{"pageNumber":"546","pageRowStart":"13625","pageSize":"25","recordCount":46856,"records":[{"id":70068733,"text":"70068733 - 2014 - Residence time control on hot moments of net nitrate production and uptake in the hyporheic zone","interactions":[],"lastModifiedDate":"2014-05-29T14:13:08","indexId":"70068733","displayToPublicDate":"2014-01-13T10:39:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Residence time control on hot moments of net nitrate production and uptake in the hyporheic zone","docAbstract":"The retention capacity for biologically available nitrogen within streams can be influenced by dynamic hyporheic zone exchange, a process that may act as either a net source or net sink of dissolved nitrogen. Over 5 weeks, nine vertical profiles of streambed chemistry (NO<sub>3</sub><sup>-</sup> and NH<sub>4</sub><sup>+</sup>) were collected above two beaver dams along with continuous high-resolution vertical hyporheic flux data. The results indicate a non-linear relation of net NO<sub>3</sub><sup>-</sup> production followed by net uptake in the hyporheic zone as a function of residence time. This Lagrangian-based relation is consistent through time and across varied morphology (bars, pools, glides) above the dams, even though biogeochemical and environmental factors varied. The empirical continuum between net NO<sub>3</sub><sup>-</sup>\n production and uptake and residence time is useful for identifying two crucial residence time thresholds: the transition to anaerobic respiration, which corresponds to the time of peak net nitrate production, and the net sink threshold, which is defined by a net uptake in NO<sub>3</sub><sup>-</sup>  relative to streamwater. Short-term hyporheic residence time variability at specific locations creates hot\nmoments of net production and uptake, enhancing NO<sub>3</sub><sup>-</sup>  production as residence times approach the anaerobic threshold, and changing zones of net NO<sub>3</sub><sup>-</sup> production to uptake as residence times increase past the net sink threshold. The anaerobic and net sink thresholds for beaver-influenced streambed morphology occur at much shorter residence times (1.3 h and 2.3 h, respectively) compared to other documented hyporheic systems, and the net sink threshold compares favorably to the lower boundary of the anaerobic threshold determined for this system with the new oxygen Damkohler number. The consistency of the residence time threshold values of NO<sub>3</sub><sup>-</sup> cycling in this study, despite environmental variability and disparate morphology, indicates that NO<sub>3</sub><sup>-</sup> hot moment dynamics are primarily driven by changes in physical hydrology and associated residence times.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Hydrological Processes","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1002/hyp.9921","usgsCitation":"Briggs, M., Lautz, L.K., and Hare, D.K., 2014, Residence time control on hot moments of net nitrate production and uptake in the hyporheic zone: Hydrological Processes, v. 28, no. 11, p. 3741-3751, https://doi.org/10.1002/hyp.9921.","productDescription":"11 p.","startPage":"3741","endPage":"3751","numberOfPages":"11","ipdsId":"IP-043725","costCenters":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true}],"links":[{"id":280854,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":280853,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/hyp.9921"}],"volume":"28","issue":"11","noUsgsAuthors":false,"publicationDate":"2013-06-28","publicationStatus":"PW","scienceBaseUri":"52d50bcee4b0f19e63d9b385","contributors":{"authors":[{"text":"Briggs, Martin A.","contributorId":10321,"corporation":false,"usgs":true,"family":"Briggs","given":"Martin A.","affiliations":[],"preferred":false,"id":488076,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lautz, Laura K.","contributorId":38890,"corporation":false,"usgs":true,"family":"Lautz","given":"Laura","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":488077,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hare, Danielle K.","contributorId":76222,"corporation":false,"usgs":true,"family":"Hare","given":"Danielle","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":488078,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70040452,"text":"70040452 - 2014 - Geochemistry of hydrothermal alteration at the Qolqoleh gold deposit, northern Sanandaj–Sirjan metamorphic belt, northwestern Iran: Vectors to high-grade ore bodies","interactions":[],"lastModifiedDate":"2021-02-05T16:46:49.1799","indexId":"70040452","displayToPublicDate":"2014-01-13T10:32:39","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2302,"text":"Journal of Geochemical Exploration","active":true,"publicationSubtype":{"id":10}},"title":"Geochemistry of hydrothermal alteration at the Qolqoleh gold deposit, northern Sanandaj–Sirjan metamorphic belt, northwestern Iran: Vectors to high-grade ore bodies","docAbstract":"<p id=\"sp0005\"><span>The Qolqoleh orogenic gold deposit in the northern part of the Sanandaj–Sirjan metamorphic belt in northwestern Iran is hosted by a steeply dipping sequence of&nbsp;greenschist facies&nbsp;Cretaceous volcano–sedimentary rocks, including mafic to intermediate&nbsp;metavolcanic rocks, sericite and chlorite&nbsp;schist, and marble. Geochemical and&nbsp;petrochemical&nbsp;data including the ∑</span>&nbsp;<span>REE, (La/Yb)</span><sub>N</sub><span>&nbsp;and Eu/Eu* ratios were obtained from country rocks, ore-enveloping alteration zones, and mineralized zones to assess the nature of the trace element and&nbsp;rare earth element&nbsp;(REE) interaction between the wall rock and the mineralizing fluid.</span></p><p id=\"sp0010\">Quartz–sulfide veins at the deposit are characterized by a pyrite–pyrrhotite–chalcopyrite–sphalerite–arsenopyrite–native gold assemblage. Alteration halos border the mineralized zones and broadly comprise: (1) an outer carbonate–chlorite alteration zone in all rock types, particularly in chlorite schist; (2) a middle sericite–carbonate alteration zone in the sericite schist; and (3) an inner quartz–sulfide alteration zone in sericite schist and mafic to intermediate metavolcanic rocks.</p><p id=\"sp0015\">The geochemical data indicate that the concentrations of Al<sub>2</sub>O<sub>3</sub>, P<sub>2</sub>O<sub>5</sub>, TiO<sub>2</sub><span>, Y, and Zr are relatively constant, suggesting that these elements were the least mobile during&nbsp;hydrothermal activity. Using Al</span><sub>2</sub>O<sub>3</sub><span>&nbsp;</span>as the immobile component, there is evidence for mobility of trace elements, particularly light REE, TiO<sub>2</sub>, and Zr in the altered wall rocks. The altered rocks show a relatively light REE depletion ((La/Yb)<sub>N</sub>&nbsp;≅&nbsp;<span>9.41), which clearly correlates with the grades of gold&nbsp;mineralization&nbsp;and intensity of the alteration (3</span>&nbsp;ppm Au). The depletion of light REE is best indicated by a decrease in (La/Yb)<sub>N</sub><span>&nbsp;as shown by ratios of 10.5 to 11.8. Wall rock&nbsp;decarbonation&nbsp;reactions during&nbsp;infiltration&nbsp;of the mineralizing fluid resulted in differential mobilization of REE, from a fluid with initially low REE content.</span></p><p id=\"sp0020\"><span>The overall trace element&nbsp;geochemistry&nbsp;of the altered wall rock is controlled by the initial composition of the wall rocks and the ore-fluid composition. Hydrothermal ore-forming fluids are recognized as CO</span><sub>2</sub>-rich near-neutral reduced fluids with high values of H<sub>2</sub><span>S, K, and S content. Observed variability in alteration halos at the Qolqoleh deposit points to major differences in REE and trace element content in original host rocks that have interacted with a relatively similar ore fluid. Therefore, depending on the composition of each host rock&nbsp;lithology, the geochemistry of&nbsp;hydrothermal alteration&nbsp;(e.g., ∑</span>&nbsp;REE content and (La/Yb)<sub>N</sub><span>&nbsp;ratios) and alteration&nbsp;mineralogy&nbsp;including the carbonate–sericite–quartz–sulfide assemblages may be used as a primary tool for lithogeochemical exploration for gold deposits in northwestern Iran.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.gexplo.2014.01.007","usgsCitation":"Aliyari, F., Rastad, E., Goldfarb, R.J., and Sharif, J.A., 2014, Geochemistry of hydrothermal alteration at the Qolqoleh gold deposit, northern Sanandaj–Sirjan metamorphic belt, northwestern Iran: Vectors to high-grade ore bodies: Journal of Geochemical Exploration, v. 140, p. 111-125, https://doi.org/10.1016/j.gexplo.2014.01.007.","productDescription":"15 p.","startPage":"111","endPage":"125","ipdsId":"IP-036917","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":383052,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Iran","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              57.19482421875,\n              27.00040800352175\n            ],\n            [\n              54.03076171874999,\n              31.484893386890164\n            ],\n            [\n              49.41650390625,\n              35.17380831799959\n            ],\n            [\n              46.91162109375,\n              37.3002752813443\n            ],\n            [\n              45.74707031249999,\n              37.24782120155428\n            ],\n            [\n              45.615234375,\n              34.161818161230386\n            ],\n            [\n              48.2958984375,\n              31.690781806136822\n            ],\n            [\n              50.5810546875,\n              29.630771207229\n            ],\n            [\n              51.2841796875,\n              28.14950321154457\n            ],\n            [\n              52.71240234375,\n              27.31321389856826\n            ],\n            [\n              54.29443359375,\n              26.54922257769204\n            ],\n            [\n              57.23876953124999,\n              26.92206991673282\n            ],\n            [\n              57.19482421875,\n              27.00040800352175\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"140","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Aliyari, Farhang","contributorId":248790,"corporation":false,"usgs":false,"family":"Aliyari","given":"Farhang","email":"","affiliations":[],"preferred":false,"id":809866,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rastad, Ebrahim","contributorId":119934,"corporation":false,"usgs":true,"family":"Rastad","given":"Ebrahim","email":"","affiliations":[],"preferred":false,"id":514686,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Goldfarb, Richard J. goldfarb@usgs.gov","contributorId":1205,"corporation":false,"usgs":true,"family":"Goldfarb","given":"Richard","email":"goldfarb@usgs.gov","middleInitial":"J.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":809867,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sharif, Jafar Abdollah","contributorId":116151,"corporation":false,"usgs":true,"family":"Sharif","given":"Jafar","email":"","middleInitial":"Abdollah","affiliations":[],"preferred":false,"id":514683,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70048919,"text":"sim3219 - 2014 - Sedimentation survey of Lago Loíza, Trujillo Alto, Puerto Rico, July 2009","interactions":[],"lastModifiedDate":"2014-01-13T09:20:25","indexId":"sim3219","displayToPublicDate":"2014-01-13T09:05:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3219","title":"Sedimentation survey of Lago Loíza, Trujillo Alto, Puerto Rico, July 2009","docAbstract":"Lago Loíza is a reservoir formed at the confluence of Río Gurabo and Río Grande de Loíza in the municipality of Trujillo Alto in central Puerto Rico, about 10 kilometers (km) north of the town of Caguas, about 9 km northwest of Gurabo, and about 3 km south of Trujillo Alto (fig. 1). The Carraizo Dam is owned and operated by the Puerto Rico Aqueduct and Sewer Authority (PRASA), and was constructed in 1953 as a water-supply reservoir for the San Juan Metropolitan area. The dam is a concrete gravity structure that is located in a shallow valley and has a gently sloping left abutment and steep right abutment. Non-overflow sections flank the spillway section. Waterways include an intake structure for the pumping station and power plant, sluiceways, a trash sluice, and a spillway.\n\nThe reservoir was built to provide a storage capacity of 26.8 million cubic meters (Mm<sup>3</sup>) of water at the maximum pool elevation of 41.14 meters (m) above mean sea level (msl) for the Sergio Cuevas Filtration Plant that serves the San Juan metropolitan area. The reservoir has a drainage area of 538 square kilometers (km<sup>2</sup>) and receives an annual mean rainfall that ranges from 1,600 to 5,000 millimeters per year (mm/yr). The principal streams that drain into Lago Loíza are the Río Grande de Loíza, Río Gurabo, and Río Cañas. Two other rivers, the Río Bairoa and Río Cagüitas, discharge into the Río Grande de Loíza just before it enters the reservoir. The combined mean annual runoff of the Río Grande de Loíza and the Río Gurabo for the 1960–2009 period of record is 323 Mm<sup>3</sup>. Flow from these streams constitutes about 89 percent of the total mean annual inflow of 364 Mm<sup>3</sup> to the reservoir (U.S. Geological Survey, 2009). Detailed information about Lago Loíza reservoir structures, historical sediment accumulation, and a dredge conducted in 1999 are available in Soler-López and Gómez-Gómez (2005).\n\nDuring July 8–15, 2009, the U.S. Geological Survey (USGS) Caribbean Water Science Center (CWSC), in cooperation with PRASA, conducted a bathymetric survey of Lago Loíza to update the reservoir storage capacity and estimate the reservoir sedimentation rate by comparing the 2009 data with the previous 2004 bathymetric survey data. The purpose of this report is to document the methods used to update and present the results of the reservoir storage capacity, sedimentation rates, and areas of substantial sediment accumulation since 2004.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3219","collaboration":"Prepared in cooperation with the Puerto Rico Aqueduct and Sewer Authority","usgsCitation":"Soler-Lopez, L.R., and Licha-Soler, N., 2014, Sedimentation survey of Lago Loíza, Trujillo Alto, Puerto Rico, July 2009: U.S. Geological Survey Scientific Investigations Map 3219, 30.14 inches x 31.62 inches, https://doi.org/10.3133/sim3219.","productDescription":"30.14 inches x 31.62 inches","additionalOnlineFiles":"N","ipdsId":"IP-023006","costCenters":[{"id":156,"text":"Caribbean Water Science Center","active":true,"usgs":true}],"links":[{"id":280832,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sim3219.jpg"},{"id":280830,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3219/"},{"id":280831,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3219/pdf/SIM3219.pdf"}],"projection":"Lambert conformal conic","datum":"Puerto Rico datum, 1940 adjustment","country":"United States","otherGeospatial":"Puerto Rico","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -66.041667,18.266667 ], [ -66.041667,18.325000 ], [ -66.000000,18.325000 ], [ -66.000000,18.266667 ], [ -66.041667,18.266667 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52d50bd0e4b0f19e63d9b38d","contributors":{"authors":[{"text":"Soler-Lopez, Luis R.","contributorId":27501,"corporation":false,"usgs":true,"family":"Soler-Lopez","given":"Luis","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":485811,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Licha-Soler, N.A.","contributorId":60945,"corporation":false,"usgs":true,"family":"Licha-Soler","given":"N.A.","email":"","affiliations":[],"preferred":false,"id":485812,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70068459,"text":"ofr20131305 - 2014 - Global surface displacement data for assessing variability of displacement at a point on a fault","interactions":[],"lastModifiedDate":"2014-01-10T15:18:00","indexId":"ofr20131305","displayToPublicDate":"2014-01-10T15:01:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-1305","title":"Global surface displacement data for assessing variability of displacement at a point on a fault","docAbstract":"<p>This report presents a global dataset of site-specific surface-displacement data on faults. We have compiled estimates of successive displacements attributed to individual earthquakes, mainly paleoearthquakes, at sites where two or more events have been documented, as a basis for analyzing inter-event variability in surface displacement on continental faults.