Site coefficients corresponding to those in tables 11.4–1 and 11.4–2 of Minimum Design Loads for Buildings and Other Structures published by the American Society of Civil Engineers (Standard ASCE/SEI 7-10) are derived from four of the Next Generation Attenuation West2 (NGA-W2) Ground-Motion Prediction Equations (GMPEs). The resulting coefficients are compared with those derived by other researchers and those derived from the NGA-West1 database. The derivation of the NGA-W2 average site coefficients provides a simple procedure to update site coefficients with each update in the Maximum Considered Earthquake Response MCER maps. The simple procedure yields average site coefficients consistent with those derived for site-specific design purposes. The NGA-W2 GMPEs provide simple scale factors to reduce conservatism in current simplified design procedures.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151116","usgsCitation":"Borcherdt, R.D., 2015, NGA-West 2 GMPE average site coefficients for use in earthquake-resistant design: U.S. Geological Survey Open-File Report 2015-1116, v, 27 p., https://doi.org/10.3133/ofr20151116.","productDescription":"v, 27 p.","numberOfPages":"32","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-062975","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":301552,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20151116.gif"},{"id":301551,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1116/pdf/ofr2015-1116.pdf","text":"Report","size":"346 KB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":301550,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2015/1116/"}],"publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"558923a4e4b0b6d21dd61a49","contributors":{"authors":[{"text":"Borcherdt, Roger D. 0000-0002-8668-0849 borcherdt@usgs.gov","orcid":"https://orcid.org/0000-0002-8668-0849","contributorId":2373,"corporation":false,"usgs":true,"family":"Borcherdt","given":"Roger","email":"borcherdt@usgs.gov","middleInitial":"D.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":548837,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70197064,"text":"70197064 - 2015 - Economic assessment of the use value of geospatial information","interactions":[],"lastModifiedDate":"2018-05-18T13:47:13","indexId":"70197064","displayToPublicDate":"2015-06-22T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5685,"text":"ISPRS International Journal of Geo-Information ","printIssn":"2220-9964","active":true,"publicationSubtype":{"id":10}},"title":"Economic assessment of the use value of geospatial information","docAbstract":"Geospatial data inform decision makers. An economic model that involves application of spatial and temporal scientific, technical, and economic data in decision making is described. The value of information (VOI) contained in geospatial data is the difference between the net benefits (in present value terms) of a decision with and without the information. A range of technologies is used to collect and distribute geospatial data. These technical activities are linked to examples that show how the data can be applied in decision making, which is a cultural activity. The economic model for assessing the VOI in geospatial data for decision making is applied to three examples: (1) a retrospective model about environmental regulation of agrochemicals; (2) a prospective model about the impact and mitigation of earthquakes in urban areas; and (3) a prospective model about developing private–public geospatial information for an ecosystem services market. Each example demonstrates the potential value of geospatial information in a decision with uncertain information.
","language":"English","publisher":"International Society for Photogrammetry and Remote Sensing","doi":"10.3390/ijgi4031142","usgsCitation":"Bernknopf, R.L., and Shapiro, C.D., 2015, Economic assessment of the use value of geospatial information: ISPRS International Journal of Geo-Information , v. 4, no. 3, p. 1142-1165, https://doi.org/10.3390/ijgi4031142.","productDescription":"24 p.","startPage":"1142","endPage":"1165","ipdsId":"IP-066480","costCenters":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"links":[{"id":472003,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/ijgi4031142","text":"Publisher Index Page"},{"id":354200,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"4","issue":"3","noUsgsAuthors":false,"publicationDate":"2015-07-09","publicationStatus":"PW","scienceBaseUri":"5afeeb5fe4b0da30c1bfc667","contributors":{"authors":[{"text":"Bernknopf, Richard L.","contributorId":97061,"corporation":false,"usgs":true,"family":"Bernknopf","given":"Richard","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":735455,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shapiro, Carl D. 0000-0002-1598-6808 cshapiro@usgs.gov","orcid":"https://orcid.org/0000-0002-1598-6808","contributorId":3048,"corporation":false,"usgs":true,"family":"Shapiro","given":"Carl","email":"cshapiro@usgs.gov","middleInitial":"D.","affiliations":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"preferred":true,"id":735456,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70156185,"text":"70156185 - 2015 - Identifying priority chronic wasting disease surveillance areas for mule deer in Montana","interactions":[],"lastModifiedDate":"2016-04-13T12:36:47","indexId":"70156185","displayToPublicDate":"2015-06-19T14:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Identifying priority chronic wasting disease surveillance areas for mule deer in Montana","docAbstract":"Chronic wasting disease (CWD) is a fatal prion disease that affects a variety of ungulate species including mule deer (Odocoileus hemionus). As of 2014, no CWD cases had been reported in free-ranging ungulates in Montana. However, nearby cases in Canada, Wyoming, and the Dakotas indicated that the disease was encroaching on Montana's borders. Mule deer are native and common throughout Montana, and they represent a significant portion of the total hunter-harvested cervids in the state. The arrival of CWD in Montana may have significant ecosystem and socioeconomic impacts as well as potential consequences for wildlife management. We used 18,879 mule deer locations from 892 individual deer collected during 1975–2011 and modeled habitat selection for 7 herds in 5 of the 7 wildlife management regions in Montana. We estimated resource selection functions (RSF) in a Bayesian framework to predict summer and winter habitat preferences for mule deer. We estimated deer abundance from flyover counts for each region, and used the RSF predictions as weights to distribute the deer across the region. We then calculated the distance to the nearest known infected herds. We predicted areas of high risk of CWD infection in mule deer as areas with densities above the median density estimate and within the lowest quartile of distances to known infected herds. We identified these areas, the southeast corner of Montana and the north-central border near Alberta and Saskatchewan, as priority areas for CWD surveillance and management efforts.
","language":"English","publisher":"Wildlife Society","doi":"10.1002/jwmg.914","usgsCitation":"Russell, R.E., Gude, J., Anderson, N., and Ramsey, J.M., 2015, Identifying priority chronic wasting disease surveillance areas for mule deer in Montana: Journal of Wildlife Management, v. 79, p. 989-997, https://doi.org/10.1002/jwmg.914.","productDescription":"9 p.","startPage":"989","endPage":"997","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-053508","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":306631,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\nA probabilistic mineral resource assessment of undiscovered resources associated with porphyry copper deposits in northeast Asia—composed mainly of Far East Russia and a small part of northeasternmost China—was completed as part of a global mineral resource assessment. Porphyry copper deposits are the main source of copper globally. Russia is an important source of copper, consistently ranking as 6th, 7th, or 8th in world production since 2000, and ranked 7th in 2014. Most of this production has been from magmatic copper-nickel-platinum-group element, volcanogenic massive sulfide, and sediment-hosted copper deposit types.
\nThe purpose of the assessment was to (1) compile a database of known deposits and significant prospects, (2) delineate permissive areas (tracts) for undiscovered porphyry copper deposits that may be present in the upper kilometer of the Earth’s crust, and (3) provide probabilistic estimates of amounts of copper (Cu), molybdenum (Mo), gold (Au), and silver (Ag) that could be contained in undiscovered porphyry copper deposits in the tracts. The assessment was completed by the U.S. Geological Survey in collaboration with geologists from the Russian Academy of Sciences and industry consultants.
\nThe database of known deposits, significant prospects, and prospects includes an inventory of mineral resources in two known porphyry copper deposits, as well as key characteristics derived from available exploration reports for 70 significant porphyry copper prospects and 86 other prospects. Resource and exploration and development activity are updated with information current through February 2013.
