The first multidisciplinary characterisation of Bowditch Seamount in the Sargasso Sea was conducted to provide new baseline knowledge of the biodiversity, geomorphology, oceanography and glacial history of this seamount. A dropframe camera transect 1483–1562 m deep on the seamount documented 77 megafaunal taxa including Vulnerable Marine Ecosystem indicator taxa such as sponges, cold-water corals, and stalked crinoids. Seabed terrain analysis of multibeam echosounder data showed species varied significantly along this transect in response to local geomorphological variability (R2adj = 31%, p < 0.0001), with changes in seafloor relief and substrata driving species composition over the seamount. 14C-calibrated and 230Th-ages of fossil corals (Desmophyllum dianthus) collected by Van Veen grabs 1517 m deep showed corals thrived on the seamount ∼24 ka BP and ∼17 ka BP. Abrupt excursions between higher and lower radiogenic εNd-composition values of the skeletons suggested that D. dianthus persisted on the seamount over times of southern source water input and detrital sediments from the melting Laurentide Ice Sheet, respectively. In agreement with other studies from the western North Atlantic, living D. dianthus were absent in the contemporary setting at these depths, and suggest a significant re-organisation of the seamount community since the deglacial when ice-rafted debris of carbonates likely resulted in a lower aragonite compensation depth allowing D. dianthus to proliferate at deeper depths. New conductivity-depth-temperature profiling revealed the seamount at these depths is now bathed by highly oxygenated Labrador Sea Water (LSW) formed at high latitudes. Co-analysis of a newly constructed 70-year long time series of temperature and salinity for the Labrador Sea and Bermuda regions revealed a 10-year transit time from high latitudes to Bowditch Seamount. This multidisciplinary approach shows how geomorphology drives local biodiversity patterns, but also how upstream climatic forcing in subpolar regions may influence Bermuda's subtropical seamount ecosystem.
Dust transported from rangelands of the Southwestern United States (US) to mountain snowpack in the Upper Colorado River Basin during spring (March-May) forces earlier and faster snowmelt, which creates problems for water resources and agriculture. To better understand the drivers of dust events, we investigated large-scale meteorology responsible for organizing two Southwest US dust events from two different dominant geographic locations: (a) the Colorado Plateau and (b) the northern Chihuahuan Desert. High-resolution Weather Research and Forecasting coupled with Chemistry model (WRF-Chem) simulations with the Air Force Weather Agency dust emission scheme incorporating a MODIS albedo-based drag-partition was used to explore land surface-atmosphere interactions driving two dust events. We identified commonalities in their meteorological setups. The meteorological analyses revealed that Polar and Sub-tropical jet stream interaction was a common upper-level meteorological feature before each of the two dust events. When the two jet streams merged, a strong northeast-directed pressure gradient upstream and over the source areas resulted in strong near-surface winds, which lifted available dust into the atmosphere. Concurrently, a strong mid-tropospheric flow developed over the dust source areas, which transported dust to the San Juan Mountains and southern Colorado snowpack. The WRF-Chem simulations reproduced both dust events, indicating that the simulations represented the dust sources that contributed to dust-on-snow events reasonably well. The representativeness of the simulated dust emission and transport in different geographic and meteorological conditions with our use of albedo-based drag partition provides a basis for additional dust-on-snow simulations to assess the hydrologic impact in the Southwest US.
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The earthquake, which occurred in the early days of both broadband seismic networks and the Internet, spurred advances in seismic monitoring, real-time systems, and development of data products. Motivated by the 30th anniversary of the earthquake, we present a brief retrospective of the earthquake and its impact, and reconsider both ground motions and the aftershock distribution using modern tools and best-available data. With improvements in instrumentation and analysis methodology, recent earthquakes continue to reveal increasing complexity of ground motions, fault systems, and earthquake ruptures. Even in the absence of data from state-of-the art instrumentation, a retrospective consideration of ground motion data from the Northridge earthquake reveals complexities beyond what could be characterized (and modeled) thirty years ago. Aftershock relocations for both the 1971 Sylmar and 1994 Northridge earthquakes also reveal an updated view of fault complexity. Our study does provide a cautionary tale regarding legacy data sets and research results that are not easily accessible, which can result in discrepancies between catalog data and products from best-available science. We also briefly describe outreach products produced as part of the anniversary commemoration.","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0320240012","usgsCitation":"Hough, S.E., Graves, R., Cochran, E.S., Yoon, C., Blair, J.L., Haefner, S., Wald, D.J., and Quitoriano, V., 2024, The 17 January 1994 Northridge, California, earthquake: A retrospective analysis: The Seismic Record, v. 4, no. 3, p. 151-160, https://doi.org/10.1785/0320240012.","productDescription":"10 p.","startPage":"151","endPage":"160","ipdsId":"IP-164904","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":489848,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1785/0320240012","text":"Publisher Index Page"},{"id":482225,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"Northridge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -118.60523974052802,\n 34.27362638562232\n ],\n [\n -118.60523974052802,\n 34.17466422238154\n ],\n [\n -118.47245060179975,\n 34.17466422238154\n ],\n [\n -118.47245060179975,\n 34.27362638562232\n ],\n [\n -118.60523974052802,\n 34.27362638562232\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"4","issue":"3","noUsgsAuthors":false,"publicationDate":"2024-07-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Hough, Susan E. 0000-0002-5980-2986","orcid":"https://orcid.org/0000-0002-5980-2986","contributorId":263442,"corporation":false,"usgs":true,"family":"Hough","given":"Susan","email":"","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927573,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Graves, Robert 0000-0001-9758-453X rwgraves@usgs.gov","orcid":"https://orcid.org/0000-0001-9758-453X","contributorId":140738,"corporation":false,"usgs":true,"family":"Graves","given":"Robert","email":"rwgraves@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927574,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cochran, Elizabeth S. 0000-0003-2485-4484 ecochran@usgs.gov","orcid":"https://orcid.org/0000-0003-2485-4484","contributorId":2025,"corporation":false,"usgs":true,"family":"Cochran","given":"Elizabeth","email":"ecochran@usgs.gov","middleInitial":"S.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927575,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Yoon, Clara 0000-0003-4521-3889","orcid":"https://orcid.org/0000-0003-4521-3889","contributorId":222019,"corporation":false,"usgs":true,"family":"Yoon","given":"Clara","email":"","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927576,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Blair, James Luke 0000-0002-6980-6446","orcid":"https://orcid.org/0000-0002-6980-6446","contributorId":213724,"corporation":false,"usgs":true,"family":"Blair","given":"James","email":"","middleInitial":"Luke","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927577,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Haefner, Scott","contributorId":350679,"corporation":false,"usgs":true,"family":"Haefner","given":"Scott","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927578,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wald, David J. 0000-0002-1454-4514 wald@usgs.gov","orcid":"https://orcid.org/0000-0002-1454-4514","contributorId":795,"corporation":false,"usgs":true,"family":"Wald","given":"David","email":"wald@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":927579,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Quitoriano, Vince 0000-0003-4157-1101 vinceq@usgs.gov","orcid":"https://orcid.org/0000-0003-4157-1101","contributorId":2582,"corporation":false,"usgs":true,"family":"Quitoriano","given":"Vince","email":"vinceq@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":927580,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70273741,"text":"70273741 - 2024 - Adaptive fine-tuning for transferring a U-net hydrography extraction model using K-means","interactions":[],"lastModifiedDate":"2026-01-27T16:31:23.793842","indexId":"70273741","displayToPublicDate":"2024-07-01T10:29:44","publicationYear":"2024","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Adaptive fine-tuning for transferring a U-net hydrography extraction model using K-means","docAbstract":"The United States Geological Survey (USGS) coordinates the collection of hydrographic features derived from remotely sensed interferometric synthetic aperture radar (IfSAR) elevation and intensity data in Alaska. Hydrographic features are cartographic representations of surface water features such as stream, rivers, lakes, ponds, canals, etc. Collection and validation procedures involve complex automated and manual techniques that furnish snapshots of hydrographic vector data that exist during the IfSAR surveys. The dynamic nature of fluvial conditions warrants monitoring and updating hydrographic data, but extraction procedures for updates can be cost prohibitive. This paper overviews progress on automated workflows to extract hydrography from IfSAR data using deep learning methods trained and tested with USGS collected hydrography data. This research tests transfer learning methods on a well-performing U-net model trained on a 4600-square kilometer (sq km) base model area in northcentral Alaska. The base model is transferred and fine-tuned to regions in the target domain covering roughly 127,000 sq km. The target domain is subdivided into areas with similar hydrogeomorphic conditions using principal components and k-means clustering, and the base model is adaptively fine-tuned to each hydrogeomorphic class by selecting training watersheds from each cluster within the target domain. Results are compared with transfer learning that is fine-tuned with a random sample of watersheds in the target domain.","conferenceTitle":"Cartography and Geographic Information Society (CaGIS) and the University Consortium for Geographic Information Science (UCGIS) 2024 Symposium","conferenceDate":"June 3-6, 2024","conferenceLocation":"Columbus, OH","language":"English","publisher":"The Cartography and Geographic Information Society (CaGIS) and the University Consortium for Geographic Information Science (UCGIS)","usgsCitation":"Stanislawski, L., Shavers, E.J., Pastick, N.J., Thiem, P.T., Wang, S., Jaroenchai, N., Jiang, Z., Kronenfeld, B.J., Buttenfield, B.P., and Camerer, A., 2024, Adaptive fine-tuning for transferring a U-net hydrography extraction model using K-means, Cartography and Geographic Information Society (CaGIS) and the University Consortium for Geographic Information Science (UCGIS) 2024 Symposium, Columbus, OH, June 3-6, 2024, 45, 6 p.","productDescription":"45, 6 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eshavers@usgs.gov","orcid":"https://orcid.org/0000-0001-9470-5199","contributorId":206890,"corporation":false,"usgs":true,"family":"Shavers","given":"Ethan","email":"eshavers@usgs.gov","middleInitial":"J.","affiliations":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":954504,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pastick, Neal J. 0000-0002-8169-3018 njpastick@usgs.gov","orcid":"https://orcid.org/0000-0002-8169-3018","contributorId":4785,"corporation":false,"usgs":true,"family":"Pastick","given":"Neal","email":"njpastick@usgs.gov","middleInitial":"J.