Since the 2018 eruption of Kīlauea Volcano, the topic of whether commercial developments not only caused the eruption to occur in the lower East Rift Zone (LERZ), but also caused its high eruption rate has been a subject of public discussion. We review Kīlauea Volcano publications from the past several decades and show that the eruptive behavior of the volcano has varied and that the 2018 eruption was similar to past eruptions in many ways. We find no evidence to support any human influence on Kīlauea Volcano.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201017","usgsCitation":"Kauahikaua, J. and Trusdell, F., 2020, Have humans influenced volcanic activity on the lower East Rift Zone of Kīlauea Volcano? A publication review: U.S. Geological Survey Open-File Report 2020–1017, 17 p., https://doi.org/10.3133/ofr20201017.","productDescription":"iv, 17","numberOfPages":"17","onlineOnly":"Y","ipdsId":"IP-111187","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":372511,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1017/ofr20201017.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1017"},{"id":372510,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1017/coverthb.jpg"},{"id":399456,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109729.htm"}],"country":"United States","state":"Hawaii","otherGeospatial":"Lower East Rift Zone of Kīlauea Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.3741455078125,\n 19.19835036116298\n ],\n [\n -155.26016235351562,\n 19.281332062593734\n ],\n [\n -155.20523071289062,\n 19.26059057084779\n ],\n [\n -155.14892578125,\n 19.264479800497103\n ],\n [\n -155.0665283203125,\n 19.30466310133747\n ],\n [\n -154.9456787109375,\n 19.37334071336406\n ],\n [\n -154.82070922851562,\n 19.474360774988355\n ],\n [\n -154.80422973632812,\n 19.530024424775405\n ],\n [\n -154.92233276367188,\n 19.596019240312494\n ],\n [\n -154.9456787109375,\n 19.621892180319374\n ],\n [\n -154.97177124023438,\n 19.641294152538578\n ],\n [\n -154.97177124023438,\n 19.676211792974332\n ],\n [\n -155.050048828125,\n 19.590844152960923\n ],\n [\n -155.12832641601562,\n 19.520964205879825\n ],\n [\n -155.18875122070312,\n 19.449759112405612\n ],\n [\n -155.26565551757812,\n 19.42256346067618\n ],\n [\n -155.35629272460938,\n 19.359089245934307\n ],\n [\n -155.38787841796872,\n 19.299478713495898\n ],\n [\n -155.4071044921875,\n 19.23206673568465\n ],\n [\n -155.4071044921875,\n 19.19186565046399\n ],\n [\n -155.3741455078125,\n 19.19835036116298\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Contacts, Hawaiian Volcano Observatory
U.S. Geological Survey
1266 Kamehameha Avenue, Suite A-8
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To update and expand a part of the Federal Emergency Management Agency Flood Insurance Study, the U.S. Geological Survey, the Muskingum Watershed Conservancy District, and the Stark County Commissioners began a cooperative study. The study consisted of hydrologic and hydraulic analyses for selected reaches of 14 streams in Stark County, Ohio: Broad-Monter Creek, Chatham Ditch, East Branch Nimishillen Creek, Fairhope Ditch, Firestone Ditch, Hayden Ditch, Middle Branch Nimishillen Creek, Middle Branch Nimishillen Creek Tributary Number 1, Nimishillen Creek, Reemsnyder Ditch, Sherrick Run, unnamed stream, West Branch Nimishillen Creek, and Zimber Ditch. The study totaled nearly 50 miles of stream reaches.
Instantaneous peak streamflows for floods with 10-, 4-, 2-, 1-, and 0.2-percent and 1-percent plus annual exceedance probabilities were estimated using historical streamflow data from the streamgages Nimishillen Creek at North Industry, Ohio (U.S. Geological Survey station number 03118500), and Middle Branch Nimishillen Creek at Canton, Ohio (U.S. Geological Survey station number 03118000), regional flood regression equations, and streamflow urbanization techniques.
The annual exceedance probability streamflows were then used in a Hydrologic Engineering Center-River Analysis System step-backwater model to determine water-surface profiles, flood-inundation boundaries for the 10-, 4-, 2-, 1-, and 0.2-percent and 1-percent plus annual exceedance probability floods, and a regulatory floodway along a selected reach of each stream. Model input included DEM-derived cross sections supplemented with field surveys of open channel cross sections and hydraulic structures, field estimates of roughness values, and annual exceedance probability flood estimates from regional regression equations and historical streamflow data. Flood-inundation boundaries were mapped for the 1- and 0.2-percent annual exceedance probability floods and a regulatory floodway for each stream reach.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205011","collaboration":"Prepared in cooperation with Stark County and the Muskingum Watershed Conservancy District","usgsCitation":"Ostheimer, C.J. and Whitehead, M.T, 2020, Hydrologic and hydraulic analyses of selected streams in Stark County, Ohio: U.S. Geological Survey Scientific Investigations Report 2020–5011, 15 p., https://doi.org/10.3133/sir20205011.","productDescription":"Report: iv, 15 p.; 4 Appendixes; Data Release","numberOfPages":"24","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-106471","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":399632,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109726.htm"},{"id":372523,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5011/coverthb.jpg"},{"id":372525,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2020/5011/sir20205011_appendix1.pdf","text":"Appendix 1","size":"3.09 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5011 Appendix 1","linkHelpText":"– Technical Support Data Notebook"},{"id":372526,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2020/5011/sir20205011_appendix2.pdf","text":"Appendix 2","size":"780 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5011 Appendix 2","linkHelpText":"– Floodway data tables"},{"id":372524,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5011/sir20205011.pdf","text":"Report","size":"1.25 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5011"},{"id":372527,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2020/5011/sir20205011_appendix3.pdf","text":"Appendix 3","size":"1.97 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5011 Appendix 3","linkHelpText":"– Water-surface profiles"},{"id":372528,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2020/5011/sir20205011_appendix4.pdf","text":"Appendix 4","size":"8.48 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5011 Appendix 4","linkHelpText":"– Flood-inundation maps"},{"id":372529,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9YQJ8B7","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Geospatial datasets and hydraulic models for selected streams in Stark County, Ohio"}],"country":"United States","state":"Ohio","county":"Stark County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-81.0864,40.9879],[-81.0865,40.9839],[-81.0866,40.978],[-81.0869,40.9013],[-81.0873,40.728],[-81.0922,40.7285],[-81.1001,40.7281],[-81.1989,40.7292],[-81.1991,40.7224],[-81.2373,40.7237],[-81.241,40.6507],[-81.2755,40.651],[-81.2791,40.6511],[-81.304,40.6518],[-81.3173,40.6519],[-81.4372,40.6529],[-81.4365,40.6584],[-81.4395,40.6625],[-81.4467,40.6657],[-81.4589,40.6654],[-81.4675,40.6555],[-81.6489,40.6346],[-81.6491,40.6681],[-81.6483,40.7371],[-81.648,40.9145],[-81.4201,40.9064],[-81.4164,40.9889],[-81.3932,40.9887],[-81.1059,40.9882],[-81.0925,40.988],[-81.0864,40.9879]]]},\"properties\":{\"name\":\"Stark\",\"state\":\"OH\"}}]}","contact":"Director, Ohio-Kentucky-Indiana Water Science Center
U.S. Geological Survey
6460 Busch Boulevard Suite 100
Columbus, OH 43229–1737
Among the hazards posed by volcanoes are the emissions of gases and particles that can affect air quality and damage agriculture and infrastructure. A recent intense episode of volcanic degassing associated with severe impacts on air quality accompanied the 2018 lower East Rift Zone (LERZ) eruption of Kīlauea volcano, Hawai'i. This resulted in a major increase in gas emission rates with respect to usual emission values for this volcano, along with a shift in the source of the dominant plume to a populated area on the lower flank of the volcano. This led to reduced air quality in downwind communities. We analyse open-access data from the permanent air quality monitoring networks operated by the Hawai'i Department of Health (HDOH) and National Park Service (NPS), and report on measurements of atmospheric sulfur dioxide (SO2) between 2007 and 2018 and PM2.5 (aerosol particulate matter with diameter <2.5 μm) between 2010 and 2018. Additional air quality data were collected through a community-operated network of low-cost PM2.5 sensors during the 2018 LERZ eruption. From 2007 to 2018 the two most significant escalations in Kīlauea's volcanic emissions were: the summit eruption that began in 2008 (Kīlauea emissions averaged 5–6 kt/day SO2 from 2008 until summit activity decreased in May 2018) and the LERZ eruption in 2018 when SO2 emission rates reached a monthly average of 200 kt/day during June. In this paper we focus on characterizing the airborne pollutants arising from the 2018 LERZ eruption and the spatial distribution and severity of volcanic air pollution events across the Island of Hawai'i. The LERZ eruption caused the most frequent and severe exceedances of the Environmental Protection Agency (EPA) PM2.5 air quality threshold (35 μg/m3 as a daily average) in Hawai'i in the period 2010–2018. In Kona, for example, the maximum 24-h-mean mass concentration of PM2.5 was recorded as 59 μg/m3 on the twenty-ninth of May 2018, which was one of eight recorded exceedances of the EPA air quality threshold during the 2018 LERZ eruption, where there had been no exceedances in the previous 8 years as measured by the HDOH and NPS networks. SO2 air pollution during the LERZ eruption was most severe in communities in the south and west of the island, as measured by selected HDOH and NPS stations in this study, with a maximum 24-h-mean mass concentration of 728 μg/m3 recorded in Ocean View (100 km west of the LERZ emission source) in May 2018. Data from the low-cost sensor network correlated well with data from the HDOH PM2.5 instruments, confirming that these low-cost sensors provide a robust means to augment reference-grade instrument networks.