</p>\n<br/>\n<p>An earlier version of this composite dataset was used in a recent study relating the variability of surface displacement at a point to the magnitude-frequency distribution of earthquakes on faults, and to hazard from fault rupture (Hecker and others, 2013). The purpose of this follow-on report is to provide potential data users with an updated comprehensive dataset, largely complete through 2010 for studies in English-language publications, as well as in some unpublished reports and abstract volumes.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131305","usgsCitation":"Hecker, S., Sickler, R., Feigelson, L., Abrahamson, N., Hassett, W., Rosa, C., and Sanquini, A., 2014, Global surface displacement data for assessing variability of displacement at a point on a fault: U.S. Geological Survey Open-File Report 2013-1305, Report: iv, 28 p.; Table 1, https://doi.org/10.3133/ofr20131305.","productDescription":"Report: iv, 28 p.; Table 1","numberOfPages":"32","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-049003","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":379,"text":"Menlo Park Science Center","active":false,"usgs":true}],"links":[{"id":280824,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131305.PNG"},{"id":280822,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1305/pdf/ofr2013-1305.pdf"},{"id":280823,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2013/1305/downloads/ofr2013-1305_Table1.xlsx"},{"id":280821,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1305/"}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -180.0,-90.0 ], [ -180.0,90.0 ], [ 180.0,90.0 ], [ 180.0,-90.0 ], [ -180.0,-90.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52d11766e4b072eb3e0c4b7b","contributors":{"authors":[{"text":"Hecker, Suzanne 0000-0002-5054-372X shecker@usgs.gov","orcid":"https://orcid.org/0000-0002-5054-372X","contributorId":3553,"corporation":false,"usgs":true,"family":"Hecker","given":"Suzanne","email":"shecker@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":488016,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sickler, Robert","contributorId":89653,"corporation":false,"usgs":true,"family":"Sickler","given":"Robert","affiliations":[],"preferred":false,"id":488020,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Feigelson, Leah","contributorId":105636,"corporation":false,"usgs":true,"family":"Feigelson","given":"Leah","email":"","affiliations":[],"preferred":false,"id":488022,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Abrahamson, Norman","contributorId":66990,"corporation":false,"usgs":true,"family":"Abrahamson","given":"Norman","affiliations":[],"preferred":false,"id":488019,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hassett, Will","contributorId":100279,"corporation":false,"usgs":true,"family":"Hassett","given":"Will","email":"","affiliations":[],"preferred":false,"id":488021,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rosa, Carla","contributorId":27780,"corporation":false,"usgs":true,"family":"Rosa","given":"Carla","affiliations":[],"preferred":false,"id":488017,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sanquini, Ann","contributorId":65374,"corporation":false,"usgs":true,"family":"Sanquini","given":"Ann","email":"","affiliations":[],"preferred":false,"id":488018,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70059781,"text":"ofr20131308 - 2014 - Response of Global Navigation Satellite System receivers to known shaking between 0.2 and 20 Hertz","interactions":[],"lastModifiedDate":"2016-08-29T15:22:23","indexId":"ofr20131308","displayToPublicDate":"2014-01-10T08:12:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-1308","title":"Response of Global Navigation Satellite System receivers to known shaking between 0.2 and 20 Hertz","docAbstract":"<p>Over the past decade, several technological advances have allowed Global Navigation Satellite Systems (GNSS) receivers to have the capability to record displacements at high frequencies, with sampling rates approaching 100 samples per second (sps). In addition, communication and computer hardware and software have allowed various institutions, including the U.S. Geological Survey (USGS), to retrieve, process, and display position changes recorded by a network of GNSS sites with small, less than 1-s delays between the time that the GNSS receiver records signals from a constellation of satellites and the time that the position is estimated (a method known as &ldquo;real-time&rdquo;). These improvements in hardware and software have allowed the USGS to process GNSS (or a subset of the GNSS, the Global Positioning System, GPS) data in real-time at 1 sps with the goal of determining displacements from earthquakes and volcanoes in real-time. However, the current set of GNSS equipment can record at rates of 100 sps, which allows the possibility of using this equipment to record earthquake displacements over the full range of frequencies that typically are recorded by acceleration and velocity transducers. The advantage of using GNSS to record earthquakes is that the displacement, rather than acceleration or velocity, is recorded, and for large earthquakes, the GNSS sensor stays on scale and will not distort the observations due to clipping of the signal at its highest amplitude. The direct observation of displacement is advantageous in estimating the size and spatial extent of the earthquake rupture. Otherwise, when using velocity or acceleration sensors, the displacements are determined by numerical integration of the observations, which can introduce significant uncertainty in the estimated displacements. However, GNSS technology can, at best, resolve displacements of a few millimeters, and for most earthquakes, their displacements are less than 1 mm. Consequently, to be useful, GNSS data are only relevant for the large earthquakes with magnitudes (M) exceeding M5.5 at best.</p>\n<p>With the capability to record GNSS data at high-rate, at sampling rates typical for seismological applications, experiments are needed to quantify the response of GNSS to shaking from earthquakes. There have been a few studies that examine the response of GNSS to strong shaking. One of the first was Elosegui and others (2006), where they simulated surface waves from a distant earthquake and mechanically applied the shaking to a GPS antenna. They processed the 1 sps observations and compared the estimated displacements with the simulated displacements. They determined that the GPS could accurately track the simulated surface wave whose primary frequency spans from 0.01 to 0.1 Hertz (Hz), which spanned the frequency band of the simulation.</p>\n<p>To test GNSS equipment due to shaking from a large earthquake in the near-field, Wang and others (2012) used a mechanical simulator or shake table with 6 degrees of freedom and studied two different inputs to the simulator&mdash;(1) the accelerometer record from one station that was located near the 2010 M8.8 Maule, Chile earthquake, and (2) a 2-Hz sinusoid. Wang and others (2012) analyzed the 2-Hz data with spectral analysis and determined that the displacements observed by the GPS included higher harmonics along with the 2-Hz signal. In addition, the background spectral amplitude was greater during periods of 2-Hz shaking than when at rest. With the simulated M 8.8 earthquake, Wang and others (2012) observed decreased signal to noise for L1 and L2 carrier frequencies of the GPS signal, at times corresponding to high acceleration and jerk (first derivative of acceleration).</p>\n<p>One of the principal limitations of these experiments was that the displacements of the shake table itself could not be measured independently. Although with the 2-Hz sinusoidal measurements, the input displacements were purely translational, Wang and others (2012) analysis of the data showed that the shake table also included rotational motions which affect horizontal inertial sensors like accelerometers and seismometers at first order.</p>\n<p>More recently, Ebinuma and Kato (2012) used a GPS simulator to electronically test several GNSS receivers and obtain the receiver characteristics at three frequencies: 1, 2, and 5 Hz. The results showed that the amplitude of 5-Hz displacements recorded by the GPS was, depending on the receiver model, between 30 and 125 percent more than the displacement input to the simulator. At low frequencies, the GPS displacement was nearly equal to the input displacement. In addition, Ebinuma and Kato (2012) examined how each receiver model amplified an earthquake displacement record in the 2&ndash;8 Hz band. The simulated earthquake was the 2008 moment magnitude (Mw) 6.8 Iwate-Miyagi earthquake where, for the simulated record, acceleration peaked at 1 G.</p>\n<p>The study discussed here builds on the tests by Ebinuma and Kato (2012), but rather than using electronic simulation, the tests are setup outdoors and closer to actual field installations of GNSS equipment. We used a one-dimensional shake table capable of 400 mm of displacement and high acceleration; the shake table also is constrained by a precision linear slider to have very low tilt that would affect inertial sensors. In addition, the stage position can be accurately monitored independent of the GNSS hardware and, importantly, provides a reference to compare with the estimated displacements from the GNSS data. Our tests spanned a greater frequency range from 0.2 to 20 Hz and we used equipment from three different manufacturers covering five different combinations of receivers and antennas. In addition, we have been able to simulate the frequency response of the GNSS equipment using a simple, causal filter. The quality of the filter was tested using additional test data where a step function in displacement was applied to the shake table. The observed displacements from the GNSS data show an overshoot in displacement at the time of the step or transition of the stage. That overshoot was accurately predicted using the filter design derived from our sinusoidal displacement tests.</p>\n<p>Similar to Wang and others (2012), we also examined the GPS displacement records using standard spectral techniques. However, we extended their work by evaluating several models of GNSS receivers using a variety of input frequencies. Because our shake table was limited on acceleration and displacement, we did not attempt to duplicate the high shaking associated with high magnitude earthquakes. However, because our shake table could measure the table displacement, we could directly compare the measured GPS displacements with the true displacements.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131308","usgsCitation":"Langbein, J.O., Evans, J.R., Blume, F., and Johanson, I., 2014, Response of Global Navigation Satellite System receivers to known shaking between 0.2 and 20 Hertz: U.S. Geological Survey Open-File Report 2013-1308, iv, 28 p., https://doi.org/10.3133/ofr20131308.","productDescription":"iv, 28 p.","numberOfPages":"32","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-049015","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":379,"text":"Menlo Park Science Center","active":false,"usgs":true}],"links":[{"id":280804,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131308.PNG"},{"id":280801,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1308/"},{"id":280803,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1308/pdf/ofr2013-1308.pdf","text":"Report","size":"4.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52d11769e4b072eb3e0c4b81","contributors":{"authors":[{"text":"Langbein, John O.","contributorId":72438,"corporation":false,"usgs":true,"family":"Langbein","given":"John","middleInitial":"O.","affiliations":[],"preferred":false,"id":487818,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Evans, John R. jrevans@usgs.gov","contributorId":529,"corporation":false,"usgs":true,"family":"Evans","given":"John","email":"jrevans@usgs.gov","middleInitial":"R.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":487816,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Blume, Fredrick","contributorId":100283,"corporation":false,"usgs":true,"family":"Blume","given":"Fredrick","email":"","affiliations":[],"preferred":false,"id":487819,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Johanson, Ingrid","contributorId":54880,"corporation":false,"usgs":true,"family":"Johanson","given":"Ingrid","affiliations":[],"preferred":false,"id":487817,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70048979,"text":"ofr20131235 - 2014 - Lesser prairie-chicken nest site selection, microclimate, and nest survival in association with vegetation response to a grassland restoration program","interactions":[],"lastModifiedDate":"2014-01-08T13:58:10","indexId":"ofr20131235","displayToPublicDate":"2014-01-08T13:49:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-1235","title":"Lesser prairie-chicken nest site selection, microclimate, and nest survival in association with vegetation response to a grassland restoration program","docAbstract":"Climate models predict that the region of the Great Plains Landscape Conservation Cooperative (GPLCC) will experience increased maximum and minimum temperatures, reduced frequency but greater intensity of precipitation events, and earlier springs. These climate changes along with different landscape management techniques may influence the persistence of the lesser prairie-chicken (Tympanuchus pallidicinctus), a candidate for protection under the Endangered Species Act and a priority species under the GPLCC, in positive or negative ways. The objectives of this study were to conduct (1) a literature review of lesser prairie-chicken nesting phenology and ecology, (2) an analysis of thermal aspects of lesser prairie-chicken nest microclimate data, and (3) an analysis of nest site selection, nest survival, and vegetation response to 10 years of tebuthiuron and/or grazing treatments.