{"pageNumber":"1427","pageRowStart":"35650","pageSize":"25","recordCount":184723,"records":[{"id":70189782,"text":"70189782 - 2014 - CyberShake-derived ground-motion prediction models for the Los Angeles region with application to earthquake early warning","interactions":[],"lastModifiedDate":"2017-07-26T11:02:38","indexId":"70189782","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1803,"text":"Geophysical Journal International","active":true,"publicationSubtype":{"id":10}},"title":"CyberShake-derived ground-motion prediction models for the Los Angeles region with application to earthquake early warning","docAbstract":"<p><span>Real-time applications such as earthquake early warning (EEW) typically use empirical ground-motion prediction equations (GMPEs) along with event magnitude and source-to-site distances to estimate expected shaking levels. In this simplified approach, effects due to finite-fault geometry, directivity and site and basin response are often generalized, which may lead to a significant under- or overestimation of shaking from large earthquakes (</span><i>M</i><span>&nbsp;&gt;&nbsp;6.5) in some locations. For enhanced site-specific ground-motion predictions considering 3-D wave-propagation effects, we develop support vector regression (SVR) models from the SCEC CyberShake low-frequency (&lt;0.5 Hz) and broad-band (0–10 Hz) data sets. CyberShake encompasses 3-D wave-propagation simulations of&nbsp;&gt;415&nbsp;000 finite-fault rupture scenarios (6.5 ≤<span>&nbsp;</span></span><i>M</i><span><span>&nbsp;</span>≤ 8.5) for southern California defined in UCERF 2.0. We use CyberShake to demonstrate the application of synthetic waveform data to EEW as a ‘proof of concept’, being aware that these simulations are not yet fully validated and might not appropriately sample the range of rupture uncertainty. Our regression models predict the maximum and the temporal evolution of instrumental intensity (MMI) at 71 selected test sites using only the hypocentre, magnitude and rupture ratio, which characterizes uni- and bilateral rupture propagation. Our regression approach is completely data-driven (where here the CyberShake simulations are considered data) and does not enforce pre-defined functional forms or dependencies among input parameters. The models were established from a subset (∼20&nbsp;per cent) of CyberShake simulations, but can explain MMI values of all&nbsp;&gt;400 k rupture scenarios with a standard deviation of about 0.4 intensity units. We apply our models to determine threshold magnitudes (and warning times) for various active faults in southern California that earthquakes need to exceed to cause at least ‘moderate’, ‘strong’ or ‘very strong’ shaking in the Los Angeles (LA) basin. These thresholds are used to construct a simple and robust EEW algorithm: to declare a warning, the algorithm only needs to locate the earthquake and to verify that the corresponding magnitude threshold is exceeded. The models predict that a relatively moderate<span>&nbsp;</span></span><i>M</i><span>6.5–7 earthquake along the Palos Verdes, Newport-Inglewood/Rose Canyon, Elsinore or San Jacinto faults with a rupture propagating towards LA could cause ‘very strong’ to ‘severe’ shaking in the LA basin; however, warning times for these events could exceed 30 s.</span></p>","language":"English","publisher":"Oxford Academic","doi":"10.1093/gji/ggu198","usgsCitation":"Bose, M., Graves, R., Gill, D., Callaghan, S., and Maechling, P.J., 2014, CyberShake-derived ground-motion prediction models for the Los Angeles region with application to earthquake early warning: Geophysical Journal International, v. 198, no. 3, p. 1438-1457, https://doi.org/10.1093/gji/ggu198.","productDescription":"20 p.","startPage":"1438","endPage":"1457","ipdsId":"IP-054646","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":473293,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1093/gji/ggu198","text":"External Repository"},{"id":344321,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"Los Angeles","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -119,\n              33\n            ],\n            [\n              -117,\n              33\n            ],\n            [\n              -117,\n              35\n            ],\n            [\n              -119,\n              35\n            ],\n            [\n              -119,\n              33\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"198","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2014-07-03","publicationStatus":"PW","scienceBaseUri":"5979aa58e4b0ec1a488b8c3f","contributors":{"authors":[{"text":"Bose, Maren","contributorId":195135,"corporation":false,"usgs":false,"family":"Bose","given":"Maren","affiliations":[],"preferred":false,"id":706331,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Graves, Robert 0000-0001-9758-453X rwgraves@usgs.gov","orcid":"https://orcid.org/0000-0001-9758-453X","contributorId":140738,"corporation":false,"usgs":true,"family":"Graves","given":"Robert","email":"rwgraves@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":706330,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gill, David","contributorId":195159,"corporation":false,"usgs":false,"family":"Gill","given":"David","email":"","affiliations":[],"preferred":false,"id":706332,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Callaghan, Scott","contributorId":195136,"corporation":false,"usgs":false,"family":"Callaghan","given":"Scott","email":"","affiliations":[],"preferred":false,"id":706333,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Maechling, Phillip J.","contributorId":117072,"corporation":false,"usgs":false,"family":"Maechling","given":"Phillip","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":706334,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70141751,"text":"70141751 - 2014 - Stratigraphy, structure and regional correlation of eastern Blue Ridge sequences in southern Virginia and northwestern North Carolina: an interim report from new USGS mapping","interactions":[],"lastModifiedDate":"2015-03-06T10:12:29","indexId":"70141751","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1724,"text":"GSA Field Guides","active":true,"publicationSubtype":{"id":10}},"title":"Stratigraphy, structure and regional correlation of eastern Blue Ridge sequences in southern Virginia and northwestern North Carolina: an interim report from new USGS mapping","docAbstract":"<p id=\"p-1\">Examination of key outcrops in the eastern Blue Ridge in southern Virginia and northwestern North Carolina is used to evaluate existing stratigraphic and structural models. Recent detailed mapping along the Blue Ridge Parkway and the eastern flank of the Mount Rogers massif provides the opportunity to (1) evaluate legacy data and interpretations and (2) formulate new ideas for regional correlation of eastern Blue Ridge geology.</p>\n<p id=\"p-2\">Lynchburg Group rocks in central Virginia (metagraywacke, quartzite, graphitic schist, amphibolite, and ultramafic rocks) carry southward along strike where they transition with other units. Wills Ridge Formation consists of graphitic schist, metagraywacke, and metaconglomerate, and marks the western boundary of the eastern Blue Ridge. The Ashe Formation consists of conglomeratic metagraywacke in southern Virginia, and mica gneiss, mica schist, and ultramafic rocks in North Carolina. The overlying Alligator Back Formation shows characteristic compositional pin-striped layers in mica gneiss, schist, and amphibolite.</p>\n<p id=\"p-3\">The contact between eastern Blue Ridge stratified rocks above Mesoproterozoic basement rocks is mostly faulted (Gossan Lead and Red Valley). The Callaway fault juxtaposes Ashe and Lynchburg rocks above Wills Ridge Formation. Alligator Back Formation rocks overlie Ashe and Lynchburg rocks along the Rock Castle Creek fault, which juxtaposes rocks of different metamorphism. The fault separates major structural domains: rocks with one penetrative foliation in the footwall, and pin-striped recrystallized compositional layering, superposed penetrative foliations, and cleavage characterize the hanging wall. These relationships are ambiguous along strike to the southwest, where the Ashe and Alligator Back formations are recrystallized at higher metamorphic grades.</p>","language":"English","publisher":"Geological Society of America","publisherLocation":"Boulder, CO","doi":"10.1130/2014.0035(07)","usgsCitation":"Carter, M.W., and Merschat, A.J., 2014, Stratigraphy, structure and regional correlation of eastern Blue Ridge sequences in southern Virginia and northwestern North Carolina: an interim report from new USGS mapping: GSA Field Guides, v. 35, p. 215-241, https://doi.org/10.1130/2014.0035(07).","productDescription":"27 p.","startPage":"215","endPage":"241","numberOfPages":"27","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-054099","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":298319,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina, Virginia","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -81.4581298828125,\n              36.45000844447082\n            ],\n            [\n              -81.4581298828125,\n              37.13842453422676\n            ],\n            [\n              -80.08209228515625,\n              37.13842453422676\n            ],\n            [\n              -80.08209228515625,\n              36.45000844447082\n            ],\n            [\n              -81.4581298828125,\n              36.45000844447082\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"35","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2014-04-01","publicationStatus":"PW","scienceBaseUri":"54faddbce4b02419550db6e2","contributors":{"authors":[{"text":"Carter, Mark W. 0000-0003-0460-7638 mcarter@usgs.gov","orcid":"https://orcid.org/0000-0003-0460-7638","contributorId":4808,"corporation":false,"usgs":true,"family":"Carter","given":"Mark","email":"mcarter@usgs.gov","middleInitial":"W.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":540998,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Merschat, Arthur J. 0000-0002-9314-4067 amerschat@usgs.gov","orcid":"https://orcid.org/0000-0002-9314-4067","contributorId":4556,"corporation":false,"usgs":true,"family":"Merschat","given":"Arthur","email":"amerschat@usgs.gov","middleInitial":"J.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":540999,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70156788,"text":"70156788 - 2014 - Forest ecosystem reorganization underway in the Southwestern US: A preview of widespread forest changes in the Anthropocene","interactions":[],"lastModifiedDate":"2018-02-20T13:39:35","indexId":"70156788","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":62,"text":"Proceedings","active":false,"publicationSubtype":{"id":1}},"seriesNumber":"RMRS-P-71","title":"Forest ecosystem reorganization underway in the Southwestern US: A preview of widespread forest changes in the Anthropocene","docAbstract":"<p>No abstract available.</p>","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Forest conservation and management in the Anthropocene: Conference proceedings","largerWorkSubtype":{"id":1,"text":"Federal Government Series"},"language":"English","publisher":"U.S. Department of Agriculture: Rocky Mountain Research Station","usgsCitation":"Allen, C.D., 2014, Forest ecosystem reorganization underway in the Southwestern US: A preview of widespread forest changes in the Anthropocene: Proceedings RMRS-P-71, 20 p.","productDescription":"20 p.","startPage":"103","endPage":"122","ipdsId":"IP-058454","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":351829,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":350429,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.fs.usda.gov/treesearch/pubs/46127"}],"publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afeee23e4b0da30c1bfc760","contributors":{"editors":[{"text":"Sample, V. Alaric","contributorId":33637,"corporation":false,"usgs":false,"family":"Sample","given":"V.","email":"","middleInitial":"Alaric","affiliations":[{"id":35996,"text":"Pinchot Institute for Conservation, Washington, DC","active":true,"usgs":false}],"preferred":false,"id":725488,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Bixler, R. Patrick","contributorId":98327,"corporation":false,"usgs":false,"family":"Bixler","given":"R.","email":"","middleInitial":"Patrick","affiliations":[{"id":35996,"text":"Pinchot Institute for Conservation, Washington, DC","active":true,"usgs":false}],"preferred":false,"id":725489,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"Allen, Craig D. 0000-0002-8777-5989 craig_allen@usgs.gov","orcid":"https://orcid.org/0000-0002-8777-5989","contributorId":2597,"corporation":false,"usgs":true,"family":"Allen","given":"Craig","email":"craig_allen@usgs.gov","middleInitial":"D.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":570547,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70173575,"text":"70173575 - 2014 - Self-confidence of anglers in identification of freshwater sport fish","interactions":[],"lastModifiedDate":"2016-06-13T14:55:20","indexId":"70173575","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1659,"text":"Fisheries Management and Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Self-confidence of anglers in identification of freshwater sport fish","docAbstract":"<p><span>Although several studies have focused on how well anglers identify species using replicas and pictures, there has been no study assessing the confidence that can be placed in angler's ability to identify recreationally important fish. Understanding factors associated with low self-confidence will be useful in tailoring education programmes to improve self-confidence in identifying common species. The purposes of this assessment were to quantify the confidence of recreational anglers to identify 13 commonly encountered warm water fish species and to relate self-confidence to species availability and angler experience. Significant variation was observed in anglers self-confidence among species and levels of self-declared skill, with greater confidence associated with greater skill and with greater exposure. This study of angler self-confidence strongly highlights the need for educational programmes that target lower skilled anglers and the importance of teaching all anglers about less common species, regardless of skill level.