{"pageNumber":"41","pageRowStart":"1000","pageSize":"25","recordCount":184785,"records":[{"id":70271481,"text":"ofr20251045 - 2025 - Three-dimensional seismic velocity model for the Cascadia Subduction Zone with shallow soils and topography, version 1.7","interactions":[{"subject":{"id":70194208,"text":"ofr20171152 - 2017 - P- and S-wave velocity models incorporating the Cascadia subduction zone for 3D earthquake ground motion simulations, Version 1.6—Update for Open-File Report 2007–1348","indexId":"ofr20171152","publicationYear":"2017","noYear":false,"title":"P- and S-wave velocity models incorporating the Cascadia subduction zone for 3D earthquake ground motion simulations, Version 1.6—Update for Open-File Report 2007–1348"},"predicate":"SUPERSEDED_BY","object":{"id":70271481,"text":"ofr20251045 - 2025 - Three-dimensional seismic velocity model for the Cascadia Subduction Zone with shallow soils and topography, version 1.7","indexId":"ofr20251045","publicationYear":"2025","noYear":false,"title":"Three-dimensional seismic velocity model for the Cascadia Subduction Zone with shallow soils and topography, version 1.7"},"id":1}],"lastModifiedDate":"2026-02-03T15:28:23.518326","indexId":"ofr20251045","displayToPublicDate":"2025-09-19T09:48:59","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-1045","displayTitle":"Three-Dimensional Seismic Velocity Model for the Cascadia Subduction Zone with Shallow Soils and Topography, Version 1.7","title":"Three-dimensional seismic velocity model for the Cascadia Subduction Zone with shallow soils and topography, version 1.7","docAbstract":"

The U.S. Geological Survey’s seismic velocity model for the Cascadia Subduction Zone provides P- and S-wave velocity (VP and VS, respectively) information from 40.2° to 50.0° N. latitude and −129.0° to −121.0° W. longitude, and is used to support a variety of research topics, including three-dimensional (3D) earthquake simulations and seismic hazard assessment in the Pacific Northwest. This report describes an update to the previous version (v) 1.6 of the 3D seismic velocity model for the Cascadia Subduction Zone. This new model (herein referred to as v1.7) contains more detailed near-surface structure for improved earthquake ground motion modeling. Updated features include the addition of a new shallow soil velocity model in the top few hundred meters and the option of adding user-specified topography. Although v1.6 of the Cascadia seismic velocity model has a minimum VS of 600 meters per second (m/s), the new model (v1.7) has a minimum VS of approximately 40 m/s. Overall, this update will allow for more accurate ground motion estimates from 3D simulations of scenario earthquakes in the Cascadia Subduction Zone region.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20251045","usgsCitation":"Wirth, E.A., Grant, A.R., Stone, I.P., Stephenson, W.J., and Frankel, A.D., 2025, Three-dimensional seismic velocity model for the Cascadia Subduction Zone with shallow soils and topography, version 1.7: U.S. Geological Survey Open-File Report 2025–1045, 18 p., https://doi.org/10.3133/ofr20251045.","productDescription":"Report: vi, 18 p.; Data Release","numberOfPages":"18","onlineOnly":"Y","ipdsId":"IP-161899","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":495639,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P14HJ3IC","text":"USGS data release","description":"Wirth, E.A., Grant, A.R., Stone, I.P., Stephenson, W.J., and Frankel, A.D., 2025, Data for A 3-D Seismic Velocity Model for Cascadia with Shallow Soils & Topography, Version 1.7: U.S. Geological Survey data release, https://doi.org/10.5066/P14HJ3IC","linkHelpText":"Data for A 3-D Seismic Velocity Model for Cascadia with Shallow Soils & Topography, Version 1.7"},{"id":495638,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2025/1045/images"},{"id":495637,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2025/1045/ofr20251045.XML","description":"OFR 2025-1045 XML"},{"id":495636,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20251045/full","linkFileType":{"id":5,"text":"html"},"description":"OFR 2025-1045 HTML"},{"id":495635,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2025/1045/ofr20251045.pdf","text":"Report","size":"4.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2025-1045 PDF"},{"id":495634,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2025/1045/coverthb.jpg"}],"country":"Canada, United States","state":"British Columbia, California, Oregon, Washington","otherGeospatial":"Cascadia Subduction Zone","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121,\n 50\n ],\n [\n -129,\n 50\n ],\n [\n -129,\n 40.2\n ],\n [\n -121,\n 40.2\n ],\n [\n -121,\n 50\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"

Earthquake Science Center
U.S. Geological Survey
350 N. Akron Rd.
Moffett Field, CA 94035

","tableOfContents":"","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2025-09-19","noUsgsAuthors":false,"publicationDate":"2025-09-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Wirth, Erin A. 0000-0002-8592-4442","orcid":"https://orcid.org/0000-0002-8592-4442","contributorId":207853,"corporation":false,"usgs":true,"family":"Wirth","given":"Erin","middleInitial":"A.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":948901,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grant, Alex R. 0000-0002-5096-4305","orcid":"https://orcid.org/0000-0002-5096-4305","contributorId":219066,"corporation":false,"usgs":true,"family":"Grant","given":"Alex","middleInitial":"R.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":948902,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stone, Ian P. 0000-0003-2622-2691","orcid":"https://orcid.org/0000-0003-2622-2691","contributorId":293630,"corporation":false,"usgs":true,"family":"Stone","given":"Ian","middleInitial":"P.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":948903,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stephenson, William J. 0000-0001-8699-0786 wstephens@usgs.gov","orcid":"https://orcid.org/0000-0001-8699-0786","contributorId":201085,"corporation":false,"usgs":true,"family":"Stephenson","given":"William","email":"wstephens@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":true,"id":948904,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Frankel, Arthur D. 0000-0001-9119-6106 afrankel@usgs.gov","orcid":"https://orcid.org/0000-0001-9119-6106","contributorId":146285,"corporation":false,"usgs":true,"family":"Frankel","given":"Arthur","email":"afrankel@usgs.gov","middleInitial":"D.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":948905,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70271482,"text":"fs20253050 - 2025 - Earthquake probabilities and hazards in the U.S. Pacific Northwest","interactions":[],"lastModifiedDate":"2026-02-03T15:27:39.519818","indexId":"fs20253050","displayToPublicDate":"2025-09-19T09:29:37","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-3050","displayTitle":"Earthquake Probabilities and Hazards in the U.S. Pacific Northwest","title":"Earthquake probabilities and hazards in the U.S. Pacific Northwest","docAbstract":"

Earthquakes and their cascading consequences pose a significant threat to the people, environment, infrastructure, and economy of the U.S. Pacific Northwest. The Pacific Northwest is susceptible to three types of earthquakes: deep (intraslab) earthquakes, subduction zone (megathrust) earthquakes, and shallow crustal earthquakes. For each of these earthquake types, earth scientists can use a variety of methods to estimate the probability of occurrence for future events, which constrains seismic hazard and informs building codes. The timing of past earthquakes indicates that there is an 85-percent chance of a magnitude 6.5 or greater deep earthquake in the Puget Sound region; a 10-15-percent chance of an approximately magnitude 9 earthquake on the Cascadia Subduction Zone; and a 17-percent chance of a magnitude 6.5 or greater crustal fault earthquake in the Puget Sound region in the next 50 years. Individuals and communities can take simple steps to prepare for and reduce the impact of future earthquakes.

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Earthquake Science Center, Seattle Field Office
U.S. Geological Survey
University of Washington, Department of Earth and Space Sciences
4000 15th Ave NE
Seattle, WA 98195

Contact Pubs Warehouse

","tableOfContents":"","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2025-09-19","revisedDate":"2025-09-30","noUsgsAuthors":false,"plainLanguageSummary":"

Earthquakes and their cascading consequences pose a significant threat to the people, environment, infrastructure, and economy of the U.S. Pacific Northwest. The timing of previous earthquakes helps estimate the likelihood of future events.

","publicationDate":"2025-09-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Wirth, Erin A. 0000-0002-8592-4442","orcid":"https://orcid.org/0000-0002-8592-4442","contributorId":207853,"corporation":false,"usgs":true,"family":"Wirth","given":"Erin","middleInitial":"A.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":948906,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Frankel, Arthur D. 0000-0001-9119-6106 afrankel@usgs.gov","orcid":"https://orcid.org/0000-0001-9119-6106","contributorId":146285,"corporation":false,"usgs":true,"family":"Frankel","given":"Arthur","email":"afrankel@usgs.gov","middleInitial":"D.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":948907,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sherrod, Brian L. 0000-0002-4492-8631 bsherrod@usgs.gov","orcid":"https://orcid.org/0000-0002-4492-8631","contributorId":2834,"corporation":false,"usgs":true,"family":"Sherrod","given":"Brian","email":"bsherrod@usgs.gov","middleInitial":"L.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":948908,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Grant, Alex R. 0000-0002-5096-4305","orcid":"https://orcid.org/0000-0002-5096-4305","contributorId":219066,"corporation":false,"usgs":true,"family":"Grant","given":"Alex","middleInitial":"R.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":948909,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dunham, Audrey 0000-0001-9719-9287","orcid":"https://orcid.org/0000-0001-9719-9287","contributorId":361490,"corporation":false,"usgs":true,"family":"Dunham","given":"Audrey","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":948910,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stone, Ian P. 0000-0003-2622-2691","orcid":"https://orcid.org/0000-0003-2622-2691","contributorId":293630,"corporation":false,"usgs":true,"family":"Stone","given":"Ian","middleInitial":"P.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":948911,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Grossman, Julia","contributorId":361491,"corporation":false,"usgs":false,"family":"Grossman","given":"Julia","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":948912,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70271743,"text":"70271743 - 2025 - Spatially resolved source apportionment of per- and polyfluoroalkyl substances (PFAS) within a post-industrial river catchment","interactions":[],"lastModifiedDate":"2025-09-23T14:33:54.417922","indexId":"70271743","displayToPublicDate":"2025-09-19T09:23:59","publicationYear":"2025","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":"Spatially resolved source apportionment of per- and polyfluoroalkyl substances (PFAS) within a post-industrial river catchment","docAbstract":"Source apportionment of per- and polyfluoroalkyl substances (PFAS) in rivers is typically based on water concentrations, which cannot quantify PFAS loads or define geographical source areas. This study applied a river catchment-scale approach to identify PFAS source zones and assess the relative importance of industrial PFAS sources in the River Mersey, UK – a post-industrial, densely populated catchment with diverse PFAS sources. Synoptic sampling and PFAS river load analysis identified key sub-catchments and river stretches contributing the majority of PFAS. Notably, the highest PFAS concentrations did not always correspond to the greatest loads. Most PFOS (64 %), PFOA (49 %), 6:2FTS (46 %) and PFHxS (56 %) were exported from the Upper Mersey sub-catchment, despite higher concentrations in northern sub-catchments, emphasising the importance of load-based monitoring. Mass balance analysis of loads highlighted substantial inputs from specific river stretches, notably the Lower Irwell (Bolton to Manchester City Centre), River Tame (Marple Bridge to Stockport), and Upper Mersey (Stockport to Urmston). While PFAS loads generally scaled with catchment area, yield (load per unit area) analysis identified disproportionately high exports from small headwater catchments, notably the upper River Roch (PFOA, PFHpA and PFHxA) and Glaze Brook (PFBS). Industrial sources in these sub-catchments (a waste management facility and landfills, respectively) were confirmed using gadolinium anomaly analysis and consented discharge records. More widely, gadolinium data suggested industrial discharges may contribute to PFAS occurrence at 62 % of our sample sites throughout the catchment. These findings demonstrate that spatial analysis of PFAS loads, rather than concentrations alone, is critical for identifying PFAS source areas. We present a scalable monitoring framework for PFAS source apportionment applied at the river catchment-scale that can be used by environmental managers to target and prioritise PFAS source areas for detailed monitoring and remediation.","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2025.180502","usgsCitation":"Byrne, P., Mayes, W.M., James, A.L., Comber, S., Biles, E., Riley, A.L., Verplanck, P., and Bradley, L., 2025, Spatially resolved source apportionment of per- and polyfluoroalkyl substances (PFAS) within a post-industrial river catchment: Science of the Total Environment, v. 1001, 180502, 12 p., https://doi.org/10.1016/j.scitotenv.2025.180502.","productDescription":"180502, 12 p.","ipdsId":"IP-180073","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":496352,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2025.180502","text":"Publisher Index Page"},{"id":495896,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United Kingdom","otherGeospatial":"River Mersey","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -2.4656527163469946,\n 53.60530248618926\n ],\n [\n -2.4656527163469946,\n 53.3355442876196\n ],\n [\n -1.966480261260216,\n 53.3355442876196\n ],\n [\n -1.966480261260216,\n 53.60530248618926\n ],\n [\n -2.4656527163469946,\n 53.60530248618926\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"1001","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Byrne, Patrick","contributorId":192845,"corporation":false,"usgs":false,"family":"Byrne","given":"Patrick","affiliations":[],"preferred":false,"id":949261,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mayes, William M.","contributorId":335073,"corporation":false,"usgs":false,"family":"Mayes","given":"William","email":"","middleInitial":"M.","affiliations":[{"id":40174,"text":"University of Hull","active":true,"usgs":false}],"preferred":false,"id":949262,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"James, Alun L.","contributorId":361704,"corporation":false,"usgs":false,"family":"James","given":"Alun","middleInitial":"L.","affiliations":[{"id":86333,"text":"Environment Agency UK","active":true,"usgs":false}],"preferred":false,"id":949263,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Comber, Sean","contributorId":335075,"corporation":false,"usgs":false,"family":"Comber","given":"Sean","email":"","affiliations":[{"id":80302,"text":"University of Plymouth,","active":true,"usgs":false}],"preferred":false,"id":949264,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Biles, Emma","contributorId":335077,"corporation":false,"usgs":false,"family":"Biles","given":"Emma","email":"","affiliations":[{"id":49583,"text":"Liverpool John Moores University","active":true,"usgs":false}],"preferred":false,"id":949265,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Riley, Alex L.","contributorId":361707,"corporation":false,"usgs":false,"family":"Riley","given":"Alex","middleInitial":"L.","affiliations":[{"id":40174,"text":"University of Hull","active":true,"usgs":false}],"preferred":false,"id":949266,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Verplanck, Philip L. 0000-0002-3653-6419","orcid":"https://orcid.org/0000-0002-3653-6419","contributorId":212813,"corporation":false,"usgs":true,"family":"Verplanck","given":"Philip","middleInitial":"L.","affiliations":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"preferred":true,"id":949267,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Bradley, Lee","contributorId":361708,"corporation":false,"usgs":false,"family":"Bradley","given":"Lee","affiliations":[{"id":86332,"text":"John Moores University","active":true,"usgs":false}],"preferred":false,"id":949268,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70271720,"text":"70271720 - 2025 - Machine learning generated streamflow drought forecasts for the Conterminous United States (CONUS): Developing and evaluating an operational tool to enhance sub-seasonal to seasonal streamflow drought early warning for gaged locations","interactions":[{"subject":{"id":70271720,"text":"70271720 - 2025 - Machine learning generated streamflow drought forecasts for the Conterminous United States (CONUS): Developing and evaluating an operational tool to enhance sub-seasonal to seasonal streamflow drought early warning for gaged locations","indexId":"70271720","publicationYear":"2025","noYear":false,"title":"Machine learning generated streamflow drought forecasts for the Conterminous United States (CONUS): Developing and evaluating an operational tool to enhance sub-seasonal to seasonal streamflow drought early warning for gaged locations"},"predicate":"SUPERSEDED_BY","object":{"id":70273497,"text":"70273497 - 2026 - Machine learning generated streamflow drought forecasts for the conterminous United States (CONUS): developing and evaluating an operational tool to enhance sub-seasonal to seasonal streamflow drought early warning for gaged locations","indexId":"70273497","publicationYear":"2026","noYear":false,"title":"Machine learning generated streamflow drought forecasts for the conterminous United States (CONUS): developing and evaluating an operational tool to enhance sub-seasonal to seasonal streamflow drought early warning for gaged locations"},"id":1}],"supersededBy":{"id":70273497,"text":"70273497 - 2026 - Machine learning generated streamflow drought forecasts for the conterminous United States (CONUS): developing and evaluating an operational tool to enhance sub-seasonal to seasonal streamflow drought early warning for gaged locations","indexId":"70273497","publicationYear":"2026","noYear":false,"title":"Machine learning generated streamflow drought forecasts for the conterminous United States (CONUS): developing and evaluating an operational tool to enhance sub-seasonal to seasonal streamflow drought early warning for gaged locations"},"lastModifiedDate":"2026-01-26T16:29:56.651322","indexId":"70271720","displayToPublicDate":"2025-09-19T09:20:12","publicationYear":"2025","noYear":false,"publicationType":{"id":27,"text":"Preprint"},"publicationSubtype":{"id":32,"text":"Preprint"},"seriesTitle":{"id":18346,"text":"EarthArXiv","active":true,"publicationSubtype":{"id":32}},"title":"Machine learning generated streamflow drought forecasts for the Conterminous United States (CONUS): Developing and evaluating an operational tool to enhance sub-seasonal to seasonal streamflow drought early warning for gaged locations","docAbstract":"

