Attribution of the causes of trends in nutrient loading is often limited to correlation, qualitative reasoning, or references to the work of others. This paper represents efforts to improve causal attribution of water-quality changes. The Red River of the North basin provides a regional test case because of international interest in the reduction of total phosphorus loads and the availability of long-term total phosphorus data and ancillary geospatial data with the potential to explain changes in water quality over time. The objectives of the study are to investigate structural equation modeling methods for application to water-quality problems and to test causal hypotheses related to the drivers of total phosphorus loads over the period 1970 to 2012. Multiple working hypotheses that explain total phosphorus loads and methods for estimating missing ancillary data were developed, and water-quality related challenges to structural equation modeling (including skewed data and scaling issues) were addressed. The model indicates that increased precipitation in season 1 (November–February) or season 2 (March–June) would increase total phosphorus loads in the basin. The effect of agricultural practices on total phosphorus loads was significant, although the effect is about one-third of the effect of season 1 precipitation. The structural equation model representing loads at six sites in the basin shows that climate and agricultural practices explain almost 60% of the annual total phosphorus load in the Red River of the North basin. The modeling process and the unexplained variance highlight the need for better ancillary long-term data for causal assessments.
","language":"English","publisher":"ACSESS","doi":"10.2134/jeq2017.04.0131","usgsCitation":"Ryberg, K.R., 2017, Structural equation model of total phosphorus loads in the Red River of the North Basin, USA and Canada: Journal of Environmental Quality, v. 46, no. 5, p. 1072-1080, https://doi.org/10.2134/jeq2017.04.0131.","productDescription":"9 p.","startPage":"1072","endPage":"1080","ipdsId":"IP-075962","costCenters":[{"id":478,"text":"North Dakota Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":469503,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2134/jeq2017.04.0131","text":"Publisher Index Page"},{"id":346042,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Red River of the North Basin","volume":"46","issue":"5","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59ca15a7e4b017cf314041a4","contributors":{"authors":[{"text":"Ryberg, Karen R. 0000-0002-9834-2046 kryberg@usgs.gov","orcid":"https://orcid.org/0000-0002-9834-2046","contributorId":1172,"corporation":false,"usgs":true,"family":"Ryberg","given":"Karen","email":"kryberg@usgs.gov","middleInitial":"R.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":711096,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70191048,"text":"70191048 - 2017 - Local adaptation in Trinidadian guppies alters stream ecosystem structure at landscape scales despite high environmental variability","interactions":[],"lastModifiedDate":"2017-09-25T12:01:36","indexId":"70191048","displayToPublicDate":"2017-09-25T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1337,"text":"Copeia","active":true,"publicationSubtype":{"id":10}},"title":"Local adaptation in Trinidadian guppies alters stream ecosystem structure at landscape scales despite high environmental variability","docAbstract":"While previous studies have shown that evolutionary divergence alters ecological processes in small-scale experiments, a major challenge is to assess whether such evolutionary effects are important in natural ecosystems at larger spatial scales. At the landscape scale, across eight streams in the Caroni drainage, we found that the presence of locally adapted populations of guppies (Poecilia reticulata) is associated with reduced algal biomass and increased invertebrate biomass, while the opposite trends were true in streams with experimentally introduced populations of non-locally adapted guppies. Exclusion experiments conducted in two separate reaches of a single stream showed that guppies with locally adapted phenotypes significantly reduced algae with no effect on invertebrates, while non-adapted guppies had no effect on algae but significantly reduced invertebrates. These divergent effects of phenotype on stream ecosystems are comparable in strength to the effects of abiotic factors (e.g., light) known to be important drivers of ecosystem condition. They also corroborate the results of previous experiments conducted in artificial streams. Our results demonstrate that local adaptation can produce phenotypes with significantly different effects in natural ecosystems at a landscape scale, within a tropical watershed, despite high variability in abiotic factors: five of the seven physical and chemical parameters measured across the eight study streams varied by more than one order of magnitude. Our findings suggest that ecosystem structure is, in part, an evolutionary product and not simply an ecological pattern.
","language":"English","publisher":"The American Society of Ichthyologists and Herpetologists","doi":"10.1643/CE-16-517","usgsCitation":"Simon, T.N., Bassar, R.D., Binderup, A.J., Flecker, A.S., Freeman, M., Gill, J.F., Marshall, M.C., Thomas, S.A., Travis, J., Reznick, D.N., and Pringle, C.M., 2017, Local adaptation in Trinidadian guppies alters stream ecosystem structure at landscape scales despite high environmental variability: Copeia, v. 105, no. 3, p. 504-513, https://doi.org/10.1643/CE-16-517.","productDescription":"10 p.","startPage":"504","endPage":"513","ipdsId":"IP-084421","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":346050,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Trinidad","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -61.59484863281249,\n 10.510766951875397\n ],\n [\n -60.99472045898437,\n 10.510766951875397\n ],\n [\n -60.99472045898437,\n 10.873767739353797\n ],\n [\n -61.59484863281249,\n 10.873767739353797\n ],\n [\n -61.59484863281249,\n 10.510766951875397\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"105","issue":"3","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2017-09-12","publicationStatus":"PW","scienceBaseUri":"59ca15abe4b017cf314041b7","contributors":{"authors":[{"text":"Simon, Troy N.","contributorId":196661,"corporation":false,"usgs":false,"family":"Simon","given":"Troy","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":711047,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bassar, Ronald D.","contributorId":150154,"corporation":false,"usgs":false,"family":"Bassar","given":"Ronald","email":"","middleInitial":"D.","affiliations":[{"id":6932,"text":"University of Massachusetts, Amherst","active":true,"usgs":false}],"preferred":false,"id":711048,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Binderup, Andrew J.","contributorId":196662,"corporation":false,"usgs":false,"family":"Binderup","given":"Andrew","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":711049,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Flecker, Alex S.","contributorId":196663,"corporation":false,"usgs":false,"family":"Flecker","given":"Alex","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":711050,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Freeman, Mary 0000-0001-7615-6923 mcfreeman@usgs.gov","orcid":"https://orcid.org/0000-0001-7615-6923","contributorId":3528,"corporation":false,"usgs":true,"family":"Freeman","given":"Mary","email":"mcfreeman@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":711046,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gill, James F.","contributorId":196664,"corporation":false,"usgs":false,"family":"Gill","given":"James","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":711051,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Marshall, Michael C.","contributorId":196665,"corporation":false,"usgs":false,"family":"Marshall","given":"Michael","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":711052,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Thomas, Steve A.","contributorId":196666,"corporation":false,"usgs":false,"family":"Thomas","given":"Steve","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":711053,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Travis, Joseph","contributorId":196667,"corporation":false,"usgs":false,"family":"Travis","given":"Joseph","email":"","affiliations":[],"preferred":false,"id":711054,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Reznick, David N.","contributorId":196668,"corporation":false,"usgs":false,"family":"Reznick","given":"David","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":711055,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Pringle, Catherine M.","contributorId":176292,"corporation":false,"usgs":false,"family":"Pringle","given":"Catherine","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":711056,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70190274,"text":"ofr20171110 - 2017 - Low-flow characteristics of streams in South Carolina","interactions":[],"lastModifiedDate":"2017-09-25T11:16:46","indexId":"ofr20171110","displayToPublicDate":"2017-09-22T15:30:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-1110","title":"Low-flow characteristics of streams in South Carolina","docAbstract":"An ongoing understanding of streamflow characteristics of the rivers and streams in South Carolina is important for the protection and preservation of the State’s water resources. Information concerning the low-flow characteristics of streams is especially important during critical flow periods, such as during the historic droughts that South Carolina has experienced in the past few decades.
Between 2008 and 2016, the U.S. Geological Survey, in cooperation with the South Carolina Department of Health and Environmental Control, updated low-flow statistics at 106 continuous-record streamgages operated by the U.S. Geological Survey for the eight major river basins in South Carolina. The low-flow frequency statistics included the annual minimum 1-, 3-, 7-, 14-, 30-, 60-, and 90-day mean flows with recurrence intervals of 2, 5, 10, 20, 30, and 50 years, depending on the length of record available at the streamflow-gaging station. Computations of daily mean flow durations for the 5-, 10-, 25-, 50-, 75-, 90-, and 95-percent probability of exceedance also were included.
This report summarizes the findings from publications generated during the 2008 to 2016 investigations. Trend analyses for the annual minimum 7-day average flows are provided as well as trend assessments of long-term annual precipitation data. Statewide variability in the annual minimum 7-day average flow is assessed at eight long-term (record lengths from 55 to 78 years) streamgages. If previous low-flow statistics were available, comparisons with the updated annual minimum 7-day average flow, having a 10-year recurrence interval, were made. In addition, methods for estimating low-flow statistics at ungaged locations near a gaged location are described.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171110","collaboration":"Prepared in cooperation with the South Carolina Department of Health and Environmental Control","usgsCitation":"Feaster, T.D., and Guimaraes, W.B., 2017, Low-flow characteristics of streams in South Carolina: U.S. Geological Survey Open-File Report 2017–1110, 161 p., https://doi.org/10.3133/ofr20171110.","productDescription":"vi, 161 p.","numberOfPages":"172","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-084824","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":346012,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1110/ofr20171110.pdf","text":"Report","size":"8.19 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 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U.S. Geological Survey
720 Gracern Road
Stephenson Center, Suite 129
Columbia, SC 29210
Prior to the arrival of the Dawn spacecraft at Ceres, the dwarf planet was anticipated to be ice-rich. Searches for morphological features related to ice have been ongoing during Dawn's mission at Ceres. Here we report the identification of pitted terrains associated with fresh Cerean impact craters. The Cerean pitted terrains exhibit strong morphological similarities to pitted materials previously identified on Mars (where ice is implicated in pit development) and Vesta (where the presence of ice is debated). We employ numerical models to investigate the formation of pitted materials on Ceres and discuss the relative importance of water ice and other volatiles in pit development there. We conclude that water ice likely plays an important role in pit development on Ceres. Similar pitted terrains may be common in the asteroid belt and may be of interest to future missions motivated by both astrobiology and in situ resource utilization.
