Computation of probabilistic earthquake hazard requires an estimate of Mmax: the moment magnitude of the largest earthquake that is thought to be possible within a specified geographic region. The region specified in this report is the Central and Eastern United States and adjacent Canada. Parts A and B of this report describe the construction of a global catalog of moderate to large earthquakes that occurred worldwide in tectonic analogs of the Central and Eastern United States. Examination of histograms of the magnitudes of these earthquakes allows estimation of Central and Eastern United States Mmax. The catalog and Mmax estimates derived from it are used in the 2014 edition of the U.S. Geological Survey national seismic-hazard maps. Part A deals with prehistoric earthquakes, and this part deals with historical events.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141025B","usgsCitation":"Wheeler, R.L., 2014, Earthquake catalog for estimation of maximum earthquake magnitude, Central and Eastern United States: Part B, historical earthquakes: U.S. Geological Survey Open-File Report 2014-1025, Report: iii, 30 p.; 1 Table, https://doi.org/10.3133/ofr20141025B.","productDescription":"Report: iii, 30 p.; 1 Table","numberOfPages":"33","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-057626","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":295927,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141025B.jpg"},{"id":295774,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1025/b/"},{"id":295925,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1025/b/pdf/ofr2014-1025b.pdf","size":"617 kB","linkFileType":{"id":1,"text":"pdf"}},{"id":295926,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2014/1025/b/downloads/table8.xlsx","text":"Table 8","size":"54.9 kB","linkFileType":{"id":3,"text":"xlsx"}}],"country":"United States","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"545c8d9ae4b0ba8303f70367","contributors":{"authors":[{"text":"Wheeler, Russell L. wheeler@usgs.gov","contributorId":858,"corporation":false,"usgs":true,"family":"Wheeler","given":"Russell","email":"wheeler@usgs.gov","middleInitial":"L.","affiliations":[],"preferred":false,"id":522761,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70129027,"text":"sim3314 - 2014 - Geologic map of the west-central Buffalo National River region, northern Arkansas","interactions":[],"lastModifiedDate":"2014-11-06T13:08:05","indexId":"sim3314","displayToPublicDate":"2014-11-06T13:45:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3314","title":"Geologic map of the west-central Buffalo National River region, northern Arkansas","docAbstract":"This map summarizes the geology of the west-central Buffalo National River region in the Ozark Plateaus region of northern Arkansas. Geologically, the region lies on the southern flank of the Ozark dome, an uplift that exposes oldest rocks at its center in Missouri. Physiographically, the map area spans the Springfield Plateau, a topographic surface generally held up by Mississippian cherty limestone and the higher Boston Mountains to the south, held up by Pennsylvanian rocks. The Buffalo River flows eastward through the map area, enhancing bedrock erosion of an approximately 1,600-ft- (490-m-) thick sequence of Ordovician, Mississippian, and Pennsylvanian carbonate and clastic sedimentary rocks that have been mildly deformed by a series of faults and folds. Quaternary surficial units are present as alluvial deposits along major streams, including a series of terrace deposits from the Buffalo River, as well as colluvium and landslide deposits mantling bedrock on hillslopes.
\n\n
This report provides a geologic map database of the map area that improves understanding of the regional geologic framework and its influence on the regional groundwater flow system. Furthermore, additional edits were made to the Ponca and Jasper quadrangles in the following ways: new control points on important contacts were obtained using modern GPS; recent higher resolution elevation data allowed further control on placement of contacts; some new contacts were added, in particular the contact separating the upper and lower Everton Formation.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3314","usgsCitation":"Hudson, M., and Turner, K.J., 2014, Geologic map of the west-central Buffalo National River region, northern Arkansas: U.S. Geological Survey Scientific Investigations Map 3314, 2 Plates: 58.0 x 51.5 inches and 58.0 x 29.0 inches; Downloads Directory, https://doi.org/10.3133/sim3314.","productDescription":"2 Plates: 58.0 x 51.5 inches and 58.0 x 29.0 inches; Downloads Directory","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-045630","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":295923,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sim3314.jpg"},{"id":295891,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3314/"},{"id":295920,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3314/pdf/SIM3314_west_sheet1.pdf","text":"Map Sheet 1 (West)","size":"71.1 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":295921,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3314/pdf/SIM3314_east_sheet2.pdf","text":"Map Sheet 2 (East)","size":"46.5","linkFileType":{"id":1,"text":"pdf"}},{"id":295922,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sim/3314/downloads/","text":"Downloads Directory"}],"scale":"24000","projection":"Universal Transverse Mercator projection","datum":"North American Datum of 1927","country":"United States","state":"Arkansas","otherGeospatial":"Buffalo National River","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"545c8d9ee4b0ba8303f7037e","contributors":{"authors":[{"text":"Hudson, Mark R. 0000-0003-0338-6079 mhudson@usgs.gov","orcid":"https://orcid.org/0000-0003-0338-6079","contributorId":1236,"corporation":false,"usgs":true,"family":"Hudson","given":"Mark R.","email":"mhudson@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":524264,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Turner, Kenzie J. 0000-0002-4940-3981 kturner@usgs.gov","orcid":"https://orcid.org/0000-0002-4940-3981","contributorId":496,"corporation":false,"usgs":true,"family":"Turner","given":"Kenzie","email":"kturner@usgs.gov","middleInitial":"J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":524265,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70099967,"text":"cir1393 - 2014 - Anisakiosis and pseudoterranovosis","interactions":[],"lastModifiedDate":"2018-07-06T15:12:58","indexId":"cir1393","displayToPublicDate":"2014-11-06T09:45:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":307,"text":"Circular","code":"CIR","onlineIssn":"2330-5703","printIssn":"1067-084X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1393","title":"Anisakiosis and pseudoterranovosis","docAbstract":"Anisakiosis and pseudoterranovosis are parasitic diseases caused by infection with larval nematodes or roundworms of the genera Anisakis and Pseudoterranova. These infections are zoonoses, meaning they are transmissible between animals and humans and vice versa. The life cycles of Anisakis spp., commonly called whaleworm, and Pseudoterranova spp., commonly called sealworm, are complex and involve three marine hosts (invertebrates, fish, and marine mammals). Whales, dolphins, or porpoises are the definitive hosts in which Anisakis spp. become sexually mature, and seals, sea lions, or walrus are the definitive hosts of Pseudoterranova spp. These zoonotic parasites have medical and economic importance and can result in considerable costs to the fishing industry. Humans are accidentally infected by consuming raw, poorly cooked, cold smoked, lightly salted, or marinated marine fish or squid, the intermediate hosts infected with larval stages. Human infections are becoming more common with the popularity of eating raw fish as well as improved medical diagnostics. This report, seventh in the series of U.S. Geological Survey Circulars on zoonotic diseases, will help us to better understand the routes of anisakiosis and pseudoterranovosis infections and how best to adequately monitor these zoonotic diseases.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1393","usgsCitation":"Measures, L., 2014, Anisakiosis and pseudoterranovosis: U.S. Geological Survey Circular 1393, vi, 33 p., https://doi.org/10.3133/cir1393.","productDescription":"vi, 33 p.","numberOfPages":"44","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-048865","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":295914,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/cir1393.jpg"},{"id":295913,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1393/pdf/circ1393.pdf"},{"id":295890,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/circ/1393/"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"545c8d98e4b0ba8303f7035e","contributors":{"authors":[{"text":"Measures, Lena","contributorId":118316,"corporation":false,"usgs":true,"family":"Measures","given":"Lena","email":"","affiliations":[],"preferred":false,"id":524263,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70131570,"text":"ofr20141225 - 2014 - Ecological implications of Laurel Wilt infestation on Everglades Tree Islands, southern Florida","interactions":[],"lastModifiedDate":"2016-04-19T11:34:56","indexId":"ofr20141225","displayToPublicDate":"2014-11-06T09:30:00","publicationYear":"2014","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":"2014-1225","title":"Ecological implications of Laurel Wilt infestation on Everglades Tree Islands, southern Florida","docAbstract":"There is a long history of introduced pests attacking native forest trees in the United States (Liebhold and others, 1995; Aukema and others, 2010). Well-known examples include chestnut blight that decimated the American chestnut (Castanea dentata), an extremely important tree in the eastern United States, both as a food source for wildlife and humans and for the wood; Dutch elm disease that attacks native elms (Ulmus spp.), including those commonly planted as shade trees along city streets; and the balsam wooly adelgid (Adelges piceae), an insect that is destroying Fraser firs (Abies fraseri) in higher elevations of Great Smoky Mountains National Park. Laurel wilt, a fungal disease transmitted by the redbay ambrosia beetle (Xyleborus glabratus), is a 21st-century example of an introduced forest pest that attacks native tree species in the laurel family (Lauraceae) (Mayfield, 2007; Hulcr and Dunn, 2011).
The introduction of laurel wilt disease has been traced to the arrival of an Asian ambrosia beetle (Xyleborus glabratus) at Port Wentworth, Georgia, near Savannah, in 2002, apparently accidently introduced in wooden shipping material (Mayfield, 2007). Within the next 2 years, it was determined that the non-native wood-boring insect was the vector of an undescribed species of fungus, responsible for killing large numbers of red bay (Persea borbonia) trees in the surrounding area. Dispersing female redbay ambrosia beetles drill into live trees and create tunnels in the wood. They carry with them fungal spores in specialized organs called mycangia at the base of each mandible and sow the spores in the tunnels they excavate. The fungus, since named Raffaelea lauricola (Harrington and others, 2008), is the food source for adults and larvae. The introduction of Raffaelea lauricola causes the host plant to react in such a way as to block the vascular tissue, resulting in loss of water conduction, wilt, and death (Kendra and others, 2013).
Although first seen in red bay, laurel wilt disease also kills other native trees that are members of the laurel family, including swamp bay (Persea palustris), silk bay (Persea borbonia var. humilis), and sassafras (Sassafras albidum), as well as the economically important cultivated avocado (Persea americana) (Fraedrich and others, 2008). This paper is concerned primarily with swamp bay, an important component of Everglades tree islands.
The spread of the redbay ambrosia beetle and its fungal symbiont has been very rapid, exceeding model predictions (Koch and Smith, 2008); by 2011, laurel wilt disease was found from the southern coastal plain of North Carolina to southern peninsular Florida. The first redbay ambrosia beetle was trapped in Miami-Dade County in March 2010, and laurel wilt disease was discovered in swamp bays in February 2011 and in commercial avocado groves about a year later (Kendra and others, 2013). By 2013, laurel wilt disease was seen in swamp bays throughout the southern Everglades in Everglades National Park, Big Cypress National Preserve, and Water Conservation Areas (WCAs) 3A and 3B (Rodgers and others, 2014).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141225","usgsCitation":"Snyder, J.R., 2014, Ecological implications of Laurel Wilt infestation on Everglades Tree Islands, southern Florida: U.S. Geological Survey Open-File Report 2014-1225, iv, 18 p., https://doi.org/10.3133/ofr20141225.","productDescription":"iv, 18 p.","numberOfPages":"26","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-056042","costCenters":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"links":[{"id":295912,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141225.JPG"},{"id":295892,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1225/"},{"id":295911,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1225/pdf/ofr2014-1225.pdf"}],"country":"United States","state":"Florida","otherGeospatial":"Everglades National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.19033813476562,\n 25.275745340949022\n ],\n [\n -81.17660522460938,\n 25.3241665257384\n ],\n [\n -81.16836547851562,\n 25.37753154832537\n ],\n [\n -81.18209838867188,\n 25.435833800555567\n ],\n [\n -81.21368408203125,\n 25.4866701822106\n ],\n [\n -81.2548828125,\n 25.553592617284565\n ],\n [\n -81.29608154296874,\n 25.615524531842528\n ],\n [\n -81.35101318359374,\n 25.66999808235069\n ],\n [\n -81.4031982421875,\n 25.740529092773226\n ],\n [\n -81.49795532226562,\n 25.798654774824335\n ],\n [\n -81.57211303710938,\n 25.84439325019514\n ],\n [\n -81.6448974609375,\n 25.88270106537761\n ],\n [\n -81.60369873046875,\n 25.916055815010868\n ],\n [\n -81.56112670898436,\n 25.91482062206972\n ],\n [\n -81.50894165039062,\n 25.949401131968656\n ],\n [\n -81.43615722656249,\n 25.944461680551118\n ],\n [\n -81.42105102539061,\n 25.94322678532246\n ],\n [\n -81.41555786132812,\n 25.899997297677864\n ],\n [\n -81.41143798828125,\n 25.86910939099931\n ],\n [\n -81.3812255859375,\n 25.856751966503136\n ],\n [\n -81.36749267578125,\n 25.903703303407667\n ],\n [\n -81.26724243164062,\n 25.904938612781873\n ],\n [\n -81.27410888671875,\n 25.849336891707605\n ],\n [\n -81.02828979492188,\n 25.693513062561056\n ],\n [\n -80.8538818359375,\n 25.695988053632746\n ],\n [\n -80.85525512695312,\n 25.849336891707605\n ],\n [\n -80.48309326171875,\n 25.855516152996614\n ],\n [\n -80.48583984375,\n 25.77392392167507\n ],\n [\n -80.49545288085938,\n 25.759082934951692\n ],\n [\n -80.49545288085938,\n 25.67866203603157\n ],\n [\n -80.51193237304688,\n 25.671235828577068\n ],\n [\n -80.518798828125,\n 25.65266828598998\n ],\n [\n -80.53115844726562,\n 25.65266828598998\n ],\n [\n -80.53253173828124,\n 25.642764414761196\n ],\n [\n -80.54763793945311,\n 25.63657407787705\n ],\n [\n -80.54763793945311,\n 25.618001141542337\n ],\n [\n -80.53939819335938,\n 25.608094394794268\n ],\n [\n -80.540771484375,\n 25.58703983205006\n ],\n [\n -80.56686401367188,\n 25.57341431679579\n ],\n [\n -80.5682373046875,\n 25.54244147012483\n ],\n [\n -80.57373046875,\n 25.512700007620513\n ],\n [\n -80.55999755859375,\n 25.50650294177565\n ],\n [\n -80.56549072265625,\n 25.47923205344432\n ],\n [\n -80.57510375976562,\n 25.47923205344432\n ],\n [\n -80.57510375976562,\n 25.469313832612475\n ],\n [\n -80.58883666992188,\n 25.46063471847754\n ],\n [\n -80.58746337890625,\n 25.42219111871144\n ],\n [\n -80.57510375976562,\n 25.42219111871144\n ],\n [\n -80.57373046875,\n 25.289404556494823\n ],\n [\n -80.43914794921875,\n 25.288162873186213\n ],\n [\n -80.43365478515625,\n 25.25960064916269\n ],\n [\n -80.42129516601562,\n 25.209911213827688\n ],\n [\n -80.3924560546875,\n 25.19002975536265\n ],\n [\n -80.41580200195312,\n 25.141555107671604\n ],\n [\n -80.45562744140625,\n 25.10301024053073\n ],\n [\n -80.47897338867188,\n 25.07440458233748\n ],\n [\n -80.52978515625,\n 25.0333500082522\n ],\n [\n -80.595703125,\n 24.98107885823501\n ],\n [\n -80.628662109375,\n 24.946219074360084\n ],\n [\n -80.70693969726562,\n 24.90263046793521\n ],\n [\n -80.76599121093749,\n 24.892665194900047\n ],\n [\n -81.0845947265625,\n 25.085598897064777\n ],\n [\n -81.13128662109375,\n 25.12787928859755\n ],\n [\n -81.1669921875,\n 25.157715464367914\n ],\n [\n -81.18209838867188,\n 25.19375777608886\n ],\n [\n -81.19445800781249,\n 25.236000699800467\n ],\n [\n -81.19033813476562,\n 25.275745340949022\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"545c8d9de4b0ba8303f70373","contributors":{"authors":[{"text":"Snyder, James R. jim_snyder@usgs.gov","contributorId":2760,"corporation":false,"usgs":true,"family":"Snyder","given":"James","email":"jim_snyder@usgs.gov","middleInitial":"R.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":524266,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70125934,"text":"ds886 - 2014 - Quality of surface water in Missouri, water year 2013","interactions":[],"lastModifiedDate":"2016-08-10T11:14:04","indexId":"ds886","displayToPublicDate":"2014-11-06T09:15:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"886","title":"Quality of surface water in Missouri, water year 2013","docAbstract":"The U.S. Geological Survey, in cooperation with the Missouri Department of Natural Resources, designed and operates a series of monitoring stations on streams and springs throughout Missouri known as the Ambient Water-Quality Monitoring Network. During the 2013 water year (October 1, 2012, through September 30, 2013), data were collected at 79 stations—73 Ambient Water-Quality Monitoring Network stations, 4 alternate Ambient Water-Quality Monitoring Network stations, and 2 U.S. Geological Survey National Stream Quality Accounting Network stations. Dissolved oxygen, specific conductance, water temperature, suspended solids, suspended sediment, Escherichia coli bacteria, fecal coliform bacteria, dissolved nitrate plus nitrite as nitrogen, total phosphorus, dissolved and total recoverable lead and zinc, and select pesticide compound summaries are presented for 76 of these stations. The stations primarily have been classified into groups corresponding to the physiography of the State, primary land use, or unique station types. In addition, a summary of hydrologic conditions in the State including peak discharges, monthly mean discharges, and 7-day low flow is presented.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds886","collaboration":"Prepared in cooperation with the Missouri Department of Natural Resources","usgsCitation":"Barr, M.N., and Schneider, R.E., 2014, Quality of surface water in Missouri, water year 2013: U.S. Geological Survey Data Series 886, iv, 21 p., https://doi.org/10.3133/ds886.","productDescription":"iv, 21 p.","numberOfPages":"30","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2013-01-01","temporalEnd":"2013-12-31","ipdsId":"IP-058570","costCenters":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true}],"links":[{"id":295907,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds886.jpg"},{"id":295894,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0886/"},{"id":295906,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0886/pdf/ds886.pdf"}],"country":"United States","state":"Missouri","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"545c8da1e4b0ba8303f703a6","contributors":{"authors":[{"text":"Barr, Miya N. 0000-0002-9961-9190 mnbarr@usgs.gov","orcid":"https://orcid.org/0000-0002-9961-9190","contributorId":3686,"corporation":false,"usgs":true,"family":"Barr","given":"Miya","email":"mnbarr@usgs.gov","middleInitial":"N.","affiliations":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":524274,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schneider, Rachel E. rschneider@usgs.gov","contributorId":5786,"corporation":false,"usgs":true,"family":"Schneider","given":"Rachel","email":"rschneider@usgs.gov","middleInitial":"E.","affiliations":[],"preferred":true,"id":524275,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70126400,"text":"sir20145172 - 2014 - Groundwater levels in the Denver Basin bedrock aquifers of Douglas County, Colorado, 2011-2013","interactions":[],"lastModifiedDate":"2014-12-02T10:44:54","indexId":"sir20145172","displayToPublicDate":"2014-11-06T09:15:00","publicationYear":"2014","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":"2014-5172","title":"Groundwater levels in the Denver Basin bedrock aquifers of Douglas County, Colorado, 2011-2013","docAbstract":"More than 70 percent of the municipal water supply in the south Denver metropolitan area is provided by groundwater, and homeowners in rural areas depend solely on self-supplied groundwater for water supply. Increased groundwater withdrawal to meet the demand of the rapidly growing population is causing water levels to decline. The U.S. Geological Survey, in cooperation with the Rural Water Authority of Douglas County, began a study in 2011 to assess the groundwater resources of the Denver Basin aquifers within Douglas County, Colorado. The primary purpose of this study was to monitor changes in the groundwater levels of the bedrock aquifers of the Denver Basin within rural Douglas County. To better assess the water resources of the Denver Basin bedrock aquifers, a groundwater monitoring network was established in 2011. More than 500 manual and 213,900 automated water-level measurements collected from the 36 domestic-well network between April 2011 and June 2013 showed water-level declines in all aquifers.