As runoff flows over the land or impervious surfaces (paved streets, parking lots, and building roofs), it accumulates debris, chemicals, sediment, and other contaminants that can adversely affect water quality if the runoff discharge remains untreated. Pathogens, commonly measured using fecal indicator bacteria such as Escherichia coli, enterococci, or fecal coliform, are the most-frequent cause of water-quality impairment in rivers and streams in the United States. Rapid Creek originates in the western Black Hills area and flows east through Rapid City, South Dakota, to its mouth at the Cheyenne River. The water quality of Rapid Creek is important because the reach that flows through Rapid City is a valuable spawning area for a self-sustaining trout fishery, is actively used for recreation, and is a seasonal municipal water supply for the City of Rapid City. These uses (fishery, recreation, and water supply) are considered beneficial uses by the South Dakota Department of Environment and Natural Resources. Numerical criteria have been established for total suspended solids and Escherichia coli concentrations, among other water-quality constituents, for these beneficial uses. The objectives of this study were to improve the method by which fecal indicator bacteria and total suspended solids are quantified in the urban drainages within Rapid City and to provide information that helps identify origins of fecal indicator bacteria and total suspended solids. This information can be used in hydrologic models to estimate fecal indicator bacteria and total suspended solid loading from certain infrastructure elements in urban environments.
Stormwater samples analyzed for Escherichia coli, total suspended solids, specific conductance, and pH were collected in three drainage basin flowpaths within Rapid City: Jackson, Wildwood, and the Eco Prayer Park. Data-collection activities for this study focused on upgradient urban flowpath elements during rainfall events. This approach builds upon previous stormwater assessments that characterized the water quality in urban basin outlets near the downstream end of the stormwater flowpaths. Within each flowpath group, 4–6 sites were selected to represent the various infrastructure elements of the runoff process. These elements included roof downspouts, parking lots, street curbs and gutters, open channels, underground storm sewers, and stormwater ponds or best-management practice facilities.
In general, the concentrations of Escherichia coli and total suspended solids increased in the downstream direction for all flowpath sites. The wash-off process after the first flush is evident for total suspended solids and specific conductance; however, Escherichia coli concentrations did not necessarily follow the same pattern. Escherichia coli concentrations in the latter part of the runoff period were similar to or greater than the initial concentrations of the first set of samples. Stormwater-quality data were summarized by infrastructure type (roof downspout, parking lot, street curb, and channel/storm sewer) to provide information about approximate water-quality concentrations originating at the upper end of urban flowpaths. Escherichia coli and total suspended solid concentrations were lowest in samples collected from locations most isolated from human influence (roof downspouts); the median concentrations at these sites were 4 most probable number per 100 milliliters and 15 milligrams per liter, respectively. The delivery potential of fecal indicator bacteria and sediment from parking lots and street curbs was similar; median concentrations of Escherichia coli and total suspended solids were around 150–220 most probable number per 100 milliliters and 56–86 milligrams per liter, respectively. The downstream receiving channels and storm sewers where stormwater was aggregated typically contained the highest Escherichia coli concentrations (median was 1,800 most probable number per 100 milliliters), but the total suspended solid concentrations were similar to upstream elements in the flowpath (median was 69 milligrams per liter). The data collected from this study demonstrate that stormwater is contaminated with fecal indicator bacteria upon initial contact with impervious surfaces and highlight the importance of controlling the volume of stormwater discharges into receiving waterbodies via storage structures and pervious elements. Diluting stormwater with high concentrations of Escherichia coli with the receiving water’s (Rapid Creek) lower concentration of Escherichia coli is likely the primary mechanism for meeting the beneficial-use criterion threshold of 235 most probable number per 100 milliliters. Although total suspended solid concentrations in the upper parts of the basin (parking lots and street curbs) also begin at concentrations (56 to 86 milligrams per liter) above the beneficial-use criterion for Rapid Creek (53 milligrams per liter), current stormwater-control practices (storage ponds, swales, and wetlands) may be able to reduce suspended-sediment concentrations to meet this threshold.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205004","collaboration":"Prepared in cooperation with the City of Rapid City","usgsCitation":"Hoogestraat, G.K., 2020, Stormwater quality of infrastructure elements in Rapid City, South Dakota, 2016–18: U.S. Geological Survey Scientific Investigations Report 2020–5004, 24 p., https://doi.org/10.3133/sir20205004.","productDescription":"Report: vii, 24 p.; Appendix; Dataset","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-108184","costCenters":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":399627,"rank":5,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109723.htm"},{"id":372437,"rank":4,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"National Water Information System database","linkHelpText":"– USGS water data for the Nation"},{"id":372436,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2020/5004/sir20205004_appendix1.csv","text":"Appendix 1","size":"12.8 kB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2020–5004 Appendix 1"},{"id":372434,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5004/coverthb.jpg"},{"id":372435,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5004/sir20205004.pdf","text":"Report","size":"3.50 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5004"}],"country":"United States","state":"South Dakota","city":"Rapid City","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -103.32,\n 44.0111\n ],\n [\n -103.1364,\n 44.0111\n ],\n [\n -103.1364,\n 44.125\n ],\n [\n -103.32,\n 44.125\n ],\n [\n -103.32,\n 44.0111\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Dakota Water Science Center
U.S. Geological Survey
821 East Interstate Avenue
Bismarck, ND 58503
1608 Mountain View Road
Rapid City, SD 57702
We present new 3-D P wave and S wave velocity models of the upper 20 km of the Mount St. Helens (MSH) region. These were obtained using local-source arrival time tomography from earthquakes and explosions recorded at 70 broadband stations deployed as part of the imaging Magma Under St. Helens (iMUSH) project and augmented by several data sets. Principal features of our models include (1) low P wave and S wave velocities along the St. Helens seismic zone to depths of at least 20 km corresponding to high conductivity imaged by iMUSH magnetotelluric studies. This delineates a zone of weakness that magma can exploit at the location of MSH; (2) a 5- to 7-km diameter, 6–15 km deep, 3–6% negative P wave and S wave velocity anomaly beneath MSH, consistent with previous estimates of the source region for recent eruptions. We interpret this as a magma storage region containing up to 15–20 km3 of partial melt, which is about 5 times more than the largest documented eruption at MSH; (3) a broad region of low P wave velocity below 10-km depth extending between Mount Adams and Mount Rainier along and to the east of the main Cascade arc, which is likely due to high-temperature arc crust and possible presence of fluids or melt; (4) several anomalies associated with surface-mapped features, including high-velocity igneous units such as the Spud Mountain and Spirit Lake plutons and low velocities in the Chehalis sedimentary basin and the Indian Heaven volcanic field. Our results place further constraints on the geometry of these features at depth.
Hellbenders Cryptobranchus alleganiensis are critically imperiled amphibians throughout the eastern USA. Rock-lifting is widely used to monitor hellbenders but can severely disturb habitat. We asked whether artificial shelter occupancy (the proportion of occupied shelters in an array) would function as a proxy for hellbender abundance and thereby serve as a viable alternative to rock-lifting. We hypothesized that shelter occupancy would vary spatially in response to hellbender density, natural shelter density, or both, and would vary temporally with hellbender seasonal activity patterns and time since shelter deployment. We established shelter arrays (n = 30 shelters each) in 6 stream reaches and monitored them monthly for up to 2 yr. We used Bayesian mixed logistic regression and model ranking criteria to assess support for hypotheses concerning drivers of shelter occupancy. In all reaches, shelter occupancy was highest from June-August each year and was higher in Year 2 relative to Year 1. Our best-supported model indicated that the extent of boulder and bedrock (hereafter, natural shelter) in a reach mediated the relationship between hellbender abundance and shelter occupancy. More explicitly, shelter occupancy was positively correlated with abundance when natural shelter covered <20% of a reach, but uncorrelated with abundance when natural shelter was more abundant. While shelter occupancy should not be used to infer variation in hellbender relative abundance when substrate composition varies among reaches, we showed that artificial shelters can function as valuable monitoring tools when reaches meet certain criteria, though regular shelter maintenance is critical.
