{"pageNumber":"270","pageRowStart":"6725","pageSize":"25","recordCount":46681,"records":[{"id":70216315,"text":"70216315 - 2019 - Nutrient scarcity as a selective pressure for mast seeding","interactions":[],"lastModifiedDate":"2020-11-11T15:35:13.934687","indexId":"70216315","displayToPublicDate":"2019-12-02T09:28:40","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5201,"text":"Nature Plants","onlineIssn":"2055-0278","active":true,"publicationSubtype":{"id":10}},"title":"Nutrient scarcity as a selective pressure for mast seeding","docAbstract":"<p><span>Mast seeding is one of the most intriguing reproductive traits in nature. Despite its potential drawbacks in terms of fitness, the widespread existence of this phenomenon suggests that it should have evolutionary advantages under certain circumstances. Using a global dataset of seed production time series for 219 plant species from all of the continents, we tested whether masting behaviour appears predominantly in species with low foliar nitrogen and phosphorus concentrations when controlling for local climate and productivity. Here, we show that masting intensity is higher in species with low foliar N and P concentrations, and especially in those with imbalanced N/P ratios, and that the evolutionary history of masting behaviour has been linked to that of nutrient economy. Our results support the hypothesis that masting is stronger in species growing under limiting conditions and suggest that this reproductive behaviour might have evolved as an adaptation to nutrient limitations and imbalances.</span></p>","language":"English","publisher":"Springer","doi":"10.1038/s41477-019-0549-y","usgsCitation":"Fernández-Martínez, M., Pearse, I., Sardans, J., Sayol, F., Koenig, W.D., LaMontagne, J.M., Bogdziewicz, M., Collalti, A., Hacket-Pain, A., Vacchiano, G., Espelta, J., Penuelas, J., and Janssens, I.A., 2019, Nutrient scarcity as a selective pressure for mast seeding: Nature Plants, v. 5, p. 1222-1228, https://doi.org/10.1038/s41477-019-0549-y.","productDescription":"7 p.","startPage":"1222","endPage":"1228","ipdsId":"IP-109180","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":459045,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://ddd.uab.cat/record/216950","text":"Publisher Index Page"},{"id":437269,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P96N15HF","text":"USGS data release","linkHelpText":"Data on interannual variability of seed production, nutrient, and weather for 219 plant species"},{"id":380416,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"5","noUsgsAuthors":false,"publicationDate":"2019-12-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Fernández-Martínez, M.","contributorId":244805,"corporation":false,"usgs":false,"family":"Fernández-Martínez","given":"M.","affiliations":[{"id":48983,"text":"U. Antwerp","active":true,"usgs":false}],"preferred":false,"id":804649,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pearse, Ian S. 0000-0001-7098-0495","orcid":"https://orcid.org/0000-0001-7098-0495","contributorId":211154,"corporation":false,"usgs":true,"family":"Pearse","given":"Ian","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":804650,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sardans, Jordi","contributorId":210471,"corporation":false,"usgs":false,"family":"Sardans","given":"Jordi","email":"","affiliations":[],"preferred":false,"id":804651,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sayol, F.","contributorId":244806,"corporation":false,"usgs":false,"family":"Sayol","given":"F.","email":"","affiliations":[{"id":48984,"text":"University of Gothenburg, Sweden","active":true,"usgs":false}],"preferred":false,"id":804652,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Koenig, W. D.","contributorId":244807,"corporation":false,"usgs":false,"family":"Koenig","given":"W.","email":"","middleInitial":"D.","affiliations":[{"id":36682,"text":"Cornell Lab of Ornithology","active":true,"usgs":false}],"preferred":false,"id":804653,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"LaMontagne, J. M.","contributorId":225095,"corporation":false,"usgs":false,"family":"LaMontagne","given":"J.","email":"","middleInitial":"M.","affiliations":[{"id":36623,"text":"DePaul University","active":true,"usgs":false}],"preferred":false,"id":804654,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bogdziewicz, M.","contributorId":228912,"corporation":false,"usgs":false,"family":"Bogdziewicz","given":"M.","affiliations":[{"id":40150,"text":"Adam Mickiewicz University, Poland","active":true,"usgs":false}],"preferred":false,"id":804655,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Collalti, A.","contributorId":244808,"corporation":false,"usgs":false,"family":"Collalti","given":"A.","email":"","affiliations":[{"id":48985,"text":"Institute for Agriculture and Forestry Systems in the Mediterranean, National Research Council of Italy","active":true,"usgs":false}],"preferred":false,"id":804656,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hacket-Pain, Andrew","contributorId":224290,"corporation":false,"usgs":false,"family":"Hacket-Pain","given":"Andrew","affiliations":[{"id":16977,"text":"University of Liverpool","active":true,"usgs":false}],"preferred":false,"id":804657,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Vacchiano, Giorgio","contributorId":224295,"corporation":false,"usgs":false,"family":"Vacchiano","given":"Giorgio","email":"","affiliations":[{"id":40851,"text":"University of Milan","active":true,"usgs":false}],"preferred":false,"id":804658,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Espelta, J. M.","contributorId":244810,"corporation":false,"usgs":false,"family":"Espelta","given":"J. M.","affiliations":[],"preferred":false,"id":804660,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Penuelas, J.","contributorId":45541,"corporation":false,"usgs":true,"family":"Penuelas","given":"J.","affiliations":[],"preferred":false,"id":804661,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Janssens, I. A.","contributorId":244809,"corporation":false,"usgs":false,"family":"Janssens","given":"I.","email":"","middleInitial":"A.","affiliations":[{"id":48983,"text":"U. Antwerp","active":true,"usgs":false}],"preferred":false,"id":804659,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}}
,{"id":70209036,"text":"70209036 - 2019 - Seasonal use of a nonnatal marine basin by juvenile hatchery chinook salmon","interactions":[],"lastModifiedDate":"2020-03-12T07:38:17","indexId":"70209036","displayToPublicDate":"2019-12-02T07:32:44","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2680,"text":"Marine and Coastal Fisheries: Dynamics, Management, and Ecosystem Science","active":true,"publicationSubtype":{"id":10}},"title":"Seasonal use of a nonnatal marine basin by juvenile hatchery chinook salmon","docAbstract":"Information on the movement patterns of fishes is essential for managers that are making critical resource decisions. We examined the frequency of a keystone species, Chinook Salmon Oncorhynchus tshawytscha that migrated from different marine basins to the Nisqually River estuary, which lies within the southernmost marine basin (hereafter, “South basin”) in Puget Sound (Washington, USA). Hatchery‐reared juvenile fish were sampled by using beach seine, lampara seine, and fyke nets to determine seasonal trends in frequency, habitat use, and the influence of different capture methods. The captured fish originated from three marine basins, nine Puget Sound rivers, and fourteen hatcheries. The data revealed a consistent pattern showing that most of the tagged fish (72%) were from the nearby Nisqually River (in the South basin), but fish from more northerly marine basins (hereafter, “Outbasin”) were also common. Although the majority of the tagged fish (99%) that were captured during April and May were originally released into rivers adjacent to the South basin, 90% of the fish that were captured in August and September had originated from rivers adjacent to Outbasin locations (up to 130 km distant). A comparison of sampling methods showed that the beach seine produced 27% Outbasin fish compared with 53% that were obtained with the lampara seine. The analysis of habitat use suggested that during June and July, more Outbasin fish (>40%) were captured in delta flats and nearshore habitats than in estuarine emergent marsh habitat (26%). Release location (river basin), but not distance, appeared to be an important factor that influenced the percentage of Outbasin fish that were captured in the South basin. However, it appeared that the fish that were released at light weights and early dates were more likely to be captured. Information on the movement of juvenile salmon to a nonnatal marine basin may help to increase our understanding of features of life history and survival, and it has application elsewhere, as many marine species are artificially propagated, released in large numbers, and have the potential to use nonnatal habitats.","language":"English","publisher":"American Fisheries Society","doi":"10.1002/mcf2.10098","usgsCitation":"Hayes, M.C., Hodgson, S., Ellings, C.S., Duval, W.D., and Rubin, S., 2019, Seasonal use of a nonnatal marine basin by juvenile hatchery chinook salmon: Marine and Coastal Fisheries: Dynamics, Management, and Ecosystem Science, v. 11, no. 6, p. 437-453, https://doi.org/10.1002/mcf2.10098.","productDescription":"17 p.","startPage":"437","endPage":"453","ipdsId":"IP-091656","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":459049,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/mcf2.10098","text":"Publisher Index Page"},{"id":373163,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Puget Sound","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -124.6124267578125,\n              48.27953734226008\n            ],\n            [\n              -122.81616210937499,\n              47.916342040161155\n            ],\n            [\n              -123.1512451171875,\n              46.90149244734082\n            ],\n            [\n              -122.05261230468751,\n              47.212105775622426\n            ],\n            [\n              -122.0745849609375,\n              48.49112712828191\n            ],\n            [\n              -122.59643554687499,\n              49.04506962208049\n            ],\n            [\n              -123.45336914062499,\n              48.96939999849952\n            ],\n            [\n              -124.771728515625,\n              48.741700879765396\n            ],\n            [\n              -124.6124267578125,\n              48.27953734226008\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"11","issue":"6","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2019-12-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Hayes, Michael C. 0000-0002-9060-0565 mhayes@usgs.gov","orcid":"https://orcid.org/0000-0002-9060-0565","contributorId":3017,"corporation":false,"usgs":true,"family":"Hayes","given":"Michael","email":"mhayes@usgs.gov","middleInitial":"C.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":784597,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hodgson, Sayre","contributorId":172121,"corporation":false,"usgs":false,"family":"Hodgson","given":"Sayre","email":"","affiliations":[{"id":26985,"text":"Nisqually Indian Tribe, Olympia, WA","active":true,"usgs":false}],"preferred":false,"id":784598,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ellings, Christopher S.","contributorId":149343,"corporation":false,"usgs":false,"family":"Ellings","given":"Christopher","email":"","middleInitial":"S.","affiliations":[{"id":17711,"text":"Dep't Natural Resources, Nisqually Indian Tribe, Olympia, WA","active":true,"usgs":false}],"preferred":false,"id":784599,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Duval, Walker D","contributorId":223217,"corporation":false,"usgs":false,"family":"Duval","given":"Walker","email":"","middleInitial":"D","affiliations":[{"id":40686,"text":"Nisqually Indian Tribe, Department of Natural Resources, 4820 She-Nah-Num Dr. SE, 8 Olympia, Washington 98513, USA","active":true,"usgs":false}],"preferred":false,"id":784600,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rubin, Steve 0000-0003-3054-7173","orcid":"https://orcid.org/0000-0003-3054-7173","contributorId":223218,"corporation":false,"usgs":true,"family":"Rubin","given":"Steve","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":784601,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70206712,"text":"70206712 - 2019 - Geologic map of the Blythe 7.5' quadrangle, La Paz County, Arizona and Riverside County, California","interactions":[],"lastModifiedDate":"2020-01-08T17:12:32","indexId":"70206712","displayToPublicDate":"2019-12-01T17:12:08","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"seriesTitle":{"id":5907,"text":" Arizona Geological Survey Digital Geologic Map","active":true,"publicationSubtype":{"id":2}},"seriesNumber":"DGM-124","title":"Geologic map of the Blythe 7.5' quadrangle, La Paz County, Arizona and Riverside County, California","docAbstract":"The geologic map of the Blythe 7.5' quadrangle spans about 60 percent of the width of the Holocene floodplain and valley floor of the lower Colorado River and the adjacent lower piedmont on the east side of the Colorado River Valley. This map depicts a composite geologic record of the river’s response to the transition from a natural flow regime to a strictly regulated one created by a series of upstream dams and channelization of much of its length. The floodplain map was developed using archival data sources including notes and maps from early river expeditions, early cadastral and topographical surveys, and a series of historical aerial photographs. The floodplain surface and its underlying young alluvial fill is herein referred to as the Blythe Alluvium, and this report provides the basis for defining it as a formal stratigraphic unit. Along the eastern edge of the map are piedmont deposits intercalated with Pliocene and Pleistocene Colorado River sediments underlying the Blythe Alluvium. The piedmont units include an array of washes and alluvial fans sourced in the Trigo and Dome Rock Mountains. These deposits were divided and mapped based on stratigraphic and geomorphic criteria including relative topographic relationships, and cross-cutting and inset stratigraphic relations among individual piedmont units and with ancestral Colorado River deposits. Varying thicknesses of those units likely exist below the Holocene floodplain, and this report presents those in the form of a lithologic-section of the valley based on available well data and accompanying descriptions.","language":"English","publisher":"Arizona Geological Survey","usgsCitation":"Block, D., Gootee, B.F., House, K., and Pearthree, P.A., 2019, Geologic map of the Blythe 7.5' quadrangle, La Paz County, Arizona and Riverside County, California:  Arizona Geological Survey Digital Geologic Map DGM-124, Report: 45 p.; 2 Sheets: 36 x 29.30 inches and 25.23 x 22.07 inches.","productDescription":"Report: 45 p.; 2 Sheets: 36 x 29.30 inches and 25.23 x 22.07 inches","ipdsId":"IP-089999","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":371092,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":371091,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://repository.azgs.az.gov/uri_gin/azgs/dlio/1932"}],"country":"United States","state":"Arizona, California","county":"La Paz County, Riverside County","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -115.08453369140625,\n              32.82421110161336\n            ],\n            [\n              -114.20013427734375,\n              32.82421110161336\n            ],\n            [\n              -114.20013427734375,\n              33.813384329112786\n            ],\n            [\n              -115.08453369140625,\n              33.813384329112786\n            ],\n            [\n              -115.08453369140625,\n              32.82421110161336\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Block, Debra 0000-0001-7348-3064 dblock@usgs.gov","orcid":"https://orcid.org/0000-0001-7348-3064","contributorId":198448,"corporation":false,"usgs":true,"family":"Block","given":"Debra","email":"dblock@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":775516,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gootee, Brian F. 0000-0001-5251-9080 bgootee@email.arizona.edu","orcid":"https://orcid.org/0000-0001-5251-9080","contributorId":201637,"corporation":false,"usgs":false,"family":"Gootee","given":"Brian","email":"bgootee@email.arizona.edu","middleInitial":"F.","affiliations":[{"id":34160,"text":"Arizona Geological Survey","active":true,"usgs":false}],"preferred":false,"id":775513,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"House, Kyle 0000-0002-0019-8075 khouse@usgs.gov","orcid":"https://orcid.org/0000-0002-0019-8075","contributorId":2293,"corporation":false,"usgs":true,"family":"House","given":"Kyle","email":"khouse@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":775514,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pearthree, Philip A 0000-0001-7676-8145","orcid":"https://orcid.org/0000-0001-7676-8145","contributorId":220713,"corporation":false,"usgs":false,"family":"Pearthree","given":"Philip","email":"","middleInitial":"A","affiliations":[{"id":34160,"text":"Arizona Geological Survey","active":true,"usgs":false}],"preferred":false,"id":775515,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70208117,"text":"70208117 - 2019 - Geochemistry and geophysics of iron oxide-apatite deposits and associated waste piles with implications for potential rare earth element resources from ore and historic mine waste in the eastern Adirondack Highlands, New York, USA","interactions":[],"lastModifiedDate":"2020-01-28T15:40:48","indexId":"70208117","displayToPublicDate":"2019-12-01T15:29:41","publicationYear":"2019","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":"Geochemistry and geophysics of iron oxide-apatite deposits and associated waste piles with implications for potential rare earth element resources from ore and historic mine waste in the eastern Adirondack Highlands, New York, USA","docAbstract":"<div class=\"article-section-wrapper \"><p>The iron oxide-apatite (IOA) deposits of the eastern Adirondack Highlands, New York, are historical high-grade magnetite mines that contain variable concentrations of rare earth element (REE)-bearing apatite crystals. The majority of the deposits are hosted within sodically altered Lyon Mountain granite gneiss, although some deposits occur within paragneiss, gabbro, anorthosite, or potassically altered Lyon Mountain granite gneiss. The IOA deposits and the waste and/or tailings piles associated with them have potential as an unconventional resource for REEs. Reprocessing of these piles would have the advantage of partial recycling of the waste material to produce a set of critical elements.