Pennsylvania’s rapid unconventional oil and gas (UOG) development—from a single well in 2004 to more than 6700 wells in 2013—has dramatically increased UOG waste transport by heavy trucks. This study quantified the amount of UOG waste and the distance it traveled between wells and disposal facilities on each type of road in each county between July 2010 and December 2013. In addition, the study estimated the associated financial costs to each county’s road infrastructure over that period. We found that UOG wells produced a median wastewater volume of 1294 m3 and a median of 89,267 kg of solid waste. The median number of waste-transport truck trips per well was 122. UOG wells existed in 38 Pennsylvania counties, but we estimated trucks transporting well waste traveled through 132 counties, including counties in West Virginia, Ohio, and New York. Median travel distance varied by disposal type, from 106 km to centralized treatment facilities up to 237 km to injection wells. Local roads experienced the greatest amount of truck traffic and associated costs ($1.1–6.5 M) and interstates, the least ($0.3–1.6 M). Counties with oil and gas development experienced the most truck traffic and incurred the highest associated roadway costs. However, many counties outside the active development area also incurred roadway repair costs, highlighting the extension of UOG development’s spatial footprint beyond the active development area. An online data visualization tool is available here: www.nicholasinstitute.duke.edu/transportation-of-hydraulic-fracturing-waste.
","language":"English","publisher":"Academic Press","publisherLocation":"New York, NY","doi":"10.1016/j.jenvman.2016.06.048","usgsCitation":"Patterson, L.A., and Maloney, K.O., 2016, Transport of hydraulic fracturing waste from Pennsylvania wells: A county-level analysis of road use and associated road repair costs: Journal of Environmental Management, v. 181, p. 353-362, https://doi.org/10.1016/j.jenvman.2016.06.048.","productDescription":"10 p.","startPage":"353","endPage":"362","ipdsId":"IP-068698","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":331668,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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human-induced wetland reduction in China over the past three decades","interactions":[],"lastModifiedDate":"2016-12-08T09:30:34","indexId":"70178810","displayToPublicDate":"2016-12-08T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"Climate-driven increase of natural wetland methane emissions offset by human-induced wetland reduction in China over the past three decades","docAbstract":"Both anthropogenic activities and climate change can affect the biogeochemical processes of natural wetland methanogenesis. Quantifying possible impacts of changing climate and wetland area on wetland methane (CH4) emissions in China is important for improving our knowledge on CH4 budgets locally and globally. However, their respective and combined effects are uncertain. We incorporated changes in wetland area derived from remote sensing into a dynamic CH4 model to quantify the human and climate change induced contributions to natural wetland CH4 emissions in China over the past three decades. Here we found that human-induced wetland loss contributed 34.3% to the CH4 emissions reduction (0.92 TgCH4), and climate change contributed 20.4% to the CH4 emissions increase (0.31 TgCH4), suggesting that decreasing CH4 emissions due to human-induced wetland reductions has offset the increasing climate-driven CH4 emissions. With climate change only, temperature was a dominant controlling factor for wetland CH4 emissions in the northeast (high latitude) and Qinghai-Tibet Plateau (high altitude) regions, whereas precipitation had a considerable influence in relative arid north China. The inevitable uncertainties caused by the asynchronous for different regions or periods due to inter-annual or seasonal variations among remote sensing images should be considered in the wetland CH4 emissions estimation.
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Jin-Sheng","contributorId":177302,"corporation":false,"usgs":false,"family":"He","given":"Jin-Sheng","email":"","affiliations":[],"preferred":false,"id":655241,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}} ,{"id":70178805,"text":"70178805 - 2016 - Climate variability and extremes, interacting with nitrogen storage, amplify eutrophication risk","interactions":[],"lastModifiedDate":"2016-12-08T09:08:11","indexId":"70178805","displayToPublicDate":"2016-12-08T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Climate variability and extremes, interacting with nitrogen storage, amplify eutrophication risk","docAbstract":"Despite 30 years of basin-wide nutrient-reduction efforts, severe hypoxia continues to be observed in the Chesapeake Bay. Here we demonstrate the critical influence of climate variability, interacting with accumulated nitrogen (N) over multidecades, on Susquehanna River dissolved nitrogen (DN) loads, known precursors of the hypoxia in the Bay. We used the process model LM3-TAN (Terrestrial and Aquatic Nitrogen), which is capable of capturing both seasonal and decadal-to-century changes in vegetation-soil-river N storage, and produced nine scenarios of DN-load distributions under different short-term scenarios of climate variability and extremes. We illustrate that after 1 to 3 yearlong dry spells, the likelihood of exceeding a threshold DN load (56 kt yr−1) increases by 40 to 65% due to flushing of N accumulated throughout the dry spells and altered microbial processes. Our analyses suggest that possible future increases in climate variability/extremes—specifically, high precipitation occurring after multiyear dry spells—could likely lead to high DN-load anomalies and hypoxia.
","language":"English","publisher":"American Geophysical Union","publisherLocation":"Washington, D.C.","doi":"10.1002/2016GL069254","usgsCitation":"Lee, M., Shevliakova, E., Malyshev, S., Milly, P., and Jaffe, P.R., 2016, Climate variability and extremes, interacting with nitrogen storage, amplify eutrophication risk: Geophysical Research Letters, v. 43, no. 14, p. 7520-7528, https://doi.org/10.1002/2016GL069254.","startPage":"7520","endPage":"7528","ipdsId":"IP-075092","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":470335,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2016gl069254","text":"Publisher Index Page"},{"id":331671,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Chesapeake Bay","volume":"43","issue":"14","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-07-16","publicationStatus":"PW","scienceBaseUri":"584a7f7ce4b07e29c706dd31","contributors":{"authors":[{"text":"Lee, Minjin","contributorId":177261,"corporation":false,"usgs":false,"family":"Lee","given":"Minjin","email":"","affiliations":[],"preferred":false,"id":655221,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shevliakova, Elena","contributorId":9596,"corporation":false,"usgs":true,"family":"Shevliakova","given":"Elena","affiliations":[],"preferred":false,"id":655222,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Malyshev, Sergey","contributorId":22175,"corporation":false,"usgs":true,"family":"Malyshev","given":"Sergey","affiliations":[],"preferred":false,"id":655223,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Milly, P. C. D.","contributorId":100489,"corporation":false,"usgs":true,"family":"Milly","given":"P. C. D.","affiliations":[],"preferred":false,"id":655224,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jaffe, Peter R.","contributorId":22503,"corporation":false,"usgs":true,"family":"Jaffe","given":"Peter","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":655225,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70178792,"text":"70178792 - 2016 - Exposure to the contraceptive progestin, gestodene, alters reproductive behavior, arrests egg deposition, and masculinizes development in the fathead minnow (Pimephales promelas)","interactions":[],"lastModifiedDate":"2018-08-09T12:22:14","indexId":"70178792","displayToPublicDate":"2016-12-08T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Exposure to the contraceptive progestin, gestodene, alters reproductive behavior, arrests egg deposition, and masculinizes development in the fathead minnow (Pimephales promelas)","docAbstract":"Endogenous progestogens and pharmaceutical progestins enter the environment through wastewater treatment plant effluent and agricultural field runoff. Lab studies demonstrate strong, negative exposure effects of these chemicals on aquatic vertebrate reproduction. Behavior can be a sensitive, early indicator of exposure to environmental contaminants associated with altered reproduction yet is rarely examined in ecotoxicology studies. Gestodene is a human contraceptive progestin and a potent activator of fish androgen receptors. Our objective was to test the effects of gestodene on reproductive behavior and associated egg deposition in the fathead minnow. After only 1 day, males exposed to ng/L of gestodene were more aggressive and less interested in courtship and mating, and exposed females displayed less female courtship behavior. Interestingly, 25% of the gestodene tanks contained a female that drove the male out of the breeding tile and displayed male-typical courtship behaviors toward the other female. Gestodene decreased or arrested egg deposition with no observed gonadal histopathology. Together, these results suggest that effects on egg deposition are primarily due to altered reproductive behavior. The mechanisms by which gestodene disrupts behavior are unknown. Nonetheless, the rapid and profound alterations of the reproductive biology of gestodene-exposed fish suggest that wild populations could be similarly affected.
","language":"English","publisher":"American Chemical Society","publisherLocation":"Easton, PA","doi":"10.1021/acs.est.6b00799","usgsCitation":"Frankel, T.E., Meyer, M.T., Kolpin, D.W., Gillis, A.B., Alvarez, D., and Orlando, E.F., 2016, Exposure to the contraceptive progestin, gestodene, alters reproductive behavior, arrests egg deposition, and masculinizes development in the fathead minnow (Pimephales promelas): Environmental Science & Technology, v. 50, no. 11, p. 5991-5999, https://doi.org/10.1021/acs.est.6b00799.","productDescription":"9 p.","startPage":"5991","endPage":"5999","ipdsId":"IP-070808","costCenters":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":331670,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"50","issue":"11","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-19","publicationStatus":"PW","scienceBaseUri":"584a7f7de4b07e29c706dd37","chorus":{"doi":"10.1021/acs.est.6b00799","url":"http://dx.doi.org/10.1021/acs.est.6b00799","publisher":"American Chemical Society (ACS)","authors":"Frankel Tyler E., Meyer Michael T., Kolpin Dana W., Gillis Amanda B., Alvarez David A., Orlando Edward F.","journalName":"Environmental Science & Technology","publicationDate":"6/7/2016"},"contributors":{"authors":[{"text":"Frankel, Tyler E.","contributorId":177293,"corporation":false,"usgs":false,"family":"Frankel","given":"Tyler","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":655216,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Meyer, Michael T. 0000-0001-6006-7985 mmeyer@usgs.gov","orcid":"https://orcid.org/0000-0001-6006-7985","contributorId":866,"corporation":false,"usgs":true,"family":"Meyer","given":"Michael","email":"mmeyer@usgs.gov","middleInitial":"T.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":655217,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kolpin, Dana W. 0000-0002-3529-6505 dwkolpin@usgs.gov","orcid":"https://orcid.org/0000-0002-3529-6505","contributorId":1239,"corporation":false,"usgs":true,"family":"Kolpin","given":"Dana","email":"dwkolpin@usgs.gov","middleInitial":"W.","affiliations":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"preferred":true,"id":655143,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gillis, Amanda B.","contributorId":177294,"corporation":false,"usgs":false,"family":"Gillis","given":"Amanda","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":655218,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Alvarez, David A. dalvarez@usgs.gov","contributorId":139231,"corporation":false,"usgs":true,"family":"Alvarez","given":"David A.","email":"dalvarez@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":false,"id":655219,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Orlando, Edward F.","contributorId":177295,"corporation":false,"usgs":false,"family":"Orlando","given":"Edward","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":655220,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70178804,"text":"70178804 - 2016 - Global statistical maps of extreme-event magnetic observatory 1 min first differences in horizontal intensity","interactions":[],"lastModifiedDate":"2016-12-08T08:32:12","indexId":"70178804","displayToPublicDate":"2016-12-08T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Global statistical maps of extreme-event magnetic observatory 1 min first differences in horizontal intensity","docAbstract":"Analysis is made of the long-term statistics of three different measures of ground level, storm time geomagnetic activity: instantaneous 1 min first differences in horizontal intensity ΔBh, the root-mean-square of 10 consecutive 1 min differences S, and the ramp change R over 10 min. Geomagnetic latitude maps of the cumulative exceedances of these three quantities are constructed, giving the threshold (nT/min) for which activity within a 24 h period can be expected to occur once per year, decade, and century. Specifically, at geomagnetic 55°, we estimate once-per-century ΔBh, S, and R exceedances and a site-to-site, proportional, 1 standard deviation range [1 σ, lower and upper] to be, respectively, 1000, [690, 1450]; 500, [350, 720]; and 200, [140, 280] nT/min. At 40°, we estimate once-per-century ΔBh, S, and R exceedances and 1 σ values to be 200, [140, 290]; 100, [70, 140]; and 40, [30, 60] nT/min.
