{"pageNumber":"1414","pageRowStart":"35325","pageSize":"25","recordCount":184733,"records":[{"id":70187385,"text":"70187385 - 2014 - Disease and predation: Sorting out causes of a bighorn sheep (Ovis canadensis) decline","interactions":[],"lastModifiedDate":"2017-05-01T12:43:40","indexId":"70187385","displayToPublicDate":"2014-02-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Disease and predation: Sorting out causes of a bighorn sheep (Ovis canadensis) decline","docAbstract":"

Estimating survival and documenting causes and timing of mortality events in neonate bighorn sheep (Ovis canadensis) improves understanding of population ecology and factors influencing recruitment. During 2010–2012, we captured and radiocollared 74 neonates in the Black Hills, South Dakota, of which 95% (70) died before 52 weeks of age. Pneumonia (36%) was the leading cause of mortality followed by predation (30%). We used known fate analysis in Program MARK to estimate weekly survival rates and investigate the influence of intrinsic variables on 52-week survival. Model {S1 wk, 2–8 wks, >8 wks} had the lowest AICc (Akaike’s Information Criterion corrected for small sample size) value, indicating that age (3-stage age-interval: 1 week, 2–8 weeks, and >8 weeks) best explained survival. Weekly survival estimates for 1 week, 2–8 weeks, and >8 weeks were 0.81 (95% CI = 0.70–0.88), 0.86 (95% CI = 0.81–0.90), and 0.94 (95% CI = 0.91–0.96), respectively. Overall probability of surviving 52 weeks was 0.02 (95% CI = 0.01–0.07). Of 70 documented mortalities, 21% occurred during the first week, 55% during weeks 2–8, and 23% occurred >8 weeks of age. We found pneumonia and predation were temporally heterogeneous with lambs most susceptible to predation during the first 2–3 weeks of life, while the greatest risk from pneumonia occurred from weeks 4–8. Our results indicated pneumonia was the major factor limiting recruitment followed by predation. Mortality from predation may have been partly compensatory to pneumonia and its effects were less pronounced as alternative prey became available. Given the high rates of pneumonia-caused mortality we observed, and the apparent lack of pneumonia-causing pathogens in bighorn populations in the western Black Hills, management activities should be geared towards eliminating contact between diseased and healthy populations.

","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0088271","usgsCitation":"Smith, J.B., Jenks, J., Grovenburg, T.W., and Klaver, R.W., 2014, Disease and predation: Sorting out causes of a bighorn sheep (Ovis canadensis) decline: PLoS ONE, v. 9, no. 2, p. 1-9, https://doi.org/10.1371/journal.pone.0088271.","productDescription":"e88271; 9 p.","startPage":"1","endPage":"9","ipdsId":"IP-051866","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":473197,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0088271","text":"Publisher Index Page"},{"id":340672,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"South Dakota","otherGeospatial":"Black Hills","volume":"9","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2014-02-07","publicationStatus":"PW","scienceBaseUri":"59084933e4b0fc4e448ffd86","contributors":{"authors":[{"text":"Smith, Joshua B.","contributorId":71883,"corporation":false,"usgs":true,"family":"Smith","given":"Joshua","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":693754,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jenks, Jonathan A.","contributorId":51591,"corporation":false,"usgs":true,"family":"Jenks","given":"Jonathan A.","affiliations":[],"preferred":false,"id":693755,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Grovenburg, Troy W.","contributorId":57712,"corporation":false,"usgs":true,"family":"Grovenburg","given":"Troy","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":693756,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Klaver, Robert W. 0000-0002-3263-9701 bklaver@usgs.gov","orcid":"https://orcid.org/0000-0002-3263-9701","contributorId":3285,"corporation":false,"usgs":true,"family":"Klaver","given":"Robert","email":"bklaver@usgs.gov","middleInitial":"W.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":693722,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70157106,"text":"70157106 - 2014 - Wildlife connectivity approaches and best practices in U.S. state wildlife action plans","interactions":[],"lastModifiedDate":"2015-09-08T16:22:22","indexId":"70157106","displayToPublicDate":"2014-02-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1321,"text":"Conservation Biology","active":true,"publicationSubtype":{"id":10}},"title":"Wildlife connectivity approaches and best practices in U.S. state wildlife action plans","docAbstract":"

As habitat loss and fragmentation threaten biodiversity on large geographic scales, creating and maintaining connectivity of wildlife populations is an increasingly common conservation objective. To assess the progress and success of large-scale connectivity planning, conservation researchers need a set of plans that cover large geographic areas and can be analyzed as a single data set. The state wildlife action plans (SWAPs) fulfill these requirements. We examined 50 SWAPs to determine the extent to which wildlife connectivity planning, via linkages, is emphasized nationally. We defined linkage as connective land that enables wildlife movement. For our content analysis, we identified and quantified 6 keywords and 7 content criteria that ranged in specificity and were related to linkages for wide-ranging terrestrial vertebrates and examined relations between content criteria and statewide data on focal wide-ranging species, spending, revenue, and conserved land. Our results reflect nationwide disparities in linkage conservation priorities and highlight the continued need for wildlife linkage planning. Only 30% or less of the 50 SWAPs fulfilled highly specific content criteria (e.g., identifying geographic areas for linkage placement or management). We found positive correlations between our content criteria and statewide data on percent conserved land, total focal species, and spending on parks and recreation. We supplemented our content analysis with interviews with 17 conservation professionals to gain specific information about state-specific context and future directions of linkage conservation. Based on our results, relevant literature, and interview responses, we suggest the following best practices for wildlife linkage conservation plans: collect ecologically meaningful background data; be specific; establish community-wide partnerships; and incorporate sociopolitical and socioeconomic information.

","language":"English","publisher":"Wiley","doi":"10.1111/cobi.12204","usgsCitation":"Lacher, I., and Wilkerson, M.L., 2014, Wildlife connectivity approaches and best practices in U.S. state wildlife action plans: Conservation Biology, v. 28, no. 1, p. 13-21, https://doi.org/10.1111/cobi.12204.","productDescription":"9 p.","startPage":"13","endPage":"21","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[],"links":[{"id":307960,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"28","issue":"1","noUsgsAuthors":false,"publicationDate":"2013-12-26","publicationStatus":"PW","scienceBaseUri":"55f006b0e4b0dacf699ea00e","contributors":{"authors":[{"text":"Lacher, Iara","contributorId":147432,"corporation":false,"usgs":false,"family":"Lacher","given":"Iara","email":"","affiliations":[],"preferred":false,"id":571668,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wilkerson, Marit L.","contributorId":147433,"corporation":false,"usgs":false,"family":"Wilkerson","given":"Marit","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":571669,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70181780,"text":"70181780 - 2014 - Thermal-maturity limit for primary thermogenic-gas generation from humic coals as determined by hydrous pyrolysis","interactions":[],"lastModifiedDate":"2017-02-14T10:36:55","indexId":"70181780","displayToPublicDate":"2014-02-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":605,"text":"AAPG Bulletin","printIssn":"0149-1423","active":true,"publicationSubtype":{"id":10}},"title":"Thermal-maturity limit for primary thermogenic-gas generation from humic coals as determined by hydrous pyrolysis","docAbstract":"

Hydrous-pyrolysis experiments at 360°C (680°F) for 72 h were conducted on 53 humic coals representing ranks from lignite through anthracite to determine the upper maturity limit for hydrocarbon-gas generation from their kerogen and associated bitumen (i.e., primary gas generation). These experimental conditions are below those needed for oil cracking to ensure that generated gas was not derived from the decomposition of expelled oil generated from some of the coals (i.e., secondary gas generation). Experimental results showed that generation of hydrocarbon gas ends before a vitrinite reflectance \"BLTN13204eq1\" of 2.0%. This reflectance is equivalent to Rock-Eval maximum-yield temperature \"BLTN13204eq2\" and hydrogen indices (HIs) of 555°C (1031°F) and 35 mg/g total organic carbon (TOC), respectively. At these maturity levels, essentially no soluble bitumen is present in the coals before or after hydrous pyrolysis. The equivalent kerogen atomic H/C ratio is 0.50 at the primary gas-generation limit and indicates that no alkyl moieties are remaining to source hydrocarbon gases. The convergence of atomic H/C ratios of type-II and -I kerogen to this same value at a reflectance of \"BLTN13204eq3\" indicates that the primary gas-generation limits for humic coal and type-III kerogen also apply to oil-prone kerogen. Although gas generation from source rocks does not exceed vitrinite reflectance values greater than \"BLTN13204eq4\", trapped hydrocarbon gases can remain stable at higher reflectance values. Distinguishing trapped gas from generated gas in hydrous-pyrolysis experiments is readily determined by \"BLTN13204eq5\" of the hydrocarbon gases when a \"BLTN13204eq6\"-depleted water is used in the experiments. Water serves as a source of hydrogen in hydrous pyrolysis and, as a result, the use of \"BLTN13204eq7\"-depleted water is reflected in the generated gases but not pre-existing trapped gases.

","language":"English","publisher":"AAPG","doi":"10.1306/06021413204","usgsCitation":"Lewan, M., and Kotarba, M., 2014, Thermal-maturity limit for primary thermogenic-gas generation from humic coals as determined by hydrous pyrolysis: AAPG Bulletin, v. 98, no. 12, p. 2581-2610, https://doi.org/10.1306/06021413204.","productDescription":"30 p.","startPage":"2581","endPage":"2610","ipdsId":"IP-051905","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":335323,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"98","issue":"12","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58a42534e4b0c825128ad434","contributors":{"authors":[{"text":"Lewan, Michael 0000-0001-6347-1553 mlewan@usgs.gov","orcid":"https://orcid.org/0000-0001-6347-1553","contributorId":173938,"corporation":false,"usgs":true,"family":"Lewan","given":"Michael","email":"mlewan@usgs.gov","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":668521,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kotarba, M.J.","contributorId":181531,"corporation":false,"usgs":false,"family":"Kotarba","given":"M.J.","affiliations":[],"preferred":false,"id":668522,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70189780,"text":"70189780 - 2014 - Maximum magnitude earthquakes induced by fluid injection","interactions":[],"lastModifiedDate":"2017-07-26T11:07:34","indexId":"70189780","displayToPublicDate":"2014-02-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2314,"text":"Journal of Geophysical Research B: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Maximum magnitude earthquakes induced by fluid injection","docAbstract":"

Analysis of numerous case histories of earthquake sequences induced by fluid injection at depth reveals that the maximum magnitude appears to be limited according to the total volume of fluid injected. Similarly, the maximum seismic moment seems to have an upper bound proportional to the total volume of injected fluid. Activities involving fluid injection include (1) hydraulic fracturing of shale formations or coal seams to extract gas and oil, (2) disposal of wastewater from these gas and oil activities by injection into deep aquifers, and (3) the development of enhanced geothermal systems by injecting water into hot, low-permeability rock. Of these three operations, wastewater disposal is observed to be associated with the largest earthquakes, with maximum magnitudes sometimes exceeding 5. To estimate the maximum earthquake that could be induced by a given fluid injection project, the rock mass is assumed to be fully saturated, brittle, to respond to injection with a sequence of earthquakes localized to the region weakened by the pore pressure increase of the injection operation and to have a Gutenberg-Richter magnitude distribution with a b value of 1. If these assumptions correctly describe the circumstances of the largest earthquake, then the maximum seismic moment is limited to the volume of injected liquid times the modulus of rigidity. Observations from the available case histories of earthquakes induced by fluid injection are consistent with this bound on seismic moment. In view of the uncertainties in this analysis, however, this should not be regarded as an absolute physical limit.

","language":"English","publisher":"AGU","doi":"10.1002/2013JB010597","usgsCitation":"McGarr, A.F., 2014, Maximum magnitude earthquakes induced by fluid injection: Journal of Geophysical Research B: Solid Earth, v. 119, no. 2, p. 1008-1019, https://doi.org/10.1002/2013JB010597.","productDescription":"12 p.","startPage":"1008","endPage":"1019","ipdsId":"IP-053945","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":473196,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2013jb010597","text":"Publisher Index Page"},{"id":344323,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"119","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2014-02-04","publicationStatus":"PW","scienceBaseUri":"5979aa57e4b0ec1a488b8c37","contributors":{"authors":[{"text":"McGarr, Arthur F. 0000-0001-9769-4093 mcgarr@usgs.gov","orcid":"https://orcid.org/0000-0001-9769-4093","contributorId":3178,"corporation":false,"usgs":true,"family":"McGarr","given":"Arthur","email":"mcgarr@usgs.gov","middleInitial":"F.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":706324,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70059286,"text":"ds810 - 2014 - Compilation of hydrologic data for White Sands pupfish habitat and nonhabitat areas, northern Tularosa Basin, White Sands Missile Range and Holloman Air Force Base, New Mexico, 1911-2008","interactions":[],"lastModifiedDate":"2014-01-31T14:55:56","indexId":"ds810","displayToPublicDate":"2014-01-31T14:42:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"810","title":"Compilation of hydrologic data for White Sands pupfish habitat and nonhabitat areas, northern Tularosa Basin, White Sands Missile Range and Holloman Air Force Base, New Mexico, 1911-2008","docAbstract":"

The White Sands pupfish (Cyprinodon tularosa), listed as threatened by the State of New Mexico and as a Federal species of concern, is endemic to the Tularosa Basin, New Mexico. Because water quality can affect pupfish and the environmental conditions of their habitat, a comprehensive compilation of hydrologic data for pupfish habitat and nonhabitat areas in the northern Tularosa Basin was undertaken by the U.S. Geological Survey in cooperation with White Sands Missile Range.

\n
\n

The four locations within the Tularosa Basin that are known pupfish habitat areas are the Salt Creek, Malpais Spring and Malpais Salt Marsh, Main Mound Spring, and Lost River habitat areas. Streamflow data from the Salt Creek near Tularosa streamflow-gaging station indicated that the average annual mean streamflow and average annual total streamflow for water years 1995–2008 were 1.35 cubic feet per second (ft3/s) and 983 acre-feet, respectively. Periods of no flow were observed in water years 2002 through 2006. Dissolved-solids concentrations in Salt Creek samples collected from 1911 through 2007 ranged from 2,290 to 66,700 milligrams per liter (mg/L).