</span></p>","language":"English","publisher":"John Wiley & Sons","doi":"10.1111/fme.12094","usgsCitation":"Chizinski, C., Martin, D.R., and Pope, K.L., 2014, Self-confidence of anglers in identification of freshwater sport fish: Fisheries Management and Ecology, v. 21, no. 6, p. 448-453, https://doi.org/10.1111/fme.12094.","productDescription":"6 p.","startPage":"448","endPage":"453","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-054382","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":323511,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"21","issue":"6","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2014-10-22","publicationStatus":"PW","scienceBaseUri":"575fd930e4b04f417c2baa78","contributors":{"authors":[{"text":"Chizinski, C.J.","contributorId":50635,"corporation":false,"usgs":true,"family":"Chizinski","given":"C.J.","email":"","affiliations":[],"preferred":false,"id":638579,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Martin, D. R.","contributorId":171766,"corporation":false,"usgs":false,"family":"Martin","given":"D.","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":638580,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pope, Kevin L. 0000-0003-1876-1687 kpope@usgs.gov","orcid":"https://orcid.org/0000-0003-1876-1687","contributorId":1574,"corporation":false,"usgs":true,"family":"Pope","given":"Kevin","email":"kpope@usgs.gov","middleInitial":"L.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":637357,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70188053,"text":"70188053 - 2014 - A design for a sustained assessment of climate forcings and feedbacks on land use land cover change","interactions":[],"lastModifiedDate":"2017-05-30T13:53:35","indexId":"70188053","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1112,"text":"Bulletin of the American Meteorological Society","onlineIssn":"1520-0477","printIssn":"0003-0007","active":true,"publicationSubtype":{"id":10}},"title":"A design for a sustained assessment of climate forcings and feedbacks on land use land cover change","docAbstract":"<p><span>Land use and land cover change (LULCC) significantly influences the climate system. Hence, to prepare the nation for future climate change and variability, a sustained assessment of LULCC and its climatic impacts needs to be undertaken. To address this objective, not only do we need to determine contemporary trends in land use and land cover that affect, or are affected by, weather and climate but also identify sectors and regions that are most affected by weather and climate variability. Moreover, it is critical that we recognize land cover and regions that are most vulnerable to climate change and how end-use practices are adapting to climate change. This paper identifies a series of steps that need to be undertaken to address these key items. In addition, national-scale institutional capabilities are identified and discussed. Included in the discussions are challenges and opportunities for collaboration among these institutions for a sustained assessment.</span></p>","language":"English","publisher":"American Meteorological Society","doi":"10.1175/BAMS-D-12-00208.1","usgsCitation":"Loveland, T., and Mahmood, R., 2014, A design for a sustained assessment of climate forcings and feedbacks on land use land cover change: Bulletin of the American Meteorological Society, v. 95, p. 1563-1572, https://doi.org/10.1175/BAMS-D-12-00208.1.","productDescription":"10 p.","startPage":"1563","endPage":"1572","ipdsId":"IP-055002","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":473302,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1175/bams-d-12-00208.1","text":"Publisher Index Page"},{"id":341866,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"95","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"592e84c7e4b092b266f10da9","contributors":{"authors":[{"text":"Loveland, Thomas 0000-0003-3114-6646 loveland@usgs.gov","orcid":"https://orcid.org/0000-0003-3114-6646","contributorId":140611,"corporation":false,"usgs":true,"family":"Loveland","given":"Thomas","email":"loveland@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":696331,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mahmood, Rezaul","contributorId":34376,"corporation":false,"usgs":true,"family":"Mahmood","given":"Rezaul","affiliations":[],"preferred":false,"id":696332,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70187708,"text":"70187708 - 2014 - Monitoring conterminous United States (CONUS) land cover change with Web-Enabled Landsat Data (WELD)","interactions":[],"lastModifiedDate":"2017-05-31T16:12:20","indexId":"70187708","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"Monitoring conterminous United States (CONUS) land cover change with Web-Enabled Landsat Data (WELD)","docAbstract":"<p>Forest cover loss and bare ground gain from 2006 to 2010 for the conterminous United States (CONUS) were quantified at a 30 m spatial resolution using Web-Enabled Landsat Data available from the USGS Center for Earth Resources Observation and Science (EROS) (http://landsat.usgs.gov/WELD.php). The approach related multi-temporal WELD metrics and expert-derived training data for forest cover loss and bare ground gain through a decision tree classification algorithm. Forest cover loss was reported at state and ecoregional scales, and the identification of core forests' absent of change was made and verified using LiDAR data from the GLAS (Geoscience Laser Altimetry System) instrument. Bare ground gain correlated with population change for large metropolitan statistical areas (MSAs) outside of desert or semi-desert environments. GoogleEarth™ time-series images were used to validate the products. Mapped forest cover loss totaled 53,084 km2 and was found to be depicted conservatively, with a user's accuracy of 78% and a producer's accuracy of 68%. Excluding errors of adjacency, user's and producer's accuracies rose to 93% and 89%, respectively. Mapped bare ground gain equaled 5974 km2 and nearly matched the estimated area from the reference (GoogleEarth™) classification; however, user's (42%) and producer's (49%) accuracies were much less than those of the forest cover loss product. Excluding errors of adjacency, user's and producer's accuracies rose to 62% and 75%, respectively. Compared to recent 2001–2006 USGS National Land Cover Database validation data for forest loss (82% and 30% for respective user's and producer's accuracies) and urban gain (72% and 18% for respective user's and producer's accuracies), results using a single CONUS-scale model with WELD data are promising and point to the potential for national-scale operational mapping of key land cover transitions. However, validation results highlighted limitations, some of which can be addressed by improving training data, creating a more robust image feature space, adding contemporaneous Landsat 5 data to the inputs, and modifying definition sets to account for differences in temporal and spatial observational scales. The presented land cover extent and change data are available via the official WELD website (ftp://weldftp.cr.usgs.gov/CONUS_5Y_LandCover/ftp://weldftp.cr.usgs.gov/CONUS_5Y_LandCover/).</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2013.08.014","usgsCitation":"Hansen, M., Egorov, A., Potapov, P., Stehman, S., Tyukavina, A., Turubanova, S., Roy, D.P., Goetz, S., Loveland, T., Ju, J., Kommareddy, A., Kovalskyy, V., Forsyth, C., and Bents, T., 2014, Monitoring conterminous United States (CONUS) land cover change with Web-Enabled Landsat Data (WELD): Remote Sensing of Environment, v. 140, p. 466-484, https://doi.org/10.1016/j.rse.2013.08.014.","productDescription":"19 p.","startPage":"466","endPage":"484","ipdsId":"IP-046262","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":341346,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"140","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"591c0fcce4b0a7fdb43ddf00","contributors":{"authors":[{"text":"Hansen, M.C.","contributorId":69690,"corporation":false,"usgs":false,"family":"Hansen","given":"M.C.","email":"","affiliations":[{"id":33433,"text":"University of Maryland, College Park","active":true,"usgs":false}],"preferred":false,"id":695302,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Egorov, Alexey","contributorId":81719,"corporation":false,"usgs":false,"family":"Egorov","given":"Alexey","email":"","affiliations":[{"id":5089,"text":"South Dakota State University","active":true,"usgs":false}],"preferred":false,"id":695303,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Potapov, P.V.","contributorId":19677,"corporation":false,"usgs":false,"family":"Potapov","given":"P.V.","email":"","affiliations":[{"id":33433,"text":"University of Maryland, College Park","active":true,"usgs":false}],"preferred":false,"id":695304,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stehman, S.V.","contributorId":91974,"corporation":false,"usgs":false,"family":"Stehman","given":"S.V.","email":"","affiliations":[{"id":27852,"text":"State University of New York, Syracuse","active":true,"usgs":false}],"preferred":false,"id":695306,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Tyukavina, A.","contributorId":19872,"corporation":false,"usgs":false,"family":"Tyukavina","given":"A.","email":"","affiliations":[{"id":33433,"text":"University of Maryland, College Park","active":true,"usgs":false}],"preferred":false,"id":695307,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Turubanova, S.A.","contributorId":108388,"corporation":false,"usgs":false,"family":"Turubanova","given":"S.A.","email":"","affiliations":[{"id":33433,"text":"University of Maryland, College Park","active":true,"usgs":false}],"preferred":false,"id":695308,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Roy, David P.","contributorId":54761,"corporation":false,"usgs":false,"family":"Roy","given":"David","email":"","middleInitial":"P.","affiliations":[{"id":7049,"text":"NASA Goddard Space Flight Center","active":true,"usgs":false},{"id":33433,"text":"University of Maryland, College Park","active":true,"usgs":false},{"id":26958,"text":"South Dakota State University, Brookings, SD","active":true,"usgs":false}],"preferred":false,"id":695309,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Goetz, S.J.","contributorId":55186,"corporation":false,"usgs":false,"family":"Goetz","given":"S.J.","email":"","affiliations":[{"id":25456,"text":"Woods Hole Research Center, Falmouth, MA, United States","active":true,"usgs":false}],"preferred":false,"id":695310,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Loveland, Thomas R. 0000-0003-3114-6646","orcid":"https://orcid.org/0000-0003-3114-6646","contributorId":106125,"corporation":false,"usgs":true,"family":"Loveland","given":"Thomas R.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":false,"id":695311,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Ju, J.","contributorId":85801,"corporation":false,"usgs":false,"family":"Ju","given":"J.","email":"","affiliations":[{"id":12721,"text":"NASA GSFC SSAI","active":true,"usgs":false}],"preferred":false,"id":695312,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Kommareddy, A.","contributorId":105638,"corporation":false,"usgs":false,"family":"Kommareddy","given":"A.","email":"","affiliations":[{"id":26958,"text":"South Dakota State University, Brookings, SD","active":true,"usgs":false}],"preferred":false,"id":695317,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Kovalskyy, Valeriy","contributorId":192062,"corporation":false,"usgs":false,"family":"Kovalskyy","given":"Valeriy","email":"","affiliations":[{"id":26958,"text":"South Dakota State University, Brookings, SD","active":true,"usgs":false}],"preferred":false,"id":695318,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Forsyth, C.","contributorId":192034,"corporation":false,"usgs":false,"family":"Forsyth","given":"C.","email":"","affiliations":[{"id":5089,"text":"South Dakota State University","active":true,"usgs":false}],"preferred":false,"id":695319,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Bents, T.","contributorId":139577,"corporation":false,"usgs":false,"family":"Bents","given":"T.","email":"","affiliations":[{"id":33302,"text":"University of Kansas, Lawrence","active":true,"usgs":false}],"preferred":false,"id":695320,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}}
,{"id":70189135,"text":"70189135 - 2014 - Carbonate rocks of the Seward Peninsula, Alaska: Their correlation and paleogeographic significance","interactions":[],"lastModifiedDate":"2018-05-07T21:00:10","indexId":"70189135","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1727,"text":"GSA Special Papers","active":true,"publicationSubtype":{"id":10}},"title":"Carbonate rocks of the Seward Peninsula, Alaska: Their correlation and paleogeographic significance","docAbstract":"Paleozoic carbonate strata deposited in shallow platform to off-platform settings occur across the Seward Peninsula and range from unmetamorphosed Ordovician–Devonian(?) rocks of the York succession in the west to highly deformed and metamorphosed Cambrian–Devonian units of the Nome Complex in the east. Faunal and lithologic correlations indicate that early Paleozoic strata in the two areas formed as part of a single carbonate platform.\n\nThe York succession makes up part of the York terrane and consists of Ordovician, lesser Silurian, and limited, possibly Devonian rocks. Shallow-water facies predominate, but subordinate graptolitic shale and calcareous turbidites accumulated in deeper water, intraplatform basin environments, chiefly during the Middle Ordovician. Lower Ordovician strata are mainly lime mudstone and peloid-intraclast grainstone deposited in a deepening upward regime; noncarbonate detritus is abundant in lower parts of the section. Upper Ordovician and Silurian rocks include carbonate mudstone, skeletal wackestone, and coral-stromatoporoid biostromes that are commonly dolomitic and accumulated in warm, shallow to very shallow settings with locally restricted circulation.\n\nThe rest of the York terrane is mainly Ordovician and older, variously deformed and metamorphosed carbonate and siliciclastic rocks intruded by early Cambrian (and younger?) metagabbros. Older (Neoproterozoic–Cambrian) parts of these units are chiefly turbidites and may have been basement for the carbonate platform facies of the York succession; younger, shallow- and deep-water strata likely represent previously unrecognized parts of the York succession and its offshore equivalents. Intensely deformed and altered Mississippian carbonate strata crop out in a small area at the western edge of the terrane.\n\nMetacarbonate rocks form all or part of several units within the blueschist- and greenschist-facies Nome Complex. The Layered sequence includes mafic meta¬igneous rocks and associated calcareous metaturbidites of Ordovician age as well as shallow-water Silurian dolostones. Scattered metacarbonate rocks are chiefly Cambrian, Ordovician, Silurian, and Devonian dolostones that formed in shallow, warm-water settings with locally restricted circulation and marbles of less constrained Paleozoic age. Carbonate metaturbidites occur on the northeast and southeast coasts and yield mainly Silurian and lesser Ordovician and Devonian conodonts; the northern succession also includes debris flows with meter-scale clasts and an argillite interval with Late Ordovician graptolites and lenses of radiolarian chert. Mafic igneous rocks at least partly of Early Devonian age are common in the southern succession.