Greater sage-grouse (Centrocercus urophasianus) are at the center of state and national land use policies largely because of their unique life-history traits as an ecological indicator for health of sagebrush ecosystems. This updated population trend analysis provides state and federal land and wildlife managers with best-available science to help guide current management and conservation plans aimed at benefitting sage-grouse populations. This analysis relied on previously published population trend modeling methodology from Coates and others (2021) and includes the addition of three analytical updates: (1) identification of population nadirs (lowest points within cycles) at the lek (breeding ground) and neighborhood cluster (group of leks) spatial scales, (2) truncation of prior distributions on rate of change in apparent abundance values to more realistic boundaries for leks with missing data, and (3) addition of 2 years of population lek count data (2020 and 2021) to the current dataset (1953–2021). Bayesian state-space models estimated 2.9 percent average annual decline in sage-grouse populations across their geographical range, which varied among subpopulations at the largest scale of analysis, termed climate clusters (2.2–4.6). Cumulative declines were 42.5, 65.6, and 80.1 percent range-wide across short (19 years), medium (35 years), and long (55 years) temporal periods, respectively. These results indicate that range-wide populations continued to decline during 2020 and 2021, although two climate clusters (eastern area and Bi-State area) have shown growth in population abundance in recent years, indicating they have surpassed a recent population abundance nadir.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/dr1165","issn":"2771-9448","collaboration":"Prepared in cooperation with the Western Association of Fish and Wildlife Agencies and the Bureau of Land Management","programNote":"Species Management Research Program","usgsCitation":"Coates, P.S., Prochazka, B.G., Aldridge, C.L., O'Donnell, M.S., Edmunds, D.R., Monroe, A.P., Hanser, S.E., Wiechman, L.A., and Chenaille, M.P., 2022, Range-wide population trend analysis for greater sage-grouse (Centrocercus urophasianus)—Updated 1960–2021: Data Report 1165, 16 p., https://doi.org/10.3133/dr1165.","productDescription":"Report: viii, 16 p.; Data Release","numberOfPages":"28","onlineOnly":"Y","ipdsId":"IP-144163","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":411225,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9OQWGIV","text":"U.S. Geological Survey data release","linkHelpText":"Trends and a targeted annual warning system for greater sage-grouse in the western United States (1960–2021)"},{"id":411222,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/dr/1165/dr1165.pdf","text":"Report","size":"8.95 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DR 1165"},{"id":411223,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/dr/1165/images"},{"id":411221,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/dr/1165/coverthb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.19101705712868,\n 48.89284566335482\n ],\n [\n -122.13131256755497,\n 48.37855671670232\n ],\n [\n -121.63700211579436,\n 47.85380781194411\n ],\n [\n -121.86067071873805,\n 47.51242609246373\n ],\n [\n -121.87668371107034,\n 47.11115078292244\n ],\n [\n -122.4532512741522,\n 46.70567448488106\n ],\n [\n -122.57397075207928,\n 46.22739431053469\n ],\n [\n -122.36606239056442,\n 45.90712886523926\n ],\n [\n -121.91588031540189,\n 45.358384504867246\n ],\n [\n -122.45322729336237,\n 44.953343420279765\n ],\n [\n -122.52983521148596,\n 44.52144457126775\n ],\n [\n -122.54530349941209,\n 44.259263341793\n ],\n [\n -122.85735468588939,\n 43.86827650155766\n ],\n [\n -123.01704364538307,\n 43.46272668287682\n ],\n [\n -123.01026119844099,\n 43.21452795313556\n ],\n [\n -123.10511846238558,\n 42.807780288627384\n ],\n [\n -122.77301525682884,\n 42.07884845828369\n ],\n [\n -122.62454526743153,\n 41.5133850817748\n ],\n [\n -122.14925905063672,\n 40.83036532174481\n ],\n [\n -121.68837858072334,\n 40.49667518946566\n ],\n [\n -121.57750448671058,\n 39.80789795232664\n ],\n [\n -121.16256808423407,\n 39.215880289775015\n ],\n [\n -120.64471039578123,\n 38.57511631320122\n ],\n [\n -119.84212022937817,\n 37.43985090599355\n ],\n [\n -118.83488568782542,\n 36.55782111752346\n ],\n [\n -118.59349323888452,\n 35.83229168807691\n ],\n [\n -117.40450808029976,\n 35.69535862053445\n ],\n [\n -116.43105077565428,\n 35.459239916109155\n ],\n [\n -114.6229823251931,\n 35.413666627683824\n ],\n [\n -96.18756245429773,\n 35.03931170375198\n ],\n [\n -94.57905716272413,\n 37.1225590274522\n ],\n [\n -94.53555587839759,\n 39.07884303955356\n ],\n [\n -95.83917624651616,\n 40.61806593890233\n ],\n [\n -96.37123578579417,\n 42.39205565405334\n ],\n [\n -96.46625839716233,\n 45.31077773932529\n ],\n [\n -97.30155203348903,\n 48.980368873698694\n ],\n [\n -122.19101705712868,\n 48.89284566335482\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Western Ecological Research Center
U.S. Geological Survey
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Sacramento, California 95819
https://www.usgs.gov/centers/werc
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Understanding what drives changes in wildlife demography is fundamental to the conservation and management of depleted or declining populations, though making inference about the intrinsic and extrinsic factors that influence survival and reproduction remains challenging. Here we use mark–resight data from 2000 to 2018 to examine the effects of environmental variability on age-specific survival and natality for the endangered western distinct population segment (wDPS) of Steller sea lions (Eumetopias jubatus) in Alaska, USA. Though this population has been studied extensively over the last four decades, the causes of divergent abundance trends that have been observed across the wDPS range remain unknown. We developed a Bayesian multievent mark–resight model that accounts for female reproductive state uncertainty. Annual survival probabilities for male pups (0.44; 0.36–0.53), female yearlings (0.63; 0.49–0.73), and male yearlings (0.62; 0.51–0.71) born in the western portion of the wDPS range, estimated here for the first time, were lower than those in the eastern portion of the wDPS range, estimated as: male pups (0.69; 0.65–0.74), female yearlings (0.76; 0.71–0.81), and male yearlings (0.71; 0.65–0.78). There was a higher proportion of young female breeders in the western portion of the range, but overall natality was lower (0.69; 0.47–0.96) than in the eastern portion of the range (0.80; 0.74–0.84). Additionally, pup mass had a positive effect on pup survival in the eastern portion of the range and a negative effect in the western portion of the range, potentially due to earlier weaning of heavier pups. Local- and basin-scale oceanographic features such as the Aleutian Low, the Arctic Oscillation Index, the North Pacific Gyre Oscillation, chlorophyll concentration, upwelling, and wind in certain seasons were correlated with vital rates. However, drawing strong inferences from these correlations is challenging given that relationships between ocean conditions and an adaptive top predator in a dynamic ecosystem are exceedingly complex. This study provides the first demographic rate estimates for the western portion of the range where abundance estimates continue to decline. These results will advance efforts to identify factors driving regionally divergent abundance trends, with implications for population-level responses to future climate variability.