\n
\n

The average annual mean streamflow and average annual total streamflow at the Malpais Spring near Oscura streamflow-gaging station for water years 2003–8 were 6.81 ft3/s and 584 acre-feet, respectively. Dissolved-solids concentrations for 16 Malpais Spring samples ranged from 3,882 to 5,500 mg/L. Isotopic data for a Malpais Spring near Oscura water sample collected in 1982 indicated that the water was more than 27,900 years old.

\n
\n

Streamflow from Main Mound Spring was estimated at 0.007 ft3/s in 1955 and 1957 and ranged from 0.02 to 0.07 ft3/s from 1996 to 2001. Dissolved-solids concentrations in samples collected between 1955 and 2007 ranged from an estimated 3,760 to 4,240 mg/L in the upper pond and 4,840 to 5,120 mg/L in the lower pond. Isotopic data for a Main Mound Spring water sample collected in 1982 indicated that the water was about 19,600 years old.

\n
\n

Dissolved-solids concentrations of Lost River samples collected from 1984 to 1999 ranged from 8,930 to 118,000 (estimated) mg/L.

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\n

Dissolved-solids concentrations in samples from nonhabitat area sites ranged from 1,740 to 54,200 (estimated) mg/L. In general, water collected from pupfish nonhabitat area sites tends to have larger proportions of calcium, magnesium, and sulfate than water from pupfish habitat area sites. Water from springs associated with mounds in pupfish nonhabitat areas was of a similar type (calcium-sulfate) to water associated with mounds in pupfish habitat areas. Alkali Spring had a sodium-chloride water type, but the proportions of sodium-chloride and magnesium-sulfate are unique as compared to samples from other sites.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds810","collaboration":"Prepared in cooperation with White Sands Missile Range","usgsCitation":"Naus, C., Myers, R.G., Saleh, D., and Myers, N.C., 2014, Compilation of hydrologic data for White Sands pupfish habitat and nonhabitat areas, northern Tularosa Basin, White Sands Missile Range and Holloman Air Force Base, New Mexico, 1911-2008: U.S. Geological Survey Data Series 810, Report: v, 35 p.; 2 Appendixes, https://doi.org/10.3133/ds810.","productDescription":"Report: v, 35 p.; 2 Appendixes","numberOfPages":"44","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"1911-01-01","temporalEnd":"2008-12-31","ipdsId":"IP-014607","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":281855,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/810/"},{"id":281856,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/810/pdf/ds810.pdf"},{"id":281857,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/810/downloads/ds810_appendix1.pdf"},{"id":281866,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds810.jpg"},{"id":281858,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/810/downloads/ds810_appendix2.xlsx"}],"projection":"Universal Transverse Mercator projection","datum":"North American Datum of 1983","country":"United States","state":"New Mexico","otherGeospatial":"Lost River;Main Mound Spring;Malpais Salt Marsh;Malpais Spring;Salt Creek;Tularosa Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -107.6056,31.241 ], [ -107.6056,34.289 ], [ -105.3836,34.289 ], [ -105.3836,31.241 ], [ -107.6056,31.241 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd522fe4b0b290850f45e6","contributors":{"authors":[{"text":"Naus, C.A.","contributorId":47693,"corporation":false,"usgs":true,"family":"Naus","given":"C.A.","affiliations":[],"preferred":false,"id":487653,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Myers, R. G.","contributorId":30642,"corporation":false,"usgs":true,"family":"Myers","given":"R.","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":487652,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Saleh, D.K. 0000-0002-1406-9303","orcid":"https://orcid.org/0000-0002-1406-9303","contributorId":82748,"corporation":false,"usgs":true,"family":"Saleh","given":"D.K.","affiliations":[],"preferred":false,"id":487654,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Myers, N. C.","contributorId":13622,"corporation":false,"usgs":true,"family":"Myers","given":"N.","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":487651,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70074330,"text":"gip155 - 2014 - Flood-tracking chart for the Withlacoochee and Little River Basins in south-central Georgia and northern Florida","interactions":[],"lastModifiedDate":"2016-12-07T12:13:36","indexId":"gip155","displayToPublicDate":"2014-01-31T12:23:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":315,"text":"General Information Product","code":"GIP","onlineIssn":"2332-354X","printIssn":"2332-3531","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"155","title":"Flood-tracking chart for the Withlacoochee and Little River Basins in south-central Georgia and northern Florida","docAbstract":"

The U.S. Geological Survey (USGS), in cooperation with other Federal, State, and local agencies, operates a flood-monitoring system in the Withlacoochee and Little River Basins. This system is a network of automated river stage stations (ten are shown on page 2 of this publication) that transmit stage data through satellite telemetry to the USGS in Atlanta, Georgia and the National Weather Service (NWS) in Peachtree City, Georgia. During floods, the public and emergency response agencies use this information to make decisions about road closures, evacuations, and other public safety issues.

