Background: For imperiled marine turtles, use of satellite telemetry has proven to be an effective method in determining long distance movements. However, the large size of the tag, relatively high cost and low spatial resolution of this method make it more difficult to examine fine-scale movements of individuals, particularly at foraging grounds where animals are frequently submerged. Acoustic telemetry offers a more suitable method of assessing fine-scale movement patterns with a smaller tag that provides more precise locations. We used acoustic telemetry to define home ranges and describe habitat use of juvenile green turtles at a temperate foraging ground in the northern Gulf of Mexico.
\nResults: We outfitted eight juvenile green turtles with acoustic transmitters and tracked them from 14 to 138 days from September 2012 to February 2013 in St. Joseph Bay, Northwest Florida. Mean home range size was relatively small compared to other studies. For four turtles, we observed a moderate inverse relationship between water temperature and water depth which is consistent with the idea that turtles moved to deeper waters when temperatures cooled. On average distance to the channel from turtle locations were different by bottom cover type. These turtles appear to forage in shallow-water seagrass beds that border deep channels. When water temperatures dropped in winter, some of the tracked turtles moved to a deep-water channel on the western side of the study site. Turtles whose foraging sites were farther from the deep-water channel exhibited greater displacement than those with sites that were closer to the channel.
\nConclusions: Green turtles in St. Joseph Bay have relatively small home ranges and many contain multiple activity centers. The frequent use of channels by turtles suggests bathymetry plays a major role in habitat selection of juvenile green turtles, particularly as temperatures drop in winter. The quality and density of seagrass habitat in St. Joseph Bay and its proximity to deep channels appears to provide ideal conditions for juvenile greens. The results of this study help define characteristics of foraging habitat utilized by juvenile greens in the northern Gulf of Mexico that managers can use in creating protected areas such as aquatic preserves.
","language":"English","publisher":"BioMed Central","doi":"10.1186/s40317-015-0089-9","usgsCitation":"Lamont, M.M., Fujisaki, I., Stephens, B.S., and Hackett, C., 2015, Home range and habitat use of juvenile green turtles (Chelonia mydas) in the northern Gulf of Mexico: Animal Biotelemetry, v. 3, no. 53, 12 p., https://doi.org/10.1186/s40317-015-0089-9.","productDescription":"12 p.","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"2012-09-01","temporalEnd":"2013-02-28","ipdsId":"IP-062733","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":471653,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s40317-015-0089-9","text":"Publisher Index Page"},{"id":311179,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Gulf of Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -85.40771484375,\n 29.818008344682042\n ],\n [\n -85.31295776367188,\n 29.821582720575016\n ],\n [\n -85.30746459960938,\n 29.68685971706881\n ],\n [\n -85.35964965820312,\n 29.682087444299334\n ],\n [\n -85.40634155273438,\n 29.785833211631733\n ],\n [\n -85.41458129882812,\n 29.81205076752506\n ],\n [\n -85.40771484375,\n 29.818008344682042\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"3","issue":"53","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2015-11-02","publicationStatus":"PW","scienceBaseUri":"56431533e4b0aafbcd017faa","contributors":{"authors":[{"text":"Lamont, Margaret M. 0000-0001-7520-6669 mlamont@usgs.gov","orcid":"https://orcid.org/0000-0001-7520-6669","contributorId":4525,"corporation":false,"usgs":true,"family":"Lamont","given":"Margaret","email":"mlamont@usgs.gov","middleInitial":"M.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":579612,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fujisaki, Ikuko","contributorId":38359,"corporation":false,"usgs":false,"family":"Fujisaki","given":"Ikuko","affiliations":[],"preferred":false,"id":579613,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stephens, Brail S.","contributorId":105214,"corporation":false,"usgs":true,"family":"Stephens","given":"Brail","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":579614,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hackett, Caitlin","contributorId":149797,"corporation":false,"usgs":false,"family":"Hackett","given":"Caitlin","affiliations":[{"id":12557,"text":"University of Florida, FLREC","active":true,"usgs":false}],"preferred":false,"id":579615,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70159580,"text":"70159580 - 2015 - Hydrogeochemical effects of a bulkhead in the Dinero mine tunnel, Sugar Loaf mining district, near Leadville, Colorado","interactions":[],"lastModifiedDate":"2018-09-04T15:44:27","indexId":"70159580","displayToPublicDate":"2015-11-10T16:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":835,"text":"Applied Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Hydrogeochemical effects of a bulkhead in the Dinero mine tunnel, Sugar Loaf mining district, near Leadville, Colorado","docAbstract":"The Dinero mine drainage tunnel is an abandoned, draining mine adit near Leadville, Colorado, that has an adverse effect on downstream water quality and aquatic life. In 2009, a bulkhead was constructed (creating a mine pool and increasing water-table elevations behind the tunnel) to limit drainage from the tunnel and improve downstream water quality. The goal of this study was to document changes to hydrology and water quality resulting from bulkhead emplacement, and to understand post-bulkhead changes in source water and geochemical processes that control mine-tunnel discharge and water quality. Comparison of pre-and post-bulkhead hydrology and water quality indicated that tunnel discharge and zinc and manganese loads decreased by up to 97 percent at the portal of Dinero tunnel and at two downstream sites (LF-537 and LF-580). However, some water-quality problems persisted at LF-537 and LF-580 during high-flow events and years, indicating the effects of the remaining mine waste in the area. In contrast, post-bulkhead water quality degraded at three upstream stream sites and a draining mine tunnel (Nelson tunnel). Water-quality degradation in the streams likely occurred from increased contributions of mine-pool groundwater to the streams. In contrast, water-quality degradation in the Nelson tunnel was likely from flow of mine-pool water along a vein that connects the Nelson tunnel to mine workings behind the Dinero tunnel bulkhead. Principal components analysis, mixing analysis, and inverse geochemical modeling using PHREEQC indicated that mixing and geochemical reactions (carbonate dissolution during acid weathering, precipitation of goethite and birnessite, and sorption of zinc) between three end-member water types generally explain the pre-and post-bulkhead water composition at the Dinero and Nelson tunnels. The three end members were (1) a relatively dilute groundwater having low sulfate and trace element concentrations; (2) mine pool water, and (3) water that flowed from a structure in front of the bulkhead after bulkhead emplacement. Both (2) and (3) had high sulfate and trace element concentrations. These results indicate how analysis of monitoring information can be used to understand hydrogeochemical changes resulting from bulkhead emplacement. This understanding, in turn, can help inform future decisions on the disposition of the remaining mine waste and water-quality problems in the area.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.apgeochem.2015.03.002","usgsCitation":"Walton-Day, K., and Mills, T.J., 2015, Hydrogeochemical effects of a bulkhead in the Dinero mine tunnel, Sugar Loaf mining district, near Leadville, Colorado: Applied Geochemistry, v. 62, p. 61-74, https://doi.org/10.1016/j.apgeochem.2015.03.002.","productDescription":"14 p.","startPage":"61","endPage":"74","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057803","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":311176,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","county":"Lake County","otherGeospatial":"Sugar Loaf Mining District","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.3974380493164,\n 39.236109077098135\n ],\n [\n -106.3974380493164,\n 39.26934111143279\n ],\n [\n -106.36722564697266,\n 39.26934111143279\n ],\n [\n -106.36722564697266,\n 39.236109077098135\n ],\n [\n -106.3974380493164,\n 39.236109077098135\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"62","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56431534e4b0aafbcd017fb0","contributors":{"authors":[{"text":"Walton-Day, Katherine 0000-0002-9146-6193 kwaltond@usgs.gov","orcid":"https://orcid.org/0000-0002-9146-6193","contributorId":1245,"corporation":false,"usgs":true,"family":"Walton-Day","given":"Katherine","email":"kwaltond@usgs.gov","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":false,"id":579558,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mills, Taylor J. 0000-0001-7252-0521 tmills@usgs.gov","orcid":"https://orcid.org/0000-0001-7252-0521","contributorId":4658,"corporation":false,"usgs":true,"family":"Mills","given":"Taylor","email":"tmills@usgs.gov","middleInitial":"J.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":579559,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70159182,"text":"sim3341 - 2015 - Seabed maps showing topography, ruggedness, backscatter intensity, sediment mobility, and the distribution of geologic substrates in Quadrangle 6 of the Stellwagen Bank National Marine Sanctuary Region offshore of Boston, Massachusetts","interactions":[],"lastModifiedDate":"2026-04-02T18:55:39.361302","indexId":"sim3341","displayToPublicDate":"2015-11-10T15:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3341","title":"Seabed maps showing topography, ruggedness, backscatter intensity, sediment mobility, and the distribution of geologic substrates in Quadrangle 6 of the Stellwagen Bank National Marine Sanctuary Region offshore of Boston, Massachusetts","docAbstract":"The U.S. Geological Survey (USGS), in cooperation with the National Oceanic and Atmospheric Administration's National Marine Sanctuary Program, has conducted seabed mapping and related research in the Stellwagen Bank National Marine Sanctuary (SBNMS) region since 1993. The area is approximately 3,700 square kilometers (km2) and is subdivided into 18 quadrangles. Seven maps, at a scale of 1:25,000, of quadrangle 6 (211 km2) depict seabed topography, backscatter, ruggedness, geology, substrate mobility, mud content, and areas dominated by fine-grained or coarse-grained sand. Interpretations of bathymetric and seabed backscatter imagery, photographs, video, and grain-size analyses were used to create the geology-based maps. In all, data from 420 stations were analyzed, including sediment samples from 325 locations. The seabed geology map shows the distribution of 10 substrate types ranging from boulder ridges to immobile, muddy sand to mobile, rippled sand. Mapped substrate types are defined on the basis of sediment grain-size composition, surface morphology, sediment layering, the mobility or immobility of substrate surfaces, and water depth range. This map series is intended to portray the major geological elements (substrates, topographic features, processes) of environments within quadrangle 6. Additionally, these maps will be the basis for the study of the ecological requirements of invertebrate and vertebrate species that utilize these substrates and guide seabed management in the region.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3341","collaboration":"Prepared in cooperation with the National Oceanic and Atmospheric Administration","usgsCitation":"Valentine, P.C., and Gallea, L.B., 2015, Seabed maps showing topography, ruggedness, backscatter intensity, sediment mobility, and the distribution of geologic substrates in quadrangle 6 of the Stellwagen Bank National Marine Sanctuary region offshore of Boston, Massachusetts: U.S. Geological Survey Scientific Investigations Map 3341, 10 sheets, scale 1:25,000, and 21-p. pamphlet, https://dx.doi.org/10.3133/sim3341.","productDescription":"Report: vii, 21 p.; 10 Plates: 28.0 x 36.0 inches; Table; Spatial Data","numberOfPages":"34","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-026747","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":426835,"rank":18,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/sim3515","text":"Scientific Investigations Map 3515","linkHelpText":"- Seabed Maps Showing Topography, Ruggedness, Backscatter Intensity, Sediment Mobility, and the Distribution of Geologic Substrates in Quadrangle 5 of the Stellwagen Bank National Marine Sanctuary Region Offshore of Boston, Massachusetts"},{"id":311079,"rank":17,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sim/3341/data/SIM3341_stations_geology.zip","text":"Station location data and metadata","size":"0.3 MB","linkFileType":{"id":6,"text":"zip"},"description":"SIM 3341"},{"id":311078,"rank":16,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sim/3341/data/bathy/SIM3341_13mbathy.zip","text":"Bathymetry data and metadata","size":"2.5 MB","linkFileType":{"id":6,"text":"zip"},"description":"SIM 3341"},{"id":311077,"rank":15,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sim/3341/data/SIM3341_1m_contours.zip","text":"1-meter contour data and metadata","size":"0.6 MB","linkFileType":{"id":6,"text":"zip"},"description":"SIM 3341"},{"id":311027,"rank":14,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sim/3341/data/SIM3341_geologic_interp.zip","text":"Geologic interpretation data and metadata","size":"0.6 MB","linkFileType":{"id":6,"text":"zip"},"description":"SIM 3341"},{"id":311026,"rank":13,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sim/3341/downloads/sim3341_table4.xlsx","text":"Table 4 - Sediment sample grain-size analyses and assignment to geologic substrates","size":"136 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIM 3341"},{"id":311025,"rank":12,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3341/downloads/sim3341_mapG.pdf","text":"Map G - Distribution of substrate mud content","size":"1.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3341","linkHelpText":"(28” x 36”)"},{"id":311024,"rank":11,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3341/downloads/sim3341_mapF.pdf","text":"Map F - Distribution of fine- and coarse-grained sand","size":"1.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3341","linkHelpText":"(28” x 36”)"},{"id":311023,"rank":10,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3341/downloads/sim3341_mapE.pdf","text":"Map E - Sediment mobility","size":"1.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3341","linkHelpText":"(28” x 36”)"},{"id":311022,"rank":9,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3341/downloads/sim3341_mapD_sheet4.pdf","text":"Map D, Distribution of geologic substrates, Sheet 4 - Seabed geology and sun-illuminated topography","size":"4.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3341","linkHelpText":"(28” x 36”)"},{"id":311021,"rank":8,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3341/downloads/sim3341_mapD_sheet3.pdf","text":"Map D, Distribution of geologic substrates, Sheet 3 - Seabed geology and station data types","size":"1.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3341","linkHelpText":"(28” x 36”)"},{"id":311020,"rank":7,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3341/downloads/sim3341_mapD_sheet2.pdf","text":"Map D, Distribution of geologic substrates, Sheet 2 - Seabed geology and stations","size":"1.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3341","linkHelpText":"(28” x 38.5”)"},{"id":311019,"rank":6,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3341/downloads/sim3341_mapD_sheet1.pdf","text":"Map D, Distribution of geologic substrates, Sheet 1 - Seabed geology","size":"1.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3341","linkHelpText":"(28” x 36”)"},{"id":311017,"rank":5,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3341/downloads/sim3341_mapC.pdf","text":"Map C - Backscatter intensity and sun-illuminated topography","size":"3.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3341","linkHelpText":"(28” x 36”)"},{"id":311016,"rank":4,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3341/downloads/sim3341_mapB.pdf","text":"Map B - Seabed ruggedness","size":"1.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3341","linkHelpText":"(28” x 36”)"},{"id":311015,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3341/downloads/sim3341_mapA.pdf","text":"Map A - Sun-illuminated topography and boulder ridges","size":"4.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3341","linkHelpText":"(28” x 36”)"},{"id":502034,"rank":20,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/sim3544","text":"Scientific Investigations Map 3544","linkHelpText":"- Seabed Maps Showing Topography, Ruggedness, Backscatter Intensity, Sediment Mobility, and the Distribution of Geologic Substrates in Quadrangle 3 of the Stellwagen Bank National Marine Sanctuary Region Offshore of Boston, Massachusetts"},{"id":465154,"rank":19,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/sim3530","text":"Scientific Investigations Map 3530","linkHelpText":"- Seabed Maps Showing Topography, Ruggedness, Backscatter Intensity, Sediment Mobility, and the Distribution of Geologic Substrates in Quadrangle 2 of the Stellwagen Bank National Marine Sanctuary Region Offshore of Boston, Massachusetts"},{"id":311014,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3341/sim3341.pdf","text":"Pamphlet","size":"6.79 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3341"},{"id":311013,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3341/coverthb.jpg"}],"country":"United States","state":"Massachusetts","city":"Boston","otherGeospatial":"Stellwagen Bank National Marine Sanctuary","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -70.565185546875,\n 42.09822241118974\n ],\n [\n -70.565185546875,\n 42.64204079304428\n ],\n [\n -69.993896484375,\n 42.64204079304428\n ],\n [\n -69.993896484375,\n 42.09822241118974\n ],\n [\n -70.565185546875,\n 42.09822241118974\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Coastal and Marine Geology Program Coordinator
U.S. Geological Survey
13 National Center
Reston, VA 20192
http://marine.usgs.gov
The U.S. Geological Survey (USGS) analyzes mineral and metal supply chains to identify and describe major components of material flows from ore extraction, through intermediate forms, to a final product. Supply chain analyses may be used to identify risks to the United States associated with the supply of critical and strategic minerals and metals and to provide greater supply chain transparency so that policymakers have the fact-based information needed to formulate public policy. This fact sheet focuses on the gold supply chain.
\nThe USGS National Minerals Information Center (NMIC) has been asked by governmental and non-governmental organizations to provide information about tantalum, tin, tungsten, and gold (collectively known as “3TG minerals” ) processing facilities worldwide in response to U.S. legislation aimed at identifying and removing the supply chain links associated with the trade of these metals and minerals among armed groups in the Democratic Republic of the Congo (DRC) and adjacent countries. Post-beneficiation processing plants (generally called smelters and refineries) for tantalum, tin, and tungsten (3T) mineral ores and concentrates were identified by company and industry association representatives as being the link in the 3T mineral supply chain through which these minerals can be traced to their source of origin (mine). Tungsten processing plants were the subject of the first fact sheet in a series of USGS reports about 3TG minerals, which was published by the NMIC in August 2014 (Bermúdez-Lugo, 2014). Background information about historical conditions and the voluntary due diligence of multinational stakeholders for minerals from conflict-affected and high-risk areas is presented in the tungsten fact sheet. The current fact sheet, the fourth and last in the series about 3TG minerals, focuses on the gold supply chain.