","language":"English","publisher":"American Geophysical Union","publisherLocation":"Washington, D.C.","doi":"10.1002/2016GL068664","usgsCitation":"Love, J.J., Coisson, P., and Pulkkinen, A., 2016, Global statistical maps of extreme-event magnetic observatory 1 min first differences in horizontal intensity: Geophysical Research Letters, v. 43, no. 9, p. 4126-4135, https://doi.org/10.1002/2016GL068664.","productDescription":"10 p.","startPage":"4126","endPage":"4135","ipdsId":"IP-074685","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":470333,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2016gl068664","text":"Publisher Index Page"},{"id":331669,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"43","issue":"9","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-10","publicationStatus":"PW","scienceBaseUri":"584a7f7ce4b07e29c706dd33","contributors":{"authors":[{"text":"Love, Jeffrey J. 0000-0002-3324-0348 jlove@usgs.gov","orcid":"https://orcid.org/0000-0002-3324-0348","contributorId":760,"corporation":false,"usgs":true,"family":"Love","given":"Jeffrey","email":"jlove@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":655157,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coisson, Pierdavide","contributorId":177260,"corporation":false,"usgs":false,"family":"Coisson","given":"Pierdavide","email":"","affiliations":[],"preferred":false,"id":655158,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pulkkinen, Antti","contributorId":145703,"corporation":false,"usgs":false,"family":"Pulkkinen","given":"Antti","affiliations":[{"id":7049,"text":"NASA Goddard Space Flight Center","active":true,"usgs":false}],"preferred":false,"id":655159,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70178057,"text":"ofr20161184 - 2016 - Estimated historical distribution of grassland communities of the Southern Great Plains","interactions":[],"lastModifiedDate":"2018-08-10T16:15:04","indexId":"ofr20161184","displayToPublicDate":"2016-12-07T17:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-1184","title":"Estimated historical distribution of grassland communities of the Southern Great Plains","docAbstract":"The purpose of this project was to map the estimated distribution of grassland communities of the Southern Great Plains prior to Euro-American settlement. The Southern Great Plains Rapid Ecoregional Assessment (REA), under the direction of the Bureau of Land Management and the Great Plains Landscape Conservation Cooperative, includes four ecoregions: the High Plains, Central Great Plains, Southwestern Tablelands, and the Nebraska Sand Hills. The REA advisors and stakeholders determined that the mapping accuracy of available national land-cover maps was insufficient in many areas to adequately address management questions for the REA. Based on the recommendation of the REA stakeholders, we estimated the potential historical distribution of 10 grassland communities within the Southern Great Plains project area using data on soils, climate, and vegetation from the Natural Resources Conservation Service (NRCS) including the Soil Survey Geographic Database (SSURGO) and Ecological Site Information System (ESIS). The dominant grassland communities of the Southern Great Plains addressed as conservation elements for the REA area are shortgrass, mixed-grass, and sand prairies. We also mapped tall-grass, mid-grass, northwest mixed-grass, and cool season bunchgrass prairies, saline and foothill grasslands, and semi-desert grassland and steppe. Grassland communities were primarily defined using the annual productivity of dominant species in the ESIS data. The historical grassland community classification was linked to the SSURGO data using vegetation types associated with the predominant component of mapped soil units as defined in the ESIS data. We augmented NRCS data with Landscape Fire and Resource Management Planning Tools (LANDFIRE) Biophysical Settings classifications 1) where NRCS data were unavailable and 2) where fifth-level watersheds intersected the boundary of the High Plains ecoregion in Wyoming. Spatial data representing the estimated historical distribution of grassland communities of the Southern Great Plains are provided as a 30 x 30-meter gridded surface (raster dataset). This information will help to address the priority management questions for grassland communities for the Southern Great Plains REA and can be used to inform other regional-level land management decisions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161184","collaboration":"Prepared in cooperation with the Bureau of Land Management and the Great Plains Landscape Conservation Cooperative","usgsCitation":"Reese, G.C., Manier, D.J., Carr, N.B., Callan, Ramana, Leinwand, I.I.F., Assal, T.J., Burris, Lucy, and Ignizio, D.A., 2016, Estimated historical distribution of grassland communities of the Southern Great Plains: U.S. Geological Survey Open-File Report 2016–1184, 13 p., https://doi.org/10.3133/ofr20161184. ","productDescription":"Report: v, 13 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-077037","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":37226,"text":"Core Science Analytics, Synthesis, and Libraries","active":true,"usgs":true}],"links":[{"id":438494,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F71Z42J3","text":"USGS data release","linkHelpText":"Estimated distribution of historical grassland communities of the Southern Great Plains"},{"id":331479,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F71Z42J3","text":"Estimated historical distribution of grassland communities of the Southern Great Plains","size":"228.75 MB","linkFileType":{"id":6,"text":"zip"},"description":"OFR 2016-1184 Data Release"},{"id":331184,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1184/coverthb.jpg"},{"id":331185,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1184/ofr20161184.pdf","text":"Report","size":"3.56 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1184"}],"country":"United States","otherGeospatial":"Southern Great Plains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109,\n 30\n ],\n [\n -109,\n 43.5\n ],\n [\n -94,\n 43.5\n ],\n [\n -94,\n 30\n ],\n [\n -109,\n 30\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Center Director, USGS Fort Collins Science Center
2150 Centre Ave., Bldg. C
Fort Collins, CO 80526-8118
The U.S. Geological Survey collects groundwater data and conducts studies to monitor hydrologic conditions, better define groundwater resources, and address problems related to water supply, water use, and water quality. In Georgia, water levels were monitored continuously at 181 wells during calendar year 2012, 185 wells during calendar year 2013, and at 171 wells during calendar year 2014. Because of missing data or short periods of record (less than 3 years) for several of these wells, a total of 164 wells are discussed in this report. These wells include 17 in the surficial aquifer system, 18 in the Brunswick aquifer system and equivalent sediments, 68 in the Upper Floridan aquifer, 15 in the Lower Floridan aquifer and underlying units, 10 in the Claiborne aquifer, 1 in the Gordon aquifer, 11 in the Clayton aquifer, 16 in the Cretaceous aquifer system, 2 in Paleozoic-rock aquifers, and 6 in crystalline-rock aquifers. Data from the well network indicate that water levels generally rose during the 2012 through 2014 calendar-year period, with water levels rising in 151 wells, declining in 12, and remained about the same in 1. Water levels declined over the long-term period of record at 94 wells, increased at 60 wells, and remained relatively constant at 10 wells.
In addition to continuous water-level data, periodic water-level measurements were collected and used to construct potentiometric-surface maps for the Upper Floridan aquifer in the following areas in Georgia: the Brunswick-Glynn County area during August 2012 and October 2014 and in the Albany-Dougherty County area during November 2012 and November 2014. Periodic water-level measurements were also collected and used to construct potentiometric surface maps for the Cretaceous aquifer system in the Augusta-Richmond County area during August 2012 and July 2014. In general, water levels in these areas were higher during 2014 than during 2012; however, the configuration of the potetiometric surface in each of the areas showed little change.
In the Brunswick area, maps showing chloride concentration of water in the Upper Floridan aquifer (constructed using data collected from 25 wells during August 2012 and from 32 wells during October 2014) indicate that chloride concentrations remained above the U.S. Environmental Protection Agency's secondary drinking-water standard in an approximately 2-square-mile area. During calendar years 2012 through 2014, chloride concentrations generally increased in over 90 percent of the wells sampled with a maximum increase of 410 milligrams per liter in a well located in the north-central part of the Brunswick area.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165161","usgsCitation":"Peck, M.F., and Painter, J.A., 2016, Groundwater conditions in Georgia, 2012–14: U.S. Geological Survey Scientific Investigations Report 2016–5161, 55 p., https://doi.org/10.3133/sir20165161. 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\"}}]}","contact":"Director, South Atlantic Water Science Center
U.S. Geological Survey
720 Gracern Road
Columbia, SC 29210
http://www.usgs.gov/water/southatlantic/
Soil bulk density (BD), soil organic matter (SOM) content, and a conversion factor between SOM and soil organic carbon (SOC) are often used in estimating SOC sequestration and storage. Spatial variability in BD, SOM, and the SOM–SOC conversion factor affects the ability to accurately estimate SOC sequestration, storage, and the benefits (e.g., land building area and vertical accretion) associated with wetland restoration efforts, such as marsh creation and sediment diversions. There are, however, only a few studies that have examined large-scale spatial variability in BD, SOM, and SOM–SOC conversion factors in coastal wetlands. In this study, soil cores, distributed across the entire coastal Louisiana (approximately 14,667 km2) were used to examine the regional-scale spatial variability in BD, SOM, and the SOM–SOC conversion factor. Soil cores for BD and SOM analyses were collected during 2006–09 from 331 spatially well-distributed sites in the Coastwide Reference Monitoring System network. Soil cores for the SOM–SOC conversion factor analysis were collected from 15 sites across coastal Louisiana during 2006–07. Results of a split-plot analysis of variance with incomplete block design indicated that BD and SOM varied significantly at a landscape level, defined by both hydrologic basins and vegetation types. Vertically, BD and SOM varied significantly among different vegetation types. The SOM–SOC conversion factor also varied significantly at the landscape level. This study provides critical information for the assessment of the role of coastal wetlands in large regional carbon budgets and the estimation of carbon credits from coastal restoration.
