Two explosions were set off on 4 March 2008 at the N3 explosion site in northeastern Taiwan. The code name for the first shot with 3000 kg explosives is N3P and that for the second shot with 750 kg explosives is N3. To record these two explosions, 8 triaxial rotational sensors, 13 triaxial accelerometers, and 12 six-channel, 24 bit dataloggers with Global Positioning System receivers were deployed to continuously record several hours before and after the explosions. These instruments were installed at about 250 m (1 station), 500 m (11 stations), and 600 m (1 station) from the explosions. The 11 stations form a center array with station spacing of about 5 m.
Except for one rotational sensor, onscale records were obtained. Although the N3P shot used four times larger amounts of explosives than those used for the N3 shot, the peak ground translational acceleration and rotational velocity at the 13 station sites from the N3P shot are only about 1.5 times larger than those for the N3 shot. We also observed large variations (by tens of percent) of translational accelerations and rotational velocities at the center array with station spacing of about 5 m. The largest peak rotational velocity was observed for the x component: 2.74 and 1.75 mrad/sec at a distance of 254 m from the N3P and N3 shots, respectively.
The main purpose of this article is to document our recordings of rotational and translation motions from two explosions in Taiwan and to release the data online for open access. The translational acceleration data from this experiment have been analyzed by Langston et al. (2009), and we plan to submit an article with analysis of the rotational velocity data in the future.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120080176","usgsCitation":"Lin, C., Liu, C., and Lee, W., 2009, Recording rotational and translational ground motions of two TAIGER explosions in northeastern Taiwan on 4 March 2008 : Bulletin of the Seismological Society of America, v. 99, no. 2B, p. 1237-1250, https://doi.org/10.1785/0120080176.","productDescription":"14 p.","startPage":"1237","endPage":"1250","costCenters":[],"links":[{"id":373430,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Taiwan","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[121.77782,24.39427],[121.17563,22.79086],[120.74708,21.97057],[120.22008,22.81486],[120.10619,23.55626],[120.69468,24.53845],[121.49504,25.29546],[121.95124,24.9976],[121.77782,24.39427]]]},\"properties\":{\"name\":\"Taiwan\"}}]}","volume":"99","issue":"2B","noUsgsAuthors":false,"publicationDate":"2009-05-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Lin, Chin-Jen","contributorId":199136,"corporation":false,"usgs":false,"family":"Lin","given":"Chin-Jen","email":"","affiliations":[],"preferred":false,"id":785285,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Liu, Chun-Chi","contributorId":75240,"corporation":false,"usgs":true,"family":"Liu","given":"Chun-Chi","email":"","affiliations":[],"preferred":false,"id":785286,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lee, W.H.K.","contributorId":35303,"corporation":false,"usgs":true,"family":"Lee","given":"W.H.K.","affiliations":[],"preferred":false,"id":785287,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":97537,"text":"ds424 - 2009 - Database of the geologic map of North America— Adapted from the map by J.C. Reed, Jr. and others (2005)","interactions":[],"lastModifiedDate":"2021-09-17T20:58:34.429635","indexId":"ds424","displayToPublicDate":"2020-01-10T11:15:00","publicationYear":"2009","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":"424","displayTitle":"Database of the Geologic Map of North America: Adapted from the Map by J.C. Reed, Jr. and others (2005)","title":"Database of the geologic map of North America— Adapted from the map by J.C. Reed, Jr. and others (2005)","docAbstract":"The Geological Society of America's (GSA) Geologic Map of North America (Reed and others, 2005a; 1:5,000,000) shows the geology of a significantly large area of the Earth, centered on North and Central America and including the submarine geology of parts of the Atlantic and Pacific Oceans. This map is now converted to a Geographic Information System (GIS) database that contains all geologic and base-map information shown on the two printed map sheets and the accompanying explanation sheet. We anticipate this map database will be revised at some unspecified time in the future, likely through the actions of a steering committee managed by the GSA and staffed by scientists from agencies including those responsible for the original map compilation.
Regarding the use of this product, as noted by the map's compilers:
“The Geologic Map of North America is an essential educational tool for teaching the geology of North America to university students and for the continuing education of professional geologists in North America and elsewhere. In addition, simplified maps derived from the Geologic Map of North America are useful for enlightening younger students and the general public about the geology of the continent.”
With publication of this database, the preparation of any type of simplified map is made significantly easier. More important perhaps, the database provides a more accessible means to explore the map information and to compare and analyze it in conjunction with other types of information (for example, land use, soils, biology) to better understand the complex interrelations among factors that affect Earth resources, hazards, ecosystems, and climate.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds424","collaboration":"Prepared in cooperation with the Geological Society of America","usgsCitation":"Garrity, C.P., and Soller, D.R., 2009, Database of the Geologic Map of North America; adapted from the map by J.C. Reed, Jr. and others (2005): U.S. Geological Survey Data Series 424 [https://pubs.usgs.gov/ds/424/].","productDescription":"Report: iii, 7 p.;Database; Metadata; ReadMe","onlineOnly":"N","additionalOnlineFiles":"Y","costCenters":[{"id":173,"text":"Central Region Earth Surface Processes","active":false,"usgs":true}],"links":[{"id":371142,"rank":7,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/424/ds424_map_units.pdf","text":"Explanation of Map Units","size":"7.33 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":371141,"rank":6,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/ds/424/USGS_DS_424.zip","text":"GIS Data Bundle","size":"71.5 MB","linkFileType":{"id":6,"text":"zip"}},{"id":371140,"rank":5,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/ds/424/metadata.txt","size":"70.8 KB","linkFileType":{"id":2,"text":"txt"}},{"id":371139,"rank":4,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/ds/424/ds424_readme.pdf","size":"34.0 KB","linkFileType":{"id":1,"text":"pdf"}},{"id":371138,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/ds/424/version_history.txt","size":"494 B","linkFileType":{"id":2,"text":"txt"}},{"id":371137,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/424/ds424_text.pdf","text":"Report","size":"93.1 KB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 424"},{"id":389454,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_86688.htm"},{"id":371136,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/424/coverthb.jpg"}],"otherGeospatial":"North America","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.6953125,\n 6.839169626342808\n ],\n [\n -77.16796875,\n 9.102096738726456\n ],\n [\n -75.05859375,\n 13.752724664396988\n ],\n [\n -62.57812500000001,\n 16.804541076383455\n ],\n [\n -58.18359375,\n 44.84029065139799\n ],\n [\n -51.85546874999999,\n 47.15984001304432\n ],\n [\n -36.38671875,\n 65.07213008560697\n ],\n [\n -19.51171875,\n 70.72897946208789\n ],\n [\n -10.546875,\n 81.79875708305217\n ],\n [\n -27.0703125,\n 83.7539108491127\n ],\n [\n -42.01171875,\n 83.65755395878921\n ],\n [\n -58.71093750000001,\n 82.58610635020881\n ],\n [\n -73.30078125,\n 83.31873282163234\n ],\n [\n -85.78125,\n 82.76537263027352\n ],\n [\n -102.3046875,\n 80.26825877186884\n ],\n [\n -123.22265625000001,\n 76.84081641443098\n ],\n [\n -129.7265625,\n 72.0739114882038\n ],\n [\n -135.52734375,\n 70.08056215839737\n ],\n [\n -137.63671875,\n 69.47296854140573\n ],\n [\n -155.21484375,\n 72.01972876525514\n ],\n [\n -163.65234374999997,\n 70.55417853776078\n ],\n [\n -167.87109375,\n 68.13885164925573\n ],\n [\n -172.44140625,\n 63.074865690586634\n ],\n [\n -170.5078125,\n 58.99531118795094\n ],\n [\n -165.234375,\n 57.89149735271034\n ],\n [\n -171.03515625,\n 53.54030739150022\n ],\n [\n -169.27734375,\n 50.62507306341435\n ],\n [\n -148.88671874999997,\n 58.07787626787517\n ],\n [\n -137.98828125,\n 54.87660665410869\n ],\n [\n -131.1328125,\n 50.51342652633956\n ],\n [\n -127.44140625,\n 41.902277040963696\n ],\n [\n -123.57421875,\n 34.88593094075317\n ],\n [\n -107.40234375,\n 16.804541076383455\n ],\n [\n -85.95703125,\n 8.581021215641854\n ],\n [\n -79.8046875,\n 5.965753671065536\n ],\n [\n -77.6953125,\n 6.839169626342808\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0","contact":"National Geologic Map Database
Resources Page
Our purpose is to annually update our creep-data archive on San Francisco Bay region active faults for use by the scientific research community. Earlier data (1979-2001) were reported in Galehouse (2002) and were analyzed and described in detail in a summary report (Galehouse and Lienkaemper, 2003). A complete analysis of our earlier results obtained on the Hayward Fault was presented in Lienkaemper, Galehouse and Simpson (2001) and updated in Lienkaemper and others (2012). Lienkaemper and others (2014) provide a new overview and analysis of fault creep along all sections of the northern San Andreas Fault system, from which they estimate by how much fault creep reduces the seismic hazard for each fault section.
