The West Antarctic Ice Sheet (WAIS) flows through the volcanically active West Antarctic Rift System (WARS). The aeromagnetic method has been the most useful geophysical tool for identification of subglacial volcanic rocks, since 1959–64 surveys, particularly combined with 1978 radar ice-sounding. The unique 1991–97 Central West Antarctica (CWA) aerogeophysical survey covering 354,000 km2 over the WAIS, (5-km line-spaced, orthogonal lines of aeromagnetic, radar ice-sounding, and aerogravity measurements), still provides invaluable information on subglacial volcanic rocks, particularly combined with the older aeromagnetic profiles. These data indicate numerous 100–>1000 nT, 5–50-km width, shallow-source, magnetic anomalies over an area greater than 1.2 × 106 km2, mostly from subglacial volcanic sources. I interpreted the CWA anomalies as defining about 1000 “volcanic centers” requiring high remanent normal magnetizations in the present field direction. About 400 anomaly sources correlate with bed topography. At least 80% of these sources have less than 200 m relief at the WAIS bed. They appear modified by moving ice, requiring a younger age than the WAIS (about 25 Ma).
\nExposed volcanoes in the WARS are < 34 Ma, but at least four are active. If a few buried volcanic centers are active, subglacial volcanism may well affect the WAIS regime. Aerogeophysical data (Blankenship et al., 1993, Mt. Casertz; Corr and Vaughan, 2008, near Hudson Mts.) indicated active subglacial volcanism. Magnetic data indicate a caldera and a surrounding “low” in the WAISCORE vicinity possibly the result of a shallow Curie isotherm. High heat flow reported from temperature logging in the WAISCORE (Conway et al., 2011; Clow, personal commun.) and a volcanic ash layer (Dunbar, 2012) are consistent with this interpretation. A subaerially erupted subglacial volcano, (Mt Thiel), about 100 km distant, may be the ash source.
\nThe present rapid changes resulting from global warming, could be accelerated by subglacial volcanism.
","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Tectonophysics","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.tecto.2012.06.035","usgsCitation":"Behrendt, J.C., 2013, The aeromagnetic method as a tool to identify Cenozoic magmatism in the West Antarctic Rift System beneath the West Antarctic Ice Sheet: a review; Thiel subglacial volcano as possible source of the ash layer in the WAISCOR: Tectonophysics, v. 585, p. 124-136, https://doi.org/10.1016/j.tecto.2012.06.035.","productDescription":"13 p.","startPage":"124","endPage":"136","costCenters":[],"links":[{"id":290998,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.tecto.2012.06.035"},{"id":290999,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Antartica","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -163.7,-85.2 ], [ -163.7,-63.3 ], [ -57.1,-63.3 ], [ -57.1,-85.2 ], [ -163.7,-85.2 ] ] ] } } ] }","volume":"585","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57f7f29ae4b0bc0bec0a049e","contributors":{"authors":[{"text":"Behrendt, John C. jbehrendt@usgs.gov","contributorId":25945,"corporation":false,"usgs":true,"family":"Behrendt","given":"John","email":"jbehrendt@usgs.gov","middleInitial":"C.","affiliations":[{"id":218,"text":"Denver Federal Center","active":false,"usgs":true},{"id":213,"text":"Crustal Imaging and Characterization Team","active":false,"usgs":true}],"preferred":false,"id":496199,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70047195,"text":"70047195 - 2013 - Crater-based dating of geological units on Mars: methods and application for the new global geological map","interactions":[],"lastModifiedDate":"2018-12-07T14:48:10","indexId":"70047195","displayToPublicDate":"2013-07-25T09:25:42","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1963,"text":"Icarus","active":true,"publicationSubtype":{"id":10}},"title":"Crater-based dating of geological units on Mars: methods and application for the new global geological map","docAbstract":"The new, post-Viking generation of Mars orbital imaging and topographical data provide significant higher-resolution details of surface morphologies, which induced a new effort to photo-geologically map the surface of Mars at 1:20,000,000 scale. Although from unit superposition relations a relative stratigraphical framework can be compiled, it was the ambition of this mapping project to provide absolute unit age constraints through crater statistics. In this study, the crater counting method is described in detail, starting with the selection of image data, type locations (both from the mapper’s and crater counter’s perspectives) and the identification of impact craters. We describe the criteria used to validate and analyse measured crater populations, and to derive and interpret crater model ages. We provide examples of how geological information about the unit’s resurfacing history can be retrieved from crater size–frequency distributions. Three cases illustrate short-, intermediate, and long-term resurfacing histories. In addition, we introduce an interpretation-independent visualisation of the crater resurfacing history that uses the reduction of the crater population in a given size range relative to the expected population given the observed crater density at larger sizes. From a set of potential type locations, 48 areas from 22 globally mapped units were deemed suitable for crater counting. Because resurfacing ages were derived from crater statistics, these secondary ages were used to define the unit age rather than the base age. Using the methods described herein, we modelled ages that are consistent with the interpreted stratigraphy. Our derived model ages allow age assignments to be included in unit names. We discuss the limitations of using the crater dating technique for global-scale geological mapping. Finally, we present recommendations for the documentation and presentation of crater statistics in publications.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.icarus.2013.04.021","usgsCitation":"Platz, T., Michael, G., Tanaka, K.L., Skinner, J., and Fortezzo, C.M., 2013, Crater-based dating of geological units on Mars: methods and application for the new global geological map: Icarus, v. 225, no. 1, p. 806-827, https://doi.org/10.1016/j.icarus.2013.04.021.","productDescription":"22 p.","startPage":"806","endPage":"827","ipdsId":"IP-041115","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":275371,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Mars","volume":"225","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51f253e9e4b0279fe2e1bfcd","contributors":{"authors":[{"text":"Platz, Thomas","contributorId":64974,"corporation":false,"usgs":true,"family":"Platz","given":"Thomas","affiliations":[],"preferred":false,"id":481326,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Michael, Gregory","contributorId":46393,"corporation":false,"usgs":true,"family":"Michael","given":"Gregory","affiliations":[],"preferred":false,"id":481325,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tanaka, Kenneth L. ktanaka@usgs.gov","contributorId":610,"corporation":false,"usgs":true,"family":"Tanaka","given":"Kenneth","email":"ktanaka@usgs.gov","middleInitial":"L.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":481322,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Skinner, James A. 0000-0002-3644-7010 jskinner@usgs.gov","orcid":"https://orcid.org/0000-0002-3644-7010","contributorId":3187,"corporation":false,"usgs":true,"family":"Skinner","given":"James A.","email":"jskinner@usgs.gov","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":481323,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fortezzo, Corey M. 0000-0001-8188-5530 cfortezzo@usgs.gov","orcid":"https://orcid.org/0000-0001-8188-5530","contributorId":25383,"corporation":false,"usgs":true,"family":"Fortezzo","given":"Corey","email":"cfortezzo@usgs.gov","middleInitial":"M.","affiliations":[{"id":130,"text":"Astrogeology Research Center","active":false,"usgs":true}],"preferred":false,"id":481324,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70047203,"text":"tm1D5 - 2013 - Optical techniques for the determination of nitrate in environmental waters: Guidelines for instrument selection, operation, deployment, maintenance, quality assurance, and data reporting","interactions":[],"lastModifiedDate":"2013-07-25T09:15:56","indexId":"tm1D5","displayToPublicDate":"2013-07-25T09:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1-D5","title":"Optical techniques for the determination of nitrate in environmental waters: Guidelines for instrument selection, operation, deployment, maintenance, quality assurance, and data reporting","docAbstract":"The recent commercial availability of in situ optical sensors, together with new techniques for data collection and analysis, provides the opportunity to monitor a wide range of water-quality constituents on time scales in which environmental conditions actually change. Of particular interest is the application of ultraviolet (UV) photometers for in situ determination of nitrate concentrations in rivers and streams. The variety of UV nitrate sensors currently available differ in several important ways related to instrument design that affect the accuracy of their nitrate concentration measurements in different types of natural waters. This report provides information about selection and use of UV nitrate sensors by the U.S. Geological Survey to facilitate the collection of high-quality data across studies, sites, and instrument types.\n\nFor those in need of technical background and information about sensor selection, this report addresses the operating principles, key features and sensor design, sensor characterization techniques and typical interferences, and approaches for sensor deployment. For those needing information about maintaining sensor performance in the field, key sections in this report address maintenance and calibration protocols, quality-assurance techniques, and data formats and reporting. Although the focus of this report is UV nitrate sensors, many of the principles can be applied to other in situ optical sensors for water-quality studies.