","language":"English","publisher":"Coastal Education and Research Foundation","doi":"10.2112/JCOASTRES-D-16-00014.1","usgsCitation":"Wang, H., Piazza, S.C., Sharp, L., Stagg, C.L., Couvillion, B.R., Steyer, G.D., and McGinnis, T., 2016, Determining the spatial variability of wetland soil bulk density, organic matter, and the conversion factor between organic matter and organic carbon across coastal Louisiana, U.S.A.: Journal of Coastal Research, v. 33, no. 3, p. 507-517, https://doi.org/10.2112/JCOASTRES-D-16-00014.1.","productDescription":"11 p.","startPage":"507","endPage":"517","ipdsId":"IP-069286","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":331619,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","volume":"33","issue":"3","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58492df0e4b06d80b7b09398","contributors":{"authors":[{"text":"Wang, Hongqing 0000-0002-2977-7732 wangh@usgs.gov","orcid":"https://orcid.org/0000-0002-2977-7732","contributorId":140432,"corporation":false,"usgs":true,"family":"Wang","given":"Hongqing","email":"wangh@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":655067,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Piazza, Sarai C. 0000-0001-6962-9008 piazzas@usgs.gov","orcid":"https://orcid.org/0000-0001-6962-9008","contributorId":466,"corporation":false,"usgs":true,"family":"Piazza","given":"Sarai","email":"piazzas@usgs.gov","middleInitial":"C.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":false,"id":655068,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sharp, Leigh A.","contributorId":43879,"corporation":false,"usgs":true,"family":"Sharp","given":"Leigh A.","affiliations":[],"preferred":false,"id":655069,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stagg, Camille L. 0000-0002-1125-7253 staggc@usgs.gov","orcid":"https://orcid.org/0000-0002-1125-7253","contributorId":4111,"corporation":false,"usgs":true,"family":"Stagg","given":"Camille","email":"staggc@usgs.gov","middleInitial":"L.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":655070,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Couvillion, Brady R. 0000-0001-5323-1687 couvillionb@usgs.gov","orcid":"https://orcid.org/0000-0001-5323-1687","contributorId":3829,"corporation":false,"usgs":true,"family":"Couvillion","given":"Brady","email":"couvillionb@usgs.gov","middleInitial":"R.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":false,"id":655071,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Steyer, Gregory D. 0000-0001-7231-0110 steyerg@usgs.gov","orcid":"https://orcid.org/0000-0001-7231-0110","contributorId":2856,"corporation":false,"usgs":true,"family":"Steyer","given":"Gregory","email":"steyerg@usgs.gov","middleInitial":"D.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":5062,"text":"Office of the Chief Scientist for Ecosystems","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":5064,"text":"Southeast Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":655072,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McGinnis, Thomas E.","contributorId":92959,"corporation":false,"usgs":true,"family":"McGinnis","given":"Thomas E.","affiliations":[],"preferred":false,"id":655073,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70178758,"text":"70178758 - 2016 - The Carolina Sandhills: Quaternary eolian sand sheets and dunes along the updip margin of the Atlantic Coastal Plain province, southeastern United States","interactions":[],"lastModifiedDate":"2016-12-07T11:15:30","indexId":"70178758","displayToPublicDate":"2016-12-07T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3218,"text":"Quaternary Research","active":true,"publicationSubtype":{"id":10}},"title":"The Carolina Sandhills: Quaternary eolian sand sheets and dunes along the updip margin of the Atlantic Coastal Plain province, southeastern United States","docAbstract":"The Carolina Sandhills is a physiographic region of the Atlantic Coastal Plain province in the southeastern United States. In Chesterfield County (South Carolina), the surficial sand of this region is the Pinehurst Formation, which is interpreted as eolian sand derived from the underlying Cretaceous Middendorf Formation. This sand has yielded three clusters of optically stimulated luminescence ages: (1) 75 to 37 thousand years ago (ka), coincident with growth of the Laurentide Ice Sheet; (2) 28 to 18 ka, coincident with the last glacial maximum (LGM); and (3) 12 to 6 ka, mostly coincident with the Younger Dryas through final collapse of the Laurentide Ice Sheet. Relict dune morphologies are consistent with winds from the west or northwest, coincident with modern and inferred LGM January wind directions. Sand sheets are more common than dunes because of effects of coarse grain size (mean range: 0.35–0.59 mm) and vegetation. The coarse grain size would have required LGM wind velocities of at least 4–6 m/sec, accounting for effects of colder air temperatures on eolian sand transport. The eolian interpretation of the Carolina Sandhills is consistent with other evidence for eolian activity in the southeastern United States during the last glaciation.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.yqres.2016.08.007","usgsCitation":"Swezey, C.S., Fitzwater, B.A., Whittecar, G.R., Mahan, S.A., Garrity, C.P., Aleman-Gonzalez, W.B., and Dobbs, K.M., 2016, The Carolina Sandhills: Quaternary eolian sand sheets and dunes along the updip margin of the Atlantic Coastal Plain province, southeastern United States: Quaternary Research, v. 86, no. 3, p. 271-286, https://doi.org/10.1016/j.yqres.2016.08.007.","productDescription":"16 p.","startPage":"271","endPage":"286","ipdsId":"IP-072092","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":331620,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"86","issue":"3","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-01-20","publicationStatus":"PW","scienceBaseUri":"58492df1e4b06d80b7b0939c","contributors":{"authors":[{"text":"Swezey, Christopher S. 0000-0003-4019-9264 cswezey@usgs.gov","orcid":"https://orcid.org/0000-0003-4019-9264","contributorId":173033,"corporation":false,"usgs":true,"family":"Swezey","given":"Christopher","email":"cswezey@usgs.gov","middleInitial":"S.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":655055,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fitzwater, Bradley A.","contributorId":177211,"corporation":false,"usgs":false,"family":"Fitzwater","given":"Bradley","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":655056,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Whittecar, G. Richard","contributorId":177212,"corporation":false,"usgs":false,"family":"Whittecar","given":"G.","email":"","middleInitial":"Richard","affiliations":[],"preferred":false,"id":655057,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mahan, Shannon A. 0000-0001-5214-7774 smahan@usgs.gov","orcid":"https://orcid.org/0000-0001-5214-7774","contributorId":147159,"corporation":false,"usgs":true,"family":"Mahan","given":"Shannon","email":"smahan@usgs.gov","middleInitial":"A.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":655058,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Garrity, Christopher P. 0000-0002-5565-1818 cgarrity@usgs.gov","orcid":"https://orcid.org/0000-0002-5565-1818","contributorId":644,"corporation":false,"usgs":true,"family":"Garrity","given":"Christopher","email":"cgarrity@usgs.gov","middleInitial":"P.","affiliations":[{"id":5061,"text":"National Cooperative Geologic Mapping and Landslide Hazards","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":655059,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Aleman-Gonzalez, Wilma B. 0000-0003-3156-0126 waleman@usgs.gov","orcid":"https://orcid.org/0000-0003-3156-0126","contributorId":2530,"corporation":false,"usgs":true,"family":"Aleman-Gonzalez","given":"Wilma","email":"waleman@usgs.gov","middleInitial":"B.","affiliations":[{"id":501,"text":"Office of Science Quality and Integrity","active":true,"usgs":true}],"preferred":true,"id":655060,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dobbs, Kerby M.","contributorId":177220,"corporation":false,"usgs":false,"family":"Dobbs","given":"Kerby","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":655061,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70178727,"text":"70178727 - 2016 - Animal movement in the absence of predation: environmental drivers of movement strategies in a partial migration system","interactions":[],"lastModifiedDate":"2017-07-03T09:36:15","indexId":"70178727","displayToPublicDate":"2016-12-07T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2939,"text":"Oikos","active":true,"publicationSubtype":{"id":10}},"title":"Animal movement in the absence of predation: environmental drivers of movement strategies in a partial migration system","docAbstract":"Animal movement strategies including migration, dispersal, nomadism, and residency are shaped by broad-scale spatial-temporal structuring of the environment, including factors such as the degrees of spatial variation, seasonality and inter-annual predictability. Animal movement strategies, in turn, interact with the characteristics of individuals and the local distribution of resources to determine local patterns of resource selection with complex and poorly understood implications for animal fitness. Here we present a multi-scale investigation of animal movement strategies and resource selection. We consider the degree to which spatial variation, seasonality, and inter-annual predictability in resources drive migration patterns among different taxa and how movement strategies in turn shape local resource selection patterns. We focus on adult Galapagos giant tortoises Chelonoidis spp. as a model system since they display many movement strategies and evolved in the absence of predators of adults. Specifically, our analysis is based on 63 individuals among four taxa tracked on three islands over six years and almost 106 tortoise re-locations. Tortoises displayed a continuum of movement strategies from migration to sedentarism that were linked to the spatio-temporal scale and predictability of resource distributions. Movement strategies shaped patterns of resource selection. Specifically, migratory individuals displayed stronger selection toward areas where resources were more predictable among years than did non-migratory individuals, which indicates a selective advantage for migrants in seasonally structured, more predictable environments. Our analytical framework combines large-scale predictions for movement strategies, based on environmental structuring, with finer-scale analysis of space-use. Integrating different organizational levels of analysis provides a deeper understanding of the eco-evolutionary dynamics at play in the emergence and maintenance of migration and the critical role of resource predictability. Our results highlight that assessing the potential benefits of differential behavioral responses first requires an understanding of the interactions among movement strategies, resource selection and individual characteristics.