\nProcessing of the 3T mineral concentrates requires substantial infrastructure and capital and generally is done at relatively few specialized facilities that are not located at the mine site; primary and secondary processors typically are at separate locations. Gold, however, can easily be processed into semi-refined products at or near the mine site and has a high unit value in any form, which allows it to be readily exported through undocumented channels, making it more difficult to track to the mine or region of origin. To put this in perspective, 30 kilograms (66 pounds) of 83 percent pure gold (20 carat) would form a cube measuring 12 centimeters per side (about the size of a small tissue box) and, at a price of $1,200 per ounce, would be worth nearly $1 million. By contrast, the equivalent value of tungsten concentrates would weigh about 45 metric tons (t) (100,000 pounds). Once conflict sourced gold has been combined with gold from other mines and scrap at a refiner, there is no feasible way to distinguish the source of the gold. Thus, once the gold leaves the immediate area of production, it is nearly indistinguishable from gold products mined in other areas.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20153075","usgsCitation":"George, M.W., 2015, Conflict minerals from the Democratic Republic of the Congo--Gold supply chain (ver. 1.1, December 10, 2015): U.S. Geological Survey Fact Sheet, 4 p., https://dx.doi.org/10.3133/fs20153075.","productDescription":"4 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068950","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":312105,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/fs/2015/3075/versionHist.txt","description":"FS 2015-3075"},{"id":311131,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2015/3075/fs20153075.pdf","text":"Report","size":"2.93 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2015-3075"},{"id":311130,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2015/3075/coverthb2.jpg"}],"country":"Democratic Republic of Congo","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[30.83386,3.50917],[30.77335,2.33988],[31.17415,2.20447],[30.85267,1.8494],[30.46851,1.58381],[30.08615,1.06231],[29.87578,0.59738],[29.8195,-0.20531],[29.58784,-0.58741],[29.57947,-1.34131],[29.29189,-1.62006],[29.25483,-2.21511],[29.11748,-2.29221],[29.02493,-2.83926],[29.27638,-3.29391],[29.34,-4.49998],[29.51999,-5.41998],[29.41999,-5.94],[29.62003,-6.52002],[30.2,-7.07998],[30.74002,-8.34001],[30.34609,-8.23826],[29.00291,-8.40703],[28.73487,-8.52656],[28.44987,-9.16492],[28.67368,-9.60592],[28.49607,-10.78988],[28.37225,-11.79365],[28.64242,-11.97157],[29.34155,-12.36074],[29.616,-12.17889],[29.69961,-13.25723],[28.93429,-13.24896],[28.52356,-12.6986],[28.15511,-12.27248],[27.3888,-12.13275],[27.16442,-11.60875],[26.55309,-11.92444],[25.75231,-11.78497],[25.41812,-11.33094],[24.78317,-11.23869],[24.31452,-11.26283],[24.25716,-10.95199],[23.91222,-10.92683],[23.45679,-10.86786],[22.83735,-11.01762],[22.4028,-10.99308],[22.15527,-11.0848],[22.20875,-9.8948],[21.87518,-9.52371],[21.8018,-8.90871],[21.94913,-8.3059],[21.74646,-7.92008],[21.72811,-7.29087],[20.51475,-7.29961],[20.60182,-6.93932],[20.09162,-6.94309],[20.03772,-7.11636],[19.4175,-7.15543],[19.16661,-7.73818],[19.01675,-7.98825],[18.46418,-7.84701],[18.13422,-7.98768],[17.47297,-8.06855],[17.09,-7.54569],[16.86019,-7.2223],[16.57318,-6.62264],[16.32653,-5.87747],[13.3756,-5.86424],[13.02487,-5.98439],[12.73517,-5.96568],[12.32243,-6.10009],[12.18234,-5.78993],[12.43669,-5.6843],[12.468,-5.24836],[12.63161,-4.99127],[12.99552,-4.7811],[13.25824,-4.88296],[13.60023,-4.50014],[14.14496,-4.51001],[14.20903,-4.79309],[14.5826,-4.97024],[15.17099,-4.34351],[15.75354,-3.85516],[16.00629,-3.53513],[15.9728,-2.71239],[16.40709,-1.74093],[16.86531,-1.22582],[17.52372,-0.74383],[17.63864,-0.42483],[17.66355,-0.05808],[17.82654,0.28892],[17.77419,0.85566],[17.89884,1.74183],[18.09428,2.36572],[18.39379,2.90044],[18.45307,3.50439],[18.54298,4.20179],[18.93231,4.70951],[19.46778,5.03153],[20.29068,4.69168],[20.92759,4.32279],[21.65912,4.22434],[22.40512,4.02916],[22.70412,4.63305],[22.84148,4.71013],[23.29721,4.60969],[24.41053,5.10878],[24.80503,4.89725],[25.12883,4.92724],[25.2788,5.17041],[25.65046,5.25609],[26.40276,5.15087],[27.04407,5.12785],[27.37423,5.23394],[27.97998,4.40841],[28.42899,4.28715],[28.69668,4.45508],[29.15908,4.38927],[29.716,4.6008],[29.9535,4.1737],[30.83386,3.50917]]]},\"properties\":{\"name\":\"Democratic Republic of the Congo\"}}]}","edition":"Originally posted November 10, 2015; Version 1.1: December 10, 2015","contact":"Director, National Minerals Information Center
U.S. Geological Survey
12201 Sunrise Valley Drive
988 National Center
Reston, VA 20192
Email: nmicrecordsmgt@usgs.gov
Or visit the USGS Minerals Information Web site at
http://minerals.usgs.gov/minerals/
Widespread bat fatalities at industrial wind turbines are a conservation issue with the potential to inhibit efficient use of an abundant source of energy. Bat fatalities can be reduced by altering turbine operations, but such curtailment decreases turbine efficiency. If additional ways of reducing bat fatalities at wind turbines were available such tradeoffs might not be needed. Based on the facts that bats perceive distant objects primarily through vision and can see in very dim lighting conditions, and the possibility that bats might interact with turbines after approaching them as they would trees, we propose a novel method of reducing bat activity at wind turbines: illumination of the structure with dim light. As a first step toward assessing this approach, we illuminated trees with dim flickering ultraviolet (UV) light in areas frequented by Hawaiian hoary bats Lasiurus cinereus semotus, an endangered subspecies affected by wind turbines. We used a repeated-measures design to quantify bat activity near trees with acoustic detectors and thermal video cameras in the presence and absence of UV illumination, while concurrently monitoring insect numbers. Results indicate that dim UV reduces bat activity despite an increase in insect numbers. Experimental treatment did not completely inhibit bat activity near trees, nor did all measures of bat activity show statistically significant differences due to high variance in bat activity among sites. However, the observed decreases in bat activity with dim UV illumination justify further testing of this method as a means to reduce bat fatalities at wind turbines.
","language":"English","publisher":"Inter Research","doi":"10.3354/esr00694","usgsCitation":"Gorresen, P.M., Cryan, P.M., Dalton, D.C., Wolf, S., Johnson, J.A., Todd, C.M., and Bonaccorso, F.J., 2015, Dim ultraviolet light as a means of deterring activity by the Hawaiian hoary bat Lasiurus cinereus semotus: Endangered Species Research, v. 28, no. 3, p. 249-257, https://doi.org/10.3354/esr00694.","productDescription":"9 p.","startPage":"249","endPage":"257","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"2014-09-08","temporalEnd":"2014-10-16","ipdsId":"IP-066322","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":471654,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/esr00694","text":"Publisher Index Page"},{"id":311166,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","volume":"28","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56431532e4b0aafbcd017fa2","contributors":{"authors":[{"text":"Gorresen, P. Marcos mgorresen@usgs.gov","contributorId":3975,"corporation":false,"usgs":true,"family":"Gorresen","given":"P.","email":"mgorresen@usgs.gov","middleInitial":"Marcos","affiliations":[],"preferred":false,"id":579228,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cryan, Paul M. 0000-0002-2915-8894 cryanp@usgs.gov","orcid":"https://orcid.org/0000-0002-2915-8894","contributorId":2356,"corporation":false,"usgs":true,"family":"Cryan","given":"Paul","email":"cryanp@usgs.gov","middleInitial":"M.","affiliations":[{"id":547,"text":"Rocky Mountain Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":579229,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dalton, David C.","contributorId":84674,"corporation":false,"usgs":true,"family":"Dalton","given":"David","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":579230,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wolf, Sandy","contributorId":147943,"corporation":false,"usgs":false,"family":"Wolf","given":"Sandy","email":"","affiliations":[{"id":16960,"text":"Bat Research and Consulting","active":true,"usgs":false}],"preferred":false,"id":579231,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Johnson, Jessica A.","contributorId":149712,"corporation":false,"usgs":false,"family":"Johnson","given":"Jessica","email":"","middleInitial":"A.","affiliations":[{"id":13351,"text":"University of Hawaii Cooperative Studies Unit","active":true,"usgs":false}],"preferred":false,"id":579232,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Todd, Christopher M.","contributorId":64548,"corporation":false,"usgs":true,"family":"Todd","given":"Christopher","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":579233,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bonaccorso, Frank J. fbonaccorso@usgs.gov","contributorId":3088,"corporation":false,"usgs":true,"family":"Bonaccorso","given":"Frank","email":"fbonaccorso@usgs.gov","middleInitial":"J.","affiliations":[{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"preferred":false,"id":579227,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70159525,"text":"70159525 - 2015 - Potential estrogenic effects of wastewaters on gene expression in Pimephales promelas and fish assemblages in streams of southeastern New York","interactions":[],"lastModifiedDate":"2018-08-09T12:37:29","indexId":"70159525","displayToPublicDate":"2015-11-10T14:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1571,"text":"Environmental Toxicology and Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Potential estrogenic effects of wastewaters on gene expression in Pimephales promelas and fish assemblages in streams of southeastern New York","docAbstract":"Direct linkages between endocrine-disrupting compounds (EDCs) from municipal and industrial wastewaters and impacts on wild fish assemblages are rare. The levels of plasma vitellogenin (Vtg) and Vtg messenger ribonucleic acid (mRNA) in male fathead minnows (Pimephales promelas) exposed to wastewater effluents and dilutions of 17α-ethinylestradiol (EE2), estrogen activity, and fish assemblages in 10 receiving streams were assessed to improve understanding of important interrelations. Results from 4-d laboratory assays indicate that EE2, plasma Vtg concentration, and Vtg gene expression in fathead minnows, and 17β-estradiol equivalents (E2Eq values) were highly related to each other (R2 = 0.98–1.00). Concentrations of E2Eq in most effluents did not exceed 2.0 ng/L, which was possibly a short-term exposure threshold for Vtg gene expression in male fathead minnows. Plasma Vtg in fathead minnows only increased significantly (up to 1136 μg/mL) in 2 wastewater effluents. Fish assemblages were generally unaffected at 8 of 10 study sites, yet the density and biomass of 79% to 89% of species populations were reduced (63–68% were reduced significantly) in the downstream reach of 1 receiving stream. These results, and moderate to high E2Eq concentrations (up to 16.1 ng/L) observed in effluents during a companion study, suggest that estrogenic wastewaters can potentially affect individual fish, their populations, and entire fish communities in comparable systems across New York, USA.
","language":"English","publisher":"SETAC Press","doi":"10.1002/etc.3120","usgsCitation":"Baldigo, B.P., George, S.D., Phillips, P., Hemming, J.D., Denslow, N., and Kroll, K.J., 2015, Potential estrogenic effects of wastewaters on gene expression in Pimephales promelas and fish assemblages in streams of southeastern New York: Environmental Toxicology and Chemistry, v. 34, no. 12, p. 2803-2815, https://doi.org/10.1002/etc.3120.","productDescription":"13 p.","startPage":"2803","endPage":"2815","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-043001","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":471656,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/etc.3120","text":"Publisher Index Page"},{"id":311165,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"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 -73.8336181640625,\n 41.25406487942273\n ],\n [\n -73.8336181640625,\n 41.53119809844284\n ],\n [\n -73.56170654296875,\n 41.53119809844284\n ],\n [\n -73.56170654296875,\n 41.25406487942273\n ],\n [\n -73.8336181640625,\n 41.25406487942273\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.267333984375,\n 42.037054301883806\n ],\n [\n -75.267333984375,\n 42.42142901536395\n ],\n [\n -74.14398193359375,\n 42.42142901536395\n ],\n [\n -74.14398193359375,\n 42.037054301883806\n ],\n [\n -75.267333984375,\n 42.037054301883806\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"34","issue":"12","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2015-10-01","publicationStatus":"PW","scienceBaseUri":"56431535e4b0aafbcd017fb4","contributors":{"authors":[{"text":"Baldigo, Barry P. 0000-0002-9862-9119 bbaldigo@usgs.gov","orcid":"https://orcid.org/0000-0002-9862-9119","contributorId":1234,"corporation":false,"usgs":true,"family":"Baldigo","given":"Barry","email":"bbaldigo@usgs.gov","middleInitial":"P.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":579382,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"George, Scott D. 0000-0002-8197-1866 sgeorge@usgs.gov","orcid":"https://orcid.org/0000-0002-8197-1866","contributorId":3014,"corporation":false,"usgs":true,"family":"George","given":"Scott","email":"sgeorge@usgs.gov","middleInitial":"D.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":579384,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Phillips, Patrick J. pjphilli@usgs.gov","contributorId":149753,"corporation":false,"usgs":true,"family":"Phillips","given":"Patrick J.","email":"pjphilli@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":false,"id":579383,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hemming, Joceyln D. C.","contributorId":149754,"corporation":false,"usgs":false,"family":"Hemming","given":"Joceyln","email":"","middleInitial":"D. C.","affiliations":[{"id":17815,"text":"Wisconsin State Laboratory of Hygiene","active":true,"usgs":false}],"preferred":false,"id":579385,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Denslow, Nancy D.","contributorId":72831,"corporation":false,"usgs":true,"family":"Denslow","given":"Nancy D.","affiliations":[],"preferred":false,"id":579386,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kroll, Kevin J.","contributorId":82051,"corporation":false,"usgs":true,"family":"Kroll","given":"Kevin","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":579387,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70162025,"text":"70162025 - 2015 - Agencies collaborate, develop a cyanobacteria assessment network","interactions":[],"lastModifiedDate":"2018-08-10T09:56:46","indexId":"70162025","displayToPublicDate":"2015-11-10T14:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3879,"text":"Eos, Earth and Space Science News","active":true,"publicationSubtype":{"id":10}},"title":"Agencies collaborate, develop a cyanobacteria assessment network","docAbstract":"Cyanobacteria are a genetically diverse group of photosynthetic microorganisms that occupy a broad range of habitats on land and water all over the world. They release toxins that can cause lung and skin irritation, alter the taste and odor of potable water, and cause human and animal illness. Cyanobacteria blooms occur worldwide, and climate change may increase the frequency, duration, and extent of these bloom events.
\nRapid detection of potentially harmful blooms is essential to protect humans and animals from exposure. Information about potential for exposure, such as bloom duration, frequency, and extent, is especially critical for developing environmental management decisions during periods of limited resources and funding.
\nThe National Research Council (NRC) report Exposure Science in the 21st Century suggested that effectively assessing and mitigating exposures requires techniques for rapid measurement of a stressor, such as an algal bloom, across diverse geographic, temporal, and biologic scales (e.g., various bloom concentrations) and an enhanced infrastructure to address threats [NRC, 2012]. The report specifically calls for approaches that use diverse information, such as satellite remote sensing, to identify and understand exposures that may pose a threat to ecosystems or human health.
\nA collaborative effort integrates the work of the U.S. Environmental Protection Agency (EPA), NASA, the National Oceanic and Atmospheric Administration (NOAA), and the U.S. Geological Survey (USGS) to provide an approach for using satellite ocean color capabilities in U.S. fresh and brackish water quality management decisions. The overarching goal of this collaborative project is to detect and quantify cyanobacteria blooms using satellite data records in order to support the environmental management and public use of U.S. lakes and reservoirs.