","language":"English","publisher":"Inter-Research Science Publisher","doi":"10.3354/esr01014","usgsCitation":"Bodinof Jachowski, C.M., Ross, B., and Hopkins, W., 2020, Evaluating artificial shelter arrays as a minimally invasive monitoring tool for the hellbender Cryptobranchus alleganiensis: Endangered Species Research, v. 41, p. 167-181, https://doi.org/10.3354/esr01014.","productDescription":"15 p.","startPage":"167","endPage":"181","ipdsId":"IP-107334","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":457730,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/esr01014","text":"Publisher Index Page"},{"id":395435,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Virginia","otherGeospatial":"upper Tennessee River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.50732421875,\n 36.56260003738545\n ],\n [\n -80.540771484375,\n 36.56260003738545\n ],\n [\n -80.540771484375,\n 37.26530995561875\n ],\n [\n -82.50732421875,\n 37.26530995561875\n ],\n [\n -82.50732421875,\n 36.56260003738545\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"41","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bodinof Jachowski, C. M.","contributorId":274670,"corporation":false,"usgs":false,"family":"Bodinof Jachowski","given":"C.","email":"","middleInitial":"M.","affiliations":[{"id":36967,"text":"Virginia Tech University","active":true,"usgs":false}],"preferred":false,"id":833211,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ross, Beth 0000-0001-5634-4951 bross@usgs.gov","orcid":"https://orcid.org/0000-0001-5634-4951","contributorId":199242,"corporation":false,"usgs":true,"family":"Ross","given":"Beth","email":"bross@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":833212,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hopkins, W.A.","contributorId":274671,"corporation":false,"usgs":false,"family":"Hopkins","given":"W.A.","email":"","affiliations":[{"id":36967,"text":"Virginia Tech University","active":true,"usgs":false}],"preferred":false,"id":833213,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70208316,"text":"pp1824I - 2020 - Geology and assessment of undiscovered oil and gas resources of the Sverdrup Basin Province, Arctic Canada, 2008","interactions":[{"subject":{"id":70208316,"text":"pp1824I - 2020 - Geology and assessment of undiscovered oil and gas resources of the Sverdrup Basin Province, Arctic Canada, 2008","indexId":"pp1824I","publicationYear":"2020","noYear":false,"chapter":"I","displayTitle":"Geology and Assessment of Undiscovered Oil and Gas Resources of the Sverdrup Basin Province, Arctic Canada, 2008","title":"Geology and assessment of undiscovered oil and gas resources of the Sverdrup Basin Province, Arctic Canada, 2008"},"predicate":"IS_PART_OF","object":{"id":70193865,"text":"pp1824 - 2017 - The 2008 Circum-Arctic Resource Appraisal ","indexId":"pp1824","publicationYear":"2017","noYear":false,"title":"The 2008 Circum-Arctic Resource Appraisal "},"id":1}],"isPartOf":{"id":70193865,"text":"pp1824 - 2017 - The 2008 Circum-Arctic Resource Appraisal ","indexId":"pp1824","publicationYear":"2017","noYear":false,"title":"The 2008 Circum-Arctic Resource Appraisal "},"lastModifiedDate":"2024-06-26T14:17:30.038365","indexId":"pp1824I","displayToPublicDate":"2020-02-11T10:01:38","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":331,"text":"Professional Paper","code":"PP","onlineIssn":"2330-7102","printIssn":"1044-9612","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1824","chapter":"I","displayTitle":"Geology and Assessment of Undiscovered Oil and Gas Resources of the Sverdrup Basin Province, Arctic Canada, 2008","title":"Geology and assessment of undiscovered oil and gas resources of the Sverdrup Basin Province, Arctic Canada, 2008","docAbstract":"The Sverdrup Basin Province, an area of 515,000 square kilometers on the northern margin of North America, extends 1,300 kilometers across the Canadian Arctic Islands from near the Mackenzie Delta to northern Ellesmere Island. It consists of an intracratonic late Paleozoic to early Cenozoic rift-sag basin and a Mesozoic rift shoulder that bounds it on the north.
Basin inception was Mississippian, manifested by deposition of nonmarine strata in rift basins, followed by Pennyslvanian marine transgression, which began with evaporites and progressed to Permian carbonate and clastic deposition at basin fringes and organic-rich marine strata in the basin center. Sediment transport was both northward from North America and southward from a now-subsided or rifted-away landmass to the north. Mesozoic strata indicate continued marine deposition, including both organic-rich, fine-grained rocks deposited during highstands and progradational deltaic sequences. A new episode of rifting began in Middle Jurassic time and culminated in the opening of the Canada Basin by Early Cretaceous seafloor spreading. The Sverdrup Rim formed as the rift shoulder between North America and the thinned, subsided crust to the north. Widespread Upper Cretaceous organic-rich shales were deposited during the major transgression induced by Canada Basin opening, followed by an influx of coarser east-derived detritus. In Paleogene time, incipient North Atlantic seafloor spreading caused deformation in northeasternmost North America, producing uplifts that shed detritus westward across the Sverdrup Basin. Tight folding and thrusting resulting from the Eurekan orogeny took place in the eastern part of the basin during the Eocene, with decreasing intensity of deformation westward. Since deformation ended in late Eocene time, little significant tectonism or deposition has taken place.
Two petroleum systems were defined in the Sverdrup Basin Province. Upper Paleozoic marine shale generated petroleum beginning in the Early Triassic, but this petroleum system was not quantitatively assessed because reservoir quality in adjacent strata is poor, the rocks are mostly overmature, and subsequent deformation likely affected trap integrity. The second petroleum system was sourced by Lower Triassic strata rich in oil-prone organic matter. Oil was generated during Paleogene burial synchronous with Eurekan deformation, and the oil migrated into Triassic and Jurassic deltaic, shallow marine and nonmarine strata. However, most of the oil may have escaped during deformation and subsequent uplift and erosion, which probably caused oil to be displaced from traps by gas expansion. The population of undiscovered accumulations was characterized as likely to include stratigraphically trapped and small, structurally trapped accumulations, with a median size of 80 million barrels of oil (MMBO); the number of undiscovered accumulations was estimated to be between 1 and 50, with the most likely number being 10. The resulting estimate of undiscovered, technically recoverable, conventional oil resources is 61 to 1,255 MMBO, with a mean of 427 MMBO. Undiscovered, technically recoverable, conventional gas resources are estimated at 4.95 trillion cubic feet (TCF), with slightly more than half of that in nonassociated gas accumulations.