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V.","contributorId":89425,"corporation":false,"usgs":true,"family":"Alexeiev","given":"Dmitriy","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":548912,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Frost, Thomas P. 0000-0001-8348-8432 tfrost@usgs.gov","orcid":"https://orcid.org/0000-0001-8348-8432","contributorId":203,"corporation":false,"usgs":true,"family":"Frost","given":"Thomas","email":"tfrost@usgs.gov","middleInitial":"P.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":548913,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Light, Thomas D.","contributorId":46098,"corporation":false,"usgs":true,"family":"Light","given":"Thomas D.","affiliations":[],"preferred":false,"id":548914,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Briggs, Deborah A. dbriggs@usgs.gov","contributorId":5722,"corporation":false,"usgs":true,"family":"Briggs","given":"Deborah","email":"dbriggs@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":548915,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hammarstrom, Jane M. 0000-0003-2742-3460 jhammars@usgs.gov","orcid":"https://orcid.org/0000-0003-2742-3460","contributorId":1226,"corporation":false,"usgs":true,"family":"Hammarstrom","given":"Jane","email":"jhammars@usgs.gov","middleInitial":"M.","affiliations":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":548916,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wallis, John C. jwallis@usgs.gov","contributorId":4084,"corporation":false,"usgs":true,"family":"Wallis","given":"John C.","email":"jwallis@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":false,"id":548917,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Bookstrom, Arthur A. 0000-0003-1336-3364 abookstrom@usgs.gov","orcid":"https://orcid.org/0000-0003-1336-3364","contributorId":1542,"corporation":false,"usgs":true,"family":"Bookstrom","given":"Arthur","email":"abookstrom@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":5056,"text":"Office of the AD Energy and Minerals, and Environmental Health","active":true,"usgs":true}],"preferred":true,"id":548918,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Panteleyev, Andre","contributorId":138932,"corporation":false,"usgs":false,"family":"Panteleyev","given":"Andre","email":"","affiliations":[{"id":12586,"text":"Consultant","active":true,"usgs":false}],"preferred":false,"id":548919,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70148356,"text":"sir20155076 - 2015 - Satellite monitoring of dramatic changes at Hawai'i's only alpine lake: Lake Waiau on Mauna Kea volcano","interactions":[],"lastModifiedDate":"2015-06-19T09:10:25","indexId":"sir20155076","displayToPublicDate":"2015-06-19T09:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-5076","title":"Satellite monitoring of dramatic changes at Hawai'i's only alpine lake: Lake Waiau on Mauna Kea volcano","docAbstract":"Lake Waiau is a small, typically 100-meter-long lake, located near the summit of Mauna Kea volcano, on the Island of Hawaiʻi. It is Hawaiʻi’s only alpine lake and is considered sacred in Hawaiian cultural tradition. Over the past few years, the lake has diminished in size, and, by October 2013, surface water had almost completely disappeared from the lake. In this study, we use high-resolution satellite images and aerial photographs to document recent changes at the lake. Based on our reconstructions covering the past 200 years, the historical lake surface area has typically ranged from 5,000 to 7,000 square meters, but in 2010 a dramatic plunge in lake area ensued. The lake area rebounded significantly in early 2014, following heavy winter storms. This near disappearance of the lake, judging from analysis of visitor photographs and field reports, appears to be highly unusual, if not unprecedented, in the historical record. The unusually low water levels in the lake are consistent with a recent severe drought in Hawaiʻi.
Tidal marshes commonly build upward apace with gradual rise in the level of the sea. It is expected, however, that few tidal marshes will keep up with accelerated sea-level rise later in this century. Tidal marshes have been drowned, moreover, after subsiding during earthquakes.
\nThis report tells of ancient marshes that endured rapid sea-level rise in a region that subsides during earthquakes. The soils of these marshes were unexpectedly encountered in borings for a public-works project at Grays Harbor, Washington. The borings were logged quickly and only a few of the core sections were conserved. The limited findings pose puzzles about how the ancient marshes endured and what their history implies for earthquake hazards.
\nThe borings establish that tidal marshes persisted during the early Holocene at Grays Harbor, an estuary along the Cascadia Subduction Zone of western North America. The persistent marshes are recorded by a unit of peaty mud up to 10 m thick and as much as 40 m below present sea level in the drowned valley of the Chehalis River. The unit was encountered in two areas 4 km apart that were tidal flats in the 19th century. The marshes originated less than 10,000 years ago and endured through most or all of an estimated 500–1,500 years.
\nThe borings further show that these persistent marshes eventually yielded to tidal flats, tidal channels, or both. The change is marked by sand and mud that overlie the peaty mud at a typically sharp contact. The marshes were drowned about 8,600–8,400 years ago if the sand and mud buried them promptly, or later if the sand and mud filled channels that migrated across the peaty mud. In one of the studied areas, tidal marshes became re-established locally in the early Holocene and widely in the middle Holocene, and deposits of middle Holocene marshes were overrun as recently as 1,000 years ago by a gravelly tidal channel. In the other area, tidal-flat and probably subtidal deposits make up all of the middle and late Holocene section below artificial fill; if marshes became re-established in this area after about 8,600–8,400 years ago, their deposits have been lost to erosion.
\nThe puzzles posed by these findings include: (1) How did the marshes manage to endure centuries of relative sea-level rise that likely approached 1 cm/yr on average? (2) Did the marshes also endure subsidence that accompanied great thrust earthquakes on the Cascadia Subduction Zone? (3) Was their eventual drowning triggered by a Cascadia earthquake of unusually large size, or can the drowning be explained by sea-level rise that included a jump from drainage of glacial Lake Agassiz?
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155063","usgsCitation":"Phipps, J.B., Hemphill-Haley, E., and Atwater, B.F., 2015, Chance findings about early Holocene tidal marshes of Grays Harbor, Washington, in relation to rapidly rising seas and great subduction earthquakes (ver. 1.1, May 2016): U.S. Geological Survey Scientific Investigations Report 2015–5063, 36 p., https://dx.doi.org/10.3133/sir20155063.","productDescription":"v, 36 p.","numberOfPages":"46","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-061411","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":301307,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5063/pdf/sir2015-5063_report.pdf","text":"Report","size":"2.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5063 Report"},{"id":301290,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2015/5063/"},{"id":321432,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5063/images/coverthb2.jpg"},{"id":321448,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2015/5063/versionHistory.txt","size":"644 B","linkFileType":{"id":2,"text":"txt"},"description":"SIR 2015-5063 Version History"}],"country":"United States","state":"Washington","otherGeospatial":"Grays Harbor","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.1949462890625,\n 46.842346477463266\n ],\n [\n -124.1949462890625,\n 47.05562189093551\n ],\n [\n -123.7445068359375,\n 47.05562189093551\n ],\n [\n -123.7445068359375,\n 46.842346477463266\n ],\n [\n -124.1949462890625,\n 46.842346477463266\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Earthquake Science Center, Seattle, Washington Field Office
U.S. Geological Survey
Dept. Earth & Space Sciences
University of Washington, Box 351310
Seattle, WA 98195-1310
http://earthquake.usgs.gov/
MAHLI (Mars Hand Lens Imager) is a 2-megapixel, Bayer pattern color CCD camera with a macro lens mounted on a rotatable turret at the end of the 2-meters-long robotic arm aboard the Mars Science Laboratory rover, Curiosity. The camera includes white and longwave ultraviolet LEDs to illuminate targets at night. Onboard data processing services include focus stack merging and data compression. Here we report on the results and status of MAHLI characterization and calibration, covering the pre-launch period from August 2008 through the early months of the extended surface mission through February 2015. Since landing in Gale crater in August 2012, MAHLI has been used for a wide range of science and engineering applications, including distinction among a variety of mafic, siliciclastic sedimentary rocks; investigation of grain-scale rock, regolith, and eolian sediment textures and structures; imaging of the landscape; inspection and monitoring of rover and science instrument hardware concerns; and supporting geologic sample selection, extraction, analysis, delivery, and documentation. The camera has a dust cover and focus mechanism actuated by a single stepper motor. The transparent cover was coated with a thin film of dust during landing, thus MAHLI is usually operated with the cover open. The camera focuses over a range from a working distance of 2.04 cm to infinity; the highest resolution images are at 13.9 µm per pixel; images acquired from 6.9 cm show features at the same scale as the Mars Exploration Rover Microscopic Imagers at 31 µm/pixel; and 100 µm/pixel is achieved at a working distance of ~26.5 cm. The very highest resolution images returned from Mars permit distinction of high contrast silt grains in the 30–40 µm size range. MAHLI has performed well; the images need no calibration in order to achieve most of the investigation’s science and engineering goals. The positioning and repeatability of robotic arm placement of the MAHLI camera head have been excellent on Mars, often with the hardware arriving within millimeters of expectation. Stability while imaging is usually such that the images are sharply focused; some exceptions—thought to result from motion induced by wind—have occurred during longer exposure LED-illuminated night imaging. Image calibration includes relative radiometric correction by removal of dark current and application of a flat field. Dark current is negligible to minor for typical daytime exposure durations and temperatures at the Gale field site. A pre-launch flat field product is usually applied to the data but new products created from images acquired by MAHLI of the Martian sky are superior and can provide a relative radiometric accuracy of ~6%. The camera lens imparts negligible distortion to its images; camera models derived from pre-launch data, with CAHV and CAHVOR parameters captured in their archived labels, can be applied to the images for analysis. MAHLI data and derived products, including pre-launch images, are archived with the NASA Planetary Data System (PDS). This report includes supplementary calibration and characterization data that are not available in the PDS archive (see supplement file MAHLITechRept0001_Supplement.zip).