\n
\n

This Withlacoochee and Little River Basins flood-tracking chart can be used by local citizens and emergency response personnel to record the latest river stage and predicted flood-crest information along the Withlacoochee River, Little River, and Okapilco Creek in south-central Georgia and northern Florida. By comparing the current stage (water-surface level above a datum) and predicted flood crest to the recorded peak stages of previous floods, emergency response personnel and residents can make informed decisions concerning the threat to life and property.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/gip155","collaboration":"Prepared in cooperation with the City of Valdosta, Lowndes County, Suwannee River Water Management District, and National Weather Service","usgsCitation":"Gotvald, A.J., McCallum, B.E., and Painter, J.A., 2014, Flood-tracking chart for the Withlacoochee and Little River Basins in south-central Georgia and northern Florida: U.S. Geological Survey General Information Product 155, 2 p., https://doi.org/10.3133/gip155.","productDescription":"2 p.","numberOfPages":"2","ipdsId":"IP-051580","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":281834,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/gip/0155/"},{"id":281835,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/gip/0155/pdf/gip-155.pdf"},{"id":281836,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/gip155.jpg"}],"datum":"North American Vertical Datum of 1988","country":"United States","state":"Florida, Georgia","otherGeospatial":"Little River Basin, Okapilco Creek, Withlacoochee River Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -83.736458,30.26011 ], [ -83.736458,31.854235 ], [ -83.034668,31.854235 ], [ -83.034668,30.26011 ], [ -83.736458,30.26011 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd59b7e4b0b290850f8e4a","contributors":{"authors":[{"text":"Gotvald, Anthony J. 0000-0002-9019-750X agotvald@usgs.gov","orcid":"https://orcid.org/0000-0002-9019-750X","contributorId":1970,"corporation":false,"usgs":true,"family":"Gotvald","given":"Anthony","email":"agotvald@usgs.gov","middleInitial":"J.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":489496,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCallum, Brian E. 0000-0002-8935-0343 bemccall@usgs.gov","orcid":"https://orcid.org/0000-0002-8935-0343","contributorId":1591,"corporation":false,"usgs":true,"family":"McCallum","given":"Brian","email":"bemccall@usgs.gov","middleInitial":"E.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":489495,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Painter, Jaime A. 0000-0001-8883-9158 jpainter@usgs.gov","orcid":"https://orcid.org/0000-0001-8883-9158","contributorId":1466,"corporation":false,"usgs":true,"family":"Painter","given":"Jaime","email":"jpainter@usgs.gov","middleInitial":"A.","affiliations":[{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":489494,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70074531,"text":"ofr20141016 - 2014 - Methow and Columbia Rivers studies: summary of data collection, comparison of database structure and habitat protocols, and impact of additional PIT tag interrogation systems to survival estimates, 2008-2012","interactions":[],"lastModifiedDate":"2014-01-31T12:09:04","indexId":"ofr20141016","displayToPublicDate":"2014-01-31T12:01:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-1016","title":"Methow and Columbia Rivers studies: summary of data collection, comparison of database structure and habitat protocols, and impact of additional PIT tag interrogation systems to survival estimates, 2008-2012","docAbstract":"The U.S. Geological Survey (USGS) received funding from the Bureau of Reclamation (Reclamation) to provide monitoring and evaluation on the effectiveness of stream restoration efforts by Reclamation in the Methow River watershed. This monitoring and evaluation program is designed to partially fulfill Reclamation’s part of the 2008 Biological Opinion for the Federal Columbia River Power System that includes a Reasonable and Prudent Alternative (RPA) to protect listed salmon and steelhead across their life cycle. The target species in the Methow River for the restoration effort include Upper Columbia River (UCR) spring Chinook salmon (Oncorhynchus tshawytscha), UCR steelhead (Oncorhynchus mykiss), and bull trout (Salvelinus confluentus), which are listed as threatened or endangered under the Endangered Species Act.\n\nSince 2004, the USGS has completed two projects of monitoring and evaluation in the Methow River watershed. The first project focused on the evaluation of barrier removal and steelhead recolonization in Beaver Creek with Libby and Gold Creeks acting as controls. The majority of this work was completed by 2008, although some monitoring continued through 2012.\n\nThe second project (2008–2012) evaluated the use and productivity of the middle Methow River reach (rkm 65–80) before the onset of multiple off-channel restoration projects planned by the Reclamation and Yakama Nation. The upper Methow River (upstream of rkm 80) and Chewuch River serve as reference reaches and the Methow River downstream of the Twisp River (downstream of rkm 65) serves as a control reach. Restoration of the M2 reach was initiated in 2012 and will be followed by a multi-year, intensive post-evaluation period.\n\nThis report is comprised of three chapters covering different aspects of the work completed by the USGS. The first chapter is a review of data collection that documents the methods used and summarizes the work done by the USGS from 2008 through 2012. This data summary was designed to show some initial analysis and to disseminate summary information that could potentially be used in ongoing modeling efforts by USGS, Reclamation, and University of Idaho. The second chapter documents the database of fish and habitat data collected by USGS from 2004 through 2012 and compares USGS habitat protocols to the Columbia Habitat Monitoring Program (CHaMP) protocol. The third chapter is a survival analysis of fish moving through Passive Integrated Transponder (PIT) tag interrogation systems in the Methow and Columbia Rivers. It examines the effects of adding PIT tags and/or PIT tag interrogation systems on survival estimates of juvenile steelhead and Chinook salmon.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141016","issn":"2331-1258","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Martens, K.D., Tibbits, W.T., Watson, G.A., Newsom, M.A., and Connolly, P., 2014, Methow and Columbia Rivers studies: summary of data collection, comparison of database structure and habitat protocols, and impact of additional PIT tag interrogation systems to survival estimates, 2008-2012: U.S. Geological Survey Open-File Report 2014-1016, Report: x, 92 p.; 12 appendices, https://doi.org/10.3133/ofr20141016.","productDescription":"Report: x, 92 p.; 12 appendices","numberOfPages":"106","onlineOnly":"Y","temporalStart":"2008-01-01","temporalEnd":"2012-12-31","ipdsId":"IP-051467","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":281830,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141016.png"},{"id":281828,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1016/"},{"id":281829,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1016/pdf/ofr2014-1016.pdf"}],"country":"United States","state":"Washington","otherGeospatial":"Methow River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -120.2117,48.0532 ], [ -120.2117,48.4789 ], [ -119.9268,48.4789 ], [ -119.9268,48.0532 ], [ -120.2117,48.0532 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd66f5e4b0b29085101134","contributors":{"authors":[{"text":"Martens, Kyle D.","contributorId":12740,"corporation":false,"usgs":true,"family":"Martens","given":"Kyle","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":489611,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tibbits, Wesley T. wtibbits@usgs.gov","contributorId":4803,"corporation":false,"usgs":true,"family":"Tibbits","given":"Wesley","email":"wtibbits@usgs.gov","middleInitial":"T.","affiliations":[],"preferred":true,"id":489609,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Watson, Grace A. gwatson@usgs.gov","contributorId":5435,"corporation":false,"usgs":true,"family":"Watson","given":"Grace","email":"gwatson@usgs.gov","middleInitial":"A.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":489610,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Newsom, Michael A.","contributorId":36855,"corporation":false,"usgs":true,"family":"Newsom","given":"Michael","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":489612,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Connolly, Patrick J. 0000-0001-7365-7618 pconnolly@usgs.gov","orcid":"https://orcid.org/0000-0001-7365-7618","contributorId":2920,"corporation":false,"usgs":true,"family":"Connolly","given":"Patrick J.","email":"pconnolly@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":489608,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70073833,"text":"ds820 - 2014 - Nutrient load summaries for major lakes and estuaries of the Eastern United States, 2002","interactions":[],"lastModifiedDate":"2024-04-18T13:52:08.876274","indexId":"ds820","displayToPublicDate":"2014-01-31T10:38:54","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"820","title":"Nutrient load summaries for major lakes and estuaries of the Eastern United States, 2002","docAbstract":"Nutrient enrichment of lakes and estuaries across the Nation is widespread. Nutrient enrichment can stimulate excessive plant and algal growth and cause a number of undesirable effects that impair aquatic life and recreational activities and can also result in economic effects. Understanding the amount of nutrients entering lakes and estuaries, the physical characteristics affecting the nutrient processing within these receiving waterbodies, and the natural and manmade sources of nutrients is fundamental to the development of effective nutrient reduction strategies. To improve this understanding, sources and stream transport of nutrients to 255 major lakes and 64 estuaries in the Eastern United States were estimated using Spatially Referenced Regression on Watershed attributes (SPARROW) nutrient models.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds820","collaboration":"National Water-Quality Assessment Program","usgsCitation":"Moorman, M.C., Hoos, A.B., Bricker, S.B., Moore, R.B., García, A., and Ator, S.W., 2014, Nutrient load summaries for major lakes and estuaries of the Eastern United States, 2002: U.S. Geological Survey Data Series 820, Report: iv, 10 p.; Table 3A & 3B; 2 Appendices, https://doi.org/10.3133/ds820.","productDescription":"Report: iv, 10 p.; Table 3A & 3B; 2 Appendices","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-049636","costCenters":[{"id":476,"text":"North Carolina Water Science Center","active":true,"usgs":true}],"links":[{"id":281809,"rank":6,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0820/"},{"id":281810,"rank":5,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0820/pdf/ds820_text-only.pdf"},{"id":281814,"rank":1,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/0820/pdf/ds820_appendix_south-only.pdf"},{"id":281813,"rank":2,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/0820/pdf/ds820_appendix_north-middle-only.pdf"},{"id":281812,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/0820/table/ds820_table3B_estuaries.xlsx"},{"id":281811,"rank":4,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/0820/table/ds820_table3A_lakes.xlsx"},{"id":281815,"rank":7,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds820.jpg"}],"country":"United States","otherGeospatial":"Eastern United 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[\n -73.96557206018338,\n 39.84272655583905\n ],\n [\n -69.48092629613068,\n 41.16961893182622\n ],\n [\n -70.31119797078843,\n 42.66860642440693\n ],\n [\n -69.6824637110146,\n 43.6864735992915\n ],\n [\n -66.85540939258277,\n 44.638899826715175\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd696be4b0b29085102ab4","contributors":{"authors":[{"text":"Moorman, Michelle C. mmoorman@usgs.gov","contributorId":4970,"corporation":false,"usgs":true,"family":"Moorman","given":"Michelle","email":"mmoorman@usgs.gov","middleInitial":"C.","affiliations":[{"id":476,"text":"North Carolina Water Science Center","active":true,"usgs":true}],"preferred":true,"id":489104,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hoos, Anne B. abhoos@usgs.gov","contributorId":2236,"corporation":false,"usgs":true,"family":"Hoos","given":"Anne","email":"abhoos@usgs.gov","middleInitial":"B.","affiliations":[],"preferred":true,"id":489103,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bricker, Suzanne B.","contributorId":64555,"corporation":false,"usgs":false,"family":"Bricker","given":"Suzanne","email":"","middleInitial":"B.","affiliations":[{"id":12448,"text":"U.S. National Oceanic and Atmospheric Administration","active":true,"usgs":false}],"preferred":false,"id":489106,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Moore, Richard B. rmoore@usgs.gov","contributorId":1464,"corporation":false,"usgs":true,"family":"Moore","given":"Richard","email":"rmoore@usgs.gov","middleInitial":"B.","affiliations":[{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":489102,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"García, Ana María","contributorId":9172,"corporation":false,"usgs":true,"family":"García","given":"Ana María","affiliations":[],"preferred":false,"id":489105,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ator, Scott W. 0000-0002-9186-4837 swator@usgs.gov","orcid":"https://orcid.org/0000-0002-9186-4837","contributorId":781,"corporation":false,"usgs":true,"family":"Ator","given":"Scott","email":"swator@usgs.gov","middleInitial":"W.","affiliations":[{"id":375,"text":"Maryland, Delaware, and the District of Columbia Water Science Center","active":false,"usgs":true}],"preferred":false,"id":489101,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70072584,"text":"ds819 - 2014 - Benthic-invertebrate, fish-community, and streambed-sediment-chemistry data for streams in the Indianapolis metropolitan area, Indiana, 2009–2012","interactions":[],"lastModifiedDate":"2014-02-03T10:18:46","indexId":"ds819","displayToPublicDate":"2014-01-31T10:16:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"819","title":"Benthic-invertebrate, fish-community, and streambed-sediment-chemistry data for streams in the Indianapolis metropolitan area, Indiana, 2009–2012","docAbstract":"Aquatic-biology and sediment-chemistry data were collected at seven sites on the White River and at six tributary sites in the Indianapolis metropolitan area of Indiana during the period 2009 through 2012. Data collected included benthic-invertebrate and fish-community information and concentrations of metals, insecticides, herbicides, and semivolatile organic compounds adsorbed to streambed sediments. A total of 120 benthic-invertebrate samples were collected, of which 16 were replicate samples. A total of 26 fish-community samples were collected in 2010 and 2012. Thirty streambed-sediment chemistry samples were collected in 2009 and 2011, of which four were concurrent duplicate samples","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds819","collaboration":"Prepared in cooperation with the Indianapolis Department of Public Works and CWA Authority, Inc.","usgsCitation":"Voelker, D.C., 2014, Benthic-invertebrate, fish-community, and streambed-sediment-chemistry data for streams in the Indianapolis metropolitan area, Indiana, 2009–2012: U.S. Geological Survey Data Series 819, Report: ix, 8 p.; 4 Appendices, https://doi.org/10.3133/ds819.","productDescription":"Report: ix, 8 p.; 4 Appendices","numberOfPages":"17","onlineOnly":"Y","ipdsId":"IP-035683","costCenters":[{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":281808,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds819.jpg"},{"id":281805,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/0819/tables/ds819_table2"},{"id":281804,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/0819/tables/ds819_table1"},{"id":281802,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0819/"},{"id":281803,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0819/pdf/ds819.pdf"},{"id":281806,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/0819/tables/ds819_table3"},{"id":281807,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/0819/tables/ds819_table4"}],"country":"United States","state":"Indiana","city":"Indianapolis","otherGeospatial":"White River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -86.4,39.5 ], [ -86.4,40.0 ], [ -86.0,40.0 ], [ -86.0,39.5 ], [ -86.4,39.5 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd4f34e4b0b290850f28fb","contributors":{"authors":[{"text":"Voelker, David C. dvoelker@usgs.gov","contributorId":278,"corporation":false,"usgs":true,"family":"Voelker","given":"David","email":"dvoelker@usgs.gov","middleInitial":"C.","affiliations":[{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":488504,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70074638,"text":"70074638 - 2014 - A Great Lakes atmospheric mercury monitoring network: evaluation and design","interactions":[],"lastModifiedDate":"2014-01-31T09:10:27","indexId":"70074638","displayToPublicDate":"2014-01-31T09:07:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":924,"text":"Atmospheric Environment","active":true,"publicationSubtype":{"id":10}},"title":"A Great Lakes atmospheric mercury monitoring network: evaluation and design","docAbstract":"As many as 51 mercury (Hg) wet-deposition-monitoring sites from 4 networks were operated in 8 USA states and Ontario, Canada in the North American Great Lakes Region from 1996 to 2010. By 2013, 20 of those sites were no longer in operation and approximately half the geographic area of the Region was represented by a single Hg-monitoring site. In response, a Great Lakes Atmospheric Mercury Monitoring (GLAMM) network is needed as a framework for regional collaboration in Hg-deposition monitoring. The purpose of the GLAMM network is to detect changes in regional atmospheric Hg deposition related to changes in Hg emissions. An optimized design for the network was determined to be a minimum of 21 sites in a representative and approximately uniform geographic distribution. A majority of the active and historic Hg-monitoring sites in the Great Lakes Region are part of the National Atmospheric Deposition Program (NADP) Mercury Deposition Network (MDN) in North America and the GLAMM network is planned to be part of the MDN.\n\nTo determine an optimized network design, active and historic Hg-monitoring sites in the Great Lakes Region were evaluated with a rating system of 21 factors that included characteristics of the monitoring locations and interpretations of Hg data. Monitoring sites were rated according to the number of Hg emissions sources and annual Hg emissions in a geographic polygon centered on each site. Hg-monitoring data from the sites were analyzed for long-term averages in weekly Hg concentrations in precipitation and weekly Hg-wet deposition, and on significant temporal trends in Hg concentrations and Hg deposition. A cluster analysis method was used to group sites with similar variability in their Hg data in order to identify sites that were unique for explaining Hg data variability in the Region. The network design included locations in protected natural areas, urban areas, Great Lakes watersheds, and in proximity to areas with a high density of annual Hg emissions and areas with high average weekly Hg wet deposition. In a statistical analysis, relatively strong, positive correlations in the wet deposition of Hg and sulfate were shown for co-located NADP Hg-monitoring and acid-rain monitoring sites in the Region. This finding indicated that efficiency in regional Hg monitoring can be improved by adding new Hg monitoring to existing NADP acid-rain monitoring sites.\n\nImplementation of the GLAMM network design will require Hg-wet-deposition monitoring to be: (a) continued at 12 MDN sites active in 2013 and (b) restarted or added at 9 NADP sites where it is absent in 2013. Ongoing discussions between the states in the Great Lakes Region, the Lake Michigan Air Directors Consortium (a regional planning entity), the NADP, the U.S. Environmental Protection Agency, and the U.S. Geological Survey are needed for coordinating the GLAMM network.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Atmospheric Environment","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.atmosenv.2013.11.050","usgsCitation":"Risch, M.R., Kenski, D., Gay, and David, A., 2014, A Great Lakes atmospheric mercury monitoring network: evaluation and design: Atmospheric Environment, v. 85, p. 109-122, https://doi.org/10.1016/j.atmosenv.2013.11.050.","productDescription":"14 p.","startPage":"109","endPage":"122","numberOfPages":"14","ipdsId":"IP-040074","costCenters":[{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":473200,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.atmosenv.2013.11.050","text":"Publisher Index Page"},{"id":281787,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":281732,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.atmosenv.2013.11.050"}],"country":"United States","otherGeospatial":"Great Lakes","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -95.0,35.0 ], [ -95.0,50.0 ], [ -70.0,50.0 ], [ -70.0,35.0 ], [ -95.0,35.0 ] ] ] } } ] }","volume":"85","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52ecc5e1e4b0e27c8af28a68","contributors":{"authors":[{"text":"Risch, Martin R. 0000-0002-7908-7887 mrrisch@usgs.gov","orcid":"https://orcid.org/0000-0002-7908-7887","contributorId":2118,"corporation":false,"usgs":true,"family":"Risch","given":"Martin","email":"mrrisch@usgs.gov","middleInitial":"R.","affiliations":[{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true},{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":489630,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kenski, Donna M.","contributorId":101992,"corporation":false,"usgs":true,"family":"Kenski","given":"Donna M.","affiliations":[],"preferred":false,"id":489633,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gay","contributorId":128216,"corporation":true,"usgs":false,"organization":"Gay","id":535625,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"David, A.","contributorId":84270,"corporation":false,"usgs":true,"family":"David","given":"A.","email":"","affiliations":[],"preferred":false,"id":489631,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70173748,"text":"70173748 - 2014 - Acceptability of residential development in a regional landscape: Potential effects on wildlife occupancy patterns","interactions":[],"lastModifiedDate":"2016-06-09T14:14:47","indexId":"70173748","displayToPublicDate":"2014-01-31T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Acceptability of residential development in a regional landscape: Potential effects on wildlife occupancy patterns","docAbstract":"

The conversion of natural lands to developed uses may pose the single greatest human threat to global terrestrial biodiversity. Continued human growth and development over the next century will further exacerbate these effects of habitat loss and fragmentation. Natural resource managers are tasked with managing wildlife as a public trust, yet often have little say in land use decisions. Generally speaking, decision makers could benefit from an understanding of what different regulations mean in terms of wildlife distribution. In a previous paper (Bettigole et al., 2013), we surveyed town residents throughout Vermont to measure how respondents feel about a range of development levels within their town boundaries. We estimated the “social carrying capacity for development” – orSKd – for 251 towns in Vermont. SKd provides an estimate of the level of developed land cover classes that town residents deem “acceptable” within their town boundaries. In this paper, we design a framework for linking the town-specific SKd estimates with the wildlife distribution patterns for three wide-ranging mammalian species: American black bear (Ursus americanus), fisher (Martes pennanti), and bobcat (Lynx rufus). We simulated landscape conditions at SKd for each town in Vermont, and then used existing occupancy models for the three target species to spatially map and compare occupancy rates in the baseline year 2000 with occupancy rates at SKd. With nearly 90% of Vermont towns willing to increase developed landcover classes within town boundaries compared to baseline levels, significant state-wide changes in occupancy rates were predicted for all three focal species. Average occupancy rates declined by −15.9% and −3.1% for black bear and bobcats, respectively. Average occupancy rates for fisher increased by 9.0%. This study provides a method for linking development standards within a town with wildlife occurrence. Across towns, the methodology spatially identifies areas that may be at risk of future development, as well as identifying areas where wildlife distribution patterns may face future change as a result of increased human population growth and development.

