Geomorphic change from extreme events in large managed rivers has implications for river management. A steady-state, quasi-three-dimensional hydrodynamic model was applied to a 29-km reach of the Missouri River using 2011 flood data. Model results for an extreme flow (500-year recurrence interval [RI]) and an elevated managed flow (75-year RI) were used to assess sediment mobility through examination of the spatial distribution of boundary or bed shear stress (τb) and longitudinal patterns of average τb, velocity, and kurtosis of τb. Kurtosis of τb was used as an indicator of planform channel complexity and can be applied to other river systems. From differences in longitudinal patterns of sediment mobility for the two flows we can infer: (1) under extreme flow, the channel behaves as a single-thread channel controlled primarily by flow, which enhances the meander pattern; (2) under elevated managed flows, the channel behaves as multithread channel controlled by the interaction of flow with bed and channel topography, resulting in a more complex channel; and (3) for both flows, the model reach lacks a consistent pattern of deposition or erosion, which indicates migration of areas of erosion and deposition within the reach. Despite caveats and limitations, the analysis provides useful information about geomorphic change under extreme flow and potential implications for river management. Although a 500-year RI is rare, extreme hydrologic events such as this are predicted to increase in frequency.
","language":"English","publisher":"Wiley","doi":"10.1111/1752-1688.12678","usgsCitation":"Nustad, R.A., Benthem, A.J., Skalak, K., McDonald, R.R., Schenk, E., and Galloway, J.M., 2021, Streamflow, sediment transport, and geomorphic change during the 2011 flood on the Missouri River near Bismarck-Mandan, ND: JAWRA, v. 54, no. 5, p. 1151-1167, https://doi.org/10.1111/1752-1688.12678.","productDescription":"17 p.","startPage":"1151","endPage":"1167","ipdsId":"IP-075678","costCenters":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":454576,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1752-1688.12678","text":"Publisher Index Page"},{"id":386466,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Dakota","city":"Bismarck","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -101.0137939453125,\n 45.94351068030587\n ],\n [\n -100.3436279296875,\n 45.94351068030587\n ],\n [\n -100.3436279296875,\n 46.98774725646568\n ],\n [\n -101.0137939453125,\n 46.98774725646568\n ],\n [\n -101.0137939453125,\n 45.94351068030587\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"54","issue":"5","noUsgsAuthors":false,"publicationDate":"2018-08-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Nustad, Rochelle A. 0000-0002-4713-5944 ranustad@usgs.gov","orcid":"https://orcid.org/0000-0002-4713-5944","contributorId":1811,"corporation":false,"usgs":true,"family":"Nustad","given":"Rochelle","email":"ranustad@usgs.gov","middleInitial":"A.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":817499,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Benthem, Adam J. 0000-0003-2372-0281","orcid":"https://orcid.org/0000-0003-2372-0281","contributorId":220000,"corporation":false,"usgs":true,"family":"Benthem","given":"Adam","middleInitial":"J.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":817502,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Skalak, Katherine 0000-0003-4122-1240 kskalak@usgs.gov","orcid":"https://orcid.org/0000-0003-4122-1240","contributorId":3990,"corporation":false,"usgs":true,"family":"Skalak","given":"Katherine","email":"kskalak@usgs.gov","affiliations":[{"id":37277,"text":"WMA - 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2021 - Contrasting mobilization of elements in contact with sediment from Lake Roosevelt and the Upper Columbia River, Washington, USA","interactions":[],"lastModifiedDate":"2021-07-13T10:20:57.226614","indexId":"70221872","displayToPublicDate":"2018-02-06T10:26:39","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":835,"text":"Applied Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Contrasting mobilization of elements in contact with sediment from Lake Roosevelt and the Upper Columbia River, Washington, USA","docAbstract":"Trace element contamination is known to be widely present in sediment of Lake Roosevelt and the riverine reach of the Columbia River in Washington State, USA due to discharges from several smelters and numerous mines dating back to the mid-1800's. In this study, the concentrations of aqueous elements in contact with bed sediment from the lake and river were examined under varying degrees of physical mixing and time scales. Contrasting geochemical processes affecting aqueous concentrations were inferred from the release of major ions (Ca and Si), elements enriched in metallurgical smelter slag (Cu and Sb), and redox-sensitive species (Fe, Mn, Mo and U). Releases of major ions reflect the contrasting sediment substrates along the length of the river and large reservoir. Calcium released from carbonate minerals and slag particles was most pronounced in regions of carbonate bedrock and near sediment deposits with a large component of slag material, while Si released from unconsolidated glacial/fluvial sediment increased with increasing distance downstream. Sb release was a consistent indicator of slag presence and weathering, possibly because its anionic nature inhibits readsorption onto metal oxides. In contrast, Cu release was quite variable, likely due to varying degrees of copper readsorption or co-precipitation onto metal oxides. The release of Mo and U appeared to be affected by redox conditions, which were assessed using aqueous Fe and Mn concentrations.
Geophysical flows occur over a large range of scales, with Reynolds numbers and Richardson numbers varying over several orders of magnitude. For this study, jets of different densities were ejected vertically into a large ambient region, considering conditions relevant to some geophysical phenomena. Using particle image velocimetry, the velocity fields were measured for three different gases exhausting into air – specifically helium, air and argon. Measurements focused on both the jet core and the entrained ambient. Experiments considered relatively low Reynolds numbers from approximately 1500 to 10 000 with Richardson numbers near 0.001 in magnitude. These included a variety of flow responses, notably a nearly laminar jet, turbulent jets and a transitioning jet in between. Several features were studied, including the jet development, the local entrainment ratio, the turbulent Reynolds stresses and the eddy strength. Compared to a fully turbulent jet, the transitioning jet showed up to 50 % higher local entrainment and more significant turbulent fluctuations. For this condition, the eddies were non-axisymmetric and larger than the exit radius. For turbulent jets, the eddies were initially smaller and axisymmetric while growing with the shear layer. At lower turbulent Reynolds number, the turbulent stresses were more than 50 % higher than at higher turbulent Reynolds number. In either case, the low-density jet developed faster than a comparable non-buoyant jet. Quadrant analysis and proper orthogonal decomposition were also utilized for insight into the entrainment of the jet, as well as to assess the energy distribution with respect to the number of eigenmodes. Reynolds shear stresses were dominant in Q1 and Q3 and exhibited negligible contributions from the remaining two quadrants. Both analysis techniques showed that the development of stresses downstream was dependent on the Reynolds number while the spanwise location of the stresses depended on the Richardson number.
Phase 2 of the Earth Mapping Resources Initiative (Earth MRI) focuses on geologic belts that are favorable for hosting mineral systems that may contain select critical minerals. Phase 1 of the Earth MRI program focused on rare earth elements (REE), and phase 2 adds aluminum, cobalt, graphite, lithium, niobium, platinum-group metals, tantalum, tin, titanium, and tungsten. This report describes the methodology and techniques utilized to define focus areas for future data acquisition in Alaska; the conterminous United States are covered in a separate report.
Definition of focus areas relies on a mineral systems framework that considers geologic features that may influence or control the formation and preservation of a mineral deposit and links the critical commodities to genetically related processes. Mineral systems are therefore larger than any given deposit. Evaluation of these larger systems allows for a broader understanding of how and where critical minerals may move through geologic systems.
