{"pageNumber":"1331","pageRowStart":"33250","pageSize":"25","recordCount":184769,"records":[{"id":70131482,"text":"70131482 - 2014 - Practical limitations on the use of diurnal temperature signals to quantify groundwater upwelling","interactions":[],"lastModifiedDate":"2018-09-18T16:25:14","indexId":"70131482","displayToPublicDate":"2014-11-07T17:15:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Practical limitations on the use of diurnal temperature signals to quantify groundwater upwelling","docAbstract":"<p>Groundwater upwelling to streams creates unique habitat by influencing stream water quality and temperature; upwelling zones also serve as vectors for contamination when groundwater is degraded. Temperature time series data acquired along vertical profiles in the streambed have been applied to simple analytical models to determine rates of vertical fluid flux. These models are based on the downward propagation characteristics (amplitude attenuation and phase-lag) of the surface diurnal signal. Despite the popularity of these models, there are few published characterizations of moderate-to-strong upwelling. We attribute this limitation to the thermodynamics of upwelling, under which the downward conductive signal transport from the streambed interface occurs opposite the upward advective fluid flux. Governing equations describing the advection&ndash;diffusion of heat within the streambed predict that under upwelling conditions, signal amplitude attenuation will increase, but, counterintuitively, phase-lag will decrease. Therefore the extinction (measurable) depth of the diurnal signal is very shallow, but phase lag is also short, yielding low signal to noise ratio and poor model sensitivity. Conversely, amplitude attenuation over similar sensor spacing is strong, yielding greater potential model sensitivity. Here we present streambed thermal time series over a range of moderate to strong upwelling sites in the Quashnet River, Cape Cod, Massachusetts. The predicted inverse relationship between phase-lag and rate of upwelling was observed in the field data over a range of conditions, but the observed phase-lags were consistently shorter than predicted. Analytical solutions for fluid flux based on signal amplitude attenuation return results consistent with numerical models and physical seepage meters, but the phase-lag analytical model results are generally unreasonable. Through numerical modeling we explore reasons why phase-lag may have been over-predicted by the analytical models, and develop guiding relations of diurnal temperature signal extinction depth based on stream diurnal signal amplitude, upwelling magnitude, and streambed thermal properties that will be useful in designing future experiments.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2014.09.030","usgsCitation":"Briggs, M.A., Lautz, L.K., Buckley, S.F., and Lane, J.W., 2014, Practical limitations on the use of diurnal temperature signals to quantify groundwater upwelling: Journal of Hydrology, v. 519, no. B, p. 1739-1751, https://doi.org/10.1016/j.jhydrol.2014.09.030.","productDescription":"13 p.","startPage":"1739","endPage":"1751","numberOfPages":"13","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057864","costCenters":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":295951,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":295952,"type":{"id":15,"text":"Index Page"},"url":"https://www.sciencedirect.com/science/article/pii/S0022169414007124"}],"volume":"519","issue":"B","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"545ddf17e4b0ba8303f8b62a","contributors":{"authors":[{"text":"Briggs, Martin A. 0000-0003-3206-4132 mbriggs@usgs.gov","orcid":"https://orcid.org/0000-0003-3206-4132","contributorId":4114,"corporation":false,"usgs":true,"family":"Briggs","given":"Martin","email":"mbriggs@usgs.gov","middleInitial":"A.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true},{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true}],"preferred":true,"id":521241,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lautz, Laura K.","contributorId":124523,"corporation":false,"usgs":false,"family":"Lautz","given":"Laura","email":"","middleInitial":"K.","affiliations":[{"id":5082,"text":"Syracuse University","active":true,"usgs":false}],"preferred":false,"id":521242,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Buckley, Sean F. sbuckley@usgs.gov","contributorId":3910,"corporation":false,"usgs":true,"family":"Buckley","given":"Sean","email":"sbuckley@usgs.gov","middleInitial":"F.","affiliations":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true}],"preferred":true,"id":521243,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lane, John W. Jr. jwlane@usgs.gov","contributorId":1738,"corporation":false,"usgs":true,"family":"Lane","given":"John","suffix":"Jr.","email":"jwlane@usgs.gov","middleInitial":"W.","affiliations":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true}],"preferred":false,"id":521244,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70131483,"text":"70131483 - 2014 - On the downscaling of actual evapotranspiration maps based on combination of MODIS and landsat-based actual evapotranspiration estimates","interactions":[],"lastModifiedDate":"2017-01-18T11:27:04","indexId":"70131483","displayToPublicDate":"2014-11-07T17:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"On the downscaling of actual evapotranspiration maps based on combination of MODIS and landsat-based actual evapotranspiration estimates","docAbstract":"<p>&nbsp;Downscaling is one of the important ways of utilizing the combined benefits of the high temporal resolution of Moderate Resolution Imaging Spectroradiometer (MODIS) images and fine spatial resolution of Landsat images. We have evaluated the output regression with intercept method and developed the Linear with Zero Intercept (LinZI) method for downscaling MODIS-based monthly actual evapotranspiration (AET) maps to the Landsat-scale monthly AET maps for the Colorado River Basin for 2010. We used the 8-day MODIS land surface temperature product (MOD11A2) and 328 cloud-free Landsat images for computing AET maps and downscaling. The regression with intercept method does have limitations in downscaling if the slope and intercept are computed over a large area. A good agreement was obtained between downscaled monthly AET using the LinZI method and the eddy covariance measurements from seven flux sites within the Colorado River Basin. The mean bias ranged from &minus;16 mm (underestimation) to 22 mm (overestimation) per month, and the coefficient of determination varied from 0.52 to 0.88. Some discrepancies between measured and downscaled monthly AET at two flux sites were found to be due to the prevailing flux footprint. A reasonable comparison was also obtained between downscaled monthly AET using LinZI method and the gridded FLUXNET dataset. The downscaled monthly AET nicely captured the temporal variation in sampled land cover classes. The proposed LinZI method can be used at finer temporal resolution (such as 8 days) with further evaluation. The proposed downscaling method will be very useful in advancing the application of remotely sensed images in water resources planning and management.</p>","language":"English","publisher":"MDPI","doi":"10.3390/rs61110483","usgsCitation":"Singh, R.K., Senay, G.B., Velpuri, N.M., Bohms, S., and Verdin, J.P., 2014, On the downscaling of actual evapotranspiration maps based on combination of MODIS and landsat-based actual evapotranspiration estimates: Remote Sensing, v. 6, no. 11, p. 10483-10509, https://doi.org/10.3390/rs61110483.","productDescription":"27 p.","startPage":"10483","endPage":"10509","numberOfPages":"27","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057248","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":472650,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs61110483","text":"Publisher Index Page"},{"id":295950,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":295953,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://www.mdpi.com/2072-4292/6/11/10483"}],"volume":"6","issue":"11","noUsgsAuthors":false,"publicationDate":"2014-10-30","publicationStatus":"PW","scienceBaseUri":"545ddf17e4b0ba8303f8b625","contributors":{"authors":[{"text":"Singh, Ramesh K. 0000-0002-8164-3483 rsingh@usgs.gov","orcid":"https://orcid.org/0000-0002-8164-3483","contributorId":3895,"corporation":false,"usgs":true,"family":"Singh","given":"Ramesh","email":"rsingh@usgs.gov","middleInitial":"K.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":521245,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Senay, Gabriel B. 0000-0002-8810-8539 senay@usgs.gov","orcid":"https://orcid.org/0000-0002-8810-8539","contributorId":3114,"corporation":false,"usgs":true,"family":"Senay","given":"Gabriel","email":"senay@usgs.gov","middleInitial":"B.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":521246,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Velpuri, Naga Manohar 0000-0002-6370-1926 nvelpuri@usgs.gov","orcid":"https://orcid.org/0000-0002-6370-1926","contributorId":4441,"corporation":false,"usgs":true,"family":"Velpuri","given":"Naga","email":"nvelpuri@usgs.gov","middleInitial":"Manohar","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":521247,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bohms, Stefanie 0000-0002-2979-4655 sbohms@usgs.gov","orcid":"https://orcid.org/0000-0002-2979-4655","contributorId":3148,"corporation":false,"usgs":true,"family":"Bohms","given":"Stefanie","email":"sbohms@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":521248,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Verdin, James P. 0000-0003-0238-9657 verdin@usgs.gov","orcid":"https://orcid.org/0000-0003-0238-9657","contributorId":720,"corporation":false,"usgs":true,"family":"Verdin","given":"James","email":"verdin@usgs.gov","middleInitial":"P.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":521249,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70129577,"text":"fs20143106 - 2014 - The 3D Elevation Program: summary for Kansas","interactions":[],"lastModifiedDate":"2016-08-17T15:20:05","indexId":"fs20143106","displayToPublicDate":"2014-11-07T16:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-3106","title":"The 3D Elevation Program: summary for Kansas","docAbstract":"<p>Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, national security, recreation, and many others. For the State of Kansas, elevation data are critical for agriculture and precision farming, natural resources conservation, flood risk management, infrastructure and construction management, geologic resource assessment and hazard mitigation, and other business uses. Today, high-density light detection and ranging (lidar) data are the primary sources for deriving elevation models and other datasets. Federal, State, Tribal, and local agencies work in partnership to (1) replace data that are older and of lower quality and (2) provide coverage where publicly accessible data do not exist. A joint goal of State and Federal partners is to acquire consistent, statewide coverage to support existing and emerging applications enabled by lidar data.</p>\n<p>The National Enhanced Elevation Assessment evaluated multiple elevation data acquisition options to determine the optimal data quality and data replacement cycle relative to cost to meet the identified requirements of the user community. The evaluation demonstrated that lidar acquisition at quality level 2 for the conterminous United States and quality level 5 interferometric synthetic aperture radar (ifsar) data for Alaska with a 6- to 10-year acquisition cycle provided the highest benefit/cost ratios. The 3D Elevation Program (3DEP) initiative selected an 8-year acquisition cycle for the respective quality levels. 3DEP, managed by the U.S. Geological Survey, the Office of Management and Budget Circular A&ndash;16 lead agency for terrestrial elevation data, responds to the growing need for high-quality topographic data and a wide range of other 3D representations of the Nation&rsquo;s natural and constructed features.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20143106","usgsCitation":"Carswell, W., 2014, The 3D Elevation Program: summary for Kansas: U.S. Geological Survey Fact Sheet 2014-3106, 2 p., https://doi.org/10.3133/fs20143106.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-059303","costCenters":[{"id":423,"text":"National Geospatial 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William J. Jr. carswell@usgs.gov","contributorId":1787,"corporation":false,"usgs":true,"family":"Carswell","given":"William J.","suffix":"Jr.","email":"carswell@usgs.gov","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":false,"id":519897,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70128252,"text":"sir20145193 - 2014 - An initial abstraction and constant loss model, and methods for estimating unit hydrographs, peak streamflows, and flood volumes for urban basins in Missouri","interactions":[],"lastModifiedDate":"2014-11-07T13:13:55","indexId":"sir20145193","displayToPublicDate":"2014-11-07T11:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-5193","title":"An initial abstraction and constant loss model, and methods for estimating unit hydrographs, peak streamflows, and flood volumes for urban basins in Missouri","docAbstract":"<p>Streamflow data, basin characteristics, and rainfall data from 39 streamflow-gaging stations for urban areas in and adjacent to Missouri were used by the U.S. Geological Survey in cooperation with the Metropolitan Sewer District of St. Louis to develop an initial abstraction and constant loss model (a time-distributed basin-loss model) and a gamma unit hydrograph (GUH) for urban areas in Missouri. Study-specific methods to determine peak streamflow and flood volume for a given rainfall event also were developed.</p>\n<p>&nbsp;</p>\n<p>Distinct basin characteristics were evaluated and selected for use on the basis of their theoretical relation to flow, results from previous studies, and the ability to reliably measure the basin characteristic using digital datasets and geographic information system (GIS) technology. The key basin characteristics determined or computed for each of the 39 basins upstream from the streamflow-gaging stations were drainage area, percent impervious area, main-channel slope based on the 10- and 85-percent length method, percentage of the basin area in storage (lakes, ponds, reservoirs, wetlands), the composite Natural Resources Conservation Service curve number estimated from a combination of the soil type data and land-use characteristics, and the streamflow variability index developed for the recently completed study of low-flow regression in Missouri.