","language":"English","publisher":"AGU Publications","doi":"10.1002/2017GL073970","usgsCitation":"Sizemore, H., Platz, T., Schorghofer, N., Prettyman, T., De Sanctis, M., Crown, D.A., Schmedemann, N., Nessemann, A., Kneissl, T., Marchi, S., Schenk, P.M., Bland, M.T., Schmidt, B., Hughson, K.H., Tosi, F., Zambon, F., Mest, S., Yingst, R., Williams, D., Russell, C., and Raymond, C., 2017, Pitted terrains on (1) Ceres and implications for shallow subsurface volatile distribution: Geophysical Research Letters, v. 44, no. 13, p. 6570-6578, https://doi.org/10.1002/2017GL073970.","productDescription":"9 p.","startPage":"6570","endPage":"6578","ipdsId":"IP-082076","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":469505,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doaj.org/article/9ec60cdecbc24e7faac0fa4f772ddd6c","text":"Publisher Index 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for Solar System Research, Göttingen, Germany","active":true,"usgs":false}],"preferred":false,"id":710938,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schorghofer, Norbert","contributorId":196619,"corporation":false,"usgs":false,"family":"Schorghofer","given":"Norbert","email":"","affiliations":[{"id":24732,"text":"Planetary Science Institute, Tucson","active":true,"usgs":false}],"preferred":false,"id":710939,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Prettyman, Thomas","contributorId":196620,"corporation":false,"usgs":false,"family":"Prettyman","given":"Thomas","affiliations":[{"id":13179,"text":"Planetary Science Institute","active":true,"usgs":false}],"preferred":false,"id":710940,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"De Sanctis, Maria Christina","contributorId":196621,"corporation":false,"usgs":false,"family":"De Sanctis","given":"Maria Christina","affiliations":[{"id":34654,"text":"Istituto di Astrofisica e 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Tucson","active":true,"usgs":false}],"preferred":false,"id":710991,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Williams, D.A.","contributorId":98048,"corporation":false,"usgs":false,"family":"Williams","given":"D.A.","email":"","affiliations":[{"id":7114,"text":"Arizona State Unviersity","active":true,"usgs":false}],"preferred":false,"id":710992,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Russell, C.T.","contributorId":32275,"corporation":false,"usgs":false,"family":"Russell","given":"C.T.","email":"","affiliations":[{"id":33607,"text":"University of California Los Angeles","active":true,"usgs":false}],"preferred":false,"id":710993,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Raymond, C.A.","contributorId":50301,"corporation":false,"usgs":false,"family":"Raymond","given":"C.A.","email":"","affiliations":[{"id":18954,"text":"Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA","active":true,"usgs":false}],"preferred":false,"id":710994,"contributorType":{"id":1,"text":"Authors"},"rank":21}]}} ,{"id":70191024,"text":"70191024 - 2017 - Annual estimates of recharge, quick-flow runoff, and ET for the contiguous U.S. using empirical regression equations","interactions":[],"lastModifiedDate":"2022-04-22T16:00:33.117943","indexId":"70191024","displayToPublicDate":"2017-09-21T00:00:00","publicationYear":"2017","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":"Annual estimates of recharge, quick-flow runoff, and ET for the contiguous U.S. using empirical regression equations","docAbstract":"This study presents new data-driven, annual estimates of the division of precipitation into the recharge, quick-flow runoff, and evapotranspiration (ET) water budget components for 2000-2013 for the contiguous United States (CONUS). The algorithms used to produce these maps ensure water budget consistency over this broad spatial scale, with contributions from precipitation influx attributed to each component at 800 m resolution. The quick-flow runoff estimates for the contribution to the rapidly varying portion of the hydrograph are produced using data from 1,434 gaged watersheds, and depend on precipitation, soil saturated hydraulic conductivity, and surficial geology type. Evapotranspiration estimates are produced from a regression using water balance data from 679 gaged watersheds and depend on land cover, temperature, and precipitation. The quick-flow and ET estimates are combined to calculate recharge as the remainder of precipitation. The ET and recharge estimates are checked against independent field data, and the results show good agreement. Comparisons of recharge estimates with groundwater extraction data show that in 15% of the country, groundwater is being extracted at rates higher than the local recharge. These maps of the internally consistent water budget components of recharge, quick-flow runoff, and ET, being derived from and tested against data, are expected to provide reliable first-order estimates of these quantities across the CONUS, even where field measurements are sparse.
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Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-5086","title":"Multiple-source tracking: Investigating sources of pathogens, nutrients, and sediment in the Upper Little River Basin, Kentucky, water years 2013–14","docAbstract":"The South Fork Little River (SFLR) and the North Fork Little River (NFLR) are two major headwater tributaries that flow into the Little River just south of Hopkinsville, Kentucky. Both tributaries are included in those water bodies in Kentucky and across the Nation that have been reported with declining water quality. Each tributary has been listed by the Kentucky Energy and Environment Cabinet—Kentucky Division of Water in the 303(d) List of Waters for Kentucky Report to Congress as impaired by nutrients, pathogens, and sediment for contact recreation from point and nonpoint sources since 2002. In 2009, the Kentucky Energy and Environment Cabinet—Kentucky Division of Water developed a pathogen total maximum daily load (TMDL) for the Little River Basin including the SFLR and NFLR Basins. Future nutrient and suspended-sediment TMDLs are planned once nutrient criteria and suspended-sediment protocols have been developed for Kentucky. In this study, different approaches were used to identify potential sources of fecal-indicator bacteria (FIB), nitrate, and suspended sediment; to inform the TMDL process; and to aid in the implementation of effective watershed-management activities. The main focus of source identification was in the SFLR Basin.
To begin understanding the potential sources of fecal contamination, samples were collected at 19 sites for densities of FIB (E. coli) in water and fluvial sediment and at 11 sites for Bacteroidales genetic markers (General AllBac, human HF183, ruminant BoBac, canid BacCan, and waterfowl GFD) during the recreational season (May through October) in 2013 and 2014. Results indicated 34 percent of all E. coli water samples (n=227 samples) did not meet the U.S. Environmental Protection Agency 2012 recommended national criteria for primary recreational waters. No criterion currently exists for E. coli in fluvial sediment. By use of the Spearman’s rank correlation test, densities of FIB in fluvial sediments were observed to have a statistically significant positive correlation with drainage area. As drainage area increased, so did the densities of FIB in the fluvial sediments. There was no statistically significant correlation between drainage area and FIB in water. The human-associated marker (HF183) was found above the detection limit in 26 percent of the samples (n=120 samples); a higher proportion of positive samples was in the NFLR Basin. The ruminant-associated marker (BoBac) was above the detection limit in 65 percent of samples; a higher proportion of positive samples was in the headwaters of the SFLR Basin.
Nutrient yields differed between the SFLR and NFLR Basins. Comparatively, the SFLR Basin produced the largest estimated mean yields of total nitrogen (16,000 pounds per year per square mile (lb/yr/mi2) and nitrite plus nitrate nitrogen (12,500 lb/yr/mi2), and the NFLR Basin produced the largest estimated mean yields of ammonia plus organic nitrogen (4,700 lb/yr/mi2), total phosphorus (1,100 lb/yr/mi2), and orthophosphorus (590 lb/yr/mi2).
Nitrate sources in surface water were assessed in both basins using dual-nitrate isotope (nitrogen and oxygen) ratios. Data from the different land uses in the SFLR Basin showed differences in nitrate concentrations and overlapping, but moderately distinct, isotopic signatures. Predominantly forested sites consistently had low nitrate concentrations (median = 0.233 milligrams per liter) with minimal variability, and agricultural sites had the highest nitrate concentrations (median = 7.55 milligrams per liter) with the greatest variability. The median nitrate concentration for sites with mixed land use was 2.66 milligrams per liter. Dual-isotope data for forested sites plotted within ranges characteristic of soil-derived nitrate with possible but minimal influence from recycled atmospheric nitrate. Ranges of dual-isotope data for sites with agricultural and mixed land uses were characteristic of possible mixtures of chemical fertilizer, soil-derived nitrate, and manure and septic wastes. In the NFLR Basin, a positive linear relation was observed between nitrate concentrations and nitrogen isotope ratios (δ15NNO3) (R2=0.56; p-value <0.001) that potentially suggests the NFLR Basin has a higher proportion of δ15NNO3-enriched sources, such as manure and sewage. However, mixing of other nitrate-derived sources cannot be excluded, because many values of δ15NNO3 and concentrations of nitrate showed minimal variation and plotted within dual-nitrate isotope ranges characteristic of fertilizer and soil-derived nitrate sources.