</p><p>Thirty-four ore, nine rock, 25 waste-pile, and four tailings-pile samples were collected and analyzed for major, minor, and trace elements. At the tailings- and waste-pile sites, composite samples were collected by combining 30 to &gt;50 subsamples randomly distributed over each pile. The total REE content of the waste and tailings piles varied from approximately 10 to 22,000 ppm, whereas the ore sample concentrations ranged from approximately 15 to 48,000 ppm total REEs. A positive correlation exists between the total REE content of ore and its associated waste pile. Median light REE/heavy REE values were 2.14 for waste/tailings piles and 2.25 for ore, which is a substantial relative enrichment in the heavy REEs in comparison to many developed REE mines, such as the mined carbonatites of Bayan Obo, China, and Mountain Pass, California. Importantly, the ore and waste samples are significantly enriched in both Y and Nd compared to other REEs in the samples. Other minor components such as Th are also elevated. Airborne radiometric surveys show large positive eTh and eU anomalies corresponding to tailings piles.</p><p>Although it is a limited data set, geochemical data of unaltered and altered host rocks suggest a speculative new model for IOA ore formation in the Adirondack Highlands that is consistent with the geology and previously published data. The ferroan ore-hosting Lyon Mountain granite gneiss underwent localized potassic alteration that enriched the altered rock in Fe, REEs, Th, and other metals. A later sodic alteration event affected the previously potassically altered Lyon Mountain granite gneiss, which increased rock porosity and remobilized Fe, REEs, and other elements from the host rock into the iron ore seams. The sodic fluids responsible for ore formation were enriched in F and Cl.</p></div>","language":"English","publisher":"Society of Economic Geologists","doi":"10.5382/econgeo.4689","usgsCitation":"Taylor, R., Shah, A.K., Walsh, G.J., and Taylor, C.D., 2019, Geochemistry and geophysics of iron oxide-apatite deposits and associated waste piles with implications for potential rare earth element resources from ore and historic mine waste in the eastern Adirondack Highlands, New York, USA: Economic Geology, v. 114, no. 8, p. 1569-1598, https://doi.org/10.5382/econgeo.4689.","productDescription":"30 p.","startPage":"1569","endPage":"1598","ipdsId":"IP-105561","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":371659,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Adirondack Highlands","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -76.35498046875,\n              42.827638636242284\n            ],\n            [\n              -73.2568359375,\n              42.827638636242284\n            ],\n            [\n              -73.2568359375,\n              45.24395342262324\n            ],\n            [\n              -76.35498046875,\n              45.24395342262324\n            ],\n            [\n              -76.35498046875,\n              42.827638636242284\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"114","issue":"8","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Taylor, Ryan D. 0000-0002-8845-5290","orcid":"https://orcid.org/0000-0002-8845-5290","contributorId":201948,"corporation":false,"usgs":true,"family":"Taylor","given":"Ryan D.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":780544,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shah, Anjana K. 0000-0002-3198-081X ashah@usgs.gov","orcid":"https://orcid.org/0000-0002-3198-081X","contributorId":2297,"corporation":false,"usgs":true,"family":"Shah","given":"Anjana","email":"ashah@usgs.gov","middleInitial":"K.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":780545,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Walsh, Gregory J. 0000-0003-4264-8836 gwalsh@usgs.gov","orcid":"https://orcid.org/0000-0003-4264-8836","contributorId":873,"corporation":false,"usgs":true,"family":"Walsh","given":"Gregory","email":"gwalsh@usgs.gov","middleInitial":"J.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":780546,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Taylor, Cliff D. 0000-0001-6376-6298 ctaylor@usgs.gov","orcid":"https://orcid.org/0000-0001-6376-6298","contributorId":1283,"corporation":false,"usgs":true,"family":"Taylor","given":"Cliff","email":"ctaylor@usgs.gov","middleInitial":"D.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":780547,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70260153,"text":"70260153 - 2019 - Impacts of the 2015 eruption of Calbuco volcano on Chilean infrastructure, utilities, agriculture, and health","interactions":[],"lastModifiedDate":"2024-10-30T14:39:24.653338","indexId":"70260153","displayToPublicDate":"2019-12-01T09:33:11","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":3,"text":"Organization Series"},"seriesTitle":{"id":18999,"text":"GNS Science Report","active":true,"publicationSubtype":{"id":3}},"seriesNumber":"2019/04","title":"Impacts of the 2015 eruption of Calbuco volcano on Chilean infrastructure, utilities, agriculture, and health","docAbstract":"<p><span>This report presents data and summarises the findings of a reconnaissance trip investigating the impacts of the April 2015 eruption of Calbuco volcano, Chile, undertaken in November-December 2016. This study is mostly focused on the Los Lagos region, focusing on impacts occurring within ~30 km of the volcano, which includes the tourism town of Puerto Varas and port city of Puerto Montt. Eruption impacts and response strategies may be similar for moderate size eruptions from other stratovolcanoes in temperate regions. As such, this study provides useful information for development of contingency plans at active volcanoes around the world. The 2015 eruption of Calbuco volcano began at 18:04 (local time) on 22 April 2015 and consisted of three eruptive phases. The first lasted for 1.5 hours and generated a 15-km eruption column and plume that was directed towards the northeast. Pyroclastic density currents (PDCs) were generated locally and distributed radially, affecting many of the major rivers. A second phase began at 01:00 (local time) on 23 April 2015, lasted six hours and generated a 17-km high eruption column and plume that was dispersed towards the north-northeast, and the most voluminous pyroclastic density currents of the sequence. A third eruptive phase occurred on 30 April 12:10 (local time) resulting in a 5-km column and plume dispersed towards the east.</span></p>","language":"English","publisher":"The Institute of Geological and Nuclear Sciences Limited (GNS Science)","doi":"10.21420/02YC-VX66","usgsCitation":"Hayes, J., Deligne, N., Bertin, L., Calderon, R., Wardman, J., Wilson, T.J., Leonard, G., C., S., Wallace, K.L., and Baxter, P., 2019, Impacts of the 2015 eruption of Calbuco volcano on Chilean infrastructure, utilities, agriculture, and health: GNS Science Report 2019/04, 102 p., https://doi.org/10.21420/02YC-VX66.","productDescription":"102 p.","ipdsId":"IP-105929","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":463432,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Chile","otherGeospatial":"Calbuco volcano","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -73.48307304563127,\n              -40.573371240910895\n            ],\n            [\n              -73.48307304563127,\n              -42.33035124814165\n            ],\n            [\n              -71.89602918061058,\n              -42.33035124814165\n            ],\n            [\n              -71.89602918061058,\n              -40.573371240910895\n            ],\n            [\n              -73.48307304563127,\n              -40.573371240910895\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hayes, J.","contributorId":345669,"corporation":false,"usgs":false,"family":"Hayes","given":"J.","affiliations":[{"id":82688,"text":"University of Canterbury, NZ","active":true,"usgs":false}],"preferred":false,"id":917219,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Deligne, N. I.","contributorId":149573,"corporation":false,"usgs":false,"family":"Deligne","given":"N. I.","affiliations":[],"preferred":false,"id":917221,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bertin, L","contributorId":345670,"corporation":false,"usgs":false,"family":"Bertin","given":"L","email":"","affiliations":[{"id":82689,"text":"SERNAGEOMIN, Chile","active":true,"usgs":false}],"preferred":false,"id":917223,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Calderon, Rodrigo","contributorId":270274,"corporation":false,"usgs":false,"family":"Calderon","given":"Rodrigo","email":"","affiliations":[{"id":37172,"text":"University of Canterbury","active":true,"usgs":false}],"preferred":true,"id":917224,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wardman, J.","contributorId":345671,"corporation":false,"usgs":false,"family":"Wardman","given":"J.","affiliations":[{"id":16634,"text":"Bermuda Institute of Ocean Sciences","active":true,"usgs":false}],"preferred":false,"id":917225,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wilson, T. J.","contributorId":31942,"corporation":false,"usgs":false,"family":"Wilson","given":"T.","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":917220,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Leonard, G.","contributorId":149590,"corporation":false,"usgs":false,"family":"Leonard","given":"G.","email":"","affiliations":[],"preferred":false,"id":917222,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"C., Stewart.","contributorId":345672,"corporation":false,"usgs":false,"family":"C.","given":"Stewart.","email":"","affiliations":[{"id":82690,"text":"GNS Science / Massey University, NZ","active":true,"usgs":false}],"preferred":false,"id":917226,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Wallace, Kristi L. 0000-0002-0962-048X kwallace@usgs.gov","orcid":"https://orcid.org/0000-0002-0962-048X","contributorId":3454,"corporation":false,"usgs":true,"family":"Wallace","given":"Kristi","email":"kwallace@usgs.gov","middleInitial":"L.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":917227,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Baxter, P.","contributorId":149588,"corporation":false,"usgs":false,"family":"Baxter","given":"P.","email":"","affiliations":[],"preferred":false,"id":917228,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70227737,"text":"70227737 - 2019 - Predicting paleoclimate from compositional data using multivariate Gaussian process inverse prediction","interactions":[],"lastModifiedDate":"2022-01-28T15:34:56.321091","indexId":"70227737","displayToPublicDate":"2019-12-01T09:31:06","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":787,"text":"Annals of Applied Statistics","active":true,"publicationSubtype":{"id":10}},"title":"Predicting paleoclimate from compositional data using multivariate Gaussian process inverse prediction","docAbstract":"<p><span>Multivariate compositional count data arise in many applications including ecology, microbiology, genetics and paleoclimate. A frequent question in the analysis of multivariate compositional count data is what underlying values of a covariate(s) give rise to the observed composition. Learning the relationship between covariates and the compositional count allows for inverse prediction of unobserved covariates given compositional count observations. Gaussian processes provide a flexible framework for modeling functional responses with respect to a covariate without assuming a functional form. Many scientific disciplines use Gaussian process approximations to improve prediction and make inference on latent processes and parameters. When prediction is desired on unobserved covariates given realizations of the response variable, this is called inverse prediction. Because inverse prediction is often mathematically and computationally challenging, predicting unobserved covariates often requires fitting models that are different from the hypothesized generative model. We present a novel computational framework that allows for efficient inverse prediction using a Gaussian process approximation to generative models. Our framework enables scientific learning about how the latent processes co-vary with respect to covariates while simultaneously providing predictions of missing covariates. The proposed framework is capable of efficiently exploring the high dimensional, multi-modal latent spaces that arise in the inverse problem. To demonstrate flexibility, we apply our method in a generalized linear model framework to predict latent climate states given multivariate count data. Based on cross-validation, our model has predictive skill competitive with current methods while simultaneously providing formal, statistical inference on the underlying community dynamics of the biological system previously not available.</span></p>","language":"English","publisher":"Institute of Mathematical Statistics","doi":"10.1214/19-AOAS1281","usgsCitation":"Tipton, J.R., Hooten, M., Nolan, C., Booth, R.K., and McLachlan, J., 2019, Predicting paleoclimate from compositional data using multivariate Gaussian process inverse prediction: Annals of Applied Statistics, v. 13, no. 4, p. 2363-2388, https://doi.org/10.1214/19-AOAS1281.","productDescription":"26 p.","startPage":"2363","endPage":"2388","ipdsId":"IP-089036","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":459065,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1214/19-aoas1281","text":"Publisher Index Page"},{"id":395052,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Tipton, John R.","contributorId":272496,"corporation":false,"usgs":false,"family":"Tipton","given":"John","email":"","middleInitial":"R.","affiliations":[{"id":56379,"text":"u ark","active":true,"usgs":false}],"preferred":false,"id":831989,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hooten, Mevin 0000-0002-1614-723X mhooten@usgs.gov","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":2958,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin","email":"mhooten@usgs.gov","affiliations":[{"id":12963,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO","active":true,"usgs":false},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":831988,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nolan, Connor","contributorId":272497,"corporation":false,"usgs":false,"family":"Nolan","given":"Connor","affiliations":[{"id":56380,"text":"u az","active":true,"usgs":false}],"preferred":false,"id":831990,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Booth, Robert K.","contributorId":272498,"corporation":false,"usgs":false,"family":"Booth","given":"Robert","email":"","middleInitial":"K.","affiliations":[{"id":56381,"text":"lehigh  u","active":true,"usgs":false}],"preferred":false,"id":831991,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McLachlan, Jason","contributorId":272499,"corporation":false,"usgs":false,"family":"McLachlan","given":"Jason","affiliations":[{"id":36611,"text":"Notre Dame","active":true,"usgs":false}],"preferred":false,"id":831992,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70236881,"text":"70236881 - 2019 - Joint system-input identification of bridge structures","interactions":[],"lastModifiedDate":"2022-09-21T13:44:58.319143","indexId":"70236881","displayToPublicDate":"2019-12-01T08:37:52","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":12599,"text":"Turkish Journal of Earthquake Research","active":true,"publicationSubtype":{"id":10}},"title":"Joint system-input identification of bridge structures","docAbstract":"<p><span>This paper presents a novel framework for system identification of bridge structures using recorded earthquake data. Bridge structures are prone to spatial variability of ground motions because they extend over relatively long distances. So, input motion measurement is a challenging task, especially for long bridges with multiple piers. Moreover, direct measurement of the bridge Foundation Input Motions (FIMs) may not be possible due to both inertial and kinematic Soil-Structure Interaction (SSI) effects. In this study, we propose a joint system-input identification solution using sparsely measured earthquake-induced responses. We verify this method and its applicability for real scale problems using simulated data obtained from the Golden Gate Bridge.