In a recent study, Hough and Page (2015) presented several lines of evidence suggesting that most of the significant earthquakes in Oklahoma during the twentieth century, including the Mw 5.7 El Reno earthquake of 9 April 1952, were likely induced by wastewater injection and possibly secondary oil recovery operations. We undertook an archival search for accounts of this event, which unearthed a newspaper article published immediately following the El Reno earthquake regarding a prominent petroleum geologist in the area who took out a rare earthquake insurance policy less than 60 days before the earthquake struck. In this study we present a historical context for this intriguing coincidence. We present a retrospective of oil industry practices in the early‐ to mid‐twentieth century, gleaned from court records and other industry reports, that potentially bear on the interplay between oil exploration activities and earthquakes, focusing on the Oklahoma City region. We describe events of the day that could plausibly have alerted a geologist to the possibility of induced earthquakes, although there is no indication that the potential for induced earthquakes was widely recognized within the industry at that time.
","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Seismological Research Letters","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Seismological Society of America","publisherLocation":"El Cerrito, CA","doi":"10.1785/0220150218","usgsCitation":"Hough, S.E., and Page, M.T., 2015, The petroleum geologist and the insurance policy: Seismological Research Letters, v. 87, no. 1, p. 171-176, https://doi.org/10.1785/0220150218.","productDescription":"6 p.","startPage":"171","endPage":"176","numberOfPages":"6","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069197","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":318022,"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 -98.08319091796875,\n 35.46738105960409\n ],\n [\n -98.08319091796875,\n 36.00467348670187\n ],\n [\n -97.47756958007812,\n 36.00467348670187\n ],\n [\n -97.47756958007812,\n 35.46738105960409\n ],\n [\n -98.08319091796875,\n 35.46738105960409\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"87","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-16","publicationStatus":"PW","scienceBaseUri":"56c304dee4b0946c6520880e","contributors":{"authors":[{"text":"Hough, Susan E. 0000-0002-5980-2986 hough@usgs.gov","orcid":"https://orcid.org/0000-0002-5980-2986","contributorId":587,"corporation":false,"usgs":true,"family":"Hough","given":"Susan","email":"hough@usgs.gov","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":620146,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Page, Morgan T. 0000-0001-9321-2990 mpage@usgs.gov","orcid":"https://orcid.org/0000-0001-9321-2990","contributorId":3762,"corporation":false,"usgs":true,"family":"Page","given":"Morgan","email":"mpage@usgs.gov","middleInitial":"T.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":620147,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70160568,"text":"70160568 - 2015 - Reintroduction of Lake Sturgeon (Acipenser fulvescens) into the St. Regis River, NY: Post-release assessment of habitat use and growth","interactions":[],"lastModifiedDate":"2015-12-23T10:02:55","indexId":"70160568","displayToPublicDate":"2015-12-15T11:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2898,"text":"Northeastern Naturalist","active":true,"publicationSubtype":{"id":10}},"title":"Reintroduction of Lake Sturgeon (Acipenser fulvescens) into the St. Regis River, NY: Post-release assessment of habitat use and growth","docAbstract":"One of the depleted endemic fish species of the Great Lakes, Acipenser fulvescens (Lake Sturgeon), has been the target of extensive conservation efforts. One strategy is reintroduction into historically productive waters. The St. Regis River, NY, represents one such adaptive-management effort, with shared management between New York and the St. Regis Mohawk Tribe. Between 1998 and 2004, a total of 4977 young-of-year Lake Sturgeon were released. Adaptive management requires intermediate progress metrics. During 2004 and 2005, we measured growth, habitat use, and survivorship metrics of the released fish. We captured a total of 95 individuals of all stocked ages. Year-class minimal-survival rates ranged from 0.19–2.1%. The size-at-age and length/biomass relationships were comparable to those reported for juveniles in other Great Lakes waters. These intermediate assessment metrics can provide feedback to resource managers who make restoration-program decisions on a much shorter time-scale than the time-frame in which the ultimate goal of a self-sustaining population can be attained.
","language":"English","publisher":"Humboldt Field Research Institute","publisherLocation":"Steuben, ME","doi":"10.1656/045.022.0408","usgsCitation":"Dittman, D.E., Chalupnicki, M.A., Johnson, J.H., and Snyder, J., 2015, Reintroduction of Lake Sturgeon (Acipenser fulvescens) into the St. Regis River, NY: Post-release assessment of habitat use and growth: Northeastern Naturalist, v. 22, no. 4, p. 704-716, https://doi.org/10.1656/045.022.0408.","productDescription":"13 p.","startPage":"704","endPage":"716","numberOfPages":"13","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-017509","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":312781,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"St. Regis River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.59579467773438,\n 45.029376918052705\n ],\n [\n -74.65965270996094,\n 45.01481658592836\n ],\n [\n -74.6905517578125,\n 44.96139702015699\n ],\n [\n -74.7344970703125,\n 44.929807512153914\n ],\n [\n -74.783935546875,\n 44.912304304581525\n ],\n [\n -74.77500915527344,\n 44.88798544802558\n ],\n [\n -74.81895446777344,\n 44.83590853592836\n ],\n [\n -74.79286193847656,\n 44.80230124552821\n ],\n [\n -74.83062744140625,\n 44.77354904110061\n ],\n [\n -74.76402282714844,\n 44.75697346938202\n ],\n [\n -74.75509643554686,\n 44.813018740612776\n ],\n [\n -74.77844238281249,\n 44.8432118765634\n ],\n [\n -74.73518371582031,\n 44.90063253713748\n ],\n [\n -74.74479675292969,\n 44.904523389609324\n ],\n [\n -74.70359802246094,\n 44.91911174115028\n ],\n [\n -74.68231201171875,\n 44.94730538740607\n ],\n [\n -74.64454650878906,\n 44.9575100188052\n ],\n [\n -74.56077575683594,\n 45.02258255721372\n ],\n [\n -74.59579467773438,\n 45.029376918052705\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"22","issue":"4","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-09","publicationStatus":"PW","scienceBaseUri":"567bd3c0e4b0a04ef491a217","contributors":{"authors":[{"text":"Dittman, Dawn E. 0000-0002-0711-3732 ddittman@usgs.gov","orcid":"https://orcid.org/0000-0002-0711-3732","contributorId":2762,"corporation":false,"usgs":true,"family":"Dittman","given":"Dawn","email":"ddittman@usgs.gov","middleInitial":"E.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":583164,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chalupnicki, Marc A. mchalupnicki@usgs.gov","contributorId":3236,"corporation":false,"usgs":true,"family":"Chalupnicki","given":"Marc","email":"mchalupnicki@usgs.gov","middleInitial":"A.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":583166,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, James H. 0000-0002-5619-3871 jhjohnson@usgs.gov","orcid":"https://orcid.org/0000-0002-5619-3871","contributorId":389,"corporation":false,"usgs":true,"family":"Johnson","given":"James","email":"jhjohnson@usgs.gov","middleInitial":"H.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":583165,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Snyder, James","contributorId":73481,"corporation":false,"usgs":true,"family":"Snyder","given":"James","affiliations":[],"preferred":false,"id":583167,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70160029,"text":"ofr20151232 - 2015 - California State Waters map series — Offshore of Pigeon Point, California","interactions":[],"lastModifiedDate":"2022-04-18T21:45:34.762725","indexId":"ofr20151232","displayToPublicDate":"2015-12-15T11:00:00","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":"2015-1232","title":"California State Waters map series — Offshore of Pigeon Point, California","docAbstract":"In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within the 3-nautical-mile limit of California’s State Waters. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data, acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow subsurface geology.
\nThe Offshore of Pigeon Point map area is located in central California, on the Pacific Coast about 50 km south of San Francisco and 25 km northwest of Santa Cruz. The onshore part of the map area is sparsely populated. The nearest significant onshore cultural center is Pescadero, an unincorporated community with a population of well under 1,000. The hilly coastal area is virtually undeveloped, used primarily for agricultural or as grazing land for sheep and cattle. Agriculture is limited to the coastal uplifted Pleistocene marine terraces and upper Pleistocene alluvial fan deposits, which lie between the shoreline and the northwest-trending Santa Cruz Mountains.
\nThe map area is cut by the San Gregorio Fault Zone, and is located a few kilometers southwest of the San Andreas Fault Zone. Coastal uplift and folding in the map area has been attributed to a westward bend in the San Andreas Fault Zone and also to right-lateral movement along the San Gregorio Fault Zone. The irregular coastal geomorphology of this area, which consists of low, rocky cliffs and sparse, small pocket beaches backed by low, terraced hills, is partly attributable to this ongoing deformation.
\nThe shelf in the map area is underlain by variable amounts (0 to 20 m) of upper Quaternary nearshore and shelf sediments deposited as sea level fluctuated in the late Pleistocene. The southern part of the map is characterized by the presence of uplifted bedrock that has been linked to a local zone of transpression in the San Gregorio Fault Zone. This uplift, coupled with high wave energy, has resulted in little or no sediment cover in this area where exposures of bedrock are present at water depths of as much as 45 m. The thickest deposits of sediment are located in the northern part of the map area.
\nCoastal sediment transport in the map area is characterized by north-to-south littoral transport of sediment that is derived mainly from streams in the Santa Cruz Mountains and also from local coastal erosion. Shoreline-change studies indicate long-term erosion; within the region between San Francisco and Davenport, the highest long- and short-term coastal-erosion rates occur in the map area, just north of Point Año Nuevo. During the last approximately 300 years, as much as 18 million cubic yards (14 million cubic meters) of sand-sized sediment has been eroded from the area between Año Nuevo Island and Point Año Nuevo and transported south. Once widened by this pulse of eroded sediment, beaches south of Point Año Nuevo are now narrowing as the tail end of this mass of sand progresses farther south.
\nThe Offshore of Pigeon Point map area lies within the cold-temperate biogeographic zone that is called either the “Oregonian province” or the “northern California ecoregion.” This biogeographic province is maintained by the long-term stability of the southward-flowing California Current, the eastern limb of the North Pacific subtropical gyre that flows from southern British Columbia to Baja California. At its midpoint off central California, the California Current transports subarctic surface (0–500 m deep) waters southward, about 150 to 1,300 km from shore. Seasonal northwesterly winds that are, in part, responsible for the California Current, generate coastal upwelling. The south end of the Oregonian province is at Point Conception (about 335 km south of the map area), although its associated phylogeographic group of marine fauna may extend beyond to the area offshore of Los Angeles in southern California. The ocean off of central California has experienced a warming over the last 50 years that is driving an ecosystem shift away from the productive subarctic regime towards a depopulated subtropical environment.