</p>\n<p>&nbsp;</p>\n<p>Characteristics of spatial and temporal rainfall distribution came from the next generation weather radar (NEXRAD) network. Procedures were developed for this study to convert the variable radar sweep rate into a 5-minute total rainfall hyetograph using data from the radar bin at the centroid of a given basin. Additional characteristics determined for each storm on the basin included the 5-day and 14-day antecedent rainfall, estimated from the mean of daily rainfall values from various rain gages in the area.</p>\n<p>&nbsp;</p>\n<p>The database of observed rainfall and runoff events for the 39 basins upstream from the streamflow-gaging stations was analyzed to compute the optimal storm-specific initial abstraction and constant loss values, as well as the time to peak, peak streamflow, and shape factor values of the GUH. The optimal storm-specific values were used to develop a regional regression equation for initial abstraction; conversely, the constant loss was estimated not by regression but from either a generalized or specific regional mean value. The optimal storm-specific values of GUH time to peak, GUH peak streamflow, and GUH shape factor were used to develop regression equations for the GUH.</p>\n<p>&nbsp;</p>\n<p>The regression equations for the GUH initially were tested alone, and then were combined with the appropriate regional regression equation for initial abstraction and both the generalized regional and specific regional mean constant loss values. For the GUH regression equations, the interquartile range was substantially smaller than the range spanned by the minimum and maximum values, which indicates most of the errors have much smaller variation, and the minimum and maximum values may be extreme outliers. The central tendency of the regressed errors for peak streamflow and runoff hydrograph volume were both approximately zero, which implies a generally unbiased estimation of these values. The mean and median of the regressed errors for time to peak streamflow were both small but greater than zero, which implies the GUH regression equations create a hydrograph that has a peak that is later in time than observed. Specifically, the regressed times indicate an offset of about 10 minutes, on average, from observed. The mean and median of the regressed errors for widths of the runoff hydrograph at 50 and 75 percent were less than zero, which implies the GUH tends to slightly underestimate these widths compared to the observed.</p>\n<p>&nbsp;</p>\n<p>The appropriate regional initial abstraction regression equation was combined with both the generalized and the specific regional mean constant loss values and the GUH regression equations. Both the generalized regional mean constant loss and specific regional mean constant loss forms of the basin-loss model worked equally well to model the observed runoff hydrograph based on the error analysis, and neither model seems to make a consistently better approximation. Both initial abstraction and constant loss models combined with the GUH regression equations were further validated using several storms available after the start of the project in early 2011 with similar but consistently higher error results. If these methods are used in an urban area in Missouri other than those examined in this study, advice to the user is given to consider using the generalized regional mean values. If these methods are used in an urban area that is a subbasin of one of the basins in this study, advice to the user is given to consider using the specific regional mean values.</p>\n<p>&nbsp;</p>\n<p>The rainfall-runoff pairs from the storm-specific GUH analysis were further analyzed against various basin and rainfall characteristics to develop equations to estimate the peak streamflow and flood volume based on a quantity of rainfall on the basin.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145193","collaboration":"Prepared in cooperation with the Metropolitan Sewer District of St. Louis","usgsCitation":"Huizinga, R.J., 2014, An initial abstraction and constant loss model, and methods for estimating unit hydrographs, peak streamflows, and flood volumes for urban basins in Missouri: U.S. Geological Survey Scientific Investigations Report 2014-5193, Report: x, 59 p.; Downloads Directory, https://doi.org/10.3133/sir20145193.","productDescription":"Report: x, 59 p.; Downloads Directory","numberOfPages":"74","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057930","costCenters":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true}],"links":[{"id":295937,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145193.jpg"},{"id":295934,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5193/"},{"id":295935,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5193/pdf/sir2014-5193.pdf"},{"id":295936,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2014/5193/downloads/"}],"country":"United States","state":"Missouri","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"545ddf16e4b0ba8303f8b61f","contributors":{"authors":[{"text":"Huizinga, Richard J. 0000-0002-2940-2324 huizinga@usgs.gov","orcid":"https://orcid.org/0000-0002-2940-2324","contributorId":2089,"corporation":false,"usgs":true,"family":"Huizinga","given":"Richard","email":"huizinga@usgs.gov","middleInitial":"J.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":519683,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70126525,"text":"70126525 - 2014 - Observations of elk movement patterns on Fossil Butte National Monument","interactions":[],"lastModifiedDate":"2014-12-09T12:39:53","indexId":"70126525","displayToPublicDate":"2014-11-07T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":3,"text":"Organization Series"},"seriesTitle":{"id":234,"text":"WLCI Fact Sheet","active":false,"publicationSubtype":{"id":3}},"seriesNumber":"6","title":"Observations of elk movement patterns on Fossil Butte National Monument","docAbstract":"<p><span>The elk herd that frequents Fossil Butte National Monument, a subset of the West Green River elk population, provides visitors with seasonal opportunities to view an iconic species of the western United States. Throughout the year, these elk range across a variety of private, State, and Federal lands within close proximity to the Monument. These lands are managed differently for various uses which can create challenging wildlife-management issues and influence the herd&rsquo;s seasonal movements and distribution. Research lead by the USGS investigates some of the factors associated with these seasonal changes.</span></p>","language":"English","publisher":"Wyoming Landscape Conservation Initiative","publisherLocation":"Rock Springs, WY","usgsCitation":"Olexa, E.M., Soileau, S.C., and Allen, L., 2014, Observations of elk movement patterns on Fossil Butte National Monument: WLCI Fact Sheet 6, 2 p.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-059430","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":296531,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/70126525.jpg"},{"id":295948,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/wlci/fs/6/"},{"id":296530,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/wlci/fs/6/pdf/wlci6.pdf","size":"2.65 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Wyoming","otherGeospatial":"Fossil Butte National Monument","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -110.91522216796875,\n              41.76106872528616\n            ],\n            [\n              -110.91522216796875,\n              41.916585116228354\n            ],\n            [\n              -110.67901611328125,\n              41.916585116228354\n            ],\n            [\n              -110.67901611328125,\n              41.76106872528616\n            ],\n            [\n              -110.91522216796875,\n              41.76106872528616\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54882b5be4b02acb4f0c8c45","contributors":{"authors":[{"text":"Olexa, Edward M. 0000-0002-2000-6798 eolexa@usgs.gov","orcid":"https://orcid.org/0000-0002-2000-6798","contributorId":4448,"corporation":false,"usgs":true,"family":"Olexa","given":"Edward","email":"eolexa@usgs.gov","middleInitial":"M.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":524765,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Soileau, Suzanna Carrithers. 0000-0002-4331-0098 ssoileau@usgs.gov","orcid":"https://orcid.org/0000-0002-4331-0098","contributorId":4427,"corporation":false,"usgs":true,"family":"Soileau","given":"Suzanna","email":"ssoileau@usgs.gov","middleInitial":"Carrithers.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":false,"id":524766,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Allen, Leslie A. laallen@usgs.gov","contributorId":358,"corporation":false,"usgs":true,"family":"Allen","given":"Leslie A.","email":"laallen@usgs.gov","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":false,"id":524767,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70114464,"text":"70114464 - 2014 - Using multiple data sets to populate probabilistic volcanic event trees","interactions":[],"lastModifiedDate":"2016-06-28T16:29:33","indexId":"70114464","displayToPublicDate":"2014-11-07T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Using multiple data sets to populate probabilistic volcanic event trees","docAbstract":"<p>The key parameters one needs to forecast outcomes of volcanic unrest are hidden kilometers beneath the Earth&rsquo;s surface, and volcanic systems are so complex that there will invariably be stochastic elements in the evolution of any unrest. Fortunately, there is sufficient regularity in behaviour that some, perhaps many, eruptions can be forecast with enough certainty for populations to be evacuated and kept safe. Volcanologists charged with forecasting eruptions must try to understand each volcanic system well enough that unrest can be interpreted in terms of pre-eruptive process, but must simultaneously recognize and convey uncertainties in their assessment. We have found that use of event trees helps to focus discussion, integrate data from multiple sources, reach consensus among scientists about both pre-eruptive process and uncertainties and, in some cases, to explain all of this to officials. Figure 1 shows a generic volcanic event tree from Newhall and Hoblitt (2002) that can be modified as needed for each specific volcano. This paper reviews how we and our colleagues have used such trees during a number of volcanic crises worldwide, for rapid hazard assessments in situations in which more formal expert elicitations could not be conducted. We describe how Multiple Data Sets can be used to estimate probabilities at each node and branch. We also present case histories of probability estimation during crises, how the estimates were used by public officials, and some suggestions for future improvements.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Volcanic Hazards, Risks and Disasters","language":"English","publisher":"Elsevier","doi":"10.1016/B978-0-12-396453-3.00008-3","usgsCitation":"Newhall, C.G., and Pallister, J.S., 2014, Using multiple data sets to populate probabilistic volcanic event trees, chap. <i>of</i> Volcanic Hazards, Risks and Disasters, p. 203-232, https://doi.org/10.1016/B978-0-12-396453-3.00008-3.","productDescription":"30 p.","startPage":"203","endPage":"232","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-055823","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":324570,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57739fb8e4b07657d1a90da1","contributors":{"authors":[{"text":"Newhall, C. G.","contributorId":93056,"corporation":false,"usgs":true,"family":"Newhall","given":"C.","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":519002,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pallister, John S. 0000-0002-2041-2147 jpallist@usgs.gov","orcid":"https://orcid.org/0000-0002-2041-2147","contributorId":2024,"corporation":false,"usgs":true,"family":"Pallister","given":"John","email":"jpallist@usgs.gov","middleInitial":"S.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":519001,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70118093,"text":"ds862 - 2014 - USGS Arctic Ocean Carbon Cruise 2012: Field Activity L-01-12-AR to collect carbon data in the Arctic Ocean, August-September 2012","interactions":[],"lastModifiedDate":"2014-11-07T13:27:04","indexId":"ds862","displayToPublicDate":"2014-11-06T16:30:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"862","title":"USGS Arctic Ocean Carbon Cruise 2012: Field Activity L-01-12-AR to collect carbon data in the Arctic Ocean, August-September 2012","docAbstract":"<p>From August 25 to September 27, 2012, the United States Coast Guard Cutter (USCGC) <em>Healy</em> was part of an <a href=\"http://continentalshelf.gov/\">Extended Continental Shelf Project</a>&nbsp;to determine the limits of the extended continental shelf in the Arctic. On a non-interference basis, a USGS ocean acidification team participated on the cruise to collect baseline water data in the Arctic. The collection of data extended from coastal waters near Barrow, Alaska, to 83&deg;2'N., -175&deg;36'W., and southward back to coastal waters near Barrow and on to Dutch Harbor, Alaska. As a consequence, a number of hypotheses were tested and questions asked associated with ocean acidification, including:</p>\n<p>&nbsp;</p>\n<ul>\n<li>What is the saturation state for different parts of the basin?</li>\n<li>What factors drive the saturation state in the different parts of the basin?</li>\n<li>How does saturation state compare to other regions?</li>\n<li>How do the carbon fluxes compare in the different parts of the basin?</li>\n<li>What is the buffering capacity of the water (Revelle factor)?</li>\n<li>What kind of variability does carbon demonstrate in the Arctic (near shore versus offshore and diurnal)?</li>\n</ul>\n<p>&nbsp;</p>\n<p>During the cruise, underway continuous and discrete water samples were collected, and discrete water samples were collected at stations to document the carbonate chemistry of the Arctic waters and quantify the saturation state of seawater with respect to calcium carbonate. These data are critical for providing baseline information in areas where no data have existed prior and will also be used to test existing models and predict future trends.