A sediment-fingerprinting approach was used to quantify the relative contribution of four upland sources in the SFLR Basin (agricultural, pasture, riparian/forest, and streambank) to understand how land management affects suspended-sediment concentration. Carbon isotope ratios (δ13C), together with calcium and carbon concentrations, were the best indicators of sediment source; the uncertainty was less than 11 percent. Fine-sediment samples collected at the SFLR Basin outlet indicated streambanks as the largest source of the fine sediment to the stream followed by cropland and riparian/forest-source areas, respectively; pasture was a minor contributing source. Streambanks and cropland were essentially equal contributors of fine sediment at the NFLR Basin outlet.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175086","collaboration":"Prepared in cooperation with the Little River Water-Quality Consortium ","usgsCitation":"Crain, A.S., Cherry, M.A., Williamson, T.N., and Bunch, A.R., 2017, Multiple-source tracking—Investigating sources of pathogens, nutrients, and sediment in the Upper Little River Basin, Kentucky, water years 2013–14: U.S. Geological Survey Scientific Investigations Report 2017–5086, 60 p., https://doi.org/10.3133/sir20175086.","productDescription":"Report: xi, 60 p; Data Release","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-070254","costCenters":[{"id":354,"text":"Kentucky Water Science Center","active":true,"usgs":true}],"links":[{"id":345723,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7ZS2TPW","text":"USGS data release","description":"USGS data release"},{"id":345721,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5086/coverthb.jpg"},{"id":345722,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5086/sir20175086.pdf","text":"Report","size":"6.68 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Kentucky","otherGeospatial":"Upper Little River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.35023498535156,\n 36.96086580957587\n ],\n [\n -87.396240234375,\n 36.96799807635307\n ],\n [\n -87.44361877441406,\n 36.9800665440453\n ],\n [\n -87.46147155761719,\n 36.98390610968992\n ],\n [\n -87.48275756835938,\n 36.97842095659727\n ],\n [\n -87.48619079589842,\n 36.97128966642495\n ],\n [\n -87.48893737792969,\n 36.96306042436515\n ],\n [\n -87.50198364257811,\n 36.953732874654285\n ],\n [\n -87.51983642578125,\n 36.958671131530316\n ],\n [\n -87.5390625,\n 36.96031714599471\n ],\n [\n -87.54798889160156,\n 36.94989178681327\n ],\n [\n -87.53768920898438,\n 36.93507434788673\n ],\n [\n -87.52326965332031,\n 36.91421529335739\n ],\n [\n -87.50404357910156,\n 36.87797284779547\n ],\n [\n -87.53082275390625,\n 36.85874638670163\n ],\n [\n -87.56240844726562,\n 36.81862991458789\n ],\n [\n -87.58163452148438,\n 36.773542488140684\n ],\n [\n -87.68531799316406,\n 36.78839127856239\n ],\n [\n -87.76496887207031,\n 36.835118682834256\n ],\n [\n -87.80479431152344,\n 36.8549005138863\n ],\n [\n -87.7862548828125,\n 36.872480066931246\n ],\n [\n -87.78350830078125,\n 36.88126832670563\n ],\n [\n -87.80136108398438,\n 36.88511287236025\n ],\n [\n -87.84049987792969,\n 36.89005557519409\n ],\n [\n -87.86727905273438,\n 36.88126832670563\n ],\n [\n -87.89199829101561,\n 36.89444882017788\n ],\n [\n -87.91328430175781,\n 36.91256828285194\n ],\n [\n -87.93594360351562,\n 36.92135192790115\n ],\n [\n -87.96272277832031,\n 36.887309668681155\n ],\n [\n -87.97920227050781,\n 36.8614933202301\n ],\n [\n -87.96821594238281,\n 36.84061414925051\n ],\n [\n -87.95173645019531,\n 36.829622821570254\n ],\n [\n -87.87071228027344,\n 36.8021375933119\n ],\n [\n -87.83226013183594,\n 36.793340236044536\n ],\n [\n -87.80616760253905,\n 36.77409249464195\n ],\n [\n -87.79312133789062,\n 36.75153899262323\n ],\n [\n -87.7587890625,\n 36.686041276581925\n ],\n [\n -87.72239685058594,\n 36.679433365517774\n ],\n [\n -87.66952514648438,\n 36.677230602346214\n ],\n [\n -87.61940002441405,\n 36.6843893520368\n ],\n [\n -87.57545471191406,\n 36.70200805115167\n ],\n [\n -87.51846313476562,\n 36.71962271257377\n ],\n [\n -87.47383117675781,\n 36.72457610850295\n ],\n [\n -87.40310668945312,\n 36.73393165140215\n ],\n [\n -87.37564086914062,\n 36.72952918496946\n ],\n [\n -87.37770080566405,\n 36.74988847598359\n ],\n [\n -87.38388061523438,\n 36.76474184748192\n ],\n [\n -87.37632751464844,\n 36.78124222006408\n ],\n [\n -87.35710144042969,\n 36.804886560237236\n ],\n [\n -87.34542846679688,\n 36.8087349481474\n ],\n [\n -87.33100891113281,\n 36.82632511529416\n ],\n [\n -87.3358154296875,\n 36.83127162140714\n ],\n [\n -87.32414245605469,\n 36.84336173438382\n ],\n [\n -87.308349609375,\n 36.85380165753812\n ],\n [\n -87.29736328125,\n 36.86698689106877\n ],\n [\n -87.26715087890625,\n 36.88950640179281\n ],\n [\n -87.2589111328125,\n 36.910372213522535\n ],\n [\n -87.29598999023438,\n 36.9400138143685\n ],\n [\n -87.35023498535156,\n 36.96086580957587\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Indiana-Kentucky Water Science Center
U.S. Geological Survey
9818 Bluegrass Parkway
Louisville, KY 40299
In recent decades, there has been increasing interest in the application of ecological indices to assess ecosystem condition in response to anthropogenic activities. An Index of Waterbird Community Integrity was previously developed for the Chesapeake Bay, USA. However, the scoring criteria were not defined well enough to generate scores for new species that were not observed in the original study. The goal of this study was to explicitly define the scoring criteria for the existing index and to develop index scores for all waterbirds of the Chesapeake Bay. The standardized index then was applied to a case study investigating the relationship between waterbird community integrity and shoreline development during late summer and late fall (2012–2014) using an alternative approach to survey methodology, which allowed for greater area coverage compared to the approach used in the original study. Index scores for both seasons were negatively related to percentage of developed shorelines. Providing these updated tools using the detailed scoring system will facilitate future application to new species or development of the index in other estuaries worldwide. This methodology allows for consistent cross-study comparisons and can be combined with other community integrity indices, allowing for more effective estuarine management.
","language":"English","publisher":"The Waterbird Society","doi":"10.1675/063.040.0305","usgsCitation":"Prosser, D.J., Nagel, J.L., Marban, P., Ze, L., Day, D.D., and Erwin, R., 2017, Standardization and application of an index of community integrity for waterbirds in the Chesapeake Bay, USA: Waterbirds, v. 40, no. 3, p. 233-251, https://doi.org/10.1675/063.040.0305.","productDescription":"19 p.","startPage":"233","endPage":"251","ipdsId":"IP-080789","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":438209,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7H70CZS","text":"USGS data release","linkHelpText":"Standardization and Application of an Index of Community Integrity for Waterbirds in the Chesapeake Bay"},{"id":345916,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Chesapeake Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.3931884765625,\n 36.76529191711624\n ],\n [\n -75.6134033203125,\n 36.76529191711624\n ],\n [\n -75.6134033203125,\n 39.639537564366684\n ],\n [\n -77.3931884765625,\n 39.639537564366684\n ],\n [\n -77.3931884765625,\n 36.76529191711624\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"40","issue":"3","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59c37e38e4b091459a6316ef","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":710847,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nagel, Jessica L. 0000-0002-4437-0324 jnagel@usgs.gov","orcid":"https://orcid.org/0000-0002-4437-0324","contributorId":3976,"corporation":false,"usgs":true,"family":"Nagel","given":"Jessica","email":"jnagel@usgs.gov","middleInitial":"L.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":710848,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Marban, Paul 0000-0002-4910-6565 pmarban@usgs.gov","orcid":"https://orcid.org/0000-0002-4910-6565","contributorId":196581,"corporation":false,"usgs":true,"family":"Marban","given":"Paul","email":"pmarban@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":710849,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ze, Luo","contributorId":196582,"corporation":false,"usgs":false,"family":"Ze","given":"Luo","email":"","affiliations":[],"preferred":false,"id":710850,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Day, Daniel D. 0000-0001-9070-7170 dday@usgs.gov","orcid":"https://orcid.org/0000-0001-9070-7170","contributorId":3985,"corporation":false,"usgs":true,"family":"Day","given":"Daniel","email":"dday@usgs.gov","middleInitial":"D.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":710851,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Erwin, R. Michael 0000-0003-2108-9502","orcid":"https://orcid.org/0000-0003-2108-9502","contributorId":196583,"corporation":false,"usgs":false,"family":"Erwin","given":"R. Michael","affiliations":[],"preferred":false,"id":710852,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70191003,"text":"70191003 - 2017 - What mediates tree mortality during drought in the southern Sierra Nevada?","interactions":[],"lastModifiedDate":"2017-12-12T12:44:47","indexId":"70191003","displayToPublicDate":"2017-09-20T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"What mediates tree mortality during drought in the southern Sierra Nevada?","docAbstract":"Severe drought has the potential to cause selective mortality within a forest, thereby inducing shifts in forest species composition. The southern Sierra Nevada foothills and mountains of California have experienced extensive forest dieback due to drought stress and insect outbreak. We used high-fidelity imaging spectroscopy (HiFIS) and light detection and ranging (LiDAR) from the Carnegie Airborne Observatory (CAO) to estimate the effect of forest dieback on species composition in response to drought stress in Sequoia National Park. Our aims were: (1) to quantify site-specific conditions that mediate tree mortality along an elevation gradient in the southern Sierra Nevada Mountains; (2) to assess where mortality events have a greater probability of occurring; and (3) to estimate which tree species have a greater likelihood of mortality along the elevation gradient. A series of statistical models were generated to classify species composition and identify tree mortality, and the influences of different environmental factors were spatially quantified and analyzed to assess where mortality events have a greater likelihood of occurring. A higher probability of mortality was observed in the lower portion of the elevation gradient, on southwest and west-facing slopes, in areas with shallow soils, on shallower slopes, and at greater distances from water. All of these factors are related to site water balance throughout the landscape. Our results also suggest that mortality is species-specific along the elevation gradient, mainly affecting Pinus ponderosa and Pinus lambertiana at lower elevations. Selective mortality within the forest may drive long-term shifts in community composition along the elevation gradient.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.1620","usgsCitation":"Paz-Kagan, T., Brodrick, P., Vaughn, N.R., Das, A.J., Stephenson, N.L., Nydick, K.R., and Asner, G.P., 2017, What mediates tree mortality during drought in the southern Sierra Nevada?: Ecological Applications, v. 27, no. 8, p. 2443-2457, https://doi.org/10.1002/eap.1620.","productDescription":"15 p.","startPage":"2443","endPage":"2457","ipdsId":"IP-085845","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":345927,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Sierra Nevada","volume":"27","issue":"8","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2017-11-29","publicationStatus":"PW","scienceBaseUri":"59c37e36e4b091459a6316e6","contributors":{"authors":[{"text":"Paz-Kagan, Tarin","contributorId":196597,"corporation":false,"usgs":false,"family":"Paz-Kagan","given":"Tarin","email":"","affiliations":[],"preferred":false,"id":710888,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brodrick, Philip","contributorId":196598,"corporation":false,"usgs":false,"family":"Brodrick","given":"Philip","affiliations":[],"preferred":false,"id":710889,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vaughn, Nicholas R.","contributorId":196599,"corporation":false,"usgs":false,"family":"Vaughn","given":"Nicholas","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":710890,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Das, Adrian J. 0000-0002-3937-2616 adas@usgs.gov","orcid":"https://orcid.org/0000-0002-3937-2616","contributorId":196600,"corporation":false,"usgs":true,"family":"Das","given":"Adrian","email":"adas@usgs.gov","middleInitial":"J.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":710891,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stephenson, Nathan L. 0000-0003-0208-7229 nstephenson@usgs.gov","orcid":"https://orcid.org/0000-0003-0208-7229","contributorId":2836,"corporation":false,"usgs":true,"family":"Stephenson","given":"Nathan","email":"nstephenson@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":710887,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nydick, Koren R.","contributorId":196601,"corporation":false,"usgs":false,"family":"Nydick","given":"Koren","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":710892,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Asner, Gregory P.","contributorId":25393,"corporation":false,"usgs":false,"family":"Asner","given":"Gregory","email":"","middleInitial":"P.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":710893,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70190995,"text":"70190995 - 2017 - Nitrate reduction mechanisms and rates in an unconfined eogenetic karst aquifer in two sites with different redox potential","interactions":[],"lastModifiedDate":"2017-09-20T11:48:44","indexId":"70190995","displayToPublicDate":"2017-09-20T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2320,"text":"Journal of Geophysical Research: Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"Nitrate reduction mechanisms and rates in an unconfined eogenetic karst aquifer in two sites with different redox potential","docAbstract":"This study integrates push-pull tracer tests (PPTT) with microbial characterization of extracted water via quantitative polymerase chain reaction (qPCR) and reverse transcriptase qPCR (RT-qPCR) of selected functional N transformation genes to quantify nitrate reduction mechanisms and rates in sites with different redox potential in a karst aquifer. PPTT treatments with nitrate (AN) and nitrate-fumarate (ANC) were executed in two wells representing anoxic and oxic geochemical end-members. Oxic aquifer zero-order nitrate loss rates (mmol L−1 h−1) were similar for AN and ANC treatment, ranging from 0.03 ± 0.01 to 0.05 ± 0.01. Anoxic aquifer zero-order nitrate loss rates ranged from 0.03 ± 0.02 (AN) to 0.13 ± 0.02 (ANC). Microbial characterization indicates mechanisms influencing these rates were dissimilatory nitrate reduction to ammonium (DNRA) at the anoxic site with AN treatment, assimilatory reduction of nitrate to ammonium (ANRA) with ANC treatment in the water column at both sites, and additional documented nitrate reduction that occurred in unsampled biofilms. With carbon treatment, total numbers of microbes (16S rRNA genes) significantly increased (fourteenfold to thirtyfold), supporting stimulated growth with resulting ANRA. Decreased DNRA gene concentrations (nrfA DNA) and increased DNRA activity ratio (nrfA-cDNA/DNA) supported the assertion that DNRA occurred in the anoxic zone with AN and ANC treatment. Furthermore, decreased DNRA gene copy numbers at the anoxic site with ANC treatment suggests that DNRA microbes in the anoxic site are chemolithoautotrophic. Increased RT-qPCR denitrification gene expression (nirK and nirS) was not observed in water samples, supporting that any observed NO3-N loss due to denitrification may be occurring in unsampled microbial biofilms.