\nSeafloor habitats in the Offshore of Pigeon Point map area lie within the Shelf (continental shelf) megahabitat. Significant rocky outcrops, which support kelp-forest communities in the nearshore and rocky-reef communities in deeper water, dominate the inner shelf waters. Biological productivity resulting from coastal upwelling supports populations of Sooty Shearwater, Western Gull, Common Murre, Cassin’s Auklet, and many other less populous bird species. In addition, an observable recovery of Humpback and Blue Whales has occurred in the area; both species are dependent on coastal upwelling to provide nutrients. The large extent of exposed inner shelf bedrock supports large forests of “bull kelp,” which is well adapted for high-wave-energy environments. Common fish species found in the kelp beds and rocky reefs include lingcod and various species of rockfish and greenling.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151232","usgsCitation":"Cochrane, G.R., Watt, J.T., Dartnell, P., Greene, H.G., Erdey, M.D., Dieter, B.E., Golden, N.E., Johnson, S.Y., Endris, C.A., Hartwell, S.R., Kvitek, R.G., Davenport, C.W., Krigsman, L.M., Ritchie, A.C., Sliter, R.W., Finlayson, D.P., and Maier, K.L. (G.R. Cochrane and S.A. Cochran, eds.), 2015, California State Waters Map Series — Offshore of Pigeon Point, California: U.S. Geological Survey Open-File Report 2015–1232, pamphlet 40 p., 10 sheets, scale 1:24,000, https://dx.doi.org/10.3133/ofr20151232.","productDescription":"Pamphlet: iv, 40 p.; 10 Sheets: 50.50 x 36.00 inches or smaller; Data Catalog; Metadata","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-057881","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":438659,"rank":21,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7513W80","text":"USGS data release","linkHelpText":"California State Waters Map Series Data Catalog--Offshore of Pigeon Point, California"},{"id":312124,"rank":15,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/ofr20151191","text":"Open-File Report 2015-1191","linkHelpText":"California State Waters Map Series—Offshore of Scott Creek, California, by Guy R. 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Each GIS data file is listed with a brief description, a small image, and links to the metadata files and the downloadable data files."},{"id":312119,"rank":10,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2015/1232/ofr20151232_sheet9.pdf","text":"Sheet 9","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1232 Sheet 9 PDF","linkHelpText":"Local (Offshore of Pigeon Point Map Area) and Regional (Offshore from Pigeon Point to Southern Monterey Bay) Shallow-Subsurface Geology and Structure, California By Janet T. Watt, Samuel Y. Johnson, Stephen R. Hartwell, Ray W. Sliter, and Katherine L. Maier"},{"id":312128,"rank":19,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1232/coverthb.jpg"},{"id":312127,"rank":18,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/of/2014/1260/","text":"Open-File Report 2014–1260","linkHelpText":"California State Waters Map Series—Offshore of Pacifica, California, by Brian D. 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Davenport"},{"id":312118,"rank":9,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2015/1232/ofr20151232_sheet8.pdf","text":"Sheet 8","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1232 Sheet 8 PDF","linkHelpText":"Seismic-Reflection Profiles, Offshore of Pigeon Point Map Area, California By Janet T. Watt, Samuel Y. Johnson, and Ray W. Sliter"},{"id":312117,"rank":8,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2015/1232/ofr20151232_sheet7.pdf","text":"Sheet 7","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1232 Sheet 7 PDF","linkHelpText":"Potential Marine Benthic Habitats, Offshore of Pigeon Point Map Area, California By Charles A. Endris, H. Gary Greene, Bryan E. Dieter, and Mercedes D. Erdey"},{"id":312111,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2015/1232/ofr20151232_sheet1.pdf","text":"Sheet 1","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1232 Sheet 1 PDF","linkHelpText":"Colored Shaded-Relief Bathymetry, Offshore of Pigeon Point Map Area, California By Peter Dartnell, Rikk G. Kvitek, Andrew C. Ritchie, and David P. Finlayson"},{"id":312112,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2015/1232/ofr20151232_sheet2.pdf","text":"Sheet 2","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1232 Sheet 2 PDF","linkHelpText":"Shaded-Relief Bathymetry, Offshore of Pigeon Point Map Area, California By Peter Dartnell, Rikk G. Kvitek, Andrew C. Ritchie, and David P. Finlayson"},{"id":312113,"rank":4,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2015/1232/ofr20151232_sheet3.pdf","text":"Sheet 3","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1232 Sheet 3 PDF","linkHelpText":"Acoustic Backscatter, Offshore of Pigeon Point Map Area, California By Peter Dartnell, Rikk G. Kvitek, Andrew C. Ritchie, and David P. Finlayson"},{"id":312114,"rank":5,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2015/1232/ofr20151232_sheet4.pdf","text":"Sheet 4","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1232 Sheet 4 PDF","linkHelpText":"Data Integration and Visualization, Offshore of Pigeon Point Map Area, California By Peter Dartnell"},{"id":312110,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1232/ofr20151232_pamphlet.pdf","text":"Pamphlet","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1232 Pamphlet PDF"},{"id":312115,"rank":6,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2015/1232/ofr20151232_sheet5.pdf","text":"Sheet 5","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1232 Sheet 5 PDF","linkHelpText":"Seafloor Character, Offshore of Pigeon Point Map Area, California By Mercedes D. Erdey and Guy R. Cochrane"},{"id":312116,"rank":7,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2015/1232/ofr20151232_sheet6.pdf","text":"Sheet 6","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1232 Sheet 6 PDF","linkHelpText":"Ground-Truth Studies, Offshore of Pigeon Point Map Area, California By Nadine E. Golden, Guy R. Cochrane, and Lisa M. Krigsman"}],"scale":"24000","country":"United States","state":"California","otherGeospatial":"Pigeon Point","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.4853,\n 37.0756\n ],\n [\n -122.4853,\n 37.2347\n ],\n [\n -122.2858,\n 37.2347\n ],\n [\n -122.2858,\n 37.0756\n ],\n [\n -122.4853,\n 37.0756\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Contact Information
Pacific Coastal & Marine Science Center
U.S. Geological Survey
Pacific Science Center
2885 Mission St.
Santa Cruz, CA 95060
http://walrus.wr.usgs.gov/
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2015 - Qualitative assessment of selected areas of the world for undiscovered sediment-hosted stratabound copper deposits: Chapter Y in Global mineral resource assessment","interactions":[{"subject":{"id":70159940,"text":"sir20105090Y - 2015 - Qualitative assessment of selected areas of the world for undiscovered sediment-hosted stratabound copper deposits: Chapter Y in Global mineral resource assessment","indexId":"sir20105090Y","publicationYear":"2015","noYear":false,"chapter":"Y","title":"Qualitative assessment of selected areas of the world for undiscovered sediment-hosted stratabound copper deposits: Chapter Y in Global mineral resource assessment"},"predicate":"IS_PART_OF","object":{"id":70040436,"text":"sir20105090 - 2010 - Global mineral resource assessment","indexId":"sir20105090","publicationYear":"2010","noYear":false,"title":"Global mineral resource assessment"},"id":1}],"isPartOf":{"id":70040436,"text":"sir20105090 - 2010 - Global mineral resource assessment","indexId":"sir20105090","publicationYear":"2010","noYear":false,"title":"Global mineral resource assessment"},"lastModifiedDate":"2018-10-29T11:14:23","indexId":"sir20105090Y","displayToPublicDate":"2015-12-14T12:00:00","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":"2010-5090","chapter":"Y","title":"Qualitative assessment of selected areas of the world for undiscovered sediment-hosted stratabound copper deposits: Chapter Y in Global mineral resource assessment","docAbstract":"
A qualitative mineral resource assessment of sediment-hosted stratabound copper mineralized areas for undiscovered copper deposits was performed for 10 selected areas of the world. The areas, in alphabetical order, are (1) Belt-Purcell Basin, United States and Canada; (2) Benguela and Cuanza Basins, Angola; (3) Chuxiong Basin, China; (4) Dongchuan Group rocks, China; (5) Egypt–Israel–Jordan Rift, Egypt, Israel, and Jordan; (6) Maritimes Basin, Canada; (7) Neuquén Basin, Argentina; (8) Northwest Botswana Rift, Botswana and Namibia; (9) Redstone Copperbelt, Canada; and (10) Salta Rift System, Argentina. This assessment (1) outlines the main characteristics of the areas, (2) classifies known deposits by deposit model subtypes, and (3) ranks the areas according to their potential to contain undiscovered copper deposits.
\nAn analytic hierarchy process (AHP) was used to rank assessment areas according to their potential for undiscovered copper deposits. Once the main characteristics of each area were compiled (age of host rock, geologic setting, stratigraphy, host lithology, deposit subtype(s), known deposits and occurrences, and mineral system components), three criteria (mineralization, extent of study area, and lithostratigraphic framework, each with multiple subcriteria) were scored for all assessment areas. Relative weights and scores were assigned to all criteria by three geologists. In addition, the assessment areas were ranked for comparison exclusively on the basis of professional opinion. The AHP and professional opinion lists are similar but not the same. Both the professional opinion and the cumulative AHP lists rate the Northwest Botswana Rift in Botswana and Namibia as the area most likely to contain the most undiscovered copper deposits. The Salta Rift System in Argentina is rated lowest among the 10 qualitatively assessed areas.
