Established in 1935, the U.S. Geological Survey (USGS) Cooperative Fish and Wildlife Research Units Program is a unique cooperative partnership among State fish and wildlife agencies, host universities, the Wildlife Management Institute, USGS, and the U.S. Fish and Wildlife Service. Designed to meet the scientific needs of natural resource management agencies and to produce trained wildlife management professionals, the program has grown from the original nine wildlife-only Units to a program that, as of 2024, includes 43 Units located on university campuses in 41 States.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1545","programNote":"Ecosystems Mission Area, Cooperative Fish and Wildlife Research Units Program","usgsCitation":"Irwin, E.R., Murphy, C.E., Childs, D.E., Dennerline, D.E., and Mawdsley, J.R., 2025, Cooperative Fish and Wildlife Research Units Program—2023 Year-in-Review: U.S. Geological Survey Circular 1545, 123 p., https://doi.org/10.3133/cir1545.","productDescription":"vi, 123 p.","numberOfPages":"123","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-163351","costCenters":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"links":[{"id":465890,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/circ/1545/coverthb.jpg"},{"id":465891,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1545/cir1545.pdf","text":"Report","size":"98.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"CIR 1545 PDF"}],"contact":"Cooperative Research Units
U.S. Geological Survey
12201 Sunrise Valley Drive, Mail Stop 303
Reston, VA 20192
Director, National Civil Applications Center
National Land Imaging Program
U.S. Geological Survey
12201 Sunrise Valley Drive, MS 562
Reston, VA 20192
Email: cac@usgs.gov
","tableOfContents":"The U.S. Geological Survey is working with Federal land management agencies to develop a series of science syntheses to support National Environmental Policy Act (NEPA) analyses. This report synthesizes science information about the potential effects of nonmotorized recreation on ungulates in the western United States. We conducted a structured literature search to find published science, data, and analysis methods about the characteristics of nonmotorized recreation, ungulate exposure and response to nonmotorized recreation, and approaches to mitigate negative effects of nonmotorized recreation on ungulates. The sections of the report align with standard elements of the NEPA analysis process. We found that timing, intensity, duration, and spatial distribution of nonmotorized recreation are important factors to understand when assessing effects of recreation on ungulates. Several aspects of ungulate biology, which vary by species, population, and individual, affect ungulate susceptibility to effects from recreation, including diet, migration and movement, and seasonal biology. Techniques for assessing effects include basic spatial analyses based on buffers around trails and recreation sites and more technical analytical methods based on displacement or avoidance of recreation sites. Options for mitigating negative effects of nonmotorized recreation on ungulates include timing and type-of-use restrictions, recreator education, and project design features to avoid human-ungulate conflicts. Public land managers can use this report by incorporating it by reference in NEPA analyses or as a general reference to find literature or identify gaps in the literature about the effects of noise from nonmotorized recreation on ungulates.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/sir20255014","collaboration":"Prepared in cooperation with the Bureau of Land Management","usgsCitation":"Jordan, S.E., Ganz, T.R., Rutherford, T.K., Blocker, M.J., Domschke, C.T., Klasner, F.L., Masters, E.H., Morgan, T.A., Ratajczak, D.R., Teige, E.C., and Carter, S.K., 2025, Effects of nonmotorized recreation on ungulates in the western United States—A science synthesis to inform National Environmental Policy Act analyses: U.S. Geological Survey Scientific Investigations Report 2025–5014, 60 p., https://doi.org/10.3133/sir20255014.","productDescription":"x, 60 p.","onlineOnly":"Y","ipdsId":"IP-164198","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":489405,"rank":9,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255014/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":489396,"rank":8,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5014/sir20255014.xml","description":"SIR 2025-5014"},{"id":489395,"rank":7,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5014/images"},{"id":486381,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20235114","text":"Effects of Noise from Oil and Gas Development on Ungulates and Small Mammals—A Science Synthesis to Inform National Environmental Policy Act Analyses"},{"id":486387,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20245087","text":"Effects of Noise from Oil and Gas Development on Raptors and Songbirds—A Science Synthesis to Inform National Environmental Policy Act Analyses"},{"id":486378,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5014/coverthb2.jpg"},{"id":486382,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20235132","text":"Effects of Culverts on Habitat Connectivity in Streams—A Science Synthesis to Inform National Environmental Policy Act Analyses"},{"id":486379,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5014/sir20255014.pdf","text":"Report","size":"4.30 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5014"},{"id":486380,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/fs20243028","text":"Structured Science Syntheses to Inform Decision Making on Federal Public Lands"}],"contact":"Director, Fort Collins Science Center
U.S. Geological Survey
2150 Centre Ave., Bldg. C
Fort Collins, CO 80526-8118
The calcified structures of fishes provide insight into their periodic growth rates and can be combined with other biological variables to identify metrics such as size or age at maturity and mortality rates. Collecting this information on growth and life history can help evaluate the success of conservation efforts and inform future management decisions for a species in need. However, before these life history data can be applied to larger stock assessments that direct management decisions, confidence in the validity of the data needs to be reported through metrics of accuracy and precision. For this report, we assessed the bias and precision of paired reader estimations of spawning marks on scales of Blueback herring (Alosa aestivalis) collected in the U.S. Fish & Wildlife (USFWS) Annual Adult River Herring Stock Assessment for the lower Connecticut River basin. The paired reads on scales from a total of 8,698 fish over the ten years of the long term monitoring program were evaluated for the annual presence of systematic bias and precision using a combination of qualitative (i.e., frequency tables) and quantitative (i.e., Evan’s and Hoenig’s Test of Symmetry, and Coefficient of Variation (CV) calculations) analyses. While seven out of the ten survey years had systematic bias detected by the tests of symmetry, only three years (2013, 2016, 2018) had imprecision values >10% CV threshold. Data were further categorized into specific age classes within survey years to increase our resolution on where bias and imprecision was most prevalent. While the ability for accurate bias detection was limited by sufficient sample sizes (>25 fish), average imprecision values increased with age, and median age classes (4 through 6) commonly had bias detected. However, the removal of insufficient age classes prior to calculating average annual CV did not significantly change the initial average. Lastly, 2023, which was the first year to implement a standardized training procedure prior to production estimating, had the highest precision for both the annual average and specific age classes compared to all prior survey years. This standardized training procedure will continue to be used by USFWS for the lower Connecticut River tributaries, and can be modified for other river systems. Overall, this report’s results highlight the importance of assessing precision and encourage the standardization of spawning mark identification quality control and assurance for future studies. With more quality assessments and baseline information on precision and bias, there can be more beneficial discussion on defining thresholds and how to implement spawning history variability into catch curve analyses.
","language":"English","publisher":"U.S. Fish and Wildlife Service","doi":"10.3996/css36742600","usgsCitation":"Stephens, J.B., Jordaan, A., Perkins, D., Sprankle, K., and Roy, A.H., 2025, Quality assessment of past spawning mark estimations from a long-term survey in the Connecticut River watershed: Cooperator Science Series CSS-168-2025, ii, 72 p., https://doi.org/10.3996/css36742600.","productDescription":"ii, 72 p.","ipdsId":"IP-176656","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":494748,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Connecticut, Massachusetts","otherGeospatial":"Connecticut River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -72.96748212492314,\n 42.29494671693686\n ],\n [\n -72.95372317204433,\n 41.28995606733855\n ],\n [\n -72.16868601132036,\n 41.26947837383972\n ],\n [\n -72.16868601132036,\n 42.30090777357515\n ],\n [\n -72.96748212492314,\n 42.29494671693686\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2025-05-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Stephens, Jacqueline B.","contributorId":360502,"corporation":false,"usgs":false,"family":"Stephens","given":"Jacqueline","middleInitial":"B.","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":947139,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jordaan, Adrian","contributorId":257709,"corporation":false,"usgs":false,"family":"Jordaan","given":"Adrian","affiliations":[{"id":37201,"text":"UMass Amherst","active":true,"usgs":false}],"preferred":false,"id":947140,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Perkins, David","contributorId":342184,"corporation":false,"usgs":false,"family":"Perkins","given":"David","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":947141,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sprankle, Kenneth","contributorId":349559,"corporation":false,"usgs":false,"family":"Sprankle","given":"Kenneth","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":947142,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Roy, Allison H. 0000-0002-8080-2729 aroy@usgs.gov","orcid":"https://orcid.org/0000-0002-8080-2729","contributorId":4240,"corporation":false,"usgs":true,"family":"Roy","given":"Allison","email":"aroy@usgs.gov","middleInitial":"H.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":947143,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70267811,"text":"70267811 - 2025 - Monitoring visitor activity and informal trail disturbance in Yosemite Valley meadows to assess temporal changes in use and impacts","interactions":[],"lastModifiedDate":"2025-06-03T15:52:20.268589","indexId":"70267811","displayToPublicDate":"2025-05-22T08:47:23","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5520,"text":"Journal of Outdoor Recreation and Tourism","active":true,"publicationSubtype":{"id":10}},"title":"Monitoring visitor activity and informal trail disturbance in Yosemite Valley meadows to assess temporal changes in use and impacts","docAbstract":"Montane meadows provide vital habitat that supports ecosystems, regulate hydrological processes, and offer valuable recreational opportunities. Meadows account for 3 % of Yosemite National Park's area, including Yosemite Valley, and are particularly susceptible to human impacts such as formation of informal trails. We collected observational data on visitor activity and quantified social trail disturbance to compare with resource monitoring datasets and through similar parameters to Walden-Schreiner and Leung (2013) who studied visitor use and behavior in three Yosemite Valley meadows in 2011. We documented change in number of visitors per hour and primary activity pursued. We also compared trends of meadow disturbance (informal trail length and disturbed area) from the early 2000s - 2023. Informal trail length at El Capitan Meadow decreased from 2004 to 2018, followed by recent increases. Disturbed area for Cooks A, Sentinel A, Slaughterhouse B, Stoneman A, and Stoneman B sub-meadows increased from 2006 to 2023. Between 2011 and 2023, the proportion of those engaged in active versus stationary pursuits showed that visitors engaged in more active pursuits in two of three meadows. Moreover, there were >3.5 times more visitors per hour in Cooks, El Capitan, and Leidig meadows in 2023 compared to 2011, yet, most visitors utilized designated trails. Meadow locational context was linked to activity preference and types of impacts. Management strategies, such as fencing and signage have been effective at minimizing impacts in several meadows. Parsing nuances of informal trail use and drivers of disturbance for various meadows is crucial for informed park management decisions and actions.