Using a geology-based assessment methodology, the U.S. Geological Survey estimated undiscovered, technically recoverable mean resources of 5 million barrels of oil and 25 billion cubic feet of gas in conventional reservoirs and 361 million barrels of oil and 10,978 billion cubic feet of gas in continuous reservoirs in the Western Gulf Basin Province of the U.S. Gulf Coast region.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/fs20253015","programNote":"National and Global Petroleum Assessment","usgsCitation":"Craddock, W.H., Counts, J.W., Doolan, C.A., Buursink, M.L., Lohr, C.D., Hatcherian, J.J., French, K.L., Gooley, J.T., Le, P.A., Mercier, T.J., Woodall, C.A., and Schenk, C.J., 2025, Assessment of undiscovered conventional and continuous oil and gas resources in the Escondido, Olmos, and San Miguel Formations of the Western Gulf Basin Province, U.S. Gulf Coast region, 2023: U.S. Geological Survey Fact Sheet 2025–3015, 4 p., https://doi.org/10.3133/fs20253015.","productDescription":"Report: 4 p.; Data Release","onlineOnly":"Y","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":493762,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118541.htm","linkFileType":{"id":5,"text":"html"}},{"id":484643,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2025/3015/fs20253015.xml"},{"id":484642,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2025/3015/images"},{"id":484421,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2025/3015/fs20253015.pdf","text":"Report","size":"1.71 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2025-3015"},{"id":484682,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/fs20253015/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"FS 2025-3015"},{"id":484420,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2025/3015/coverthb.jpg"},{"id":484422,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13GQ4CU","text":"USGS data release","linkHelpText":"USGS National and Global Oil and Gas Assessment Project-Gulf Coast Escondido, Olmos, and San Miguel Formations Conventional and Continuous Oil and Gas Assessment Unit Boundaries, Assessment Input Data, and Fact Sheet Data Tables"}],"country":"United States","state":"Texas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -101,\n 30.5\n ],\n [\n -101,\n 27.8\n ],\n [\n -97,\n 27.8\n ],\n [\n -97,\n 30.5\n ],\n [\n -101,\n 30.5\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
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Potentiometric-surface and depth-to-water maps for spring 2022 were created for the Mississippi River Valley alluvial aquifer (MRVA) using groundwater-altitude data from 1,136 wells completed in the MRVA and from the altitude of the top of the water surface in area rivers from 160 streamgages. The potentiometric-surface and depth-to-water maps for 2022 were created to support investigations to characterize the MRVA as part of the U.S. Geological Survey Water Availability and Use Science Program. Sufficient data were available to map the potentiometric surface and depth to water of the MRVA for spring 2022 for about 83 percent of the aquifer area. The potentiometric contours ranged from 0 to 340 feet (ft) above the North American Vertical Datum of 1988. The regional direction of groundwater gradient was generally to the south-southwest, except in areas of groundwater-altitude depressions, where the groundwater gradient was into the depression, and near rivers, where the groundwater gradient can be from aquifer to the river or from the river into the aquifer. There are large depressions in the potentiometric-surface map in the lower one-half of the Cache region and in much of the Grand Prairie and Delta regions. Depth to water in the MRVA, spring 2022, by well ranged from 5.00 ft above land surface to 145.66 ft below land surface.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3532","programNote":"Water Availability and Use Science Program","usgsCitation":"McGuire, V.L., Strauch, K.R., Wojtylko, E.A., Asquith, W.H., Nottmeier, A.M., Thomas, J.C., Tollett, R.W., and Kress, W.H., 2025, Altitude of the potentiometric surface and depth to water in the Mississippi River Valley alluvial aquifer, spring 2022: U.S. Geological Survey Scientific Investigations Map 3532, 5 sheets, scales 1:1,000,000 and 1:2,000,000, 19-p. pamphlet, https://doi.org/10.3133/sim3532.","productDescription":"Pamphlet: ix, 19 p.; 5 Sheets: 30.00 x 45.00 inches or smaller; Data Release; Dataset","numberOfPages":"32","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-137606","costCenters":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"links":[{"id":493761,"rank":13,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118540.htm","linkFileType":{"id":5,"text":"html"}},{"id":484091,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sim3532/full"},{"id":484092,"rank":6,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3532/downloads/sim3532_sheet1.pdf","text":"Sheet 1","size":"16 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":484094,"rank":7,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3532/downloads/sim3532_sheet2.pdf","text":"Sheet 2","size":"5.3 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":484095,"rank":8,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3532/downloads/sim3532_sheet3.pdf","text":"Sheet 3","size":"7.4 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":484096,"rank":9,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3532/downloads/sim3532_sheet4.pdf","text":"Sheet 4","size":"5.2 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":484097,"rank":10,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3532/downloads/sim3532_sheet5.pdf","text":"Sheet 5","size":"7.6 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":484098,"rank":11,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P95883TJ","text":"USGS data release","linkHelpText":"Datasets used to map the potentiometric surface and depth to water, Mississippi River Valley alluvial aquifer, spring 2022"},{"id":484099,"rank":12,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"- USGS water data for the Nation"},{"id":484087,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3532/coverthb.jpg"},{"id":484088,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3532/sim3532.pdf","text":"Pamphlet","size":"14 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3532"},{"id":484089,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sim/3532/sim3532.XML"},{"id":484090,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sim/3532/images/"}],"country":"United States","otherGeospatial":"Mississippi River Valley alluvial aquifer","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -91.7960849146639,\n 39.04358924105398\n ],\n [\n -91.7960849146639,\n 28.527159743704843\n ],\n [\n -88.44541245375156,\n 28.527159743704843\n ],\n [\n -88.44541245375156,\n 39.04358924105398\n ],\n [\n -91.7960849146639,\n 39.04358924105398\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Nebraska Water Science Center
U.S. Geological Survey
5231 South 19th Street
Lincoln, NE 68512
Each year, U.S. Geological Survey (USGS) personnel collect approximately 52,000 water-quality samples from rivers and streams across the United States. Several samplers are used by the USGS for water-quality sample collection in riverine environments. These samplers are coated with Plasti Dip to protect the exterior of the sampler; however, Plasti Dip is susceptible to fraying and wear, requiring maintenance. Alternative coatings were tested to determine if a different coating is better suited for the samplers. The alternative coatings included Raptor, powder coating, and DuraCoat; a fifth option was bare metal. Samplers with different coatings were evaluated based on initial coating application, equipment blank samples, a controlled wear test, blank sample collection with worn samplers, maintenance and re-coating of samplers, and field-use and wear tracking. The powder-coated sampler proved to be the top performer overall in the study.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20251016","usgsCitation":"Thornton, A.M., 2025, Evaluation of alternative coatings for U.S. Geological Survey water-quality samplers: U.S. Geological Survey Open-File Report 2025–1016, 15 p., https://doi.org/10.3133/ofr20251016.","productDescription":"Report: iv, 15 p.; Data Release","numberOfPages":"15","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-173533","costCenters":[{"id":37280,"text":"Virginia and West Virginia Water Science Center ","active":true,"usgs":true}],"links":[{"id":484591,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P144VS6G","text":"USGS data release","linkHelpText":"Data to support the evaluation of alternative Coatings for USGS Water-Quality Samplers"},{"id":484590,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2025/1016/images/"},{"id":484589,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2025/1016/ofr20251016.XML","linkFileType":{"id":8,"text":"xml"},"description":"OFR 2025-1016 XML"},{"id":484588,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20251016/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2025-1016 HTML"},{"id":484587,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2025/1016/ofr20251016.pdf","text":"Report","size":"3.46 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2025-1016 PDF"},{"id":484586,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2025/1016/coverthb.jpg"}],"contact":"Director, Virginia and West Virginia Water Science Center
U.S. Geological Survey
1730 East Parham Road
Richmond, Virginia 23228
This review assesses gaps in water quality modeling, emphasizing opportunities to improve next-generation models that are essential for managing water quality and are integral to meeting goals of scientific and management agencies. In particular, this paper identifies gaps in water quality modeling capabilities that, if addressed, could support assessments, projections, and evaluations of management alternatives to support ecosystem health and human beneficial use of water resources. It covers surface water and groundwater quality modeling, dealing with a broad suite of physical, biogeochemical, and anthropogenic drivers. Modeling capabilities for six constituents (or constituent categories) are explored: water temperature, salinity, nutrients, sediment, geogenic constituents, and contaminants of emerging concern. Each constituent was followed through the coupled atmospheric-hydrologic-human system, with prominent modeling gaps described for a diverse array of relevant inputs, processes, and human activities. Commonly identified modeling gaps primarily fall under three types: (1) model gaps, (2) data gaps, and (3) process understanding gaps. In addition to potential solutions for addressing specific individual modeling limitations, some broad approaches (e.g., enhanced data collection and compilation, machine learning, reduced-complexity modeling) are discussed as ways forward for tackling multiple gaps. This gap analysis establishes a framework of diverse approaches that may support improved process representation, scale, and accuracy of models for a wide range of water quality issues.