</span></p>","language":"English, Turkish","doi":"10.46464/tdad.593551","usgsCitation":"Ghahari, S., Celebi, M., Ebrahimian, H., Cetiner, B., and Taciroglu, E., 2019, Joint system-input identification of bridge structures: Turkish Journal of Earthquake Research, v. 1, no. 2, p. 98-122, https://doi.org/10.46464/tdad.593551.","productDescription":"25 p.","startPage":"98","endPage":"122","ipdsId":"IP-108253","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":459070,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.46464/tdad.593551","text":"Publisher Index Page"},{"id":407132,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"San Francisco","otherGeospatial":"Golden Gate Bridge","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.48090744018555,\n              37.808292105520145\n            ],\n            [\n              -122.47455596923828,\n              37.808292105520145\n            ],\n            [\n              -122.47455596923828,\n              37.82687023785448\n            ],\n            [\n              -122.48090744018555,\n              37.82687023785448\n            ],\n            [\n              -122.48090744018555,\n              37.808292105520145\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"1","issue":"2","noUsgsAuthors":false,"publicationDate":"2019-12-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Ghahari, S. F.","contributorId":296773,"corporation":false,"usgs":false,"family":"Ghahari","given":"S. F.","affiliations":[{"id":13399,"text":"UCLA","active":true,"usgs":false}],"preferred":false,"id":852456,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Celebi, Mehmet 0000-0002-4769-7357 celebi@usgs.gov","orcid":"https://orcid.org/0000-0002-4769-7357","contributorId":200969,"corporation":false,"usgs":true,"family":"Celebi","given":"Mehmet","email":"celebi@usgs.gov","affiliations":[],"preferred":true,"id":852457,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ebrahimian, H.","contributorId":296774,"corporation":false,"usgs":false,"family":"Ebrahimian","given":"H.","affiliations":[{"id":64167,"text":"SC Solutions","active":true,"usgs":false}],"preferred":false,"id":852458,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cetiner, Barbaros","contributorId":296879,"corporation":false,"usgs":false,"family":"Cetiner","given":"Barbaros","email":"","affiliations":[],"preferred":false,"id":852623,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Taciroglu, E.","contributorId":147710,"corporation":false,"usgs":false,"family":"Taciroglu","given":"E.","email":"","affiliations":[{"id":13399,"text":"UCLA","active":true,"usgs":false}],"preferred":false,"id":852459,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70216464,"text":"70216464 - 2019 - A shallow rift basin segmented in space and time: The southern San Luis Basin, Rio Grande rift, northern New Mexico, U.S.A.","interactions":[],"lastModifiedDate":"2020-11-20T14:11:15.783736","indexId":"70216464","displayToPublicDate":"2019-12-01T07:59:29","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3310,"text":"Rocky Mountain Geology","active":true,"publicationSubtype":{"id":10}},"title":"A shallow rift basin segmented in space and time: The southern San Luis Basin, Rio Grande rift, northern New Mexico, U.S.A.","docAbstract":"<p><span>Interpretation of gravity, magnetotelluric, and aeromagnetic data in conjunction with geologic constraints reveals details of basin geometry, thickness, and spatiotemporal evolution of the southern San Luis Basin, one of the major basins of the northern Rio Grande rift. Spatial variations of low-density basin-fill thickness are estimated primarily using a 3D gravity inversion method that improves on previous modeling efforts by separating the effects of the low-density basin fill from the effects of pre-rift rocks. The basin is found to be significantly narrower—and more complex in the subsurface—than indicated or implied by previous modeling efforts. The basin is also estimated to be significantly shallower than previously estimated. Five distinct subbasins are recognized within the broader southern San Luis Basin. The oldest and shallowest subbasin is the Las Mesitas graben along the northwestern basin margin, formed during the Oligocene transition from Southern Rocky Mountain volcanic field magmatism to rifting. In this subbasin, sediments are estimated to reach a maximum thickness of ~400 m within a north–south elongated structural depression. Other subbasins that likely initially developed during the Miocene are the dominant tectonic features in the southern San Luis Basin. This includes the Tres Orejas subbasin, which formed in the southwestern portion of the basin by the Embudo fault zone and a hypothesized fault zone along its western margin. This subbasin reaches a maximum thickness of ~2 km, as indicated by magnetotelluric and gravity modeling. The Sunshine Valley, Questa, and Taos subbasins occupy the eastern part of the southern San Luis Basin. The southern Sangre de Cristo fault zone is the dominant tectonic feature that controlled their development after ~20 Ma. The east-down Gorge fault zone controlled the western margins of significant parts of these eastern subbasins, although much of the Taos subbasin may be superimposed on the Tres Orejas subbasin. Maximum low-density basin-fill thicknesses are estimated to be 1.2 km for the Sunshine Valley subbasin, 800 m for the Questa subbasin, and 1.8 km for the Taos subbasin. Subbasin-forming tectonic activity along the Gorge fault zone and within the Tres Orejas subbasin ceased by the end of the development of the largely Pliocene Taos Plateau volcanic field. After that, rift-related subsidence became more narrowly centered on the eastern margin of the basin, controlled mainly by the linked Embudo and southern Sangre de Cristo fault zones.</span></p>","language":"English","publisher":"Rocky Mountain Geology","doi":"10.24872/rmgjournal.54.2.97","usgsCitation":"Drenth, B.J., Grauch, V.J., Turner, K.J., Rodriguez, B.D., Thompson, R., and Bauer, P.W., 2019, A shallow rift basin segmented in space and time: The southern San Luis Basin, Rio Grande rift, northern New Mexico, U.S.A.: Rocky Mountain Geology, v. 54, no. 2, p. 97-131, https://doi.org/10.24872/rmgjournal.54.2.97.","productDescription":"35 p.","startPage":"97","endPage":"131","ipdsId":"IP-104797","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":459077,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.24872/rmgjournal.54.2.97","text":"Publisher Index Page"},{"id":380645,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United  States","state":"New Mexico","otherGeospatial":"San Luis Basin, Rio Grande rift","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -106.45751953125,\n              35.817813158696616\n            ],\n            [\n              -104.78759765625,\n              35.817813158696616\n            ],\n            [\n              -104.78759765625,\n              37.01132594307015\n            ],\n            [\n              -106.45751953125,\n              37.01132594307015\n            ],\n            [\n              -106.45751953125,\n              35.817813158696616\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"54","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Drenth, Benjamin J. 0000-0002-3954-8124 bdrenth@usgs.gov","orcid":"https://orcid.org/0000-0002-3954-8124","contributorId":1315,"corporation":false,"usgs":true,"family":"Drenth","given":"Benjamin","email":"bdrenth@usgs.gov","middleInitial":"J.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":805195,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grauch, V. J. 0000-0002-0761-3489 tien@usgs.gov","orcid":"https://orcid.org/0000-0002-0761-3489","contributorId":152256,"corporation":false,"usgs":true,"family":"Grauch","given":"V.","email":"tien@usgs.gov","middleInitial":"J.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":805196,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Turner, Kenzie J. 0000-0002-4940-3981 kturner@usgs.gov","orcid":"https://orcid.org/0000-0002-4940-3981","contributorId":496,"corporation":false,"usgs":true,"family":"Turner","given":"Kenzie","email":"kturner@usgs.gov","middleInitial":"J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":805197,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rodriguez, Brian D. 0000-0002-2263-611X brod@usgs.gov","orcid":"https://orcid.org/0000-0002-2263-611X","contributorId":836,"corporation":false,"usgs":true,"family":"Rodriguez","given":"Brian","email":"brod@usgs.gov","middleInitial":"D.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":805198,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thompson, Ren A. 0000-0002-3044-3043","orcid":"https://orcid.org/0000-0002-3044-3043","contributorId":207982,"corporation":false,"usgs":true,"family":"Thompson","given":"Ren A.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":805199,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bauer, Paul W.","contributorId":145562,"corporation":false,"usgs":false,"family":"Bauer","given":"Paul","email":"","middleInitial":"W.","affiliations":[{"id":16150,"text":"New Mexico Bureau of Geology and Mineral Resources","active":true,"usgs":false}],"preferred":false,"id":805200,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70206721,"text":"70206721 - 2019 - Estimating market conditions for potential entry of new sources of anthropogenic CO2 for EOR in the Permian Basin","interactions":[],"lastModifiedDate":"2019-12-03T06:51:56","indexId":"70206721","displayToPublicDate":"2019-11-30T12:17:12","publicationYear":"2019","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":18,"text":"Abstract or summary"},"title":"Estimating market conditions for potential entry of new sources of anthropogenic CO2 for EOR in the Permian Basin","docAbstract":"This study attempts to determine feasible carbon dioxide (CO2) price thresholds for entry of new sources of anthropogenic (man-made) CO2 for utilization in enhanced oil recovery (EOR) in the Permian Basin. Much of the discussion about carbon capture, utilization, and storage (CCUS) has focused on the high costs of carbon capture as the major barrier to entry of new anthropogenic sources of CO2 for EOR. In addition, a recent study by Edwards and Celia (2018) suggests that the lack of a CO2 transportation network to efficiently transport CO2 from ethanol plants in the Midwest to EOR sites in the Permian Basin could be a prohibitive barrier to commercial-scale entry (without some Government assistance to help finance the construction of new CO2 pipelines), despite the costs of carbon capture from ethanol plants being relatively low. Thus, entry of additional sources of anthropogenic CO2 for use in EOR in the Permian Basin could be primarily by major carbon emitters that are located closest to the existing CO2 pipeline network that currently transports mostly natural CO2 (extracted from geologic reservoirs) to EOR sites. Data from the U.S. Environmental Protection Agency (EPA)’s Greenhouse Gas Reporting Program (GHGRP) (U.S. Environmental Protection Agency, 2019) suggest that numerous major CO2 emitters are located within 50 km of the existing pipeline network that provides CO2 for EOR in the Permian Basin. The costs for connecting these potential sources of CO2 to the existing transportation infrastructure could be very low. Of these potential sources of anthropogenic CO2, the leading emitters are coal-fired electricity generation plants, and the sources with next-largest emissions are natural gas-fired power plants. However, the CO2 concentrations in the emission streams of these types of power plants is typically far lower than that for ethanol plants and some other industrial facilities (including natural gas processing plants), which causes the estimated capture costs (using currently available technologies) to be far higher, in general. In addition, the potential cost (per metric ton of CO2 supplied) of adding these new sources of anthropogenic CO2 for EOR in the Permian basin could be greater than expanding production of existing suppliers and developing new sources of natural CO2. On the other hand, their proximity to the existing pipeline network could allow them to be viable sources of anthropogenic CO2 for EOR in the Permian Basin, and the relative competitiveness of these sources with the existing use of natural CO2 could be further enhanced if they qualify for the recently revised 45Q tax credit (Heitkamp, 2017). The results of this study provide some estimates of the potential gaps in the costs of CO2 supply from these distinct sources, and the potential implications of the results for the market conditions that could be necessary to overcome those gaps are discussed.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"U.S. Association for Energy Economics and International Association for Energy Economics North American Conference, 37th","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"U.S. Association for Energy Economics and International Association for Energy Economics North American Conference, 37th","conferenceDate":"November 3-6, 2019","conferenceLocation":"Denver, CO","language":"English","publisher":"U.S. Association for Energy Economics","usgsCitation":"Anderson, S.T., and Cahan, S., 2019, Estimating market conditions for potential entry of new sources of anthropogenic CO2 for EOR in the Permian Basin, <i>in</i> U.S. Association for Energy Economics and International Association for Energy Economics North American Conference, 37th, Denver, CO, November 3-6, 2019, 2 p.","productDescription":"2 p.","ipdsId":"IP-110474","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":369807,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":369308,"type":{"id":15,"text":"Index Page"},"url":"https://www.usaee.org/usaee2019/program_concurrent.aspx"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Anderson, Steven T. 0000-0003-3481-3424 sanderson@usgs.gov","orcid":"https://orcid.org/0000-0003-3481-3424","contributorId":2532,"corporation":false,"usgs":true,"family":"Anderson","given":"Steven","email":"sanderson@usgs.gov","middleInitial":"T.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":775548,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cahan, Steven M. 0000-0002-4776-3668","orcid":"https://orcid.org/0000-0002-4776-3668","contributorId":205929,"corporation":false,"usgs":true,"family":"Cahan","given":"Steven M.