Conventional, regression-based methods of inferring depth from passive optical image data undermine the advantages of remote sensing for characterizing river systems. This study introduces and evaluates a more flexible framework, Image-to-Depth Quantile Transformation (IDQT), that involves linking the frequency distribution of pixel values to that of depth. In addition, a new image processing workflow involving deep water correction and Minimum Noise Fraction (MNF) transformation can reduce a hyperspectral data set to a single variable related to depth and thus suitable for input to IDQT. Applied to a gravel bed river, IDQT avoided negative depth estimates along channel margins and underpredictions of pool depth. Depth retrieval accuracy (R25 0.79) and precision (0.27 m) were comparable to an established band ratio-based method, although a small shallow bias (0.04 m) was observed. Several ways of specifying distributions of pixel values and depths were evaluated but had negligible impact on the resulting depth estimates, implying that IDQT was robust to these implementation details. In essence, IDQT uses frequency distributions of pixel values and depths to achieve an aspatial calibration; the image itself provides information on the spatial distribution of depths. The approach thus reduces sensitivity to misalignment between field and image data sets and allows greater flexibility in the timing of field data collection relative to image acquisition, a significant advantage in dynamic channels. IDQT also creates new possibilities for depth retrieval in the absence of field data if a model could be used to predict the distribution of depths within a reach.
","language":"English","publisher":"AGU Publications","doi":"10.1002/2016WR018730","usgsCitation":"Legleiter, C.J., 2016, Inferring river bathymetry via Image-to-Depth Quantile Transformation (IDQT): Water Resources Research, v. 52, no. 5, p. 3722-3741, https://doi.org/10.1002/2016WR018730.","productDescription":"20 p.","startPage":"3722","endPage":"3741","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-072989","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":470836,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2016wr018730","text":"Publisher Index Page"},{"id":324402,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"52","issue":"5","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-14","publicationStatus":"PW","scienceBaseUri":"5772401fe4b07657d1a7937e","contributors":{"authors":[{"text":"Legleiter, Carl J. 0000-0003-0940-8013 cjl@usgs.gov","orcid":"https://orcid.org/0000-0003-0940-8013","contributorId":169002,"corporation":false,"usgs":true,"family":"Legleiter","given":"Carl","email":"cjl@usgs.gov","middleInitial":"J.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":640728,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70174065,"text":"70174065 - 2016 - Gravel-bed river floodplains are the ecological nexus of glaciated mountain landscapes","interactions":[],"lastModifiedDate":"2016-06-27T11:11:47","indexId":"70174065","displayToPublicDate":"2016-06-27T12:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5010,"text":"Science Advances","active":true,"publicationSubtype":{"id":10}},"title":"Gravel-bed river floodplains are the ecological nexus of glaciated mountain landscapes","docAbstract":"Gravel-bed river floodplains in mountain landscapes disproportionately concentrate diverse habitats, nutrient cycling, productivity of biota, and species interactions. Although stream ecologists know that river channel and floodplain habitats used by aquatic organisms are maintained by hydrologic regimes that mobilize gravel-bed sediments, terrestrial ecologists have largely been unaware of the importance of floodplain structures and processes to the life requirements of a wide variety of species. We provide insight into gravel-bed rivers as the ecological nexus of glaciated mountain landscapes. We show why gravel-bed river floodplains are the primary arena where interactions take place among aquatic, avian, and terrestrial species from microbes to grizzly bears and provide essential connectivity as corridors for movement for both aquatic and terrestrial species. Paradoxically, gravel-bed river floodplains are also disproportionately unprotected where human developments are concentrated. Structural modifications to floodplains such as roads, railways, and housing and hydrologicaltering hydroelectric or water storage dams have severe impacts to floodplain habitat diversity and productivity, restrict local and regional connectivity, and reduce the resilience of both aquatic and terrestrial species, including adaptation to climate change. To be effective, conservation efforts in glaciated mountain landscapes intended to benefit the widest variety of organisms need a paradigm shift that has gravel-bed rivers and their floodplains as the central focus and that prioritizes the maintenance or restoration of the intact structure and processes of these critically important systems throughout their length and breadth.
","language":"English","publisher":"American Association for the Advancement of Science","doi":"10.1126/sciadv.1600026","usgsCitation":"Hauer, F.R., Locke, H., Dreitz, V., Hebblewhite, M., Lowe, W., Muhlfeld, C.C., Nelson, C., Proctor, M.F., and Rood, S.B., 2016, Gravel-bed river floodplains are the ecological nexus of glaciated mountain landscapes: Science Advances, v. 2, no. 6, e1600026; 13 p., https://doi.org/10.1126/sciadv.1600026.","productDescription":"e1600026; 13 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068965","costCenters":[{"id":547,"text":"Rocky Mountain Geographic Science Center","active":true,"usgs":true}],"links":[{"id":470839,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1126/sciadv.1600026","text":"Publisher Index Page"},{"id":324397,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"2","issue":"6","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5772401fe4b07657d1a79373","contributors":{"authors":[{"text":"Hauer, F. Richard","contributorId":76892,"corporation":false,"usgs":true,"family":"Hauer","given":"F.","email":"","middleInitial":"Richard","affiliations":[],"preferred":false,"id":640780,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Locke, Harvey","contributorId":172456,"corporation":false,"usgs":false,"family":"Locke","given":"Harvey","email":"","affiliations":[{"id":27049,"text":"Yellowstone to Yukon Conservation Initiative","active":true,"usgs":false}],"preferred":false,"id":640781,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dreitz, Victoria","contributorId":172457,"corporation":false,"usgs":false,"family":"Dreitz","given":"Victoria","affiliations":[{"id":5097,"text":"University of Montana, Division of Biological Sciences","active":true,"usgs":false}],"preferred":false,"id":640782,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hebblewhite, Mark","contributorId":69455,"corporation":false,"usgs":true,"family":"Hebblewhite","given":"Mark","affiliations":[],"preferred":false,"id":640783,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lowe, Winsor","contributorId":115672,"corporation":false,"usgs":true,"family":"Lowe","given":"Winsor","affiliations":[],"preferred":false,"id":640784,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Muhlfeld, Clint C. 0000-0002-4599-4059 cmuhlfeld@usgs.gov","orcid":"https://orcid.org/0000-0002-4599-4059","contributorId":924,"corporation":false,"usgs":true,"family":"Muhlfeld","given":"Clint","email":"cmuhlfeld@usgs.gov","middleInitial":"C.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":640779,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Nelson, Cara","contributorId":172458,"corporation":false,"usgs":false,"family":"Nelson","given":"Cara","email":"","affiliations":[{"id":5097,"text":"University of Montana, Division of Biological Sciences","active":true,"usgs":false}],"preferred":false,"id":640785,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Proctor, Michael F.","contributorId":150939,"corporation":false,"usgs":false,"family":"Proctor","given":"Michael","email":"","middleInitial":"F.","affiliations":[{"id":18147,"text":"Birchdale Ecological","active":true,"usgs":false}],"preferred":false,"id":640786,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Rood, Stewart B.","contributorId":169010,"corporation":false,"usgs":false,"family":"Rood","given":"Stewart","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":640787,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70170827,"text":"ds995 - 2016 - Post-Hurricane Joaquin coastal oblique aerial photographs collected from the South Carolina/North Carolina border to Montauk Point, New York, October 7–9, 2015","interactions":[],"lastModifiedDate":"2022-11-02T14:57:45.94871","indexId":"ds995","displayToPublicDate":"2016-06-27T11:00:00","publicationYear":"2016","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":"995","title":"Post-Hurricane Joaquin coastal oblique aerial photographs collected from the South Carolina/North Carolina border to Montauk Point, New York, October 7–9, 2015","docAbstract":"The U.S. Geological Survey (USGS), as part of the National Assessment of Coastal Change Hazards project, conducts baseline and storm-response photography missions to document and understand the changes in vulnerability of the Nation's coasts to extreme storms (Morgan, 2009). On October 7–9, 2015, the USGS conducted an oblique aerial photographic survey of the coast from the South Carolina/North Carolina border to Montauk Point, New York (fig. 1), aboard a Cessna 182 (aircraft) at an altitude of 500 feet (ft) and approximately 1,200 ft offshore fig. 2. This mission was conducted to collect post-Hurricane Joaquin data for assessing incremental changes in the beach and nearshore area since the last surveys, mission flown in September 2014 (Virginia to New York: Morgan, 2015), November 2012 (northern North Carolina: Morgan and others, 2014) and May 2008 (southern North Carolina: unpublished report), and the data can be used to assess of future coastal change.
The photographs in this report are Joint Photographic Experts Group (JPEG) images. ExifTool was used to add the following to the header of each photo: time of collection, Global Positioning System (GPS) latitude, GPS longitude, keywords, credit, artist (photographer), caption, copyright, and contact information. The photograph locations are an estimate of the position of the aircraft at the time the photograph was taken and do not indicate the location of any feature in the images (see the Navigation Data page). These photographs document the state of the barrier islands and other coastal features at the time of the survey. Pages containing thumbnail images of the photographs, referred to as contact sheets, were created in 5-minute segments of flight time. These segments can be found on the Photos and Maps page. Photographs can be opened directly with any JPEG-compatible image viewer by clicking on a thumbnail on the contact sheet.