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jort.2025.100896","usgsCitation":"Shiflett, S., Jenkins, J., Mattos, R., Thiry, K., Ibsen, P.C., Booher, M., Tricomi, A., and Athearn, N.D., 2025, Monitoring visitor activity and informal trail disturbance in Yosemite Valley meadows to assess temporal changes in use and impacts: Journal of Outdoor Recreation and Tourism, v. 50, 100896, 13 p., https://doi.org/10.1016/j.jort.2025.100896.","productDescription":"100896, 13 p.","ipdsId":"IP-172211","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":490667,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jort.2025.100896","text":"Publisher Index Page"},{"id":489476,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Yosemite Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -119.73284138722612,\n 37.993305694720945\n ],\n [\n -119.73284138722612,\n 37.66294383877451\n ],\n [\n -119.39779065426013,\n 37.66294383877451\n ],\n [\n -119.39779065426013,\n 37.993305694720945\n ],\n [\n -119.73284138722612,\n 37.993305694720945\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"50","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Shiflett, Sheri A.","contributorId":347753,"corporation":false,"usgs":false,"family":"Shiflett","given":"Sheri A.","affiliations":[{"id":39509,"text":"National Park Service, Yosemite National Park","active":true,"usgs":false}],"preferred":false,"id":938991,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jenkins, Jeffery S.","contributorId":347754,"corporation":false,"usgs":false,"family":"Jenkins","given":"Jeffery S.","affiliations":[{"id":38695,"text":"University of California Merced","active":true,"usgs":false}],"preferred":false,"id":938992,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mattos, Rachel F.","contributorId":347755,"corporation":false,"usgs":false,"family":"Mattos","given":"Rachel F.","affiliations":[{"id":39509,"text":"National Park Service, Yosemite National Park","active":true,"usgs":false}],"preferred":false,"id":938993,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thiry, Kai","contributorId":356273,"corporation":false,"usgs":false,"family":"Thiry","given":"Kai","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":938994,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ibsen, Peter Christian 0000-0002-3436-9100","orcid":"https://orcid.org/0000-0002-3436-9100","contributorId":260735,"corporation":false,"usgs":true,"family":"Ibsen","given":"Peter","email":"","middleInitial":"Christian","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":938995,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Booher, Melissa","contributorId":356275,"corporation":false,"usgs":false,"family":"Booher","given":"Melissa","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":938996,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Tricomi, Angela","contributorId":356276,"corporation":false,"usgs":false,"family":"Tricomi","given":"Angela","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":938997,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Athearn, Nicole D","contributorId":221011,"corporation":false,"usgs":false,"family":"Athearn","given":"Nicole","email":"","middleInitial":"D","affiliations":[{"id":40310,"text":"NPS, Yosemite National Park, CA","active":true,"usgs":false}],"preferred":false,"id":938998,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70267107,"text":"fs20253027 - 2025 - Enhanced geothermal systems electric-resource assessment for the Great Basin, southwestern United States","interactions":[],"lastModifiedDate":"2025-08-07T21:23:21.965161","indexId":"fs20253027","displayToPublicDate":"2025-05-22T08:17:48","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-3027","displayTitle":"Enhanced Geothermal Systems Electric-Resource Assessment for the Great Basin, Southwestern United States","title":"Enhanced geothermal systems electric-resource assessment for the Great Basin, southwestern United States","docAbstract":"The U.S. Geological Survey recently (2025) completed a provisional assessment of the geothermal-electric resources associated with high-temperature, low-permeability rock formations of the Great Basin, Southwestern United States. If sufficient technological advances to commercialize enhanced geothermal systems occur, then a current best provisional estimate for electric-power generation capacity of 135 gigawatts electric are available from the upper 6 kilometers of the Earth’s crust. This estimate is a potential substantial increase of the installed geothermal electricity-generating capacity from <1 to 10 percent of current total U.S. power production capacity.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20253027","programNote":"Energy and Mineral Resources Mission Area—Energy Resources Program","usgsCitation":"Burns, E.R., Williams, C.F., and DeAngelo, J., 2025, Enhanced geothermal systems electric-resource assessment for the Great Basin, southwestern United States: U.S. Geological Survey Fact Sheet 2025–3027, 4 p. https://doi.org/10.3133/fs20253027.","productDescription":"Report: 4 p.; Data Release","numberOfPages":"4","ipdsId":"IP-177645","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":493778,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118578.htm","linkFileType":{"id":5,"text":"html"}},{"id":486026,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P14LU7WD","text":"USGS data release","description":"USGS data release","linkHelpText":"Data Estimating Enhanced Geothermal Systems (EGS) Electric-Resources for the Great Basin, USA"},{"id":486022,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2025/3027/fs20253027.pdf","text":"Report","size":"2.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2025-3027 PDF"},{"id":486021,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2025/3027/coverthb.jpg"}],"country":"United States","state":"California, Idaho, Nevada, Oregon, Utah","otherGeospatial":"Great Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -114.92749394923595,\n 35.49948391514789\n ],\n [\n -113.44714007770372,\n 37.284535141996415\n ],\n [\n -110.54433535091547,\n 41.018998252584026\n ],\n [\n -111.06210525110734,\n 43.04655379942898\n ],\n [\n -113.6957417348722,\n 42.704446111080244\n ],\n [\n -117.31076594348397,\n 42.992280758630415\n ],\n [\n -122.0302036294112,\n 43.77202682002738\n ],\n [\n -121.44656418460002,\n 40.43779341701659\n ],\n [\n -119.84395373047022,\n 38.18593468324721\n ],\n [\n -115.84611645924261,\n 34.46059631275067\n ],\n [\n -114.92749394923595,\n 35.49948391514789\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Geology, Minerals, Energy, & Geophysics Science Center
U.S. Geological Survey
Building 19, 350 N. Akron Rd.
P.O. Box 158
Moffett Field, CA 94035
Renibacterium salmoninarum, the cause of bacterial kidney disease (BKD), severely impacts salmonid populations. Much of our understanding of the BKD pathology in salmonids comes from evaluating fatal infections in wild populations or spawning Pacific Northwest salmonids. Our study investigated the histological progression and bacterial load dynamics of R. salmoninarum infection in Chinook salmon following intraperitoneal injection to enhance understanding of the disease’s dynamics. Seventy presmolt salmon were injected with the ATCC-33209 isolate of R. salmoninarum and monitored over 10 wk. Histological signs of disease were observed in spleen and liver tissues at 1 wk post-injection and in kidney tissues at 4 wk post-injection, with signs of disease increasing over time. Additionally, histopathological analysis revealed splenic and hepatic capsulitis (coelomitis), individual hepatocyte necrosis, progressive granulomatous hepatitis, splenitis, and nephritis with necrosis. Gram staining confirmed the presence of Gram-positive bacteria within macrophages and extracellularly in infected tissues. Quantitative PCR revealed significant increases in bacterial loads in both kidney and liver tissues over the study period, with higher bacterial loads observed in the kidney tissue. Bacterial load was strongly correlated with disease stage, with peak bacterial burdens coinciding with the most severe histological changes. Our study provides a comprehensive account of R. salmoninarum infection and disease progression in Chinook salmon after intraperitoneal injection.
","language":"English","publisher":"Inter-Research Science Publisher","doi":"10.3354/dao03852","usgsCitation":"Dils, R., Firestone, T., Schaffer, P., Winkelman, D.L., and Fetherman, E., 2025, Histological progression and bacterial load dynamics of Renibacterium salmoninarum in Chinook salmon Oncorhynchus tshawytscha: Diseases of Aquatic Organisms, v. 162, p. 85-97, https://doi.org/10.3354/dao03852.","productDescription":"13 p.","startPage":"85","endPage":"97","ipdsId":"IP-170058","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":490168,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/dao03852","text":"Publisher Index Page"},{"id":489379,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"162","noUsgsAuthors":false,"publicationDate":"2025-05-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Dils, Riley E.","contributorId":356264,"corporation":false,"usgs":false,"family":"Dils","given":"Riley E.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":938929,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Firestone, Tawni B.R.","contributorId":356266,"corporation":false,"usgs":false,"family":"Firestone","given":"Tawni B.R.","affiliations":[{"id":39887,"text":"Colorado Parks and Wildlife","active":true,"usgs":false}],"preferred":false,"id":938930,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schaffer, Paula A.","contributorId":356267,"corporation":false,"usgs":false,"family":"Schaffer","given":"Paula A.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":938931,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Winkelman, Dana L. 0000-0002-5247-0114 danaw@usgs.gov","orcid":"https://orcid.org/0000-0002-5247-0114","contributorId":4141,"corporation":false,"usgs":true,"family":"Winkelman","given":"Dana","email":"danaw@usgs.gov","middleInitial":"L.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":938932,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fetherman, Eric R.","contributorId":356269,"corporation":false,"usgs":false,"family":"Fetherman","given":"Eric R.","affiliations":[{"id":39887,"text":"Colorado Parks and Wildlife","active":true,"usgs":false}],"preferred":false,"id":938933,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70267233,"text":"fs20253023 - 2025 - Assessment of conventional and continuous oil and gas resources in the Mowry Composite Total Petroleum System in the Southwestern Wyoming Province, Wyoming, Colorado, and Utah, 2024","interactions":[],"lastModifiedDate":"2025-08-07T21:21:20.730288","indexId":"fs20253023","displayToPublicDate":"2025-05-21T11:45:00","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-3023","displayTitle":"Assessment of Conventional and Continuous Oil and Gas Resources in the Mowry Composite Total Petroleum System in the Southwestern Wyoming Province, Wyoming, Colorado, and Utah, 2024","title":"Assessment of conventional and continuous oil and gas resources in the Mowry Composite Total Petroleum System in the Southwestern Wyoming Province, Wyoming, Colorado, and Utah, 2024","docAbstract":"Using a geology-based assessment methodology, the U.S. Geological Survey estimated undiscovered, technically recoverable mean conventional and continuous resources of 473 million barrels of oil and 27 trillion cubic feet of gas in the Mowry Composite Total Petroleum System in the Southwestern Wyoming Province, Wyoming, Colorado, and Utah.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/fs20253023","programNote":"National and Global Petroleum Assessment","usgsCitation":"Hearon, J.S., Schenk, C.J., Gelman, S.E., Johnson, B.G., Lagesse, J.H., Mercier, T.J., Leathers-Miller, H.M., Timm, K.K., Drake, R.M., II, Cicero, A.D., and Le, P.A., 2025, Assessment of conventional and continuous oil and gas resources in the Mowry Composite Total Petroleum System in the Southwestern Wyoming Province, Wyoming, Colorado, and Utah, 2024: U.S. Geological Survey Fact Sheet 2025–3023, 4 p., https://doi.org/10.3133/fs20253023.","productDescription":"Report: 4 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-171719","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":493777,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118581.htm","linkFileType":{"id":5,"text":"html"}},{"id":486357,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/fs20253023/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"FS 2025-3023"},{"id":486076,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2025/3023/coverthb.jpg"},{"id":486080,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2025/3023/fs20253023.pdf","text":"Report","size":"1.50 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2025-3023"},{"id":486081,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1J8WGJG","text":"USGS data release","linkHelpText":"USGS National and Global Oil and Gas Assessment Project - Southwestern Wyoming Province, Mowry Shale Conventional and Continuous Assessment Unit Boundaries, Assessment Input Data, and Fact Sheet Data Tables"},{"id":486289,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2025/3023/images"},{"id":486290,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2025/3023/fs20253023.xml","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"FS 2025-3023"}],"country":"United States","state":"Colorado, Utah, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -110.93624300443219,\n 43.211509034130984\n ],\n [\n -110.93624300443219,\n 39.24100524328816\n ],\n [\n -106.08413558819743,\n 39.24100524328816\n ],\n [\n -106.08413558819743,\n 43.211509034130984\n ],\n [\n -110.93624300443219,\n 43.211509034130984\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
Denver, CO 80225-0046
The bedrock geology of the Bellows Falls 7.5- x 15-minute quadrangle, Vermont and New Hampshire, consists of polydeformed Ordovician to Devonian metasedimentary, metavolcanic, and metaplutonic rocks of the Connecticut Valley trough, Bronson Hill anticlinorium (or Bronson Hill terrane), and the Central Maine terrane. Previous work in this area includes a 1:62,500-scale published map and text (1946), State geologic maps of New Hampshire (1997) and Vermont (2011), and various maps and reports presented largely as parts of field trip guidebooks. A provisional open-file map of the geology of the Vermont part of the Bellows Falls 7.5- x 15-minute quadrangle, completed in 1997, is incorporated and revised on this map based on additional fieldwork.