Forecasts of streamflow drought, when streamflow declines below typical levels, are notably less available than for floods or meteorological drought, despite widespread impacts. To address this gap, we apply machine learning (ML) models to forecast streamflow drought 1-13 weeks into the future at > 3,000 streamgage locations across the conterminous United States (CONUS). We applied two ML methods (Long short-term memory (LSTM) neural networks; Light Gradient-Boosting Machine - LightGBM) and two benchmark model approaches (persistence; Autoregressive Integrated Moving Average - ARIMA) to predict weekly streamflow percentiles with independent models for each forecast horizon. To explore whether a training focus on dry weeks improved performance, both ML models were trained using all percentiles (LSTM-all, LightGBM-all) and only percentiles below 30% (LSTM<30, LightGBM<30). We evaluated model performance regionally and nationally for drought occurrence (the classification performance for a future date) and for drought onset/termination (performance identifying drought starts and ends). ML models generally performed worse than the persistence model for discrete classification (moderate, severe, extreme drought) of drought occurrence but exceeded the benchmark models for onset/termination. ML models outperformed benchmarks in predicting continuous streamflow percentiles below 30%. Occurrence performance was better for less intense droughts and shorter forecast horizons, with the ML models having predictive power at 1-4 week horizons for severe droughts (10th percentile threshold). All models struggled to forecast onset, though the best ML model was the LSTM<30 (sensitivity of 22%). Termination performance was greater, with the drought termination performance greatest for the LightGBM-all model. When estimating model uncertainty, the LSTM<30 model had the narrowest 90% percentile interval with closest to optimal capture. This work highlights the challenges and opportunities to further advance hydrological drought forecasting and supports an experimental operational streamflow drought assessment and forecast tool.

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Per- and polyfluoroalkyl substances (PFAS), frequently called “forever chemicals,” are used for a wide variety of industrial purposes and are often found in common household and industrial items such as firefighting foams, non-stick cookware, and water-resistant materials. The contamination of water, air, and soil by PFAS is a national and global issue due to their widespread occurrence in multiple applications and resistance to biodegradation and other traditional treatment processes. Research indicates that many PFAS can be emitted to the atmosphere and transported and deposited long distances from the source.

The U.S. Geological Survey (USGS) Water Resources Mission Area received funding to implement a national-scale sampling effort to assess PFAS occurrence. To follow agency directives, the National Water Quality Network (NWQN) added PFAS sample monitoring for both surface water and groundwater, and also added PFAS monitoring to selected sites in the National Atmospheric Deposition Program (NADP).

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National Network Coordinators
Observing Systems Division
Water Mission Area
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192

","tableOfContents":"","publishedDate":"2025-09-19","noUsgsAuthors":false,"publicationDate":"2025-09-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Riskin, Melissa L. 0000-0001-6499-3775 mriskin@usgs.gov","orcid":"https://orcid.org/0000-0001-6499-3775","contributorId":654,"corporation":false,"usgs":true,"family":"Riskin","given":"Melissa","email":"mriskin@usgs.gov","middleInitial":"L.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"preferred":true,"id":949171,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lindsey, Bruce D. 0000-0002-7180-4319 blindsey@usgs.gov","orcid":"https://orcid.org/0000-0002-7180-4319","contributorId":175346,"corporation":false,"usgs":true,"family":"Lindsey","given":"Bruce","email":"blindsey@usgs.gov","middleInitial":"D.","affiliations":[{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":949172,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McCammon, Ryan Conner 0009-0003-2787-5878","orcid":"https://orcid.org/0009-0003-2787-5878","contributorId":346258,"corporation":false,"usgs":false,"family":"McCammon","given":"Ryan","email":"","middleInitial":"Conner","affiliations":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"preferred":false,"id":949173,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70271686,"text":"70271686 - 2025 - Sundial: A method for inferring image acquisition time from shadow orientation","interactions":[],"lastModifiedDate":"2025-09-19T14:56:19.138181","indexId":"70271686","displayToPublicDate":"2025-09-18T09:55:14","publicationYear":"2025","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":"Sundial: A method for inferring image acquisition time from shadow orientation","docAbstract":"

Aerial photography and satellite imagery can be used to characterize landscape change over time and help to understand how these changes are related to climate and hydrology. Publicly available optical imagery from sources such as the United States National Agricultural Imagery Program (NAIP) is particularly valuable in this context due to its high temporal and spatial resolution. However, the exact time an image was acquired is often unknown, which complicates, if not precludes, linking images with other types of high temporal resolution data, such as streamflow records. In this letter, we propose a ‘sundial method’ to infer image acquisition time from shadow orientation. This approach involves measuring the direction of a shadow on the image and using solar geometry calculated for the known image date and location to infer the former sun position. Time estimates for 16 Worldview satellite and six NAIP aerial images based on 407 independent measurements of shadow orientation demonstrate the sundial method had an error of 2.1 ± 3.4 min, indicating that image acquisition times can be inferred with a high degree of accuracy and precision. Sensitivity analyses confirm the robustness of the method across different object types, shadow lengths, and solar zenith angles, while also providing practical guidelines regarding the number of measurements required and errors associated with uncertainty in the image date.

","language":"English","publisher":"Wiley","doi":"10.1002/esp.70157","usgsCitation":"Bae, I., Legleiter, C.J., and Yager, E., 2025, Sundial: A method for inferring image acquisition time from shadow orientation: Earth Surface Processes and Landforms, v. 50, no. 12, e70157, 10 p., https://doi.org/10.1002/esp.70157.","productDescription":"e70157, 10 p.","ipdsId":"IP-173049","costCenters":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"links":[{"id":495797,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"50","issue":"12","noUsgsAuthors":false,"publicationDate":"2025-09-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Bae, Inhyeok 0000-0003-3942-4110","orcid":"https://orcid.org/0000-0003-3942-4110","contributorId":347541,"corporation":false,"usgs":false,"family":"Bae","given":"Inhyeok","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":949025,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Legleiter, Carl J. 0000-0003-0940-8013 cjl@usgs.gov","orcid":"https://orcid.org/0000-0003-0940-8013","contributorId":169002,"corporation":false,"usgs":true,"family":"Legleiter","given":"Carl","email":"cjl@usgs.gov","middleInitial":"J.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":949024,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yager, Elowyn 0000-0002-3382-2356","orcid":"https://orcid.org/0000-0002-3382-2356","contributorId":347542,"corporation":false,"usgs":false,"family":"Yager","given":"Elowyn","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":949026,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70271707,"text":"70271707 - 2025 - Scenario projections of COVID-19 burden in the US, 2024-2025","interactions":[],"lastModifiedDate":"2025-09-19T14:41:41.794225","indexId":"70271707","displayToPublicDate":"2025-09-18T09:33:49","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":20081,"text":"JAMA Network Open","active":true,"publicationSubtype":{"id":10}},"title":"Scenario projections of COVID-19 burden in the US, 2024-2025","docAbstract":"

Importance  COVID-19 remains a disease with high burden in the US, prompting continued debate about optimal targets for annual vaccination.

Objective  To project COVID-19 burden in the US for April 2024 to April 2025 under 6 scenarios of immune escape (20% and 50% per year) and levels of vaccine recommendation (no recommendation, vaccination for individuals at high risk only, vaccination for all eligible groups) and to assess the potential benefit of vaccine recommendations in reducing disease burden.

Design, Setting, and Participants  For this decision analytical model, the US Scenario Modeling Hub, a collaborative modeling effort, convened 9 teams to provide scenario projections of US COVID-19 hospitalizations and deaths for April 2024 to April 2025, under 6 scenarios combining levels of immune escape and possible vaccine recommendations.

Exposure  Annually reformulated vaccines were assumed to be 75% effective against hospitalization for variants circulating on June 15, 2024, and available on September 1, 2024. Age- and state-specific coverage was assumed to be as reported in September 2023 to April 2024.

Main Outcomes and Measures  Ensemble estimates were made for weekly COVID-19 hospitalizations and deaths. Projections are presented for relative and absolute prevented hospitalizations and deaths averted due to vaccination over the April 2024 to April 2025 period.

Results  For the US population (332 million, with an estimated 58 million aged ≥65 years), COVID-19 was expected to cause 814 000 (95% projection interval [PI], 400 000-1.2 million) hospitalizations and 54 000 (95% PI, 17 000-98 000) deaths for April 2024 to April 2025, comparable in magnitude to the prior year. Vaccination of high-risk groups only was projected to reduce hospitalizations (compared to no vaccination recommendation) by 76 000 (95% CI, 34 000-118 000) and deaths by 7000 (95% CI, 3000-11 000) across both immune escape scenarios. Compared with vaccinating high-risk groups only, a universal vaccine recommendation was projected to provide direct and indirect benefits, further preventing 11 000 hospitalizations and 1000 deaths in those aged 65 years and older.

