{"pageNumber":"722","pageRowStart":"18025","pageSize":"25","recordCount":40783,"records":[{"id":70187487,"text":"70187487 - 2012 - Habitat and prey availability attributes associated with juvenile and early adult pallid sturgeon occurrence in the Missouri River, USA","interactions":[],"lastModifiedDate":"2017-05-04T18:14:07","indexId":"70187487","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1497,"text":"Endangered Species Research","active":true,"publicationSubtype":{"id":10}},"title":"Habitat and prey availability attributes associated with juvenile and early adult pallid sturgeon occurrence in the Missouri River, USA","docAbstract":"<p><span>The pallid sturgeon </span><i>Scaphirhynchus albus</i><span> is a federally endangered species native to the Missouri and lower Mississippi Rivers, USA. As part of recovery efforts, over 360000 pallid sturgeon have been stocked into the Missouri River since 1994, and a standardized, long-term monitoring program was initiated in 2003. Understanding the distribution and habitat requirements of juvenile and early adult pallid sturgeon (fork length &lt;720 mm, age &lt;10 yr) is an important goal of the monitoring and recovery programs. In this study, we collected information on habitat characteristics and prey availability from the upper Missouri River along the Nebraska-South Dakota border and compared these attributes between capture (present) and non-capture (absent) locations (N = 59). To evaluate the relative influence of habitat and prey availability on pallid sturgeon occurrence, we examined several candidate models using an information-theoretic approach. A prey availability model had the most support and included site-specific information on Diptera and Ephemeroptera abundance. A habitat-based model showed that juveniles and early adults were found in relatively deeper water and avoided areas where bottom velocities were greater than 1.2 m s</span><sup>−1</sup><span>. Although not as well supported as the prey-effects model (evidence ratio = 6.4), habitat features also provided a plausible model for predicting occurrence. The models developed here could be used to evaluate pallid sturgeon habitat potential in the Missouri River basin and help guide future monitoring and conservation management of this endangered species.</span></p>","language":"English","publisher":"Inter-Research","doi":"10.3354/esr00408","usgsCitation":"Spindler, B.D., Chipps, S.R., Klumb, R.A., Graeb, B.D., and Wimberly, M.C., 2012, Habitat and prey availability attributes associated with juvenile and early adult pallid sturgeon occurrence in the Missouri River, USA: Endangered Species Research, v. 16, no. 3, p. 225-234, https://doi.org/10.3354/esr00408.","productDescription":"10 p.","startPage":"225","endPage":"234","ipdsId":"IP-034025","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":474669,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/esr00408","text":"Publisher Index Page"},{"id":340847,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Missouri River","volume":"16","issue":"3","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"590c3dcbe4b0e541a038dd2f","contributors":{"authors":[{"text":"Spindler, Bryan D.","contributorId":171900,"corporation":false,"usgs":true,"family":"Spindler","given":"Bryan","email":"","middleInitial":"D.","affiliations":[{"id":561,"text":"South Dakota Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true},{"id":5089,"text":"South Dakota State University","active":true,"usgs":false}],"preferred":false,"id":694161,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":694226,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Klumb, Robert A.","contributorId":86606,"corporation":false,"usgs":true,"family":"Klumb","given":"Robert","email":"","middleInitial":"A.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false},{"id":5089,"text":"South Dakota State University","active":true,"usgs":false},{"id":561,"text":"South Dakota Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true}],"preferred":false,"id":694227,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Graeb, Brian D. S.","contributorId":171851,"corporation":false,"usgs":false,"family":"Graeb","given":"Brian","email":"","middleInitial":"D. S.","affiliations":[{"id":26956,"text":"Departement of Natural Resource Management, Brookings, SD","active":true,"usgs":false}],"preferred":false,"id":694228,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wimberly, Michael C.","contributorId":167855,"corporation":false,"usgs":false,"family":"Wimberly","given":"Michael","email":"","middleInitial":"C.","affiliations":[{"id":5089,"text":"South Dakota State University","active":true,"usgs":false}],"preferred":false,"id":694229,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70187481,"text":"70187481 - 2012 - An application and extension of the constraints–effects–mitigation model to Minnesota waterfowl hunting","interactions":[],"lastModifiedDate":"2017-05-08T11:21:10","indexId":"70187481","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1909,"text":"Human Dimensions of Wildlife","active":true,"publicationSubtype":{"id":10}},"title":"An application and extension of the constraints–effects–mitigation model to Minnesota waterfowl hunting","docAbstract":"<p><span>This study extends modeling work on the leisure constraint negotiation process from physically active leisure and celebrity fandom to hunting. We test a model derived from the constraints–effects–mitigation model of leisure participation. The model is examined in the context of continued Minnesota waterfowl hunting among a sample of Minnesota residents who purchased a North Dakota waterfowl stamp. Results are from a mail survey conducted in 2006. In our modeling, successful constraint negotiation fully mediated the constraints–participation relationship, while involvement had both direct and indirect effects on participation. Hunter motivation was positively related to involvement. Results advance understanding of the relationships among factors that influence leisure participation, and suggest that constraint negotiation may differ among recreation activities with different participant profiles.</span></p>","language":"English","publisher":"Taylor & Francis","doi":"10.1080/10871209.2012.650317","usgsCitation":"Schroeder, S., Fulton, D.C., Lawrence, J.S., and Cordts, S.D., 2012, An application and extension of the constraints–effects–mitigation model to Minnesota waterfowl hunting: Human Dimensions of Wildlife, v. 17, no. 3, p. 174-192, https://doi.org/10.1080/10871209.2012.650317.","productDescription":"19 p.","startPage":"174","endPage":"192","ipdsId":"IP-035094","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":340915,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"17","issue":"3","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"591183b9e4b0e541a03c1a88","contributors":{"authors":[{"text":"Schroeder, Susan A.","contributorId":78235,"corporation":false,"usgs":true,"family":"Schroeder","given":"Susan A.","affiliations":[],"preferred":false,"id":694418,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fulton, David C. 0000-0001-5763-7887 dcf@usgs.gov","orcid":"https://orcid.org/0000-0001-5763-7887","contributorId":2208,"corporation":false,"usgs":true,"family":"Fulton","given":"David","email":"dcf@usgs.gov","middleInitial":"C.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":694122,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lawrence, Jeffrey S.","contributorId":171470,"corporation":false,"usgs":false,"family":"Lawrence","given":"Jeffrey","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":694419,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cordts, Steven D.","contributorId":171471,"corporation":false,"usgs":false,"family":"Cordts","given":"Steven","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":694420,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70193553,"text":"70193553 - 2012 - Seawater capacitance – a promising proxy for mapping and characterizing drifting hydrocarbon plumes in the deep ocean","interactions":[],"lastModifiedDate":"2017-11-02T16:49:14","indexId":"70193553","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5537,"text":"Ocean Science","active":true,"publicationSubtype":{"id":10}},"title":"Seawater capacitance – a promising proxy for mapping and characterizing drifting hydrocarbon plumes in the deep ocean","docAbstract":"<p><span>Hydrocarbons released into the deep ocean are an inevitable consequence of natural seep, seafloor drilling, and leaking wellhead-to-collection-point pipelines. The Macondo 252 (Deepwater Horizon) well blowout of 2010 was even larger than the Ixtoc event in the Gulf of Campeche in 1979. History suggests it will not be the last accidental release, as deepwater drilling expands to meet an ever-growing demand. For those who must respond to this kind of disaster, the first line of action should be to know what is going on. This includes knowing where an oil plume is at any given time, where and how fast it is moving, and how it is evolving or degrading. We have experimented in the laboratory with induced polarization as a method to track hydrocarbons in the seawater column and find that finely dispersed oil in seawater gives rise to a large distributed capacitance. From previous sea trials, we infer this could potentially be used to both map and characterize oil plumes, down to a ratio of less than 0.001 oil-to-seawater, drifting and evolving in the deep ocean. A side benefit demonstrated in some earlier sea trials is that this same approach in modified form can also map certain heavy placer minerals, as well as communication cables, pipelines, and wrecks buried beneath the seafloor.</span></p>","language":"English","publisher":"EGU","doi":"10.5194/os-8-1099-2012","usgsCitation":"Wynn, J., and Fleming, J., 2012, Seawater capacitance – a promising proxy for mapping and characterizing drifting hydrocarbon plumes in the deep ocean: Ocean Science, v. 8, p. 1099-1104, https://doi.org/10.5194/os-8-1099-2012.","productDescription":"6 p.","startPage":"1099","endPage":"1104","ipdsId":"IP-036617","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":474631,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/os-8-1099-2012","text":"Publisher Index Page"},{"id":348151,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2012-12-18","publicationStatus":"PW","scienceBaseUri":"59fc2eb1e4b0531197b28028","contributors":{"authors":[{"text":"Wynn, Jeff 0000-0002-8102-3882 jwynn@usgs.gov","orcid":"https://orcid.org/0000-0002-8102-3882","contributorId":2803,"corporation":false,"usgs":true,"family":"Wynn","given":"Jeff","email":"jwynn@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":719347,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fleming, John A.","contributorId":199522,"corporation":false,"usgs":false,"family":"Fleming","given":"John A.","affiliations":[],"preferred":false,"id":719348,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70190475,"text":"70190475 - 2012 - The Quaternary thrust system of the northern Alaska Range","interactions":[],"lastModifiedDate":"2017-09-01T09:51:29","indexId":"70190475","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1820,"text":"Geosphere","active":true,"publicationSubtype":{"id":10}},"title":"The Quaternary thrust system of the northern Alaska Range","docAbstract":"<p id=\"p-1\">The framework of Quaternary faults in Alaska remains poorly constrained. Recent studies in the Alaska Range north of the Denali fault add significantly to the recognition of Quaternary deformation in this active orogen. Faults and folds active during the Quaternary occur over a length of ∼500 km along the northern flank of the Alaska Range, extending from Mount McKinley (Denali) eastward to the Tok River valley. These faults exist as a continuous system of active structures, but we divide the system into four regions based on east-west changes in structural style. At the western end, the Kantishna Hills have only two known faults but the highest rate of shallow crustal seismicity. The western northern foothills fold-thrust belt consists of a 50-km-wide zone of subparallel thrust and reverse faults. This broad zone of deformation narrows to the east in a transition zone where the range-bounding fault of the western northern foothills fold-thrust belt terminates and displacement occurs on thrust and/or reverse faults closer to the Denali fault. The eastern northern foothills fold-thrust belt is characterized by ∼40-km-long thrust fault segments separated across left-steps by NNE-trending left-lateral faults. Altogether, these faults accommodate much of the topographic growth of the northern flank of the Alaska Range.</p><p id=\"p-2\">Recognition of this thrust fault system represents a significant concern in addition to the Denali fault for infrastructure adjacent to and transecting the Alaska Range. Although additional work is required to characterize these faults sufficiently for seismic hazard analysis, the regional extent and structural character should require the consideration of the northern Alaska Range thrust system in regional tectonic models.