Reestablishing sagebrush cover will require more than 20 years using past restoration methods. Given current fire frequencies and restoration capabilities, protection of landscapes containing a mix of dwarf sagebrush and big sagebrush steppe, minimal human development, and low non-native plant cover may provide the best opportunity for conservation of sage-grouse habitats.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ecosphere","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Ecological Society of America","doi":"10.1890/ES13-00278.1","usgsCitation":"Arkle, R., Pilliod, D., Hanser, S.E., Brooks, M.L., Chambers, J., Grace, J.B., Knutson, K., Pyke, D.A., and Welty, J., 2014, Quantifying restoration effectiveness using multi-scale habitat models: implications for sage-grouse in the Great Basin: Ecosphere, v. 5, no. 3, 32 p., https://doi.org/10.1890/ES13-00278.1.","productDescription":"32 p.","ipdsId":"IP-052298","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":473093,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1890/es13-00278.1","text":"Publisher Index Page"},{"id":284420,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":284418,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1890/ES13-00278.1"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -119.8169,39.7241 ], [ -119.8169,44.4652 ], [ -112.7417,44.4652 ], [ -112.7417,39.7241 ], [ -119.8169,39.7241 ] ] ] } } ] }","volume":"5","issue":"3","noUsgsAuthors":false,"publicationDate":"2014-03-24","publicationStatus":"PW","scienceBaseUri":"5351705de4b05569d805a381","contributors":{"authors":[{"text":"Arkle, Robert S.","contributorId":55679,"corporation":false,"usgs":true,"family":"Arkle","given":"Robert S.","affiliations":[],"preferred":false,"id":491962,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pilliod, David S.","contributorId":101760,"corporation":false,"usgs":true,"family":"Pilliod","given":"David S.","affiliations":[],"preferred":false,"id":491966,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hanser, Steven E.","contributorId":99273,"corporation":false,"usgs":true,"family":"Hanser","given":"Steven","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":491965,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brooks, Matthew L. 0000-0002-3518-6787 mlbrooks@usgs.gov","orcid":"https://orcid.org/0000-0002-3518-6787","contributorId":393,"corporation":false,"usgs":true,"family":"Brooks","given":"Matthew","email":"mlbrooks@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":491958,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chambers, Jeanne C.","contributorId":75889,"corporation":false,"usgs":false,"family":"Chambers","given":"Jeanne C.","affiliations":[],"preferred":false,"id":491963,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Grace, James B. 0000-0001-6374-4726 gracej@usgs.gov","orcid":"https://orcid.org/0000-0001-6374-4726","contributorId":884,"corporation":false,"usgs":true,"family":"Grace","given":"James","email":"gracej@usgs.gov","middleInitial":"B.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":491959,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Knutson, Kevin C. kevin_knutson@usgs.gov","contributorId":3646,"corporation":false,"usgs":true,"family":"Knutson","given":"Kevin C.","email":"kevin_knutson@usgs.gov","affiliations":[],"preferred":true,"id":491961,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Pyke, David A. 0000-0002-4578-8335 david_a_pyke@usgs.gov","orcid":"https://orcid.org/0000-0002-4578-8335","contributorId":3118,"corporation":false,"usgs":true,"family":"Pyke","given":"David","email":"david_a_pyke@usgs.gov","middleInitial":"A.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":491960,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Welty, Justin L.","contributorId":80558,"corporation":false,"usgs":true,"family":"Welty","given":"Justin L.","affiliations":[],"preferred":false,"id":491964,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70099203,"text":"70099203 - 2014 - Advances in a distributed approach for ocean model data interoperability","interactions":[],"lastModifiedDate":"2014-03-25T08:24:40","indexId":"70099203","displayToPublicDate":"2014-03-24T16:14:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2380,"text":"Journal of Marine Science and Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Advances in a distributed approach for ocean model data interoperability","docAbstract":"An infrastructure for earth science data is emerging across the globe based on common data models and web services. As we evolve from custom file formats and web sites to standards-based web services and tools, data is becoming easier to distribute, find and retrieve, leaving more time for science. We describe recent advances that make it easier for ocean model providers to share their data, and for users to search, access, analyze and visualize ocean data using MATLAB® and Python®. These include a technique for modelers to create aggregated, Climate and Forecast (CF) metadata convention datasets from collections of non-standard Network Common Data Form (NetCDF) output files, the capability to remotely access data from CF-1.6-compliant NetCDF files using the Open Geospatial Consortium (OGC) Sensor Observation Service (SOS), a metadata standard for unstructured grid model output (UGRID), and tools that utilize both CF and UGRID standards to allow interoperable data search, browse and access. We use examples from the U.S. Integrated Ocean Observing System (IOOS®) Coastal and Ocean Modeling Testbed, a project in which modelers using both structured and unstructured grid model output needed to share their results, to compare their results with other models, and to compare models with observed data. The same techniques used here for ocean modeling output can be applied to atmospheric and climate model output, remote sensing data, digital terrain and bathymetric data.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Marine Science and Engineering","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Multidisciplinary Digital Publishing Institute","doi":"10.3390/jmse2010194","usgsCitation":"Signell, R.P., and Snowden, D.P., 2014, Advances in a distributed approach for ocean model data interoperability: Journal of Marine Science and Engineering, v. 2, no. 1, p. 194-208, https://doi.org/10.3390/jmse2010194.","productDescription":"15 p.","startPage":"194","endPage":"208","ipdsId":"IP-054706","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":473095,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/jmse2010194","text":"Publisher Index Page"},{"id":284419,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":284348,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.3390/jmse2010194"}],"volume":"2","issue":"1","noUsgsAuthors":false,"publicationDate":"2014-03-19","publicationStatus":"PW","scienceBaseUri":"53516f2de4b05569d805a02d","contributors":{"authors":[{"text":"Signell, Richard P. rsignell@usgs.gov","contributorId":1435,"corporation":false,"usgs":true,"family":"Signell","given":"Richard","email":"rsignell@usgs.gov","middleInitial":"P.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":491858,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Snowden, Derrick P.","contributorId":54112,"corporation":false,"usgs":true,"family":"Snowden","given":"Derrick","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":491859,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70099277,"text":"70099277 - 2014 - Hierarchical spatial capture-recapture models: Modeling population density from stratified populations","interactions":[],"lastModifiedDate":"2016-11-08T08:50:48","indexId":"70099277","displayToPublicDate":"2014-03-24T14:23:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2717,"text":"Methods in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Hierarchical spatial capture-recapture models: Modeling population density from stratified populations","docAbstract":"
  1. Capture–recapture studies are often conducted on populations that are stratified by space, time or other factors. In this paper, we develop a Bayesian spatial capture–recapture (SCR) modelling framework for stratified populations – when sampling occurs within multiple distinct spatial and temporal strata.
  2. We describe a hierarchical model that integrates distinct models for both the spatial encounter history data from capture–recapture sampling, and also for modelling variation in density among strata. We use an implementation of data augmentation to parameterize the model in terms of a latent categorical stratum or group membership variable, which provides a convenient implementation in popular BUGS software packages.
  3. We provide an example application to an experimental study involving small-mammal sampling on multiple trapping grids over multiple years, where the main interest is in modelling a treatment effect on population density among the trapping grids.
  4. Many capture–recapture studies involve some aspect of spatial or temporal replication that requires some attention to modelling variation among groups or strata. We propose a hierarchical model that allows explicit modelling of group or strata effects. Because the model is formulated for individual encounter histories and is easily implemented in the BUGS language and other free software, it also provides a general framework for modelling individual effects, such as are present in SCR models.
","language":"English","publisher":"British Ecological Society","doi":"10.1111/2041-210X.12135","usgsCitation":"Royle, J., and Converse, S., 2014, Hierarchical spatial capture-recapture models: Modeling population density from stratified populations: Methods in Ecology and Evolution, v. 5, no. 1, p. 37-43, https://doi.org/10.1111/2041-210X.12135.","productDescription":"7 p.","startPage":"37","endPage":"43","ipdsId":"IP-052063","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":473096,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/2041-210x.12135","text":"Publisher Index Page"},{"id":284411,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":284408,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/2041-210X.12135"}],"volume":"5","issue":"1","noUsgsAuthors":false,"publicationDate":"2013-12-05","publicationStatus":"PW","scienceBaseUri":"53517046e4b05569d805a24f","contributors":{"authors":[{"text":"Royle, J. Andrew 0000-0003-3135-2167","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":80808,"corporation":false,"usgs":true,"family":"Royle","given":"J. Andrew","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":491937,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Converse, Sarah J.","contributorId":85716,"corporation":false,"usgs":true,"family":"Converse","given":"Sarah J.","affiliations":[],"preferred":false,"id":491938,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70099977,"text":"70099977 - 2014 - Simulation of the effects of seasonally varying pumping on intraborehole flow and the vulnerability of public-supply wells to contamination","interactions":[],"lastModifiedDate":"2014-09-23T13:05:27","indexId":"70099977","displayToPublicDate":"2014-03-24T14:07:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1861,"text":"Ground Water","active":true,"publicationSubtype":{"id":10}},"title":"Simulation of the effects of seasonally varying pumping on intraborehole flow and the vulnerability of public-supply wells to contamination","docAbstract":"Public-supply wells with long screens in alluvial aquifers can produce waters of differing quality from different depths. Seasonal changes in quality are linked to seasonal changes in pumping rates that influence the distribution of flow into the well screens under pumping conditions and the magnitude and direction of intraborehole flow within the wells under ambient conditions. Groundwater flow and transport simulations with MODFLOW and MT3DMS were developed to quantify the effects of changes in average seasonal pumping rates on intraborehole flow and water quality at two long-screened, public-supply wells, in Albuquerque, New Mexico and Modesto, California, where widespread pumping has altered groundwater flow patterns. Simulation results indicate that both wells produce water requiring additional treatment to maintain potable quality in winter when groundwater withdrawals are reduced because less water is derived from parts of the aquifer that contain water requiring less treatment. Simulation results indicate that the water quality at both wells could be improved by increasing average winter-pumping rates to induce more lateral flow from parts of the aquifer that contain better quality water. Arsenic-bearing water produced by the Albuquerque well could be reduced from 55% to 45% by doubling average winter-pumping rate, while nitrate- and uranium-bearing water produced by the Modesto well could be reduced from 95% to 65% by nearly tripling the average winter-pumping rate. Higher average winter-pumping rates would also reduce the volume of intraborehole flow within both wells and prevent the exchange of poor quality water between shallow and deep parts of both aquifers.