{"pageNumber":"480","pageRowStart":"11975","pageSize":"25","recordCount":46651,"records":[{"id":70139227,"text":"ds916 - 2015 - Geochronology of Cenozoic rocks in the Bodie Hills, California and Nevada","interactions":[],"lastModifiedDate":"2015-03-03T08:39:00","indexId":"ds916","displayToPublicDate":"2015-03-03T09:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"916","title":"Geochronology of Cenozoic rocks in the Bodie Hills, California and Nevada","docAbstract":"<p>The purpose of this report is to present geochronologic data for unaltered volcanic rocks, hydrothermally altered volcanic rocks, and mineral deposits of the Miocene Bodie Hills and Pliocene to Pleistocene Aurora volcanic fields of east-central California and west-central Nevada. Most of the data presented here were derived from samples collected between 2000&ndash;13, but some of the geochronologic data, compiled from a variety of sources, pertain to samples collected during prior investigations. New data presented here (tables 1 and 2; Appendixes 1&ndash;3) were acquired in three U.S. Geological Survey (USGS)&nbsp;<sup>40</sup>Ar/<sup>39</sup>Ar labs by three different geochronologists: Robert J. Fleck (Menlo Park, CA), Lawrence W. Snee (Denver, CO), and Michael A. Cosca (Denver, CO). Analytical methods and data derived from each of these labs are presented separately.</p>\n<p>The middle to late Miocene Bodie Hills volcanic field (BHVF) is a large (&gt;700 km<sup>2</sup>), long-lived (~9 million years [m.y.]), episodic eruptive complex (John and others, 2012) in the southern segment of the ancestral Cascades arc (du Bray and others, written commun., 2015) north of Mono Lake and east of Bridgeport, California (fig. 1). The field is near the west edge of the Walker Lane and the northwest edge of the Mina deflection where structures related to these shear zones may have localized magmatism. The Walker Lane (fig. 1) is a broad, northwest-striking zone of right-lateral shear that accommodates right-lateral motion between the Pacific and North America plates; the Mina deflection constitutes a 60-km-long right step in the Walker Lane (Faulds and Henry, 2008; Oldow, 1992, 2003; Stewart, 1988). The Bodie Hills volcanic field includes at least 31 volcanic rock units erupted from 21 significant volcanic eruptive centers.</p>\n<p>Four trachyandesite stratovolcanoes developed along the margins of the volcanic field and numerous silicic trachyandesite to rhyolite flow dome complexes erupted more centrally. Volcanism in the Bodie Hills volcanic field peaked at two periods, ~15.0 to 12.6 million years before present (Ma) and ~9.9 to 8.0 Ma, which were dominated by emplacement of large stratovolcanoes and large silicic trachyandesite-dacite lava domes, respectively. A final period of small-volume silicic dome emplacement began in the western part of the volcanic field at ~6 Ma and culminated at ~5.5 Ma (John and others, 2012).</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds916","usgsCitation":"Fleck, R.J., du Bray, E.A., John, D.A., Vikre, P., Cosca, M.A., Snee, L., and Box, S.E., 2015, Geochronology of Cenozoic rocks in the Bodie Hills, California and Nevada: U.S. Geological Survey Data Series 916, Report: iii, 26 p.; 3 Appendixes, https://doi.org/10.3133/ds916.","productDescription":"Report: iii, 26 p.; 3 Appendixes","numberOfPages":"34","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-060692","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":298237,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds916.gif"},{"id":298232,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0916/"},{"id":298233,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0916/downloads/ds916_report.pdf","size":"4.5 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":298234,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/0916/downloads/ds916_appendix1.xls","text":"Appendix 1","size":"709 kB","linkFileType":{"id":3,"text":"xlsx"},"linkHelpText":"Analytical results of CO2-laser-fusion and resistance-furnace incremental heating 40Ar/39Ar age determinations for samples of the Bodie Hills volcanic field."},{"id":298236,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/0916/downloads/ds916_appendix3.xls","text":"Appendix 3","size":"26 kB","linkFileType":{"id":3,"text":"xlsx"},"linkHelpText":"Analytical results of CO2-laser incremental heating 40Ar/39Ar experiments (Denver lab, Cosca) for samples of the Bodie Hills volcanic field."},{"id":298235,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/0916/downloads/ds916_appendix2.xls","text":"Appendix 2","size":"101 kB","linkFileType":{"id":3,"text":"xlsx"},"linkHelpText":"Analytical results of furnace incremental heating 40Ar/39Ar experiments (Denver lab, Snee) for samples of the Bodie Hills volcanic field."}],"country":"United States","state":"California, Nevada","otherGeospatial":"Bodie Hills","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -119.32250976562499,\n              38.013476231041935\n            ],\n            [\n              -119.32250976562499,\n              38.453588708941375\n            ],\n            [\n              -118.7017822265625,\n              38.453588708941375\n            ],\n            [\n              -118.7017822265625,\n              38.013476231041935\n            ],\n            [\n              -119.32250976562499,\n              38.013476231041935\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54f6db29e4b02419550d3092","contributors":{"authors":[{"text":"Fleck, Robert J. 0000-0002-3149-8249 fleck@usgs.gov","orcid":"https://orcid.org/0000-0002-3149-8249","contributorId":1048,"corporation":false,"usgs":true,"family":"Fleck","given":"Robert","email":"fleck@usgs.gov","middleInitial":"J.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":541737,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"du Bray, Edward A. 0000-0002-4383-8394 edubray@usgs.gov","orcid":"https://orcid.org/0000-0002-4383-8394","contributorId":755,"corporation":false,"usgs":true,"family":"du Bray","given":"Edward","email":"edubray@usgs.gov","middleInitial":"A.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":541724,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"John, David A. 0000-0001-7977-9106 djohn@usgs.gov","orcid":"https://orcid.org/0000-0001-7977-9106","contributorId":1748,"corporation":false,"usgs":true,"family":"John","given":"David","email":"djohn@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":541738,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vikre, Peter G. pvikre@usgs.gov","contributorId":1800,"corporation":false,"usgs":true,"family":"Vikre","given":"Peter G.","email":"pvikre@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":false,"id":541739,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cosca, Michael A. 0000-0002-0600-7663 mcosca@usgs.gov","orcid":"https://orcid.org/0000-0002-0600-7663","contributorId":1000,"corporation":false,"usgs":true,"family":"Cosca","given":"Michael","email":"mcosca@usgs.gov","middleInitial":"A.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":541740,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Snee, Lawrence W.","contributorId":81534,"corporation":false,"usgs":true,"family":"Snee","given":"Lawrence W.","affiliations":[],"preferred":false,"id":541741,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Box, Stephen E. 0000-0002-5268-8375 sbox@usgs.gov","orcid":"https://orcid.org/0000-0002-5268-8375","contributorId":1843,"corporation":false,"usgs":true,"family":"Box","given":"Stephen","email":"sbox@usgs.gov","middleInitial":"E.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":541742,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70143510,"text":"70143510 - 2015 - Trophic cascades from wolves to grizzly bears or changing abundance of bears and alternate foods?","interactions":[],"lastModifiedDate":"2017-09-08T10:12:05","indexId":"70143510","displayToPublicDate":"2015-03-03T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2158,"text":"Journal of Animal Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Trophic cascades from wolves to grizzly bears or changing abundance of bears and alternate foods?","docAbstract":"<p>This is a Forum article commenting on: Ripple, W. J., Beschta, R. L., Fortin, J. K., &amp; Robbins, C. T. (2014) Trophic cascades from wolves to grizzly bears in Yellowstone. Journal of Animal Ecology, 83, 223&ndash;233. Comparisons Ripple et al. (2014) used to demonstrate increased fruit availability and consumption by grizzly bears post-wolf reintroduction are flawed and tenuous at best. Importantly, a more parsimonious (than trophic cascades) hypothesis, not sufficiently considered by Ripple et al., exists and is better supported by available data I review.</p>","language":"English","publisher":"Journal of Animal Ecology","doi":"10.1111/1365-2656.12338","usgsCitation":"Barber-Meyer, S., 2015, Trophic cascades from wolves to grizzly bears or changing abundance of bears and alternate foods?: Journal of Animal Ecology, v. 84, no. 3, 5 p., https://doi.org/10.1111/1365-2656.12338.","productDescription":"5 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-054778","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":472227,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2656.12338","text":"Publisher Index Page"},{"id":298761,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -111.2530517578125,\n              44.05601169578525\n            ],\n            [\n              -109.94018554687499,\n              44.05601169578525\n            ],\n            [\n              -109.94018554687499,\n              45.04635929200553\n            ],\n            [\n              -111.2530517578125,\n              45.04635929200553\n            ],\n            [\n              -111.2530517578125,\n              44.05601169578525\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"84","issue":"3","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2015-03-03","publicationStatus":"PW","scienceBaseUri":"550bf33be4b02e76d759ce0a","contributors":{"authors":[{"text":"Barber-Meyer, Shannon M. 0000-0002-3048-2616 sbarber-meyer@usgs.gov","orcid":"https://orcid.org/0000-0002-3048-2616","contributorId":4422,"corporation":false,"usgs":true,"family":"Barber-Meyer","given":"Shannon M.","email":"sbarber-meyer@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":542728,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70142095,"text":"ds909 - 2015 - Hydrographic surveys at seven chutes and three backwaters on the Missouri River in Nebraska, Iowa, and Missouri, 2011-13","interactions":[],"lastModifiedDate":"2015-03-03T11:22:33","indexId":"ds909","displayToPublicDate":"2015-03-02T14:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"909","title":"Hydrographic surveys at seven chutes and three backwaters on the Missouri River in Nebraska, Iowa, and Missouri, 2011-13","docAbstract":"<p>The U.S. Geological Survey cooperated with the U.S. Army Corps of Engineers (USACE), Omaha District, to complete hydrographic surveys of seven chutes and three backwaters on the Missouri River yearly during 2011&ndash;13. These chutes and backwaters were constructed by the USACE to increase the amount of available shallow water habitat (SWH) to support threatened and endangered species, as required by the amended &ldquo;2000 Biological Opinion&rdquo; on the operation of the Missouri River main-stem reservoir system. Chutes surveyed included Council chute, Plattsmouth chute, Tobacco chute, Upper Hamburg chute, Lower Hamburg chute, Kansas chute, and Deroin chute. Backwaters surveyed included Ponca backwater, Plattsmouth backwater, and Langdon backwater. Hydrographic data from these chute and backwater surveys will aid the USACE to assess the current (2011&ndash;13) amount of available SWH, the effects river flow have had on evolving morphology of the chutes and backwaters, and the functionality of the chute and backwater designs. Chutes and backwaters were surveyed from August through November 2011, June through November 2012, and May through October 2013. During the 2011 surveys, high water was present at all sites because of the major flooding on the Missouri River. The hydrographic survey data are published along with this report in comma-separated-values (csv) format with associated metadata.</p>\n<p>Hydrographic surveys included bathymetric and Real-Time Kinematic Global Navigation Satellite System surveys. Hydrographic data were collected along transects extending across the channel from top of bank to top of bank. Transect segments with water depths greater than 1 meter were surveyed using a single-beam echosounder to measure depth and a differentially corrected global positioning system to measure location. These depth soundings were converted to elevation using water-surface-elevation information collected with a Real-Time Kinematic Global Navigation Satellite System. Transect segments with water depths less than 1 meter were surveyed using Real-Time Kinematic Global Navigation Satellite Systems. Surveyed features included top of bank, toe of bank, edge of water, sand bars, and near-shore areas.</p>\n<p>Discharge was measured at chute survey sites, in both the main channel of the Missouri River upstream from the chute and the chute. Many chute entrances and control structures were damaged by floodwater during the 2011 Missouri River flood, allowing a larger percentage of the total Missouri River discharge to flow through the chute than originally intended in the chute design. Measured discharge split between the main channel and the chute at most chutes was consistent with effects of the 2011 Missouri River flood damages and a larger percent of the total Missouri River discharge was flowing through the chute than originally intended. The U.S. Army Corps of Engineers repaired many of these chutes in 2012 and 2013, and the resulting hydraulic changes are reflected in the discharge splits.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds909","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers, Omaha District","usgsCitation":"Krahulik, J., Densmore, B.K., Anderson, K.J., and Kavan, C.L., 2015, Hydrographic surveys at seven chutes and three backwaters on the Missouri River in Nebraska, Iowa, and Missouri, 2011-13: U.S. Geological Survey Data Series 909, Report: vi, 28 p.; 10 Figures: 8.5 inches x 11 inches; GIS Datasets, https://doi.org/10.3133/ds909.","productDescription":"Report: vi, 28 p.; 10 Figures: 8.5 inches x 11 inches; GIS Datasets","startPage":"28","numberOfPages":"38","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2011-01-01","temporalEnd":"2013-12-31","ipdsId":"IP-057194","costCenters":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"links":[{"id":298222,"rank":14,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds909.jpg"},{"id":298210,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0909/pdf/ds909.pdf","text":"Report","size":"2.34 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":298209,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0909/"},{"id":298211,"rank":3,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/0909/downloads/ds909_figure4.pdf","text":"Figure 4","size":"2.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Figure 4","linkHelpText":"Layered PDF"},{"id":298212,"rank":4,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/0909/downloads/ds909_figure5.pdf","text":"Figure 5","size":"17.