From 1979 until his retirement from the project in 2001, Jon Galehouse of San Francisco State University (SFSU) and many student research assistants measured creep (aseismic slip) rates on these faults. The creep measurement project, which was initiated by Galehouse, continued through the Geosciences Department at SFSU from 2001-2006 under the direction of Karen Grove and John Caskey (Grove and Caskey, 2005) and since 2006 under Caskey (2007). Forrest McFarland has managed most of the technical and logistical project operations, as well as data processing and compilation since 2001. Data from 2001-2007 are found in McFarland and others (2007). From 2009 onward, we have released the raw data annually using this report (OF2009-1119) as a permanent publication link, while publishing more detailed analyses of these data in the scientific literature, such as Lienkaemper and others (2014).
We maintain a project Web site (http://funnel.sfsu.edu/creep/) that includes the following information: project description, project personnel, creep characteristics and measurement, map of creep-measurement sites, creep-measurement site information, and links to data plots for each measurement site. Our most current, annually updated results are, therefore, accessible to the scientific community and to the general public. Information about the project can currently be requested by the public by an email link (fltcreep@sfsu.edu) found on our project Web site.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20091119","usgsCitation":"McFarland, F., Lienkaemper, J.J., and Caskey, S.J., 2009, Data from theodolite measurements of creep rates on San Francisco Bay region faults, California (Version 1.0: July 8, 2009; Version 1.1: April 19, 2010; Version 1.2: May 5, 2011; Version 1.3: April 19, 2012; Version 1.4: March 20, 2013; Version 1.5: February 3, 2014; Version 1.6: March 16, 2015; Version 1.8: March 29, 2016): U.S. Geological Survey Open-File Report 2009-1119, Report: 21 p.; Data Files, https://doi.org/10.3133/ofr20091119.","productDescription":"Report: 21 p.; Data Files","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"1979-01-01","temporalEnd":"2012-12-31","costCenters":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":369532,"rank":4,"type":{"id":28,"text":"Dataset"},"url":"https://pubs.usgs.gov/of/2009/1119/data","text":"Data folder"},{"id":269859,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2009/1119/ofr20091119.pdf","text":"Report","size":"2.44 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2009-1119"},{"id":394202,"rank":5,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_86844.htm"},{"id":369531,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2009/1119/versionhistory.txt","size":"1.86 KB"},{"id":118504,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2009/1119/coverthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.8,\n 36.8\n ],\n [\n -121.0722,\n 36.8\n ],\n [\n -121.0722,\n 39.8\n ],\n [\n -123.8,\n 39.8\n ],\n [\n -123.8,\n 36.8\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: July 8, 2009; Version 1.1: April 19, 2010; Version 1.2: May 5, 2011; Version 1.3: April 19, 2012; Version 1.4: March 20, 2013; Version 1.5: February 3, 2014; Version 1.6: March 16, 2015; Version 1.8: March 29, 2016","contact":"Earthquake Science Center in Menlo Park, California
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Habitat modeling is an important tool used to simulate the potential distribution of a species for a variety of basic and applied questions. The desert tortoise (Gopherus agassizii) is a federally listed threatened species in the Mojave Desert and parts of the Sonoran Desert of California, Nevada, Utah, and Arizona. Land managers in this region require reliable information about the potential distribution of desert tortoise habitat to plan conservation efforts, guide monitoring activities, monitor changes in the amount and quality of habitat available, minimize and mitigate disturbances, and ultimately to assess the status of the tortoise and its habitat toward recovery of the species. By applying information from the literature and our knowledge or assumptions of environmental variables that could potentially explain variability in the quality of desert tortoise habitat, we developed a quantitative habitat model for the desert tortoise using an extensive set of field-collected presence data. Sixteen environmental data layers were converted into a grid covering the study area and merged with the desert tortoise presence data that we gathered for input into the Maxent habitat-modeling algorithm. This model provides output of the statistical probability of habitat potential that can be used to map potential areas of desert tortoise habitat. This type of analysis, while robust in its predictions of habitat, does not account for anthropogenic changes that may have altered habitat with relatively high potential into areas with lower potential.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20091102","collaboration":"Prepared as a part of the Department of the Interior on the Landscape - Mojave Project for the Western Region, of the U.S. Geological Survey ","usgsCitation":"Nussear, K.E., Esque, T.C., Inman, R.D., Gass, Leila, Thomas, K.A., Wallace, C.S.A., Blainey, J.B., Miller, D.M., and Webb, R.H., 2009, Modeling habitat of the desert tortoise (Gopherus agassizii) in the Mojave and parts of the Sonoran Deserts of California, Nevada, Utah, and Arizona: U.S. Geological Survey Open-File Report 2009-1102, 18 p.","productDescription":"Report: iv, 18 p.; 2 Companion Files","numberOfPages":"18","additionalOnlineFiles":"Y","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":367969,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2009/1102/ofr20091102_dt_Habitat_Model.zip","size":"162 KB","linkFileType":{"id":6,"text":"zip"},"linkHelpText":" - Habitat Model"},{"id":195896,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2009/1102/coverthb.gif"},{"id":367970,"rank":4,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2009/1102/ofr20091102_Environmental_Layers.zip","size":"27.4 MB","linkFileType":{"id":6,"text":"zip"},"linkHelpText":" - Environmental Layers"},{"id":367968,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2009/1102/ofr20091102.pdf","text":"Report","size":"1.52 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2009-1102"}],"country":"United States","state":"California, Nevada, Utah, Arizona","otherGeospatial":"Mojave Desert, Sonoran Desert","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.30029296875,\n 32.76880048488168\n ],\n [\n -109.2919921875,\n 32.76880048488168\n ],\n [\n -109.2919921875,\n 39.2492708462234\n ],\n [\n -120.30029296875,\n 39.2492708462234\n ],\n [\n -120.30029296875,\n 32.76880048488168\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Ecological Research Center
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3020 State University Drive East
Modoc Hall, Room 3006
Sacramento, CA 95819
Fishery-independent (FI) surveys provide critical information used for the sustainable management and conservation of fish populations. Because fisheries management often requires the effects of management actions to be evaluated and detected within a relatively short time frame, it is important that research be directed toward FI survey evaluation, especially with respect to the ability to detect temporal trends. Using annual FI gill-net survey data for Lake Erie walleyes Sander vitreus collected from 1978 to 2006 as a case study, our goals were to (1) highlight the usefulness of hierarchical models for estimating spatial and temporal sources of variation in catch per effort (CPE); (2) demonstrate how the resulting variance estimates can be used to examine the statistical power to detect temporal trends in CPE in relation to sample size, duration of sampling, and decisions regarding what data are most appropriate for analysis; and (3) discuss recommendations for evaluating FI surveys and analyzing the resulting data to support fisheries management. This case study illustrated that the statistical power to detect temporal trends was low over relatively short sampling periods (e.g., 5–10 years) unless the annual decline in CPE reached 10–20%. For example, if 50 sites were sampled each year, a 10% annual decline in CPE would not be detected with more than 0.80 power until 15 years of sampling, and a 5% annual decline would not be detected with more than 0.8 power for approximately 22 years. Because the evaluation of FI surveys is essential for ensuring that trends in fish populations can be detected over management-relevant time periods, we suggest using a meta-analysis–type approach across systems to quantify sources of spatial and temporal variation. This approach can be used to evaluate and identify sampling designs that increase the ability of managers to make inferences about trends in fish stocks.