In addition to the photographs, a Google Earth Keyhole Markup Language (KML) file is provided and can be used to view the images by clicking on the marker and then clicking on either the thumbnail or the link above the thumbnail. The KML file was created using the photographic navigation files. This KML file can be found in the kml folder.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds995","usgsCitation":"Morgan, K.L.M., 2016, Post-Hurricane Joaquin coastal oblique aerial photographs collected from the South Carolina/North Carolina border to Montauk Point, New York, October 7–9, 2015: U.S. Geological Survey Data Series 995, https://dx.doi.org/10.3133/ds995.","productDescription":"HTML Document","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-074292","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":321248,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0995"},{"id":324389,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"}],"country":"United States","state":"Delaware, Maryland, New Jersey, New York, North Carolina, South Carolina, Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -78.55224609374999,\n 33.7243396617476\n ],\n [\n -77.816162109375,\n 33.76088200086917\n ],\n [\n -76.431884765625,\n 34.58799745550482\n ],\n [\n -75.41015624999999,\n 35.21869749632885\n ],\n [\n -75.333251953125,\n 35.7286770448517\n ],\n [\n -75.860595703125,\n 36.923547681089296\n ],\n [\n -75.552978515625,\n 37.448696585910376\n ],\n [\n -74.87182617187499,\n 38.53097889440026\n ],\n [\n -74.70703125,\n 39.00211029922512\n ],\n [\n -74.014892578125,\n 39.63953756436671\n ],\n [\n -73.89404296875,\n 40.51379915504413\n ],\n [\n -72.960205078125,\n 40.60561205826018\n ],\n [\n -71.630859375,\n 41.062786068733026\n ],\n [\n -71.817626953125,\n 41.1455697310095\n ],\n [\n -73.10302734375,\n 40.85537053192496\n ],\n [\n -73.948974609375,\n 40.73893324113603\n ],\n [\n -74.1357421875,\n 40.55554790286311\n ],\n [\n -74.38842773437499,\n 39.7240885773337\n ],\n [\n -75.047607421875,\n 39.00211029922512\n ],\n [\n -75.234375,\n 38.47939467327645\n ],\n [\n -76.256103515625,\n 36.94111143010772\n ],\n [\n -75.684814453125,\n 35.68407153314097\n ],\n [\n -75.69580078125,\n 35.38904996691167\n ],\n [\n -76.57470703125,\n 34.92197103616377\n ],\n [\n -77.376708984375,\n 34.7506398050501\n ],\n [\n -78.046875,\n 34.23451236236984\n ],\n [\n -78.837890625,\n 33.916013113401696\n ],\n [\n -78.55224609374999,\n 33.7243396617476\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, St. Petersburg Coastal and Marine Science Center
U.S. Geological Survey
600 4th Street South
St. Petersburg, FL 33701
(727) 502–8000
http://coastal.er.usgs.gov
In shallow coastal bays where nutrient loading and riverine inputs are low, turbidity, and the consequent light environment are controlled by resuspension of bed sediments due to wind-waves and tidal currents. High sediment resuspension and low light environments can limit benthic primary productivity; however, both currents and waves are affected by the presence of benthic plants such as seagrass. This feedback between the presence of benthic primary producers such as seagrass and the consequent light environment has been predicted to induce bistable dynamics locally. However, these vegetated areas influence a larger area than they footprint, including a barren adjacent downstream area which exhibits reduced shear stresses. Here we explore through modeling how the patchy structure of seagrass meadows on a landscape may affect sediment resuspension and the consequent light environment due to the presence of this sheltered region. Heterogeneous vegetation covers comprising a mosaic of randomly distributed patches were generated to investigate the effect of patch modified hydrodynamics. Actual cover of vegetation on the landscape was used to facilitate comparisons across landscape realizations. Hourly wave and current shear stresses on the landscape along with suspended sediment concentration and light attenuation characteristics were then calculated and spatially averaged to examine how actual cover and mean water depth affect the bulk sediment and light environment. The results indicate that an effective cover, which incorporates the sheltering area, has important controls on the distributions of shear stress, suspended sediment, light environment, and consequent seagrass habitat suitability. Interestingly, an optimal habitat occurs within a depth range where, if actual cover is reduced past some threshold, the bulk light environment would no longer favor seagrass growth.
","language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.advwatres.2015.09.001","usgsCitation":"Carr, J., D’Odorico, P., McGlathery, K., and Wiberg, P.L., 2016, Spatially explicit feedbacks between seagrass meadow structure, sediment and light: Habitat suitability for seagrass growth: Advances in Water Resources, v. 93, Part B, p. 315-325, https://doi.org/10.1016/j.advwatres.2015.09.001.","productDescription":"21 p.","startPage":"315","endPage":"325","numberOfPages":"21","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-067162","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":470840,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.advwatres.2015.09.001","text":"Publisher Index Page"},{"id":324539,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":324494,"type":{"id":15,"text":"Index Page"},"url":"https://www.sciencedirect.com/science/article/pii/S030917081500202X"}],"volume":"93, Part B","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57739fb7e4b07657d1a90d66","contributors":{"authors":[{"text":"Carr, Joel A. 0000-0002-9164-4156 jcarr@usgs.gov","orcid":"https://orcid.org/0000-0002-9164-4156","contributorId":168645,"corporation":false,"usgs":true,"family":"Carr","given":"Joel A.","email":"jcarr@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":641019,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"D’Odorico, Paul","contributorId":172510,"corporation":false,"usgs":false,"family":"D’Odorico","given":"Paul","email":"","affiliations":[],"preferred":false,"id":641079,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McGlathery, Karen","contributorId":36057,"corporation":false,"usgs":true,"family":"McGlathery","given":"Karen","affiliations":[],"preferred":false,"id":641080,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wiberg, Patricia L.","contributorId":72716,"corporation":false,"usgs":true,"family":"Wiberg","given":"Patricia","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":641081,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70174046,"text":"fs20163037 - 2016 - Mapping water use—Landsat and water resources in the United States","interactions":[],"lastModifiedDate":"2019-09-20T10:50:09","indexId":"fs20163037","displayToPublicDate":"2016-06-27T00:00:00","publicationYear":"2016","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":"2016-3037","displayTitle":"Mapping Water Use—Landsat and Water Resources in the United States","title":"Mapping water use—Landsat and water resources in the United States","docAbstract":"Using Landsat satellite data, scientists with the U.S. Geological Survey have helped to refine a technique called evapotranspiration mapping to measure how much water crops are using across landscapes and through time. These water-use maps are created using a computer model that integrates Landsat and weather data.
Crucial to the process is the thermal (infrared) band from Landsat. Using the Landsat thermal band with its 100-meter resolution, water-use maps can be created at a scale detailed enough to show how much water crops are using at the level of individual fields anywhere in the world.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20163037","collaboration":"Prepared in cooperation with the National Aeronautics and Space Administration","usgsCitation":"U.S. Geological Survey, 2016, Mapping water use—Landsat and water resources in the United States (ver. 1.1, September 2019): U.S. Geological Survey Fact Sheet 2016–3037, 2 p., https://doi.org/10.3133/fs20163037.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-075235","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":367504,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2016/3037/fs20163037_2.pdf","text":"Report","size":"5.74 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2016–3037"},{"id":324411,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2016/3037/coverthb2.jpg"},{"id":367505,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/fs/2016/3037/versionHist.txt","size":"1.0 kB","linkFileType":{"id":2,"text":"txt"},"description":"Version History"}],"edition":"Version 1.0: June 27, 2016; Version 1.1 September 18, 2019","contact":"Director, Earth Resources Observation and Science (EROS) Center
U.S. Geological Survey
47914 252nd Street
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While commonplace in clinical settings, DNA-based assays for identification or enumeration of drinking water pathogens and other biological contaminants remain widely unadopted by the monitoring community. In this study, shotgun metagenomics was used to identify taste-and-odor producers and toxin-producing cyanobacteria over a 2-year period in a drinking water reservoir. The sequencing data implicated several cyanobacteria, including Anabaena spp.,Microcystis spp., and an unresolved member of the order Oscillatoriales as the likely principal producers of geosmin, microcystin, and 2-methylisoborneol (MIB), respectively. To further demonstrate this, quantitative PCR (qPCR) assays targeting geosmin-producing Anabaena and microcystin-producing Microcystis were utilized, and these data were fitted using generalized linear models and compared with routine monitoring data, including microscopic cell counts, sonde-based physicochemical analyses, and assays of all inorganic and organic nitrogen and phosphorus forms and fractions. The qPCR assays explained the greatest variation in observed geosmin (adjusted R2 = 0.71) and microcystin (adjusted R2 = 0.84) concentrations over the study period, highlighting their potential for routine monitoring applications. The origin of the monoterpene cyclase required for MIB biosynthesis was putatively linked to a periphytic cyanobacterial mat attached to the concrete drinking water inflow structure. We conclude that shotgun metagenomics can be used to identify microbial agents involved in water quality deterioration and to guide PCR assay selection or design for routine monitoring purposes. Finally, we offer estimates of microbial diversity and metagenomic coverage of our data sets for reference to others wishing to apply shotgun metagenomics to other lacustrine systems.
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2016 - Relation between Enterococcus concentrations and turbidity in fresh and saline recreational waters, coastal Horry County, South Carolina, 2003–04","interactions":[],"lastModifiedDate":"2016-12-08T17:14:53","indexId":"ofr20161015","displayToPublicDate":"2016-06-24T10:45:00","publicationYear":"2016","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":"2016-1015","title":"Relation between Enterococcus concentrations and turbidity in fresh and saline recreational waters, coastal Horry County, South Carolina, 2003–04","docAbstract":"Bacteria related to the intestinal tract of humans and other warm-blooded animals have been detected in fresh and saline surface waters used for recreational purposes in coastal areas of Horry County, South Carolina, since the early 2000s. Specifically, concentrations of the facultative anaerobic organism, Enterococcus, have been observed to exceed the single-sample regulatory limit of 104 colony forming units per 100 milliliters of water. Water bodies characterized by these concentrations are identified on the 303(d) list for impaired water in South Carolina; moreover, because current analytical methods used to monitor Enterococcus concentrations take up to 1 day for results to become available, water-quality advisories are not reflective of the actual health risk.
\nTo determine if Enterococcus concentrations in surface water could be assessed in a more rapid manner, an investigation was completed between 2003 and 2004 in the study area of coastal Horry County, South Carolina. The study was designed to assess the relation between Enterococcus concentrations and turbidity, which, unlike Enterococcus concentrations, can be measured continuously by using a multiparameter water-quality sensor and results reported in real time. In 2003, three water-quality data collection stations that included a multiparameter water-quality sensor that measured turbidity were located in three representative surface-water basins in coastal Horry County, South Carolina. All these locations had previous reports of high Enterococcus concentrations. At each station, the water-quality sensor was placed in the water column and continuously measured turbidity, pH, specific conductivity, dissolved oxygen, and temperature. Each water-quality data collection station also monitored instantaneous precipitation and wind speed and direction. Surface-water samples were collected at each station during events characterized by no precipitation and by some recorded precipitation using manual and automatic methods, and analyzed for Enterococcus concentrations. A comparison of Enterococcus concentrations in surface-water samples collected simultaneously using both methods indicated a positive relation, although the average percent relative difference between the methods was 46 percent.