","language":"English","publisher":"Wiley","doi":"10.1002/2016JG003463","usgsCitation":"Henson, W.R., Huang, L., Graham, W.D., and Ogram, A., 2017, Nitrate reduction mechanisms and rates in an unconfined eogenetic karst aquifer in two sites with different redox potential: Journal of Geophysical Research: Biogeosciences, v. 122, no. 5, p. 1062-1077, https://doi.org/10.1002/2016JG003463.","productDescription":"16 p.","startPage":"1062","endPage":"1077","ipdsId":"IP-073069","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":469513,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2016jg003463","text":"Publisher Index Page"},{"id":345921,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","volume":"122","issue":"5","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2017-05-06","publicationStatus":"PW","scienceBaseUri":"59c37e38e4b091459a6316ec","contributors":{"authors":[{"text":"Henson, Wesley R. 0000-0003-4962-5565 whenson@usgs.gov","orcid":"https://orcid.org/0000-0003-4962-5565","contributorId":384,"corporation":false,"usgs":true,"family":"Henson","given":"Wesley","email":"whenson@usgs.gov","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":710858,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Huang, Laibin","contributorId":196586,"corporation":false,"usgs":false,"family":"Huang","given":"Laibin","email":"","affiliations":[{"id":12558,"text":"University of Florida, Gainesville","active":true,"usgs":false}],"preferred":false,"id":710859,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Graham, Wendy D.","contributorId":196587,"corporation":false,"usgs":false,"family":"Graham","given":"Wendy","email":"","middleInitial":"D.","affiliations":[{"id":12558,"text":"University of Florida, Gainesville","active":true,"usgs":false}],"preferred":false,"id":710860,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ogram, Andrew","contributorId":173041,"corporation":false,"usgs":false,"family":"Ogram","given":"Andrew","email":"","affiliations":[{"id":12558,"text":"University of Florida, Gainesville","active":true,"usgs":false}],"preferred":false,"id":710861,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70190179,"text":"sir20175090 - 2017 - Water-level trends and potentiometric surfaces in the Nacatoch Aquifer in northeastern and southwestern Arkansas and in the Tokio Aquifer in southwestern Arkansas, 2014–15","interactions":[],"lastModifiedDate":"2017-09-20T10:33:20","indexId":"sir20175090","displayToPublicDate":"2017-09-20T00:00:00","publicationYear":"2017","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":"2017-5090","title":"Water-level trends and potentiometric surfaces in the Nacatoch Aquifer in northeastern and southwestern Arkansas and in the Tokio Aquifer in southwestern Arkansas, 2014–15","docAbstract":"The Nacatoch Sand in northeastern and southwestern Arkansas and the Tokio Formation in southwestern Arkansas are sources of groundwater for agricultural, domestic, industrial, and public use. Water-level altitudes measured in 51 wells completed in the Nacatoch Sand and 42 wells completed in the Tokio Formation during 2014 and 2015 were used to create potentiometric-surface maps of the two areas. Aquifers in the Nacatoch Sand and Tokio Formation are hereafter referred to as the Nacatoch aquifer and the Tokio aquifer, respectively.
Potentiometric surfaces show that groundwater in the Nacatoch aquifer flows southeast toward the Mississippi River in northeastern Arkansas. Groundwater flow direction is towards the south and southeast in Hempstead, Little River, and Nevada Counties in southwestern Arkansas. An apparent cone of depression exists in southern Clark County and likely alters groundwater flow from a regional direction toward the depression.
In southwestern Arkansas, potentiometric surfaces indicate that groundwater flow in the Tokio aquifer is towards the city of Hope. Northwest of Hope, an apparent cone of depression exists. In southwestern Pike, northwestern Nevada, and northeastern Hempstead Counties, an area of artesian flow (water levels are at or above land surface) exists.
Water-level changes in wells were identified using two methods: (1) linear regression analysis of hydrographs from select wells with a minimum of 20 years of water-level data, and (2) a direct comparison between water-level measurements from 2008 and 2014–15 at each well. Of the six hydrographs analyzed in the Nacatoch aquifer, four indicated a decline in water levels. Compared to 2008 measurements, the largest rise in water levels was 35.14 feet (ft) in a well in Clark County, whereas the largest decline was 14.76 ft in a well in Nevada County, both located in southwestern Arkansas.
Of the four hydrographs analyzed in the Tokio aquifer, one indicated a decline in water levels, while the others remained relatively unchanged. Compared to 2008 measurements, the largest rise in water levels was 21.34 ft in Hempstead County, and the largest water-level decline was 39.37 ft in Clark County. Although changes in water levels since 2008 are spatially varied; long-term trends indicate an overall decline in water levels in both aquifers.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175090","collaboration":"Prepared in cooperation with the Arkansas Natural Resources Commission and the Arkansas Geological Survey","usgsCitation":"Rodgers, K.D., 2017, Water-level trends and potentiometric surfaces in the Nacatoch aquifer in northeastern and southwestern Arkansas and in the Tokio aquifer in southwestern Arkansas, 2014–15: U.S. Geological Survey Scientific Investigations Report 2017–5090, 30 p., https://doi.org/10.3133/sir20175090.","productDescription":"Report: iv, 30 p.; Data Release","numberOfPages":"38","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-069974","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":345860,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5090/sir20175090.pdf","text":"Report","size":"2.54 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\"}}]}","contact":"Director, Lower Mississippi-Gulf Water Science Center
U.S. Geological Survey
401 Hardin Road
Little Rock, AR 72211
Study region
The state of Ohio in the United States, a humid, continental climate.
Study focus
The estimation of nonexceedance probabilities of daily streamflows as an alternative means of establishing the relative magnitudes of streamflows associated with hydrologic and water-quality observations.
New hydrological insights for the region
Several methods for estimating nonexceedance probabilities of daily mean streamflows are explored, including single-index methodologies (nearest-neighboring index) and geospatial tools (kriging and topological kriging). These methods were evaluated by conducting leave-one-out cross-validations based on analyses of nearly 7 years of daily streamflow data from 79 unregulated streamgages in Ohio and neighboring states. The pooled, ordinary kriging model, with a median Nash–Sutcliffe performance of 0.87, was superior to the single-site index methods, though there was some bias in the tails of the probability distribution. Incorporating network structure through topological kriging did not improve performance. The pooled, ordinary kriging model was applied to 118 locations without systematic streamgaging across Ohio where instantaneous streamflow measurements had been made concurrent with water-quality sampling on at least 3 separate days. Spearman rank correlations between estimated nonexceedance probabilities and measured streamflows were high, with a median value of 0.76. In consideration of application, the degree of regulation in a set of sample sites helped to specify the streamgages required to implement kriging approaches successfully.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ejrh.2017.08.006","usgsCitation":"Farmer, W.H., and Koltun, G.F., 2017, Geospatial tools effectively estimate nonexceedance probabilities of daily streamflow at ungauged and intermittently gauged locations in Ohio: Journal of Hydrology: Regional Studies, v. 13, p. 208-221, https://doi.org/10.1016/j.ejrh.2017.08.006.","productDescription":"14 p.","startPage":"208","endPage":"221","ipdsId":"IP-081013","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":461399,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ejrh.2017.08.006","text":"Publisher Index Page"},{"id":438211,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7TM788T","text":"USGS data release","linkHelpText":"Geospatial Tools Effectively Estimate Nonexceedance Probabilities of Daily Streamflow at Ungaged and 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\"}}]}","volume":"13","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59c22cb3e4b091459a61b730","contributors":{"authors":[{"text":"Farmer, William H. 0000-0002-2865-2196 wfarmer@usgs.gov","orcid":"https://orcid.org/0000-0002-2865-2196","contributorId":4374,"corporation":false,"usgs":true,"family":"Farmer","given":"William","email":"wfarmer@usgs.gov","middleInitial":"H.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":true,"id":710766,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Koltun, G. F. 0000-0003-0255-2960 gfkoltun@usgs.gov","orcid":"https://orcid.org/0000-0003-0255-2960","contributorId":140048,"corporation":false,"usgs":true,"family":"Koltun","given":"G.","email":"gfkoltun@usgs.gov","middleInitial":"F.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":710767,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70190788,"text":"ofr20171116 - 2017 - Morphologic evolution of the wilderness area breach at Fire Island, New York—2012–15","interactions":[],"lastModifiedDate":"2024-12-27T15:18:20.876985","indexId":"ofr20171116","displayToPublicDate":"2017-09-18T11:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-1116","title":"Morphologic evolution of the wilderness area breach at Fire Island, New York—2012–15","docAbstract":"Hurricane Sandy, which made landfall on October 29, 2012, near Atlantic City, New Jersey, had a significant impact on the coastal system along the south shore of Long Island, New York. A record significant wave height of 9.6 meters (m) was measured at wave buoy 44025, approximately 48 kilometers offshore of Fire Island, New York. Surge and runup during the storm resulted in extensive beach and dune erosion and breaching of the Fire Island barrier island system at two locations, including a breach that formed within the Otis Pike Fire Island High Dune Wilderness area on the eastern side of Fire Island.
The U.S. Geological Survey (USGS) has a long history of conducting morphologic change and processes research at Fire Island. One of the primary objectives of the current research effort is to understand the morphologic evolution of the barrier system on a variety of time scales (from storm scale to decade(s) to century). A number of studies that support the project objectives have been published. Prior to Hurricane Sandy, however, little information was available on specific storm-driven change in this region. The USGS received Hurricane Sandy supplemental funding (project GS2–2B: Linking Coastal Processes and Vulnerability, Fire Island, New York, Regional Study) to enhance existing research efforts at Fire Island. The existing research was greatly expanded to include inner continental shelf mapping and investigations of processes of inner shelf sediment transport; beach and dune response and recovery; and observation, analysis, and modeling of the newly formed breach in the Otis Pike High Dune Wilderness area, herein referred to as the wilderness breach. The breach formed at the site of Old Inlet, which was open from 1763 to 1825. The location of the initial island breaching does not directly correspond with topographic lows of the dunes, but instead the breach formed in the location of a cross-island boardwalk that was destroyed during Hurricane Sandy.
