Amphibians are experiencing devastating population declines globally. A major driver is chytridiomycosis, an emerging infectious disease caused by the fungal pathogens Batrachochytrium dendrobatidis (Bd) and Batrachochytrium salamandrivorans (Bsal). Bdwas described in 1999 and has been linked with declines since the 1970s, while Bsal is a more recently discovered pathogen that was described in 2013. It is hypothesized that Bsaloriginated in Asia and spread via international trade to Europe, where it has been linked to salamander die-offs. Trade in live amphibians thus represents a significant threat to global biodiversity in amphibians. We review the current state of knowledge regarding Bsal and describe the risk of Bsal spread. We discuss regional responses to Bsal and barriers that impede a rapid, coordinated global effort. The discovery of a second deadly emerging chytrid fungal pathogen in amphibians poses an opportunity for scientists, conservationists, and governments to improve global biosecurity and further protect humans and wildlife from a growing number of emerging infectious diseases.
","language":"English","publisher":"Springer","doi":"10.1007/s10393-017-1278-1","usgsCitation":"Yap, T.A., Nguyen, N.T., Serr, M., Shepak, A., and Vredenburg, V., 2017, Batrachochytrium salamandrivorans and the risk of a second amphibian pandemic: EcoHealth, v. 14, no. 4, p. 851-864, https://doi.org/10.1007/s10393-017-1278-1.","productDescription":"14 p.","startPage":"851","endPage":"864","ipdsId":"IP-083788","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":469308,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10393-017-1278-1","text":"Publisher Index Page"},{"id":349068,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","issue":"4","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2017-11-16","publicationStatus":"PW","scienceBaseUri":"5a60fb0ee4b06e28e9c22b7c","contributors":{"authors":[{"text":"Yap, Tiffany A.","contributorId":200555,"corporation":false,"usgs":false,"family":"Yap","given":"Tiffany","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":722651,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nguyen, Natalie T. 0000-0001-9389-1655 ntnguyen@usgs.gov","orcid":"https://orcid.org/0000-0001-9389-1655","contributorId":195838,"corporation":false,"usgs":true,"family":"Nguyen","given":"Natalie","email":"ntnguyen@usgs.gov","middleInitial":"T.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":722650,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Serr, Megan","contributorId":200556,"corporation":false,"usgs":false,"family":"Serr","given":"Megan","email":"","affiliations":[],"preferred":false,"id":722652,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shepak, Alex","contributorId":200557,"corporation":false,"usgs":false,"family":"Shepak","given":"Alex","email":"","affiliations":[],"preferred":false,"id":722653,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Vredenburg, Vance","contributorId":200558,"corporation":false,"usgs":false,"family":"Vredenburg","given":"Vance","affiliations":[],"preferred":false,"id":722654,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70192788,"text":"70192788 - 2017 - Hatching success and predation of Bog Turtle (Glyptemys muhlenbergii) eggs in New Jersey and Pennsylvania","interactions":[],"lastModifiedDate":"2018-01-11T16:16:22","indexId":"70192788","displayToPublicDate":"2017-11-17T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1210,"text":"Chelonian Conservation and Biology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Hatching success and predation of Bog Turtle (Glyptemys muhlenbergii) eggs in New Jersey and Pennsylvania","title":"Hatching success and predation of Bog Turtle (Glyptemys muhlenbergii) eggs in New Jersey and Pennsylvania","docAbstract":"Nest-site selection by most turtles affects the survival of females and their offspring. Although bog turtles (Glyptemys muhlenbergii) do not typically leave their wetlands for nesting, nest-site selection can impact hatching success and hatchling survival. Between 1974 and 2012, we monitored the fates of 258 bog turtle eggs incubated in the field and 91 eggs incubated under laboratory conditions from 11 different bogs, fens, or wetland complexes in New Jersey and Pennsylvania. Laboratory-incubated eggs exhibited the greatest hatching success (81%), but we did not detect a significant difference in hatching success between nests protected with predator excluder cages (43%) and unprotected nests (33%). However, we found significantly lower predation rates in protected nests, suggesting that while predator excluder cages successfully reduced predation, other environmental factors persisted to reduce egg survival in the field. Natural hatching success was potentially reduced by poor weather conditions, which may have resulted in embryo developmental problems, dehydration, or embryos drowning in the egg. Our results suggest that egg depredation, coupled with embryo developmental problems and infertility, are limiting factors to hatching success in our study populations. Using predator excluder cages to protect bog turtle eggs in the field, or incubating eggs in the laboratory and releasing hatchlings at original nesting areas, may be an effective conservation tool for recovering populations of this federally threatened species.
","language":"English","publisher":"Chelonian Research Foundation","doi":"10.2744/CCB-1237.1","usgsCitation":"Zappalorti, R.T., Tutterow, A.M., Pittman, S.E., and Lovich, J.E., 2017, Hatching success and predation of Bog Turtle (Glyptemys muhlenbergii) eggs in New Jersey and Pennsylvania: Chelonian Conservation and Biology, v. 16, no. 2, p. 194-202, https://doi.org/10.2744/CCB-1237.1.","productDescription":"9 p.","startPage":"194","endPage":"202","ipdsId":"IP-080552","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":495030,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2744/ccb-1237.1","text":"Publisher Index Page"},{"id":349056,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Jersey, Pennsylvania","volume":"16","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fb0fe4b06e28e9c22b7f","contributors":{"authors":[{"text":"Zappalorti, Robert T.","contributorId":169450,"corporation":false,"usgs":false,"family":"Zappalorti","given":"Robert","email":"","middleInitial":"T.","affiliations":[{"id":25511,"text":"Herpetological Associates, Inc., Plant and Wildlife Consultants, 575 Toms River Road, Jackson, NJ 08527 USA. Corresponding author e-mail: RZappalort@aol.com","active":true,"usgs":false}],"preferred":false,"id":716948,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tutterow, Annalee M.","contributorId":198723,"corporation":false,"usgs":false,"family":"Tutterow","given":"Annalee","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":716949,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pittman, Shannon E.","contributorId":22169,"corporation":false,"usgs":false,"family":"Pittman","given":"Shannon","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":716950,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lovich, Jeffrey E. 0000-0002-7789-2831 jeffrey_lovich@usgs.gov","orcid":"https://orcid.org/0000-0002-7789-2831","contributorId":458,"corporation":false,"usgs":true,"family":"Lovich","given":"Jeffrey","email":"jeffrey_lovich@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":716947,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70194248,"text":"70194248 - 2017 - Mineral supply for sustainable development requires resource governance","interactions":[],"lastModifiedDate":"2017-11-20T11:23:15","indexId":"70194248","displayToPublicDate":"2017-11-17T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2840,"text":"Nature","active":true,"publicationSubtype":{"id":10}},"title":"Mineral supply for sustainable development requires resource governance","docAbstract":"Successful delivery of the United Nations sustainable development goals and implementation of the Paris Agreement requires technologies that utilize a wide range of minerals in vast quantities. Metal recycling and technological change will contribute to sustaining supply, but mining must continue and grow for the foreseeable future to ensure that such minerals remain available to industry. New links are needed between existing institutional frameworks to oversee responsible sourcing of minerals, trajectories for mineral exploration, environmental practices, and consumer awareness of the effects of consumption. Here we present, through analysis of a comprehensive set of data and demand forecasts, an interdisciplinary perspective on how best to ensure ecologically viable continuity of global mineral supply over the coming decades.