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":954505,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thiem, Philip T. 0000-0002-3324-2589","orcid":"https://orcid.org/0000-0002-3324-2589","contributorId":287990,"corporation":false,"usgs":true,"family":"Thiem","given":"Philip","email":"","middleInitial":"T.","affiliations":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":954506,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wang, Shaowen","contributorId":198966,"corporation":false,"usgs":false,"family":"Wang","given":"Shaowen","email":"","affiliations":[],"preferred":false,"id":954507,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jaroenchai, Nattapon","contributorId":267318,"corporation":false,"usgs":false,"family":"Jaroenchai","given":"Nattapon","email":"","affiliations":[{"id":38021,"text":"University of Illinois 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0000-0001-5961-5809","orcid":"https://orcid.org/0000-0001-5961-5809","contributorId":206887,"corporation":false,"usgs":false,"family":"Buttenfield","given":"Barbara","email":"","middleInitial":"P.","affiliations":[{"id":16144,"text":"University of Colorado-Boulder","active":true,"usgs":false}],"preferred":false,"id":954511,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Camerer, Adam","contributorId":331850,"corporation":false,"usgs":false,"family":"Camerer","given":"Adam","email":"","affiliations":[{"id":26996,"text":"Missouri University of Science & Technology","active":true,"usgs":false}],"preferred":false,"id":954512,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70255905,"text":"70255905 - 2024 - Pacific Lamprey responses to stressors: Dewatering and electrofishing","interactions":[],"lastModifiedDate":"2024-07-10T15:16:13.598471","indexId":"70255905","displayToPublicDate":"2024-07-01T10:12:18","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":3,"text":"Organization Series"},"title":"Pacific Lamprey responses to stressors: Dewatering and electrofishing","docAbstract":"The Pacific Lamprey Conservation Initiative (PLCI) is a collaboration of Tribes, Federal, and State agencies working together to protect and restore Pacific Lamprey (Entosphenus tridentatus) and other native lampreys (i.e., Lampetra spp.) in Alaska, Washington, Oregon, California, and Idaho. The U.S. Fish and Wildlife Service hosts and facilitates the PLCI, and the Columbia River Tribes play a large role in setting conservation goals and defining research needs. The PLCI annually solicits proposals for research and restoration activities, which are reviewed and ranked in collaboration with the Bonneville Power Administration (BPA), who annually provides funding to support PLCI priority proposals. This report summarizes two research projects selected through PLCI, and funded under one BPA contract, in support of Pacific Lamprey conservation. The two projects were not topically related apart from a common theme of potential stressors to lampreys and are being reported together because they were combined under one BPA agreement for contracting.
","language":"English","publisher":"Bonneville Power Administration","usgsCitation":"Liedtke, T.L., Weiland, L.K., Skalicky, J., Harris, J., Blanchard, M.R., Grote, A.B., Gray, A.E., and Ekstrom, B.K., 2024, Pacific Lamprey responses to stressors: Dewatering and electrofishing, 70 p.","productDescription":"70 p.","ipdsId":"IP-164929","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":430897,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":430866,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.cbfish.org/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Liedtke, Theresa L. 0000-0001-6063-9867 tliedtke@usgs.gov","orcid":"https://orcid.org/0000-0001-6063-9867","contributorId":2999,"corporation":false,"usgs":true,"family":"Liedtke","given":"Theresa","email":"tliedtke@usgs.gov","middleInitial":"L.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":905972,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Weiland, Lisa K. 0000-0002-9729-4062 lweiland@usgs.gov","orcid":"https://orcid.org/0000-0002-9729-4062","contributorId":3565,"corporation":false,"usgs":true,"family":"Weiland","given":"Lisa","email":"lweiland@usgs.gov","middleInitial":"K.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":905973,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Skalicky, Joe","contributorId":340042,"corporation":false,"usgs":false,"family":"Skalicky","given":"Joe","email":"","affiliations":[{"id":81432,"text":"U.S. Fish and Wildlife Service, Columbia River Fish and Wildlife Conservation Office, Vancouver, Washington","active":true,"usgs":false}],"preferred":false,"id":905974,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Harris, Julie","contributorId":340043,"corporation":false,"usgs":false,"family":"Harris","given":"Julie","email":"","affiliations":[{"id":81432,"text":"U.S. Fish and Wildlife Service, Columbia River Fish and Wildlife Conservation Office, Vancouver, Washington","active":true,"usgs":false}],"preferred":false,"id":905975,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Blanchard, Monica R.","contributorId":316728,"corporation":false,"usgs":false,"family":"Blanchard","given":"Monica","email":"","middleInitial":"R.","affiliations":[{"id":68685,"text":"Washington Department of Fish and Wildlife, 5525 S 11th St, Ridgefield, Washington 98642","active":true,"usgs":false}],"preferred":false,"id":905976,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Grote, Ann B.","contributorId":169715,"corporation":false,"usgs":false,"family":"Grote","given":"Ann","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":905977,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gray, Ann E.","contributorId":195113,"corporation":false,"usgs":false,"family":"Gray","given":"Ann","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":905978,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ekstrom, Brian K. 0000-0002-1162-1780 bekstrom@usgs.gov","orcid":"https://orcid.org/0000-0002-1162-1780","contributorId":3704,"corporation":false,"usgs":true,"family":"Ekstrom","given":"Brian","email":"bekstrom@usgs.gov","middleInitial":"K.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":905979,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70257648,"text":"70257648 - 2024 - State of California sea level rise guidance: 2024 Science and policy update","interactions":[],"lastModifiedDate":"2024-08-21T15:18:18.630279","indexId":"70257648","displayToPublicDate":"2024-07-01T10:09:12","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"title":"State of California sea level rise guidance: 2024 Science and policy update","docAbstract":"No abstract available.
","language":"English","publisher":"California Ocean Protection Council/California Ocean Science Science Trust","usgsCitation":"Adusumilli, S., Barnard, P.L., Cayan, D., Engeman, L., Griggs, G., Hamlington, B.D., Hill, K., Landerer, F., and Thompson, P., 2024, State of California sea level rise guidance: 2024 Science and policy update, 101 p.","productDescription":"101 p.","ipdsId":"IP-153230","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":433006,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":432982,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://opc.ca.gov/","linkFileType":{"id":5,"text":"html"}}],"country":"United 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D.","contributorId":343469,"corporation":false,"usgs":false,"family":"Hamlington","given":"Benjamin","email":"","middleInitial":"D.","affiliations":[{"id":38788,"text":"NASA","active":true,"usgs":false}],"preferred":false,"id":911200,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hill, Kristina","contributorId":343472,"corporation":false,"usgs":false,"family":"Hill","given":"Kristina","email":"","affiliations":[{"id":36942,"text":"University of California, Berkeley","active":true,"usgs":false}],"preferred":false,"id":911204,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Landerer, Felix","contributorId":343532,"corporation":false,"usgs":false,"family":"Landerer","given":"Felix","email":"","affiliations":[],"preferred":false,"id":911205,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Thompson, Phillip","contributorId":343473,"corporation":false,"usgs":false,"family":"Thompson","given":"Phillip","affiliations":[{"id":36402,"text":"University of Hawaii","active":true,"usgs":false}],"preferred":false,"id":911206,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70267248,"text":"70267248 - 2024 - Framework for implementing damping scaling factors in U.S. Geological Survey National Seismic Hazard Models","interactions":[],"lastModifiedDate":"2025-05-20T14:56:34.636132","indexId":"70267248","displayToPublicDate":"2024-07-01T09:56:08","publicationYear":"2024","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Framework for implementing damping scaling factors in U.S. Geological Survey National Seismic Hazard Models","docAbstract":"Traditionally, probabilistic seismic hazard analysis (PSHA) has focused on calculating ground motion hazard curves for elastic, 5%-damped pseudo spectral accelerations, Sa(T,5%), which are used as the basis for engineering design parameters and targets for ground motion selection and modification. However, structures and geotechnical systems can exhibit a wide range of damping ratios both above and below the 5% level, depending on the construction material, structural system, nonstructural elements, or subsurface soil properties. When spectral parameters at such damping levels are required for certain applications, 5%-damped accelerations have traditionally been extracted from PSHA-based hazard curves and adjusted outside of the hazard integral using damping scaling factors (DSF) such as those from Newmark & Hall (1982). Recent advances in the development of more rigorous and comprehensive damping scaling models (e.g., Rezaeian et al., 2014; Rezaeian et al., 2021) have allowed for the modeling of means and standard deviations of DSFs as functions of earthquake source and path properties for crustal, intraslab, and subduction interface tectonic environments. These DSF models can be applied to ground motion model (GMM) estimates of Sa(T,5%) for a given earthquake rupture scenario to produce a corresponding mean and standard deviation Sa at a specified damping ratio β, Sa(T,β). In this study, the DSF models of Rezaeian et al. (2014) and Rezaeian et al. (2021) are implemented within the U.S. Geological Survey National Seismic Hazard Model (NSHM) PSHA framework to calculate probabilistic hazard curves for spectral accelerations at damping ratios from 0.5% to 30%. The DSF models are applied directly to the mean and standard deviation of Sa(T,5%) predictions from each GMM in the NSHM logic tree. Resulting hazard curves and uniform hazard and risk spectra for Sa(T,β) are presented for several geographic locations and compared with corresponding spectra estimated using current design practices by applying the same DSFs outside of the PSHA calculation. Key differences between the two methods for estimating Sa(T,β) are discussed, and potential strategies are presented for the implementation and usage of the hazard-consistent Sa(T,β) in building codes. Comparing the results to those from DSFs used in current design practices that are mainly based on Newmark & Hall (1982) is not explored in this study.
