{"pageNumber":"563","pageRowStart":"14050","pageSize":"25","recordCount":46680,"records":[{"id":70047503,"text":"70047503 - 2013 - Social learning of migratory performance","interactions":[],"lastModifiedDate":"2013-10-30T12:41:03","indexId":"70047503","displayToPublicDate":"2013-09-03T11:12:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3338,"text":"Science","active":true,"publicationSubtype":{"id":10}},"title":"Social learning of migratory performance","docAbstract":"Successful bird migration can depend on individual learning, social learning, and innate navigation programs. Using 8 years of data on migrating whooping cranes, we were able to partition genetic and socially learned aspects of migration. Specifically, we analyzed data from a reintroduced population wherein all birds were captive bred and artificially trained by ultralight aircraft on their first lifetime migration. For subsequent migrations, in which birds fly individually or in groups but without ultralight escort, we found evidence of long-term social learning, but no effect of genetic relatedness on migratory performance. Social learning from older birds reduced deviations from a straight-line path, with 7 years of experience yielding a 38% improvement in migratory accuracy.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Science","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.1126/science.1237139","usgsCitation":"Mueller, T., O’Hara, R.B., Converse, S.J., Urbanek, R.P., and Fagan, W., 2013, Social learning of migratory performance: Science, v. 341, no. 6149, p. 999-1002, https://doi.org/10.1126/science.1237139.","productDescription":"4 p.","startPage":"999","endPage":"1002","numberOfPages":"4","ipdsId":"IP-049651","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":277238,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":277237,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1126/science.1237139"}],"volume":"341","issue":"6149","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5226f6e1e4b01904cf5a8153","contributors":{"authors":[{"text":"Mueller, Thomas","contributorId":91393,"corporation":false,"usgs":true,"family":"Mueller","given":"Thomas","affiliations":[],"preferred":false,"id":482204,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"O’Hara, Robert B.","contributorId":46402,"corporation":false,"usgs":true,"family":"O’Hara","given":"Robert","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":482203,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Converse, Sarah J. 0000-0002-3719-5441 sconverse@usgs.gov","orcid":"https://orcid.org/0000-0002-3719-5441","contributorId":3513,"corporation":false,"usgs":true,"family":"Converse","given":"Sarah","email":"sconverse@usgs.gov","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":482201,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Urbanek, Richard P.","contributorId":38400,"corporation":false,"usgs":true,"family":"Urbanek","given":"Richard","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":482202,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fagan, William F.","contributorId":108239,"corporation":false,"usgs":true,"family":"Fagan","given":"William F.","affiliations":[],"preferred":false,"id":482205,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70047947,"text":"70047947 - 2013 - Continuous gravity measurements reveal a low-density lava lake at Kīlauea Volcano, Hawai‘i","interactions":[],"lastModifiedDate":"2013-10-30T12:39:36","indexId":"70047947","displayToPublicDate":"2013-09-03T10:03:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1427,"text":"Earth and Planetary Science Letters","active":true,"publicationSubtype":{"id":10}},"title":"Continuous gravity measurements reveal a low-density lava lake at Kīlauea Volcano, Hawai‘i","docAbstract":"On 5 March 2011, the lava lake within the summit eruptive vent at Kīlauea Volcano, Hawai‘i, began to drain as magma withdrew to feed a dike intrusion and fissure eruption on the volcanoʼs east rift zone. The draining was monitored by a variety of continuous geological and geophysical measurements, including deformation, thermal and visual imagery, and gravity. Over the first ∼14 hours of the draining, the ground near the eruptive vent subsided by about 0.15 m, gravity dropped by more than 100 μGal, and the lava lake retreated by over 120 m. We used GPS data to correct the gravity signal for the effects of subsurface mass loss and vertical deformation in order to isolate the change in gravity due to draining of the lava lake alone. Using a model of the eruptive vent geometry based on visual observations and the lava level over time determined from thermal camera data, we calculated the best-fit lava density to the observed gravity decrease — to our knowledge, the first geophysical determination of the density of a lava lake anywhere in the world. Our result, 950 +/- 300 kg m<sup>-3</sup>, suggests a lava density less than that of water and indicates that Kīlaueaʼs lava lake is gas-rich, which can explain why rockfalls that impact the lake trigger small explosions. Knowledge of such a fundamental material property as density is also critical to investigations of lava-lake convection and degassing and can inform calculations of pressure change in the subsurface magma plumbing system.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Earth and Planetary Science Letters","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.epsl.2013.06.024","usgsCitation":"Carbone, D., Poland, M., Patrick, M.R., and Orr, T., 2013, Continuous gravity measurements reveal a low-density lava lake at Kīlauea Volcano, Hawai‘i: Earth and Planetary Science Letters, v. 376, no. 15 August, p. 178-185, https://doi.org/10.1016/j.epsl.2013.06.024.","productDescription":"8 p.","startPage":"178","endPage":"185","numberOfPages":"8","ipdsId":"IP-048829","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":277225,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.epsl.2013.06.024"},{"id":277228,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawai'i","otherGeospatial":"Kilauea Volcano","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -155.295439,19.388239 ], [ -155.295439,19.426125 ], [ -155.242481,19.426125 ], [ -155.242481,19.388239 ], [ -155.295439,19.388239 ] ] ] } } ] }","volume":"376","issue":"15 August","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5226f6dfe4b01904cf5a8143","contributors":{"authors":[{"text":"Carbone, Daniele","contributorId":38458,"corporation":false,"usgs":true,"family":"Carbone","given":"Daniele","affiliations":[],"preferred":false,"id":483365,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Poland, Michael P. 0000-0001-5240-6123 mpoland@usgs.gov","orcid":"https://orcid.org/0000-0001-5240-6123","contributorId":635,"corporation":false,"usgs":true,"family":"Poland","given":"Michael P.","email":"mpoland@usgs.gov","affiliations":[{"id":336,"text":"Hawaiian Volcano Observatory","active":false,"usgs":true}],"preferred":false,"id":483362,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Patrick, Matthew R. 0000-0002-8042-6639 mpatrick@usgs.gov","orcid":"https://orcid.org/0000-0002-8042-6639","contributorId":2070,"corporation":false,"usgs":true,"family":"Patrick","given":"Matthew","email":"mpatrick@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":483363,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Orr, Tim R. torr@usgs.gov","contributorId":3766,"corporation":false,"usgs":true,"family":"Orr","given":"Tim R.","email":"torr@usgs.gov","affiliations":[],"preferred":false,"id":483364,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70048654,"text":"70048654 - 2013 - Spatial capture-recapture","interactions":[],"lastModifiedDate":"2013-11-05T16:10:31","indexId":"70048654","displayToPublicDate":"2013-09-01T16:06:00","publicationYear":"2013","noYear":false,"publicationType":{"id":4,"text":"Book"},"title":"Spatial capture-recapture","docAbstract":"Spatial Capture-Recapture provides a revolutionary extension of traditional capture-recapture methods for studying animal populations using data from live trapping, camera trapping, DNA sampling, acoustic sampling, and related field methods.  This book is a conceptual and methodological synthesis of spatial capture-recapture modeling. As a comprehensive how-to manual, this reference contains detailed examples of a wide range of relevant spatial capture-recapture models for inference about population size and spatial and temporal variation in demographic parameters. Practicing field biologists studying animal populations will find this book to be a useful resource, as will graduate students and professionals in ecology, conservation biology, and fisheries and wildlife management.","language":"English","publisher":"Academic Press","publisherLocation":"Waltham, MA","isbn":"9780124059399","usgsCitation":"Royle, J., Chandler, R.B., Sollmann, R., and Gardner, B., 2013, Spatial capture-recapture, xxix, 577 p.","productDescription":"xxix, 577 p.","ipdsId":"IP-048864","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":278866,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":278477,"type":{"id":15,"text":"Index Page"},"url":"https://store.elsevier.com/Spatial-Capture-Recapture/J_-Royle/isbn-9780124059399/"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"527a219de4b051792d019641","contributors":{"authors":[{"text":"Royle, J. Andrew 0000-0003-3135-2167","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":80808,"corporation":false,"usgs":true,"family":"Royle","given":"J. Andrew","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":485309,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chandler, Richard B. rchandler@usgs.gov","contributorId":63524,"corporation":false,"usgs":true,"family":"Chandler","given":"Richard","email":"rchandler@usgs.gov","middleInitial":"B.","affiliations":[],"preferred":false,"id":485308,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sollmann, Rahel","contributorId":31667,"corporation":false,"usgs":true,"family":"Sollmann","given":"Rahel","affiliations":[],"preferred":false,"id":485307,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gardner, Beth","contributorId":91612,"corporation":false,"usgs":false,"family":"Gardner","given":"Beth","affiliations":[{"id":13553,"text":"University of Washington-Seattle","active":true,"usgs":false}],"preferred":false,"id":485310,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70048749,"text":"70048749 - 2013 - Geomagnetic referencing--the real-time compass for directional drillers","interactions":[],"lastModifiedDate":"2020-07-14T14:48:48.757797","indexId":"70048749","displayToPublicDate":"2013-09-01T15:50:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2943,"text":"Oilfield Review","active":true,"publicationSubtype":{"id":10}},"title":"Geomagnetic referencing--the real-time compass for directional drillers","docAbstract":"To pinpoint the location and direction of a wellborne, directional driller rely on measurements from accelerometers, magnetometer and gyroscopes. In the past, high-accuracy guidance methods required a halt in drilling to obtain directional measurements. Advances in geomagnetic referencing now allow companies to use real-time data acquired during drilling to accurately potion horizontal wells, decrease well spacing and drill multiple wells from limited surface locations.","language":"English","publisher":"Schlumberger","usgsCitation":"Buchanan, A., Finn, C., Love, J.J., Worthington, E.W., Lawson, F., Maus, S., Okewunmi, S., and Poedjono, B., 2013, Geomagnetic referencing--the real-time compass for directional drillers: Oilfield Review, v. 25, no. 3, p. 32-47.","productDescription":"16 p.","startPage":"32","endPage":"47","numberOfPages":"16","ipdsId":"IP-052299","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":280776,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"25","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd5e96e4b0b290850fbcb0","contributors":{"authors":[{"text":"Buchanan, Andrew","contributorId":90581,"corporation":false,"usgs":true,"family":"Buchanan","given":"Andrew","email":"","affiliations":[],"preferred":false,"id":485564,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Finn, Carol 0000-0003-3144-1645","orcid":"https://orcid.org/0000-0003-3144-1645","contributorId":13201,"corporation":false,"usgs":true,"family":"Finn","given":"Carol","affiliations":[],"preferred":false,"id":485559,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Love, Jeffrey J. 0000-0002-3324-0348 jlove@usgs.gov","orcid":"https://orcid.org/0000-0002-3324-0348","contributorId":760,"corporation":false,"usgs":true,"family":"Love","given":"Jeffrey","email":"jlove@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":485558,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Worthington, E. William 0000-0002-5879-0477 bworth@usgs.gov","orcid":"https://orcid.org/0000-0002-5879-0477","contributorId":69833,"corporation":false,"usgs":true,"family":"Worthington","given":"E.","email":"bworth@usgs.gov","middleInitial":"William","affiliations":[],"preferred":false,"id":485563,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lawson, Fraser","contributorId":17129,"corporation":false,"usgs":true,"family":"Lawson","given":"Fraser","email":"","affiliations":[],"preferred":false,"id":485560,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Maus, Stefan","contributorId":21060,"corporation":false,"usgs":true,"family":"Maus","given":"Stefan","email":"","affiliations":[],"preferred":false,"id":485561,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Okewunmi, Shola","contributorId":48859,"corporation":false,"usgs":true,"family":"Okewunmi","given":"Shola","email":"","affiliations":[],"preferred":false,"id":485562,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Poedjono, Benny","contributorId":105218,"corporation":false,"usgs":true,"family":"Poedjono","given":"Benny","email":"","affiliations":[],"preferred":false,"id":485565,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70200748,"text":"70200748 - 2013 - The Anemomilos prediction methodology for Dst","interactions":[],"lastModifiedDate":"2018-10-30T15:39:46","indexId":"70200748","displayToPublicDate":"2013-09-01T15:39:36","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3456,"text":"Space Weather","active":true,"publicationSubtype":{"id":10}},"title":"The Anemomilos prediction methodology for Dst","docAbstract":"<p><span>This paper describes new capabilities for operational geomagnetic&nbsp;</span><span class=\"underlined\">D</span><span>isturbance&nbsp;</span><span class=\"underlined\">s</span><span>torm&nbsp;</span><span class=\"underlined\">t</span><span>ime (Dst) index forecasts. We present a data‐driven, deterministic algorithm called&nbsp;</span><i>Anemomilos</i><span>&nbsp;for forecasting Dst out to a maximum of 6 days for large, medium, and small storms, depending upon transit time to the Earth. This capability is used for operational satellite management and debris avoidance in Low Earth Orbit (LEO).