\n\nWe found few reports in the literature containing useful data on the nesting phenology of lesser prairie-chickens; therefore, managers must rely on short-term observations and measurements of parameters that provide some predictive insight into climate impacts on nesting ecology. Our field studies showed that prairie-chickens on nests were able to maintain relatively consistent average nest temperature of 31 °C and nest humidities of 56.8 percent whereas average external temperatures (20.3–35.0 °C) and humidities (35.2–74.9 percent) varied widely throughout the 24 hour (hr) cycle. Grazing and herbicide treatments within our experimental areas were designed to be less intensive than in common practice. We determined nest locations by radio-tagging hen lesser prairie-chickens captured at leks, which are display grounds at which male lesser prairie-chickens aggregate and attempt to attract a female for mating. Because nest locations selected by hen lesser prairie-chicken are strongly associated with the lek at which they were captured, we assessed nesting habitat use on the basis of hens captured at individual leks, and then for all leks pooled. There was no clear pattern of selection for treatment type for nest placement among hens associated with individual leks; however, when hens from all leks were pooled, we found nesting lesser prairie-chickens selected control plots for nesting over plots that were grazed, treated with tebuthiuron, or were both grazed and treated with tebuthiuron. Overall, the probability of a nest surviving the incubation period was 0.57 for this study and did not vary significantly among treatment types. In contrast to nesting preference for untreated habitats, lek use exhibited no noticeable selection of treatment type. Over the 10 years of the habitat management study, there was 91 percent less sand shinnery oak (Quercus havardii) in treated areas than untreated areas. The removal of sand shinnery oak made environmental soil moisture more available for grasses and forbs to germinate and grow. Grasses increased by 149 percent and forbs increased by 257 percent in treated areas as compared to untreated areas throughout the study period. Our combined results, including our habitat selection analysis at the individual lek level, indicated that reduced rates of herbicide and short-duration grazing treatments were not detrimental to nesting lesser prairie-chickens and that populations of lesser prairie-chickens in shrub-dominated ecosystems may benefit from reduced rates of herbicide application and short duration of grazing that results in increased habitat heterogeneity.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131235","issn":"2331-1258","collaboration":"Prepared in cooperation with New Mexico Game and Fish and Texas Parks and Wildlife Department","usgsCitation":"Boal, C.W., Grisham, B.A., Haukos, D.A., Zavaleta, J.C., and Dixon, C., 2014, Lesser prairie-chicken nest site selection, microclimate, and nest survival in association with vegetation response to a grassland restoration program: U.S. Geological Survey Open-File Report 2013-1235, x, 35 p., https://doi.org/10.3133/ofr20131235.","productDescription":"x, 35 p.","numberOfPages":"48","onlineOnly":"Y","ipdsId":"IP-042288","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":280746,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131235.jpg"},{"id":280745,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1235/pdf/ofr2013-1235.pdf"},{"id":280744,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1235/"}],"country":"United States","state":"New Mexico;Texas","county":"Cochran County;Hockley County;Roosevelt County;Terry County;Yoakum County","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -103.9475,32.5586 ], [ -103.9475,34.6068 ], [ -101.0989,34.6068 ], [ -101.0989,32.5586 ], [ -103.9475,32.5586 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52ce7482e4b073e0995b2de3","contributors":{"authors":[{"text":"Boal, Clint W. 0000-0001-6008-8911 cboal@usgs.gov","orcid":"https://orcid.org/0000-0001-6008-8911","contributorId":1909,"corporation":false,"usgs":true,"family":"Boal","given":"Clint","email":"cboal@usgs.gov","middleInitial":"W.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":485918,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grisham, Blake A.","contributorId":75419,"corporation":false,"usgs":true,"family":"Grisham","given":"Blake","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":485921,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haukos, David A. 0000-0001-5372-9960 dhaukos@usgs.gov","orcid":"https://orcid.org/0000-0001-5372-9960","contributorId":3664,"corporation":false,"usgs":true,"family":"Haukos","given":"David","email":"dhaukos@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":485919,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zavaleta, Jennifer C.","contributorId":102785,"corporation":false,"usgs":true,"family":"Zavaleta","given":"Jennifer","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":485922,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dixon, Charles","contributorId":68203,"corporation":false,"usgs":true,"family":"Dixon","given":"Charles","email":"","affiliations":[],"preferred":false,"id":485920,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70048697,"text":"70048697 - 2014 - Island history affects faunal composition: the treeshrews (Mammalia: Scandentia: Tupaiidae) from the Mentawai and Batu Islands, Indonesia","interactions":[],"lastModifiedDate":"2016-08-16T14:59:36","indexId":"70048697","displayToPublicDate":"2014-01-08T13:37:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1019,"text":"Biological Journal of the Linnean Society","active":true,"publicationSubtype":{"id":10}},"title":"Island history affects faunal composition: the treeshrews (Mammalia: Scandentia: Tupaiidae) from the Mentawai and Batu Islands, Indonesia","docAbstract":"<p>The Mentawai and Batu Island groups off the west coast of Sumatra have a complicated geological and biogeographical history. The Batu Islands have shared a connection with the Sumatran &lsquo;mainland&rsquo; during periods of lowered sea level, whereas the Mentawai Islands, despite being a similar distance from Sumatra, have remained isolated from Sumatra, and probably from the Batu Islands as well. These contrasting historical relationships to Sumatra have influenced the compositions of the respective mammalian faunas of these island groups. Treeshrews (Scandentia, Tupaiidae) from these islands have, at various times in their history, been recognized as geographically circumscribed populations of a broadly distributed Tupaia glis, subspecies, or distinct species. We used multivariate analyses of measurements from the skull and hands to compare the island populations from Siberut (Mentawai Islands) and Tanahbala (Batu Islands) with the geographically adjacent species from the southern Mentawai Islands (T.&thinsp;chrysogaster) and Sumatra (T.&thinsp;ferruginea). Results from both the skull and manus of the Siberut population show that it is most similar to T.&thinsp;chrysogaster, whereas the Tanahbala population is more similar to T.&thinsp;ferruginea, confirming predictions based on island history. These results are further corroborated by mammae counts. Based on these lines of evidence, we include the Siberut population in T.&thinsp;chrysogaster and the Tanahbala population in T.&thinsp;ferruginea. Our conclusions expand the known distributions of both the Mentawai and Sumatran species. The larger geographical range of the endangered T.&thinsp;chrysogaster has conservation implications for this Mentawai endemic, so populations and habitat should be re-evaluated on each of the islands it inhabits. However, until such a re-evaluation is conducted, we recommend that the IUCN Red List status of this species be changed from &lsquo;Endangered&rsquo; to &lsquo;Data Deficient&rsquo;.</p>","language":"English","publisher":"Wiley","doi":"10.1111/bij.12195","usgsCitation":"Sargis, E.J., Woodman, N., Morningstar, N.C., Reese, A.T., and Olson, L., 2014, Island history affects faunal composition: the treeshrews (Mammalia: Scandentia: Tupaiidae) from the Mentawai and Batu Islands, Indonesia: Biological Journal of the Linnean Society, v. 111, no. 2, p. 290-304, https://doi.org/10.1111/bij.12195.","productDescription":"15 p.","startPage":"290","endPage":"304","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-051997","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":473228,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/bij.12195","text":"Publisher Index Page"},{"id":280742,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":280741,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/bij.12195"}],"country":"Indonesia","otherGeospatial":"Mentawai;Batu Islands","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 93.84,-11.25 ], [ 93.84,6.97 ], [ 131.0,6.97 ], [ 131.0,-11.25 ], [ 93.84,-11.25 ] ] ] } } ] }","volume":"111","issue":"2","noUsgsAuthors":false,"publicationDate":"2014-01-02","publicationStatus":"PW","scienceBaseUri":"52ce7481e4b073e0995b2ddf","contributors":{"authors":[{"text":"Sargis, Eric J.","contributorId":100726,"corporation":false,"usgs":true,"family":"Sargis","given":"Eric","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":485458,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Woodman, Neal 0000-0003-2689-7373 nwoodman@usgs.gov","orcid":"https://orcid.org/0000-0003-2689-7373","contributorId":3547,"corporation":false,"usgs":true,"family":"Woodman","given":"Neal","email":"nwoodman@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":485454,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Morningstar, Natalie C.","contributorId":31293,"corporation":false,"usgs":true,"family":"Morningstar","given":"Natalie","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":485456,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Reese, Aspen T.","contributorId":23826,"corporation":false,"usgs":true,"family":"Reese","given":"Aspen","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":485455,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Olson, Link E.","contributorId":60927,"corporation":false,"usgs":true,"family":"Olson","given":"Link E.","affiliations":[],"preferred":false,"id":485457,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70047737,"text":"70047737 - 2014 - Ground motion in the presence of complex topography: Earthquake and ambient noise sources","interactions":[],"lastModifiedDate":"2016-01-29T11:13:00","indexId":"70047737","displayToPublicDate":"2014-01-08T11:58:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Ground motion in the presence of complex topography: Earthquake and ambient noise sources","docAbstract":"<p>To study the influence of topography on ground motion, eight seismic recorders were deployed for a period of one year over Poverty Ridge on the east side of the San Francisco Bay Area, California. This location is desirable because of its proximity to local earthquake sources and the significant topographic relief of the array (439 m). Topographic amplification is evaluated as a function of frequency using a variety of methods, including reference‐site‐based spectral ratios and single‐station horizontal‐to‐vertical spectral ratios using both shear waves from earthquakes and ambient noise. Field observations are compared with the predicted ground motion from an accurate digital model of the topography and a 3D local velocity model. Amplification factors from the theoretical calculations are consistent with observations. The fundamental resonance of the ridge is prominently observed in the spectra of data and synthetics; however, higher‐frequency peaks are also seen primarily for sources in line with the major axis of the ridge, perhaps indicating higher resonant modes. Excitations of lateral ribs off of the main ridge are also seen at frequencies consistent with their dimensions. The favored directions of resonance are shown to be transverse to the major axes of the topographic features.</p>","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Bulletin of the Seismological Society of America","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Seismological Society of America","publisherLocation":"Stanford","doi":"10.1785/0120130088","usgsCitation":"Hartzell, S.H., Meremonte, M., Ramírez-Guzmán, L., and McNamara, D., 2014, Ground motion in the presence of complex topography: Earthquake and ambient noise sources: Bulletin of the Seismological Society of America, v. 104, no. 1, p. 451-466, https://doi.org/10.1785/0120130088.","productDescription":"16 p.","startPage":"451","endPage":"466","numberOfPages":"16","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-050721","costCenters":[{"id":218,"text":"Denver Federal Center","active":false,"usgs":true}],"links":[{"id":280770,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"Santa Clara Valley","otherGeospatial":"Diablo Mountains; Poverty Ridge","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.0,37.2 ], [ -122.0,37.6 ], [ -121.6,37.6 ], [ -121.6,37.2 ], [ -122.0,37.2 ] ] ] } } ] }","volume":"104","issue":"1","noUsgsAuthors":false,"publicationDate":"2013-11-19","publicationStatus":"PW","scienceBaseUri":"52ce747ee4b073e0995b2dd7","contributors":{"authors":[{"text":"Hartzell, Stephen H. 0000-0003-0858-9043 shartzell@usgs.gov","orcid":"https://orcid.org/0000-0003-0858-9043","contributorId":2594,"corporation":false,"usgs":true,"family":"Hartzell","given":"Stephen","email":"shartzell@usgs.gov","middleInitial":"H.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":482862,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Meremonte, Mark","contributorId":56968,"corporation":false,"usgs":true,"family":"Meremonte","given":"Mark","affiliations":[],"preferred":false,"id":482864,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ramírez-Guzmán, Leonardo","contributorId":45946,"corporation":false,"usgs":true,"family":"Ramírez-Guzmán","given":"Leonardo","affiliations":[],"preferred":false,"id":482863,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McNamara, Daniel","contributorId":103566,"corporation":false,"usgs":true,"family":"McNamara","given":"Daniel","affiliations":[],"preferred":false,"id":482865,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70044825,"text":"70044825 - 2014 - Investigation of off-site airborne transport of lead from a superfund removal action site using lead isotope ratios and concentrations","interactions":[],"lastModifiedDate":"2014-01-08T14:12:51","indexId":"70044825","displayToPublicDate":"2014-01-08T09:08:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":835,"text":"Applied Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Investigation of off-site airborne transport of lead from a superfund removal action site using lead isotope ratios and concentrations","docAbstract":"Lead (Pb) concentration and Pb isotopic composition of surface and subsurface soil samples were used to investigate the potential for off-site air transport of Pb from a former white Pb processing facility to neighboring residential homes in a six block area on Staten Island, NY. Surface and subsurface soil samples collected on the Jewett White Pb site were found to range from 1.122 to 1.138 for <sup>206</sup>Pb/<sup>207</sup>Pb and 2.393 to 2.411 for <sup>208</sup>Pb/<sup>207</sup>Pb. The off-site surface soil samples collected from residential backyards, train trestle, near site grass patches and background areas varied from 1.144 to 1.196 for <sup>206</sup>Pb/<sup>207</sup>Pb and 2.427 to 2.464 for <sup>208</sup>Pb/<sup>207</sup>Pb. Two soil samples collected along Richmond Terrace, where Jewett site soils accumulated after major rain events, varied from 1.136 to 1.147 for <sup>206</sup>Pb/<sup>207</sup>Pb and 2.407 to 2.419 for <sup>208</sup>Pb/<sup>207</sup>Pb. Lead concentration for on-site surface soil samples ranged from 450 to 8000 ug/g, on-site subsurface soil samples ranged from 90,000 to 240,000 ug/g and off-site samples varied from 380 to 3500 ug/g. Lead concentration and isotopic composition for the Staten Island off-site samples were similar to previously published data for other northeastern US cities and reflect re-suspension and re-mobilization of local accumulated Pb. The considerable differences in both the Pb isotopic composition and Pb concentration of on-site and off-site samples resulted in the ability to geochemically trace the transport of particulate Pb. Data in this study indicate minimal off-site surface transport of Pb from the Jewett site into the neighboring residential area.