{"pageNumber":"551","pageRowStart":"13750","pageSize":"25","recordCount":40783,"records":[{"id":70141451,"text":"sir20155029 - 2015 - Detailed interpretation of aeromagnetic data from the Patagonia Mountains area, southeastern Arizona","interactions":[],"lastModifiedDate":"2015-03-24T09:15:44","indexId":"sir20155029","displayToPublicDate":"2015-03-24T10:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-5029","title":"Detailed interpretation of aeromagnetic data from the Patagonia Mountains area, southeastern Arizona","docAbstract":"<p>The induced magnetic field and the remanent magnetic field of rock masses are important to geologic modeling based on Earth&rsquo;s magnetic field data. The orientation of the induced magnetic field is approximately parallel to the orientation of Earth&rsquo;s geomagnetic field and its intensity can be derived from measured magnetic susceptibilities of rocks in a study area. The orientation and intensity of the natural remanent magnetic field is much harder to determine; therefore, few investigators have included magnetic remanence as a contributing factor to studies of continental magnetic anomalies. All rocks have remanent magnetism and, in intrusive or volcanic rocks, this component of the total magnetic intensity of the Earth&rsquo;s magnetic field can be as large as or larger than the induced component.</p>\n<p>The Patagonia Mountains in southeastern Arizona were selected to produce a subsurface geologic model from aeromagnetic data by incorporating physical properties of rock including measured magnetic susceptibilities, estimated remanent magnetic field orientations and intensities, a known association of intrusive events, and information from existing geologic mapping. The result is a model of geology at depth that may better represent reality than previous poorly substantiated cross sectional models. This new model includes concealed intrusive rocks and defines areas where concealed mineral deposits may be found. It also shows that volcanic rocks might occupy basins at relatively shallow depths in basins with low aeromagnetic anomalies.</p>\n<p>Euler deconvolution depth estimates derived from aeromagnetic data with a structural index of 0 show that mapped faults on the northern margin of the Patagonia Mountains generally agree with the depth estimates in the new geologic model. The deconvolution depth estimates also show that the concealed Patagonia Fault southwest of the Patagonia Mountains is more complex than recent geologic mapping represents. Additionally, Euler deconvolution depth estimates with a structural index of 2 locate many potential intrusive bodies that might be associated with known and unknown mineralization.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155029","usgsCitation":"Bultman, M.W., 2015, Detailed interpretation of aeromagnetic data from the Patagonia Mountains area, southeastern Arizona: U.S. Geological Survey Scientific Investigations Report 2015-5029, iv, 25 p., https://doi.org/10.3133/sir20155029.","productDescription":"iv, 25 p.","numberOfPages":"34","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-046013","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":298881,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2015/5029/"},{"id":298886,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5029/pdf/sir2015-5029.pdf","size":"2.7 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":298888,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20155029.jpg"}],"projection":"United States Continuous Albers Equal Area Conic project USGS version","country":"United States","state":"Arizona","otherGeospatial":"Patagonia Mountains","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -110.82321166992188,\n              31.33252503230784\n            ],\n            [\n              -110.82321166992188,\n              31.577365480690492\n            ],\n            [\n              -110.6378173828125,\n              31.577365480690492\n            ],\n            [\n              -110.6378173828125,\n              31.33252503230784\n            ],\n            [\n              -110.82321166992188,\n              31.33252503230784\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55127ca5e4b02e76d75bd5e3","contributors":{"authors":[{"text":"Bultman, Mark W. 0000-0001-8352-101X mbultman@usgs.gov","orcid":"https://orcid.org/0000-0001-8352-101X","contributorId":3348,"corporation":false,"usgs":true,"family":"Bultman","given":"Mark","email":"mbultman@usgs.gov","middleInitial":"W.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":false,"id":543101,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70143873,"text":"70143873 - 2015 - Wide-area ratios of evapotranspiration to precipitation in monsoon-dependent semiarid vegetation communities","interactions":[],"lastModifiedDate":"2015-03-23T15:09:50","indexId":"70143873","displayToPublicDate":"2015-03-23T14:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2183,"text":"Journal of Arid Environments","active":true,"publicationSubtype":{"id":10}},"title":"Wide-area ratios of evapotranspiration to precipitation in monsoon-dependent semiarid vegetation communities","docAbstract":"<p><span>Evapotranspiration (ET) and the ratio of ET to precipitation (PPT) are important factors in the water budget of semiarid rangelands and are in part determined by the dominant plant communities. Our goal was to see if landscape changes such as tree or shrub encroachment and replacement of native grasses by invasive grasses impacted ET and ET/PPT and therefore watershed hydrology in this biome. We determined ET and ET/PPT for shrublands, grasslands and mesquite savannas in southern Arizona at five moisture flux towers and determined the environmental factors controlling ET in each plant community. We then scaled ET over areas of 4&ndash;36&nbsp;km</span><sup>2</sup><span>, representing homogeneous patches of each plant community, using the Enhanced Vegetation Index (EVI) from MODIS sensors on the Terra satellite. Over wide areas, estimated ET/PPT projected from MODIS EVI ranged from 0.71 for a sparsely-vegetated shrub site to 1.00 for grasslands and mesquite savannas. The results did not support hypotheses that encroachment of mesquites into grasslands or that replacement of native grasses with introduced<span class=\"Apple-converted-space\">&nbsp;</span></span><i>Eragrostis lehmanniana</i><span><span class=\"Apple-converted-space\">&nbsp;</span>(lehmann lovegrass) have increased rangeland ET.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jaridenv.2015.02.010","usgsCitation":"Glenn, E., Scott, R.L., Nguyen, U., and Nagler, P.L., 2015, Wide-area ratios of evapotranspiration to precipitation in monsoon-dependent semiarid vegetation communities: Journal of Arid Environments, v. 117, p. 84-95, https://doi.org/10.1016/j.jaridenv.2015.02.010.","productDescription":"12 p.","startPage":"84","endPage":"95","numberOfPages":"12","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057910","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":298879,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -111.05804443359375,\n              31.59959193922864\n            ],\n            [\n              -111.05804443359375,\n              31.961483557268558\n            ],\n            [\n              -109.71221923828125,\n              31.961483557268558\n            ],\n            [\n              -109.71221923828125,\n              31.59959193922864\n            ],\n            [\n              -111.05804443359375,\n              31.59959193922864\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"117","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55112b21e4b02e76d75b50bc","contributors":{"authors":[{"text":"Glenn, Edward P.","contributorId":56542,"corporation":false,"usgs":false,"family":"Glenn","given":"Edward P.","affiliations":[{"id":13060,"text":"Department of Soil, Water and Environmental Science, University of Arizona","active":true,"usgs":false}],"preferred":false,"id":543095,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Scott, Russell L.","contributorId":39875,"corporation":false,"usgs":false,"family":"Scott","given":"Russell","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":543096,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nguyen, Uyen","contributorId":71863,"corporation":false,"usgs":false,"family":"Nguyen","given":"Uyen","email":"","affiliations":[{"id":13060,"text":"Department of Soil, Water and Environmental Science, University of Arizona","active":true,"usgs":false}],"preferred":false,"id":543097,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nagler, Pamela L. 0000-0003-0674-103X pnagler@usgs.gov","orcid":"https://orcid.org/0000-0003-0674-103X","contributorId":1398,"corporation":false,"usgs":true,"family":"Nagler","given":"Pamela","email":"pnagler@usgs.gov","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":543098,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70147867,"text":"70147867 - 2015 - Recovery of a mining-damaged stream ecosystem","interactions":[],"lastModifiedDate":"2015-09-14T11:43:45","indexId":"70147867","displayToPublicDate":"2015-03-23T12:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3888,"text":"Elementa: Science of the Anthropocene","active":true,"publicationSubtype":{"id":10}},"title":"Recovery of a mining-damaged stream ecosystem","docAbstract":"<p>This paper presents a 30+ year record of changes in benthic macroinvertebrate communities and fish populations associated with improving water quality in mining-influenced streams. Panther Creek, a tributary to the Salmon River in central Idaho, USA suffered intensive damage from mining and milling operations at the Blackbird Mine that released copper (Cu), arsenic (As), and cobalt (Co) into tributaries. From the 1960s through the 1980s, no fish and few aquatic invertebrates could be found in 40 km of mine-affected reaches of Panther Creek downstream of the metals contaminated tributaries, Blackbird and Big Deer Creeks.</p>\n<p>Efforts to restore water quality began in 1995, and by 2002 Cu levels had been reduced by about 90%, with incremental declines since. Rainbow Trout (<i>Oncorhynchus mykiss</i>) were early colonizers, quickly expanding their range as areas became habitable when Cu concentrations dropped below about 3X the U.S. Environmental Protection Agency's biotic ligand model (BLM) based chronic aquatic life criterion. Anadromous Chinook Salmon (<i>O. tshawytscha</i>) and steelhead (<i>O. mykiss</i>) have also reoccupied Panther Creek. Full recovery of salmonid populations occurred within about 12-years after the onset of restoration efforts and about 4-years after the Cu chronic criteria had mostly been met, with recovery interpreted as similarity in densities, biomass, year class strength, and condition factors between reference sites and mining-influenced sites. Shorthead Sculpin (<i>Cottus confusus</i>) were slower than salmonids to disperse and colonize. While benthic macroinvertebrate biomass has increased, species richness has plateaued at about 70 to 90% of reference despite the Cu criterion having been met for several years. Different invertebrate taxa had distinctly different recovery trajectories. Among the slowest taxa to recover were <i>Ephemerella</i>, <i>Cinygmula</i> and <i>Rhithrogena</i> mayflies, <i>Enchytraeidae oligochaetes</i>, and <i>Heterlimnius</i> aquatic beetles. Potential reasons for the failure of some invertebrate taxa to recover include competition, and high sensitivity to Co and Cu.</p>","language":"English","publisher":"Harwood Academic","publisherLocation":"Yverdon, Switzerland","doi":"10.12952/journal.elementa.000042","collaboration":"Rio Tinto","usgsCitation":"Mebane, C.A., Eakins, R.J., Fraser, B.G., and Adams, W.J., 2015, Recovery of a mining-damaged stream ecosystem: Elementa: Science of the Anthropocene, v. 3, p. 1-34, https://doi.org/10.12952/journal.elementa.000042.","productDescription":"34 p.","startPage":"1","endPage":"34","numberOfPages":"34","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-042317","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":472203,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.12952/journal.elementa.000042","text":"Publisher Index Page"},{"id":308101,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"Panther Creek","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -114.74395751953125,\n              44.72917434046452\n            ],\n            [\n              -114.74395751953125,\n              45.04053733158769\n            ],\n            [\n              -114.2633056640625,\n              45.04053733158769\n            ],\n            [\n              -114.2633056640625,\n              44.72917434046452\n            ],\n            [\n              -114.74395751953125,\n              44.72917434046452\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"3","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-03-23","publicationStatus":"PW","scienceBaseUri":"55f7efc4e4b05d6c4e4fa997","contributors":{"authors":[{"text":"Mebane, Christopher A. 0000-0002-9089-0267 cmebane@usgs.gov","orcid":"https://orcid.org/0000-0002-9089-0267","contributorId":110,"corporation":false,"usgs":true,"family":"Mebane","given":"Christopher","email":"cmebane@usgs.gov","middleInitial":"A.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":546349,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Eakins, Robert J.","contributorId":140637,"corporation":false,"usgs":false,"family":"Eakins","given":"Robert","email":"","middleInitial":"J.","affiliations":[{"id":13541,"text":"EcoMetrix Ltd, Brampton, ON Canada","active":true,"usgs":false}],"preferred":false,"id":546351,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fraser, Brian G.","contributorId":140636,"corporation":false,"usgs":false,"family":"Fraser","given":"Brian","email":"","middleInitial":"G.","affiliations":[{"id":13541,"text":"EcoMetrix Ltd, Brampton, ON Canada","active":true,"usgs":false}],"preferred":false,"id":546350,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Adams, William J.","contributorId":140638,"corporation":false,"usgs":false,"family":"Adams","given":"William","email":"","middleInitial":"J.","affiliations":[{"id":13542,"text":"Rio Tinto, Lake Point, UT","active":true,"usgs":false}],"preferred":false,"id":546352,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70142445,"text":"fs20153017 - 2015 - The 3D Elevation Program: summary for West Virginia","interactions":[],"lastModifiedDate":"2016-08-17T15:04:48","indexId":"fs20153017","displayToPublicDate":"2015-03-23T10:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-3017","title":"The 3D Elevation Program: summary for West Virginia","docAbstract":"<p>Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, national security, recreation, and many others. For the State of West Virginia, elevation data are critical for natural resources conservation, flood risk management, forest resources management, infrastructure and construction management, agriculture and precision farming, and other business uses. Today, high-density light detection and ranging (lidar) data are the primary sources for deriving elevation models and other datasets. Federal, State, Tribal, and local agencies work in partnership to (1) replace data that are older and of lower quality and (2) provide coverage where publicly accessible data do not exist. A joint goal of State and Federal partners is to acquire consistent, statewide coverage to support existing and emerging applications enabled by lidar data.</p>\n<p>The National Enhanced Elevation Assessment evaluated multiple elevation data acquisition options to determine the optimal data quality and data replacement cycle relative to cost to meet the identified requirements of the user community. The evaluation demonstrated that lidar acquisition at quality level 2 for the conterminous United States and quality level 5 interferometric synthetic aperture radar (ifsar) data for Alaska with a 6- to 10-year acquisition cycle provided the highest benefit/cost ratios. The 3D Elevation Program (3DEP) initiative selected an 8-year acquisition cycle for the respective quality levels. 