\nDuring a period of no precipitation in February 2004, no relation between turbidity and Enterococcus concentrations was observed for surface-water samples collected at the water-quality data collection station located in the channel that drains a freshwater swamp. In contrast, during periods of precipitation in March and August 2004 at this location, a positive relation was observed between turbidity and Enterococcus concentrations in surface-water samples; that is, water samples characterized by higher turbidity also contained higher Enterococcus concentrations. At the water-quality data collection station located in a channel that drains to the surf zone of the Atlantic Ocean, no relation was observed between turbidity and Enterococcus concentrations during periods of either no precipitation (July 2004) or precipitation (August 2004). At this location, the turbidity was inversely related to relative tide height, high turbidity was observed during low tide when freshwater flowed seaward, and low turbidity was observed during high tide when saline seawater flowed landward.
\nThe positive relation observed between turbidity and Enterococcus concentrations in surface water at the water-quality data collection station located in the channel that drains a freshwater swamp may be attributed to bacterial survival in the abundant channel bed sediments that characterized this more naturalized area. Surface-water bed sediments collected near each water-quality data collection station and the surf zone were incubated in static microcosms in the laboratory and analyzed for Enterococcus concentrations over time. Enterococcus concentrations continued to persist in bed sediments collected in the channel that drains the swamp even after almost 4 months of incubation. Conversely, enterococci were not observed to persist in bed sediments characterized by high specific conductance. Although it is currently (2016) unknown whether this persistence of enterococci demonstrates growth or viability, the data indicate that enterococci can exist in channel bed-sediment environments outside of a host for a long time. This observation confirms previous reports that challenge the use of Enterococcus concentrations as an indicator of the recent introduction of fecal-related material and the associated acute risk to other pathogens.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/ofr20161015","collaboration":"Prepared in cooperation with Horry County Stormwater Management ","usgsCitation":"Landmeyer, J.E., and Garigen, T.J., 2016, Relation between Enterococcus concentrations and turbidity in fresh and saline recreational waters, coastal Horry County, South Carolina, 2003–04: U.S. Geological Survey Open-File Report 2016–1015, 21 p., https://dx.doi.org/10.3133/ofr20161015.","productDescription":"Report: viii, 21 p., Appendixes: Tables 1-1, 1-2, 1-3","startPage":"1","endPage":"21","numberOfPages":"34","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-064657","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":324066,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1015/ofr20161015.pdf","text":"Report","size":"12.3 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South Atlantic Water Science Center
U.S. Geological Survey
1770 Corporate Drive, Suite 500
Norcross, GA 30093
(678) 924–6700
https://www.usgs.gov/water/southatlantic/
Working in partnership since 1996, the U.S. Fish and Wildlife Service and the Nisqually Indian Tribe have restored 902 acres of tidally influenced coastal marsh in the Nisqually River Delta (NRD), making it the largest estuary-restoration project in the Pacific Northwest to date. Marsh restoration increases the capacity of the estuary to support a diversity of wildlife species. Restoration also increases carbon (C) production of marsh plant communities that support food webs for wildlife and can help mitigate climate change through long-term C storage in marsh soils.
In 2015, an interdisciplinary team of U.S. Geological Survey (USGS) researchers began to study the benefits of carbon for wetland wildlife and storage in the NRD. Our primary goals are (1) to identify the relative importance of the different carbon sources that support juvenile chinook (Oncorhynchus tshawytscha) food webs and contribute to current and historic peat formation, (2) to determine the net ecosystem carbon balance (NECB) in a reference marsh and a restoration marsh site, and (3) to model the sustainability of the reference and restoration marshes under projected sea-level rise conditions along with historical vegetation change. In this fact sheet, we focus on the main C sources and exchanges to determine NECB, including carbon dioxide (CO2) uptake through plant photosynthesis, the loss of CO2 through plant and soil respiration, emissions of methane (CH4), and the lateral movement or leaching loss of C in tidal waters.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20163042","collaboration":"Prepared in cooperation with the U.S.G.S. Land Carbon Program and the U.S. Fish and Wildlife Service","usgsCitation":"Anderson, Frank, 2016, Assessing wildlife benefits and carbon from restored and natural coastal marshes in the Nisqually River delta: Determining marsh net ecosystem carbon balance: U.S. Geological Survey Fact Sheet 2016-3042, 2 p., https://dx.doi.org/10.3133/fs20163042.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065411","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":324375,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2016/3042/coverthb.jpg"},{"id":324376,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2016/3042/fs20163042.pdf","text":"Report","size":"898 KB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2016-3042"}],"country":"United States","state":"Washington","otherGeospatial":"Nisqually River Delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.73977279663085,\n 47.066497210333836\n ],\n [\n -122.73977279663085,\n 47.1214245689578\n ],\n [\n -122.66733169555663,\n 47.1214245689578\n ],\n [\n -122.66733169555663,\n 47.066497210333836\n ],\n [\n -122.73977279663085,\n 47.066497210333836\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
http://ca.water.usgs.gov
The U.S. Geological Survey is collecting geologic samples from local stream channels, aquifer materials, and rock outcrops for studies of trace elements in the Mojave Desert, southern California. These samples are collected because geologic materials can release a variety of elements to the environment when exposed to water. The samples are to be analyzed with a handheld X-ray fluorescence (XRF) spectrometer to determine the concentrations of up to 27 elements, including chromium.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20163043","usgsCitation":"Groover, K.D., and Izbicki, J.A., 2016, Geochemical analysis using a handheld X-Ray Fluorescence spectrometer. U.S. Geological Survey Fact Sheet 2015-3043, 2 p., https://dx.doi.org/10.3133/fs20163043.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-068919","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":324370,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2016/3043/fs20163043.pdf","text":"Report","size":"1.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2016-3043"},{"id":324369,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2016/3043/coverthb.jpg"}],"contact":"Director, California Water Science Center
6000 J Street, Placer Hall
Sacramento, CA 95819
http://ca.water.usgs.gov/mojave/
http://ca.water.usgs.gov/projects/hinkley/
This report describes the analytical methods and results of a pilot study to enhance the Ohio StreamStats application by adding the ability to obtain water-use information for selected areas in the northeast quadrant of Ohio. Water-use estimates are determined in StreamStats through a simple multistep process.
\nWater-use data used to develop the Ohio StreamStats water-use application were obtained from the Ohio Department of Natural Resources (ODNR) and 2010 countywide estimates of self-supplied domestic water use (hereafter referred to as “domestic water use”) compiled by the U.S. Geological Survey (USGS). With the exception of domestic water uses, monthly time series of reported water uses for 2005–2012 are used to calculate average monthly and average annual withdrawals. Domestic water use is estimated from the USGS 2010 countywide estimates, assuming that water use is distributed uniformly in space and time. Consumptive-use coefficients are used to estimate net withdrawals and facilitate computation of return flows.
\nTemporary water-use registrations for hydraulic fracturing are tabulated separately from the other water uses. Water-use indices are computed by dividing average annual net withdrawals (with and without temporary registrations) by the mean October streamflow estimated with StreamStats. The water-use indices are intended to provide metrics of potential consumptive water use.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165077","collaboration":"Prepared in cooperation with the Ohio Water Development Authority and the Muskingum Watershed Conservancy District","usgsCitation":"Koltun, G.F., Nardi, M.R., and Shaffer, K.H., 2016, Estimation of upstream water use with Ohio’s StreamStats application: U.S. Geological Survey Scientific Investigations Report 2016–5077, 13 p., https://dx.doi.org/10.3133/sir20165077.","productDescription":"iv, 12 p.","numberOfPages":"20","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-072219","costCenters":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"links":[{"id":324337,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5077/sir20165077.pdf","text":"Report","size":"3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5077"},{"id":324336,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5077/coverthb.jpg"}],"contact":"Director, Ohio Water Science Center
U.S. Geological Survey
6480 Doubletree Ave
Columbus, OH 43229–1111
http://oh.water.usgs.gov/
Excessive phosphorus (TP) and nitrogen (TN) inputs from the Red–Assiniboine River Basin (RARB) have been linked to eutrophication of Lake Winnipeg; therefore, it is important for the management of water resources to understand where and from what sources these nutrients originate. The RARB straddles the Canada–United States border and includes portions of two provinces and three states. This study represents the first binationally focused application of SPAtially Referenced Regressions on Watershed attributes (SPARROW) models to estimate loads and sources of TP and TN by jurisdiction and basin at multiple spatial scales. Major hurdles overcome to develop these models included: (1) harmonization of geospatial data sets, particularly construction of a contiguous stream network; and (2) use of novel calibration steps to accommodate limitations in spatial variability across the model extent and in the number of calibration sites. Using nutrient inputs for a 2002 base year, a RARB TP SPARROW model was calibrated that included inputs from agriculture, forests and wetlands, wastewater treatment plants (WWTPs) and stream channels, and a TN model was calibrated that included inputs from agriculture, WWTPs and atmospheric deposition. At the RARB outlet, downstream from Winnipeg, Manitoba, the majority of the delivered TP and TN came from the Red River Basin (90%), followed by the Upper Assiniboine River and Souris River basins. Agriculture was the single most important TP and TN source for each major basin, province and state. In general, stream channels (historically deposited nutrients and from bank erosion) were the second most important source of TP. Performance metrics for the RARB SPARROW model are similarly robust compared to other, larger US SPARROW models making it a potentially useful tool to address questions of where nutrients originate and their relative contributions to loads delivered to Lake Winnipeg.