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Figure 5","linkHelpText":"Layered PDF"},{"id":298213,"rank":5,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/0909/downloads/ds909_figure6.pdf","text":"Figure 6","size":"3.09 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Figure 6","linkHelpText":"Layered PDF"},{"id":298214,"rank":6,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/0909/downloads/ds909_figure7.pdf","text":"Figure 7","size":"3.02 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Figure 7","linkHelpText":"Layered PDF"},{"id":298215,"rank":7,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/0909/downloads/ds909_figure8.pdf","text":"Figure 8","size":"3.15 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Figure 8","linkHelpText":"Layered PDF"},{"id":298216,"rank":8,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/0909/downloads/ds909_figure9.pdf","text":"Figure 9","size":"4.43 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Figure 9","linkHelpText":"Layered PDF"},{"id":298217,"rank":9,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/0909/downloads/ds909_figure10.pdf","text":"Figure 10","size":"3.52 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Figure 10","linkHelpText":"Layered PDF"},{"id":298218,"rank":10,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/0909/downloads/ds909_figure11.pdf","text":"Figure 11","size":"2.96 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Figure 11","linkHelpText":"Layered PDF"},{"id":298219,"rank":11,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/0909/downloads/ds909_figure12.pdf","text":"Figure 12","size":"2.65 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Figure 12","linkHelpText":"Layered PDF"},{"id":298220,"rank":12,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/0909/downloads/ds909_figure13.pdf","text":"Figure 13","size":"4.38 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"Layered PDF"},{"id":298221,"rank":13,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/0909/downloads/GISdatasets.html","text":"GIS Datasets","description":"GIS Datasets"}],"country":"United States","state":"Iowa, Missouri, Nebraska","otherGeospatial":"Missouri River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -98.1298828125,\n              39.977120098439634\n            ],\n            [\n              -98.1298828125,\n              43.35713822211053\n            ],\n            [\n              -94.52636718749999,\n            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bdensmore@usgs.gov","orcid":"https://orcid.org/0000-0003-2429-638X","contributorId":4896,"corporation":false,"usgs":true,"family":"Densmore","given":"Brenda","email":"bdensmore@usgs.gov","middleInitial":"K.","affiliations":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"preferred":true,"id":541666,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anderson, Kayla J. kjanderson@usgs.gov","contributorId":5678,"corporation":false,"usgs":true,"family":"Anderson","given":"Kayla","email":"kjanderson@usgs.gov","middleInitial":"J.","affiliations":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"preferred":true,"id":541667,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kavan, Cory L. 0000-0002-5887-9316 ckavan@usgs.gov","orcid":"https://orcid.org/0000-0002-5887-9316","contributorId":5677,"corporation":false,"usgs":true,"family":"Kavan","given":"Cory","email":"ckavan@usgs.gov","middleInitial":"L.","affiliations":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"preferred":true,"id":541668,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70170326,"text":"70170326 - 2015 - Experimental flights using a small unmanned aircraft system for mapping emergent sandbars","interactions":[],"lastModifiedDate":"2016-04-18T10:46:24","indexId":"70170326","displayToPublicDate":"2015-03-02T11:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1859,"text":"Great Plains Research","active":true,"publicationSubtype":{"id":10}},"title":"Experimental flights using a small unmanned aircraft system for mapping emergent sandbars","docAbstract":"<p><span>The US Geological Survey and Parallel Inc. conducted experimental flights with the Tarantula Hawk (T-Hawk) unmanned aircraft system (UAS</span><small class=\"caps\">&nbsp;</small><span>) at the Dyer and Cottonwood Ranch properties located along reaches of the Platte River near Overton, Nebraska, in July 2013. We equipped the T-Hawk UAS</span><small class=\"caps\">&nbsp;</small><span>platform with a consumer-grade digital camera to collect imagery of emergent sandbars in the reaches and used photogrammetric software and surveyed control points to generate orthophotographs and digital elevation models (DEMS</span><small class=\"caps\">&nbsp;</small><span>) of the reaches. To optimize the image alignment process, we retained and/or eliminated tie points based on their relative errors and spatial resolution, whereby minimizing the total error in the project. Additionally, we collected seven transects that traversed emergent sandbars concurrently with global positioning system location data to evaluate the accuracy of the&nbsp;UAS</span><small class=\"caps\">&nbsp;</small><span>survey methodology. The root mean square errors for the elevation of emergent points along each transect across the DEMS</span><small class=\"caps\">&nbsp;</small><span>ranged from 0.04 to 0.12 m. If adequate survey control is established, a UAS</span><small class=\"caps\">&nbsp;</small><span>combined with photogrammetry software shows promise for accurate monitoring of emergent sandbar morphology and river management activities in short (1&ndash;2 km) river reaches.</span></p>","language":"English","publisher":"University of Nebraska--Lincoln. Center for Great Plains Studies","publisherLocation":"Lincoln, NE","doi":"10.1353/gpr.2015.0018","usgsCitation":"Kinzel, P.J., Bauer, M., Feller, M.R., Holmquist-Johnson, C., and Preston, T., 2015, Experimental flights using a small unmanned aircraft system for mapping emergent sandbars: Great Plains Research, v. 25, no. 1, p. 39-52, https://doi.org/10.1353/gpr.2015.0018.","productDescription":"14 p.","startPage":"39","endPage":"52","numberOfPages":"14","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-053315","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":320129,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nebraska","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -99.45064544677734,\n              40.68138655718806\n            ],\n            [\n              -99.45064544677734,\n              40.68724434319262\n            ],\n            [\n              -99.43382263183594,\n              40.68724434319262\n            ],\n            [\n              -99.43382263183594,\n              40.68138655718806\n            ],\n            [\n              -99.45064544677734,\n              40.68138655718806\n            ]\n          ]\n        ]\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -99.55973625183105,\n              40.679759303041855\n            ],\n            [\n              -99.55973625183105,\n              40.683990081194764\n            ],\n            [\n              -99.54733371734619,\n              40.683990081194764\n            ],\n            [\n              -99.54733371734619,\n              40.679759303041855\n            ],\n            [\n              -99.55973625183105,\n              40.679759303041855\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"25","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57160536e4b0ef3b7ca91ff4","contributors":{"authors":[{"text":"Kinzel, Paul J. 0000-0002-6076-9730 pjkinzel@usgs.gov","orcid":"https://orcid.org/0000-0002-6076-9730","contributorId":743,"corporation":false,"usgs":true,"family":"Kinzel","given":"Paul","email":"pjkinzel@usgs.gov","middleInitial":"J.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":626879,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bauer, Mark A. mabauer@usgs.gov","contributorId":1409,"corporation":false,"usgs":true,"family":"Bauer","given":"Mark A.","email":"mabauer@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":626880,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Feller, Mark R. mrfeller@usgs.gov","contributorId":3904,"corporation":false,"usgs":true,"family":"Feller","given":"Mark","email":"mrfeller@usgs.gov","middleInitial":"R.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":626881,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Holmquist-Johnson, Christopher 0000-0002-2782-7687 h-johnsonc@usgs.gov","orcid":"https://orcid.org/0000-0002-2782-7687","contributorId":168648,"corporation":false,"usgs":true,"family":"Holmquist-Johnson","given":"Christopher","email":"h-johnsonc@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":626882,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Preston, Todd","contributorId":81379,"corporation":false,"usgs":true,"family":"Preston","given":"Todd","affiliations":[],"preferred":false,"id":626883,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70140748,"text":"ds921 - 2015 - Ground-based lidar beach topography of Fire Island, New York, April 2013","interactions":[],"lastModifiedDate":"2017-08-14T11:25:35","indexId":"ds921","displayToPublicDate":"2015-03-02T09:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"921","title":"Ground-based lidar beach topography of Fire Island, New York, April 2013","docAbstract":"<p><span>The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center in Florida and the U.S. Army Corps of Engineers Field Research Facility in Duck, North Carolina, collaborated to gather alongshore ground-based lidar beach elevation data at Fire Island, New York. This high-resolution elevation dataset was collected on April 10, 2013, to characterize beach topography following substantial erosion that occurred during Hurricane Sandy, which made landfall on October 29, 2012, and multiple, strong winter storms. The ongoing beach monitoring is part of the Hurricane Sandy Supplemental Project GS2-2B. This USGS data series includes the resulting processed elevation point data (xyz) and an interpolated digital elevation model (DEM).</span></p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds921","usgsCitation":"Brenner, O.T., Hapke, C.J., Spore, N.J., Brodie, K.L., and McNinch, J., 2015, Ground-based lidar beach topography of Fire Island, New York, April 2013: U.S. Geological Survey Data Series 921, HTML Document, https://doi.org/10.3133/ds921.","productDescription":"HTML Document","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2013-04-01","temporalEnd":"2013-04-30","ipdsId":"IP-060922","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":298194,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds921.jpg"},{"id":344813,"rank":7,"type":{"id":18,"text":"Project Site"},"url":"https://coastal.er.usgs.gov/fire-island/research/sandy/","text":"Fire Island Coastal Change"},{"id":298188,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0921/"},{"id":342394,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/ds/0921/ds921_data.html","text":"April 10, 2013 Dataset"},{"id":342395,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://dx.doi.org/10.5066/F77H1GNN","text":"April 1, 2014 Dataset"},{"id":298193,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0921/ds921_abstract.html","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"Report"},{"id":344812,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://coastal.er.usgs.gov/data-release/doi-F7N29VV5/","text":"January 30, 2012 Dataset"}],"country":"United States","state":"New York","otherGeospatial":"Fire Island","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -73.26370239257812,\n              40.61812224225511\n            ],\n            [\n              -73.26370239257812,\n              40.80237530523985\n            ],\n            [\n              -72.65121459960938,\n              40.80237530523985\n            ],\n            [\n              -72.65121459960938,\n              40.61812224225511\n            ],\n            [\n              -73.26370239257812,\n              40.61812224225511\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54f589aee4b02419550d2f31","contributors":{"authors":[{"text":"Brenner, Owen T. 0000-0002-1588-721X obrenner@usgs.gov","orcid":"https://orcid.org/0000-0002-1588-721X","contributorId":4933,"corporation":false,"usgs":true,"family":"Brenner","given":"Owen","email":"obrenner@usgs.gov","middleInitial":"T.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":541603,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hapke, Cheryl J. 0000-0002-2753-4075 chapke@usgs.gov","orcid":"https://orcid.org/0000-0002-2753-4075","contributorId":2981,"corporation":false,"usgs":true,"family":"Hapke","given":"Cheryl","email":"chapke@usgs.gov","middleInitial":"J.","affiliations":[{"id":6676,"text":"USGS (retired)","active":true,"usgs":false}],"preferred":true,"id":541604,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Spore, Nicholas J.","contributorId":139216,"corporation":false,"usgs":false,"family":"Spore","given":"Nicholas","email":"","middleInitial":"J.","affiliations":[{"id":12700,"text":"ACE at Duck NC","active":true,"usgs":false}],"preferred":false,"id":541605,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brodie, Katherine L.","contributorId":139217,"corporation":false,"usgs":false,"family":"Brodie","given":"Katherine","email":"","middleInitial":"L.","affiliations":[{"id":34410,"text":"USACE-Coastal Hydraulic Lab, Duck, NC","active":true,"usgs":false},{"id":12700,"text":"ACE at Duck NC","active":true,"usgs":false}],"preferred":false,"id":541607,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McNinch, Jesse E.","contributorId":93804,"corporation":false,"usgs":true,"family":"McNinch","given":"Jesse E.","affiliations":[],"preferred":false,"id":541606,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70139543,"text":"sir20155011 - 2015 - Evaluation of the effects of sewering on nitrogen loads to the Niantic River, southeastern Connecticut, 2005-2011","interactions":[],"lastModifiedDate":"2015-03-02T13:47:10","indexId":"sir20155011","displayToPublicDate":"2015-03-02T09:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-5011","title":"Evaluation of the effects of sewering on nitrogen loads to the Niantic River, southeastern Connecticut, 2005-2011","docAbstract":"<p>Nitrogen concentration data were collected from 20 wells near the Niantic River Estuary, during 18 sampling periods from 2005 through 2011, as part of a study to determine changes in nitrogen concentrations and loads as a result of sewering on the Pine Grove peninsula in Niantic, Connecticut. The Pine Grove peninsula area is a neighborhood of 35 acres containing 172 residences with onsite wastewater treatment systems at the beginning of the study in 2005. From 2008 through 2009, the residences were connected to a newly installed sewer system. Water-quality data collection continued from 2010 through 2011, after the sewers were installed.</p>\n<p>The peninsula is underlain by glacial stratified deposits. The freshwater in this aquifer ranges from 10 to 45 feet (ft) in thickness and overlies saline groundwater. The mean water-table altitude was from 0.09 to 0.97 ft above the North American Vertical Datum of 1988, with a horizontal hydraulic gradient of 0.0004 to 0.0005.</p>\n<p>Initial sampling of the wells included analysis for nutrients, major ions, boron, bromide, and dissolved gases. Concentrations of nitrate plus nitrite nitrogen from the initial sampling ranged from 0.94 to 20 milligrams per liter (mg/L) in samples collected spatially and with depth in the aquifer. The mean concentration of total dissolved nitrogen before the sewers were installed was 7.5 mg/L, and dissolved gas analyses indicated little or no denitrification in the aquifer. Chloride to bromide ratios and boron analysis of the initial water samples confirmed that wastewater was a source of groundwater recharge to most of the wells. Annual recharge from onsite wastewater-disposal systems in 2006 was 4.98 inches, based on analysis of water-use data.