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":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate 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":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":5061,"text":"National Cooperative Geologic Mapping and Landslide Hazards","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":70175434,"text":"sir20165110 - 2016 - Hydrologic assessment of the shallow groundwater flow system beneath the Shinnecock Nation tribal lands, Suffolk County, New York","interactions":[],"lastModifiedDate":"2016-12-02T11:21:10","indexId":"sir20165110","displayToPublicDate":"2016-12-02T08:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-5110","title":"Hydrologic assessment of the shallow groundwater flow system beneath the Shinnecock Nation tribal lands, Suffolk County, New York","docAbstract":"Defining the distribution and flow of shallow groundwater beneath the Shinnecock Nation tribal lands in Suffolk County, New York, is a crucial first step in identifying sources of potential contamination to the surficial aquifer and coastal ecosystems. The surficial or water table aquifer beneath the tribal lands is the primary source of potable water supply for at least 6 percent of the households on the tribal lands. Oyster fisheries and other marine ecosystems are critical to the livelihood of many residents living on the tribal lands, but are susceptible to contamination from groundwater entering the embayment from the surficial aquifer. Contamination of the surficial aquifer from flooding during intense coastal storms, nutrient loading from fertilizers, and septic effluent have been identified as potential sources of human and ecological health concerns on tribal lands.
The U.S. Geological Survey (USGS) facilitated the installation of 17 water table wells on and adjacent to the tribal lands during March 2014. These wells were combined with other existing wells to create a 32-well water table monitoring network that was used to assess local hydrologic conditions. Survey-grade, global-navigation-satellite systems provided centimeter-level accuracy for positioning wellhead surveys. Water levels were measured by the USGS during May (spring) and November (fall) 2014 to evaluate seasonal effects on the water table. Water level measurements were made at high and low tide during May 2014 to identify potential effects on the water table caused by changes in tidal stage (tidal flux) in Shinnecock Bay. Water level contour maps indicate that the surficial aquifer is recharged by precipitation and upgradient groundwater flow that moves from the recharge zone located generally beneath Sunrise Highway, to the discharge zone beneath the tribal lands, and eventually discharges into the embayment, tidal creeks, and estuaries that bound the tribal lands to the east, south, and west.
Water levels in many of the wells in the network fluctuated in response to precipitation, upgradient groundwater flow, and tidal flux in Shinnecock Bay. Water level altitudes ranged from 6.66 to 0.47 feet (ft) above the North American Vertical Datum of 1988 during the spring measurement period, and from 5.25 to -0.24 ft (NAVD 88) during fall 2014. Historically, annual and seasonal precipitation seem to indicate long-term water level trends in an index well located in the town of Southampton, correlates with changes in storage in the upper glacial aquifer, but does not necessarily indicate water level extremes in the shallow groundwater system. To place the study period in perspective, calendar year 2014 was the 32d wettest year on record, with precipitation for the year totaling 48.1 inches, a 2.6-percent increase from the annual average (46.9 inches per year), based on 81 years of complete record at the National Oceanographic and Atmospheric Administration, National Weather Service cooperative meteorological station at Bridgehampton, New York. Estimated recharge to the water table beneath the tribal lands from precipitation for 2014 is 25.4 inches.
Tidal flux caused water levels in wells to fluctuate from 0.30 to -0.24 ft during May 2014. Water levels in wells located north of Old Fort Pond and beneath the southernmost extent of the tribal lands were most influenced by tidal flux. During June 2014, hydrographs indicate that tidal flux influenced water levels by 0.48 ft in a well located near the southernmost extent of the tribal lands approximately 0.3 miles north of Shinnecock Bay, and was zero at a well located approximately 0.5 miles south of Montauk Highway, and 0.4 miles west of Heady Creek, near the geographic center of the tribal lands. Tidal-influence delay time (time interval between peak high-tide stage and corresponding peak high-water level) ranged from 1.75 hours at the well located near the southernmost extent of the tribal lands, to more than 4 hours at a well located north of Old Fort Pond, near the northwestern part of the tribal lands.
Estimated hydraulic-conductivity values derived from the results of specific-capacity tests that were completed at nine observation wells during March 2015 were used to calculate average linear velocity. Average linear velocity along conceptualized flow-path segments of the upper glacial aquifer located beneath the tribal lands was estimated using an assumed effective porosity value, and hydraulic-conductivity and hydraulic-head values that were interpolated from measured values. Groundwater travel times were estimated by dividing the length of the flow-path segment by the average linear velocity along the flow-path segment. Total estimated groundwater travel time along a conceptualized flow path, beginning near Sunrise Highway and terminating at Shinnecock Bay, is approximately 45 years using a porosity value of 30 percent.
A surficial-silty unit was identified from approximately 0 to 10 ft below land surface at multiple locations beneath the tribal lands. The lithology of the surficial unit was verified by interpreted gamma log results obtained from select wells, and auger-rig drill cuttings from an observation well located near the geographic center of the tribal lands. The altitude of the unit varies with topography and was delineated along a cross section line that trends north-south along the approximate centerline (spine) of the tribal lands. The altitude of the hydrogeologic contact between the upper glacial and the Magothy aquifers generally decreases from northwest to southeast, occurs at a depth ranging from about 150 to 200 ft beneath the tribal lands, and was identified at two locations north of the tribal lands, near Sunrise Highway and Sebonac Road. Results of electrical geophysical surveys indicate that the depth to the freshwater/saltwater interface decreases from north to south with decreasing water level altitude, and the Magothy and upper glacial aquifers contain saltwater at varying depths along the north-south trending section. Results of the surveys also indicate that the Magothy aquifer beneath the tribal lands contains brackish and salty water and is not considered a source of potable water supply. In general, depth to the interface increases with increasing geographic distance from the coastline. Low water table altitudes can result in increased saltwater encroachment into the surficial aquifer beneath the tribal lands. This upward movement and shallow depth of the freshwater/saltwater interface can jeopardize water quality in wells that supply water for domestic use.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165110","isbn":"978-1-4113-4082-4","collaboration":"Prepared in cooperation with the Shinnecock Nation and the Suffolk County Department of Health Services","usgsCitation":"Noll, M.L., Rivera, S.L., and Busciolano, Ronald, 2016, Hydrologic assessment of the shallow groundwater flow system beneath the Shinnecock Nation tribal lands, Suffolk County, New York: U.S. Geological Survey Scientific Investigations Report 2016–5110, 44 p., https://dx.doi.org/10.3133/sir20165110.\n","productDescription":"Report: ix, 44 p. ","startPage":"1","endPage":"44","numberOfPages":"58","onlineOnly":"N","ipdsId":"IP-068431","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":330721,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5110/sir20165110.pdf","text":"Report","size":"4.05 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5110"},{"id":330720,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5110/coverthb.jpg"}],"country":"United States","state":"New York","county":"Suffolk County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.50927734375,\n 40.22712123211294\n ],\n [\n -74.50927734375,\n 41.166249339092\n ],\n [\n -71.69403076171875,\n 41.166249339092\n ],\n [\n -71.69403076171875,\n 40.22712123211294\n ],\n [\n -74.50927734375,\n 40.22712123211294\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New York Water Science Center
U.S. Geological Survey
2045 Route 112, Building 4
Coram, NY 11727
Information requests:
(518) 285-5602
Or visit our Web site at:
http://ny.water.usgs.gov
Oxygen, hydrogen, sulfur, and carbon isotopes have been analyzed in the Pea Ridge magnetite-apatite deposit, the largest historic producer among the known iron deposits in the southeast Missouri portion of the 1.5 to 1.3 Ga eastern granite-rhyolite province. The data were collected to investigate the sources of ore fluids, conditions of ore formation, and provenance of sulfur, and to improve the general understanding of the copper, gold, and rare earth element potential of iron deposits regionally. The δ18O values of Pea Ridge magnetite are 1.9 to 4.0‰, consistent with a model in which some magnetite crystallized from a melt and other magnetite—perhaps the majority—precipitated from an aqueous fluid of magmatic origin. The δ18O values of quartz, apatite, actinolite, K-feldspar, sulfates, and calcite are significantly higher, enough so as to indicate growth or equilibration under cooler conditions than magnetite and/or in the presence of a fluid that was not entirely magmatic. A variety of observations, including stable isotope observations, implicate a second fluid that may ultimately have been meteoric in origin and may have been modified by isotopic exchange with rocks or by evaporation during storage in lakes.
Sulfur isotope analyses of sulfides from Pea Ridge and seven other mineral deposits in the region reveal two distinct populations that average 3 and 13‰. Two sulfur sources are implied. One was probably igneous melts or rocks belonging to the mafic- to intermediate-composition volcanic suite that is present at or near most of the iron deposits; the other was either melts or volcanic rocks that had degassed very extensively, or else volcanic lakes that had trapped rising magmatic gases. The higher δ34S values correspond to deposits or prospects where copper is noteworthy—the Central Dome portion of the Boss deposit, the Bourbon deposit, and the Vilander prospective area. The correspondence suggests that (1) sulfur either limited the deposition of copper or was cotransported with copper, and (2) sulfur isotope analysis may be useful in evaluating southeast Missouri iron deposits for copper and possibly for gold.