From 2013 to November 2015, bathymetric data were collected by the USGS St. Petersburg Coastal and Marine Science Center during three surveys of the breach channel and tidal shoals, and shoreline positions on each side of the breach (also collected by the National Park Service). Additionally, pre-storm topography/bathymetry EAARL–B light detection and ranging (lidar) data were collected by the USGS the day prior to Hurricane Sandy’s landfall. These data serve as a baseline for change analyses during four subsequent periods: June 2013, June 2014, October 2014, and May 2015. The June 2013 single-beam bathymetry data were collected in collaboration with the U.S. Army Corps of Engineers (USACE), using the Lighter Amphibious Resupply Cargo (LARC) vessel, and included the ebb shoal and breach channel. The USGS collected and processed the three additional bathymetric datasets using personal watercraft equipped with single-beam echo sounders and backpack Global Positioning System (GPS) over shallow flood shoals.
Eastern and western breach shorelines were surveyed weekly to monthly beginning on November 6, 2012 (by the National Park Service [NPS], and USGS St. Petersburg Coastal and Marine Science Center), with measurements made every few weeks for the first year and every few months after October 2013. The NPS and researchers from Stony Brook University monitored the breach by collecting field data of the breach channel bathymetry, conducting aerial photographic overflights, and performing water-quality analyses (see http://po.msrc.sunysb.edu/GSB/). The aerial photography collected and rectified by Stony Brook University is used extensively in our morphologic change description to examine changes to breach shorelines (supplementing shoreline data collected in the field), channel width, and orientation. Due to the uncertainties and the variation in survey methods, a rigorous quantitative analysis was not performed. However, average calculations of various breach metrics allow a qualitative analysis of breach development and evolution.
This report presents an overview of the data collected and a summary discussion of the observed changes to the breach system and the seasonal wave climatology associated with the breach morphodynamic response.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171116","usgsCitation":"Hapke, C.J., Nelson, T.R., Henderson, R.E., Brenner, O.T., and Miselis, J.L., 2017, Morphologic evolution of the wilderness area breach at Fire Island, New York—2012–15: U.S. Geological Survey Open-File Report 2017–1116, 17 p., https://doi.org/10.3133/ofr20171116.","productDescription":"Report: vi, 17 p.","numberOfPages":"24","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-086286","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":345809,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ds1049","text":"Data Series 1049","description":"Data Series 1049","linkHelpText":"- Coastal bathymetry data collected in May 2015 from Fire Island, New York—Wilderness breach and shoreface"},{"id":345808,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ds1034","text":"Data Series 1034","description":"Data Series 1034","linkHelpText":"Bathymetry data collected in October 2014 from Fire Island, New York—The wilderness breach, shoreface, and bay"},{"id":345810,"rank":7,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ds1007","text":"Data Series 1007","description":"Data Series 1007","linkHelpText":"- Coastal bathymetry data collected in June 2014 from Fire Island, New York—The wilderness breach and shoreface"},{"id":345750,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1116/coverthb.jpg"},{"id":345805,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1116/ofr20171116.pdf","text":"Report","size":"21.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1116"},{"id":345806,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ds914","text":"Data Series 914","description":"Data Series 914","linkHelpText":"- Bathymetry of Wilderness Breach at Fire Island, New York from June 2013"},{"id":345807,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7G15Z17","text":"USGS data release","description":"USGS data release","linkHelpText":"Hurricane Sandy Beach Response and Recovery at Fire Island, New York—Shoreline and Beach Profile Data, October 2012 to June 2016"}],"country":"United States","state":"New York","otherGeospatial":"Fire Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.32000732421875,\n 40.6113461833302\n ],\n [\n -72.87574768066406,\n 40.6113461833302\n ],\n [\n -72.87574768066406,\n 40.73581157695217\n ],\n [\n -73.32000732421875,\n 40.73581157695217\n ],\n [\n -73.32000732421875,\n 40.6113461833302\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
We used camera traps to determine which predators were responsible for depredated Pomacea maculata (Maculata Apple Snail) shells at 2 different study sites. Evidence of predation at these sites included operculums near the shells with a small amount of flesh attached and shells accumulating a meter or more from the water’s edge with no evidence of recent flooding. In both locations, the most frequently observed potential predators were Procyon lotor (Raccoon), which was the only species directly observed capturing and eating Apple Snails.
","language":"English","publisher":"Eagle Hill Publications","doi":"10.1656/058.016.0302","usgsCitation":"Carter, J., Merino, S., Prejean, D., and LaFleur, G., 2017, Observations of raccoon (Procyon lotor) predation on the invasive Maculata apple snail (Pomacea maculata) in southern Louisiana: Southeastern Naturalist, v. 16, no. 3, p. N14-N18, https://doi.org/10.1656/058.016.0302.","productDescription":"5 p.","startPage":"N14","endPage":"N18","ipdsId":"IP-085459","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":438213,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7N87807","text":"USGS data release","linkHelpText":"Video observations of raccoon (Procyon loctor) predation on the invasive Maculata apple snail (Pomacea maculata) in south Louisiana, USA - 2017"},{"id":345823,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.02099609375,\n 28.700224692776988\n ],\n [\n -89.176025390625,\n 28.700224692776988\n ],\n [\n -89.176025390625,\n 31.12819929911196\n ],\n [\n -94.02099609375,\n 31.12819929911196\n ],\n [\n -94.02099609375,\n 28.700224692776988\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"16","issue":"3","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59bf8998e4b091459a5e0877","contributors":{"authors":[{"text":"Carter, Jacoby 0000-0003-0110-0284 carterj@usgs.gov","orcid":"https://orcid.org/0000-0003-0110-0284","contributorId":2399,"corporation":false,"usgs":true,"family":"Carter","given":"Jacoby","email":"carterj@usgs.gov","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":710622,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Merino, Sergio 0000-0002-2834-2243 merinos@usgs.gov","orcid":"https://orcid.org/0000-0002-2834-2243","contributorId":3653,"corporation":false,"usgs":true,"family":"Merino","given":"Sergio","email":"merinos@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":710623,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Prejean, Drew","contributorId":195560,"corporation":false,"usgs":false,"family":"Prejean","given":"Drew","email":"","affiliations":[{"id":33463,"text":"Nicholls State University, Thibodaux, LA","active":true,"usgs":false}],"preferred":false,"id":710625,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"LaFleur, Gary","contributorId":195559,"corporation":false,"usgs":false,"family":"LaFleur","given":"Gary","email":"","affiliations":[{"id":33463,"text":"Nicholls State University, Thibodaux, LA","active":true,"usgs":false}],"preferred":false,"id":710624,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70190828,"text":"70190828 - 2017 - Sensitivity of the downward to sweeping velocity ratio to the bypass flow percentage along a guide wall for downstream fish passage","interactions":[],"lastModifiedDate":"2017-09-17T10:01:00","indexId":"70190828","displayToPublicDate":"2017-09-17T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1454,"text":"Ecological Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Sensitivity of the downward to sweeping velocity ratio to the bypass flow percentage along a guide wall for downstream fish passage","docAbstract":"Partial-depth impermeable guidance structures (or guide walls) are used as a method to assist in the downstream passage of fish at a hydroelectric facility. However, guide walls can result in a strong downward velocity causing the approaching fish to pass below the wall and into the direction of the turbine intakes. The objective of this study was to describe how the ratio of the vertical velocity to the sweeping velocity magnitude changes along the full length and depth of a guide wall under a wide range of bypass flow percentages within a power canal. This paper focused on two guide wall configurations, each set at an angle of 45 ° to the approaching flow field and at a depth of 10 and 20 ft (3.05 and 6.10 m). The hydraulic conditions upstream of each guide wall configuration were shown to be impacted by a change in the bypass flow percentage, not only near the bypass but also at upstream sections of the guide wall. Furthermore, the effect of changing the bypass flow percentage was similar for both guide wall depths. In both cases, the effect of increasing the bypass flow percentage was magnified closer to the bypass and deeper in the water column along the guide wall.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecoleng.2017.08.012","usgsCitation":"Mulligan, K., Towler, B., Haro, A.J., and Ahlfeld, D.P., 2017, Sensitivity of the downward to sweeping velocity ratio to the bypass flow percentage along a guide wall for downstream fish passage: Ecological Engineering, v. 109, no. Part A, p. 10-14, https://doi.org/10.1016/j.ecoleng.2017.08.012.","productDescription":"5 p.","startPage":"10","endPage":"14","ipdsId":"IP-080644","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":461403,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.osti.gov/biblio/1549958","text":"Publisher Index Page"},{"id":345820,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"109","issue":"Part A","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59bf8999e4b091459a5e0879","contributors":{"authors":[{"text":"Mulligan, Kevin B. 0000-0002-3534-4239 kmulligan@usgs.gov","orcid":"https://orcid.org/0000-0002-3534-4239","contributorId":177024,"corporation":false,"usgs":true,"family":"Mulligan","given":"Kevin","email":"kmulligan@usgs.gov","middleInitial":"B.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":710618,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Towler, Brett","contributorId":141164,"corporation":false,"usgs":false,"family":"Towler","given":"Brett","email":"","affiliations":[{"id":6927,"text":"USFWS, National Wildlife Refuge System","active":true,"usgs":false}],"preferred":false,"id":710619,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haro, Alexander J. 0000-0002-7188-9172 aharo@usgs.gov","orcid":"https://orcid.org/0000-0002-7188-9172","contributorId":2917,"corporation":false,"usgs":true,"family":"Haro","given":"Alexander","email":"aharo@usgs.gov","middleInitial":"J.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":710620,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ahlfeld, David P.","contributorId":196530,"corporation":false,"usgs":false,"family":"Ahlfeld","given":"David","email":"","middleInitial":"P.","affiliations":[{"id":34616,"text":"University of Massachusetts Amherst","active":true,"usgs":false}],"preferred":false,"id":710621,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70190838,"text":"70190838 - 2017 - A rare and cryptic endemic of the Central Rocky Mountains, U.S.A: The distribution of the Arapahoe snowfly, Arsapnia arapahoe (Nelson & Kondratieff, 1988) (Plecoptera: Capniidae)","interactions":[],"lastModifiedDate":"2020-10-23T11:58:59.600213","indexId":"70190838","displayToPublicDate":"2017-09-17T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1972,"text":"Illiesia","onlineIssn":"1854-0392","printIssn":"1855-5810","active":true,"publicationSubtype":{"id":10}},"displayTitle":"A rare and cryptic endemic of the Central Rocky Mountains, U.S.A: The distribution of the Arapahoe snowfly, Arsapnia arapahoe (Nelson & Kondratieff, 1988) (Plecoptera: Capniidae)","title":"A rare and cryptic endemic of the Central Rocky Mountains, U.S.A: The distribution of the Arapahoe snowfly, Arsapnia arapahoe (Nelson & Kondratieff, 1988) (Plecoptera: Capniidae)","docAbstract":"The Arapahoe snowfly, Arsapnia arapahoe (Nelson & Kondratieff, 1988) (Plecoptera: Capniidae) is a candidate species warranted for listing under the Endangered Species Act. Prior to this study, A. arapahoe was known from only two tributaries of the Cache la Poudre River in Larimer County, Colorado: Young Gulch and Elkhorn Creek. The objectives of this study were to determine the distribution of this endemic stonefly, and to identify sympatric species as possible surrogate indicators of its occurrence. Eighty-four streams were sampled within the expected geographical range and emergence time-period from 2013 to 2017. Adults of A. arapahoe were discovered in 19 first-, second-, and fourth-order streams beyond the original type localities tributary to the Cache la Poudre River. The new and recently recorded localities were discovered in the Big Thompson River, St. Vrain River, Boulder Creek, and Upper South Platte River Watersheds. Two species, A. decepta (Banks, 1897) and Capnia gracilaria Claassen, 1924, always co-occurred with A. arapahoe, suggesting this species pair may serve as a surrogate indicator of suitable stream habitat for A. arapahoe. Suggestions for future investigation into the distribution, life-history, and habitat of A. arapahoe are presented to aid the conservation of this rare and endemic Colorado stonefly.
