In 1998, the U.S. Geological Survey, in cooperation with the Sweetwater Authority, began a study to assess the overall health of the Sweetwater watershed in San Diego County, California. This study was designed to provide a data set that could be used to evaluate potential effects from the construction and operation of State Route 125 within the broader context of the water quality and air quality in the watershed. The study included regular sampling of water, air, and surficial bed sediment at Sweetwater Reservoir (SWR) for chemical constituents, including volatile organic compounds (VOCs), base-neutral and acid- extractable organic compounds (BNAs) that include polycyclic aromatic hydrocarbons (PAHs), pesticides, and metals. Additionally, water samples were collected for anthropogenic organic indicator compounds in and around SWR. Background water samples were collected at Loveland Reservoir for VOCs, BNAs, pesticides, and metals. Surficial bed-sediment samples were collected for PAHs, organochlorine pesticides, and metals at Sweetwater and Loveland Reservoirs.
\nTo monitor changes in contaminant concentration in water and air at SWR during the construction and operation of State Route 125, this study was divided into three phases. Phase One sampling (September 1998 to September 2004) was designed to establish baseline conditions for target compounds in terms of detection frequency and concentration in air and water. Phase Two (October 2004 to September 2007) continued sampling at selected monitoring sites during construction of State Route 125 to assess any effect from the construction process and the use of heavy equipment to build the roadway. Phase Three (October 2007 to August 2009) continued sampling for 2 years after the opening of State Route 125 to assess the potential changes in water quality related to vehicle emissions from the roadway alignment. Surficial bed-sediment samples were collected three times during the study—at the beginning of the study, at the start of Phase Two, and at the end of the study.
\nThis report describes the study design and the sampling and analytical methods and presents data from water, air, and surficial bed-sediment samples collected from the sixth to eleventh years of the study (October 2003–August 2009), spanning the last year of Phase one and all of Phases Two and Three. Data collected during the first 5 years of sampling have been previously published.
\nThree types of quality-control samples were used in this study—matrix spikes, blanks, and replicates. Matrix-spike data are considered to be adequate if the recovery concentration is within 30 percent of the matrix concentration. Replicate data are considered to be adequate if the replicate sample concentration is within 30 percent of the environmental sample concentration. Additionally, surrogate compounds were added to most samples to monitor sample-specific performance of the analytical method.
\nMost VOC matrix-spike recovery data associated with water samples are within acceptable criteria, but three VOCs had recoveries below the acceptable criteria; these compounds may not have been detected in water samples if they were present at low concentrations. Data for blanks associated with water samples for VOCs and metals showed no detections above their laboratory reporting levels. Most replicate data are within acceptable criteria. Quality-control data for VOC air samples resulted in flagging several reported concentrations for acetone, benzene, ethenylbenzene, and naphthalene because they may be biased high. Acetone, benzene, and toluene were detected at low concentrations in almost every VOC air blank. Some PAH and pesticide concentrations in air samples were designated as estimated because of method performance limitations. PAHs in surficial bed sediment had 83 percent of surrogates below the acceptable criteria. No matrix-spike data for metals in surficial bed sediment were outside the acceptable criteria; only beryllium had a replicate comparison outside the acceptable criteria.
\nSampling results show concentrations of the gasoline oxygenate methyl tert-butyl ether in water and air samples declined after it was phased out by the State of California in January 2004. The largest concentrations of gasoline hydrocarbons benzene and toluene in water were detected at or near the surface of the SWR. Isophorone and phenol were the two most frequently detected BNA compounds in water. Diuron, prometon, and simazine were the most frequently detected pesticide compounds in water. Concentrations of benzene and toluene in air samples were highest during the cooler months and had a consistent seasonal pattern over time. Ten PAH compounds were detected frequently in air samples. Twelve pesticide compounds were also detected in air samples. Surficial bed-sediment samples were analyzed for 53 PAHs; 22 of the compounds had one or more detections. Surficial bed-sediment samples were analyzed for 22 organic compounds; only 6 compounds had one or more detections. Surficial bed-sediment samples were analyzed for 37 metals.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds879","collaboration":"Prepared in cooperation with the Sweetwater Authority","usgsCitation":"Mendez, G.O., Majewski, M.S., Foreman, W., and Morita, A.Y., 2015, Water- and air-quality and surficial bed-sediment monitoring of the Sweetwater Reservoir watershed, San Diego County, California, 2003-09: U.S. Geological Survey Data Series 879, Report: xi, 226 p.; 5 Tables, https://doi.org/10.3133/ds879.","productDescription":"Report: xi, 226 p.; 5 Tables","numberOfPages":"242","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2003-01-01","temporalEnd":"2009-12-31","ipdsId":"IP-002295","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":297815,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds879.jpg"},{"id":297808,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0879/"},{"id":297809,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0879/pdf/ds879.pdf","size":"6.2 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":297810,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/0879/downloads/ds879_table4b_voc.xls","text":"Table 4B","size":"174 kB","linkFileType":{"id":3,"text":"xlsx"}},{"id":297811,"rank":4,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/0879/downloads/ds879_table5b_bna.xls","text":"Table 5B","size":"82 kB","linkFileType":{"id":3,"text":"xlsx"}},{"id":297812,"rank":5,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/0879/downloads/ds879_table10b_avoc.xls","text":"Table 10B","size":"240 kB","linkFileType":{"id":3,"text":"xlsx"}},{"id":297813,"rank":6,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/0879/downloads/ds879_table11b_pah.xls","text":"Table 11B","size":"313 kB","linkFileType":{"id":3,"text":"xlsx"}},{"id":297814,"rank":7,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/0879/downloads/ds879_table13_airtm.xls","text":"Table 13","size":"124 kB","linkFileType":{"id":3,"text":"xlsx"}}],"scale":"100000","projection":"Universal Transverse Mercator projection","country":"United States","state":"California","county":"San Diego County","otherGeospatial":"Sweetwater Reservoir watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.1142578125,\n 32.58963484306727\n ],\n [\n -117.1142578125,\n 32.99945000822839\n ],\n [\n -116.46606445312499,\n 32.99945000822839\n ],\n [\n -116.46606445312499,\n 32.58963484306727\n ],\n [\n -117.1142578125,\n 32.58963484306727\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2acde4b08de9379b3214","contributors":{"authors":[{"text":"Mendez, Gregory O. 0000-0002-9955-3726 gomendez@usgs.gov","orcid":"https://orcid.org/0000-0002-9955-3726","contributorId":1489,"corporation":false,"usgs":true,"family":"Mendez","given":"Gregory","email":"gomendez@usgs.gov","middleInitial":"O.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":540012,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Majewski, Michael S. majewski@usgs.gov","contributorId":440,"corporation":false,"usgs":true,"family":"Majewski","given":"Michael","email":"majewski@usgs.gov","middleInitial":"S.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":540013,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Foreman, William T. wforeman@usgs.gov","contributorId":1473,"corporation":false,"usgs":true,"family":"Foreman","given":"William T.","email":"wforeman@usgs.gov","affiliations":[{"id":452,"text":"National Water Quality Laboratory","active":true,"usgs":true}],"preferred":false,"id":540014,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Morita, Andrew Y. 0000-0002-8120-996X amorita@usgs.gov","orcid":"https://orcid.org/0000-0002-8120-996X","contributorId":1487,"corporation":false,"usgs":true,"family":"Morita","given":"Andrew","email":"amorita@usgs.gov","middleInitial":"Y.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":540015,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70134473,"text":"sir20145220 - 2015 - Estimation of unaltered daily mean streamflow at ungaged streams of New York, excluding Long Island, water years 1961-2010","interactions":[],"lastModifiedDate":"2015-02-06T12:59:44","indexId":"sir20145220","displayToPublicDate":"2015-02-06T13:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-5220","title":"Estimation of unaltered daily mean streamflow at ungaged streams of New York, excluding Long Island, water years 1961-2010","docAbstract":"The lakes, rivers, and streams of New York State provide an essential water resource for the State. The information provided by time series hydrologic data is essential to understanding ways to promote healthy instream ecology and to strengthen the scientific basis for sound water management decision making in New York. The U.S. Geological Survey, in cooperation with The Nature Conservancy and the New York State Energy Research and Development Authority, has developed the New York Streamflow Estimation Tool to estimate a daily mean hydrograph for the period from October 1, 1960, to September 30, 2010, at ungaged locations across the State. The New York Streamflow Estimation Tool produces a complete estimated daily mean time series from which daily flow statistics can be estimated. In addition, the New York Streamflow Estimation Tool provides a means for quantitative flow assessments at ungaged locations that can be used to address the objectives of the Clean Water Act—to restore and maintain the chemical, physical, and biological integrity of the Nation’s waters.
\nThe New York Streamflow Estimation Tool uses data from the U.S. Geological Survey streamflow network for selected streamgages in New York (excluding Long Island) and surrounding States with shared hydrologic boundaries, and physical and climate basin characteristics to estimate the natural unaltered streamflow at ungaged stream locations. The unaltered streamflow is representative of flows that are minimally altered by regulation, diversion, or mining, and other anthropogenic activities. With the streamflow network data, flow-duration exceedance probability equations were developed to estimate unaltered streamflow exceedance probabilities at an ungaged location using a methodology that equates streamflow as a percentile from a flow-duration curve for a particular day at a hydrologically similar reference streamgage with streamflow as a percentile from the flow-duration curve for the same day at an ungaged location. The reference streamgage is selected using map correlation, a geostatistical method in which variogram models are developed that correlate streamflow at one streamgage with streamflows at all other locations in the study area. Regression equations used to predict 17 flow-duration exceedance probabilities were developed to estimate the flow-duration curves at ungaged locations for New York using geographic information system-derived basin characteristics.