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Section D: Water quality in Book 1 Collection of Water Data by Direct Measurement","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm1D5","collaboration":"This report is Chapter 5 of Section D: Water quality in Book 1 Collection of Water Data by Direct Measurement","usgsCitation":"Pellerin, B., Bergamaschi, B., Downing, B.D., Saraceno, J., Garrett, J.D., and Olsen, L., 2013, Optical techniques for the determination of nitrate in environmental waters: Guidelines for instrument selection, operation, deployment, maintenance, quality assurance, and data reporting: U.S. Geological Survey Techniques and Methods 1-D5, vi, 37 p., https://doi.org/10.3133/tm1D5.","productDescription":"vi, 37 p.","numberOfPages":"48","additionalOnlineFiles":"N","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":275370,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/tm1D5.jpg"},{"id":275369,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/tm/01/d5/"},{"id":275368,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/01/d5/pdf/tm1d5.pdf"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51f253eae4b0279fe2e1bfd9","contributors":{"authors":[{"text":"Pellerin, Brian A.","contributorId":58385,"corporation":false,"usgs":true,"family":"Pellerin","given":"Brian A.","affiliations":[],"preferred":false,"id":481349,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bergamaschi, Brian A. 0000-0002-9610-5581","orcid":"https://orcid.org/0000-0002-9610-5581","contributorId":73241,"corporation":false,"usgs":true,"family":"Bergamaschi","given":"Brian A.","affiliations":[],"preferred":false,"id":481351,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Downing, Bryan D. 0000-0002-2007-5304 bdowning@usgs.gov","orcid":"https://orcid.org/0000-0002-2007-5304","contributorId":1449,"corporation":false,"usgs":true,"family":"Downing","given":"Bryan","email":"bdowning@usgs.gov","middleInitial":"D.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":481346,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Saraceno, John Franco 0000-0003-0064-1820","orcid":"https://orcid.org/0000-0003-0064-1820","contributorId":71686,"corporation":false,"usgs":true,"family":"Saraceno","given":"John Franco","affiliations":[],"preferred":false,"id":481350,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Garrett, Jessica D. 0000-0002-4466-3709 jgarrett@usgs.gov","orcid":"https://orcid.org/0000-0002-4466-3709","contributorId":4229,"corporation":false,"usgs":true,"family":"Garrett","given":"Jessica","email":"jgarrett@usgs.gov","middleInitial":"D.","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":481348,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Olsen, Lisa D. ldolsen@usgs.gov","contributorId":2707,"corporation":false,"usgs":true,"family":"Olsen","given":"Lisa D.","email":"ldolsen@usgs.gov","affiliations":[{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true}],"preferred":true,"id":481347,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70188810,"text":"70188810 - 2013 - Implications for late Grenvillian (Rigolet phase) construction of Rodinia using new U-Pb data from the Mars Hill terrane, Tennessee and North Carolina, United States","interactions":[],"lastModifiedDate":"2017-06-27T11:02:54","indexId":"70188810","displayToPublicDate":"2013-07-25T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1796,"text":"Geology","active":true,"publicationSubtype":{"id":10}},"title":"Implications for late Grenvillian (Rigolet phase) construction of Rodinia using new U-Pb data from the Mars Hill terrane, Tennessee and North Carolina, United States","docAbstract":"New data for zircon (external morphology, cathodoluminescence zoning, and sensitive high resolution ion microprobe [SHRIMP] U-Pb ages) from the Carvers Gap granulite gneiss of the Mars Hill terrane (Tennessee and North Carolina, United States) require reevaluation of interpretations of the age and origin of this rock. The new results indicate that the zircon is detrital and that the sedimentary protolith of this gneiss (and related Cloudland gneiss) was deposited no earlier than ca. 1.02 Ga and was metamorphosed at ca. 0.98 Ga. Tectonic models that included the gneiss as a piece of 1.8 Ga Amazonian crust (perhaps as part of the hypothetical Columbia supercontinent) are now untenable. The remarkably fast cycle of exhumation, erosion, deposition, and deep burial also is characteristic of other late Grenvillian (post-Ottawan) Mesoproterozoic paragneisses that occur throughout the Appalachians. These rocks provide new evidence for the duration of the formation of the Rodinia supercontinent lasting until at least 0.98 Ma.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/G34779.1","usgsCitation":"Aleinikoff, J.N., Southworth, S., and Merschat, A.J., 2013, Implications for late Grenvillian (Rigolet phase) construction of Rodinia using new U-Pb data from the Mars Hill terrane, Tennessee and North Carolina, United States: Geology, v. 41, no. 10, p. 1087-1090, https://doi.org/10.1130/G34779.1.","productDescription":"4 p.","startPage":"1087","endPage":"1090","ipdsId":"IP-041874","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":342873,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina, Tennesee","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.3150634765625,\n 35.860117799832544\n ],\n [\n -81.73004150390625,\n 35.860117799832544\n ],\n [\n -81.73004150390625,\n 36.295204533693536\n ],\n [\n -82.3150634765625,\n 36.295204533693536\n ],\n [\n -82.3150634765625,\n 35.860117799832544\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"41","issue":"10","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59521d28e4b062508e3c36c7","contributors":{"authors":[{"text":"Aleinikoff, John N. 0000-0003-3494-6841 jaleinikoff@usgs.gov","orcid":"https://orcid.org/0000-0003-3494-6841","contributorId":1478,"corporation":false,"usgs":true,"family":"Aleinikoff","given":"John","email":"jaleinikoff@usgs.gov","middleInitial":"N.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":700459,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Southworth, Scott","contributorId":93933,"corporation":false,"usgs":true,"family":"Southworth","given":"Scott","affiliations":[],"preferred":false,"id":700643,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Merschat, Arthur J. 0000-0002-9314-4067 amerschat@usgs.gov","orcid":"https://orcid.org/0000-0002-9314-4067","contributorId":4556,"corporation":false,"usgs":true,"family":"Merschat","given":"Arthur","email":"amerschat@usgs.gov","middleInitial":"J.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":700644,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70042047,"text":"70042047 - 2013 - Monitoring intensity and patterns of off-highway vehicle (OHV) use in remote areas of the western USA","interactions":[],"lastModifiedDate":"2013-07-24T09:17:51","indexId":"70042047","displayToPublicDate":"2013-07-24T16:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2933,"text":"Oecologia Australis","active":true,"publicationSubtype":{"id":10}},"title":"Monitoring intensity and patterns of off-highway vehicle (OHV) use in remote areas of the western USA","docAbstract":"The continued growth of off-highway vehicle (OHV) activities – demonstrated by the dramatic increase in OHV sales, number of users, and areas experiencing OHV use – has elevated concerns about their ecological effects, the impacts on wildlife, and the sustainability of OHV use on secondary and tertiary road networks. Conflicts between visitors and wildlife are raising concerns about system resiliency and sustainable management. In order to quantify the spatial and temporal impacts of OHV use it is imperative to know about the timing and patterns of vehicle use. This study tested and used multiple vehicle-counter types to study vehicular OHV use patterns and volume throughout a mountainous road network in western Colorado. OHV counts were analyzed by time of day, day of week, season, and year. While daily use peaked within a two to three hour range for all sites, the overall volume of use varied among sites on an annual basis. The data also showed that there are at least two distinct patterns of OHV use: one dominated by a majority of use on weekends, and the other with continuous use throughout the week. This project provided important, but rarely captured, metrics about patterns of OHV use in a remote, mountainous region of Colorado. The techniques described here can provide land managers with a quantitative evaluation of OHV use across the landscape, an essential foundation for travel management planning. They also provide researchers with robust tools to further investigate the impacts of OHV use.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Oecologia Australis","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Oecologia Australis","doi":"10.4257/oeco.2013.1701.09","usgsCitation":"Ouren, D.S., and Coffin, A.W., 2013, Monitoring intensity and patterns of off-highway vehicle (OHV) use in remote areas of the western USA: Oecologia Australis, v. 17, no. 1, p. 96-110, https://doi.org/10.4257/oeco.2013.1701.09.","productDescription":"5 p.","startPage":"96","endPage":"110","ipdsId":"IP-039074","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":473653,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.4257/oeco.2013.1701.09","text":"Publisher Index Page"},{"id":275330,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":275326,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.4257/oeco.2013.1701.09"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.8,24.5 ], [ -124.8,49.383333 ], [ -66.95,49.383333 ], [ -66.95,24.5 ], [ -124.8,24.5 ] ] ] } } ] }","volume":"17","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51f0e95be4b04309f4e38ce7","contributors":{"authors":[{"text":"Ouren, Douglas S. ourend@usgs.gov","contributorId":1931,"corporation":false,"usgs":true,"family":"Ouren","given":"Douglas","email":"ourend@usgs.gov","middleInitial":"S.","affiliations":[],"preferred":true,"id":470670,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coffin, Alisa W. coffina@usgs.gov","contributorId":17305,"corporation":false,"usgs":true,"family":"Coffin","given":"Alisa","email":"coffina@usgs.gov","middleInitial":"W.","affiliations":[],"preferred":false,"id":470671,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70047191,"text":"ds720 - 2013 - EAARL coastal topography and imagery–Western Louisiana, post-Hurricane Rita, 2005: First surface","interactions":[],"lastModifiedDate":"2023-04-05T03:32:02.774678","indexId":"ds720","displayToPublicDate":"2013-07-24T13:05:00","publicationYear":"2013","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":"720","title":"EAARL coastal topography and imagery–Western Louisiana, post-Hurricane Rita, 2005: First surface","docAbstract":"These remotely sensed, geographically referenced color-infrared (CIR) imagery and elevation measurements of lidar-derived first-surface (FS) topography datasets were produced by the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center, St. Petersburg, Florida, and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, Virginia. This project provides highly detailed and accurate datasets of a portion of the Louisiana coastline beachface, acquired post-Hurricane Rita on September 27-28 and October 2, 2005. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative airborne lidar instrument originally developed at the National Aeronautics and Space Administration (NASA) Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multispectral color-infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for sub-meter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine Cessna 310 aircraft, but the instrument may be deployed on a range of light aircraft. A single pilot, a lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of lidar data in an interactive or batch mode. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or sub-aerial topography. Specialized filtering algorithms have been implemented to determine the \"bare earth\" under vegetation from a point cloud of last return elevations. For more information about similar projects, please visit the Lidar for Science and Resource Management Website.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds720","usgsCitation":"Bonisteel-Cormier, J.M., Wright, W.C., Fredericks, X., Klipp, E.S., Nagle, D., Sallenger, A., and Brock, J., 2013, EAARL coastal topography and imagery–Western Louisiana, post-Hurricane Rita, 2005: First surface: U.S. Geological Survey Data Series 720, HTML Document, https://doi.org/10.3133/ds720.","productDescription":"HTML Document","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":275345,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":275344,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/720/title.html"},{"id":275343,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/720/"}],"country":"United States","state":"Louisiana","otherGeospatial":"Gulf of Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -94.00837692113316,\n 30.239834373180088\n ],\n [\n -94.00837692113316,\n 29.170414182419464\n ],\n [\n -91.68628733181568,\n 29.170414182419464\n ],\n [\n -91.68628733181568,\n 30.239834373180088\n ],\n [\n -94.00837692113316,\n 30.239834373180088\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51f0e959e4b04309f4e38cdb","contributors":{"authors":[{"text":"Bonisteel-Cormier, Jamie M.","contributorId":18085,"corporation":false,"usgs":true,"family":"Bonisteel-Cormier","given":"Jamie","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":481318,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wright, Wayne C.","contributorId":6747,"corporation":false,"usgs":true,"family":"Wright","given":"Wayne","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":481317,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fredericks, Xan 0000-0001-7186-6555 afredericks@usgs.gov","orcid":"https://orcid.org/0000-0001-7186-6555","contributorId":2972,"corporation":false,"usgs":true,"family":"Fredericks","given":"Xan","email":"afredericks@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":481316,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Klipp, Emily S. eklipp@usgs.gov","contributorId":2754,"corporation":false,"usgs":true,"family":"Klipp","given":"Emily","email":"eklipp@usgs.gov","middleInitial":"S.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":481315,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nagle, Doug B.","contributorId":34802,"corporation":false,"usgs":true,"family":"Nagle","given":"Doug B.","affiliations":[],"preferred":false,"id":481320,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sallenger, Asbury H. Jr.","contributorId":27458,"corporation":false,"usgs":true,"family":"Sallenger","given":"Asbury H.","suffix":"Jr.","affiliations":[],"preferred":false,"id":481319,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Brock, John 0000-0002-5289-9332 jbrock@usgs.gov","orcid":"https://orcid.org/0000-0002-5289-9332","contributorId":2261,"corporation":false,"usgs":true,"family":"Brock","given":"John","email":"jbrock@usgs.gov","affiliations":[{"id":5061,"text":"National Cooperative Geologic Mapping and Landslide Hazards","active":true,"usgs":true}],"preferred":true,"id":481314,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70047186,"text":"ofr20131151 - 2013 - Quality-assurance plan for groundwater activities, U.S. Geological Survey, Washington Water Science Center","interactions":[],"lastModifiedDate":"2013-07-24T09:48:45","indexId":"ofr20131151","displayToPublicDate":"2013-07-24T09:25:00","publicationYear":"2013","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":"2013-1151","title":"Quality-assurance plan for groundwater activities, U.S. Geological Survey, Washington Water Science Center","docAbstract":"This report documents the standard procedures, policies, and field methods used by the U.S. Geological Survey’s (USGS) Washington Water Science Center staff for activities related to the collection, processing, analysis, storage, and publication of groundwater data. This groundwater quality-assurance plan changes through time to accommodate new methods and requirements developed by the Washington Water Science Center and the USGS Office of Groundwater. The plan is based largely on requirements and guidelines provided by the USGS Office of Groundwater, or the USGS Water Mission Area. Regular updates to this plan represent an integral part of the quality-assurance process. Because numerous policy memoranda have been issued by the Office of Groundwater since the previous groundwater quality assurance plan was written, this report is a substantial revision of the previous report, supplants it, and contains significant additional policies not covered in the previous report.\n\nThis updated plan includes information related to the organization and responsibilities of USGS Washington Water Science Center staff, training, safety, project proposal development, project review procedures, data collection activities, data processing activities, report review procedures, and archiving of field data and interpretative information pertaining to groundwater flow models, borehole aquifer tests, and aquifer tests. Important updates from the previous groundwater quality assurance plan include: (1) procedures for documenting and archiving of groundwater flow models; (2) revisions to procedures and policies for the creation of sites in the Groundwater Site Inventory database; (3) adoption of new water-level forms to be used within the USGS Washington Water Science Center; (4) procedures for future creation of borehole geophysics, surface geophysics, and aquifer-test archives; and (5) use of the USGS Multi Optional Network Key Entry System software for entry of routine water-level data collected as part of long-term water-level monitoring networks.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131151","usgsCitation":"Kozar, M.D., and Kahle, S.C., 2013, Quality-assurance plan for groundwater activities, U.S. Geological Survey, Washington Water Science Center: U.S. Geological Survey Open-File Report 2013-1151, iv, 88 p., https://doi.org/10.3133/ofr20131151.","productDescription":"iv, 88 p.","numberOfPages":"92","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":275337,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131151.bmp"},{"id":275335,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1151/pdf/ofr20131151.pdf"},{"id":275336,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1151/"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51f0e95de4b04309f4e38cf3","contributors":{"authors":[{"text":"Kozar, Mark D. 0000-0001-7755-7657 mdkozar@usgs.gov","orcid":"https://orcid.org/0000-0001-7755-7657","contributorId":1963,"corporation":false,"usgs":true,"family":"Kozar","given":"Mark","email":"mdkozar@usgs.gov","middleInitial":"D.","affiliations":[{"id":37280,"text":"Virginia and West Virginia Water Science Center ","active":true,"usgs":true}],"preferred":true,"id":481304,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kahle, Sue C. 0000-0003-1262-4446 sckahle@usgs.gov","orcid":"https://orcid.org/0000-0003-1262-4446","contributorId":3096,"corporation":false,"usgs":true,"family":"Kahle","given":"Sue","email":"sckahle@usgs.gov","middleInitial":"C.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":481305,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70047173,"text":"70047173 - 2013 - Applying UV cameras for SO2 detection to distant or optically thick volcanic plumes","interactions":[],"lastModifiedDate":"2013-07-23T15:23:06","indexId":"70047173","displayToPublicDate":"2013-07-23T15:18:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Applying UV cameras for SO2 detection to distant or optically thick volcanic plumes","docAbstract":"Ultraviolet (UV) camera systems represent an exciting new technology for measuring two dimensional sulfur dioxide (SO2) distributions in volcanic plumes. The high frame rate of the cameras allows the retrieval of SO2 emission rates at time scales of 1 Hz or higher, thus allowing the investigation of high-frequency signals and making integrated and comparative studies with other high-data-rate volcano monitoring techniques possible. One drawback of the technique, however, is the limited spectral information recorded by the imaging systems. Here, a framework for simulating the sensitivity of UV cameras to various SO2 distributions is introduced. Both the wavelength-dependent transmittance of the optical imaging system and the radiative transfer in the atmosphere are modeled. The framework is then applied to study the behavior of different optical setups and used to simulate the response of these instruments to volcanic plumes containing varying SO2 and aerosol abundances located at various distances from the sensor. Results show that UV radiative transfer in and around distant and/or optically thick plumes typically leads to a lower sensitivity to SO2 than expected when assuming a standard Beer–Lambert absorption model. Furthermore, camera response is often non-linear in SO2 and dependent on distance to the plume and plume aerosol optical thickness and single scatter albedo. The model results are compared with camera measurements made at Kilauea Volcano (Hawaii) and a method for integrating moderate resolution differential optical absorption spectroscopy data with UV imagery to retrieve improved SO2 column densities is discussed.