3DEP, managed by the U.S. Geological Survey, the Office of Management and Budget Circular A&ndash;16 lead agency for terrestrial elevation data, responds to the growing need for high-quality topographic data and a wide range of other 3D representations of the Nation&rsquo;s natural and constructed features.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20153017","usgsCitation":"Carswell, W., 2015, The 3D Elevation Program: summary for West Virginia (Version 1.0: Originally posted March 23, 2015; Version: 1.1: June 25, 2015): U.S. Geological Survey Fact Sheet 2015-3017, 2 p., https://doi.org/10.3133/fs20153017.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-059937","costCenters":[{"id":423,"text":"National Geospatial 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Jr. carswell@usgs.gov","contributorId":127609,"corporation":false,"usgs":true,"family":"Carswell","given":"William J.","suffix":"Jr.","email":"carswell@usgs.gov","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":false,"id":541905,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70160539,"text":"70160539 - 2015 - Book review: Analysis of capture–recapture data","interactions":[],"lastModifiedDate":"2017-06-27T14:24:00","indexId":"70160539","displayToPublicDate":"2015-03-21T01:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2151,"text":"Journal of Agricultural, Biological, and Environmental Statistics","active":true,"publicationSubtype":{"id":10}},"title":"Book review: Analysis of capture–recapture data","docAbstract":"<p class=\"p1\"><span class=\"s1\"><i>Analysis of Capture&ndash;Recapture Data</i> by McCrea and Morgan is an excellent, easy to read monograph about capture&ndash;recapture models. In this book, the authors provide a concise overview of traditional closed population capture&ndash;recapture models (Models M0, Mb, Mh, etc.), individual covariate models, and open population models such as the Cormack&ndash;Jolly&ndash;Seber, Jolly&ndash;Seber models, multi-state models, and more recent developments such as occupancy models, state-space models, and integrated population models. The authors write &ldquo;In this book we aim to cover the many modern developments in the area of capture&ndash;recapture and related models, and to set them in historical context of relevant research over the past 100 years.&rdquo; The book does a good job of achieving this objective. And it is a very easy to read because it is well organized and the writing is clear and concise. I would recommend this book as a reference for the quantitative ecologist or statistician interested in knowing what&rsquo;s out there.</span></p>\n<p class=\"p1\"><span class=\"s1\">Review info:&nbsp;</span><i>Analysis of Capture&ndash;Recapture Data.</i> By&nbsp;Rachel S. McCrea and Byron J. T. Morgan, 2015. ISBN: 978-14398-6590,&nbsp;&nbsp;xx+292 pp.</p>\n<p class=\"p1\"><i></i>&nbsp;</p>","language":"English","publisher":"American Statistical Association : International Biometric Society","publisherLocation":"Alexandria, VA","doi":"10.1007/s13253-015-0202-9","usgsCitation":"Royle, A., 2015, Book review: Analysis of capture–recapture data: Journal of Agricultural, Biological, and Environmental Statistics, v. 20, no. 3, p. 431-432, https://doi.org/10.1007/s13253-015-0202-9.","productDescription":"2 p.","startPage":"431","endPage":"432","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064018","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":312933,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"20","issue":"3","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2015-03-21","publicationStatus":"PW","scienceBaseUri":"56826b3ce4b0a04ef4925b27","contributors":{"authors":[{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":146229,"corporation":false,"usgs":true,"family":"Royle","given":"J. Andrew","email":"aroyle@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":583084,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70135764,"text":"sir20145228 - 2015 - Geophysical log analysis of selected test and residential wells at the Shenandoah Road National Superfund Site, East Fishkill, Dutchess County, New York","interactions":[],"lastModifiedDate":"2015-03-20T09:35:52","indexId":"sir20145228","displayToPublicDate":"2015-03-20T10:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-5228","title":"Geophysical log analysis of selected test and residential wells at the Shenandoah Road National Superfund Site, East Fishkill, Dutchess County, New York","docAbstract":"<p>The U.S. Geological Survey collected and analyzed geophysical logs from 20 test wells and 23 residential wells at the Shenandoah Road National Superfund Site in East Fishkill, New York, from 2006 through 2010 as part of an Interagency Agreement to provide hydrogeologic technical support to the U.S. Environmental Protection Agency, Region 2. The geophysical logs collected include caliper, gamma, acoustic and optical televiewer, deviation, electromagnetic-induction, magnetic-susceptibility, fluid-property, and flow under ambient and pumped conditions. The geophysical logs were analyzed along with single-well aquifer test data and drilling logs to characterize the lithology, fabric, fractures, and flow zones penetrated by the wells. The results of the geophysical log analysis were used as part of the hydrogeologic characterization of the site and in the design of discrete-zone monitoring installations in the test wells and selected residential wells.</p>\n<p>Most of the logged test and residential wells penetrated gneiss of the Hudson Highlands Complex or dolostones in the Wappinger Group, and some wells penetrated both the dolostone and gneiss. The bedrock fabric reflects the regional northeast-southwest structural trend, as well as localized folding, and includes foliation in the gneiss and bedding in the dolostone. Many fractures were oriented along the bedrock fabric, whereas others were orthogonal to the fabric.</p>\n<p>Total wellbore transmissivity of the wells was estimated from short-term, single-well aquifer test data through the use of the Cooper-Jacob analytical solution. An empirical relation was established to estimate total wellbore transmissivity from specific-capacity data for wells with insufficient transient drawdown measurements. Wellbore transmissivity estimates ranged from 0.36 to 370 feet squared per day (ft<sup>2</sup>/d), whereas specific capacities ranged from 0.03 to 2.1 gallons per minute per foot ((gal/min)/ft).</p>\n<p>Transmissivity and hydraulic heads of individual fracture zones were estimated from the total wellbore transmissivity and flow logs through use of an analytical model based on the Thiem equation. The model-estimated transmissivity of 95 fracture zones delineated in the 43 wells ranged from 0.25 to 340 ft<sup>2</sup>/d, with a median value of 6.7 ft<sup>2</sup>/d. The difference between model-estimated fracture-zone heads and the composite heads in each well ranged from less 0.01 to more than 10 feet (ft). Flow-log analysis generally provided an order of magnitude estimate for the fracture-zone hydraulic-head difference on the basis of a comparison of estimated and measured values.</p>\n<p>The geophysical logs and their analyses are available for display and download from the U.S. Geological Survey, New York Water Science Center, online geophysical log archive (<a href=\"http://ny.water.usgs.gov/maps/geologs/\">http://ny.water.usgs.gov/maps/geologs/</a>) in LAS (Log ASCII Standard), PDF, and WellCad formats.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145228","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency","usgsCitation":"Reynolds, R.J., Anderson, J.A., and Williams, J., 2015, Geophysical log analysis of selected test and residential wells at the Shenandoah Road National Superfund Site, East Fishkill, Dutchess County, New York: U.S. Geological Survey Scientific Investigations Report 2014-5228, Report: viii, 30 p.; Geophysical Log Archive; WellCad reader download, https://doi.org/10.3133/sir20145228.","productDescription":"Report: viii, 30 p.; Geophysical Log Archive; WellCad reader download","numberOfPages":"42","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-042201","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":298827,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145228.jpg"},{"id":298824,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5228/pdf/sir2014-5228.pdf","size":"2.38 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":298825,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://ny.water.usgs.gov/maps/geologs/","text":"Geophysical Log Archive","linkHelpText":"The USGS New York Water Science Center has developed an online geophysical log archive where the logs and log analysis of the Shenandoah Road Superfund site wells, as well as many others throughout the State, can be viewed or downloaded."},{"id":298823,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5228/"},{"id":298826,"rank":4,"type":{"id":7,"text":"Companion Files"},"url":"https://www.alt.lu/downloads.htm","text":"WellCad reader download","linkHelpText":"The locations of the Shenandoah Road National Superfund Site wells are shown on the index map. The user can zoom-in to the well cluster located just east of Fishkill, N.Y., to expand the view of the wells logged.  Clicking on an individual well will bring up a menu of the available log formats, which are LAS, PDF, and WellCad Reader. WellCad Reader is available online free of charge."}],"scale":"24000","country":"United States","state":"New York","county":"Dutchess County","city":"East Fishkill","otherGeospatial":"Shenandoah Road National Superfund Site","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -73.80074501037598,\n              41.5186034007529\n            ],\n            [\n              -73.80074501037598,\n              41.545075129729334\n            ],\n            [\n              -73.7743091583252,\n              41.545075129729334\n            ],\n            [\n              -73.7743091583252,\n              41.5186034007529\n            ],\n            [\n              -73.80074501037598,\n              41.5186034007529\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"550d369be4b02e76d759d867","contributors":{"authors":[{"text":"Reynolds, Richard J. 0000-0001-5032-6613 rjreynol@usgs.gov","orcid":"https://orcid.org/0000-0001-5032-6613","contributorId":1082,"corporation":false,"usgs":true,"family":"Reynolds","given":"Richard","email":"rjreynol@usgs.gov","middleInitial":"J.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":536842,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, J. Alton aanders@usgs.gov","contributorId":1602,"corporation":false,"usgs":true,"family":"Anderson","given":"J.","email":"aanders@usgs.gov","middleInitial":"Alton","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":false,"id":536840,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Williams, John 0000-0002-6054-6908 jhwillia@usgs.gov","orcid":"https://orcid.org/0000-0002-6054-6908","contributorId":1553,"corporation":false,"usgs":true,"family":"Williams","given":"John","email":"jhwillia@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":536841,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70146538,"text":"70146538 - 2015 - Chemical variations in Yellowknife Bay formation sedimentary rocks analyzed by ChemCam on board the Curiosity rover on Mars","interactions":[],"lastModifiedDate":"2015-04-22T15:29:41","indexId":"70146538","displayToPublicDate":"2015-03-19T11:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2317,"text":"Journal of Geophysical Research E: Planets","active":true,"publicationSubtype":{"id":10}},"title":"Chemical variations in Yellowknife Bay formation sedimentary rocks analyzed by ChemCam on board the Curiosity rover on Mars","docAbstract":"<p>The Yellowknife Bay formation represents a ~5 m thick stratigraphic section of lithified fluvial and lacustrine sediments analyzed by the Curiosity rover in Gale crater, Mars. Previous works have mainly focused on the mudstones that were drilled by the rover at two locations. The present study focuses on the sedimentary rocks stratigraphically above the mudstones by studying their chemical variations in parallel with rock textures. Results show that differences in composition correlate with textures and both manifest subtle but significant variations through the stratigraphic column. Though the chemistry of the sediments does not vary much in the lower part of the stratigraphy, the variations in alkali elements indicate variations in the source material and/or physical sorting, as shown by the identification of alkali feldspars. The sandstones contain similar relative proportions of hydrogen to the mudstones below, suggesting the presence of hydrous minerals that may have contributed to their cementation. Slight variations in magnesium correlate with changes in textures suggesting that diagenesis through cementation and dissolution modified the initial rock composition and texture simultaneously. The upper part of the stratigraphy (~1 m thick) displays rocks with different compositions suggesting a strong change in the depositional system. The presence of float rocks with similar compositions found along the rover traverse suggests that some of these outcrops extend further away in the nearby hummocky plains.</p>","language":"English","publisher":"American Geophysical Union","publisherLocation":"Richmond, VA","doi":"10.1002/2014JE004681","usgsCitation":"Mangold, N., Forni, O., Dromart, G., Stack, K., Wiens, R.C., Gasnault, O., Sumner, D.Y., Nachon, M., Meslin, P., Anderson, R., Barraclough, B., Bell, J., Berger, G., Blaney, D., Bridges, J., Calef, F., Clark, B.R., Clegg, S.M., Cousin, A., Edgar, L., Edgett, K., Ehlmann, B., Fabre, C., Fisk, M., Grotzinger, J., Gupta, S., Herkenhoff, K.E., Hurowitz, J., Johnson, J.R., Kah, L., Lanza, N.L., Lasue, J., Le Mouélic, S., Lewin, E., Malin, M., McLennan, S.M., Maurice, S., Melikechi, N., Mezzacappa, A., Milliken, R.E., Newsome, H., Ollila, A., Rowland, S.K., Sautter, V., Schmidt, M., Schroder, S., D'Uston, C., Vaniman, D., and Williams, R.A., 2015, Chemical variations in Yellowknife Bay formation sedimentary rocks analyzed by ChemCam on board the Curiosity rover on Mars: Journal of Geophysical Research E: Planets, v. 120, no. 3, p. 452-482, https://doi.org/10.1002/2014JE004681.","productDescription":"31 p.","startPage":"452","endPage":"482","numberOfPages":"31","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-053373","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":472206,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hal.univ-lorraine.fr/hal-01281801","text":"External Repository"},{"id":299775,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":299730,"type":{"id":15,"text":"Index Page"},"url":"https://onlinelibrary.wiley.com/doi/10.1002/2014JE004681/abstract"}],"volume":"120","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-03-19","publicationStatus":"PW","scienceBaseUri":"55362333e4b0b22a15807a85","contributors":{"authors":[{"text":"Mangold, Nicolas","contributorId":52903,"corporation":false,"usgs":false,"family":"Mangold","given":"Nicolas","email":"","affiliations":[],"preferred":false,"id":545245,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Forni, Olivier","contributorId":72690,"corporation":false,"usgs":false,"family":"Forni","given":"Olivier","email":"","affiliations":[],"preferred":false,"id":545246,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dromart, G.","contributorId":7153,"corporation":false,"usgs":true,"family":"Dromart","given":"G.","affiliations":[],"preferred":false,"id":545247,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stack, K.M.","contributorId":20628,"corporation":false,"usgs":true,"family":"Stack","given":"K.M.","affiliations":[],"preferred":false,"id":545248,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wiens, Roger C.","contributorId":140330,"corporation":false,"usgs":false,"family":"Wiens","given":"Roger","email":"","middleInitial":"C.","affiliations":[{"id":13447,"text":"Los Alamos National Laboratory","active":true,"usgs":false}],"preferred":false,"id":545249,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gasnault, Olivier","contributorId":53709,"corporation":false,"usgs":true,"family":"Gasnault","given":"Olivier","affiliations":[],"preferred":false,"id":545250,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sumner, Dawn