\nA graphical user interface, with an integrated spreadsheet summary report, has been developed to estimate and display the daily mean streamflows and statistics and to evaluate different water management or water withdrawal scenarios with the estimated monthly data. This package of regression equations, U.S. Geological Survey streamgage data, and spreadsheet application produces an interactive tool to estimate an unaltered daily streamflow hydrograph and streamflow statistics at ungaged sites in New York. Among other uses, the New York Streamflow Estimation Tool can assist water managers with permitting water withdrawals, implementing habitat protection, estimating contaminant loads, or determining the potential affect from chemical spills.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145220","collaboration":"Prepared in cooperation with The Nature Conservancy and the New York State Energy Research and Development Authority","usgsCitation":"Gazoorian, C.L., 2015, Estimation of unaltered daily mean streamflow at ungaged streams of New York, excluding Long Island, water years 1961-2010: U.S. Geological Survey Scientific Investigations Report 2014-5220, Report: viii, 29 p.; Readme; 5 Appendixes; NYSET application, https://doi.org/10.3133/sir20145220.","productDescription":"Report: viii, 29 p.; Readme; 5 Appendixes; NYSET application","numberOfPages":"42","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"1960-10-01","temporalEnd":"2010-09-30","ipdsId":"IP-055442","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":297799,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145220.jpg"},{"id":297792,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5220/"},{"id":297793,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5220/pdf/sir2014-5220.pdf"},{"id":297794,"rank":3,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sir/2014/5220/attachments/sir2014-5220_readme.pdf","text":"Readme Appendix 1-5","size":"58 kB","linkFileType":{"id":1,"text":"pdf"}},{"id":297795,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5220/attachments/sir2014-5220_app1-4.pdf","text":"Appendix 1-4 PDF","size":"308 kB","linkFileType":{"id":1,"text":"pdf"}},{"id":297796,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5220/attachments/sir2014-5220_app1-4.xlsx","text":"Appendix 1-4 XLS","size":"75 kB","linkFileType":{"id":3,"text":"xlsx"}},{"id":297797,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5220/attachments/SIR2014-5220_app5.pdf","text":"Appendix 5","size":"696 kB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"User’s Guide for the New York Streamflow Estimation Tool (NYSET) version 1.0"},{"id":297798,"rank":7,"type":{"id":7,"text":"Companion Files"},"url":"https://ny.water.usgs.gov/projects/nyset/","text":"NYSET application","linkFileType":{"id":5,"text":"html"}}],"scale":"200000","projection":"Universal Transverse Mercator projection","datum":"North American Datum of 1983","country":"United States","state":"New York","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -79.771728515625,\n 42.27730877423709\n ],\n [\n -79.7607421875,\n 42.00032514831621\n ],\n [\n -75.35522460937499,\n 42.00032514831621\n ],\n [\n -75.003662109375,\n 41.46742831254425\n ],\n [\n -73.773193359375,\n 40.863679665481676\n ],\n [\n -73.487548828125,\n 41.054501963290505\n ],\n [\n -73.2568359375,\n 42.779275360241904\n ],\n [\n -73.223876953125,\n 45.01141864227728\n ],\n [\n -75.003662109375,\n 45.034714778688624\n ],\n [\n -76.5966796875,\n 44.166444664458595\n ],\n [\n -76.201171875,\n 43.58834891179792\n ],\n [\n -79.068603515625,\n 43.29320031385282\n ],\n [\n -79.771728515625,\n 42.27730877423709\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2a74e4b08de9379b3070","contributors":{"authors":[{"text":"Gazoorian, Christopher L. 0000-0002-5408-6212 cgazoori@usgs.gov","orcid":"https://orcid.org/0000-0002-5408-6212","contributorId":2929,"corporation":false,"usgs":true,"family":"Gazoorian","given":"Christopher","email":"cgazoori@usgs.gov","middleInitial":"L.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":525962,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70138830,"text":"ofr20151012 - 2015 - Simulations of a hypothetical temperature control structure at Detroit Dam on the North Santiam River, northwestern Oregon","interactions":[],"lastModifiedDate":"2015-02-06T13:46:26","indexId":"ofr20151012","displayToPublicDate":"2015-02-06T13:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-1012","title":"Simulations of a hypothetical temperature control structure at Detroit Dam on the North Santiam River, northwestern Oregon","docAbstract":"Water temperature models of Detroit Lake, Big Cliff Lake, and the North Santiam River in northwestern Oregon were used to assess the potential for a hypothetical structure with variable intake elevations and an internal connection to power turbines at Detroit Dam (scenario SlidingWeir) to release more natural, pre-dam temperatures year round. This hypothetical structure improved outflow temperature control from Detroit Dam while meeting minimum dry-season release rates and lake levels specified by the rule curve specified for Detroit Lake.
\nA water temperature target based on long-term, without-dams temperature estimates was developed and used to guide the Detroit Lake model to blend releases from the user-defined outlets at Detroit Dam. Simulations that included warm surface water releases during the spring and summer, and cool, deep hypolimnetic water releases later during autumn typically met the temperature target. Immediately downstream of Detroit Dam, these simulations resulted in temperatures within the range of the without-dams temperature estimates for most of the year until about November. The minimum release rates of flow imposed at Detroit Dam during late summer and early autumn exceeded unregulated, without-dams flow estimates. This higher flow led to temperatures near the low end of the without-dams temperature range 46.3 river miles downstream at Greens Bridge from July to September; the high flows released from Detroit Dam were less susceptible to downstream warming than the low unregulated flows. Simulations that blended warm and cool water from different outlets at Detroit Dam resulted in less daily temperature variation compared to the without-dams scenarios as far downstream as Greens Bridge.
\nEstimated egg-emergence days for endangered Upper Willamette River Chinook salmon (Oncorhynchus tshawytscha) and Upper Willamette River winter steelhead (Oncorhynchus mykiss) were assessed for all scenarios. Estimated spring Chinook fry emergence under SlidingWeir scenarios was 9 days later immediately downstream of Big Cliff Dam, and 4 days later at Greens Bridge compared with existing structural scenarios at Detroit Dam. Despite the inclusion of a hypothetical sliding weir at Detroit Dam, temperatures exceeded without-dams temperatures during November and December. These late-autumn exceedances likely represent the residual thermal effect of Detroit Lake operated to meet minimum dry-season release rates (supporting instream habitat and irrigation requirements) and lake levels specified by the current (2014) operating rules (supporting recreation and flood mitigation).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151012","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Buccola, N.L., Stonewall, A.J., and Rounds, S.A., 2015, Simulations of a hypothetical temperature control structure at Detroit Dam on the North Santiam River, northwestern Oregon: U.S. Geological Survey Open-File Report 2015-1012, vi, 30 p., https://doi.org/10.3133/ofr20151012.","productDescription":"vi, 30 p.","numberOfPages":"40","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-057390","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":297807,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20151012.JPG"},{"id":297805,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2015/1012/"},{"id":297806,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1012/pdf/ofr2015-1012.pdf","text":"Report","size":"4.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"projection":"Universal Transverse Mercator projection, Zone 10","datum":"North American Datum of 1927","country":"United States","state":"Oregon","otherGeospatial":"Big Cliff Lake, Detroit Lake, North Santiam River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.20068359374999,\n 44.469071224701096\n ],\n [\n -123.20068359374999,\n 44.912304304581525\n ],\n [\n -121.77246093750001,\n 44.912304304581525\n ],\n [\n -121.77246093750001,\n 44.469071224701096\n ],\n [\n -123.20068359374999,\n 44.469071224701096\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2ab4e4b08de9379b3194","contributors":{"authors":[{"text":"Buccola, Norman L. nbuccola@usgs.gov","contributorId":139094,"corporation":false,"usgs":true,"family":"Buccola","given":"Norman","email":"nbuccola@usgs.gov","middleInitial":"L.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":false,"id":539999,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stonewall, Adam J. 0000-0002-3277-8736 stonewal@usgs.gov","orcid":"https://orcid.org/0000-0002-3277-8736","contributorId":138801,"corporation":false,"usgs":true,"family":"Stonewall","given":"Adam","email":"stonewal@usgs.gov","middleInitial":"J.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":false,"id":540000,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rounds, Stewart A. 0000-0002-8540-2206 sarounds@usgs.gov","orcid":"https://orcid.org/0000-0002-8540-2206","contributorId":905,"corporation":false,"usgs":true,"family":"Rounds","given":"Stewart","email":"sarounds@usgs.gov","middleInitial":"A.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":540001,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70140094,"text":"70140094 - 2015 - Mineral commodity summaries 2015","interactions":[],"lastModifiedDate":"2015-02-09T14:21:20","indexId":"70140094","displayToPublicDate":"2015-02-06T13:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":6,"text":"USGS Unnumbered Series"},"seriesTitle":{"id":323,"text":"Mineral Commodity Summaries","code":"MCS","active":true,"publicationSubtype":{"id":5}},"title":"Mineral commodity summaries 2015","docAbstract":"Each chapter of the 2015 edition of the U.S. Geological Survey (USGS) Mineral Commodity Summaries (MCS) includes information on events, trends, and issues for each mineral commodity as well as discussions and tabular presentations on domestic industry structure, Government programs, tariffs, 5-year salient statistics, and world production and resources. The MCS is the earliest comprehensive source of 2014 mineral production data for the world. More than 90 individual minerals and materials are covered by two-page synopses.
\nFor mineral commodities for which there is a Government stockpile, detailed information concerning the stockpile status is included in the two-page synopsis.
\nAbbreviations and units of measure, and definitions of selected terms used in the report, are in Appendix A and Appendix B, respectively. \"Appendix C—Reserves and Resources” includes “Part A—Resource/Reserve Classification for Minerals” and “Part B—Sources of Reserves Data.\" A directory of USGS minerals information country specialists and their responsibilities is Appendix D.
\nThe USGS continually strives to improve the value of its publications to users. Constructive comments and suggestions by readers of the MCS 2015 are welcomed.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/70140094","productDescription":"Report: 196 p.; 1 Appendix","numberOfPages":"199","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063093","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":297786,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/70140094.gif"},{"id":297784,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://minerals.usgs.gov/minerals/pubs/mcs/2015/mcs2015.pdf","size":"2.5 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":297785,"rank":2,"type":{"id":3,"text":"Appendix"},"url":"https://minerals.usgs.gov/minerals/pubs/mcs/2015/mcsapp2015.pdf","linkFileType":{"id":1,"text":"pdf"}}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2a97e4b08de9379b3124","contributors":{"authors":[{"text":"Water Resources Division, U.S. Geological Survey","contributorId":128075,"corporation":true,"usgs":false,"organization":"Water Resources Division, U.S. Geological Survey","id":539782,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70140180,"text":"ofr20151027 - 2015 - Improved algorithms in the CE-QUAL-W2 water-quality model for blending dam releases to meet downstream water-temperature targets","interactions":[],"lastModifiedDate":"2015-02-06T12:51:55","indexId":"ofr20151027","displayToPublicDate":"2015-02-06T12:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-1027","title":"Improved algorithms in the CE-QUAL-W2 water-quality model for blending dam releases to meet downstream water-temperature targets","docAbstract":"Water-quality models allow water resource professionals to examine conditions under an almost unlimited variety of potential future scenarios. The two-dimensional (longitudinal, vertical) water-quality model CE-QUAL-W2, version 3.7, was enhanced and augmented with new features to help dam operators and managers explore and optimize potential solutions for temperature management downstream of thermally stratified reservoirs. Such temperature management often is accomplished by blending releases from multiple dam outlets that access water of different temperatures at different depths. The modified blending algorithm in version 3.7 of CE-QUAL-W2 allows the user to specify a time-series of target release temperatures, designate from 2 to 10 floating or fixed-elevation outlets for blending, impose minimum and maximum head and flow constraints for any blended outlet, and set priority designations for each outlet that allow the model to choose which outlets to use and how to balance releases among them. The modified model was tested with a variety of examples and against a previously calibrated model of Detroit Lake on the North Santiam River in northwestern Oregon, and the results compared well. These updates to the blending algorithms will allow more complicated dam-operation scenarios to be evaluated somewhat automatically with the model, with decreased need for multiple model runs or preprocessing of model inputs to fully characterize the operational constraints.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151027","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Rounds, S.A., and Buccola, N., 2015, Improved algorithms in the CE-QUAL-W2 water-quality model for blending dam releases to meet downstream water-temperature targets: U.S. Geological Survey Open-File Report 2015-1027, Report: vi, 36 p.; Examples; Model Source, https://doi.org/10.3133/ofr20151027.","productDescription":"Report: vi, 36 p.; Examples; Model Source","numberOfPages":"46","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-057372","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":297791,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20151027.JPG"},{"id":297788,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1027/pdf/ofr2015-1027.pdf","text":"Report","size":"3.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":297787,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2015/1027/"},{"id":297789,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2015/1027/downloads/ofr2015-1027_code_changes_examples.zip","text":"Examples","size":"17.2 MB","description":"Examples"},{"id":297790,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2015/1027/downloads/ofr2015-1027_code_changes_model_source.zip","text":"Model Source","size":"2.7 MB","description":"Model Source"}],"publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2a88e4b08de9379b30da","contributors":{"authors":[{"text":"Rounds, Stewart A. 0000-0002-8540-2206 sarounds@usgs.gov","orcid":"https://orcid.org/0000-0002-8540-2206","contributorId":905,"corporation":false,"usgs":true,"family":"Rounds","given":"Stewart","email":"sarounds@usgs.gov","middleInitial":"A.