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Volcanology and Geothermal Research","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2013.06.009","usgsCitation":"Kern, C., Werner, C., Elias, T., Sutton, A.J., and Lübcke, P., 2013, Applying UV cameras for SO2 detection to distant or optically thick volcanic plumes: Journal of Volcanology and Geothermal Research, v. 262, p. 80-89, https://doi.org/10.1016/j.jvolgeores.2013.06.009.","productDescription":"10 p.","startPage":"80","endPage":"89","ipdsId":"IP-043068","costCenters":[{"id":157,"text":"Cascades Volcano Observatory","active":false,"usgs":true}],"links":[{"id":275321,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":275320,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.jvolgeores.2013.06.009"},{"id":275310,"type":{"id":15,"text":"Index Page"},"url":"https://linkinghub.elsevier.com/retrieve/pii/S0377027313001832"}],"volume":"262","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51ef97cfe4b0b09fbe58f145","contributors":{"authors":[{"text":"Kern, Christoph 0000-0002-8920-5701 ckern@usgs.gov","orcid":"https://orcid.org/0000-0002-8920-5701","contributorId":3387,"corporation":false,"usgs":true,"family":"Kern","given":"Christoph","email":"ckern@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":481220,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Werner, Cynthia 0000-0003-3311-6694","orcid":"https://orcid.org/0000-0003-3311-6694","contributorId":11444,"corporation":false,"usgs":true,"family":"Werner","given":"Cynthia","affiliations":[],"preferred":false,"id":481222,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Elias, Tamar 0000-0002-9592-4518 telias@usgs.gov","orcid":"https://orcid.org/0000-0002-9592-4518","contributorId":3916,"corporation":false,"usgs":true,"family":"Elias","given":"Tamar","email":"telias@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":481221,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sutton, A. Jeff","contributorId":45605,"corporation":false,"usgs":true,"family":"Sutton","given":"A.","email":"","middleInitial":"Jeff","affiliations":[],"preferred":false,"id":481223,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lübcke, Peter","contributorId":82202,"corporation":false,"usgs":true,"family":"Lübcke","given":"Peter","affiliations":[],"preferred":false,"id":481224,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70043322,"text":"70043322 - 2013 - Presence of indicator plant species as a predictor of wetland vegetation integrity","interactions":[],"lastModifiedDate":"2013-07-23T13:36:52","indexId":"70043322","displayToPublicDate":"2013-07-23T13:23:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3086,"text":"Plant Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Presence of indicator plant species as a predictor of wetland vegetation integrity","docAbstract":"We fit regression and classification tree models to vegetation data collected from Ohio (USA) wetlands to determine (1) which species best predict Ohio vegetation index of biotic integrity (OVIBI) score and (2) which species best predict high-quality wetlands (OVIBI score >75). The simplest regression tree model predicted OVIBI score based on the occurrence of three plant species: skunk-cabbage (Symplocarpus foetidus), cinnamon fern (Osmunda cinnamomea), and swamp rose (Rosa palustris). The lowest OVIBI scores were best predicted by the absence of the selected plant species rather than by the presence of other species. The simplest classification tree model predicted high-quality wetlands based on the occurrence of two plant species: skunk-cabbage and marsh-fern (Thelypteris palustris). The overall misclassification rate from this tree was 13 %. Again, low-quality wetlands were better predicted than high-quality wetlands by the absence of selected species rather than the presence of other species using the classification tree model. Our results suggest that a species’ wetland status classification and coefficient of conservatism are of little use in predicting wetland quality. A simple, statistically derived species checklist such as the one created in this study could be used by field biologists to quickly and efficiently identify wetland sites likely to be regulated as high-quality, and requiring more intensive field assessments. Alternatively, it can be used for advanced determinations of low-quality wetlands. Agencies can save considerable money by screening wetlands for the presence/absence of such “indicator” species before issuing permits.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Plant Ecology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","doi":"10.1007/s11258-013-0168-z","usgsCitation":"Stapanian, M.A., Adams, J.V., and Gara, B., 2013, Presence of indicator plant species as a predictor of wetland vegetation integrity: Plant Ecology, v. 214, no. 2, p. 291-302, https://doi.org/10.1007/s11258-013-0168-z.","productDescription":"12 p.","startPage":"291","endPage":"302","numberOfPages":"12","ipdsId":"IP-043331","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":275306,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":275302,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s11258-013-0168-z"}],"country":"United States","state":"Ohio","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -84.1502,38.4032 ], [ -84.1502,41.9321 ], [ -80.519,41.9321 ], [ -80.519,38.4032 ], [ -84.1502,38.4032 ] ] ] } } ] }","volume":"214","issue":"2","noUsgsAuthors":false,"publicationDate":"2013-01-26","publicationStatus":"PW","scienceBaseUri":"51ef97d8e4b0b09fbe58f165","contributors":{"authors":[{"text":"Stapanian, Martin A. 0000-0001-8173-4273 mstapanian@usgs.gov","orcid":"https://orcid.org/0000-0001-8173-4273","contributorId":3425,"corporation":false,"usgs":true,"family":"Stapanian","given":"Martin","email":"mstapanian@usgs.gov","middleInitial":"A.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":473387,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Adams, Jean V. 0000-0002-9101-068X jvadams@usgs.gov","orcid":"https://orcid.org/0000-0002-9101-068X","contributorId":3140,"corporation":false,"usgs":true,"family":"Adams","given":"Jean","email":"jvadams@usgs.gov","middleInitial":"V.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":473386,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gara, Brian","contributorId":52061,"corporation":false,"usgs":true,"family":"Gara","given":"Brian","affiliations":[],"preferred":false,"id":473388,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70047164,"text":"ofr20131127 - 2013 - Streamflow, water quality, and constituent loads and yields, Scituate Reservoir drainage area, Rhode Island, water year 2011","interactions":[],"lastModifiedDate":"2014-07-15T08:57:18","indexId":"ofr20131127","displayToPublicDate":"2013-07-23T11:14:00","publicationYear":"2013","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":"2013-1127","title":"Streamflow, water quality, and constituent loads and yields, Scituate Reservoir drainage area, Rhode Island, water year 2011","docAbstract":"Streamflow and concentrations of sodium and chloride estimated from records of specific conductance were used to calculate loads of sodium and chloride during water year (WY) 2011 (October 1, 2010, to September 30, 2011), for tributaries to the Scituate Reservoir, Rhode Island. Streamflow and water-quality data used in the study were collected by the U.S. Geological Survey (USGS) or the Providence Water Supply Board (PWSB). Streamflow was measured or estimated by the USGS following standard methods at 23 streamgages; 14 of these streamgages were also equipped with instrumentation capable of continuously monitoring water level, specific conductance, and water temperature. Water-quality samples also were collected at 37 sampling stations by the PWSB and at 14 continuous-record streamgages by the USGS during WY 2011 as part of a long-term sampling program; all stations were in the Scituate Reservoir drainage area. Water-quality data collected by PWSB are summarized by using values of central tendency and are used, in combination with measured (or estimated) streamflows, to calculate loads and yields (loads per unit area) of selected water-quality constituents for WY 2011.
\nThe largest tributary to the reservoir (the Ponaganset River, which was monitored by the USGS) contributed a mean streamflow of about 37 cubic feet per second (ft3/s) to the reservoir during WY 2011. For the same time period, annual mean1 streamflows measured (or estimated) for the other monitoring stations in this study ranged from about 0.5 to about 21 ft3/s. Together, tributaries (equipped with instrumentation capable of continuously monitoring specific conductance) transported about 1,600,000 kg (kilograms) of sodium and 2,600,000 kg of chloride to the Scituate Reservoir during WY 2011; sodium and chloride yields for the tributaries ranged from 9,800 to 53,000 kilograms per square mile (kg/mi2) and from 15,000 to 90,000 kg/mi2, respectively.
\nAt the stations where water-quality samples were collected by the PWSB, the median of the median chloride concentrations was 20.0 milligrams per liter (mg/L), median nitrite concentration was 0.002 mg/L as nitrogen (N), median nitrate concentration was 0.01 mg/L as N, median orthophosphate concentration was 0.07 mg/L as phosphorus, and median concentrations of total coliform and Escherichia coli (E. coli) bacteria were 33 and 23 colony forming units per 100 milliliters (CFU/100mL), respectively. The medians of the median daily loads (and yields) of chloride, nitrite, nitrate, orthophosphate, and total coliform and E. coli bacteria were 230 kilograms per day (kg/d) (80 kilograms per day per square mile (kg/d/mi2)); 10 grams per day (g/d) (6.3 grams per day per square mile (g/d/mi2)); 110 g/d (29 g/d/mi2); 610 g/d (270 g/d/mi2); 4,600 million colony forming units per day (CFUx106/d) (2,500 CFUx106/d/mi2); and 1,800 CFUx106/d (810 CFUx106/d/mi2), respectively.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131127","collaboration":"Prepared in cooperation with the Providence Water Supply Board","usgsCitation":"Smith, K.P., 2013, Streamflow, water quality, and constituent loads and yields, Scituate Reservoir drainage area, Rhode Island, water year 2011 (First posted July 23, 2013; Revised and reposted July 14, 2014, version 1.1): U.S. Geological Survey Open-File Report 2013-1127, vi, 32 p., https://doi.org/10.3133/ofr20131127.","productDescription":"vi, 32 p.","numberOfPages":"42","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2010-09-30","temporalEnd":"2011-10-31","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":275281,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131127.jpg"},{"id":275279,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1127/"},{"id":275280,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1127/pdf/ofr2013-1127.pdf"}],"country":"United States","state":"Rhode Island","otherGeospatial":"Scituate Reservoir","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -72.0,41.5 ], [ -72.0,42.0 ], [ -71.5,42.0 ], [ -71.5,41.5 ], [ -72.0,41.5 ] ] ] } } ] }","edition":"First posted July 23, 2013; Revised and reposted July 14, 2014, version 1.1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51ef97d9e4b0b09fbe58f16d","contributors":{"authors":[{"text":"Smith, Kirk P. 0000-0003-0269-474X kpsmith@usgs.gov","orcid":"https://orcid.org/0000-0003-0269-474X","contributorId":1516,"corporation":false,"usgs":true,"family":"Smith","given":"Kirk","email":"kpsmith@usgs.gov","middleInitial":"P.