{"pageNumber":"580","pageRowStart":"14475","pageSize":"25","recordCount":46856,"records":[{"id":70046435,"text":"sir20135113 - 2013 - A historical perspective on precipitation, drought severity, and streamflow in Texas during 1951-56 and 2011","interactions":[],"lastModifiedDate":"2016-08-05T13:23:40","indexId":"sir20135113","displayToPublicDate":"2013-06-11T00:00:00","publicationYear":"2013","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":"2013-5113","title":"A historical perspective on precipitation, drought severity, and streamflow in Texas during 1951-56 and 2011","docAbstract":"<p>The intense drought throughout Texas during 2011 resulted in substantial declines in streamflow. By April 2011, nearly all of the State was experiencing severe to extreme drought according to data from the University of Nebraska&ndash;Lincoln Drought Monitor. By the end of July 2011, more than 75 percent of the State was experiencing exceptional drought. The worst of the drought occurred around October 4, 2011, when 97 percent of Texas was suffering from extreme to exceptional drought. The historical drought of 1951&ndash;56 has long been used by water-resource managers, engineers, and scientists as a point of reference for water-supply planning. A comparison of drought conditions during the 2011 water year (October 1, 2010, through September 30, 2011) to the historical drought of 1951&ndash;56 from a hydrologic perspective serves as an additional reference for water-supply planning.</p>\n<p>A record low statewide average annual precipitation of 11.27 inches for the period 1895&ndash;2011 was recorded during the 2011 water year; the prior record low statewide average precipitation was 13.91 inches during the 1956 water year. The statewide monthly Palmer Drought Severity Index (PDSI) declined to -7.93 during September 2011, which was larger in magnitude than the statewide PDSI during any drought-affected month in the 1950s.</p>\n<p>Annual mean streamflow and streamflow-duration curves for the 1951&ndash;56 and 2011 water years were assessed for 19 unregulated U.S. Geological Survey (USGS) streamflow-gaging stations. At eight of these streamflow-gaging stations, the annual mean streamflow was lower in 2011 than for any year during 1951&ndash;56; many of these stations are located in eastern Texas. Annual mean streamflows for streamflow-gaging stations in the Guadalupe, Blanco, and upper Frio River Basins were lower in 1956 than in 2011. The streamflow-duration curves for many streamflow-gaging stations indicate a lack of (or diminished) storm runoff during 2011. Low streamflows (those exceeded 90 to 95 percent of days) were lower for 1956 than for 2011 at seven streamflow-gaging stations. For most of these stations, the lowest of the low streamflows during 1951&ndash;56 occurred in 1956. During March to September 2011, record daily lows were measured at USGS streamflow-gaging station 08041500 Village Creek near Kountze, Tex., which has more than 70 years of record. Many other USGS streamflow-gaging stations in Texas started the 2011 water year with normal streamflow but by the end of the water year were flowing at near-record lows.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135113","collaboration":"Prepared in cooperation with the Texas Water Development Board","usgsCitation":"Winters, K.E., 2013, A historical perspective on precipitation, drought severity, and streamflow in Texas during 1951-56 and 2011: U.S. Geological Survey Scientific Investigations Report 2013-5113, v, 24 p., https://doi.org/10.3133/sir20135113.","productDescription":"v, 24 p.","numberOfPages":"34","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"1951-01-01","temporalEnd":"2011-12-31","ipdsId":"IP-044869","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":273629,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135113.jpg"},{"id":273627,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5113/"},{"id":273628,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5113/pdf/sir20135113.pdf"}],"country":"United States","state":"Texas","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -106.6,25.8 ], [ -106.6,36.5 ], [ -93.5,36.5 ], [ -93.5,25.8 ], [ -106.6,25.8 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51b838d1e4b03203c522b17a","contributors":{"authors":[{"text":"Winters, Karl E. kwinters@usgs.gov","contributorId":3554,"corporation":false,"usgs":true,"family":"Winters","given":"Karl","email":"kwinters@usgs.gov","middleInitial":"E.","affiliations":[],"preferred":true,"id":479648,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70046402,"text":"fs20133030 - 2013 - Water resources of St. Bernard Parish, Louisiana","interactions":[],"lastModifiedDate":"2026-06-10T20:40:15.590115","indexId":"fs20133030","displayToPublicDate":"2013-06-11T00:00:00","publicationYear":"2013","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":"2013-3030","title":"Water resources of St. Bernard Parish, Louisiana","docAbstract":"In 2010, about 261 million gallons per day (Mgal/d) of water were withdrawn in St. Bernard Parish, Louisiana, almost entirely from surface-water sources. Industrial use accounted for about 97 percent (253 Mgal/d) of the total water withdrawn. Other categories of use included public supply, rural domestic, and livestock. Water-use data collected at 5-year intervals from 1960 to 2010 indicated that total water withdrawals in the parish ranged from about 138 to 720 Mgal/d, with industrial use of surface water making up the bulk of water withdrawals. The large decline in surface-water withdrawals from 1980 to 1985 was largely attributable to a decrease in industrial use from 654 Mgal/d in 1980 to 127 Mgal/d in 1985.\n\nThis fact sheet summarizes basic information on the water resources of St. Bernard Parish. Information on groundwater and surface-water availability, quality, development, use, and trends is based on previously published reports listed in the Selected References section.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20133030","collaboration":"Prepared in cooperation with the Louisiana Department of Transportation and Development","usgsCitation":"Prakken, L., 2013, Water resources of St. Bernard Parish, Louisiana: U.S. Geological Survey Fact Sheet 2013-3030, 4 p., https://doi.org/10.3133/fs20133030.","productDescription":"4 p.","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"links":[{"id":505345,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_98548.htm","linkFileType":{"id":5,"text":"html"}},{"id":273597,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20133030.gif"},{"id":273595,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2013/3030/"},{"id":273596,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2013/3030/pdf/FS2013-3030_StBernard.pdf"}],"country":"United States","state":"Louisiana","county":"St. Bernard Parish","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -90.166666,29.333333 ], [ -90.166666,30.333333 ], [ -89.833333,30.333333 ], [ -89.833333,29.333333 ], [ -90.166666,29.333333 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51b838dee4b03203c522b1ae","contributors":{"authors":[{"text":"Prakken, Larry B.","contributorId":86673,"corporation":false,"usgs":true,"family":"Prakken","given":"Larry B.","affiliations":[],"preferred":false,"id":479619,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70046403,"text":"fs20133031 - 2013 - Water resources of Plaquemines Parish, Louisiana","interactions":[],"lastModifiedDate":"2026-06-10T20:41:55.99042","indexId":"fs20133031","displayToPublicDate":"2013-06-11T00:00:00","publicationYear":"2013","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":"2013-3031","title":"Water resources of Plaquemines Parish, Louisiana","docAbstract":"In 2010, about 85.1 million gallons per day (Mgal/d) of water were withdrawn in Plaquemines Parish, Louisiana. Surface-water sources accounted for almost all withdrawals; groundwater sources accounted for only 0.04 Mgal/d. Industrial use accounted for about 92 percent of the total water withdrawn. Other categories of use included public supply, rural domestic, and livestock. Water-use data collected at 5-year intervals from 1960 to 2010 indicated that water withdrawals in Plaquemines Parish peaked at about 177 Mgal/d in 1975. The peak resulted primarily from an increase in industrial surface-water withdrawals from about 23.8 Mgal/d in 1970 to 171 Mgal/d in 1975. Since 1975, water withdrawals have ranged from about 157 to 85.1 Mgal/d, with industrial surface-water withdrawals accounting for most of the variation.\n\nThis fact sheet summarizes basic information on the water resources of Plaquemines Parish. Information on groundwater and surface-water availability, quality, development, use, and trends is based on previously published reports listed in the Selected References section.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20133031","collaboration":"Prepared in cooperation with the Louisiana Department of Transportation and Development","usgsCitation":"Prakken, L., 2013, Water resources of Plaquemines Parish, Louisiana: U.S. Geological Survey Fact Sheet 2013-3031, 6 p., https://doi.org/10.3133/fs20133031.","productDescription":"6 p.","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"links":[{"id":505349,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_98549.htm","linkFileType":{"id":5,"text":"html"}},{"id":273599,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2013/3031/pdf/FS2013-3031_Plaquemines.pdf"},{"id":273598,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2013/3031/"},{"id":273600,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20133031.gif"}],"country":"United States","state":"Louisiana","county":"Plaquemines Parish","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -90.166666,29.833333 ], [ -90.166666,30.166666 ], [ -89.833333,30.166666 ], [ -89.833333,29.833333 ], [ -90.166666,29.833333 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51b838dee4b03203c522b1aa","contributors":{"authors":[{"text":"Prakken, Larry B.","contributorId":86673,"corporation":false,"usgs":true,"family":"Prakken","given":"Larry B.","affiliations":[],"preferred":false,"id":479620,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70189759,"text":"70189759 - 2013 - Inferring fault rheology from low-frequency earthquakes on the San Andreas","interactions":[],"lastModifiedDate":"2019-03-25T13:57:48","indexId":"70189759","displayToPublicDate":"2013-06-11T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2312,"text":"Journal of Geophysical Research","active":true,"publicationSubtype":{"id":10}},"title":"Inferring fault rheology from low-frequency earthquakes on the San Andreas","docAbstract":"<p><span>Families of recurring low-frequency earthquakes (LFEs) within nonvolcanic tremor (NVT) on the San Andreas fault in central California show strong sensitivity to shear stress induced by the daily tidal cycle. LFEs occur at all levels of the tidal shear stress and are in phase with the very small, ~400 Pa, stress amplitude. To quantitatively explain the correlation, we use a model from the existing literature that assumes the LFE sources are small, persistent regions that repeatedly fail during shear of a much larger scale, otherwise aseismically creeping fault zone. The LFE source patches see tectonic loading, creep of the surrounding fault which may be modulated by the tidal stress, and direct tidal loading. If the patches are small relative to the surrounding creeping fault then the stressing is dominated by fault creep, and if patch failure occurs at a threshold stress, then the resulting seismicity rate is proportional to the fault creep rate or fault zone strain rate. Using the seismicity rate as a proxy for strain rate and the tidal shear stress, we fit the data with possible fault rheologies that produce creep in laboratory experiments at temperatures of 400 to 600°C appropriate for the LFE source depth. The rheological properties of rock-forming minerals for dislocation creep and dislocation glide are not consistent with the observed fault creep because strong correlation between small stress perturbations and strain rate requires perturbation on the order of the ambient stress. The observed tidal modulation restricts ambient stress to be at most a few kilopascal, much lower than rock strength. A purely rate dependent friction is consistent with the observations only if the product of the friction rate dependence and effective normal stress is ~ 0.5 kPa. Extrapolating the friction rate strengthening dependence of phyllosilicates (talc) to depth would require the effective normal stress to be ~50 kPa, implying pore pressure is lithostatic. If the LFE source is on the order of tens of meters, as required by the model, rate-weakening friction rate dependence (e.g., olivine) at 400 to 600°C requires that the minimum effective pressure at the LFE source is ~ 2.5 MPa.