Population models often require detailed information on sex-, age-, or size-specific abundances, but population monitoring programs cannot always acquire data at the desired resolution. Thus, state uncertainty in monitoring data can potentially limit the demographic resolution of management decisions, which may be particularly problematic for stage- or size-structured species subject to consumptive use. American alligators (Alligator mississippiensis; hereafter alligator) have a complex life history characterized by delayed maturity and slow somatic growth, which makes the species particularly sensitive to overharvest. Though alligator populations are subject to recreational harvest throughout their range, the most widely used monitoring method (nightlight surveys) is often unable to obtain size class-specific counts, which limits the ability of managers to evaluate the effects of harvest policies. We constructed a Bayesian integrated population model (IPM) for alligators in Georgetown County, SC, USA, using records of mark–recapture–recovery, clutch size, harvest, and nightlight survey counts collected locally, and auxiliary information on fecundity, sex ratio, and somatic growth from other studies. We created a multistate mark–recapture–recovery model with six size classes to estimate survival probability, and we linked it to a state-space count model to derive estimates of size class-specific detection probability and abundance. Because we worked from a count dataset in which 60% of the original observations were of unknown size, we treated size class as a latent property of detections and developed a novel observation model to make use of information where size could be partly observed. Detection probability was positively associated with alligator size and water temperature, and negatively influenced by water level. Survival probability was lowest in the smallest size class but was relatively similar among the other five size classes (>0.90 for each). While the two nightlight survey count sites exhibited relatively stable population trends, we detected substantially different patterns in size class-specific abundance and trends between each site, including 30%–50% declines in the largest size classes at the site with greater harvest pressure. Here, we illustrate the use of IPMs to produce high-resolution output of latent population structure that is partially observed during the monitoring process.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.4321","usgsCitation":"Lawson, A.J., Jodice, P.G., Rainwater, T., Dunham, K.D., Hart, M., Butfiloski, J.W., Wilkinson, P., and Moore, C., 2022, Hidden in plain sight: Integrated population models to resolve partially observable latent population structure: Ecosphere, v. 13, e4321, 22 p., https://doi.org/10.1002/ecs2.4321.","productDescription":"e4321, 22 p.","ipdsId":"IP-137983","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":445620,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.4321","text":"Publisher Index Page"},{"id":430217,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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University","active":true,"usgs":false}],"preferred":false,"id":903451,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dunham, Kylee Denise 0000-0002-9249-0590","orcid":"https://orcid.org/0000-0002-9249-0590","contributorId":296991,"corporation":false,"usgs":true,"family":"Dunham","given":"Kylee","email":"","middleInitial":"Denise","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":903452,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hart, Morgan","contributorId":338673,"corporation":false,"usgs":false,"family":"Hart","given":"Morgan","email":"","affiliations":[{"id":35670,"text":"South Carolina Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":903453,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Butfiloski, Joseph W.","contributorId":338675,"corporation":false,"usgs":false,"family":"Butfiloski","given":"Joseph","email":"","middleInitial":"W.","affiliations":[{"id":35670,"text":"South Carolina Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":903454,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wilkinson, Philip M.","contributorId":338676,"corporation":false,"usgs":false,"family":"Wilkinson","given":"Philip M.","affiliations":[{"id":54598,"text":"Tom Yawkey Wildlife Center","active":true,"usgs":false}],"preferred":false,"id":903455,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Moore, Clinton 0000-0001-7782-3994 cmoore@usgs.gov","orcid":"https://orcid.org/0000-0001-7782-3994","contributorId":338679,"corporation":false,"usgs":true,"family":"Moore","given":"Clinton","email":"cmoore@usgs.gov","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":903456,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70239065,"text":"ofr20221119 - 2022 - Hydrologic effects of leakage from the Catskill Aqueduct on the bedrock-aquifer system near High Falls, New York, November 2019–January 2020","interactions":[],"lastModifiedDate":"2026-03-30T20:55:17.842923","indexId":"ofr20221119","displayToPublicDate":"2022-12-27T14:00:00","publicationYear":"2022","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":"2022-1119","displayTitle":"Hydrologic Effects of Leakage from the Catskill Aqueduct on the Bedrock-Aquifer System near High Falls, New York, November 2019–January 2020","title":"Hydrologic effects of leakage from the Catskill Aqueduct on the bedrock-aquifer system near High Falls, New York, November 2019–January 2020","docAbstract":"Historical observations by the New York City Department of Environmental Protection (NYCDEP) indicate that the Rondout pressure tunnel has been leaking in the vicinity of the hamlet of High Falls, New York. In the 74 days from November 11, 2019, to January 23, 2020, NYCDEP shut down and partially dewatered the pressure tunnel for inspection and repairs. On November 5–7, 2019 (during normal tunnel operations), and on January 21–22, 2020 (when the tunnel was shut down), the U.S. Geological Survey used a network of 31 groundwater wells to collect water-level elevations and determine the potentiometric surface of the bedrock aquifer adjacent to the Rondout pressure tunnel. When the tunnel was fully pressurized during normal operations, water levels indicated a two-mile-long groundwater mound which trended northeastward, approximately along the regional strike of the bedrock units. The mound ranged in elevation from 250 to 300 feet (ft) above the North American Vertical Datum of 1988 and extended from 1,500 ft southwest of a suspected leak at the Rondout pressure tunnel to about 8,500 ft northeast of the possible leak. During the 74-day shutdown, during which the aqueduct was nonoperational, this groundwater mound decreased in magnitude and extent as it reverted to equilibrium conditions. This resulted in a flattening of the potentiometric surface, represented by two remnant groundwater plateaus.
Water-level differences were calculated for wells that may be affected by potential tunnel leakage to determine the influence on the local bedrock aquifer. The five largest water-level differences (77, 61, 49, 42, and 41 ft) occurred in wells that were generally aligned with the northeastward trend of regional bedrock strike; these wells may penetrate the karstic Helderberg Group bedrock unit. Near the suspected tunnel leak, the Helderberg Group overlies the Binnewater Sandstone and the High Falls Shale, both of which produced substantial groundwater inflows during the construction of the Rondout pressure tunnel. Water levels in wells penetrating the Shawangunk Formation just east of Rondout Creek, where the unit is in contact with the High Falls Shale, and in wells penetrating the Esopus Shale, which is adjacent to the Helderberg Group and northwest of the tunnel leak, may be affected by tunnel leakage. It is unclear if water levels in a well 9,000 ft northwest of the suspected tunnel leak are influenced by the tunnel leakage, by another source of artificial recharge, or by both. This well penetrates the Onondaga Limestone in the northwestern part of the study area. An unconsolidated aquifer composed of stratified gravel, sand, silt, and clay overlies the limestone bedrock in this part of study area―additional study is required to determine if this unconsolidated aquifer is affected by tunnel leakage.
Robert Francis Breault, Center Director
New York Water Science Center
U.S. Geological Survey
425 Jordan Road
Troy, NY 12180-8349
The U.S. Geological Survey (USGS) completed an assessment in 2007 of the undiscovered, technically recoverable, continuous gas potential of Cretaceous–Tertiary coal beds of the onshore areas and State waters of the northern Gulf of Mexico Coastal Plain. The assessment was based on geologic elements including hydrocarbon source rocks, availability of suitable reservoir rocks, and hydrocarbon accumulations in three coalbed gas total petroleum systems (TPSs) identified in the region: (1) the Olmos Coalbed Gas TPS (Upper Cretaceous), (2) the Wilcox Coalbed Gas TPS (Paleocene–Eocene), and (3) the Cretaceous-Tertiary Coalbed Gas TPS. Four continuous assessment units (AUs) were defined within these three TPSs: (1) the Cretaceous Olmos Coalbed Gas AU, (2) the Rio Escondido Basin Olmos Coalbed Gas AU, (3) the Wilcox Coalbed Gas AU, and (4) the Cretaceous-Tertiary Coalbed Gas AU, which was not quantitatively assessed and which includes all other Cretaceous and Tertiary coal beds that are not included in the other AUs.