","language":"English","publisher":"Society of Economic Geologists","doi":"10.2113/econgeo.111.8.2017","usgsCitation":"Johnson, C.A., Day, W.C., and Rye, R.O., 2016, Oxygen, hydrogen, sulfur, and carbon isotopes in the Pea Ridge magnetite-apatite deposit, southeast Missouri, and sulfur isotope comparisons to other iron deposits in the region: Economic Geology, v. 111, no. 8, p. 2017-2032, https://doi.org/10.2113/econgeo.111.8.2017.","productDescription":"16 p.","startPage":"2017","endPage":"2032","ipdsId":"IP-069800","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":331639,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Missouri","volume":"111","issue":"8","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-11-16","publicationStatus":"PW","scienceBaseUri":"58492df2e4b06d80b7b093a0","contributors":{"authors":[{"text":"Johnson, Craig A. 0000-0002-1334-2996 cjohnso@usgs.gov","orcid":"https://orcid.org/0000-0002-1334-2996","contributorId":909,"corporation":false,"usgs":true,"family":"Johnson","given":"Craig","email":"cjohnso@usgs.gov","middleInitial":"A.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":655118,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Day, Warren C. 0000-0002-9278-2120 wday@usgs.gov","orcid":"https://orcid.org/0000-0002-9278-2120","contributorId":1308,"corporation":false,"usgs":true,"family":"Day","given":"Warren","email":"wday@usgs.gov","middleInitial":"C.","affiliations":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"preferred":true,"id":655119,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rye, Robert O. rrye@usgs.gov","contributorId":1486,"corporation":false,"usgs":true,"family":"Rye","given":"Robert","email":"rrye@usgs.gov","middleInitial":"O.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":655120,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70186922,"text":"70186922 - 2016 - Spatial and ecological variation in dryland ecohydrological responses to climate change: implications for management","interactions":[],"lastModifiedDate":"2017-04-14T13:06:19","indexId":"70186922","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Spatial and ecological variation in dryland ecohydrological responses to climate change: implications for management","docAbstract":"Ecohydrological responses to climate change will exhibit spatial variability and understanding the spatial pattern of ecological impacts is critical from a land management perspective. To quantify climate change impacts on spatial patterns of ecohydrology across shrub steppe ecosystems in North America, we asked the following question: How will climate change impacts on ecohydrology differ in magnitude and variability across climatic gradients, among three big sagebrush ecosystems (SB-Shrubland, SB-Steppe, SB-Montane), and among Sage-grouse Management Zones? We explored these potential changes for mid-century for RCP8.5 using a process-based water balance model (SOILWAT) for 898 big sagebrush sites using site- and scenario-specific inputs. We summarize changes in available soil water (ASW) and dry days, as these ecohydrological variables may be helpful in guiding land management decisions about where to geographically concentrate climate change mitigation and adaptation resources. Our results suggest that during spring, soils will be wetter in the future across the western United States, while soils will be drier in the summer. The magnitude of those predictions differed depending on geographic position and the ecosystem in question: Larger increases in mean daily spring ASW were expected for high-elevation SB-Montane sites and the eastern and central portions of our study area. The largest decreases in mean daily summer ASW were projected for warm, dry, mid-elevation SB-Montane sites in the central and west-central portions of our study area (decreases of up to 50%). Consistent with declining summer ASW, the number of dry days was projected to increase rangewide, but particularly for SB-Montane and SB-Steppe sites in the eastern and northern regions. Collectively, these results suggest that most sites will be drier in the future during the summer, but changes were especially large for mid- to high-elevation sites in the northern half of our study area. Drier summer conditions in high-elevation, SB-Montane sites may result in increased habitat suitability for big sagebrush, while those same changes will likely reduce habitat suitability for drier ecosystems. Our work has important implications for where land managers should prioritize resources for the conservation of North American shrub steppe plant communities and the species that depend on them.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.1590","usgsCitation":"Palmquist, K.A., Schlaepfer, D., Bradford, J.B., and Lauenroth, W.K., 2016, Spatial and ecological variation in dryland ecohydrological responses to climate change: implications for management: Ecosphere, v. 7, no. 11, e01590; 20 p., https://doi.org/10.1002/ecs2.1590.","productDescription":"e01590; 20 p.","ipdsId":"IP-074039","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":470352,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.1590","text":"Publisher Index Page"},{"id":339736,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"11","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-11-28","publicationStatus":"PW","scienceBaseUri":"58f1e0c9e4b08144348b7df4","contributors":{"authors":[{"text":"Palmquist, Kyle A.","contributorId":169517,"corporation":false,"usgs":false,"family":"Palmquist","given":"Kyle","email":"","middleInitial":"A.","affiliations":[{"id":7098,"text":"University of Wyoming, Department of Botany, 1000 E. University Avenue, Laramie, WY 82071, USA","active":true,"usgs":false}],"preferred":false,"id":691010,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schlaepfer, Daniel R.","contributorId":105189,"corporation":false,"usgs":false,"family":"Schlaepfer","given":"Daniel R.","affiliations":[{"id":7098,"text":"University of Wyoming, Department of Botany, 1000 E. University Avenue, Laramie, WY 82071, USA","active":true,"usgs":false}],"preferred":false,"id":691012,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bradford, John B. 0000-0001-9257-6303 jbradford@usgs.gov","orcid":"https://orcid.org/0000-0001-9257-6303","contributorId":611,"corporation":false,"usgs":true,"family":"Bradford","given":"John","email":"jbradford@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":691009,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lauenroth, William K.","contributorId":80982,"corporation":false,"usgs":false,"family":"Lauenroth","given":"William","email":"","middleInitial":"K.","affiliations":[{"id":7098,"text":"University of Wyoming, Department of Botany, 1000 E. University Avenue, Laramie, WY 82071, USA","active":true,"usgs":false}],"preferred":false,"id":691011,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70176062,"text":"70176062 - 2016 - Assessment of trace element accumulation by earthworms in an orchard soil remediation study using soil amendments","interactions":[],"lastModifiedDate":"2018-08-09T12:21:31","indexId":"70176062","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3728,"text":"Water, Air, & Soil Pollution","onlineIssn":"1573-2932","printIssn":"0049-6979","active":true,"publicationSubtype":{"id":10}},"title":"Assessment of trace element accumulation by earthworms in an orchard soil remediation study using soil amendments","docAbstract":"This study assessed potential bioaccumulation of various trace elements in grasses and earthworms as a consequence of soil incorporation of organic amendments for in situ remediation of an orchard field soil contaminated with organochlorine and Pb pesticide residues. In this experiment, four organic amendments of differing total organic carbon content and quality (two types of composted manure, composted biosolids, and biochar) were added to a contaminated orchard field soil, planted with two types of grasses, and tested for their ability to reduce bioaccumulation of organochlorine pesticides and metals in earthworms. The experiment was carried out in 4-L soil microcosms in a controlled environment for 90 days. After 45 days of orchardgrass or perennial ryegrass growth, Lumbricus terrestris L. were introduced to the microcosms and exposed to the experimental soils for 45 days before the experiment was ended. Total trace element concentrations in the added organic amendments were below recommended safe levels and their phytoavailablity and earthworm availability remained low during a 90-day bioremediation study. At the end of the experiment, total tissue concentrations of Cu, Cd, Mn, Pb, and Zn in earthworms and grasses were below recommended safe levels. Total concentrations of Pb in test soil were similar to maximum background levels of Pb recorded in soils in the Eastern USA (100 mg kg−1 d.w.) because of previous application of orchard pesticides. Addition of aged dairy manure compost and presence of grasses was effective in reducing the accumulation of soil-derived Pb in earthworms, thus reducing the risk of soil Pb entry into wildlife food chains.
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Cullen","contributorId":12588,"corporation":false,"usgs":false,"family":"Sherwood","given":"W.","email":"","middleInitial":"Cullen","affiliations":[],"preferred":false,"id":728200,"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":728201,"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":728202,"contributorType":{"id":2,"text":"Editors"},"rank":4}],"authors":[{"text":"Hibbard, James P.","contributorId":178189,"corporation":false,"usgs":false,"family":"Hibbard","given":"James","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":658153,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Beard, James S.","contributorId":178187,"corporation":false,"usgs":false,"family":"Beard","given":"James","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":658151,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Henika, William S.","contributorId":178188,"corporation":false,"usgs":false,"family":"Henika","given":"William","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":658152,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Horton, J. Wright Jr. 0000-0001-6756-6365 whorton@usgs.gov","orcid":"https://orcid.org/0000-0001-6756-6365","contributorId":173694,"corporation":false,"usgs":true,"family":"Horton","given":"J.","suffix":"Jr.","email":"whorton@usgs.gov","middleInitial":"Wright","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":false,"id":658150,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70191260,"text":"70191260 - 2016 - Geochemistry, Nd-Pb Isotopes, and Pb-Pb Ages of the Mesoproterozoic Pea Ridge Iron Oxide-Apatite–Rare Earth Element Deposit, Southeast Missouri","interactions":[],"lastModifiedDate":"2017-10-02T16:32:15","indexId":"70191260","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1472,"text":"Economic Geology","active":true,"publicationSubtype":{"id":10}},"title":"Geochemistry, Nd-Pb Isotopes, and Pb-Pb Ages of the Mesoproterozoic Pea Ridge Iron Oxide-Apatite–Rare Earth Element Deposit, Southeast Missouri","docAbstract":"Iron oxide-apatite and iron oxide-copper-gold deposits occur within ~1.48 to 1.47 Ga volcanic rocks of the St. Francois Mountains terrane near a regional boundary separating crustal blocks having contrasting depleted-mantle Sm-Nd model ages (TDM). Major and trace element analyses and Nd and Pb isotope data were obtained to characterize the Pea Ridge deposit, improve identification of exploration targets, and better understand the regional distribution of mineralization with respect to crustal blocks. The Pea Ridge deposit is spatially associated with felsic volcanic rocks and plutons. Mafic to intermediate-composition rocks are volumetrically minor. Data for major element variations are commonly scattered and strongly suggest element mobility. Ratios of relatively immobile elements indicate that the felsic rocks are evolved subalkaline dacite and rhyolite; the mafic rocks are basalt to basaltic andesite. Granites and rhyolites display geochemical features typical of rocks produced by subduction. Rare earth element (REE) variations for the rhyolites are diagnostic of rocks affected by hydrothermal alteration and associated REE mineralization. The magnetite-rich rocks and REE-rich breccias show similar REE and mantle-normalized trace element patterns.
Nd isotope compositions (age corrected) show that: (1) host rhyolites have ɛNd from 3.44 to 4.25 and TDM from 1.51 to 1.59 Ga; (2) magnetite ore and specular hematite rocks display ɛNd from 3.04 to 4.21 and TDM from 1.6 to 1.51 Ga, and ɛNd from 2.23 to 2.81, respectively; (3) REE-rich breccias have ɛNd from 3.04 to 4.11 and TDM from 1.6 to 1.51 Ga; and (4) mafic to intermediate-composition rocks range in ɛNd from 2.35 to 3.66 and in TDM from 1.66 to 1.56. The ɛNd values of the magnetite and specular hematite samples show that the REE mineralization is magmatic; no evidence exists for major overprinting by younger, crustal meteoric fluids, or by externally derived Nd. Host rocks, breccias, and magnetite ore shared a common origin from a similar source.
Lead isotope ratios are diverse: (1) host rhyolite has 206Pb/204Pb from 24.261 to 50.091; (2) Pea Ridge and regional galenas have 206Pb/204Pb from 16.030 to 33.548; (3) REE-rich breccia, magnetite ore, and specular hematite rock are more radiogenic than galena; (4) REE-rich breccias have high 206Pb/204Pb (38.122–1277.61) compared to host rhyolites; and (5) REE-rich breccias are more radiogenic than magnetite ore and specular-hematite rock, having 206Pb/204Pb up to 230.65. Radiogenic 207Pb/206Pb age estimates suggest the following: (1) rhyolitic host rocks have ages of ~1.50 Ga, (2) magnetite ore is ~1.44 Ga, and (3) REE-rich breccias are ~1.48 Ga. These estimates are broadly consistent and genetically link the host rhyolite, REE-rich breccia, and magnetite ore as being contemporaneous.
Alteration style and mineralogical or textural distinctions among the magnetite-rich rocks and REE-rich breccias do not correlate with different isotopic sources. In our model, magmatic fluids leached metals from the coeval felsic rocks (rhyolites), which provided the metal source reflected in the compositions of the REE-rich breccias and mineralized rocks. This model allows for the likelihood of contributions from other genetically related felsic and intermediate to more mafic rocks stored deeper in the crust. The deposit thus records an origin as a magmatic-hydrothermal system that was not affected by Nd and Pb remobilization processes, particularly if these processes also triggered mixing with externally sourced metal-bearing fluids. The Pea Ridge deposit was part of a single, widespread, homogeneous mixing system that produced a uniform isotopic composition, thus representing an excellent example of an igneous-dominated system that generated coeval magmatism and REE mineralization. Geochemical features suggest that components in the Pea Ridge deposit originated from sources in an orogenic margin. Basaltic magmatism produced by mantle decompression melting provided heat for extracting melts from the middle or lower crust. Continual addition of mafic magmas to the base of the subcontinental lithosphere, in a back-arc setting, remelted calc-alkaline rocks enriched in metals that were stored in the crust.
The St. Francois Mountains terrane is adjacent to the regional TDM line (defined at a value of 1.55 Ga) that separates ~1600 Ma basement to the west, from younger basements to the east. Data for Pea Ridge straddle the TDM values proposed for the line. The Sm-Nd isotope system has been closed since formation of the deposit and the original igneous signatures have not been affected by cycles of alteration or superimposed mineralizing events. No evidence exists for externally derived Nd or Sm. The source region for metals within the Pea Ridge deposit had a moderate compositional variation and the REE-rich breccias and mineralized rocks are generally isotopically homogeneous. The Pea Ridge deposit thus constitutes a distinctive isotopic target for use as a model in identifying other mineralized systems that may share the same metal source in the St. Francois Mountains terrane and elsewhere in the eastern Granite-Rhyolite province.