","language":"English","publisher":"Elseiver","doi":"10.1016/j.biocon.2013.07.029","usgsCitation":"Bettigole, C.A., Donovan, T., Manning, R., Austin, J., and Long, R., 2014, Acceptability of residential development in a regional landscape: Potential effects on wildlife occupancy patterns: Biological Conservation, v. 169, p. 401-409, https://doi.org/10.1016/j.biocon.2013.07.029.","productDescription":"9 p.","startPage":"401","endPage":"409","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-040028","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":323385,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"169","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"575a932fe4b04f417c27511c","contributors":{"authors":[{"text":"Bettigole, Charles A.","contributorId":171660,"corporation":false,"usgs":false,"family":"Bettigole","given":"Charles","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":638230,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Donovan, Therese tdonovan@usgs.gov","contributorId":171599,"corporation":false,"usgs":true,"family":"Donovan","given":"Therese","email":"tdonovan@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":638060,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Manning, Robert","contributorId":171662,"corporation":false,"usgs":false,"family":"Manning","given":"Robert","affiliations":[],"preferred":false,"id":638231,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Austin, John","contributorId":171664,"corporation":false,"usgs":false,"family":"Austin","given":"John","affiliations":[],"preferred":false,"id":638232,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Long, Robert","contributorId":171665,"corporation":false,"usgs":false,"family":"Long","given":"Robert","affiliations":[],"preferred":false,"id":638233,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70189268,"text":"70189268 - 2014 - Understanding uncertainties in future Colorado River streamflow","interactions":[],"lastModifiedDate":"2017-07-07T11:57:09","indexId":"70189268","displayToPublicDate":"2014-01-31T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1112,"text":"Bulletin of the American Meteorological Society","onlineIssn":"1520-0477","printIssn":"0003-0007","active":true,"publicationSubtype":{"id":10}},"title":"Understanding uncertainties in future Colorado River streamflow","docAbstract":"The Colorado River is the primary water source for more than 30 million people in the United States and Mexico. Recent studies that project streamf low changes in the Colorado River all project annual declines, but the magnitude of the projected decreases range from less than 10% to 45% by the mid-twenty-first century. To understand these differences, we address the questions the management community has raised: Why is there such a wide range of projections of impacts of future climate change on Colorado River streamflow, and how should this uncertainty be interpreted? We identify four major sources of disparities among studies that arise from both methodological and model differences. In order of importance, these are differences in 1) the global climate models (GCMs) and emission scenarios used; 2) the ability of land surface and atmospheric models to simulate properly the high-elevation runoff source areas; 3) the sensitivities of land surface hydrology models to precipitation and temperature changes; and 4) the methods used to statistically downscale GCM scenarios. In accounting for these differences, there is substantial evidence across studies that future Colorado River streamflow will be reduced under the current trajectories of anthropogenic greenhouse gas emissions because of a combination of strong temperature-induced runoff curtailment and reduced annual precipitation. Reconstructions of preinstrumental streamflows provide additional insights; the greatest risk to Colorado River streamf lows is a multidecadal drought, like that observed in paleoreconstructions, exacerbated by a steady reduction in flows due to climate change. This could result in decades of sustained streamflows much lower than have been observed in the ~100 years of instrumental record.","language":"English","publisher":"American Meteorological Society","doi":"10.1175/BAMS-D-12-00228.1","usgsCitation":"Julie A. Vano, Bradley Udall, Cayan, D., Overpeck, J.T., Brekke, L., Das, T., Hartmann, H.C., Hidalgo, H.G., Hoerling, M., McCabe, G., Morino, K., Webb, R.S., Werner, K., and Lettenmaier, D.P., 2014, Understanding uncertainties in future Colorado River streamflow: Bulletin of the American Meteorological Society, v. 95, no. 1, p. 59-78, https://doi.org/10.1175/BAMS-D-12-00228.1.","productDescription":"20 p. ","startPage":"59","endPage":"78","ipdsId":"IP-044796","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":473201,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1175/bams-d-12-00228.1","text":"Publisher Index Page"},{"id":343471,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Colorado River ","volume":"95","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59609db9e4b0d1f9f0594c44","contributors":{"authors":[{"text":"Julie A. Vano","contributorId":194362,"corporation":false,"usgs":false,"family":"Julie A. Vano","affiliations":[],"preferred":false,"id":703826,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bradley Udall","contributorId":194360,"corporation":false,"usgs":false,"family":"Bradley Udall","affiliations":[],"preferred":false,"id":703824,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cayan, Daniel drcayan@usgs.gov","contributorId":149912,"corporation":false,"usgs":true,"family":"Cayan","given":"Daniel","email":"drcayan@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":703821,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Overpeck, Jonathan T","contributorId":194361,"corporation":false,"usgs":false,"family":"Overpeck","given":"Jonathan","email":"","middleInitial":"T","affiliations":[],"preferred":false,"id":703825,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brekke, Levi D.","contributorId":35847,"corporation":false,"usgs":true,"family":"Brekke","given":"Levi D.","affiliations":[],"preferred":false,"id":703836,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Das, Tapash","contributorId":194364,"corporation":false,"usgs":false,"family":"Das","given":"Tapash","email":"","affiliations":[],"preferred":false,"id":703837,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hartmann, Holly C.","contributorId":194365,"corporation":false,"usgs":false,"family":"Hartmann","given":"Holly","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":703838,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hidalgo, Hugo G.","contributorId":194367,"corporation":false,"usgs":false,"family":"Hidalgo","given":"Hugo","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":703839,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hoerling, Martin P","contributorId":145843,"corporation":false,"usgs":false,"family":"Hoerling","given":"Martin P","affiliations":[{"id":16257,"text":"NOAA Earth System Research Laboratory, Boulder, Colorado","active":true,"usgs":false}],"preferred":false,"id":703840,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"McCabe, Gregory J. 0000-0002-9258-2997 gmccabe@usgs.gov","orcid":"https://orcid.org/0000-0002-9258-2997","contributorId":1453,"corporation":false,"usgs":true,"family":"McCabe","given":"Gregory J.","email":"gmccabe@usgs.gov","affiliations":[{"id":218,"text":"Denver Federal Center","active":false,"usgs":true}],"preferred":false,"id":703841,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Morino, Kiyomi","contributorId":78210,"corporation":false,"usgs":true,"family":"Morino","given":"Kiyomi","email":"","affiliations":[],"preferred":false,"id":703842,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Webb, Robert S.","contributorId":72894,"corporation":false,"usgs":true,"family":"Webb","given":"Robert","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":703843,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Werner, Kevin","contributorId":194369,"corporation":false,"usgs":false,"family":"Werner","given":"Kevin","email":"","affiliations":[],"preferred":false,"id":703844,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Lettenmaier, Dennis P.","contributorId":139779,"corporation":false,"usgs":false,"family":"Lettenmaier","given":"Dennis","email":"","middleInitial":"P.","affiliations":[{"id":12763,"text":"University of California, Los Angeles","active":true,"usgs":false}],"preferred":false,"id":703845,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}} ,{"id":70188811,"text":"70188811 - 2014 - Phanerozoic continental growth and gold metallogeny of Asia","interactions":[],"lastModifiedDate":"2017-06-26T13:09:07","indexId":"70188811","displayToPublicDate":"2014-01-31T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1848,"text":"Gondwana Research","active":true,"publicationSubtype":{"id":10}},"title":"Phanerozoic continental growth and gold metallogeny of Asia","docAbstract":"

The Asian continent formed during the past 800 m.y. during late Neoproterozoic through Jurassic closure of the Tethyan ocean basins, followed by late Mesozoic circum-Pacific and Cenozoic Himalayan orogenies. The oldest gold deposits in Asia reflect accretionary events along the margins of the Siberia, Kazakhstan, North China, Tarim–Karakum, South China, and Indochina Precambrian blocks while they were isolated within the Paleotethys and surrounding Panthalassa Oceans. Orogenic gold deposits are associated with large-scale, terrane-bounding fault systems and broad areas of deformation that existed along many of the active margins of the Precambrian blocks. Deposits typically formed during regional transpressional to transtensional events immediately after to as much as 100 m.y. subsequent to the onset of accretion or collision. Major orogenic gold provinces associated with this growth of the Asian continental mass include: (1) the ca. 750 Ma Yenisei Ridge, ca. 500 Ma East Sayan, and ca. 450–350 Ma Patom provinces along the southern margins of the Siberia craton; (2) the 450 Ma Charsk belt of north-central Kazakhstan; (3) the 310–280 Ma Kalba belt of NE Kazakhstan, extending into adjacent NW Xinjiang, along the Siberia–Kazakhstan suture; (4) the ca. 300–280 Ma deposits within the Central Asian southern and middle Tien Shan (e.g., Kumtor, Zarmitan, Muruntau), marking the closure of the Turkestan Ocean between Kazakhstan and the Tarim–Karakum block; (5) the ca. 190–125 Ma Transbaikal deposits along the site of Permian to Late Jurassic diachronous closure of the Mongol–Okhotsk Ocean between Siberia and Mongolia/North China; (6) the probable Late Silurian–Early Devonian Jiagnan belt formed along the margin of Gondwana at the site of collision between the Yangtze and Cathaysia blocks; (7) Triassic deposits of the Paleozoic Qilian Shan and West Qinling orogens along the SW margin of the North China block developed during collision of South China; and (8) Jurassic(?) ores on the margins of the Subumusu block in Myanmar and Malaysia. Circum-Pacific tectonism led to major orogenic gold province formation along the length of the eastern side of Asia between ca. 135 and 120 Ma, although such deposits are slightly older in South Korea and slightly younger in the Amur region of the Russian Southeast. Deformation related to collision of the Kolyma–Omolon microcontinent with the Pacific margin of the Siberia craton led to formation of 136–125 Ma ores of the Yana–Kolyma belt (Natalka, Sarylakh) and 125–119 Ma ores of the South Verkhoyansk synclinorium (Nezhdaninskoe). Giant ca. 125 Ma gold provinces developed in the Late Archean uplifted basement of the decratonized North China block, within its NE edge and into adjacent North Korea, in the Jiaodong Peninsula, and in the Qinling Mountains. The oldest gold-bearing magmatic–hydrothermal deposits of Asia include the ca. 485 Ma Duobaoshan porphyry within a part of the Tuva–Mongol arc, ca. 355 Ma low-sulfidation epithermal deposits (Kubaka) of the Omolon terrane accreted to eastern Russia, and porphyries (Bozshakol, Taldy Bulak) within Ordovican to Early Devonian oceanic arcs formed off the Kazakhstan microcontinent. The Late Devonian to Carboniferous was marked by widespread gold-rich porphyry development along the margins of the closing Ob–Zaisan, Junggar–Balkhash, and Turkestan basins (Amalyk, Oyu Tolgoi); most were formed in continental arcs, although the giant Oyu Tolgoi porphyry was part of a near-shore oceanic arc. Permian subduction-related deformation along the east side of the Indochina block led to ca. 300 Ma gold-bearing skarn and disseminated gold ore formation in the Truong Son fold belt of Laos, and along the west side to ca. 250 Ma gold-bearing skarns and epithermal deposits in the Loei fold belt of Laos and Thailand. In the Mesozoic Transbaikal region, extension along the basin margins subsequent to Mongol–Okhotsk closure was associated with ca. 150–125 Ma formation of important auriferous epithermal (Balei), skarn (Bystray), and porphyry (Kultuminskoe) deposits. In northeastern Russia, Early Cretaceous Pacific margin subduction and Late Cretaceous extension were associated with epithermal gold-deposit formation in the Uda–Murgal (Julietta) and Okhotsk–Chukotka (Dukat, Kupol) volcanic belts, respectively. In southeastern Russia, latest Cretaceous to Oligocene extension correlates with other low-sulfidation epithermal ores that formed in the East Sikhote–Alin volcanic belt. Other extensional events, likely related to changing plate dynamics along the Pacific margin of Asia, relate to epithermal–skarn–porphyry districts that formed at ca. 125–85 Ma in northeastmost China and ca. 105–90 Ma in the Coast Volcanic belt of SE China. The onset of strike slip along a part of the southeastern Pacific margin appears to correlate with the giant 148–135 Ma gold-rich porphyry–skarn province of the lower and middle Yangtze River. It is still controversial as to whether true Carlin-like gold deposits exist in Asia. Those deposits that most closely resemble the Nevada (USA) ores are those in the Permo-Triassic Youjiang basin of SW China and NE Vietnam, and are probably Late Triassic in age, although this is not certain. Other Carlin-like deposits have been suggested to exist in the Sepon basin of Laos and in the Mongol–Okhotsk region (Kuranakh) of Transbaikal.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.gr.2013.03.002","usgsCitation":"Goldfarb, R.J., Taylor, R.D., Collins, G.S., Goryachev, N.A., and Orlandini, O., 2014, Phanerozoic continental growth and gold metallogeny of Asia: Gondwana Research, v. 25, no. 1, p. 48-102, https://doi.org/10.1016/j.gr.2013.03.002.","productDescription":"55 p. ","startPage":"48","endPage":"102","ipdsId":"IP-042602","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":342894,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Asia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 78.57421875,\n 3.8642546157214084\n ],\n [\n 101.953125,\n -7.885147283424331\n ],\n [\n 107.22656249999999,\n -6.839169626342808\n ],\n [\n 107.22656249999999,\n -2.6357885741666065\n ],\n [\n 106.34765625,\n 2.28455066023697\n ],\n [\n 111.4453125,\n 11.005904459659451\n ],\n [\n 117.42187500000001,\n 16.636191878397664\n ],\n [\n 133.41796874999997,\n 29.53522956294847\n ],\n [\n 139.74609375,\n 32.54681317351514\n ],\n [\n 144.4921875,\n 37.85750715625203\n ],\n [\n 146.6015625,\n 42.94033923363181\n ],\n [\n 144.4921875,\n 44.96479793033101\n ],\n [\n 141.85546875,\n 45.460130637921004\n ],\n [\n 135.17578125,\n 46.31658418182218\n ],\n [\n 133.76953125,\n 46.6795944656402\n ],\n [\n 130.95703125,\n 48.3416461723746\n ],\n [\n 128.49609375,\n 49.61070993807422\n ],\n [\n 125.68359374999999,\n 52.696361078274485\n ],\n [\n 121.11328124999999,\n 52.16045455774706\n ],\n [\n 118.828125,\n 49.61070993807422\n ],\n [\n 117.0703125,\n 48.80686346108517\n ],\n [\n 118.125,\n 48.45835188280866\n ],\n [\n 120.234375,\n 47.635783590864854\n ],\n [\n 118.828125,\n 47.040182144806664\n ],\n [\n 115.31249999999999,\n 45.460130637921004\n ],\n [\n 111.62109375,\n 43.197167282501276\n ],\n [\n 108.28125,\n 42.16340342422401\n ],\n [\n 101.25,\n 42.293564192170095\n ],\n [\n 92.28515625,\n 44.96479793033101\n ],\n [\n 89.296875,\n 47.87214396888731\n ],\n [\n 86.8359375,\n 48.80686346108517\n ],\n [\n 84.375,\n 47.517200697839414\n ],\n [\n 80.68359375,\n 49.83798245308484\n ],\n [\n 77.16796875,\n 53.54030739150022\n ],\n [\n 74.53125,\n 52.16045455774706\n ],\n [\n 72.24609375,\n 49.61070993807422\n ],\n [\n 71.89453125,\n 47.989921667414194\n ],\n [\n 68.02734375,\n 40.84706035607122\n ],\n [\n 65.21484375,\n 37.16031654673677\n ],\n [\n 63.369140625,\n 35.24561909420681\n ],\n [\n 64.86328125,\n 33.87041555094183\n ],\n [\n 68.37890625,\n 32.99023555965106\n ],\n [\n 70.224609375,\n 31.80289258670676\n ],\n [\n 69.169921875,\n 28.69058765425071\n ],\n [\n 67.67578124999999,\n 27.059125784374068\n ],\n [\n 67.5,\n 24.44714958973082\n ],\n [\n 68.90625,\n 21.12549763660628\n ],\n [\n 71.015625,\n 19.80805412808859\n ],\n [\n 73.125,\n 11.178401873711785\n ],\n [\n 78.57421875,\n 3.8642546157214084\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"25","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59521d23e4b062508e3c36b0","contributors":{"authors":[{"text":"Goldfarb, Richard J. goldfarb@usgs.gov","contributorId":1205,"corporation":false,"usgs":true,"family":"Goldfarb","given":"Richard","email":"goldfarb@usgs.gov","middleInitial":"J.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":700460,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Taylor, Ryan D. 0000-0002-8845-5290 rtaylor@usgs.gov","orcid":"https://orcid.org/0000-0002-8845-5290","contributorId":3412,"corporation":false,"usgs":true,"family":"Taylor","given":"Ryan","email":"rtaylor@usgs.gov","middleInitial":"D.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":700679,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Collins, Gregory S.","contributorId":193511,"corporation":false,"usgs":false,"family":"Collins","given":"Gregory","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":700680,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Goryachev, Nicolay A.","contributorId":193512,"corporation":false,"usgs":false,"family":"Goryachev","given":"Nicolay","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":700681,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Orlandini, Omero Felipe","contributorId":193513,"corporation":false,"usgs":false,"family":"Orlandini","given":"Omero Felipe","affiliations":[],"preferred":false,"id":700682,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70192062,"text":"70192062 - 2014 - Distal facies variability within the Upper Triassic part of the Otuk Formation in northern Alaska","interactions":[],"lastModifiedDate":"2018-05-07T20:59:17","indexId":"70192062","displayToPublicDate":"2014-01-31T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Distal facies variability within the Upper Triassic part of the Otuk Formation in northern Alaska","docAbstract":"

