In January 2016, the Secretary of the U.S. Department of the Interior tasked the U.S. Geological Survey (USGS) with producing a publicly available and annually updated database of estimated greenhouse gas emissions associated with the extraction and use (predominantly some form of combustion) of fossil fuels from Federal lands. In response, the USGS has produced estimates of the greenhouse gas emissions resulting from the extraction and end-use combustion of fossil fuels produced on Federal lands in the United States, as well as estimates of ecosystem carbon emissions and sequestration on those lands. American Indian and Tribal lands were not included in this analysis. The emissions estimates span a 10-year period (2005–14) and are reported for 28 States and two offshore areas. Nationwide emissions from fossil fuels produced on Federal lands in 2014 were 1,279.0 million metric tons of carbon dioxide equivalent (MMT CO2 Eq.) for carbon dioxide (CO2), 47.6 MMT CO2 Eq. for methane (CH4), and 5.5 MMT CO2 Eq. for nitrous oxide (N2O). Compared to 2005, the 2014 totals represent decreases in emissions for all three greenhouse gases (decreases of 6.1 percent for CO2, 10.5 percent for CH4, and 20.3 percent for N2O). Emissions from fossil fuels produced on Federal lands represent, on average, 23.7 percent of national emissions for CO2, 7.3 percent for CH4, and 1.5 percent for N2O over the 10 years included in this estimate.
In 2005, Federal lands of the conterminous United States stored 82,289 MMT CO2 Eq. in terrestrial ecosystems. By 2014, carbon storage, or sequestration, was estimated at 83,600 MMT CO2 Eq., representing an increase of 1.6 percent, or 1,311 MMT CO2 Eq. Soils stored most of the ecosystem carbon (63 percent), followed by live vegetation (26 percent) and dead organic matter (11 percent). The rate of net carbon uptake in ecosystems ranged from a sink (sequestration) of 475 million metric tons of carbon dioxide per year (MMT CO2 Eq./yr) to a source (emission) of 51 MMT CO2 Eq./yr because of annual variability in climate and weather, rates of land-use and land-cover change, and wildfire frequency, among other factors. At the national level, the USGS estimates that terrestrial ecosystems (forests, grasslands, and shrublands) on Federal lands sequestered an average of 195 MMT CO2 Eq./yr between 2005 and 2014, offsetting approximately 15 percent of the CO2 emissions resulting from the extraction of fossil fuels on Federal lands and their end-use combustion.
The USGS estimates presented in this report represent a first-of-its-kind accounting for the emissions resulting from fossil fuel extraction on Federal lands and the end-use combustion of those fuels, as well as for the sequestration of carbon in terrestrial ecosystems on Federal lands. The net CO2 emissions estimate, which is the difference between the emitted and sequestered CO2, provides an informative combined result describing the emissions (fossil fuel extraction and end-use combustion) associated with a State’s Federal lands and sequestration on those same lands. The estimates included in this report can provide context for future energy decisions, as well as a basis to track change in the future.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185131","usgsCitation":"Merrill, M.D., Sleeter, B.M., Freeman, P.A., Liu, J., Warwick, P.D., and Reed, B.C., 2018, Federal lands greenhouse emissions and sequestration in the United States—Estimates for 2005–14: U.S. Geological Survey Scientific Investigations Report 2018–5131, 31 p., https://doi.org/10.3133/sir20185131.","productDescription":"Report: viii, 31 p.; Data Release","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-095255","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":437674,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7KH0MK4","text":"USGS data release","linkHelpText":"Federal Lands Greenhouse Gas Emissions and Sequestration in the United States: Estimates 2005-14 - Data Release"},{"id":359542,"rank":4,"type":{"id":18,"text":"Project 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U.S. Geological Survey
956 National Center
12201 Sunrise Valley Drive
Reston, VA 20192
The geologic map of the northern half of the Lake Walcott 30ʹ×60ʹ quadrangle shows the volcanic geology of the southern part of the Craters of the Moon lava field, the complex geologic features of the Holocene Kings Bowl and Wapi lava fields, and the southern part of the Great Rift volcanic rift zone. The long extent and distribution of skylights in lava-tube systems of the Horse Butte and Wapi Park lava fields are depicted on this map. 40Ar/39Ar and K/Ar age determinations give detail to the Holocene, late Pleistocene, and late middle Pleistocene volcanic lava fields in this quadrangle. Most of the younger basalt eruptions (less than 150 thousand years [ka]) have occurred along the Great Rift volcanic rift zone, but two of the younger lava fields are located in the western part of the quadrangle. Kimama Butte, a shield volcano, is 87±11 ka, and Shale Butte is dated at 11±6 ka. Paleomagnetic studies have shown that the Horse Butte-Inferno Chasm eruptive fissure system has at least five paleomagnetic-correlative lava fields, the Claasen vent complex consists of at least seven correlative lava fields, and the Streifling-Flat Top vent complex includes at least four correlative lava fields.
This map provides geologic, geochronologic, and paleomagnetic data for Holocene lava fields along the southern part of the Great Rift, and for late Pleistocene and late middle Pleistocene lava fields in the central and western parts of the quadrangle. These data can contribute to wise management and preservation of the Craters of the Moon National Monument and for broad-scale understanding of the basaltic-volcanic evolution of the eastern Snake River Plain.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3405","collaboration":"Prepared in cooperation with the National Park Service and the Bureau of Land Management","usgsCitation":"Kuntz, M.A., Champion, D.E., Turrin, B.R., Gans, P.B., Covington, H.R., and VanSistine, D.P., 2018, Geologic map of the north half of the Lake Walcott 30'×60' quadrangle, Idaho: U.S. Geological Survey Scientific Investigations Report 3405, pamphlet 25 p., scale 1:100,000, https://doi.org/10.3133/sim3405.","productDescription":"Report: v, 25 p.; Sheet: 49.75 x 34.00 inches; Read Me; Data Release","onlineOnly":"Y","ipdsId":"IP-084554","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":358860,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3405/sim3405_sheet_georeferenced.pdf","text":"Map","size":"75.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3405 Hillshaded Map"},{"id":358861,"rank":3,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sim/3405/sim3405_Readme.txt","text":"Read Me","size":"8.00 KB","linkFileType":{"id":2,"text":"txt"},"description":"SIM 3405 Read Me"},{"id":358862,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7VQ30VZ","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Data Release for Geologic Map of the north half of the Lake Walcott 30' x 60' Quadrangle, Idaho"},{"id":359523,"rank":5,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3405/sim3405_pamphlet.pdf","text":"Report","size":"5.62 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3405 Pamphlet"},{"id":358856,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3405/coverthb2.jpg"}],"country":"United States","state":"Idaho","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114,\n 42.75\n ],\n [\n -113,\n 42.75\n ],\n [\n -113,\n 43\n ],\n [\n -114,\n 43\n ],\n [\n -114,\n 42.75\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Geosciences and Environmental Change Science Center
U.S. Geological Survey
Box 25046, MS-980
Denver, CO 80225-0046
Sediment transport past rocky headlands has received less attention compared to transport along beaches. Here we explore, in a field-based study, possible pathways for sediment movement adjacent to Point Dume, a headland in Santa Monica Bay, California. This prominent shoreline feature is a nearly symmetrical, triangular-shaped promontory interior to the Santa Monica Littoral Cell. We collected current, wave, and turbidity data for 74 days during which several wave events occurred, including one associated with a remote hurricane and another generated by the first winter storm of 2014. We also acquired sediment samples to quantify seabed grain-size distributions. Near-bottom currents towards the headland dominated on both of its sides and wave-driven longshore currents in the surf zone were faster on the exposed side. Bed shear stresseswere generated mostly by waves with minor contributions from currents, but both wave-driven and other currents contributed to sediment flux. On the wave-exposed west side of the headland, suspended sediment concentrations correlated with bed stress suggesting local resuspension whereas turbidity levels on the sheltered east side of the headland are more easily explained by advective delivery. Most of the suspended sediment appears to be exported offshore due to flow separation at the apex of the headland but may not move far given that sediment fluxes at moorings offshore of the apex were small. Further, wave-driven sediment flux in the surf zone is unlikely to pass the headland due to the discontinuity in wave forcing that causes longshore transport in different directions on each side of the headland. It is thus unlikely that sand is transported past the headland (specifically in a westerly direction), although some transport of finer fractions may occur offshore in deep water. These findings of minimal sediment flux past Point Dume are consistent with its role as a littoral cell boundary, although more complex multi-stage processes and unusual events may account for some transport at times.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.csr.2018.10.011","usgsCitation":"George, D.A., Largier, J.L., Storlazzi, C.D., Robart, M.J., and Gaylord, B., 2018, Currents, waves and sediment transport around the headland of Pt. Dume, California: Continental Shelf Research, v. 171, p. 63-76, https://doi.org/10.1016/j.csr.2018.10.011.","productDescription":"14 p.","startPage":"63","endPage":"76","ipdsId":"IP-091841","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":468242,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.csr.2018.10.011","text":"Publisher Index Page"},{"id":359531,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Pt. Dume","volume":"171","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5befe5b9e4b045bfcadf7f26","contributors":{"authors":[{"text":"George, Douglas A.","contributorId":60328,"corporation":false,"usgs":true,"family":"George","given":"Douglas","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":751417,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Largier, John L.","contributorId":175121,"corporation":false,"usgs":false,"family":"Largier","given":"John","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":751418,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Storlazzi, Curt D. 0000-0001-8057-4490 cstorlazzi@usgs.gov","orcid":"https://orcid.org/0000-0001-8057-4490","contributorId":140584,"corporation":false,"usgs":true,"family":"Storlazzi","given":"Curt","email":"cstorlazzi@usgs.gov","middleInitial":"D.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":751416,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Robart, Matthew J.","contributorId":210665,"corporation":false,"usgs":false,"family":"Robart","given":"Matthew","email":"","middleInitial":"J.","affiliations":[{"id":38129,"text":"UCD/BML","active":true,"usgs":false}],"preferred":false,"id":751419,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gaylord, Brian","contributorId":210666,"corporation":false,"usgs":false,"family":"Gaylord","given":"Brian","email":"","affiliations":[{"id":38129,"text":"UCD/BML","active":true,"usgs":false}],"preferred":false,"id":751420,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70200902,"text":"70200902 - 2018 - Two-event lode-ore deposition at Butte, USA: 40Ar/39Ar and U-Pb documentation of Ag-Au-polymetallic lodes overprinted by younger stockwork Cu-Mo ores and penecontemporaneous Cu lodes","interactions":[],"lastModifiedDate":"2018-11-14T15:13:05","indexId":"70200902","displayToPublicDate":"2018-11-14T15:12:47","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2954,"text":"Ore Geology Reviews","active":true,"publicationSubtype":{"id":10}},"title":"Two-event lode-ore deposition at Butte, USA: 40Ar/39Ar and U-Pb documentation of Ag-Au-polymetallic lodes overprinted by younger stockwork Cu-Mo ores and penecontemporaneous Cu lodes","docAbstract":"The ore-genesis model for world-class deposits of the Butte mining district, Montana, USA, is deep pre-Main Stage porphyry Cu-Mo and overlying Main Stage Ag-Zn-Cu zoned-lode deposits, both of which formed from hydrothermal fluids driven by minor volumes of rhyolitic magma. The lode-specific model is that hydrothermal processes diminished in intensity outward from district center along lode veins, synchronously forming metal zones. The accepted models are controverted by new geologic and multi-method geochronologic studies.