\nSatellite remote sensing tools may enable policy makers and environmental managers to assess the sustainability of watershed ecosystems and the services they provide, now and in the future. Satellite technology allows us to develop early-warning indicators of cyanobacteria blooms at the local scale while maintaining continuous national coverage.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2015EO038809","usgsCitation":"Schaeffer, B., Loftin, K.A., Stumpf, R., and Werdell, P., 2015, Agencies collaborate, develop a cyanobacteria assessment network: Eos, Earth and Space Science News, v. 96, HTML Document, https://doi.org/10.1029/2015EO038809.","productDescription":"HTML Document","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-063681","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":471657,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2015eo038809","text":"Publisher Index Page"},{"id":314537,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"96","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56a0bdc5e4b0961cf280dc0a","contributors":{"authors":[{"text":"Schaeffer, Blake A.","contributorId":152172,"corporation":false,"usgs":false,"family":"Schaeffer","given":"Blake A.","affiliations":[{"id":6784,"text":"US EPA","active":true,"usgs":false}],"preferred":false,"id":588361,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Loftin, Keith A. 0000-0001-5291-876X kloftin@usgs.gov","orcid":"https://orcid.org/0000-0001-5291-876X","contributorId":868,"corporation":false,"usgs":true,"family":"Loftin","given":"Keith","email":"kloftin@usgs.gov","middleInitial":"A.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":588360,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stumpf, Richard P.","contributorId":7739,"corporation":false,"usgs":true,"family":"Stumpf","given":"Richard P.","affiliations":[],"preferred":false,"id":588362,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Werdell, P. Jeremy","contributorId":152173,"corporation":false,"usgs":false,"family":"Werdell","given":"P. Jeremy","affiliations":[{"id":7049,"text":"NASA Goddard Space Flight Center","active":true,"usgs":false}],"preferred":false,"id":588363,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70159497,"text":"70159497 - 2015 - Conservation planning for offsetting the impacts of development: a case study of biodiversity and renewable energy in the Mojave Desert","interactions":[],"lastModifiedDate":"2015-11-10T13:07:21","indexId":"70159497","displayToPublicDate":"2015-11-10T14:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Conservation planning for offsetting the impacts of development: a case study of biodiversity and renewable energy in the Mojave Desert","docAbstract":"Balancing society’s competing needs of development and conservation requires careful consideration of tradeoffs. Renewable energy development and biodiversity conservation are often considered beneficial environmental goals. The direct footprint and disturbance of renewable energy, however, can displace species’ habitat and negatively impact populations and natural communities if sited without ecological consideration. Offsets have emerged as a potentially useful tool to mitigate residual impacts after trying to avoid, minimize, or restore affected sites. Yet the problem of efficiently designing a set of offset sites becomes increasingly complex where many species or many sites are involved. Spatial conservation prioritization tools are designed to handle this problem, but have seen little application to offset siting and analysis. To address this need we designed an offset siting support tool for the Desert Renewable Energy Conservation Plan (DRECP) of California, and present a case study of hypothetical impacts from solar development in the Western Mojave subsection. We compare two offset scenarios designed to mitigate a hypothetical 15,331 ha derived from proposed utility-scale solar energy development (USSED) projects. The first scenario prioritizes offsets based precisely on impacted features, while the second scenario offsets impacts to maximize biodiversity conservation gains in the region. The two methods only agree on 28% of their prioritized sites and differ in meeting species-specific offset goals. Differences between the two scenarios highlight the importance of clearly specifying choices and priorities for offset siting and mitigation in general. Similarly, the effects of background climate and land use change may lessen the durability or effectiveness of offsets if not considered. Our offset siting support tool was designed specifically for the DRECP area, but with minor code modification could work well in other offset analyses, and could provide continuing support for a potentially innovative mitigation solution to environmental impacts.
","language":"English","publisher":"Public Library of Science (PLOS)","doi":"10.1371/journal.pone.0140226","usgsCitation":"Kreitler, J.R., Schloss, C.A., Soong, O., Hannah, L., and Davis, F., 2015, Conservation planning for offsetting the impacts of development: a case study of biodiversity and renewable energy in the Mojave Desert: PLoS ONE, v. 10, no. 11, e0140226; 15 p., https://doi.org/10.1371/journal.pone.0140226.","productDescription":"e0140226; 15 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-058617","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":471658,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0140226","text":"Publisher Index Page"},{"id":311163,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Mojave Desert","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.03759765625,\n 32.62087018318113\n ],\n [\n -116.488037109375,\n 33.26624989076275\n ],\n [\n -115.697021484375,\n 33.8339199536547\n ],\n [\n -117.454833984375,\n 34.31621838080741\n ],\n [\n -118.817138671875,\n 34.8047829195724\n ],\n [\n -117.88330078125,\n 35.69299463209881\n ],\n [\n -118.38867187500001,\n 37.212831514455964\n ],\n [\n -117.960205078125,\n 37.54457732085582\n ],\n [\n -114.63134765625001,\n 35.02099970111467\n ],\n [\n -114.12597656249999,\n 34.32529192442733\n ],\n [\n -114.58740234375,\n 33.44977658311846\n ],\n [\n -114.664306640625,\n 33.03629817885956\n ],\n [\n -114.488525390625,\n 33.02708758002874\n ],\n [\n -114.488525390625,\n 32.79651010951669\n ],\n [\n -114.67529296874999,\n 32.694865977875075\n ],\n [\n -116.03759765625,\n 32.62087018318113\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"10","issue":"11","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-11-03","publicationStatus":"PW","scienceBaseUri":"56431532e4b0aafbcd017f9e","contributors":{"authors":[{"text":"Kreitler, Jason R. 0000-0002-0243-5281 jkreitler@usgs.gov","orcid":"https://orcid.org/0000-0002-0243-5281","contributorId":4050,"corporation":false,"usgs":true,"family":"Kreitler","given":"Jason","email":"jkreitler@usgs.gov","middleInitial":"R.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":579234,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schloss, Carrie A.","contributorId":149713,"corporation":false,"usgs":false,"family":"Schloss","given":"Carrie","email":"","middleInitial":"A.","affiliations":[{"id":17788,"text":"The Nature Conservancy of California","active":true,"usgs":false}],"preferred":false,"id":579235,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Soong, Oliver","contributorId":147794,"corporation":false,"usgs":false,"family":"Soong","given":"Oliver","email":"","affiliations":[{"id":16936,"text":"University of California Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":579236,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hannah, Lee","contributorId":149715,"corporation":false,"usgs":false,"family":"Hannah","given":"Lee","affiliations":[{"id":16938,"text":"Conservation International","active":true,"usgs":false}],"preferred":false,"id":579239,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Davis, Frank W.","contributorId":36894,"corporation":false,"usgs":true,"family":"Davis","given":"Frank W.","affiliations":[],"preferred":false,"id":579237,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70155507,"text":"ofr20151139 - 2015 - Hydraulic laboratory testing of Sontek-IQ Plus","interactions":[],"lastModifiedDate":"2015-11-10T13:12:47","indexId":"ofr20151139","displayToPublicDate":"2015-11-10T14:00:00","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":"2015-1139","title":"Hydraulic laboratory testing of Sontek-IQ Plus","docAbstract":"The SonTek-IQ Plus (IQ Plus) is a bottom-mounted Doppler instrument used for the measurement of water depth and velocity. Evaluation testing of the IQ Plus was performed to assess the accuracy of water depth, discharge, and velocity measurements. The IQ Plus met the manufacturer’s specifications and the U.S. Geological Survey (USGS) standard for depth accuracy measurement when the unit was installed, according to the manufacturer’s instructions, at 0 degrees pitch and roll. However, because of the limited depth testing conducted, the depth measurement is not recommended as a primary stage measurement. The IQ Plus was tested in a large indoor tilting flume in a 5-foot (ft) wide, approximately 2.3-ft deep section with mean velocities of 0.5, 1, 2, and 3 ft per second. Four IQ Plus instruments using firmware 1.52 tested for water-discharge accuracy using SonTek’s “theoretical” discharge method had a negative bias of -2.4 to -11.6 percent when compared with discharge measured with a SonTek FlowTracker and the midsection discharge method. The IQ Pluses with firmware 1.52 did not meet the manufacturer’s specification of +/-1 percent for measuring velocity. Three IQ Pluses using firmware 1.60 and SonTek’s “theoretical” method had a difference of -1.6 to -7.9 percent when compared with discharge measured with a SonTek FlowTracker and the midsection method. Mean-velocity measurements with firmware 1.60 met the manufacturer’s specification and Price Type AA meter accuracy requirements when compared with FlowTracker measurements. Because of the instrument’s velocity accuracy, the SonTek-IQ Plus with firmware 1.60 is considered acceptable for use as an index velocity instrument for the USGS. The discharge computed by the SonTek-IQ Plus during the tests had a substantial negative bias and will not be as accurate as a discharge computed with the index velocity method. The USGS does not recommend the use of undocumented computation methods, such as SonTek’s “theoretical” method for computing discharge.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151139","usgsCitation":"Fulford, J.M., and Kimball, Scott, 2015, Hydraulic laboratory testing of SonTek-IQ Plus: U.S. Geological Survey Open-File Report 2015–1139, 16 p., https://dx.doi.org/10.3133/ofr20151139.","productDescription":"vi, 16 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-065363","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":311142,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1139/ofr20151139.pdf","text":"Report","size":"1.09 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1139"},{"id":311141,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1139/coverthb.jpg"}],"contact":"Chief, Hydrologic Instrumentation Facility
U.S. Geological Survey
Building 2101
Stennis Space Center, MS 39529
http://water.usgs.gov/hif/
In a study conducted by the U.S. Geological Survey (USGS) in cooperation with the New York State Department of Environmental Conservation, water samples were collected from 4 production wells and 4 domestic wells in the Chemung River Basin, 8 production wells and 7 domestic wells in the Eastern Lake Ontario Basin, and 12 production wells and 13 domestic wells in the Lower Hudson River Basin (south of the Federal Lock and Dam at Troy) in New York. All samples were collected in June, July, and August 2013 to characterize groundwater quality in these basins. The samples were collected and processed using standard USGS procedures and were analyzed for 148 physiochemical properties and constituents, including dissolved gases, major ions, nutrients, trace elements, pesticides, volatile organic compounds, radionuclides, and indicator bacteria.
\nThe Chemung River Basin study area covers 1,744 square miles in south-central New York and encompasses the part of the Chemung River Basin that lies within New York. Two of the wells sampled in the Chemung River Basin are completed in sand and gravel, and 6 are completed in bedrock. Groundwater in the Chemung River Basin was generally of good quality, although properties and concentrations of some constituents—sodium, arsenic, aluminum, iron, manganese, radon-222, total coliform bacteria, and Escherichia coli bacteria—equaled or exceeded primary, secondary, or proposed drinking-water standards. The constituent most frequently detected in concentrations exceeding drinking-water standards (six of eight samples) was radon-222.
\nThe Eastern Lake Ontario Basin study area covers 3,225 square miles in north-central New York. The Eastern Lake Ontario Basin (between the Oswego River Basin and the St. Lawrence River Basin) includes the Mid-Northern Lake Ontario Basin, the Black River Basin, and the Chaumont River-Perch River Basin. Five of the wells sampled in the Eastern Lake Ontario Basin are completed in sand and gravel, and 10 are completed in bedrock. Groundwater in the Eastern Lake Ontario Basin was generally of good quality, although properties and concentrations of some constituents—color, pH, sodium, dissolved solids, fluoride, iron, manganese, uranium, gross-α radioactivity, radon-222, total coliform bacteria, and fecal coliform bacteria—equaled or exceeded primary, secondary, or proposed drinking-water standards. The constituent most frequently detected in concentrations exceeding drinking-water standards (10 of 15 samples) was radon-222.
\nThe Lower Hudson River Basin study area covers 5,607 square miles and encompasses the part of the Lower Hudson River Basin that lies within New York plus the parts of the Housatonic, Hackensack, Bronx, and Saugatuck River Basins that are in New York. Twelve of the wells sampled in the Lower Hudson River Basin are completed in sand-and-gravel deposits, and 13 are completed in bedrock. Groundwater in the Lower Hudson River Basin was generally of good quality, although properties and concentrations of some constituents—pH, sodium, chloride, dissolved solids, arsenic, aluminum, iron, manganese, radon-222, total coliform bacteria, fecal coliform bacteria, Escherichia coli bacteria, and heterotrophic plate count—equaled or exceeded primary, secondary, or proposed drinking-water standards. The constituent most frequently detected in concentrations exceeding drinking-water standards (20 of 25 samples) was radon-222.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151168","collaboration":"Prepared in cooperation with the New York State Department of Environmental Conservation","usgsCitation":"Scott, T.-M., Nystrom, E.A., and Reddy, J.E., 2015, Groundwater quality in the Chemung River, eastern Lake Ontario, and lower Hudson River Basins, New York, 2013: U.S. Geological Survey Open-File Report 2015–1168, 41 p., appendixes, https://dx.doi.org/10.3133/ofr20151168.","productDescription":"Report: viii, 39 p.; Appendixes: 1-2","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2013-01-01","temporalEnd":"2013-12-31","ipdsId":"IP-061358","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":310960,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1168/ofr20151168.pdf","text":"Report","size":"15.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1168"},{"id":310961,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2015/1168/appendix/ofr20151168_appendix1.xlsx","text":"Appendix 1","size":"113 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2015-1168","linkHelpText":"Results of Water-Sample Analyses, 2013"},{"id":310962,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2015/1168/appendix/ofr20151168_appendix2.xlsx","text":"Appendix 2","size":"58.5 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2015-1168","linkHelpText":"Results of Water-Sample Analyses, 2008 and 2013"},{"id":310959,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1168/coverthb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Chemung River Basin, Eastern Lake Ontario Basin, Lower Hudson River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.6845703125,\n 43.30119623257966\n ],\n [\n -76.6845703125,\n 44.41024041296011\n ],\n [\n -73.76220703125,\n 44.41024041296011\n ],\n [\n -73.76220703125,\n 43.30119623257966\n ],\n [\n -76.6845703125,\n 43.30119623257966\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.7227783203125,\n 42.00032514831621\n ],\n [\n -77.7227783203125,\n 42.44778143462245\n ],\n [\n -76.4263916015625,\n 42.44778143462245\n ],\n [\n -76.4263916015625,\n 42.00032514831621\n ],\n [\n -77.7227783203125,\n 42.00032514831621\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.817138671875,\n 40.81796653313175\n ],\n [\n -73.641357421875,\n 41.0130657870063\n ],\n [\n -73.7127685546875,\n 41.10005163093046\n ],\n [\n -73.4600830078125,\n 41.20758898181025\n ],\n [\n -73.5479736328125,\n 41.29844430929419\n ],\n [\n -73.27880859375,\n 42.742978093466434\n ],\n [\n -74.2291259765625,\n 42.90011265525328\n ],\n [\n -74.72351074218749,\n 41.364441530542244\n ],\n [\n -73.916015625,\n 41.000629848685385\n ],\n [\n -74.036865234375,\n 40.713955826286046\n ],\n [\n -73.817138671875,\n 40.81796653313175\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New York Water Science Center
U.S. Geological Survey
425 Jordan Road
Troy, NY 12180-8349
Information requests:
(518) 285-5602
or visit our Web site at:
http://ny.water.usgs.gov
Effective population size (Ne) is a key parameter for monitoring the genetic health of threatened populations because it reflects a population's evolutionary potential and risk of extinction due to genetic stochasticity. However, its application to wildlife monitoring has been limited because it is difficult to measure in natural populations. The isolated and well-studied population of grizzly bears (Ursus arctos) in the Greater Yellowstone Ecosystem provides a rare opportunity to examine the usefulness of different Ne estimators for monitoring. We genotyped 729 Yellowstone grizzly bears using 20 microsatellites and applied three single-sample estimators to examine contemporary trends in generation interval (GI), effective number of breeders (Nb) and Ne during 1982–2007. We also used multisample methods to estimate variance (NeV) and inbreeding Ne (NeI). Single-sample estimates revealed positive trajectories, with over a fourfold increase in Ne (≈100 to 450) and near doubling of the GI (≈8 to 14) from the 1980s to 2000s. NeV (240–319) and NeI (256) were comparable with the harmonic mean single-sample Ne (213) over the time period. Reanalysing historical data, we found NeV increased from ≈80 in the 1910s–1960s to ≈280 in the contemporary population. The estimated ratio of effective to total census size (Ne/Nc) was stable and high (0.42–0.66) compared to previous brown bear studies. These results support independent demographic evidence for Yellowstone grizzly bear population growth since the 1980s. They further demonstrate how genetic monitoring of Ne can complement demographic-based monitoring of Nc and vital rates, providing a valuable tool for wildlife managers.