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U.S. Geological Survey
12201 Sunrise Valley Drive
913 National Center
Reston, VA 20192
http://minerals.usgs.gov/
Quantifying the impact of anthropogenic development on local populations is important for conservation biology and wildlife management. However, these local populations are often subject to demographic stochasticity because of their small population size. Traditional modeling efforts such as population projection matrices do not consider this source of variation whereas individual-based models, which include demographic stochasticity, are computationally intense and lack analytical tractability. One compromise between approaches is branching process models because they accommodate demographic stochasticity and are easily calculated. These models are known within some sub-fields of probability and mathematical ecology but are not often applied in conservation biology and applied ecology. We applied branching process models to quantitatively compare and prioritize species locally vulnerable to the development of wind energy facilities. Specifically, we examined species vulnerability using branching process models for four representative species: A cave bat (a long-lived, low fecundity species), a tree bat (short-lived, moderate fecundity species), a grassland songbird (a short-lived, high fecundity species), and an eagle (a long-lived, slow maturation species). Wind turbine-induced mortality has been observed for all of these species types, raising conservation concerns. We simulated different mortality rates from wind farms while calculating local extinction probabilities. The longer-lived species types (e.g., cave bats and eagles) had much more pronounced transitions from low extinction risk to high extinction risk than short-lived species types (e.g., tree bats and grassland songbirds). High-offspring-producing species types had a much greater variability in baseline risk of extinction than the lower-offspring-producing species types. Long-lived species types may appear stable until a critical level of incidental mortality occurs. After this threshold, the risk of extirpation for a local population may rapidly increase with only minimal increases in wind mortality. Conservation biologists and wildlife managers may need to consider this mortality pattern when issuing take permits and developing monitoring protocols for wind facilities. We also describe how our branching process models may be generalized across a wider range of species for a larger assessment project and then describe how our methods may be applied to other stressors in addition to wind.
Water temperature is a basic, but important, measure of the condition of all aquatic environments, including the flowing waters in the streams that drain our landscape and the receiving waters of those streams. Climatic conditions have a strong influence on water temperature, which is therefore naturally variable both in time and across the landscape. Changes to natural water-temperature regimes, however, can result in a myriad of effects on aquatic organisms, water quality, circulation patterns, recreation, industry, and utility operations. For example, most species of fish, insects, and other organisms, as well as aquatic vegetation, are highly dependent on water temperature. Warming waters can result in shifts in floral and faunal species distributions, including invasive species and pathogens previously unable to inhabit the once cooler streams. Many chemical processes are temperature dependent, with reactions occurring faster in warmer conditions, leading to degraded water quality as contaminants are released into waterways at greater rates. Circulation patterns in receiving waters, such as bays and estuaries, can change as a result of warmer inflows from streams, thereby affecting organisms in those receiving waters. Changes in abundance of some aquatic species and (or) degradation of water quality can reduce the recreational value of water bodies as waters are perceived as less desirable for water-related activities or as sportfish become less available for anglers. Finally, increasing water temperatures can affect industry and utilities as the thermal capacity is reduced, making the water less effective for cooling purposes.
Chesapeake Bay is the largest estuary in the United States. Eutrophication, the enrichment of a water body with excess nutrients, has plagued the bay for decades and has led to extensive restoration efforts throughout the bay watershed. The warming of stream water can exacerbate eutrophication through increased release of nutrients from in-stream sediments, so understanding changes in stream-water temperature throughout the bay watershed is critical to resource managers seeking to restore the bay ecosystem.
The U.S. Environmental Protection Agency (EPA) uses indicators that “represent the state or trend of certain environmental or societal conditions … to track and better understand the effects of changes in the Earth’s climate” (U.S. Environmental Protection Agency, 2014). Updates to these indicators are published biennially by the EPA. The U.S. Geological Survey (USGS), in cooperation with the EPA, has completed analyses of air- and stream-water-temperature trends in the Chesapeake Bay region to be included as an indicator in a future release of the EPA report.
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U.S. Geological Suvey
1730 East Parham Road
Richmond, VA 23228
http://va.water.usgs.gov/
Without human assistance, the terrestrial environment and oceans represent barriers to the dispersal of freshwater aquatic organisms. The ability to overcome such barriers depends on the existence of anthropogenic vectors that can transport live organisms to new areas, and the species’ biology to survive the transportation and transplantation into the new environment (Johnson et al., 2006).
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Biological invasions in changing ecosystems: vectors, ecological impacts, management and predictions","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"De Gruyter","usgsCitation":"Fuller, P.L., 2015, Vectors of invasions in freshwater invertebrates and fishes, chap. of Biological invasions in changing ecosystems: vectors, ecological impacts, management and predictions, p. 88-115.","productDescription":"28 p.","startPage":"88","endPage":"115","numberOfPages":"28","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-054860","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":312230,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":312494,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://www.degruyter.com/view/books/9783110438666/9783110438666-009/9783110438666-009.xml"}],"publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"566fe82de4b09cfe53ca7959","contributors":{"editors":[{"text":"Canning-Clode, Joao","contributorId":170603,"corporation":false,"usgs":false,"family":"Canning-Clode","given":"Joao","email":"","affiliations":[],"preferred":false,"id":633855,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"authors":[{"text":"Fuller, Pamela L. 0000-0002-9389-9144 pfuller@usgs.gov","orcid":"https://orcid.org/0000-0002-9389-9144","contributorId":3217,"corporation":false,"usgs":true,"family":"Fuller","given":"Pamela","email":"pfuller@usgs.gov","middleInitial":"L.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":false,"id":581910,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70159778,"text":"sir20155169 - 2015 - Sediment transport and evaluation of sediment surrogate ratings in the Kootenai River near Bonners Ferry, Idaho, Water Years 2011–14","interactions":[],"lastModifiedDate":"2015-12-14T15:02:54","indexId":"sir20155169","displayToPublicDate":"2015-12-14T09:15:00","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":"2015-5169","title":"Sediment transport and evaluation of sediment surrogate ratings in the Kootenai River near Bonners Ferry, Idaho, Water Years 2011–14","docAbstract":"The Kootenai River white sturgeon (Acipenser transmontanus) and other native fish species are culturally important to the Kootenai Tribe of Idaho, but their habitat and recruitment have been affected by anthropogenic changes to the river. Although the interconnections among anthropogenic changes and their impacts on fish are complex, the Kootenai Tribe of Idaho, in cooperation with other agencies, has been trying to understand and promote native fish recruitment through the development and implementation of the Kootenai River Habitat Restoration Program. As part of this effort, the U.S. Geological Survey collected sediment and streamflow information and evaluated use of acoustic backscatter as a sediment surrogate for estimating continuous suspended-sediment concentration at three sites in the Kootenai River white sturgeon critical habitat during water years 2011–14.
\nDuring the study, total suspended-sediment and fines concentrations were driven primarily by contributions from tributaries flowing into the Kootenai River between Libby Dam and the study area and were highest during rain-on-snow events in those tributary watersheds. On average, the relative percentage of suspended-sediment concentration in equal-width-increment samples collected in water years 2011–14 composed of fines less than 0.0625 mm (called washload) was 73, 71, and 70 percent at the Below Moyie, Crossport, and Tribal Hatchery sites, respectively. Suspended sand transport often increased with high streamflows, typically but not always associated with releases from Libby Dam. Bedload measured at the Crossport site was about 5 percent, on average, of the total sediment load measured in samples collected in water years 2011–13 and was positively correlated with suspended-sediment load. Comparisons with regional regression and envelope lines for suspended-sediment and bedload transport in relation to unregulated drainage area (drainage area downstream of Libby Dam) show that sediment transport was substantially less in the Kootenai River than in selected, minimally regulated Rocky Mountain rivers.
\nAcoustic surrogate ratings were developed between backscatter data collected using acoustic Doppler velocity meters (ADVMs) and results of suspended-sediment samples. Ratings were successfully fit to various sediment size classes (total, fines, and sands) using ADVMs of different frequencies (1.5 and 3 megahertz). Surrogate ratings also were developed using variations of streamflow and seasonal explanatory variables. The streamflow surrogate ratings produced average annual sediment load estimates that were 8–32 percent higher, depending on site and sediment type, than estimates produced using the acoustic surrogate ratings. The streamflow surrogate ratings tended to overestimate suspended-sediment concentrations and loads during periods of elevated releases from Libby Dam as well as on the falling limb of the streamflow hydrograph. Estimates from the acoustic surrogate ratings more closely matched suspended-sediment sample results than did estimates from the streamflow surrogate ratings during these periods as well as for rating validation samples collected in water year 2014. Acoustic surrogate technologies are an effective means to obtain continuous, accurate estimates of suspended-sediment concentrations and loads for general monitoring and sediment-transport modeling. In the Kootenai River, continued operation of the acoustic surrogate sites and use of the acoustic surrogate ratings to calculate continuous suspended-sediment concentrations and loads will allow for tracking changes in sediment transport over time.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155169","collaboration":"Prepared in cooperation with the Kootenai Tribe of Idaho","usgsCitation":"Wood, M.S., Fosness, R.L., and Etheridge, A.B., 2015, Sediment transport and evaluation of sediment surrogate ratings in the Kootenai River near Bonners Ferry, Idaho, water years 2011–14: U.S. Geological Survey Scientific Investigations Report 2015–5169, 48 p., https://dx.doi.org/10.3133/sir20155169.","productDescription":"Report:vi, 45 p.; Appendix","numberOfPages":"56","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-046285","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":312256,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5169/sir20155169.pdf","text":"Report","size":"2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5169 Report PDF"},{"id":312257,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5169/sir20155169_appendixA.xlsx","text":"Appendix A","size":"87 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2015-5169 Appendix A"},{"id":312255,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5169/coverthb.jpg"}],"country":"United States","state":"Idaho","city":"Bonners Ferry","otherGeospatial":"Kootenai River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.57318115234375,\n 48.65014969395597\n ],\n [\n -116.57318115234375,\n 48.94505319583951\n ],\n [\n -116.04858398437499,\n 48.94505319583951\n ],\n [\n -116.04858398437499,\n 48.65014969395597\n ],\n [\n -116.57318115234375,\n 48.65014969395597\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Idaho Water Science Center
U.S. Geological Survey
230 Collins Road
Boise, Idaho 83702
http://id.water.usgs.gov
The economic vitality and national security of the United States depend on the reliable supply of numerous nonfuel mineral commodities. Over the past six decades, many of these commodities have been sourced increasingly from outside the United States. The mix of commodities for which the United States is import dependent has changed as technologies have advanced, as substitute materials have been developed, and as world economies have changed. Although reliance on imports is only one of the many factors that determine supply risk, a clear, long-term trend has emerged from the data compiled and published by the U.S. Geological Survey, National Minerals Information Center (USGS–NMIC), and its predecessor organizations. Because the global distribution of mineral resources and reserves is not uniform, the United States has always been import reliant for some mineral commodities. Essentially, the type of commodities and the countries from which they are sourced determine risk related to import dependence. In light of projections that 2.5 billion to 3 billion people globally could move into the middle class by 2030, the demand for many types of mineral commodities is likely to continue to increase. Recent concerns regarding so-called “critical minerals” have been driven by market dislocations in the rare-earth-element supply chain in 2010 that resulted from a short-term policy decision by the Government of the People’s Republic of China to limit exports. That policy has since been changed as a result of actions by the World Trade Organization, but the events that followed, such as higher prices and intensive efforts to diversify sources of supply, illustrate the underlying issues of supply risk and the influence that disruptions can have on supply. These factors are often used in the classification of a mineral commodity as “critical.”