The new data reveal the following sequence of events: (1) Thermal study of country rock indicates that the 76.9-Ma Butte Granite cooled to 350–400 °C by 4 m.y. after emplacement. (2) Five quartz porphyry rhyolite dikes were emplaced at 67–65 Ma and another at 60 Ma (SHRIMP U-Pb) into the cooled Butte Granite without resetting 40Ar/39Ar ages in country rock. (3) Fifty-eight white mica and K-feldspar samples from alteration envelopes adjacent to Ag-Au-polymetallic lodes in outer parts of the district, Zn-rich lodes in intermediate parts, and Cu-rich lodes in the district center yield 40Ar/39Ar ages of 73–70 Ma for Ag-rich lodes, 65–64 Ma for Cu-rich lodes, and complex age spectra of 69–65 Ma for Zn-rich lodes.
The data show that Ag-Au-polymetallic lodes occupied cross-district fractures by about 73 Ma, forming the greater Butte mining district. At 67–65 Ma, minor quartz porphyry dikes were emplaced into central and eastern parts of the rejuvenated fracture system but without evidence of related cupola or volcanic rocks or of thermal disturbance in the country rock. At 64.5 Ma, overlapping hydrothermal cells formed two stockwork Cu-Mo domes in deep parts of the fracture system. At 65–64 Ma and closely related to late-stage stockwork Cu-Mo activity, a penecontemporaneous hydrothermal pulse formed a high-sulfidation hydrothermal plume that (1) utilized the large re-opened fractures to cannibalize and remobilize Cu from autologous, stockwork, and older Ag-Au-polymetallic lodes, (2) deposited the rich, high-sulfidation Cu lodes, and (3) mobilized metals from early Ag-Au-polymetallic veins in middle parts of the district, transported the metals outward and redeposited them, enriching early veins, especially in the intermediate Zn plus Cu areas.
Metals zones in lodes of the Butte district are the result of an intensely focused, Cu-rich hydrothermal plume that variably reworked the center of significantly larger, 10 m.y. older, Ag-Au-polymetallic lodes.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.oregeorev.2018.05.018","usgsCitation":"Lund, K., McAleer, R., Aleinikoff, J.N., Cosca, M.A., and Kunk, M.J., 2018, Two-event lode-ore deposition at Butte, USA: 40Ar/39Ar and U-Pb documentation of Ag-Au-polymetallic lodes overprinted by younger stockwork Cu-Mo ores and penecontemporaneous Cu lodes: Ore Geology Reviews, v. 102, p. 666-700, https://doi.org/10.1016/j.oregeorev.2018.05.018.","productDescription":"35 p.","startPage":"666","endPage":"700","ipdsId":"IP-087572","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":359430,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","city":"Butte","volume":"102","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5bed4270e4b0b3fc5cf91c70","contributors":{"authors":[{"text":"Lund, Karen 0000-0002-4249-3582 klund@usgs.gov","orcid":"https://orcid.org/0000-0002-4249-3582","contributorId":1235,"corporation":false,"usgs":true,"family":"Lund","given":"Karen","email":"klund@usgs.gov","affiliations":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":751253,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McAleer, Ryan J. 0000-0003-3801-7441 rmcaleer@usgs.gov","orcid":"https://orcid.org/0000-0003-3801-7441","contributorId":5301,"corporation":false,"usgs":true,"family":"McAleer","given":"Ryan J.","email":"rmcaleer@usgs.gov","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":false,"id":751254,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Aleinikoff, John N. 0000-0003-3494-6841 jaleinikoff@usgs.gov","orcid":"https://orcid.org/0000-0003-3494-6841","contributorId":1478,"corporation":false,"usgs":true,"family":"Aleinikoff","given":"John","email":"jaleinikoff@usgs.gov","middleInitial":"N.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":751255,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cosca, Michael A. 0000-0002-0600-7663 mcosca@usgs.gov","orcid":"https://orcid.org/0000-0002-0600-7663","contributorId":1000,"corporation":false,"usgs":true,"family":"Cosca","given":"Michael","email":"mcosca@usgs.gov","middleInitial":"A.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":751256,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kunk, Michael J. 0000-0003-4424-7825 mkunk@usgs.gov","orcid":"https://orcid.org/0000-0003-4424-7825","contributorId":200968,"corporation":false,"usgs":true,"family":"Kunk","given":"Michael","email":"mkunk@usgs.gov","middleInitial":"J.","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":751257,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70196840,"text":"sim3399 - 2018 - Geologic map of the Fort Collins 30'×60' quadrangle, Larimer and Jackson Counties, Colorado, and Albany and Laramie Counties, Wyoming","interactions":[],"lastModifiedDate":"2018-11-19T14:01:35","indexId":"sim3399","displayToPublicDate":"2018-11-08T10:30:00","publicationYear":"2018","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":"3399","displayTitle":"Geologic Map of the Fort Collins 30'×60' quadrangle, Larimer and Jackson Counties, Colorado, and Albany and Laramie Counties, Wyoming","title":"Geologic map of the Fort Collins 30'×60' quadrangle, Larimer and Jackson Counties, Colorado, and Albany and Laramie Counties, Wyoming","docAbstract":"The rocks and landforms of the Fort Collins 30′ × 60′ 1:100,000-scale U.S. Geological Survey quadrangle reveals a particularly complete record of geologic history in the northern Front Range of Colorado. The Proterozoic basement rocks exposed in the core of the range preserve evidence of Paleoproterozoic marine sedimentation, volcanism, and regional soft-sediment deformation, followed by regional folding and gradational metamorphism. Mesoproterozoic time was marked by intrusion of the Berthoud Plutonic Suite into crust that was structurally neutral or moderately extending in an east-northeast direction.
Evidence of the late Paleozoic Anasazi uplift (Ancestral Rocky Mountains uplift) within the quadrangle is recorded by removal of Permian and older sediments and deposition of proximal Pennsylvanian and Permian strata unconformably onto the exhumed Proterozoic basement rocks. The Phanerozoic sediments indicate a steady progression of fluvial, eolian, and lacustrine environments throughout most of the Mesozoic Era which was a time of relatively slow sediment accumulation. Early Cretaceous time was marked by incursion of the Cretaceous Western Interior Seaway, a shallow-water marine embayment that persisted throughout the latter part of the Mesozoic Era. Sedimentation rates increased significantly in the latter part of this period during down-warping related to distant crustal loading by thrusting along the western continental margin.
With onset of the Laramide orogeny in latest Cretaceous time, mountain building resumed in this region. This deformation placed Proterozoic rock over Cretaceous and Paleocene strata along the western margin of the Front Range and Medicine Bow Mountains. Post-Laramide time was marked by a prolonged period of weathering, erosion, and planation of the basement-rock surface, extending perhaps into late Oligocene or early Miocene time.
Erosion on the eastern slope of the Front Range in late Paleogene to early Neogene time produced a broad, rolling surface surrounding residual highlands and east-trending fluvial channels filled with coarse, boulder gravel.
Significant global cooling during the Pliocene led to glaciation during the Quaternary. In the Rocky Mountain region, renewed uplift allowed erosion to accentuate the topographic relief across the high mountains of the map area and established the elevations necessary to trigger accumulation of persistent snow and ice. Mountain glaciers advanced and retreated during at least three glacial-interglacial cycles during the middle and late Pleistocene in this area.
Erosion continues to this day on the High Plains east of the mountain front, and progressive incision of the drainage is recorded by at least five major gravel-clad terrace and pediment surfaces along the major fluvial channels that connect to the South Platte River system.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3399","usgsCitation":"Workman, J.B., Cole, J.C., Shroba, R.R., Kellogg, K.S., and Premo, W.R., 2018, Geologic map of the Fort Collins 30'×60' quadrangle, Larimer and Jackson Counties, Colorado, and Albany and Laramie Counties, Wyoming: U.S. Geological Survey Scientific Investigations Map 3399, pamphlet 83 p., scale 1:100,000, https://doi.org/10.3133/sim3399/.","productDescription":"Report: vii, 83 p.; 2 Maps: 59.0 x 38.5 inches; Data Release; Read Me","onlineOnly":"Y","ipdsId":"IP-078484","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":359260,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7G44PHV","text":"USGS data release","linkHelpText":"Data release for geologic map of the Fort Collins 30' x 60' quadrangle, Larimer and Jackson Counties, Colorado and Albany and Laramie Counties, Wyoming"},{"id":359258,"rank":4,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3399/sim3399_sheet_georeferenced.pdf","text":"Georeferenced Map","size":"59.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3399 Georeferenced Map"},{"id":359257,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3399/sim3399_sheet.pdf","text":"Map","size":"57.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3399 Map"},{"id":359259,"rank":5,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sim/3399/sim3399_Readme.txt","text":"Read Me","size":"8.0 kB","linkFileType":{"id":2,"text":"txt"},"description":"SIM 3399 Read Me"},{"id":359255,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3399/coverthb2.jpg"},{"id":359256,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3399/sim3399_pamphlet.pdf","text":"Report","size":"19.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3399 Pamphlet"}],"country":"United States","state":"Colorado, Wyoming","county":"Albany County, Jackson County, Laramie County, Larimer County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106,\n 40.5\n ],\n [\n -105,\n 40.5\n ],\n [\n -105,\n 41\n ],\n [\n -106,\n 41\n ],\n [\n -106,\n 40.5\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Geosciences and Environmental Change Science Center
U.S. Geological Survey
Box 25046, MS-980
Denver, CO 80225-0046
Wind and other energy development are expanding rapidly and on an unprecedented scale within the range of the Golden Eagle (Aquila chrysaetos) while other anthropogenic-related changes, wildfires, invasive plants, drought, and climate change are altering or destroying native habitats occupied by Golden Eagles. However, the potential effects of these factors on North American Golden Eagle populations are largely unknown and the most recent evidence indicates that the population in the western United States is declining slightly. Impediments to evaluating the potential effects of energy development projects on wintering Golden Eagles include issues of scale and a paucity of available information about eagle winter use areas and ecology. We applied a predictive model of eagle winter distribution developed for Idaho and Montana, to Idaho, Utah, Nevada and eastern Oregon to help identify potential wintering areas and identify risks that occur in those areas. The model identifies ~40% of the four state study area as potentially suitable eagle winter habitat and provides a basis for spatial assessment of possible risk factors to eagles wintering there. We used eBird and Christmas Bird Count citizen science datasets for an independent evaluation of the accuracy of our predictive distribution model. The model was robust, accurately predicting the presence of wintering Golden Eagles significantly more often than expected. We used digital environmental datasets (layers) of potential risk factors, in conjunction with model predicted eagle distribution, to better understand and estimate the extent of risks to the wintering eagle population in the study area. These layers represent available data for some of the factors previously identified as risks in the landscape to wintering Golden Eagles. The majority of predicted eagle wintering areas occurred where there was little habitat fragmentation (<10%). All predicted winter areas contained at least one potential risk factor (e.g., potential for energy development); 39.4% of predicted winter areas contained at least two known risk factors. The greatest number of risks often occurred where the human footprint was highest and where eagles were less likely to occur during winter. Our results can be used to help prioritize field surveys for identifying important Golden Eagle winter areas in the western United States and determine potential locations where energy development is least likely to have negative effects on wintering eagles. Survey efforts can be allocated in consideration of management and conservation objectives based on predicted habitat suitability and risk factors. For example, surveys for areas of high suitability and low risk can identify places to focus management for conservation of eagle winter areas. Further, sites proposed for wind energy development could be reviewed initially based on model predicted eagle wintering areas and then surveyed to determine if permitting for development is appropriate.