Cheatgrass exhibits spatial and temporal phenological variability across the Great Basin as described by ecological models formed using remote sensing and other spatial data-sets. We developed a rule-based, piecewise regression-tree model trained on 99 points that used three data-sets – latitude, elevation, and start of season time based on remote sensing input data – to estimate cheatgrass beginning of spring growth (BOSG) in the northern Great Basin. The model was then applied to map the location and timing of cheatgrass spring growth for the entire area. The model was strong (R2 = 0.85) and predicted an average cheatgrass BOSG across the study area of 29 March–4 April. Of early cheatgrass BOSG areas, 65% occurred at elevations below 1452 m. The highest proportion of cheatgrass BOSG occurred between mid-April and late May. Predicted cheatgrass BOSG in this study matched well with previous Great Basin cheatgrass green-up studies.
","language":"English","publisher":"Taylor & Francis","publisherLocation":"Abingdon, UK","doi":"10.1080/17538947.2013.860196","usgsCitation":"Boyte, S.P., Wylie, B.K., Major, D.J., and Brown, J.F., 2015, The integration of geophysical and enhanced Moderate Resolution Imaging Spectroradiometer Normalized Difference Vegetation Index data into a rule-based, piecewise regression-tree model to estimate cheatgrass beginning of spring growth: International Journal of Digital Earth, v. 8, no. 2, p. 116-130, https://doi.org/10.1080/17538947.2013.860196.","productDescription":"15 p.","startPage":"116","endPage":"130","numberOfPages":"15","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-037330","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":472279,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/17538947.2013.860196","text":"Publisher Index Page"},{"id":297921,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Great Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -113.84033203125,\n 40.12849105685408\n ],\n [\n -120.66284179687499,\n 39.21523130910491\n ],\n [\n -122.03613281249999,\n 44.5278427984555\n ],\n [\n -114.686279296875,\n 45.398449976304086\n ],\n [\n -113.84033203125,\n 40.12849105685408\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"8","issue":"2","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2013-11-28","publicationStatus":"PW","scienceBaseUri":"54dd2abfe4b08de9379b31d2","contributors":{"authors":[{"text":"Boyte, Stephen P. 0000-0002-5462-3225 sboyte@usgs.gov","orcid":"https://orcid.org/0000-0002-5462-3225","contributorId":3463,"corporation":false,"usgs":true,"family":"Boyte","given":"Stephen","email":"sboyte@usgs.gov","middleInitial":"P.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":540443,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wylie, Bruce K. 0000-0002-7374-1083 wylie@usgs.gov","orcid":"https://orcid.org/0000-0002-7374-1083","contributorId":750,"corporation":false,"usgs":true,"family":"Wylie","given":"Bruce","email":"wylie@usgs.gov","middleInitial":"K.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":540450,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Major, Donald J.","contributorId":83405,"corporation":false,"usgs":false,"family":"Major","given":"Donald","email":"","middleInitial":"J.","affiliations":[{"id":7217,"text":"Bureau of Land Management","active":true,"usgs":false}],"preferred":false,"id":540451,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brown, Jesslyn F. 0000-0002-9976-1998 jfbrown@usgs.gov","orcid":"https://orcid.org/0000-0002-9976-1998","contributorId":3241,"corporation":false,"usgs":true,"family":"Brown","given":"Jesslyn","email":"jfbrown@usgs.gov","middleInitial":"F.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":540452,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70140950,"text":"70140950 - 2015 - Mapping and monitoring cheatgrass dieoff in rangelands of the Northern Great Basin, USA","interactions":[],"lastModifiedDate":"2017-01-18T10:05:49","indexId":"70140950","displayToPublicDate":"2015-02-11T12:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3228,"text":"Rangeland Ecology and Management","onlineIssn":"1551-5028","printIssn":"1550-7424","active":true,"publicationSubtype":{"id":10}},"title":"Mapping and monitoring cheatgrass dieoff in rangelands of the Northern Great Basin, USA","docAbstract":"Understanding cheatgrass (Bromus tectorum) dynamics in the Northern Great Basin rangelands, USA, is necessary to effectively manage the region’s lands. This study’s goal was to map and monitor cheatgrass performance to identify where and when cheatgrass dieoff occurred in the Northern Great Basin and to discover how this phenomenon was affected by climatic, topographic, and edaphic variables. We also examined how fire affected cheatgrass performance. Land managers and scientists are concerned by cheatgrass dieoff because it can increase land degradation, and its causes and effects are not fully known. To better understand the scope of cheatgrass dieoff, we developed multiple ecological models that integrated remote sensing data with geophysical and biophysical data. The models’ R2 ranged from 0.71 to 0.88, and their root mean squared errors (RMSEs) ranged from 3.07 to 6.95. Validation of dieoff data showed that 41% of pixels within independently developed dieoff polygons were accurately classified as dieoff, whereas 2% of pixels outside of dieoff polygons were classified as dieoff. Site potential, a long-term spatial average of cheatgrass cover, dominated the development of the cheatgrass performance model. Fire negatively affected cheatgrass performance 1 year postfire, but by the second year postfire performance exceeded prefire levels. The landscape-scale monitoring study presented in this paper helps increase knowledge about recent rangeland dynamics, including where cheatgrass dieoffs occurred and how cheatgrass responded to fire. This knowledge can help direct further investigation and/or guide land management activities that can capitalize on, or mitigate the effects of, cheatgrass dieoff.
","language":"English","publisher":"Society for Range Management","doi":"10.1016/j.rama.2014.12.005","usgsCitation":"Boyte, S.P., Wylie, B.K., and Major, D.J., 2015, Mapping and monitoring cheatgrass dieoff in rangelands of the Northern Great Basin, USA: Rangeland Ecology and Management, v. 68, no. 1, p. 18-28, https://doi.org/10.1016/j.rama.2014.12.005.","productDescription":"11 p.","startPage":"18","endPage":"28","numberOfPages":"11","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-053587","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":297920,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Northern Great Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.22314453124999,\n 40.1452892956766\n ],\n [\n -121.22314453124999,\n 44.85586880735725\n ],\n [\n -110.85205078124999,\n 44.85586880735725\n ],\n [\n -110.85205078124999,\n 40.1452892956766\n ],\n [\n -121.22314453124999,\n 40.1452892956766\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"68","issue":"1","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2a94e4b08de9379b3112","contributors":{"authors":[{"text":"Boyte, Stephen P. 0000-0002-5462-3225 sboyte@usgs.gov","orcid":"https://orcid.org/0000-0002-5462-3225","contributorId":3463,"corporation":false,"usgs":true,"family":"Boyte","given":"Stephen","email":"sboyte@usgs.gov","middleInitial":"P.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":540447,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wylie, Bruce K. 0000-0002-7374-1083 wylie@usgs.gov","orcid":"https://orcid.org/0000-0002-7374-1083","contributorId":750,"corporation":false,"usgs":true,"family":"Wylie","given":"Bruce","email":"wylie@usgs.gov","middleInitial":"K.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":540448,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Major, Donald J.","contributorId":83405,"corporation":false,"usgs":false,"family":"Major","given":"Donald","email":"","middleInitial":"J.","affiliations":[{"id":7217,"text":"Bureau of Land Management","active":true,"usgs":false}],"preferred":false,"id":540449,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70141321,"text":"70141321 - 2015 - Detrital zircon U-Pb reconnaissance of the Franciscan subduction complex in northwestern California","interactions":[],"lastModifiedDate":"2015-02-23T11:17:16","indexId":"70141321","displayToPublicDate":"2015-02-11T12:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2020,"text":"International Geology Review","active":true,"publicationSubtype":{"id":10}},"title":"Detrital zircon U-Pb reconnaissance of the Franciscan subduction complex in northwestern California","docAbstract":"In northwestern California, the Franciscan subduction complex has been subdivided into seven major tectonostratigraphic units. We report U-Pb ages of ≈2400 detrital zircon grains from 26 sandstone samples from 5 of these units. Here, we tabulate each unit's interpreted predominant sediment source areas and depositional age range, ordered from the oldest to the youngest unit. (1) Yolla Bolly terrane: nearby Sierra Nevada batholith (SNB); ca. 118 to 98 Ma. Rare fossils had indicated that this unit was mostly 151-137 Ma, but it is mostly much younger. (2) Central Belt: SND; ca. 103 too 53 Ma (but poorly constrained), again mostly younger than previously thought. (3) Yager terrane: distant Idaho batholith (IB); ca. 52 to 50 Ma. Much of the Yager's detritus was shed during major core complex extension and erosion in Idaho that started 53 Ma. An eocene Princeton River-Princeton submarine canyon system transported this detritus to the Great Valley forearc basin and thence to the Franciscan trench. (4) Coastal terrane: mostly IB, ±SNB, ±nearby Cascade arc, ±Nevada Cenozoic ignimbrite belt; 52 to <32 Ma. (5) King Range terrane: dominated by IB and SNB zircons; parts 16-14 Ma based on microfossils. Overall, some Franciscan units are younger than previously thought, making them more compatible with models for the growth of subduction complexes by positive accretion. From ca. 118 to 70 Ma, Franciscan sediments were sourced mainly from the nearby Sierra Nevada region and were isolated from southwestern US and Mexican sources. From 53 to 49 Ma, the Franciscan was sourced from both Idaho and the Sierra Nevada. By 37-32 Ma, input from Idaho had ceased. The influx from Idaho probably reflects major tectonism in Idaho, Oregon, and Washington, plus development of a through-going Princeton River to California, rather than radical changes in the subduction system at the Franciscan trench itself.
","language":"English","publisher":"American Geological Institute","publisherLocation":"Silver Spring, MD","doi":"10.1080/00206814.2015.1008060","collaboration":"Stanford University, UC Santa Cruz","usgsCitation":"Dimitru, T., Ernst, W.G., Hourigan, J.K., and McLaughlin, R.J., 2015, Detrital zircon U-Pb reconnaissance of the Franciscan subduction complex in northwestern California: International Geology Review, p. 1-35, https://doi.org/10.1080/00206814.2015.1008060.","productDescription":"35 p.","startPage":"1","endPage":"35","numberOfPages":"35","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060941","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":472280,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://figshare.com/articles/journal_contribution/Detrital_zircon_U_8211_Pb_reconnaissance_of_the_Franciscan_subduction_complex_in_northwestern_California/1305626","text":"External Repository"},{"id":298107,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.71679687499999,\n 38.25543637637947\n ],\n [\n -124.71679687499999,\n 41.96765920367816\n ],\n [\n -121.17919921875001,\n 41.96765920367816\n ],\n [\n -121.17919921875001,\n 38.25543637637947\n ],\n [\n -124.71679687499999,\n 38.25543637637947\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-02-11","publicationStatus":"PW","scienceBaseUri":"54ec5d3ee4b02d776a67daa0","contributors":{"authors":[{"text":"Dimitru, Trevor","contributorId":139288,"corporation":false,"usgs":false,"family":"Dimitru","given":"Trevor","email":"","affiliations":[{"id":6705,"text":"Stanford Synchrotron Radiation Lightsource, Menlo Park CA","active":true,"usgs":false}],"preferred":false,"id":540670,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ernst, W. 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Since early 2010, numerous organizations have deployed temporary portable seismic stations in central Oklahoma in order to record the evolving seismicity. In this study, we apply a multiple-event relocation method to produce a catalog of 3,639 central Oklahoma earthquakes from late 2009 through 2014. RMT source parameters were determined for 195 of the largest and best-recorded earthquakes. Combining RMT results with relocated seismicity enabled us to determine the length, depth and style-of-faulting occurring on reactivated subsurface fault systems. Results show that the majority of earthquakes occur on near vertical, optimally oriented (NE-SW and NW-SE), strike-slip faults in the shallow crystalline basement. These are necessary first order observations required to assess the potential hazards of individual faults in Oklahoma.