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds862","usgsCitation":"Robbins, L.L., Wynn, J., Knorr, P.O., Onac, B., Lisle, J.T., McMullen, K.Y., Yates, K.K., Byrne, R., and Liu, X., 2014, USGS Arctic Ocean Carbon Cruise 2012: Field Activity L-01-12-AR to collect carbon data in the Arctic Ocean, August-September 2012: U.S. Geological Survey Data Series 862, HTML Document, https://doi.org/10.3133/ds862.","productDescription":"HTML Document","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2012-08-01","temporalEnd":"2012-09-30","ipdsId":"IP-051020","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":295933,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds862.jpg"},{"id":295931,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0862/"},{"id":295932,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0862/ds862_abstract.html"}],"country":"United States","otherGeospatial":"Arctic Ocean","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"545c8da2e4b0ba8303f703c0","contributors":{"authors":[{"text":"Robbins, Lisa L. 0000-0003-3681-1094 lrobbins@usgs.gov","orcid":"https://orcid.org/0000-0003-3681-1094","contributorId":422,"corporation":false,"usgs":true,"family":"Robbins","given":"Lisa","email":"lrobbins@usgs.gov","middleInitial":"L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":519133,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wynn, Jonathan","contributorId":9943,"corporation":false,"usgs":false,"family":"Wynn","given":"Jonathan","affiliations":[],"preferred":false,"id":524457,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Knorr, Paul O. pknorr@usgs.gov","contributorId":3691,"corporation":false,"usgs":true,"family":"Knorr","given":"Paul","email":"pknorr@usgs.gov","middleInitial":"O.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":524458,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Onac, Bogdan","contributorId":127356,"corporation":false,"usgs":false,"family":"Onac","given":"Bogdan","affiliations":[],"preferred":false,"id":524459,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lisle, John T. 0000-0002-5447-2092 jlisle@usgs.gov","orcid":"https://orcid.org/0000-0002-5447-2092","contributorId":2944,"corporation":false,"usgs":true,"family":"Lisle","given":"John","email":"jlisle@usgs.gov","middleInitial":"T.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":524460,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McMullen, Katherine Y. kmcmullen@usgs.gov","contributorId":2148,"corporation":false,"usgs":true,"family":"McMullen","given":"Katherine","email":"kmcmullen@usgs.gov","middleInitial":"Y.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":524461,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Yates, Kimberly K. 0000-0001-8764-0358 kyates@usgs.gov","orcid":"https://orcid.org/0000-0001-8764-0358","contributorId":420,"corporation":false,"usgs":true,"family":"Yates","given":"Kimberly","email":"kyates@usgs.gov","middleInitial":"K.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":524462,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Byrne, Robert H.","contributorId":83260,"corporation":false,"usgs":true,"family":"Byrne","given":"Robert H.","affiliations":[],"preferred":false,"id":524463,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Liu, Xuewu","contributorId":87676,"corporation":false,"usgs":true,"family":"Liu","given":"Xuewu","email":"","affiliations":[],"preferred":false,"id":524464,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70120966,"text":"ofr20141025B - 2014 - Earthquake catalog for estimation of maximum earthquake magnitude, Central and Eastern United States: Part B, historical earthquakes","interactions":[],"lastModifiedDate":"2014-11-14T11:42:22","indexId":"ofr20141025B","displayToPublicDate":"2014-11-06T14:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-1025","chapter":"B","title":"Earthquake catalog for estimation of maximum earthquake magnitude, Central and Eastern United States: Part B, historical earthquakes","docAbstract":"<p>Computation of probabilistic earthquake hazard requires an estimate of Mmax: the moment magnitude of the largest earthquake that is thought to be possible within a specified geographic region. The region specified in this report is the Central and Eastern United States and adjacent Canada. Parts A and B of this report describe the construction of a global catalog of moderate to large earthquakes that occurred worldwide in tectonic analogs of the Central and Eastern United States. Examination of histograms of the magnitudes of these earthquakes allows estimation of Central and Eastern United States Mmax. The catalog and Mmax estimates derived from it are used in the 2014 edition of the U.S. Geological Survey national seismic-hazard maps. Part A deals with prehistoric earthquakes, and this part deals with historical events.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141025B","usgsCitation":"Wheeler, R.L., 2014, Earthquake catalog for estimation of maximum earthquake magnitude, Central and Eastern United States: Part B, historical earthquakes: U.S. Geological Survey Open-File Report 2014-1025, Report: iii, 30 p.; 1 Table, https://doi.org/10.3133/ofr20141025B.","productDescription":"Report: iii, 30 p.; 1 Table","numberOfPages":"33","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-057626","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":295927,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141025B.jpg"},{"id":295774,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1025/b/"},{"id":295925,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1025/b/pdf/ofr2014-1025b.pdf","size":"617 kB","linkFileType":{"id":1,"text":"pdf"}},{"id":295926,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2014/1025/b/downloads/table8.xlsx","text":"Table 8","size":"54.9 kB","linkFileType":{"id":3,"text":"xlsx"}}],"country":"United States","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"545c8d9ae4b0ba8303f70367","contributors":{"authors":[{"text":"Wheeler, Russell L. wheeler@usgs.gov","contributorId":858,"corporation":false,"usgs":true,"family":"Wheeler","given":"Russell","email":"wheeler@usgs.gov","middleInitial":"L.","affiliations":[],"preferred":false,"id":522761,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70129027,"text":"sim3314 - 2014 - Geologic map of the west-central Buffalo National River region, northern Arkansas","interactions":[],"lastModifiedDate":"2014-11-06T13:08:05","indexId":"sim3314","displayToPublicDate":"2014-11-06T13:45:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3314","title":"Geologic map of the west-central Buffalo National River region, northern Arkansas","docAbstract":"<p>This map summarizes the geology of the west-central Buffalo National River region in the Ozark Plateaus region of northern Arkansas. Geologically, the region lies on the southern flank of the Ozark dome, an uplift that exposes oldest rocks at its center in Missouri. Physiographically, the map area spans the Springfield Plateau, a topographic surface generally held up by Mississippian cherty limestone and the higher Boston Mountains to the south, held up by Pennsylvanian rocks. The Buffalo River flows eastward through the map area, enhancing bedrock erosion of an approximately 1,600-ft- (490-m-) thick sequence of Ordovician, Mississippian, and Pennsylvanian carbonate and clastic sedimentary rocks that have been mildly deformed by a series of faults and folds. Quaternary surficial units are present as alluvial deposits along major streams, including a series of terrace deposits from the Buffalo River, as well as colluvium and landslide deposits mantling bedrock on hillslopes.</p>\n<p>&nbsp;</p>\n<p>This report provides a geologic map database of the map area that improves understanding of the regional geologic framework and its influence on the regional groundwater flow system. Furthermore, additional edits were made to the Ponca and Jasper quadrangles in the following ways: new control points on important contacts were obtained using modern GPS; recent higher resolution elevation data allowed further control on placement of contacts; some new contacts were added, in particular the contact separating the upper and lower Everton Formation.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3314","usgsCitation":"Hudson, M., and Turner, K.J., 2014, Geologic map of the west-central Buffalo National River region, northern Arkansas: U.S. Geological Survey Scientific Investigations Map 3314, 2 Plates: 58.0 x 51.5 inches and 58.0 x 29.0 inches; Downloads Directory, https://doi.org/10.3133/sim3314.","productDescription":"2 Plates: 58.0 x 51.5 inches and 58.0 x 29.0 inches; Downloads Directory","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-045630","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":295923,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sim3314.jpg"},{"id":295891,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3314/"},{"id":295920,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3314/pdf/SIM3314_west_sheet1.pdf","text":"Map Sheet 1 (West)","size":"71.1 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":295921,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3314/pdf/SIM3314_east_sheet2.pdf","text":"Map Sheet 2 (East)","size":"46.5","linkFileType":{"id":1,"text":"pdf"}},{"id":295922,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sim/3314/downloads/","text":"Downloads Directory"}],"scale":"24000","projection":"Universal Transverse Mercator projection","datum":"North American Datum of 1927","country":"United States","state":"Arkansas","otherGeospatial":"Buffalo National River","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"545c8d9ee4b0ba8303f7037e","contributors":{"authors":[{"text":"Hudson, Mark R. 0000-0003-0338-6079 mhudson@usgs.gov","orcid":"https://orcid.org/0000-0003-0338-6079","contributorId":1236,"corporation":false,"usgs":true,"family":"Hudson","given":"Mark R.","email":"mhudson@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":524264,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Turner, Kenzie J. 0000-0002-4940-3981 kturner@usgs.gov","orcid":"https://orcid.org/0000-0002-4940-3981","contributorId":496,"corporation":false,"usgs":true,"family":"Turner","given":"Kenzie","email":"kturner@usgs.gov","middleInitial":"J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":524265,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70099967,"text":"cir1393 - 2014 - Anisakiosis and pseudoterranovosis","interactions":[],"lastModifiedDate":"2018-07-06T15:12:58","indexId":"cir1393","displayToPublicDate":"2014-11-06T09:45:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":307,"text":"Circular","code":"CIR","onlineIssn":"2330-5703","printIssn":"1067-084X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1393","title":"Anisakiosis and pseudoterranovosis","docAbstract":"<p>Anisakiosis and pseudoterranovosis are parasitic diseases caused by infection with larval nematodes or roundworms of the genera <em>Anisakis</em> and <em>Pseudoterranova</em>. These infections are zoonoses, meaning they are transmissible between animals and humans and vice versa. The life cycles of <em>Anisakis</em> spp., commonly called whaleworm, and <em>Pseudoterranova</em> spp., commonly called sealworm, are complex and involve three marine hosts (invertebrates, fish, and marine mammals). Whales, dolphins, or porpoises are the definitive hosts in which Anisakis spp. become sexually mature, and seals, sea lions, or walrus are the definitive hosts of <em>Pseudoterranova</em> spp. These zoonotic parasites have medical and economic importance and can result in considerable costs to the fishing industry. Humans are accidentally infected by consuming raw, poorly cooked, cold smoked, lightly salted, or marinated marine fish or squid, the intermediate hosts infected with larval stages. Human infections are becoming more common with the popularity of eating raw fish as well as improved medical diagnostics. This report, seventh in the series of U.S. Geological Survey Circulars on zoonotic diseases, will help us to better understand the routes of anisakiosis and pseudoterranovosis infections and how best to adequately monitor these zoonotic diseases.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1393","usgsCitation":"Measures, L., 2014, Anisakiosis and pseudoterranovosis: U.S. Geological Survey Circular 1393, vi, 33 p., https://doi.org/10.3133/cir1393.","productDescription":"vi, 33 p.","numberOfPages":"44","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-048865","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":295914,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/cir1393.jpg"},{"id":295913,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1393/pdf/circ1393.pdf"},{"id":295890,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/circ/1393/"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"545c8d98e4b0ba8303f7035e","contributors":{"authors":[{"text":"Measures, Lena","contributorId":118316,"corporation":false,"usgs":true,"family":"Measures","given":"Lena","email":"","affiliations":[],"preferred":false,"id":524263,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70131570,"text":"ofr20141225 - 2014 - Ecological implications of Laurel Wilt infestation on Everglades Tree Islands, southern Florida","interactions":[],"lastModifiedDate":"2016-04-19T11:34:56","indexId":"ofr20141225","displayToPublicDate":"2014-11-06T09:30:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-1225","title":"Ecological implications of Laurel Wilt infestation on Everglades Tree Islands, southern Florida","docAbstract":"<p>There is a long history of introduced pests attacking native forest trees in the United States (Liebhold and others, 1995; Aukema and others, 2010). Well-known examples include chestnut blight that decimated the American chestnut (<i>Castanea dentata</i>), an extremely important tree in the eastern United States, both as a food source for wildlife and humans and for the wood; Dutch elm disease that attacks native elms (<i>Ulmus</i> spp.), including those commonly planted as shade trees along city streets; and the balsam wooly adelgid (Adelges piceae), an insect that is destroying Fraser firs (<i>Abies fraseri</i>) in higher elevations of Great Smoky Mountains National Park. Laurel wilt, a fungal disease transmitted by the redbay ambrosia beetle (Xyleborus glabratus), is a 21st-century example of an introduced forest pest that attacks native tree species in the laurel family (Lauraceae) (Mayfield, 2007; Hulcr and Dunn, 2011).</p><p>The introduction of laurel wilt disease has been traced to the arrival of an Asian ambrosia beetle (<i>Xyleborus glabratus</i>) at Port Wentworth, Georgia, near Savannah, in 2002, apparently accidently introduced in wooden shipping material (Mayfield, 2007). Within the next 2 years, it was determined that the non-native wood-boring insect was the vector of an undescribed species of fungus, responsible for killing large numbers of red bay (<i>Persea borbonia</i>) trees in the surrounding area. Dispersing female redbay ambrosia beetles drill into live trees and create tunnels in the wood. They carry with them fungal spores in specialized organs called mycangia at the base of each mandible and sow the spores in the tunnels they excavate. The fungus, since named Raffaelea lauricola (Harrington and others, 2008), is the food source for adults and larvae. The introduction of <i>Raffaelea lauricola</i> causes the host plant to react in such a way as to block the vascular tissue, resulting in loss of water conduction, wilt, and death (Kendra and others, 2013).