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Machine learning for ecology and sustainable natural resource management","language":"English","publisher":"Springer","doi":"10.1007/978-3-319-96978-7_19","usgsCitation":"Craig, E.H., Fuller, M.R., Craig, T.H., and Huettmann, F., 2018, Assessment of potential risks from renewable energy development and other anthropogenic factors to wintering Golden Eagles in the western United States, chap. of Machine learning for ecology and sustainable natural resource management, p. 379-407, https://doi.org/10.1007/978-3-319-96978-7_19.","productDescription":"29 p.","startPage":"379","endPage":"407","ipdsId":"IP-097959","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":361650,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-11-06","publicationStatus":"PW","contributors":{"editors":[{"text":"Humphries, Grant","contributorId":213887,"corporation":false,"usgs":false,"family":"Humphries","given":"Grant","email":"","affiliations":[],"preferred":false,"id":758612,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Magness, Dawn","contributorId":147692,"corporation":false,"usgs":false,"family":"Magness","given":"Dawn","affiliations":[{"id":16903,"text":"U.S. Fish and Wildlife Service, Kenai National Wildlife Refuge, Soldotna, AK, 99669, USA","active":true,"usgs":false}],"preferred":false,"id":758613,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Huettmann, Falk","contributorId":15663,"corporation":false,"usgs":false,"family":"Huettmann","given":"Falk","email":"","affiliations":[],"preferred":false,"id":758614,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"Craig, Erica H.","contributorId":176469,"corporation":false,"usgs":false,"family":"Craig","given":"Erica","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":758021,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fuller, Mark R. 0000-0001-7459-1729 mark_fuller@usgs.gov","orcid":"https://orcid.org/0000-0001-7459-1729","contributorId":2296,"corporation":false,"usgs":true,"family":"Fuller","given":"Mark","email":"mark_fuller@usgs.gov","middleInitial":"R.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":758022,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Craig, Tim H.","contributorId":213558,"corporation":false,"usgs":false,"family":"Craig","given":"Tim","email":"","middleInitial":"H.","affiliations":[{"id":27672,"text":"Aquila Environmental","active":true,"usgs":false}],"preferred":false,"id":758023,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Huettmann, Falk","contributorId":15663,"corporation":false,"usgs":false,"family":"Huettmann","given":"Falk","email":"","affiliations":[],"preferred":false,"id":758024,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70199458,"text":"sim3417 - 2018 - Geologic map of the San Antonio Mountain area, northern New Mexico and southern Colorado","interactions":[],"lastModifiedDate":"2022-10-31T15:54:04.421473","indexId":"sim3417","displayToPublicDate":"2018-11-05T16:30:00","publicationYear":"2018","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":"3417","title":"Geologic map of the San Antonio Mountain area, northern New Mexico and southern Colorado","docAbstract":"The geologic map of the San Antonio Mountain area in northern New Mexico and southern Colorado is located along the west-central part of the San Luis Valley. The San Luis Valley is the geomorphic expression of the San Luis Basin, an extensional basin associated with the northern Rio Grande rift. Deposits within the map area record volcanic, sedimentary, and tectonic processes over the last ~33 million years. Oldest exposed deposits include Oligocene volcanic rocks associated with the southeast San Juan Mountains locus of volcanism within the Southern Rocky Mountains volcanic field. Overlying deposits of the Southern Rocky Mountains volcanic field are volcaniclastic sedimentary rocks interbedded with predominantly basaltic lava flows of Oligocene to Miocene age. Basalt to rhyolite volcanic rocks of the Pliocene to Pleistocene Taos Plateau volcanic field unconformably overlie Oligocene to Miocene volcanic and sedimentary deposits. Superposed on the Tertiary deposits are Pleistocene to Holocene alluvial and colluvial deposits.
North- to northwest-trending faults displace rocks within the map area. Magnitude of deformation is broadly correlative with age of the deposits inasmuch as Oligocene to Miocene rocks display a greater degree of fault displacement and east tilting than Pliocene volcanic rocks. Within the map area, faults displace Oligocene to Miocene deposits 10–30 meters with generally down-to-west offset, and the units dip eastward 3–7 degrees. Pliocene volcanic rocks exhibit shallower eastward dips inferred primarily from the slope of upper lava flow surfaces that dip eastward from 1–3 degrees and lava flows are generally displaced less than 5 meters.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3417","usgsCitation":"Turner, K.J., Thompson, R.A., Cosca, M.A., Shroba, R.R., Chan, C.F., and Morgan, L.E., 2018, Geologic map of the San Antonio Mountain area, northern New Mexico and southern Colorado: U.S. Geological Survey Scientific Investigations Map 3417, scale 1:50,000, https://doi.org/10.3133/sim3417.","productDescription":"2 Plates: 54.57 x 45.00 inches; Data Release; Read Me","onlineOnly":"Y","ipdsId":"IP-096384","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":359163,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F72N51M5","text":"USGS data release","linkHelpText":"Data release of geospatial map database, argon geochronology and geochemistry data for: Geologic map of the San Antonio Mountain area, northern New Mexico and southern Colorado"},{"id":359166,"rank":5,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sim/3417/sim3417_ReadMe.txt","text":"Read Me","size":"8.0 KB","linkFileType":{"id":2,"text":"txt"},"description":"SIM 3417 Read Me"},{"id":359159,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3417/sim3417_georeferenced.pdf","text":"Georeferenced Map","size":"23.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3417 Georeferenced Map"},{"id":359154,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3417/sim3417.pdf","text":"Map","size":"30.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3417 Map"},{"id":359153,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3417/coverthb.jpg"}],"country":"United States","state":"Colorado, New Mexico","otherGeospatial":"San Antonio Mountain area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -106.02936536993761,\n 37.00446329492584\n ],\n [\n -106.48758186305275,\n 37.00536016826341\n ],\n [\n -106.31462759849488,\n 36.86352300557036\n ],\n [\n -106.28655060749503,\n 36.615124233650306\n ],\n [\n -106.0203807328178,\n 36.611518344641\n ],\n [\n -106.02936536993761,\n 37.00446329492584\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Geosciences and Environmental Change Science Center
U.S. Geological Survey
Box 25046, MS-980
Denver, CO 80225-0046
The U.S. Geological Survey (USGS) has developed the National Land Cover Database (NLCD) to provide consistent land cover and land cover change products for the nation since 2001. As one of products in the NLCD, the percent impervious surface area (ISA), which was estimated with Landsat imagery, represents the fraction of human-made impervious area in a 30-m grid and has been used to quantify urban land cover types and extents for the United States. However, it is still a challenge to clearly determine urban land cover intensity and extents using remote sensing data with spatial and spectral resolutions similar to Landsat in part because of highly heterogeneous features of urban land cover. Most urban areas, especially in low intensity development areas, exhibit sub-pixel characteristics that mix impervious surface with other land covers (e.g., grass and trees) in the 30-m resolution satellite imagery. Furthermore, the influence of highly heterogeneous features in many urban areas and how they alter the spectral signature of urban landscapes has not yet been fully studied. Recent advances in remote sensing technology have provided multiple spectral and spatial resolution data from several satellites including WorldView (WV), Sentinel-2, and the Landsat Operational Land Imager (OLI). Remote sensing images having different spectral bands and high spatial resolution provide the potential to derive detailed information on the nature and properties of different surface materials on the urban ground. This study focuses on performance of mapping impervious surface using data collected from WorldView-3, Sentinel-2, and Landsat OLI. We compared ISA results estimated from these sensors and evaluated benefits and limitations of radiometric and spatial resolutions for mapping impervious surface in a study area on the Eastern corridor between Washington, D.C., and Baltimore, where developed impervious surface containing both residential housings, office buildings, and roads, in the United States. The impact of different band combinations in Sentinel-2 imagery on mapping urban impervious surface and urban land cover was also evaluated.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium","conferenceDate":"Jul 22-27, 2018","conferenceLocation":"Valencia, Spain","language":"English","publisher":"IEEE","doi":"10.1109/IGARSS.2018.8518013","usgsCitation":"Xian, G.Z., Shi, H., Dewitz, J., and Wu, Z., 2018, Analysis of different sensor performances in impervious surface mapping, in IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium, Valencia, Spain, Jul 22-27, 2018, p. 8189-8192, https://doi.org/10.1109/IGARSS.2018.8518013.","productDescription":"4 p.","startPage":"8189","endPage":"8192","ipdsId":"IP-093474","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":377825,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Xian, George Z. 0000-0001-5674-2204","orcid":"https://orcid.org/0000-0001-5674-2204","contributorId":238919,"corporation":false,"usgs":true,"family":"Xian","given":"George","email":"","middleInitial":"Z.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":796922,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shi, Hua 0000-0001-7013-1565 hshi@usgs.gov","orcid":"https://orcid.org/0000-0001-7013-1565","contributorId":646,"corporation":false,"usgs":true,"family":"Shi","given":"Hua","email":"hshi@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":796923,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dewitz, Jon 0000-0002-0458-212X dewitz@usgs.gov","orcid":"https://orcid.org/0000-0002-0458-212X","contributorId":2401,"corporation":false,"usgs":true,"family":"Dewitz","given":"Jon","email":"dewitz@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":797261,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wu, Zhuoting 0000-0001-7393-1832 zwu@usgs.gov","orcid":"https://orcid.org/0000-0001-7393-1832","contributorId":4953,"corporation":false,"usgs":true,"family":"Wu","given":"Zhuoting","email":"zwu@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true},{"id":498,"text":"Office of Land Remote Sensing (Geography)","active":true,"usgs":true}],"preferred":true,"id":796924,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70196593,"text":"ofr20181071 - 2018 - Concentrations of lead and other inorganic constituents in samples of raw intake and treated drinking water from the municipal water filtration plant and residential tapwater in Chicago, Illinois, and East Chicago, Indiana, July–December 2017","interactions":[],"lastModifiedDate":"2019-03-04T10:35:48","indexId":"ofr20181071","displayToPublicDate":"2018-11-01T17:00:00","publicationYear":"2018","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":"2018-1071","title":"Concentrations of lead and other inorganic constituents in samples of raw intake and treated drinking water from the municipal water filtration plant and residential tapwater in Chicago, Illinois, and East Chicago, Indiana, July–December 2017","docAbstract":"The U.S. Geological Survey (USGS) Environmental Health Mission Area (EHMA) is providing comprehensive science on sources, movement, and transformation of contaminants and pathogens in watershed and aquifer drinking-water supplies and in built water and wastewater infrastructure (referred to as the USGS Water and Wastewater Infrastructure project) in the Greater Chicago Area and elsewhere in the United States, to fill data gaps identified by stakeholders and collaborators in drinking water and public health. EHMA Water and Wastewater Infrastructure research specifically provides insight into natural factors in the environment as well as those water-infrastructure components and processes (such as source-water corrosivity, treatment, plumbing, and so forth) that might influence human exposure to chemical and microbial contaminants at the residential tap. This infrastructure-exposure research role is fulfilled uniquely by the USGS and not by the U.S. Environmental Protection Agency (EPA), other agencies, or municipalities that focus on regulatory and policy activities and related compliance. The USGS approach to assessing the possible links between human health and chemical contaminant and pathogen exposure in drinking water is conducted in collaboration with public health experts and includes comprehensive characterization of the presence/absence and concentrations of more than 500 organic and 27 inorganic chemical constituents at the point of use (tap).