","language":"English","publisher":"Wiley-Blackwell Publishing, Inc.","doi":"10.1002/2014GL062730","usgsCitation":"McNamara, D.E., Benz, H.M., Herrmann, R., Bergman, E.A., Earle, P.S., Holland, A.F., Baldwin, R.W., and Gassner, A., 2015, Earthquake hypocenters and focal mechanisms in central Oklahoma reveal a complex system of reactivated subsurface strike-slip faulting: Geophysical Research Letters, v. 42, no. 8, p. 2742-2749, https://doi.org/10.1002/2014GL062730.","productDescription":"8 p.","startPage":"2742","endPage":"2749","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063056","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":488297,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://doi.crossref.org/servlet/query?format=unixref&pid=bib@gfz-potsdam.de&id=10.1002/2014GL062730","text":"Publisher Index Page"},{"id":297918,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oklahoma","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -102.996826171875,\n 33.38558626887102\n ],\n [\n -102.996826171875,\n 37.58811876638322\n ],\n [\n -93.9990234375,\n 37.58811876638322\n ],\n [\n -93.9990234375,\n 33.38558626887102\n ],\n [\n -102.996826171875,\n 33.38558626887102\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"42","issue":"8","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-04-23","publicationStatus":"PW","scienceBaseUri":"54dd2a6fe4b08de9379b305e","contributors":{"authors":[{"text":"McNamara, Daniel E. 0000-0001-6860-0350 mcnamara@usgs.gov","orcid":"https://orcid.org/0000-0001-6860-0350","contributorId":402,"corporation":false,"usgs":true,"family":"McNamara","given":"Daniel","email":"mcnamara@usgs.gov","middleInitial":"E.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":540397,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Benz, Harley M. 0000-0002-6860-2134 benz@usgs.gov","orcid":"https://orcid.org/0000-0002-6860-2134","contributorId":794,"corporation":false,"usgs":true,"family":"Benz","given":"Harley","email":"benz@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":540398,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Herrmann, Robert B.","contributorId":80255,"corporation":false,"usgs":false,"family":"Herrmann","given":"Robert B.","affiliations":[],"preferred":false,"id":540399,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bergman, Eric A. 0000-0002-7069-8286","orcid":"https://orcid.org/0000-0002-7069-8286","contributorId":84513,"corporation":false,"usgs":false,"family":"Bergman","given":"Eric","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":540400,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Earle, Paul S. pearle@usgs.gov","contributorId":840,"corporation":false,"usgs":true,"family":"Earle","given":"Paul","email":"pearle@usgs.gov","middleInitial":"S.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":false,"id":540401,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Holland, Austin F.","contributorId":59243,"corporation":false,"usgs":false,"family":"Holland","given":"Austin","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":540402,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Baldwin, Randy W. rbaldwin@usgs.gov","contributorId":4510,"corporation":false,"usgs":true,"family":"Baldwin","given":"Randy","email":"rbaldwin@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":540403,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Gassner, A.","contributorId":139218,"corporation":false,"usgs":true,"family":"Gassner","given":"A.","email":"","affiliations":[],"preferred":false,"id":540404,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70138590,"text":"fs20153004 - 2015 - Effects of water-resource development on Yellowstone River streamflow, 1928-2002","interactions":[],"lastModifiedDate":"2015-02-11T10:42:27","indexId":"fs20153004","displayToPublicDate":"2015-02-11T10:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-3004","title":"Effects of water-resource development on Yellowstone River streamflow, 1928-2002","docAbstract":"Major floods in 1996 and 1997 intensified public concern about the effects of human activities on the Yellowstone River in Montana. In 1999, the Yellowstone River Conservation District Council, whose members are primarily representatives from the conservation districts bordering the main stem of the Yellowstone River, was formed to promote wise use and conservation of the Yellowstone River’s natural resources. The Yellowstone River Conservation District Council is working with the U.S. Army Corps of Engineers to understand the cumulative hydrologic effects of water-resource development in the Yellowstone River Basin. The U.S. Army Corps of Engineers, Yellowstone River Conservation District Council, and U.S. Geological Survey began cooperatively studying the Yellowstone River in 2010, publishing four reports describing streamflow information for selected sites in the Yellowstone River Basin, 1928–2002. Detailed information about the methods used, as well as summary streamflow statistics, are available in the four reports. The purpose of this fact sheet is to highlight findings from the published reports and describe the effects of water use and structures, primarily dams, on the Yellowstone River streamflow.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20153004","collaboration":"Prepared in cooperation with the Yellowstone River Conservation District Council and the U.S. Army Corps of Engineers","usgsCitation":"Eddy-Miller, C., and Chase, K.J., 2015, Effects of water-resource development on Yellowstone River streamflow, 1928-2002: U.S. Geological Survey Fact Sheet 2015-3004, 6 p., https://doi.org/10.3133/fs20153004.","productDescription":"6 p.","numberOfPages":"6","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"1928-01-01","temporalEnd":"2002-12-31","ipdsId":"IP-059463","costCenters":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"links":[{"id":297914,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20153004.jpg"},{"id":297913,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2015/3004/pdf/fs2015-3004.pdf","text":"Report","size":"1.38 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":297906,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2015/3004/"}],"projection":"Lambert Conformal Conic projection","datum":"North American Datum of 1983","country":"United States","state":"Montana","otherGeospatial":"Yellowstone River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.03881835937499,\n 42.374778361114195\n ],\n [\n -111.03881835937499,\n 47.938426929481054\n ],\n [\n -103.216552734375,\n 47.938426929481054\n ],\n [\n -103.216552734375,\n 42.374778361114195\n ],\n [\n -111.03881835937499,\n 42.374778361114195\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2a6fe4b08de9379b3061","contributors":{"authors":[{"text":"Eddy-Miller, Cheryl A.","contributorId":86755,"corporation":false,"usgs":true,"family":"Eddy-Miller","given":"Cheryl A.","affiliations":[],"preferred":false,"id":540411,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chase, Katherine J. 0000-0002-5796-4148 kchase@usgs.gov","orcid":"https://orcid.org/0000-0002-5796-4148","contributorId":454,"corporation":false,"usgs":true,"family":"Chase","given":"Katherine","email":"kchase@usgs.gov","middleInitial":"J.","affiliations":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"preferred":true,"id":540442,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70140818,"text":"ofr20141248 - 2015 - Magnetotelluric data collected to characterize aquifers in the San Luis Basin, New Mexico","interactions":[],"lastModifiedDate":"2015-02-11T09:38:42","indexId":"ofr20141248","displayToPublicDate":"2015-02-11T09:30:00","publicationYear":"2015","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":"2014-1248","title":"Magnetotelluric data collected to characterize aquifers in the San Luis Basin, New Mexico","docAbstract":"The U.S. Geological Survey is conducting a series of multidisciplinary studies of the San Luis Basin as part of the Geologic Framework of Rio Grande Basins project. Detailed geologic mapping, high-resolution airborne magnetic surveys, gravity surveys, magnetotelluric surveys, and hydrologic and lithologic data are being used to better understand the aquifers in the San Luis Basin. This report describes one north-south and two east-west regional magnetotelluric sounding profiles, acquired in June of 2010 and July and August of 2011, across the San Luis Basin in northern New Mexico. No interpretation of the data is included.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141248","usgsCitation":"Ailes, C.E., and Rodriguez, B.D., 2015, Magnetotelluric data collected to characterize aquifers in the San Luis Basin, New Mexico: U.S. Geological Survey Open-File Report 2014-1248, Report: iv, 9 p.; Table 2; Appendix, https://doi.org/10.3133/ofr20141248.","productDescription":"Report: iv, 9 p.; Table 2; Appendix","numberOfPages":"13","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-038565","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":297912,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141248.jpg"},{"id":297905,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1248/"},{"id":297909,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1248/pdf/ofr2014-1248.pdf","text":"Report","size":"1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":297910,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2014/1248/downloads/ofr2014-1248_Table2.xls","text":"Table 2","size":"1.27 MB","linkFileType":{"id":3,"text":"xlsx"},"description":"Table 2"},{"id":297911,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2014/1248/downloads/ofr2014-1248_Appendix.pdf","size":"79.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Appendix"}],"country":"United States","state":"New Mexico","otherGeospatial":"San Luis Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.28036499023438,\n 36.147855714690515\n ],\n [\n -106.28036499023438,\n 36.99377838872517\n ],\n [\n -105.10345458984375,\n 36.99377838872517\n ],\n [\n -105.10345458984375,\n 36.147855714690515\n ],\n [\n -106.28036499023438,\n 36.147855714690515\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2a94e4b08de9379b310e","contributors":{"authors":[{"text":"Ailes, Chad E. cailes@usgs.gov","contributorId":3995,"corporation":false,"usgs":true,"family":"Ailes","given":"Chad","email":"cailes@usgs.gov","middleInitial":"E.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":540410,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rodriguez, Brian D. 0000-0002-2263-611X brod@usgs.gov","orcid":"https://orcid.org/0000-0002-2263-611X","contributorId":836,"corporation":false,"usgs":true,"family":"Rodriguez","given":"Brian","email":"brod@usgs.gov","middleInitial":"D.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":540409,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70140628,"text":"ofr20151028 - 2015 - Strike-parallel and strike-normal coordinate system around geometrically complicated rupture traces: use by NGA-West2 and further improvements","interactions":[],"lastModifiedDate":"2015-02-11T09:20:44","indexId":"ofr20151028","displayToPublicDate":"2015-02-11T09:15:00","publicationYear":"2015","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":"2015-1028","title":"Strike-parallel and strike-normal coordinate system around geometrically complicated rupture traces: use by NGA-West2 and further improvements","docAbstract":"We present a two-dimensional system of generalized coordinates for use with geometrically complex fault ruptures that are neither straight nor continuous. The coordinates are a generalization of the conventional strike-normal and strike-parallel coordinates of a single straight fault. The presented conventions and formulations are applicable to a single curved trace, as well as multiple traces representing the rupture of branching faults or noncontiguous faults. An early application of our generalized system is in the second round of the Next Generation of Ground-Motion Attenuation Model project for the Western United States (NGA-West2), where they were used in the characterization of the hanging-wall effects. We further improve the NGA-West2 strike-parallel formulation for multiple rupture traces with a more intuitive definition of the nominal strike direction. We also derive an analytical expression for the gradient of the generalized strike-normal coordinate. The direction of this gradient may be used as the strike-normal direction in the study of polarization effects on ground motions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151028","usgsCitation":"Spudich, P.A., and Chiou, B., 2015, Strike-parallel and strike-normal coordinate system around geometrically complicated rupture traces: use by NGA-West2 and further improvements: U.S. Geological Survey Open-File Report 2015-1028, iv, 20 p., https://doi.org/10.3133/ofr20151028.","productDescription":"iv, 20 p.","numberOfPages":"28","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-062882","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":297908,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20151028.PNG"},{"id":297903,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2015/1028/"},{"id":297907,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1028/pdf/ofr2015-1028.pdf","text":"Report","size":"938 kB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2ab9e4b08de9379b31ad","contributors":{"authors":[{"text":"Spudich, Paul A. 0000-0002-9484-4997 spudich@usgs.gov","orcid":"https://orcid.org/0000-0002-9484-4997","contributorId":2372,"corporation":false,"usgs":true,"family":"Spudich","given":"Paul","email":"spudich@usgs.gov","middleInitial":"A.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":540396,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chiou, Brian","contributorId":139219,"corporation":false,"usgs":false,"family":"Chiou","given":"Brian","affiliations":[],"preferred":false,"id":540412,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70225727,"text":"70225727 - 2015 - Simulation of acceleration field of the Lushan earthquake (Ms7.0, April 20, 2013, China)","interactions":[],"lastModifiedDate":"2021-11-05T11:49:49.750359","indexId":"70225727","displayToPublicDate":"2015-02-11T06:45:27","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1517,"text":"Engineering Geology","active":true,"publicationSubtype":{"id":10}},"title":"Simulation of acceleration field of the Lushan earthquake (Ms7.0, April 20, 2013, China)","docAbstract":"The acceleration field of the Lushan earthquake (Ms7.0, April 20, 2013, China) is simulated using a new modified version of the stochastic finite-fault method (EXSIM) based on a dynamic corner frequency approach. To incorporate the effect of heterogeneous slip distribution on the variation of source spectrum, we adopt an empirical source spectral model and derive the corresponding dynamic parameters, which vary with the cumulative seismic moment of the ruptured area.