Y.","contributorId":88997,"corporation":false,"usgs":true,"family":"Sumner","given":"Dawn","email":"","middleInitial":"Y.","affiliations":[],"preferred":false,"id":545251,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Nachon, Marion","contributorId":48485,"corporation":false,"usgs":false,"family":"Nachon","given":"Marion","email":"","affiliations":[],"preferred":false,"id":545252,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Meslin, Pierre-Yves","contributorId":66186,"corporation":false,"usgs":false,"family":"Meslin","given":"Pierre-Yves","email":"","affiliations":[],"preferred":false,"id":545253,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Anderson, Ryan B.","contributorId":25438,"corporation":false,"usgs":true,"family":"Anderson","given":"Ryan B.","affiliations":[],"preferred":false,"id":545254,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Barraclough, Bruce","contributorId":72724,"corporation":false,"usgs":true,"family":"Barraclough","given":"Bruce","email":"","affiliations":[],"preferred":false,"id":545255,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Bell, J.F. III","contributorId":97612,"corporation":false,"usgs":true,"family":"Bell","given":"J.F.","suffix":"III","email":"","affiliations":[],"preferred":false,"id":545256,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Berger, G.","contributorId":48064,"corporation":false,"usgs":true,"family":"Berger","given":"G.","email":"","affiliations":[],"preferred":false,"id":545257,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Blaney, D.L.","contributorId":43477,"corporation":false,"usgs":true,"family":"Blaney","given":"D.L.","email":"","affiliations":[],"preferred":false,"id":545258,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Bridges, J.C.","contributorId":51968,"corporation":false,"usgs":true,"family":"Bridges","given":"J.C.","email":"","affiliations":[],"preferred":false,"id":545259,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Calef, F.","contributorId":45616,"corporation":false,"usgs":true,"family":"Calef","given":"F.","affiliations":[],"preferred":false,"id":545260,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Clark, Brian R. 0000-0001-6611-3807 brclark@usgs.gov","orcid":"https://orcid.org/0000-0001-6611-3807","contributorId":1502,"corporation":false,"usgs":true,"family":"Clark","given":"Brian","email":"brclark@usgs.gov","middleInitial":"R.","affiliations":[{"id":38131,"text":"WMA - Office of Planning and Programming","active":true,"usgs":true}],"preferred":true,"id":545261,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Clegg, Samuel M.","contributorId":23460,"corporation":false,"usgs":false,"family":"Clegg","given":"Samuel","email":"","middleInitial":"M.","affiliations":[{"id":13447,"text":"Los Alamos National Laboratory","active":true,"usgs":false}],"preferred":false,"id":545262,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Cousin, Agnes","contributorId":40139,"corporation":false,"usgs":false,"family":"Cousin","given":"Agnes","email":"","affiliations":[{"id":13447,"text":"Los Alamos National Laboratory","active":true,"usgs":false}],"preferred":false,"id":545263,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Edgar, L.","contributorId":39618,"corporation":false,"usgs":true,"family":"Edgar","given":"L.","email":"","affiliations":[],"preferred":false,"id":545264,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Edgett, Kenneth S.","contributorId":12736,"corporation":false,"usgs":true,"family":"Edgett","given":"Kenneth S.","affiliations":[],"preferred":false,"id":545265,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Ehlmann, B.L.","contributorId":107837,"corporation":false,"usgs":true,"family":"Ehlmann","given":"B.L.","email":"","affiliations":[],"preferred":false,"id":545266,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Fabre, Cecile","contributorId":7206,"corporation":false,"usgs":true,"family":"Fabre","given":"Cecile","affiliations":[],"preferred":false,"id":545267,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Fisk, M.","contributorId":140310,"corporation":false,"usgs":false,"family":"Fisk","given":"M.","affiliations":[],"preferred":false,"id":545268,"contributorType":{"id":1,"text":"Authors"},"rank":24},{"text":"Grotzinger, John P.","contributorId":22247,"corporation":false,"usgs":true,"family":"Grotzinger","given":"John P.","affiliations":[],"preferred":false,"id":545269,"contributorType":{"id":1,"text":"Authors"},"rank":25},{"text":"Gupta, S.C.","contributorId":58863,"corporation":false,"usgs":true,"family":"Gupta","given":"S.C.","email":"","affiliations":[],"preferred":false,"id":545270,"contributorType":{"id":1,"text":"Authors"},"rank":26},{"text":"Herkenhoff, Kenneth E. 0000-0002-3153-6663 kherkenhoff@usgs.gov","orcid":"https://orcid.org/0000-0002-3153-6663","contributorId":2275,"corporation":false,"usgs":true,"family":"Herkenhoff","given":"Kenneth","email":"kherkenhoff@usgs.gov","middleInitial":"E.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":545271,"contributorType":{"id":1,"text":"Authors"},"rank":27},{"text":"Hurowitz, J.A.","contributorId":10994,"corporation":false,"usgs":true,"family":"Hurowitz","given":"J.A.","email":"","affiliations":[],"preferred":false,"id":545272,"contributorType":{"id":1,"text":"Authors"},"rank":28},{"text":"Johnson, J. 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A.","contributorId":82323,"corporation":false,"usgs":true,"family":"Williams","given":"R.","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":545293,"contributorType":{"id":1,"text":"Authors"},"rank":49}]}}
,{"id":70160090,"text":"70160090 - 2015 - A review of the global relationship among freshwater fish, autotrophic activity, and regional climate","interactions":[],"lastModifiedDate":"2015-12-14T11:44:15","indexId":"70160090","displayToPublicDate":"2015-03-19T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3278,"text":"Reviews in Fish Biology and Fisheries","active":true,"publicationSubtype":{"id":10}},"title":"A review of the global relationship among freshwater fish, autotrophic activity, and regional climate","docAbstract":"<p><span>The relationship between autotrophic activity and freshwater fish populations is an important consideration for ecologists describing trophic structure in aquatic communities, fisheries managers tasked with increasing sustainable fisheries development, and fish farmers seeking to maximize production. Previous studies of the empirical relationships of autotrophic activity and freshwater fish yield have found positive relationships but were limited by small sample sizes, small geographic scopes, and the inability to compare patterns among many types of measurement techniques. Individual studies and reviews have also lacked consistent consideration of regional climate factors which may inform relationships between fisheries and autotrophic activity. We compiled data from over 700 freshwater systems worldwide and used meta-analysis and linear models to develop a comprehensive global synthesis between multiple metrics of autotrophic activity, fisheries, and climate indicators. Our results demonstrate that multiple metrics of fish (i.e., catch per unit effort, yield, and production) increase with autotrophic activity across a variety of fisheries. At the global scale additional variation in this positive relationship can be ascribed to regional climate differences (i.e., temperature and precipitation) across systems. Our results provide a method and proof-of-concept for assessing inland fisheries production at the global scale, where current estimates are highly uncertain, and may therefore inform the continued sustainable use of global inland fishery resources.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s11160-015-9384-z","usgsCitation":"Deines, A., Bunnell, D., Rogers, M.W., Beard, T., and Taylor, W., 2015, A review of the global relationship among freshwater fish, autotrophic activity, and regional climate: Reviews in Fish Biology and Fisheries, v. 25, no. 2, p. 323-336, https://doi.org/10.1007/s11160-015-9384-z.","productDescription":"14 p.","startPage":"323","endPage":"336","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-055723","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":312247,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"25","issue":"2","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2015-03-19","publicationStatus":"PW","scienceBaseUri":"566ff63ae4b09cfe53ca7963","contributors":{"authors":[{"text":"Deines, Andrew M.","contributorId":94601,"corporation":false,"usgs":true,"family":"Deines","given":"Andrew M.","affiliations":[],"preferred":false,"id":581847,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bunnell, David B. dbunnell@usgs.gov","contributorId":141167,"corporation":false,"usgs":true,"family":"Bunnell","given":"David B.","email":"dbunnell@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":581846,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rogers, Mark W. 0000-0001-7205-5623 mwrogers@usgs.gov","orcid":"https://orcid.org/0000-0001-7205-5623","contributorId":4590,"corporation":false,"usgs":true,"family":"Rogers","given":"Mark","email":"mwrogers@usgs.gov","middleInitial":"W.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":581848,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Beard, T. Douglas Jr. dbeard@usgs.gov","contributorId":150495,"corporation":false,"usgs":true,"family":"Beard","given":"T. Douglas","suffix":"Jr.","email":"dbeard@usgs.gov","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":false,"id":581849,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Taylor, William W.","contributorId":49735,"corporation":false,"usgs":false,"family":"Taylor","given":"William W.","affiliations":[],"preferred":false,"id":581850,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70143006,"text":"70143006 - 2015 - Bahamas connection: residence areas selected by breeding female loggerheads tagged in Dry Tortugas National Park, USA","interactions":[],"lastModifiedDate":"2015-03-18T15:08:00","indexId":"70143006","displayToPublicDate":"2015-03-18T15:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":773,"text":"Animal Biotelemetry","active":true,"publicationSubtype":{"id":10}},"title":"Bahamas connection: residence areas selected by breeding female loggerheads tagged in Dry Tortugas National Park, USA","docAbstract":"<p>Background</p>\n<p>Delineation of home ranges, residence and foraging areas, and migration corridors is important for understanding the habitat needs for a given species. Recently, many population segments of Northwest Atlantic loggerhead sea turtles (<i>Caretta caretta</i>) were designated as endangered or threatened; the smallest subpopulation is in the Dry Tortugas. Foraging and residence areas for this subpopulation have not been defined outside the Gulf of Mexico. Here, for Dry Tortugas loggerheads that traveled to the Bahamas, we use a combination of switching state-space modeling (SSM) and home-range estimators to determine migration period, spatially delineate and describe residence areas, and examine inter-annual home-range repeatability.</p>\n<p>Results</p>\n<p>In 5,973 tracking days, migration dates for Dry Tortugas loggerheads traveling to the Bahamas occurred during July&ndash;September, with turtles tracked twice showing remarkably similar migration paths and timing of departure from nesting sites. Core-use residence areas for 19 loggerheads ranged from 3.7 to 179.5&nbsp;km<sup>2</sup><span class=\"Apple-converted-space\">&nbsp;</span>(mean&thinsp;&plusmn;&thinsp;1 SD&thinsp;=&thinsp;56.2&thinsp;&plusmn;&thinsp;49.5&nbsp;km<sup>2</sup>). For three turtles, we found inter-annual home-range repeatability, with centroids of core areas only 0.7&ndash;2.9&nbsp;km apart and significant overlap of inter-annual 50% kernel contours.</p>\n<p>Conclusions</p>\n<p>We demonstrate a previously unknown link between Dry Tortugas nesting beaches and Bahamas residence areas; 17/39 (43.6%) of nesting loggerheads tagged in and tracked from the Dry Tortugas take up residence at sites in the Bahamas. Residence area estimates for these turtles were similar in size to previous foraging area estimates for two turtles tracked to the Bahamas in other studies. We show inter-annual residence area repeatability, and that residence areas of different individuals generally did not overlap. We suggest that these loggerheads possibly establish territories.</p>","language":"English","publisher":"BioMed Central","publisherLocation":"London","doi":"10.1186/s40317-014-0019-2","usgsCitation":"Hart, K.M., Sartain-Iverson, A.R., and Fujisaki, I., 2015, Bahamas connection: residence areas selected by breeding female loggerheads tagged in Dry Tortugas National Park, USA: Animal Biotelemetry, v. 3, no. 3, 17 p., https://doi.org/10.1186/s40317-014-0019-2.","productDescription":"17 p.","numberOfPages":"17","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056898","costCenters":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"links":[{"id":472208,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s40317-014-0019-2","text":"Publisher Index Page"},{"id":298729,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Dry Tortugas National Park","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -82.80052185058592,\n              24.726251180537773\n            ],\n            [\n              -82.76653289794922,\n              24.701301018708502\n            ],\n            [\n              -82.76653289794922,\n              24.66854634616668\n            ],\n            [\n              -82.80086517333983,\n              24.617369459303212\n            ],\n            [\n              -82.89802551269531,\n              24.56773283789708\n            ],\n            [\n              -82.96531677246094,\n              24.566796108748612\n            ],\n            [\n              -82.96669006347656,\n              24.64920145194691\n            ],\n            [\n              -82.90077209472656,\n              24.717831059976803\n            ],\n            [\n              -82.86712646484375,\n              24.726251180537773\n            ],\n            [\n              -82.80052185058592,\n              24.726251180537773\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"3","issue":"3","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"550a939ae4b02e76d7590bb3","contributors":{"authors":[{"text":"Hart, Kristen M. 0000-0002-5257-7974 kristen_hart@usgs.gov","orcid":"https://orcid.org/0000-0002-5257-7974","contributorId":1966,"corporation":false,"usgs":true,"family":"Hart","given":"Kristen","email":"kristen_hart@usgs.gov","middleInitial":"M.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":542420,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sartain-Iverson, Autumn R. 0000-0002-8353-6745 asartain@usgs.gov","orcid":"https://orcid.org/0000-0002-8353-6745","contributorId":5477,"corporation":false,"usgs":true,"family":"Sartain-Iverson","given":"Autumn","email":"asartain@usgs.gov","middleInitial":"R.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":false,"id":542421,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fujisaki, Ikuko","contributorId":38359,"corporation":false,"usgs":false,"family":"Fujisaki","given":"Ikuko","affiliations":[],"preferred":false,"id":542422,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70139748,"text":"ds918 - 2015 - Sample descriptions and geophysical logs for cored well BP-3-USGS, Great Sand Dunes National Park and Preserve, Alamosa County, Colorado","interactions":[],"lastModifiedDate":"2015-03-17T14:13:31","indexId":"ds918","displayToPublicDate":"2015-03-17T15:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"918","title":"Sample descriptions and geophysical logs for cored well BP-3-USGS, Great Sand Dunes National Park and Preserve, Alamosa County, Colorado","docAbstract":"<p>The BP-3-USGS well was drilled at the southwestern corner of Great Sand Dunes National Park in the San Luis Valley, south-central Colorado, 68 feet (ft, 20.7 meters [m]) southwest of the National Park Service&rsquo;s boundary-piezometer (BP) well 3. BP-3-USGS is located at latitude 37&deg;43ʹ18.06ʺN. and longitude 105&deg;43ʹ39.30ʺW., at an elevation of 7,549 ft (2,301 m). The well was drilled through poorly consolidated sediments to a depth of 326 ft (99.4 m) in September 2009. Water began flowing from the well after penetrating a clay-rich layer that was first intercepted at a depth of 119 ft (36.3 m). The base of this layer, at an elevation of 7,415 ft (2,260 m) above sea level, likely marks the top of a regional confined aquifer recognized throughout much of the San Luis Valley. Approximately 69 ft (21 m) of core was recovered (about 21 percent), almost exclusively from clay-rich zones. Coarser grained fractions were collected from mud extruded from the core barrel or captured from upwelling drilling fluids. Natural gamma-ray, full waveform sonic, density, neutron, resistivity, spontaneous potential, and induction logs were acquired. The well is now plugged and abandoned.