A third petroleum system in the adjacent Amerasia Basin Province to the north was considered somewhat likely to contain accumulations on the Sverdrup Rim. Deeply buried Upper Jurassic, Upper Cretaceous, and Eocene organic-rich strata probably generated oil that may have migrated up the continental slope into Triassic to Paleogene sandstones on the Sverdrup Rim. Based on analogy with the Barrow Arch in Alaska, a median of 20 accumulations was estimated, with accumulation volumes as much as 2,500 MMBO and a median of 100 MMBO. The probability of at least one accumulation of the minimum size assessed (50 MMBO) was estimated at 0.22. The resulting estimate of undiscovered, technically recoverable, conventional oil resources is 0 to 2,679 MMBO, with a mean of 424 MMBO. Mean estimates for associated and nonassociated gas are 1.3 and 2.3 TCF, respectively.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1824I","usgsCitation":"Tennyson, M.E., and Pitman, J.K., 2020, Geology and assessment of undiscovered oil and gas resources of the Sverdrup Basin Province, Arctic Canada, 2008, chap. I of Moore, T.E., and Gautier, D.L., eds., The 2008 Circum-Arctic Resource Appraisal: U.S. Geological Survey Professional Paper 1824, 21 p., https://doi.org/10.3133/pp1824I.","productDescription":"Report: vi, 21 p.; 3 appendixes","numberOfPages":"21","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-062463","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":372144,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1824/i/pp1824i.pdf","text":"Report"},{"id":372233,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1824/i/coverthb.jpg"},{"id":372236,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/pp/1824/i/pp1824i_appendix3.xls","text":"Appendix 3","size":"50 KB","linkFileType":{"id":3,"text":"xlsx"},"linkHelpText":"- Assessment input data for the Banks Island-Sverdrup Rim Assessment Unit."},{"id":372235,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/pp/1824/i/pp1824i_appendix2.xls","text":"Appendix 2","size":"50 KB","linkFileType":{"id":3,"text":"xlsx"},"linkHelpText":"- Assessment input data for the Sverdrup Mesozoic Assessment Unit."},{"id":372234,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/pp/1824/i/pp1824i_appendix1.xls","text":"Appendix 1","size":"50 KB","linkFileType":{"id":3,"text":"xlsx"},"linkHelpText":"- Assessment input data for the Sverdrup Upper Paleozoic Assessment Unit."}],"country":"Canada, United States","otherGeospatial":"Sverdrup Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.98242187499999,\n 74.09197431391087\n ],\n [\n -111.796875,\n 75.84516854027044\n ],\n [\n -95.625,\n 74.59010800882325\n ],\n [\n -82.265625,\n 77.54209596075547\n ],\n [\n -74.53125,\n 82.1183836069127\n ],\n [\n -91.7578125,\n 81.30832090051811\n ],\n [\n -82.265625,\n 83.1110709962606\n ],\n [\n -101.25,\n 81.4139332828511\n ],\n [\n -121.28906250000001,\n 77.31251993823143\n ],\n [\n -148.359375,\n 70.1403642720717\n ],\n [\n -144.4921875,\n 69.77895177646761\n ],\n [\n -130.4296875,\n 71.18775391813158\n ],\n [\n -116.98242187499999,\n 74.09197431391087\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Contact Information,
Geology, Minerals, Energy, & Geophysics Science Center—Menlo Park
U.S. Geological Survey
345 Middlefield Road
Menlo Park, CA 94025-3591
FAX 650-329-4936
The US Fish and Wildlife Service has initiated a re-envisioned approach for providing decision makers with the best available science and synthesis of that information, called the Species Status Assessment (SSA), for endangered species decision making. The SSA report is a descriptive document that provides decision makers with an assessment of a species’ current status and predicted future status. These analyses support all manner of decisions under the US Endangered Species Act, such as listing, reclassification, recovery planning, etc. Novel scientific analysis and predictive modeling in SSAs could be an important part of rooting species conservation decisions in current data and cutting edge analytical and modeling techniques. Here we describe a novel analysis of available data to assess current condition of eastern black rail across its range in a dynamic occupancy analysis. We used the results of the analysis to develop a site occupancy projection model where the model parameters (initial occupancy, site persistence, colonization) were linked to environmental covariates, such as land management and land cover change (sea-level rise, development, etc.). We used the projection model to predict future conditions under multiple sea-level rise and habitat management scenarios. Occupancy probability and site colonization were low in all analysis units and site persistence was also low, suggesting low resiliency and redundancy currently. Extinction probability was high for all analysis units in all simulated scenarios except one with significant effort to preserve existing habitat, suggesting low future resiliency and redundancy. With results of these data analyses and predictive modeling, the US Fish and Wildlife Service concluded that protections of the Endangered Species Act were warranted for this subspecies.
","language":"English","publisher":"Inter-Research","doi":"10.3354/esr01063","usgsCitation":"McGowan, C.P., Angeli, N., Beisler, W., Snyder, C., Rankin, N., Woodrow, J., Wilson, J., Rivenbark, E., Schwarzer, A., Hand, C., Anthony, R., Griffin, R., Barrett, K., Haverland, A., Roach, N., Schneider, T., Smith, A.J., Smith, F., Tolliver, J., and Watts, B.D., 2020, Linking monitoring and data analysis to predictions and decisions for the range-wide eastern black rail status assessment: Endangered Species Research, v. 43, p. 209-222, https://doi.org/10.3354/esr01063.","productDescription":"14 p.","startPage":"209","endPage":"222","ipdsId":"IP-111624","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":457761,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/esr01063","text":"Publisher Index 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J.","contributorId":67040,"corporation":false,"usgs":false,"family":"Smith","given":"A.","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":834433,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Smith, F.","contributorId":275953,"corporation":false,"usgs":false,"family":"Smith","given":"F.","affiliations":[{"id":6686,"text":"College of William and Mary","active":true,"usgs":false}],"preferred":false,"id":834434,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Tolliver, J.","contributorId":275957,"corporation":false,"usgs":false,"family":"Tolliver","given":"J.","email":"","affiliations":[{"id":6677,"text":"Texas State University","active":true,"usgs":false}],"preferred":false,"id":834435,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Watts, Bryan D","contributorId":243507,"corporation":false,"usgs":false,"family":"Watts","given":"Bryan","email":"","middleInitial":"D","affiliations":[],"preferred":false,"id":834436,"contributorType":{"id":1,"text":"Authors"},"rank":20}]}} ,{"id":70219032,"text":"70219032 - 2020 - Oil-source rock correlation studies in the unconventional Upper Cretaceous Tuscaloosa marine shale (TMS) petroleum system, Mississippi and Louisiana, USA","interactions":[],"lastModifiedDate":"2021-03-22T12:07:49.855628","indexId":"70219032","displayToPublicDate":"2020-02-11T06:55:54","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2419,"text":"Journal of Petroleum Science and Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Oil-source rock correlation studies in the unconventional Upper Cretaceous Tuscaloosa marine shale (TMS) petroleum system, Mississippi and Louisiana, USA","docAbstract":"The U.S. Geological Survey assessed undiscovered unconventional hydrocarbon resources reservoired in the Upper Cretaceous Tuscaloosa marine shale (TMS) of southern Mississippi and adjacent Louisiana in 2018. As part of the assessment, oil-source rock correlations were examined in the TMS play area where operators produce light (38–45° API), sweet oil from horizontal, hydraulically-fractured wells in an overpressured ‘high-resistivity’ (>5 Ω-m) zone at the base of the TMS. Geochemical data from 39 oil samples and 17 source rock solvent extracts collected from the TMS play area indicate close correspondence for Tuscaloosa Group oils [from lower Tuscaloosa, middle Tuscaloosa (the TMS) and upper Tuscaloosa reservoirs] in thermal maturity (computed from MPI), SARA proportions, n-alkane distributions, isoprenoid and DBT/P ratios, monoaromatic steroids, and δ13C isotopic compositions (from whole oils, saturate and aromatic fractions). Other parameters (normal steranes, extended homohopanes, C31R/C30 hopane, norhopane/hopane and tricyclic terpane ratios, gammacerane/hopane) show most oil samples have similar values, suggesting all Tuscaloosa Group oils are from a common mixed marine-terrigenous source rock. Tighter distributions for triaromatic steroid (TAS) and δ13C isotopic composition for conventional oils in lower and upper Tuscaloosa reservoirs may indicate charge occurred in a single or shorter pulse relative to TMS oils which show broader TAS and δ13C properties, possibly from their generation over an extended period of burial maturation. Dissimilarity in geochemical properties between lower Tuscaloosa source rock solvent extracts and Tuscaloosa Group oils indicates lower Tuscaloosa source rocks did not contribute significantly to conventional and unconventional Tuscaloosa Group hydrocarbon accumulations. Whereas, TMS solvent extracts are similar to Tuscaloosa Group oils, suggesting an oil-source rock correlation. Excluding the possibility for long-distance lateral migration from a similar source downdip (which is unnecessary given thermal maturity considerations), the observations indicate 1. the TMS is a self-sourced reservoir, 2. the TMS is the source of oils accumulated in nearby conventional Tuscaloosa Group reservoirs, and 3. thin organic-rich shales in the lower Tuscaloosa did not contribute substantially to any oil accumulations in the Tuscaloosa Group.