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2013JB010118","usgsCitation":"Beeler, N.M., Thomas, A., Bürgmann, R., and Shelly, D.R., 2013, Inferring fault rheology from low-frequency earthquakes on the San Andreas: Journal of Geophysical Research, v. 118, no. 11, p. 5976-5990, https://doi.org/10.1002/2013JB010118.","productDescription":"15 p.","startPage":"5976","endPage":"5990","ipdsId":"IP-051647","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"links":[{"id":473756,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2013jb010118","text":"Publisher Index Page"},{"id":344245,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United  States","state":"California","otherGeospatial":"San Andreas fault","volume":"118","issue":"11","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2013-11-27","publicationStatus":"PW","scienceBaseUri":"59770755e4b0ec1a48889fc8","contributors":{"authors":[{"text":"Beeler, Nicholas M. 0000-0002-3397-8481 nbeeler@usgs.gov","orcid":"https://orcid.org/0000-0002-3397-8481","contributorId":2682,"corporation":false,"usgs":true,"family":"Beeler","given":"Nicholas","email":"nbeeler@usgs.gov","middleInitial":"M.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":true,"id":706225,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thomas, Amanda","contributorId":195086,"corporation":false,"usgs":false,"family":"Thomas","given":"Amanda","affiliations":[],"preferred":false,"id":706226,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bürgmann, Roland","contributorId":195087,"corporation":false,"usgs":false,"family":"Bürgmann","given":"Roland","affiliations":[],"preferred":false,"id":706227,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shelly, David R. dshelly@usgs.gov","contributorId":2978,"corporation":false,"usgs":true,"family":"Shelly","given":"David","email":"dshelly@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":706228,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70190217,"text":"70190217 - 2013 - Evidence of territoriality and species interactions from spatial point-pattern analyses of subarctic-nesting geese","interactions":[],"lastModifiedDate":"2017-08-20T10:43:36","indexId":"70190217","displayToPublicDate":"2013-06-11T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Evidence of territoriality and species interactions from spatial point-pattern analyses of subarctic-nesting geese","docAbstract":"<p><span>Quantifying spatial patterns of bird nests and nest fate provides insights into processes influencing a species’ distribution. At Cape Churchill, Manitoba, Canada, recent declines in breeding Eastern Prairie Population Canada geese (</span><i>Branta canadensis interior</i><span>) has coincided with increasing populations of nesting lesser snow geese (</span><i>Chen caerulescens caerulescens</i><span>) and Ross’s geese (</span><i>Chen rossii</i><span>). We conducted a spatial analysis of point patterns using Canada goose nest locations and nest fate, and lesser snow goose nest locations at two study areas in northern Manitoba with different densities and temporal durations of sympatric nesting Canada and lesser snow geese. Specifically, we assessed (1) whether Canada geese exhibited territoriality and at what scale and nest density; and (2) whether spatial patterns of Canada goose nest fate were associated with the density of nesting lesser snow geese as predicted by the protective-association hypothesis. Between 2001 and 2007, our data suggest that Canada geese were territorial at the scale of nearest neighbors, but were aggregated when considering overall density of conspecifics at slightly broader spatial scales. The spatial distribution of nest fates indicated that lesser snow goose nest proximity and density likely influence Canada goose nest fate. Our analyses of spatial point patterns suggested that continued changes in the distribution and abundance of breeding lesser snow geese on the Hudson Bay Lowlands may have impacts on the reproductive performance of Canada geese, and subsequently the spatial distribution of Canada goose nests.</span></p>","language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pone.0081029","usgsCitation":"Reiter, M., and Andersen, D., 2013, Evidence of territoriality and species interactions from spatial point-pattern analyses of subarctic-nesting geese: PLoS ONE, v. 8, no. 12, Article e81029: 10 p., https://doi.org/10.1371/journal.pone.0081029.","productDescription":"Article e81029: 10 p.","ipdsId":"IP-017802","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":473757,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0081029","text":"Publisher Index Page"},{"id":344978,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"12","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2013-12-02","publicationStatus":"PW","scienceBaseUri":"599a9fb6e4b0b589267d58b9","contributors":{"authors":[{"text":"Reiter, Matthew","contributorId":195769,"corporation":false,"usgs":false,"family":"Reiter","given":"Matthew","email":"","affiliations":[{"id":17734,"text":"Point Blue Conservation Science","active":true,"usgs":false}],"preferred":true,"id":708098,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Andersen, David E. 0000-0001-9535-3404 dea@usgs.gov","orcid":"https://orcid.org/0000-0001-9535-3404","contributorId":2168,"corporation":false,"usgs":true,"family":"Andersen","given":"David E.","email":"dea@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":34539,"text":"Minnesota Cooperative Fish and Wildlife Research Unit","active":true,"usgs":false}],"preferred":true,"id":708019,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70047853,"text":"70047853 - 2013 - A domain decomposition approach to implementing fault slip in finite-element models of quasi-static and dynamic crustal deformation","interactions":[],"lastModifiedDate":"2017-11-27T13:06:23","indexId":"70047853","displayToPublicDate":"2013-06-10T07:31:38","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2314,"text":"Journal of Geophysical Research B: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"A domain decomposition approach to implementing fault slip in finite-element models of quasi-static and dynamic crustal deformation","docAbstract":"We employ a domain decomposition approach with Lagrange multipliers to implement fault slip in a finite-element code, PyLith, for use in both quasi-static and dynamic crustal deformation applications. This integrated approach to solving both quasi-static and dynamic simulations leverages common finite-element data structures and implementations of various boundary conditions, discretization schemes, and bulk and fault rheologies. We have developed a custom preconditioner for the Lagrange multiplier portion of the system of equations that provides excellent scalability with problem size compared to conventional additive Schwarz methods. We demonstrate application of this approach using benchmarks for both quasi-static viscoelastic deformation and dynamic spontaneous rupture propagation that verify the numerical implementation in PyLith.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Geophysical Research B: Solid Earth","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"American Geophysical Union","doi":"10.1002/jgrb.50217","usgsCitation":"Aagaard, B.T., Knepley, M., and Williams, C., 2013, A domain decomposition approach to implementing fault slip in finite-element models of quasi-static and dynamic crustal deformation: Journal of Geophysical Research B: Solid Earth, v. 118, no. 6, p. 3059-3079, https://doi.org/10.1002/jgrb.50217.","productDescription":"21 p.","startPage":"3059","endPage":"3079","ipdsId":"IP-045732","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":473758,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://arxiv.org/abs/1308.5846","text":"External Repository"},{"id":277066,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":277064,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/jgrb.50217"}],"volume":"118","issue":"6","noUsgsAuthors":false,"publicationDate":"2013-06-10","publicationStatus":"PW","scienceBaseUri":"521f1be0e4b0f8bf2b0760b9","contributors":{"authors":[{"text":"Aagaard, Brad T. 0000-0002-8795-9833 baagaard@usgs.gov","orcid":"https://orcid.org/0000-0002-8795-9833","contributorId":192869,"corporation":false,"usgs":true,"family":"Aagaard","given":"Brad","email":"baagaard@usgs.gov","middleInitial":"T.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":false,"id":483151,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Knepley, M.G.","contributorId":76634,"corporation":false,"usgs":true,"family":"Knepley","given":"M.G.","affiliations":[],"preferred":false,"id":483152,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Williams, C.A.","contributorId":79571,"corporation":false,"usgs":true,"family":"Williams","given":"C.A.","email":"","affiliations":[],"preferred":false,"id":483153,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70040669,"text":"70040669 - 2013 - At-sea behavior varies with lunar phase in a nocturnal pelagic seabird, the swallow-tailed gull","interactions":[],"lastModifiedDate":"2013-06-10T11:13:09","indexId":"70040669","displayToPublicDate":"2013-06-10T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"At-sea behavior varies with lunar phase in a nocturnal pelagic seabird, the swallow-tailed gull","docAbstract":"Strong and predictable environmental variability can reward flexible behaviors among animals. We used long-term records of activity data that cover several lunar cycles to investigate whether behavior at-sea of swallow-tailed gulls Creagrus furcatus, a nocturnal pelagic seabird, varied with lunar phase in the Galápagos Islands. A Bayesian hierarchical model showed that nighttime at-sea activity of 37 breeding swallow-tailed gulls was clearly associated with changes in moon phase. Proportion of nighttime spent on water was highest during darker periods of the lunar cycle, coinciding with the cycle of the diel vertical migration (DVM) that brings prey to the sea surface at night. Our data show that at-sea behavior of a tropical seabird can vary with environmental changes, including lunar phase.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"PLoS ONE","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pone.0056889","usgsCitation":"Cruz, S.M., Hooten, M., Huyvaert, K., Proano, C.B., Anderson, D.J., Afanasyev, V., and Wikelski, M., 2013, At-sea behavior varies with lunar phase in a nocturnal pelagic seabird, the swallow-tailed gull: PLoS ONE, v. 8, no. 2, e56889, https://doi.org/10.1371/journal.pone.0056889.","productDescription":"e56889","ipdsId":"IP-037822","costCenters":[{"id":189,"text":"Colorado Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true}],"links":[{"id":473766,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0056889","text":"Publisher Index Page"},{"id":273495,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":273493,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1371/journal.pone.0056889"}],"otherGeospatial":"Gal�pagos Islands","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -92.01,-1.41 ], [ -92.01,1.66 ], [ -89.24,1.66 ], [ -89.24,-1.41 ], [ -92.01,-1.41 ] ] ] } } ] }","volume":"8","issue":"2","noUsgsAuthors":false,"publicationDate":"2013-02-26","publicationStatus":"PW","scienceBaseUri":"51b6e758e4b0097a7158ab3d","contributors":{"authors":[{"text":"Cruz, Sebastian M.","contributorId":56136,"corporation":false,"usgs":true,"family":"Cruz","given":"Sebastian","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":468757,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hooten, Mevin","contributorId":18254,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin","affiliations":[],"preferred":false,"id":468755,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Huyvaert, Kathryn P.","contributorId":73906,"corporation":false,"usgs":true,"family":"Huyvaert","given":"Kathryn P.","affiliations":[],"preferred":false,"id":468758,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Proano, Carolina B.","contributorId":94195,"corporation":false,"usgs":true,"family":"Proano","given":"Carolina","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":468760,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Anderson, David J.","contributorId":15099,"corporation":false,"usgs":true,"family":"Anderson","given":"David","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":468754,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Afanasyev, Vsevolod","contributorId":18661,"corporation":false,"usgs":true,"family":"Afanasyev","given":"Vsevolod","email":"","affiliations":[],"preferred":false,"id":468756,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wikelski, Martin","contributorId":76451,"corporation":false,"usgs":true,"family":"Wikelski","given":"Martin","affiliations":[],"preferred":false,"id":468759,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70041504,"text":"70041504 - 2013 - Temporal variation and scale in movement-based resource selection functions","interactions":[],"lastModifiedDate":"2013-12-02T09:44:44","indexId":"70041504","displayToPublicDate":"2013-06-10T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3475,"text":"Statistical Methodology","active":true,"publicationSubtype":{"id":10}},"title":"Temporal variation and scale in movement-based resource selection functions","docAbstract":"A common population characteristic of interest in animal ecology studies pertains to the selection of resources. That is, given the resources available to animals, what do they ultimately choose to use? A variety of statistical approaches have been employed to examine this question and each has advantages and disadvantages with respect to the form of available data and the properties of estimators given model assumptions. A wealth of high resolution telemetry data are now being collected to study animal population movement and space use and these data present both challenges and opportunities for statistical inference. We summarize traditional methods for resource selection and then describe several extensions to deal with measurement uncertainty and an explicit movement process that exists in studies involving high-resolution telemetry data. Our approach uses a correlated random walk movement model to obtain temporally varying use and availability distributions that are employed in a weighted distribution context to estimate selection coefficients. The temporally varying coefficients are then weighted by their contribution to selection and combined to provide inference at the population level. The result is an intuitive and accessible statistical procedure that uses readily available software and is computationally feasible for large datasets. These methods are demonstrated using data collected as part of a large-scale mountain lion monitoring study in Colorado, USA.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Statistical Methodology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.stamet.2012.12.001","usgsCitation":"Hooten, M., Hanks, E., Johnson, D., and Alldredge, M., 2013, Temporal variation and scale in movement-based resource selection functions: Statistical Methodology, v. 17, p. 82-98, https://doi.org/10.1016/j.stamet.2012.12.001.","productDescription":"17 p.","startPage":"82","endPage":"98","ipdsId":"IP-038933","costCenters":[{"id":189,"text":"Colorado Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true}],"links":[{"id":273501,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.stamet.2012.12.001"},{"id":273503,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"17","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51b6e75ce4b0097a7158ab65","contributors":{"authors":[{"text":"Hooten, M.B.","contributorId":50261,"corporation":false,"usgs":true,"family":"Hooten","given":"M.B.","email":"","affiliations":[],"preferred":false,"id":469866,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hanks, E.M.","contributorId":104305,"corporation":false,"usgs":true,"family":"Hanks","given":"E.M.","email":"","affiliations":[],"preferred":false,"id":469868,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, D.S.","contributorId":30485,"corporation":false,"usgs":true,"family":"Johnson","given":"D.S.","email":"","affiliations":[],"preferred":false,"id":469865,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Alldredge, M.W.","contributorId":50263,"corporation":false,"usgs":true,"family":"Alldredge","given":"M.W.","email":"","affiliations":[],"preferred":false,"id":469867,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70043855,"text":"70043855 - 2013 - Aggregation of carbon dioxide sequestration storage assessment units","interactions":[],"lastModifiedDate":"2013-10-23T14:46:39","indexId":"70043855","displayToPublicDate":"2013-06-10T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3478,"text":"Stochastic Environmental Research and Risk Assessment","active":true,"publicationSubtype":{"id":10}},"title":"Aggregation of carbon dioxide sequestration storage assessment units","docAbstract":"The U.S. Geological Survey is currently conducting a national assessment of carbon dioxide (CO<sub>2</sub>) storage resources, mandated by the Energy Independence and Security Act of 2007. Pre-emission capture and storage of CO<sub>2</sub> in subsurface saline formations is one potential method to reduce greenhouse gas emissions and the negative impact of global climate change. Like many large-scale resource assessments, the area under investigation is split into smaller, more manageable storage assessment units (SAUs), which must be aggregated with correctly propagated uncertainty to the basin, regional, and national scales. The aggregation methodology requires two types of data: marginal probability distributions of storage resource for each SAU, and a correlation matrix obtained by expert elicitation describing interdependencies between pairs of SAUs. Dependencies arise because geologic analogs, assessment methods, and assessors often overlap. The correlation matrix is used to induce rank correlation, using a Cholesky decomposition, among the empirical marginal distributions representing individually assessed SAUs. This manuscript presents a probabilistic aggregation method tailored to the correlations and dependencies inherent to a CO<sub>2</sub> storage assessment. Aggregation results must be presented at the basin, regional, and national scales. A single stage approach, in which one large correlation matrix is defined and subsets are used for different scales, is compared to a multiple stage approach, in which new correlation matrices are created to aggregate intermediate results. Although the single-stage approach requires determination of significantly more correlation coefficients, it captures geologic dependencies among similar units in different basins and it is less sensitive to fluctuations in low correlation coefficients than the multiple stage approach. Thus, subsets of one single-stage correlation matrix are used to aggregate to basin, regional, and national scales.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Stochastic Environmental Research and Risk Assessment","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","doi":"10.1007/s00477-013-0718-x","usgsCitation":"Blondes, M., Schuenemeyer, J.H., Olea, R., and Drew, L.J., 2013, Aggregation of carbon dioxide sequestration storage assessment units: Stochastic Environmental Research and Risk Assessment, v. 27, no. 8, p. 1839-1859, https://doi.org/10.1007/s00477-013-0718-x.","productDescription":"21 p.","startPage":"1839","endPage":"1859","ipdsId":"IP-037774","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":273553,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":273548,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s00477-013-0718-x"}],"volume":"27","issue":"8","noUsgsAuthors":false,"publicationDate":"2013-05-18","publicationStatus":"PW","scienceBaseUri":"51b6e758e4b0097a7158ab39","contributors":{"authors":[{"text":"Blondes, Madalyn S. 0000-0003-0320-0107 mblondes@usgs.gov","orcid":"https://orcid.org/0000-0003-0320-0107","contributorId":3598,"corporation":false,"usgs":true,"family":"Blondes","given":"Madalyn S.","email":"mblondes@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":474316,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schuenemeyer, John H.","contributorId":54227,"corporation":false,"usgs":true,"family":"Schuenemeyer","given":"John","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":474318,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Olea, Ricardo A. 0000-0003-4308-0808","orcid":"https://orcid.org/0000-0003-4308-0808","contributorId":47873,"corporation":false,"usgs":true,"family":"Olea","given":"Ricardo A.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":474317,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Drew, Lawrence J. ldrew@usgs.gov","contributorId":2635,"corporation":false,"usgs":true,"family":"Drew","given":"Lawrence","email":"ldrew@usgs.gov","middleInitial":"J.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":474315,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70045538,"text":"70045538 - 2013 - Age-specific survival of tundra swans on the lower Alaska Peninsula","interactions":[],"lastModifiedDate":"2018-06-20T20:24:17","indexId":"70045538","displayToPublicDate":"2013-06-10T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3551,"text":"The Condor","active":true,"publicationSubtype":{"id":10}},"title":"Age-specific survival of tundra swans on the lower Alaska Peninsula","docAbstract":"The population of Tundra Swans (Cygnus columbianus columbianus) breeding on the lower Alaska Peninsula represents the southern extremity of the species' range and is uniquely nonmigratory. We used data on recaptures, resightings, and recoveries of neck-collared Tundra Swans on the lower Alaska Peninsula to estimate collar loss, annual apparent survival, and other demographic parameters for the years 1978–1989. Annual collar loss was greater for adult males fitted with either the thinner collar type (0.34) or the thicker collar type (0.15) than for other age/sex classes (thinner: 0.10, thicker: 0.04). The apparent mean probability of survival of adults (0.61) was higher than that of immatures (0.41) and for both age classes varied considerably by year (adult range: 0.44–0.95, immature range: 0.25–0.90). To assess effects of permanent emigration by age and breeding class, we analyzed post hoc the encounter histories of swans known to breed in our study area. The apparent mean survival of known breeders (0.65) was generally higher than that of the entire marked sample but still varied considerably by year (range 0.26–1.00) and indicated that permanent emigration of breeding swans was likely. We suggest that reductions in apparent survival probability were influenced primarily by high and variable rates of permanent emigration and that immigration by swans from elsewhere may be important in sustaining a breeding population at and near Izembek National Wildlife Refuge.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"The Condor","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"University of California Press","doi":"10.1525/cond.2013.110213","usgsCitation":"Meixell, B.W., Lindberg, M.S., Conn, P.B., Dau, C.P., Sarvis, J.E., and Sowl, K.M., 2013, Age-specific survival of tundra swans on the lower Alaska Peninsula: The Condor, v. 115, no. 2, p. 280-289, https://doi.org/10.1525/cond.2013.110213.","productDescription":"10 p.","startPage":"280","endPage":"289","ipdsId":"IP-041285","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"links":[{"id":473760,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1525/cond.2013.110213","text":"Publisher Index Page"},{"id":273547,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":273545,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1525/cond.2013.110213"}],"country":"United States","state":"Alaska","otherGeospatial":"Alaska Peninsula","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 172.5,51.2 ], [ 172.5,71.4 ], [ -130.0,71.4 ], [ -130.0,51.2 ], [ 172.5,51.2 ] ] ] } } ] }","volume":"115","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51b6e757e4b0097a7158ab35","contributors":{"authors":[{"text":"Meixell, Brandt W. 0000-0002-6738-0349 bmeixell@usgs.gov","orcid":"https://orcid.org/0000-0002-6738-0349","contributorId":138716,"corporation":false,"usgs":true,"family":"Meixell","given":"Brandt","email":"bmeixell@usgs.gov","middleInitial":"W.