</p>","language":"English","publisher":"Geosphere","doi":"10.1130/GES00695.1","usgsCitation":"Bemis, S.P., Carver, G.A., and Koehler, R., 2012, The Quaternary thrust system of the northern Alaska Range: Geosphere, v. 8, no. 1, p. 196-205, https://doi.org/10.1130/GES00695.1.","productDescription":"10 p.","startPage":"196","endPage":"205","ipdsId":"IP-028908","costCenters":[{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":474688,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges00695.1","text":"Publisher Index Page"},{"id":345409,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","volume":"8","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59aa71dbe4b0e9bde130cffc","contributors":{"authors":[{"text":"Bemis, Sean P.","contributorId":30709,"corporation":false,"usgs":true,"family":"Bemis","given":"Sean","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":709399,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carver, Gary A.","contributorId":196121,"corporation":false,"usgs":false,"family":"Carver","given":"Gary","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":709400,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Koehler, Richard D.","contributorId":76993,"corporation":false,"usgs":true,"family":"Koehler","given":"Richard D.","affiliations":[],"preferred":false,"id":709401,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70193579,"text":"70193579 - 2012 - The 2010 explosive eruption of Java's Merapi volcano—A ‘100-year’ event","interactions":[],"lastModifiedDate":"2017-11-02T10:54:49","indexId":"70193579","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"The 2010 explosive eruption of Java's Merapi volcano—A ‘100-year’ event","docAbstract":"<p><span>Merapi volcano (Indonesia) is one of the most active and hazardous volcanoes in the world. It is known for frequent small to moderate eruptions, pyroclastic flows produced by lava dome collapse, and the large population settled on and around the flanks of the volcano that is at risk. Its usual behavior for the last decades abruptly changed in late October and early November 2010, when the volcano produced its largest and most explosive eruptions in more than a century, displacing at least a third of a million people, and claiming nearly 400 lives. Despite the challenges involved in forecasting this ‘hundred year eruption’, we show that the magnitude of precursory signals (seismicity, ground deformation, gas emissions) was proportional to the large size and intensity of the eruption. In addition and for the first time, near-real-time satellite radar imagery played an equal role with seismic, geodetic, and gas observations in monitoring eruptive activity during a major volcanic crisis. The Indonesian Center of Volcanology and Geological Hazard Mitigation (CVGHM) issued timely forecasts of the magnitude of the eruption phases, saving 10,000–20,000 lives. In addition to reporting on aspects of the crisis management, we report the first synthesis of scientific observations of the eruption. Our monitoring and petrologic data show that the 2010 eruption was fed by rapid ascent of magma from depths ranging from 5 to 30</span><span>&nbsp;</span><span>km. Magma reached the surface with variable gas content resulting in alternating explosive and rapid effusive eruptions, and released a total of ~</span><span>&nbsp;</span><span>0.44</span><span>&nbsp;</span><span>Tg of SO</span><sub>2</sub><span>. The eruptive behavior seems also related to the seismicity along a tectonic fault more than 40</span><span>&nbsp;</span><span>km from the volcano, highlighting both the complex stress pattern of the Merapi region of Java and the role of magmatic pressurization in activating regional faults. We suggest a dynamic triggering of the main explosions on 3 and 4 November by the passing seismic waves generated by regional earthquakes on these days.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2012.06.018","usgsCitation":", S., Jousset, P., Pallister, J.S., Boichu, M., Buongiorno, M.F., Budisantoso, A., Costa, F., Andreastuti, S., Prata, F., Schneider, D.J., Clarisse, L., Humaida, H., Sumarti, S., Bignami, C., Griswold, J.P., Carn, S.A., Oppenheimer, C., and Lavigne, F., 2012, The 2010 explosive eruption of Java's Merapi volcano—A ‘100-year’ event: Journal of Volcanology and Geothermal Research, v. 241-242, p. 121-135, https://doi.org/10.1016/j.jvolgeores.2012.06.018.","productDescription":"15 p.","startPage":"121","endPage":"135","ipdsId":"IP-037583","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":488719,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://gfzpublic.gfz-potsdam.de/pubman/item/item_246296","text":"External Repository"},{"id":348072,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Indonesia","otherGeospatial":"Merapi volcano","volume":"241-242","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59fc2eb1e4b0531197b28026","contributors":{"authors":[{"text":" Surono","contributorId":149582,"corporation":false,"usgs":false,"given":"Surono","email":"","affiliations":[],"preferred":false,"id":719436,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jousset, Philippe","contributorId":194796,"corporation":false,"usgs":false,"family":"Jousset","given":"Philippe","email":"","affiliations":[],"preferred":false,"id":719437,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pallister, John S. 0000-0002-2041-2147 jpallist@usgs.gov","orcid":"https://orcid.org/0000-0002-2041-2147","contributorId":2024,"corporation":false,"usgs":true,"family":"Pallister","given":"John","email":"jpallist@usgs.gov","middleInitial":"S.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":719438,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Boichu, Marie","contributorId":199559,"corporation":false,"usgs":false,"family":"Boichu","given":"Marie","email":"","affiliations":[],"preferred":false,"id":719439,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Buongiorno, M. Fabrizia","contributorId":102698,"corporation":false,"usgs":true,"family":"Buongiorno","given":"M.","email":"","middleInitial":"Fabrizia","affiliations":[],"preferred":false,"id":719440,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Budisantoso, Agus","contributorId":199556,"corporation":false,"usgs":false,"family":"Budisantoso","given":"Agus","email":"","affiliations":[],"preferred":false,"id":719441,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Costa, Fidel","contributorId":184169,"corporation":false,"usgs":false,"family":"Costa","given":"Fidel","email":"","affiliations":[],"preferred":false,"id":719442,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Andreastuti, Supriyati","contributorId":82087,"corporation":false,"usgs":true,"family":"Andreastuti","given":"Supriyati","email":"","affiliations":[],"preferred":false,"id":719443,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Prata, Fred","contributorId":148068,"corporation":false,"usgs":false,"family":"Prata","given":"Fred","email":"","affiliations":[{"id":16991,"text":"Norwegian Institute for Air Research","active":true,"usgs":false}],"preferred":false,"id":719444,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Schneider, David J. 0000-0001-9092-1054 djschneider@usgs.gov","orcid":"https://orcid.org/0000-0001-9092-1054","contributorId":198601,"corporation":false,"usgs":true,"family":"Schneider","given":"David","email":"djschneider@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":true,"id":719445,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Clarisse, Lieven","contributorId":199561,"corporation":false,"usgs":false,"family":"Clarisse","given":"Lieven","email":"","affiliations":[],"preferred":false,"id":719446,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Humaida, Hanik","contributorId":199562,"corporation":false,"usgs":false,"family":"Humaida","given":"Hanik","email":"","affiliations":[],"preferred":false,"id":719447,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Sumarti, Sri","contributorId":149584,"corporation":false,"usgs":false,"family":"Sumarti","given":"Sri","email":"","affiliations":[],"preferred":false,"id":719448,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Bignami, Christian","contributorId":199563,"corporation":false,"usgs":false,"family":"Bignami","given":"Christian","email":"","affiliations":[],"preferred":false,"id":719449,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Griswold, Julia P. griswold@usgs.gov","contributorId":4148,"corporation":false,"usgs":true,"family":"Griswold","given":"Julia","email":"griswold@usgs.gov","middleInitial":"P.","affiliations":[],"preferred":true,"id":719450,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Carn, Simon A.","contributorId":28092,"corporation":false,"usgs":true,"family":"Carn","given":"Simon","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":719451,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Oppenheimer, Clive","contributorId":174445,"corporation":false,"usgs":false,"family":"Oppenheimer","given":"Clive","email":"","affiliations":[{"id":27136,"text":"University of Cambridge","active":true,"usgs":false}],"preferred":false,"id":719452,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Lavigne, Franck","contributorId":66030,"corporation":false,"usgs":true,"family":"Lavigne","given":"Franck","email":"","affiliations":[],"preferred":false,"id":719453,"contributorType":{"id":1,"text":"Authors"},"rank":18}]}}
,{"id":70191242,"text":"70191242 - 2012 - The origins of Late Quaternary debris avalanche and debris flow deposits from Cofre de Perote volcano, México","interactions":[],"lastModifiedDate":"2017-10-02T15:21:19","indexId":"70191242","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1820,"text":"Geosphere","active":true,"publicationSubtype":{"id":10}},"title":"The origins of Late Quaternary debris avalanche and debris flow deposits from Cofre de Perote volcano, México","docAbstract":"<p id=\"p-1\">Cofre de Perote volcano is a compound, shield-like volcano located in the northeastern Trans-Mexican volcanic belt. Large debris avalanche and lahar deposits are associated with the evolution of Cofre. The two best preserved of these debris-avalanche and debris-flow deposits are the ∼42 ka “Los Pescados debris flow” deposit and the ∼11–13 ka “Xico avalanche” deposit, both of which display contrasting morphological and textural characteristics, source materials, origins and emplacement environments. Laboratory X-ray diffraction and visible-infrared reflectance spectroscopy were used to identify the most abundant clay, sulfate, ferric-iron, and silica minerals in the deposits, which were either related to hydrothermal alteration or chemical weathering processes. Cloud-free Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) remote sensing imagery, supporting EO-1 Hyperion image spectra, and field ground truth samples were used to map the mineralogy and distribution of hydrothermally altered rocks on the modern summit of Cofre de Perote. The results were then compared to minerals identified in the two debris-avalanche and debris-flow deposits in order to assess possible source materials and origins for the two deposits.</p><p id=\"p-2\">The older Los Pescados debris-flow deposit contains mostly halloysite and hydrous silica minerals, which match the dominant mineralogy of soils and weathered volcanic deposit in the surrounding flanks of Cofre de Perote. Its source materials were most likely derived from initially noncohesive or clay-poor flows, which subsequently bulked with clay-rich valley soils and alluvium in a manner similar to lahars from Nevado del Ruiz in 1985, but on a larger scale. The younger Xico avalanche deposit contains abundant smectite, jarosite, kaolinite, gypsum, and mixed-layered illite/smectite, which are either definitely or most likely of hydrothermal alteration origin. Smectite in particular appears to be the most abundant and spectrally dominant mineral in summit ground truth samples, ASTER mapping results, Xico avalanche deposit, and an older (pre-Xico avalanche) deposit derived from collapse(s) of ancestral Cofre de Perote edifice. However, both Xico avalanche and Los Pescados debris flow deposits show some evidence of secondary, postemplacement weathering and induration, which is evident by the presence of gibbsite, and hydroxyl interlayered minerals, in addition to recently formed halloysite and hydrous silica (i.e., indurating) cements. Field-based, visible infrared image spectroscopy (VIS/IR) spectral measurements offer the possibility of distinguishing primary minerals of hydrothermal alteration origin in debris-avalanche and debris-flow deposits from those produced either by in situ chemical weathering or bulked from weathered source materials.</p>","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES00709.1","usgsCitation":"Diaz-Castellon, R., Hubbard, B.E., Carrasco-Nunez, G., and Rodriguez-Vargas, J.L., 2012, The origins of Late Quaternary debris avalanche and debris flow deposits from Cofre de Perote volcano, México: Geosphere, v. 8, no. 4, p. 950-971, https://doi.org/10.1130/GES00709.1.","productDescription":"22 p.","startPage":"950","endPage":"971","ipdsId":"IP-018041","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":474665,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges00709.1","text":"Publisher Index Page"},{"id":346331,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico","otherGeospatial":"Cofre de Perote volcano","volume":"8","issue":"4","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59d3502ce4b05fe04cc34d88","contributors":{"authors":[{"text":"Diaz-Castellon, Rodolfo","contributorId":37936,"corporation":false,"usgs":true,"family":"Diaz-Castellon","given":"Rodolfo","email":"","affiliations":[],"preferred":false,"id":711786,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hubbard, Bernard E. 0000-0002-9315-2032 bhubbard@usgs.gov","orcid":"https://orcid.org/0000-0002-9315-2032","contributorId":2342,"corporation":false,"usgs":true,"family":"Hubbard","given":"Bernard","email":"bhubbard@usgs.gov","middleInitial":"E.