","language":"English","publisher":"Wiley-Blackwell","doi":"10.1111/mec.13398","collaboration":"Prepared in collaboration with U.S. Fish and Wildlife Service","usgsCitation":"Kamath, P.L., Haroldson, M.A., Luikart, G., Paetkau, D., Whitman, C., and van Manen, F.T., 2015, Multiple estimates of effective population size for monitoring a long-lived vertebrate: An application to Yellowstone grizzly bears: Molecular Ecology, v. 24, no. 22, p. 5507-5521, https://doi.org/10.1111/mec.13398.","productDescription":"15 p.","startPage":"5507","endPage":"5521","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066690","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":311150,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Montana, Wyoming","otherGeospatial":"Grand Teton National Park, Yellowstone National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.181396484375,\n 42.44778143462245\n ],\n [\n -112.181396484375,\n 45.69083283645816\n ],\n [\n -108.62182617187499,\n 45.69083283645816\n ],\n [\n -108.62182617187499,\n 42.44778143462245\n ],\n [\n -112.181396484375,\n 42.44778143462245\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"24","issue":"22","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-10-28","publicationStatus":"PW","scienceBaseUri":"56431534e4b0aafbcd017fb2","contributors":{"authors":[{"text":"Kamath, Pauline L. pkamath@usgs.gov","contributorId":4517,"corporation":false,"usgs":true,"family":"Kamath","given":"Pauline","email":"pkamath@usgs.gov","middleInitial":"L.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":579569,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haroldson, Mark A. 0000-0002-7457-7676 mharoldson@usgs.gov","orcid":"https://orcid.org/0000-0002-7457-7676","contributorId":1773,"corporation":false,"usgs":true,"family":"Haroldson","given":"Mark","email":"mharoldson@usgs.gov","middleInitial":"A.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":579570,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Luikart, Gordon","contributorId":97409,"corporation":false,"usgs":false,"family":"Luikart","given":"Gordon","affiliations":[{"id":6580,"text":"University of Montana, Flathead Lake Biological Station, Polson, Montana 59860, USA","active":true,"usgs":false}],"preferred":false,"id":579571,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Paetkau, David","contributorId":97712,"corporation":false,"usgs":false,"family":"Paetkau","given":"David","email":"","affiliations":[],"preferred":false,"id":579572,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Whitman, Craig L. cwhitman@usgs.gov","contributorId":4313,"corporation":false,"usgs":true,"family":"Whitman","given":"Craig L.","email":"cwhitman@usgs.gov","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":579573,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"van Manen, Frank T. 0000-0001-5340-8489 fvanmanen@usgs.gov","orcid":"https://orcid.org/0000-0001-5340-8489","contributorId":2267,"corporation":false,"usgs":true,"family":"van Manen","given":"Frank","email":"fvanmanen@usgs.gov","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":579574,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70169021,"text":"70169021 - 2015 - Shaping species with ephemeral boundaries: The distribution and genetic structure of desert tortoise (Gopherus morafkai) in the Sonoran Desert region","interactions":[],"lastModifiedDate":"2016-03-21T12:59:44","indexId":"70169021","displayToPublicDate":"2015-11-10T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2193,"text":"Journal of Biogeography","active":true,"publicationSubtype":{"id":10}},"title":"Shaping species with ephemeral boundaries: The distribution and genetic structure of desert tortoise (Gopherus morafkai) in the Sonoran Desert region","docAbstract":"We examine the role biogeographical features played in the evolution of Morafka's desert tortoise (Gopherus morafkai) and test the hypothesis that G. morafkai maintains genetically distinct lineages associated with different Sonoran Desert biomes. Increased knowledge of the past and present distribution of the Sonoran Desert region's biota provides insight into the forces that drive and maintain its biodiversity.
\nSonoran Desert biogeographical region; Sonora and Sinaloa, Mexico and Arizona, USA.
\nWe examined wild tortoises from Mexico (n = 155) and Arizona (n = 78), spanning their known distribution. We used mtDNA sequences to reconstruct matrilineal relationships and 25 microsatellite (STR) loci for Bayesian analyses of gene flow. We performed clinal analyses on both mtDNA and STR loci to determine the position and amount of introgression where lineages co-occur. We used GIS to assess the association of genetic structuring with ecological features. We used these data in a hypothesis-driven approach to assess different models of how genetic diversity is maintained and distributed in G. morafkai.
\nGopherus morafkai was found to comprise genetically and geographically distinct ‘Sonoran’ and ‘Sinaloan’ lineages. Both lineages occurred in a relatively narrow zone of overlap in Sinaloan thornscrub, where it transitions into Sonoran desertscrub. Limited introgression occurred at the contact zone. The best-fit model suggests that these lineages diverged in parapatry where the distribution of genotypes is environment-dependent and introgression is inhibited by exogenous selection.
\nThe historically shifting ecotone between tropical deciduous forest and Sonoran desertscrub appears to be a boundary that fostered divergence between parapatric lineages of tortoises. The sharp genetic cline between the two lineages suggests that periods of isolation in temporary refugia due to Pleistocene climatic cycling influenced divergence. Despite incomplete reproductive isolation, the Sonoran and Sinaloan lineages of G. morafkai are on separate evolutionary trajectories.
","language":"English","publisher":"John Wiley & Sons Ltd.","doi":"10.1111/jbi.12664","usgsCitation":"Edwards, T., Vaughn, M., Rosen, P.C., Torres, M.C., Karl, A.E., Culver, M., and Murphy, R.W., 2015, Shaping species with ephemeral boundaries: The distribution and genetic structure of desert tortoise (Gopherus morafkai) in the Sonoran Desert region: Journal of Biogeography, v. 43, p. 484-497, https://doi.org/10.1111/jbi.12664.","productDescription":"14 p.","startPage":"484","endPage":"497","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061035","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":471659,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/jbi.12664","text":"Publisher Index Page"},{"id":319095,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico, United States","state":"Arizona, Sonora","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.896484375,\n 25.403584973186703\n ],\n [\n -108.6328125,\n 25.54244147012483\n ],\n [\n -108.52294921875,\n 25.97779895546436\n ],\n [\n -108.47900390625,\n 26.509904531413927\n ],\n [\n -108.4130859375,\n 27.137368359795584\n ],\n [\n -108.74267578125,\n 27.877928333679495\n ],\n [\n -108.83056640625,\n 28.265682390146477\n ],\n [\n -108.80859375,\n 28.786918085420226\n ],\n [\n -108.87451171875,\n 29.439597566602902\n ],\n [\n -109.3359375,\n 29.954934549656144\n ],\n [\n -109.62158203125,\n 30.467614102257855\n ],\n [\n -110.23681640625,\n 30.90222470517144\n ],\n [\n -110.58837890625,\n 31.015278981711266\n ],\n [\n -111.005859375,\n 31.316101383495624\n ],\n [\n -110.89599609375,\n 31.728167146023935\n ],\n [\n -110.4345703125,\n 32.676372772089834\n ],\n [\n -110.45654296875,\n 33.37641235124676\n ],\n [\n -110.12695312499999,\n 33.797408767572485\n ],\n [\n -110.36865234374999,\n 34.30714385628804\n ],\n [\n -110.76416015625,\n 34.813803317113155\n ],\n [\n -111.70898437499999,\n 35.02999636902566\n ],\n [\n -112.91748046874999,\n 35.47856499535729\n ],\n [\n -113.40087890624999,\n 35.55010533588552\n ],\n [\n -113.92822265625,\n 35.53222622770337\n ],\n [\n -114.14794921875,\n 35.51434313431818\n ],\n [\n -114.49951171875,\n 35.31736632923788\n ],\n [\n -114.60937499999999,\n 35.17380831799959\n ],\n [\n -114.49951171875,\n 34.74161249883172\n ],\n [\n -114.2578125,\n 34.361576287484176\n ],\n [\n -114.23583984374999,\n 34.161818161230386\n ],\n [\n -114.521484375,\n 33.76088200086917\n ],\n [\n -114.71923828124999,\n 33.26624989076273\n ],\n [\n -114.5654296875,\n 33.100745405144245\n ],\n [\n -114.63134765625001,\n 32.95336814579932\n ],\n [\n -114.521484375,\n 32.694865977875075\n ],\n [\n -114.54345703125,\n 32.43561304116276\n ],\n [\n -114.08203125,\n 32.10118973232094\n ],\n [\n -113.7744140625,\n 31.80289258670676\n ],\n [\n -113.5986328125,\n 31.57853542647338\n ],\n [\n -113.26904296874999,\n 31.316101383495624\n ],\n [\n -112.9833984375,\n 31.12819929911196\n ],\n [\n -113.04931640625,\n 30.694611546632277\n ],\n [\n -112.96142578125,\n 30.29701788337205\n ],\n [\n -112.8076171875,\n 30.14512718337613\n ],\n [\n -112.74169921875,\n 29.897805610155874\n ],\n [\n -112.6318359375,\n 29.7453016622136\n ],\n [\n -112.56591796875,\n 29.516110386062277\n ],\n [\n -112.54394531249999,\n 29.248063243796576\n ],\n [\n -112.6318359375,\n 28.863918426224537\n ],\n [\n -112.3681640625,\n 28.5941685062326\n ],\n [\n -112.19238281249999,\n 28.690587654250685\n ],\n [\n -112.0166015625,\n 28.806173508854776\n ],\n [\n -111.73095703125,\n 28.51696944040106\n ],\n [\n -111.37939453125,\n 28.304380682962783\n ],\n [\n -111.15966796875,\n 28.110748760633534\n ],\n [\n -110.89599609375,\n 27.916766641249065\n ],\n [\n -110.5224609375,\n 27.839076094777816\n ],\n [\n -110.25878906249999,\n 27.566721430409707\n ],\n [\n -109.9072265625,\n 27.137368359795584\n ],\n [\n -109.75341796875,\n 26.902476886279807\n ],\n [\n -109.6875,\n 26.82407078047018\n ],\n [\n -109.53369140625,\n 26.80446076654616\n ],\n [\n -109.27001953125,\n 26.54922257769204\n ],\n [\n -109.22607421875,\n 26.27371402440643\n ],\n [\n -109.40185546874999,\n 25.958044673317843\n ],\n [\n -109.40185546874999,\n 25.760319754713887\n ],\n [\n -109.13818359375,\n 25.58208527870072\n ],\n [\n -108.896484375,\n 25.403584973186703\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"43","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-11-10","publicationStatus":"PW","scienceBaseUri":"56f11b6de4b0f59b85ddc509","chorus":{"doi":"10.1111/jbi.12664","url":"http://dx.doi.org/10.1111/jbi.12664","publisher":"Wiley-Blackwell","authors":"Edwards Taylor, Vaughn Mercy, Rosen Philip C., Meléndez Torres Cristina, Karl Alice E., Culver Melanie, Murphy Robert W.","journalName":"Journal of Biogeography","publicationDate":"11/10/2015","auditedOn":"11/12/2015"},"contributors":{"authors":[{"text":"Edwards, Taylor","contributorId":62337,"corporation":false,"usgs":true,"family":"Edwards","given":"Taylor","affiliations":[],"preferred":false,"id":623131,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vaughn, Mercy","contributorId":21881,"corporation":false,"usgs":true,"family":"Vaughn","given":"Mercy","email":"","affiliations":[],"preferred":false,"id":623132,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rosen, Philip C.","contributorId":70311,"corporation":false,"usgs":true,"family":"Rosen","given":"Philip","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":623133,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Torres, Ma. Cristina Melendez","contributorId":138858,"corporation":false,"usgs":false,"family":"Torres","given":"Ma.","email":"","middleInitial":"Cristina Melendez","affiliations":[{"id":12550,"text":"Comision de Ecologia y Desarrollo Sustentable del Estado de Sonora","active":true,"usgs":false}],"preferred":false,"id":623134,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Karl, Alice E.","contributorId":32844,"corporation":false,"usgs":true,"family":"Karl","given":"Alice","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":623135,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Culver, Melanie 0000-0001-5380-3059 mculver@usgs.gov","orcid":"https://orcid.org/0000-0001-5380-3059","contributorId":4327,"corporation":false,"usgs":true,"family":"Culver","given":"Melanie","email":"mculver@usgs.gov","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":12625,"text":"School of Natural Resources and the Environment, University of Arizona, Tucson, AZ, 85721, USA","active":true,"usgs":false},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":127,"text":"Arizona Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true}],"preferred":false,"id":622558,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Murphy, Robert W.","contributorId":147498,"corporation":false,"usgs":false,"family":"Murphy","given":"Robert","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":623136,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70159570,"text":"70159570 - 2015 - Consolidation drainage and climate change may reduce Piping Plover habitat in the Great Plains","interactions":[],"lastModifiedDate":"2016-06-24T10:59:06","indexId":"70159570","displayToPublicDate":"2015-11-09T13:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Consolidation drainage and climate change may reduce Piping Plover habitat in the Great Plains","docAbstract":"Many waterbird species utilize a diversity of aquatic habitats; however, with increasing anthropogenic needs to manage water regimes there is global concern over impacts to waterbird populations. The federally threatened Piping Plover (Charadrius melodus; hereafter plovers) is a shorebird that breeds in three habitat types in the Prairie Pothole Region of North Dakota, South Dakota, and Canada: riverine sandbars; reservoir shorelines; and prairie wetlands. Water surface areas of these habitats fluctuate in response to wet-dry periods; decreasing water surface areas expose shorelines that plovers utilize for nesting. Climate varies across the region so when other habitats are unavailable for plover nesting because of flooding, prairie wetlands may periodically provide habitat. Over the last century, many of the wetlands used by plovers in the Prairie Pothole Region have been modified to receive water from consolidation drainage (drainage of smaller wetlands into another wetland), which could eliminate shoreline nesting habitat. We evaluated whether consolidation drainage and fuller wetlands have decreased plover presence in 32 wetlands historically used by plovers. We found that wetlands with more consolidation drainage in their catchment and wetlands that were fuller had a lower probability of plover presence. These results suggest that plovers could have historically used prairie wetlands during the breeding season but consolidation drainage and/or climate change have reduced available shoreline habitat for plovers through increased water levels. Prairie wetlands, outside of some alkali wetlands in the western portion of the region, are less studied as habitat for plovers when compared to river and reservoir shorelines. Our study suggests that these wetlands may have played a larger role in plover ecology than previously thought. Wetland restoration and conservation, through the restoration of natural hydrology, may be required to ensure that adequate habitat exists among the three habitat types in the face of existing or changing climate and to ensure long-term conservation.
","language":"English","publisher":"Scientific Journals","doi":"10.3996/072015-JFWM-068","usgsCitation":"McCauley, L.A., Anteau, M.J., and Post van der Burg, M., 2015, Consolidation drainage and climate change may reduce Piping Plover habitat in the Great Plains: Journal of Fish and Wildlife Management, v. 7, no. 1, 9 p., https://doi.org/10.3996/072015-JFWM-068.","productDescription":"9 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060019","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":311113,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Dakota","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 -104.029541015625,\n 48.45835188280866\n ],\n [\n -103.33740234375,\n 48.58932584966972\n ],\n [\n -102.7001953125,\n 48.545705491847464\n ],\n [\n -102.0849609375,\n 48.27588152743497\n ],\n [\n -101.414794921875,\n 48.144097934938884\n ],\n [\n -100.634765625,\n 48.16608541901253\n ],\n [\n -100.206298828125,\n 48.011975126709956\n ],\n [\n -99.84374999999999,\n 47.4355191531953\n ],\n [\n -99.68994140625,\n 46.392411189814645\n ],\n [\n -100.579833984375,\n 46.2330529447983\n ],\n [\n -100.6732177734375,\n 46.24824991289166\n ],\n [\n -100.71716308593749,\n 46.51351558059737\n ],\n [\n -100.84899902343749,\n 46.66074749832071\n ],\n [\n -100.975341796875,\n 46.88647742351024\n ],\n [\n -101.0797119140625,\n 47.12621341795227\n ],\n [\n -101.2664794921875,\n 47.18224592701489\n ],\n [\n -101.5521240234375,\n 47.37231462056695\n ],\n [\n -101.7498779296875,\n 47.42065432071321\n ],\n [\n -102.05749511718749,\n 47.43923470537306\n ],\n [\n -102.4530029296875,\n 47.431803338643334\n ],\n [\n -102.579345703125,\n 47.56170075451973\n ],\n [\n -102.557373046875,\n 47.71715357016648\n ],\n [\n -102.7386474609375,\n 47.85003078545827\n ],\n [\n -102.7001953125,\n 48.00094957553023\n ],\n [\n -102.9913330078125,\n 48.06706753191901\n ],\n [\n -103.150634765625,\n 48.0156497866894\n ],\n [\n -103.55712890625,\n 47.923704717745686\n ],\n [\n -103.765869140625,\n 48.103763074117765\n ],\n [\n -103.9251708984375,\n 48.334343174592014\n ],\n [\n -104.029541015625,\n 48.45835188280866\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"7","issue":"1","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2015-11-01","publicationStatus":"PW","scienceBaseUri":"5641c3aae4b0831b7d62e725","contributors":{"authors":[{"text":"McCauley, Lisa A. lmccauley@usgs.gov","contributorId":5048,"corporation":false,"usgs":true,"family":"McCauley","given":"Lisa","email":"lmccauley@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":579519,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anteau, Michael J. 0000-0002-5173-5870 manteau@usgs.gov","orcid":"https://orcid.org/0000-0002-5173-5870","contributorId":3427,"corporation":false,"usgs":true,"family":"Anteau","given":"Michael","email":"manteau@usgs.gov","middleInitial":"J.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":579518,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Post van der Burg, Max 0000-0002-3943-4194 maxpostvanderburg@usgs.gov","orcid":"https://orcid.org/0000-0002-3943-4194","contributorId":4947,"corporation":false,"usgs":true,"family":"Post van der Burg","given":"Max","email":"maxpostvanderburg@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":579520,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70160098,"text":"70160098 - 2015 - Accounting for time- and space-varying changes in the gravity field to improve the network adjustment of relative-gravity data","interactions":[],"lastModifiedDate":"2015-12-14T11:38:47","indexId":"70160098","displayToPublicDate":"2015-11-09T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1803,"text":"Geophysical Journal International","active":true,"publicationSubtype":{"id":10}},"title":"Accounting for time- and space-varying changes in the gravity field to improve the network adjustment of relative-gravity data","docAbstract":"The relative gravimeter is the primary terrestrial instrument for measuring spatially and temporally varying gravitational fields. The background noise of the instrument—that is, non-linear drift and random tares—typically requires some form of least-squares network adjustment to integrate data collected during a campaign that may take several days to weeks. Here, we present an approach to remove the change in the observed relative-gravity differences caused by hydrologic or other transient processes during a single campaign, so that the adjusted gravity values can be referenced to a single epoch. The conceptual approach is an example of coupled hydrogeophysical inversion, by which a hydrologic model is used to inform and constrain the geophysical forward model. The hydrologic model simulates the spatial variation of the rate of change of gravity as either a linear function of distance from an infiltration source, or using a 3-D numerical groundwater model. The linear function can be included in and solved for as part of the network adjustment. Alternatively, the groundwater model is used to predict the change of gravity at each station through time, from which the accumulated gravity change is calculated and removed from the data prior to the network adjustment. Data from a field experiment conducted at an artificial-recharge facility are used to verify our approach. Maximum gravity change due to hydrology (observed using a superconducting gravimeter) during the relative-gravity field campaigns was up to 2.6 μGal d−1, each campaign was between 4 and 6 d and one month elapsed between campaigns. The maximum absolute difference in the estimated gravity change between two campaigns, two months apart, using the standard network adjustment method and the new approach, was 5.5 μGal. The maximum gravity change between the same two campaigns was 148 μGal, and spatial variation in gravity change revealed zones of preferential infiltration and areas of relatively high groundwater storage. The accommodation for spatially varying gravity change would be most important for long-duration campaigns, campaigns with very rapid changes in gravity and (or) campaigns where especially precise observed relative-gravity differences are used in the network adjustment.