","language":"English","publisher":"Nature","doi":"10.1038/nature21359","usgsCitation":"Ali, S.H., Giurco, D., Arndt, N., Nickless, E., Brown, G., Demetriades, A., Durrheim, R., Enriquez, M.A., Kinnaird, J., Littleboy, A., Meinert, L.D., Oberhansli, R., Salem, J., Schodde, R., Schneider, G., Vidal, O., and Yakovleva, N., 2017, Mineral supply for sustainable development requires resource governance: Nature, v. 543, p. 367-372, https://doi.org/10.1038/nature21359.","productDescription":"6 p.","startPage":"367","endPage":"372","ipdsId":"IP-086614","costCenters":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"links":[{"id":469307,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://insu.hal.science/insu-03596079","text":"External Repository"},{"id":349122,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"543","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-03-16","publicationStatus":"PW","scienceBaseUri":"5a60fb0ee4b06e28e9c22b78","contributors":{"authors":[{"text":"Ali, Saleem H.","contributorId":200594,"corporation":false,"usgs":false,"family":"Ali","given":"Saleem","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":722828,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Giurco, Damien","contributorId":200595,"corporation":false,"usgs":false,"family":"Giurco","given":"Damien","email":"","affiliations":[],"preferred":false,"id":722829,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Arndt, Nicholas","contributorId":200596,"corporation":false,"usgs":false,"family":"Arndt","given":"Nicholas","affiliations":[],"preferred":false,"id":722830,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nickless, Edmund","contributorId":200597,"corporation":false,"usgs":false,"family":"Nickless","given":"Edmund","email":"","affiliations":[],"preferred":false,"id":722831,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brown, Graham","contributorId":200598,"corporation":false,"usgs":false,"family":"Brown","given":"Graham","email":"","affiliations":[],"preferred":false,"id":722832,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Demetriades, Alecos","contributorId":200599,"corporation":false,"usgs":false,"family":"Demetriades","given":"Alecos","email":"","affiliations":[],"preferred":false,"id":722833,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Durrheim, Ray","contributorId":200600,"corporation":false,"usgs":false,"family":"Durrheim","given":"Ray","email":"","affiliations":[],"preferred":false,"id":722834,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Enriquez, Maria Amelia","contributorId":200601,"corporation":false,"usgs":false,"family":"Enriquez","given":"Maria","email":"","middleInitial":"Amelia","affiliations":[],"preferred":false,"id":722835,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kinnaird, Judith","contributorId":200602,"corporation":false,"usgs":false,"family":"Kinnaird","given":"Judith","email":"","affiliations":[],"preferred":false,"id":722836,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Littleboy, Anna","contributorId":200603,"corporation":false,"usgs":false,"family":"Littleboy","given":"Anna","email":"","affiliations":[],"preferred":false,"id":722837,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Meinert, Lawrence D. lmeinert@usgs.gov","contributorId":1639,"corporation":false,"usgs":true,"family":"Meinert","given":"Lawrence","email":"lmeinert@usgs.gov","middleInitial":"D.","affiliations":[{"id":387,"text":"Mineral Resources 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Gabi","contributorId":200607,"corporation":false,"usgs":false,"family":"Schneider","given":"Gabi","email":"","affiliations":[],"preferred":false,"id":722841,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Vidal, Olivier","contributorId":200608,"corporation":false,"usgs":false,"family":"Vidal","given":"Olivier","email":"","affiliations":[],"preferred":false,"id":722842,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Yakovleva, Natalia","contributorId":200609,"corporation":false,"usgs":false,"family":"Yakovleva","given":"Natalia","email":"","affiliations":[],"preferred":false,"id":722843,"contributorType":{"id":1,"text":"Authors"},"rank":17}]}} ,{"id":70190505,"text":"sim3386 - 2017 - Bedrock geology and hydrostratigraphy of the Edwards and Trinity aquifers within the Driftwood and Wimberley 7.5-minute quadrangles, Hays and Comal Counties, Texas","interactions":[],"lastModifiedDate":"2017-11-16T17:10:15","indexId":"sim3386","displayToPublicDate":"2017-11-16T17:30:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3386","title":"Bedrock geology and hydrostratigraphy of the Edwards and Trinity aquifers within the Driftwood and Wimberley 7.5-minute quadrangles, Hays and Comal Counties, Texas","docAbstract":"The Edwards and Trinity aquifers are major sources of water in south-central Texas and are both classified as major aquifers by the State of Texas. The population in Hays and Comal Counties is rapidly growing, increasing demands on the area’s water resources. To help effectively manage the water resources in the area, refined maps and descriptions of the geologic structures and hydrostratigraphic units of the aquifers are needed. This report presents the detailed 1:24,000-scale bedrock hydrostratigraphic map as well as names and descriptions of the geologic and hydrostratigraphic units of the Driftwood and Wimberley 7.5-minute quadrangles in Hays and Comal Counties, Tex.
Hydrostratigraphically, the rocks exposed in the study area represent a section of the upper confining unit to the Edwards aquifer, the Edwards aquifer, the upper zone of the Trinity aquifer, and the middle zone of the Trinity aquifer. In the study area, the Edwards aquifer is composed of the Georgetown Formation and the rocks forming the Edwards Group. The Trinity aquifer is composed of the rocks forming the Trinity Group. The Edwards and Trinity aquifers are karstic with high secondary porosity along bedding and fractures. The Del Rio Clay is a confining unit above the Edwards aquifer and does not supply appreciable amounts of water to wells in the study area.
The hydrologic connection between the Edwards and Trinity aquifers and the various hydrostratigraphic units is complex because the aquifer system is a combination of the original Cretaceous depositional environment, bioturbation, primary and secondary porosity, diagenesis, and fracturing of the area from Miocene faulting. All of these factors have resulted in development of modified porosity, permeability, and transmissivity within and between the aquifers. Faulting produced highly fractured areas which allowed for rapid infiltration of water and subsequently formed solutionally enhanced fractures, bedding planes, channels, and caves that are highly permeable and transmissive. Because of faulting the juxtaposition of the aquifers and hydrostratigraphic units has resulted in areas of interconnectedness between the Edwards and Trinity aquifers and the various hydrostratigraphic units that form the aquifers.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3386","usgsCitation":"Clark, A.K., and Morris, R.R., 2017, Bedrock geology and hydrostratigraphy of the Edwards and Trinity aquifers within the Driftwood and Wimberley 7.5-minute quadrangles, Hays and Comal Counties, Texas: U.S. Geological Survey Scientific Investigations Map 3386, 12 p., 1 sheet, scale 1:24,000, https://doi.org/10.3133/sim3386.","productDescription":"Report: iv, 12 p.; Plates: 34.78 x 53.96 inches; Table; Data Release; Read Me","onlineOnly":"Y","ipdsId":"IP-078819","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":348918,"rank":5,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sim/3386/sim3386_ReadMe.txt","text":"Read Me","size":"8.00 kB","linkFileType":{"id":2,"text":"txt"},"description":"SIM 3386 Read Me"},{"id":348916,"rank":3,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3386/sim3386_map.pdf","text":"Map","size":"63.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3386 Map"},{"id":348917,"rank":4,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3386/sim3386_geomap.pdf","text":"Georeferenced map","size":"70.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3386 Georeferenced Map"},{"id":348913,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3386/sim3386_pamphlet.pdf","text":"Report","size":"46.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3386 Report"},{"id":348933,"rank":8,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sim/3386/sim3386_Table_1.pdf","text":"Table 1—","size":"264 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3386 Table 1","linkHelpText":"Summary of bedrock geology and hydrostratigraphy of the Edwards and Trinity aquifers within the Driftwood and Wimberley 7.5-minute quadrangles, Hays and Comal Counties, Texas"},{"id":348912,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3386/coverthb.jpg"},{"id":348921,"rank":7,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sim3363","text":"Scientific Investigations Map 3363—","linkHelpText":"Geologic framework, hydrostratigraphy, and ichnology of the Blanco, Payton, and Rough Hollow 7.5-minute quadrangles, Blanco, Comal, Hays, and Kendall Counties, Texas"},{"id":348919,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F76D5RXQ","text":"USGS Data Release","description":"USGS Data Release","linkHelpText":"Data release for bedrock geology and hydrostratigraphy of the Edwards and Trinity Aquifers within the Driftwood and Wimberley 7.5-Minute Quadrangles, Hays and Comal Counties, Texas at 1:24,000 scale"}],"country":"United States","state":"Texas","county":"Comal County, Hays County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -98.125,\n 30.125\n ],\n [\n -98,\n 30.125\n ],\n [\n -98,\n 29.875\n ],\n [\n -98.125,\n 29.875\n ],\n [\n -98.125,\n 30.125\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, Texas 78754-4501
The Colour and Stereo Surface Imaging System (CaSSIS) is the main imaging system onboard the European Space Agency’s ExoMars Trace Gas Orbiter (TGO) which was launched on 14 March 2016. CaSSIS is intended to acquire moderately high resolution (4.6 m/pixel) targeted images of Mars at a rate of 10–20 images per day from a roughly circular orbit 400 km above the surface. Each image can be acquired in up to four colours and stereo capability is foreseen by the use of a novel rotation mechanism. A typical product from one image acquisition will be a
The Alaskan population of Emperor Geese (Chen canagica) nests on the Yukon–Kuskokwim Delta in western Alaska. Numbers of Emperor Geese in Alaska declined from the 1960s to the mid-1980s and since then, their numbers have slowly increased. Low statistical power of microsatellite loci developed in other waterfowl species and used in previous studies of Emperor Geese are unable to confidently assign individual identity. Microsatellite loci for Emperor Goose were therefore developed using shotgun amplification and next-generation sequencing technology. Forty-one microsatellite loci were screened and 14 were found to be polymorphic in Emperor Geese. Only six markers – a combination of four novel loci and two loci developed in other waterfowl species – are needed to identify an individual from among the Alaskan Emperor Goose population. Genetic markers for identifying sex in Emperor Geese were also developed. The 14 novel variable loci and 15 monomorphic loci were screened for polymorphism in four other Arctic-nesting goose species, Black Brant (Branta bernicla nigricans), Greater White-fronted (Anser albifrons), Canada (B. canadensis) and Cackling (B. hutchinsii) Goose. Emperor Goose exhibited the smallest average number of alleles (3.3) and the lowest expected heterozygosity (0.467). Greater White-fronted Geese exhibited the highest average number of alleles (4.7) and Cackling Geese the highest expected heterozygosity (0.599). Six of the monomorphic loci were variable and able to be characterised in the other goose species assayed, a predicted outcome of reverse ascertainment bias. These findings fail to support the hypothesis of ascertainment bias due to selection of microsatellite markers.