The new modified method is validated by: 1) comparison of the simulation results with those obtained from the EXSIM method using near-fault ground motion data of the 1994 Northridge earthquake; 2) comparison of simulated PGA contour map inferred from synthetic time histories at 315 grid locations with the observed PGA shakemap for the 2013 Lushan earthquake; 3) comparison of simulated PGA with those predicted by ground-motion prediction equations (GMPEs); and 4) comparison of simulated time histories with observed acceleration records at six strong motion stations during the mainshock of the Lushan earthquake, in which local site response is considered in the simulation. These comparisons confirm the validity of the new simulation procedure for purposes of regional strong ground motion estimation. Limitations of the procedure in modeling the phasing of different arrivals in the seismic signal and near-surface response of geologic deposits are discussed.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.enggeo.2015.02.003","usgsCitation":"Guoxin, W., Yang, D., and Borcherdt, R.D., 2015, Simulation of acceleration field of the Lushan earthquake (Ms7.0, April 20, 2013, China): Engineering Geology, v. 189, p. 84-97, https://doi.org/10.1016/j.enggeo.2015.02.003.","productDescription":"14 p.","startPage":"84","endPage":"97","ipdsId":"IP-052934","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":391420,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"China","otherGeospatial":"Lushan","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 113.31298828125,\n 28.478348692223165\n ],\n [\n 118.7841796875,\n 28.478348692223165\n ],\n [\n 118.7841796875,\n 32.2313896627376\n ],\n [\n 113.31298828125,\n 32.2313896627376\n ],\n [\n 113.31298828125,\n 28.478348692223165\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"189","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Guoxin, Wang","contributorId":268328,"corporation":false,"usgs":false,"family":"Guoxin","given":"Wang","email":"","affiliations":[],"preferred":false,"id":826420,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yang, Ding","contributorId":268329,"corporation":false,"usgs":false,"family":"Yang","given":"Ding","email":"","affiliations":[],"preferred":false,"id":826421,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Borcherdt, Roger D. 0000-0002-8668-0849","orcid":"https://orcid.org/0000-0002-8668-0849","contributorId":257482,"corporation":false,"usgs":true,"family":"Borcherdt","given":"Roger","email":"","middleInitial":"D.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":826422,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70140627,"text":"70140627 - 2015 - Repeated landscape-scale treatments following fire suppress a non-native annual grass and promote recovery of native perennial vegetation","interactions":[],"lastModifiedDate":"2015-05-18T11:07:49","indexId":"70140627","displayToPublicDate":"2015-02-10T14:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1018,"text":"Biological Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Repeated landscape-scale treatments following fire suppress a non-native annual grass and promote recovery of native perennial vegetation","docAbstract":"Invasive non-native species pose a large threat to restoration efforts following large-scale disturbances. Bromus tectorum (cheatgrass) is a non-native annual grass in the western U.S. that both spreads quickly following fire and accelerates the fire cycle. Herbicide and seeding applications are common restoration practices to break the positive fire-invasion feedback loop and recover native perennial species, but their interactive effects have infrequently been tested at the landscape-scale and repeated in time to encourage long-lasting effects. We determined the efficacy of repeated post-fire application of the herbicide imazapic and seeding treatments to suppressBromus abundance and promote perennial vegetation recovery. We found that the selective herbicide reduced Bromus cover by ~30 % and density by >50 % across our study sites, but had a strong initial negative effect on seeded species. The most effective treatment to promote perennial seeded species cover was seeding them alone followed by herbicide application 3 years later when the seeded species had established. The efficacy of the treatments was strongly influenced by water availability, as precipitation positively affected the density and cover of Bromus; soil texture and aspect secondarily influenced Bromus abundance and seeded species cover by modifying water retention in this semi-arid region. Warmer temperatures positively affected the non-native annual grass in the cool-season, but negatively affected seeded perennial species in the warm-season, suggesting an important role of seasonality in a region projected to experience large increases in warming in the future. Our results highlight the importance of environmental interactions and repeated treatments in influencing restoration outcomes at the landscape-scale.
","language":"English","publisher":"Springer","doi":"10.1007/s10530-015-0847-x","usgsCitation":"Munson, S.M., Long, A.L., Decker, C.E., Johnson, K.A., Walsh, K., and Miller, M.E., 2015, Repeated landscape-scale treatments following fire suppress a non-native annual grass and promote recovery of native perennial vegetation: Biological Invasions, v. 17, no. 6, p. 1915-1926, https://doi.org/10.1007/s10530-015-0847-x.","productDescription":"12 p.","startPage":"1915","endPage":"1926","numberOfPages":"12","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-058692","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":297901,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah","otherGeospatial":"Zion National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -113.26629638671875,\n 37.084762325442966\n ],\n [\n -113.26629638671875,\n 37.54893261064109\n ],\n [\n -112.78976440429688,\n 37.54893261064109\n ],\n [\n -112.78976440429688,\n 37.084762325442966\n ],\n [\n -113.26629638671875,\n 37.084762325442966\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"17","issue":"6","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-02-05","publicationStatus":"PW","scienceBaseUri":"54dd2aa9e4b08de9379b3170","contributors":{"authors":[{"text":"Munson, Seth M. 0000-0002-2736-6374 smunson@usgs.gov","orcid":"https://orcid.org/0000-0002-2736-6374","contributorId":1334,"corporation":false,"usgs":true,"family":"Munson","given":"Seth","email":"smunson@usgs.gov","middleInitial":"M.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":540261,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Long, A. Lexine along@usgs.gov","contributorId":139181,"corporation":false,"usgs":true,"family":"Long","given":"A.","email":"along@usgs.gov","middleInitial":"Lexine","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":false,"id":540262,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Decker, Cheryl E.","contributorId":86051,"corporation":false,"usgs":false,"family":"Decker","given":"Cheryl","email":"","middleInitial":"E.","affiliations":[{"id":6959,"text":"National Park Service Southeast Utah Group","active":true,"usgs":false}],"preferred":false,"id":540263,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Johnson, Katie A.","contributorId":139182,"corporation":false,"usgs":false,"family":"Johnson","given":"Katie","email":"","middleInitial":"A.","affiliations":[{"id":12684,"text":"National Park Service, Lassen Volcanic National Park, Mineral, CA, 96063, USA","active":true,"usgs":false}],"preferred":false,"id":540264,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Walsh, Kathleen","contributorId":139183,"corporation":false,"usgs":false,"family":"Walsh","given":"Kathleen","email":"","affiliations":[{"id":12685,"text":"National Park Service, Zion National Park, Springdale, UT, 84767, USA","active":true,"usgs":false}],"preferred":false,"id":540265,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Miller, Mark E.","contributorId":91580,"corporation":false,"usgs":false,"family":"Miller","given":"Mark","email":"","middleInitial":"E.","affiliations":[{"id":6959,"text":"National Park Service Southeast Utah Group","active":true,"usgs":false}],"preferred":false,"id":540266,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70142047,"text":"70142047 - 2015 - Model-based interpretation of sediment concentration and vertical flux measurements in a shallow estuarine environment","interactions":[],"lastModifiedDate":"2015-03-09T11:10:42","indexId":"70142047","displayToPublicDate":"2015-02-10T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2620,"text":"Limnology and Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"Model-based interpretation of sediment concentration and vertical flux measurements in a shallow estuarine environment","docAbstract":"A one-dimensional numerical model describing tidally varying vertical mixing and settling was used to interpret sediment concentrations and vertical fluxes observed in the shoals of South San Francisco Bay by two acoustic Doppler velocimeters (ADVs) at elevations of 0.36 m and 0.72 m above bed. Measured sediment concentrations changed by up to 100 g m−3 over the semidiurnal tidal cycle. These dynamics were dominated by local resuspension and settling. Multiple particle class models suggested the existence of a class with fast settling velocities (ws of 9.0 × 10−4 m s−1 in spring and 5.8 × 10−4 m s−1 in fall) and a slowly settling particle fraction (ws of <1 × 10−7 m s−1 in spring and 1.4 × 10−5 m s−1 in fall). Modeled concentrations of slowly settling particles at 0.36 m were as high as 20 g m−3 during fall and varied with the spring-neap cycle while fine sediment concentrations in spring were constant around 5 g m−3. Analysis of in situ water column floc size distributions suggested that floc properties in the lower part of the water column were most likely governed by particle-size distribution on the bed and not by coagulation, validating our multiple particle size approach. A comparison of different sediment bed models with respect to model performance, sensitivity, and identifiability suggested that the use of a sediment erosion model linear in bottom shear stress τb (E = M (τb − τc)) was the most appropriate choice to describe the field observations when the critical shear stress τc and the proportionality factor M were kept constant.
","language":"English","publisher":"Wiley","doi":"10.1002/lno.10047","usgsCitation":"Brand, A., Lacy, J.R., Gladding, S., Holleman, R., and Stacey, M., 2015, Model-based interpretation of sediment concentration and vertical flux measurements in a shallow estuarine environment: Limnology and Oceanography, v. 60, no. 2, p. 463-481, https://doi.org/10.1002/lno.10047.","productDescription":"19 p.","startPage":"463","endPage":"481","numberOfPages":"19","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-030148","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":472281,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.dora.lib4ri.ch/eawag/islandora/object/eawag%3A8063","text":"External Repository"},{"id":298178,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"South San Francisco Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.40554809570311,\n 37.42307124980106\n ],\n [\n -122.40554809570311,\n 37.69849090879089\n ],\n [\n -121.92008972167969,\n 37.69849090879089\n ],\n [\n -121.92008972167969,\n 37.42307124980106\n ],\n [\n -122.40554809570311,\n 37.42307124980106\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"60","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-02-10","publicationStatus":"PW","scienceBaseUri":"54f19544e4b02419550ceae8","contributors":{"authors":[{"text":"Brand, Andreas","contributorId":32415,"corporation":false,"usgs":false,"family":"Brand","given":"Andreas","email":"","affiliations":[{"id":12775,"text":"Department of Surface Waters – Research and Management, Swiss Federal Institute of Aquatic Science and Technology (Eawag), Kastanienbaum, Switzerland","active":true,"usgs":false}],"preferred":false,"id":541568,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lacy, Jessica R. 0000-0002-2797-6172 jlacy@usgs.gov","orcid":"https://orcid.org/0000-0002-2797-6172","contributorId":3158,"corporation":false,"usgs":true,"family":"Lacy","given":"Jessica","email":"jlacy@usgs.gov","middleInitial":"R.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":541567,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gladding, Steve","contributorId":54481,"corporation":false,"usgs":false,"family":"Gladding","given":"Steve","email":"","affiliations":[{"id":12776,"text":"Department of Civil and Environmental Engineering, University of California, Berkeley, California, USA","active":true,"usgs":false}],"preferred":false,"id":541571,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Holleman, Rusty","contributorId":139500,"corporation":false,"usgs":false,"family":"Holleman","given":"Rusty","affiliations":[{"id":12776,"text":"Department of Civil and Environmental Engineering, University of California, Berkeley, California, USA","active":true,"usgs":false}],"preferred":false,"id":541570,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stacey, Mark T.","contributorId":94531,"corporation":false,"usgs":false,"family":"Stacey","given":"Mark T.","affiliations":[{"id":12776,"text":"Department of Civil and Environmental Engineering, University of California, Berkeley, California, USA","active":true,"usgs":false}],"preferred":false,"id":541569,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70099102,"text":"sir20145007 - 2015 - Geomorphic, flood, and groundwater-flow characteristics of Bayfield Peninsula streams, Wisconsin, and implications for brook-trout habitat","interactions":[],"lastModifiedDate":"2015-02-09T16:17:27","indexId":"sir20145007","displayToPublicDate":"2015-02-09T16:15:00","publicationYear":"2015","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":"2014-5007","title":"Geomorphic, flood, and groundwater-flow characteristics of Bayfield Peninsula streams, Wisconsin, and implications for brook-trout habitat","docAbstract":"In 2002–03, the U.S. Geological Survey conducted a study of the geomorphic, flood, and groundwater-flow characteristics of five Bayfield Peninsula streams, Wisconsin (Cranberry River, Bark River, Raspberry River, Sioux River, and Whittlesey Creek) to determine the physical limitations for brook-trout habitat. The goals of the study were threefold: (1) to describe geomorphic characteristics and processes, (2) to determine how land-cover characteristics affect flood peaks, and (3) to determine how regional groundwater flow patterns affect base flow.