","conferenceTitle":"18th World Conference on Earthquake Engineering","conferenceDate":"June 30- July 5, 2024","conferenceLocation":"Milan, Italy","language":"English","publisher":"International Association of Earthquake Engineering","usgsCitation":"Makdisi, A.J., Smith, D., Rezaeian, S., Powers, P.M., and Withers, K., 2024, Framework for implementing damping scaling factors in U.S. Geological Survey National Seismic Hazard Models, 18th World Conference on Earthquake Engineering, Milan, Italy, June 30- July 5, 2024, 11 p.","productDescription":"11 p.","ipdsId":"IP-159606","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":486139,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://proceedings-wcee.org/view.html?id=23633&conference=18WCEE"},{"id":486214,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Makdisi, Andrew James 0000-0002-8239-0692","orcid":"https://orcid.org/0000-0002-8239-0692","contributorId":267917,"corporation":false,"usgs":true,"family":"Makdisi","given":"Andrew","email":"","middleInitial":"James","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":937507,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, Dallin","contributorId":355505,"corporation":false,"usgs":false,"family":"Smith","given":"Dallin","affiliations":[{"id":6681,"text":"Brigham Young University","active":true,"usgs":false}],"preferred":false,"id":937508,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rezaeian, Sanaz 0000-0001-7589-7893","orcid":"https://orcid.org/0000-0001-7589-7893","contributorId":238513,"corporation":false,"usgs":true,"family":"Rezaeian","given":"Sanaz","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":937509,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Powers, Peter M. 0000-0003-2124-6184 pmpowers@usgs.gov","orcid":"https://orcid.org/0000-0003-2124-6184","contributorId":176814,"corporation":false,"usgs":true,"family":"Powers","given":"Peter","email":"pmpowers@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":937510,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Withers, Kyle 0000-0001-7863-3930","orcid":"https://orcid.org/0000-0001-7863-3930","contributorId":203492,"corporation":false,"usgs":true,"family":"Withers","given":"Kyle","email":"","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":937511,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70267251,"text":"70267251 - 2024 - Effects of stochastically-simulated near-fault ground motions on soil liquefaction","interactions":[],"lastModifiedDate":"2025-05-20T14:51:11.280957","indexId":"70267251","displayToPublicDate":"2024-07-01T09:50:05","publicationYear":"2024","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Effects of stochastically-simulated near-fault ground motions on soil liquefaction","docAbstract":"The scarcity of historically recorded near-fault ground motions poses a challenge to systematically understanding the influence of near-fault effects on various types of seismic demands for engineering purposes. In particular, the current state of knowledge of the influence of ground-shaking intensity on soil liquefaction and its consequences does not specifically account for the effects of near-fault ground motion characteristics. In this study, the influence of near-fault ground motions on liquefaction triggering and lateral spreading are investigated using non-linear modeling of a hypothetical liquefiable soil column in the finite-element computational platform OpenSees subjected to simulated ground motion time series that represent strong earthquake shaking in the near field. The simulated ground motion time series and resulting datasets are based on a parametric stochastic model and are developed for a range of source and path parameters to represent a realistic variability of ground motion characteristics. Dependencies between ground motion intensity measures (IMs) and liquefaction demand parameters are investigated for near-fault pulse and nonpulse-like ground motion sets. Evolutionary IMs, such as cumulative absolute velocity (CAV) and the time-varying magnitude-adjusted peak ground acceleration (PGAM), are considered in developing liquefaction triggering probability density functions. Post-liquefaction triggering responses such as lateral spreading displacements are examined in relation to PGAM and CAV. The ground motion simulations are validated by comparing their liquefaction-capacity PGAM fragilities and post-triggering CAV vulnerability relationships to historical records from the 1994 Northridge earthquake in California, USA. Finally, a path forward for future studies that includes finding systematic differences in the IM-liquefaction demand relationships between near-fault and far-field stochastic ground motion sets is outlined.
","conferenceTitle":"18th World Conference on Earthquake Engineering","conferenceDate":"June 30-July 5., 2024","conferenceLocation":"Milan, Italy","language":"English","publisher":"International Association of Earthquake Engineering","usgsCitation":"Makdisi, A.J., Dabaghi, M., Brito Silveira, L., Rezaeian, S., Haynie, K.L., and Mason, H., 2024, Effects of stochastically-simulated near-fault ground motions on soil liquefaction, 18th World Conference on Earthquake Engineering, Milan, Italy, June 30-July 5., 2024, 12 p.","productDescription":"12 p.","ipdsId":"IP-159292","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":486140,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://proceedings-wcee.org/view.html?id=25504&conference=18WCEE","linkFileType":{"id":5,"text":"html"}},{"id":486213,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2024-07-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Makdisi, Andrew James 0000-0002-8239-0692","orcid":"https://orcid.org/0000-0002-8239-0692","contributorId":267917,"corporation":false,"usgs":true,"family":"Makdisi","given":"Andrew","email":"","middleInitial":"James","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":937512,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dabaghi, Mayssa","contributorId":221888,"corporation":false,"usgs":false,"family":"Dabaghi","given":"Mayssa","email":"","affiliations":[{"id":40455,"text":"American University of Beirut","active":true,"usgs":false}],"preferred":false,"id":937513,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brito Silveira, Lianne 0000-0002-8331-7104","orcid":"https://orcid.org/0000-0002-8331-7104","contributorId":355508,"corporation":false,"usgs":true,"family":"Brito Silveira","given":"Lianne","affiliations":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"preferred":true,"id":937514,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rezaeian, Sanaz 0000-0001-7589-7893","orcid":"https://orcid.org/0000-0001-7589-7893","contributorId":238513,"corporation":false,"usgs":true,"family":"Rezaeian","given":"Sanaz","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":937515,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Haynie, Kirstie Lafon 0000-0001-9930-6736","orcid":"https://orcid.org/0000-0001-9930-6736","contributorId":289894,"corporation":false,"usgs":true,"family":"Haynie","given":"Kirstie","email":"","middleInitial":"Lafon","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":937516,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mason, Henry 0000-0003-4279-2854","orcid":"https://orcid.org/0000-0003-4279-2854","contributorId":293188,"corporation":false,"usgs":true,"family":"Mason","given":"Henry","email":"","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":937517,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70257647,"text":"70257647 - 2024 - Lake Ontario April prey fish survey results and Alewife assessment, 2024","interactions":[],"lastModifiedDate":"2024-08-21T14:56:36.633289","indexId":"70257647","displayToPublicDate":"2024-07-01T09:46:00","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":3,"text":"Organization Series"},"title":"Lake Ontario April prey fish survey results and Alewife assessment, 2024","docAbstract":"The Lake Ontario April bottom trawl survey assesses pelagic prey fish populations, in particular Alewife Alosa pseudoharengus, which are the primary prey supporting the lake’s sport fish populations. The 2024 survey included 234 trawls in the main lake and embayments and sampled depths from 3.9 to 245 m (13 – 809 ft). The survey captured 441,942 fish from 28 species with a total weight of 10,519 kg (23,142 lbs.). Alewife were 89% of the total catch by number while Deepwater Sculpin Myoxocephalus thompsonii, Round Goby Neogobius melanostomus, and Rainbow Smelt Osmerus mordax, comprised 4%, 3%, and 2% of the catch respectively.
The estimated Alewife biomass increases slightly from 2023 to 2024 (83.9 to 84.2 kg·ha-1) and was the largest biomass value since whole lake sampling began in 2016. Adult Alewife abundance increased in 2024 as predicted in 2023, and most of the total Alewife biomass was comprised of adult fish (97%), predominantly from the 2020 and 2022 year classes. In contrast, Age-1 Alewife biomass (2.2 kg·ha-1) was the lowest estimated since whole lake sampling began in 2016 (previous range: 2.7 – 26.7 kg·ha-1), indicating reproductive success was poor in 2023. Adult Alewife biomass is predicted to remain relatively high but decline slightly in 2025 and 2026, due to the smaller year classes produced in 2021 and 2023. Alewife condition as measured by the weight of a standard length fish (165 mm; ~6.5 inches), was 32.8 g, which was within of the range of previously observed values (28.0 – 35.9 g, 1997 – 2023). Acoustic-based prey fish densities, in the water above the bottom trawl, were similar to observations from 2021 – 2023 and were orders of magnitude lower than bottom trawl densities. These acoustic results support the seasonal timing of the April survey, when the majority of Alewife and other pelagic prey fishes are near the lake bottom and susceptible to capture with bottom trawls.