Conclusions and Relevance  In this decision analytical modeling study of COVID-19 burden in the US in 2024 to 2025, ensemble projections suggested that although vaccinating high-risk groups had substantial benefits in reducing disease burden, maintaining the vaccine recommendation for all individuals had the potential to save thousands more lives. Despite divergence of projections from observed disease trends in 2024 to 2025—possibly driven by variant emergence patterns and immune escape—averted COVID-19 burden due to vaccination was robust across immune escape scenarios, emphasizing the substantial benefit of broader vaccine availability for all individuals.

","language":"English","publisher":"JAMA","doi":"10.1001/jamanetworkopen.2025.32469","usgsCitation":"Loo, S.L., Jung, S., Contamin, L., Howerton, E., Bents, S., Hochheiser, H., Runge, M., Smith, C.P., Carcelén, E., Yan, K., Lemaitre, J.C., Przykucki, E., McKee, C., Sato, K., Hill, A., Chinazzi, M., Davis, J.T., Bay, C., Vespignani, A., Chen, S., Paul, R., Janies, D., Thill, J., Moore, S., Perkins, T.A., Srivastava, A., Aawar, M.A., Bi, K., Bandekar, S.R., Bouchnita, A., Fox, S., Meyers, L.A., Porebski, P., Venkatramanan, S., Lewis, B., Chen, J., Marathe, M., Ben-Nun, M., Turtle, J., Riley, P., Shea, K., Viboud, C., Lessler, J., and Truelove, S., 2025, Scenario projections of COVID-19 burden in the US, 2024-2025: JAMA Network Open, v. 8, no. 9, e2532469, 12 p., https://doi.org/10.1001/jamanetworkopen.2025.32469.","productDescription":"e2532469, 12 p.","ipdsId":"IP-180247","costCenters":[{"id":50464,"text":"Eastern Ecological Science 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Field surveys form the basis of many research efforts and are the foundation for estimates of population size and density that inform conservation and management practices for imperiled species. As a result, evaluating the performance of different survey methods across a range of conditions that may be encountered in the field can increase understanding of the time and effort that may be required to ensure that survey results are sufficiently accurate and reliable for conservation goals. We used a spatially explicit agent-based model to simulate four commonly used freshwater mussel field survey methodologies: simple random sampling (SRS), transect random sampling (TRS), adaptive cluster sampling (ACS), and qualitative timed searches (QTS) to investigate the influence of sampling method, spatial distribution, and mussel density on the performance (i.e., accuracy, precision, and detection rate) of survey techniques. Our analysis suggests that mussel density, spatial distribution, and sampling effort influence sampling accuracy, precision, and species detection for all sampling methods. QTS produces highly variable catch-per-unit-effort (CPUE) metrics when mussels are dense and/or clustered, indicating the technique may be unreliable as a proxy for density. Quantitative methods like SRS and TRS may be well-suited for estimating population characteristics, but a high level of effort may be needed to obtain reasonable accuracy when mussels occur at low densities. ACS may be more efficient for mussels at low densities, but it can be challenging to plan for the level of effort required to complete an ACS protocol. Designing an ecological survey requires careful consideration of research objectives and available resources. Future research may consider the performance of qualitative and quantitative surveys in combination as a means of overcoming some of the practical challenges of applying individual survey methods.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2025.114172","usgsCitation":"Foxfoot, I.R., Cushway, K.C., Schwalb, A.N., Smith, D.R., and Swannack, T.M., 2025, Evaluating freshwater mussel sampling methodologies using a simulation model: Ecological Indicators, v. 179, 114172, 14 p., https://doi.org/10.1016/j.ecolind.2025.114172.","productDescription":"114172, 14 p.","ipdsId":"IP-181659","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":499327,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolind.2025.114172","text":"Publisher Index Page"},{"id":499174,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"179","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Foxfoot, Iris R.","contributorId":336806,"corporation":false,"usgs":false,"family":"Foxfoot","given":"Iris","middleInitial":"R.","affiliations":[{"id":12537,"text":"USACE","active":true,"usgs":false}],"preferred":false,"id":954690,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cushway, Kiara C.","contributorId":365735,"corporation":false,"usgs":false,"family":"Cushway","given":"Kiara","middleInitial":"C.","affiliations":[{"id":87200,"text":"US Army Engineer Research and Development Center; UIC Government Services LLC","active":true,"usgs":false}],"preferred":false,"id":954691,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schwalb, Astrid N.","contributorId":333385,"corporation":false,"usgs":false,"family":"Schwalb","given":"Astrid","middleInitial":"N.","affiliations":[{"id":6677,"text":"Texas State University","active":true,"usgs":false}],"preferred":false,"id":954692,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, David R. 0000-0001-6074-9257 drsmith@usgs.gov","orcid":"https://orcid.org/0000-0001-6074-9257","contributorId":168442,"corporation":false,"usgs":true,"family":"Smith","given":"David","email":"drsmith@usgs.gov","middleInitial":"R.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":954693,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Swannack, Todd M.","contributorId":336813,"corporation":false,"usgs":false,"family":"Swannack","given":"Todd","middleInitial":"M.","affiliations":[{"id":12537,"text":"USACE","active":true,"usgs":false}],"preferred":false,"id":954694,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70272608,"text":"70272608 - 2025 - Native crayfish shows high desiccation tolerance and potential to outcompete invader","interactions":[],"lastModifiedDate":"2025-11-24T15:46:26.826539","indexId":"70272608","displayToPublicDate":"2025-09-18T08:40:23","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1018,"text":"Biological Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Native crayfish shows high desiccation tolerance and potential to outcompete invader","docAbstract":"

Biological invasions threaten global biodiversity, with aquatic systems being particularly susceptible. Invasive crayfish drive native crayfish imperilment in North America and worldwide. Despite the probable increase in extreme hydrological events, the synergistic effects from invasive species and drought on crayfish are understudied. The invasion of Faxonius neglectus chaenodactylus in the Spring River drainage (AR, MO) has likely contributed to native crayfish displacement through mechanisms related to stream drying. F. n. chaenodactylus may further expand its range, posing a threat to other native species like Faxonius marchandi, the Mammoth Spring crayfish, a narrow-ranged endemic. We used stream mesocosms to examine (1) effects of invasive species on F. marchandi growth and survival, (2) responses of both species to simulated stream drying, and (3) additive effects of invasion and drought on F. marchandi. Additionally, we assessed differential desiccation tolerance using environmental chambers. We found no significant interaction between drought and competition nor any significant main effects on crayfish mass change or survival; however, interspecific competition significantly reduced length change in F. n. chaenodactylus. All populations showed differential desiccation tolerance, with survival rates varying significantly (p < 0.05) and carapace length (CL) positively influencing survival (p < 0.01). Understanding the effects of drought, invasion, and their interactions on native crayfish is essential, particularly given the potential expansion of an invader and increasing drought intensity from future climate change.

","language":"English","publisher":"Springer Nature","doi":"10.1007/s10530-025-03675-5","usgsCitation":"Bayer, L.M., and Magoulick, D.D., 2025, Native crayfish shows high desiccation tolerance and potential to outcompete invader: Biological Invasions, v. 27, 216, 16 p., https://doi.org/10.1007/s10530-025-03675-5.","productDescription":"216, 16 p.","ipdsId":"IP-170452","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":496826,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas, Missouri","otherGeospatial":"Spring River drainage","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -92.82880316322702,\n 36.78950866025838\n ],\n [\n -92.82880316322702,\n 35.94152912534426\n ],\n [\n -91.54070609793327,\n 35.94152912534426\n ],\n [\n -91.54070609793327,\n 36.78950866025838\n ],\n [\n -92.82880316322702,\n 36.78950866025838\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"27","noUsgsAuthors":false,"publicationDate":"2025-09-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Bayer, Leah M.","contributorId":363007,"corporation":false,"usgs":false,"family":"Bayer","given":"Leah","middleInitial":"M.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":950908,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Magoulick, Daniel D. 0000-0001-9665-5957 danmag@usgs.gov","orcid":"https://orcid.org/0000-0001-9665-5957","contributorId":2513,"corporation":false,"usgs":true,"family":"Magoulick","given":"Daniel","email":"danmag@usgs.gov","middleInitial":"D.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":950909,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70271926,"text":"70271926 - 2025 - Reservoir operational strategies for sustainable sand management in the Colorado River","interactions":[],"lastModifiedDate":"2025-09-24T15:24:43.186803","indexId":"70271926","displayToPublicDate":"2025-09-18T08:14:16","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Reservoir operational strategies for sustainable sand management in the Colorado River","docAbstract":"

Climate change and increasing societal demands for water pose challenges for the management of dam-regulated rivers. Management decisions impact the environment of these rivers, creating the need to balance societal needs with environmental conservation. Here we present a modeling framework that optimizes resource benefits within imposed water use goals for the Colorado River in Grand Canyon, where sandbars are a valued natural feature. The current sand-management paradigm utilizes controlled dam-release floods to build and maintain sandbars without exhausting the limited sand supplied by tributaries downstream from Glen Canyon Dam, which blocks all sand supplied from upriver. High monthly releases outside of controlled floods erode sandbars and cause net sand export from Grand Canyon, reducing the sand available to build sandbars. Releases are high in some months owing to the need to adjust flows to meet annual delivery targets, which can be updated throughout the year. Here, we present alternative strategies for operations that avoid high releases, while meeting water storage and delivery goals. We test these strategies using a simplified reservoir model which accounts for forecast uncertainty. We show how these strategies affect sand mass balance and sandbar size using previously developed models. Strategies optimal for sustainable sandbar building maintained sufficient reservoir elevations for implementing controlled floods, avoided high monthly releases by relaxing annual release constraints, and implemented controlled floods in fall immediately following tributary sand inputs. Coordinated modeling of reservoir operations and environmental resources is valuable for managers seeking to balance societal and environmental needs in regulated rivers worldwide.

","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2024WR038315","usgsCitation":"Salter, G.L., Topping, D.J., Wang, J., Schmidt, J.C., Yackulic, C., Bair, L., Mueller, E., and Grams, P.E., 2025, Reservoir operational strategies for sustainable sand management in the Colorado River: Water Resources Research, v. 61, no. 9, e2024WR038315, 27 p., https://doi.org/10.1029/2024WR038315.","productDescription":"e2024WR038315, 27 p.","ipdsId":"IP-167426","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":496155,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2024wr038315","text":"Publisher Index Page"},{"id":496013,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Colorado River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -114.0504953550317,\n 36.97634003343833\n ],\n [\n -114.0504953550317,\n 35.748902843127084\n ],\n [\n -111.3294352062603,\n 35.748902843127084\n ],\n [\n -111.3294352062603,\n 36.97634003343833\n ],\n [\n -114.0504953550317,\n 36.97634003343833\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"61","issue":"9","noUsgsAuthors":false,"publicationDate":"2025-09-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Salter, Gerard Lewis 0000-0001-6426-0133","orcid":"https://orcid.org/0000-0001-6426-0133","contributorId":333645,"corporation":false,"usgs":true,"family":"Salter","given":"Gerard","email":"","middleInitial":"Lewis","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":949399,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Topping, David J. 0000-0002-2104-4577","orcid":"https://orcid.org/0000-0002-2104-4577","contributorId":215068,"corporation":false,"usgs":true,"family":"Topping","given":"David","middleInitial":"J.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":949400,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wang, Jianghao","contributorId":195004,"corporation":false,"usgs":false,"family":"Wang","given":"Jianghao","email":"","affiliations":[],"preferred":false,"id":949401,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schmidt, John C.","contributorId":361760,"corporation":false,"usgs":false,"family":"Schmidt","given":"John","middleInitial":"C.","affiliations":[{"id":86346,"text":"Center for Colorado River Studies, Department of Watershed Sciences, Utah State University, Logan, UT, USA","active":true,"usgs":false}],"preferred":false,"id":949402,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Yackulic, Charles B. 0000-0001-9661-0724","orcid":"https://orcid.org/0000-0001-9661-0724","contributorId":218825,"corporation":false,"usgs":true,"family":"Yackulic","given":"Charles","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":949403,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bair, Lucas 0000-0002-9911-3624","orcid":"https://orcid.org/0000-0002-9911-3624","contributorId":248714,"corporation":false,"usgs":true,"family":"Bair","given":"Lucas","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":949404,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Mueller, Erich R. 0000-0001-8202-154X","orcid":"https://orcid.org/0000-0001-8202-154X","contributorId":207750,"corporation":false,"usgs":false,"family":"Mueller","given":"Erich R.","affiliations":[{"id":37626,"text":"Department of Geography, University of Wyoming, Laramie, WY, USA","active":true,"usgs":false}],"preferred":false,"id":949405,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Grams, Paul E. 0000-0002-0873-0708","orcid":"https://orcid.org/0000-0002-0873-0708","contributorId":216115,"corporation":false,"usgs":true,"family":"Grams","given":"Paul","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":949406,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70273390,"text":"70273390 - 2025 - Habitat features influencing waterbird use of managed wetlands enrolled in a public-private partnership for land conservation: The California Waterfowl Habitat Program","interactions":[],"lastModifiedDate":"2026-01-12T14:53:19.867404","indexId":"70273390","displayToPublicDate":"2025-09-18T07:47:45","publicationYear":"2025","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":"Habitat features influencing waterbird use of managed wetlands enrolled in a public-private partnership for land conservation: The California Waterfowl Habitat Program","docAbstract":"

Draining, water diversion, and development have greatly reduced the availability of freshwater wetland habitat around the world, and many remaining wetlands are on private lands. Public–private partnership programs can be an important means for promoting habitat conservation and management on private lands. We investigated bird use of 117 wetlands enrolled in the California Waterfowl Habitat Program in California's Central Valley, where two-thirds of wetlands are under private ownership and management. Specifically, we quantified the influence of wetland habitat features and surrounding land cover on waterbird density and diversity in late winter and early spring and during the waterfowl breeding season. Dabbling duck and shorebird densities were highest in wetlands that had water depths < 20 cm, and waterbird densities decreased with water depth. Greater amounts of emergent vegetation, especially tall and dense emergent vegetation, had a negative effect on total waterbird density but a positive effect on species richness and secretive marsh bird density. Shorebird and breeding duck densities were lower in wetlands with a large number of trees and other potential perch sites, and waterbird densities decreased with the amount of nearby wetland habitat on the landscape. Overall, we estimated that during late winter and early spring, private properties that were enrolled in the California Waterfowl Habitat Program (8000–8500 ha each year) supported 480,000 birds per day during extreme drought conditions in 2022 and 280,000 birds per day in more normal, non-drought conditions in 2023. Over the 76-day winter and early spring survey period, this amounted to more than 20 million bird use days on wetlands enrolled in the California Waterfowl Habitat Program during late winter and early spring. These results demonstrate the value of public–private wetland conservation partnerships, the influence of wetland habitat features and surrounding land cover on waterbird abundance, and the benefits of habitat features that could be incorporated into management plans and wetland selection criteria for enrollment into public–private conservation programs.