","language":"English","publisher":"Society of Economic Geologists","doi":"10.2113/econgeo.111.8.1935","usgsCitation":"Ayuso, R.A., Slack, J.F., Day, W.C., and McCafferty, A.E., 2016, Geochemistry, Nd-Pb Isotopes, and Pb-Pb Ages of the Mesoproterozoic Pea Ridge Iron Oxide-Apatite–Rare Earth Element Deposit, Southeast Missouri: Economic Geology, v. 111, no. 8, p. 1935-1962, https://doi.org/10.2113/econgeo.111.8.1935.","productDescription":"28 p.","startPage":"1935","endPage":"1962","ipdsId":"IP-070054","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":346336,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Missouri","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.5,\n 37\n ],\n [\n -89,\n 37\n ],\n [\n -89,\n 38.5\n ],\n [\n -91.5,\n 38.5\n ],\n [\n -91.5,\n 37\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"111","issue":"8","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-11-16","publicationStatus":"PW","scienceBaseUri":"59d35028e4b05fe04cc34d5f","contributors":{"authors":[{"text":"Ayuso, Robert A. 0000-0002-8496-9534 rayuso@usgs.gov","orcid":"https://orcid.org/0000-0002-8496-9534","contributorId":2654,"corporation":false,"usgs":true,"family":"Ayuso","given":"Robert","email":"rayuso@usgs.gov","middleInitial":"A.","affiliations":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":711725,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Slack, John F. 0000-0001-6600-3130 jfslack@usgs.gov","orcid":"https://orcid.org/0000-0001-6600-3130","contributorId":1032,"corporation":false,"usgs":true,"family":"Slack","given":"John","email":"jfslack@usgs.gov","middleInitial":"F.","affiliations":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":711726,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Day, Warren C. 0000-0002-9278-2120 wday@usgs.gov","orcid":"https://orcid.org/0000-0002-9278-2120","contributorId":1308,"corporation":false,"usgs":true,"family":"Day","given":"Warren","email":"wday@usgs.gov","middleInitial":"C.","affiliations":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"preferred":true,"id":711727,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McCafferty, Anne E. 0000-0001-5574-9201 anne@usgs.gov","orcid":"https://orcid.org/0000-0001-5574-9201","contributorId":1120,"corporation":false,"usgs":true,"family":"McCafferty","given":"Anne","email":"anne@usgs.gov","middleInitial":"E.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":711728,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70184459,"text":"70184459 - 2016 - The 2015 Fillmore earthquake swarm and possible crustal deformation mechanisms near the bottom of the eastern Ventura Basin, California","interactions":[],"lastModifiedDate":"2017-03-09T13:08:07","indexId":"70184459","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"The 2015 Fillmore earthquake swarm and possible crustal deformation mechanisms near the bottom of the eastern Ventura Basin, California","docAbstract":"The 2015 Fillmore swarm occurred about 6 km west of the city of Fillmore in Ventura, California, and was located beneath the eastern part of the actively subsiding Ventura basin at depths from 11.8 to 13.8 km, similar to two previous swarms in the area. Template‐matching event detection showed that it started on 5 July 2015 at 2:21 UTC with an M∼1.0 earthquake. The swarm exhibited unusual episodic spatial and temporal migrations and unusual diversity in the nodal planes of the focal mechanisms as compared to the simple hypocenter‐defined plane. It was also noteworthy because it consisted of >1400 events of M≥0.0, with M 2.8 being the largest event. We suggest that fluids released by metamorphic dehydration processes, migration of fluids along a detachment zone, and cascading asperity failures caused this prolific earthquake swarm, but other mechanisms (such as simple mainshock–aftershock stress triggering or a regional aseismic creep event) are less likely. Dilatant strengthening may be a mechanism that causes the temporal decay of the swarm as pore‐pressure drop increased the effective normal stress, and counteracted the instability driving the swarm.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220160020","usgsCitation":"Hauksson, E., Andrews, J., Plesch, A., Shaw, J.H., and Shelly, D.R., 2016, The 2015 Fillmore earthquake swarm and possible crustal deformation mechanisms near the bottom of the eastern Ventura Basin, California: Seismological Research Letters, v. 87, no. 4, p. 807-815, https://doi.org/10.1785/0220160020.","productDescription":"9 p.","startPage":"807","endPage":"815","ipdsId":"IP-070915","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":470384,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1785/0220160020","text":"External Repository"},{"id":337210,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Eastern Ventura Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.47769165039061,\n 34.15159051366224\n ],\n [\n -118.79928588867188,\n 34.15159051366224\n ],\n [\n -118.79928588867188,\n 34.558597459864096\n ],\n [\n -119.47769165039061,\n 34.558597459864096\n ],\n [\n -119.47769165039061,\n 34.15159051366224\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"87","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-18","publicationStatus":"PW","scienceBaseUri":"58c277d8e4b014cc3a3e76af","contributors":{"authors":[{"text":"Hauksson, Egill","contributorId":48174,"corporation":false,"usgs":false,"family":"Hauksson","given":"Egill","affiliations":[{"id":27150,"text":"Seismological Laboratory, California Institute of Technology, Pasadena, CA, USA","active":true,"usgs":false}],"preferred":false,"id":681601,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Andrews, Jennifer","contributorId":187764,"corporation":false,"usgs":false,"family":"Andrews","given":"Jennifer","affiliations":[],"preferred":false,"id":681602,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Plesch, Andreas 0000-0002-3355-9199","orcid":"https://orcid.org/0000-0002-3355-9199","contributorId":187765,"corporation":false,"usgs":false,"family":"Plesch","given":"Andreas","email":"","affiliations":[{"id":16811,"text":"Harvard University","active":true,"usgs":false}],"preferred":false,"id":681603,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shaw, John H.","contributorId":187766,"corporation":false,"usgs":false,"family":"Shaw","given":"John","email":"","middleInitial":"H.","affiliations":[{"id":13619,"text":"Department of Earth & Planetary Sciences, Harvard University, Cambridge, MA","active":true,"usgs":false}],"preferred":false,"id":681604,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Shelly, David R. dshelly@usgs.gov","contributorId":2978,"corporation":false,"usgs":true,"family":"Shelly","given":"David","email":"dshelly@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":681600,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70178700,"text":"70178700 - 2016 - Modeling the effects of land cover and use on landscape capability for urban ungulate populations","interactions":[],"lastModifiedDate":"2020-08-25T16:33:19.998207","indexId":"70178700","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"11","title":"Modeling the effects of land cover and use on landscape capability for urban ungulate populations","docAbstract":"Expanding ungulate populations are causing concerns for wildlife professionals and residents in many urban areas worldwide. Nowhere is the phenomenon more apparent than in the eastern US, where urban white-tailed deer (Odocoileus virginianus) populations are increasing. Most habitat suitability models for deer have been developed in rural areas and across large (>1000 km2) spatial extents. Only recently have we begun to understand the factors that contribute to space use by deer over much smaller spatial extents. In this study, we explore the concepts, terminology, methodology and state-of-the-science in wildlife abundance modeling as applied to overabundant deer populations across heterogeneous urban landscapes. We used classified, high-resolution digital orthoimagery to extract landscape characteristics in several urban areas of upstate New York. In addition, we assessed deer abundance and distribution in 1-km2 blocks across each study area from either aerial surveys or ground-based distance sampling. We recorded the number of detections in each block and used binomial mixture models to explore important relationships between abundance and key landscape features. Finally, we cross-validated statistical models of abundance and compared covariate relationships across study sites. Study areas were characterized along a gradient of urbanization based on the proportions of impervious surfaces and natural vegetation which, based on the best-supported models, also distinguished blocks potentially occupied by deer. Models performed better at identifying occurrence of deer and worse at predicting abundance in cross-validation comparisons. We attribute poor predictive performance to differences in deer population trajectories over time. The proportion of impervious surfaces often yielded better predictions of abundance and occurrence than did the proportion of natural vegetation, which we attribute to a lack of certain land cover classes during cold and snowy winters. Merits and limitations of our approach to habitat suitability modeling are discussed in detail.","largerWorkType":{"id":4,"text":"Book"},"largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"International Association for Landscape Ecology","publisherLocation":"Urban landscape ecology: Science, policy and practice","usgsCitation":"Underwood, H.B., and Kilheffer, C.R., 2016, Modeling the effects of land cover and use on landscape capability for urban ungulate populations, p. 181-208.","productDescription":"28 p.","startPage":"181","endPage":"208","ipdsId":"IP-061055","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":331585,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":331463,"type":{"id":15,"text":"Index Page"},"url":"https://www.routledge.com/Urban-Landscape-Ecology-Science-policy-and-practice/Francis-Millington-Chadwick/p/book/9781138888517"}],"publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5847dc7de4b06d80b7af6aaf","contributors":{"editors":[{"text":"Francis, Robert A.","contributorId":112146,"corporation":false,"usgs":true,"family":"Francis","given":"Robert","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":655011,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Millington, James D. A.","contributorId":169900,"corporation":false,"usgs":false,"family":"Millington","given":"James","email":"","middleInitial":"D. A.","affiliations":[{"id":25615,"text":"Department of Geography, King's College London","active":true,"usgs":false}],"preferred":false,"id":655012,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Chadwick, Michael A.","contributorId":177208,"corporation":false,"usgs":false,"family":"Chadwick","given":"Michael","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":655013,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"Underwood, H. Brian 0000-0002-2064-9128 hbunderw@usgs.gov","orcid":"https://orcid.org/0000-0002-2064-9128","contributorId":140185,"corporation":false,"usgs":true,"family":"Underwood","given":"H.","email":"hbunderw@usgs.gov","middleInitial":"Brian","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":654863,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kilheffer, Chellby R.","contributorId":177173,"corporation":false,"usgs":false,"family":"Kilheffer","given":"Chellby","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":654864,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70179666,"text":"70179666 - 2016 - Geology of the eastern Piedmont in Virginia","interactions":[],"lastModifiedDate":"2018-02-12T13:14:40","indexId":"70179666","displayToPublicDate":"2016-12-01T00:00:00","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":"Geology of the eastern Piedmont in Virginia","docAbstract":"No abstract available.