\n\nCarbonate rocks on Seward Peninsula experienced a range of deformational and thermal histories equivalent to those documented in the Brooks Range. Conodont color alteration indices (CAIs) from Seward Peninsula, like those from the Brooks Range, define distinct thermal provinces that likely reflect structural burial. Penetratively deformed high-pressure metamorphic rocks of the Nome Complex (CAIs ≥5) correspond to rocks of the Schist belt in the southern Brooks Range; both record subduction during early stages of the Jurassic–Cretaceous Brooks Range orogeny. Weakly metamorphosed to unmetamorphosed strata of the York terrane (CAIs mainly 2–5), like Brooks Range rocks in the Central belt and structural allochthons to the north, experienced moderate to shallow burial during the main phase of the Brooks Range orogeny. The nature of the contact between the York terrane and the Nome Complex is uncertain; it may be a thrust fault, an extensional surface, or a thrust fault later reactivated as an extensional fault.\n\nLithofacies and biofacies data indicate that, in spite of their divergent Mesozoic histories, rocks of the York terrane and protoliths of the Nome Complex formed as part of the same lower Paleozoic carbonate platform. Stratigraphies in both","language":"English","publisher":"Geological Society of America","doi":"10.1130/2014.2506(03)","usgsCitation":"Dumoulin, J.A., Harris, A., and Repetski, J.E., 2014, Carbonate rocks of the Seward Peninsula, Alaska: Their correlation and paleogeographic significance: GSA Special Papers, v. 506, p. 59-110, https://doi.org/10.1130/2014.2506(03).","productDescription":"52 p.","startPage":"59","endPage":"110","ipdsId":"IP-046076","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":343246,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"506","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59576338e4b0d1f9f051b544","contributors":{"authors":[{"text":"Dumoulin, Julie A. 0000-0003-1754-1287 dumoulin@usgs.gov","orcid":"https://orcid.org/0000-0003-1754-1287","contributorId":203209,"corporation":false,"usgs":true,"family":"Dumoulin","given":"Julie","email":"dumoulin@usgs.gov","middleInitial":"A.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":703118,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Harris, Alta aharris@usgs.gov","contributorId":148394,"corporation":false,"usgs":true,"family":"Harris","given":"Alta","email":"aharris@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":703120,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Repetski, John E. 0000-0002-2298-7120 jrepetski@usgs.gov","orcid":"https://orcid.org/0000-0002-2298-7120","contributorId":2596,"corporation":false,"usgs":true,"family":"Repetski","given":"John","email":"jrepetski@usgs.gov","middleInitial":"E.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":703119,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70188038,"text":"70188038 - 2014 - Evapotranspiration variability and its association with vegetation dynamics in the Nile Basin, 2002–2011","interactions":[],"lastModifiedDate":"2017-05-30T16:22:30","indexId":"70188038","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Evapotranspiration variability and its association with vegetation dynamics in the Nile Basin, 2002–2011","docAbstract":"<p><span>Evapotranspiration (ET) is a vital component in land-atmosphere interactions. In drylands, over 90% of annual rainfall evaporates. The Nile Basin in Africa is about 42% dryland in a region experiencing rapid population growth and development. The relationship of ET with climate, vegetation and land cover in the basin during 2002–2011 is analyzed using thermal-based Simplified Surface Energy Balance Operational (SSEBop) ET, Normalized Difference Vegetation Index (NDVI)-based MODIS Terrestrial (MOD16) ET, MODIS-derived NDVI as a proxy for vegetation productivity and rainfall from Tropical Rainfall Measuring Mission (TRMM). Interannual variability and trends are analyzed using established statistical methods. Analysis based on thermal-based ET revealed that &gt;50% of the study area exhibited negative ET anomalies for 7 years (2009, driest), while &gt;60% exhibited positive ET anomalies for 3 years (2007, wettest). NDVI-based monthly ET correlated strongly (r &gt; 0.77) with vegetation than thermal-based ET (0.52 &lt; r &lt; 0.73) at </span><i>p</i><span> &lt; 0.001. Climate-zone averaged thermal-based ET anomalies positively correlated (r = 0.6, </span><i>p</i><span> &lt; 0.05) with rainfall in 4 of the 9 investigated climate zones. Thermal-based and NDVI-based ET estimates revealed minor discrepancies over rainfed croplands (60 mm/yr higher for thermal-based ET), but a significant divergence over wetlands (440 mm/yr higher for thermal-based ET). Only 5% of the study area exhibited statistically significant trends in ET.</span></p>","language":"English","publisher":"MDPI","doi":"10.3390/rs6075885","usgsCitation":"Alemu, H., Senay, G., Kaptue, A.T., and Kovalskyy, V., 2014, Evapotranspiration variability and its association with vegetation dynamics in the Nile Basin, 2002–2011: Remote Sensing, v. 6, no. 7, p. 5885-5908, https://doi.org/10.3390/rs6075885.","productDescription":"24 p.","startPage":"5885","endPage":"5908","ipdsId":"IP-057424","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":473457,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs6075885","text":"Publisher Index Page"},{"id":341890,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Nile Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              23.818359375,\n              -3.688855143147035\n            ],\n            [\n              37.6171875,\n              -3.688855143147035\n            ],\n            [\n              37.6171875,\n              31.57853542647338\n            ],\n            [\n              23.818359375,\n              31.57853542647338\n            ],\n            [\n              23.818359375,\n              -3.688855143147035\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"6","issue":"7","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2014-06-25","publicationStatus":"PW","scienceBaseUri":"592e84c7e4b092b266f10db3","contributors":{"authors":[{"text":"Alemu, Henok","contributorId":124527,"corporation":false,"usgs":false,"family":"Alemu","given":"Henok","email":"","affiliations":[{"id":5087,"text":"Geographic Information Science Center of Excellence (GIScCE), South Dakota State University, Brookings, USA","active":true,"usgs":false}],"preferred":false,"id":696572,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":696291,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kaptue, Armel T.","contributorId":189254,"corporation":false,"usgs":false,"family":"Kaptue","given":"Armel","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":696573,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kovalskyy, Valeriy","contributorId":192062,"corporation":false,"usgs":false,"family":"Kovalskyy","given":"Valeriy","email":"","affiliations":[{"id":26958,"text":"South Dakota State University, Brookings, SD","active":true,"usgs":false}],"preferred":false,"id":696574,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70189074,"text":"70189074 - 2014 - Spectroscopy from Space","interactions":[],"lastModifiedDate":"2020-11-05T16:48:04.612491","indexId":"70189074","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3281,"text":"Reviews in Mineralogy and Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Spectroscopy from Space","docAbstract":"<p>This chapter reviews detection of materials on solid and liquid (lakes and ocean) surfaces in the solar system using ultraviolet to infrared spectroscopy from space, or near space (high altitude aircraft on the Earth), or in the case of remote objects, earth-based and earth-orbiting telescopes. Point spectrometers and imaging spectrometers have been probing the surfaces of our solar system for decades. Spacecraft carrying imaging spectrometers are currently in orbit around Mercury, Venus, Earth, Mars, and Saturn, and systems have recently visited Jupiter, comets, asteroids, and one spectrometer-carrying spacecraft is on its way to Pluto. Together these systems are providing a wealth of data that will enable a better understanding of the composition of condensed matter bodies in the solar system.</p><p>Minerals, ices, liquids, and other materials have been detected and mapped on the Earth and all planets and/or their satellites where the surface can be observed from space, with the exception of Venus whose thick atmosphere limits surface observation. Basaltic minerals (e.g., pyroxene and olivine) have been detected with spectroscopy on the Earth, Moon, Mars and some asteroids. The greatest mineralogic diversity seen from space is observed on the Earth and Mars. The Earth, with oceans, active tectonic and hydrologic cycles, and biological processes, displays the greatest material diversity including the detection of amorphous and crystalline inorganic materials, organic compounds, water and water ice.</p><p>Water ice is a very common mineral throughout the Solar System and has been unambiguously detected or inferred in every planet and/or their moon(s) where good spectroscopic data has been obtained.</p><p>In addition to water ice, other molecular solids have been observed in the solar system using spectroscopic methods. Solid carbon dioxide is found on all systems beyond the Earth except Pluto, although CO<sub>2</sub><span>&nbsp;</span>sometimes appears to be trapped in other solids rather than as an ice on some objects. The largest deposits of carbon dioxide ice are found on Mars. Sulfur dioxide ice is found in the Jupiter system. Nitrogen and methane ices are common beyond the Uranian system.</p><p>Saturn’s moon Titan probably has the most complex active extra-terrestrial surface chemistry involving organic compounds. Some of the observed or inferred compounds include ices of benzene (C<sub>6</sub>H<sub>6</sub>), cyanoacetylene (HC<sub>3</sub>N), toluene (C<sub>7</sub>H<sub>8</sub>), cyanogen (C<sub>2</sub>N<sub>2</sub>), acetonitrile (CH<sub>3</sub>CN), water (H<sub>2</sub>O), carbon dioxide (CO<sub>2</sub>), and ammonia (NH<sub>3</sub>). Confirming compounds on Titan is hampered by its thick smoggy atmosphere, where in relative terms the atmospheric interferences that hamper surface characterization lie between that of Venus and Earth.</p><p>In this chapter we exclude discussion of the planets Jupiter, Saturn, Uranus, and Neptune because their thick atmospheres preclude observing the surface, even if surfaces exist. However, we do discuss spectroscopic observations on a number of the extra-terrestrial satellite bodies. Ammonia was predicted on many icy moons but is notably absent among the definitively detected ices with possible exceptions on Charon and possible trace amounts on some of the Saturnian satellites. Comets, storehouses of many compounds that could exist as ices in their nuclei, have only had small amounts of water ice definitively detected on their surfaces from spectroscopy. Only two asteroids have had a direct detection of surface water ice, although its presence can be inferred in others.</p>","language":"English","publisher":"Mineralogical Society of America","doi":"10.2138/rmg.2014.78.10","usgsCitation":"Clark, R.N., Swayze, G.A., Carlson, R.R., Grundy, W., and Noll, K., 2014, Spectroscopy from Space: Reviews in Mineralogy and Geochemistry, v. 78, no. 1, p. 399-446, https://doi.org/10.2138/rmg.2014.78.10.","productDescription":"48 p.","startPage":"399","endPage":"446","ipdsId":"IP-036673","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":343176,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"78","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2014-02-27","publicationStatus":"PW","scienceBaseUri":"595611b9e4b0d1f9f0506772","contributors":{"authors":[{"text":"Clark, Roger N. 0000-0002-7021-1220 rclark@usgs.gov","orcid":"https://orcid.org/0000-0002-7021-1220","contributorId":515,"corporation":false,"usgs":true,"family":"Clark","given":"Roger","email":"rclark@usgs.gov","middleInitial":"N.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":702780,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Swayze, Gregg A. 0000-0002-1814-7823 gswayze@usgs.gov","orcid":"https://orcid.org/0000-0002-1814-7823","contributorId":518,"corporation":false,"usgs":true,"family":"Swayze","given":"Gregg","email":"gswayze@usgs.gov","middleInitial":"A.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":702779,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Carlson, Robert R.","contributorId":71944,"corporation":false,"usgs":true,"family":"Carlson","given":"Robert","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":702931,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Grundy, Will","contributorId":156333,"corporation":false,"usgs":false,"family":"Grundy","given":"Will","email":"","affiliations":[],"preferred":false,"id":702932,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Noll, Keith","contributorId":193877,"corporation":false,"usgs":false,"family":"Noll","given":"Keith","email":"","affiliations":[],"preferred":false,"id":702933,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70188054,"text":"70188054 - 2014 - Earth observation based assessment of the water production and water consumption of Nile Basin agro-ecosystems","interactions":[],"lastModifiedDate":"2017-05-31T16:11:56","indexId":"70188054","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Earth observation based assessment of the water production and water consumption of Nile Basin agro-ecosystems","docAbstract":"<p><span>The increasing competition for water resources requires a better understanding of flows, fluxes, stocks, and the services and benefits related to water consumption. This paper explains how public domain Earth Observation data based on Moderate Resolution Imaging Spectroradiometer (MODIS), Second Generation Meteosat (MSG), Tropical Rainfall Measurement Mission (TRMM) and various altimeter measurements can be used to estimate net water production (rainfall (P) &gt; evapotranspiration (ET)) and net water consumption (ET &gt; P) of Nile Basin agro-ecosystems. Rainfall data from TRMM and the Famine Early Warning System Network (FEWS-NET) RainFall Estimates (RFE) products were used in conjunction with actual evapotranspiration from the Operational Simplified Surface Energy Balance (SSEBop) and ETLook models. Water flows laterally between net water production and net water consumption areas as a result of runoff and withdrawals. This lateral flow between the 15 sub-basins of the Nile was estimated, and partitioned into stream flow and non-stream flow using the discharge data. A series of essential water