</p>\n<p>Concentrations of total dissolved nitrogen decreased following sewering in samples from most of the wells that were identified as having nitrogen related to wastewater discharge. Concentrations of total dissolved nitrogen in individual wells decreased by as much as 11.7 mg/L between the periods before and after the sewers were installed, and the mean concentration of total dissolved nitrogen in all wells decreased by 2.3 mg/L to a mean concentration of 5.2 mg/L.</p>\n<p>Nitrogen loads from groundwater in the Pine Grove peninsula area were estimated for three time periods by using the measured mean concentrations of total dissolved nitrogen and estimated recharge rates. The estimated nitrogen load before sewering was 1,675 pounds per year (lb/yr) and following sewering was 963 lb/yr. Mean concentrations of total dissolved nitrogen were assumed to have been reduced to 1.1 to 2.3 mg/L after the aquifer had stabilized and sewage-related nitrogen had been completely discharged from the system, with an estimated future load of 202 to 423 lb/yr.</p>\n<p>Nitrogen loads from groundwater discharge to the Niantic River Estuary from the lower part of the Niantic River watershed, including Pine Grove, were estimated to be 18,800 pounds (lb) in 2011. This compares with an additional 51,000 lb from the surface-water tributaries to the estuary and an unknown quantity of nitrogen load from stormwater runoff in the lower Niantic watershed.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155011","collaboration":"Prepared in cooperation with the Connecticut Department of Energy and Environmental Protection","usgsCitation":"Mullaney, J.R., 2015, Evaluation of the effects of sewering on nitrogen loads to the Niantic River, southeastern Connecticut, 2005-2011: U.S. Geological Survey Scientific Investigations Report 2015-5011, vii, 30 p., https://doi.org/10.3133/sir20155011.","productDescription":"vii, 30 p.","numberOfPages":"42","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2005-01-01","temporalEnd":"2011-12-31","ipdsId":"IP-057160","costCenters":[{"id":196,"text":"Connecticut Water Science Center","active":true,"usgs":true}],"links":[{"id":298197,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20155011.jpg"},{"id":298196,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5011/pdf/sir2015-5011.pdf","text":"Report","size":"2.33 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":298195,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2015/5011/"}],"country":"United States","state":"Connecticut","otherGeospatial":"Niantic River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -72.2024917602539,\n              41.321138395239565\n            ],\n            [\n              -72.2024917602539,\n              41.372944119757406\n            ],\n            [\n              -72.16747283935547,\n              41.372944119757406\n            ],\n            [\n              -72.16747283935547,\n              41.321138395239565\n            ],\n            [\n              -72.2024917602539,\n              41.321138395239565\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54f589a9e4b02419550d2f2f","contributors":{"authors":[{"text":"Mullaney, John R. 0000-0003-4936-5046 jmullane@usgs.gov","orcid":"https://orcid.org/0000-0003-4936-5046","contributorId":1957,"corporation":false,"usgs":true,"family":"Mullaney","given":"John","email":"jmullane@usgs.gov","middleInitial":"R.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":196,"text":"Connecticut Water Science Center","active":true,"usgs":true}],"preferred":true,"id":539432,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70157346,"text":"70157346 - 2015 - Higher-order statistical moments and a procedure that detects potentially anomalous years as two alternative methods describing alterations in continuous environmental data","interactions":[],"lastModifiedDate":"2017-11-22T18:01:31","indexId":"70157346","displayToPublicDate":"2015-03-02T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1928,"text":"Hydrology and Earth System Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Higher-order statistical moments and a procedure that detects potentially anomalous years as two alternative methods describing alterations in continuous environmental data","docAbstract":"<p><span>Statistics of central tendency and dispersion may not capture relevant or desired characteristics of the distribution of continuous phenomena and, thus, they may not adequately describe temporal patterns of change. Here, we present two methodological approaches that can help to identify temporal changes in environmental regimes. First, we use higher-order statistical moments (skewness and kurtosis) to examine potential changes of empirical distributions at decadal extents. Second, we adapt a statistical procedure combining a non-metric multidimensional scaling technique and higher density region plots to detect potentially anomalous years. We illustrate the use of these approaches by examining long-term stream temperature data from minimally and highly human-influenced streams. In particular, we contrast predictions about thermal regime responses to changing climates and human-related water uses. Using these methods, we effectively diagnose years with unusual thermal variability and patterns in variability through time, as well as spatial variability linked to regional and local factors that influence stream temperature. Our findings highlight the complexity of responses of thermal regimes of streams and reveal their differential vulnerability to climate warming and human-related water uses. The two approaches presented here can be applied with a variety of other continuous phenomena to address historical changes, extreme events, and their associated ecological responses.</span></p>","language":"English","publisher":"Copernicus Publications","doi":"10.5194/hess-19-1169-2015","usgsCitation":"Arismendi, I., Johnson, S.L., and Dunham, J.B., 2015, Higher-order statistical moments and a procedure that detects potentially anomalous years as two alternative methods describing alterations in continuous environmental data: Hydrology and Earth System Sciences, v. 19, p. 1169-1180, https://doi.org/10.5194/hess-19-1169-2015.","productDescription":"12 p.","startPage":"1169","endPage":"1180","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056997","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":472230,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/hess-19-1169-2015","text":"Publisher Index Page"},{"id":308333,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":308307,"type":{"id":15,"text":"Index Page"},"url":"https://www.hydrol-earth-syst-sci.net/19/1169/2015/hess-19-1169-2015.html"}],"volume":"19","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-03-02","publicationStatus":"PW","scienceBaseUri":"56012a52e4b03bc34f544402","contributors":{"authors":[{"text":"Arismendi, Ivan","contributorId":70661,"corporation":false,"usgs":true,"family":"Arismendi","given":"Ivan","affiliations":[],"preferred":false,"id":572770,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Sherri L.","contributorId":91757,"corporation":false,"usgs":true,"family":"Johnson","given":"Sherri","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":572771,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dunham, Jason B. 0000-0002-6268-0633 jdunham@usgs.gov","orcid":"https://orcid.org/0000-0002-6268-0633","contributorId":147808,"corporation":false,"usgs":true,"family":"Dunham","given":"Jason","email":"jdunham@usgs.gov","middleInitial":"B.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":572769,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70168685,"text":"70168685 - 2015 - Comparing models of Red Knot population dynamics","interactions":[],"lastModifiedDate":"2016-02-24T14:45:15","indexId":"70168685","displayToPublicDate":"2015-03-01T15:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3551,"text":"The Condor","active":true,"publicationSubtype":{"id":10}},"title":"Comparing models of Red Knot population dynamics","docAbstract":"<p>Predictive population modeling contributes to our basic scientific understanding of population dynamics, but can also inform management decisions by evaluating alternative actions in virtual environments. Quantitative models mathematically reflect scientific hypotheses about how a system functions. In Delaware Bay, mid-Atlantic Coast, USA, to more effectively manage horseshoe crab (<i>Limulus polyphemus</i>) harvests and protect Red Knot (<i>Calidris canutus rufa</i>) populations, models are used to compare harvest actions and predict the impacts on crab and knot populations. Management has been chiefly driven by the core hypothesis that horseshoe crab egg abundance governs the survival and reproduction of migrating Red Knots that stopover in the Bay during spring migration. However, recently, hypotheses proposing that knot dynamics are governed by cyclical lemming dynamics garnered some support in data analyses. In this paper, I present alternative models of Red Knot population dynamics to reflect alternative hypotheses. Using 2 models with different lemming population cycle lengths and 2 models with different horseshoe crab effects, I project the knot population into the future under environmental stochasticity and parametric uncertainty with each model. I then compare each model's predictions to 10 yr of population monitoring from Delaware Bay. Using Bayes' theorem and model weight updating, models can accrue weight or support for one or another hypothesis of population dynamics. With 4 models of Red Knot population dynamics and only 10 yr of data, no hypothesis clearly predicted population count data better than another. The collapsed lemming cycle model performed best, accruing ~35% of the model weight, followed closely by the horseshoe crab egg abundance model, which accrued ~30% of the weight. The models that predicted no decline or stable populations (i.e. the 4-yr lemming cycle model and the weak horseshoe crab effect model) were the most weakly supported.</p>","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"The Condor","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Cooper Ornithological Club","publisherLocation":"Santa Clara","doi":"10.1650/CONDOR-15-9.1","usgsCitation":"McGowan, C.P., 2015, Comparing models of Red Knot population dynamics: The Condor, v. 117, no. 4, p. 494-502, https://doi.org/10.1650/CONDOR-15-9.1.","productDescription":"9 p.","startPage":"494","endPage":"502","numberOfPages":"9","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061278","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":472231,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1650/condor-15-9.1","text":"Publisher Index Page"},{"id":318370,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"117","issue":"4","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56cee255e4b015c306ec5e96","contributors":{"authors":[{"text":"McGowan, Conor P. 0000-0002-7330-9581 cmcgowan@usgs.gov","orcid":"https://orcid.org/0000-0002-7330-9581","contributorId":167162,"corporation":false,"usgs":true,"family":"McGowan","given":"Conor","email":"cmcgowan@usgs.gov","middleInitial":"P.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":false,"id":621321,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70143179,"text":"70143179 - 2015 - Distance measures and optimization spaces in quantitative fatty acid signature analysis","interactions":[],"lastModifiedDate":"2018-04-23T10:22:40","indexId":"70143179","displayToPublicDate":"2015-03-01T14:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Distance measures and optimization spaces in quantitative fatty acid signature analysis","docAbstract":"<p>Quantitative fatty acid signature analysis has become an important method of diet estimation in ecology, especially marine ecology. Controlled feeding trials to validate the method and estimate the calibration coefficients necessary to account for differential metabolism of individual fatty acids have been conducted with several species from diverse taxa. However, research into potential refinements of the estimation method has been limited. We compared the performance of the original method of estimating diet composition with that of five variants based on different combinations of distance measures and calibration-coefficient transformations between prey and predator fatty acid signature spaces. Fatty acid signatures of pseudopredators were constructed using known diet mixtures of two prey data sets previously used to estimate the diets of polar bears Ursus maritimus and gray seals Halichoerus grypus, and their diets were then estimated using all six variants. In addition, previously published diets of Chukchi Sea polar bears were re-estimated using all six methods. Our findings reveal that the selection of an estimation method can meaningfully influence estimates of diet composition. Among the pseudopredator results, which allowed evaluation of bias and precision, differences in estimator performance were rarely large, and no one estimator was universally preferred, although estimators based on the Aitchison distance measure tended to have modestly superior properties compared to estimators based on the Kullback-Leibler distance measure. However, greater differences were observed among estimated polar bear diets, most likely due to differential estimator sensitivity to assumption violations. Our results, particularly the polar bear example, suggest that additional research into estimator performance and model diagnostics is warranted.</p>","language":"English","publisher":"Wiley","doi":"10.1002/ece3.1429","usgsCitation":"Bromaghin, J.F., Rode, K.D., Budge, S.M., and Thiemann, G.W., 2015, Distance measures and optimization spaces in quantitative fatty acid signature analysis: Ecology and Evolution, v. 6, no. 5, p. 1249-1262, https://doi.org/10.1002/ece3.1429.","productDescription":"14 p.","startPage":"1249","endPage":"1262","numberOfPages":"14","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059904","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":472234,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.1429","text":"Publisher Index Page"},{"id":298624,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","issue":"5","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-02-24","publicationStatus":"PW","scienceBaseUri":"5509502ee4b02e76d757e614","contributors":{"authors":[{"text":"Bromaghin, Jeffrey F. 0000-0002-7209-9500 jbromaghin@usgs.gov","orcid":"https://orcid.org/0000-0002-7209-9500","contributorId":139899,"corporation":false,"usgs":true,"family":"Bromaghin","given":"Jeffrey","email":"jbromaghin@usgs.gov","middleInitial":"F.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":542494,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rode, Karyn D. 0000-0002-3328-8202 krode@usgs.gov","orcid":"https://orcid.org/0000-0002-3328-8202","contributorId":5053,"corporation":false,"usgs":true,"family":"Rode","given":"Karyn","email":"krode@usgs.gov","middleInitial":"D.