&nbsp;</span><i>Anemomilos</i><span>&nbsp;has a 15 min cadence, 1 h time granularity, 144 h prediction window (+6 days), and up to 1 h latency. A new finding is that nearly all flare events above a certain irradiance threshold, occurring within a defined solar longitude/latitude region and having sufficient estimated liftoff velocity of ejected material, will produce a geoeffective Dst perturbation. Three solar observables are used for operational Dst forecasting: flare magnitude, integrated flare irradiance through time, and event location. Magnitude is a proxy for ejecta quantity or mass and, combined with speed derived from the integrated flare irradiance, represents the kinetic energy. Speed is estimated as the line‐of‐sight velocity for events within 45° radial of solar disk center. Storms resulting from high‐speed streams emanating from coronal holes are not modeled or predicted. A new result is that solar disk, not limb, observable features are used for predictive techniques. Comparisons between&nbsp;</span><i>Anemomilos</i><span>&nbsp;predicted and measured Dst for every hour over 25 months in three continuous time frames between 2001 (high solar activity), 2005 (low solar activity), and 2012 (rising solar activity) are shown. The&nbsp;</span><i>Anemomilos</i><span>&nbsp;operational algorithm was developed for a specific customer use related to thermospheric mass density forecasting. It is an operational space weather technology breakthrough using solar disk observables to predict geomagnetically effective Dst up to several days at 1 h time granularity. Real‐time forecasts are presented at&nbsp;</span><a class=\"linkBehavior\" href=\"http://sol.spacenvironment.net/~sam_ops/index.html?\" data-mce-href=\"http://sol.spacenvironment.net/~sam_ops/index.html\">http://sol.spacenvironment.net/~sam_ops/index.html?</a></p>","language":"English","publisher":"AGU","doi":"10.1002/swe.20094","usgsCitation":"Tobiska, W.K., Knipp, D., Burke, W.J., Bouwer, D., Bailey, J., Odstrcil, D., Hagan, M.P., Gannon, J., and Bowman, B.R., 2013, The Anemomilos prediction methodology for Dst: Space Weather, v. 11, no. 9, p. 490-508, https://doi.org/10.1002/swe.20094.","productDescription":"19 p.","startPage":"490","endPage":"508","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":473558,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/swe.20094","text":"Publisher Index Page"},{"id":358986,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","issue":"9","noUsgsAuthors":false,"publicationDate":"2013-09-19","publicationStatus":"PW","scienceBaseUri":"5c10b8c5e4b034bf6a7ecc12","contributors":{"authors":[{"text":"Tobiska, W. K.","contributorId":210274,"corporation":false,"usgs":false,"family":"Tobiska","given":"W.","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":750350,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Knipp, D.","contributorId":210275,"corporation":false,"usgs":false,"family":"Knipp","given":"D.","email":"","affiliations":[],"preferred":false,"id":750351,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Burke, W. J.","contributorId":210276,"corporation":false,"usgs":false,"family":"Burke","given":"W.","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":750352,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bouwer, D.","contributorId":210277,"corporation":false,"usgs":false,"family":"Bouwer","given":"D.","email":"","affiliations":[],"preferred":false,"id":750353,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bailey, J.","contributorId":11981,"corporation":false,"usgs":true,"family":"Bailey","given":"J.","affiliations":[],"preferred":false,"id":750354,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Odstrcil, D.","contributorId":210278,"corporation":false,"usgs":false,"family":"Odstrcil","given":"D.","email":"","affiliations":[],"preferred":false,"id":750355,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hagan, M. P.","contributorId":210279,"corporation":false,"usgs":false,"family":"Hagan","given":"M.","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":750356,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Gannon, J.","contributorId":52869,"corporation":false,"usgs":true,"family":"Gannon","given":"J.","email":"","affiliations":[],"preferred":false,"id":750357,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Bowman, B. R.","contributorId":210280,"corporation":false,"usgs":false,"family":"Bowman","given":"B.","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":750358,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70057407,"text":"70057407 - 2013 - Mitigating the effects of landscape development on streams in urbanizing watersheds","interactions":[],"lastModifiedDate":"2014-02-03T11:21:16","indexId":"70057407","displayToPublicDate":"2013-09-01T15:11:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"Mitigating the effects of landscape development on streams in urbanizing watersheds","docAbstract":"This collaborative study examined urbanization and impacts on area streams while using the best available sediment and erosion control (S&EC) practices in developing watersheds in Maryland, United States. During conversion of the agricultural and forested watersheds to urban land use, land surface topography was graded and vegetation was removed creating a high potential for sediment generation and release during storm events. The currently best available S&EC facilities were used during the development process to mitigate storm runoff water quality, quantity, and timing before entering area streams. Detailed Geographic Information System (GIS) maps were created to visualize changing land use and S&EC practices, five temporal collections of LiDAR (light detection and ranging) imagery were used to map the changing landscape topography, and streamflow, physical geomorphology, and habitat data were used to assess the ability of the S&EC facilities to protect receiving streams during development. Despite the use of the best available S&EC facilities, receiving streams experienced altered flow, geomorphology, and decreased biotic community health. These impacts on small streams during watershed development affect sediment and nutrient loads to larger downstream aquatic ecosystems such as the Chesapeake Bay.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of the American Water Resources Association","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1111/jawr.12123","usgsCitation":"Hogan, D.M., Jarnagin, S., Loperfido, J.V., and Van Ness, K., 2013, Mitigating the effects of landscape development on streams in urbanizing watersheds: Journal of the American Water Resources Association, v. 50, no. 1, p. 163-178, https://doi.org/10.1111/jawr.12123.","productDescription":"16 p.","startPage":"163","endPage":"178","numberOfPages":"16","ipdsId":"IP-040683","costCenters":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"links":[{"id":279616,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":279615,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/jawr.12123"}],"country":"United States","state":"Maryl","county":"Montgomery County","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -77.527376,38.93428 ], [ -77.527376,39.354025 ], [ -76.888361,39.354025 ], [ -76.888361,38.93428 ], [ -77.527376,38.93428 ] ] ] } } ] }","volume":"50","issue":"1","noUsgsAuthors":false,"publicationDate":"2013-09-12","publicationStatus":"PW","scienceBaseUri":"52908b09e4b0bbdcf23f0935","contributors":{"authors":[{"text":"Hogan, Dianna M. 0000-0003-1492-4514 dhogan@usgs.gov","orcid":"https://orcid.org/0000-0003-1492-4514","contributorId":2299,"corporation":false,"usgs":true,"family":"Hogan","given":"Dianna","email":"dhogan@usgs.gov","middleInitial":"M.","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":false,"id":486670,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jarnagin, S. Taylor","contributorId":32816,"corporation":false,"usgs":true,"family":"Jarnagin","given":"S. Taylor","affiliations":[],"preferred":false,"id":486672,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Loperfido, John V. jloperfido@usgs.gov","contributorId":4324,"corporation":false,"usgs":true,"family":"Loperfido","given":"John","email":"jloperfido@usgs.gov","middleInitial":"V.","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":false,"id":486671,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Van Ness, Keith","contributorId":46866,"corporation":false,"usgs":true,"family":"Van Ness","given":"Keith","email":"","affiliations":[],"preferred":false,"id":486673,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70112716,"text":"70112716 - 2013 - Ecological prediction with nonlinear multivariate time-frequency functional data models","interactions":[],"lastModifiedDate":"2016-11-22T14:09:39","indexId":"70112716","displayToPublicDate":"2013-09-01T14:03:25","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2151,"text":"Journal of Agricultural, Biological, and Environmental Statistics","active":true,"publicationSubtype":{"id":10}},"title":"Ecological prediction with nonlinear multivariate time-frequency functional data models","docAbstract":"Time-frequency analysis has become a fundamental component of many scientific inquiries. Due to improvements in technology, the amount of high-frequency signals that are collected for ecological and other scientific processes is increasing at a dramatic rate. In order to facilitate the use of these data in ecological prediction, we introduce a class of nonlinear multivariate time-frequency functional models that can identify important features of each signal as well as the interaction of signals corresponding to the response variable of interest. Our methodology is of independent interest and utilizes stochastic search variable selection to improve model selection and performs model averaging to enhance prediction. We illustrate the effectiveness of our approach through simulation and by application to predicting spawning success of shovelnose sturgeon in the Lower Missouri River.","language":"English","publisher":"Springer","doi":"10.1007/s13253-013-0142-1","usgsCitation":"Yang, W., Wikle, C.K., Holan, S.H., and Wildhaber, M.L., 2013, Ecological prediction with nonlinear multivariate time-frequency functional data models: Journal of Agricultural, Biological, and Environmental Statistics, v. 18, no. 3, p. 450-474, https://doi.org/10.1007/s13253-013-0142-1.","productDescription":"25 p.","startPage":"450","endPage":"474","numberOfPages":"25","ipdsId":"IP-041815","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":288701,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":288700,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s13253-013-0142-1"}],"country":"United States","otherGeospatial":"Lower Missouri River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -101.36,38.0 ], [ -101.36,44.98 ], [ -89.65,44.98 ], [ -89.65,38.0 ], [ -101.36,38.0 ] ] ] } } ] }","volume":"18","issue":"3","noUsgsAuthors":false,"publicationDate":"2013-06-26","publicationStatus":"PW","scienceBaseUri":"53ae7693e4b0abf75cf2bfab","contributors":{"authors":[{"text":"Yang, Wen-Hsi","contributorId":45228,"corporation":false,"usgs":true,"family":"Yang","given":"Wen-Hsi","email":"","affiliations":[],"preferred":false,"id":494856,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wikle, Christopher K.","contributorId":55680,"corporation":false,"usgs":true,"family":"Wikle","given":"Christopher","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":494857,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Holan, Scott H.","contributorId":15878,"corporation":false,"usgs":true,"family":"Holan","given":"Scott","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":494855,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wildhaber, Mark L. 0000-0002-6538-9083 mwildhaber@usgs.gov","orcid":"https://orcid.org/0000-0002-6538-9083","contributorId":1386,"corporation":false,"usgs":true,"family":"Wildhaber","given":"Mark","email":"mwildhaber@usgs.gov","middleInitial":"L.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":494854,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70047801,"text":"70047801 - 2013 - Application of uniaxial confining-core clamp with hydrous pyrolysis in petrophysical and geochemical studies of source rocks at various thermal maturities","interactions":[],"lastModifiedDate":"2014-05-30T10:01:39","indexId":"70047801","displayToPublicDate":"2013-09-01T13:46:00","publicationYear":"2013","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Application of uniaxial confining-core clamp with hydrous pyrolysis in petrophysical and geochemical studies of source rocks at various thermal maturities","docAbstract":"Understanding changes in petrophysical and geochemical parameters during source rock thermal maturation is a critical component in evaluating source-rock petroleum accumulations. Natural core data are preferred, but obtaining cores that represent the same facies of a source rock at different thermal maturities is seldom possible. An alternative approach is to induce thermal maturity changes by laboratory pyrolysis on aliquots of a source-rock sample of a given facies of interest. Hydrous pyrolysis is an effective way to induce thermal maturity on source-rock cores and provide expelled oils that are similar in composition to natural crude oils. However, net-volume increases during bitumen and oil generation result in expanded cores due to opening of bedding-plane partings. Although meaningful geochemical measurements on expanded, recovered cores are possible, the utility of the core for measuring petrophysical properties relevant to natural subsurface cores is not suitable. This problem created during hydrous pyrolysis is alleviated by using a stainless steel uniaxial confinement clamp on rock cores cut perpendicular to bedding fabric. The clamp prevents expansion just as overburden does during natural petroleum formation in the subsurface. As a result, intact cores can be recovered at various thermal maturities for the measurement of petrophysical properties as well as for geochemical analyses. This approach has been applied to 1.7-inch diameter cores taken perpendicular to the bedding fabric of a 2.3- to 2.4-inch thick slab of Mahogany oil shale from the Eocene Green River Formation. Cores were subjected to hydrous pyrolysis at 360 °C for 72 h, which represents near maximum oil generation. One core was heated unconfined and the other was heated in the uniaxial confinement clamp. The unconfined core developed open tensile fractures parallel to the bedding fabric that result in a 38 % vertical expansion of the core. These open fractures did not occur in the confined core, but short, discontinuous vertical fractures on the core periphery occurred as a result of lateral expansion.