","language":"English","publisher":"University of Illinois","usgsCitation":"Fairchild, M.P., Belcher, T.P., Zuellig, R.E., Vieira, N.M., and Kondratieff, B.C., 2017, A rare and cryptic endemic of the Central Rocky Mountains, U.S.A: The distribution of the Arapahoe snowfly, Arsapnia arapahoe (Nelson & Kondratieff, 1988) (Plecoptera: Capniidae): Illiesia, v. 13, no. 4, p. 50-58.","productDescription":"9 p.","startPage":"50","endPage":"58","ipdsId":"IP-086310","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":345826,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":345804,"type":{"id":15,"text":"Index Page"},"url":"https://illiesia.speciesfile.org/html/2017.html"}],"country":"United States","state":"Colorado","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.8,\n 37.8\n ],\n [\n -104.5,\n 37.8\n ],\n [\n -104.5,\n 41\n ],\n [\n -105.8,\n 41\n ],\n [\n -105.8,\n 37.8\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"13","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59bf8996e4b091459a5e0875","contributors":{"authors":[{"text":"Fairchild, Matthew P.","contributorId":196533,"corporation":false,"usgs":false,"family":"Fairchild","given":"Matthew","email":"","middleInitial":"P.","affiliations":[{"id":24595,"text":"USDA Forest Service, Fort Collins CO","active":true,"usgs":false}],"preferred":false,"id":710669,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Belcher, Thomas P. III","contributorId":196532,"corporation":false,"usgs":false,"family":"Belcher","given":"Thomas","suffix":"III","email":"","middleInitial":"P.","affiliations":[{"id":17860,"text":"Colorado State University, Fort Collins, Colorado","active":true,"usgs":false}],"preferred":false,"id":710670,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zuellig, Robert E. 0000-0002-4784-2905 rzuellig@usgs.gov","orcid":"https://orcid.org/0000-0002-4784-2905","contributorId":1620,"corporation":false,"usgs":true,"family":"Zuellig","given":"Robert","email":"rzuellig@usgs.gov","middleInitial":"E.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":710671,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vieira, Nicole M. K.","contributorId":104172,"corporation":false,"usgs":false,"family":"Vieira","given":"Nicole","email":"","middleInitial":"M. K.","affiliations":[{"id":17860,"text":"Colorado State University, Fort Collins, Colorado","active":true,"usgs":false}],"preferred":false,"id":710672,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kondratieff, Boris C.","contributorId":24868,"corporation":false,"usgs":false,"family":"Kondratieff","given":"Boris","email":"","middleInitial":"C.","affiliations":[{"id":17860,"text":"Colorado State University, Fort Collins, Colorado","active":true,"usgs":false}],"preferred":false,"id":710673,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70187402,"text":"ds1050 - 2017 - Results of hydrologic monitoring of a landslide-prone hillslope in Portland’s West Hills, Oregon, 2006–2017","interactions":[],"lastModifiedDate":"2017-09-20T11:40:26","indexId":"ds1050","displayToPublicDate":"2017-09-15T16:00:00","publicationYear":"2017","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":"1050","title":"Results of hydrologic monitoring of a landslide-prone hillslope in Portland’s West Hills, Oregon, 2006–2017","docAbstract":"The West Hills of Portland, in the southern Tualatin Mountains, trend northwest along the west side of Portland, Oregon. These silt-mantled mountains receive significant wet-season precipitation and are prone to sliding during wet conditions, occasionally resulting in property damage or casualties. In an effort to develop a baseline for interpretive analysis of the groundwater response to rainfall, an automated monitoring system was installed in 2006 to measure rainfall, pore-water pressure, soil suction, soil-water potential, and volumetric water content at 15-minute intervals. The data show a cyclical pattern of groundwater and moisture content levels—wet from October to May and dry between June and September. Saturated soil conditions tend to last throughout the wet season. These data show the hydrologic response of the monitored area to rainfall and provide insight into the dynamics of rainfall-initiated landsliding. This report details the monitoring methods and presents data collected from January 10, 2006, through January 23, 2017.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1050","collaboration":"Prepared in cooperation with Portland State University","usgsCitation":"Smith, J.B., Godt, J.W., Baum, R.L., Coe, J.A., Ellis, W.L., Jones, E.S., and Burns, S.F., 2017, Results of hydrologic monitoring of a landslide-prone hillslope in Portland’s West Hills, Oregon, 2006–2017: U.S. Geological Survey Data Series 1050, 10 p., https://doi.org/10.3133/ds1050.","productDescription":"Report: iv, 10 p.; Data Release","numberOfPages":"18","onlineOnly":"Y","ipdsId":"IP-080635","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":345599,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7KK98XK","text":"USGS Data Release","description":"USGS Data Release","linkHelpText":"Results of Hydrologic Monitoring of a Landslide-Prone Hillslope in Portland’s West Hills, Oregon, 2006–2017"},{"id":345590,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1050/coverthb.jpg"},{"id":345591,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1050/ds1050.pdf","text":"Report","size":"1.33 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1050"}],"country":"United States","state":"Oregon","city":"Portland","otherGeospatial":"Tualatin Mountains, West Hills of Portland","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.7372,\n 45.5214\n ],\n [\n -122.7333,\n 45.5214\n ],\n [\n -122.7333,\n 45.5233\n ],\n [\n -122.7372,\n 45.5233\n ],\n [\n -122.7372,\n 45.5214\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Geologic Hazards Science Center
U.S. Geological Survey
Box 25046, MS–966
Denver, CO 80225–0046
Several streams used for recreational activities, such as fishing, swimming, and boating, in Chester County, Pennsylvania, are known to have periodic elevated concentrations of fecal coliform bacteria, a type of bacteria used to indicate the potential presence of fecally related pathogens that may pose health risks to humans exposed through water contact. The availability of near real-time continuous stream discharge, turbidity, and other water-quality data for some streams in the county presents an opportunity to use surrogates to estimate near real-time concentrations of fecal coliform (FC) bacteria and thus provide some information about associated potential health risks during recreational use of streams.
The U.S. Geological Survey (USGS), in cooperation with the Chester County Health Department (CCHD) and the Chester County Water Resources Authority (CCWRA), has collected discrete stream samples for analysis of FC concentrations during March–October annually at or near five gaging stations where near real-time continuous data on stream discharge, turbidity, and water temperature have been collected since 2007 (or since 2012 at 2 of the 5 stations). In 2014, the USGS, in cooperation with the CCWRA and CCHD, began to develop regression equations to estimate FC concentrations using available near real-time continuous data. Regression equations included possible explanatory variables of stream discharge, turbidity, water temperature, and seasonal factors calculated using Julian Day with base-10 logarithmic (log) transformations of selected variables.
The regression equations were developed using the data from 2007 to 2015 (101–106 discrete bacteria samples per site) for three gaging stations on Brandywine Creek (West Branch Brandywine Creek at Modena, East Branch Brandywine Creek below Downingtown, and Brandywine Creek at Chadds Ford) and from 2012 to 2015 (37–38 discrete bacteria samples per site) for one station each on French Creek near Phoenixville and White Clay Creek near Strickersville. Fecal coliform bacteria data collected by USGS in 2016 (about nine samples per site) were used to validate the equations. The best-fit regression equations included log turbidity and seasonality factors computed using Julian Day as explanatory variables to estimate log FC concentrations at all five stream sites. The adjusted coefficient of determination for the equations ranged from 0.61 to 0.76, with the strength of the regression equations likely affected in part by the limited amount and variability of FC bacteria data. During summer months, the estimated and measured FC concentrations commonly were greater than the Pennsylvania Department of Environmental Protection established standards of 200 and 400 colonies per 100 milliliters for water contact from May through September at the 5 stream sites, with concentrations typically higher at 2 sites (White Clay Creek and West Branch Brandywine Creek at Modena) than at the other 3 sites. The estimated concentrations of FC bacteria during the summer months commonly were higher than measured concentrations and therefore could be considered cautious estimates of potential human-health risk. Additional water-quality data are needed to maintain and (or) improve the ability of regression equations to estimate FC concentrations by use of surrogate data.