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ground Water","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"State Water Control Board","publisherLocation":"Richmond, VA","doi":"10.1111/gwat.12150","usgsCitation":"Yager, R.M., and Heywood, C.E., 2014, Simulation of the effects of seasonally varying pumping on intraborehole flow and the vulnerability of public-supply wells to contamination: Ground Water, v. 52, no. S1, p. 40-52, https://doi.org/10.1111/gwat.12150.","productDescription":"13 p.","startPage":"40","endPage":"52","numberOfPages":"13","ipdsId":"IP-042995","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":473097,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1111/gwat.12150","text":"External Repository"},{"id":285105,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":285102,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/gwat.12150"},{"id":285103,"type":{"id":15,"text":"Index Page"},"url":"https://onlinelibrary.wiley.com/doi/10.1111/gwat.12150/abstract"}],"country":"United States","state":"California;New Mexico","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -121.074,34.946 ], [ -121.074,37.714 ], [ -106.471,37.714 ], [ -106.471,34.946 ], [ -121.074,34.946 ] ] ] } } ] }","volume":"52","issue":"S1","noUsgsAuthors":false,"publicationDate":"2014-01-10","publicationStatus":"PW","scienceBaseUri":"53517062e4b05569d805a3b3","contributors":{"authors":[{"text":"Yager, Richard M. 0000-0001-7725-1148 ryager@usgs.gov","orcid":"https://orcid.org/0000-0001-7725-1148","contributorId":950,"corporation":false,"usgs":true,"family":"Yager","given":"Richard","email":"ryager@usgs.gov","middleInitial":"M.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true},{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":492087,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Heywood, Charles E. cheywood@usgs.gov","contributorId":2043,"corporation":false,"usgs":true,"family":"Heywood","given":"Charles","email":"cheywood@usgs.gov","middleInitial":"E.","affiliations":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":492088,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70099228,"text":"70099228 - 2014 - Mercury and methylmercury dynamics in the hyporheic zone of an Oregon stream","interactions":[],"lastModifiedDate":"2014-03-24T14:20:07","indexId":"70099228","displayToPublicDate":"2014-03-24T13:54:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3728,"text":"Water, Air, & Soil Pollution","onlineIssn":"1573-2932","printIssn":"0049-6979","active":true,"publicationSubtype":{"id":10}},"title":"Mercury and methylmercury dynamics in the hyporheic zone of an Oregon stream","docAbstract":"The role of the hyporheic zone in mercury (Hg) cycling has received limited attention despite the biogeochemically active nature of this zone and, thus, its potential to influence Hg behavior in streams. An assessment of Hg geochemistry in the hyporheic zone of a coarse-grained island in the Coast Fork Willamette River in Oregon, USA, illustrates the spatially dynamic nature of this region of the stream channel for Hg mobilization and attenuation. Hyporheic flow through the island was evident from the water-table geometry and supported by hyporheic-zone chemistry distinct from that of the bounding groundwater system. Redox-indicator species changed abruptly along a transect through the hyporheic zone, indicating a biogeochemically reactive stream/hyporheic-zone continuum. Dissolved organic carbon (DOC), total Hg, and methylmercury (MeHg) concentrations increased in the upgradient portion of the hyporheic zone and decreased in the downgradient region. Total Hg (collected in 2002 and 2003) and MeHg (collected in 2003) were correlated with DOC in hyporheic-zone samples: r2=0.63 (total Hg-DOC, 2002), 0.73 (total Hg-DOC, 2003), and 0.94 (MeHg-DOC, 2003). Weaker Hg/DOC association in late summer 2002 than in early summer 2003 may reflect seasonal differences in DOC reactivity. Observed correlations between DOC and both total Hg and MeHg reflect the importance of DOC for Hg mobilization, transport, and fate in this hyporheic zone. Correlations with DOC provide a framework for conceptualizing and quantifying Hg and MeHg dynamics in this region of the stream channel, and provide a refined conceptual model of the role hyporheic zones may play in aquatic ecosystems.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Water, Air, and Soil Pollution","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","doi":"10.1007/s11270-013-1694-y","usgsCitation":"Hinkle, S.R., Bencala, K.E., Wentz, D.A., and Krabbenhoft, D.P., 2014, Mercury and methylmercury dynamics in the hyporheic zone of an Oregon stream: Water, Air, & Soil Pollution, v. 225, no. 1, 17 p., https://doi.org/10.1007/s11270-013-1694-y.","productDescription":"17 p.","ipdsId":"IP-034165","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":284407,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":284350,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s11270-013-1694-y"},{"id":284351,"type":{"id":15,"text":"Index Page"},"url":"https://link.springer.com/article/10.1007/s11270-013-1694-y"}],"volume":"225","issue":"1","noUsgsAuthors":false,"publicationDate":"2013-11-29","publicationStatus":"PW","scienceBaseUri":"53517054e4b05569d805a321","contributors":{"authors":[{"text":"Hinkle, Stephen R. srhinkle@usgs.gov","contributorId":1171,"corporation":false,"usgs":true,"family":"Hinkle","given":"Stephen","email":"srhinkle@usgs.gov","middleInitial":"R.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":491870,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bencala, Kenneth E. kbencala@usgs.gov","contributorId":1541,"corporation":false,"usgs":true,"family":"Bencala","given":"Kenneth","email":"kbencala@usgs.gov","middleInitial":"E.","affiliations":[],"preferred":true,"id":491871,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wentz, Dennis A. dawentz@usgs.gov","contributorId":1838,"corporation":false,"usgs":true,"family":"Wentz","given":"Dennis","email":"dawentz@usgs.gov","middleInitial":"A.","affiliations":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"preferred":false,"id":491873,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Krabbenhoft, David P. 0000-0003-1964-5020 dpkrabbe@usgs.gov","orcid":"https://orcid.org/0000-0003-1964-5020","contributorId":1658,"corporation":false,"usgs":true,"family":"Krabbenhoft","given":"David","email":"dpkrabbe@usgs.gov","middleInitial":"P.","affiliations":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":491872,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70099286,"text":"70099286 - 2014 - New permafrost is forming around shrinking Arctic lakes, but will it last?","interactions":[],"lastModifiedDate":"2018-01-12T17:20:40","indexId":"70099286","displayToPublicDate":"2014-03-24T11:33:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"New permafrost is forming around shrinking Arctic lakes, but will it last?","docAbstract":"Widespread lake shrinkage in cold regions has been linked to climate warming and permafrost thaw. Permafrost aggradation, however, has been observed within the margins of recently receded lakes, in seeming contradiction of climate warming. Here permafrost aggradation dynamics are examined at Twelvemile Lake, a retreating lake in interior Alaska. Observations reveal patches of recently formed permafrost within the dried lake margin, colocated with discrete bands of willow shrub. We test ecological succession, which alters shading, infiltration, and heat transport, as the driver of aggradation using numerical simulation of variably saturated groundwater flow and heat transport with phase change (i.e., freeze-thaw). Simulations support permafrost development under current climatic conditions, but only when net effects of vegetation on soil conditions are incorporated, thus pointing to the role of ecological succession. Furthermore, model results indicate that permafrost aggradation is transitory with further climate warming, as new permafrost thaws within seven decades.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Geophysical Research Letters","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"American Geophysical Union","doi":"10.1002/2014GL059251","usgsCitation":"Briggs, M., Walvoord, M.A., McKenzie, J.M., Voss, C.I., Day-Lewis, F.D., and Lane, J.W., 2014, New permafrost is forming around shrinking Arctic lakes, but will it last?: Geophysical Research Letters, v. 41, no. 5, p. 1585-1592, https://doi.org/10.1002/2014GL059251.","productDescription":"8 p.","startPage":"1585","endPage":"1592","ipdsId":"IP-053609","costCenters":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true}],"links":[{"id":473098,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2014gl059251","text":"Publisher Index Page"},{"id":284385,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/2014GL059251"},{"id":284387,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Twelvemile Lake","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -145.570227,66.434705 ], [ -145.570227,66.4607 ], [ -145.501777,66.4607 ], [ -145.501777,66.434705 ], [ -145.570227,66.434705 ] ] ] } } ] }","volume":"41","issue":"5","noUsgsAuthors":false,"publicationDate":"2014-03-07","publicationStatus":"PW","scienceBaseUri":"53517057e4b05569d805a341","contributors":{"authors":[{"text":"Briggs, Martin A.","contributorId":10321,"corporation":false,"usgs":true,"family":"Briggs","given":"Martin A.","affiliations":[],"preferred":false,"id":491951,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Walvoord, Michelle Ann 0000-0003-4269-8366 walvoord@usgs.gov","orcid":"https://orcid.org/0000-0003-4269-8366","contributorId":147211,"corporation":false,"usgs":true,"family":"Walvoord","given":"Michelle","email":"walvoord@usgs.gov","middleInitial":"Ann","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":491953,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McKenzie, Jeffrey M.","contributorId":64999,"corporation":false,"usgs":true,"family":"McKenzie","given":"Jeffrey","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":491952,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Voss, Clifford I. 0000-0001-5923-2752 cvoss@usgs.gov","orcid":"https://orcid.org/0000-0001-5923-2752","contributorId":1559,"corporation":false,"usgs":true,"family":"Voss","given":"Clifford","email":"cvoss@usgs.gov","middleInitial":"I.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":491948,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Day-Lewis, Frederick D. 0000-0003-3526-886X daylewis@usgs.gov","orcid":"https://orcid.org/0000-0003-3526-886X","contributorId":1672,"corporation":false,"usgs":true,"family":"Day-Lewis","given":"Frederick","email":"daylewis@usgs.gov","middleInitial":"D.","affiliations":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":491949,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lane, John W. Jr. jwlane@usgs.gov","contributorId":1738,"corporation":false,"usgs":true,"family":"Lane","given":"John","suffix":"Jr.","email":"jwlane@usgs.gov","middleInitial":"W.","affiliations":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true}],"preferred":false,"id":491950,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70095134,"text":"ofr20131297 - 2014 - Analysis of pharmaceutical and other organic wastewater compounds in filtered and unfiltered water samples by gas chromatography/mass spectrometry","interactions":[],"lastModifiedDate":"2014-03-25T11:02:20","indexId":"ofr20131297","displayToPublicDate":"2014-03-24T07:53:00","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":"2013-1297","title":"Analysis of pharmaceutical and other organic wastewater compounds in filtered and unfiltered water samples by gas chromatography/mass spectrometry","docAbstract":"