","language":"English","publisher":"Taylor and Francis Group","doi":"10.1080/07011784.2016.1178601","collaboration":"International Joint Commission","usgsCitation":"Benoy, G.A., Jenkinson, R., Robertson, D.M., and Saad, D.A., 2016, Nutrient delivery to Lake Winnipeg from the Red-Assiniboine River Basin – A binational application of the SPARROW model: Canadian Water Resources Journal, v. 41, no. 3, p. 429-447, https://doi.org/10.1080/07011784.2016.1178601.","productDescription":"19 p.","startPage":"429","endPage":"447","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068514","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":324322,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":324318,"type":{"id":15,"text":"Index Page"},"url":"https://dx.doi.org/10.1080/07011784.2016.1178601"}],"country":"Canada, United States","state":"Manitoba, Minnesota, Saskatchewan","otherGeospatial":"Assiniboine River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.152099609375,\n 50.064191736659104\n ],\n [\n -98.009033203125,\n 50.2612538275847\n ],\n [\n -99.47021484375,\n 50.162824333817284\n ],\n [\n -102.469482421875,\n 51.248163159055906\n ],\n [\n -104.8974609375,\n 50.597186230587035\n ],\n [\n -103.853759765625,\n 49.1888842152458\n ],\n [\n -101.898193359375,\n 48.04870994288686\n ],\n [\n -99.41528320312499,\n 48.268569112964336\n ],\n [\n -97.152099609375,\n 50.064191736659104\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"41","issue":"3","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2016-06-20","publicationStatus":"PW","scienceBaseUri":"576cfa1de4b07657d1a33c62","contributors":{"authors":[{"text":"Benoy, Glenn A. 0000-0001-6530-7220","orcid":"https://orcid.org/0000-0001-6530-7220","contributorId":172405,"corporation":false,"usgs":false,"family":"Benoy","given":"Glenn","email":"","middleInitial":"A.","affiliations":[{"id":13361,"text":"International Joint Commission, Washington DC","active":true,"usgs":false}],"preferred":false,"id":640604,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jenkinson, R. Wayne","contributorId":172406,"corporation":false,"usgs":false,"family":"Jenkinson","given":"R. Wayne","affiliations":[{"id":13361,"text":"International Joint Commission, Washington DC","active":true,"usgs":false}],"preferred":false,"id":640605,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Robertson, Dale M. 0000-0001-6799-0596 dzrobert@usgs.gov","orcid":"https://orcid.org/0000-0001-6799-0596","contributorId":150760,"corporation":false,"usgs":true,"family":"Robertson","given":"Dale","email":"dzrobert@usgs.gov","middleInitial":"M.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":640606,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Saad, David A. dasaad@usgs.gov","contributorId":121,"corporation":false,"usgs":true,"family":"Saad","given":"David","email":"dasaad@usgs.gov","middleInitial":"A.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":640607,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70174034,"text":"70174034 - 2016 - Spatial modeling of wild bird risk factors to investigate highly pathogenic A(H5N1) avian influenza virus transmission","interactions":[],"lastModifiedDate":"2018-08-09T12:46:44","indexId":"70174034","displayToPublicDate":"2016-06-23T14:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":948,"text":"Avian Diseases","active":true,"publicationSubtype":{"id":10}},"title":"Spatial modeling of wild bird risk factors to investigate highly pathogenic A(H5N1) avian influenza virus transmission","docAbstract":"One of the longest-persisting avian influenza viruses in history, highly pathogenic avian influenza virus (HPAIV) A(H5N1), continues to evolve after 18 years, advancing the threat of a global pandemic. Wild waterfowl (family Anatidae), are reported as secondary transmitters of HPAIV, and primary reservoirs for low-pathogenic avian influenza viruses, yet spatial inputs for disease risk modeling for this group have been lacking. Using GIS and Monte Carlo simulations, we developed geospatial indices of waterfowl abundance at 1 and 30 km resolutions and for the breeding and wintering seasons for China, the epicenter of H5N1. Two spatial layers were developed: cumulative waterfowl abundance (WAB), a measure of predicted abundance across species, and cumulative abundance weighted by H5N1 prevalence (WPR), whereby abundance for each species was adjusted based on prevalence values then totaled across species. Spatial patterns of the model output differed between seasons, with higher WAB and WPR in the northern and western regions of China for the breeding season and in the southeast for the wintering season. Uncertainty measures indicated highest error in southeastern China for both WAB and WPR. We also explored the effect of resampling waterfowl layers from 1 km to 30 km resolution for multi-scale risk modeling. Results indicated low average difference (less than 0.16 and 0.01 standard deviations for WAB and WPR, respectively), with greatest differences in the north for the breeding season and southeast for the wintering season. This work provides the first geospatial models of waterfowl abundance available for China. The indices provide important inputs for modeling disease transmission risk at the interface of poultry and wild birds. These models are easily adaptable, have broad utility to both disease and conservation needs, and will be available to the scientific community for advanced modeling applications.
","language":"English","publisher":"American Association of Avian Pathologists","doi":"10.1637/11125-050615-Reg","usgsCitation":"Prosser, D.J., Hungerford, L.L., Erwin, R.M., Ottinger, M.A., Takekawa, J.Y., Newman, S.H., Xiao, X., and Ellis, E.C., 2016, Spatial modeling of wild bird risk factors to investigate highly pathogenic A(H5N1) avian influenza virus transmission: Avian Diseases, v. 60, no. 1s, p. 329-336, https://doi.org/10.1637/11125-050615-Reg.","productDescription":"8 p.","startPage":"329","endPage":"336","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-071327","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":438608,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9B6ZDUR","text":"USGS data release","linkHelpText":"Spatial Models of Wild Bird Risk Factors for Highly Pathogenic A(H5N1) Avian Influenza Virus Transmission"},{"id":324325,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"60","issue":"1s","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"576cfa1de4b07657d1a33c66","contributors":{"authors":[{"text":"Prosser, Diann J. 0000-0002-5251-1799 dprosser@usgs.gov","orcid":"https://orcid.org/0000-0002-5251-1799","contributorId":2389,"corporation":false,"usgs":true,"family":"Prosser","given":"Diann","email":"dprosser@usgs.gov","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":640624,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hungerford, Laura L.","contributorId":14291,"corporation":false,"usgs":true,"family":"Hungerford","given":"Laura","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":640625,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Erwin, R. Michael 0000-0003-2108-9502","orcid":"https://orcid.org/0000-0003-2108-9502","contributorId":57125,"corporation":false,"usgs":true,"family":"Erwin","given":"R.","email":"","middleInitial":"Michael","affiliations":[],"preferred":false,"id":640626,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ottinger, Mary Ann","contributorId":26422,"corporation":false,"usgs":false,"family":"Ottinger","given":"Mary","email":"","middleInitial":"Ann","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":640627,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Takekawa, John Y. 0000-0003-0217-5907 john_takekawa@usgs.gov","orcid":"https://orcid.org/0000-0003-0217-5907","contributorId":176168,"corporation":false,"usgs":true,"family":"Takekawa","given":"John","email":"john_takekawa@usgs.gov","middleInitial":"Y.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":640628,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Newman, Scott H.","contributorId":101372,"corporation":false,"usgs":true,"family":"Newman","given":"Scott","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":640629,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Xiao, Xianming","contributorId":145908,"corporation":false,"usgs":false,"family":"Xiao","given":"Xianming","email":"","affiliations":[{"id":16292,"text":"Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou, China","active":true,"usgs":false}],"preferred":false,"id":640630,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ellis, Erie C.","contributorId":87678,"corporation":false,"usgs":true,"family":"Ellis","given":"Erie","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":640631,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70174030,"text":"70174030 - 2016 - Temporal variation in survival and recovery rates of lesser scaup","interactions":[],"lastModifiedDate":"2017-11-27T13:02:56","indexId":"70174030","displayToPublicDate":"2016-06-23T13:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Temporal variation in survival and recovery rates of lesser scaup","docAbstract":"Management of lesser scaup (Aythya affinis) has been hindered by access to reliable data on population trajectories and vital rates. We conducted a Bayesian analysis of historical (1951–2011) band-recovery data throughout North America to estimate annual survival and recovery rates for juvenile and adult male and female lesser scaup to determine if increasing harvest or declining survival rates have contributed to population changes and to determine if harvest has been primarily additive or compensatory. Annual recovery rates were low, ranging from 1% to 4% for adults and 2% to 10% for juveniles during most years, with trend models indicating that recovery rates have declined through time for all age–sex classes. Annual survival (mid-Aug to mid-Aug) averaged 0.402 (σ ̂ 0.043) for juvenile males, 0.416 (σ ̂ 0.067) for juvenile females, 0.689 (σ ̂ 0.109) for adult males, and 0.602 (σ ̂ 0.115) for adult females, where σ ̂ represents an estimate of annual process variation in each survival rate. Annual survival rates exhibited no evidence of long-term declines or negative correlations with annual recovery rates (i.e., an index of harvest intensity) for any age–sex class, suggesting that declining fecundity was the most likely explanation for population declines during 1975–2005. We conclude that hunting mortality played a minor role in affecting population dynamics of lesser scaup and waterfowl managers could take a less cautious approach in managing harvest, especially if recruiting or maintaining waterfowl hunters are viewed as important management objectives.