This study recognizes three major structural levels from west to east and from lowest to highest: (1) autochthonous rocks of the Connecticut Valley trough; (2) allochthonous rocks of the New Hampshire sequence and Bronson Hill arc in the Monroe thrust sheet (or nappe), including the Skitchewaug nappe; and (3) allochthonous rocks of the Fall Mountain thrust sheet or nappe.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3535","collaboration":"Prepared in cooperation with the State of Vermont, Vermont Agency of Natural Resources, Vermont Geological Survey; and the State of New Hampshire, Department of Environmental Services, New Hampshire Geological Survey","usgsCitation":"Merschat, A.J., Walsh, G.J., Valley, P.M., McAleer, R.J., and Armstrong, T.R., 2025, Bedrock geologic map of the Bellows Falls 7.5- x 15-minute quadrangle, Windham and Windsor Counties, Vermont, and Sullivan and Cheshire Counties, New Hampshire: U.S. Geological Survey Scientific Investigations Map 3535, 2 sheets, scale 1:24,000, https://doi.org/10.3133/sim3535.","productDescription":"2 Sheets: 57.26 x 41.62 inches and 61.56 x 35.74 inches; Data Release","numberOfPages":"2","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-101604","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":493775,"rank":5,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118580.htm","linkFileType":{"id":5,"text":"html"}},{"id":486061,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3535/coverthb.jpg"},{"id":486062,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3535/sim3535_sheet1.pdf","text":"Sheet 1","size":"10.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3535 Sheet 1 PDF"},{"id":486063,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3535/sim3535_sheet2.pdf","text":"Sheet 2","size":"5.86 MB","description":"SIM 3535 Sheet 2 PDF"},{"id":486065,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P172BBFC","text":"USGS data release","linkHelpText":"Database for the bedrock geologic map of the Bellows Falls 7.5- x 15-Minute Quadrangle, Windham and Windsor Counties, Vermont, and Sullivan and Cheshire Counties, New Hampshire"}],"country":"United States","state":"New Hampshire, Vermont","county":"Cheshire County, Sullivan County, Windham County, Windsor County","otherGeospatial":"Bellows Falls 7.5- x 15-minute quadrangle","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -72.5,\n 43.25\n ],\n [\n -72.5,\n 43.125\n ],\n [\n -72.25,\n 43.125\n ],\n [\n -72.25,\n 43.25\n ],\n [\n -72.5,\n 43.25\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Florence Bascom Geoscience Center
U.S. Geological Survey
Mailstop 926A
12201 Sunrise Valley Drive
Reston, VA 20192
Foragers on patchy landscapes must acquire sufficient resources despite uncertainty in the location and amount of the resources. Optimal Foraging Theory posits that foragers deal with this uncertainty by using strategies that optimize resource intake within foraging periods. For species such as wading birds, this optimization is closely linked to their survival and reproductive success. Understanding the influence of patch selection on individual resource intake and foraging distribution is therefore crucial. In this study, we simulated how resource distribution, interference competition, and social cues—such as aggregation behaviors—influence resource intake and foraging spatial distribution. We employed an individual-based model simulating wading bird foraging behaviors, with 900 individuals simultaneously foraging across a landscape with unknown resource distribution. Birds employed one of three patch-finding strategies: random, cue-searching, or hybrid, which uses both searching strategies. Each bird decided whether to remain in a patch based on a prey density threshold. We compared the daily resource intake and foraging distribution of birds across different modeled patch-finding strategies, resource distribution patterns, and the presence or absence of interference competition. Wading birds exhibiting aggregation behavior displayed increased intake rates when resources were concentrated and interference minimal. Aggregation behavior led to a closer match with the ideal free distribution when the prey density threshold was optimal. These findings provide theoretical support that aggregation behavior is effective in scenarios where resources are concentrated in a few patches, social cues are used by relatively few individuals, and interference competition is limited.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolmodel.2025.111178","usgsCitation":"Lee, H.W., DeAngelis, D., Yurek, S., and Papastamatiou, Y., 2025, Foraging of wading birds on a patchy landscape: Simulating effects of social information, interference competition, and patch selection on prey intake and individual distribution: Ecological Modelling, v. 507, 111178, 14 p., https://doi.org/10.1016/j.ecolmodel.2025.111178.","productDescription":"111178, 14 p.","ipdsId":"IP-175552","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":491501,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolmodel.2025.111178","text":"Publisher Index Page"},{"id":491277,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"507","noUsgsAuthors":false,"publicationDate":"2025-05-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Lee, Hyo Won","contributorId":292184,"corporation":false,"usgs":false,"family":"Lee","given":"Hyo","email":"","middleInitial":"Won","affiliations":[{"id":7017,"text":"Florida International University","active":true,"usgs":false}],"preferred":false,"id":941239,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"DeAngelis, Donald L. 0000-0002-1570-4057","orcid":"https://orcid.org/0000-0002-1570-4057","contributorId":357336,"corporation":false,"usgs":false,"family":"DeAngelis","given":"Donald L.","affiliations":[{"id":7065,"text":"USGS emeritus","active":true,"usgs":false}],"preferred":false,"id":941240,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yurek, Simeon 0000-0002-6209-7915","orcid":"https://orcid.org/0000-0002-6209-7915","contributorId":216733,"corporation":false,"usgs":true,"family":"Yurek","given":"Simeon","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":941241,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Papastamatiou, Yannis P.","contributorId":356586,"corporation":false,"usgs":false,"family":"Papastamatiou","given":"Yannis P.","affiliations":[{"id":85026,"text":"Biological Sciences, Institute of Environment, Florida International University, 3000 NE 151st Street, 33181 North Miami (Florida), United States of America","active":true,"usgs":false}],"preferred":false,"id":941242,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70269943,"text":"70269943 - 2025 - White‐tailed deer habitat use and implications for chronic wasting disease transmission","interactions":[],"lastModifiedDate":"2025-08-07T16:31:26.329695","indexId":"70269943","displayToPublicDate":"2025-05-21T09:24:47","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3773,"text":"Wildlife Monographs","active":true,"publicationSubtype":{"id":10}},"title":"White‐tailed deer habitat use and implications for chronic wasting disease transmission","docAbstract":"Animal space use, activity patterns, and habitat selection—and heterogeneity in these patterns—have important implications for where and when infectious diseases are transmitted. White-tailed deer (Odocoileus virginianus) are habitat generalists, with a high degree of heterogeneity in their movement ecology based on sex, age, season, and region. These heterogeneities have important implications for the transmission and management of chronic wasting disease (CWD), which is a deadly prion disease transmitted both directly and indirectly through the environment. As such, favored deer habitats may promote direct interactions between conspecifics or indirect spatial overlap and subsequent environmental transmission. However, little is known about how individual animal space use translates to actual spatial overlap between individuals, leaving uncertainty in how habitat shapes the risk of direct or environmental CWD transmission. In this study, we evaluated seasonal activity patterns, home ranges, and habitat selection for 596 white-tailed deer in southwest Wisconsin, USA, from 2017-2022. We also estimated seasonal encounter distributions—regions where a pair of deer were most likely to encounter each other—for all pairs of deer putatively in different social groups (between-group) in our study, and quantified seasonal variation in the habitat composition of these areas. We found that deer selection for crops, pasture, or grasslands was generally low, relative to forest, but was highest in the post-fawning (summer) and non-breeding (winter) seasons. We observed similar patterns for the habitat composition of encounter distributions, suggesting that crops, pasture, and grasslands may be attractive resources that facilitate between-group transmission. Site fidelity between years was generally high; combined with small female home ranges in the fawning season, this implies that females likely re-use the same small, high-quality fawning habitats from year to year. We found that attraction toward between-group individuals was low during the post-fawning season but high during the breeding (fall) and non-breeding seasons. These results suggest that space use and habitat selection could shape the risk of environmental transmission in the fawning and post-fawning seasons, social selection could favor direct transmission risk in the breeding season, and combined social and habitat selection may shape risk of both direct and environmental transmission during the non-breeding season. We provide a detailed picture of the physiological and social drivers of deer movement through the year, with implications for CWD transmission and management.