","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":"Virginia Museum of Natural History","publisherLocation":"Martinsville, VA","isbn":"1-884549-40-3","usgsCitation":"Horton, J.W., Owens, B.E., Hackley, P.C., Burton, W.C., Sacks, P.E., and Hibbard, J.P., 2016, Geology of the eastern Piedmont in Virginia, chap. of The geology of Virginia (Virginia Museum of Natural History Special Publication 18): Virginia Museum of Natural History Special Publication, p. 125-158.","productDescription":"34 p.","startPage":"125","endPage":"158","ipdsId":"IP-019977","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science 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Cullen","contributorId":12588,"corporation":false,"usgs":false,"family":"Sherwood","given":"W.","email":"","middleInitial":"Cullen","affiliations":[],"preferred":false,"id":728204,"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":728205,"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":728206,"contributorType":{"id":2,"text":"Editors"},"rank":4}],"authors":[{"text":"Horton, J. Wright Jr. 0000-0001-6756-6365 whorton@usgs.gov","orcid":"https://orcid.org/0000-0001-6756-6365","contributorId":173694,"corporation":false,"usgs":true,"family":"Horton","given":"J.","suffix":"Jr.","email":"whorton@usgs.gov","middleInitial":"Wright","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":false,"id":658156,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Owens, Brent E.","contributorId":178190,"corporation":false,"usgs":false,"family":"Owens","given":"Brent","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":658158,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hackley, Paul C. 0000-0002-5957-2551 phackley@usgs.gov","orcid":"https://orcid.org/0000-0002-5957-2551","contributorId":592,"corporation":false,"usgs":true,"family":"Hackley","given":"Paul","email":"phackley@usgs.gov","middleInitial":"C.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":658155,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Burton, William C. 0000-0001-7519-5787 bburton@usgs.gov","orcid":"https://orcid.org/0000-0001-7519-5787","contributorId":1293,"corporation":false,"usgs":true,"family":"Burton","given":"William","email":"bburton@usgs.gov","middleInitial":"C.","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}],"preferred":true,"id":658154,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sacks, Paul E.","contributorId":178191,"corporation":false,"usgs":false,"family":"Sacks","given":"Paul","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":658159,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hibbard, James P.","contributorId":178189,"corporation":false,"usgs":false,"family":"Hibbard","given":"James","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":658157,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70189481,"text":"70189481 - 2016 - Eastern Whip-poor-wills (Antrostomus vociferus) are positively associated with low elevation forest In the central Appalachians","interactions":[],"lastModifiedDate":"2018-03-26T11:46:34","indexId":"70189481","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3784,"text":"Wilson Journal of Ornithology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Eastern Whip-poor-wills (Antrostomus vociferus) are positively associated with low elevation forest In the central Appalachians","title":"Eastern Whip-poor-wills (Antrostomus vociferus) are positively associated with low elevation forest In the central Appalachians","docAbstract":"Populations of the Eastern Whip-poor-will (Antrostomus vociferus) are thought to be declining because of a range of potential factors including habitat loss, pesticide use, and predation. However, this species is nocturnal and, as a consequence, it is poorly studied, and its population status is not well assessed by traditional diurnal bird surveys. We used nocturnal road surveys to study habitat associations and distribution of Eastern Whip-poor-wills to better understand and contextualize their population status and to provide a framework for subsequent research and management. We used occupancy models to associate presence of Eastern Whip-poor-wills with habitat characteristics. Global models with habitat associations at a radius of 1600 m (1.0-ha area) were the best supported by the data, suggesting that this was the scale at which the species responded to the habitat parameters we measured. At this scale, Eastern Whip-poor-wills most frequently occupied areas lower in elevation and characterized by forested, herbaceous, and wetland cover types. In contrast, high elevation conifer forest communities had substantially fewer Eastern Whip-poor-wills. Detection rates were positively correlated with moon visibility and negatively correlated with noise. We used the results of our surveys to generate a regional model to predict distributions of Eastern Whip-poor-wills and that can be used as a framework for future management. Our results suggest that succession of agricultural fields and other clearings into forested habitats with dense understory may be a contributing factor to ongoing declines of Eastern Whip-poor-wills.
","language":"English","publisher":"The Wilson Ornithological Society","doi":"10.1676/15-156.1","usgsCitation":"Slover, C.L., and Katzner, T., 2016, Eastern Whip-poor-wills (Antrostomus vociferus) are positively associated with low elevation forest In the central Appalachians: Wilson Journal of Ornithology, v. 128, no. 4, p. 846-856, https://doi.org/10.1676/15-156.1.","productDescription":"11 p.","startPage":"846","endPage":"856","ipdsId":"IP-073699","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":343818,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"West Virginia","otherGeospatial":"Appalachians, Monongahela National Forest","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.6231689453125,\n 38.02213147353745\n ],\n [\n -79.398193359375,\n 38.02213147353745\n ],\n [\n -79.398193359375,\n 39.198205348894795\n ],\n [\n -80.6231689453125,\n 39.198205348894795\n ],\n [\n -80.6231689453125,\n 38.02213147353745\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"128","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"596886a1e4b0d1f9f05f59ac","contributors":{"authors":[{"text":"Slover, Christina L.","contributorId":194653,"corporation":false,"usgs":false,"family":"Slover","given":"Christina","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":704879,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Katzner, Todd E. 0000-0003-4503-8435 tkatzner@usgs.gov","orcid":"https://orcid.org/0000-0003-4503-8435","contributorId":5979,"corporation":false,"usgs":true,"family":"Katzner","given":"Todd E.","email":"tkatzner@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":false,"id":704880,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70178583,"text":"70178583 - 2016 - Geologic map and cross sections of the Embudo Fault Zone in the Southern Taos Valley, Taos County, New Mexico","interactions":[],"lastModifiedDate":"2017-04-18T09:47:08","indexId":"70178583","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"seriesTitle":{"id":128,"text":"Open-File Report","active":false,"publicationSubtype":{"id":2}},"seriesNumber":"584","title":"Geologic map and cross sections of the Embudo Fault Zone in the Southern Taos Valley, Taos County, New Mexico","docAbstract":"The southern Taos Valley encompasses the physiographic and geologic transition zone between the Picuris Mountains and the San Luis Basin of the Rio Grande rift. The Embudo fault zone is the rift transfer structure that has accommodated the kinematic disparities between the San Luis Basin and the Española Basin during Neogene rift extension. The eastern terminus of the transfer zone coincides with the intersection of four major fault zones (Embudo, Sangre de Cristo, Los Cordovas, and Picuris-Pecos), resulting in an area of extreme geologic and hydrogeologic complexities in both the basin-fill deposits and the bedrock. \r\nAlthough sections of the Embudo fault zone are locally exposed in the bedrock of the Picuris Mountains and in the late Cenozoic sedimentary units along the top of the Picuris piedmont, the full proportions of the fault zone have remained elusive due to a pervasive cover of Quaternary surficial deposits. We combined insights derived from the latest geologic mapping of the area with deep borehole data and high-resolution aeromagnetic and gravity models to develop a detailed stratigraphic/structural model of the rift basin in the southern Taos Valley area.\r\nThe four fault systems in the study area overlap in various ways in time and space. Our geologic model states that the Picuris-Pecos fault system exists in the basement rocks (Picuris formation and older units) of the rift, where it is progressively down dropped and offset to the west by each Embudo fault strand between the Picuris Mountains and the Rio Pueblo de Taos. In this model, the Miranda graben exists in the subsurface as a series of offset basement blocks between the Ponce de Leon neighborhood and the Rio Pueblo de Taos. In the study area, the Embudo faults are pervasive structures between the Picuris Mountains and the Rio Pueblo de Taos, affecting all geologic units that are older than the Quaternary surficial deposits. The Los Cordovas faults are thought to represent the late Tertiary to Quaternary reactivation of the old and deeply buried Picuris-Pecos faults. If so, then the Los Cordovas structures may extend southward under the Picuris piedmont, where they form growth faults as they merge downward into the Picuris-Pecos bedrock faults.\r\nThe exceptionally high density of cross-cutting faults in the study area has severely disrupted the stratigraphy of the Picuris formation and the Santa Fe Group. The Picuris formation exists at the surface in the Miranda and Rio Grande del Rancho grabens, and locally along the top of the Picuris piedmont. In the subsurface, it deepens rapidly from the mountain front into the rift basin. In a similar manner, the Tesuque and Chamita Formations are shallowly exposed close to the mountain front, but are down dropped into the basin along the Embudo faults. The Ojo Caliente Sandstone Member of the Tesuque Formation appears to be thickest in the northwestern study area, and thins toward the south and the east. In the study area, the Lama formation thins westward and southward. The Servilleta Basalt is generally thickest to the north and northwest, thins under the Picuris piedmont, and terminates along a major, linear, buried strand of the Embudo fault zone, demonstrating that the Servilleta flows were spatially and temporally related to Embudo fault activity.","language":"English","publisher":"New Mexico Bureau of Geology and Mineral Resources","usgsCitation":"Bauer, P.W., Kelson, K., Grauch, V.J., Drenth, B.J., Johnson, P.S., Aby, S.B., and Felix, B., 2016, Geologic map and cross sections of the Embudo Fault Zone in the Southern Taos Valley, Taos County, New Mexico: Open-File Report 584, 46 p.","productDescription":"46 p.","ipdsId":"IP-078911","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":339840,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":331296,"type":{"id":15,"text":"Index Page"},"url":"https://geoinfo.nmt.edu/publications/openfile/details.cfml?Volume=584"}],"country":"United States","state":"New Mexico","otherGeospatial":"Taos Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.77980041503906,\n 36.42901741282473\n ],\n [\n -105.78117370605469,\n 36.26531407324164\n ],\n [\n -105.62942504882812,\n 36.26586770430287\n ],\n [\n -105.62805175781249,\n 36.21547120903648\n ],\n [\n -105.56007385253906,\n 36.2165791734887\n ],\n [\n -105.5621337890625,\n 36.43177971506432\n ],\n [\n -105.77980041503906,\n 36.42901741282473\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58f725e6e4b0b7ea5451eecc","contributors":{"authors":[{"text":"Bauer, Paul W.","contributorId":145562,"corporation":false,"usgs":false,"family":"Bauer","given":"Paul","email":"","middleInitial":"W.","affiliations":[{"id":16150,"text":"New Mexico Bureau of Geology and Mineral Resources","active":true,"usgs":false}],"preferred":false,"id":691307,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kelson, Keith I.","contributorId":75851,"corporation":false,"usgs":true,"family":"Kelson","given":"Keith I.","affiliations":[],"preferred":false,"id":691308,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Grauch, V. J. S. 0000-0002-0761-3489 tien@usgs.gov","orcid":"https://orcid.org/0000-0002-0761-3489","contributorId":886,"corporation":false,"usgs":true,"family":"Grauch","given":"V.","email":"tien@usgs.gov","middleInitial":"J. S.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":691309,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Drenth, Benjamin J. 0000-0002-3954-8124 bdrenth@usgs.gov","orcid":"https://orcid.org/0000-0002-3954-8124","contributorId":1315,"corporation":false,"usgs":true,"family":"Drenth","given":"Benjamin","email":"bdrenth@usgs.gov","middleInitial":"J.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":691310,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Johnson, Peggy S.","contributorId":85689,"corporation":false,"usgs":true,"family":"Johnson","given":"Peggy","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":691311,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Aby, Scott B.","contributorId":172710,"corporation":false,"usgs":false,"family":"Aby","given":"Scott","email":"","middleInitial":"B.","affiliations":[{"id":27087,"text":"Muddy Spring Geology","active":true,"usgs":false}],"preferred":false,"id":691312,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Felix, Brigitte","contributorId":191017,"corporation":false,"usgs":false,"family":"Felix","given":"Brigitte","email":"","affiliations":[],"preferred":false,"id":691313,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70179443,"text":"70179443 - 2016 - Modeling and simulation of storm surge on Staten Island to understand inundation mitigation strategies","interactions":[],"lastModifiedDate":"2017-01-03T11:32:41","indexId":"70179443","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2220,"text":"Journal of Coastal Research","active":true,"publicationSubtype":{"id":10}},"title":"Modeling and simulation of storm surge on Staten Island to understand inundation mitigation strategies","docAbstract":"Hurricane Sandy made landfall on October 29, 2012, near Brigantine, New Jersey, and had a transformative impact on Staten Island and the New York Metropolitan area. Of the 43 New York City fatalities, 23 occurred on Staten Island. The borough, with a population of approximately 500,000, experienced some of the most devastating impacts of the storm. Since Hurricane Sandy, protective dunes have been constructed on the southeast shore of Staten Island. ADCIRC+SWAN model simulations run on The City University of New York's Cray XE6M, housed at the College of Staten Island, using updated topographic data show that the coast of Staten Island is still susceptible to tidal surge similar to those generated by Hurricane Sandy. Sandy hindcast simulations of storm surges focusing on Staten Island are in good agreement with observed storm tide measurements. Model results calculated from fine-scaled and coarse-scaled computational grids demonstrate that finer grids better resolve small differences in the topography of critical hydraulic control structures, which affect storm surge inundation levels. The storm surge simulations, based on post-storm topography obtained from high-resolution lidar, provide much-needed information to understand Staten Island's changing vulnerability to storm surge inundation. The results of fine-scale storm surge simulations can be used to inform efforts to improve resiliency to future storms. For example, protective barriers contain planned gaps in the dunes to provide for beach access that may inadvertently increase the vulnerability of the area.