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.petrol.2020.107015","usgsCitation":"Hackley, P.C., Dennen, K.O., Garza, D., Lohr, C., Valentine, B., Hatcherian, J.J., Enomoto, C., and Dulong, F.T., 2020, Oil-source rock correlation studies in the unconventional Upper Cretaceous Tuscaloosa marine shale (TMS) petroleum system, Mississippi and Louisiana, USA: Journal of Petroleum Science and Engineering, v. 190, 107015, 16 p., https://doi.org/10.1016/j.petrol.2020.107015.","productDescription":"107015, 16 p.","ipdsId":"IP-110731","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":457773,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.petrol.2020.107015","text":"Publisher Index Page"},{"id":384492,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana, Mississippi","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.15283203125,\n 29.19053283229458\n ],\n [\n -88.08837890625,\n 29.19053283229458\n ],\n [\n -88.08837890625,\n 33.063924198120645\n ],\n [\n -94.15283203125,\n 33.063924198120645\n ],\n [\n -94.15283203125,\n 29.19053283229458\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"190","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hackley, Paul C. 0000-0002-5957-2551 phackley@usgs.gov","orcid":"https://orcid.org/0000-0002-5957-2551","contributorId":592,"corporation":false,"usgs":true,"family":"Hackley","given":"Paul","email":"phackley@usgs.gov","middleInitial":"C.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":812499,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dennen, Kristin Opferkuch","contributorId":255529,"corporation":false,"usgs":true,"family":"Dennen","given":"Kristin","email":"","middleInitial":"Opferkuch","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":812500,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Garza, Daniel","contributorId":255532,"corporation":false,"usgs":false,"family":"Garza","given":"Daniel","email":"","affiliations":[{"id":51576,"text":"Sanchez Oil & Gas Corporation","active":true,"usgs":false}],"preferred":false,"id":812501,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lohr, Celeste D. 0000-0001-6287-9047 clohr@usgs.gov","orcid":"https://orcid.org/0000-0001-6287-9047","contributorId":209992,"corporation":false,"usgs":true,"family":"Lohr","given":"Celeste","email":"clohr@usgs.gov","middleInitial":"D.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":812520,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Valentine, Brett 0000-0002-8678-2431 bvalentine@usgs.gov","orcid":"https://orcid.org/0000-0002-8678-2431","contributorId":209829,"corporation":false,"usgs":true,"family":"Valentine","given":"Brett","email":"bvalentine@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":812521,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hatcherian, Javin J. 0000-0001-9151-6798 jhatcherian@usgs.gov","orcid":"https://orcid.org/0000-0001-9151-6798","contributorId":195770,"corporation":false,"usgs":true,"family":"Hatcherian","given":"Javin","email":"jhatcherian@usgs.gov","middleInitial":"J.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":812522,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Enomoto, Catherine B. 0000-0002-4119-1953","orcid":"https://orcid.org/0000-0002-4119-1953","contributorId":211802,"corporation":false,"usgs":true,"family":"Enomoto","given":"Catherine B.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":812523,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Dulong, Frank T. 0000-0001-7388-647X fdulong@usgs.gov","orcid":"https://orcid.org/0000-0001-7388-647X","contributorId":650,"corporation":false,"usgs":true,"family":"Dulong","given":"Frank","email":"fdulong@usgs.gov","middleInitial":"T.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":812524,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70205997,"text":"pp1861 - 2020 - Geochronologic age constraints on tectonostratigraphic units of the central Virginia Piedmont, USA","interactions":[],"lastModifiedDate":"2022-04-22T19:07:33.289959","indexId":"pp1861","displayToPublicDate":"2020-02-07T10:10:00","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":331,"text":"Professional Paper","code":"PP","onlineIssn":"2330-7102","printIssn":"1044-9612","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1861","displayTitle":"Geochronologic Age Constraints on Tectonostratigraphic Units of the Central Virginia Piedmont, USA","title":"Geochronologic age constraints on tectonostratigraphic units of the central Virginia Piedmont, USA","docAbstract":"New geologic mapping coupled with uranium-lead (U-Pb) zircon geochronology (sensitive high-resolution ion microprobe-reverse geometry [SHRIMP-RG] and laser ablation-inductively coupled plasma-mass spectrometry [LA-ICP-MS]) analyses of 10 samples, provides new constraints on the tectonostratigraphic framework of the central Virginia Piedmont. Detrital zircon analysis confirms that the Silurian-Devonian Quantico Formation is a postorogenic successor basin, with zircons derived primarily from Ordovician Chopawamsic Formation volcanic rocks. Detrital zircons from strata of the Long Island syncline, previously mapped as a separate successor basin, have a peri-Gondwanan component distinct from Laurentian-sourced rocks of the Potomac terrane to the west. Volcanism of the Chopawamsic Formation spanned at least 14 million years during the Ordovician. The Chopawamsic Formation contains sheet-like Late Ordovician-Silurian granodioritic and tonalitic intrusions that were once mapped as Carboniferous. Biotite-muscovite migmatitic paragneiss, which borders the Chopawamsic Formation on its southeast side and also occurs east of the Lakeside fault, preserves evidence of Silurian deformation and metamorphism, with a Carboniferous (Alleghanian) overprint. Limited SHRIMP-RG analysis of detrital zircons from this paragneiss yields a Laurentian (Mesoproterozoic) signature, which suggests that the structurally concordant contact between volcanic rocks of the Chopawamsic Formation and paragneiss is either a pre-Alleghanian fault or an unconformity.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1861","usgsCitation":"Carter, M.W., McAleer, R.J., Holm-Denoma, C.S., Spears, D.B., Regan, S.P., Burton, W.C., and Evans, N.H., 2020, Geochronologic age constraints on tectonostratigraphic units of the central Virginia Piedmont, USA: U.S. Geological Survey Professional Paper 1861, 28 p., https://doi.org/10.3133/pp1861.","productDescription":"Report: vi, 28 p.; 2 Tables","numberOfPages":"38","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-099524","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":399507,"rank":5,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109674.htm"},{"id":372001,"rank":4,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/pp/1861/pp1861_table3.xlsx","text":"Table 3","size":"447 KB","linkFileType":{"id":3,"text":"xlsx"},"linkHelpText":"- Isotopic data for all analyses by secondary ionization mass spectrometry on the U.S. Geological Survey/Stanford sensitive high-resolution ion microprobe-reverse geometry"},{"id":372000,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/pp/1861/pp1861_table2.xlsx","text":"Table 2","size":"98.5 KB","linkFileType":{"id":3,"text":"xlsx"},"linkHelpText":"- Isotopic data for all analyses by laser ablation-inductively coupled plasma-mass spectrometry at the U.S. Geological Survey Central Mineral and Environmental Resources Science Center Isotope Laboratory in Denver, Colorado"},{"id":372114,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1861/pp1861.pdf","text":"Report","size":"9.51 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1861"},{"id":371998,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1861/coverthb.jpg"}],"country":"United States","state":"Virginia","otherGeospatial":"central Virginia Piedmont","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -78.37,\n 37.6278\n ],\n [\n -77.5,\n 37.6278\n ],\n [\n -77.5,\n 38.3758\n ],\n [\n -78.37,\n 38.3758\n ],\n [\n -78.37,\n 37.6278\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Florence Bascom Geoscience Center
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 21092
The Dixie Valley fault bounds the east side of the Stillwater Range in west‐central Nevada and last ruptured in 1954. Offset basalts indicate that slip began more recently than ~14 Ma, and prior work has interpreted the southern segment as an active low‐angle normal fault. Oligocene igneous rocks in the southern Stillwater Range were steeply tilted during large‐magnitude extension prior to ~14 Ma. To refine the timing of early extension and the onset of slip on the Dixie Valley fault, we collected two transects of samples for apatite fission track, apatite and zircon (U‐Th)/He (AHe and ZHe), and apatite 4He/3He thermochronometry. Apatite fission track ages from the Oligocene IXL pluton indicate rapid cooling ~18–14 Ma, and AHe and ZHe ages from the Cretaceous La Plata Canyon pluton indicate rapid cooling ~16–19 Ma. We interpret these data to record cooling during rapid extension. AHe ages from the IXL pluton are ~6–8 Ma and record cooling during slip on the Dixie Valley fault. We modeled these ages and 4He/3He spectra from one sample as the result of cooling during exhumation of a tilted fault block at a constant extension rate. The model predicts slip on the Dixie Valley fault beginning ~8 Ma. Although it does not constrain the initial fault dip, the model illustrates how a low‐angle fault requires a higher extension rate to reproduce cooling ages. Consequently, we prefer a high‐angle southern Dixie Valley fault for strain compatibility with the high‐angle northern segment.