","language":"English","publisher":"Mars Science Laboratory","doi":"10.13140/RG.2.1.3798.5447","usgsCitation":"Edgett, K., Caplinger, M.A., Maki, J.N., Ravine, M.A., Ghaemi, F., McNair, S., Herkenhoff, K.E., Duston, B.M., Wilson, R.G., Yingst, R.A., Kennedy, M.R., Minitti, M.E., Sengstacken, A.J., Supulver, K.D., Lipkaman, L.J., Krezoski, G.M., McBride, M.J., Jones, T.L., Nixon, B.E., Van Beek, J., Krysak, D.J., and Kirk, R.L., 2015, Curiosity’s robotic arm-mounted Mars Hand Lens Imager (MAHLI): Characterization and calibration status: MSL MAHLI Technical Report 0001, 102 p., https://doi.org/10.13140/RG.2.1.3798.5447.","productDescription":"102 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063280","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":320167,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"571756b0e4b0ef3b7caa5fc1","contributors":{"authors":[{"text":"Edgett, Kenneth S.","contributorId":12736,"corporation":false,"usgs":true,"family":"Edgett","given":"Kenneth S.","affiliations":[],"preferred":false,"id":622188,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Caplinger, Michael A.","contributorId":70635,"corporation":false,"usgs":true,"family":"Caplinger","given":"Michael","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":623137,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Maki, Justin N.","contributorId":30498,"corporation":false,"usgs":true,"family":"Maki","given":"Justin","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":623138,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ravine, Michael A.","contributorId":105959,"corporation":false,"usgs":true,"family":"Ravine","given":"Michael","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":623139,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ghaemi, F. Tony","contributorId":90586,"corporation":false,"usgs":true,"family":"Ghaemi","given":"F. Tony","affiliations":[],"preferred":false,"id":623140,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McNair, Sean","contributorId":167688,"corporation":false,"usgs":false,"family":"McNair","given":"Sean","email":"","affiliations":[{"id":24734,"text":"Malin Space Science Systems, San Diego","active":true,"usgs":false}],"preferred":false,"id":623141,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Herkenhoff, Kenneth E. 0000-0002-3153-6663 kherkenhoff@usgs.gov","orcid":"https://orcid.org/0000-0002-3153-6663","contributorId":2275,"corporation":false,"usgs":true,"family":"Herkenhoff","given":"Kenneth","email":"kherkenhoff@usgs.gov","middleInitial":"E.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":622187,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Duston, Brian M.","contributorId":167689,"corporation":false,"usgs":false,"family":"Duston","given":"Brian","email":"","middleInitial":"M.","affiliations":[{"id":24734,"text":"Malin Space Science Systems, San Diego","active":true,"usgs":false}],"preferred":false,"id":623142,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Wilson, Reg G.","contributorId":72250,"corporation":false,"usgs":true,"family":"Wilson","given":"Reg","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":623143,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Yingst, R. Aileen","contributorId":52827,"corporation":false,"usgs":true,"family":"Yingst","given":"R.","email":"","middleInitial":"Aileen","affiliations":[],"preferred":false,"id":623144,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Kennedy, Megan R.","contributorId":19474,"corporation":false,"usgs":true,"family":"Kennedy","given":"Megan","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":623145,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Minitti, Michelle E.","contributorId":19422,"corporation":false,"usgs":true,"family":"Minitti","given":"Michelle","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":623146,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Sengstacken, Aaron J.","contributorId":66114,"corporation":false,"usgs":true,"family":"Sengstacken","given":"Aaron","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":623147,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Supulver, Kimberley D.","contributorId":167690,"corporation":false,"usgs":false,"family":"Supulver","given":"Kimberley","email":"","middleInitial":"D.","affiliations":[{"id":24734,"text":"Malin Space Science Systems, San Diego","active":true,"usgs":false}],"preferred":false,"id":623148,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Lipkaman, Leslie J.","contributorId":167691,"corporation":false,"usgs":false,"family":"Lipkaman","given":"Leslie","email":"","middleInitial":"J.","affiliations":[{"id":24734,"text":"Malin Space Science Systems, San Diego","active":true,"usgs":false}],"preferred":false,"id":623149,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Krezoski, Gillian M.","contributorId":167692,"corporation":false,"usgs":false,"family":"Krezoski","given":"Gillian","email":"","middleInitial":"M.","affiliations":[{"id":24734,"text":"Malin Space Science Systems, San Diego","active":true,"usgs":false}],"preferred":false,"id":623150,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"McBride, Marie J.","contributorId":167693,"corporation":false,"usgs":false,"family":"McBride","given":"Marie","email":"","middleInitial":"J.","affiliations":[{"id":24734,"text":"Malin Space Science Systems, San Diego","active":true,"usgs":false}],"preferred":false,"id":623151,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Jones, Tessa L.","contributorId":167694,"corporation":false,"usgs":false,"family":"Jones","given":"Tessa","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":623152,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Nixon, Brian E.","contributorId":167695,"corporation":false,"usgs":false,"family":"Nixon","given":"Brian","email":"","middleInitial":"E.","affiliations":[{"id":24734,"text":"Malin Space Science Systems, San Diego","active":true,"usgs":false}],"preferred":false,"id":622189,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Van Beek, Jason K.","contributorId":167696,"corporation":false,"usgs":false,"family":"Van Beek","given":"Jason K.","affiliations":[{"id":24734,"text":"Malin Space Science Systems, San Diego","active":true,"usgs":false}],"preferred":false,"id":623153,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Krysak, Daniel J.","contributorId":167697,"corporation":false,"usgs":false,"family":"Krysak","given":"Daniel","email":"","middleInitial":"J.","affiliations":[{"id":24734,"text":"Malin Space Science Systems, San Diego","active":true,"usgs":false}],"preferred":false,"id":623154,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Kirk, Randolph L. 0000-0003-0842-9226 rkirk@usgs.gov","orcid":"https://orcid.org/0000-0003-0842-9226","contributorId":2765,"corporation":false,"usgs":true,"family":"Kirk","given":"Randolph","email":"rkirk@usgs.gov","middleInitial":"L.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":623155,"contributorType":{"id":1,"text":"Authors"},"rank":22}]}} ,{"id":70189613,"text":"70189613 - 2015 - Cascadia subducting plate fluids channelled to fore-arc mantle corner: ETS and silica deposition","interactions":[],"lastModifiedDate":"2018-01-30T18:43:14","indexId":"70189613","displayToPublicDate":"2015-06-19T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2312,"text":"Journal of Geophysical Research","active":true,"publicationSubtype":{"id":10}},"title":"Cascadia subducting plate fluids channelled to fore-arc mantle corner: ETS and silica deposition","docAbstract":"In this study we first summarize the constraints that on the Cascadia subduction thrust, there is a 70 km gap downdip between the megathrust seismogenic zone and the Episodic Tremor and Slip (ETS) that lies further landward; there is not a continuous transition from unstable to conditionally stable sliding. Seismic rupture occurs mainly offshore for this hot subduction zone. ETS lies onshore. We then suggest what does control the downdip position of ETS. We conclude that fluids from dehydration of the downgoing plate, focused to rise above the fore-arc mantle corner, are responsible for ETS. There is a remarkable correspondence between the position of ETS and this corner along the whole margin. Hydrated mineral assemblages in the subducting oceanic crust and uppermost mantle are dehydrated with downdip increasing temperature, and seismic tomography data indicate that these fluids have strongly serpentinized the overlying fore-arc mantle. Laboratory data show that such fore-arc mantle serpentinite has low permeability and likely blocks vertical expulsion and restricts flow updip within the underlying permeable oceanic crust and subduction shear zone. At the fore-arc mantle corner these fluids are released upward into the more permeable overlying fore-arc crust. An indication of this fluid flux comes from low Poisson's Ratios (and Vp/Vs) found above the corner that may be explained by a concentration of quartz which has exceptionally low Poisson's Ratio. The rising fluids should be silica saturated and precipitate quartz with decreasing temperature and pressure as they rise above the corner.