The trawl survey also provides information on the status of other pelagic prey fishes and native fish restorations. In 2024, biomass indices for Rainbow Smelt, Emerald Shiner Notropis atherinoides, and Threespine Stickleback Gasterosteus aculeatus, were similar to 2023 values while the index for Cisco Coregonus artedi declined. The density index for naturally reproduced, juvenile Lake Trout Salvelinus namaycush declined relative to 2023. Density estimates of Lake Whitefish Coregonus clupeaformis continue to be orders of magnitude lower in U.S. waters relative to Canadian waters. A single purported Bloater Coregonus hoyi (total length = 148 mm, sampling depth = 105 m) was captured near Rochester, NY during the 2024 survey. This is the eighth Bloater recaptured during this survey since restoration stocking began in 2012.
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line","interactions":[],"lastModifiedDate":"2026-01-27T15:18:40.916703","indexId":"70273748","displayToPublicDate":"2024-07-01T09:17:20","publicationYear":"2024","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Untangling the knots: A procedure for identifying discernibility conflicts on a cartographic line","docAbstract":"Reducing detail on polyline features aids in legibility, allowing features to appear more distinct and preventing coalescence with other features. Current metrics for evaluating generalization outcomes emphasize geometric change rather than legibility. The present study reports on development and testing of a vector-based metric of the discernibility of a single polyline feature or group of features, defined as the absence of visual coalescence at a target map scale. This metric prioritizes legibility problems due to resolution and the physical/optical limits of discernibility. The metric identifies specific locations of coalescence, and is invariant to translation and rotation, providing a consistent measure across display contexts. A procedure for computing the above definition of discernibility and identifying the locations of discernibility conflicts will be presented. The algorithm is currently being tested in python code, and the goal is to include this tool in an open source python toolbox for cartographic generalization assessment.","conferenceTitle":"Cartography and Geographic Information Society (CaGIS) and the University Consortium for Geographic Information Science (UCGIS) 2024 Symposium","conferenceDate":"June 3-6, 2024","conferenceLocation":"Columbus, OH","language":"English","publisher":"The Cartography and Geographic Information Society (CaGIS) and the University Consortium for Geographic Information Science (UCGIS)","usgsCitation":"Kronenfeld, B.J., Buttenfield, B.P., Stanislawski, L., and Shavers, E.J., 2024, Untangling the knots: A procedure for identifying discernibility conflicts on a cartographic line, Cartography and Geographic Information Society (CaGIS) and the University Consortium for Geographic Information Science (UCGIS) 2024 Symposium, Columbus, OH, June 3-6, 2024, 48, 4 p.","productDescription":"48, 4 p.","ipdsId":"IP-162432","costCenters":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"links":[{"id":499089,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":499086,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://cartogis.org/conferences/cagis2024/program/"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kronenfeld, Barry J. 0000-0002-9518-2462","orcid":"https://orcid.org/0000-0002-9518-2462","contributorId":207104,"corporation":false,"usgs":false,"family":"Kronenfeld","given":"Barry","email":"","middleInitial":"J.","affiliations":[{"id":5043,"text":"Eastern Illinois University","active":true,"usgs":false}],"preferred":false,"id":954530,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Buttenfield, Barbara P. 0000-0001-5961-5809","orcid":"https://orcid.org/0000-0001-5961-5809","contributorId":206887,"corporation":false,"usgs":false,"family":"Buttenfield","given":"Barbara","email":"","middleInitial":"P.","affiliations":[{"id":16144,"text":"University of Colorado-Boulder","active":true,"usgs":false}],"preferred":false,"id":954531,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stanislawski, Larry 0000-0002-9437-0576","orcid":"https://orcid.org/0000-0002-9437-0576","contributorId":217849,"corporation":false,"usgs":true,"family":"Stanislawski","given":"Larry","affiliations":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":954532,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shavers, Ethan J. 0000-0001-9470-5199 eshavers@usgs.gov","orcid":"https://orcid.org/0000-0001-9470-5199","contributorId":206890,"corporation":false,"usgs":true,"family":"Shavers","given":"Ethan","email":"eshavers@usgs.gov","middleInitial":"J.","affiliations":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":954533,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70261254,"text":"70261254 - 2024 - 2024 Crustal Deformation Modeling Workshop report","interactions":[],"lastModifiedDate":"2024-12-04T15:17:20.396096","indexId":"70261254","displayToPublicDate":"2024-07-01T09:15:56","publicationYear":"2024","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"2024 Crustal Deformation Modeling Workshop report","docAbstract":"The 2024 Crustal Deformation Modeling Workshop was held June 10–14 at the Colorado School of Mines. The workshop included two days of tutorials on using PyLith for crustal deformation modeling, followed by three days of science talks and discussions. The workshop focused on four primary themes:
● Constraining long-term fault slip rates and their uncertainties using geodetic and geologic data;
● Earthquake cycle modeling with a focus on constraining models using seismic and geodetic data;
● Interaction of fluids and faulting; and
● Separating contributions of surface loading and tectonic loading in crustal deformation.
The complete agenda is available on the CIG website.
","conferenceTitle":"2024 Crustal Deformation Modeling Workshop","conferenceDate":"June 10-14, 2024","conferenceLocation":"Golden, CO","language":"English","publisher":"Computational Infrastructure for Geodynamics","usgsCitation":"Aagaard, B.T., Knepley, M., Lindsey, E., Materna, K.Z., Martens, H.R., and Williams, C., 2024, 2024 Crustal Deformation Modeling Workshop report, 2024 Crustal Deformation Modeling Workshop, Golden, CO, June 10-14, 2024, 4 p.","productDescription":"4 p.","ipdsId":"IP-172275","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":464748,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":464724,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://geodynamics.org/resources/2113/supportingdocs"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Aagaard, Brad T. 0000-0002-8795-9833 baagaard@usgs.gov","orcid":"https://orcid.org/0000-0002-8795-9833","contributorId":192869,"corporation":false,"usgs":true,"family":"Aagaard","given":"Brad","email":"baagaard@usgs.gov","middleInitial":"T.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":false,"id":920126,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Knepley, Matthew","contributorId":304241,"corporation":false,"usgs":false,"family":"Knepley","given":"Matthew","affiliations":[{"id":37334,"text":"University at Buffalo","active":true,"usgs":false}],"preferred":false,"id":920127,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lindsey, Eric","contributorId":261913,"corporation":false,"usgs":false,"family":"Lindsey","given":"Eric","email":"","affiliations":[{"id":48937,"text":"Earth Observatory of Singapore, Nanyang Technological University, Singapore","active":true,"usgs":false}],"preferred":false,"id":920128,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Materna, Kathryn Z. 0000-0002-6687-980X","orcid":"https://orcid.org/0000-0002-6687-980X","contributorId":209697,"corporation":false,"usgs":false,"family":"Materna","given":"Kathryn","middleInitial":"Z.","affiliations":[{"id":13693,"text":"University of Colorado Boulder","active":true,"usgs":false}],"preferred":false,"id":920129,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Martens, Hilary R","contributorId":215383,"corporation":false,"usgs":false,"family":"Martens","given":"Hilary","email":"","middleInitial":"R","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":920130,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Williams, Charles 0000-0001-7435-9196","orcid":"https://orcid.org/0000-0001-7435-9196","contributorId":243027,"corporation":false,"usgs":false,"family":"Williams","given":"Charles","email":"","affiliations":[{"id":36277,"text":"GNS Science","active":true,"usgs":false}],"preferred":false,"id":920131,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70272709,"text":"70272709 - 2024 - Impacts of convective storms on runoff, erosion, and carbon export in a continuous permafrost landscape","interactions":[],"lastModifiedDate":"2025-12-08T14:19:02.218112","indexId":"70272709","displayToPublicDate":"2024-07-01T08:57:37","publicationYear":"2024","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Impacts of convective storms on runoff, erosion, and carbon export in a continuous permafrost landscape","docAbstract":"Permafrost holds more than twice the amount of carbon currently in the atmosphere, but this large carbon reservoir is vulnerable to thaw and erosion under a rapidly changing Arctic climate. Convective storms are becoming increasingly common during Arctic summers and can amplify runoff and erosion. These extreme events, in concert with active layer deepening, may accelerate carbon loss from the Arctic landscape. However, we lack measurements of carbon fluxes during these events.