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KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Model Archive Summary for Best-Fit Regression Developed to Estimate Fecal Coliform Concentration at Station 01480870; East Branch Brandywine Creek below Downingtown, Pennsylvania"},{"id":345650,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5075/coverthb4.jpg"},{"id":345652,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2017/5075/sir20175075_appendix1.pdf","text":"Appendix 1","size":"505 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Model Archive Summary for Best-Fit Regression Developed to Estimate Fecal Coliform Concentration at Station 01480617; West Branch Brandywine Creek at Modena, Pennsylvania"},{"id":345651,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5075/sir20175075.pdf","text":"Report","size":"12.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5075"}],"country":"United 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U.S. Geological Survey
215 Limekiln Road
New Cumberland, PA 17070-2424
A module for simulation of daily mean water temperature in a network of stream segments has been developed as an enhancement to the U.S. Geological Survey Precipitation Runoff Modeling System (PRMS). This new module is based on the U.S. Fish and Wildlife Service Stream Network Temperature model, a mechanistic, one-dimensional heat transport model. The new module is integrated in PRMS. Stream-water temperature simulation is activated by selection of the appropriate input flags in the PRMS Control File and by providing the necessary additional inputs in standard PRMS input files.This report includes a comprehensive discussion of the methods relevant to the stream temperature calculations and detailed instructions for model input preparation.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Section D: Groundwater/surface-water interactions in Book 6: Modeling techniques","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm6D4","usgsCitation":"Sanders, M.J., Markstrom, S.L., Regan, R.S., and Atkinson, R.D., 2017, Documentation of a daily mean stream temperature module—An enhancement to the Precipitation-Runoff Modeling System: U.S. Geological Survey Techniques and Methods, book 6, chap. D4, 18 p., https://doi.org/10.3133/tm6D4.","productDescription":"v, 18 p.","numberOfPages":"28","onlineOnly":"Y","ipdsId":"IP-081476","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":345706,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/06/d04/coverthb.jpg"},{"id":345707,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/06/d04/tm6d4.pdf","text":"Report","size":"796 kB","linkFileType":{"id":1,"text":"pdf"},"description":"TM 6-D4"}],"publicComments":"This report in Chapter 4 of Section D: Groundwater/surface-water interactions in Book 6: Modeling techniques.","contact":"Chief, Branch of Regional Research, Central Region
U.S. Geological Survey
Box 25046, MS–418
Denver, CO 80225–0046
Dam removals with unmanaged sediment releases are good opportunities to learn about channel response to abruptly increased bed material supply. Understanding these events is important because they affect aquatic habitats and human uses of floodplains. A longstanding paradigm in geomorphology holds that response rates to landscape disturbance exponentially decay through time. However, a previous study of the Merrimack Village Dam (MVD) removal on the Souhegan River in New Hampshire, USA, showed that an exponential function poorly described the early geomorphic response. Erosion of impounded sediments there was two-phased. We had an opportunity to quantitatively test the two-phase response model proposed for MVD by extending the record there and comparing it with data from the Simkins Dam removal on the Patapsco River in Maryland, USA. The watershed sizes are the same order of magnitude (102 km2), and at both sites low-head dams were removed (~3–4 m) and ~65 000 m3 of sand-sized sediments were discharged to low-gradient reaches. Analyzing four years of repeat morphometry and sediment surveys at the Simkins site, as well as continuous discharge and turbidity data, we observed the two-phase erosion response described for MVD. In the early phase, approximately 50% of the impounded sediment at Simkins was eroded rapidly during modest flows. After incision to base level and widening, a second phase began when further erosion depended on floods large enough to go over bank and access impounded sediments more distant from the newly-formed channel. Fitting functional forms to the data for both sites, we found that two-phase exponential models with changing decay constants fit the erosion data better than single-phase models. Valley width influences the two-phase erosion responses upstream, but downstream responses appear more closely related to local gradient, sediment re-supply from the upstream impoundments, and base flows.
","language":"English","publisher":"Wiley","doi":"10.1002/esp.4108","usgsCitation":"Collins, M.J., Snyder, N.P., Boardman, G., Banks, W.S., Andrews, M., Baker, M.E., Conlon, M., Gellis, A.C., McClain, S., Miller, A., and Wilcock, P., 2017, Channel response to sediment release: insights from a paired analysis of dam removal: Earth Surface Processes and Landforms, v. 42, no. 11, p. 1636-1651, https://doi.org/10.1002/esp.4108.","productDescription":"16 p.","startPage":"1636","endPage":"1651","ipdsId":"IP-072066","costCenters":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true}],"links":[{"id":347228,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland","otherGeospatial":"Simkins Dam ","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.79872512817383,\n 39.264689574787724\n ],\n [\n -76.70053482055663,\n 39.20671884491848\n ],\n [\n -76.69126510620117,\n 39.215630305545304\n ],\n [\n -76.78979873657227,\n 39.27213188522936\n ],\n [\n -76.79872512817383,\n 39.264689574787724\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"42","issue":"11","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2017-02-14","publicationStatus":"PW","scienceBaseUri":"59f05121e4b0220bbd9a1d83","contributors":{"authors":[{"text":"Collins, Mathias J.","contributorId":181551,"corporation":false,"usgs":false,"family":"Collins","given":"Mathias","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":714847,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Snyder, Noah P.","contributorId":198029,"corporation":false,"usgs":false,"family":"Snyder","given":"Noah","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":714848,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Boardman, Graham","contributorId":198030,"corporation":false,"usgs":false,"family":"Boardman","given":"Graham","email":"","affiliations":[],"preferred":false,"id":714849,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Banks, William S. 0000-0002-2090-8708 wsbanks@usgs.gov","orcid":"https://orcid.org/0000-0002-2090-8708","contributorId":2349,"corporation":false,"usgs":true,"family":"Banks","given":"William","email":"wsbanks@usgs.gov","middleInitial":"S.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":714850,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Andrews, Mary","contributorId":198031,"corporation":false,"usgs":false,"family":"Andrews","given":"Mary","email":"","affiliations":[],"preferred":false,"id":714851,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Baker, Matthew E.","contributorId":42889,"corporation":false,"usgs":true,"family":"Baker","given":"Matthew","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":715151,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Conlon, Maricate","contributorId":198032,"corporation":false,"usgs":false,"family":"Conlon","given":"Maricate","email":"","affiliations":[],"preferred":false,"id":714852,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Gellis, Allen C. 0000-0002-3449-2889 agellis@usgs.gov","orcid":"https://orcid.org/0000-0002-3449-2889","contributorId":197684,"corporation":false,"usgs":true,"family":"Gellis","given":"Allen","email":"agellis@usgs.gov","middleInitial":"C.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":714846,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"McClain, Serena","contributorId":198033,"corporation":false,"usgs":false,"family":"McClain","given":"Serena","email":"","affiliations":[],"preferred":false,"id":714853,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Miller, Andrew","contributorId":196361,"corporation":false,"usgs":false,"family":"Miller","given":"Andrew","affiliations":[],"preferred":false,"id":714854,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Wilcock, Peter","contributorId":198034,"corporation":false,"usgs":false,"family":"Wilcock","given":"Peter","affiliations":[],"preferred":false,"id":714855,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70190789,"text":"70190789 - 2017 - Novel analyses of long-term data provide a scientific basis for chlorophyll-a thresholds in San Francisco Bay","interactions":[],"lastModifiedDate":"2017-09-14T11:00:17","indexId":"70190789","displayToPublicDate":"2017-09-14T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1587,"text":"Estuarine, Coastal and Shelf Science","active":true,"publicationSubtype":{"id":10}},"title":"Novel analyses of long-term data provide a scientific basis for chlorophyll-a thresholds in San Francisco Bay","docAbstract":"San Francisco Bay (SFB), USA, is highly enriched in nitrogen and phosphorus, but has been resistant to the classic symptoms of eutrophication associated with over-production of phytoplankton. Observations in recent years suggest that this resistance may be weakening, shown by: significant increases of chlorophyll-a (chl-a) and decreases of dissolved oxygen (DO), common occurrences of phytoplankton taxa that can form Harmful Algal Blooms (HAB), and algal toxins in water and mussels reaching levels of concern. As a result, managers now ask: what levels of chl-a in SFB constitute tipping points of phytoplankton biomass beyond which water quality will become degraded, requiring significant nutrient reductions to avoid impairments? We analyzed data for DO, phytoplankton species composition, chl-a, and algal toxins to derive quantitative relationships between three indicators (HAB abundance, toxin concentrations, DO) and chl-a. Quantile regressions relating HAB abundance and DO to chl-a were significant, indicating SFB is at increased risk of adverse HAB and low DO levels if chl-a continues to increase. Conditional probability analysis (CPA) showed chl-a of 13 mg m−3 as a “protective” threshold below which probabilities for exceeding alert levels for HAB abundance and toxins were reduced. This threshold was similar to chl-a of 13–16 mg m−3 that would meet a SFB-wide 80% saturation Water Quality Criterion (WQC) for DO. Higher “at risk” chl-a thresholds from 25 to 40 mg m−3 corresponded to 0.5 probability of exceeding alert levels for HAB abundance, and for DO below a WQC of 5.0 mg L−1 designated for lower South Bay (LSB) and South Bay (SB). We submit these thresholds as a basis to assess eutrophication status of SFB and to inform nutrient management actions. This approach is transferrable to other estuaries to derive chl-a thresholds protective against eutrophication.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecss.2017.07.009","usgsCitation":"Sutula, M., Kudela, R., Hagy, J.D., Harding, L.W., Senn, D., Cloern, J.E., Bricker, S.B., Beck, M.W., and Berg, G.M., 2017, Novel analyses of long-term data provide a scientific basis for chlorophyll-a thresholds in San Francisco Bay: Estuarine, Coastal and Shelf Science, v. 197, p. 107-118, https://doi.org/10.1016/j.ecss.2017.07.009.","productDescription":"12 p.","startPage":"107","endPage":"118","ipdsId":"IP-071224","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":469523,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/6134865","text":"Publisher Index Page"},{"id":345755,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","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 -122.62115478515625,\n 37.385435182627226\n ],\n [\n -121.35498046875,\n 37.385435182627226\n ],\n [\n -121.35498046875,\n 38.199338565983844\n ],\n [\n -122.62115478515625,\n 38.199338565983844\n ],\n [\n -122.62115478515625,\n 37.385435182627226\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"197","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59bb952de4b091459a578178","contributors":{"authors":[{"text":"Sutula, Martha","contributorId":191008,"corporation":false,"usgs":false,"family":"Sutula","given":"Martha","email":"","affiliations":[],"preferred":false,"id":710406,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kudela, Raphael","contributorId":196461,"corporation":false,"usgs":false,"family":"Kudela","given":"Raphael","affiliations":[],"preferred":false,"id":710407,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hagy, James","contributorId":196462,"corporation":false,"usgs":false,"family":"Hagy","given":"James","affiliations":[],"preferred":false,"id":710408,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Harding, Lawrence W. Jr.","contributorId":196465,"corporation":false,"usgs":false,"family":"Harding","given":"Lawrence","suffix":"Jr.","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":710416,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Senn, David","contributorId":177368,"corporation":false,"usgs":false,"family":"Senn","given":"David","affiliations":[],"preferred":false,"id":710409,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cloern, James E. 0000-0002-5880-6862 jecloern@usgs.gov","orcid":"https://orcid.org/0000-0002-5880-6862","contributorId":1488,"corporation":false,"usgs":true,"family":"Cloern","given":"James","email":"jecloern@usgs.gov","middleInitial":"E.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":710405,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Bricker, Suzanne B.","contributorId":64555,"corporation":false,"usgs":false,"family":"Bricker","given":"Suzanne","email":"","middleInitial":"B.","affiliations":[{"id":12448,"text":"U.S. National Oceanic and Atmospheric Administration","active":true,"usgs":false}],"preferred":false,"id":710410,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Berg, Gry Mine","contributorId":196466,"corporation":false,"usgs":false,"family":"Berg","given":"Gry","email":"","middleInitial":"Mine","affiliations":[],"preferred":false,"id":710412,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Beck, Marcus W.","contributorId":172025,"corporation":false,"usgs":false,"family":"Beck","given":"Marcus","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":710413,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70194618,"text":"70194618 - 2017 - Effects of surgically implanted transmitters on reproduction and survival in mallards","interactions":[],"lastModifiedDate":"2017-12-08T10:33:57","indexId":"70194618","displayToPublicDate":"2017-09-14T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3779,"text":"Wildlife Society Bulletin","onlineIssn":"1938-5463","printIssn":"0091-7648","active":true,"publicationSubtype":{"id":10}},"title":"Effects of surgically implanted transmitters on reproduction and survival in mallards","docAbstract":"Abdominally implanted radiotransmitters have been widely used in studies of waterbird ecology; however, the longer handling times and invasiveness of surgical implantation raise important concerns about animal welfare and potential effects on data quality. Although it is difficult to assess effects of handling and marking wild animals by comparing them with unmarked controls, insights can often be obtained by evaluating variation in handling or marking techniques. Here, we used data from 243 female mallards (Anas platyrhynchos) and mallard–grey duck hybrids (A. platyrhynchos × A. superciliosa) equipped with fully encapsulated abdominally implanted radiotransmitters from 2 study sites in New Zealand during 2014–2015 to assess potential marking effects. We evaluated survival, dispersal, and reproductive effort (e.g., breeding propensity, nest initiation date, clutch size) in response to 3 different attributes of handling duration and procedures: 1) processing time, including presurgery banding, measurements, and blood sampling of unanaesthetized birds; 2) surgery time from initiation to cessation of anesthetic; and 3) total holding time from first capture until release. We found no evidence that female survival, dispersal probability, or reproductive effort were negatively affected by holding, processing, or surgery time and concluded that we collected reliable data without compromising animal welfare. Our results support previous research that techniques using fully encapsulated abdominal-implant radiotransmitters are suitable to enable researchers to obtain reliable estimates of reproductive performance and survival.