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":711660,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Carrasco-Nunez, Gerardo","contributorId":44714,"corporation":false,"usgs":true,"family":"Carrasco-Nunez","given":"Gerardo","email":"","affiliations":[],"preferred":false,"id":711787,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rodriguez-Vargas, Jose Luis","contributorId":196860,"corporation":false,"usgs":false,"family":"Rodriguez-Vargas","given":"Jose","email":"","middleInitial":"Luis","affiliations":[],"preferred":false,"id":711788,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70191252,"text":"70191252 - 2012 - Strata-bound Fe-Co-Cu-Au-Bi-Y-REE deposits of the Idaho Cobalt Belt: Multistage hydrothermal mineralization in a magmatic-related iron oxide copper-gold system","interactions":[],"lastModifiedDate":"2017-10-02T16:37:55","indexId":"70191252","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1472,"text":"Economic Geology","active":true,"publicationSubtype":{"id":10}},"title":"Strata-bound Fe-Co-Cu-Au-Bi-Y-REE deposits of the Idaho Cobalt Belt: Multistage hydrothermal mineralization in a magmatic-related iron oxide copper-gold system","docAbstract":"<p id=\"p-1\">Mineralogical and geochemical studies of strata-bound Fe-Co-Cu-Au-Bi-Y-rare-earth element (REE) deposits of the Idaho cobalt belt in east-central Idaho provide evidence of multistage epigenetic mineralization by magmatic-hydrothermal processes in an iron oxide copper-gold (IOCG) system. Deposits of the Idaho cobalt belt comprise three types: (1) strata-bound sulfide lenses in the Blackbird district, which are cobaltite and, less commonly, chalcopyrite rich with locally abundant gold, native bismuth, bismuthinite, xenotime, allanite, monazite, and the Be-rich silicate gadolinite-(Y), with sparse uraninite, stannite, and Bi tellurides, in a gangue of quartz, chlorite, biotite, muscovite, garnet, tourmaline, chloritoid, and/or siderite, with locally abundant fluorapatite or magnetite; (2) discordant tourmalinized breccias in the Blackbird district that in places have concentrations of cobaltite, chalcopyrite, gold, and xenotime; and (3) strata-bound magnetite-rich lenses in the Iron Creek area, which contain cobaltiferous pyrite and locally sparse chalcopyrite or xenotime. Most sulfide-rich deposits in the Blackbird district are enclosed by strata-bound lenses composed mainly of Cl-rich Fe biotite; some deposits have quartz-rich envelopes.</p><p id=\"p-2\">Whole-rock analyses of 48 Co- and/or Cu-rich samples show high concentrations of Au (up to 26.8 ppm), Bi (up to 9.16 wt %), Y (up to 0.83 wt %), ∑REEs (up to 2.56 wt %), Ni (up to 6,780 ppm), and Be (up to 1,180 ppm), with locally elevated U (up to 124 ppm) and Sn (up to 133 ppm); Zn and Pb contents are uniformly low (≤821 and ≤61 ppm, respectively). Varimax factor analysis of bulk compositions of these samples reveals geochemically distinct element groupings that reflect statistical associations of monazite, allanite, and xenotime; biotite and gold; detrital minerals; chalcopyrite and sparse stannite; quartz; and cobaltite with sparse selenides and tellurides. Significantly, Cu is statistically separate from Co and As, consistent with the general lack of abundant chalcopyrite in cobaltite-rich samples.</p><p id=\"p-3\">Paragenetic relations determined by scanning electron microscopy indicate that the earliest Y-REE-Be mineralization preceded deposition of Co, Cu, Au, and Bi. Allanite, xenotime, and gadolinite-(Y) commonly occur as intergrowths with and inclusions in cobaltite; the opposite texture is rare. Monazite, in contrast, forms a poikiloblastic matrix to cobaltite and thin rims on allanite and xenotime, reflecting a later metamorphic paragenesis. Allanite and xenotime also show evidence of late dissolution and reprecipitation, forming discordant rims on older anhedral allanite and xenotime and separate euhedral crystals of each mineral. Textural data suggest extensive deformation of the deposits by folding and shearing, and by pervasive recrystallization, all during Cretaceous metamorphism. Sensitive high resolution ion microprobe U-Pb geochronology by<span>&nbsp;</span><span id=\"xref-ref-4-1\" class=\"xref-bibr\">Aleinikoff et al. (2012)</span><span>&nbsp;</span>supports these paragenetic interpretations, documenting contemporaneous Mesoproterozoic growth of early xenotime and crystallization of megacrystic A-type granite on the northern border of the district. These ages are used together with mineralogical and geochemical data from the present study to support an epigenetic, IOCG model for Fe-Co-Cu-Au-Bi-Y-REE deposits of the Idaho cobalt belt. A sulfide facies variant of IOCG deposits is proposed for the Blackbird district, in which reducing hydrothermal conditions favored deposition of sulfide minerals over iron oxides. This new model includes Mesoproterozoic vein mineralization and related Fe-Cl metasomatism that formed the biotite-rich lenses, a predominantly felsic magmatic source for metals in the deposits, given their local abundance of Y, REEs, and Be, and a major sedimentary component in the hydrothermal fluids based on independent sulfur isotope and boron isotope data for sulfides and ore-related tourmaline, respectively.</p>","language":"English","publisher":"Society of Economic Geologists","doi":"10.2113/econgeo.107.6.1089","usgsCitation":"Slack, J.F., 2012, Strata-bound Fe-Co-Cu-Au-Bi-Y-REE deposits of the Idaho Cobalt Belt: Multistage hydrothermal mineralization in a magmatic-related iron oxide copper-gold system: Economic Geology, v. 107, no. 6, p. 1089-1113, https://doi.org/10.2113/econgeo.107.6.1089.","productDescription":"25 p.","startPage":"1089","endPage":"1113","ipdsId":"IP-030528","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":346338,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"107","issue":"6","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2012-09-20","publicationStatus":"PW","scienceBaseUri":"59d3502ce4b05fe04cc34d84","contributors":{"authors":[{"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":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":711688,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70193004,"text":"70193004 - 2012 - Design and implementation of the next generation Landsat satellite communications system","interactions":[],"lastModifiedDate":"2017-12-20T10:53:10","indexId":"70193004","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Design and implementation of the next generation Landsat satellite communications system","docAbstract":"<p>The next generation Landsat satellite, Landsat 8 (L8), also known as the Landsat Data Continuity Mission (LDCM), uses a highly spectrally efficient modulation and data formatting approach to provide large amounts of downlink (D/L) bandwidth in a limited X-Band spectrum allocation. In addition to purely data throughput and bandwidth considerations, there were a number of additional constraints based on operational considerations for prevention of interference with the NASA Deep-Space Network (DSN) band just above the L8 D/L band, minimization of jitter contributions to prevent impacts to instrument performance, and the need to provide an interface to the Landsat International Cooperator (IC) community. A series of trade studies were conducted to consider either X- or Ka-Band, modulation type, and antenna coverage type, prior to the release of the request for proposal (RFP) for the spacecraft. Through use of the spectrally efficient rate-7/8 Low-Density Parity-Check error-correction coding and novel filtering, an XBand frequency plan was developed that balances all the constraints and considerations, while providing world-class link performance, fitting 384 Mbits/sec of data into the 375 MHz X-Band allocation with bit-error rates better than 10-12 using an earth-coverage antenna.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings from the International Telemetering Conference ","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"International Foundation for Telemetering","usgsCitation":"Mah, G.R., O’Brien, M., Garon, H., Mott, C., Ames, A., and Dearth, K., 2012, Design and implementation of the next generation Landsat satellite communications system, <i>in</i> Proceedings from the International Telemetering Conference , 14 p.","productDescription":"14 p.","ipdsId":"IP-038940","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":350124,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":347674,"type":{"id":15,"text":"Index Page"},"url":"https://arizona.openrepository.com/arizona/handle/10150/581626"}],"publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a6105a0e4b06e28e9c2557f","contributors":{"authors":[{"text":"Mah, Grant R. 0000-0002-2584-3915 mah@usgs.gov","orcid":"https://orcid.org/0000-0002-2584-3915","contributorId":4087,"corporation":false,"usgs":true,"family":"Mah","given":"Grant","email":"mah@usgs.gov","middleInitial":"R.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":717588,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"O’Brien, Michael mobrien@usgs.gov","contributorId":4333,"corporation":false,"usgs":true,"family":"O’Brien","given":"Michael","email":"mobrien@usgs.gov","affiliations":[],"preferred":true,"id":717589,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Garon, Howard","contributorId":198902,"corporation":false,"usgs":false,"family":"Garon","given":"Howard","email":"","affiliations":[],"preferred":false,"id":717592,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mott, Claire","contributorId":198901,"corporation":false,"usgs":false,"family":"Mott","given":"Claire","email":"","affiliations":[],"preferred":false,"id":717591,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ames, Alan","contributorId":198900,"corporation":false,"usgs":false,"family":"Ames","given":"Alan","email":"","affiliations":[],"preferred":false,"id":717590,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dearth, Ken","contributorId":198903,"corporation":false,"usgs":false,"family":"Dearth","given":"Ken","email":"","affiliations":[],"preferred":false,"id":717593,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70188861,"text":"70188861 - 2012 - Fluvial transport and surface enrichment of arsenic in semi-arid mining regions: examples from the Mojave Desert, California","interactions":[],"lastModifiedDate":"2017-06-27T10:11:21","indexId":"70188861","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2259,"text":"Journal of Environmental Monitoring","active":true,"publicationSubtype":{"id":10}},"title":"Fluvial transport and surface enrichment of arsenic in semi-arid mining regions: examples from the Mojave Desert, California","docAbstract":"<p><span>As a result of extensive gold and silver mining in the Mojave Desert, southern California, mine wastes and tailings containing highly elevated arsenic (As) concentrations remain exposed at a number of former mining sites. Decades of weathering and erosion have contributed to the mobilization of As-enriched tailings, which now contaminate surrounding communities. Fluvial transport plays an intermittent yet important and relatively undocumented role in the migration and dispersal of As-contaminated mine wastes in semi-arid climates. Assessing the contribution of fluvial systems to tailings mobilization is critical in order to assess the distribution and long-term exposure potential of tailings in a mining-impacted environment. Extensive sampling, chemical analysis, and geospatial mapping of dry streambed (wash) sediments, tailings piles, alluvial fans, and rainwater runoff at multiple mine sites have aided the development of a conceptual model to explain the fluvial migration of mine wastes in semi-arid climates. Intense and episodic </span>precipitation<span> events mobilize mine wastes downstream and downslope as a series of discrete pulses, causing dispersion both down and lateral to washes with exponential decay behavior as distance from the source increases. Accordingly a quantitative model of arsenic concentrations in wash sediments, represented as a series of overlapping exponential power-law decay curves, results in the acceptable reproducibility of observed arsenic concentration patterns. Such a model can be transferable to other abandoned mine lands as a predictive tool for monitoring the fate and transport of arsenic and related contaminants in similar settings. Effective remediation of contaminated mine wastes in a semi-arid environment requires addressing concurrent changes in the amounts of potential tailings released through fluvial processes and the transport capacity of a wash.</span></p>","language":"English","publisher":"Royal Society of Chemistry","doi":"10.1039/C2EM30135K","usgsCitation":"Kim, C.S., Slack, D.H., and Rytuba, J.J., 2012, Fluvial transport and surface enrichment of arsenic in semi-arid mining regions: examples from the Mojave Desert, California: Journal of Environmental Monitoring, v. 14, no. 7, p. 1798-1813, https://doi.org/10.1039/C2EM30135K.","productDescription":"16 p.","startPage":"1798","endPage":"1813","ipdsId":"IP-038049","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":342949,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Mojave Desert","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -117.89566040039062,\n              35.24337596896174\n            ],\n            [\n              -117.43698120117189,\n              35.24337596896174\n            ],\n            [\n              -117.43698120117189,\n              35.44388973159731\n            ],\n            [\n              -117.89566040039062,\n              35.44388973159731\n            ],\n            [\n              -117.89566040039062,\n              35.24337596896174\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"14","issue":"7","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59536eafe4b062508e3c7abd","contributors":{"authors":[{"text":"Kim, Christopher S.","contributorId":193526,"corporation":false,"usgs":false,"family":"Kim","given":"Christopher","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":700729,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Slack, David H.","contributorId":193527,"corporation":false,"usgs":false,"family":"Slack","given":"David","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":700730,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rytuba, James J. jrytuba@usgs.gov","contributorId":3043,"corporation":false,"usgs":true,"family":"Rytuba","given":"James","email":"jrytuba@usgs.gov","middleInitial":"J.