","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.21074","usgsCitation":"Arnold, T.W., Afton, A.D., Anteau, M.J., Koons, D.N., and Nicolai, C., 2016, Temporal variation in survival and recovery rates of lesser scaup: Journal of Wildlife Management, v. 80, no. 5, p. 850-861, https://doi.org/10.1002/jwmg.21074.","productDescription":"12 p.","startPage":"850","endPage":"861","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-071708","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":324293,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"80","issue":"5","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2016-04-13","publicationStatus":"PW","scienceBaseUri":"576cfa1de4b07657d1a33c68","contributors":{"authors":[{"text":"Arnold, Todd W.","contributorId":36058,"corporation":false,"usgs":false,"family":"Arnold","given":"Todd","email":"","middleInitial":"W.","affiliations":[{"id":12644,"text":"University of Minnesota, St. Paul","active":true,"usgs":false}],"preferred":false,"id":640563,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Afton, Alan D. 0000-0002-0436-8588 aafton@usgs.gov","orcid":"https://orcid.org/0000-0002-0436-8588","contributorId":139582,"corporation":false,"usgs":false,"family":"Afton","given":"Alan","email":"aafton@usgs.gov","middleInitial":"D.","affiliations":[{"id":368,"text":"Louisiana Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true}],"preferred":false,"id":640564,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":640562,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Koons, David N.","contributorId":28137,"corporation":false,"usgs":false,"family":"Koons","given":"David","email":"","middleInitial":"N.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":640565,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nicolai, Chris","contributorId":169592,"corporation":false,"usgs":true,"family":"Nicolai","given":"Chris","affiliations":[],"preferred":false,"id":640566,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70174020,"text":"70174020 - 2016 - Waterbird nest-site selection is influenced by neighboring nests and island topography","interactions":[],"lastModifiedDate":"2017-12-13T17:45:48","indexId":"70174020","displayToPublicDate":"2016-06-23T11:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Waterbird nest-site selection is influenced by neighboring nests and island topography","docAbstract":"Avian nest-site selection is influenced by factors operating across multiple spatial scales. Identifying preferred physical characteristics (e.g., topography, vegetation structure) can inform managers to improve nesting habitat suitability. However, social factors (e.g., attraction, territoriality, competition) can complicate understanding physical characteristics preferred by nesting birds. We simultaneously evaluated the physical characteristics and social factors influencing selection of island nest sites by colonial-nesting American avocets (Recurvirostra americana) and Forster's terns (Sterna forsteri) at 2 spatial scales in San Francisco Bay, 2011–2012. At the larger island plot (1 m2) scale, we used real-time kinematics to produce detailed topographies of nesting islands and map the distribution of nests. Nesting probability was greatest in island plots between 0.5 m and 1.5 m above the water surface, at distances <10 m from the water's edge, and of moderately steep (avocets) or flat (terns) slopes. Further, avocet and tern nesting probability increased as the number of nests initiated in adjacent plots increased up to a peak of 11–12 tern nests, and then decreased thereafter. Yet, avocets were less likely to nest in plots adjacent to plots with nesting avocets, suggesting an influence of intra-specific territoriality. At the smaller microhabitat scale, or the area immediately surrounding the nest, we compared topography, vegetation, and distance to nearest nest between nest sites and paired random sites. Topography had little influence on selection of the nest microhabitat. Instead, nest sites were more likely to have vegetation present, and greater cover, than random sites. Finally, avocet, and to a lesser extent tern, nest sites were closer to other active conspecific or heterospecific nests than random sites, indicating that social attraction played a role in selection of nest microhabitat. Our results demonstrate key differences in nest-site selection between co-occurring avocets and terns, and indicate the effects of physical characteristics and social factors on selection of nesting habitat are dependent on the spatial scale examined. Moreover, these results indicate that islands with abundant area between 0.5 m and 1.5 m above the water surface, within 10 m of the water's edge, and containing a mosaic of slopes ranging from flat to moderately steep would provide preferred nesting habitat for avocets and terns. © 2016 The Wildlife Society.
","language":"English","publisher":"Wiley","doi":"10.1002/jwmg.21105","usgsCitation":"Hartman, C.A., Ackerman, J., Takekawa, J.Y., and Herzog, M.P., 2016, Waterbird nest-site selection is influenced by neighboring nests and island topography: Journal of Wildlife Management, v. 80, no. 7, p. 1267-1279, https://doi.org/10.1002/jwmg.21105.","productDescription":"13 p.","startPage":"1267","endPage":"1279","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-062454","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":324283,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"San Francisco","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.11235046386717,\n 37.56362983491151\n ],\n [\n -122.06153869628906,\n 37.57070524233116\n ],\n [\n -122.01828002929686,\n 37.50155517264162\n ],\n [\n -121.95991516113283,\n 37.51027052249435\n ],\n [\n -121.91734313964844,\n 37.45687303762862\n ],\n [\n -121.99493408203125,\n 37.41816326969145\n ],\n [\n -122.10617065429688,\n 37.43179575348695\n ],\n [\n -122.11235046386717,\n 37.56362983491151\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"80","issue":"7","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2016-06-10","publicationStatus":"PW","scienceBaseUri":"576cfa1ee4b07657d1a33c6c","contributors":{"authors":[{"text":"Hartman, C. Alex 0000-0002-7222-1633 chartman@usgs.gov","orcid":"https://orcid.org/0000-0002-7222-1633","contributorId":131157,"corporation":false,"usgs":true,"family":"Hartman","given":"C.","email":"chartman@usgs.gov","middleInitial":"Alex","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":640520,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ackerman, Joshua T. 0000-0002-3074-8322 jackerman@usgs.gov","orcid":"https://orcid.org/0000-0002-3074-8322","contributorId":147078,"corporation":false,"usgs":true,"family":"Ackerman","given":"Joshua T.","email":"jackerman@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":640519,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Takekawa, John Y. 0000-0003-0217-5907 john_takekawa@usgs.gov","orcid":"https://orcid.org/0000-0003-0217-5907","contributorId":176168,"corporation":false,"usgs":true,"family":"Takekawa","given":"John","email":"john_takekawa@usgs.gov","middleInitial":"Y.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":640522,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Herzog, Mark P. 0000-0002-5203-2835 mherzog@usgs.gov","orcid":"https://orcid.org/0000-0002-5203-2835","contributorId":131158,"corporation":false,"usgs":true,"family":"Herzog","given":"Mark","email":"mherzog@usgs.gov","middleInitial":"P.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":640521,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70170870,"text":"sir20165039 - 2016 - Occurrence and concentrations of selected trace elements and halogenated organic compounds in stream sediments and potential sources of polychlorinated biphenyls, Leon Creek, San Antonio, Texas, 2012–14","interactions":[],"lastModifiedDate":"2016-06-24T08:42:42","indexId":"sir20165039","displayToPublicDate":"2016-06-23T00:00:00","publicationYear":"2016","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":"2016-5039","title":"Occurrence and concentrations of selected trace elements and halogenated organic compounds in stream sediments and potential sources of polychlorinated biphenyls, Leon Creek, San Antonio, Texas, 2012–14","docAbstract":"The Texas Department of State Health Services issued fish consumption advisories in 2003 and 2010 for Leon Creek in San Antonio, Texas, based on elevated concentrations of polychlorinated biphenyls (PCBs) in fish tissues. The U.S. Geological Survey (USGS) measured elevated PCB concentrations in stream-sediment samples collected during 2007–9 from Leon Creek at Lackland Air Force Base (now known as Joint Base San Antonio-Lackland; the sampling site at this base is hereinafter referred to as the “Joint Base site”) and sites on Leon Creek downstream from the base. This report describes the occurrence and concentrations of selected trace elements and halogenated organic compounds (pesticides, flame retardants, and PCBs) and potential sources of PCBs in stream-sediment samples collected from four sites on Leon Creek during 2012–14. In downstream order, sediment samples were collected from Leon Creek at northwest Interstate Highway 410 (Loop 410), Rodriguez Park, Morey Road, and Joint Base. The USGS periodically collected streambed-sediment samples during low flow and suspended-sediment samples during high flow.
\nTrace element concentrations were low compared to the consensus-based sediment-quality guidelines (SQGs) for the threshold effect concentration (TEC) and probable effect concentration (PEC). Adverse effects to benthic biota are not expected at concentrations less than the TEC and are expected at concentrations greater than the PEC. No trace element concentrations were greater than the PEC in any of the samples. Trace element concentrations were greatest at the Morey Road and Joint Base sites and exceeded the TECs by 41 and 27 percent, respectively. Trace element concentrations were lowest at the Rodriguez Park and Loop 410 sites and exceeded the TECs by 18 and 14 percent, respectively.
\nPesticides that have been banned for several decades are commonly detected in Leon Creek stream sediments, particularly the chlordane compounds. Chlordane compounds were detected in 84 percent of the samples and at every sample collection site. The samples collected from the Rodriguez Park site had the most pesticide compounds detected. Only samples collected from the Joint Base site had dichlorodiphenyldichloroethane (DDD), dichlorodiphenyldichloroethylene (DDE), or dichlorodiphenyltrichloroethane (DDT) concentrations greater than the TEC, and a few were also greater than the PEC.
\nFlame retardants were found at every site on Leon Creek where stream sediments were collected; however, a few compounds were frequently detected in the laboratory reagent blanks so their detections in the environmental samples may not be from local sources. Consensus-based SQGs were not available for flame retardants so samples were compared to Environment Canada Federal Environmental Quality Guidelines (FEQGs). The concentrations of flame retardants generally were greater in the suspended-sediment samples than the streambed-sediment samples and greater than the FEQGs in many cases.
\nEighteen PCB congeners were quantified in the sediment samples collected from Leon Creek. The samples collected from the Joint Base site had the most frequent PCB congener detections. Total PCB concentrations, computed as the sum of the 18 congeners by using the Kaplan-Meier method for left-censored environmental data, were much smaller than the TEC of 59.8 micrograms per kilogram (μg/kg). When detected, the concentrations of total PCBs in the stream-sediment samples collected from Leon Creek during 2012–14 ranged from an estimated 0.2 to 8.7 μg/kg.