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":775549,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70215197,"text":"70215197 - 2019 - Separating sea and slow slip signals on the seafloor","interactions":[],"lastModifiedDate":"2020-10-12T13:02:09.265924","indexId":"70215197","displayToPublicDate":"2019-11-29T08:00:07","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5999,"text":"Journal of Geophysical Research- Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Separating sea and slow slip signals on the seafloor","docAbstract":"<div class=\"article-section__content en main\"><p>Seafloor pressure measurements hold promise for estimating vertical displacements from transient slow slip events on submarine faults. We assess the accuracy of pressure offset estimates that evolve over days to weeks and the confidence with which they may be attributed to tectonic deformation or to the ocean water column. One common approach to resolve this ambiguity assumes water column pressures vary insignificantly over the study region and are represented by stable reference site pressures. Assessing the validity of this assumption requires independent evidence. Correlations between pressures and colocated temperatures collected during the Hikurangi Ocean Bottom Investigation of Tremor and Slow Slip experiment suggest temperatures might provide a useful independent proxy for water column pressures. We compared offsets estimated using several methods, with temperature and other proxies. The use of a temperature proxy was unsuccessful, because seafloor temperatures did not track the seasonal signal that contributes significantly to seafloor pressure changes over the slow slip event period. Regardless of the&nbsp;estimation method, offsets varied within a few cm around some uncertain reference level. Commonly used statistical measures are shown not to be reliable indicators of offset accuracy since offsets contribute minimally to the total variance. Offsets estimated using identical methods but with seafloor pressures simulated using a regional ocean model were larger than those derived from the data but had a similar pattern. Since the model simulates only water column processes, this suggests a significant fraction of the estimated pressure offsets are due to seasonal water column signal and are&nbsp;not of tectonic origin.</p></div>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2019JB018285","usgsCitation":"Gomberg, J.S., Hautala, S., Johnson, P., and Chiswell, S., 2019, Separating sea and slow slip signals on the seafloor: Journal of Geophysical Research- Solid Earth, v. 124, no. 12, p. 13486-13503, https://doi.org/10.1029/2019JB018285.","productDescription":"18 p.","startPage":"13486","endPage":"13503","ipdsId":"IP-109456","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":498872,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2019jb018285","text":"Publisher Index Page"},{"id":379298,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"New Zealand","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              177.418212890625,\n              -39.82541310342477\n            ],\n            [\n              179.219970703125,\n              -39.82541310342477\n            ],\n            [\n              179.219970703125,\n              -38.54816542304657\n            ],\n            [\n              177.418212890625,\n              -38.54816542304657\n            ],\n            [\n              177.418212890625,\n              -39.82541310342477\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"124","issue":"12","noUsgsAuthors":false,"publicationDate":"2019-12-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Gomberg, Joan S. 0000-0002-0134-2606 gomberg@usgs.gov","orcid":"https://orcid.org/0000-0002-0134-2606","contributorId":1269,"corporation":false,"usgs":true,"family":"Gomberg","given":"Joan","email":"gomberg@usgs.gov","middleInitial":"S.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":801139,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hautala, Susan","contributorId":194235,"corporation":false,"usgs":false,"family":"Hautala","given":"Susan","email":"","affiliations":[],"preferred":false,"id":801140,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Paul","contributorId":189150,"corporation":false,"usgs":false,"family":"Johnson","given":"Paul","email":"","affiliations":[],"preferred":false,"id":801141,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chiswell, Steve","contributorId":242932,"corporation":false,"usgs":false,"family":"Chiswell","given":"Steve","email":"","affiliations":[{"id":48587,"text":"National Institute of Water & Atmospheric Research Ltd","active":true,"usgs":false}],"preferred":false,"id":801142,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70207980,"text":"70207980 - 2019 - Orogenic recycling of detrital zircons characterizes age distributions of North American Cordilleran strata","interactions":[],"lastModifiedDate":"2021-04-02T14:31:04.434435","indexId":"70207980","displayToPublicDate":"2019-11-28T10:51:36","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3524,"text":"Tectonics","active":true,"publicationSubtype":{"id":10}},"title":"Orogenic recycling of detrital zircons characterizes age distributions of North American Cordilleran strata","docAbstract":"<div id=\"pb-page-content\" data-ng-non-bindable=\"\"><div data-pb-dropzone=\"main\" data-pb-dropzone-name=\"Main\"><div class=\"pageBody hub-page-body body-text\" data-widget-def=\"pageBody\" data-widget-id=\"72100436-7a82-49fc-933b-c6c9d8c42914\"><div class=\"page-body pagefulltext\"><div data-pb-dropzone=\"main\"><div class=\"hub-main-content\" data-widget-def=\"ux3-layout-widget\" data-widget-id=\"0f7bccba-8328-4dbd-a1fa-e84c526dd9ab\"><div class=\"container\"><div class=\"row\"><div class=\"agu-hub col-md-12\"><div class=\"row article-row\"><div id=\"article__content\" class=\"col-sm-12 col-md-8 col-lg-8 article__content article-row-left\"><div class=\"article__body \"><div class=\"abstract-group\"><div class=\"article-section__content en main\"><p><span>Detrital zircon (DZ) analysis has become the standard tool for source‐to‐sink sediment routing studies at many spatial and temporal scales. In North American source‐to‐sink studies, DZ distributions are commonly classified according to the presence/absence and proportions of DZ age groups associated with North American crustal provinces as well as peri‐Gondwanan and Cordilleran terranes. Although such a classification scheme is descriptive, these age groups typically do not uniquely identify most recent DZ source areas. Using a compilation of &gt;19,000 individual DZ ages for Mesoproterozoic‐Paleogene strata of the northern Rocky Mountains, including 2,053 new analyses from the Paleogene Renova Formation and its equivalents in southwestern Montana, we demonstrate periodic derivation of first‐cycle DZ from crystalline sources and widespread recycling of poly‐cycle DZ from sedimentary sources over multimillion‐year timescales. Results show that (1) DZ age distributions become increasingly complex between Mesoproterozoic and Paleogene time with the introduction of new DZ sources to the study area, but (2) once an age group appears in the northern Rocky Mountains stratigraphy, grains of that age persist up‐section. These trends show that most DZ age groups are spatiotemporally ubiquitous and nonunique. We largely attribute this to periodic, tectonically induced recycling of DZ into progressively younger sedimentary systems, rather than prolonged derivation of DZ from crystalline basement sources, a trend that reflects the growth of increasingly complex topography associated with the North American Cordillera.</span></p></div></div></div></div></div></div></div></div></div></div></div></div></div></div>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2019TC005810","usgsCitation":"Schwartz, T.M., Schwartz, R., and Weislogel, A., 2019, Orogenic recycling of detrital zircons characterizes age distributions of North American Cordilleran strata: Tectonics, v. 38, no. 12, p. 4320-4334, https://doi.org/10.1029/2019TC005810.","productDescription":"15 p.","startPage":"4320","endPage":"4334","ipdsId":"IP-110379","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":371464,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Montana, Wyoming","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -116.19140625,\n              43.691707903073805\n            ],\n            [\n              -109.48974609375,\n              43.691707903073805\n            ],\n            [\n              -109.48974609375,\n              46.17983040759436\n            ],\n            [\n              -116.19140625,\n              46.17983040759436\n            ],\n            [\n              -116.19140625,\n              43.691707903073805\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"38","issue":"12","noUsgsAuthors":false,"publicationDate":"2019-12-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Schwartz, Theresa Maude 0000-0001-6606-4072","orcid":"https://orcid.org/0000-0001-6606-4072","contributorId":221707,"corporation":false,"usgs":false,"family":"Schwartz","given":"Theresa","email":"","middleInitial":"Maude","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":false,"id":780021,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schwartz, Robert K.","contributorId":221708,"corporation":false,"usgs":false,"family":"Schwartz","given":"Robert K.","affiliations":[],"preferred":false,"id":780022,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Weislogel, A.L.","contributorId":45896,"corporation":false,"usgs":true,"family":"Weislogel","given":"A.L.","email":"","affiliations":[],"preferred":false,"id":780023,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70223764,"text":"70223764 - 2019 - Salinity and water clarity dictate seasonal variability in coastal submerged aquatic vegetation in subtropical estuarine environments","interactions":[],"lastModifiedDate":"2021-09-07T15:09:15.564186","indexId":"70223764","displayToPublicDate":"2019-11-28T10:04:03","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":860,"text":"Aquatic Biology","active":true,"publicationSubtype":{"id":10}},"title":"Salinity and water clarity dictate seasonal variability in coastal submerged aquatic vegetation in subtropical estuarine environments","docAbstract":"<p><span>Spatial and temporal variability characterize submerged aquatic vegetation (SAV) assemblages, but understanding the complex interactions of environmental drivers of SAV assemblages remains elusive. We documented SAV composition and biomass across a salinity gradient in a coastal estuary over 12 mo. Ten macrophyte species were identified. The dominant species,&nbsp;</span><i>Ceratophyllum demersum</i><span>&nbsp;and&nbsp;</span><i>Myriophyllum spicatum,</i><span>&nbsp;accounted for over 40% of total biomass. Only&nbsp;</span><i>Ruppia maritima</i><span>&nbsp;occurred across the salinity gradient. Salinity, water depth and clarity delineated 3 assemblages: a saline assemblage, and 2 groups of fresher-water species, one associated with deeper water and lower water clarity and the other associated with shallow water and higher water clarity. These assemblages exhibited intra-annual variation, with at least 5 times more biomass in late spring/mid-summer compared to early winter. This pattern was consistent across the estuary, although the difference between peak and low biomass varied by habitat type; brackish exhibited the greatest magnitude. This variation is likely due to higher variation in salinity and the species composition of this habitat. As climate change and coastal restoration impact timing and range of salinity, water depth and clarity in this region, these data can be used to help inform predictive models and management decisions.</span></p>","language":"English","publisher":"Inter-Research Science Publisher","doi":"10.3354/ab00719","usgsCitation":"Hillmann, E.R., DeMarco, K., and La Peyre, M., 2019, Salinity and water clarity dictate seasonal variability in coastal submerged aquatic vegetation in subtropical estuarine environments: Aquatic Biology, v. 28, p. 175-186, https://doi.org/10.3354/ab00719.","productDescription":"12 p.","startPage":"175","endPage":"186","ipdsId":"IP-105293","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":459093,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/ab00719","text":"Publisher Index Page"},{"id":388877,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -91.483154296875,\n              28.748396571187406\n            ],\n            [\n              -88.956298828125,\n              28.748396571187406\n            ],\n            [\n              -88.956298828125,\n              30.330212685432734\n            ],\n            [\n              -91.483154296875,\n              30.330212685432734\n            ],\n            [\n              -91.483154296875,\n              28.748396571187406\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"28","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hillmann, Eva R.","contributorId":200686,"corporation":false,"usgs":false,"family":"Hillmann","given":"Eva","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":822573,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"DeMarco, Kristin","contributorId":200003,"corporation":false,"usgs":false,"family":"DeMarco","given":"Kristin","email":"","affiliations":[],"preferred":false,"id":822574,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"La Peyre, Megan K. 0000-0001-9936-2252","orcid":"https://orcid.org/0000-0001-9936-2252","contributorId":264343,"corporation":false,"usgs":true,"family":"La Peyre","given":"Megan K.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":822576,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70215317,"text":"70215317 - 2019 - Potential threats facing a globally important population of the magnificent frigatebird Fregata magnificens","interactions":[],"lastModifiedDate":"2020-10-16T14:15:55.277198","indexId":"70215317","displayToPublicDate":"2019-11-27T12:10:57","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7163,"text":"Tropical Zoology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Potential threats facing a globally important population of the magnificent frigatebird <i>Fregata magnificens</i>","title":"Potential threats facing a globally important population of the magnificent frigatebird Fregata magnificens","docAbstract":"<div class=\"hlFld-Abstract test\"><div class=\"abstractSection abstractInFull\"><p>Tracking of seabirds has been used to identify foraging hotspots, migratory routes and to assess at-sea threats facing populations. One such threat is the potential negative interaction between seabirds and fisheries through incidental by-catch. In 2012, 60 magnificent frigatebirds<span>&nbsp;</span><i>Fregata magnificens</i><span>&nbsp;</span>were found dead, entangled in fishing line, at the globally important breeding site in the British Virgin Islands (BVI). To assess the potential relationship between foraging behaviour and fishing activity, data loggers were deployed on breeding magnificent frigatebirds to record foraging movements. In addition, a survey of local fishers was conducted to assess the scale of incidental by-catch. We recorded 28 complete foraging trips from GPS and GPS-GSM loggers, and 1758 PTT locations. Birds travelled up to 3.3–1067 km from their breeding colony and entered the waters of 10 neighbouring territories. A high percentage of fishers (93%<span>&nbsp;</span><i>n</i> = 28) reported catching at least one seabird annually, of which the most common were magnificent frigatebirds and brown boobies<span>&nbsp;</span><i>Sula leucogaster</i>. There are estimated to be at least 1112 vessels in the recreational and artisanal fishing fleets of BVI and its neighbouring islands. Thus, this substantial fishery may have potentially profound effects on seabird populations in the region.