metrics necessary for successful integrated water management are explained and computed. Net water withdrawal estimates (natural and humanly instigated) were assumed to be the difference between net rainfall (P</span><sub>net</sub><span>) and actual evapotranspiration (ET) and some first estimates of withdrawals—without flow meters—are provided. Groundwater-dependent ecosystems withdraw large volumes of groundwater, which exceed water withdrawals for the irrigation sector. There is a strong need for the development of more open-access Earth Observation databases, especially for information related to actual ET. The fluxes, flows and storage changes presented form the basis for a global framework to describe monthly and annual water accounts in ungauged river basins. </span></p>","language":"English","publisher":"MDPI","doi":"10.3390/rs61110306","usgsCitation":"Bastiaanssen, W., Karimi, P., Rebelo, L., Duan, Z., Senay, G., Muthuwatte, L., and Smakhtin, V., 2014, Earth observation based assessment of the water production and water consumption of Nile Basin agro-ecosystems: Remote Sensing, v. 6, no. 11, p. 10306-10334, https://doi.org/10.3390/rs61110306.","productDescription":"29 p.","startPage":"10306","endPage":"10334","ipdsId":"IP-057431","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":473300,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs61110306","text":"Publisher Index Page"},{"id":341872,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Nile Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              23.818359375,\n              -3.688855143147035\n            ],\n            [\n              37.6171875,\n              -3.688855143147035\n            ],\n            [\n              37.6171875,\n              31.57853542647338\n            ],\n            [\n              23.818359375,\n              31.57853542647338\n            ],\n            [\n              23.818359375,\n              -3.688855143147035\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"6","issue":"11","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2014-10-24","publicationStatus":"PW","scienceBaseUri":"592e84c6e4b092b266f10da3","contributors":{"authors":[{"text":"Bastiaanssen, Wim","contributorId":192421,"corporation":false,"usgs":false,"family":"Bastiaanssen","given":"Wim","email":"","affiliations":[],"preferred":false,"id":696478,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Karimi, Poolad","contributorId":192422,"corporation":false,"usgs":false,"family":"Karimi","given":"Poolad","email":"","affiliations":[],"preferred":false,"id":696479,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rebelo, Lisa-Maria","contributorId":192423,"corporation":false,"usgs":false,"family":"Rebelo","given":"Lisa-Maria","email":"","affiliations":[],"preferred":false,"id":696480,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Duan, Zheng","contributorId":192424,"corporation":false,"usgs":false,"family":"Duan","given":"Zheng","email":"","affiliations":[],"preferred":false,"id":696481,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Senay, Gabriel B. 0000-0002-8810-8539 senay@usgs.gov","orcid":"https://orcid.org/0000-0002-8810-8539","contributorId":166812,"corporation":false,"usgs":true,"family":"Senay","given":"Gabriel","email":"senay@usgs.gov","middleInitial":"B.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":696333,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Muthuwatte, Lal","contributorId":192425,"corporation":false,"usgs":false,"family":"Muthuwatte","given":"Lal","email":"","affiliations":[],"preferred":false,"id":696482,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Smakhtin, Vladimir","contributorId":192426,"corporation":false,"usgs":false,"family":"Smakhtin","given":"Vladimir","email":"","affiliations":[],"preferred":false,"id":696483,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70187261,"text":"70187261 - 2014 - Predicting impacts of future human population growth and development on occupancy rates of forest-dependent birds","interactions":[],"lastModifiedDate":"2017-04-27T11:17:37","indexId":"70187261","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Predicting impacts of future human population growth and development on occupancy rates of forest-dependent birds","docAbstract":"<p><span>Forest loss and fragmentation are among the largest threats to forest-dwelling wildlife species today, and projected increases in human population growth are expected to increase these threats in the next century. We combined spatially-explicit growth models with wildlife distribution models to predict the effects of human development on 5 forest-dependent bird species in Vermont, New Hampshire, and Massachusetts, USA. We used single-species occupancy models to derive the probability of occupancy for each species across the study area in the years 2000 and 2050. Over half a million new housing units were predicted to be added to the landscape. The maximum change in housing density was nearly 30 houses per hectare; however, 30% of the towns in the study area were projected to add less than 1 housing unit per hectare. In the face of predicted human growth, the overall occupancy of each species decreased by as much as 38% (ranging from 19% to 38% declines in the worst-case scenario) in the year 2050. These declines were greater outside of protected areas than within protected lands. Ninety-seven percent of towns experienced some decline in species occupancy within their borders, highlighting the value of spatially-explicit models. The mean decrease in occupancy probability within towns ranged from 3% for hairy woodpecker to 8% for ovenbird and hermit thrush. Reductions in occupancy probability occurred on the perimeters of cities and towns where exurban development is predicted to increase in the study area. This spatial approach to wildlife planning provides data to evaluate trade-offs between development scenarios and forest-dependent wildlife species.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2013.07.039","usgsCitation":"Brown, M.L., Donovan, T., Schwenk, W.S., and Theobald, D.M., 2014, Predicting impacts of future human population growth and development on occupancy rates of forest-dependent birds: Biological Conservation, v. 170, p. 311-320, https://doi.org/10.1016/j.biocon.2013.07.039.","productDescription":"10 p.","startPage":"311","endPage":"320","ipdsId":"IP-039574","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":340499,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"170","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59030328e4b0e862d230f751","contributors":{"authors":[{"text":"Brown, Michelle L.","contributorId":168990,"corporation":false,"usgs":false,"family":"Brown","given":"Michelle","email":"","middleInitial":"L.","affiliations":[{"id":7147,"text":"Wayne State University","active":true,"usgs":false}],"preferred":false,"id":693186,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Donovan, Therese tdonovan@usgs.gov","contributorId":171599,"corporation":false,"usgs":true,"family":"Donovan","given":"Therese","email":"tdonovan@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":693119,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schwenk, W. Scott","contributorId":172274,"corporation":false,"usgs":false,"family":"Schwenk","given":"W.","email":"","middleInitial":"Scott","affiliations":[],"preferred":false,"id":693187,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Theobald, David M. 0000-0002-1271-9368","orcid":"https://orcid.org/0000-0002-1271-9368","contributorId":10271,"corporation":false,"usgs":false,"family":"Theobald","given":"David","email":"","middleInitial":"M.","affiliations":[{"id":13470,"text":"Conservation Science Partners","active":true,"usgs":false}],"preferred":true,"id":693188,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70188048,"text":"70188048 - 2014 - Spatio-temporal patterns and climate variables controlling of biomass carbon stock of global grassland ecosystems from 1982 to 2006","interactions":[],"lastModifiedDate":"2017-05-30T15:15:06","indexId":"70188048","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Spatio-temporal patterns and climate variables controlling of biomass carbon stock of global grassland ecosystems from 1982 to 2006","docAbstract":"<p><span>Grassland ecosystems play an important role in subsistence agriculture and the global carbon cycle. However, the global spatio-temporal patterns and environmental controls of grassland biomass are not well quantified and understood. The goal of this study was to estimate the spatial and temporal patterns of the global grassland biomass and analyze their driving forces using field measurements, Normalized Difference Vegetation Index (NDVI) time series from satellite data, climate reanalysis data, and a satellite-based statistical model. Results showed that the NDVI-based biomass carbon model developed from this study explained 60% of the variance across 38 sites globally. The global carbon stock in grassland aboveground live biomass was 1.05 Pg·C, averaged from 1982 to 2006, and increased at a rate of 2.43 Tg·C·y</span><sup>−1</sup><span> during this period. Temporal change of the global biomass was significantly and positively correlated with temperature and precipitation. The distribution of biomass carbon density followed the precipitation gradient. The dynamics of regional grassland biomass showed various trends largely determined by regional climate variability, disturbances, and management practices (such as grazing for meat production). The methods and results from this study can be used to monitor the dynamics of grassland aboveground biomass and evaluate grassland susceptibility to climate variability and change, disturbances, and management.</span></p>","language":"English","publisher":"MDPI","doi":"10.3390/rs6031783","usgsCitation":"Xia, J., Liu, S., Liang, S., Chen, Y., Xu, W., and Yuan, W., 2014, Spatio-temporal patterns and climate variables controlling of biomass carbon stock of global grassland ecosystems from 1982 to 2006: Remote Sensing, v. 6, no. 3, p. 1783-1802, https://doi.org/10.3390/rs6031783.","productDescription":"20 p.","startPage":"1783","endPage":"1802","ipdsId":"IP-052038","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":486959,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs6031783","text":"Publisher Index Page"},{"id":341874,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","issue":"3","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2014-02-26","publicationStatus":"PW","scienceBaseUri":"592e84c7e4b092b266f10dae","contributors":{"authors":[{"text":"Xia, Jiangzhou","contributorId":192427,"corporation":false,"usgs":false,"family":"Xia","given":"Jiangzhou","email":"","affiliations":[],"preferred":false,"id":696484,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Liu, Shuguang 0000-0002-6027-3479 sliu@usgs.gov","orcid":"https://orcid.org/0000-0002-6027-3479","contributorId":147403,"corporation":false,"usgs":true,"family":"Liu","given":"Shuguang","email":"sliu@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":696320,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Liang, Shunlin","contributorId":192428,"corporation":false,"usgs":false,"family":"Liang","given":"Shunlin","email":"","affiliations":[],"preferred":false,"id":696485,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chen, Yang","contributorId":192429,"corporation":false,"usgs":false,"family":"Chen","given":"Yang","email":"","affiliations":[],"preferred":false,"id":696486,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Xu, Wenfang","contributorId":192430,"corporation":false,"usgs":false,"family":"Xu","given":"Wenfang","email":"","affiliations":[],"preferred":false,"id":696487,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Yuan, Wenping","contributorId":83435,"corporation":false,"usgs":true,"family":"Yuan","given":"Wenping","email":"","affiliations":[],"preferred":false,"id":696488,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70189138,"text":"70189138 - 2014 - New ichnological, paleobotanical and detrital zircon data from an unnamed rock unit in Yukon-Charley Rivers National Preserve (Cretaceous: Alaska): Stratigraphic implications for the region","interactions":[],"lastModifiedDate":"2017-06-30T16:04:04","indexId":"70189138","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3000,"text":"Palaios","active":true,"publicationSubtype":{"id":10}},"title":"New ichnological, paleobotanical and detrital zircon data from an unnamed rock unit in Yukon-Charley Rivers National Preserve (Cretaceous: Alaska): Stratigraphic implications for the region","docAbstract":"<p><span>A paleontological reconnaissance survey on Cretaceous and Paleogene terrestrial units along the Yukon River drainage through much of east-central Alaska has provided new chronostratigraphic constraints, paleoclimatological data, and the first information on local biodiversity within an ancient, high-latitude ecosystem. The studied unnamed rock unit is most notable for its historic economic gold placer deposits, but our survey documents its relevance as a source rock for Mesozoic terrestrial vertebrates, invertebrates, and associated flora. Specifically, new U-Pb ages from detrital zircons combined with ichnological data are indicative of a Late Cretaceous age for at least the lower section of the studied rock unit, previously considered to be representative of nearly exclusively Paleogene deposition. Further, the results of our survey show that this sedimentary rock unit preserves the first record of dinosaurs in the vast east-central Alaska region. Lastly, paleobotanical data, when compared to correlative rock units, support previous interpretations that the Late Cretaceous continental ecosystem of Alaska was heterogeneous in nature and seasonal.