","language":"English","publisher":"MDPI","doi":"10.3390/w17081200","usgsCitation":"Lucas, L., Brown, C., Robertson, D., Baker, N.T., Johnson, Z., Green, C., Cho, J., Erickson, M., Gellis, A.C., Jasmann, J.R., Knowles, N., Prein, A., and Stackelberg, P.E., 2025, Gaps in water quality modeling of hydrologic systems: Water, v. 17, no. 8, 1200, 98 p., https://doi.org/10.3390/w17081200.","productDescription":"1200, 98 p.","ipdsId":"IP-157684","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":488460,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w17081200","text":"Publisher Index Page"},{"id":484764,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"17","issue":"8","noUsgsAuthors":false,"publicationDate":"2025-04-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Lucas, Lisa 0000-0001-7797-5517 llucas@usgs.gov","orcid":"https://orcid.org/0000-0001-7797-5517","contributorId":260498,"corporation":false,"usgs":true,"family":"Lucas","given":"Lisa","email":"llucas@usgs.gov","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":933941,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brown, Craig J. 0000-0002-3858-3964","orcid":"https://orcid.org/0000-0002-3858-3964","contributorId":210450,"corporation":false,"usgs":true,"family":"Brown","given":"Craig J.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":933942,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Robertson, Dale M. 0000-0001-6799-0596","orcid":"https://orcid.org/0000-0001-6799-0596","contributorId":217258,"corporation":false,"usgs":true,"family":"Robertson","given":"Dale M.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":933943,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Baker, Nancy T. 0000-0002-7979-5744","orcid":"https://orcid.org/0000-0002-7979-5744","contributorId":222870,"corporation":false,"usgs":true,"family":"Baker","given":"Nancy","email":"","middleInitial":"T.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":933944,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Johnson, Zachary 0000-0002-0149-5223 zjohnson@usgs.gov","orcid":"https://orcid.org/0000-0002-0149-5223","contributorId":190399,"corporation":false,"usgs":true,"family":"Johnson","given":"Zachary","email":"zjohnson@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":933945,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Green, Christopher 0000-0002-6480-8194","orcid":"https://orcid.org/0000-0002-6480-8194","contributorId":201642,"corporation":false,"usgs":true,"family":"Green","given":"Christopher","email":"","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":933946,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cho, Jong 0000-0001-5514-6056","orcid":"https://orcid.org/0000-0001-5514-6056","contributorId":291384,"corporation":false,"usgs":true,"family":"Cho","given":"Jong","email":"","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":933947,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Erickson, Melinda L. 0000-0002-1117-2866 merickso@usgs.gov","orcid":"https://orcid.org/0000-0002-1117-2866","contributorId":3671,"corporation":false,"usgs":true,"family":"Erickson","given":"Melinda L.","email":"merickso@usgs.gov","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":933948,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"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":933949,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Jasmann, Jeramy Roland 0000-0002-5251-6987","orcid":"https://orcid.org/0000-0002-5251-6987","contributorId":238713,"corporation":false,"usgs":true,"family":"Jasmann","given":"Jeramy","email":"","middleInitial":"Roland","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":933950,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Knowles, Noah 0000-0001-5652-1049","orcid":"https://orcid.org/0000-0001-5652-1049","contributorId":206338,"corporation":false,"usgs":true,"family":"Knowles","given":"Noah","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":933951,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Prein, Andreas","contributorId":352146,"corporation":false,"usgs":false,"family":"Prein","given":"Andreas","affiliations":[{"id":24610,"text":"NCAR","active":true,"usgs":false}],"preferred":false,"id":933952,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Stackelberg, Paul E. 0000-0002-1818-355X","orcid":"https://orcid.org/0000-0002-1818-355X","contributorId":204864,"corporation":false,"usgs":true,"family":"Stackelberg","given":"Paul","middleInitial":"E.","affiliations":[{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"preferred":true,"id":933953,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70266873,"text":"70266873 - 2025 - Selenium differentially influences methylmercury retention across mayfly life stages","interactions":[],"lastModifiedDate":"2025-05-14T14:32:43.488492","indexId":"70266873","displayToPublicDate":"2025-04-16T09:30:38","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5925,"text":"Environmental Science and Technology","active":true,"publicationSubtype":{"id":10}},"title":"Selenium differentially influences methylmercury retention across mayfly life stages","docAbstract":"Though high mercury and selenium concentrations are individually toxic to organisms, there is a hypothesized antagonistic relationship. This potential mercury–selenium interaction is under-studied in aquatic macroinvertebrates, particularly in relation to complex life histories. We examined the proposed effect of selenium on methylmercury accumulation between four life stages for a parthenogenetic mayfly (Neocloeon triangulifer). We exposed diatoms to elevated methylmercury concentrations and fed them to mayflies exposed to elevated aqueous selenomethionine. We found some support for the mercury–selenium antagonism hypothesis, but it was context-specific. Selenium reduced methylmercury accumulation in high but not low methylmercury environments. Though terrestrial adult life stages had higher mercury concentrations compared to aquatic larval life stages, cumulative life history transfer factor (LHTF; ratio of methylmercury in adult imago to late instar larvae) differed by treatment. LHTF was constant for all aqueous selenium exposure levels at high dietary methylmercury (selenium impacts on methylmercury uptake and loss) but increased with aqueous selenium exposures at low dietary methylmercury (selenium impacts on methylmercury uptake only), suggesting a synergistic enhancement of MeHg transfer between life stages with increased aqueous Se exposure levels. These results suggest that animals eating adult aquatic insects are exposed to higher concentrations of methylmercury than those feeding on larval insects across selenium and methylmercury levels, but interference of selenium on methylmercury accumulation is only present at high methylmercury environments.
","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.est.5c00338","usgsCitation":"Gerson, J.R., Dorman, R.A., Eagles-Smith, C., and Walters, D., 2025, Selenium differentially influences methylmercury retention across mayfly life stages: Environmental Science and Technology, v. 59, no. 16, p. 8201-8209, https://doi.org/10.1021/acs.est.5c00338.","productDescription":"9 p.","startPage":"8201","endPage":"8209","ipdsId":"IP-165623","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":490120,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1021/acs.est.5c00338","text":"Publisher Index Page"},{"id":485932,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"59","issue":"16","noUsgsAuthors":false,"publicationDate":"2025-04-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Gerson, Jacqueline R.","contributorId":198378,"corporation":false,"usgs":false,"family":"Gerson","given":"Jacqueline","email":"","middleInitial":"R.","affiliations":[{"id":5082,"text":"Syracuse University","active":true,"usgs":false},{"id":27331,"text":"Duke University, Durham, NC","active":true,"usgs":false}],"preferred":false,"id":937005,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dorman, Rebecca A. 0000-0002-5748-7046","orcid":"https://orcid.org/0000-0002-5748-7046","contributorId":28522,"corporation":false,"usgs":true,"family":"Dorman","given":"Rebecca","email":"","middleInitial":"A.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":937006,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Eagles-Smith, Collin A. 0000-0003-1329-5285","orcid":"https://orcid.org/0000-0003-1329-5285","contributorId":221745,"corporation":false,"usgs":true,"family":"Eagles-Smith","given":"Collin A.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":937007,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Walters, David 0000-0002-4237-2158","orcid":"https://orcid.org/0000-0002-4237-2158","contributorId":205915,"corporation":false,"usgs":true,"family":"Walters","given":"David","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":937008,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70266843,"text":"70266843 - 2025 - Does the Lost Jim lava flow (Alaska) really preserve evidence of interaction with permafrost?","interactions":[],"lastModifiedDate":"2025-05-13T16:35:06.894023","indexId":"70266843","displayToPublicDate":"2025-04-16T09:29:32","publicationYear":"2025","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":"Does the Lost Jim lava flow (Alaska) really preserve evidence of interaction with permafrost?","docAbstract":"The basaltic Lost Jim lava flow, the youngest member of the Imuruk Lake volcanic field, Alaska, is reported to have interacted with underlying permafrost by thawing it and forming cavities into which the lava flow collapsed, forming pits and other depressions on the lava flow's surface. Our field observations contradict this hypothesis. The Lost Jim lava flow exhibits surface features typical of an inflated pāhoehoe flow, and we propose instead that most of the pits are unambiguously the result of flow inflation (i.e., lava-rise pits). These pits are found on elevated, relatively level surfaces, and their inner walls preserve features like rotated surface slabs and fine-scale flow banding on exposed crack surfaces, both of which are hallmarks of lava flow inflation. While collapse pits do exist on the Lost Jim lava flow, they are morphologically distinct and formed by crustal failure into drained lava tubes.
Satellite images of the Lost Jim lava flow show similarities in the size and distribution of pits within other young pāhoehoe lava flows scattered across the globe. The small diameter of many of the pits (<10 m), compared to flow thickness (≥10 m), also argues against collapse—numerical modeling shows that the relatively high tensile strength of a coherent lava flow would have prevented its collapse into cavities similar in diameter to the lava flow's thickness. Finally, the pits are found scattered across the Lost Jim lava flow, including in locations where the lava flow rests directly on bedrock, which consists of older lava flows. Segregated ice lenses and soil expansion—necessary components for thermokarst formation when thawed—do not exist in such locations. Altogether, these factors show that the Lost Jim lava flow is an inflated lava flow, and permafrost played no significant role during or after its emplacement.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2025.108347","usgsCitation":"Orr, T., Coombs, W., Rader, E., and Larsen, J., 2025, Does the Lost Jim lava flow (Alaska) really preserve evidence of interaction with permafrost?: Journal of Volcanology and Geothermal Research, v. 464, 108347, 12 p., https://doi.org/10.1016/j.jvolgeores.2025.108347.","productDescription":"108347, 12 p.","ipdsId":"IP-156249","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":488269,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jvolgeores.2025.108347","text":"Publisher Index Page"},{"id":485838,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Lost Jim lava flow","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -163.99392503271278,\n 65.97766449153795\n ],\n [\n -163.99392503271278,\n 65.7063086880865\n ],\n [\n -162.3815948765932,\n 65.7063086880865\n ],\n [\n -162.3815948765932,\n 65.97766449153795\n ],\n [\n -163.99392503271278,\n 65.97766449153795\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"464","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Orr, Tim R. 0000-0003-1157-7588","orcid":"https://orcid.org/0000-0003-1157-7588","contributorId":26365,"corporation":false,"usgs":true,"family":"Orr","given":"Tim R.","affiliations":[{"id":336,"text":"Hawaiian Volcano Observatory","active":false,"usgs":true}],"preferred":true,"id":936886,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coombs, William M. 0000-0003-2099-1676","orcid":"https://orcid.org/0000-0003-2099-1676","contributorId":355121,"corporation":false,"usgs":false,"family":"Coombs","given":"William M.","affiliations":[{"id":35079,"text":"Durham University, Durham, UK","active":true,"usgs":false}],"preferred":false,"id":936887,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rader, Erika 0000-0001-8205-3461","orcid":"https://orcid.org/0000-0001-8205-3461","contributorId":331813,"corporation":false,"usgs":false,"family":"Rader","given":"Erika","email":"","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":936888,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Larsen, Jessica 0000-0003-1171-129X","orcid":"https://orcid.org/0000-0003-1171-129X","contributorId":242808,"corporation":false,"usgs":false,"family":"Larsen","given":"Jessica","email":"","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":936889,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70266571,"text":"70266571 - 2025 - Field and laboratory evaluations of visible light as a cue for guiding downstream-migrating juvenile Sea Lamprey","interactions":[],"lastModifiedDate":"2025-05-09T14:09:18.996832","indexId":"70266571","displayToPublicDate":"2025-04-16T08:57:42","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Field and laboratory evaluations of visible light as a cue for guiding downstream-migrating juvenile Sea Lamprey","docAbstract":"We evaluated white light as a potential guidance cue for juvenile Sea Lamprey Petromyzon marinus in a natural setting as well as the effect of water velocity (0.25-, 0.50-, 0.75-, and 1.0-m/s test velocities) on light guidance behavior in a controlled laboratory flume, and characterized emigration timing and movement rates in a small stream (∼10 m wide and 0.7 m deep).