\nThe geomorphic characterization consisted of analyses of historical aerial photographs and General Land Office Survey notes, observations from helicopter video footage, surveys of valley cross sections, and coring. Sources of sediment were identified from the helicopter video and field surveys, and past erosion-control techniques were evaluated. Geomorphic processes, such as runoff sediment erosion, transport, and deposition, are driven by channel location within the drainage network, texture of glacial deposits, and proximity to postglacial lake shorelines; these processes have historically increased because of decreases in upland forest cover and channel roughness. Sources of sediment for all studied streams mainly came from bank, terrace, or bluff erosion along main stem reaches and along feeder tributaries that bisect main-stem entrenched valley sides. Bluff, terrace, and bank erosion were the major sources of sediment to Whittlesey Creek and the Sioux River. No active bluff erosion was observed on the Cranberry River or the Bark River but anecdotal information suggests that landslides occasionally happen on the Cranberry River. For the Bark River, sources of sediment were somewhat evenly divided among road crossings (bridges, culverts, and unimproved forest lanes), terrace erosion, bank erosion, and incision along upper main stems and feeder channels along valley sides. Evaluation of past erosion-control techniques indicated that bluffs were stabilized by a combination of artificial hardening and bioengineering of the bluff base and reducing mass wasting of the tops of the bluffs.
\nFlood hydrographs for the Cranberry River were simulated for four land-cover scenarios—late 20th century (1992–93), presettlement (before 1870), peak agriculture (1928), and developed (25 percent urban). Results were compared to previous simulations of flood peaks for Whittlesey Creek and for North Fish Creek (southern adjacent basin to Whittlesey Creek). Even though most uplands are presently forested, flood peaks simulated for 1992–93 were 1.5 to 2 times larger than presettlement flood peaks. The increased flood peaks caused (1) increased incision along upper main stems and tributaries that bisect entrenched valley sides, (2) bluff and terrace erosion along reaches with entrenched valleys, (3) overbank deposition and bar formation in middle and lower main stems, and (4) aggradation in mouth areas.
\nA base-flow survey was conducted and a groundwater-flow model was developed for the Bayfield Peninsula to delineate groundwater contributing areas. A deep aquifer system, which includes thick deposits of sand and the upper part of the bedrock, is recharged through the permeable sands in the center of the peninsula. Base flow is unevenly distributed among the Bayfield streams and depends on the amount of channel incision and the proximity of the channels to the recharge area and coarse outwash deposits. Groundwater contributing areas for the five streams do not coincide with surface-water-contributing areas. About 89 percent of total recharge to the deep aquifer system discharges to Bayfield streams; the remaining 11 percent directly discharges to Lake Superior. Historical land-cover changes have had negligible effects on groundwater-flow from the deep aquifer system.
\nAvailable brook-trout habitat is dependent on the locations of groundwater upwellings, the sizes of flood peaks, and sediment loads. Management practices that focus on reducing or slowing runoff from upland areas and increasing channel roughness have potential to reduce flood peaks, erosion, and sedimentation and improve brook-trout habitat in all Bayfield Peninsula streams.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145007","collaboration":"In cooperation with the Wisconsin Department of Natural Resources","usgsCitation":"Fitzpatrick, F.A., Peppler, M.C., Saad, D.A., Pratt, D.M., and Lenz, B.N., 2015, Geomorphic, flood, and groundwater-flow characteristics of Bayfield Peninsula streams, Wisconsin, and implications for brook-trout habitat: U.S. Geological Survey Scientific Investigations Report 2014-5007, vii, 79 p., https://doi.org/10.3133/sir20145007.","productDescription":"vii, 79 p.","numberOfPages":"92","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-051103","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":297884,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145007.jpg"},{"id":297883,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5007/pdf/sir2014-5007.pdf","text":"Report","size":"23.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":297882,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5007/"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Bayfield Peninsula","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.29638671875,\n 46.30140615437332\n ],\n [\n -91.29638671875,\n 47.07012182383309\n ],\n [\n -89.93408203124999,\n 47.07012182383309\n ],\n [\n -89.93408203124999,\n 46.30140615437332\n ],\n [\n -91.29638671875,\n 46.30140615437332\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2a82e4b08de9379b30b3","contributors":{"authors":[{"text":"Fitzpatrick, Faith A. fafitzpa@usgs.gov","contributorId":1182,"corporation":false,"usgs":true,"family":"Fitzpatrick","given":"Faith","email":"fafitzpa@usgs.gov","middleInitial":"A.","affiliations":[{"id":476,"text":"North Carolina Water Science Center","active":true,"usgs":true}],"preferred":false,"id":518619,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Peppler, Marie C. 0000-0002-1120-9673 mpeppler@usgs.gov","orcid":"https://orcid.org/0000-0002-1120-9673","contributorId":825,"corporation":false,"usgs":true,"family":"Peppler","given":"Marie","email":"mpeppler@usgs.gov","middleInitial":"C.","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":518618,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Saad, David A. dasaad@usgs.gov","contributorId":121,"corporation":false,"usgs":true,"family":"Saad","given":"David","email":"dasaad@usgs.gov","middleInitial":"A.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":518617,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pratt, Dennis M.","contributorId":7673,"corporation":false,"usgs":true,"family":"Pratt","given":"Dennis","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":518620,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lenz, Bernard N.","contributorId":85170,"corporation":false,"usgs":true,"family":"Lenz","given":"Bernard","email":"","middleInitial":"N.","affiliations":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"preferred":false,"id":518621,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70140587,"text":"fs20143098 - 2015 - Climate change: evaluating your local and regional water resources","interactions":[],"lastModifiedDate":"2015-02-09T14:43:33","indexId":"fs20143098","displayToPublicDate":"2015-02-09T14:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-3098","title":"Climate change: evaluating your local and regional water resources","docAbstract":"The BCM is a fine-scale hydrologic model that uses detailed maps of soils, geology, topography, and transient monthly or daily maps of potential evapotranspiration, air temperature, and precipitation to generate maps of recharge, runoff, snow pack, actual evapotranspiration, and climatic water deficit. With these comprehensive environmental inputs and experienced scientific analysis, the BCM provides resource managers with important hydrologic and ecologic understanding of a landscape or basin at hillslope to regional scales. The model is calibrated using historical climate and streamflow data over the range of geologic materials specific to an area. Once calibrated, the model is used to translate climate-change data into hydrologic responses for a defined landscape, to provide managers an understanding of potential ecological risks and threats to water supplies and managed hydrologic systems. Although limited to estimates of unimpaired hydrologic conditions, estimates of impaired conditions, such as agricultural demand, diversions, or reservoir outflows can be incorporated into the calibration of the model to expand its utility. Additionally, the model can be linked to other models, such as groundwater-flow models (that is, MODFLOW) or the integrated hydrologic model (MF-FMP), to provide information about subsurface hydrologic processes. The model can be applied at a relatively small scale, but also can be applied to large-scale national and international river basins.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20143098","usgsCitation":"Flint, L.E., Flint, A.L., and Thorne, J.H., 2015, Climate change: evaluating your local and regional water resources: U.S. Geological Survey Fact Sheet 2014-3098, 6 p., https://doi.org/10.3133/fs20143098.","productDescription":"6 p.","numberOfPages":"6","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-045835","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":297878,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20143098.JPG"},{"id":297877,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2014/3098/pdf/fs2014-3098.pdf","text":"Report","size":"4.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":297875,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2014/3098/"}],"publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2a5ee4b08de9379b301c","contributors":{"authors":[{"text":"Flint, Lorraine E. 0000-0002-7868-441X lflint@usgs.gov","orcid":"https://orcid.org/0000-0002-7868-441X","contributorId":1184,"corporation":false,"usgs":true,"family":"Flint","given":"Lorraine","email":"lflint@usgs.gov","middleInitial":"E.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":540209,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Flint, Alan L. 0000-0002-5118-751X aflint@usgs.gov","orcid":"https://orcid.org/0000-0002-5118-751X","contributorId":1492,"corporation":false,"usgs":true,"family":"Flint","given":"Alan","email":"aflint@usgs.gov","middleInitial":"L.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":540208,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thorne, James H.","contributorId":139144,"corporation":false,"usgs":false,"family":"Thorne","given":"James","email":"","middleInitial":"H.","affiliations":[{"id":12659,"text":"U C Davis","active":true,"usgs":false}],"preferred":false,"id":540210,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70143183,"text":"ds69JJ - 2015 - Map of assessed continuous (unconventional) oil resources in the United States, 2014","interactions":[],"lastModifiedDate":"2015-05-01T11:05:45","indexId":"ds69JJ","displayToPublicDate":"2015-02-09T09:00:00","publicationYear":"2015","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":"69","chapter":"JJ","title":"Map of assessed continuous (unconventional) oil resources in the United States, 2014","docAbstract":"The U.S. Geological Survey (USGS) conducts quantitative assessments of potential oil and gas resources of the onshore United States and associated coastal State waters. Since 2000, the USGS has completed assessments of continuous (unconventional) resources in the United States based on geologic studies and analysis of well-production data and has compiled digital maps of the assessment units classified into four categories: shale gas, tight gas, coalbed gas, and shale oil or tight oil (continuous oil). This is the fourth digital map product in a series of USGS unconventional oil and gas resource maps; its focus being shale-oil or tight-oil (continuous-oil) assessments. The map plate included in this report can be printed in hardcopy form or downloaded in a Geographic Information System (GIS) data package, which includes an ArcGIS ArcMap document (.mxd), geodatabase (.gdb), and a published map file (.pmf). Supporting geologic studies of total petroleum systems and assessment units, as well as studies of the methodology used in the assessment of continuous-oil resources in the United States, are listed with hyperlinks in table 1. Assessment results and geologic reports are available at the USGS websitehttp://energy.usgs.gov/OilGas/AssessmentsData/NationalOilGasAssessment.aspx.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds69JJ","usgsCitation":"U.S. Geological Survey National Assessment of Oil and Gas Resources Team, 2015, Map of assessed continuous (unconventional) oil resources in the United States, 2014: U.S. Geological Survey Data Series 69, Report: iv, 14 p.; Map: 46.00 x 33.00 inches; 1 Table; Downloads Directory, https://doi.org/10.3133/ds69JJ.","productDescription":"Report: iv, 14 p.; Map: 46.00 x 33.00 inches; 1 Table; Downloads Directory","numberOfPages":"22","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2014-01-01","temporalEnd":"2014-12-31","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":298631,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":298625,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/dds/dds-069/dds-069-jj/"},{"id":298626,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/dds/dds-069/dds-069-jj/pdf/dds_69_jj.pdf","size":"1.0 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":298627,"rank":3,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/dds/dds-069/dds-069-jj/downloads/dds69-jj_plate1.pdf","text":"Map","size":"3.2 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":298628,"rank":4,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/dds/dds-069/dds-069-jj/downloads/table_1.pdf","text":"Table 1","size":"436 kB","linkFileType":{"id":1,"text":"pdf"}},{"id":298629,"rank":5,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/dds/dds-069/dds-069-jj/downloads/","text":"Downloads Directory","linkHelpText":"Contains: geospatial database. 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H. lbiewick@usgs.gov","contributorId":1086,"corporation":false,"usgs":true,"family":"Biewick","given":"Laura","email":"lbiewick@usgs.gov","middleInitial":"R. H.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":542499,"contributorType":{"id":3,"text":"Compilers"},"rank":1}],"authors":[{"text":"U.S. Geological Survey National Assessment of Oil and Gas Resources Team","contributorId":128233,"corporation":true,"usgs":false,"organization":"U.S. Geological Survey National Assessment of Oil and Gas Resources Team","id":542498,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70141187,"text":"70141187 - 2015 - Medea genes, handedness and other traits","interactions":[],"lastModifiedDate":"2015-03-17T16:02:58","indexId":"70141187","displayToPublicDate":"2015-02-08T17:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3870,"text":"Journal of Sleep Disorders & Therapy","active":true,"publicationSubtype":{"id":10}},"title":"Medea genes, handedness and other traits","docAbstract":"Medea factors or genes are maternal-effects mechanisms, found in many species, in which the mother's body selectively kills embryos of a certain genotype.Humans have a similar genetic mechanism, the gene RHD which produces Rh-factor involved in blood type.Recently I proposed that RHD acts as a maternal-effects gene that determines handedness (i.e., right handed or non-right handed) in individuals of our species. Here, I argue that RHD functions as a Medea gene as well.The handedness gene (and also RHD itself in some cases) has been implicated in autism spectrum disorders (ASD), bipolar disorder, cerebral laterality (i.e., right-brained or left-brained speech laterality), hair-whorl rotation, schizophrenia, sexual orientation, and speech dyslexia.Identifying the gene or genes that determine handedness or cerebral laterality may help uncover the mechanisms underlying these behavioral phenotypes in our species.A relatively simple test of the handedness hypothesis has been proposed:In a sample of humans for whom handedness has been evaluated, we would need to genotype for RHD by determining whether Rh+ individuals have one or two copies of the dominant allele. If RHD and perhaps also an interaction with RHCE are involved in sexual orientation, it explains how selection could favor a gene or genes which cause some people to become non-heterosexual.The literature on Medea genes provides the explanation:A Medea allele must increase in frequency, sometimes to fixation (i.e., 100% frequency) even if it reduces fecundity (e.g., birth rate).In addition, treatment for RHD maternal-fetal genotype incompatibility, which allows more fetuses to survive to term now, may be one explanation for why ASD appears to be increasing in frequency in some populations, if RHD is indeed the handedness gene, although many other mechanisms have also been suggested. One wonders if bipolar disorder and the other alternative phenotypes are also increasing in frequency.