</span></p>","language":"English","publisher":"Society for Sedimentary Geology","doi":"10.2110/palo.2013.054","usgsCitation":"Fiorillo, A.R., Fanti, F., Hults, C., and Hasiotis, S.T., 2014, New ichnological, paleobotanical and detrital zircon data from an unnamed rock unit in Yukon-Charley Rivers National Preserve (Cretaceous: Alaska): Stratigraphic implications for the region: Palaios, v. 29, no. 1, p. 16-26, https://doi.org/10.2110/palo.2013.054.","productDescription":"11 p.","startPage":"16","endPage":"26","ipdsId":"IP-053208","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":343247,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"29","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2014-06-12","publicationStatus":"PW","scienceBaseUri":"59576338e4b0d1f9f051b541","contributors":{"authors":[{"text":"Fiorillo, Anthony R.","contributorId":194070,"corporation":false,"usgs":false,"family":"Fiorillo","given":"Anthony","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":703133,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fanti, Federico","contributorId":194071,"corporation":false,"usgs":false,"family":"Fanti","given":"Federico","email":"","affiliations":[],"preferred":false,"id":703134,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hults, Chad chults@usgs.gov","contributorId":194069,"corporation":false,"usgs":true,"family":"Hults","given":"Chad","email":"chults@usgs.gov","affiliations":[],"preferred":true,"id":703132,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hasiotis, Stephen T","contributorId":194072,"corporation":false,"usgs":false,"family":"Hasiotis","given":"Stephen","email":"","middleInitial":"T","affiliations":[],"preferred":false,"id":703135,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70189139,"text":"70189139 - 2014 - Sulfur and oxygen isotopic study of Paleozoic sediment-hosted Zn-Pb(-Ag-Au-Ba-F) deposits and associated hydrothermal alteration zones in the Nome Complex, Seward Peninsula, Alaska","interactions":[],"lastModifiedDate":"2018-11-20T09:53:26","indexId":"70189139","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1727,"text":"GSA Special Papers","active":true,"publicationSubtype":{"id":10}},"title":"Sulfur and oxygen isotopic study of Paleozoic sediment-hosted Zn-Pb(-Ag-Au-Ba-F) deposits and associated hydrothermal alteration zones in the Nome Complex, Seward Peninsula, Alaska","docAbstract":"Results of sulfur and oxygen isotope studies of sedimentary exhalative (SEDEX) Zn-Pb(-Ag-Au-Ba-F) deposits hosted in metamorphosed Paleozoic clastic and carbonate rocks of the Nome Complex, Seward Peninsula, Alaska, are consistent with data for similar deposits worldwide.  Stable isotopic studies of the Nome Complex are challenging because the rocks have undergone Mesozoic blueschist- and greenschist-facies metamorphism and deformation at temperatures estimated from 390–490 °C.  Studies of sulfur and oxygen isotopes in other areas suggest that, in the absence of chemical and mineralogical evidence for metasomatism, the principal effect of metamorphism is re-equilibration between individual minerals at the temperature of metamorphism, which commonly leads to a narrowing of the overall range of isotope values for a suite of rocks, but generally does not significantly modify the average whole rock value for that suite.\n\tSulfur isotope studies of the stratabound and locally stratiform sulfide lenses at the Aurora Creek-Christophosen deposit, which is of possible Late Devonian-early Carboniferous age, show a large range of δ34Ssulfide values from -9.7 to 39.4‰, suggesting multiple sulfur sources and possibly complex processes of sulfide formation that may include bacterial sulfate reduction, thermochemical sulfate reduction, and Rayleigh distillation.  Low δ34S values probably represent bacterial sulfide minerals remobilized from the host metasedimentary rocks either during the original seafloor mineralization or are related to a Cretaceous mineralizing event that produced Au-vein and base-metal replacement deposits; the latter process is supported by Pb isotope data.  \nThe Wheeler North deposit is similar to Aurora Creek-Christophosen but does not have negative δ34S values.  It also probably formed in an euxinic sub-basin.\nThe stratabound Nelson deposit, and the deformed veins at the Galena and Quarry deposits, may be older than the Aurora Creek-Christophosen and Wheeler North deposits.  The Nelson deposit has a lower and narrower range of δ34S values (1.9 to 10.4‰), averaging about 8‰.  The Galena and Quarry veins display δ34S values that are similar to those of the stratabound Nelson deposit.  Barite samples from the Aurora Creek-Christophosen, Wheeler North, and Quarry deposits have 34S-enriched δ34S values between 25 and 30‰ that are consistent with derivation of the sulfur from coeval (Paleozoic) seawater sulfate.  \nGiven their δ34S values, it is likely that the Aurora Creek-Christophosen and Wheeler North deposits formed in closed sub-basins with euxinic conditions that led to extreme Rayleigh distillation to produce the very large range and very high δ34S values.  The Nelson deposit probably formed within an anoxic but not euxinic sub-basin. At Nelson, sulfide was likely derived by a subsurface thermochemical sulfate reduction (TSR) reaction, similar to reactions that are inferred to have produced the sulfides in the Galena and Quarry deposits, which are interpreted as feeder veins for the stratabound deposits.\n\tCalculations of oxygen isotope temperatures are based on the assumption that evolved seawater with δ18O of 3‰ was the mineralizing and altering fluid related to the formation of the sulfide deposits. Temperatures of aluminous alteration and sulfide mineralization were between 109 and 209 °C, determined on the basis of oxygen isotope fractionations between the mineralizing fluid and proportionate amounts of quartz and muscovite in the rocks.  These temperature estimates agree well with known temperatures of SEDEX mineralization worldwide.   Sulfur isotope values also are generally consistent with the known ranges in SEDEX deposits worldwide (δ34S ≈ -5 to 25‰).","language":"English","publisher":"Geological Society of America","doi":"10.1130/2014.2506(08)","usgsCitation":"Shanks, W.P., Slack, J.F., Till, A.B., Thurston, R., and Gemery-Hill, P., 2014, Sulfur and oxygen isotopic study of Paleozoic sediment-hosted Zn-Pb(-Ag-Au-Ba-F) deposits and associated hydrothermal alteration zones in the Nome Complex, Seward Peninsula, Alaska: GSA Special Papers, v. 506, p. 235-258, https://doi.org/10.1130/2014.2506(08).","productDescription":"24 p.","startPage":"235","endPage":"258","ipdsId":"IP-054559","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":343249,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"506","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59576338e4b0d1f9f051b53c","contributors":{"authors":[{"text":"Shanks, W.C. Pat III","contributorId":93949,"corporation":false,"usgs":true,"family":"Shanks","given":"W.C.","suffix":"III","email":"","middleInitial":"Pat","affiliations":[],"preferred":false,"id":703137,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Slack, John F. 0000-0001-6600-3130 jfslack@usgs.gov","orcid":"https://orcid.org/0000-0001-6600-3130","contributorId":1032,"corporation":false,"usgs":true,"family":"Slack","given":"John","email":"jfslack@usgs.gov","middleInitial":"F.","affiliations":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":703138,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Till, Alison B. atill@usgs.gov","contributorId":2482,"corporation":false,"usgs":true,"family":"Till","given":"Alison","email":"atill@usgs.gov","middleInitial":"B.","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":703136,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thurston, Roland","contributorId":194075,"corporation":false,"usgs":false,"family":"Thurston","given":"Roland","affiliations":[],"preferred":false,"id":703139,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gemery-Hill, Pamela","contributorId":194076,"corporation":false,"usgs":false,"family":"Gemery-Hill","given":"Pamela","email":"","affiliations":[],"preferred":false,"id":703140,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70187420,"text":"70187420 - 2014 - Normative standards for land use in Vermont: Implications for biodiversity","interactions":[],"lastModifiedDate":"2017-05-02T12:52:14","indexId":"70187420","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Normative standards for land use in Vermont: Implications for biodiversity","docAbstract":"<p><span>The conversion of natural lands to developed uses poses a great threat to global terrestrial biodiversity. Natural resource managers, tasked with managing wildlife as a public trust, require techniques for predicting&nbsp;</span><i>how much</i><span>&nbsp;and&nbsp;</span><i>where</i><span>&nbsp;wildlife habitat is likely to be converted in the future. Here, we develop a methodology to&nbsp;estimate the “social carrying capacity for development” – </span><i>SK<sub>d</sub></i><span> – for 251 towns across the state of Vermont, USA. </span><i>SK<sub>d</sub></i><span> represents town residents’ minimum acceptable human population size and level of development within town boundaries. To estimate </span><i>SK<sub>d</sub></i><span> across towns within the state of Vermont (USA), as well as the average state-wide </span><i>SK<sub>d</sub></i><span>, we administered a visual preference survey (</span><i>n</i><span>&nbsp;=&nbsp;1505 responses) to Vermont residents, and asked respondents to rate alternative landuse scenarios in a fictional Vermont town on a scale of +4 (highly acceptable) to −4 (highly unacceptable). We additionally collected demographic data such as age and income, as well as ancillary information such as participation in town-planning meetings and location of residence. We used model selection and AIC to fit a cubic function to the response data, allowing us&nbsp;to estimate </span><i>SK<sub>d</sub></i><span>&nbsp;at a town scale based on town demographic characteristics. On average, Vermonters had a&nbsp;</span><i>SK<sub>d</sub></i><span>&nbsp;of 9.1% development on the landscape; this estimate is 68% higher than year 2000 levels for development (5.4%). Respondents indicated that management action to curb development was appropriate at 9.4% development (roughly the statewide </span><i>SK<sub>d</sub></i><span> average). Management by local, regional, and state levels were considered acceptable for curbing development while federal level management of development was considered unacceptable. Given a scenario where development levels were at </span><i>SK<sub>d</sub></i><span>, we predicted a 16,753&nbsp;km</span><sup>2</sup><span> reduction in forested land (−11.16%) and a 1038&nbsp;km</span><sup>2</sup><span> reduction in farmland (−60.45%). Such changes would dramatically alter biodiversity patterns state-wide. In a companion paper, we estimate how these changes would affect the distribution of wildlife species.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2013.07.009","usgsCitation":"Bettigole, C.A., Donovan, T., Manning, R., and Austin, J., 2014, Normative standards for land use in Vermont: Implications for biodiversity: Biological Conservation, v. 169, p. 392-400, https://doi.org/10.1016/j.biocon.2013.07.009.","productDescription":"9 p.","startPage":"392","endPage":"400","ipdsId":"IP-040027","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":340738,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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,{"id":70188032,"text":"70188032 - 2014 - Detecting emergence, growth, and senescence of wetland vegetation with polarimetric synthetic aperture radar (SAR) data","interactions":[],"lastModifiedDate":"2017-05-31T15:19:27","indexId":"70188032","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Detecting emergence, growth, and senescence of wetland vegetation with polarimetric synthetic aperture radar (SAR) data","docAbstract":"<p><span>Wetlands provide ecosystem goods and services vitally important to humans. Land managers and policymakers working to conserve wetlands require regularly updated information on the statuses of wetlands across the landscape. However, wetlands are challenging to map remotely with high accuracy and consistency. We investigated the use of multitemporal polarimetric synthetic aperture radar (SAR) data acquired with Canada’s Radarsat-2 system to track within-season changes in wetland vegetation and surface water. We speculated, </span><i>a priori</i><span>, how temporal and morphological traits of different types of wetland vegetation should respond over a growing season with respect to four energy-scattering mechanisms. We used ground-based monitoring data and other ancillary information to assess the limits and consistency of the SAR data for tracking seasonal changes in wetlands. We found the traits of different types of vertical emergent wetland vegetation were detected well with the SAR data and corresponded with our anticipated backscatter responses. We also found using data from Landsat’s optical/infrared sensors in conjunction with SAR data helped remove confusion of wetland features with upland grasslands. These results suggest SAR data can provide useful monitoring information on the statuses of wetlands over time.</span></p>","language":"English","publisher":"MDPI","doi":"10.3390/w6030694","usgsCitation":"Gallant, A.L., Kaya, S.G., White, L., Brisco, B., Roth, M.F., Sadinski, W.J., and Rover, J., 2014, Detecting emergence, growth, and senescence of wetland vegetation with polarimetric synthetic aperture radar (SAR) data: Water, v. 6, no. 3, p. 694-722, https://doi.org/10.3390/w6030694.","productDescription":"29 p.","startPage":"694","endPage":"722","ipdsId":"IP-053361","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":473304,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w6030694","text":"Publisher Index Page"},{"id":341958,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","issue":"3","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2014-03-24","publicationStatus":"PW","scienceBaseUri":"592fd640e4b0e9bd0ea8970a","contributors":{"authors":[{"text":"Gallant, Alisa L. 0000-0002-3029-6637 gallant@usgs.gov","orcid":"https://orcid.org/0000-0002-3029-6637","contributorId":2940,"corporation":false,"usgs":true,"family":"Gallant","given":"Alisa","email":"gallant@usgs.gov","middleInitial":"L.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":696252,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kaya, Shannon G.","contributorId":192330,"corporation":false,"usgs":false,"family":"Kaya","given":"Shannon","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":696253,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"White, Lori","contributorId":192557,"corporation":false,"usgs":false,"family":"White","given":"Lori","email":"","affiliations":[],"preferred":false,"id":696254,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brisco, Brian","contributorId":37665,"corporation":false,"usgs":true,"family":"Brisco","given":"Brian","email":"","affiliations":[],"preferred":false,"id":696255,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Roth, Mark F. 0000-0001-5095-1865 mroth@usgs.gov","orcid":"https://orcid.org/0000-0001-5095-1865","contributorId":3286,"corporation":false,"usgs":true,"family":"Roth","given":"Mark","email":"mroth@usgs.gov","middleInitial":"F.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":696256,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sadinski, Walter J. wsadinski@usgs.gov","contributorId":3287,"corporation":false,"usgs":true,"family":"Sadinski","given":"Walter","email":"wsadinski@usgs.gov","middleInitial":"J.