</p>\n<p>This report presents lithologic descriptions from the well samples and core, along with a compilation and basic data processing of the geophysical logs. The succession of sediments in the well can be generalized into three lithologic packages: (1) mostly sand from the surface to about 77 ft (23.5 m) depth; (2) interbedded sand, silt, and clay, decreasing in overall grain size downward, from 77 to 232 ft (23.5 to 70.7 m) depth; and (3) layers of massive clay alternating with layers of fine sand to silt from 232 to 326 ft (70.7 to 99.4 m), the total depth of the well. The topmost clay layers of the deepest package have a blue tint, prompting a correlation with the &ldquo;blue clay&rdquo; of the San Luis Valley that is commonly considered as the top of the confined aquifer. However, a confining clay was intercepted 113 ft (34.4 m) higher than the blue clay in BP-3-USGS.</p>\n<p>Most of the geophysical logs have good correspondence to the lithologic variations in the well. Exceptions are the gamma-ray log, which is likely affected by naturally occurring radiation from abundant volcanic detritus, and one interval within the deepest lithologic package, which appears to be abnormally electrically conductive. Resistivity logs and variations in sand versus clay content within the well are consistent with electrical resistivity models derived from time-domain electromagnetic geophysical surveys for the area. In particular, the topmost blue clay corresponds to a strong electrical conductor that is prominent in the electromagnetic geophysical data throughout the park and vicinity.</p>\n<p>BP-3-USGS was sited to test hypotheses developed from geophysical studies and to answer questions about the history and evolution of Pliocene and Pleistocene Lake Alamosa, which is represented by lacustrine deposits sampled by the well. The findings reported here represent a basis from which future studies can answer these questions and address other important scientific questions in the San Luis Valley regarding geologic history and climate change, groundwater hydrology, and geophysical interpretation.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds918","collaboration":"Prepared in cooperation with National Park Service","usgsCitation":"Grauch, V.J., Skipp, G.L., Thomas, J.V., Davis, J.K., and Benson, M.E., 2015, Sample descriptions and geophysical logs for cored well BP-3-USGS, Great Sand Dunes National Park and Preserve, Alamosa County, Colorado: U.S. Geological Survey Data Series 918, Report: vi, 53 p.; Log files; Photographs, https://doi.org/10.3133/ds918.","productDescription":"Report: vi, 53 p.; Log files; Photographs","numberOfPages":"64","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-059656","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":298635,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds918.jpg"},{"id":298632,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0918/pdf/ds918.pdf","size":"3.10 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":298633,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/0918/downloads/LogFiles/","text":"Log files--data for borehole geophysical logs"},{"id":298634,"rank":4,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/0918/downloads/PhotoFiles/","text":"Photographs of samples taken onsite"},{"id":298630,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0918/"}],"country":"United States","state":"Colorado","otherGeospatial":"Great Sand Dune National Park, Great Sand Dune National Preserve","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -106.754150390625,\n              37.00255267215955\n            ],\n            [\n              -106.754150390625,\n              39.16414104768742\n            ],\n            [\n              -104.117431640625,\n              39.16414104768742\n            ],\n            [\n              -104.117431640625,\n              37.00255267215955\n            ],\n            [\n              -106.754150390625,\n              37.00255267215955\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55094222e4b02e76d757d919","contributors":{"authors":[{"text":"Grauch, V. J. S. 0000-0002-0761-3489 tien@usgs.gov","orcid":"https://orcid.org/0000-0002-0761-3489","contributorId":886,"corporation":false,"usgs":true,"family":"Grauch","given":"V.","email":"tien@usgs.gov","middleInitial":"J. S.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":542500,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Skipp, Gary L. 0000-0002-9404-0980 gskipp@usgs.gov","orcid":"https://orcid.org/0000-0002-9404-0980","contributorId":2102,"corporation":false,"usgs":true,"family":"Skipp","given":"Gary","email":"gskipp@usgs.gov","middleInitial":"L.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":542501,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thomas, Jonathan V. 0000-0003-0903-9713 jvthomas@usgs.gov","orcid":"https://orcid.org/0000-0003-0903-9713","contributorId":2194,"corporation":false,"usgs":true,"family":"Thomas","given":"Jonathan","email":"jvthomas@usgs.gov","middleInitial":"V.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":542502,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Davis, Joshua K.","contributorId":138996,"corporation":false,"usgs":false,"family":"Davis","given":"Joshua","email":"","middleInitial":"K.","affiliations":[{"id":12430,"text":"University of Texas at Austin","active":true,"usgs":false}],"preferred":false,"id":542503,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Benson, Mary Ellen 0000-0002-4424-0730 mbenson@usgs.gov","orcid":"https://orcid.org/0000-0002-4424-0730","contributorId":4724,"corporation":false,"usgs":true,"family":"Benson","given":"Mary","email":"mbenson@usgs.gov","middleInitial":"Ellen","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":542504,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70142977,"text":"sir20155009 - 2015 - An assessment of two methods for identifying undocumented levees using remotely sensed data","interactions":[],"lastModifiedDate":"2015-03-17T10:32:39","indexId":"sir20155009","displayToPublicDate":"2015-03-17T11:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-5009","title":"An assessment of two methods for identifying undocumented levees using remotely sensed data","docAbstract":"<p><span>Many undocumented and commonly unmaintained levees exist in the landscape complicating flood forecasting, risk management, and emergency response. This report describes a pilot study completed by the U.S. Geological Survey in cooperation with the U.S. Army Corps of Engineers to assess two methods to identify undocumented levees by using remotely sensed, high-resolution topographic data. For the first method, the U.S. Army Corps of Engineers examined hillshades computed from a digital elevation model that was derived from light detection and ranging (lidar) to visually identify potential levees and then used detailed site visits to assess the validity of the identifications. For the second method, the U.S. Geological Survey applied a wavelet transform to a lidar-derived digital elevation model to identify potential levees. The hillshade method was applied to Delano, Minnesota, and the wavelet-transform method was applied to Delano and Springfield, Minnesota. Both methods were successful in identifying levees but also identified other features that required interpretation to differentiate from levees such as constructed barriers, high banks, and bluffs. Both methods are complementary to each other, and a potential conjunctive method for testing in the future includes (1) use of the wavelet-transform method to rapidly identify slope-break features in high-resolution topographic data, (2) further examination of topographic data using hillshades and aerial photographs to classify features and map potential levees, and (3) a verification check of each identified potential levee with local officials and field visits.</span></p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155009","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Czuba, C.R., Williams, B.K., Westman, J., and LeClaire, K., 2015, An assessment of two methods for identifying undocumented levees using remotely sensed data: U.S. Geological Survey Scientific Investigations Report 2015-5009, vii, 19 p., https://doi.org/10.3133/sir20155009.","productDescription":"vii, 19 p.","numberOfPages":"32","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-046266","costCenters":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"links":[{"id":298608,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20155009.jpg"},{"id":298556,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2015/5009/"},{"id":298607,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5009/pdf/sir2015-5009.pdf","size":"6.04 MB","linkFileType":{"id":1,"text":"pdf"}}],"scale":"24000","projection":"Universal Transverse Mercator projection","datum":"North American Datum of 1983","country":"United States","state":"Minnesota","city":"Delano, Springfield","otherGeospatial":"Cottonwood River, South Fork Crow River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -93.83766174316406,\n              45.00437940337335\n            ],\n            [\n              -93.83766174316406,\n              45.06782265048428\n            ],\n            [\n              -93.75646591186523,\n              45.06782265048428\n            ],\n            [\n              -93.75646591186523,\n              45.00437940337335\n            ],\n            [\n              -93.83766174316406,\n              45.00437940337335\n            ]\n          ]\n        ]\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -95.01251220703125,\n              44.2075577272807\n            ],\n            [\n              -95.01251220703125,\n              44.25460557622782\n            ],\n            [\n              -94.94685173034668,\n              44.25460557622782\n            ],\n            [\n              -94.94685173034668,\n              44.2075577272807\n            ],\n            [\n              -95.01251220703125,\n              44.2075577272807\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55094218e4b02e76d757d90b","contributors":{"authors":[{"text":"Czuba, Christiana R. cczuba@usgs.gov","contributorId":4555,"corporation":false,"usgs":true,"family":"Czuba","given":"Christiana","email":"cczuba@usgs.gov","middleInitial":"R.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":false,"id":542369,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Williams, Byron K. 0000-0001-7644-1396","orcid":"https://orcid.org/0000-0001-7644-1396","contributorId":86616,"corporation":false,"usgs":true,"family":"Williams","given":"Byron","email":"","middleInitial":"K.","affiliations":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"preferred":false,"id":542370,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Westman, Jack","contributorId":139665,"corporation":false,"usgs":false,"family":"Westman","given":"Jack","email":"","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":542372,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"LeClaire, Keith","contributorId":139664,"corporation":false,"usgs":false,"family":"LeClaire","given":"Keith","email":"","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":542371,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70155816,"text":"70155816 - 2015 - Chromosomal damage and EROD induction in tree swallows (Tachycineta bicolor) along the Upper Mississippi River, Minnesota, USA","interactions":[],"lastModifiedDate":"2022-11-15T15:53:44.996779","indexId":"70155816","displayToPublicDate":"2015-03-17T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1479,"text":"Ecotoxicology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Chromosomal damage and EROD induction in tree swallows (<i>Tachycineta bicolor</i>) along the Upper Mississippi River, Minnesota, USA","title":"Chromosomal damage and EROD induction in tree swallows (Tachycineta bicolor) along the Upper Mississippi River, Minnesota, USA","docAbstract":"<div id=\"Abs1-section\" class=\"c-article-section\"><div id=\"Abs1-content\" class=\"c-article-section__content\"><p>The health of tree swallows,<span>&nbsp;</span><i>Tachycineta bicolor,</i><span>&nbsp;</span>on the Upper Mississippi River (UMR) was assessed in 2010 and 2011 using biomarkers at six sites downriver of Minneapolis/St. Paul, MN metropolitan area, a tributary into the UMR, and a nearby lake. Chromosomal damage was evaluated in nestling blood by measuring the coefficient of variation of DNA content (DNA CV) using flow cytometry. Cytochrome P450 1A activity in nestling liver was measured using the ethoxyresorufin-<i>O</i>-dealkylase (EROD) assay, and oxidative stress was estimated in nestling livers via determination of thiobarbituric acid reacting substances (TBARS), reduced glutathione (GSH), oxidized glutathione (GSSG), the ratio GSSG/GSH, total sulfhydryl, and protein bound sulfhydryl (PBSH). A multilevel regression model (DNA CV) and simple regressions (EROD and oxidative stress) were used to evaluate biomarker responses for each location. Chromosomal damage was significantly elevated at two sites on the UMR (Pigs Eye and Pool 2) relative to the Green Mountain Lake reference site, while the induction of EROD activity was only observed at Pigs Eye. No measures of oxidative stress differed among sites. Multivariate analysis confirmed an increased DNA CV at Pigs Eye and Pool 2, and elevated EROD activity at Pigs Eye. These results suggest that the health of tree swallows has been altered at the DNA level at Pigs Eye and Pool 2 sites, and at the physiological level at Pigs Eye site only.</p></div></div>","language":"English","publisher":"Springer","doi":"10.1007/s10646-015-1443-7","usgsCitation":"Bigorgne, E., Custer, T.W., Dummer, P.M., Erickson, R.A., Karouna-Renier, N.K., Schultz, S.L., Custer, C.M., Thogmartin, W.E., and Matson, C.W., 2015, Chromosomal damage and EROD induction in tree swallows (Tachycineta bicolor) along the Upper Mississippi River, Minnesota, USA: Ecotoxicology, v. 24, no. 5, p. 1028-1039, https://doi.org/10.1007/s10646-015-1443-7.","productDescription":"12 p.","startPage":"1028","endPage":"1039","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057678","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":306554,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota","otherGeospatial":"Upper Mississippi River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -92.3445469165147,\n              44.53697445015797\n            ],\n            [\n              -92.83259341591337,\n              44.76622110058835\n            ],\n            [\n              -93.50861954785603,\n              44.65669445359666\n            ],\n            [\n              -93.21439055778808,\n              44.32269458666789\n            ],\n            [\n              -92.34337934115722,\n              44.51866217361814\n            ],\n            [\n              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tcuster@usgs.gov","orcid":"https://orcid.org/0000-0003-3170-6519","contributorId":2835,"corporation":false,"usgs":true,"family":"Custer","given":"Thomas","email":"tcuster@usgs.gov","middleInitial":"W.