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":542495,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Budge, Suzanne M.","contributorId":92168,"corporation":false,"usgs":false,"family":"Budge","given":"Suzanne","email":"","middleInitial":"M.","affiliations":[{"id":24650,"text":"Dalhousie University","active":true,"usgs":false}],"preferred":false,"id":542496,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thiemann, Gregory W.","contributorId":83023,"corporation":false,"usgs":false,"family":"Thiemann","given":"Gregory","email":"","middleInitial":"W.","affiliations":[{"id":27291,"text":"York University, Toronto, ON","active":true,"usgs":false}],"preferred":false,"id":542497,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70157354,"text":"70157354 - 2015 - Strain accumulation across the Prince William Sound asperity, Southcentral Alaska","interactions":[],"lastModifiedDate":"2015-09-23T11:27:52","indexId":"70157354","displayToPublicDate":"2015-03-01T12:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2314,"text":"Journal of Geophysical Research B: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Strain accumulation across the Prince William Sound asperity, Southcentral Alaska","docAbstract":"<p><span>The surface velocities predicted by the conventional subduction model are compared to velocities measured in a GPS array (surveyed in 1993, 1995, 1997, 2000, and 2004) spanning the Prince William Sound asperity. The observed velocities in the comparison have been corrected to remove the contributions from postseismic (1964 Alaska earthquake) mantle relaxation. Except at the most seaward monument (located on Middleton Island at the seaward edge of the continental shelf, just 50&thinsp;km landward of the deformation front in the Aleutian Trench), the corrected velocities qualitatively agree with those predicted by an improved, two-dimensional, back slip, subduction model in which the locked megathrust coincides with the plate interface identified by seismic refraction surveys, and the back slip rate is equal to the plate convergence rate. A better fit to the corrected velocities is furnished by either a back slip rate 20% greater than the plate convergence rate or a 30% shallower megathrust. The shallow megathrust in the latter fit may be an artifact of the uniform half-space Earth model used in the inversion. Backslip at the plate convergence rate on the megathrust mapped by refraction surveys would fit the data as well if the rigidity of the underthrust plate was twice that of the overlying plate, a rigidity contrast higher than expected. The anomalous motion at Middleton Island is attributed to continuous slip at near the plate convergence rate on a postulated, listric fault that splays off the megathrust at depth of about 12&thinsp;km and outcrops on the continental slope south-southeast of Middleton Island.</span></p>","language":"English","publisher":"American Geophysical Union","publisherLocation":"Richmond, VA","doi":"10.1002/2014JB011652","usgsCitation":"Savage, J.C., Svarc, J.L., and Lisowski, M., 2015, Strain accumulation across the Prince William Sound asperity, Southcentral Alaska: Journal of Geophysical Research B: Solid Earth, v. 120, no. 3, p. 1820-1832, https://doi.org/10.1002/2014JB011652.","productDescription":"13 p.","startPage":"1820","endPage":"1832","numberOfPages":"13","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-055343","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":472235,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2014jb011652","text":"Publisher Index Page"},{"id":308440,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"120","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-03-09","publicationStatus":"PW","scienceBaseUri":"5603cd5be4b03bc34f544b40","contributors":{"authors":[{"text":"Savage, James C. 0000-0002-5114-7673 jasavage@usgs.gov","orcid":"https://orcid.org/0000-0002-5114-7673","contributorId":2412,"corporation":false,"usgs":true,"family":"Savage","given":"James","email":"jasavage@usgs.gov","middleInitial":"C.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":572822,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Svarc, Jerry L. 0000-0002-2802-4528 jsvarc@usgs.gov","orcid":"https://orcid.org/0000-0002-2802-4528","contributorId":2413,"corporation":false,"usgs":true,"family":"Svarc","given":"Jerry","email":"jsvarc@usgs.gov","middleInitial":"L.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":572823,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lisowski, Michael 0000-0003-4818-2504 mlisowski@usgs.gov","orcid":"https://orcid.org/0000-0003-4818-2504","contributorId":637,"corporation":false,"usgs":true,"family":"Lisowski","given":"Michael","email":"mlisowski@usgs.gov","affiliations":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":572824,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70155022,"text":"70155022 - 2015 - The data quality analyzer: a quality control program for seismic data","interactions":[],"lastModifiedDate":"2018-02-07T19:04:03","indexId":"70155022","displayToPublicDate":"2015-03-01T12:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1315,"text":"Computers & Geosciences","printIssn":"0098-3004","active":true,"publicationSubtype":{"id":10}},"title":"The data quality analyzer: a quality control program for seismic data","docAbstract":"<p>The U.S. Geological Survey's Albuquerque Seismological Laboratory (ASL) has several initiatives underway to enhance and track the quality of data produced from ASL seismic stations and to improve communication about data problems to the user community. The Data Quality Analyzer (DQA) is one such development and is designed to characterize seismic station data quality in a quantitative and automated manner.</p>\n<p>The DQA consists of a metric calculator, a PostgreSQL database, and a Web interface: The metric calculator, SEEDscan, is a Java application that reads and processes miniSEED data and generates metrics based on a configuration file. SEEDscan compares hashes of metadata and data to detect changes in either and performs subsequent recalculations as needed. This ensures that the metric values are up to date and accurate. SEEDscan can be run as a scheduled task or on demand. The PostgreSQL database acts as a central hub where metric values and limited station descriptions are stored at the channel level with one-day granularity. The Web interface dynamically loads station data from the database and allows the user to make requests for time periods of interest, review specific networks and stations, plot metrics as a function of time, and adjust the contribution of various metrics to the overall quality grade of the station.</p>\n<p>The quantification of data quality is based on the evaluation of various metrics (e.g., timing quality, daily noise levels relative to long-term noise models, and comparisons between broadband data and event synthetics). Users may select which metrics contribute to the assessment and those metrics are aggregated into a &ldquo;grade&rdquo; for each station. The DQA is being actively used for station diagnostics and evaluation based on the completed metrics (availability, gap count, timing quality, deviation from a global noise model, deviation from a station noise model, coherence between co-located sensors, and comparison between broadband data and synthetics for earthquakes) on stations in the Global Seismographic Network and Advanced National Seismic System.</p>","language":"English","publisher":"Computer Oriented Geological Society","publisherLocation":"Oxford","doi":"10.1016/j.cageo.2014.12.006","usgsCitation":"Ringler, A.T., Hagerty, M., Holland, J., Gonzales, A., Gee, L.S., Edwards, J., Wilson, D.C., and Baker, A., 2015, The data quality analyzer: a quality control program for seismic data: Computers & Geosciences, v. 76, p. 96-111, https://doi.org/10.1016/j.cageo.2014.12.006.","productDescription":"16 p.","startPage":"96","endPage":"111","numberOfPages":"16","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061275","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":305952,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"76","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55b361b6e4b09a3b01b5dabb","contributors":{"authors":[{"text":"Ringler, Adam T. 0000-0002-9839-4188 aringler@usgs.gov","orcid":"https://orcid.org/0000-0002-9839-4188","contributorId":145576,"corporation":false,"usgs":true,"family":"Ringler","given":"Adam","email":"aringler@usgs.gov","middleInitial":"T.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":564683,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hagerty, M.T.","contributorId":145577,"corporation":false,"usgs":false,"family":"Hagerty","given":"M.T.","email":"","affiliations":[{"id":13422,"text":"Boston College","active":true,"usgs":false}],"preferred":false,"id":564684,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Holland, James F. jholland@usgs.gov","contributorId":5334,"corporation":false,"usgs":true,"family":"Holland","given":"James F.","email":"jholland@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":564685,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gonzales, A.","contributorId":145578,"corporation":false,"usgs":false,"family":"Gonzales","given":"A.","email":"","affiliations":[{"id":16157,"text":"Honeywell Technology Solutions Incoporation","active":true,"usgs":false}],"preferred":false,"id":564686,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gee, Lind S. lgee@usgs.gov","contributorId":145579,"corporation":false,"usgs":true,"family":"Gee","given":"Lind","email":"lgee@usgs.gov","middleInitial":"S.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":false,"id":564687,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Edwards, J.D.","contributorId":69622,"corporation":false,"usgs":true,"family":"Edwards","given":"J.D.","email":"","affiliations":[],"preferred":false,"id":564688,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wilson, David C. 0000-0003-2582-5159 dwilson@usgs.gov","orcid":"https://orcid.org/0000-0003-2582-5159","contributorId":145580,"corporation":false,"usgs":true,"family":"Wilson","given":"David","email":"dwilson@usgs.gov","middleInitial":"C.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":564689,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Baker, Adam ambaker@usgs.gov","contributorId":145581,"corporation":false,"usgs":true,"family":"Baker","given":"Adam","email":"ambaker@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":564690,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70155019,"text":"70155019 - 2015 - Evolution of pathogen virulence across space during an epidemic","interactions":[],"lastModifiedDate":"2015-07-24T10:59:00","indexId":"70155019","displayToPublicDate":"2015-03-01T12:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":740,"text":"American Naturalist","active":true,"publicationSubtype":{"id":10}},"title":"Evolution of pathogen virulence across space during an epidemic","docAbstract":"<p><span>We explore pathogen virulence evolution during the spatial expansion of an infectious disease epidemic in the presence of a novel host movement trade-off, using a simple, spatially explicit mathematical model. This work is motivated by empirical observations of the&nbsp;</span><i>Mycoplasma gallisepticum</i><span>&nbsp;invasion into North American house finch (</span><i>Haemorhous mexicanus</i><span>) populations; however, our results likely have important applications to other emerging infectious diseases in mobile hosts. We assume that infection reduces host movement and survival and that across pathogen strains the severity of these reductions increases with pathogen infectiousness. Assuming these trade-offs between pathogen virulence (host mortality), pathogen transmission, and host movement, we find that pathogen virulence levels near the epidemic front (that maximize wave speed) are lower than those that have a short-term growth rate advantage or that ultimately prevail (i.e., are evolutionarily stable) near the epicenter and where infection becomes endemic (i.e., that maximize the pathogen basic reproductive ratio). We predict that, under these trade-offs, less virulent pathogen strains will dominate the periphery of an epidemic and that more virulent strains will increase in frequency after invasion where disease is endemic. These results have important implications for observing and interpreting spatiotemporal epidemic data and may help explain transient virulence dynamics of emerging infectious diseases.</span></p>","language":"English","publisher":"American Society of Naturalists","publisherLocation":"Salem, MA","doi":"10.1086/679734","usgsCitation":"Osnas, E.E., Hurtado, P.J., and Dobson, A.P., 2015, Evolution of pathogen virulence across space during an epidemic: American Naturalist, v. 185, no. 3, p. 332-342, https://doi.org/10.1086/679734.","productDescription":"11 p.","startPage":"332","endPage":"342","numberOfPages":"11","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059359","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":472236,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1086/679734","text":"Publisher Index Page"},{"id":305950,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"185","issue":"3","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55b361b0e4b09a3b01b5da9c","contributors":{"authors":[{"text":"Osnas, Erik E. 0000-0001-9528-0866 eosnas@usgs.gov","orcid":"https://orcid.org/0000-0001-9528-0866","contributorId":5586,"corporation":false,"usgs":true,"family":"Osnas","given":"Erik","email":"eosnas@usgs.gov","middleInitial":"E.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":564672,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hurtado, Paul J.","contributorId":145574,"corporation":false,"usgs":false,"family":"Hurtado","given":"Paul","email":"","middleInitial":"J.","affiliations":[{"id":6714,"text":"Ohio State University, School of Earth Sciences, Columbus, Ohio, USA","active":true,"usgs":false}],"preferred":false,"id":564673,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dobson, Andrew P.","contributorId":63693,"corporation":false,"usgs":true,"family":"Dobson","given":"Andrew","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":564674,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70048750,"text":"70048750 - 2015 - Hawaiian fissure fountains: Quantifying vent and shallow conduit geometry, episode 1 of the 1969-1974 Mauna Ulu eruption","interactions":[],"lastModifiedDate":"2022-12-29T15:39:25.607531","indexId":"70048750","displayToPublicDate":"2015-03-01T11:43:00","publicationYear":"2015","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"17","title":"Hawaiian fissure fountains: Quantifying vent and shallow conduit geometry, episode 1 of the 1969-1974 Mauna Ulu eruption","docAbstract":"<p><span>Geometries of shallow magmatic pathways feeding volcanic eruptions are poorly constrained, yet many key interpretations about eruption dynamics depend on knowledge of these geometries. Direct quantification is difficult because vents typically become blocked with lava at the end of eruptions. Indirect geophysical techniques have shed light on some volcanic conduit geometries, but the scales are too coarse to resolve narrow fissures (widths typically 1 m). Kīlauea's Mauna Ulu eruption, which started with &lt;50 m high Hawaiian fountains along a 4.5 km fissure on 24 May 1969, provides a unique opportunity to measure the detailed geometry of a shallow magmatic pathway, as the western vents remain unobstructed to depths &gt;30 m. Direct measurements at the ground surface were augmented by tripod-mounted lidar measurements to quantify the shallow conduit geometry for three vents at a resolution &lt;4 cm. We define the form of the fissure in terms of aspect ratio, flaring ratio, irregularity, sinuosity, and segmentation and discuss the factors influencing these parameters. In the past, simplified first-order fissure geometries have been used in computational modeling. Our data can provide more accurate conduit shapes for better understanding of shallow fissure fluid dynamics and how it controls eruptive behavior, especially if incorporated into computer models.