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":696257,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rover, Jennifer 0000-0002-3437-4030 jrover@usgs.gov","orcid":"https://orcid.org/0000-0002-3437-4030","contributorId":192333,"corporation":false,"usgs":true,"family":"Rover","given":"Jennifer","email":"jrover@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":696258,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70192418,"text":"70192418 - 2014 - Major and trace element geochemistry and background concentrations for soils in Connecticut","interactions":[],"lastModifiedDate":"2021-08-02T11:37:54.198201","indexId":"70192418","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5673,"text":"Northeastern Geoscience","active":true,"publicationSubtype":{"id":10}},"title":"Major and trace element geochemistry and background concentrations for soils in Connecticut","docAbstract":"<p>Soil samples were collected throughout Connecticut (CT) to determine the relationship of soil chemistry with the underlying geology and to better understand background concentrations of major and trace elements in soils. Soil samples were collected (1) from the upper 5 cm of surficial soil at 100 sites, (2) from the A horizon at 86 of these sites, and (3) from the deeper horizon, typically the C horizon, at 79 of these sites. The &lt;2-millimeter fraction of each sample was analyzed for 44 elements by methods that yield the total or near-total elemental content. Sample sites were characterized by glacial setting, underlying bedrock geology, and soil type. These spatial data were used with element concentrations in the C-horizon to relate geologic factors to soil chemistry. </p><p>Concentrations of elements in C-horizon soils varied with grain size in surficial glacial materials and with underlying rock types, as determined using nonparametric statistical procedures. Concentrations of most elements in C-horizon soils showed a positive correlation with silt and (or) clay content and were higher in surficial materials mapped as till, thick till, and (or) fines. Element concentrations in C-horizon soils showed significant differences among the underlying geologic provinces and were highest overlying the Grenville Belt and (or) the Grenville Shelf Sequence Provinces in western CT. These rocks consist mainly of carbonates and the relatively high element concentrations in overlying soils likely result from less influence of dilution by quartz compared to other provinces. Element concentrations in C-horizon soils in CT were compared with those in samples from other New England states overlying similar lithologic bedrock types. The upper range of As concentrations in C-horizon soils overlying the New Hampshire-Maine (NH-ME) Sequence in CT was 15 mg/kg, lower than the upper range of 24 mg/kg in C-horizon soils overlying the same sequence in ME. In CT, U concentration means were significantly higher in C-horizon soils overlying Avalonian granites, and U concentrations ranged as high as 14 mg/kg, compared to those in C-horizon soil samples collected from other New England states, which ranged as high as 6.1 mg/kg in a sample in NH overlying the NH-ME Sequence. </p><p>Element concentrations in C-horizon soils in CT were compared with those in samples collected from shallower depths. Concentrations of most major elements were highest in C-horizon soil samples, including Al, Ca, Fe, K, Na, and Ti, but element concentrations showed a relatively similar pattern in A-horizon and surficial soil samples among the underlying geologic provinces. Trace element concentrations, including Ba, W, Ga, Ni, Cs, Rb, Sr, Th, Sc, and U, also were higher in C-horizon soil samples than in overlying soil samples. Concentrations of Mg, and several trace elements, including Mn, P, As, Nb, Sn, Be, Bi, Hg, Se, Sb, La, Co, Cr, Pb, V, Y, Cu, Pb, and Zn were highest in some A-horizon or surficial soils, and indicate possible contributions from anthropogenic sources. Because element concentrations in soils above the C horizon are more likely to be affected by anthropogenic factors, concentration ranges in C-horizon soils and their spatially varying geologic associations should be considered when estimating background concentrations of elements in CT soils. <br></p>","language":"English","publisher":"Northeastern Geoscience","usgsCitation":"Brown, C.J., and Thomas, M., 2014, Major and trace element geochemistry and background concentrations for soils in Connecticut: Northeastern Geoscience, v. 32, p. 1-37.","productDescription":"37 p.","startPage":"1","endPage":"37","ipdsId":"IP-054875","costCenters":[{"id":196,"text":"Connecticut Water Science Center","active":true,"usgs":true}],"links":[{"id":352951,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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 \"}}]}","volume":"32","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afeee10e4b0da30c1bfc753","contributors":{"authors":[{"text":"Brown, Craig J. 0000-0002-3858-3964 cjbrown@usgs.gov","orcid":"https://orcid.org/0000-0002-3858-3964","contributorId":198350,"corporation":false,"usgs":true,"family":"Brown","given":"Craig","email":"cjbrown@usgs.gov","middleInitial":"J.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":715762,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thomas, Margaret A.","contributorId":191171,"corporation":false,"usgs":false,"family":"Thomas","given":"Margaret A.","affiliations":[],"preferred":false,"id":715763,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70187380,"text":"70187380 - 2014 - A new map of global ecological land units — An ecophysiographic stratification approach","interactions":[],"lastModifiedDate":"2022-09-16T18:13:10.033614","indexId":"70187380","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":4,"text":"Book"},"publicationSubtype":{"id":15,"text":"Monograph"},"title":"A new map of global ecological land units — An ecophysiographic stratification approach","docAbstract":"<p>In response to the need and an intergovernmental commission for a high resolution and data-derived global ecosystem map, land surface elements of global ecological pattern were characterized in an ecophysiographic stratification of the planet. The stratification produced 3,923 terrestrial ecological land units (ELUs) at a base resolution of 250 meters. The ELUs were derived from data on land surface features in a three step approach. The first step involved acquiring or developing four global raster datalayers representing the primary components of ecosystem structure: bioclimate, landform, lithology, and land cover. These datasets generally represent the most accurate, current, globally comprehensive, and finest spatial and thematic resolution data available for each of the four inputs. The second step involved a spatial combination of the four inputs into a single, new integrated raster dataset where every cell represents a combination of values from the bioclimate, landforms, lithology, and land cover datalayers. This foundational global raster datalayer, called ecological facets (EFs), contains 47,650 unique combinations of the four inputs. The third step involved an aggregation of the EFs into the 3,923 ELUs. This subdivision of the Earth’s surface into relatively fine, ecological land areas is designed to be useful for various types of ecosystem research and management applications, including assessments of climate change impacts to ecosystems, economic and non-economic valuation of ecosystem services, and conservation planning.</p>","language":"English","publisher":"Association of American Geographers, U. S. Geological Survey, GEO BON","isbn":"978-0-89291-276-6","usgsCitation":"Sayre, R., Dangermond, J., Frye, C., Vaughan, R., Aniello, P., Breyer, S.P., Cribbs, D., Hopkins, D., Nauman, R., Derrenbacher, W., Wright, D.J., Brown, C., Convis, C., Smith, J.H., Benson, L., VanSistine, D.P., Warner, H., Cress, J.J., Danielson, J.J., Hamann, S.L., Cecere, T., Reddy, A.D., Burton, D., Grosse, A., TRUE, D., Metzger, M., Hartmann, J., Moosdorf, N., Durr, H., Paganini, M., Defourny, P., Arino, O., Maynard, S., Anderson, M., and Comer, P., 2014, A new map of global ecological land units — An ecophysiographic stratification approach, 46 p.","productDescription":"46 p.","ipdsId":"IP-060509","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":5055,"text":"Land Change Science","active":true,"usgs":true}],"links":[{"id":340699,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":406868,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://geobon.org/documents/biodiversity-monitoring/"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59084934e4b0fc4e448ffd8a","contributors":{"authors":[{"text":"Sayre, Roger 0000-0001-6703-7105 rsayre@usgs.gov","orcid":"https://orcid.org/0000-0001-6703-7105","contributorId":191629,"corporation":false,"usgs":true,"family":"Sayre","given":"Roger","email":"rsayre@usgs.gov","affiliations":[{"id":505,"text":"Office of the AD Climate and Land-Use Change","active":true,"usgs":true},{"id":5055,"text":"Land Change Science","active":true,"usgs":true}],"preferred":true,"id":693663,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dangermond, Jack","contributorId":191630,"corporation":false,"usgs":false,"family":"Dangermond","given":"Jack","email":"","affiliations":[],"preferred":false,"id":693664,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Frye, Charlie","contributorId":191631,"corporation":false,"usgs":false,"family":"Frye","given":"Charlie","affiliations":[{"id":18946,"text":"Environmental Systems Research Institute, Inc. (ESRI), Redlands, CA","active":true,"usgs":false}],"preferred":false,"id":693665,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vaughan, Randy","contributorId":191632,"corporation":false,"usgs":false,"family":"Vaughan","given":"Randy","email":"","affiliations":[{"id":18946,"text":"Environmental Systems Research Institute, Inc. (ESRI), Redlands, CA","active":true,"usgs":false}],"preferred":false,"id":693666,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Aniello, Peter","contributorId":191633,"corporation":false,"usgs":false,"family":"Aniello","given":"Peter","affiliations":[{"id":18946,"text":"Environmental Systems Research Institute, Inc. (ESRI), Redlands, CA","active":true,"usgs":false}],"preferred":false,"id":693667,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Breyer, Sean P.","contributorId":191634,"corporation":false,"usgs":false,"family":"Breyer","given":"Sean","email":"","middleInitial":"P.","affiliations":[{"id":18946,"text":"Environmental Systems Research Institute, Inc. (ESRI), Redlands, CA","active":true,"usgs":false}],"preferred":false,"id":693668,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cribbs, Douglas","contributorId":191635,"corporation":false,"usgs":false,"family":"Cribbs","given":"Douglas","email":"","affiliations":[],"preferred":false,"id":693669,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hopkins, Dabney","contributorId":191636,"corporation":false,"usgs":false,"family":"Hopkins","given":"Dabney","email":"","affiliations":[],"preferred":false,"id":693670,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Nauman, Richard","contributorId":191637,"corporation":false,"usgs":false,"family":"Nauman","given":"Richard","email":"","affiliations":[],"preferred":false,"id":693671,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Derrenbacher, William","contributorId":191638,"corporation":false,"usgs":false,"family":"Derrenbacher","given":"William","email":"","affiliations":[],"preferred":false,"id":693672,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Wright, Dawn J.","contributorId":191639,"corporation":false,"usgs":false,"family":"Wright","given":"Dawn","email":"","middleInitial":"J.","affiliations":[{"id":18946,"text":"Environmental Systems Research Institute, Inc. 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Pierre","contributorId":146809,"corporation":false,"usgs":false,"family":"Defourny","given":"Pierre","email":"","affiliations":[],"preferred":false,"id":693693,"contributorType":{"id":1,"text":"Authors"},"rank":31},{"text":"Arino, Olivier","contributorId":191651,"corporation":false,"usgs":false,"family":"Arino","given":"Olivier","email":"","affiliations":[],"preferred":false,"id":693694,"contributorType":{"id":1,"text":"Authors"},"rank":32},{"text":"Maynard, Simone","contributorId":191652,"corporation":false,"usgs":false,"family":"Maynard","given":"Simone","email":"","affiliations":[],"preferred":false,"id":693695,"contributorType":{"id":1,"text":"Authors"},"rank":33},{"text":"Anderson, Mark","contributorId":191653,"corporation":false,"usgs":false,"family":"Anderson","given":"Mark","affiliations":[{"id":12462,"text":"U.S. Department of the Interior, National Park Service","active":true,"usgs":false}],"preferred":false,"id":693696,"contributorType":{"id":1,"text":"Authors"},"rank":34},{"text":"Comer, Patrick","contributorId":191654,"corporation":false,"usgs":false,"family":"Comer","given":"Patrick","affiliations":[],"preferred":false,"id":693697,"contributorType":{"id":1,"text":"Authors"},"rank":35}]}}