","language":"English","publisher":"OMICS Publishing Group","publisherLocation":"Los Angeles, CA","doi":"10.4172/2167-0277.1000188","usgsCitation":"Hatfield, J., 2015, Medea genes, handedness and other traits: Journal of Sleep Disorders & Therapy, v. 4, no. 1, 2 p., https://doi.org/10.4172/2167-0277.1000188.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-062923","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":472282,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.4172/2167-0277.1000188","text":"Publisher Index Page"},{"id":298652,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"4","issue":"1","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55095031e4b02e76d757e628","contributors":{"authors":[{"text":"Hatfield, Jeffrey 0000-0002-6517-2925 jhatfield@usgs.gov","orcid":"https://orcid.org/0000-0002-6517-2925","contributorId":139261,"corporation":false,"usgs":true,"family":"Hatfield","given":"Jeffrey","email":"jhatfield@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":540545,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70142199,"text":"70142199 - 2015 - Steep spatial gradients of volcanic and marine sulfur in Hawaiian rainfall and ecosystems","interactions":[],"lastModifiedDate":"2015-03-04T09:54:57","indexId":"70142199","displayToPublicDate":"2015-02-07T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Steep spatial gradients of volcanic and marine sulfur in Hawaiian rainfall and ecosystems","docAbstract":"Sulfur, a nutrient required by terrestrial ecosystems, is likely to be regulated by atmospheric processes in well-drained, upland settings because of its low concentration in most bedrock and generally poor retention by inorganic reactions within soils. Environmental controls on sulfur sources in unpolluted ecosystems have seldom been investigated in detail, even though the possibility of sulfur limiting primary production is much greater where atmospheric deposition of anthropogenic sulfur is low. Here we measure sulfur isotopic compositions of soils, vegetation and bulk atmospheric deposition from the Hawaiian Islands for the purpose of tracing sources of ecosystem sulfur. Hawaiian lava has a mantle-derived sulfur isotopic composition (δ34S VCDT) of − 0.8‰. Bulk deposition on the island of Maui had a δ34S VCDT that varied temporally, spanned a range from + 8.2 to + 19.7‰, and reflected isotopic mixing from three sources: sea-salt (+ 21.1‰), marine biogenic emissions (+ 15.6‰), and volcanic emissions from active vents on Kilauea Volcano (+ 0.8‰). A straightforward, weathering-driven transition in ecosystem sulfur sources could be interpreted in the shift from relatively low (0.0 to + 2.7‰) to relatively high (+ 17.8 to + 19.3‰) soil δ34S values along a 0.3 to 4100 ka soil age-gradient, and similar patterns in associated vegetation. However, sub-kilometer scale spatial variation in soil sulfur isotopic composition was found along soil transects assumed by age and mass balance to be dominated by atmospheric sulfur inputs. Soil sulfur isotopic compositions ranged from + 8.1 to + 20.3‰ and generally decreased with increasing elevation (0–2000 m), distance from the coast (0–12 km), and annual rainfall (180–5000 mm). Such trends reflect the spatial variation in marine versus volcanic inputs from atmospheric deposition. Broadly, these results illustrate how the sources and magnitude of atmospheric deposition can exert controls over ecosystem sulfur biogeochemistry across relatively small spatial scales.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2015.02.001","usgsCitation":"Bern, C., Chadwick, O.A., Kendall, C., and Pribil, M.J., 2015, Steep spatial gradients of volcanic and marine sulfur in Hawaiian rainfall and ecosystems: Science of the Total Environment, v. 514, p. 250-260, https://doi.org/10.1016/j.scitotenv.2015.02.001.","productDescription":"11 p.","startPage":"250","endPage":"260","numberOfPages":"11","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059624","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":472284,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://escholarship.org/uc/item/4f7889p8","text":"External Repository"},{"id":298239,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -159.906005859375,\n 18.843913201134132\n ],\n [\n -159.906005859375,\n 22.29926149974121\n ],\n [\n -154.70947265625,\n 22.29926149974121\n ],\n [\n -154.70947265625,\n 18.843913201134132\n ],\n [\n -159.906005859375,\n 18.843913201134132\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"514","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54f6e948e4b02419550d30a7","contributors":{"authors":[{"text":"Bern, Carleton R. cbern@usgs.gov","contributorId":127601,"corporation":false,"usgs":true,"family":"Bern","given":"Carleton R.","email":"cbern@usgs.gov","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":false,"id":541713,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chadwick, Oliver A.","contributorId":88244,"corporation":false,"usgs":false,"family":"Chadwick","given":"Oliver","email":"","middleInitial":"A.","affiliations":[{"id":6710,"text":"University of California, Santa Barbara, CA","active":true,"usgs":false}],"preferred":false,"id":541714,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kendall, Carol 0000-0002-0247-3405 ckendall@usgs.gov","orcid":"https://orcid.org/0000-0002-0247-3405","contributorId":1462,"corporation":false,"usgs":true,"family":"Kendall","given":"Carol","email":"ckendall@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":541715,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pribil, Michael J. mpribil@usgs.gov","contributorId":2027,"corporation":false,"usgs":true,"family":"Pribil","given":"Michael","email":"mpribil@usgs.gov","middleInitial":"J.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":541716,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70126012,"text":"ds879 - 2015 - Water- and air-quality and surficial bed-sediment monitoring of the Sweetwater Reservoir watershed, San Diego County, California, 2003-09","interactions":[],"lastModifiedDate":"2015-02-20T14:37:22","indexId":"ds879","displayToPublicDate":"2015-02-06T15:15:00","publicationYear":"2015","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":"879","title":"Water- and air-quality and surficial bed-sediment monitoring of the Sweetwater Reservoir watershed, San Diego County, California, 2003-09","docAbstract":"In 1998, the U.S. Geological Survey, in cooperation with the Sweetwater Authority, began a study to assess the overall health of the Sweetwater watershed in San Diego County, California. This study was designed to provide a data set that could be used to evaluate potential effects from the construction and operation of State Route 125 within the broader context of the water quality and air quality in the watershed. The study included regular sampling of water, air, and surficial bed sediment at Sweetwater Reservoir (SWR) for chemical constituents, including volatile organic compounds (VOCs), base-neutral and acid- extractable organic compounds (BNAs) that include polycyclic aromatic hydrocarbons (PAHs), pesticides, and metals. Additionally, water samples were collected for anthropogenic organic indicator compounds in and around SWR. Background water samples were collected at Loveland Reservoir for VOCs, BNAs, pesticides, and metals. Surficial bed-sediment samples were collected for PAHs, organochlorine pesticides, and metals at Sweetwater and Loveland Reservoirs.
\nTo monitor changes in contaminant concentration in water and air at SWR during the construction and operation of State Route 125, this study was divided into three phases. Phase One sampling (September 1998 to September 2004) was designed to establish baseline conditions for target compounds in terms of detection frequency and concentration in air and water. Phase Two (October 2004 to September 2007) continued sampling at selected monitoring sites during construction of State Route 125 to assess any effect from the construction process and the use of heavy equipment to build the roadway. Phase Three (October 2007 to August 2009) continued sampling for 2 years after the opening of State Route 125 to assess the potential changes in water quality related to vehicle emissions from the roadway alignment. Surficial bed-sediment samples were collected three times during the study—at the beginning of the study, at the start of Phase Two, and at the end of the study.
\nThis report describes the study design and the sampling and analytical methods and presents data from water, air, and surficial bed-sediment samples collected from the sixth to eleventh years of the study (October 2003–August 2009), spanning the last year of Phase one and all of Phases Two and Three. Data collected during the first 5 years of sampling have been previously published.
\nThree types of quality-control samples were used in this study—matrix spikes, blanks, and replicates. Matrix-spike data are considered to be adequate if the recovery concentration is within 30 percent of the matrix concentration. Replicate data are considered to be adequate if the replicate sample concentration is within 30 percent of the environmental sample concentration. Additionally, surrogate compounds were added to most samples to monitor sample-specific performance of the analytical method.
\nMost VOC matrix-spike recovery data associated with water samples are within acceptable criteria, but three VOCs had recoveries below the acceptable criteria; these compounds may not have been detected in water samples if they were present at low concentrations. Data for blanks associated with water samples for VOCs and metals showed no detections above their laboratory reporting levels. Most replicate data are within acceptable criteria. Quality-control data for VOC air samples resulted in flagging several reported concentrations for acetone, benzene, ethenylbenzene, and naphthalene because they may be biased high. Acetone, benzene, and toluene were detected at low concentrations in almost every VOC air blank. Some PAH and pesticide concentrations in air samples were designated as estimated because of method performance limitations. PAHs in surficial bed sediment had 83 percent of surrogates below the acceptable criteria. No matrix-spike data for metals in surficial bed sediment were outside the acceptable criteria; only beryllium had a replicate comparison outside the acceptable criteria.