Behaviors and rates of downstream movement were monitored using PIT telemetry in both studies.
In the field study, downstream movement by juveniles released during October 30–November 27 appeared to be cued by precipitation-induced flow events when water temperatures ranged between 4°C and 8°C. Juveniles expressed lateral attraction to a short, bank-mounted linear light array, but the guidance effect was not strong or consistent between bank light locations. Downstream movement rates decreased slightly when juveniles were exposed to the light cue. In the laboratory flume experiment, at water velocities of 0.25 and 0.75 m/s, lamprey were 2.8 and 3.3 times more likely to be detected at antennas along a wall with a linear light array compared with other antennas across the width of the flume. Significant changes in distribution were detected farther upstream in the flume during 0.25- and 0.50-m/s water velocity trials compared with 0.75-m/s trials. Further, the rate of downstream movement through the length of the flume decreased under artificial lighting compared with dark controls under the 0.25- and 0.75-m/s velocity conditions.
The results suggest lamprey exhibit a behavioral response to the light cue in both lab and field, but water velocity influences how effectively juveniles can respond to light cues.
The 2018–2023 phreatomagmatic eruptions at Semisopochnoi Island, Alaska produced abundant long-period (LP) seismicity, harmonic and broadband tremor, and explosion signals over several well-monitored periods of eruption and quiescence. The corresponding dataset provides an excellent opportunity to investigate precursory and syn-eruptive geophysical signals of long-lived phreatomagmatic eruptions using multiparameter observations. We generated explosion and LP event catalogs through novel implementations of the REDPy (Hotovec-Ellis, 2024) repeating event detector in mid-2021 following a network upgrade and the onset of a new phase of the eruption. The hundreds of detected explosions show a high degree of infrasound waveform similarity over more than a year, indicating a repeating source mechanism likely associated with explosive magma-water interaction. The seismic LP catalog shows that events began over a month prior to renewed explosive activity at the beginning of August 2021, and that lower frequency index (FI) LPs were generated in the week prior to the onset of explosions. We applied a recently developed machine learning tool (VOISS-Net, Tan et al., 2024) to catalog abundant broadband and harmonic seismic tremor recorded before and during the renewed explosive activity, along with LPs and explosions. The tremor catalogs complement the LP and explosion catalogs by filling out the seismic sequence with the dominant signal types. Together, these catalogs reveal a seismic sequence of renewed unrest that started with several weeks of LP events, followed by LPs with lower FI values and harmonic tremor in the days prior to explosive activity, and finally the onset of discrete explosions and broadband eruption tremor. We interpret this sequence as the ascent of a new pulse of magma that first interacted with the hydrothermal/groundwater system to produce LPs, followed by harmonic tremor, and that ultimately drove explosive magma-water interactions and periods of continuous ash emissions. The 2021 seismic sequence, in combination with long-term records of satellite SO2 emissions, deformation from interferometric synthetic aperture radar (InSAR) analysis, ash sample analysis, infrasound, and volcano tectonic seismicity, allows us to interpret the entire 9-year period of unrest and eruption that began with an intrusion and earthquake swarm in 2014.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2025.108329","usgsCitation":"Lyons, J.J., Tan, D., Angarita, M., Loewen, M.W., Lopez, T., Grapenthin, R., Hotovec-Ellis, A.J., Fee, D., and Haney, M.M., 2025, Identifying precursors and tracking pulses of magma ascent in multidisciplinary data during the 2018–2023 phreatomagmatic eruption at Semisopochnoi Island, Alaska: Journal of Volcanology and Geothermal Research, v. 463, 108329, 20 p., https://doi.org/10.1016/j.jvolgeores.2025.108329.","productDescription":"108329, 20 p.","ipdsId":"IP-176345","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":492468,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jvolgeores.2025.108329","text":"Publisher Index Page"},{"id":492125,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Semisopochnoi Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 179.45548299275004,\n 52.040459864240546\n ],\n [\n 179.45548299275004,\n 51.86149191597676\n ],\n [\n 179.7966363352781,\n 51.86149191597676\n ],\n [\n 179.7966363352781,\n 52.040459864240546\n ],\n [\n 179.45548299275004,\n 52.040459864240546\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"463","noUsgsAuthors":false,"publicationDate":"2025-04-16","publicationStatus":"PW","contributors":{"authors":[{"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":942753,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tan, Darren 0000-0001-8210-6041","orcid":"https://orcid.org/0000-0001-8210-6041","contributorId":304978,"corporation":false,"usgs":false,"family":"Tan","given":"Darren","email":"","affiliations":[{"id":66199,"text":"Geophysical Institute and Alaska Volcano Observatory, University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":942754,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Angarita, Mario","contributorId":215655,"corporation":false,"usgs":false,"family":"Angarita","given":"Mario","email":"","affiliations":[{"id":37066,"text":"OVSICORI","active":true,"usgs":false}],"preferred":false,"id":942755,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Loewen, Matthew W. 0000-0002-5621-285X","orcid":"https://orcid.org/0000-0002-5621-285X","contributorId":213321,"corporation":false,"usgs":true,"family":"Loewen","given":"Matthew","email":"","middleInitial":"W.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":942756,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lopez, Taryn","contributorId":237830,"corporation":false,"usgs":false,"family":"Lopez","given":"Taryn","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":942757,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Grapenthin, Ronni","contributorId":257035,"corporation":false,"usgs":false,"family":"Grapenthin","given":"Ronni","email":"","affiliations":[{"id":7026,"text":"New Mexico Tech","active":true,"usgs":false}],"preferred":false,"id":942758,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hotovec-Ellis, Alicia J. 0000-0003-1917-0205","orcid":"https://orcid.org/0000-0003-1917-0205","contributorId":211785,"corporation":false,"usgs":true,"family":"Hotovec-Ellis","given":"Alicia","email":"","middleInitial":"J.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":942759,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"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":942760,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Haney, Matthew M. 0000-0003-3317-7884 mhaney@usgs.gov","orcid":"https://orcid.org/0000-0003-3317-7884","contributorId":172948,"corporation":false,"usgs":true,"family":"Haney","given":"Matthew","email":"mhaney@usgs.gov","middleInitial":"M.","affiliations":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":942761,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70270107,"text":"70270107 - 2025 - What is the lowest latitude of discrete aurorae during superstorms?","interactions":[],"lastModifiedDate":"2025-08-11T15:47:09.174324","indexId":"70270107","displayToPublicDate":"2025-04-16T08:41:37","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3456,"text":"Space Weather","active":true,"publicationSubtype":{"id":10}},"title":"What is the lowest latitude of discrete aurorae during superstorms?","docAbstract":"From a survey of published accounts of visual sightings of aurorae, a compilation is presented of the lowest identified geomagnetic latitude at which discrete aurorae were seen at local zenith during magnetic storms having intensities with maximum −Dst > 200 nT. The compilation includes data for the superstorms of 2 September 1859, 4 February 1872, and 15 May 1921. A statistical model is developed representing the equatorward boundary of discrete aurorae versus storm intensity. The model indicates that a once-per-century storm would likely induce discrete aurorae at zenith down to a geomagnetic latitude of 34°. Insofar as aurorae can be taken as a proxy for electrojet currents, such a storm would expose many nighttime electric-power systems, in the contiguous United States or Europe, to high levels of geomagnetic disturbance. A Carrington-class storm would induce discrete aurorae down to 24°. These exposures are much greater than those indicated in recent numerical simulations of extreme magnetic storms. Using the model to infer storm intensity from reports of low-latitude aurorae, a storm on 28 August 1859, likely had maximum −Dst = 673 nT. That this storm occurred just a few days before the Carrington storm of 2 September (maximum −Dst = 964 nT) deserves attention. A storm that occurred on 17 September 1770 is estimated to have had maximum −Dst = 928 nT. The vision of Ezekiel could have been inspired by aurorae from a storm with maximum −Dst = 550 nT.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2024SW004286","usgsCitation":"Love, J.J., Mann, I., Qvick, T., and Mursula, K., 2025, What is the lowest latitude of discrete aurorae during superstorms?: Space Weather, v. 23, no. 4, e2024SW004286, 22 p., https://doi.org/10.1029/2024SW004286.","productDescription":"e2024SW004286, 22 p.","ipdsId":"IP-173082","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":494191,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2024sw004286","text":"Publisher Index Page"},{"id":493936,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"23","issue":"4","noUsgsAuthors":false,"publicationDate":"2025-04-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Love, Jeffrey J. 0000-0002-3324-0348 jlove@usgs.gov","orcid":"https://orcid.org/0000-0002-3324-0348","contributorId":760,"corporation":false,"usgs":true,"family":"Love","given":"Jeffrey","email":"jlove@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":945473,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mann, Ian R.","contributorId":359451,"corporation":false,"usgs":false,"family":"Mann","given":"Ian R.","affiliations":[{"id":36696,"text":"University of Alberta","active":true,"usgs":false}],"preferred":false,"id":945474,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Qvick, Timo","contributorId":359452,"corporation":false,"usgs":false,"family":"Qvick","given":"Timo","affiliations":[{"id":82926,"text":"University of Oulu","active":true,"usgs":false}],"preferred":false,"id":945475,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mursula, Kalevi","contributorId":344048,"corporation":false,"usgs":false,"family":"Mursula","given":"Kalevi","affiliations":[{"id":82280,"text":"Space Climate Group, Space Physics and Astronomy Research Unit, University of Oulu, PO Box 3000, 90014 Oulu, Finland","active":true,"usgs":false}],"preferred":false,"id":945476,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70265880,"text":"70265880 - 2025 - April 2025","interactions":[],"lastModifiedDate":"2025-09-19T13:07:11.821879","indexId":"70265880","displayToPublicDate":"2025-04-16T08:41:08","publicationYear":"2025","noYear":false,"publicationType":{"id":25,"text":"Newsletter"},"publicationSubtype":{"id":30,"text":"Newsletter"},"seriesTitle":{"id":18358,"text":"Flow Photo Explorer","active":true,"publicationSubtype":{"id":30}},"title":"April 2025","docAbstract":"No abstract available.