Research on the effects of exposure of stream biota to complex mixtures of pharmaceuticals and other organic compounds associated with wastewater requires the development of additional analytical capabilities for these compounds in water samples. Two gas chromatography/mass spectrometry (GC/MS) analytical methods used at the U.S. Geological Survey National Water Quality Laboratory (NWQL) to analyze organic compounds associated with wastewater were adapted to include additional pharmaceutical and other organic compounds beginning in 2009. This report includes a description of method performance for 42 additional compounds for the filtered-water method (hereafter referred to as the filtered method) and 46 additional compounds for the unfiltered-water method (hereafter referred to as the unfiltered method). The method performance for the filtered method described in this report has been published for seven of these compounds; however, the addition of several other compounds to the filtered method and the addition of the compounds to the unfiltered method resulted in the need to document method performance for both of the modified methods. Most of these added compounds are pharmaceuticals or pharmaceutical degradates, although two nonpharmaceutical compounds are included in each method. The main pharmaceutical compound classes added to the two modified methods include muscle relaxants, opiates, analgesics, and sedatives. These types of compounds were added to the original filtered and unfiltered methods largely in response to the tentative identification of a wide range of pharmaceutical and other organic compounds in samples collected from wastewater-treatment plants.

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Filtered water samples are extracted by vacuum through disposable solid-phase cartridges that contain modified polystyrene-divinylbenzene resin. Unfiltered samples are extracted by using continuous liquid-liquid extraction with dichloromethane. The compounds of interest for filtered and unfiltered sample types were determined by use of the capillary-column gas chromatography/mass spectrometry.