,{"id":70191023,"text":"70191023 - 2014 - Dispersion analysis of passive surface-wave noise generated during hydraulic-fracturing operations","interactions":[],"lastModifiedDate":"2017-09-21T12:06:41","indexId":"70191023","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2165,"text":"Journal of Applied Geophysics","active":true,"publicationSubtype":{"id":10}},"title":"Dispersion analysis of passive surface-wave noise generated during hydraulic-fracturing operations","docAbstract":"<p><span>Surface-wave dispersion analysis is useful for estimating near-surface shear-wave velocity models, designing receiver arrays, and suppressing surface waves. Here, we analyze whether passive seismic noise generated during hydraulic-fracturing operations can be used to extract surface-wave dispersion characteristics. Applying seismic interferometry to noise measurements, we extract surface waves by cross-correlating several minutes of passive records; this approach is distinct from previous studies that used hours or days of passive records for cross-correlation. For comparison, we also perform dispersion analysis for an active-source array that has some receivers in common with the passive array. The active and passive data show good agreement in the dispersive character of the fundamental-mode surface-waves. For the higher mode surface waves, however, active and passive data resolve the dispersive properties at different frequency ranges. To demonstrate an application of dispersion analysis, we invert the observed surface-wave dispersion characteristics to determine the near-surface, one-dimensional shear-wave velocity.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jappgeo.2014.09.008","usgsCitation":"Forghani-Arani, F., Willis, M., Snieder, R., Haines, S.S., Behura, J., Batzle, M., and Davidson, M., 2014, Dispersion analysis of passive surface-wave noise generated during hydraulic-fracturing operations: Journal of Applied Geophysics, v. 111, p. 129-134, https://doi.org/10.1016/j.jappgeo.2014.09.008.","productDescription":"6 p.","startPage":"129","endPage":"134","ipdsId":"IP-058038","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":473305,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.osti.gov/biblio/1556315","text":"Publisher Index Page"},{"id":345987,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"111","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59c4cf97e4b017cf313d3cb8","contributors":{"authors":[{"text":"Forghani-Arani, Farnoush","contributorId":196642,"corporation":false,"usgs":false,"family":"Forghani-Arani","given":"Farnoush","email":"","affiliations":[{"id":34665,"text":"Microseismic Inc.","active":true,"usgs":false}],"preferred":false,"id":710974,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Willis, Mark","contributorId":196643,"corporation":false,"usgs":false,"family":"Willis","given":"Mark","email":"","affiliations":[{"id":34662,"text":"Halliburton","active":true,"usgs":false}],"preferred":false,"id":710975,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Snieder, Roel","contributorId":196644,"corporation":false,"usgs":false,"family":"Snieder","given":"Roel","email":"","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":710976,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Haines, Seth S. 0000-0003-2611-8165 shaines@usgs.gov","orcid":"https://orcid.org/0000-0003-2611-8165","contributorId":1344,"corporation":false,"usgs":true,"family":"Haines","given":"Seth","email":"shaines@usgs.gov","middleInitial":"S.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":710973,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Behura, Jyoti","contributorId":196645,"corporation":false,"usgs":false,"family":"Behura","given":"Jyoti","email":"","affiliations":[{"id":34663,"text":"Seismic Science LLC","active":true,"usgs":false}],"preferred":false,"id":710977,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Batzle, Mike","contributorId":196646,"corporation":false,"usgs":false,"family":"Batzle","given":"Mike","email":"","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":710978,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Davidson, Michael","contributorId":196647,"corporation":false,"usgs":false,"family":"Davidson","given":"Michael","email":"","affiliations":[{"id":17916,"text":"ConocoPhillips","active":true,"usgs":false}],"preferred":false,"id":710979,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70187371,"text":"70187371 - 2014 - Influence of variable rainbow smelt and gizzard shad abundance on walleye diets and growth","interactions":[],"lastModifiedDate":"2017-05-01T12:58:13","indexId":"70187371","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2592,"text":"Lake and Reservoir Management","active":true,"publicationSubtype":{"id":10}},"title":"Influence of variable rainbow smelt and gizzard shad abundance on walleye diets and growth","docAbstract":"<div class=\"hlFld-Abstract test\"><div class=\"abstractSection abstractInFull\"><p>Prey availability influences growth and condition of walleye (<i>Sander vitreus</i>) in large systems. In Lake Oahe, South Dakota, rainbow smelt (<i>Osmerus mordax</i>) and gizzard shad (<i>Dorosoma cepedianum</i>) are primary prey of walleye, but their abundance varies substantially year to year. To evaluate the influence of gizzard shad and rainbow smelt on walleye diets and growth in Lake Oahe, we compared recent estimates of walleye diets and growth in 2008 through 2010 with those from the late 1990s and early 2000s. Walleye diets differed seasonally with increased piscivory in July and October. In 2008, gizzard shad were the dominant prey item of walleye, representing about 60% of the diets by weight; however, by 2009, gizzard shad declined appreciably in the diet (22%) and were completely absent from walleye diets by 2010. Conversely, rainbow smelt abundance represented 12%, 27%, and 90% of walleye diets by weight in 2008, 2009 and 2010, respectively. Changes in growth corresponded to changes in diets, with the slowest growth occurring when gizzard shad were dominant in the diets and increasing growth every year thereafter. Because gizzard shad are only available during short periods (&lt;3 months) in late summer, walleye can only achieve about 50% of their annual maintenance energy requirements from this prey source. Conversely, rainbow smelt, which are available and consumed year round, provide a continuous energy source that contributes to high growth rates. Nonetheless, when abundant, gizzard shad may provide an important subsidy to Lake Oahe walleye during periods of low rainbow smelt abundance.</p></div></div>","language":"English","publisher":"Taylor & Francis","doi":"10.1080/10402381.2014.914989","usgsCitation":"Fincel, M.J., Dembkowski, D., and Chipps, S.R., 2014, Influence of variable rainbow smelt and gizzard shad abundance on walleye diets and growth: Lake and Reservoir Management, v. 30, no. 3, p. 258-267, https://doi.org/10.1080/10402381.2014.914989.","productDescription":"10 p.","startPage":"258","endPage":"267","ipdsId":"IP-049945","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":340675,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"30","issue":"3","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2014-05-16","publicationStatus":"PW","scienceBaseUri":"59084934e4b0fc4e448ffd8c","contributors":{"authors":[{"text":"Fincel, Mark J.","contributorId":171853,"corporation":false,"usgs":false,"family":"Fincel","given":"Mark","email":"","middleInitial":"J.","affiliations":[{"id":26957,"text":"South Dakota Game, Fish and Parks, Ft. Pierre, SD","active":true,"usgs":false}],"preferred":false,"id":693765,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dembkowski, Daniel J.","contributorId":78237,"corporation":false,"usgs":true,"family":"Dembkowski","given":"Daniel J.","affiliations":[],"preferred":false,"id":693766,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chipps, Steven R. 0000-0001-6511-7582 steve_chipps@usgs.gov","orcid":"https://orcid.org/0000-0001-6511-7582","contributorId":2243,"corporation":false,"usgs":true,"family":"Chipps","given":"Steven","email":"steve_chipps@usgs.gov","middleInitial":"R.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":693634,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70187415,"text":"70187415 - 2014 - Incorporating detection probability into northern Great Plains pronghorn population estimates","interactions":[],"lastModifiedDate":"2017-05-02T13:34:29","indexId":"70187415","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Incorporating detection probability into northern Great Plains pronghorn population estimates","docAbstract":"<p><span>Pronghorn (</span><i>Antilocapra americana</i><span>) abundances commonly are estimated using fixed-wing surveys, but these estimates are likely to be negatively biased because of violations of key assumptions underpinning line-transect methodology. Reducing bias and improving precision of abundance estimates through use of detection probability and mark-resight models may allow for more responsive pronghorn management actions. Given their potential application in population estimation, we evaluated detection probability and mark-resight models for use in estimating pronghorn population abundance. We used logistic regression to quantify probabilities that detecting pronghorn might be influenced by group size, animal activity, percent vegetation, cover type, and topography. We estimated pronghorn population size by study area and year using mixed logit-normal mark-resight (MLNM) models. Pronghorn detection probability increased with group size, animal activity, and percent vegetation; overall detection probability was 0.639 (95% CI = 0.612–0.667) with 396 of 620 pronghorn groups detected. Despite model selection uncertainty, the best detection probability models were 44% (range = 8–79%) and 180% (range = 139–217%) greater than traditional pronghorn population estimates. Similarly, the best MLNM models were 28% (range = 3–58%) and 147% (range = 124–180%) greater than traditional population estimates. Detection probability of pronghorn was not constant but depended on both intrinsic and extrinsic factors. When pronghorn detection probability is a function of animal group size, animal activity, landscape complexity, and percent vegetation, traditional aerial survey techniques will result in biased pronghorn abundance estimates. Standardizing survey conditions, increasing resighting occasions, or accounting for variation in individual heterogeneity in mark-resight models will increase the accuracy and precision of pronghorn population estimates.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/jwmg.634","usgsCitation":"Jacques, C.N., Jenks, J., Grovenburg, T.W., Klaver, R.W., and DePerno, C.S., 2014, Incorporating detection probability into northern Great Plains pronghorn population estimates: Journal of Wildlife Management, v. 78, no. 1, p. 164-174, https://doi.org/10.1002/jwmg.634.","productDescription":"11 p.","startPage":"164","endPage":"174","ipdsId":"IP-042502","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":473276,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://lib.dr.iastate.edu/nrem_pubs/231","text":"External Repository"},{"id":340745,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"78","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2013-12-16","publicationStatus":"PW","scienceBaseUri":"59099ab1e4b0fc4e44915810","contributors":{"authors":[{"text":"Jacques, Christopher N.","contributorId":15521,"corporation":false,"usgs":true,"family":"Jacques","given":"Christopher","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":693977,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jenks, Jonathan A.","contributorId":51591,"corporation":false,"usgs":true,"family":"Jenks","given":"Jonathan A.","affiliations":[],"preferred":false,"id":693978,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Grovenburg, Troy W.","contributorId":57712,"corporation":false,"usgs":true,"family":"Grovenburg","given":"Troy","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":693979,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Klaver, Robert W. 0000-0002-3263-9701 bklaver@usgs.gov","orcid":"https://orcid.org/0000-0002-3263-9701","contributorId":3285,"corporation":false,"usgs":true,"family":"Klaver","given":"Robert","email":"bklaver@usgs.gov","middleInitial":"W.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":693980,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"DePerno, Christopher S.","contributorId":10327,"corporation":false,"usgs":true,"family":"DePerno","given":"Christopher","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":693981,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70188320,"text":"70188320 - 2014 - Detecting the influence of best management practices on vegetation near ephemeral streams with Landsat data","interactions":[],"lastModifiedDate":"2017-06-06T14:00:55","indexId":"70188320","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3228,"text":"Rangeland Ecology and Management","onlineIssn":"1551-5028","printIssn":"1550-7424","active":true,"publicationSubtype":{"id":10}},"title":"Detecting the influence of best management practices on vegetation near ephemeral streams with Landsat data","docAbstract":"<p><span>Various best management practices (BMPs) have been implemented on rangelands with the goals of controlling nonpoint source pollution, reducing the impact of livestock in ecologically important riparian areas, and improving grazing distribution. Providing off-stream water sources to livestock in pastures, cross-fencing, and rotational grazing are common rangeland BMPs that have demonstrated success in drawing livestock grazing pressure away from streams. We evaluated the effects of rangeland BMP implementation with six commercial-scale pastures in the northern mixed-grass prairie. Four pastures received a BMP suite consisting of off-stream water, cross-fencing, and deferred-rotation grazing, and two pastures did not receive BMPs. We hypothesized that the BMPs increased the quantity of riparian vegetation cover relative to the conditions in these pastures during the pre-BMP period and to the two pastures that did not receive BMPs. We used a series of 30-m Landsat normalized difference vegetation index (NDVI) images to track the spatial and temporal changes (1984–2010, </span><i>n</i><span> = 24) in vegetation cover, to which NDVI has been well correlated. Validation indicated that the remotely sensed signal from in-channel vegetation was representative of ground conditions. The BMP suite was associated with a 15% increase in the in-channel NDVI (0–30 m from stream centerline) and 18% increase in the riparian NDVI (30–180 m from stream center line). Conversely, the in-channel and riparian NDVI of non-BMP pastures declined 30% and 18% over the study period. The majority of change occurred within 2 yr of BMP implementation. The patterns of in-channel NDVI among pastures suggested that BMP implementation likely altered grazing distribution by decreasing the preferential use of riparian and in-channel areas. We demonstrated that satellite imagery time series are useful in retrospectively evaluating the efficacy of conservation practices, providing critical information to guide adaptive management and decision makers.</span></p>","language":"English","publisher":"Elsevier","doi":"10.2111/REM-D-12-00185.1","usgsCitation":"Rigge, M.B., Smart, A., Wylie, B.K., and de Van Kamp, K., 2014, Detecting the influence of best management practices on vegetation near ephemeral streams with Landsat data: Rangeland Ecology and Management, v. 67, no. 1, p. 1-8, https://doi.org/10.2111/REM-D-12-00185.1.","productDescription":"8 p.","startPage":"1","endPage":"8","ipdsId":"IP-035745","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":342160,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"67","issue":"1","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5937bf2fe4b0f6c2d0d9c781","contributors":{"authors":[{"text":"Rigge, Matthew B. 0000-0003-4471-8009 mrigge@usgs.gov","orcid":"https://orcid.org/0000-0003-4471-8009","contributorId":751,"corporation":false,"usgs":true,"family":"Rigge","given":"Matthew","email":"mrigge@usgs.gov","middleInitial":"B.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":697194,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smart, Alexander","contributorId":24262,"corporation":false,"usgs":true,"family":"Smart","given":"Alexander","affiliations":[],"preferred":false,"id":697310,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wylie, Bruce K. 0000-0002-7374-1083 wylie@usgs.gov","orcid":"https://orcid.org/0000-0002-7374-1083","contributorId":750,"corporation":false,"usgs":true,"family":"Wylie","given":"Bruce","email":"wylie@usgs.gov","middleInitial":"K.