","language":"English","publisher":"The Wildlife Society","doi":"10.1002/wmon.70001","usgsCitation":"Gilbertson, M.L., Ketz, A.C., Hunsaker, M.A., Walsh, D.P., Storm, D.J., and Turner, W.C., 2025, White‐tailed deer habitat use and implications for chronic wasting disease transmission: Wildlife Monographs, v. 217, no. 1, e70001, 47 p., https://doi.org/10.1002/wmon.70001.","productDescription":"e70001, 47 p.","ipdsId":"IP-168016","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":493807,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/wmon.70001","text":"Publisher Index Page"},{"id":493726,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Iowa, Wisconsin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -91.29506381028423,\n 43.10642465075958\n ],\n [\n -91.29506381028423,\n 42.78719726813827\n ],\n [\n -90.43353604760068,\n 42.78719726813827\n ],\n [\n -90.43353604760068,\n 43.10642465075958\n ],\n [\n -91.29506381028423,\n 43.10642465075958\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"217","issue":"1","noUsgsAuthors":false,"publicationDate":"2025-05-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Gilbertson, Marie L.J.","contributorId":359152,"corporation":false,"usgs":false,"family":"Gilbertson","given":"Marie","middleInitial":"L.J.","affiliations":[{"id":16925,"text":"University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":944997,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ketz, Alison C.","contributorId":359154,"corporation":false,"usgs":false,"family":"Ketz","given":"Alison","middleInitial":"C.","affiliations":[{"id":85750,"text":"Funga","active":true,"usgs":false}],"preferred":false,"id":944998,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hunsaker, Matthew A.","contributorId":359155,"corporation":false,"usgs":false,"family":"Hunsaker","given":"Matthew","middleInitial":"A.","affiliations":[{"id":16925,"text":"University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":944999,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Walsh, Daniel P. 0000-0002-7772-2445","orcid":"https://orcid.org/0000-0002-7772-2445","contributorId":219539,"corporation":false,"usgs":true,"family":"Walsh","given":"Daniel","email":"","middleInitial":"P.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":945000,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Storm, Daniel J.","contributorId":359157,"corporation":false,"usgs":false,"family":"Storm","given":"Daniel","middleInitial":"J.","affiliations":[{"id":6913,"text":"Wisconsin Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":945001,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Turner, Wendy Christine 0000-0002-0302-1646","orcid":"https://orcid.org/0000-0002-0302-1646","contributorId":287053,"corporation":false,"usgs":true,"family":"Turner","given":"Wendy","email":"","middleInitial":"Christine","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":945002,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70267725,"text":"70267725 - 2025 - Bayesian ETAS modeling for the Pacific Northwest: Uncovering effects of tectonic regimes, regional differences, and swarms on aftershock parameters","interactions":[],"lastModifiedDate":"2025-09-22T15:18:36.884038","indexId":"70267725","displayToPublicDate":"2025-05-21T09:23:08","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Bayesian ETAS modeling for the Pacific Northwest: Uncovering effects of tectonic regimes, regional differences, and swarms on aftershock parameters","docAbstract":"The Pacific Northwest (PNW) of North America has high seismic hazard due to numerous earthquake sources under populated areas. It hosts several tectonic regimes and subregional seismic zones that are hypothesized to have different patterns of earthquake and aftershock occurrence. It is also predisposed to earthquake swarms, which can complicate the statistical modeling of these patterns. We present the first statistical seismicity model of the PNW catalog using the epidemic‐type aftershock sequence (ETAS) framework. We develop a Bayesian inference procedure that provides a stable estimation of both ETAS parameters and their uncertainties for different sets of PNW earthquakes, even those with very sparse catalogs. The Bayesian approach allows us to investigate how parameter estimates change between the intraslab and crustal tectonic regimes, the northern and southern PNW, and when swarms are included and excluded from the catalog. We also utilize our Bayesian framework to calculate parameter estimates under different prior beliefs about PNW seismicity, as well as to propagate catalog measurement errors into ETAS parameter estimates. We discuss the implications of parameter differences across the region for aftershock forecasting for the PNW.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120240249","usgsCitation":"Schneider, M., Barall, M., Guttorp, P., Hardebeck, J.L., Michael, A.J., Page, M.T., and van der Elst, N., 2025, Bayesian ETAS modeling for the Pacific Northwest: Uncovering effects of tectonic regimes, regional differences, and swarms on aftershock parameters: Bulletin of the Seismological Society of America, v. 115, no. 5, p. 2219-2236, https://doi.org/10.1785/0120240249.","productDescription":"18 p.","startPage":"2219","endPage":"2236","ipdsId":"IP-170994","costCenters":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":486723,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Pacific Northwest","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -133.48546091610666,\n 52.60993149081935\n ],\n [\n -127.12402970642239,\n 39.04184775255658\n ],\n [\n -117.3837323841093,\n 39.378962497073985\n ],\n [\n -117.06660127855778,\n 51.3962329850375\n ],\n [\n -133.48546091610666,\n 52.60993149081935\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"115","issue":"5","noUsgsAuthors":false,"publicationDate":"2025-05-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Schneider, Max 0000-0003-2945-7904","orcid":"https://orcid.org/0000-0003-2945-7904","contributorId":340346,"corporation":false,"usgs":true,"family":"Schneider","given":"Max","email":"","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":938651,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barall, Michael 0000-0001-7724-8563 mbarall@usgs.gov","orcid":"https://orcid.org/0000-0001-7724-8563","contributorId":271197,"corporation":false,"usgs":true,"family":"Barall","given":"Michael","email":"mbarall@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":938652,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Guttorp, Peter","contributorId":350934,"corporation":false,"usgs":false,"family":"Guttorp","given":"Peter","affiliations":[{"id":83880,"text":"Norwegian Computing Center","active":true,"usgs":false}],"preferred":false,"id":938653,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hardebeck, Jeanne L. 0000-0002-6737-7780","orcid":"https://orcid.org/0000-0002-6737-7780","contributorId":254964,"corporation":false,"usgs":true,"family":"Hardebeck","given":"Jeanne","email":"","middleInitial":"L.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":938654,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Michael, Andrew J. 0000-0002-2403-5019 michael@usgs.gov","orcid":"https://orcid.org/0000-0002-2403-5019","contributorId":1280,"corporation":false,"usgs":true,"family":"Michael","given":"Andrew","email":"michael@usgs.gov","middleInitial":"J.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":true,"id":938655,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Page, Morgan T. 0000-0001-9321-2990 mpage@usgs.gov","orcid":"https://orcid.org/0000-0001-9321-2990","contributorId":3762,"corporation":false,"usgs":true,"family":"Page","given":"Morgan","email":"mpage@usgs.gov","middleInitial":"T.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":true,"id":938656,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"van der Elst, Nicholas 0000-0002-3812-1153 nvanderelst@usgs.gov","orcid":"https://orcid.org/0000-0002-3812-1153","contributorId":147858,"corporation":false,"usgs":true,"family":"van der Elst","given":"Nicholas","email":"nvanderelst@usgs.gov","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":938657,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70270741,"text":"70270741 - 2025 - Reconciling scale using the Resist-Accept-Direct (RAD) Framework to improve management of woody encroachment in grasslands","interactions":[],"lastModifiedDate":"2025-08-22T16:28:13.594774","indexId":"70270741","displayToPublicDate":"2025-05-21T09:19:19","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2258,"text":"Journal of Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Reconciling scale using the Resist-Accept-Direct (RAD) Framework to improve management of woody encroachment in grasslands","docAbstract":"Implementing strategies to navigate large-scale ecological transitions in grasslands is one of this century's greatest conservation challenges. In the US Great Plains, managing areas impacted by woody transitions have been reactive, short-lived, costly, and ineffective. Along with current technological innovation in rangeland monitoring, the promise of early warning science is to provide managers with sufficient time to be better prepared for novel signals of ecological change. Combining the science of early warning signals and frameworks such as the Resist – Accept – Direct (RAD) can provide land managers with guidelines to identify proactive strategies when facing ecological change. Using this approach, we found that opportunities to resist woody transitions decreased from 84 % to 60 % between 1990 and 2020 over the entire biome but remained highest in the northern and western Great Plains, which contributes to large scale conservation targets. These are key areas to prioritize resist opportunities. In contrast, 11 % of the biome exhibited early warning transition signals across all hierarchical scales by 2020, a fourfold increase since 1990. Lastly by 2020, 30 % of the biome exhibited early warning signals across multiple but not all scales. Here, efforts may be more effective when management is directed to conserve fragmented grassland legacies within a woody-dominated matrix and avoid large-scale monocultures of problematic encroaching woody species. Our multi-scale study indicates that 1) anchoring to the last remaining grassland core areas with no early warning of transitions and 2) strategically investing in these intact grasslands may provide the best results for grassland conservation.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jenvman.2025.125820","usgsCitation":"Scholtz, R., Uden, D.R., Allred, B.W., Donovan, V.M., Maestas, J.D., Morford, S.L., Jones, M.O., Naugle, D.E., Cady, S.M., Fogarty, D.T., Metcalf, A.L., Chaffin, B.C., Allen, C., Roberts, C.P., Rowen, E., Meredith, G.R., Nesbitt, H.K., Williamson, M.A., Gulab, S., Hamlin, S., Lohani, S., and Twidwell, D., 2025, Reconciling scale using the Resist-Accept-Direct (RAD) Framework to improve management of woody encroachment in grasslands: Journal of Environmental Management, v. 387, 125820, 13 p., https://doi.org/10.1016/j.jenvman.2025.125820.","productDescription":"125820, 13 p.","ipdsId":"IP-168014","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":495046,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jenvman.2025.125820","text":"Publisher Index Page"},{"id":494535,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Great Plains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -107.39454653811954,\n 49.16869841050328\n ],\n [\n -100.97208373500898,\n 43.309178424283424\n ],\n [\n -103.19994315323261,\n 33.825943793220816\n ],\n [\n -94.82473255675053,\n 32.84125885561559\n ],\n [\n -92.36737038374883,\n 43.37515219536034\n ],\n [\n -96.44583898768245,\n 48.95049791474963\n ],\n [\n -107.39454653811954,\n 49.16869841050328\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"387","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Scholtz, 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Nebraska","active":true,"usgs":false}],"preferred":false,"id":946970,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Meredith, Gwendwr R.","contributorId":195701,"corporation":false,"usgs":false,"family":"Meredith","given":"Gwendwr","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":946971,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Nesbitt, Holly K.","contributorId":360327,"corporation":false,"usgs":false,"family":"Nesbitt","given":"Holly","middleInitial":"K.","affiliations":[{"id":16201,"text":"Boise State University","active":true,"usgs":false}],"preferred":false,"id":946972,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Williamson, Matthew A.","contributorId":360328,"corporation":false,"usgs":false,"family":"Williamson","given":"Matthew","middleInitial":"A.","affiliations":[{"id":16201,"text":"Boise State University","active":true,"usgs":false}],"preferred":false,"id":946973,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Gulab, Sabrina","contributorId":360329,"corporation":false,"usgs":false,"family":"Gulab","given":"Sabrina","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":946974,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Hamlin, Samantha","contributorId":360330,"corporation":false,"usgs":false,"family":"Hamlin","given":"Samantha","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":946975,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Lohani, Sapana","contributorId":360331,"corporation":false,"usgs":false,"family":"Lohani","given":"Sapana","affiliations":[{"id":86000,"text":"William and Mary","active":true,"usgs":false}],"preferred":false,"id":946976,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Twidwell, Dirac","contributorId":341491,"corporation":false,"usgs":false,"family":"Twidwell","given":"Dirac","affiliations":[{"id":16610,"text":"University of Nebraska-Lincoln","active":true,"usgs":false}],"preferred":false,"id":946978,"contributorType":{"id":1,"text":"Authors"},"rank":22}]}} ,{"id":70267676,"text":"70267676 - 2025 - Linking fire radiative power to land cover, fire history, and environmental setting in Alaska, 2003–2022","interactions":[],"lastModifiedDate":"2025-05-29T14:11:26.313587","indexId":"70267676","displayToPublicDate":"2025-05-21T09:06:54","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2083,"text":"International Journal of Wildland Fire","active":true,"publicationSubtype":{"id":10}},"title":"Linking fire radiative power to land cover, fire history, and environmental setting in Alaska, 2003–2022","docAbstract":"Fire radiative power (FRP) shows promise as a diagnostic and predictive indicator of fire behavior and post-fire effects in Alaska, USA.