\nSampling results show concentrations of the gasoline oxygenate methyl tert-butyl ether in water and air samples declined after it was phased out by the State of California in January 2004. The largest concentrations of gasoline hydrocarbons benzene and toluene in water were detected at or near the surface of the SWR. Isophorone and phenol were the two most frequently detected BNA compounds in water. Diuron, prometon, and simazine were the most frequently detected pesticide compounds in water. Concentrations of benzene and toluene in air samples were highest during the cooler months and had a consistent seasonal pattern over time. Ten PAH compounds were detected frequently in air samples. Twelve pesticide compounds were also detected in air samples. Surficial bed-sediment samples were analyzed for 53 PAHs; 22 of the compounds had one or more detections. Surficial bed-sediment samples were analyzed for 22 organic compounds; only 6 compounds had one or more detections. Surficial bed-sediment samples were analyzed for 37 metals.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds879","collaboration":"Prepared in cooperation with the Sweetwater Authority","usgsCitation":"Mendez, G.O., Majewski, M.S., Foreman, W., and Morita, A.Y., 2015, Water- and air-quality and surficial bed-sediment monitoring of the Sweetwater Reservoir watershed, San Diego County, California, 2003-09: U.S. Geological Survey Data Series 879, Report: xi, 226 p.; 5 Tables, https://doi.org/10.3133/ds879.","productDescription":"Report: xi, 226 p.; 5 Tables","numberOfPages":"242","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2003-01-01","temporalEnd":"2009-12-31","ipdsId":"IP-002295","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":297815,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds879.jpg"},{"id":297808,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0879/"},{"id":297809,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0879/pdf/ds879.pdf","size":"6.2 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":297810,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/0879/downloads/ds879_table4b_voc.xls","text":"Table 4B","size":"174 kB","linkFileType":{"id":3,"text":"xlsx"}},{"id":297811,"rank":4,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/0879/downloads/ds879_table5b_bna.xls","text":"Table 5B","size":"82 kB","linkFileType":{"id":3,"text":"xlsx"}},{"id":297812,"rank":5,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/0879/downloads/ds879_table10b_avoc.xls","text":"Table 10B","size":"240 kB","linkFileType":{"id":3,"text":"xlsx"}},{"id":297813,"rank":6,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/0879/downloads/ds879_table11b_pah.xls","text":"Table 11B","size":"313 kB","linkFileType":{"id":3,"text":"xlsx"}},{"id":297814,"rank":7,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/0879/downloads/ds879_table13_airtm.xls","text":"Table 13","size":"124 kB","linkFileType":{"id":3,"text":"xlsx"}}],"scale":"100000","projection":"Universal Transverse Mercator projection","country":"United States","state":"California","county":"San Diego County","otherGeospatial":"Sweetwater Reservoir watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.1142578125,\n 32.58963484306727\n ],\n [\n -117.1142578125,\n 32.99945000822839\n ],\n [\n -116.46606445312499,\n 32.99945000822839\n ],\n [\n -116.46606445312499,\n 32.58963484306727\n ],\n [\n -117.1142578125,\n 32.58963484306727\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2acde4b08de9379b3214","contributors":{"authors":[{"text":"Mendez, Gregory O. 0000-0002-9955-3726 gomendez@usgs.gov","orcid":"https://orcid.org/0000-0002-9955-3726","contributorId":1489,"corporation":false,"usgs":true,"family":"Mendez","given":"Gregory","email":"gomendez@usgs.gov","middleInitial":"O.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":540012,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Majewski, Michael S. majewski@usgs.gov","contributorId":440,"corporation":false,"usgs":true,"family":"Majewski","given":"Michael","email":"majewski@usgs.gov","middleInitial":"S.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":540013,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Foreman, William T. wforeman@usgs.gov","contributorId":1473,"corporation":false,"usgs":true,"family":"Foreman","given":"William T.","email":"wforeman@usgs.gov","affiliations":[{"id":452,"text":"National Water Quality Laboratory","active":true,"usgs":true}],"preferred":false,"id":540014,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Morita, Andrew Y. 0000-0002-8120-996X amorita@usgs.gov","orcid":"https://orcid.org/0000-0002-8120-996X","contributorId":1487,"corporation":false,"usgs":true,"family":"Morita","given":"Andrew","email":"amorita@usgs.gov","middleInitial":"Y.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":540015,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70134473,"text":"sir20145220 - 2015 - Estimation of unaltered daily mean streamflow at ungaged streams of New York, excluding Long Island, water years 1961-2010","interactions":[],"lastModifiedDate":"2015-02-06T12:59:44","indexId":"sir20145220","displayToPublicDate":"2015-02-06T13:45:00","publicationYear":"2015","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":"2014-5220","title":"Estimation of unaltered daily mean streamflow at ungaged streams of New York, excluding Long Island, water years 1961-2010","docAbstract":"The lakes, rivers, and streams of New York State provide an essential water resource for the State. The information provided by time series hydrologic data is essential to understanding ways to promote healthy instream ecology and to strengthen the scientific basis for sound water management decision making in New York. The U.S. Geological Survey, in cooperation with The Nature Conservancy and the New York State Energy Research and Development Authority, has developed the New York Streamflow Estimation Tool to estimate a daily mean hydrograph for the period from October 1, 1960, to September 30, 2010, at ungaged locations across the State. The New York Streamflow Estimation Tool produces a complete estimated daily mean time series from which daily flow statistics can be estimated. In addition, the New York Streamflow Estimation Tool provides a means for quantitative flow assessments at ungaged locations that can be used to address the objectives of the Clean Water Act—to restore and maintain the chemical, physical, and biological integrity of the Nation’s waters.
\nThe New York Streamflow Estimation Tool uses data from the U.S. Geological Survey streamflow network for selected streamgages in New York (excluding Long Island) and surrounding States with shared hydrologic boundaries, and physical and climate basin characteristics to estimate the natural unaltered streamflow at ungaged stream locations. The unaltered streamflow is representative of flows that are minimally altered by regulation, diversion, or mining, and other anthropogenic activities. With the streamflow network data, flow-duration exceedance probability equations were developed to estimate unaltered streamflow exceedance probabilities at an ungaged location using a methodology that equates streamflow as a percentile from a flow-duration curve for a particular day at a hydrologically similar reference streamgage with streamflow as a percentile from the flow-duration curve for the same day at an ungaged location. The reference streamgage is selected using map correlation, a geostatistical method in which variogram models are developed that correlate streamflow at one streamgage with streamflows at all other locations in the study area. Regression equations used to predict 17 flow-duration exceedance probabilities were developed to estimate the flow-duration curves at ungaged locations for New York using geographic information system-derived basin characteristics.
\nA graphical user interface, with an integrated spreadsheet summary report, has been developed to estimate and display the daily mean streamflows and statistics and to evaluate different water management or water withdrawal scenarios with the estimated monthly data. This package of regression equations, U.S. Geological Survey streamgage data, and spreadsheet application produces an interactive tool to estimate an unaltered daily streamflow hydrograph and streamflow statistics at ungaged sites in New York. Among other uses, the New York Streamflow Estimation Tool can assist water managers with permitting water withdrawals, implementing habitat protection, estimating contaminant loads, or determining the potential affect from chemical spills.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145220","collaboration":"Prepared in cooperation with The Nature Conservancy and the New York State Energy Research and Development Authority","usgsCitation":"Gazoorian, C.L., 2015, Estimation of unaltered daily mean streamflow at ungaged streams of New York, excluding Long Island, water years 1961-2010: U.S. Geological Survey Scientific Investigations Report 2014-5220, Report: viii, 29 p.; Readme; 5 Appendixes; NYSET application, https://doi.org/10.3133/sir20145220.","productDescription":"Report: viii, 29 p.; Readme; 5 Appendixes; NYSET application","numberOfPages":"42","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"1960-10-01","temporalEnd":"2010-09-30","ipdsId":"IP-055442","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":297799,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145220.jpg"},{"id":297792,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5220/"},{"id":297793,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5220/pdf/sir2014-5220.pdf"},{"id":297794,"rank":3,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sir/2014/5220/attachments/sir2014-5220_readme.pdf","text":"Readme Appendix 1-5","size":"58 kB","linkFileType":{"id":1,"text":"pdf"}},{"id":297795,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5220/attachments/sir2014-5220_app1-4.pdf","text":"Appendix 1-4 PDF","size":"308 kB","linkFileType":{"id":1,"text":"pdf"}},{"id":297796,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5220/attachments/sir2014-5220_app1-4.xlsx","text":"Appendix 1-4 XLS","size":"75 kB","linkFileType":{"id":3,"text":"xlsx"}},{"id":297797,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5220/attachments/SIR2014-5220_app5.pdf","text":"Appendix 5","size":"696 kB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"User’s Guide for the New York Streamflow Estimation Tool (NYSET) version 1.0"},{"id":297798,"rank":7,"type":{"id":7,"text":"Companion Files"},"url":"https://ny.water.usgs.gov/projects/nyset/","text":"NYSET application","linkFileType":{"id":5,"text":"html"}}],"scale":"200000","projection":"Universal Transverse Mercator projection","datum":"North American Datum of 1983","country":"United States","state":"New York","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -79.771728515625,\n 42.27730877423709\n ],\n [\n -79.7607421875,\n 42.00032514831621\n ],\n [\n -75.35522460937499,\n 42.00032514831621\n ],\n [\n -75.003662109375,\n 41.46742831254425\n ],\n [\n -73.773193359375,\n 40.863679665481676\n ],\n [\n -73.487548828125,\n 41.054501963290505\n ],\n [\n -73.2568359375,\n 42.779275360241904\n ],\n [\n -73.223876953125,\n 45.01141864227728\n ],\n [\n -75.003662109375,\n 45.034714778688624\n ],\n [\n -76.5966796875,\n 44.166444664458595\n ],\n [\n -76.201171875,\n 43.58834891179792\n ],\n [\n -79.068603515625,\n 43.29320031385282\n ],\n [\n -79.771728515625,\n 42.27730877423709\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2a74e4b08de9379b3070","contributors":{"authors":[{"text":"Gazoorian, Christopher L. 0000-0002-5408-6212 cgazoori@usgs.gov","orcid":"https://orcid.org/0000-0002-5408-6212","contributorId":2929,"corporation":false,"usgs":true,"family":"Gazoorian","given":"Christopher","email":"cgazoori@usgs.gov","middleInitial":"L.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":525962,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70140605,"text":"70140605 - 2015 - Convergence of soil nitrogen isotopes across global climate gradients","interactions":[],"lastModifiedDate":"2017-11-20T15:41:19","indexId":"70140605","displayToPublicDate":"2015-02-06T13:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"Convergence of soil nitrogen isotopes across global climate gradients","docAbstract":"Quantifying global patterns of terrestrial nitrogen (N) cycling is central to predicting future patterns of primary productivity, carbon sequestration, nutrient fluxes to aquatic systems, and climate forcing. With limited direct measures of soil N cycling at the global scale, syntheses of the 15 N: 14 N ratio of soil organic matter across climate gradients provide key insights into understanding global patterns of N cycling. In synthesizing data from over 6000 soil samples, we show strong global relationships among soil N isotopes, mean annual temperature (MAT), mean annual precipitation (MAP), and the concentrations of organic carbon and clay in soil. In both hot ecosystems and dry ecosystems, soil organic matter was more enriched in 15 N than in corresponding cold ecosystems or wet ecosystems. Below a MAT of 9.8°C, soil δ15N was invariant with MAT. At the global scale, soil organic C concentrations also declined with increasing MAT and decreasing MAP. After standardizing for variation among mineral soils in soil C and clay concentrations, soil δ15N showed no consistent trends across global climate and latitudinal gradients. Our analyses could place new constraints on interpretations of patterns of ecosystem N cycling and global budgets of gaseous N loss.