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":566459,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dummer, Paul M. 0000-0002-2055-9480 pdummer@usgs.gov","orcid":"https://orcid.org/0000-0002-2055-9480","contributorId":3015,"corporation":false,"usgs":true,"family":"Dummer","given":"Paul","email":"pdummer@usgs.gov","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":566461,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Erickson, Richard A. 0000-0003-4649-482X rerickson@usgs.gov","orcid":"https://orcid.org/0000-0003-4649-482X","contributorId":5455,"corporation":false,"usgs":true,"family":"Erickson","given":"Richard","email":"rerickson@usgs.gov","middleInitial":"A.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":566462,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Karouna-Renier, Natalie K. 0000-0001-7127-033X nkarouna@usgs.gov","orcid":"https://orcid.org/0000-0001-7127-033X","contributorId":141213,"corporation":false,"usgs":true,"family":"Karouna-Renier","given":"Natalie","email":"nkarouna@usgs.gov","middleInitial":"K.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":566463,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schultz, Sandra L. 0000-0003-3394-2857 sschultz@usgs.gov","orcid":"https://orcid.org/0000-0003-3394-2857","contributorId":5966,"corporation":false,"usgs":true,"family":"Schultz","given":"Sandra","email":"sschultz@usgs.gov","middleInitial":"L.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":566464,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Custer, Christine M. 0000-0003-0500-1582 ccuster@usgs.gov","orcid":"https://orcid.org/0000-0003-0500-1582","contributorId":1143,"corporation":false,"usgs":true,"family":"Custer","given":"Christine","email":"ccuster@usgs.gov","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":566465,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Thogmartin, Wayne E. 0000-0002-2384-4279 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,{"id":70142164,"text":"ofr20141224 - 2015 - Sea-floor morphology and sedimentary environments in western Block Island Sound, offshore of Fishers Island, New York","interactions":[],"lastModifiedDate":"2015-03-18T08:42:24","indexId":"ofr20141224","displayToPublicDate":"2015-03-16T13:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-1224","title":"Sea-floor morphology and sedimentary environments in western Block Island Sound, offshore of Fishers Island, New York","docAbstract":"<p><span>Multibeam-bathymetric and sidescan-sonar data, collected by the National Oceanic and Atmospheric Administration in a 114-square-kilometer area of Block Island Sound, southeast of Fishers Island, New York, are combined with sediment samples and bottom photography collected by the U.S. Geological Survey from 36 stations in this area in order to interpret sea-floor features and sedimentary environments. These interpretations and datasets provide base maps for studies on benthic ecology and resource management. The geologic features and sedimentary environments on the sea floor are products of the area&rsquo;s glacial history and modern processes. These features include bedrock, drumlins, boulders, cobbles, large current-scoured bathymetric depressions, obstacle marks, and glaciolacustrine sediments found in high-energy sedimentary environments of erosion or nondeposition; and sand waves and megaripples in sedimentary environments characterized by coarse-grained bedload transport. Trawl marks are preserved in lower energy environments of sorting and reworking. This report releases the multibeam-bathymetric, sidescan-sonar, sediment, and photographic data and interpretations of the features and sedimentary environments in Block Island Sound, offshore Fishers Island.</span></p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141224","collaboration":"Prepared in cooperation with the National Oceanic and Atmospheric Administration","usgsCitation":"McMullen, K.Y., Poppe, L.J., Danforth, W.W., Blackwood, D.S., Winner, W.G., and Parker, C.E., 2015, Sea-floor morphology and sedimentary environments in western Block Island Sound, offshore of Fishers Island, New York: U.S. Geological Survey Open-File Report 2014-1224, HTML Document; DVD-ROM, https://doi.org/10.3133/ofr20141224.","productDescription":"HTML Document; DVD-ROM","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060422","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":298568,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1224/"},{"id":298569,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1224/ofr2014-1224-title_page.html","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":298570,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141224.jpg"}],"datum":"World Geodetic System 1984","country":"United States","state":"New York","otherGeospatial":"Block Island Sound, Fishers Island","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -72.0047378540039,\n              41.193381423508484\n            ],\n            [\n              -72.00576782226562,\n              41.25458109268851\n            ],\n            [\n              -71.97452545166016,\n              41.27393614529453\n            ],\n            [\n              -71.92955017089844,\n              41.287094304074884\n            ],\n            [\n              -71.85745239257812,\n              41.28761025624326\n            ],\n            [\n              -71.85745239257812,\n              41.194156460760546\n            ],\n            [\n              -72.0047378540039,\n              41.193381423508484\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5507f09fe4b02e76d757c126","contributors":{"authors":[{"text":"McMullen, Katherine Y. kmcmullen@usgs.gov","contributorId":2148,"corporation":false,"usgs":true,"family":"McMullen","given":"Katherine","email":"kmcmullen@usgs.gov","middleInitial":"Y.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":541646,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Poppe, Lawrence J. lpoppe@usgs.gov","contributorId":139521,"corporation":false,"usgs":true,"family":"Poppe","given":"Lawrence","email":"lpoppe@usgs.gov","middleInitial":"J.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":541647,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Danforth, William W. 0000-0002-6382-9487 bdanforth@usgs.gov","orcid":"https://orcid.org/0000-0002-6382-9487","contributorId":3292,"corporation":false,"usgs":true,"family":"Danforth","given":"William","email":"bdanforth@usgs.gov","middleInitial":"W.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":541648,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Blackwood, Dann S. dblackwood@usgs.gov","contributorId":2457,"corporation":false,"usgs":true,"family":"Blackwood","given":"Dann","email":"dblackwood@usgs.gov","middleInitial":"S.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":541649,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Winner, William G.","contributorId":139522,"corporation":false,"usgs":false,"family":"Winner","given":"William","email":"","middleInitial":"G.","affiliations":[{"id":12641,"text":"NOAA NMFS","active":true,"usgs":false}],"preferred":false,"id":541650,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Parker, Castle E.","contributorId":28684,"corporation":false,"usgs":false,"family":"Parker","given":"Castle","email":"","middleInitial":"E.","affiliations":[{"id":12448,"text":"U.S. National Oceanic and Atmospheric Administration","active":true,"usgs":false}],"preferred":false,"id":541651,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70175295,"text":"70175295 - 2015 - Modeling climate change, urbanization, and fire effects on <i>Pinus palustris</i> ecosystems of the southeastern U.S.","interactions":[],"lastModifiedDate":"2018-12-20T12:59:26","indexId":"70175295","displayToPublicDate":"2015-03-15T11:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2258,"text":"Journal of Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Modeling climate change, urbanization, and fire effects on <i>Pinus palustris</i> ecosystems of the southeastern U.S.","docAbstract":"<p><span>Managing ecosystems for resilience and sustainability requires understanding how they will respond to future anthropogenic drivers such as climate change and urbanization. In fire-dependent ecosystems, predicting this response requires a focus on how these drivers will impact fire regimes. Here, we use scenarios of climate change, urbanization and management to simulate the future dynamics of the critically endangered and fire-dependent longleaf pine (</span><i>Pinus palustris</i><span>) ecosystem. We investigated how climate change and urbanization will affect the ecosystem, and whether the two conservation goals of a 135% increase in total longleaf area and a doubling of fire-maintained open-canopy habitat can be achieved in the face of these drivers. Our results show that while climatic warming had little effect on the wildfire regime, and thus on longleaf pine dynamics, urban growth led to an 8% reduction in annual wildfire area. The management scenarios we tested increase the ecosystem's total extent by up to 62% and result in expansion of open-canopy longleaf by as much as 216%, meeting one of the two conservation goals for the ecosystem. We find that both conservation goals for this ecosystem, which is climate-resilient but vulnerable to urbanization, are only attainable if a greater focus is placed on restoration of non-longleaf areas as opposed to maintaining existing longleaf stands. Our approach demonstrates the importance of accounting for multiple relevant anthropogenic threats in an ecosystem-specific context in order to facilitate more effective management actions.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jenvman.2014.12.032","usgsCitation":"Costanza, J., Terando, A.J., McKerrow, A., and Collazo, J., 2015, Modeling climate change, urbanization, and fire effects on <i>Pinus palustris</i> ecosystems of the southeastern U.S.: Journal of Environmental Management, v. 151, p. 186-199, https://doi.org/10.1016/j.jenvman.2014.12.032.","startPage":"186","endPage":"199","numberOfPages":"14","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056277","costCenters":[{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true},{"id":37226,"text":"Core Science Analytics, Synthesis, and Libraries","active":true,"usgs":true},{"id":38315,"text":"GAP Analysis Project","active":true,"usgs":true}],"links":[{"id":326103,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"151","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57a46749e4b0ebae89b63cd4","contributors":{"authors":[{"text":"Costanza, Jennifer","contributorId":74689,"corporation":false,"usgs":true,"family":"Costanza","given":"Jennifer","affiliations":[],"preferred":false,"id":644718,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Terando, Adam J. 0000-0002-9280-043X aterando@usgs.gov","orcid":"https://orcid.org/0000-0002-9280-043X","contributorId":173447,"corporation":false,"usgs":true,"family":"Terando","given":"Adam","email":"aterando@usgs.gov","middleInitial":"J.","affiliations":[{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":644717,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McKerrow, Alexa 0000-0002-8312-2905 amckerrow@usgs.gov","orcid":"https://orcid.org/0000-0002-8312-2905","contributorId":127753,"corporation":false,"usgs":true,"family":"McKerrow","given":"Alexa","email":"amckerrow@usgs.gov","affiliations":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":true,"id":644719,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Collazo, Jaime A. 0000-0002-1816-7744 jaime_collazo@usgs.gov","orcid":"https://orcid.org/0000-0002-1816-7744","contributorId":173448,"corporation":false,"usgs":true,"family":"Collazo","given":"Jaime A.","email":"jaime_collazo@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":644720,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70142450,"text":"fs20153019 - 2015 - The 3D Elevation Program: summary for Pennsylvania","interactions":[],"lastModifiedDate":"2016-08-10T21:04:52","indexId":"fs20153019","displayToPublicDate":"2015-03-12T15:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-3019","title":"The 3D Elevation Program: summary for Pennsylvania","docAbstract":"<p>Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, national security, recreation, and many others. For the Commonwealth of Pennsylvania, elevation data are critical for natural resources conservation (including the effects of drilling for oil and natural gas), agriculture and precision farming, flood risk management, infrastructure and construction management, water supply and quality, geologic resource assessment and hazard mitigation, and other business uses. Today, high-density light detection and ranging (lidar) data are the primary sources for deriving elevation models and other datasets. Federal, State, and local agencies work in partnership to replace data that are older and of lower quality. A joint goal of Commonwealth and Federal partners is to provide a temporal and density refresh of the current statewide coverage in order to support existing and emerging applications enabled by improved lidar data.</p>\n<p>The National Enhanced Elevation Assessment evaluated multiple elevation data acquisition options to determine the optimal data quality and data replacement cycle relative to cost to meet the identified requirements of the user community. The evaluation demonstrated that lidar acquisition at quality level 2 for the conterminous United States and quality level 5 interferometric synthetic aperture radar (ifsar) data for Alaska with a 6- to 10-year acquisition cycle provided the highest benefit/cost ratios. The 3D Elevation Program (3DEP) initiative selected an 8-year acquisition cycle for the respective quality levels. 3DEP, managed by the U.S. Geological Survey, the Office of Management and Budget Circular A&ndash;16 lead agency for terrestrial elevation data, responds to the growing need for high-quality topographic data and a wide range of other 3D representations of the Nation&rsquo;s natural and constructed features.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20153019","usgsCitation":"Carswell, W., 2015, The 3D Elevation Program: summary for Pennsylvania (Version 1: Originally posted March 12, 2015; Version 1.1: June 24, 2015): U.S. Geological Survey Fact Sheet 2015-3019, 2 p., https://doi.org/10.3133/fs20153019.","productDescription":"2 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-060799","costCenters":[{"id":423,"text":"National Geospatial 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,{"id":70142446,"text":"fs20153018 - 2015 - The 3D Elevation Program: summary for Iowa","interactions":[],"lastModifiedDate":"2016-08-17T15:06:20","indexId":"fs20153018","displayToPublicDate":"2015-03-12T15:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-3018","title":"The 3D Elevation Program: summary for Iowa","docAbstract":"<p>Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, national security, recreation, and many others. For the State of Iowa, elevation data are critical for agriculture and precision farming, infrastructure and construction management, natural resources conservation, flood risk management, water supply and quality, and other business uses. Today, high-density light detection and ranging (lidar) data are the primary sources for deriving elevation models and other datasets. Federal, State, Tribal, and local agencies work in partnership to (1) replace data that are older and of lower quality and (2) provide coverage where publicly accessible data do not exist. A joint goal of State and Federal partners is to acquire consistent, statewide coverage to support existing and emerging applications enabled by lidar data.</p>\n<p>The National Enhanced Elevation Assessment evaluated multiple elevation data acquisition options to determine the optimal data quality and data replacement cycle relative to cost to meet the identified requirements of the user community. 