Laboratory results for lead and other inorganic contaminants in Chicago, Illinois, and East Chicago, Indiana, residential tapwater are being released to ensure the timely release of quality-assured data to participants in the study. Concentrations of lead and other inorganic constituents were assessed in drinking water at the point of use (kitchen tap or filter) in 45 residential locations and in two locations within each of the two Chicago water purification plants and the two East Chicago water filtration plants during July–December 2017. Three methods were used for analyzing lead. The most sensitive method had a reporting limit of 0.020 micrograms per liter (µg/L). When using the most sensitive analytical method, lead was detected in 39 of 45 residential tapwater samples, with concentrations ranging from less than 0.020 µg/L to 5.31 µg/L (median of the detected values = 0.481 µg/L). Concentrations of lead also were detected in Lake Michigan intake water at all water purification/filtration plant facilities at concentrations ranging from 0.083 to 0.330 µg/L, but were not detected above the reporting limit in any samples of treated, pre-distribution drinking water at any of the water purification/filtration plant facilities.
Because the USGS Water and Wastewater Infrastructure project in the Greater Chicago Area is focused on the potential human exposure to a broad suite of organic and inorganic contaminants in drinking water and is not focused specifically on lead, the sampling protocol did not include “first-draw,” stagnant sampling and samples were collected with point-of-use treatment in place, if present. Thus, the lead results reported herein are not appropriate for assessment of compliance with the EPA 1991 Lead and Copper Rule. Information resources for lead mitigation and water filtration are provided.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181071","collaboration":"Prepared in cooperation with the City of Chicago, Department of Water Management; City of East Chicago, Utilities Department; Indiana Department of Environmental Management, Drinking Water Branch; National Institutes of Health/National Institute of Environmental Health Sciences (NIH/NIEHS); University of Illinois at Chicago, School of Public Health","usgsCitation":"Romanok, K.M., Kolpin, D.W., Meppelink, S.M., Focazio, M.J., Argos, M., Hollingsworth, M.E., McCleskey, R.B., Putz, A.R., Stark, A., Weis, C.P., Zehraoui, A., and Bradley, P.M., 2018, Concentrations of lead and other inorganic constituents in samples of raw intake and treated drinking water from the municipal water filtration plant and residential tapwater in Chicago, Illinois, and East Chicago, Indiana, July–December 2017: U.S. Geological Survey Open-File Report 2018–1071, 10 p., https://doi.org/10.3133/ofr20181071.","productDescription":"Report: iv, 10 p.; Data release","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-094493","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":358915,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20181098","text":"Open-File Report 2018–1098","linkHelpText":"- Methods Used for the Collection and Analysis of Chemical and Biological Data for the Tapwater Exposure Study, United States, 2016–17"},{"id":358912,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1071/coverthb.jpg"},{"id":358914,"rank":3,"type":{"id":30,"text":"Data Release"},"url":" https://doi.org/10.5066/F70R9NN0","text":"USGS data release ","description":"USGS data release ","linkHelpText":"Occurrence and Concentrations of Trace Elements in Discrete Tapwater Samples Collected in Chicago, Illinois and East Chicago, Indiana, 2017"},{"id":358913,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1071/ofr20181071.pdf","text":"Report","size":"1.26 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1071"}],"country":"United States","state":"Illinois, Indiana","city":"Chicago, East Chicago","contact":"Director, South Atlantic Water Science Center
U.S. Geological Survey
720 Gracern Road
Columbia, SC 29210
In 2016, the U.S. Geological Survey (USGS) Environmental Health Mission Area, initiated the Tapwater Exposure Study as part of an infrastructure project to assess human exposure to potential threats from complex mixtures of contaminants. In the pilot phase (2016), samples were collected from 11 States throughout the United States, and in the second phase (2017), the study focused on the Greater Chicago area, including North and South Chicago, Illinois, and East Chicago, Indiana. Residential tapwater samples were collected at private residences during both phases, and during the first phase, samples were collected from Federal office buildings and from one office 19-liter water-bottle source. During the second phase, raw intake and treated (pre-distributional) water samples also were collected from four drinking-water treatment facilities in the Greater Chicago area. Samples were sent to laboratories at the USGS, U.S. Environmental Protection Agency, National Institute of Environmental Health Sciences, and Colorado School of Mines Center for Environmental Risk Assessment, for potential drinking-water pathogens, chemical, and bioassay analyses. These analyses included more than 400 chemicals such as trace elements, steroid hormones, pharmaceuticals, volatile organic compounds, pesticides, per- and polyfluorinated alkyl substances, cyanotoxins, and other organic compounds. The in vitro bioassay analyses included estrogen, androgen, and glucocorticoid receptor activity.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181098","collaboration":"Prepared in cooperation with the Colorado School of Mines, Center for Environmental Risk Assessment; National Institutes of Health/National Institute of Environmental Health Sciences (NIH/NIEHS), National Toxicology Program Laboratory; University of Illinois at Chicago, School of Public Health; U.S. Environmental Protection Agency, National Exposure Research Laboratory; U.S. Environmental Protection Agency, National Health and Environmental Effects Laboratory","usgsCitation":"Romanok, K.M., Kolpin, D.W., Meppelink, S.M., Argos, M., Brown, J.B., DeVito, M.J., Dietze, J.E., Givens, C.E., Gray, J.L., Higgins, C.P., Hladik, M.L., Iwanowicz, L.R., Loftin, K.A., McCleskey, R.B., McDonough, C.A., Meyer, M.T., Strynar, M.J., Weis, C.P., Wilson, V.S., and Bradley, P.M., 2018, Methods used for the collection and analysis of chemical and biological data for the Tapwater Exposure Study, United States, 2016–17: U.S. Geological Survey Open-File Report 2018–1098, 79 p., https://doi.org/10.3133/ofr20181098.","productDescription":"Report: ix, 79 p.; 2 Data Releases","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-094498","costCenters":[{"id":452,"text":"National Water Quality Laboratory","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":358920,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1098/coverthb.jpg"},{"id":358921,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1098/ofr20181098.pdf","text":"Report","size":"1.07 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1098"},{"id":358923,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20181071","text":"Open-File Report 2018-1071","linkHelpText":"- Concentrations of Lead and Other Inorganic Constituents in Samples of Raw Intake and Treated Drinking Water From the Municipal Water Filtration Plant and Residential Tapwater in Chicago, Illinois, and East Chicago, Indiana, July–December 2017"},{"id":358922,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7959GVJ","text":"USGS data release","description":"USGS data release","linkHelpText":"Target-Chemical Concentrations, Exposure Activity Ratios, and Bioassay Results for Assessment of Mixed-Organic/Inorganic-Chemical Exposure in USA Tapwater, 2016"},{"id":359038,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F70R9NN0","text":"USGS data release","description":"USGS data release","linkHelpText":"Occurrence and Concentrations of Trace Elements in Discrete Tapwater Samples Collected in Chicago, Illinois and East Chicago, Indiana, 2017"}],"country":"United States","geographicExtents":"{\n 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U.S. Geological Survey
720 Gracern Road
Columbia, SC 29210
The Sierra Nevada region is critical to the environment and economy of California. Its places and peoples provide
essential natural resources including fresh water, clean power, working lands, and famous wilderness. The region
encompasses tremendous geographical, climatological, and ecological diversity that spans majestic mountains to
deep desert basins. The climate consists of cool, wet winters and warm, dry summers with large differences due to
latitude (e.g., the southern Sierra is snowier than northern Sierra) and topography (e.g., the Westside is wetter than
the Eastside). Variability is another notable feature of the climate with the region experiencing some of the largest
year-to-year climatic fluctuations in the United States. Herein we summarize our assessment of climate-change
vulnerabilities and adaptation actions in the region.
The quantity of spruce-fir forest and some conifer-associated breeding bird abundances in the Atlantic Northern Forest have declined in recent decades emphasizing the need to better understand avian responses to forest management and to identify options that proactively conserve habitat for birds during the breeding and post-breeding period. We conducted avian point counts and vegetation surveys on publicly and privately-owned lands with known management histories to assess relationships between avian assemblages in harvest and postharvest treatments that could provide habitat for passerine birds associated with the spruce-fir forest type. We sampled regenerating conifer-dominated stands 5–41 years-since-harvest (YSH) in three harvest treatments (selection, irregular first-stage shelterwood, and clearcuts) and three postharvest treatments including regenerating clearcuts treated with aerially applied herbicide (e.g., glyphosate), precommercial thinning (PCT), both herbicide and PCT, and mature stands (≥48 YSH). Spruce-fir obligate and associate birds were more abundant in stands with greater spruce-fir tree composition (≥70% and ≥60%, respectively). Avian richness of spruce-fir obligates, associates, and species of concern was greater in clearcuts and clearcuts with postharvest treatments. Vegetative features associated with greater richness and abundance of spruce-fir birds, such as greater spruce-fir composition and smaller tree diameter at breast height, were prominent in regenerating clearcuts and postharvest treatments and suggested that these management practices promote local abundances and richness of spruce-fir birds. Richness and abundances of spruce-fir birds were least in selection, shelterwood, and mature stands, and vegetative features associated with greater richness and abundance of spruce-fir birds were diminished in these stands. Forestry trends in Maine indicate that the extent of the clearcut suite of treatments has decreased on the landscape while selection and shelterwood harvests have increased. Thus, changes in incentives for managers to apply even-aged management coupled with post-harvest applications of herbicides or precommercial thinning might mitigate further declines in habitat for spruce-fir passerines assemblages. A greater ratio of clearcuts with postharvest treatments 11–40 YSH compared to other treatments (mature forest ≥48 YSH, selection and shelterwood 5–41 YSH) would maintain diverse spruce-fir bird communities on the landscape. Use of clearcuts with postharvest treatments in the hemiboreal forests of northern New England, southern Quebec, and Maritime Provinces of eastern Canada may enhance habitat for breeding and post-breeding spruce-fir birds, especially where the quantity of conifer forests are declining and residual patches of conifers are increasingly fragmented.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.foreco.2018.05.068","usgsCitation":"Rolek, B.W., Harrison, D.J., Loftin, C., and Wood, P.B., 2018, Regenerating clearcuts combined with postharvest forestry treatments promote habitat for breeding and post-breeding spruce-fir avian assemblages in the Atlantic Northern Forest: Forest Ecology and Management, v. 427, p. 392-413, https://doi.org/10.1016/j.foreco.2018.05.068.","productDescription":"22 p.","startPage":"392","endPage":"413","ipdsId":"IP-091144","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":468276,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.foreco.2018.05.068","text":"Publisher Index Page"},{"id":359779,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Atlantic Northern 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\"}}]}","volume":"427","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c0108d2e4b0815414cc2df1","contributors":{"authors":[{"text":"Rolek, Brian W.","contributorId":210901,"corporation":false,"usgs":false,"family":"Rolek","given":"Brian","email":"","middleInitial":"W.","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":752706,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Harrison, Daniel J.","contributorId":210902,"corporation":false,"usgs":false,"family":"Harrison","given":"Daniel","email":"","middleInitial":"J.","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":752707,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Loftin, Cynthia S. 0000-0001-9104-3724 cyndy_loftin@usgs.gov","orcid":"https://orcid.org/0000-0001-9104-3724","contributorId":2167,"corporation":false,"usgs":true,"family":"Loftin","given":"Cynthia S.","email":"cyndy_loftin@usgs.gov","affiliations":[],"preferred":true,"id":752704,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wood, Petra B. 0000-0002-8575-1705 pbwood@usgs.gov","orcid":"https://orcid.org/0000-0002-8575-1705","contributorId":199090,"corporation":false,"usgs":true,"family":"Wood","given":"Petra","email":"pbwood@usgs.gov","middleInitial":"B.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":752705,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70199146,"text":"ds1096 - 2018 - Geologic, hydrologic, and water-quality data from multiple-well monitoring sites in the Bunker Hill and Yucaipa Groundwater Subbasins, San Bernardino County, California, 1974–2016","interactions":[],"lastModifiedDate":"2018-12-03T14:16:01","indexId":"ds1096","displayToPublicDate":"2018-10-31T10:49:21","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"1096","title":"Geologic, hydrologic, and water-quality data from multiple-well monitoring sites in the Bunker Hill and Yucaipa Groundwater Subbasins, San Bernardino County, California, 1974–2016","docAbstract":"In 1974, the U.S. Geological Survey (USGS), in cooperation with the San Bernardino Valley Municipal Water District, initiated a study to assess the regional groundwater resources in the Bunker Hill Subbasin of the Upper Santa Ana Valley Groundwater Basin in San Bernardino County, California. The study area expanded east into the Yucaipa Subbasin in 1996. This report compiles the geologic (borehole lithology and geophysical logs) and hydrologic (water-quality and water-level) data collected from 1974–2016 for 11 multiple-well monitoring sites (48 individual wells) constructed by the USGS in the Bunker Hill (7 sites) and Yucaipa (4 sites) Groundwater Subbasins.