","language":"English","publisher":"Taylor & Francis","doi":"10.1577/M08-197.1","usgsCitation":"Wagner, T., Vandergoot, C.S., and Tyson, J., 2009, Evaluating the power to detect temporal trends in fishery independent surveys: A case study based on Gillnets Set in the Ohio waters of Lake Erie for walleye: North American Journal of Fisheries Management, v. 29, no. 3, p. 805-816, https://doi.org/10.1577/M08-197.1.","productDescription":"11 p.","startPage":"805","endPage":"816","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-008027","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":323907,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Ohio","otherGeospatial":"Lake Erie","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.5352783203125,\n 41.97174336327968\n ],\n [\n -80.540771484375,\n 42.32606244456202\n ],\n [\n -81.287841796875,\n 42.200038266046754\n ],\n [\n -82.40295410156249,\n 41.672911819602085\n ],\n [\n -82.6885986328125,\n 41.672911819602085\n ],\n [\n -83.067626953125,\n 41.86137915587359\n ],\n [\n -83.111572265625,\n 41.95131994679697\n ],\n [\n -83.4356689453125,\n 41.701627343789184\n ],\n [\n -82.9852294921875,\n 41.56203190200195\n ],\n [\n -82.99072265625,\n 41.46742831254425\n ],\n [\n -82.913818359375,\n 41.40153558289846\n ],\n [\n -82.7490234375,\n 41.422134246213616\n ],\n [\n -82.6611328125,\n 41.44684402008925\n ],\n [\n -82.45788574218749,\n 41.347948493443546\n ],\n [\n -82.0458984375,\n 41.492120839687786\n ],\n [\n -81.88110351562499,\n 41.44272637767212\n ],\n [\n -81.6888427734375,\n 41.44684402008925\n ],\n [\n -81.3262939453125,\n 41.7180304600481\n ],\n [\n -81.1285400390625,\n 41.79179268262892\n ],\n [\n -80.804443359375,\n 41.87774145109676\n ],\n [\n -80.5352783203125,\n 41.97174336327968\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"29","issue":"3","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2009-06-01","publicationStatus":"PW","scienceBaseUri":"57651f33e4b07657d19c7898","contributors":{"authors":[{"text":"Wagner, Tyler 0000-0003-1726-016X twagner@usgs.gov","orcid":"https://orcid.org/0000-0003-1726-016X","contributorId":1050,"corporation":false,"usgs":true,"family":"Wagner","given":"Tyler","email":"twagner@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":637167,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vandergoot, Christopher S.","contributorId":71849,"corporation":false,"usgs":false,"family":"Vandergoot","given":"Christopher","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":639602,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tyson, Jeff","contributorId":147298,"corporation":false,"usgs":false,"family":"Tyson","given":"Jeff","affiliations":[],"preferred":false,"id":639603,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70007521,"text":"70007521 - 2009 - Contributions of nitrogen to the Barnegat Bay-Little Egg Harbor Estuary: Updated loading estimates","interactions":[],"lastModifiedDate":"2016-04-25T14:32:31","indexId":"70007521","displayToPublicDate":"2015-07-14T13:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Contributions of nitrogen to the Barnegat Bay-Little Egg Harbor Estuary: Updated loading estimates","docAbstract":"Based on the most recent and most accurate data available through 2008, the total load of nitrogen to the Barnegat Bay‐Little Egg Harbor (BB‐LEH) estuary from the most substantial sources (surface water, including surface‐water discharge and direct storm runoff; ground‐water discharge; and atmospheric deposition) is estimated to be 650,000 kilograms of nitrogen per year (kg N/yr). Surface water contributes 66 percent (431,000 kg N/yr), direct ground‐ water discharge accounts for 12 percent (78,000 kg N/yr), and atmospheric deposition accounts for 22 percent (141,000 kg N/yr). This new loading estimate was compared to a previously published estimate produced by using similar methodology but less current data through 1997. Findings of the present study include a substantially lower estimate of atmospheric deposition of nitrogen to the estuary compared to the previous estimate. The study results also offer further support of the relation between land use and nitrogen levels, and indicate that the Toms and Metedeconk River basins account for more than 60 percent of the nitrogen load to the estuary from surface‐water discharge. Differences between the two estimates can be attributed to both the use of more accurate and more recent data in the revised estimate, and actual changes in the magnitude of nitrogen loads from various sources. Gaps in available water‐quality and hydrologic data are documented, and additional analysis and monitoring that may improve the reliability of future nitrogen loading estimates are presented.
","largerWorkTitle":"Barnegat Bay Partnership State of the Bay Technical Report","language":"English","publisher":"U.S. Geological Survey","collaboration":"Prepared in cooperation with the Barnegat Bay National Estuary Program","usgsCitation":"Wieben, C.M., and Baker, R.J., 2009, Contributions of nitrogen to the Barnegat Bay-Little Egg Harbor Estuary: Updated loading estimates, 25 p.","productDescription":"25 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-017449","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":320532,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":320531,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://bbp.ocean.edu/pages/184.asp"}],"country":"United States","state":"New Jersey","otherGeospatial":"Barnegat Bay‐Little Egg Harbor estuary","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.014892578125,\n 40.14318974292438\n ],\n [\n -74.04510498046875,\n 40.03392360399664\n ],\n [\n -74.07257080078125,\n 39.87812720644829\n ],\n [\n -74.0863037109375,\n 39.74521015328692\n ],\n [\n -74.15496826171874,\n 39.65011210186371\n ],\n [\n -74.22088623046875,\n 39.5633531658293\n ],\n [\n -74.2840576171875,\n 39.50615988027491\n ],\n [\n -74.3609619140625,\n 39.5146359327835\n ],\n [\n -74.41864013671875,\n 39.53370327008705\n ],\n [\n -74.47906494140625,\n 39.552765371831015\n ],\n [\n -74.49554443359375,\n 39.592990390285024\n ],\n [\n -74.4873046875,\n 39.66491373749128\n ],\n [\n -74.4488525390625,\n 39.707186656826565\n ],\n [\n -74.36370849609375,\n 39.7958755252971\n ],\n [\n -74.33624267578125,\n 39.838068180000015\n ],\n [\n -74.35821533203125,\n 39.871803651624425\n ],\n [\n -74.42962646484375,\n 39.90762941952987\n ],\n [\n -74.46258544921875,\n 39.95817509460007\n ],\n [\n -74.5037841796875,\n 40.03182061333687\n ],\n [\n -74.5037841796875,\n 40.157885249506506\n ],\n [\n -74.4708251953125,\n 40.24179856487036\n ],\n [\n -74.4158935546875,\n 40.25228042623783\n ],\n [\n -74.29504394531249,\n 40.250184183819854\n ],\n [\n -74.19891357421875,\n 40.2313150803688\n ],\n [\n -74.14672851562499,\n 40.21873275657031\n ],\n [\n -74.1192626953125,\n 40.20195268954057\n ],\n [\n -74.0643310546875,\n 40.176774799905445\n ],\n [\n -74.014892578125,\n 40.14318974292438\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"571f3fb3e4b071321fe56a10","contributors":{"authors":[{"text":"Wieben, Christine M. 0000-0001-5825-5119 cwieben@usgs.gov","orcid":"https://orcid.org/0000-0001-5825-5119","contributorId":4270,"corporation":false,"usgs":true,"family":"Wieben","given":"Christine","email":"cwieben@usgs.gov","middleInitial":"M.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":626208,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baker, Ronald J. rbaker@usgs.gov","contributorId":1436,"corporation":false,"usgs":true,"family":"Baker","given":"Ronald","email":"rbaker@usgs.gov","middleInitial":"J.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":626209,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70041533,"text":"70041533 - 2009 - The observed relationship between wave conditions and beach response, Ocean Beach, San Francisco, CA","interactions":[],"lastModifiedDate":"2015-10-29T14:24:25","indexId":"70041533","displayToPublicDate":"2015-07-06T08:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2220,"text":"Journal of Coastal Research","active":true,"publicationSubtype":{"id":10}},"title":"The observed relationship between wave conditions and beach response, Ocean Beach, San Francisco, CA","docAbstract":"Understanding how sandy beaches respond to storms is critical for effective sediment management and developing successful erosion mitigation efforts. However, only limited progress has been made in relating observed beach changes to wave conditions, with one of the major limiting factors being the lack of temporally dense beach topography and nearshore wave data in most studies. This study uses temporally dense beach topographic and offshore wave data to directly link beach response and wave forcing with generally good results. Ocean Beach is an open coast high-energy sandy beach located in San Francisco, CA, USA. From April 2004 through the end of 2008, 60 three-dimensional topographic beach surveys were conducted on approximately a monthly basis, with more frequent “short-term surveys during the winters of 2005-06 and 2006-07. Shoreline position data from the short-term surveys show good correlation with offshore wave height, period, and direction averaged over several days prior to the survey (mean R*=0.54 for entire beach). There is, however, considerable alongshore variation in model performance, with R- values ranging from 0.81 to 0.19 for individual sections of the beach. After wave height, the direction of wave approach was the most important factor in determining the response of the shoreline, followed by wave period. Our results indicate that an empirical predictive model of beach response to wave conditions at Ocean Beach is possible with frequent beach mapping and wave data, and that such a model could be useful to coastal managers.