\nThe USGS–NMIC collects, analyzes, and disseminates information on a monthly, quarterly, or annual basis for more than 90 nonfuel mineral commodities from more than 180 countries. These data indicate that from 1954 through 2014 there was (1) a clear increase in the number and type of nonfuel mineral commodities for which the United States was net import reliant, (2) an increase in the percentage of import reliance for individual nonfuel mineral commodities, and (3) a shift in the geographic distribution of the source countries.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20153082","usgsCitation":"Fortier, S.M., DeYoung, J.H., Jr., Sangine, E.S., and Schnebele, E.K., 2015, Comparison of U.S. net import reliance for nonfuel mineral commodities—A 60-year retrospective (1954–1984–2014): U.S. Geological Survey Fact Sheet 2015–3082, 4 p., https://dx.doi.org/10.3133/fs20153082.","productDescription":"2 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-069937","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":312149,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2015/3082/coverthb.jpg"},{"id":312150,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2015/3082/fs20153082.pdf","text":"Report","size":"2.18 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2015-3082"}],"contact":"Director, National Minerals Information Center
U.S. Geological Survey
12201 Sunrise Valley Drive
988 National Center
Reston, VA 20192
Email: nmicrecordsmgt@usgs.gov
Or visit the USGS Minerals Information Web site at http://minerals.usgs.gov/minerals/
","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2015-12-14","noUsgsAuthors":false,"publicationDate":"2015-12-14","publicationStatus":"PW","scienceBaseUri":"566fe82ae4b09cfe53ca7951","contributors":{"authors":[{"text":"Fortier, Steven M. sfortier@usgs.gov","contributorId":140391,"corporation":false,"usgs":true,"family":"Fortier","given":"Steven M.","email":"sfortier@usgs.gov","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":false,"id":580636,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"DeYoung, Jr. 0000-0003-1169-6026 jdeyoung@usgs.gov","orcid":"https://orcid.org/0000-0003-1169-6026","contributorId":523,"corporation":false,"usgs":true,"family":"DeYoung","suffix":"Jr.","email":"jdeyoung@usgs.gov","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":false,"id":580637,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sangine, Elizabeth S. escottsangine@usgs.gov","contributorId":5806,"corporation":false,"usgs":true,"family":"Sangine","given":"Elizabeth","email":"escottsangine@usgs.gov","middleInitial":"S.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":false,"id":580638,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schnebele, Emily K. eschnebele@usgs.gov","contributorId":139796,"corporation":false,"usgs":true,"family":"Schnebele","given":"Emily","email":"eschnebele@usgs.gov","middleInitial":"K.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":false,"id":580639,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70164517,"text":"70164517 - 2015 - Mapping geoelectric fields during magnetic storms: Synthetic analysis of empirical United States impedances","interactions":[],"lastModifiedDate":"2016-02-09T13:05:23","indexId":"70164517","displayToPublicDate":"2015-12-14T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Mapping geoelectric fields during magnetic storms: Synthetic analysis of empirical United States impedances","docAbstract":"Empirical impedance tensors obtained from EarthScope magnetotelluric data at sites distributed across the midwestern United States are used to examine the feasibility of mapping magnetic storm induction of geoelectric fields. With these tensors, in order to isolate the effects of Earth conductivity structure, we perform a synthetic analysis—calculating geoelectric field variations induced by a geomagnetic field that is geographically uniform but varying sinusoidally with a chosen set of oscillation frequencies that are characteristic of magnetic storm variations. For north-south oriented geomagnetic oscillations at a period of T0=100 s, induced geoelectric field vectors show substantial geographically distributed differences in amplitude (approximately a factor of 100), direction (up to 130∘), and phase (over a quarter wavelength). These differences are the result of three-dimensional Earth conductivity structure, and they highlight a shortcoming of one-dimensional conductivity models (and other synthetic models not derived from direct geophysical measurement) that are used in the evaluation of storm time geoelectric hazards for the electric power grid industry. A hypothetical extremely intense magnetic storm having 500 nT amplitude at T0=100 s would induce geoelectric fields with an average amplitude across the midwestern United States of about 2.71 V/km, but with a representative site-to-site range of 0.15 V/km to 16.77 V/km. Significant improvement in the evaluation of such hazards will require detailed knowledge of the Earth's interior three-dimensional conductivity structure.
\n","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2015GL066636","usgsCitation":"Bedrosian, P.A., and Love, J.J., 2015, Mapping geoelectric fields during magnetic storms: Synthetic analysis of empirical United States impedances: Geophysical Research Letters, v. 42, no. 23, p. 10160-10170, https://doi.org/10.1002/2015GL066636.","productDescription":"11 p.","startPage":"10160","endPage":"10170","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070730","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":471565,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015gl066636","text":"Publisher Index Page"},{"id":316741,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"42","issue":"23","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-14","publicationStatus":"PW","scienceBaseUri":"56bb1bc7e4b08d617f654e29","contributors":{"authors":[{"text":"Bedrosian, Paul A. 0000-0002-6786-1038 pbedrosian@usgs.gov","orcid":"https://orcid.org/0000-0002-6786-1038","contributorId":839,"corporation":false,"usgs":true,"family":"Bedrosian","given":"Paul","email":"pbedrosian@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":597711,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Love, Jeffrey J. 0000-0002-3324-0348 jlove@usgs.gov","orcid":"https://orcid.org/0000-0002-3324-0348","contributorId":760,"corporation":false,"usgs":true,"family":"Love","given":"Jeffrey","email":"jlove@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":597712,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70160545,"text":"70160545 - 2015 - Infecting Pacific Herring with Ichthyophonus sp. in the laboratory","interactions":[],"lastModifiedDate":"2015-12-22T16:09:29","indexId":"70160545","displayToPublicDate":"2015-12-14T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2177,"text":"Journal of Aquatic Animal Health","active":true,"publicationSubtype":{"id":10}},"title":"Infecting Pacific Herring with Ichthyophonus sp. in the laboratory","docAbstract":"
The protistan parasite Ichthyophonus sp. occurs in coastal populations of Pacific Herring Clupea pallasii throughout the northeast Pacific region, but the route(s) by which these planktivorous fish become infected is unknown. Several methods for establishing Ichthyophonus infections in laboratory challenges were examined. Infections were most effectively established after intraperitoneal (IP) injections with suspended parasite isolates from culture or after repeated feedings with infected fish tissues. Among groups that were offered the infected tissues, infection prevalence was greater after multiple feedings (65%) than after a single feeding (5%). Additionally, among groups that were exposed to parasite suspensions prepared from culture isolates, infection prevalence was greater after exposure by IP injection (74%) than after exposure via gastric intubation (12%); the flushing of parasite suspensions over the gills did not lead to infections in any of the experimental fish. Although the consumption of infected fish tissues is unlikely to be the primary route of Ichthyophonus sp. transmission in wild populations of Pacific Herring, this route may contribute to abnormally high infection prevalence in areas where juveniles have access to infected offal.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/08997659.2015.1095809","usgsCitation":"Hershberger, P., Hart, L., MacKenzie, A., Yanney, M., Conway, C.M., and Elliott, D.G., 2015, Infecting Pacific Herring with Ichthyophonus sp. in the laboratory: Journal of Aquatic Animal Health, v. 27, no. 4, p. 217-221, https://doi.org/10.1080/08997659.2015.1095809.","productDescription":"5 p.","startPage":"217","endPage":"221","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066737","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":471566,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/08997659.2015.1095809","text":"Publisher Index Page"},{"id":312750,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":312738,"type":{"id":15,"text":"Index Page"},"url":"https://www.tandfonline.com/doi/full/10.1080/08997659.2015.1095809"}],"volume":"27","issue":"4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-14","publicationStatus":"PW","scienceBaseUri":"567a823ce4b0a04ef490fced","contributors":{"authors":[{"text":"Hershberger, Paul 0000-0002-2261-7760 phershberger@usgs.gov","orcid":"https://orcid.org/0000-0002-2261-7760","contributorId":150816,"corporation":false,"usgs":true,"family":"Hershberger","given":"Paul","email":"phershberger@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":583101,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hart, Lucas 0000-0001-7035-8778 lhart@usgs.gov","orcid":"https://orcid.org/0000-0001-7035-8778","contributorId":140133,"corporation":false,"usgs":true,"family":"Hart","given":"Lucas","email":"lhart@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":583102,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"MacKenzie, Ashley 0000-0002-7402-7877 amackenzie@usgs.gov","orcid":"https://orcid.org/0000-0002-7402-7877","contributorId":150817,"corporation":false,"usgs":true,"family":"MacKenzie","given":"Ashley","email":"amackenzie@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":583103,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Yanney, M.L.","contributorId":150818,"corporation":false,"usgs":false,"family":"Yanney","given":"M.L.","email":"","affiliations":[{"id":18110,"text":"USGS, WFRC, MMFS, Nortdland, WA","active":true,"usgs":false}],"preferred":false,"id":583104,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Conway, Carla M. 0000-0002-3851-3616 cmconway@usgs.gov","orcid":"https://orcid.org/0000-0002-3851-3616","contributorId":2946,"corporation":false,"usgs":true,"family":"Conway","given":"Carla","email":"cmconway@usgs.gov","middleInitial":"M.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":583105,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Elliott, Diane G. 0000-0002-4809-6692 dgelliott@usgs.gov","orcid":"https://orcid.org/0000-0002-4809-6692","contributorId":2947,"corporation":false,"usgs":true,"family":"Elliott","given":"Diane","email":"dgelliott@usgs.gov","middleInitial":"G.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":583106,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70160086,"text":"70160086 - 2015 - Characterization of the extremely arsenic-resistant Brevibacterium linens strain AE038-8 isolated from contaminated groundwater in Tucumán, Argentina","interactions":[],"lastModifiedDate":"2015-12-14T11:55:12","indexId":"70160086","displayToPublicDate":"2015-12-14T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2018,"text":"International Biodeterioration and Biodegradation","active":true,"publicationSubtype":{"id":10}},"title":"Characterization of the extremely arsenic-resistant Brevibacterium linens strain AE038-8 isolated from contaminated groundwater in Tucumán, Argentina","docAbstract":"Brevibacterium linens AE038-8, isolated from As-contaminated groundwater in Tucumán (Argentina), is highly resistant to arsenic oxyanions, being able to tolerate up to 1 M As(V) and 75 mM As(III) in a complex medium. Strain AE038-8 was also able to reduce As(V) to As(III) when grown in complex medium but paradoxically it could not do this in a defined minimal medium with sodium acetate and ammonium sulfate as carbon and nitrogen sources, respectively. No oxidation of As(III) to As(V) was observed under any conditions. Three copies of the ars operon comprising arsenic resistance genes were found on B. linens AE038-8 genome. In addition to the well known arsC, ACR3 andarsR, two copies of the arsO gene of unknown function were detected.