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2015JB011920","usgsCitation":"Hyndman, R.D., McCrory, P.A., Wech, A., Kao, H., and Ague, J., 2015, Cascadia subducting plate fluids channelled to fore-arc mantle corner: ETS and silica deposition: Journal of Geophysical Research, v. 120, no. 6, p. 4344-4358, https://doi.org/10.1002/2015JB011920.","productDescription":"15 p. ","startPage":"4344","endPage":"4358","ipdsId":"IP-061356","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":344022,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"120","issue":"6","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-06-19","publicationStatus":"PW","scienceBaseUri":"59706fb9e4b0d1f9f065a8c1","contributors":{"authors":[{"text":"Hyndman, Roy D.","contributorId":194831,"corporation":false,"usgs":false,"family":"Hyndman","given":"Roy","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":705440,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCrory, Patricia A. 0000-0003-2471-0018 pmccrory@usgs.gov","orcid":"https://orcid.org/0000-0003-2471-0018","contributorId":2728,"corporation":false,"usgs":true,"family":"McCrory","given":"Patricia","email":"pmccrory@usgs.gov","middleInitial":"A.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":705439,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wech, Aaron awech@usgs.gov","contributorId":194832,"corporation":false,"usgs":true,"family":"Wech","given":"Aaron","email":"awech@usgs.gov","affiliations":[],"preferred":true,"id":705441,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kao, Han","contributorId":194833,"corporation":false,"usgs":false,"family":"Kao","given":"Han","email":"","affiliations":[],"preferred":false,"id":705442,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ague, Jay","contributorId":194834,"corporation":false,"usgs":false,"family":"Ague","given":"Jay","email":"","affiliations":[],"preferred":false,"id":705443,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70155898,"text":"70155898 - 2015 - Estimating population size for Capercaillie (Tetrao urogallus L.) with spatial capture-recapture models based on genotypes from one field sample","interactions":[],"lastModifiedDate":"2015-08-17T10:32:35","indexId":"70155898","displayToPublicDate":"2015-06-18T11:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Estimating population size for Capercaillie (Tetrao urogallus L.) with spatial capture-recapture models based on genotypes from one field sample","docAbstract":"We conducted a survey of an endangered and cryptic forest grouse, the capercaillie Tetrao urogallus, based on droppings collected on two sampling occasions in eight forest fragments in central Switzerland in early spring 2009. We used genetic analyses to sex and individually identify birds. We estimated sex-dependent detection probabilities and population size using a modern spatial capture-recapture (SCR) model for the data from pooled surveys. A total of 127 capercaillie genotypes were identified (77 males, 46 females, and 4 of unknown sex). The SCR model yielded atotal population size estimate (posterior mean) of 137.3 capercaillies (posterior sd 4.2, 95% CRI 130–147). The observed sex ratio was skewed towards males (0.63). The posterior mean of the sex ratio under the SCR model was 0.58 (posterior sd 0.02, 95% CRI 0.54–0.61), suggesting a male-biased sex ratio in our study area. A subsampling simulation study indicated that a reduced sampling effort representing 75% of the actual detections would still yield practically acceptable estimates of total size and sex ratio in our population. Hence, field work and financial effort could be reduced without compromising accuracy when the SCR model is used to estimate key population parameters of cryptic species.
","language":"English","publisher":"Public Library of Science","publisherLocation":"San Francisco, CA","doi":"10.1371/journal.pone.0129020","usgsCitation":"Mollet, P., Kery, M., Gardner, B., Pasinelli, G., and Royle, A., 2015, Estimating population size for Capercaillie (Tetrao urogallus L.) with spatial capture-recapture models based on genotypes from one field sample: PLoS ONE, v. 10, no. 6, p. 1-16, https://doi.org/10.1371/journal.pone.0129020.","productDescription":"16 p.","startPage":"1","endPage":"16","numberOfPages":"16","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065910","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":472006,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0129020","text":"Publisher Index Page"},{"id":306781,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","issue":"6","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2015-06-18","publicationStatus":"PW","scienceBaseUri":"55d305b2e4b0518e35468cf5","contributors":{"authors":[{"text":"Mollet, Pierre","contributorId":146551,"corporation":false,"usgs":false,"family":"Mollet","given":"Pierre","email":"","affiliations":[],"preferred":false,"id":568217,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kery, Marc","contributorId":38680,"corporation":false,"usgs":true,"family":"Kery","given":"Marc","affiliations":[],"preferred":false,"id":568218,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gardner, Beth","contributorId":91612,"corporation":false,"usgs":false,"family":"Gardner","given":"Beth","affiliations":[{"id":13553,"text":"University of Washington-Seattle","active":true,"usgs":false}],"preferred":false,"id":568219,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pasinelli, Gilberto","contributorId":146552,"corporation":false,"usgs":false,"family":"Pasinelli","given":"Gilberto","email":"","affiliations":[],"preferred":false,"id":568220,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":146229,"corporation":false,"usgs":true,"family":"Royle","given":"J. Andrew","email":"aroyle@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":566695,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70155960,"text":"70155960 - 2015 - Landscape genomics of Sphaeralcea ambigua in the Mojave Desert: a multivariate, spatially-explicit approach to guide ecological restoration","interactions":[],"lastModifiedDate":"2015-11-09T11:41:53","indexId":"70155960","displayToPublicDate":"2015-06-18T03:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1324,"text":"Conservation Genetics","active":true,"publicationSubtype":{"id":10}},"title":"Landscape genomics of Sphaeralcea ambigua in the Mojave Desert: a multivariate, spatially-explicit approach to guide ecological restoration","docAbstract":"Local adaptation influences plant species’ responses to climate change and their performance in ecological restoration. Fine-scale physiological or phenological adaptations that direct demographic processes may drive intraspecific variability when baseline environmental conditions change. Landscape genomics characterize adaptive differentiation by identifying environmental drivers of adaptive genetic variability and mapping the associated landscape patterns. We applied such an approach to Sphaeralcea ambigua, an important restoration plant in the arid southwestern United States, by analyzing variation at 153 amplified fragment length polymorphism loci in the context of environmental gradients separating 47 Mojave Desert populations. We identified 37 potentially adaptive loci through a combination of genome scan approaches. We then used a generalized dissimilarity model (GDM) to relate variability in potentially adaptive loci with spatial gradients in temperature, precipitation, and topography. We identified non-linear thresholds in loci frequencies driven by summer maximum temperature and water stress, along with continuous variation corresponding to temperature seasonality. Two GDM-based approaches for mapping predicted patterns of local adaptation are compared. Additionally, we assess uncertainty in spatial interpolations through a novel spatial bootstrapping approach. Our study presents robust, accessible methods for deriving spatially-explicit models of adaptive genetic variability in non-model species that will inform climate change modelling and ecological restoration.