</p></div></div>","language":"English","publisher":"Taylor and Francis","doi":"10.1080/03946975.2019.1682352","usgsCitation":"Zaluski, S., Soanes, L., Bright, J., Georges, A., Jodice, P.G., Meyer, K., N., W.P., and Green, J., 2019, Potential threats facing a globally important population of the magnificent frigatebird Fregata magnificens: Tropical Zoology, v. 32, no. 4, p. 188-201, https://doi.org/10.1080/03946975.2019.1682352.","productDescription":"14 p.","startPage":"188","endPage":"201","ipdsId":"IP-070962","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":502429,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doaj.org/article/4fbe5e50633d473e8da2edd444dfde43","text":"External Repository"},{"id":379467,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"32","issue":"4","noUsgsAuthors":false,"publicationDate":"2019-11-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Zaluski, S.","contributorId":243185,"corporation":false,"usgs":false,"family":"Zaluski","given":"S.","email":"","affiliations":[{"id":48654,"text":"Jost Van Dykes Preservation Society","active":true,"usgs":false}],"preferred":false,"id":801680,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Soanes, L.M.","contributorId":243186,"corporation":false,"usgs":false,"family":"Soanes","given":"L.M.","email":"","affiliations":[{"id":16977,"text":"University of Liverpool","active":true,"usgs":false}],"preferred":false,"id":801681,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bright, J.A.","contributorId":243187,"corporation":false,"usgs":false,"family":"Bright","given":"J.A.","email":"","affiliations":[{"id":38853,"text":"Royal Society for the Protection of Birds","active":true,"usgs":false}],"preferred":false,"id":801682,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Georges, A.","contributorId":239467,"corporation":false,"usgs":false,"family":"Georges","given":"A.","email":"","affiliations":[{"id":47871,"text":"Institute for Applied Ecology, University of Canberra, Canberra, Australia","active":true,"usgs":false}],"preferred":false,"id":801683,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jodice, Patrick G.R. 0000-0001-8716-120X pjodice@usgs.gov","orcid":"https://orcid.org/0000-0001-8716-120X","contributorId":200009,"corporation":false,"usgs":true,"family":"Jodice","given":"Patrick","email":"pjodice@usgs.gov","middleInitial":"G.R.","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":801684,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Meyer, K.","contributorId":243188,"corporation":false,"usgs":false,"family":"Meyer","given":"K.","affiliations":[{"id":48655,"text":"Avian Research and Conservation Institute","active":true,"usgs":false}],"preferred":false,"id":801685,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"N., Woodfield- Pascoe","contributorId":243189,"corporation":false,"usgs":false,"family":"N.","given":"Woodfield-","email":"","middleInitial":"Pascoe","affiliations":[{"id":48656,"text":"National Parks Trust of the Virgin Islands","active":true,"usgs":false}],"preferred":false,"id":801686,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Green, J.A","contributorId":243190,"corporation":false,"usgs":false,"family":"Green","given":"J.A","affiliations":[{"id":16977,"text":"University of Liverpool","active":true,"usgs":false}],"preferred":false,"id":801687,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70204774,"text":"ofr20191093 - 2019 - Report of the River Master of the Delaware River for the period December 1, 2009–November 30, 2010","interactions":[],"lastModifiedDate":"2019-11-26T09:15:58","indexId":"ofr20191093","displayToPublicDate":"2019-11-26T10:35:00","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-1093","displayTitle":"Report of the River Master of the Delaware River for the Period December 1, 2009–November 30, 2010","title":"Report of the River Master of the Delaware River for the period December 1, 2009–November 30, 2010","docAbstract":"<p>A Decree of the Supreme Court of the United States, entered June 7, 1954, established the position of Delaware River Master within the U.S. Geological Survey. In addition, the Decree authorizes diversion of water from the Delaware River Basin and requires compensating releases from certain reservoirs, owned by New York City, to be made under the supervision and direction of the River Master. The Decree stipulates that the River Master will furnish reports to the Court, not less frequently than annually. This report is the 57th Annual Report of the River Master of the Delaware River. It covers the 2010 River Master report year, the period from December 1, 2009, to November 30, 2010.</p><p>During the report year, precipitation in the upper Delaware River Basin was 49.38 inches or 112 percent of the long-term average. Combined storage in Pepacton, Cannonsville, and Neversink Reservoirs remained high much of the year and did not decline below 80 percent of combined capacity until September 2010. A lower basin drought warning was issued by the Delaware River Basin Commission on September 24, 2010. It automatically ended on October 31, 2010, when the reservoir contents rose above drought levels, due in large part to heavy rainfall during the last week of September. River Master operations during the year were conducted as stipulated by the Decree and the Flexible Flow Management Program.</p><p>Diversions from the Delaware River Basin by New York City and New Jersey were in full compliance with the Decree. Reservoir releases were made as directed by the River Master at rates designed to meet the flow objective for the Delaware River at Montague, New Jersey, on 81 days during the report year. Interim Excess Release Quantity and conservation releases, designed to relieve thermal stress and protect the fishery and aquatic habitat in the tailwaters of the reservoirs, were made during the report year.</p><p>The quality of water in the Delaware Estuary between Trenton, New Jersey, and Reedy Island Jetty, Delaware, was monitored at various locations. Data on water temperature, specific conductance, dissolved oxygen, and pH were collected continuously by electronic instruments at four sites.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191093","usgsCitation":"Russell, K.L., Ockerman, D., Krejmas, B.E., Paulachok, G.N., and Mason, R.R., Jr., 2019, Report of the River Master of the Delaware River for the period December 1, 2009–November 30, 2010: U.S. Geological Survey Open-File Report 2019–1093, 128 p., https://doi.org/10.3133/ofr20191093.","productDescription":"x, 128 p.","numberOfPages":"142","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-099205","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":369615,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1093/ofr20191093.pdf","text":"Report","size":"3.08 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1093"},{"id":368735,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1093/coverthb.jpg"}],"country":"United States","state":"Delaware, Maryland, New Jersey, New York, Pennsylvania","otherGeospatial":"Delaware River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -76.278076171875,\n              39.32579941789298\n            ],\n            [\n              -74.608154296875,\n              39.32579941789298\n            ],\n            [\n              -74.608154296875,\n              42.68243539838623\n            ],\n            [\n              -76.278076171875,\n              42.68243539838623\n            ],\n            [\n              -76.278076171875,\n              39.32579941789298\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto: gs-w_odrm_webmaster@usgs.gov\" data-mce-href=\"mailto: gs-w_odrm_webmaster@usgs.gov\">Deputy Delaware River Master</a><br><a href=\"https://webapps.usgs.gov/odrm/\" data-mce-href=\"https://webapps.usgs.gov/odrm/\">Office of the Delaware River Master</a><br>U.S. Geological Survey<br>120 Route 209 South<br>Milford, PA 18337</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Definition of Terms and Procedures</li><li>Introduction</li><li>Method to Determine Directed Releases from New York City Reservoirs</li><li>Hydrologic Conditions</li><li>Operations</li><li>Comparison of River Master Operations Data with Other Records</li><li>Quality of Water in the Delaware Estuary</li><li>References Cited</li><li>Appendix 1. Flexible Flow Management Program Effective October 1, 2007</li><li>Appendix 2. Flexible Flow Management Program Effective December 10, 2008</li><li>Appendix 3. Temporary IERQ Extraordinary Needs Bank Releases Program for Summer 2010</li><li>Appendix 4. Temporary Thermal Releases Program for Fishery Protection</li><li>Appendix 5. Consent to Action by the Delaware River Master Amendment Number 1</li><li>Appendix 6. Temporary Supplemental Releases Program for Tentative 2009 Rondout West Branch Tunnel Shutdown</li><li>Appendix 7. Temporary Supplemental Releases Program for Tentative 2010 Rondout West Branch Tunnel Shutdown</li></ul>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2019-10-31","noUsgsAuthors":false,"publicationDate":"2019-10-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Russell, Kendra L. 0000-0002-3046-7440","orcid":"https://orcid.org/0000-0002-3046-7440","contributorId":218135,"corporation":false,"usgs":true,"family":"Russell","given":"Kendra","email":"","middleInitial":"L.","affiliations":[{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true}],"preferred":true,"id":768414,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ockerman, Darwin 0000-0003-1958-1688","orcid":"https://orcid.org/0000-0003-1958-1688","contributorId":218138,"corporation":false,"usgs":true,"family":"Ockerman","given":"Darwin","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":768418,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Krejmas, Bruce E.","contributorId":218136,"corporation":false,"usgs":false,"family":"Krejmas","given":"Bruce","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":768415,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Paulachok, Gary N.","contributorId":218137,"corporation":false,"usgs":false,"family":"Paulachok","given":"Gary","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":768416,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mason,, Robert R. Jr. 0000-0002-3998-3468 rrmason@usgs.gov","orcid":"https://orcid.org/0000-0002-3998-3468","contributorId":176493,"corporation":false,"usgs":true,"family":"Mason,","given":"Robert R.","suffix":"Jr.","email":"rrmason@usgs.gov","affiliations":[{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":false,"id":768417,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70212716,"text":"70212716 - 2019 - Combining sediment fingerprinting with age-dating sediment using fallout radionuclides for an agricultural stream, Walnut Creek, Iowa, USA","interactions":[],"lastModifiedDate":"2020-08-27T15:33:34.188151","indexId":"70212716","displayToPublicDate":"2019-11-26T10:08:29","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2457,"text":"Journal of Soils and Sediments","active":true,"publicationSubtype":{"id":10}},"title":"Combining sediment fingerprinting with age-dating sediment using fallout radionuclides for an agricultural stream, Walnut Creek, Iowa, USA","docAbstract":"<h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Purpose</h3><p>The main purpose of this study was to demonstrate the utility of the sediment fingerprinting approach to apportion surface-derived sediment, and then age date that portion using short-lived fallout radionuclides. In systems where a large mass of mobile sediment is in channel storage, age dating provides an understanding of the transfer of sediment through the watershed and the time scales over which management actions to reduce sediment loadings may be effective.</p><h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Materials and methods</h3><p>In the agricultural Walnut Creek watershed, Iowa, the sediment-fingerprinting approach with elemental analysis was used to apportion the sources of fine-grained sediment (croplands, prairie, unpaved roads, and channel banks). Fallout radionuclides (<sup>7</sup>Be,<span>&nbsp;</span><sup>210</sup>Pb<sub>ex</sub>) were used to age the portion of suspended sediment that was derived from agricultural topsoil. Age dating was performed at two different scales:<span>&nbsp;</span><sup>210</sup>Pb<sub>ex</sub><span>&nbsp;</span>which can date sediment to ~ 85&nbsp;years and<span>&nbsp;</span><sup>7</sup>Be to ~ 1&nbsp;year.</p><h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Results and discussion</h3><p>Sediment fingerprinting results indicated that the majority of suspended sediment is derived from cropland (62%) with streambanks contributing 36%, and prairie, pasture, and unpaved roads each contributing ≤ 1%. The topsoil–derived portion of sediment (primarily agriculture) dated using<span>&nbsp;</span><sup>210</sup>Pb<sub>ex</sub><span>&nbsp;</span>has ages ranging from 1 to 58&nbsp;years, and using<span>&nbsp;</span><sup>7</sup>Be, a component of much younger sediment that yields ages ranging from 44 to 205&nbsp;days. The occurrence of<span>&nbsp;</span><sup>7</sup>Be indicates that some portion of the sediment is young, on the order of months, whereas the dating based on<span>&nbsp;</span><sup>210</sup>Pb<sub>ex</sub><span>&nbsp;</span>indicates that some of the surface-derived sediment has been in channel storage for decades. Published studies in Walnut Creek indicate that a large component of sediment is stored in the channel bed.</p><h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Conclusions</h3><p>We conclude that the<span>&nbsp;</span><sup>210</sup>Pb<sub>ex</sub>-based ages are a reasonable estimate for the mean age of the surface-derived fraction and that<span>&nbsp;</span><sup>7</sup>Be activities are evidence that there is a smaller fraction of very young sediment in the stream. We propose a geomorphic model where agricultural soil is delivered to the channel and conveyed to the watershed outlet at three time scales: a geologic-millennial time scale, decades, and a young time scale (&lt; 1&nbsp;year).</p>","language":"English","publisher":"Springer","doi":"10.1007/s11368-018-2168-z","usgsCitation":"Gellis, A.C., Fuller, C.C., Van Metre, P.C., Filstrup, C.T., Cole, K., and Sabitov, T., 2019, Combining sediment fingerprinting with age-dating sediment using fallout radionuclides for an agricultural stream, Walnut Creek, Iowa, USA: Journal of Soils and Sediments, v. 19, p. 3374-3396, https://doi.org/10.1007/s11368-018-2168-z.","productDescription":"23 p.","startPage":"3374","endPage":"3396","ipdsId":"IP-090014","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":377887,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Iowa","county":"Jasper County","otherGeospatial":"Walnut Creek","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-93.234,41.8622],[-93.1187,41.8624],[-93.0035,41.8624],[-92.8845,41.8619],[-92.7674,41.8618],[-92.7683,41.776],[-92.768,41.6879],[-92.7683,41.6007],[-92.7567,41.6011],[-92.7564,41.509],[-92.8729,41.5082],[-92.9894,41.5083],[-93.1047,41.5078],[-93.2181,41.5076],[-93.3304,41.5074],[-93.3314,41.6004],[-93.3504,41.6004],[-93.3496,41.688],[-93.3494,41.7757],[-93.3492,41.8624],[-93.234,41.8622]]]},\"properties\":{\"name\":\"Jasper\",\"state\":\"IA\"}}]}","volume":"19","noUsgsAuthors":false,"publicationDate":"2018-11-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Gellis, Allen C. 0000-0002-3449-2889 agellis@usgs.gov","orcid":"https://orcid.org/0000-0002-3449-2889","contributorId":197684,"corporation":false,"usgs":true,"family":"Gellis","given":"Allen","email":"agellis@usgs.gov","middleInitial":"C.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":797334,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fuller, Christopher C. 0000-0002-2354-8074 ccfuller@usgs.gov","orcid":"https://orcid.org/0000-0002-2354-8074","contributorId":1831,"corporation":false,"usgs":true,"family":"Fuller","given":"Christopher","email":"ccfuller@usgs.gov","middleInitial":"C.","affiliations":[{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":797341,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Van Metre, Peter C. 0000-0001-7564-9814","orcid":"https://orcid.org/0000-0001-7564-9814","contributorId":211144,"corporation":false,"usgs":true,"family":"Van Metre","given":"Peter","email":"","middleInitial":"C.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":797342,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Filstrup, Christopher T.","contributorId":169032,"corporation":false,"usgs":false,"family":"Filstrup","given":"Christopher","email":"","middleInitial":"T.","affiliations":[{"id":6911,"text":"Iowa State University","active":true,"usgs":false}],"preferred":false,"id":797343,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cole, Kevin","contributorId":208183,"corporation":false,"usgs":false,"family":"Cole","given":"Kevin","email":"","affiliations":[{"id":37761,"text":"USDA-ARS, National Laboratory for Agriculture and the Environment, 1015 N. University Blvd, Ames. IA 50011","active":true,"usgs":false}],"preferred":false,"id":797344,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sabitov, Timur","contributorId":236885,"corporation":false,"usgs":false,"family":"Sabitov","given":"Timur","email":"","affiliations":[{"id":47559,"text":"Geology and Geophysics, Academy of Science of Uzbekistan","active":true,"usgs":false}],"preferred":false,"id":797345,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70206894,"text":"70206894 - 2019 - Phenology patterns indicate recovery trajectories of ponderosa pine forests after high-severity fires","interactions":[],"lastModifiedDate":"2019-12-09T15:04:14","indexId":"70206894","displayToPublicDate":"2019-11-26T08:49:29","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Phenology patterns indicate recovery trajectories of ponderosa pine forests after high-severity fires","docAbstract":"Post-fire recovery trajectories in ponderosa pine (Pinus ponderosa Laws.) forests of the US Southwest are increasingly shifting away from pre-burn vegetation communities.  This study investigated whether phenological metrics derived from a multi-decade remotely sensed imagery time-series could differentiate among grass, evergreen shrub, deciduous, or conifer-dominated replacement pathways.  We focused on 10 fires that burned ponderosa pine forests in Arizona and New Mexico, USA before the year 2000.  A total of 29 sites with discernable post-fire recovery signals were selected within high-severity burn areas.  At each site, we used Google Earth Engine to derive time-series of normalized difference vegetation index (NDVI) signals from Landsat Thematic Mapper, Enhanced Thematic Mapper+, and Operational Line Imager data from 1984 to 2017.  