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":700727,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70191700,"text":"70191700 - 2012 - KINEROS2/AGWA: Model use, calibration and validation","interactions":[],"lastModifiedDate":"2017-10-19T11:03:06","indexId":"70191700","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3619,"text":"Transactions of the ASABE","active":true,"publicationSubtype":{"id":10}},"displayTitle":"KINEROS<sub>2</sub>/AGWA: Model use, calibration and validation","title":"KINEROS2/AGWA: Model use, calibration and validation","docAbstract":"<p><span>KINEROS (KINematic runoff and EROSion) originated in the 1960s as a distributed event-based model that conceptualizes a watershed as a cascade of overland flow model elements that flow into trapezoidal channel model elements. KINEROS was one of the first widely available watershed models that interactively coupled a finite difference approximation of the kinematic overland flow equations to a physically based infiltration model. Development and improvement of KINEROS continued from the 1960s on a variety of projects for a range of purposes, which has resulted in a suite of KINEROS-based modeling tools. This article focuses on KINEROS2 (K2), a spatially distributed, event-based watershed rainfall-runoff and erosion model, and the companion ArcGIS-based Automated Geospatial Watershed Assessment (AGWA) tool. AGWA automates the time-consuming tasks of watershed delineation into distributed model elements and initial parameterization of these elements using commonly available, national GIS data layers. A variety of approaches have been used to calibrate and validate K2 successfully across a relatively broad range of applications (e.g., urbanization, pre- and post-fire, hillslope erosion, erosion from roads, runoff and recharge, and manure transport). The case studies presented in this article (1) compare lumped to stepwise calibration and validation of runoff and sediment at plot, hillslope, and small watershed scales; and (2) demonstrate an uncalibrated application to address relative change in watershed response to wildfire.</span></p>","language":"English","publisher":"ASABE","doi":"10.13031/2013.42264","usgsCitation":"Goodrich, D., Burns, I., Unkrich, C., Semmens, D.J., Guertin, D., Hernandez, M., Yatheendradas, S., Kennedy, J.R., and Levick, L.R., 2012, KINEROS2/AGWA: Model use, calibration and validation: Transactions of the ASABE, v. 55, no. 4, p. 1561-1574, https://doi.org/10.13031/2013.42264.","productDescription":"14 p.","startPage":"1561","endPage":"1574","ipdsId":"IP-036418","costCenters":[{"id":547,"text":"Rocky Mountain Geographic Science Center","active":true,"usgs":true}],"links":[{"id":502526,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/2060/20140009153","text":"External Repository"},{"id":346949,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"55","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59e9b998e4b05fe04cd65ceb","contributors":{"authors":[{"text":"Goodrich, D.C.","contributorId":98492,"corporation":false,"usgs":false,"family":"Goodrich","given":"D.C.","email":"","affiliations":[],"preferred":false,"id":713890,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burns, I.S.","contributorId":197274,"corporation":false,"usgs":false,"family":"Burns","given":"I.S.","email":"","affiliations":[],"preferred":false,"id":713891,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Unkrich, C.L.","contributorId":74537,"corporation":false,"usgs":false,"family":"Unkrich","given":"C.L.","affiliations":[],"preferred":false,"id":713892,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Semmens, Darius J. 0000-0001-7924-6529 dsemmens@usgs.gov","orcid":"https://orcid.org/0000-0001-7924-6529","contributorId":1714,"corporation":false,"usgs":true,"family":"Semmens","given":"Darius","email":"dsemmens@usgs.gov","middleInitial":"J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":713893,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Guertin, D.P.","contributorId":36264,"corporation":false,"usgs":true,"family":"Guertin","given":"D.P.","email":"","affiliations":[],"preferred":false,"id":713894,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hernandez, M.","contributorId":197277,"corporation":false,"usgs":false,"family":"Hernandez","given":"M.","email":"","affiliations":[],"preferred":false,"id":713895,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Yatheendradas, S.","contributorId":13035,"corporation":false,"usgs":false,"family":"Yatheendradas","given":"S.","affiliations":[],"preferred":false,"id":713896,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kennedy, Jeffrey R. 0000-0002-3365-6589 jkennedy@usgs.gov","orcid":"https://orcid.org/0000-0002-3365-6589","contributorId":2172,"corporation":false,"usgs":true,"family":"Kennedy","given":"Jeffrey","email":"jkennedy@usgs.gov","middleInitial":"R.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":713897,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Levick, Lainie R.","contributorId":23229,"corporation":false,"usgs":true,"family":"Levick","given":"Lainie","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":713898,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70192533,"text":"70192533 - 2012 - Use of occupancy models to evaluate expert knowledge-based species-habitat relationships","interactions":[],"lastModifiedDate":"2018-12-21T13:06:14","indexId":"70192533","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":947,"text":"Avian Conservation and Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Use of occupancy models to evaluate expert knowledge-based species-habitat relationships","docAbstract":"<p><span>Expert knowledge-based species-habitat relationships are used extensively to guide conservation planning, particularly when data are scarce. Purported relationships describe the initial state of knowledge, but are rarely tested. We assessed support in the data for suitability rankings of vegetation types based on expert knowledge for three terrestrial avian species in the South Atlantic Coastal Plain of the United States. Experts used published studies, natural history, survey data, and field experience to rank vegetation types as optimal, suitable, and marginal. We used single-season occupancy models, coupled with land cover and Breeding Bird Survey data, to examine the hypothesis that patterns of occupancy conformed to species-habitat suitability rankings purported by experts. Purported habitat suitability was validated for two of three species. As predicted for the Eastern Wood-Pewee (</span><i>Contopus virens</i><span>) and Brown-headed Nuthatch (</span><i>Sitta pusilla</i><span>), occupancy was strongly influenced by vegetation types classified as “optimal habitat” by the species suitability rankings for nuthatches and wood-pewees. Contrary to predictions, Red-headed Woodpecker (</span><i>Melanerpes erythrocephalus</i><span>) models that included vegetation types as covariates received similar support by the data as models without vegetation types. For all three species, occupancy was also related to sampling latitude. Our results suggest that covariates representing other habitat requirements might be necessary to model occurrence of generalist species like the woodpecker. The modeling approach described herein provides a means to test expert knowledge-based species-habitat relationships, and hence, help guide conservation planning.</span></p>","language":"English","publisher":"Avian Conservation and Ecology","doi":"10.5751/ACE-00551-070205","usgsCitation":"Iglecia, M.N., Collazo, J., and McKerrow, A., 2012, Use of occupancy models to evaluate expert knowledge-based species-habitat relationships: Avian Conservation and Ecology, v. 7, no. 2, p. 1-13, https://doi.org/10.5751/ACE-00551-070205.","productDescription":"Article 5; 13 p.","startPage":"1","endPage":"13","ipdsId":"IP-029469","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":37226,"text":"Core Science Analytics, Synthesis, and Libraries","active":true,"usgs":true},{"id":38315,"text":"GAP Analysis Project","active":true,"usgs":true}],"links":[{"id":474667,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5751/ace-00551-070205","text":"Publisher Index Page"},{"id":349461,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"2","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a6105a0e4b06e28e9c25585","contributors":{"authors":[{"text":"Iglecia, Monica N.","contributorId":200933,"corporation":false,"usgs":false,"family":"Iglecia","given":"Monica","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":723848,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Collazo, Jaime A. 0000-0002-1816-7744 jaime_collazo@usgs.gov","orcid":"https://orcid.org/0000-0002-1816-7744","contributorId":173448,"corporation":false,"usgs":true,"family":"Collazo","given":"Jaime A.","email":"jaime_collazo@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":716133,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McKerrow, Alexa 0000-0002-8312-2905 amckerrow@usgs.gov","orcid":"https://orcid.org/0000-0002-8312-2905","contributorId":127753,"corporation":false,"usgs":true,"family":"McKerrow","given":"Alexa","email":"amckerrow@usgs.gov","affiliations":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":true,"id":723849,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70188864,"text":"70188864 - 2012 - Multifractal model of magnetic susceptibility distributions in some igneous rocks","interactions":[],"lastModifiedDate":"2017-06-27T10:06:08","indexId":"70188864","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2878,"text":"Nonlinear Processes in Geophysics","active":true,"publicationSubtype":{"id":10}},"title":"Multifractal model of magnetic susceptibility distributions in some igneous rocks","docAbstract":"<p><span>Measurements of in-situ magnetic susceptibility were compiled from mainly Precambrian crystalline basement rocks beneath the Colorado Plateau and ranges in Arizona, Colorado, and New Mexico. The susceptibility meter used measures about 30 cm</span><sup>3</sup><span> of rock and measures variations in the modal distribution of magnetic minerals that form a minor component volumetrically in these coarsely crystalline granitic to granodioritic rocks. Recent measurements include 50–150 measurements on each outcrop, and show that the distribution of magnetic susceptibilities is highly variable, multimodal and strongly non-Gaussian. Although the distribution of magnetic susceptibility is well known to be multifractal, the small number of data points at an outcrop precludes calculation of the multifractal spectrum by conventional methods. Instead, a brute force approach was adopted using multiplicative cascade models to fit the outcrop scale variability of magnetic minerals. Model segment proportion and length parameters resulted in 26 676 models to span parameter space. Distributions at each outcrop were normalized to unity magnetic susceptibility and added to compare all data for a rock body accounting for variations in petrology and alteration. Once the best-fitting model was found, the equation relating the segment proportion and length parameters was solved numerically to yield the multifractal spectrum estimate. For the best fits, the relative density (the proportion divided by the segment length) of one segment tends to be dominant and the other two densities are smaller and nearly equal. No other consistent relationships between the best fit parameters were identified. The multifractal spectrum estimates appear to distinguish between metamorphic gneiss sites and sites on plutons, even if the plutons have been metamorphosed. In particular, rocks that have undergone multiple tectonic events tend to have a larger range of scaling exponents.</span></p>","language":"English","publisher":"European Geosciences Union","doi":"10.5194/npg-19-635-2012","usgsCitation":"Gettings, M.E., 2012, Multifractal model of magnetic susceptibility distributions in some igneous rocks: Nonlinear Processes in Geophysics, v. 19, p. 635-642, https://doi.org/10.5194/npg-19-635-2012.","productDescription":"8 p.","startPage":"635","endPage":"642","ipdsId":"IP-042313","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":474628,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/npg-19-635-2012","text":"Publisher Index Page"},{"id":342945,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"19","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2012-11-23","publicationStatus":"PW","scienceBaseUri":"59536eafe4b062508e3c7abb","contributors":{"authors":[{"text":"Gettings, Mark E. 0000-0002-2910-2321 mgetting@usgs.gov","orcid":"https://orcid.org/0000-0002-2910-2321","contributorId":602,"corporation":false,"usgs":true,"family":"Gettings","given":"Mark","email":"mgetting@usgs.gov","middleInitial":"E.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":700740,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70189204,"text":"70189204 - 2012 - MT3DMS: Model use, calibration, and validation","interactions":[],"lastModifiedDate":"2017-07-05T16:15:38","indexId":"70189204","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3619,"text":"Transactions of the ASABE","active":true,"publicationSubtype":{"id":10}},"title":"MT3DMS: Model use, calibration, and validation","docAbstract":"<p><span>MT3DMS is a three-dimensional multi-species solute transport model for solving advection, dispersion, and chemical reactions of contaminants in saturated groundwater flow systems. MT3DMS interfaces directly with the U.S. Geological Survey finite-difference groundwater flow model MODFLOW for the flow solution and supports the hydrologic and discretization features of MODFLOW. MT3DMS contains multiple transport solution techniques in one code, which can often be important, including in model calibration. Since its first release in 1990 as MT3D for single-species mass transport modeling, MT3DMS has been widely used in research projects and practical field applications. This article provides a brief introduction to MT3DMS and presents recommendations about calibration and validation procedures for field applications of MT3DMS. The examples presented suggest the need to consider alternative processes as models are calibrated and suggest opportunities and difficulties associated with using groundwater age in transport model calibration.