","language":"English","publisher":"Springer","doi":"10.1007/s10592-015-0741-1","usgsCitation":"Shryock, D.F., Havrilla, C.A., DeFalco, L., Esque, T., Custer, N., and Wood, T.E., 2015, Landscape genomics of Sphaeralcea ambigua in the Mojave Desert: a multivariate, spatially-explicit approach to guide ecological restoration: Conservation Genetics, v. 16, no. 6, p. 1303-1317, https://doi.org/10.1007/s10592-015-0741-1.","productDescription":"15 p.","startPage":"1303","endPage":"1317","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-062958","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":306668,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Nevada","otherGeospatial":"Mojave Desert ecogregion","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.14697265625,\n 33.284619968887704\n ],\n [\n -118.14697265625,\n 37.68382032669382\n ],\n [\n -111.81884765624999,\n 37.68382032669382\n ],\n [\n -111.81884765624999,\n 33.284619968887704\n ],\n [\n -118.14697265625,\n 33.284619968887704\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"16","issue":"6","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2015-06-18","publicationStatus":"PW","scienceBaseUri":"55cdbfb7e4b08400b1fe140e","contributors":{"authors":[{"text":"Shryock, Daniel F. dshryock@usgs.gov","contributorId":5139,"corporation":false,"usgs":true,"family":"Shryock","given":"Daniel","email":"dshryock@usgs.gov","middleInitial":"F.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":567428,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Havrilla, Caroline A. 0000-0003-3913-0980","orcid":"https://orcid.org/0000-0003-3913-0980","contributorId":146326,"corporation":false,"usgs":true,"family":"Havrilla","given":"Caroline","email":"","middleInitial":"A.","affiliations":[{"id":16669,"text":"U of CO, Boulder","active":true,"usgs":false},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":false,"id":567429,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DeFalco, Lesley ldefalco@usgs.gov","contributorId":139012,"corporation":false,"usgs":true,"family":"DeFalco","given":"Lesley","email":"ldefalco@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":567427,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Esque, Todd C. tesque@usgs.gov","contributorId":145679,"corporation":false,"usgs":true,"family":"Esque","given":"Todd C.","email":"tesque@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":567430,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Custer, Nathan ncuster@usgs.gov","contributorId":5561,"corporation":false,"usgs":true,"family":"Custer","given":"Nathan","email":"ncuster@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":567431,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wood, Troy E. 0000-0002-1533-5714 twood@usgs.gov","orcid":"https://orcid.org/0000-0002-1533-5714","contributorId":4023,"corporation":false,"usgs":true,"family":"Wood","given":"Troy","email":"twood@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":567432,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70190054,"text":"70190054 - 2015 - Vertical deformation through a complete seismic cycle at Isla Santa María, Chile","interactions":[],"lastModifiedDate":"2021-08-30T16:21:29.619833","indexId":"70190054","displayToPublicDate":"2015-06-18T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2845,"text":"Nature Geoscience","active":true,"publicationSubtype":{"id":10}},"title":"Vertical deformation through a complete seismic cycle at Isla Santa María, Chile","docAbstract":"Individual great earthquakes are posited to release the elastic strain energy that has accumulated over centuries by the gradual movement of tectonic plates1, 2. However, knowledge of plate deformation during a complete seismic cycle—two successive great earthquakes and the intervening interseismic period—remains incomplete3. A complete seismic cycle began in south-central Chile in 1835 with an earthquake of about magnitude 8.5 (refs 4, 5) and ended in 2010 with a magnitude 8.8 earthquake6. During the first earthquake, an uplift of Isla Santa María by 2.4 to 3 m was documented4, 5. In the second earthquake, the island was uplifted7 by 1.8 m. Here we use nautical surveys made in 1804, after the earthquake in 1835 and in 1886, together with modern echo sounder surveys and GPS measurements made immediately before and after the 2010 earthquake, to quantify vertical deformation through the complete seismic cycle. We find that in the period between the two earthquakes, Isla Santa María subsided by about 1.4 m. We simulate the patterns of vertical deformation with a finite-element model and find that they agree broadly with predictions from elastic rebound theory2. However, comparison with geomorphic and geologic records of millennial coastline emergence8, 9 reveal that 10–20% of the vertical uplift could be permanent.
","language":"English","publisher":"Nature","doi":"10.1038/ngeo2468","usgsCitation":"Wesson, R.L., Melnick, D., Cisternas, M., Moreno, M., and Ely, L., 2015, Vertical deformation through a complete seismic cycle at Isla Santa María, Chile: Nature Geoscience, v. 8, p. 547-551, https://doi.org/10.1038/ngeo2468.","productDescription":"5 p.","startPage":"547","endPage":"551","ipdsId":"IP-065712","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":344685,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Chile","otherGeospatial":"Isla Santa María","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.5919189453125,\n -37.092430683283474\n ],\n [\n -73.45046997070312,\n -37.092430683283474\n ],\n [\n -73.45046997070312,\n -36.96251177659819\n ],\n [\n -73.5919189453125,\n -36.96251177659819\n ],\n [\n -73.5919189453125,\n -37.092430683283474\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"8","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-06-22","publicationStatus":"PW","scienceBaseUri":"598acddde4b09fa1cb0e13de","contributors":{"authors":[{"text":"Wesson, Robert L. 0000-0003-2702-0012 rwesson@usgs.gov","orcid":"https://orcid.org/0000-0003-2702-0012","contributorId":850,"corporation":false,"usgs":true,"family":"Wesson","given":"Robert","email":"rwesson@usgs.gov","middleInitial":"L.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":707343,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Melnick, Daniel","contributorId":195525,"corporation":false,"usgs":false,"family":"Melnick","given":"Daniel","email":"","affiliations":[],"preferred":false,"id":707344,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cisternas, Marco","contributorId":195526,"corporation":false,"usgs":false,"family":"Cisternas","given":"Marco","affiliations":[],"preferred":false,"id":707345,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Moreno, Marcos","contributorId":195527,"corporation":false,"usgs":false,"family":"Moreno","given":"Marcos","email":"","affiliations":[],"preferred":false,"id":707346,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ely, Lisa","contributorId":195528,"corporation":false,"usgs":false,"family":"Ely","given":"Lisa","affiliations":[],"preferred":false,"id":707347,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70097572,"text":"sir20105070M - 2015 - Sediment-hosted stratabound copper deposit model","interactions":[],"lastModifiedDate":"2021-08-31T15:26:02.154065","indexId":"sir20105070M","displayToPublicDate":"2015-06-17T15:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2010-5070","chapter":"M","title":"Sediment-hosted stratabound copper deposit model","docAbstract":"This report contains a descriptive model of sediment-hosted stratabound copper (SSC) deposits that supersedes the model of Cox and others (2003). This model is for use in assessments of mineral resource potential. SSC deposits are the second most important sources of copper in the world behind porphyry copper deposits. Around 20 percent of the copper in the world is produced from this class of deposits. They are also the most important sources of cobalt in the world, and they are fourth among classes of ore deposits in production of silver. SSC deposits are the basis of the economies of three countries: Democratic Republic of Congo, Poland, and Zambia. This report provides a description of the key features of SSC deposits; it identifies their tectonic-sedimentary environments; it illustrates geochemical, geophysical, and geoenvironmental characteristics of SSC deposits; it reviews and evaluates hypotheses on how these deposits formed; it presents exploration and assessment guides; and it lists some gaps in our knowledge about the SSC deposits. A summary follows that provides overviews of many subjects concerning SSC deposits.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Mineral deposit model for resource assessment (Scientific Investigations Report 2010-5070)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20105070M","usgsCitation":"Hayes, T.S., Cox, D.P., Bliss, J.D., Piatak, N., and Seal,, R., 2015, Sediment-hosted stratabound copper deposit model: U.S. Geological Survey Scientific Investigations Report 2010-5070, x, 147 p., https://doi.org/10.3133/sir20105070M.","productDescription":"x, 147 p.","startPage":"147","numberOfPages":"161","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-026182","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":301284,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20105070m.jpg"},{"id":301282,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2010/5070/m/"},{"id":301283,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2010/5070/m/pdf/sir2010-5070m.pdf","text":"Report","size":"110 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55828c24e4b023124e8f3fb2","contributors":{"authors":[{"text":"Hayes, Timothy S. thayes@usgs.gov","contributorId":1547,"corporation":false,"usgs":true,"family":"Hayes","given":"Timothy","email":"thayes@usgs.gov","middleInitial":"S.","affiliations":[{"id":662,"text":"Western Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":548836,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cox, Dennis P. dcox@usgs.gov","contributorId":2766,"corporation":false,"usgs":true,"family":"Cox","given":"Dennis","email":"dcox@usgs.gov","middleInitial":"P.","affiliations":[],"preferred":true,"id":548831,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bliss, James D. jbliss@usgs.gov","contributorId":2790,"corporation":false,"usgs":true,"family":"Bliss","given":"James","email":"jbliss@usgs.gov","middleInitial":"D.