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":477795,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lindberg, Mark S.","contributorId":63292,"corporation":false,"usgs":false,"family":"Lindberg","given":"Mark","email":"","middleInitial":"S.","affiliations":[{"id":7211,"text":"University of Alaska, Fairbanks","active":true,"usgs":false}],"preferred":false,"id":477798,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Conn, Paul B.","contributorId":87440,"corporation":false,"usgs":true,"family":"Conn","given":"Paul","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":477800,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dau, Christian P.","contributorId":26185,"corporation":false,"usgs":true,"family":"Dau","given":"Christian","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":477796,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sarvis, John E.","contributorId":66576,"corporation":false,"usgs":true,"family":"Sarvis","given":"John","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":477799,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sowl, Kristine M.","contributorId":60372,"corporation":false,"usgs":false,"family":"Sowl","given":"Kristine","email":"","middleInitial":"M.","affiliations":[{"id":12598,"text":"Izembek National Wildlife Refuge","active":true,"usgs":false}],"preferred":false,"id":477797,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70046333,"text":"70046333 - 2013 - Inferential consequences of modeling rather than measuring snow accumulation in studies of animal ecology","interactions":[],"lastModifiedDate":"2017-09-12T11:53:47","indexId":"70046333","displayToPublicDate":"2013-06-10T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Inferential consequences of modeling rather than measuring snow accumulation in studies of animal ecology","docAbstract":"Abstract. It is increasingly common for studies of animal ecology to use model-based predictions of environmental variables as explanatory or predictor variables, even though model prediction uncertainty is typically unknown. To demonstrate the potential for misleading inferences when model predictions with error are used in place of direct measurements, we compared snow water equivalent (SWE) and snow depth as predicted by the Snow Data Assimilation System (SNODAS) to field measurements of SWE and snow depth. We examined locations on elk (Cervus canadensis) winter ranges in western Wyoming, because modeled data such as SNODAS output are often used for inferences on elk ecology. Overall, SNODAS predictions tended to overestimate field measurements, prediction uncertainty was high, and the difference between SNODAS predictions and field measurements was greater in snow shadows for both snow variables compared to non-snow shadow areas. We used a simple simulation of snow effects on the probability of an elk being killed by a predator to show that, if SNODAS prediction uncertainty was ignored, we might have mistakenly concluded that SWE was not an important factor in where elk were killed in predatory attacks during the winter. In this simulation, we were interested in the effects of snow at finer scales (<1 km<sup>2</sup>) than the resolution of SNODAS. If bias were to decrease when SNODAS predictions are averaged over coarser scales, SNODAS would be applicable to population-level ecology studies. In our study, however, averaging predictions over moderate to broad spatial scales (9–2200 km<sup>2</sup>) did not reduce the differences between SNODAS predictions and field measurements. This study highlights the need to carefully evaluate two issues when using model output as an explanatory variable in subsequent analysis: (1) the model’s resolution relative to the scale of the ecological question of interest and (2) the implications of prediction uncertainty on inferences when using model predictions as explanatory or predictor variables.","language":"English","publisher":"Ecological Society of America","doi":"10.1890/12-0959.1","usgsCitation":"Cross, P.C., Klaver, R.W., Brennan, A., Creel, S., Beckmann, J., Higgs, M., and Scurlock, B.M., 2013, Inferential consequences of modeling rather than measuring snow accumulation in studies of animal ecology: Ecological Applications, v. 23, no. 3, p. 643-653, https://doi.org/10.1890/12-0959.1.","productDescription":"11 p.","startPage":"643","endPage":"653","numberOfPages":"11","additionalOnlineFiles":"N","ipdsId":"IP-032991","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":473759,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://lib.dr.iastate.edu/nrem_pubs/212","text":"External Repository"},{"id":273468,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":273467,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1890/12-0959.1"}],"country":"United States","state":"Wyoming","volume":"23","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51b6e75be4b0097a7158ab55","contributors":{"authors":[{"text":"Cross, Paul C. 0000-0001-8045-5213 pcross@usgs.gov","orcid":"https://orcid.org/0000-0001-8045-5213","contributorId":2709,"corporation":false,"usgs":true,"family":"Cross","given":"Paul","email":"pcross@usgs.gov","middleInitial":"C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":479478,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Klaver, Robert W. 0000-0002-3263-9701 bklaver@usgs.gov","orcid":"https://orcid.org/0000-0002-3263-9701","contributorId":3285,"corporation":false,"usgs":true,"family":"Klaver","given":"Robert","email":"bklaver@usgs.gov","middleInitial":"W.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":479473,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brennan, Angela","contributorId":40871,"corporation":false,"usgs":true,"family":"Brennan","given":"Angela","affiliations":[],"preferred":false,"id":479476,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Creel, Scott","contributorId":15089,"corporation":false,"usgs":true,"family":"Creel","given":"Scott","affiliations":[],"preferred":false,"id":479475,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Beckmann, Jon P.","contributorId":73098,"corporation":false,"usgs":true,"family":"Beckmann","given":"Jon P.","affiliations":[],"preferred":false,"id":479477,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Higgs, Megan D.","contributorId":14718,"corporation":false,"usgs":true,"family":"Higgs","given":"Megan D.","affiliations":[],"preferred":false,"id":479474,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Scurlock, Brandon M.","contributorId":93788,"corporation":false,"usgs":false,"family":"Scurlock","given":"Brandon","email":"","middleInitial":"M.","affiliations":[{"id":6917,"text":"Wyoming Game and Fish Department, Laramie, USA","active":true,"usgs":false}],"preferred":false,"id":479479,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70046357,"text":"sim2999 - 2013 - Reconnaissance geologic map of Kodiak Island and adjacent islands, Alaska","interactions":[],"lastModifiedDate":"2017-06-07T16:20:26","indexId":"sim2999","displayToPublicDate":"2013-06-10T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2999","title":"Reconnaissance geologic map of Kodiak Island and adjacent islands, Alaska","docAbstract":"Kodiak Island and its adjacent islands, located on the west side of the Gulf of Alaska, contain one of the largest areas of exposure of the flysch and melange of the Chugach terrane of southern Alaska. However, in the past 25 years, only detailed mapping covering small areas in the archipelago has been done. This map and its associated digital files (Wilson and others, 2005) present the best available mapping compiled in an integrated fashion. The map and associated digital files represent part of a systematic effort to release geologic map data for the United States in a uniform manner. The geologic data have been compiled from a wide variety of sources, ranging from state and regional geologic maps to large-scale field mapping. The map data are presented for use at a nominal scale of 1:500,000, although individual datasets (see Wilson and others, 2005) may contain data suitable for use at larger scales.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim2999","usgsCitation":"Wilson, F.H., 2013, Reconnaissance geologic map of Kodiak Island and adjacent islands, Alaska: U.S. Geological Survey Scientific Investigations Map 2999, Pamphlet: ii, 8 p.; 1 Map: 24.66 x 31.32 inches; OFR 2005-1340, https://doi.org/10.3133/sim2999.","productDescription":"Pamphlet: ii, 8 p.; 1 Map: 24.66 x 31.32 inches; OFR 2005-1340","numberOfPages":"12","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"links":[{"id":273529,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sim2999.gif"},{"id":273527,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/2999/sim2999_map.pdf"},{"id":273526,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/2999/sim2999_pamphlet.pdf"},{"id":273528,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/of/2005/1340/"},{"id":273525,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/2999/"}],"country":"United States","state":"Alaska","otherGeospatial":"Kodiak Island","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -0.015277777777777777,5.085277777777778 ], [ -0.015277777777777777,0.001388888888888889 ], [ -152.5,0.001388888888888889 ], [ -152.5,5.085277777777778 ], [ -0.015277777777777777,5.085277777777778 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51b6e75be4b0097a7158ab59","contributors":{"authors":[{"text":"Wilson, Frederic H. 0000-0003-1761-6437 fwilson@usgs.gov","orcid":"https://orcid.org/0000-0003-1761-6437","contributorId":67174,"corporation":false,"usgs":true,"family":"Wilson","given":"Frederic","email":"fwilson@usgs.gov","middleInitial":"H.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":479546,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70040670,"text":"70040670 - 2013 - Spatial occupancy models for large data sets","interactions":[],"lastModifiedDate":"2013-06-10T11:18:23","indexId":"70040670","displayToPublicDate":"2013-06-10T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Spatial occupancy models for large data sets","docAbstract":"Since its development, occupancy modeling has become a popular and useful tool for ecologists wishing to learn about the dynamics of species occurrence over time and space. Such models require presence–absence data to be collected at spatially indexed survey units. However, only recently have researchers recognized the need to correct for spatially induced overdisperison by explicitly accounting for spatial autocorrelation in occupancy probability. Previous efforts to incorporate such autocorrelation have largely focused on logit-normal formulations for occupancy, with spatial autocorrelation induced by a random effect within a hierarchical modeling framework. Although useful, computational time generally limits such an approach to relatively small data sets, and there are often problems with algorithm instability, yielding unsatisfactory results. Further, recent research has revealed a hidden form of multicollinearity in such applications, which may lead to parameter bias if not explicitly addressed. Combining several techniques, we present a unifying hierarchical spatial occupancy model specification that is particularly effective over large spatial extents. This approach employs a probit mixture framework for occupancy and can easily accommodate a reduced-dimensional spatial process to resolve issues with multicollinearity and spatial confounding while improving algorithm convergence. Using open-source software, we demonstrate this new model specification using a case study involving occupancy of caribou (Rangifer tarandus) over a set of 1080 survey units spanning a large contiguous region (108 000 km<sup>2</sup>) in northern Ontario, Canada. Overall, the combination of a more efficient specification and open-source software allows for a facile and stable implementation of spatial occupancy models for large data sets.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ecology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"ESA","doi":"10.1890/12-0564.1","usgsCitation":"Johnson, D., Conn, P.B., Hooten, M., Ray, J., and Pond, B.A., 2013, Spatial occupancy models for large data sets: Ecology, v. 94, no. 4, p. 801-808, https://doi.org/10.1890/12-0564.1.","productDescription":"8 p.","startPage":"801","endPage":"808","ipdsId":"IP-036098","costCenters":[{"id":189,"text":"Colorado Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true}],"links":[{"id":473764,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1890/12-0564.1","text":"Publisher Index Page"},{"id":273500,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":273496,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1890/12-0564.1"}],"volume":"94","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51b6e75be4b0097a7158ab5d","contributors":{"authors":[{"text":"Johnson, Devin S.","contributorId":47524,"corporation":false,"usgs":true,"family":"Johnson","given":"Devin S.","affiliations":[],"preferred":false,"id":468763,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conn, Paul B.","contributorId":87440,"corporation":false,"usgs":true,"family":"Conn","given":"Paul","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":468765,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hooten, Mevin 0000-0002-1614-723X mhooten@usgs.gov","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":2958,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin","email":"mhooten@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":12963,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO","active":true,"usgs":false}],"preferred":true,"id":468761,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ray, Justina C.","contributorId":69043,"corporation":false,"usgs":true,"family":"Ray","given":"Justina C.","affiliations":[],"preferred":false,"id":468764,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pond, Bruce A.","contributorId":43659,"corporation":false,"usgs":true,"family":"Pond","given":"Bruce","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":468762,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70046339,"text":"sir20135013 - 2013 - A national streamflow network gap analysis","interactions":[],"lastModifiedDate":"2013-06-10T09:29:21","indexId":"sir20135013","displayToPublicDate":"2013-06-10T00:00:00","publicationYear":"2013","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":"2013-5013","title":"A national streamflow network gap analysis","docAbstract":"The U.S. Geological Survey (USGS) conducted a gap analysis to evaluate how well the USGS streamgage network meets a variety of needs, focusing on the ability to calculate various statistics at locations that have streamgages (gaged) and that do not have streamgages (ungaged). This report presents the results of analysis to determine where there are gaps in the network of gaged locations, how accurately desired statistics can be calculated with a given length of record, and whether the current network allows for estimation of these statistics at ungaged locations.  