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Unconventional Resources Technology Conference, Denver, Colorado, 12-14 August 2013","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"Society of Exploration Geophysicists, American Association of Petroleum Geologists, Society of Petroleum Engineers","doi":"10.1190/urtec2013-267","usgsCitation":"Lewan, M., and Birdwell, J.E., 2013, Application of uniaxial confining-core clamp with hydrous pyrolysis in petrophysical and geochemical studies of source rocks at various thermal maturities, <i>in</i> Unconventional Resources Technology Conference, Denver, Colorado, 12-14 August 2013, p. 2565-2572, https://doi.org/10.1190/urtec2013-267.","productDescription":"8 p.","startPage":"2565","endPage":"2572","numberOfPages":"8","ipdsId":"IP-045856","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":287612,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":287652,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1190/urtec2013-267"}],"noUsgsAuthors":false,"publicationDate":"2013-09-26","publicationStatus":"PW","scienceBaseUri":"5385b3e9e4b09e18fc023a22","contributors":{"editors":[{"text":"Baez, Luis","contributorId":111487,"corporation":false,"usgs":true,"family":"Baez","given":"Luis","email":"","affiliations":[],"preferred":false,"id":509582,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Beeney, Ken","contributorId":112969,"corporation":false,"usgs":true,"family":"Beeney","given":"Ken","email":"","affiliations":[],"preferred":false,"id":509584,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Sonnenberg, Steve","contributorId":112354,"corporation":false,"usgs":true,"family":"Sonnenberg","given":"Steve","affiliations":[],"preferred":false,"id":509583,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"Lewan, Michael D. mlewan@usgs.gov","contributorId":940,"corporation":false,"usgs":true,"family":"Lewan","given":"Michael D.","email":"mlewan@usgs.gov","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":482997,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Birdwell, Justin E. 0000-0001-8263-1452 jbirdwell@usgs.gov","orcid":"https://orcid.org/0000-0001-8263-1452","contributorId":3302,"corporation":false,"usgs":true,"family":"Birdwell","given":"Justin","email":"jbirdwell@usgs.gov","middleInitial":"E.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":482998,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70057613,"text":"70057613 - 2013 - Custom microarray construction and analysis for determining potential biomarkers of subchronic androgen exposure in the Eastern Mosquitofish (<i>Gambusia holbrooki</i>)","interactions":[],"lastModifiedDate":"2015-10-29T10:27:55","indexId":"70057613","displayToPublicDate":"2013-09-01T13:37:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":956,"text":"BMC Genomics","active":true,"publicationSubtype":{"id":10}},"title":"Custom microarray construction and analysis for determining potential biomarkers of subchronic androgen exposure in the Eastern Mosquitofish (<i>Gambusia holbrooki</i>)","docAbstract":"<h4>Background</h4>\n<p>The eastern mosquitofish (<i>Gambusia holbrooki</i>) has the potential to become a bioindicator organism of endocrine disrupting chemicals (EDCs) due to its androgen-driven secondary sexual characteristics. However, the lack of molecular information on&nbsp;<i>G</i>.&nbsp;<i>holbrooki</i>&nbsp;hinders its use as a bioindicator coupled with biomarker data. While traditional gene-by-gene approaches provide insight for biomarker development, a holistic analysis would provide more rapid and expansive determination of potential biomarkers. The objective of this study was to develop and utilize a mosquitofish microarray to determine potential biomarkers of subchronic androgen exposure. To achieve this objective, two specific aims were developed: 1) Sequence a&nbsp;<i>G</i>.&nbsp;<i>holbrooki</i>&nbsp;cDNA library, and 2) Use microarray analysis to determine genes that are differentially regulated by subchronic androgen exposure in hepatic tissues of 17&beta;-trenbolone (TB) exposed adult female&nbsp;<i>G</i>.&nbsp;<i>holbrooki</i>.</p>\n<h4>Results</h4>\n<p>A normalized library of multiple organs of male and female&nbsp;<i>G</i>.&nbsp;<i>holbrooki</i>&nbsp;was prepared and sequenced by the Illumina GA IIx and Roche 454 XLR70. Over 30,000 genes with e-value&thinsp;&le;&thinsp;10<sup>-4</sup>were annotated and 14,758 of these genes were selected for inclusion on the microarray. Hepatic microarray analysis of adult female&nbsp;<i>G</i>.&nbsp;<i>holbrooki</i>&nbsp;exposed to the vehicle control or 1&nbsp;&mu;g/L of TB (a potent anabolic androgen) revealed 229 genes upregulated and 279 downregulated by TB (one-way ANOVA, p&thinsp;&lt;&thinsp;0.05, FDR &alpha;&thinsp;=&thinsp;0.05, fold change&thinsp;&gt;&thinsp;1.5 and&thinsp;&lt;&thinsp;&minus;1.5). Fifteen gene ontology biological processes were enriched by TB exposure (Fisher&rsquo;s Exact Test, p&thinsp;&lt;&thinsp;0.05). The expression levels of<i>17&beta;</i>-<i>hydroxysteroid dehydrogenase 3</i>&nbsp;and&nbsp;<i>zona pellucida glycoprotein 2</i>&nbsp;were validated by quantitative polymerase chain reaction (qPCR) (Student&rsquo;s t-test, p&thinsp;&lt;&thinsp;0.05).</p>\n<h4>Conclusions</h4>\n<p>Coupling microarray data with phenotypic changes driven by androgen exposure in mosquitofish is key for developing this organism into a bioindicator for EDCs. Future studies using this array will enhance knowledge of the biology and toxicological response of this species. This work provides a foundation of molecular knowledge and tools that can be used to delve further into understanding the biology of&nbsp;<i>G</i>.&nbsp;<i>holbrooki</i>&nbsp;and how this organism can be used as a bioindicator organism for endocrine disrupting pollutants in the environment.</p>","language":"English","publisher":"BioMed Central","doi":"10.1186/1471-2164-14-660","usgsCitation":"Brockmeier, E.K., Yu, F., Amador, D.M., Bargar, T.A., and Denslow, N., 2013, Custom microarray construction and analysis for determining potential biomarkers of subchronic androgen exposure in the Eastern Mosquitofish (<i>Gambusia holbrooki</i>): BMC Genomics, v. 14, no. 660, art660: 11 p., https://doi.org/10.1186/1471-2164-14-660.","productDescription":"art660: 11 p.","numberOfPages":"11","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-046312","costCenters":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"links":[{"id":473560,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/1471-2164-14-660","text":"Publisher Index Page"},{"id":279841,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":279840,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1186/1471-2164-14-660"}],"volume":"14","issue":"660","noUsgsAuthors":false,"publicationDate":"2013-09-28","publicationStatus":"PW","scienceBaseUri":"5295d10ae4b0becc369c8b12","contributors":{"authors":[{"text":"Brockmeier, Erica K.","contributorId":26619,"corporation":false,"usgs":true,"family":"Brockmeier","given":"Erica","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":486858,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yu, Fahong","contributorId":107180,"corporation":false,"usgs":true,"family":"Yu","given":"Fahong","email":"","affiliations":[],"preferred":false,"id":486860,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Amador, David Moraga","contributorId":18262,"corporation":false,"usgs":true,"family":"Amador","given":"David","email":"","middleInitial":"Moraga","affiliations":[],"preferred":false,"id":486857,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bargar, Timothy A. 0000-0001-8588-3436 tbargar@usgs.gov","orcid":"https://orcid.org/0000-0001-8588-3436","contributorId":2450,"corporation":false,"usgs":true,"family":"Bargar","given":"Timothy","email":"tbargar@usgs.gov","middleInitial":"A.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":486856,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Denslow, Nancy D.","contributorId":72831,"corporation":false,"usgs":true,"family":"Denslow","given":"Nancy D.","affiliations":[],"preferred":false,"id":486859,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70047803,"text":"70047803 - 2013 - A new laboratory approach to shale analysis using NMR relaxometry","interactions":[],"lastModifiedDate":"2014-05-30T10:03:33","indexId":"70047803","displayToPublicDate":"2013-09-01T13:32:00","publicationYear":"2013","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"A new laboratory approach to shale analysis using NMR relaxometry","docAbstract":"<p>Low-field nuclear magnetic resonance (LF-NMR) relaxometry is a non-invasive technique commonly used to assess hydrogen-bearing fluids in petroleum reservoir rocks. Measurements made using LF-NMR provide information on rock porosity, pore-size distributions, and in some cases, fluid types and saturations (Timur, 1967; Kenyon et al., 1986; Straley et al., 1994; Brown, 2001; Jackson, 2001; Kleinberg, 2001; Hurlimann et al., 2002). Recent improvements in LF-NMR instrument electronics have made it possible to apply methods used to measure pore fluids to assess highly viscous and even solid organic phases within reservoir rocks. T<sub>1</sub> and T<sub>2</sub> relaxation responses behave very differently in solids and liquids; therefore the relationship between these two modes of relaxation can be used to differentiate organic phases in rock samples or to characterize extracted organic materials. Using T<sub>1</sub>-T<sub>2</sub> correlation data, organic components present in shales, such as kerogen and bitumen, can be examined in laboratory relaxometry measurements. In addition, implementation of a solid-echo pulse sequence to refocus T<sub>2</sub> relaxation caused by homonuclear dipolar coupling during correlation measurements allows for improved resolution of solid-phase protons.</p>\n<br/>\n<p>LF-NMR measurements of T<sub>1</sub> and T<sub>2</sub> relaxation time distributions were carried out on raw oil shale samples from the Eocene Green River Formation and pyrolyzed samples of these shales processed by hydrous pyrolysis and techniques meant to mimic surface and in-situ retorting. Samples processed using the In Situ Simulator approach ranged from bitumen and early oil generation through to depletion of petroleum generating potential. The standard T<sub>1</sub>-T<sub>2</sub> correlation plots revealed distinct peaks representative of solid- and liquid-like organic phases; results on the pyrolyzed shales reflect changes that occurred during thermal processing. The solid-echo T<sub>1</sub> and T<sub>2</sub> measurements were used to improve assessment of the solid organic phases, specifically kerogen, thermally degraded kerogen, and char. Integrated peak areas from the LF-NMR results representative of kerogen and bitumen were found to be well correlated with S1 and S2 parameters from Rock-Eval programmed pyrolysis. This study demonstrates that LFNMR relaxometry can provide a wide range of information on shales and other reservoir rocks that goes well beyond porosity and pore-fluid analysis.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Unconventional Resources Technology Conference, Denver, Colorado, 12-14 August 2013","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"Society of Exploration Geophysicists, American Association of Petroleum Geologists, Society of Petroleum Engineers","doi":"10.1190/urtec2013-181","usgsCitation":"Washburn, K.E., and Birdwell, J.E., 2013, A new laboratory approach to shale analysis using NMR relaxometry, <i>in</i> Unconventional Resources Technology Conference, Denver, Colorado, 12-14 August 2013, p. 1775-1782, https://doi.org/10.1190/urtec2013-181.","productDescription":"8 p.","startPage":"1775","endPage":"1782","numberOfPages":"8","ipdsId":"IP-045895","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":287609,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":287656,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1190/urtec2013-181"}],"noUsgsAuthors":false,"publicationDate":"2013-09-26","publicationStatus":"PW","scienceBaseUri":"5385b3e5e4b09e18fc023a10","contributors":{"editors":[{"text":"Baez, Luis","contributorId":111487,"corporation":false,"usgs":true,"family":"Baez","given":"Luis","email":"","affiliations":[],"preferred":false,"id":509585,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Beeney, Ken","contributorId":112969,"corporation":false,"usgs":true,"family":"Beeney","given":"Ken","email":"","affiliations":[],"preferred":false,"id":509587,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Sonnenberg, Steve","contributorId":112354,"corporation":false,"usgs":true,"family":"Sonnenberg","given":"Steve","affiliations":[],"preferred":false,"id":509586,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"Washburn, Kathryn E.","contributorId":76644,"corporation":false,"usgs":false,"family":"Washburn","given":"Kathryn","email":"","middleInitial":"E.","affiliations":[{"id":7152,"text":"Weatherford International","active":true,"usgs":false}],"preferred":false,"id":483000,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Birdwell, Justin E. 0000-0001-8263-1452 jbirdwell@usgs.gov","orcid":"https://orcid.org/0000-0001-8263-1452","contributorId":3302,"corporation":false,"usgs":true,"family":"Birdwell","given":"Justin","email":"jbirdwell@usgs.gov","middleInitial":"E.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":482999,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70104281,"text":"70104281 - 2013 - Evaluating analytical approaches for estimating pelagic fish biomass using simulated fish communities","interactions":[],"lastModifiedDate":"2014-05-13T12:56:27","indexId":"70104281","displayToPublicDate":"2013-09-01T12:51:56","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating analytical approaches for estimating pelagic fish biomass using simulated fish communities","docAbstract":"Pelagic fish assessments often combine large amounts of acoustic-based fish density data and limited midwater trawl information to estimate species-specific biomass density. We compared the accuracy of five apportionment methods for estimating pelagic fish biomass density using simulated communities with known fish numbers that mimic Lakes Superior, Michigan, and Ontario, representing a range of fish community complexities. Across all apportionment methods, the error in the estimated biomass generally declined with increasing effort, but methods that accounted for community composition changes with water column depth performed best. Correlations between trawl catch and the true species composition were highest when more fish were caught, highlighting the benefits of targeted trawling in locations of high fish density. Pelagic fish surveys should incorporate geographic and water column depth stratification in the survey design, use apportionment methods that account for species-specific depth differences, target midwater trawling effort in areas of high fish density, and include at least 15 midwater trawls. With relatively basic biological information, simulations of fish communities and sampling programs can optimize effort allocation and reduce error in biomass estimates.