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":548832,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Piatak, Nadine M. 0000-0002-1973-8537 npiatak@usgs.gov","orcid":"https://orcid.org/0000-0002-1973-8537","contributorId":141203,"corporation":false,"usgs":true,"family":"Piatak","given":"Nadine M.","email":"npiatak@usgs.gov","affiliations":[],"preferred":false,"id":548834,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Seal,, Robert R. II 0000-0003-0901-2529 rseal@usgs.gov","orcid":"https://orcid.org/0000-0003-0901-2529","contributorId":141204,"corporation":false,"usgs":true,"family":"Seal,","given":"Robert R.","suffix":"II","email":"rseal@usgs.gov","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":548835,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70148594,"text":"70148594 - 2015 - A century of oilfield operations and earthquakes in the greater Los Angeles Basin, southern California","interactions":[],"lastModifiedDate":"2015-06-17T11:47:34","indexId":"70148594","displayToPublicDate":"2015-06-17T12:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3568,"text":"The Leading Edge","active":true,"publicationSubtype":{"id":10}},"title":"A century of oilfield operations and earthquakes in the greater Los Angeles Basin, southern California","docAbstract":"Most of the seismicity in the Los Angeles Basin (LA Basin) occurs at depth below the sediments and is caused by transpressional tectonics related to the big bend in the San Andreas fault. However, some of the seismicity could be associated with fluid extraction or injection in oil fields that have been in production for almost a century and cover ∼ 17% of the basin. In a recent study, first the influence of industry operations was evaluated by analyzing seismicity characteristics, including normalized seismicity rates, focal depths, and b-values, but no significant difference was found in seismicity characteristics inside and outside the oil fields. In addition, to identify possible temporal correlations, the seismicity and available monthly fluid extraction and injection volumes since 1977 were analyzed. Second, the production and deformation history of the Wilmington oil field were used to evaluate whether other oil fields are likely to experience similar surface deformation in the future. Third, the maximum earthquake magnitudes of events within the perimeters of the oil fields were analyzed to see whether they correlate with total net injected volumes, as suggested by previous studies. Similarly, maximum magnitudes were examined to see whether they exhibit an increase with net extraction volume. Overall, no obvious previously unidentified induced earthquakes were found, and the management of balanced production and injection of fluids appears to reduce the risk of induced-earthquake activity in the oil fields.
","language":"English","publisher":"Society of Exploration Geophysics","doi":"10.1190/tle34060650.1","usgsCitation":"Hauksson, E., Goebel, T., Ampuero, J., and Cochran, E.S., 2015, A century of oilfield operations and earthquakes in the greater Los Angeles Basin, southern California: The Leading Edge, v. 34, p. 650-656, https://doi.org/10.1190/tle34060650.1.","productDescription":"17 p.","startPage":"650","endPage":"656","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-062978","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":301279,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Los Angeles Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.6083984375,\n 33.62376800118814\n ],\n [\n -118.6083984375,\n 34.1890858311724\n ],\n [\n -117.22412109375,\n 34.1890858311724\n ],\n [\n -117.22412109375,\n 33.62376800118814\n ],\n [\n -118.6083984375,\n 33.62376800118814\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"34","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55828c1ce4b023124e8f3f92","contributors":{"authors":[{"text":"Hauksson, Egill","contributorId":48174,"corporation":false,"usgs":false,"family":"Hauksson","given":"Egill","affiliations":[{"id":27150,"text":"Seismological Laboratory, California Institute of Technology, Pasadena, CA, USA","active":true,"usgs":false}],"preferred":false,"id":548801,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Goebel, Thomas","contributorId":43982,"corporation":false,"usgs":true,"family":"Goebel","given":"Thomas","affiliations":[],"preferred":false,"id":548802,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ampuero, Jean-Paul","contributorId":141194,"corporation":false,"usgs":false,"family":"Ampuero","given":"Jean-Paul","email":"","affiliations":[{"id":13711,"text":"Caltech","active":true,"usgs":false}],"preferred":false,"id":548803,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cochran, Elizabeth S. 0000-0003-2485-4484 ecochran@usgs.gov","orcid":"https://orcid.org/0000-0003-2485-4484","contributorId":2025,"corporation":false,"usgs":true,"family":"Cochran","given":"Elizabeth","email":"ecochran@usgs.gov","middleInitial":"S.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":548800,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70148596,"text":"70148596 - 2015 - Improved rapid magnitude estimation for a community-based, low-cost MEMS accelerometer network","interactions":[],"lastModifiedDate":"2017-01-11T16:10:20","indexId":"70148596","displayToPublicDate":"2015-06-17T12:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Improved rapid magnitude estimation for a community-based, low-cost MEMS accelerometer network","docAbstract":"Immediately following the Mw 7.2 Darfield, New Zealand, earthquake, over 180 Quake‐Catcher Network (QCN) low‐cost micro‐electro‐mechanical systems accelerometers were deployed in the Canterbury region. Using data recorded by this dense network from 2010 to 2013, we significantly improved the QCN rapid magnitude estimation relationship. The previous scaling relationship (Lawrence et al., 2014) did not accurately estimate the magnitudes of nearby (<35 km) events. The new scaling relationship estimates earthquake magnitudes within 1 magnitude unit of the GNS Science GeoNet earthquake catalog magnitudes for 99% of the events tested, within 0.5 magnitude units for 90% of the events, and within 0.25 magnitude units for 57% of the events. These magnitudes are reliably estimated within 3 s of the initial trigger recorded on at least seven stations. In this report, we present the methods used to calculate a new scaling relationship and demonstrate the accuracy of the revised magnitude estimates using a program that is able to retrospectively estimate event magnitudes using archived data.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120140232","usgsCitation":"Chung, A., Cochran, E.S., Kaiser, A.E., Christensen, C.M., Yildirim, B., and Lawrence, J.F., 2015, Improved rapid magnitude estimation for a community-based, low-cost MEMS accelerometer network: Bulletin of the Seismological Society of America, v. 105, no. 3, p. 1314-1323, https://doi.org/10.1785/0120140232.","productDescription":"10 p.","startPage":"1314","endPage":"1323","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-058446","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":301277,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"105","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-05-20","publicationStatus":"PW","scienceBaseUri":"55828c22e4b023124e8f3fa6","contributors":{"authors":[{"text":"Chung, Angela","contributorId":141196,"corporation":false,"usgs":false,"family":"Chung","given":"Angela","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":548810,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cochran, Elizabeth S. 0000-0003-2485-4484 ecochran@usgs.gov","orcid":"https://orcid.org/0000-0003-2485-4484","contributorId":2025,"corporation":false,"usgs":true,"family":"Cochran","given":"Elizabeth","email":"ecochran@usgs.gov","middleInitial":"S.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":548809,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kaiser, Anna E.","contributorId":141200,"corporation":false,"usgs":false,"family":"Kaiser","given":"Anna","email":"","middleInitial":"E.","affiliations":[{"id":6956,"text":"GNS Science/Massey University","active":true,"usgs":false}],"preferred":false,"id":548811,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Christensen, Carl M.","contributorId":141197,"corporation":false,"usgs":false,"family":"Christensen","given":"Carl","email":"","middleInitial":"M.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":548812,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Yildirim, Battalgazi","contributorId":141195,"corporation":false,"usgs":false,"family":"Yildirim","given":"Battalgazi","email":"","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":548813,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lawrence, Jesse F.","contributorId":141198,"corporation":false,"usgs":false,"family":"Lawrence","given":"Jesse","email":"","middleInitial":"F.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":548814,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70148595,"text":"70148595 - 2015 - On the reliability of Quake-Catcher Network earthquake detections","interactions":[],"lastModifiedDate":"2015-06-17T11:41:44","indexId":"70148595","displayToPublicDate":"2015-06-17T12:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"On the reliability of Quake-Catcher Network earthquake detections","docAbstract":"Over the past two decades, there have been several initiatives to create volunteer‐based seismic networks. The Personal Seismic Network, proposed around 1990, used a short‐period seismograph to record earthquake waveforms using existing phone lines (Cranswick and Banfill, 1990; Cranswicket al., 1993). NetQuakes (Luetgert et al., 2010) deploys triaxial Micro‐Electromechanical Systems (MEMS) sensors in private homes, businesses, and public buildings where there is an Internet connection. Other seismic networks using a dense array of low‐cost MEMS sensors are the Community Seismic Network (Clayton et al., 2012; Kohler et al., 2013) and the Home Seismometer Network (Horiuchi et al., 2009). One main advantage of combining low‐cost MEMS sensors and existing Internet connection in public and private buildings over the traditional networks is the reduction in installation and maintenance costs (Koide et al., 2006). In doing so, it is possible to create a dense seismic network for a fraction of the cost of traditional seismic networks (D’Alessandro and D’Anna, 2013; D’Alessandro, 2014; D’Alessandro et al., 2014).