","language":"English","publisher":"Wiley","doi":"10.1002/ece3.72032","usgsCitation":"Hartman, C.A., Ackerman, J.T., Peterson, S.H., Fettig, B.L., and Herzog, M.P., 2025, Habitat features influencing waterbird use of managed wetlands enrolled in a public-private partnership for land conservation: The California Waterfowl Habitat Program: Ecology and Evolution, v. 15, no. 9, e72032, 31 p., https://doi.org/10.1002/ece3.72032.","productDescription":"e72032, 31 p.","ipdsId":"IP-177295","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":498681,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.72032","text":"Publisher Index Page"},{"id":498542,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento Valley, San Joaquin Valley, Yolo-Delta and Suisun Marsh area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.95679541485802,\n 39.955731811890246\n ],\n [\n -122.95679541485802,\n 36.78915144435925\n ],\n [\n -120.20809606036002,\n 36.78915144435925\n ],\n [\n -120.20809606036002,\n 39.955731811890246\n ],\n [\n -122.95679541485802,\n 39.955731811890246\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"15","issue":"9","noUsgsAuthors":false,"publicationDate":"2025-09-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Hartman, C. Alex 0000-0002-7222-1633 chartman@usgs.gov","orcid":"https://orcid.org/0000-0002-7222-1633","contributorId":131157,"corporation":false,"usgs":true,"family":"Hartman","given":"C.","email":"chartman@usgs.gov","middleInitial":"Alex","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":953547,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ackerman, Joshua T. 0000-0002-3074-8322","orcid":"https://orcid.org/0000-0002-3074-8322","contributorId":202848,"corporation":false,"usgs":true,"family":"Ackerman","given":"Joshua","middleInitial":"T.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":953548,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Peterson, Sarah H. 0000-0003-2773-3901 sepeterson@usgs.gov","orcid":"https://orcid.org/0000-0003-2773-3901","contributorId":167181,"corporation":false,"usgs":true,"family":"Peterson","given":"Sarah","email":"sepeterson@usgs.gov","middleInitial":"H.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":953549,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fettig, Brady Lynn 0000-0002-3124-2606","orcid":"https://orcid.org/0000-0002-3124-2606","contributorId":302106,"corporation":false,"usgs":true,"family":"Fettig","given":"Brady","email":"","middleInitial":"Lynn","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":953550,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Herzog, Mark P. 0000-0002-5203-2835 mherzog@usgs.gov","orcid":"https://orcid.org/0000-0002-5203-2835","contributorId":131158,"corporation":false,"usgs":true,"family":"Herzog","given":"Mark","email":"mherzog@usgs.gov","middleInitial":"P.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":953551,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70264311,"text":"70264311 - 2025 - Interrogating process deficiencies in large-scale hydrologic models with interpretable machine learning","interactions":[],"lastModifiedDate":"2025-11-26T16:47:08.362588","indexId":"70264311","displayToPublicDate":"2025-09-17T10:34:37","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1928,"text":"Hydrology and Earth System Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Interrogating process deficiencies in large-scale hydrologic models with interpretable machine learning","docAbstract":"

Large-scale hydrologic models are increasingly being developed for operational use in the forecasting and planning of water resources. However, the predictive strength of such models depends on how well they resolve various functions of catchment hydrology, which are influenced by gradients in climate, topography, soils, and land use. Most assessments of hydrologic model uncertainty have been limited to traditional statistical methods. Here, we present a proof-of-concept approach that uses interpretable machine learning techniques to provide post hoc assessment of model sensitivity and process deficiency in hydrologic models. We train a random forest model to predict the Kling–Gupta efficiency (KGE) of National Water Model (NWM) and National Hydrologic Model (NHM) streamflow predictions for 4383 stream gauges in the conterminous United States. Thereafter, we explain the local and global controls that 48 catchment attributes exert on KGE prediction using interpretable Shapley values. Overall, we find that soil water content is the most impactful feature controlling successful model performance, suggesting that soil water storage is difficult for hydrologic models to resolve, particularly for arid locations. We identify nonlinear thresholds beyond which predictive performance decreases for NWM and NHM. For example, soil water content less than 210 mm, precipitation less than 900 mm yr−1, road density greater than 5 km km−2, and lake area percent greater than 10 % contributed to lower KGE values. These results suggest that improvements in how these influential processes are represented could result in the largest increases in NWM and NHM predictive performance. This study demonstrates the utility of interrogating process-based models using data-driven techniques, which has broad applicability and potential for improving the next generation of large-scale hydrologic models.

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University)","active":true,"usgs":false}],"preferred":false,"id":930390,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hammond, John Christopher 0000-0002-6241-3551","orcid":"https://orcid.org/0000-0002-6241-3551","contributorId":302952,"corporation":false,"usgs":true,"family":"Hammond","given":"John","email":"","middleInitial":"Christopher","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":930391,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Price, Adam N. 0000-0002-7211-4758","orcid":"https://orcid.org/0000-0002-7211-4758","contributorId":295971,"corporation":false,"usgs":false,"family":"Price","given":"Adam","email":"","middleInitial":"N.","affiliations":[{"id":27155,"text":"University of California Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":930392,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Roundy, Joshua","contributorId":352231,"corporation":false,"usgs":false,"family":"Roundy","given":"Joshua","affiliations":[{"id":84135,"text":"Department of Civil, Environmental and Architectural Engineering, University of Kansas","active":true,"usgs":false}],"preferred":false,"id":930393,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70273507,"text":"70273507 - 2025 - A glimpse into the future of tectonic tremor monitoring","interactions":[],"lastModifiedDate":"2026-02-10T13:35:45.088926","indexId":"70273507","displayToPublicDate":"2025-09-17T09:10:17","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7501,"text":"JGR Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"A glimpse into the future of tectonic tremor monitoring","docAbstract":"

Tectonic tremor is a weak, long-duration seismic signal often observed in subduction zones and on some other plate-bounding faults. Because of tremor's characteristically low amplitude (and low signal-to-noise) and lack of clear phase arrivals, detecting and locating tremor usually requires techniques distinct from those applied to typical earthquakes. Major advances in detection and understanding of tremor have derived in the past from a powerful combination of new data and new analysis techniques. In a recent study, Sagae et al. (2025, https://doi.org/10.1029/2025jb031348) exploit that combination again, developing a new machine-learning based workflow and applying it to the S-net cabled seismic network in the Japan trench offshore northern Honshu. Their approach, although complex, succeeds in detecting several times more tremor activity than earlier studies, resulting in new insights and providing a blueprint for similar approaches that could be applied elsewhere. As real-time earthquake monitoring adopts similar tools, it may present an opportunity to bring tremor monitoring into operational workflows. In turn, this could solidify tremor monitoring as a component of future operational earthquake forecasting.

","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2025JB032642","usgsCitation":"Shelly, D.R., 2025, A glimpse into the future of tectonic tremor monitoring: JGR Solid Earth, v. 130, no. 9, e2025JB032642, 5 p., https://doi.org/10.1029/2025JB032642.","productDescription":"e2025JB032642, 5 p.","ipdsId":"IP-181421","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":498930,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2025jb032642","text":"Publisher Index Page"},{"id":498798,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"130","issue":"9","noUsgsAuthors":false,"publicationDate":"2025-09-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Shelly, David R. 0000-0003-2783-5158 dshelly@usgs.gov","orcid":"https://orcid.org/0000-0003-2783-5158","contributorId":206750,"corporation":false,"usgs":true,"family":"Shelly","given":"David","email":"dshelly@usgs.gov","middleInitial":"R.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":954083,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70271488,"text":"70271488 - 2025 - Reduced Atlantic reef growth past 2 °C warming amplifies sea-level impacts","interactions":[],"lastModifiedDate":"2025-12-01T16:35:40.162981","indexId":"70271488","displayToPublicDate":"2025-09-17T09:09:26","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2840,"text":"Nature","active":true,"publicationSubtype":{"id":10}},"title":"Reduced Atlantic reef growth past 2 °C warming amplifies sea-level impacts","docAbstract":"

Coral reefs form complex physical structures that can help to mitigate coastal flooding risk1,2. This function will be reduced by sea-level rise (SLR) and impaired reef growth caused by climate change and local anthropogenic stressors3. Water depths above reef surfaces are projected to increase as a result, but the magnitudes and timescales of this increase are poorly constrained, which limits modelling of coastal vulnerability4,5. Here we analyse fossil reef deposits to constrain links between reef ecology and growth potential across more than 400 tropical western Atlantic sites, and assess the magnitudes of resultant above-reef increases in water depth through to 2100 under various shared socioeconomic pathway (SSP) emission scenarios. Our analysis predicts that more than 70% of tropical western Atlantic reefs will transition into net erosional states by 2040, but that if warming exceeds 2 °C (SSP2–4.5 and higher), nearly all reefs (at least 99%) will be eroding by 2100. The divergent trajectories of reef growth and SLR will thus magnify the effects of SLR; increases in water depth of around 0.3–0.5 m above the present are projected under all warming scenarios by 2060, but depth increases of 0.7–1.2 m are predicted by 2100 under scenarios in which warming surpasses 2 °C. This would increase the risk of flooding along vulnerable reef-fronted coasts and modify nearshore hydrodynamics and ecosystems. Reef restoration offers one pathway back to higher reef growth6,7, but would dampen the effects of SLR in 2100 only by around 0.3–0.4 m, and only when combined with aggressive climate mitigation.

","language":"English","publisher":"Nature","doi":"10.1038/s41586-025-09439-4","usgsCitation":"Perry, C.T., de Bakker, D., Webb, A., Comeau, S., Harvey, B., Cornwall, C., Alvarez-Filip, L., Perez-Cervantes, E., Morris, J.T., Enochs, I.C., Toth, L., O'Dea, A., Dillon, E.M., Meesters, E.H., and Precht, W., 2025, Reduced Atlantic reef growth past 2 °C warming amplifies sea-level impacts: Nature, v. 646, p. 619-626, https://doi.org/10.1038/s41586-025-09439-4.","productDescription":"8 p.","startPage":"619","endPage":"626","ipdsId":"IP-174363","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":495742,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41586-025-09439-4","text":"Publisher Index Page"},{"id":495706,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Bonaire, Mexico, United 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Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":949002,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Meesters, Erik H,","contributorId":361576,"corporation":false,"usgs":false,"family":"Meesters","given":"Erik","middleInitial":"H,","affiliations":[],"preferred":false,"id":948947,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Precht, William F.","contributorId":119464,"corporation":false,"usgs":true,"family":"Precht","given":"William F.","affiliations":[],"preferred":false,"id":949003,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}} ,{"id":70269893,"text":"sir20255057 - 2025 - Sources of water and salts for the Zuni Salt Lake in west-central New Mexico","interactions":[],"lastModifiedDate":"2026-02-03T15:26:20.493234","indexId":"sir20255057","displayToPublicDate":"2025-09-17T09:01:13","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-5057","displayTitle":"Sources of Water and Salts for the Zuni Salt Lake in West-Central New Mexico","title":"Sources of water and salts for the Zuni Salt Lake in west-central New Mexico","docAbstract":"