","language":"English","publisher":"Coastal Education & Research Foundation","usgsCitation":"Hansen, J., and Barnard, P., 2009, The observed relationship between wave conditions and beach response, Ocean Beach, San Francisco, CA: Journal of Coastal Research, no. Special Issue 56, p. 1771-1775.","productDescription":"5 p.","startPage":"1771","endPage":"1775","numberOfPages":"5","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-011160","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":310776,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"San Francisco","otherGeospatial":"Ocean Beach","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.60604858398438,\n 37.505368263398104\n ],\n [\n -122.60604858398438,\n 37.804358908571395\n ],\n [\n -122.43301391601562,\n 37.804358908571395\n ],\n [\n -122.43301391601562,\n 37.505368263398104\n ],\n [\n -122.60604858398438,\n 37.505368263398104\n ]\n ]\n ]\n }\n }\n ]\n}","issue":"Special Issue 56","publicComments":"Proceedings of the 10th International Coastal Symposium","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56334344e4b048076347eeed","contributors":{"authors":[{"text":"Hansen, J.E.","contributorId":11855,"corporation":false,"usgs":true,"family":"Hansen","given":"J.E.","email":"","affiliations":[],"preferred":false,"id":578725,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barnard, P.L.","contributorId":20527,"corporation":false,"usgs":true,"family":"Barnard","given":"P.L.","email":"","affiliations":[],"preferred":false,"id":578726,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70004127,"text":"70004127 - 2009 - Responses of stream nitrate and dissolved organic carbon loadings to hydrological forcing and climate change in an upland forest of the northeast USA","interactions":[],"lastModifiedDate":"2015-11-16T14:43:54","indexId":"70004127","displayToPublicDate":"2015-06-08T09:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2312,"text":"Journal of Geophysical Research","active":true,"publicationSubtype":{"id":10}},"title":"Responses of stream nitrate and dissolved organic carbon loadings to hydrological forcing and climate change in an upland forest of the northeast USA","docAbstract":"[1] In coming decades, higher annual temperatures, increased growing season length, and increased dormant season precipitation are expected across the northeastern United States in response to anthropogenic forcing of global climate. We synthesized long-term stream hydrochemical data from the Sleepers River Research Watershed in Vermont, United States, to explore the relationship of catchment wetness to stream nitrate and DOC loadings. We modeled changes in growing season length and precipitation patterns to simulate future climate scenarios and to assess how stream nutrient loadings respond to climate change. Model results for the 2070–2099 time period suggest that stream nutrient loadings during both the dormant and growing seasons will respond to climate change. During a warmer climate, growing season stream fluxes (runoff +20%, nitrate +57%, and DOC +58%) increase as more precipitation (+28%) and quick flow (+39%) occur during a longer growing season (+43 days). During the dormant season, stream water and nutrient loadings decrease. Net annual stream runoff (+8%) and DOC loading (+9%) increases are commensurate with the magnitude of the average increase of net annual precipitation (+7%). Net annual stream water and DOC loadings are primarily affected by increased dormant season precipitation. In contrast, decreased annual loading of stream nitrate (−2%) reflects a larger effect of growing season controls on stream nitrate and the effects of lengthened growing seasons in a warmer climate. Our findings suggest that leaching of nitrate and DOC from catchment soils will be affected by anthropogenic climate forcing, thereby affecting the timing and magnitude of annual stream loadings in the northeastern United States.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2008JG000778","usgsCitation":"Sebestyen, S.D., Boyer, E.W., and Shanley, J.B., 2009, Responses of stream nitrate and dissolved organic carbon loadings to hydrological forcing and climate change in an upland forest of the northeast USA: Journal of Geophysical Research, v. 114, no. G2, 11 p., https://doi.org/10.1029/2008JG000778.","productDescription":"11 p.","numberOfPages":"11","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-006854","costCenters":[],"links":[{"id":475963,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2008jg000778","text":"Publisher Index Page"},{"id":311383,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":311382,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://onlinelibrary.wiley.com/doi/10.1029/2008JG000778/abstract"}],"country":"United States","state":"Vermont","otherGeospatial":"Sleepers River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -71.8890380859375,\n 44.10139306449849\n ],\n [\n -71.8890380859375,\n 44.896741421341964\n ],\n [\n -71.0101318359375,\n 44.896741421341964\n ],\n [\n -71.0101318359375,\n 44.10139306449849\n ],\n [\n -71.8890380859375,\n 44.10139306449849\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"114","issue":"G2","noUsgsAuthors":false,"publicationDate":"2009-04-07","publicationStatus":"PW","scienceBaseUri":"564b0c5be4b0ebfbef0d3183","contributors":{"authors":[{"text":"Sebestyen, Stephen D.","contributorId":107562,"corporation":false,"usgs":true,"family":"Sebestyen","given":"Stephen","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":579889,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boyer, Elizabeth W.","contributorId":44659,"corporation":false,"usgs":false,"family":"Boyer","given":"Elizabeth","email":"","middleInitial":"W.","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":579890,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shanley, James B. 0000-0002-4234-3437 jshanley@usgs.gov","orcid":"https://orcid.org/0000-0002-4234-3437","contributorId":1953,"corporation":false,"usgs":true,"family":"Shanley","given":"James","email":"jshanley@usgs.gov","middleInitial":"B.","affiliations":[{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":579891,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70192959,"text":"70192959 - 2009 - Characterization of rock samples and mineralogical controls on leachates","interactions":[],"lastModifiedDate":"2017-12-21T10:35:51","indexId":"70192959","displayToPublicDate":"2015-06-02T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"title":"Characterization of rock samples and mineralogical controls on leachates","docAbstract":"Rocks associated with coal beds typically include shale, sandstone, and (or) limestone. In addition to common rock-forming minerals, all of these rock types may contain sulfide and sulfate minerals, various carbonate minerals, and organic material. These different minerals have inherently different solubility characteristics, as well as different acid-generating or acid-neutralizing potentials. The abundance and composition of sulfur- and carbonate-bearing minerals are of particular interest in interpreting the leaching column data because (1) pyrite and carbonate minerals are the primary controls on the acid-base account of a sample, (2) these minerals incorporate trace metals that can be released during weathering, and (3) these minerals readily react during weathering due to mineral dissolution and oxidation of iron.
Rock samples were collected by the Pennsylvania Department of Environmental Protection (PaDEP) from five different sites to assess the draft standardized leaching column method (ADTI-WP2) for the prediction of weathering rates and water quality at coal mines. Samples were sent to USGS laboratories for mineralogical characterization and to ActLabs for chemical analysis. The samples represent a variety of rock types (shales, sandstones, and coal refuse) that are typical of coal overburden in the eastern United States. These particular samples were chosen for testing the weathering protocols because they represent a range of geochemical and lithologic characteristics, sulfur contents, and acid-base accounting characteristics (Hornberger et al., 2003). The rocks contain variable amounts of pyrite and carbonate minerals and vary in texture.
This chapter includes bulk rock chemical data and detailed mineralogical and textural data for unweathered starting materials used in the interlaboratory validation study, and for two samples used in the early phases of leaching column tests (Wadesville Sandstone, Leechburg Coal Refuse). We also characterize some of the post-weathering rock samples, report trace-element content in leachate, and discuss mineralogical controls on leachate quality based on data from one of the participating laboratories. Table 5.1 lists the samples described in this chapter, the sample numbers, and comments on the characteristics of each lithology. Sample locations are plotted in Figure 5.1. Chapters 2 and 3 describe the sample locations, sample preparation protocols, ABA characteristics, and rationale for selection of rock samples for testing. Microprobe data for pyrite and carbonate minerals are tabulated in Appendix 5.1. Leachate data, along with a series of graphs showing concentration and cumulative transport trends, for the laboratory data discussed in this chapter are included as Excel spreadsheets in Appendices 5.2 and 5.3. Leach column data for the interlaboratory study are evaluated and interpreted in Chapters 7 -11.
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EPA Method 1627","language":"English","publisher":"Office of Surface Mining Reclamation and Enforcement","usgsCitation":"Hammarstrom, J.M., Cravotta, C., Galeone, D.G., Jackson, J.C., and Dulong, F.T., 2009, Characterization of rock samples and mineralogical controls on leachates, 51 p.","productDescription":"51 p.","startPage":"61","endPage":"111","ipdsId":"IP-011226","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":350149,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":347650,"type":{"id":15,"text":"Index Page"},"url":"https://aciddrainage.com/publications/"}],"country":"United States","state":"Arkansas, Florida, Georgia, Illinois, Indiana, Iowa, Kansas, Kentucky, Louisiana, Michigan, Mississippi, Missouri, Nebraska, Ohio, Oklahoma, Pennsylvania, Tennessee, Texas, Virginia, West Virginia","geographicExtents":"{\n \"type\": 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III 0000-0003-3116-4684 cravotta@usgs.gov","orcid":"https://orcid.org/0000-0003-3116-4684","contributorId":196993,"corporation":false,"usgs":true,"family":"Cravotta","given":"Charles A.","suffix":"III","email":"cravotta@usgs.gov","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":false,"id":717439,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Galeone, Daniel G. 0000-0002-8007-9278 dgaleone@usgs.gov","orcid":"https://orcid.org/0000-0002-8007-9278","contributorId":2301,"corporation":false,"usgs":true,"family":"Galeone","given":"Daniel","email":"dgaleone@usgs.gov","middleInitial":"G.","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":717440,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jackson, John C. jjackson@usgs.gov","contributorId":2652,"corporation":false,"usgs":true,"family":"Jackson","given":"John","email":"jjackson@usgs.gov","middleInitial":"C.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":717443,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dulong, Frank T. 0000-0001-7388-647X fdulong@usgs.gov","orcid":"https://orcid.org/0000-0001-7388-647X","contributorId":650,"corporation":false,"usgs":true,"family":"Dulong","given":"Frank","email":"fdulong@usgs.gov","middleInitial":"T.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":717441,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70157388,"text":"70157388 - 2009 - Estimating phosphorus concentrations following alum treatment using apparent settling velocity","interactions":[],"lastModifiedDate":"2018-02-06T12:36:14","indexId":"70157388","displayToPublicDate":"2015-06-01T05:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2592,"text":"Lake and Reservoir Management","active":true,"publicationSubtype":{"id":10}},"title":"Estimating phosphorus concentrations following alum treatment using apparent settling velocity","docAbstract":"he apparent settling velocity (Vs) is a term used in empirical, steady-state, mass-balance lake models to represent the net phosphorus flux from the water column. The Vollenweider (1969) mixed-reactor lake model was rearranged and used to calculate Vs values for total phosphorus (TP) for three lakes treated with alum to reduce the internal flux of P to the water column (Delavan Lake, Wisconsin; Lake Morey, Vermont; and West Twin Lake, Ohio). An analysis of Vs values was conducted using data from these three lakes for both the pre- and post-alum treated conditions. Analysis of Vs values for both the pre- and post-alum conditions in Lake Morey and West Twin Lake resulted in a post-treatment mean Vs value of 7 ± 2.0 m·yr−1. The effect of the alum treatment, although short-lived in Delavan Lake, resulted in a mean post-treatment Vs value of 3.4 ± 0.3 m·yr−1. The consistency in the post-treatment Vs values in Lake Morey and West Twin Lake is used to demonstrate a predictive analysis method for water column TP concentrations in lakes following a successful treatment of the anoxic sediment area with alum. Additional pre- and post-alum in-lake and watershed loading data are needed to advance this concept into a management model.