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Applied Geochemistry","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.apgeochem.2013.11.004","usgsCitation":"Pribil, M., Maddaloni, M.A., Staiger, K., Wilson, E., Magriples, N., Ali, M., and Santella, D., 2014, Investigation of off-site airborne transport of lead from a superfund removal action site using lead isotope ratios and concentrations: Applied Geochemistry, v. 41, p. 89-94, https://doi.org/10.1016/j.apgeochem.2013.11.004.","productDescription":"6 p.","startPage":"89","endPage":"94","numberOfPages":"6","ipdsId":"IP-024846","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":280750,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":280749,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.apgeochem.2013.11.004"}],"country":"United States","state":"New York","city":"Staten Island","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -74.181499,40.609152 ], [ -74.181499,40.647384 ], [ -74.096002,40.647384 ], [ -74.096002,40.609152 ], [ -74.181499,40.609152 ] ] ] } } ] }","volume":"41","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52ce7480e4b073e0995b2ddb","contributors":{"authors":[{"text":"Pribil, Michael J.","contributorId":62115,"corporation":false,"usgs":true,"family":"Pribil","given":"Michael J.","affiliations":[],"preferred":false,"id":476378,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Maddaloni, Mark A.","contributorId":66164,"corporation":false,"usgs":true,"family":"Maddaloni","given":"Mark","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":476380,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Staiger, Kimberly","contributorId":74292,"corporation":false,"usgs":true,"family":"Staiger","given":"Kimberly","email":"","affiliations":[],"preferred":false,"id":476381,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wilson, Eric","contributorId":96542,"corporation":false,"usgs":true,"family":"Wilson","given":"Eric","email":"","affiliations":[],"preferred":false,"id":476382,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Magriples, Nick","contributorId":58935,"corporation":false,"usgs":true,"family":"Magriples","given":"Nick","email":"","affiliations":[],"preferred":false,"id":476377,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ali, Mustafa","contributorId":64150,"corporation":false,"usgs":true,"family":"Ali","given":"Mustafa","email":"","affiliations":[],"preferred":false,"id":476379,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Santella, Dennis","contributorId":49695,"corporation":false,"usgs":true,"family":"Santella","given":"Dennis","email":"","affiliations":[],"preferred":false,"id":476376,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70049021,"text":"fs20133084 - 2014 - The 3D Elevation Program: Summary for South Dakota","interactions":[],"lastModifiedDate":"2026-06-12T13:17:44.580435","indexId":"fs20133084","displayToPublicDate":"2014-01-07T15:08:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-3084","title":"The 3D Elevation Program: Summary for South Dakota","docAbstract":"<p>Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, national security, recreation, and many others. For the State of South Dakota, elevation data are critical for agriculture and precision farming, natural resources conservation, water supply and quality, infrastructure and construction management, flood risk management, geologic resource assessment and hazard mitigation, and other business uses. Today, high-density light detection and ranging (lidar) data are the primary sources for deriving elevation models and other datasets. Federal, State, tribal, and local agencies work in partnership to (1) replace data that are older and of lower quality and (2) provide coverage where publicly accessible data do not exist. A joint goal of State and Federal partners is to acquire consistent, statewide coverage to support existing and emerging applications enabled by lidar data.</p>\n<p>The National Enhanced Elevation Assessment (NEEA; Dewberry, 2011) evaluated multiple elevation data acquisition options to determine the optimal data quality and data replacement cycle relative to cost to meet the identified requirements of the user community. The evaluation demonstrated that lidar acquisition at quality level 2 for the conterminous United States and quality level 5 ifsar data for Alaska with a 6- to 10-year acquisition cycle provided the highest benefit/cost ratios.The new 3D Elevation Program (3DEP) initiative selected an 8-year acquisition cycle for the respective quality levels. 3DEP, managed by the U.S. Geological Survey, the Office of Management and Budget Circular A&ndash;16 lead agency for terrestrial elevation data, responds to the growing need for high-quality topographic data and a wide range of other 3D representations of the Nation&rsquo;s natural and constructed features.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20133084","usgsCitation":"Carswell, W., 2014, The 3D Elevation Program: summary for South Dakota: U.S. Geological Survey Fact Sheet 2013-3084, 2 p., https://doi.org/10.3133/fs20133084.","productDescription":"2 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,{"id":70048996,"text":"ofr20131266 - 2014 - Natural heat storage in a brine-filled solar pond in the Tully Valley of central New York","interactions":[],"lastModifiedDate":"2014-01-07T14:27:58","indexId":"ofr20131266","displayToPublicDate":"2014-01-07T14:06:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-1266","title":"Natural heat storage in a brine-filled solar pond in the Tully Valley of central New York","docAbstract":"The Tully Valley, located in southern Onondaga County, New York, has a long history of unusual natural hydrogeologic phenomena including mudboils (Kappel, 2009), landslides (Tamulonis and others, 2009; Pair and others, 2000), landsurface subsidence (Hackett and others, 2009; Kappel, 2009), and a brine-filled sinkhole or “Solar pond” (fig. 1), which is documented in this report. A solar pond is a pool of salty water (brine) which stores the sun’s energy in the form of heat. The saltwater naturally forms distinct layers with increasing density between transitional zones (haloclines) of rapidly changing specific conductance with depth. In a typical solar pond, the top layer has a low salt content and is often times referred to as the upper convective zone (Lu and others, 2002). The bottom layer is a concentrated brine that is either convective or temperature stratified dependent on the surrounding environment. Solar insolation is absorbed and stored in the lower, denser brine while the overlying halocline acts as an insulating layer and prevents heat from moving upwards from the lower zone (Lu and others, 2002). In the case of the Tully Valley solar pond, water within the pond can be over 90 degrees Fahrenheit (&deg;F) in late summer and early fall. The purpose of this report is to summarize observations at the Tully Valley brine-filled sinkhole and provide supplemental climate data which might affect the pond salinity gradients insolation (solar energy).","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131266","issn":"2331-1258","usgsCitation":"Hayhurst, B., and Kappel, W.M., 2014, Natural heat storage in a brine-filled solar pond in the Tully Valley of central New York: U.S. Geological Survey Open-File Report 2013-1266, 14 p., https://doi.org/10.3133/ofr20131266.","productDescription":"14 p.","numberOfPages":"14","onlineOnly":"Y","ipdsId":"IP-044705","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":280666,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131266.jpg"},{"id":280664,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1266/pdf/ofr2013-1266.pdf"},{"id":280665,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1266/"}],"scale":"24000","country":"United States","state":"New York","county":"Onondaga County","otherGeospatial":"Tully Valley","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -76.166667,42.816667 ], [ -76.166667,42.9 ], [ -76.125,42.9 ], [ -76.125,42.816667 ], [ -76.166667,42.816667 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52cd21fee4b0c3f95143ed05","contributors":{"authors":[{"text":"Hayhurst, Brett 0000-0002-1717-2015","orcid":"https://orcid.org/0000-0002-1717-2015","contributorId":96995,"corporation":false,"usgs":true,"family":"Hayhurst","given":"Brett","affiliations":[],"preferred":false,"id":485964,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kappel, William M. 0000-0002-2382-9757 wkappel@usgs.gov","orcid":"https://orcid.org/0000-0002-2382-9757","contributorId":1074,"corporation":false,"usgs":true,"family":"Kappel","given":"William","email":"wkappel@usgs.gov","middleInitial":"M.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":485963,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70059915,"text":"70059915 - 2014 - What do data used to develop ground-motion prediction equations tell us about motions near faults?","interactions":[],"lastModifiedDate":"2016-12-14T11:40:26","indexId":"70059915","displayToPublicDate":"2014-01-06T16:10:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3208,"text":"Pure and Applied Geophysics","active":true,"publicationSubtype":{"id":10}},"title":"What do data used to develop ground-motion prediction equations tell us about motions near faults?","docAbstract":"<p>A large database of ground motions from shallow earthquakes occurring in active tectonic regions around the world, recently developed in the Pacific Earthquake Engineering Center&rsquo;s NGA-West2 project, has been used to investigate what such a database can say about the properties and processes of crustal fault zones. There are a relatively small number of near-rupture records, implying that few recordings in the database are within crustal fault zones, but the records that do exist emphasize the complexity of ground-motion amplitudes and polarization close to individual faults. On average over the whole data set, however, the scaling of ground motions with magnitude at a fixed distance, and the distance dependence of the ground motions, seem to be largely consistent with simple seismological models of source scaling, path propagation effects, and local site amplification. The data show that ground motions close to large faults, as measured by elastic response spectra, tend to saturate and become essentially constant for short periods. This saturation seems to be primarily a geometrical effect, due to the increasing size of the rupture surface with magnitude, and not due to a breakdown in self similarity.</p>","language":"English","publisher":"Springer","doi":"10.1007/s00024-013-0748-9","usgsCitation":"Boore, D.M., 2014, What do data used to develop ground-motion prediction equations tell us about motions near faults?: Pure and Applied Geophysics, v. 171, no. 11, p. 3023-3043, https://doi.org/10.1007/s00024-013-0748-9.","productDescription":"21 p.","startPage":"3023","endPage":"3043","numberOfPages":"21","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-051125","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":280636,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":280635,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s00024-013-0748-9"}],"volume":"171","issue":"11","noUsgsAuthors":false,"publicationDate":"2013-12-15","publicationStatus":"PW","scienceBaseUri":"52cbd084e4b03116c9ddba10","contributors":{"authors":[{"text":"Boore, David M. boore@usgs.gov","contributorId":2509,"corporation":false,"usgs":true,"family":"Boore","given":"David","email":"boore@usgs.gov","middleInitial":"M.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":false,"id":487853,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70160095,"text":"70160095 - 2014 - Comparative recruitment dynamics of Alewife and Bloater in Lakes Michigan and Huron","interactions":[],"lastModifiedDate":"2015-12-11T15:50:51","indexId":"70160095","displayToPublicDate":"2014-01-06T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Comparative recruitment dynamics of Alewife and Bloater in Lakes Michigan and Huron","docAbstract":"<p>The predictive power of recruitment models often relies on the identification and quantification of external variables, in addition to stock size. In theory, the identification of climatic, biotic, or demographic influences on reproductive success assists fisheries management by identifying factors that have a direct and reproducible influence on the population dynamics of a target species. More often, models are constructed as one-time studies of a single population whose results are not revisited when further data become available. Here, we present results from stock recruitment models for Alewife Alosa pseudoharengus and Bloater Coregonus hoyi in Lakes Michigan and Huron. The factors that explain variation in Bloater recruitment were remarkably consistent across populations and with previous studies that found Bloater recruitment to be linked to population demographic patterns in Lake Michigan. Conversely, our models were poor predictors of Alewife recruitment in Lake Huron but did show some agreement with previously published models from Lake Michigan. Overall, our results suggest that external predictors of fish recruitment are difficult to discern using traditional fisheries models, and reproducing the results from previous studies may be difficult particularly at low population sizes.</p>","language":"English","publisher":"Taylor & Francis","doi":"10.1080/00028487.2013.833986","collaboration":"University of Michigan","usgsCitation":"Collingsworth, P.D., Bunnell, D., Madenjian, C.P., and Riley, S.C., 2014, Comparative recruitment dynamics of Alewife and Bloater in Lakes Michigan and Huron: Transactions of the American Fisheries Society, v. 143, no. 1, p. 294-309, https://doi.org/10.1080/00028487.2013.833986.","productDescription":"16 p.","startPage":"294","endPage":"309","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-049393","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":473233,"rank":0,"type":{"id":41,"text":"Open Access External Repository 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Center","active":true,"usgs":true}],"preferred":false,"id":581990,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Madenjian, Charles P. 0000-0002-0326-164X cmadenjian@usgs.gov","orcid":"https://orcid.org/0000-0002-0326-164X","contributorId":2200,"corporation":false,"usgs":true,"family":"Madenjian","given":"Charles","email":"cmadenjian@usgs.gov","middleInitial":"P.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":581991,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Riley, Stephen C. 0000-0002-8968-8416 sriley@usgs.gov","orcid":"https://orcid.org/0000-0002-8968-8416","contributorId":2661,"corporation":false,"usgs":true,"family":"Riley","given":"Stephen","email":"sriley@usgs.gov","middleInitial":"C.