Delineation of focus areas in Alaska was informed by statewide geological, geochemical, geophysical, and mineral occurrence datasets that are publicly available. Additionally, previously published prospectivity analyses for six different critical mineral-bearing deposit types help identify focus areas. A total of 74 focus areas prospective for the phase 2 critical minerals that occur in 12 different mineral systems were defined in Alaska. Identified focus areas may be used to guide future geologic, geochemical, and geophysical data in the State of Alaska.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191023C","collaboration":"Prepared in cooperation with the Alaska Division of Geological & Geophysical Surveys","usgsCitation":"Kreiner, D.C., and Jones, J.V., 2020, Focus areas for data acquisition for potential domestic resources of 11 critical minerals in Alaska—Aluminum, cobalt, graphite, lithium, niobium, platinum group elements, rare earth elements, tantalum, tin, titanium, and tungsten (ver. 1.1, July 2022), chap. 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Resources of 13 Critical Minerals in the Conterminous United States and Puerto Rico—Antimony, Barite, Beryllium, Chromium, Fluorspar, Hafnium, Helium, Magnesium, Manganese, Potash, Uranium, Vanadium, and Zirconium"},{"id":501523,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_110565.htm","linkFileType":{"id":5,"text":"html"}},{"id":378569,"rank":5,"type":{"id":6,"text":"Chapter"},"url":"https://doi.org/10.3133/ofr20191023B","text":"Open-File Report 2019-1023-B","description":"Open-File Report 2019-1023-B","linkHelpText":"- Focus Areas for Data Acquisition for Potential Domestic Resources of 11 Critical Minerals in the Conterminous United States, Hawaii, and Puerto Rico—Aluminum, Cobalt, Graphite, Lithium, Niobium, Platinum-Group Elements, Rare Earth Elements, Tantalum, Tin, Titanium, and Tungsten"},{"id":378568,"rank":4,"type":{"id":6,"text":"Chapter"},"url":"https://doi.org/10.3133/ofr20191023A","text":"Open-File Report 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1.0: September 2020: Version 1.1: July 2022","contact":"Director, Alaska Science Center
U.S. Geological Survey
4210 University Drive
Anchorage, Alaska 99508
In response to a need for information on potential domestic sources of critical minerals, the Earth Mapping Resources Initiative (Earth MRI) was established to identify and prioritize areas for acquisition of new geologic mapping, geophysical data, and elevation data to improve our knowledge of the geologic framework of the United States. Phase 1 of Earth MRI concentrated on those geologic terranes favorable for hosting the rare earth elements (REEs). Phase 2 continued to address the REEs and also identified focus areas for potential domestic sources of 10 more of the 35 critical minerals on the U.S. critical minerals list (aluminum, cobalt, graphite, lithium, niobium, platinum-group elements, tantalum, tin, titanium, tungsten). This report describes the methodology, data sources, and summary results for mineral systems that host these 11 critical minerals in the conterminous United States, Hawaii, and Puerto Rico; Alaska is covered in a separate report. The mineral systems framework adopted for this study links critical mineral commodities to families of genetically related mineral deposit types. The mineral systems approach is an efficient approach, providing a simultaneous evaluation of geologic terranes through aggregation of genetically related mineral deposit types that are much larger than individual ore deposits. Geologic, geochemical, topographic, and geophysical mapping provided by Earth MRI will document geologic features that reflect the extent of individual mineral systems and provide information about critical mineral deposits that may not have been recognized previously.
Each critical mineral commodity is discussed in terms of importance to the Nation’s economy, modes of occurrence, mineral systems, and deposit types along with maps and tables listing examples of focus areas for each critical mineral. Important mineral systems for these critical minerals include chemical weathering systems for aluminum (bauxite); placer systems for titanium and REEs; metamorphic systems for graphite; mafic magmatic systems for platinum-group elements and cobalt; lacustrine evaporite and porphyry tin systems for lithium; and copper-molybdenum-gold (Cu-Mo-Au) systems for tungsten. REEs occur in many different mineral systems. Focus areas were developed by scientists from the U.S. Geological Survey in collaboration with scientists from State geological surveys and other institutions. This first national-scale compilation of focus areas represents an initial step in addressing the Nation’s critical mineral needs by screening areas for acquisition of new data to provide the geologic framework necessary for identifying domestic sources of critical minerals.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191023B","collaboration":"Prepared in cooperation with American Association of State Geologists","usgsCitation":"Hammarstrom, J., Dicken, C., Day, W., Hofstra, A., Drenth, B., Shah, A., McCafferty, A., Woodruff, L., Foley, N., Ponce, D., Frost, T., and Stillings, L., 2020, Focus areas for data acquisition for potential domestic resources of 11 critical minerals in the conterminous United States, Hawaii, and Puerto Rico—Aluminum, cobalt, graphite, lithium, niobium, platinum-group elements, rare earth elements, tantalum, tin, titanium, and tungsten (ver. 1.1, July 2022), chap. B of U.S. Geological Survey, Focus areas for data acquisition for potential domestic sources of critical minerals: U.S. Geological Survey Open-File Report 2019–1023, 67 p., https://doi.org/10.3133/ofr20191023B.","productDescription":"xiii, 67 p.","numberOfPages":"67","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-119187","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":436687,"rank":9,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9U6SODG","text":"USGS data release","linkHelpText":"GIS for focus areas of potential domestic resources of 11 critical minerals-aluminum, cobalt, graphite, lithium, niobium, platinum group elements, rare earth elements, tantalum, tin, titanium, and tungsten (version 2.0, August 2020)"},{"id":436686,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P95CO8LR","text":"USGS data release","linkHelpText":"GIS for focus areas of potential domestic resources of 11 critical minerals - aluminum, cobalt, graphite, lithium, niobium, platinum group elements, rare earth elements, tantalum, tin, titanium, and tungsten"},{"id":403732,"rank":7,"type":{"id":6,"text":"Chapter"},"url":"https://doi.org/10.3133/ofr20191023E","text":"Open-File Report 2019-1023-E","linkHelpText":"- Alaska Focus Area Definition for Data Acquisition for Potential Domestic Sources of Critical Minerals in Alaska for Antimony, Barite, Beryllium, Chromium, Fluorspar, Hafnium, Magnesium, Manganese, Uranium, Vanadium, and 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U.S. Geological Survey
913 National Center
Reston, VA 20192
Building on a geology-based assessment of undiscovered, technically recoverable petroleum resources in the Eagle Ford Group in south Texas, the U.S. Geological Survey has estimated the required water and proppant demands and formation water production volumes associated with possible future development of these petroleum resources. The results of the water and proppant assessment are presented here, along with related drilling information and relevant water budget volumes for the region.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20203037","usgsCitation":"Gianoutsos, N.J., Haines, S.S., Varela, B.A., Whidden, K.J., Birdwell, J.E., Burke, L.A., Drake, R.M, II, Finn, T.M., French, K.L., Jenni, K.E., Kinney, S.A., Le, P.A., Leathers-Miller, H.M., Marra, K.R., Mercier, T.J., Paxton, S.T., Pitman, J.K., Schenk, C.J., Shaffer, B.N., Shorten, C.M., Tennyson, M.E., and Woodall, C.A., 2020, Assessment of water and proppant quantities associated with petroleum production from the Eagle Ford Group, Gulf Coast, Texas, 2019 (ver 1.1, March 2022): U.S. Geological Survey Fact Sheet 2020-3037, 4 p., https://doi.org/10.3133/fs20203037.","productDescription":"Report: 4 p.; Data Release","onlineOnly":"N","ipdsId":"IP-117221","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":501274,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_110420.htm","linkFileType":{"id":5,"text":"html"}},{"id":397279,"rank":6,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2020/3037/images"},{"id":397276,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2020/3037/fs20203037.xml"},{"id":397275,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/fs/2020/3037/versionHist.txt","text":"Version History","size":"4.0 kB","linkFileType":{"id":2,"text":"txt"},"description":"FS 2020-3037 version history"},{"id":376646,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2020/3037/fs20203037.pdf","text":"Report","size":"1.32 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2020-3037"},{"id":376647,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9NWKE6G","text":"USGS data release","linkHelpText":"Input forms for 2019 water and proppant assessment of the Eagle Ford Group, Gulf Coast, Texas"},{"id":376645,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2020/3037/coverthb.jpg"}],"country":"United States","state":"Texas","otherGeospatial":"Eagle Ford Group, Gulf Coast","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -100.94238281249999,\n 25.58208527870072\n ],\n [\n -95.07568359375,\n 25.58208527870072\n ],\n [\n -95.07568359375,\n 29.420460341013133\n ],\n [\n -100.94238281249999,\n 29.420460341013133\n ],\n [\n -100.94238281249999,\n 25.58208527870072\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Originally posted July 27, 2020; Revised October March 18, 2022","contact":"Director, Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver, CO 80225-0046
The lesser prairie-chicken (Tympanuchus pallidicinctus) occurs in the semiarid southern Great Plains, a region prone to periods of drought. Researchers generally believe that lesser prairie-chickens are able to satisfy their water requirements through preformed water and metabolic processes, but also know that they experience low survival and reproductive success during periods of drought. We used motion-sensing cameras to assess lesser prairie-chicken visits to man-made free water sources over a 48-month period from March 2009 to February 2013 in west Texas. Our objective was to examine temporal patterns of water use by lesser prairie-chickens, and to explore life history phenology and environmental conditions that may influence the species' use of free water. We documented 1,439 visits to water sources by lesser prairie-chickens. Their use of water sources was high during the winter months (December–February; 92 visits per 100 trap days) but the highest average visit rate to water sources occurred during the lekking-nesting life stage (March–May; 146 visits per 100 trap days). Water use was lower during the brood-rearing stage (June–August; 71 visits per 100 trap days) and lowest during the brood dispersal and independence stage (September–November; 19 visits per 100 trap days). Water use was strongly associated with dew point (P < 0.0001) and temperature (P = 0.0002) but was not associated with precipitation (P = 0.1037). These data indicate life-cycle stage (e.g., lekking-nesting) and reduced availability of preformed water may influence use of free water sources by lesser prairie-chickens. Current climate models predict the region of the study area will experience increases in temperature and decreases in frequency of precipitation. The combined effect of this would be reduced environmental moisture. If the prediction of increasing aridity in the region holds true, man-made water sources may become a tool for conservation of the species.