","language":"English","publisher":"North American Lake Management Society","doi":"10.1080/07438149909353949","usgsCitation":"Panuska, J., and Robertson, D.M., 2009, Estimating phosphorus concentrations following alum treatment using apparent settling velocity: Lake and Reservoir Management, v. 15, no. 1, p. 28-38, https://doi.org/10.1080/07438149909353949.","productDescription":"11 p.","startPage":"28","endPage":"38","numberOfPages":"11","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[],"links":[{"id":475965,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/07438149909353949","text":"Publisher Index Page"},{"id":308376,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Ohio, Vermont, Wisconsin","otherGeospatial":"Lake Delevan, Lake Morey, West Twin 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\"}}]}","volume":"15","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56027bbee4b03bc34f54482c","contributors":{"authors":[{"text":"Panuska, John","contributorId":31025,"corporation":false,"usgs":false,"family":"Panuska","given":"John","affiliations":[{"id":6913,"text":"Wisconsin Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":572948,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Robertson, Dale M. 0000-0001-6799-0596 dzrobert@usgs.gov","orcid":"https://orcid.org/0000-0001-6799-0596","contributorId":150760,"corporation":false,"usgs":true,"family":"Robertson","given":"Dale","email":"dzrobert@usgs.gov","middleInitial":"M.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":572949,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70041614,"text":"70041614 - 2009 - Diffusion-equation representations of landform evolution in the simplest circumstances: Appendix C","interactions":[],"lastModifiedDate":"2015-10-29T10:03:39","indexId":"70041614","displayToPublicDate":"2014-12-08T08:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":4,"text":"Book"},"publicationSubtype":{"id":13,"text":"Handbook"},"title":"Diffusion-equation representations of landform evolution in the simplest circumstances: Appendix C","docAbstract":"The diffusion equation is one of the three great partial differential equations of classical physics. It describes the flow or diffusion of heat in the presence of temperature gradients, fluid flow in porous media in the presence of pressure gradients, and the diffusion of molecules in the presence of chemical gradients. [The other two equations are the wave equation, which describes the propagation of electromagnetic waves (including light), acoustic (sound) waves, and elastic (seismic) waves radiated from earthquakes; and LaPlace’s equation, which describes the behavior of electric, gravitational, and fluid potentials, all part of potential field theory. The diffusion equation reduces to LaPlace’s equation at steady state, when the field of interest does not depend on t. Poisson’s equation is LaPlace’s equation with a source term.]
\nJoseph Fourier developed the diffusion equation for heat conduction in 1807, and it has significant associations with probability theory (Narasimhan, 2009), as we will see shortly. In a novel and fascinating application, Gene Humphreys has employed solutions of the diffusion equation to describe the density of desert tortoises in the presence of population gradients caused by new dirt roads cut in the Mojave Desert. These new dirt roads induce an immediate line sink for unsuspecting tortoises. As of this writing in early September, I am not sure whether Gene has published this work.
\nMost of us here know that the diffusion equation has also been used to describe the evolution through time of scarp-like landforms, including fault scarps, shoreline scarps, or a set of marine terraces. The methods, models, and data employed in such studies have been described in the literature many times over the past 25 years. For most situations, everything you will ever need (or want) to know can be found in Hanks et al. (1984) and Hanks (2000), the latter being a review of numerous studies of the 1980s and 1990s and a summary of available estimates of the mass diffusivity κ. The geometric parameterization of scarp-like landforms is shown in Figure 1.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Friends of the Pleistocene 2009 Pacific Cell Field Trip: Paleoseismic, geomorphic, and geodetic studies across the Central Great Basin: Exploring active deformation along the eastern edge of the Pacific/North American plate boundary.","largerWorkSubtype":{"id":13,"text":"Handbook"},"language":"English","usgsCitation":"Hanks, T.C., 2009, Diffusion-equation representations of landform evolution in the simplest circumstances: Appendix C, 6 p.","productDescription":"6 p.","numberOfPages":"6","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-016448","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":310751,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56334338e4b048076347eebf","contributors":{"authors":[{"text":"Hanks, Thomas C. 0000-0003-0928-0056 thanks@usgs.gov","orcid":"https://orcid.org/0000-0003-0928-0056","contributorId":3065,"corporation":false,"usgs":true,"family":"Hanks","given":"Thomas","email":"thanks@usgs.gov","middleInitial":"C.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":578665,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70120865,"text":"70120865 - 2009 - Online interactive U.S. Reservoir Sedimentation Survey Database","interactions":[],"lastModifiedDate":"2014-08-18T10:27:35","indexId":"70120865","displayToPublicDate":"2013-08-18T10:22:00","publicationYear":"2009","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1578,"text":"Eos, Transactions, American Geophysical Union","onlineIssn":"2324-9250","printIssn":"0096-394","active":true,"publicationSubtype":{"id":10}},"title":"Online interactive U.S. Reservoir Sedimentation Survey Database","docAbstract":"In April 2009, the U.S. Geological Survey and the Natural Resources Conservation Service (prior to 1994, the Soil Conservation Service) created the Reservoir Sedimentation Survey Database (RESSED) and Web site, the most comprehensive compilation of data from reservoir bathymetric and dry basin surveys in the United States. RESSED data can be useful for a number of purposes, including calculating changes in reservoir storage characteristics, quantifying rates of sediment delivery to reservoirs, and estimating erosion rates in a reservoir's watershed.
","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Eos, Transactions American Geophysical Union","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1029/2009EO230003","usgsCitation":"Gray, J., Bernard, J., Schwarz, G., Stewart, D.W., and Ray, K., 2009, Online interactive U.S. Reservoir Sedimentation Survey Database: Eos, Transactions, American Geophysical Union, v. 90, no. 23, https://doi.org/10.1029/2009EO230003.","productDescription":"1 p.","startPage":"199","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":475967,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2009eo230003","text":"Publisher Index Page"},{"id":292389,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":292387,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1029/2009EO230003"}],"country":"Puerto Rico;United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 144.616667,12.233333 ], [ 144.616667,71.833333 ], [ -64.566667,71.833333 ], [ -64.566667,12.233333 ], [ 144.616667,12.233333 ] ] ] } } ] }","volume":"90","issue":"23","noUsgsAuthors":false,"publicationDate":"2011-06-03","publicationStatus":"PW","scienceBaseUri":"53f25fe9e4b033341871893b","contributors":{"authors":[{"text":"Gray, J.B.","contributorId":73119,"corporation":false,"usgs":true,"family":"Gray","given":"J.B.","email":"","affiliations":[],"preferred":false,"id":498503,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bernard, J.M.","contributorId":43999,"corporation":false,"usgs":true,"family":"Bernard","given":"J.M.","email":"","affiliations":[],"preferred":false,"id":498502,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schwarz, G. E. 0000-0002-9239-4566","orcid":"https://orcid.org/0000-0002-9239-4566","contributorId":14852,"corporation":false,"usgs":true,"family":"Schwarz","given":"G. E.","affiliations":[],"preferred":false,"id":498501,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stewart, D. W.","contributorId":86194,"corporation":false,"usgs":true,"family":"Stewart","given":"D.","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":498505,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ray, K.T.","contributorId":77758,"corporation":false,"usgs":true,"family":"Ray","given":"K.T.","email":"","affiliations":[],"preferred":false,"id":498504,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70047288,"text":"70047288 - 2009 - Converting nonstandard fish sampling data to standardized data","interactions":[],"lastModifiedDate":"2021-06-04T16:44:48.968639","indexId":"70047288","displayToPublicDate":"2013-01-01T21:25:04","publicationYear":"2009","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"12","title":"Converting nonstandard fish sampling data to standardized data","docAbstract":"Fishery biologists spend considerable effort over multiple years collecting data on fish population and community status using a particular sampling method or set of methods. However, new (and often more effective) sampling methods and technologies are continuously being developed. To incorporate these new sampling techniques, fishery biologists need a means for converting sample data collected using old methods so they can be compared with data collected using new methods. Similarly, fishery biologists often need a means to compare fish sample data collected using the same method over time (e.g., from year to year) and space (e.g., between sample sites). If fish abundance, species presence, or richness are estimated using an unbiased statistical estimator, the estimates can be validly compared, even if the fish sample data were collected with different methods. However, if unbiased statistical estimators were not used, biologists need methods for adjusting fish sampling data collected using different methods or using the same method collected under different sampling conditions. In this chapter, we describe and provide examples of statistical techniques for converting nonstandard fish sampling data to standardized data and for making comparisons of fish sampling data collected at different times or at different locations. We define standard fish sampling data as data collected using the standardized fish sampling methods described throughout this book. Any other sampling methods and associated data are thus defined as nonstandard. Before delving into the details of the statistical modeling techniques, we describe the nature of fish sample data, their uses, and their limitations.