</p><p>Although first seen in red bay, laurel wilt disease also kills other native trees that are members of the laurel family, including swamp bay (<i>Persea palustris</i>), silk bay (<i>Persea borbonia</i> var. <i>humilis</i>), and sassafras (<i>Sassafras albidum</i>), as well as the economically important cultivated avocado (<i>Persea americana</i>) (Fraedrich and others, 2008). This paper is concerned primarily with swamp bay, an important component of Everglades tree islands.</p><p>The spread of the redbay ambrosia beetle and its fungal symbiont has been very rapid, exceeding model predictions (Koch and Smith, 2008); by 2011, laurel wilt disease was found from the southern coastal plain of North Carolina to southern peninsular Florida. The first redbay ambrosia beetle was trapped in Miami-Dade County in March 2010, and laurel wilt disease was discovered in swamp bays in February 2011 and in commercial avocado groves about a year later (Kendra and others, 2013). By 2013, laurel wilt disease was seen in swamp bays throughout the southern Everglades in Everglades National Park, Big Cypress National Preserve, and Water Conservation Areas (WCAs) 3A and 3B (Rodgers and others, 2014).</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141225","usgsCitation":"Snyder, J.R., 2014, Ecological implications of Laurel Wilt infestation on Everglades Tree Islands, southern Florida: U.S. Geological Survey Open-File Report 2014-1225, iv, 18 p., https://doi.org/10.3133/ofr20141225.","productDescription":"iv, 18 p.","numberOfPages":"26","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-056042","costCenters":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"links":[{"id":295912,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141225.JPG"},{"id":295892,"type":{"id":15,"text":"Index 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,{"id":70129339,"text":"sir20145203 - 2014 - Selenium in the upper Blackfoot River watershed, southeastern Idaho, 2001-12","interactions":[],"lastModifiedDate":"2015-08-11T09:02:02","indexId":"sir20145203","displayToPublicDate":"2014-11-06T09:15:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-5203","title":"Selenium in the upper Blackfoot River watershed, southeastern Idaho, 2001-12","docAbstract":"<p>The upper Blackfoot River in southeastern Idaho receives runoff from 12 large phosphate mines. Waste shales that are removed to access the phosphate ore are highly enriched with selenium, resulting in elevated selenium in runoff from the mine waste dumps. In 2001, in cooperation with the Bureau of Land Management, the U.S. Geological Survey (USGS) began monitoring streamflow, selenium, and other water-quality parameters at a single location near the outlet of the upper Blackfoot River to the Blackfoot Reservoir. Water samples primarily were collected by a flow triggered, automated pump sampler, supplemented by manual point and equal-width integrated manual samples.</p>\n<p>&nbsp;</p>\n<p>The approach to monitoring concentrations and streamflow over time at a fixed location is ideal for evaluating temporal trends, but provides no information about the relative source contributions from the mine waste dumps draining into various tributaries. In 2001, the Idaho Department of Environmental Quality (IDEQ) began an annual, mid-May, synoptic survey of selenium concentrations and streamflow at 21 locations along the main stem Blackfoot River and its tributaries. Individually, neither the intensive USGS sampling at the outlet nor the IDEQ annual synoptic sampling provides a comprehensive view of selenium runoff in the Blackfoot River watershed. Together, the efforts are complementary; therefore, in this report, results are presented from both sampling efforts.</p>\n<p>&nbsp;</p>\n<p>The USGS collected time-series data from 2001 to 2012 at a fixed location, the Blackfoot River near the outlet of the reservoir, near Henry, Idaho (USGS streamgage 13063000). Dissolved selenium concentrations from 450 filtered samples collected at this site ranged from 0.5 to 11.4 micrograms per liter (&mu;g/L). The State of Idaho chronic aquatic life criterion concentration of 5 &mu;g/L was exceeded in 31 percent of the samples, with most exceedances occurring during May of each year. No exceedances of the selenium criterion were recorded in months other than April, May, or June. Concentrations of selenium in unfiltered and filtered samples were similar, and concentrations from samples collected by depth and width integrated methods were similar to those collected by grab (point) samples, indicating that the grab samples adequately represent selenium concentrations across the entire river cross section. In speciation analyses made during 2003 and 2004, the median percentage of total selenium as selenate was 81 percent, ranging from 17 to 98 percent, and the median percentage of total selenium as selenite was 19 percent, ranging from 2 to 83 percent of the total selenium. During the period of study, selenium concentrations had an upward trend during the lowflow season of August&ndash;October. Time trends were not obvious during other seasons. Selenium daily loads varied by more than a factor of 900 during the study period and ranged from 0.03 kilograms per day (kg/d) to more than 24 kg/d. Annual maximum daily loads of selenium varied over nearly a factor of 12, ranging from about 2 to 24 kg/d.</p>\n<p>&nbsp;</p>\n<p>For the annual spring synoptic samples collected by the IDEQ along the main stem Blackfoot River and major tributaries, selenium concentrations ranged from less than 2 to 870 &mu;g/L in 176 samples. In most years, the synoptic sampling showed that the majority of the selenium loads passing the USGS streamgage at the outlet of the watershed could be attributed to a single tributary, East Mill Creek, which enters the Blackfoot River through Spring Creek. Selenium loads decreased by about half from East Mill Creek before reaching the Blackfoot River, suggesting that much selenium is at least temporarily removed from the water column by uptake by aquatic vegetation or by losses to sediment. Similar decreases in selenium loads occurred through the main stem Blackfoot River before reaching the outlet in low flow years, but not in high flow years.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145203","collaboration":"Prepared in cooperation with the Bureau of Land Management","usgsCitation":"Mebane, C.A., Mladenka, G.C., Van Every, Lynn, Williams, M.L., Hardy, M.A., and Garbarino, J.R., 2014, Selenium in the upper Blackfoot River watershed, southeastern Idaho, 2001–12, with an appendix on selenium speciation analytical methods, by Garbarino, J.R. (ver.1.1, August 2015): U.S. Geological Survey Scientific Investigations Report 2014-5203, 34 p., plus appendixes, https://dx.doi.org/10.3133/sir20145203.","productDescription":"Report: vi, 34 p.; 5 Appendixes","numberOfPages":"44","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2001-01-01","temporalEnd":"2012-12-31","ipdsId":"IP-048924","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":295905,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145203.jpg"},{"id":295899,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5203/pdf/sir2014-5203.pdf","text":"Report","size":"2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2014-5203 report"},{"id":295900,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5203/downloads/sir2014-5203_appendixa.kml","text":"Appendix A","size":"7 KB"},{"id":295901,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5203/downloads/sir2014-5203_appendixb.pdf","text":"Appendix B","size":"280 KB","linkFileType":{"id":1,"text":"pdf"}},{"id":295902,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5203/downloads/sir2014-5203_appendixc.pdf","text":"Appendix C","size":"706 KB","linkFileType":{"id":1,"text":"pdf"}},{"id":295895,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5203/"},{"id":295903,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5203/downloads/sir2014-5203_appendixd.xlsx","text":"Appendix D","size":"321 KB","linkFileType":{"id":3,"text":"xlsx"}},{"id":295904,"rank":8,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5203/downloads/sir2014-5203_appendixe.pdf","text":"Appendix E","size":"507 KB","linkFileType":{"id":1,"text":"pdf"}},{"id":306562,"rank":9,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2014/5203/versionHist.pdf","linkFileType":{"id":1,"text":"pdf"}}],"scale":"100000","projection":"Transverse Mercator projection","datum":"North American Datum of 1983","country":"United States","state":"Idaho","otherGeospatial":"Blackfoot River watershed","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -111.544189453125,\n              42.49842801732158\n            ],\n            [\n              -111.544189453125,\n              42.974511174899156\n            ],\n            [\n              -111.0662841796875,\n              42.974511174899156\n            ],\n            [\n              -111.0662841796875,\n              42.49842801732158\n            ],\n            [\n              -111.544189453125,\n              42.49842801732158\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","edition":"Version 1: Originally posted November 5, 2014; Version 1.1: August 2015","contact":"<p><a href=\"mailto:dc_id@usgs.gov\">Director</a>, Idaho Water Science Center<br /> U.S. Geological Survey<br /> 230 Collins Road<br /> Boise, Idaho 83702<br /><a href=\"http://id.water.usgs.gov/\">http://id.water.usgs.gov</a>&nbsp;</p>","publishedDate":"2014-11-05","revisedDate":"2015-08-10","noUsgsAuthors":false,"publicationDate":"2014-11-05","publicationStatus":"PW","scienceBaseUri":"545c8da2e4b0ba8303f703af","contributors":{"authors":[{"text":"Mebane, Christopher A. 0000-0002-9089-0267 cmebane@usgs.gov","orcid":"https://orcid.org/0000-0002-9089-0267","contributorId":110,"corporation":false,"usgs":true,"family":"Mebane","given":"Christopher","email":"cmebane@usgs.gov","middleInitial":"A.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":524276,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mladenka, Greg","contributorId":116680,"corporation":false,"usgs":true,"family":"Mladenka","given":"Greg","affiliations":[],"preferred":false,"id":524277,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Van Every, Lynn","contributorId":127352,"corporation":false,"usgs":false,"family":"Van Every","given":"Lynn","affiliations":[{"id":6912,"text":"Idaho Department of Environmental Quality","active":true,"usgs":false}],"preferred":false,"id":524280,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Williams, Marshall L. mlwilliams@usgs.gov","contributorId":1444,"corporation":false,"usgs":true,"family":"Williams","given":"Marshall","email":"mlwilliams@usgs.gov","middleInitial":"L.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":524278,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hardy, Mark A.","contributorId":50902,"corporation":false,"usgs":true,"family":"Hardy","given":"Mark","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":524279,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Garbarino, John R. jrgarb@usgs.gov","contributorId":2189,"corporation":false,"usgs":true,"family":"Garbarino","given":"John","email":"jrgarb@usgs.gov","middleInitial":"R.","affiliations":[{"id":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true}],"preferred":true,"id":524281,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70125934,"text":"ds886 - 2014 - Quality of surface water in Missouri, water year 2013","interactions":[],"lastModifiedDate":"2016-08-10T11:14:04","indexId":"ds886","displayToPublicDate":"2014-11-06T09:15:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"886","title":"Quality of surface water in Missouri, water year 2013","docAbstract":"<p>The U.S. Geological Survey, in cooperation with the Missouri Department of Natural Resources, designed and operates a series of monitoring stations on streams and springs throughout Missouri known as the Ambient Water-Quality Monitoring Network. During the 2013 water year (October 1, 2012, through September 30, 2013), data were collected at 79 stations&mdash;73 Ambient Water-Quality Monitoring Network stations, 4 alternate Ambient Water-Quality Monitoring Network stations, and 2 U.S. Geological Survey National Stream Quality Accounting Network stations. Dissolved oxygen, specific conductance, water temperature, suspended solids, suspended sediment, Escherichia coli bacteria, fecal coliform bacteria, dissolved nitrate plus nitrite as nitrogen, total phosphorus, dissolved and total recoverable lead and zinc, and select pesticide compound summaries are presented for 76 of these stations. The stations primarily have been classified into groups corresponding to the physiography of the State, primary land use, or unique station types. In addition, a summary of hydrologic conditions in the State including peak discharges, monthly mean discharges, and 7-day low flow is presented.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds886","collaboration":"Prepared in cooperation with the Missouri Department of Natural Resources","usgsCitation":"Barr, M.N., and Schneider, R.E., 2014, Quality of surface water in Missouri, water year 2013: U.S. Geological Survey Data Series 886, iv, 21 p., https://doi.org/10.3133/ds886.","productDescription":"iv, 21 p.","numberOfPages":"30","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2013-01-01","temporalEnd":"2013-12-31","ipdsId":"IP-058570","costCenters":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true}],"links":[{"id":295907,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds886.jpg"},{"id":295894,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0886/"},{"id":295906,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0886/pdf/ds886.pdf"}],"country":"United States","state":"Missouri","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"545c8da1e4b0ba8303f703a6","contributors":{"authors":[{"text":"Barr, Miya N. 0000-0002-9961-9190 mnbarr@usgs.gov","orcid":"https://orcid.org/0000-0002-9961-9190","contributorId":3686,"corporation":false,"usgs":true,"family":"Barr","given":"Miya","email":"mnbarr@usgs.gov","middleInitial":"N.","affiliations":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":524274,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schneider, Rachel E. rschneider@usgs.gov","contributorId":5786,"corporation":false,"usgs":true,"family":"Schneider","given":"Rachel","email":"rschneider@usgs.gov","middleInitial":"E.","affiliations":[],"preferred":true,"id":524275,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70126400,"text":"sir20145172 - 2014 - Groundwater levels in the Denver Basin bedrock aquifers of Douglas County, Colorado, 2011-2013","interactions":[],"lastModifiedDate":"2014-12-02T10:44:54","indexId":"sir20145172","displayToPublicDate":"2014-11-06T09:15:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-5172","title":"Groundwater levels in the Denver Basin bedrock aquifers of Douglas County, Colorado, 2011-2013","docAbstract":"<p>More than 70 percent of the municipal water supply in the south Denver metropolitan area is provided by groundwater, and homeowners in rural areas depend solely on self-supplied groundwater for water supply. Increased groundwater withdrawal to meet the demand of the rapidly growing population is causing water levels to decline. The U.S. Geological Survey, in cooperation with the Rural Water Authority of Douglas County, began a study in 2011 to assess the groundwater resources of the Denver Basin aquifers within Douglas County, Colorado. The primary purpose of this study was to monitor changes in the groundwater levels of the bedrock aquifers of the Denver Basin within rural Douglas County. To better assess the water resources of the Denver Basin bedrock aquifers, a groundwater monitoring network was established in 2011. More than 500 manual and 213,900 automated water-level measurements collected from the 36 domestic-well network between April 2011 and June 2013 showed water-level declines in all aquifers.