The analysis indicated that there is variability across the Nation’s streamflow data-collection network in terms of the spatial and temporal coverage of streamgages. In general, the Eastern United States has better coverage than the Western United States. The arid Southwestern United States, Alaska, and Hawaii were observed to have the poorest spatial coverage, using the dataset assembled for this study. Except in Hawaii, these areas also tended to have short streamflow records. Differences in hydrology lead to differences in the uncertainty of statistics calculated in different regions of the country. Arid and semiarid areas of the Central and Southwestern United States generally exhibited the highest levels of interannual variability in flow, leading to larger uncertainty in flow statistics.  At ungaged locations, information can be transferred from nearby streamgages if there is sufficient similarity between the gaged watersheds and the ungaged watersheds of interest. Areas where streamgages exhibit high correlation are most likely to be suitable for this type of information transfer. The areas with the most highly correlated streamgages appear to coincide with mountainous areas of the United States. Lower correlations are found in the Central United States and coastal areas of the Southeastern United States. Information transfer from gaged basins to ungaged basins is also most likely to be successful when basin attributes show high similarity. At the scale of the analysis completed in this study, the attributes of basins upstream of USGS streamgages cover the full range of basin attributes observed at potential locations of interest fairly well. Some exceptions included very high or very low elevation areas and very arid areas.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135013","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Kiang, J.E., Stewart, D.W., Archfield, S.A., Osborne, E.B., and Eng, K., 2013, A national streamflow network gap analysis: U.S. Geological Survey Scientific Investigations Report 2013-5013, Report: ix, 82 p.; 1 Appendix, https://doi.org/10.3133/sir20135013.","productDescription":"Report: ix, 82 p.; 1 Appendix","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":273473,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135013.gif"},{"id":273471,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2013/5013/sir2013-5013_app1_final.xlsx"},{"id":273469,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5013/pdf/sir2013-5013.pdf"},{"id":273470,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5013/"}],"country":"United States","otherGeospatial":"Puerto Rico","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 144.61,13.23 ], [ 144.61,71.83 ], [ -65.22,71.83 ], [ -65.22,13.23 ], [ 144.61,13.23 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51b6e750e4b0097a7158ab2d","contributors":{"authors":[{"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":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":true,"id":479505,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stewart, David W. dwstewar@usgs.gov","contributorId":2390,"corporation":false,"usgs":true,"family":"Stewart","given":"David","email":"dwstewar@usgs.gov","middleInitial":"W.","affiliations":[],"preferred":true,"id":479506,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Archfield, Stacey A. 0000-0002-9011-3871 sarch@usgs.gov","orcid":"https://orcid.org/0000-0002-9011-3871","contributorId":1874,"corporation":false,"usgs":true,"family":"Archfield","given":"Stacey","email":"sarch@usgs.gov","middleInitial":"A.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":true,"id":479504,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Osborne, Emily B.","contributorId":101971,"corporation":false,"usgs":true,"family":"Osborne","given":"Emily","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":479508,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Eng, Ken","contributorId":89480,"corporation":false,"usgs":true,"family":"Eng","given":"Ken","affiliations":[],"preferred":false,"id":479507,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70046359,"text":"ds771 - 2013 - Database for the geologic map of Newberry Volcano, Deschutes, Klamath, and Lake Counties, Oregon","interactions":[],"lastModifiedDate":"2026-05-20T16:47:42.569769","indexId":"ds771","displayToPublicDate":"2013-06-10T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"771","title":"Database for the geologic map of Newberry Volcano, Deschutes, Klamath, and Lake Counties, Oregon","docAbstract":"Newberry Volcano, one of the largest Quaternary volcanoes in the conterminous United States, is a broad shield-shaped volcano measuring 60 km north-south by 30 km east-west with a maximum elevation of more than 2 km. Newberry Volcano is the product of deposits from thousands of eruptions, including at least 25 in the past approximately 12,000 years (Holocene Epoch). Newberry Volcano has erupted as recently as 1,300 years ago, but isotopic ages indicate that the volcano began its growth as early as 0.6 million years ago. Such a long eruptive history and recent activity suggest that Newberry Volcano is likely to erupt in the future. This geologic map database of Newberry Volcano distinguishes rocks and deposits based on their composition, age, and lithology.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds771","collaboration":"Database for Miscellaneous Investigations Series Map I-2455","usgsCitation":"Bard, J.A., Ramsey, D.W., MacLeod, N.S., Sherrod, D.R., Chitwood, L.A., and Jensen, R.A., 2013, Database for the Geologic Map of Newberry Volcano, Deschutes, Klamath, and Lake Counties, Oregon: U.S. Geological Survey Data Series 771, HTML Document, Database, https://doi.org/10.3133/ds771.","productDescription":"HTML Document, Database","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":504559,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_98541.htm","linkFileType":{"id":5,"text":"html"}},{"id":273531,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/771/"},{"id":273532,"rank":1,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/ds/771/database/index.html"},{"id":273533,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds771.png"}],"country":"United States","state":"Oregon","county":"Deschutes County, Klamath County, Lake County","otherGeospatial":"Newberry Volcano","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -121.5,43.5 ], [ -121.5,44.0 ], [ -121.0,44.0 ], [ -121.0,43.5 ], [ -121.5,43.5 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51b6e759e4b0097a7158ab45","contributors":{"authors":[{"text":"Bard, Joseph A. 0000-0003-3143-4007 jbard@usgs.gov","orcid":"https://orcid.org/0000-0003-3143-4007","contributorId":5590,"corporation":false,"usgs":true,"family":"Bard","given":"Joseph","email":"jbard@usgs.gov","middleInitial":"A.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":479549,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ramsey, David W. 0000-0003-1698-2523 dramsey@usgs.gov","orcid":"https://orcid.org/0000-0003-1698-2523","contributorId":3819,"corporation":false,"usgs":true,"family":"Ramsey","given":"David","email":"dramsey@usgs.gov","middleInitial":"W.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":479548,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"MacLeod, Norman S.","contributorId":13643,"corporation":false,"usgs":true,"family":"MacLeod","given":"Norman","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":479550,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sherrod, David R. 0000-0001-9460-0434 dsherrod@usgs.gov","orcid":"https://orcid.org/0000-0001-9460-0434","contributorId":527,"corporation":false,"usgs":true,"family":"Sherrod","given":"David","email":"dsherrod@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":479547,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chitwood, Lawrence A.","contributorId":54655,"corporation":false,"usgs":true,"family":"Chitwood","given":"Lawrence","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":479552,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jensen, Robert A.","contributorId":35469,"corporation":false,"usgs":false,"family":"Jensen","given":"Robert","email":"","middleInitial":"A.","affiliations":[{"id":7134,"text":"USFS","active":true,"usgs":false}],"preferred":false,"id":479551,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70038720,"text":"70038720 - 2013 - One hundred and six years of population and community dynamics of Sonoran Desert Laboratory perennials","interactions":[],"lastModifiedDate":"2013-06-07T10:10:20","indexId":"70038720","displayToPublicDate":"2013-06-07T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1451,"text":"Ecological Archives","active":true,"publicationSubtype":{"id":10}},"title":"One hundred and six years of population and community dynamics of Sonoran Desert Laboratory perennials","docAbstract":"This data set constitutes all information associated with the Spalding-Shreve permanent vegetation plots from 1906 through 2012, which is the longest-running plant monitoring program in the world. The program consists of detailed maps of all Sonoran Desert perennial plants in 30 permanent plots located on Tumamoc Hill, near Tucson, Arizona, USA. Most of these plots are 10 m × 10 m quadrats that were established by Volney Spalding and Forrest Shreve between 1906 and 1928. Analyses derived from these data have been pivotal in testing early theories on plant community succession, plant life history traits, plant longevity, and population dynamics. One of the major contributions of this data set is the species-specific demographic traits that derived from estimating individual plant trajectories for more than 106 years. Further use of these data might shed light on spatially explicit population and community dynamics, as well as long-term changes attributable to global change.\n\nData presented here consist of digital versions of original maps created between 1906 and 1984 and digital data from recent censuses between 1993 and 2012. Attributes associated with these maps include location and coverage of all shrubs, and in some cases, plant height. In addition, we present plot-specific summaries of plant cover and density for each census year and all other information collected, including seedling counts, grass coverage, and annual species enumerations. We reference the repeat photography of these plots, which began in 1906; these images are stored at the Desert Laboratory Collection of Repeat Photography in Tucson. Initial data collection consisted of grid-mapping the plots manually on graph paper; starting in 1993, Total Stations (which allow a direct digitalization, and more accurate mapping) were used to survey root crowns and canopies.