","language":"English","publisher":"Ingenta Connect","doi":"10.3184/175815617X14969254461396","usgsCitation":"Gravley, M.C., Sage, G.K., Schmutz, J.A., and Talbot, S.L., 2017, Development of microsatellite loci exhibiting reverse ascertainment bias and a sexing marker for use in Emperor Geese (Chen canagica): Avian Biology Research, v. 10, no. 4, p. 201-210, https://doi.org/10.3184/175815617X14969254461396.","productDescription":"10 p.","startPage":"201","endPage":"210","ipdsId":"IP-083205","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":438147,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F71V5C4S","text":"USGS data release","linkHelpText":"DNA Microsatellite and Sex Identification Markers for Emperor Goose (Chen canagica) and Cross-Species Amplification of Microsatellites in Select Goose Species, Alaska 2016"},{"id":349005,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Yukon–Kuskokwim Delta","volume":"10","issue":"4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-11-01","publicationStatus":"PW","scienceBaseUri":"5a60fb0fe4b06e28e9c22b86","contributors":{"authors":[{"text":"Gravley, Megan C. 0000-0002-4947-0236 mgravley@usgs.gov","orcid":"https://orcid.org/0000-0002-4947-0236","contributorId":202812,"corporation":false,"usgs":true,"family":"Gravley","given":"Megan","email":"mgravley@usgs.gov","middleInitial":"C.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":722455,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sage, George K. 0000-0003-1431-2286 ksage@usgs.gov","orcid":"https://orcid.org/0000-0003-1431-2286","contributorId":87833,"corporation":false,"usgs":true,"family":"Sage","given":"George","email":"ksage@usgs.gov","middleInitial":"K.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":false,"id":722457,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schmutz, Joel A. 0000-0002-6516-0836 jschmutz@usgs.gov","orcid":"https://orcid.org/0000-0002-6516-0836","contributorId":1805,"corporation":false,"usgs":true,"family":"Schmutz","given":"Joel","email":"jschmutz@usgs.gov","middleInitial":"A.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":722456,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Talbot, Sandra L. 0000-0002-3312-7214 stalbot@usgs.gov","orcid":"https://orcid.org/0000-0002-3312-7214","contributorId":140512,"corporation":false,"usgs":true,"family":"Talbot","given":"Sandra","email":"stalbot@usgs.gov","middleInitial":"L.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":722454,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70193330,"text":"ofr20171141 - 2017 - Behavioral response of giant gartersnakes (Thamnophis gigas) to the relative availability of aquatic habitat on the landscape","interactions":[],"lastModifiedDate":"2017-11-17T10:20:53","indexId":"ofr20171141","displayToPublicDate":"2017-11-16T00:00:00","publicationYear":"2017","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":"2017-1141","displayTitle":"Behavioral response of giant gartersnakes (Thamnophis gigas) to the relative availability of aquatic habitat on the landscape","title":"Behavioral response of giant gartersnakes (Thamnophis gigas) to the relative availability of aquatic habitat on the landscape","docAbstract":"Most extant giant gartersnake (Thamnophis gigas) populations persist in an agro-ecosystem dominated by rice, which serves as a surrogate to the expansive marshes lost to flood control projects and development of the Great Central Valley of California. Knowledge of how giant gartersnakes use the rice agricultural landscape, including how they respond to fallowing, idling, or crop rotations, would greatly benefit conservation of giant gartersnakes by informing more snake-friendly land and water management practices. We studied adult giant gartersnakes at 11 sites in the rice-growing regions of the Sacramento Valley during an extended drought in California to evaluate their response to differences in water availability at the site and individual levels. Although our study indicated that giant gartersnakes make little use of rice fields themselves, and avoid cultivated rice relative to its availability on the landscape, rice is a crucial component of the modern landscape for giant gartersnakes. Giant gartersnakes are strongly associated with the canals that supply water to and drain water from rice fields; these canals provide much more stable habitat than rice fields because they maintain water longer and support marsh-like conditions for most of the giant gartersnake active season. Nonetheless, our results suggest that maintaining canals without neighboring rice fields would be detrimental to giant gartersnake populations, with decreases in giant gartersnake survival rates associated with less rice production in the surrounding landscape. Increased productivity of prey populations, dispersion of potential predators across a larger landscape, and a more secure water supply are just some of the mechanisms by which rice fields might benefit giant gartersnakes in adjacent canals. Results indicate that identifying how rice benefits giant gartersnakes in canals and the extent to which the rice agro-ecosystem could provide these benefits when rice is fallowed would inform the use of water for other purposes without harm to giant gartersnakes. Our study also suggests that without such understanding, maintaining rice and associated canals in the Sacramento Valley is critical for the sustainability of giant gartersnake populations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171141","collaboration":"Prepared in cooperation with the California Department of Water Resources","usgsCitation":"Reyes, G.A., Halstead, B.J., Rose, J.P., Ersan, J.S.M., Jordan, A.C., Essert, A.M., Fouts, K.J., Fulton, A.M., Gustafson, K.B., Wack, R.F., Wylie, G.D., and Casazza, M.L., 2017, Behavioral response of giant gartersnakes (Thamnophis gigas) to the relative availability of aquatic habitat on the landscape: U.S. Geological Survey Open-File Report 2017-1141, 134 p., https://doi.org/10.3133/ofr20171141.","productDescription":"vi, 134 p.","numberOfPages":"144","onlineOnly":"Y","ipdsId":"IP-086237","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":348951,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1141/coverthb.jpg"},{"id":348952,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1141/ofr20171141.pdf","text":"Report","size":"9.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1141"}],"country":"United States","state":"California","otherGeospatial":"Sacramento Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.42340087890624,\n 38.62116234642254\n ],\n [\n -121.36596679687499,\n 38.62116234642254\n ],\n [\n -121.36596679687499,\n 39.605688178320804\n ],\n [\n -122.42340087890624,\n 39.605688178320804\n ],\n [\n -122.42340087890624,\n 38.62116234642254\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive
East Sacramento, California 95819
Mechanisms relating offshore geologic framework to shoreline evolution are determined through geologic investigations, oceanographic deployments, and numerical modeling. Analysis of shoreline positions from the past 50 years along Fire Island, New York, a 50 km long barrier island, demonstrates a persistent undulating shape along the western half of the island. The shelf offshore of these persistent undulations is characterized with shoreface-connected sand ridges (SFCR) of a similar alongshore length scale, leading to a hypothesis that the ridges control the shoreline shape through the modification of flow. To evaluate this, a hydrodynamic model was configured to start with the US East Coast and scale down to resolve the Fire Island nearshore. The model was validated using observations along western Fire Island and buoy data, and used to compute waves, currents and sediment fluxes. To isolate the influence of the SFCR on the generation of the persistent shoreline shape, simulations were performed with a linearized nearshore bathymetry to remove alongshore transport gradients associated with shoreline shape. The model accurately predicts the scale and variation of the alongshore transport that would generate the persistent shoreline undulations. In one location, however, the ridge crest connects to the nearshore and leads to an offshore-directed transport that produces a difference in the shoreline shape. This qualitatively supports the hypothesized effect of cross-shore fluxes on coastal evolution. Alongshore flows in the nearshore during a representative storm are driven by wave breaking, vortex force, advection and pressure gradient, all of which are affected by the SFCR.
","language":"English","publisher":"AGU","doi":"10.1002/2017JC012808","usgsCitation":"Safak, I., List, J.H., Warner, J., and Schwab, W.C., 2017, Persistent shoreline shape induced from offshore geologic framework: Effects of shoreface connected ridges: Journal of Geophysical Research C: Oceans, v. 122, no. 11, p. 8721-8738, https://doi.org/10.1002/2017JC012808.","productDescription":"18 p.","startPage":"8721","endPage":"8738","ipdsId":"IP-082366","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":469311,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://hdl.handle.net/1912/9472","text":"Publisher Index Page"},{"id":349010,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Fire Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.33099365234375,\n 40.588928169693745\n ],\n [\n -72.35321044921875,\n 40.588928169693745\n ],\n [\n -72.35321044921875,\n 40.865756786006806\n ],\n [\n -73.33099365234375,\n 40.865756786006806\n ],\n [\n -73.33099365234375,\n 40.588928169693745\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"122","issue":"11","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2017-11-15","publicationStatus":"PW","scienceBaseUri":"5a60fb0fe4b06e28e9c22b8e","contributors":{"authors":[{"text":"Safak, Ilgar 0000-0001-7675-0770 isafak@usgs.gov","orcid":"https://orcid.org/0000-0001-7675-0770","contributorId":5522,"corporation":false,"usgs":true,"family":"Safak","given":"Ilgar","email":"isafak@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":722349,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"List, Jeffrey H. 0000-0001-8594-2491 jlist@usgs.gov","orcid":"https://orcid.org/0000-0001-8594-2491","contributorId":174581,"corporation":false,"usgs":true,"family":"List","given":"Jeffrey","email":"jlist@usgs.gov","middleInitial":"H.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":722350,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Warner, John C. 0000-0002-3734-8903 jcwarner@usgs.gov","orcid":"https://orcid.org/0000-0002-3734-8903","contributorId":2681,"corporation":false,"usgs":true,"family":"Warner","given":"John C.","email":"jcwarner@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":722351,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schwab, William C. 0000-0001-9274-5154 bschwab@usgs.gov","orcid":"https://orcid.org/0000-0001-9274-5154","contributorId":417,"corporation":false,"usgs":true,"family":"Schwab","given":"William","email":"bschwab@usgs.gov","middleInitial":"C.