The Gales Creek fault (GCF) is a 60-km-long, northwest-striking dextral fault system (west of Portland, Oregon) that accommodates northward motion and uplift of the Oregon Coast Range. New geologic mapping and geophysical models confirm inferred offsets from earlier geophysical surveys and document ∼12 km of right-lateral offset of a basement high in Eocene Siletz River Volcanics since ca. 35 Ma and ∼8.8 km of right-lateral separation of Miocene Columbia River Basalt at Newberg, Oregon, since 15 Ma (∼0.62 ± 0.12 mm/yr, average long-term rate). Relative uplift of Eocene Coast Range basalt basement west of the fault zone is at least 5 km based on depth to basement under the Tualatin Basin from a recent inversion of gravity data. West of the city of Forest Grove, the fault consists of two subparallel strands ∼7 km apart. The westernmost, Parsons Creek strand, forms a linear valley southward to Henry Hagg Lake, where it continues southward to Newberg as a series of en echelon strands forming both extensional and compressive step-overs. Compressive step-overs in the GCF occur at intersections with ESE-striking sinistral faults crossing the Coast Range, suggesting the GCF is the eastern boundary of an R′ Riedel shear domain that could accommodate up to half of the ∼45° of post–40 Ma clockwise rotation of the Coast Range documented by paleomagnetic studies. Gravity and magnetic anomalies suggest the western strands of the GCF extend southward beneath Newberg into the Northern Willamette Valley, where colinear magnetic anomalies have been correlated with the Mount Angel fault, the proposed source of the 1993 M 5.7 Scotts Mills earthquake. The potential-field data and water-well data also indicate the eastern, Gales Creek strand of the fault may link to the NNW-striking Canby fault through the E-W Beaverton fault to form a 30-km-wide compressive step-over along the south side of the Tualatin Basin. LiDAR data reveal right-lateral stream offsets of as much as 1.5 km, shutter ridges, and other youthful geomorphic features for 60 km along the geophysical and geologic trace of the GCF north of Newberg, Oregon. Paleoseismic trenches document Eocene bedrock thrust over 250 ka surficial deposits along a reverse splay of the fault system near Yamhill, Oregon, and Holocene motion has been recently documented on the GCF along Scoggins Creek and Parsons Creek. The GCF could produce earthquakes in excess of Mw 7, if the entire 60 km segment ruptured in one earthquake. The apparent subsurface links of the GCF to other faults in the Northern Willamette Valley suggest that other faults in the system may also be active.
Lead poisoning of scavenging birds is a global issue. However, the drivers of lead exposure of avian scavengers have been understood from the perspective of individual species, not cross‐taxa assemblages. We analyzed blood (n = 285) and liver (n = 226) lead concentrations of 5 facultative (American crows [Corvus brachyrhynchos], bald eagles [Haliaeetus leucocephalus], golden eagles [Aquila chrysaetos], red‐shouldered hawks [Buteo lineatus], and red‐tailed hawks [Buteo jamaicensis]) and 2 obligate (black vultures [Coragyps atratus] and turkey vultures [Cathartes aura] avian scavenger species to identify lead exposure patterns. Species and age were significant (α < 0.05) predictors of blood lead exposure of facultative scavengers; species, but not age, was a significant predictor of their liver lead exposure. We detected temporal variations in lead concentrations of facultative scavengers (blood: median = 4.41 µg/dL in spring and summer vs 13.08 µg/dL in autumn and winter; p = <0.001; liver: 0.32 ppm in spring and summer vs median = 4.25 ppm in autumn and winter; p = <0.001). At the species level, we detected between‐period differences in blood lead concentrations of bald eagles (p = 0.01) and red‐shouldered hawks during the winter (p = 0.001). During summer, obligate scavengers had higher liver lead concentrations than did facultative scavengers (median = 1.76 ppm vs 0.22 ppm; p = <0.001). These data suggest that the feeding ecology of avian scavengers is a determinant of the degree to which they are lead exposed, and they highlight the importance of dietary and behavioral variation in determining lead exposure.
","language":"English","publisher":"Society of Environmental Toxicology and Chemistry","doi":"10.1002/etc.4680","usgsCitation":"Slabe, V., Anderson, J.T., Cooper, J.L., Miller, T.A., Brown, B., Wrona, A., Ortiz, P., Buchweitz, J., McRuer, D., Dominguez-Villegas, E., Behmke, S., and Katzner, T., 2020, Feeding ecology drives lead exposure of facultative and obligate avian scavengers in the eastern United States: Environmental Toxicology and Chemistry, v. 39, no. 4, p. 882-892, https://doi.org/10.1002/etc.4680.","productDescription":"11 p.","startPage":"882","endPage":"892","ipdsId":"IP-111260","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":380840,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alabama, Georgia, Maryland, New Jersey, New York, North Carolina, Pennsylvania, Tennessee, Virginia, West 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Resources","active":true,"usgs":false}],"preferred":false,"id":805757,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, James T.","contributorId":28071,"corporation":false,"usgs":false,"family":"Anderson","given":"James","email":"","middleInitial":"T.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":805758,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cooper, Jeff L","contributorId":217949,"corporation":false,"usgs":false,"family":"Cooper","given":"Jeff","email":"","middleInitial":"L","affiliations":[{"id":35592,"text":"Virginia Department of Game and Inland Fisheries","active":true,"usgs":false}],"preferred":false,"id":805759,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Miller, Tricia A.","contributorId":190591,"corporation":false,"usgs":false,"family":"Miller","given":"Tricia","email":"","middleInitial":"A.","affiliations":[{"id":16210,"text":"Division of Forestry and Natural Resources, West Virginia University","active":true,"usgs":false}],"preferred":false,"id":805760,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brown, Bracken","contributorId":217945,"corporation":false,"usgs":false,"family":"Brown","given":"Bracken","email":"","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":805761,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wrona, Anna","contributorId":245285,"corporation":false,"usgs":false,"family":"Wrona","given":"Anna","email":"","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":805762,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ortiz, Patricia 0000-0003-3067-7904","orcid":"https://orcid.org/0000-0003-3067-7904","contributorId":217946,"corporation":false,"usgs":true,"family":"Ortiz","given":"Patricia","email":"","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":805763,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Buchweitz, John","contributorId":217947,"corporation":false,"usgs":false,"family":"Buchweitz","given":"John","email":"","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":805764,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"McRuer, David","contributorId":205308,"corporation":false,"usgs":false,"family":"McRuer","given":"David","email":"","affiliations":[{"id":37079,"text":"Wildlife Center of Virginia","active":true,"usgs":false}],"preferred":false,"id":805765,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Dominguez-Villegas, Ernesto","contributorId":223077,"corporation":false,"usgs":false,"family":"Dominguez-Villegas","given":"Ernesto","email":"","affiliations":[{"id":37079,"text":"Wildlife Center of Virginia","active":true,"usgs":false}],"preferred":false,"id":805766,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Behmke, Shannon","contributorId":195117,"corporation":false,"usgs":false,"family":"Behmke","given":"Shannon","email":"","affiliations":[],"preferred":false,"id":805767,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Katzner, Todd E. 0000-0003-4503-8435 tkatzner@usgs.gov","orcid":"https://orcid.org/0000-0003-4503-8435","contributorId":191353,"corporation":false,"usgs":true,"family":"Katzner","given":"Todd E.","email":"tkatzner@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":805768,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70219049,"text":"70219049 - 2020 - Evidence of wildfires and elevated atmospheric oxygen at the Frasnian–Famennian boundary in New York (USA): Implications for the Late Devonian mass extinction","interactions":[],"lastModifiedDate":"2021-03-22T13:26:33.056379","indexId":"70219049","displayToPublicDate":"2020-02-05T08:23:26","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1786,"text":"Geological Society of America Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"Evidence of wildfires and elevated atmospheric oxygen at the Frasnian–Famennian boundary in New York (USA): Implications for the Late Devonian mass extinction","docAbstract":"The Devonian Period experienced significant fluctuations of atmospheric oxygen (O2) levels (∼25–13%), for which the extent and timing are debated. Also characteristic of the Devonian Period, at the Frasnian–Famennian (F–F) boundary, is one of the “big five” mass extinction events of the Phanerozoic. Fossilized charcoal (inertinite) provides a record of wildfire events, which in turn can provide insight into the evolution of terrestrial ecosystems and the atmospheric composition. Here, we report organic petrology, programmed pyrolysis analysis, major and trace element analyses, and initial osmium isotope (Osi) stratigraphy from five sections of Upper Devonian (F–F interval) from western New York, USA. These data are discussed to infer evidence of a wildfire event at the F–F boundary. Based on the evidence for a wildfire at the F–F boundary we also provide an estimate of atmospheric O2 levels of ∼23–25% at this interval, which is in agreement with the models that predict elevated pO2 levels during the Late Devonian. This, coupled with our Os isotope records, support the currently published Osi data that lacks any evidence for an extra-terrestrial impact or volcanic event at the F–F interval, and therefore to act as a trigger for the F–F mass extinction. The elevated O2 level at the F–F interval inferred from this study supports the hypothesis that pCO2 drawdown and associated climate cooling may have acted as a driving mechanism of the F–F mass extinction.