Catch-effort measures, such as relative abundance and catch per unit effort (CPUE), are more formally described as indices. Here, we define an index as any measure or count of a species or community (e.g., species richness) based on direct observation without an estimate of the ability to count individuals or species. Indices have some very desirable characteristics for use in fisheries research and management. In general (but not always), indices require less effort to collect and are usually more precise than unbiased population estimators (e.g., CPUE versus capture–recapture estimates of abundance). The proper use of indices for assessment of fish populations or communities, however, requires that the relationship between an index and the true value (e.g., fish density, species richness) is relatively constant (1) across the observable range of true values, (2) through time when evaluating trends at a single location, and (3) across space when making comparisons among locations.
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The purpose of this group, which came to be known as the “International Charter - Space and Major Disasters”, is to promote cooperation among space agencies in the use of satellite data to manage crises during and after disasters. When tropical storms, floods, oil spills, earthquakes, landslides, volcanoes or fires endanger human life, the Charter member agencies provide valuable information about these events’ extent and impact.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Photogrammetric Engineering and Remote Sensing","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"ASPRS","usgsCitation":"Stryker, T., and Jones, B., 2009, Disaster response and the international charter program: Photogrammetric Engineering and Remote Sensing, v. 2009, no. 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Disjunct populations of the widespread western toad Anaxyrus boreas from Colorado and southern Wyoming, the southern rocky mountain population (SRMP), were previously candidates for listing under the United States Endangered Species Act (ESA) as a distinct population segment (DPS), but were removed due to a lack of significant genetic differentiation in preliminary studies. The purpose of this study was to conduct phylogeographic and population genetic analyses of A. boreas and three related species using mitochondrial DNA sequence data and nuclear microsatellite genotype data. 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They reference unnamed sources for pre-1997 horseshoe crab harvest to conclude that recent harvest exceeds historic harvest. In fact, reported landings from New Jersey, Delaware, Maryland, and Virginia in 2006 (352 metric tons [mt]) were between landings in 1989 (365 mt) and 1990 (232 mt) (www.st.nmfs.noaa.gov/st1/commercial/inaex.html), despite nonmandatory reporting coastwide before 1998 (Kreamer and Michels 2009). They present egg densities from New Jersey beaches only. Of the 11 Delaware beaches sampled, eggs in the top 5 centimeters exceeded their monitoring target of 50,000 per square meter at 5 in 2006 and at 6 in 2007 (Kalasz et al. 2008). They rely on the Delaware trawl survey for historic trends. 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Commercially available instruments operating on bulk optic (turbidity), laser optic, pressure difference, and acoustic backscatter principles are evaluated based on cost, reliability, robustness, accuracy, sample volume, susceptibility to biological fouling, and suitable range of mass concentration and particle size distribution. In situ turbidimeters are widely used. They provide reliable data where the point measurements can be reliably correlated to the river's mean cross section concentration value, effects of biological fouling can be minimized, and concentrations remain below the sensor's upper measurement limit. In situ laser diffraction instruments have similar limitations and can cost 6 times the approximate $5000 purchase price of a turbidimeter. However, laser diffraction instruments provide volumetric‐concentration data in 32 size classes. Pressure differential instruments measure mass density in a water column, thus integrating substantially more streamflow than a point measurement. They are designed for monitoring medium‐to‐large concentrations, are generally unaffected by biological fouling, and cost about the same as a turbidimeter. However, their performance has been marginal in field applications. Acoustic Doppler profilers use acoustic backscatter to measure suspended sediment concentrations in orders of magnitude more streamflow than do instruments that rely on point measurements. The technology is relatively robust and generally immune to effects of biological fouling. Cost of a single‐frequency device is about double that of a turbidimeter. Multifrequency arrays also provide the potential to resolve concentrations by clay silt versus sand size fractions. Multifrequency hydroacoustics shows the most promise for revolutionizing collection of continuous suspended sediment data by instruments that require only periodic calibration for correlation to mean concentrations in river cross sections. Broad application of proven suspended sediment surrogate technologies has the potential to revolutionize fluvial sediment monitoring. Once applied, benefits could be enormous, providing for safer, more frequent and consistent, arguably more accurate, and ultimately less expensive sediment data for managing the world's sedimentary resources.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2008WR007063","usgsCitation":"Gray, J.R., and Gartner, J.W., 2009, Technological advances in suspended‐sediment surrogate monitoring: Water Resources Research, v. 45, no. 4, Article W00D29; 20 p., https://doi.org/10.1029/2008WR007063.","productDescription":"Article W00D29; 20 p.","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":475975,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2008wr007063","text":"Publisher Index Page"},{"id":257928,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"45","issue":"4","noUsgsAuthors":false,"publicationDate":"2009-03-06","publicationStatus":"PW","scienceBaseUri":"505ba43de4b08c986b3201d2","contributors":{"authors":[{"text":"Gray, John R. 0000-0002-8817-3701 jrgray@usgs.gov","orcid":"https://orcid.org/0000-0002-8817-3701","contributorId":1158,"corporation":false,"usgs":true,"family":"Gray","given":"John","email":"jrgray@usgs.gov","middleInitial":"R.","affiliations":[{"id":5058,"text":"Office of the Chief Scientist for Water","active":true,"usgs":true}],"preferred":true,"id":463463,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gartner, Jeffrey W.","contributorId":77524,"corporation":false,"usgs":true,"family":"Gartner","given":"Jeffrey","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":463464,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70038469,"text":"70038469 - 2009 - The Restoration Rapid Assessment Tool: An Access/Visual Basic application","interactions":[],"lastModifiedDate":"2016-09-21T13:37:40","indexId":"70038469","displayToPublicDate":"2012-06-14T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"title":"The Restoration Rapid Assessment Tool: An Access/Visual Basic application","docAbstract":"Managers of parks and natural areas are increasingly faced with difficult decisions concerning restoration of disturbed lands. Financial and workforce resources often limit these restoration efforts, and rarely can a manager afford to address all concerns within the region of interest. With limited resources, managers and scientists have to decide which areas will be targeted for restoration and the restoration treatments to use in these areas. A broad range of approaches are used to make such decisions, from well-researched expert opinions (Cipollini et al. 2005) to gut feeling, with variable degrees of input from site visits, data collection, and data analysis used to support the decision. A standardized approach including an analytical assessment of site characteristics based on the best information available, with a written or electronic record of all the steps taken along the way, would make comparisons among a group of sites easier and lend credibility through use of common, documented criteria at all sites. In response to these concerns, we have developed the Restoration Rapid Assessment Tool (RRAT). RRAT is based on field observations of key indicators of site degradation, stressors influencing the site, value of the site with respect to larger management objectives, likelihood of achieving the management goals, and logistical constraints to restoration. The purpose of RRAT is not to make restoration decisions or prescribe methods, but rather to ensure that a basic set of pertinent issues are considered for each site and to facilitate comparisons among sites. Several concepts have been central to the development of RRAT. First, the management goal (also known as desired future condition) of any site under evaluation should be defined before the field evaluation begins. Second, the evaluation should be based upon readily observable indicators so as to avoid cumbersome field methods. Third, the ease with which site stressors can be ameliorated must be factored into the evaluation. Fourth, intrinsic site value must be assessed independently of current condition. Finally, logistical considerations must also be addressed. Our initial focus has been on riparian areas because they are among the most heavily impacted habitat types, and RRAT indicators reflect this focus.","language":"English","publisher":"National Park Service","publisherLocation":"Washington, D.C.","usgsCitation":"Hiebert, R., Larson, D., Thomas, K., Tancreto, N., Haines, D., Richey, A., Dow, T., and Drees, L., 2009, The Restoration Rapid Assessment Tool: An Access/Visual Basic application, Users Manual and computer software application.","productDescription":"Users Manual and computer software application","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":257603,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505ba8b8e4b08c986b321de6","contributors":{"authors":[{"text":"Hiebert, Ron","contributorId":52021,"corporation":false,"usgs":true,"family":"Hiebert","given":"Ron","email":"","affiliations":[],"preferred":false,"id":464311,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Larson, D.L. 0000-0001-5202-0634","orcid":"https://orcid.org/0000-0001-5202-0634","contributorId":69501,"corporation":false,"usgs":true,"family":"Larson","given":"D.L.