The Triassic-Jurassic Otuk Formation is a potentially important source rock in allochthonous structural positions in the northern foothills of the Brooks Range in the North Slope of Alaska. This study focuses on three localities of the Upper Triassic (Norian) limestone member, which form a present-day, 110-km-long, east-west transect in the central Brooks Range. All three sections are within the structurally lowest Endicott Mountain allochthon and are interpreted to have been deposited along a marine outer shelf with a ramp geometry.

The uppermost limestone member of the Otuk was chosen for this study in order to better understand lateral and vertical variability within carbonate source rocks, to aid prediction of organic richness, and ultimately, to evaluate the potential for these units to act as continuous (or unconventional) reservoirs. At each locality, 1 to 4 m sections of the limestone member were measured and sampled in detail to capture fine-scale features. Hand sample and thin section descriptions reveal four major microfacies in the study area, and one diagenetically recrystallized microfacies. Microfacies 1 and 2 are interpreted to represent redeposition of material by downslope transport, whereas microfacies 3 and 4 have high total organic carbon (TOC) values and are classified as primary depositional organofacies. Microfacies 3 is interpreted to have been deposited under primarily high productivity conditions, with high concentrations of radiolarian tests. Microfacies 4 was deposited under the lowest relative-oxygen conditions, but abundant thin bivalve shells indicate that the sediment-water interface was probably not anoxic.

The Otuk Formation is interpreted to have been deposited outboard of a southwest-facing ramp margin, with the location of the three limestone outcrops likely in relatively close proximity during deposition. All three sections have evidence of transported material, implying that the Triassic Alaskan Basin was not a low-energy, deep-water setting, but rather a dynamic system with intermittent, yet significant, downslope flow. Upwelling played an important role in the small-scale vertical variability in microfacies. The zone of upwelling and resultant oxygen-minimum zone may have migrated across the ramp during fourth- or fifth-order sea-level changes.