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,{"id":70178147,"text":"70178147 - 2015 - A comparison of methods to estimate seismic phase delays--Numerical examples for coda wave interferometry","interactions":[],"lastModifiedDate":"2016-11-04T11:05:23","indexId":"70178147","displayToPublicDate":"2015-03-12T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1803,"text":"Geophysical Journal International","active":true,"publicationSubtype":{"id":10}},"title":"A comparison of methods to estimate seismic phase delays--Numerical examples for coda wave interferometry","docAbstract":"Time-shift estimation between arrivals in two seismic traces before and after a velocity perturbation is a crucial step in many seismic methods. The accuracy of the estimated velocity perturbation location and amplitude depend on this time shift. Windowed cross correlation and trace stretching are two techniques commonly used to estimate local time shifts in seismic signals. In the work presented here, we implement Dynamic Time Warping (DTW) to estimate the warping function – a vector of local time shifts that globally minimizes the misfit between two seismic traces. We illustrate the differences of all three methods compared to one another using acoustic numerical experiments. We show that DTW is comparable to or better than the other two methods when the velocity perturbation is homogeneous and the signal-to-noise ratio is high. When the signal-to-noise ratio is low, we find that DTW and windowed cross correlation are more accurate than the stretching method. Finally, we show that the DTW algorithm has better time resolution when identifying small differences in the seismic traces for a model with an isolated velocity perturbation. These results impact current methods that utilize not only time shifts between (multiply) scattered waves, but also amplitude and decoherence measurements. DTW is a new tool that may find new applications in seismology and other geophysical methods (e.g., as a waveform inversion misfit function).","language":"English","publisher":"Oxford University Press on behalf of The Royal Astronomical Society","doi":"10.1093/gji/ggv138","usgsCitation":"Mikesell, T.D., Malcolm, A.E., Yang, D., and Haney, M., 2015, A comparison of methods to estimate seismic phase delays--Numerical examples for coda wave interferometry: Geophysical Journal International, v. 202, no. 1, p. 347-360, https://doi.org/10.1093/gji/ggv138.","productDescription":"13 p.","startPage":"347","endPage":"360","ipdsId":"IP-062686","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":472212,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/gji/ggv138","text":"Publisher Index Page"},{"id":330749,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"202","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-04-30","publicationStatus":"PW","scienceBaseUri":"581d9e2be4b0dee4cc90cbc5","contributors":{"authors":[{"text":"Mikesell, T. Dylan","contributorId":52856,"corporation":false,"usgs":true,"family":"Mikesell","given":"T.","email":"","middleInitial":"Dylan","affiliations":[],"preferred":false,"id":653075,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Malcolm, Alison E.","contributorId":176672,"corporation":false,"usgs":false,"family":"Malcolm","given":"Alison","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":653076,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yang, Di","contributorId":176675,"corporation":false,"usgs":false,"family":"Yang","given":"Di","email":"","affiliations":[],"preferred":false,"id":653077,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Haney, Matthew M.","contributorId":61356,"corporation":false,"usgs":true,"family":"Haney","given":"Matthew M.","affiliations":[],"preferred":false,"id":653078,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70137274,"text":"sir20145231 - 2015 - A comparison of methods to predict historical daily streamflow time series in the southeastern United States","interactions":[],"lastModifiedDate":"2015-03-11T15:26:27","indexId":"sir20145231","displayToPublicDate":"2015-03-11T15:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-5231","title":"A comparison of methods to predict historical daily streamflow time series in the southeastern United States","docAbstract":"<p><span>Effective and responsible management of water resources relies on a thorough understanding of the quantity and quality of available water. Streamgages cannot be installed at every location where streamflow information is needed. As part of its National Water Census, the U.S. Geological Survey is planning to provide streamflow predictions for ungaged locations. In order to predict streamflow at a useful spatial and temporal resolution throughout the Nation, efficient methods need to be selected. This report examines several methods used for streamflow prediction in ungaged basins to determine the best methods for regional and national implementation. A pilot area in the southeastern United States was selected to apply 19 different streamflow prediction methods and evaluate each method by a wide set of performance metrics. Through these comparisons, two methods emerged as the most generally accurate streamflow prediction methods: the nearest-neighbor implementations of nonlinear spatial interpolation using flow duration curves (NN-QPPQ) and standardizing logarithms of streamflow by monthly means and standard deviations (NN-SMS12L). It was nearly impossible to distinguish between these two methods in terms of performance. Furthermore, neither of these methods requires significantly more parameterization in order to be applied: NN-SMS12L requires 24 regional regressions&mdash;12 for monthly means and 12 for monthly standard deviations. NN-QPPQ, in the application described in this study, required 27 regressions of particular quantiles along the flow duration curve. Despite this finding, the results suggest that an optimal streamflow prediction method depends on the intended application. Some methods are stronger overall, while some methods may be better at predicting particular statistics. The methods of analysis presented here reflect a possible framework for continued analysis and comprehensive multiple comparisons of methods of prediction in ungaged basins (PUB). Additional metrics of comparison can easily be incorporated into this type of analysis. By considering such a multifaceted approach, the top-performing models can easily be identified and considered for further research. The top-performing models can then provide a basis for future applications and explorations by scientists, engineers, managers, and practitioners to suit their own needs.</span></p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145231","collaboration":"In cooperation with the Department of the Interior WaterSMART Program","usgsCitation":"Farmer, W.H., Archfield, S.A., Over, T.M., Hay, L.E., LaFontaine, J., and Kiang, J.E., 2015, A comparison of methods to predict historical daily streamflow time series in the southeastern United States: U.S. Geological Survey Scientific Investigations Report 2014-5231, Report: vi, 34 p.; Appendixes A-C; Tables 1-7, https://doi.org/10.3133/sir20145231.","productDescription":"Report: vi, 34 p.; Appendixes A-C; Tables 1-7","numberOfPages":"44","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-057098","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":298452,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145231.jpg"},{"id":298445,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5231/"},{"id":298446,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5231/pdf/sir2014-5231.pdf","text":"Report","size":"1.14 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":298447,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5231/appendix/sir2014-5231_appendixa.pdf","text":"Appendix A","size":"59.2 KB","linkFileType":{"id":1,"text":"pdf"},"description":"Appendix A","linkHelpText":"A summary of sites where small portions of the historical record were completed using alternative techniques."},{"id":298448,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5231/appendix/sir2014-5231_appendixb.pdf","text":"Appendix B","size":"200 KB","linkFileType":{"id":1,"text":"pdf"},"description":"Appendix B","linkHelpText":"A description of all basin characteristics considered as potential explanatory variables in the various regressions conducted as part of the Southeast Model Comparison."},{"id":298449,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5231/appendix/sir2014-5231_appendixc.pdf","text":"Appendix C","size":"309 KB","linkFileType":{"id":1,"text":"pdf"},"description":"Appendix C","linkHelpText":"Supplemental Data"},{"id":298450,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5231/appendix/sir2014-5231_appendixc_figures.pdf","text":"Appendix C Figures","size":"184 KB","linkFileType":{"id":1,"text":"pdf"},"description":"Appendix C Figures"},{"id":298451,"rank":7,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2014/5231/table/sir2014-5231_tables%201-7.pdf","text":"Tables 1-7","size":"185 KB","linkFileType":{"id":1,"text":"pdf"},"description":"Tables 1-7","linkHelpText":"Contains: Records for each streamgage used in the Southeast Model Comparsion, a listing of all names and abbreviations of prediction methods, root-mean-square error data, fitted coefficients and goodness-of-fit statistics, mean rank performance metric, and mean and standard deviation of average ranks for each method of prediction."}],"country":"United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -91.20849609375,\n              24.387127324604496\n            ],\n            [\n              -91.20849609375,\n              39.01064750994083\n            ],\n            [\n              -76.97021484375,\n              39.01064750994083\n            ],\n            [\n              -76.97021484375,\n              24.387127324604496\n            ],\n            [\n              -91.20849609375,\n              24.387127324604496\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"551a659ae4b03238427833e4","contributors":{"authors":[{"text":"Farmer, William H. 0000-0002-2865-2196 wfarmer@usgs.gov","orcid":"https://orcid.org/0000-0002-2865-2196","contributorId":4374,"corporation":false,"usgs":true,"family":"Farmer","given":"William","email":"wfarmer@usgs.gov","middleInitial":"H.","affiliations":[{"id":37778,"text":"WMA - 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Central Branch","active":true,"usgs":true}],"preferred":true,"id":542166,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"LaFontaine, Jacob H. jlafonta@usgs.gov","contributorId":138508,"corporation":false,"usgs":true,"family":"LaFontaine","given":"Jacob H.","email":"jlafonta@usgs.gov","affiliations":[],"preferred":false,"id":542167,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kiang, Julie E. 0000-0003-0653-4225 jkiang@usgs.gov","orcid":"https://orcid.org/0000-0003-0653-4225","contributorId":2179,"corporation":false,"usgs":true,"family":"Kiang","given":"Julie","email":"jkiang@usgs.gov","middleInitial":"E.","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":542168,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70137613,"text":"ds891 - 2015 - Wyoming greater sage-grouse habitat prioritization: A collection of multi-scale seasonal models and geographic information systems land management tools","interactions":[],"lastModifiedDate":"2017-12-27T15:13:45","indexId":"ds891","displayToPublicDate":"2015-03-11T10:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"891","title":"Wyoming greater sage-grouse habitat prioritization: A collection of multi-scale seasonal models and geographic information systems land management tools","docAbstract":"<p>With rapidly changing landscape conditions within Wyoming and the potential effects of landscape changes on sage-grouse habitat, land managers and conservation planners, among others, need procedures to assess the location and juxtaposition of important habitats, land-cover, and land-use patterns to balance wildlife requirements with multiple human land uses. Biologists frequently develop habitat-selection studies to identify prioritization efforts for species of conservation concern to increase understanding and help guide habitat-conservation efforts. Recently, the authors undertook a large-scale collaborative effort that developed habitat-selection models for Greater Sage-grouse (<i>Centrocercus urophasianus</i>) across large landscapes in Wyoming, USA and for multiple life-stages (nesting, late brood-rearing, and winter). We developed these habitat models using resource selection functions, based upon sage-grouse telemetry data collected for localized studies and within each life-stage. The models allowed us to characterize and spatially predict seasonal sage-grouse habitat use in Wyoming. Due to the quantity of models, the diversity of model predictors (in the form of geographic information system data) produced by analyses, and the variety of potential applications for these data, we present here a resource that complements our published modeling effort, which will further support land managers.</p>\n<p>We deliver all products described herein as online geographic information system data for visualization and downloading. We outline the data properties for each model and their data inputs, describe the process of selecting appropriate data products for multifarious applications, describe all data products and software, provide newly derived model composites, and discuss how land managers may use the models to inform future sage-grouse studies and potentially refine conservation efforts. The models, software tools, and associated opportunities for novel applications of these products should provide a suite of additional, but not exclusive, tools for assessing Wyoming Greater Sage-grouse habitats, which land managers, conservationists, and scientists can apply to myriad applications.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds891","usgsCitation":"O’Donnell, M.S., Aldridge, C.L., Doherty, K., and Fedy, B., 2015, Wyoming greater sage-grouse habitat prioritization: A collection of multi-scale seasonal models and geographic information systems land management tools: U.S. Geological Survey Data Series 891, Report: iv, 27 p.; Downloads Directory, https://doi.org/10.3133/ds891.","productDescription":"Report: iv, 27 p.; Downloads Directory","numberOfPages":"35","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-052571","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":298435,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds891.jpg"},{"id":298434,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/ds/0891/downloads/","text":"Downloads Directory","description":"Downloads Directory","linkHelpText":"Contains: geospatial database."},{"id":298433,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0891/pdf/ds891.pdf","text":"Report","size":"8.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":298425,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0891/"}],"country":"United States","state":"Wyoming","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -111.060791015625,\n              40.9964840143779\n            ],\n            [\n              -111.060791015625,\n              45.00365115687189\n            ],\n            [\n              -104.051513671875,\n              45.00365115687189\n            ],\n            [\n              -104.051513671875,\n              40.9964840143779\n            ],\n            [\n              -111.060791015625,\n              40.9964840143779\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"551a65bee4b0323842783480","contributors":{"authors":[{"text":"O’Donnell, Michael S. 0000-0002-3488-003X odonnellm@usgs.gov","orcid":"https://orcid.org/0000-0002-3488-003X","contributorId":3351,"corporation":false,"usgs":true,"family":"O’Donnell","given":"Michael","email":"odonnellm@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":542119,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aldridge, Cameron L. 0000-0003-3926-6941 aldridgec@usgs.gov","orcid":"https://orcid.org/0000-0003-3926-6941","contributorId":191773,"corporation":false,"usgs":true,"family":"Aldridge","given":"Cameron","email":"aldridgec@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":542120,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Doherty, Kevin E.","contributorId":62452,"corporation":false,"usgs":true,"family":"Doherty","given":"Kevin E.","affiliations":[],"preferred":false,"id":542122,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fedy, Bradley C.","contributorId":40536,"corporation":false,"usgs":true,"family":"Fedy","given":"Bradley C.","affiliations":[],"preferred":false,"id":542121,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70139794,"text":"sir20155008 - 2015 - Water-quality trends for selected sites in the Boulder River and Tenmile Creek watersheds, Montana, based on data collected during water years 1997-2013","interactions":[],"lastModifiedDate":"2015-03-11T10:53:50","indexId":"sir20155008","displayToPublicDate":"2015-03-11T10:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-5008","title":"Water-quality trends for selected sites in the Boulder River and Tenmile Creek watersheds, Montana, based on data collected during water years 1997-2013","docAbstract":"<p>In the Boulder River and Tenmile Creek watersheds in southwestern Montana, there was intensive mining during a 40-year period after the discovery of gold in the early 1860s. Potential effects from the historic mining activities include acid-mine drainage and elevated concentrations of potentially toxic trace elements from mining remnants such as waste rock and tailing piles. In support of remediation efforts, water-quality monitoring by the U.S. Geological Survey began in 1997 in the Boulder River and Tenmile Creek watersheds and has continued to present (2014). The U.S. Geological Survey, in cooperation with the U.S. Forest Service, investigated temporal trends in water quality at 13 sites, including 2 adit (or mine entrance) sites and 11 stream sites. The primary purpose of this report is to present results of trend analysis of specific conductance, selected trace-elements (cadmium, copper, lead, zinc, and arsenic), and suspended sediment for the 13 sites.