To investigate relationships between FRP, vegetation functional groups, and environmental settings in Alaska (2003–2022) under various fire history conditions.
We tested for distinctness of MODIS FRP distributions associated with vegetation classes and fire legacies (frequency and number of previous burns). We used a random forest model to examine relative importance of vegetation class for FRP versus bottom-up biophysical and temporal parameters.
FRP distributions are statistically distinct among vegetation functional groups with contrasting fuel biomass, or within functional groups with contrasting burn characteristics. Location and topography, which constrain vegetation class, strongly determine FRP, and fire history is of lesser importance over the 19-year analysis period.
FRP can be used to identify wildfire consumption in dissimilar vegetation classes but is highly conditioned by geographic location. The complex and evolving vegetation composition of post-fire boreal landscapes precludes a clear association of expected FRP at distinct stages of recovery.
These results can inform further study of FRP as an indicator of fire behavior and fuel consumption and for informing dynamics of post-fire recovery across Alaska.
Digital flood-inundation map libraries for two reaches that constitute 14.8 miles of Little and Big Papillion Creeks in Omaha, Nebraska, were created by the U.S. Geological Survey (USGS) in cooperation with the Papio-Missouri River Natural Resource District. The flood-inundation maps, which can be accessed through the USGS Flood Inundation Mapping Program website at https://www.usgs.gov/mission-areas/water-resources/science/flood-inundation-mapping-fim-program, depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at Little Papillion Creek at Irvington, Nebr. (USGS station 06610750), Little Papillion Creek at Ak-Sar-Ben at Omaha, Nebr. (USGS station 06610765), and Big Papillion Creek at Q Street at Omaha, Nebr. (USGS station 06610770) streamgages. Near-real-time stages at these streamgages may be obtained from the USGS National Water Information System database at https://doi.org/10.5066/F7P55KJN or from the National Weather Service Advanced Hydrologic Prediction Service at https://water.weather.gov/ahps/.
Flood profiles were computed for two different reaches that constitute 14.8 miles of stream length in the study area by using hydraulic models. The models were calibrated by adjusting roughness coefficients to best represent the current (2022) stage-streamflow relation at the streamgages within the study reach.
The hydraulic models were then used to compute water-surface profiles at 1-foot stage intervals for selected stage ranges to represent various flooding scenarios at the streamgages in each reach. The simulated water-surface profiles then were combined with a digital elevation model using a geographic information system, which had a 10-foot grid spacing to delineate the flooding extents and water depths for each stage. The availability of these flood-inundation maps, along with information regarding current stage from the USGS streamgages, can provide emergency management personnel and residents with information that is critical for flood response activities and post flood recovery efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255032","collaboration":"Prepared in cooperation with the Papio-Missouri River Natural Resource District","usgsCitation":"Strauch, K.R., and Hoefer, B.R., 2025, Flood-inundation maps for 14.8 miles of Little and Big Papillion Creeks in Omaha, Nebraska, 2023: U.S. Geological Survey Scientific Investigations Report 2025–5032, 14 p., https://doi.org/10.3133/sir20255032.","productDescription":"Report: vi, 14 p.; Data Release; Dataset","numberOfPages":"24","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-152753","costCenters":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"links":[{"id":493771,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118579.htm","linkFileType":{"id":5,"text":"html"}},{"id":485915,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5032/coverthb.jpg"},{"id":485916,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5032/sir20255032.pdf","text":"Report","size":"2.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5032"},{"id":485920,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5032/sir20255032.XML"},{"id":485921,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5032/images/"},{"id":485922,"rank":5,"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":485923,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9OU7E42","text":"USGS data release","linkHelpText":"Flood-inundation geospatial datasets for 14.8 miles of the Little and Big Papillion Creeks in Omaha, Nebraska, 2023"},{"id":485924,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255032/full"}],"country":"United States","state":"Nebraska","city":"Omaha","otherGeospatial":"Little and Big Papillion Creeks","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -96.15305796306968,\n 41.36725587936067\n ],\n [\n -96.15305796306968,\n 41.117996650104345\n ],\n [\n -95.92667071234595,\n 41.117996650104345\n ],\n [\n -95.92667071234595,\n 41.36725587936067\n ],\n [\n -96.15305796306968,\n 41.36725587936067\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
The Von Damm vent field (VDVF) on the Mid-Cayman Rise in the Caribbean Sea is unique among modern hydrothermal systems in that the chimneys and mounds are almost entirely composed of talc. We analyzed samples collected in 2020 and report that in addition to disordered talc of variable crystallinity, carbonates are a major class of mineral at VDVF. The carbonate minerals include aragonite, calcite, magnesium-rich calcite, and dolomite. Talc and carbonate mineral textures indicate that, rather than replacing volcanic host rock, they precipitate from the mixing of hydrothermal fluids and seawater at the seafloor, occurring in chimneys and surrounding rubble. Alternating precipitation of this mineral assemblage is pervasive, with carbonate minerals typically being succeeded by talc, and with indications that in some cases talc and carbonate minerals replace one another. Stable carbon isotopic data indicate the carbonate minerals originate from the mixing of seawater and hydrothermal fluid, which is supported by U-Th data. Radiocarbon calcite ages and talc 234U-230Th isochron ages indicate mineral ages spanning over thousands to tens of thousands of years. Analyses of these samples illustrate a dynamic system that transitions from carbonate-dominated to Mg-silicate−dominated precipitation over time scales of thousands of years. Our observations raise questions regarding the eventual fate of seafloor precipitates and whether carbonate and silicate minerals in such settings are sequestered and represented in the rock record.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/G53228.1","usgsCitation":"Gartman, A., Blackburn, T., Frank, K., Lang, S., and Seewald, J., 2025, Kiloyear cycles of carbonate and Mg-silicate replacement at Von Damm hydrothermal vent field: Geology, v. 53, no. 8, p. 668-672, https://doi.org/10.1130/G53228.1.","productDescription":"5 p.","startPage":"668","endPage":"672","ipdsId":"IP-168945","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":486283,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":487010,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/g53228.1","text":"Publisher Index Page"}],"volume":"53","issue":"8","noUsgsAuthors":false,"publicationDate":"2025-05-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Gartman, Amy 0000-0001-9307-3062 agartman@usgs.gov","orcid":"https://orcid.org/0000-0001-9307-3062","contributorId":177057,"corporation":false,"usgs":true,"family":"Gartman","given":"Amy","email":"agartman@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":938045,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Blackburn, Terrence 0000-0003-0029-0709","orcid":"https://orcid.org/0000-0003-0029-0709","contributorId":259241,"corporation":false,"usgs":false,"family":"Blackburn","given":"Terrence","email":"","affiliations":[{"id":6949,"text":"University of California, Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":938046,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Frank, Kiana","contributorId":355717,"corporation":false,"usgs":false,"family":"Frank","given":"Kiana","affiliations":[{"id":39036,"text":"University of Hawaii at Manoa","active":true,"usgs":false}],"preferred":false,"id":938047,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lang, Susan Q.","contributorId":355719,"corporation":false,"usgs":false,"family":"Lang","given":"Susan Q.","affiliations":[{"id":36711,"text":"Woods Hole Oceanographic Institution","active":true,"usgs":false}],"preferred":false,"id":938048,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Seewald, Jeffrey S.","contributorId":58758,"corporation":false,"usgs":true,"family":"Seewald","given":"Jeffrey S.","affiliations":[],"preferred":false,"id":938049,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70270607,"text":"70270607 - 2025 - Negative growth in body mass of trout and salmon in a small stream network","interactions":[],"lastModifiedDate":"2025-08-21T16:10:47.579059","indexId":"70270607","displayToPublicDate":"2025-05-20T09:02:37","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Negative growth in body mass of trout and salmon in a small stream network","docAbstract":"In species inhabiting stressful environments, some individuals experience negative growth in body mass during their lives, potentially influencing survival, reproduction, populations, and ecosystems. Using data from a long-term (1997–2015) study of brook trout (Salvelinus fontinalis), brown trout (Salmo trutta), and juvenile Atlantic salmon (Salmo salar) in Massachusetts, USA, we analyzed the frequency, causes, and consequences of seasonal mass loss. Negative growth occurred in 14.8% of observations (3573 instances), with the highest prevalence during summer (June–September). Species differed markedly: 42.5% of juvenile Atlantic salmon, 24.9% of brook trout, but only 7.7% of brown trout exhibited negative growth. The likelihood of mass loss increased with size, age, and low stream flows, particularly in summer. Brook trout in the small or isolated tributaries exhibited less summer mass loss than those in the larger streams. Other factors, including temperature and population density, had minimal or inconsistent effects. Individuals experiencing negative growth, especially brook trout in summer and autumn, were less likely to be re-encountered. As we observed no association of mass loss with movement, this suggests a potential survival cost of negative body mass growth.