\nRivers are sensitive to physical, chemical, and hydrological perturbations, and thus are excellent systems for studying landscape responses to thunderstorms. We present observations from the Canning River, Alaska, which drains the northern Brooks Range and flows across a continuous permafrost landscape to the Beaufort Sea. During summer 2022 and 2023 field campaigns, we opportunistically monitored river discharge, sediment, and organic carbon fluxes during several thunderstorms. During one notable storm, river discharge nearly doubled from ~130 m3/s to ~240 m3/s, suspended sediment flux increased 70-fold, and the particulate organic carbon (POC) flux increased 90-fold relative to non-storm conditions. Taken together, the river exported ~16 metric tons of POC over one hour of this sustained event, not including the additional flux of woody debris. Furthermore, the dissolved organic carbon (DOC) flux nearly doubled. Although these thunderstorm-driven fluxes are short-lived (hours to days), they play an outsized role in exporting organic carbon from Arctic rivers. Understanding how these extreme events impact river water, sediment, and carbon dynamics will help predict how Arctic climate change will modify the global carbon cycle.","conferenceTitle":"12th International Conference on Permafrost","conferenceDate":"June 16-20, 2024","conferenceLocation":"Whitehorse, Yukon","language":"English","publisher":"International Conference on Permafrost","doi":"10.52381/ICOP2024.104.1","usgsCitation":"Repasch, M., Arcuri, J., Overeem, I., Anderson, S.P., Anderson, R.G., and Koch, J.C., 2024, Impacts of convective storms on runoff, erosion, and carbon export in a continuous permafrost landscape, 12th International Conference on Permafrost, Whitehorse, Yukon, June 16-20, 2024, p. 341-348, https://doi.org/10.52381/ICOP2024.104.1.","productDescription":"8 p.","startPage":"341","endPage":"348","ipdsId":"IP-157679","costCenters":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"links":[{"id":497137,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Canning River, North Slope","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -144.75,\n 70.25\n ],\n [\n -146.5,\n 70.25\n ],\n [\n -146.5,\n 68.5\n ],\n [\n -144.75,\n 68.5\n ],\n [\n -144.75,\n 70.25\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2024-06-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Repasch, Marisa 0000-0003-2636-9896","orcid":"https://orcid.org/0000-0003-2636-9896","contributorId":334190,"corporation":false,"usgs":false,"family":"Repasch","given":"Marisa","email":"","affiliations":[],"preferred":false,"id":951399,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Arcuri, Josie","contributorId":363269,"corporation":false,"usgs":false,"family":"Arcuri","given":"Josie","affiliations":[{"id":36621,"text":"University of Colorado","active":true,"usgs":false}],"preferred":false,"id":951400,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Overeem, Irina","contributorId":197487,"corporation":false,"usgs":false,"family":"Overeem","given":"Irina","email":"","affiliations":[],"preferred":false,"id":951401,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Anderson, Suzanne P. 0000-0002-6796-6649","orcid":"https://orcid.org/0000-0002-6796-6649","contributorId":172732,"corporation":false,"usgs":false,"family":"Anderson","given":"Suzanne","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":951402,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Anderson, Robert G.","contributorId":197569,"corporation":false,"usgs":false,"family":"Anderson","given":"Robert","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":951403,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Koch, Joshua C. 0000-0001-7180-6982 jkoch@usgs.gov","orcid":"https://orcid.org/0000-0001-7180-6982","contributorId":202532,"corporation":false,"usgs":true,"family":"Koch","given":"Joshua","email":"jkoch@usgs.gov","middleInitial":"C.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":951404,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70259712,"text":"70259712 - 2024 - New 10Be-26Al isochron burial dating informs the Pliocene and Pleistocene evolution of the lower Colorado River, southwestern United States","interactions":[],"lastModifiedDate":"2024-10-19T13:59:50.376643","indexId":"70259712","displayToPublicDate":"2024-07-01T08:55:25","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1582,"text":"Episodes","active":true,"publicationSubtype":{"id":10}},"title":"New 10Be-26Al isochron burial dating informs the Pliocene and Pleistocene evolution of the lower Colorado River, southwestern United States","docAbstract":"Four new 10Be-26Al isochron burial ages ranging from 4.4 to 2 Ma on ancestral Colorado River deposits in the lower Colorado River corridor (LCRC) help constrain the river’s evolution during the Pliocene and early Pleistocene. They help fill a gap between previous work that focused on older and younger deposits: Older dated deposits include the 5 Ma Bouse Formation, which records the integration of the Colorado River through a series of preexisting basins to the Gulf of California and the ca. 4.5 - 3.5 Ma Bullhead Alluvium, a 200 to 300 m thick aggregational package that immediately followed integration. The much younger, 100 - 70 ka, Chemehuevi Formation is another major aggradation package mapped throughout the LCRC. The new burial ages on the facies of Santa Fe Railway (4.37 ± 0.71 Ma), boulder conglomerate of Bat Cave Wash (2.12 ± 0.26 and 2.05 ± 0.31 Ma), and the Palo Verde alluvium (3.03 ± 0.26 Ma) partially fill in a 3.5 M.y. gap between the deposition of the Bullhead Alluvium and the Chemeheuvi Formation and document the timescales over which the Colorado River was able to remove the Bullhead aggradational package and initiate newer and smaller aggradational pulses.
As part of the 2014 Chesapeake Bay Watershed Agreement, all Bay States and the District of Columbia have committed to improving the condition of the Bay, which includes a goal to achieve sustainable fisheries. One outcome under that broad goal is improved effectiveness of fish habitat conservation and preservation efforts. In support of that outcome, the U.S. Geological Survey Eastern Ecological Science Center (USGS-EESC) and the National Oceanic and Atmospheric Association’s National Centers for Coastal Ocean Science (NOAA-NCCOS) are actively developing datasets, methods, and analyses to conduct fish habitat assessments in the Chesapeake Bay watershed, guided by recommendations from a regional stakeholder workshop held by the Chesapeake Bay Program’s (CBP) Fish Habitat Action Team (FHAT) in 2018. The joint USGS and NOAA team has been collaborating on methods for conducting inland and estuarine assessments and exploring whether a seamless headwater to estuary assessment could be developed. The goals of this assessment are to benefit both State and Federal fisheries managers, help advance fisheries science, and provide beneficial information for the public. While past national and regional assessments (e.g. the National Fish Habitat Partnership National Assessment) treated inland and estuarine fish habitat conditions separately due to differences in environments, GIS data representation, and data availability, a seamless habitat assessment could be of value for a broad range of stakeholders as many fish species, several of which are invasive or under federal jurisdiction, use habitats across both inland and estuarine waters. This project developed a pilot framework, explored and tested methods necessary for a finer scale, seamless assessment across both inland and estuarine waters, and demonstrated its use.
Although there was interest by the CBP FHAT for the generation of a Baywide fish habitat assessment that spanned tidal salt, tidal fresh, warm non-tidal and cold non-tidal waters, there are a myriad of implementation details and considerations around conducting a Baywide assessment across all four of these general habitat areas. Therefore, the practical need to conduct a tributary-specific pilot assessment arose. At the beginning of this pilot process, members of the FHAT were presented with a decision matrix to choose a study basin using factors such as data availability and tributary size. FHAT members chose the Patuxent River basin, which has been relatively well sampled and studied. Several spatial frameworks were considered before selection of an inclusive gridded framework for summary and analysis that represented inland drainage networks and landscape influences as well as estuarine bathymetry. A suite of landscape and in-water stressor variables were summarized into the framework and were largely generalized over time. In order to assess the viability of the framework, we chose to use species distribution modeling for each of the species to test the framework’s ability to predict habitat use of non-tidal resident, estuarine resident, and migratory species. Tessellated darter (Etheostoma olmstedi), American eel (Anguilla rostrata), and white perch (Morone americana) were chosen as illustrative fish species based on data availability, and differences in life history and habitat use. A nested modeling approach, which involved successive model runs at multiple scales (1000m, 100m, and 10m raster grids) was developed to examine differences in variable importance at different spatial scales and to enhance modeling efficiency. For white perch, a complementary modeling analysis was performed for variables available only in estuarine waters. For all testing, an ensemble modeling approach was conducted, using a suite of potential statistical techniques driven by model strength and variable predictive power. The statistical testing that we conducted was intended only to test the framework and modeling approach, and not to definitively predict all habitats where specific fish species might be present. The modeling we conducted to test the framework did have some limitations. For example, the spatial distribution of favorable habitat areas for white perch was likely influenced by the predominance of fish survey locations near the center channel of the river and the use of generalized in-water conditions. For all species, the use of juvenile and adult fish survey data limits the estimation of habitat use to those life stages. Despite such limitations of the data inputs and modeling approach, we found the framework could seamlessly predict fish habitat distribution across freshwater and tidal environments and integrate the influence of landscape stressors with local in-water factors. The developed framework presented to the Sustainable Fisheries Goal Implementation Team (GIT) and FHAT is informative and could potentially be used for other modeling applications in the Chesapeake Bay watershed and elsewhere. In particular the framework and modeling approach lend themselves to evaluating living resource distributions and underlying habitat conditions in shallow tidal waters and beyond, as recommended by the recent Comprehensive Evaluation of System Response (CESR) report from the Chesapeake Bay Program.