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220140218","usgsCitation":"Yildirim, B., Cochran, E.S., Chung, A., Christensen, C.M., and Lawrence, J.F., 2015, On the reliability of Quake-Catcher Network earthquake detections: Seismological Research Letters, v. 86, p. 856-869, https://doi.org/10.1785/0220140218.","productDescription":"14 p.","startPage":"856","endPage":"869","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060617","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":301278,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"86","edition":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-04-01","publicationStatus":"PW","scienceBaseUri":"55828c23e4b023124e8f3fae","contributors":{"authors":[{"text":"Yildirim, Battalgazi","contributorId":141195,"corporation":false,"usgs":false,"family":"Yildirim","given":"Battalgazi","email":"","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":548805,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cochran, Elizabeth S. 0000-0003-2485-4484 ecochran@usgs.gov","orcid":"https://orcid.org/0000-0003-2485-4484","contributorId":2025,"corporation":false,"usgs":true,"family":"Cochran","given":"Elizabeth","email":"ecochran@usgs.gov","middleInitial":"S.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":548804,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chung, Angela","contributorId":141196,"corporation":false,"usgs":false,"family":"Chung","given":"Angela","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":548806,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Christensen, Carl M.","contributorId":141197,"corporation":false,"usgs":false,"family":"Christensen","given":"Carl","email":"","middleInitial":"M.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":548807,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lawrence, Jesse F.","contributorId":141198,"corporation":false,"usgs":false,"family":"Lawrence","given":"Jesse","email":"","middleInitial":"F.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":548808,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70148577,"text":"70148577 - 2015 - Encapsulating model complexity and landscape-scale analyses of state-and-transition simulation models: an application of ecoinformatics and juniper encroachment in sagebrush steppe ecosystems","interactions":[],"lastModifiedDate":"2015-09-16T09:27:50","indexId":"70148577","displayToPublicDate":"2015-06-17T12:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3893,"text":"AIMS Environmental Science","active":true,"publicationSubtype":{"id":10}},"title":"Encapsulating model complexity and landscape-scale analyses of state-and-transition simulation models: an application of ecoinformatics and juniper encroachment in sagebrush steppe ecosystems","docAbstract":"State-and-transition simulation modeling relies on knowledge of vegetation composition and structure (states) that describe community conditions, mechanistic feedbacks such as fire that can affect vegetation establishment, and ecological processes that drive community conditions as well as the transitions between these states. However, as the need for modeling larger and more complex landscapes increase, a more advanced awareness of computing resources becomes essential. The objectives of this study include identifying challenges of executing state-and-transition simulation models, identifying common bottlenecks of computing resources, developing a workflow and software that enable parallel processing of Monte Carlo simulations, and identifying the advantages and disadvantages of different computing resources. To address these objectives, this study used the ApexRMS® SyncroSim software and embarrassingly parallel tasks of Monte Carlo simulations on a single multicore computer and on distributed computing systems. The results demonstrated that state-and-transition simulation models scale best in distributed computing environments, such as high-throughput and high-performance computing, because these environments disseminate the workloads across many compute nodes, thereby supporting analysis of larger landscapes, higher spatial resolution vegetation products, and more complex models. Using a case study and five different computing environments, the top result (high-throughput computing versus serial computations) indicated an approximate 96.6% decrease of computing time. With a single, multicore compute node (bottom result), the computing time indicated an 81.8% decrease relative to using serial computations. These results provide insight into the tradeoffs of using different computing resources when research necessitates advanced integration of ecoinformatics incorporating large and complicated data inputs and models. - See more at: http://aimspress.com/aimses/ch/reader/view_abstract.aspx?file_no=Environ2015030&flag=1#sthash.p1XKDtF8.dpuf
","language":"English","publisher":"AIMS Press","doi":"10.3934/environsci.2015.3.464","usgsCitation":"O’Donnell, M.S., 2015, Encapsulating model complexity and landscape-scale analyses of state-and-transition simulation models: an application of ecoinformatics and juniper encroachment in sagebrush steppe ecosystems: AIMS Environmental Science, v. 2, no. 3, p. 464-493, https://doi.org/10.3934/environsci.2015.3.464.","productDescription":"30 p.","startPage":"464","endPage":"493","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-062986","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":472008,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3934/environsci.2015.3.464","text":"Publisher Index Page"},{"id":301276,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"2","issue":"3","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55828c21e4b023124e8f3fa0","contributors":{"authors":[{"text":"O’Donnell, Michael S. 0000-0002-3488-003X odonnellm@usgs.gov","orcid":"https://orcid.org/0000-0002-3488-003X","contributorId":140876,"corporation":false,"usgs":true,"family":"O’Donnell","given":"Michael","email":"odonnellm@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":548708,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70148590,"text":"70148590 - 2015 - Nest-site selection and reproductive success of greater sage-grouse in a fire-affected habitat of northwestern Nevada","interactions":[],"lastModifiedDate":"2016-04-13T12:38:01","indexId":"70148590","displayToPublicDate":"2015-06-17T12:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Nest-site selection and reproductive success of greater sage-grouse in a fire-affected habitat of northwestern Nevada","docAbstract":"Identifying links between micro-habitat selection and wildlife reproduction is imperative to population persistence and recovery. This information is particularly important for landscape species such as greater sage-grouse (Centrocercus urophasianus; sage-grouse). Although this species has been widely studied, because environmental factors can affect sage-grouse populations, local and regional studies are crucial for developing viable conservation strategies. We studied the habitat-use patterns of 71 radio-marked sage-grouse inhabiting an area affected by wildfire in the Virginia Mountains of northwestern Nevada during 2009–2011 to determine the effect of micro-habitat attributes on reproductive success. We measured standard vegetation parameters at nest and random sites using a multi-scale approach (range = 0.01–15,527 ha). We used an information-theoretic modeling approach to identify environmental factors influencing nest-site selection and survival, and determine whether nest survival was a function of resource selection. Sage-grouse selected micro-sites with greater shrub canopy cover and less cheatgrass (Bromus tectorum) cover than random sites. Total shrub canopy, including sagebrush (Artemisia spp.) and other shrub species, at small spatial scales (0.8 ha and 3.1 ha) was the single contributing selection factor to higher nest survival. These results indicate that reducing the risk of wildfire to maintain important sagebrush habitats could be emphasized in sage-grouse conservation strategies in Nevada. Managers may seek to mitigate the influx of annual grass invasion by preserving large intact sagebrush-dominated stands with a mixture of other shrub species. For this area of Nevada, the results suggest that ≥40% total shrub canopy cover in sage-grouse nesting areas could yield improved reproductive success.