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true}],"preferred":true,"id":481197,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70046834,"text":"70046834 - 2013 - Potentially induced earthquakes in Oklahoma, USA: links between wastewater injection and the 2011 Mw 5.7 earthquake sequence","interactions":[],"lastModifiedDate":"2019-07-17T16:26:58","indexId":"70046834","displayToPublicDate":"2013-07-23T09:38:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1796,"text":"Geology","active":true,"publicationSubtype":{"id":10}},"title":"Potentially induced earthquakes in Oklahoma, USA: links between wastewater injection and the 2011 Mw 5.7 earthquake sequence","docAbstract":"Significant earthquakes are increasingly occurring within the continental interior of the United States, including five of moment magnitude (Mw) ≥ 5.0 in 2011 alone. Concurrently, the volume of fluid injected into the subsurface related to the production of unconventional resources continues to rise. Here we identify the largest earthquake potentially related to injection, an Mw 5.7 earthquake in November 2011 in Oklahoma. The earthquake was felt in at least 17 states and caused damage in the epicentral region. It occurred in a sequence, with 2 earthquakes of Mw 5.0 and a prolific sequence of aftershocks. We use the aftershocks to illuminate the faults that ruptured in the sequence, and show that the tip of the initial rupture plane is within ~200 m of active injection wells and within ~1 km of the surface; 30% of early aftershocks occur within the sedimentary section. Subsurface data indicate that fluid was injected into effectively sealed compartments, and we interpret that a net fluid volume increase after 18 yr of injection lowered effective stress on reservoir-bounding faults. Significantly, this case indicates that decades-long lags between the commencement of fluid injection and the onset of induced earthquakes are possible, and modifies our common criteria for fluid-induced events. The progressive rupture of three fault planes in this sequence suggests that stress changes from the initial rupture triggered the successive earthquakes, including one larger than the first.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Geology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Geological Society of America","doi":"10.1130/G34045.1","usgsCitation":"Keranen, K., Savage, H.M., Abers, G.A., and Cochran, E.S., 2013, Potentially induced earthquakes in Oklahoma, USA: links between wastewater injection and the 2011 Mw 5.7 earthquake sequence: Geology, v. 41, no. 6, p. 699-702, https://doi.org/10.1130/G34045.1.","productDescription":"4 p.","startPage":"699","endPage":"702","ipdsId":"IP-039045","costCenters":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":275269,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":274697,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1130/G34045.1"}],"country":"United States","state":"Oklahoma","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -103.0,33.62 ], [ -103.0,37.0 ], [ -94.43,37.0 ], [ -94.43,33.62 ], [ -103.0,33.62 ] ] ] } } ] }","volume":"41","issue":"6","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51ef97d6e4b0b09fbe58f15d","contributors":{"authors":[{"text":"Keranen, Katie M.","contributorId":44064,"corporation":false,"usgs":true,"family":"Keranen","given":"Katie M.","affiliations":[],"preferred":false,"id":480414,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Savage, Heather M.","contributorId":65363,"corporation":false,"usgs":true,"family":"Savage","given":"Heather","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":480415,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Abers, Geoffrey A.","contributorId":90195,"corporation":false,"usgs":true,"family":"Abers","given":"Geoffrey","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":480416,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cochran, Elizabeth S. 0000-0003-2485-4484 ecochran@usgs.gov","orcid":"https://orcid.org/0000-0003-2485-4484","contributorId":2025,"corporation":false,"usgs":true,"family":"Cochran","given":"Elizabeth","email":"ecochran@usgs.gov","middleInitial":"S.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":480413,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70046061,"text":"70046061 - 2013 - Predicting the likelihood of altered streamflows at ungauged rivers across the conterminous United States","interactions":[],"lastModifiedDate":"2013-07-23T09:48:25","indexId":"70046061","displayToPublicDate":"2013-07-23T09:35:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3301,"text":"River Research and Applications","active":true,"publicationSubtype":{"id":10}},"title":"Predicting the likelihood of altered streamflows at ungauged rivers across the conterminous United States","docAbstract":"An approach is presented in this study to aid water-resource managers in characterizing streamflow alteration at ungauged rivers. Such approaches can be used to take advantage of the substantial amounts of biological data collected at ungauged rivers to evaluate the potential ecological consequences of altered streamflows. National-scale random forest statistical models are developed to predict the likelihood that ungauged rivers have altered streamflows (relative to expected natural condition) for five hydrologic metrics (HMs) representing different aspects of the streamflow regime. The models use human disturbance variables, such as number of dams and road density, to predict the likelihood of streamflow alteration. For each HM, separate models are derived to predict the likelihood that the observed metric is greater than (‘inflated’) or less than (‘diminished’) natural conditions. The utility of these models is demonstrated by applying them to all river segments in the South Platte River in Colorado, USA, and for all 10-digit hydrologic units in the conterminous United States. In general, the models successfully predicted the likelihood of alteration to the five HMs at the national scale as well as in the South Platte River basin. However, the models predicting the likelihood of diminished HMs consistently outperformed models predicting inflated HMs, possibly because of fewer sites across the conterminous United States where HMs are inflated. The results of these analyses suggest that the primary predictors of altered streamflow regimes across the Nation are (i) the residence time of annual runoff held in storage in reservoirs, (ii) the degree of urbanization measured by road density and (iii) the extent of agricultural land cover in the river basin.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"River Research and Applications","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1002/rra.2565","usgsCitation":"Eng, K., Carlisle, D.M., Wolock, D.M., and Falcone, J.A., 2013, Predicting the likelihood of altered streamflows at ungauged rivers across the conterminous United States: River Research and Applications, v. 29, no. 6, p. 781-791, https://doi.org/10.1002/rra.2565.","productDescription":"10 p.","startPage":"781","endPage":"791","numberOfPages":"10","ipdsId":"IP-034661","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":275268,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":275267,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/rra.2565"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -125.14,25.89 ], [ -125.14,49.11 ], [ -66.95,49.11 ], [ -66.95,25.89 ], [ -125.14,25.89 ] ] ] } } ] }","volume":"29","issue":"6","noUsgsAuthors":false,"publicationDate":"2012-03-09","publicationStatus":"PW","scienceBaseUri":"51ef97d8e4b0b09fbe58f161","contributors":{"authors":[{"text":"Eng, Ken 0000-0001-6838-5849 keng@usgs.gov","orcid":"https://orcid.org/0000-0001-6838-5849","contributorId":3580,"corporation":false,"usgs":true,"family":"Eng","given":"Ken","email":"keng@usgs.gov","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":478791,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carlisle, Daren M. 0000-0002-7367-348X dcarlisle@usgs.gov","orcid":"https://orcid.org/0000-0002-7367-348X","contributorId":513,"corporation":false,"usgs":true,"family":"Carlisle","given":"Daren","email":"dcarlisle@usgs.gov","middleInitial":"M.","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"preferred":true,"id":478788,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wolock, David M. 0000-0002-6209-938X dwolock@usgs.gov","orcid":"https://orcid.org/0000-0002-6209-938X","contributorId":540,"corporation":false,"usgs":true,"family":"Wolock","given":"David","email":"dwolock@usgs.gov","middleInitial":"M.