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":581992,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70065876,"text":"70065876 - 2014 - Geographic variability in elevation and topographic constraints on the distribution of native and nonnative trout in the Great Basin","interactions":[],"lastModifiedDate":"2014-01-07T15:46:30","indexId":"70065876","displayToPublicDate":"2014-01-01T15:41:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Geographic variability in elevation and topographic constraints on the distribution of native and nonnative trout in the Great Basin","docAbstract":"Understanding local and geographic factors influencing species distributions is a prerequisite for conservation planning. Our objective in this study was to model local and geographic variability in elevations occupied by native and nonnative trout in the northwestern Great Basin, USA. To this end, we analyzed a large existing data set of trout presence (5,156 observations) to evaluate two fundamental factors influencing occupied elevations: climate-related gradients in geography and local constraints imposed by topography. We applied quantile regression to model upstream and downstream distribution elevation limits for each trout species commonly found in the region (two native and two nonnative species). With these models in hand, we simulated an upstream shift in elevation limits of trout distributions to evaluate potential consequences of habitat loss. Downstream elevation limits were inversely associated with latitude, reflecting regional gradients in temperature. Upstream limits were positively related to maximum stream elevation as expected. Downstream elevation limits were constrained topographically by valley bottom elevations in northern streams but not in southern streams, where limits began well above valley bottoms. Elevation limits were similar among species. Upstream shifts in elevation limits for trout would lead to more habitat loss in the north than in the south, a result attributable to differences in topography. Because downstream distributions of trout in the north extend into valley bottoms with reduced topographic relief, trout in more northerly latitudes are more likely to experience habitat loss associated with an upstream shift in lower elevation limits. By applying quantile regression to relatively simple information (species presence, elevation, geography, topography), we were able to identify elevation limits for trout in the Great Basin and explore the effects of potential shifts in these limits that could occur in response to changing climate conditions that alter streams directly (e.g., through changes in temperature and precipitation) or indirectly (e.g., through changing water use).","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Transactions of the American Fisheries Society","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Taylor & Francis","doi":"10.1080/00028487.2013.833551","usgsCitation":"Warren, D.R., Dunham, J., and Hockman-Wert, D., 2014, Geographic variability in elevation and topographic constraints on the distribution of native and nonnative trout in the Great Basin: Transactions of the American Fisheries Society, v. 143, no. 1, p. 205-218, https://doi.org/10.1080/00028487.2013.833551.","productDescription":"14 p.","startPage":"205","endPage":"218","numberOfPages":"14","ipdsId":"IP-049648","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":473235,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/00028487.2013.833551","text":"Publisher Index Page"},{"id":280675,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":280651,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1080/00028487.2013.833551"}],"country":"United States","state":"California;Idaho;Nevada;Oregon","otherGeospatial":"Great Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -125.0,39.0 ], [ -125.0,44.0 ], [ -112.0,44.0 ], [ -112.0,39.0 ], [ -125.0,39.0 ] ] ] } } ] }","volume":"143","issue":"1","noUsgsAuthors":false,"publicationDate":"2014-01-06","publicationStatus":"PW","scienceBaseUri":"53cd5b23e4b0b290850f9d0f","contributors":{"authors":[{"text":"Warren, Dana R.","contributorId":96139,"corporation":false,"usgs":true,"family":"Warren","given":"Dana","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":487929,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dunham, Jason B.","contributorId":64791,"corporation":false,"usgs":true,"family":"Dunham","given":"Jason B.","affiliations":[],"preferred":false,"id":487928,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hockman-Wert, David 0000-0003-2436-6237 dhockman-wert@usgs.gov","orcid":"https://orcid.org/0000-0003-2436-6237","contributorId":3891,"corporation":false,"usgs":true,"family":"Hockman-Wert","given":"David","email":"dhockman-wert@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":487927,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70100736,"text":"70100736 - 2014 - Deep-sea coral record of human impact on watershed quality in the Mississippi River Basin","interactions":[],"lastModifiedDate":"2014-04-04T15:37:48","indexId":"70100736","displayToPublicDate":"2014-01-01T15:34:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1836,"text":"Global Biogeochemical Cycles","active":true,"publicationSubtype":{"id":10}},"title":"Deep-sea coral record of human impact on watershed quality in the Mississippi River Basin","docAbstract":"One of the greatest drivers of historical nutrient and sediment transport into the Gulf of Mexico is the unprecedented scale and intensity of land use change in the Mississippi River Basin. These landscape changes are linked to enhanced fluxes of carbon and nitrogen pollution from the Mississippi River, and persistent eutrophication and hypoxia in the northern Gulf of Mexico. Increased terrestrial runoff is one hypothesis for recent enrichment in bulk nitrogen isotope (δ<sup>15</sup>N) values, a tracer for nutrient source, observed in a Gulf of Mexico deep-sea coral record. However, unambiguously linking anthropogenic land use change to whole scale shifts in downstream Gulf of Mexico biogeochemical cycles is difficult. Here we present a novel approach, coupling a new tracer of agro-industrialization to a multiproxy record of nutrient loading in long-lived deep-sea corals collected in the Gulf of Mexico. We found that coral bulk δ<sup>15</sup>N values are enriched over the last 150–200 years relative to the last millennia, and compound-specific amino acid δ<sup>15</sup>N data indicate a strong increase in baseline δ<sup>15</sup>N of nitrate as the primary cause. Coral rhenium (Re) values are also strongly elevated during this period, suggesting that 34% of Re is of anthropogenic origin, consistent with Re enrichment in major world rivers. However, there are no pre-anthropogenic measurements of Re to confirm this observation. For the first time, an unprecedented record of natural and anthropogenic Re variability is documented through coral Re records. Taken together, these novel proxies link upstream changes in water quality to impacts on the deep-sea coral ecosystem.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Global Biogeochemical Cycles","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1002/2013GB004754","usgsCitation":"Prouty, N.G., Roark, E., Koenig, A.E., Demopoulos, A., Batista, F.C., Kocar, B.D., Selby, D., McCarthy, M.D., and Mienis, F., 2014, Deep-sea coral record of human impact on watershed quality in the Mississippi River Basin: Global Biogeochemical Cycles, v. 28, no. 1, p. 29-43, https://doi.org/10.1002/2013GB004754.","productDescription":"15 p.","startPage":"29","endPage":"43","numberOfPages":"15","ipdsId":"IP-051800","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":473237,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"text":"External Repository"},{"id":285751,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":285750,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/2013GB004754"}],"country":"United States","otherGeospatial":"Mississippi River Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -116.0,24.0 ], [ -116.0,48.0 ], [ -76.0,48.0 ], [ -76.0,24.0 ], [ -116.0,24.0 ] ] ] } } ] }","volume":"28","issue":"1","noUsgsAuthors":false,"publicationDate":"2014-01-24","publicationStatus":"PW","scienceBaseUri":"53559002e4b0120853e8beb3","contributors":{"authors":[{"text":"Prouty, Nancy G. 0000-0002-8922-0688 nprouty@usgs.gov","orcid":"https://orcid.org/0000-0002-8922-0688","contributorId":3350,"corporation":false,"usgs":true,"family":"Prouty","given":"Nancy","email":"nprouty@usgs.gov","middleInitial":"G.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":492406,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Roark, E. Brendan","contributorId":25464,"corporation":false,"usgs":true,"family":"Roark","given":"E. Brendan","affiliations":[],"preferred":false,"id":492409,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Koenig, Alan E. 0000-0002-5230-0924 akoenig@usgs.gov","orcid":"https://orcid.org/0000-0002-5230-0924","contributorId":1564,"corporation":false,"usgs":true,"family":"Koenig","given":"Alan","email":"akoenig@usgs.gov","middleInitial":"E.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":492405,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Demopoulos, Amanda W.J. 0000-0003-2096-4694 ademopoulos@usgs.gov","orcid":"https://orcid.org/0000-0003-2096-4694","contributorId":371,"corporation":false,"usgs":true,"family":"Demopoulos","given":"Amanda W.J.","email":"ademopoulos@usgs.gov","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":false,"id":492404,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Batista, Fabian C.","contributorId":47694,"corporation":false,"usgs":true,"family":"Batista","given":"Fabian","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":492411,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kocar, Benjamin D.","contributorId":44460,"corporation":false,"usgs":true,"family":"Kocar","given":"Benjamin","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":492410,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Selby, David","contributorId":58167,"corporation":false,"usgs":true,"family":"Selby","given":"David","affiliations":[],"preferred":false,"id":492412,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"McCarthy, Matthew D.","contributorId":23846,"corporation":false,"usgs":true,"family":"McCarthy","given":"Matthew","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":492408,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Mienis, Furu","contributorId":20255,"corporation":false,"usgs":true,"family":"Mienis","given":"Furu","affiliations":[],"preferred":false,"id":492407,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70199858,"text":"70199858 - 2014 - Effects of climate change and urban development on the distribution and conservation of vegetation in a Mediterranean type ecosystem","interactions":[],"lastModifiedDate":"2018-10-01T15:25:47","indexId":"70199858","displayToPublicDate":"2014-01-01T15:25:41","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2046,"text":"International Journal of Geographical Information Science","active":true,"publicationSubtype":{"id":10}},"title":"Effects of climate change and urban development on the distribution and conservation of vegetation in a Mediterranean type ecosystem","docAbstract":"<p><span>Climate and land-use changes are projected to threaten biodiversity over this century. However, few studies have considered the spatial and temporal overlap of these threats to evaluate how ongoing land-use change could affect species ranges projected to shift outside conservation areas. We evaluated climate change and urban development effects on vegetation distribution in the Southwest ecoregion, California Floristic Province, USA. We also evaluated how well a conservation network protects suitable habitat for rare plant species under these change projections and identified primary sources of uncertainty. We used consensus-based maps from three species distribution models (SDMs) to project current and future suitable habitat for 19 species representing different functional types (defined by fire-response – obligate seeders, resprouting shrubs – and life forms – herbs, subshrubs), and range sizes (large/common, small/rare). We used one spatially explicit urban growth projection; two climate models, emission scenarios, and probability thresholds applied to SDMs; and high-resolution (90&nbsp;m) environmental data. We projected that suitable habitat could disappear for 4 species and decrease for 15 by 2080. Averaged centroids of suitable habitat (all species) were projected to shift tens (up to hundreds) of kilometers. Herbs showed a small-projected response to climate change, while obligate seeders could suffer the greatest losses. Several rare species could lose suitable habitat inside conservation areas while increasing area outside. We concluded that (i) climate change is more important than urban development for vegetation habitat loss in this ecoregion through 2080 due to diminishing amounts of undeveloped private land in this region; (ii) the existing conservation plan, while extensive, may be inadequate to protect plant diversity under projected patterns of climate change and urban development, (iii) regional assessments of the dynamics of the drivers of biodiversity change based on high-resolution environmental data and consensus predictive mapping, such as this study, are necessary to identify the species expected to be the most vulnerable and to meaningfully inform regional-scale conservation.</span></p>","language":"English","publisher":"Taylor & Francis","doi":"10.1080/13658816.2013.846472","usgsCitation":"Beltran, B., Franklin, J., Syphard, A.D., Regan, H.M., Flint, L.E., and Flint, A.L., 2014, Effects of climate change and urban development on the distribution and conservation of vegetation in a Mediterranean type ecosystem: International Journal of Geographical Information Science, v. 28, no. 8, p. 1561-1589, https://doi.org/10.1080/13658816.2013.846472.","productDescription":"29 p.","startPage":"1561","endPage":"1589","ipdsId":"IP-041948","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":473238,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://escholarship.org/uc/item/4zf1737x","text":"External Repository"},{"id":357986,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -117.94921874999999,\n              32.519026027827515\n            ],\n            [\n              -115.850830078125,\n              32.519026027827515\n            ],\n            [\n              -115.850830078125,\n              34.161818161230386\n            ],\n            [\n              -117.94921874999999,\n              34.161818161230386\n            ],\n            [\n              -117.94921874999999,\n              32.519026027827515\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"28","issue":"8","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2013-10-18","publicationStatus":"PW","scienceBaseUri":"5bc038ebe4b0fc368eb53b15","contributors":{"authors":[{"text":"Beltran, Bray","contributorId":197901,"corporation":false,"usgs":false,"family":"Beltran","given":"Bray","email":"","affiliations":[],"preferred":false,"id":746933,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Franklin, Janet","contributorId":192373,"corporation":false,"usgs":false,"family":"Franklin","given":"Janet","affiliations":[],"preferred":false,"id":746935,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Syphard, Alexandra D.","contributorId":8977,"corporation":false,"usgs":false,"family":"Syphard","given":"Alexandra","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":746932,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Regan, Helen M.","contributorId":149953,"corporation":false,"usgs":false,"family":"Regan","given":"Helen","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":746934,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Flint, Lorraine E. 0000-0002-7868-441X lflint@usgs.gov","orcid":"https://orcid.org/0000-0002-7868-441X","contributorId":1184,"corporation":false,"usgs":true,"family":"Flint","given":"Lorraine","email":"lflint@usgs.gov","middleInitial":"E.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":746931,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Flint, Alan L. 0000-0002-5118-751X aflint@usgs.gov","orcid":"https://orcid.org/0000-0002-5118-751X","contributorId":1492,"corporation":false,"usgs":true,"family":"Flint","given":"Alan","email":"aflint@usgs.gov","middleInitial":"L.