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Canadian Journal of Fisheries and Aquatic Sciences","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"NRC Research Press","doi":"10.1139/cjfas-2013-0072","usgsCitation":"Yule, D., Adams, J.V., Warner, D.M., Hrabik, T.R., Kocovsky, P., Weidel, B., Rudstam, L.G., and Sullivan, P., 2013, Evaluating analytical approaches for estimating pelagic fish biomass using simulated fish communities: Canadian Journal of Fisheries and Aquatic Sciences, v. 70, no. 12, p. 1845-1857, https://doi.org/10.1139/cjfas-2013-0072.","productDescription":"13 p.","startPage":"1845","endPage":"1857","numberOfPages":"13","ipdsId":"IP-050720","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":287090,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":287089,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1139/cjfas-2013-0072"}],"volume":"70","issue":"12","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53733ef6e4b04970612788f2","contributors":{"authors":[{"text":"Yule, Daniel L.","contributorId":92130,"corporation":false,"usgs":true,"family":"Yule","given":"Daniel L.","affiliations":[],"preferred":false,"id":493654,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Adams, Jean V. 0000-0002-9101-068X jvadams@usgs.gov","orcid":"https://orcid.org/0000-0002-9101-068X","contributorId":3140,"corporation":false,"usgs":true,"family":"Adams","given":"Jean","email":"jvadams@usgs.gov","middleInitial":"V.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":493650,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":493649,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hrabik, Thomas R.","contributorId":35614,"corporation":false,"usgs":false,"family":"Hrabik","given":"Thomas","email":"","middleInitial":"R.","affiliations":[{"id":6915,"text":"University of Minnesota - Duluth","active":true,"usgs":false}],"preferred":false,"id":493651,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kocovsky, Patrick M.","contributorId":89381,"corporation":false,"usgs":true,"family":"Kocovsky","given":"Patrick M.","affiliations":[],"preferred":false,"id":493653,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Weidel, Brian 0000-0001-6095-2773 bweidel@usgs.gov","orcid":"https://orcid.org/0000-0001-6095-2773","contributorId":2485,"corporation":false,"usgs":true,"family":"Weidel","given":"Brian","email":"bweidel@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":493648,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rudstam, Lars G.","contributorId":56609,"corporation":false,"usgs":false,"family":"Rudstam","given":"Lars","email":"","middleInitial":"G.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":493652,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sullivan, Patrick J.","contributorId":97813,"corporation":false,"usgs":true,"family":"Sullivan","given":"Patrick J.","affiliations":[],"preferred":false,"id":493655,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70048694,"text":"70048694 - 2013 - Wintering and breeding bird monitoring data analysis 2010-2013: San Antonio Missions National Historical Park","interactions":[],"lastModifiedDate":"2014-01-10T13:05:00","indexId":"70048694","displayToPublicDate":"2013-09-01T12:47:39","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"seriesTitle":{"id":270,"text":"National Park Service Natural Resource Data Series","active":false,"publicationSubtype":{"id":4}},"seriesNumber":"NPS/GULN/NRDS—2013/556","title":"Wintering and breeding bird monitoring data analysis 2010-2013: San Antonio Missions National Historical Park","docAbstract":"Following guidance issued within the Avian Inventory and Monitoring in National Parks of the Gulf Coast Network: Gulf Coast Network Avian Monitoring Plan, 40 point locations were established and monitored within San Antonio Missions National Historical Park. During three breeding seasons (May – Jun) and winters (Dec – Feb) between 2010 and 2013, birds were monitored at 20 or 30 of these point locations via time-distance point counts (breeding) or area searches (winter). To ensure data from all 40 random locations were included in analyses, monitoring data from two consecutive years were combined. As a result, some points were monitored twice during the period of analysis. Even so, I have treated each survey as an independent monitoring event, thereby assuming each visit to be equally representative of the bird community for the entirety of San Antonio Missions National Historical Park. When translating avian densities to park-wide populations, I used an area of 334 ha to represent San Antonio Missions National Historical Park including the Rancho de las Cabras unit.","language":"English","publisher":"U.S. National Park Service","publisherLocation":"Fort Collins, CO","usgsCitation":"Twedt, D.J., 2013, Wintering and breeding bird monitoring data analysis 2010-2013: San Antonio Missions National Historical Park: National Park Service Natural Resource Data Series NPS/GULN/NRDS—2013/556, v, 24 p.","productDescription":"v, 24 p.","numberOfPages":"31","temporalStart":"2010-05-01","temporalEnd":"2013-12-31","ipdsId":"IP-025848","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":280816,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":278578,"type":{"id":15,"text":"Index Page"},"url":"https://irma.nps.gov/App/Reference/Profile/2203425"}],"country":"United States","state":"Texas","city":"San Antonio","otherGeospatial":"San Antonio Missions National Historical Park","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -98.512344,29.311249 ], [ -98.512344,29.431151 ], [ -98.43544,29.431151 ], [ -98.43544,29.311249 ], [ -98.512344,29.311249 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd7dbfe4b0b2908510f923","contributors":{"authors":[{"text":"Twedt, Daniel J. 0000-0003-1223-5045 dtwedt@usgs.gov","orcid":"https://orcid.org/0000-0003-1223-5045","contributorId":398,"corporation":false,"usgs":true,"family":"Twedt","given":"Daniel","email":"dtwedt@usgs.gov","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":485448,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70074055,"text":"70074055 - 2013 - Low-field nuclear magnetic resonance characterization of organic content in shales","interactions":[],"lastModifiedDate":"2014-05-28T11:56:54","indexId":"70074055","displayToPublicDate":"2013-09-01T11:41:09","publicationYear":"2013","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Low-field nuclear magnetic resonance characterization of organic content in shales","docAbstract":"<p>Low-field nuclear magnetic resonance (LF-NMR) relaxometry is a non-invasive technique commonly used to assess hydrogen-bearing fluids in petroleum reservoir rocks. Longitudinal T<sub>1</sub> and transverse T<sub>2</sub> relaxation time measurements made using LF-NMR on conventional reservoir systems provides information on rock porosity, pore size distributions, and fluid types and saturations in some cases. Recent improvements in LF-SNMR instrument electronics have made it possible to apply these methods to assess highly viscous and even solid organic phases within reservoir rocks. T<sub>1</sub> and T<sub>2</sub> relaxation responses behave very differently in solids and liquids, therefore the relationship between these two modes of relaxation can be used to differentiate organic phases in rock samples or to characterize extracted organic materials. Using T<sub>1</sub>-T<sub>2</sub> correlation data, organic components present in shales, such as kerogen and bitumen, can be examined in laboratory relaxometry measurements. In addition, implementation of a solid-echo pulse sequence to refocus some types of T<sub>2</sub> relaxation during correlation measurements allows for improved resolution of solid phase photons.</p>\n<br/>\n<p>LF-NMR measurements of T<sub>1</sub> and T<sub>2</sub> relaxation time correlations were carried out on raw oil shale samples from resources around the world. These shales vary widely in mineralogy, total organic carbon (TOC) content and kerogen type. NMR results were correlcated with Leco TOC and geochemical data obtained from Rock-Eval. There is excellent correlation between NMR data and programmed pyrolysis parameters, particularly TOC and S2, and predictive capability is also good. To better understand the NMR response, the 2D NMR spectra were compared to similar NMR measurements made using high-field (HF) NMR equipment.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings: International Symposium of the Society of Core Analysts","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"Society of Core Analysts","usgsCitation":"Washburn, K.E., Birdwell, J.E., Seymour, J.D., Kirkland, C., and Vogt, S.J., 2013, Low-field nuclear magnetic resonance characterization of organic content in shales, <i>in</i> Proceedings: International Symposium of the Society of Core Analysts, 12 p.","productDescription":"12 p.","numberOfPages":"12","ipdsId":"IP-045577","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":287670,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":287669,"type":{"id":15,"text":"Index Page"},"url":"https://www.scaweb.org/symposium_2013_proceedings.shtml"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5387056de4b0aa26cd7b53c5","contributors":{"authors":[{"text":"Washburn, Kathryn E.","contributorId":76644,"corporation":false,"usgs":false,"family":"Washburn","given":"Kathryn","email":"","middleInitial":"E.","affiliations":[{"id":7152,"text":"Weatherford International","active":true,"usgs":false}],"preferred":false,"id":489351,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Birdwell, Justin E. 0000-0001-8263-1452 jbirdwell@usgs.gov","orcid":"https://orcid.org/0000-0001-8263-1452","contributorId":3302,"corporation":false,"usgs":true,"family":"Birdwell","given":"Justin","email":"jbirdwell@usgs.gov","middleInitial":"E.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":489349,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Seymour, Joseph D.","contributorId":59353,"corporation":false,"usgs":true,"family":"Seymour","given":"Joseph","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":489350,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kirkland, Catherine","contributorId":82616,"corporation":false,"usgs":true,"family":"Kirkland","given":"Catherine","affiliations":[],"preferred":false,"id":489352,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Vogt, Sarah J.","contributorId":86267,"corporation":false,"usgs":true,"family":"Vogt","given":"Sarah","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":489353,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70074054,"text":"70074054 - 2013 - NMR measurement of oil shale magnetic relaxation at high magnetic field","interactions":[],"lastModifiedDate":"2014-05-28T11:39:50","indexId":"70074054","displayToPublicDate":"2013-09-01T11:26:46","publicationYear":"2013","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"NMR measurement of oil shale magnetic relaxation at high magnetic field","docAbstract":"Nuclear magnetic resonance (NMR) at low field is used extensively to provide porosity and \npore-size distributions in reservoir rocks. For unconventional resources, due to low porosity and \npermeability of the samples, much of the signal exists at very short T<sub>2</sub> relaxation times. In \naddition, the organic content of many shales will also produce signal at short relaxation times. \nDespite recent improvements in low-field technology, limitations still exist that make it difficult \nto account for all hydrogen-rich constituents in very tight rocks, such as shales. The short pulses \nand dead times along with stronger gradients available when using high-field NMR equipment \nprovides a more complete measurement of hydrogen-bearing phases due to the ability to probe \nshorter T<sub>2</sub> relaxation times (<10<sup>-5</sup>\n sec) than can be examined using low-field equipment. Access \nto these shorter T<sub>2</sub> times allows for confirmation of partially resolved peaks observed in low-field \nNMR data that have been attributed to solid organic phases in oil shales. High-field (300 MHz or \n7 T) NMR measurements of spin-spin T<sub>2</sub> and spin-lattice T<sub>1</sub> magnetic relaxation of raw and \nartificially matured oil shales have potential to provide data complementary to low field (2 MHz \nor 0.05T) measurements. Measurements of high-field T<sub>2</sub> and T<sub>1</sub>-T<sub>2</sub> correlations are presented. \nThese data can be interpreted in terms of organic matter phases and mineral-bound water known \nto be present in the shale samples, as confirmed by Fourier transform infrared spectroscopy, and \nshow distributions of hydrogen-bearing phases present in the shales that are similar to those \nobserved in low field measurements.