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ecological Archives","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"ESA","doi":"10.1890/12-1164.1","usgsCitation":"Rodriguez-Buritica, S., Raichle, H., Webb, R., Turner, R., and Venable, L., 2013, One hundred and six years of population and community dynamics of Sonoran Desert Laboratory perennials: Ecological Archives, v. 94, no. 4, p. 976-976, https://doi.org/10.1890/12-1164.1.","productDescription":"1 p.","startPage":"976","endPage":"976","ipdsId":"IP-038596","costCenters":[{"id":148,"text":"Branch of Regional Research-Western Region","active":false,"usgs":true}],"links":[{"id":273435,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":273434,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1890/12-1164.1"}],"volume":"94","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51b2f2dbe4b01368e589e3c2","contributors":{"authors":[{"text":"Rodriguez-Buritica, Susana","contributorId":29723,"corporation":false,"usgs":true,"family":"Rodriguez-Buritica","given":"Susana","affiliations":[],"preferred":false,"id":464788,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Raichle, Helen hraichle@usgs.gov","contributorId":4387,"corporation":false,"usgs":true,"family":"Raichle","given":"Helen","email":"hraichle@usgs.gov","affiliations":[],"preferred":true,"id":464786,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Webb, Robert H. rhwebb@usgs.gov","contributorId":1573,"corporation":false,"usgs":false,"family":"Webb","given":"Robert H.","email":"rhwebb@usgs.gov","affiliations":[{"id":12625,"text":"School of Natural Resources and the Environment, University of Arizona, Tucson, AZ, 85721, USA","active":true,"usgs":false}],"preferred":false,"id":464785,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Turner, Raymond M.","contributorId":7383,"corporation":false,"usgs":true,"family":"Turner","given":"Raymond M.","affiliations":[],"preferred":false,"id":464787,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Venable, Larry","contributorId":71861,"corporation":false,"usgs":true,"family":"Venable","given":"Larry","affiliations":[],"preferred":false,"id":464789,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70046309,"text":"sir20135025 - 2013 - Hydrogeology of the West Branch Delaware River basin, Delaware County, New York","interactions":[],"lastModifiedDate":"2013-06-06T11:23:48","indexId":"sir20135025","displayToPublicDate":"2013-06-06T00:00:00","publicationYear":"2013","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":"2013-5025","title":"Hydrogeology of the West Branch Delaware River basin, Delaware County, New York","docAbstract":"In 2009, the U.S. Geological Survey, in cooperation with the New York State Department of Environmental Conservation, began a study of the hydrogeology of the West Branch Delaware River (Cannonsville Reservoir) watershed. There has been recent interest by energy companies in developing the natural gas reserves that are trapped within the Marcellus Shale, which is part of the Hamilton Group of Devonian age that underlies all the West Branch Delaware River Basin. Knowing the extent and thickness of stratified-drift (sand and gravel) aquifers within this basin can help State and Federal regulatory agencies evaluate any effects on these aquifers that gas-well drilling might produce. This report describes the hydrogeology of the 455-square-mile basin in the southwestern Catskill Mountain region of southeastern New York and includes a detailed surficial geologic map of the basin. Analysis of surficial geologic data indicates that the most widespread surficial geologic unit within the basin is till, which is present as deposits of ablation till in major stream valleys and as thick deposits of lodgment till that fill upland basins. Till and colluvium (remobilized till) cover about 89 percent of the West Branch Delaware River Basin, whereas stratified drift (outwash and ice-contact deposits) and alluvium account for 8.9 percent. The Cannonsville Reservoir occupies about 1.9 percent of the basin area. Large areas of outwash and ice-contact deposits occupy the West Branch Delaware River valley along its entire length. These deposits form a stratified-drift aquifer that ranges in thickness from 40 to 50 feet (ft) in the upper West Branch Delaware River valley, from 70 to 140 ft in the middle West Branch Delaware River valley, and from 60 to 70 ft in the lower West Branch Delaware River valley. The gas-bearing Marcellus Shale underlies the entire West Branch Delaware River Basin and ranges in thickness from 600 to 650 ft along the northern divide of the basin to 750 ft thick along the southern divide. The depth to the top of the Marcellus Shale ranges from 3,240 ft along the northern basin divide to 4,150 ft along the southern basin divide. Yields of wells completed in the aquifer are as high as 500 gallons per minute (gal/min). Springs from fractured sandstone bedrock are an important source of domestic and small municipal water supplies in the West Branch Delaware River Basin and elsewhere in Delaware County. The average yield of 178 springs in Delaware County is 8.5 gal/min with a median yield of 3 gal/min. An analysis of two low-flow statistics indicates that groundwater contributions from fractured bedrock compose a significant part of the base flow of the West Branch Delaware River and its tributaries.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135025","collaboration":"Prepared in cooperation with the New York State Department of Environmental Conservation","usgsCitation":"Reynolds, R.J., 2013, Hydrogeology of the West Branch Delaware River basin, Delaware County, New York: U.S. Geological Survey Scientific Investigations Report 2013-5025, Report: vi, 28 p.; 1 Map: 42 x 36 inches, https://doi.org/10.3133/sir20135025.","productDescription":"Report: vi, 28 p.; 1 Map: 42 x 36 inches","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":273375,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135025.gif"},{"id":273374,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2013/5025/pdf/Well_Locations_sheet.pdf"},{"id":273372,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5025/"},{"id":273373,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5025/pdf/sir2013-5025_reynolds_508.pdf"}],"scale":"100000","country":"United States","state":"New York","county":"Delaware","otherGeospatial":"West Branch Delaware River Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -75.30,42 ], [ -75.30,42.30 ], [ -74.30,42.30 ], [ -74.30,42 ], [ -75.30,42 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51b1a16fe4b022a6a540f994","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":479435,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70046310,"text":"fs20133032 - 2013 - The 3D Elevation Program: summary for Wisconsin","interactions":[],"lastModifiedDate":"2016-08-17T16:17:52","indexId":"fs20133032","displayToPublicDate":"2013-06-06T00:00:00","publicationYear":"2013","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":"2013-3032","title":"The 3D Elevation Program: summary for Wisconsin","docAbstract":"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 Wisconsin, elevation data are critical for agriculture and precision farming, natural resources conservation, flood risk management, infrastructure and construction management, water supply and quality, and other business uses. Today, high-quality light detection and ranging (lidar) data are the sources for creating elevation models and other elevation datasets. Federal, State, and local agencies work in partnership to (1) replace data, on a national basis, that are (on average) 30 years old 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. The new 3D Elevation Program (3DEP) initiative, managed by the U.S. Geological Survey (USGS), responds to the growing need for high-quality topographic data and a wide range of other three-dimensional representations of the Nation’s natural and constructed features.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20133032","usgsCitation":"Carswell, W., 2013, The 3D Elevation Program: summary for Wisconsin (Originally posted on June 6, 2013; Revised June 13, 2013): U.S. Geological Survey Fact Sheet 2013-3032, 2 p., https://doi.org/10.3133/fs20133032.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"links":[{"id":273378,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20133032.gif"},{"id":273376,"type":{"id":15,"text":"Index 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Jr. carswell@usgs.gov","contributorId":1787,"corporation":false,"usgs":true,"family":"Carswell","given":"William J.","suffix":"Jr.","email":"carswell@usgs.gov","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":false,"id":479436,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70043161,"text":"70043161 - 2013 - In situ quantification of Br and Cl in minerals and fluid inclusions by LA-ICP-MS: a powerful tool to identify fluid sources","interactions":[],"lastModifiedDate":"2013-06-06T14:31:36","indexId":"70043161","displayToPublicDate":"2013-06-06T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1213,"text":"Chemical Geology","active":true,"publicationSubtype":{"id":10}},"title":"In situ quantification of Br and Cl in minerals and fluid inclusions by LA-ICP-MS: a powerful tool to identify fluid sources","docAbstract":"Bromine and chlorine are important halogens for fluid source identification in the Earth's crust, but until recently we lacked routine analytical techniques to determine the concentration of these elements in situ on a micrometer scale in minerals and fluid inclusions. In this study, we evaluate the potential of in situ Cl and Br measurements by LA-ICP-MS through analysis of a range of scapolite grains with known Cl and Br concentrations. We assess the effects of varying spot sizes, variable plasma energy and resolve the contribution of polyatomic interferences on Br measurements. Using well-characterised natural scapolite standards, we show that LA-ICP-MS analysis allows measurement of Br and Cl concentrations in scapolite, and fluid inclusions as small as 16 μm in diameter and potentially in sodalite and a variety of other minerals, such as apatite, biotite, and amphibole. As a demonstration of the accuracy and potential of Cl and Br analyses by LA-ICP-MS, we analysed natural fluid inclusions hosted in sphalerite and compared them to crush and leach ion chromatography Cl/Br analyses. Limit of detection for Br is ~8 μg g<sup>−1</sup>, whereas relatively high Cl concentrations (> 500 μg g<sup>−1</sup>) are required for quantification by LA-ICP-MS. In general, our LA-ICP-MS fluid inclusion results agree well with ion chromatography (IC) data. Additionally, combined cathodoluminescence and LA-ICP-MS analyses on natural scapolites within a well-studied regional metamorphic suite in South Australia demonstrate that Cl and Br can be quantified with a ~25 μm resolution in natural minerals. This technique can be applied to resolve a range of hydrothermal geology problems, including determining the origins of ore forming brines and ore deposition processes, mapping metamorphic and hydrothermal fluid provinces and pathways, and constraining the effects of fluid–rock reactions and fluid mixing.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Chemical Geology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.chemgeo.2012.12.002","usgsCitation":"Hammerli, J., Rusk, B., Spandler, C., Emsbo, P., and Oliver, N.H., 2013, In situ quantification of Br and Cl in minerals and fluid inclusions by LA-ICP-MS: a powerful tool to identify fluid sources: Chemical Geology, v. 337-338, p. 75-87, https://doi.org/10.1016/j.chemgeo.2012.12.002.","productDescription":"13 p.","startPage":"75","endPage":"87","ipdsId":"IP-042825","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":273412,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":273411,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.chemgeo.2012.12.002"}],"volume":"337-338","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51b1a170e4b022a6a540f99c","contributors":{"authors":[{"text":"Hammerli, Johannes","contributorId":105201,"corporation":false,"usgs":true,"family":"Hammerli","given":"Johannes","email":"","affiliations":[],"preferred":false,"id":473085,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rusk, Brian","contributorId":53519,"corporation":false,"usgs":true,"family":"Rusk","given":"Brian","affiliations":[],"preferred":false,"id":473083,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Spandler, Carl","contributorId":30895,"corporation":false,"usgs":true,"family":"Spandler","given":"Carl","email":"","affiliations":[],"preferred":false,"id":473082,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Emsbo, Poul 0000-0001-9421-201X pemsbo@usgs.gov","orcid":"https://orcid.org/0000-0001-9421-201X","contributorId":997,"corporation":false,"usgs":true,"family":"Emsbo","given":"Poul","email":"pemsbo@usgs.gov","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":473081,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Oliver, Nicholas H.S.","contributorId":54871,"corporation":false,"usgs":true,"family":"Oliver","given":"Nicholas","email":"","middleInitial":"H.S.","affiliations":[],"preferred":false,"id":473084,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70174344,"text":"70174344 - 2013 - New perspectives on the geometry of the Albuquerque Basin, Rio