The Northern High Plains aquifer underlies about 93,000 square miles of Colorado, Kansas, Nebraska, South Dakota, and Wyoming and is the largest subregion of the nationally important High Plains aquifer. Irrigation, primarily using groundwater, has supported agricultural production since before 1940, resulting in nearly $50 billion in sales in 2012. In 2010, the High Plains aquifer had the largest groundwater withdrawals of any major aquifer system in the United States. Nearly one-half of those withdrawals were from the Northern High Plains aquifer, which has little hydrologic interaction with parts of the aquifer farther south. Land-surface elevation ranges from more than 7,400 feet (ft) near the western edge to less than 1,100 ft near the eastern edge. Major stream primarily flow west to east and include the Big Blue River, Elkhorn River, Loup River, Niobrara River, Republican River and Platte River with its two forks—the North Platte River and South Platte River. Population in the Northern High Plain aquifer area is sparse with only 2 cities having a population greater than 30,000.
Droughts across much of the area from 2001 to 2007, combined with recent (2004–18) legislation, have heightened concerns regarding future groundwater availability and highlighted the need for science-based water-resource management. Groundwater models with the capability to provide forecasts of groundwater availability and related stream base flows from the Northern High Plains aquifer were published recently (2016) and were used to analyze groundwater availability. Stream base flows are generally the dominant component of total streamflow in the Northern High Plains aquifer, and total streamflows or shortages thereof define conjunctive management triggers, at least in Nebraska. Groundwater availability was evaluated through comparison of aquifer-scale water budgets compared for periods before and after major groundwater development and across selected future forecasts. Groundwater-level declines and the forecast amount of groundwater in storage in the aquifer also were examined.
Director, Nebraska Water Science Center
U.S. Geological Survey
5231 South 19th Street
Lincoln, NE 68512
This article assesses the ability of regionally specific, frequency‐dependent crustal attenuation (
In addition to its resident Golden Eagles (Aquila chrysaetos), the Southern Great Plains of North America receives an influx of migrant Golden Eagles each winter. However, little current or quantitative information is available regarding eagle presence or the species' land cover associations across the region. During the winters of 2014/2015 and 2015/2016, we surveyed Golden Eagles along 51 approximately 55-km-long road survey transects within a 136,800-km2 area of the Southern Great Plains of eastern New Mexico and the panhandles of Texas and Oklahoma. Our goal was to estimate the winter density of Golden Eagles in the region and to evaluate their land cover associations. Detections were low, with an estimated regional winter density of 0.31 eagles per 100 km2. We found that Golden Eagles were detected in rangeland cover types in greater proportion, and in agricultural and other land cover types in lesser proportion, to their availability. Our results provide regulatory agencies with data that may facilitate better-informed decision making for eagle conservation in the region.
","language":"English","doi":"10.3398/064.080.0402","usgsCitation":"Mitchell, N., Boal, C.W., and Skipper, B., 2020, Distribution, density, and land cover associations of wintering Golden Eagles in the Southern Great Plains: Western North American Naturalist, v. 80, no. 4, p. 452-461, https://doi.org/10.3398/064.080.0402.","productDescription":"10 p.","startPage":"452","endPage":"461","ipdsId":"IP-099428","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":395427,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico, Oklahoma, Texas","otherGeospatial":"Southern Great Plains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -107.05078125,\n 33.578014746143985\n ],\n [\n -97.822265625,\n 33.578014746143985\n ],\n [\n -97.822265625,\n 37.09023980307208\n ],\n [\n -107.05078125,\n 37.09023980307208\n ],\n [\n -107.05078125,\n 33.578014746143985\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"80","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Mitchell, N.R.","contributorId":274259,"corporation":false,"usgs":false,"family":"Mitchell","given":"N.R.","email":"","affiliations":[{"id":36331,"text":"Texas Tech University","active":true,"usgs":false}],"preferred":false,"id":832848,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boal, Clint W. 0000-0001-6008-8911 cboal@usgs.gov","orcid":"https://orcid.org/0000-0001-6008-8911","contributorId":1909,"corporation":false,"usgs":true,"family":"Boal","given":"Clint","email":"cboal@usgs.gov","middleInitial":"W.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":832849,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Skipper, B.R.","contributorId":270348,"corporation":false,"usgs":false,"family":"Skipper","given":"B.R.","email":"","affiliations":[{"id":56152,"text":"Angelo State University","active":true,"usgs":false}],"preferred":false,"id":832850,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70228237,"text":"70228237 - 2020 - Eastern oyster clearance and respiration rates in response to acute and chronic exposure to suspended sediment loads","interactions":[],"lastModifiedDate":"2022-02-08T15:47:02.571742","indexId":"70228237","displayToPublicDate":"2020-02-01T09:31:23","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2449,"text":"Journal of Sea Research","active":true,"publicationSubtype":{"id":10}},"title":"Eastern oyster clearance and respiration rates in response to acute and chronic exposure to suspended sediment loads","docAbstract":"Coastal Louisiana supports some of the most productive areas for the eastern oyster, Crassostrea virginica. Changing conditions from restoration and climate change alter freshwater and sediment inflows into critical estuarine areas affecting water quality, including salinity and concentrations of suspended sediment. This study examined the effects of acute (1 h) and chronic (8 weeks) exposure of suspended sediment concentrations on the eastern oyster's respiration and clearance rates. Acute exposure at six sediment concentrations (0, 10, 50, 200, 500, 1000 mg L−1) and one salinity (15) indicated that sediment concentration significantly affected oyster clearance rates, with increasing clearance rates as suspended sediment concentrations increased up to 500 mg L−1. Respiration rates were not affected by sediment concentration (p = .12). Chronic exposure at two salinities (6 and 15) and three sediment concentrations (0, 50, 400 mg L−1) found no significant effect of sediment, salinity or their interaction on clearance rates. Respiration rate was reduced at higher sediment concentrations (50 and 400 mg L−1 versus 0 mg L−1) and lower salinity. As clearance and oxygen consumption rates critically inform oyster energetic models, these data provide valuable insight to more accurately predict eastern oyster population dynamics and inform harvest models in the face of changing estuarine conditions. Changes in rates of growth through altered energetic demands ultimately can impact not just the economic viability of the industry, but also the ability for the populations to maintain sustainable reefs.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.seares.2019.101831","usgsCitation":"La Peyre, M., Bernasconi, S.K., Lavaud, R., Casas, S.M., and La Peyre, J.F., 2020, Eastern oyster clearance and respiration rates in response to acute and chronic exposure to suspended sediment loads: Journal of Sea Research, v. 157, p. 1-7, https://doi.org/10.1016/j.seares.2019.101831.","productDescription":"101831, 7 p.","startPage":"1","endPage":"7","ipdsId":"IP-109899","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":499828,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://digitalcommons.lsu.edu/animalsciences_pubs/794","text":"External Repository"},{"id":395621,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Bay Gardene","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.68508720397949,\n 29.56188581810685\n ],\n [\n -89.6129035949707,\n 29.56188581810685\n ],\n [\n -89.6129035949707,\n 29.609804580144143\n ],\n [\n -89.68508720397949,\n 29.609804580144143\n ],\n [\n -89.68508720397949,\n 29.56188581810685\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"157","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"La Peyre, Megan K. 0000-0001-9936-2252","orcid":"https://orcid.org/0000-0001-9936-2252","contributorId":264343,"corporation":false,"usgs":true,"family":"La Peyre","given":"Megan K.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":833502,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bernasconi, S. K.","contributorId":274906,"corporation":false,"usgs":false,"family":"Bernasconi","given":"S.","email":"","middleInitial":"K.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":833503,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lavaud, R.","contributorId":273051,"corporation":false,"usgs":false,"family":"Lavaud","given":"R.","affiliations":[{"id":32913,"text":"Louisiana State University Agricultural Center","active":true,"usgs":false}],"preferred":false,"id":833504,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Casas, S. M.","contributorId":272906,"corporation":false,"usgs":false,"family":"Casas","given":"S.","email":"","middleInitial":"M.