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings: International Symposium of the Society of Core Analysts","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"Society of Core Analysts","usgsCitation":"Seymour, J.D., Washburn, K.E., Kirkland, C.M., Vogt, S.J., Birdwell, J.E., and Codd, S.L., 2013, NMR measurement of oil shale magnetic relaxation at high magnetic field, <i>in</i> Proceedings: International Symposium of the Society of Core Analysts, 6 p.","productDescription":"6 p.","numberOfPages":"6","ipdsId":"IP-045781","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":287667,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":287665,"type":{"id":15,"text":"Index Page"},"url":"https://www.scaweb.org/symposium_2013_proceedings.shtml"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5387056fe4b0aa26cd7b53d8","contributors":{"authors":[{"text":"Seymour, Joseph D.","contributorId":59353,"corporation":false,"usgs":true,"family":"Seymour","given":"Joseph","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":489344,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Washburn, Kathryn E.","contributorId":76644,"corporation":false,"usgs":false,"family":"Washburn","given":"Kathryn","email":"","middleInitial":"E.","affiliations":[{"id":7152,"text":"Weatherford International","active":true,"usgs":false}],"preferred":false,"id":489347,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kirkland, Catherine M.","contributorId":67414,"corporation":false,"usgs":true,"family":"Kirkland","given":"Catherine","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":489345,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vogt, Sarah J.","contributorId":86267,"corporation":false,"usgs":true,"family":"Vogt","given":"Sarah","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":489348,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Birdwell, Justin E. 0000-0001-8263-1452 jbirdwell@usgs.gov","orcid":"https://orcid.org/0000-0001-8263-1452","contributorId":3302,"corporation":false,"usgs":true,"family":"Birdwell","given":"Justin","email":"jbirdwell@usgs.gov","middleInitial":"E.","affiliations":[{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":489343,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Codd, Sarah L.","contributorId":70291,"corporation":false,"usgs":true,"family":"Codd","given":"Sarah","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":489346,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70171010,"text":"70171010 - 2013 - Evaluation of near-critical overdamping effects in slug-test response","interactions":[],"lastModifiedDate":"2016-05-17T10:00:25","indexId":"70171010","displayToPublicDate":"2013-09-01T11:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3825,"text":"Groundwater","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of near-critical overdamping effects in slug-test response","docAbstract":"<p><span>A slug test behaves as a harmonic oscillator, subject to both inertial effects and viscous damping. When viscous and inertial forces are closely balanced, the system is nearly critically damped, and water-level recovery is affected by inertial effects, but does not exhibit oscillation. These effects were investigated by use of type curves, generated both by modification of Kipp's (1985) computer program and by use of the Butler-Zhan (2004) model. Utility of the type curves was verified by re-analysis of the Regina slug test previously analyzed by Kipp. These type curves indicate that near-critical inertial effects result in early-time delayed water-level response followed by merger with, or more rapid recovery than, response for the fully damped case. Because of this early time response, slug tests in the moderately over-damped range are best analyzed using log-log type curves of (1 &minus;</span><i>&nbsp;H</i><span>/</span><i>H</i><span>0</span><span>) vs.&nbsp;</span><i>Tt</i><span>/</span><img class=\"inlineGraphic\" src=\"http://api.onlinelibrary.wiley.com/asset/v1/doi/10.1111%2Fj.1745-6584.2012.01012.x/asset/equation%2Fgwat1012_mu1.gif?l=j6%2BNsqLlmq%2FmQfl1QGCE0TaRAkVTmoGxSAOc7sP4TM8tzsNQHl4l6HUmaFRwikEHj%2FVqSi8TVqIp%0AG7%2FBJIqfj6bnXKtCVPNm\" alt=\"inline image\" /><span>. Failure to recognize inertial effects in slug test data could result in an over-estimate of transmissivity, and a too-small estimate of storage coefficient or too-large estimate of well skin. However, application of the widely used but highly empirical Hvorslev (1951) method to analyze both the Regina slug test and type-curve generated data indicate that such analyses provide&nbsp;</span><i>T</i><span>&nbsp;values within a factor of 2 of the true value.</span></p>","language":"English","publisher":"State Water Control Board","publisherLocation":"Richmond, VA","doi":"10.1111/j.1745-6584.2012.01012.x","usgsCitation":"Weeks, E.P., and Clark, A.C., 2013, Evaluation of near-critical overdamping effects in slug-test response: Groundwater, v. 51, no. 5, p. 775-780, https://doi.org/10.1111/j.1745-6584.2012.01012.x.","productDescription":"6 p.","startPage":"775","endPage":"780","numberOfPages":"6","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-034442","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":321279,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"51","issue":"5","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2012-11-19","publicationStatus":"PW","scienceBaseUri":"574d64fde4b07e28b6683dee","contributors":{"authors":[{"text":"Weeks, Edwin P. epweeks@usgs.gov","contributorId":2576,"corporation":false,"usgs":true,"family":"Weeks","given":"Edwin","email":"epweeks@usgs.gov","middleInitial":"P.","affiliations":[],"preferred":true,"id":629524,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Clark, Arthur C. aclark@usgs.gov","contributorId":2320,"corporation":false,"usgs":true,"family":"Clark","given":"Arthur","email":"aclark@usgs.gov","middleInitial":"C.","affiliations":[],"preferred":true,"id":629523,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70046791,"text":"70046791 - 2013 - Effects of error covariance structure on estimation of model averaging weights and predictive performance","interactions":[],"lastModifiedDate":"2018-02-04T13:30:51","indexId":"70046791","displayToPublicDate":"2013-09-01T10:24:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Effects of error covariance structure on estimation of model averaging weights and predictive performance","docAbstract":"When conducting model averaging for assessing groundwater conceptual model uncertainty, the averaging weights are often evaluated using model selection criteria such as AIC, AICc, BIC, and KIC (Akaike Information Criterion, Corrected Akaike Information Criterion, Bayesian Information Criterion, and Kashyap Information Criterion, respectively). However, this method often leads to an unrealistic situation in which the best model receives overwhelmingly large averaging weight (close to 100%), which cannot be justified by available data and knowledge. It was found in this study that this problem was caused by using the covariance matrix, C<sub>E</sub>, of measurement errors for estimating the negative log likelihood function common to all the model selection criteria. This problem can be resolved by using the covariance matrix, C<sub>ek</sub>, of total errors (including model errors and measurement errors) to account for the correlation between the total errors. An iterative two-stage method was developed in the context of maximum likelihood inverse modeling to iteratively infer the unknown C<sub>ek</sub> from the residuals during model calibration. The inferred C<sub>ek</sub> was then used in the evaluation of model selection criteria and model averaging weights. While this method was limited to serial data using time series techniques in this study, it can be extended to spatial data using geostatistical techniques. The method was first evaluated in a synthetic study and then applied to an experimental study, in which alternative surface complexation models were developed to simulate column experiments of uranium reactive transport. It was found that the total errors of the alternative models were temporally correlated due to the model errors. The iterative two-stage method using C<sub>ek</sub>resolved the problem that the best model receives 100% model averaging weight, and the resulting model averaging weights were supported by the calibration results and physical understanding of the alternative models. Using C<sub>ek</sub> obtained from the iterative two-stage method also improved predictive performance of the individual models and model averaging in both synthetic and experimental studies.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Water Resource Reseach","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1002/wrcr.20441","usgsCitation":"Lu, D., Ye, M., Meyer, P., Curtis, G.P., Shi, X., Niu, X., and Yabusaki, S.B., 2013, Effects of error covariance structure on estimation of model averaging weights and predictive performance: Water Resources Research, v. 49, no. 9, p. 6029-6047, https://doi.org/10.1002/wrcr.20441.","productDescription":"19 p.","startPage":"6029","endPage":"6047","numberOfPages":"19","ipdsId":"IP-048964","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":473568,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/wrcr.20441","text":"Publisher Index Page"},{"id":278963,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":278962,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/wrcr.20441"}],"volume":"49","issue":"9","noUsgsAuthors":false,"publicationDate":"2013-09-24","publicationStatus":"PW","scienceBaseUri":"527e5869e4b02d2057dd95d5","contributors":{"authors":[{"text":"Lu, Dan","contributorId":58176,"corporation":false,"usgs":true,"family":"Lu","given":"Dan","affiliations":[],"preferred":false,"id":480264,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ye, Ming","contributorId":70276,"corporation":false,"usgs":true,"family":"Ye","given":"Ming","affiliations":[],"preferred":false,"id":480266,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Meyer, Philip D.","contributorId":6363,"corporation":false,"usgs":true,"family":"Meyer","given":"Philip D.","affiliations":[],"preferred":false,"id":480261,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Curtis, Gary P. 0000-0003-3975-8882 gpcurtis@usgs.gov","orcid":"https://orcid.org/0000-0003-3975-8882","contributorId":2346,"corporation":false,"usgs":true,"family":"Curtis","given":"Gary","email":"gpcurtis@usgs.gov","middleInitial":"P.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":480260,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Shi, Xiaoqing","contributorId":54102,"corporation":false,"usgs":true,"family":"Shi","given":"Xiaoqing","affiliations":[],"preferred":false,"id":480263,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Niu, Xu-Feng","contributorId":68639,"corporation":false,"usgs":true,"family":"Niu","given":"Xu-Feng","email":"","affiliations":[],"preferred":false,"id":480265,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Yabusaki, Steve B.","contributorId":26961,"corporation":false,"usgs":true,"family":"Yabusaki","given":"Steve","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":480262,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70101027,"text":"70101027 - 2013 - Geographic variation in migration chronology and winter distribution of midcontinent greater white-fronted geese","interactions":[],"lastModifiedDate":"2014-04-09T10:40:18","indexId":"70101027","displayToPublicDate":"2013-09-01T10:22:56","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Geographic variation in migration chronology and winter distribution of midcontinent greater white-fronted geese","docAbstract":"We evaluated spatial and temporal differences in migratory behavior among different breeding groups of midcontinent greater white-fronted geese (Anser albifrons) using band-recovery data and observations of neck collared geese during migration and winter. Birds from different breeding areas were initially delineated by geographic distance into 6 banding reference areas (BRAs): 1) interior Alaska, 2) North Slope of Alaska, 3) western Northwest Territories (NWT), 4) western Nunavut, 5) central Nunavut, and 6) eastern Nunavut. The banding groups also differed by breeding habitat, with geese from interior Alaska nesting in the boreal forest (taiga), and all other groups breeding in tundra habitats. Geese from interior Alaska migrated earlier during autumn, and were more likely to winter farther south (in Mexico) than geese from other breeding areas. Geese banded in central and eastern Nunavut (Queen Maud Gulf and Inglis River) wintered farther east (in Louisiana) than geese from other breeding areas. Small-scale (within-state) geographic segregation of wintering flocks was evidenced by the recent (post-1990) nearly exclusive use of a new wintering area in north central Texas by geese from interior Alaska. Segregation among BRAs was also apparent in Mexico, where taiga geese were found predominantly in the central Highlands (states of Zacatecas and Durango), whereas tundra geese mostly used states along the Gulf Coast (primarily Tamaulipas). Interior Alaska birds initiated spring migration earlier than geese from other areas, and were more likely than others to stop in the Rainwater Basin of Nebraska, a region where cholera outbreaks periodically kill thousands of geese. Geese from interior Alaska were the first to arrive at spring staging areas in prairie Canada where BRAs exhibited spatial delineation (a longitudinal cline) in relation to breeding areas. Our results show significant geographic and temporal variation among taiga and tundra breeding cohorts during autumn, winter, and spring. Temporal and spatial differences in migratory behavior may allow management practices that accommodate potential demographic differences between taiga and tundra populations.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Wildlife Management","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1002/jwmg.573","usgsCitation":"Ely, C.R., Nieman, D.J., Alisauskas, R., Schmutz, J.A., and Hines, J., 2013, Geographic variation in migration chronology and winter distribution of midcontinent greater white-fronted geese: Journal of Wildlife Management, v. 77, no. 6, p. 1182-1191, https://doi.org/10.1002/jwmg.573.","productDescription":"10 p.","startPage":"1182","endPage":"1191","ipdsId":"IP-026808","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"links":[{"id":473569,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://zenodo.org/record/1229275","text":"External Repository"},{"id":285913,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/jwmg.573"},{"id":285946,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada;Mexico;United States","volume":"77","issue":"6","noUsgsAuthors":false,"publicationDate":"2013-07-01","publicationStatus":"PW","scienceBaseUri":"5355943ce4b0120853e8bfa0","contributors":{"authors":[{"text":"Ely, Craig R. 0000-0003-4262-0892 cely@usgs.gov","orcid":"https://orcid.org/0000-0003-4262-0892","contributorId":3214,"corporation":false,"usgs":true,"family":"Ely","given":"Craig","email":"cely@usgs.gov","middleInitial":"R.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":492549,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nieman, Daniel J.","contributorId":22681,"corporation":false,"usgs":true,"family":"Nieman","given":"Daniel","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":492552,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Alisauskas, Ray T.","contributorId":20883,"corporation":false,"usgs":true,"family":"Alisauskas","given":"Ray T.","affiliations":[],"preferred":false,"id":492551,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schmutz, Joel A. 0000-0002-6516-0836 jschmutz@usgs.gov","orcid":"https://orcid.org/0000-0002-6516-0836","contributorId":1805,"corporation":false,"usgs":true,"family":"Schmutz","given":"Joel","email":"jschmutz@usgs.gov","middleInitial":"A.