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":539980,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Buccola, Norman L. nbuccola@usgs.gov","contributorId":138859,"corporation":false,"usgs":true,"family":"Buccola","given":"Norman L.","email":"nbuccola@usgs.gov","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":false,"id":539981,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70137743,"text":"sir20155004 - 2015 - Climate change and prairie pothole wetlands: mitigating water-level and hydroperiod effects through upland management","interactions":[],"lastModifiedDate":"2018-01-05T10:15:53","indexId":"sir20155004","displayToPublicDate":"2015-02-06T11:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-5004","title":"Climate change and prairie pothole wetlands: mitigating water-level and hydroperiod effects through upland management","docAbstract":"Prairie pothole wetlands offer crucial habitat for North America’s waterfowl populations. The wetlands also support an abundance of other species and provide ecological services valued by society. The hydrology of prairie pothole wetlands is dependent on atmospheric interactions. Therefore, changes to the region’s climate can have profound effects on wetland hydrology. The relevant literature related to climate change and upland management effects on prairie pothole wetland water levels and hydroperiods was reviewed. Climate change is widely expected to affect water levels and hydroperiods of prairie pothole wetlands, as well as the biota and ecological services that the wetlands support. In general, hydrologic model projections that incorporate future climate change scenarios forecast lower water levels in prairie pothole wetlands and longer periods spent in a dry condition, despite potential increases in precipitation. However, the extreme natural variability in climate and hydrology of prairie pothole wetlands necessitates caution when interpreting model results. Recent changes in weather patterns throughout much of the Prairie Pothole Region have been in increased precipitation that results in increased water inputs to wetlands above losses associated with warmer temperatures. However, observed precipitation increases are within the range of natural climate variability and therefore, may not persist. Identifying management techniques with the potential to affect water inputs to prairie pothole wetlands would provide increased options for managers when dealing with the uncertainties associated with a changing climate. Several grassland management techniques (for example, grazing and burning) have the potential to affect water levels and hydroperiods of prairie pothole by affecting infiltration, evapotranspiration, and snow deposition.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155004","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service and North Dakota State University","usgsCitation":"Renton, D., Mushet, D.M., and DeKeyser, E., 2015, Climate change and prairie pothole wetlands: mitigating water-level and hydroperiod effects through upland management: U.S. Geological Survey Scientific Investigations Report 2015-5004, 32 p., https://doi.org/10.3133/sir20155004.","productDescription":"32 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059680","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":297781,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20155004.jpg"},{"id":297779,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2015/5004/"},{"id":297780,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5004/pdf/sir2015-5004.pdf","text":"Report","size":"3.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"country":"Canada, United States","otherGeospatial":"Prairie Pothole Region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.9169921875,\n 54.03358633521085\n ],\n [\n -114.82910156249999,\n 48.1367666796927\n ],\n [\n -102.4365234375,\n 46.619261036171515\n ],\n [\n -98.8330078125,\n 43.32517767999296\n ],\n [\n -95.00976562499999,\n 41.541477666790286\n ],\n [\n -91.8896484375,\n 41.50857729743935\n ],\n [\n -92.021484375,\n 45.644768217751924\n ],\n [\n -96.3720703125,\n 50.65294336725709\n ],\n [\n -101.77734374999999,\n 52.802761415419674\n ],\n [\n -114.9169921875,\n 54.03358633521085\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2a5ee4b08de9379b301a","contributors":{"authors":[{"text":"Renton, David A. drenton@usgs.gov","contributorId":138600,"corporation":false,"usgs":true,"family":"Renton","given":"David A.","email":"drenton@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":539966,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mushet, David M. 0000-0002-5910-2744 dmushet@usgs.gov","orcid":"https://orcid.org/0000-0002-5910-2744","contributorId":1299,"corporation":false,"usgs":true,"family":"Mushet","given":"David","email":"dmushet@usgs.gov","middleInitial":"M.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":539965,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DeKeyser, Edward S.","contributorId":138601,"corporation":false,"usgs":false,"family":"DeKeyser","given":"Edward S.","affiliations":[{"id":12459,"text":"NDSU","active":true,"usgs":false}],"preferred":false,"id":539967,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70140268,"text":"70140268 - 2015 - Long-term plant responses to climate are moderated by biophysical attributes in a North American desert","interactions":[],"lastModifiedDate":"2017-11-27T08:44:57","indexId":"70140268","displayToPublicDate":"2015-02-06T11:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2242,"text":"Journal of Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Long-term plant responses to climate are moderated by biophysical attributes in a North American desert","docAbstract":"A regional, two-dimensional, steady-state groundwater-flow model was developed to simulate the groundwater-flow system and groundwater/surface-water interactions within the Menominee Indian Reservation. The model was developed by the U.S. Geological Survey (USGS), in cooperation with the Menominee Indian Tribe of Wisconsin, to contribute to the fundamental understanding of the region’s hydrogeology. The objectives of the regional model were to improve understanding of the groundwater-flow system, including groundwater/surface-water interactions, and to develop a tool suitable for evaluating the effects of potential regional water-management programs. The computer code GFLOW was used because of the ease with which the model can simulate groundwater/surface-water interactions, provide a framework for simulating regional groundwater-flow systems, and be refined in a stepwise fashion to incorporate new data and simulate groundwater-flow patterns at multiple scales. Simulations made with the regional model reproduce groundwater levels and stream base flows representative of recent conditions (1970–2013) and illustrate groundwater-flow patterns with maps of (1) the simulated water table and groundwater-flow directions, (2) probabilistic areas contributing recharge to high-capacity pumped wells, and (3) estimation of the extent of infiltrated wastewater from treatment lagoons.
\nThe groundwater-flow model described in this report simulates the major hydrogeologic features of the modeled area, including surficial unconsolidated aquifers, groundwater/surface-water interactions, and groundwater withdrawals from existing high-capacity production wells. Areas contributing recharge to pumped high-capacity wells on the Menominee Indian Reservation were delineated by tracking simulated water particles from the water table to wells in combination with Monte Carlo techniques, and maps of the probability of capture for each well nest were produced. Groundwater-agebased areas contributing recharge to wells were simulated by using the calibrated set of parameters and porosity values adjusted to account for bias in simulated saturated thickness. Simulations were performed for current (2013) pumping rates. The simulations show a range in sensitivity of the simulated areas contributing recharge to wells given the parameters evaluated through the Monte Carlo analysis. The areas contributing recharge to supply wells for the villages of Zoar and Neopit are long and narrow, with a sharp gradation from high to low probability of capture. The areas contributing recharge to supply wells for Middle Village and the village of Keshena exhibit a sharp gradation from high to low probability over a relatively small area between the well and a local groundwater mound. The highest probability areas contributing recharge to the supply wells for the Villages of Onekewat and Redwing are in the immediate vicinity of the wells. These wells also have an extensive area with low probability for capturing water that is likely due to a locally low hydraulic gradient and the large degree of uncertainty associated with the lakebed resistance parameters that control interaction between groundwater and local lakes. Additional field investigations and associated local model refinements would facilitate further reductions in uncertainty associated with simulated areas contributing recharge to the wells.
\nThe likely extent of the Neopit wastewater plume was simulated by using the groundwater-flow model and Monte Carlo techniques to evaluate the sensitivity of predictive simulations to a range of model parameter values. Wastewater infiltrated from the currently operating lagoons flows predominantly south toward Tourtillotte Creek. Some of the infiltrated wastewater is simulated as having a low probability of flowing beneath Tourtillotte Creek to the nearby West Branch Wolf River. Results for the probable extent of the wastewater plume are considered to be qualitative because the method only considers advective flow and does not account for processes affecting contaminant transport in porous media. Therefore, results for the probable extent of the wastewater plume are sensitive to the number of particles used to represent flow from the lagoon and the resolution of a synthetic grid used for the analysis. Nonetheless, it is expected that the qualitative results may be of use for identifying potential downgradient areas of concern that can then be evaluated using the quantitative “area contributing recharge to wells” method or traditional contaminant-transport simulations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145237","collaboration":"In cooperation with the Menominee Indian Tribe of Wisconsin","usgsCitation":"Juckem, P.F., and Dunning, C., 2015, Simulation of the regional groundwater-flow system of the Menominee Indian Reservation, Wisconsin: U.S. Geological Survey Scientific Investigations Report 2014-5237, Report: vi, 40 p.; 1 Appendix, https://doi.org/10.3133/sir20145237.","productDescription":"Report: vi, 40 p.; 1 Appendix","numberOfPages":"50","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-051827","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":297772,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145237.jpg"},{"id":297770,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5237/pdf/sir2014-5237.pdf","size":"11.5 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":297771,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5237/appendix/sir2014-5237_appendix1.xlsx","text":"Appendix 1","size":"43 kB","linkFileType":{"id":3,"text":"xlsx"},"linkHelpText":"Data from auger surveys near the Villages of Neopit, Zoar, and Keshena."},{"id":297768,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5237/"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Menominee Indian Reservation","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.98376464843749,\n 45.11133093583214\n ],\n [\n -88.98239135742188,\n 44.94633342311665\n ],\n [\n -88.73794555664062,\n 44.94438944516438\n ],\n [\n -88.7310791015625,\n 44.85100108620397\n ],\n [\n -88.47152709960938,\n 44.8490538825394\n ],\n [\n -88.472900390625,\n 45.11326925230233\n ],\n [\n -88.98376464843749,\n 45.11133093583214\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2ab4e4b08de9379b3192","contributors":{"authors":[{"text":"Juckem, Paul F. 0000-0002-3613-1761 pfjuckem@usgs.gov","orcid":"https://orcid.org/0000-0002-3613-1761","contributorId":1905,"corporation":false,"usgs":true,"family":"Juckem","given":"Paul","email":"pfjuckem@usgs.gov","middleInitial":"F.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":539963,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dunning, Charles P. cdunning@usgs.gov","contributorId":892,"corporation":false,"usgs":true,"family":"Dunning","given":"Charles P.","email":"cdunning@usgs.gov","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":false,"id":539964,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70139975,"text":"fs20143089 - 2015 - Water resources of La Salle Parish, Louisiana","interactions":[],"lastModifiedDate":"2026-06-25T20:23:18.79338","indexId":"fs20143089","displayToPublicDate":"2015-02-05T15:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-3089","title":"Water resources of La Salle Parish, Louisiana","docAbstract":"Information concerning the availability, use, and quality of water in La Salle Parish, Louisiana, is critical for proper water-supply management. The purpose of this fact sheet is to present information that can be used by water managers, parish residents, and others for stewardship of this vital resource. Information on the availability, past and current use, use trends, and water quality from groundwater and surface-water sources in the parish is presented. Previously published reports and data stored in the U.S. Geological Survey’s National Water Information System (http://waterdata.usgs.gov/nwis) are the primary sources of the information presented here.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20143089","collaboration":"Prepared in cooperation with the Louisiana Department of Transportation and Development","usgsCitation":"White, V.E., and Prakken, L.B., 2015, Water resources of La Salle Parish, Louisiana: U.S. Geological Survey Fact Sheet 2014-3089, 6 p., https://doi.org/10.3133/fs20143089.","productDescription":"6 p.","numberOfPages":"6","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056216","costCenters":[{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"links":[{"id":297693,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2014/3089/"},{"id":297764,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2014/3089/pdf/fs2014-3089.pdf","text":"Report","size":"1.45 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":297765,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20143089.jpg"},{"id":506021,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_101319.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Louisiana","county":"La Salle Parish","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.384033203125,\n 31.33252503230784\n ],\n [\n -92.384033203125,\n 31.924192605327708\n ],\n [\n -91.9940185546875,\n 31.924192605327708\n ],\n [\n -91.9940185546875,\n 31.33252503230784\n ],\n [\n -92.384033203125,\n 31.33252503230784\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2acde4b08de9379b3211","contributors":{"authors":[{"text":"White, Vincent E. 0000-0002-1660-0102 vwhite@usgs.gov","orcid":"https://orcid.org/0000-0002-1660-0102","contributorId":5388,"corporation":false,"usgs":true,"family":"White","given":"Vincent","email":"vwhite@usgs.gov","middleInitial":"E.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":539752,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Prakken, Lawrence B. lprakken@usgs.gov","contributorId":2319,"corporation":false,"usgs":true,"family":"Prakken","given":"Lawrence","email":"lprakken@usgs.gov","middleInitial":"B.","affiliations":[{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"preferred":false,"id":539753,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70157345,"text":"70157345 - 2015 - Fire modulates climate change response of simulated aspen distribution across topoclimatic gradients in a semi-arid montane landscape","interactions":[],"lastModifiedDate":"2017-11-20T15:40:32","indexId":"70157345","displayToPublicDate":"2015-02-05T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2602,"text":"Landscape Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Fire modulates climate change response of simulated aspen distribution across topoclimatic gradients in a semi-arid montane landscape","docAbstract":"Content Changing aspen distribution in response to climate change and fire is a major focus of biodiversity conservation, yet little is known about the potential response of aspen to these two driving forces along topoclimatic gradients. Objective This study is set to evaluate how aspen distribution might shift in response to different climate-fire scenarios in a semi-arid montane landscape, and quantify the influence of fire regime along topoclimatic gradients. Methods We used a novel integration of a forest landscape succession and disturbance model (LANDIS-II) with a fine-scale climatic water deficit approach to simulate dynamics of aspen and associated conifer and shrub species over the next 150 years under various climate-fire scenarios. Results Simulations suggest that many aspen stands could persist without fire for centuries under current climate conditions. However, a simulated 2–5 °C increase in temperature caused a substantial reduction of aspen coverage at lower elevations and a modest increase at upper elevations, leading to an overall reduction of aspen range at the landscape level. Increasing fire activity may favor aspen increase at its upper elevation limits adjacent to coniferous forest, but may also favor reduction of aspen at lower elevation limits adjacent to xeric shrubland. Conclusions Our study highlights the importance of incorporating fine-scale terrain effects on climatic water deficit and ecohydrology when modeling species distribution response to climate change. This modeling study suggests that climate mitigation and adaptation strategies that use fire would benefit from consideration of spatial context at landscape scales.