","language":"English","publisher":"U.S. Geological Survey","usgsCitation":"Fair, J.H., 2025, April 2025: Flow Photo Explorer, HTML Document.","productDescription":"HTML Document","ipdsId":"IP-178021","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":484673,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://content.govdelivery.com/accounts/USDOIGS/bulletins/3db2be1","linkFileType":{"id":5,"text":"html"}},{"id":495703,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Fair, Jennifer H. 0000-0002-9902-1893","orcid":"https://orcid.org/0000-0002-9902-1893","contributorId":245941,"corporation":false,"usgs":true,"family":"Fair","given":"Jennifer","middleInitial":"H.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":933799,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70267815,"text":"70267815 - 2025 - Lithium from magma to mine in an early Yellowstone hotspot caldera","interactions":[],"lastModifiedDate":"2025-07-10T14:50:14.042773","indexId":"70267815","displayToPublicDate":"2025-04-16T08:37:29","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1796,"text":"Geology","active":true,"publicationSubtype":{"id":10}},"title":"Lithium from magma to mine in an early Yellowstone hotspot caldera","docAbstract":"Renewable energy technologies rely on the extraction of metals not historically in high demand, such as lithium (Li), for which ore deposit models are incompletely understood. One of the world’s largest Li deposits is hosted in lake sediments of the 16.4 Ma McDermitt caldera, which formed during the early stages of Yellowstone hotspot volcanism in the western United States. Eruptive and posteruptive mobility of Li are major challenges in elucidating deposit formation. Melt inclusions preserved in quartz crystals provide a means to assess pre-eruptive magmatic Li contents. Concentrations of Li determined by ion microprobe for melt inclusions in a McDermitt rhyolite lava are 400−1350 ppm, compared to 20−70 ppm Li in matrix rhyolite glasses. Synthesis with melt inclusion data for eight additional calderas demonstrates a recurrence of Li-rich rhyolitic magmas (200−2000 ppm Li) in the western part of the Yellowstone hotspot track. However, unlike the multicyclic caldera complexes with overlapping fault networks that may have compromised Li retention, the McDermitt caldera remained a closed hydrologic system throughout its evolution. Modeling indicates 100 km3 of resurgent magma could yield 25−150 Mt Li in a magmatic fluid and supports accumulation of Li-rich magmatic fluid in a closed intracaldera lake, followed by evaporative concentration and sequestration of Li within clay minerals to generate the McDermitt deposit.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/G53140.1","usgsCitation":"Watts, K., 2025, Lithium from magma to mine in an early Yellowstone hotspot caldera: Geology, v. 53, no. 7, p. 592-596, https://doi.org/10.1130/G53140.1.","productDescription":"5 p.","startPage":"592","endPage":"596","ipdsId":"IP-167363","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":489475,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":490666,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/g53140.1","text":"Publisher Index Page"}],"country":"United States","state":"Idaho, Nevada, Oregon, Wyoming","otherGeospatial":"Yellowstone hotspot caldera","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -110.21830246150877,\n 45.126578896874065\n ],\n [\n -119.21693278725452,\n 45.126578896874065\n ],\n [\n -119.21693278725452,\n 41.23242701033587\n ],\n [\n -114.17059390138817,\n 40.859473447854995\n ],\n [\n -114.02540645163282,\n 42.00890055289802\n ],\n [\n -110.44161856797778,\n 41.981517173869975\n ],\n [\n -110.21830246150877,\n 45.126578896874065\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"53","issue":"7","noUsgsAuthors":false,"publicationDate":"2025-04-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Watts, Kathryn E. 0000-0002-6110-7499","orcid":"https://orcid.org/0000-0002-6110-7499","contributorId":204344,"corporation":false,"usgs":true,"family":"Watts","given":"Kathryn E.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":939006,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70266349,"text":"70266349 - 2025 - The Harmonized Landsat and Sentinel-2 version 2.0 surface reflectance dataset","interactions":[],"lastModifiedDate":"2025-05-07T13:11:44.831779","indexId":"70266349","displayToPublicDate":"2025-04-16T08:13:35","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"The Harmonized Landsat and Sentinel-2 version 2.0 surface reflectance dataset","docAbstract":"Frequent multispectral observations of sufficient spatial detail from well-calibrated spaceborne sensors are needed for large-scale terrestrial monitoring. To meet this demand, the NASA Harmonized Landsat and Sentinel-2 (HLS) project was initiated in early 2010s to produce comparable 30-m surface reflectance from the US Landsat 8 Operational Land Imager (OLI) and the European Copernicus Sentinel-2A MultiSpectral Instrument (MSI), and currently from two OLI and two MSI sensors, by applying atmospheric correction to top-of-atmosphere (TOA) reflectance, masking out clouds and cloud shadows, normalizing bi-directional reflectance view angle effects, adjusting for sensor bandpass differences with the OLI as the reference, and providing the harmonized data in a common grid. Several versions of HLS dataset have been produced in the last few years. The recent improvements on almost all the harmonization algorithms had prompted a production of a new HLS dataset, tagged Version 2.0, which was completed in the summer of 2023 and for the first time takes on a global coverage (except for Antarctica). The HLS V2.0 data record starts in April 2013, two months after Landsat 8 launch. For 2022, the first whole year two Landsat and two Sentinel-2 satellites were available, HLS provides a global median of 66 cloud-free observations over land, substantially more than from a single sensor. This paper describes the HLS algorithm improvements and assesses the harmonization efficacy by examining how the reflectance difference between contemporaneous Landsat and Sentinel-2 observations was successively reduced by each harmonization step. The assessment was conducted on 545 pairs of globally distributed same-day Landsat/Sentinel-2 images from 2021 to 2022. Compared to the TOA data, the HLS atmospheric correction slightly increased the reflectance relative difference between Landsat and Sentinel-2 for most of the spectral bands, especially for the two blue bands and the green bands. The subsequent bi-directional reflectance view angle effect normalization effectively reduced the between-sensor reflectance difference present in the atmospherically corrected data for all the spectral bands, and notably to a level below the TOA differences for the red, near-infrared (NIR), and the two shortwave infrared (SWIR) bands. The bandpass adjustment only had a modest effect on reducing the between-sensor reflectance difference. In the final HLS products, the same-day reflectance difference between Landsat and Sentinel-2 was below 4.2% for the red, NIR, and the two SWIR bands, all smaller than the difference in the TOA data. However, the between-sensor differences for the two blue and the green bands remain slightly higher than in TOA data, and this reflects the difficulty in accurately correcting for atmospheric effects in the shorter wavelength visible bands. The data consistency evaluation on a suite of commonly used vegetation indices (VI) calculated from the HLS V2.0 reflectance data showed that the between-sensor VI difference is below 4.5% for most of the indices. These results suggest that the harmonization is robust and the HLS V2.0 data are adequate for quantitative terrestrial applications.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2025.114723","usgsCitation":"Ju, J., Zhou, Q., Freitag, B., Roy, D., Zhang, H., Sridhar, M., Mandel, J., Arab, S., Schmidt, G.L., Crawford, C., Gascon, F., Strobl, P., Masek, J.G., and Neigh, C., 2025, The Harmonized Landsat and Sentinel-2 version 2.0 surface reflectance dataset: Remote Sensing of Environment, v. 324, 114723, 17 p., https://doi.org/10.1016/j.rse.2025.114723.","productDescription":"114723, 17 p.","ipdsId":"IP-178601","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":488127,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rse.2025.114723","text":"Publisher Index Page"},{"id":485453,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"324","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ju, Junchang","contributorId":354466,"corporation":false,"usgs":false,"family":"Ju","given":"Junchang","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":935736,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zhou, Qiang","contributorId":354468,"corporation":false,"usgs":false,"family":"Zhou","given":"Qiang","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":935737,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Freitag, Brian","contributorId":354470,"corporation":false,"usgs":false,"family":"Freitag","given":"Brian","affiliations":[{"id":16239,"text":"NASA Marshall Space Flight Center","active":true,"usgs":false}],"preferred":false,"id":935738,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Roy, David P.","contributorId":294404,"corporation":false,"usgs":false,"family":"Roy","given":"David P.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":935739,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zhang, Hankui","contributorId":354472,"corporation":false,"usgs":false,"family":"Zhang","given":"Hankui","affiliations":[{"id":5089,"text":"South Dakota State University","active":true,"usgs":false}],"preferred":false,"id":935740,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sridhar, Madhu","contributorId":350383,"corporation":false,"usgs":false,"family":"Sridhar","given":"Madhu","affiliations":[{"id":83729,"text":"University of Alabama Huntsville","active":true,"usgs":false}],"preferred":false,"id":935741,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Mandel, John","contributorId":354474,"corporation":false,"usgs":false,"family":"Mandel","given":"John","affiliations":[{"id":16239,"text":"NASA Marshall Space Flight Center","active":true,"usgs":false}],"preferred":false,"id":935742,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Arab, Saeed 0000-0003-1602-8801","orcid":"https://orcid.org/0000-0003-1602-8801","contributorId":354476,"corporation":false,"usgs":true,"family":"Arab","given":"Saeed","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":935743,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Schmidt, Gail L. 0000-0002-9684-8158 gschmidt@usgs.gov","orcid":"https://orcid.org/0000-0002-9684-8158","contributorId":3475,"corporation":false,"usgs":true,"family":"Schmidt","given":"Gail","email":"gschmidt@usgs.gov","middleInitial":"L.