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":722352,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70194083,"text":"70194083 - 2017 - Late Quaternary uplift along the North America-Caribbean plate boundary: Evidence from the sea level record of Guantanamo Bay, Cuba","interactions":[],"lastModifiedDate":"2017-11-16T14:27:29","indexId":"70194083","displayToPublicDate":"2017-11-16T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3219,"text":"Quaternary Science Reviews","active":true,"publicationSubtype":{"id":10}},"title":"Late Quaternary uplift along the North America-Caribbean plate boundary: Evidence from the sea level record of Guantanamo Bay, Cuba","docAbstract":"The tectonic setting of the North America-Caribbean plate boundary has been studied intensively, but some aspects are still poorly understood, particularly along the Oriente fault zone. Guantanamo Bay, southern Cuba, is considered to be on a coastline that is under a transpressive tectonic regime along this zone, and is hypothesized to have a low uplift rate. We tested this by studying emergent reef terrace deposits around the bay. Reef elevations in the protected, inner part of the bay are ∼11–12 m and outer-coast, wave-cut benches are as high as ∼14 m. Uranium-series analyses of corals yield ages ranging from ∼133 ka to ∼119 ka, correlating this reef to the peak of the last interglacial period, marine isotope stage (MIS) 5.5. Assuming a span of possible paleo-sea levels at the time of the last interglacial period yields long-term tectonic uplift rates of 0.02–0.11 m/ka, supporting the hypothesis that the tectonic uplift rate is low. Nevertheless, on the eastern and southern coasts of Cuba, east and west of Guantanamo Bay, there are flights of multiple marine terraces, at higher elevations, that could record a higher rate of uplift, implying that Guantanamo Bay may be anomalous. Southern Cuba is considered to have experienced a measurable but modest effect from glacial isostatic adjustment (GIA) processes. Thus, with a low uplift rate, Guantanamo Bay should show no evidence of emergent marine terraces dating to the ∼100 ka (MIS 5.3) or ∼80 ka (MIS 5.1) sea stands and results of the present study support this.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.quascirev.2017.10.024","usgsCitation":"Muhs, D., Schweig, E.S., Simmons, K., and Halley, R.B., 2017, Late Quaternary uplift along the North America-Caribbean plate boundary: Evidence from the sea level record of Guantanamo Bay, Cuba: Quaternary Science Reviews, v. 178, p. 54-76, https://doi.org/10.1016/j.quascirev.2017.10.024.","productDescription":"23 p.","startPage":"54","endPage":"76","ipdsId":"IP-080061","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":469309,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.quascirev.2017.10.024","text":"Publisher Index Page"},{"id":349015,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Cuba","otherGeospatial":"Guantanamo Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.234375,\n 19.88910880963871\n ],\n [\n -75.0802230834961,\n 19.88910880963871\n ],\n [\n -75.0802230834961,\n 19.980447420014933\n ],\n [\n -75.234375,\n 19.980447420014933\n ],\n [\n -75.234375,\n 19.88910880963871\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"178","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fb10e4b06e28e9c22b93","contributors":{"authors":[{"text":"Muhs, Daniel R. 0000-0001-7449-251X dmuhs@usgs.gov","orcid":"https://orcid.org/0000-0001-7449-251X","contributorId":168575,"corporation":false,"usgs":true,"family":"Muhs","given":"Daniel R.","email":"dmuhs@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":722058,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schweig, Eugene S. 0000-0003-3669-9741 schweig@usgs.gov","orcid":"https://orcid.org/0000-0003-3669-9741","contributorId":1271,"corporation":false,"usgs":true,"family":"Schweig","given":"Eugene","email":"schweig@usgs.gov","middleInitial":"S.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":722060,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Simmons, Kathleen 0000-0002-7920-094X ksimmons@usgs.gov","orcid":"https://orcid.org/0000-0002-7920-094X","contributorId":200362,"corporation":false,"usgs":true,"family":"Simmons","given":"Kathleen","email":"ksimmons@usgs.gov","affiliations":[],"preferred":true,"id":722059,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Halley, Robert B.","contributorId":195075,"corporation":false,"usgs":false,"family":"Halley","given":"Robert","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":722553,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70191327,"text":"sir20175105 - 2017 - Suitability of river delta sediment as proppant, Missouri and Niobrara Rivers, Nebraska and South Dakota, 2015","interactions":[],"lastModifiedDate":"2018-11-19T10:10:32","indexId":"sir20175105","displayToPublicDate":"2017-11-16T00:00:00","publicationYear":"2017","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":"2017-5105","title":"Suitability of river delta sediment as proppant, Missouri and Niobrara Rivers, Nebraska and South Dakota, 2015","docAbstract":"Sediment management is a challenge faced by reservoir managers who have several potential options, including dredging, for mitigation of storage capacity lost to sedimentation. As sediment is removed from reservoir storage, potential use of the sediment for socioeconomic or ecological benefit could potentially defray some costs of its removal. Rivers that transport a sandy sediment load will deposit the sand load along a reservoir-headwaters reach where the current of the river slackens progressively as its bed approaches and then descends below the reservoir water level. Given a rare combination of factors, a reservoir deposit of alluvial sand has potential to be suitable for use as proppant for hydraulic fracturing in unconventional oil and gas development. In 2015, the U.S. Geological Survey began a program of researching potential sources of proppant sand from reservoirs, with an initial focus on the Missouri River subbasins that receive sand loads from the Nebraska Sand Hills. This report documents the methods and results of assessments of the suitability of river delta sediment as proppant for a pilot study area in the delta headwaters of Lewis and Clark Lake, Nebraska and South Dakota. Results from surface-geophysical surveys of electrical resistivity guided borings to collect 3.7-meter long cores at 25 sites on delta sandbars using the direct-push method to recover duplicate, 3.8-centimeter-diameter cores in April 2015. In addition, the U.S. Geological Survey collected samples of upstream sand sources in the lower Niobrara River valley.
At the laboratory, samples were dried, weighed, washed, dried, and weighed again. Exploratory analysis of natural sand for determining its suitability as a proppant involved application of a modified subset of the standard protocols known as American Petroleum Institute (API) Recommended Practice (RP) 19C. The RP19C methods were not intended for exploration-stage evaluation of raw materials. Results for the washed samples are not directly applicable to evaluations of suitability for use as fracture sand because, except for particle-size distribution, the API-recommended practices for assessing proppant properties (sphericity, roundness, bulk density, and crush resistance) require testing of specific proppant size classes. An optical imaging particle-size analyzer was used to make measurements of particle-size distribution and particle shape. Measured samples were sieved to separate the dominant-size fraction, and the separated subsample was further tested for roundness, sphericity, bulk density, and crush resistance.
For the bulk washed samples collected from the Missouri River delta, the geometric mean size averaged 0.27 millimeters (mm), 80 percent of the samples were predominantly sand in the API 40/70 size class, and 17 percent were predominantly sand in the API 70/140 size class. Distributions of geometric mean size among the four sandbar complexes were similar, but samples collected from sandbar complex B were slightly coarser sand than those from the other three complexes. The average geometric mean sizes among the four sandbar complexes ranged only from 0.26 to 0.30 mm. For 22 main-stem sampling locations along the lower Niobrara River, geometric mean size averaged 0.26 mm, an average of 61 percent was sand in the API 40/70 size class, and 28 percent was sand in the API 70/140 size class. Average composition for lower Niobrara River samples was 48 percent medium sand, 37 percent fine sand, and about 7 percent each very fine sand and coarse sand fractions. On average, samples were moderately well sorted.
Particle shape and strength were assessed for the dominant-size class of each sample. For proppant strength, crush resistance was tested at a predetermined level of stress (34.5 megapascals [MPa], or 5,000 pounds-force per square inch). To meet the API minimum requirement for proppant, after the crush test not more than 10 percent of the tested sample should be finer than the precrush dominant-size class. For particle shape, all samples surpassed the recommended minimum criteria for sphericity and roundness, with most samples being well-rounded.
For proppant strength, of 57 crush-resistance tested Missouri River delta samples of 40/70-sized sand, 23 (40 percent) were interpreted as meeting the minimum criterion at 34.5 MPa, or 5,000 pounds-force per square inch. Of 12 tested samples of 70/140-sized sand, 9 (75 percent) of the Missouri River delta samples had less than 10 percent fines by volume following crush testing, achieving the minimum criterion at 34.5 MPa. Crush resistance for delta samples was strongest at sandbar complex A, where 67 percent of tested samples met the 10-percent fines criterion at the 34.5-MPa threshold. This frequency was higher than was indicated by samples from sandbar complexes B, C, and D that had rates of 50, 46, and 42 percent, respectively. The group of sandbar complex A samples also contained the largest percentages of samples dominated by the API 70/140 size class, which overall had a higher percentage of samples meeting the minimum criterion compared to samples dominated by coarser size classes; however, samples from sandbar complex A that had the API 40/70 size class tested also had a higher rate for meeting the minimum criterion (57 percent) than did samples from sandbar complexes B, C, and D (50, 43, and 40 percent, respectively).
For samples collected along the lower Niobrara River, of the 25 tested samples of 40/70-sized sand, 9 samples passed the API minimum criterion at 34.5 MPa, but only 3 samples passed the more-stringent criterion of 8 percent postcrush fines. All four tested samples of 70/140 sand passed the minimum criterion at 34.5 MPa, with postcrush fines percentage of at most 4.1 percent.
For two reaches of the lower Niobrara River, where hydraulic sorting was energized artificially by the hydraulic head drop at and immediately downstream from Spencer Dam, suitability of channel deposits for potential use as fracture sand was confirmed by test results. All reach A washed samples were well-rounded and had sphericity scores above 0.65, and samples for 80 percent of sampled locations met the crush-resistance criterion at the 34.5-MPa stress level. A conservative lower-bound estimate of sand volume in the reach A deposits was about 86,000 cubic meters. All reach B samples were well-rounded but sphericity averaged 0.63, a little less than the average for upstream reaches A and SP. All four samples tested passed the crush-resistance test at 34.5 MPa. Of three reach B sandbars, two had no more than 3 percent fines after the crush test, surpassing more stringent criteria for crush resistance that accept a maximum of 6 percent fines following the crush test for the API 70/140 size class.