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"preferred":true,"id":478789,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Falcone, James A. 0000-0001-7202-3592 jfalcone@usgs.gov","orcid":"https://orcid.org/0000-0001-7202-3592","contributorId":614,"corporation":false,"usgs":true,"family":"Falcone","given":"James","email":"jfalcone@usgs.gov","middleInitial":"A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":478790,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70047160,"text":"70047160 - 2013 - Correlating multispectral imaging and compositional data from the Mars Exploration Rovers and implications for Mars Science Laboratory","interactions":[],"lastModifiedDate":"2013-07-23T09:22:27","indexId":"70047160","displayToPublicDate":"2013-07-23T09:17:55","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1963,"text":"Icarus","active":true,"publicationSubtype":{"id":10}},"title":"Correlating multispectral imaging and compositional data from the Mars Exploration Rovers and implications for Mars Science Laboratory","docAbstract":"In an effort to infer compositional information about distant targets based on multispectral imaging data, we investigated methods of relating Mars Exploration Rover (MER) Pancam multispectral remote sensing observations to in situ alpha particle X-ray spectrometer (APXS)-derived elemental abundances and Mössbauer (MB)-derived abundances of Fe-bearing phases at the MER field sites in Gusev crater and Meridiani Planum. The majority of the partial correlation coefficients between these data sets were not statistically significant. Restricting the targets to those that were abraded by the rock abrasion tool (RAT) led to improved Pearson’s correlations, most notably between the red–blue ratio (673 nm/434 nm) and Fe3+-bearing phases, but partial correlations were not statistically significant. Partial Least Squares (PLS) calculations relating Pancam 11-color visible to near-IR (VNIR; ∼400–1000 nm) “spectra” to APXS and Mössbauer element or mineral abundances showed generally poor performance, although the presence of compositional outliers led to improved PLS results for data from Meridiani. When the Meridiani PLS model for pyroxene was tested by predicting the pyroxene content of Gusev targets, the results were poor, indicating that the PLS models for Meridiani are not applicable to data from other sites. Soft Independent Modeling of Class Analogy (SIMCA) classification of Gusev crater data showed mixed results. Of the 24 Gusev test regions of interest (ROIs) with known classes, 11 had >30% of the pixels in the ROI classified correctly, while others were mis-classified or unclassified. k-Means clustering of APXS and Mössbauer data was used to assign Meridiani targets to compositional classes. The clustering-derived classes corresponded to meaningful geologic and/or color unit differences, and SIMCA classification using these classes was somewhat successful, with >30% of pixels correctly classified in 9 of the 11 ROIs with known classes.\n\nThis work shows that the relationship between SWIR multispectral imaging data and APXS- and Mössbauer-derived composition/mineralogy is often weak, a perhaps not entirely unexpected result given the different surface sampling depths of SWIR imaging (uppermost few microns) vs. APXS (tens of μm) and MB measurements (hundreds of μm). Results from the upcoming Mars Science Laboratory (MSL) rover’s ChemCam Laser Induced Breakdown Spectroscopy (LIBS) instrument may show a closer relationship to Mastcam SWIR multispectral observations, however, because the initial laser shots onto a target will analyze only the upper few micrometers of the surface. The clustering and classification methods used in this study can be applied to any data set to formalize the definition of classes and identify targets that do not fit in previously defined classes.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Icarus","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.icarus.2012.11.029","usgsCitation":"Anderson, R., and Bell, J.F., 2013, Correlating multispectral imaging and compositional data from the Mars Exploration Rovers and implications for Mars Science Laboratory: Icarus, v. 223, no. 1, p. 157-180, https://doi.org/10.1016/j.icarus.2012.11.029.","productDescription":"24 p.","startPage":"157","endPage":"180","ipdsId":"IP-036034","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":275266,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":275265,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.icarus.2012.11.029"}],"otherGeospatial":"Mars","volume":"223","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51ef97d4e4b0b09fbe58f149","contributors":{"authors":[{"text":"Anderson, Ryan B.","contributorId":25438,"corporation":false,"usgs":true,"family":"Anderson","given":"Ryan B.","affiliations":[],"preferred":false,"id":481190,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bell, James F. III","contributorId":12737,"corporation":false,"usgs":true,"family":"Bell","given":"James","suffix":"III","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":481189,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70046880,"text":"70046880 - 2013 - Population genetics and evaluation of genetic evidence for subspecies in the Semipalmated Sandpiper (Calidris pusilla)","interactions":[],"lastModifiedDate":"2020-12-29T15:03:14.119164","indexId":"70046880","displayToPublicDate":"2013-07-23T08:34:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3731,"text":"Waterbirds","onlineIssn":"19385390","printIssn":"15244695","active":true,"publicationSubtype":{"id":10}},"title":"Population genetics and evaluation of genetic evidence for subspecies in the Semipalmated Sandpiper (Calidris pusilla)","docAbstract":"Semipalmated Sandpipers (Calidris pusilla) are among the most common North American shorebirds. Breeding in Arctic North America, this species displays regional differences in migratory pathways and possesses longitudinal bill length variation. Previous investigations suggested that genetic structure may occur within Semipalmated Sandpipers and that three subspecies corresponding to western, central, and eastern breeding groups exist. In this study, mitochondrial control region sequences and nuclear microsatellite loci were used to analyze DNA of birds (microsatellites: n = 120; mtDNA: n = 114) sampled from seven North American locations. Analyses designed to quantify genetic structure and diversity patterns, evaluate genetic evidence for population size changes, and determine if genetic data support the existence of Semipalmated Sandpiper subspecies were performed. Genetic structure based only on the mtDNA data was observed, whereas the microsatellite loci provided no evidence of genetic differentiation. Differentiation among locations and regions reflected allele frequency differences rather than separate phylogenetic groups, and similar levels of genetic diversity were noted. Combined, the two data sets provided no evidence to support the existence of subspecies and were not useful for determining migratory connectivity between breeding sites and wintering grounds. Birds from western and central groups displayed signatures of population expansions, whereas the eastern group was more consistent with a stable overall population. Results of this analysis suggest that the eastern group was the source of individuals that colonized the central and western regions currently utilized by Semipalmated Sandpipers.
","language":"English","publisher":"The Waterbird Society","doi":"10.1675/063.036.0206","usgsCitation":"Miller, M.P., Gratto-Trevor, C., Haig, S.M., Mizrahi, D.S., Mitchell, M.M., and Mullins, T., 2013, Population genetics and evaluation of genetic evidence for subspecies in the Semipalmated Sandpiper (Calidris pusilla): Waterbirds, v. 36, no. 2, p. 166-178, https://doi.org/10.1675/063.036.0206.","productDescription":"13 p.","startPage":"166","endPage":"178","ipdsId":"IP-042836","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":473660,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1675/063.036.0206","text":"Publisher Index Page"},{"id":381723,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"North America","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -178.8,25.3 ], [ -178.8,83.2 ], [ -51.3,83.2 ], [ -51.3,25.3 ], [ -178.8,25.3 ] ] ] } } ] }","volume":"36","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51ef97d6e4b0b09fbe58f159","contributors":{"authors":[{"text":"Miller, Mark P. 0000-0003-1045-1772 mpmiller@usgs.gov","orcid":"https://orcid.org/0000-0003-1045-1772","contributorId":1967,"corporation":false,"usgs":true,"family":"Miller","given":"Mark","email":"mpmiller@usgs.gov","middleInitial":"P.","affiliations":[{"id":38131,"text":"WMA - Office of Planning and Programming","active":true,"usgs":true}],"preferred":true,"id":480555,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gratto-Trevor, Cheri","contributorId":58539,"corporation":false,"usgs":true,"family":"Gratto-Trevor","given":"Cheri","affiliations":[],"preferred":false,"id":480559,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haig, Susan M. 0000-0002-6616-7589 susan_haig@usgs.gov","orcid":"https://orcid.org/0000-0002-6616-7589","contributorId":719,"corporation":false,"usgs":true,"family":"Haig","given":"Susan","email":"susan_haig@usgs.gov","middleInitial":"M.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":480554,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mizrahi, David S.","contributorId":11100,"corporation":false,"usgs":true,"family":"Mizrahi","given":"David","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":480556,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mitchell, Melanie M.","contributorId":38045,"corporation":false,"usgs":true,"family":"Mitchell","given":"Melanie","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":480558,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mullins, Thomas D.","contributorId":12819,"corporation":false,"usgs":true,"family":"Mullins","given":"Thomas D.","affiliations":[],"preferred":false,"id":480557,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70047143,"text":"ofr20131146 - 2013 - Geochronologic and geochemical data from Mesozoic rocks in the Black Mountain area northeast of Victorville, San Bernardino County, California","interactions":[],"lastModifiedDate":"2023-06-05T15:09:34.640808","indexId":"ofr20131146","displayToPublicDate":"2013-07-22T15:55:00","publicationYear":"2013","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":"2013-1146","title":"Geochronologic and geochemical data from Mesozoic rocks in the Black Mountain area northeast of Victorville, San Bernardino County, California","docAbstract":"We present geochronologic and geochemical data for Mesozoic rocks in the Black Mountain area northeast of Victorville, California, to supplement previous geologic mapping. These data, together with previously published results, limit the depositional age of the sedimentary Fairview Valley Formation to Early Jurassic, refine the ages and chemical compositions of selected units in the overlying Jurassic Sidewinder Volcanics and of related intrusive units, and limit the age of some post-Sidewinder faulting in the Black Mountain area to a brief interval in the Late Jurassic. The new information contributes to a more complete understanding of the Mesozoic magmatic and tectonic evolution of the western Mojave Desert and surrounding regions.