\n
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The performance of each method was assessed by using data on recoveries of compounds in fortified surface-water, wastewater, and reagent-water samples. These experiments (referred to as spike experiments) consist of fortifying (or spiking) samples with known amounts of target analytes. Surface-water-spike experiments were performed by using samples obtained from a stream in Colorado (unfiltered method) and a stream in New York (filtered method). Wastewater spike experiments for both the filtered and unfiltered methods were performed by using a treated wastewater obtained from a single wastewater treatment plant in New York. Surface water and wastewater spike experiments were fortified at both low and high concentrations and termed low- and high-level spikes, respectively. Reagent water spikes were assessed in three ways: (1) set spikes, (2) a low-concentration fortification experiment, and (3) a high-concentration fortification experiment. Set spike samples have been determined since 2009, and consist of analysis of fortified reagent water for target compounds included for each group of 10 to18 environmental samples analyzed at the NWQL. The low-concentration and high-concentration reagent spike experiments, by contrast, represent a one-time assessment of method performance. For each spike experiment, mean recoveries ranging from 60 to 130 percent indicate low bias, and relative standard deviations (RSDs) less than (<) 30 percent indicate low variability.

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\n

Of the compounds included in the filtered method, 21 had mean recoveries ranging from 63 to 129 percent for the low-level and high-level surface-water spikes, and had low (<15 percent) RSDs for these spikes. The remaining 21 compounds generally had high bias for the low-level or the high-level spike experiments for surface water [mean recoveries <58 percent or greater than (>)132 percent]. For wastewater spikes, 24 of the compounds included in the filtered method had recoveries ranging from 61 to 130 percent for the low-level and high-level spikes. RSDs were <29 percent for both of these spike experiments for the 24 compounds. The remaining 18 compounds in the filtered method generally had high recoveries (>130 percent) or variable recoveries (RSDs >30 percent) for low-level wastewater spikes, or low recoveries (<60 percent) for high-level wastewater spikes. Of the compounds included in the filtered method, 34 had mean set-spike recoveries between 61 and 126 percent, and RSDs <30 percent.

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Of the compounds included in the unfiltered method, 17 had mean spike recoveries ranging from 74 to 129 percent and RSDs ranging from 5 to 25 percent for low-level and high-level surface water spikes. The remaining compounds had poor mean recoveries (<60 or >130 percent), or high RSDs (>29 percent) for these spikes. For wastewater, 14 of the compounds included in the unfiltered method had mean recoveries ranging from 62 to 127 percent and RSDs <25 percent for the low-level and high-level spikes. Most of the remaining compounds had high mean recoveries for wastewater (>130 percent), or low mean recoveries (<20 percent) or high RSDs (>33 percent) for the low-level wastewater spikes. Of the compounds found in wastewater, 24 had mean set spike recoveries ranging from 64 to 104 percent and RSDs <30 percent.

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\n

Separate method detection limits (MDLs) were computed for surface water and wastewater for both the filtered and unfiltered methods. Filtered method MDLs ranged from 0.007 to 0.14 microgram per liter (μg/L) for the surface water matrix and from 0.004 to 0.62 μg/L for the wastewater matrix. Unfiltered method MDLs ranged from 0.014 to 0.33 μg/L for the surface water matrix and from 0.008 to 0.36 μg/L for the wastewater matrix.

","language":"English","publisher":"U.S Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131297","collaboration":"Prepared in cooperation with the New York State Department of Environmental Conservation","usgsCitation":"Zaugg, S.D., Phillips, P., and Smith, S.G., 2014, Analysis of pharmaceutical and other organic wastewater compounds in filtered and unfiltered water samples by gas chromatography/mass spectrometry: U.S. Geological Survey Open-File Report 2013-1297, Report: v, 24 p.; Appendix, https://doi.org/10.3133/ofr20131297.","productDescription":"Report: v, 24 p.; Appendix","onlineOnly":"Y","ipdsId":"IP-040896","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":284375,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131297.jpg"},{"id":284374,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2013/1297/tables/ofr2013-1297_tables1-appendix1.xlsx"},{"id":284372,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1297/"},{"id":284373,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1297/pdf/ofr2013-1297.pdf"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.8,24.5 ], [ -124.8,49.383333 ], [ -66.95,49.383333 ], [ -66.95,24.5 ], [ -124.8,24.5 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd4ce0e4b0b290850f13b4","contributors":{"authors":[{"text":"Zaugg, Steven D. sdzaugg@usgs.gov","contributorId":768,"corporation":false,"usgs":true,"family":"Zaugg","given":"Steven","email":"sdzaugg@usgs.gov","middleInitial":"D.","affiliations":[],"preferred":true,"id":491079,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Phillips, Patrick J. pjphilli@usgs.gov","contributorId":856,"corporation":false,"usgs":true,"family":"Phillips","given":"Patrick J.","email":"pjphilli@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":false,"id":491080,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, Steven G. sgsmith@usgs.gov","contributorId":1560,"corporation":false,"usgs":true,"family":"Smith","given":"Steven","email":"sgsmith@usgs.gov","middleInitial":"G.","affiliations":[],"preferred":true,"id":491081,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70094915,"text":"fs20143013 - 2014 - The 3D Elevation Program: summary for Maine","interactions":[],"lastModifiedDate":"2016-08-17T15:47:53","indexId":"fs20143013","displayToPublicDate":"2014-03-24T07:28:00","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":"2014-3013","title":"The 3D Elevation Program: summary for Maine","docAbstract":"

Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, national security, recreation, and many others. For the State of Maine, elevation data are critical for natural resources conservation, flood risk management, forest resources management, agriculture and precision farming, coastal zone management, and other business uses. Today, high-density light detection and ranging (lidar) data are the primary sources for deriving elevation models and other datasets. Federal, State, Tribal, and local agencies work in partnership to (1) replace data that are older and of lower quality and (2) provide coverage where publicly accessible data do not exist. A joint goal of State and Federal partners is to acquire consistent, statewide coverage to support existing and emerging applications enabled by lidar data.

\n

The National Enhanced Elevation Assessment evaluated multiple elevation data acquisition options to determine the optimal data quality and data replacement cycle relative to cost to meet the identified requirements of the user community. The evaluation demonstrated that lidar acquisition at quality level 2 for the conterminous United States and quality level 5 ifsar data for Alaska with a 6- to 10-year acquisition cycle provided the highest benefit/cost ratios. The 3D Elevation Program (3DEP) initiative selected an 8-year acquisition cycle for the respective quality levels. 3DEP, managed by the U.S. Geological Survey (USGS), the Office of Management and Budget Circular A–16 lead agency for terrestrial elevation data, responds to the growing need for high-quality topographic data and a wide range of other 3D representations of the Nation’s natural and constructed features.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20143013","usgsCitation":"Carswell, W., 2014, The 3D Elevation Program: summary for Maine: U.S. Geological Survey Fact Sheet 2014-3013, 2 p., https://doi.org/10.3133/fs20143013.","productDescription":"2 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-052810","costCenters":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"links":[{"id":284364,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20143013.jpg"},{"id":284362,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2014/3013/"},{"id":284363,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2014/3013/pdf/fs2014-3013.pdf","text":"Report","size":"344 KB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"country":"United 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Jr. carswell@usgs.gov","contributorId":1787,"corporation":false,"usgs":true,"family":"Carswell","given":"William J.","suffix":"Jr.","email":"carswell@usgs.gov","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":false,"id":490945,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70134498,"text":"70134498 - 2014 - Large natural pH, CO2 and O2 fluctuations in a temperate tidal salt marsh on diel, seasonal, and interannual time scales","interactions":[],"lastModifiedDate":"2020-12-23T16:21:27.378371","indexId":"70134498","displayToPublicDate":"2014-03-21T13:15:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1584,"text":"Estuaries and Coasts","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Large natural pH, CO2 and O2 fluctuations in a temperate tidal salt marsh on diel, seasonal, and interannual time scales","title":"Large natural pH, CO2 and O2 fluctuations in a temperate tidal salt marsh on diel, seasonal, and interannual time scales","docAbstract":"