","language":"English","publisher":"Wiley","doi":"10.1111/oik.03928","usgsCitation":"Bastille-Rousseau, G., Gibbs, J.P., Yackulic, C.B., Frair, J.L., Cabrera, F., and Rousseau, L., 2016, Animal movement in the absence of predation: environmental drivers of movement strategies in a partial migration system: Oikos, v. 126, no. 7, p. 1004-1019, https://doi.org/10.1111/oik.03928.","productDescription":"16 p.","startPage":"1004","endPage":"1019","ipdsId":"IP-077124","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":470339,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://nbn-resolving.de/urn:nbn:de:bsz:352-0-397949","text":"External Repository"},{"id":331621,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"126","issue":"7","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-01-23","publicationStatus":"PW","scienceBaseUri":"58492df1e4b06d80b7b0939e","contributors":{"authors":[{"text":"Bastille-Rousseau, Guillaume","contributorId":169986,"corporation":false,"usgs":false,"family":"Bastille-Rousseau","given":"Guillaume","affiliations":[{"id":25645,"text":"State Uni. of New York","active":true,"usgs":false}],"preferred":false,"id":655080,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gibbs, James P.","contributorId":102418,"corporation":false,"usgs":false,"family":"Gibbs","given":"James","email":"","middleInitial":"P.","affiliations":[{"id":12623,"text":"State University of New York College of Environmental Science and Forestry","active":true,"usgs":false}],"preferred":false,"id":655081,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yackulic, Charles B. 0000-0001-9661-0724 cyackulic@usgs.gov","orcid":"https://orcid.org/0000-0001-9661-0724","contributorId":4662,"corporation":false,"usgs":true,"family":"Yackulic","given":"Charles","email":"cyackulic@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":655082,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Frair, Jacqueline L.","contributorId":140184,"corporation":false,"usgs":false,"family":"Frair","given":"Jacqueline","email":"","middleInitial":"L.","affiliations":[{"id":13404,"text":"SUNY College of Environmental Science & Forestry","active":true,"usgs":false}],"preferred":false,"id":655083,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cabrera, Fredy","contributorId":139278,"corporation":false,"usgs":false,"family":"Cabrera","given":"Fredy","affiliations":[{"id":12718,"text":"Charles Darwin Foundation","active":true,"usgs":false}],"preferred":false,"id":655084,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rousseau, Louis-Philippe","contributorId":177206,"corporation":false,"usgs":false,"family":"Rousseau","given":"Louis-Philippe","email":"","affiliations":[],"preferred":false,"id":655085,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70192017,"text":"70192017 - 2016 - Hydrogeology of Virginia","interactions":[],"lastModifiedDate":"2018-02-12T13:13:22","indexId":"70192017","displayToPublicDate":"2016-12-07T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"seriesTitle":{"id":5623,"text":"Virginia Museum of Natural History Special Publication","active":true,"publicationSubtype":{"id":24}},"title":"Hydrogeology of Virginia","docAbstract":"The hydrogeology of Virginia documented herein is in two parts. Part 1 consists of an overview and description of the hydrogeology within each regional aquifer system in the Commonwealth. Part 2 includes discussions of hydrogeologic research topics of current relevance including: 1. the Chesapeake Bay impact structure, 2. subsidence/compaction in the Coastal Plain, 3. groundwater age and aquifer susceptibility, 4. the occurrence of groundwater at depth in fractured-rock and karst terrains, and 5. hydrologic response of wells to earthquakes around the world.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"The geology of Virginia (Virginia Museum of Natural History Special Publication 18)","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"The Virginia Museum of Natural History","publisherLocation":"Martinsville, VA","isbn":"1-884549-40-3","usgsCitation":"Nelms, D.L., Harlow, G., and Bruce, T.S., 2016, Hydrogeology of Virginia, chap. of The geology of Virginia (Virginia Museum of Natural History Special Publication 18): Virginia Museum of Natural History Special Publication, p. 315-340.","productDescription":"26 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\"}}]}","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee92ee4b0da30c1bfc530","contributors":{"editors":[{"text":"Bailey, Christopher M.","contributorId":70503,"corporation":false,"usgs":true,"family":"Bailey","given":"Christopher","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":728228,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Sherwood, W. Cullen","contributorId":12588,"corporation":false,"usgs":false,"family":"Sherwood","given":"W.","email":"","middleInitial":"Cullen","affiliations":[],"preferred":false,"id":728229,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Eaton, L. Scott lse5a@usgs.gov","contributorId":67582,"corporation":false,"usgs":true,"family":"Eaton","given":"L.","email":"lse5a@usgs.gov","middleInitial":"Scott","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":false,"id":728230,"contributorType":{"id":2,"text":"Editors"},"rank":3},{"text":"Powars, David S. 0000-0002-6787-8964 dspowars@usgs.gov","orcid":"https://orcid.org/0000-0002-6787-8964","contributorId":1181,"corporation":false,"usgs":true,"family":"Powars","given":"David","email":"dspowars@usgs.gov","middleInitial":"S.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":728231,"contributorType":{"id":2,"text":"Editors"},"rank":4}],"authors":[{"text":"Nelms, David L. 0000-0001-5747-642X dlnelms@usgs.gov","orcid":"https://orcid.org/0000-0001-5747-642X","contributorId":1892,"corporation":false,"usgs":true,"family":"Nelms","given":"David","email":"dlnelms@usgs.gov","middleInitial":"L.","affiliations":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true},{"id":37759,"text":"VA/WV Water Science Center","active":true,"usgs":true}],"preferred":true,"id":713844,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Harlow, George 0000-0002-7538-6812 geharlow@usgs.gov","orcid":"https://orcid.org/0000-0002-7538-6812","contributorId":197587,"corporation":false,"usgs":true,"family":"Harlow","given":"George","email":"geharlow@usgs.gov","affiliations":[],"preferred":true,"id":713845,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bruce, T. Scott","contributorId":197588,"corporation":false,"usgs":false,"family":"Bruce","given":"T.","email":"","middleInitial":"Scott","affiliations":[],"preferred":false,"id":713846,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70187103,"text":"70187103 - 2016 - Identification of Marbon in the Indiana Harbor and Ship Canal","interactions":[],"lastModifiedDate":"2017-04-21T16:20:59","indexId":"70187103","displayToPublicDate":"2016-12-06T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Identification of Marbon in the Indiana Harbor and Ship Canal","docAbstract":"Marbon is isomeric with Dechlorane Plus (DP). Both are produced by the Diels−\nAlder condensation of hexachlorocyclopentadiene with cyclic dienes, and both have elemental\ncompositions of C18H12Cl12. Dechlorane Plus is commonly found in the environment throughout\nthe world, but Marbon has, so far, only been detected at low levels in one sediment core collected\nnear the mouth of the Niagara River in Lake Ontario. Here we report on the concentrations of\nMarbon and anti-DP in 59 water samples from five Lake Michigan tributaries [the Grand,\nKalamazoo, St. Joseph, and Lower Fox Rivers, and the Indiana Harbor and Ship Canal (IHSC)],\n10 surface sediment samples from the IHSC, and 2 surface sediment samples from the Chicago\nSanitary and Ship Canal. Three Marbon diastereomers were detected in the water and sediment\nsamples from the IHSC, which is far from the location of its previous detection in Lake Ontario.\nThe sum of the concentrations of the three Marbons was greater in the water from the IHSC (N =\n11, median =150 pg/L) compared to those in water from the other four tributaries (N = 11−13,\nmedians =0.9−2.0 pg/L). Marbon concentrations in sediment samples from the IHSC were up to\n450 ng/g dry weight. Anti-DP was also measured for comparison. Its concentrations were not\nsignificantly different among the water samples, but its sediment concentrations in the IHSC were significantly correlated with\nthose of Marbon. The source of Marbon contamination in the IHSC is not clear.","language":"English","publisher":"American Chemical Society","publisherLocation":"Washington, D.C.","doi":"10.1021/acs.est.6b04646","usgsCitation":"Guo, J., Venier, M., Romanak, K., Westenbroek, S.M., and Hites, R.A., 2016, Identification of Marbon in the Indiana Harbor and Ship Canal: Environmental Science & Technology, v. 50, no. 24, p. 13232-13238, https://doi.org/10.1021/acs.est.6b04646.","productDescription":"7 p.","startPage":"13232","endPage":"13238","ipdsId":"IP-081272","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":340101,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Indiana","otherGeospatial":"Indiana Harbor, Ship Canal","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.51245498657227,\n 41.62853140372287\n ],\n [\n -87.39572525024414,\n 41.62853140372287\n ],\n [\n -87.39572525024414,\n 41.69496238228255\n ],\n [\n -87.51245498657227,\n 41.69496238228255\n ],\n [\n -87.51245498657227,\n 41.62853140372287\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"50","issue":"24","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2016-12-06","publicationStatus":"PW","scienceBaseUri":"58fb1a4ce4b0c3010a8087b7","contributors":{"authors":[{"text":"Guo, Jiehong","contributorId":191232,"corporation":false,"usgs":false,"family":"Guo","given":"Jiehong","email":"","affiliations":[],"preferred":false,"id":692430,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Venier, Marta","contributorId":191233,"corporation":false,"usgs":false,"family":"Venier","given":"Marta","email":"","affiliations":[],"preferred":false,"id":692431,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Romanak, Kevin","contributorId":191234,"corporation":false,"usgs":false,"family":"Romanak","given":"Kevin","affiliations":[],"preferred":false,"id":692432,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Westenbroek, Stephen M. 0000-0002-6284-8643 smwesten@usgs.gov","orcid":"https://orcid.org/0000-0002-6284-8643","contributorId":2210,"corporation":false,"usgs":true,"family":"Westenbroek","given":"Stephen","email":"smwesten@usgs.gov","middleInitial":"M.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":692429,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hites, Ronald A.","contributorId":191235,"corporation":false,"usgs":false,"family":"Hites","given":"Ronald","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":692433,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70178699,"text":"70178699 - 2016 - Potential trophic cascades triggered by the barred owl range expansion","interactions":[],"lastModifiedDate":"2017-11-22T17:17:16","indexId":"70178699","displayToPublicDate":"2016-12-06T00:00:00","publicationYear":"2016","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":"Potential trophic cascades triggered by the barred owl range expansion","docAbstract":"Recently, the barred owl (Strix varia) has expanded its range into the Pacific Northwest of the United States resulting in pronounced effects on the demography and behavior of the northern spotted owl (S. occidentalis caurina). The range expansion has brought together historically allopatric species, creating the potential for significant changes in the avian predator community with possible cascading effects on food-web dynamics. The adverse effects of the barred owl on the behavior and demography of the northern spotted owl are well-documented, but little is known about the immediate and long-term effects changes in the predator community may have on native species composition and ecosystem processes. Based on northern spotted owl and barred owl selection for diet and habitat resources, there is a potential for trophic cascades within the region's predator and prey communities, differing responses by their shared and unique prey species, and possible direct and indirect effects on ecosystem processes. We explored the possible ecological consequences of the barred owl range expansion to wildlife communities of the Pacific Northwest based on the theoretical underpinnings of predator–prey relationships, interspecific competition, intraguild predation, and potential cascading trophic interactions. Negative effects on fitness of northern spotted owls because of interspecific competition with barred owls are strong selection forces that may contribute to the regional extinction of the northern spotted owl. In addition, we posit that shared prey species and those uniquely consumed by barred owls, along with other competing native predators, may experience changes in behavior, abundance, and distribution as a result of increased rates of predation by rapidly expanding populations of barred owls.