We aggregated values to 8- and 16-day intervals, fit Savitzy-Golay filters to each sequence, and extracted annual phenology metrics of amplitude, base value, peak value, and timing of peak value in the Timesat analysis package. Results show that relative to post-fire conditions, pre-burn ponderosa pine forests exhibit significantly lower mean NDVI amplitude (0.14 vs. 0.21), higher mean base NDVI (0.47 vs. 0.22), higher mean peak NDVI (0.60 vs. 0.43), and later mean peak NDVI (day of year 277 vs. 237).  Vegetation succession exhibits distinct phenometric characteristics as early as year five (amplitude) and as late as year 20 (timing of peak NDVI).  This study confirms the feasibility of leveraging phenology metrics derived from long-term imagery time series to identify and monitor ecological outcomes. This information may be of benefit to land resource managers who seek indicators of future landscape composition to inform management strategies.","language":"English","publisher":"MDPI","doi":"10.3390/rs11232782","usgsCitation":"Walker, J.J., and Soulard, C.E., 2019, Phenology patterns indicate recovery trajectories of ponderosa pine forests after high-severity fires: Remote Sensing, v. 11, no. 23, 2782, https://doi.org/10.3390/rs11232782.","productDescription":"2782","ipdsId":"IP-112858","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":459110,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs11232782","text":"Publisher Index Page"},{"id":437276,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9Y1Z03F","text":"USGS data release","linkHelpText":"Phenology pattern data indicating recovery trajectories of ponderosa pine forests after 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 \"}}]}","volume":"11","issue":"23","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-11-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Walker, Jessica J. 0000-0002-3225-0317 jjwalker@usgs.gov","orcid":"https://orcid.org/0000-0002-3225-0317","contributorId":169458,"corporation":false,"usgs":true,"family":"Walker","given":"Jessica","email":"jjwalker@usgs.gov","middleInitial":"J.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":776179,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Soulard, Christopher E. 0000-0002-5777-9516 csoulard@usgs.gov","orcid":"https://orcid.org/0000-0002-5777-9516","contributorId":2642,"corporation":false,"usgs":true,"family":"Soulard","given":"Christopher","email":"csoulard@usgs.gov","middleInitial":"E.","affiliations":[{"id":657,"text":"Western Geographic Science 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,{"id":70220223,"text":"70220223 - 2019 - Investigating the accuracy of one‐dimensional volcanic plume models using laboratory experiments and field data","interactions":[],"lastModifiedDate":"2021-04-28T13:13:55.608928","indexId":"70220223","displayToPublicDate":"2019-11-26T08:11:29","publicationYear":"2019","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":"Investigating the accuracy of one‐dimensional volcanic plume models using laboratory experiments and field data","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>During volcanic eruptions, model predictions of plume height are limited by the accuracy of entrainment coefficients used in many plume models. Typically, two parameters are used,<span>&nbsp;</span><i>α</i><span>&nbsp;</span>and<span>&nbsp;</span><i>β</i>, which relate the entrained air speed to the jet speed in the axial and cross‐flow directions, respectively. To improve estimates of these parameters, wind tunnel experiments have been conducted for a range of cross‐wind velocities and turbulence conditions. Measurements are compared directly to computations from the 1‐D plume model, Plumeria, in the near‐field, bending region of the jet. Entrainment coefficients are determined through regression analysis, demonstrating optimal combinations of effective<span>&nbsp;</span><i>α</i><span>&nbsp;</span>and<span>&nbsp;</span><i>β</i><span>&nbsp;</span>values. For turbulent conditions, all wind speeds overlapped at a single combination,<span>&nbsp;</span><i>α</i><span>&nbsp;</span>= 0.06 and<span>&nbsp;</span><i>β</i>=0.46, each of&nbsp;which are slightly reduced from standard values. Refined coefficients were used to model plume heights for 20 historical eruptions. Model accuracy improves modestly in most cases, agreeing to within 3&nbsp;km with observed plume heights. For weak eruptions, uncertainty in field measurements can outweigh the effects of these refinements, illustrating the challenge of applying plume models in practice.</p></div></div></div></div>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2018jb017224","usgsCitation":"McNeal, J., Mastin, L.G., Cal, R., and Solovitz, S.A., 2019, Investigating the accuracy of one‐dimensional volcanic plume models using laboratory experiments and field data: Journal of Volcanology and Geothermal Research, v. 124, no. 11, p. 11290-11304, https://doi.org/10.1029/2018jb017224.","productDescription":"15 p.","startPage":"11290","endPage":"11304","ipdsId":"IP-101393","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":459113,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2018jb017224","text":"Publisher Index Page"},{"id":385350,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"124","issue":"11","noUsgsAuthors":false,"publicationDate":"2019-11-30","publicationStatus":"PW","contributors":{"authors":[{"text":"McNeal, James S.","contributorId":257656,"corporation":false,"usgs":false,"family":"McNeal","given":"James S.","affiliations":[{"id":52077,"text":"Washington State University, Vancouver","active":true,"usgs":false}],"preferred":false,"id":814847,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mastin, Larry G. 0000-0002-4795-1992 lgmastin@usgs.gov","orcid":"https://orcid.org/0000-0002-4795-1992","contributorId":555,"corporation":false,"usgs":true,"family":"Mastin","given":"Larry","email":"lgmastin@usgs.gov","middleInitial":"G.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":814850,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cal, Raul B.","contributorId":257658,"corporation":false,"usgs":false,"family":"Cal","given":"Raul B.","affiliations":[{"id":6929,"text":"Portland State University","active":true,"usgs":false}],"preferred":false,"id":814849,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Solovitz, Stephen A. 0000-0001-7019-2958","orcid":"https://orcid.org/0000-0001-7019-2958","contributorId":257659,"corporation":false,"usgs":false,"family":"Solovitz","given":"Stephen","email":"","middleInitial":"A.","affiliations":[{"id":52077,"text":"Washington State University, Vancouver","active":true,"usgs":false}],"preferred":false,"id":814852,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70204598,"text":"sir20195071 - 2019 - Pecos River Basin salinity assessment, Santa Rosa Lake, New Mexico, to the confluence of the Pecos River and the Rio Grande, Texas, 2015","interactions":[],"lastModifiedDate":"2019-11-26T06:25:41","indexId":"sir20195071","displayToPublicDate":"2019-11-25T16:39:51","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-5071","displayTitle":"Pecos River Basin Salinity Assessment, Santa Rosa Lake, New Mexico, to the Confluence of the Pecos River and the Rio Grande, Texas, 2015","title":"Pecos River Basin salinity assessment, Santa Rosa Lake, New Mexico, to the confluence of the Pecos River and the Rio Grande, Texas, 2015","docAbstract":"<p>The elevated salinity of the Pecos River throughout much of its length is of paramount concern to water users and water managers. Dissolved-solids concentrations in the Pecos River exceed 3,000 milligrams per liter in many of its reaches in the study area, from Santa Rosa Lake, New Mexico, to the confluence of the Pecos River with the Rio Grande, Texas. The salinity of the Pecos River increases downstream and affects the availability of useable water in the Pecos River Basin. In this report, “salinity” and “dissolved-solids concentration” are considered synonymous; both terms are used to refer to the total ionic concentration of dissolved minerals in water. The sources of salinity in the Pecos River Basin are natural (geologic) and anthropogenic, including but not limited to groundwater discharge, springs, and irrigation return flows. Previous studies in the Pecos River Basin were project specific and designed to address salinity issues in specific parts of the basin; therefore, in 2015, the U.S. Geological Survey in cooperation with the U.S. Army Corps of Engineers, New Mexico Interstate Stream Commission, Texas Commission on Environmental Quality, and Texas Water Development Board assessed the major sources of salinity throughout the extent of the basin where elevated salinity in the Pecos River is well documented (that is, in the drainage area of the Pecos River from Santa Rosa Lake to the confluence of the Pecos River and the Rio Grande). The goal was to gain a better understanding of how specific areas might be contributing to the elevated salinity in the Pecos River and how salinity of the Pecos River has changed over time. This assessment includes a literature review and compilation of previously published salinity-related data, which guided the collection of additional water-quality samples and streamflow gain-loss measurements. Differences in water quality of surface-water and groundwater samples, streamflow measurements, and geophysical data were assessed to gain new insights regarding sources of salinity in the Pecos River Basin and a more detailed assessment of potential areas of elevated salinity in the basin. The datasets compiled for this assessment are available in a companion data release.</p><p>The literature review identified several potential sources of salinity inputs to the Pecos River in New Mexico and Texas. In New Mexico, sources of salinity inputs included sinkhole springs discharging into El Rito Creek, the Bitter Lake National Wildlife Refuge inflow to the Pecos River, inflow from the Rio Hondo, including the main channel and a restored channel at the Bitter Lake National Wildlife Refuge referred to as the “Rio Hondo spring channel,” the outflow from Lea Lake at Bottomless Lakes State Park, and the Malaga Bend region of the Pecos River. In Texas, sources of salinity inputs included Salt Creek downstream from Red Bluff Reservoir and the area near the Horsehead Crossing ford on the Pecos River.</p><p>The compilation of historical water-quality data revealed a lack of consistent sampling of the same constituents at the same sites along the main stem of the Pecos River, which results in data gaps that hinder the ability to effectively analyze long-term changes in water quality that may help with the understanding of how salinity in the Pecos River has changed over time and identifying the sources of salinity in the Pecos River Basin. To help fill these data gaps, water-quality and streamflow data were collected in the study area in February 2015 by the U.S. Geological Survey. Historical water-quality data and newly collected data from February 2015 were evaluated for selected major-ion concentrations, dissolved-solids concentrations, and deuterium, oxygen, and strontium isotopes. Analysis of the data indicated several areas of increasing salinity in the Pecos River. Most notable increases were in two subreaches of the river, between Acme, N. Mex., and Artesia, N. Mex., and between Orla, Tex., and Grandfalls, Tex. Increasing sodium and chloride concentrations from Acme to Artesia coincided with changes in isotopic ratios within the Pecos River Basin. Changes in isotopic ratios in this reach indicate a likely inflow from an isotopically different source of water compared to the water in the main stem of the Pecos River, such as groundwater inflow, inflow from surface-water features distinct from the main stem of the Pecos River, or both. In the subreach between Orla and Grandfalls, an increase in dissolved-solids concentrations was observed along with a shift in isotope values, indicating that neither evaporative processes in Red Bluff Reservoir nor inflow from Salt Creek likely solely influences the salinity of the Pecos River in this subreach. The highest dissolved-solids concentrations in the Pecos River Basin were measured downstream from Grandfalls, where dissolved-solids concentrations are greater than 16,000 milligrams per liter near Iraan, Tex. Changes in isotopic values (deuterium, oxygen, and strontium) indicate mixing of different waters at several areas along the main stem of the Pecos River. The spatial distribution of the areas of interest from the literature review and the water-quality data are available in the companion data release.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195071","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers, New Mexico Interstate Stream Commission, Texas Commission on Environmental Quality, and Texas Water Development Board","usgsCitation":"Houston, N.A., Thomas, J.V., Ging, P.B., Teeple, A.P., Pedraza, D.E., and Wallace, D.S., 2019, Pecos River Basin salinity assessment, Santa Rosa Lake, New Mexico, to the confluence of the Pecos River and the Rio Grande, Texas, 2015: U.S. Geological Survey Scientific Investigations Report 2019–5071, 75 p., https://doi.org/10.3133/sir20195071.","productDescription":"Report: xi, 75 p.; Data Release","numberOfPages":"91","onlineOnly":"Y","ipdsId":"IP-083306","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":369530,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7DB800T","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Water Quality, Streamflow Gain Loss, Geologic, and Geospatial Data Used in the Pecos River Basin Salinity Assessment from Santa Rosa Lake, New Mexico to the Confluence of the Pecos River and the Rio Grande, Texas, 1900–2015"},{"id":369528,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5071/coverthb.jpg"},{"id":369529,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5071/sir20195071.pdf","text":"Report","size":"9.72 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019–5071"}],"country":"United States","state":"Texas, New Mexico","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -102.39257812499999,\n              29.916852233070173\n            ],\n            [\n              -101.162109375,\n              29.305561325527698\n            ],\n            [\n              -100.1513671875,\n              30.826780904779774\n            ],\n            [\n              -99.97558593749999,\n              32.32427558887655\n            ],\n            [\n              -101.9970703125,\n              33.797408767572485\n            ],\n            [\n              -103.5791015625,\n              34.74161249883172\n            ],\n            [\n              -105.0732421875,\n              35.567980458012094\n            ],\n            [\n              -106.787109375,\n              36.38591277287651\n            ],\n            [\n              -107.22656249999999,\n              35.53222622770337\n            ],\n            [\n              -107.6220703125,\n              34.34343606848294\n            ],\n            [\n              -105.908203125,\n              32.62087018318113\n            ],\n            [\n              -102.39257812499999,\n              29.916852233070173\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, <a data-mce-href=\"https://www.usgs.gov/centers/tx-water\" href=\"https://www.usgs.gov/centers/tx-water\">Oklahoma-Texas Water Science Center</a><br>U.S. Geological Survey<br>1505 Ferguson Lane <br>Austin, TX 78754–4501 </p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Methods</li><li>Pecos River Basin Salinity Assessment</li><li>Summary</li><li>References Cited</li><li>Appendix 1. Recommendations From the Literature</li></ul>","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2019-11-25","noUsgsAuthors":false,"publicationDate":"2019-11-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Houston, Natalie A. 0000-0002-6071-4545","orcid":"https://orcid.org/0000-0002-6071-4545","contributorId":217873,"corporation":false,"usgs":true,"family":"Houston","given":"Natalie","email":"","middleInitial":"A.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":767724,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thomas, Jonathan V. 0000-0003-0903-9713","orcid":"https://orcid.org/0000-0003-0903-9713","contributorId":217874,"corporation":false,"usgs":true,"family":"Thomas","given":"Jonathan V.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":767725,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ging, Patricia B. 0000-0001-5491-8448","orcid":"https://orcid.org/0000-0001-5491-8448","contributorId":217875,"corporation":false,"usgs":true,"family":"Ging","given":"Patricia B.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":767726,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Teeple, Andrew P. 0000-0003-1781-8354","orcid":"https://orcid.org/0000-0003-1781-8354","contributorId":217876,"corporation":false,"usgs":true,"family":"Teeple","given":"Andrew P.