","language":"English","publisher":"Southwestern Association of Naturalists","doi":"10.1894/0038-4909-65.3-4.197","usgsCitation":"Gicklhorn, T.S., Boal, C.W., and Borsdorf, P.K., 2020, Lesser prairie-chicken (Tympanuchus pallidicinctus) use of man-made water sources: Southwestern Naturalist, v. 65, no. 3-4, p. 197-204, https://doi.org/10.1894/0038-4909-65.3-4.197.","productDescription":"8 p.","startPage":"197","endPage":"204","ipdsId":"IP-083938","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":402264,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Texas","county":"Cochran County, Hockley County, Terry County, Yoakum County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -103.03802490234375,\n 33.01557297778958\n ],\n [\n -102.36785888671875,\n 33.01557297778958\n ],\n [\n -102.36785888671875,\n 33.73347670599252\n ],\n [\n -103.03802490234375,\n 33.73347670599252\n ],\n [\n -103.03802490234375,\n 33.01557297778958\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"65","issue":"3-4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gicklhorn, Trevor S.","contributorId":166698,"corporation":false,"usgs":false,"family":"Gicklhorn","given":"Trevor","email":"","middleInitial":"S.","affiliations":[{"id":24740,"text":"Department of Natural Resources Management, Texas Tech University, Lubbock, TX, 79409, USA","active":true,"usgs":false}],"preferred":false,"id":844733,"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":844734,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Borsdorf, Philip K.","contributorId":93386,"corporation":false,"usgs":false,"family":"Borsdorf","given":"Philip","email":"","middleInitial":"K.","affiliations":[{"id":24740,"text":"Department of Natural Resources Management, Texas Tech University, Lubbock, TX, 79409, USA","active":true,"usgs":false}],"preferred":false,"id":844735,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70208401,"text":"ofr20201012 - 2020 - Major-element compositional data and thermal data for drill core from Kīlauea Iki lava lake, plus analyses of glasses from scoria of the 1959 summit eruption of Kīlauea Volcano, Hawaii","interactions":[],"lastModifiedDate":"2021-12-16T12:03:49.083736","indexId":"ofr20201012","displayToPublicDate":"2021-12-15T15:40:00","publicationYear":"2020","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":"2020-1012","displayTitle":"Major-Element Compositional Data and Thermal Data for Drill Core from Kīlauea Iki Lava Lake, Plus Analyses of Glasses from Scoria of the 1959 Summit Eruption of Kīlauea Volcano, Hawaii","title":"Major-element compositional data and thermal data for drill core from Kīlauea Iki lava lake, plus analyses of glasses from scoria of the 1959 summit eruption of Kīlauea Volcano, Hawaii","docAbstract":"This report presents electron microprobe data on glasses and selected crystalline phases from Kīlauea Iki lava lake and glasses from the 1959 summit eruption of Kīlauea Volcano, Hawaii. Some of these data have been published previously, but the complete set has not been published before. In addition, this report includes electron microprobe data for phases in melting experiments reported earlier, which form the basis for using many of the glass compositions reported here to estimate quenching temperatures of the samples. Finally, because of the latter application, this report includes all useful field determinations of temperature taken in Kīlauea Iki boreholes from 1967 to 1988. These field measurements have been merged with geothermometry based on glass and Fe-Ti oxide compositions to produce a comprehensive review of all available thermal information for Kīlauea Iki. Making these datasets available completes documentation of field and chemical information on Kīlauea Iki lava lake, supplementing six previous U.S. Geological Survey Open-File Reports listed in the References Cited.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201012","usgsCitation":"Helz, R.T., 2020, Major-element compositional data and thermal data for drill core from Kīlauea Iki lava lake, plus analyses of glasses from scoria of the 1959 summit eruption of Kīlauea Volcano, Hawaii (ver 1.1, December 2021): U.S. Geological Survey Open-File Report 2020–1012, 48 p., https://doi.org/10.3133/ofr20201012.","productDescription":"Report: v, 48 p.; Appendix 1-2","numberOfPages":"54","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-109981","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":374174,"rank":2,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2020/1012/ofr20201012_appendix1.xlsx","text":"Appendix 1","size":"206 KB","linkFileType":{"id":3,"text":"xlsx"},"linkHelpText":"- Tables 1.1–1.13 as an Excel file"},{"id":374175,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2020/1012/ofr20201012_appendix2.xlsx","text":"Appendix 2","size":"48.5 KB","linkFileType":{"id":3,"text":"xlsx"},"linkHelpText":"- Tables 2.1–2.4 as an Excel file"},{"id":374172,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1012/coverthb2.jpg"},{"id":374177,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2020/1012/ofr20201021_appendix2_csv.zip","text":"Appendix 2","size":"5.50 KB","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- Tables 2.1–2.4 as CSV files in a zipped folder"},{"id":374205,"rank":6,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1012/ofr20201012.pdf","text":"Report","size":"3.00 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1012"},{"id":392665,"rank":7,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2020/1012/versionHist.txt","size":"691 B","linkFileType":{"id":2,"text":"txt"}},{"id":374176,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2020/1012/ofr20201021_appendix1_csv.zip","text":"Appendix 1","size":"41.5 KB","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- Tables 1.1–1.13 as CSV files in a zipped folder"}],"country":"United States","state":"Hawaii","otherGeospatial":"Kīlauea Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.30410766601562,\n 19.38759093442151\n ],\n [\n -155.2306365966797,\n 19.38759093442151\n ],\n [\n -155.2306365966797,\n 19.44846418467642\n ],\n [\n -155.30410766601562,\n 19.44846418467642\n ],\n [\n -155.30410766601562,\n 19.38759093442151\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: April 23, 2020; Version 1.1: December 15, 2021","contact":"Director, Florence Bascom Geoscience Center
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(Re)insurance companies rely on earthquake risk models to estimate the frequency and severity of their potential financial losses. To protect themselves, they sometimes use parametric risk transfer solutions, which are derivative-form agreements that provide compensation as a function of routine measurable earthquake characteristics. These mechanisms typically remain in force for one to three years and assume seismic conditions—and our estimates of them—remain unchanged during this period. However, seismic risk estimates evolve continuously due to changes in nearby seismicity, sudden ruptures, slower redistributions of stress, or improvements in our own understanding of these phenomena. As a consequence, the likelihood of some loss-causing events might decrease and make the protection superfluous (wasted money), or, more problematically, it might increase and render the protection insufficient (increased risk). This paper explores the construction of parametric earthquake risk transfer mechanisms that adapt efficiently (i.e., near real-time) to changes in seismicity throughout the lifetime of the transaction. The mechanism proposes the periodic adjustment of the payment conditions of the parametric agreement in harmony with the evolving probabilities of event occurrence. This, we hypothesize, may result in a more efficient allocation of premiums that reflects the changing nature of seismic risk. To build the proposed dynamic risk transfer mechanism, we first employ one of the earthquake models commonly used in the (re)insurance industry to assess the risk of a portfolio of assets. The modeling exercise yields the expected frequency distribution of loss, which a standard (re)insurance transaction would typically consider constant for the entire coverage period. Here, we use these results simply as a baseline for the initial time step of reference. Next, we construct a retrospective update loop, which consists of two parts: (1) we obtain the earthquake occurrence rate conditions at a previous time step taking into account the changes in seismicity observed in the interim period; and (2) we use the modeled losses and adjusted frequencies at the new time step to build a parametric risk transfer solution. This parametric solution remains in force until it is updated at the next iteration. We also track the effects on the efficiency of the risk transfer solution and its premium if these continuous updates were not implemented.