</span></p>","language":"English","publisher":"ASABE","doi":"10.13031/2013.42263","usgsCitation":"Zheng, C., Hill, M.C., Cao, G., and Ma, R., 2012, MT3DMS: Model use, calibration, and validation: Transactions of the ASABE, v. 55, no. 4, p. 1549-1559, https://doi.org/10.13031/2013.42263.","productDescription":"11 p.","startPage":"1549","endPage":"1559","ipdsId":"IP-040350","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":343365,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"55","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"595dfab9e4b0d1f9f056a7b6","contributors":{"authors":[{"text":"Zheng, C.","contributorId":39976,"corporation":false,"usgs":true,"family":"Zheng","given":"C.","email":"","affiliations":[],"preferred":false,"id":703498,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hill, Mary C. mchill@usgs.gov","contributorId":974,"corporation":false,"usgs":true,"family":"Hill","given":"Mary","email":"mchill@usgs.gov","middleInitial":"C.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":703499,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cao, G.","contributorId":22970,"corporation":false,"usgs":true,"family":"Cao","given":"G.","email":"","affiliations":[],"preferred":false,"id":703500,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ma, R.","contributorId":17458,"corporation":false,"usgs":true,"family":"Ma","given":"R.","email":"","affiliations":[],"preferred":false,"id":703501,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70192540,"text":"70192540 - 2012 - Morphometric-based sexual determination of Bananaquits (Coereba flaveola)","interactions":[],"lastModifiedDate":"2017-11-28T12:47:13","indexId":"70192540","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2967,"text":"Ornitologia Neotropical","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Morphometric-based sexual determination of Bananaquits (<i>Coereba flaveola</i>)","title":"Morphometric-based sexual determination of Bananaquits (Coereba flaveola)","docAbstract":"<p>The Bananaquit (Coereba flaveola) is a common passerine throughout the tropics and has been a convenient species for ecological studies. This species has sexually monomorphic plumage and cannot be reliably sexed unless in breeding condition. This is problematic for demographic and comparative studies, which are contingent upon accurately aging and sexing individuals. Although male Bananaquits are larger than females, there is overlap in both wing chord and mass. We used morphometric data collected over eight years to develop a predictive model based on logistic regression to assign adult Bananaquits to sex. Our model classified 96% of validation individuals to the correct sex. We suggest that this approach may enhance ecological studies of the species by facilitating correct sex determination independent of breeding status. We believe our modeling approach is applicable elsewhere but, because there may be geographical variation across the species distribution, models will need to be customized to local populations.</p>","language":"English","publisher":"The Neotropical Ornithological Society","usgsCitation":"Bibles, B.D., and Boal, C.W., 2012, Morphometric-based sexual determination of Bananaquits (Coereba flaveola): Ornitologia Neotropical, v. 23, p. 507-515.","productDescription":"9 p.","startPage":"507","endPage":"515","ipdsId":"IP-030771","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":349456,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":349455,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://sora.unm.edu/node/133335"}],"country":"British Virgin Islands","otherGeospatial":"Guana Island","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -64.58527565002441,\n              18.46235033603078\n            ],\n            [\n              -64.55703735351562,\n              18.46235033603078\n            ],\n            [\n              -64.55703735351562,\n              18.49112747057403\n            ],\n            [\n              -64.58527565002441,\n              18.49112747057403\n            ],\n            [\n              -64.58527565002441,\n              18.46235033603078\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"23","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a6105a0e4b06e28e9c25583","contributors":{"authors":[{"text":"Bibles, Brent D.","contributorId":77720,"corporation":false,"usgs":true,"family":"Bibles","given":"Brent","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":723845,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boal, Clint W. 0000-0001-6008-8911 cboal@usgs.gov","orcid":"https://orcid.org/0000-0001-6008-8911","contributorId":1909,"corporation":false,"usgs":true,"family":"Boal","given":"Clint","email":"cboal@usgs.gov","middleInitial":"W.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":716154,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70192319,"text":"70192319 - 2012 - Have recent earthquakes exposed flaws in or misunderstandings of probabilistic seismic hazard analysis?","interactions":[],"lastModifiedDate":"2017-10-24T15:38:31","indexId":"70192319","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Have recent earthquakes exposed flaws in or misunderstandings of probabilistic seismic hazard analysis?","docAbstract":"<p>In a recent Opinion piece in these pages, Stein et al. (2011) offer a remarkable indictment of the methods, models, and results of probabilistic seismic hazard analysis (PSHA). The principal object of their concern is the PSHA map for Japan released by the Japan Headquarters for Earthquake Research Promotion (HERP), which is reproduced by Stein et al. (2011) as their Figure 1 and also here as our Figure 1. It shows the probability of exceedance (also referred to as the “hazard”) of the Japan Meteorological Agency (JMA) intensity 6–lower (JMA 6–) in Japan for the 30-year period beginning in January 2010. JMA 6– is an earthquake-damage intensity measure that is associated with fairly strong ground motion that can be damaging to well-built structures and is potentially destructive to poor construction (HERP, 2005, appendix 5). Reiterating Geller (2011, p. 408), Stein et al. (2011, p. 623) have this to say about Figure 1: </p><p>The regions assessed as most dangerous are the zones of three hypothetical “scenario earthquakes” (Tokai, Tonankai, and Nankai; see map). However, since 1979, earthquakes that caused 10 or more fatalities in Japan actually occurred in places assigned a relatively low probability. This discrepancy—the latest in a string of negative results for the characteristic model and its cousin the seismic-gap model—strongly suggest that the hazard map and the methods used to produce it are flawed and should be discarded. </p><p>Given the central role that PSHA now plays in seismic risk analysis, performance-based engineering, and design-basis ground motions, discarding PSHA would have important consequences. We are not persuaded by the arguments of Geller (2011) and Stein et al. (2011) for doing so because important misunderstandings about PSHA seem to have conditioned them. In the quotation above, for example, they have confused important differences between earthquake-occurrence observations and ground-motion hazard calculations.</p>","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220120043","usgsCitation":"Hanks, T.C., Beroza, G.C., and Toda, S., 2012, Have recent earthquakes exposed flaws in or misunderstandings of probabilistic seismic hazard analysis?: Seismological Research Letters, v. 83, no. 5, p. 759-764, https://doi.org/10.1785/0220120043.","productDescription":"6 p.","startPage":"759","endPage":"764","ipdsId":"IP-036939","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":347270,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"83","issue":"5","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2012-09-06","publicationStatus":"PW","scienceBaseUri":"59f05125e4b0220bbd9a1dc6","contributors":{"authors":[{"text":"Hanks, Thomas C. 0000-0003-0928-0056 thanks@usgs.gov","orcid":"https://orcid.org/0000-0003-0928-0056","contributorId":3065,"corporation":false,"usgs":true,"family":"Hanks","given":"Thomas","email":"thanks@usgs.gov","middleInitial":"C.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":715291,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Beroza, Gregory C.","contributorId":191201,"corporation":false,"usgs":false,"family":"Beroza","given":"Gregory","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":715290,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Toda, Shinji","contributorId":43062,"corporation":false,"usgs":true,"family":"Toda","given":"Shinji","email":"","affiliations":[],"preferred":false,"id":715292,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70186908,"text":"70186908 - 2012 - Geomorphic determinants of species composition of alpine tundra, Glacier National Park, U.S.A.","interactions":[],"lastModifiedDate":"2022-11-02T14:13:25.975559","indexId":"70186908","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":899,"text":"Arctic, Antarctic, and Alpine Research","active":true,"publicationSubtype":{"id":10}},"title":"Geomorphic determinants of species composition of alpine tundra, Glacier National Park, U.S.A.","docAbstract":"<p><span>Because the distribution of alpine tundra is associated with spatially limited cold climates, global warming may threaten its local extent or existence. This notion has been challenged, however, based on observations of the diversity of alpine tundra in small areas primarily due to topographic variation. The importance of diversity in temperature or moisture conditions caused by topographic variation is an open question, and we extend this to geomorphology more generally. The extent to which geomorphic variation </span><i>per se</i><span>, based on relatively easily assessed indicators, can account for the variation in alpine tundra community composition is analyzed versus the inclusion of broad indicators of regional climate variation. Visual assessments of topography are quantified and reduced using principal components analysis (PCA). Observations of species cover are reduced using detrended correspondence analysis (DCA). A “best subsets” regression approach using the Akaike Information Criterion for selection of variables is compared to a simple stepwise regression with DCA scores as the dependent variable and scores on significant PCA axes plus more direct measures of topography as independent variables. Models with geographic coordinates (representing regional climate gradients) excluded explain almost as much variation in community composition as models with them included, although they are important contributors to the latter. The geomorphic variables in the model are those associated with local moisture differences such as snowbeds. The potential local variability of alpine tundra can be a buffer against climate change, but change in precipitation may be as important as change in temperature.</span></p>","language":"English","publisher":"Institute of Arctic, Antarctic, and Alpine Research","publisherLocation":"Boulder, CO","doi":"10.1657/1938-4246-44.2.197","usgsCitation":"George P. Malanson, Bengtson, L.E., and Fagre, D.B., 2012, Geomorphic determinants of species composition of alpine tundra, Glacier National Park, U.S.A.: Arctic, Antarctic, and Alpine Research, v. 44, no. 2, p. 197-209, https://doi.org/10.1657/1938-4246-44.2.197.","productDescription":"9 p.","startPage":"197","endPage":"209","ipdsId":"IP-033599","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":474643,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1657/1938-4246-44.2.197","text":"Publisher Index Page"},{"id":339710,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","otherGeospatial":"Glacier National Park","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": 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-113.61236572265624,\n              48.996438064932285\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"44","issue":"2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-19","publicationStatus":"PW","scienceBaseUri":"58f08e63e4b06911a29fa862","contributors":{"authors":[{"text":"George P. Malanson","contributorId":127023,"corporation":false,"usgs":false,"family":"George P. Malanson","affiliations":[{"id":6768,"text":"University of Iowa","active":true,"usgs":false}],"preferred":false,"id":690969,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bengtson, Lindsey E.","contributorId":28497,"corporation":false,"usgs":true,"family":"Bengtson","given":"Lindsey","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":690968,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fagre, Daniel B. 0000-0001-8552-9461 dan_fagre@usgs.gov","orcid":"https://orcid.org/0000-0001-8552-9461","contributorId":2036,"corporation":false,"usgs":true,"family":"Fagre","given":"Daniel","email":"dan_fagre@usgs.gov","middleInitial":"B.