</p>\n<p>&nbsp;</p>\n<p>Manual and automated (time-series) water-level data collection from these sites between 2011 and 2013 showed water level declines in 36 wells. Over the 2-year monitoring period, average declines of approximately 0.4 foot per year were observed in the upper Dawson aquifer, declines of over 2.6 feet per year were observed in the lower Dawson aquifer, declines of about 3.2 feet per year were observed in the Denver aquifer, declines of about 1.9 feet per year were observed in the Arapahoe aquifer, and declines of about 9.9 feet per year were observed in the Laramie-Fox Hills aquifer.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145172","collaboration":"Prepared in cooperation with the Rural Water Authority of Douglas County","usgsCitation":"Everett, R., 2014, Groundwater levels in the Denver Basin bedrock aquifers of Douglas County, Colorado, 2011-2013: U.S. Geological Survey Scientific Investigations Report 2014-5172, viii, 45 p., https://doi.org/10.3133/sir20145172.","productDescription":"viii, 45 p.","numberOfPages":"56","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-055778","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":295924,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145172.jpg"},{"id":295918,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5172/"},{"id":295919,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5172/pdf/sir2014-5172.pdf"}],"country":"United States","state":"Colorado","county":"Douglas County","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"545c8d9ee4b0ba8303f70385","contributors":{"authors":[{"text":"Everett, Rhett R. 0000-0001-7983-6270 reverett@usgs.gov","orcid":"https://orcid.org/0000-0001-7983-6270","contributorId":843,"corporation":false,"usgs":true,"family":"Everett","given":"Rhett R.","email":"reverett@usgs.gov","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":false,"id":524352,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70121112,"text":"fs20143078 - 2014 - The rare-earth elements: Vital to modern technologies and lifestyles","interactions":[],"lastModifiedDate":"2017-04-21T13:53:18","indexId":"fs20143078","displayToPublicDate":"2014-11-06T09:15:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-3078","title":"The rare-earth elements: Vital to modern technologies and lifestyles","docAbstract":"<p>Until recently, the rare-earth elements (REEs) were familiar to a relatively small number of people, such as chemists, geologists, specialized materials scientists, and engineers. In the 21st century, the REEs have gained visibility through many media outlets because of (1) the public has recognized the critical, specialized properties that REEs contribute to modern technology, as well as (2) China's dominance in production and supply of the REEs and (3) international dependence on China for the majority of the world's REE supply.</p><p>Since the late 1990s, China has provided 85–95 percent of the world’s REEs. In 2010, China announced their intention to reduce REE exports. During this timeframe, REE use increased substantially. REEs are used as components in high technology devices, including smart phones, digital cameras, computer hard disks, fluorescent and light-emitting-diode (LED) lights, flat screen televisions, computer monitors, and electronic displays. Large quantities of some REEs are used in clean energy and defense technologies. Because of the many important uses of REEs, nations dependent on new technologies, such as Japan, the United States, and members of the European Union, reacted with great concern to China’s intent to reduce its REE exports. Consequently, exploration activities intent on discovering economic deposits of REEs and bringing them into production have increased.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20143078","collaboration":"USGS Mineral Resources Program","usgsCitation":"Van Gosen, B.S., Verplanck, P.L., Long, K.R., Gambogi, J., and Seal, R., 2014, The rare-earth elements: Vital to modern technologies and lifestyles: U.S. Geological Survey Fact Sheet 2014-3078, 4 p., https://doi.org/10.3133/fs20143078.","productDescription":"4 p.","numberOfPages":"4","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-051526","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":295910,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20143078.jpg"},{"id":295909,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2014/3078/pdf/fs2014-3078.pdf"},{"id":295908,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2014/3078/"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"545c8da2e4b0ba8303f703b7","contributors":{"authors":[{"text":"Van Gosen, Bradley S. 0000-0003-4214-3811 bvangose@usgs.gov","orcid":"https://orcid.org/0000-0003-4214-3811","contributorId":1174,"corporation":false,"usgs":true,"family":"Van Gosen","given":"Bradley","email":"bvangose@usgs.gov","middleInitial":"S.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"preferred":true,"id":519244,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Verplanck, Philip L. 0000-0002-3653-6419 plv@usgs.gov","orcid":"https://orcid.org/0000-0002-3653-6419","contributorId":728,"corporation":false,"usgs":true,"family":"Verplanck","given":"Philip","email":"plv@usgs.gov","middleInitial":"L.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":524284,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Long, Keith R. 0000-0002-6457-2820 klong@usgs.gov","orcid":"https://orcid.org/0000-0002-6457-2820","contributorId":2279,"corporation":false,"usgs":true,"family":"Long","given":"Keith","email":"klong@usgs.gov","middleInitial":"R.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":524285,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gambogi, Joseph 0000-0002-5719-2280 jgambogi@usgs.gov","orcid":"https://orcid.org/0000-0002-5719-2280","contributorId":4424,"corporation":false,"usgs":true,"family":"Gambogi","given":"Joseph","email":"jgambogi@usgs.gov","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":false,"id":524286,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Seal, Robert R. II 0000-0003-0901-2529 rseal@usgs.gov","orcid":"https://orcid.org/0000-0003-0901-2529","contributorId":397,"corporation":false,"usgs":true,"family":"Seal","given":"Robert R.","suffix":"II","email":"rseal@usgs.gov","affiliations":[],"preferred":false,"id":524287,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70129421,"text":"fs20143105 - 2014 - Mapping traditional place names along the Koyukuk River: Koyukuk, Huslia, and Hughes, Western Interior Alaska","interactions":[],"lastModifiedDate":"2014-11-06T08:52:40","indexId":"fs20143105","displayToPublicDate":"2014-11-06T09:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-3105","title":"Mapping traditional place names along the Koyukuk River: Koyukuk, Huslia, and Hughes, Western Interior Alaska","docAbstract":"<p>Koyukon Athabascan peoples have settled along the Koyukuk River in Western Interior Alaska for thousands of years using the surrounding landscape for subsistence and cultural resources. However, recent changes in climate, technology, resource availability, and way of life have affected land-use patterns in the region, as well as use of the Denaakk'e (Koyukon) language. The current Koyukon population is about 2,300, and about 150 still speak the language (the youngest of whom are in their fifties). In addition, Elders, important keepers of both language and traditional subsistence-use areas, are aging, and opportunities to record their knowledge are diminishing.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20143105","collaboration":"Eliza Jones - Koyukuk Elder; Susan Paskvan - Yukon- Koyukuk School District; Karin Bodony - Fish and Wildlife Service; Catherine Moncrieff - Yukon River Drainage Fisheries Association","usgsCitation":"McCloskey, S., and Jones, B.M., 2014, Mapping traditional place names along the Koyukuk River: Koyukuk, Huslia, and Hughes, Western Interior Alaska: U.S. Geological Survey Fact Sheet 2014-3105, 2 p., https://doi.org/10.3133/fs20143105.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-059057","costCenters":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"links":[{"id":295898,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20143105.JPG"},{"id":295896,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2014/3105/"},{"id":295897,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2014/3105/pdf/fs2014-3105.pdf"}],"country":"United States","state":"Alaska","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"545c8d9fe4b0ba8303f7039b","contributors":{"authors":[{"text":"McCloskey, Sarah E. smccloskey@usgs.gov","contributorId":4850,"corporation":false,"usgs":true,"family":"McCloskey","given":"Sarah E.","email":"smccloskey@usgs.gov","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":false,"id":524283,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jones, Benjamin M. 0000-0002-1517-4711 bjones@usgs.gov","orcid":"https://orcid.org/0000-0002-1517-4711","contributorId":2286,"corporation":false,"usgs":true,"family":"Jones","given":"Benjamin","email":"bjones@usgs.gov","middleInitial":"M.","affiliations":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":524282,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70129724,"text":"fs20143109 - 2014 - Summary of estimated water use in the United States in 2010","interactions":[],"lastModifiedDate":"2014-11-04T22:48:07","indexId":"fs20143109","displayToPublicDate":"2014-11-05T08:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-3109","title":"Summary of estimated water use in the United States in 2010","docAbstract":"<p>About 355,000 million gallons per day (Mgal/d) of water was withdrawn for use in the United States during 2010, a decline of 13 percent from 2005 and a substantial change from the level of about 400,000 Mgal/d reported from 1985 to 2005. Withdrawals for 2010 were lower than withdrawals estimated for 1970. Fresh surface-water withdrawals (230,000 Mgal/d) were almost 15 percent less than in 2005, and fresh groundwater withdrawals (76,000 Mgal/day) were about 4 percent less than in 2005. Saline surface-water withdrawals were 45,000 Mgal/d, or 24 percent less than in 2005, and saline groundwater withdrawals in 2010, mostly used for mining, were 3,290 Mgal/d.</p>\n<p>&nbsp;</p>\n<p>As in 2005, water withdrawals in four States&mdash;California, Texas, Idaho, and Florida&mdash;accounted for more than one-quarter of all fresh and saline water withdrawn in the United States in 2010. California accounted for 11 percent of the total withdrawals nationwide and 10 percent of the total freshwater withdrawals. More than 60 percent of California&rsquo;s withdrawals were for irrigation, and 17 percent, almost exclusively saline water, was for thermoelectric power. In Texas, about 45 percent of withdrawals were for thermoelectric power, and 28 percent was for irrigation. Irrigation accounted for 81 percent of water withdrawn in Idaho, and thermoelectric power accounted for 61 percent of water withdrawn in Florida.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20143109","usgsCitation":"Barber, N.L., 2014, Summary of estimated water use in the United States in 2010: U.S. Geological Survey Fact Sheet 2014-3109, 2 p., https://doi.org/10.3133/fs20143109.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060372","costCenters":[{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true}],"links":[{"id":295889,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20143109.jpg"},{"id":295873,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2014/3109/"},{"id":295874,"rank":2,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/circ/1405"},{"id":295875,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2014/3109/pdf/fs2014-3109.pdf"}],"country":"United States","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"545b3c1be4b009f8aec98d4e","contributors":{"authors":[{"text":"Barber, Nancy L. 0000-0002-2952-5017 nlbarber@usgs.gov","orcid":"https://orcid.org/0000-0002-2952-5017","contributorId":3679,"corporation":false,"usgs":true,"family":"Barber","given":"Nancy","email":"nlbarber@usgs.gov","middleInitial":"L.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":519919,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70127140,"text":"cir1405 - 2014 - Estimated use of water in the United States in 2010","interactions":[],"lastModifiedDate":"2014-11-06T11:09:49","indexId":"cir1405","displayToPublicDate":"2014-11-05T08:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":307,"text":"Circular","code":"CIR","onlineIssn":"2330-5703","printIssn":"1067-084X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1405","title":"Estimated use of water in the United States in 2010","docAbstract":"<p>Water use in the United States in 2010 was estimated to be about 355 billion gallons per day (Bgal/d), which was 13 percent less than in 2005. The 2010 estimates put total withdrawals at the lowest level since before 1970. Freshwater withdrawals were 306 Bgal/d, or 86 percent of total withdrawals, and saline-water withdrawals were 48.3 Bgal/d, or 14 percent of total withdrawals. Fresh surface-water withdrawals (230 Bgal/d) were almost 15 percent less than in 2005, and fresh groundwater withdrawals (76.0 Bgal/d) were about 4 percent less than in 2005. Saline surface-water withdrawals were 45.0 Bgal/d, or 24 percent less than in 2005. Updates to the 2005 saline groundwater withdrawals, mostly for thermoelectric power, reduced total saline groundwater withdrawals to 1.51 Bgal/d, down from the originally reported 3.02 Bgal/d. Total saline groundwater withdrawals in 2010 were 3.29 Bgal/d, mostly for mining use.