We apply the proposed mechanism to California and find that changes in seismicity can cause swings in the frequency of parametric payments (which is related to the premium paid for the cover) in average of 16% and up to 36% in any three-year period from 1986 to 2020. We also find that avoiding an update of the parametric solution on a yearly basis to match the new risk profile can decrease the efficiency of the cover (measured as the relative contribution to the average annual loss of the events covered) in the same time period by 13% on average and up to 35%.
","conferenceTitle":"17th World Conference on Earthquake Engineering, 17WCEE","conferenceDate":"September 13-18, 2020","conferenceLocation":"Sendai, Japan","language":"English","publisher":"Japan Association for Earthquake Engineering","usgsCitation":"Franco, G., Guidotti, R., Field, E., Milner, K., Lee, Y., and Stein, R.S., 2020, An exploration of parametric earthquake risk transfer solutions that dynamically adapt to seismicity changes, 17th World Conference on Earthquake Engineering, 17WCEE, Sendai, Japan, September 13-18, 2020, 12 p.","productDescription":"12 p.","ipdsId":"IP-117006","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":425797,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://wcee.nicee.org/wcee/seventeenth_conf_sendai_japan/","linkFileType":{"id":5,"text":"html"}},{"id":425798,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Franco, Guillermo","contributorId":194951,"corporation":false,"usgs":false,"family":"Franco","given":"Guillermo","email":"","affiliations":[],"preferred":false,"id":783436,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Guidotti, R","contributorId":222891,"corporation":false,"usgs":false,"family":"Guidotti","given":"R","email":"","affiliations":[{"id":40620,"text":"Guy Carpenter","active":true,"usgs":false}],"preferred":false,"id":783437,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Field, Edward H. 0000-0001-8172-7882 field@usgs.gov","orcid":"https://orcid.org/0000-0001-8172-7882","contributorId":1165,"corporation":false,"usgs":true,"family":"Field","given":"Edward H.","email":"field@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":false,"id":783435,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Milner, K.R.","contributorId":222892,"corporation":false,"usgs":false,"family":"Milner","given":"K.R.","email":"","affiliations":[{"id":13249,"text":"University of Southern California","active":true,"usgs":false}],"preferred":false,"id":783438,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lee, Y.J.","contributorId":222893,"corporation":false,"usgs":false,"family":"Lee","given":"Y.J.","affiliations":[{"id":40621,"text":"ImageCat Inc.","active":true,"usgs":false}],"preferred":false,"id":783439,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stein, R. S.","contributorId":222894,"corporation":false,"usgs":false,"family":"Stein","given":"R.","email":"","middleInitial":"S.","affiliations":[{"id":40622,"text":"Temblor","active":true,"usgs":false}],"preferred":false,"id":783440,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70228603,"text":"70228603 - 2020 - Decision context as an essential component of population viability analysis","interactions":[],"lastModifiedDate":"2022-02-14T14:59:02.146641","indexId":"70228603","displayToPublicDate":"2021-09-30T08:41:55","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1321,"text":"Conservation Biology","active":true,"publicationSubtype":{"id":10}},"title":"Decision context as an essential component of population viability analysis","docAbstract":"Population viability analysis (PVA) is a widely used tool that applies demographic data in simulation frameworks to assess extinction risk for species or populations. It is used in diverse conservation applications, including evaluating management effectiveness, relative risk of threats, and potential changes to protective status (Beissinger & McCullough, 2002), and can be a critical tool for making decisions with imperfect knowledge of the system state, often on limited timelines (Meine et al., 2006).
Chaudhary and Oli (2020) recently developed a framework to appraise the quality of PVAs based on the presence of essential background, model, and analysis components. They evaluated 160 published PVAs and reported a decline in the quality of PVAs over time (1990−2017). We agree PVA studies should report unambiguous descriptions of their essential components (Table 1 in Chaudhary and Oli) and explicitly state the model's biological and statistical assumptions. The need for increased transparency in PVAs is evident. Morrison et al. (2016) reported that only 50% of PVAs published in peer-reviewed and gray literature were both reproducible and repeatable. Further, in an examination of 67 studies that used matrix population models (widely used in PVAs), Kendall et al. (2019) reported that models frequently contained misspecification errors. Given the rapid advancement of simulation techniques, updated guidance for PVA construction is warranted.
However, we believe the essential PVA components identified by Chaudhary and Oli contain a critical omission: the decision context in which the PVA was created and its usefulness in that context. Quality and utility are not mutually exclusive; however, some models that do not meet idealized quality standards might still be valuable because they are useful and represent the best available science for a given decision context (hereafter, decision-support models). The definition of quality for decision-support models should be different than models developed for the purpose of learning (hereafter, heuristic models) and should incorporate how useful the model was, despite information gaps. We further argue that assessment questions should be used prospectively to guide modeling projects, rather than for retrospective comparison of model quality.