Relative to the crush-resistance test results for the API 40/70 size fraction of two samples of mine output from Loup River settling-basin dredge spoils near Genoa, Nebr., four of five reach A sample locations compared favorably. The four samples had increases in fines composition of 1.6–5.9 percentage points, whereas fines in the two mine-output samples increased by an average 6.8 percentage points.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175105","collaboration":"Prepared in cooperation with Midwest Region Initiative on Natural Sources of Fracture Sand","usgsCitation":"Zelt, R.B., Hobza, C.M., Burton, B.L., Schaepe, N.J., and Piatak, Nadine, 2017, Suitability of river delta sediment as proppant, Missouri and Niobrara Rivers, Nebraska and South Dakota, 2015: U.S. Geological Survey Scientific Investigations Report 2017–5105, 51 p., https://doi.org/10.3133/sir20175105.","productDescription":"Report: viii, 51 p.; Tables: 4; Data Release","numberOfPages":"64","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-077776","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"links":[{"id":348988,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5105/sir20175105.pdf","text":"Report","size":"5.51 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5105"},{"id":348987,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5105/coverthb2.jpg"},{"id":348989,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2017/5105/sir20175105_table4.xlsx","text":"Table 4","size":"38.0 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2017–5105 Table 4"},{"id":348990,"rank":4,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2017/5105/sir20175105_table5.xlsx","text":"Table 5","size":"26.6 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2017–5105 Table 5"},{"id":348991,"rank":5,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2017/5105/sir20175105_table6.xlsx","text":"Table 6","size":"70.8 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2017–5105 Table 6"},{"id":348992,"rank":6,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2017/5105/sir20175105_table9.xlsx","text":"Table 9","size":"75.0","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2017–5105 Table 9"},{"id":348993,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F79W0CQB","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Streambed sediment data for Missouri and Niobrara Rivers, Nebraska and South Dakota, 2015"}],"country":"United States","state":"Nebraska, South Dakota","otherGeospatial":"Missouri River, Niobrara River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -98.75,\n 42.5\n ],\n [\n -97.45,\n 42.5\n ],\n [\n -97.45,\n 43\n ],\n [\n -98.75,\n 43\n ],\n [\n -98.75,\n 42.5\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Nebraska Water Science Center
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5231 South 19th Street
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Global Positioning System (CGPS) data from Mount Etna between May 2015 and September 2016 show intense inflation and a concurrent Slow Slip Event (SSE) from 11 December 2015 to 17 May 2016. In May 2016, an eruptive phase started from the summit craters, temporarily stopping the ongoing inflation. The CGPS data presented here give us the opportunity to determine (1) the source of the inflating body, (2) the strain rate parameters highlighting shear strain rate accumulating along NE Rift and S Rift, (3) the magnitude of the SSE, and (4) possible interaction between modeled sources and other flank structures through stress calculations. By analytical inversion, we find an inflating source 5.5 km under the summit (4.4 km below sea level) and flank slip in a fragmented shallow structure accommodating displacements equivalent to a magnitude Mw6.1 earthquake. These large displacements reflect a complex mechanism of rotations indicated by the inversion of CGPS data for strain rate parameters. At the scale of the volcano, these processes can be considered precursors of seismic activity in the eastern flank of the volcano but concentrated mainly on the northern boundary of the mobile eastern flank along the Pernicana Fault and in the area of the Timpe Fault System.
We quantified gas and heat emissions in an acid-sulfate, vapor-dominated area (0.04-km2) of Norris Geyser Basin, located just north of the 0.63 Ma Yellowstone Caldera and near an area of anomalous uplift. From 14 May to 3 October 2016, an eddy covariance system measured half-hourly CO2, H2O and sensible (H) and latent (LE) heat fluxes and a Multi-GAS instrument measured (1 Hz frequency) atmospheric H2O, CO2 and H2S volumetric mixing ratios. We also measured soil CO2 fluxes using the accumulation chamber method and temperature profiles on a grid and collected fumarole gas samples for geochemical analysis. Eddy covariance CO2 fluxes ranged from − 56 to 885 g m− 2 d− 1. Using wavelet analysis, average daily eddy covariance CO2 fluxes were locally correlated with average daily environmental parameters on several-day to monthly time scales. Estimates of CO2emission rate from the study area ranged from 8.6 t d− 1 based on eddy covariance measurements to 9.8 t d− 1 based on accumulation chamber measurements. Eddy covariance water vapor fluxes ranged from 1178 to 24,600 g m− 2 d− 1. Nighttime H and LEwere considered representative of hydrothermal heat fluxes and ranged from 4 to 183 and 38 to 504 W m− 2, respectively. The total hydrothermal heat emission rate (H + LE + radiant) estimated for the study area was 11.6 MW and LE contributed 69% of the output. The mean ± standard deviation of H2O, CO2 and H2S mixing ratios measured by the Multi-GAS system were 9.3 ± 3.1 parts per thousand, 467 ± 61 ppmv, and 0.5 ± 0.6 ppmv, respectively, and variations in the gas compositions were strongly correlated with diurnal variations in environmental parameters (wind speed and direction, atmospheric temperature). After removing ambient H2O and CO2, the observed variations in the Multi-GAS data could be explained by the mixing of relatively H2O-CO2-H2S-rich fumarole gases with CO2-rich and H2O-H2S-poor soil gases. The fumarole H2O/CO2 and CO2/H2S end member ratios (101.7 and 27.1, respectively, on average) were invariant during the measurement period and fell within the range of values measured in direct fumarole gas samples. The soil gas H2O/CO2end member ratios (~ 15–30) were variable and low relative to the fumarole end member, likely resulting from water vapor loss during cooling and condensation in the shallow subsurface, whereas the CO2/H2S end member ratio was high (~ 160), presumably related to transport of CO2-dominated soil gas emissions mixed with trace fumarolic emissions to the Multi-GAS station. Nighttime eddy covariance ratios of H2O to CO2 flux were typically between the soil gas and fumarole end member H2O/CO2 ratios defined by Multi-GAS measurements. Overall, the combined eddy covariance and Multi-GAS approach provides a powerful tool for quasi-continuous measurements of gas and heat emissions for improved volcano-hydrothermal monitoring.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2017.10.001","usgsCitation":"Lewicki, J.L., Kelly, P.J., Bergfeld, D., Vaughan, R., and Lowenstern, J.B., 2017, Monitoring gas and heat emissions at Norris Geyser Basin, Yellowstone National Park, USA based on a combined eddy covariance and Multi-GAS approach: Journal of Volcanology and Geothermal Research, v. 347, p. 312-326, https://doi.org/10.1016/j.jvolgeores.2017.10.001.","productDescription":"15 p.","startPage":"312","endPage":"326","ipdsId":"IP-088820","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":349628,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Norris Geyser Basin, Yellowstone National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.72776794433592,\n 44.71642860567541\n ],\n [\n -110.6945514678955,\n 44.71642860567541\n ],\n [\n -110.6945514678955,\n 44.742222087511614\n ],\n [\n -110.72776794433592,\n 44.742222087511614\n ],\n [\n -110.72776794433592,\n 44.71642860567541\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"347","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fb10e4b06e28e9c22b9e","contributors":{"authors":[{"text":"Lewicki, Jennifer L. 0000-0003-1994-9104 jlewicki@usgs.gov","orcid":"https://orcid.org/0000-0003-1994-9104","contributorId":5071,"corporation":false,"usgs":true,"family":"Lewicki","given":"Jennifer","email":"jlewicki@usgs.gov","middleInitial":"L.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":724170,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kelly, Peter J. 0000-0002-3868-1046 pkelly@usgs.gov","orcid":"https://orcid.org/0000-0002-3868-1046","contributorId":5931,"corporation":false,"usgs":true,"family":"Kelly","given":"Peter","email":"pkelly@usgs.gov","middleInitial":"J.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":724171,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bergfeld, Deborah 0000-0003-4570-7627 dbergfel@usgs.gov","orcid":"https://orcid.org/0000-0003-4570-7627","contributorId":152531,"corporation":false,"usgs":true,"family":"Bergfeld","given":"Deborah","email":"dbergfel@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":724172,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vaughan, R. Greg gvaughan@usgs.gov","contributorId":200796,"corporation":false,"usgs":true,"family":"Vaughan","given":"R. Greg","email":"gvaughan@usgs.gov","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":false,"id":724173,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lowenstern, Jacob B. 0000-0003-0464-7779 jlwnstrn@usgs.gov","orcid":"https://orcid.org/0000-0003-0464-7779","contributorId":2755,"corporation":false,"usgs":true,"family":"Lowenstern","given":"Jacob","email":"jlwnstrn@usgs.gov","middleInitial":"B.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":724174,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70192446,"text":"70192446 - 2017 - Comparing catchment hydrologic response to a regional storm using specific conductivity sensors","interactions":[],"lastModifiedDate":"2018-03-27T14:04:10","indexId":"70192446","displayToPublicDate":"2017-11-15T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Comparing catchment hydrologic response to a regional storm using specific conductivity sensors","docAbstract":"A better understanding of stormwater generation and solute sources is needed to improve the protection of aquatic ecosystems, infrastructure, and human health from large runoff events. Much of our understanding of water and solutes produced during stormflow comes from studies of individual, small headwater catchments. This study compared many different types of catchments during a single large event to help isolate landscape controls on streamwater and solute generation, including human-impacted land cover. We used a distributed network of specific electrical conductivity sensors to trace storm response during the post-tropical cyclone Sandy event of October 2012 at 29 catchments across the state of New Hampshire. A citizen science sensor network, Lotic Volunteer for Temperature, Electrical Conductivity, and Stage, provided a unique opportunity to investigate high-temporal resolution stream behavior at a broad spatial scale. Three storm response metrics were analyzed in this study: (a) fraction of new water contributing to the hydrograph; (b) presence of first flush (mobilization of solutes during the beginning of the rain event); and (c) magnitude of first flush. We compared new water and first flush to 64 predictor attributes related to land cover, soil, topography, and precipitation. The new water fraction was positively correlated with low and medium intensity development in the catchment and riparian buffers and with the precipitation from a rain event 9 days prior to Sandy. The presence of first flush was most closely related (positively) to soil organic matter. Magnitude of first flush was not strongly related to any of the catchment variables. Our results highlight the potentially important role of human landscape modification in runoff generation at multiple spatial scales and the lack of a clear role in solute flushing. Further development of regional-scale in situ sensor networks will provide better understanding of stormflow and solute generation across a wide range of landscape conditions.","language":"English","publisher":"Wiley","doi":"10.1002/hyp.11091","usgsCitation":"Inserillo, A., Green, M., Shanley, J.B., and Boyer, J., 2017, Comparing catchment hydrologic response to a regional storm using specific conductivity sensors: Hydrological Processes, v. 31, no. 5, p. 1074-1085, https://doi.org/10.1002/hyp.11091.","productDescription":"12 p.","startPage":"1074","endPage":"1085","ipdsId":"IP-076898","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":348888,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New 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observatory","interactions":[],"lastModifiedDate":"2017-11-15T10:37:40","indexId":"70191844","displayToPublicDate":"2017-11-15T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5518,"text":"Geoscientific Instrumentation, Methods and Data Systems","active":true,"publicationSubtype":{"id":10}},"title":"Geoelectric monitoring at the Boulder magnetic observatory","docAbstract":"Despite its importance to a range of applied and fundamental studies, and obvious parallels to a robust network of magnetic-field observatories, long-term geoelectric field monitoring is rarely performed. The installation of a new geoelectric monitoring system at the Boulder magnetic observatory of the US Geological Survey is summarized. Data from the system are expected, among other things, to be used for testing and validating algorithms for mapping North American geoelectric fields. An example time series of recorded electric and magnetic fields during a modest magnetic storm is presented. Based on our experience, we additionally present operational aspects of a successful geoelectric field monitoring system.