</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Hawaiian volcanoes: From source to surface","largerWorkSubtype":{"id":15,"text":"Monograph"},"conferenceTitle":"AGU Chapman Conference","conferenceDate":"August 20-24, 2012","conferenceLocation":"Waikoloa, Hawai'i","language":"English","publisher":"American Geophysical Union","publisherLocation":"Washington, D.C.","doi":"10.1002/9781118872079.ch17","usgsCitation":"Parcheta, C., Fagents, S., Swanson, D., Houghton, B.F., and Ericksen, T., 2015, Hawaiian fissure fountains: Quantifying vent and shallow conduit geometry, episode 1 of the 1969-1974 Mauna Ulu eruption, chap. 17 <i>of</i> Hawaiian volcanoes: From source to surface, v. 208, p. 369-391, https://doi.org/10.1002/9781118872079.ch17.","productDescription":"23 p.","startPage":"369","endPage":"391","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-050831","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":311101,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Mauna Ulu Volcano","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -155.21106719970703,\n              19.37253100428563\n            ],\n            [\n              -155.1870346069336,\n              19.3741504184188\n            ],\n            [\n              -155.18394470214844,\n              19.35520226587889\n            ],\n            [\n              -155.20832061767578,\n              19.355364225230744\n            ],\n            [\n              -155.21106719970703,\n              19.37253100428563\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"208","noUsgsAuthors":false,"publicationDate":"2015-02-27","publicationStatus":"PW","scienceBaseUri":"563ddd41e4b0831b7d6271ed","contributors":{"editors":[{"text":"Carey, Rebecca","contributorId":121557,"corporation":false,"usgs":true,"family":"Carey","given":"Rebecca","affiliations":[],"preferred":false,"id":692144,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Cayol, Valerie","contributorId":121509,"corporation":false,"usgs":false,"family":"Cayol","given":"Valerie","email":"","affiliations":[],"preferred":false,"id":692145,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Poland, Michael P. 0000-0001-5240-6123 mpoland@usgs.gov","orcid":"https://orcid.org/0000-0001-5240-6123","contributorId":127857,"corporation":false,"usgs":true,"family":"Poland","given":"Michael","email":"mpoland@usgs.gov","middleInitial":"P.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":false,"id":692146,"contributorType":{"id":2,"text":"Editors"},"rank":3},{"text":"Weis, Dominique","contributorId":121531,"corporation":false,"usgs":true,"family":"Weis","given":"Dominique","affiliations":[],"preferred":false,"id":692147,"contributorType":{"id":2,"text":"Editors"},"rank":4}],"authors":[{"text":"Parcheta, Carolyn","contributorId":115234,"corporation":false,"usgs":true,"family":"Parcheta","given":"Carolyn","affiliations":[],"preferred":false,"id":518229,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fagents, Sarah","contributorId":116991,"corporation":false,"usgs":true,"family":"Fagents","given":"Sarah","affiliations":[],"preferred":false,"id":518230,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Swanson, Donald A. 0000-0002-1680-3591 donswan@usgs.gov","orcid":"https://orcid.org/0000-0002-1680-3591","contributorId":3137,"corporation":false,"usgs":true,"family":"Swanson","given":"Donald A.","email":"donswan@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":false,"id":518226,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Houghton, Bruce F. 0000-0002-7532-9770","orcid":"https://orcid.org/0000-0002-7532-9770","contributorId":140077,"corporation":false,"usgs":false,"family":"Houghton","given":"Bruce","email":"","middleInitial":"F.","affiliations":[{"id":13351,"text":"University of Hawaii Cooperative Studies Unit","active":true,"usgs":false},{"id":6977,"text":"University of Hawai`i at Hilo","active":true,"usgs":false}],"preferred":false,"id":518228,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ericksen, Todd","contributorId":25484,"corporation":false,"usgs":true,"family":"Ericksen","given":"Todd","affiliations":[],"preferred":false,"id":518227,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70146993,"text":"70146993 - 2015 - EverVIEW: a visualization platform for hydrologic and Earth science gridded data","interactions":[],"lastModifiedDate":"2015-04-24T11:47:41","indexId":"70146993","displayToPublicDate":"2015-03-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1315,"text":"Computers & Geosciences","printIssn":"0098-3004","active":true,"publicationSubtype":{"id":10}},"title":"EverVIEW: a visualization platform for hydrologic and Earth science gridded data","docAbstract":"<p><span>The EverVIEW Data Viewer is a cross-platform desktop application that combines and builds upon multiple open source libraries to help users to explore spatially-explicit gridded data stored in Network Common Data Form (NetCDF). Datasets are displayed across multiple side-by-side geographic or tabular displays, showing colorized overlays on an Earth globe or grid cell values, respectively. Time-series datasets can be animated to see how water surface elevation changes through time or how habitat suitability for a particular species might change over time under a given scenario. Initially targeted toward Florida's Everglades restoration planning, EverVIEW has been flexible enough to address the varied needs of large-scale planning beyond Florida, and is currently being used in biological planning efforts nationally and internationally.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.cageo.2014.12.004","usgsCitation":"Romañach, S., McKelvy, M., Suir, K.J., and Conzelmann, C., 2015, EverVIEW: a visualization platform for hydrologic and Earth science gridded data: Computers & Geosciences, v. 76, p. 88-95, https://doi.org/10.1016/j.cageo.2014.12.004.","productDescription":"8 p.","startPage":"88","endPage":"95","numberOfPages":"8","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056104","costCenters":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"links":[{"id":472245,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.cageo.2014.12.004","text":"Publisher Index Page"},{"id":299865,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"76","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"553b6945e4b0a658d79371bb","chorus":{"doi":"10.1016/j.cageo.2014.12.004","url":"http://dx.doi.org/10.1016/j.cageo.2014.12.004","publisher":"Elsevier BV","authors":"Romañach Stephanie S., McKelvy Mark, Suir Kevin, Conzelmann Craig","journalName":"Computers & Geosciences","publicationDate":"3/2015","auditedOn":"2/10/2015","publiclyAccessibleDate":"12/16/2014"},"contributors":{"authors":[{"text":"Romañach, Stephanie S. 0000-0003-0271-7825 sromanach@usgs.gov","orcid":"https://orcid.org/0000-0003-0271-7825","contributorId":138936,"corporation":false,"usgs":true,"family":"Romañach","given":"Stephanie S.","email":"sromanach@usgs.gov","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":false,"id":545554,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McKelvy, Mark 0000-0001-5465-2571 mckelvym@usgs.gov","orcid":"https://orcid.org/0000-0001-5465-2571","contributorId":4865,"corporation":false,"usgs":true,"family":"McKelvy","given":"Mark","email":"mckelvym@usgs.gov","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":545555,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Suir, Kevin J. 0000-0003-1570-9648 suirk@usgs.gov","orcid":"https://orcid.org/0000-0003-1570-9648","contributorId":4894,"corporation":false,"usgs":true,"family":"Suir","given":"Kevin","email":"suirk@usgs.gov","middleInitial":"J.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":545556,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Conzelmann, Craig 0000-0002-4227-8719 conzelmannc@usgs.gov","orcid":"https://orcid.org/0000-0002-4227-8719","contributorId":2361,"corporation":false,"usgs":true,"family":"Conzelmann","given":"Craig","email":"conzelmannc@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":545557,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70148597,"text":"70148597 - 2015 - The Red Atrapa Sismos (Quake Catcher Network in Mexico): assessing performance during large and damaging earthquakes.","interactions":[],"lastModifiedDate":"2015-06-26T12:39:02","indexId":"70148597","displayToPublicDate":"2015-03-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"The Red Atrapa Sismos (Quake Catcher Network in Mexico): assessing performance during large and damaging earthquakes.","docAbstract":"<p id=\"p-1\">The Quake‐Catcher Network (QCN) is an expanding seismic array made possible by thousands of participants who volunteered time and resources from their computers to record seismic data using low‐cost accelerometers (http://qcn.stanford.edu/; last accessed December 2014). Sensors based on Micro‐Electromechanical Systems (MEMS) technology have rapidly improved over the last few years due to the demand of the private sector (e.g., automobiles, cell phones, and laptops). For strong‐motion applications, low‐cost MEMS accelerometers have promising features due to an increasing resolution and near‐linear phase and amplitude response (<span class=\"xref-bibr\">Cochran, Lawrence, Christensen, and Jakka, 2009</span>;&nbsp;<span class=\"xref-bibr\">Clayton&nbsp;<i>et&nbsp;al.</i>, 2011</span>;&nbsp;<span class=\"xref-bibr\">Evans&nbsp;<i>et&nbsp;al.</i>, 2014</span>).</p>\n<p id=\"p-2\">Each volunteer computer monitors ground motion and communicates using the Berkeley Open Infrastructure for Network Computing (BOINC,&nbsp;<span class=\"xref-bibr\">Anderson, 2004</span>). Using a standard short‐term average, long‐term average (STLA) algorithm (<span class=\"xref-bibr\">Earle and Shearer, 1994</span>;&nbsp;<span class=\"xref-bibr\">Cochran, Lawrence, Christensen, Chung, 2009</span>;&nbsp;<span class=\"xref-bibr\">Cochran, Lawrence, Christensen, and Jakka, 2009</span>), volunteer computer and sensor systems detect abrupt changes in the acceleration recordings. Each time a possible trigger signal is declared, a small package of information containing sensor and ground‐motion information is streamed to one of the QCN servers (<span class=\"xref-bibr\">Chung&nbsp;<i>et&nbsp;al.</i>, 2011</span>). Trigger signals, correlated in space and time, are then processed by the QCN server to look for potential earthquakes.</p>","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220140171","usgsCitation":"Dominguez, L.A., Yildirim, B., Husker, A.L., Cochran, E.S., Christensen, C., and Cruz-Atienza, V., 2015, The Red Atrapa Sismos (Quake Catcher Network in Mexico): assessing performance during large and damaging earthquakes.: Seismological Research Letters, v. 86, no. 3, p. 848-855, https://doi.org/10.1785/0220140171.","productDescription":"8 p.","startPage":"848","endPage":"855","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059988","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":472248,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://resolver.caltech.edu/CaltechAUTHORS:20210518-133755918","text":"External Repository"},{"id":302510,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-97.14001,25.87],[-97.52807,24.99214],[-97.70295,24.27234],[-97.77604,22.93258],[-97.87237,22.44421],[-97.69904,21.89869],[-97.38896,21.41102],[-97.18933,20.63543],[-96.52558,19.89093],[-96.29213,19.32037],[-95.90088,18.82802],[-94.83906,18.56272],[-94.42573,18.14437],[-93.54865,18.42384],[-92.78611,18.52484],[-92.03735,18.70457],[-91.4079,18.87608],[-90.77187,19.28412],[-90.53359,19.86742],[-90.45148,20.70752],[-90.27862,20.99986],[-89.60132,21.26173],[-88.54387,21.49368],[-87.65842,21.45885],[-87.05189,21.54354],[-86.81198,21.33151],[-86.84591,20.84986],[-87.38329,20.2554],[-87.62105,19.64655],[-87.43675,19.4724],[-87.58656,19.04013],[-87.83719,18.25982],[-88.09066,18.51665],[-88.30003,18.49998],[-88.49012,18.48683],[-88.84834,17.8832],[-89.02986,18.00151],[-89.15091,17.95547],[-89.14308,17.80832],[-90.06793,17.81933],[-91.00152,17.81759],[-91.00227,17.25466],[-91.45392,17.25218],[-91.08167,16.91848],[-90.71182,16.68748],[-90.60085,16.47078],[-90.43887,16.41011],[-90.46447,16.06956],[-91.74796,16.06656],[-92.22925,15.25145],[-92.08722,15.06458],[-92.20323,14.8301],[-92.22775,14.53883],[-93.35946,15.61543],[-93.87517,15.94016],[-94.69166,16.20098],[-95.25023,16.12832],[-96.05338,15.75209],[-96.55743,15.65352],[-97.26359,15.91706],[-98.01303,16.10731],[-98.94768,16.56604],[-99.6974,16.70616],[-100.8295,17.17107],[-101.66609,17.64903],[-101.91853,17.91609],[-102.47813,17.97575],[-103.50099,18.29229],[-103.91753,18.74857],[-104.99201,19.31613],[-105.49304,19.94677],[-105.7314,20.4341],[-105.39777,20.53172],[-105.50066,20.8169],[-105.27075,21.07628],[-105.26582,21.4221],[-105.60316,21.87115],[-105.69341,22.26908],[-106.02872,22.77375],[-106.90998,23.76777],[-107.91545,24.54892],[-108.4019,25.17231],[-109.2602,25.58061],[-109.44409,25.82488],[-109.29164,26.44293],[-109.80146,26.67618],[-110.39173,27.16211],[-110.64102,27.85988],[-111.17892,27.94124],[-111.75961,28.46795],[-112.22823,28.95441],[-112.27182,29.26684],[-112.80959,30.02111],[-113.16381,30.78688],[-113.14867,31.17097],[-113.87188,31.56761],[-114.20574,31.52405],[-114.77645,31.79953],[-114.9367,31.39348],[-114.77123,30.91362],[-114.6739,30.16268],[-114.33097,29.75043],[-113.58888,29.06161],[-113.42405,28.82617],[-113.27197,28.75478],[-113.14004,28.41129],[-112.9623,28.42519],[-112.76159,27.78022],[-112.45791,27.52581],[-112.24495,27.17173],[-111.61649,26.66282],[-111.28467,25.73259],[-110.98782,25.29461],[-110.71001,24.826],[-110.65505,24.29859],[-110.17286,24.26555],[-109.77185,23.81118],[-109.4091,23.36467],[-109.43339,23.18559],[-109.85422,22.81827],[-110.03139,22.82308],[-110.29507,23.43097],[-110.9495,24.00096],[-111.67057,24.48442],[-112.18204,24.73841],[-112.14899,25.47013],[-112.30071,26.012],[-112.7773,26.32196],[-113.46467,26.76819],[-113.59673,26.63946],[-113.84894,26.90006],[-114.46575,27.14209],[-115.05514,27.72273],[-114.98225,27.7982],[-114.57037,27.74149],[-114.19933,28.115],[-114.16202,28.56611],[-114.93184,29.27948],[-115.51865,29.55636],[-115.88737,30.18079],[-116.25835,30.83646],[-116.72153,31.63574],[-117.12776,32.53534],[-115.99135,32.61239],[-114.72139,32.72083],[-114.815,32.52528],[-113.30498,32.03914],[-111.02361,31.33472],[-109.035,31.34194],[-108.24194,31.34222],[-108.24,31.75485],[-106.50759,31.75452],[-106.1429,31.39995],[-105.63159,31.08383],[-105.03737,30.64402],[-104.70575,30.12173],[-104.45697,29.57196],[-103.94,29.27],[-103.11,28.97],[-102.48,29.76],[-101.6624,29.7793],[-100.9576,29.38071],[-100.45584,28.69612],[-100.11,28.11],[-99.52,27.54],[-99.3,26.84],[-99.02,26.37],[-98.24,26.06],[-97.53,25.84],[-97.14001,25.87]]]},\"properties\":{\"name\":\"Mexico\"}}]}","volume":"86","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-03-11","publicationStatus":"PW","scienceBaseUri":"558e77bee4b0b6d21dd65979","contributors":{"authors":[{"text":"Dominguez, Luis A.","contributorId":143832,"corporation":false,"usgs":false,"family":"Dominguez","given":"Luis","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":557245,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yildirim, Battalgazi","contributorId":141195,"corporation":false,"usgs":false,"family":"Yildirim","given":"Battalgazi","email":"","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":557246,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Husker, Allen L.","contributorId":143833,"corporation":false,"usgs":false,"family":"Husker","given":"Allen","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":557247,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cochran, Elizabeth S. 0000-0003-2485-4484 ecochran@usgs.gov","orcid":"https://orcid.org/0000-0003-2485-4484","contributorId":2025,"corporation":false,"usgs":true,"family":"Cochran","given":"Elizabeth","email":"ecochran@usgs.gov","middleInitial":"S.