","language":"English","publisher":"Society for Conservation Biology","doi":"10.1111/cobi.13818","usgsCitation":"Lawson, A.J., Folt, B., Tucker, A.M., Erickson, F.T., and McGowan, C.P., 2020, Decision context as an essential component of population viability analysis: Conservation Biology, no. 5, p. 1683-1685, https://doi.org/10.1111/cobi.13818.","productDescription":"3 p.","startPage":"1683","endPage":"1685","ipdsId":"IP-118153","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":395881,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"issue":"5","noUsgsAuthors":false,"publicationDate":"2021-08-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Lawson, Abigail Jean 0000-0002-2799-8750","orcid":"https://orcid.org/0000-0002-2799-8750","contributorId":276319,"corporation":false,"usgs":true,"family":"Lawson","given":"Abigail","email":"","middleInitial":"Jean","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":834747,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Folt, Brian","contributorId":267702,"corporation":false,"usgs":false,"family":"Folt","given":"Brian","affiliations":[{"id":13360,"text":"Auburn University","active":true,"usgs":false}],"preferred":false,"id":834748,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tucker, Anna Maureen 0000-0002-1473-2048 amtucker@usgs.gov","orcid":"https://orcid.org/0000-0002-1473-2048","contributorId":257906,"corporation":false,"usgs":true,"family":"Tucker","given":"Anna","email":"amtucker@usgs.gov","middleInitial":"Maureen","affiliations":[],"preferred":true,"id":834749,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Erickson, Francesca T.","contributorId":276320,"corporation":false,"usgs":false,"family":"Erickson","given":"Francesca","email":"","middleInitial":"T.","affiliations":[{"id":13360,"text":"Auburn University","active":true,"usgs":false}],"preferred":false,"id":834750,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McGowan, Conor P. 0000-0002-7330-9581 cmcgowan@usgs.gov","orcid":"https://orcid.org/0000-0002-7330-9581","contributorId":167162,"corporation":false,"usgs":true,"family":"McGowan","given":"Conor","email":"cmcgowan@usgs.gov","middleInitial":"P.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":false,"id":834751,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70213131,"text":"70213131 - 2020 - Lampricide residues in sea lamprey larvae carcasses recovered after 3-trifluoromethyl-4- nitrophenol (TFM) or TFM/Bayluscide stream treatments","interactions":[],"lastModifiedDate":"2022-04-21T16:58:18.655836","indexId":"70213131","displayToPublicDate":"2021-09-01T11:51:06","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":3,"text":"Organization Series"},"seriesTitle":{"id":7568,"text":"Project Completion Report","active":true,"publicationSubtype":{"id":3}},"title":"Lampricide residues in sea lamprey larvae carcasses recovered after 3-trifluoromethyl-4- nitrophenol (TFM) or TFM/Bayluscide stream treatments","docAbstract":"Lampricide concentrations in whole larval sea lamprey (Petromyzon marinus) carcasses collected after lampricide treatments were determined to support risk assessment for non-target organisms that may consume lampricide-laden carcasses. Dead larvae were collected by Sea Lamprey Control personnel following the Ford River (Delta County, Michigan) 4.1 mg·L-1 3-trifluoromethyl-4-nitrophenol (TFM) treatment, Sturgeon River (Baraga County, Michigan) 0.64 mg·L-1 /7.1 µg·L-1 TFM/niclosamide treatment, and two treatments on the Chippewa River (Isabella County, Michigan). The upper reach of the Chippewa River was treated with 3.1 mg·L-1 /33 µg·L-1 TFM/Bayluscide and the lower reach was treated with 4.1 mg·L-1 TFM. Carcasses were removed from each stream via scap nets immediately after treatment completion. To assess instream degradation, half of the collected carcasses from both Chippewa River treatments were placed in cages and returned to the river for 2 days before they were analyzed for lampricide residues. The estimated mean and standard error of the mean (SEM) TFM concentration in the fresh carcasses (n = 80) collected from all the TFM and TFM/Bayluscide treated rivers was 4.6 µg·g-1 (SEM =1.1 µg·g-1 ). The mean concentration of niclosamide (the active ingredient in Bayluscide) in the fresh carcasses (n = 40) from the two rivers treated with TFM/ Bayluscide was 0.49 µg·g-1 (SEM = 0.21 µg·g-1 ). The mean 2-day postmortem carcasses from the Chippewa River TFM/Bayluscide treatment contained 0.14 µg·g-1 (3%) of the TFM and 0.41 µg·g-1 (64%) of the niclosamide found in the fresh-carcass group (4.4 µg·g-1 TFM and 0.64 µg·g-1 niclosamide). The mean 2-day postmortem carcasses from the Chippewa River TFM treatment contained 0.72 µg·g-1 (12%) compared to the 6.1 µg·g-1 of TFM found in the fresh-carcass group.
","language":"English","publisher":"Great Lakes Fishery Commission","usgsCitation":"Bernardy, J., and Schloesser, N., 2020, Lampricide residues in sea lamprey larvae carcasses recovered after 3-trifluoromethyl-4- nitrophenol (TFM) or TFM/Bayluscide stream treatments: Project Completion Report, 16 p.","productDescription":"16 p.","ipdsId":"IP-112331","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":399097,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":399096,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.glfc.org/"}],"country":"United States","state":"Michigan","otherGeospatial":"Chippewa river, Ford River, Harlow Creek, Sturgeon River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.6761474609375,\n 46.57774276255591\n ],\n [\n -88.3465576171875,\n 46.57774276255591\n ],\n [\n -88.3465576171875,\n 46.916503267244835\n ],\n [\n -88.6761474609375,\n 46.916503267244835\n ],\n [\n -88.6761474609375,\n 46.57774276255591\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.16312408447266,\n 45.66132705384569\n ],\n [\n -87.12089538574219,\n 45.66132705384569\n ],\n [\n -87.12089538574219,\n 45.69395042477016\n ],\n [\n -87.16312408447266,\n 45.69395042477016\n ],\n [\n -87.16312408447266,\n 45.66132705384569\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -85.220947265625,\n 43.51270490464819\n ],\n [\n -84.48486328124999,\n 43.51270490464819\n ],\n [\n -84.48486328124999,\n 43.96119063892024\n ],\n [\n -85.220947265625,\n 43.96119063892024\n ],\n [\n -85.220947265625,\n 43.51270490464819\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.48631954193115,\n 46.628663099851025\n ],\n [\n -87.4681234359741,\n 46.628663099851025\n ],\n [\n -87.4681234359741,\n 46.63880017254108\n ],\n [\n -87.48631954193115,\n 46.63880017254108\n ],\n [\n -87.48631954193115,\n 46.628663099851025\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bernardy, Jeffry 0000-0001-7443-1995","orcid":"https://orcid.org/0000-0001-7443-1995","contributorId":213528,"corporation":false,"usgs":true,"family":"Bernardy","given":"Jeffry","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":798336,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schloesser, Nicholas 0000-0002-3815-5302","orcid":"https://orcid.org/0000-0002-3815-5302","contributorId":237025,"corporation":false,"usgs":true,"family":"Schloesser","given":"Nicholas","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":798337,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70223674,"text":"70223674 - 2020 - Outside the box: Working with wildlife in biocontainment","interactions":[],"lastModifiedDate":"2022-01-25T16:48:58.603578","indexId":"70223674","displayToPublicDate":"2021-08-23T08:22:36","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5255,"text":"ILAR Journal","active":true,"publicationSubtype":{"id":10}},"title":"Outside the box: Working with wildlife in biocontainment","docAbstract":"Research with captive wildlife in Animal Biosafety Level 2 (ABSL2) and 3 (ABSL3) facilities is becoming increasingly necessary as emerging and re-emerging diseases involving wildlife have increasing impacts on human, animal, and environmental health. Utilizing wildlife species in a research facility often requires outside the box thinking with specialized knowledge, practices, facilities, and