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":464312,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thomas, K.","contributorId":37962,"corporation":false,"usgs":true,"family":"Thomas","given":"K.","email":"","affiliations":[],"preferred":false,"id":464309,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tancreto, N.","contributorId":91729,"corporation":false,"usgs":true,"family":"Tancreto","given":"N.","affiliations":[],"preferred":false,"id":464314,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Haines, D.","contributorId":30424,"corporation":false,"usgs":true,"family":"Haines","given":"D.","email":"","affiliations":[],"preferred":false,"id":464308,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Richey, A.","contributorId":45947,"corporation":false,"usgs":true,"family":"Richey","given":"A.","email":"","affiliations":[],"preferred":false,"id":464310,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dow, T.","contributorId":17868,"corporation":false,"usgs":true,"family":"Dow","given":"T.","email":"","affiliations":[],"preferred":false,"id":464307,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Drees, L.","contributorId":73050,"corporation":false,"usgs":true,"family":"Drees","given":"L.","email":"","affiliations":[],"preferred":false,"id":464313,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70003362,"text":"70003362 - 2009 - Investigating hydraulic connections and the origin of water in a mine tunnel using stable isotopes and hydrographs","interactions":[],"lastModifiedDate":"2021-03-25T18:36:07.567184","indexId":"70003362","displayToPublicDate":"2012-05-27T11:42:00","publicationYear":"2009","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":835,"text":"Applied Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Investigating hydraulic connections and the origin of water in a mine tunnel using stable isotopes and hydrographs","docAbstract":"Turquoise Lake is a water-supply reservoir located north of the historic Sugarloaf Mining district near Leadville, Colorado, USA. Elevated water levels in the reservoir may increase flow of low-quality water from abandoned mine tunnels in the Sugarloaf District and degrade water quality downstream. The objective of this study was to understand the sources of water to Dinero mine drainage tunnel and evaluate whether or not there was a direct hydrologic connection between Dinero mine tunnel and Turquoise Lake from late 2002 to early 2008. This study utilized hydrograph data from nearby draining mine tunnels and the lake, and stable isotope (δ18O and δ2H) data from the lake, nearby draining mine tunnels, imported water, and springs to characterize water sources in the study area. Hydrograph results indicate that flow from the Dinero mine tunnel decreased 26% (2006) and 10% (2007) when lake elevation (above mean sea level) decreased below approximately 3004 m (approximately 9855 feet). Results of isotope analysis delineated two meteoric water lines in the study area. One line characterizes surface water and water imported to the study area from the western side of the Continental Divide. The other line characterizes groundwater including draining mine tunnels, springs, and seeps. Isotope mixing calculations indicate that water from Turquoise Lake or seasonal groundwater recharge from snowmelt represents approximately 10% or less of the water in Dinero mine tunnel. However, most of the water in Dinero mine tunnel is from deep groundwater having minimal isotopic variation. The asymmetric shape of the Dinero mine tunnel hydrograph may indicate that a limited mine pool exists behind a collapse in the tunnel and attenutates seasonal recharge. Alternatively, a conceptual model is presented (and supported with MODFLOW simulations) that is consistent with current and previous data collected in the study area, and illustrates how fluctuating lake levels change the local water-table elevation which can affect discharge from the Dinero mine tunnel without physical transfer of water between the two locations.","language":"English","publisher":"Elsevier","doi":"10.1016/j.apgeochem.2009.09.015","usgsCitation":"Walton-Day, K., and Poeter, E., 2009, Investigating hydraulic connections and the origin of water in a mine tunnel using stable isotopes and hydrographs: Applied Geochemistry, v. 24, no. 12, p. 2266-2282, https://doi.org/10.1016/j.apgeochem.2009.09.015.","productDescription":"17 p.","startPage":"2266","endPage":"2282","temporalStart":"2002-01-01","temporalEnd":"2008-12-31","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":257154,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","city":"Leadville","otherGeospatial":"Turquoise Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.4688491821289,\n 39.19581074223468\n ],\n [\n -106.28929138183594,\n 39.19581074223468\n ],\n [\n -106.28929138183594,\n 39.313581716526485\n ],\n [\n -106.4688491821289,\n 39.313581716526485\n ],\n [\n -106.4688491821289,\n 39.19581074223468\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"24","issue":"12","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a3e68e4b0c8380cd63d63","contributors":{"authors":[{"text":"Walton-Day, Katherine 0000-0002-9146-6193","orcid":"https://orcid.org/0000-0002-9146-6193","contributorId":68339,"corporation":false,"usgs":true,"family":"Walton-Day","given":"Katherine","affiliations":[],"preferred":false,"id":347022,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Poeter, Eileen","contributorId":24616,"corporation":false,"usgs":true,"family":"Poeter","given":"Eileen","affiliations":[],"preferred":false,"id":347021,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70007546,"text":"70007546 - 2009 - Historical range, current distribution, and conservation status of the Swift Fox, Vulpes velox, in North America","interactions":[],"lastModifiedDate":"2013-04-05T10:44:09","indexId":"70007546","displayToPublicDate":"2012-05-27T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1163,"text":"Canadian Field-Naturalist","active":true,"publicationSubtype":{"id":10}},"title":"Historical range, current distribution, and conservation status of the Swift Fox, Vulpes velox, in North America","docAbstract":"The Swift Fox (Vulpes velox) was once common in the shortgrass and mixed-grass prairies of the Great Plains of North America. The species' abundance declined and its distribution retracted following European settlement of the plains. By the late 1800s, the species had been largely extirpated from the northern portion of its historical range, and its populations were acutely depleted elsewhere. Swift Fox populations have naturally recovered somewhat since the 1950s, but overall abundance and distribution remain below historical levels. In a 1995 assessment of the species' status under the US Endangered Species Act, the US Fish and Wildlife Service concluded that a designation of threatened or endangered was warranted, but the species was \"precluded from listing by higher listing priorities.\" A major revelation of the 1995 assessment was the recognition that information useful for determining population status was limited. Fundamental information was missing, including an accurate estimate of the species' distribution before European settlement and an estimate of the species' current distribution and trends. The objectives of this paper are to fill those gaps in knowledge. Historical records were compiled and, in combination with knowledge of the habitat requirements of the species, the historical range of the Swift Fox is estimated to be approximately 1.5 million km2. Using data collected between 2001 and 2006, the species' current distribution is estimated to be about 44% of its historical range in the United States and 3% in Canada. Under current land use, approximately 39% of the species' historical range contains grassland habitats with very good potential for Swift Fox occupation and another 10% supports grasslands with characteristics that are less preferred (e.g., a sparse shrub component or taller stature) but still suitable. Additionally, land use on at least 25% of the historical range supports dryland farming, which can be suitable for Swift Fox occupation. In the United States, approximately 52% of highest quality habitats currently available are occupied by Swift Foxes.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Canadian Field-Naturalist","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"The Canadian Field-Naturalist","publisherLocation":"Ottawa, Ontario, Canada","usgsCitation":"Sovada, M.A., Woodward, R.O., and Igl, L.D., 2009, Historical range, current distribution, and conservation status of the Swift Fox, Vulpes velox, in North America: Canadian Field-Naturalist, v. 123, no. 4, p. 346-367.","productDescription":"22 p.","startPage":"346","endPage":"367","numberOfPages":"2","temporalStart":"2001-01-01","temporalEnd":"2006-12-31","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":257181,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":257166,"rank":200,"type":{"id":11,"text":"Document"},"url":"https://www.canadianfieldnaturalist.ca/index.php/cfn/article/viewArticle/1004","linkFileType":{"id":5,"text":"html"}}],"country":"United States","volume":"123","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a3199e4b0c8380cd5e06a","contributors":{"authors":[{"text":"Sovada, Marsha A. msovada@usgs.gov","contributorId":2601,"corporation":false,"usgs":true,"family":"Sovada","given":"Marsha","email":"msovada@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":356655,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Woodward, Robert O. rwoodward@usgs.gov","contributorId":4259,"corporation":false,"usgs":true,"family":"Woodward","given":"Robert","email":"rwoodward@usgs.gov","middleInitial":"O.","affiliations":[],"preferred":true,"id":356656,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Igl, Lawrence D. 0000-0003-0530-7266 ligl@usgs.gov","orcid":"https://orcid.org/0000-0003-0530-7266","contributorId":2381,"corporation":false,"usgs":true,"family":"Igl","given":"Lawrence","email":"ligl@usgs.gov","middleInitial":"D.