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":767727,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pedraza, Diana E. 0000-0003-4483-8094","orcid":"https://orcid.org/0000-0003-4483-8094","contributorId":217877,"corporation":false,"usgs":true,"family":"Pedraza","given":"Diana E.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":767728,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wallace, David S. 0000-0002-9134-8197","orcid":"https://orcid.org/0000-0002-9134-8197","contributorId":217878,"corporation":false,"usgs":true,"family":"Wallace","given":"David","email":"","middleInitial":"S.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":767729,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70205808,"text":"sir20195111 - 2019 - Evaluating associations between environmental variables and Escherichia coli levels for predictive modeling at Pawtuckaway Beach in Nottingham, New Hampshire, from 2015 to 2017","interactions":[],"lastModifiedDate":"2019-11-25T09:58:08","indexId":"sir20195111","displayToPublicDate":"2019-11-25T09:35:00","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-5111","displayTitle":"Evaluating Associations Between Environmental Variables and <i>Escherichia Coli</i> Levels for Predictive Modeling at Pawtuckaway Beach in Nottingham, New Hampshire, From 2015 to 2017","title":"Evaluating associations between environmental variables and Escherichia coli levels for predictive modeling at Pawtuckaway Beach in Nottingham, New Hampshire, from 2015 to 2017","docAbstract":"<p>From 2015 through 2017, the U.S. Geological Survey in cooperation with the New Hampshire Department of Health and Human Services and the New Hampshire Department of Environmental Services studied occurrences of high levels of <i>Escherichia coli</i> (<i>E. coli</i>) bacteria at the Pawtuckaway State Park Beach in Nottingham, New Hampshire. Historic data collected by the New Hampshire Department of Environmental Services indicated that <i>E. coli</i> concentrations in the water typically increased through the beach season to levels considered potentially harmful to beachgoers. During the three beach seasons that were studied, <i>E. coli</i> samples were collected three to four times per week, and water-quality and meteorological data were collected continuously. The Virtual Beach software was used to generate a predictive model for each year of the study (2015–2017), and the model for each of these years was tested with data from the other two. Additionally, data from all study years were combined to generate a comprehensive model to help identify independent variables that might characterize environmental conditions relative to <i>E. coli</i> levels during multiple seasons. The accuracy of the models in predicting the occurrence of high <i>E. coli</i> levels was marginal, but the models did provide insights into the likely mechanisms for increased <i>E. coli</i> levels during the seasons. Variables most important in explaining high <i>E. coli</i> levels were the presence of geese at the beach, the progression of the season, the number of visitors at the beach, and wind vectors relative to beach orientation.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195111","collaboration":"Prepared in cooperation with the New Hampshire Department of Health and Human Services and the New Hampshire Department of Environmental Services","usgsCitation":"Coles, J.F., and Bush, K.F., 2019, Evaluating associations between environmental variables and <i>Escherichia coli</i> levels for predictive modeling at Pawtuckaway Beach in Nottingham, New Hampshire, from 2015 to 2017: U.S. Geological Survey Scientific Investigations Report 2019–5111, 28 p., https://doi.org/10.3133/sir20195111.","productDescription":"Report: vii, 28 p.; Data release","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-101776","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":369290,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5111/coverthb.jpg"},{"id":369288,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://www.sciencebase.gov/catalog/item/5cc70bf4e4b09b8c0b77e5b7","text":"USGS data release","linkFileType":{"id":5,"text":"html"},"linkHelpText":"Data collected at Pawtuckaway Beach in Nottingham, New Hampshire, 2015–2017"},{"id":369409,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5111/sir20195111.pdf","text":"Report","size":"4.57 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019-5111"}],"country":"United States","state":"New Hampshire","city":"Nottingham","otherGeospatial":"Pawtuckaway Beach","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -71.1595630645752,\n              43.08080002811761\n            ],\n            [\n              -71.14797592163086,\n              43.08080002811761\n            ],\n            [\n              -71.14797592163086,\n              43.08650455068649\n            ],\n            [\n              -71.1595630645752,\n              43.08650455068649\n            ],\n            [\n              -71.1595630645752,\n              43.08080002811761\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto: dc_nweng@usgs.gov\" data-mce-href=\"mailto: dc_nweng@usgs.gov\">Director</a>, <a href=\"https://www.usgs.gov/centers/new-england-water\" data-mce-href=\"https://www.usgs.gov/centers/new-england-water\">New England Water Science Center</a><br>U.S. Geological Survey<br>331 Commerce Way, Suite 2<br>Pembroke, NH 03275</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Objectives and Approach</li><li>Methods</li><li>Results</li><li>Discussion</li><li>Summary</li><li>Selected References</li><li>Appendix 1. The Virtual Beach Modeling Tool</li></ul>","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"publishedDate":"2019-11-25","noUsgsAuthors":false,"publicationDate":"2019-11-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Coles, James F. 0000-0002-1953-012X jcoles@usgs.gov","orcid":"https://orcid.org/0000-0002-1953-012X","contributorId":2239,"corporation":false,"usgs":true,"family":"Coles","given":"James","email":"jcoles@usgs.gov","middleInitial":"F.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":772439,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bush, Kathleen F.","contributorId":219516,"corporation":false,"usgs":false,"family":"Bush","given":"Kathleen","email":"","middleInitial":"F.","affiliations":[{"id":40019,"text":"NH-Dept. Health and Human Services","active":true,"usgs":false}],"preferred":false,"id":772440,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70207039,"text":"70207039 - 2019 - Using δ13C and δ18O to analyze loblolly pine (Pinus taeda L.) response to experimental drought and fertilization","interactions":[],"lastModifiedDate":"2019-12-05T06:36:50","indexId":"70207039","displayToPublicDate":"2019-11-21T15:26:48","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3649,"text":"Tree Physiology","active":true,"publicationSubtype":{"id":10}},"title":"Using δ13C and δ18O to analyze loblolly pine (Pinus taeda L.) response to experimental drought and fertilization","docAbstract":"Drought frequency and intensity are projected to increase throughout the southeastern USA, the natural range of loblolly pine (Pinus taeda L.), and are expected to have major ecological and economic implications. We analyzed the carbon and oxygen isotopic compositions in tree ring cellulose of loblolly pine in a factorial drought (~30% throughfall reduction) and fertilization experiment, supplemented with trunk sap flow, allometry and microclimate data. We then simulated leaf temperature and applied a multi-dimensional sensitivity analysis to interpret the changes in the oxygen isotope data. This analysis found that the observed changes in tree ring cellulose could only be accounted for by inferring a change in the isotopic composition of the source water, indicating that the drought treatment increased the uptake of stored moisture from earlier precipitation events. The drought treatment also increased intrinsic water-use efficiency, but had no effect on growth, indicating that photosynthesis remained relatively unaffected despite 19% decrease in canopy conductance. In contrast, fertilization increased growth, but had no effect on the isotopic composition of tree ring cellulose, indicating that the fertilizer gains in biomass were attributable to greater leaf area and not to changes in leaf-level gas exchange. The multi-dimensional sensitivity analysis explored model behavior under different scenarios, highlighting the importance of explicit consideration of leaf temperature in the oxygen isotope discrimination (Δ18Oc) simulation and is expected to expand the inference space of the Δ18Oc models for plant ecophysiological studies.","language":"English","publisher":"Oxford Academic","doi":"10.1093/treephys/tpz096","usgsCitation":"Lin, W., Domec, J., Ward, E., Marshall, J.D., King, J.S., Laviner, M.A., Fox, T.R., West, J.B., Sun, G., McNulty, S., and Noormets, A., 2019, Using δ13C and δ18O to analyze loblolly pine (Pinus taeda L.) response to experimental drought and fertilization: Tree Physiology, tpz096, https://doi.org/10.1093/treephys/tpz096.","productDescription":"tpz096","ipdsId":"IP-109073","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":459124,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1093/treephys/tpz096","text":"External Repository"},{"id":369919,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2019-11-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Lin, Wen","contributorId":221015,"corporation":false,"usgs":false,"family":"Lin","given":"Wen","email":"","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":776600,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Domec, Jean-Christophe","contributorId":146460,"corporation":false,"usgs":false,"family":"Domec","given":"Jean-Christophe","email":"","affiliations":[],"preferred":false,"id":776601,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ward, Eric 0000-0002-5047-5464","orcid":"https://orcid.org/0000-0002-5047-5464","contributorId":221014,"corporation":false,"usgs":true,"family":"Ward","given":"Eric","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":776599,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Marshall, John D.","contributorId":176597,"corporation":false,"usgs":false,"family":"Marshall","given":"John","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":776602,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"King, John S","contributorId":221017,"corporation":false,"usgs":false,"family":"King","given":"John","email":"","middleInitial":"S","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":776604,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Laviner, Marshall A.","contributorId":221018,"corporation":false,"usgs":false,"family":"Laviner","given":"Marshall","email":"","middleInitial":"A.","affiliations":[{"id":40311,"text":"Virginia Polytechnic Institute and University","active":true,"usgs":false}],"preferred":false,"id":776605,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Fox, Thomas R","contributorId":221016,"corporation":false,"usgs":false,"family":"Fox","given":"Thomas","email":"","middleInitial":"R","affiliations":[{"id":40311,"text":"Virginia Polytechnic Institute and University","active":true,"usgs":false}],"preferred":false,"id":776603,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"West, Jason B.","contributorId":221019,"corporation":false,"usgs":false,"family":"West","given":"Jason","email":"","middleInitial":"B.","affiliations":[{"id":6747,"text":"Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":776606,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Sun, Ge","contributorId":145893,"corporation":false,"usgs":false,"family":"Sun","given":"Ge","email":"","affiliations":[{"id":6684,"text":"USDA Forest Service, Southern Research Station, Aiken, SC","active":true,"usgs":false}],"preferred":false,"id":776607,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"McNulty, Steve G","contributorId":145897,"corporation":false,"usgs":false,"family":"McNulty","given":"Steve G","affiliations":[{"id":6684,"text":"USDA Forest Service, Southern Research Station, Aiken, SC","active":true,"usgs":false}],"preferred":false,"id":776608,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Noormets, Asko","contributorId":217423,"corporation":false,"usgs":false,"family":"Noormets","given":"Asko","email":"","affiliations":[{"id":6747,"text":"Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":776609,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70208996,"text":"70208996 - 2019 - General external uncertainty models of three-plane intersection point for 3D absolute accuracy assessment of lidar point cloud","interactions":[],"lastModifiedDate":"2020-03-10T13:53:55","indexId":"70208996","displayToPublicDate":"2019-11-21T13:47:56","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"General external uncertainty models of three-plane intersection point for 3D absolute accuracy assessment of lidar point cloud","docAbstract":"The traditional practice to assess accuracy in lidar data involves calculating RMSEz (root mean square error of the vertical component). Accuracy assessment of lidar point clouds in full 3D (dimension) is not routinely performed. The main challenge in assessing accuracy in full 3D is how to identify a conjugate point of a ground-surveyed checkpoint in the lidar point cloud with the smallest possible uncertainty value.  Relatively coarse point-spacing in airborne lidar data makes it challenging to determine a conjugate point accurately. As a result, a substantial unwanted error is added to the inherent positional uncertainty of the lidar data. Unless we keep this additional error small enough, the 3D accuracy assessment result will not properly represent the inherent uncertainty. We call this added error “external uncertainty,” which is associated with conjugate point identification. This research developed a general external uncertainty model using three-plane intersections and accounts for several factors (sensor precision, feature dimension, and point density). This method can be used for lidar point cloud data from a wide range of sensor qualities, point densities, and sizes of the features of interest. The external uncertainty model was derived as a semi-analytical function that takes the number of points on a plane as an input. It is a normalized general function that can be scaled by smooth surface precision (SSP) of a lidar system. This general uncertainty model provides a quantitative guideline on the required conditions for the conjugate point based on the geometric features. Applications of external uncertainty model was demonstrated using various lidar point cloud data from US Geological Survey (USGS) 3D Elevation Program (3DEP) library to determine the valid conditions for a conjugate point from three-plane.","language":"English","publisher":"MDPI","doi":"10.3390/rs11232737","usgsCitation":"Kim, M., Park, S., Danielson, J.J., Irwin, J., Stensaas, G.L., Stoker, J.M., and Nimetz, J., 2019, General external uncertainty models of three-plane intersection point for 3D absolute accuracy assessment of lidar point cloud: Remote Sensing, v. 11, no. 23, 2737, 18 p., https://doi.org/10.3390/rs11232737.","productDescription":"2737, 18 p.","ipdsId":"IP-113404","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":459128,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs11232737","text":"Publisher Index Page"},{"id":373048,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","issue":"23","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2019-11-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Kim, Minsu 0000-0003-4472-0926 minsukim@contractor.usgs.gov","orcid":"https://orcid.org/0000-0003-4472-0926","contributorId":216429,"corporation":false,"usgs":true,"family":"Kim","given":"Minsu","email":"minsukim@contractor.usgs.gov","affiliations":[{"id":54490,"text":"KBR, Inc., under contract to USGS","active":true,"usgs":false}],"preferred":true,"id":784451,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Park, Seonkyung 0000-0003-3203-1998","orcid":"https://orcid.org/0000-0003-3203-1998","contributorId":223182,"corporation":false,"usgs":true,"family":"Park","given":"Seonkyung","email":"","affiliations":[{"id":54490,"text":"KBR, Inc., under contract to USGS","active":true,"usgs":false}],"preferred":true,"id":784452,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Danielson, Jeffrey J. 0000-0003-0907-034X daniels@usgs.gov","orcid":"https://orcid.org/0000-0003-0907-034X","contributorId":3996,"corporation":false,"usgs":true,"family":"Danielson","given":"Jeffrey","email":"daniels@usgs.gov","middleInitial":"J.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":784453,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Irwin, Jeffrey 0000-0001-5828-0787 jrirwin@usgs.gov","orcid":"https://orcid.org/0000-0001-5828-0787","contributorId":222485,"corporation":false,"usgs":true,"family":"Irwin","given":"Jeffrey","email":"jrirwin@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":784454,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stensaas, Gregory L. 0000-0001-6679-2416 stensaas@usgs.gov","orcid":"https://orcid.org/0000-0001-6679-2416","contributorId":2551,"corporation":false,"usgs":true,"family":"Stensaas","given":"Gregory","email":"stensaas@usgs.gov","middleInitial":"L.