","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2024-0376","usgsCitation":"Letcher, B., Nislow, K., O’Donnell, M., Hayden, M.J., and Dubreuil, T., 2025, Negative growth in body mass of trout and salmon in a small stream network: Canadian Journal of Fisheries and Aquatic Sciences, v. 82, p. 1-14, https://doi.org/10.1139/cjfas-2024-0376.","productDescription":"14 p.","startPage":"1","endPage":"14","ipdsId":"IP-171146","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":501009,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hdl.handle.net/1807/144649","text":"External Repository"},{"id":494396,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"82","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Letcher, Benjamin H. 0000-0003-0191-5678","orcid":"https://orcid.org/0000-0003-0191-5678","contributorId":315442,"corporation":false,"usgs":true,"family":"Letcher","given":"Benjamin H.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":946666,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nislow, Keith","contributorId":201434,"corporation":false,"usgs":false,"family":"Nislow","given":"Keith","affiliations":[{"id":27110,"text":"U.S. Dept of Agriculture, Forest Service","active":true,"usgs":false}],"preferred":false,"id":946667,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"O’Donnell, Matthew 0000-0002-9089-2377 mjodonnell@usgs.gov","orcid":"https://orcid.org/0000-0002-9089-2377","contributorId":167315,"corporation":false,"usgs":true,"family":"O’Donnell","given":"Matthew","email":"mjodonnell@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":946668,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hayden, Michael J. 0000-0002-9010-6831","orcid":"https://orcid.org/0000-0002-9010-6831","contributorId":291388,"corporation":false,"usgs":true,"family":"Hayden","given":"Michael","middleInitial":"J.","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":946762,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dubreuil, Todd 0000-0003-0189-4336","orcid":"https://orcid.org/0000-0003-0189-4336","contributorId":217872,"corporation":false,"usgs":true,"family":"Dubreuil","given":"Todd","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":946670,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70267294,"text":"sir20255016 - 2025 - Flood of July 2023 in Vermont","interactions":[],"lastModifiedDate":"2025-08-07T21:13:56.630851","indexId":"sir20255016","displayToPublicDate":"2025-05-19T14:50:00","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":"2025-5016","displayTitle":"Flood of July 2023 in Vermont","title":"Flood of July 2023 in Vermont","docAbstract":"A major storm caused catastrophic flooding in many parts of Vermont on July 9–12, 2023, resulting in millions of dollars in damages. The high amount of rainfall caused several rivers to peak at record levels, in some cases exceeding records set during Tropical Storm Irene in 2011. The U.S. Geological Survey, in cooperation with the Federal Emergency Management Agency, collected and analyzed data that characterized the flood in Vermont. The data collected included peak water-surface elevations, taken from high-water marks at bridges, dams, and roads, and peak streamflow and annual exceedance probabilities (AEPs) at streamgages, lake gages, and selected ungaged locations. At 11 of the 80 streamgages with 12 to 94 years of record, the July 2023 peak streamflow was the peak of record. Ten streamgages recorded a peak streamflow with an AEP of less than or equal to 1 percent (greater than or equal to a 100-year recurrence interval).
The July 2023 flood affected many of the same communities as the historical flood caused by Tropical Storm Irene in 2011. Twenty of the 45 continuous-recording streamgages running during both events recorded greater peak streamflows during the July 2023 flood than during Tropical Storm Irene in 2011. Four of the 11 U.S. Geological Survey streamgages with period-of-record maximum peak streamflows observed during the July 2023 flood had previously recorded their maximum period-of-record peak streamflows during Tropical Storm Irene. There were 17 rivers in Vermont that were surveyed for high-water marks during both Tropical Storm Irene and the July 2023 flood. On those 17 rivers, a total of 103 sites contained surveyed high-water marks for both events. Thirty-two of these sites had higher surveyed elevations for the July 2023 flood than Tropical Storm Irene, including Black River in Newport, Black River in Springfield, Jewell Brook, Middlebury River, Missisquoi River, Ottauquechee River, Otter Creek, Wells River, Whetstone Brook, and Winooski River. Peak water-surface elevations were not collected on the Lamoille River in 2011.
Federal Emergency Management Agency flood insurance studies were evaluated in the context of the July 2023 flood. Peak streamflows at streamgages and nearby locations were assessed to determine the influence of the July 2023 flood on the AEPs used in past studies. Overall, 21 of 26 streamflow-computation locations in the flood insurance studies had more than a 10 percent difference in the 1-percent AEP streamflow. A hydraulic evaluation of surveyed water-surface elevations following the July 2023 flood was compared with the AEP profiles from past studies. Four of the 10 streamgages analyzed had poor alignment between the AEPs of the observed streamflows and the AEPs of the observed peak water-surface elevations as computed from flood insurance studies.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255016","collaboration":"Prepared in cooperation with the Federal Emergency Management Agency","usgsCitation":"Smith, T.L., Olson, S.A., LeNoir, J.M., Kalmon, R.D., and Ahearn, E.A., 2025, Flood of July 2023 in Vermont (ver. 1.1, May 22, 2025): U.S. Geological Survey Scientific Investigations Report 2025–5016, 21 p., https://doi.org/10.3133/sir20255016.","productDescription":"Report; vii, 21 p.; 2 Data Releases: Application Site","numberOfPages":"21","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-167054","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":493770,"rank":10,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118574.htm","linkFileType":{"id":5,"text":"html"}},{"id":486164,"rank":4,"type":{"id":31,"text":"Publication 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data viewer"},{"id":486167,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P14XBBAT","text":"USGS data release","linkHelpText":"Vermont Flood of July 2023 Data"},{"id":486291,"rank":8,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2025/5016/versionHist.txt","size":"879 B","linkFileType":{"id":2,"text":"txt"}},{"id":486405,"rank":9,"type":{"id":30,"text":"Data Release"},"url":"https://www.sciencebase.gov/catalog/item/664e23efd34e702fe8744b3c","text":"USGS data release","linkHelpText":"Peak Streamflow, Peak Stage, and Annual Exceedance Probability Data of the July 2023 Flood in Vermont, with attached data tables 1.1 to 1.4 in Vermont_Flood_2023_tables.xlsx"}],"country":"United 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\"}}]}","edition":"Version 1.0: May 19, 2025; Version 1.1: May 22, 2025","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
A major storm caused catastrophic flooding in many parts of Vermont on July 9–12, 2023, resulting in millions of dollars in damages. The high amount of rainfall caused several rivers to peak at record levels, in some cases surpassing records set during Tropical Storm Irene in 2011. The U.S. Geological Survey, in cooperation with the Federal Emergency Management Agency, collected and analyzed data on peak water-surface elevations, peak streamflow, and annual exceedance probabilities at streamgages, lake gages, and selected ungaged locations. Of the 80 streamgages with records ranging from 12 to 94 years, 11 streamgages recorded peak streamflows during the July 2023 flood that were the highest on record, whereas 10 streamgages had peak streamflows with a recurrence interval of 100 years or more. The July 2023 flood affected many of the same communities as Tropical Storm Irene in 2011, but 20 of the 45 monitored streamgages recorded higher peak flows in the July 2023 flood. Seventeen rivers were surveyed for high-water marks during both Tropical Storm Irene and the July 2023 flood, and 32 of the 103 sites had higher water levels during the July 2023 flood compared with Tropical Storm Irene. Flood insurance studies by the Federal Emergency Management Agency were evaluated against the July 2023 flood data. Twenty-one of the 26 locations analyzed had more than a 10 percent difference in the 1-percent annual exceedance probability streamflow.