","language":"English","publisher":"Copernicus Publications","doi":"10.5194/gi-2017-27","usgsCitation":"Blum, C., White, T., Sauter, E.A., Stewart, D., Bedrosian, P.A., and Love, J.J., 2017, Geoelectric monitoring at the Boulder magnetic observatory: Geoscientific Instrumentation, Methods and Data Systems, v. 6, p. 447-452, https://doi.org/10.5194/gi-2017-27.","productDescription":"6 p.","startPage":"447","endPage":"452","ipdsId":"IP-088490","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":469316,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/gi-2017-27","text":"Publisher Index Page"},{"id":348869,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","city":"Boulder","volume":"6","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fb11e4b06e28e9c22bb8","contributors":{"authors":[{"text":"Blum, Cletus","contributorId":197377,"corporation":false,"usgs":false,"family":"Blum","given":"Cletus","affiliations":[],"preferred":false,"id":713359,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"White, Tim 0000-0002-3563-0649 ttwhite@usgs.gov","orcid":"https://orcid.org/0000-0002-3563-0649","contributorId":2010,"corporation":false,"usgs":true,"family":"White","given":"Tim","email":"ttwhite@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":713360,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sauter, Edward A. 0000-0001-7541-8506 esauter@usgs.gov","orcid":"https://orcid.org/0000-0001-7541-8506","contributorId":3773,"corporation":false,"usgs":true,"family":"Sauter","given":"Edward","email":"esauter@usgs.gov","middleInitial":"A.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":713361,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stewart, Duff 0000-0001-6378-6600 dcstewart@usgs.gov","orcid":"https://orcid.org/0000-0001-6378-6600","contributorId":3787,"corporation":false,"usgs":true,"family":"Stewart","given":"Duff","email":"dcstewart@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":713362,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"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":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":713363,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"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":713364,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70188187,"text":"pp1824N - 2017 - Geology and assessment of undiscovered oil and gas resources of the Timan-Pechora Basin Province, Russia, 2008","interactions":[{"subject":{"id":70188187,"text":"pp1824N - 2017 - Geology and assessment of undiscovered oil and gas resources of the Timan-Pechora Basin Province, Russia, 2008","indexId":"pp1824N","publicationYear":"2017","noYear":false,"chapter":"N","title":"Geology and assessment of undiscovered oil and gas resources of the Timan-Pechora Basin Province, Russia, 2008"},"predicate":"IS_PART_OF","object":{"id":70193865,"text":"pp1824 - 2017 - The 2008 Circum-Arctic Resource Appraisal ","indexId":"pp1824","publicationYear":"2017","noYear":false,"title":"The 2008 Circum-Arctic Resource Appraisal "},"id":1}],"isPartOf":{"id":70193865,"text":"pp1824 - 2017 - The 2008 Circum-Arctic Resource Appraisal ","indexId":"pp1824","publicationYear":"2017","noYear":false,"title":"The 2008 Circum-Arctic Resource Appraisal "},"lastModifiedDate":"2024-06-26T14:12:03.055778","indexId":"pp1824N","displayToPublicDate":"2017-11-15T00:00:00","publicationYear":"2017","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":"1824","chapter":"N","title":"Geology and assessment of undiscovered oil and gas resources of the Timan-Pechora Basin Province, Russia, 2008","docAbstract":"The Timan-Pechora Basin Province is a triangular area that represents the northeasternmost cratonic block of east European Russia. A 75-year history of petroleum exploration and production in the area there has led to the discovery of more than 16 billion barrels of oil (BBO) and 40 trillion cubic feet of gas (TCFG). Three geologic assessment units (AUs) were defined for assessing the potential for undiscovered oil and gas resources in the province: (1) the Northwest Izhma Depression AU, which includes all potential structures and reservoirs that formed in the northwestern part of the Izhma-Pechora Depression, although this part of the basin contains only sparse source and reservoir rocks and so was not assessed quantitatively; (2) the Main Basin Platform AU, which includes all potential structures and reservoirs that formed in the central part of the basin, where the tectonic and petroleum system evolution was complex; and (3) the Foredeep Basins AU, which includes all potential structures and reservoirs that formed within the thick sedimentary section of the foredeep basins west of the Uralian fold and thrust belt during the Permian and Triassic Uralian orogeny.
For the Timan-Pechora Basin Province, the estimated means of undiscovered resources are 3.3 BBO, 17 TCFG, and 0.3 billion barrels of natural-gas liquids (BBNGL). For the AU areas north of the Arctic Circle in the province, the estimated means of undiscovered resources are 1.7 BBO, 9.0 TCFG, and 0.2 BBNGL. These assessment results indicate that exploration in the Timan-Pechora Basin Province is at a mature level.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1824N","usgsCitation":"Schenk, C.J., 2017, Geology and assessment of undiscovered oil and gas resources of the Timan-Pechora Basin Province, Russia, 2008, chap. N of Moore, T.E., and Gautier, D.L., eds., The 2008 Circum-Arctic Resource Appraisal: U.S. Geological Survey Professional Paper 1824, 22 p., https://doi.org/10.3133/pp1824N.","productDescription":"Report: vii, 22 p.; 7 Appendixes","numberOfPages":"33","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-050986","costCenters":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"links":[{"id":348514,"rank":9,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/pp/1824/n/pp1824_chaptern_appendix7.pdf","text":"Appendix 7","size":"485 KB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1824 Chapter N Appendix 7","linkHelpText":"Detailed Assessment Results for the Foredeep Basins Assessment Unit"},{"id":348513,"rank":8,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/pp/1824/n/pp1824_chaptern_appendix6.pdf","text":"Appendix 6","size":"499 KB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1824 Chapter N Appendix 6","linkHelpText":"Detailed Assessment Results for the Main Basin Platform Assessment Unit"},{"id":348512,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/pp/1824/n/pp1824_chaptern_appendix5.xls","text":"Appendix 5","size":"50 KB xls","description":"PP 1824 Chapter N Appendix 5","linkHelpText":"Input data for the Foredeep Basins Assessment Unit"},{"id":348511,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/pp/1824/n/pp1824_chaptern_appendix4.pdf","text":"Appendix 4","size":"713 KB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1824 Chapter N Appendix 4","linkHelpText":"Basin Evolution Chart for the Foredeep Basins Assessment Unit"},{"id":348510,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/pp/1824/n/pp1824_chaptern_appendix3.xls","text":"Appendix 3","size":"45 KB xls","description":"PP 1824 Chapter N Appendix 3","linkHelpText":"Input Data for the Main Basin Platform Assessment Unit"},{"id":348509,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/pp/1824/n/pp1824_chaptern_appendix2.pdf","text":"Appendix 2","size":"713 KB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1824 Chapter N Appendix 2","linkHelpText":"Basin Evolution Chart for the Main Basin Platform Assessment Unit"},{"id":348507,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1824/n/pp1824n.pdf","text":"Report","size":"1.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1824 Chapter N"},{"id":348506,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1824/n/coverthb.jpg"},{"id":348508,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/pp/1824/n/pp1824_chaptern_appendix1.xls","text":"Appendix 1","size":"40 KB xls","description":"PP 1824 Chapter N Appendix 1","linkHelpText":"Input Data for the Northwest Izhma Depression Assessment Unit"}],"country":"Russia","otherGeospatial":"Timan-Pechora Basin Province","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 44,\n 60.06484046010452\n ],\n [\n 65.390625,\n 60.06484046010452\n ],\n [\n 65.390625,\n 73.22669969306126\n ],\n [\n 44,\n 73.22669969306126\n ],\n [\n 44,\n 60.06484046010452\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Contact Information, Geology, Minerals, Energy, & Geophysics Science Center—Menlo Park
U.S. Geological Survey
345 Middlefield Road
Menlo Park, CA 94025-3591
FAX 650-329-4936
The U.S. Geological Survey (USGS) recently assessed the potential for undiscovered petroleum resources of the East Barents Basins Province and the Novaya Zemlya Basins and Admiralty Arch Province as part of its Circum-Arctic Resource Appraisal. These two provinces are situated northeast of Scandinavia and the northwestern Russian Federation, on the Barents Sea Shelf between Novaya Zemlya to the east and the Barents Platform to the west. Three assessment units (AUs) were defined in the East Barents Basins Province for this study: the Kolguyev Terrace AU, the South Barents and Ludlov Saddle AU, and the North Barents Basin AU. A fourth AU, defined as the Novaya Zemlya Basins and Admiralty Arch AU, coincides with the Novaya Zemlya Basins and Admiralty Arch Province. These four AUs, all lying north of the Arctic Circle, were assessed for undiscovered, technically recoverable resources, resulting in total estimated mean volumes of ~7.4 billion barrels of crude oil, 318 trillion cubic feet (TCF) of natural gas, and 1.4 billion barrels of natural-gas liquids.