","language":"English","publisher":"The Wildlife Society","doi":"10.1002/wsb.809","usgsCitation":"Sheppard, J., Arnold, T.W., Amundson, C.L., and Klee, D., 2017, Effects of surgically implanted transmitters on reproduction and survival in mallards: Wildlife Society Bulletin, v. 41, no. 3, p. 597-604, https://doi.org/10.1002/wsb.809.","productDescription":"8 p.","startPage":"597","endPage":"604","ipdsId":"IP-076756","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":469524,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doaj.org/article/aca8693eb8bb4dda98863dc3669b1e0b","text":"Publisher Index Page"},{"id":349877,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"New Zealand","volume":"41","issue":"3","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-09-09","publicationStatus":"PW","scienceBaseUri":"5a60fb51e4b06e28e9c22f37","contributors":{"authors":[{"text":"Sheppard, Jennifer","contributorId":201215,"corporation":false,"usgs":false,"family":"Sheppard","given":"Jennifer","affiliations":[],"preferred":false,"id":724644,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":724645,"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":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":724643,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Klee, David","contributorId":201217,"corporation":false,"usgs":false,"family":"Klee","given":"David","email":"","affiliations":[],"preferred":false,"id":724647,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70190584,"text":"fs20173070 - 2017 - U.S. Geological Survey geohydrologic studies and monitoring at the Idaho National Laboratory, southeastern Idaho","interactions":[],"lastModifiedDate":"2017-09-18T10:31:25","indexId":"fs20173070","displayToPublicDate":"2017-09-14T00:00:00","publicationYear":"2017","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":"2017-3070","title":"U.S. Geological Survey geohydrologic studies and monitoring at the Idaho National Laboratory, southeastern Idaho","docAbstract":"The U.S. Geological Survey (USGS) geohydrologic studies and monitoring at the Idaho National Laboratory (INL) is an ongoing, long-term program. This program, which began in 1949, includes hydrologic monitoring networks and investigative studies that describe the effects of waste disposal on water contained in the eastern Snake River Plain (ESRP) aquifer and the availability of water for long-term consumptive and industrial use. Interpretive reports documenting study findings are available to the U.S. Department of Energy (DOE) and its contractors; other Federal, State, and local agencies; private firms; and the public at https://id.water.usgs.gov/INL/Pubs/index.html. Information contained within these reports is crucial to the management and use of the aquifer by the INL and the State of Idaho. USGS geohydrologic studies and monitoring are done in cooperation with the DOE Idaho Operations Office.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20173070","usgsCitation":"Bartholomay, R.C., 2017, U.S. Geological Survey geohydrologic studies and monitoring at the Idaho National Laboratory, southeastern Idaho: U.S. Geological Survey Fact Sheet 2017–3070, 4 p., https://doi.org/10.3133/fs20173070.","productDescription":"4 p.","onlineOnly":"Y","ipdsId":"IP-090121","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":345796,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2017/3070/fs20173070.pdf","text":"Report","size":"1.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2017-3070"},{"id":345795,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2017/3070/coverthb.jpg"}],"country":"United States","state":"Idaho","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -113.73046875,\n 43.36312895068202\n ],\n [\n -112.2308349609375,\n 43.36312895068202\n ],\n [\n -112.2308349609375,\n 44.465151013519616\n ],\n [\n -113.73046875,\n 44.465151013519616\n ],\n [\n -113.73046875,\n 43.36312895068202\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Idaho National Laboratory Project Office
U.S. Geological Survey
1955 N. Fremont
Idaho Falls, Idaho 83415
Background: Metolachlor [(RS)-2-Chloro-N-(2-ethyl-6-methyl-phenyl)-N-(1-methoxypropan-2-yl)acetamide] and two degradates (metolachlor ethane-sulfonic acid and metolachlor oxanilic acid) are commonly observed in surface and groundwater. The behavior and fate of these compounds were examined over a 12-year period in seven agricultural watersheds in the United States. They were quantified in air, rain, streams, overland flow, groundwater, soil water, subsurface drain water, and water at the stream/groundwater interface. The compounds were frequently detected in surface and groundwater associated with agricultural areas. A mass budget approach, based on all available data from the study and literature, was used to determine a percentage-wise generalized distribution and fate of applied parent metolachlor in typical agricultural environments.
Results: In these watersheds, about 90% of applied metolachlor was taken up by plants or degraded, 10% volatilized, and 0.3% returned as rainfall. One percent was transported to surface water, while an equal amount infiltrated into the unsaturated zone soil water. < 0.02% reached the groundwater. Subsurface flow paths resulted in greater degradation of metolachlor because degradation reactions had more time to proceed.
Conclusions: An understanding of the residence times of water in the different environmental compartments, and the important processes affecting metolachlor as it is transported along flowpaths among the environmental compartments allows for a degree of predictability of metolachlor's fate. Degradates with long half-lives can be used (in a limited capacity) as tracers of metolachlor, because of their persistence and widespread occurrence in the environment.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2017.08.154","usgsCitation":"Rose, C.E., Coupe, R.H., Capel, P.D., and Webb, R.M., 2017, Holistic assessment of occurrence and fate of metolachlor within environmental compartments of agricultural watersheds: Science of the Total Environment, v. 612, p. 708-719, https://doi.org/10.1016/j.scitotenv.2017.08.154.","productDescription":"12 p.","startPage":"708","endPage":"719","ipdsId":"IP-077291","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":345776,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"612","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59bb952ce4b091459a578170","contributors":{"authors":[{"text":"Rose, Claire E. 0000-0002-5519-3538 cerose@usgs.gov","orcid":"https://orcid.org/0000-0002-5519-3538","contributorId":2317,"corporation":false,"usgs":true,"family":"Rose","given":"Claire","email":"cerose@usgs.gov","middleInitial":"E.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":710480,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coupe, Richard H. 0000-0001-8679-1015 rhcoupe@usgs.gov","orcid":"https://orcid.org/0000-0001-8679-1015","contributorId":551,"corporation":false,"usgs":true,"family":"Coupe","given":"Richard","email":"rhcoupe@usgs.gov","middleInitial":"H.","affiliations":[{"id":394,"text":"Mississippi Water Science Center","active":true,"usgs":true}],"preferred":true,"id":710481,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Capel, Paul D. 0000-0003-1620-5185 capel@usgs.gov","orcid":"https://orcid.org/0000-0003-1620-5185","contributorId":1002,"corporation":false,"usgs":true,"family":"Capel","given":"Paul","email":"capel@usgs.gov","middleInitial":"D.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":710482,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Webb, Richard M. 0000-0001-9531-2207 rmwebb@usgs.gov","orcid":"https://orcid.org/0000-0001-9531-2207","contributorId":1570,"corporation":false,"usgs":true,"family":"Webb","given":"Richard","email":"rmwebb@usgs.gov","middleInitial":"M.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":710483,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70190153,"text":"ds1062 - 2017 - A reservoir morphology database for the conterminous United States","interactions":[],"lastModifiedDate":"2017-09-13T13:38:23","indexId":"ds1062","displayToPublicDate":"2017-09-13T12:00:00","publicationYear":"2017","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":"1062","title":"A reservoir morphology database for the conterminous United States","docAbstract":"The U.S. Geological Survey, in cooperation with the Reservoir Fisheries Habitat Partnership, combined multiple national databases to create one comprehensive national reservoir database and to calculate new morphological metrics for 3,828 reservoirs. These new metrics include, but are not limited to, shoreline development index, index of basin permanence, development of volume, and other descriptive metrics based on established morphometric formulas. The new database also contains modeled chemical and physical metrics. Because of the nature of the existing databases used to compile the Reservoir Morphology Database and the inherent missing data, some metrics were not populated. One comprehensive database will assist water-resource managers in their understanding of local reservoir morphology and water chemistry characteristics throughout the continental United States.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1062","collaboration":"Prepared in cooperation with the Reservoir Fisheries Habitat Partnership","usgsCitation":"Rodgers, K.D., 2017, A reservoir morphology database for the conterminous United States: U.S. Geological Survey Data Series 1062, https://doi.org/10.3133/ds1062.","productDescription":"HTML Document; Data Release; Appendix 1","onlineOnly":"Y","ipdsId":"IP-071730","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":345577,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7GF0RQZ","text":"USGS data release","description":"USGS data release","linkHelpText":"A Reservoir Morphology Database for the Conterminous United States"},{"id":345576,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1062/index.html","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"DS 1062 REport HTML"},{"id":345693,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1062/images/coverthb.png"}],"contact":"Director, Lower Mississippi-Gulf Water Science Center
U.S. Geological Survey
401 Hardin Road
Little Rock, AR 72211
http://ar.water.usgs.gov