Approximately 240 water-quality samples from the 11 sites were analyzed for constituents including major and minor ions, nutrients, selected trace elements, organic wastewater compounds (OWCs), volatile organic compounds (VOCs), pesticides and pesticide degradates, the stable isotopes of hydrogen, oxygen, and nitrogen, and the radiogenic isotopes of tritium and carbon-14. All environmental data associated with these sites are available on the project web page for the San Bernardino Optimal Basin Management study (https://ca.water.usgs.gov/sanbern/) and the Yucaipa Valley Hydrogeology study (https://ca.water.usgs.gov/yucaipa/).
Quality-assurance blank samples were processed periodically throughout the study and show that approximately 2.4 percent of the analytical results for major and minor ions, trace elements, and nutrients, and 1.5 percent of the results for VOCs fall below the acceptable study reporting limits and therefore are censored.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1096","collaboration":"Prepared in cooperation with the San Bernardino Valley Municipal Water District","usgsCitation":"Mendez, G.O., Anders, R., McPherson, K.R., and Danskin, W.R., 2018, Geologic, hydrologic, and water-quality data from multiple-well monitoring sites in the Bunker Hill and Yucaipa Groundwater Subbasins, San Bernardino County, California, 1974–2016 (ver 1.1): U.S. Geological Survey Data Series 1096, 215 p., https://doi.org/10.3133/ds1096.","productDescription":"viii, 215 p.","onlineOnly":"Y","temporalStart":"1974-01-01","temporalEnd":"2016-12-31","ipdsId":"IP-077227","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":358988,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1096/coverthb.jpg"},{"id":359774,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/ds/1096/versionHist.txt","size":"3 KB","linkFileType":{"id":2,"text":"txt"},"description":"DS 1096 Version History"},{"id":358989,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1096/ds1096_v1.1.pdf","text":"Report","size":"25.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1096"}],"country":"United States","state":"California","county":"San Bernardino County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.54547119140624,\n 33.863573814253485\n ],\n [\n -116.54022216796875,\n 33.863573814253485\n ],\n [\n -116.54022216796875,\n 34.34343606848294\n ],\n [\n -117.54547119140624,\n 34.34343606848294\n ],\n [\n -117.54547119140624,\n 33.863573814253485\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.1: November 2018; Version 1.0: October 2018","contact":"Director,
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6000 J Street, Placer Hall
Sacramento, California 95819
We report data for 112 apatite and 31 zircon fission track (AFT and ZFT) outcrop sandstone samples along a transect that spans the western Brooks Range. Sampling targeted structures that modify the Middle Jurassic‐Early Cretaceous early Brookian orogen. The AFT samples record latest Cretaceous to Eocene in situ exhumational cooling and resolve two kinematic phases. The first phase was focused at 65–60 Ma. To the north, cooling age patterns at this time are attributable to wide‐spaced fault‐related folding. Farther south, within the allochthon belt, exhumation was related to uplift of a broad region, likely in the hanging wall of deep‐seated faults that extend into basement rocks. The second kinematic phase occurred around ~45 Ma. It was characterized by north and east directed thrusting to the north, and coeval extension in the allochthon belt to the south. The ZFT cooling ages are all Early Cretaceous or older and put an upper limit on the magnitude of Cenozoic exhumation across the western Brooks Range. Synthesis of exhumation patterns and structural styles show that Paleocene rejuvenation of contraction was roughly contemporaneous along the entire ~1,000‐km orogen. Later, around ~45 Ma in the Eocene, contraction in the frontal parts of the orogen was contemporaneous with extension interior to the orogen. Following previous authors, we suggest that the Paleocene rejuvenation was a far‐field response to subduction of a mid‐ocean ridge in southern Alaska. However, by the Eocene, strain patterns in the western Brooks Range changed, possibly to accommodate rotations of fault blocks in southwestern Alaska.
Data collected from April 2014 through September 2016 were used to assess geomorphic characteristics and geomorphic changes over time in a selected reach of Tenmile Creek, a small rural watershed near Clarksburg, Maryland. Longitudinal profiles of the channel bed, water surface, and bank features were developed from field surveys. Changes in cross-section geometry between field surveys were documented. Grain-size distributions for the channel bed were developed from pebble counts. Continuous-record streamflow and precipitation data were also collected in the Tenmile Creek watershed and used to supplement the geomorphic analyses.
The Rosgen system of stream classification was used to classify the stream channel according to morphological measurements of slope, entrenchment ratio, width-to-depth ratio, sinuosity, and median particle diameter of the channel materials. Boundary shear stress near the U.S. Geological Survey (USGS) streamflow-gaging station was assessed by using hydraulic variables computed from the cross-section surveys and slope measurements derived from crest-stage gages and temporary data loggers installed along the study reach.
Analysis of the longitudinal profiles indicated relatively small changes in the percentage and distribution of riffles, pools, and runs in the study reach between April 2014 and March 2015. More noticeable changes were observed during surveys conducted in March 2016 and September 2016. The channel-bed slope showed a net reduction over time from 0.0072 to 0.0040 feet per foot (ft/ft). The low-flow water-surface slope also showed a net reduction over time from 0.0065 to 0.0045 ft/ft. Net aggradation in the lower section of the study reach combined with net degradation in the upper section of the study reach contributed to the net reduction in channel-bed and water-surface slope. The large storm and resulting flood on July 30, 2016 was a major factor in observed changes in the longitudinal profiles between the March 2016 and September 2016 surveys.
Comparison of data from the cross-sectional surveys indicated vertical changes in all cross sections, with more extreme changes observed between surveys in the lower section of the study reach due in part to alternating periods of net storage and transport of sand. Lateral erosion was not a major factor in the study reach, with the exception of cross section Dd, where considerable lateral erosion was documented during the study period. The flood that resulted from the large storm on July 30, 2016 was a major factor in some of the vertical changes observed in the channel bed of the study reach cross sections.
Particle-size analyses of the channel bed from pebble counts indicated median particle diameters ranging from 15.5 millimeters (mm) to 23.1 mm, which is characterized as medium to coarse gravel. Sand percentages ranging from 3.4 percent to 16.4 percent of the total counts were observed over time. Net increases in storage of fine sediment in the reach were observed between April 2014 and March 2016, and a considerable reduction in storage was observed between March 2016 and September 2016.
The Tenmile Creek stream channel was classified as a C4 channel, based on morphological descriptions from the Rosgen system of stream classification. The C4 classification describes a single-thread channel with a slight entrenchment ratio; a moderate to high width-to-depth ratio; moderate to high sinuosity; a water-surface slope of less than 2 percent; and a median particle diameter in the gravel range of 2 to 64 mm.
The analysis of boundary shear stress indicated a range of 0.35 to 1.18 pounds per square foot for instantaneous streamflow ranging from 79 to 2,860 cubic feet per second during the study period. The relation between discharge and boundary shear stress for Tenmile Creek was compared to similar relations that were previously developed for Minebank Run, a small, urban watershed in the eastern section of the Piedmont Physiographic Province in Baltimore County, Md. that was physically restored during 2004–05. The comparison indicated a much flatter slope in the relation for Minebank Run in both its unrestored and restored conditions. This difference in the relations indicates that the erosive power in the urban watershed of Minebank Run is much more sensitive to increases in discharge magnitude than in the non-urban watershed of Tenmile Creek.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185098","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency and the Montgomery County Department of Environmental Protection","usgsCitation":"Doheny, E.J., and Baker, S.M., 2018, Geomorphic characteristics of Tenmile Creek, Montgomery County, Maryland, 2014–16: U.S. Geological Survey Scientific Investigations Report 2018–5098, 34 p., https://doi.org/10.3133/sir20185098.","productDescription":"Report: viii, 34 p.; Data release","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-090630","costCenters":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"links":[{"id":437714,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7WW7GKQ","text":"USGS data release","linkHelpText":"Datasets from an assessment of geomorphic characteristics of Tenmile Creek, Montgomery County, Maryland, 2014-16"},{"id":358408,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5098/coverthb.jpg"},{"id":358410,"rank":3,"type":{"id":30,"text":"Data Release"},"url":" https://doi.org/10.5066/F7WW7GKQ","text":"USGS data release","description":"USGS data release","linkHelpText":"Datasets from an assessment of geomorphic characteristics of Tenmile Creek, Montgomery County, Maryland, 2014–16"},{"id":358409,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5098/sir20185098.pdf","text":"Report","size":"17.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5098"}],"country":"United States","state":"Maryland","county":"Montgomery County","otherGeospatial":"Tenmile Creek watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.3356,\n 39.2075\n ],\n [\n -77.2786,\n 39.2075\n ],\n [\n -77.2786,\n 39.2492\n ],\n [\n -77.3356,\n 39.2492\n ],\n [\n -77.3356,\n 39.2075\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, MD-DE-DC Water Science Center
U.S. Geological Survey
5522 Research Park Drive
Baltimore, MD 21228
The Island Night Lizard (Xantusia riversiana) was removed from the federal list of threatened species in May 2014. This strongly differentiated species is endemic to 3 of the southern California Channel Islands—San Clemente, San Nicolas, and Santa Barbara. Suitable habitat for Island Night Lizards is extensive on San Clemente Island, and the species is abundant there. Habitat is limited and fragmented, however, on San Nicolas Island and small Santa Barbara Island. Bringing together extensive field surveys and mark-recapture sampling, we synthesize available data for Island Night Lizards on San Nicolas Island and calculate population and density estimates for the species in major habitats on the island. Island Night Lizards are widely distributed across most of the eastern half of San Nicolas Island. In contrast, they are nearly absent over the western third of the island except for isolated populations in boulder beach habitats. We combined mark-recapture population estimates with comprehensive measurements of the extent of cactus, boxthorn, and other habitat types on the island to arrive at a more accurate assessment of the status of Island Night Lizards on San Nicolas Island. High densities of Island Night Lizards on the island are found in small areas of cholla cactus (Cylindropuntia prolifera; mean of 4100 lizards/ha), boulder beach habitat (mean of 3400 lizards/ha), and prickly pear cactus (Opuntia spp.; mean of 1700 lizards/ha); low numbers are found in more extensive mixed-shrub habitat (mean of 250 lizards/ha). The U.S. Fish and Wildlife Service requires a post-delisting program for “monitoring the overall health of the Island Night Lizard” to assure the continued long-term viability of the species in its restricted distribution. The information on population size and habitat presented here will inform and guide conservation and management efforts by the U.S. Navy on San Nicolas Island over the coming years.