The Zuni Salt Lake is located in a maar in west-central New Mexico and contains hypersaline water that has long been used by Native Americans for religious purposes and the collection of salt. There have been several investigations suggesting different sources for the water and salt to the lake. Springs, seeps, and ephemeral streamflow have all been observed to contribute freshwater to the lake, and brackish to hypersaline seeps have been documented along the banks of the lake. This report summarizes the findings of a study that characterizes the lake’s hydrology, its water and salinity sources, and the hydrogeologic conceptual model. Regional groundwater levels indicate that each of the aquifers in the area have the potential to discharge groundwater to the lake. There is also evidence of vertical groundwater flow pathways at the maar that were likely created by the igneous intrusion that fractured the intersecting aquifers. A detailed water budget was constructed from continuous lake stage, precipitation, and evaporation data to estimate the groundwater inflow to the Zuni Salt Lake. It was determined that groundwater inflow to the lake is 441 ±94 acre-feet per year, which composes as much as 77 percent of the total inflows. The high sodium and chloride concentrations measured in two hypersaline samples collected near the lake indicate that the majority of the dissolved solids entering the lake are from a hypersaline groundwater source. The geochemical and isotopic compositions measured in the lake and surrounding features support the interpretation that hypersaline groundwater is the primary source of salts to the lake, which is likely sourced from the older (and deeper) Permian units. The hypersaline groundwater samples collected during this investigation have a unique aqueous chemistry relative to each of the mapped aquifers, and variability in groundwater compositions is interpreted to result from differences in minerology and residence time.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255057","issn":"2328-0328","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Robertson, A.J., Pepin, J.D., Gray, E.L., Collison, J.W., Brown, J., Ritchie, A., and Ball, G., 2025, Sources of water and salts for the Zuni Salt Lake in west-central New Mexico: U.S. Geological Survey Scientific Investigations Report 2025–5057, 40 p., https://doi.org/10.3133/sir20255057.","productDescription":"Report: viii, 40 p.; Data Release; 2 Datasets","numberOfPages":"52","onlineOnly":"Y","ipdsId":"IP-167505","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":496025,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118875.htm","linkFileType":{"id":5,"text":"html"}},{"id":493625,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS Dataset","linkHelpText":"- USGS water data for the Nation"},{"id":493624,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://data.usbr.gov/catalog/4699","text":"Bureau of Relamation Dataset","linkHelpText":"- Zuni Salt Lake weather monitoring data"},{"id":493647,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P16248E8","text":"USGS Data Release","linkHelpText":"- Aerial imagery, digital elevation model, orthomosaic image, ground control points, and bathymetry surveys to identify sources of water and salts for the Zuni Salt Lake in west-central New Mexico, United States"},{"id":493627,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255057/full","linkFileType":{"id":5,"text":"html"},"description":"SIR 2025-5057 HTML"},{"id":493628,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5057/sir20255057.XML","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2025-5057 XML"},{"id":493626,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5057/sir20255057.pdf","size":"10.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5057"},{"id":493629,"rank":2,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5057/images"},{"id":493630,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5057/coverthb.jpg"}],"country":"United States","state":"New Mexico","otherGeospatial":"Zuni Salt Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -109,\n 34.75\n ],\n [\n -109,\n 34.333\n ],\n [\n -108.333,\n 34.333\n ],\n [\n -108.333,\n 34.75\n ],\n [\n -109,\n 34.75\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"

Director, New Mexico Water Science Center
U.S. Geological Survey
6700 Edith Blvd. NE
Albuquerque, NM 87113

Contact Us- USGS Publications Warehouse

","tableOfContents":"","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2025-09-17","noUsgsAuthors":false,"publicationDate":"2025-09-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Robertson, Andrew J. 0000-0003-2130-0347 ajrobert@usgs.gov","orcid":"https://orcid.org/0000-0003-2130-0347","contributorId":4129,"corporation":false,"usgs":true,"family":"Robertson","given":"Andrew","email":"ajrobert@usgs.gov","middleInitial":"J.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":944889,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pepin, Jeff D. 0000-0002-7410-9979","orcid":"https://orcid.org/0000-0002-7410-9979","contributorId":222161,"corporation":false,"usgs":true,"family":"Pepin","given":"Jeff","email":"","middleInitial":"D.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":944890,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gray, Erin L. 0000-0002-3945-6393","orcid":"https://orcid.org/0000-0002-3945-6393","contributorId":359054,"corporation":false,"usgs":true,"family":"Gray","given":"Erin","middleInitial":"L.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":944891,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Collison, Jake W. collison@usgs.gov","contributorId":5505,"corporation":false,"usgs":true,"family":"Collison","given":"Jake W.","email":"collison@usgs.gov","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":false,"id":944892,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brown, Jeb E. 0000-0001-7671-2379","orcid":"https://orcid.org/0000-0001-7671-2379","contributorId":225088,"corporation":false,"usgs":true,"family":"Brown","given":"Jeb E.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":944893,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ritchie, Andre 0000-0003-1289-653X abritchie@usgs.gov","orcid":"https://orcid.org/0000-0003-1289-653X","contributorId":195788,"corporation":false,"usgs":true,"family":"Ritchie","given":"Andre","email":"abritchie@usgs.gov","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":944894,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ball, Grady 0000-0003-3030-055X","orcid":"https://orcid.org/0000-0003-3030-055X","contributorId":220746,"corporation":false,"usgs":true,"family":"Ball","given":"Grady","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":944895,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70271523,"text":"70271523 - 2025 - Energetic value of Arctic forage-sized fish with implications for a nearshore seabird predator","interactions":[],"lastModifiedDate":"2025-09-18T15:25:56.527767","indexId":"70271523","displayToPublicDate":"2025-09-17T08:16:26","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2660,"text":"Marine Biology","active":true,"publicationSubtype":{"id":10}},"title":"Energetic value of Arctic forage-sized fish with implications for a nearshore seabird predator","docAbstract":"

Arctic cod (Boreogadus saida, also called polar cod) are considered the single most important Arctic forage fish due to their high abundance and nutritional quality. Because Arctic cod are strongly ice associated and prefer colder waters, their frequency in coastal waters has declined with warming, decreasing availability to nearshore predators. To consider the nutritional quality of alternative prey, we measured energy density and estimated whole-body energy of forage-size (39–200 mm) fishes collected during summers 2021–2023 (n = 274). The fishes sampled included 16 potential prey species from Foggy Island Bay (70.3°N, 147.5°W, near Prudhoe Bay) and Lion Bay (70.2°N, 146.4°W, near Flaxman Island), northern Alaska. Dry weight energy densities ranged from 16.2 to 27.5 kJ g-1 (mean ± SD = 22.0 ± 1.73 kJ g-1, n = 274) across individuals. Of common species, Arctic cod had the highest mean energy density (24.3 ± 1.1 kJ g-1, n = 25) and fourhorn sculpin (Myoxocephalus quadricornis) had the lowest (19.7 ± 0.8 kJ g-1, n = 20). To account for size differences among prey species, whole-body energy of typical fish sizes available to predators were modeled using whole-body energy to length relationships and length distributions. Juvenile salmonids (e.g., ciscoes and whitefishes) provided the most energy per individual and were four-fold greater than smaller-bodied Arctic cod. Predators that consume juvenile ciscoes and whitefishes may be more resilient to declines in Arctic cod availability than predators with smaller gapes.

","language":"English","publisher":"Springer Nature","doi":"10.1007/s00227-025-04705-5","usgsCitation":"Stanek, A.E., Uher-Koch, B.D., Dunton, K.H., and von Biela, V.R., 2025, Energetic value of Arctic forage-sized fish with implications for a nearshore seabird predator: Marine Biology, v. 172, 157, 13 p., https://doi.org/10.1007/s00227-025-04705-5.","productDescription":"157, 13 p.","ipdsId":"IP-171231","costCenters":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":495747,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s00227-025-04705-5","text":"Publisher Index Page"},{"id":495713,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Beaufort Sea coast","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -157.2117957640097,\n 71.3543754933907\n ],\n [\n -157.2117957640097,\n 69.83926146873208\n ],\n [\n -145.833226056111,\n 69.83926146873208\n ],\n [\n -145.833226056111,\n 71.3543754933907\n ],\n [\n -157.2117957640097,\n 71.3543754933907\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"172","noUsgsAuthors":false,"publicationDate":"2025-09-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Stanek, Ashley E. 0000-0001-5184-2126","orcid":"https://orcid.org/0000-0001-5184-2126","contributorId":290682,"corporation":false,"usgs":true,"family":"Stanek","given":"Ashley","email":"","middleInitial":"E.","affiliations":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"preferred":true,"id":948998,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Uher-Koch, Brian D. 0000-0002-1885-0260 buher-koch@usgs.gov","orcid":"https://orcid.org/0000-0002-1885-0260","contributorId":5117,"corporation":false,"usgs":true,"family":"Uher-Koch","given":"Brian","email":"buher-koch@usgs.gov","middleInitial":"D.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":948999,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dunton, Kenneth H. 0000-0003-3498-8021","orcid":"https://orcid.org/0000-0003-3498-8021","contributorId":361574,"corporation":false,"usgs":false,"family":"Dunton","given":"Kenneth","middleInitial":"H.","affiliations":[{"id":47685,"text":"Marine Science Institute, University of Texas at Austin","active":true,"usgs":false}],"preferred":false,"id":949000,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"von Biela, Vanessa R. 0000-0002-7139-5981 vvonbiela@usgs.gov","orcid":"https://orcid.org/0000-0002-7139-5981","contributorId":3104,"corporation":false,"usgs":true,"family":"von Biela","given":"Vanessa","email":"vvonbiela@usgs.gov","middleInitial":"R.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":949001,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70272173,"text":"70272173 - 2025 - Ecophysiology of two mesophotic octocorals intended for restoration: Effects of light and temperature","interactions":[],"lastModifiedDate":"2025-12-01T16:53:34.273606","indexId":"70272173","displayToPublicDate":"2025-09-17T08:08:58","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2620,"text":"Limnology and Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"Ecophysiology of two mesophotic octocorals intended for restoration: Effects of light and temperature","docAbstract":"

Light and temperature are driving forces that shape the evolution and physiology of mesophotic organisms. On the Mississippi-Alabama continental shelf, octocorals dominate the mesophotic seascape and provide habitat for many fish and invertebrate species. Gaps in knowledge regarding the fundamental physiological responses of these species to light and temperature are of particular interest to restoration activities following the Deepwater Horizon oil spill. To address these gaps, the photobiology and thermal tolerance of Swiftia exserta and Muricea pendula were assessed in the field and laboratory. Pulse amplitude modulated fluorometry, histology, light microscopy, and epifluorescence imaging revealed low densities of photosynthetic endobionts in samples of S. exserta and none in samples of M. pendula collected near the determined bottom of the euphotic zone (51.45 m). Response to the recorded monthly mean habitat temperature range (18.5–25.4°C) was assessed using respirometry and polyp activity data from live corals exposed to temperatures between 18°C and 26°C. There was no significant difference in oxygen consumption for either species between 18°C and 26°C, and calculated Q10 values were not significantly different from 1, thus suggesting that both species have a low sensitivity to the local thermal environment. However, a negative correlation between temperature and polyp activity suggests that M. pendula is more sensitive to higher temperatures than S. exserta. This study improves the understanding of the effects of light and temperature on mesophotic octocoral physiology and lays the foundation for future work to explore the thermal thresholds of each species and the endobiont–host relationship in S. exserta.