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":697311,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"de Van Kamp, Kendall","contributorId":192662,"corporation":false,"usgs":false,"family":"de Van Kamp","given":"Kendall","email":"","affiliations":[],"preferred":false,"id":697312,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70187359,"text":"70187359 - 2014 - The temperature-productivity squeeze: Constraints on brook trout growth along an Appalachian river continuum","interactions":[],"lastModifiedDate":"2017-05-04T12:34:08","indexId":"70187359","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1919,"text":"Hydrobiologia","onlineIssn":"1573-5117","printIssn":"0018-8158","active":true,"publicationSubtype":{"id":10}},"title":"The temperature-productivity squeeze: Constraints on brook trout growth along an Appalachian river continuum","docAbstract":"<p><span>We tested the hypothesis that brook trout growth rates are controlled by a complex interaction of food availability, water temperature, and competitor density. We quantified trout diet, growth, and consumption in small headwater tributaries characterized as cold with low food and high trout density, larger tributaries characterized as cold with moderate food and moderate trout density, and large main stems characterized as warm with high food and low trout density. Brook trout consumption was highest in the main stem where diets shifted from insects in headwaters to fishes and crayfish in larger streams. Despite high water temperatures, trout growth rates also were consistently highest in the main stem, likely due to competitively dominant trout monopolizing thermal refugia. Temporal changes in trout density had a direct negative effect on brook trout growth rates. Our results suggest that competition for food constrains brook trout growth in small streams, but access to thermal refugia in productive main stem habitats enables dominant trout to supplement growth at a watershed scale. Brook trout conservation in this region should seek to relieve the “temperature-productivity squeeze,” whereby brook trout productivity is constrained by access to habitats that provide both suitable water temperature and sufficient prey.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s10750-013-1794-0","usgsCitation":"Petty, J.T., Thorne, D., Huntsman, B.M., and Mazik, P.M., 2014, The temperature-productivity squeeze: Constraints on brook trout growth along an Appalachian river continuum: Hydrobiologia, v. 727, no. 1, p. 151-166, https://doi.org/10.1007/s10750-013-1794-0.","productDescription":"16 p.","startPage":"151","endPage":"166","ipdsId":"IP-042627","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":340823,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"West Virginia","otherGeospatial":"Upper Shaver's Fork","volume":"727","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2013-12-31","publicationStatus":"PW","scienceBaseUri":"590c3dcbe4b0e541a038dd2d","contributors":{"authors":[{"text":"Petty, J. Todd","contributorId":166749,"corporation":false,"usgs":false,"family":"Petty","given":"J.","email":"","middleInitial":"Todd","affiliations":[{"id":24497,"text":"West Virginia University, Morgantown, WV","active":true,"usgs":false}],"preferred":false,"id":693608,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thorne, David","contributorId":191765,"corporation":false,"usgs":false,"family":"Thorne","given":"David","email":"","affiliations":[{"id":24498,"text":"West Virginia Division of Natural Resources, Point Pleasant, WV","active":true,"usgs":false},{"id":25281,"text":"West Virginia University, WV","active":true,"usgs":false}],"preferred":false,"id":694167,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Huntsman, Brock M. 0000-0003-4090-1949","orcid":"https://orcid.org/0000-0003-4090-1949","contributorId":166748,"corporation":false,"usgs":false,"family":"Huntsman","given":"Brock","email":"","middleInitial":"M.","affiliations":[{"id":24497,"text":"West Virginia University, Morgantown, WV","active":true,"usgs":false}],"preferred":false,"id":694168,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mazik, Patricia M. 0000-0002-8046-5929 pmazik@usgs.gov","orcid":"https://orcid.org/0000-0002-8046-5929","contributorId":2318,"corporation":false,"usgs":true,"family":"Mazik","given":"Patricia","email":"pmazik@usgs.gov","middleInitial":"M.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":694169,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70155991,"text":"70155991 - 2014 - Chromic and iron oxides as fecal markers to identify individual whooping cranes","interactions":[],"lastModifiedDate":"2018-02-06T12:41:48","indexId":"70155991","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Chromic and iron oxides as fecal markers to identify individual whooping cranes","docAbstract":"<p>The whooping crane (<i>Grus americana</i>) is listed as endangered under the IUCN Red List, the United States Endangered Species Act, and the Canadian Species at Risk Act (BirdLife International 2012, CWS and USFWS 2007). A major focus of recovery efforts for this endangered species is reintroduction to establish new populations (CWS and USFWS 2007). Captive populations are critical as a source of individuals for reintroduction efforts and also serve as insurance populations. Currently, there are a total of 157 whooping cranes held in captive breeding centers across North America, with the largest at the USGS Patuxent Wildlife Research Center (PWRC) in Laurel, Maryland. Birds produced in this facility are currently being released as part of efforts to establish the Eastern Migratory Population (EMP, Urbanek et al. 2005) and in an effort to establish a non-migratory population in Louisiana. In the past decade, PWRC has produced and released annually an average of 18 birds into the wild; however, reproductive performance of birds at this facility is lower than desired. PWRC had a 60% fertility rate for eggs laid from 2000 through 2010 (J. N. Chandler, personal communication, 2011). Furthermore, reproductive onset in this captive population appears to be delayed compared to wild populations. In wild populations, reproductive onset (production of sperm and eggs) normally occurs ~5 years of age in both males and females, ~2 years after initial pair formation occurs (Ellis et al., 1996), while some females in the EMP have laid eggs earlier than 5 years of age (Converse et al. 2011). However, PWRC females in some cases do not start to lay eggs until 7 years of age (Mirande et al. 1996). Currently, the PWRC population consists of a total of 74 whooping cranes, including 22 pairs. Six of these pairs (27%) are consistently infertile (i.e., no production of fertile eggs) and 3 other pairs (14%) have low fertility (30- 45% fertility in eggs laid), which is variable from year to year. Six pairs (27%) are recently formed and have not produced eggs, and so have unknown fertility. This leaves only 7 pairs (33%) which contribute maximally to PWRC’s chick production (J. N. Chandler, personal communication, 2011). Because of the challenges occurring within this captive colony, PWRC and Smithsonian National Zoo have initiated a joint research project to identify potential underlying causes of poor reproduction in captive whooping cranes. </p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the twelfth North American crane workshop","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"Twelfth North American Crane Workshop","conferenceDate":"March 13-16, 2011","conferenceLocation":"Grand Island, NE","language":"English","publisher":"North American Crane Working Group","isbn":"978-0-9659324-3-1","usgsCitation":"Brown, M.E., Doyle, R., Chandler, J.N., Olsen, G.H., French, J.B., Wildt, D.E., Converse, S.J., Keefer, C., and Songsasen, N., 2014, Chromic and iron oxides as fecal markers to identify individual whooping cranes, <i>in</i> Proceedings of the twelfth North American crane workshop, Grand Island, NE, March 13-16, 2011, p. 68-72.","productDescription":"5 p.","startPage":"68","endPage":"72","ipdsId":"IP-067572","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":339661,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":339660,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.nacwg.org/proceedings12.html"}],"otherGeospatial":"North America","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58f08e63e4b06911a29fa860","contributors":{"editors":[{"text":"Aborn, David","contributorId":141173,"corporation":false,"usgs":false,"family":"Aborn","given":"David","email":"","affiliations":[],"preferred":false,"id":690815,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Urbanek, Richard P.","contributorId":38400,"corporation":false,"usgs":true,"family":"Urbanek","given":"Richard","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":690816,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"Brown, Megan E.","contributorId":146367,"corporation":false,"usgs":false,"family":"Brown","given":"Megan","email":"","middleInitial":"E.","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":567580,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Doyle, Robert rcdoyle@usgs.gov","contributorId":146368,"corporation":false,"usgs":true,"family":"Doyle","given":"Robert","email":"rcdoyle@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":567581,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chandler, Jane N. 0000-0002-6131-2396 jchandler@usgs.gov","orcid":"https://orcid.org/0000-0002-6131-2396","contributorId":3512,"corporation":false,"usgs":true,"family":"Chandler","given":"Jane","email":"jchandler@usgs.gov","middleInitial":"N.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":567582,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Olsen, Glenn H. 0000-0002-7188-6203 golsen@usgs.gov","orcid":"https://orcid.org/0000-0002-7188-6203","contributorId":40918,"corporation":false,"usgs":true,"family":"Olsen","given":"Glenn","email":"golsen@usgs.gov","middleInitial":"H.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":567583,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"French, John B. 0000-0001-8901-7092 jbfrench@usgs.gov","orcid":"https://orcid.org/0000-0001-8901-7092","contributorId":377,"corporation":false,"usgs":true,"family":"French","given":"John","email":"jbfrench@usgs.gov","middleInitial":"B.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":567584,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wildt, David E","contributorId":146369,"corporation":false,"usgs":false,"family":"Wildt","given":"David","email":"","middleInitial":"E","affiliations":[{"id":7035,"text":"Smithsonian Conservation Biology Institute, National Zoological Park","active":true,"usgs":false}],"preferred":false,"id":567585,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Converse, Sarah J. 0000-0002-3719-5441 sconverse@usgs.gov","orcid":"https://orcid.org/0000-0002-3719-5441","contributorId":3513,"corporation":false,"usgs":true,"family":"Converse","given":"Sarah","email":"sconverse@usgs.gov","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":567579,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Keefer, Carol L","contributorId":146370,"corporation":false,"usgs":false,"family":"Keefer","given":"Carol L","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":567586,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Songsasen, Nucharin","contributorId":146371,"corporation":false,"usgs":false,"family":"Songsasen","given":"Nucharin","email":"","affiliations":[{"id":7035,"text":"Smithsonian Conservation Biology Institute, National Zoological Park","active":true,"usgs":false}],"preferred":false,"id":567587,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70187711,"text":"70187711 - 2014 - Estuarine removal of glacial iron and implications for iron fluxes to the ocean","interactions":[],"lastModifiedDate":"2017-05-15T21:45:19","indexId":"70187711","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Estuarine removal of glacial iron and implications for iron fluxes to the ocean","docAbstract":"<p>While recent work demonstrates that glacial meltwater provides a substantial and relatively labile flux of the micronutrient iron to oceans, the role of high-latitude estuary environments as a potential sink of glacial iron is unknown. Here we present the first quantitative description of iron removal in a meltwater-dominated estuary. We find that 85% of “dissolved” Fe is removed in the low-salinity region of the estuary along with 41% of “total dissolvable” iron associated with glacial flour. We couple these findings with hydrologic and geochemical data from Gulf of Alaska (GoA) glacierized catchments to calculate meltwater-derived fluxes of size and species partitioned Fe to the GoA. Iron flux data indicate that labile iron in the glacial flour and associated Fe minerals dominate the meltwater contribution to the Fe budget of the GoA. As such, GoA nutrient cycles and related ecosystems could be strongly influenced by continued ice loss in its watershed.</p>","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2014GL060199","usgsCitation":"Schroth, A.W., Crusius, J., Hoyer, I., and Campbell, R., 2014, Estuarine removal of glacial iron and implications for iron fluxes to the ocean: Geophysical Research Letters, v. 41, no. 11, p. 3951-3958, https://doi.org/10.1002/2014GL060199.","productDescription":"8 p.","startPage":"3951","endPage":"3958","ipdsId":"IP-055771","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":473420,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2014gl060199","text":"Publisher Index Page"},{"id":341327,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"41","issue":"11","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2014-06-06","publicationStatus":"PW","scienceBaseUri":"591abe39e4b0a7fdb43c8bff","contributors":{"authors":[{"text":"Schroth, Andrew W.","contributorId":192042,"corporation":false,"usgs":false,"family":"Schroth","given":"Andrew","email":"","middleInitial":"W.","affiliations":[{"id":17809,"text":"University of Vermont, Burlington","active":true,"usgs":false}],"preferred":false,"id":695218,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Crusius, John 0000-0003-2554-0831 jcrusius@usgs.gov","orcid":"https://orcid.org/0000-0003-2554-0831","contributorId":2155,"corporation":false,"usgs":true,"family":"Crusius","given":"John","email":"jcrusius@usgs.gov","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":695216,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hoyer, Ian","contributorId":192041,"corporation":false,"usgs":false,"family":"Hoyer","given":"Ian","email":"","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":695217,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Campbell, Robert","contributorId":192043,"corporation":false,"usgs":false,"family":"Campbell","given":"Robert","affiliations":[{"id":13600,"text":"Prince William Sound Science Center","active":true,"usgs":false}],"preferred":false,"id":695219,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
]}