</p>\n<p>Trend results for most stream sites in the Boulder River watershed for water years 2000&ndash;13 (water year is the 12-month period from October 1 through September 30 and is designated by the year in which it ends) indicate decreasing trends in flow-adjusted specific conductance, in flow-adjusted concentrations (FACs) for most filtered and unfiltered-recoverable trace elements, and in suspended sediment. Overall, magnitudes of the decreasing trends in FACs of metallic contaminants are largest for Bullion Mine tributary at mouth (site 3), Jack Creek at mouth (site 4), and Cataract Creek at Basin (site 8). For sites 3, 4, and 8, magnitudes of decreasing trends generally ranged from about -5 to -10 percent per year. Notably, the watersheds upstream from sites 3, 4, and 8 have been targeted by substantial remediation activities. Consideration of trend patterns among all stream sites in the Boulder River watershed provides strong evidence that remediation activities are the primary cause of decreasing trends in metallic contaminants.</p>\n<p>Trend results for sites in the Tenmile Creek watershed generally are more variable and difficult to interpret than for sites in the Boulder River watershed. Trend results for Tenmile Creek above City Diversion (site 11) and Minnehaha Creek near Rimini (site 12) for water years 2000&ndash;13 indicate decreasing trends in FACs of cadmium, copper, and zinc. The magnitudes of the decreasing trends in FACs of copper generally are moderate and statistically significant for sites 11 and 12. The magnitudes of the decreasing trends in FACs of cadmium and zinc for site 11 are minor to small and not statistically significant; however, the magnitudes for site 12 are moderate and statistically significant. In general, patterns in FACs for Tenmile Creek near Rimini (site 13) are not well represented by fitted trends within the short data collection period, which might indicate that the trend-analysis structure of the study is not appropriate for describing trends in FACs for site 13. The large decreasing trend in FACs of suspended sediment is the strongest indication of change in water quality during the short period of record for site 13; however, this trend is not statistically significant.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155008","collaboration":"Prepared in cooperation with the U.S. Forest Service","usgsCitation":"Sando, S.K., Clark, M.L., Cleasby, T., and Barnhart, E.P., 2015, Water-quality trends for selected sites in the Boulder River and Tenmile Creek watersheds, Montana, based on data collected during water years 1997-2013: U.S. Geological Survey Scientific Investigations Report 2015-5008, Report: x, 46 p.; Appendix 1 tables; Appendix 2 table; Appendix 3 tables; Appendix 3 figures, https://doi.org/10.3133/sir20155008.","productDescription":"Report: x, 46 p.; Appendix 1 tables; Appendix 2 table; Appendix 3 tables; Appendix 3 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,{"id":70142756,"text":"70142756 - 2015 - Modelling non-Euclidean movement and landscape connectivity in highly structured ecological networks","interactions":[],"lastModifiedDate":"2015-03-11T10:23:50","indexId":"70142756","displayToPublicDate":"2015-03-11T10:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2717,"text":"Methods in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Modelling non-Euclidean movement and landscape connectivity in highly structured ecological networks","docAbstract":"<ol id=\"list-0001\" class=\"numbered\">\n<li>Movement is influenced by landscape structure, configuration and geometry, but measuring distance as perceived by animals poses technical and logistical challenges. Instead, movement is typically measured using Euclidean distance, irrespective of location or landscape structure, or is based on arbitrary cost surfaces. A recently proposed extension of spatial capture-recapture (SCR) models resolves this issue using spatial encounter histories of individuals to calculate least-cost paths (ecological distance:&nbsp;<i>Ecology</i>,<strong>&nbsp;94</strong>, 2013, 287) thereby relaxing the Euclidean assumption. We evaluate the consequences of not accounting for movement heterogeneity when estimating abundance in highly structured landscapes, and demonstrate the value of this approach for estimating biologically realistic space-use patterns and landscape connectivity.</li>\n<li>We simulated SCR data in a riparian habitat network, using the ecological distance model under a range of scenarios where space-use in and around the landscape was increasingly associated with water (i.e. increasingly less Euclidean). To assess the influence of miscalculating distance on estimates of population size, we compared the results from the ecological and Euclidean distance based models. We then demonstrate that the ecological distance model can be used to estimate home range geometry when space use is not symmetrical. Finally, we provide a method for calculating landscape connectivity based on modelled species-landscape interactions generated from capture-recapture data.</li>\n<li>Using ecological distance always produced unbiased estimates of abundance. Explicitly modelling the strength of the species-landscape interaction provided a direct measure of landscape connectivity and better characterised true home range geometry. Abundance under the Euclidean distance model was increasingly (negatively) biased as space use was more strongly associated with water and, because home ranges are assumed to be symmetrical, produced poor characterisations of home range geometry and no information about landscape connectivity.</li>\n<li>The ecological distance SCR model uses spatially indexed capture-recapture data to estimate how activity patterns are influenced by landscape structure. As well as reducing bias in estimates of abundance, this approach provides biologically realistic representations of home range geometry, and direct information about species-landscape interactions. The incorporation of both structural (landscape) and functional (movement) components of connectivity provides a direct measure of species-specific landscape connectivity.</li>\n</ol>","language":"English","publisher":"Wiley-Blackwell Publishing Ltd.","publisherLocation":"Hoboken, NJ","doi":"10.1111/2041-210X.12316","usgsCitation":"Sutherland, C., Fuller, A.K., and Royle, J., 2015, Modelling non-Euclidean movement and landscape connectivity in highly structured ecological networks: Methods in Ecology and Evolution, v. 6, no. 2, p. 169-177, https://doi.org/10.1111/2041-210X.12316.","productDescription":"9 p.","startPage":"169","endPage":"177","numberOfPages":"9","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060023","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":472213,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/2041-210x.12316","text":"Publisher Index Page"},{"id":298416,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","issue":"2","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2014-12-30","publicationStatus":"PW","scienceBaseUri":"551a65b0e4b032384278343e","contributors":{"authors":[{"text":"Sutherland, Christopher","contributorId":139624,"corporation":false,"usgs":false,"family":"Sutherland","given":"Christopher","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":542114,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fuller, Angela K. 0000-0002-9247-7468 afuller@usgs.gov","orcid":"https://orcid.org/0000-0002-9247-7468","contributorId":3984,"corporation":false,"usgs":true,"family":"Fuller","given":"Angela","email":"afuller@usgs.gov","middleInitial":"K.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":542112,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":139623,"corporation":false,"usgs":true,"family":"Royle","given":"J. Andrew","email":"aroyle@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":542111,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70173530,"text":"70173530 - 2015 - Quantifying avian predation on fish populations: integrating predator-specific deposition probabilities in tag-recovery studies","interactions":[],"lastModifiedDate":"2016-06-09T15:28:46","indexId":"70173530","displayToPublicDate":"2015-03-11T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Quantifying avian predation on fish populations: integrating predator-specific deposition probabilities in tag-recovery studies","docAbstract":"<p><span>Accurate assessment of specific mortality factors is vital to prioritize recovery actions for threatened and endangered species. For decades, tag recovery methods have been used to estimate fish mortality due to avian predation. Predation probabilities derived from fish tag recoveries on piscivorous waterbird colonies typically reflect minimum estimates of predation due to an unknown and unaccounted-for fraction of tags that are consumed but not deposited on-colony (i.e., deposition probability). We applied an integrated tag recovery modeling approach in a Bayesian context to estimate predation probabilities that accounted for predator-specific tag detection and deposition probabilities in a multiple-predator system. Studies of PIT tag deposition were conducted across three bird species nesting at seven different colonies in the Columbia River basin, USA. Tag deposition probabilities differed significantly among predator species (Caspian terns</span><i>Hydroprogne caspia</i><span>: deposition probability = 0.71, 95% credible interval [CRI] = 0.51&ndash;0.89; double-crested cormorants&nbsp;</span><i>Phalacrocorax auritus</i><span>: 0.51, 95% CRI = 0.34&ndash;0.70; California gulls&nbsp;</span><i>Larus californicus</i><span>: 0.15, 95% CRI = 0.11&ndash;0.21) but showed little variation across trials within a species or across years. Data from a 6-year study (2008&ndash;2013) of PIT-tagged juvenile Snake River steelhead&nbsp;</span><i>Oncorhynchus mykiss</i><span>&nbsp;(listed as threatened under the Endangered Species Act) indicated that colony-specific predation probabilities ranged from less than 0.01 to 0.17 and varied by predator species, colony location, and year. Integrating the predator-specific deposition probabilities increased the predation probabilities by a factor of approximately 1.4 for Caspian terns, 2.0 for double-crested cormorants, and 6.7 for California gulls compared with traditional minimum predation rate methods, which do not account for deposition probabilities. Results supported previous findings on the high predation impacts from strictly piscivorous waterbirds nesting in the Columbia River estuary (i.e., terns and cormorants), but our findings also revealed greater impacts of a generalist predator species (i.e., California gulls) than were previously documented. Approaches used in this study allow for direct comparisons among multiple fish mortality factors and considerably improve the reliability of tag recovery models for estimating predation probabilities in multiple-predator systems.</span></p>","language":"English","publisher":"Taylor & Francis","doi":"10.1080/00028487.2014.988882","usgsCitation":"Hostetter, N.J., Evans, A.F., Cramer, B.M., Collis, K., Lyons, D., and Roby, D.D., 2015, Quantifying avian predation on fish populations: integrating predator-specific deposition probabilities in tag-recovery studies: Transactions of the American Fisheries Society, v. 144, no. 2, p. 410-422, https://doi.org/10.1080/00028487.2014.988882.","productDescription":"13 p.","startPage":"410","endPage":"422","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-058968","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":472214,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://figshare.com/articles/journal_contribution/Quantifying_Avian_Predation_on_Fish_Populations_Integrating_Predator_Specific_Deposition_Probabilities_in_Tag_Recovery_Studies/1332455","text":"External Repository"},{"id":323421,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"144","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-03-11","publicationStatus":"PW","scienceBaseUri":"575a9335e4b04f417c275178","contributors":{"authors":[{"text":"Hostetter, Nathan J.","contributorId":171690,"corporation":false,"usgs":false,"family":"Hostetter","given":"Nathan","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":638312,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Evans, Allen F.","contributorId":171691,"corporation":false,"usgs":false,"family":"Evans","given":"Allen","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":638313,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cramer, Bradley M.","contributorId":171692,"corporation":false,"usgs":false,"family":"Cramer","given":"Bradley","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":638314,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Collis, Ken","contributorId":149991,"corporation":false,"usgs":false,"family":"Collis","given":"Ken","email":"","affiliations":[{"id":17879,"text":"Real Time Research, Inc., 231 SW Scalehouse Loop, Suite 101, Bend, OR 97702","active":true,"usgs":false}],"preferred":false,"id":638315,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lyons, Donald E.","contributorId":20119,"corporation":false,"usgs":true,"family":"Lyons","given":"Donald E.","affiliations":[],"preferred":false,"id":638316,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Roby, Daniel D. 0000-0001-9844-0992 droby@usgs.gov","orcid":"https://orcid.org/0000-0001-9844-0992","contributorId":3702,"corporation":false,"usgs":true,"family":"Roby","given":"Daniel","email":"droby@usgs.gov","middleInitial":"D.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":637266,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70142371,"text":"ofr20151025 - 2015 - Geochemical maps of stream sediments in central Colorado, from New Mexico to Wyoming","interactions":[],"lastModifiedDate":"2015-05-04T10:18:12","indexId":"ofr20151025","displayToPublicDate":"2015-03-10T15:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-1025","title":"Geochemical maps of stream sediments in central Colorado, from New Mexico to Wyoming","docAbstract":"<p><span>The U.S. Geological Survey has completed a series of geologic, mineral resource, and environmental assessment studies in the Rocky Mountains of central Colorado, from Leadville eastward to the range front and from New Mexico to the Wyoming border. Regional stream-sediment geochemical maps, useful for assessing mineral resources and environmental effects of historical mining activities, were produced as part of the study. The data portrayed in this 56-parameter portfolio of landscape geochemical maps serve as a geochemical baseline for the region, indicate element abundances characteristic of various lithologic terranes, and identify gross anthropogenic effects of historical mining. However, although reanalyzed in this study by modern, sensitive methods, the majority of the stream-sediment samples were collected in the 1970s. Thus, metal concentrations portrayed in these maps represent stream-sediment geochemistry at the time of collection.