","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Deposits, architecture, and controls of carbonate margin, slope and basinal settings","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"SEPM Society for Sedimentary Geology","doi":"10.2110/sepmsp.105.16","usgsCitation":"Whidden, K.J., Dumoulin, J.A., Whalen, M., Hutton, E., Moore, T.E., and Gaswirth, S.B., 2014, Distal facies variability within the Upper Triassic part of the Otuk Formation in northern Alaska, chap. of Deposits, architecture, and controls of carbonate margin, slope and basinal settings, v. 105, https://doi.org/10.2110/sepmsp.105.16.","ipdsId":"IP-037443","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":348875,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Otuk Formation","volume":"105","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2014-09-01","publicationStatus":"PW","scienceBaseUri":"5a6100c8e4b06e28e9c2540d","contributors":{"authors":[{"text":"Whidden, Katherine J. 0000-0002-7841-2553 kwhidden@usgs.gov","orcid":"https://orcid.org/0000-0002-7841-2553","contributorId":3960,"corporation":false,"usgs":true,"family":"Whidden","given":"Katherine","email":"kwhidden@usgs.gov","middleInitial":"J.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":714043,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dumoulin, Julie A. 0000-0003-1754-1287 dumoulin@usgs.gov","orcid":"https://orcid.org/0000-0003-1754-1287","contributorId":203209,"corporation":false,"usgs":true,"family":"Dumoulin","given":"Julie","email":"dumoulin@usgs.gov","middleInitial":"A.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":714042,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Whalen, M.T.","contributorId":197673,"corporation":false,"usgs":false,"family":"Whalen","given":"M.T.","email":"","affiliations":[],"preferred":false,"id":714047,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hutton, E.","contributorId":197672,"corporation":false,"usgs":false,"family":"Hutton","given":"E.","affiliations":[],"preferred":false,"id":714046,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Moore, Thomas E. 0000-0002-0878-0457 tmoore@usgs.gov","orcid":"https://orcid.org/0000-0002-0878-0457","contributorId":127538,"corporation":false,"usgs":true,"family":"Moore","given":"Thomas","email":"tmoore@usgs.gov","middleInitial":"E.","affiliations":[{"id":662,"text":"Western Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":714045,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gaswirth, Stephanie B. 0000-0001-5821-6347 sgaswirth@usgs.gov","orcid":"https://orcid.org/0000-0001-5821-6347","contributorId":150417,"corporation":false,"usgs":true,"family":"Gaswirth","given":"Stephanie","email":"sgaswirth@usgs.gov","middleInitial":"B.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":714044,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70073500,"text":"70073500 - 2014 - Assessing streamflow sensitivity to variations in glacier mass balance","interactions":[],"lastModifiedDate":"2018-08-24T11:29:38","indexId":"70073500","displayToPublicDate":"2014-01-30T13:47:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1252,"text":"Climatic Change","active":true,"publicationSubtype":{"id":10}},"title":"Assessing streamflow sensitivity to variations in glacier mass balance","docAbstract":"The mountains ringing the Gulf of Alaska (GOA) receive upwards of 4–8 m yr−1 of precipitation (Simpson et al.2005; Weingartner et al. 2005; O’Neel 2012), much of which runs off into productive coastal waters. The alpine landscape is heavily glacierized, and storage and turnover of water by glaciers substantially influences the regional surface water balance (Neal et al. 2010). In turn, the land-to-ocean flux of freshwater impacts the biogeochemistry, physical oceanography, freshwater and marine ecology of the downstream components of the GOA ecosystem (e.g., Royer et al. 2001; Hood and Scott 2008). In this way, the links between terrestrial and ocean ecosystems along the GOA have widespread impacts on regional socioeconomic issues including water and hydropower resources, fish populations, and sea level change (Dorava and Milner 2000; Royer and Grosch 2006; Cherry et al. 2010; Gardner et al. 2013). Moreover, predicting future changes in physical, chemical and biological processes in near-shore ecosystems along the GOA hinges, in part, on developing a robust understanding of water storage and transfer by glaciers through streams to the ocean.\nGlacierized basins (i.e. presently ice covered as opposed to glaciated, or historically ice covered) are very efficient producers of runoff, yielding 2–10 times greater runoff than similarly sized, non-glacierized basins (Mayo 1984). The unique energy balance that characterizes these basins (Jansson et al. 2003; Hock 2005) results in substantial alterations to streamflow, even when fractional ice coverage is very small (Stahl and Moore 2006). Consistent and precise treatment of glacier runoff is key to accurate assessment of hydrologic, ecological and socioeconomic impacts, but previously used definitions for glacier runoff are variable. They include: 1) meltwater produced as negative annual mass balance (e.g., Fountain and Tangborn 1985); 2) storage changes in the monthly water budget, where solid precipitation is balanced by melt and evaporation (Huss 2011, concept #2); 3) meltwater derived from melting ice only (irrespective of melting snow or mass balance) (Nolin et al. 2010; Huss 2011, concept #1); 4) all meltwater derived from the glacier surface (Cogley et al. 2011, meltwater runoff); 5) total runoff from the glacier surface (meltwater runoff plus rain on the glacier) (Neal et al. 2010).\nTotal glacier runoff (Definitions 4 and 5 above) includes a contribution from annual mass balance, i.e. the sum of accumulation and ablation through a mass balance year (Definition 1), or what has historically been referred to as the “net” balance (Cogley et al. 2011). Indeed, annual balance has been shown to be an important driver of streamflow trends in glacierized basins, with periods of persistent negative annual balance resulting in statistically significant increases in streamflow (e.g., Pellicciotti et al. 2010). However, in maritime climates, anomalies in glacier runoff can be disconnected from annual balance because of the high variability in winter precipitation. For example, positive anomalies in winter accumulation can result in elevated levels of glacier runoff in times of positive annual mass balance (Thayyen and Gergan 2010).\nQuantifying the impacts of changing glacier geometries (annual balance) on glacier runoff is essential for predicting future changes in streamflow in glacierized basins. However, determining the role that this component plays in total glacier runoff (Definition 5) requires consistent measurements of seasonal (or shorter period) mass balances, measurements of precipitation at multiple locations within a basin, and streamflow measurements in close proximity to a glacier’s terminus. Practical and logistical challenges associated with assembling such data sets typically preclude such partitioning. As a result, most analyses of the relationship between annual mass balance and streamflow rely on some component of model output to compute glacier runoff (e.g. Huss et al. 2008; Kaser et al. 2010). Ultimately, developing an understanding of how total glacier runoff will change in the future is critical for predicting downstream ecological impacts associated with changes in riverine fluxes of water, sediment, and solutes (e.g., metals and nutrients) to near-shore coastal ecosystems.\nThe purpose of this paper is to evaluate relationships among seasonal and annual glacier mass balances, glacier runoff and streamflow in two glacierized basins in different climate settings. We use long-term glacier mass balance and streamflow datasets from the United States Geological Survey (USGS) Alaska Benchmark Glacier Program to compare and contrast glacier-streamflow interactions in a maritime climate (Wolverine Glacier) with those in a continental climate (Gulkana Glacier). Our overall goal is to improve our understanding of how glacier mass balance processes impact streamflow, ultimately improving our conceptual understanding of the future evolution of glacier runoff in continental and maritime climates.","language":"English","publisher":"Springer","doi":"10.1007/s10584-013-1042-7","usgsCitation":"O’Neel, S., Hood, E., Arendt, A., and Sass, L., 2014, Assessing streamflow sensitivity to variations in glacier mass balance: Climatic Change, v. 123, no. 2, p. 329-341, https://doi.org/10.1007/s10584-013-1042-7.","productDescription":"13 p.","startPage":"329","endPage":"341","ipdsId":"IP-049370","costCenters":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"links":[{"id":473202,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10584-013-1042-7","text":"Publisher Index Page"},{"id":281844,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":281842,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s10584-013-1042-7"}],"country":"United States","state":"Alaska","volume":"123","issue":"2","noUsgsAuthors":false,"publicationDate":"2014-01-30","publicationStatus":"PW","scienceBaseUri":"53517024e4b05569d805a161","contributors":{"authors":[{"text":"O’Neel, Shad 0000-0002-9185-0144 soneel@usgs.gov","orcid":"https://orcid.org/0000-0002-9185-0144","contributorId":166740,"corporation":false,"usgs":true,"family":"O’Neel","given":"Shad","email":"soneel@usgs.gov","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true},{"id":107,"text":"Alaska Climate Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"preferred":true,"id":488826,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hood, Eran","contributorId":106802,"corporation":false,"usgs":false,"family":"Hood","given":"Eran","affiliations":[],"preferred":false,"id":488828,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Arendt, Anthony","contributorId":74661,"corporation":false,"usgs":true,"family":"Arendt","given":"Anthony","affiliations":[],"preferred":false,"id":488827,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sass, Louis C. 0000-0003-4677-029X lsass@usgs.gov","orcid":"https://orcid.org/0000-0003-4677-029X","contributorId":3555,"corporation":false,"usgs":true,"family":"Sass","given":"Louis C.","email":"lsass@usgs.gov","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"preferred":true,"id":488825,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70074653,"text":"70074653 - 2014 - Slip rate and tremor genesis in Cascadia","interactions":[],"lastModifiedDate":"2019-03-14T16:42:38","indexId":"70074653","displayToPublicDate":"2014-01-30T08:51:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Slip rate and tremor genesis in Cascadia","docAbstract":"At many plate boundaries, conditions in the transition zone between seismogenic and stable slip produce slow earthquakes. In the Cascadia subduction zone, these events are consistently observed as slow, aseismic slip on the plate interface accompanied by persistent tectonic tremor. However, not all slow slip at other plate boundaries coincides spatially and temporally with tremor, leaving the physics of tremor genesis poorly understood. Here we analyze seismic, geodetic, and strainmeter data in Cascadia to observe for the first time a large, tremor-generating slow earthquake change from tremor-genic to silent and back again. The tremor falls silent at reduced slip speeds when the migrating slip front pauses as it loads the stronger adjacent fault segment to failure. The finding suggests that rheology and slip-speed-regulated stressing rate control tremor genesis, and the same section of fault can slip both with and without detectable tremor, limiting tremor's use as a proxy for slip.","language":"English","publisher":"Wiley","doi":"10.1002/2013GL058607","usgsCitation":"Wech, A.G., and Bartlow, N., 2014, Slip rate and tremor genesis in Cascadia: Geophysical Research Letters, v. 41, no. 2, p. 392-398, https://doi.org/10.1002/2013GL058607.","productDescription":"7 p.","startPage":"392","endPage":"398","numberOfPages":"7","ipdsId":"IP-052361","costCenters":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":473203,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2013gl058607","text":"Publisher Index Page"},{"id":281786,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"British Columbia, California, Oregon, Washington","otherGeospatial":"Cascadia Subduction Zone","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -128.7,38.06 ], [ -128.7,51.29 ], [ -120.59,51.29 ], [ -120.59,38.06 ], [ -128.7,38.06 ] ] ] } } ] }","volume":"41","issue":"2","noUsgsAuthors":false,"publicationDate":"2014-01-30","publicationStatus":"PW","scienceBaseUri":"53517063e4b05569d805a3b9","contributors":{"authors":[{"text":"Wech, Aaron G. 0000-0003-4983-1991 awech@usgs.gov","orcid":"https://orcid.org/0000-0003-4983-1991","contributorId":5344,"corporation":false,"usgs":true,"family":"Wech","given":"Aaron","email":"awech@usgs.gov","middleInitial":"G.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":489691,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bartlow, Noel M.","contributorId":38868,"corporation":false,"usgs":true,"family":"Bartlow","given":"Noel M.","affiliations":[],"preferred":false,"id":489692,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70074652,"text":"70074652 - 2014 - Dynamics of submarine groundwater discharge and associated fluxes of dissolved nutrients, carbon, and trace gases to the coastal zone (Okatee River estuary, South Carolina)","interactions":[],"lastModifiedDate":"2016-11-30T13:46:11","indexId":"70074652","displayToPublicDate":"2014-01-30T08:28:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1759,"text":"Geochimica et Cosmochimica Acta","active":true,"publicationSubtype":{"id":10}},"title":"Dynamics of submarine groundwater discharge and associated fluxes of dissolved nutrients, carbon, and trace gases to the coastal zone (Okatee River estuary, South Carolina)","docAbstract":"Multiple techniques, including thermal infrared aerial remote sensing, geophysical and geological data, geochemical characterization and radium isotopes, were used to evaluate the role of groundwater as a source of dissolved nutrients, carbon, and trace gases to the Okatee River estuary, South Carolina. Thermal infrared aerial remote sensing surveys illustrated the presence of multiple submarine groundwater discharge sites in Okatee headwaters. Significant relationships were observed between groundwater geochemical constituents and 226Ra activity in groundwater with higher 226Ra activity correlated to higher concentrations of organics, dissolved inorganic carbon, nutrients, and trace gases to the Okatee system. A system-level radium mass balance confirmed a substantial submarine groundwater discharge contribution of these constituents to the Okatee River. Diffusive benthic flux measurements and potential denitrification rate assays tracked the fate of constituents in creek bank sediments. Diffusive benthic fluxes were substantially lower than calculated radium-based submarine groundwater discharge inputs, showing that advection of groundwater-derived nutrients dominated fluxes in the system. While a considerable potential for denitrification in tidal creek bank sediments was noted, in situ denitrification rates were nitrate-limited, making intertidal sediments an inefficient nitrogen sink in this system. Groundwater geochemical data indicated significant differences in groundwater chemical composition and radium activity ratios between the eastern and western sides of the river; these likely arose from the distinct hydrological regimes observed in each area. Groundwater from the western side of the Okatee headwaters was characterized by higher concentrations of dissolved organic and inorganic carbon, dissolved organic nitrogen, inorganic nutrients and reduced metabolites and trace gases, i.e. methane and nitrous oxide, than groundwater from the eastern side. Differences in microbial sulfate reduction, organic matter supply, and/or groundwater residence time likely contributed to this pattern. The contrasting features of the east and west sub-marsh zones highlight the need for multiple techniques for characterization of submarine groundwater discharge sources and the impact of biogeochemical processes on the delivery of nutrients and carbon to coastal areas via submarine groundwater discharge.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Geochimica et Cosmochimica Acta","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.gca.2013.12.030","usgsCitation":"Porubsky, W., Weston, N., Moore, W., Ruppel, C., and Joye, S., 2014, Dynamics of submarine groundwater discharge and associated fluxes of dissolved nutrients, carbon, and trace gases to the coastal zone (Okatee River estuary, South Carolina): Geochimica et Cosmochimica Acta, v. 131, p. 81-97, https://doi.org/10.1016/j.gca.2013.12.030.","productDescription":"17 p.","startPage":"81","endPage":"97","numberOfPages":"17","ipdsId":"IP-051744","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":281785,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":281783,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.gca.2013.12.030"}],"country":"United States","state":"South Carolina","otherGeospatial":"Okatee River Estuary","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -80.95,32.26 ], [ -80.95,32.3 ], [ -80.9,32.3 ], [ -80.9,32.26 ], [ -80.95,32.26 ] ] ] } } ] }","volume":"131","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53517035e4b05569d805a1d1","contributors":{"authors":[{"text":"Porubsky, W.P.","contributorId":32000,"corporation":false,"usgs":true,"family":"Porubsky","given":"W.P.","email":"","affiliations":[],"preferred":false,"id":489686,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Weston, N.B.","contributorId":33221,"corporation":false,"usgs":true,"family":"Weston","given":"N.B.","email":"","affiliations":[],"preferred":false,"id":489687,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Moore, W.S.","contributorId":90875,"corporation":false,"usgs":true,"family":"Moore","given":"W.S.","email":"","affiliations":[],"preferred":false,"id":489689,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ruppel, C.","contributorId":82050,"corporation":false,"usgs":true,"family":"Ruppel","given":"C.","email":"","affiliations":[],"preferred":false,"id":489688,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Joye, S.B.","contributorId":97266,"corporation":false,"usgs":true,"family":"Joye","given":"S.B.","email":"","affiliations":[],"preferred":false,"id":489690,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70059911,"text":"sir20135240 - 2014 - Trends in precipitation, streamflow, reservoir pool elevations, and reservoir releases in Arkansas and selected sites in Louisiana, Missouri, and Oklahoma, 1951–2011","interactions":[],"lastModifiedDate":"2018-07-09T16:27:42","indexId":"sir20135240","displayToPublicDate":"2014-01-30T07:25:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-5240","title":"Trends in precipitation, streamflow, reservoir pool elevations, and reservoir releases in Arkansas and selected sites in Louisiana, Missouri, and Oklahoma, 1951–2011","docAbstract":"The U.S. Geological Survey (USGS) and the U.S. Army Corps of Engineers (USACE) conducted a statistical analysis of trends in precipitation, streamflow, reservoir pool elevations, and reservoir releases in Arkansas and selected sites in Louisiana, Missouri, and Oklahoma for the period 1951–2011. The Mann-Kendall test was used to test for trends in annual and seasonal precipitation, annual and seasonal streamflows of 42 continuous-record USGS streamflow-gaging stations, annual pool elevations and releases from 16 USACE reservoirs, and annual releases from 11 dams on the Arkansas River. A statistically significant (p≤0.10) upward trend was observed in annual precipitation for the State, with a Sen slope of approximately 0.10 inch per year. Autumn and winter were the only seasons that had statistically significant trends in precipitation. Five of six physiographic sections and six of seven 4-digit hydrologic unit code (HUC) regions in Arkansas had statistically significant upward trends in autumn precipitation, with Sen slopes of approximately 0.06 to 0.10 inch per year. Sixteen sites had statistically significant upward trends in the annual mean daily streamflow and were located on streams that drained regions with statistically significant upward trends in annual precipitation. Expected annual rates of change corresponding to statistically significant trends in annual mean daily streamflows, which ranged from 0.32 to 0.88 percent, were greater than those corresponding to regions with statistically significant upward trends in annual precipitation, which ranged from 0.19 to 0.28 percent, suggesting that the observed trends in regional annual precipitation do not fully account for the observed trends in annual mean daily streamflows. Trends in annual maximum daily streamflows were similar to trends in the annual mean daily streamflows but were only statistically significant at seven sites. There were more statistically significant trends (28 of 42 sites) in the annual minimum daily streamflows than in the annual means or maximums. Statistically significant trends in the annual minimum daily streamflows were upward at 18 sites and downward at 10 sites. Despite autumn being the only season that had statistically significant upward trends in seasonal precipitation, statistically significant upward trends in seasonal mean streamflows occurred in every season but spring. Trends in the annual mean, maximum, and minimum daily pool elevations of USACE reservoirs were consistent between metrics for reservoirs in the White, Arkansas, and Ouachita River watersheds, while trends varied between metrics at DeQueen Lake, Millwood Lake, and Lake Chicot. Most of the statistically significant trends in pool elevation metrics were upward and gradual—Sen slopes were less than 0.37 foot per year—and were likely the result of changes in reservoir regulation plans. Trends in the annual mean and maximum daily releases from USACE reservoirs were generally upward in all HUC regions. There were few statistically significant trends in the annual mean daily releases because the reservoirs are operated to maintain a regulation stage at a downstream site according to guidelines set forth in the regulation plans of the reservoirs. The annual number of low-flow days was both increasing and decreasing for reservoirs in northern Arkansas and southern Missouri and generally increasing for reservoirs in southern Arkansas.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135240","collaboration":"Prepared in cooperation with the Arkansas Natural Resources Commission","usgsCitation":"Wagner, D.M., Krieger, J.D., and Merriman, K.R., 2014, Trends in precipitation, streamflow, reservoir pool elevations, and reservoir releases in Arkansas and selected sites in Louisiana, Missouri, and Oklahoma, 1951–2011: U.S. Geological Survey Scientific Investigations Report 2013-5240, vi, 61 p., https://doi.org/10.3133/sir20135240.","productDescription":"vi, 61 p.","numberOfPages":"67","onlineOnly":"Y","ipdsId":"IP-052791","costCenters":[{"id":129,"text":"Arkansas Water Science Center","active":true,"usgs":true}],"links":[{"id":281685,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5240/"},{"id":281684,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5240/pdf/sir2013-5240.pdf"},{"id":281686,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135240.jpg"}],"country":"United States","state":"Arkansas;Louisiana;Missouri;Oklahoma","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -96,8.333333333333334E-4 ], [ -96,8.333333333333334E-4 ], [ -90,8.333333333333334E-4 ], [ -90,8.333333333333334E-4 ], [ -96,8.333333333333334E-4 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd79a5e4b0b2908510cf57","contributors":{"authors":[{"text":"Wagner, Daniel M. 0000-0002-0432-450X dwagner@usgs.gov","orcid":"https://orcid.org/0000-0002-0432-450X","contributorId":4531,"corporation":false,"usgs":true,"family":"Wagner","given":"Daniel","email":"dwagner@usgs.gov","middleInitial":"M.","affiliations":[{"id":129,"text":"Arkansas Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":487841,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Krieger, Joshua D.","contributorId":43667,"corporation":false,"usgs":true,"family":"Krieger","given":"Joshua","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":487843,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Merriman, Katherine R. 0000-0002-1303-2410 kmerriman@usgs.gov","orcid":"https://orcid.org/0000-0002-1303-2410","contributorId":4973,"corporation":false,"usgs":true,"family":"Merriman","given":"Katherine","email":"kmerriman@usgs.gov","middleInitial":"R.","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":false,"id":487842,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70148067,"text":"70148067 - 2014 - Undersampling power-law size distributions: effect on the assessment of extreme natural hazards","interactions":[],"lastModifiedDate":"2015-05-19T10:50:07","indexId":"70148067","displayToPublicDate":"2014-01-29T12:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2822,"text":"Natural Hazards","active":true,"publicationSubtype":{"id":10}},"title":"Undersampling power-law size distributions: effect on the assessment of extreme natural hazards","docAbstract":"

The effect of undersampling on estimating the size of extreme natural hazards from historical data is examined. Tests using synthetic catalogs indicate that the tail of an empirical size distribution sampled from a pure Pareto probability distribution can range from having one-to-several unusually large events to appearing depleted, relative to the parent distribution. Both of these effects are artifacts caused by limited catalog length. It is more difficult to diagnose the artificially depleted empirical distributions, since one expects that a pure Pareto distribution is physically limited in some way. Using maximum likelihood methods and the method of moments, we estimate the power-law exponent and the corner size parameter of tapered Pareto distributions for several natural hazard examples: tsunamis, floods, and earthquakes. Each of these examples has varying catalog lengths and measurement thresholds, relative to the largest event sizes. In many cases where there are only several orders of magnitude between the measurement threshold and the largest events, joint two-parameter estimation techniques are necessary to account for estimation dependence between the power-law scaling exponent and the corner size parameter. Results indicate that whereas the corner size parameter of a tapered Pareto distribution can be estimated, its upper confidence bound cannot be determined and the estimate itself is often unstable with time. Correspondingly, one cannot statistically reject a pure Pareto null hypothesis using natural hazard catalog data. Although physical limits to the hazard source size and by attenuation mechanisms from source to site constrain the maximum hazard size, historical data alone often cannot reliably determine the corner size parameter. Probabilistic assessments incorporating theoretical constraints on source size and propagation effects are preferred over deterministic assessments of extreme natural hazards based on historic data.