","language":"English","publisher":"NOAA","doi":"10.25923/4jqw-mw29","usgsCitation":"Nisonson, H., Kiser, A.H., Gressler, B.P., Leight, A., and Young, J.A., 2024, Pilot framework for fish habitat assessments across tidal and non tidal waters in the Patuxent River Basin: NOAA Technical Memorandum NOS NCCOS 332, vi, 41 p., https://doi.org/10.25923/4jqw-mw29.","productDescription":"vi, 41 p.","ipdsId":"IP-163665","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":432484,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland","otherGeospatial":"Patuxent River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -76.5870885061828,\n 38.29653642168418\n ],\n [\n -76.39765972760698,\n 38.2523876845089\n ],\n [\n -76.39469990294168,\n 38.39635283845547\n ],\n [\n -76.5219723635473,\n 38.51224538633858\n ],\n [\n -76.5930081555134,\n 38.75962947245472\n ],\n [\n -76.57524920752218,\n 38.93252018914461\n ],\n [\n -76.82683430406816,\n 39.192214789667304\n ],\n [\n -77.06635333905636,\n 39.45429197245687\n ],\n [\n -77.25054644375115,\n 39.48452671490274\n ],\n [\n -77.41561427713579,\n 39.40769859848646\n ],\n [\n -77.04882238288116,\n 39.139433495010024\n ],\n [\n -76.96002764292388,\n 39.04065023841653\n ],\n [\n -76.82979535765293,\n 38.90718862957951\n ],\n [\n -76.82091588365701,\n 38.66493779010759\n ],\n [\n -76.74100152907371,\n 38.412588059675414\n ],\n [\n -76.5870885061828,\n 38.29653642168418\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Nisonson, H","contributorId":342011,"corporation":false,"usgs":false,"family":"Nisonson","given":"H","affiliations":[{"id":81821,"text":"Cooperative Oxford Lab","active":true,"usgs":false}],"preferred":false,"id":909477,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kiser, Alexander H. 0000-0002-2871-0640","orcid":"https://orcid.org/0000-0002-2871-0640","contributorId":342012,"corporation":false,"usgs":true,"family":"Kiser","given":"Alexander","middleInitial":"H.","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":909478,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gressler, Benjamin P. 0000-0001-6639-8558","orcid":"https://orcid.org/0000-0001-6639-8558","contributorId":270167,"corporation":false,"usgs":true,"family":"Gressler","given":"Benjamin","middleInitial":"P.","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":909479,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Leight, A","contributorId":342013,"corporation":false,"usgs":false,"family":"Leight","given":"A","email":"","affiliations":[{"id":81821,"text":"Cooperative Oxford Lab","active":true,"usgs":false}],"preferred":false,"id":909480,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Young, John A. 0000-0002-4500-3673 jyoung@usgs.gov","orcid":"https://orcid.org/0000-0002-4500-3673","contributorId":3777,"corporation":false,"usgs":true,"family":"Young","given":"John","email":"jyoung@usgs.gov","middleInitial":"A.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":909481,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70259933,"text":"70259933 - 2024 - Oil and gas development influences potential for dust emission from the Upper Colorado River Basin, USA","interactions":[],"lastModifiedDate":"2024-10-30T21:48:35.428948","indexId":"70259933","displayToPublicDate":"2024-07-01T07:09:35","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1425,"text":"Earth Surface Processes and Landforms","active":true,"publicationSubtype":{"id":10}},"title":"Oil and gas development influences potential for dust emission from the Upper Colorado River Basin, USA","docAbstract":"Wind erosion and dust emission from drylands have large consequences for ecosystem function and human health. Wind erosion is naturally reduced by soil crusting and sheltering by non-erodible roughness elements such as plants. Land uses that reduce surface roughness and disturb the soil surface can dramatically increase dust emission. Extraction of oil and gas is a common and growing land use in the western United States (US) that removes vegetation and other roughness elements for construction of well pads and unpaved access roads, resulting in thousands of small (1–4 ha), discrete patches of unprotected soil. Here, we use a satellite albedo-based model to assess the effect of oil/gas activity on surface roughness in the Uinta-Piceance Basin, an area of the Upper Colorado River Basin (UCRB) with dense oil and natural gas development and modelled how the change in surface roughness could impact aeolian sediment flux and dust emission. We also investigated how regional drought influences the response of surface roughness to well pads and access roads. Oil/gas activity reduced surface roughness and increased modelled aeolian sediment flux at the landscape scale across much of the study region, resulting in a modest increase of 10 139 kg of dust per year, which is small relative to dust loads from a single regional dust event observed in the region, but downwind impact could be significant. The magnitude of surface roughness reductions by oil/gas activity was generally consistent among land cover types. However, in parts of the basin that had high cover of annual forbs and grasses, oil/gas activity was associated with larger surface roughness and smaller potential dust emission. Drought decreased surface roughness across disturbed and undisturbed sites, but there was no interactive effect of oil/gas activity and drought on surface roughness. These results suggest that oil/gas activity may increase sediment fluxes and likely contributes to dust emission from landscapes in the UCRB. Understanding how drought and land use change contribute to dust emissions will benefit mitigation of undesirable impacts of wind erosion and dust transport.
","language":"English","publisher":"British Society for Geomorphology","doi":"10.1002/esp.5887","usgsCitation":"Tyree, G.L., Chappell, A., Villarreal, M.L., Dhital, S., Duniway, M.C., Edwards, B., Faist, A., Nauman, T., and Webb, N., 2024, Oil and gas development influences potential for dust emission from the Upper Colorado River Basin, USA: Earth Surface Processes and Landforms, v. 49, no. 11, p. 3292-3307, https://doi.org/10.1002/esp.5887.","productDescription":"16 p.","startPage":"3292","endPage":"3307","ipdsId":"IP-158320","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":466989,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/esp.5887","text":"Publisher Index Page"},{"id":463243,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, Utah","otherGeospatial":"Upper Colorado River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -112.52852783555946,\n 41.270866482469955\n ],\n [\n -112.52852783555946,\n 37.65911929948223\n ],\n [\n -106.31026611680981,\n 37.65911929948223\n ],\n [\n -106.31026611680981,\n 41.270866482469955\n ],\n [\n -112.52852783555946,\n 41.270866482469955\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"49","issue":"11","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Tyree, Gayle Loren 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mvillarreal@usgs.gov","orcid":"https://orcid.org/0000-0003-0720-1422","contributorId":1424,"corporation":false,"usgs":true,"family":"Villarreal","given":"Miguel","email":"mvillarreal@usgs.gov","middleInitial":"L.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":916867,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dhital, S.","contributorId":345531,"corporation":false,"usgs":false,"family":"Dhital","given":"S.","email":"","affiliations":[{"id":80080,"text":"USDA-ARS Jornada Experimental Range, Las Cruces, NM, USA","active":true,"usgs":false}],"preferred":false,"id":916868,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Duniway, Michael C. 0000-0002-9643-2785 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USA","active":true,"usgs":false}],"preferred":false,"id":916871,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Nauman, T.W.","contributorId":345534,"corporation":false,"usgs":false,"family":"Nauman","given":"T.W.","email":"","affiliations":[{"id":82620,"text":"USDA-NRCS National Soil Survey Center, Lincoln, NE, USA","active":true,"usgs":false}],"preferred":false,"id":916872,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Webb, N.P.","contributorId":345535,"corporation":false,"usgs":false,"family":"Webb","given":"N.P.","email":"","affiliations":[{"id":80080,"text":"USDA-ARS Jornada Experimental Range, Las Cruces, NM, USA","active":true,"usgs":false}],"preferred":false,"id":916873,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70255704,"text":"70255704 - 2024 - Reduction of large vessel traffic improves water quality and alters fish habitat-use throughout a large river","interactions":[],"lastModifiedDate":"2024-07-02T11:59:32.798901","indexId":"70255704","displayToPublicDate":"2024-07-01T06:57:02","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Reduction of large vessel traffic improves water quality and alters fish habitat-use throughout a large river","docAbstract":"Rivers are increasingly used as superhighways for the continental-scale transportation of freight goods, but the ecological impact of large vessel traffic on river ecosystems is difficult to study. Recently, the temporary maintenance closure of lock and dam systems on the Illinois Waterway (USA) brought commercial vessel traffic to a halt along the river's length, offering a rare opportunity to study the response of the ecosystem before, during, and after an extended pause of this persistent anthropogenic disturbance. We observed improvements in main- and side-channel water quality and a redistribution of fish habitat-use during a months-long, near-complete reduction of large vessel traffic. Over 3600 water quality and 1300 fish community samples indicate that large vessel traffic reduction coincided with a 33 % reduction in turbidity as well as increased use of sampling strata near vessel navigation corridors by sound-sensitive and rheophilic fishes. Gizzard shad (Dorosoma cepedianum), the most abundant species in the system, also expanded their use of these ‘impact’ areas. Though inland waterway transport is an economically- and climate-friendly alternative to trucking and rail for the shipment of freight, our data suggest that intense vessel traffic may have profound physical and biological impacts across a large river. Monitoring and mitigation of ecological impacts of the ongoing expansion of inland waterway transport around the world will be critical to balancing large rivers as both useful navigation corridors and functional ecosystems.
Side-scan sonar (SSS) is a powerful tool that can be used to address many key questions in fisheries science. In principle, SSS uses dual transducers to transmit a narrow-beam, wide-angle acoustic signal as the survey vessel transits an area. The intensity of reflected sound is recorded to generate an image mosaic comprised of benthic substrates and targets in the water column, including organisms such as fish. Although SSS has been around for decades, recent advancements have opened new opportunities to leverage this technology to directly measure fish populations. In this paper, we review the current state of the science and identify opportunities to further refine SSS for fisheries applications.