</p>\n<p>&nbsp;</p>\n<p>Thermoelectric power and irrigation remained the two largest uses of water in 2010, and total withdrawals for both were notably less than in 2005. Withdrawals in 2010 for thermoelectric power were 20 percent less and withdrawals for irrigation were 9 percent less than in 2005. Similarly, other uses showed reductions compared to 2005, specifically public supply (&ndash;5 percent), self-supplied domestic (&ndash;3 percent), self-supplied industrial (&ndash;12 percent), and livestock (&ndash;7 percent). Only mining (39 percent) and aquaculture (7 percent) reported larger withdrawals in 2010 compared to 2005. Thermoelectric power, irrigation, and public-supply withdrawals accounted for 90 percent of total withdrawals in 2010.</p>\n<p>&nbsp;</p>\n<p>Withdrawals for thermoelectric power were 161 Bgal/d in 2010 and represented the lowest levels since before 1970. Surface-water withdrawals accounted for more than 99 percent of total thermoelectric-power withdrawals, and 73 percent of those surface-water withdrawals were from freshwater sources. Saline surface-water withdrawals for thermoelectric power accounted for 97 percent of total saline surface-water withdrawals for all uses. Thermoelectric-power withdrawals accounted for 45 percent of total withdrawals for all uses, and freshwater withdrawals for thermoelectric power accounted for 38 percent of the total freshwater withdrawals for all uses.</p>\n<p>&nbsp;</p>\n<p>Irrigation withdrawals were 115 Bgal/d in 2010 and represented the lowest levels since before 1965. Irrigation withdrawals, all freshwater, accounted for 38 percent of total freshwater withdrawals for all uses, or 61 percent of total freshwater withdrawals for all uses excluding thermoelectric power. Surface-water withdrawals (65.9 Bgal/d) accounted for 57 percent of the total irrigation withdrawals, or about 12 percent less than in 2005. Groundwater withdrawals were 49.5 Bgal/d in 2010, about 6 percent less than in 2005. About 62,400 thousand acres were irrigated in 2010, an increase from 2005 of about 950 thousand acres (1.5 percent). The number of acres irrigated using sprinkler and microirrigation systems continued to increase and accounted for 58 percent of the total irrigated lands in 2010.</p>\n<p>&nbsp;</p>\n<p>Public-supply withdrawals in 2010 were 42.0 Bgal/d, or 5 percent less than in 2005, and represented the first declines in public-supply withdrawals since the 5-year reporting began in 1950. Total population in the United States increased from 300.7 million people in 2005 to 313.0 million people in 2010, an increase of 4 percent. Public-supply withdrawals accounted for 14 percent of the total freshwater withdrawals for all uses and 22 percent of freshwater withdrawals for all uses excluding thermoelectric power. The number of people that received potable water from public-supply facilities in 2010 was 268 million, or about 86 percent of the total U.S. population. This percentage was unchanged from 2005. Self-supplied domestic withdrawals were 3.60 Bgal/d, or 3 percent less than in 2005. More than 98 percent of the self-supplied domestic withdrawals were from groundwater sources.</p>\n<p>&nbsp;</p>\n<p>Self-supplied industrial withdrawals were 15.9 Bgal/d in 2010, a 12 percent decline from 2005, and continued the downward trend since the peak of 47 Bgal/d in 1970. Total self-supplied industrial withdrawals were 4 percent of total withdrawals for all uses and 8 percent of total withdrawals for all uses excluding thermoelectric power. Most of the total self-supplied industrial withdrawals were from surface-water sources (82 percent), and nearly all (93 percent) of those surface-water withdrawals were from freshwater sources. Nearly all of the groundwater withdrawals for self-supplied industrial use (98 percent) were from freshwater sources.</p>\n<p>&nbsp;</p>\n<p>Total aquaculture withdrawals were 9.42 Bgal/d in 2010, or 7 percent more than in 2005, and surface water was the primary source (81 percent). Most of the surface-water withdrawals occurred at facilities that operated flowthrough raceways, which returned the water to the source directly after use. Aquaculture withdrawals accounted for 3 percent of the total withdrawals for all uses and 5 percent of the total withdrawals for all uses excluding thermoelectric.</p>\n<p>&nbsp;</p>\n<p>Total mining withdrawals in 2010 were 5.32 Bgal/d, or about 1 percent of total withdrawals from all uses and 3 percent of total withdrawals from all uses excluding thermoelectric. Mining withdrawals accounted for the largest percentage increase (39 percent) in water use between 2005 and 2010 among all the categories. Groundwater withdrawals accounted for 73 percent of the total mining withdrawals, and the majority of the groundwater was saline (71 percent). The majority (80 percent) of surface-water withdrawals for mining was freshwater.</p>\n<p>&nbsp;</p>\n<p>Livestock withdrawals in 2010 were 2.00 Bgal/d, or 7 percent less than in 2005. All livestock withdrawals were from freshwater sources, mostly from groundwater (60 percent). Livestock withdrawals accounted for about 1 percent of total freshwater withdrawals for all uses excluding thermoelectric power.</p>\n<p>&nbsp;</p>\n<p>In 2010, more than 50 percent of the total withdrawals in the United States were accounted for by 12 States. California accounted for about 11 percent of the total withdrawals and 10 percent of freshwater withdrawals in the United States, predominantly for irrigation. Texas accounted for about 7 percent of total withdrawals, predominantly for thermoelectric power, irrigation, and public supply. Florida accounted for 18 percent of the total saline-water withdrawals in the United States, mostly from surface-water sources for thermoelectric power. Oklahoma and Texas accounted for about 70 percent of the total saline groundwater withdrawals in the United States, mostly for mining.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1405","usgsCitation":"Maupin, M.A., Kenny, J.F., Hutson, S.S., Lovelace, J.K., Barber, N.L., and Linsey, K.S., 2014, Estimated use of water in the United States in 2010: U.S. Geological Survey Circular 1405, Report: iv, 56 p.; County-level data; Related work, https://doi.org/10.3133/cir1405.","productDescription":"Report: iv, 56 p.; County-level data; Related work","numberOfPages":"64","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057650","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":295888,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/cir1405.jpg"},{"id":295877,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1405/pdf/circ1405.pdf"},{"id":295878,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/fs/2014/3109/"},{"id":295879,"rank":4,"type":{"id":7,"text":"Companion Files"},"url":"https://water.usgs.gov/watuse/data/2010/"},{"id":295876,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/circ/1405/"}],"country":"United States","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"545b3c19e4b009f8aec98d48","contributors":{"authors":[{"text":"Maupin, Molly A. 0000-0002-2695-5505 mamaupin@usgs.gov","orcid":"https://orcid.org/0000-0002-2695-5505","contributorId":951,"corporation":false,"usgs":true,"family":"Maupin","given":"Molly","email":"mamaupin@usgs.gov","middleInitial":"A.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":519593,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kenny, Joan F. jkenny@usgs.gov","contributorId":3676,"corporation":false,"usgs":true,"family":"Kenny","given":"Joan","email":"jkenny@usgs.gov","middleInitial":"F.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":false,"id":519596,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hutson, Susan S. sshutson@usgs.gov","contributorId":2040,"corporation":false,"usgs":true,"family":"Hutson","given":"Susan","email":"sshutson@usgs.gov","middleInitial":"S.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":519595,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lovelace, John K. 0000-0002-8532-2599 jlovelac@usgs.gov","orcid":"https://orcid.org/0000-0002-8532-2599","contributorId":999,"corporation":false,"usgs":true,"family":"Lovelace","given":"John","email":"jlovelac@usgs.gov","middleInitial":"K.","affiliations":[{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":519594,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Barber, Nancy L. 0000-0002-2952-5017 nlbarber@usgs.gov","orcid":"https://orcid.org/0000-0002-2952-5017","contributorId":3679,"corporation":false,"usgs":true,"family":"Barber","given":"Nancy","email":"nlbarber@usgs.gov","middleInitial":"L.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true},{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":519598,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Linsey, Kristin S. 0000-0001-6492-7639 kslinsey@usgs.gov","orcid":"https://orcid.org/0000-0001-6492-7639","contributorId":3678,"corporation":false,"usgs":true,"family":"Linsey","given":"Kristin","email":"kslinsey@usgs.gov","middleInitial":"S.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":519597,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70156257,"text":"70156257 - 2014 - Using ecological indicators and a decision support system for integrated ecological assessment at two national park units in the Mid-Atlantic region, U.S.A.","interactions":[],"lastModifiedDate":"2022-11-10T16:32:18.700862","indexId":"70156257","displayToPublicDate":"2014-11-05T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1547,"text":"Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Using ecological indicators and a decision support system for integrated ecological assessment at two national park units in the Mid-Atlantic region, U.S.A.","docAbstract":"<p><span>We implemented an integrated ecological assessment using a GIS-based decision support system model for Upper Delaware Scenic and Recreational River (UPDE) and Delaware Water Gap National Recreation Area (DEWA)&mdash;national park units with the mid-Atlantic region of the United States. Our assessment examined a variety of aquatic and terrestrial indicators of ecosystem components that reflect the parks&rsquo; conservation purpose and reference condition. Our assessment compared these indicators to ecological thresholds to determine the condition of park watersheds. Selected indicators included chemical and physical measures of water quality, biologic indicators of water quality, and landscape condition measures. For the chemical and physical measures of water quality, we used a water quality index and each of its nine components to assess the condition of water quality in each watershed. For biologic measures of water quality, we used the Ephemeroptera, Plecoptera, Trichoptera aquatic macroinvertebrate index and, secondarily, the Hilsenhoff aquatic macroinvertebrate index. Finally, for the landscape condition measures of our model, we used percent forest and percent impervious surface. Based on our overall assessment, UPDE and DEWA watersheds had an ecological assessment score of 0.433 on a &minus;1 to 1 fuzzy logic scale. This score indicates that, in general, the natural resource condition within watersheds at these parks is healthy or ecologically unimpaired; however, we had only partial data for many of our indicators. Our model is iterative and new data may be incorporated as they become available. These natural parks are located within a rapidly urbanizing landscape&mdash;we recommend that natural resource managers remain vigilant to surrounding land uses that may adversely affect natural resources within the parks.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s00267-014-0391-y","usgsCitation":"Mahan, C.G., Young, J.A., Miller, B., and Saunders, M.C., 2014, Using ecological indicators and a decision support system for integrated ecological assessment at two national park units in the Mid-Atlantic region, U.S.A.: Environmental Management, v. 55, no. 2, p. 508-522, https://doi.org/10.1007/s00267-014-0391-y.","productDescription":"14 p.","startPage":"508","endPage":"522","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061210","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":472651,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index 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Altoona","active":true,"usgs":false}],"preferred":false,"id":568352,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Young, John A. 0000-0002-4500-3673 jyoung@usgs.gov","orcid":"https://orcid.org/0000-0002-4500-3673","contributorId":3777,"corporation":false,"usgs":true,"family":"Young","given":"John","email":"jyoung@usgs.gov","middleInitial":"A.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":568351,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miller, Bruce","contributorId":146583,"corporation":false,"usgs":false,"family":"Miller","given":"Bruce","email":"","affiliations":[{"id":6945,"text":"private 3721 2nd Avenue, Salt Lake City","active":true,"usgs":false}],"preferred":false,"id":568353,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Saunders, Michael C.","contributorId":146584,"corporation":false,"usgs":false,"family":"Saunders","given":"Michael","email":"","middleInitial":"C.","affiliations":[{"id":16724,"text":"Penn Sate University","active":true,"usgs":false}],"preferred":false,"id":568354,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70132480,"text":"ofr20141230 - 2014 - Short-term occupancy and abundance dynamics of the Oregon spotted frog (Rana pretiosa) across its core range","interactions":[],"lastModifiedDate":"2017-11-22T14:21:32","indexId":"ofr20141230","displayToPublicDate":"2014-11-04T16:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-1230","displayTitle":"Short-term occupancy and abundance dynamics of the Oregon spotted frog (<i>Rana pretiosa</i>) across its core range","title":"Short-term occupancy and abundance dynamics of the Oregon spotted frog (Rana pretiosa) across its core range","docAbstract":"<p>The Oregon spotted frog (<em>Rana pretiosa</em>) occupies only a fraction of its original range and is listed as Threatened under the Endangered Species Act. We surveyed 93 sites in a rotating frame design (2010&ndash;13) in the Klamath and Deschutes Basins, Oregon, which encompass most of the species&rsquo; core extant range. Oregon spotted frogs are declining in abundance and probability of site occupancy. We did not find an association between the probability that Oregon spotted frogs disappear from a site (local extinction) and any of the variables hypothesized to affect Oregon spotted frog occupancy. This 4-year study provides baseline data, but the 4-year period was too short to draw firm conclusions. Further study is essential to understand how habitat changes and management practices relate to the status and trends of this species.