","language":"English","publisher":"Wiley","doi":"10.1002/wsb.714","usgsCitation":"Holm, S.R., Noon, B.R., Wiens, D., and Ripple, W.J., 2016, Potential trophic cascades triggered by the barred owl range expansion: Wildlife Society Bulletin, v. 40, no. 4, p. 615-624, https://doi.org/10.1002/wsb.714.","productDescription":"10 p.","startPage":"615","endPage":"624","ipdsId":"IP-054746","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":499972,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doaj.org/article/8a219f6d5443479cbbc0dc22c60efcd3","text":"External Repository"},{"id":331554,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"40","issue":"4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-11-27","publicationStatus":"PW","scienceBaseUri":"5847dc7ce4b06d80b7af6aa9","contributors":{"authors":[{"text":"Holm, Samantha R.","contributorId":177172,"corporation":false,"usgs":false,"family":"Holm","given":"Samantha","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":654963,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Noon, Barry R.","contributorId":119751,"corporation":false,"usgs":true,"family":"Noon","given":"Barry","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":654964,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wiens, David 0000-0002-2020-038X jwiens@usgs.gov","orcid":"https://orcid.org/0000-0002-2020-038X","contributorId":167538,"corporation":false,"usgs":true,"family":"Wiens","given":"David","email":"jwiens@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":654965,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ripple, William J.","contributorId":24271,"corporation":false,"usgs":true,"family":"Ripple","given":"William","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":654966,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70178720,"text":"70178720 - 2016 - Morphometric body condition indices of wild Florida manatees (Trichechus manatus latirostris)","interactions":[],"lastModifiedDate":"2016-12-07T09:35:32","indexId":"70178720","displayToPublicDate":"2016-12-06T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":869,"text":"Aquatic Mammals","active":true,"publicationSubtype":{"id":10}},"title":"Morphometric body condition indices of wild Florida manatees (Trichechus manatus latirostris)","docAbstract":"In many species, body weight (W) increases geometrically with body length (L), so W/L3 provides a body condition index (BCI) that can be used to evaluate nutritional status once a normal range has been established. No such index has been established for Florida manatees (Trichechus manatus latirostris). This study was designed to determine a normal range of BCIs of Florida manatees by comparing W in kg with straight total length (SL), curvilinear total length (CL), and umbilical girth (UG) in m for 146 wild manatees measured during winter health assessments at three Florida locations. Small calves to large adults of SL from 1.47 to 3.23 m and W from 77 to 751 kg were compared. BCIs were significantly greater in adult females than in adult males (p < 0.05). W scaled proportionally to L3 in females but not in males, which were slimmer than females. The logarithms of W and of each linear measurement were regressed to develop amended indices that allow for sex differences. The regression slope for log W against log SL was 2.915 in females and 2.578 in males; W/SL2.915 ranged from 18.9 to 29.6 (mean 23.2) in females and from 24.6 to 37.3 (mean 29.8) in males. Some BCIs were slightly (4%), but significantly (p ≤ 0.05), higher for females in Crystal River than in Tampa Bay or Indian River, but there was no evidence of geographic variation in condition among males. These normal ranges should help evaluate the nutritional status of both wild and rehabilitating captive manatees.
","language":"English","publisher":"Aquatic Mammals","doi":"10.1578/AM.42.4.2016.428","usgsCitation":"Harshaw, L.T., Larkin, I.V., Bonde, R.K., Deutsch, C., and Hill, R.C., 2016, Morphometric body condition indices of wild Florida manatees (Trichechus manatus latirostris): Aquatic Mammals, v. 42, no. 4, p. 428-439, https://doi.org/10.1578/AM.42.4.2016.428.","productDescription":"12 p.","startPage":"428","endPage":"439","ipdsId":"IP-068590","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":331509,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {\n \"stroke\": \"#555555\",\n \"stroke-width\": 2,\n \"stroke-opacity\": 1,\n \"fill\": \"#555555\",\n \"fill-opacity\": 0.5\n },\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.76805114746094,\n 28.47774513090883\n ],\n [\n -80.77629089355469,\n 28.506712182731704\n ],\n [\n -80.75569152832031,\n 28.506712182731704\n ],\n [\n -80.75569152832031,\n 28.47714156614553\n ],\n [\n -80.76805114746094,\n 28.47774513090883\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.430419921875,\n 27.786239014835164\n ],\n [\n -82.430419921875,\n 27.812964428734308\n ],\n [\n -82.40707397460938,\n 27.812964428734308\n ],\n [\n -82.40707397460938,\n 27.786239014835164\n ],\n [\n -82.430419921875,\n 27.786239014835164\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.60620117187499,\n 28.890674728586355\n ],\n [\n -82.60620117187499,\n 28.89578469901921\n ],\n [\n -82.59160995483398,\n 28.89578469901921\n ],\n [\n -82.59160995483398,\n 28.890674728586355\n ],\n [\n -82.60620117187499,\n 28.890674728586355\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"42","issue":"4","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2016-12-01","publicationStatus":"PW","scienceBaseUri":"5847dc76e4b06d80b7af6aa3","contributors":{"authors":[{"text":"Harshaw, Lauren T.","contributorId":177184,"corporation":false,"usgs":false,"family":"Harshaw","given":"Lauren","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":654917,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Larkin, Iskande V.","contributorId":177187,"corporation":false,"usgs":false,"family":"Larkin","given":"Iskande","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":654918,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bonde, Robert K. 0000-0001-9179-4376 rbonde@usgs.gov","orcid":"https://orcid.org/0000-0001-9179-4376","contributorId":2675,"corporation":false,"usgs":true,"family":"Bonde","given":"Robert","email":"rbonde@usgs.gov","middleInitial":"K.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":654919,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Deutsch, Charles J.","contributorId":64135,"corporation":false,"usgs":true,"family":"Deutsch","given":"Charles J.","affiliations":[],"preferred":false,"id":654920,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hill, Richard C.","contributorId":177188,"corporation":false,"usgs":false,"family":"Hill","given":"Richard","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":654921,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70178701,"text":"70178701 - 2016 - Byproduct metal requirements for U.S. wind and solar photovoltaic electricity generation up to the year 2040 under various Clean Power Plan scenarios","interactions":[],"lastModifiedDate":"2016-12-06T12:34:47","indexId":"70178701","displayToPublicDate":"2016-12-06T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":832,"text":"Applied Energy","active":true,"publicationSubtype":{"id":10}},"title":"Byproduct metal requirements for U.S. wind and solar photovoltaic electricity generation up to the year 2040 under various Clean Power Plan scenarios","docAbstract":"The United States has and will likely continue to obtain an increasing share of its electricity from solar photovoltaics (PV) and wind power, especially under the Clean Power Plan (CPP). The need for additional solar PV modules and wind turbines will, among other things, result in greater demand for a number of minor metals that are produced mainly or only as byproducts. In this analysis, the quantities of 11 byproduct metals (Ag, Cd, Te, In, Ga, Se, Ge, Nd, Pr, Dy, and Tb) required for wind turbines with rare-earth permanent magnets and four solar PV technologies are assessed through the year 2040. Three key uncertainties (electricity generation capacities, technology market shares, and material intensities) are varied to develop 42 scenarios for each byproduct metal. The results indicate that byproduct metal requirements vary significantly across technologies, scenarios, and over time. In certain scenarios, the requirements are projected to become a significant portion of current primary production. This is especially the case for Te, Ge, Dy, In, and Tb under the more aggressive scenarios of increasing market share and conservative material intensities. Te and Dy are, perhaps, of most concern given their substitution limitations. In certain years, the differences in byproduct metal requirements between the technology market share and material intensity scenarios are greater than those between the various CPP and No CPP scenarios. Cumulatively across years 2016–2040, the various CPP scenarios are estimated to require 15–43% more byproduct metals than the No CPP scenario depending on the specific byproduct metal and scenario. Increasing primary production via enhanced recovery rates of the byproduct metals during the beneficiation and enrichment operations, improving end-of-life recycling rates, and developing substitutes are important strategies that may help meet the increased demand for these byproduct metals.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.apenergy.2016.08.062","usgsCitation":"Nassar, N., Wilburn, D.R., and Goonan, T.G., 2016, Byproduct metal requirements for U.S. wind and solar photovoltaic electricity generation up to the year 2040 under various Clean Power Plan scenarios: Applied Energy, v. 183, p. 1209-1226, https://doi.org/10.1016/j.apenergy.2016.08.062.","productDescription":"18 p.","startPage":"1209","endPage":"1226","ipdsId":"IP-078635","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":331545,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"183","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5847dc7be4b06d80b7af6aa7","contributors":{"authors":[{"text":"Nassar, Nedal T. 0000-0001-8758-9732 nnassar@usgs.gov","orcid":"https://orcid.org/0000-0001-8758-9732","contributorId":177175,"corporation":false,"usgs":true,"family":"Nassar","given":"Nedal T.","email":"nnassar@usgs.gov","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":false,"id":654872,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wilburn, David R. 0000-0002-5371-7617 wilburn@usgs.gov","orcid":"https://orcid.org/0000-0002-5371-7617","contributorId":1755,"corporation":false,"usgs":true,"family":"Wilburn","given":"David","email":"wilburn@usgs.gov","middleInitial":"R.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":654873,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Goonan, Thomas G. goonan@usgs.gov","contributorId":2761,"corporation":false,"usgs":true,"family":"Goonan","given":"Thomas","email":"goonan@usgs.gov","middleInitial":"G.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":654874,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70175362,"text":"70175362 - 2016 - Survival estimates for reintroduced populations of the Chiricahua Leopard Frog (Lithobates chiricahuensis)","interactions":[],"lastModifiedDate":"2016-12-06T10:24:46","indexId":"70175362","displayToPublicDate":"2016-12-06T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1337,"text":"Copeia","active":true,"publicationSubtype":{"id":10}},"title":"Survival estimates for reintroduced populations of the Chiricahua Leopard Frog (Lithobates chiricahuensis)","docAbstract":"Global amphibian declines have been attributed to a number of factors including disease, invasive species, habitat degradation, and climate change. Reintroduction is one management action that is commonly used with the goal of recovering imperiled species. The success of reintroductions varies widely, and evaluating their efficacy requires estimates of population viability metrics, such as underlying vital rates and trends in abundance. Although rarely quantified, assessing vital rates for recovering populations provides a more mechanistic understanding of population growth than numerical trends in population occupancy or abundance. We used three years of capture-mark-recapture data from three breeding ponds and a Cormack-Jolly-Seber model to estimate annual apparent survival for reintroduced populations of the federally threatened Chiricahua Leopard Frog (Lithobates chiricahuensis) at the Buenos Aires National Wildlife Refuge (BANWR), in the Altar Valley, Arizona, USA. To place our results in context, we also compiled published survival estimates for other ranids. Average apparent survival of Chiricahua Leopard Frogs at BANWR was 0.27 (95% CI [0.07, 0.74]) and average individual capture probability was 0.02 (95% CI [0, 0.05]). Our apparent survival estimate for Chiricahua Leopard Frogs is lower than for most other ranids and is not consistent with recent research that showed metapopulation viability in the Altar Valley is high. We suggest that low apparent survival may be indicative of high emigration rates. We recommend that future research should estimate emigration rates so that actual, rather than apparent, survival can be quantified to improve population viability assessments of threatened species following reintroduction efforts.