","language":"English","publisher":"Published for the Royal Astronomical Society, the Deutsche Geophysikalische Gesellschaft, and the European Geophysical Society by Blackwell Scientific Publications","publisherLocation":"Oxford, UK","doi":"10.1093/gji/ggv493","usgsCitation":"Kennedy, J.R., and Ferre, T.P., 2015, Accounting for time- and space-varying changes in the gravity field to improve the network adjustment of relative-gravity data: Geophysical Journal International, v. 2, no. 204, p. 892-906, https://doi.org/10.1093/gji/ggv493.","productDescription":"15 p.","startPage":"892","endPage":"906","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-067380","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":471661,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/gji/ggv493","text":"Publisher Index Page"},{"id":312246,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"2","issue":"204","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-10","publicationStatus":"PW","scienceBaseUri":"566ff63be4b09cfe53ca7965","contributors":{"authors":[{"text":"Kennedy, Jeffrey R. 0000-0002-3365-6589 jkennedy@usgs.gov","orcid":"https://orcid.org/0000-0002-3365-6589","contributorId":2172,"corporation":false,"usgs":true,"family":"Kennedy","given":"Jeffrey","email":"jkennedy@usgs.gov","middleInitial":"R.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":581889,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ferre, Ty P.A.","contributorId":102167,"corporation":false,"usgs":true,"family":"Ferre","given":"Ty","email":"","middleInitial":"P.A.","affiliations":[],"preferred":false,"id":581890,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70133111,"text":"ds896 - 2015 - Introductory text","interactions":[],"lastModifiedDate":"2019-11-08T06:28:40","indexId":"ds896","displayToPublicDate":"2015-11-07T12:40:20","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":"896","title":"Introductory text","docAbstract":"The U.S. Geological Survey (USGS) provides information on the current use and flow of minerals and mineral-based materials in the U.S. and world economies. This Data Series report on “Historical Global Statistics for Mineral and Material Commodities” contains information on the production of selected commodities from 1990 to the most current year. The data may be used in the analysis of socioeconomic developments and trends and in the study of environmental issues associated with the extraction and processing of the selected commodities.\n\nThis report on global statistics includes U.S. data and is a companion to Data Series 140 on “Historical Statistics for Mineral and Material Commodities in the United States.”","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/ds896","usgsCitation":"Matos, G.R., Miller, L.D., and Barry, J.J., 2015, Introductory text: U.S. Geological Survey Data Series 896, HTML, https://doi.org/10.3133/ds896.","productDescription":"HTML","ipdsId":"IP-053968","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":369046,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":299384,"type":{"id":15,"text":"Index Page"},"url":"https://minerals.usgs.gov/minerals/pubs/historical-statistics/global/"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"551d089ee4b0256c24f42152","contributors":{"authors":[{"text":"Matos, Grecia R. 0000-0002-3285-3070 gmatos@usgs.gov","orcid":"https://orcid.org/0000-0002-3285-3070","contributorId":2656,"corporation":false,"usgs":true,"family":"Matos","given":"Grecia","email":"gmatos@usgs.gov","middleInitial":"R.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":false,"id":544080,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Miller, Lisa D. millerl@usgs.gov","contributorId":1304,"corporation":false,"usgs":true,"family":"Miller","given":"Lisa","email":"millerl@usgs.gov","middleInitial":"D.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":544081,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barry, James J. jbarry@usgs.gov","contributorId":501,"corporation":false,"usgs":true,"family":"Barry","given":"James","email":"jbarry@usgs.gov","middleInitial":"J.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":544082,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70159443,"text":"sir20155120 - 2015 - Water Quality, Cyanobacteria, and Environmental Factors and Their Relations to Microcystin Concentrations for Use in Predictive Models at Ohio Lake Erie and Inland Lake Recreational Sites, 2013-14","interactions":[],"lastModifiedDate":"2015-11-10T13:25:43","indexId":"sir20155120","displayToPublicDate":"2015-11-06T13:00:00","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":"2015-5120","title":"Water Quality, Cyanobacteria, and Environmental Factors and Their Relations to Microcystin Concentrations for Use in Predictive Models at Ohio Lake Erie and Inland Lake Recreational Sites, 2013-14","docAbstract":"Harmful cyanobacterial “algal” blooms (cyanoHABs) and associated toxins, such as microcystin, are a major water-quality issue for Lake Erie and inland lakes in Ohio. Predicting when and where a bloom may occur is important to protect the public that uses and consumes a water resource; however, predictions are complicated and likely site specific because of the many factors affecting toxin production. Monitoring for a variety of environmental and water-quality factors, for concentrations of cyanobacteria by molecular methods, and for algal pigments such as chlorophyll and phycocyanin by using optical sensors may provide data that can be used to predict the occurrence of cyanoHABs.
\nTo test these monitoring approaches, water-quality samples were collected at Ohio recreational sites during May–November in 2013 and 2014. In 2013, samples were collected monthly at eight sites at eight lakes to facilitate an initial assessment and select sites for more intensive sampling during 2014. In 2014, samples were collected approximately weekly at five sites at three lakes. Physical water-quality parameters were measured at the time of sampling. Composite samples were preserved and analyzed for dissolved and total nutrients, toxins, phytoplankton abundance and biovolume, and cyanobacterial genes by molecular methods. Molecular assays were done to enumerate (1) general cyanobacteria, (2) general Microcystis and Dolichospermum (Anabaena), (3) mcyE genes forMicrocystis, Dolichospermum (Anabaena), and Planktothrix targeting deoxyribonucleic acid (DNA), and (4) mcyE transcripts for Microcystis, Dolichospermum (Anabaena), and Planktothrix targeting ribonucleic acid (RNA).The DNA assays for the mcyE gene provide data on cyanobacteria that have the potential to produce microcystin, whereas the RNA assays provide data on cyanobacteria that are actively transcribing the toxin gene. Environmental data were obtained from available online sources. Quality-control (QC) samples were collected and analyzed for all constituents to characterize bias and variability; however, QC data for molecular assays were examined in more detail than for the other constituents. The QC data for molecular assays suggested that sampling variability and qPCR variability were small in comparison with the combined variability associated with sample filtering, extraction and purification, and the matrix itself.
\nA total of 46 water-quality samples were collected during 2013 at 8 beach sites—Buck Creek, Buckeye Crystal, Deer Creek, Harsha Main, Maumee Bay State Park (MBSP) Inland (negative control site), MBSP Lake Erie, Port Clinton, and Sandusky Bay. Microcystin was detected in 67–100 percent of samples at all sites except for MBSP Inland, where microcystin was detected in only 20 percent of samples. Microcystin concentrations ranged from <0.10 to 48 micrograms per liter (µ/L), with the widest range found at MBSP Lake Erie and the highest concentrations found at Buckeye Crystal. Saxitoxin was detected in five samples, and cylindrospermopsin was not detected in any samples.
\nA total of 65 water-quality samples were collected during 2014 at 5 sites on 3 lakes—Buckeye Fairfield and Onion Island, Harsha Main and Campers, and MBSP Lake Erie beach. Four of the sites were bathing beaches and one site, Onion Island, was an offshore boater swim area. Concentrations of microcystin ranged from <0.10 to 240 µ/L and, as in 2013, the widest range was found at MBSP Lake Erie. At Buckeye Lake, microcystin concentrations were consistently high (greater than 20 µ/L), ranging from 23 to 81 µ/L. At Harsha Main and Campers, microcystin concentrations ranged from <0.10 to 15 µ/L. Saxitoxin was detected in four samples collected at MBSP Lake Erie. Throughout the 2014 season, the cyanobacterial community, as determined by molecular and microscopy methods, and the dominance associated with the highest microcystin concentrations were unique to individual lakes. At Buckeye Lake, Planktothrix dominated the cyanobacterial community throughout the season and Planktothrix DNA and RNA were found in 100 percent of samples; Microcystis mcyE DNA was found in low concentrations. At Harsha Lake, Dolichospermum and Microcystis were a substantial percentage of the community from late May through August, and the highest microcystin concentrations occurred in June and July. At MBSP Lake Erie, Microcystis generally dominated from mid-July through early November, and the highest microcystin concentrations occurred in August.
\nSpearman’s correlation coefficient (rho) was computed to determine the relations between environmental and water-quality factors and microcystin concentrations at four sites—Buckeye Fairfield, Buckeye Onion Island, Harsha Main, and MBSP Lake Erie. Factors were evaluated for use as potential independent variables in two types of predictive models—daily and long-term models. Easily or continuously measured water-quality factors and available environmental data are used for daily predictions that do not require a site visit. Data from factors used in daily predictions and results from samples collected and analyzed in a laboratory are used for long-term predictions (a few days to several weeks). A few statistically significant correlations (p ≤ 0.05) between microcystin concentrations and factors for both daily and long-term predictions were found at Buckeye Onion Island, and many were found at Harsha Main and MBSP Lake Erie. There were only a few statistically significant factors for daily predictions at Buckeye Fairfield, likely because of the lack of variability in microcystin concentrations. Among factors for daily predictions, phycocyanin had the highest Spearman’s correlation to microcystin concentrations (rho = 0.79 to 0.93) at all sites except for Buckeye Fairfield. Turbidity, pH, algae category, and Secchi depth were significantly correlated to microcystin concentrations at Harsha Main and MBSP Lake Erie. Algae categories were observational categories from 0 (none) to 4 (extreme). Several discharge variables (Maumee River at Waterville, river mouth is approximately 3.5 miles from the beach) at MBSP Lake Erie were promising environmental factors for daily predictions. In addition to discrete water-quality measurements recorded at Harsha Main at the time of sampling, many manipulated measurements (factors derived from mathematical manipulation of time-series data) available from a nearby continuous monitor were strongly correlated to microcystin concentrations; the highest correlation was found for the relation between microcystin concentrations and the antecedent 7-day average phycocyanin (rho = 0.98). For long-term predictions, the most highly correlated molecular assays were Planktothrix mcyE DNA at Buckeye Onion Island and Microcystis mcyE DNA at Harsha Main and MBSP Lake Erie. Concentrations of several nutrient constituents were significantly correlated to microcystin concentrations including total nitrogen at Buckeye Onion Island, ammonia and nitrate plus nitrite (both negatively correlated) at Harsha Main and MBSP Lake Erie, and total phosphorus at MBSP Lake Erie.
\nThe results of this study showed that water-quality and environmental variables are promising for use in site-specific daily or long-term predictive models. In order to develop more accurate models to predict toxin concentrations at freshwater lake sites, data need to be collected more frequently and for consecutive days in future studies.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155120","collaboration":"Prepared in cooperation with the Ohio Water Development Authority","usgsCitation":"Francy, D.S., Graham, J.L., Stelzer, E.A., Ecker, C.D., Brady, A.M.G., Struffolino, Pamela, and Loftin, K.A., 2015, Water quality, cyanobacteria, and environmental factors and their relations to microcystin concentrations for use in predictive models at Ohio Lake Erie and inland lake recreational sites, 2013–14: U.S. Geological Survey Scientific Investigations Report 2015–5120, 58 p., https://dx.doi.org/10.3133/sir20155120.","productDescription":"Report: vii, 58 p.; Appendix","numberOfPages":"70","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2013-05-01","temporalEnd":"2014-11-01","ipdsId":"IP-064699","costCenters":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"links":[{"id":310974,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5120/sir20155120.pdf","text":"Report","size":"9.41 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":310973,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5120/coverthb.jpg"},{"id":310975,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5120/sir20155120_appendix2_phytoplanktondata.xlsx","text":"Appendix 2","size":"181 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"Appendix 2","linkHelpText":"Phytoplankton abundance and community composition at Ohio recreational lake sites, 2013–14."}],"country":"United States","state":"Ohio","otherGeospatial":"Buck Creek State Park, Buckeye Lake State Park, Deer Creek State Park, East Fork State Park, Lake Erie","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.638916015625,\n 41.413895564677304\n ],\n [\n -83.638916015625,\n 41.7672146942102\n ],\n [\n -82.6556396484375,\n 41.7672146942102\n ],\n [\n -82.6556396484375,\n 41.413895564677304\n ],\n [\n -83.638916015625,\n 41.413895564677304\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.54440307617188,\n 39.89498716884207\n ],\n [\n -82.54440307617188,\n 39.94712141785606\n ],\n [\n -82.40432739257812,\n 39.94712141785606\n ],\n [\n -82.40432739257812,\n 39.89498716884207\n ],\n [\n -82.54440307617188,\n 39.89498716884207\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.17449951171875,\n 38.983965305617666\n ],\n [\n -84.17449951171875,\n 39.0533181067413\n ],\n [\n -84.05982971191406,\n 39.0533181067413\n ],\n [\n -84.05982971191406,\n 38.983965305617666\n ],\n [\n -84.17449951171875,\n 38.983965305617666\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.7546157836914,\n 39.94212035820183\n ],\n [\n -83.7546157836914,\n 39.99369266969988\n ],\n [\n -83.70586395263672,\n 39.99369266969988\n ],\n [\n -83.70586395263672,\n 39.94212035820183\n ],\n [\n -83.7546157836914,\n 39.94212035820183\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.27104568481445,\n 39.59748778978444\n ],\n [\n -83.27104568481445,\n 39.64535376010791\n ],\n [\n -83.21285247802734,\n 39.64535376010791\n ],\n [\n -83.21285247802734,\n 39.59748778978444\n ],\n [\n -83.27104568481445,\n 39.59748778978444\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Ohio Water Science Center
U.S. Geological Survey
6480 Doubletree Ave
Columbus, OH 43229-1111
http://oh.water.usgs.gov/
A collection of 24 datasets, including streamflow, well characteristics, groundwater elevations, and discrete water-quality concentrations, is provided to produce a consistent set of example data to demonstrate typical data manipulations or statistical analysis of hydrologic data. These example data are provided in an R package called smwrData. The data in the package have been collected by the U.S. Geological Survey or published in its reports, for example Helsel and Hirsch (2002). The R package provides a convenient mechanism for distributing the data to users of R within the U.S. Geological Survey and other users in the R community.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151103","usgsCitation":"Lorenz, D.L., 2015, smwrData—An R package of example hydrologic data, version 1.1.1: U.S. Geological\nSurvey Open-File Report 2015–1103, 5 p., https://dx.doi.org/10.3133/ofr20151103.","productDescription":"Report: iii, 3 p.; Appendix","numberOfPages":"14","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-040392","costCenters":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"links":[{"id":311067,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1103/coverthb.jpg"},{"id":311068,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1103/ofr20151103.pdf","text":"Report","size":"316 kB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":311069,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2015/1103/downloads/smwrData-manual.pdf","text":"Appendix","size":"193 kB","linkFileType":{"id":1,"text":"pdf"},"description":"Appendix"}],"contact":"Director, Minnesota Water Science Center
U.S. Geological Survey
2280 Woodale Drive
Mounds View, Minnesota 55112
http://mn.water.usgs.gov/
This special issue of Applied Geochemistry honors Dr. D. Kirk Nordstrom, and his influential career spent primarily at the U.S. Geological Survey (USGS). This issue does not herald his retirement or other significant career milestone, but serves as a recognition of the impact his work has had on the field of geochemistry in general. This special issue grew from a symposium in Kirk’s honor (affectionately dubbed “Kirkfest”) at the Geological Society of America’s annual meeting in Denver, Colorado, USA, during October 2013. At GSA, 27 talks and 35 posters showed how Kirk’s work has influenced a wide range of current hydrogeochemical research, from geothermal processes to acid mine drainage to geochemical modeling. The breadth of his knowledge and his many contributions to the published literature have left an indelible mark on the field of geochemistry, and this special issue is a tribute to his experience and contributions.