Coastal marine organisms experience dynamic pH and dissolved oxygen (DO) conditions in their natural habitats, which may impact their susceptibility to long-term anthropogenic changes. Robust characterizations of all temporal scales of natural pH and DO fluctuations in different marine habitats are needed; however, appropriate time series of pH and DO are still scarce. We used multiyear (2008–2012), high-frequency (6 min) monitoring data to quantify diel, seasonal, and interannual scales of pH and DO variability in a productive, temperate tidal salt marsh (Flax Pond, Long Island, US). pHNBS and DO showed strong and similar seasonal patterns, with average (minimum) conditions declining from 8.2 (8.1) and 12.5 (11.4) mg l−1 at the end of winter to 7.6 (7.2) and 6.3 (2.8) mg l−1 in late summer, respectively. Concomitantly, average diel fluctuations increased from 0.22 and 2.2 mg l−1 (February) to 0.74 and 6.5 mg l−1 (August), respectively. Diel patterns were modulated by tides and time of day, eliciting the most extreme minima when low tides aligned with the end of the night. Simultaneous in situ pCO2 measurements showed striking fluctuations between ∼330 and ∼1,200 (early May), ∼2,200 (mid June), and ∼4,000 μatm (end of July) within single tidal cycles. These patterns also indicate that the marsh’s strong net heterotrophy influences its adjacent estuary by ‘outwelling’ acidified and hypoxic water during ebb tides. Our analyses emphasize the coupled and fluctuating nature of pH and DO conditions in productive coastal and estuarine environments, which have yet to be adequately represented by experiments.

","language":"English","publisher":"Springer Link","doi":"10.1007/s12237-014-9800-y","usgsCitation":"Baumann, H., Wallace, R., Tagliaferri, T.N., and Gobler, C.J., 2014, Large natural pH, CO2 and O2 fluctuations in a temperate tidal salt marsh on diel, seasonal, and interannual time scales: Estuaries and Coasts, v. 38, p. 220-231, https://doi.org/10.1007/s12237-014-9800-y.","productDescription":"12 p.","startPage":"220","endPage":"231","numberOfPages":"12","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-052918","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":296386,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Flax Pond, Long Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.15135002136229,\n 40.95967830900992\n ],\n [\n -73.13070774078369,\n 40.95967830900992\n ],\n [\n -73.13070774078369,\n 40.96816877082855\n ],\n [\n -73.15135002136229,\n 40.96816877082855\n ],\n [\n -73.15135002136229,\n 40.95967830900992\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"38","noUsgsAuthors":false,"publicationDate":"2014-03-21","publicationStatus":"PW","scienceBaseUri":"547ee2cce4b09357f05f8a5f","contributors":{"authors":[{"text":"Baumann, Hannes","contributorId":127638,"corporation":false,"usgs":false,"family":"Baumann","given":"Hannes","affiliations":[{"id":7093,"text":"Adjunct Assist Prof, School of Marine & Atmospheric Sciences, Stony Brook Univ","active":true,"usgs":false}],"preferred":false,"id":526053,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wallace, Ryan","contributorId":127639,"corporation":false,"usgs":false,"family":"Wallace","given":"Ryan","email":"","affiliations":[{"id":7094,"text":"Grad Student, School of Marine & Atmospheric Sciences, Stony Brook Univ","active":true,"usgs":false}],"preferred":false,"id":526054,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tagliaferri, Tristen N. 0000-0001-7408-7899 ttagliaferri@usgs.gov","orcid":"https://orcid.org/0000-0001-7408-7899","contributorId":5138,"corporation":false,"usgs":true,"family":"Tagliaferri","given":"Tristen","email":"ttagliaferri@usgs.gov","middleInitial":"N.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":526052,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gobler, Christopher J.","contributorId":127640,"corporation":false,"usgs":false,"family":"Gobler","given":"Christopher","email":"","middleInitial":"J.","affiliations":[{"id":7095,"text":"Professor, School of Marine & Atmospheric Sciences, Stony Brook University","active":true,"usgs":false}],"preferred":false,"id":526055,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70187384,"text":"70187384 - 2014 - Transmission of chronic wasting disease in Wisconsin white-tailed deer: Implications for disease spread and management","interactions":[],"lastModifiedDate":"2017-05-01T12:47:43","indexId":"70187384","displayToPublicDate":"2014-03-21T00:00:00","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":"Transmission of chronic wasting disease in Wisconsin white-tailed deer: Implications for disease spread and management","docAbstract":"

Few studies have evaluated the rate of infection or mode of transmission for wildlife diseases, and the implications of alternative management strategies. We used hunter harvest data from 2002 to 2013 to investigate chronic wasting disease (CWD) infection rate and transmission modes, and address how alternative management approaches affect disease dynamics in a Wisconsin white-tailed deer population. Uncertainty regarding demographic impacts of CWD on cervid populations, human and domestic animal health concerns, and potential economic consequences underscore the need for strategies to control CWD distribution and prevalence. Using maximum-likelihood methods to evaluate alternative multi-state deterministic models of CWD transmission, harvest data strongly supports a frequency-dependent transmission structure with sex-specific infection rates that are two times higher in males than females. As transmissible spongiform encephalopathies are an important and difficult-to-study class of diseases with major economic and ecological implications, our work supports the hypothesis of frequency-dependent transmission in wild deer at a broad spatial scale and indicates that effective harvest management can be implemented to control CWD prevalence. Specifically, we show that harvest focused on the greater-affected sex (males) can result in stable population dynamics and control of CWD within the next 50 years, given the constraints of the model. We also provide a quantitative estimate of geographic disease spread in southern Wisconsin, validating qualitative assessments that CWD spreads relatively slowly. Given increased discovery and distribution of CWD throughout North America, insights from our study are valuable to management agencies and to the general public concerned about the impacts of CWD on white-tailed deer populations.