Grande rift, New Mexico: Insights from geophysical models of rift-fill thickness","interactions":[],"lastModifiedDate":"2016-07-08T18:26:12","indexId":"70174344","displayToPublicDate":"2013-06-04T01:15:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3459,"text":"Special Paper of the Geological Society of America","active":true,"publicationSubtype":{"id":10}},"title":"New perspectives on the geometry of the Albuquerque Basin, Rio Grande rift, New Mexico: Insights from geophysical models of rift-fill thickness","docAbstract":"<p><span>Discrepancies among previous models of the geometry of the Albuquerque Basin motivated us to develop a new model using a comprehensive approach. Capitalizing on a natural separation between the densities of mainly Neogene basin fill (Santa Fe Group) and those of older rocks, we developed a three-dimensional (3D) geophysical model of syn-rift basin-fill thickness that incorporates well data, seismic-reflection data, geologic cross sections, and other geophysical data in a constrained gravity inversion. Although the resulting model does not show structures directly, it elucidates important aspects of basin geometry. The main features are three, 3&ndash;5-km-deep, interconnected structural depressions, which increase in size, complexity, and segmentation from north to south: the Santo Domingo, Calabacillas, and Belen subbasins. The increase in segmentation and complexity may reflect a transition of the Rio Grande rift from well-defined structural depressions in the north to multiple, segmented basins within a broader region of crustal extension to the south. The modeled geometry of the subbasins and their connections differs from a widely accepted structural model based primarily on seismic-reflection interpretations. Key elements of the previous model are an east-tilted half-graben block on the north separated from a west-tilted half-graben block on the south by a southwest-trending, scissor-like transfer zone. Instead, we find multiple subbasins with predominantly easterly tilts for much of the Albuquerque Basin, a restricted region of westward tilting in the southwestern part of the basin, and a northwesterly trending antiform dividing subbasins in the center of the basin instead of a major scissor-like transfer zone. The overall eastward tilt indicated by the 3D geophysical model generally conforms to stratal tilts observed for the syn-rift succession, implying a prolonged eastward tilting of the basin during Miocene time. An extensive north-south synform in the central part of the Belen subbasin suggests a possible path for the ancestral Rio Grande during late Miocene or early Pliocene time. Variations in rift-fill thickness correspond to pre-rift structures in several places, suggesting that a better understanding of pre-rift history may shed light on debates about structural inheritance within the rift.</span></p>","language":"English","publisher":"Geological Society of America","doi":"10.1130/2013.2494(16)","usgsCitation":"Grauch, V.J., and Connell, S.D., 2013, New perspectives on the geometry of the Albuquerque Basin, Rio Grande rift, New Mexico: Insights from geophysical models of rift-fill thickness: Special Paper of the Geological Society of America, v. 494, p. 427-462, https://doi.org/10.1130/2013.2494(16).","productDescription":"36 p.","startPage":"427","endPage":"462","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-023201","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":324988,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"494","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5780cebce4b081161682238e","contributors":{"authors":[{"text":"Grauch, V. J. 0000-0002-0761-3489 tien@usgs.gov","orcid":"https://orcid.org/0000-0002-0761-3489","contributorId":152256,"corporation":false,"usgs":true,"family":"Grauch","given":"V.","email":"tien@usgs.gov","middleInitial":"J.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":641980,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Connell, Sean D.","contributorId":7374,"corporation":false,"usgs":true,"family":"Connell","given":"Sean","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":641981,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70046248,"text":"ds770 - 2013 - Groundwater well inventory and assessment in the area of the proposed Normally Pressured Lance natural gas development project, Green River Basin, Wyoming, 2012","interactions":[],"lastModifiedDate":"2013-06-04T09:41:04","indexId":"ds770","displayToPublicDate":"2013-06-04T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"770","title":"Groundwater well inventory and assessment in the area of the proposed Normally Pressured Lance natural gas development project, Green River Basin, Wyoming, 2012","docAbstract":"During May through September 2012, the U.S. Geological Survey, in cooperation with the Bureau of Land Management, inventoried and assessed existing water wells in southwestern Wyoming for inclusion in a possible groundwater-monitor network. Records were located for 3,282 wells in the upper Green River Basin, which includes the U.S. Geological Survey study area and the proposed Normally Pressured Lance natural gas development project area. Records for 2,713 upper Green River Basin wells were determined to be unique (not duplicated) and to have a Wyoming State Engineers Office permit. Further, 376 of these wells were within the U.S. Geological Survey Normally Pressured Lance study area. Of the 376 wells in the U.S. Geological Survey Normally Pressured Lance study area, 141 well records had sufficient documentation, such as well depth, open interval, geologic log, and depth to water, to meet many, but not always all, established monitor well criteria. Efforts were made to locate each of the 141 wells and to document their current condition. Field crews were able to locate 121 of the wells, and the remaining 20 wells either were not located as described, or had been abandoned and the site reclaimed. Of the 121 wells located, 92 were found to meet established monitor well criteria. Results of the field efforts during May through September 2012, and specific physical characteristics of the 92 wells, are presented in this report.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds770","collaboration":"Prepared in cooperation with the Bureau of Land Management","usgsCitation":"Sweat, M.J., 2013, Groundwater well inventory and assessment in the area of the proposed Normally Pressured Lance natural gas development project, Green River Basin, Wyoming, 2012: U.S. Geological Survey Data Series 770, v, 27 p., https://doi.org/10.3133/ds770.","productDescription":"v, 27 p.","numberOfPages":"38","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2012-05-01","temporalEnd":"2012-09-30","costCenters":[{"id":684,"text":"Wyoming Water Science Center","active":false,"usgs":true}],"links":[{"id":273148,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds770.gif"},{"id":273146,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/770/"},{"id":273147,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/770/ds770.pdf"}],"country":"United States","state":"Wyoming","otherGeospatial":"Green River Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -111.0,41.0 ], [ -111.0,45.0 ], [ -104.0,45.0 ], [ -104.0,41.0 ], [ -111.0,41.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51aefe59e4b08a3322c2c25c","contributors":{"authors":[{"text":"Sweat, Michael J. mjsweat@usgs.gov","contributorId":356,"corporation":false,"usgs":true,"family":"Sweat","given":"Michael","email":"mjsweat@usgs.gov","middleInitial":"J.","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":479298,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70044948,"text":"70044948 - 2013 - History and evaluation of national-scale geochemical data sets for the United States","interactions":[],"lastModifiedDate":"2025-05-14T19:20:27.255318","indexId":"70044948","displayToPublicDate":"2013-06-04T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1814,"text":"Geoscience Frontiers","active":true,"publicationSubtype":{"id":10}},"title":"History and evaluation of national-scale geochemical data sets for the United States","docAbstract":"Six national-scale, or near national-scale, geochemical data sets for soils or stream sediments exist for the United States. The earliest of these, here termed the ‘Shacklette’ data set, was generated by a U.S. Geological Survey (USGS) project conducted from 1961 to 1975. This project used soil collected from a depth of about 20 cm as the sampling medium at 1323 sites throughout the conterminous U.S. The National Uranium Resource Evaluation Hydrogeochemical and Stream Sediment Reconnaissance (NURE-HSSR) Program of the U.S. Department of Energy was conducted from 1975 to 1984 and collected either stream sediments, lake sediments, or soils at more than 378,000 sites in both the conterminous U.S. and Alaska. The sampled area represented about 65% of the nation. The Natural Resources Conservation Service (NRCS), from 1978 to 1982, collected samples from multiple soil horizons at sites within the major crop-growing regions of the conterminous U.S. This data set contains analyses of more than 3000 samples. The National Geochemical Survey, a USGS project conducted from 1997 to 2009, used a subset of the NURE-HSSR archival samples as its starting point and then collected primarily stream sediments, with occasional soils, in the parts of the U.S. not covered by the NURE-HSSR Program. This data set contains chemical analyses for more than 70,000 samples. The USGS, in collaboration with the Mexican Geological Survey and the Geological Survey of Canada, initiated soil sampling for the North American Soil Geochemical Landscapes Project in 2007. Sampling of three horizons or depths at more than 4800 sites in the U.S. was completed in 2010, and chemical analyses are currently ongoing. The NRCS initiated a project in the 1990s to analyze the various soil horizons from selected pedons throughout the U.S. This data set currently contains data from more than 1400 sites. This paper (1) discusses each data set in terms of its purpose, sample collection protocols, and analytical methods; and (2) evaluates each data set in terms of its appropriateness as a national-scale geochemical database and its usefulness for national-scale geochemical mapping.","language":"English","publisher":"Elsevier","doi":"10.1016/j.gsf.2012.07.002","usgsCitation":"Smith, D., Smith, S.M., and Horton, J.D., 2013, History and evaluation of national-scale geochemical data sets for the United States: Geoscience Frontiers, v. 4, no. 2, p. 167-183, https://doi.org/10.1016/j.gsf.2012.07.002.","productDescription":"17 p.","startPage":"167","endPage":"183","ipdsId":"IP-030636","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":473776,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gsf.2012.07.002","text":"Publisher Index Page"},{"id":273160,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Conterminous United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"geometry\": {\n        \"type\": \"MultiPolygon\",\n        \"coordinates\": [\n          [\n            [\n              [\n                -94.81758,\n                49.38905\n              ],\n              [\n                -94.64,\n                48.84\n              ],\n              [\n                -94.32914,\n                48.67074\n              ],\n              [\n                -93.63087,\n                48.60926\n              ],\n              [\n                -92.61,\n                48.45\n              ],\n              [\n                -91.64,\n                48.14\n              ],\n              [\n                -90.83,\n            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]\n}","volume":"4","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51aefe59e4b08a3322c2c260","contributors":{"authors":[{"text":"Smith, David B. 0000-0001-8396-9105 dsmith@usgs.gov","orcid":"https://orcid.org/0000-0001-8396-9105","contributorId":1274,"corporation":false,"usgs":true,"family":"Smith","given":"David B.","email":"dsmith@usgs.gov","affiliations":[{"id":218,"text":"Denver Federal Center","active":false,"usgs":true}],"preferred":false,"id":476499,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, Steven M. 0000-0003-3591-5377 smsmith@usgs.gov","orcid":"https://orcid.org/0000-0003-3591-5377","contributorId":1460,"corporation":false,"usgs":true,"family":"Smith","given":"Steven","email":"smsmith@usgs.gov","middleInitial":"M.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"preferred":true,"id":476500,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Horton, John D. 0000-0003-2969-9073 jhorton@usgs.gov","orcid":"https://orcid.org/0000-0003-2969-9073","contributorId":1227,"corporation":false,"usgs":true,"family":"Horton","given":"John","email":"jhorton@usgs.gov","middleInitial":"D.