This USGS assessment estimated a mean of 4.06 trillion cubic feet of undiscovered, technically recoverable, continuous coalbed gas resources in the four AUs that were assessed. Nearly all of the undiscovered continuous gas resources that were estimated (95 percent, or 3.86 trillion cubic feet of gas [TCFG]) were in the Wilcox Coalbed Gas AU. The continuous gas resources resided in coalbed reservoirs. Gas sourced from these coal beds may also occur as conventional accumulations in adjacent or interlayered sandstones that were not included in this assessment of continuous resources. The assessment was conducted via the established USGS methodology for continuous petroleum accumulations and reflects estimates of undiscovered resources based on vertical (nonhorizontal) drilling technology.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171167","usgsCitation":"Warwick, P.D., 2022, Geologic assessment of undiscovered gas resources in Cretaceous–Tertiary coal beds of the U.S. Gulf of Mexico Coastal Plain: U.S. Geological Survey Open-File Report 2017–1167, 52 p., https://doi.org/10.3133/ofr20171167.","productDescription":"Report: vi, 52 p.; 3 Appendixes","numberOfPages":"52","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-017257","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":501520,"rank":10,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113996.htm","linkFileType":{"id":5,"text":"html"}},{"id":410558,"rank":9,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.er.usgs.gov/publication/ofr20171111","text":"Open-File Report 2017–1111","linkHelpText":"- Geologic assessment of undiscovered conventional oil and gas resources in the Lower Paleogene Midway and Wilcox Groups, and the Carrizo Sand of the Claiborne Group, of the Northern Gulf coast region"},{"id":410555,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2017/1167/ofr20171167_appendix1.pdf","text":"Appendix 1","size":"165 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Input Data Form for the Cretaceous Olmos Coalbed Gas Assessment Unit (50470281)"},{"id":410985,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/ofr20171167/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2017-1167"},{"id":410553,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1167/ofr20171167.pdf","text":"Report","size":"15.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1167"},{"id":410552,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1167/coverthb.jpg"},{"id":409355,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2017/1167/ofr20171167.XML"},{"id":409356,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2017/1167/images/"},{"id":410556,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2017/1167/ofr20171167_appendix2.pdf","text":"Appendix 2","size":"161 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Input Data Form for the Rio Escondido Basin Olmos Coalbed Gas Assessment Unit (53000281)"},{"id":410557,"rank":8,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2017/1167/ofr20171167_appendix3.pdf","text":"Appendix 3","size":"168 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Input Data Form for the Wilcox Coalbed Gas Assessment Unit (50470381)"}],"country":"United States","otherGeospatial":"U.S. Gulf of Mexico Coastal Plain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -99.32775336731807,\n 26.212616580411137\n ],\n [\n -81.93279691237665,\n 26.212616580411137\n ],\n [\n -81.3178237043738,\n 38.82626189520937\n ],\n [\n -99.67916662903421,\n 38.491360932976605\n ],\n [\n -102.44654606504763,\n 38.43753817164347\n ],\n [\n -102.40261940733356,\n 36.63809827557699\n ],\n [\n -102.4904727227622,\n 31.785348237738653\n ],\n [\n -99.32775336731807,\n 26.212616580411137\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Program Coordinator, Energy Resources Program
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The U.S. Geological Survey, in cooperation with the U.S. Air Force Civil Engineer Center, used surface-geophysical methods to delineate the top of Cretaceous Pierre Shale along survey transects in selected areas east and southeast of Ellsworth Air Force Base, South Dakota, from April to September 2021. Two complementary geophysical methods—electrical resistivity and passive seismic—were used along 21 colocated transect surveys east and southeast of Ellsworth Air Force Base for a total of 24.7 line-kilometers. Electrical resistivity results were analyzed using EarthImager2D electrical resistivity tomography processing and inversion software. Two-dimensional earth models showing the electrical properties of the subsurface were evaluated by directly comparing the high and low subsurface resistivity values to a surficial-geologic map and nearby wells with drillers logs. Passive seismic data were analyzed using the horizontal-to-vertical spectral ratio method to determine the depth to the Cretaceous Pierre Shale at each survey point. The depth to the Pierre Shale along the transects ranged from 0.0 to about 19.8 meters, and the mean and median depths were about 6.1 and 5.6 meters, respectively. The elevation of the Pierre Shale and thickness of unconsolidated deposits generally increased with land-surface elevation from south to north; however, some transects displayed topographically high and low areas that did not correlate with land-surface topography.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3497","collaboration":"Prepared in cooperation with the U.S. Air Force Civil Engineer Center","usgsCitation":"Medler, C.J., 2022, Delineating the Pierre Shale from geophysical surveys east and southeast of Ellsworth Air Force Base, South Dakota, 2021: U.S. Geological Survey Scientific Investigations Map 3497, 3 sheets, 15-p. pamphlet, https://doi.org/10.3133/sim3497.","productDescription":"Report: vi, 15 p.; 3 Sheets: 64.00 × 53.33 inches or smaller; Data Release","numberOfPages":"24","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-137098","costCenters":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":501938,"rank":10,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113997.htm","linkFileType":{"id":5,"text":"html"}},{"id":410625,"rank":7,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3497/sim3497_sheet03.pdf","text":"Sheet 3","size":"16.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3497, sheet 3","linkHelpText":"—Depth to Pierre Shale from Electrical Resistivity Tomography Inversion and Horizontal-to-Vertical Spectral Ratio Results for Transects 4A, 4B, 4D, 4E, 4FD3, 4FD4, 4FD5, 4G, 4H, and 5, Ellsworth Air Force Base, South Dakota"},{"id":410609,"rank":6,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3497/sim3497_sheet02.pdf","text":"Sheet 2","size":"14.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3497, sheet 2","linkHelpText":"—Depth to Pierre Shale from Electrical Resistivity Tomography Inversion and Horizontal-to-Vertical Spectral Ratio Results for Transects 2, 3A, 3B, 3D, 3E, and 3F, Ellsworth Air Force Base, South Dakota"},{"id":410608,"rank":5,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3497/sim3497_sheet01.pdf","text":"Sheet 1","size":"16.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3497, sheet 1","linkHelpText":"—Depth to Pierre Shale from Electrical Resistivity Tomography Inversion and Horizontal-to-Vertical Spectral Ratio Results for Transects 1A, 1C, 1D, 4F Alternate 1, and 4F Alternate 2, Ellsworth Air Force Base, South Dakota"},{"id":410607,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sim/3497/images"},{"id":410606,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sim/3497/sim3497.XML"},{"id":410605,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3497/sim3497.pdf","text":"Report","size":"8.72 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3497"},{"id":410604,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3497/coverthb.jpg"},{"id":410698,"rank":9,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sim3497/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":410626,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9X57BS0","text":"USGS data release","linkHelpText":"Electrical resistivity tomography (ERT) and horizontal-to-vertical spectral ratio (HVSR) data collected East and Southeast of Ellsworth Air Force Base, South Dakota, in 2021"}],"country":"United States","state":"South Dakota","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -103.08,\n 44.06\n ],\n [\n -102.84286176348763,\n 44.06\n ],\n [\n -102.84286176348763,\n 44.2\n ],\n [\n -103.08,\n 44.2\n ],\n [\n -103.08,\n 44.06\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Dakota Water Science Center
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New zircon U-Pb ages for the Alabama Hills Granite in Owens Valley, eastern California, range from 103 to 102 Ma, nearly 20 Ma older than previously published zircon ages. The data preclude previously implied links between the pluton and the adjacent Late Cretaceous Mount Whitney Intrusive Suite. Geochronologic and isotopic data indicate a connection between the Alabama Hills Granite and leucogranites to the northwest on the Sierra Nevada crest, as well as a pluton to the southeast in the Coso Range. We refer to these units as the Kearsarge plutons. The suite was intruded from 103 to 100.5 Ma with
Rare plant species that are constrained by shading may be threatened by a lack of natural disturbance that removes overhanging vegetation. The original distribution of the study species Physostegia correllii (Lundell) Shinners included freshwater floodplains of large rivers in the southcentral U.S. (Colorado, Rio Grande, and Mississippi rivers). A second species, Trillium texanum Buckley was found in seep spring baygalls in east-central Texas and extreme northwestern Louisiana. Experiments to determine the effects of shading on P. correllii and T. texanum were conducted using short-term shade cloth treatments (full sunlight vs. 30% shading for 2–3 weeks), and a dryness treatment for T. texanum (moist vs. less moist). Mean height and cover responses of individuals for both species were determined in conservation gardens located in Lafayette, Louisiana. Physostegia correllii grown in shaded environments for 2.5 weeks had shorter mean height than if grown in full sunlight. Half of the shaded plants in shaded plots had died by the mid-summer. For T. texanum, shading reduced the mean height and cover of plants. Therefore, management to remove overhanging ground vegetation to mimic natural disturbance might revive P. correllii and/or T. texanum populations where overhanging vegetation is increasing due to lack of natural disturbance (e.g., flood pulsing, grazing, burning).