","language":"English","publisher":"International Association of Geochemistry and Cosmochemistry","publisherLocation":"Oxford","doi":"10.1016/j.apgeochem.2015.04.012","usgsCitation":"Campbell, K.M., Verplanck, P.L., McCleskey, R.B., and Alpers, C.N., 2015, From extreme pH to extreme temperature: An issue in honor of the geochemical contributions of Kirk Nordstrom, USGS hydrogeochemist: Applied Geochemistry, v. 62, p. 1-2, https://doi.org/10.1016/j.apgeochem.2015.04.012.","productDescription":"2 p.","startPage":"1","endPage":"2","ipdsId":"IP-064998","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":330924,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"62","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58259561e4b01fad86db2415","contributors":{"authors":[{"text":"Campbell, Kate M. 0000-0002-8715-5544 kcampbell@usgs.gov","orcid":"https://orcid.org/0000-0002-8715-5544","contributorId":1441,"corporation":false,"usgs":true,"family":"Campbell","given":"Kate","email":"kcampbell@usgs.gov","middleInitial":"M.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":653462,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Verplanck, Philip L. 0000-0002-3653-6419 plv@usgs.gov","orcid":"https://orcid.org/0000-0002-3653-6419","contributorId":728,"corporation":false,"usgs":true,"family":"Verplanck","given":"Philip","email":"plv@usgs.gov","middleInitial":"L.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":653463,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McCleskey, R. Blaine 0000-0002-2521-8052 rbmccles@usgs.gov","orcid":"https://orcid.org/0000-0002-2521-8052","contributorId":147399,"corporation":false,"usgs":true,"family":"McCleskey","given":"R.","email":"rbmccles@usgs.gov","middleInitial":"Blaine","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true}],"preferred":true,"id":653464,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Alpers, Charles N. 0000-0001-6945-7365 cnalpers@usgs.gov","orcid":"https://orcid.org/0000-0001-6945-7365","contributorId":411,"corporation":false,"usgs":true,"family":"Alpers","given":"Charles","email":"cnalpers@usgs.gov","middleInitial":"N.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":653465,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70159387,"text":"ofr20151203 - 2015 - Seasonal microbial and environmental parameters at Crocker Reef, Florida Keys, 2014–2015","interactions":[],"lastModifiedDate":"2015-11-04T08:50:58","indexId":"ofr20151203","displayToPublicDate":"2015-11-04T08:00:00","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":"2015-1203","title":"Seasonal microbial and environmental parameters at Crocker Reef, Florida Keys, 2014–2015","docAbstract":"Crocker Reef, located on the outer reef tract of the Florida Keys (fig. 1), was the site of an integrated “reefscape characterization” effort focused on calcification and related biogeochemical processes as part of the U.S. Geological Survey (USGS) Coral Reef Ecosystem STudies (CREST) project. It is characterized as a senile or dead reef, with only scattered stony coral colonies and areas of sand and rubble. It was chosen as an end-member for later comparison to sites with a healthy, growing reef framework. The CREST reefscape characterization included two intensive seasonal sampling trips to capture summer (July 8–17, 2014) and winter (January 29–February 5, 2015) conditions. This report presents water column microbial and environmental data collected for use as metadata in future publications examining reef metabolic processes via metagenomes derived from water samples and fine-scale temporal and spatial carbonate chemistry measurements.
\nMicrobial measurements included enumeration of total bacteria, enumeration of virus-like particles, and plate counts of Vibrio spp. colony-forming units (CFU). These measurements were intended to give a sense of any seasonal changes in the total microbial load and to provide an indication of water quality. Additional environmental parameters measured included water temperature, salinity, dissolved oxygen, and pH. Four sites (table 1) were intensively sampled for periods of approximately 48 hours during summer (July 2014) and winter (January–February 2015), during which water samples were collected every 4 hours for analysis, except when prevented by weather conditions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151203","usgsCitation":"Kellogg, C.A., Yates, K.K., Lawler, S.N., Moore, C.S., and Smiley, N.A., 2015, Seasonal microbial and environmental parameters at Crocker Reef, Florida Keys, 2014–2015: U.S. Geological Survey Open-File Report 2015–1203, 12 p., https://dx.doi.org/10.3133/ofr20151203.","productDescription":"Report: iv, 12 p.; Data Release","numberOfPages":"17","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-068435","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":310880,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1203/coverthb.jpg"},{"id":310883,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://dx.doi.org/10.5066/F74Q7S25","text":"Data Release","linkFileType":{"id":5,"text":"html"},"description":"OFR 2015-1203","linkHelpText":"Microbial and environmental dataset from Crocker Reef, Florida Keys, 2014-2015"},{"id":310881,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1203/ofr20151203.pdf","text":"Report","size":"776 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1203"}],"country":"United States","state":"Florida","otherGeospatial":"Crocker Reef","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.58677673339842,\n 24.94186090727989\n ],\n [\n -80.58677673339842,\n 25.027750592082853\n ],\n [\n -80.49407958984375,\n 25.027750592082853\n ],\n [\n -80.49407958984375,\n 24.94186090727989\n ],\n [\n -80.58677673339842,\n 24.94186090727989\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, St. Petersburg Coastal and Marine Science Center
600 Fourth Street South
St. Petersburg, Florida 33701-4846
http://coastal.er.usgs.gov/
Hybridization between introduced and native fauna is a risk to native species and may threaten the long-term persistence of numerous taxa. Rainbow Trout Oncorhynchus mykiss has been one of the most widely introduced species around the globe and often hybridizes with native Cutthroat Trout O. clarkii in the Rocky Mountains. Previous work has shown that hybridization negatively affects reproductive success, but identification of the traits contributing to that reduction has been elusive. In this study, we used a combination of field and laboratory techniques to assess how hybridization with Rainbow Trout affects seven traits during several stages of Westslope Cutthroat Trout development: embryonic survival, ova size, ova energy concentration, sperm motility, juvenile weight, juvenile survival, and burst swimming endurance. Rainbow Trout admixture was correlated with an increase in embryonic survival and ova energy concentration but with a decrease in juvenile weight and burst swimming endurance. These correlations differed from previously observed patterns of reproductive success and likely do not explain the declines in reproductive success associated with admixture. Future investigation of additional, unstudied traits and the use of different environments may shed light on the traits responsible for reproductive success in admixed Cutthroat Trout.
","language":"English","publisher":"American Fisheries Society","publisherLocation":"Bethesda, MD","doi":"10.1080/00028487.2015.1064475","usgsCitation":"Drinan, D.P., Webb, M.A., Naish, K., Kalinowski, S.T., Boyer, M.C., Steed, A.C., Shepard, B.B., and Muhlfeld, C.C., 2015, Effects of hybridization between nonnative Rainbow Trout and native Westslope Cutthroat Trout on fitness-related traits: Transactions of the American Fisheries Society, v. 144, no. 6, p. 1275-1291, https://doi.org/10.1080/00028487.2015.1064475.","productDescription":"17 p.","startPage":"1275","endPage":"1291","numberOfPages":"17","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-051248","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":488967,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.6084/m9.figshare.1591877.v1","text":"External Repository"},{"id":314031,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"144","issue":"6","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-11-03","publicationStatus":"PW","scienceBaseUri":"5690ebcce4b09c7f9a218bda","contributors":{"authors":[{"text":"Drinan, Daniel P.","contributorId":37614,"corporation":false,"usgs":true,"family":"Drinan","given":"Daniel","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":588003,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Webb, Molly A. H.","contributorId":152118,"corporation":false,"usgs":false,"family":"Webb","given":"Molly","email":"","middleInitial":"A. H.","affiliations":[{"id":18870,"text":"Bozeman Fish Technology Center, U.S. Fish and Wildlife Service, Bozeman, Montana 59715","active":true,"usgs":false}],"preferred":false,"id":588004,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Naish, Kerry A.","contributorId":20243,"corporation":false,"usgs":true,"family":"Naish","given":"Kerry A.","affiliations":[],"preferred":false,"id":588005,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kalinowski, Steven T.","contributorId":145736,"corporation":false,"usgs":false,"family":"Kalinowski","given":"Steven","email":"","middleInitial":"T.","affiliations":[{"id":16214,"text":"Montana State University, Department of Ecology","active":true,"usgs":false}],"preferred":false,"id":588006,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Boyer, Matthew C.","contributorId":126725,"corporation":false,"usgs":false,"family":"Boyer","given":"Matthew","email":"","middleInitial":"C.","affiliations":[{"id":6581,"text":"Montana Fish, Wildlife and Parks, Kalispell, Montana 59901, USA","active":true,"usgs":false}],"preferred":false,"id":588007,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Steed, Amber C.","contributorId":78864,"corporation":false,"usgs":true,"family":"Steed","given":"Amber","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":588008,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Shepard, Bradley B.","contributorId":145880,"corporation":false,"usgs":false,"family":"Shepard","given":"Bradley","email":"","middleInitial":"B.","affiliations":[{"id":6765,"text":"Montana State University, Department of Land Resources and Environmental Sciences","active":true,"usgs":false}],"preferred":false,"id":588009,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Muhlfeld, Clint C. 0000-0002-4599-4059 cmuhlfeld@usgs.gov","orcid":"https://orcid.org/0000-0002-4599-4059","contributorId":924,"corporation":false,"usgs":true,"family":"Muhlfeld","given":"Clint","email":"cmuhlfeld@usgs.gov","middleInitial":"C.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":588002,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70157083,"text":"sir20155130 - 2015 - Hydrogeology and sources of water to select springs in Black Canyon, south of Hoover Dam, Lake Mead National Recreation Area, Nevada and Arizona","interactions":[],"lastModifiedDate":"2015-11-04T09:06:08","indexId":"sir20155130","displayToPublicDate":"2015-11-03T14:00:00","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":"2015-5130","title":"Hydrogeology and sources of water to select springs in Black Canyon, south of Hoover Dam, Lake Mead National Recreation Area, Nevada and Arizona","docAbstract":"Springs in Black Canyon of the Colorado River, directly south of Hoover Dam in the Lake Mead National Recreation Area, Nevada and Arizona, are important hydrologic features that support a unique riparian ecosystem including habitat for endangered species. Rapid population growth in areas near and surrounding Black Canyon has caused concern among resource managers that such growth could affect the discharge from these springs. The U.S. Geological Survey studied the springs in Black Canyon between January 2008, and May 2014. The purposes of this study were to provide a baseline of discharge and hydrochemical data from selected springs in Black Canyon and to better understand the sources of water to the springs.
\nVarious hydrologic, hydrochemical, geochemical, and geologic data were collected and analyzed during this study. More than 100 hydrologic sites consisting of springs, seeps, pools, rivers, reservoirs, and wells were investigated, and measurements were taken at 75 of these sites. Water levels were measured or compiled for 42 wells and samples of water were collected from 36 unique sites and submitted for laboratory analyses of hydrochemical constituents. Measurements of discrete discharge were made from nine unique spring areas and four sites in Black Canyon were selected for continuous monitoring of discharge. Additionally, samples of rock near Hoover Dam were collected and analyzed to determine the age of spring deposits.
\nResults of hydrochemical analyses indicate that discharge from springs in Black Canyon is from two sources: (1) Lake Mead, and (2) a local and (or) regional source. Discharge from springs closest to Hoover Dam contains a substantial percentage (>50 percent) of water from Lake Mead. This includes springs that are between Hoover Dam and Palm Tree Spring. Discharge from springs south of Palm Tree Spring contains a substantial percentage (>50 percent) of the water that is believed to come from a combination of other local and regional sources, although the exact location and nature of these sources is not clear. The unique hydrochemistry of some springs, such as Bighorn Sheep Spring and Latos Pool, suggests that little if any water discharging from these springs comes from Lake Mead. Geochronological results of spring deposits at several sites near Hoover Dam indicate that most deposits are young and likely formed after the construction of Hoover Dam.
\nSeveral major faults, including the Salt Cedar Fault and the Palm Tree Fault, play an important role in the movement of groundwater. Groundwater may move along these faults and discharge where faults intersect volcanic breccias or fractured rock. Vertical movement of groundwater along faults is suggested as a mechanism for the introduction of heat energy present in groundwater from many of the springs. Groundwater altitudes in the study area indicate a potential for flow from Eldorado Valley to Black Canyon although current interpretations of the geology of this area do not favor such flow. If groundwater from Eldorado Valley discharges at springs in Black Canyon then the development of groundwater resources in Eldorado Valley could result in a decrease in discharge from the springs. Geology and structure indicate that it is not likely that groundwater can move between Detrital Valley and Black Canyon. Thus, the development of groundwater resources in Detrital Valley may not result in a decrease in discharge from springs in Black Canyon.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155130","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Moran, M.J., Wilson, J.W., and Beard, L.S., 2015, Hydrogeology and sources of water to select springs in Black Canyon, south of Hoover Dam, Lake Mead National Recreation Area, Nevada and Arizona: U.S. Geological Survey Scientific Investigations Report 2015–5130, 61 p., https://dx.doi.org/10.3133/sir20155130.","productDescription":"Report: viii, 61 p.; 4 Appendixes","numberOfPages":"74","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-060431","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":310988,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5130/coverthb.jpg"},{"id":310989,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5130/sir20155130.pdf","text":"Report","size":"13.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5130"},{"id":310990,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5130/sir20155130_appendixa.xlsx","text":"Appendix A","size":"25 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2015-5130 Appendix A"},{"id":310991,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5130/sir20155130_appendixb.xlsx","text":"Appendix B","size":"32 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2015-5130 Appendix B"},{"id":310992,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5130/sir20155130_appendixc.xlsx","text":"Appendix C","size":"36 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2015-5130 Appendix C"},{"id":310993,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5130/sir20155130_appendixd.xlsx","text":"Appendix D","size":"68 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2015-5130 Appendix D"}],"country":"United States","state":"Arizona, Nevada","otherGeospatial":"Black Canyon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.78790283203125,\n 35.8411948281412\n ],\n [\n -114.78790283203125,\n 36.058536144240506\n ],\n [\n -114.62928771972655,\n 36.058536144240506\n ],\n [\n -114.62928771972655,\n 35.8411948281412\n ],\n [\n -114.78790283203125,\n 35.8411948281412\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Nevada Water Science Center
U.S. Geological Survey
2730 N. Deer Run Rd.
Carson City, NV 89701
http://nevada.usgs.gov/water/
While numerous methods exist for estimating abundance when detection is imperfect, these methods may not be appropriate due to logistical difficulties or unrealistic assumptions. In particular, if highly mobile taxa are frequently absent from survey locations, methods that estimate a probability of detection conditional on presence will generate biased abundance estimates. Here, we propose a new estimator for estimating abundance of mobile populations using telemetry and counts of unmarked animals. The estimator assumes that the target population conforms to a fission-fusion grouping pattern, in which the population is divided into groups that frequently change in size and composition. If assumptions are met, it is not necessary to locate all groups in the population to estimate abundance. We derive an estimator, perform a simulation study, conduct a power analysis, and apply the method to field data. The simulation study confirmed that our estimator is asymptotically unbiased with low bias, narrow confidence intervals, and good coverage, given a modest survey effort. The power analysis provided initial guidance on survey effort. When applied to small data sets obtained by radio-tracking Indiana bats, abundance estimates were reasonable, although imprecise. The proposed method has the potential to improve abundance estimates for mobile species that have a fission-fusion social structure, such as Indiana bats, because it does not condition detection on presence at survey locations and because it avoids certain restrictive assumptions.