","language":"English","publisher":"Coastal Education and Research Foundation","doi":"10.2112/SI76-013","usgsCitation":"Kress, M.E., Benimoff, A.I., Fritz, W.J., Thatcher, C.A., Blanton, B.O., and Dzedzits, E., 2016, Modeling and simulation of storm surge on Staten Island to understand inundation mitigation strategies: Journal of Coastal Research, v. Special Issue 76, p. 149-161, https://doi.org/10.2112/SI76-013.","productDescription":"13 p.","startPage":"149","endPage":"161","ipdsId":"IP-062638","costCenters":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"links":[{"id":462021,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.17615/7b0p-2a36","text":"External Repository"},{"id":332735,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Staten Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.13625717163086,\n 40.52593506631396\n ],\n [\n -74.04544830322264,\n 40.605090749765786\n ],\n [\n -74.06364440917969,\n 40.61890405098613\n ],\n [\n -74.1525650024414,\n 40.53806878053114\n ],\n [\n -74.13625717163086,\n 40.52593506631396\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"Special Issue 76","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"586cc695e4b0f5ce109fa94f","contributors":{"authors":[{"text":"Kress, Michael E.","contributorId":177814,"corporation":false,"usgs":false,"family":"Kress","given":"Michael","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":657220,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Benimoff, Alan I.","contributorId":177815,"corporation":false,"usgs":false,"family":"Benimoff","given":"Alan","email":"","middleInitial":"I.","affiliations":[],"preferred":false,"id":657221,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fritz, William J.","contributorId":177816,"corporation":false,"usgs":false,"family":"Fritz","given":"William","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":657222,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thatcher, Cindy A. 0000-0003-0331-071X thatcherc@usgs.gov","orcid":"https://orcid.org/0000-0003-0331-071X","contributorId":2868,"corporation":false,"usgs":true,"family":"Thatcher","given":"Cindy","email":"thatcherc@usgs.gov","middleInitial":"A.","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":false,"id":657223,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Blanton, Brian O.","contributorId":177817,"corporation":false,"usgs":false,"family":"Blanton","given":"Brian","email":"","middleInitial":"O.","affiliations":[],"preferred":false,"id":657224,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dzedzits, Eugene","contributorId":177818,"corporation":false,"usgs":false,"family":"Dzedzits","given":"Eugene","email":"","affiliations":[],"preferred":false,"id":657225,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70178571,"text":"70178571 - 2016 - Clinal patterns in genetic variation for northern leopard frog (Rana pipiens): Conservation status and population histories","interactions":[],"lastModifiedDate":"2017-01-03T16:01:46","indexId":"70178571","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3750,"text":"Wetlands","onlineIssn":"1943-6246","printIssn":"0277-5212","active":true,"publicationSubtype":{"id":10}},"title":"Clinal patterns in genetic variation for northern leopard frog (Rana pipiens): Conservation status and population histories","docAbstract":"The security of the northern leopard frog (Rana pipiens) varies spatially with populations east and west of North Dakota considered as secure and at risk, respectively. We used genetic markers to characterize the conservation status of northern leopard frog populations across North Dakota. We used multiple regression analyses and model selection to evaluate correlations of expected heterozygosity (HE) with the direct and additive effects of: i) geographic location,ii) wetland density and iii) average annual precipitation. There was lower genetic diversity in the western portion of the state due to lower levels of diversity for populations southwest of the Missouri River. This may reflect a refugial/colonization signature for the only non-glaciated area of North Dakota. Genetic diversity was also positively associated with wetland densities which is consistent with the reliance of this species on a mosaic of wetlands. Our findings suggest that populations in the southwestern part of North Dakota are of higher conservation concern, a finding consistent with the higher risk noted for northern leopard frog populations in most states west of North Dakota. Our findings also pose the hypothesis that climate change induced changes in wetland densities will reduce genetic diversity of northern leopard frog populations.
","language":"English","publisher":"Sprinker","doi":"10.1007/s13157-016-0847-3","usgsCitation":"Stockwell, C., Fisher, J.D., and McLean, K.I., 2016, Clinal patterns in genetic variation for northern leopard frog (Rana pipiens): Conservation status and population histories: Wetlands, v. 36, no. s2, p. 437-443, https://doi.org/10.1007/s13157-016-0847-3.","productDescription":"7 p.","startPage":"437","endPage":"443","ipdsId":"IP-077323","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":331368,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North 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Center","active":true,"usgs":true}],"preferred":false,"id":654592,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70178626,"text":"70178626 - 2016 - Use of structured decision-making to explicitly incorporate environmental process understanding in management of coastal restoration projects: Case study on barrier islands of the northern Gulf of Mexico","interactions":[],"lastModifiedDate":"2017-04-27T10:16:08","indexId":"70178626","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2258,"text":"Journal of Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Use of structured decision-making to explicitly incorporate environmental process understanding in management of coastal restoration projects: Case study on barrier islands of the northern Gulf of Mexico","docAbstract":"Coastal ecosystem management typically relies on subjective interpretation of scientific understanding, with limited methods for explicitly incorporating process knowledge into decisions that must meet multiple, potentially competing stakeholder objectives. Conversely, the scientific community lacks methods for identifying which advancements in system understanding would have the highest value to decision-makers. A case in point is barrier island restoration, where decision-makers lack tools to objectively use system understanding to determine how to optimally use limited contingency funds when project construction in this dynamic environment does not proceed as expected. In this study, collaborative structured decision-making (SDM) was evaluated as an approach to incorporate process understanding into mid-construction decisions and to identify priority gaps in knowledge from a management perspective. The focus was a barrier island restoration project at Ship Island, Mississippi, where sand will be used to close an extensive breach that currently divides the island. SDM was used to estimate damage that may occur during construction, and guide repair decisions within the confines of limited availability of sand and funding to minimize adverse impacts to project objectives. Sand was identified as more limiting than funds, and unrepaired major breaching would negatively impact objectives. Repairing minor damage immediately was determined to be generally more cost effective (depending on the longshore extent) than risking more damage to a weakened project. Key gaps in process-understanding relative to project management were identified as the relationship of island width to breach formation; the amounts of sand lost during breaching, lowering, or narrowing of the berm; the potential for minor breaches to self-heal versus developing into a major breach; and the relationship between upstream nourishment and resiliency of the berm to storms. This application is a prototype for using structured decision-making in support of engineering projects in dynamic environments where mid-construction decisions may arise; highlights uncertainty about barrier island physical processes that limit the ability to make robust decisions; and demonstrates the potential for direct incorporation of process-based models in a formal adaptive management decision framework.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jenvman.2016.08.078","usgsCitation":"Dalyander, P.S., Meyers, M.B., Mattsson, B., Steyer, G., Godsey, E., McDonald, J., Byrnes, M.R., and Ford, M., 2016, Use of structured decision-making to explicitly incorporate environmental process understanding in management of coastal restoration projects: Case study on barrier islands of the northern Gulf of Mexico: Journal of Environmental Management, v. 183, no. 3, p. 497-509, https://doi.org/10.1016/j.jenvman.2016.08.078.","productDescription":"13 p.","startPage":"497","endPage":"509","ipdsId":"IP-068842","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":470460,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jenvman.2016.08.078","text":"Publisher Index Page"},{"id":331388,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Mississippi","otherGeospatial":"East Ship Island, West Ship Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.000244140625,\n 30.18994745521063\n ],\n [\n -89.000244140625,\n 30.267370168467806\n ],\n [\n -88.85639190673828,\n 30.267370168467806\n ],\n [\n -88.85639190673828,\n 30.18994745521063\n ],\n [\n -89.000244140625,\n 30.18994745521063\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"183","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"584144dce4b04fc80e507373","contributors":{"authors":[{"text":"Dalyander, P. Soupy 0000-0001-9583-0872 sdalyander@usgs.gov","orcid":"https://orcid.org/0000-0001-9583-0872","contributorId":141015,"corporation":false,"usgs":true,"family":"Dalyander","given":"P.","email":"sdalyander@usgs.gov","middleInitial":"Soupy","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":654607,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Meyers, Michelle B. 0000-0002-5937-1012 mmeyers@usgs.gov","orcid":"https://orcid.org/0000-0002-5937-1012","contributorId":5608,"corporation":false,"usgs":true,"family":"Meyers","given":"Michelle","email":"mmeyers@usgs.gov","middleInitial":"B.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":654608,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mattsson, Brady","contributorId":59692,"corporation":false,"usgs":true,"family":"Mattsson","given":"Brady","affiliations":[],"preferred":false,"id":654609,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Steyer, Gregory 0000-0001-7231-0110","orcid":"https://orcid.org/0000-0001-7231-0110","contributorId":27797,"corporation":false,"usgs":true,"family":"Steyer","given":"Gregory","affiliations":[],"preferred":false,"id":654610,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Godsey, Elizabeth","contributorId":177095,"corporation":false,"usgs":false,"family":"Godsey","given":"Elizabeth","affiliations":[],"preferred":false,"id":654611,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McDonald, Justin","contributorId":171407,"corporation":false,"usgs":false,"family":"McDonald","given":"Justin","email":"","affiliations":[{"id":26898,"text":"University of Auckland, New Zealand","active":true,"usgs":false}],"preferred":false,"id":654612,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Byrnes, Mark R.","contributorId":102504,"corporation":false,"usgs":true,"family":"Byrnes","given":"Mark","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":654613,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ford, Mark","contributorId":177097,"corporation":false,"usgs":false,"family":"Ford","given":"Mark","email":"","affiliations":[],"preferred":false,"id":654614,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70185043,"text":"70185043 - 2016 - Application of frequency- and time-domain electromagnetic surveys to characterize hydrostratigraphy and landfill construction at the Amargosa Desert Research Site, Beatty, Nevada","interactions":[],"lastModifiedDate":"2018-08-06T12:35:04","indexId":"70185043","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Application of frequency- and time-domain electromagnetic surveys to characterize hydrostratigraphy and landfill construction at the Amargosa Desert Research Site, Beatty, Nevada","docAbstract":"In 2014 and 2015, the U.S. Geological Survey (USGS), conducted frequency-domain electromagnetic (FDEM) surveys at the USGS Amargosa Desert Research Site (ADRS), approximately 17 kilometers (km) south of Beatty, Nevada. The FDEM surveys were conducted within and adjacent to a closed low-level radioactive waste disposal site located at the ADRS. FDEM surveys were conducted on a grid of north-south and east-west profiles to assess the locations and boundaries of historically recorded waste-disposal trenches. In 2015, the USGS conducted time-domain (TDEM) soundings along a profile adjacent to the disposal site (landfill) in cooperation with the U.S. Environmental Protection Agency (USEPA), to assess the thickness and characteristics of the underlying deep unsaturated zone, and the hydrostratigraphy of the underlying saturated zone.