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":935744,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Crawford, Christopher J. 0000-0002-7145-0709 cjcrawford@usgs.gov","orcid":"https://orcid.org/0000-0002-7145-0709","contributorId":213607,"corporation":false,"usgs":true,"family":"Crawford","given":"Christopher J.","email":"cjcrawford@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":935745,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Gascon, Ferran","contributorId":173965,"corporation":false,"usgs":false,"family":"Gascon","given":"Ferran","email":"","affiliations":[{"id":27013,"text":"European Space Agency, Belgium","active":true,"usgs":false}],"preferred":false,"id":935746,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Strobl, Peter A.","contributorId":354478,"corporation":false,"usgs":false,"family":"Strobl","given":"Peter A.","affiliations":[{"id":54481,"text":"European Commission","active":true,"usgs":false}],"preferred":false,"id":935747,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Masek, Jeffrey G.","contributorId":197725,"corporation":false,"usgs":false,"family":"Masek","given":"Jeffrey","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":935748,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Neigh, Christopher S.R.","contributorId":354481,"corporation":false,"usgs":false,"family":"Neigh","given":"Christopher S.R.","affiliations":[{"id":7049,"text":"NASA Goddard Space Flight Center","active":true,"usgs":false}],"preferred":false,"id":935749,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}} ,{"id":70265860,"text":"70265860 - 2025 - Development of species-specific primers for the identification of Atlantic and shortnose sturgeons","interactions":[],"lastModifiedDate":"2025-04-28T15:15:19.546759","indexId":"70265860","displayToPublicDate":"2025-04-16T08:01:07","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1325,"text":"Conservation Genetics Resources","active":true,"publicationSubtype":{"id":10}},"title":"Development of species-specific primers for the identification of Atlantic and shortnose sturgeons","docAbstract":"Atlantic (Acipenser oxyrinchus oxyrinchus) and shortnose sturgeon (Acipenser brevirostrum) are broadly distributed along the Atlantic Coast of North America, where they use rivers, estuaries, and coastal habitats. In order to support management under the U.S. Endangered Species Act, it is important to understand when and where these fish occur. However, this presents a challenge as the two taxa are sometimes misidentified and some life stages (e.g., eggs) are challenging to identify with confidence. In this study, we used cytochrome b sequences to develop molecular primers to confirm the identity of shortnose and Atlantic sturgeon samples. We tested these primers using reference DNA samples for these two species. The results suggested that the primers were able to positively identify and distinguish Atlantic and shortnose sturgeon. The accuracy of the Atlantic sturgeon primers was 95.34%, whereas the accuracy of the shortnose sturgeon primers was 90.7%. Even though there were some individuals that were not positively identified as their corresponding species (false negatives), we did not observe any false positives. Our paper does not aim to develop eDNA markers; rather, the objective of our study was to create species-specific, unlabeled, and cost-effective primers which can be amplified using conventional PCR. The amplification product can be observed in a 2% agarose gel run through electrophoresis. This entire procedure is relatively inexpensive and involves basic instruments found in most conservation genetics laboratories.
","language":"English","publisher":"Springer Nature","doi":"10.1007/s12686-024-01376-0","usgsCitation":"Hyde, M., and Kazyak, D.C., 2025, Development of species-specific primers for the identification of Atlantic and shortnose sturgeons: Conservation Genetics Resources, v. 17, p. 59-65, https://doi.org/10.1007/s12686-024-01376-0.","productDescription":"7 p.","startPage":"59","endPage":"65","ipdsId":"IP-159855","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":484679,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"17","noUsgsAuthors":false,"publicationDate":"2025-04-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Hyde, Miluska Olivera 0000-0003-1465-3048","orcid":"https://orcid.org/0000-0003-1465-3048","contributorId":347141,"corporation":false,"usgs":true,"family":"Hyde","given":"Miluska Olivera","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":933769,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kazyak, David C. 0000-0001-9860-4045","orcid":"https://orcid.org/0000-0001-9860-4045","contributorId":140409,"corporation":false,"usgs":true,"family":"Kazyak","given":"David","email":"","middleInitial":"C.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":933770,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70265441,"text":"70265441 - 2025 - Anomalous shear stress variation in wet granular medium: Implications for landslide lateral faults","interactions":[],"lastModifiedDate":"2025-04-07T14:59:19.926401","indexId":"70265441","displayToPublicDate":"2025-04-16T07:55:07","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Anomalous shear stress variation in wet granular medium: Implications for landslide lateral faults","docAbstract":"Landslide assessments typically focus on the mechanical properties of the basal shear zone, but lateral faults are frequently overlooked, possibly due to their lower normal stresses and variably saturated conditions. Using double-cylinder shear experiments on wet granular systems as analogs for landslide lateral faults, we observe anomalous shear stress variations with fluid volume fractions, defying an expected unimodal relationship associated with capillary cohesion. At low fluid volume fractions, shear strength weakens as the wet grain assembly experiences reduced lateral pressure and increased boundary slip. This boundary slip subsequently vanishes, with an abrupt strengthening due to the dilation of the grain assembly against fluid surface tension as saturation approaches. Strike-slip motion and confinement in this system explain the strength anomaly, highlighting a critical role of lateral faults in landslide stability, particularly in cases where dynamics cannot be adequately explained by monitored pore-water pressure or basal friction.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2024GL113816","usgsCitation":"Chang, C., Ono, K., Schulz, W.H., and Yamaguchi, T., 2025, Anomalous shear stress variation in wet granular medium: Implications for landslide lateral faults: Geophysical Research Letters, v. 52, no. 7, e2024GL113816, 11 p., https://doi.org/10.1029/2024GL113816.","productDescription":"e2024GL113816, 11 p.","ipdsId":"IP-172400","costCenters":[{"id":78941,"text":"Geologic Hazards Science Center - Landslides / Earthquake Geology","active":true,"usgs":true}],"links":[{"id":488564,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2024gl113816","text":"Publisher Index Page"},{"id":484245,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"52","issue":"7","noUsgsAuthors":false,"publicationDate":"2025-04-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Chang, Chengrui","contributorId":353010,"corporation":false,"usgs":false,"family":"Chang","given":"Chengrui","affiliations":[{"id":7267,"text":"University of Tokyo","active":true,"usgs":false}],"preferred":false,"id":932733,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ono, Kohei","contributorId":353012,"corporation":false,"usgs":false,"family":"Ono","given":"Kohei","affiliations":[{"id":7267,"text":"University of Tokyo","active":true,"usgs":false}],"preferred":false,"id":932734,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schulz, William H. 0000-0001-9980-3580 wschulz@usgs.gov","orcid":"https://orcid.org/0000-0001-9980-3580","contributorId":942,"corporation":false,"usgs":true,"family":"Schulz","given":"William","email":"wschulz@usgs.gov","middleInitial":"H.