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":833506,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"La Peyre, J. F.","contributorId":273052,"corporation":false,"usgs":false,"family":"La Peyre","given":"J.","email":"","middleInitial":"F.","affiliations":[{"id":32913,"text":"Louisiana State University Agricultural Center","active":true,"usgs":false}],"preferred":false,"id":833505,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70209147,"text":"70209147 - 2020 - Influence of remediation on sediment toxicity within the Grand Calumet River, Indiana, USA","interactions":[],"lastModifiedDate":"2020-03-20T06:47:36","indexId":"70209147","displayToPublicDate":"2020-01-31T18:49:21","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1226,"text":"Chemosphere","active":true,"publicationSubtype":{"id":10}},"title":"Influence of remediation on sediment toxicity within the Grand Calumet River, Indiana, USA","docAbstract":"The Grand Calumet River (GCR), located in northern Indiana, is contaminated due to a wide range of historical industrial activities. This study was conducted to determine the influence of sediment remediation within the GCR on concentrations of chemical contaminants and toxicity to sediment-dwelling organisms. Between 2005 and 2016, sediments with high concentrations of metals and toxic organic compounds were remediated through a combination of removal, addition of activated carbon and organoclay amendments, and capping with sand or relatively uncontaminated sediment. Short-term and long-term sediment toxicity tests with the amphipod Hyalella azteca, the midge Chironomus dilutus, and the mussel Lampsilis siliquoidea were conducted with samples collected in 2013, 2015, and 2017, from 29 sites, including both remediated and non-remediated sites. Sediment chemistry and toxicity data for three groups of remediated sites (US Steel, West Branch, and East Branch) were compared to samples from contaminated but unremediated sites and to relatively uncontaminated reference sites. In general, remediated sediments had lower levels of PAHs, PCBs and metals, although sediments from the US Steel area still had elevated levels of PAH, PCB and chromium. Sediments from the three remediated sites and from reference sites showed significantly reduced toxic effects in short-term sediment bioassays, compared to unremediated sites. Variation in the long-term success of remediation may reflect site-specific factors such as the type of remediation and the potential for recontamination from uncontrolled sources.","language":"English","publisher":"Elsevier","doi":"10.1016/j.chemosphere.2020.126056","usgsCitation":"Steevens, J.A., Besser, J.M., Dorman, R.A., and Sparks, D.W., 2020, Influence of remediation on sediment toxicity within the Grand Calumet River, Indiana, USA: Chemosphere, v. 249, 126056, https://doi.org/10.1016/j.chemosphere.2020.126056.","productDescription":"126056","ipdsId":"IP-113273","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":437131,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9XIDHOV","text":"USGS data release","linkHelpText":"Chemical and biological exposure bioassay data from sediment collected within the Grand Calumet River, Indiana, 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Rebecca A. 0000-0002-5748-7046","orcid":"https://orcid.org/0000-0002-5748-7046","contributorId":28522,"corporation":false,"usgs":true,"family":"Dorman","given":"Rebecca","email":"","middleInitial":"A.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":785124,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sparks, Daniel W.","contributorId":223469,"corporation":false,"usgs":false,"family":"Sparks","given":"Daniel","email":"","middleInitial":"W.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":785125,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70208237,"text":"70208237 - 2020 - Direct trace element determination in oil and gas produced waters with inductively coupled plasma - Optical emission spectrometry (ICP-OES): Advantages of high salinity tolerance","interactions":[],"lastModifiedDate":"2020-06-04T16:51:39.984534","indexId":"70208237","displayToPublicDate":"2020-01-31T16:07:26","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1822,"text":"Geostandards and Geoanalytical Research","active":true,"publicationSubtype":{"id":10}},"title":"Direct trace element determination in oil and gas produced waters with inductively coupled plasma - Optical emission spectrometry (ICP-OES): Advantages of high salinity tolerance","docAbstract":"Waters co-produced during petroleum extraction are the largest waste stream from oil and gas development. Reuse or disposal of these waters is difficult due to their high salinities and the sheer volumes generated. Produced waters may also contain valuable mineral commodities. While an understanding of produced water trace element composition is required for evaluating the associated resource and waste potential of these materials, measuring trace elements in brines is challenging due to the dilution requirements of typical methods. Alternatively, inductively coupled plasma-optical emission spectrometry (ICP-OES) has shown promise as being capable of direct measurements of trace elements within produced waters with minimal dilution. Here we evaluate direct ICP-OES trace element quantification in produced waters for 17 trace elements (As, Al, Ba, Be, Cd, Cr, Co, Cu, Hg, Mo, Ni, Pb, Rb, Sb, U, V, and Zn) within 15 produced waters from five U.S. continuous reservoirs. The ICP-OES results are compared against trace element levels determined using inductively coupled plasma-mass spectrometry from the same samples. Our results demonstrate the potential for direct analysis of high salinity waters using ICP-OES with minimal dilution and provide trace element concentrations in waters from several important U.S. petroleum-generating reservoirs where available data is sparse.","language":"English","publisher":"Wiley","doi":"10.1111/GGR.12316","usgsCitation":"Jubb, A., Engle, M., Chenault, J., Blondes, M., Danforth, C.G., Doolan, C., Gallegos, T., Mueller, D., and Shelton, J., 2020, Direct trace element determination in oil and gas produced waters with inductively coupled plasma - Optical emission spectrometry (ICP-OES): Advantages of high salinity tolerance: Geostandards and Geoanalytical Research, v. 44, no. 2, p. 385-397, https://doi.org/10.1111/GGR.12316.","productDescription":"13 p.","startPage":"385","endPage":"397","ipdsId":"IP-111055","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":457922,"rank":0,"type":{"id":40,"text":"Open 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Ecosystem: An integration of paleoecologic data and models","docAbstract":"Determining hydrologic conditions prior to instrumental records is a challenge for restoration of freshwater ecosystems worldwide. Paleoecologic data provide this information on past conditions and when these data are used to adjust hydrologic models, allow conditions to be hindcast that may not be directly estimated from the paleo-data alone. In this context, the paleo-data provide real-world estimates as input to the models. Restoration of the Greater Everglades Ecosystem requires this understanding of the hydrology of the natural system prior to significant alterations due to water management and land use. Large scale models such as the Natural Systems Model (NSM 4.6.2) have been used by the South Florida Water Management District and other agencies responsible for restoration to estimate past hydrologic conditions; however, these models typically portray a drier natural system for the beginning of the 20th century than what is indicated by paleoecologic analyses and historical data. The purpose of this study is to estimate pre-20th century water levels, hydroperiods and flow in the freshwater wetlands of the Everglades by using pollen assemblage data in three sediment cores to adjust the Natural Systems Model. This study is designed to further test estimates of flow through the Everglades derived from analysis of sediment cores collected in Florida Bay. The results demonstrate that the NSM 4.6.2 underestimates water levels and hydroperiods in the Everglades compared to the paleo-adjusted NSM 4.6.2 model outputs. Flow models that use the paleo-adjusted water levels as input indicate flow through Shark River Slough in the late 19th century was approximately two times flow between 1990 and 2000, and flow through Taylor Slough was approximately three times flow between 1990 and 2000. The flow estimates derived from this study agree with the estimates derived from earlier studies using estuarine cores. This integration of paleoecologic information and hydrologic models provides resource managers with the best available estimates of past conditions and allows them to set realistic targets for restoration of freshwater ecosystems.","language":"English","publisher":"Frontiers","doi":"10.3389/fenvs.2020.00003","usgsCitation":"Marshall, F.E., Bernhardt, C.E., and Wingard, G.L., 2020, Estimating late 19th century hydrology in the Greater Everglades Ecosystem: An integration of paleoecologic data and models: Frontiers in Environmental Science, v. 8, no. 3, 21 p., https://doi.org/10.3389/fenvs.2020.00003.","productDescription":"21 p.","ipdsId":"IP-099728","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":457934,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fenvs.2020.00003","text":"Publisher Index Page"},{"id":372206,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Everglades ","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.58447265624999,\n 25.110471486223346\n ],\n [\n -80.2716064453125,\n 25.110471486223346\n ],\n [\n -80.2716064453125,\n 25.903703303407667\n ],\n [\n -81.58447265624999,\n 25.903703303407667\n ],\n [\n -81.58447265624999,\n 25.110471486223346\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"8","issue":"3","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2020-01-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Marshall, Frank E.","contributorId":222355,"corporation":false,"usgs":false,"family":"Marshall","given":"Frank","email":"","middleInitial":"E.","affiliations":[{"id":40533,"text":"Cetacean Logic Foundation","active":true,"usgs":false}],"preferred":false,"id":781946,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bernhardt, Christopher E. 0000-0003-0082-4731 cbernhardt@usgs.gov","orcid":"https://orcid.org/0000-0003-0082-4731","contributorId":2131,"corporation":false,"usgs":true,"family":"Bernhardt","given":"Christopher","email":"cbernhardt@usgs.gov","middleInitial":"E.","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":781947,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wingard, G. 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