\n\n
Manual and automated (time-series) water-level data collection from these sites between 2011 and 2013 showed water level declines in 36 wells. Over the 2-year monitoring period, average declines of approximately 0.4 foot per year were observed in the upper Dawson aquifer, declines of over 2.6 feet per year were observed in the lower Dawson aquifer, declines of about 3.2 feet per year were observed in the Denver aquifer, declines of about 1.9 feet per year were observed in the Arapahoe aquifer, and declines of about 9.9 feet per year were observed in the Laramie-Fox Hills aquifer.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145172","collaboration":"Prepared in cooperation with the Rural Water Authority of Douglas County","usgsCitation":"Everett, R., 2014, Groundwater levels in the Denver Basin bedrock aquifers of Douglas County, Colorado, 2011-2013: U.S. Geological Survey Scientific Investigations Report 2014-5172, viii, 45 p., https://doi.org/10.3133/sir20145172.","productDescription":"viii, 45 p.","numberOfPages":"56","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-055778","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":295924,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145172.jpg"},{"id":295918,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5172/"},{"id":295919,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5172/pdf/sir2014-5172.pdf"}],"country":"United States","state":"Colorado","county":"Douglas County","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"545c8d9ee4b0ba8303f70385","contributors":{"authors":[{"text":"Everett, Rhett R. 0000-0001-7983-6270 reverett@usgs.gov","orcid":"https://orcid.org/0000-0001-7983-6270","contributorId":843,"corporation":false,"usgs":true,"family":"Everett","given":"Rhett R.","email":"reverett@usgs.gov","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":false,"id":524352,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70129339,"text":"sir20145203 - 2014 - Selenium in the upper Blackfoot River watershed, southeastern Idaho, 2001-12","interactions":[],"lastModifiedDate":"2015-08-11T09:02:02","indexId":"sir20145203","displayToPublicDate":"2014-11-06T09:15:00","publicationYear":"2014","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":"2014-5203","title":"Selenium in the upper Blackfoot River watershed, southeastern Idaho, 2001-12","docAbstract":"The upper Blackfoot River in southeastern Idaho receives runoff from 12 large phosphate mines. Waste shales that are removed to access the phosphate ore are highly enriched with selenium, resulting in elevated selenium in runoff from the mine waste dumps. In 2001, in cooperation with the Bureau of Land Management, the U.S. Geological Survey (USGS) began monitoring streamflow, selenium, and other water-quality parameters at a single location near the outlet of the upper Blackfoot River to the Blackfoot Reservoir. Water samples primarily were collected by a flow triggered, automated pump sampler, supplemented by manual point and equal-width integrated manual samples.
\n\n
The approach to monitoring concentrations and streamflow over time at a fixed location is ideal for evaluating temporal trends, but provides no information about the relative source contributions from the mine waste dumps draining into various tributaries. In 2001, the Idaho Department of Environmental Quality (IDEQ) began an annual, mid-May, synoptic survey of selenium concentrations and streamflow at 21 locations along the main stem Blackfoot River and its tributaries. Individually, neither the intensive USGS sampling at the outlet nor the IDEQ annual synoptic sampling provides a comprehensive view of selenium runoff in the Blackfoot River watershed. Together, the efforts are complementary; therefore, in this report, results are presented from both sampling efforts.
\n\n
The USGS collected time-series data from 2001 to 2012 at a fixed location, the Blackfoot River near the outlet of the reservoir, near Henry, Idaho (USGS streamgage 13063000). Dissolved selenium concentrations from 450 filtered samples collected at this site ranged from 0.5 to 11.4 micrograms per liter (μg/L). The State of Idaho chronic aquatic life criterion concentration of 5 μg/L was exceeded in 31 percent of the samples, with most exceedances occurring during May of each year. No exceedances of the selenium criterion were recorded in months other than April, May, or June. Concentrations of selenium in unfiltered and filtered samples were similar, and concentrations from samples collected by depth and width integrated methods were similar to those collected by grab (point) samples, indicating that the grab samples adequately represent selenium concentrations across the entire river cross section. In speciation analyses made during 2003 and 2004, the median percentage of total selenium as selenate was 81 percent, ranging from 17 to 98 percent, and the median percentage of total selenium as selenite was 19 percent, ranging from 2 to 83 percent of the total selenium. During the period of study, selenium concentrations had an upward trend during the lowflow season of August–October. Time trends were not obvious during other seasons. Selenium daily loads varied by more than a factor of 900 during the study period and ranged from 0.03 kilograms per day (kg/d) to more than 24 kg/d. Annual maximum daily loads of selenium varied over nearly a factor of 12, ranging from about 2 to 24 kg/d.
\n\n
For the annual spring synoptic samples collected by the IDEQ along the main stem Blackfoot River and major tributaries, selenium concentrations ranged from less than 2 to 870 μg/L in 176 samples. In most years, the synoptic sampling showed that the majority of the selenium loads passing the USGS streamgage at the outlet of the watershed could be attributed to a single tributary, East Mill Creek, which enters the Blackfoot River through Spring Creek. Selenium loads decreased by about half from East Mill Creek before reaching the Blackfoot River, suggesting that much selenium is at least temporarily removed from the water column by uptake by aquatic vegetation or by losses to sediment. Similar decreases in selenium loads occurred through the main stem Blackfoot River before reaching the outlet in low flow years, but not in high flow years.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145203","collaboration":"Prepared in cooperation with the Bureau of Land Management","usgsCitation":"Mebane, C.A., Mladenka, G.C., Van Every, Lynn, Williams, M.L., Hardy, M.A., and Garbarino, J.R., 2014, Selenium in the upper Blackfoot River watershed, southeastern Idaho, 2001–12, with an appendix on selenium speciation analytical methods, by Garbarino, J.R. (ver.1.1, August 2015): U.S. Geological Survey Scientific Investigations Report 2014-5203, 34 p., plus appendixes, https://dx.doi.org/10.3133/sir20145203.","productDescription":"Report: vi, 34 p.; 5 Appendixes","numberOfPages":"44","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2001-01-01","temporalEnd":"2012-12-31","ipdsId":"IP-048924","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":295905,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145203.jpg"},{"id":295899,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5203/pdf/sir2014-5203.pdf","text":"Report","size":"2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2014-5203 report"},{"id":295900,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5203/downloads/sir2014-5203_appendixa.kml","text":"Appendix A","size":"7 KB"},{"id":295901,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5203/downloads/sir2014-5203_appendixb.pdf","text":"Appendix B","size":"280 KB","linkFileType":{"id":1,"text":"pdf"}},{"id":295902,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5203/downloads/sir2014-5203_appendixc.pdf","text":"Appendix C","size":"706 KB","linkFileType":{"id":1,"text":"pdf"}},{"id":295895,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5203/"},{"id":295903,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5203/downloads/sir2014-5203_appendixd.xlsx","text":"Appendix D","size":"321 KB","linkFileType":{"id":3,"text":"xlsx"}},{"id":295904,"rank":8,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5203/downloads/sir2014-5203_appendixe.pdf","text":"Appendix E","size":"507 KB","linkFileType":{"id":1,"text":"pdf"}},{"id":306562,"rank":9,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2014/5203/versionHist.pdf","linkFileType":{"id":1,"text":"pdf"}}],"scale":"100000","projection":"Transverse Mercator projection","datum":"North American Datum of 1983","country":"United States","state":"Idaho","otherGeospatial":"Blackfoot River watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.544189453125,\n 42.49842801732158\n ],\n [\n -111.544189453125,\n 42.974511174899156\n ],\n [\n -111.0662841796875,\n 42.974511174899156\n ],\n [\n -111.0662841796875,\n 42.49842801732158\n ],\n [\n -111.544189453125,\n 42.49842801732158\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1: Originally posted November 5, 2014; Version 1.1: August 2015","contact":"Director, Idaho Water Science Center
U.S. Geological Survey
230 Collins Road
Boise, Idaho 83702
http://id.water.usgs.gov
Until recently, the rare-earth elements (REEs) were familiar to a relatively small number of people, such as chemists, geologists, specialized materials scientists, and engineers. In the 21st century, the REEs have gained visibility through many media outlets because of (1) the public has recognized the critical, specialized properties that REEs contribute to modern technology, as well as (2) China's dominance in production and supply of the REEs and (3) international dependence on China for the majority of the world's REE supply.
Since the late 1990s, China has provided 85–95 percent of the world’s REEs. In 2010, China announced their intention to reduce REE exports. During this timeframe, REE use increased substantially. REEs are used as components in high technology devices, including smart phones, digital cameras, computer hard disks, fluorescent and light-emitting-diode (LED) lights, flat screen televisions, computer monitors, and electronic displays. Large quantities of some REEs are used in clean energy and defense technologies. Because of the many important uses of REEs, nations dependent on new technologies, such as Japan, the United States, and members of the European Union, reacted with great concern to China’s intent to reduce its REE exports. Consequently, exploration activities intent on discovering economic deposits of REEs and bringing them into production have increased.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20143078","collaboration":"USGS Mineral Resources Program","usgsCitation":"Van Gosen, B.S., Verplanck, P.L., Long, K.R., Gambogi, J., and Seal, R., 2014, The rare-earth elements: Vital to modern technologies and lifestyles: U.S. Geological Survey Fact Sheet 2014-3078, 4 p., https://doi.org/10.3133/fs20143078.","productDescription":"4 p.","numberOfPages":"4","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-051526","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":295910,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20143078.jpg"},{"id":295909,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2014/3078/pdf/fs2014-3078.pdf"},{"id":295908,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2014/3078/"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"545c8da2e4b0ba8303f703b7","contributors":{"authors":[{"text":"Van Gosen, Bradley S. 0000-0003-4214-3811 bvangose@usgs.gov","orcid":"https://orcid.org/0000-0003-4214-3811","contributorId":1174,"corporation":false,"usgs":true,"family":"Van Gosen","given":"Bradley","email":"bvangose@usgs.gov","middleInitial":"S.","affiliations":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":519244,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Verplanck, Philip L. 0000-0002-3653-6419 plv@usgs.gov","orcid":"https://orcid.org/0000-0002-3653-6419","contributorId":728,"corporation":false,"usgs":true,"family":"Verplanck","given":"Philip","email":"plv@usgs.gov","middleInitial":"L.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":524284,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Long, Keith R. 0000-0002-6457-2820 klong@usgs.gov","orcid":"https://orcid.org/0000-0002-6457-2820","contributorId":2279,"corporation":false,"usgs":true,"family":"Long","given":"Keith","email":"klong@usgs.gov","middleInitial":"R.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":524285,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gambogi, Joseph 0000-0002-5719-2280 jgambogi@usgs.gov","orcid":"https://orcid.org/0000-0002-5719-2280","contributorId":4424,"corporation":false,"usgs":true,"family":"Gambogi","given":"Joseph","email":"jgambogi@usgs.gov","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":false,"id":524286,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Seal, Robert R. II 0000-0003-0901-2529 rseal@usgs.gov","orcid":"https://orcid.org/0000-0003-0901-2529","contributorId":397,"corporation":false,"usgs":true,"family":"Seal","given":"Robert R.","suffix":"II","email":"rseal@usgs.gov","affiliations":[],"preferred":false,"id":524287,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70129421,"text":"fs20143105 - 2014 - Mapping traditional place names along the Koyukuk River: Koyukuk, Huslia, and Hughes, Western Interior Alaska","interactions":[],"lastModifiedDate":"2014-11-06T08:52:40","indexId":"fs20143105","displayToPublicDate":"2014-11-06T09:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-3105","title":"Mapping traditional place names along the Koyukuk River: Koyukuk, Huslia, and Hughes, Western Interior Alaska","docAbstract":"Koyukon Athabascan peoples have settled along the Koyukuk River in Western Interior Alaska for thousands of years using the surrounding landscape for subsistence and cultural resources. However, recent changes in climate, technology, resource availability, and way of life have affected land-use patterns in the region, as well as use of the Denaakk'e (Koyukon) language. The current Koyukon population is about 2,300, and about 150 still speak the language (the youngest of whom are in their fifties). In addition, Elders, important keepers of both language and traditional subsistence-use areas, are aging, and opportunities to record their knowledge are diminishing.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20143105","collaboration":"Eliza Jones - Koyukuk Elder; Susan Paskvan - Yukon- Koyukuk School District; Karin Bodony - Fish and Wildlife Service; Catherine Moncrieff - Yukon River Drainage Fisheries Association","usgsCitation":"McCloskey, S., and Jones, B.M., 2014, Mapping traditional place names along the Koyukuk River: Koyukuk, Huslia, and Hughes, Western Interior Alaska: U.S. Geological Survey Fact Sheet 2014-3105, 2 p., https://doi.org/10.3133/fs20143105.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-059057","costCenters":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"links":[{"id":295898,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20143105.JPG"},{"id":295896,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2014/3105/"},{"id":295897,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2014/3105/pdf/fs2014-3105.pdf"}],"country":"United States","state":"Alaska","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"545c8d9fe4b0ba8303f7039b","contributors":{"authors":[{"text":"McCloskey, Sarah E. smccloskey@usgs.gov","contributorId":4850,"corporation":false,"usgs":true,"family":"McCloskey","given":"Sarah E.","email":"smccloskey@usgs.gov","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":false,"id":524283,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jones, Benjamin M. 0000-0002-1517-4711 bjones@usgs.gov","orcid":"https://orcid.org/0000-0002-1517-4711","contributorId":2286,"corporation":false,"usgs":true,"family":"Jones","given":"Benjamin","email":"bjones@usgs.gov","middleInitial":"M.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"preferred":true,"id":524282,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70127140,"text":"cir1405 - 2014 - Estimated use of water in the United States in 2010","interactions":[],"lastModifiedDate":"2014-11-06T11:09:49","indexId":"cir1405","displayToPublicDate":"2014-11-05T08:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":307,"text":"Circular","code":"CIR","onlineIssn":"2330-5703","printIssn":"1067-084X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1405","title":"Estimated use of water in the United States in 2010","docAbstract":"Water use in the United States in 2010 was estimated to be about 355 billion gallons per day (Bgal/d), which was 13 percent less than in 2005. The 2010 estimates put total withdrawals at the lowest level since before 1970. Freshwater withdrawals were 306 Bgal/d, or 86 percent of total withdrawals, and saline-water withdrawals were 48.3 Bgal/d, or 14 percent of total withdrawals. Fresh surface-water withdrawals (230 Bgal/d) were almost 15 percent less than in 2005, and fresh groundwater withdrawals (76.0 Bgal/d) were about 4 percent less than in 2005. Saline surface-water withdrawals were 45.0 Bgal/d, or 24 percent less than in 2005. Updates to the 2005 saline groundwater withdrawals, mostly for thermoelectric power, reduced total saline groundwater withdrawals to 1.51 Bgal/d, down from the originally reported 3.02 Bgal/d. Total saline groundwater withdrawals in 2010 were 3.29 Bgal/d, mostly for mining use.