","publicationDate":"2025-05-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Smith, Travis L. 0000-0002-3448-2787 tlsmith@usgs.gov","orcid":"https://orcid.org/0000-0002-3448-2787","contributorId":297400,"corporation":false,"usgs":true,"family":"Smith","given":"Travis","email":"tlsmith@usgs.gov","middleInitial":"L.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":937647,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Olson, Scott A. 0000-0002-1064-2125","orcid":"https://orcid.org/0000-0002-1064-2125","contributorId":210173,"corporation":false,"usgs":true,"family":"Olson","given":"Scott A.","affiliations":[{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":937648,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"LeNoir, James M. 0000-0003-3295-4901","orcid":"https://orcid.org/0000-0003-3295-4901","contributorId":302690,"corporation":false,"usgs":true,"family":"LeNoir","given":"James","email":"","middleInitial":"M.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":937649,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kalmon, Rena D. 0000-0002-3210-3210","orcid":"https://orcid.org/0000-0002-3210-3210","contributorId":206320,"corporation":false,"usgs":true,"family":"Kalmon","given":"Rena","email":"","middleInitial":"D.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":937650,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ahearn, Elizabeth A. 0000-0002-5633-2640 eaahearn@usgs.gov","orcid":"https://orcid.org/0000-0002-5633-2640","contributorId":194658,"corporation":false,"usgs":true,"family":"Ahearn","given":"Elizabeth","email":"eaahearn@usgs.gov","middleInitial":"A.","affiliations":[{"id":377,"text":"Massachusetts-Rhode Island Water Science Center","active":false,"usgs":true},{"id":196,"text":"Connecticut Water Science Center","active":true,"usgs":true}],"preferred":false,"id":937651,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70267230,"text":"sir20235064G - 2025 - Peak streamflow trends in Montana and northern Wyoming and their relation to changes in climate, water years 1921–2020","interactions":[{"subject":{"id":70267230,"text":"sir20235064G - 2025 - Peak streamflow trends in Montana and northern Wyoming and their relation to changes in climate, water years 1921–2020","indexId":"sir20235064G","publicationYear":"2025","noYear":false,"chapter":"G","displayTitle":"Peak Streamflow Trends in Montana and Northern Wyoming and Their Relation to Changes in Climate, Water Years 1921–2020","title":"Peak streamflow trends in Montana and northern Wyoming and their relation to changes in climate, water years 1921–2020"},"predicate":"IS_PART_OF","object":{"id":70251152,"text":"sir20235064 - 2024 - Peak streamflow trends and their relation to changes in climate in Illinois, Iowa, Michigan, Minnesota, Missouri, Montana, North Dakota, South Dakota, and Wisconsin","indexId":"sir20235064","publicationYear":"2024","noYear":false,"title":"Peak streamflow trends and their relation to changes in climate in Illinois, Iowa, Michigan, Minnesota, Missouri, Montana, North Dakota, South Dakota, and Wisconsin"},"id":1}],"isPartOf":{"id":70251152,"text":"sir20235064 - 2024 - Peak streamflow trends and their relation to changes in climate in Illinois, Iowa, Michigan, Minnesota, Missouri, Montana, North Dakota, South Dakota, and Wisconsin","indexId":"sir20235064","publicationYear":"2024","noYear":false,"title":"Peak streamflow trends and their relation to changes in climate in Illinois, Iowa, Michigan, Minnesota, Missouri, Montana, North Dakota, South Dakota, and Wisconsin"},"lastModifiedDate":"2026-01-26T19:13:21.257304","indexId":"sir20235064G","displayToPublicDate":"2025-05-19T13:20:42","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":"2023-5064","chapter":"G","displayTitle":"Peak Streamflow Trends in Montana and Northern Wyoming and Their Relation to Changes in Climate, Water Years 1921–2020","title":"Peak streamflow trends in Montana and northern Wyoming and their relation to changes in climate, water years 1921–2020","docAbstract":"Frequency analysis on annual peak streamflow (hereinafter, peak flow) is essential to water-resources management applications, including critical structure design (for example, bridges and culverts) and floodplain mapping. Nonstationarity is a statistical property of a peak-flow series such that the distributional properties (the mean, variance, or skew) change either gradually (monotonic trend) or abruptly (shift, step change or change point) through time. Not incorporating or accounting for observed nonstationarity into peak-flow frequency analysis might result in a poor representation of the true probability of large floods and thus misrepresent the actual flood risks to life and property. This report summarizes how hydroclimatic variability might affect the temporal and spatial distributions of peak-flow data in the State of Montana (and northern Wyoming) and is part of a larger study to document peak-flow nonstationarity and hydroclimatic changes across a nine-State region consisting of Illinois, Iowa, Michigan, Minnesota, Missouri, Montana, North Dakota, South Dakota, and Wisconsin. A wide range of analyses and statistical approaches are applied to document the primary mechanisms controlling floods and characterize temporal changes in hydroclimatic variables and peak flows. This study was completed in cooperation with the Montana Department of Natural Resources and Conservation.
The purpose of this report is to characterize temporal and spatial patterns of nonstationarity in peak flows and hydroclimatology in Montana and northern Wyoming. In this evaluation, peak-flow, daily streamflow, and model-simulated gridded climatic data were examined for monotonic trends, change points, and other statistical properties that might indicate changing climatic and environmental conditions. This report includes background information on the study area, the history of U.S. Geological Survey peak-flow data collection and frequency analysis in Montana, and the review of research relating to hydroclimatic variability and change in Montana. This study might help provide a framework for addressing potential nonstationarity issues in peak-flow frequency updates that commonly are completed by the U.S. Geological Survey in cooperation with other agencies throughout the Nation.
The analytical structure of this study includes analyses of monotonic trends and change points in numerous hydroclimatic variables in assigned 30-, 50-, 75-, and 100-year analysis periods. For Montana and part of Wyoming, the 30-, 50-, 75, and 100-year analyses included 157, 70, 48, and 12 streamgages, respectively. For those streamgages, nonstationarities were analyzed in the following variables: (1) climatic variables, including annual and seasonal (winter, spring, summer, and fall) temperature and precipitation; (2) daily streamflow variables, including the annual center of volume duration, annual center of volume median, and peaks over threshold with a mean of four events per year; and (3) annual peak-flow variables, including peak-flow timing and magnitude. A likelihood approach was used to express statistical confidence and assign the nonstationarity results as likely upward or downward (highest statistical confidence), somewhat likely upward or downward (less statistical confidence), or about as likely as not (little statistical confidence; hereinafter, neutral). For the nonstationarity analyses of the climatic, daily streamflow, and peak-flow variables, the results are presented in detail and discussed with respect to statewide patterns and geographic variability. For each of the 30-, 50-, and 75-year analyses, peak-flow change-point and monotonic trend analyses were compiled for streamgages classified with likely downward or likely upward trends. For those streamgages, the associated basin characteristics and nonstationarity results for peak-flow timing, daily streamflow, and climatic variables were investigated and statistically compared to discern associations among other variables that might contribute to the peak-flow nonstationarity results.
The 50- and 75-year peak-flow nonstationarities identified in this study are mostly downward, in association with mostly upward temperature and potential evapotranspiration:precipitation monotonic trends. For the 50-, 75-, and 100-year analyses, the peak-flow change points are predominantly downward and are concentrated in the 1970s and 1980s, which indicates general consistency among the longer trend periods. These findings are in association with substantial research documenting globally rising temperature and atmospheric greenhouse gas concentrations that might be largely attributed to anthropogenic activities. Anthropogenic effects might represent long-term (on the order of several decades to more than a century) climate changes that might happen within highly variable natural climate fluctuations. Several paleo studies in the north-central United States have indicated that hydroclimatic extremes (that is, low- and high-streamflow conditions) before European settlement have been outside of extremes since the 1900s. Depending on the interactions of anthropogenic effects and natural climate variability, extreme high-streamflow conditions might occur in the future, even in the presence of long-term downward peak-flow trends.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235064G","collaboration":"Prepared in cooperation with the Montana Department of Natural Resources and Conservation","usgsCitation":"Sando, S.K., Barth, N.A., Sando, R., and Chase, K.J., 2025, Peak streamflow trends in Montana and northern Wyoming and their relation to changes in climate, water years 1921–2020, chap. G of Ryberg, K.R., comp., Peak streamflow trends and their relation to changes in climate in Illinois, Iowa, Michigan, Minnesota, Missouri, Montana, North Dakota, South Dakota, and Wisconsin: U.S. Geological Survey Scientific Investigations Report 2023–5064, 129 p., https://doi.org/10.3133/sir20235064G.","productDescription":"Report: x, 129 p.; Data Release; Dataset","numberOfPages":"144","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-159092","costCenters":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"links":[{"id":486055,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5064/g/sir20235064g.pdf","text":"Report","size":"19 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5064-G"},{"id":486054,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5064/g/coverthb.jpg"},{"id":486056,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5064/g/sir20235064g.XML"},{"id":486057,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5064/g/images/"},{"id":486059,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235064G/full"},{"id":499038,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118575.htm","linkFileType":{"id":5,"text":"html"}},{"id":486073,"rank":7,"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":486058,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9R71WWZ","text":"USGS data release","linkHelpText":"Peak streamflow data, climate data, and results from investigating hydroclimatic trends and climate change effects on peak streamflow in the Central United States, 1921–2020"}],"country":"United States","state":"Montana, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -116.16658108866669,\n 49\n ],\n [\n -116.16658108866669,\n 43\n ],\n [\n -104.0598539498924,\n 43\n ],\n [\n -104.0598539498924,\n 49\n ],\n [\n -116.16658108866669,\n 49\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Wyoming-Montana Water Science Center
U.S. Geological Survey
3162 Bozeman Avenue
Helena, MT 59601
We explore how and when Hells Canyon, North America’s deepest river gorge (~2,400 m deep), formed, addressing these fundamental questions first posed by W. Lindgren [The Gold Belt of the Blue Mountains of Oregon (1901)]. Existing hypotheses about the canyon’s formation and timing of incision remain speculative due to a lack of direct constraints and geomorphic analysis in the canyon. Herein, we combine cosmogenic nuclide dating of cave-bound river deposits, river profile analysis, and numerical modeling to provide the first direct age constraints and systematic analysis of incision processes at work in Hells Canyon. Our study reveals a significant drainage capture triggered rapid incision at ~2.1 ± 1.0 Ma, establishing the Snake River’s modern route into the Columbia River system. The increased drainage area and subsequent increase in stream power resulted in the rapid incision of Hells Canyon and the formation of tributary knickpoints (KPs) that decrease in elevation away from the capture location. Cosmogenic dating of cave deposits indicates incision rates increased from ~0.01 to ~0.16 mm y−1. Numerical modeling of the stream capture supports these observations, demonstrating how abrupt drainage area increase drives rapid river incision. Our findings from Hells Canyon provide a well-constrained example of how drainage capture can dramatically shape the evolution of a major river gorge.