FDEM survey results indicate the general location and extent of the waste-disposal trenches and reveal potential differences in material properties and the type and concentration of waste in several areas of the landfill. The TDEM surveys provide information on the underlying hydrostratigraphy and characteristics of the unsaturated zone that inform the site conceptual model and support an improved understanding of the hydrostratigraphic framework. Additional work is needed to interpret the TDEM results in the context of the local and regional structural geology.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"Society of Exploration Geophysicists","publisherLocation":"Symposium on the application of geophysics to engineering and environmental problems 2016","doi":"10.4133/SAGEEP.29-024","usgsCitation":"White, E.A., Day-Lewis, F.D., Johnson, C.D., and Lane, J.W., 2016, Application of frequency- and time-domain electromagnetic surveys to characterize hydrostratigraphy and landfill construction at the Amargosa Desert Research Site, Beatty, Nevada, p. 119-125, https://doi.org/10.4133/SAGEEP.29-024.","productDescription":"7 p.","startPage":"119","endPage":"125","ipdsId":"IP-073130","costCenters":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":337694,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-03-24","publicationStatus":"PW","scienceBaseUri":"58cba41ae4b0849ce97dc73a","contributors":{"authors":[{"text":"White, Eric A. 0000-0002-7782-146X eawhite@usgs.gov","orcid":"https://orcid.org/0000-0002-7782-146X","contributorId":1737,"corporation":false,"usgs":false,"family":"White","given":"Eric","email":"eawhite@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":684055,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Day-Lewis, Frederick D. 0000-0003-3526-886X daylewis@usgs.gov","orcid":"https://orcid.org/0000-0003-3526-886X","contributorId":1672,"corporation":false,"usgs":true,"family":"Day-Lewis","given":"Frederick","email":"daylewis@usgs.gov","middleInitial":"D.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true}],"preferred":true,"id":684057,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Carole D. 0000-0001-6941-1578 cjohnson@usgs.gov","orcid":"https://orcid.org/0000-0001-6941-1578","contributorId":1891,"corporation":false,"usgs":true,"family":"Johnson","given":"Carole","email":"cjohnson@usgs.gov","middleInitial":"D.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":684058,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lane, John W. Jr. 0000-0002-3558-243X jwlane@usgs.gov","orcid":"https://orcid.org/0000-0002-3558-243X","contributorId":189168,"corporation":false,"usgs":true,"family":"Lane","given":"John","suffix":"Jr.","email":"jwlane@usgs.gov","middleInitial":"W.","affiliations":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true}],"preferred":false,"id":684056,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70191724,"text":"70191724 - 2016 - MODIS imagery improves pest risk assessment: A case study of wheat stem sawfly (Cephus cinctus, Hymenoptera: Cephidae) in Colorado, USA","interactions":[],"lastModifiedDate":"2017-10-25T12:30:57","indexId":"70191724","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1536,"text":"Environmental Entomology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"MODIS imagery improves pest risk assessment: A case study of wheat stem sawfly (Cephus cinctus, Hymenoptera: Cephidae) in Colorado, USA","title":"MODIS imagery improves pest risk assessment: A case study of wheat stem sawfly (Cephus cinctus, Hymenoptera: Cephidae) in Colorado, USA","docAbstract":"Wheat stem sawfly (Cephus cinctus Norton, Hymenoptera: Cephidae) has long been a significant insect pest of spring, and more recently, winter wheat in the northern Great Plains. Wheat stem sawfly was first observed infesting winter wheat in Colorado in 2010 and, subsequently, has spread rapidly throughout wheat production regions of the state. Here, we used maximum entropy modeling (MaxEnt) to generate habitat suitability maps in order to predict the risk of crop damage as this species spreads throughout the winter wheat-growing regions of Colorado. We identified environmental variables that influence the current distribution of wheat stem sawfly in the state and evaluated whether remotely sensed variables improved model performance. We used presence localities of C. cinctus and climatic, topographic, soils, and normalized difference vegetation index and enhanced vegetation index data derived from Moderate Resolution Imaging Spectroradiometer (MODIS) imagery as environmental variables. All models had high performance in that they were successful in predicting suitable habitat for C. cinctus in its current distribution in eastern Colorado. The enhanced vegetation index for the month of April improved model performance and was identified as a top contributor to MaxEnt model. Soil clay percent at 0–5 cm, temperature seasonality, and precipitation seasonality were also associated with C. cinctus distribution in Colorado. The improved model performance resulting from integrating vegetation indices in our study demonstrates the ability of remote sensing technologies to enhance species distribution modeling. These risk maps generated can assist managers in planning control measures for current infestations and assess the future risk of C. cinctus establishment in currently uninfested regions.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/ee/nvw095","usgsCitation":"Lestina, J., Cook, M., Kumar, S., Morisette, J.T., Ode, P.J., and Peirs, F., 2016, MODIS imagery improves pest risk assessment: A case study of wheat stem sawfly (Cephus cinctus, Hymenoptera: Cephidae) in Colorado, USA: Environmental Entomology, v. 45, no. 6, p. 1343-1351, https://doi.org/10.1093/ee/nvw095.","productDescription":"9 p.","startPage":"1343","endPage":"1351","ipdsId":"IP-077680","costCenters":[{"id":477,"text":"North Central Climate Science Center","active":true,"usgs":true}],"links":[{"id":347349,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","volume":"45","issue":"6","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-09-22","publicationStatus":"PW","scienceBaseUri":"59f1a2a7e4b0220bbd9d9f72","contributors":{"authors":[{"text":"Lestina, Jordan","contributorId":197312,"corporation":false,"usgs":false,"family":"Lestina","given":"Jordan","email":"","affiliations":[],"preferred":false,"id":713173,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cook, Maxwell","contributorId":197313,"corporation":false,"usgs":false,"family":"Cook","given":"Maxwell","email":"","affiliations":[],"preferred":false,"id":713174,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kumar, Sunil","contributorId":195493,"corporation":false,"usgs":false,"family":"Kumar","given":"Sunil","affiliations":[],"preferred":false,"id":713175,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Morisette, Jeffrey T. 0000-0002-0483-0082 morisettej@usgs.gov","orcid":"https://orcid.org/0000-0002-0483-0082","contributorId":307,"corporation":false,"usgs":true,"family":"Morisette","given":"Jeffrey","email":"morisettej@usgs.gov","middleInitial":"T.","affiliations":[{"id":477,"text":"North Central Climate Science Center","active":true,"usgs":true},{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":713176,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ode, Paul J.","contributorId":197314,"corporation":false,"usgs":false,"family":"Ode","given":"Paul","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":713177,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Peirs, Frank","contributorId":197315,"corporation":false,"usgs":false,"family":"Peirs","given":"Frank","email":"","affiliations":[],"preferred":false,"id":713178,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70179442,"text":"70179442 - 2016 - Creating a Coastal National Elevation Database (CoNED) for science and conservation applications","interactions":[],"lastModifiedDate":"2022-04-22T14:43:57.030153","indexId":"70179442","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2220,"text":"Journal of Coastal Research","active":true,"publicationSubtype":{"id":10}},"title":"Creating a Coastal National Elevation Database (CoNED) for science and conservation applications","docAbstract":"The U.S. Geological Survey is creating the Coastal National Elevation Database, an expanding set of topobathymetric elevation models that extend seamlessly across coastal regions of high societal or ecological significance in the United States that are undergoing rapid change or are threatened by inundation hazards. Topobathymetric elevation models are raster datasets useful for inundation prediction and other earth science applications, such as the development of sediment-transport and storm surge models. These topobathymetric elevation models are being constructed by the broad regional assimilation of numerous topographic and bathymetric datasets, and are intended to fulfill the pressing needs of decision makers establishing policies for hazard mitigation and emergency preparedness, coastal managers tasked with coastal planning compatible with predictions of inundation due to sea-level rise, and scientists investigating processes of coastal geomorphic change. A key priority of this coastal elevation mapping effort is to foster collaborative lidar acquisitions that meet the standards of the USGS National Geospatial Program's 3D Elevation Program, a nationwide initiative to systematically collect high-quality elevation data. The focus regions are located in highly dynamic environments, for example in areas subject to shoreline change, rapid wetland loss, hurricane impacts such as overwash and wave scouring, and/or human-induced changes to coastal topography.
","language":"English","publisher":"Coastal Education and Research Foundation","doi":"10.2112/SI76-007","usgsCitation":"Thatcher, C.A., Brock, J., Danielson, J.J., Poppenga, S.K., Gesch, D.B., Palaseanu-Lovejoy, M., Barras, J., Evans, G.A., and Gibbs, A., 2016, Creating a Coastal National Elevation Database (CoNED) for science and conservation applications: Journal of Coastal Research, v. Special Issue 76, p. 64-74, https://doi.org/10.2112/SI76-007.","productDescription":"11 p.","startPage":"64","endPage":"74","ipdsId":"IP-065916","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"links":[{"id":470361,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://www.bioone.org/doi/10.2112/SI76-007","text":"External Repository"},{"id":332736,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"Special Issue 76","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"586cc695e4b0f5ce109fa951","contributors":{"authors":[{"text":"Thatcher, Cindy A. 0000-0003-0331-071X thatcherc@usgs.gov","orcid":"https://orcid.org/0000-0003-0331-071X","contributorId":2868,"corporation":false,"usgs":true,"family":"Thatcher","given":"Cindy","email":"thatcherc@usgs.gov","middleInitial":"A.","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":false,"id":657210,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brock, John 0000-0002-5289-9332 jbrock@usgs.gov","orcid":"https://orcid.org/0000-0002-5289-9332","contributorId":2261,"corporation":false,"usgs":true,"family":"Brock","given":"John","email":"jbrock@usgs.gov","affiliations":[{"id":5061,"text":"National Cooperative Geologic Mapping and Landslide Hazards","active":true,"usgs":true}],"preferred":true,"id":657211,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Danielson, Jeffrey J. 0000-0003-0907-034X daniels@usgs.gov","orcid":"https://orcid.org/0000-0003-0907-034X","contributorId":3996,"corporation":false,"usgs":true,"family":"Danielson","given":"Jeffrey","email":"daniels@usgs.gov","middleInitial":"J.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":657212,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Poppenga, Sandra K. 0000-0002-2846-6836 spoppenga@usgs.gov","orcid":"https://orcid.org/0000-0002-2846-6836","contributorId":3327,"corporation":false,"usgs":true,"family":"Poppenga","given":"Sandra","email":"spoppenga@usgs.gov","middleInitial":"K.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":657213,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gesch, Dean B. 0000-0002-8992-4933 gesch@usgs.gov","orcid":"https://orcid.org/0000-0002-8992-4933","contributorId":2956,"corporation":false,"usgs":true,"family":"Gesch","given":"Dean","email":"gesch@usgs.gov","middleInitial":"B.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":657214,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Palaseanu-Lovejoy, Monica 0000-0002-3786-5118 mpal@usgs.gov","orcid":"https://orcid.org/0000-0002-3786-5118","contributorId":3639,"corporation":false,"usgs":true,"family":"Palaseanu-Lovejoy","given":"Monica","email":"mpal@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true},{"id":5061,"text":"National Cooperative Geologic Mapping and Landslide Hazards","active":true,"usgs":true}],"preferred":true,"id":657215,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Barras, John 0000-0002-4207-2972 jbarras@usgs.gov","orcid":"https://orcid.org/0000-0002-4207-2972","contributorId":177812,"corporation":false,"usgs":true,"family":"Barras","given":"John","email":"jbarras@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":657216,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Evans, Gayla A. 0000-0001-5072-4232 gevans@usgs.gov","orcid":"https://orcid.org/0000-0001-5072-4232","contributorId":3125,"corporation":false,"usgs":true,"family":"Evans","given":"Gayla","email":"gevans@usgs.gov","middleInitial":"A.