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":932735,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Yamaguchi, Tetsuo","contributorId":353015,"corporation":false,"usgs":false,"family":"Yamaguchi","given":"Tetsuo","affiliations":[{"id":7267,"text":"University of Tokyo","active":true,"usgs":false}],"preferred":false,"id":932736,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70267832,"text":"70267832 - 2025 - Mercury trophic transfer to a freshwater biosentinel: Quantifying controlled bioaccumulation in larval dragonflies","interactions":[],"lastModifiedDate":"2025-07-10T14:48:56.758985","indexId":"70267832","displayToPublicDate":"2025-04-16T07:53:40","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1571,"text":"Environmental Toxicology and Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Mercury trophic transfer to a freshwater biosentinel: Quantifying controlled bioaccumulation in larval dragonflies","docAbstract":"Mercury bioavailability and biomagnification in freshwater systems can be highly variable; thus, tissue data from biosentinel taxa can be useful to assess risk. Dragonfly larvae have emerged as biological indicators of mercury impairment, yet their mercury biodynamics over time and across exposure levels are not well understood. Evaluating these attributes using controlled experimental approaches is an important step to validate larval dragonflies as biosentinels for spatial and temporal trends in mercury risk. We conducted an experimental series quantifying methylmercury trophic transfer from dosed prey to predatory dragonfly larvae at environmentally relevant concentrations. Dragonfly total mercury concentrations increased proportionally by factors of 2.7 to 4.2 with each doubling of prey methylmercury concentration, responding to dietary treatments in 7–28 days and reaching equilibrium in as little as 40 days, supporting their utility to indicate changing mercury exposure regimes. Dosed dragonflies biomagnified methylmercury by factors of 1.0 ± 0.1 to 3.4 ± 0.2 relative to their prey, and biomagnification efficiency decreased by over 40% for each doubling of prey methylmercury concentration. Dragonfly development had dose-dependent effects on bioaccumulation: mercury concentrations increased with growth and decreased with age in higher exposure treatments, whereas they decreased with growth and increased with age in lower exposure treatments. Bioaccumulation also varied taxonomically; within treatments, mean mercury concentrations for each genus varied up to 10% from family-level means. Dragonfly sex, size, and body condition did not significantly affect mercury concentrations. These results help validate and expand the utility of dragonfly larvae as biosentinels to monitor mercury risk and better protect wildlife and human health.","language":"English","publisher":"Oxford Academic","doi":"10.1093/etojnl/vgaf100","usgsCitation":"Sinclair, C.A., Garcia, T.S., Vasta, R., and Eagles-Smith, C., 2025, Mercury trophic transfer to a freshwater biosentinel: Quantifying controlled bioaccumulation in larval dragonflies: Environmental Toxicology and Chemistry, v. 44, no. 7, p. 1824-1834, https://doi.org/10.1093/etojnl/vgaf100.","productDescription":"11 p.","startPage":"1824","endPage":"1834","ipdsId":"IP-172263","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":490664,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/etojnl/vgaf100","text":"Publisher Index Page"},{"id":489458,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","county":"Benton County","otherGeospatial":"William L. Finley National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -123.38434279122359,\n 44.500601858064925\n ],\n [\n -123.38434279122359,\n 44.43616065782959\n ],\n [\n -123.30603623577454,\n 44.43616065782959\n ],\n [\n -123.30603623577454,\n 44.500601858064925\n ],\n [\n -123.38434279122359,\n 44.500601858064925\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"44","issue":"7","noUsgsAuthors":false,"publicationDate":"2025-04-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Sinclair, Cailin A","contributorId":340137,"corporation":false,"usgs":false,"family":"Sinclair","given":"Cailin","email":"","middleInitial":"A","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":939073,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Garcia, Tiffany S.","contributorId":171591,"corporation":false,"usgs":false,"family":"Garcia","given":"Tiffany","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":939074,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vasta, Rachel","contributorId":356293,"corporation":false,"usgs":false,"family":"Vasta","given":"Rachel","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":939075,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Eagles-Smith, Collin A. 0000-0003-1329-5285","orcid":"https://orcid.org/0000-0003-1329-5285","contributorId":221745,"corporation":false,"usgs":true,"family":"Eagles-Smith","given":"Collin A.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":939076,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70265700,"text":"sir20255003 - 2025 - Estimation of baseflow and flooding characteristics for East Canyon Creek, Summit and Morgan Counties, Utah","interactions":[],"lastModifiedDate":"2025-08-07T20:57:16.247704","indexId":"sir20255003","displayToPublicDate":"2025-04-16T07:09:29","publicationYear":"2025","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":"2025-5003","displayTitle":"Estimation of Baseflow and Flooding Characteristics for East Canyon Creek, Summit and Morgan Counties, Utah","title":"Estimation of baseflow and flooding characteristics for East Canyon Creek, Summit and Morgan Counties, Utah","docAbstract":"An improved understanding of hydrologic responses to changing climatic conditions is needed to better inform water management practices. East Canyon Creek, a perennial, snowmelt-dominated stream in the Wasatch Mountains of northern Utah, is subjected to increasing development and demands on water in the Snyderville Basin and adjacent areas. In this study, streamflow and specific conductance measured at three U.S. Geological Survey streamgages on East Canyon Creek were used to estimate daily baseflow for water years 2011–22. Trends in these estimates and correlations with climate data from two Natural Resource Conservation Service snow telemetry (SNOTEL) stations within the Snyderville Basin above East Canyon Reservoir, were quantified and reported. Peak annual streamflow also was assessed for flood potential on the study reach of East Canyon Creek. The hydrograph separations showed consistent baseflow indices among all sites, with a larger baseflow component during the fall–spring period (September–April; baseflow indices approximately equal to [≈] 0.751–0.835) and smaller component during the summer period (May–August; baseflow indices ≈ 0.428–0.532). In-stream specific conductance during spring (February–April) was influenced by road salt application, limiting the utility of the hydrograph separation approach. Annual streamflow and climate data were evaluated for trends using the nonparametric Mann–Kendall test, with inconclusive results. Related tests for trends, the Seasonal and Regional Kendall tests, were used to evaluate data at monthly timesteps and indicated a decreasing trend in total streamflow and baseflow at all streamgages. The rank-based Kendall’s tau test for correlation was used to measure the ordinal association with climatic data at co-located SNOTEL stations. Total streamflow and baseflow were strongly correlated with precipitation and snow-water equivalent. By incorporating a predictive regression model, the nonparametric Theil–Sen line, these correlations could support the development of streamflow forecast models using climate data from SNOTEL stations. Such models would provide water managers with tools to help make proactive decisions, such as reservoir or water reclamation releases and curtailment of withdrawals, in response to regional drought or varying snowpack and spring runoff in a given year.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255003","collaboration":"Prepared in cooperation with Snyderville Basin Water Reclamation District","usgsCitation":"Root, J.C., and Rumsey, C.A., 2025, Estimation of baseflow and flooding characteristics for East Canyon Creek, Summit and Morgan Counties, Utah: U.S. Geological Survey Scientific Investigations Report 2025–5003, 29 p., https://doi.org/10.3133/sir20255003.","productDescription":"Report: viii, 29 p.; Data Release","numberOfPages":"29","onlineOnly":"Y","ipdsId":"IP-162488","costCenters":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":493759,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118539.htm","linkFileType":{"id":5,"text":"html"}},{"id":484540,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P14SJDMX","text":"USGS data release","description":"Root, J.C., 2025, Baseflow estimation and trend and correlation analysis results for East Canyon Creek, Summit and Morgan Counties, Utah, 2010–2022: U.S. Geological Survey data release, https://doi.org/10.5066/P14SJDMX.","linkHelpText":"Baseflow estimation and trend and correlation analysis results for East Canyon Creek, Summit and Morgan Counties, Utah, 2010–2022"},{"id":484539,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5003/images"},{"id":484538,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5003/sir20255003.XML","description":"SIR 2025-5003 XML"},{"id":484537,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255003/full","linkFileType":{"id":5,"text":"html"},"description":"SIR 2025-5003 HTML"},{"id":484536,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5003/sir20255003.pdf","text":"Report","size":"8.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5003 PDF"},{"id":484535,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5003/coverthb.jpg"}],"country":"United States","state":"Utah","county":"Morgan County, Summit County","otherGeospatial":"East Canyon Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -111.85739630382633,\n 41.2514958778022\n ],\n [\n -111.85739630382633,\n 40.5798335667547\n ],\n [\n -110.91729451616551,\n 40.5798335667547\n ],\n [\n -110.91729451616551,\n 41.2514958778022\n ],\n [\n -111.85739630382633,\n 41.2514958778022\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director,
Utah Water Science Center
U.S. Geological Survey
2329 West Orton Circle
Salt Lake City, Utah 84119-2047
In 2023, an outbreak of highly pathogenic avian influenza occurred among critically endangered California condors (Gymnogyps californianus), and >21 died. We evaluated safety, immunogenicity, vaccination strategies, and correlates of antibody response of an influenza vaccine for poultry in black vultures (Coragyps atratus) and then California condors. We noted differences in antibody titers between vaccinated and unvaccinated birds (vultures p<0.004; condors p<0.02) but no adverse effects of vaccination. All vaccinated vultures and 80% of vaccinated condors showed maximum measured antibody response within the published range associated with survival of vaccinated and virally challenged chickens. We noted weak evidence of higher antibody responses for birds given two 0.5-mL vaccines versus those given one 1-mL vaccine but no correlation between antibody titers and sex for either species or between antibody titers and bone lead concentrations in vultures. Our results prompted initiation of a vaccination program for condors that could reduce spread of this disease among highly threatened species.