\n\n
Thermoelectric power and irrigation remained the two largest uses of water in 2010, and total withdrawals for both were notably less than in 2005. Withdrawals in 2010 for thermoelectric power were 20 percent less and withdrawals for irrigation were 9 percent less than in 2005. Similarly, other uses showed reductions compared to 2005, specifically public supply (–5 percent), self-supplied domestic (–3 percent), self-supplied industrial (–12 percent), and livestock (–7 percent). Only mining (39 percent) and aquaculture (7 percent) reported larger withdrawals in 2010 compared to 2005. Thermoelectric power, irrigation, and public-supply withdrawals accounted for 90 percent of total withdrawals in 2010.
\n\n
Withdrawals for thermoelectric power were 161 Bgal/d in 2010 and represented the lowest levels since before 1970. Surface-water withdrawals accounted for more than 99 percent of total thermoelectric-power withdrawals, and 73 percent of those surface-water withdrawals were from freshwater sources. Saline surface-water withdrawals for thermoelectric power accounted for 97 percent of total saline surface-water withdrawals for all uses. Thermoelectric-power withdrawals accounted for 45 percent of total withdrawals for all uses, and freshwater withdrawals for thermoelectric power accounted for 38 percent of the total freshwater withdrawals for all uses.
\n\n
Irrigation withdrawals were 115 Bgal/d in 2010 and represented the lowest levels since before 1965. Irrigation withdrawals, all freshwater, accounted for 38 percent of total freshwater withdrawals for all uses, or 61 percent of total freshwater withdrawals for all uses excluding thermoelectric power. Surface-water withdrawals (65.9 Bgal/d) accounted for 57 percent of the total irrigation withdrawals, or about 12 percent less than in 2005. Groundwater withdrawals were 49.5 Bgal/d in 2010, about 6 percent less than in 2005. About 62,400 thousand acres were irrigated in 2010, an increase from 2005 of about 950 thousand acres (1.5 percent). The number of acres irrigated using sprinkler and microirrigation systems continued to increase and accounted for 58 percent of the total irrigated lands in 2010.
\n\n
Public-supply withdrawals in 2010 were 42.0 Bgal/d, or 5 percent less than in 2005, and represented the first declines in public-supply withdrawals since the 5-year reporting began in 1950. Total population in the United States increased from 300.7 million people in 2005 to 313.0 million people in 2010, an increase of 4 percent. Public-supply withdrawals accounted for 14 percent of the total freshwater withdrawals for all uses and 22 percent of freshwater withdrawals for all uses excluding thermoelectric power. The number of people that received potable water from public-supply facilities in 2010 was 268 million, or about 86 percent of the total U.S. population. This percentage was unchanged from 2005. Self-supplied domestic withdrawals were 3.60 Bgal/d, or 3 percent less than in 2005. More than 98 percent of the self-supplied domestic withdrawals were from groundwater sources.
\n\n
Self-supplied industrial withdrawals were 15.9 Bgal/d in 2010, a 12 percent decline from 2005, and continued the downward trend since the peak of 47 Bgal/d in 1970. Total self-supplied industrial withdrawals were 4 percent of total withdrawals for all uses and 8 percent of total withdrawals for all uses excluding thermoelectric power. Most of the total self-supplied industrial withdrawals were from surface-water sources (82 percent), and nearly all (93 percent) of those surface-water withdrawals were from freshwater sources. Nearly all of the groundwater withdrawals for self-supplied industrial use (98 percent) were from freshwater sources.
\n\n
Total aquaculture withdrawals were 9.42 Bgal/d in 2010, or 7 percent more than in 2005, and surface water was the primary source (81 percent). Most of the surface-water withdrawals occurred at facilities that operated flowthrough raceways, which returned the water to the source directly after use. Aquaculture withdrawals accounted for 3 percent of the total withdrawals for all uses and 5 percent of the total withdrawals for all uses excluding thermoelectric.
\n\n
Total mining withdrawals in 2010 were 5.32 Bgal/d, or about 1 percent of total withdrawals from all uses and 3 percent of total withdrawals from all uses excluding thermoelectric. Mining withdrawals accounted for the largest percentage increase (39 percent) in water use between 2005 and 2010 among all the categories. Groundwater withdrawals accounted for 73 percent of the total mining withdrawals, and the majority of the groundwater was saline (71 percent). The majority (80 percent) of surface-water withdrawals for mining was freshwater.
\n\n
Livestock withdrawals in 2010 were 2.00 Bgal/d, or 7 percent less than in 2005. All livestock withdrawals were from freshwater sources, mostly from groundwater (60 percent). Livestock withdrawals accounted for about 1 percent of total freshwater withdrawals for all uses excluding thermoelectric power.
\n\n
In 2010, more than 50 percent of the total withdrawals in the United States were accounted for by 12 States. California accounted for about 11 percent of the total withdrawals and 10 percent of freshwater withdrawals in the United States, predominantly for irrigation. Texas accounted for about 7 percent of total withdrawals, predominantly for thermoelectric power, irrigation, and public supply. Florida accounted for 18 percent of the total saline-water withdrawals in the United States, mostly from surface-water sources for thermoelectric power. Oklahoma and Texas accounted for about 70 percent of the total saline groundwater withdrawals in the United States, mostly for mining.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1405","usgsCitation":"Maupin, M.A., Kenny, J.F., Hutson, S.S., Lovelace, J.K., Barber, N.L., and Linsey, K.S., 2014, Estimated use of water in the United States in 2010: U.S. Geological Survey Circular 1405, Report: iv, 56 p.; County-level data; Related work, https://doi.org/10.3133/cir1405.","productDescription":"Report: iv, 56 p.; County-level data; Related work","numberOfPages":"64","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057650","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":295888,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/cir1405.jpg"},{"id":295877,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1405/pdf/circ1405.pdf"},{"id":295878,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/fs/2014/3109/"},{"id":295879,"rank":4,"type":{"id":7,"text":"Companion Files"},"url":"https://water.usgs.gov/watuse/data/2010/"},{"id":295876,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/circ/1405/"}],"country":"United States","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"545b3c19e4b009f8aec98d48","contributors":{"authors":[{"text":"Maupin, Molly A. 0000-0002-2695-5505 mamaupin@usgs.gov","orcid":"https://orcid.org/0000-0002-2695-5505","contributorId":951,"corporation":false,"usgs":true,"family":"Maupin","given":"Molly","email":"mamaupin@usgs.gov","middleInitial":"A.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":519593,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kenny, Joan F. jkenny@usgs.gov","contributorId":3676,"corporation":false,"usgs":true,"family":"Kenny","given":"Joan","email":"jkenny@usgs.gov","middleInitial":"F.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":false,"id":519596,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hutson, Susan S. sshutson@usgs.gov","contributorId":2040,"corporation":false,"usgs":true,"family":"Hutson","given":"Susan","email":"sshutson@usgs.gov","middleInitial":"S.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":519595,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lovelace, John K. 0000-0002-8532-2599 jlovelac@usgs.gov","orcid":"https://orcid.org/0000-0002-8532-2599","contributorId":999,"corporation":false,"usgs":true,"family":"Lovelace","given":"John","email":"jlovelac@usgs.gov","middleInitial":"K.","affiliations":[{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":519594,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Barber, Nancy L. 0000-0002-2952-5017 nlbarber@usgs.gov","orcid":"https://orcid.org/0000-0002-2952-5017","contributorId":3679,"corporation":false,"usgs":true,"family":"Barber","given":"Nancy","email":"nlbarber@usgs.gov","middleInitial":"L.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":519598,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Linsey, Kristin S. 0000-0001-6492-7639 kslinsey@usgs.gov","orcid":"https://orcid.org/0000-0001-6492-7639","contributorId":3678,"corporation":false,"usgs":true,"family":"Linsey","given":"Kristin","email":"kslinsey@usgs.gov","middleInitial":"S.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":519597,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70129724,"text":"fs20143109 - 2014 - Summary of estimated water use in the United States in 2010","interactions":[],"lastModifiedDate":"2014-11-04T22:48:07","indexId":"fs20143109","displayToPublicDate":"2014-11-05T08:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-3109","title":"Summary of estimated water use in the United States in 2010","docAbstract":"About 355,000 million gallons per day (Mgal/d) of water was withdrawn for use in the United States during 2010, a decline of 13 percent from 2005 and a substantial change from the level of about 400,000 Mgal/d reported from 1985 to 2005. Withdrawals for 2010 were lower than withdrawals estimated for 1970. Fresh surface-water withdrawals (230,000 Mgal/d) were almost 15 percent less than in 2005, and fresh groundwater withdrawals (76,000 Mgal/day) were about 4 percent less than in 2005. Saline surface-water withdrawals were 45,000 Mgal/d, or 24 percent less than in 2005, and saline groundwater withdrawals in 2010, mostly used for mining, were 3,290 Mgal/d.
\n\n
As in 2005, water withdrawals in four States—California, Texas, Idaho, and Florida—accounted for more than one-quarter of all fresh and saline water withdrawn in the United States in 2010. California accounted for 11 percent of the total withdrawals nationwide and 10 percent of the total freshwater withdrawals. More than 60 percent of California’s withdrawals were for irrigation, and 17 percent, almost exclusively saline water, was for thermoelectric power. In Texas, about 45 percent of withdrawals were for thermoelectric power, and 28 percent was for irrigation. Irrigation accounted for 81 percent of water withdrawn in Idaho, and thermoelectric power accounted for 61 percent of water withdrawn in Florida.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20143109","usgsCitation":"Barber, N.L., 2014, Summary of estimated water use in the United States in 2010: U.S. Geological Survey Fact Sheet 2014-3109, 2 p., https://doi.org/10.3133/fs20143109.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060372","costCenters":[{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true}],"links":[{"id":295889,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20143109.jpg"},{"id":295873,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2014/3109/"},{"id":295874,"rank":2,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/circ/1405"},{"id":295875,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2014/3109/pdf/fs2014-3109.pdf"}],"country":"United States","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"545b3c1be4b009f8aec98d4e","contributors":{"authors":[{"text":"Barber, Nancy L. 0000-0002-2952-5017 nlbarber@usgs.gov","orcid":"https://orcid.org/0000-0002-2952-5017","contributorId":3679,"corporation":false,"usgs":true,"family":"Barber","given":"Nancy","email":"nlbarber@usgs.gov","middleInitial":"L.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true},{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":519919,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70156257,"text":"70156257 - 2014 - Using ecological indicators and a decision support system for integrated ecological assessment at two national park units in the Mid-Atlantic region, U.S.A.","interactions":[],"lastModifiedDate":"2022-11-10T16:32:18.700862","indexId":"70156257","displayToPublicDate":"2014-11-05T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1547,"text":"Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Using ecological indicators and a decision support system for integrated ecological assessment at two national park units in the Mid-Atlantic region, U.S.A.","docAbstract":"We implemented an integrated ecological assessment using a GIS-based decision support system model for Upper Delaware Scenic and Recreational River (UPDE) and Delaware Water Gap National Recreation Area (DEWA)—national park units with the mid-Atlantic region of the United States. Our assessment examined a variety of aquatic and terrestrial indicators of ecosystem components that reflect the parks’ conservation purpose and reference condition. Our assessment compared these indicators to ecological thresholds to determine the condition of park watersheds. Selected indicators included chemical and physical measures of water quality, biologic indicators of water quality, and landscape condition measures. For the chemical and physical measures of water quality, we used a water quality index and each of its nine components to assess the condition of water quality in each watershed. For biologic measures of water quality, we used the Ephemeroptera, Plecoptera, Trichoptera aquatic macroinvertebrate index and, secondarily, the Hilsenhoff aquatic macroinvertebrate index. Finally, for the landscape condition measures of our model, we used percent forest and percent impervious surface. Based on our overall assessment, UPDE and DEWA watersheds had an ecological assessment score of 0.433 on a −1 to 1 fuzzy logic scale. This score indicates that, in general, the natural resource condition within watersheds at these parks is healthy or ecologically unimpaired; however, we had only partial data for many of our indicators. Our model is iterative and new data may be incorporated as they become available. These natural parks are located within a rapidly urbanizing landscape—we recommend that natural resource managers remain vigilant to surrounding land uses that may adversely affect natural resources within the parks.