","language":"English","publisher":"Ecological Society of America","doi":"10.1890/ES15-00180.1","usgsCitation":"Clement, M., O’Keefe, J.M., and Walters, B., 2015, A method for estimating abundance of mobile populations using telemetry and counts of unmarked animals: Ecosphere, v. 6, no. 10, art184; 13 p., https://doi.org/10.1890/ES15-00180.1.","productDescription":"art184; 13 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059014","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":471663,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1890/es15-00180.1","text":"Publisher Index Page"},{"id":310986,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","issue":"10","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2015-10-22","publicationStatus":"PW","scienceBaseUri":"5639dafde4b0d6133fe732ca","contributors":{"authors":[{"text":"Clement, Matthew mclement@usgs.gov","contributorId":138815,"corporation":false,"usgs":true,"family":"Clement","given":"Matthew","email":"mclement@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":579114,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"O’Keefe, Joy M","contributorId":149672,"corporation":false,"usgs":false,"family":"O’Keefe","given":"Joy","email":"","middleInitial":"M","affiliations":[{"id":17777,"text":"Indiana State University","active":true,"usgs":false}],"preferred":false,"id":579115,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Walters, Brianne","contributorId":149673,"corporation":false,"usgs":false,"family":"Walters","given":"Brianne","email":"","affiliations":[{"id":17777,"text":"Indiana State University","active":true,"usgs":false}],"preferred":false,"id":579116,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70159467,"text":"70159467 - 2015 - A century of induced earthquakes in Oklahoma?","interactions":[],"lastModifiedDate":"2015-11-03T11:29:12","indexId":"70159467","displayToPublicDate":"2015-11-03T12:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"A century of induced earthquakes in Oklahoma?","docAbstract":"Seismicity rates have increased sharply since 2009 in the central and eastern United States, with especially high rates of activity in the state of Oklahoma. Growing evidence indicates that many of these events are induced, primarily by injection of wastewater in deep disposal wells. The upsurge in activity has raised two questions: What is the background rate of tectonic earthquakes in Oklahoma? How much has the rate varied throughout historical and early instrumental times? In this article, we show that (1) seismicity rates since 2009 surpass previously observed rates throughout the twentieth century; (2) several lines of evidence suggest that most of the significant earthquakes in Oklahoma during the twentieth century were likely induced by oil production activities, as they exhibit statistically significant temporal and spatial correspondence with disposal wells, and intensity measurements for the 1952 El Reno earthquake and possibly the 1956 Tulsa County earthquake follow the pattern observed in other induced earthquakes; and (3) there is evidence for a low level of tectonic seismicity in southeastern Oklahoma associated with the Ouachita structural belt. The 22 October 1882 Choctaw Nation earthquake, for which we estimate Mw 4.8, occurred in this zone.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120150109","usgsCitation":"Hough, S.E., and Page, M.T., 2015, A century of induced earthquakes in Oklahoma?: Bulletin of the Seismological Society of America, v. 105, no. 6, 6 p., https://doi.org/10.1785/0120150109.","productDescription":"6 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063741","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":310984,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oklahoma","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-96.944611,33.949217],[-96.973807,33.935697],[-96.979818,33.941588],[-96.981031,33.94916],[-96.979347,33.95513],[-96.981337,33.956378],[-96.987892,33.954671],[-96.994288,33.949206],[-96.996183,33.941728],[-96.995023,33.932035],[-96.984939,33.904866],[-96.983971,33.892083],[-96.985567,33.886522],[-97.023899,33.844213],[-97.041245,33.837761],[-97.052209,33.841737],[-97.057554,33.840133],[-97.058623,33.837728],[-97.055148,33.825701],[-97.058623,33.818752],[-97.087999,33.808747],[-97.092112,33.804097],[-97.095236,33.794136],[-97.085218,33.765512],[-97.086195,33.743933],[-97.097154,33.727809],[-97.108936,33.720294],[-97.121102,33.717174],[-97.13753,33.718664],[-97.149394,33.721967],[-97.16281,33.729118],[-97.172192,33.737545],[-97.187792,33.769702],[-97.190397,33.781153],[-97.205431,33.801488],[-97.204995,33.81887],[-97.1997,33.827322],[-97.195831,33.830803],[-97.18137,33.831375],[-97.171627,33.835335],[-97.166824,33.840395],[-97.166629,33.847311],[-97.180845,33.895204],[-97.185458,33.9007],[-97.210921,33.916064],[-97.226522,33.914642],[-97.244946,33.903092],[-97.249209,33.875101],[-97.255636,33.863698],[-97.271532,33.86256],[-97.279108,33.864555],[-97.299245,33.880175],[-97.30749,33.878204],[-97.314413,33.866989],[-97.318243,33.865121],[-97.324158,33.866017],[-97.327563,33.873903],[-97.33294,33.87444],[-97.336524,33.872827],[-97.339392,33.86763],[-97.348338,33.843876],[-97.358513,33.830018],[-97.368744,33.821471],[-97.372941,33.819454],[-97.426493,33.819398],[-97.444193,33.823773],[-97.453057,33.828536],[-97.462857,33.841772],[-97.461486,33.84956],[-97.451469,33.87093],[-97.450954,33.891398],[-97.460376,33.903948],[-97.486505,33.916994],[-97.50096,33.919643],[-97.525277,33.911751],[-97.551541,33.897947],[-97.55827,33.897099],[-97.587441,33.902479],[-97.596289,33.913769],[-97.597115,33.917868],[-97.591514,33.9282],[-97.589598,33.953554],[-97.609091,33.968093],[-97.633778,33.981257],[-97.65621,33.989488],[-97.671772,33.99137],[-97.69311,33.983699],[-97.709684,33.954997],[-97.725289,33.941045],[-97.733723,33.936392],[-97.752957,33.937049],[-97.762768,33.934396],[-97.759399,33.91882],[-97.765446,33.913532],[-97.772672,33.914382],[-97.783717,33.91056],[-97.78034,33.904833],[-97.779683,33.899243],[-97.784657,33.890632],[-97.801578,33.885138],[-97.805423,33.877167],[-97.834333,33.857671],[-97.871447,33.849001],[-97.896738,33.857985],[-97.936743,33.879204],[-97.951215,33.878424],[-97.967777,33.88243],[-97.977808,33.889883],[-97.983769,33.8972],[-97.983552,33.904002],[-97.978804,33.912548],[-97.969873,33.905999],[-97.964461,33.907398],[-97.957155,33.914454],[-97.952679,33.929482],[-97.953395,33.936445],[-97.954467,33.937774],[-97.971175,33.937129],[-97.974173,33.942832],[-97.960351,33.951928],[-97.94573,33.989839],[-97.958325,33.990846],[-97.974173,34.006716],[-97.987388,33.999823],[-98.027672,33.993357],[-98.055197,33.995841],[-98.082839,34.002412],[-98.088203,34.005481],[-98.105482,34.031307],[-98.104022,34.036233],[-98.098001,34.03824],[-98.096177,34.044625],[-98.114587,34.06228],[-98.120208,34.072127],[-98.121039,34.081266],[-98.119417,34.084474],[-98.099328,34.104295],[-98.092421,34.116917],[-98.089755,34.128211],[-98.101937,34.14683],[-98.109462,34.154111],[-98.123377,34.15454],[-98.130816,34.150532],[-98.154354,34.122734],[-98.16912,34.114171],[-98.203711,34.117676],[-98.241013,34.133103],[-98.256467,34.129481],[-98.293901,34.13302],[-98.300209,34.134579],[-98.325445,34.151025],[-98.364023,34.157109],[-98.381238,34.149454],[-98.398441,34.128456],[-98.400967,34.122236],[-98.39816,34.121396],[-98.399777,34.099973],[-98.414426,34.085074],[-98.419995,34.082488],[-98.42848,34.085523],[-98.440092,34.084311],[-98.443724,34.082152],[-98.449034,34.073462],[-98.475066,34.064269],[-98.486328,34.062598],[-98.504182,34.072371],[-98.5282,34.094961],[-98.536257,34.107343],[-98.550917,34.119334],[-98.558593,34.128254],[-98.560191,34.133202],[-98.572451,34.145091],[-98.599789,34.160571],[-98.616733,34.156418],[-98.643223,34.164531],[-98.648073,34.164441],[-98.690072,34.133155],[-98.717537,34.13645],[-98.734287,34.135758],[-98.741966,34.12553],[-98.757037,34.124633],[-98.759653,34.126912],[-98.760558,34.132388],[-98.76557,34.136376],[-98.792015,34.143736],[-98.80681,34.155901],[-98.812954,34.158444],[-98.831115,34.162154],[-98.855585,34.161621],[-98.8579,34.159627],[-98.860125,34.149913],[-98.868116,34.149635],[-98.874872,34.155657],[-98.871211,34.163012],[-98.872922,34.166584],[-98.918333,34.181831],[-98.94022,34.203686],[-98.952358,34.212579],[-98.960791,34.21303],[-98.96247,34.204668],[-98.966302,34.201323],[-98.974132,34.203566],[-98.981364,34.217583],[-98.987294,34.221223],[-98.990852,34.221633],[-99.000761,34.217643],[-99.003433,34.214466],[-99.002916,34.208782],[-99.013075,34.203222],[-99.036273,34.206912],[-99.043471,34.198208],[-99.058084,34.200569],[-99.060344,34.204761],[-99.066465,34.208404],[-99.079535,34.211518],[-99.092191,34.209316],[-99.108758,34.203401],[-99.119204,34.201747],[-99.126567,34.203004],[-99.131885,34.207382],[-99.126614,34.215329],[-99.130609,34.219408],[-99.13822,34.219159],[-99.143985,34.214763],[-99.159016,34.20888],[-99.189511,34.214312],[-99.192683,34.218825],[-99.190146,34.22966],[-99.197153,34.244298],[-99.196926,34.260929],[-99.19457,34.272424],[-99.195605,34.280839],[-99.207561,34.283505],[-99.211648,34.292232],[-99.213476,34.310672],[-99.209724,34.324935],[-99.210716,34.336304],[-99.213135,34.340369],[-99.217335,34.34152],[-99.226153,34.339726],[-99.232606,34.34238],[-99.237233,34.362717],[-99.242945,34.372668],[-99.248969,34.375984],[-99.254722,34.372405],[-99.258696,34.372634],[-99.274926,34.384904],[-99.273958,34.38756],[-99.264508,34.388085],[-99.25898,34.391243],[-99.261321,34.403499],[-99.294648,34.415373],[-99.308274,34.410014],[-99.319606,34.408869],[-99.334037,34.427536],[-99.356713,34.442144],[-99.354672,34.451857],[-99.358795,34.455863],[-99.36961,34.458699],[-99.381011,34.456936],[-99.394956,34.442099],[-99.396902,34.418688],[-99.393919,34.415274],[-99.391492,34.405631],[-99.397253,34.377871],[-99.40296,34.373481],[-99.408848,34.372776],[-99.420432,34.380464],[-99.430995,34.373414],[-99.44076,34.374123],[-99.452648,34.388252],[-99.470969,34.396471],[-99.487219,34.397955],[-99.499875,34.409608],[-99.51428,34.414035],[-99.529786,34.411452],[-99.549242,34.412715],[-99.569696,34.418418],[-99.58006,34.416653],[-99.58448,34.407673],[-99.585442,34.388914],[-99.600026,34.374688],[-99.624197,34.373577],[-99.649662,34.379885],[-99.659362,34.37439],[-99.665992,34.374185],[-99.678283,34.379799],[-99.696462,34.381036],[-99.712682,34.390928],[-99.715089,34.400754],[-99.720259,34.406295],[-99.754248,34.421289],[-99.767234,34.430502],[-99.765599,34.437488],[-99.775743,34.444225],[-99.782986,34.444364],[-99.793684,34.453894],[-99.814313,34.476204],[-99.818739,34.484976],[-99.818186,34.48784],[-99.825325,34.497596],[-99.853066,34.511593],[-99.868953,34.527615],[-99.874403,34.537095],[-99.887147,34.549047],[-99.915771,34.565975],[-99.921801,34.570253],[-99.923211,34.574552],[-99.94572,34.579273],[-99.954567,34.578195],[-99.958898,34.571271],[-99.971555,34.562179],[-99.985833,34.560079],[-100.000381,34.560509],[-100.000406,36.499702],[-103.002434,36.500397],[-103.002199,37.000104],[-102.986976,36.998524],[-102.75986,37.000019],[-102.698142,36.995149],[-102.04224,36.993083],[-100.115722,37.002206],[-99.648652,36.999604],[-98.219499,36.997824],[-95.049499,36.99958],[-94.61808,36.998135],[-94.617919,36.499414],[-94.571806,36.213748],[-94.522634,35.934892],[-94.431215,35.39429],[-94.433915,35.387391],[-94.431515,35.369591],[-94.437774,35.239271],[-94.45753,34.642961],[-94.485875,33.637867],[-94.487514,33.628939],[-94.491503,33.625115],[-94.520725,33.616567],[-94.526291,33.619203],[-94.528928,33.62184],[-94.529221,33.634437],[-94.533322,33.63766],[-94.549142,33.635902],[-94.552658,33.638246],[-94.552072,33.65348],[-94.557052,33.656702],[-94.570821,33.654945],[-94.572286,33.656995],[-94.569357,33.663441],[-94.569943,33.66637],[-94.57962,33.677623],[-94.586641,33.678968],[-94.596895,33.671351],[-94.603047,33.671351],[-94.607442,33.67223],[-94.621211,33.681018],[-94.627656,33.677796],[-94.635273,33.669886],[-94.64289,33.668421],[-94.646113,33.6693],[-94.648457,33.673401],[-94.648457,33.684534],[-94.652265,33.690979],[-94.659167,33.692138],[-94.684792,33.684353],[-94.707858,33.686876],[-94.710088,33.68815],[-94.710725,33.691654],[-94.709451,33.699617],[-94.711043,33.705669],[-94.719006,33.708217],[-94.724102,33.705669],[-94.728243,33.699617],[-94.732384,33.700254],[-94.737161,33.704713],[-94.739072,33.710128],[-94.73748,33.716179],[-94.739391,33.72255],[-94.742576,33.727009],[-94.759139,33.729557],[-94.762961,33.731787],[-94.767739,33.73752],[-94.766465,33.750897],[-94.770924,33.754401],[-94.775064,33.755038],[-94.789716,33.74612],[-94.798634,33.744527],[-94.812012,33.751853],[-94.817427,33.752172],[-94.824753,33.749305],[-94.826027,33.74389],[-94.830804,33.740068],[-94.849296,33.739585],[-94.8693,33.745871],[-94.87708,33.75222],[-94.876033,33.760771],[-94.879218,33.764912],[-94.886226,33.764594],[-94.902276,33.776289],[-94.911427,33.778383],[-94.919614,33.786305],[-94.916834,33.804617],[-94.91945,33.810176],[-94.924518,33.812792],[-94.9358,33.810339],[-94.944302,33.812138],[-94.948716,33.818023],[-94.949533,33.825708],[-94.957676,33.835004],[-94.964401,33.837021],[-94.968895,33.860916],[-94.973411,33.861731],[-94.98165,33.852284],[-94.988487,33.851],[-94.992671,33.852455],[-95.000223,33.862505],[-95.008376,33.866089],[-95.022325,33.859813],[-95.046568,33.862565],[-95.049025,33.86409],[-95.061065,33.895292],[-95.065492,33.899585],[-95.07126,33.901597],[-95.078905,33.898377],[-95.084002,33.89328],[-95.090441,33.89328],[-95.093929,33.895963],[-95.095002,33.904816],[-95.10077,33.912193],[-95.103318,33.913669],[-95.110964,33.912998],[-95.119951,33.915815],[-95.122365,33.918632],[-95.121184,33.931307],[-95.1247,33.934675],[-95.131056,33.936925],[-95.161109,33.937598],[-95.184075,33.950353],[-95.219358,33.961567],[-95.230491,33.960764],[-95.252906,33.933648],[-95.250737,33.917083],[-95.253095,33.905444],[-95.26385,33.899256],[-95.272542,33.902055],[-95.277846,33.900877],[-95.280351,33.896751],[-95.283445,33.877746],[-95.287865,33.874946],[-95.294789,33.875388],[-95.325572,33.885704],[-95.333452,33.886286],[-95.334854,33.876831],[-95.339122,33.868873],[-95.407795,33.866308],[-95.44737,33.86885],[-95.463346,33.872313],[-95.461499,33.883686],[-95.464925,33.886709],[-95.469962,33.886105],[-95.478575,33.879301],[-95.492028,33.874822],[-95.502304,33.874742],[-95.506085,33.87639],[-95.506234,33.886306],[-95.510063,33.890135],[-95.515302,33.891142],[-95.533283,33.881162],[-95.545197,33.880294],[-95.552085,33.888422],[-95.549145,33.90795],[-95.559414,33.930179],[-95.563424,33.932193],[-95.585945,33.93448],[-95.599678,33.934247],[-95.603657,33.927195],[-95.636978,33.906613],[-95.647273,33.905976],[-95.659818,33.909092],[-95.665338,33.908132],[-95.669978,33.905844],[-95.684831,33.890232],[-95.696962,33.885218],[-95.71354,33.885124],[-95.728449,33.893704],[-95.737508,33.895967],[-95.747335,33.895756],[-95.756367,33.892625],[-95.761916,33.883402],[-95.762559,33.874367],[-95.757458,33.867957],[-95.753513,33.856464],[-95.758016,33.85008],[-95.772067,33.843817],[-95.776255,33.845145],[-95.789867,33.857686],[-95.805149,33.861304],[-95.820596,33.858465],[-95.821666,33.856633],[-95.818976,33.844456],[-95.820784,33.840564],[-95.828245,33.836054],[-95.837516,33.83564],[-95.859469,33.852456],[-95.881292,33.860627],[-95.915961,33.881148],[-95.935198,33.887101],[-95.937202,33.884652],[-95.935308,33.878724],[-95.936631,33.870615],[-95.941267,33.861619],[-95.944284,33.859811],[-95.951609,33.857017],[-95.972156,33.856371],[-95.980966,33.859307],[-95.984254,33.864403],[-95.991487,33.866869],[-95.996748,33.864403],[-95.998351,33.851049],[-96.005296,33.845505],[-96.019599,33.840566],[-96.022065,33.843196],[-96.022229,33.850923],[-96.029463,33.852402],[-96.037191,33.841245],[-96.048834,33.836468],[-96.084626,33.846656],[-96.100095,33.847971],[-96.101473,33.846709],[-96.097638,33.837935],[-96.097448,33.832725],[-96.09936,33.83047],[-96.109993,33.832396],[-96.122951,33.839964],[-96.14807,33.837799],[-96.15163,33.831946],[-96.148792,33.819197],[-96.150765,33.816987],[-96.164217,33.817001],[-96.17589,33.814627],[-96.178964,33.810553],[-96.17515,33.801951],[-96.162123,33.79614],[-96.162757,33.788769],[-96.169452,33.770131],[-96.178059,33.760518],[-96.1999,33.752117],[-96.220521,33.74739],[-96.229023,33.748021],[-96.269896,33.768405],[-96.277269,33.769735],[-96.292482,33.766419],[-96.303009,33.750878],[-96.307389,33.735005],[-96.307035,33.719987],[-96.309964,33.710489],[-96.316925,33.698997],[-96.321103,33.6951],[-96.348306,33.686379],[-96.355946,33.687155],[-96.362198,33.691818],[-96.363253,33.70105],[-96.36959,33.716809],[-96.408469,33.751192],[-96.422643,33.776041],[-96.436455,33.78005],[-96.448045,33.781031],[-96.459154,33.775232],[-96.500268,33.772583],[-96.511914,33.781478],[-96.515912,33.787795],[-96.516584,33.803168],[-96.526655,33.820891],[-96.532865,33.823005],[-96.551223,33.819129],[-96.572937,33.819098],[-96.592926,33.830916],[-96.623155,33.841483],[-96.62929,33.845488],[-96.628969,33.852407],[-96.61197,33.869016],[-96.597348,33.875101],[-96.590112,33.880665],[-96.58536,33.888948],[-96.587934,33.894784],[-96.628294,33.894477],[-96.659896,33.916666],[-96.667187,33.91694],[-96.673449,33.912278],[-96.680947,33.896204],[-96.683464,33.884217],[-96.682209,33.873876],[-96.684727,33.862905],[-96.690708,33.849959],[-96.699574,33.839049],[-96.712422,33.831633],[-96.761588,33.824406],[-96.766235,33.825458],[-96.770676,33.829621],[-96.776766,33.841976],[-96.780569,33.860098],[-96.783485,33.863534],[-96.794276,33.868886],[-96.832157,33.874835],[-96.839778,33.868396],[-96.841592,33.852894],[-96.845896,33.848975],[-96.85609,33.84749],[-96.866438,33.853149],[-96.88301,33.868019],[-96.895728,33.896414],[-96.899442,33.933728],[-96.907387,33.950025],[-96.9163,33.957798],[-96.922114,33.959579],[-96.944611,33.949217]]]},\"properties\":{\"name\":\"Oklahoma\",\"nation\":\"USA \"}}]}","volume":"105","issue":"6","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-10-20","publicationStatus":"PW","scienceBaseUri":"5639daf8e4b0d6133fe732c8","contributors":{"authors":[{"text":"Hough, Susan E. 0000-0002-5980-2986 hough@usgs.gov","orcid":"https://orcid.org/0000-0002-5980-2986","contributorId":587,"corporation":false,"usgs":true,"family":"Hough","given":"Susan","email":"hough@usgs.gov","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":579028,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Page, Morgan T. 0000-0001-9321-2990 mpage@usgs.gov","orcid":"https://orcid.org/0000-0001-9321-2990","contributorId":3762,"corporation":false,"usgs":true,"family":"Page","given":"Morgan","email":"mpage@usgs.gov","middleInitial":"T.