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131146","usgsCitation":"Stone, P., Barth, A.P., Wooden, J., Fohey-Breting, N.K., Vazquez, J.A., and Priest, S.S., 2013, Geochronologic and geochemical data from Mesozoic rocks in the Black Mountain area northeast of Victorville, San Bernardino County, California: U.S. Geological Survey Open-File Report 2013-1146, iv, 31 p., https://doi.org/10.3133/ofr20131146.","productDescription":"iv, 31 p.","numberOfPages":"37","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":275252,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131146.gif"},{"id":275250,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1146/","linkFileType":{"id":5,"text":"html"}},{"id":275251,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1146/of2013-1146.pdf","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"California","county":"San Bernardino","otherGeospatial":"Black Mountain Area","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -117.5823,34.07 ], [ -117.5823,34.98 ], [ -117.347,34.98 ], [ -117.347,34.07 ], [ -117.5823,34.07 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51ee4655e4b00ffbed48f849","contributors":{"authors":[{"text":"Stone, Paul 0000-0002-1439-0156 pastone@usgs.gov","orcid":"https://orcid.org/0000-0002-1439-0156","contributorId":273,"corporation":false,"usgs":true,"family":"Stone","given":"Paul","email":"pastone@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":481156,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barth, Andrew P.","contributorId":94547,"corporation":false,"usgs":true,"family":"Barth","given":"Andrew","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":481160,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wooden, Joseph L.","contributorId":32209,"corporation":false,"usgs":true,"family":"Wooden","given":"Joseph L.","affiliations":[],"preferred":false,"id":481159,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fohey-Breting, Nicole K.","contributorId":102363,"corporation":false,"usgs":true,"family":"Fohey-Breting","given":"Nicole","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":481161,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Vazquez, Jorge A. 0000-0003-2754-0456 jvazquez@usgs.gov","orcid":"https://orcid.org/0000-0003-2754-0456","contributorId":4458,"corporation":false,"usgs":true,"family":"Vazquez","given":"Jorge","email":"jvazquez@usgs.gov","middleInitial":"A.","affiliations":[{"id":5056,"text":"Office of the AD Energy and Minerals, and Environmental Health","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":501,"text":"Office of Science Quality and Integrity","active":true,"usgs":true}],"preferred":true,"id":481157,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Priest, Susan S. spriest@usgs.gov","contributorId":30204,"corporation":false,"usgs":true,"family":"Priest","given":"Susan","email":"spriest@usgs.gov","middleInitial":"S.","affiliations":[],"preferred":false,"id":481158,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70047141,"text":"ds775 - 2013 - High-water marks from tropical storm Irene for selected river reaches in northwestern Massachusetts, August 2011","interactions":[],"lastModifiedDate":"2013-07-22T14:32:20","indexId":"ds775","displayToPublicDate":"2013-07-22T14:10:00","publicationYear":"2013","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":"775","title":"High-water marks from tropical storm Irene for selected river reaches in northwestern Massachusetts, August 2011","docAbstract":"A Presidential Disaster Declaration was issued for Massachusetts, with a focus on the northwestern counties, following flooding from tropical storm Irene on August 28–29, 2011. Three to 10 inches of rain fell during the storm on soils that were susceptible to flash flooding because of wet antecedent conditions. The gage height at one U.S. Geological Survey (USGS) streamgage rose nearly 20 feet in less than 4 hours because of the combination of saturated soils and intense rainfall. Eight of 16 USGS long-term streamgages in western Massachusetts set new peaks of record on August 28 or 29, 2011. To document the historic water levels of the streamflows from tropical storm Irene, the USGS identified, flagged, and surveyed 323 high-water marks in the Deerfield and Hudson- Hoosic River basins in northwestern Massachusetts. Areas targeted for high-water marks were generally upstream and downstream from structures along selected river reaches. Elevations from high-water marks can be used to confirm peak river stages or help compute peak streamflows, to calibrate hydraulic models, or to update flood-inundation and recovery maps. For areas in western Massachusetts that flooded as a result of tropical storm Irene, high-water marks surveyed for this study have helped to confirm or determine instantaneous peak river gage heights at several USGS streamgages.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds775","collaboration":"Prepared in cooperation with the Federal Emergency Management Agency","usgsCitation":"Bent, G.C., Medalie, L., and Nielsen, M.G., 2013, High-water marks from tropical storm Irene for selected river reaches in northwestern Massachusetts, August 2011: U.S. Geological Survey Data Series 775, Report: iv, 13 p.; Appendix 1: XLS file; Appendix 2: KMZ file, https://doi.org/10.3133/ds775.","productDescription":"Report: iv, 13 p.; Appendix 1: XLS file; Appendix 2: KMZ file","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":275237,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds775.jpg"},{"id":275234,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/775/"},{"id":275235,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/775/appendix/USGS_Data_Series_775_Appendix_1.xlsx"},{"id":275236,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/775/appendix/USGS_Data_Series_775_Appendix_2_HWMs.kmz"},{"id":275233,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/775/pdf/ds775_report_508.pdf"}],"country":"United States","state":"Massachusetts","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -73.493042,42.012571 ], [ -73.493042,42.710696 ], [ -72.463074,42.710696 ], [ -72.463074,42.012571 ], [ -73.493042,42.012571 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51ee4655e4b00ffbed48f84d","contributors":{"authors":[{"text":"Bent, Gardner C. 0000-0002-5085-3146 gbent@usgs.gov","orcid":"https://orcid.org/0000-0002-5085-3146","contributorId":1864,"corporation":false,"usgs":true,"family":"Bent","given":"Gardner","email":"gbent@usgs.gov","middleInitial":"C.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":481153,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Medalie, Laura 0000-0002-2440-2149 lmedalie@usgs.gov","orcid":"https://orcid.org/0000-0002-2440-2149","contributorId":3657,"corporation":false,"usgs":true,"family":"Medalie","given":"Laura","email":"lmedalie@usgs.gov","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":481154,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nielsen, Martha G. 0000-0003-3038-9400 mnielsen@usgs.gov","orcid":"https://orcid.org/0000-0003-3038-9400","contributorId":4169,"corporation":false,"usgs":true,"family":"Nielsen","given":"Martha","email":"mnielsen@usgs.gov","middleInitial":"G.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":481155,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70046965,"text":"70046965 - 2013 - Relating Yellow Rail (Coturnicops noveboracensis) occupancy to habitat and landscape features in the context of fire","interactions":[],"lastModifiedDate":"2017-09-08T09:12:23","indexId":"70046965","displayToPublicDate":"2013-07-22T13:44:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3731,"text":"Waterbirds","onlineIssn":"19385390","printIssn":"15244695","active":true,"publicationSubtype":{"id":10}},"title":"Relating Yellow Rail (Coturnicops noveboracensis) occupancy to habitat and landscape features in the context of fire","docAbstract":"The Yellow Rail (Coturnicops noveboracensis) is a focal species of concern associated with shallowly flooded emergent wetlands, most commonly sedge (Carex spp.) meadows. Their populations are believed to be limited by loss or degradation of wetland habitat due to drainage, altered hydrology, and fire suppression, factors that have often resulted in encroachment of shrubs into sedge meadows and change in vegetative cover. Nocturnal call-playback surveys for Yellow Rails were conducted over 3 years at Seney National Wildlife Refuge in the Upper Peninsula of Michigan. Effects of habitat structure and landscape variables on the probability of use by Yellow Rails were assessed at two scales, representing a range of home range sizes, using generalized linear mixed models. At the 163-m (8-ha) scale, year with quadratic models of maximum and mean water depths best explained the data. At the 300-m (28-ha) scale, the best model contained year and time since last fire (≤ 1, 2–5, and > 10 years). The probability of use by Yellow Rails was 0.285 ± 0.132 (SE) for points burned 2-5 years ago, 0.253 ± 0.097 for points burned ≤ 1 year ago, and 0.028 ± 0.019 for points burned > 10 years ago. Habitat differences relative to fire history and comparisons between sites with and without Yellow Rails indicated that Yellow Rails used areas with the deepest litter and highest ground cover, and relatively low shrub cover and heights, as well as landscapes having greater sedge-grass cover and less lowland woody or upland cover types. Burning every 2-5 years appears to provide the litter, ground-level cover, and woody conditions attractive to Yellow Rails. Managers seeking to restore and sustain these wetland systems would benefit from further investigations into how flooding and fire create habitat conditions attractive to breeding Yellow Rails","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Waterbirds","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"The Waterbird Society","doi":"10.1675/063.036.0209","usgsCitation":"Austin, J., and Buhl, D., 2013, Relating Yellow Rail (Coturnicops noveboracensis) occupancy to habitat and landscape features in the context of fire: Waterbirds, v. 36, no. 2, p. 199-213, https://doi.org/10.1675/063.036.0209.","productDescription":"15 p.","startPage":"199","endPage":"213","ipdsId":"IP-039078","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":473663,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1675/063.036.0209","text":"Publisher Index Page"},{"id":275190,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":274839,"type":{"id":15,"text":"Index Page"},"url":"https://www.bioone.org/doi/pdf/10.1675/063.036.0209"},{"id":275184,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1675/063.036.0209"}],"country":"United States","state":"Michigan","otherGeospatial":"Seney National Wildlife Refuge","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -86.27,46.16 ], [ -86.27,46.77 ], [ -84.95,46.77 ], [ -84.95,46.16 ], [ -86.27,46.16 ] ] ] } } ] }","volume":"36","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51ee465be4b00ffbed48f875","contributors":{"authors":[{"text":"Austin, Jane E.","contributorId":43094,"corporation":false,"usgs":true,"family":"Austin","given":"Jane