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":492548,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hines, James E. jhines@usgs.gov","contributorId":3506,"corporation":false,"usgs":true,"family":"Hines","given":"James E.","email":"jhines@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":492550,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70048258,"text":"70048258 - 2013 - The importance of record length in estimating the magnitude of climatic changes: an example using 175 years of lake ice-out dates in New England","interactions":[],"lastModifiedDate":"2019-04-09T13:39:20","indexId":"70048258","displayToPublicDate":"2013-09-01T10:02:29","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1252,"text":"Climatic Change","active":true,"publicationSubtype":{"id":10}},"title":"The importance of record length in estimating the magnitude of climatic changes: an example using 175 years of lake ice-out dates in New England","docAbstract":"Many studies have shown that lake ice-out (break-up) dates in the Northern Hemisphere are useful indicators of late winter/early spring climate change. Trends in lake ice-out dates in New England, USA, were analyzed for 25, 50, 75, 100, 125, 150, and 175 year periods ending in 2008. More than 100 years of ice-out data were available for 19 of the 28 lakes in this study. The magnitude of trends over time depends on the length of the period considered. For the recent 25-year period, there was a mix of earlier and later ice-out dates. Lake ice-outs during the last 50 years became earlier by 1.8 days/decade (median change for all lakes with adequate data). This is a much higher rate than for longer historical periods; ice-outs became earlier by 0.6 days/decade during the last 75 years, 0.4 days/ decade during the last 100 years, and 0.6 days/decade during the last 125 years. The significance of trends was assessed under the assumption of serial independence of historical ice-out dates and under the assumption of short and long term persistence. Hypolimnion dissolved oxygen (DO) levels are an important factor in lake eutrophication and coldwater fish survival. Based on historical data available at three lakes, 32 to 46 % of the interannual variability of late summer hypolimnion DO levels was related to ice-out dates; earlier ice-outs were associated with lower DO levels.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Climatic Change","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","doi":"10.1007/s10584-013-0766-8","usgsCitation":"Hodgkins, G.A., 2013, The importance of record length in estimating the magnitude of climatic changes: an example using 175 years of lake ice-out dates in New England: Climatic Change, v. 119, p. 705-718, https://doi.org/10.1007/s10584-013-0766-8.","productDescription":"14 p.","startPage":"705","endPage":"718","ipdsId":"IP-015081","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":277957,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":277956,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s10584-013-0766-8"}],"country":"United States","state":"Maine;Massachusetts;New Hampshire;Rhode Island","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -74.28955078125,\n              40.93011520598305\n            ],\n            [\n              -66.5771484375,\n              40.93011520598305\n            ],\n            [\n              -66.5771484375,\n              47.635783590864854\n            ],\n            [\n              -74.28955078125,\n              47.635783590864854\n            ],\n            [\n              -74.28955078125,\n              40.93011520598305\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"119","noUsgsAuthors":false,"publicationDate":"2013-05-24","publicationStatus":"PW","scienceBaseUri":"523d6e69e4b097188d6c7713","contributors":{"authors":[{"text":"Hodgkins, Glenn A. 0000-0002-4916-5565 gahodgki@usgs.gov","orcid":"https://orcid.org/0000-0002-4916-5565","contributorId":2020,"corporation":false,"usgs":true,"family":"Hodgkins","given":"Glenn","email":"gahodgki@usgs.gov","middleInitial":"A.","affiliations":[{"id":371,"text":"Maine Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":484202,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70048054,"text":"70048054 - 2013 - Melts of garnet lherzolite: experiments, models and comparison to melts of pyroxenite and carbonated lherzolite","interactions":[],"lastModifiedDate":"2013-09-10T10:00:24","indexId":"70048054","displayToPublicDate":"2013-09-01T09:52:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1336,"text":"Contributions to Mineralogy and Petrology","active":true,"publicationSubtype":{"id":10}},"title":"Melts of garnet lherzolite: experiments, models and comparison to melts of pyroxenite and carbonated lherzolite","docAbstract":"Phase equilibrium experiments on a compositionally modified olivine leucitite from the Tibetan plateau have been carried out from 2.2 to 2.8 GPa and 1,380–1,480 °C. The experiments-produced liquids multiply saturated with spinel and garnet lherzolite phase assemblages (olivine, orthopyroxene, clinopyroxene and spinel ± garnet) under nominally anhydrous conditions. These SiO<sub>2</sub>-undersaturated liquids and published experimental data are utilized to develop a predictive model for garnet lherzolite melting of compositionally variable mantle under anhydrous conditions over the pressure range of 1.9–6 GPa. The model estimates the major element compositions of garnet-saturated melts for a range of mantle lherzolite compositions and predicts the conditions of the spinel to garnet lherzolite phase transition for natural peridotite compositions at above-solidus temperatures and pressures. We compare our predicted garnet lherzolite melts to those of pyroxenite and carbonated lherzolite and develop criteria for distinguishing among melts of these different source types. We also use the model in conjunction with a published predictive model for plagioclase and spinel lherzolite to characterize the differences in major element composition for melts in the plagioclase, spinel and garnet facies and develop tests to distinguish between melts of these three lherzolite facies based on major elements. The model is applied to understand the source materials and conditions of melting for high-K lavas erupted in the Tibetan plateau, basanite–nephelinite lavas erupted early in the evolution of Kilauea volcano, Hawaii, as well as younger tholeiitic to alkali lavas from Kilauea.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Contributions to Mineralogy and Petrology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","doi":"10.1007/s00410-013-0899-9","usgsCitation":"Grove, T., Holbig, E.S., Barr, J.A., Till, C.B., and Krawczynski, M., 2013, Melts of garnet lherzolite: experiments, models and comparison to melts of pyroxenite and carbonated lherzolite: Contributions to Mineralogy and Petrology, v. 166, no. 3, p. 887-910, https://doi.org/10.1007/s00410-013-0899-9.","productDescription":"24 p.","startPage":"887","endPage":"910","numberOfPages":"24","ipdsId":"IP-046062","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":473573,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/1721.1/103411","text":"External Repository"},{"id":277442,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":277412,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s00410-013-0899-9"}],"volume":"166","issue":"3","noUsgsAuthors":false,"publicationDate":"2013-08-22","publicationStatus":"PW","scienceBaseUri":"52303f64e4b04b8e63a2064b","contributors":{"authors":[{"text":"Grove, Timothy L.","contributorId":68546,"corporation":false,"usgs":true,"family":"Grove","given":"Timothy L.","affiliations":[],"preferred":false,"id":483672,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Holbig, Eva S.","contributorId":62511,"corporation":false,"usgs":true,"family":"Holbig","given":"Eva","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":483671,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barr, Jay A.","contributorId":95371,"corporation":false,"usgs":true,"family":"Barr","given":"Jay","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":483674,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Till, Christy B. cbtill@usgs.gov","contributorId":4394,"corporation":false,"usgs":true,"family":"Till","given":"Christy","email":"cbtill@usgs.gov","middleInitial":"B.","affiliations":[],"preferred":true,"id":483670,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Krawczynski, Michael J.","contributorId":75425,"corporation":false,"usgs":true,"family":"Krawczynski","given":"Michael J.","affiliations":[],"preferred":false,"id":483673,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70094676,"text":"70094676 - 2013 - Integrated geophysical imaging of a concealed mineral deposit: a case study of the world-class Pebble porphyry deposit in southwestern Alaska","interactions":[],"lastModifiedDate":"2014-02-24T09:53:49","indexId":"70094676","displayToPublicDate":"2013-09-01T09:48:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1808,"text":"Geophysics","active":true,"publicationSubtype":{"id":10}},"title":"Integrated geophysical imaging of a concealed mineral deposit: a case study of the world-class Pebble porphyry deposit in southwestern Alaska","docAbstract":"We combined aeromagnetic, induced polarization, magnetotelluric, and gravity surveys as well as drillhole geologic, alteration, magnetic susceptibility, and density data for exploration and characterization of the Cu-Au-Mo Pebble porphyry deposit. This undeveloped deposit is almost completely concealed by postmineralization sedimentary and volcanic rocks, presenting an exploration challenge. Individual geophysical methods primarily assist regional characterization. Positive chargeability and conductivity anomalies are observed over a broad region surrounding the deposit, likely representing sulfide minerals that accumulated during multiple stages of hydrothermal alteration. The mineralized area occupies only a small part of the chargeability anomaly because sulfide precipitation was not unique to the deposit, and mafic rocks also exhibit strong chargeability. Conductivity anomalies similarly reflect widespread sulfides as well as water-saturated glacial sediments. Mineralogical and magnetic susceptibility data indicate magnetite destruction primarily within the Cu-Au-Mo mineralized area. The magnetic field does not show a corresponding anomaly low but the analytic signal does in areas where the deposit is not covered by postmineralization igneous rocks. The analytic signal shows similar lows over sedimentary rocks outside of the mineralized area, however, and cannot uniquely distinguish the deposit. We find that the intersection of positive chargeability anomalies with analytic signal lows, indicating elevated sulfide concentrations but low magnetite at shallow depths, roughly delineates the deposit where it is covered only by glacial sediments. Neither chargeability highs nor analytic signal lows are present where the deposit is covered by several hundred meters of sedimentary and volcanic rocks, but a 3D resistivity model derived from magnetotelluric data shows a corresponding zone of higher conductivity. Gravity data highlight geologic features within the deposit, including shallow diorite sills that locally contain higher-grade mineralization. The results thus show ways in which an integrated survey approach might be used to distinguish zones of potentially economic mineralization.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Geophysics","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Society of Exploration Geophysicists","doi":"10.1190/geo2013-0046.1","usgsCitation":"Shah, A.K., Bedrosian, P.A., Anderson, E.D., Kelley, K., and Lang, J., 2013, Integrated geophysical imaging of a concealed mineral deposit: a case study of the world-class Pebble porphyry deposit in southwestern Alaska: Geophysics, v. 78, no. 5, p. 317-328, https://doi.org/10.1190/geo2013-0046.1.","productDescription":"12 p.","startPage":"317","endPage":"328","numberOfPages":"12","ipdsId":"IP-043864","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":282665,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":282664,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1190/geo2013-0046.1"}],"country":"United States","state":"Alaska","otherGeospatial":"Kahiltna Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -158.0,59.0 ], [ -158.0,61.0 ], [ -154.0,61.0 ], [ -154.0,59.0 ], [ -158.0,59.0 ] ] ] } } ] }","volume":"78","issue":"5","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd62b0e4b0b290850fe596","contributors":{"authors":[{"text":"Shah, Anjana K. 0000-0002-3198-081X ashah@usgs.gov","orcid":"https://orcid.org/0000-0002-3198-081X","contributorId":2297,"corporation":false,"usgs":true,"family":"Shah","given":"Anjana","email":"ashah@usgs.gov","middleInitial":"K.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":490799,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bedrosian, Paul A. 0000-0002-6786-1038 pbedrosian@usgs.gov","orcid":"https://orcid.org/0000-0002-6786-1038","contributorId":839,"corporation":false,"usgs":true,"family":"Bedrosian","given":"Paul","email":"pbedrosian@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":490797,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anderson, Eric D. 0000-0002-0138-6166 ericanderson@usgs.gov","orcid":"https://orcid.org/0000-0002-0138-6166","contributorId":1733,"corporation":false,"usgs":true,"family":"Anderson","given":"Eric","email":"ericanderson@usgs.gov","middleInitial":"D.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":490798,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kelley, Karen D. 0000-0002-3232-5809","orcid":"https://orcid.org/0000-0002-3232-5809","contributorId":57817,"corporation":false,"usgs":true,"family":"Kelley","given":"Karen D.","affiliations":[],"preferred":false,"id":490801,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lang, James","contributorId":15931,"corporation":false,"usgs":true,"family":"Lang","given":"James","affiliations":[],"preferred":false,"id":490800,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70104148,"text":"70104148 - 2013 - Environmental fate of fungicides and other current-use pesticides in a central California estuary","interactions":[],"lastModifiedDate":"2014-05-12T09:46:19","indexId":"70104148","displayToPublicDate":"2013-09-01T09:30:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2676,"text":"Marine Pollution Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"Environmental fate of fungicides and other current-use pesticides in a central California estuary","docAbstract":"The current study documents the fate of current-use pesticides in an agriculturally-dominated central California coastal estuary by focusing on the occurrence in water, sediment and tissue of resident aquatic organisms. Three fungicides (azoxystrobin, boscalid, and pyraclostrobin), one herbicide (propyzamide) and two organophosphate insecticides (chlorpyrifos and diazinon) were detected frequently. Dissolved pesticide concentrations in the estuary corresponded to the timing of application while bed sediment pesticide concentrations correlated with the distance from potential sources. Fungicides and insecticides were detected frequently in fish and invertebrates collected near the mouth of the estuary and the contaminant profiles differed from the sediment and water collected. This is the first study to document the occurrence of many current-use pesticides, including fungicides, in tissue. Limited information is available on the uptake, accumulation and effects of current-use pesticides on non-target organisms. Additional data are needed to understand the impacts of pesticides, especially in small agriculturally-dominated estuaries.