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":690970,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70189201,"text":"70189201 - 2012 - VS2DI: Model use, calibration, and validation","interactions":[],"lastModifiedDate":"2017-07-05T17:01:11","indexId":"70189201","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3619,"text":"Transactions of the ASABE","active":true,"publicationSubtype":{"id":10}},"title":"VS2DI: Model use, calibration, and validation","docAbstract":"<p><span>VS2DI is a software package for simulating water, solute, and heat transport through soils or other porous media under conditions of variable saturation. The package contains a graphical preprocessor for constructing simulations, a postprocessor for displaying simulation results, and numerical models that solve for flow and solute transport (VS2DT) and flow and heat transport (VS2DH). Flow is described by the Richards equation, and solute and heat transport are described by advection-dispersion equations; the finite-difference method is used to solve these equations. Problems can be simulated in one, two, or three (assuming radial symmetry) dimensions. This article provides an overview of calibration techniques that have been used with VS2DI; included is a detailed description of calibration procedures used in simulating the interaction between groundwater and a stream fed by drainage from agricultural fields in central Indiana. Brief descriptions of VS2DI and the various types of problems that have been addressed with the software package are also presented.</span></p>","language":"English","publisher":"ASABE","doi":"10.13031/2013.42238","usgsCitation":"Healy, R.W., and Essaid, H.I., 2012, VS2DI: Model use, calibration, and validation: Transactions of the ASABE, v. 55, no. 4, p. 1249-1260, https://doi.org/10.13031/2013.42238.","productDescription":"12 p.","startPage":"1249","endPage":"1260","ipdsId":"IP-034395","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":343374,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"55","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"595dfab9e4b0d1f9f056a7b9","contributors":{"authors":[{"text":"Healy, Richard W. 0000-0002-0224-1858 rwhealy@usgs.gov","orcid":"https://orcid.org/0000-0002-0224-1858","contributorId":658,"corporation":false,"usgs":true,"family":"Healy","given":"Richard","email":"rwhealy@usgs.gov","middleInitial":"W.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":703466,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Essaid, Hedeff I. 0000-0003-0154-8628 hiessaid@usgs.gov","orcid":"https://orcid.org/0000-0003-0154-8628","contributorId":2284,"corporation":false,"usgs":true,"family":"Essaid","given":"Hedeff","email":"hiessaid@usgs.gov","middleInitial":"I.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":703465,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70192794,"text":"70192794 - 2012 - A new perspective on the geometry of the San Andreas Fault in southern California and its relationship to lithospheric structure","interactions":[],"lastModifiedDate":"2017-10-31T11:23:28","indexId":"70192794","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"A new perspective on the geometry of the San Andreas Fault in southern California and its relationship to lithospheric structure","docAbstract":"<p><span>The widely held perception that the San Andreas fault (SAF) is vertical or steeply dipping in most places in southern California may not be correct. From studies of potential‐field data, active‐source imaging, and seismicity, the dip of the SAF is significantly nonvertical in many locations. The direction of dip appears to change in a systematic way through the Transverse Ranges: moderately southwest (55°–75°) in the western bend of the SAF in the Transverse Ranges (Big Bend); vertical to steep in the Mojave Desert; and moderately northeast (37°–65°) in a region extending from San Bernardino to the Salton Sea, spanning the eastern bend of the SAF in the Transverse Ranges. The shape of the modeled SAF is crudely that of a propeller. If confirmed by further studies, the geometry of the modeled SAF would have important implications for tectonics and strong ground motions from SAF earthquakes. The SAF can be traced or projected through the crust to the north side of a well documented high‐velocity body (HVB) in the upper mantle beneath the Transverse Ranges. The north side of this HVB may be an extension of the plate boundary into the mantle, and the HVB would appear to be part of the Pacific plate.</span></p>","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120110041","usgsCitation":"Fuis, G.S., Scheirer, D., Langenheim, V., and Kohler, M.D., 2012, A new perspective on the geometry of the San Andreas Fault in southern California and its relationship to lithospheric structure: Bulletin of the Seismological Society of America, v. 102, no. 1, p. 236-251, https://doi.org/10.1785/0120110041.","productDescription":"16 p.","startPage":"236","endPage":"251","ipdsId":"IP-013720","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":347839,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Andreas Fault","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -120,\n              32\n            ],\n            [\n              -116,\n              32\n            ],\n            [\n              -116,\n              36\n            ],\n            [\n              -120,\n              36\n            ],\n            [\n              -120,\n              32\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"102","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2012-02-15","publicationStatus":"PW","scienceBaseUri":"59f98bc1e4b0531197afa071","contributors":{"authors":[{"text":"Fuis, Gary S. 0000-0002-3078-1544 fuis@usgs.gov","orcid":"https://orcid.org/0000-0002-3078-1544","contributorId":2639,"corporation":false,"usgs":true,"family":"Fuis","given":"Gary","email":"fuis@usgs.gov","middleInitial":"S.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":716967,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Scheirer, Daniel S. dscheirer@usgs.gov","contributorId":2325,"corporation":false,"usgs":true,"family":"Scheirer","given":"Daniel S.","email":"dscheirer@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":716966,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Langenheim, Victoria E. 0000-0003-2170-5213 zulanger@usgs.gov","orcid":"https://orcid.org/0000-0003-2170-5213","contributorId":151042,"corporation":false,"usgs":true,"family":"Langenheim","given":"Victoria E.","email":"zulanger@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":716968,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kohler, Monica D.","contributorId":57054,"corporation":false,"usgs":true,"family":"Kohler","given":"Monica","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":716969,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70191461,"text":"70191461 - 2012 - Gulf Coast Ecosystem Restoration Task Force---Gulf of Mexico Ecosystem Science Assessment and Needs","interactions":[],"lastModifiedDate":"2017-10-16T14:48:07","indexId":"70191461","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":9,"text":"Other Report"},"title":"Gulf Coast Ecosystem Restoration Task Force---Gulf of Mexico Ecosystem Science Assessment and Needs","docAbstract":"<p>The Gulf Coast Ecosystem Restoration Task Force (GCERTF) was established by Executive Order 13554 as a result of recommendations from “America’s Gulf Coast: A Long-term Recovery Plan after the Deepwater Horizon Oil Spill” by Secretary of the Navy Ray Mabus (Mabus Report). The GCERTF consists of members from 11 Federal agencies and representatives from each State bordering the Gulf of Mexico. The GCERTF was charged to develop a holistic, long-term, science-based Regional Ecosystem Restoration Strategy for the Gulf of Mexico. Federal and State agencies staffed the GCERTF with experts in fields such as policy, budgeting, and science to help develop the Strategy. The Strategy was built on existing authorities and resources and represents enhanced collaboration and a recognition of the shared responsibility among Federal and State governments to restore the Gulf Coast ecosystem. In this time of severe fiscal constraints, Task Force member agencies and States are committed to establishing shared priorities and working together to achieve them.</p><p>As part of this effort, three staffers, one National Oceanic and Atmospheric Administration (NOAA) scientist and two U.S. Geological Survey (USGS) scientists, created and led a Science Coordination Team (SCT) to guide scientific input into the development of the Gulf of Mexico Regional Ecosystem Restoration Strategy. </p><p>The SCT leads from the GCERTF coordinated more than 70 scientists from the Federal and State Task Force member agencies to participate in development of a restoration-oriented science document focused on the entire Gulf of Mexico, from inland watersheds to the deep blue waters. The SCT leads and scientists were organized into six different working groups based on expanded goals from the Mabus Report: </p><ol><li>Coastal habitats are healthy and resilient.<br></li><li>Living coastal and marine resources are healthy, diverse, and sustainable.<br></li><li>Coastal communities are adaptive and resilient.<br></li><li>Storm buffers are sustainable.<br></li><li>Inland habitats and watersheds are managed to help support healthy and sustainable Gulf of Mexico ecosystems.<br></li><li>Offshore environments are healthy and well managed<br></li></ol><p>Each working group was charged with defining their specific goal, describing the current conditions related to that goal (for example, the status of coastal habitats in the Gulf of Mexico), providing highlevel activities needed to further define and achieve the goal, with associated outcome-based performance indicators, and identifying the scientific gaps in understanding to accomplish the goal and implement the recommended activities. The overall scientific assessment reveals that the Gulf of Mexico ecosystem continues to suffer from extensive degradation, and action is necessary to develop a healthy, resilient, and sustainable Gulf of Mexico ecosystem. </p><p>The six groups also were tasked with outlining the necessary monitoring, modeling, and research needs to aid in achieving the goals. Recognizing that (1) the scientific needs (monitoring, modeling, and research) overlap among many of the goals, and (2) an overarching scientific framework could be developed to implement the necessary science in support of the Strategy, a seventh group was created with several members from each of the original six working groups. This seventh group compiled all of the cross-cutting monitoring, modeling, and research needs previously identified by the individual groups. These scientific requirements are found in Chapter 5 of this document. </p><p>The seventh group also has developed a Science Plan, outlined in Chapter 6. The Science Plan provides the basic science infrastructure to support the overall Gulf restoration program and Strategy. The Science Plan allows for the development of an iterative and flexible approach to adaptive management and decision-making related to restoration projects based on sound science that includes monitoring, modeling, and research. Taken in its entirety, this document helps to articulate the current state of the system and the critical science needs to support effective restoration of the Gulf of Mexico resources that have been trending towards decline for decades. </p>","language":"English","publisher":"Gulf Coast Ecosystem Restoration Task Force Science Coordination Team","usgsCitation":"2012, Gulf Coast Ecosystem Restoration Task Force---Gulf of Mexico Ecosystem Science Assessment and Needs, viii, 72 p.","productDescription":"viii, 72 p.","numberOfPages":"81","ipdsId":"IP-033671","costCenters":[{"id":5064,"text":"Southeast Regional Director's Office","active":true,"usgs":true}],"links":[{"id":346636,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":346635,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://archive.epa.gov/gulfcoasttaskforce/web/pdf/gcertf-book-final-042712.pdf"}],"otherGeospatial":"Gulf of Mexico","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59e5c51ce4b05fe04cd1c9e4","contributors":{"editors":[{"text":"Walker, Shelby","contributorId":197112,"corporation":false,"usgs":false,"family":"Walker","given":"Shelby","email":"","affiliations":[],"preferred":false,"id":712605,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Dausman, Alyssa M. adausman@usgs.gov","contributorId":1545,"corporation":false,"usgs":true,"family":"Dausman","given":"Alyssa","email":"adausman@usgs.gov","middleInitial":"M.","affiliations":[],"preferred":false,"id":712606,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Lavoie, Dawn L. dlavoie@usgs.gov","contributorId":3006,"corporation":false,"usgs":true,"family":"Lavoie","given":"Dawn","email":"dlavoie@usgs.gov","middleInitial":"L.","affiliations":[],"preferred":true,"id":712607,"contributorType":{"id":2,"text":"Editors"},"rank":3}]}}