We developed Vp, Vs, Vp/Vs ratio, and Poisson’s ratio models of the uppermost crust (<4 km depth) from the eastern San Francisco (SF) Bay (California, USA) to near the Calaveras fault along a 15-km-long, linear profile. Upper crustal velocities are highly variable beneath, west, and well east of the Hayward fault. We observe eight notable features, from west to east: (1) Near San Francisco Bay, there is an ~2-km-wide structure with high Vp/Vs ratios (up to 5) and Poisson’s ratios (up to 0.48) extending from the surface to the base of our model, which we suggest the structure is a near-vertical fault that lies along a straight-line projection between the Silver Creek fault to the south and the Point Richmond fault to the north. The structure may be part of an ~90-km-long fault along the eastern SF Bay. (2) The western East Bay Plain, the lower lying area between the bay and the hills, includes up to 800 m of low-velocity sediments (Vp ~1600–3000 m/s, Vs ~500 m/s to ~1000 m/s), underlain by higher velocity basement rocks (Vp ~3000–5800 m/s; Vs ~1000–1500 m/s). (3) Between ~1 km and 3 km east of the Bay shoreline, sediments thin in a series of steps (likely faults) toward the Hayward fault. (4) Between ~3 km west and ~1 km east of the Hayward fault (at the East Chabot fault) at depths greater than 1 km, basement Vp (up to 6000 m/s) and Vs (up to 2800 m/s) are high, and Vp/Vs ratios (<2) and Poisson’s ratios (<0.3) are low, suggesting crystalline rocks. Furthermore, a near-vertical zone of low Vp/Vs ratios and Poisson’s ratios is between near-surface traces of the Hayward and East Chabot faults, likely corresponding to the San Leandro Gabbro of Ponce et al. (2003). (5) Eastward of the East Chabot fault in the upper 1.5 km, basement Vp (~3000 m/s to ~4200 m/s) and Vs (~1200–2000 m/s) are lower than those west of the fault. (6) In the eastern Hayward/Oakland Hills, there are zones of laterally varying, high- and low-velocity (Vp ~2500–3000 m/s) Jurassic–Cretaceous and Tertiary sediments in the shallow subsurface that likely extend much deeper than imaged. (7) Seismic energy that propagates westward from sources east of the Hayward fault (HF) appear weaker than energy that propagates eastward from sources west of the HF, suggesting that the HF acts as a partial barrier to shallow seismic energy propagation into the more populated eastern SF Bay area. (8) Unlike many fault zones, it appears that the active trace of the Hayward fault (in our study area) is not cored by a prominent, low-velocity zone relative to rocks to the east and west of the active trace. However, the active trace does mark a prominent change from relatively higher velocities to the west and lower velocities to the east.
","language":"English","publisher":"GeoScienceWorld","doi":"10.1130/B36919.1","usgsCitation":"Catchings, R.D., Strayer, L.M., Chan, J.H., Goldman, M., McEvilly, A., and Suppe, J., 2024, Upper crustal seismic velocity structure of the Hayward fault zone, San Francisco Bay, California, USA: Results from the 2016 East Bay Seismic Experiment (EBSI-16): GSA Bulletin, v. 136, no. 7-8, p. 3261-3276, https://doi.org/10.1130/B36919.1.","productDescription":"16 p.","startPage":"3261","endPage":"3276","ipdsId":"IP-124842","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":482454,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.49518270211846,\n 37.855388424415295\n ],\n [\n -122.49518270211846,\n 37.389789695119845\n ],\n [\n -121.96137507277817,\n 37.389789695119845\n ],\n [\n -121.96137507277817,\n 37.855388424415295\n ],\n [\n -122.49518270211846,\n 37.855388424415295\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"136","issue":"7-8","noUsgsAuthors":false,"publicationDate":"2024-01-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Catchings, Rufus D. 0000-0002-5191-6102 catching@usgs.gov","orcid":"https://orcid.org/0000-0002-5191-6102","contributorId":1519,"corporation":false,"usgs":true,"family":"Catchings","given":"Rufus","email":"catching@usgs.gov","middleInitial":"D.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":928559,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Strayer, Luther M.","contributorId":139930,"corporation":false,"usgs":false,"family":"Strayer","given":"Luther","email":"","middleInitial":"M.","affiliations":[{"id":13318,"text":"California State University East Bay","active":true,"usgs":false}],"preferred":false,"id":928585,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chan, Joanne H. 0000-0002-2065-2423 jchan@usgs.gov","orcid":"https://orcid.org/0000-0002-2065-2423","contributorId":178625,"corporation":false,"usgs":true,"family":"Chan","given":"Joanne","email":"jchan@usgs.gov","middleInitial":"H.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":928586,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Goldman, Mark 0000-0002-0802-829X","orcid":"https://orcid.org/0000-0002-0802-829X","contributorId":205863,"corporation":false,"usgs":true,"family":"Goldman","given":"Mark","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":928587,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McEvilly, Andrian T.","contributorId":351006,"corporation":false,"usgs":false,"family":"McEvilly","given":"Andrian T.","affiliations":[],"preferred":false,"id":928588,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Suppe, J.","contributorId":61178,"corporation":false,"usgs":true,"family":"Suppe","given":"J.","email":"","affiliations":[{"id":68365,"text":"Department of Earth and Atmospheric Sciences, University of Houston","active":true,"usgs":false}],"preferred":false,"id":928589,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70257474,"text":"70257474 - 2024 - Predicting the response of a long-distance migrant to changing environmental conditions in winter","interactions":[],"lastModifiedDate":"2024-08-16T15:14:57.180412","indexId":"70257474","displayToPublicDate":"2024-06-29T10:10:26","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Predicting the response of a long-distance migrant to changing environmental conditions in winter","docAbstract":"Access to high-quality food is critical for long-distance migrants to provide energy for migration and arrival at breeding grounds in good condition. We studied effects of changing abundance and availability of a marine food, common eelgrass (Zostera marina L.), on an arctic-breeding, migratory goose, black brant (Brant bernicla nigricans Lawrence 1846), at a key non-breeding site, Bahía San Quintín, Mexico. Eelgrass, the primary food of brant, is consumed when exposed by the tide or within reach from the water's surface. Using an individual-based model, we predicted effects of observed changes (1991–2013) in parameters influencing food abundance and availability: eelgrass biomass (abundance), eelgrass shoot length (availability, as longer shoots more within reach), brant population size (availability, as competition greater with more birds), and sea level (availability, as less food within reach when sea level higher). The model predicted that the ability to gain enough energy to migrate was most strongly influenced by eelgrass biomass (threshold January biomass for migration = 60 g m−2 dry mass). Conversely, annual variation in population size (except for 1998), was relatively low, and variation in eelgrass shoot length and sea level were not strongly related to ability to migrate. We used observed data on brant body mass at Bahía San Quintín and annual survival to test for effects of eelgrass biomass in the real system. The lowest observed values of body mass and survival were in years when biomass was below 60 g m−2, although in some years of low biomass body mass and/or survival was higher. This suggests that the real birds may have some capacity to compensate to meet their energy demands when eelgrass biomass is low. We discuss consequences for brant population trends and conservation.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.11619","usgsCitation":"Stillman, R.A., Rivers, E., Gilkerson, W., Wood, K.A., Clausen, P., Deane, C., and Ward, D.H., 2024, Predicting the response of a long-distance migrant to changing environmental conditions in winter: Ecology and Evolution, v. 14, no. 7, e11619, 15 p., https://doi.org/10.1002/ece3.11619.","productDescription":"e11619, 15 p.","ipdsId":"IP-160623","costCenters":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":439315,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.11619","text":"Publisher Index Page"},{"id":434933,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7T43R88","text":"USGS data release","linkHelpText":"Data from Black Brant (Branta bernicla nigricans) Overwintering in Three Lagoons Along the Baja California Peninsula, Mexico"},{"id":432860,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico","state":"Baja California","otherGeospatial":"Bahía San Quintín","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -116.06430118019601,\n 30.523772316473426\n ],\n [\n -116.06430118019601,\n 30.37195862378512\n ],\n [\n -115.92021973295668,\n 30.37195862378512\n ],\n [\n -115.92021973295668,\n 30.523772316473426\n ],\n [\n -116.06430118019601,\n 30.523772316473426\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"14","issue":"7","noUsgsAuthors":false,"publicationDate":"2024-06-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Stillman, Richard A.","contributorId":151661,"corporation":false,"usgs":false,"family":"Stillman","given":"Richard","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":910500,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rivers, E.M.","contributorId":245657,"corporation":false,"usgs":false,"family":"Rivers","given":"E.M.","email":"","affiliations":[{"id":49249,"text":"Merkel & Associates, Inc.","active":true,"usgs":false}],"preferred":false,"id":910501,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gilkerson, W.","contributorId":245658,"corporation":false,"usgs":false,"family":"Gilkerson","given":"W.","affiliations":[{"id":49250,"text":"Wildfowl & Wetlands Trust","active":true,"usgs":false}],"preferred":false,"id":910502,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wood, K. A.","contributorId":167726,"corporation":false,"usgs":false,"family":"Wood","given":"K.","email":"","middleInitial":"A.","affiliations":[{"id":24818,"text":"Department of Life and Environmental Sciences, Bournemouth University, United Kingdom","active":true,"usgs":false}],"preferred":false,"id":910503,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Clausen, P.","contributorId":245661,"corporation":false,"usgs":false,"family":"Clausen","given":"P.","email":"","affiliations":[{"id":49252,"text":"Department of Bioscience – Wildlife Ecology, Aarhus University","active":true,"usgs":false}],"preferred":false,"id":910505,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Deane, C.","contributorId":342932,"corporation":false,"usgs":false,"family":"Deane","given":"C.","email":"","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":910506,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ward, David H. 0000-0002-5242-2526 dward@usgs.gov","orcid":"https://orcid.org/0000-0002-5242-2526","contributorId":3247,"corporation":false,"usgs":true,"family":"Ward","given":"David","email":"dward@usgs.gov","middleInitial":"H.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":910507,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70255892,"text":"70255892 - 2024 - Use of Doppler velocity radars to monitor and predict debris and flood wave velocities and travel times in post-wildfire basins","interactions":[],"lastModifiedDate":"2024-07-10T14:33:11.692633","indexId":"70255892","displayToPublicDate":"2024-06-29T09:21:56","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5836,"text":"Journal of Hydrology X","onlineIssn":"2589-9155","active":true,"publicationSubtype":{"id":10}},"title":"Use of Doppler velocity radars to monitor and predict debris and flood wave velocities and travel times in post-wildfire basins","docAbstract":"The magnitude and timing of extreme events such as debris and floodflows (collectively referred to as floodflows) in post-wildfire basins are difficult to measure and are even more difficult to predict. To address this challenge, a sensor ensemble consisting of noncontact, ground-based (near-field), Doppler velocity (velocity) and pulsed (stage or gage height) radars, rain gages, and a redundant radio communication network was leveraged to monitor flood wave velocities, to validate travel times, and to compliment observations from NEXRAD weather radar. The sensor ensemble (DEbris and Floodflow Early warNing System, DEFENS) was deployed in Waldo Canyon, Pike National Forest, Colorado, USA, which was burned entirely (100 percent burned) by the Waldo Canyon fire during the summer of 2012 (MTBS, 2020).