</span></p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151025","usgsCitation":"Eppinger, R.G., Giles, S.A., and Klein, T.L., 2015, Geochemical maps of stream sediments in central Colorado, from New Mexico to Wyoming: U.S. Geological Survey Open-File Report 2015-1025, Report: viii, 120 p.; Downloads Directory, https://doi.org/10.3133/ofr20151025.","productDescription":"Report: viii, 120 p.; Downloads Directory","numberOfPages":"131","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-054650","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":298413,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20151025.jpg"},{"id":298411,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1025/pdf/ofr2015-1025.pdf","size":"54.1 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":298410,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2015/1025/"},{"id":298412,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2015/1025/downloads/","text":"Downloads Directory"}],"country":"United States","state":"Colorado","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -106.6168212890625,\n              41.00270266805319\n            ],\n            [\n              -105.14190673828125,\n              41.00270266805319\n            ],\n            [\n              -105.1556396484375,\n              39.76210275375137\n            ],\n            [\n              -104.9853515625,\n              39.757879992021756\n            ],\n            [\n              -104.9908447265625,\n              39.38526381099774\n            ],\n            [\n              -104.83154296875,\n              39.38738660316804\n            ],\n            [\n              -104.853515625,\n              36.99377838872517\n            ],\n            [\n              -105.99884033203125,\n              36.99158465967016\n            ],\n            [\n              -105.985107421875,\n              38.37396220263092\n            ],\n            [\n              -106.64978027343749,\n              38.3868805698475\n            ],\n            [\n              -106.6168212890625,\n              41.00270266805319\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55000799e4b02419550fa5cd","contributors":{"authors":[{"text":"Eppinger, Robert G. eppinger@usgs.gov","contributorId":849,"corporation":false,"usgs":true,"family":"Eppinger","given":"Robert","email":"eppinger@usgs.gov","middleInitial":"G.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":541851,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Giles, Stuart A. 0000-0002-8696-5078 sgiles@usgs.gov","orcid":"https://orcid.org/0000-0002-8696-5078","contributorId":1233,"corporation":false,"usgs":true,"family":"Giles","given":"Stuart","email":"sgiles@usgs.gov","middleInitial":"A.","affiliations":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":541850,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Klein, Terry L. tklein@usgs.gov","contributorId":1244,"corporation":false,"usgs":true,"family":"Klein","given":"Terry","email":"tklein@usgs.gov","middleInitial":"L.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":541852,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70142660,"text":"tm13A2 - 2015 - A multipurpose camera system for monitoring Kīlauea Volcano, Hawai'i","interactions":[],"lastModifiedDate":"2015-03-10T10:23:46","indexId":"tm13A2","displayToPublicDate":"2015-03-10T11:15:00","publicationYear":"2015","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":"13-A2","title":"A multipurpose camera system for monitoring Kīlauea Volcano, Hawai'i","docAbstract":"<p><span>We describe a low-cost, compact multipurpose camera system designed for field deployment at active volcanoes that can be used either as a webcam (transmitting images back to an observatory in real-time) or as a time-lapse camera system (storing images onto the camera system for periodic retrieval during field visits). The system also has the capability to acquire high-definition video. The camera system uses a Raspberry Pi single-board computer and a 5-megapixel low-light (near-infrared sensitive) camera, as well as a small Global Positioning System (GPS) module to ensure accurate time-stamping of images. Custom Python scripts control the webcam and GPS unit and handle data management. The inexpensive nature of the system allows it to be installed at hazardous sites where it might be lost. Another major advantage of this camera system is that it provides accurate internal timing (independent of network connection) and, because a full Linux operating system and the Python programming language are available on the camera system itself, it has the versatility to be configured for the specific needs of the user. We describe example deployments of the camera at Kīlauea Volcano, Hawai&lsquo;i, to monitor ongoing summit lava lake activity.&nbsp;</span></p>","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Section A: Methods Used in Volcano Monitoring in Book 13 <i>Volcano Monitoring</i>","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm13A2","usgsCitation":"Patrick, M.R., Orr, T.R., Lee, L., and Moniz, C.J., 2015, A multipurpose camera system for monitoring Kīlauea Volcano, Hawai'i: U.S. Geological Survey Techniques and Methods 13-A2, Report: iv, 25 p.; 6 videos, https://doi.org/10.3133/tm13A2.","productDescription":"Report: iv, 25 p.; 6 videos","numberOfPages":"34","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-055070","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":298406,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/tm13a2.gif"},{"id":298393,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/tm/13/a2/"},{"id":298399,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/13/a2/tm13-A2.pdf","size":"7.9 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":298400,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/tm/13/a2/videos/TM_13-A2_video01.mov","text":"Halema'uma'u plume time-lapse MOV","size":"54.7 MB","linkHelpText":"This video shows an image every 10 minutes, from February 3, 2014, at 0001 Hawai‘i Standard Time (HST) to February 9, 2014, at 2359 HST. The movie shows the commonly fluctuating wind directions typical of winter months, when the normally steady trade winds become unstable. The camera was positioned in the Hawaiian Volcano Observatory observation tower. In the lower right corner of the image is the public overlook at Jaggar Museum."},{"id":298403,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/tm/13/a2/videos/TM_13-A2_video02.mp4","text":"Halema'uma'u lake time-lapse MP4","size":"7.4 MB","linkHelpText":"This video shows an image every minute, from February 14, 2014, at 1200 Hawai‘i Standard Time (HST) to February 15, 2014, at 1200 HST. The plot of RSAM (real-time seismic amplitude measurement), which can be taken as a proxy for the amplitude of seismic tremor, is shown below. Spikes in RSAM correspond with the appearance of additional spattering sources on the lake margin, whereas the sustained low level in RSAM after about 0800 on February 15 is an indicator of the absence of spattering at the lake and very quiet activity."},{"id":298404,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/tm/13/a2/videos/TM_13-A2_video03.mov","text":"Halema'uma'u lake video clips MOV","size":"20.2 MB","linkHelpText":"Four clips from February 2014 are shown, taken at the following times: (1) February 14, 1200 Hawai‘i Standard Time (HST); (2) February 14, 1800 HST; (3) February 15, 0000 HST; (4) February 15, 0600 HST.  Videos are shown at 3× speed."},{"id":298405,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/tm/13/a2/videos/TM_13-A2_video03.mp4","text":"Halema'uma'u lake video clips MP4","size":"4.7 MB","linkHelpText":"Four clips from February 2014 are shown, taken at the following times: (1) February 14, 1200 Hawai‘i Standard Time (HST); (2) February 14, 1800 HST; (3) February 15, 0000 HST; (4) February 15, 0600 HST.  Videos are shown at 3× speed."},{"id":298401,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/tm/13/a2/videos/TM_13-A2_video01.mp4","text":"Halema'uma'u plume time-lapse MP4","size":"14.9 MB","linkHelpText":"This video shows an image every 10 minutes, from February 3, 2014, at 0001 Hawai‘i Standard Time (HST) to February 9, 2014, at 2359 HST. The movie shows the commonly fluctuating wind directions typical of winter months, when the normally steady trade winds become unstable. The camera was positioned in the Hawaiian Volcano Observatory observation tower. In the lower right corner of the image is the public overlook at Jaggar Museum."},{"id":298402,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/tm/13/a2/videos/TM_13-A2_video02.mov","text":"Halema'uma'u lake time-lapse MOV","size":"19.1 MB","linkHelpText":"This video shows an image every minute, from February 14, 2014, at 1200 Hawai‘i Standard Time (HST) to February 15, 2014, at 1200 HST. The plot of RSAM (real-time seismic amplitude measurement), which can be taken as a proxy for the amplitude of seismic tremor, is shown below. Spikes in RSAM correspond with the appearance of additional spattering sources on the lake margin, whereas the sustained low level in RSAM after about 0800 on February 15 is an indicator of the absence of spattering at the lake and very quiet activity."}],"country":"United States","state":"Hawai'i","otherGeospatial":"Kīlauea Volcano","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -155.29483795166016,\n              19.405887684701234\n            ],\n            [\n              -155.29483795166016,\n              19.43535245949092\n            ],\n            [\n              -155.2558708190918,\n              19.43535245949092\n            ],\n            [\n              -155.2558708190918,\n              19.405887684701234\n            ],\n            [\n              -155.29483795166016,\n              19.405887684701234\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","publicComments":"This report is Chapter 2 of Section A: Methods Used in Volcano Monitoring in Book 13 <i>Volcano Monitoring</i>.","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55000798e4b02419550fa5cb","contributors":{"authors":[{"text":"Patrick, Matthew R. 0000-0002-8042-6639 mpatrick@usgs.gov","orcid":"https://orcid.org/0000-0002-8042-6639","contributorId":2070,"corporation":false,"usgs":true,"family":"Patrick","given":"Matthew","email":"mpatrick@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":542091,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Orr, Tim R. torr@usgs.gov","contributorId":139620,"corporation":false,"usgs":true,"family":"Orr","given":"Tim","email":"torr@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":false,"id":542092,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lee, Lopaka","contributorId":83167,"corporation":false,"usgs":true,"family":"Lee","given":"Lopaka","email":"","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":false,"id":542093,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Moniz, Cyril J. cjmoniz@usgs.gov","contributorId":5291,"corporation":false,"usgs":true,"family":"Moniz","given":"Cyril","email":"cjmoniz@usgs.gov","middleInitial":"J.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":542094,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70140150,"text":"fs20153009 - 2015 - UCERF3: A new earthquake forecast for California's complex fault system","interactions":[],"lastModifiedDate":"2015-03-17T08:48:30","indexId":"fs20153009","displayToPublicDate":"2015-03-10T10:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-3009","title":"UCERF3: A new earthquake forecast for California's complex fault system","docAbstract":"<p>With innovations, fresh data, and lessons learned from recent earthquakes, scientists have developed a new earthquake forecast model for California, a region under constant threat from potentially damaging events. The new model, referred to as the third Uniform California Earthquake Rupture Forecast, or \"UCERF\" (<a href=\"http://www.WGCEP.org/UCERF3\">http://www.WGCEP.org/UCERF3</a>), provides authoritative estimates of the magnitude, location, and likelihood of earthquake fault rupture throughout the state. Overall the results confirm previous findings, but with some significant changes because of model improvements. For example, compared to the previous forecast (Uniform California Earthquake Rupture Forecast 2), the likelihood of moderate-sized earthquakes (magnitude 6.5 to 7.5) is lower, whereas that of larger events is higher. This is because of the inclusion of multifault ruptures, where earthquakes are no longer confined to separate, individual faults, but can occasionally rupture multiple faults simultaneously. The public-safety implications of this and other model improvements depend on several factors, including site location and type of structure (for example, family dwelling compared to a long-span bridge). Building codes, earthquake insurance products, emergency plans, and other risk-mitigation efforts will be updated accordingly. This model also serves as a reminder that damaging earthquakes are inevitable for California. Fortunately, there are many simple steps residents can take to protect lives and property.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20153009","usgsCitation":"Field, E.H., and 2014 Working Group on California Earthquake Probabilities, 2015, UCERF3: A new earthquake forecast for California's complex fault system: U.S. Geological Survey Fact Sheet 2015-3009, 6 p., https://doi.org/10.3133/fs20153009.","productDescription":"6 p.","numberOfPages":"6","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-062714","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":298397,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20153009.jpg"},{"id":298396,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2015/3009/pdf/fs2015-3009.pdf","text":"Report","size":"32.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2015-3009 Report"},{"id":298394,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2015/3009/"}],"country":"United States","state":"California","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -124.365234375,\n              42.00032514831621\n            ],\n            [\n              -119.970703125,\n              42.01665183556825\n            ],\n            [\n              -119.94873046875,\n              39.07890809706475\n            ],\n            [\n              -114.63134765625001,\n              35.10193405724606\n            ],\n            [\n              -113.9501953125,\n              34.23451236236984\n            ],\n            [\n              -114.3896484375,\n              32.731840896865684\n            ],\n            [\n              -117.18017578125,\n              32.52828936482526\n            ],\n            [\n              -117.53173828125,\n              33.119150226768866\n            ],\n            [\n              -119.64111328125,\n              34.27083595165\n            ],\n            [\n              -120.82763671875,\n              34.379712580462204\n            ],\n            [\n              -123.90380859374999,\n              38.94232097947902\n            ],\n            [\n              -124.49707031249999,\n              40.38002840251183\n            ],\n            [\n              -124.365234375,\n              42.00032514831621\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55000799e4b02419550fa5cf","contributors":{"authors":[{"text":"Field, Edward H. 0000-0001-8172-7882 field@usgs.gov","orcid":"https://orcid.org/0000-0001-8172-7882","contributorId":52242,"corporation":false,"usgs":true,"family":"Field","given":"Edward","email":"field@usgs.gov","middleInitial":"H.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":542095,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"2014 Working Group on California Earthquake Probabilities","contributorId":139622,"corporation":true,"usgs":false,"organization":"2014 Working Group on California Earthquake Probabilities","id":542098,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
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