","language":"English","publisher":"Monte L. Bean Life Science Museum, Brigham Young University","doi":"10.3398/064.078.0310","usgsCitation":"Drost, C.A., Fellers, G.M., Murphey, T.R., Kleeman, P.M., Halstead, B., and O'Donnell, R., 2018, Distribution, habitat, and population size of Island Night Lizards on San Nicolas Island, California: Western North American Naturalist, v. 78, no. 3, p. 358-369, https://doi.org/10.3398/064.078.0310.","productDescription":"12 p.","startPage":"358","endPage":"369","ipdsId":"IP-088859","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":358584,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Nicholas Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.60781097412108,\n 33.19675310661128\n ],\n [\n -119.41177368164061,\n 33.19675310661128\n ],\n [\n -119.41177368164061,\n 33.30040366624405\n ],\n [\n -119.60781097412108,\n 33.30040366624405\n ],\n [\n -119.60781097412108,\n 33.19675310661128\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"78","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c10a91be4b034bf6a7e4fc0","contributors":{"authors":[{"text":"Drost, Charles A. 0000-0002-4792-7095 charles_drost@usgs.gov","orcid":"https://orcid.org/0000-0002-4792-7095","contributorId":3151,"corporation":false,"usgs":true,"family":"Drost","given":"Charles","email":"charles_drost@usgs.gov","middleInitial":"A.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":749098,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fellers, Gary M.","contributorId":209920,"corporation":false,"usgs":false,"family":"Fellers","given":"Gary","email":"","middleInitial":"M.","affiliations":[{"id":38025,"text":"9 Goldfinch Court, Novato, CA 94947; gary_fellers@worldnet.att.net","active":true,"usgs":false}],"preferred":false,"id":749099,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Murphey, Thomas R.","contributorId":209921,"corporation":false,"usgs":false,"family":"Murphey","given":"Thomas","email":"","middleInitial":"R.","affiliations":[{"id":38026,"text":"Monterey Ranger District, Los Padres National Forest, King City, CA 93930","active":true,"usgs":false}],"preferred":false,"id":749100,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kleeman, Patrick M. 0000-0001-6567-3239 pkleeman@usgs.gov","orcid":"https://orcid.org/0000-0001-6567-3239","contributorId":3948,"corporation":false,"usgs":true,"family":"Kleeman","given":"Patrick","email":"pkleeman@usgs.gov","middleInitial":"M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":749101,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Halstead, Brian J. 0000-0002-5535-6528 bhalstead@usgs.gov","orcid":"https://orcid.org/0000-0002-5535-6528","contributorId":3051,"corporation":false,"usgs":true,"family":"Halstead","given":"Brian J.","email":"bhalstead@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":749102,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"O'Donnell, Ryan P.","contributorId":209922,"corporation":false,"usgs":false,"family":"O'Donnell","given":"Ryan P.","affiliations":[{"id":38027,"text":"Arizona Game and Fish Department, 5000 W. Carefree Highway, Phoenix, AZ 85086","active":true,"usgs":false}],"preferred":false,"id":749103,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70201200,"text":"70201200 - 2018 - Mapping crop residue and tillage intensity using WorldView-3 satellite shortwave infrared residue indices","interactions":[],"lastModifiedDate":"2018-12-06T11:24:25","indexId":"70201200","displayToPublicDate":"2018-10-18T11:24:19","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Mapping crop residue and tillage intensity using WorldView-3 satellite shortwave infrared residue indices","docAbstract":"Crop residues serve many important functions in agricultural conservation including preserving soil moisture, building soil organic carbon, and preventing erosion. Percent crop residue cover on a field surface reflects the outcome of tillage intensity and crop management practices. Previous studies using proximal hyperspectral remote sensing have demonstrated accurate measurement of percent residue cover using residue indices that characterize cellulose and lignin absorption features found between 2100 nm and 2300 nm in the shortwave infrared (SWIR) region of the electromagnetic spectrum. The 2014 launch of the WorldView-3 (WV3) satellite has now provided a space-borne platform for the collection of narrow band SWIR reflectance imagery capable of measuring these cellulose and lignin absorption features. In this study, WorldView-3 SWIR imagery (14 May 2015) was acquired over farmland on the Eastern Shore of Chesapeake Bay (Maryland, USA), was converted to surface reflectance, and eight different SWIR reflectance indices were calculated. On-farm photographic sampling was used to measure percent residue cover at a total of 174 locations in 10 agricultural fields, ranging from plow-till to continuous no-till management, and these in situ measurements were used to develop percent residue cover prediction models from the SWIR indices using both polynomial and linear least squares regressions. Analysis was limited to agricultural fields with minimal green vegetation (Normalized Difference Vegetation Index < 0.3) due to expected interference of vegetation with the SWIR indices. In the resulting residue prediction models, spectrally narrow residue indices including the Shortwave Infrared Normalized Difference Residue Index (SINDRI) and the Lignin Cellulose Absorption Index (LCA) were determined to be more accurate than spectrally broad Landsat-compatible indices such as the Normalized Difference Tillage Index (NDTI), as determined by respective R2 values of 0.94, 0.92, and 0.84 and respective residual mean squared errors (RMSE) of 7.15, 8.40, and 12.00. Additionally, SINDRI and LCA were more resistant to interference from low levels of green vegetation. The model with the highest correlation (2nd order polynomial SINDRI, R2 = 0.94) was used to convert the SWIR imagery into a map of crop residue cover for non-vegetated agricultural fields throughout the imagery extent, describing the distribution of tillage intensity within the farm landscape. WorldView-3 satellite imagery provides spectrally narrow SWIR reflectance measurements that show utility for a robust mapping of crop residue cover.
","language":"English","publisher":"MDPI","doi":"10.3390/rs10101657","usgsCitation":"Hively, W.D., Lamb, B.T., Daughtry, C.S., Shermeyer, J., McCarty, G.W., and Quemada, M., 2018, Mapping crop residue and tillage intensity using WorldView-3 satellite shortwave infrared residue indices: Remote Sensing, v. 10, no. 10, p. 1-22, https://doi.org/10.3390/rs10101657.","productDescription":"Article 1657; 22 p.","startPage":"1","endPage":"22","ipdsId":"IP-090230","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":468309,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs10101657","text":"Publisher Index Page"},{"id":437715,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7930SDB","text":"USGS data release","linkHelpText":"WorldView-3 satellite imagery and crop residue field data collection, Talbot County, MD, May 2015"},{"id":359980,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland","otherGeospatial":"Choptank River watershed","volume":"10","issue":"10","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-10-18","publicationStatus":"PW","scienceBaseUri":"5c0a4357e4b0815414d28132","contributors":{"authors":[{"text":"Hively, W. Dean 0000-0002-5383-8064","orcid":"https://orcid.org/0000-0002-5383-8064","contributorId":201565,"corporation":false,"usgs":true,"family":"Hively","given":"W.","email":"","middleInitial":"Dean","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":753190,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lamb, Brian T.","contributorId":211092,"corporation":false,"usgs":false,"family":"Lamb","given":"Brian","email":"","middleInitial":"T.","affiliations":[{"id":38178,"text":"City College of New York","active":true,"usgs":false}],"preferred":false,"id":753191,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Daughtry, Craig S. T.","contributorId":211093,"corporation":false,"usgs":false,"family":"Daughtry","given":"Craig","email":"","middleInitial":"S. T.","affiliations":[{"id":38179,"text":"USDA Agricultural Research Service, Hydrology and Remote Sensing Laboratory","active":true,"usgs":false}],"preferred":false,"id":753192,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shermeyer, Jacob 0000-0002-8143-2790 jshermeyer@usgs.gov","orcid":"https://orcid.org/0000-0002-8143-2790","contributorId":211095,"corporation":false,"usgs":true,"family":"Shermeyer","given":"Jacob","email":"jshermeyer@usgs.gov","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":753195,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McCarty, Gregory W.","contributorId":192367,"corporation":false,"usgs":false,"family":"McCarty","given":"Gregory","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":753193,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Quemada, Miguel","contributorId":211094,"corporation":false,"usgs":false,"family":"Quemada","given":"Miguel","email":"","affiliations":[{"id":38180,"text":"School of Agricultural Engineering and CEIGRAM, Technical University of Madrid","active":true,"usgs":false}],"preferred":false,"id":753194,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70227762,"text":"70227762 - 2018 - Patterns in fish assemblage structure in a small western stream","interactions":[],"lastModifiedDate":"2022-01-28T13:15:05.732041","indexId":"70227762","displayToPublicDate":"2018-10-18T07:12:02","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1337,"text":"Copeia","active":true,"publicationSubtype":{"id":10}},"title":"Patterns in fish assemblage structure in a small western stream","docAbstract":"Knowledge of how patterns in fish assemblages are spatially structured is important for guiding management and conservation actions. However, most studies have taken place in the eastern and midwestern U.S., resulting in a poor understanding of factors influencing western stream fishes. The objectives of this study were to evaluate habitat and species associations of fishes in Deep Creek, a small tributary of the Kootenai River in Idaho. Fishes and habitat were sampled from 58 reaches in Deep Creek. In total, 7,129 individual fishes representing 18 species were sampled. Patterns in species richness were largely a function of channel gradient and associated habitat characteristics. Species richness decreased with increased channel gradient. Species-specific habitat relationships for native and nonnative fishes in Deep Creek provided specific insights into the ecology of each species. Predicted probability of occurrence and relative abundance varied by species and were related to a broad suite of environmental characteristics. This study provides insight on patterns of fish assemblage structure, as well as important information on the ecology of native and nonnative fishes in a western stream system.
We conducted the first systematic inventory of birds in the lowlands (areas ≤100 m above sea level) of the Alaska Peninsula during summers of 2004–2007 to determine their breeding distributions and habitat associations in this remote region. Using a stratified random survey design, we allocated sample plots by elevation and land cover with a preference for wetland cover types used by shorebirds, a group of particular interest to land managers. We surveyed birds during 10-min counts at 792 points across 52, 5 km × 5 km sample plots distributed from south of the Naknek River (58.70°N,157.00°W) to north of Port Moller (56.00°N,160.52°W). We detected 95 bird species including 19 species of shorebirds and 34 species (36% of total) considered at the time to be of conservation concern for the land managers in the region. The most numerous shorebirds on point counts were dunlin Calidris alpina, short-billed dowitcher Limnodromus griseus, and Wilson's snipe Gallinago delicata.We found the breeding-season endemic marbled godwit Limosa fedoa beringiae at 20 plots within a 3,000-km2 area from north of Ugashik Bay to just north of Port Heiden and east to the headwaters of the Dog Salmon and Ugashik rivers. The most abundant passerines on point counts were American tree sparrow Spizelloides arborea, Lapland longspur Calcarius lapponicus, and savannah sparrow Passerculus sandwichensis. Sandhill crane Antigone canadensis, glaucous-winged gull Larus glaucescens, and greater scaup Aythya marila were also relatively abundant. We categorized habitat associations for 30 common species and found that lowland herbaceous vegetation supported wetland-focused species including sandhill crane, marbled godwit, short-billed dowitcher, and dunlin; whereas, dwarf shrub-ericaceous vegetation supported tundra-associated species such as willow ptarmigan Lagopus lagopus, rock sandpiper Calidris ptilocnemis, and American pipit Anthus rubescens. Tall shrub vegetation was important to several species of warblers and sparrows, as well as one species of shorebird (greater yellowlegs Tringa melanoleuca). We found that point counts augmented with incidental observations provided an almost complete inventory of lowland-breeding species on the study area. These data form a baseline to monitor any future changes in bird distribution and abundance on the Alaska Peninsula.