,{"id":70032287,"text":"70032287 - 2012 - Climate change and human health: Spatial modeling of water availability, malnutrition, and livelihoods in Mali, Africa","interactions":[],"lastModifiedDate":"2018-02-21T14:19:00","indexId":"70032287","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":836,"text":"Applied Geography","active":true,"publicationSubtype":{"id":10}},"title":"Climate change and human health: Spatial modeling of water availability, malnutrition, and livelihoods in Mali, Africa","docAbstract":"<p><span>This study develops a novel approach for projecting climate trends in the Sahel in relation to shifting livelihood zones and health outcomes. Focusing on Mali, we explore baseline relationships between temperature, precipitation, livelihood, and malnutrition in 407 Demographic and Health Survey (DHS) clusters with a total of 14,238 children, resulting in a thorough spatial analysis of coupled climate-health dynamics. Results suggest links between livelihoods and each measure of malnutrition, as well as a link between climate and stunting. A ‘front-line’ of vulnerability, related to the transition between agricultural and pastoral livelihoods, is identified as an area where mitigation efforts might be usefully targeted. Additionally, climate is projected to 2025 for the Sahel, and demographic trends are introduced to explore how the intersection of climate and demographics may shift the vulnerability ‘front-line’, potentially exposing an additional 6 million people in Mali, up to a million of them children, to heightened risk of malnutrition from climate and livelihood changes. Results indicate that, holding constant morbidity levels, approximately one quarter of a million children will suffer stunting, nearly two hundred thousand will be malnourished, and over one hundred thousand will become anemic in this expanding arid zone by 2025. Climate and health research conducted at finer spatial scales and within shorter projected time lines can identify vulnerability hot spots that are of the highest priority for adaptation interventions; such an analysis can also identify areas with similar characteristics that may be at heightened risk. Such meso-scale coupled human-environment research may facilitate appropriate policy interventions strategically located beyond today’s vulnerability front-line.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.apgeog.2011.08.009","issn":"01436228","usgsCitation":"Jankowska, M.M., Lopez-Carr, D., Funk, C., Husak, G.J., and Chafe, Z., 2012, Climate change and human health: Spatial modeling of water availability, malnutrition, and livelihoods in Mali, Africa: Applied Geography, v. 33, no. 1, p. 4-15, https://doi.org/10.1016/j.apgeog.2011.08.009.","productDescription":"12 p.","startPage":"4","endPage":"15","numberOfPages":"12","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":214763,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.apgeog.2011.08.009"},{"id":242513,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"33","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059f64ce4b0c8380cd4c68b","contributors":{"authors":[{"text":"Jankowska, Marta M.","contributorId":145838,"corporation":false,"usgs":false,"family":"Jankowska","given":"Marta","email":"","middleInitial":"M.","affiliations":[{"id":16253,"text":"Department of Geography, San Diego State University","active":true,"usgs":false}],"preferred":false,"id":435448,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lopez-Carr, David","contributorId":193003,"corporation":false,"usgs":false,"family":"Lopez-Carr","given":"David","email":"","affiliations":[],"preferred":false,"id":435447,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Funk, Chris 0000-0002-9254-6718 cfunk@usgs.gov","orcid":"https://orcid.org/0000-0002-9254-6718","contributorId":167070,"corporation":false,"usgs":true,"family":"Funk","given":"Chris","email":"cfunk@usgs.gov","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":435445,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Husak, Gregory J.","contributorId":34435,"corporation":false,"usgs":true,"family":"Husak","given":"Gregory","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":435446,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chafe, Z.A.","contributorId":23777,"corporation":false,"usgs":true,"family":"Chafe","given":"Z.A.","email":"","affiliations":[],"preferred":false,"id":435444,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70032295,"text":"70032295 - 2012 - Quantifying anthropogenically driven morphologic changes on a barrier island: Fire Island National Seashore, New York","interactions":[],"lastModifiedDate":"2017-08-29T11:03:20","indexId":"70032295","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2220,"text":"Journal of Coastal Research","active":true,"publicationSubtype":{"id":10}},"title":"Quantifying anthropogenically driven morphologic changes on a barrier island: Fire Island National Seashore, New York","docAbstract":"<p>Beach scraping, beach replenishment, and the presence of moderate development have altered the morphology of the dune–beach system at Fire Island National Seashore, located on a barrier island on the south coast of Long Island, New York. Seventeen communities are interspersed with sections of natural, nonmodified land within the park boundary. Beach width, dune elevation change, volume change, and shoreline change were calculated from light detection and ranging (LIDAR), real-time kinematic global positioning system (RTK GPS), and beach profile data sets at two ∼4&nbsp;km long study sites. Each site contains both modified (developed, replenished, and/or scraped) and nonmodified (natural) areas. The analysis spans 9&nbsp;years, from 1998 to 2007, which encompasses both scraping and replenishment events at Fire Island. The objectives of this study were to quantify and compare morphological changes in modified and nonmodified zones, and to identify erosional areas within the study sites.</p><p>Areas of increased volume and shoreline accretion were observed at both sites and at the western site are consistent with sand replenishment activities. The results indicate that from 1998 to 2007 locations backed by development and that employed beach scraping and/or replenishment as erosion control measures experienced more loss of volume, width, and dune elevation as compared with adjacent nonmodified areas. A detailed analysis of one specific modification, beach scraping, shows distinct morphological differences in scraped areas relative to nonscraped areas of the beach. In general, scraped areas where there is development on the dunes showed decreases in all measured parameters and are more likely to experience overwash during storm events. Furthermore, the rapid mobilization of material from the anthropogenic (scraped) dune results in increased beach accretion downcoast.</p><p class=\"last\">National park lands are immediately adjacent to developed areas on Fire Island, and even relatively small human-induced modifications can affect park resources and beach–dune response to storms. This study is the first to conduct a systematic analysis on how anthropogenic modifications affect resources at Fire Island National Seashore and provides essential information for effective management and preservation of coastal resources within the park.</p>","language":"English","publisher":"Coastal Education and Research Foundation","doi":"10.2112/JCOASTRES-D-10-00012.1","issn":"07490208","usgsCitation":"Kratzmann, M.G., and Hapke, C.J., 2012, Quantifying anthropogenically driven morphologic changes on a barrier island: Fire Island National Seashore, New York: Journal of Coastal Research, v. 28, no. 1, p. 76-88, https://doi.org/10.2112/JCOASTRES-D-10-00012.1.","productDescription":"13 p.","startPage":"76","endPage":"88","numberOfPages":"13","ipdsId":"IP-018448","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":242710,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":214949,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.2112/JCOASTRES-D-10-00012.1"}],"country":"United States","state":"New York","otherGeospatial":"Fire Island National Seashore","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -73.32550048828125,\n              40.608739823836984\n            ],\n            [\n              -72.89566040039062,\n              40.608739823836984\n            ],\n            [\n              -72.89566040039062,\n              40.724364221722716\n            ],\n            [\n              -73.32550048828125,\n              40.724364221722716\n            ],\n            [\n              -73.32550048828125,\n              40.608739823836984\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"28","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a91c2e4b0c8380cd8043d","contributors":{"authors":[{"text":"Kratzmann, Meredith G. 0000-0002-2513-2144 mkratzmann@usgs.gov","orcid":"https://orcid.org/0000-0002-2513-2144","contributorId":194453,"corporation":false,"usgs":true,"family":"Kratzmann","given":"Meredith","email":"mkratzmann@usgs.gov","middleInitial":"G.","affiliations":[],"preferred":false,"id":435488,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hapke, Cheryl J. 0000-0002-2753-4075 chapke@usgs.gov","orcid":"https://orcid.org/0000-0002-2753-4075","contributorId":2981,"corporation":false,"usgs":true,"family":"Hapke","given":"Cheryl","email":"chapke@usgs.gov","middleInitial":"J.","affiliations":[{"id":6676,"text":"USGS (retired)","active":true,"usgs":false}],"preferred":true,"id":435489,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70032498,"text":"70032498 - 2012 - Advancing representation of hydrologic processes in the Soil and Water Assessment Tool (SWAT) through integration of the TOPographic MODEL (TOPMODEL) features","interactions":[],"lastModifiedDate":"2013-04-07T10:14:19","indexId":"70032498","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Advancing representation of hydrologic processes in the Soil and Water Assessment Tool (SWAT) through integration of the TOPographic MODEL (TOPMODEL) features","docAbstract":"This paper presents a study of the integration of the Soil and Water Assessment Tool (SWAT) model and the TOPographic MODEL (TOPMODEL) features for enhancing the physical representation of hydrologic processes. In SWAT, four hydrologic processes, which are surface runoff, baseflow, groundwater re-evaporation and deep aquifer percolation, are modeled by using a group of empirical equations. The empirical equations usually constrain the simulation capability of relevant processes. To replace these equations and to model the influences of topography and water table variation on streamflow generation, the TOPMODEL features are integrated into SWAT, and a new model, the so-called SWAT-TOP, is developed. In the new model, the process of deep aquifer percolation is removed, the concept of groundwater re-evaporation is refined, and the processes of surface runoff and baseflow are remodeled. Consequently, three parameters in SWAT are discarded, and two new parameters to reflect the TOPMODEL features are introduced. SWAT-TOP and SWAT are applied to the East River basin in South China, and the results reveal that, compared with SWAT, the new model can provide a more reasonable simulation of the hydrologic processes of surface runoff, groundwater re-evaporation, and baseflow. This study evidences that an established hydrologic model can be further improved by integrating the features of another model, which is a possible way to enhance our understanding of the workings of catchments.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Hydrology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.jhydrol.2011.12.022","issn":"00221694","usgsCitation":"Chen, J., and Wu, Y., 2012, Advancing representation of hydrologic processes in the Soil and Water Assessment Tool (SWAT) through integration of the TOPographic MODEL (TOPMODEL) features: Journal of Hydrology, v. 420-421, p. 319-328, https://doi.org/10.1016/j.jhydrol.2011.12.022.","productDescription":"10 p.","startPage":"319","endPage":"328","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":213999,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.jhydrol.2011.12.022"},{"id":241683,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"420-421","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059e708e4b0c8380cd477e5","contributors":{"authors":[{"text":"Chen, J.","contributorId":104634,"corporation":false,"usgs":true,"family":"Chen","given":"J.","email":"","affiliations":[],"preferred":false,"id":436481,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wu, Y.","contributorId":79312,"corporation":false,"usgs":true,"family":"Wu","given":"Y.","email":"","affiliations":[],"preferred":false,"id":436480,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70032503,"text":"70032503 - 2012 - Assessment of pingo distribution and morphometry using an IfSAR derived digital surface model, western Arctic Coastal Plain, Northern Alaska","interactions":[],"lastModifiedDate":"2018-08-07T12:20:33","indexId":"70032503","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1801,"text":"Geomorphology","active":true,"publicationSubtype":{"id":10}},"title":"Assessment of pingo distribution and morphometry using an IfSAR derived digital surface model, western Arctic Coastal Plain, Northern Alaska","docAbstract":"<p><span>Pingos are circular to elongate ice-cored mounds that form by injection and freezing of pressurized water in near-surface permafrost. Here we use a digital surface model (DSM) derived from an airborne Interferometric Synthetic Aperture Radar (IfSAR) system to assess the distribution and morphometry of pingos within a 40,000</span><span>&nbsp;</span><span>km</span><sup>2</sup><span>&nbsp;area on the western Arctic Coastal Plain of northern Alaska. We have identified 1247 pingo forms in the study region, ranging in height from 2 to 21</span><span>&nbsp;</span><span>m, with a mean height of 4.6</span><span>&nbsp;</span><span>m. Pingos in this region are of hydrostatic origin, with 98% located within 995 drained lake basins, most of which are underlain by thick eolian sand deposits. The highest pingo density (0.18</span><span>&nbsp;</span><span>km</span><sup>−&nbsp;2</sup><span>) occurs where streams have reworked these deposits. Morphometric analyses indicate that most pingos are small to medium in size (&lt;</span><span>&nbsp;</span><span>200</span><span>&nbsp;</span><span>m diameter), gently to moderately sloping (&lt;</span><span>&nbsp;</span><span>30°), circular to slightly elongate (mean circularity index of 0.88), and of relatively low height (2 to 5</span><span>&nbsp;</span><span>m). However, 57 pingos stand higher than 10</span><span>&nbsp;</span><span>m, 26 have a maximum slope greater than 30°, and 42 are larger than 200</span><span>&nbsp;</span><span>m in diameter. Comparison with a legacy pingo dataset based on 1950s stereo-pair photography indicates that 66 may have partially or completely collapsed over the last half-century. However, we mapped over 400 pingos not identified in the legacy dataset, and identified only three higher than 2</span><span>&nbsp;</span><span>m to have formed between ca. 1955 and ca. 2005, indicating that caution should be taken when comparing contemporary and legacy datasets derived by different techniques. This comprehensive database of pingo location and morphometry based on an IfSAR DSM may prove useful for land and resource managers as well as aid in the identification of pingo-like features on Mars.