","language":"English","publisher":"Springer","doi":"10.1007/s10980-015-0160-1","usgsCitation":"Yang, J., Weisberg, P.J., Shinneman, D.J., Dilts, T.E., Earnst, S.L., and Scheller, R., 2015, Fire modulates climate change response of simulated aspen distribution across topoclimatic gradients in a semi-arid montane landscape: Landscape Ecology, v. 30, no. 6, p. 1055-1073, https://doi.org/10.1007/s10980-015-0160-1.","productDescription":"24 p.","startPage":"1055","endPage":"1073","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-054573","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":308332,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":308306,"type":{"id":15,"text":"Index Page"},"url":"https://link.springer.com/article/10.1007/s10980-015-0160-1"}],"volume":"30","issue":"6","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-02-05","publicationStatus":"PW","scienceBaseUri":"56012a4ce4b03bc34f5443ff","contributors":{"authors":[{"text":"Yang, Jian","contributorId":147806,"corporation":false,"usgs":false,"family":"Yang","given":"Jian","email":"","affiliations":[{"id":16940,"text":"Institute of Applied Ecology, Chinese Academy of Sciences","active":true,"usgs":false}],"preferred":false,"id":572764,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Weisberg, Peter J.","contributorId":33631,"corporation":false,"usgs":true,"family":"Weisberg","given":"Peter","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":572765,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shinneman, Douglas J. 0000-0002-4909-5181 dshinneman@usgs.gov","orcid":"https://orcid.org/0000-0002-4909-5181","contributorId":147745,"corporation":false,"usgs":true,"family":"Shinneman","given":"Douglas","email":"dshinneman@usgs.gov","middleInitial":"J.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":572763,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dilts, Thomas E.","contributorId":36833,"corporation":false,"usgs":true,"family":"Dilts","given":"Thomas","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":572766,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Earnst, Susan L. susan_earnst@usgs.gov","contributorId":4446,"corporation":false,"usgs":true,"family":"Earnst","given":"Susan","email":"susan_earnst@usgs.gov","middleInitial":"L.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":572767,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Scheller, Robert M","contributorId":147807,"corporation":false,"usgs":false,"family":"Scheller","given":"Robert M","affiliations":[{"id":16941,"text":"Environmental Science and Management Department, Portland State University","active":true,"usgs":false}],"preferred":false,"id":572768,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70140168,"text":"70140168 - 2015 - Mercury concentrations and distribution in soil, water, mine waste leachates, and air in and around mercury mines in the Big Bend region, Texas, USA","interactions":[],"lastModifiedDate":"2018-09-04T15:32:43","indexId":"70140168","displayToPublicDate":"2015-02-04T15:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1538,"text":"Environmental Geochemistry and Health","active":true,"publicationSubtype":{"id":10}},"title":"Mercury concentrations and distribution in soil, water, mine waste leachates, and air in and around mercury mines in the Big Bend region, Texas, USA","docAbstract":"Samples of soil, water, mine waste leachates, soil gas, and air were collected from areas mined for mercury (Hg) and baseline sites in the Big Bend area, Texas, to evaluate potential Hg contamination in the region. Soil samples collected within 300 m of an inactive Hg mine contained elevated Hg concentrations (3.8–11 µg/g), which were considerably higher than Hg in soil collected from baseline sites (0.03–0.05 µg/g) distal (as much as 24 km) from mines. Only three soil samples collected within 300 m of the mine exceeded the probable effect concentration for Hg of 1.06 µg/g, above which harmful effects are likely to be observed in sediment-dwelling organisms. Concentrations of Hg in mine water runoff (7.9–14 ng/L) were generally higher than those found in springs and wells (0.05–3.1 ng/L), baseline streams (1.1–9.7 ng/L), and sources of drinking water (0.63–9.1 ng/L) collected in the Big Bend region. Concentrations of Hg in all water samples collected in this study were considerably below the 2,000 ng/L drinking water Hg guideline and the 770 ng/L guideline recommended by the U.S. Environmental Protection Agency (USEPA) to protect aquatic wildlife from chronic effects of Hg. Concentrations of Hg in water leachates obtained from leaching of mine wastes varied widely from <0.001 to 760 µg of Hg in leachate/g of sample leached, but only one leachate exceeded the USEPA Hg industrial soil screening level of 31 µg/g. Concentrations of Hg in soil gas collected at mined sites (690–82,000 ng/m3) were highly elevated compared to soil gas collected from baseline sites (1.2–77 ng/m3). However, air collected from mined areas at a height of 2 m above the ground surface contained concentrations of Hg (4.9–64 ng/m3) that were considerably lower than Hg in soil gas from the mined areas. Although concentrations of Hg emitted from mine-contaminated soils and mine wastes were elevated, persistent wind in southwest Texas disperses Hg in the air within a few meters of the ground surface.
","language":"English","publisher":"Springer Netherlands","doi":"10.1007/s10653-014-9628-1","usgsCitation":"Gray, J.E., Theodorakos, P.M., Fey, D.L., and Krabbenhoft, D.P., 2015, Mercury concentrations and distribution in soil, water, mine waste leachates, and air in and around mercury mines in the Big Bend region, Texas, USA: Environmental Geochemistry and Health, v. 37, no. 1, p. 35-48, https://doi.org/10.1007/s10653-014-9628-1.","productDescription":"14 p.","startPage":"35","endPage":"48","numberOfPages":"14","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-055323","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":472288,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10653-014-9628-1","text":"Publisher Index Page"},{"id":297743,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Texas","otherGeospatial":"Big Bend region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -103.78372192382812,\n 28.96609636803482\n ],\n [\n -103.78372192382812,\n 29.627190028270117\n ],\n [\n -102.78396606445312,\n 29.627190028270117\n ],\n [\n -102.78396606445312,\n 28.96609636803482\n ],\n [\n -103.78372192382812,\n 28.96609636803482\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"37","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2014-06-29","publicationStatus":"PW","scienceBaseUri":"54dd2a96e4b08de9379b311a","contributors":{"authors":[{"text":"Gray, John E. jgray@usgs.gov","contributorId":1275,"corporation":false,"usgs":true,"family":"Gray","given":"John","email":"jgray@usgs.gov","middleInitial":"E.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":539852,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Theodorakos, Peter M. ptheodor@usgs.gov","contributorId":1566,"corporation":false,"usgs":true,"family":"Theodorakos","given":"Peter","email":"ptheodor@usgs.gov","middleInitial":"M.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":539853,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fey, David L. dfey@usgs.gov","contributorId":713,"corporation":false,"usgs":true,"family":"Fey","given":"David","email":"dfey@usgs.gov","middleInitial":"L.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":539855,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Krabbenhoft, David P. 0000-0003-1964-5020 dpkrabbe@usgs.gov","orcid":"https://orcid.org/0000-0003-1964-5020","contributorId":1658,"corporation":false,"usgs":true,"family":"Krabbenhoft","given":"David","email":"dpkrabbe@usgs.gov","middleInitial":"P.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":539854,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70138588,"text":"ofr20151008 - 2015 - Social Values for Ecosystem Services, version 3.0 (SolVES 3.0): documentation and user manual","interactions":[],"lastModifiedDate":"2015-02-04T14:31:17","indexId":"ofr20151008","displayToPublicDate":"2015-02-04T14:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-1008","title":"Social Values for Ecosystem Services, version 3.0 (SolVES 3.0): documentation and user manual","docAbstract":"The geographic information system (GIS) tool, Social Values for Ecosystem Services (SolVES), was developed to incorporate quantified and spatially explicit measures of social values into ecosystem service assessments. SolVES 3.0 continues to extend the functionality of SolVES, which was designed to assess, map, and quantify the social values of ecosystem services. Social values—the perceived, nonmarket values the public ascribes to ecosystem services, particularly cultural services, such as aesthetics and recreation—can be evaluated for various stakeholder groups. These groups are distinguishable by their attitudes and preferences regarding public uses, such as motorized recreation and logging. As with previous versions, SolVES 3.0 derives a quantitative 10-point, social-values metric—the value index—from a combination of spatial and nonspatial responses to public value and preference surveys. The tool also calculates metrics characterizing the underlying environment, such as average distance to water and dominant landcover. SolVES 3.0 is integrated with Maxent maximum entropy modeling software to generate more complete social-value maps and offer robust statistical models describing the relationship between the value index and explanatory environmental variables. A model’s goodness of fit to a primary study area and its potential performance in transferring social values to similar areas using value-transfer methodology can be evaluated. SolVES 3.0 provides an improved public-domain tool for decision makers and researchers to evaluate the social values of ecosystem services and to facilitate discussions among diverse stakeholders regarding the tradeoffs among ecosystem services in a variety of physical and social contexts ranging from forest and rangeland to coastal and marine.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151008","usgsCitation":"Sherrouse, B.C., and Semmens, D.J., 2015, Social Values for Ecosystem Services, version 3.0 (SolVES 3.0): documentation and user manual: U.S. Geological Survey Open-File Report 2015-1008, Report: vi, 65 p.; SolVES 3.0, https://doi.org/10.3133/ofr20151008.","productDescription":"Report: vi, 65 p.; SolVES 3.0","startPage":"65","numberOfPages":"71","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-059598","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":297741,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20151008.jpg"},{"id":297738,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2015/1008/"},{"id":297739,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1008/pdf/ofr2015-1008.pdf","text":"Report","size":"5.98 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":297740,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2015/1008/downloads/SolVES_V3.zip","text":"SolVES 3.0","size":"54.2 MB","description":"SolVES 3.0"}],"publicComments":"Land Change Science Program","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2ab4e4b08de9379b3198","contributors":{"authors":[{"text":"Sherrouse, Benson C. 0000-0002-5102-5895 bcsherrouse@usgs.gov","orcid":"https://orcid.org/0000-0002-5102-5895","contributorId":2445,"corporation":false,"usgs":true,"family":"Sherrouse","given":"Benson","email":"bcsherrouse@usgs.gov","middleInitial":"C.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":539842,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Semmens, Darius J. 0000-0001-7924-6529 dsemmens@usgs.gov","orcid":"https://orcid.org/0000-0001-7924-6529","contributorId":1714,"corporation":false,"usgs":true,"family":"Semmens","given":"Darius","email":"dsemmens@usgs.gov","middleInitial":"J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":539843,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70140152,"text":"ofr20141258 - 2015 - Lake Michigan Diversion Accounting land cover change estimation by use of the National Land Cover Dataset and raingage network partitioning analysis","interactions":[],"lastModifiedDate":"2015-02-04T10:58:40","indexId":"ofr20141258","displayToPublicDate":"2015-02-04T10:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-1258","title":"Lake Michigan Diversion Accounting land cover change estimation by use of the National Land Cover Dataset and raingage network partitioning analysis","docAbstract":"The U.S. Army Corps of Engineers (USACE), Chicago District, is responsible for monitoring and computation of the quantity of Lake Michigan water diverted by the State of Illinois. As part of this effort, the USACE uses the Hydrological Simulation Program–FORTRAN (HSPF) with measured meteorological data inputs to estimate runoff from the Lake Michigan diversion special contributing areas (SCAs), the North Branch Chicago River above Niles and the Little Calumet River above South Holland gaged basins, and the Lower Des Plaines and the Calumet ungaged that historically drained to Lake Michigan. These simulated runoffs are used for estimating the total runoff component from the diverted Lake Michigan watershed, which is accountable to the total diversion by the State of Illinois. The runoff is simulated from three interpreted land cover types in the HSPF models: impervious, grass, and forest. The three land cover data types currently in use were derived from aerial photographs acquired in the early 1990s.