E.","affiliations":[],"preferred":false,"id":480725,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Buhl, Deborah A. 0000-0002-8563-5990","orcid":"https://orcid.org/0000-0002-8563-5990","contributorId":26250,"corporation":false,"usgs":true,"family":"Buhl","given":"Deborah A.","affiliations":[],"preferred":false,"id":480724,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70046801,"text":"70046801 - 2013 - Predicting breeding shorebird distributions on the Arctic Coastal Plain of Alaska","interactions":[],"lastModifiedDate":"2017-11-22T10:19:51","indexId":"70046801","displayToPublicDate":"2013-07-22T13:22:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Predicting breeding shorebird distributions on the Arctic Coastal Plain of Alaska","docAbstract":"The Arctic Coastal Plain (ACP) of Alaska is an important region for millions of migrating and nesting shorebirds. However, this region is threatened by climate change and increased human development (e.g., oil and gas production) that have the potential to greatly impact shorebird populations and breeding habitat in the near future. Because historic data on shorebird distributions in the ACP are very coarse and incomplete, we sought to develop detailed, contemporary distribution maps so that the potential impacts of climate-mediated changes and development could be ascertained. To do this, we developed and mapped habitat suitability indices for eight species of shorebirds (Black-bellied Plover [Pluvialis squatarola], American Golden-Plover [Pluvialis dominica], Semipalmated Sandpiper [Calidris pusilla], Pectoral Sandpiper [Calidris melanotos], Dunlin [Calidris alpina], Long-billed Dowitcher [Limnodromus scolopaceus], Red-necked Phalarope [Phalaropus lobatus], and Red Phalarope [Phalaropus fulicarius]) that commonly breed within the ACP of Alaska. These habitat suitability models were based on 767 plots surveyed during nine years between 1998 and 2008 (surveys were not conducted in 2003 and 2005), using single-visit rapid area searches during territory establishment and incubation (8 June, 1 July). Species specific habitat suitability indices were developed and mapped using presence-only modeling techniques (partitioned Mahalanobis distance) and landscape environmental variables. For most species, habitat suitability was greater at lower elevations (i.e., near the coast and river deltas) and lower within upland habitats. Accuracy of models was high for all species, ranging from 65 -98%. Our models predicted that the largest fraction of suitable habitat for the majority of species occurred within the National Petroleum Reserve-Alaska, with highly suitable habitat also occurring within coastal areas of the Arctic National Wildlife Refuge west to Prudhoe Bay.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ecosphere","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Ecological Society of America","doi":"10.1890/ES12-00292.1","usgsCitation":"Saalfeld, S., Lanctot, R.B., Brown, S.C., Saalfeld, D.T., Johnson, J., Andres, B.A., and Bart, J.R., 2013, Predicting breeding shorebird distributions on the Arctic Coastal Plain of Alaska: Ecosphere, v. 4, no. 1, 17 p., https://doi.org/10.1890/ES12-00292.1.","productDescription":"17 p.","numberOfPages":"17","ipdsId":"IP-043081","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":473664,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1890/es12-00292.1","text":"Publisher Index Page"},{"id":275229,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":274693,"type":{"id":15,"text":"Index Page"},"url":"https://www.esajournals.org/doi/pdf/10.1890/ES12-00292.1"},{"id":275228,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1890/ES12-00292.1"}],"country":"United States","state":"Alaska","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -160.29,69.08 ], [ -160.29,71.41 ], [ -142.34,71.41 ], [ -142.34,69.08 ], [ -160.29,69.08 ] ] ] } } ] }","volume":"4","issue":"1","noUsgsAuthors":false,"publicationDate":"2013-01-31","publicationStatus":"PW","scienceBaseUri":"51ee465ae4b00ffbed48f86d","contributors":{"authors":[{"text":"Saalfeld, Sarah T.","contributorId":41721,"corporation":false,"usgs":true,"family":"Saalfeld","given":"Sarah T.","affiliations":[],"preferred":false,"id":480298,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lanctot, Richard B.","contributorId":31894,"corporation":false,"usgs":true,"family":"Lanctot","given":"Richard","email":"","middleInitial":"B.","affiliations":[{"id":135,"text":"Biological Resources Division","active":false,"usgs":true},{"id":7029,"text":"Queen's University, Kingston, Ontario, Canada","active":true,"usgs":false},{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false},{"id":17786,"text":"Carleton University","active":true,"usgs":false}],"preferred":false,"id":480296,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brown, Stephen C.","contributorId":38457,"corporation":false,"usgs":false,"family":"Brown","given":"Stephen","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":480297,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Saalfeld, David T.","contributorId":49685,"corporation":false,"usgs":true,"family":"Saalfeld","given":"David","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":480299,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Johnson, James A.","contributorId":84649,"corporation":false,"usgs":true,"family":"Johnson","given":"James A.","affiliations":[],"preferred":false,"id":480302,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Andres, Brad A.","contributorId":68811,"corporation":false,"usgs":true,"family":"Andres","given":"Brad","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":480300,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bart, Jonathan R.","contributorId":74273,"corporation":false,"usgs":true,"family":"Bart","given":"Jonathan","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":480301,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70045973,"text":"70045973 - 2013 - Predicting locations of rare aquatic species’ habitat with a combination of species-specific and assemblage-based models","interactions":[],"lastModifiedDate":"2013-07-22T11:47:36","indexId":"70045973","displayToPublicDate":"2013-07-22T11:34:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1399,"text":"Diversity and Distributions","active":true,"publicationSubtype":{"id":10}},"title":"Predicting locations of rare aquatic species’ habitat with a combination of species-specific and assemblage-based models","docAbstract":"Aim: Rare aquatic species are a substantial component of biodiversity, and their conservation is a major objective of many management plans. However, they are difficult to assess, and their optimal habitats are often poorly known. Methods to effectively predict the likely locations of suitable rare aquatic species habitats are needed. We combine two modelling approaches to predict occurrence and general abundance of several rare fish species. Location: Allegheny watershed of western New York State (USA) Methods: Our method used two empirical neural network modelling approaches (species specific and assemblage based) to predict stream-by-stream occurrence and general abundance of rare darters, based on broad-scale habitat conditions. Species-specific models were developed for longhead darter (Percina macrocephala), spotted darter (Etheostoma maculatum) and variegate darter (Etheostoma variatum) in the Allegheny drainage. An additional model predicted the type of rare darter-containing assemblage expected in each stream reach. Predictions from both models were then combined inclusively and exclusively and compared with additional independent data. Results Example rare darter predictions demonstrate the method's effectiveness. Models performed well (R2 ≥ 0.79), identified where suitable darter habitat was most likely to occur, and predictions matched well to those of collection sites. Additional independent data showed that the most conservative (exclusive) model slightly underestimated the distributions of these rare darters or predictions were displaced by one stream reach, suggesting that new darter habitat types were detected in the later collections. Main conclusions Broad-scale habitat variables can be used to effectively identify rare species' habitats. Combining species-specific and assemblage-based models enhances our ability to make use of the sparse data on rare species and to identify habitat units most likely and least likely to support those species. This hybrid approach may assist managers with the prioritization of habitats to be examined or conserved for rare species.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Diversity and Distributions","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1111/ddi.12059","usgsCitation":"McKenna, J., Carlson, D.M., and Payne-Wynne, M.L., 2013, Predicting locations of rare aquatic species’ habitat with a combination of species-specific and assemblage-based models: Diversity and Distributions, v. 19, no. 5-6, p. 503-517, https://doi.org/10.1111/ddi.12059.","productDescription":"15 p.","startPage":"503","endPage":"517","numberOfPages":"15","ipdsId":"IP-039413","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":473665,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ddi.12059","text":"Publisher Index Page"},{"id":275216,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":275215,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/ddi.12059"}],"country":"United States","state":"New York","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -79.881592,41.459195 ], [ -79.881592,42.228517 ], [ -78.222656,42.228517 ], [ -78.222656,41.459195 ], [ -79.881592,41.459195 ] ] ] } } ] }","volume":"19","issue":"5-6","noUsgsAuthors":false,"publicationDate":"2013-05-06","publicationStatus":"PW","scienceBaseUri":"51ee465be4b00ffbed48f871","contributors":{"authors":[{"text":"McKenna, James E.","contributorId":9217,"corporation":false,"usgs":true,"family":"McKenna","given":"James E.","affiliations":[],"preferred":false,"id":478619,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carlson, Douglas M.","contributorId":91001,"corporation":false,"usgs":false,"family":"Carlson","given":"Douglas","email":"","middleInitial":"M.","affiliations":[{"id":13678,"text":"New York State Department of Environmental Conservation","active":true,"usgs":false}],"preferred":false,"id":478621,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Payne-Wynne, Molly L.","contributorId":33604,"corporation":false,"usgs":true,"family":"Payne-Wynne","given":"Molly","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":478620,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ]}