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Marine Pollution Bulletin","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.marpolbul.2013.05.028","usgsCitation":"Smalling, K., Kuivila, K., Orlando, J., Phillips, B.M., Anderson, B.S., Siegler, K., Hunt, J.W., and Hamilton, M., 2013, Environmental fate of fungicides and other current-use pesticides in a central California estuary: Marine Pollution Bulletin, v. 73, no. 1, p. 144-153, https://doi.org/10.1016/j.marpolbul.2013.05.028.","productDescription":"10 p.","startPage":"144","endPage":"153","numberOfPages":"10","ipdsId":"IP-043831","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":287046,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":287045,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.marpolbul.2013.05.028"}],"country":"United States","state":"California","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -120.7961,34.4986 ], [ -120.7961,35.0952 ], [ -119.3953,35.0952 ], [ -119.3953,34.4986 ], [ -120.7961,34.4986 ] ] ] } } ] }","volume":"73","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5371ed70e4b0844954788413","contributors":{"authors":[{"text":"Smalling, Kelly L.","contributorId":16105,"corporation":false,"usgs":true,"family":"Smalling","given":"Kelly L.","affiliations":[],"preferred":false,"id":493566,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kuivila, Kathryn  0000-0001-7940-489X kkuivila@usgs.gov","orcid":"https://orcid.org/0000-0001-7940-489X","contributorId":1367,"corporation":false,"usgs":true,"family":"Kuivila","given":"Kathryn ","email":"kkuivila@usgs.gov","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":false,"id":493565,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Orlando, James L. 0000-0002-0099-7221","orcid":"https://orcid.org/0000-0002-0099-7221","contributorId":95954,"corporation":false,"usgs":true,"family":"Orlando","given":"James L.","affiliations":[],"preferred":false,"id":493572,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Phillips, Bryn M.","contributorId":77053,"corporation":false,"usgs":true,"family":"Phillips","given":"Bryn","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":493570,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Anderson, Brian S.","contributorId":42882,"corporation":false,"usgs":true,"family":"Anderson","given":"Brian","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":493567,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Siegler, Katie","contributorId":54893,"corporation":false,"usgs":true,"family":"Siegler","given":"Katie","email":"","affiliations":[],"preferred":false,"id":493569,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hunt, John W.","contributorId":50445,"corporation":false,"usgs":true,"family":"Hunt","given":"John","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":493568,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hamilton, Mary","contributorId":86696,"corporation":false,"usgs":true,"family":"Hamilton","given":"Mary","email":"","affiliations":[],"preferred":false,"id":493571,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70074635,"text":"70074635 - 2013 - Recent land-use/land-cover change in the Central California Valley","interactions":[],"lastModifiedDate":"2014-01-31T09:33:11","indexId":"70074635","displayToPublicDate":"2013-09-01T09:22:30","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2367,"text":"Journal of Land Use Science","active":true,"publicationSubtype":{"id":10}},"title":"Recent land-use/land-cover change in the Central California Valley","docAbstract":"Open access to Landsat satellite data has enabled annual analyses of modern land-use and land-cover change (LULCC) for the Central California Valley ecoregion between 2005 and 2010. Our annual LULCC estimates capture landscape-level responses to water policy changes, climate, and economic instability. From 2005 to 2010, agriculture in the region fluctuated along with regulatory-driven changes in water allocation as well as persistent drought conditions. Grasslands and shrublands declined, while developed lands increased in former agricultural and grassland/shrublands. Development rates stagnated in 2007, coinciding with the onset of the historic foreclosure crisis in California and the global economic downturn. We utilized annual LULCC estimates to generate interval-based LULCC estimates (2000–2005 and 2005–2010) and extend existing 27 year interval-based land change monitoring through 2010. Resulting change data provides insights into the drivers of landscape change in the Central California Valley ecoregion and represents the first, continuous, 37 year mapping effort of its kind.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Land Use Science","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Taylor & Francis","doi":"10.1080/1747423X.2013.841297","usgsCitation":"Soulard, C.E., and Wilson, T.S., 2013, Recent land-use/land-cover change in the Central California Valley: Journal of Land Use Science, 22 p., https://doi.org/10.1080/1747423X.2013.841297.","productDescription":"22 p.","ipdsId":"IP-041215","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":473576,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/1747423x.2013.841297","text":"Publisher Index Page"},{"id":281791,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":281790,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1080/1747423X.2013.841297"}],"country":"United States","state":"California","otherGeospatial":"Central California Valley","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -121.62,34.86 ], [ -121.62,39.22 ], [ -119.18,39.22 ], [ -119.18,34.86 ], [ -121.62,34.86 ] ] ] } } ] }","noUsgsAuthors":false,"publicationDate":"2013-09-25","publicationStatus":"PW","scienceBaseUri":"53cd6f50e4b0b29085106578","contributors":{"authors":[{"text":"Soulard, Christopher E. 0000-0002-5777-9516 csoulard@usgs.gov","orcid":"https://orcid.org/0000-0002-5777-9516","contributorId":2642,"corporation":false,"usgs":true,"family":"Soulard","given":"Christopher","email":"csoulard@usgs.gov","middleInitial":"E.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":489618,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wilson, Tamara S.","contributorId":36640,"corporation":false,"usgs":true,"family":"Wilson","given":"Tamara","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":489619,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70128147,"text":"70128147 - 2013 - Projecting demographic responses to climate change: adult and juvenile survival respond differently to direct and indirect effects of weather in a passerine population","interactions":[],"lastModifiedDate":"2014-10-07T09:22:14","indexId":"70128147","displayToPublicDate":"2013-09-01T09:20:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"Projecting demographic responses to climate change: adult and juvenile survival respond differently to direct and indirect effects of weather in a passerine population","docAbstract":"Few studies have quantitatively projected changes in demography in response to climate change, yet doing so can provide important insights into the processes that may lead to population declines and changes in species distributions. Using a long-term mark-recapture data set, we examined the influence of multiple direct and indirect effects of weather on adult and juvenile survival for a population of Song Sparrows (Melospiza melodia) in California. We found evidence for a positive, direct effect of winter temperature on adult survival, and a positive, indirect effect of prior rainy season precipitation on juvenile survival, which was consistent with an effect of precipitation on food availability during the breeding season. We used these relationships, and climate projections of significantly warmer and slightly drier winter weather by the year 2100, to project a significant increase in mean adult survival (12-17%) and a slight decrease in mean juvenile survival (4-6%) under the B1 and A2 climate change scenarios. Together with results from previous studies on seasonal fecundity and postfledging survival in this population, we integrated these results in a population model and projected increases in the population growth rate under both climate change scenarios. Our results underscore the importance of considering multiple, direct, and indirect effects of weather throughout the annual cycle, as well as differences in the responses of each life stage to climate change. Projecting demographic responses to climate change can identify not only how populations will be affected by climate change but also indicate the demographic process(es) and specific mechanisms that may be responsible. This information can, in turn, inform climate change adaptation plans, help prioritize future research, and identify where limited conservation resources will be most effectively and efficiently spent.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Global Change Biology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Blackwell Science","publisherLocation":"Oxford, England","doi":"10.1111/gcb.12228","usgsCitation":"Dybala, K.E., Eadie, J.M., Gardali, T., Seavy, N.E., and Herzog, M., 2013, Projecting demographic responses to climate change: adult and juvenile survival respond differently to direct and indirect effects of weather in a passerine population: Global Change Biology, v. 19, no. 9, p. 2688-2697, https://doi.org/10.1111/gcb.12228.","productDescription":"10 p.","startPage":"2688","endPage":"2697","numberOfPages":"10","ipdsId":"IP-037635","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":294976,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":294952,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/gcb.12228"}],"country":"United States","state":"California","volume":"19","issue":"9","noUsgsAuthors":false,"publicationDate":"2013-07-15","publicationStatus":"PW","scienceBaseUri":"543500b6e4b0a4f4b46a23c2","contributors":{"authors":[{"text":"Dybala, Kristen E.","contributorId":64168,"corporation":false,"usgs":true,"family":"Dybala","given":"Kristen","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":502775,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Eadie, John M.","contributorId":34067,"corporation":false,"usgs":false,"family":"Eadie","given":"John","email":"","middleInitial":"M.","affiliations":[{"id":6961,"text":"Department of Wildlife, Fish & Conservation Biology, University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":502773,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gardali, Thomas","contributorId":10356,"corporation":false,"usgs":true,"family":"Gardali","given":"Thomas","email":"","affiliations":[],"preferred":false,"id":502772,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Seavy, Nathaniel E.","contributorId":58964,"corporation":false,"usgs":true,"family":"Seavy","given":"Nathaniel","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":502774,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Herzog, Mark P. mherzog@usgs.gov","contributorId":3965,"corporation":false,"usgs":true,"family":"Herzog","given":"Mark P.","email":"mherzog@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":502771,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70095255,"text":"70095255 - 2013 - A generalized Grubbs-Beck test statistic for detecting multiple potentially influential low outliers in flood series","interactions":[],"lastModifiedDate":"2014-03-04T08:17:54","indexId":"70095255","displayToPublicDate":"2013-09-01T08:13:52","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"A generalized Grubbs-Beck test statistic for detecting multiple potentially influential low outliers in flood series","docAbstract":"he Grubbs-Beck test is recommended by the federal guidelines for detection of low outliers in flood flow frequency computation in the United States. This paper presents a generalization of the Grubbs-Beck test for normal data (similar to the Rosner (1983) test; see also Spencer and McCuen (1996)) that can provide a consistent standard for identifying multiple potentially influential low flows. In cases where low outliers have been identified, they can be represented as “less-than” values, and a frequency distribution can be developed using censored-data statistical techniques, such as the Expected Moments Algorithm. This approach can improve the fit of the right-hand tail of a frequency distribution and provide protection from lack-of-fit due to unimportant but potentially influential low flows (PILFs) in a flood series, thus making the flood frequency analysis procedure more robust.