Surface velocity, stage, and precipitation time series collected during the DEFENS deployment on 10 August 2015 were used to monitor and predict flood wave velocities and travel times as a function of stream discharge (discharge; streamflow). The 10 August 2015 event exhibited spatial and temporal variations in rainfall intensity and duration that resulted in a discharge equal to 5.01 cubic meters per second (m3/s). Discharge was estimated post-event using a slope-conveyance indirect discharge method and was verified using velocity radars and the probability concept algorithm. Mean flood wave velocities – represented by the kinematic celerity (
Measured flood wave velocities and travel times agreed well with predicted values. Absolute percent differences between predicted and measured flood wave velocities ranged from 1.6 percent to 49 percent and varied with water slope, hydraulic radius, and depth. The kinematic celerity was a better predictor for steep slopes and wide flood plains associated with the Upper Waldo and Middle Waldo radar streamgages; whereas, the dynamic celerity was a better surrogate for shallow slopes and incised channels such as the Lower Waldo radar streamgage.
The method demonstrates the potential extensibility of a post-wildfire warning system by (1) leveraging multiple systems (i.e., weather radar, near-field velocity and stage radars, and rain gages) for accurate and timely warnings of debris and floodflows, (2) establishing an order of operations to site, install, and operate near-field radars and conventional rain gages to record floodflows, forecast travel times, and document geomorphic change in this basin and hydrologically similar basins that lack data, and (3) communicating data operationally with the Colorado Department of Transportation engineering staff, National Weather Service forecasters, and emergency managers.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.hydroa.2024.100180","usgsCitation":"Fulton, J.W., Hall, N.G., Hempel, L.A., Gourley, J., Henneberg, M.F., Kohn, M.S., Farmer, W., Asquith, W.H., Wasielewski, D., Stecklein, A.S., Mommandi, A., and Khan, A., 2024, Use of Doppler velocity radars to monitor and predict debris and flood wave velocities and travel times in post-wildfire basins: Journal of Hydrology X, v. 24, 100180, 17 p., https://doi.org/10.1016/j.hydroa.2024.100180.","productDescription":"100180, 17 p.","ipdsId":"IP-112029","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":439317,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.hydroa.2024.100180","text":"Publisher Index Page"},{"id":430892,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Waldo Canyon basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -105,\n 39\n ],\n [\n -105,\n 38.8333\n ],\n [\n -104.8167,\n 38.8333\n ],\n [\n -104.8167,\n 39\n ],\n [\n -105,\n 39\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"24","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Fulton, John W, 0000-0002-5335-0720","orcid":"https://orcid.org/0000-0002-5335-0720","contributorId":213630,"corporation":false,"usgs":true,"family":"Fulton","given":"John","middleInitial":"W,","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":905913,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hall, Nicholas Graff 0000-0002-7331-8947","orcid":"https://orcid.org/0000-0002-7331-8947","contributorId":315497,"corporation":false,"usgs":true,"family":"Hall","given":"Nicholas","email":"","middleInitial":"Graff","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":905914,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hempel, Laura A. 0000-0001-5020-6056","orcid":"https://orcid.org/0000-0001-5020-6056","contributorId":224286,"corporation":false,"usgs":true,"family":"Hempel","given":"Laura","email":"","middleInitial":"A.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":905915,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gourley, J.J.","contributorId":340018,"corporation":false,"usgs":false,"family":"Gourley","given":"J.J.","email":"","affiliations":[{"id":41181,"text":"NOAA National Severe Storms Laboratory","active":true,"usgs":false}],"preferred":false,"id":905916,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Henneberg, Mark F. 0000-0002-6991-1211 mfhenneb@usgs.gov","orcid":"https://orcid.org/0000-0002-6991-1211","contributorId":187481,"corporation":false,"usgs":true,"family":"Henneberg","given":"Mark","email":"mfhenneb@usgs.gov","middleInitial":"F.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":905917,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kohn, Michael S. 0000-0002-5989-7700 mkohn@usgs.gov","orcid":"https://orcid.org/0000-0002-5989-7700","contributorId":4549,"corporation":false,"usgs":true,"family":"Kohn","given":"Michael","email":"mkohn@usgs.gov","middleInitial":"S.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":905918,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Farmer, William H. 0000-0002-2865-2196","orcid":"https://orcid.org/0000-0002-2865-2196","contributorId":223181,"corporation":false,"usgs":true,"family":"Farmer","given":"William H.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":905919,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Asquith, William H. 0000-0002-7400-1861 wasquith@usgs.gov","orcid":"https://orcid.org/0000-0002-7400-1861","contributorId":1007,"corporation":false,"usgs":true,"family":"Asquith","given":"William","email":"wasquith@usgs.gov","middleInitial":"H.","affiliations":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":905920,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Wasielewski, Daniel","contributorId":340019,"corporation":false,"usgs":false,"family":"Wasielewski","given":"Daniel","email":"","affiliations":[{"id":41181,"text":"NOAA National Severe Storms Laboratory","active":true,"usgs":false}],"preferred":false,"id":905921,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Stecklein, Andrew S.","contributorId":340020,"corporation":false,"usgs":false,"family":"Stecklein","given":"Andrew","email":"","middleInitial":"S.","affiliations":[{"id":78854,"text":"Colorado Department of Transportation","active":true,"usgs":false}],"preferred":false,"id":905922,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Mommandi, Amanullah","contributorId":340021,"corporation":false,"usgs":false,"family":"Mommandi","given":"Amanullah","affiliations":[{"id":78854,"text":"Colorado Department of Transportation","active":true,"usgs":false}],"preferred":false,"id":905923,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Khan, Aziz","contributorId":340022,"corporation":false,"usgs":false,"family":"Khan","given":"Aziz","affiliations":[{"id":78854,"text":"Colorado Department of Transportation","active":true,"usgs":false}],"preferred":false,"id":905924,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70255757,"text":"70255757 - 2024 - Characterising, quantifying, and accessing eruption source parameters of explosive volcanic eruptions for operational simulation of tephra dispersion: A current view and future perspectives","interactions":[],"lastModifiedDate":"2024-07-03T12:02:59.820318","indexId":"70255757","displayToPublicDate":"2024-06-29T07:01:50","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1109,"text":"Bulletin of Volcanology","active":true,"publicationSubtype":{"id":10}},"title":"Characterising, quantifying, and accessing eruption source parameters of explosive volcanic eruptions for operational simulation of tephra dispersion: A current view and future perspectives","docAbstract":"Eruption source parameters (ESPs) are crucial for characterising volcanic eruptions and are essential inputs to numerical models used for hazard assessment. Key ESPs of explosive volcanic eruptions include plume height, mass eruption rate, eruption duration, and grain-size distribution. Some of these ESPs can be directly observed during an eruption, but others are difficult to measure in real-time, or indeed, accurately and precisely quantify afterwards. Estimates of ESPs for eruptions that cannot be observed, for example, due to the remote location of a volcano or poor weather conditions, are often defined using expert judgement and data from past eruptions, both from the volcano of interest and analogue volcanoes farther afield. Analysis of such information is time intensive and difficult, particularly during eruption response. These difficulties have resulted in the production of datasets to aid quick identification of ESPs prior to or during an eruption for use in operational response settings such as those at volcano observatories and Volcanic Ash Advisory Centres. These resources include the Mastin et al. (2009a) ESP dataset and the Catalogue of Icelandic Volcanoes and European Catalogue of Volcanoes aviation tables. Here, we review and compare these resources, which take different approaches to assigning ESPs. We identify future areas for development of these resources, highlighting the need for frequent updates as more knowledge of volcanic activity is gained and as modelling capabilities and requirements change.
An innovative payload containing a sensitive mid-wave infrared camera was flown on an uncrewed aircraft system (UAS) to acquire thermal imagery along a reach of the Sacramento River, California, USA. The imagery was used as input for an ensemble particle image velocimetry (PIV) algorithm to produce near-continuous maps of surface flow velocity along a reach approximately 1 km in length. To assess the accuracy of PIV velocity estimates, in situ measurements of flow velocity were obtained with an acoustic Doppler current profiler (ADCP). ADCP measurements were collected along pre-planned cross-section lines within the area covered by the imagery. The PIV velocities showed good agreement with the depth-averaged velocity measured by the ADCP, with