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":548815,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Christensen, Carl","contributorId":43562,"corporation":false,"usgs":true,"family":"Christensen","given":"Carl","affiliations":[],"preferred":false,"id":557248,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cruz-Atienza, Victor M.","contributorId":69387,"corporation":false,"usgs":true,"family":"Cruz-Atienza","given":"Victor M.","affiliations":[],"preferred":false,"id":557249,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70195567,"text":"70195567 - 2015 - Robust estimates of environmental effects on population vital rates: an integrated capture–recapture model of seasonal brook trout growth, survival and movement in a stream network","interactions":[],"lastModifiedDate":"2018-07-09T12:11:49","indexId":"70195567","displayToPublicDate":"2015-03-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2158,"text":"Journal of Animal Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Robust estimates of environmental effects on population vital rates: an integrated capture–recapture model of seasonal brook trout growth, survival and movement in a stream network","docAbstract":"<ol id=\"jane12308-list-0001\" class=\"o-list--numbered o-list--paragraph\"><li>Modelling the effects of environmental change on populations is a key challenge for ecologists, particularly as the pace of change increases. Currently, modelling efforts are limited by difficulties in establishing robust relationships between environmental drivers and population responses.</li><li>We developed an integrated capture–recapture state-space model to estimate the effects of two key environmental drivers (stream flow and temperature) on demographic rates (body growth, movement and survival) using a long-term (11&nbsp;years), high-resolution (individually tagged, sampled seasonally) data set of brook trout (<i>Salvelinus fontinalis</i>) from four sites in a stream network. Our integrated model provides an effective context within which to estimate environmental driver effects because it takes full advantage of data by estimating (latent) state values for missing observations, because it propagates uncertainty among model components and because it accounts for the major demographic rates and interactions that contribute to annual survival.</li><li>We found that stream flow and temperature had strong effects on brook trout demography. Some effects, such as reduction in survival associated with low stream flow and high temperature during the summer season, were consistent across sites and age classes, suggesting that they may serve as robust indicators of vulnerability to environmental change. Other survival effects varied across ages, sites and seasons, indicating that flow and temperature may not be the primary drivers of survival in those cases. Flow and temperature also affected body growth rates; these responses were consistent across sites but differed dramatically between age classes and seasons. Finally, we found that tributary and mainstem sites responded differently to variation in flow and temperature.</li><li>Annual survival (combination of survival and body growth across seasons) was insensitive to body growth and was most sensitive to flow (positive) and temperature (negative) in the summer and fall.</li><li>These observations, combined with our ability to estimate the occurrence, magnitude and direction of fish movement between these habitat types, indicated that heterogeneity in response may provide a mechanism providing potential resilience to environmental change. Given that the challenges we faced in our study are likely to be common to many intensive data sets, the integrated modelling approach could be generally applicable and useful.</li></ol>","language":"English","publisher":"Wiley","doi":"10.1111/1365-2656.12308","usgsCitation":"Letcher, B., Schueller, P., Bassar, R.D., Nislow, K.H., Coombs, J.A., Sakrejda, K., Morrissey, M., Sigourney, D.B., Whiteley, A.R., O'Donnell, M., and Dubreuil, T.L., 2015, Robust estimates of environmental effects on population vital rates: an integrated capture–recapture model of seasonal brook trout growth, survival and movement in a stream network: Journal of Animal Ecology, v. 84, no. 2, p. 337-352, https://doi.org/10.1111/1365-2656.12308.","productDescription":"16 p.","startPage":"337","endPage":"352","ipdsId":"IP-049123","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true},{"id":37273,"text":"Advanced Research Computing (ARC)","active":true,"usgs":true}],"links":[{"id":351877,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"84","issue":"2","noUsgsAuthors":false,"publicationDate":"2014-12-03","publicationStatus":"PW","scienceBaseUri":"5afeebcfe4b0da30c1bfc684","contributors":{"authors":[{"text":"Letcher, Benjamin H. 0000-0003-0191-5678 bletcher@usgs.gov","orcid":"https://orcid.org/0000-0003-0191-5678","contributorId":2864,"corporation":false,"usgs":true,"family":"Letcher","given":"Benjamin H.","email":"bletcher@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":729303,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schueller, Paul","contributorId":181829,"corporation":false,"usgs":false,"family":"Schueller","given":"Paul","email":"","affiliations":[],"preferred":false,"id":729304,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bassar, Ronald D.","contributorId":150154,"corporation":false,"usgs":false,"family":"Bassar","given":"Ronald","email":"","middleInitial":"D.","affiliations":[{"id":6932,"text":"University of Massachusetts, Amherst","active":true,"usgs":false}],"preferred":false,"id":729305,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nislow, Keith H.","contributorId":103564,"corporation":false,"usgs":true,"family":"Nislow","given":"Keith","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":729306,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Coombs, Jason A.","contributorId":77039,"corporation":false,"usgs":true,"family":"Coombs","given":"Jason","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":729307,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sakrejda, Krzysztof","contributorId":202679,"corporation":false,"usgs":false,"family":"Sakrejda","given":"Krzysztof","email":"","affiliations":[],"preferred":false,"id":729308,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Morrissey, Michael","contributorId":202680,"corporation":false,"usgs":false,"family":"Morrissey","given":"Michael","email":"","affiliations":[],"preferred":false,"id":729309,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sigourney, Douglas B.","contributorId":103068,"corporation":false,"usgs":true,"family":"Sigourney","given":"Douglas","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":729310,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Whiteley, Andrew R.","contributorId":52072,"corporation":false,"usgs":false,"family":"Whiteley","given":"Andrew","email":"","middleInitial":"R.","affiliations":[{"id":6932,"text":"University of Massachusetts, Amherst","active":true,"usgs":false}],"preferred":false,"id":729311,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"O'Donnell, Matthew J. 0000-0002-9089-2377 mjodonnell@usgs.gov","orcid":"https://orcid.org/0000-0002-9089-2377","contributorId":138979,"corporation":false,"usgs":true,"family":"O'Donnell","given":"Matthew J.","email":"mjodonnell@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":729312,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Dubreuil, Todd L. 0000-0003-0189-4336 tdubreuil@usgs.gov","orcid":"https://orcid.org/0000-0003-0189-4336","contributorId":5552,"corporation":false,"usgs":true,"family":"Dubreuil","given":"Todd","email":"tdubreuil@usgs.gov","middleInitial":"L.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":729313,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70168391,"text":"70168391 - 2015 - The importance of scaling for detecting community patterns: success and failure in assemblages of introduced species","interactions":[],"lastModifiedDate":"2016-08-31T16:00:07","indexId":"70168391","displayToPublicDate":"2015-03-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1398,"text":"Diversity","active":true,"publicationSubtype":{"id":10}},"title":"The importance of scaling for detecting community patterns: success and failure in assemblages of introduced species","docAbstract":"<p><span>Community saturation can help to explain why biological invasions fail. However, previous research has documented inconsistent relationships between failed invasions (</span><i>i.e</i><span>., an invasive species colonizes but goes extinct) and the number of species present in the invaded community. We use data from bird communities of the Hawaiian island of Oahu, which supports a community of 38 successfully established introduced birds and where 37 species were introduced but went extinct (failed invasions). We develop a modified approach to evaluate the effects of community saturation on invasion failure. Our method accounts (1) for the number of species present (NSP) when the species goes extinct rather than during its introduction; and (2) scaling patterns in bird body mass distributions that accounts for the hierarchical organization of ecosystems and the fact that interaction strength amongst species varies with scale. We found that when using NSP at the time of extinction, NSP was higher for failed introductions as compared to successful introductions, supporting the idea that increasing species richness and putative community saturation mediate invasion resistance. Accounting for scale-specific patterns in body size distributions further improved the relationship between NSP and introduction failure. Results show that a better understanding of invasion outcomes can be obtained when scale-specific community structure is accounted for in the analysis.</span></p>","language":"English","publisher":"MDPI","doi":"10.3390/d7030229","usgsCitation":"Allen, C.R., Angeler, D., Moulton, M.P., and Holling, C.S., 2015, The importance of scaling for detecting community patterns: success and failure in assemblages of introduced species: Diversity, v. 7, no. 3, p. 229-241, https://doi.org/10.3390/d7030229.","productDescription":"13 p.","startPage":"229","endPage":"241","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066119","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":472251,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/d7030229","text":"Publisher Index Page"},{"id":317933,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Oahu","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -157.89962768554685, 21.624239377938288 ], [ -157.87216186523438, 21.59231986280347 ], [ -157.85568237304688, 21.5731647743054 ], [ -157.82958984375, 21.542511366159946 ], [ -157.82958984375, 21.5080185422074 ], [ -157.8364562988281, 21.49013015124931 ], [ -157.82546997070312, 21.478629309978384 ], [ -157.81173706054688, 21.46968358313921 ], [ -157.78701782226562, 21.46968358313921 ], [ -157.76779174804688, 21.47735138264276 ], [ -157.73895263671875, 21.47223956115867 ], [ -157.71697998046875, 21.47096157775494 ], [ -157.71697998046875, 21.444121337131314 ], [ -157.72796630859372, 21.422389905231366 ], [ -157.70736694335938, 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Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":619857,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Angeler, David G.","contributorId":25027,"corporation":false,"usgs":true,"family":"Angeler","given":"David G.","affiliations":[],"preferred":false,"id":619881,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Moulton, Michael P.","contributorId":166723,"corporation":false,"usgs":false,"family":"Moulton","given":"Michael","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":619882,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Holling, Crawford S.","contributorId":20511,"corporation":false,"usgs":true,"family":"Holling","given":"Crawford","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":619883,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70188044,"text":"70188044 - 2015 - Characterizing Congo Basin rainfall and climate using Tropical Rainfall Measuring Mission (TRMM) satellite data and limited rain gauge ground observations","interactions":[],"lastModifiedDate":"2017-05-31T16:09:14","indexId":"70188044","displayToPublicDate":"2015-03-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5202,"text":"Journal of Applied Meteorology and Climatology","onlineIssn":"1558-8432","printIssn":"1558-8424","active":true,"publicationSubtype":{"id":10}},"title":"Characterizing Congo Basin rainfall and climate using Tropical Rainfall Measuring Mission (TRMM) satellite data and limited rain gauge ground observations","docAbstract":"<p><span>Quantitative understanding of Congo River basin hydrological behavior is poor because of the basin’s limited hydrometeorological observation network. In cases such as the Congo basin where ground data are scarce, satellite-based estimates of rainfall, such as those from the joint NASA/JAXA Tropical Rainfall Measuring Mission (TRMM), can be used to quantify rainfall patterns. This study tests and reports the use of limited rainfall gauge data within the Democratic Republic of Congo (DRC) to recalibrate a TRMM science product (TRMM 3B42, version 6) in characterizing precipitation and climate in the Congo basin. Rainfall estimates from TRMM 3B42, version 6, are compared and adjusted using ground precipitation data from 12 DRC meteorological stations from 1998 to 2007. Adjustment is achieved on a monthly scale by using a regression-tree algorithm. The output is a new, basin-specific estimate of monthly and annual rainfall and climate types across the Congo basin. This new product and the latest version-7 TRMM 3B43 science product are validated by using an independent long-term dataset of historical isohyets. Standard errors of the estimate, root-mean-square errors, and regression coefficients </span><i>r</i><span> were slightly and uniformly better with the recalibration from this study when compared with the 3B43 product (mean monthly standard errors of 31 and 40 mm of precipitation and mean </span><i>r</i><sup>2</sup><span> of 0.85 and 0.82, respectively), but the 3B43 product was slightly better in terms of bias estimation (1.02 and 1.00). Despite reasonable doubts that have been expressed in studies of other tropical regions, within the Congo basin the TRMM science product (3B43) performed in a manner that is comparable to the performance of the recalibrated product that is described in this study.</span></p>","language":"English","publisher":"American Meteorological Society","doi":"10.1175/JAMC-D-14-0052.1","usgsCitation":"Munzimi, Y.A., Hansen, M.C., Adusei, B., and Senay, G., 2015, Characterizing Congo Basin rainfall and climate using Tropical Rainfall Measuring Mission (TRMM) satellite data and limited rain gauge ground observations: Journal of Applied Meteorology and Climatology, v. 54, p. 541-555, https://doi.org/10.1175/JAMC-D-14-0052.1.","productDescription":"15 p.","startPage":"541","endPage":"555","ipdsId":"IP-061697","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":341878,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Congo Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              12,\n              -13\n            ],\n            [\n              35,\n              -13\n            ],\n            [\n              35,\n              10\n            ],\n            [\n              12,\n              10\n            ],\n            [\n              12,\n              -13\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"54","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"592e84bde4b092b266f10d4b","contributors":{"authors":[{"text":"Munzimi, Yolande A.","contributorId":192431,"corporation":false,"usgs":false,"family":"Munzimi","given":"Yolande","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":696495,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hansen, Matthew C.","contributorId":192036,"corporation":false,"usgs":false,"family":"Hansen","given":"Matthew","email":"","middleInitial":"C.","affiliations":[{"id":12623,"text":"State University of New York College of Environmental Science and Forestry","active":true,"usgs":false},{"id":5089,"text":"South Dakota State University","active":true,"usgs":false}],"preferred":false,"id":696496,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Adusei, Bernard","contributorId":192432,"corporation":false,"usgs":false,"family":"Adusei","given":"Bernard","email":"","affiliations":[],"preferred":false,"id":696497,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Senay, Gabriel B. 0000-0002-8810-8539 senay@usgs.gov","orcid":"https://orcid.org/0000-0002-8810-8539","contributorId":152206,"corporation":false,"usgs":true,"family":"Senay","given":"Gabriel B.","email":"senay@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":696308,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70155113,"text":"70155113 - 2015 - Identifying the location and population served by domestic wells in California","interactions":[],"lastModifiedDate":"2015-08-05T13:10:48","indexId":"70155113","displayToPublicDate":"2015-03-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3823,"text":"Journal of Hydrology: Regional Studies","active":true,"publicationSubtype":{"id":10}},"title":"Identifying the location and population served by domestic wells in California","docAbstract":"<h4 id=\"absSec_1\">Study region</h4>\n<p id=\"spar0005\">California, USA.