","language":"English","publisher":"Botanical Research Institute of Texas","doi":"10.17348/jbrit.v16.i2.1270","usgsCitation":"Middleton, B., Williams, C.R., Doffitt, C., and Johnson, D., 2022, Effects of shading on the rare plant species, Physostegia correllii (Lamiaceae) and Trillium texanum (Melanthiaceae): Journal of the Botanical Research Institute of Texas, v. 16, no. 2, p. 591-603, https://doi.org/10.17348/jbrit.v16.i2.1270.","productDescription":"13 p.; 2 Data Releases","startPage":"591","endPage":"603","ipdsId":"IP-133104","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":445669,"rank":4,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.17348/jbrit.v16.i2.1270","text":"Publisher Index Page"},{"id":410472,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":414828,"rank":3,"type":{"id":30,"text":"Data 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However, quantifying the temporal vertical and spatial extent, is challenging due to the paucity of evidence in the geological record. Here, we utilize dense seismic and well data covering the intersection of the Great Meteor Hotspot (GMH) track with the U.S. Atlantic continental margin to constrain the surface expression of the hotspot passage under the lithosphere. The continuous sedimentary record of the eastern North American margin during its passage over the hotspot allows determination of the timing, magnitude, width and rate of denudation. We find that a ∼300 km wide region was denuded by up to 850 m between ∼97 and 86 Ma, ∼10 m.y. after the passage of the GMH. Stratigraphic relationships suggest a decaying rock uplift rate with time and no subsequent sagging. The broad, long-lasting, and delayed uplift was modeled as a surface manifestation of either sub-lithospheric mantle depletion, permanently eroded base of the continental lithosphere, or intrusions of depleted magma. We consider sub-lithospheric depletion to be the most likely cause, based on seismic imaging results.
The tectonic domains of Basin and Range extension, Cascadia subduction zone contraction, and Walker Lane dextral transtension converge in the Mushroom Rock region of northeastern California, USA. We combined analysis of high-resolution topographic data, bedrock mapping, 40Ar/39Ar geochronology, low-temperature thermochronology, and existing geologic and fault mapping to characterize an extensive dextral-normal-oblique fault system called the Pondosa fault zone. This fault zone extends north-northwest from the Pit River east of Soldier Mountain, California, into moderately high-relief volcanic topography as far north as the Bartle (California) townsite with normal and dextral offset apparent in geomorphology and fault exposures. New and existing 40Ar/39Ar and radiocarbon dating of offset lava flows provides ages of 12.4 ka to 9.6 Ma for late Cenozoic stratigraphic units. Scarp morphology and geomorphic expression indicate that the fault system was active in the late Pleistocene. The Pondosa fault zone may represent a dextral-oblique accommodation zone between north-south–oriented Basin and Range extensional fault systems and/or part of the Sierra Nevada–Oregon Coast block microplate boundary.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES02450.1","usgsCitation":"Jobe, J.A., Briggs, R.W., Gold, R.D., DeLong, S.B., Hille, M., Delano, J., Johnstone, S., Pickering, A., Phillips, R., and Calvert, A.T., 2022, The Pondosa fault zone: A distributed dextral-normal-oblique fault system in northeastern California, USA: Geosphere, v. 19, no. 1, p. 179-205, https://doi.org/10.1130/GES02450.1.","productDescription":"27 p.","startPage":"179","endPage":"205","ipdsId":"IP-137700","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":492497,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges02450.1","text":"Publisher Index Page"},{"id":492284,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"eastern California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.27831636230019,\n 41.12301709043055\n ],\n [\n -122.27831636230019,\n 39.963081252129996\n ],\n [\n -120.53795346715106,\n 39.963081252129996\n ],\n [\n -120.53795346715106,\n 41.12301709043055\n ],\n [\n -122.27831636230019,\n 41.12301709043055\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"19","issue":"1","noUsgsAuthors":false,"publicationDate":"2022-12-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Jobe, Jessica Ann Thompson 0000-0001-5574-4523","orcid":"https://orcid.org/0000-0001-5574-4523","contributorId":295377,"corporation":false,"usgs":true,"family":"Jobe","given":"Jessica","email":"","middleInitial":"Ann Thompson","affiliations":[{"id":300,"text":"Geologic Hazards Science 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0000-0002-0945-2172 sdelong@usgs.gov","orcid":"https://orcid.org/0000-0002-0945-2172","contributorId":5240,"corporation":false,"usgs":true,"family":"DeLong","given":"Stephen","email":"sdelong@usgs.gov","middleInitial":"B.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":943091,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hille, Madeline 0000-0001-7240-8214","orcid":"https://orcid.org/0000-0001-7240-8214","contributorId":315582,"corporation":false,"usgs":false,"family":"Hille","given":"Madeline","email":"","affiliations":[{"id":37387,"text":"University of Michigan","active":true,"usgs":false}],"preferred":false,"id":943092,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Delano, Jaime 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resolved rates of land subsidence, thus new constraints on vertical land motions (VLM) in the region are warranted. In this paper, we provide a description of two campaign-style Global Positioning System (GPS) datasets, explain the methods used in data collection and validation, and present the experiment designed to quantify a new baseline of VLM in the Chesapeake Bay region of eastern North America. Data from GPS campaigns in 2019 and 2020 are presented as ASCII RINEX2.11 files and logsheets for each observation from the campaigns. Data were quality checked using the open-source program TEQC, resulting in average multipath 1 and 2 values of 0.68 and 0.57, respectively. All data are archived and publicly available for open access at the geodesy facility UNAVCO to abide by Findable, Accessible, Interoperable, Reusable (FAIR) data principles.
","language":"English","publisher":"Nature","doi":"10.1038/s41597-022-01864-8","usgsCitation":"Troia, G., Stamps, S., Lotspeich, R., Duda, J.M., McCoy, K., Moore, W., Hensel, P., Hippenstiel, R., McKenna, T., Andreasen, D.C., Geoghegan, C., Ulizo, T.P., Kronebusch, M., Carr, J., Walters, D., and Winn, N., 2022, GPS data from 2019 and 2020 campaigns in the Chesapeake Bay region towards quantifying vertical land motions: Scientific Data, v. 9, no. 1, 744, 9 p., https://doi.org/10.1038/s41597-022-01864-8.","productDescription":"744, 9 p.","ipdsId":"IP-122566","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":37759,"text":"VA/WV Water Science Center","active":true,"usgs":true}],"links":[{"id":445723,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41597-022-01864-8","text":"Publisher Index Page"},{"id":410538,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Chesapeake Bay area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -77.29568067904435,\n 40.12967557474843\n ],\n [\n -77.29568067904435,\n 36.768971760646394\n ],\n [\n -75.43832592966815,\n 36.768971760646394\n ],\n [\n -75.43832592966815,\n 40.12967557474843\n ],\n [\n -77.29568067904435,\n 40.12967557474843\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"9","issue":"1","noUsgsAuthors":false,"publicationDate":"2022-12-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Troia, Gabrielle 0000-0001-6566-4623","orcid":"https://orcid.org/0000-0001-6566-4623","contributorId":299921,"corporation":false,"usgs":false,"family":"Troia","given":"Gabrielle","email":"","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":859036,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stamps, Sarah 0000-0002-3531-1752","orcid":"https://orcid.org/0000-0002-3531-1752","contributorId":299923,"corporation":false,"usgs":false,"family":"Stamps","given":"Sarah","email":"","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":859037,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lotspeich, R. 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Some of these changes may disproportionally affect birds that rely on gap dynamics or other forest canopy disturbances to create understory habitat. The Canada Warbler (Cardellina canadensis) is one such understory specialist that has undergone consistent declines. We assessed environmental and interspecific factors associated with Canada Warbler space use in its southern breeding distribution to understand potential causes of population declines and inform conservation efforts. We evaluated Canada Warbler occupancy from 840 point count surveys conducted in 2017 and 2018 at 470 unique locations (79% of locations surveyed in both years) throughout Monongahela National Forest, West Virginia, USA. We modeled Canada Warbler occupancy probability as a function of environmental variables and included Black-throated Blue Warbler (Setophaga caerulescens) and Hermit Thrush (Catharus guttatus) as interacting species because all three species exhibit similar habitat preferences. Canada Warblers were most likely to occur in areas with rhododendron (Rhododendron maximum) density > 0.27 stems/m² and within 3 m of riparian areas (streams and wetlands). They were also more likely to occur in mid-elevation (highest occupancy at 930 m) northern hardwood forests when Black-throated Blue Warblers were also present. Black-throated Blue Warblers were most likely to occupy mid-elevation sites with high shrub density, whereas Hermit Thrushes were more likely to occupy high-elevation, old-age forests. Potential management actions could focus on conserving riparian areas in northern hardwood forests, especially those with dense rhododendron thickets. Such potential actions could also be beneficial across the entire elevation range we explored within the region (500–1300 m). Canada Warblers may be benefiting from the recent spread of rhododendron habitats and northern hardwood forest types within West Virginia.