","language":"English","publisher":"Elsevier Applied Science","publisherLocation":"Barking, Essex, England","doi":"10.1016/j.ibiod.2015.11.022","usgsCitation":"Maizel, D., Blum, J.S., Ferrero, M.A., Utturkar, S.M., Brown, S.D., Rosen, B.P., and Oremland, R.S., 2015, Characterization of the extremely arsenic-resistant Brevibacterium linens strain AE038-8 isolated from contaminated groundwater in Tucumán, Argentina: International Biodeterioration and Biodegradation, v. 107, p. 147-153, https://doi.org/10.1016/j.ibiod.2015.11.022.","productDescription":"7 p.","startPage":"147","endPage":"153","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066757","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":471567,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ibiod.2015.11.022","text":"Publisher Index Page"},{"id":312248,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Argentina","state":"Tucumán","city":"Los Pereyra","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -64.9,\n -27\n ],\n [\n -64.9,\n -26.9\n ],\n [\n -64.8,\n -26.9\n ],\n [\n -64.8,\n -27\n ],\n [\n -64.9,\n -27\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"107","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"566fe829e4b09cfe53ca794f","chorus":{"doi":"10.1016/j.ibiod.2015.11.022","url":"http://dx.doi.org/10.1016/j.ibiod.2015.11.022","publisher":"Elsevier BV","authors":"Maizel Daniela, Blum Jodi Switzer, Ferrero Marcela A., Utturkar Sagar M., Brown Steven D., Rosen Barry P., Oremland Ronald S.","journalName":"International Biodeterioration & Biodegradation","publicationDate":"2/2016"},"contributors":{"authors":[{"text":"Maizel, Daniela","contributorId":150487,"corporation":false,"usgs":false,"family":"Maizel","given":"Daniela","email":"","affiliations":[{"id":18034,"text":"PROIMI-CONICET- Universidad Nacional de Tucuman, Tucuman, 4000 Argentina","active":true,"usgs":false}],"preferred":false,"id":581820,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Blum, Jodi S. jsblum@usgs.gov","contributorId":4263,"corporation":false,"usgs":true,"family":"Blum","given":"Jodi","email":"jsblum@usgs.gov","middleInitial":"S.","affiliations":[{"id":438,"text":"National Research Program - 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Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":581819,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70192075,"text":"70192075 - 2015 - Wildlife Habitat Restoration: Chapter 12","interactions":[],"lastModifiedDate":"2017-12-14T13:48:11","indexId":"70192075","displayToPublicDate":"2015-12-14T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Wildlife Habitat Restoration: Chapter 12","docAbstract":"As the preceding chapters point out, many wildlife species and the habitat they depend on are in peril. However, opportunities exist to restore habitat for many imperiled wildlife species. But what is wildlife habitat restoration? We begin this chapter by defining habitat restoration and then provide recommendations on how to maximize success of future habitat restoration efforts for wildlife. Finally, we evaluate whether we have been successful in restoring wildlife habitat and supply recommendations to advance habitat restoration. Successful restoration requires clear and explicit goals that are based on our best understanding of what the habitat was like prior to the disturbing event. Ideally, a restoration project would include: (1) a summary of prerestoration conditions that define the existing status of wildlife populations and their habitat; (2) a description of habitat features required by the focal or indicator species for persistence; (3) an a priori description of measurable, quantitative metrics that define restoration goals and measures of success; (4) a monitoring plan; (5) postrestoration comparisons of habitat features and wildlife populations with adjacent unmodified areas that are similar to the restoration site; and (6) expert review of the entire restoration plan (i.e., the five aforementioned components).
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Wildlife habitat conservation : concepts, challenges, and solutions","language":"English","publisher":"Johns Hopkins University Press","publisherLocation":"Baltimore, MD","usgsCitation":"Conway, C.J., and Borgmann, K.L., 2015, Wildlife Habitat Restoration: Chapter 12, chap. of Wildlife habitat conservation : concepts, challenges, and solutions, p. 157-167.","productDescription":"11 p.","startPage":"157","endPage":"167","ipdsId":"IP-056236","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":349997,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":349996,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://jhupbooks.press.jhu.edu/content/wildlife-habitat-conservation"}],"country":"United States","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fe47e4b06e28e9c252db","contributors":{"editors":[{"text":"Morrison, Michael L.","contributorId":169013,"corporation":false,"usgs":false,"family":"Morrison","given":"Michael","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":725069,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Mathewson, Heather A.","contributorId":70184,"corporation":false,"usgs":false,"family":"Mathewson","given":"Heather","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":725070,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"Conway, Courtney J. 0000-0003-0492-2953 cconway@usgs.gov","orcid":"https://orcid.org/0000-0003-0492-2953","contributorId":2951,"corporation":false,"usgs":true,"family":"Conway","given":"Courtney","email":"cconway@usgs.gov","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":714089,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Borgmann, Kathi L.","contributorId":171647,"corporation":false,"usgs":false,"family":"Borgmann","given":"Kathi","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":725071,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70161863,"text":"70161863 - 2015 - The role of dynamic surface water-groundwater exchange on streambed denitrification in a first-order, low-relief agricultural watershed","interactions":[],"lastModifiedDate":"2016-12-16T10:44:50","indexId":"70161863","displayToPublicDate":"2015-12-13T15:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"The role of dynamic surface water-groundwater exchange on streambed denitrification in a first-order, low-relief agricultural watershed","docAbstract":"The role of temporally varying surface water-groundwater (SW-GW) exchange on nitrate removal by streambed denitrification was examined along a reach of Leary Weber Ditch (LWD), Indiana, a small, first-order, low-relief agricultural watershed within the Upper Mississippi River basin, using data collected in 2004 and 2005. Stream stage, GW heads (H), and temperatures (T) were continuously monitored in streambed piezometers and stream bank wells for two transects across LWD accompanied by synoptic measurements of stream stage, H, T, and nitrate (NO3) concentrations along the reach. The H and T data were used to develop and calibrate vertical two-dimensional, models of streambed water flow and heat transport across and along the axis of the stream. Model-estimated SW-GW exchange varied seasonally and in response to high-streamflow events due to dynamic interactions between SW stage and GW H. Comparison of 2004 and 2005 conditions showed that small changes in precipitation amount and intensity, evapotranspiration, and/or nearby GW levels within a low-relief watershed can readily impact SW-GW interactions. The calibrated LWD flow models and observed stream and streambed NO3 concentrations were used to predict temporal variations in streambed NO3 removal in response to dynamic SW-GW exchange. NO3 removal rates underwent slow seasonal changes, but also underwent rapid changes in response to high-flow events. These findings suggest that increased temporal variability of SW-GW exchange in low-order, low-relief watersheds may be a factor contributing their more efficient removal of NO3.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2014WR016739","usgsCitation":"Rahimi Kazerooni, M.N., Essaid, H.I., and Wilson, J.T., 2015, The role of dynamic surface water-groundwater exchange on streambed denitrification in a first-order, low-relief agricultural watershed: Water Resources Research, v. 51, no. 12, p. 9514-9538, https://doi.org/10.1002/2014WR016739.","productDescription":"25 p.","startPage":"9514","endPage":"9538","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061362","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":471568,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2014wr016739","text":"Publisher Index Page"},{"id":314041,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Indiana","otherGeospatial":"Leary Weber Ditch","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -85.83828449249268,\n 39.854443814802465\n ],\n [\n -85.84047317504883,\n 39.85763940869116\n ],\n [\n -85.84309101104736,\n 39.85974776029954\n ],\n [\n -85.84562301635741,\n 39.86034072251865\n ],\n [\n -85.84811210632324,\n 39.85987953012439\n ],\n [\n -85.84965705871582,\n 39.85796884289973\n ],\n [\n -85.84982872009277,\n 39.85609104672825\n ],\n [\n -85.84794044494629,\n 39.85605810247719\n ],\n [\n -85.84725379943846,\n 39.85757352165968\n ],\n [\n -85.8457088470459,\n 39.85819944590483\n ],\n [\n -85.84377765655518,\n 39.85721114185585\n ],\n [\n -85.83987236022949,\n 39.853323674511145\n ],\n [\n -85.83871364593504,\n 39.85137985826863\n ],\n [\n -85.83768367767334,\n 39.84798628442432\n ],\n [\n -85.83673954010008,\n 39.846108215141285\n ],\n [\n -85.8330488204956,\n 39.84561397784372\n ],\n [\n -85.8301305770874,\n 39.84479024110811\n ],\n [\n -85.82794189453125,\n 39.841989462283536\n ],\n [\n -85.82360744476318,\n 39.84192356022963\n ],\n [\n -85.82369327545166,\n 39.84334044044997\n ],\n [\n -85.82661151885986,\n 39.843406341144004\n ],\n [\n -85.82824230194092,\n 39.84558102856405\n ],\n [\n -85.82961559295654,\n 39.8466353976705\n ],\n [\n -85.83193302154541,\n 39.847294370139366\n ],\n [\n -85.8345079421997,\n 39.84782154356041\n ],\n [\n -85.83566665649414,\n 39.84834871293334\n ],\n [\n -85.83600997924805,\n 39.85049029688317\n ],\n [\n -85.83828449249268,\n 39.854443814802465\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"51","issue":"12","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-13","publicationStatus":"PW","scienceBaseUri":"5690ebd1e4b09c7f9a218bec","contributors":{"authors":[{"text":"Rahimi Kazerooni, Mina N. mrahimikazerooni@usgs.gov","contributorId":5706,"corporation":false,"usgs":true,"family":"Rahimi Kazerooni","given":"Mina","email":"mrahimikazerooni@usgs.gov","middleInitial":"N.","affiliations":[{"id":438,"text":"National Research Program - 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2015 - Complex interactions in Lake Michigan’s rapidly changing ecosystem","interactions":[],"lastModifiedDate":"2015-12-10T14:00:34","indexId":"70160079","displayToPublicDate":"2015-12-10T15:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Complex interactions in Lake Michigan’s rapidly changing ecosystem","docAbstract":"For over 30 years, Lake Michigan’s food web has been in a constant state of transition from reductions in nutrient loading and proliferation of invasive species at multiple trophic levels. In particular, there has been concern about impacts from the invasive predatory cercopagids (Bythotrephes longimanus and Cercopagis pengoi) and expanding dreissenid mussel and round goby populations. This special issue brings together papers that explore the status of the Lake Michigan food web and the factors responsible for these changes, and suggests research paths that must be taken for understanding and predicting system behavior. This introductory paper describes the special issue origin, presents an overview of the papers, and draws overarching conclusions from the papers.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2015.11.001","usgsCitation":"Vanderploeg, H., Bunnell, D., Carrick, H.J., and Hook, T.O., 2015, Complex interactions in Lake Michigan’s rapidly changing ecosystem: Journal of Great Lakes Research, v. 41, no. Supplement 3, p. 1-6, https://doi.org/10.1016/j.jglr.2015.11.001.","productDescription":"7 p","startPage":"1","endPage":"6","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069601","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":312138,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Lake Michigan","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.737548828125,\n 45.78284835197676\n ],\n [\n -85.572509765625,\n 44.68427737181225\n ],\n [\n -85.74829101562499,\n 44.762336674810996\n ],\n [\n -85.550537109375,\n 45.19752230305685\n ],\n [\n -86.077880859375,\n 44.84029065139799\n ],\n [\n -86.46240234375,\n 44.05601169578525\n ],\n [\n -86.484375,\n 43.61221676817573\n ],\n [\n -86.220703125,\n 43.04480541304369\n ],\n [\n -86.253662109375,\n 42.32606244456202\n ],\n [\n -86.627197265625,\n 41.88592102814744\n ],\n [\n -87.16552734375,\n 41.60722821271717\n ],\n [\n -87.550048828125,\n 41.65649719441145\n ],\n [\n -87.86865234374999,\n 42.261049162113856\n ],\n [\n -87.8466796875,\n 42.78733853172001\n ],\n [\n -87.95654296875,\n 43.25320494908846\n ],\n [\n -87.725830078125,\n 44.071800467511565\n ],\n [\n -87.000732421875,\n 45.30580259943578\n ],\n [\n -87.9345703125,\n 44.535674532413196\n ],\n [\n -88.099365234375,\n 44.50434127765394\n ],\n [\n -87.82470703125,\n 44.972570682240644\n ],\n [\n -86.98974609375,\n 45.92822950933618\n ],\n [\n -86.934814453125,\n 45.71385093029221\n ],\n [\n -86.561279296875,\n 45.95878764035642\n ],\n [\n -86.68212890625,\n 45.67548217560647\n ],\n [\n -86.2646484375,\n 45.97406038956237\n ],\n [\n -85.67138671875,\n 45.99696161820381\n ],\n [\n -85.4736328125,\n 46.13417004624326\n ],\n [\n -85.02319335937499,\n 46.042735653846506\n ],\n [\n -84.737548828125,\n 45.78284835197676\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"41","issue":"Supplement 3","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"566aa23ae4b09cfe53ca44d9","contributors":{"authors":[{"text":"Vanderploeg, Henry A.","contributorId":85929,"corporation":false,"usgs":true,"family":"Vanderploeg","given":"Henry A.","affiliations":[],"preferred":false,"id":581781,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bunnell, David B. dbunnell@usgs.gov","contributorId":141167,"corporation":false,"usgs":true,"family":"Bunnell","given":"David B.","email":"dbunnell@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":581780,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Carrick, Hunter J.","contributorId":150479,"corporation":false,"usgs":false,"family":"Carrick","given":"Hunter","email":"","middleInitial":"J.","affiliations":[{"id":13588,"text":"Central Michigan University","active":true,"usgs":false}],"preferred":false,"id":581782,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hook, Tomas O.","contributorId":150480,"corporation":false,"usgs":false,"family":"Hook","given":"Tomas","email":"","middleInitial":"O.","affiliations":[{"id":13186,"text":"Purdue University","active":true,"usgs":false}],"preferred":false,"id":581783,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70159654,"text":"fs20153079 - 2015 - Shift in Global Tantalum Mine Production, 2000–2014","interactions":[],"lastModifiedDate":"2016-02-02T13:22:21","indexId":"fs20153079","displayToPublicDate":"2015-12-10T15:00:00","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":"2015-3079","title":"Shift in Global Tantalum Mine Production, 2000–2014","docAbstract":"Tantalum has a unique set of properties that make it useful in a number of diverse applications. The ability of the metal to store and release electrical energy makes it ideally suited for use in certain types of capacitors that are widely used in modern electronics. Approximately 60 percent of global tantalum consumption is in the electronics industry. The ductility and corrosion resistance of the metal lends itself to application in the chemical processing industry, and its high melting point and high strength retention at elevated temperatures make it an important component of super alloys used in aircraft engines.
\nAs a major industrialized nation, the United States is a leading consumer of tantalum and tantalum-containing products. Domestic deposits typically are of low grade, and no tantalum has been recovered from mining activities in the United States since 1959. Consequently, the United States is nearly completely reliant on imports to meet its domestic consumption of tantalum for economic and national security needs. The recovery of tantalum from mine production is economically viable in only a few countries.
\nAlthough developed countries dominated tantalum mine production in the early 2000s, production today is dominated by countries in the Great Lakes Region of Africa. There is concern that the sales of minerals, including columbite-tantalite or “coltan,” a mineral from which tantalum is derived, have helped finance rebel groups accused of violating human rights as part of the continuing armed conflict in the Democratic Republic of the Congo (DRC) and neighboring countries. These accusations have prompted the passage of legislation in the United States to curb the procurement of these mineral commodities, referred to as “conflict minerals,” from the DRC. Specifically, section 1502 of the 2010 Dodd-Frank Wall Street Reform and Consumer Protection Act (Public Law 111–203, 124 Stat. 2213–2218) requires companies that source tantalum, tin, tungsten, and gold (3TG) to perform due diligence on their supply chains to determine if the materials they use originate from the DRC or adjoining countries (defined as sharing a border with the DRC).
\nThe DRC, Rwanda, and surrounding countries are not globally significant sources of tin, tungsten, or gold, accounting for only about 2 percent of the mined world supply for each of these elements. The region has, however, evolved to become the world’s largest producer of mined tantalum.
\nA further complication of the production of tantalum stems from the opacity of the tantalum market. Unlike most base and precious metals, tantalum concentrates are not publicly traded through commodities exchanges but are bought and sold through networks of dealers and on contract between producers and consumers, some of whom may not provide accurate statistical data concerning the amounts, origins, and destination of the concentrates. Some price data can be found in trade journals or in other publications; however, there are no recognized official set exchange prices for either concentrate or tantalum metal. Because price is determined by negotiation between buyer and seller, published prices for concentrate are probably not representative of global prices paid for concentrate. The development of a mine-to-market supply-chain analysis is complicated and difficult because many of the industry participants that produce, trade, and consume tantalum do not publish statistical information, contracts are long term between miners and buyers, and much of the industry is vertically integrated.
\nAs a result of these and other considerations, tantalum is considered by many to be a “critical” commodity. This fact sheet identifies and addresses the major geographic shifts in the source of mine production of tantalum which have occurred over the past 15 years, some of the factors that drove this shift, and some of the related consequences.