</p>\n<h4 id=\"absSec_2\">Study focus</h4>\n<p id=\"spar0010\">Identification of groundwater use is an important step in the regional-scale assessment of groundwater quality. In California, 1990 US Census data indicate that domestic wells provide drinking-water to about 1.2 million people. However, the location of these domestic well users of groundwater is poorly identified because the census tracts can be quite large (up to 20,000&nbsp;km<sup>2</sup>). The purposes of this paper are to present methods used for (1) estimating the location of domestic wells, (2) estimating the location of households using domestic well water; and (3) identifying where in California groundwater is an important source of domestic drinking supply.</p>\n<h4 id=\"absSec_3\">New hydrological insights for the region</h4>\n<p id=\"spar0015\">Aggregating the results indicates that three hydrogeologic provinces contain nearly 80% of all domestic wells and also have the highest density of domestic well users: Central Valley (31.6%), Sierra Nevada (31.5%), and Northern Coast Ranges (16.6%). Results were also aggregated into groundwater basins and highland areas, collectively called Groundwater Units (GUs). Twenty-eight of the 938 GUs contain more than 50% of the total population served by domestic wells, 70 GUs contain more than 75%, and 150 GUs contain 90%. The 28 GUs are mostly located in the eastern and southern San Joaquin Valley (11), the Sacramento Valley (7), and the western foothills of the Sierra Nevada province (5). Using the information presented in this research along with other information about domestic-well use, the US Geological Survey has begun sampling high-use GUs for the Shallow Aquifer Assessment component of the Groundwater Ambient Assessment (GAMA) program.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ejrh.2014.09.002","usgsCitation":"Johnson, T.D., and Belitz, K., 2015, Identifying the location and population served by domestic wells in California: Journal of Hydrology: Regional Studies, v. 3, p. 31-86, https://doi.org/10.1016/j.ejrh.2014.09.002.","productDescription":"56 p.","startPage":"31","endPage":"86","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-055416","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":472243,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ejrh.2014.09.002","text":"Publisher Index 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Program","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":564808,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70156234,"text":"70156234 - 2015 - Equation-free modeling unravels the behavior of complex ecological systems","interactions":[],"lastModifiedDate":"2015-08-19T10:55:00","indexId":"70156234","displayToPublicDate":"2015-03-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2982,"text":"PNAS","active":true,"publicationSubtype":{"id":10}},"title":"Equation-free modeling unravels the behavior of complex ecological systems","docAbstract":"<p>Ye et al. (1) address a critical problem confronting the management of natural ecosystems: How can we make forecasts of possible future changes in populations to help guide management actions? This problem is especially acute for marine and anadromous fisheries, where the large interannual fluctuations of populations, arising from complex nonlinear interactions among species and with varying environmental factors, have defied prediction over even short time scales. The empirical dynamic modeling (EDM) described in Ye et al.&rsquo;s report, the latest in a series of papers by Sugihara and his colleagues, offers a promising quantitative approach to building models using time series to successfully project dynamics into the future. With the term &ldquo;equation-free&rdquo; in the article title, Ye et al. (1) are suggesting broader implications of their approach, considering the centrality of equations in modern science. From the 1700s on, nature has been increasingly described by mathematical equations, with differential or difference equations forming the basic framework for describing dynamics. The use of mathematical equations for ecological systems came much later, pioneered by Lotka and Volterra, who showed that population cycles might be described in terms of simple coupled nonlinear differential equations. It took decades for Lotka&ndash;Volterra-type models to become established, but the development of appropriate differential equations is now routine in modeling ecological dynamics. There is no question that the injection of mathematical equations, by forcing &ldquo;clarity and precision into conjecture&rdquo; (2), has led to increased understanding of population and community dynamics. As in science in general, in ecology equations are a key method of communication and of framing hypotheses. These equations serve as compact representations of an enormous amount of empirical data and can be analyzed by the powerful methods of mathematics.</p>","language":"English","publisher":"National Academy of Sciences of the United States of America","doi":"10.1073/pnas.1503154112","usgsCitation":"DeAngelis, D., and Yurek, S., 2015, Equation-free modeling unravels the behavior of complex ecological systems: PNAS, v. 112, no. 13, p. 3856-3857, https://doi.org/10.1073/pnas.1503154112.","productDescription":"2 p.","startPage":"3856","endPage":"3857","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063709","costCenters":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"links":[{"id":472255,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1073/pnas.1503154112","text":"Publisher Index Page"},{"id":306924,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"112","issue":"13","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2015-03-17","publicationStatus":"PW","scienceBaseUri":"55d5a8afe4b0518e3546a4be","chorus":{"doi":"10.1073/pnas.1503154112","url":"http://dx.doi.org/10.1073/pnas.1503154112","publisher":"Proceedings of the National Academy of Sciences","authors":"DeAngelis Donald L., Yurek Simeon","journalName":"Proceedings of the National Academy of Sciences","publicationDate":"3/17/2015"},"contributors":{"authors":[{"text":"DeAngelis, Donald L. 0000-0002-1570-4057 don_deangelis@usgs.gov","orcid":"https://orcid.org/0000-0002-1570-4057","contributorId":138934,"corporation":false,"usgs":true,"family":"DeAngelis","given":"Donald L.","email":"don_deangelis@usgs.gov","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":false,"id":568114,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yurek, Simeon 0000-0002-6209-7915 syurek@usgs.gov","orcid":"https://orcid.org/0000-0002-6209-7915","contributorId":103167,"corporation":false,"usgs":true,"family":"Yurek","given":"Simeon","email":"syurek@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":568568,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70154774,"text":"70154774 - 2015 - Turbidity, light, temperature, and hydropeaking control primary productivity in the Colorado River, Grand Canyon","interactions":[],"lastModifiedDate":"2022-11-14T17:37:39.358873","indexId":"70154774","displayToPublicDate":"2015-03-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2620,"text":"Limnology and Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"Turbidity, light, temperature, and hydropeaking control primary productivity in the Colorado River, Grand Canyon","docAbstract":"<p><span>Dams and river regulation greatly alter the downstream environment for gross primary production (GPP) because of changes in water clarity, flow, and temperature regimes. We estimated reach-scale GPP in five locations of the regulated Colorado River in Grand Canyon using an open channel model of dissolved oxygen. Benthic GPP dominates in Grand Canyon due to fast transport times and low pelagic algal biomass. In one location, we used a 738 days time series of GPP to identify the relative contribution of different physical controls of GPP. We developed both linear and semimechanistic time series models that account for unmeasured temporal covariance due to factors such as algal biomass dynamics. GPP varied from 0 g O</span><sub>2</sub><span>&nbsp;m</span><sup>−2</sup><span>&nbsp;d</span><sup>−1</sup><span>&nbsp;to 3.0 g O</span><sub>2</sub><span>&nbsp;m</span><sup>−2</sup><span>&nbsp;d</span><sup>−1</sup><span>&nbsp;with a relatively low annual average of 0.8 g O</span><sub>2</sub><span>&nbsp;m</span><sup>−2</sup><span>&nbsp;d</span><sup>−1</sup><span>. Semimechanistic models fit the data better than linear models and demonstrated that variation in turbidity primarily controlled GPP. Lower solar insolation during winter and from cloud cover lowered GPP much further. Hydropeaking lowered GPP but only during turbid conditions. Using the best model and parameter values, the model accurately predicted seasonal estimates of GPP at 3 of 4 upriver sites and outperformed the linear model at all sites; discrepancies were likely from higher algal biomass at upstream sites. This modeling approach can predict how changes in physical controls will affect relative rates of GPP throughout the 385 km segment of the Colorado River in Grand Canyon and can be easily applied to other streams and rivers.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/lno.10031","usgsCitation":"Hall, R., Yackulic, C.B., Kennedy, T., Yard, M., Rosi-Marshall, E.J., Voichick, N., and Behn, K.E., 2015, Turbidity, light, temperature, and hydropeaking control primary productivity in the Colorado River, Grand Canyon: Limnology and Oceanography, v. 60, no. 2, p. 512-516, https://doi.org/10.1002/lno.10031.","productDescription":"5 p.","startPage":"512","endPage":"516","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056074","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":472242,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/lno.10031","text":"Publisher Index Page"},{"id":306634,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Colorado River, Grand Canyon","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -111.97690643788997,\n              35.96223553892966\n            ],\n            [\n              -111.95607071326728,\n              36.15089215745617\n            ],\n            [\n              -112.47488025637692,\n              36.439732993660684\n            ],\n            [\n              -113.00202408933613,\n              36.35587791388548\n            ],\n            [\n              -113.62917940048527,\n              35.88968479994075\n            ],\n            [\n              -113.53125149475788,\n              35.705479139380046\n            ],\n            [\n              -113.28747351666969,\n              35.724088071319485\n            ],\n            [\n              -113.16870988631914,\n              35.9959573825395\n            ],\n            [\n              -112.61031246642614,\n              36.256812611305506\n            ],\n            [\n              -111.97690643788997,\n              35.96223553892966\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"60","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-01-30","publicationStatus":"PW","scienceBaseUri":"55cdbfc0e4b08400b1fe1456","chorus":{"doi":"10.1002/lno.10031","url":"http://dx.doi.org/10.1002/lno.10031","publisher":"Wiley-Blackwell","authors":"Hall Robert O., Yackulic Charles B., Kennedy Theodore A., Yard Michael D., Rosi-Marshall Emma J., Voichick Nicholas, Behn Kathrine E.","journalName":"Limnology and Oceanography","publicationDate":"1/30/2015","auditedOn":"1/29/2017","publiclyAccessibleDate":"1/30/2015"},"contributors":{"authors":[{"text":"Hall, Robert O. Jr.","contributorId":145459,"corporation":false,"usgs":false,"family":"Hall","given":"Robert O.","suffix":"Jr.","affiliations":[{"id":16121,"text":"Uni. of Wyoming, Department of Zoology and Physiology","active":true,"usgs":false}],"preferred":false,"id":564095,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yackulic, Charles B. 0000-0001-9661-0724 cyackulic@usgs.gov","orcid":"https://orcid.org/0000-0001-9661-0724","contributorId":4662,"corporation":false,"usgs":true,"family":"Yackulic","given":"Charles","email":"cyackulic@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":564094,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kennedy, Theodore A. tkennedy@usgs.gov","contributorId":140027,"corporation":false,"usgs":true,"family":"Kennedy","given":"Theodore A.","email":"tkennedy@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":false,"id":564096,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Yard, Michael D. 0000-0002-6580-6027 myard@usgs.gov","orcid":"https://orcid.org/0000-0002-6580-6027","contributorId":2889,"corporation":false,"usgs":true,"family":"Yard","given":"Michael D.","email":"myard@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":false,"id":564097,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rosi-Marshall, Emma J.","contributorId":17722,"corporation":false,"usgs":true,"family":"Rosi-Marshall","given":"Emma","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":564098,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Voichick, Nicholas nvoichick@usgs.gov","contributorId":5015,"corporation":false,"usgs":true,"family":"Voichick","given":"Nicholas","email":"nvoichick@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":564099,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Behn, Kathrine E.","contributorId":83839,"corporation":false,"usgs":true,"family":"Behn","given":"Kathrine","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":564100,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70174829,"text":"70174829 - 2015 - Quantifying suspended sediment loads delivered to Cheney Reservoir, Kansas: Temporal patterns and management implications","interactions":[],"lastModifiedDate":"2016-07-18T11:37:50","indexId":"70174829","displayToPublicDate":"2015-03-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2456,"text":"Journal of Soil and Water Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Quantifying suspended sediment loads delivered to Cheney Reservoir, Kansas: Temporal patterns and management implications","docAbstract":"<p><span>Cheney Reservoir, constructed during 1962 to 1965, is the primary water supply for the city of Wichita, the largest city in Kansas. Sediment is an important concern for the reservoir as it degrades water quality and progressively decreases water storage capacity. Long-term data collection provided a unique opportunity to estimate the annual suspended sediment loads for the entire history of the reservoir. To quantify and characterize sediment loading to Cheney Reservoir, discrete suspended sediment samples and continuously measured streamflow data were collected from the North Fork Ninnescah River, the primary inflow to Cheney Reservoir, over a 48-year period. Continuous turbidity data also were collected over a 15-year period. These data were used together to develop simple linear regression models to compute continuous suspended sediment concentrations and loads from 1966 to 2013. The inclusion of turbidity as an additional explanatory variable with streamflow improved regression model diagnostics and increased the amount of variability in suspended sediment concentration explained by 14%. Using suspended sediment concentration from the streamflow-only model, the average annual suspended sediment load was 102,517 t (113,006 tn) and ranged from 4,826 t (5,320 tn) in 1966 to 967,569 t (1,066,562 tn) in 1979. The sediment load in 1979 accounted for about 20% of the total load over the 48-year history of the reservoir and 92% of the 1979 sediment load occurred in one 24-hour period during a 1% annual exceedance probability flow event (104-year flood). Nearly 60% of the reservoir sediment load during the 48-year study period occurred in 5 years with extreme flow events (9% to 1% annual exceedance probability, or 11- to 104-year flood events). A substantial portion (41%) of sediment was transported to the reservoir during five storm events spanning only eight 24-hour periods during 1966 to 2013. Annual suspended sediment load estimates based on streamflow were, on average, within &plusmn;20% of estimates based on streamflow and turbidity combined. Results demonstrate that large suspended sediment loads are delivered to Cheney Reservoir in very short time periods, indicating that sediment management plans eventually must address large, infrequent inflow events to be effective.