","language":"English","publisher":"Nature Publishing Group","publisherLocation":"London","doi":"10.1038/srep08280","usgsCitation":"Craine, J.M., Elmore, A.J., Wang, L., Augusto, L., Baisden, W., Brookshire, E.N., Cramer, M.D., Hasselquist, N.J., Hobbie, E.A., Kahmen, A., Koba, K., Kranabetter, J.M., Mack, M., Marin-Spiotta, E., Mayor, J.R., McLauchlan, K.K., Michelsen, A., Nardoto, G.B., Oliveira, R., Perakis, S.S., Peri, P., Quesada, C.A., Richter, A., Schipper, L.A., Stevenson, B.A., Turner, B.L., Viani, R.A., Wanek, W., and Zeller, B., 2015, Convergence of soil nitrogen isotopes across global climate gradients: Scientific Reports, v. 5, 8 p.; Article number: 8280, https://doi.org/10.1038/srep08280.","productDescription":"8 p.; Article number: 8280","numberOfPages":"8","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-050936","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":472286,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/srep08280","text":"Publisher Index Page"},{"id":297896,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -165.9375,\n -55.77657301866769\n ],\n [\n -165.9375,\n 79.10508621944108\n ],\n [\n 180.703125,\n 79.10508621944108\n ],\n [\n 180.703125,\n -55.77657301866769\n ],\n [\n -165.9375,\n -55.77657301866769\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"5","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-02-06","publicationStatus":"PW","scienceBaseUri":"54dd2a60e4b08de9379b3029","contributors":{"authors":[{"text":"Craine, Joseph M.","contributorId":139154,"corporation":false,"usgs":false,"family":"Craine","given":"Joseph","email":"","middleInitial":"M.","affiliations":[{"id":12661,"text":"Kansas State University","active":true,"usgs":false}],"preferred":false,"id":540226,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Elmore, Andrew J.","contributorId":29702,"corporation":false,"usgs":true,"family":"Elmore","given":"Andrew","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":540228,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wang, Lixin","contributorId":92943,"corporation":false,"usgs":true,"family":"Wang","given":"Lixin","email":"","affiliations":[],"preferred":false,"id":540253,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Augusto, Laurent","contributorId":139156,"corporation":false,"usgs":false,"family":"Augusto","given":"Laurent","email":"","affiliations":[{"id":12663,"text":"Bordeaux Sciences Agro","active":true,"usgs":false}],"preferred":false,"id":540229,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Baisden, W. 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G.","contributorId":139175,"corporation":false,"usgs":false,"family":"Viani","given":"Ricardo","email":"","middleInitial":"A. 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This hypothetical structure improved outflow temperature control from Detroit Dam while meeting minimum dry-season release rates and lake levels specified by the rule curve specified for Detroit Lake.
\nA water temperature target based on long-term, without-dams temperature estimates was developed and used to guide the Detroit Lake model to blend releases from the user-defined outlets at Detroit Dam. Simulations that included warm surface water releases during the spring and summer, and cool, deep hypolimnetic water releases later during autumn typically met the temperature target. Immediately downstream of Detroit Dam, these simulations resulted in temperatures within the range of the without-dams temperature estimates for most of the year until about November. The minimum release rates of flow imposed at Detroit Dam during late summer and early autumn exceeded unregulated, without-dams flow estimates. This higher flow led to temperatures near the low end of the without-dams temperature range 46.3 river miles downstream at Greens Bridge from July to September; the high flows released from Detroit Dam were less susceptible to downstream warming than the low unregulated flows. Simulations that blended warm and cool water from different outlets at Detroit Dam resulted in less daily temperature variation compared to the without-dams scenarios as far downstream as Greens Bridge.
\nEstimated egg-emergence days for endangered Upper Willamette River Chinook salmon (Oncorhynchus tshawytscha) and Upper Willamette River winter steelhead (Oncorhynchus mykiss) were assessed for all scenarios. Estimated spring Chinook fry emergence under SlidingWeir scenarios was 9 days later immediately downstream of Big Cliff Dam, and 4 days later at Greens Bridge compared with existing structural scenarios at Detroit Dam. Despite the inclusion of a hypothetical sliding weir at Detroit Dam, temperatures exceeded without-dams temperatures during November and December. These late-autumn exceedances likely represent the residual thermal effect of Detroit Lake operated to meet minimum dry-season release rates (supporting instream habitat and irrigation requirements) and lake levels specified by the current (2014) operating rules (supporting recreation and flood mitigation).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151012","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Buccola, N.L., Stonewall, A.J., and Rounds, S.A., 2015, Simulations of a hypothetical temperature control structure at Detroit Dam on the North Santiam River, northwestern Oregon: U.S. Geological Survey Open-File Report 2015-1012, vi, 30 p., https://doi.org/10.3133/ofr20151012.","productDescription":"vi, 30 p.","numberOfPages":"40","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-057390","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":297807,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20151012.JPG"},{"id":297805,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2015/1012/"},{"id":297806,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1012/pdf/ofr2015-1012.pdf","text":"Report","size":"4.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"projection":"Universal Transverse Mercator projection, Zone 10","datum":"North American Datum of 1927","country":"United States","state":"Oregon","otherGeospatial":"Big Cliff Lake, Detroit Lake, North Santiam River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.20068359374999,\n 44.469071224701096\n ],\n [\n -123.20068359374999,\n 44.912304304581525\n ],\n [\n -121.77246093750001,\n 44.912304304581525\n ],\n [\n -121.77246093750001,\n 44.469071224701096\n ],\n [\n -123.20068359374999,\n 44.469071224701096\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2ab4e4b08de9379b3194","contributors":{"authors":[{"text":"Buccola, Norman L. nbuccola@usgs.gov","contributorId":139094,"corporation":false,"usgs":true,"family":"Buccola","given":"Norman","email":"nbuccola@usgs.gov","middleInitial":"L.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":false,"id":539999,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stonewall, Adam J. 0000-0002-3277-8736 stonewal@usgs.gov","orcid":"https://orcid.org/0000-0002-3277-8736","contributorId":138801,"corporation":false,"usgs":true,"family":"Stonewall","given":"Adam","email":"stonewal@usgs.gov","middleInitial":"J.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":false,"id":540000,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rounds, Stewart A. 0000-0002-8540-2206 sarounds@usgs.gov","orcid":"https://orcid.org/0000-0002-8540-2206","contributorId":905,"corporation":false,"usgs":true,"family":"Rounds","given":"Stewart","email":"sarounds@usgs.gov","middleInitial":"A.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":540001,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70140094,"text":"70140094 - 2015 - Mineral commodity summaries 2015","interactions":[],"lastModifiedDate":"2015-02-09T14:21:20","indexId":"70140094","displayToPublicDate":"2015-02-06T13:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":6,"text":"USGS Unnumbered Series"},"seriesTitle":{"id":323,"text":"Mineral Commodity Summaries","code":"MCS","active":true,"publicationSubtype":{"id":5}},"title":"Mineral commodity summaries 2015","docAbstract":"Each chapter of the 2015 edition of the U.S. Geological Survey (USGS) Mineral Commodity Summaries (MCS) includes information on events, trends, and issues for each mineral commodity as well as discussions and tabular presentations on domestic industry structure, Government programs, tariffs, 5-year salient statistics, and world production and resources. The MCS is the earliest comprehensive source of 2014 mineral production data for the world. More than 90 individual minerals and materials are covered by two-page synopses.
\nFor mineral commodities for which there is a Government stockpile, detailed information concerning the stockpile status is included in the two-page synopsis.
\nAbbreviations and units of measure, and definitions of selected terms used in the report, are in Appendix A and Appendix B, respectively. \"Appendix C—Reserves and Resources” includes “Part A—Resource/Reserve Classification for Minerals” and “Part B—Sources of Reserves Data.\" A directory of USGS minerals information country specialists and their responsibilities is Appendix D.
\nThe USGS continually strives to improve the value of its publications to users. Constructive comments and suggestions by readers of the MCS 2015 are welcomed.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/70140094","productDescription":"Report: 196 p.; 1 Appendix","numberOfPages":"199","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063093","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":297786,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/70140094.gif"},{"id":297784,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://minerals.usgs.gov/minerals/pubs/mcs/2015/mcs2015.pdf","size":"2.5 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":297785,"rank":2,"type":{"id":3,"text":"Appendix"},"url":"https://minerals.usgs.gov/minerals/pubs/mcs/2015/mcsapp2015.pdf","linkFileType":{"id":1,"text":"pdf"}}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2a97e4b08de9379b3124","contributors":{"authors":[{"text":"Water Resources Division, U.S. Geological Survey","contributorId":128075,"corporation":true,"usgs":false,"organization":"Water Resources Division, U.S. Geological Survey","id":539782,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70140180,"text":"ofr20151027 - 2015 - Improved algorithms in the CE-QUAL-W2 water-quality model for blending dam releases to meet downstream water-temperature targets","interactions":[],"lastModifiedDate":"2015-02-06T12:51:55","indexId":"ofr20151027","displayToPublicDate":"2015-02-06T12:45:00","publicationYear":"2015","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":"2015-1027","title":"Improved algorithms in the CE-QUAL-W2 water-quality model for blending dam releases to meet downstream water-temperature targets","docAbstract":"Water-quality models allow water resource professionals to examine conditions under an almost unlimited variety of potential future scenarios. The two-dimensional (longitudinal, vertical) water-quality model CE-QUAL-W2, version 3.7, was enhanced and augmented with new features to help dam operators and managers explore and optimize potential solutions for temperature management downstream of thermally stratified reservoirs. Such temperature management often is accomplished by blending releases from multiple dam outlets that access water of different temperatures at different depths. The modified blending algorithm in version 3.7 of CE-QUAL-W2 allows the user to specify a time-series of target release temperatures, designate from 2 to 10 floating or fixed-elevation outlets for blending, impose minimum and maximum head and flow constraints for any blended outlet, and set priority designations for each outlet that allow the model to choose which outlets to use and how to balance releases among them. The modified model was tested with a variety of examples and against a previously calibrated model of Detroit Lake on the North Santiam River in northwestern Oregon, and the results compared well. These updates to the blending algorithms will allow more complicated dam-operation scenarios to be evaluated somewhat automatically with the model, with decreased need for multiple model runs or preprocessing of model inputs to fully characterize the operational constraints.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151027","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Rounds, S.A., and Buccola, N., 2015, Improved algorithms in the CE-QUAL-W2 water-quality model for blending dam releases to meet downstream water-temperature targets: U.S. Geological Survey Open-File Report 2015-1027, Report: vi, 36 p.; Examples; Model Source, https://doi.org/10.3133/ofr20151027.","productDescription":"Report: vi, 36 p.; Examples; Model Source","numberOfPages":"46","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-057372","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":297791,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20151027.JPG"},{"id":297788,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1027/pdf/ofr2015-1027.pdf","text":"Report","size":"3.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":297787,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2015/1027/"},{"id":297789,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2015/1027/downloads/ofr2015-1027_code_changes_examples.zip","text":"Examples","size":"17.2 MB","description":"Examples"},{"id":297790,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2015/1027/downloads/ofr2015-1027_code_changes_model_source.zip","text":"Model Source","size":"2.7 MB","description":"Model Source"}],"publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2a88e4b08de9379b30da","contributors":{"authors":[{"text":"Rounds, Stewart A. 0000-0002-8540-2206 sarounds@usgs.gov","orcid":"https://orcid.org/0000-0002-8540-2206","contributorId":905,"corporation":false,"usgs":true,"family":"Rounds","given":"Stewart","email":"sarounds@usgs.gov","middleInitial":"A.