","language":"English","publisher":"U.S. Fish & Wildlife Service","doi":"10.3996/082017-JFWM-070","usgsCitation":"Savage, S.E., Tibbitts, T.L., Sesser, K., and Kaler, R., 2018, Inventory of lowland-breeding birds on the Alaska Peninsula: Journal of Fish and Wildlife Management, v. 9, no. 2, p. 637-658, https://doi.org/10.3996/082017-JFWM-070.","productDescription":"22 p.","startPage":"637","endPage":"658","ipdsId":"IP-090348","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":468316,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/082017-jfwm-070","text":"Publisher Index Page"},{"id":437716,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9FR8FLZ","text":"USGS data release","linkHelpText":"Inventory Data of Lowland-Breeding Birds and Associated Vegetation Types on the Alaska Peninsula, 2004-2007"},{"id":358402,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Alaska Peninsula","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -164,\n 54.5\n ],\n [\n -152,\n 54.5\n ],\n [\n -152,\n 59\n ],\n [\n -164,\n 59\n ],\n [\n -164,\n 54.5\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"9","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-08-14","publicationStatus":"PW","scienceBaseUri":"5c10a91ce4b034bf6a7e4fe6","contributors":{"authors":[{"text":"Savage, Susan E.","contributorId":140748,"corporation":false,"usgs":false,"family":"Savage","given":"Susan","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":748673,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tibbitts, T. Lee 0000-0002-0290-7592 ltibbitts@usgs.gov","orcid":"https://orcid.org/0000-0002-0290-7592","contributorId":102185,"corporation":false,"usgs":true,"family":"Tibbitts","given":"T.","email":"ltibbitts@usgs.gov","middleInitial":"Lee","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":748672,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sesser, Kristin","contributorId":209737,"corporation":false,"usgs":false,"family":"Sesser","given":"Kristin","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":748674,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kaler, Robb S.A.","contributorId":69066,"corporation":false,"usgs":true,"family":"Kaler","given":"Robb S.A.","affiliations":[],"preferred":false,"id":748675,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70263621,"text":"70263621 - 2018 - A proposed rupture scenario for the 1925 Mw 6.5 Santa Barbara, California, earthquake","interactions":[],"lastModifiedDate":"2025-02-19T16:07:44.421642","indexId":"70263621","displayToPublicDate":"2018-10-13T10:01:40","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3525,"text":"Tectonophysics","active":true,"publicationSubtype":{"id":10}},"title":"A proposed rupture scenario for the 1925 Mw 6.5 Santa Barbara, California, earthquake","docAbstract":"The 29 June 1925 Santa Barbara earthquake is among the largest 20th century earthquakes in southern California. The earthquake also predated the installation of strong motion and local monitoring instruments in southern California; some instrumental data are, however, available from long-period instruments at regional and teleseismic distances. The current catalog moment magnitude is MW 6.8. Initial intensity magnitudes (MI) estimated from original Coast and Geodetic Survey intensity assignments were lower (MI 6.3). In this study we assign modified Mercalli intensity values at 239 locations, including 144 specific locations within the city of Santa Barbara for which detailed damage information is available. Comparing the reinterpreted intensities with Did You Feel it? intensities for recent events in California, we estimate MW = 6.5, with a plausible range of 6.3–6.6. We further consider reported instrumental amplitudes to estimate an instrumental moment magnitude of MW = 6.6 ± 0.5. Our preferred final estimate is MW 6.5. Based on available constraints including aftershock locations inferred from data recorded on portable instruments, we propose that the earthquake nucleated east of the city of Santa Barbara, closer to the coast than previously estimated, and ruptured unilaterally ~30 km to the west, possibly along the south-dipping Mesa-Rincon Creek, and the More Ranch fault systems. Contrary to suggestions made in earlier studies (e.g. Willis, 1925a), relatively high intensities ~50 km west of Santa Barbara can then be explained by directivity rather than involvement of the Santa Ynez fault. Finally, we discuss the possibility that the earthquake was triggered by the larger MW = 6.6 Clarkston, Montana earthquake the previous day or induced by oil production in the Summerland oil field.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.tecto.2018.09.012","usgsCitation":"Hough, S.E., and Martin, S.S., 2018, A proposed rupture scenario for the 1925 Mw 6.5 Santa Barbara, California, earthquake: Tectonophysics, v. 747-748, p. 211-224, https://doi.org/10.1016/j.tecto.2018.09.012.","productDescription":"14 p.","startPage":"211","endPage":"224","ipdsId":"IP-096386","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":482219,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"Santa Barabara","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -119.9,\n 34.65\n ],\n [\n -119.9,\n 34.25\n ],\n [\n -119.45,\n 34.25\n ],\n [\n -119.45,\n 34.65\n ],\n [\n -119.9,\n 34.65\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"747-748","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hough, Susan E. 0000-0002-5980-2986 hough@usgs.gov","orcid":"https://orcid.org/0000-0002-5980-2986","contributorId":587,"corporation":false,"usgs":true,"family":"Hough","given":"Susan","email":"hough@usgs.gov","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927596,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Martin, Stacey S.","contributorId":140021,"corporation":false,"usgs":false,"family":"Martin","given":"Stacey","email":"","middleInitial":"S.","affiliations":[{"id":5110,"text":"Earth Observatory of Singapore, Nanyang Technological University","active":true,"usgs":false}],"preferred":false,"id":927597,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70200142,"text":"70200142 - 2018 - Estimating the pressure-limited CO2 injection and storage capacity of the United States saline formations: Effect of the presence of hydrocarbon reservoirs","interactions":[],"lastModifiedDate":"2019-02-07T12:13:09","indexId":"70200142","displayToPublicDate":"2018-10-12T14:00:28","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2049,"text":"International Journal of Greenhouse Gas Control","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Estimating the pressure-limited CO2 injection and storage capacity of the United States saline formations: Effect of the presence of hydrocarbon reservoirs","title":"Estimating the pressure-limited CO2 injection and storage capacity of the United States saline formations: Effect of the presence of hydrocarbon reservoirs","docAbstract":"The U.S. Geological Survey (USGS) national assessment of carbon dioxide (CO2) storage capacity evaluated 192 saline Storage Assessment Units (SAUs) in 33 U.S. onshore sedimentary basins that may be utilized for CO2 storage (see USGS Circular 1386). Similar to many other available models, volumetric analysis was utilized to estimate the initial CO2injection and storage capacity of these SAUs based on aquifer characteristics and buoyant and residual trapping. The factor being almost always overlooked in most CO2 storage capacity models is that many of the evaluated SAUs contain large numbers of both conventional and unconventional discovered and undiscovered oil and gas reservoirs. The hydrocarbon production and pressure distribution of the resident oil and gas reservoirs may be negatively influenced by the propagated CO2 plume and pressure front resulting from a CO2 injection and storage operation in the surrounding SAU.
To have a more realistic and accurate estimation of CO2 injection and storage capacity in saline formations, a model was previously developed that considers the CO2 injectivity of a given formation, underground pressure build-up limitations imposed by the rock fracturing pressure and the presence of hydrocarbon reservoirs within these aquifers. The developed method estimates the pre–brine extraction, pressure-limited CO2 injection and storage capacity of a saline formation by applying 3D numerical simulation only on the effective injection area (Aeff) surrounding each CO2 injection well utilizing TOUGH2-ECO2N simulation software.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ijggc.2018.09.011","usgsCitation":"Jahediesfanjani, H., Warwick, P., and Anderson, S.T., 2018, Estimating the pressure-limited CO2 injection and storage capacity of the United States saline formations: Effect of the presence of hydrocarbon reservoirs: International Journal of Greenhouse Gas Control, v. 79, p. 14-24, https://doi.org/10.1016/j.ijggc.2018.09.011.","productDescription":"11 p.","startPage":"14","endPage":"24","ipdsId":"IP-093110","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":468324,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ijggc.2018.09.011","text":"Publisher Index Page"},{"id":358344,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Sligo and Hosston Formations","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -99.82177734375,\n 26.941659545381516\n ],\n [\n -86.220703125,\n 26.941659545381516\n ],\n [\n -86.220703125,\n 34.52466147177172\n ],\n [\n -99.82177734375,\n 34.52466147177172\n ],\n [\n -99.82177734375,\n 26.941659545381516\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"79","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c10a920e4b034bf6a7e500b","contributors":{"authors":[{"text":"Jahediesfanjani, Hossein 0000-0001-6281-5166","orcid":"https://orcid.org/0000-0001-6281-5166","contributorId":201000,"corporation":false,"usgs":false,"family":"Jahediesfanjani","given":"Hossein","affiliations":[],"preferred":false,"id":748291,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Warwick, Peter D. 0000-0002-3152-7783","orcid":"https://orcid.org/0000-0002-3152-7783","contributorId":207248,"corporation":false,"usgs":true,"family":"Warwick","given":"Peter D.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":748290,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anderson, Steven T. 0000-0003-3481-3424 sanderson@usgs.gov","orcid":"https://orcid.org/0000-0003-3481-3424","contributorId":2532,"corporation":false,"usgs":true,"family":"Anderson","given":"Steven","email":"sanderson@usgs.gov","middleInitial":"T.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":748292,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70200124,"text":"70200124 - 2018 - Variability of organic carbon content and the retention and release of trichloroethene in the rock matrix of a mudstone aquifer","interactions":[],"lastModifiedDate":"2018-10-12T13:56:40","indexId":"70200124","displayToPublicDate":"2018-10-12T13:56:34","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2233,"text":"Journal of Contaminant Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Variability of organic carbon content and the retention and release of trichloroethene in the rock matrix of a mudstone aquifer","docAbstract":"Contaminants diffusing from fractures into the immobile porosity of the rock matrix are subject to prolonged residence times. Organic contaminants can adsorb onto organic carbonaceous materials in the matrix extending contaminant retention. An investigation of spatial variability of the fraction of organic carbon (foc) is conducted on samples of rock core from seven closely spaced boreholes in a mudstone aquifer contaminated with trichloroethene (TCE). A total of 378 samples were analyzed at depths between 14 and 36 m below land surface. Mudstone units associated with deep water deposition have the largest foc, with a maximum value of 0.0396, and units associated with shallow water deposition have the smallest foc. Even though foc correlates with depositional conditions, foc still varies over more than an order of magnitude in continuous mudstone layers between boreholes, and there is large variability in foc over short distances perpendicular to bedding. Simulations of diffusion and linear equilibrium adsorption of TCE using spatially variable foc in the rock matrix show order of magnitude variability in the adsorbed TCE over short distances in the matrix and residence times extending to hundreds of years following remediation in adjacent fractures. Simulations using average values of foc do not capture the range of TCE mass that can be retained in a rock matrix characterized by spatially variable foc. Bounds on TCE mass within the rock matrix can be obtained by simulations with spatially uniform values of focequal to the maximum and minimum values of foc for a given mudstone unit.