</span></p>","language":"English","publisher":"Soil and Water Conservation Society","doi":"10.2489/jswc.70.2.91","usgsCitation":"Stone, M.L., Juracek, K.E., Graham, J., and Foster, G.M., 2015, Quantifying suspended sediment loads delivered to Cheney Reservoir, Kansas: Temporal patterns and management implications: Journal of Soil and Water Conservation, v. 70, no. 2, p. 91-100, https://doi.org/10.2489/jswc.70.2.91.","productDescription":"10 p.","startPage":"91","endPage":"100","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-058102","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":472250,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2489/jswc.70.2.91","text":"Publisher Index Page"},{"id":325358,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Kansas","otherGeospatial":"Cheney Reservoir Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -99.0692138671875,\n              37.67077737288316\n            ],\n            [\n              -99.0692138671875,\n              38.01564013749379\n            ],\n            [\n              -97.77145385742188,\n              38.01564013749379\n            ],\n            [\n              -97.77145385742188,\n              37.67077737288316\n            ],\n            [\n              -99.0692138671875,\n              37.67077737288316\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"70","issue":"2","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2015-03-12","publicationStatus":"PW","scienceBaseUri":"578dfdb8e4b0f1bea0e0f8e1","contributors":{"authors":[{"text":"Stone, Mandy L. 0000-0002-6711-1536 mstone@usgs.gov","orcid":"https://orcid.org/0000-0002-6711-1536","contributorId":4409,"corporation":false,"usgs":true,"family":"Stone","given":"Mandy","email":"mstone@usgs.gov","middleInitial":"L.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":642667,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Juracek, Kyle E. 0000-0002-2102-8980 kjuracek@usgs.gov","orcid":"https://orcid.org/0000-0002-2102-8980","contributorId":2022,"corporation":false,"usgs":true,"family":"Juracek","given":"Kyle","email":"kjuracek@usgs.gov","middleInitial":"E.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":642668,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Graham, Jennifer L. 0000-0002-6420-9335 jlgraham@usgs.gov","orcid":"https://orcid.org/0000-0002-6420-9335","contributorId":150737,"corporation":false,"usgs":true,"family":"Graham","given":"Jennifer L.","email":"jlgraham@usgs.gov","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":false,"id":642669,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Foster, Guy M. 0000-0002-9581-057X gfoster@usgs.gov","orcid":"https://orcid.org/0000-0002-9581-057X","contributorId":149145,"corporation":false,"usgs":true,"family":"Foster","given":"Guy","email":"gfoster@usgs.gov","middleInitial":"M.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":642670,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70193750,"text":"70193750 - 2015 - Advances in interpretation of subsurface processes with time-lapse electrical imaging","interactions":[],"lastModifiedDate":"2018-09-04T15:44:06","indexId":"70193750","displayToPublicDate":"2015-03-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Advances in interpretation of subsurface processes with time-lapse electrical imaging","docAbstract":"<p><span>Electrical geophysical methods, including electrical resistivity, time-domain induced polarization, and complex resistivity, have become commonly used to image the near subsurface. Here, we outline their utility for time-lapse imaging of hydrological, geochemical, and biogeochemical processes, focusing on new instrumentation, processing, and analysis techniques specific to monitoring. We review data collection procedures, parameters measured, and petrophysical relationships and then outline the state of the science with respect to inversion methodologies, including coupled inversion. We conclude by highlighting recent research focused on innovative applications of time-lapse imaging in hydrology, biology, ecology, and geochemistry, among other areas of interest.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/hyp.10280","usgsCitation":"Singha, K., Day-Lewis, F.D., Johnson, T.B., and Slater, L., 2015, Advances in interpretation of subsurface processes with time-lapse electrical imaging: Hydrological Processes, v. 29, no. 6, p. 1549-1576, https://doi.org/10.1002/hyp.10280.","productDescription":"18 p.","startPage":"1549","endPage":"1576","ipdsId":"IP-057740","costCenters":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":349127,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"29","issue":"6","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2014-08-08","publicationStatus":"PW","scienceBaseUri":"5a60feaee4b06e28e9c2532d","contributors":{"authors":[{"text":"Singha, Kaminit","contributorId":199845,"corporation":false,"usgs":false,"family":"Singha","given":"Kaminit","email":"","affiliations":[],"preferred":false,"id":720189,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Day-Lewis, Frederick D. 0000-0003-3526-886X daylewis@usgs.gov","orcid":"https://orcid.org/0000-0003-3526-886X","contributorId":1672,"corporation":false,"usgs":true,"family":"Day-Lewis","given":"Frederick","email":"daylewis@usgs.gov","middleInitial":"D.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true}],"preferred":true,"id":720188,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Tim B.","contributorId":127336,"corporation":false,"usgs":false,"family":"Johnson","given":"Tim","email":"","middleInitial":"B.","affiliations":[{"id":6780,"text":"Ontario Ministry of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":720190,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Slater, Lee D. 0000-0003-0292-746X","orcid":"https://orcid.org/0000-0003-0292-746X","contributorId":192555,"corporation":false,"usgs":false,"family":"Slater","given":"Lee D.","affiliations":[],"preferred":false,"id":720191,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70144704,"text":"70144704 - 2015 - Flow management and fish density regulate salmonid recruitment and adult size in tailwaters across western North America","interactions":[],"lastModifiedDate":"2015-12-21T13:16:57","indexId":"70144704","displayToPublicDate":"2015-03-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Flow management and fish density regulate salmonid recruitment and adult size in tailwaters across western North America","docAbstract":"<p class=\"first\">Rainbow and brown trout have been intentionally introduced into tailwaters downriver of dams globally and provide billions of dollars in economic benefits. At the same time, recruitment and maximum length of trout populations in tailwaters often fluctuate erratically, which negatively affects the value of fisheries. Large recruitment events may increase dispersal downriver where other fish species may be a priority (e.g., endangered species). There is an urgent need to understand the drivers of trout population dynamics in tailwaters, in particular the role of flow management. Here, we evaluate how flow, fish density, and other physical factors of the river influence recruitment and mean adult length in tailwaters across western North America using data from 29 dams spanning 1-19 years. Rainbow trout recruitment was negatively correlated with high annual, summer, and spring flow and dam latitude, and positively correlated with high winter flow, sub-adult brown trout catch, and reservoir storage capacity. Brown trout recruitment was negatively correlated with high water velocity and daily fluctuations in flow (i.e., hydropeaking) and positively correlated with adult rainbow trout catch. Among these many drivers, rainbow trout recruitment was primarily correlated with high winter flow combined with low spring flow, whereas brown trout recruitment was most related to high water velocity.</p>\n<p class=\"last\">The mean lengths of adult rainbow and brown trout were influenced by similar flow and catch metrics. Length in both species was positively correlated with high annual flow but declined in tailwaters with high daily fluctuations in flow, high catch rates of conspecifics, and when large cohorts recruited to adult size. Whereas brown trout did not respond to the proportion of water allocated between seasons, rainbow trout length increased in rivers that released more water during winter than in spring. Rainbow trout length was primarily related to high catch rates of conspecifics, whereas brown trout length was mainly related to large cohorts recruiting to the adult size class. Species-specific responses to flow management are likely attributable to differences in seasonal timing of key life history events such as spawning, egg hatching, and fry emergence.</p>","language":"English","publisher":"Ecological Society of America","doi":"10.1890/14-2211.1","usgsCitation":"Dibble, K.L., Yackulic, C.B., Kennedy, T., and Budy, P.E., 2015, Flow management and fish density regulate salmonid recruitment and adult size in tailwaters across western North America: Ecological Applications, v. 25, no. 8, p. 2168-2179, https://doi.org/10.1890/14-2211.1.","productDescription":"12 p.","startPage":"2168","endPage":"2179","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060840","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":438714,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F79P2ZQ2","text":"USGS data release","linkHelpText":"Flow management and fish density regulate salmonid recruitment and adult size in tailwaters across western North AmericaData"},{"id":299221,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -125.0244140625,\n              31.31610138349565\n            ],\n            [\n              -125.0244140625,\n              49.009050809382046\n            ],\n            [\n              -101.90917968749999,\n              49.009050809382046\n            ],\n            [\n              -101.90917968749999,\n              31.31610138349565\n            ],\n            [\n              -125.0244140625,\n              31.31610138349565\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"25","issue":"8","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"551bc52be4b0323842783a4a","contributors":{"authors":[{"text":"Dibble, Kimberly L. 0000-0003-0799-4477 kdibble@usgs.gov","orcid":"https://orcid.org/0000-0003-0799-4477","contributorId":5174,"corporation":false,"usgs":true,"family":"Dibble","given":"Kimberly","email":"kdibble@usgs.gov","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":543797,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yackulic, Charles B. 0000-0001-9661-0724 cyackulic@usgs.gov","orcid":"https://orcid.org/0000-0001-9661-0724","contributorId":4662,"corporation":false,"usgs":true,"family":"Yackulic","given":"Charles","email":"cyackulic@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":543798,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kennedy, Theodore A. tkennedy@usgs.gov","contributorId":3320,"corporation":false,"usgs":true,"family":"Kennedy","given":"Theodore A.","email":"tkennedy@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":false,"id":543799,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Budy, Phaedra E. pbudy@usgs.gov","contributorId":2232,"corporation":false,"usgs":true,"family":"Budy","given":"Phaedra","email":"pbudy@usgs.gov","middleInitial":"E.","affiliations":[{"id":322,"text":"Grand Canyon Monitoring and Research Center","active":false,"usgs":true}],"preferred":false,"id":543800,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70159501,"text":"70159501 - 2015 - Ahead of his time: Jacob Lipman's 1930 estimate of atmospheric sulfur deposition for the conterminous United States","interactions":[],"lastModifiedDate":"2015-11-09T12:50:15","indexId":"70159501","displayToPublicDate":"2015-03-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3419,"text":"Soil Science","active":true,"publicationSubtype":{"id":10}},"title":"Ahead of his time: Jacob Lipman's 1930 estimate of atmospheric sulfur deposition for the conterminous United States","docAbstract":"<p>A 1936 New Jersey Agricultural Experiment Station Bulletin provided an early quantitative assessment of atmospheric deposition of sulfur for the United States that has been compared in this study with more recent assessments. In the early 20th century, anthropogenic sulfur additions from the atmosphere to the soil by the combustion of fossil fuels were viewed as part of the requisite nutrient supply of crops. Jacob G. Lipman, the founding editor of Soil Science, and his team at Rutgers University, made an inventory of such additions to soils of the conterminous United States during the economic depression of the 1930s as part of a federally funded project looking at nutrient balances in soils. Lipman's team gathered data compiled by the US Bureau of Mines on coal and other fuel consumption by state and calculated the corresponding amounts of sulfur emitted. Their work pioneered a method of assessment that became the norm in the 1970s to 1980s&mdash;when acid rain emerged as a national issue. Lipman's estimate of atmospheric sulfur deposition in the 1930 is in reasonable agreement with recent historic reconstructions.</p>","language":"English","publisher":"Wolters Kluwer","doi":"10.1097/SS.0000000000000118","usgsCitation":"Landa, E.R., and Shanley, J.B., 2015, Ahead of his time: Jacob Lipman's 1930 estimate of atmospheric sulfur deposition for the conterminous United States: Soil Science, v. 180, no. 3, p. 87-89, https://doi.org/10.1097/SS.0000000000000118.","productDescription":"3 p.","startPage":"87","endPage":"89","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063544","costCenters":[{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true}],"links":[{"id":311117,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n 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