\nThis study used the National Land Cover Dataset (NLCD) and developed an automated process for determining the area of the three land cover types, thereby allowing faster updating of future models, and for evaluating land cover changes by use of historical NLCD datasets. The study also carried out a raingage partitioning analysis so that the segmentation of land cover and rainfall in each modeled unit is directly applicable to the HSPF modeling. Historical and existing impervious, grass, and forest land acreages partitioned by percentages covered by two sets of raingages for the Lake Michigan diversion SCAs, gaged basins, and ungaged basins are presented.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141258","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers, Chicago District","usgsCitation":"Sharpe, J.B., and Soong, D.T., 2015, Lake Michigan Diversion Accounting land cover change estimation by use of the National Land Cover Dataset and raingage network partitioning analysis: U.S. Geological Survey Open-File Report 2014-1258, Report: iv, 12 p.; Downloads Directory, https://doi.org/10.3133/ofr20141258.","productDescription":"Report: iv, 12 p.; Downloads Directory","numberOfPages":"20","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-060110","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":297727,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141258.jpg"},{"id":297724,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1258/"},{"id":297725,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1258/pdf/ofr2014-1258.pdf","text":"Report","size":"2.12 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":297726,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2014/1258/downloads/ofr2014-1258_tables5-20.xlsx","text":"Downloads Directory","description":"Downloads Directory","linkHelpText":"Contains: Excel spreadsheets of tables 5 through 20."}],"projection":"Albers Equal-Area Conic Projection","country":"United States","state":"Illinois","otherGeospatial":"Calumet River, Lake Michigan, Little Calumet River, Lower Des Plaines River, North Branch Chicago River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.989501953125,\n 41.3500103516271\n ],\n [\n -87.989501953125,\n 42.370720143531955\n ],\n [\n -87.286376953125,\n 42.370720143531955\n ],\n [\n -87.286376953125,\n 41.3500103516271\n ],\n [\n -87.989501953125,\n 41.3500103516271\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2a8de4b08de9379b30ee","contributors":{"authors":[{"text":"Sharpe, Jennifer B. 0000-0002-5192-7848 jbsharpe@usgs.gov","orcid":"https://orcid.org/0000-0002-5192-7848","contributorId":2825,"corporation":false,"usgs":true,"family":"Sharpe","given":"Jennifer","email":"jbsharpe@usgs.gov","middleInitial":"B.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":539829,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Soong, David T. dsoong@usgs.gov","contributorId":2230,"corporation":false,"usgs":true,"family":"Soong","given":"David","email":"dsoong@usgs.gov","middleInitial":"T.","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":false,"id":539830,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70193113,"text":"70193113 - 2015 - Exxon Valdez Oil Spill Restoration Project final report: Monitoring for evaluation of recovery and restoration of injured nearshore resources","interactions":[],"lastModifiedDate":"2017-12-21T10:24:09","indexId":"70193113","displayToPublicDate":"2015-02-04T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":9,"text":"Other Report"},"displayTitle":"Exxon Valdez Oil Spill Restoration Project final report: Monitoring for evaluation of recovery and restoration of injured nearshore resources","title":"Exxon Valdez Oil Spill Restoration Project final report: Monitoring for evaluation of recovery and restoration of injured nearshore resources","docAbstract":"In 2012, we completed three consecutive years of full field sampling in WPWS for EVOS Restoration Project 10100750. Nearshore monitoring was conducted in collaboration with the NPS SWAN I&M program and, beginning in 2012, as part of the EVOSTC GWA program. Data collection was done in accordance with standard operating procedures set forth to monitor marine water chemistry and quality, marine intertidal invertebrates, kelps and seagrasses, marine birds, black oystercatchers, and sea otters. Summer sampling in 2012 represented the fourth year of sampling in WPWS (an initial year of sampling was done in WPWS in 2007; EVOS Restoration Project 070750). Based on our monitoring of nearshore species in WPWS, and comparisons of data from WPWS and other areas within the Gulf of Alaska, we have no evidence of continued injury to biological resources at the spatial scales we are monitoring. A key finding is that recovery of the sea otter population is no longer constrained by exposure to lingering oil; this is consistent with related EVOSTC studies on harlequin ducks (Restoration Project 12120114-Q). We anticipate continued annual nearshore monitoring in WPWS and at KATM and KEFJ under GWA, with data summaries and analyses including all three areas to provide a larger spatial and temporal context to the understanding of processes and patterns in nearshore ecosystems of the GOA which were impacted by the EVOS of 1989.
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2015 - Low-flow characteristics for selected streams in Indiana","interactions":[],"lastModifiedDate":"2015-02-03T10:35:00","indexId":"sir20145242","displayToPublicDate":"2015-02-03T11:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-5242","title":"Low-flow characteristics for selected streams in Indiana","docAbstract":"The management and availability of Indiana’s water resources increase in importance every year. Specifically, information on low-flow characteristics of streams is essential to State water-management agencies. These agencies need low-flow information when working with issues related to irrigation, municipal and industrial water supplies, fish and wildlife protection, and the dilution of waste. Industrial, municipal, and other facilities must obtain National Pollutant Discharge Elimination System (NPDES) permits if their discharges go directly to surface waters. The Indiana Department of Environmental Management (IDEM) requires low-flow statistics in order to administer the NPDES permit program. Low-flow-frequency characteristics were computed for 272 continuous-record stations. The information includes low-flow-frequency analysis, flow-duration analysis, and harmonic mean for the continuous-record stations. For those stations affected by some form of regulation, low-flow frequency curves are based on the longest period of homogeneous record under current conditions. Low-flow-frequency values and harmonic mean flow (if sufficient data were available) were estimated for the 166 partial-record stations. Partial-record stations are ungaged sites where streamflow measurements were made at base flow.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145242","collaboration":"Prepared in cooperation with the Indiana Department of Environmental Management","usgsCitation":"Fowler, K.K., and Wilson, J.T., 2015, Low-flow characteristics for selected streams in Indiana: U.S. Geological Survey Scientific Investigations Report 2014-5242, Report: iv, 353 p.; 2 Tables, https://doi.org/10.3133/sir20145242.","productDescription":"Report: iv, 353 p.; 2 Tables","numberOfPages":"361","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-051143","costCenters":[{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":297704,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145242.jpg"},{"id":297699,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5242/"},{"id":297701,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5242/pdf/sir2014-5242.pdf","text":"Report","size":"9.36 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2014-5242 Report"},{"id":297702,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2014/5242/table/sir2014-5242_table1.xlsx","text":"Table 1","size":"72.4 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2014-5242 Table","linkHelpText":"Continuous-record stations."},{"id":297703,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2014/5242/table/sir2014-5242_table2.xlsx","text":"Table 2","size":"87.2 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2014-5242 Table","linkHelpText":"Partial-record stations."}],"country":"United States","state":"Indiana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.528076171875,\n 41.7631174470059\n ],\n [\n -84.803466796875,\n 41.77950486590359\n ],\n [\n -84.7705078125,\n 38.74551518488265\n ],\n [\n -85.36376953125,\n 38.65119833229951\n ],\n [\n -85.36376953125,\n 38.47939467327645\n ],\n [\n -85.968017578125,\n 37.87485339352928\n ],\n [\n -86.33056640625,\n 37.98750437106374\n ],\n [\n -86.59423828125,\n 37.74465712069939\n ],\n [\n -86.802978515625,\n 37.85750715625203\n ],\n [\n -87.0556640625,\n 37.68382032669382\n ],\n [\n -88.05541992187499,\n 37.727280276860036\n ],\n [\n -88.187255859375,\n 37.87485339352928\n ],\n [\n -88.0224609375,\n 38.272688535980976\n ],\n [\n -87.60498046875,\n 38.762650338334154\n ],\n [\n -87.681884765625,\n 39.14710270770074\n ],\n [\n -87.6708984375,\n 39.317300373271024\n ],\n [\n -87.528076171875,\n 39.36827914916014\n ],\n [\n -87.528076171875,\n 41.7631174470059\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2a94e4b08de9379b310c","contributors":{"authors":[{"text":"Fowler, Kathleen K. 0000-0002-0107-3848 kkfowler@usgs.gov","orcid":"https://orcid.org/0000-0002-0107-3848","contributorId":2439,"corporation":false,"usgs":true,"family":"Fowler","given":"Kathleen","email":"kkfowler@usgs.gov","middleInitial":"K.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true},{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true},{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":539754,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wilson, John T. 0000-0001-6752-4069 jtwilson@usgs.gov","orcid":"https://orcid.org/0000-0001-6752-4069","contributorId":1954,"corporation":false,"usgs":true,"family":"Wilson","given":"John","email":"jtwilson@usgs.gov","middleInitial":"T.","affiliations":[{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":false,"id":539756,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70175239,"text":"70175239 - 2015 - Glacier-derived August runoff in northwest Montana","interactions":[],"lastModifiedDate":"2016-08-03T09:30:10","indexId":"70175239","displayToPublicDate":"2015-02-03T10:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":899,"text":"Arctic, Antarctic, and Alpine Research","active":true,"publicationSubtype":{"id":10}},"title":"Glacier-derived August runoff in northwest Montana","docAbstract":"The second largest concentration of glaciers in the U.S. Rocky Mountains is located in Glacier National Park (GNP), Montana. The total glacier-covered area in this region decreased by ∼35% over the past 50 years, which has raised substantial concern about the loss of the water derived from glaciers during the summer. We used an innovative weather station design to collect in situ measurements on five remote glaciers, which are used to parameterize a regional glacier melt model. This model offered a first-order estimate of the summer meltwater production by glaciers. We find, during the normally dry month of August, glaciers in the region produce approximately 25 × 106 m3 of potential runoff. We then estimated the glacier runoff component in five gaged streams sourced from GNP basins containing glaciers. Glacier-melt contributions range from 5% in a basin only 0.12% glacierized to >90% in a basin 28.5% glacierized. Glacier loss would likely lead to lower discharges and warmer temperatures in streams draining basins >20% glacier-covered. Lower flows could even be expected in streams draining basins as little as 1.4% glacierized if glaciers were to disappear.