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Water Resources Research","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1002/wrcr.20392","usgsCitation":"Cohn, T., England, J., Berenbrock, C., Mason, R., Stedinger, J., and Lamontagne, J., 2013, A generalized Grubbs-Beck test statistic for detecting multiple potentially influential low outliers in flood series: Water Resources Research, v. 49, no. 8, p. 5047-5058, https://doi.org/10.1002/wrcr.20392.","productDescription":"12 p.","startPage":"5047","endPage":"5058","ipdsId":"IP-042563","costCenters":[{"id":629,"text":"Water Resources Division","active":false,"usgs":true}],"links":[{"id":473579,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/wrcr.20392","text":"Publisher Index Page"},{"id":283198,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":283197,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/wrcr.20392"}],"volume":"49","issue":"8","noUsgsAuthors":false,"publicationDate":"2013-08-19","publicationStatus":"PW","scienceBaseUri":"53cd49dae4b0b290850ef6be","contributors":{"authors":[{"text":"Cohn, T.A.","contributorId":84789,"corporation":false,"usgs":true,"family":"Cohn","given":"T.A.","email":"","affiliations":[],"preferred":false,"id":491161,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"England, J.F.","contributorId":47687,"corporation":false,"usgs":true,"family":"England","given":"J.F.","affiliations":[],"preferred":false,"id":491159,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Berenbrock, C. E.","contributorId":103321,"corporation":false,"usgs":true,"family":"Berenbrock","given":"C. E.","affiliations":[],"preferred":false,"id":491163,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mason, R.R.","contributorId":34520,"corporation":false,"usgs":true,"family":"Mason","given":"R.R.","affiliations":[],"preferred":false,"id":491158,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stedinger, J.R.","contributorId":90733,"corporation":false,"usgs":true,"family":"Stedinger","given":"J.R.","affiliations":[],"preferred":false,"id":491162,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lamontagne, J.R.","contributorId":56148,"corporation":false,"usgs":true,"family":"Lamontagne","given":"J.R.","email":"","affiliations":[],"preferred":false,"id":491160,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70148139,"text":"70148139 - 2013 - A spatial capture-recapture model to estimate fish survival and location from linear continuous monitoring arrays","interactions":[],"lastModifiedDate":"2015-05-27T14:21:13","indexId":"70148139","displayToPublicDate":"2013-09-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"A spatial capture-recapture model to estimate fish survival and location from linear continuous monitoring arrays","docAbstract":"<p><span>We developed a spatial capture&ndash;recapture model to evaluate survival and activity centres (i.e., mean locations) of tagged individuals detected along a linear array. Our spatially explicit version of the Cormack&ndash;Jolly&ndash;Seber model, analyzed using a Bayesian framework, correlates movement between periods and can incorporate environmental or other covariates. We demonstrate the model using 2010 data for anadromous American shad (</span><i>Alosa sapidissima</i><span>) tagged with passive integrated transponders (PIT) at a weir near the mouth of a North Carolina river and passively monitored with an upstream array of PIT antennas. The river channel constrained migrations, resulting in linear, one-dimensional encounter histories that included both weir captures and antenna detections. Individual activity centres in a given time period were a function of the individual&rsquo;s previous estimated location and the river conditions (i.e., gage height). Model results indicate high within-river spawning mortality (mean weekly survival = 0.80) and more extensive movements during elevated river conditions. This model is applicable for any linear array (e.g., rivers, shorelines, and corridors), opening new opportunities to study demographic parameters, movement or migration, and habitat use.</span></p>","language":"English","publisher":"NRC Research Press","doi":"10.1139/cjfas-2013-0198","usgsCitation":"Raabe, J.K., Gardner, B., and Hightower, J.E., 2013, A spatial capture-recapture model to estimate fish survival and location from linear continuous monitoring arrays: Canadian Journal of Fisheries and Aquatic Sciences, v. 71, no. 1, p. 120-130, https://doi.org/10.1139/cjfas-2013-0198.","productDescription":"11 p.","startPage":"120","endPage":"130","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-044001","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":300868,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina","otherGeospatial":"Little River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -78.20686340332031,\n              35.60288130725417\n            ],\n            [\n              -78.19244384765625,\n              35.58166340367189\n            ],\n            [\n              -78.17562103271484,\n              35.572448615622804\n            ],\n            [\n              -78.16497802734375,\n              35.563512051219696\n            ],\n            [\n              -78.16978454589842,\n              35.554015859485595\n            ],\n            [\n              -78.17150115966797,\n              35.54619462154643\n            ],\n            [\n              -78.1680679321289,\n              35.538093249404184\n            ],\n            [\n              -78.17150115966797,\n              35.53166744135354\n            ],\n            [\n              -78.17081451416016,\n              35.52244690472594\n            ],\n            [\n              -78.16497802734375,\n              35.518534841844364\n            ],\n            [\n              -78.17218780517578,\n              35.515740394479316\n            ],\n            [\n              -78.17699432373047,\n              35.50847437608772\n            ],\n            [\n              -78.17047119140625,\n              35.498971667611976\n            ],\n            [\n              -78.16463470458984,\n              35.49785362799176\n            ],\n            [\n              -78.15845489501953,\n              35.50120770016921\n            ],\n            [\n              -78.15364837646484,\n              35.496456056584165\n            ],\n            [\n              -78.15502166748047,\n              35.48779057119978\n            ],\n            [\n              -78.13304901123047,\n              35.46570333507351\n            ],\n            [\n              -78.12755584716797,\n              35.46598295825904\n            ],\n            [\n              -78.11588287353516,\n              35.46290704974907\n            ],\n            [\n              -78.10386657714844,\n              35.458153141593264\n            ],\n            [\n              -78.0963134765625,\n              35.46039030983905\n            ],\n            [\n              -78.08738708496094,\n              35.4508819151422\n            ],\n            [\n              -78.06541442871094,\n              35.443050628750456\n            ],\n            [\n              -78.06129455566406,\n              35.449483527031475\n            ],\n            [\n              -78.057861328125,\n              35.449483527031475\n            ],\n            [\n              -78.05477142333984,\n              35.43913469980961\n            ],\n            [\n              -78.04378509521484,\n              35.441372396815304\n            ],\n            [\n              -78.035888671875,\n              35.44500852178629\n            ],\n            [\n              -78.03279876708984,\n              35.43913469980961\n            ],\n            [\n              -78.02799224853516,\n              35.43381992014202\n            ],\n            [\n              -78.0197525024414,\n              35.431582013221295\n            ],\n            [\n              -78.02215576171875,\n              35.42626673502823\n            ],\n            [\n              -78.0197525024414,\n              35.420111764144515\n            ],\n            [\n              -78.01116943359375,\n              35.4159149234562\n            ],\n            [\n              -78.0087661743164,\n              35.41227748469718\n            ],\n            [\n              -78.01528930664062,\n              35.41003897923532\n            ],\n            [\n              -78.02696228027344,\n              35.40724075997159\n            ],\n            [\n              -78.03314208984375,\n              35.403882768619475\n            ],\n            [\n              -78.03348541259766,\n              35.3960469114653\n            ],\n            [\n              -78.02970886230467,\n              35.38429169786879\n            ],\n            [\n              -78.02799224853516,\n              35.37981307060428\n            ],\n            [\n              -78.02936553955077,\n              35.37477431775729\n            ],\n            [\n              -78.02112579345703,\n              35.375334194722704\n            ],\n            [\n              -78.01700592041016,\n              35.380372912608856\n            ],\n            [\n              -78.01769256591797,\n              35.38653091826541\n            ],\n            [\n              -78.02043914794922,\n              35.39296833065277\n            ],\n            [\n              -78.02043914794922,\n              35.399405229214004\n            ],\n            [\n              -78.01563262939453,\n              35.40220372048504\n            ],\n            [\n              -78.00670623779297,\n              35.401644030002146\n            ],\n            [\n              -78.00636291503905,\n              35.40584161390886\n            ],\n            [\n              -78.00052642822266,\n              35.41003897923532\n            ],\n            [\n              -77.99915313720703,\n              35.423469079290605\n            ],\n            [\n              -78.01116943359375,\n              35.42486791930558\n            ],\n            [\n              -78.00945281982422,\n              35.42738577011564\n            ],\n            [\n              -78.01116943359375,\n              35.43745638623712\n            ],\n            [\n              -78.02146911621092,\n              35.44109268809115\n            ],\n            [\n              -78.02661895751953,\n              35.4433303306713\n            ],\n            [\n              -78.0307388305664,\n              35.45172093634465\n            ],\n            [\n              -78.0410385131836,\n              35.453119285575234\n            ],\n            [\n              -78.04859161376953,\n              35.447525742853344\n            ],\n            [\n              -78.05065155029297,\n              35.447805429223266\n            ],\n            [\n              -78.05065155029297,\n              35.45591591113412\n            ],\n            [\n              -78.05923461914062,\n              35.45899208697615\n            ],\n            [\n              -78.06781768798828,\n              35.458153141593264\n            ],\n            [\n              -78.07296752929688,\n              35.45591591113412\n            ],\n            [\n              -78.07193756103516,\n              35.451441263582495\n            ],\n            [\n              -78.07846069335938,\n              35.45703453414025\n            ],\n            [\n              -78.08429718017577,\n              35.458153141593264\n            ],\n            [\n              -78.0849838256836,\n              35.46710144127944\n            ],\n            [\n              -78.09219360351561,\n              35.46961797120201\n            ],\n            [\n              -78.101806640625,\n              35.46849952318069\n            ],\n            [\n              -78.10626983642578,\n              35.46626258047241\n            ],\n            [\n              -78.10970306396484,\n              35.46794029333679\n            ],\n            [\n              -78.11141967773438,\n              35.476048745444416\n            ],\n            [\n              -78.11965942382812,\n              35.47800583551617\n            ],\n            [\n              -78.12137603759766,\n              35.474371201749165\n            ],\n            [\n              -78.12755584716797,\n              35.47660791889787\n            ],\n            [\n              -78.13133239746094,\n              35.47660791889787\n            ],\n            [\n              -78.14609527587889,\n              35.488629207403235\n            ],\n            [\n              -78.1467819213867,\n              35.49925117508564\n            ],\n            [\n              -78.14952850341797,\n              35.506238545834904\n            ],\n            [\n              -78.15467834472655,\n              35.50987173838399\n            ],\n            [\n              -78.15467834472655,\n              35.51825540148536\n            ],\n            [\n              -78.16154479980469,\n              35.528594046864725\n            ],\n            [\n              -78.16291809082031,\n              35.53278501016141\n            ],\n            [\n              -78.15536499023438,\n              35.540328192421704\n            ],\n            [\n              -78.15811157226562,\n              35.54423919285255\n            ],\n            [\n              -78.1509017944336,\n              35.55373654269702\n            ],\n            [\n              -78.15605163574219,\n              35.55485380401207\n            ],\n            [\n              -78.14987182617188,\n              35.56183633443312\n            ],\n            [\n              -78.15742492675781,\n              35.56881825654513\n            ],\n            [\n              -78.15673828125,\n              35.576916524038616\n            ],\n            [\n              -78.15433502197264,\n              35.58501397284422\n            ],\n            [\n              -78.16223144531249,\n              35.587806006729444\n            ],\n            [\n              -78.17218780517578,\n              35.58278027563934\n            ],\n            [\n              -78.17596435546875,\n              35.58278027563934\n            ],\n            [\n              -78.1732177734375,\n              35.591156318876756\n            ],\n            [\n              -78.1783676147461,\n              35.59311060288303\n            ],\n            [\n              -78.18283081054688,\n              35.59031875398378\n            ],\n            [\n              -78.19278717041016,\n              35.596181524214686\n            ],\n            [\n              -78.1955337524414,\n              35.60204386504707\n            ],\n            [\n              -78.19793701171875,\n              35.60539358129148\n            ],\n            [\n              -78.20686340332031,\n              35.60288130725417\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"71","issue":"1","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5566eab5e4b0d9246a9ec2cc","contributors":{"authors":[{"text":"Raabe, Joshua K.","contributorId":140952,"corporation":false,"usgs":false,"family":"Raabe","given":"Joshua","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":547782,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gardner, Beth","contributorId":91612,"corporation":false,"usgs":false,"family":"Gardner","given":"Beth","affiliations":[{"id":13553,"text":"University of Washington-Seattle","active":true,"usgs":false}],"preferred":false,"id":547783,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hightower, Joseph E. jhightower@usgs.gov","contributorId":835,"corporation":false,"usgs":true,"family":"Hightower","given":"Joseph","email":"jhightower@usgs.gov","middleInitial":"E.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":547468,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
]}