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":657217,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Gibbs, Ann agibbs@usgs.gov","contributorId":177813,"corporation":false,"usgs":true,"family":"Gibbs","given":"Ann","email":"agibbs@usgs.gov","affiliations":[],"preferred":true,"id":657218,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70178632,"text":"70178632 - 2016 - Concentrations of mineral aerosol from desert to plains across the central Rocky Mountains, western United States","interactions":[],"lastModifiedDate":"2017-04-27T10:13:23","indexId":"70178632","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":666,"text":"Aeolian Research","active":true,"publicationSubtype":{"id":10}},"title":"Concentrations of mineral aerosol from desert to plains across the central Rocky Mountains, western United States","docAbstract":"Mineral dusts can have profound effects on climate, clouds, ecosystem processes, and human health. Because regional dust emission and deposition in western North America are not well understood, measurements of total suspended particulate (TSP) from 2011 to 2013 were made along a 500-km transect of five remote sites in Utah and Colorado, USA. The TSP concentrations in μg m−3 adjusted to a 24-h period were relatively high at the two westernmost, dryland sites at Canyonlands National Park (mean = 135) and at Mesa Verde National Park (mean = 99), as well as at the easternmost site on the Great Plains (mean = 143). The TSP concentrations at the two intervening montane sites were less, with more loading on the western slope of the Rocky Mountains (Telluride, mean = 68) closest to the desert sites compared with the site on the eastern slope (Niwot Ridge, mean = 58). Dust concentrations were commonly highest during late winter-late spring, when Pacific frontal storms are the dominant causes of regional wind. Low concentrations (<7 wt%) of organic matter indicated that rock-derived mineral particles composed most TSP. Most TSP mass was carried by particle sizes larger than 10 μm (PM>10), as revealed by relatively low average daily concentrations of fine (<5 μg m−3; PM2.5) and coarse (<10 μg m−3; PM2.5–10) fractions monitored at or near four sites. Standard air-quality measurements for PM2.5 and PM10 apparently do not capture the large majority of mineral-particulate pollution in the remote western interior U.S.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.aeolia.2016.09.001","usgsCitation":"Reynolds, R.L., Munson, S.M., Fernandez, D., Goldstein, H.L., and Neff, J.C., 2016, Concentrations of mineral aerosol from desert to plains across the central Rocky Mountains, western United States: Aeolian Research, v. 23, p. 21-35, https://doi.org/10.1016/j.aeolia.2016.09.001.","productDescription":"15 p.","startPage":"21","endPage":"35","ipdsId":"IP-067488","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":462023,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.aeolia.2016.09.001","text":"Publisher Index Page"},{"id":331402,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"23","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"584144dce4b04fc80e50736d","contributors":{"authors":[{"text":"Reynolds, Richard L. 0000-0002-4572-2942 rreynolds@usgs.gov","orcid":"https://orcid.org/0000-0002-4572-2942","contributorId":139068,"corporation":false,"usgs":true,"family":"Reynolds","given":"Richard","email":"rreynolds@usgs.gov","middleInitial":"L.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":654643,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Munson, Seth M. 0000-0002-2736-6374 smunson@usgs.gov","orcid":"https://orcid.org/0000-0002-2736-6374","contributorId":1334,"corporation":false,"usgs":true,"family":"Munson","given":"Seth","email":"smunson@usgs.gov","middleInitial":"M.","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":654644,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fernandez, Daniel","contributorId":80588,"corporation":false,"usgs":true,"family":"Fernandez","given":"Daniel","affiliations":[],"preferred":false,"id":654645,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Goldstein, Harland L. 0000-0002-6092-8818 hgoldstein@usgs.gov","orcid":"https://orcid.org/0000-0002-6092-8818","contributorId":807,"corporation":false,"usgs":true,"family":"Goldstein","given":"Harland","email":"hgoldstein@usgs.gov","middleInitial":"L.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":654646,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Neff, Jason C.","contributorId":169417,"corporation":false,"usgs":false,"family":"Neff","given":"Jason","email":"","middleInitial":"C.","affiliations":[{"id":25504,"text":"Univ. of Colorado, Coulder, CO","active":true,"usgs":false}],"preferred":false,"id":654647,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70178563,"text":"70178563 - 2016 - Lidar-based mapping of flood control levees in south Louisiana","interactions":[],"lastModifiedDate":"2022-04-22T14:50:07.222","indexId":"70178563","displayToPublicDate":"2016-11-30T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2068,"text":"International Journal of Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Lidar-based mapping of flood control levees in south Louisiana","docAbstract":"Flood protection in south Louisiana is largely dependent on earthen levees, and in the aftermath of Hurricane Katrina the state’s levee system has received intense scrutiny. Accurate elevation data along the levees are critical to local levee district managers responsible for monitoring and maintaining the extensive system of non-federal levees in coastal Louisiana. In 2012, high resolution airborne lidar data were acquired over levees in Lafourche Parish, Louisiana, and a mobile terrestrial lidar survey was conducted for selected levee segments using a terrestrial lidar scanner mounted on a truck. The mobile terrestrial lidar data were collected to test the feasibility of using this relatively new technology to map flood control levees and to compare the accuracy of the terrestrial and airborne lidar. Metrics assessing levee geometry derived from the two lidar surveys are also presented as an efficient, comprehensive method to quantify levee height and stability. The vertical root mean square error values of the terrestrial lidar and airborne lidar digital-derived digital terrain models were 0.038 m and 0.055 m, respectively. The comparison of levee metrics derived from the airborne and terrestrial lidar-based digital terrain models showed that both types of lidar yielded similar results, indicating that either or both surveying techniques could be used to monitor geomorphic change over time. Because airborne lidar is costly, many parts of the USA and other countries have never been mapped with airborne lidar, and repeat surveys are often not available for change detection studies. Terrestrial lidar provides a practical option for conducting repeat surveys of levees and other terrain features that cover a relatively small area, such as eroding cliffs or stream banks, and dunes.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/01431161.2016.1249304","usgsCitation":"Thatcher, C.A., Lim, S., Palaseanu-Lovejoy, M., Danielson, J.J., and Kimbrow, D.R., 2016, Lidar-based mapping of flood control levees in south Louisiana: International Journal of Remote Sensing, v. 37, no. 24, p. 5708-5725, https://doi.org/10.1080/01431161.2016.1249304.","productDescription":"18 p.","startPage":"5708","endPage":"5725","ipdsId":"IP-055230","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"links":[{"id":331364,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","county":"Lafourche Parish","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.56,\n 29.56\n ],\n [\n -90.56,\n 29.65\n ],\n [\n -90.45,\n 29.65\n ],\n [\n -90.45,\n 29.56\n ],\n [\n -90.56,\n 29.56\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"37","issue":"24","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-11-28","publicationStatus":"PW","scienceBaseUri":"583ff34be4b04fc80e437256","contributors":{"authors":[{"text":"Thatcher, Cindy A. 0000-0003-0331-071X thatcherc@usgs.gov","orcid":"https://orcid.org/0000-0003-0331-071X","contributorId":2868,"corporation":false,"usgs":true,"family":"Thatcher","given":"Cindy","email":"thatcherc@usgs.gov","middleInitial":"A.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true},{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":false,"id":654379,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lim, Samsung","contributorId":177043,"corporation":false,"usgs":false,"family":"Lim","given":"Samsung","email":"","affiliations":[],"preferred":false,"id":654380,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Palaseanu-Lovejoy, Monica 0000-0002-3786-5118 mpal@usgs.gov","orcid":"https://orcid.org/0000-0002-3786-5118","contributorId":3639,"corporation":false,"usgs":true,"family":"Palaseanu-Lovejoy","given":"Monica","email":"mpal@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true},{"id":5061,"text":"National Cooperative Geologic Mapping and Landslide Hazards","active":true,"usgs":true}],"preferred":true,"id":654381,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Danielson, Jeffrey J. 0000-0003-0907-034X daniels@usgs.gov","orcid":"https://orcid.org/0000-0003-0907-034X","contributorId":3996,"corporation":false,"usgs":true,"family":"Danielson","given":"Jeffrey","email":"daniels@usgs.gov","middleInitial":"J.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":654382,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kimbrow, Dustin R. dkimbrow@usgs.gov","contributorId":3915,"corporation":false,"usgs":true,"family":"Kimbrow","given":"Dustin","email":"dkimbrow@usgs.gov","middleInitial":"R.","affiliations":[{"id":105,"text":"Alabama Water Science Center","active":true,"usgs":true}],"preferred":true,"id":654383,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70177047,"text":"sir20165145 - 2016 - Characterization and relation of precipitation, streamflow, and water-quality data at the U.S. Army Garrison Fort Carson and Piñon Canyon Maneuver Site, Colorado, water years 2013–14","interactions":[],"lastModifiedDate":"2016-11-30T11:06:37","indexId":"sir20165145","displayToPublicDate":"2016-11-29T16:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-5145","title":"Characterization and relation of precipitation, streamflow, and water-quality data at the U.S. Army Garrison Fort Carson and Piñon Canyon Maneuver Site, Colorado, water years 2013–14","docAbstract":"To evaluate the influence of military training activities on streamflow and water quality, the U.S. Geological Survey, in cooperation with the U.S. Department of the Army, began a hydrologic data collection network on the U.S. Army Garrison Fort Carson in 1978 and on the Piñon Canyon Maneuver Site in 1983. This report is a summary and characterization of the precipitation, streamflow, and water-quality data collected at 43 sites between October 1, 2012, and September 30, 2014 (water years 2013 and 2014).
Variations in the frequency of daily precipitation, seasonal distribution, and seasonal and annual precipitation at 5 stations at the U.S. Army Garrison Fort Carson and 18 stations at or near the Piñon Canyon Maneuver Site were evaluated. Isohyetal diagrams indicated a general pattern of increase in total annual precipitation from east to west at the U.S. Army Garrison Fort Carson and the Piñon Canyon Maneuver Site. Between about 54 and 79 percent of daily precipitation was 0.1 inch or less in magnitude. Precipitation events were larger and more frequent between July and September.
Daily streamflow data from 16 sites were used to evaluate temporal and spatial variations in streamflow for the water years 2013 and 2014. At all sites, median daily mean streamflow for the 2-year period ranged from 0.0 to 9.60 cubic feet per second. Daily mean streamflow hydrographs are included in this report. Five sites on the Piñon Canyon Maneuver Site were monitored for peak stage using crest-stage gages.
At the Piñon Canyon Maneuver Site, five sites had a stage recorder and precipitation gage, providing a paired streamflow-precipitation dataset. There was a statistically significant correlation between precipitation and streamflow based on Spearman’s rho correlation (rho values ranged from 0.17 to 0.35).
Suspended-sediment samples were collected in April through October for water years 2013–14 at one site at the U.S. Army Garrison Fort Carson and five sites at the Piñon Canyon Maneuver Site. Suspended-sediment-transport curves were used to illustrate the relation between streamflow and suspended-sediment concentration. All these sediment-transport curves showed a streamflow dependent suspended-sediment concentration relation except for the U.S. Geological Survey station Bent Canyon Creek at mouth near Timpas, CO.
Water-quality data were collected and reported from seven sites on the U.S. Army Garrison Fort Carson and the Piñon Canyon Maneuver Site during water years 2013–14. Sample results exceeding an established water-quality standard were identified. Selected water-quality properties and constituents were stratified to compare spatial variation among selected characteristics using boxplots.
Trilinear diagrams were used to classify water type based on ionic concentrations of water-quality samples collected during the study period.