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":356654,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70038409,"text":"fs20093003 - 2009 - Streamflow of 2008--Water year summary","interactions":[],"lastModifiedDate":"2012-05-26T01:01:37","indexId":"fs20093003","displayToPublicDate":"2012-05-22T00:00:00","publicationYear":"2009","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":"2009-3003","title":"Streamflow of 2008--Water year summary","docAbstract":"The maps and graphs appearing in this summary describe streamflow conditions for water-year 2008 (October 1, 2007 to September 30, 2008) in the context of the 79-year period 1930-2008, unless otherwise noted. The illustrations are based on observed data from the U.S. Geological Survey's (USGS) National Streamflow Information Program. The period 1930-2008 was used because prior to 1930, the number of streamgages was too small to provide representative data for computing statistics for most regions of the country.\r\nIn the summary, reference is made to the term \"runoff,\" which is the depth to which a river basin, State, or other geographic area would be covered with water if all the streamflow within the area during a single year was uniformly distributed upon it. Runoff quantifies the magnitude of water flowing through the Nation's rivers and streams in measurement units that can be compared from one area to another. The runoff value for a geographic area is computed as the median runoff value for all streamgages in that geographic area. For example, the runoff value for a State is the median for all streamgages in that State, and the median for the Nation is the median value for all streamgages in the Nation.\r\nEach of the maps and graphs below can be expanded to a larger view by clicking on the image. In all the graphics, a rank of 1 indicates the highest flow of all years analyzed.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20093003","usgsCitation":"Xiaodong, J., Wolock, D.M., Lins, H.F., and Brady, S., 2009, Streamflow of 2008--Water year summary: U.S. Geological Survey Fact Sheet 2009-3003, 8 p., https://doi.org/10.3133/fs20093003.","productDescription":"8 p.","onlineOnly":"Y","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":256942,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs_2009_3003.gif"},{"id":256937,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2009/3003/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505b9b11e4b08c986b31cc6c","contributors":{"authors":[{"text":"Xiaodong, Jian","contributorId":10260,"corporation":false,"usgs":true,"family":"Xiaodong","given":"Jian","email":"","affiliations":[],"preferred":false,"id":464054,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wolock, David M. 0000-0002-6209-938X dwolock@usgs.gov","orcid":"https://orcid.org/0000-0002-6209-938X","contributorId":540,"corporation":false,"usgs":true,"family":"Wolock","given":"David","email":"dwolock@usgs.gov","middleInitial":"M.","affiliations":[{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":464052,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lins, Harry F. 0000-0001-5385-9247 hlins@usgs.gov","orcid":"https://orcid.org/0000-0001-5385-9247","contributorId":1505,"corporation":false,"usgs":true,"family":"Lins","given":"Harry","email":"hlins@usgs.gov","middleInitial":"F.","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":true,"id":464053,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brady, Steve","contributorId":108351,"corporation":false,"usgs":true,"family":"Brady","given":"Steve","email":"","affiliations":[],"preferred":false,"id":464055,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70003417,"text":"70003417 - 2009 - Estuarine water quality in parks of the Northeast Coastal and Barrier Network: Development and early implementation of vital signs estuarine nutrient-enrichment monitoring, 2003-06","interactions":[],"lastModifiedDate":"2012-05-29T01:01:35","indexId":"70003417","displayToPublicDate":"2012-05-20T09:40:00","publicationYear":"2009","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2828,"text":"Natural Resource Technical Report","active":true,"publicationSubtype":{"id":10}},"title":"Estuarine water quality in parks of the Northeast Coastal and Barrier Network: Development and early implementation of vital signs estuarine nutrient-enrichment monitoring, 2003-06","docAbstract":"This report documents results of pilot tests of a protocol for monitoring estuarine nutrient enrichment for the Vital Signs Monitoring Program of the National Park Service Northeast Coastal and Barrier Network. Data collected from four parks during protocol development in 2003-06 are presented: Gateway National Recreation Area, Colonial National Historic Park, Fire Island National Seashore, and Assateague Island National Seashore. The monitoring approach incorporates several spatial and temporal designs to address questions at a hierarchy of scales. Indicators of estuarine response to nutrient enrichment were sampled using a probability design within park estuaries during a late-summer index period. Monitoring variables consisted of dissolved-oxygen concentration, chlorophyll a concentration, water temperature, salinity, attenuation of downwelling photosynthetically available radiation (PAR), and turbidity. The statistical sampling design allowed the condition of unsampled locations to be inferred from the distribution of data from a set of randomly positioned \"probability\" stations. A subset of sampling stations was sampled repeatedly during the index period, and stations were not rerandomized in subsequent years. These \"trend stations\" allowed us to examine temporal variability within the index period, and to improve the sensitivity of the monitoring protocol to detecting change through time. Additionally, one index site in each park was equipped for continuous monitoring throughout the index period. Thus, the protocol includes elements of probabilistic and targeted spatial sampling, and the temporal intensity ranges from snapshot assessments to continuous monitoring.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Natural Resource Technical Report","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"National Park Service","usgsCitation":"Kopp, B.S., Nielsen, M., Glisic, D., and Neckles, H.A., 2009, Estuarine water quality in parks of the Northeast Coastal and Barrier Network: Development and early implementation of vital signs estuarine nutrient-enrichment monitoring, 2003-06: Natural Resource Technical Report, v. 266.","numberOfPages":"135","temporalStart":"2003-01-01","temporalEnd":"2006-12-31","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":256980,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":21686,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://www.nps.gov/nero/science/FINAL/NCBN_water_quality.html","linkFileType":{"id":5,"text":"html"}}],"country":"United States","volume":"266","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a0bc5e4b0c8380cd52881","contributors":{"authors":[{"text":"Kopp, Blaine S.","contributorId":99648,"corporation":false,"usgs":true,"family":"Kopp","given":"Blaine","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":347223,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nielsen, Martha","contributorId":19415,"corporation":false,"usgs":true,"family":"Nielsen","given":"Martha","affiliations":[],"preferred":false,"id":347221,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Glisic, Dejan","contributorId":93742,"corporation":false,"usgs":true,"family":"Glisic","given":"Dejan","email":"","affiliations":[],"preferred":false,"id":347222,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Neckles, Hilary A. 0000-0002-5662-2314 hneckles@usgs.gov","orcid":"https://orcid.org/0000-0002-5662-2314","contributorId":3821,"corporation":false,"usgs":true,"family":"Neckles","given":"Hilary","email":"hneckles@usgs.gov","middleInitial":"A.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":347220,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70037798,"text":"70037798 - 2009 - Problems with the claim of ecotype and taxon status of the wolf in the Great Lakes region","interactions":[],"lastModifiedDate":"2017-09-15T09:46:18","indexId":"70037798","displayToPublicDate":"2012-03-18T14:27:00","publicationYear":"2009","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2774,"text":"Molecular Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Problems with the claim of ecotype and taxon status of the wolf in the Great Lakes region","docAbstract":"Koblmuller et al. (2009) analysed molecular genetic data of the wolf in the Great Lakes (GL) region of the USA and concluded that the animal was a unique ecotype of grey wolf and that genetic data supported the population as a discrete wolf taxon. However, some of the literature that the researchers used to support their position actually did not, and additional confusion arises from indefinite use of terminology. Herein, we discuss the problems with designation of a wolf population as a taxon or ecotype without proper definition and assessment of criteria.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Molecular Ecology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Blackwell Publishing","publisherLocation":"Malden, MA","doi":"10.1111/j.1365-294X.2009.04431.x","usgsCitation":"Cronin, M.A., and Mech, L.D., 2009, Problems with the claim of ecotype and taxon status of the wolf in the Great Lakes region: Molecular Ecology, v. 18, no. 24, p. 4991-4993, https://doi.org/10.1111/j.1365-294X.2009.04431.x.","productDescription":"3 p.","startPage":"4991","endPage":"4993","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":475976,"rank":101,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/j.1365-294x.2009.04431.x","text":"Publisher Index Page"},{"id":246836,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":246828,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://dx.doi.org/10.1111/j.1365-294X.2009.04431.x","linkFileType":{"id":5,"text":"html"}}],"country":"United States","otherGeospatial":"Great Lakes Region","volume":"18","issue":"24","noUsgsAuthors":false,"publicationDate":"2009-12-16","publicationStatus":"PW","scienceBaseUri":"505a8cebe4b0c8380cd7e972","contributors":{"authors":[{"text":"Cronin, Matthew A.","contributorId":57307,"corporation":false,"usgs":false,"family":"Cronin","given":"Matthew","email":"","middleInitial":"A.","affiliations":[{"id":7211,"text":"University of Alaska, Fairbanks","active":true,"usgs":false},{"id":28157,"text":"LGL Alaska Research Associates, Anchorage, AK","active":true,"usgs":false}],"preferred":false,"id":462746,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mech, L. David 0000-0003-3944-7769 david_mech@usgs.gov","orcid":"https://orcid.org/0000-0003-3944-7769","contributorId":2518,"corporation":false,"usgs":true,"family":"Mech","given":"L.","email":"david_mech@usgs.gov","middleInitial":"David","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":462745,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ]}