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":784455,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stoker, Jason M. 0000-0003-2455-0931 jstoker@usgs.gov","orcid":"https://orcid.org/0000-0003-2455-0931","contributorId":3021,"corporation":false,"usgs":true,"family":"Stoker","given":"Jason","email":"jstoker@usgs.gov","middleInitial":"M.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":true,"id":784456,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Nimetz, Joshua 0000-0002-7132-9992","orcid":"https://orcid.org/0000-0002-7132-9992","contributorId":223183,"corporation":false,"usgs":true,"family":"Nimetz","given":"Joshua","email":"","affiliations":[{"id":5047,"text":"NGTOC Denver","active":true,"usgs":true}],"preferred":true,"id":784457,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70207442,"text":"70207442 - 2019 - Holocene earthquake history and slip rate of the southern Teton fault, Wyoming, USA","interactions":[],"lastModifiedDate":"2020-07-09T14:28:34.224535","indexId":"70207442","displayToPublicDate":"2019-11-21T13:12:47","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1786,"text":"Geological Society of America Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"Holocene earthquake history and slip rate of the southern Teton fault, Wyoming, USA","docAbstract":"The 72-km-long Teton normal fault bounds the eastern base of the Teton Range in northwestern Wyoming, USA. Although geomorphic surfaces along the fault record latest Pleistocene to Holocene fault movement, the postglacial earthquake history of the fault has remained enigmatic. We excavated a paleoseismic trench at the Buffalo Bowl site along the southernmost part of the fault to determine its Holocene rupture history and slip rate. At the site, ∼6.3 m of displacement postdates an early Holocene (ca. 10.5 ka) alluvial-fan surface. We document evidence of three surface-faulting earthquakes based on packages of scarp-derived colluvium that postdate the alluvial-fan units. Bayesian modeling of radiocarbon and luminescence ages yields earthquake times of ca. 9.9 ka, ca. 7.1 ka, and ca. 4.6 ka, forming the longest, most complete paleoseismic record of the Teton fault. We integrate these data with a displaced deglacial surface 4 km NE at Granite Canyon to calculate a postglacial to mid-Holocene (14.4−4.6 ka) slip rate of ∼1.1 mm/yr. Our analysis also suggests that the postglacial to early Holocene (14.4−9.9 ka) slip rate exceeds the Holocene (9.9−4.6 ka) rate by a factor of ∼2 (maximum of 3); however, a uniform rate for the fault is possible considering the 95% slip-rate errors. The ∼5 k.y. elapsed time since the last rupture of the southernmost Teton fault implies a current slip deficit of ∼4−5 m, which is possibly explained by spatially/temporally incomplete paleoseismic data, irregular earthquake recurrence, and/or variable per-event displacement. Our study emphasizes the importance of minimizing slip-rate uncertainties by integrating paleoseismic and geomorphic data sets and capturing multiple earthquake cycles.","language":"English","publisher":"Geological Society of America","doi":"10.1130/B35363.1","usgsCitation":"DuRoss, C., Gold, R.D., Briggs, R.W., Delano, J.E., Ostenaa, D.A., Zellman, M., Cholewinski, N., Wittke, S., and Mahan, S.A., 2019, Holocene earthquake history and slip rate of the southern Teton fault, Wyoming, USA: Geological Society of America Bulletin, v. 132, no. 7-8, p. 1566-1586, https://doi.org/10.1130/B35363.1.","productDescription":"21 p.","startPage":"1566","endPage":"1586","ipdsId":"IP-111318","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":370499,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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Seth","contributorId":221402,"corporation":false,"usgs":false,"family":"Wittke","given":"Seth","email":"","affiliations":[{"id":40366,"text":"Wyoming State Geological  Survey","active":true,"usgs":false}],"preferred":false,"id":778058,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Mahan, Shannon A. 0000-0001-5214-7774 smahan@usgs.gov","orcid":"https://orcid.org/0000-0001-5214-7774","contributorId":147159,"corporation":false,"usgs":true,"family":"Mahan","given":"Shannon","email":"smahan@usgs.gov","middleInitial":"A.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":778059,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70207991,"text":"70207991 - 2019 - Accumulating evidence in ecology: Once is not enough","interactions":[],"lastModifiedDate":"2020-01-23T06:32:34","indexId":"70207991","displayToPublicDate":"2019-11-21T06:31:34","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Accumulating evidence in ecology: Once is not enough","docAbstract":"Many published studies in ecological science are viewed as stand-alone investigations that purport to provide new insights into how ecological systems behave based on single analyses. But it is rare for results of single studies to provide definitive results, as evidenced in current discussions of the “reproducibility crisis” in science. The key step in science is the comparison of hypothesis-based predictions with observations, where the predictions are typically generated by hypothesis-specific models. Repeating this step allows us to gain confidence in the predictive ability of a model, and its corresponding hypothesis, and thus to accumulate evidence and eventually knowledge. This accumulation may occur via an ad hoc approach, via meta-analyses, or via a more systematic approach based on the anticipated evolution of an information state. We argue the merits of this latter approach, provide an example, and discuss implications for designing sequences of studies focused on a particular question. We conclude by discussing current data collection programs that are pre-adapted to use this approach and argue that expanded use would increase the rate of learning in ecology, as well as our confidence in what is learned.","language":"English","publisher":"Wiley","doi":"10.1002/ece3.5836","usgsCitation":"Nichols, J.D., Kendall, W., and Boomer, G., 2019, Accumulating evidence in ecology: Once is not enough: Ecology and Evolution, v. 9, no. 24, p. 13991-14004, https://doi.org/10.1002/ece3.5836.","productDescription":"14 p.","startPage":"13991","endPage":"14004","ipdsId":"IP-108580","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":459138,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.5836","text":"Publisher Index Page"},{"id":371489,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","issue":"24","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2019-11-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Nichols, James D. 0000-0002-7631-2890 jnichols@usgs.gov","orcid":"https://orcid.org/0000-0002-7631-2890","contributorId":200533,"corporation":false,"usgs":true,"family":"Nichols","given":"James","email":"jnichols@usgs.gov","middleInitial":"D.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":780056,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kendall, William 0000-0002-7632-3000","orcid":"https://orcid.org/0000-0002-7632-3000","contributorId":221720,"corporation":false,"usgs":true,"family":"Kendall","given":"William","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":780057,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Boomer, G.Scott","contributorId":221721,"corporation":false,"usgs":false,"family":"Boomer","given":"G.Scott","email":"","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":780058,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70215274,"text":"70215274 - 2019 - Creating figures in R that meet the AFS style guide: Standardization and supporting script","interactions":[],"lastModifiedDate":"2020-10-14T23:00:00.667232","indexId":"70215274","displayToPublicDate":"2019-11-20T17:59:45","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5686,"text":"Fisheries Magazine","active":true,"publicationSubtype":{"id":10}},"title":"Creating figures in R that meet the AFS style guide: Standardization and supporting script","docAbstract":"<p><span>Visual display of information in scientific and non‐scientific literature is the most efficient way to summarize large amounts data, focus the readers’ attention on patterns, and substantiate the message in the narrative. Figures often represent years of data collection and substantial monetary investment, and it is worth repeating the cliché “a [figure] is worth a thousand words.” Well‐designed figures are usually simple, yet their ability to relate complex information through simplicity makes them powerful (Tufte&nbsp;</span><span><a id=\"fsh10272-bib-0013R\" class=\"bibLink tab-link\" href=\"https://afspubs.onlinelibrary.wiley.com/doi/full/10.1002/fsh.10272#fsh10272-bib-0013\" data-tab=\"pane-pcw-references\" data-mce-href=\"https://afspubs.onlinelibrary.wiley.com/doi/full/10.1002/fsh.10272#fsh10272-bib-0013\">2001</a></span><span>). Figures are often the focal point of articles when scientists, science communicators, and policy makers are quickly searching for scientific information. Scientists in academia ranked figures and tables as the most important component of research articles (Hubbard and Dunbar&nbsp;</span><span><a id=\"fsh10272-bib-0005R\" class=\"bibLink tab-link\" href=\"https://afspubs.onlinelibrary.wiley.com/doi/full/10.1002/fsh.10272#fsh10272-bib-0005\" data-tab=\"pane-pcw-references\" data-mce-href=\"https://afspubs.onlinelibrary.wiley.com/doi/full/10.1002/fsh.10272#fsh10272-bib-0005\">2017</a></span><span>); moreover, figures quickly become the focus when discussing articles among colleagues or in a classroom setting. If created effectively in combination with a well‐articulated figure caption, figures convey complex information readily for the reader to make a conclusion about results without reading details presented in the narrative. This is especially important as the quantity of research articles continues to increase exponentially in the 21st century, as does the number of journals with specific figure guidelines (Jinha&nbsp;</span><span><a id=\"fsh10272-bib-0006R\" class=\"bibLink tab-link\" href=\"https://afspubs.onlinelibrary.wiley.com/doi/full/10.1002/fsh.10272#fsh10272-bib-0006\" data-tab=\"pane-pcw-references\" data-mce-href=\"https://afspubs.onlinelibrary.wiley.com/doi/full/10.1002/fsh.10272#fsh10272-bib-0006\">2010</a></span><span>).</span></p>","language":"English","publisher":"American Fisheries Society","doi":"10.1002/fsh.10272","usgsCitation":"Glassic, H., Heim, K.C., and Guy, C.S., 2019, Creating figures in R that meet the AFS style guide: Standardization and supporting script: Fisheries Magazine, v. 44, no. 11, p. 539-544, https://doi.org/10.1002/fsh.10272.","productDescription":"6 p.","startPage":"539","endPage":"544","ipdsId":"IP-099496","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":379394,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"44","issue":"11","noUsgsAuthors":false,"publicationDate":"2019-11-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Glassic, Hayley C.","contributorId":243051,"corporation":false,"usgs":false,"family":"Glassic","given":"Hayley C.","affiliations":[{"id":36244,"text":"MSU","active":true,"usgs":false}],"preferred":false,"id":801437,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Heim, Kurt C.","contributorId":138832,"corporation":false,"usgs":false,"family":"Heim","given":"Kurt","email":"","middleInitial":"C.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":801438,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Guy, Christopher S. 0000-0002-9936-4781 cguy@usgs.gov","orcid":"https://orcid.org/0000-0002-9936-4781","contributorId":2876,"corporation":false,"usgs":true,"family":"Guy","given":"Christopher","email":"cguy@usgs.gov","middleInitial":"S.","affiliations":[{"id":5062,"text":"Office of the Chief Scientist for Ecosystems","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":801439,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70207193,"text":"70207193 - 2019 - Using component ratios to detect metadata and instrument problems of seismic stations: Examples from 18 years of GEOSCOPE data","interactions":[],"lastModifiedDate":"2020-01-08T14:22:39","indexId":"70207193","displayToPublicDate":"2019-11-20T14:53:24","publicationYear":"2019","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":"Using component ratios to detect metadata and instrument problems of seismic stations: Examples from 18 years of GEOSCOPE data","docAbstract":"Replacement or deterioration of seismic instruments and the evolution of the installation conditions and sites can alter the seismic signal in very subtle ways, so it is notoriously difficult to monitor the signal quality of permanent seismic stations. We present a simple tool, energy ratios between each pair of the three recorded components, aimed at characterizing and monitoring signal quality, as a complement to existing methods. To calculate stable daily energy ratios over a large frequency range (0.01 Hz – 5 Hz), we use the daily median energy ratio over all 5-minute windows within the day. The method is applied to all GEOSCOPE stations, for continuous BH channel data collected since 2001. We show applications to identify past gain problems (stations ROCAM and CRZF), to provide feedback after field interventions at remote sites (Antarctic station DRV), and to shed light on complex instrument problems (stations ECH and KIP). Our results show that component energy ratios have excellent time resolution and that they are visually simple for identification of problems. They can be used both for ongoing continuous monitoring of the signal quality, or as a tool to identify past problems. The associated python codes are available on GitHub.","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220190180","usgsCitation":"Pedersen, H.A., Leroy, N., Zigone, D., Vallee, M., Ringler, A.T., and Wilson, D.C., 2019, Using component ratios to detect metadata and instrument problems of seismic stations: Examples from 18 years of GEOSCOPE data: Seismological Research Letters, v. 91, no. 1, p. 272-286, https://doi.org/10.1785/0220190180.","productDescription":"15 p.","startPage":"272","endPage":"286","ipdsId":"IP-112065","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":370182,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"91","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-11-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Pedersen, Helle A.","contributorId":221155,"corporation":false,"usgs":false,"family":"Pedersen","given":"Helle","email":"","middleInitial":"A.","affiliations":[{"id":40340,"text":"Univ. Grenoble Alpes, Univ. Savoie Mont Blanc, CNRS, IRD, IFSTTAR, ISTerre, 38000 Grenoble, France","active":true,"usgs":false}],"preferred":false,"id":777231,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Leroy, Nicolas","contributorId":221156,"corporation":false,"usgs":false,"family":"Leroy","given":"Nicolas","email":"","affiliations":[{"id":40341,"text":"Institut de Physique du Globe de Paris, Sorbonne Paris Cité, Université Paris Diderot, CNRS, France","active":true,"usgs":false}],"preferred":false,"id":777232,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zigone, Dimitri","contributorId":221157,"corporation":false,"usgs":false,"family":"Zigone","given":"Dimitri","email":"","affiliations":[{"id":40342,"text":"Institut de Physique du Globe de Strasbourg, UMR 7516, Université de Strasbourg/EOST, CNRS, Strasbourg, France","active":true,"usgs":false}],"preferred":false,"id":777233,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vallee, Martin","contributorId":221158,"corporation":false,"usgs":false,"family":"Vallee","given":"Martin","email":"","affiliations":[{"id":40341,"text":"Institut de Physique du Globe de Paris, Sorbonne Paris Cité, Université Paris Diderot, CNRS, France","active":true,"usgs":false}],"preferred":false,"id":777234,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ringler, Adam T. 0000-0002-9839-4188 aringler@usgs.gov","orcid":"https://orcid.org/0000-0002-9839-4188","contributorId":145576,"corporation":false,"usgs":true,"family":"Ringler","given":"Adam","email":"aringler@usgs.gov","middleInitial":"T.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":777235,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wilson, David C. 0000-0003-2582-5159 dwilson@usgs.gov","orcid":"https://orcid.org/0000-0003-2582-5159","contributorId":145580,"corporation":false,"usgs":true,"family":"Wilson","given":"David","email":"dwilson@usgs.gov","middleInitial":"C.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":777236,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
]}