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.geomorph.2011.08.007","issn":"0169555X","usgsCitation":"Jones, B.M., Grosse, G., Hinkel, K.M., Arp, C., Walker, S., Beck, R., and Galloway, J., 2012, Assessment of pingo distribution and morphometry using an IfSAR derived digital surface model, western Arctic Coastal Plain, Northern Alaska: Geomorphology, v. 138, no. 1, p. 1-14, https://doi.org/10.1016/j.geomorph.2011.08.007.","productDescription":"14 p.","startPage":"1","endPage":"14","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"links":[{"id":241755,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":214067,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.geomorph.2011.08.007"}],"volume":"138","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059ee48e4b0c8380cd49c89","contributors":{"authors":[{"text":"Jones, Benjamin M. 0000-0002-1517-4711 bjones@usgs.gov","orcid":"https://orcid.org/0000-0002-1517-4711","contributorId":2286,"corporation":false,"usgs":true,"family":"Jones","given":"Benjamin","email":"bjones@usgs.gov","middleInitial":"M.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"preferred":true,"id":436511,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grosse, G.","contributorId":82140,"corporation":false,"usgs":true,"family":"Grosse","given":"G.","affiliations":[],"preferred":false,"id":436514,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hinkel, Kenneth M.","contributorId":15405,"corporation":false,"usgs":true,"family":"Hinkel","given":"Kenneth","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":436508,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Arp, C.D.","contributorId":54715,"corporation":false,"usgs":true,"family":"Arp","given":"C.D.","email":"","affiliations":[],"preferred":false,"id":436512,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Walker, S.","contributorId":71777,"corporation":false,"usgs":true,"family":"Walker","given":"S.","email":"","affiliations":[],"preferred":false,"id":436513,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Beck, R.A.","contributorId":44246,"corporation":false,"usgs":true,"family":"Beck","given":"R.A.","email":"","affiliations":[],"preferred":false,"id":436510,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Galloway, J. P.","contributorId":19142,"corporation":false,"usgs":true,"family":"Galloway","given":"J. P.","affiliations":[],"preferred":false,"id":436509,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70032250,"text":"70032250 - 2012 - Geostatistical modeling of the gas emission zone and its in-place gas content for Pittsburgh-seam mines using sequential Gaussian simulation","interactions":[],"lastModifiedDate":"2018-09-21T12:39:12","indexId":"70032250","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2033,"text":"International Journal of Coal Geology","active":true,"publicationSubtype":{"id":10}},"title":"Geostatistical modeling of the gas emission zone and its in-place gas content for Pittsburgh-seam mines using sequential Gaussian simulation","docAbstract":"<p id=\"sp0005\">Determination of the size of the gas emission zone, the locations of gas sources within, and especially the amount of gas retained in those zones is one of the most important steps for designing a successful<span>&nbsp;</span><a title=\"Learn more about Methane\" href=\"https://www.sciencedirect.com/topics/earth-and-planetary-sciences/methane\" data-mce-href=\"https://www.sciencedirect.com/topics/earth-and-planetary-sciences/methane\">methane</a><span>&nbsp;control strategy and an efficient ventilation system in longwall&nbsp;<a title=\"Learn more about Coal\" href=\"https://www.sciencedirect.com/topics/earth-and-planetary-sciences/coal\" data-mce-href=\"https://www.sciencedirect.com/topics/earth-and-planetary-sciences/coal\">coal</a>&nbsp;mining. The formation of the gas emission zone and the potential amount of gas-in-place (GIP) that might be available for migration into a mine are factors of local geology and rock properties that usually show spatial variability in continuity and may also show geometric&nbsp;<a title=\"Learn more about anisotropy\" href=\"https://www.sciencedirect.com/topics/earth-and-planetary-sciences/anisotropy\" data-mce-href=\"https://www.sciencedirect.com/topics/earth-and-planetary-sciences/anisotropy\">anisotropy</a>. Geostatistical methods are used here for modeling and prediction of gas amounts and for assessing their associated uncertainty in gas emission zones of longwall mines for methane control.</span></p><p id=\"sp0010\">This study used core data obtained from 276 vertical exploration<span>&nbsp;</span><a title=\"Learn more about boreholes\" href=\"https://www.sciencedirect.com/topics/earth-and-planetary-sciences/boreholes\" data-mce-href=\"https://www.sciencedirect.com/topics/earth-and-planetary-sciences/boreholes\">boreholes</a><span>&nbsp;drilled from the surface to the bottom of the Pittsburgh&nbsp;<a title=\"Learn more about coal seam\" href=\"https://www.sciencedirect.com/topics/earth-and-planetary-sciences/coal-seam\" data-mce-href=\"https://www.sciencedirect.com/topics/earth-and-planetary-sciences/coal-seam\">coal seam</a>&nbsp;in a&nbsp;<a title=\"Learn more about mining district\" href=\"https://www.sciencedirect.com/topics/earth-and-planetary-sciences/mining-district\" data-mce-href=\"https://www.sciencedirect.com/topics/earth-and-planetary-sciences/mining-district\">mining district</a>&nbsp;in the Northern Appalachian basin. After identifying important coal and non-coal layers for the gas emission zone, univariate statistical and semivariogram analyses were conducted for data from different formations to define the distribution and continuity of various attributes. Sequential simulations performed stochastic assessment of these attributes, such as gas content, strata thickness, and strata displacement. These analyses were followed by calculations of gas-in-place and their uncertainties in the Pittsburgh seam caved zone and fractured zone of longwall mines in this mining district. Grid blanking was used to isolate the volume over the actual panels from the entire modeled district and to calculate gas amounts that were directly related to the emissions in longwall mines.</span></p><p id=\"sp0015\">Results indicated that gas-in-place in the Pittsburgh seam, in the caved zone and in the fractured zone, as well as displacements in major rock units, showed spatial correlations that could be modeled and estimated using geostatistical methods. This study showed that GIP volumes may change up to 3&nbsp;MMscf per acre and, in a multi-panel district, may total 9&nbsp;<span>Bcf of methane within the gas emission zone. Therefore, ventilation and gas capture systems should be designed accordingly. In addition, rock displacements within the gas emission zone are spatially distributed. From an engineering and practical point of view,&nbsp;<a title=\"Learn more about spatial distribution\" href=\"https://www.sciencedirect.com/topics/earth-and-planetary-sciences/spatial-distribution\" data-mce-href=\"https://www.sciencedirect.com/topics/earth-and-planetary-sciences/spatial-distribution\">spatial distributions</a>&nbsp;of GIP and distributions of rock displacements should be correlated with in-mine emissions and gob gas venthole productions.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.coal.2011.10.010","issn":"01665162","usgsCitation":"Karacan, C.O., Olea, R., and Goodman, G., 2012, Geostatistical modeling of the gas emission zone and its in-place gas content for Pittsburgh-seam mines using sequential Gaussian simulation: International Journal of Coal Geology, v. 90-91, p. 50-71, https://doi.org/10.1016/j.coal.2011.10.010.","productDescription":"22 p.","startPage":"50","endPage":"71","ipdsId":"IP-031033","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":474676,"rank":10000,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/4589251","text":"External Repository"},{"id":242409,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":214664,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.coal.2011.10.010"}],"volume":"90-91","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a28b3e4b0c8380cd5a320","contributors":{"authors":[{"text":"Karacan, Cevat O. 0000-0002-0947-8241","orcid":"https://orcid.org/0000-0002-0947-8241","contributorId":67742,"corporation":false,"usgs":true,"family":"Karacan","given":"Cevat","email":"","middleInitial":"O.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":435243,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Olea, Ricardo A. 0000-0003-4308-0808","orcid":"https://orcid.org/0000-0003-4308-0808","contributorId":26436,"corporation":false,"usgs":true,"family":"Olea","given":"Ricardo A.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":435241,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Goodman, G.","contributorId":29233,"corporation":false,"usgs":true,"family":"Goodman","given":"G.","email":"","affiliations":[],"preferred":false,"id":435242,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70032251,"text":"70032251 - 2012 - Petroleum prospectivity of the Canada Basin, Arctic Ocean","interactions":[],"lastModifiedDate":"2020-12-03T21:17:52.831554","indexId":"70032251","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2682,"text":"Marine and Petroleum Geology","active":true,"publicationSubtype":{"id":10}},"title":"Petroleum prospectivity of the Canada Basin, Arctic Ocean","docAbstract":"<p id=\"abspara0010\">Reconnaissance seismic reflection data indicate that Canada Basin is a &gt;700,000 sq. km. remnant of the Amerasia Basin of the Arctic Ocean that lies south of the Alpha-Mendeleev Large Igneous Province, which was constructed across the northern part of the Amerasia Basin between about 127 and 89–83.5&nbsp;Ma. Canada Basin was filled by Early Jurassic to Holocene detritus from the Beaufort–Mackenzie Deltaic System, which drains the northern third of interior North America, with sizable contributions from Alaska and Northwest Canada. The basin contains roughly 5 or 6 million cubic km of sediment. Three fourths or more of this volume generates low amplitude seismic reflections, interpreted to represent hemipelagic deposits, which contain lenses to extensive interbeds of moderate amplitude reflections interpreted to represent unconfined turbidite and amalgamated channel deposits.</p><p id=\"abspara0015\">Extrapolation from Arctic Alaska and Northwest Canada suggests that three fourths of the section in Canada Basin is correlative with stratigraphic sequences in these areas that contain intervals of hydrocarbon source rocks. In addition, worldwide heat flow averages suggest that about two thirds of Canada Basin lies in the oil or gas windows. Structural, stratigraphic and combined structural and stratigraphic features of local to regional occurrence offer exploration targets in Canada Basin, and at least one of these contains bright spots. However, deep water (to almost 4000&nbsp;m), remoteness from harbors and markets, and thick accumulations of seasonal to permanent sea ice (until its possible removal by global warming later this century) will require the discovery of very large deposits for commercial success in most parts of Canada Basin.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.marpetgeo.2011.11.001","issn":"02648172","usgsCitation":"Grantz, A., and Hart, P.E., 2012, Petroleum prospectivity of the Canada Basin, Arctic Ocean: Marine and Petroleum Geology, v. 30, no. 1, p. 126-143, https://doi.org/10.1016/j.marpetgeo.2011.11.001.","productDescription":"18 p.","startPage":"126","endPage":"143","numberOfPages":"18","ipdsId":"IP-024561","costCenters":[{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":242442,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":214694,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.marpetgeo.2011.11.001"}],"country":"United States","otherGeospatial":"Canada Basin, Arctic Ocean","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -154.68749999999997,\n              71.30079291637452\n            ],\n            [\n              -125.859375,\n              67.33986082559095\n            ],\n            [\n              -99.140625,\n              67.47492238478702\n            ],\n            [\n              -62.57812500000001,\n              78.56048828398782\n            ],\n            [\n              -53.0859375,\n              83.599030708362\n            ],\n            [\n              -125.15625000000001,\n              84.77052832075908\n            ],\n            [\n              -170.859375,\n              83.52016238353205\n            ],\n            [\n              -164.8828125,\n              73.92246884621463\n            ],\n            [\n              -154.68749999999997,\n              71.30079291637452\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"30","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a77fce4b0c8380cd785e8","contributors":{"authors":[{"text":"Grantz, Arthur agrantz@usgs.gov","contributorId":2585,"corporation":false,"usgs":true,"family":"Grantz","given":"Arthur","email":"agrantz@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":435245,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hart, Patrick E. 0000-0002-5080-1426 hart@usgs.gov","orcid":"https://orcid.org/0000-0002-5080-1426","contributorId":2879,"corporation":false,"usgs":true,"family":"Hart","given":"Patrick","email":"hart@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":435244,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
]}