","language":"English","publisher":"Association for the Sciences of Limnology and Oceanography","doi":"10.1002/lno.70214","usgsCitation":"Lange, K., Aquilina-Beck, A., Mccauley, M., Johnstone, J., Demopoulos, A., Greig, T., Beers, J.M., Spalding, H.L., and Etnoyer, P.J., 2025, Ecophysiology of two mesophotic octocorals intended for restoration: Effects of light and temperature: Limnology and Oceanography, v. 70, no. 11, p. 3309-3321, https://doi.org/10.1002/lno.70214.","productDescription":"13 p.","startPage":"3309","endPage":"3321","ipdsId":"IP-170683","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":496730,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/lno.70214","text":"Publisher Index Page"},{"id":496581,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alabama, Mississippi, South Carolina","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -89.45340087314823,\n 30.115510467549512\n ],\n [\n -89.64821880892258,\n 27.852030542053697\n ],\n [\n -77.85588264276542,\n 30.821175006212798\n ],\n [\n -78.19061941496408,\n 33.2102871797333\n ],\n [\n -89.45340087314823,\n 30.115510467549512\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"70","issue":"11","noUsgsAuthors":false,"publicationDate":"2025-09-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Lange, Kassidy","contributorId":362314,"corporation":false,"usgs":false,"family":"Lange","given":"Kassidy","affiliations":[{"id":86500,"text":"Consolidated Safety Services (CSS) Inc., under contract to National Oceanic and Atmospheric Administration (NOAA), National Ocean Service, National Centers for Coastal Ocean Science, Charleston, SC, United States","active":true,"usgs":false}],"preferred":false,"id":950304,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aquilina-Beck, Allisan","contributorId":362315,"corporation":false,"usgs":false,"family":"Aquilina-Beck","given":"Allisan","affiliations":[{"id":86500,"text":"Consolidated Safety Services (CSS) Inc., under contract to National Oceanic and Atmospheric Administration (NOAA), National Ocean Service, National Centers for Coastal Ocean Science, Charleston, SC, United States","active":true,"usgs":false}],"preferred":false,"id":950305,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mccauley, Mark 0000-0001-5347-6860","orcid":"https://orcid.org/0000-0001-5347-6860","contributorId":357083,"corporation":false,"usgs":true,"family":"Mccauley","given":"Mark","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":950306,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Johnstone, Julia","contributorId":243034,"corporation":false,"usgs":false,"family":"Johnstone","given":"Julia","email":"","affiliations":[{"id":48621,"text":"Darling Marine Center, University of Maine","active":true,"usgs":false}],"preferred":false,"id":950307,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Demopoulos, Amanda 0000-0003-2096-4694","orcid":"https://orcid.org/0000-0003-2096-4694","contributorId":210508,"corporation":false,"usgs":true,"family":"Demopoulos","given":"Amanda","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":950308,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Greig, Thomas","contributorId":362316,"corporation":false,"usgs":false,"family":"Greig","given":"Thomas","affiliations":[{"id":86503,"text":"National Oceanic and Atmospheric Administration (NOAA), National Ocean Service, National Centers for Coastal Ocean Science, Charleston, SC, United States","active":true,"usgs":false}],"preferred":false,"id":950309,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Beers, Jody M.","contributorId":362317,"corporation":false,"usgs":false,"family":"Beers","given":"Jody","middleInitial":"M.","affiliations":[{"id":86504,"text":"College of Charleston, Charleston, SC, United States","active":true,"usgs":false}],"preferred":false,"id":950310,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Spalding, Heather L.","contributorId":362318,"corporation":false,"usgs":false,"family":"Spalding","given":"Heather","middleInitial":"L.","affiliations":[{"id":86504,"text":"College of Charleston, Charleston, SC, United States","active":true,"usgs":false}],"preferred":false,"id":950311,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Etnoyer, Peter J.","contributorId":362319,"corporation":false,"usgs":false,"family":"Etnoyer","given":"Peter","middleInitial":"J.","affiliations":[{"id":86503,"text":"National Oceanic and Atmospheric Administration (NOAA), National Ocean Service, National Centers for Coastal Ocean Science, Charleston, SC, United States","active":true,"usgs":false}],"preferred":false,"id":950312,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70273247,"text":"70273247 - 2025 - Variation and controls of sediment oxygen demand in backwater lakes of the Upper Mississippi River during winter","interactions":[],"lastModifiedDate":"2025-12-23T15:09:19.316964","indexId":"70273247","displayToPublicDate":"2025-09-17T08:02:00","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3301,"text":"River Research and Applications","active":true,"publicationSubtype":{"id":10}},"title":"Variation and controls of sediment oxygen demand in backwater lakes of the Upper Mississippi River during winter","docAbstract":"

Many ecological processes affect the availability of winter dissolved oxygen (DO) concentrations in rivers, a key feature of overwintering fish habitat. Sediment oxygen demand (SOD) contributes to DO depletion, particularly during ice-covered periods, and may cause hypoxic conditions in backwater lakes, affecting the availability of suitable overwintering habitat. Understanding the drivers of SOD on habitat conditions during winter is critical for the management of the Upper Mississippi River System (UMRS). We measured SOD rates in three different habitat types (shallow, non-vegetated; deep, non-vegetated; and vegetated) within 12 backwater lakes in Pools 4, Pool 8, and Pool 13 of the UMRS in January and February 2022. Sediment physicochemical characteristics were measured to identify potential drivers of winter SOD rates. Measured SOD rates ranged from 0.04–0.44 g O2/(m2d) at in situ temperatures, and 0.14–1.46 g O2/(m2d) when corrected to 20°C. There were no statistically significant relations between in situ SOD and most sediment characteristics. SOD was positively associated with aquatic vegetation presence and negatively associated with sediment pH, water depth, flow velocity, and ice depth. SOD was typically higher at vegetated sites with lower flow velocity, with four of the five highest SOD rates measured at vegetated sites. Vegetation presence, depth, and flow velocity played greater roles in controlling SOD rates than sediment characteristics. Additionally, DO concentrations near the sediment–water interface at deep sites (> 1.5 m) were much lower than DO concentrations 0.2 m under the water surface, indicating that SOD was influencing DO concentrations and may be affecting overwintering habitat in backwater lakes.

","language":"English","publisher":"Wiley","doi":"10.1002/rra.70011","usgsCitation":"Perner, P.M., Kreiling, R.M., Jankowski, K.J., and Strauss, E.A., 2025, Variation and controls of sediment oxygen demand in backwater lakes of the Upper Mississippi River during winter: River Research and Applications, v. 41, no. 10, p. 2189-2204, https://doi.org/10.1002/rra.70011.","productDescription":"16 p.","startPage":"2189","endPage":"2204","ipdsId":"IP-170589","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":498054,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/rra.70011","text":"Publisher Index Page"},{"id":497936,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois, Iowa, Minnesota, Missouri, Wisconsin","otherGeospatial":"Upper Mississippi River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -93.10097042912157,\n 44.97281290065325\n ],\n [\n -91.759506701898,\n 43.740062945434715\n ],\n [\n -90.9674401636216,\n 42.01556148014882\n ],\n [\n -91.743596973701,\n 39.81261700824835\n ],\n [\n -90.48342253124173,\n 38.34168124893585\n ],\n [\n -89.22324808878244,\n 36.870745489623346\n ],\n [\n -90.81905145778899,\n 40.275434086550305\n ],\n [\n -89.87713786574906,\n 41.79816956524569\n ],\n [\n -90.01573449349698,\n 42.334520209936784\n ],\n [\n -91.1511012598934,\n 43.92329321891202\n ],\n [\n -92.65275956586878,\n 45.089302207190485\n ],\n [\n -93.10097042912157,\n 44.97281290065325\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"41","issue":"10","noUsgsAuthors":false,"publicationDate":"2025-09-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Perner, Patrik Mathis 0000-0002-6142-518X","orcid":"https://orcid.org/0000-0002-6142-518X","contributorId":261675,"corporation":false,"usgs":true,"family":"Perner","given":"Patrik","email":"","middleInitial":"Mathis","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":952847,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kreiling, Rebecca M. 0000-0002-9295-4156","orcid":"https://orcid.org/0000-0002-9295-4156","contributorId":202193,"corporation":false,"usgs":true,"family":"Kreiling","given":"Rebecca","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":952848,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jankowski, Kathi Jo 0000-0002-3292-4182","orcid":"https://orcid.org/0000-0002-3292-4182","contributorId":207429,"corporation":false,"usgs":true,"family":"Jankowski","given":"Kathi","email":"","middleInitial":"Jo","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":952849,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Strauss, Eric A. 0000-0002-3134-2535","orcid":"https://orcid.org/0000-0002-3134-2535","contributorId":364544,"corporation":false,"usgs":false,"family":"Strauss","given":"Eric","middleInitial":"A.","affiliations":[{"id":47908,"text":"University of Wisconsin - La Crosse","active":true,"usgs":false}],"preferred":false,"id":952850,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70275088,"text":"70275088 - 2025 - Silver Carp passage at three locks and dams on the Tennessee and Cumberland rivers from 2016–2019","interactions":[],"lastModifiedDate":"2026-04-15T15:34:54.276451","indexId":"70275088","displayToPublicDate":"2025-09-17T00:00:00","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Silver Carp passage at three locks and dams on the Tennessee and Cumberland rivers from 2016–2019","docAbstract":"

Bigheaded carps (i.e., Silver Carp Hypophthalmichthys molitrix and Bighead Carp H. nobilis) are non-native species that continue to expand their ranges throughout North American river systems, including the Tennessee and Cumberland river systems in the southeastern United States. These species are known to have deleterious effects on native fishes. Management efforts have focused on reducing upstream passage at dams coupled with intensive removal of individuals occupying upstream reaches. Understanding mechanisms affecting the success of upstream fish passage through lock chambers is critical to determining immigration rates into upstream habitats, the likelihood of success for upstream removal efforts, and potential effects of upstream passage reduction using deterrents. We used acoustic telemetry to examine the timing of Silver Carp upstream and downstream dam passages, patterns of fish movement throughout the river systems, and the relationship between fish size and upstream passage through the lock chamber. During 2016–2019, 465 Silver Carp were surgically implanted with transmitters within the two river systems. We documented 37 upstream passages and 57 downstream passages of Barkley, Kentucky, and Pickwick dams. During the two years in which dam passages were observed, most upstream dam passages (89%) occurred during April–August when water temperature ranged from 12–31°C. Most downstream passages (89%) occurred from late-February through July. The relatively small portion of Silver Carp tagged in Pickwick Lake (11% of total tagged), the uppermost reach of the study area, accounted for nearly two-thirds of all dam passages. Our findings may help managers model Silver Carp populations and inform decisions regarding fish deterrent placement and operation.

","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.70112","usgsCitation":"Vallazza, J.M., Mosel, K.J., Budnick, W.R., Gibson-Reinemer, D.K., Tompkins, J.K., Morris, J., Spier, T.W., Cox, T.L., Rogers, M.W., Harty, C.R., Knights, B.C., Brey, M.K., and Fritts, A.K., 2025, Silver Carp passage at three locks and dams on the Tennessee and Cumberland rivers from 2016–2019: Journal of Wildlife Management, v. 89, no. 8, e70112, 15 p., https://doi.org/10.1002/jwmg.70112.","productDescription":"e70112, 15 p.","ipdsId":"IP-158291","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":502818,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alabama, Arkansas, Illinois, Kentucky, Mississippi, Tennessee","otherGeospatial":"Cumberland River, Tennessee River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -90.38515431169161,\n 37.38962563616131\n ],\n [\n -91.12672658546718,\n 34.95004928050432\n ],\n [\n -90.54678356290209,\n 34.125109085841345\n ],\n [\n -87.05805719979179,\n 34.23904824400745\n ],\n [\n -87.64952721730523,\n 37.4254281941071\n ],\n [\n -90.38515431169161,\n 37.38962563616131\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"89","issue":"8","noUsgsAuthors":false,"publicationDate":"2025-09-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Vallazza, Jon M. 0000-0003-2367-4887","orcid":"https://orcid.org/0000-0003-2367-4887","contributorId":355214,"corporation":false,"usgs":false,"family":"Vallazza","given":"Jon","middleInitial":"M.","affiliations":[{"id":48800,"text":"Former USGS, UMESC employee","active":true,"usgs":false}],"preferred":false,"id":959409,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mosel, Kyle J. 0000-0002-9885-6960","orcid":"https://orcid.org/0000-0002-9885-6960","contributorId":317887,"corporation":false,"usgs":true,"family":"Mosel","given":"Kyle","middleInitial":"J.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":959410,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Budnick, William R R. 0000-0001-9288-6782","orcid":"https://orcid.org/0000-0001-9288-6782","contributorId":355213,"corporation":false,"usgs":false,"family":"Budnick","given":"William R","middleInitial":"R.","affiliations":[{"id":48800,"text":"Former USGS, UMESC employee","active":true,"usgs":false}],"preferred":false,"id":959411,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gibson-Reinemer, Daniel K. 0000-0002-8992-014X","orcid":"https://orcid.org/0000-0002-8992-014X","contributorId":317886,"corporation":false,"usgs":true,"family":"Gibson-Reinemer","given":"Daniel","middleInitial":"K.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":959412,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Tompkins, Joshua K.","contributorId":369943,"corporation":false,"usgs":false,"family":"Tompkins","given":"Joshua","middleInitial":"K.","affiliations":[{"id":13409,"text":"Kentucky Department of Fish & Wildlife Resources","active":true,"usgs":false}],"preferred":false,"id":959413,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Morris, Jessica","contributorId":331135,"corporation":false,"usgs":false,"family":"Morris","given":"Jessica","email":"","affiliations":[{"id":53972,"text":"Kentucky Department of Fish and Wildlife Resources","active":true,"usgs":false}],"preferred":false,"id":959414,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Spier, Timothy W.","contributorId":369945,"corporation":false,"usgs":false,"family":"Spier","given":"Timothy","middleInitial":"W.","affiliations":[{"id":84083,"text":"Murray State University","active":true,"usgs":false}],"preferred":false,"id":959415,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Cox, Tanner L.","contributorId":369948,"corporation":false,"usgs":false,"family":"Cox","given":"Tanner","middleInitial":"L.","affiliations":[{"id":56209,"text":"Tennessee Tech University","active":true,"usgs":false}],"preferred":false,"id":959416,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Rogers, Mark W.","contributorId":369950,"corporation":false,"usgs":false,"family":"Rogers","given":"Mark","middleInitial":"W.","affiliations":[{"id":56209,"text":"Tennessee Tech University","active":true,"usgs":false}],"preferred":false,"id":959417,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Harty, Cole R.","contributorId":369951,"corporation":false,"usgs":false,"family":"Harty","given":"Cole","middleInitial":"R.","affiliations":[{"id":56209,"text":"Tennessee Tech University","active":true,"usgs":false}],"preferred":false,"id":959418,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Knights, Brent C. 0000-0001-8526-8468","orcid":"https://orcid.org/0000-0001-8526-8468","contributorId":304124,"corporation":false,"usgs":false,"family":"Knights","given":"Brent","middleInitial":"C.","affiliations":[{"id":65975,"text":"UMESC Retired","active":true,"usgs":false}],"preferred":false,"id":959419,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Brey, Marybeth K. 0000-0003-4403-9655 mbrey@usgs.gov","orcid":"https://orcid.org/0000-0003-4403-9655","contributorId":187651,"corporation":false,"usgs":true,"family":"Brey","given":"Marybeth","email":"mbrey@usgs.gov","middleInitial":"K.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":959420,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Fritts, Andrea K. 0000-0003-2142-3339","orcid":"https://orcid.org/0000-0003-2142-3339","contributorId":204594,"corporation":false,"usgs":true,"family":"Fritts","given":"Andrea","email":"","middleInitial":"K.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":959421,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70272270,"text":"70272270 - 2025 - Hydrologic connectivity in floodplain systems: A multiscale review of concepts, metrics and management","interactions":[],"lastModifiedDate":"2025-11-20T16:06:54.982885","indexId":"70272270","displayToPublicDate":"2025-09-16T10:03:43","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Hydrologic connectivity in floodplain systems: A multiscale review of concepts, metrics and management","docAbstract":"