","language":"English","publisher":"Resilience Alliance Publications","doi":"10.5751/ace-02079-170120","usgsCitation":"Dimmig, G., Rota, C., Wood, P.B., and Lituma, C., 2022, Understory structure and heterospecifics influence the occupancy of a ground-nesting species of conservation concern, the Canada Warbler: Avian Conservation and Ecology, v. 17, no. 1, 20, 16 p., https://doi.org/10.5751/ace-02079-170120.","productDescription":"20, 16 p.","ipdsId":"IP-123270","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":487031,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5751/ace-02079-170120","text":"Publisher Index Page"},{"id":481747,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United sTates","state":"West Virginia","otherGeospatial":"Monongahela National Forest","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -80.58889045378262,\n 37.463537077379684\n ],\n [\n -80.3485425975682,\n 37.51121532612136\n ],\n [\n -79.62749902892529,\n 38.552413228981266\n ],\n [\n -79.33707870266615,\n 38.442685588318085\n ],\n [\n -78.8463684962287,\n 39.0674460432719\n ],\n [\n -79.48729611280025,\n 39.1995023289459\n ],\n [\n -79.48729611280025,\n 39.455139390658985\n ],\n [\n -79.8978903671664,\n 39.37777230668391\n ],\n [\n -81.23983256436323,\n 37.88364086385796\n ],\n [\n -81.01951369616684,\n 37.54298391685913\n ],\n [\n -80.58889045378262,\n 37.463537077379684\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"17","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Dimmig, Gordon W.","contributorId":350556,"corporation":false,"usgs":false,"family":"Dimmig","given":"Gordon W.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":926339,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rota, Christopher T.","contributorId":350557,"corporation":false,"usgs":false,"family":"Rota","given":"Christopher T.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":926340,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wood, Petra B. 0000-0002-8575-1705 pbwood@usgs.gov","orcid":"https://orcid.org/0000-0002-8575-1705","contributorId":199090,"corporation":false,"usgs":true,"family":"Wood","given":"Petra","email":"pbwood@usgs.gov","middleInitial":"B.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":926338,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lituma, Christopher M.","contributorId":350558,"corporation":false,"usgs":false,"family":"Lituma","given":"Christopher M.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":926341,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70237132,"text":"70237132 - 2022 - Soils","interactions":[],"lastModifiedDate":"2023-01-13T15:59:55.675314","indexId":"70237132","displayToPublicDate":"2022-12-01T09:52:33","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"chapter":"V","title":"Soils","docAbstract":"Soils play a strong role in determining how New Mexico’s diverse landscapes will respond to climate change. Soil cover acts like a sponge, holding in water that falls as rain or snow. The presence of soil supports vegetation, and substantially reduces runoff and erosion. Soil enhances other processes such as infiltration of water and aquifer recharge. Soils can be damaged by a warming climate. Loss of vegetation in the Northwest High Desert and Eastern Plains, where soils are not well developed and easily damaged, will lead to dustier conditions in much of the state. On mountain hillslopes, the loss of vegetation cover in response to ongoing climate change will increase soil erosion, which then increases hillslope runoff. This, in turn, causes additional increases in soil erosion and bedrock exposure, which can largely prevent widespread recolonization by most plants, including trees. Soils on mountain hillslopes that face south, which are typically hotter and drier, will be damaged sooner by a warming climate than those on generally north-facing hillslopes that are slightly cooler and moister. Soils take many thousands of years to form, so these hillslopes will increasingly support sparse forests, or, in some circumstances, be entirely deforested. These changes are already well underway in some mountains in New Mexico.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Climate change in New Mexico over the next 50 years: Impacts on water resources (Bulletin 164)","largerWorkSubtype":{"id":2,"text":"State or Local Government Series"},"language":"English","publisher":"New Mexico Bureau of Geology and Mineral Resources","usgsCitation":"McFadden, L.D., Tillery, A.C., and Allen, C., 2022, Soils, 14 p.","productDescription":"14 p.","startPage":"55","endPage":"68","ipdsId":"IP-136194","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":411866,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":411863,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://geoinfo.nmt.edu/publications/monographs/bulletins/164/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"New 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Mexico\",\"nation\":\"USA \"}}]}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"McFadden, Leslie D.","contributorId":139971,"corporation":false,"usgs":false,"family":"McFadden","given":"Leslie","email":"","middleInitial":"D.","affiliations":[{"id":13339,"text":"University of New Mexico, Albuquerque","active":true,"usgs":false}],"preferred":false,"id":853424,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tillery, Anne C. 0000-0002-9508-7908 atillery@usgs.gov","orcid":"https://orcid.org/0000-0002-9508-7908","contributorId":2549,"corporation":false,"usgs":true,"family":"Tillery","given":"Anne","email":"atillery@usgs.gov","middleInitial":"C.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":853423,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Allen, Craig 0000-0002-8777-5989","orcid":"https://orcid.org/0000-0002-8777-5989","contributorId":297137,"corporation":false,"usgs":false,"family":"Allen","given":"Craig","affiliations":[{"id":36307,"text":"University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":853425,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70230030,"text":"70230030 - 2022 - Geologic setting and geomorphic history of La Botica and surrounding area","interactions":[],"lastModifiedDate":"2026-03-18T14:06:14.010431","indexId":"70230030","displayToPublicDate":"2022-12-01T08:54:09","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":3,"text":"Organization Series"},"seriesTitle":{"id":23617,"text":"Research Contributions","active":true,"publicationSubtype":{"id":3}},"seriesNumber":"115","title":"Geologic setting and geomorphic history of La Botica and surrounding area","docAbstract":"La Botica is located on the gently east-dipping marginal area between the high San Juan Mountains to the west and the San Luis Basin to the east in south-central Colorado. The site is positioned on a topographic bench perched about 70 to 80 m above La Jara Creek (figure 2.1), a tributary to the Rio Grande. The unique floral assemblage at La Botica has resulted in intermittent occupation over the last several thousand years. The physical environment supporting this assemblage is a result of Quaternary surface processes that have modified the underlying Tertiary bedrock. Underlying bedrock at the site consists of Oligocene to Pliocene volcanic and sedimentary deposits related to the Rio Grande rift and the San Juan volcanic locus of the Southern Rocky Mountains volcanic field. Local bedrock is mildly deformed by normal faulting and eastward tilting due to the onset of Oligocene extensional deformation and initial formation of the San Luis Basin. The geomorphic evolution and incision history of La Jara Creek are directly linked to middle to late Pleistocene evolution of the Rio Grande and to regional alpine glacial cycles over the last 500 k.y. (thousand years). Subsequent degradation of surrounding bedrock and development of mass-wasting deposits, such as landslides and talus slopes, have strongly influenced the incision history of La Jara Creek and the local environment at La Botica. In addition, local talus slopes and blockfields can host processes that actively modify the local environment, and these processes may have contributed to establishment of the floral assemblage.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Multidisciplinary research at the La Botica site, Conjeos County, Colorado","largerWorkSubtype":{"id":3,"text":"Organization Series"},"language":"English","publisher":"Paleocultural Research Group","usgsCitation":"Turner, K.J., Ruleman, C.A., and Mahan, S.A., 2022, Geologic setting and geomorphic history of La Botica and surrounding area: Research Contributions 115, 20 p.","productDescription":"20 p.","startPage":"9","endPage":"28","ipdsId":"IP-123501","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":501237,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":501236,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://paleocultural.org/Research/la-botica/"}],"country":"United States","state":"Colorado","otherGeospatial":"La Botica","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -106.79256393659836,\n 37.70573798045494\n ],\n [\n -106.79256393659836,\n 37.02301823232551\n ],\n [\n -105.74755024473933,\n 37.02301823232551\n ],\n [\n -105.74755024473933,\n 37.70573798045494\n ],\n [\n -106.79256393659836,\n 37.70573798045494\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"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":838788,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ruleman, Chester A. 0000-0002-1503-4591 cruleman@usgs.gov","orcid":"https://orcid.org/0000-0002-1503-4591","contributorId":1264,"corporation":false,"usgs":true,"family":"Ruleman","given":"Chester","email":"cruleman@usgs.gov","middleInitial":"A.