\nSediment samples collected from Leon Creek by the USGS during 2007–9 and 2012–14 at a total of eight sites following identical field and laboratory methods were evaluated to determine if potential PCB sources could be identified. Total PCB concentrations in the sediment samples collected upstream from the Joint Base site were low or nondetections; while concentrations in the samples collected on and downstream from the Joint Base site were greater. Congeners 180 and 138 constituted the greatest proportion of the PCB mixture in samples collected upstream from, on, and downstream from the Joint Base site. Upstream from the Joint Base site, congeners 180 and 138 constituted 50 percent and 35 percent respectively of the PCBs congeners found in the samples. On and downstream from the Joint Base site, congeners 180 and 138 constituted 80 percent and 13 percent respectively of the PCBs congeners found in the samples. Chi-square (C2) tests also indicate that samples collected from the Loop 410 site were statistically different from samples collected from the Joint Base site and sites downstream. The PCB congener pattern in the Leon Creek samples is most like the congener mixture in Aroclor 1260, which is chemically similar to the PCBs detected in the fish samples that resulted in the 2003 fish consumption advisory.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165039","collaboration":"Prepared in cooperation with the San Antonio River Authority","usgsCitation":"Wilson, J.T., 2016, Occurrence and concentrations of selected trace elements and halogenated organic compounds in stream sediments and potential sources of polychlorinated biphenyls, Leon Creek, San Antonio, Texas, 2012–14: U.S. Geological Survey Scientific Investigations Report 2016–5039, 99 p., https://dx.doi.org/10.3133/sir20165039.","productDescription":"viii, 99 p.","startPage":"1","endPage":"99","numberOfPages":"111","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069499","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":324297,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5039/sir20165039.pdf","text":"Report","size":"1.90 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016–5039"},{"id":324296,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5039/coverthb.jpg"}],"country":"United States","state":"Texas","city":"San Antonio","otherGeospatial":"Leon Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -98.60401153564452,\n 29.2324852813013\n ],\n [\n -98.60401153564452,\n 29.354349397730857\n ],\n [\n -98.5089111328125,\n 29.354349397730857\n ],\n [\n -98.5089111328125,\n 29.2324852813013\n ],\n [\n -98.60401153564452,\n 29.2324852813013\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, TX 78754-4501
Despite being the driest inhabited continent, Australia has one of the highest per capita water consumptions in the world. In addition, instead of having fit-for-purpose water supplies (using different qualities of water for different applications), highly treated drinking water is used for nearly all of Australia’s urban water supply needs, including landscape irrigation. The water requirement of urban landscapes, and particularly urban parklands, is of growing concern. The estimation of ET and subsequently plant water requirements in urban vegetation needs to consider the heterogeneity of plants, soils, water and climate characteristics. Accurate estimation of evapotranspiration (ET), which is the main component of a plant’s water requirement, in urban parks is highly desirable because this water maintains the health of green infrastructure and this in turn provides essential ecosystem services. This research contributes to a broader effort to establish sustainable irrigation practices within the Adelaide Parklands in Adelaide, South Australia.
","language":"English","publisher":"MDPI AG","doi":"10.3390/rs8060492","usgsCitation":"Nouri, H., Glenn, E.P., Beecham, S., Chavoshi Boroujeni, S., Sutton, P., Alaghmand, S., Nagler, P.L., and Noori, B., 2016, Comparing three approaches of evapotranspiration estimation in mixed urban vegetation; field-based, remote sensing-based and observational-based methods: Remote Sensing, v. 8, no. 6, Article 492; 15 p., https://doi.org/10.3390/rs8060492.","productDescription":"Article 492; 15 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-072315","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":470854,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs8060492","text":"Publisher Index Page"},{"id":324278,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"6","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-06-10","publicationStatus":"PW","scienceBaseUri":"576ba89de4b07657d1a1765e","contributors":{"authors":[{"text":"Nouri, Hamideh 0000-0002-7424-5030","orcid":"https://orcid.org/0000-0002-7424-5030","contributorId":16327,"corporation":false,"usgs":true,"family":"Nouri","given":"Hamideh","email":"","affiliations":[],"preferred":false,"id":640499,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Glenn, Edward P.","contributorId":19289,"corporation":false,"usgs":true,"family":"Glenn","given":"Edward","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":640500,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Beecham, Simon","contributorId":95397,"corporation":false,"usgs":true,"family":"Beecham","given":"Simon","affiliations":[],"preferred":false,"id":640501,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chavoshi Boroujeni, Sattar","contributorId":172386,"corporation":false,"usgs":false,"family":"Chavoshi Boroujeni","given":"Sattar","email":"","affiliations":[{"id":27030,"text":"School of Natural and Built Environments, University of South Australia, Adelaide, SA","active":true,"usgs":false}],"preferred":false,"id":640502,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sutton, Paul","contributorId":172387,"corporation":false,"usgs":false,"family":"Sutton","given":"Paul","email":"","affiliations":[{"id":27030,"text":"School of Natural and Built Environments, University of South Australia, Adelaide, SA","active":true,"usgs":false}],"preferred":false,"id":640503,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Alaghmand, Sina","contributorId":172388,"corporation":false,"usgs":false,"family":"Alaghmand","given":"Sina","email":"","affiliations":[{"id":27031,"text":"School of Natural and Built Environments, U. So. Aus and Discipline of Civil Engineering, School Of Engineering, Monash University Malaysia","active":true,"usgs":false}],"preferred":false,"id":640504,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Nagler, Pamela L. 0000-0003-0674-103X pnagler@usgs.gov","orcid":"https://orcid.org/0000-0003-0674-103X","contributorId":1398,"corporation":false,"usgs":true,"family":"Nagler","given":"Pamela","email":"pnagler@usgs.gov","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":640498,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Noori, Behnaz","contributorId":172392,"corporation":false,"usgs":false,"family":"Noori","given":"Behnaz","email":"","affiliations":[],"preferred":false,"id":640518,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70174013,"text":"70174013 - 2016 - Regional effects of agricultural conservation practices on nutrient transport in the Upper Mississippi River Basin","interactions":[],"lastModifiedDate":"2018-03-15T10:26:40","indexId":"70174013","displayToPublicDate":"2016-06-22T16:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Regional effects of agricultural conservation practices on nutrient transport in the Upper Mississippi River Basin","docAbstract":"Despite progress in the implementation of conservation practices, related improvements in water quality have been challenging to measure in larger river systems. In this paper we quantify these downstream effects by applying the empirical U.S. Geological Survey water-quality model SPARROW to investigate whether spatial differences in conservation intensity were statistically correlated with variations in nutrient loads. In contrast to other forms of water quality data analysis, the application of SPARROW controls for confounding factors such as hydrologic variability, multiple sources and environmental processes. A measure of conservation intensity was derived from the USDA-CEAP regional assessment of the Upper Mississippi River and used as an explanatory variable in a model of the Upper Midwest. The spatial pattern of conservation intensity was negatively correlated (p = 0.003) with the total nitrogen loads in streams in the basin. Total phosphorus loads were weakly negatively correlated with conservation (p = 0.25). Regional nitrogen reductions were estimated to range from 5 to 34% and phosphorus reductions from 1 to 10% in major river basins of the Upper Mississippi region. The statistical associations between conservation and nutrient loads are consistent with hydrological and biogeochemical processes such as denitrification. The results provide empirical evidence at the regional scale that conservation practices have had a larger statistically detectable effect on nitrogen than on phosphorus loadings in streams and rivers of the Upper Mississippi Basin.
","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.est.5b03543","usgsCitation":"Garcia, A.M., Alexander, R.B., Arnold, J.G., Norfleet, L., White, M.J., Robertson, D.M., and Schwarz, G., 2016, Regional effects of agricultural conservation practices on nutrient transport in the Upper Mississippi River Basin: Environmental Science & Technology, v. 50, no. 13, p. 6991-7000, https://doi.org/10.1021/acs.est.5b03543.","productDescription":"10 p.","startPage":"6991","endPage":"7000","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-067273","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":470859,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1021/acs.est.5b03543","text":"Publisher Index Page"},{"id":324247,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"50","issue":"13","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2016-06-21","publicationStatus":"PW","scienceBaseUri":"576ba89fe4b07657d1a17688","chorus":{"doi":"10.1021/acs.est.5b03543","url":"http://dx.doi.org/10.1021/acs.est.5b03543","publisher":"American Chemical Society (ACS)","authors":"García Ana María, Alexander Richard B., Arnold Jeffrey G., Norfleet Lee, White Michael J., Robertson Dale M., Schwarz Gregory","journalName":"Environmental Science & Technology","publicationDate":"7/5/2016","auditedOn":"6/23/2016","publiclyAccessibleDate":"6/21/2016"},"contributors":{"authors":[{"text":"Garcia, Ana Maria 0000-0002-5388-1281 agarcia@usgs.gov","orcid":"https://orcid.org/0000-0002-5388-1281","contributorId":2035,"corporation":false,"usgs":true,"family":"Garcia","given":"Ana","email":"agarcia@usgs.gov","middleInitial":"Maria","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":640414,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Alexander, Richard B. 0000-0001-9166-0626 ralex@usgs.gov","orcid":"https://orcid.org/0000-0001-9166-0626","contributorId":541,"corporation":false,"usgs":true,"family":"Alexander","given":"Richard","email":"ralex@usgs.gov","middleInitial":"B.","affiliations":[{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":640415,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Arnold, Jeffrey G.","contributorId":172345,"corporation":false,"usgs":false,"family":"Arnold","given":"Jeffrey","email":"","middleInitial":"G.","affiliations":[{"id":6758,"text":"USDA-ARS","active":true,"usgs":false}],"preferred":false,"id":640417,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Norfleet, Lee","contributorId":172346,"corporation":false,"usgs":false,"family":"Norfleet","given":"Lee","email":"","affiliations":[{"id":24598,"text":"USDA-NRCS retired","active":true,"usgs":false}],"preferred":false,"id":640418,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"White, Michael J.","contributorId":172348,"corporation":false,"usgs":false,"family":"White","given":"Michael","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":640425,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Robertson, Dale M. 0000-0001-6799-0596 dzrobert@usgs.gov","orcid":"https://orcid.org/0000-0001-6799-0596","contributorId":150760,"corporation":false,"usgs":true,"family":"Robertson","given":"Dale","email":"dzrobert@usgs.gov","middleInitial":"M.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":640416,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Schwarz, Gregory E. 0000-0002-9239-4566 gschwarz@usgs.gov","orcid":"https://orcid.org/0000-0002-9239-4566","contributorId":543,"corporation":false,"usgs":true,"family":"Schwarz","given":"Gregory E.","email":"gschwarz@usgs.gov","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":5067,"text":"Northeast Regional Director's Office","active":true,"usgs":true}],"preferred":false,"id":640419,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70173952,"text":"70173952 - 2016 - Variability and trends in runoff efficiency in the conterminous United States","interactions":[],"lastModifiedDate":"2017-08-29T09:38:33","indexId":"70173952","displayToPublicDate":"2016-06-22T14:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"Variability and trends in runoff efficiency in the conterminous United States","docAbstract":"Variability and trends in water-year runoff efficiency (RE) — computed as the ratio of water-year runoff (streamflow per unit area) to water-year precipitation — in the conterminous United States (CONUS) are examined for the 1951 through 2012 period. Changes in RE are analyzed using runoff and precipitation data aggregated to United States Geological Survey 8-digit hydrologic cataloging units (HUs). Results indicate increases in RE for some regions in the north-central CONUS and large decreases in RE for the south-central CONUS. The increases in RE in the north-central CONUS are explained by trends in climate, whereas the large decreases in RE in the south-central CONUS likely are related to groundwater withdrawals from the Ogallala aquifer to support irrigated agriculture.