equipment. The USGS National Wildlife Health Center (NWHC) houses an ABSL3 facility dedicated to understanding wildlife diseases and developing tools to mitigate their impacts on animal and human health. This review presents considerations for utilizing captive wildlife for infectious disease studies, including, husbandry, animal welfare, veterinary care, and biosafety. Examples are drawn from primary literature review and collective 40-year experience of the NWHC. Working with wildlife in ABSL2 and ABSL3 facilities differs from laboratory animals in that typical laboratory housing systems, husbandry practices, and biosafety practices are not designed for work with wildlife. This requires thoughtful adaptation of standard equipment and practices, invention of customized solutions and development of appropriate enrichment plans using the natural history of the species and the microbiological characteristics of introduced and native pathogens. Ultimately, this task requires critical risk assessment, understanding of the physical and psychological needs of diverse species, creativity, innovation, and flexibility. Finally, continual reassessment and improvement are imperative in this constantly changing specialty area of infectious disease and environmental hazard research.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/ilar/ilab025","usgsCitation":"Falendysz, E., Calhoun, D.M., Smith, C.A., and Sleeman, J.M., 2020, Outside the box: Working with wildlife in biocontainment: ILAR Journal, v. 61, no. 1, p. 72-85, https://doi.org/10.1093/ilar/ilab025.","productDescription":"14 p.","startPage":"72","endPage":"85","ipdsId":"IP-123136","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":454587,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/ilar/ilab025","text":"Publisher Index Page"},{"id":388725,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"61","issue":"1","noUsgsAuthors":false,"publicationDate":"2021-08-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Falendysz, Elizabeth 0000-0003-2895-8918 efalendysz@usgs.gov","orcid":"https://orcid.org/0000-0003-2895-8918","contributorId":127751,"corporation":false,"usgs":true,"family":"Falendysz","given":"Elizabeth","email":"efalendysz@usgs.gov","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":822284,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Calhoun, Dana Marie 0000-0002-9483-2064","orcid":"https://orcid.org/0000-0002-9483-2064","contributorId":245039,"corporation":false,"usgs":true,"family":"Calhoun","given":"Dana","email":"","middleInitial":"Marie","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":822285,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, Carrie Alison 0000-0002-2684-3407","orcid":"https://orcid.org/0000-0002-2684-3407","contributorId":228816,"corporation":false,"usgs":true,"family":"Smith","given":"Carrie","email":"","middleInitial":"Alison","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":822286,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sleeman, Jonathan M. 0000-0002-9910-6125 jsleeman@usgs.gov","orcid":"https://orcid.org/0000-0002-9910-6125","contributorId":128,"corporation":false,"usgs":true,"family":"Sleeman","given":"Jonathan","email":"jsleeman@usgs.gov","middleInitial":"M.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true},{"id":82110,"text":"Midcontinent Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":822287,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70221395,"text":"70221395 - 2020 - Asian carp population modeling to support an adaptive management framework","interactions":[],"lastModifiedDate":"2021-06-14T13:17:12.747593","indexId":"70221395","displayToPublicDate":"2021-06-01T08:15:31","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Asian carp population modeling to support an adaptive management framework","docAbstract":"This Monitoring and Response Plan provides the Asian Carp Regional Coordinating Committee (ACRCC) with updates on FWS and USGS modeling efforts for the Spatially Explicit Asian carp Population (SEAcarP) model. For FY2020, efforts are underway to parameterize and analyze the SEAcarP model. Themes: invasive species; Asian carp; Great Lakes.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Monitoring Response Plans, Asian Carp Regional Coordinating Committee","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"Asian Carp Regional Coordinating Committee","collaboration":"U.S. Fish and Wildlife Service; ACRCC","usgsCitation":"Kallis, J.L., Erickson, R.A., and Fritts, M.W., 2020, Asian carp population modeling to support an adaptive management framework, 6 p.","productDescription":"6 p.","startPage":"95","endPage":"100","ipdsId":"IP-119007","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":386470,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":386461,"type":{"id":15,"text":"Index Page"},"url":"https://www.asiancarp.us/PlansReports.html"}],"country":"United States","state":"Illinois","otherGeospatial":"Illinois River Waterway system","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.5830078125,\n 41.73852846935917\n ],\n [\n -87.62695312499999,\n 42.00032514831621\n ],\n [\n -87.8466796875,\n 42.00032514831621\n ],\n [\n -88.26416015625,\n 41.713930073371294\n ],\n [\n -88.857421875,\n 41.60722821271717\n ],\n [\n -89.439697265625,\n 41.44272637767212\n ],\n [\n -89.8681640625,\n 41.253032440653186\n ],\n [\n -90.32958984375,\n 40.64730356252251\n ],\n [\n -90.791015625,\n 39.93501296038254\n ],\n [\n -90.791015625,\n 39.257778150283364\n ],\n [\n -90.52734374999999,\n 38.659777730712534\n ],\n [\n -90.098876953125,\n 38.65119833229951\n ],\n [\n -90.087890625,\n 39.07037913108751\n ],\n [\n -90.4833984375,\n 39.45316112807394\n ],\n [\n -90.06591796875,\n 40.027614437486655\n ],\n [\n -89.088134765625,\n 40.94671366508002\n ],\n [\n -88.2861328125,\n 41.29431726315258\n ],\n [\n -87.5830078125,\n 41.73852846935917\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kallis, Jahn L.","contributorId":205603,"corporation":false,"usgs":false,"family":"Kallis","given":"Jahn","email":"","middleInitial":"L.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":817507,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Erickson, Richard A. 0000-0003-4649-482X rerickson@usgs.gov","orcid":"https://orcid.org/0000-0003-4649-482X","contributorId":5455,"corporation":false,"usgs":true,"family":"Erickson","given":"Richard","email":"rerickson@usgs.gov","middleInitial":"A.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":817508,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fritts, Mark W.","contributorId":139239,"corporation":false,"usgs":false,"family":"Fritts","given":"Mark","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":817509,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70221394,"text":"70221394 - 2020 - USGS Illinois River monitoring and evaluation","interactions":[],"lastModifiedDate":"2021-11-01T19:06:35.968534","indexId":"70221394","displayToPublicDate":"2021-06-01T08:08:15","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"displayTitle":"USGS Illinois River Monitoring and Evaluation","title":"USGS Illinois River monitoring and evaluation","docAbstract":"Asian carp monitoring and contract removal will continue throughout the Upper Illinois Waterway system as needed for adaptive management to mitigate, control, and contain Asian carp. Compiling data from monitoring and removal efforts into a centralized database (Illinois River Catch Database application) facilitates data standardization, quality, accessibility, sharing, and analysis to aid in Asian carp removal efforts, evaluations of management actions, and modeling efforts (e.g., SEACarP model). Data summarization, visualization, and modeling supports a better understanding of bigheaded carp life history, behavior, and habitat use. Integrating Asian carp-related data and analyses into decision support tools and products aids in applying control and containment methods in an informed and transparent manner (e.g., improved efficiencies in implementations of the Unified Method, inform