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141230","collaboration":"Prepared in cooperation with the Interagency Special Status / Sensitive Species Program (ISSSSP). The ISSSSP is a cooperative program of the Pacific Northwest Regional Office of the U.S. Forest Service and Oregon/Washington State Office of the Bureau of Land Management","usgsCitation":"Adams, M.J., Pearl, C.A., McCreary, B., and Galvan, S., 2014, Short-term occupancy and abundance dynamics of the Oregon spotted frog (Rana pretiosa) across its core range: U.S. Geological Survey Open-File Report 2014-1230, iv, 10 p., https://doi.org/10.3133/ofr20141230.","productDescription":"iv, 10 p.","numberOfPages":"18","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-059622","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":295887,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141230.jpg"},{"id":295880,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1230/"},{"id":295886,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1230/pdf/ofr2014-1230.pdf"}],"country":"United States","state":"Oregon","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5459eaa3e4b009f8aec9700e","contributors":{"authors":[{"text":"Adams, M. J. 0000-0001-8844-042X mjadams@usgs.gov","orcid":"https://orcid.org/0000-0001-8844-042X","contributorId":3133,"corporation":false,"usgs":false,"family":"Adams","given":"M.","email":"mjadams@usgs.gov","middleInitial":"J.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":523280,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pearl, Christopher A. 0000-0003-2943-7321 christopher_pearl@usgs.gov","orcid":"https://orcid.org/0000-0003-2943-7321","contributorId":3131,"corporation":false,"usgs":true,"family":"Pearl","given":"Christopher","email":"christopher_pearl@usgs.gov","middleInitial":"A.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":false,"id":523281,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McCreary, Brome 0000-0002-0313-7796 brome_mccreary@usgs.gov","orcid":"https://orcid.org/0000-0002-0313-7796","contributorId":3130,"corporation":false,"usgs":true,"family":"McCreary","given":"Brome","email":"brome_mccreary@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":523282,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Galvan, Stephanie 0000-0002-9864-3674 stephanie_galvan@usgs.gov","orcid":"https://orcid.org/0000-0002-9864-3674","contributorId":3135,"corporation":false,"usgs":true,"family":"Galvan","given":"Stephanie","email":"stephanie_galvan@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":523283,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70074082,"text":"sir20105090P - 2014 - Porphyry copper assessment of East and Southeast Asia: Philippines, Taiwan (Republic of China), Republic of Korea (South Korea), and Japan","interactions":[{"subject":{"id":70074082,"text":"sir20105090P - 2014 - Porphyry copper assessment of East and Southeast Asia: Philippines, Taiwan (Republic of China), Republic of Korea (South Korea), and Japan","indexId":"sir20105090P","publicationYear":"2014","noYear":false,"chapter":"P","title":"Porphyry copper assessment of East and Southeast Asia: Philippines, Taiwan (Republic of China), Republic of Korea (South Korea), and Japan"},"predicate":"IS_PART_OF","object":{"id":70040436,"text":"sir20105090 - 2010 - Global mineral resource assessment","indexId":"sir20105090","publicationYear":"2010","noYear":false,"title":"Global mineral resource assessment"},"id":1}],"isPartOf":{"id":70040436,"text":"sir20105090 - 2010 - Global mineral resource assessment","indexId":"sir20105090","publicationYear":"2010","noYear":false,"title":"Global mineral resource assessment"},"lastModifiedDate":"2020-07-01T19:22:00.184549","indexId":"sir20105090P","displayToPublicDate":"2014-11-04T14:30:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2010-5090","chapter":"P","title":"Porphyry copper assessment of East and Southeast Asia: Philippines, Taiwan (Republic of China), Republic of Korea (South Korea), and Japan","docAbstract":"<p>The U.S. Geological Survey collaborated with member countries of the Coordinating Committee for Geoscience Programmes in East and Southeast Asia (CCOP) on an assessment of the porphyry copper resources of East and Southeast Asia as part of a global mineral resource assessment. The assessment covers the Philippines in Southeast Asia, and the Republic of Korea (South Korea), Taiwan (Province of China), and Japan in East Asia. The Philippines host world class porphyry copper deposits, such as the Tampakan and Atlas deposits. No porphyry copper deposits have been discovered in the Republic of Korea (South Korea), Taiwan (Province of China), or Japan.</p>\n<p>Thirteen geographic areas were delineated as tracts that are permissive for porphyry copper deposits in the assessed area. Individual tracts range from about 3,000 to 100,000 square kilometers in area. Permissive tracts are delineated on the basis of mapped distributions of igneous rocks of specific age ranges that define subduction-related magmatic arcs or magmatic belts that might contain porphyry copper deposits. Most of these magmatic arcs are subduction related, although some porphyry deposits and prospects are present in back-arc or poorly understood tectonic settings. Maps at various scales were used in the compilation; however, the final tract boundaries are intended for use at a scale of 1:1,000,000.</p>\n<p>Numbers of undiscovered deposits were estimated at different levels of confidence for 10 permissive tracts in the Philippines including one area that extends to eastern Taiwan (Republic of China); permissive tracts in South Korea and Japan are discussed qualitatively. Estimates of numbers of undiscovered deposits were combined with grade and tonnage models using Monte Carlo simulation to estimate amounts of undiscovered resources. Grades and tonnages of known porphyry copper deposits in the study area were compared with global grade and tonnage models to determine the appropriate model for simulation of undiscovered resources. Most of the known deposits are best described as copper-gold subtypes of porphyry copper deposits. For some permissive tracts, a general porphyry copper-gold-molybdenum model was used.</p>\n<p>Thirty-eight porphyry copper deposits are known in the Philippines; the mean number of undiscovered deposits was estimated to be 28. Mean (arithmetic) resources that could be associated with the undiscovered deposits are 90 million metric tons of copper and 5,800 metric tons of gold, as well as byproduct molybdenum and silver. Additional resources that could be discovered in extensions to known deposits were not evaluated. Assessment results, presented in tables and graphs, indicate expected amounts of total contained metal and mineralized rock in undiscovered deposits at different quantile levels, as well as the arithmetic mean for each tract.</p>\n<p>The Philippines have a long history of porphyry exploration cycles and mine development, interrupted at times by political and social unrest, environmental concerns, and natural disasters. Changes in mining laws within the region and the recent high price of gold on the world market have prompted renewed interest in porphyry copper deposits in the region. South Korea and Japan have been thoroughly explored for many types of mineral deposits. Available data suggest that the permissive rocks in South Korea typically are too deeply eroded to preserve porphyry copper deposits. Porphyry copper systems may be present in Japan, but are likely to lie at depths greater than the 1 kilometer from the surface protocol adopted for this study.</p>\n<p>Descriptions of the geologic basis for delineating each tract, the data used, the geologic criteria and rationale for the assessment, and results of the assessment are included in appendixes along with the description of a geographic information system (GIS) that includes tract boundaries, known porphyry copper deposits and significant prospects, and assessment results.</p>","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Global mineral resource assessment","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20105090P","collaboration":"Prepared in cooperation with the <a href=\"http://www.ccop.or.th/\">Coordinating Committee for Geoscience Programmes in East and Southeast Asia</a>.","usgsCitation":"Hammarstrom, J.M., Bookstrom, A.A., Demarr, M.W., Dicken, C., Ludington, S., Robinson, G.R., and Zientek, M.L., 2014, Porphyry copper assessment of East and Southeast Asia: Philippines, Taiwan (Republic of China), Republic of Korea (South Korea), and Japan: U.S. Geological Survey Scientific Investigations Report 2010-5090, Report: xiii, 243 p.; Tabloid Figures; GIS Package, https://doi.org/10.3133/sir20105090P.","productDescription":"Report: xiii, 243 p.; Tabloid Figures; GIS Package","numberOfPages":"262","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-039384","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"links":[{"id":295885,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20105090P.jpg"},{"id":295884,"type":{"id":23,"text":"Spatial 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jhammars@usgs.gov","orcid":"https://orcid.org/0000-0003-2742-3460","contributorId":1226,"corporation":false,"usgs":true,"family":"Hammarstrom","given":"Jane","email":"jhammars@usgs.gov","middleInitial":"M.","affiliations":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":523284,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bookstrom, Arthur A. 0000-0003-1336-3364 abookstrom@usgs.gov","orcid":"https://orcid.org/0000-0003-1336-3364","contributorId":1542,"corporation":false,"usgs":true,"family":"Bookstrom","given":"Arthur","email":"abookstrom@usgs.gov","middleInitial":"A.","affiliations":[{"id":5056,"text":"Office of the AD Energy and Minerals, and Environmental Health","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":523285,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Demarr, Michael W.","contributorId":127350,"corporation":false,"usgs":false,"family":"Demarr","given":"Michael","email":"","middleInitial":"W.","affiliations":[{"id":6785,"text":"USGS Contractor, Minerals & Environmental Resources Sci Ctr","active":true,"usgs":false}],"preferred":false,"id":523286,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dicken, Connie L. cdicken@usgs.gov","contributorId":4714,"corporation":false,"usgs":true,"family":"Dicken","given":"Connie L.","email":"cdicken@usgs.gov","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":523287,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ludington, Stephen slud@usgs.gov","contributorId":3093,"corporation":false,"usgs":true,"family":"Ludington","given":"Stephen","email":"slud@usgs.gov","affiliations":[{"id":662,"text":"Western Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":523288,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Robinson, Gilpin R. Jr. grobinso@usgs.gov","contributorId":3083,"corporation":false,"usgs":true,"family":"Robinson","given":"Gilpin","suffix":"Jr.","email":"grobinso@usgs.gov","middleInitial":"R.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":523289,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Zientek, Michael L. 0000-0002-8522-9626 mzientek@usgs.gov","orcid":"https://orcid.org/0000-0002-8522-9626","contributorId":2420,"corporation":false,"usgs":true,"family":"Zientek","given":"Michael","email":"mzientek@usgs.gov","middleInitial":"L.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":523290,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70122982,"text":"ds852 - 2014 - Digital topographic data based on lidar survey of Mount Shasta Volcano, California, July-September 2010","interactions":[],"lastModifiedDate":"2019-03-15T10:15:30","indexId":"ds852","displayToPublicDate":"2014-11-04T13:30:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"852","title":"Digital topographic data based on lidar survey of Mount Shasta Volcano, California, July-September 2010","docAbstract":"<p>The most voluminous of the Cascade volcanoes, northern California’s Mount Shasta, is a massive compound stratovolcano composed of at least four main edifices constructed over a period of at least 590,000 years. An ancestral Shasta volcano was destroyed by Earth’s largest known Quaternary subaerial debris avalanche, which filled Shasta Valley, northwest of the volcano. The Hotlum cone, forming the present summit, the Shastina lava dome complex, and the Black Butte lava dome on the southwest flank, were constructed during the early Holocene.</p><p>As part of the American Recovery and Reinvestment Act (ARRA) of 2009, the U.S. Geological Survey was awarded funding for high-precision airborne lidar (light detection and ranging) data collection at several volcanoes in the Cascade Range. Data collection was arranged by the Oregon Lidar Consortium, administered by the Oregon Department of Geology and Mineral Industries (DOGAMI). The Oregon Lidar Consortium contracted with Watershed Sciences, Inc., to collect 1,220 square km of high-precision airborne lidar data. These data provide a digital map of the ground surface beneath forest cover with horizontal resolution of 1 m (average of 1.82 ground laser returns per square meter) and estimated vertical accuracy of ±4 centimeters (1 sigma), and horizontal accuracies of ±1.5 centimeters. These data will contribute to monitoring and description of natural hazards, the study of regional geology and volcanic landforms, and analysis of landscape modification during and after the next volcanic eruption at Mount Shasta.