","language":"English","publisher":"Springer","doi":"10.1007/s00267-014-0391-y","usgsCitation":"Mahan, C.G., Young, J.A., Miller, B., and Saunders, M.C., 2014, Using ecological indicators and a decision support system for integrated ecological assessment at two national park units in the Mid-Atlantic region, U.S.A.: Environmental Management, v. 55, no. 2, p. 508-522, https://doi.org/10.1007/s00267-014-0391-y.","productDescription":"14 p.","startPage":"508","endPage":"522","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061210","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":472651,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s00267-014-0391-y","text":"Publisher Index Page"},{"id":306857,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Jersey, New York, Pennsylvania","otherGeospatial":"Delaware Water Gap National Recreation Area, Upper Delaware Scenic and Recreational River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -75.16363259831336,\n 41.00157864774306\n ],\n [\n -75.18360089268816,\n 40.93121492169374\n ],\n [\n -75.10372771518792,\n 40.93456727654237\n ],\n [\n -75.10150901581329,\n 40.96305542448701\n ],\n [\n -74.91957566706338,\n 41.065176406050654\n ],\n [\n -74.7931098026881,\n 41.170479402035426\n ],\n [\n -74.81085939768826,\n 41.20220428653266\n ],\n [\n -74.77314150831329,\n 41.26560793794221\n ],\n [\n -74.7687041095635,\n 41.2906187651337\n ],\n [\n -74.65333174206344,\n 41.342277434101675\n ],\n [\n -74.69548703018819,\n 41.37225400060595\n ],\n [\n -74.79089110331344,\n 41.33894585228984\n ],\n [\n -74.8618894833131,\n 41.31228706249345\n ],\n [\n -74.90626347081299,\n 41.25726886581319\n ],\n [\n -74.90404477143836,\n 41.21388852711442\n ],\n [\n -74.93066916393812,\n 41.17214951599155\n ],\n [\n -74.96838705331307,\n 41.15210533865738\n ],\n [\n -75.03051063581313,\n 41.105311752732376\n ],\n [\n -75.05935372768802,\n 41.056811790208826\n ],\n [\n -75.16363259831336,\n 41.00157864774306\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -75.31006585769143,\n 41.939183002612225\n ],\n [\n -75.28566016456683,\n 41.8384297630042\n ],\n [\n -75.19469349019188,\n 41.84173566734978\n ],\n [\n -75.12591380956687,\n 41.80205354376042\n ],\n [\n -75.12813250894152,\n 41.762346830362134\n ],\n [\n -75.09485201831683,\n 41.74413970315629\n ],\n [\n -75.08597722081676,\n 41.63976304239466\n ],\n [\n -75.10594551519156,\n 41.60659218093528\n ],\n [\n -75.03494713519191,\n 41.51694563301149\n ],\n [\n -74.99279184706664,\n 41.453786486136295\n ],\n [\n -74.93954306206668,\n 41.450460615191105\n ],\n [\n -74.921793467067,\n 41.42717474429995\n ],\n [\n -74.75317231456697,\n 41.39722349174036\n ],\n [\n -74.74207881769173,\n 41.3839073914761\n ],\n [\n -74.69770483019184,\n 41.39722349174036\n ],\n [\n -74.71545442519201,\n 41.442145191832054\n ],\n [\n -74.8042024001918,\n 41.46043771647152\n ],\n [\n -74.86410728331671,\n 41.46708826471874\n ],\n [\n -74.92401216644163,\n 41.51030020105466\n ],\n [\n -74.95507395769167,\n 41.513623002313324\n ],\n [\n -75.0194162395669,\n 41.60493318994418\n ],\n [\n -75.02163493894153,\n 41.772275813796995\n ],\n [\n -75.04604063206665,\n 41.82520443777676\n ],\n [\n -75.15919430019153,\n 41.89790990874036\n ],\n [\n -75.23019268019168,\n 41.89790990874036\n ],\n [\n -75.25681707269143,\n 41.9655837730665\n ],\n [\n -75.31006585769143,\n 41.939183002612225\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"55","issue":"2","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2014-11-05","publicationStatus":"PW","scienceBaseUri":"55d45736e4b0518e35469508","contributors":{"authors":[{"text":"Mahan, Carolyn G.","contributorId":146582,"corporation":false,"usgs":false,"family":"Mahan","given":"Carolyn","email":"","middleInitial":"G.","affiliations":[{"id":12754,"text":"Penn State University Altoona","active":true,"usgs":false}],"preferred":false,"id":568352,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Young, John A. 0000-0002-4500-3673 jyoung@usgs.gov","orcid":"https://orcid.org/0000-0002-4500-3673","contributorId":3777,"corporation":false,"usgs":true,"family":"Young","given":"John","email":"jyoung@usgs.gov","middleInitial":"A.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":568351,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miller, Bruce","contributorId":146583,"corporation":false,"usgs":false,"family":"Miller","given":"Bruce","email":"","affiliations":[{"id":6945,"text":"private 3721 2nd Avenue, Salt Lake City","active":true,"usgs":false}],"preferred":false,"id":568353,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Saunders, Michael C.","contributorId":146584,"corporation":false,"usgs":false,"family":"Saunders","given":"Michael","email":"","middleInitial":"C.","affiliations":[{"id":16724,"text":"Penn Sate University","active":true,"usgs":false}],"preferred":false,"id":568354,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70132480,"text":"ofr20141230 - 2014 - Short-term occupancy and abundance dynamics of the Oregon spotted frog (Rana pretiosa) across its core range","interactions":[],"lastModifiedDate":"2017-11-22T14:21:32","indexId":"ofr20141230","displayToPublicDate":"2014-11-04T16:00:00","publicationYear":"2014","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":"2014-1230","displayTitle":"Short-term occupancy and abundance dynamics of the Oregon spotted frog (Rana pretiosa) across its core range","title":"Short-term occupancy and abundance dynamics of the Oregon spotted frog (Rana pretiosa) across its core range","docAbstract":"The Oregon spotted frog (Rana pretiosa) occupies only a fraction of its original range and is listed as Threatened under the Endangered Species Act. We surveyed 93 sites in a rotating frame design (2010–13) in the Klamath and Deschutes Basins, Oregon, which encompass most of the species’ core extant range. Oregon spotted frogs are declining in abundance and probability of site occupancy. We did not find an association between the probability that Oregon spotted frogs disappear from a site (local extinction) and any of the variables hypothesized to affect Oregon spotted frog occupancy. This 4-year study provides baseline data, but the 4-year period was too short to draw firm conclusions. Further study is essential to understand how habitat changes and management practices relate to the status and trends of this species.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141230","collaboration":"Prepared in cooperation with the Interagency Special Status / Sensitive Species Program (ISSSSP). The ISSSSP is a cooperative program of the Pacific Northwest Regional Office of the U.S. Forest Service and Oregon/Washington State Office of the Bureau of Land Management","usgsCitation":"Adams, M.J., Pearl, C.A., McCreary, B., and Galvan, S., 2014, Short-term occupancy and abundance dynamics of the Oregon spotted frog (Rana pretiosa) across its core range: U.S. Geological Survey Open-File Report 2014-1230, iv, 10 p., https://doi.org/10.3133/ofr20141230.","productDescription":"iv, 10 p.","numberOfPages":"18","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-059622","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":295887,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141230.jpg"},{"id":295880,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1230/"},{"id":295886,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1230/pdf/ofr2014-1230.pdf"}],"country":"United States","state":"Oregon","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5459eaa3e4b009f8aec9700e","contributors":{"authors":[{"text":"Adams, M. J. 0000-0001-8844-042X mjadams@usgs.gov","orcid":"https://orcid.org/0000-0001-8844-042X","contributorId":3133,"corporation":false,"usgs":false,"family":"Adams","given":"M.","email":"mjadams@usgs.gov","middleInitial":"J.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":523280,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pearl, Christopher A. 0000-0003-2943-7321 christopher_pearl@usgs.gov","orcid":"https://orcid.org/0000-0003-2943-7321","contributorId":3131,"corporation":false,"usgs":true,"family":"Pearl","given":"Christopher","email":"christopher_pearl@usgs.gov","middleInitial":"A.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":false,"id":523281,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McCreary, Brome 0000-0002-0313-7796 brome_mccreary@usgs.gov","orcid":"https://orcid.org/0000-0002-0313-7796","contributorId":3130,"corporation":false,"usgs":true,"family":"McCreary","given":"Brome","email":"brome_mccreary@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":523282,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Galvan, Stephanie 0000-0002-9864-3674 stephanie_galvan@usgs.gov","orcid":"https://orcid.org/0000-0002-9864-3674","contributorId":3135,"corporation":false,"usgs":true,"family":"Galvan","given":"Stephanie","email":"stephanie_galvan@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":523283,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70074082,"text":"sir20105090P - 2014 - Porphyry copper assessment of East and Southeast Asia: Philippines, Taiwan (Republic of China), Republic of Korea (South Korea), and Japan","interactions":[{"subject":{"id":70074082,"text":"sir20105090P - 2014 - Porphyry copper assessment of East and Southeast Asia: Philippines, Taiwan (Republic of China), Republic of Korea (South Korea), and Japan","indexId":"sir20105090P","publicationYear":"2014","noYear":false,"chapter":"P","title":"Porphyry copper assessment of East and Southeast Asia: Philippines, Taiwan (Republic of China), Republic of Korea (South Korea), and Japan"},"predicate":"IS_PART_OF","object":{"id":70040436,"text":"sir20105090 - 2010 - Global mineral resource assessment","indexId":"sir20105090","publicationYear":"2010","noYear":false,"title":"Global mineral resource assessment"},"id":1}],"isPartOf":{"id":70040436,"text":"sir20105090 - 2010 - Global mineral resource assessment","indexId":"sir20105090","publicationYear":"2010","noYear":false,"title":"Global mineral resource assessment"},"lastModifiedDate":"2020-07-01T19:22:00.184549","indexId":"sir20105090P","displayToPublicDate":"2014-11-04T14:30:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2010-5090","chapter":"P","title":"Porphyry copper assessment of East and Southeast Asia: Philippines, Taiwan (Republic of China), Republic of Korea (South Korea), and Japan","docAbstract":"The U.S. Geological Survey collaborated with member countries of the Coordinating Committee for Geoscience Programmes in East and Southeast Asia (CCOP) on an assessment of the porphyry copper resources of East and Southeast Asia as part of a global mineral resource assessment. The assessment covers the Philippines in Southeast Asia, and the Republic of Korea (South Korea), Taiwan (Province of China), and Japan in East Asia. The Philippines host world class porphyry copper deposits, such as the Tampakan and Atlas deposits. No porphyry copper deposits have been discovered in the Republic of Korea (South Korea), Taiwan (Province of China), or Japan.
\nThirteen geographic areas were delineated as tracts that are permissive for porphyry copper deposits in the assessed area. Individual tracts range from about 3,000 to 100,000 square kilometers in area. Permissive tracts are delineated on the basis of mapped distributions of igneous rocks of specific age ranges that define subduction-related magmatic arcs or magmatic belts that might contain porphyry copper deposits. Most of these magmatic arcs are subduction related, although some porphyry deposits and prospects are present in back-arc or poorly understood tectonic settings. Maps at various scales were used in the compilation; however, the final tract boundaries are intended for use at a scale of 1:1,000,000.
\nNumbers of undiscovered deposits were estimated at different levels of confidence for 10 permissive tracts in the Philippines including one area that extends to eastern Taiwan (Republic of China); permissive tracts in South Korea and Japan are discussed qualitatively. Estimates of numbers of undiscovered deposits were combined with grade and tonnage models using Monte Carlo simulation to estimate amounts of undiscovered resources. Grades and tonnages of known porphyry copper deposits in the study area were compared with global grade and tonnage models to determine the appropriate model for simulation of undiscovered resources. Most of the known deposits are best described as copper-gold subtypes of porphyry copper deposits. For some permissive tracts, a general porphyry copper-gold-molybdenum model was used.
\nThirty-eight porphyry copper deposits are known in the Philippines; the mean number of undiscovered deposits was estimated to be 28. Mean (arithmetic) resources that could be associated with the undiscovered deposits are 90 million metric tons of copper and 5,800 metric tons of gold, as well as byproduct molybdenum and silver. Additional resources that could be discovered in extensions to known deposits were not evaluated. Assessment results, presented in tables and graphs, indicate expected amounts of total contained metal and mineralized rock in undiscovered deposits at different quantile levels, as well as the arithmetic mean for each tract.
\nThe Philippines have a long history of porphyry exploration cycles and mine development, interrupted at times by political and social unrest, environmental concerns, and natural disasters. Changes in mining laws within the region and the recent high price of gold on the world market have prompted renewed interest in porphyry copper deposits in the region. South Korea and Japan have been thoroughly explored for many types of mineral deposits. Available data suggest that the permissive rocks in South Korea typically are too deeply eroded to preserve porphyry copper deposits. Porphyry copper systems may be present in Japan, but are likely to lie at depths greater than the 1 kilometer from the surface protocol adopted for this study.