","language":"English","publisher":"International Society for the Prevention and Mitigation of Natural Hazards","publisherLocation":"Dordrecht","doi":"10.1007/s11069-013-1024-0","usgsCitation":"Geist, E.L., and Parsons, T.E., 2014, Undersampling power-law size distributions: effect on the assessment of extreme natural hazards: Natural Hazards, v. 72, no. 2, p. 565-595, https://doi.org/10.1007/s11069-013-1024-0.","productDescription":"31 p.","startPage":"565","endPage":"595","numberOfPages":"31","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-049313","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":300546,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"72","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2014-01-29","publicationStatus":"PW","scienceBaseUri":"555c5ec9e4b0a92fa7eacc1b","contributors":{"authors":[{"text":"Geist, Eric L. 0000-0003-0611-1150 egeist@usgs.gov","orcid":"https://orcid.org/0000-0003-0611-1150","contributorId":1956,"corporation":false,"usgs":true,"family":"Geist","given":"Eric","email":"egeist@usgs.gov","middleInitial":"L.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":547111,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Parsons, Thomas E. 0000-0002-0582-4338 tparsons@usgs.gov","orcid":"https://orcid.org/0000-0002-0582-4338","contributorId":2314,"corporation":false,"usgs":true,"family":"Parsons","given":"Thomas","email":"tparsons@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":547112,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70074287,"text":"ofr20131237 - 2014 - National requirements for improved elevation data","interactions":[],"lastModifiedDate":"2014-01-29T08:00:53","indexId":"ofr20131237","displayToPublicDate":"2014-01-29T07:41:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-1237","title":"National requirements for improved elevation data","docAbstract":"This report presents the results of surveys, structured interviews, and workshops conducted to identify key national requirements for improved elevation data for the United States and its territories, including coastlines. Organizations also identified and reported the expected economic benefits that would be realized if their requirements for improved elevation were met (appendixes 1–3). This report describes the data collection methodology and summarizes the findings. Participating organizations included 34 Federal agencies, 50 States and two territories, and a sampling of local governments, tribes, and nongovernmental orgnizations. The nongovernmental organizations included The Nature Conservancy and a sampling of private sector businesses. These data were collected in 2010-2011 as part of the National Enhanced Elevation Assessment (NEEA), a study to identify program alternatives for better meeting the Nation’s elevation data needs. NEEA tasks included the collection of national elevation requirements; analysis of the benefits and costs of meeting these requirements; assessment of emerging elevation technologies, lifecycle data management needs, and costs for managing and distributing a national-scale dataset and derived products; and candidate national elevation program alternatives that balance costs and benefits in meeting the Nation’s elevation requirements. The NEEA was sponsored by the National Digital Elevation Program (NDEP), a government coordination body with the U.S. Geological Survey (USGS) as managing partner that includes the National Geospatial-Intelligence Agency (NGA), the Federal Emergency Management Agency (FEMA), the Natural Resources Conservation Service (NRCS), the U.S. Army Corps of Engineers (USACE), and the National Oceanic and Atmospheric Administration (NOAA), among the more than a dozen agencies and organizations. The term enhanced elevation data as used in this report refers broadly to three-dimensional measurements of land or submerged topography, built features, vegetation structure, and other landscape detail. Additional information about NEEA and its later use in the development of a 3D Elevation Program (3DEP) can be found at http://nationalmap.gov/3DEP/index.html.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131237","collaboration":"Prepared in cooperation with the Federal Emergency Management Agency, the National Geospatial - Intelligence Agency, and the Natural Resources Conservation Service","usgsCitation":"Snyder, G., Sugarbaker, L.J., Jason, A.L., and Maune, D.F., 2014, National requirements for improved elevation data: U.S. Geological Survey Open-File Report 2013-1237, Report: iv, 11 p.; Appendix 1: 142 p.; Appendix 2: 203 p.; Appendix 3: 32 p., https://doi.org/10.3133/ofr20131237.","productDescription":"Report: iv, 11 p.; Appendix 1: 142 p.; Appendix 2: 203 p.; Appendix 3: 32 p.","onlineOnly":"Y","ipdsId":"IP-044391","costCenters":[{"id":498,"text":"Office of Land Remote Sensing (Geography)","active":true,"usgs":true}],"links":[{"id":281633,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131237.jpg"},{"id":281628,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1237/"},{"id":281629,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1237/pdf/of2013-1237.pdf"},{"id":281631,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2013/1237/pdf/ofr2013-1237_app2.pdf"},{"id":281630,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2013/1237/pdf/ofr2013-1237_app1.pdf"},{"id":281632,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2013/1237/pdf/ofr2013-1237_app3.pdf"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 144.616667,13.233333 ], [ 144.616667,71.833333 ], [ -64.566667,71.833333 ], [ -64.566667,13.233333 ], [ 144.616667,13.233333 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd689ee4b0b290851022b5","contributors":{"authors":[{"text":"Snyder, Gregory I. gsnyder@usgs.gov","contributorId":4069,"corporation":false,"usgs":true,"family":"Snyder","given":"Gregory I.","email":"gsnyder@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":489491,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sugarbaker, Larry J. lsugarbaker@usgs.gov","contributorId":3079,"corporation":false,"usgs":true,"family":"Sugarbaker","given":"Larry","email":"lsugarbaker@usgs.gov","middleInitial":"J.","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":true,"id":489490,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jason, Allyson L. ajason@usgs.gov","contributorId":5754,"corporation":false,"usgs":true,"family":"Jason","given":"Allyson","email":"ajason@usgs.gov","middleInitial":"L.","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":true,"id":489492,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Maune, David F.","contributorId":34042,"corporation":false,"usgs":true,"family":"Maune","given":"David","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":489493,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70059169,"text":"sir20135236 - 2014 - Simulation of groundwater flow and saltwater movement in the Onslow County area, North Carolina: predevelopment-2010","interactions":[],"lastModifiedDate":"2017-01-17T20:55:28","indexId":"sir20135236","displayToPublicDate":"2014-01-28T14:17:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-5236","title":"Simulation of groundwater flow and saltwater movement in the Onslow County area, North Carolina: predevelopment-2010","docAbstract":"

Onslow County, North Carolina, is located within the designated Central Coastal Plain Capacity Use Area (CCPCUA). The CCPCUA was designated by law as a result of groundwater level declines of as much as 200 feet during the past four decades within aquifers in rocks of Cretaceous age in the central Coastal Plain of North Carolina and a depletion of water in storage from increased groundwater withdrawals in the area. The declines and depletion of water in storage within the Cretaceous aquifers increase the potential for saltwater migration—both lateral encroachment and upward leakage of brackish water. Within the CCPCUA, a reduction in groundwater withdrawals over a period of 16 years from 2003 to 2018 is mandated. Under the CCPCUA rules, withdrawals in excess of 100,000 gallons per day from any of the Cretaceous aquifer well systems are subject to water-use reductions of as much as 75 percent. To assess the effects of the CCPCUA rules and to assist with groundwater-management decisions, a numerical model was developed to simulate the groundwater flow and chloride concentrations in the surficial Castle Hayne, Beaufort, Peedee, and Black Creek aquifers in the Onslow County area. The model was used to (1) simulate groundwater flow from 1900 to 2010; (2) assess chloride movement throughout the aquifer system; and (3) create hypothetical scenarios of future groundwater development.

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\n

After calibration of a groundwater flow model and conversion to a variable-density model, five scenarios were created to simulate future groundwater conditions in the Onslow County area: (1) full implementation of the CCPCUA rules with three phases of withdrawal reductions simulated through 2028; (2) implementation of only phase 1 withdrawal reductions of the CCPCUA rules and simulated through 2028; (3) implementation of only phases 1 and 2 withdrawal reductions of the CCPCUA rules and simulated through 2028; (4) full implementation of the CCPCUA rules with the addition of withdrawals from the Castle Hayne aquifer in Onslow County at the fully permitted amount in the final stress period and simulated through 2028; and (5) full implementation of the CCPCUA rules as in scenario 1 except simulated through 2100. Results from the scenarios give an indication of the water-level recovery in the Black Creek aquifer throughout each phase of the CCPCUA rules in Onslow County. Furthermore, as development of the Castle Hayne aquifers was increased in the scenarios, cones of depression were created around pumping centers. Additionally, the scenarios indicated little to no change in chloride concentrations for the time periods simulated.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135236","collaboration":"Prepared in cooperation with the City of Jacksonville, Onslow Water and Sewer Authority, and the United States Marine Corps Base Camp Lejeune","usgsCitation":"Fine, J.M., and Kuniansky, E.L., 2014, Simulation of groundwater flow and saltwater movement in the Onslow County area, North Carolina: predevelopment-2010: U.S. Geological Survey Scientific Investigations Report 2013-5236, x, 106 p., https://doi.org/10.3133/sir20135236.","productDescription":"x, 106 p.","numberOfPages":"120","onlineOnly":"Y","ipdsId":"IP-042993","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":281621,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135236.jpg"},{"id":281620,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5236/"},{"id":281619,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5236/pdf/sir2013-5236.pdf"}],"country":"United States","state":"North Carolina","county":"Onslow County","otherGeospatial":"Central Coastal Plain Capacity Use Area","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -78.0011,34.1967 ], [ -78.0011,35.4025 ], [ -76.892,35.4025 ], [ -76.892,34.1967 ], [ -78.0011,34.1967 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd72e5e4b0b290851089b3","contributors":{"authors":[{"text":"Fine, Jason M. 0000-0002-6386-256X jmfine@usgs.gov","orcid":"https://orcid.org/0000-0002-6386-256X","contributorId":2238,"corporation":false,"usgs":true,"family":"Fine","given":"Jason","email":"jmfine@usgs.gov","middleInitial":"M.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":487510,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kuniansky, Eve L. 0000-0002-5581-0225 elkunian@usgs.gov","orcid":"https://orcid.org/0000-0002-5581-0225","contributorId":932,"corporation":false,"usgs":true,"family":"Kuniansky","given":"Eve","email":"elkunian@usgs.gov","middleInitial":"L.","affiliations":[{"id":5064,"text":"Southeast Regional Director's Office","active":true,"usgs":true},{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true}],"preferred":true,"id":487509,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70048970,"text":"sir20135179 - 2014 - Trends in major-ion constituents and properties for selected sampling sites in the Tongue and Powder River watersheds, Montana and Wyoming, based on data collected during water years 1980-2010","interactions":[],"lastModifiedDate":"2014-01-28T13:11:27","indexId":"sir20135179","displayToPublicDate":"2014-01-28T12:52:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-5179","title":"Trends in major-ion constituents and properties for selected sampling sites in the Tongue and Powder River watersheds, Montana and Wyoming, based on data collected during water years 1980-2010","docAbstract":"

The primary purpose of this report is to present information relating to flow-adjusted temporal trends in major-ion constituents and properties for 16 sampling sites in the Tongue and Powder River watersheds based on data collected during 1980–2010. In association with this primary purpose, the report presents background information on major-ion characteristics (including specific conductance, calcium, magnesium, potassium, sodium adsorption ratio, sodium, alkalinity, chloride, fluoride, dissolved sulfate, and dissolved solids) of the sampling sites and coal-bed methane (CBM) produced water (groundwater pumped from coal seams) in the site watersheds, trend analysis methods, streamflow conditions, and factors that affect trend results.

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\n

The Tongue and Powder River watersheds overlie the Powder River structural basin (PRB) in northeastern Wyoming and southeastern Montana. Limited extraction of coal-bed methane (CBM) from the PRB began in the early 1990’s, and increased dramatically during the late 1990’s and early 2000’s. CBM-extraction activities produce discharges of water with high concentrations of dissolved solids (particularly sodium and bicarbonate ions) relative to most stream water in the Tongue and Powder River watersheds. Water-quality of CBM produced water is of concern because of potential effects of sodium on agricultural soils and potential effects of bicarbonate on aquatic biota.

\n
\n

Two parametric trend-analysis methods were used in this study: the time-series model (TSM) and ordinary least squares regression (OLS) on time, streamflow, and season. The TSM was used to analyze trends for 11 of the 16 study sites. For five sites, data requirements of the TSM were not met and OLS was used to analyze trends. Two primary 10-year trend-analysis periods were selected. Trend-analysis period 1 (water years 1986–95; hereinafter referred to as period 1) was selected to represent variability in major-ion concentrations in the Tongue and Powder River watersheds before potential effects of CBM-extraction activities. Trend analysis period 2 (water years 2001–10; hereinafter referred to as period 2) was selected because it encompassed substantial CBM-extraction activities and therefore might indicate potential effects of CBM-extraction activities on water quality of receiving streams in the Tongue and Powder River watersheds. For sites that did not satisfy data requirements for the TSM, OLS was used to analyze trends for period 2 (if complete data were available) or a 6-year period (2005–10).

\n
\n

Flow-rate characteristics of CBM-produced water were estimated to allow general comparisons with streamflow characteristics of the sampling sites. The information on flow-rate characteristics of CBM-produced water in relation to streamflow does not account for effects of disposal, treatment, or other remediation activities on the potential quantitative effects of CBM-produced water on receiving streams. In many places, CBM-produced water is discharged into impoundments or channels in upper reaches of tributary watersheds where water infiltrates and does not directly contribute to streamflow. For Tongue River at State line (site 4) mean annual pumping rate of CBM-produced water during water years 2001–10 (hereinafter referred to as mean CBM pumping rate) was 6 percent of the mean of annual median streamflows during water years 2001–10 (hereinafter referred to as 2001–10 median streamflow). For main-stem Tongue River sites 5, 7, and 10, mean CBM pumping rate was 8–12 percent of 2001–10 median streamflow. For main-stem Powder River sites (sites 12, 13, and 16), mean CBM pumping rates were 26, 28, and 34 percent of 2001–10 median streamflows, respectively.