","language":"English","publisher":"Institute of Arctic and Alpine Research","publisherLocation":"Boulder, CO","doi":"10.1657/AAAR0014-033","usgsCitation":"Clark, A., Harper, J.T., and Fagre, D.B., 2015, Glacier-derived August runoff in northwest Montana: Arctic, Antarctic, and Alpine Research, v. 47, no. 1, p. 1-16, https://doi.org/10.1657/AAAR0014-033.","startPage":"1","endPage":"16","numberOfPages":"16","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059157","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":472292,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://www.bioone.org/doi/10.1657/AAAR0014-033","text":"External Repository"},{"id":326012,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","otherGeospatial":"Glacier National Park","volume":"47","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-05","publicationStatus":"PW","scienceBaseUri":"57a315c3e4b006cb45558ad3","contributors":{"authors":[{"text":"Clark, Adam","contributorId":173391,"corporation":false,"usgs":false,"family":"Clark","given":"Adam","affiliations":[{"id":16951,"text":"Department of Geosciences, University of Montana, Missoula, MT 59812, USA","active":true,"usgs":false}],"preferred":false,"id":644491,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Harper, Joel T.","contributorId":173392,"corporation":false,"usgs":false,"family":"Harper","given":"Joel","email":"","middleInitial":"T.","affiliations":[{"id":16951,"text":"Department of Geosciences, University of Montana, Missoula, MT 59812, USA","active":true,"usgs":false}],"preferred":false,"id":644492,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fagre, Daniel B. 0000-0001-8552-9461 dan_fagre@usgs.gov","orcid":"https://orcid.org/0000-0001-8552-9461","contributorId":2036,"corporation":false,"usgs":true,"family":"Fagre","given":"Daniel","email":"dan_fagre@usgs.gov","middleInitial":"B.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":644490,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70139779,"text":"ofr20151020 - 2015 - Mercury and selenium contamination in waterbird eggs and risk to avian reproduction at Great Salt Lake, Utah","interactions":[],"lastModifiedDate":"2020-04-30T11:37:38.243248","indexId":"ofr20151020","displayToPublicDate":"2015-02-02T16:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-1020","title":"Mercury and selenium contamination in waterbird eggs and risk to avian reproduction at Great Salt Lake, Utah","docAbstract":"The wetlands of the Great Salt Lake ecosystem are recognized regionally, nationally, and hemispherically for their importance as breeding, wintering, and migratory habitat for diverse groups of waterbirds. Bear River Migratory Bird Refuge is the largest freshwater component of the Great Salt Lake ecosystem and provides critical breeding habitat for more than 60 bird species. However, the Great Salt Lake ecosystem also has a history of both mercury and selenium contamination, and this pollution could reduce the health and reproductive success of waterbirds. The overall objective of this study was to evaluate the risk of mercury and selenium contamination to birds breeding within Great Salt Lake, especially at Bear River Migratory Bird Refuge, and to identify the waterbird species and areas at greatest risk to contamination. We sampled eggs from 33 species of birds breeding within wetlands of Great Salt Lake during 2010 ̶ 2012 and focused on American avocets (Recurvirostra americana), black-necked stilts (Himantopus mexicanus), Forster’s terns (Sterna forsteri), white-faced ibis (Plegadis chihi), and marsh wrens (Cistothorus palustris) for additional studies of the effects of contaminants on reproduction.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151020","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Ackerman, J., Herzog, M., Hartman, C.A., Isanhart, J., Herring, G., Vaughn, S., Cavitt, J.F., Eagles-Smith, C.A., Browers, H., Cline, C., and Vest, J., 2015, Mercury and selenium contamination in waterbird eggs and risk to avian reproduction at Great Salt Lake, Utah: U.S. Geological Survey Open-File Report 2015-1020, Report: x, 164 p.; Data Release, https://doi.org/10.3133/ofr20151020.","productDescription":"Report: x, 164 p.; Data Release","numberOfPages":"178","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-061800","costCenters":[{"id":651,"text":"Western Ecological Research 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planning","interactions":[],"lastModifiedDate":"2017-02-08T13:32:17","indexId":"ofr20151017","displayToPublicDate":"2015-02-02T14:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-1017","title":"A framework for modeling anthropogenic impacts on waterbird habitats: addressing future uncertainty in conservation planning","docAbstract":"The amount and quality of natural resources available for terrestrial and aquatic wildlife habitats are expected to decrease throughout the world in areas that are intensively managed for urban and agricultural uses. Changes in climate and management of increasingly limited water supplies may further impact water resources essential for sustaining habitats. In this report, we document adapting a Water Evaluation and Planning (WEAP) system model for the Central Valley of California. We demonstrate using this adapted model (WEAP-CVwh) to evaluate impacts produced from plausible future scenarios on agricultural and wetland habitats used by waterbirds and other wildlife. Processed output from WEAP-CVwh indicated varying levels of impact caused by projected climate, urbanization, and water supply management in scenarios used to exemplify this approach. Among scenarios, the NCAR-CCSM3 A2 climate projection had a greater impact than the CNRM-CM3 B1 climate projection, whereas expansive urbanization had a greater impact than strategic urbanization, on annual availability of waterbird habitat. Scenarios including extensive rice-idling or substantial instream flow requirements on important water supply sources produced large impacts on annual availability of waterbird habitat. In the year corresponding with the greatest habitat reduction for each scenario, the scenario including instream flow requirements resulted in the greatest decrease in habitats throughout all months of the wintering period relative to other scenarios. This approach provides a new and useful tool for habitat conservation planning in the Central Valley and a model to guide similar research investigations aiming to inform conservation, management, and restoration of important wildlife habitats.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151017","collaboration":"Prepared in cooperation with the California Landscape Conservation Cooperative, California Department of Fish and Wildlife, and U.S. Fish and Wildlife Service","usgsCitation":"Matchett, E., Fleskes, J.P., Young, C., and Purkey, D.R., 2015, A framework for modeling anthropogenic impacts on waterbird habitats: addressing future uncertainty in conservation planning: U.S. Geological Survey Open-File Report 2015-1017, vi, 40 p., https://doi.org/10.3133/ofr20151017.","productDescription":"vi, 40 p.","numberOfPages":"50","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-053267","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":334995,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7H13050","text":"Data for projected impacts of climate, urbanization, water management, and wetland restoration on waterbird habitat in California’s Central Valley"},{"id":297683,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2015/1017/"},{"id":297684,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20151017.PNG"},{"id":297685,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1017/pdf/ofr2015-1017.pdf","text":"Report","size":"3.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"country":"United States","state":"California","otherGeospatial":"Central Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.16748046874999,\n 34.59704151614417\n ],\n [\n -124.16748046874999,\n 40.68063802521456\n ],\n [\n -119.68505859375,\n 40.68063802521456\n ],\n [\n -119.68505859375,\n 34.59704151614417\n ],\n [\n -124.16748046874999,\n 34.59704151614417\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2a4ae4b08de9379b2fc4","contributors":{"authors":[{"text":"Matchett, Elliott 0000-0001-5095-2884 ematchett@usgs.gov","orcid":"https://orcid.org/0000-0001-5095-2884","contributorId":5541,"corporation":false,"usgs":true,"family":"Matchett","given":"Elliott","email":"ematchett@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":539694,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fleskes, Joseph P. 0000-0001-5388-6675 joe_fleskes@usgs.gov","orcid":"https://orcid.org/0000-0001-5388-6675","contributorId":1889,"corporation":false,"usgs":true,"family":"Fleskes","given":"Joseph","email":"joe_fleskes@usgs.gov","middleInitial":"P.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":539695,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Young, Charles A.","contributorId":139008,"corporation":false,"usgs":false,"family":"Young","given":"Charles A.","affiliations":[],"preferred":false,"id":539698,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Purkey, David R.","contributorId":139005,"corporation":false,"usgs":false,"family":"Purkey","given":"David","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":539696,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70123191,"text":"ds877 - 2015 - Wetland paleoecological study of southwest coastal Louisiana: sediment cores and diatom calibration dataset","interactions":[],"lastModifiedDate":"2015-02-02T12:50:59","indexId":"ds877","displayToPublicDate":"2015-02-02T12:45:00","publicationYear":"2015","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":"877","title":"Wetland paleoecological study of southwest coastal Louisiana: sediment cores and diatom calibration dataset","docAbstract":"Wetland sediment data were collected in 2009 and 2010 throughout the southwest Louisiana Chenier Plain as part of a pilot study to develop a diatom-based proxy for past wetland water chemistry and the identification of sediment deposits from tropical storms. The complete dataset includes forty-six surface sediment samples and nine sediment cores. The surface sediment samples were collected in fresh, intermediate, and brackish marsh and are located coincident with Coastwide Reference Monitoring System (CRMS) sites. The nine sediment cores were collected at the Rockefeller Wildlife Refuge (RWR) located in Grand Chenier, La.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds877","usgsCitation":"Smith, K.E., Flocks, J.G., Steyer, G.D., and Piazza, S.C., 2015, Wetland paleoecological study of southwest coastal Louisiana: sediment cores and diatom calibration dataset: U.S. Geological Survey Data Series 877, HTML Document, https://doi.org/10.3133/ds877.","productDescription":"HTML Document","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-052587","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":297680,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds877.PNG"},{"id":297678,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0877/"},{"id":297679,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0877/html/ds877_abstract.html","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"Report"}],"country":"United States","state":"Louisiana","city":"Grand Chenier","otherGeospatial":"Chenier Plain, Rockefeller Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.85894775390625,\n 29.508939763268394\n ],\n [\n -93.85894775390625,\n 30.071470887901302\n ],\n [\n -91.96929931640624,\n 30.071470887901302\n ],\n [\n -91.96929931640624,\n 29.508939763268394\n ],\n [\n -93.85894775390625,\n 29.508939763268394\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2ad0e4b08de9379b321c","contributors":{"authors":[{"text":"Smith, Kathryn E. L. kelsmith@usgs.gov","contributorId":3242,"corporation":false,"usgs":true,"family":"Smith","given":"Kathryn","email":"kelsmith@usgs.gov","middleInitial":"E. L.","affiliations":[],"preferred":false,"id":519342,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Flocks, James G. 0000-0002-6177-7433 jflocks@usgs.gov","orcid":"https://orcid.org/0000-0002-6177-7433","contributorId":816,"corporation":false,"usgs":true,"family":"Flocks","given":"James","email":"jflocks@usgs.gov","middleInitial":"G.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":539675,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Steyer, Gregory D. 0000-0001-7231-0110 steyerg@usgs.gov","orcid":"https://orcid.org/0000-0001-7231-0110","contributorId":2856,"corporation":false,"usgs":true,"family":"Steyer","given":"Gregory","email":"steyerg@usgs.gov","middleInitial":"D.","affiliations":[{"id":5062,"text":"Office of the Chief Scientist for Ecosystems","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":5064,"text":"Southeast Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":539676,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Piazza, Sarai C. 0000-0001-6962-9008 piazzas@usgs.gov","orcid":"https://orcid.org/0000-0001-6962-9008","contributorId":466,"corporation":false,"usgs":true,"family":"Piazza","given":"Sarai","email":"piazzas@usgs.gov","middleInitial":"C.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":false,"id":539677,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70133604,"text":"ds901 - 2015 - Mount St. Helens: Controlled-source audio-frequency magnetotelluric (CSAMT) data and inversions","interactions":[],"lastModifiedDate":"2016-02-08T14:09:10","indexId":"ds901","displayToPublicDate":"2015-02-02T12:30:00","publicationYear":"2015","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":"901","title":"Mount St. Helens: Controlled-source audio-frequency magnetotelluric (CSAMT) data and inversions","docAbstract":"This report describes a series of geoelectrical soundings carried out on and near Mount St. Helens volcano, Washington, in 2010–2011. These soundings used a controlled-source audio-frequency magnetotelluric (CSAMT) approach (Zonge and Hughes, 1991; Simpson and Bahr, 2005). We chose CSAMT for logistical reasons: It can be deployed by helicopter, has an effective depth of penetration of as much as 1 kilometer, and requires less wire than a Schlumberger sounding.