","language":"English","publisher":"The American Society of Ichthyologists and Herpetologists","doi":"10.1643/CE-16-406","usgsCitation":"Howell, P., Hossack, B.R., Muths, E.L., Sigafus, B.H., and Chandler, R.B., 2016, Survival estimates for reintroduced populations of the Chiricahua Leopard Frog (Lithobates chiricahuensis): Copeia, v. 104, no. 4, p. 824-830, https://doi.org/10.1643/CE-16-406.","productDescription":"7 p.","startPage":"824","endPage":"830","ipdsId":"IP-072948","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":331507,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"104","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5847dc7ce4b06d80b7af6aab","contributors":{"authors":[{"text":"Howell, Paige E.","contributorId":173495,"corporation":false,"usgs":false,"family":"Howell","given":"Paige E.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":644889,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hossack, Blake R. 0000-0001-7456-9564 blake_hossack@usgs.gov","orcid":"https://orcid.org/0000-0001-7456-9564","contributorId":1177,"corporation":false,"usgs":true,"family":"Hossack","given":"Blake","email":"blake_hossack@usgs.gov","middleInitial":"R.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":644888,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Muths, Erin L. 0000-0002-5498-3132 muthse@usgs.gov","orcid":"https://orcid.org/0000-0002-5498-3132","contributorId":1260,"corporation":false,"usgs":true,"family":"Muths","given":"Erin","email":"muthse@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":644890,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sigafus, Brent H. 0000-0002-7422-8927 bsigafus@usgs.gov","orcid":"https://orcid.org/0000-0002-7422-8927","contributorId":4534,"corporation":false,"usgs":true,"family":"Sigafus","given":"Brent","email":"bsigafus@usgs.gov","middleInitial":"H.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":644891,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chandler, Richard B. rchandler@usgs.gov","contributorId":63524,"corporation":false,"usgs":true,"family":"Chandler","given":"Richard","email":"rchandler@usgs.gov","middleInitial":"B.","affiliations":[],"preferred":false,"id":644892,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70178141,"text":"gip169 - 2016 - USGS Colorado Water Science Center bookmark","interactions":[{"subject":{"id":70178141,"text":"gip169 - 2016 - USGS Colorado Water Science Center bookmark","indexId":"gip169","publicationYear":"2016","noYear":false,"title":"USGS Colorado Water Science Center bookmark"},"predicate":"SUPERSEDED_BY","object":{"id":70243480,"text":"gip223 - 2023 - USGS Colorado Water Science Center bookmark","indexId":"gip223","publicationYear":"2023","noYear":false,"title":"USGS Colorado Water Science Center bookmark"},"id":1}],"supersededBy":{"id":70243480,"text":"gip223 - 2023 - USGS Colorado Water Science Center bookmark","indexId":"gip223","publicationYear":"2023","noYear":false,"title":"USGS Colorado Water Science Center bookmark"},"lastModifiedDate":"2023-05-12T20:38:27.167896","indexId":"gip169","displayToPublicDate":"2016-12-05T17:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":315,"text":"General Information Product","code":"GIP","onlineIssn":"2332-354X","printIssn":"2332-3531","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"169","title":"USGS Colorado Water Science Center bookmark","docAbstract":"The U.S. Geological Survey Colorado Water Science Center conducts its water-resources activities primarily in Colorado in cooperation with more than 125 different entities. These activities include extensive data-collection efforts and studies of streamflow, water quality, and groundwater to address many specific issues of concern to Colorado water-management entities and citizens. The collected data are provided in the National Water Information System, and study results are documented in reports and information served on the Internet.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/gip169","usgsCitation":"U.S. Geological Survey, 2016, Colorado Water Science Center bookmark: U.S. Geological Survey General Information Product 169, https://doi.org/10.3133/gip169.","productDescription":"Bookmark","onlineOnly":"N","ipdsId":"IP-079427","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":331200,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/gip/0169/gip169.pdf","text":"Bookmark","size":"5.09 MB","linkFileType":{"id":1,"text":"pdf"},"description":"GIP 169"},{"id":331199,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/gip/0169/coverthb2_superseded.jpg"}],"contact":"Director, USGS Colorado Water Science Center
Box 25046, Mail Stop 415
Denver, CO 80225
The U.S. Geological Survey collected high-resolution seismic-reflection data in September 2009, on survey S-8-09-NC, offshore of northern California between Bolinas and Sea Ranch.
The survey area spans about 125 km of California’s coast and extends around Point Reyes. Data were collected aboard the U.S. Geological Survey R/V Parke Snavely. Cumulatively, ~1,150 km of seismic-reflection data were acquired using a SIG 2mille minisparker. Subbottom acoustic depth of penetration spanned tens to several hundred meters and varied by location and underlying sediments and rock types.
This report includes maps and a navigation file of the surveyed transects, utilizing Google Earth™ software, as well as digital data files showing images of each transect in SEG-Y and JPEG formats. The images of bedrock, sediment deposits, and tectonic structure provide geologic information that is essential to hazard assessment, regional sediment management, and coastal and marine spatial planning at Federal, State and local levels. This information is also valuable for future research on the geomorphic, sedimentary, tectonic, and climatic record of central California.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161058","usgsCitation":"Sliter, R.W., Johnson, S.Y., Chin, J.L., Allwardt, P., Beeson, J., and Triezenberg, P.J., 2016, High-resolution seismic-reflection data from offshore of northern California—Bolinas to Sea Ranch: U.S. Geological Survey Open-File Report 2016–1058, https://dx.doi.org/10.3133/ofr20161058.","productDescription":"HTML Document","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-079352","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":330668,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1058","text":"Report HTML","linkFileType":{"id":5,"text":"html"},"description":"OFR 2016-1058 HTML"},{"id":330667,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1058/images/coverthb.jpg"}],"country":"United States","state":"California","city":"Bolinas, Sea Ranch","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.75299072265624,\n 37.83798775896512\n ],\n [\n -123.0853271484375,\n 37.95502661288625\n ],\n [\n -123.10729980468749,\n 38.04160203158016\n ],\n [\n -123.101806640625,\n 38.23386541556985\n ],\n [\n -123.4808349609375,\n 38.528830289587674\n ],\n [\n -123.662109375,\n 38.74337300148123\n ],\n [\n -123.51104736328125,\n 38.83328935686689\n ],\n [\n -123.035888671875,\n 38.43207668538207\n ],\n [\n -122.63763427734375,\n 37.90736658145496\n ],\n [\n -122.75299072265624,\n 37.83798775896512\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Pacific Coastal and Marine Science Center
U.S. Geological Survey
Pacific Science Center
2885 Mission St.
Santa Cruz, CA 95060
http://walrus.wr.usgs.gov/
The U.S. Geological Survey, National Minerals Information Center, analyzes mineral and metal supply chains by identifying and describing major components of mineral and material flows from ore extraction, through intermediate forms, to a final product. This report focuses on an important component of the world’s supply chain: the amounts and global distribution of major consumer, producer, and exchange stocks of selected mineral commodities. In this report, the term “stock” is used instead of “inventory” and refers to accumulations of mined ore, intermediate products, and refined mineral-based commodities that are in a form that meets the agreed-upon specifications of a buyer or processor of intermediate products. These may include certain ores such as bauxite, concentrates, smelter products, and refined metals. Materials sometimes referred to as inventory for accounting purposes, such as ore contained in a deposit or in a leach pile, or materials that need to be further processed before they can be shipped to a consumer, are not considered. Stocks may be held (owned) by consumers, governments, investors, producers, and traders. They may serve as (1) a means to achieve economic, social, and strategic goals through government policies; (2) a secure source of supply to meet demand and to mitigate potential shortages in the supply chain; (3) a hedge to mitigate price volatility; and (4) vehicles for speculative investment.