\n
\n

For main-stem Tongue River sites analyzed by using the TSM and downstream from substantial CBM-extraction activities [Tongue River at State line (site 4), Tongue River at Tongue River Dam (site 5), Tongue River at Birney Day School (site 7), and Tongue River at Miles City (site 10)], generally small significant or nonsignificant decreases in most constituents are indicated for period 1. For period 2 for these sites, the TSM trend results do not allow confident conclusions concerning detection of effects of CBM-extraction activities on stream water quality. Detection of significant trends in major-ion constituents and properties for period 2 generally was infrequent, and direction, magnitudes, and significance of fitted trends were not strongly consistent with relative differences in water quality between stream water and CBM-produced water. The TSM indicated significant or generally large magnitude increases in median values of sodium adsorption ratio (SAR), sodium, and alkalinity for period 2 for sites 5 and 7, which might indicate potential effects of CBM-extraction activities on stream water. However, other factors, including operations of Tongue River Reservoir, irrigation activities, contributions of saline groundwater, and operations of the Decker coal mine, confound confident determination of causes of detected significant trends for sites 5 and 7. For all mainstem Tongue River sites, trends for period 2 generally are within ranges of those for period 1 before substantial CBM-extraction activities.

\n
\n

For main-stem Powder River sites analyzed by using the TSM [Powder River at Sussex (site 11), Powder River at Arvada (site 12), Powder River at Moorhead (site 13), and Powder River near Locate (site 16)], significant or generally large magnitude decreases in median values of SAR, sodium, estimated alkalinity, chloride, fluoride, specific conductance, and dissolved solids are indicated for period 1. Patterns in trend results for period 1 for main-stem Powder River sites are consistent with effects of Salt Creek oil-brine reinjection that started in 1990. Trend results for all main-stem Powder River sites downstream from substantial CBM-extraction activities (sites 12, 13, and 16) indicate evidence of potential effects of CBM-extraction activities on stream water quality, although evidence is stronger for sites 12 and 13 than for site 16. Evidence in support of potential CBM effects includes significant increases in median values of SAR, sodium, and estimated alkalinity for period 2 for sites 12, 13, and 16 that are consistent with relative differences between stream water and CBM-produced water. Significant increases in median values of these constituents for period 2 are not indicated for Powder River at Sussex (site 11) upstream from substantial CBM-extraction activities. In interpreting the trend results, it is notable that the fitted trends evaluate changes in median concentrations and also notable that changes in median concentrations that might be attributed to CBM-extraction activities probably are more strongly evident during low to median streamflow conditions than during mean to high streamflow conditions. This observation is relevant in assessing trend results in relation to specific water-quality concerns, including effects of water-quality changes on irrigators and effects on stream biota and ecology.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135179","collaboration":"Prepared in cooperation with the Montana Department of Natural Resources and Conservation, Water Management Bureau","usgsCitation":"Sando, S.K., Vecchia, A.V., Barnhart, E.P., Sando, R., Clark, M.L., and Lorenz, D.L., 2014, Trends in major-ion constituents and properties for selected sampling sites in the Tongue and Powder River watersheds, Montana and Wyoming, based on data collected during water years 1980-2010: U.S. Geological Survey Scientific Investigations Report 2013-5179, x, 123 p., https://doi.org/10.3133/sir20135179.","productDescription":"x, 123 p.","numberOfPages":"140","temporalStart":"1979-10-01","temporalEnd":"2010-09-30","ipdsId":"IP-041145","costCenters":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"links":[{"id":281609,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135179.jpg"},{"id":281606,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5179/"},{"id":281608,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5179/pdf/sir2013-5179.pdf"}],"projection":"Albers Equal-Area Conic Projection","datum":"North American Datum of 1983","country":"United States","state":"Montana;Wyoming","otherGeospatial":"Powder River;Tongue River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -108.0,42.9725 ], [ -108.0,47.0 ], [ -104.502,47.0 ], [ -104.502,42.9725 ], [ -108.0,42.9725 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd79a3e4b0b2908510cf3d","contributors":{"authors":[{"text":"Sando, Steven K. 0000-0003-1206-1030 sksando@usgs.gov","orcid":"https://orcid.org/0000-0003-1206-1030","contributorId":1016,"corporation":false,"usgs":true,"family":"Sando","given":"Steven","email":"sksando@usgs.gov","middleInitial":"K.","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":485900,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vecchia, Aldo V. 0000-0002-2661-4401","orcid":"https://orcid.org/0000-0002-2661-4401","contributorId":41810,"corporation":false,"usgs":true,"family":"Vecchia","given":"Aldo","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":485905,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barnhart, Elliott P. 0000-0002-8788-8393 epbarnhart@usgs.gov","orcid":"https://orcid.org/0000-0002-8788-8393","contributorId":5385,"corporation":false,"usgs":true,"family":"Barnhart","given":"Elliott","email":"epbarnhart@usgs.gov","middleInitial":"P.","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":485904,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sando, Roy 0000-0003-0704-6258","orcid":"https://orcid.org/0000-0003-0704-6258","contributorId":3874,"corporation":false,"usgs":true,"family":"Sando","given":"Roy","email":"","affiliations":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"preferred":true,"id":485903,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Clark, Melanie L. mlclark@usgs.gov","contributorId":1827,"corporation":false,"usgs":true,"family":"Clark","given":"Melanie","email":"mlclark@usgs.gov","middleInitial":"L.","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":485902,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lorenz, David L. 0000-0003-3392-4034 lorenz@usgs.gov","orcid":"https://orcid.org/0000-0003-3392-4034","contributorId":1384,"corporation":false,"usgs":true,"family":"Lorenz","given":"David","email":"lorenz@usgs.gov","middleInitial":"L.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":485901,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70157381,"text":"70157381 - 2014 - Deep long-period earthquakes west of the volcanic arc in Oregon: evidence of serpentine dehydration in the fore-arc mantle wedge","interactions":[],"lastModifiedDate":"2019-03-14T08:29:03","indexId":"70157381","displayToPublicDate":"2014-01-28T11:45:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Deep long-period earthquakes west of the volcanic arc in Oregon: evidence of serpentine dehydration in the fore-arc mantle wedge","docAbstract":"

Here we report on deep long-period earthquakes (DLPs) newly observed in four places in western Oregon. The DLPs are noteworthy for their location within the subduction fore arc: 40–80 km west of the volcanic arc, well above the slab, and near the Moho. These “offset DLPs” occur near the top of the inferred stagnant mantle wedge, which is likely to be serpentinized and cold. The lack of fore-arc DLPs elsewhere along the arc suggests that localized heating may be dehydrating the serpentinized mantle wedge at these latitudes and causing DLPs by dehydration embrittlement. Higher heat flow in this region could be introduced by anomalously hot mantle, associated with the western migration of volcanism across the High Lava Plains of eastern Oregon, entrained in the corner flow proximal to the mantle wedge. Alternatively, fluids rising from the subducting slab through the mantle wedge may be the source of offset DLPs. As far as we know, these are among the first DLPs to be observed in the fore arc of a subduction-zone system.

","language":"English","publisher":"American Geophysical Union","publisherLocation":"Washington, D.C.","doi":"10.1002/2013GL059118","usgsCitation":"Vidale, J.E., Schmidt, D.A., Malone, S.D., Hotovec-Ellis, A.J., Moran, S.C., Creager, K.C., and Houston, H., 2014, Deep long-period earthquakes west of the volcanic arc in Oregon: evidence of serpentine dehydration in the fore-arc mantle wedge: Geophysical Research Letters, v. 41, no. 2, p. 370-376, https://doi.org/10.1002/2013GL059118.","productDescription":"7 p.","startPage":"370","endPage":"376","numberOfPages":"7","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-052448","costCenters":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":308429,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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ONE","active":true,"publicationSubtype":{"id":10}},"title":"Influence of climate change on productivity of American White Pelicans, Pelecanus erythrorhynchos","docAbstract":"In the past decade, severe weather and West Nile virus were major causes of chick mortality at American white pelican (Pelecanus erythrorhynchos) colonies in the northern plains of North America. At one of these colonies, Chase Lake National Wildlife Refuge in North Dakota, spring arrival by pelicans has advanced approximately 16 days over a period of 44 years (1965–2008). We examined phenology patterns of pelicans and timing of inclement weather through the 44-year period, and evaluated the consequence of earlier breeding relative to weather-related chick mortality. We found severe weather patterns to be random through time, rather than concurrently shifting with the advanced arrival of pelicans. In recent years, if nest initiations had followed the phenology patterns of 1965 (i.e., nesting initiated 16 days later), fewer chicks likely would have died from weather-related causes. That is, there would be fewer chicks exposed to severe weather during a vulnerable transition period that occurs between the stage when chicks are being brooded by adults and the stage when chicks from multiple nests become part of a thermally protective crèche.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"PLoS ONE","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pone.0083430","usgsCitation":"Sovada, M.A., Igl, L.D., Pietz, P., and Bartos, A.J., 2014, Influence of climate change on productivity of American White Pelicans, Pelecanus erythrorhynchos: PLoS ONE, v. 9, no. 1, 8 p., https://doi.org/10.1371/journal.pone.0083430.","productDescription":"8 p.","onlineOnly":"Y","ipdsId":"IP-044358","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":473204,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0083430","text":"Publisher Index Page"},{"id":281558,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":281506,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1371/journal.pone.0083430"}],"country":"United States","state":"North Dakota","county":"Stutsman County","otherGeospatial":"Chase Lake National Wildlife Refuge","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -99.481105,46.983794 ], [ -99.481105,47.030693 ], [ -99.417191,47.030693 ], [ -99.417191,46.983794 ], [ -99.481105,46.983794 ] ] ] } } ] }","volume":"9","issue":"1","noUsgsAuthors":false,"publicationDate":"2014-01-08","publicationStatus":"PW","scienceBaseUri":"52e78088e4b0b93270c2f282","contributors":{"authors":[{"text":"Sovada, Marsha A. msovada@usgs.gov","contributorId":2601,"corporation":false,"usgs":true,"family":"Sovada","given":"Marsha","email":"msovada@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":489258,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Igl, Lawrence D. 0000-0003-0530-7266 ligl@usgs.gov","orcid":"https://orcid.org/0000-0003-0530-7266","contributorId":2381,"corporation":false,"usgs":true,"family":"Igl","given":"Lawrence","email":"ligl@usgs.gov","middleInitial":"D.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":489256,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pietz, Pamela J. ppietz@usgs.gov","contributorId":2382,"corporation":false,"usgs":true,"family":"Pietz","given":"Pamela J.","email":"ppietz@usgs.gov","affiliations":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"preferred":false,"id":489257,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bartos, Alisa J. abartos@usgs.gov","contributorId":5177,"corporation":false,"usgs":true,"family":"Bartos","given":"Alisa","email":"abartos@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":true,"id":489259,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70073926,"text":"70073926 - 2014 - Changes in population evacuation potential for tsunami hazards in Seward, Alaska, since the 1964 Good Friday earthquake","interactions":[],"lastModifiedDate":"2014-01-27T10:56:05","indexId":"70073926","displayToPublicDate":"2014-01-27T10:53:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2822,"text":"Natural Hazards","active":true,"publicationSubtype":{"id":10}},"title":"Changes in population evacuation potential for tsunami hazards in Seward, Alaska, since the 1964 Good Friday earthquake","docAbstract":"Pedestrian evacuation modeling for tsunami hazards typically focuses on current land-cover conditions and population distributions. To examine how post-disaster redevelopment may influence the evacuation potential of at-risk populations to future threats, we modeled pedestrian travel times to safety in Seward, Alaska, based on conditions before the 1964 Good Friday earthquake and tsunami disaster and on modern conditions. Anisotropic, path distance modeling is conducted to estimate travel times to safety during the 1964 event and in modern Seward, and results are merged with various population data, including the location and number of residents, employees, public venues, and dependent care facilities. Results suggest that modeled travel time estimates conform well to the fatality patterns of the 1964 event and that evacuation travel times have increased in modern Seward due to the relocation and expansion of port and harbor facilities after the disaster. The majority of individuals threatened by tsunamis today in Seward are employee, customer, and tourist populations, rather than residents in their homes. Modern evacuation travel times to safety for the majority of the region are less than wave arrival times for future tectonic tsunamis but greater than arrival times for landslide-related tsunamis. Evacuation travel times will likely be higher in the winter time, when the presence of snow may constrain evacuations to roads.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Natural Hazards","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","doi":"10.1007/s11069-013-0859-8","usgsCitation":"Wood, N.J., Schmidtlein, M.C., and Peters, J., 2014, Changes in population evacuation potential for tsunami hazards in Seward, Alaska, since the 1964 Good Friday earthquake: Natural Hazards, v. 70, no. 2, p. 1031-1053, https://doi.org/10.1007/s11069-013-0859-8.","productDescription":"23 p.","startPage":"1031","endPage":"1053","numberOfPages":"23","ipdsId":"IP-046272","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":281557,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":281485,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s11069-013-0859-8"}],"country":"United States","state":"Alaska","city":"Seward","otherGeospatial":"Resurrection Bay","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -149.476625,60.085063 ], [ -149.476625,60.154232 ], [ -149.273115,60.154232 ], [ -149.273115,60.085063 ], [ -149.476625,60.085063 ] ] ] } } ] }","volume":"70","issue":"2","noUsgsAuthors":false,"publicationDate":"2013-10-06","publicationStatus":"PW","scienceBaseUri":"52e77fe2e4b0b93270c2f258","contributors":{"authors":[{"text":"Wood, Nathan J. 0000-0002-6060-9729 nwood@usgs.gov","orcid":"https://orcid.org/0000-0002-6060-9729","contributorId":3347,"corporation":false,"usgs":true,"family":"Wood","given":"Nathan","email":"nwood@usgs.gov","middleInitial":"J.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":489238,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schmidtlein, Mathew C.","contributorId":90999,"corporation":false,"usgs":true,"family":"Schmidtlein","given":"Mathew","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":489240,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Peters, Jeff 0000-0003-4312-0590 jpeters@usgs.gov","orcid":"https://orcid.org/0000-0003-4312-0590","contributorId":4711,"corporation":false,"usgs":true,"family":"Peters","given":"Jeff","email":"jpeters@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":489239,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ]}