</p><p>Survey Bounding Coordinates:</p><ul><li>West Bounding Coordinate: −122.438774</li><li>East Bounding Coordinate: −121.888382</li><li>North Bounding Coordinate: 41.564495</li><li>South Bounding Coordinate: 41.126339</li></ul>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds852","usgsCitation":"Robinson, J., 2014, Digital topographic data based on lidar survey of Mount Shasta Volcano, California, July-September 2010: U.S. Geological Survey Data Series 852, Elevation Data; Metadata; Shaded Relief Maps; Mt Shasta Delivery Report; Mt Shasta Acceptance Report, https://doi.org/10.3133/ds852.","productDescription":"Elevation Data; Metadata; Shaded Relief Maps; Mt Shasta Delivery Report; Mt Shasta Acceptance Report","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"2010-07-01","temporalEnd":"2010-09-30","ipdsId":"IP-049301","costCenters":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":295872,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds852.JPG"},{"id":295867,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/0852/downloads/ds852_lidar.zip","text":"Elevation Data","size":"3.2 GB"},{"id":295868,"rank":2,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/ds/0852/downloads/ds852_metadata.txt","size":"14 kB","linkFileType":{"id":2,"text":"txt"}},{"id":295869,"rank":4,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/0852/downloads/TiffFiles/","text":"Shaded Relief Maps"},{"id":295820,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0852/"},{"id":295870,"rank":5,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/ds/0852/downloads/ds852_MtShastaDeliveryReport.pdf","text":"Mt Shasta Delivery Report","size":"5.2 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":295871,"rank":6,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/ds/0852/downloads/ds852_MtShastaAcceptanceReport.pdf","text":"Mt Shasta Acceptance Report","size":"1.5 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"California","otherGeospatial":"Mount Shasta Volcano","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.40,\n              41\n            ],\n            [\n              -121.92626953124999,\n              41\n            ],\n            [\n              -121.92626953124999,\n              41.5\n            ],\n            [\n              -122.40,\n              41.5\n            ],\n            [\n              -122.40,\n              41\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5459ea9fe4b009f8aec96fbd","contributors":{"authors":[{"text":"Robinson, Joel E. 0000-0002-5193-3666 jrobins@usgs.gov","orcid":"https://orcid.org/0000-0002-5193-3666","contributorId":2757,"corporation":false,"usgs":true,"family":"Robinson","given":"Joel E.","email":"jrobins@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":522916,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70131501,"text":"70131501 - 2014 - Whitebark pine, population density, and home-range size of grizzly bears in the greater Yellowstone ecosystem","interactions":[],"lastModifiedDate":"2018-03-17T17:13:33","indexId":"70131501","displayToPublicDate":"2014-11-04T13:15:00","publicationYear":"2014","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":"Whitebark pine, population density, and home-range size of grizzly bears in the greater Yellowstone ecosystem","docAbstract":"<p>Changes in life history traits of species can be an important indicator of potential factors influencing populations. For grizzly bears (<em>Ursus arctos</em>) in the Greater Yellowstone Ecosystem (GYE), recent decline of whitebark pine (WBP; <em>Pinus albicaulis</em>), an important fall food resource, has been paired with a slowing of population growth following two decades of robust population increase. These observations have raised questions whether resource decline or density-dependent processes may be associated with changes in population growth. Distinguishing these effects based on changes in demographic rates can be difficult. However, unlike the parallel demographic responses expected from both decreasing food availability and increasing population density, we hypothesized opposing behavioral responses of grizzly bears with regard to changes in home-range size. We used the dynamic changes in food resources and population density of grizzly bears as a natural experiment to examine hypotheses regarding these potentially competing influences on grizzly bear home-range size. We found that home-range size did not increase during the period of whitebark pine decline and was not related to proportion of whitebark pine in home ranges. However, female home-range size was negatively associated with an index of population density. Our data indicate that home-range size of grizzly bears in the GYE is not associated with availability of WBP, and, for female grizzly bears, increasing population density may constrain home-range size.</p>","language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pone.0088160","collaboration":"US Fish and Wildlife Service","usgsCitation":"Bjornlie, D., van Manen, F.T., Ebinger, M.R., Haroldson, M.A., Thompson, D.J., and Costello, C., 2014, Whitebark pine, population density, and home-range size of grizzly bears in the greater Yellowstone ecosystem: PLoS ONE, v. 9, no. 2, p. 1-7, https://doi.org/10.1371/journal.pone.0088160.","productDescription":"Article e88160; 7 p.","startPage":"1","endPage":"7","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-053114","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":472652,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0088160","text":"Publisher Index Page"},{"id":295865,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Montana, Wyoming","otherGeospatial":"Yellowstone National Park","volume":"9","issue":"2","noUsgsAuthors":false,"publicationDate":"2014-02-10","publicationStatus":"PW","scienceBaseUri":"5459eaa5e4b009f8aec97040","contributors":{"authors":[{"text":"Bjornlie, Daniel D.","contributorId":145512,"corporation":false,"usgs":false,"family":"Bjornlie","given":"Daniel D.","affiliations":[{"id":16140,"text":"Wyoming Game & Fish Department, Large Carnivore Section, Lander, Wyoming 82520, USA","active":true,"usgs":false}],"preferred":false,"id":521328,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"van Manen, Frank T. 0000-0001-5340-8489 fvanmanen@usgs.gov","orcid":"https://orcid.org/0000-0001-5340-8489","contributorId":2267,"corporation":false,"usgs":true,"family":"van Manen","given":"Frank","email":"fvanmanen@usgs.gov","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":521327,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ebinger, Michael R. mebinger@usgs.gov","contributorId":5771,"corporation":false,"usgs":true,"family":"Ebinger","given":"Michael","email":"mebinger@usgs.gov","middleInitial":"R.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":521329,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Haroldson, Mark A. 0000-0002-7457-7676 mharoldson@usgs.gov","orcid":"https://orcid.org/0000-0002-7457-7676","contributorId":1773,"corporation":false,"usgs":true,"family":"Haroldson","given":"Mark","email":"mharoldson@usgs.gov","middleInitial":"A.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":521330,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thompson, Daniel J.","contributorId":149795,"corporation":false,"usgs":false,"family":"Thompson","given":"Daniel","email":"","middleInitial":"J.","affiliations":[{"id":5116,"text":"Large Carnivore Section, Wyoming Game & Fish Department, 260 Buena Vista, Lander, WY 82520, USA","active":true,"usgs":false}],"preferred":false,"id":521331,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Costello, Cecily M.","contributorId":145510,"corporation":false,"usgs":false,"family":"Costello","given":"Cecily M.","affiliations":[{"id":5117,"text":"University of Montana, College of Forestry and Conservation, University Hall, Room 309, Missoula, MT 59812, USA","active":true,"usgs":false}],"preferred":false,"id":521332,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70131500,"text":"70131500 - 2014 - A numerical study of vegetation impact on reducing storm surge by wetlands in a semi-enclosed estuary","interactions":[],"lastModifiedDate":"2020-12-23T14:50:27.713946","indexId":"70131500","displayToPublicDate":"2014-11-04T13:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1262,"text":"Coastal Engineering","active":true,"publicationSubtype":{"id":10}},"title":"A numerical study of vegetation impact on reducing storm surge by wetlands in a semi-enclosed estuary","docAbstract":"<p><span>Coastal wetlands play a unique role in extreme hurricane events. The impact of wetlands on storm surge depends on multiple factors including vegetation, landscape, and storm characteristics. The Delft3D model, in which vegetation effects on flow and turbulence are explicitly incorporated, was applied to the semi-enclosed Breton Sound (BS) estuary in coastal Louisiana to investigate the wetland impact. Guided by extensive field observations, a series of numerical experiments were conducted based on variations of actual vegetation properties and storm parameters from Hurricane Isaac in 2012. Both the vegetation-induced maximum surge reduction (MSR) and maximum surge reduction rate (MSRR) increased with stem height and stem density, and were more sensitive to stem height. The MSR and MSRR decreased significantly with increasing wind intensity. The MSRR was the highest with a fast-moving weak storm. It was also found that the MSRR varied proportionally to the expression involving the maximum bulk velocity and surge over the area of interest, and was more dependent on the maximum bulk surge. Both MSR and MSRR appeared to increase when the area of interest decreased from the whole BS estuary to the upper estuary. Within the range of the numerical experiments, the maximum simulated MSR and MSRR over the upper estuary were 0.7</span><span>&nbsp;</span><span>m and 37%, respectively.</span></p>","language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Holland","doi":"10.1016/j.coastaleng.2014.09.008","usgsCitation":"Kelin, H., Qin, C., and Wang, H., 2014, A numerical study of vegetation impact on reducing storm surge by wetlands in a semi-enclosed estuary: Coastal Engineering, v. 95, p. 66-76, https://doi.org/10.1016/j.coastaleng.2014.09.008.","productDescription":"11 p.","startPage":"66","endPage":"76","numberOfPages":"11","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056053","costCenters":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":295863,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Breton Sound Estuary","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -89.16366577148438,\n              29.597341920567366\n            ],\n            [\n              -89.72946166992188,\n              29.858510452312036\n            ],\n            [\n              -89.95880126953125,\n              29.881136828132842\n            ],\n            [\n              -90.0164794921875,\n              29.776297851831366\n            ],\n            [\n              -89.93820190429688,\n              29.635545914466675\n            ],\n            [\n              -89.6649169921875,\n              29.47307903155816\n            ],\n            [\n              -89.5880126953125,\n              29.3965337391284\n            ],\n            [\n              -89.46990966796875,\n              29.348663646523626\n            ],\n            [\n              -89.40673828125,\n              29.335495425659694\n            ],\n            [\n              -89.27902221679688,\n              29.209713225868185\n            ],\n            [\n              -89.22134399414062,\n              29.136568744954467\n            ],\n            [\n              -89.02496337890625,\n              29.554345125748267\n            ],\n            [\n              -89.16366577148438,\n              29.597341920567366\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"95","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5459ea9ae4b009f8aec96f95","contributors":{"authors":[{"text":"Kelin, Hu","contributorId":124567,"corporation":false,"usgs":false,"family":"Kelin","given":"Hu","email":"","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":521325,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Qin, Chen","contributorId":124568,"corporation":false,"usgs":false,"family":"Qin","given":"Chen","email":"","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":521326,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wang, Hongqing 0000-0002-2977-7732 wangh@usgs.gov","orcid":"https://orcid.org/0000-0002-2977-7732","contributorId":4421,"corporation":false,"usgs":true,"family":"Wang","given":"Hongqing","email":"wangh@usgs.gov","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":false,"id":521324,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70127432,"text":"ds884 - 2014 - Water quality, discharge, and groundwater levels in the Palomas, Mesilla, and Hueco Basins in New Mexico and Texas from below Caballo Reservoir, New Mexico, to Fort Quitman, Texas, 1889-2013","interactions":[],"lastModifiedDate":"2014-11-04T13:08:23","indexId":"ds884","displayToPublicDate":"2014-11-04T13:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"884","title":"Water quality, discharge, and groundwater levels in the Palomas, Mesilla, and Hueco Basins in New Mexico and Texas from below Caballo Reservoir, New Mexico, to Fort Quitman, Texas, 1889-2013","docAbstract":"<p>The U.S. Geological Survey, in cooperation with the New Mexico Environment Department, compiled data from various sources to develop a dataset that can be used to conduct an assessment of the total dissolved solids in surface water and groundwater of the Palomas, Mesilla, and Hueco Basins in New Mexico and Texas, from below Caballo Reservoir, N. Mex., to Fort Quitman, Tex. Data include continuous surface-water discharge records at various locations on the Rio Grande; surface-water-quality data for the Rio Grande collected at selected locations in the Palomas, Mesilla, and Hueco Basins; groundwater levels and groundwater-quality data collected from selected wells in the Palomas and Mesilla Basins; and data from several seepage investigations conducted on the Rio Grande and selected drains in the Mesilla Basin.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds884","collaboration":"Prepared in cooperation with the New Mexico Environment Department","usgsCitation":"McKean, S., Matherne, A.M., and Thomas, N., 2014, Water quality, discharge, and groundwater levels in the Palomas, Mesilla, and Hueco Basins in New Mexico and Texas from below Caballo Reservoir, New Mexico, to Fort Quitman, Texas, 1889-2013: U.S. Geological Survey Data Series 884, Report: HTML Document; Downloads Directory, https://doi.org/10.3133/ds884.","productDescription":"Report: HTML Document; Downloads Directory","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"1889-01-01","temporalEnd":"2013-12-31","ipdsId":"IP-057294","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":295866,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds884.png"},{"id":295851,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0884/"},{"id":295864,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/0884/downloads/","text":"Downloads Directory"}],"projection":"Universal Transverse Mercator projection","datum":"North American Datum of 1983","country":"United States","state":"New Mexico, Texas","otherGeospatial":"Hueco Basin, Mesilla Basin, Palomas Basin","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5459eaa4e4b009f8aec97025","contributors":{"authors":[{"text":"McKean, Sarah E.","contributorId":71894,"corporation":false,"usgs":true,"family":"McKean","given":"Sarah E.","affiliations":[],"preferred":false,"id":523263,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Matherne, Anne Marie 0000-0002-5873-2226 matherne@usgs.gov","orcid":"https://orcid.org/0000-0002-5873-2226","contributorId":303,"corporation":false,"usgs":true,"family":"Matherne","given":"Anne","email":"matherne@usgs.gov","middleInitial":"Marie","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":523264,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thomas, Nicole nithomas@usgs.gov","contributorId":5649,"corporation":false,"usgs":true,"family":"Thomas","given":"Nicole","email":"nithomas@usgs.gov","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":523265,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
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