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jconhyd.2018.09.001","usgsCitation":"Shapiro, A.M., and Brenneis, R.J., 2018, Variability of organic carbon content and the retention and release of trichloroethene in the rock matrix of a mudstone aquifer: Journal of Contaminant Hydrology, v. 217, p. 32-42, https://doi.org/10.1016/j.jconhyd.2018.09.001.","productDescription":"11 p.","startPage":"32","endPage":"42","ipdsId":"IP-097448","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":468325,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jconhyd.2018.09.001","text":"Publisher Index Page"},{"id":437719,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F75719Z7","text":"USGS data release","linkHelpText":"Organic and total carbon analyses of rock core collected from boreholes 83BR, 84BR, 85BR, 86BR, 87BR, 88BR, and 89BR in the mudstone underlying the former Naval Air Warfare Center, West Trenton, New Jersey"},{"id":358343,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Jersey","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.81951236724854,\n 40.26534772331598\n ],\n [\n -74.80661630630493,\n 40.26534772331598\n ],\n [\n -74.80661630630493,\n 40.27682455737567\n ],\n [\n -74.81951236724854,\n 40.27682455737567\n ],\n [\n -74.81951236724854,\n 40.26534772331598\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"217","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c10a920e4b034bf6a7e500e","contributors":{"authors":[{"text":"Shapiro, Allen M. 0000-0002-6425-9607 ashapiro@usgs.gov","orcid":"https://orcid.org/0000-0002-6425-9607","contributorId":2164,"corporation":false,"usgs":true,"family":"Shapiro","given":"Allen","email":"ashapiro@usgs.gov","middleInitial":"M.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":748286,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brenneis, Rebecca J.","contributorId":209022,"corporation":false,"usgs":false,"family":"Brenneis","given":"Rebecca","email":"","middleInitial":"J.","affiliations":[{"id":37550,"text":"Yale University","active":true,"usgs":false}],"preferred":false,"id":748287,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70198293,"text":"sim3412B - 2018 - Aeromagnetic map of Mountain Pass and vicinity, California and Nevada","interactions":[{"subject":{"id":70198293,"text":"sim3412B - 2018 - Aeromagnetic map of Mountain Pass and vicinity, California and Nevada","indexId":"sim3412B","publicationYear":"2018","noYear":false,"chapter":"B","title":"Aeromagnetic map of Mountain Pass and vicinity, California and Nevada"},"predicate":"IS_PART_OF","object":{"id":70199511,"text":"sim3412 - 2018 - Geophysical and geologic maps of Mountain Pass and vicinity, California and Nevada","indexId":"sim3412","publicationYear":"2018","noYear":false,"title":"Geophysical and geologic maps of Mountain Pass and vicinity, California and Nevada"},"id":1}],"isPartOf":{"id":70199511,"text":"sim3412 - 2018 - Geophysical and geologic maps of Mountain Pass and vicinity, California and Nevada","indexId":"sim3412","publicationYear":"2018","noYear":false,"title":"Geophysical and geologic maps of Mountain Pass and vicinity, California and Nevada"},"lastModifiedDate":"2018-10-15T13:00:57","indexId":"sim3412B","displayToPublicDate":"2018-10-11T13:56:23","publicationYear":"2018","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":"3412","chapter":"B","title":"Aeromagnetic map of Mountain Pass and vicinity, California and Nevada","docAbstract":"Magnetic investigations of Mountain Pass and vicinity were begun as part of an effort to study regional crustal structures as an aid to understanding the geologic framework and mineral resources of the eastern Mojave Desert. The study area, which straddles the state boundary between southeastern California and southern Nevada, encompasses Mountain Pass, which is host to one of the world’s largest rare earth element carbonatite deposits.
The deposit is found along a north-northwest-trending, fault-bounded block that extends along the eastern parts of the Clark Mountain Range, Mescal Range, and Ivanpah Mountains. This Paleoproterozoic block is composed of a 1.7-Ga metamorphic complex of gneiss and schist that underwent widespread metamorphism and associated plutonism during the Ivanpah orogeny. The Paleoproterozoic rocks were intruded by a Mesoproterozoic (1.4 Ga) ultrapotassic alkaline intrusive suite and carbonatite body. The intrusive rocks include, from oldest to youngest, shonkinite, mesosyenite, syenite, quartz syenite, potassic granite, carbonatite, carbonatite dikes, and late shonkinite dikes.
Generally speaking, magnetic anomalies reflect lateral changes in subsurface magnetization that can be used to infer subsurface geologic structure, revealing variations in lithology and delineating geologic features such as faults, plutons, volcanic rocks, calderas, and sedimentary basins.
A regional aeromagnetic map was derived from statewide aeromagnetic maps of California and Nevada that were compiled from numerous surveys flown at various flightline altitudes and spacings. This compilation, although composed of surveys acquired using different specifications, allows seamless interpretation of magnetic anomalies across survey boundaries.
In addition, a high-resolution aeromagnetic survey was flown by helicopter over parts of the Clark Mountain Range, Mescal Range, and Ivanpah Mountains. The resulting mapped magnetic anomalies show in much greater detail the complex subsurface structures in the Mountain Pass area.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3412B","usgsCitation":"Ponce, D.A., and Denton, K.M. (D.A. Ponce, ed.), 2018, Aeromagnetic map of Mountain Pass and vicinity, California and Nevada: U.S. Geological Survey Scientific Investigations Map 3412–B, scale 1:62,500, https://doi.org/10.3133/sim3412B.","productDescription":"Sheet: 44.05 x 30.24 inches; Data Releases","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-099318","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":357531,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P92XVOOF","text":"USGS Data Release","description":"USGS data release","linkHelpText":"High-resolution aeromagnetic survey of Mountain Pass, California"},{"id":357529,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3412/b/coverthb.jpg"},{"id":357530,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3412/b/sim3412b.pdf","text":"Report","size":"19 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3412-B"}],"country":"United States","state":"California, Nevada","otherGeospatial":"Mountain Pass","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.75,\n 35.2833\n ],\n [\n -115.25,\n 35.2833\n ],\n [\n -115.25,\n 35.6167\n ],\n [\n -115.75,\n 35.6167\n ],\n [\n -115.75,\n 35.2833\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Geology, Minerals, Energy, & Geophysics Science Center
Menlo Park, California
U.S. Geological Survey
345 Middlefield Road
Menlo Park, CA 94025-3591
Gravity investigations of Mountain Pass and vicinity were begun as part of an effort to study regional crustal structures as an aid to understanding the geologic framework and mineral resources of the eastern Mojave Desert. The study area, which straddles the state boundary between southeastern California and southern Nevada, encompasses Mountain Pass, which is host to one of the world’s largest rare earth element carbonatite deposits.
The deposit is found along a north-northwest-trending, fault-bounded block that extends along the eastern parts of the Clark Mountain Range, Mescal Range, and Ivanpah Mountains. This Paleoproterozoic block is composed of a 1.7-Ga metamorphic complex of gneiss and schist that underwent widespread metamorphism and associated plutonism during the Ivanpah orogeny. The Paleoproterozoic rocks were intruded by a Mesoproterozoic (1.4 Ga) ultrapotassic alkaline intrusive suite and carbonatite body. The intrusive rocks include, from oldest to youngest, shonkinite, mesosyenite, syenite, quartz syenite, potassic granite, carbonatite, carbonatite dikes, and late shonkinite dikes.
Generally speaking, gravity anomalies can be used to infer subsurface geologic structure, revealing variations in lithology and delineating features such as faults, plutons, volcanic centers, calderas, and deep sedimentary basins.
As part of this study, gravity data from more than 2,400 stations were collected and processed to identify lateral changes in subsurface density. Gravity stations were distributed across parts of Shadow Valley, Clark Mountain Range, Mescal Range, Ivanpah Mountains, and Ivanpah Valley. The new gravity data were combined with preexisting gravity data from the surrounding areas in California and Nevada. All gravity data were gridded using a minimum curvature algorithm at an interval of 200 m, and the result is displayed as a color-contour isostatic gravity map.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3412A","usgsCitation":"Ponce, D.A., and Denton, K.M. (D.A. Ponce, ed.), 2018, Isostatic gravity map of Mountain Pass and vicinity, California and Nevada: U.S. Geological Survey Scientific Investigations Map 3412–A, scale 1:62,500, https://doi.org/10.3133/sim3412A.","productDescription":"44.06 x 30.24 inches","onlineOnly":"Y","ipdsId":"IP-095950","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":357499,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3412/a/coverthb.jpg"},{"id":357500,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3412/a/sim3412a.pdf","text":"Report","size":"23 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3412-A"}],"country":"United States","state":"California, Nevada","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.75,\n 35.2833\n ],\n [\n -115.25,\n 35.2833\n ],\n [\n -115.25,\n 35.6167\n ],\n [\n -115.75,\n 35.6167\n ],\n [\n -115.75,\n 35.2833\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Geology, Minerals, Energy, & Geophysics Science Center
Menlo Park, California
U.S. Geological Survey
345 Middlefield Road
Menlo Park, CA 94025-3591
U.S. Geological Survey Scientific Investigations Map 3412 is a series of products that consists of geophysical and geologic maps of Mountain Pass and vicinity, California. Maps A and B (red outline in above map image) are gravity and aeromagnetic maps, respectively. The map series was begun as part of an effort to study regional crustal structures as an aid to understanding the geologic framework and mineral resources of the southeast Mojave Desert.
Mountain Pass resides within the southeast Mojave Desert, and it is host to a one of the world’s largest rare earth element carbonatite deposits. The deposit is found along a north-northwest- trending, fault-bounded block that extends along the eastern parts of the Clark Mountain Range, Mescal Range, and Ivanpah Mountains. This Paleoproterozoic block is composed of a 1.7-Ga metamorphic complex of gneiss and schist that underwent widespread metamorphism and associated plutonism during the Ivanpah orogeny. The Paleoproterozoic rocks were intruded by a Mesoproterozoic (1.4 Ga) ultrapotassic alkaline intrusive suite and carbonatite body. The intrusive rocks include, from oldest to youngest, shonkinite, mesosyenite, syenite, quartz syenite, potassic granite, carbonatite, carbonatite dikes, and late shonkinite dikes.
Each map in the series provides the basis for geophysical and geologic interpretations of the Mountain Pass carbonatite terrane. Combined, they provide a comprehensive framework of the regional subsurface geologic structure of the area. Together, they form the first publicly available series of geophysical and geologic maps of this part of the southeast Mojave Desert.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3412","productDescription":"Map","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":357545,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3412/sim3412_map.pdf","text":"Simplified geological map of study area","size":"900 KB","linkFileType":{"id":1,"text":"pdf"}},{"id":357521,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3412/coverthb.jpg"}],"country":"United States","state":"California, Nevada","otherGeospatial":"Mountain Pass","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.75,\n 35.25\n ],\n [\n -115.25,\n 35.25\n ],\n [\n -115.25,\n 35.625\n ],\n [\n -115.75,\n 35.625\n ],\n [\n -115.75,\n 35.25\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Geology, Minerals, Energy, & Geophysics Science Center
Menlo Park, California
U.S. Geological Survey
345 Middlefield Road
Menlo Park, CA 94025-3591