","language":"English","publisher":"National Academy of Sciences","doi":"10.1073/pnas.2413069122","usgsCitation":"Morriss, M., Mitchell, N., Yanites, B., Staisch, L.M., and Korup, O., 2025, Cave records reveal recent origin of North America’s deepest canyon: Proceedings of the National Academy of Sciences, v. 122, no. 21, e2413069122, 9 p., https://doi.org/10.1073/pnas.2413069122.","productDescription":"e2413069122, 9 p.","ipdsId":"IP-167780","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":490153,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1073/pnas.2413069122","text":"Publisher Index Page"},{"id":486579,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Oregon, Washington","otherGeospatial":"Hell's Canyon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.54194789662489,\n 46.1007348974789\n ],\n [\n -117.54194789662489,\n 44.98900450879145\n ],\n [\n -116.26934949051348,\n 44.98900450879145\n ],\n [\n -116.26934949051348,\n 46.1007348974789\n ],\n [\n -117.54194789662489,\n 46.1007348974789\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"122","issue":"21","noUsgsAuthors":false,"publicationDate":"2025-05-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Morriss, Matthew","contributorId":355886,"corporation":false,"usgs":false,"family":"Morriss","given":"Matthew","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":938354,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mitchell, Nate","contributorId":355887,"corporation":false,"usgs":false,"family":"Mitchell","given":"Nate","affiliations":[{"id":37145,"text":"Indiana University","active":true,"usgs":false}],"preferred":false,"id":938355,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yanites, Brian","contributorId":91373,"corporation":false,"usgs":true,"family":"Yanites","given":"Brian","affiliations":[],"preferred":false,"id":938356,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Staisch, Lydia M. 0000-0002-1414-5994 lstaisch@usgs.gov","orcid":"https://orcid.org/0000-0002-1414-5994","contributorId":167068,"corporation":false,"usgs":true,"family":"Staisch","given":"Lydia","email":"lstaisch@usgs.gov","middleInitial":"M.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":938357,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Korup, Oliver","contributorId":218071,"corporation":false,"usgs":false,"family":"Korup","given":"Oliver","email":"","affiliations":[{"id":39735,"text":"Institute of Earth and Environmental Science, University of Potsdam, Germany","active":true,"usgs":false}],"preferred":false,"id":938358,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70267066,"text":"fs20253024 - 2025 - Diagnostic success—A quick guide to quality carcass submissions for diagnostic services","interactions":[],"lastModifiedDate":"2025-07-01T19:08:46.884612","indexId":"fs20253024","displayToPublicDate":"2025-05-19T09:21:03","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-3024","displayTitle":"Diagnostic Success—A Quick Guide to Quality Carcass Submissions for Diagnostic Services","title":"Diagnostic success—A quick guide to quality carcass submissions for diagnostic services","docAbstract":"The U.S. Geological Survey National Wildlife Health Center provides diagnostic services to determine causes of wildlife morbidity and mortality events to State, Federal, and Tribal partners. To accomplish this, we rely on the timely collection and evaluation of submitted carcasses and the epidemiologic information relayed from personnel in the field. Our current submission criteria can be found here: https://www.usgs.gov/centers/nwhc/science/ diagnostic-case-submission-guidelines. If the majority of carcasses found in the field are unsuitable for submission, then sick animals (birds, mammals, reptiles) that have been euthanized are acceptable specimens. Depending on the agency or affiliated institution, there may be additional requirements for submission. When applicable, always consult the organization’s wildlife health or veterinary staff.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20253024","usgsCitation":"Bodenstein, B.L., and Weidenkopf, S.J., 2025, Diagnostic success—A quick guide to quality carcass submissions for diagnostic services: U.S. Geological Survey Fact Sheet 2025–3024, 2 p., https://doi.org/10.3133/fs20253024.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-171086","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":486020,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/fs20253024/full"},{"id":486019,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2025/3024/fs20253024.XML"},{"id":486012,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2025/3024/images/"},{"id":486011,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2025/3024/fs20253024.pdf","text":"Report","size":"1.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2025-3024"},{"id":486010,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2025/3024/coverthb.jpg"}],"contact":"Director, National Wildlife Health Center
U.S. Geological Survey
6006 Schroeder Road
Madison, WI 53711
Infrasound (acoustic waves below 20 Hz) can be used to detect, locate and quantify activity in the atmosphere such as volcanic eruptions and anthropogenic explosions. Attempts to quantify volcanic eruption parameters such as exit velocity, plume height and mass flow rate using infrasound data depend strongly on assumptions of the acoustic source type. Infrasonic sources may produce omnidirectional or directional wavefields, while propagation effects, such as interaction with topography, can induce further wavefield directivity that is measured by field instrumentation. Limited sampling of these wavefields can hinder our ability to infer the underlying source, and thus our understanding of the eruption characteristics. Equivalent sources are often used to represent acoustic source mechanisms and resultant wavefields. In this study, we review equivalent acoustic sources as they pertain to infrasonic scale and wavelengths commonly encountered in very local (<5 km range) geophysical field deployments. We highlight the equivalent infrasonic bipole source that can be induced by ground-reflection of an elevated monopole; we are not aware of any prior infrasound studies that use the bipole source concept. We use analytical and numerical methods to explore source directivity of monopole, dipole and bipole ground-reflected sources at infrasonic frequencies as well as the additional directivity complications introduced by interactions with topography. We illustrate that for typical volcano-infrasound wavelengths, increasing height above the ground as well as increasing source frequency leads to increased wavefield directivity. Numerical modelling using a simple omnidirectional monopole source embedded in topography further illustrates that both horizontal and vertical infrasound directionality can be induced by topography at the distance scales appropriate for local volcano infrasound monitoring. Information summarized in this analytical and numerical exploration of infrasound directivity may be used to help guide future volcano-infrasound field deployments intended to estimate source parameters or quantify wavefield directivity. Analytic solutions for simple whole-space or half-space atmospheres provide useful formulations for planning or initially analysing geophysical field-scale experimental data; however, especially at very local distances from the source (<5 km), 3-D simulations are necessary to account for complex topography commonly encountered in volcano-infrasound applications.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/gji/ggaf180","usgsCitation":"Iezzi, A.M., Matoza, R.S., Opper, E., and Kim, K., 2025, Infrasonic directivity of monopole, dipole, and bipole ground-surface reflected sources: Geophysical Journal International, v. 242, no. 2, ggaf180, 23 p., https://doi.org/10.1093/gji/ggaf180.","productDescription":"ggaf180, 23 p.","ipdsId":"IP-175386","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":493308,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/gji/ggaf180","text":"Publisher Index Page"},{"id":492906,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"242","issue":"2","noUsgsAuthors":false,"publicationDate":"2025-05-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Iezzi, Alexandra M. 0000-0002-6782-7681","orcid":"https://orcid.org/0000-0002-6782-7681","contributorId":304206,"corporation":false,"usgs":true,"family":"Iezzi","given":"Alexandra","email":"","middleInitial":"M.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":943967,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Matoza, Robin S.","contributorId":257265,"corporation":false,"usgs":false,"family":"Matoza","given":"Robin","email":"","middleInitial":"S.","affiliations":[{"id":36524,"text":"University of California, Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":943968,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Opper, Emma V.","contributorId":358570,"corporation":false,"usgs":false,"family":"Opper","given":"Emma V.","affiliations":[{"id":85657,"text":"Department of Applied Mathematics, University of Colorado Boulder","active":true,"usgs":false}],"preferred":false,"id":943969,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kim, Keehoon","contributorId":252842,"corporation":false,"usgs":false,"family":"Kim","given":"Keehoon","email":"","affiliations":[{"id":27196,"text":"LANL","active":true,"usgs":false}],"preferred":false,"id":943970,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70267753,"text":"70267753 - 2025 - Serological assessment of pathogen exposure among desert bighorn sheep in southwestern Arizona","interactions":[],"lastModifiedDate":"2025-05-30T15:55:56.491711","indexId":"70267753","displayToPublicDate":"2025-05-19T08:50:13","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5991,"text":"The Southwestern Naturalist","active":true,"publicationSubtype":{"id":10}},"title":"Serological assessment of pathogen exposure among desert bighorn sheep in southwestern Arizona","docAbstract":"Bighorn sheep (Ovis canadensis) are influenced by infectious diseases. Although Mycoplasma ovipneumoniae has been the main focus of bighorn sheep managers since early 2010, other pathogens may also influence bighorn sheep populations. We sampled desert bighorn sheep (Ovis canadensis mexicana) captured for a study on the Cabeza Prieta National Wildlife Refuge in southwestern Arizona, USA, 2001–2005, for a suite of pathogens: bluetongue (BT), epizootic hemorrhagic disease (EHD), parainfluenza 3, bovine respiratory syncytial virus, Clamydia, seven Leptospira serovars, bovine herpesvirus 1 (causative agent of infectious bovine rhinotracheitis), bovine viral diarrhea virus, and bovine respiratory syncytial virus. We recorded evidence of exposure to seven of these pathogens, with two Leptospira serovars (hardjo and bratislava), five strains of BT, and two strains of EHD detected. Seroprevalence rates of detected pathogens varied between 12–49%. We observed high levels of co-occurrence for EHD and BT. These results highlight that multiple pathogens may influence desert bighorn sheep populations. These data also provide historical context to pathogen exposure for a region where few such data are available.
","language":"English","publisher":"BioOne","doi":"10.1894/0038-4909-68.4.6","usgsCitation":"Padilla, C., Cain, J.W., Gompper, M., Krausman, P., and Devos, J., 2025, Serological assessment of pathogen exposure among desert bighorn sheep in southwestern Arizona: The Southwestern Naturalist, v. 68, no. 4, p. 294-300, https://doi.org/10.1894/0038-4909-68.4.6.","productDescription":"7 p.","startPage":"294","endPage":"300","ipdsId":"IP-158089","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":489284,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Cabeza Prieta National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -114.0165865297831,\n 32.53576263609473\n ],\n [\n -114.0165865297831,\n 31.947344458858936\n ],\n [\n -112.69784561865545,\n 31.947344458858936\n ],\n [\n -112.69784561865545,\n 32.53576263609473\n ],\n [\n -114.0165865297831,\n 32.53576263609473\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"68","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Padilla, Colton J.","contributorId":353982,"corporation":false,"usgs":false,"family":"Padilla","given":"Colton J.","affiliations":[{"id":12628,"text":"New Mexico State University","active":true,"usgs":false}],"preferred":false,"id":938735,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cain, James W. III 0000-0003-4743-516X jwcain@usgs.gov","orcid":"https://orcid.org/0000-0003-4743-516X","contributorId":4063,"corporation":false,"usgs":true,"family":"Cain","given":"James","suffix":"III","email":"jwcain@usgs.gov","middleInitial":"W.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":938736,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gompper, Matthew E.","contributorId":353984,"corporation":false,"usgs":false,"family":"Gompper","given":"Matthew E.","affiliations":[{"id":12628,"text":"New Mexico State University","active":true,"usgs":false}],"preferred":false,"id":938737,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Krausman, Paul R.","contributorId":356094,"corporation":false,"usgs":false,"family":"Krausman","given":"Paul R.","affiliations":[{"id":12628,"text":"New Mexico State University","active":true,"usgs":false}],"preferred":false,"id":938738,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Devos, JIM","contributorId":356095,"corporation":false,"usgs":false,"family":"Devos","given":"JIM","affiliations":[{"id":12628,"text":"New Mexico State University","active":true,"usgs":false}],"preferred":false,"id":938739,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ]}