\nDescriptions of the geologic basis for delineating each tract, the data used, the geologic criteria and rationale for the assessment, and results of the assessment are included in appendixes along with the description of a geographic information system (GIS) that includes tract boundaries, known porphyry copper deposits and significant prospects, and assessment results.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Global mineral resource assessment","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20105090P","collaboration":"Prepared in cooperation with the Coordinating Committee for Geoscience Programmes in East and Southeast Asia.","usgsCitation":"Hammarstrom, J.M., Bookstrom, A.A., Demarr, M.W., Dicken, C., Ludington, S., Robinson, G.R., and Zientek, M.L., 2014, Porphyry copper assessment of East and Southeast Asia: Philippines, Taiwan (Republic of China), Republic of Korea (South Korea), and Japan: U.S. Geological Survey Scientific Investigations Report 2010-5090, Report: xiii, 243 p.; Tabloid Figures; GIS Package, https://doi.org/10.3133/sir20105090P.","productDescription":"Report: xiii, 243 p.; Tabloid Figures; GIS Package","numberOfPages":"262","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-039384","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"links":[{"id":295885,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20105090P.jpg"},{"id":295884,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sir/2010/5090/p/GIS_SIR2010-5090-P.zip","text":"GIS Package","size":"36.9 MB"},{"id":295881,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2010/5090/p/"},{"id":295883,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2010/5090/p/pdf/Tabloid%20Figures.pdf","text":"Tabloid Figures","size":"21 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":295882,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2010/5090/p/pdf/sir2010-5090-P.pdf","size":"25.7 MB","linkFileType":{"id":1,"text":"pdf"}}],"projection":"Asia North Albers Equal Area Conic projection","country":"China, Japan, Philippines, South Korea","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 140.86669921875,\n 45.69083283645816\n ],\n [\n 142.40478515625,\n 45.49094569262732\n ],\n [\n 146.57958984375,\n 44.5435052132082\n ],\n [\n 147.19482421875,\n 43.78695837311561\n ],\n [\n 143.32763671875,\n 41.72213058512578\n ],\n [\n 141.591796875,\n 41.47566020027821\n ],\n [\n 142.2509765625,\n 39.436192999314066\n ],\n [\n 141.064453125,\n 35.67514743608467\n ],\n [\n 139.954833984375,\n 32.40779154205701\n ],\n [\n 135.791015625,\n 33.33970700424026\n ],\n [\n 132.8466796875,\n 32.54681317351514\n ],\n [\n 131.68212890625,\n 31.541089879585808\n ],\n [\n 131.1767578125,\n 30.221101852485987\n ],\n [\n 128.056640625,\n 25.878994400196202\n ],\n [\n 123.8818359375,\n 23.765236889758672\n ],\n [\n 121.6845703125,\n 22.268764039073968\n ],\n [\n 122.6953125,\n 17.14079039331665\n ],\n [\n 122.32177734375,\n 16.151368535968885\n ],\n [\n 123.0908203125,\n 14.647368383896632\n ],\n [\n 124.34326171874999,\n 14.26438308756265\n ],\n [\n 125.88134765625,\n 12.060809058367294\n ],\n [\n 126.87011718749999,\n 7.406047717076271\n ],\n [\n 126.27685546874999,\n 6.0094592380595495\n ],\n [\n 125.48583984375,\n 5.200364681183489\n ],\n [\n 124.25537109375,\n 5.878332109674327\n ],\n [\n 122.3876953125,\n 6.249776453227831\n ],\n [\n 119.61914062499999,\n 4.368320420876243\n ],\n [\n 119.0478515625,\n 4.477856485570586\n ],\n [\n 119.42138671875,\n 5.266007882805498\n ],\n [\n 117.31201171875001,\n 7.689217127736191\n ],\n [\n 116.806640625,\n 7.754537346539386\n ],\n [\n 116.8505859375,\n 8.276727101164047\n ],\n [\n 119.46533203125,\n 11.609193407938953\n ],\n [\n 119.83886718750001,\n 13.923403897723347\n ],\n [\n 119.5751953125,\n 16.277960306212524\n ],\n [\n 120.47607421874999,\n 18.729501999072138\n ],\n [\n 119.17968749999999,\n 23.241346102386135\n ],\n [\n 119.39941406249999,\n 23.82555130688476\n ],\n [\n 120.62988281249999,\n 25.20494115356912\n ],\n [\n 121.61865234375,\n 25.48295117535531\n ],\n [\n 122.14599609375001,\n 25.145284610685064\n ],\n [\n 124.16748046874999,\n 24.766784522874453\n ],\n [\n 126.62841796875,\n 26.70635985763354\n ],\n [\n 129.26513671875,\n 29.859701442126756\n ],\n [\n 129.462890625,\n 31.80289258670676\n ],\n [\n 128.408203125,\n 32.54681317351514\n ],\n [\n 125.96923828125,\n 33.119150226768866\n ],\n [\n 124.82666015624999,\n 33.925129700072\n ],\n [\n 124.892578125,\n 34.831841149828655\n ],\n [\n 125.83740234374999,\n 35.55010533588552\n ],\n [\n 125.70556640625,\n 37.56199695314352\n ],\n [\n 126.65039062499999,\n 37.83148014503288\n ],\n [\n 126.968994140625,\n 38.24680876017446\n ],\n [\n 127.232666015625,\n 38.315801006824984\n ],\n [\n 128.02368164062497,\n 38.34165619279593\n ],\n [\n 128.29833984375,\n 38.47939467327645\n ],\n [\n 128.353271484375,\n 38.62545397209084\n ],\n [\n 131.06689453125,\n 37.68382032669382\n ],\n [\n 133.57177734375,\n 36.36822190085111\n ],\n [\n 135.186767578125,\n 35.871246850027966\n ],\n [\n 136.571044921875,\n 37.42252593456307\n ],\n [\n 138.36181640624997,\n 38.53097889440024\n ],\n [\n 139.46044921875,\n 39.977120098439634\n ],\n [\n 139.46044921875,\n 40.713955826286046\n ],\n [\n 139.04296875,\n 42.147114459220994\n ],\n [\n 140.29541015624997,\n 43.51668853502906\n ],\n [\n 140.9765625,\n 43.6599240747891\n ],\n [\n 140.73486328125,\n 45.36758436884978\n ],\n [\n 140.86669921875,\n 45.69083283645816\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5459eaa2e4b009f8aec97008","contributors":{"authors":[{"text":"Hammarstrom, Jane M. 0000-0003-2742-3460 jhammars@usgs.gov","orcid":"https://orcid.org/0000-0003-2742-3460","contributorId":1226,"corporation":false,"usgs":true,"family":"Hammarstrom","given":"Jane","email":"jhammars@usgs.gov","middleInitial":"M.","affiliations":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":523284,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bookstrom, Arthur A. 0000-0003-1336-3364 abookstrom@usgs.gov","orcid":"https://orcid.org/0000-0003-1336-3364","contributorId":1542,"corporation":false,"usgs":true,"family":"Bookstrom","given":"Arthur","email":"abookstrom@usgs.gov","middleInitial":"A.","affiliations":[{"id":5056,"text":"Office of the AD Energy and Minerals, and Environmental Health","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":523285,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Demarr, Michael W.","contributorId":127350,"corporation":false,"usgs":false,"family":"Demarr","given":"Michael","email":"","middleInitial":"W.","affiliations":[{"id":6785,"text":"USGS Contractor, Minerals & Environmental Resources Sci Ctr","active":true,"usgs":false}],"preferred":false,"id":523286,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dicken, Connie L. cdicken@usgs.gov","contributorId":4714,"corporation":false,"usgs":true,"family":"Dicken","given":"Connie L.","email":"cdicken@usgs.gov","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":523287,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ludington, Stephen slud@usgs.gov","contributorId":3093,"corporation":false,"usgs":true,"family":"Ludington","given":"Stephen","email":"slud@usgs.gov","affiliations":[{"id":662,"text":"Western Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":523288,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Robinson, Gilpin R. Jr. grobinso@usgs.gov","contributorId":3083,"corporation":false,"usgs":true,"family":"Robinson","given":"Gilpin","suffix":"Jr.","email":"grobinso@usgs.gov","middleInitial":"R.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":523289,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Zientek, Michael L. 0000-0002-8522-9626 mzientek@usgs.gov","orcid":"https://orcid.org/0000-0002-8522-9626","contributorId":2420,"corporation":false,"usgs":true,"family":"Zientek","given":"Michael","email":"mzientek@usgs.gov","middleInitial":"L.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":523290,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70122982,"text":"ds852 - 2014 - Digital topographic data based on lidar survey of Mount Shasta Volcano, California, July-September 2010","interactions":[],"lastModifiedDate":"2019-03-15T10:15:30","indexId":"ds852","displayToPublicDate":"2014-11-04T13:30:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"852","title":"Digital topographic data based on lidar survey of Mount Shasta Volcano, California, July-September 2010","docAbstract":"The most voluminous of the Cascade volcanoes, northern California’s Mount Shasta, is a massive compound stratovolcano composed of at least four main edifices constructed over a period of at least 590,000 years. An ancestral Shasta volcano was destroyed by Earth’s largest known Quaternary subaerial debris avalanche, which filled Shasta Valley, northwest of the volcano. The Hotlum cone, forming the present summit, the Shastina lava dome complex, and the Black Butte lava dome on the southwest flank, were constructed during the early Holocene.
As part of the American Recovery and Reinvestment Act (ARRA) of 2009, the U.S. Geological Survey was awarded funding for high-precision airborne lidar (light detection and ranging) data collection at several volcanoes in the Cascade Range. Data collection was arranged by the Oregon Lidar Consortium, administered by the Oregon Department of Geology and Mineral Industries (DOGAMI). The Oregon Lidar Consortium contracted with Watershed Sciences, Inc., to collect 1,220 square km of high-precision airborne lidar data. These data provide a digital map of the ground surface beneath forest cover with horizontal resolution of 1 m (average of 1.82 ground laser returns per square meter) and estimated vertical accuracy of ±4 centimeters (1 sigma), and horizontal accuracies of ±1.5 centimeters. These data will contribute to monitoring and description of natural hazards, the study of regional geology and volcanic landforms, and analysis of landscape modification during and after the next volcanic eruption at Mount Shasta.
Survey Bounding Coordinates:
Changes in life history traits of species can be an important indicator of potential factors influencing populations. For grizzly bears (Ursus arctos) in the Greater Yellowstone Ecosystem (GYE), recent decline of whitebark pine (WBP; Pinus albicaulis), an important fall food resource, has been paired with a slowing of population growth following two decades of robust population increase. These observations have raised questions whether resource decline or density-dependent processes may be associated with changes in population growth. Distinguishing these effects based on changes in demographic rates can be difficult. However, unlike the parallel demographic responses expected from both decreasing food availability and increasing population density, we hypothesized opposing behavioral responses of grizzly bears with regard to changes in home-range size. We used the dynamic changes in food resources and population density of grizzly bears as a natural experiment to examine hypotheses regarding these potentially competing influences on grizzly bear home-range size. We found that home-range size did not increase during the period of whitebark pine decline and was not related to proportion of whitebark pine in home ranges. However, female home-range size was negatively associated with an index of population density. Our data indicate that home-range size of grizzly bears in the GYE is not associated with availability of WBP, and, for female grizzly bears, increasing population density may constrain home-range size.
","language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pone.0088160","collaboration":"US Fish and Wildlife Service","usgsCitation":"Bjornlie, D., van Manen, F.T., Ebinger, M.R., Haroldson, M.A., Thompson, D.J., and Costello, C., 2014, Whitebark pine, population density, and home-range size of grizzly bears in the greater Yellowstone ecosystem: PLoS ONE, v. 9, no. 2, p. 1-7, https://doi.org/10.1371/journal.pone.0088160.","productDescription":"Article e88160; 7 p.","startPage":"1","endPage":"7","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-053114","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":472652,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0088160","text":"Publisher Index Page"},{"id":295865,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Montana, Wyoming","otherGeospatial":"Yellowstone National Park","volume":"9","issue":"2","noUsgsAuthors":false,"publicationDate":"2014-02-10","publicationStatus":"PW","scienceBaseUri":"5459eaa5e4b009f8aec97040","contributors":{"authors":[{"text":"Bjornlie, Daniel D.","contributorId":145512,"corporation":false,"usgs":false,"family":"Bjornlie","given":"Daniel D.","affiliations":[{"id":16140,"text":"Wyoming Game & Fish Department, Large Carnivore Section, Lander, Wyoming 82520, USA","active":true,"usgs":false}],"preferred":false,"id":521328,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"van Manen, Frank T. 0000-0001-5340-8489 fvanmanen@usgs.gov","orcid":"https://orcid.org/0000-0001-5340-8489","contributorId":2267,"corporation":false,"usgs":true,"family":"van Manen","given":"Frank","email":"fvanmanen@usgs.gov","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":521327,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ebinger, Michael R. mebinger@usgs.gov","contributorId":5771,"corporation":false,"usgs":true,"family":"Ebinger","given":"Michael","email":"mebinger@usgs.gov","middleInitial":"R.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":521329,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Haroldson, Mark A. 0000-0002-7457-7676 mharoldson@usgs.gov","orcid":"https://orcid.org/0000-0002-7457-7676","contributorId":1773,"corporation":false,"usgs":true,"family":"Haroldson","given":"Mark","email":"mharoldson@usgs.gov","middleInitial":"A.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":521330,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thompson, Daniel J.","contributorId":149795,"corporation":false,"usgs":false,"family":"Thompson","given":"Daniel","email":"","middleInitial":"J.","affiliations":[{"id":5116,"text":"Large Carnivore Section, Wyoming Game & Fish Department, 260 Buena Vista, Lander, WY 82520, USA","active":true,"usgs":false}],"preferred":false,"id":521331,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Costello, Cecily M.","contributorId":145510,"corporation":false,"usgs":false,"family":"Costello","given":"Cecily M.","affiliations":[{"id":5117,"text":"University of Montana, College of Forestry and Conservation, University Hall, Room 309, Missoula, MT 59812, USA","active":true,"usgs":false}],"preferred":false,"id":521332,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70131500,"text":"70131500 - 2014 - A numerical study of vegetation impact on reducing storm surge by wetlands in a semi-enclosed estuary","interactions":[],"lastModifiedDate":"2020-12-23T14:50:27.713946","indexId":"70131500","displayToPublicDate":"2014-11-04T13:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1262,"text":"Coastal Engineering","active":true,"publicationSubtype":{"id":10}},"title":"A numerical study of vegetation impact on reducing storm surge by wetlands in a semi-enclosed estuary","docAbstract":"Coastal wetlands play a unique role in extreme hurricane events. The impact of wetlands on storm surge depends on multiple factors including vegetation, landscape, and storm characteristics. The Delft3D model, in which vegetation effects on flow and turbulence are explicitly incorporated, was applied to the semi-enclosed Breton Sound (BS) estuary in coastal Louisiana to investigate the wetland impact. Guided by extensive field observations, a series of numerical experiments were conducted based on variations of actual vegetation properties and storm parameters from Hurricane Isaac in 2012. Both the vegetation-induced maximum surge reduction (MSR) and maximum surge reduction rate (MSRR) increased with stem height and stem density, and were more sensitive to stem height. The MSR and MSRR decreased significantly with increasing wind intensity. The MSRR was the highest with a fast-moving weak storm. It was also found that the MSRR varied proportionally to the expression involving the maximum bulk velocity and surge over the area of interest, and was more dependent on the maximum bulk surge. Both MSR and MSRR appeared to increase when the area of interest decreased from the whole BS estuary to the upper estuary. Within the range of the numerical experiments, the maximum simulated MSR and MSRR over the upper estuary were 0.7 m and 37%, respectively.
","language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Holland","doi":"10.1016/j.coastaleng.2014.09.008","usgsCitation":"Kelin, H., Qin, C., and Wang, H., 2014, A numerical study of vegetation impact on reducing storm surge by wetlands in a semi-enclosed estuary: Coastal Engineering, v. 95, p. 66-76, https://doi.org/10.1016/j.coastaleng.2014.09.008.","productDescription":"11 p.","startPage":"66","endPage":"76","numberOfPages":"11","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056053","costCenters":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":295863,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Breton Sound Estuary","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.16366577148438,\n 29.597341920567366\n ],\n [\n -89.72946166992188,\n 29.858510452312036\n ],\n [\n -89.95880126953125,\n 29.881136828132842\n ],\n [\n -90.0164794921875,\n 29.776297851831366\n ],\n [\n -89.93820190429688,\n 29.635545914466675\n ],\n [\n -89.6649169921875,\n 29.47307903155816\n ],\n [\n -89.5880126953125,\n 29.3965337391284\n ],\n [\n -89.46990966796875,\n 29.348663646523626\n ],\n [\n -89.40673828125,\n 29.335495425659694\n ],\n [\n -89.27902221679688,\n 29.209713225868185\n ],\n [\n -89.22134399414062,\n 29.136568744954467\n ],\n [\n -89.02496337890625,\n 29.554345125748267\n ],\n [\n -89.16366577148438,\n 29.597341920567366\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"95","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5459ea9ae4b009f8aec96f95","contributors":{"authors":[{"text":"Kelin, Hu","contributorId":124567,"corporation":false,"usgs":false,"family":"Kelin","given":"Hu","email":"","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":521325,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Qin, Chen","contributorId":124568,"corporation":false,"usgs":false,"family":"Qin","given":"Chen","email":"","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":521326,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wang, Hongqing 0000-0002-2977-7732 wangh@usgs.gov","orcid":"https://orcid.org/0000-0002-2977-7732","contributorId":4421,"corporation":false,"usgs":true,"family":"Wang","given":"Hongqing","email":"wangh@usgs.gov","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":false,"id":521324,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70127432,"text":"ds884 - 2014 - Water quality, discharge, and groundwater levels in the Palomas, Mesilla, and Hueco Basins in New Mexico and Texas from below Caballo Reservoir, New Mexico, to Fort Quitman, Texas, 1889-2013","interactions":[],"lastModifiedDate":"2014-11-04T13:08:23","indexId":"ds884","displayToPublicDate":"2014-11-04T13:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"884","title":"Water quality, discharge, and groundwater levels in the Palomas, Mesilla, and Hueco Basins in New Mexico and Texas from below Caballo Reservoir, New Mexico, to Fort Quitman, Texas, 1889-2013","docAbstract":"The U.S. Geological Survey, in cooperation with the New Mexico Environment Department, compiled data from various sources to develop a dataset that can be used to conduct an assessment of the total dissolved solids in surface water and groundwater of the Palomas, Mesilla, and Hueco Basins in New Mexico and Texas, from below Caballo Reservoir, N. Mex., to Fort Quitman, Tex. Data include continuous surface-water discharge records at various locations on the Rio Grande; surface-water-quality data for the Rio Grande collected at selected locations in the Palomas, Mesilla, and Hueco Basins; groundwater levels and groundwater-quality data collected from selected wells in the Palomas and Mesilla Basins; and data from several seepage investigations conducted on the Rio Grande and selected drains in the Mesilla Basin.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds884","collaboration":"Prepared in cooperation with the New Mexico Environment Department","usgsCitation":"McKean, S., Matherne, A.M., and Thomas, N., 2014, Water quality, discharge, and groundwater levels in the Palomas, Mesilla, and Hueco Basins in New Mexico and Texas from below Caballo Reservoir, New Mexico, to Fort Quitman, Texas, 1889-2013: U.S. Geological Survey Data Series 884, Report: HTML Document; Downloads Directory, https://doi.org/10.3133/ds884.","productDescription":"Report: HTML Document; Downloads Directory","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"1889-01-01","temporalEnd":"2013-12-31","ipdsId":"IP-057294","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":295866,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds884.png"},{"id":295851,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0884/"},{"id":295864,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/0884/downloads/","text":"Downloads Directory"}],"projection":"Universal Transverse Mercator projection","datum":"North American Datum of 1983","country":"United States","state":"New Mexico, Texas","otherGeospatial":"Hueco Basin, Mesilla Basin, Palomas Basin","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5459eaa4e4b009f8aec97025","contributors":{"authors":[{"text":"McKean, Sarah E.","contributorId":71894,"corporation":false,"usgs":true,"family":"McKean","given":"Sarah E.","affiliations":[],"preferred":false,"id":523263,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Matherne, Anne Marie 0000-0002-5873-2226 matherne@usgs.gov","orcid":"https://orcid.org/0000-0002-5873-2226","contributorId":303,"corporation":false,"usgs":true,"family":"Matherne","given":"Anne","email":"matherne@usgs.gov","middleInitial":"Marie","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":523264,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thomas, Nicole nithomas@usgs.gov","contributorId":5649,"corporation":false,"usgs":true,"family":"Thomas","given":"Nicole","email":"nithomas@usgs.gov","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":523265,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70131499,"text":"70131499 - 2014 - Lake Michigan offshore ecosystem structure and food web changes from 1987 to 2008","interactions":[],"lastModifiedDate":"2014-11-04T12:50:31","indexId":"70131499","displayToPublicDate":"2014-11-04T13:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Lake Michigan offshore ecosystem structure and food web changes from 1987 to 2008","docAbstract":"Ecosystems undergo dynamic changes owing to species invasions, fisheries management decisions, landscape modifications, and nutrient inputs. At Lake Michigan, new invaders (e.g., dreissenid mussels (Dreissena spp.), spiny water flea (Bythotrephes longimanus), round goby (Neogobius melanostomus)) have proliferated and altered energy transfer pathways, while nutrient concentrations and stocking rates to support fisheries have changed. We developed an ecosystem model to describe food web structure in 1987 and ran simulations through 2008 to evaluate changes in biomass of functional groups, predator consumption, and effects of recently invading species. Keystone functional groups from 1987 were identified as Mysis, burbot (Lota lota), phytoplankton, alewife (Alosa pseudoharengus), nonpredatory cladocerans, and Chinook salmon (Oncorhynchus tshawytscha). Simulations predicted biomass reductions across all trophic levels and predicted biomasses fit observed trends for most functional groups. The effects of invasive species (e.g., dreissenid grazing) increased across simulation years, but were difficult to disentangle from other changes (e.g., declining offshore nutrient concentrations). In total, our model effectively represented recent changes to the Lake Michigan ecosystem and provides an ecosystem-based tool for exploring future resource management scenarios.