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1824O","usgsCitation":"Klett, T.R., 2017, Geology and Assessment of Undiscovered Oil and Gas Resources of the East Barents Basins Province and the Novaya Zemlya Basins and Admiralty Arch Province, 2008, chap. O of Moore, T.E., and Gautier, D.L., eds., The 2008 Circum-Arctic Resource Appraisal: U.S. Geological Survey Professional Paper 1824, 27 p., https://doi.org/10.3133/pp1824O.","productDescription":"Report: vii, 27 p.; 4 Appendixes","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-050985","costCenters":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"links":[{"id":348502,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/pp/1824/o/pp1824_chaptero_appendix4.xls","text":"Appendix 4","size":"53 KB xls","description":"PP 1824 Chapter O Appendix 4","linkHelpText":"Input Data for the Novaya Zemlya Basins and Admiralty Arch Assessment Unit"},{"id":348501,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/pp/1824/o/pp1824_chaptero_appendix3.xls","text":"Appendix 3","size":"53 KB xls","description":"PP 1824 Chapter O Appendix 3","linkHelpText":"Input Data for the North Barents Basin Assessment Unit"},{"id":348500,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/pp/1824/o/pp1824_chaptero_appendix2.xls","text":"Appendix 2","size":"53 KB xls","description":"PP 1824 Chapter O Appendix 2","linkHelpText":"Input Data for the South Barents Basin and Ludlov Saddle Assessment Unit"},{"id":348497,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1824/o/coverthb.jpg"},{"id":348499,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/pp/1824/o/pp1824_chaptero_appendix1.xls","text":"Appendix 1","size":"53 KB xls","description":"PP 1824 Chapter O Appendix 1","linkHelpText":"Input Data for the Kolguyev Terrace Assessment Unit"},{"id":348498,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1824/o/pp1824o.pdf","text":"Report","size":"2.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1824 Chapter O"}],"otherGeospatial":"Admiralty Arch Province, East Barents Basins Province, Novaya Zemlya Basins","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 32,\n 68\n ],\n [\n 73,\n 68\n ],\n [\n 73,\n 83\n ],\n [\n 32,\n 83\n ],\n [\n 32,\n 68\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Contact Information, Geology, Minerals, Energy, & Geophysics Science Center—Menlo Park
U.S. Geological Survey
345 Middlefield Road
Menlo Park, CA 94025-3591
FAX 650-329-4936
The U.S. Geological Survey (USGS) recently assessed the potential for undiscovered oil and gas resources of the North Kara Basins and Platforms Province as part of the its Circum-Arctic Resource Appraisal. This geologic province is north of western Siberia, Russian Federation, in the North Kara Sea between Novaya Zemlya to the west and Severnaya Zemlya to the east. One assessment unit (AU) was defined, the North Kara Basins and Platforms AU, which coincides with the geologic province. This AU was assessed for undiscovered, technically recoverable resources. The total estimated mean volumes of undiscovered petroleum resources in the province are ~1.8 billion barrels of crude oil, ~15.0 trillion cubic feet of natural gas, and ~0.4 billion barrels of natural-gas liquids, all north of the Arctic Circle.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1824P","usgsCitation":"Klett, T.R., and Pitman, J.K., 2017, Geology and assessment of undiscovered oil and gas resources of the North Kara Basins and Platforms Province, 2008, chap. P of Moore, T.E., and Gautier, D.L., eds., The 2008 Circum-Arctic Resource Appraisal: U.S. Geological Survey Professional Paper 1824, 15 p., https://doi.org/10.3133/pp1824P.","productDescription":"Report: vii, 15 p.; Appendix","numberOfPages":"26","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-050987","costCenters":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"links":[{"id":348833,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1824/p/pp1824p.pdf","text":"Report","size":"1.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1824 Chapter P"},{"id":348832,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1824/p/coverthb.jpg"},{"id":348834,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/pp/1824/p/pp1824P_chapterp_appendix.xls","size":"53 KB xls","description":"PP 1824 Chapter P Appendix","linkHelpText":"Input Data for the North Kara Basins and Platforms Assessment Unit"}],"otherGeospatial":"North Kara Basins, Platforms Province","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 70,\n 75\n ],\n [\n 100,\n 75\n ],\n [\n 100,\n 82\n ],\n [\n 70,\n 82\n ],\n [\n 70,\n 75\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Contact Information, Geology, Minerals, Energy, & Geophysics Science Center—Menlo Park
U.S. Geological Survey
345 Middlefield Road
Menlo Park, CA 94025-3591
FAX 650-329-4936
Arctic Ocean temperatures influence ecosystems, sea ice, species diversity, biogeochemical cycling, seafloor methane stability, deep-sea circulation, and CO2 cycling. Today's Arctic Ocean and surrounding regions are undergoing climatic changes often attributed to \"Arctic amplification\" - that is, amplified warming in Arctic regions due to sea-ice loss and other processes, relative to global mean temperature. However, the long-term evolution of Arctic amplification is poorly constrained due to lack of continuous sediment proxy records of Arctic Ocean temperature, sea ice cover and circulation. Here we present reconstructions of Arctic Ocean intermediate depth water (AIW) temperatures and sea-ice cover spanning the last ~ 1.5 million years (Ma) of orbitally-paced glacial/interglacial cycles (GIC). Using Mg/Ca paleothermometry of the ostracode Krithe and sea-ice planktic and benthic indicator species, we suggest that the Mid-Brunhes Event (MBE), a major climate transition ~ 400-350 ka, involved fundamental changes in AIW temperature and sea-ice variability. Enhanced Arctic amplification at the MBE suggests a major climate threshold was reached at ~ 400 ka involving Atlantic Meridional Overturning Circulation (AMOC), inflowing warm Atlantic Layer water, ice sheet, sea-ice and ice-shelf feedbacks, and sensitivity to higher post-MBE interglacial CO2 concentrations.
","language":"English","publisher":"Springer","doi":"10.1038/s41598-017-13821-2","usgsCitation":"Cronin, T.M., Dwyer, G.S., Caverly, E., Farmer, J., DeNinno, L., Rodriguez-Lazaro, J., and Gemery, L., 2017, Enhanced Arctic amplification began at the Mid-Brunhes Event 430,000 years ago: Scientific Reports, v. 7, 14475; 6 p., https://doi.org/10.1038/s41598-017-13821-2.","productDescription":"14475; 6 p.","ipdsId":"IP-083962","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":469313,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-017-13821-2","text":"Publisher Index Page"},{"id":348868,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Arctic Ocean","volume":"7","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-11-03","publicationStatus":"PW","scienceBaseUri":"5a60fb11e4b06e28e9c22bbc","contributors":{"authors":[{"text":"Cronin, Thomas M. 0000-0002-2643-0979 tcronin@usgs.gov","orcid":"https://orcid.org/0000-0002-2643-0979","contributorId":2579,"corporation":false,"usgs":true,"family":"Cronin","given":"Thomas","email":"tcronin@usgs.gov","middleInitial":"M.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":712449,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dwyer, Gary S.","contributorId":197070,"corporation":false,"usgs":false,"family":"Dwyer","given":"Gary","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":712450,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Caverly, Emma","contributorId":197071,"corporation":false,"usgs":false,"family":"Caverly","given":"Emma","affiliations":[],"preferred":false,"id":712451,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Farmer, Jesse","contributorId":197072,"corporation":false,"usgs":false,"family":"Farmer","given":"Jesse","affiliations":[],"preferred":false,"id":712452,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"DeNinno, Lauren H.","contributorId":197073,"corporation":false,"usgs":false,"family":"DeNinno","given":"Lauren H.","affiliations":[],"preferred":false,"id":712453,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rodriguez-Lazaro, Julio","contributorId":197074,"corporation":false,"usgs":false,"family":"Rodriguez-Lazaro","given":"Julio","email":"","affiliations":[],"preferred":false,"id":712454,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gemery, Laura 0000-0003-1966-8732 lgemery@usgs.gov","orcid":"https://orcid.org/0000-0003-1966-8732","contributorId":5402,"corporation":false,"usgs":true,"family":"Gemery","given":"Laura","email":"lgemery@usgs.gov","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":722116,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70193865,"text":"pp1824 - 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Twenty-eight chapters summarize the petroleum geology and resource potential of individual, geologically defined provinces north of the Arctic Circle, including those of northern Alaska, northern Canada, east and west Greenland, and most of Arctic Russia, as well as certain offshore areas of the north Atlantic Basin and the Polar Sea. Appendixes tabulate the input and output information used during the assessment.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1824","usgsCitation":"Moore, T.E., and Gautier, D.L., eds., 2017, The 2008 Circum-Arctic Resource Appraisal: U.S. Geological Survey Professional Paper 1824, https://doi.org/10.3133/pp1824.","productDescription":"30 Chapters","onlineOnly":"Y","costCenters":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"links":[{"id":348379,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1824/pp1824_illustration.pdf","text":"Illustration","size":"2.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1824 Illustration"},{"id":348332,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1824/coverthb_.jpg"}],"otherGeospatial":"Arctic Circle","contact":"Contact Information, Geology, Minerals, Energy, & Geophysics Science Center—Menlo Park
U.S. Geological Survey
345 Middlefield Road
Menlo Park, CA 94025-3591
FAX 650-329-4936
Biological diversity, or biodiversity, is the variety and abundance of species in a defined area, and is one of the oldest and most basic descriptions of biological communities. Understanding how populations and communities are structured and change over space and time in response to internal and external forces is a management priority. Effective management practices and conservation strategies depend on our understanding of the relationship between changes in biodiversity and ecological drivers such as invasive species, land use and climate change. To demonstrate how changes in biodiversity may be monitored over a large (400 km2) tract of native forest habitat, we compared bird and plant community composition and structure in an upper montane region of Hawai‘i Island originally surveyed in 1977 as part of the Hawai‘i Forest Bird Survey (Scott et al. 1986) with a comprehensive sample of the same region in 2015.