","language":"English","publisher":"Wildlife Society","doi":"10.1002/jwmg.899","usgsCitation":"Lockyer, Z.B., Coates, P.S., Casazza, M.L., Espinosa, S., and Delehanty, D., 2015, Nest-site selection and reproductive success of greater sage-grouse in a fire-affected habitat of northwestern Nevada: Journal of Wildlife Management, v. 79, no. 5, p. 785-797, https://doi.org/10.1002/jwmg.899.","productDescription":"13 p.","startPage":"785","endPage":"797","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-043230","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":301275,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada","otherGeospatial":"Virginia Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.56558227539062,\n 39.90973623453719\n ],\n [\n -119.65484619140625,\n 39.86231722624386\n ],\n [\n -119.77157592773436,\n 39.94238358098156\n ],\n [\n -119.79629516601562,\n 39.929747745342944\n ],\n [\n -119.73999023437499,\n 39.871803651624425\n ],\n [\n -119.77981567382812,\n 39.83174093314558\n ],\n [\n -119.81689453125,\n 39.83490462943255\n ],\n [\n -119.86495971679686,\n 39.85388374694187\n ],\n [\n -119.90203857421875,\n 39.9034155951341\n ],\n [\n -119.94873046875,\n 40.01814959351699\n ],\n [\n -119.99954223632812,\n 40.02025300564682\n ],\n [\n -120.00091552734375,\n 40.134790883048524\n ],\n [\n -119.9542236328125,\n 40.13269100586688\n ],\n [\n -119.9542236328125,\n 40.110638378278054\n ],\n [\n -119.90203857421875,\n 40.094882122321174\n ],\n [\n -119.86495971679686,\n 40.110638378278054\n ],\n [\n -119.85946655273438,\n 40.13584079730779\n ],\n [\n -119.81964111328124,\n 40.14633904771964\n ],\n [\n -119.83612060546874,\n 40.22921818870117\n ],\n [\n -119.75921630859374,\n 40.23446029614241\n ],\n [\n -119.6685791015625,\n 39.98448618198461\n ],\n [\n -119.56558227539062,\n 39.90973623453719\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"79","issue":"5","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2015-06-01","publicationStatus":"PW","scienceBaseUri":"55828c22e4b023124e8f3faa","contributors":{"authors":[{"text":"Lockyer, Zachary B.","contributorId":91614,"corporation":false,"usgs":true,"family":"Lockyer","given":"Zachary","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":548780,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coates, Peter S. 0000-0003-2672-9994 pcoates@usgs.gov","orcid":"https://orcid.org/0000-0003-2672-9994","contributorId":3263,"corporation":false,"usgs":true,"family":"Coates","given":"Peter","email":"pcoates@usgs.gov","middleInitial":"S.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":548781,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Casazza, Michael L. 0000-0002-5636-735X mike_casazza@usgs.gov","orcid":"https://orcid.org/0000-0002-5636-735X","contributorId":2091,"corporation":false,"usgs":true,"family":"Casazza","given":"Michael","email":"mike_casazza@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":548779,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Espinosa, Shawn","contributorId":20253,"corporation":false,"usgs":true,"family":"Espinosa","given":"Shawn","affiliations":[],"preferred":false,"id":548782,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Delehanty, David J.","contributorId":86683,"corporation":false,"usgs":true,"family":"Delehanty","given":"David J.","affiliations":[],"preferred":false,"id":548783,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70148593,"text":"70148593 - 2015 - Weathering and transport of chromium and nickel from serpentinite in the Coast Range ophiolite to the Sacramento Valley, California, USA","interactions":[],"lastModifiedDate":"2015-06-17T11:06:53","indexId":"70148593","displayToPublicDate":"2015-06-17T12:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":835,"text":"Applied Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Weathering and transport of chromium and nickel from serpentinite in the Coast Range ophiolite to the Sacramento Valley, California, USA","docAbstract":"A soil geochemical study in northern California was done to investigate the role that weathering and transport play in the regional distribution and mobility of geogenic Cr and Ni, which are both potentially toxic and carcinogenic. These elements are enriched in ultramafic rocks (primarily serpentinite) and the soils derived from them (1700–10,000 mg Cr per kg soil and 1300–3900 mg Ni per kg soil) in the Coast Range ophiolite. Chromium and Ni have been transported eastward from the Coast Range into the western Sacramento Valley and as a result, valley soil is enriched in Cr (80–1420 mg kg−1) and Ni (65–224 mg kg−1) compared to median values of U.S. soils of 50 and 15 mg kg−1, respectively. Nickel in ultramafic source rocks and soils is present in serpentine minerals (lizardite, antigorite, and chrysotile) and is more easily weathered compared to Cr, which primarily resides in highly refractory chromite ([Mg,Fe2+][Cr3+,Al,Fe3+]2O4). Although the majority of Cr and Ni in soils are in refractory chromite and serpentine minerals, the etching and dissolution of these minerals, presence of Cr- and Ni-enriched clay minerals and development of nanocrystalline Fe (hydr)oxides is evidence that a significant fractions of these elements have been transferred to potentially more labile phases.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.apgeochem.2015.05.018","usgsCitation":"Morrison, J.M., Goldhaber, M.B., Mills, C., Breit, G.N., Hooper, R.L., Holloway, J.M., Diehl, S.F., and Ranville, J.F., 2015, Weathering and transport of chromium and nickel from serpentinite in the Coast Range ophiolite to the Sacramento Valley, California, USA: Applied Geochemistry, v. 62, p. 72-86, https://doi.org/10.1016/j.apgeochem.2015.05.018.","productDescription":"15 p.","startPage":"72","endPage":"86","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-033273","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":301274,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": 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Although there are reports of sightings of mountain lions or observations of mountain lion sign, most have not been verified by photographs or physical samples. Beginning in 2010, we conducted a pilot study of mountain lions in Marin County using motion-triggered cameras. Our objectives were to obtain additional documentations, confirm the presence of mountain lions outside of Point Reyes National Seashore, and determine if mountain lions had a regular presence in the county.
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The most important overall discriminators for the minor and trace element chemistry of magnetite from the investigated porphyry and skarn deposits are Mg, Al, Ti, V, Mn, Co, Zn, and Ga—of these the elements with the highest variance for (I) igneous magnetite are Mg, Al, Ti, V, Mn, Zn, for (II) hydrothermal porphyry magnetite are Mg, Ti, V, Mn, Co, Zn, and for (III) hydrothermal skarn magnetite are Mg, Ti, Mn, Zn, and Ga. Nickel could only be detected at levels above the limit of reporting (LOR) in two igneous magnetites. Equally, Cr could only be detected in one igneous occurrence. Copper, As, Mo, Ag, Au, and Pb have been reported in magnetite by other authors but could not be detected at levels greater than their respective LORs in our samples. Comparison with the chemical signature of igneous magnetite from the barren Inner Zone Batholith, Japan, suggests that V, Mn, Co, and Ga concentrations are relatively depleted in magnetite from the porphyry and skarn deposits. Higher formation conditions in combination with distinct differences between melt and hydrothermal fluid compositions are reflected in Al, Ti, V, and Ga concentrations that are, on average, higher in igneous magnetite than in hydrothermal magnetite (including porphyry and skarn magnetite). Low Ti and V concentrations in combination with high Mn concentrations are characteristic features of magnetite from skarn deposits. High Mg concentrations (<1,000 ppm) are characteristic for magnetite from magnesian skarn and likely reflect extensive fluid/rock interaction. In porphyry deposits, hydrothermal magnetite from different vein types can be distinguished by varying Ti, V, Mn, and Zn contents. Titanium and V concentrations are highly variable among hydrothermal and igneous magnetites, but Ti concentrations above 3,560 ppm could only be detected in igneous magnetite, and V concentrations are on average lower in hydrothermal magnetite. The highest Ti concentrations are present in igneous magnetite from gabbro and monzonite. The lowest Ti concentrations were recorded in igneous magnetite from granodiorite and granodiorite breccia and largely overlap with Ti concentrations found in hydrothermal porphyry magnetite. Magnesium and Mn concentrations vary between magnetite from different skarn deposits but are generally greater than in hydrothermal magnetite from the porphyry deposits. High Mg, and low Ti and V concentrations characterize hydrothermal magnetite from magnesian skarn deposits and follow a trend that indicates that magnetite from skarn (calcic and magnesian) commonly has low Ti and V concentrations.
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