","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Canadian Journal of Fisheries and Aquatic Sciences","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"NRC Research Press","publisherLocation":"Ottawa, Canada","usgsCitation":"Rogers, M.W., Bunnell, D., Madenjian, C.P., and Warner, D.M., 2014, Lake Michigan offshore ecosystem structure and food web changes from 1987 to 2008: Canadian Journal of Fisheries and Aquatic Sciences, v. 71, no. 7, p. 1072-7086.","productDescription":"15 p.","startPage":"1072","endPage":"7086","numberOfPages":"15","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-055220","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":295862,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":295769,"type":{"id":15,"text":"Index Page"},"url":"https://www.nrcresearchpress.com/doi/abs/10.1139/cjfas-2013-0514#.VFOBV_nF-8w"}],"country":"United States","otherGeospatial":"Lake Michigan","volume":"71","issue":"7","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5459eaa1e4b009f8aec96fee","contributors":{"authors":[{"text":"Rogers, Mark W. 0000-0001-7205-5623 mwrogers@usgs.gov","orcid":"https://orcid.org/0000-0001-7205-5623","contributorId":4590,"corporation":false,"usgs":true,"family":"Rogers","given":"Mark","email":"mwrogers@usgs.gov","middleInitial":"W.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":521314,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bunnell, David B. 0000-0003-3521-7747 dbunnell@usgs.gov","orcid":"https://orcid.org/0000-0003-3521-7747","contributorId":3139,"corporation":false,"usgs":true,"family":"Bunnell","given":"David B.","email":"dbunnell@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":521315,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Madenjian, Charles P. 0000-0002-0326-164X cmadenjian@usgs.gov","orcid":"https://orcid.org/0000-0002-0326-164X","contributorId":2200,"corporation":false,"usgs":true,"family":"Madenjian","given":"Charles","email":"cmadenjian@usgs.gov","middleInitial":"P.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":521316,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Warner, David M. 0000-0003-4939-5368 dmwarner@usgs.gov","orcid":"https://orcid.org/0000-0003-4939-5368","contributorId":2986,"corporation":false,"usgs":true,"family":"Warner","given":"David","email":"dmwarner@usgs.gov","middleInitial":"M.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":521317,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70125639,"text":"ds885 - 2014 - EAARL-B submerged topography: Barnegat Bay, New Jersey, pre-Hurricane Sandy, 2012","interactions":[],"lastModifiedDate":"2014-11-06T10:09:12","indexId":"ds885","displayToPublicDate":"2014-11-04T12:45:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"885","title":"EAARL-B submerged topography: Barnegat Bay, New Jersey, pre-Hurricane Sandy, 2012","docAbstract":"These remotely sensed, geographically referenced elevation measurements of lidar-derived submerged topography datasets were produced by the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center, St. Petersburg, Florida.
\n\n
This project provides highly detailed and accurate datasets for part of Barnegat Bay, New Jersey, acquired pre-Hurricane Sandy on October 18, 22, 23, and 26, 2012. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative airborne lidar, known as the second-generation Experimental Advanced Airborne Research Lidar (EAARL-B), was used during data acquisition. The EAARL-B system is a raster-scanning, waveform-resolving, green-wavelength (532-nm) lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL-B sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive lidar, down-looking red-green-blue (RGB) and infrared (IR) digital cameras, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for sub-meter georeferencing of each laser sample. The nominal EAARL-B platform is a twin-engine Cessna 310 aircraft, but the instrument may be deployed on a range of light aircraft. A single pilot, a lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys.
\n\n
Elevation measurements were collected over the survey area using the EAARL-B system. The resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed originally in a NASA-USGS collaboration. The exploration and processing of lidar data in an interactive or batch mode is supported using ALPS. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. The Airborne Lidar Processing System (ALPS) is used routinely to create maps that represent submerged or sub-aerial topography. Specialized filtering algorithms have been implemented to determine the \"bare earth\" under vegetation from a point cloud of last return elevations.
\n\n
For more information about similar projects, please visit the Lidar for Science and Resource Management Web site.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds885","usgsCitation":"Wright, C.W., Troche, R.J., Klipp, E.S., Kranenburg, C., Fredericks, X., and Nagle, D.B., 2014, EAARL-B submerged topography: Barnegat Bay, New Jersey, pre-Hurricane Sandy, 2012: U.S. Geological Survey Data Series 885, Web Page, https://doi.org/10.3133/ds885.","productDescription":"Web Page","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-054940","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":295861,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":295859,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0885/"},{"id":295860,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0885/home.html"}],"country":"United States","state":"New Jersey","otherGeospatial":"Barnegat Bay","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57f7f032e4b0bc0bec09f5fe","contributors":{"authors":[{"text":"Wright, C. Wayne wwright@usgs.gov","contributorId":2973,"corporation":false,"usgs":true,"family":"Wright","given":"C.","email":"wwright@usgs.gov","middleInitial":"Wayne","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":519514,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Troche, Rodolfo J. rtroche@usgs.gov","contributorId":4304,"corporation":false,"usgs":true,"family":"Troche","given":"Rodolfo","email":"rtroche@usgs.gov","middleInitial":"J.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":519517,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Klipp, Emily S. eklipp@usgs.gov","contributorId":2754,"corporation":false,"usgs":true,"family":"Klipp","given":"Emily","email":"eklipp@usgs.gov","middleInitial":"S.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":519512,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kranenburg, Christine J. ckranenburg@usgs.gov","contributorId":3924,"corporation":false,"usgs":true,"family":"Kranenburg","given":"Christine J.","email":"ckranenburg@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":519516,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fredericks, Xan 0000-0001-7186-6555 afredericks@usgs.gov","orcid":"https://orcid.org/0000-0001-7186-6555","contributorId":2972,"corporation":false,"usgs":true,"family":"Fredericks","given":"Xan","email":"afredericks@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":519513,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nagle, David B. 0000-0002-2306-6147 dnagle@usgs.gov","orcid":"https://orcid.org/0000-0002-2306-6147","contributorId":3380,"corporation":false,"usgs":true,"family":"Nagle","given":"David","email":"dnagle@usgs.gov","middleInitial":"B.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":519515,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70128981,"text":"ds888 - 2014 - EAARL-B coastal topography: Fire Island, New York, pre-Hurricane Sandy, 2012: seamless (bare earth and submerged)","interactions":[],"lastModifiedDate":"2014-11-06T10:54:55","indexId":"ds888","displayToPublicDate":"2014-11-04T12:15:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"888","title":"EAARL-B coastal topography: Fire Island, New York, pre-Hurricane Sandy, 2012: seamless (bare earth and submerged)","docAbstract":"These remotely sensed, geographically referenced elevation measurements of lidar-derived seamless (bare-earth and submerged) topography datasets were produced by the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center, St. Petersburg, Florida.
\n\n
This project provides highly detailed and accurate datasets for part of Fire Island, New York, acquired pre-Hurricane Sandy on October 27, 2012. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative airborne lidar, known as the second-generation Experimental Advanced Airborne Research Lidar (EAARL-B), was used during data acquisition. The EAARL-B system is a raster-scanning, waveform-resolving, green-wavelength (532-nm) lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL-B sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive lidar, down-looking red-green-blue (RGB) and infrared (IR) digital cameras, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for sub-meter georeferencing of each laser sample. The nominal EAARL-B platform is a twin-engine Cessna 310 aircraft, but the instrument may be deployed on a range of light aircraft. A single pilot, a lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys.
\n\n
Elevation measurements were collected over the survey area using the EAARL-B system. The resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed originally in a NASA-USGS collaboration. The exploration and processing of lidar data in an interactive or batch mode is supported using ALPS. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. The Airborne Lidar Processing System (ALPS) is used routinely to create maps that represent submerged or sub-aerial topography. Specialized filtering algorithms have been implemented to determine the \"bare earth\" under vegetation from a point cloud of last return elevations.
\n\n
For more information about similar projects, please visit the Lidar for Science and Resource Management Web site.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds888","usgsCitation":"Wright, C.W., Kranenburg, C., Klipp, E.S., Troche, R.J., Fredericks, X., Masessa, M.L., and Nagle, D.B., 2014, EAARL-B coastal topography: Fire Island, New York, pre-Hurricane Sandy, 2012: seamless (bare earth and submerged): U.S. Geological Survey Data Series 888, HTML Document, https://doi.org/10.3133/ds888.","productDescription":"HTML Document","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-056095","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":295858,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":295857,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0888/html/home.html"},{"id":295856,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0888/"}],"country":"United States","state":"New York","otherGeospatial":"Fire Island","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57f7f032e4b0bc0bec09f600","contributors":{"authors":[{"text":"Wright, C. Wayne wwright@usgs.gov","contributorId":2973,"corporation":false,"usgs":true,"family":"Wright","given":"C.","email":"wwright@usgs.gov","middleInitial":"Wayne","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":519776,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kranenburg, Christine J. ckranenburg@usgs.gov","contributorId":3924,"corporation":false,"usgs":true,"family":"Kranenburg","given":"Christine J.","email":"ckranenburg@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":519778,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Klipp, Emily S. eklipp@usgs.gov","contributorId":2754,"corporation":false,"usgs":true,"family":"Klipp","given":"Emily","email":"eklipp@usgs.gov","middleInitial":"S.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":519774,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Troche, Rodolfo J. rtroche@usgs.gov","contributorId":4304,"corporation":false,"usgs":true,"family":"Troche","given":"Rodolfo","email":"rtroche@usgs.gov","middleInitial":"J.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":519779,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fredericks, Xan 0000-0001-7186-6555 afredericks@usgs.gov","orcid":"https://orcid.org/0000-0001-7186-6555","contributorId":2972,"corporation":false,"usgs":true,"family":"Fredericks","given":"Xan","email":"afredericks@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":519775,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Masessa, Melanie L. mmasessa@usgs.gov","contributorId":5903,"corporation":false,"usgs":true,"family":"Masessa","given":"Melanie","email":"mmasessa@usgs.gov","middleInitial":"L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":519780,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Nagle, David B. 0000-0002-2306-6147 dnagle@usgs.gov","orcid":"https://orcid.org/0000-0002-2306-6147","contributorId":3380,"corporation":false,"usgs":true,"family":"Nagle","given":"David","email":"dnagle@usgs.gov","middleInitial":"B.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":519777,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70131492,"text":"70131492 - 2014 - Limitations to estimating bacterial cross-speciestransmission using genetic and genomic markers: Inferences from simulation modeling","interactions":[],"lastModifiedDate":"2020-12-29T12:52:06.935036","indexId":"70131492","displayToPublicDate":"2014-11-04T11:30:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1601,"text":"Evolutionary Applications","active":true,"publicationSubtype":{"id":10}},"title":"Limitations to estimating bacterial cross-speciestransmission using genetic and genomic markers: Inferences from simulation modeling","docAbstract":"Cross‐species transmission (CST) of bacterial pathogens has major implications for human health, livestock, and wildlife management because it determines whether control actions in one species may have subsequent effects on other potential host species. The study of bacterial transmission has benefitted from methods measuring two types of genetic variation: variable number of tandem repeats (VNTRs) and single nucleotide polymorphisms (SNPs). However, it is unclear whether these data can distinguish between different epidemiological scenarios. We used a simulation model with two host species and known transmission rates (within and between species) to evaluate the utility of these markers for inferring CST. We found that CST estimates are biased for a wide range of parameters when based on VNTRs and a most parsimonious reconstructed phylogeny. However, estimations of CST rates lower than 5% can be achieved with relatively low bias using as low as 250 SNPs. CST estimates are sensitive to several parameters, including the number of mutations accumulated since introduction, stochasticity, the genetic difference of strains introduced, and the sampling effort. Our results suggest that, even with whole‐genome sequences, unbiased estimates of CST will be difficult when sampling is limited, mutation rates are low, or for pathogens that were recently introduced.
Recent changes in Lake Michigan’s lower trophic levels were hypothesized to have influenced the diet of omnivorous Mysis diluviana. In this study, the stomach contents of Mysis were examined from juvenile and adults collected monthly (April–October) from a 110-m bottom depth site to describe their seasonal diet in LakeMichigan during 2010. Diatoms were the most common prey item ingested, followed by calanoid copepods, and chrysophytes. Dreissenid veligers were documented in mysid diets for the first time in the Great Lakes, and Cercopagis pengoi were not only consumed but even preferred by adults in summer. Diet proportions by weight were dominated by calanoids, although diets showed a marked shift toward cladocerans in autumn. Juvenile and adult Mysis selected primarily for cladoceran prey but also selected for some calanoid copepod taxa. Comparing available Mysis diet data from 1985 to 2010 indicated generally fewer cladocerans and rotifers per gut and less consistent differences in copepods and Peridinium consumed. The seasonal composition of phyto- and zooplankton prey documented herein should be useful to those seeking to understand the trophic role of Mysis in offshore food webs, but caution should be expressed when generalizing similarities in Mysis diets across other lakes because Lake Michigan’s population seems relatively more herbivorous.
","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Plankton Research","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Oxford University Press","publisherLocation":"Oxford, England","doi":"10.1093/plankt/fbu038","usgsCitation":"O’Malley, B.P., and Bunnell, D., 2014, Diet of Mysis diluviana reveals seasonal patterns of omnivory and consumption of invasive species in offshore Lake Michigan: Journal of Plankton Research, v. 36, no. 4, p. 989-1002, https://doi.org/10.1093/plankt/fbu038.","productDescription":"14 p.","startPage":"989","endPage":"1002","numberOfPages":"14","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-053800","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":472653,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/plankt/fbu038","text":"Publisher Index Page"},{"id":295854,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":295978,"type":{"id":15,"text":"Index Page"},"url":"https://plankt.oxfordjournals.org/content/36/4/989.abstract"}],"country":"United States","otherGeospatial":"Lake Michigan","volume":"36","issue":"4","noUsgsAuthors":false,"publicationDate":"2014-05-16","publicationStatus":"PW","scienceBaseUri":"5459ea9fe4b009f8aec96fb4","contributors":{"authors":[{"text":"O’Malley, Brian P. bomalley@usgs.gov","contributorId":5615,"corporation":false,"usgs":true,"family":"O’Malley","given":"Brian","email":"bomalley@usgs.gov","middleInitial":"P.","affiliations":[],"preferred":true,"id":521313,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bunnell, David B. 0000-0003-3521-7747 dbunnell@usgs.gov","orcid":"https://orcid.org/0000-0003-3521-7747","contributorId":3139,"corporation":false,"usgs":true,"family":"Bunnell","given":"David B.","email":"dbunnell@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":521312,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70131493,"text":"70131493 - 2014 - Assembling evidence for identifying reservoirs of infection","interactions":[],"lastModifiedDate":"2018-09-18T16:33:13","indexId":"70131493","displayToPublicDate":"2014-11-04T11:15:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3653,"text":"Trends in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Assembling evidence for identifying reservoirs of infection","docAbstract":"Many pathogens persist in multihost systems, making the identification of infection reservoirs crucial for devising effective interventions. Here, we present a conceptual framework for classifying patterns of incidence and prevalence, and review recent scientific advances that allow us to study and manage reservoirs simultaneously. We argue that interventions can have a crucial role in enriching our mechanistic understanding of how reservoirs function and should be embedded as quasi-experimental studies in adaptive management frameworks. Single approaches to the study of reservoirs are unlikely to generate conclusive insights whereas the formal integration of data and methodologies, involving interventions, pathogen genetics, and contemporary surveillance techniques, promises to open up new opportunities to advance understanding of complex multihost systems.