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":746930,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70119388,"text":"70119388 - 2014 - An ontology design pattern for surface water features","interactions":[],"lastModifiedDate":"2017-06-30T13:59:53","indexId":"70119388","displayToPublicDate":"2014-01-01T15:19:00","publicationYear":"2014","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"An ontology design pattern for surface water features","docAbstract":"Surface water is a primary concept of human experience but concepts are captured in cultures and languages in many different ways. Still, many commonalities exist due to the physical basis of many of the properties and categories. An abstract ontology of surface water features based only on those physical properties of landscape features has the best potential for serving as a foundational domain ontology for other more context-dependent ontologies. The Surface Water ontology design pattern was developed both for domain knowledge distillation and to serve as a conceptual building-block for more complex or specialized surface water ontologies. A fundamental distinction is made in this ontology between landscape features that act as containers (e.g., stream channels, basins) and the bodies of water (e.g., rivers, lakes) that occupy those containers. Concave (container) landforms semantics are specified in a Dry module and the semantics of contained bodies of water in a Wet module. The pattern is implemented in OWL, but Description Logic axioms and a detailed explanation is provided in this paper. The OWL ontology will be an important contribution to Semantic Web vocabulary for annotating surface water feature datasets. Also provided is a discussion of why there is a need to complement the pattern with other ontologies, especially the previously developed Surface Network pattern. Finally, the practical value of the pattern in semantic querying of surface water datasets is illustrated through an annotated geospatial dataset and sample queries using the classes of the Surface Water pattern.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Geographic Information Science: Proceedings of the 8th International Conference, GIScience","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"Springer","doi":"10.1007/978-3-319-11593-1_13","usgsCitation":"Sinha, G., Mark, D., Kolas, D., Varanka, D., Romero, B.E., Feng, C., Usery, E.L., Liebermann, J., and Sorokine, A., 2014, An ontology design pattern for surface water features, <i>in</i> Geographic Information Science: Proceedings of the 8th International Conference, GIScience, v. 8728, p. 187-203, https://doi.org/10.1007/978-3-319-11593-1_13.","productDescription":"16 p.","startPage":"187","endPage":"203","numberOfPages":"16","ipdsId":"IP-056598","costCenters":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"links":[{"id":294560,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":294559,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/978-3-319-11593-1_13"}],"volume":"8728","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54252e9ee4b0e641df8a6e69","contributors":{"authors":[{"text":"Sinha, Gaurav","contributorId":75075,"corporation":false,"usgs":true,"family":"Sinha","given":"Gaurav","affiliations":[],"preferred":false,"id":497643,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mark, David","contributorId":71906,"corporation":false,"usgs":true,"family":"Mark","given":"David","affiliations":[],"preferred":false,"id":497642,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kolas, Dave","contributorId":12390,"corporation":false,"usgs":true,"family":"Kolas","given":"Dave","email":"","affiliations":[],"preferred":false,"id":497640,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Varanka, Dalia","contributorId":99654,"corporation":false,"usgs":true,"family":"Varanka","given":"Dalia","affiliations":[],"preferred":false,"id":497647,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Romero, Boleslo E.","contributorId":79414,"corporation":false,"usgs":true,"family":"Romero","given":"Boleslo","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":497644,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Feng, Chen-Chieh","contributorId":83854,"corporation":false,"usgs":true,"family":"Feng","given":"Chen-Chieh","email":"","affiliations":[],"preferred":false,"id":497645,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Usery, E. Lynn 0000-0002-2766-2173 usery@usgs.gov","orcid":"https://orcid.org/0000-0002-2766-2173","contributorId":231,"corporation":false,"usgs":true,"family":"Usery","given":"E.","email":"usery@usgs.gov","middleInitial":"Lynn","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":true,"id":497639,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Liebermann, Joshua","contributorId":90659,"corporation":false,"usgs":true,"family":"Liebermann","given":"Joshua","email":"","affiliations":[],"preferred":false,"id":497646,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Sorokine, Alexandre","contributorId":58206,"corporation":false,"usgs":true,"family":"Sorokine","given":"Alexandre","email":"","affiliations":[],"preferred":false,"id":497641,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70100634,"text":"70100634 - 2014 - Uncertainty and extreme events in future climate and hydrologic projections for the Pacific Northwest: providing a basis for vulnerability and core/corridor assessments","interactions":[],"lastModifiedDate":"2018-09-27T10:52:40","indexId":"70100634","displayToPublicDate":"2014-01-01T15:17:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":3,"text":"Organization Series"},"title":"Uncertainty and extreme events in future climate and hydrologic projections for the Pacific Northwest: providing a basis for vulnerability and core/corridor assessments","docAbstract":"<p>The purpose of this project was to (1) provide an internally-consistent set of downscaled projections across the Western U.S., (2) include information about projection uncertainty, and (3) assess projected changes of hydrologic extremes. These objectives were designed to address decision support needs for climate adaptation and resource management actions. Specifically, understanding of uncertainty in climate projections – in particular for extreme events – is currently a key scientific and management barrier to adaptation planning and vulnerability assessment.</p><p>The new dataset fills in the Northwest domain to cover a key gap in the previous dataset, adds additional projections (both from other global climate models and a comparison with dynamical downscaling) and includes an assessment of changes to flow and soil moisture extremes. This new information can be used to assess variations in impacts across the landscape, uncertainty in projections, and how these differ as a function of region, variable, and time period.</p><p>In this project, existing University of Washington Climate Impacts Group (UW CIG) products were extended to develop a comprehensive data archive that accounts (in a reigorous and physically based way) for climate model uncertainty in future climate and hydrologic scenarios. These products can be used to determine likely impacts on vegetation and aquatic habitat in the Pacific Northwest (PNW) region, including WA, OR, ID, northwest MT to the continental divide, northern CA, NV, UT, and the Columbia Basin portion of western WY New data series and summaries produced for this project include: 1) extreme statistics for surface hydrology (e.g. frequency of soil moisture and summer water deficit) and streamflow (e.g. the 100-year flood, extreme 7-day low flows with a 10-year recurrence interval); 2) snowpack vulnerability as indicated by the ratio of April 1 snow water to cool-season precipitation; and, 3) uncertainty analyses for multiple climate scenarios.</p>","language":"English","publisher":"Climate Impacts Group","publisherLocation":"Seattle, WA","usgsCitation":"Littell, J.S., Mauger, G., Salathe, E.P., Hamlet, A.F., Lee, S., Stumbaugh, M.R., Elsner, M., Norheim, R., Lutz, E.R., and Mantua, N.J., 2014, Uncertainty and extreme events in future climate and hydrologic projections for the Pacific Northwest: providing a basis for vulnerability and core/corridor assessments, 19 p.","productDescription":"19 p.","ipdsId":"IP-054776","costCenters":[{"id":107,"text":"Alaska Climate Science Center","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":287631,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":287630,"type":{"id":15,"text":"Index Page"},"url":"https://cses.washington.edu/db/pubs/abstract825.shtml"}],"country":"United States","state":"Arizona, California, Colorado, Idaho, Montana, Nevada, New Mexico, Oregon, Utah, Washington, Wyoming","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.79,31.27 ], [ -124.79,49.0 ], [ -104.08,49.0 ], [ -104.08,31.27 ], [ -124.79,31.27 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5385b405e4b09e18fc023ac5","contributors":{"authors":[{"text":"Littell, Jeremy S.","contributorId":54506,"corporation":false,"usgs":true,"family":"Littell","given":"Jeremy","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":492350,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mauger, Guillaume S.","contributorId":11954,"corporation":false,"usgs":true,"family":"Mauger","given":"Guillaume S.","affiliations":[],"preferred":false,"id":492347,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Salathe, Eric P.","contributorId":85887,"corporation":false,"usgs":true,"family":"Salathe","given":"Eric","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":492356,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hamlet, Alan F.","contributorId":15529,"corporation":false,"usgs":true,"family":"Hamlet","given":"Alan","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":492348,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lee, Se-Yeun","contributorId":76657,"corporation":false,"usgs":true,"family":"Lee","given":"Se-Yeun","email":"","affiliations":[],"preferred":false,"id":492354,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stumbaugh, Matt R.","contributorId":17916,"corporation":false,"usgs":true,"family":"Stumbaugh","given":"Matt","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":492349,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Elsner, Marketa","contributorId":55344,"corporation":false,"usgs":true,"family":"Elsner","given":"Marketa","email":"","affiliations":[],"preferred":false,"id":492351,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Norheim, Robert","contributorId":75446,"corporation":false,"usgs":true,"family":"Norheim","given":"Robert","email":"","affiliations":[],"preferred":false,"id":492353,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Lutz, Eric R.","contributorId":57775,"corporation":false,"usgs":true,"family":"Lutz","given":"Eric","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":492352,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Mantua, Nathan J.","contributorId":83429,"corporation":false,"usgs":true,"family":"Mantua","given":"Nathan","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":492355,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70161811,"text":"70161811 - 2014 - Arsenic speciation in solids using X-ray absorption spectroscopy","interactions":[],"lastModifiedDate":"2016-01-06T13:50:52","indexId":"70161811","displayToPublicDate":"2014-01-01T15:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3281,"text":"Reviews in Mineralogy and Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Arsenic speciation in solids using X-ray absorption spectroscopy","docAbstract":"<p>Synchrotron-based X-ray absorption spectroscopy (XAS) is an <i>in situ</i>, minimally-destructive, element-specific, molecular-scale structural probe that has been employed to study the chemical forms (species) of arsenic (As) in solid and aqueous phases (including rocks, soils, sediment, synthetic compounds, and numerous types of biota including humans) for more than 20 years. Although several excellent reviews of As geochemistry and As speciation in the environment have been published previously (including recent contributions in this volume), the explosion of As-XAS studies over the past decade (especially studies employing microfocused X-ray beams) warrants this new review of the literature and of data analysis methods.</p>\n<p>This review has two main sections. The first is a presentation of methods for sample preparation and for the collection, processing and analysis of As-XAS spectra. Since several more comprehensive reviews of the X-ray absorption theory and data collection methodology exist, this section is brief and focused specifically on As. The second section is a critical review of the As-XAS literature, arranged by sample type and accompanied by summary tables (collected as appendices at the end of the chapter).</p>\n<p>One of the most important aims of this review is to clarify the different types of analysis that are performed on As-XAS spectra, and to describe the benefits, drawbacks, and limitations of each. Arsenic XAS spectra are analyzed to obtain one or more of the following types of information (in increasing order of sophistication):</p>","language":"English","publisher":"Mineralogical Society of America","publisherLocation":"Washington D.C.","doi":"10.2138/rmg.2014.79.5","usgsCitation":"Foster, A.L., and Kim, C.S., 2014, Arsenic speciation in solids using X-ray absorption spectroscopy: Reviews in Mineralogy and Geochemistry, v. 79, no. 1, p. 257-369, https://doi.org/10.2138/rmg.2014.79.5.","productDescription":"113 p.","startPage":"257","endPage":"369","numberOfPages":"113","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057070","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":313958,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"79","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2014-09-05","publicationStatus":"PW","scienceBaseUri":"568e48e3e4b0e7a44bc41885","contributors":{"authors":[{"text":"Foster, Andrea L. 0000-0003-1362-0068 afoster@usgs.gov","orcid":"https://orcid.org/0000-0003-1362-0068","contributorId":1740,"corporation":false,"usgs":true,"family":"Foster","given":"Andrea","email":"afoster@usgs.gov","middleInitial":"L.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":662,"text":"Western Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":587841,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kim, Chris S.","contributorId":152089,"corporation":false,"usgs":false,"family":"Kim","given":"Chris","email":"","middleInitial":"S.","affiliations":[{"id":18864,"text":"Chapman University","active":true,"usgs":false}],"preferred":false,"id":587842,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70074738,"text":"70074738 - 2014 - Elk monitoring in Lewis and Clark National Historical Park: 2008-2012 synthesis report","interactions":[],"lastModifiedDate":"2014-04-09T15:00:12","indexId":"70074738","displayToPublicDate":"2014-01-01T14:51:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":54,"text":"Natural Resource Technical Report","active":false,"publicationSubtype":{"id":1}},"seriesNumber":"NPS/NCCN/NRTR--2014/837","title":"Elk monitoring in Lewis and Clark National Historical Park: 2008-2012 synthesis report","docAbstract":"<p>Maintaining elk (Cervus elaphus roosevelti) herds that frequent Lewis and Clark National Historical Park (NHP) is central to the park’s purpose of preserving the historic, cultural, scenic, and natural resources associated with the winter encampment of the Lewis and Clark expedition. Elk were critically important to the Lewis and Clark expedition in providing food and hides that sustained the expedition during the winter of 1805-06 and supplied them for their return east during 1806. Today, elk remain a key component of interpreting the Lewis and Clark story to over 200,000 park visitors each year at the Fort Clatsop visitor center.</p>\n<br>\n<p>In 2008, the US Geological Survey (USGS) began collaborating with Lewis and Clark NHP and \nthe NPS North Coast and Cascades Network to develop a protocol for monitoring long-term \nchanges in the magnitude and spatial patterns of elk use within and adjacent to Lewis and Clark \nNHP (Griffin et al. 2011). Specific objectives of the monitoring program were to measure trends \nin (1) relative use of the Fort Clatsop unit by elk during winter; (2) the proportion of areas where \nelk sign is present in the Fort Clatsop unit in winter; and (3) the frequency of elk sightings from \nroads in and around the Fort Clatsop unit. This report synthesizes the results of the first four \nyears of monitoring elk distribution and use in Lewis and Clark NHP from 2008-2012. We also \npresent data from FY2012 (Appendix 1), in lieu of an annual report for that year.