","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0091043","usgsCitation":"Jennelle, C., Henaux, V., Wasserberg, G., Thiagarajan, B., Rolley, R.E., and Samuel, M.D., 2014, Transmission of chronic wasting disease in Wisconsin white-tailed deer: Implications for disease spread and management: PLoS ONE, v. 9, no. 3, p. 1-12, https://doi.org/10.1371/journal.pone.0091043.","productDescription":" e91043; 12 p.","startPage":"1","endPage":"12","ipdsId":"IP-038460","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":473099,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0091043","text":"Publisher Index Page"},{"id":340673,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","volume":"9","issue":"3","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2014-03-21","publicationStatus":"PW","scienceBaseUri":"59084932e4b0fc4e448ffd82","contributors":{"authors":[{"text":"Jennelle, Christopher S.","contributorId":50823,"corporation":false,"usgs":true,"family":"Jennelle","given":"Christopher S.","affiliations":[],"preferred":false,"id":693757,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Henaux, Viviane","contributorId":171388,"corporation":false,"usgs":false,"family":"Henaux","given":"Viviane","email":"","affiliations":[{"id":24576,"text":"University of Wisconsin, Madison, WI","active":true,"usgs":false}],"preferred":false,"id":693758,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wasserberg, Gideon","contributorId":31185,"corporation":false,"usgs":true,"family":"Wasserberg","given":"Gideon","email":"","affiliations":[],"preferred":false,"id":693759,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thiagarajan, Bala","contributorId":92520,"corporation":false,"usgs":true,"family":"Thiagarajan","given":"Bala","email":"","affiliations":[],"preferred":false,"id":693760,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rolley, Robert E.","contributorId":171376,"corporation":false,"usgs":false,"family":"Rolley","given":"Robert","email":"","middleInitial":"E.","affiliations":[{"id":24833,"text":"Wisconsin DNR, Madison, WI","active":true,"usgs":false}],"preferred":false,"id":693761,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Samuel, Michael D. msamuel@usgs.gov","contributorId":1419,"corporation":false,"usgs":true,"family":"Samuel","given":"Michael","email":"msamuel@usgs.gov","middleInitial":"D.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":693721,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70161768,"text":"70161768 - 2014 - Strength of evidence for the effects of feral cats on insular wildlife: The Club Med Syndrome Part II","interactions":[],"lastModifiedDate":"2018-03-23T14:23:52","indexId":"70161768","displayToPublicDate":"2014-03-20T14:30:00","publicationYear":"2014","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Strength of evidence for the effects of feral cats on insular wildlife: The Club Med Syndrome Part II","docAbstract":"

Various types of evidence have been promulgated as proof for the effects of feral cats on wildlife, typically including numerous studies on predation inferred from diet, mortality attributed to pathogens, and photographic or videographic documentation. The strength of these types of evidence is often short of conclusive. For example, studies of predation inferred from diet provide weak evidence for two reasons: 1) they cannot differentiate depredation from scavenging by feral cats, and 2) they cannot address population-level effects on wildlife because it is rarely understood if mortality acts in compensatory or additive manner. Likewise, pathogens may cause mortality of individuals, but population-level effects of pathogens are rarely known. Photographic or videographic documentation provides direct ‘smoking gun’ evidence that may be useful for positive identification of depredation by cats, or identification of prey designated as threatened or endangered species. However, the most direct and compelling evidence comes from examples where feral cats have been entirely removed from islands. In many cases, several species of seabirds as well as other wildlife have recovered after the complete removal of cats. Where possible, the experimental removal of cats would provide the most conclusive proof of effects on wildlife populations. In other cases where cat removal is not feasible, modeling based on predation rates and life history parameters of species may be the only means of assessing population-level effects on wildlife. Understanding population-level effects of feral cats on wildlife will ultimately be necessary to resolve long-standing wildlife management issues.

","conferenceTitle":"26th Vertebrate Pest Conference","conferenceDate":"March 3, 2014","conferenceLocation":"Waikoloa, HI","language":"English","publisher":"University of California, Davis","usgsCitation":"Hess, S.C., 2014, Strength of evidence for the effects of feral cats on insular wildlife: The Club Med Syndrome Part II, 26th Vertebrate Pest Conference, Waikoloa, HI, March 3, 2014, p. 211-216.","productDescription":"5 p.","startPage":"211","endPage":"216","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057984","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":326239,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":326238,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.vpconference.org/Proceedings_of_the_Vertebrate_Pest_Conference/"}],"country":"United States","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57a9ad73e4b05e859bdfbb17","contributors":{"authors":[{"text":"Hess, Steve C. 0000-0001-6403-9922 shess@usgs.gov","orcid":"https://orcid.org/0000-0001-6403-9922","contributorId":150366,"corporation":false,"usgs":true,"family":"Hess","given":"Steve","email":"shess@usgs.gov","middleInitial":"C.","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":587717,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70099120,"text":"70099120 - 2014 - Quantity and quality of groundwater discharge in a hypersaline lake environment","interactions":[],"lastModifiedDate":"2017-01-03T14:57:56","indexId":"70099120","displayToPublicDate":"2014-03-20T13:59:00","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":"Quantity and quality of groundwater discharge in a hypersaline lake environment","docAbstract":"Geophysical and geochemical surveys were conducted to understand groundwater discharge to Great Salt Lake (GSL) and assess the potential significance of groundwater discharge as a source of selenium (Se). Continuous resistivity profiling (CRP) focusing below the sediment/water interface and fiber-optic distributed temperature sensing (FO-DTS) surveys were conducted along the south shore of GSL. FO-DTS surveys identified persistent cold-water temperature anomalies at 10 separate locations. Seepage measurements were conducted at 17 sites (mean seepage rate = 0.8 cm/day). High resistivity anomalies identified by the CRP survey were likely a mirabilite (Na2SO4·10H2O) salt layer acting as a semi-confining layer for the shallow groundwater below the south shore of the lake. Positive seepage rates measured along the near-shore areas of GSL indicate that a ∼1-m thick oolitic sand overlying the mirabilite layer is likely acting as a shallow, unconfined aquifer. Using the average seepage rate of 0.8 cm/day over an area of 1.6 km2, an annual Se mass loading to GSL of 23.5 kg was estimated. Determination of R/Ra values (calculated 3He/4He ratio over the present-day atmospheric 3He/4He ratio) <1 and tritium activities of 1.2–2.0 tritium units in groundwater within and below the mirabilite layer indicates a convergence of regional and local groundwater flow paths discharging into GSL. Groundwater within and below the mirabilite layer obtains its high sulfate salinity from the dissolution of mirabilite. The δ34S and δ18O isotopic values in samples of dissolved sulfate from the shallow groundwater below the mirabilite are almost identical to the isotopic signature of the mirabilite core material. The saturation index calculated for groundwater samples using PHREEQC indicates the water is at equilibrium with mirabilite. Water samples collected from GSL immediately off shore contained Se concentrations that were 3–4 times higher than other sampling sites >25 km offshore from the study site and may be originating from less saline groundwater seeps mixing with the more saline water from GSL. Additional evidence for mixing with near shore seeps is found in the δD and δ18O isotopic values and Br:Cl ratios. Geochemical modeling for a water sample collected in the vicinity of the study area indicates that under chemically reducing conditions, arsenic- (As) bearing minerals could dissolve while Se-bearing minerals will likely precipitate out of solution, possibly explaining why the shallow groundwater below and within the mirabilite salt layer contains low concentrations of Se (0.9–2.3 μg/L).","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2014.02.040","usgsCitation":"Anderson, R., Naftz, D.L., Day-Lewis, F., Henderson, R., Rosenberry, D., Stolp, B., and Jewell, P., 2014, Quantity and quality of groundwater discharge in a hypersaline lake environment: Journal of Hydrology, v. 512, p. 177-194, https://doi.org/10.1016/j.jhydrol.2014.02.040.","productDescription":"18 p.","startPage":"177","endPage":"194","ipdsId":"IP-037434","costCenters":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":284337,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah","otherGeospatial":"Great Salt Lake","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -112.326622,40.499181 ], [ -112.326622,40.849657 ], [ -111.94931,40.849657 ], [ -111.94931,40.499181 ], [ -112.326622,40.499181 ] ] ] } } ] }","volume":"512","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5351705de4b05569d805a383","contributors":{"authors":[{"text":"Anderson, R.B.","contributorId":48693,"corporation":false,"usgs":true,"family":"Anderson","given":"R.B.","email":"","affiliations":[],"preferred":false,"id":491834,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Naftz, D. L.","contributorId":40624,"corporation":false,"usgs":true,"family":"Naftz","given":"D.","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":491833,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Day-Lewis, F. D. 0000-0003-3526-886X","orcid":"https://orcid.org/0000-0003-3526-886X","contributorId":35773,"corporation":false,"usgs":true,"family":"Day-Lewis","given":"F. D.","affiliations":[],"preferred":false,"id":491831,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Henderson, R.D.","contributorId":14269,"corporation":false,"usgs":true,"family":"Henderson","given":"R.D.","email":"","affiliations":[{"id":6619,"text":"University of Connecticutt","active":true,"usgs":false},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true}],"preferred":false,"id":491830,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rosenberry, D.O. 0000-0003-0681-5641","orcid":"https://orcid.org/0000-0003-0681-5641","contributorId":38500,"corporation":false,"usgs":true,"family":"Rosenberry","given":"D.O.","affiliations":[],"preferred":true,"id":491832,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stolp, Bernard J. 0000-0003-3803-1497","orcid":"https://orcid.org/0000-0003-3803-1497","contributorId":71942,"corporation":false,"usgs":true,"family":"Stolp","given":"Bernard J.","affiliations":[],"preferred":false,"id":491835,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jewell, P.","contributorId":77843,"corporation":false,"usgs":true,"family":"Jewell","given":"P.","email":"","affiliations":[],"preferred":false,"id":491836,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70095112,"text":"pp1798H - 2014 - Geomorphic changes caused by the 2011 flood at selected sites along the lower Missouri River and comparison to historical floods","interactions":[{"subject":{"id":70095112,"text":"pp1798H - 2014 - Geomorphic changes caused by the 2011 flood at selected sites along the lower Missouri River and comparison to historical floods","indexId":"pp1798H","publicationYear":"2014","noYear":false,"chapter":"H","title":"Geomorphic changes caused by the 2011 flood at selected sites along the lower Missouri River and comparison to historical floods"},"predicate":"IS_PART_OF","object":{"id":70047427,"text":"pp1798 - 2013 - 2011 floods of the central United States","indexId":"pp1798","publicationYear":"2013","noYear":false,"title":"2011 floods of the central United States"},"id":1}],"isPartOf":{"id":70047427,"text":"pp1798 - 2013 - 2011 floods of the central United States","indexId":"pp1798","publicationYear":"2013","noYear":false,"title":"2011 floods of the central United States"},"lastModifiedDate":"2024-10-18T13:25:37.893753","indexId":"pp1798H","displayToPublicDate":"2014-03-19T15:44:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":331,"text":"Professional Paper","code":"PP","onlineIssn":"2330-7102","printIssn":"1044-9612","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1798","chapter":"H","title":"Geomorphic changes caused by the 2011 flood at selected sites along the lower Missouri River and comparison to historical floods","docAbstract":"