\nThis Data Series provides the edited data for these CSAMT soundings as well as several different types of 1-D inversions (where the signal data are converted to conductivity-versus-depth models). In addition, we include a map showing station locations on and around the volcano and the Pumice Plain to the north.
\nThe apparent conductivity (or its inverse, apparent resistivity) measured by a geoelectrical system is caused by several factors. The most important of these are water-filled rock porosity and the presence of water-filled fractures; however, rock type and minerals (for instance, sulfides and clay content) also contribute to apparent conductivity. In situations with little recharge (for instance, in arid regions), variations in ionic content of water occupying pore space and fractures sampled by the measurement system must also be factored in (Wynn, 2006). Variations in ionic content may also be present in hydrothermal fluids surrounding volcanoes in wet regions. In unusual cases, temperature may also affect apparent conductivity (Keller, 1989; Palacky, 1989). There is relatively little hydrothermal alteration (and thus fewer clay minerals that might add to the apparent conductivity) in the eruptive products of Mount St. Helens (Reid and others, 2010), so conductors observed in the Fischer, Occam, and Marquardt inversion results later in this report are thus believed to map zones with significant water content. Geoelectrical surveys thus have the potential to reveal subsurface regions with significant groundwater content, including perched and regional aquifers. Reid and others (2001) and Reid (2004) have suggested that groundwater involvement may figure in both the scale and the character of some if not all volcanic edifice collapse events. Ongoing research by the U.S. Geological Survey (USGS) and others aims to better understand the contribution of groundwater to both edifice pore pressure and rock alteration as well as its direct influence on eruption processes by violent interaction with magma (Schmincke, 1998).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds901","usgsCitation":"Wynn, J., and Pierce, H., 2015, Mount St. Helens: Controlled-source audio-frequency magnetotelluric (CSAMT) data and inversions: U.S. Geological Survey Data Series 901, HTML Document, https://doi.org/10.3133/ds901.","productDescription":"HTML Document","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-044700","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":297677,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds901.gif"},{"id":316600,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0901/ds901.pdf","text":"Report","size":"3.8 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":297676,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0901/cover.html","text":"Report","linkFileType":{"id":5,"text":"html"}}],"projection":"Universal Transverse Mercator projection, Zone 10N","datum":"World Geodetic System 1984","country":"United States","state":"Washington","otherGeospatial":"Mount St. Helens","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.28675842285158,\n 46.150107913663334\n ],\n [\n -122.28675842285158,\n 46.27388525189855\n ],\n [\n -122.09415435791016,\n 46.27388525189855\n ],\n [\n -122.09415435791016,\n 46.150107913663334\n ],\n [\n -122.28675842285158,\n 46.150107913663334\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2a9ce4b08de9379b3137","contributors":{"authors":[{"text":"Wynn, Jeff 0000-0002-8102-3882 jwynn@usgs.gov","orcid":"https://orcid.org/0000-0002-8102-3882","contributorId":2803,"corporation":false,"usgs":true,"family":"Wynn","given":"Jeff","email":"jwynn@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":539674,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pierce, Herbert A.","contributorId":83093,"corporation":false,"usgs":true,"family":"Pierce","given":"Herbert A.","affiliations":[],"preferred":false,"id":539673,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70148078,"text":"70148078 - 2015 - Mapping migratory flyways in Asia using dynamic Brownian bridge movement models","interactions":[],"lastModifiedDate":"2017-07-26T17:13:27","indexId":"70148078","displayToPublicDate":"2015-02-02T11:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2792,"text":"Movement Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Mapping migratory flyways in Asia using dynamic Brownian bridge movement models","docAbstract":"Background
\nIdentifying movement routes and stopover sites is necessary for developing effective management and conservation strategies for migratory animals. In the case of migratory birds, a collection of migration routes, known as a flyway, is often hundreds to thousands of kilometers long and can extend across political boundaries. Flyways encompass the entire geographic range between the breeding and non-breeding areas of a population, species, or a group of species, and they provide spatial frameworks for management and conservation across international borders. Existing flyway maps are largely qualitative accounts based on band returns and survey data rather than observed movement routes. In this study, we use satellite and GPS telemetry data and dynamic Brownian bridge movement models to build upon existing maps and describe waterfowl space use probabilistically in the Central Asian and East Asian-Australasian Flyways.
\nResults
\nOur approach provided new information on migratory routes that was not easily attainable with existing methods to describe flyways. Utilization distributions from dynamic Brownian bridge movement models identified key staging and stopover sites, migration corridors and general flyway outlines in the Central Asian and East Asian-Australasian Flyways. A map of space use from ruddy shelducks depicted two separate movement corridors within the Central Asian Flyway, likely representing two distinct populations that show relatively strong connectivity between breeding and wintering areas. Bar-headed geese marked at seven locations in the Central Asian Flyway showed heaviest use at several stopover sites in the same general region of high-elevation lakes along the eastern Qinghai-Tibetan Plateau. Our analysis of data from multiple Anatidae species marked at sites throughout Asia highlighted major movement corridors across species and confirmed that the Central Asian and East Asian-Australasian Flyways were spatially distinct.
\nConclusions
\nThe dynamic Brownian bridge movement model improves our understanding of flyways by estimating relative use of regions in the flyway while providing detailed, quantitative information on migration timing and population connectivity including uncertainty between locations. This model effectively quantifies the relative importance of different migration corridors and stopover sites and may help prioritize specific areas in flyways for conservation of waterbird populations.
","language":"English","publisher":"Minerva Center for Movement Ecology","publisherLocation":"London","doi":"10.1186/s40462-015-0029-6","usgsCitation":"Palm, E., Newman, S.H., Prosser, D.J., Xiao, X., Luo, Z., Batbayar, N., Balachandran, S., and Takekawa, J.Y., 2015, Mapping migratory flyways in Asia using dynamic Brownian bridge movement models: Movement Ecology, v. 3, no. 1, p. 1-10, https://doi.org/10.1186/s40462-015-0029-6.","productDescription":"10 p.","startPage":"1","endPage":"10","numberOfPages":"10","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-062254","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":472293,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s40462-015-0029-6","text":"Publisher Index Page"},{"id":300545,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"3","issue":"1","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2015-02-02","publicationStatus":"PW","scienceBaseUri":"555c5eb6e4b0a92fa7eacc02","contributors":{"authors":[{"text":"Palm, E.C.","contributorId":40708,"corporation":false,"usgs":true,"family":"Palm","given":"E.C.","email":"","affiliations":[],"preferred":false,"id":547228,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Newman, S. H.","contributorId":21888,"corporation":false,"usgs":false,"family":"Newman","given":"S.","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":547229,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Prosser, Diann J. 0000-0002-5251-1799 dprosser@usgs.gov","orcid":"https://orcid.org/0000-0002-5251-1799","contributorId":2389,"corporation":false,"usgs":true,"family":"Prosser","given":"Diann","email":"dprosser@usgs.gov","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":547230,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Xiao, Xiangming","contributorId":67212,"corporation":false,"usgs":true,"family":"Xiao","given":"Xiangming","affiliations":[],"preferred":false,"id":547231,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Luo, Ze","contributorId":41307,"corporation":false,"usgs":true,"family":"Luo","given":"Ze","affiliations":[],"preferred":false,"id":547232,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Batbayar, Nyambayar","contributorId":40338,"corporation":false,"usgs":true,"family":"Batbayar","given":"Nyambayar","affiliations":[],"preferred":false,"id":547233,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Balachandran, Sivananinthaperumal","contributorId":20593,"corporation":false,"usgs":true,"family":"Balachandran","given":"Sivananinthaperumal","affiliations":[],"preferred":false,"id":547234,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Takekawa, John Y. 0000-0003-0217-5907 john_takekawa@usgs.gov","orcid":"https://orcid.org/0000-0003-0217-5907","contributorId":176168,"corporation":false,"usgs":true,"family":"Takekawa","given":"John","email":"john_takekawa@usgs.gov","middleInitial":"Y.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":547235,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70135892,"text":"sir20145232 - 2015 - Potentiometric surfaces and water-level trends in the Cockfield (upper Claiborne) aquifer in southern Arkansas and the Wilcox (lower Wilcox) aquifer of northeastern and southern Arkansas, 2012","interactions":[],"lastModifiedDate":"2015-04-20T14:25:03","indexId":"sir20145232","displayToPublicDate":"2015-02-02T09:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-5232","title":"Potentiometric surfaces and water-level trends in the Cockfield (upper Claiborne) aquifer in southern Arkansas and the Wilcox (lower Wilcox) aquifer of northeastern and southern Arkansas, 2012","docAbstract":"The Cockfield aquifer, located in southern Arkansas, is composed of Eocene-age sand beds found near the base of the Cockfield Formation of Claiborne Group. The Wilcox aquifer, located in northeastern and southern Arkansas, is composed of Paleocene-age sand beds found in the middle to lower part of the Wilcox Group. The Cockfield and Wilcox aquifers are primary sources of groundwater. In 2010, withdrawals from the Cockfield aquifer in Arkansas totaled 19.2 million gallons per day (Mgal/d), and withdrawals from the Wilcox aquifer totaled 36.5 Mgal/d.
\nA study was conducted by the U.S. Geological Survey in cooperation with the Arkansas Natural Resources Commission and the Arkansas Geological Survey to measure water levels associated with the Cockfield aquifer and the Wilcox aquifer in northeastern and southern Arkansas. Water levels were measured at 43 wells completed in the Cockfield aquifer and 47 wells completed in the Wilcox aquifer in February and March 2012. Measurements from 2012 are presented as potentiometric-surface maps and in combination with measurements from 2006 as water-level difference maps. Trends in water-level change over time within the Cockfield and Wilcox aquifers were determined using the water-level difference maps and selected well hydrographs.
\nThe Cockfield aquifer study area in southern Arkansas is bounded on the east by the Mississippi River and on the west by the area that contains outcrops and subcrops of the Cockfield Formation. The northern boundary of the Cockfield aquifer study area is defined by the area that contains observation wells completed in the Cockfield aquifer and the southern boundary is the Louisiana State line.