","language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam","doi":"10.1016/j.tree.2014.03.002","usgsCitation":"Viana, M., Mancy, R., Biek, R., Cleaveland, S., Cross, P.C., Lloyd-Smith, J.O., and Haydon, D.T., 2014, Assembling evidence for identifying reservoirs of infection: Trends in Ecology and Evolution, v. 29, no. 5, p. 270-279, https://doi.org/10.1016/j.tree.2014.03.002.","productDescription":"10 p.","startPage":"270","endPage":"279","numberOfPages":"10","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-052966","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":472655,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.tree.2014.03.002","text":"Publisher Index Page"},{"id":295852,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"29","issue":"5","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5459ea9de4b009f8aec96f9f","contributors":{"authors":[{"text":"Viana, Mafalda","contributorId":124533,"corporation":false,"usgs":false,"family":"Viana","given":"Mafalda","affiliations":[{"id":5092,"text":"Boyd Orr Centre for Population and Ecosystems Health, Institute of Biodiversity, Animal Health and Comparative Medicine, University of Glasgow, Glasgow G12 8QQ, UK","active":true,"usgs":false}],"preferred":false,"id":521274,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mancy, Rebecca","contributorId":124534,"corporation":false,"usgs":false,"family":"Mancy","given":"Rebecca","email":"","affiliations":[{"id":5093,"text":"Boyd Orr Centre for Population and Ecosystems Health, Institute of Biodiversity, Animal Health and Comparative Medicine, University of Glasgow, Glasgow G12 8QQ, UK; School of Computing Science, University of Glasgow, Glasgow G12 8QQ, UK","active":true,"usgs":false}],"preferred":false,"id":521275,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Biek, Roman","contributorId":124535,"corporation":false,"usgs":false,"family":"Biek","given":"Roman","affiliations":[{"id":5094,"text":"Boyd Orr Centre for Population and Ecosystems Health, Institute of Biodiversity, Animal Health and Comparative Medicine, University of Glasgow, Glasgow G12 8QQ, UK; Fogarty International Center, National Institutes of Health, Bethesda, MD 20892 USA","active":true,"usgs":false}],"preferred":false,"id":521276,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cleaveland, Sarah","contributorId":124536,"corporation":false,"usgs":false,"family":"Cleaveland","given":"Sarah","email":"","affiliations":[{"id":5092,"text":"Boyd Orr Centre for Population and Ecosystems Health, Institute of Biodiversity, Animal Health and Comparative Medicine, University of Glasgow, Glasgow G12 8QQ, UK","active":true,"usgs":false}],"preferred":false,"id":521277,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cross, Paul C. 0000-0001-8045-5213 pcross@usgs.gov","orcid":"https://orcid.org/0000-0001-8045-5213","contributorId":2709,"corporation":false,"usgs":true,"family":"Cross","given":"Paul","email":"pcross@usgs.gov","middleInitial":"C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":521273,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lloyd-Smith, James O.","contributorId":124537,"corporation":false,"usgs":false,"family":"Lloyd-Smith","given":"James","email":"","middleInitial":"O.","affiliations":[{"id":5095,"text":"Fogarty International Center, National Institutes of Health, Bethesda, MD 20892; Department of Ecology and Evolutionary Biology, University of California at Los Angeles, Los Angeles, CA 90095, USA","active":true,"usgs":false}],"preferred":false,"id":521278,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Haydon, Daniel T.","contributorId":124538,"corporation":false,"usgs":false,"family":"Haydon","given":"Daniel","email":"","middleInitial":"T.","affiliations":[{"id":5092,"text":"Boyd Orr Centre for Population and Ecosystems Health, Institute of Biodiversity, Animal Health and Comparative Medicine, University of Glasgow, Glasgow G12 8QQ, UK","active":true,"usgs":false}],"preferred":false,"id":521279,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70124957,"text":"sir20145177 - 2014 - Estimation of regional flow-duration curves for Indiana and Illinois","interactions":[],"lastModifiedDate":"2026-04-02T14:14:01.303233","indexId":"sir20145177","displayToPublicDate":"2014-11-04T10:30:00","publicationYear":"2014","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":"2014-5177","displayTitle":"Estimation of Regional Flow-Duration Curves for Indiana and Illinois","title":"Estimation of regional flow-duration curves for Indiana and Illinois","docAbstract":"Flow-duration curves (FDCs) of daily streamflow are useful for many applications in water resources planning and management but must be estimated at ungaged sites. One common technique for estimating FDCs at ungaged sites in a given region is to use equations obtained by linear regression of FDC quantiles against multiple basin characteristics that can be computed by means of a geographic information system (GIS) computer program. In this study, such regional regression equations for estimating FDC quantiles were computed at the 0.1, 0.2, 0.5, 1, 2, 5, 10, 20, 25, 30, 40, 50, 60, 70, 75, 80, 90, 95, 98, 99, 99.5, 99.8, and 99.9-percent exceedance probabilities for rural, unregulated streams in Indiana and Illinois with temporally stationary records, using data through September 30, 2007. The approach used accounts for censored values below 0.01 cubic feet per second, which are observed at exceedance probabilities as low as 70 percent (that is, occurring at least 30 percent of the time). The basin characteristics used are suitable for computation by the USGS Web-based application, StreamStats, and are available for all U.S. Environmental Protection Agency (EPA) Region V states and the larger Great Lakes area, with some specific local exceptions. Indiana and Illinois were each divided into three regions, and a different set of equations for estimating FDC quantiles was computed for each region.
The error of estimation of the FDC quantiles, measured as the mean square residual in log space converted to a percentage of the quantile, varies somewhat among regions and varies strongly with exceedance probability, with a minimum error of 10 to 20 percent at an exceedance probability of 5 or 10 percent, but rises to 17 to 38 percent at the high-flow end of the FDCs (the 0.1-percent quantile) and 100 to 745 percent at the low-flow end. For comparison, errors of estimation also were computed for FDC quantiles estimated by linear regression on drainage area alone and by using the drainage-area ratio (DAR) method. Three criteria, the nearest basin centroid and two others termed “strict” and “broad”, were used to select index stations for the DAR method. The “strict” and “broad” criteria put conditions on the basin centroid distance and the range of their drainage-area ratios, and the errors were averaged for all index station pairs satisfying each criterion. The use of the simpler DAR method usually resulted in higher errors of estimation compared to the linear regression equations with multiple basin characteristics, except occasionally in the case of the DAR method with the strict index station selection criterion, a criterion that is rarely possible to satisfy in practice.
An example application of the estimated equations to one gaged and a few ungaged locations in a watershed in the study area is included to illustrate the steps required. These steps are the computation of the basin characteristics and, using those characteristics together with the estimated equations, the computation of the FDC quantiles and their uncertainties.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145177","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency, Region V, and the Indiana Department of Environmental Management","usgsCitation":"Over, T.M., Riley, J.D., Marti, M.K., Sharpe, J.B., and Arvin, D., 2014, Estimation of regional flow-duration curves for Indiana and Illinois (ver. 2.0, April 2022): U.S. Geological Survey Scientific Investigations Report 2014–5177, 24 p. and additional downloads, tables 2–5, 8–13, and 18, https://doi.org/10.3133/sir20145177.","productDescription":"Report: v, 24 p.; Tables: 2-5, 8-13, and 18; Data Release","numberOfPages":"34","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-053042","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":438739,"rank":26,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9FM4VUZ","text":"USGS data release","linkHelpText":"Data for the Estimation of Regional Flow-Duration Curves for Indiana and Illinois (ver. 3.0, December 2021)"},{"id":398053,"rank":25,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2014/5177/sir20145177_table18.xlsx","text":"Table 18","size":"37.7 kB","linkFileType":{"id":3,"text":"xlsx"}},{"id":398052,"rank":24,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2014/5177/sir20145177_table18.csv","text":"Table 18","size":"9.80 kB","linkFileType":{"id":7,"text":"csv"}},{"id":398051,"rank":23,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2014/5177/sir20145177_table13.xlsx","text":"Table 13","size":"28.0 kB","linkFileType":{"id":3,"text":"xlsx"}},{"id":398050,"rank":22,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2014/5177/sir20145177_table13.csv","text":"Table 13","size":"6.03 kB","linkFileType":{"id":7,"text":"csv"}},{"id":398048,"rank":21,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2014/5177/sir20145177_table12.xlsx","text":"Table 12","size":"29.3 kB","linkFileType":{"id":3,"text":"xlsx"}},{"id":398047,"rank":20,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2014/5177/sir20145177_table12.csv","text":"Table 12","size":"7.08 kB","linkFileType":{"id":7,"text":"csv"}},{"id":398045,"rank":19,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2014/5177/sir20145177_table11.xlsx","text":"Table 11","size":"27.5 kB","linkFileType":{"id":3,"text":"xlsx"}},{"id":398044,"rank":18,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2014/5177/sir20145177_table11.csv","text":"Table 11","size":"5.33 kB","linkFileType":{"id":7,"text":"csv"}},{"id":398042,"rank":17,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2014/5177/sir20145177_table10.xlsx","text":"Table 10","size":"30.0 kB","linkFileType":{"id":3,"text":"xlsx"}},{"id":398041,"rank":16,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2014/5177/sir20145177_table10.csv","text":"Table 10","size":"6.81 kB","linkFileType":{"id":7,"text":"csv"}},{"id":398040,"rank":15,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2014/5177/sir20145177_table9.xlsx","text":"Table 9","size":"32.1 kB","linkFileType":{"id":3,"text":"xlsx"}},{"id":398037,"rank":12,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2014/5177/sir20145177_table8.csv","text":"Table 8","size":"6.54 kB","linkFileType":{"id":7,"text":"csv"}},{"id":398035,"rank":11,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2014/5177/sir20145177_table5.xlsx","text":"Table 5","size":"66.0 kB","linkFileType":{"id":3,"text":"xlsx"}},{"id":398034,"rank":10,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2014/5177/sir20145177_table5.csv","text":"Table 5","size":"50.2 kB","linkFileType":{"id":7,"text":"csv"}},{"id":398033,"rank":9,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2014/5177/sir20145177_table4.xlsx","text":"Table 4","size":"83.9 kB","linkFileType":{"id":3,"text":"xlsx"}},{"id":398032,"rank":8,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2014/5177/sir20145177_table4.csv","text":"Table 4","size":"38.1 kB","linkFileType":{"id":7,"text":"csv"}},{"id":398030,"rank":7,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2014/5177/sir20145177_table3.xlsx","text":"Table 3","size":"71.9 kB","linkFileType":{"id":3,"text":"xlsx"}},{"id":398029,"rank":6,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2014/5177/sir20145177_table3.csv","text":"Table 3","size":"27.5 kB","linkFileType":{"id":7,"text":"csv"}},{"id":398028,"rank":5,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2014/5177/sir20145177_table2.xlsx","text":"Table 2","size":"62.7 kB","linkFileType":{"id":3,"text":"xlsx"}},{"id":398039,"rank":14,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2014/5177/sir20145177_table9.csv","text":"Table 9","size":"22.2 kB","linkFileType":{"id":7,"text":"csv"}},{"id":398038,"rank":13,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2014/5177/sir20145177_table8.xlsx","text":"Table 8","size":"29.4 kB","linkFileType":{"id":3,"text":"xlsx"}},{"id":398027,"rank":4,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2014/5177/sir20145177_table2.csv","text":"Table 2","size":"25.1 kB","linkFileType":{"id":7,"text":"csv"}},{"id":398026,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2014/5177/versionHist.txt","text":"Version History","size":"1 kB","linkFileType":{"id":2,"text":"txt"}},{"id":398025,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5177/sir20145177.pdf","text":"Report","size":"1.63 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":398024,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2014/5177/coverthb2.jpg"},{"id":501940,"rank":27,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_101022.htm","linkFileType":{"id":5,"text":"html"}}],"projection":"Albers Equal-Area Conic projection","country":"United