At the U.S. Army Garrison Fort Carson and the Piñon Canyon Maneuver Site, 27 samples were classified as very hard or brackish. Seven samples had a lower hardness character relative to the other samples. Four of those nine samples were collected at two U.S. Geological Survey stations (Turkey Creek near Fountain, CO, and Little Fountain Creek above Highway 115 at Fort Carson, CO), which have different geologic makeup. Three samples collected at the Piñon Canyon Maneuver Site had a markedly lower hardness likely because of dilution from an increase in streamflow.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165145","collaboration":"Prepared in cooperation the U.S. Department of the Army","usgsCitation":"Holmberg, M.J., Stogner, R.W., Sr., and Bruce, J.F., 2016, Characterization and relation of precipitation, streamflow, and water-quality data at the U.S. Army Garrison Fort Carson and Piñon Canyon Maneuver Site, Colorado, water years 2013–14: U.S. Geological Survey Scientific Investigations Report 2016–5145, 58 p., https://doi.org/10.3133/sir20165145.","productDescription":"viii, 58 p.","onlineOnly":"Y","ipdsId":"IP-071890","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":331269,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5145/coverthb.jpg"},{"id":331270,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5145/sir20165145.pdf","text":"Report","size":"6.82 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5145"}],"country":"United States","state":"Colorado","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -104.5,\n 38\n ],\n [\n -104.5,\n 39\n ],\n [\n -105,\n 39\n ],\n [\n -105,\n 38\n ],\n [\n -104.5,\n 38\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -104.2,\n 37.5\n ],\n [\n -104.2,\n 38\n ],\n [\n -103.5,\n 38\n ],\n [\n -103.5,\n 37.5\n ],\n [\n -104.2,\n 37.5\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, USGS Colorado Water Science Center
Box 25046, Mail Stop 415
Denver, CO 80225
Heavy rainfall occurred across Louisiana, Texas, Arkansas, and Mississippi in March 2016 as a result of a slow-moving southward dip in the jetstream, funneling tropical moisture into parts of the Gulf Coast States and the Mississippi River Valley. The storm caused major flooding in the northwestern and southeastern parts of Louisiana and in eastern Texas. Flooding also occurred in the Mississippi River Valley in Arkansas and Mississippi. Over 26 inches of rain were reported near Monroe, Louisiana, over the duration of the storm. In March 2016, U.S. Geological Survey (USGS) hydrographers made more than 500 streamflow measurements in Louisiana, Texas, Arkansas, and Mississippi. Many of those streamflow measurements were made to verify the accuracy of stage-streamflow relations at gaging stations operated by the USGS. Peak streamflows were the highest on record at 14 locations, and streamflows at 29 locations ranked in the top five for the period of record at USGS streamflow-gaging stations analyzed for this report. Following the storm, USGS hydrographers documented 451 high-water marks in Louisiana and on the western side of the Sabine River in Texas. Many of these high-water marks were used to create 19 flood-inundation maps for selected areas of Louisiana and Texas that experienced flooding in March 2016.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165162","collaboration":"Prepared in cooperation with the Federal Emergency Management Administration","usgsCitation":"Breaker, B.K., Watson, K.M., Ensminger, P.A., Storm, J.B., and Rose, C.E., 2016,Characterization of peak streamflows and flood inundation of selected areas in Louisiana, Texas, Arkansas, and Mississippi from flood of March 2016: U.S. Geological Survey Scientific Investigations Report 2016–5162, 33 p. https://doi.org/10.3133/sir20165162.","productDescription":"Report: vi, 33 p.; Data Release","startPage":"1","endPage":"33","numberOfPages":"43","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-080223","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":331216,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5162/coverthb2.jpg"},{"id":331217,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5162/sir20165162.pdf","text":"Report","size":"12.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016–5162"},{"id":331218,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7T43R6C","text":"USGS data release - Flood inundation extent and depth in selected areas of Louisiana, Texas, and Mississippi in March 2016","description":"USGS data release"}],"country":"United States","state":"Arkansas, Louisiana, Mississippi, Texas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88,\n 29\n ],\n [\n -88,\n 35\n ],\n [\n -95,\n 35\n ],\n [\n -95,\n 29\n ],\n [\n -88,\n 29\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Lower Mississippi-Gulf Water Science Center
U.S. Geological Survey
401 Hardin Road
Little Rock, AR 72211
The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Energy, has maintained a water-level monitoring program at the Idaho National Laboratory (INL) since 1949. The purpose of the program is to systematically measure and report water-level data to assess the eastern Snake River Plain aquifer and long term changes in groundwater recharge, discharge, movement, and storage. Water-level data are commonly used to generate potentiometric maps and used to infer increases and (or) decreases in the regional groundwater system. Well deviation is one component of water-level data that is often overlooked and is the result of the well construction and the well not being plumb. Depending on measured slant angle, where well deviation generally increases linearly with increasing slant angle, well deviation can suggest artificial anomalies in the water table. To remove the effects of well deviation, the USGS INL Project Office applies a correction factor to water-level data when a well deviation survey indicates a change in the reference elevation of greater than or equal to 0.2 ft.
Borehole well deviation survey data were considered for 177 wells completed within the eastern Snake River Plain aquifer, but not all wells had deviation survey data available. As of 2016, USGS INL Project Office database includes: 57 wells with gyroscopic survey data; 100 wells with magnetic deviation survey data; 11 wells with erroneous gyroscopic data that were excluded; and, 68 wells with no deviation survey data available. Of the 57 wells with gyroscopic deviation surveys, correction factors for 16 wells ranged from 0.20 to 6.07 ft and inclination angles (SANG) ranged from 1.6 to 16.0 degrees. Of the 100 wells with magnetic deviation surveys, a correction factor for 21 wells ranged from 0.20 to 5.78 ft and SANG ranged from 1.0 to 13.8 degrees, not including the wells that did not meet the correction factor criteria of greater than or equal to 0.20 ft.
Forty-seven wells had gyroscopic and magnetic deviation survey data for the same well. Datasets for both survey types were compared for the same well to determine whether magnetic survey data were consistent with gyroscopic survey data. Of those 47 wells, 96 percent showed similar correction factor estimates (≤ 0.20 ft) for both magnetic and gyroscopic well deviation surveys. A linear comparison of correction factor estimates for both magnetic and gyroscopic deviation well surveys for all 47 wells indicate good linear correlation, represented by an r-squared of 0.88. The correction factor difference between the gyroscopic and magnetic surveys for 45 of 47 wells ranged from 0.00 to 0.18 ft, not including USGS 57 and USGS 125. Wells USGS 57 and USGS 125 show a correction factor difference of 2.16 and 0.36 ft, respectively; however, review of the data files suggest erroneous SANG data for both magnetic deviation well surveys. The difference in magnetic and gyroscopic well deviation SANG measurements, for all wells, ranged from 0.0 to 0.9 degrees. These data indicate good agreement between SANG data measured using the magnetic deviation survey methods and SANG data measured using gyroscopic deviation survey methods, even for surveys collected years apart.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165163","collaboration":"DOE/ID-22241Director, Idaho Water Science Center
U.S. Geological Survey
230 Collins Road
Boise, Idaho 83702
http://id.water.usgs.gov
In 2012, the U.S. Geological Survey, in cooperation with the Arkansas River Basin Regional Resource Planning Group, initiated a study of groundwater and surface-water interaction, water quality, and loading of dissolved solids, selenium, and uranium to Fountain Creek near Pueblo, Colorado, to improve understanding of sources and processes affecting loading of these constituents to streams in the Arkansas River Basin. Fourteen monitoring wells were installed in a series of three transects across Fountain Creek near Pueblo, and temporary streamgages were established at each transect to facilitate data collection for the study. Groundwater and surface-water interaction was characterized by using hydrogeologic mapping, groundwater and stream-surface levels, groundwater and stream temperatures, vertical hydraulic-head gradients and ratios of oxygen and hydrogen isotopes in the hyporheic zone, and streamflow mass-balance measurements. Water quality was characterized by collecting periodic samples from groundwater, surface water, and the hyporheic zone for analysis of dissolved solids, selenium, uranium, and other selected constituents and by evaluating the oxidation-reduction condition for each groundwater sample under different hydrologic conditions throughout the study period. Groundwater loads to Fountain Creek and in-stream loads were computed for the study area, and processes affecting loads of dissolved solids, selenium, and uranium were evaluated on the basis of geology, geochemical conditions, land and water use, and evapoconcentration.
During the study period, the groundwater-flow system generally contributed flow to Fountain Creek and its hyporheic zone (as a single system) except for the reach between the north and middle transects. However, the direction of flow between the stream, the hyporheic zone, and the near-stream aquifer was variable in response to streamflow and stage. During periods of low streamflow, Fountain Creek generally gained flow from groundwater. However, during periods of high streamflow, the hydraulic gradient between groundwater and the stream temporarily reversed, causing the stream to lose flow to groundwater.
Concentrations of dissolved solids, selenium, and uranium in groundwater generally had greater spatial variability than surface water or hyporheic-zone samples, and constituent concentrations in groundwater generally were greater than in surface water. Constituent concentrations in the hyporheic zone typically were similar to or intermediate between concentrations in groundwater and surface water. Concentrations of dissolved solids, selenium, uranium, and other constituents in groundwater samples collected from wells located on the east side of the north monitoring well transect were substantially greater than for other groundwater, surface-water, and hyporheic-zone samples. With one exception, groundwater samples collected from wells on the east side of the north transect exhibited oxic to mixed (oxic-anoxic) conditions, whereas most other groundwater samples exhibited anoxic to suboxic conditions. Concentrations of dissolved solids, selenium, and uranium in surface water generally increased in a downstream direction along Fountain Creek from the north transect to the south transect and exhibited an inverse relation to streamflow with highest concentration occurring during periods of low streamflow and lowest concentrations occurring during periods of high streamflow.
Groundwater loads of dissolved solids, selenium, and uranium to Fountain Creek were small because of the small amount of groundwater flowing to the stream under typical low-streamflow conditions. In-stream loads of dissolved solids, selenium, and uranium in Fountain Creek varied by date, primarily in relation to streamflow at each transect and were much larger than computed constituent loads from groundwater. In-stream loads generally decreased with decreases in streamflow and increased as streamflow increased. In-stream loads of dissolved solids and selenium increased between the north and middle transects but generally decreased between the middle and south transects. By contrast, uranium loads generally decreased between the north and middle transects but increased between the middle and south transects. In-stream load differences between transects appear primarily to be related to differences in streamflow. However, because groundwater typically flows to Fountain Creek under low-flow conditions, and groundwater has greater concentrations of dissolved solids, selenium, and uranium than surface water in Fountain Creek, increases in loads between transects likely are affected by inflow of groundwater to the stream, which can account for a substantial proportion of the in-stream load difference between transects. When loads decreased between transects, the primary cause likely was decreased streamflow as a result of losses to groundwater and flow through the hyporheic zone. However, localized groundwater inflow likely attenuated the magnitude by which the in-stream loads decreased.
The combination of localized soluble geologic sources and oxic conditions likely is the primary reason for the occurrence of high concentrations of dissolved solids, selenium, and uranium in groundwater on the east side of the north monitoring well transect. To evaluate conditions potentially responsible for differences in water quality and redox conditions, physical characteristics such as depth to water, saturated thickness, screen depth below the water table, screen height above bedrock, and aquifer hydraulic conductivity were compared by using Wilcoxon rank-sum tests. Results indicated no significant difference between depth to water, screen height above bedrock, and hydraulic conductivity for groundwater samples collected from wells on the east side of the north transect and groundwater samples from all other wells. However, saturated thickness and screen depth below the water table both were significantly smaller for groundwater samples collected from wells on the east side of the north transect than for groundwater samples from other wells, indicating that these characteristics might be related to the elevated constituent concentrations found at that location. Similarly, saturated thickness and screen depth below the water table were significantly smaller for groundwater samples under oxic or mixed (oxic-anoxic) conditions than for those under anoxic to suboxic conditions.
The greater constituent concentrations at wells on the east side of the north transect also could, in part, be related to groundwater discharge from an unnamed alluvial drainage located directly upgradient from that location. Although the quantity and quality of water discharging from the drainage is not known, the drainage appears to collect water from a residential area located upgradient to the east of the wells, and groundwater could become concentrated in nitrate and other dissolved constituents before flowing through the drainage. High levels of nitrate, whether from anthropogenic or natural geologic sources, could promote more soluble forms of selenium and other constituents by affecting the redox condition of groundwater. Whether oxic conditions at wells on the east side of the north transect are the result of physical characteristics or of groundwater inflow from the alluvial drainage, the oxic conditions appear to cause increased dissolution of minerals from the shallow shale bedrock at that location. Because ratios of hydrogen and oxygen isotopes indicate evaporation likely has not had a substantial effect on groundwater, constituent concentrations at that location likely are not the result of evapoconcentration.
Director, USGS Colorado Water Science Center
Box 25046, Mail Stop 415
Denver, CO 80225