","language":"English","publisher":"U.S. Centers for Disease Control and Prevention","doi":"10.3201/eid3106.241558","usgsCitation":"Katzner, T., Blackford, A., Donahue, M., Gibbs, S.E., Lenoch, J.B., Martin, M.K., Rocke, T.E., Root, J.J., Styles, D., Cooper, S., Dean, K., Dvornicky-Raymond, Z., Keller, D., Sanchez, C., Dunlap, B., Grier, T., Jones, M., Nitzel, G., Patrick, E., Purcell, M., Specht, A., and Suarez, D.L., 2025, Safety and immunogenicity of poultry vaccine for protecting critically endangered avian species against highly pathogenic avian influenza virus, United States: Emerging Infectious Diseases, v. 31, no. 6, p. 1131-1139, https://doi.org/10.3201/eid3106.241558.","productDescription":"9 p.","startPage":"1131","endPage":"1139","ipdsId":"IP-171779","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":485999,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":490125,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3201/eid3106.241558","text":"Publisher Index Page"}],"volume":"31","issue":"6","noUsgsAuthors":false,"publicationDate":"2025-04-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Katzner, Todd E. 0000-0003-4503-8435 tkatzner@usgs.gov","orcid":"https://orcid.org/0000-0003-4503-8435","contributorId":191353,"corporation":false,"usgs":true,"family":"Katzner","given":"Todd E.","email":"tkatzner@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":933551,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Blackford, Ashleigh V.","contributorId":353436,"corporation":false,"usgs":false,"family":"Blackford","given":"Ashleigh V.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":933552,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Donahue, Mary","contributorId":353439,"corporation":false,"usgs":false,"family":"Donahue","given":"Mary","affiliations":[{"id":36658,"text":"U.S. Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":933553,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gibbs, Samantha E.J.","contributorId":225084,"corporation":false,"usgs":false,"family":"Gibbs","given":"Samantha","email":"","middleInitial":"E.J.","affiliations":[],"preferred":true,"id":933554,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lenoch, Julianna B.","contributorId":317921,"corporation":false,"usgs":false,"family":"Lenoch","given":"Julianna","email":"","middleInitial":"B.","affiliations":[{"id":69193,"text":"Wildlife Services National Wildlife Disease Program, Animal and Plant Health Inspections Service, USDA","active":true,"usgs":false}],"preferred":false,"id":933555,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Martin, Michael K.","contributorId":214245,"corporation":false,"usgs":false,"family":"Martin","given":"Michael","email":"","middleInitial":"K.","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":933556,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rocke, Tonie E. 0000-0003-3933-1563 trocke@usgs.gov","orcid":"https://orcid.org/0000-0003-3933-1563","contributorId":2665,"corporation":false,"usgs":true,"family":"Rocke","given":"Tonie","email":"trocke@usgs.gov","middleInitial":"E.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":933557,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Root, J. Jeffrey","contributorId":212847,"corporation":false,"usgs":false,"family":"Root","given":"J.","email":"","middleInitial":"Jeffrey","affiliations":[{"id":36589,"text":"USDA","active":true,"usgs":false}],"preferred":false,"id":933558,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Styles, Darren","contributorId":353440,"corporation":false,"usgs":false,"family":"Styles","given":"Darren","affiliations":[{"id":36658,"text":"U.S. Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":933559,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Cooper, Sunny","contributorId":353443,"corporation":false,"usgs":false,"family":"Cooper","given":"Sunny","affiliations":[{"id":84398,"text":"Carolina Raptor Center","active":true,"usgs":false}],"preferred":false,"id":933560,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Dean, Kristin","contributorId":353444,"corporation":false,"usgs":false,"family":"Dean","given":"Kristin","affiliations":[{"id":84398,"text":"Carolina Raptor Center","active":true,"usgs":false}],"preferred":false,"id":933561,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Dvornicky-Raymond, Zachary 0000-0001-9426-2631","orcid":"https://orcid.org/0000-0001-9426-2631","contributorId":353445,"corporation":false,"usgs":false,"family":"Dvornicky-Raymond","given":"Zachary","affiliations":[{"id":65735,"text":"San Diego Zoo Wildlife Alliance","active":true,"usgs":false}],"preferred":false,"id":933562,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Keller, Dominique","contributorId":353446,"corporation":false,"usgs":false,"family":"Keller","given":"Dominique","affiliations":[{"id":84401,"text":"Los Angeles Zoo and Botanical Garden","active":true,"usgs":false}],"preferred":false,"id":933563,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Sanchez, Carlos","contributorId":353447,"corporation":false,"usgs":false,"family":"Sanchez","given":"Carlos","affiliations":[{"id":18050,"text":"Oregon Zoo","active":true,"usgs":false}],"preferred":false,"id":933564,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Dunlap, Brett","contributorId":353448,"corporation":false,"usgs":false,"family":"Dunlap","given":"Brett","affiliations":[{"id":36658,"text":"U.S. Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":933565,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Grier, Thomas","contributorId":353449,"corporation":false,"usgs":false,"family":"Grier","given":"Thomas","affiliations":[{"id":13186,"text":"Purdue University","active":true,"usgs":false}],"preferred":false,"id":933566,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Jones, Michael P.","contributorId":353450,"corporation":false,"usgs":false,"family":"Jones","given":"Michael P.","affiliations":[{"id":84402,"text":"American Eagle Foundation","active":true,"usgs":false}],"preferred":false,"id":933567,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Nitzel, Gregory","contributorId":353451,"corporation":false,"usgs":false,"family":"Nitzel","given":"Gregory","affiliations":[{"id":84403,"text":"Zoetis Inc.","active":true,"usgs":false}],"preferred":false,"id":933568,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Patrick, Erin","contributorId":353452,"corporation":false,"usgs":false,"family":"Patrick","given":"Erin","affiliations":[{"id":36658,"text":"U.S. Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":933569,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Purcell, Maureen 0000-0003-0154-8433 mpurcell@usgs.gov","orcid":"https://orcid.org/0000-0003-0154-8433","contributorId":220163,"corporation":false,"usgs":true,"family":"Purcell","given":"Maureen","email":"mpurcell@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":933570,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Specht, Aaron J. 0000-0002-3342-1229","orcid":"https://orcid.org/0000-0002-3342-1229","contributorId":353453,"corporation":false,"usgs":false,"family":"Specht","given":"Aaron J.","affiliations":[{"id":13186,"text":"Purdue University","active":true,"usgs":false}],"preferred":false,"id":933571,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Suarez, David L.","contributorId":203570,"corporation":false,"usgs":false,"family":"Suarez","given":"David","email":"","middleInitial":"L.","affiliations":[{"id":36658,"text":"U.S. Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":933572,"contributorType":{"id":1,"text":"Authors"},"rank":22}]}} ,{"id":70266026,"text":"70266026 - 2025 - Relative abundance, seasonal occurrence, and distribution of marine birds in the northern Gulf of Mexico","interactions":[],"lastModifiedDate":"2025-08-04T15:39:01.205508","indexId":"70266026","displayToPublicDate":"2025-04-15T10:32:15","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2675,"text":"Marine Ornithology: Journal of Seabird Research and Conservation","onlineIssn":"2074-1235","printIssn":"1018-3337","active":true,"publicationSubtype":{"id":10}},"title":"Relative abundance, seasonal occurrence, and distribution of marine birds in the northern Gulf of Mexico","docAbstract":"Marine birds in the U.S. Gulf of Mexico have long been poorly studied. Given statutory obligations to protect migratory birds and endangered species, three broad-scale vessel and aerial programs initiated since 2010 have now surveyed the entire northern Gulf. Vessel coverage alone exceeds 700 d and 74,000 km of observer effort using 300-m strip transects. We supplemented these survey data with earlier, smaller-scale studies, eBird checklists, literature reviews, and other less accessible sources to create snapshot summaries of relative abundance, seasonal occurrence, and regional distribution for 117 taxa of marine and water birds reported from the northern Gulf (113 of which were substantiated with physical evidence). Using taxonomic and functional criteria, we identified 56 taxa characteristic of open shelf, slope, and pelagic waters (federal jurisdiction), 41 taxa with primarily coastal affinities (state and federal jurisdiction), and 20 taxa of sea and diving ducks. High species richness of marine birds in the northern Gulf is attributed to (1) a temperate-to-tropical gradient facilitating diverse marine environments year-round; (2) varied geographic origins of marine bird species using the Gulf; and (3) a mostly enclosed sea basin acting as a vagrant trap for wide-ranging species. Our taxonomic list and status updates seek to bridge information gaps for marine birds now subject to accelerated commercial uses of this region's continental shelf, including newly proposed offshore wind energy development. Other applications include guiding risk and vulnerability assessments of Gulf marine birds, providing core content for seabird observer training, and prioritizing environmental impact reviews and monitoring programs in offshore energy construction and operations plans.
","language":"English","publisher":"African Seabird Group/Pacific Seabird Group","doi":"10.5038/2074-1235.53.1.1634","usgsCitation":"Haney, J., Michael, P., Gleason, J.S., Wilson, R., Satgé, Y., Hixson, K.M., and Jodice, P.G., 2025, Relative abundance, seasonal occurrence, and distribution of marine birds in the northern Gulf of Mexico: Marine Ornithology: Journal of Seabird Research and Conservation, v. 53, p. 189-206, https://doi.org/10.5038/2074-1235.53.1.1634.","productDescription":"18 p.","startPage":"189","endPage":"206","ipdsId":"IP-164512","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":484987,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":493287,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5038/2074-1235.53.1.1634","text":"Publisher Index Page"}],"otherGeospatial":"Gulf of Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -99.06492683279039,\n 30.605180321059038\n ],\n [\n -99.06492683279039,\n 24.549635648982317\n ],\n [\n -81.11757130707277,\n 24.549635648982317\n ],\n [\n -81.11757130707277,\n 30.605180321059038\n ],\n [\n -99.06492683279039,\n 30.605180321059038\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"53","noUsgsAuthors":false,"publicationDate":"2025-04-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Haney, J. Christopher","contributorId":341154,"corporation":false,"usgs":false,"family":"Haney","given":"J. 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In this study we explore the origin of the two modes of degassing revealed by time-series gas data at Turrialba volcano (Costa Rica) in the context of new melt inclusion (MI) data. To reconstruct the c[CO2] of undegassed magma, we developed a rapid-quench piston-cylinder assembly to rehomogenize the vapor bubble commonly contained in MIs. We focus on olivine-hosted MIs from a mafic scoria sample erupted from Turrialba in 1864–1866. The reconstructed CO2 contents in MIs decrease from ∼4000 to <1000 ppmw as S contents decrease from 3500 to <1000 ppmw. The highest reconstructed S and CO2 in the MIs resulted in an initial magmatic CO2/ ST ratio (molar) of 0.83. Informed by the MI data, we modeled the decompression degassing of Turrialba magma and vapor composition using the Sulfur_X and EVo models. Instead of being controlled by initial magmatic CO2/ST ratio as suggested by previous studies, we find that the quiescent gas emitted from Turrialba during 2014–2018 (CO2/ ST = 2.3 ± 0.8, molar) appears to reflectequilibrium with magmas stored at 4–8 km (Sulfur_X) or 2 km (EVo) depth, when H2O is degassing extensively from the magma. A magma storage region at 4–8 km is also supported by seismic tomography. The second gas mode is noted by spikes in CO2/ ST ∼ 7.9 ± 2 in the weeks prior to eruption. This gas reflects equilibrium with a magma at 12–18 km (Sulfur_X) or 4–8 km (EVo), where the ascending magma is saturated with a CO2-rich vapor. Thus, there are two important trans crustal depths beneath the volcano: one where the rate of H2O loss from the magma and thus magma viscosity increases, and one at greater depths where high CO2/ST vapor forms and may facilitate dike propagation. We interpret the shallower, H2O-loss region as the main site of magma stalling and storage, where quiescent gas is generated continuously. We interpret the greater depth (12–18 km) as the source of the precursory gas that precedes eruption, and where the mafic melt lastly equilibrated with a mush zone before ascending and triggering eruption weeks later. This hypothesis is ripe for testing at other volcanoes that exhibit two modes in gas geochemistry.