\nOne of the activities of the U.S. Geological Survey National Minerals Information Center (USGS-NMIC) is to analyze global supply chains and characterize major components of mineral and material flows from ore extraction through processing to first tier products. These analyses support the core mission of the USGS-NMIC as the Federal entity responsible for the collection, analysis, and dissemination of objective, unbiased, factual information on minerals essential to the U.S. economy and national security.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20153079","usgsCitation":"Bleiwas, D.I., Papp, J.F., and Yager, T.R., 2015, Shift in global tantalum mine production, 2000–2014: U.S. Geological Survey Fact Sheet 2015–3079, 6 p., https://dx.doi.org/10.3133/fs20153079.","productDescription":"6 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070022","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":312092,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2015/3079/fs20153079.pdf","text":"Report","size":"469 KB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2015-3079"},{"id":312091,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2015/3079/coverthb.jpg"}],"contact":"Director, National Minerals Information Center
U.S. Geological Survey
12201 Sunrise Valley Drive
988 National Center
Reston, VA 20192
Email: nmicrecordsmgt@usgs.gov
Or visit the USGS Minerals Information Web site at http://minerals.usgs.gov/minerals/
","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2015-12-10","noUsgsAuthors":false,"publicationDate":"2015-12-10","publicationStatus":"PW","scienceBaseUri":"566aa23ee4b09cfe53ca44df","contributors":{"authors":[{"text":"Bleiwas, Donald I. bleiwas@usgs.gov","contributorId":1434,"corporation":false,"usgs":true,"family":"Bleiwas","given":"Donald","email":"bleiwas@usgs.gov","middleInitial":"I.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":579900,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Papp, John F. jpapp@usgs.gov","contributorId":2895,"corporation":false,"usgs":true,"family":"Papp","given":"John","email":"jpapp@usgs.gov","middleInitial":"F.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":579901,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yager, Thomas R. tyager@usgs.gov","contributorId":499,"corporation":false,"usgs":true,"family":"Yager","given":"Thomas","email":"tyager@usgs.gov","middleInitial":"R.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":false,"id":579902,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70160084,"text":"70160084 - 2015 - A new method to generate a high-resolution global distribution map of lake chlorophyll","interactions":[],"lastModifiedDate":"2015-12-10T13:35:13","indexId":"70160084","displayToPublicDate":"2015-12-10T14:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2068,"text":"International Journal of Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"A new method to generate a high-resolution global distribution map of lake chlorophyll","docAbstract":"A new method was developed, evaluated, and applied to generate a global dataset of growing-season chlorophyll-a (chl) concentrations in 2011 for freshwater lakes. Chl observations from freshwater lakes are valuable for estimating lake productivity as well as assessing the role that these lakes play in carbon budgets. The standard 4 km NASA OceanColor L3 chlorophyll concentration products generated from MODIS and MERIS sensor data are not sufficiently representative of global chl values because these can only resolve larger lakes, which generally have lower chl concentrations than lakes of smaller surface area. Our new methodology utilizes the 300 m-resolution MERIS full-resolution full-swath (FRS) global dataset as input and does not rely on the land mask used to generate standard NASA products, which masks many lakes that are otherwise resolvable in MERIS imagery. The new method produced chl concentration values for 78,938 and 1,074 lakes in the northern and southern hemispheres, respectively. The mean chl for lakes visible in the MERIS composite was 19.2 ± 19.2, the median was 13.3, and the interquartile range was 3.90–28.6 mg m−3. The accuracy of the MERIS-derived values was assessed by comparison with temporally near-coincident and globally distributed in situmeasurements from the literature (n = 185, RMSE = 9.39, R2 = 0.72). This represents the first global-scale dataset of satellite-derived chl estimates for medium to large lakes.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/01431161.2015.1029099","usgsCitation":"Sayers, M., Grimm, A.G., Shuchman, R.A., Deines, A., Bunnell, D., Raymer, Z., Rogers, M.W., Woelmer, W., Bennion, D., Brooks, C., Whitley, M.A., Warner, D.M., and Mychek-Londer, J., 2015, A new method to generate a high-resolution global distribution map of lake chlorophyll: International Journal of Remote Sensing, v. 36, no. 7, p. 1942-1964, https://doi.org/10.1080/01431161.2015.1029099.","productDescription":"23 p.","startPage":"1942","endPage":"1964","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-062466","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":471569,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/01431161.2015.1029099","text":"Publisher Index 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dmwarner@usgs.gov","orcid":"https://orcid.org/0000-0003-4939-5368","contributorId":2986,"corporation":false,"usgs":true,"family":"Warner","given":"David","email":"dmwarner@usgs.gov","middleInitial":"M.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":581814,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Mychek-Londer, Justin G.","contributorId":64138,"corporation":false,"usgs":true,"family":"Mychek-Londer","given":"Justin G.","affiliations":[],"preferred":false,"id":581815,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70156028,"text":"pp1794C - 2015 - Status and trends of land change in the Midwest–South Central United States—1973 to 2000","interactions":[],"lastModifiedDate":"2017-01-18T09:26:06","indexId":"pp1794C","displayToPublicDate":"2015-12-10T08:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":331,"text":"Professional Paper","code":"PP","onlineIssn":"2330-7102","printIssn":"1044-9612","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1794","chapter":"C","title":"Status and trends of land change in the Midwest–South Central United States—1973 to 2000","docAbstract":"U.S. Geological Survey (USGS) Professional Paper 1794–C is the third in a four-volume series on the status and trends of the Nation’s land use and land cover, providing an assessment of the rates and causes of land-use and land-cover change in the Midwest–South Central United States between 1973 and 2000. Volumes A, B, and D provide similar analyses for the Western United States, the Great Plains of the United States, and the Eastern United States, respectively. The assessments of land-use and land-cover trends are conducted on an ecoregion-by-ecoregion basis, and each ecoregion assessment is guided by a nationally consistent study design that includes mapping, statistical methods, field studies, and analysis. Individual assessments provide a picture of the characteristics of land change occurring in a given ecoregion; in combination, they provide a framework for understanding the complex national mosaic of change and also the causes and consequences of change. Thus, each volume in this series provides a regional assessment of how (and how fast) land use and land cover are changing, and why. The four volumes together form the first comprehensive picture of land change across the Nation.
Geographic understanding of land-use and land-cover change is directly relevant to a wide variety of stakeholders, including land and resource managers, policymakers, and scientists. The chapters in this volume present brief summaries of the patterns and rates of land change observed in each ecoregion in the Midwest–South Central United States, together with field photographs, statistics, and comparisons with other assessments. In addition, a synthesis chapter summarizes the scope of land change observed across the entire Midwest–South Central United States. The studies provide a way of integrating information across the landscape, and they form a critical component in the efforts to understand how land use and land cover affect important issues such as the provision of ecological goods and services and also the determination of risks to, and vulnerabilities of, human communities. Results from this project also are published in peer-reviewed journals, and they are further used to produce maps of change and other tools for land management, as well as to provide inputs for carbon-cycle modeling and other climate change research.
Contact information, U.S. Geological Survey
Earth Resources Observation and Science (EROS) Center
47914 252nd Street
Sioux Falls, SD 57198-0001
Walker Lake is a threatened and federally protected desert terminal lake in western Nevada. To help protect the desert terminal lake and the surrounding watershed, the Bureau of Reclamation and U.S. Geological Survey have been studying the hydrology of the Walker River Basin in Nevada and California since 2004. Hydrologic data collected for this study during water years 2010 through 2014 included groundwater levels, surface-water discharge, water chemistry, and meteorological data. Groundwater levels were measured in wells, and surface-water discharge was measured in streams, canals, and ditches. Water samples for chemical analyses were collected from wells, streams, springs, and Walker Lake. Chemical analyses included determining physical properties; the concentrations of major ions, nutrients, trace metals, dissolved gases, and radionuclides; and ratios of the stable isotopes of hydrogen and oxygen. Walker Lake water properties and meteorological parameters were monitored from a floating platform on the lake. Data collection methods followed established U.S. Geological Survey guidelines, and all data are stored in the National Water Information System database. All of the data are presented in this report and accessible on the internet, except multiple-depth Walker Lake water-chemistry data, which are available only in this report.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds967","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Pavelko, Michael T., and Orozco, Erin L., 2015, Hydrologic data for the Walker River Basin, Nevada and California, water years 2010–14: U.S. Geological Survey Data Series 967, 17 p., plus appendixes, https://dx.doi.org/10.3133/ds967.","productDescription":"Report: iv, 17 p.; 6 Appendixes","numberOfPages":"26","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2009-10-01","temporalEnd":"2014-09-30","ipdsId":"IP-065428","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":311927,"rank":8,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/0967/ds967_appendix06.xlsx","text":"Appendix 6","size":"3.3 MB","linkFileType":{"id":3,"text":"xlsx"},"description":"DS 967 Appendix 6","linkHelpText":"Lake water-chemistry and meteorological data from sites located on Walker Lake, water years 2011–14."},{"id":311920,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/0967/coverthb.jpg"},{"id":311922,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/0967/ds967_appendix01.xlsx","text":"Appendix 1","size":"156 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"DS 967 Appendix 1","linkHelpText":"Water-level measurements for the Walker River Basin study, water years 2010–14."},{"id":311919,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0967/ds967.pdf","text":"Report","size":"2.5 MB","description":"DS 967 PDF"},{"id":311923,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/0967/ds967_appendix02.xlsx","text":"Appendix 2","size":"20 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"DS 967 Appendix 2","linkHelpText":"Surface-water discharge measurements for the Walker River Basin study, water years 2011–13."},{"id":311924,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/0967/ds967_appendix03.xlsx","text":"Appendix 3","size":"56 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"DS 967 Appendix 3","linkHelpText":"Groundwater-chemistry data for the Walker River Basin study, water years 2010–12."},{"id":311926,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/0967/ds967_appendix05.xlsx","text":"Appendix 5","size":"19 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"DS 967 Appendix 5","linkHelpText":"Spring water-chemistry data for the Walker River Basin study, water years 2010–13."},{"id":311925,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/0967/ds967_appendix04.xlsx","text":"Appendix 4","size":"40 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"DS 967 Appendix 4","linkHelpText":"Stream water-chemistry data for the Walker River Basin study, water years 2011–13."}],"country":"United States","state":"California, Nevada","otherGeospatial":"Walker River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.22912597656249,\n 38.026458711461245\n ],\n [\n -118.98193359375,\n 38.1734326790354\n ],\n [\n -118.8006591796875,\n 38.24249456800328\n ],\n [\n -118.6138916015625,\n 38.29424797320529\n ],\n [\n -118.48205566406251,\n 38.182068998322094\n ],\n [\n -118.55895996093749,\n 38.06539235133249\n ],\n [\n -118.54248046874999,\n 37.97884504049713\n ],\n [\n -118.38317871093749,\n 38.02213147353745\n ],\n [\n -118.26232910156249,\n 38.16479533621134\n ],\n [\n -118.23486328125,\n 38.29424797320529\n ],\n [\n -118.35571289062499,\n 38.638327308061875\n ],\n [\n -118.4381103515625,\n 38.70265930723801\n ],\n [\n -118.5150146484375,\n 38.839707613545144\n ],\n [\n -118.46557617187499,\n 38.950865400919994\n ],\n [\n -118.487548828125,\n 39.02345139405932\n ],\n [\n -118.63037109375,\n 39.027718840211605\n ],\n [\n -118.828125,\n 39.08743603215884\n ],\n [\n -118.9544677734375,\n 39.142842478062505\n ],\n [\n -119.11376953125,\n 39.1854331703021\n ],\n [\n -119.24560546875001,\n 39.1854331703021\n ],\n [\n -119.44335937499999,\n 39.104488809440475\n ],\n [\n -119.54223632812501,\n 38.96795115401593\n ],\n [\n -119.608154296875,\n 38.796908303484294\n ],\n [\n -119.65209960937501,\n 38.732661120482334\n ],\n [\n -119.7344970703125,\n 38.61257832462118\n ],\n [\n -119.6685791015625,\n 38.5008925889646\n ],\n [\n -119.63562011718751,\n 38.40194908237825\n ],\n [\n -119.63012695312499,\n 38.190704293996504\n ],\n [\n -119.60266113281249,\n 38.06971703320484\n ],\n [\n -119.4049072265625,\n 38.0091482264894\n ],\n [\n -119.2950439453125,\n 37.97018468810549\n ],\n [\n -119.22912597656249,\n 38.026458711461245\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Nevada Water Science Center
U.S. Geological Survey
2730 N. Deer Run Rd.
Carson City, NV 89701
http://nevada.usgs.gov/water/
The Catahoula aquifer is an important source of fresh groundwater in central Louisiana. In 2010, about 3.96 million gallons per day (Mgal/d) were withdrawn from the Catahoula aquifer in Louisiana.