The paucity and uneven reliability of data for stocks of ores and concentrates and for material held by producers, consumers, and merchants hinder the accurate estimating of the size and distribution of this portion of the supply chain for certain commodities. This paper reviews the more visible stocks held in commodity exchange warehouses distributed throughout the world.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165152","usgsCitation":"Wilburn, D.R., Bleiwas, D.I., and Karl, N.A., 2016, Global stocks of selected mineral-based commodities: U.S. Geological Survey Scientific Investigations Report 2016–5152, 13 p., https://doi.org/10.3133/sir20165152. ","productDescription":"Report: iv, 13 p.; Tables 2-10","numberOfPages":"22","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-074458","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":331397,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2016/5152/sir20165152_tables2-10.xlsx","text":"Tables 2 through 10","size":"94 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2016-5152 - Tables 2-10","linkHelpText":"- Global Stocks of Selected Mineral-Based Commodities"},{"id":331396,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5152/sir20165152.pdf","text":"Report ","size":"1.79 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5152"},{"id":331395,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5152/coverthb.jpg"}],"contact":"Director, National Minerals Information Center
U.S. Geological Survey
988 National Center
12201 Sunrise Valley Drive
Reston, VA 20192
Email: nmicrecordsmgt@usgs.gov
http://minerals.usgs.gov/minerals/
Suspended-sediment concentrations (SSCs) and turbidity were monitored within the Beaver Kill, Stony Clove Creek, and Warner Creek tributaries to the upper Esopus Creek in New York, the main source of water to the Ashokan Reservoir, from October 1, 2010, through September 30, 2014. The purpose of the monitoring was to determine the effects of suspended-sediment and turbidity reduction projects (STRPs) on SSC and turbidity in two of the three streams; no STRPs were constructed in the Beaver Kill watershed. During the study period, four STRPs were completed in the Stony Clove Creek and Warner Creek watersheds. Daily mean SSCs decreased significantly for a given streamflow after the STRPs were completed. The most substantial decreases in daily mean SSCs were measured at the highest streamflows. Background SSCs, as measured in water samples collected in upstream reference stream reaches, in all three streams in this study were less than 5 milligrams per liter during low and high streamflows. Longitudinal stream sampling identified stream reaches with failing hillslopes in contact with the stream channel as the primary sediment sources in the Beaver Kill and Stony Clove Creek watersheds.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165157","collaboration":"Prepared in cooperation with the Ashokan Watershed Stream Management Program","usgsCitation":"Siemion, Jason, McHale, M.R., and Davis, W.D., 2016, Suspended-sediment and turbidity responses to sediment and turbidity reduction projects in the Beaver Kill, Stony Clove Creek, and Warner Creek Watersheds, New York, 2010–14: U.S. Geological Survey Scientific Investigations Report 2016–5157, 28 p., https://doi.org/10.3133/sir20165157.","productDescription":"Report: viii, 28 p.; Appendix 1","numberOfPages":"40","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-075484","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":331382,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5157/sir20165157_appendix1.csv","text":"Appendix 1","size":"8.93 KB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2016-5157 - Appendix 1","linkHelpText":"- Suspended sediment concentrations and concurrent turbidity"},{"id":331381,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5157/sir20165157.pdf","text":"Report","size":"2.88 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5157"},{"id":331380,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5157/coverthb.jpg"},{"id":331383,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5157/sir20165157_appendix1.xlsx","text":"Appendix 1","size":"18.5 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2016-5157 - Appendix 1"}],"country":"United States","state":"New York","otherGeospatial":"Stony Clove Creek Watershed, Warner Creek Watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.4873046875,\n 42.049292638686836\n ],\n [\n -74.4873046875,\n 42.19088154556975\n ],\n [\n -74.15908813476562,\n 42.19088154556975\n ],\n [\n -74.15908813476562,\n 42.049292638686836\n ],\n [\n -74.4873046875,\n 42.049292638686836\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New York Water Science Center
U.S. Geological Survey
425 Jordan Road
Troy, NY 12180-8349
Information Requests:
(518) 285-5602
Or visit our Website at:
http://ny.water.usgs.gov
Methane is a powerful greenhouse gas, and atmospheric concentrations have risen 2.5 times since the beginning of the Industrial age. While much of this increase is attributed to anthropogenic sources, natural sources, which contribute between 35% and 50% of global methane emissions, are thought to have a role in the atmospheric methane increase, in part due to human influences. Methane emissions from many natural sources are sensitive to climate, and positive feedbacks from climate change and cultural eutrophication may promote increased emissions to the atmosphere. These natural sources include aquatic environments such as wetlands, freshwater lakes, streams and rivers, and estuarine, coastal, and marine systems. Furthermore, there are significant marine sediment stores of methane in the form of clathrates that are vulnerable to mobilization and release to the atmosphere from climate feedbacks, and subsurface thermogenic gas which in exceptional cases may be released following accidents and disasters (North Sea blowout and Deepwater Horizon Spill respectively). Understanding of natural sources, key processes, and controls on emission is continually evolving as new measurement and modeling capabilities develop, and different sources and processes are revealed. This special issue of Limnology and Oceanography gathers together diverse studies on methane production, consumption, and emissions from freshwater, estuarine, and marine systems, and provides a broad view of the current science on methane dynamics of aquatic ecosystems. Here, we provide a general overview of aquatic methane sources, their contribution to the global methane budget, and key uncertainties. We then briefly summarize the contributions to and highlights of this special issue.
","language":"English","publisher":"ASLO","doi":"10.1002/lno.10449","usgsCitation":"Hamdan, L.J., and Wickland, K.P., 2016, Methane emissions from oceans, coasts, and freshwater habitats: New perspectives and feedbacks on climate: Limnology and Oceanography, v. 61, no. S1, p. S3-S12, https://doi.org/10.1002/lno.10449.","productDescription":"10 p.","startPage":"S3","endPage":"S12","ipdsId":"IP-079689","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":462003,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/lno.10449","text":"Publisher Index Page"},{"id":331455,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"61","issue":"S1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-11-10","publicationStatus":"PW","scienceBaseUri":"58468ae8e4b04fc80e5236c1","contributors":{"authors":[{"text":"Hamdan, Leila J.","contributorId":177155,"corporation":false,"usgs":false,"family":"Hamdan","given":"Leila","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":654819,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wickland, Kimberly P. 0000-0002-6400-0590 kpwick@usgs.gov","orcid":"https://orcid.org/0000-0002-6400-0590","contributorId":1835,"corporation":false,"usgs":true,"family":"Wickland","given":"Kimberly","email":"kpwick@usgs.gov","middleInitial":"P.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true}],"preferred":true,"id":654818,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70178691,"text":"70178691 - 2016 - Towards simplification of hydrologic modeling: Identification of dominant processes","interactions":[],"lastModifiedDate":"2016-12-05T11:04:39","indexId":"70178691","displayToPublicDate":"2016-12-05T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1928,"text":"Hydrology and Earth System Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Towards simplification of hydrologic modeling: Identification of dominant processes","docAbstract":"The Precipitation–Runoff Modeling System (PRMS), a distributed-parameter hydrologic model, has been applied to the conterminous US (CONUS). Parameter sensitivity analysis was used to identify: (1) the sensitive input parameters and (2) particular model output variables that could be associated with the dominant hydrologic process(es). Sensitivity values of 35 PRMS calibration parameters were computed using the Fourier amplitude sensitivity test procedure on 110 000 independent hydrologically based spatial modeling units covering the CONUS and then summarized to process (snowmelt, surface runoff, infiltration, soil moisture, evapotranspiration, interflow, baseflow, and runoff) and model performance statistic (mean, coefficient of variation, and autoregressive lag 1). Identified parameters and processes provide insight into model performance at the location of each unit and allow the modeler to identify the most dominant process on the basis of which processes are associated with the most sensitive parameters.