Hydrologic connectivity (HC), particularly in floodplain systems, is pivotal in regulating ecosystem services by facilitating the movement of nutrients, sediments, chemicals, and biota. However, human interventions such as dam construction, levee installation, water management practices, and alterations in vegetation have significantly disrupted natural HC patterns globally. To provide a structured entry into the growing body of HC research, we conducted a systematic literature review of 1920 studies, analysing diverse definitions, influencing factors, quantification approaches, spatial and temporal scales, and management strategies. In addition to traditional review methods, our approach integrates keyword and cluster analysis to elucidate dominant research themes and trends across the literature. Our review reveals that the literature is heavily skewed towards research in North America and Europe (accounting for 72% of studies) and predominantly utilises field investigations, simulation modelling, and remote sensing integrated with geographic information systems. Although these methodologies have advanced our understanding, most studies focus on restricted spatial scales such as individual hillslopes, catchments, or stream networks and short temporal intervals, including single precipitation events or seasonal cycles. A narrow focus becomes a limitation when such studies do not contribute to broader efforts aimed at scaling insights across larger domains. These limitations highlight the potential benefits of innovative conceptual frameworks and quantification methods to better capture HC across broader environments and extended temporal scales. We conclude by discussing challenges in defining and quantifying floodplain HC and outlining potential future research directions to advance connectivity science and management, particularly in floodplain systems characterised by frequent hydrologic fluctuations, such as seasonal inundation and changing flow paths.

","language":"English","publisher":"Wiley","doi":"10.1002/hyp.70260","usgsCitation":"Hafez Ahmad, Miranda, L.E., Dunn, C.G., Melanie R. Boudreau, and Colvin, M.E., 2025, Hydrologic connectivity in floodplain systems: A multiscale review of concepts, metrics and management: Hydrological Processes, v. 39, no. 9, e70260, 23 p., https://doi.org/10.1002/hyp.70260.","productDescription":"e70260, 23 p.","ipdsId":"IP-177204","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":496691,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"39","issue":"9","noUsgsAuthors":false,"publicationDate":"2025-09-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Hafez Ahmad","contributorId":362594,"corporation":false,"usgs":false,"family":"Hafez Ahmad","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":950631,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Miranda, Leandro E. 0000-0002-2138-7924 smiranda@usgs.gov","orcid":"https://orcid.org/0000-0002-2138-7924","contributorId":531,"corporation":false,"usgs":true,"family":"Miranda","given":"Leandro","email":"smiranda@usgs.gov","middleInitial":"E.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":950632,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dunn, Corey Garland 0000-0002-7102-2165","orcid":"https://orcid.org/0000-0002-7102-2165","contributorId":288691,"corporation":false,"usgs":true,"family":"Dunn","given":"Corey","email":"","middleInitial":"Garland","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":950633,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Melanie R. Boudreau","contributorId":362597,"corporation":false,"usgs":false,"family":"Melanie R. Boudreau","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":950634,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Colvin, Michael E. 0000-0002-6581-4764","orcid":"https://orcid.org/0000-0002-6581-4764","contributorId":331490,"corporation":false,"usgs":true,"family":"Colvin","given":"Michael","email":"","middleInitial":"E.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":950735,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70271379,"text":"sir20255074 - 2025 - Using satellite imagery and soil data to understand occurrences and migration of soil conditions harmful to archaeological sites on Jamestown Island, Virginia","interactions":[],"lastModifiedDate":"2026-02-03T15:25:33.505229","indexId":"sir20255074","displayToPublicDate":"2025-09-16T10:00:00","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-5074","displayTitle":"Using Satellite Imagery and Soil Data To Understand Occurrences and Migration of Soil Conditions Harmful to Archaeological Sites on Jamestown Island, Virginia","title":"Using satellite imagery and soil data to understand occurrences and migration of soil conditions harmful to archaeological sites on Jamestown Island, Virginia","docAbstract":"

Many know Jamestown Island, Virginia, hereafter referred to as “the Island,” located near the mouth of the James River into the Chesapeake Bay, as the home of the first permanent English settlement in North America. However, the Island is home to 15,000 years’ worth of cultural artifacts and archaeological sites. In addition to its rich history, the Island is home to a variety of native plants and animals, including many rare, threatened, and endangered species. Preserving historical and natural resources is part of Colonial National Historic Park’s (COLO) enabling legislation. To this end, COLO has been seeking data to inform management decisions on how to prioritize resources to preserve archaeological sites and anticipate changes to natural systems from sea-level rise and other effects of climate change. The U.S. Geological Survey (USGS), in partnership with COLO, collected and analyzed data to help determine soil conditions detrimental to archaeological sites across the Island using a combination of soil samples and assessments of vegetative health as a proxy for soil conditions. This study combined normalized difference vegetative index raster grids spanning 8 years, 2010 to 2018, and soil data from 50 sites sampled in dry (June 2021) and wet months (March 2022) at two different soil horizons to investigate potential hazards to plant health and corrosive conditions in the unsaturated subsurface. The data suggest that access to the James River drives soil pH and soil conductivity. Areas of the Island that are subject to frequent inundation were observed to have both higher soil conductivity (as high as 4,845 millisiemens per meter [mS/m]) and lower pH (as low as 3.84). Higher soil conductivity, or salinity, and more acidity create corrosive environment, which can destroy buried artifacts and are detrimental to vegetative health. These conditions were not limited to the edges of the Island, like Black Point. Inland locations, such as the Pitch and Tar Swamp, were observed to have some of the highest conductivity values, which were likely caused by from a combination of inflow of James River water along Back Creek into the Pitch and Tar Swamp and proximity to the Visitor Center and other high-traffic areas of the Island. A difference of normalized difference vegetative index values from 2010 to 2018 raster grid appears to support this, showing an apparent loss of vegetative health in marsh grass in the Pitch and Tar Swamp. These data may inform COLO about areas of the Island that are currently most threatened by corrosive conditions and how those conditions are likely to migrate in the future.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255074","isbn":"978-1-4113-4629-1","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Caldwell, S.H., 2025, Using satellite imagery and soil data to understand occurrences and migration of soil conditions harmful to archaeological sites on Jamestown Island, Virginia (ver. 1.1, November 2025): U.S. Geological Survey Scientific Investigations Report 2025–5074, 22 p., https://doi.org/10.3133/sir20255074.","productDescription":"Report: vii, 22 p.; Data Release","numberOfPages":"22","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-167335","costCenters":[{"id":37280,"text":"Virginia and West Virginia Water Science Center ","active":true,"usgs":true}],"links":[{"id":497790,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118874.htm"},{"id":496292,"rank":7,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2025/5074/versionHist.txt","size":"632 B","linkFileType":{"id":2,"text":"txt"}},{"id":495295,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13J32J4","text":"USGS data release","linkHelpText":"Satellite imagery products from 2010, 2011, 2018 and soil data from 2021–22 on Jamestown Island, Va."},{"id":495294,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5074/images/"},{"id":495293,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5074/sir20255074.XML","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2025-5074 XML"},{"id":495292,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255074/full","linkFileType":{"id":5,"text":"html"},"description":"SIR 2025-5074 HTML"},{"id":495291,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5074/sir20255074.pdf","text":"Report","size":"4.19 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5074 PDF"},{"id":495290,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5074/coverthb3.jpg"}],"country":"United States","state":"Virginia","otherGeospatial":"Jamestown Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -76.785,\n 37.22\n ],\n [\n -76.785,\n 37.19007232242731\n ],\n [\n -76.73168289008015,\n 37.19007232242731\n ],\n [\n -76.73168289008015,\n 37.22\n ],\n [\n -76.785,\n 37.22\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","edition":"Version 1.0: September 16, 2025; Version 1.1: September 30, 2025","contact":"

Director, Virginia and West Virginia Water Science Center
U.S. Geological Survey
1730 East Parham Road
Richmond, Virginia 23228

","tableOfContents":"","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"publishedDate":"2025-09-16","revisedDate":"2025-11-17","noUsgsAuthors":false,"publicationDate":"2025-09-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Caldwell, Samuel H. 0000-0002-4444-7002","orcid":"https://orcid.org/0000-0002-4444-7002","contributorId":292520,"corporation":false,"usgs":true,"family":"Caldwell","given":"Samuel","email":"","middleInitial":"H.","affiliations":[{"id":37280,"text":"Virginia and West Virginia Water Science Center ","active":true,"usgs":true}],"preferred":true,"id":948327,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70271504,"text":"70271504 - 2025 - To heal or not to heal?: 2. The moment-recurrence time behavior of repeating earthquakes in the 2011 Prague, Oklahoma aftershock sequence is consistent with laboratory healing rates","interactions":[],"lastModifiedDate":"2025-09-18T14:38:35.152792","indexId":"70271504","displayToPublicDate":"2025-09-16T09:27:03","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7501,"text":"JGR Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"To heal or not to heal?: 2. The moment-recurrence time behavior of repeating earthquakes in the 2011 Prague, Oklahoma aftershock sequence is consistent with laboratory healing rates","docAbstract":"

The timing and failure conditions of an earthquake are governed by the interplay between fault reloading and restrengthening. The moment-recurrence time behavior of repeating earthquakes can give observational estimates of fault healing rates; however, it is difficult to link these observed healing rates to laboratory studies of frictional healing in part because of uncertainty in lithology. Here, we study the 2011 Prague earthquake sequence, which includes repeating earthquakes in the Arbuckle group and the granitic basement, and compare them to laboratory experiments on samples of the Arbuckle and Troy granite (representative of the basement rock) (Okamoto et al., 2025, https://doi.org/10.1029/2024JB030573). We find three spatially distinct groups of repeating earthquakes with different moment-recurrence behavior: (a) constant moment-recurrence time in the Arbuckle group, (b) scattered moment-recurrence time at the intersection of the foreshock-mainshock fault in the granitic basement, and (c) moment-predictable behavior outside of the foreshock-mainshock fault intersection also in the granitic basement. Our observation of stagnant healing for repeating sequences in the Arbuckle group is consistent with laboratory observations of low healing rates for moderately high pore fluid pressures in Arbuckle samples. For the moment-predictable group, the source radius that is required in order to match healing rates is consistent with source radius estimations when taking into account reasonable attenuation of the P-pulse width. Overall, we observe diverse healing behaviors in the seismic families that are consistent with laboratory healing rates, providing seismic evidence that contact-scale frictional mechanisms are relevant to large-scale earthquake dynamics.

","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2024JB030548","usgsCitation":"Okamoto, K., Savage, H., Cochran, E.S., Brodsky, E., and Abercrombie, R., 2025, To heal or not to heal?: 2. The moment-recurrence time behavior of repeating earthquakes in the 2011 Prague, Oklahoma aftershock sequence is consistent with laboratory healing rates: JGR Solid Earth, v. 130, no. 9, e2024JB030548, 18 p., https://doi.org/10.1029/2024JB030548.","productDescription":"e2024JB030548, 18 p.","ipdsId":"IP-172199","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":495743,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2024jb030548","text":"Publisher Index Page"},{"id":495707,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oklahoma","city":"Prague","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -96.7,\n 35.6\n ],\n [\n -96.9,\n 35.6\n ],\n [\n -96.9,\n 35.4\n ],\n [\n -96.7,\n 35.4\n ],\n [\n -96.7,\n 35.6\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"130","issue":"9","noUsgsAuthors":false,"publicationDate":"2025-09-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Okamoto, Kristina","contributorId":296586,"corporation":false,"usgs":false,"family":"Okamoto","given":"Kristina","email":"","affiliations":[{"id":6948,"text":"UC Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":948974,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Savage, Heather M.","contributorId":296588,"corporation":false,"usgs":false,"family":"Savage","given":"Heather","middleInitial":"M.","affiliations":[{"id":6948,"text":"UC Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":948975,"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":948976,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brodsky, Emily","contributorId":299735,"corporation":false,"usgs":false,"family":"Brodsky","given":"Emily","affiliations":[{"id":27155,"text":"University of California Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":948977,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Abercrombie, Rachel E.","contributorId":293131,"corporation":false,"usgs":false,"family":"Abercrombie","given":"Rachel E.","affiliations":[{"id":7208,"text":"Department of Earth and Environment, Boston University","active":true,"usgs":false}],"preferred":false,"id":948978,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70271923,"text":"70271923 - 2025 - Environmental drivers of Greater Sage-grouse population trends over 25 years in Idaho, USA","interactions":[],"lastModifiedDate":"2025-09-24T15:36:30.070481","indexId":"70271923","displayToPublicDate":"2025-09-16T08:31:12","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Environmental drivers of Greater Sage-grouse population trends over 25 years in Idaho, USA","docAbstract":"

Greater Sage-grouse (Centrocercus urophasianus) populations have been in decline for decades across much of the US Intermountain West. However, findings from 25 years of lek counts in Idaho indicate that some populations are stable or even increasing. After accounting for potential biases in past lek count data, we sought to explain the variability in population trends among all 70 lek clusters (i.e., populations) we identified in the state. For each population, we identified lek count troughs, or low-point years, that occurred between the mid-1990s and 2021 and used a regression slope of those abundance low points to quantify each population's trend over the 25-year time span. We related the 70 populations' slopes to climate, fire, topographic, vegetation, and landcover variables. Our analyses revealed that populations with negative trends tend to occur toward the ends of climate gradients (i.e., extremes of occupied habitats) and in locations with more wildfire, agriculture, and riparian landcover. Populations with positive trends generally occur in landscapes toward the middle of the climate gradient, with high amounts of low sagebrush (Artemisia arbuscula) landcover and intermediate amounts of riparian and agricultural landcover. Post hoc analysis indicated that the latter two drivers were strongly associated with high raven occupancy rates, which may contribute to the negative sage-grouse population trends we observed in areas with high riparian or agricultural landcover. When modeled separately for different regions however, various region-specific drivers were identified, including tree cover, annual herbaceous cover, and human development. This information can help guide sage-grouse habitat management decisions and set expectations for population recovery, given the diversity of habitats occupied by the species and the cyclic nature of sage-grouse populations.