</p>\n<br>\n<p>We used fecal pellet group surveys as the cornerstone for monitoring trends in both relative use \nof the Fort Clatsop Unit by elk and the proportion of areas where elk sign was present at the end \nof winter. We estimated pellet group density based on data collected from a network of fecal \npellet plots distributed systematically throughout the unit. We developed a double observer \nsampling scheme that enabled us to estimate detection biases and improve the accuracy of pellet \ngroup density estimates. We computed the estimated detection probability for any pellet group \nobserved; this probability was a function of the pellet group size and stage of decay, as well as \nlighting and vegetation conditions, and the number of observers (one or two) searching for \npellets in that subplot. We then used these estimated detection probabilities to adjust the raw \ncounts of the detected pellet groups to account for groups that likely went undetected under \nsimilar pellet and environmental conditions (each observed pellet group was weighted by the \ninverse of its estimated detection probability). We also used results from the late winter fecal \npellet surveys to quantify the proportion of areas where elk pellets occurred (PAO), which was \nbased on the presence of fecal pellet groups and estimation of detection biases (i.e., accounting \nfor pellet groups that likely went undetected by both observers). In this synthesis, we report \ntemporal trends in both pellet group density and PAO from 2008-2012, based on weighted linear \nregression analyses as well as spatial variation of pellet group densities over time.</p> \n<br>\n<p>We completed late winter fecal pellet surveys at 61-66 plots annually, depending on yearly \nvariation in access. We cleared fecal pellets at survey points in late October / early November \neach year and returned in late February / early March to count pellet groups left by elk over the \nwinter. The estimated probability that a pellet group was detected by any one observer during \nlate winter was affected most by the pellet group size and was less affected by decay class and \nlighting conditions. Per-observer detection probabilities ranged from as low as ~10-15% for \nsingle pellets to ~85-90% for pellet groups with 50 pellets. Average pellet group density in the \nFort Clatsop unit ranged annually from 0.58 (+/- 1.43 standard error [SE]) to 0.93 (+/- 2.25 SE) \npellet groups per 3-m radius subplot. Pellet group density declined over time, at approximately 8.8% per year (+/- 2.5% SE), but that slope was not statistically distinguishable from zero (2-\ntailed P=0.16). Following correction for detection biases, the proportion of surveyed points used \nby elk (i.e., PAO) ranged from 0.44 (+/- 0.07 SE) to 0.53 (+/- 0.07 SE) during the 4 winters. The \nestimated proportion of areas where elk pellets occurred (PAO) declined at a rate of 2.6% per \nyear (+/- 1.2% per year SE), but that trend also was not statistically distinguishable from zero (2-\ntailed P=0.17). Statistical significance of a measure’s trend depends on both the magnitude (i.e., \nslope) of the observed trend and the number of years the trend continues in the same increasing \nor decreasing direction. Through simulation modeling we determined how many additional years \nof surveys would be required to reveal a statistically significant trend, based on the same trends \nin pellet group density and PAO, and associated variation, observed from 2009-2012. Assuming \nthe same trends persist in the future, simulations indicated that there is a 70% probability that a \nstatistically significant trend would be detected after two more years of conducting pellet group \nsurveys.</p> \n<br>\n<p>Relative use by elk during winter, as indexed by elk pellet group density, was generally greatest \nin the southeast region of the Fort Clatsop unit in or near the large freshwater marsh at the mouth \nof Colewort Creek and adjacent upland areas. Pellet group density was also higher than average \nin the north-central forested area, not far from a privately-owned pasture north of the park \nboundary. This spatial pattern in pellet group densities across the Fort Clatsop unit was \nconsistent across all four years, although specific pellet group densities varied from year to year. \nPellet group density declined significantly over time at two points in the southeast of the Fort \nClatsop unit, even though pellet group density at those points remained higher than the unit \naverage. Pellet group density increased significantly over time at one point in the north-central \nregion, and at one point in the south-central region of the unit, indicating a slight shift in the \ndistribution of elk use within the Fort Clatsop Unit over the four years.</p>\n<br>\n<p>As an index of visitors’ opportunities to see elk in and around the Fort Clatsop Unit, we \nconducted replicated roadside elk surveys 3-5 times monthly during February, April, June, \nAugust, October and December 2008-2012. During each morning of survey, we searched for elk \nalong four routes that totaled 32 km. We examined bimonthly trends in the numbers of elk \ngroups seen, the total number of elk seen, and the observed composition ratios for those six \nmonths of the year. The average number of elk groups seen per survey ranged from 0.75 (+/- \n0.32 SE) during February to a peak of 1.95 (+/- 0.36 SE) during June. Despite this seasonal \nvariation in numbers of elk groups seen, the average total number of elk seen per morning was \nless variable. The average ratios of antlered elk to antlerless adult elk (i.e., bulls:cows) and \ncalves to antlerless adult elk (i.e. calves:cows) varied seasonally, with the highest of both \naverage ratios observed in August. We detected no significant trends in the average number of \nelk groups and total numbers of elk seen per survey from 2008-2012. Similarly, ratios of calves \nand antlered elk per antlerless elk did not differ over time.</p> \n<br>\n<p>Elk groups were frequently seen from January to August in the southeast region of the Fort \nClatsop unit, in the vicinity of Colewort Creek. Outside of NPS lands, we observed elk most \nfrequently in open areas near the Astoria regional airport, in the pastures and forests immediately \nnorth of the Fort Clatsop unit and, prior to the construction of a residential development, in a \npasture northwest of the Fort Clatsop unit.</p>\n<br>\n<p> Elk monitoring at Lewis and Clark NHP is still in its initial years and additional monitoring will \nbe required to verify trends that appear to be emerging. For example, the initial monitoring \nsuggested incipient declining trends in both pellet group density and proportion of plots with \npellets present, as well as, potentially, a small shift in elk distribution away from a new trail that \nwas recently constructed in the southeast portion of the Fort Clatsop unit. Continued monitoring \nwill aid in determining whether this local change in distribution persists (or, alternatively, \nresulted from short-term random variation), and whether there will be any positive or negative \neffect in the northern portion of the unit where a new trail has been constructed. High variability \nin road counts prevented our ability to find any clear trend in numbers or composition of elk \nobserved in and near Fort Clatsop, but changes in the patterns of observations of elk from \nroadways suggest that residential development outside the park has reduced the available habitat \nfor elk in some of the areas surveyed, and may have affected spatial use patterns of elk adjacent \nto some areas of the park. In addition to monitoring future effects of land use changes outside the \npark, continued monitoring may also prove useful for assessing elk responses to natural \nsuccession in forests disturbed by windthrow in December 2007 and to NPS vegetation \nmanagement activities such as variable density thinning in the forest, trail development, and \nrestoration at Otter Point tidal area and Colewort Creek Slough.</p>","language":"English","publisher":"National Park Service","usgsCitation":"Griffin, P., Jenkins, K.J., Cole, C., Clatterbuck, C., Boetsch, J., and Beirne, K., 2014, Elk monitoring in Lewis and Clark National Historical Park: 2008-2012 synthesis report: Natural Resource Technical Report NPS/NCCN/NRTR--2014/837, xii, 56 p.","productDescription":"xii, 56 p.","numberOfPages":"72","temporalStart":"2008-01-01","temporalEnd":"2012-12-31","ipdsId":"IP-053359","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":286057,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":281885,"type":{"id":15,"text":"Index Page"},"url":"https://irma.nps.gov/App/Reference/Profile/2206594"}],"country":"United States","state":"Oregon;Washington","otherGeospatial":"Lewis And Clark National Historical Park","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.1,45.9 ], [ -124.1,46.3 ], [ -123.8,46.3 ], [ -123.8,45.9 ], [ -124.1,45.9 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53559432e4b0120853e8bf5d","contributors":{"authors":[{"text":"Griffin, Paul C.","contributorId":7802,"corporation":false,"usgs":true,"family":"Griffin","given":"Paul C.","affiliations":[],"preferred":false,"id":489768,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jenkins, Kurt J. 0000-0003-1415-6607 kurt_jenkins@usgs.gov","orcid":"https://orcid.org/0000-0003-1415-6607","contributorId":3415,"corporation":false,"usgs":true,"family":"Jenkins","given":"Kurt","email":"kurt_jenkins@usgs.gov","middleInitial":"J.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":489767,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cole, Carla","contributorId":44809,"corporation":false,"usgs":true,"family":"Cole","given":"Carla","email":"","affiliations":[],"preferred":false,"id":489769,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Clatterbuck, Chris","contributorId":53697,"corporation":false,"usgs":true,"family":"Clatterbuck","given":"Chris","email":"","affiliations":[],"preferred":false,"id":489770,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Boetsch, John","contributorId":57766,"corporation":false,"usgs":true,"family":"Boetsch","given":"John","affiliations":[],"preferred":false,"id":489771,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Beirne, Katherine","contributorId":58754,"corporation":false,"usgs":true,"family":"Beirne","given":"Katherine","affiliations":[],"preferred":false,"id":489772,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70098947,"text":"70098947 - 2014 - Automated Cropland Classification Algorithm (ACCA) for California using multi-sensor remote sensing","interactions":[],"lastModifiedDate":"2024-07-09T13:43:41.863777","indexId":"70098947","displayToPublicDate":"2014-01-01T14:38:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5987,"text":"Photogrammetric Engineering & Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Automated Cropland Classification Algorithm (ACCA) for California using multi-sensor remote sensing","docAbstract":"<p>Increasing pressure to feed the growing population with scarce water resources requires accurate and routine cropland mapping. This paper develops and implements a rule-based automated cropland classification algorithm (ACCA) using multi-sensor remote sensing data. Pixel-by-pixel accuracy assessments showed that ACCA produced an overall accuracy of 96 percent (K<sub>hat</sub><span>&nbsp;</span>= 0.8) when tested using independent data layers. Furthermore, ACCA-generated county cropland areas showed high agreement (R-square values 0.94) when compared with three independent data sources: (a) US Department of Agriculture (USDA) cropland data layer derived cropland areas, (b) county specific crop acreage data from the Farm Service Agency, and (c) the Census of Agriculture data for the 58 counties in California. Our results demonstrate the ability of ACCA to generate cropland extent and areas over space and time, in an automated fashion with high degree of accuracies year after year, greatly contributing to food and water security analysis and decision making.</p>","language":"English","publisher":"American Society for Photogrammetry and Remote Sensing","doi":"10.14358/PERS.80.1.81","usgsCitation":"Wu, Z., Thenkabail, P.S., and Verdin, J., 2014, Automated Cropland Classification Algorithm (ACCA) for California using multi-sensor remote sensing: Photogrammetric Engineering & Remote Sensing, v. 80, no. 1, p. 81-90, https://doi.org/10.14358/PERS.80.1.81.","productDescription":"10 p.","startPage":"81","endPage":"90","ipdsId":"IP-041735","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":473239,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.14358/pers.80.1.81","text":"Publisher Index Page"},{"id":284274,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.er.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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,{"id":70199971,"text":"70199971 - 2014 - Source and progression of a submarine landslide and tsunami: The 1964 Great Alaska earthquake at Valdez","interactions":[],"lastModifiedDate":"2021-04-06T13:43:11.545868","indexId":"70199971","displayToPublicDate":"2014-01-01T14:35:15","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7514,"text":"Journal of Geophysical Research - Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Source and progression of a submarine landslide and tsunami: The 1964 Great Alaska earthquake at Valdez","docAbstract":"<p><span>Like many subduction zone earthquakes, the deadliest aspects of the 1964&nbsp;</span><i>M</i><span> = 9.2 Alaska earthquake were the tsunamis it caused. The worst of these were generated by local submarine landslides induced by the earthquake. These caused high runups, engulfing several coastal towns in Prince William Sound. In this paper, we study one of these cases in detail, the Port Valdez submarine landslide and tsunami. We combine eyewitness reports, preserved film, and careful posttsunami surveys with new geophysical data to inform numerical models for landslide tsunami generation. We review the series of events as recorded at Valdez old town and then determine the corresponding subsurface events that led to the tsunami. We build digital elevation models of part of the pretsunami and posttsunami fjord‐head delta. Comparing them reveals a ~1500 m long region that receded 150 m to the east, which we interpret as the primary delta landslide source. Multibeam imagery and high‐resolution seismic reflection data identify a ~400 m wide chute with hummocky deposits at its terminus, which may define the primary slide path. Using these elements we run hydrodynamic models of the landslide‐driven tsunamis that match observations of current direction, maximum inundation, and wave height at Valdez old town. We speculate that failure conditions at the delta front may have been influenced by manmade changes in drainage patterns as well as the fast retreat of Valdez and other glaciers during the past century.