\nThe Wilcox aquifer study area in northeastern Arkansas is bounded on the east by the Mississippi River and on the north by the Missouri State line. The southern and western boundaries are defined by areas containing observation wells completed in the Wilcox aquifer or by outcrop areas on or near Crowleys Ridge. The Wilcox aquifer study area in southern Arkansas is defined by observation wells completed in the Wilcox aquifer or by areas that contain outcrops of the Wilcox Group, or both.
\nThe potentiometric-surface map of the Cockfield aquifer shows the regional direction of groundwater flow was generally toward the east-southeast, except in areas of intense groundwater withdrawals such as southwestern Ashley County, where groundwater flows toward the town of Crossett. The highest water-level altitude measured was 350 feet (ft) above National Geodetic Vertical Datum of 1929 (NGVD 29) in central Columbia County. The lowest water-level altitude measured was 40 ft above NGVD 29 in southeastern Lincoln County.
\nThe water-level difference map for the Cockfield aquifer in Arkansas was constructed using 42 water-level measurements made during 2006 and 2012. The difference in water levels for the Cockfield aquifer ranged from 27.4 ft to -10.4 ft. The largest water-level rise was in Calhoun County, and the largest water-level decline was 10.4 ft in Union County. Of the 42 wells, 13 wells had a rise in water level, and the remaining 29 wells had a decline in water level.
\nHydrographs for 32 wells in the Cockfield aquifer with historical water-level data were evaluated using linear regression to calculate the annual rise or decline for each well. These data were aggregated by county and statistically evaluated for the range, mean, and median of water-level change in each county. Hydrographs for Bradley, Calhoun, Chicot, Columbia, and Union Counties indicated both rising and declining water levels. The mean annual water-level rise or decline for Calhoun County was 0.00 foot per year (ft/yr) or unchanged. The mean annual water-level for Ashley, Bradley, Chicot, Cleveland, Columbia, Lincoln, and Union Counties show declines ranging from -0.02 to -1.10 ft/yr.
\nTwo potentiometric-surface maps, one for the southern area and one for the northeastern area, were constructed to show the altitude of the water surface in the Wilcox aquifer. The direction of groundwater flow in the northeastern area was generally towards the south-southwest except for some areas immediately adjacent to the Mississippi River where the flow was more eastward towards the river. The highest water-level altitude was 219 ft in northern Mississippi County, and the lowest water-level altitude was 123 ft near West Memphis in Crittenden County. The direction of groundwater flow in the northern part of the southern area was generally towards the southwest. The direction of groundwater flow in the southern part was in all directions because of two cones of depression and two water-level mounds. The highest water-level altitude measured was 394 ft at the center of a water-level mound in eastern Hot Spring County and a water-level mound in southwestern Hempstead County. The lowest water-level altitude measured was 145 ft at the center of the cone of depression in Clark County.
\nWater-level difference maps for the Wilcox aquifer in Arkansas were constructed using 47 water-level measurements made during 2006 and 2012. The difference in water levels for the Wilcox aquifer in the northeastern area ranged from 22.0 ft to -17.9 ft. The largest rise in water level occurred in Crittenden County, and the largest decline occurred in Lee County. Twenty-one wells had rising water levels, and 10 wells had declining water levels. The difference in water levels for the Wilcox aquifer in the southern area ranged from 18.1 ft to -4.2 ft. The largest rise and the largest decline in water level occurred in Nevada County. Twelve wells had rising water levels, and 4 wells had declining water levels.
\nLinear regression analysis of long-term hydrographs was used to determine the mean annual water-level rise and decline in the Wilcox aquifer in the northeastern and southern areas of Arkansas. In the northeastern area, the mean annual water level declined in all seven counties. The mean annual declines ranged from -0.55 ft/yr in Craighead County to -1.46 ft/yr in St. Francis County. In the southern area, the annual rise and decline calculations for wells with over 20 years of records indicate rising and declining water levels in Clark, Hot Spring, and Nevada Counties. The mean annual water level declined in all counties except Hot Spring County.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145232","collaboration":"Prepared in cooperation with the Arkansas Natural Resources Commission and the Arkansas Geological Survey","usgsCitation":"Rodgers, K.D., 2015, Potentiometric surfaces and water-level trends in the Cockfield (upper Claiborne) aquifer in southern Arkansas and the Wilcox (lower Wilcox) aquifer of northeastern and southern Arkansas, 2012: U.S. Geological Survey Scientific Investigations Report 2014-5232, v, 46 p., https://doi.org/10.3133/sir20145232.","productDescription":"v, 46 p.","numberOfPages":"55","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-056679","costCenters":[{"id":129,"text":"Arkansas Water Science Center","active":true,"usgs":true}],"links":[{"id":297673,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5232/pdf/sir2014-5232.pdf","text":"Report","size":"4.53 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Basin","docAbstract":"In 2009, the U.S. Geological Survey (USGS) developed a Spatially Referenced Regressions on Watershed Attributes (SPARROW) surface-water quality model for the Upper Colorado River Basin (UCRB) relating dissolved-solids sources and transport in the 1991 water year to upstream catchment characteristics. The SPARROW model focused on geologic and agricultural sources of dissolved solids in the UCRB and was calibrated using water-year 1991 dissolved-solids loads from 218 monitoring sites. A new UCRB SPARROW model is planned that will update the investigation of dissolved-solids sources and transport in the basin to circa 2010 conditions and will improve upon the 2009 model by incorporating more detailed information about agricultural-irrigation and rangeland-management practices, among other improvements. Geospatial datasets relating to circa 2010 rangeland conditions are required for the new UCRB SPARROW modeling effort. This study compiled geospatial datasets for the UCRB that relate to the biotic alterations and rangeland conditions of grazing, fire and other land disturbance, and vegetation type and cover. Datasets representing abiotic alterations of access control (off-highway vehicles) and sediment generation and transport in general, were also compiled. These geospatial datasets may be tested in the upcoming SPARROW model to better understand the potential contribution of rangelands to dissolved-solids loading in UCRB streams.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151007","collaboration":"Prepared in cooperation with the U.S. Bureau of Reclamation","usgsCitation":"Tillman, F., Flynn, M., and Anning, D.W., 2015, Geospatial datasets for assessing the effects of rangeland conditions on dissolved-solids yields in the Upper Colorado River Basin: U.S. Geological Survey Open-File Report 2015-1007, Report: v, 21 p.; 6 Geospatial Datasets, https://doi.org/10.3133/ofr20151007.","productDescription":"Report: v, 21 p.; 6 Geospatial Datasets","numberOfPages":"32","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-060100","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":297671,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20151007.gif"},{"id":297670,"rank":9,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/of/2015/1007/downloads/datasets/UCRB_R-factor.zip","text":"Rainfall-Runoff Erosivity","size":"962 kB","description":"Geospatial dataset","linkHelpText":"This tabular dataset presents the 1971–2000 average annual rainfall-runoff erosivity factor (R-factor) for the UCRB. The R-factor is a measure of the cumulative erosive force of individual precipitation events (Daly and Taylor, 2002). All other factors being constant, sediment generation from precipitation is directly proportional to the product of the total kinetic energy of a storm and the storm’s maximum 30-minute intensity. The mean annual R-factor is a sum of this product for all storms in a year, averaged over all years of record (Daly and Taylor, 2002)."},{"id":297663,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2015/1007/"},{"id":297668,"rank":7,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/of/2015/1007/downloads/datasets/2010_UCRB_VegTypeCover.zip","text":"Existing Vegetation Type and Cover","size":"540 MB","description":"Geospatial dataset","linkHelpText":"These layers include information on the vegetation type and vegetation cover in 2010 in the UCRB. The 2010 existing vegetation cover (EVC) layer represents the vertically projected percent cover of the live canopy layer. The 2010 existing vegetation type (EVT) layer represents the species composition. Spatially, both grids cover the entire UCRB and have a 30-meter pixel resolution."},{"id":297664,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1007/downloads/OFR2015-1007.pdf","text":"Report","size":"5.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":297666,"rank":5,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/of/2015/1007/downloads/datasets/2010_UCRB_USFS_Grazing_projected.zip","text":"U.S. Forest Service Grazing","size":"3.8 MB","description":"Geospatial dataset","linkHelpText":"The shapefile contains 444 polygons of USFS grazing allotments within or bordering the UCRB (fig. 4). Attributes for the allotment polygons include the allotment name (RMU_NAME) and number (RMU_CN), the authorized number of animal unit months for the allotment (AUTH_AUMS), and the area of the allotment in both acres (AREA_acres) and square kilometers (AREA_km2). USFS-billed grazing is referred to as the \"authorized\" amount and is equivalent to BLM’s \"billed\" grazing (U.S. Government Accountability Office, 2005)."},{"id":297669,"rank":8,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/of/2015/1007/downloads/datasets/2010_UCRB_Roads.zip","text":"2010 Roads","size":"172 MB","description":"Geospatial dataset","linkHelpText":"This layer contains information about the location and type of roads in the UCRB in 2010. One value in the MAF/TIGER Feature Class Code (MTFCC) attribute field in the roads layer is S1500, named \"Vehicular Trail (4WD)\", and is described as \"an unpaved dirt trail where a four-wheel drive vehicle is required\" (table 5). The Vehicular Trail (4WD) attribute presents potential UCRB locations of off-highway vehicle use—an activity directly related to the \"access controls\" abiotic alteration in Weltz and others (2014) (table 5; fig. 7). The 2010 roads layer covers the entire UCRB."},{"id":297665,"rank":4,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/of/2015/1007/downloads/datasets/2010_UCRB_BLM_Grazing_projected.zip","text":"Bureau of Land Management Grazing","size":"12.9 MB","description":"Geospatial dataset","linkHelpText":"The shapefile contains 2,367 polygons of BLM grazing allotments within or bordering the UCRB (fig. 4). Attributes for the allotment polygons include the allotment name (ALLOT_NAME) and number (ST_ALLOT), the authorized number of \"animal unit months\" for the allotment (AUTH_AUMS), and the area of the allotment in both acres (AREA_acres) and square kilometers (AREA_km2)."},{"id":297667,"rank":6,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/of/2015/1007/downloads/datasets/1999-2010_UCRB_LandDisturbance.zip","text":"Land Disturbance","size":"26 MB","description":"Geospatial dataset","linkHelpText":"These layers include temporal and spatial information on disturbances to the landscape as a result of management activities or natural events. Two types of grids are presented: yearly disturbance grids for 1999–2010 and a composite grid of the yearly disturbance grids that summarizes vegetation disturbance for 1999–2010. 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In this study, we used molecular approaches to describe the unique population structure of brook trout inhabiting the Shavers Fork watershed, located in eastern West Virginia, and contrast it to nearby populations in tributaries of the upper Greenbrier River and North Fork South Branch Potomac Rivers. Bayesian and maximum likelihood clustering methods identified minimal population structuring among 14 collections of brook trout from throughout the mainstem and tributaries of Shavers Fork, highlighting the role of the cold-water mainstem for connectivity and high rates of effective migration among tributaries. In contrast, the Potomac and Greenbrier River collections displayed distinct levels of population differentiation among tributaries, presumably resulting from tributary isolation by warm-water mainstems. Our results highlight the importance of protecting and restoring cold-water mainstem habitats as part of region-wide brook trout conservation efforts. In addition, our results from Shavers Fork provide a contrast to previous genetic studies that characterize Appalachian brook trout as fragmented isolates rather than well-mixed populations. Additional study is needed to determine whether the existence of brook trout as genetically similar populations among tributaries is truly unique and whether connectivity among brook trout populations can potentially be restored within other central Appalachian watersheds.
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