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":579029,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70159444,"text":"70159444 - 2015 - Validation of a spatial model used to locate fish spawning reef construction sites in the St. Clair–Detroit River system","interactions":[],"lastModifiedDate":"2015-12-21T13:37:10","indexId":"70159444","displayToPublicDate":"2015-11-03T12:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Validation of a spatial model used to locate fish spawning reef construction sites in the St. Clair–Detroit River system","docAbstract":"Lake sturgeon (Acipenser fulvescens) populations have suffered precipitous declines in the St. Clair–Detroit River system, following the removal of gravel spawning substrates and overfishing in the late 1800s to mid-1900s. To assist the remediation of lake sturgeon spawning habitat, three hydrodynamic models were integrated into a spatial model to identify areas in two large rivers, where water velocities were appropriate for the restoration of lake sturgeon spawning habitat. Here we use water velocity data collected with an acoustic Doppler current profiler (ADCP) to assess the ability of the spatial model and its sub-models to correctly identify areas where water velocities were deemed suitable for restoration of fish spawning habitat. ArcMap 10.1 was used to create raster grids of water velocity data from model estimates and ADCP measurements which were compared to determine the percentage of cells similarly classified as unsuitable, suitable, or ideal for fish spawning habitat remediation. The spatial model categorized 65% of the raster cells the same as depth-averaged water velocity measurements from the ADCP and 72% of the raster cells the same as surface water velocity measurements from the ADCP. Sub-models focused on depth-averaged velocities categorized the greatest percentage of cells similar to ADCP measurements where 74% and 76% of cells were the same as depth-averaged water velocity measurements. Our results indicate that integrating depth-averaged and surface water velocity hydrodynamic models may have biased the spatial model and overestimated suitable spawning habitat. A model solely integrating depth-averaged velocity models could improve identification of areas suitable for restoration of fish spawning habitat.
","language":"English","publisher":"ScienceDirect","doi":"10.1016/j.jglr.2015.09.019","usgsCitation":"Fischer, J.L., Bennion, D., Roseman, E., and Manny, B.A., 2015, Validation of a spatial model used to locate fish spawning reef construction sites in the St. Clair–Detroit River system: Journal of Great Lakes Research, v. 41, no. 4, p. 1178-1184, https://doi.org/10.1016/j.jglr.2015.09.019.","productDescription":"7 p.","startPage":"1178","endPage":"1184","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064602","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":310982,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Michigan","otherGeospatial":"Detroit River, Lake St. Clair","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.496337890625,\n 42.81555136172695\n ],\n [\n -82.55126953124999,\n 42.62991729384455\n ],\n [\n -82.6611328125,\n 42.70867781741311\n ],\n [\n -82.8424072265625,\n 42.65820178455667\n ],\n [\n -82.91107177734375,\n 42.48425110546248\n ],\n [\n -82.9742431640625,\n 42.36057345238458\n ],\n [\n -83.14453125,\n 42.285437007491545\n ],\n [\n -83.21868896484375,\n 42.114523952464246\n ],\n [\n -83.2159423828125,\n 42.01869237684385\n ],\n [\n -83.08959960937499,\n 42.05948945192712\n ],\n [\n -83.067626953125,\n 42.28340504748079\n ],\n [\n -82.93853759765625,\n 42.33215399891373\n ],\n [\n -82.74627685546874,\n 42.28340504748079\n ],\n [\n -82.452392578125,\n 42.3037216984154\n ],\n [\n -82.39471435546875,\n 42.36869093640926\n ],\n [\n -82.3919677734375,\n 42.49640294093708\n ],\n [\n -82.49908447265625,\n 42.5995982130586\n ],\n [\n -82.44964599609374,\n 42.817566071581616\n ],\n [\n -82.496337890625,\n 42.81555136172695\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"41","issue":"4","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5639db04e4b0d6133fe732d4","contributors":{"authors":[{"text":"Fischer, Jason L. 0000-0001-7226-6500 jfischer@usgs.gov","orcid":"https://orcid.org/0000-0001-7226-6500","contributorId":149532,"corporation":false,"usgs":true,"family":"Fischer","given":"Jason","email":"jfischer@usgs.gov","middleInitial":"L.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":578711,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bennion, David 0000-0003-4927-4195 dbennion@usgs.gov","orcid":"https://orcid.org/0000-0003-4927-4195","contributorId":149533,"corporation":false,"usgs":true,"family":"Bennion","given":"David","email":"dbennion@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":578712,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Roseman, Edward F. eroseman@usgs.gov","contributorId":138592,"corporation":false,"usgs":true,"family":"Roseman","given":"Edward F.","email":"eroseman@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":578713,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Manny, Bruce A. 0000-0002-4074-9329 bmanny@usgs.gov","orcid":"https://orcid.org/0000-0002-4074-9329","contributorId":3699,"corporation":false,"usgs":true,"family":"Manny","given":"Bruce","email":"bmanny@usgs.gov","middleInitial":"A.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":578714,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70159470,"text":"70159470 - 2015 - Investing in citizen science can improve natural resource management and environmental protection","interactions":[],"lastModifiedDate":"2017-07-12T15:31:47","indexId":"70159470","displayToPublicDate":"2015-11-03T12:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2121,"text":"Issues in Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Investing in citizen science can improve natural resource management and environmental protection","docAbstract":"Citizen science has made substantive contributions to science for hundreds of years. More recently, it has contributed to many articles in peer-reviewed scientific journals and has influenced natural resource management and environmental protection decisions and policies across the nation. Over the last 10 years, citizen science—participation by the public in a scientific project—has seen explosive growth in the United States, particularly in ecology, the environmental sciences, and related fields of inquiry. In this report, we explore the current use of citizen science in natural resource and environmental science and decision making in the United States and describe the investments organizations might make to benefit from citizen science.
","language":"English","publisher":"Ecological Society of America","usgsCitation":"McKinley, D.C., Miller-Rushing, A.J., Ballard, H.L., Bonney, R., Brown, H., Evans, D.M., French, R.A., Parrish, J.K., Phillips, T.B., Ryan, S.F., Shanley, L.A., Shirk, J.L., Stepenuck, K.F., Weltzin, J., Wiggins, A., Boyle, O.D., Briggs, R.D., Chapin, S., Hewitt, D.A., Preuss, P.W., and Soukup, M.A., 2015, Investing in citizen science can improve natural resource management and environmental protection: Issues in Ecology, v. 19, 27 p.","productDescription":"27 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-054104","costCenters":[{"id":433,"text":"National Phenology Network","active":true,"usgs":true}],"links":[{"id":310981,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":310956,"type":{"id":15,"text":"Index Page"},"url":"https://www.esa.org/esa/science/issues/"}],"volume":"19","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5639db02e4b0d6133fe732d0","contributors":{"authors":[{"text":"McKinley, Duncan C.","contributorId":149649,"corporation":false,"usgs":false,"family":"McKinley","given":"Duncan","email":"","middleInitial":"C.","affiliations":[{"id":7134,"text":"USFS","active":true,"usgs":false}],"preferred":false,"id":579065,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Miller-Rushing, Abraham J.","contributorId":149650,"corporation":false,"usgs":false,"family":"Miller-Rushing","given":"Abraham","email":"","middleInitial":"J.","affiliations":[{"id":7237,"text":"NPS, Olympic National Park","active":true,"usgs":false}],"preferred":false,"id":579066,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ballard, Heidi L.","contributorId":149651,"corporation":false,"usgs":false,"family":"Ballard","given":"Heidi","email":"","middleInitial":"L.","affiliations":[{"id":12711,"text":"UC Davis","active":true,"usgs":false}],"preferred":false,"id":579067,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bonney, Rick","contributorId":112611,"corporation":false,"usgs":false,"family":"Bonney","given":"Rick","email":"","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":579068,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brown, Hutch","contributorId":149653,"corporation":false,"usgs":false,"family":"Brown","given":"Hutch","email":"","affiliations":[{"id":7134,"text":"USFS","active":true,"usgs":false}],"preferred":false,"id":579069,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Evans, Daniel M.","contributorId":149654,"corporation":false,"usgs":false,"family":"Evans","given":"Daniel","email":"","middleInitial":"M.","affiliations":[{"id":17680,"text":"AAAS Science & Technology Policy Fellow/NASA","active":true,"usgs":false}],"preferred":false,"id":579070,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"French, Rebecca A.","contributorId":149655,"corporation":false,"usgs":false,"family":"French","given":"Rebecca","email":"","middleInitial":"A.","affiliations":[{"id":12657,"text":"EPA NEIC","active":true,"usgs":false}],"preferred":false,"id":579071,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Parrish, Julia K.","contributorId":47270,"corporation":false,"usgs":true,"family":"Parrish","given":"Julia","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":579072,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Phillips, Tina B.","contributorId":149656,"corporation":false,"usgs":false,"family":"Phillips","given":"Tina","email":"","middleInitial":"B.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":579073,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Ryan, Sean F.","contributorId":149657,"corporation":false,"usgs":false,"family":"Ryan","given":"Sean","email":"","middleInitial":"F.","affiliations":[{"id":16905,"text":"University of Notre Dame, Dept. of Biological Sciences, Notre Dame, IN, 46556, USA","active":true,"usgs":false}],"preferred":false,"id":579074,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Shanley, Lea A.","contributorId":149658,"corporation":false,"usgs":false,"family":"Shanley","given":"Lea","email":"","middleInitial":"A.","affiliations":[{"id":17773,"text":"Wilson Center","active":true,"usgs":false}],"preferred":false,"id":579075,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Shirk, Jennifer L.","contributorId":149659,"corporation":false,"usgs":false,"family":"Shirk","given":"Jennifer","email":"","middleInitial":"L.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":579076,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Stepenuck, Kristine F.","contributorId":149660,"corporation":false,"usgs":false,"family":"Stepenuck","given":"Kristine","email":"","middleInitial":"F.","affiliations":[{"id":16117,"text":"Wisconsin DNR","active":true,"usgs":false}],"preferred":false,"id":579077,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Weltzin, Jake F. 0000-0001-8641-6645 jweltzin@usgs.gov","orcid":"https://orcid.org/0000-0001-8641-6645","contributorId":149648,"corporation":false,"usgs":true,"family":"Weltzin","given":"Jake F.","email":"jweltzin@usgs.gov","affiliations":[{"id":433,"text":"National Phenology Network","active":true,"usgs":true}],"preferred":false,"id":579064,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Wiggins, Andrea","contributorId":149661,"corporation":false,"usgs":false,"family":"Wiggins","given":"Andrea","email":"","affiliations":[{"id":17774,"text":"U New Mexico","active":true,"usgs":false}],"preferred":false,"id":579078,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Boyle, Owen D.","contributorId":149662,"corporation":false,"usgs":false,"family":"Boyle","given":"Owen","email":"","middleInitial":"D.","affiliations":[{"id":16117,"text":"Wisconsin DNR","active":true,"usgs":false}],"preferred":false,"id":579079,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Briggs, Russell D.","contributorId":149663,"corporation":false,"usgs":false,"family":"Briggs","given":"Russell","email":"","middleInitial":"D.","affiliations":[{"id":6650,"text":"SUNY - Brockport","active":true,"usgs":false}],"preferred":false,"id":579080,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Chapin, Stuart F. III","contributorId":149664,"corporation":false,"usgs":false,"family":"Chapin","given":"Stuart F.","suffix":"III","affiliations":[{"id":17775,"text":"U Alaska","active":true,"usgs":false}],"preferred":false,"id":579081,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Hewitt, David A. 0000-0002-5387-0275 dhewitt@usgs.gov","orcid":"https://orcid.org/0000-0002-5387-0275","contributorId":3767,"corporation":false,"usgs":false,"family":"Hewitt","given":"David","email":"dhewitt@usgs.gov","middleInitial":"A.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":579082,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Preuss, Peter W.","contributorId":149665,"corporation":false,"usgs":false,"family":"Preuss","given":"Peter","email":"","middleInitial":"W.","affiliations":[{"id":12657,"text":"EPA NEIC","active":true,"usgs":false}],"preferred":false,"id":579083,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Soukup, Michael A.","contributorId":149666,"corporation":false,"usgs":false,"family":"Soukup","given":"Michael","email":"","middleInitial":"A.","affiliations":[{"id":7237,"text":"NPS, Olympic National Park","active":true,"usgs":false}],"preferred":false,"id":579084,"contributorType":{"id":1,"text":"Authors"},"rank":21}]}} ]}