An analysis of recent and historical U.S. Geological Survey streamgage information was used to assess geomorphic changes caused by the 2011 flood, in comparison to selected historical floods, at three streamgage sites along the lower Missouri River—Sioux City, Iowa; Omaha, Nebraska; and Kansas City, Missouri. Channel-width change was not evident at the three streamgage sites following the 2011 flood and likely was inhibited by bank stabilization. Pronounced changes in channel-bed elevation were indicated.

At Sioux City and Omaha, the geomorphic effects of the 2011 flood were similar in terms of the magnitude of channelbed scour and recovery. At both sites, the 2011 flood caused pronounced scour (about 3 feet) of the channel bed; however, at Omaha, most of the channel-bed scour occurred after the flood had receded. More than 1 year after the flood, the channel bed had only partially recovered (about 1 foot) at both sites. Pronounced scour (about 3 feet at Sioux City and about 1.5 feet at Omaha) also was caused by the 1952 flood, which had a substantially larger peak discharge but was much shorter in duration at both sites. Again, at Omaha, most of the channel- bed scour occurred after the flood had receded. At Sioux City, substantial recovery of the channel bed (about 2.5 feet) was documented 1 year after the 1952 flood. Recovery to the pre-flood elevation was complete by April 1954. The greater recovery following the 1952 flood, compared to the 2011 flood, likely was related to a more abundant sediment supply because the flood predated the completion of most of the main-stem dam, channelization, and bank stabilization projects. At Omaha, following the 1952 flood, the channel bed never fully recovered to its pre-flood elevation.

The geomorphic effect of the 2011 flood at Kansas City was fill (about 1 foot) on the channel bed followed by relative stability. The 1952 flood, which had a substantially larger peak discharge but was much shorter in duration, caused modest fill (about 0.5 foot) on the channel bed. The 1993 flood, which also had a substantially larger peak discharge but was much shorter in duration, caused pronounced scour of the channel bed (possibly as much as 4 feet). Similar to the floods at Omaha, much of the channel-bed scour at Kansas City occurred after the 1993 flood had receded. More than 1 year after the 1993 flood, following partial recovery (about 1 foot), the channel bed had stabilized, at least temporarily. Following the 1993 flood, the channel bed never fully recovered to its pre-flood elevation.

For each flood in the post-dam era that resulted in substantial channel-bed scour (Sioux City in 2011, Omaha in 2011, Kansas City in 1993), recovery of the channel bed to its pre-flood elevation had not occurred more than 1 year after the flood (20 years after the 1993 flood at Kansas City). Thus, the possibility exists that channel-bed scour caused by large floods may have a cumulative effect along the lower Missouri River. The persistence of the flood-related decreases in channel-bed elevation may be indicative of the constrained ability of the channel to recover given a limited sediment supply caused by one or more of the following factors: upstream storage of sediment in reservoirs, bank stabilization, commercial sand dredging, depletion of readily available sediment by the flood, and a lack of post-flood sediment contributions from tributaries.

","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"2011 floods of the central United States (Professional Paper 1798)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1798H","usgsCitation":"Juracek, K.E., 2014, Geomorphic changes caused by the 2011 flood at selected sites along the lower Missouri River and comparison to historical floods: U.S. Geological Survey Professional Paper 1798, iv, 15 p., https://doi.org/10.3133/pp1798H.","productDescription":"iv, 15 p.","numberOfPages":"24","onlineOnly":"Y","ipdsId":"IP-050647","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":284283,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/pp/1798h/","linkFileType":{"id":5,"text":"html"}},{"id":284284,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1798h/pdf/pp1798h.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":284285,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/pp1798h.jpg"}],"scale":"10000000","projection":"Clarke 1866 Albers Projection","country":"United States","state":"Colorado, Idaho, Iowa, Kansas, Missouri, Montana, Nebraska, North Dakota, South Dakota, Wyoming","otherGeospatial":"lower Missouri River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -110.0,35.0 ], [ -110.0,50.0 ], [ -90.0,50.0 ], [ -90.0,35.0 ], [ -110.0,35.0 ] ] ] } } ] }","contact":"

Contact Pubs Warehouse

","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd5e9de4b0b290850fbcf7","contributors":{"authors":[{"text":"Juracek, Kyle E. 0000-0002-2102-8980 kjuracek@usgs.gov","orcid":"https://orcid.org/0000-0002-2102-8980","contributorId":2022,"corporation":false,"usgs":true,"family":"Juracek","given":"Kyle","email":"kjuracek@usgs.gov","middleInitial":"E.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":491078,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70094490,"text":"sir20145030 - 2014 - Methods for estimating the magnitude and frequency of floods for urban and small, rural streams in Georgia, South Carolina, and North Carolina, 2011","interactions":[],"lastModifiedDate":"2017-01-17T20:56:35","indexId":"sir20145030","displayToPublicDate":"2014-03-19T14:26:00","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":"2014-5030","title":"Methods for estimating the magnitude and frequency of floods for urban and small, rural streams in Georgia, South Carolina, and North Carolina, 2011","docAbstract":"