States","state":"Illinois, Indiana","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-89.366031,42.500274],[-88.786681,42.491983],[-88.115285,42.496219],[-87.800561,42.49192],[-87.79823,42.473054],[-87.80537,42.384721],[-87.820858,42.361584],[-87.830646,42.331368],[-87.834769,42.301522],[-87.828569,42.269922],[-87.812461,42.232278],[-87.800066,42.208024],[-87.741662,42.128227],[-87.712206,42.096455],[-87.682359,42.075729],[-87.671462,42.058334],[-87.668982,42.029142],[-87.630953,41.933132],[-87.624134,41.904574],[-87.611659,41.892216],[-87.616251,41.868933],[-87.60945,41.845233],[-87.600549,41.826833],[-87.580948,41.804334],[-87.576347,41.786034],[-87.560646,41.766034],[-87.542845,41.752135],[-87.530745,41.748235],[-87.524141,41.72399],[-87.524044,41.708335],[-87.520544,41.709935],[-87.505343,41.691535],[-87.470742,41.672835],[-87.463142,41.675535],[-87.446113,41.66934],[-87.43853,41.670679],[-87.432396,41.66053],[-87.438941,41.654335],[-87.42344,41.642835],[-87.365439,41.629536],[-87.324338,41.623036],[-87.261536,41.620336],[-87.187651,41.629653],[-87.160625,41.637266],[-87.160784,41.645385],[-87.125835,41.650302],[-87.120322,41.645701],[-87.027888,41.674661],[-86.93483,41.709638],[-86.90913,41.726938],[-86.824828,41.76024],[-84.805883,41.760216],[-84.802547,40.50181],[-84.814179,39.814212],[-84.820157,39.10548],[-84.831197,39.10192],[-84.860689,39.07814],[-84.888873,39.066376],[-84.897364,39.057378],[-84.889065,39.04082],[-84.870168,39.025551],[-84.83712,38.988059],[-84.829857,38.969385],[-84.83516,38.957961],[-84.877762,38.920357],[-84.877029,38.909016],[-84.867778,38.899133],[-84.812746,38.895132],[-84.785234,38.880439],[-84.785799,38.869496],[-84.791002,38.860572],[-84.823363,38.839196],[-84.829958,38.830632],[-84.827098,38.818634],[-84.813939,38.800209],[-84.812877,38.786087],[-84.828714,38.783208],[-84.887919,38.794652],[-84.941071,38.775627],[-84.990006,38.778383],[-85.100963,38.7268],[-85.13868,38.699168],[-85.172528,38.688082],[-85.190507,38.68795],[-85.213257,38.695446],[-85.226062,38.705456],[-85.246505,38.731821],[-85.275454,38.741172],[-85.306049,38.741649],[-85.363827,38.730477],[-85.410925,38.73708],[-85.434065,38.729455],[-85.452114,38.709348],[-85.456978,38.689135],[-85.455486,38.68209],[-85.438742,38.659319],[-85.437446,38.601724],[-85.415821,38.563558],[-85.4156,38.546341],[-85.423077,38.531581],[-85.472221,38.506279],[-85.482897,38.485701],[-85.498866,38.468242],[-85.536542,38.456083],[-85.587758,38.450495],[-85.607629,38.439295],[-85.620521,38.423105],[-85.632937,38.395666],[-85.638041,38.380338],[-85.638777,38.361443],[-85.653641,38.327108],[-85.683561,38.295469],[-85.744862,38.26717],[-85.761062,38.27257],[-85.765963,38.280469],[-85.780963,38.288469],[-85.816164,38.282969],[-85.829364,38.276769],[-85.845464,38.23027],[-85.894764,38.188469],[-85.908764,38.161169],[-85.906163,38.08617],[-85.915214,38.067664],[-85.925418,38.023456],[-85.951467,38.005608],[-86.009127,37.998529],[-86.029509,37.99264],[-86.035012,37.984814],[-86.033386,37.970382],[-86.038188,37.95935],[-86.045208,37.958258],[-86.053912,37.963571],[-86.064859,37.975618],[-86.075393,37.996948],[-86.095766,38.00893],[-86.12757,38.016011],[-86.16731,38.009879],[-86.178983,38.011308],[-86.220371,38.027922],[-86.233057,38.039305],[-86.261273,38.052721],[-86.273584,38.067443],[-86.27872,38.089303],[-86.271802,38.137874],[-86.287773,38.15805],[-86.317139,38.172907],[-86.347736,38.195363],[-86.360377,38.198796],[-86.373801,38.193352],[-86.378151,38.185845],[-86.377434,38.171379],[-86.37174,38.164183],[-86.325941,38.154317],[-86.321274,38.147418],[-86.323453,38.139032],[-86.335145,38.129242],[-86.379775,38.129274],[-86.401653,38.105396],[-86.431749,38.126121],[-86.449793,38.127223],[-86.463248,38.119278],[-86.466081,38.114437],[-86.463858,38.101177],[-86.434046,38.086763],[-86.430091,38.078638],[-86.432789,38.067171],[-86.452192,38.05049],[-86.51176,38.044448],[-86.521825,38.038327],[-86.524969,38.027879],[-86.525174,37.968228],[-86.520503,37.954438],[-86.50939,37.942492],[-86.50662,37.930719],[-86.534156,37.917007],[-86.586542,37.922285],[-86.599848,37.906754],[-86.598108,37.867382],[-86.609163,37.855408],[-86.638265,37.842718],[-86.652516,37.841636],[-86.661637,37.849714],[-86.661233,37.862761],[-86.644754,37.894806],[-86.647081,37.908621],[-86.680929,37.91501],[-86.716138,37.894073],[-86.73146,37.89434],[-86.75099,37.912893],[-86.765054,37.93251],[-86.794985,37.988982],[-86.820071,37.999392],[-86.85595,37.987292],[-86.902413,37.946161],[-86.919329,37.936664],[-86.969044,37.932858],[-87.010315,37.919668],[-87.033444,37.906593],[-87.045101,37.893775],[-87.043854,37.870796],[-87.067836,37.806065],[-87.090636,37.787808],[-87.111133,37.782512],[-87.129629,37.786608],[-87.14195,37.816176],[-87.162319,37.840159],[-87.20224,37.843791],[-87.220944,37.849134],[-87.302324,37.898445],[-87.344933,37.911164],[-87.380247,37.935596],[-87.418585,37.944763],[-87.450458,37.941451],[-87.501131,37.909162],[-87.511499,37.906426],[-87.559342,37.931146],[-87.57203,37.947466],[-87.577915,37.971542],[-87.589816,37.976042],[-87.601416,37.972542],[-87.606216,37.949642],[-87.625616,37.933442],[-87.628416,37.92145],[-87.620272,37.906922],[-87.591582,37.887194],[-87.588729,37.860984],[-87.615399,37.831974],[-87.645858,37.825899],[-87.672397,37.829127],[-87.679188,37.836321],[-87.681633,37.855917],[-87.66282,37.881449],[-87.665025,37.893514],[-87.67573,37.90193],[-87.684018,37.903498],[-87.717971,37.89257],[-87.740148,37.89465],[-87.76226,37.890906],[-87.7909,37.875714],[-87.830578,37.876516],[-87.841193,37.882325],[-87.844691,37.892048],[-87.857243,37.900649],[-87.87254,37.920999],[-87.883321,37.926238],[-87.898062,37.927514],[-87.904789,37.924892],[-87.936784,37.892587],[-87.940839,37.883338],[-87.936228,37.867937],[-87.910276,37.843416],[-87.903804,37.817762],[-87.90681,37.807624],[-87.932554,37.797672],[-87.944506,37.775256],[-87.95259,37.771742],[-87.96003,37.773223],[-87.976389,37.788004],[-87.997102,37.797672],[-88.015144,37.80193],[-88.02803,37.799224],[-88.035827,37.791917],[-88.042602,37.76712],[-88.059588,37.742608],[-88.122412,37.709685],[-88.159372,37.661847],[-88.156827,37.632801],[-88.142225,37.603737],[-88.139973,37.586451],[-88.13341,37.574273],[-88.105585,37.55618],[-88.088049,37.535124],[-88.069018,37.525297],[-88.061342,37.505327],[-88.064234,37.484548],[-88.067728,37.481593],[-88.072386,37.483563],[-88.087664,37.471059],[-88.135142,37.471626],[-88.188615,37.461896],[-88.281667,37.452596],[-88.312585,37.440591],[-88.333183,37.42721],[-88.348405,37.410726],[-88.365471,37.401663],[-88.39734,37.421644],[-88.413108,37.424468],[-88.456,37.408482],[-88.476592,37.386875],[-88.484462,37.345609],[-88.511497,37.298527],[-88.515939,37.284043],[-88.506942,37.266656],[-88.509328,37.26213],[-88.487277,37.244077],[-88.471753,37.220155],[-88.447764,37.203527],[-88.431488,37.160298],[-88.424403,37.152428],[-88.443538,37.109192],[-88.444605,37.098601],[-88.458948,37.073796],[-88.504437,37.065265],[-88.545403,37.070003],[-88.576718,37.085852],[-88.589207,37.099655],[-88.625889,37.119458],[-88.644872,37.122844],[-88.693983,37.141155],[-88.720224,37.140641],[-88.732105,37.143956],[-88.80572,37.188595],[-88.916934,37.224291],[-88.966831,37.229891],[-89.000968,37.224401],[-89.041263,37.202881],[-89.086526,37.165602],[-89.111189,37.119052],[-89.134931,37.103278],[-89.14132,37.093865],[-89.154504,37.088907],[-89.168087,37.074218],[-89.181369,37.046305],[-89.178975,37.020928],[-89.166447,37.003337],[-89.132685,36.9822],[-89.170008,36.970298],[-89.185491,36.973518],[-89.192097,36.979995],[-89.200793,37.016164],[-89.234053,37.037277],[-89.25493,37.072014],[-89.259936,37.064071],[-89.307726,37.069654],[-89.310819,37.057897],[-89.304752,37.047565],[-89.277715,37.03614],[-89.260003,37.023288],[-89.257608,37.015496],[-89.263527,37.00005],[-89.278628,36.98867],[-89.29213,36.992189],[-89.322982,37.01609],[-89.362397,37.030156],[-89.378277,37.039605],[-89.385434,37.05513],[-89.375712,37.080505],[-89.37871,37.094586],[-89.38805,37.107481],[-89.41173,37.122507],[-89.42558,37.138235],[-89.461862,37.199517],[-89.4675,37.221844],[-89.458246,37.247066],[-89.470525,37.253357],[-89.488728,37.251507],[-89.506773,37.268537],[-89.51834,37.285497],[-89.511842,37.310825],[-89.489005,37.333368],[-89.447556,37.340475],[-89.432836,37.347056],[-89.421054,37.387668],[-89.42594,37.407471],[-89.439769,37.4372],[-89.475525,37.471388],[-89.516447,37.535558],[-89.521925,37.560735],[-89.519808,37.582748],[-89.486062,37.580853],[-89.477548,37.585885],[-89.475932,37.592998],[-89.517718,37.641217],[-89.51204,37.680985],[-89.514255,37.689923],[-89.52573,37.698441],[-89.583316,37.713261],[-89.596566,37.732886],[-89.615586,37.74235],[-89.615933,37.748184],[-89.64953,37.745498],[-89.663352,37.750052],[-89.667993,37.759484],[-89.66038,37.786296],[-89.669644,37.799922],[-89.71748,37.825724],[-89.739873,37.84693],[-89.754104,37.846358],[-89.782035,37.855092],[-89.786369,37.851734],[-89.796087,37.859505],[-89.80036,37.868625],[-89.798041,37.879655],[-89.842649,37.905196],[-89.862949,37.896906],[-89.881475,37.879591],[-89.901832,37.869822],[-89.923185,37.870672],[-89.950594,37.881526],[-89.973642,37.917661],[-89.974918,37.926719],[-89.962273,37.934363],[-89.959646,37.940196],[-89.947429,37.940336],[-89.932467,37.947497],[-89.925389,37.95413],[-89.925085,37.960021],[-89.933797,37.959143],[-89.942099,37.970121],[-89.978919,37.962791],[-89.997103,37.963225],[-90.008353,37.970179],[-90.03241,37.995258],[-90.051357,38.003584],[-90.059367,38.015543],[-90.08826,38.015772],[-90.11052,38.026547],[-90.126194,38.040702],[-90.126396,38.054897],[-90.130788,38.062341],[-90.158533,38.074735],[-90.17222,38.069636],[-90.218708,38.094365],[-90.243116,38.112669],[-90.274928,38.157615],[-90.290765,38.170453],[-90.331554,38.18758],[-90.359559,38.224525],[-90.373929,38.281853],[-90.372519,38.323354],[-90.368219,38.340254],[-90.349743,38.377609],[-90.295316,38.426753],[-90.285215,38.443453],[-90.279215,38.472453],[-90.260314,38.528352],[-90.224212,38.575051],[-90.196011,38.594451],[-90.18451,38.611551],[-90.17801,38.63375],[-90.18111,38.65955],[-90.18641,38.67475],[-90.20921,38.70275],[-90.21201,38.71175],[-90.20991,38.72605],[-90.176309,38.754449],[-90.166409,38.772649],[-90.123107,38.798048],[-90.114707,38.815048],[-90.109407,38.843548],[-90.113327,38.849306],[-90.166409,38.876348],[-90.19761,38.887648],[-90.223041,38.907389],[-90.250248,38.919344],[-90.309454,38.92412],[-90.395816,38.960037],[-90.440078,38.967364],[-90.450792,38.967764],[-90.472122,38.958838],[-90.482419,38.94446],[-90.486974,38.925982],[-90.500117,38.910408],[-90.54403,38.87505],[-90.566557,38.868847],[-90.583388,38.86903],[-90.628485,38.891617],[-90.639917,38.908272],[-90.653164,38.916141],[-90.663372,38.928042],[-90.675949,38.96214],[-90.678193,38.991851],[-90.713629,39.053977],[-90.682744,39.088348],[-90.681086,39.10059],[-90.686051,39.117785],[-90.702923,39.138749],[-90.707902,39.15086],[-90.71048,39.176366],[-90.717404,39.197414],[-90.717113,39.213912],[-90.72996,39.255894],[-90.751599,39.265432],[-90.767648,39.280025],[-90.775673,39.292811],[-90.790675,39.302908],[-90.793461,39.309498],[-90.816851,39.320496],[-90.8475,39.345272],[-90.893777,39.367343],[-90.904862,39.379403],[-90.928745,39.387544],[-90.939025,39.402744],[-90.993789,39.422959],[-91.03827,39.448436],[-91.059439,39.46886],[-91.064305,39.494643],[-91.079769,39.507728],[-91.100307,39.538695],[-91.153628,39.548248],[-91.168419,39.564928],[-91.174232,39.591975],[-91.181936,39.602677],[-91.229317,39.620853],[-91.27614,39.665759],[-91.302485,39.679631],[-91.367753,39.729029],[-91.369953,39.745042],[-91.365125,39.758723],[-91.363444,39.792804],[-91.377971,39.811273],[-91.432919,39.840554],[-91.446385,39.870394],[-91.443513,39.893583],[-91.420878,39.914865],[-91.41936,39.927717],[-91.465315,39.983995],[-91.494878,40.036453],[-91.489606,40.057435],[-91.509245,40.121876],[-91.511749,40.147091],[-91.508324,40.156326],[-91.513079,40.178537],[-91.504477,40.198262],[-91.507269,40.209338],[-91.505828,40.238839],[-91.490524,40.259498],[-91.492727,40.278217],[-91.46214,40.342414],[-91.439342,40.366569],[-91.415695,40.381381],[-91.381958,40.387632],[-91.372921,40.399108],[-91.373721,40.417891],[-91.381769,40.442555],[-91.364915,40.484168],[-91.364211,40.500043],[-91.367876,40.510479],[-91.384531,40.530948],[-91.404125,40.539127],[-91.405241,40.554641],[-91.379752,40.57445],[-91.359873,40.601805],[-91.339719,40.613488],[-91.306524,40.626231],[-91.253074,40.637962],[-91.18698,40.637297],[-91.123928,40.669152],[-91.110927,40.703262],[-91.115735,40.725168],[-91.110424,40.745528],[-91.091703,40.779708],[-91.092256,40.792909],[-91.097649,40.805575],[-91.092993,40.821079],[-91.05643,40.848387],[-91.044653,40.868356],[-91.021562,40.884021],[-91.009536,40.900565],[-90.962916,40.924957],[-90.952233,40.954047],[-90.958142,40.979767],[-90.945949,41.006495],[-90.942253,41.034702],[-90.949383,41.07271],[-90.946259,41.094734],[-90.99496,41.160624],[-91.007586,41.166183],[-91.027214,41.163373],[-91.041536,41.166138],[-91.07298,41.207151],[-91.113648,41.241401],[-91.114186,41.250029],[-91.092034,41.286911],[-91.074841,41.305578],[-91.06652,41.365246],[-91.05158,41.385283],[-91.04589,41.414085],[-91.027787,41.423603],[-90.979815,41.434321],[-90.930016,41.421404],[-90.846558,41.455141],[-90.750142,41.449632],[-90.655839,41.462132],[-90.605937,41.494232],[-90.602137,41.506032],[-90.595237,41.511032],[-90.567236,41.517532],[-90.556235,41.524232],[-90.540935,41.526133],[-90.500633,41.518033],[-90.461432,41.523533],[-90.41283,41.565333],[-90.343228,41.587833],[-90.339528,41.598633],[-90.343452,41.646959],[-90.334525,41.679559],[-90.313435,41.698082],[-90.317668,41.72269],[-90.310708,41.742214],[-90.278633,41.767358],[-90.216889,41.795335],[-90.187969,41.803163],[-90.180954,41.809354],[-90.181901,41.843216],[-90.173006,41.857402],[-90.170041,41.876439],[-90.153584,41.906614],[-90.152659,41.933058],[-90.163847,41.944934],[-90.164135,41.956178],[-90.146225,41.981329],[-90.140061,42.003252],[-90.150916,42.02944],[-90.163446,42.040407],[-90.168358,42.075779],[-90.161504,42.098912],[-90.162895,42.116718],[-90.17097,42.125198],[-90.190452,42.125779],[-90.201404,42.130937],[-90.207421,42.149109],[-90.216107,42.15673],[-90.250129,42.171469],[-90.282173,42.178846],[-90.328273,42.201047],[-90.356964,42.205445],[-90.391108,42.225473],[-90.400653,42.239293],[-90.419326,42.254467],[-90.430884,42.27823],[-90.420454,42.305374],[-90.421047,42.316109],[-90.415937,42.322699],[-90.419027,42.328505],[-90.477279,42.383794],[-90.487154,42.385141],[-90.506829,42.398792],[-90.555018,42.416138],[-90.560439,42.432897],[-90.567968,42.440389],[-90.606328,42.451505],[-90.646727,42.471904],[-90.654027,42.478503],[-90.656527,42.489203],[-90.640927,42.508302],[-90.07367,42.508275],[-89.366031,42.500274]]]},\"properties\":{\"name\":\"Illinois\",\"nation\":\"USA \"}}]}","edition":"Version 1.0: October 29, 2014; Version 2.0: April 5, 2022","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
405 North Goodwin
Urbana, IL 61801