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":539980,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Buccola, Norman L. nbuccola@usgs.gov","contributorId":138859,"corporation":false,"usgs":true,"family":"Buccola","given":"Norman L.","email":"nbuccola@usgs.gov","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":false,"id":539981,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70137743,"text":"sir20155004 - 2015 - Climate change and prairie pothole wetlands: mitigating water-level and hydroperiod effects through upland management","interactions":[],"lastModifiedDate":"2018-01-05T10:15:53","indexId":"sir20155004","displayToPublicDate":"2015-02-06T11:15:00","publicationYear":"2015","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":"2015-5004","title":"Climate change and prairie pothole wetlands: mitigating water-level and hydroperiod effects through upland management","docAbstract":"Prairie pothole wetlands offer crucial habitat for North America’s waterfowl populations. The wetlands also support an abundance of other species and provide ecological services valued by society. The hydrology of prairie pothole wetlands is dependent on atmospheric interactions. Therefore, changes to the region’s climate can have profound effects on wetland hydrology. The relevant literature related to climate change and upland management effects on prairie pothole wetland water levels and hydroperiods was reviewed. Climate change is widely expected to affect water levels and hydroperiods of prairie pothole wetlands, as well as the biota and ecological services that the wetlands support. In general, hydrologic model projections that incorporate future climate change scenarios forecast lower water levels in prairie pothole wetlands and longer periods spent in a dry condition, despite potential increases in precipitation. However, the extreme natural variability in climate and hydrology of prairie pothole wetlands necessitates caution when interpreting model results. Recent changes in weather patterns throughout much of the Prairie Pothole Region have been in increased precipitation that results in increased water inputs to wetlands above losses associated with warmer temperatures. However, observed precipitation increases are within the range of natural climate variability and therefore, may not persist. Identifying management techniques with the potential to affect water inputs to prairie pothole wetlands would provide increased options for managers when dealing with the uncertainties associated with a changing climate. Several grassland management techniques (for example, grazing and burning) have the potential to affect water levels and hydroperiods of prairie pothole by affecting infiltration, evapotranspiration, and snow deposition.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155004","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service and North Dakota State University","usgsCitation":"Renton, D., Mushet, D.M., and DeKeyser, E., 2015, Climate change and prairie pothole wetlands: mitigating water-level and hydroperiod effects through upland management: U.S. Geological Survey Scientific Investigations Report 2015-5004, 32 p., https://doi.org/10.3133/sir20155004.","productDescription":"32 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059680","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":297781,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20155004.jpg"},{"id":297779,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2015/5004/"},{"id":297780,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5004/pdf/sir2015-5004.pdf","text":"Report","size":"3.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"country":"Canada, United States","otherGeospatial":"Prairie Pothole Region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.9169921875,\n 54.03358633521085\n ],\n [\n -114.82910156249999,\n 48.1367666796927\n ],\n [\n -102.4365234375,\n 46.619261036171515\n ],\n [\n -98.8330078125,\n 43.32517767999296\n ],\n [\n -95.00976562499999,\n 41.541477666790286\n ],\n [\n -91.8896484375,\n 41.50857729743935\n ],\n [\n -92.021484375,\n 45.644768217751924\n ],\n [\n -96.3720703125,\n 50.65294336725709\n ],\n [\n -101.77734374999999,\n 52.802761415419674\n ],\n [\n -114.9169921875,\n 54.03358633521085\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2a5ee4b08de9379b301a","contributors":{"authors":[{"text":"Renton, David A. drenton@usgs.gov","contributorId":138600,"corporation":false,"usgs":true,"family":"Renton","given":"David A.","email":"drenton@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":539966,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mushet, David M. 0000-0002-5910-2744 dmushet@usgs.gov","orcid":"https://orcid.org/0000-0002-5910-2744","contributorId":1299,"corporation":false,"usgs":true,"family":"Mushet","given":"David","email":"dmushet@usgs.gov","middleInitial":"M.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":539965,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DeKeyser, Edward S.","contributorId":138601,"corporation":false,"usgs":false,"family":"DeKeyser","given":"Edward S.","affiliations":[{"id":12459,"text":"NDSU","active":true,"usgs":false}],"preferred":false,"id":539967,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70140268,"text":"70140268 - 2015 - Long-term plant responses to climate are moderated by biophysical attributes in a North American desert","interactions":[],"lastModifiedDate":"2017-11-27T08:44:57","indexId":"70140268","displayToPublicDate":"2015-02-06T11:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2242,"text":"Journal of Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Long-term plant responses to climate are moderated by biophysical attributes in a North American desert","docAbstract":"A regional, two-dimensional, steady-state groundwater-flow model was developed to simulate the groundwater-flow system and groundwater/surface-water interactions within the Menominee Indian Reservation. The model was developed by the U.S. Geological Survey (USGS), in cooperation with the Menominee Indian Tribe of Wisconsin, to contribute to the fundamental understanding of the region’s hydrogeology. The objectives of the regional model were to improve understanding of the groundwater-flow system, including groundwater/surface-water interactions, and to develop a tool suitable for evaluating the effects of potential regional water-management programs. The computer code GFLOW was used because of the ease with which the model can simulate groundwater/surface-water interactions, provide a framework for simulating regional groundwater-flow systems, and be refined in a stepwise fashion to incorporate new data and simulate groundwater-flow patterns at multiple scales. Simulations made with the regional model reproduce groundwater levels and stream base flows representative of recent conditions (1970–2013) and illustrate groundwater-flow patterns with maps of (1) the simulated water table and groundwater-flow directions, (2) probabilistic areas contributing recharge to high-capacity pumped wells, and (3) estimation of the extent of infiltrated wastewater from treatment lagoons.
\nThe groundwater-flow model described in this report simulates the major hydrogeologic features of the modeled area, including surficial unconsolidated aquifers, groundwater/surface-water interactions, and groundwater withdrawals from existing high-capacity production wells. Areas contributing recharge to pumped high-capacity wells on the Menominee Indian Reservation were delineated by tracking simulated water particles from the water table to wells in combination with Monte Carlo techniques, and maps of the probability of capture for each well nest were produced. Groundwater-agebased areas contributing recharge to wells were simulated by using the calibrated set of parameters and porosity values adjusted to account for bias in simulated saturated thickness. Simulations were performed for current (2013) pumping rates. The simulations show a range in sensitivity of the simulated areas contributing recharge to wells given the parameters evaluated through the Monte Carlo analysis. The areas contributing recharge to supply wells for the villages of Zoar and Neopit are long and narrow, with a sharp gradation from high to low probability of capture. The areas contributing recharge to supply wells for Middle Village and the village of Keshena exhibit a sharp gradation from high to low probability over a relatively small area between the well and a local groundwater mound. The highest probability areas contributing recharge to the supply wells for the Villages of Onekewat and Redwing are in the immediate vicinity of the wells. These wells also have an extensive area with low probability for capturing water that is likely due to a locally low hydraulic gradient and the large degree of uncertainty associated with the lakebed resistance parameters that control interaction between groundwater and local lakes. Additional field investigations and associated local model refinements would facilitate further reductions in uncertainty associated with simulated areas contributing recharge to the wells.
\nThe likely extent of the Neopit wastewater plume was simulated by using the groundwater-flow model and Monte Carlo techniques to evaluate the sensitivity of predictive simulations to a range of model parameter values. Wastewater infiltrated from the currently operating lagoons flows predominantly south toward Tourtillotte Creek. Some of the infiltrated wastewater is simulated as having a low probability of flowing beneath Tourtillotte Creek to the nearby West Branch Wolf River. Results for the probable extent of the wastewater plume are considered to be qualitative because the method only considers advective flow and does not account for processes affecting contaminant transport in porous media. Therefore, results for the probable extent of the wastewater plume are sensitive to the number of particles used to represent flow from the lagoon and the resolution of a synthetic grid used for the analysis. Nonetheless, it is expected that the qualitative results may be of use for identifying potential downgradient areas of concern that can then be evaluated using the quantitative “area contributing recharge to wells” method or traditional contaminant-transport simulations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145237","collaboration":"In cooperation with the Menominee Indian Tribe of Wisconsin","usgsCitation":"Juckem, P.F., and Dunning, C., 2015, Simulation of the regional groundwater-flow system of the Menominee Indian Reservation, Wisconsin: U.S. Geological Survey Scientific Investigations Report 2014-5237, Report: vi, 40 p.; 1 Appendix, https://doi.org/10.3133/sir20145237.","productDescription":"Report: vi, 40 p.; 1 Appendix","numberOfPages":"50","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-051827","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":297772,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145237.jpg"},{"id":297770,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5237/pdf/sir2014-5237.pdf","size":"11.5 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":297771,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5237/appendix/sir2014-5237_appendix1.xlsx","text":"Appendix 1","size":"43 kB","linkFileType":{"id":3,"text":"xlsx"},"linkHelpText":"Data from auger surveys near the Villages of Neopit, Zoar, and Keshena."},{"id":297768,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5237/"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Menominee Indian Reservation","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.98376464843749,\n 45.11133093583214\n ],\n [\n -88.98239135742188,\n 44.94633342311665\n ],\n [\n -88.73794555664062,\n 44.94438944516438\n ],\n [\n -88.7310791015625,\n 44.85100108620397\n ],\n [\n -88.47152709960938,\n 44.8490538825394\n ],\n [\n -88.472900390625,\n 45.11326925230233\n ],\n [\n -88.98376464843749,\n 45.11133093583214\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2ab4e4b08de9379b3192","contributors":{"authors":[{"text":"Juckem, Paul F. 0000-0002-3613-1761 pfjuckem@usgs.gov","orcid":"https://orcid.org/0000-0002-3613-1761","contributorId":1905,"corporation":false,"usgs":true,"family":"Juckem","given":"Paul","email":"pfjuckem@usgs.gov","middleInitial":"F.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":539963,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dunning, Charles P. cdunning@usgs.gov","contributorId":892,"corporation":false,"usgs":true,"family":"Dunning","given":"Charles P.","email":"cdunning@usgs.gov","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":false,"id":539964,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70148013,"text":"70148013 - 2015 - Timescales alter the inferred strength and temporal consistency of intraspecific diet specialization","interactions":[],"lastModifiedDate":"2015-05-12T14:46:44","indexId":"70148013","displayToPublicDate":"2015-02-06T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2932,"text":"Oecologia","active":true,"publicationSubtype":{"id":10}},"title":"Timescales alter the inferred strength and temporal consistency of intraspecific diet specialization","docAbstract":"Many populations consist of individuals that differ substantially in their diets. Quantification of the magnitude and temporal consistency of such intraspecific diet variation is needed to understand its importance, but the extent to which different approaches for doing so reflect instantaneous vs. time-aggregated measures of individual diets may bias inferences. We used direct observations of sea otter individuals (Enhydra lutris nereis) to assess how: (1) the timescale of sampling, (2) under-sampling, and (3) the incidence- vs. frequency-based consideration of prey species affect the inferred strength and consistency of intraspecific diet variation. Analyses of feeding observations aggregated over hourly to annual intervals revealed a substantial bias associated with time aggregation that decreases the inferred magnitude of specialization and increases the inferred consistency of individuals’ diets. Time aggregation also made estimates of specialization more sensitive to the consideration of prey frequency, which decreased estimates relative to the use of prey incidence; time aggregation did not affect the extent to which under-sampling contributed to its overestimation. Our analyses demonstrate the importance of studying intraspecific diet variation with an explicit consideration of time and thereby suggest guidelines for future empirical efforts. Failure to consider time will likely produce inconsistent predictions regarding the effects of intraspecific variation on predator–prey interactions.
","language":"English","publisher":"Springer","doi":"10.1007/s00442-014-3213-2","usgsCitation":"Novak, M., and Tinker, M.T., 2015, Timescales alter the inferred strength and temporal consistency of intraspecific diet specialization: Oecologia, v. 178, no. 1, p. 61-74, https://doi.org/10.1007/s00442-014-3213-2.","productDescription":"14 p.","startPage":"61","endPage":"74","numberOfPages":"14","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059989","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":300352,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"178","issue":"1","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2015-02-06","publicationStatus":"PW","scienceBaseUri":"5553243be4b0a92fa7e94ca4","contributors":{"authors":[{"text":"Novak, Mark","contributorId":45229,"corporation":false,"usgs":false,"family":"Novak","given":"Mark","email":"","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":546792,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tinker, M. Tim 0000-0002-3314-839X ttinker@usgs.gov","orcid":"https://orcid.org/0000-0002-3314-839X","contributorId":2796,"corporation":false,"usgs":true,"family":"Tinker","given":"M.","email":"ttinker@usgs.gov","middleInitial":"Tim","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":546793,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ]}