","language":"English","publisher":"Wiley","doi":"10.1111/1752-1688.12431","usgsCitation":"McCabe, G., and Wolock, D.M., 2016, Variability and trends in runoff efficiency in the conterminous United States: Journal of the American Water Resources Association, v. 52, no. 5, p. 1046-1055, https://doi.org/10.1111/1752-1688.12431.","productDescription":"10 p.","startPage":"1046","endPage":"1055","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-076068","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":324221,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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sparrow","interactions":[],"lastModifiedDate":"2016-06-23T17:09:46","indexId":"ofr20161107","displayToPublicDate":"2016-06-22T13:00:00","publicationYear":"2016","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":"2016-1107","title":"Evaluating water management scenarios to support habitat management for the Cape Sable seaside sparrow","docAbstract":"The endangered Cape Sable seaside sparrow (Ammodramus maritimus mirabilis) is endemic to south Florida and a key indicator species of marl prairie, a highly diverse freshwater community in the Florida Everglades. Maintenance and creation of suitable habitat is seen as the most important pathway to the persistence of the six existing sparrow subpopulations; however, major uncertainties remain in how to increase suitable habitat within and surrounding these subpopulations, which are vulnerable to environmental stochasticity. Currently, consistently suitable conditions for the Cape Sable seaside sparrow are only present in two of these subpopulations (B and E). The water management scenarios evaluated herein were intended to lower water levels and improve habitat conditions in subpopulation A and D, raise water levels to improve habitat conditions in subpopulations C and F, and minimize impacts to subpopulations B and E. Our objective in this analysis was to compare these scenarios utilizing a set of metrics (short- to long-time scales) that relate habitat suitability to hydrologic conditions. Although hydrologic outputs are similar across scenarios in subpopulation A, scenario R2H reaches the hydroperiod and depth suitability targets more than the other scenarios relative to ECB, while minimizing negative consequences to subpopulation E. However, although R2H hydroperiods are longer than those for ECB during the wet season in subpopulations C and F, depths during the breeding season are predicted to decrease in suitability (less than -50 cm) relative to existing conditions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161107","usgsCitation":"Beerens, J.M., Romañach, S.S., and McKelvy, Mark. 2016, Evaluating water management scenarios to support habitat management for the Cape Sable seaside sparrow: U.S. Geological Survey Open-File Report 2016-1107, 62 p., https://dx.doi.org/10.3133/ofr20161107.","productDescription":"x, 52 p.","numberOfPages":"62","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-076424","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":324233,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1107/ofr20161107.pdf","text":"Report","size":"5.56 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1107"},{"id":324232,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1107/coverthb.jpg"}],"country":"United States","state":"Florida","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.84814453125,\n 25.110471486223346\n ],\n [\n -81.84814453125,\n 26.23430203240673\n ],\n [\n -80.079345703125,\n 26.23430203240673\n ],\n [\n -80.079345703125,\n 25.110471486223346\n ],\n [\n -81.84814453125,\n 25.110471486223346\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Wetland and Aquatic Research Center
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https://www.usgs.gov/centers/wetland-and-aquatic-research-center-warc
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","language":"English","publisher":"Elsevier","doi":"10.1016/j.marpolbul.2016.05.045","usgsCitation":"Reilly, T.J., Focazio, M.J., and Simmons, D.L., 2016, Resetting the bar: Establishing baselines for persistent contaminants after Hurricane Sandy in the coastal environments of New Jersey and New York, USA: Marine Pollution Bulletin, v. 107, no. 2, p. 414-421, https://doi.org/10.1016/j.marpolbul.2016.05.045.","productDescription":"8 p.","startPage":"414","endPage":"421","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070873","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":324212,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Jersey, New York","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.52001953125,\n 38.57393751557591\n ],\n [\n -75.52001953125,\n 41.57436130598913\n ],\n [\n -71.7901611328125,\n 41.57436130598913\n ],\n [\n -71.7901611328125,\n 38.57393751557591\n ],\n [\n -75.52001953125,\n 38.57393751557591\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"107","issue":"2","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"576ba89fe4b07657d1a1768e","contributors":{"authors":[{"text":"Reilly, Timothy J. 0000-0002-2939-3050 tjreilly@usgs.gov","orcid":"https://orcid.org/0000-0002-2939-3050","contributorId":1858,"corporation":false,"usgs":true,"family":"Reilly","given":"Timothy","email":"tjreilly@usgs.gov","middleInitial":"J.","affiliations":[{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true},{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":629957,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Focazio, Michael J. 0000-0003-0967-5576 mfocazio@usgs.gov","orcid":"https://orcid.org/0000-0003-0967-5576","contributorId":1276,"corporation":false,"usgs":true,"family":"Focazio","given":"Michael","email":"mfocazio@usgs.gov","middleInitial":"J.","affiliations":[{"id":38175,"text":"Toxics Substances Hydrology Program","active":true,"usgs":true},{"id":5056,"text":"Office of the AD Energy and Minerals, and Environmental Health","active":true,"usgs":true}],"preferred":true,"id":629958,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Simmons, Dale L. dsimmons@usgs.gov","contributorId":575,"corporation":false,"usgs":true,"family":"Simmons","given":"Dale","email":"dsimmons@usgs.gov","middleInitial":"L.","affiliations":[{"id":5072,"text":"Office of Communication and Publishing","active":true,"usgs":true}],"preferred":true,"id":629959,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70174041,"text":"70174041 - 2016 - Effects of salt pond restoration on benthic flux: Sediment as a source of nutrients to the water column","interactions":[],"lastModifiedDate":"2017-10-30T09:47:42","indexId":"70174041","displayToPublicDate":"2016-06-22T10:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5102,"text":"Journal of Environmental Protection","active":true,"publicationSubtype":{"id":10}},"title":"Effects of salt pond restoration on benthic flux: Sediment as a source of nutrients to the water column","docAbstract":"Understanding nutrient flux between the benthos and the overlying water (benthic flux) is critical to restoration of water quality and biological resources because it can represent a major source of nutrients to the water column. Extensive water management commenced in the San Francisco Bay, Beginning around 1850, San Francisco Bay wetlands were converted to salt ponds and mined extensively for more than a century. Long-term (decadal) salt pond restoration efforts began in 2003. A patented device for sampling porewater at varying depths, to calculate the gradient, was employed between 2010 and 2012. Within the former ponds, the benthic flux of soluble reactive phosphorus and that of dissolved ammonia were consistently positive (i.e., moving out of the sediment into the water column). The lack of measurable nitrate or nitrite concentration gradients across the sediment-water interface suggested negligible fluxes for dissolved nitrate and nitrite. The dominance of ammonia in the porewater indicated anoxic sediment conditions, even at only 1 cm depth, which is consistent with the observed, elevated sediment oxygen demand. Nearby openestuary sediments showed much lower benthic flux values for nutrients than the salt ponds under resortation. Allochthonous solute transport provides a nutrient advective flux for comparison to benthic flux. For ammonia, averaged for all sites and dates, benthic flux was about 80,000 kg/year, well above the advective flux range of −50 to 1500 kg/year, with much of the variability depending on the tidal cycle. By contrast, the average benthic flux of soluble reactive phosphorus was about 12,000 kg/year, of significant magnitude, but less than the advective flux range of 21,500 to 30,000 kg/year. These benthic flux estimates, based on solute diffusion across the sediment-water interface, reveal a significant nutrient source to the water column of the pond which stimulates algal blooms (often autotrophic). This benthic source may be augmented further by bioturbation, bioirrigation and episodic sediment resuspension events.
","language":"English","publisher":"Scientific Research Publishing Inc","doi":"10.4236/jep.2016.77095","usgsCitation":"Topping, B.R., Kuwabara, J.S., Carter, J.L., Garrettt, K.K., Mruz, E., Piotter, S., and Takekawa, J.Y., 2016, Effects of salt pond restoration on benthic flux: Sediment as a source of nutrients to the water column: Journal of Environmental Protection, v. 7, p. 1064-1071, https://doi.org/10.4236/jep.2016.77095.","productDescription":"8 p.","startPage":"1064","endPage":"1071","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063951","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":552,"text":"San Francisco Bay-Delta","active":false,"usgs":true}],"links":[{"id":470861,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.4236/jep.2016.77095","text":"Publisher Index Page"},{"id":324356,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"San Francisco","otherGeospatial":"San Francisco Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.33276367187499,\n 37.20626914065441\n ],\n [\n -122.58270263671876,\n 37.64468458716586\n ],\n [\n -122.83538818359375,\n 38.34596449365382\n ],\n [\n -121.87683105468749,\n 38.34596449365382\n ],\n [\n -121.88507080078125,\n 37.201893907733826\n ],\n [\n -122.33276367187499,\n 37.20626914065441\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"7","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"576e59aee4b07657d1a43c59","contributors":{"authors":[{"text":"Topping, Brent R. 0000-0002-7887-4221 btopping@usgs.gov","orcid":"https://orcid.org/0000-0002-7887-4221","contributorId":1484,"corporation":false,"usgs":true,"family":"Topping","given":"Brent","email":"btopping@usgs.gov","middleInitial":"R.","affiliations":[{"id":438,"text":"National Research Program - 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Downscaled GCMs project a + 2.1 to + 4.0 °C change in average-annual air temperature (+ 2.6 °C average) and a − 5.1% to + 16.7% change in total annual precipitation (+ 5.1% average) for this geographic area by the middle of this century (2045–2065) and larger changes by the end of the century. The climatic changes by mid-century are projected to result in a − 21.2% to + 8.9% change in total annual streamflow (− 1.8% average) and a − 29.6% to + 17.2% change in total annual P loading (− 3.1% average). Although the average projected changes in streamflow and P loading are relatively small for the entire basin, considerable variability exists spatially and among GCMs because of their variability in projected future precipitation.