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":838789,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":838790,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70240308,"text":"70240308 - 2022 - Modeling risk dynamics of contaminants of emerging concern in a temperate-region wastewater effluent-dominated stream","interactions":[],"lastModifiedDate":"2023-02-03T14:45:16.85921","indexId":"70240308","displayToPublicDate":"2022-12-01T08:24:40","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5112,"text":"Environmental Science: Water Research & Technology","active":true,"publicationSubtype":{"id":10}},"title":"Modeling risk dynamics of contaminants of emerging concern in a temperate-region wastewater effluent-dominated stream","docAbstract":"Wastewater effluent-dominated streams are becoming increasingly common worldwide, including in temperate regions, with potential impacts on ecological systems and drinking water sources. We recently quantified the occurrence/spatiotemporal dynamics of pharmaceutical mixtures in a representative temperate-region wastewater effluent-dominated stream (Muddy Creek, Iowa) under baseflow conditions and characterized relevant fate processes. Herein, we quantified the ecological risk quotients (RQs) of 19 effluent-derived contaminants of emerging concern (CECs; including: 14 pharmaceuticals, 2 industrial chemicals, and 3 neonicotinoid insecticides) and 1 run-off-derived compound (atrazine) in the stream under baseflow conditions, and estimated the probabilistic risks of effluent-derived CECs under all-flow conditions (i.e., including runoff events) using stochastic risk modeling. We determined that 11 out of 20 CECs pose medium-to-high risks to local ecological systems (i.e., algae, invertebrates, fish) based on literature-derived acute effects under measured baseflow conditions. Stochastic risk modeling indicated decreased, but still problematic, risk of effluent-derived CECs (i.e., RQ ≥ 0.1) under all-flow conditions when runoff events were included. Dilution of effluent-derived chemicals from storm flows thus only minimally decreased risk to aquatic biota in the effluent-dominated stream. We also modeled in-stream transport. Thirteen out of 14 pharmaceuticals persisted along the stream reach (median attenuation rate constant k < 0.1 h−1) and entered the Iowa River at elevated concentrations. Predicted and measured concentrations in the drinking water treatment plant were below the human health benchmarks. This study demonstrates the application of probabilistic risk assessments for effluent-derived CECs in a representative effluent-dominated stream under variable flow conditions (when measurements are less practical) and provides an enhanced prediction tool transferable to other effluent-dominated systems.
","language":"English","publisher":"Royal Society of Chemistry","doi":"10.1039/D2EW00157H","usgsCitation":"Zhi, H., Webb, D.T., Schnoor, J.L., Kolpin, D., Klaper, R.D., Iwanowicz, L., and LeFevre, G.H., 2022, Modeling risk dynamics of contaminants of emerging concern in a temperate-region wastewater effluent-dominated stream: Environmental Science: Water Research & Technology, v. 8, p. 1408-1422, https://doi.org/10.1039/D2EW00157H.","productDescription":"15 p.","startPage":"1408","endPage":"1422","ipdsId":"IP-129637","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":445736,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/9431852","text":"External 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L","contributorId":302047,"corporation":false,"usgs":false,"family":"Schnoor","given":"Jerald","email":"","middleInitial":"L","affiliations":[{"id":6768,"text":"University of Iowa","active":true,"usgs":false}],"preferred":false,"id":863355,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kolpin, Dana W. 0000-0002-3529-6505","orcid":"https://orcid.org/0000-0002-3529-6505","contributorId":204154,"corporation":false,"usgs":true,"family":"Kolpin","given":"Dana W.","affiliations":[{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true},{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true}],"preferred":true,"id":863356,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Klaper, Rebecca D.","contributorId":218114,"corporation":false,"usgs":false,"family":"Klaper","given":"Rebecca","email":"","middleInitial":"D.","affiliations":[{"id":18038,"text":"University of Wisconsin, Milwaukee","active":true,"usgs":false}],"preferred":false,"id":863357,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Iwanowicz, Luke 0000-0002-1197-6178 liwanowicz@usgs.gov","orcid":"https://orcid.org/0000-0002-1197-6178","contributorId":302048,"corporation":false,"usgs":true,"family":"Iwanowicz","given":"Luke","email":"liwanowicz@usgs.gov","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":863358,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"LeFevre, Gregory H.","contributorId":211880,"corporation":false,"usgs":false,"family":"LeFevre","given":"Gregory","email":"","middleInitial":"H.","affiliations":[{"id":6768,"text":"University of Iowa","active":true,"usgs":false}],"preferred":true,"id":863359,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70239798,"text":"70239798 - 2022 - Horseshoe crab","interactions":[],"lastModifiedDate":"2023-01-20T14:27:56.757671","indexId":"70239798","displayToPublicDate":"2022-12-01T08:17:53","publicationYear":"2022","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"7.1.2","title":"Horseshoe crab","docAbstract":"No abstract available.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Technical report for the Delaware estuary and basin, PDE Report No. 22-05","largerWorkSubtype":{"id":3,"text":"Organization Series"},"language":"English","publisher":"Partnership for the Delaware Estuary","usgsCitation":"Smith, D.R., 2022, Horseshoe crab, chap. 7.1.2 of Technical report for the Delaware estuary and basin, PDE Report No. 22-05, p. 308-315.","productDescription":"8 p.","startPage":"308","endPage":"315","ipdsId":"IP-142284","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":412120,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":412119,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://delawareestuary.org/data-and-reports/state-of-the-estuary-report-2/"}],"country":"United States","otherGeospatial":"Delaware Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -74.5,\n 39.85382793829535\n ],\n [\n -75.6425148831999,\n 39.85382793829535\n ],\n [\n -75.6425148831999,\n 38.75\n ],\n [\n -74.5,\n 38.75\n ],\n [\n -74.5,\n 39.85382793829535\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Smith, David R. 0000-0001-6074-9257 drsmith@usgs.gov","orcid":"https://orcid.org/0000-0001-6074-9257","contributorId":168442,"corporation":false,"usgs":true,"family":"Smith","given":"David","email":"drsmith@usgs.gov","middleInitial":"R.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":861983,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70239124,"text":"70239124 - 2022 - Effects of release techniques on parent-reared whooping cranes in the eastern migratory population","interactions":[],"lastModifiedDate":"2022-12-28T13:42:34.222167","indexId":"70239124","displayToPublicDate":"2022-12-01T07:40:38","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":12807,"text":"Proceedings of the North American Crane Workshop","active":true,"publicationSubtype":{"id":10}},"title":"Effects of release techniques on parent-reared whooping cranes in the eastern migratory population","docAbstract":"Reintroduction of an Eastern Migratory Population (EMP) of whooping cranes (Grus americana) in the United States by release of captive-reared individuals began in 2001. As of 2020, the EMP has approximately 21 breeding pairs and has had limited recruitment of wild-hatched individuals, thus captive-reared juveniles continue to be released into breeding areas in Wisconsin to maintain the population. We investigated the effects of release techniques on survival, behavior, site fidelity, and conspecific associations of 42 captive-parent-reared whooping cranes released during 2013-2019 into the EMP. Individuals were monitored intensively post-release, then as a part of a long-term monitoring program, locational, behavioral, and habitat use data were collected and analyzed. Most cranes roosted in water post-release; however, we documented 4 parent-reared cranes roosting on dry land. Most cranes eventually associated with other whooping cranes; however, juveniles released near single adult cranes were less likely to associate with other whooping cranes during their first migration or winter than juveniles released near other types of whooping crane pairs or groups. Parent-reared and costume-reared whooping cranes had similar rates of survival 1 year post-release (69.0% and 64.4%, respectively). The highest risk of mortality was within the first 100 days post-release, and the leading known causes of death were predation and impact trauma due to powerline or vehicle collisions. Both costume- and parent-reared cranes had strong fidelity to release sites. We advise releasing parent-reared cranes near pairs or groups of whooping cranes and taking measures to reduce the risk of mortality during the immediate period after release (e.g., predator aversion training, marking powerlines).