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":476498,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70045505,"text":"70045505 - 2013 - Heterogeneous rupture in the great Cascadia earthquake of 1700 inferred from coastal subsidence estimates","interactions":[],"lastModifiedDate":"2013-07-01T09:59:20","indexId":"70045505","displayToPublicDate":"2013-06-03T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2314,"text":"Journal of Geophysical Research B: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Heterogeneous rupture in the great Cascadia earthquake of 1700 inferred from coastal subsidence estimates","docAbstract":"Past earthquake rupture models used to explain paleoseismic estimates of coastal subsidence during the great A.D. 1700 Cascadia earthquake have assumed a uniform slip distribution along the megathrust. Here we infer heterogeneous slip for the Cascadia margin in A.D. 1700 that is analogous to slip distributions during instrumentally recorded great subduction earthquakes worldwide. The assumption of uniform distribution in previous rupture models was due partly to the large uncertainties of then available paleoseismic data used to constrain the models. In this work, we use more precise estimates of subsidence in 1700 from detailed tidal microfossil studies. We develop a 3-D elastic dislocation model that allows the slip to vary both along strike and in the dip direction. Despite uncertainties in the updip and downdip slip extensions, the more precise subsidence estimates are best explained by a model with along-strike slip heterogeneity, with multiple patches of high-moment release separated by areas of low-moment release. For example, in A.D. 1700, there was very little slip near Alsea Bay, Oregon (~44.4°N), an area that coincides with a segment boundary previously suggested on the basis of gravity anomalies. A probable subducting seamount in this area may be responsible for impeding rupture during great earthquakes. Our results highlight the need for more precise, high-quality estimates of subsidence or uplift during prehistoric earthquakes from the coasts of southern British Columbia, northern Washington (north of 47°N), southernmost Oregon, and northern California (south of 43°N), where slip distributions of prehistoric earthquakes are poorly constrained.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Geophysical Research B: Solid Earth","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"AGU","doi":"10.1002/jgrb.50101","usgsCitation":"Wang, P., Engelhart, S.E., Wang, K., Hawkes, A., Horton, B.P., Nelson, A.R., and Witter, R., 2013, Heterogeneous rupture in the great Cascadia earthquake of 1700 inferred from coastal subsidence estimates: Journal of Geophysical Research B: Solid Earth, v. 118, no. 5, p. 2460-2473, https://doi.org/10.1002/jgrb.50101.","productDescription":"14 p.","startPage":"2460","endPage":"2473","ipdsId":"IP-043739","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":473779,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jgrb.50101","text":"Publisher Index Page"},{"id":273088,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":273086,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/jgrb.50101"}],"country":"United States;Canada","state":"British Columbia;Washington;Oregon;California","otherGeospatial":"Cascadia","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -139.1,32.5 ], [ -139.1,60.0 ], [ -114.1,60.0 ], [ -114.1,32.5 ], [ -139.1,32.5 ] ] ] } } ] }","volume":"118","issue":"5","noUsgsAuthors":false,"publicationDate":"2013-05-15","publicationStatus":"PW","scienceBaseUri":"51adace2e4b07c214e64bcbf","contributors":{"authors":[{"text":"Wang, Pei-Ling","contributorId":44066,"corporation":false,"usgs":true,"family":"Wang","given":"Pei-Ling","email":"","affiliations":[],"preferred":false,"id":477663,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Engelhart, Simon E.","contributorId":60104,"corporation":false,"usgs":false,"family":"Engelhart","given":"Simon","email":"","middleInitial":"E.","affiliations":[{"id":6923,"text":"University of Rhode Island, Kingston, RI","active":true,"usgs":false}],"preferred":false,"id":477664,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wang, Kelin","contributorId":15266,"corporation":false,"usgs":true,"family":"Wang","given":"Kelin","affiliations":[],"preferred":false,"id":477661,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hawkes, Andrea D.","contributorId":20240,"corporation":false,"usgs":true,"family":"Hawkes","given":"Andrea D.","affiliations":[],"preferred":false,"id":477662,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Horton, Benjamin P.","contributorId":63641,"corporation":false,"usgs":true,"family":"Horton","given":"Benjamin","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":477665,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nelson, Alan R. 0000-0001-7117-7098 anelson@usgs.gov","orcid":"https://orcid.org/0000-0001-7117-7098","contributorId":812,"corporation":false,"usgs":true,"family":"Nelson","given":"Alan","email":"anelson@usgs.gov","middleInitial":"R.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":477659,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Witter, Robert C. 0000-0002-1721-254X rwitter@usgs.gov","orcid":"https://orcid.org/0000-0002-1721-254X","contributorId":4528,"corporation":false,"usgs":true,"family":"Witter","given":"Robert C.","email":"rwitter@usgs.gov","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":477660,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70046244,"text":"fs20133022 - 2013 - UNLV’s environmentally friendly Science and Engineering Building is monitored for earthquake shaking","interactions":[],"lastModifiedDate":"2013-06-03T19:04:56","indexId":"fs20133022","displayToPublicDate":"2013-06-03T00:00:00","publicationYear":"2013","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":"2013-3022","title":"UNLV’s environmentally friendly Science and Engineering Building is monitored for earthquake shaking","docAbstract":"The University of Nevada Las Vegas’ (UNLV) Science and Engineering Building is at the cutting edge of environmentally friendly design. As the result of a recent effort by the U.S. Geological Survey’s National Strong Motion Project in cooperation with UNLV, the building is now also in the forefront of buildings installed with structural monitoring systems to measure response during earthquakes. This is particularly important because this is the first such building in Las Vegas. The seismic instrumentation will provide essential data to better understand the structural performance of buildings, especially in this seismically active region.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20133022","collaboration":"In cooperation with University of Nevada, Las Vegas","usgsCitation":"Kalkan, E., Savage, W., Reza, S., Knight, E., and Tian, Y., 2013, UNLV’s environmentally friendly Science and Engineering Building is monitored for earthquake shaking: U.S. Geological Survey Fact Sheet 2013-3022, 4 p., https://doi.org/10.3133/fs20133022.","productDescription":"4 p.","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":273134,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20133022.gif"},{"id":273132,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2013/3022/"},{"id":273133,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2013/3022/fs2013-3022.pdf"}],"country":"United States","state":"Nevada","city":"Las Vegas","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -115.136391,36.043348 ], [ -115.136391,36.045125 ], [ -115.134986,36.045125 ], [ -115.134986,36.043348 ], [ -115.136391,36.043348 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51adace5e4b07c214e64bcd3","contributors":{"authors":[{"text":"Kalkan, Erol 0000-0002-9138-9407 ekalkan@usgs.gov","orcid":"https://orcid.org/0000-0002-9138-9407","contributorId":1218,"corporation":false,"usgs":true,"family":"Kalkan","given":"Erol","email":"ekalkan@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":479272,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Savage, Woody","contributorId":46395,"corporation":false,"usgs":true,"family":"Savage","given":"Woody","email":"","affiliations":[],"preferred":false,"id":479274,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reza, Shahneam sreza@usgs.gov","contributorId":5361,"corporation":false,"usgs":true,"family":"Reza","given":"Shahneam","email":"sreza@usgs.gov","affiliations":[],"preferred":true,"id":479273,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Knight, Eric","contributorId":56543,"corporation":false,"usgs":true,"family":"Knight","given":"Eric","email":"","affiliations":[],"preferred":false,"id":479275,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Tian, Ying","contributorId":92955,"corporation":false,"usgs":true,"family":"Tian","given":"Ying","email":"","affiliations":[],"preferred":false,"id":479276,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70046235,"text":"70046235 - 2013 - The timing of scour and fill in a gravel-bedded river measured with buried accelerometers","interactions":[],"lastModifiedDate":"2016-05-27T13:26:16","indexId":"70046235","displayToPublicDate":"2013-06-03T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"The timing of scour and fill in a gravel-bedded river measured with buried accelerometers","docAbstract":"<p>A device that measures the timing of streambed scour and the duration of sediment mobilization at specific depths of a streambed was developed using data-logging accelerometers placed within the gravel substrate of the Cedar River, Washington, USA. Each accelerometer recorded its orientation every 20 min and remained stable until the surrounding gravel matrix mobilized as sediment was transported downstream and scour reached the level of the accelerometer. The accelerometer scour monitors were deployed at 26 locations in salmon-spawning habitat during the 2010&ndash;2011 flood season to record when the streambed was scoured to the depth of typical egg-pocket deposition. Scour was recorded at one location during a moderate high-flow event (65 m<sup>3</sup>/s; 1.25&ndash;1.5-year recurrence interval) and at 17 locations during a larger high-flow event (159 m<sup>3</sup>/s; 7-year recurrence interval). Accelerometer scour monitors recorded periods of intermittent sediment mobilization and stability within a high-flow event providing insight into the duration of scour. Most scour was recorded during the rising limb and at the peak of a flood hydrograph, though some scour occurred during sustained high flows following the peak of the flood hydrograph.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2013.05.012","usgsCitation":"Gendaszek, A.S., Magirl, C.S., Czuba, C.R., and Konrad, C.P., 2013, The timing of scour and fill in a gravel-bedded river measured with buried accelerometers: Journal of Hydrology, v. 495, p. 186-196, https://doi.org/10.1016/j.jhydrol.2013.05.012.","productDescription":"11 p.","startPage":"186","endPage":"196","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-044142","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":273131,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":273130,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.jhydrol.2013.05.012"}],"volume":"495","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51adace4e4b07c214e64bccf","contributors":{"authors":[{"text":"Gendaszek, Andrew S. 0000-0002-2373-8986 agendasz@usgs.gov","orcid":"https://orcid.org/0000-0002-2373-8986","contributorId":3509,"corporation":false,"usgs":true,"family":"Gendaszek","given":"Andrew","email":"agendasz@usgs.gov","middleInitial":"S.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":479250,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Magirl, Christopher S. 0000-0002-9922-6549 magirl@usgs.gov","orcid":"https://orcid.org/0000-0002-9922-6549","contributorId":1822,"corporation":false,"usgs":true,"family":"Magirl","given":"Christopher","email":"magirl@usgs.gov","middleInitial":"S.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true},{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":479249,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":479251,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Konrad, Christopher P. 0000-0002-7354-547X cpkonrad@usgs.gov","orcid":"https://orcid.org/0000-0002-7354-547X","contributorId":1716,"corporation":false,"usgs":true,"family":"Konrad","given":"Christopher","email":"cpkonrad@usgs.gov","middleInitial":"P.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":479248,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
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