targeted removal efforts or deterrent deployments in key locations based on preferential benthic characteristics and environmental conditions).","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"2020 Asian Carp Monitoring and Response Plan","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"Invasive Species Regional Coordinating Committee","usgsCitation":"Harrison, T.J., Hop, K.D., Hlavacek, E., and Knights, B.C., 2020, USGS Illinois River monitoring and evaluation, 4 p.","productDescription":"4 p.","startPage":"87","endPage":"90","ipdsId":"IP-119472","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":386469,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":391210,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://invasivecarp.us/Documents/Monitoring-Response-Plan-2020.pdf","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Illinois","otherGeospatial":"Illinois River Waterway system","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.5830078125,\n 41.73852846935917\n ],\n [\n -87.62695312499999,\n 42.00032514831621\n ],\n [\n -87.8466796875,\n 42.00032514831621\n ],\n [\n -88.26416015625,\n 41.713930073371294\n ],\n [\n -88.857421875,\n 41.60722821271717\n ],\n [\n -89.439697265625,\n 41.44272637767212\n ],\n [\n -89.8681640625,\n 41.253032440653186\n ],\n [\n -90.32958984375,\n 40.64730356252251\n ],\n [\n -90.791015625,\n 39.93501296038254\n ],\n [\n -90.791015625,\n 39.257778150283364\n ],\n [\n -90.52734374999999,\n 38.659777730712534\n ],\n [\n -90.098876953125,\n 38.65119833229951\n ],\n [\n -90.087890625,\n 39.07037913108751\n ],\n [\n -90.4833984375,\n 39.45316112807394\n ],\n [\n -90.06591796875,\n 40.027614437486655\n ],\n [\n -89.088134765625,\n 40.94671366508002\n ],\n [\n -88.2861328125,\n 41.29431726315258\n ],\n [\n -87.5830078125,\n 41.73852846935917\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Harrison, Travis J. 0000-0002-9195-738X","orcid":"https://orcid.org/0000-0002-9195-738X","contributorId":213966,"corporation":false,"usgs":true,"family":"Harrison","given":"Travis","email":"","middleInitial":"J.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":817503,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hop, Kevin D. 0000-0002-9928-4773 khop@usgs.gov","orcid":"https://orcid.org/0000-0002-9928-4773","contributorId":1438,"corporation":false,"usgs":true,"family":"Hop","given":"Kevin","email":"khop@usgs.gov","middleInitial":"D.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":817504,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hlavacek, Enrika 0000-0002-9872-2305 ehlavacek@usgs.gov","orcid":"https://orcid.org/0000-0002-9872-2305","contributorId":149114,"corporation":false,"usgs":true,"family":"Hlavacek","given":"Enrika","email":"ehlavacek@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":817505,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Knights, Brent C. 0000-0001-8526-8468 bknights@usgs.gov","orcid":"https://orcid.org/0000-0001-8526-8468","contributorId":2906,"corporation":false,"usgs":true,"family":"Knights","given":"Brent","email":"bknights@usgs.gov","middleInitial":"C.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":817506,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70210044,"text":"ofr20201042 - 2020 - Systems-deposits-commodities-critical minerals table for the earth mapping resources initiative","interactions":[],"lastModifiedDate":"2021-05-28T19:26:40.9176","indexId":"ofr20201042","displayToPublicDate":"2021-05-28T11:40:00","publicationYear":"2020","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":"2020-1042","displayTitle":"Systems-Deposits-Commodities-Critical Minerals Table for the Earth Mapping Resources Initiative","title":"Systems-deposits-commodities-critical minerals table for the earth mapping resources initiative","docAbstract":"To define and prioritize focus areas across the United States with resource potential for 35 critical minerals in a few years’ time, the U.S Geological Survey Earth Mapping Resources Initiative (Earth MRI) required an efficient approach to streamline workflow. A mineral systems approach based on current understanding of how ore deposits that contain critical minerals form and relate to broader geologic frameworks and the tectonic history of the Earth was used to satisfy this Earth MRI need. This report describes the rationale for, and structure of, a table developed for Earth MRI that relates critical minerals and principal commodities to the deposit types and mineral systems in which they are concentrated. The hierarchical relationship between systems, deposits, commodities, and critical minerals makes it possible to define and prioritize each system-based focus area once for all of the critical minerals that it may contain. This approach is advantageous because mineral systems are much larger than individual ore deposits and they generally have geologic features that can be “imaged” by the topographic, geologic, geochemical, and geophysical mapping techniques deployed by Earth MRI.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201042","usgsCitation":"Hofstra, A.H., and Kreiner, D.C., 2020, Systems-Deposits-Commodities-Critical Minerals Table for the Earth Mapping Resources Initiative (ver. 1.1, May 2021): U.S. Geological Survey Open-File Report 2020–1042, 26 p., \nhttps://doi.org/10.3133/ofr20201042.","productDescription":"Report: vii, 24 p.; Table","onlineOnly":"Y","ipdsId":"IP-115500","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":374652,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1042/coverthb2.jpg"},{"id":374653,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1042/ofr20201042.pdf","text":"Report","size":"3.01 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1042"},{"id":374654,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2020/1042/ofr20201042_table1.pdf","text":"Table 1. Systems-Deposits-Commodities-Critical Minerals Table for the Earth Mapping Resources Initiative","size":"196 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1042 Table 1"},{"id":385684,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2020/1042/versionHist.txt","size":"4.0 kB","linkFileType":{"id":2,"text":"txt"},"description":"OFR 2020-1042 version history"}],"edition":"Version 1.0: May 28, 2020; Version 1.1: May 19, 2021","contact":"Director, Geology, Geophysics, and Geochemistry Science Center
U.S. Geological Survey
MS 973, Box 25046
Denver, CO 80225
Anadromous Pacific salmon Oncorhynchus spp. are semelparous, and resource subsidies from spawning adult salmon (marine-derived nutrients [MDN]) benefit juvenile salmonids while they rear in freshwater. However, it is unclear if juvenile salmon populations respond predictably to the abundance of spawning salmon at the watershed scale. To address whether hypothesized benefits to rearing juveniles scale up to population and watershed scales, we examined juvenile Coho Salmon Oncorhynchus kisutch and Chinook Salmon O. tshawytscha growth, fork length, condition, and abundance as a function of MDN assimilation throughout the Unalakleet and North rivers in western Alaska. Additionally, a mark–recapture experiment provided abundance estimates of Coho Salmon smolts emigrating from these two rivers. Prior to spawning, residual MDN from past years offered little advantage to juvenile salmon. However, after the arrival of spawning adults, juveniles demonstrated a positive relationship between MDN and fish size, growth, and condition in fall and winter. Out-migrating smolts also benefitted from MDN resources via increased size and growth rates. Coho Salmon smolt abundance was unrelated to total spawner biomass, but a positive relationship between MDN assimilation and smolt abundance suggested a possible effect on overwinter survival. Furthermore, similar trends in spawner biomass and the abundance of age-1 smolts suggested that age at smolting was influenced by MDN. These relationships support the hypothesis that salmon spawner abundance during Coho and Chinook Salmon rearing is an important factor in the juvenile productivity of these species.