Decades of poor reproductive success and young-of-the-year survival, combined with adult mortality events, have led to a decline in the smallmouth bass (SMB; Micropterus dolomieu) population in sections of the Potomac River. Previous studies have identified numerous biologic and environmental stressors associated with negative effects on SMB health. To better understand the impact of these stressors, this study was conducted at the confluence of Antietam Creek and the Potomac River from 2013 to 2019 to identify temporal changes associated with SMB reproductive health. Surface water samples were collected and analyzed for over 300 organic contaminants, including pesticides, phytoestrogens, pharmaceuticals, hormones and total estrogenicity (E2Eq). Adult SMB were collected and sampled for multiple endpoints, including gene transcripts associated with reproduction (molecular), histopathology (cellular), and organosomatic indices (tissue). In males, biomarkers of estrogenic endocrine disruption, including testicular oocytes (TO) and plasma vitellogenin (Vtg) were assessed. Numerous agriculture-related contaminants or land use patterns were associated with gene transcript abundance in both male and female SMB. Positive associations between pesticides in the immediate catchment with TO severity and E2Eq with plasma Vtg in males were identified. In males, the prevalence of TO and detectable levels of plasma Vtg, liver vitellogenin transcripts (vtg) and testis vtg were high throughout the study. Peaks of complex mixtures of numerous contaminants occurred during the spring/early summer when spawning and early development occurs and to a lesser extent in fall/winter during recrudescence. Management practices to reduce exposure during these critical and sensitive periods may enhance reproductive health of these economically important sportfishes.
The Petro-Chemical Systems, Inc. (Turtle Bayou), Superfund site is 15 miles southeast of Liberty, Texas, in Liberty County. Improper disposal of waste oils led to contamination of soil and groundwater at the site. In cooperation with the U.S. Environmental Protection Agency, the U.S. Geological Survey collected water-quality samples from 11 monitoring wells at the site, in particular the area near well MW-109A (the MW-109 area), in August and September 2020 and compared the water-quality results to the results from previous water-quality sampling events at the site in June 2016 and August 2018 with a focus on benzene concentrations. Contours of groundwater-level altitudes in the MW-109 area indicate that groundwater-flow direction is south-southeasterly in the eastern part and south-southwesterly in the western part.
Of the 51 volatile organic compounds analyzed, 13 were detected in groundwater samples from 1 or more wells. In all but 1 well, MW-109A, concentrations of these compounds were less than 100 micrograms per liter. Benzene is still the principal contaminant of concern, as it persists at concentrations exceeding 53,000 micrograms per liter, although naphthalene also appears to be a contaminant of concern, as it was detected at the greatest concentration of any semivolatile organic compound analyte (1,100 micrograms per liter in the sample from well MW-109A).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225104","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency","usgsCitation":"Braun, C.L., and Becher, K.D., 2022, Groundwater-level altitudes and groundwater-flow direction and nature and extent of volatile and semivolatile organic compounds at Petro-Chemical Systems, Inc. (Turtle Bayou), Superfund site, Liberty County, Texas, 2020: U.S. Geological Survey Scientific Investigations Report 2022–5104, 17 p., https://doi.org/10.3133/sir20225104.","productDescription":"Report: v, 17 p.; Data release","numberOfPages":"28","onlineOnly":"Y","ipdsId":"IP-135616","costCenters":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":411892,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20225104/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":409695,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5104/sir20225104.XML"},{"id":409693,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5104/coverthb.jpg"},{"id":409694,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5104/sir20225104.pdf","text":"Report","size":"1.56 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022–5104"},{"id":409697,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9GX8YU7","text":"USGS data release","linkHelpText":"Groundwater-level altitudes and volatile and semivolatile organic compound concentrations at the Petro-Chemical Systems, Inc. (Turtle Bayou) Superfund site, Liberty County, Texas, 2020"},{"id":409696,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5104/images"}],"country":"United States","state":"Texas","county":"Liberty County","otherGeospatial":"Petro-Chemical Systems, Inc. (Turtle Bayou), Superfund site","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -94.7111,\n 29.9222\n ],\n [\n -94.7111,\n 29.9167\n ],\n [\n -94.6667,\n 29.9167\n ],\n [\n -94.6667,\n 29.9222\n ],\n [\n -94.7111,\n 29.9222\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Oklahoma-Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, TX 78754–4501
Although there is extensive evidence of declines in the American Kestrel (Falco sparverius) population across North America, the cause of such declines remains a mystery. One hypothesized driver of decline is anticoagulant rodenticide (AR) exposure, which could potentially cause mortality or reduced fitness. We investigated AR exposure in wild American Kestrels in Utah, USA. We collected and tested for AR residues in liver samples (n = 8) from kestrels opportunistically encountered dead and in blood samples (n = 71) from live wild kestrels, both nestlings and adults. We found high detection rates in both tissues. Adult kestrels were more likely to exhibit exposure than juveniles sampled in nests. Three-quarters (six of eight) of tested liver samples from adult kestrels exhibited evidence of AR exposure. Additionally, liver samples (n = 19) opportunistically collected from seven species of raptors within our study area had detectable levels of AR residues, with seven of eight raptor species evidencing exposure; across all raptors, five ARs were detected in liver samples, with brodifacoum the most prevalent, being found in over half (14 of 27) of samples. Over half (7 of 12) of the blood samples from adult kestrels had detectible levels of ARs, while only one of 59 juvenile nest samples tested positive. The difference in exposure rates between adults and juveniles could indicate differential exposure pathways by age class. Based on these findings, we recommend that ARs be further investigated as a potential cause of kestrel declines. Future research could focus on expanding sampling to provide sufficient sample sizes to test for potential nonlethal effects of AR exposure (e.g., fecundity, nesting success), identifying potential exposure pathways, and developing methods for passive sampling of ARs in excreta.