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2014JB011514","usgsCitation":"Parsons, T.E., Geist, E.L., Ryan, H.F., Lee, H., Haeussler, P.J., Lynett, P., Hart, P.E., Sliter, R.W., and Roland, E.C., 2014, Source and progression of a submarine landslide and tsunami: The 1964 Great Alaska earthquake at Valdez: Journal of Geophysical Research - Solid Earth, v. 119, no. 11, p. 8502-8516, https://doi.org/10.1002/2014JB011514.","productDescription":"15 p.","startPage":"8502","endPage":"8516","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":473240,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2014jb011514","text":"Publisher Index Page"},{"id":358210,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","city":"Valdez","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -146.964111328125,\n              60.85293796664351\n            ],\n            [\n              -146.0137939453125,\n              60.85293796664351\n            ],\n            [\n              -146.0137939453125,\n              61.22531306274158\n            ],\n            [\n              -146.964111328125,\n              61.22531306274158\n            ],\n            [\n              -146.964111328125,\n              60.85293796664351\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"119","issue":"11","noUsgsAuthors":false,"publicationDate":"2014-11-16","publicationStatus":"PW","scienceBaseUri":"5bc038ebe4b0fc368eb53b17","contributors":{"authors":[{"text":"Parsons, Thomas E. 0000-0002-0582-4338 tparsons@usgs.gov","orcid":"https://orcid.org/0000-0002-0582-4338","contributorId":2314,"corporation":false,"usgs":true,"family":"Parsons","given":"Thomas","email":"tparsons@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":747532,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Geist, Eric L. 0000-0003-0611-1150 egeist@usgs.gov","orcid":"https://orcid.org/0000-0003-0611-1150","contributorId":1956,"corporation":false,"usgs":true,"family":"Geist","given":"Eric","email":"egeist@usgs.gov","middleInitial":"L.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":747533,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ryan, Holly F. hryan@usgs.gov","contributorId":2375,"corporation":false,"usgs":true,"family":"Ryan","given":"Holly","email":"hryan@usgs.gov","middleInitial":"F.","affiliations":[],"preferred":false,"id":747534,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lee, Homa J. hjlee@usgs.gov","contributorId":1021,"corporation":false,"usgs":true,"family":"Lee","given":"Homa J.","email":"hjlee@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":747535,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Haeussler, Peter J. 0000-0002-1503-6247 pheuslr@usgs.gov","orcid":"https://orcid.org/0000-0002-1503-6247","contributorId":503,"corporation":false,"usgs":true,"family":"Haeussler","given":"Peter","email":"pheuslr@usgs.gov","middleInitial":"J.","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":747536,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lynett, Patrick","contributorId":24298,"corporation":false,"usgs":true,"family":"Lynett","given":"Patrick","affiliations":[],"preferred":false,"id":747537,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hart, Patrick E. 0000-0002-5080-1426 hart@usgs.gov","orcid":"https://orcid.org/0000-0002-5080-1426","contributorId":2879,"corporation":false,"usgs":true,"family":"Hart","given":"Patrick","email":"hart@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":747538,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sliter, Ray W. 0000-0003-0337-3454 rsliter@usgs.gov","orcid":"https://orcid.org/0000-0003-0337-3454","contributorId":1992,"corporation":false,"usgs":true,"family":"Sliter","given":"Ray","email":"rsliter@usgs.gov","middleInitial":"W.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":747539,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Roland, Emily C. eroland@usgs.gov","contributorId":5075,"corporation":false,"usgs":true,"family":"Roland","given":"Emily","email":"eroland@usgs.gov","middleInitial":"C.","affiliations":[],"preferred":false,"id":747540,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70047368,"text":"70047368 - 2014 - Integrating disparate lidar data at the national scale to assess the relationships between height above ground, land cover and ecoregions","interactions":[],"lastModifiedDate":"2024-06-13T16:33:39.373998","indexId":"70047368","displayToPublicDate":"2014-01-01T14:21:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3052,"text":"Photogrammetric Engineering and Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Integrating disparate lidar data at the national scale to assess the relationships between height above ground, land cover and ecoregions","docAbstract":"With the acquisition of lidar data for over 30 percent of the US, it is now possible to assess the three-dimensional distribution of features at the national scale. This paper integrates over 350 billion lidar points from 28 disparate datasets into a national-scale database and evaluates if height above ground is an important variable in the context of other nationalscale layers, such as the US Geological Survey National Land Cover Database and the US Environmental Protection Agency ecoregions maps. While the results were not homoscedastic and the available data did not allow for a complete height census in any of the classes, it does appear that where lidar data were used, there were detectable differences in heights among many of these national classification schemes. This study supports the hypothesis that there were real, detectable differences in heights in certain national-scale classification schemes, despite height not being a variable used in any of the classification routines.","language":"English","publisher":"American Society for Photogrammetry and Remote Sensing","doi":"10.14358/PERS.80.1.59","usgsCitation":"Stoker, J.M., Cochrane, M.A., and Roy, D.P., 2014, Integrating disparate lidar data at the national scale to assess the relationships between height above ground, land cover and ecoregions: Photogrammetric Engineering and Remote Sensing, v. 80, no. 1, p. 59-70, https://doi.org/10.14358/PERS.80.1.59.","productDescription":"12 p.","startPage":"59","endPage":"70","numberOfPages":"12","ipdsId":"IP-049075","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":473244,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.14358/pers.80.1.59","text":"Publisher Index Page"},{"id":280754,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"80","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd62bbe4b0b290850fe5bf","contributors":{"authors":[{"text":"Stoker, Jason M. 0000-0003-2455-0931 jstoker@usgs.gov","orcid":"https://orcid.org/0000-0003-2455-0931","contributorId":3021,"corporation":false,"usgs":true,"family":"Stoker","given":"Jason","email":"jstoker@usgs.gov","middleInitial":"M.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":true,"id":481852,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cochrane, Mark A.","contributorId":20884,"corporation":false,"usgs":false,"family":"Cochrane","given":"Mark","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":481850,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Roy, David P.","contributorId":71083,"corporation":false,"usgs":true,"family":"Roy","given":"David","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":481851,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70148164,"text":"70148164 - 2014 - Reproductive ecology of American Oystercatchers nesting on shell rakes","interactions":[],"lastModifiedDate":"2015-05-26T12:57:05","indexId":"70148164","displayToPublicDate":"2014-01-01T14:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1318,"text":"Condor","active":true,"publicationSubtype":{"id":10}},"title":"Reproductive ecology of American Oystercatchers nesting on shell rakes","docAbstract":"<p>Degradation of nesting habitat for coastal birds has led to the use of nontraditional nesting habitat. The American Oystercatcher (<i>Haematopus palliatus</i>) is listed as a \"Species of High Concern'' by the U. S. Shorebird Conservation Plan and is declining in the southern portion of its U. S. breeding range, where ~ 50% of breeding oystercatchers nest on shell substrate instead of beachfront habitat. We measured daily survival rates during incubation and chick rearing in shell rake habitats over five breeding seasons in the Cape Romain region of South Carolina, USA. Of 354 nesting attempts monitored, 16.1% hatched at least one egg. During incubation, daily survival rate was 0.938, corresponding to 22.8% success to hatching (nest success). For broods, daily survival was 0.991, or 74.0% success from hatching to fledging. Productivity in the Cape Romain region is primarily being lost during the incubation phase, when nests are exposed to overwash and predation. Mobile chicks may, however, be able to avoid flood events or predators by relocating to higher or more protected portions of a shell rake. Based on comparative data for American Oystercatchers from elsewhere in their range, it does not appear that shell rakes in the Cape Romain region are inferior breeding habitat. Our data suggest that conservation actions targeting nest and chick loss from flooding and predation have the greatest opportunity to enhance reproductive success in this core breeding area, and that an assessment of the availability, structure, avian use, and protection status of shell rakes is warranted.</p>","language":"English","publisher":"Cooper Ornithological Club","publisherLocation":"Santa Clara, CA","doi":"10.1650/CONDOR-14-35.1","collaboration":"National Fish and Wildlife Foundation; South Carolina State Wildlife Grants Program; Cape Romain National Wildlife Refuge; U.S. Fish and Wildlife Service, U. S. Geological Survey South Carolina Cooperative Fish and Wildlife Research Unit, and Clemson University; South Carolina Department of Natural Resources, Clemson University, the U.S. Fish and Wildlife Service; U.S. Geological Survey","usgsCitation":"Jodice, P.G., Thibault, J.M., Collins, S., Spinks, M.D., and Sanders, F.J., 2014, Reproductive ecology of American Oystercatchers nesting on shell rakes: Condor, v. 116, no. 4, p. 588-598, https://doi.org/10.1650/CONDOR-14-35.1.","productDescription":"11 p.","startPage":"588","endPage":"598","numberOfPages":"11","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-054897","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":473245,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1650/condor-14-35.1","text":"Publisher Index Page"},{"id":300793,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"116","issue":"4","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55659953e4b0d9246a9eb63f","contributors":{"authors":[{"text":"Jodice, Patrick G.R. 0000-0001-8716-120X pjodice@usgs.gov","orcid":"https://orcid.org/0000-0001-8716-120X","contributorId":1119,"corporation":false,"usgs":true,"family":"Jodice","given":"Patrick","email":"pjodice@usgs.gov","middleInitial":"G.R.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":547522,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thibault, Janet M.","contributorId":140932,"corporation":false,"usgs":false,"family":"Thibault","given":"Janet","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":547623,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Collins, S.A.","contributorId":63947,"corporation":false,"usgs":true,"family":"Collins","given":"S.A.","email":"","affiliations":[],"preferred":false,"id":547624,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Spinks, Mark D.","contributorId":140933,"corporation":false,"usgs":false,"family":"Spinks","given":"Mark","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":547625,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sanders, Felicia J.","contributorId":56574,"corporation":false,"usgs":false,"family":"Sanders","given":"Felicia","email":"","middleInitial":"J.","affiliations":[{"id":35670,"text":"South Carolina Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":547626,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70097361,"text":"70097361 - 2014 - Status of pelagic prey fishes in Lake Michigan, 2013","interactions":[],"lastModifiedDate":"2014-05-27T13:31:37","indexId":"70097361","displayToPublicDate":"2014-01-01T13:24:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":6,"text":"USGS Unnumbered Series"},"title":"Status of pelagic prey fishes in Lake Michigan, 2013","docAbstract":"Acoustic surveys were conducted in late summer/early fall during the years 1992-1996 and 2001-2013 to estimate pelagic prey fish biomass in Lake Michigan. Midwater trawling during the surveys as well as target strength provided a measure of species and size composition of the fish community for use in scaling acoustic data and providing species-specific abundance estimates. The 2013 survey consisted of 27 acoustic transects (546 km total) and 31 midwater trawl tows. Mean prey fish biomass was 6.1 kg/ha (relative standard error, RSE = 11%) or 29.6 kilotonnes (kt = 1,000 metric tons), which was similar to the estimate in 2012 (31.1 kt) and 23.5% of the long-term (18 years) mean. The numeric density of the 2013 alewife year class was 6% of the time series average and this year-class contributed 4% of total alewife biomass (5.2 kg/ha, RSE = 12%). Alewife ≥age-1 comprised 96% of alewife biomass. In 2013, alewife comprised 86% of total prey fish biomass, while rainbow smelt and bloater were 4 and 10% of total biomass, respectively. Rainbow smelt biomass in 2013 (0.24 kg/ha, RSE = 17%) was essentially identical to the rainbow smelt biomass in 2012 and was 6% of the long term mean. Bloater biomass in 2013 was 0.6 kg/ha, only half the 2012 biomass, and 6% of the long term mean. Mean density of small bloater in 2013 (29 fish/ha, RSE = 29%) was lower than peak values observed in 2007-2009 and was 23% of the time series mean. In 2013, pelagic prey fish biomass in Lake Michigan was similar to Lake Huron, but pelagic community composition differs in the two lakes, with Lake Huron dominated by bloater.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/70097361","usgsCitation":"Warner, D.M., Farha, S.A., O’Brien, T.P., Ogilvie, L., Claramunt, R., and Hanson, D., 2014, Status of pelagic prey fishes in Lake Michigan, 2013, 12 p., https://doi.org/10.3133/70097361.","productDescription":"12 p.","numberOfPages":"12","ipdsId":"IP-054851","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":287608,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":287607,"type":{"id":11,"text":"Document"},"url":"https://www.in.gov/dnr/fishwild/files/fw-Lake_Michigan_acoustic_report_2014_final.pdf"}],"country":"United States","otherGeospatial":"Lake Michigan","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -88.0434,41.6089 ], [ -88.0434,46.1024 ], [ -84.7385,46.1024 ], [ -84.7385,41.6089 ], [ -88.0434,41.6089 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5385b403e4b09e18fc023aae","contributors":{"authors":[{"text":"Warner, David M. 0000-0003-4939-5368 dmwarner@usgs.gov","orcid":"https://orcid.org/0000-0003-4939-5368","contributorId":2986,"corporation":false,"usgs":true,"family":"Warner","given":"David","email":"dmwarner@usgs.gov","middleInitial":"M.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":491537,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Farha, Steven A.","contributorId":79026,"corporation":false,"usgs":true,"family":"Farha","given":"Steven","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":491541,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"O’Brien, Timothy P. 0000-0003-4502-5204 tiobrien@usgs.gov","orcid":"https://orcid.org/0000-0003-4502-5204","contributorId":2662,"corporation":false,"usgs":true,"family":"O’Brien","given":"Timothy","email":"tiobrien@usgs.gov","middleInitial":"P.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":491536,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ogilvie, Lynn","contributorId":60540,"corporation":false,"usgs":true,"family":"Ogilvie","given":"Lynn","affiliations":[],"preferred":false,"id":491540,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Claramunt, Randall M.","contributorId":19047,"corporation":false,"usgs":true,"family":"Claramunt","given":"Randall M.","affiliations":[],"preferred":false,"id":491538,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hanson, Dale","contributorId":43676,"corporation":false,"usgs":true,"family":"Hanson","given":"Dale","affiliations":[],"preferred":false,"id":491539,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
]}