The results of this study indicate that: (1) the choice of performance statistic and output variables has a strong influence on parameter sensitivity, (2) the apparent model complexity to the modeler can be reduced by focusing on those processes that are associated with sensitive parameters and disregarding those that are not, (3) different processes require different numbers of parameters for simulation, and (4) some sensitive parameters influence only one hydrologic process, while others may influence many
","language":"English","publisher":"Europen Geosciences Union","doi":"10.5194/hess-20-4655-2016","usgsCitation":"Markstrom, S.L., Hay, L.E., and Clark, M., 2016, Towards simplification of hydrologic modeling: Identification of dominant processes: Hydrology and Earth System Sciences, v. 20, p. 4655-4671, https://doi.org/10.5194/hess-20-4655-2016.","productDescription":"17 p.","startPage":"4655","endPage":"4671","ipdsId":"IP-076154","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":470341,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/hess-20-4655-2016","text":"Publisher Index Page"},{"id":331454,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"20","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-11-22","publicationStatus":"PW","scienceBaseUri":"58468ae8e4b04fc80e5236bf","contributors":{"authors":[{"text":"Markstrom, Steven L. 0000-0001-7630-9547 markstro@usgs.gov","orcid":"https://orcid.org/0000-0001-7630-9547","contributorId":146553,"corporation":false,"usgs":true,"family":"Markstrom","given":"Steven","email":"markstro@usgs.gov","middleInitial":"L.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":654822,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hay, Lauren E. 0000-0003-3763-4595 lhay@usgs.gov","orcid":"https://orcid.org/0000-0003-3763-4595","contributorId":1287,"corporation":false,"usgs":true,"family":"Hay","given":"Lauren","email":"lhay@usgs.gov","middleInitial":"E.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":654823,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Clark, Martyn P.","contributorId":21445,"corporation":false,"usgs":true,"family":"Clark","given":"Martyn P.","affiliations":[],"preferred":false,"id":654824,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70178694,"text":"70178694 - 2016 - Molecular-level evidence provided by ultrahigh resolution mass spectrometry for oil-derived doc in groundwater at Bemidji, Minnesota","interactions":[],"lastModifiedDate":"2018-08-06T13:07:03","indexId":"70178694","displayToPublicDate":"2016-12-05T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2331,"text":"Journal of Hazardous Materials","active":true,"publicationSubtype":{"id":10}},"title":"Molecular-level evidence provided by ultrahigh resolution mass spectrometry for oil-derived doc in groundwater at Bemidji, Minnesota","docAbstract":"Dissolved organic matter samples extracted from ground water at the USGS Bemidji oil spill site in Minnesota were investigated by ultrahigh resolution mass spectrometry. Principle component analysis (PCA) of the elemental composition assignments of the samples showed that the score plots for the contaminated sites were well separated from those for the uncontaminated sites. Additionally, spectra obtained from the same sampling site 7 and 19 years after the spill were grouped together in the score plot, strongly suggesting a steady state of contamination within the 12 year interval. The double bond equivalence (DBE) of Ox class compounds was broader for the samples from the contaminated sites, because of the complex nature of oil and the consequent formation of compounds with saturated and/or aromatic structures from the oxygenated products of oil. In addition, Ox class compounds with a relatively smaller number of x (x < 8; x = number of oxygen) and OxS1 class compounds were more abundant in the samples from the contaminated sites, because of the lower oxygen and higher sulfur contents of the oil compared to humic substances. The molecular-level signatures presented here can be a fundamental basis for in-depth analysis of oil contamination.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhazmat.2016.08.018","usgsCitation":"Islam, A., Ahmed, A., Hur, M., Thorn, K.A., and Kim, S., 2016, Molecular-level evidence provided by ultrahigh resolution mass spectrometry for oil-derived doc in groundwater at Bemidji, Minnesota: Journal of Hazardous Materials, v. 320, p. 123-132, https://doi.org/10.1016/j.jhazmat.2016.08.018.","productDescription":"10 p.","startPage":"123","endPage":"132","ipdsId":"IP-073491","costCenters":[{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":331452,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota","city":"Bemidji","volume":"320","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58468ae7e4b04fc80e5236bd","contributors":{"authors":[{"text":"Islam, Ananna","contributorId":177160,"corporation":false,"usgs":false,"family":"Islam","given":"Ananna","email":"","affiliations":[],"preferred":false,"id":654844,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ahmed, Arif","contributorId":177162,"corporation":false,"usgs":false,"family":"Ahmed","given":"Arif","email":"","affiliations":[],"preferred":false,"id":654845,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hur, Manhoi","contributorId":177161,"corporation":false,"usgs":false,"family":"Hur","given":"Manhoi","email":"","affiliations":[],"preferred":false,"id":654846,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thorn, Kevin A. 0000-0003-2236-5193 kathorn@usgs.gov","orcid":"https://orcid.org/0000-0003-2236-5193","contributorId":3288,"corporation":false,"usgs":true,"family":"Thorn","given":"Kevin","email":"kathorn@usgs.gov","middleInitial":"A.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":654847,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kim, Sunghwan","contributorId":45606,"corporation":false,"usgs":true,"family":"Kim","given":"Sunghwan","affiliations":[],"preferred":false,"id":654848,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70178688,"text":"70178688 - 2016 - Potential effects of drought on carrying capacity for wintering waterfowl in the Central Valley of California","interactions":[],"lastModifiedDate":"2016-12-06T10:01:53","indexId":"70178688","displayToPublicDate":"2016-12-05T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Potential effects of drought on carrying capacity for wintering waterfowl in the Central Valley of California","docAbstract":"We used the bioenergetics model TRUEMET to evaluate potential effects of California's recent drought on food supplies for waterfowl wintering in the Central Valley under a range of habitat and waterfowl population scenarios. In nondrought years in the current Central Valley landscape, food supplies are projected to be adequate for waterfowl from fall through early spring (except late March) even if waterfowl populations reach North American Waterfowl Management Plan goals. However, in all drought scenarios that we evaluated, food supplies were projected to be exhausted for ducks by mid- to late winter and by late winter or early spring for geese. For ducks, these results were strongly related to projected declines in winter-flooded rice fields that provide 45% of all the food energy available to ducks in the Central Valley in nondrought water years. Delayed flooding of some managed wetlands may help alleviate food shortages by providing wetland food resources better timed with waterfowl migration and abundance patterns in the Central Valley, as well as reducing the amount of water needed to manage these habitats. However, future research is needed to evaluate the impacts of delayed flooding on waterfowl hunting, and whether California's existing water delivery system would make delayed flooding feasible. Securing adequate water supplies for waterfowl and other wetland-dependent birds is among the greatest challenges facing resource managers in coming years, especially in the increasingly arid western United States.","doi":"10.3996/082015-JFWM-082","usgsCitation":"Petrie, M.J., Fleskes, J., Wolder, M.A., Isola, C.R., Yarris, G., and Skalos, D.A., 2016, Potential effects of drought on carrying capacity for wintering waterfowl in the Central Valley of California: Journal of Fish and Wildlife Management, v. 7, no. 2, p. 408-422, https://doi.org/10.3996/082015-JFWM-082.","productDescription":"15 p.","startPage":"408","endPage":"422","onlineOnly":"N","ipdsId":"IP-073695","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":488586,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/082015-jfwm-082","text":"Publisher Index Page"},{"id":331451,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"2","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2016-09-01","publicationStatus":"PW","scienceBaseUri":"58468ae8e4b04fc80e5236c3","contributors":{"authors":[{"text":"Petrie, Mark J.","contributorId":89655,"corporation":false,"usgs":true,"family":"Petrie","given":"Mark","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":654838,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fleskes, Joseph P. joe_fleskes@usgs.gov","contributorId":138999,"corporation":false,"usgs":true,"family":"Fleskes","given":"Joseph P.","email":"joe_fleskes@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":654839,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wolder, Mike A.","contributorId":6403,"corporation":false,"usgs":true,"family":"Wolder","given":"Mike","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":654840,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Isola, Craig R.","contributorId":177166,"corporation":false,"usgs":false,"family":"Isola","given":"Craig","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":654841,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Yarris, Gregory S.","contributorId":115361,"corporation":false,"usgs":true,"family":"Yarris","given":"Gregory S.","affiliations":[],"preferred":false,"id":654842,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Skalos, Daniel A.","contributorId":64123,"corporation":false,"usgs":true,"family":"Skalos","given":"Daniel","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":654843,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70192557,"text":"70192557 - 2016 - Interactive effects between nest microclimate and nest vegetation structure confirm microclimate thresholds for Lesser Prairie-Chicken nest survival","interactions":[],"lastModifiedDate":"2017-12-04T14:32:13","indexId":"70192557","displayToPublicDate":"2016-12-05T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3551,"text":"The Condor","active":true,"publicationSubtype":{"id":10}},"title":"Interactive effects between nest microclimate and nest vegetation structure confirm microclimate thresholds for Lesser Prairie-Chicken nest survival","docAbstract":"The range of Lesser Prairie-Chickens (Tympanuchus pallidicinctus) spans 4 unique ecoregions along 2 distinct environmental gradients. The Sand Shinnery Oak Prairie ecoregion of the Southern High Plains of New Mexico and Texas is environmentally isolated, warmer, and more arid than the Short-Grass, Sand Sagebrush, and Mixed-Grass Prairie ecoregions in Colorado, Kansas, Oklahoma, and the northeast panhandle of Texas. Weather is known to influence Lesser Prairie-Chicken nest survival in the Sand Shinnery Oak Prairie ecoregion; regional variation may also influence nest microclimate and, ultimately, survival during incubation. To address this question, we placed data loggers adjacent to nests during incubation to quantify temperature and humidity distribution functions in 3 ecoregions. We developed a suite of a priori nest survival models that incorporated derived microclimate parameters and visual obstruction as covariates in Program MARK. We monitored 49 nests in Mixed-Grass, 22 nests in Sand Shinnery Oak, and 30 nests in Short-Grass ecoregions from 2010 to 2014. Our findings indicated that (1) the Sand Shinnery Oak Prairie ecoregion was hotter and drier during incubation than the Mixed- and Short-Grass ecoregions; (2) nest microclimate varied among years within ecoregions; (3) visual obstruction was positively associated with nest survival; but (4) daily nest survival probability decreased by 10% every half-hour when temperature was greater than 34°C and vapor pressure deficit was less than −23 mmHg during the day (about 0600–2100 hours). Our major finding confirmed microclimate thresholds for nest survival under natural conditions across the species' distribution, although Lesser Prairie-Chickens are more likely to experience microclimate conditions that result in nest failures in the Sand Shinnery Oak Prairie ecoregion. The species would benefit from identification of thermal landscapes and management actions that promote cooler, more humid nest microclimates.
","language":"English","doi":"10.1650/CONDOR-16-38.1","usgsCitation":"Grisham, B.A., Godar, A.J., Boal, C.W., and Haukos, D.A., 2016, Interactive effects between nest microclimate and nest vegetation structure confirm microclimate thresholds for Lesser Prairie-Chicken nest survival: The Condor, v. 118, no. 4, p. 728-746, https://doi.org/10.1650/CONDOR-16-38.1.","productDescription":"19 p.","startPage":"728","endPage":"746","ipdsId":"IP-043669","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":470342,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1650/condor-16-38.1","text":"Publisher Index Page"},{"id":349658,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"118","issue":"4","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2016-10-19","publicationStatus":"PW","scienceBaseUri":"5a60fc7ce4b06e28e9c23eff","contributors":{"authors":[{"text":"Grisham, Blake A.","contributorId":75419,"corporation":false,"usgs":true,"family":"Grisham","given":"Blake","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":724360,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Godar, Alixandra J.","contributorId":201107,"corporation":false,"usgs":false,"family":"Godar","given":"Alixandra","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":724362,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Boal, Clint W. 0000-0001-6008-8911 cboal@usgs.gov","orcid":"https://orcid.org/0000-0001-6008-8911","contributorId":1909,"corporation":false,"usgs":true,"family":"Boal","given":"Clint","email":"cboal@usgs.gov","middleInitial":"W.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":716190,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Haukos, David A. 0000-0001-5372-9960 dhaukos@usgs.gov","orcid":"https://orcid.org/0000-0001-5372-9960","contributorId":3664,"corporation":false,"usgs":true,"family":"Haukos","given":"David","email":"dhaukos@usgs.gov","middleInitial":"A.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":724361,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ]}