Our findings suggest that across a region spanning an elevation range of 600 to 2,000 m considerable changes occurred in the plant and bird communities between 1977 and 2015. Endemic and indigenous plants species richness (i.e., total number of species) decreased dramatically in the low and middle elevations below an invasive weed front, whereas naturalized plant species richness did not change between the two periods at any elevation. Endemic bird abundance decreased and two species were lost in the lower elevations (< 1,100 m) between 1977 and 2015, while naturalized bird abundance and the numbers of species increased in the same area. In addition to changes in community composition, the structure of the forest showed evidence of changes in dominant and sub-dominant tree canopy cover, shrub and herbaceous cover, dominant tree canopy height, and matted fern cover.
Biodiversity monitoring helps to define specific conservation targets and to measure progress towards reaching those targets. It is difficult to ascribe causative factors to a change in biodiversity without directly manipulating the environment. Forest habitat in a variety of settings (i.e., islands and regions with differing land-use histories and elevation ranges), however, can provide opportunities to evaluate the influence of ecological drivers. Declines in native bird biodiversity in low-elevation areas may be attributed to invasive species as land use and climate conditions have remained relatively similar over the 40-year period. Thus, the shift from an endemic-naturalized co-dominated community in 1977 to one dominated by naturalized, alien birds in 2015, and reduction in native bird abundance over that period, may reflect increasing dominance by naturalized plants within this forested area. Inferences drawn from analyses of region-wide surveys, especially with replicate datasets, will facilitate the identification of broad-scale changes in biodiversity, and provide a needed current datum in Hawaiian plant and bird biodiversity monitoring.
The amount of yet-to-find oil and gas in the high northern latitudes is one of the great uncertainties of future energy supply. The possibility of extensive new petroleum developments in the Arctic Ocean is of interest to the Arctic nations, to petroleum companies, and to those concerned with the delicate and changing Arctic environment. The U.S. Geological Survey (USGS) 2008 Circum-Arctic Resource Appraisal (CARA) had the express purpose of conducting a geologically based assessment of undiscovered petroleum north of the Arctic Circle, thereby providing an initial evaluation of resource potential.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1824A","usgsCitation":"Gautier, D.L., and Moore, T.E., 2017, Introduction to the 2008 Circum-Arctic Resource Appraisal (CARA) professional paper, chap. A of Moore, T.E., and Gautier, D.L., eds., The 2008 Circum-Arctic Resource Appraisal: U.S. Geological Survey Professional Paper 1824, 9 p., https://doi.org/10.3133/pp1824A.","productDescription":"vi, 9 p.","numberOfPages":"20","onlineOnly":"Y","ipdsId":"IP-092028","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":348491,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1824/a/coverthb2.jpg"},{"id":348492,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1824/a/pp1824a.pdf","text":"Report","size":"3.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1824 Chapter A"}],"otherGeospatial":"Arctic Circle","contact":"Contact Information, Geology, Minerals, Energy, & Geophysics Science Center—Menlo Park
U.S. Geological Survey
345 Middlefield Road
Menlo Park, CA 94025-3591
FAX 650-329-4936
A major issue affecting land-based, closed containment Atlantic salmon Salmo salar growout production in water recirculation aquaculture systems (RAS) is precocious male maturation, which can negatively impact factors such as feed conversion, fillet yield, and product quality. Along with other water quality parameters, elevated nitrate nitrogen (NO3-N) has been shown to influence the reproductive development and endogenous sex steroid production in a number of aquatic animal species, including Atlantic salmon. We sought to determine whether elevated NO3-N in RAS can influence early maturation in post-smolt Atlantic salmon in an 8-month trial in replicated freshwater RAS. Post-smolt Atlantic salmon (102 ± 1 g) were stocked into six RAS, with three RAS randomly selected for dosing with high NO3-N (99 ± 1 mg/L) and three RAS set for low NO3-N (10 ± 0 mg/L). At 2-, 4-, 6-, and 8-months post-stocking, 5 fish were randomly sampled from each RAS, gonadosomatic index(GSI) data were collected, and plasma was sampled for 11-ketotestosterone(11-KT) quantification. At 4- and 8-months post-stocking, samples of culture tank and spring water (used as “makeup” or replacement water) were collected and tested for a suite of 42 hormonally active compounds using liquid chromatography/mass spectrometry, as well as for estrogenicity using the bioluminescent yeast estrogen screen (BLYES) reporter system. Finally, at 8-months post-stocking 8–9 salmon were sampled from each RAS for blood gas and chemistry analyses, and multiple organ tissues were sampled for histopathology evaluation. Overall, sexually mature males were highly prevalent in both NO3-N treatment groups by study’s end, and there did not appear to be an effect of NO3-N on male maturation prevalence based on grilse identification, GSI, and 11-KT results, indicating that other culture parameters likely instigated early maturation. No important differences were noted between treatment groups for whole blood gas and chemistry parameters, and no significant tissue changes were noted on histopathology. No hormones, hormone conjugates, or mycotoxins were detected in any water samples; phytoestrogens were generally detected at low levels but were unrelated to NO3-N treatment. Finally, low-level estrogenicity was detected in RAS water, but a NO3-N treatment effect could not be determined. The major findings of this study are i) the NO3-N treatments did not appear to be related to the observed male maturation, and ii) the majority of hormonally active compounds were not detectable in RAS water.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.aquaeng.2016.09.003","usgsCitation":"Good, C., Davidson, J., Iwanowicz, L.R., Meyer, M.T., Dietze, J.E., Kolpin, D.W., Marancik, D., Birkett, J., Williams, C., and Summerfelt, S.T., 2017, Investigating the influence of nitrate nitrogen on post-smolt Atlantic salmon Salmo salar reproductive physiology in water recirculation aquaculture systems: Aquacultural Engineering, v. 78, no. 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2017 - Methodology for assessment of undiscovered oil and gas resources for the 2008 Circum-Arctic Resource Appraisal","interactions":[{"subject":{"id":70187714,"text":"pp1824B - 2017 - Methodology for assessment of undiscovered oil and gas resources for the 2008 Circum-Arctic Resource Appraisal","indexId":"pp1824B","publicationYear":"2017","noYear":false,"chapter":"B","title":"Methodology for assessment of undiscovered oil and gas resources for the 2008 Circum-Arctic Resource Appraisal"},"predicate":"IS_PART_OF","object":{"id":70193865,"text":"pp1824 - 2017 - The 2008 Circum-Arctic Resource Appraisal ","indexId":"pp1824","publicationYear":"2017","noYear":false,"title":"The 2008 Circum-Arctic Resource Appraisal "},"id":1}],"isPartOf":{"id":70193865,"text":"pp1824 - 2017 - The 2008 Circum-Arctic Resource Appraisal ","indexId":"pp1824","publicationYear":"2017","noYear":false,"title":"The 2008 Circum-Arctic Resource Appraisal "},"lastModifiedDate":"2024-06-26T14:28:36.409831","indexId":"pp1824B","displayToPublicDate":"2017-11-15T00:00:00","publicationYear":"2017","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":"1824","chapter":"B","title":"Methodology for assessment of undiscovered oil and gas resources for the 2008 Circum-Arctic Resource Appraisal","docAbstract":"The methodological procedures used in the geologic assessments of the 2008 Circum-Arctic Resource Appraisal (CARA) were based largely on the methodology developed for the 2000 U.S. Geological Survey World Petroleum Assessment. The main variables were probability distributions for numbers and sizes of undiscovered accumulations with an associated risk of occurrence. The CARA methodology expanded on the previous methodology in providing additional tools and procedures more applicable to the many Arctic basins that have little or no exploration history. Most importantly, geologic analogs from a database constructed for this study were used in many of the assessments to constrain numbers and sizes of undiscovered oil and gas accumulations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1824B","usgsCitation":"Charpentier, R.R., 2017, Methodology for assessment of undiscovered oil and gas resources for the 2008 Circum-Arctic Resource Appraisal, chap. B of Moore, T.L., and Gautier, D.L., eds., The 2008 Circum-Arctic Resource Appraisal: U.S. Geological Survey Professional Paper 1824, 7 p., https://doi.org/10.3133/pp1824B.","productDescription":"Report: vii, 7 p.; 3 Appendixes","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-050993","costCenters":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"links":[{"id":348828,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/pp/1824/b/pp1824_chapterb_appendix3.xls","text":"Appendix 3","size":"42 KB xls","description":"PP 1824 Chapter B Appendix 3","linkHelpText":"Circum-Arctic Resource Appraisal Geologic Data Form for Conventional Assessment Units"},{"id":348827,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/pp/1824/b/pp1824_chapterb_appendix2.pdf","text":"Appendix 2","size":"445 KB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1824 Chapter B Appendix 2","linkHelpText":"Basin Evolution Chart"},{"id":348826,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/pp/1824/b/pp1824_chapterb_appendix1.pdf","text":"Appendix 1","size":"51 KB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1824 Chapter B Appendix 1","linkHelpText":"Monte Carlo Program for Estimating Oil/Gas Accumation Mix"},{"id":348825,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1824/b/pp1824b.pdf","text":"Report","size":"1.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1824 Chapter B"},{"id":348824,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1824/b/coverthb.jpg"}],"otherGeospatial":"Arctic Circle","contact":"Contact Information, Geology, Minerals, Energy, & Geophysics Science Center—Menlo Park
U.S. Geological Survey
345 Middlefield Road
Menlo Park, CA 94025-3591
FAX 650-329-4936