","language":"English","publisher":"BioOne","doi":"10.3356/JRR-22-18","usgsCitation":"Buechley, E.R., Oleyar, D., Watson, J., Bridgeman, J., Volker, S., Goldade, D.A., Swift, C.E., and Rattner, B.A., 2022, Preliminary evidence of anticoagulant rodenticide exposure in American kestrels (Falco sparverius) in the western United States: Journal of Raptor Research, v. 57, no. 2, 11 p., https://doi.org/10.3356/JRR-22-18.","productDescription":"11 p.","ipdsId":"IP-137518","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":409788,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -112.7171265349214,\n 41.72856999995494\n ],\n [\n -112.7171265349214,\n 39.7315850693289\n ],\n [\n -111.00398688405573,\n 39.7315850693289\n ],\n [\n -111.00398688405573,\n 41.72856999995494\n ],\n [\n -112.7171265349214,\n 41.72856999995494\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"57","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Buechley, Evan R.","contributorId":299452,"corporation":false,"usgs":false,"family":"Buechley","given":"Evan","email":"","middleInitial":"R.","affiliations":[{"id":64849,"text":"Smithsonian Conservaiton Biology Institute","active":true,"usgs":false}],"preferred":false,"id":857836,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Oleyar, Dave","contributorId":299453,"corporation":false,"usgs":false,"family":"Oleyar","given":"Dave","email":"","affiliations":[{"id":35596,"text":"HawkWatch International","active":true,"usgs":false}],"preferred":false,"id":857905,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Watson, Jesse","contributorId":243506,"corporation":false,"usgs":false,"family":"Watson","given":"Jesse","email":"","affiliations":[],"preferred":false,"id":857906,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bridgeman, Jennifer","contributorId":299455,"corporation":false,"usgs":false,"family":"Bridgeman","given":"Jennifer","email":"","affiliations":[{"id":35596,"text":"HawkWatch International","active":true,"usgs":false}],"preferred":false,"id":857907,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Volker, Steven","contributorId":299456,"corporation":false,"usgs":false,"family":"Volker","given":"Steven","affiliations":[{"id":64850,"text":"USDA, APHIS","active":true,"usgs":false}],"preferred":false,"id":857908,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Goldade, David A.","contributorId":299457,"corporation":false,"usgs":false,"family":"Goldade","given":"David","email":"","middleInitial":"A.","affiliations":[{"id":64850,"text":"USDA, APHIS","active":true,"usgs":false}],"preferred":false,"id":857909,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Swift, Catherine E.","contributorId":299495,"corporation":false,"usgs":false,"family":"Swift","given":"Catherine","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":857910,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Rattner, Barnett A. 0000-0003-3676-2843 brattner@usgs.gov","orcid":"https://orcid.org/0000-0003-3676-2843","contributorId":4142,"corporation":false,"usgs":true,"family":"Rattner","given":"Barnett","email":"brattner@usgs.gov","middleInitial":"A.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":857911,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70238753,"text":"70238753 - 2022 - Ordovician geology of Alaska","interactions":[],"lastModifiedDate":"2022-12-07T12:36:32.458661","indexId":"70238753","displayToPublicDate":"2022-11-28T06:32:58","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1791,"text":"Geological Society, London, Special Publications","active":true,"publicationSubtype":{"id":10}},"title":"Ordovician geology of Alaska","docAbstract":"Real-time monitoring is crucial to assess hazards and mitigate risks of sustained volcanic eruptions that last hours to months or more. Sustained eruptions have been shown to produce a low frequency (infrasonic) form of jet noise. We analyze the lava fountaining at fissure 8 during the 2018 Lower East Rift Zone eruption of Kīlauea volcano, Hawaii, and connect changes in fountain properties with recorded infrasound signals from an array about 500 m from the fountain using jet noise scaling laws and visual imagery. Video footage from the eruption reveals a change in lava fountain dynamics from a tall, distinct fountain at the beginning of June to a low fountain with a turbulent, out-pouring lava pond surrounded by a tephra cone by mid-June. During mid-June, the sound pressure level reaches a maximum, and peak frequency drops. We develop a model that uses jet noise scaling relationships to estimate changes in volcanic jet diameter and jet velocity from infrasound sound pressure levels and peak frequencies. The results of this model indicate a decrease in velocity in mid-June which coincides with the decrease in fountain height. Furthermore, the model results suggest an increase in jet diameter, which can be explained by the larger width of the fountain that resembles a turbulent lava pond compared to the distinct fountain at the beginning of June. The agreement between the infrasound-derived and visually observed changes in fountain dynamics suggests that jet noise scaling relationships can be used to monitor lava fountain dynamics using infrasound recordings.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/feart.2022.1027408","usgsCitation":"Gestrich, J., Fee, D., Matoza, R., Lyons, J.J., Dietterich, H., Cigala, V., Kueppers, U., Patrick, M.R., and Parcheta, C., 2022, Lava fountain jet noise during the 2018 eruption of fissure 8 of Kīlauea volcano: Frontiers Earth Science Journal, v. 10, 1027408, 18 p., https://doi.org/10.3389/feart.2022.1027408.","productDescription":"1027408, 18 p.","ipdsId":"IP-144544","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":467142,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/feart.2022.1027408","text":"Publisher Index Page"},{"id":462663,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Kilauea Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -155.40616179843389,\n 19.510647106982844\n ],\n [\n -155.40616179843389,\n 19.352324463279487\n ],\n [\n -155.20934216439622,\n 19.352324463279487\n ],\n [\n -155.20934216439622,\n 19.510647106982844\n ],\n [\n -155.40616179843389,\n 19.510647106982844\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"10","noUsgsAuthors":false,"publicationDate":"2022-11-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Gestrich, Julia","contributorId":268787,"corporation":false,"usgs":false,"family":"Gestrich","given":"Julia","affiliations":[{"id":50446,"text":"UAF-GI","active":true,"usgs":false}],"preferred":false,"id":915202,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fee, David 0000-0002-0936-9977","orcid":"https://orcid.org/0000-0002-0936-9977","contributorId":267231,"corporation":false,"usgs":false,"family":"Fee","given":"David","affiliations":[{"id":13097,"text":"Geophysical Institute, University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":915203,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Matoza, Robin","contributorId":268788,"corporation":false,"usgs":false,"family":"Matoza","given":"Robin","affiliations":[{"id":7168,"text":"UCSB","active":true,"usgs":false}],"preferred":false,"id":915204,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lyons, John J. 0000-0001-5409-1698 jlyons@usgs.gov","orcid":"https://orcid.org/0000-0001-5409-1698","contributorId":5394,"corporation":false,"usgs":true,"family":"Lyons","given":"John","email":"jlyons@usgs.gov","middleInitial":"J.","affiliations":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":915205,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dietterich, Hannah R. 0000-0001-7898-4343","orcid":"https://orcid.org/0000-0001-7898-4343","contributorId":212771,"corporation":false,"usgs":true,"family":"Dietterich","given":"Hannah R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":915206,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cigala, Valerie","contributorId":344976,"corporation":false,"usgs":false,"family":"Cigala","given":"Valerie","affiliations":[{"id":62362,"text":"LMU","active":true,"usgs":false}],"preferred":false,"id":915207,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kueppers, Ulrich","contributorId":178534,"corporation":false,"usgs":false,"family":"Kueppers","given":"Ulrich","affiliations":[],"preferred":false,"id":915208,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Patrick, Matthew R. 0000-0002-8042-6639 mpatrick@usgs.gov","orcid":"https://orcid.org/0000-0002-8042-6639","contributorId":2070,"corporation":false,"usgs":true,"family":"Patrick","given":"Matthew","email":"mpatrick@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":915209,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Parcheta, Carolyn 0000-0001-6556-4630 cparcheta@usgs.gov","orcid":"https://orcid.org/0000-0001-6556-4630","contributorId":215617,"corporation":false,"usgs":true,"family":"Parcheta","given":"Carolyn","email":"cparcheta@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":915210,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ]}