Reliable estimates of the magnitude and frequency of floods are essential for the design of transportation and water-conveyance structures, flood-insurance studies, and flood-plain management. Such estimates are particularly important in densely populated urban areas. In order to increase the number of streamflow-gaging stations (streamgages) available for analysis, expand the geographical coverage that would allow for application of regional regression equations across State boundaries, and build on a previous flood-frequency investigation of rural U.S Geological Survey streamgages in the Southeast United States, a multistate approach was used to update methods for determining the magnitude and frequency of floods in urban and small, rural streams that are not substantially affected by regulation or tidal fluctuations in Georgia, South Carolina, and North Carolina. The at-site flood-frequency analysis of annual peak-flow data for urban and small, rural streams (through September 30, 2011) included 116 urban streamgages and 32 small, rural streamgages, defined in this report as basins draining less than 1 square mile. The regional regression analysis included annual peak-flow data from an additional 338 rural streamgages previously included in U.S. Geological Survey flood-frequency reports and 2 additional rural streamgages in North Carolina that were not included in the previous Southeast rural flood-frequency investigation for a total of 488 streamgages included in the urban and small, rural regression analysis. The at-site flood-frequency analyses for the urban and small, rural streamgages included the expected moments algorithm, which is a modification of the Bulletin 17B log-Pearson type III method for fitting the statistical distribution to the logarithms of the annual peak flows. Where applicable, the flood-frequency analysis also included low-outlier and historic information. Additionally, the application of a generalized Grubbs-Becks test allowed for the detection of multiple potentially influential low outliers.

\n
\n

Streamgage basin characteristics were determined using geographical information system techniques. Initial ordinary least squares regression simulations reduced the number of basin characteristics on the basis of such factors as statistical significance, coefficient of determination, Mallow’s Cp statistic, and ease of measurement of the explanatory variable. Application of generalized least squares regression techniques produced final predictive (regression) equations for estimating the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probability flows for urban and small, rural ungaged basins for three hydrologic regions (HR1, Piedmont–Ridge and Valley; HR3, Sand Hills; and HR4, Coastal Plain), which previously had been defined from exploratory regression analysis in the Southeast rural flood-frequency investigation. Because of the limited availability of urban streamgages in the Coastal Plain of Georgia, South Carolina, and North Carolina, additional urban streamgages in Florida and New Jersey were used in the regression analysis for this region. Including the urban streamgages in New Jersey allowed for the expansion of the applicability of the predictive equations in the Coastal Plain from 3.5 to 53.5 square miles. Average standard error of prediction for the predictive equations, which is a measure of the average accuracy of the regression equations when predicting flood estimates for ungaged sites, range from 25.0 percent for the 10-percent annual exceedance probability regression equation for the Piedmont–Ridge and Valley region to 73.3 percent for the 0.2-percent annual exceedance probability regression equation for the Sand Hills region.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145030","collaboration":"Prepared in cooperation with the South Carolina Department of Transportation, Office of Materials and Research, and the North Carolina Department of Transportation, Division of Highways (Hydraulics Unit)","usgsCitation":"Feaster, T., Gotvald, A.J., and Weaver, J., 2014, Methods for estimating the magnitude and frequency of floods for urban and small, rural streams in Georgia, South Carolina, and North Carolina, 2011 (First posted March 19, 2014; Revised March 26, 2014, ver. 1.1): U.S. Geological Survey Scientific Investigations Report 2014-5030, Report: vii, 104 p.; Application-of-Methods-Tool, https://doi.org/10.3133/sir20145030.","productDescription":"Report: vii, 104 p.; Application-of-Methods-Tool","numberOfPages":"116","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-051253","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":284263,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145030.jpg"},{"id":284261,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5030/pdf/sir2014-5030.pdf"},{"id":284260,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5030/"},{"id":284262,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2014/5030/sir2014-5030_applications_tool-ver1.1.xlsx"}],"country":"United States","state":"Georgia, North Carolina, South Carolina","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -86.04,29.95 ], [ -86.04,38.01 ], [ -74.69,38.01 ], [ -74.69,29.95 ], [ -86.04,29.95 ] ] ] } } ] }","edition":"First posted March 19, 2014; Revised March 26, 2014, ver. 1.1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53517055e4b05569d805a32a","contributors":{"authors":[{"text":"Feaster, Toby D. 0000-0002-5626-5011 tfeaster@usgs.gov","orcid":"https://orcid.org/0000-0002-5626-5011","contributorId":1109,"corporation":false,"usgs":true,"family":"Feaster","given":"Toby D.","email":"tfeaster@usgs.gov","affiliations":[{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true}],"preferred":false,"id":490633,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gotvald, Anthony J. 0000-0002-9019-750X agotvald@usgs.gov","orcid":"https://orcid.org/0000-0002-9019-750X","contributorId":1970,"corporation":false,"usgs":true,"family":"Gotvald","given":"Anthony","email":"agotvald@usgs.gov","middleInitial":"J.","affiliations":[{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":490634,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Weaver, J. Curtis","contributorId":42260,"corporation":false,"usgs":true,"family":"Weaver","given":"J. Curtis","affiliations":[],"preferred":false,"id":490635,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70094629,"text":"ds826 - 2014 - Topographic data of selected areas along the Alabama River near Montgomery, Alabama, collected using mobile terrestrial light detection and ranging (T-LiDAR) technology","interactions":[],"lastModifiedDate":"2014-03-19T12:54:35","indexId":"ds826","displayToPublicDate":"2014-03-19T12:47:00","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":"826","title":"Topographic data of selected areas along the Alabama River near Montgomery, Alabama, collected using mobile terrestrial light detection and ranging (T-LiDAR) technology","docAbstract":"Topographic data at selected areas within the Alabama River flood plain near Montgomery, Alabama, were collected using a truck-mounted mobile terrestrial light detection and ranging system. These data were collected for inclusion in a flood inundation model developed by the National Weather Service in Birmingham, Alabama. Data are presented as ArcGIS point shapefiles with the extension .shp.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds826","collaboration":"Prepared in cooperation with the National Weather Service Forecast Office, Birmingham, Alabama","usgsCitation":"Kimbrow, D., 2014, Topographic data of selected areas along the Alabama River near Montgomery, Alabama, collected using mobile terrestrial light detection and ranging (T-LiDAR) technology: U.S. Geological Survey Data Series 826, HTML Document; Downloads Directory, https://doi.org/10.3133/ds826.","productDescription":"HTML Document; Downloads Directory","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-051220","costCenters":[{"id":105,"text":"Alabama Water Science Center","active":true,"usgs":true}],"links":[{"id":284234,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds826.jpg"},{"id":284233,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/0826/Downloads"},{"id":284231,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0826/"},{"id":284235,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0826/title_page.html"}],"country":"United States","state":"Alabama","city":"Montgomery","otherGeospatial":"Alabama River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -86.419,32.249 ], [ -86.419,32.437 ], [ -86.072,32.437 ], [ -86.072,32.249 ], [ -86.419,32.249 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd7929e4b0b2908510ca51","contributors":{"authors":[{"text":"Kimbrow, D.R.","contributorId":25702,"corporation":false,"usgs":true,"family":"Kimbrow","given":"D.R.","affiliations":[],"preferred":false,"id":490673,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ]}