","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.70331","usgsCitation":"Arkle, R.S., Pilliod, D.S., Jeffries, M.I., Welty, J.L., Moser, A., Ellsworth, E.A., and Major, D.J., 2025, Environmental drivers of Greater Sage-grouse population trends over 25 years in Idaho, USA: Ecosphere, v. 16, no. 9, e70331, 20 p., https://doi.org/10.1002/ecs2.70331.","productDescription":"e70331, 20 p.","ipdsId":"IP-156975","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":496159,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.70331","text":"Publisher Index Page"},{"id":496016,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.51050707303654,\n 44.996426283603455\n ],\n [\n -117.51050707303654,\n 41.98536993997118\n ],\n [\n -110.93279337585523,\n 41.98536993997118\n ],\n [\n -110.93279337585523,\n 44.996426283603455\n ],\n [\n -117.51050707303654,\n 44.996426283603455\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"16","issue":"9","noUsgsAuthors":false,"publicationDate":"2025-09-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Arkle, Robert S. 0000-0003-3021-1389","orcid":"https://orcid.org/0000-0003-3021-1389","contributorId":218006,"corporation":false,"usgs":true,"family":"Arkle","given":"Robert","middleInitial":"S.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":949392,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pilliod, David S. 0000-0003-4207-3518","orcid":"https://orcid.org/0000-0003-4207-3518","contributorId":216342,"corporation":false,"usgs":true,"family":"Pilliod","given":"David","middleInitial":"S.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":949393,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jeffries, Michelle I. 0000-0003-1146-1331","orcid":"https://orcid.org/0000-0003-1146-1331","contributorId":202734,"corporation":false,"usgs":true,"family":"Jeffries","given":"Michelle","middleInitial":"I.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":949394,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Welty, Justin L. 0000-0001-7829-7324 jwelty@usgs.gov","orcid":"https://orcid.org/0000-0001-7829-7324","contributorId":216345,"corporation":false,"usgs":true,"family":"Welty","given":"Justin","email":"jwelty@usgs.gov","middleInitial":"L.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":949395,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Moser, Ann","contributorId":201657,"corporation":false,"usgs":false,"family":"Moser","given":"Ann","affiliations":[{"id":36224,"text":"Idaho Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":949396,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ellsworth, Ethan A.","contributorId":201653,"corporation":false,"usgs":false,"family":"Ellsworth","given":"Ethan","email":"","middleInitial":"A.","affiliations":[{"id":7217,"text":"Bureau of Land Management","active":true,"usgs":false}],"preferred":false,"id":949397,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Major, Donald J.","contributorId":361757,"corporation":false,"usgs":false,"family":"Major","given":"Donald","middleInitial":"J.","affiliations":[{"id":7217,"text":"Bureau of Land Management","active":true,"usgs":false}],"preferred":false,"id":949398,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70272260,"text":"70272260 - 2025 - Spatial regimes provide ample early warning of tipping points","interactions":[],"lastModifiedDate":"2025-11-20T15:25:12.703711","indexId":"70272260","displayToPublicDate":"2025-09-16T08:21:56","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5217,"text":"Advances in Ecological Research","active":true,"publicationSubtype":{"id":10}},"title":"Spatial regimes provide ample early warning of tipping points","docAbstract":"

Accelerating global change is a hallmark of the Anthropocene, and the interaction of rapid change in climate, land use and land cover makes understanding the response of social-ecological systems to global change difficult to predict. Global change directly and indirectly affects both social-ecological systems and the landscapes in which they are embedded. Spatial heterogeneity in the location, manifestation of, and responses to global change makes spatially explicit approaches to management and conservation necessary. Spatial regimes, a concept derived from resilience theory, are at the forefront of attempts to operationalize and quantify resilience of dynamic landscapes. Spatial regimes are defined as dynamic landscape units that are shaped by a self-organizing set of processes and structures. They have identifiable spatial extents with discrete boundaries at a given scale that exhibit relative homogeneity in process, structure and composition maintained by feedback mechanisms. Here, we describe the concept of, evidence for, and applications of spatial regimes and how spatial regimes relate to scale and telecoupling of change across social-ecological systems. We emphasize the utility of the concept as an early warning of regime change, one that can provide ample early warning. We discuss methods that can be used to detect spatial regimes and uses of the concept for understanding and managing the spatio-temporal response of social-ecological systems to global change.

","language":"English","publisher":"Elsevier","doi":"10.1016/bs.aecr.2025.08.001","usgsCitation":"Allen, C.R., Garmestani, A., Angeler, D.G., Gunderson, L., Roberts, C.P., Sundstrom, S., Uden, D.R., and Liu, J., 2025, Spatial regimes provide ample early warning of tipping points: Advances in Ecological Research, v. 73, p. 151-167, https://doi.org/10.1016/bs.aecr.2025.08.001.","productDescription":"17 p.","startPage":"151","endPage":"167","ipdsId":"IP-179805","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":496683,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"73","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Allen, Craig R.","contributorId":362564,"corporation":false,"usgs":false,"family":"Allen","given":"Craig","middleInitial":"R.","affiliations":[{"id":86532,"text":"University of Nebraska – Lincoln","active":true,"usgs":false}],"preferred":false,"id":950596,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Garmestani, Ahjond","contributorId":362565,"corporation":false,"usgs":false,"family":"Garmestani","given":"Ahjond","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":950597,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Angeler, David G.","contributorId":362566,"corporation":false,"usgs":false,"family":"Angeler","given":"David","middleInitial":"G.","affiliations":[{"id":86532,"text":"University of Nebraska – Lincoln","active":true,"usgs":false}],"preferred":false,"id":950598,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gunderson, Lance","contributorId":362567,"corporation":false,"usgs":false,"family":"Gunderson","given":"Lance","affiliations":[{"id":40432,"text":"Emory University","active":true,"usgs":false}],"preferred":false,"id":950599,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Roberts, Caleb Powell 0000-0002-8716-0423","orcid":"https://orcid.org/0000-0002-8716-0423","contributorId":288567,"corporation":false,"usgs":true,"family":"Roberts","given":"Caleb","email":"","middleInitial":"Powell","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":950600,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sundstrom, S.M.","contributorId":362568,"corporation":false,"usgs":false,"family":"Sundstrom","given":"S.M.","affiliations":[{"id":86532,"text":"University of Nebraska – Lincoln","active":true,"usgs":false}],"preferred":false,"id":950601,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Uden, Daniel R.","contributorId":362569,"corporation":false,"usgs":false,"family":"Uden","given":"Daniel","middleInitial":"R.","affiliations":[{"id":86532,"text":"University of Nebraska – Lincoln","active":true,"usgs":false}],"preferred":false,"id":950602,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Liu, Jianguo 0000-0002-6058-5472","orcid":"https://orcid.org/0000-0002-6058-5472","contributorId":202620,"corporation":false,"usgs":false,"family":"Liu","given":"Jianguo","email":"","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":950603,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70272213,"text":"70272213 - 2025 - Sand provenance boundary in the Mu Us Sandy Land of northern China","interactions":[],"lastModifiedDate":"2025-11-19T15:16:22.762176","indexId":"70272213","displayToPublicDate":"2025-09-16T08:10:17","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1801,"text":"Geomorphology","active":true,"publicationSubtype":{"id":10}},"title":"Sand provenance boundary in the Mu Us Sandy Land of northern China","docAbstract":"

Desert dunes are often assumed to have uniform mineral compositions due to extensive mixing during lateral transport, which complicates provenance studies. The Mu Us Sandy Land in north-central China, near the East Asian summer monsoon precipitation boundary, experiences a wetter climate than most deserts. Climate wetting as a result of a warming climate, and the ‘Sand Control Project’ implemented by the Chinese government to decrease the lateral movement of sand dunes in this area provide an opportunity to study surface processes of sand production and transport. Previous studies using zircon U\"singlePb geochronology and heavy mineral composition indicate distinct sand sources for the Mu Us Sandy Land: local basement-derived middle Yellow River sediments and recycled dried-up lacustrine sediments for the eastern part, and northeastern Tibetan Plateau-derived upper Yellow River sediments for the western part. However, zircons and heavy minerals only represent trace amounts of the bulk mineralogy within a sand dune, so broader provenance analysis targeting common minerals is essential. We focus on the area near the proposed provenance difference boundary between the western and eastern Mu Us Sandy Land, using comprehensive sampling and provenance techniques to confirm distinct provenance characteristics and delineate the provenance boundary. Our findings reveal that sand from most of the Mu Us Sandy Land originated from the erosion of local basement by the middle Yellow River and recycled local dried-up lacustrine sediments, whereas the southwestern corner and the neighboring western-central Chinese Loess Plateau received sediments from the distal northeastern Tibetan Plateau.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.geomorph.2025.110005","usgsCitation":"Li, M., Nie, J., Zhang, H., Pfaff, K.I., and Zhang, Z., 2025, Sand provenance boundary in the Mu Us Sandy Land of northern China: Geomorphology, v. 490, 110005, 12 p., https://doi.org/10.1016/j.geomorph.2025.110005.","productDescription":"110005, 12 p.","ipdsId":"IP-174615","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":496631,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"China","otherGeospatial":"Mu Us Sandy Land","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 99.15372125788178,\n 42.092298158578245\n ],\n [\n 99.15372125788178,\n 37.26174832930788\n ],\n [\n 107.2705734716717,\n 37.26174832930788\n ],\n [\n 107.2705734716717,\n 42.092298158578245\n ],\n [\n 99.15372125788178,\n 42.092298158578245\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"490","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Li, Maotong 0009-0002-9753-6540","orcid":"https://orcid.org/0009-0002-9753-6540","contributorId":362427,"corporation":false,"usgs":false,"family":"Li","given":"Maotong","affiliations":[{"id":86518,"text":"Key Laboratory of Western China’s Environment Systems (Ministry of Education), College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China","active":true,"usgs":false}],"preferred":false,"id":950456,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nie, Junsheng 0000-0002-1700-7116","orcid":"https://orcid.org/0000-0002-1700-7116","contributorId":362428,"corporation":false,"usgs":false,"family":"Nie","given":"Junsheng","affiliations":[{"id":86519,"text":"School of Earth Sciences, Lanzhou University, Lanzhou 730000, China","active":true,"usgs":false}],"preferred":false,"id":950457,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zhang, Haobo 0000-0003-0086-4856","orcid":"https://orcid.org/0000-0003-0086-4856","contributorId":362429,"corporation":false,"usgs":false,"family":"Zhang","given":"Haobo","affiliations":[{"id":86519,"text":"School of Earth Sciences, Lanzhou University, Lanzhou 730000, China","active":true,"usgs":false}],"preferred":false,"id":950458,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pfaff, Katharina I. 0000-0002-6605-2722","orcid":"https://orcid.org/0000-0002-6605-2722","contributorId":362430,"corporation":false,"usgs":true,"family":"Pfaff","given":"Katharina","middleInitial":"I.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":950459,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zhang, Zengjie 0000-0001-7627-9480","orcid":"https://orcid.org/0000-0001-7627-9480","contributorId":362431,"corporation":false,"usgs":false,"family":"Zhang","given":"Zengjie","affiliations":[{"id":86521,"text":"Guangdong Provincial Key Laboratory of Geodynamics and Geohazards, School of Earth Sciences and Engineering, Sun Yat-sen University, Zhuhai, China","active":true,"usgs":false}],"preferred":false,"id":950460,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ]}