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Joshua 0000-0003-4850-3953 erigler@usgs.gov","orcid":"https://orcid.org/0000-0003-4850-3953","contributorId":4367,"corporation":false,"usgs":true,"family":"Rigler","given":"E.","email":"erigler@usgs.gov","middleInitial":"Joshua","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":945478,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hartinger, Michael D.","contributorId":359453,"corporation":false,"usgs":false,"family":"Hartinger","given":"Michael","middleInitial":"D.","affiliations":[{"id":85815,"text":"Space Science Institute, Boulder, CO, USA","active":true,"usgs":false}],"preferred":false,"id":945479,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lucas, Greg M.","contributorId":359454,"corporation":false,"usgs":false,"family":"Lucas","given":"Greg","middleInitial":"M.","affiliations":[{"id":48584,"text":"Laboratory for Atmospheric and Space Physics, University of Colorado, Boulder, CO, USA","active":true,"usgs":false}],"preferred":false,"id":945480,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kelbert, Anna","contributorId":359455,"corporation":false,"usgs":false,"family":"Kelbert","given":"Anna","affiliations":[{"id":85814,"text":"Harvard-Smithsonian Center for Astrophysics, Cambridge, Massachusetts, 02138, USA","active":true,"usgs":false}],"preferred":false,"id":945481,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bedrosian, Paul A. 0000-0002-6786-1038 pbedrosian@usgs.gov","orcid":"https://orcid.org/0000-0002-6786-1038","contributorId":839,"corporation":false,"usgs":true,"family":"Bedrosian","given":"Paul","email":"pbedrosian@usgs.gov","middleInitial":"A.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":945482,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70272696,"text":"70272696 - 2025 - Assessing legacy nitrogen in groundwater using numerical models of the Long Island aquifer system, New York","interactions":[],"lastModifiedDate":"2025-12-04T15:01:52.627998","indexId":"70272696","displayToPublicDate":"2025-04-15T08:56:58","publicationYear":"2025","noYear":false,"publicationType":{"id":27,"text":"Preprint"},"publicationSubtype":{"id":32,"text":"Preprint"},"seriesTitle":{"id":18346,"text":"EarthArXiv","active":true,"publicationSubtype":{"id":32}},"title":"Assessing legacy nitrogen in groundwater using numerical models of the Long Island aquifer system, New York","docAbstract":"Nitrogen transported along groundwater flow paths in coastal aquifers can contribute substantially to nitrogen loading into surface water receptors, particularly in hydrologic systems dominated by groundwater discharge. Nitrogen entrained in the aquifer is a function of land use and associated nitrogen sources at the time of groundwater recharge, which may differ considerably from present-day sources. Legacy nitrogen can result in substantial discrepancies between observed present-day nitrogen loading to surface water receptors and loading estimated from present-day sources. Additionally, legacy nitrogen can continue to discharge into surface waters after nitrogen mitigation actions have been undertaken. Here, we use a numerical modeling framework to compare three methods of estimating time-varying historical nitrogen loads to four water bodies (receptors) on eastern Long Island, New York. The methods span a range of data requirements and process complexity, from instantaneous receptor loads calculated from steady-state groundwater contributing areas, to transient loads estimated by explicitly simulating legacy groundwater nitrogen transport over a century with large changes in nitrogen sources and hydrologic conditions. The effects of legacy nitrogen on estimated receptor loads varied temporally and spatially within the study area. Depending on antecedent nitrogen inputs and hydrologic conditions, historical annual nitrogen loads estimated from transient simulations accounting for legacy nitrogen can be quite similar (<10% difference) or substantially different (±100%) from those estimated from simpler instantaneous methods. Continued input of present-day nitrogen sources using methods that account for legacy nitrogen results in asymptotic increases in receptor nitrogen loads over time, indicating that simulated present-day receptor nitrogen loads are not in equilibrium with present-day inputs. For these receptors in disequilibrium, models simulating transient groundwater nitrogen transport could be used to account for legacy nitrogen lag times to help resource managers evaluate the potential effectiveness of proposed nitrogen mitigation actions.
","language":"English","publisher":"EarthArXiv","doi":"10.31223/X56Q8J","usgsCitation":"Jahn, K., and Walter, D.A., 2025, Assessing legacy nitrogen in groundwater using numerical models of the Long Island aquifer system, New York: EarthArXiv, https://doi.org/10.31223/X56Q8J.","productDescription":"38 p.","ipdsId":"IP-170367","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":497047,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Jahn, Kalle 0000-0002-4976-0137","orcid":"https://orcid.org/0000-0002-4976-0137","contributorId":333053,"corporation":false,"usgs":true,"family":"Jahn","given":"Kalle","email":"","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":951352,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Walter, Donald A. 0000-0003-0879-4477 dawalter@usgs.gov","orcid":"https://orcid.org/0000-0003-0879-4477","contributorId":1101,"corporation":false,"usgs":true,"family":"Walter","given":"Donald","email":"dawalter@usgs.gov","middleInitial":"A.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":951353,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70263947,"text":"70263947 - 2025 - From hydrated silica to quartz: Potential hydrothermal precipitates found in Jezero crater, Mars","interactions":[],"lastModifiedDate":"2025-03-03T15:32:48.429612","indexId":"70263947","displayToPublicDate":"2025-04-15T08:25:39","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1427,"text":"Earth and Planetary Science Letters","active":true,"publicationSubtype":{"id":10}},"title":"From hydrated silica to quartz: Potential hydrothermal precipitates found in Jezero crater, Mars","docAbstract":"On Earth, silica-rich phases from opal to quartz are important indicators and tracers of geological processes. Hydrated silica, such as opal, is a particularly good matrix for the preservation of molecular and macroscopic biosignatures. Cherts, a type of silica-dominated rocks, provide a unique archive of ancient terrestrial life while quartz is the emblematic mineral of the Earth's continental crust. On Mars, hydrated silica has been detected in several locations based on remote sensing and rover-based studies. In the present article we report on the detection of cobbles made of hydrated silica (opal or chalcedony), as well as well-crystallized quartz. These detections were made with the SuperCam instrument onboard Perseverance (Mars 2020 mission), using a combination of LIBS, infrared and Raman spectroscopy. Quartz-dominated stones are detected unambiguously for the first time on the Martian surface, and based on grain size and crystallinity are proposed to be of hydrothermal origin. Although these rocks were all found as float, we propose that these detections are part of a common hydrothermal system, and represent different depths / temperatures of precipitation. This attests that hydrothermal processes were active in and around Jezero crater, possibly triggered by the Jezero crater-forming impact. These silica-rich rocks, in particular opaline silica, are very promising targets for sampling and return to Earth given their high biosignature preservation potential.","language":"English","publisher":"Elsevier","doi":"10.1016/j.epsl.2025.119256","usgsCitation":"Beck, P., Beyssac, O., Dehouck, E., Bernard, S., Pineau, M., Mandon, L., Royer, C., Clave, E., Schroder, S., Forni, O., Francis, R., Mangold, N., Bedford, C., Broz, A., Cloutis, E., Johnson, J., Poulet, F., Fouchet, T., Quantin-Nataf, C., Pilorget, C., Rapin, W., Meslin, P., Gabriel, T.S., Arana, G., Madariaga, J., Brown, A., Maurice, S., Clegg, S.M., Gasnault, O., Cousin, A., Wiens, R., and The SuperCam Team, 2025, From hydrated silica to quartz: Potential hydrothermal precipitates found in Jezero crater, Mars: Earth and Planetary Science Letters, v. 656, 119256, 12 p., https://doi.org/10.1016/j.epsl.2025.119256.","productDescription":"119256, 12 p.","ipdsId":"IP-175708","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":487147,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.epsl.2025.119256","text":"Publisher Index Page"},{"id":482739,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"656","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Beck, P.S.A.","contributorId":223295,"corporation":false,"usgs":false,"family":"Beck","given":"P.S.A.","email":"","affiliations":[],"preferred":false,"id":929219,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Beyssac, O.","contributorId":290034,"corporation":false,"usgs":false,"family":"Beyssac","given":"O.","affiliations":[{"id":62313,"text":"Institut de Minéralogie, de Physique des Matériaux et de Cosmochimie, CNRS, Sorbonne Université","active":true,"usgs":false}],"preferred":false,"id":929220,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dehouck, E.","contributorId":290073,"corporation":false,"usgs":false,"family":"Dehouck","given":"E.","affiliations":[{"id":62330,"text":"Univ. 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To better understand current and future LSMPA value, we concurrently tracked nine species (seabirds, cetaceans, pelagic fishes, manta rays, reef sharks) at Palmyra Atoll and Kingman Reef (PKMPA) in the U.S. Pacific Islands Heritage Marine National Monument. PKMPA and the U.S. Exclusive Economic Zone encompassed 39% and 54% of species movements (n = 83; tracking duration range: 0.5–350 days), respectively. Species distribution models indicated 73% of PKMPA contained highly suitable habitat. Under two projected future scenarios (SSP 1–2.6, “Sustainability”; SSP 3–7.0, “Rocky Road”), strong sea surface temperature gradients initially could cause abrupt oceanic change resulting in predicted habitat loss in 2040–2050, followed by an equilibrium response and regained habitat by 2090–2100. Current and future suitable habitats were available adjacent to PKMPA, suggesting that increased MPA size could enhance protection. Our three-tiered approach combining animal tracking with publicly available remote sensing data and future projected environmental scenarios could be used to design, study, and monitor protected areas throughout the world. Holistic approaches that encompass diverse species and habitat use can enhance assessments of protected area designs. Animal telemetry and remote sensing may be helpful for ascertaining the extent to which other MPAs protect large mobile species in the future.
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