","language":"English","publisher":"Wiley","doi":"10.1002/tafs.10233","usgsCitation":"Joy, P.J., Stricker, C.A., Ivanoff, R., Wang, S.Y., Wipfli, M.S., Seitz, A., Huang, J., and Tyers, M.B., 2020, Juvenile Coho and Chinook salmon growth, size, and condition linked to watershed-scale salmon spawner abundance: Transactions of the American Fisheries Society, v. 150, no. 3, p. 307-326, https://doi.org/10.1002/tafs.10233.","productDescription":"20 p.","startPage":"307","endPage":"326","ipdsId":"IP-109480","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":395641,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Chirosky River, North River, Unalakleet River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -160.8185577392578,\n 63.82825415987884\n ],\n [\n -160.5370330810547,\n 63.82825415987884\n ],\n [\n -160.5370330810547,\n 63.91352961251089\n ],\n [\n -160.8185577392578,\n 63.91352961251089\n ],\n [\n -160.8185577392578,\n 63.82825415987884\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"150","issue":"3","noUsgsAuthors":false,"publicationDate":"2021-04-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Joy, Philip J.","contributorId":274930,"corporation":false,"usgs":false,"family":"Joy","given":"Philip","email":"","middleInitial":"J.","affiliations":[{"id":56688,"text":"adfg","active":true,"usgs":false}],"preferred":false,"id":833517,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stricker, Craig A. 0000-0002-5031-9437 cstricker@usgs.gov","orcid":"https://orcid.org/0000-0002-5031-9437","contributorId":1097,"corporation":false,"usgs":true,"family":"Stricker","given":"Craig","email":"cstricker@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":833516,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ivanoff, Renae","contributorId":274931,"corporation":false,"usgs":false,"family":"Ivanoff","given":"Renae","email":"","affiliations":[{"id":56689,"text":"nsedc","active":true,"usgs":false}],"preferred":false,"id":833518,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wang, Shiao Y.","contributorId":274932,"corporation":false,"usgs":false,"family":"Wang","given":"Shiao","email":"","middleInitial":"Y.","affiliations":[{"id":56690,"text":"usm","active":true,"usgs":false}],"preferred":false,"id":833519,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wipfli, Mark S. 0000-0002-4856-6068 mwipfli@usgs.gov","orcid":"https://orcid.org/0000-0002-4856-6068","contributorId":1425,"corporation":false,"usgs":true,"family":"Wipfli","given":"Mark","email":"mwipfli@usgs.gov","middleInitial":"S.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":833515,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Seitz, Andrew C.","contributorId":274933,"corporation":false,"usgs":false,"family":"Seitz","given":"Andrew C.","affiliations":[{"id":6695,"text":"UAF","active":true,"usgs":false}],"preferred":false,"id":833520,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Huang, Jiaqi","contributorId":274934,"corporation":false,"usgs":false,"family":"Huang","given":"Jiaqi","email":"","affiliations":[{"id":56688,"text":"adfg","active":true,"usgs":false}],"preferred":false,"id":833521,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Tyers, Mathew B.","contributorId":274935,"corporation":false,"usgs":false,"family":"Tyers","given":"Mathew","email":"","middleInitial":"B.","affiliations":[{"id":56688,"text":"adfg","active":true,"usgs":false}],"preferred":false,"id":833522,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70216163,"text":"sir20205090 - 2020 - Analysis of remedial scenarios affecting plume movement through a sole-source aquifer system, southeastern Nassau County, New York","interactions":[],"lastModifiedDate":"2021-04-27T17:33:12.761031","indexId":"sir20205090","displayToPublicDate":"2021-04-27T13:40:00","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-5090","displayTitle":"Analysis of Remedial Scenarios Affecting Plume Movement Through a Sole-Source Aquifer System, Southeastern Nassau County, New York","title":"Analysis of remedial scenarios affecting plume movement through a sole-source aquifer system, southeastern Nassau County, New York","docAbstract":"A steady-state three-dimensional groundwater-flow model based on present conditions is coupled with the particle-tracking program MODPATH to assess the fate and transport of volatile organic-compound plumes within the Magothy and upper glacial aquifers in southeastern Nassau County, New York. Particles are forward tracked from locations within plumes defined by surfaces of equal concentration. Particles move toward ultimate well capture and discharge to the general head and drain boundaries representing natural receptors in the models. Because rates of advection within coarse-grained sediments typically exceed 0.1 foot per day, mechanisms of dispersion and diffusion were assumed to be negligible. Resulting particle pathlines are influenced by hydrogeologic framework features and the interplay of nearby hydrologic stresses. Simulated hydrologic effects include cones of depression near pumping wells and water-table mounding near points of treated water recharge; however, remedial pumping amounts are balanced by treated-water return, and net effects at distant regional boundaries, including freshwater/saltwater interfaces, are minor.
Once a steady-state model was developed and calibrated, eight hypothetical remedial scenarios were evaluated to hydraulically contain the volatile organic-compound plumes. Specifically, the remedial scenarios were optimized to achieve full containment by altering the pumping-well locations, adjusting the pumping rates, and adjusting the discharge locations and rates. Based on the results, total hypothetical extraction rates varied from about 5,462 gallons per minute during an anticipated near-future condition to about 13,340 gallons per minute during full hydraulic containment of all site-related compounds identified by the New York State standards, criteria, and guidance for environmental investigations and cleanup. Targeting of high-concentration zones of the plume increases the total amount of remedial pumpage necessary to capture all parts of the plume but may decrease the total amount of time necessary to operate a remedial system. Simulated time frames of advective transport ranged from about 12 years to capture zones with elevated concentrations of volatile organic compounds (mean particle travel time plus the standard deviation of travel time) to more than 100 years to capture all zones.
Groundwater-flow model analysis indicates that all the optimal plume-containment scenarios would have negligible effects on streams and the saltwater-freshwater interface along the south shore of Long Island. Massapequa, Bellmore, Seaman, and Seaford Creeks are represented by using MODFLOW drain-boundary conditions. Saltwater-freshwater interfaces are represented by using MODFLOW general head-boundary conditions where the Magothy aquifer discharges upward into saline groundwater across the Gardiners clay confining unit and the Lloyd aquifer discharges upward into saline groundwater across the Raritan confining unit.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205090","collaboration":"Prepared in cooperation with the New York State Department of Environmental Conservation","usgsCitation":"Misut, P.E., Walter, D., Schubert, C., and Dressler, S., 2020, Analysis of remedial scenarios affecting plume movement through a sole-source aquifer system, southeastern Nassau County, New York: U.S. Geological Survey Scientific Investigations Report 2020–5090, 83 p., https://doi.org/10.3133/sir20205090.","productDescription":"Report: vi, 83 p.; Data Release; 5 Figures","numberOfPages":"83","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-105143","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":380266,"rank":4,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/sir/2020/5090/sir20205090_figures.zip","text":"High-resolution figures","size":"159 MB","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- Figures 16, 18, 20, 22, and 24"},{"id":380264,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9DOBQ8N","text":"USGS data release","linkHelpText":"MODFLOW–NWT and MODPATH6 model use to analyze remedial scenarios affecting plume movement through a sole-source aquifer system, southeastern Nassau County, New York"},{"id":380262,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5090/coverthb.jpg"},{"id":380263,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5090/sir20205090.pdf","text":"Report","size":"18.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5090"}],"country":"United States","state":"New York","county":"Nassau County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.87619018554688,\n 40.482470524589516\n ],\n [\n -73.289794921875,\n 40.482470524589516\n ],\n [\n -73.289794921875,\n 40.81796653313175\n ],\n [\n -73.87619018554688,\n 40.81796653313175\n ],\n [\n -73.87619018554688,\n 40.482470524589516\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New York Water Science Center
U.S. Geological Survey
425 Jordan Road
Troy, NY 12180–8349
We applied compound-specific sulfur isotope analysis (CSSIA) to organic matter (OM) extracted from ancient and immature organic-rich rocks from the Cretaceous Ghareb (Shefela Basin locality, Israel) and Miocene Monterey (Naples Beach locality, California, USA) Formations. Large variations in the δ34S values of different organosulfur compounds (OSCs), that reach up to 28‰ and 36‰, were observed in the Ghareb and Monterey samples, respectively. Additionally, some common OSCs in both locations showed consistent 34S trends relative to each other. The consistent enrichment in 34S of C35 hopane thiophene relative to iC20 thiophene in the studied sections probably resulted from differences in the timing of OM sulfurization. Reactive organic precursors quickly consume the most 34S-depleted reduced S, while less reactive species incorporate the heavier residual S at a later time. Despite the differences in the depositional environments, ages, and the initial δ34S values of the reduced S (represented by the δ34S of pyrite) between the Ghareb and the Monterey Formations, the sulfurization order of common organic compounds seems to be similar. All of the δ34S values of OSCs are 34S enriched relative to that of the coexisting pyrite with the exception of the C25 highly branched isoprenoid (HBI) thiophene in several samples from the Monterey Formation. The existence of 34S-depleted sulfurized HBI may point to OM sulfurization that occurred at or near the sediment-water interface during the deposition of the Monterey. Moreover, the δ34S of steroid sulfides shows an inverse trend with the pristane/phytane ratio, which may indicate that the sulfurization mechanism of these OSCs are affected by redox conditions. Further investigation of CSSI values in immature rocks from other basins may help constrain the OM sulfurization process, timescale, and depositional conditions and their possible use as paleoenvironmental proxies.
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