\nIn 2012, the U.S. Geological Survey in cooperation with the Louisiana Department of Natural Resources began a study to document current water levels in selected aquifers in Louisiana. This report presents water-level data and a map that illustrates the potentiometric surface of the Catahoula aquifer in 2013.
\nThe Catahoula aquifer crops out in a narrow band across north-central Louisiana. This band is broken by alluvial deposits in the valleys of the Red, Little, and Ouachita Rivers that have incised into the aquifer. Saltwater ridges under the Red, Little, and Tensas River Valleys divide the freshwater extents of the Catahoula aquifer and limit the flow of freshwater between these areas. The Catahoula aquifer generally ranges in thickness from about 50 feet (ft) in the outcrop area to about 450 ft in southern Vernon Parish. Sand beds in the aquifer are generally discontinuous, lenticular, and interbedded with silts and clays.
\nThe potentiometric surface of the Catahoula aquifer was constructed by using the altitude of water levels measured at 29 wells during the period May through September 2013. The altitude of water levels ranged from 0.02 ft above the National Geodetic Vertical Datum of 1929 (NGVD 29) in well Co-51 to 238 ft above NGVD 29 in well Na-317. Groundwater movement in the Catahoula aquifer is generally to the southeast and towards discharge areas beneath the Sabine, Red, Little, and Tensas River Valleys.
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3535 S. Sherwood Forest Blvd., Suite 120
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This report describes an R package called smwrBase, which consists of a collection of functions to import, transform, manipulate, and manage hydrologic data within the R statistical environment. Functions in the package allow users to import surface-water and groundwater data from the U.S. Geological Survey’s National Water Information System database and other sources. Additional functions are provided to transform, manipulate, and manage hydrologic data in ways necessary for analyzing the data.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151202","usgsCitation":"Lorenz, D.L., 2015, smwrBase—An R package for managing hydrologic data, version 1.1.1: U.S. Geological\nSurvey Open-File Report 2015–1202, 7 p., https://dx.doi.org/10.3133/ofr20151202.","productDescription":"Report: iii, 5 p.; Appendixes: 1-3","numberOfPages":"16","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-052705","costCenters":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"links":[{"id":311723,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1202/ofr20151202.pdf","text":"Report","size":"241 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1202"},{"id":311724,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ofr/2015/1202/downloads/","text":"Appendix","description":"OFR 2015-1202 Appendix","linkHelpText":"Director, Minnesota Water Science Center
U.S. Geological Survey
2280 Woodale Drive
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http://mn.water.usgs.gov/
This report summarizes outcomes from a two-day scenario planning workshop for Acadia National Park, Maine. The primary objective of the workshop was to help Acadia senior leadership make management and planning decisions based on up-to-date climate science and assessments of future uncertainty. The workshop was also designed as a training program, helping build participants' capabilities to develop and use scenarios. The details of the workshop are given in later sections. The climate scenarios presented here are based on published global climate model output. The scenario implications for resources and management decisions are based on expert knowledge distilled through scientist-manager interaction during workgroup break-out sessions at the workshop. Thus, the descriptions below are from these small-group discussions in a workshop setting and should not be taken as vetted research statements of responses to the climate scenarios, but rather as insights and examinations of possible futures. Here we provide the main conclusions from the scenario planning workshop.
","language":"English","publisher":"National Park Service","usgsCitation":"Star, J., Fisichelli, N., Bryan, A., Babson, A., Cole-Will, R., and Miller-Rushing, A.J., 2015, Acadia National Park climate change scenario planning workshop summary, 50 p.","productDescription":"50 p.","ipdsId":"IP-069634","costCenters":[{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":381169,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":381167,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://home.nps.gov/subjects/climatechange/acadiaworkshop.htm"}],"country":"United States","state":"Maine","otherGeospatial":"Acadia National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -68.45100402832031,\n 44.22650439062394\n ],\n [\n -68.13789367675781,\n 44.22650439062394\n ],\n [\n -68.13789367675781,\n 44.42446328709913\n ],\n [\n -68.45100402832031,\n 44.42446328709913\n ],\n [\n -68.45100402832031,\n 44.22650439062394\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Star, Jonathan","contributorId":168823,"corporation":false,"usgs":false,"family":"Star","given":"Jonathan","email":"","affiliations":[{"id":25365,"text":"Scenario Insight","active":true,"usgs":false}],"preferred":false,"id":806566,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fisichelli, Nicholas","contributorId":168824,"corporation":false,"usgs":false,"family":"Fisichelli","given":"Nicholas","affiliations":[{"id":25366,"text":"National Park Service, Climate Change Response Program","active":true,"usgs":false}],"preferred":false,"id":806567,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bryan, Alexander 0000-0003-2040-7636 abryan@usgs.gov","orcid":"https://orcid.org/0000-0003-2040-7636","contributorId":168822,"corporation":false,"usgs":true,"family":"Bryan","given":"Alexander","email":"abryan@usgs.gov","affiliations":[{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":806568,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Babson, Amanda","contributorId":168825,"corporation":false,"usgs":false,"family":"Babson","given":"Amanda","email":"","affiliations":[{"id":25367,"text":"National Park Service, Northeast Region","active":true,"usgs":false}],"preferred":false,"id":806569,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cole-Will, Rebecca","contributorId":168826,"corporation":false,"usgs":false,"family":"Cole-Will","given":"Rebecca","email":"","affiliations":[{"id":25368,"text":"National Park Service, Acadia National Park","active":true,"usgs":false}],"preferred":false,"id":806570,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Miller-Rushing, Abraham J.","contributorId":149650,"corporation":false,"usgs":false,"family":"Miller-Rushing","given":"Abraham","email":"","middleInitial":"J.","affiliations":[{"id":7237,"text":"NPS, Olympic National Park","active":true,"usgs":false}],"preferred":false,"id":806571,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70216840,"text":"70216840 - 2015 - Indicators of climate impacts for forests: Recommendations for the U.S. National Climate Assessment Indicators system","interactions":[],"lastModifiedDate":"2020-12-09T14:26:06.364871","indexId":"70216840","displayToPublicDate":"2015-12-09T08:18:32","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Indicators of climate impacts for forests: Recommendations for the U.S. National Climate Assessment Indicators system","docAbstract":"The Third National Climate Assessment (NCA) process for the United States focused in part on developing a system of indicators to communicate key aspects of the physical climate, climate impacts, vulnerabilities, and preparedness to inform decisionmakers and the public. Initially, 13 active teams were formed to recommend indicators in a range of categories, including forest, agriculture, grassland, phenology, mitigation, and physical climate. This publication describes the work of the Forest Indicators Technical Team. We briefly describe the NCA indicator system effort, propose and explain our conceptual model for the forest system, present our methods, and discuss our recommendations. Climate is only one driver of changes in U.S. forests; other drivers include socioeconomic drivers such as population and culture, and other environmental drivers such as nutrients, light, and disturbance. We offer additional details of our work for transparency and to inform an NCA indicator Web portal. We recommend metrics for 11 indicators of climate impacts on forest, spanning the range of important aspects of forest as an ecological type and as a sector. Some indicators can be reported in a Web portal now; others need additional work for reporting in the near future. Indicators such as budburst, which are important to forest but more relevant to other NCA indicator teams, are identified. Potential indicators that need more research are also presented.
","language":"English","publisher":"U.S. Forest Service","doi":"10.2737/NRS-GTR-155","collaboration":"USDA Forest Service, Northern Research Station, USGCRP","usgsCitation":"Heath, L.S., Anderson, S., Emery, M.R., Hicke, J., Littell, J.S., Lucier, A., Masek, J.G., Peterson, D.L., Pouyat, R., Potter, K.M., Robertson, G., Sperry, J., Bytnerowicz, A., Jovan, S.E., Mockrin, M.H., Musselman, R., Schulz, B.K., Smith, R.J., and Stewart, S.I., 2015, Indicators of climate impacts for forests: Recommendations for the U.S. National Climate Assessment Indicators system, 143 p., https://doi.org/10.2737/NRS-GTR-155.","productDescription":"143 p.","ipdsId":"IP-065101","costCenters":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":471570,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2737/nrs-gtr-155","text":"Publisher Index 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We developed equations to estimate methylmercury exposure of piscivorous birds and sport fish using mercury concentrations in prey fish. We collected original data on western grebes (Aechmophorus occidentalis) and Clark’s grebes (Aechmophorus clarkii) and summarized the published literature to generate predictive equations specific to grebes and a general equation for piscivorous birds. We measured mercury concentrations in 354 grebes (blood averaged 1.06 ± 0.08 μg/g ww), 101 grebe eggs, 230 sport fish (predominantly largemouth bass and rainbow trout), and 505 prey fish (14 species) at 25 lakes throughout California. Mercury concentrations in grebe blood, grebe eggs, and sport fish were strongly related to mercury concentrations in prey fish among lakes. Each 1.0 μg/g dw (∼0.24 μg/g ww) increase in prey fish resulted in an increase in mercury concentrations of 103% in grebe blood, 92% in grebe eggs, and 116% in sport fish. 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Machine learning methods can learn complex patterns in the data but because of overfitting may not generalize well to new data. The statistical learning framework involves cross-validation (CV) training and testing data and a separate hold-out data set for model evaluation, with the goal of optimizing predictive performance by controlling for model overfit. The order of prediction performance according to both CV testing R2 and that for the hold-out data set was BRT > BN > ANN. For each method we identified two models based on CV testing results: that with maximum testing R2 and a version with R2 within one standard error of the maximum (the 1SE model). The former yielded CV training R2 values of 0.94–1.0. Cross-validation testing R2 values indicate predictive performance, and these were 0.22–0.39 for the maximum R2 models and 0.19–0.36 for the 1SE models. Evaluation with hold-out data suggested that the 1SE BRT and ANN models predicted better for an independent data set compared with the maximum R2 versions, which is relevant to extrapolation by mapping. Scatterplots of predicted vs. observed hold-out data obtained for final models helped identify prediction bias, which was fairly pronounced for ANN and BN. Lastly, the models were compared with multiple linear regression (MLR) and a previous random forest regression (RFR) model. Whereas BRT results were comparable to RFR, MLR had low hold-out R2 (0.07) and explained less than half the variation in the training data. Spatial patterns of predictions by the final, 1SE BRT model agreed reasonably well with previously observed patterns of nitrate occurrence in groundwater of the Central Valley.
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