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dechrist@usgs.gov","orcid":"https://orcid.org/0000-0001-6108-2247","contributorId":366,"corporation":false,"usgs":true,"family":"Christiansen","given":"Daniel","email":"dechrist@usgs.gov","middleInitial":"E.","affiliations":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"preferred":true,"id":631152,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lorenz, David J","contributorId":169822,"corporation":false,"usgs":false,"family":"Lorenz","given":"David","email":"","middleInitial":"J","affiliations":[{"id":7122,"text":"University of Wisconsin","active":true,"usgs":false}],"preferred":false,"id":631153,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70170976,"text":"sir20165061 - 2016 - Bathymetric and velocimetric surveys at highway bridges crossing the Missouri River near Kansas City, Missouri, June 2–4, 2015","interactions":[],"lastModifiedDate":"2016-06-22T09:37:57","indexId":"sir20165061","displayToPublicDate":"2016-06-22T00:00:00","publicationYear":"2016","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":"2016-5061","title":"Bathymetric and velocimetric surveys at highway bridges crossing the Missouri River near Kansas City, Missouri, June 2–4, 2015","docAbstract":"Bathymetric and velocimetric data were collected by the U.S. Geological Survey, in cooperation with the Missouri Department of Transportation, near 8 bridges at 7 highway crossings of the Missouri River in Kansas City, Missouri, from June 2 to 4, 2015. A multibeam echosounder mapping system was used to obtain channel-bed elevations for river reaches ranging from 1,640 to 1,660 feet longitudinally and extending laterally across the active channel from bank to bank during low to moderate flood flow conditions. These bathymetric surveys indicate the channel conditions at the time of the surveys and provide characteristics of scour holes that may be useful in the development of predictive guidelines or equations for scour holes. These data also may be useful to the Missouri Department of Transportation as a low to moderate flood flow comparison to help assess the bridges for stability and integrity issues with respect to bridge scour during floods.
\nBathymetric data were collected around every pier that was in water, except those at the edge of water or surrounded by a debris raft, and scour holes were observed at most surveyed piers. The observed scour holes at the surveyed bridges were examined with respect to shape and depth. Although exposure of parts of substructural support elements was observed at several piers, the exposure likely can be considered minimal compared to the overall substructure that remains buried in bed material at these piers.
\nThe frontal slope values determined for scour holes observed in the current (2015) study generally are similar to recommended values in the literature and values determined for scour holes in previous bathymetric surveys. Several of the structures had piers that were skewed to primary approach flow, and generally the scour hole was deeper and longer on the side of the pier with impinging flow, with some amount of deposition on the leeward side, typical of conditions observed at piers skewed to approach flow; however, at structure A7650 (site 10), the scour hole was deeper and longer on the leeward side of the pier, possibly because of a deflection and contraction of flow caused by a protrusion of the corresponding bank at the bridge.
\nPrevious bathymetric surveys exist for all the sites examined in this study. Comparisons between bathymetric surfaces from the previous surveys (in March 2010 and during the 2011 flood) and those of this study do not indicate any consistent correlation in channel-bed elevations with flow conditions. A simplified assumption of equal to lesser magnitude scour for the lower discharge in the 2015 surveys did not consistently prove to be true, particularly in respect to the depth of observed scour near the piers when compared to results collected during the 2011 flood.
\nA local spatial minimum average channel-bed elevation at structure A7650 (site 10) compared to adjacent sites may indicate this site is at or near a local feature that controls sediment deposition and scour. The average channel-bed elevation values and the distribution of channel-bed elevations imply that sediment unable to deposit near structure A7650 is flushed downstream and deposits at the next downstream site, structure A5817 (site 11).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165061","collaboration":"Prepared in cooperation with the Missouri Department of Transportation","usgsCitation":"Huizinga, R.J., 2016, Bathymetric and velocimetric surveys at highway bridges crossing the Missouri River near Kansas City, Missouri, June 2–4, 2015: U.S. Geological Survey Scientific Investigations Report 2016–5061, 93 p., https://dx.doi.org/10.3133/sir20165061.","productDescription":"ix, 93 p.","startPage":"1","endPage":"93","numberOfPages":"108","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-073946","costCenters":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true}],"links":[{"id":324168,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5061/sir20165061.pdf","text":"Report","size":"27.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016–5061"},{"id":324167,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5061/coverthb.jpg"}],"country":"United States","state":"Missouri","otherGeospatial":"Missouri River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.7,\n 39.2\n ],\n [\n -94.7,\n 39\n ],\n [\n -94.3,\n 39\n ],\n [\n -94.3,\n 39.2\n ],\n [\n -94.7,\n 39.2\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Missouri Water Science Center
U.S. Geological Survey
1400 Independence Road
Rolla, MO 65401
Summary 1. Wildfires are the principal disturbance in the boreal forest, and their size and frequency are increasing as the climate warms. Impacts of fires on boreal wildlife are largely unknown, especially for the tens of millions of waterfowl that breed in the region. This knowledge gap creates significant barriers to the integrative management of fires and waterfowl, leading to fire policies that largely disregard waterfowl. 2. Waterfowl populations across the western boreal forest of North America have been monitored annually since 1955 by the Waterfowl Breeding Population and Habitat Survey (BPOP), widely considered the most extensive wildlife survey in the world. Using these data, we examined impacts of forest fires on abundance of two waterfowl guilds – dabblers and divers. We modelled waterfowl abundance in relation to fire extent (i.e. amount of survey transect burned) and time since fire, examining both immediate and lagged fire impacts. 3. From 1955 to 2014, >1100 fires in the western boreal forest intersected BPOP survey transects, and many transects burned multiple times. Nonetheless, fires had no detectable impact on waterfowl abundance; annual transect counts of dabbler and diver pairs remained stable from the pre- to post-fire period. 4. The absence of fire impacts on waterfowl abundance extended from the years immediately following the fire to those more than a decade afterwards. Likewise, the amount of transect burned did not influence waterfowl abundance, with similar pair counts from the pre- to post-fire period for small (1–20% burned), medium (21–60%) and large (>60%) burns. 5. Policy implications. Waterfowl populations appear largely resilient to forest fires, providing initial evidence that current policies of limited fire suppression, which predominate throughout much of the boreal forest, have not been detrimental to waterfowl populations. Likewise, fire-related management actions, such as prescribed burning or targeted suppression, seem to have limited impacts on waterfowl abundance and productivity. For waterfowl managers, our results suggest that adaptive models of waterfowl harvest, which annually guide hunting quotas, do not need to emphasize fires when integrating climate change effects.
","language":"English","publisher":"British Ecological Society","publisherLocation":"London, United Kingdom","doi":"10.1111/1365-2664.12705","collaboration":"University of Alaska, Fairbanks","usgsCitation":"Lewis, T., Schmutz, J.A., Amundson, C.L., and Lindberg, M., 2016, Waterfowl populations are resilient to immediate and lagged impacts of wildfires in the boreal forest: Journal of Applied Ecology, v. 53, no. 3, 9 p., https://doi.org/10.1111/1365-2664.12705.","productDescription":"9 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-071371","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":470863,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2664.12705","text":"Publisher Index Page"},{"id":438609,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7RR1WBN","text":"USGS data release","linkHelpText":"Waterfowl Counts and Wildfire Burn Data from the Western Boreal Forest of North America, 1955-2014"},{"id":324532,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":324531,"type":{"id":15,"text":"Index Page"},"url":"https://dx.doi.org/10.1111/1365-2664.12705"}],"volume":"53","issue":"3","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-06-21","publicationStatus":"PW","scienceBaseUri":"57739fb9e4b07657d1a90da4","chorus":{"doi":"10.1111/1365-2664.12705","url":"http://dx.doi.org/10.1111/1365-2664.12705","publisher":"Wiley-Blackwell","authors":"Lewis Tyler L., Schmutz Joel A., Amundson Courtney L., Lindberg Mark S.","journalName":"Journal of Applied Ecology","publicationDate":"6/21/2016"},"contributors":{"authors":[{"text":"Lewis, Tyler 0000-0002-4998-3031 tlewis@usgs.gov","orcid":"https://orcid.org/0000-0002-4998-3031","contributorId":169307,"corporation":false,"usgs":true,"family":"Lewis","given":"Tyler","email":"tlewis@usgs.gov","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":641075,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schmutz, Joel A. 0000-0002-6516-0836 jschmutz@usgs.gov","orcid":"https://orcid.org/0000-0002-6516-0836","contributorId":1805,"corporation":false,"usgs":true,"family":"Schmutz","given":"Joel","email":"jschmutz@usgs.gov","middleInitial":"A.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":641076,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Amundson, Courtney L. 0000-0002-0166-7224 camundson@usgs.gov","orcid":"https://orcid.org/0000-0002-0166-7224","contributorId":4833,"corporation":false,"usgs":true,"family":"Amundson","given":"Courtney","email":"camundson@usgs.gov","middleInitial":"L.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":641077,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lindberg, Mark S.","contributorId":89466,"corporation":false,"usgs":false,"family":"Lindberg","given":"Mark S.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":641078,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70173403,"text":"70173403 - 2016 - Surface water connectivity drives richness and composition of Arctic lake fish assemblages","interactions":[],"lastModifiedDate":"2018-06-20T20:06:42","indexId":"70173403","displayToPublicDate":"2016-06-21T17:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1696,"text":"Freshwater Biology","active":true,"publicationSubtype":{"id":10}},"title":"Surface water connectivity drives richness and composition of Arctic lake fish assemblages","docAbstract":"