We simulate ground shaking in western Washington State from hypothetical Mw7.0–7.5 earthquakes on the southern Whidbey Island fault (SWIF). Ground motions are modeled considering kinematic source distributions on a complex fault plane, a 3D seismic velocity model, and region‐specific soil velocity models. We run simulations with varying model resolutions, including regional‐scale simulations with a maximum‐modeled frequency of ∼1 Hz and local‐scale simulations with a maximum‐modeled frequency of ∼2.5 Hz. Additional local‐scale simulations are run considering high‐resolution surface topography. We explore how source parameters (i.e., magnitude, hypocenter location, and dip direction) and 3D velocity structure impact peak shaking intensity and its variability. In particular, we find that earthquakes on the SWIF would likely produce strong shaking throughout the populated Puget Lowland, including in the cities of Everett, Seattle, Bellevue, and Tacoma, Washington. Simulated short‐period (T ≤ 2 s) spectral accelerations are strong throughout the Puget Lowland, and long‐period shaking (T ≥ 5 s) is strong in the deep regional sedimentary basins, especially the Everett and Seattle basins. Source parameters strongly influence intra‐ and interevent variability in response, primarily through changes in source and site geometry, as well as rupture directivity. We also note a potential coupling between rupture directivity and basin effects, wherein directivity pulses are seemingly guided through the region’s deep, interconnected sedimentary basins. Overall, this work highlights the impacts of 3D source, path, and site effects on seismic hazard in the U.S. Pacific Northwest and substantially expands the catalog of simulated ground motions for Puget Sound area crustal faults.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120250149","usgsCitation":"Stone, I.P., Wirth, E.A., Grant, A.R., and Frankel, A.D., 2025, High frequency and region-scale simulations of large (Mw7+) earthquakes on the southern Whidbey Island fault, Washington, USA: Bulletin of the Seismological Society of America, https://doi.org/10.1785/0120250149.","ipdsId":"IP-178598","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":497703,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1785/0120250149","text":"Publisher Index Page"},{"id":497472,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"south Whidbey Island fault","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.3911893112707,\n 48.27472068018639\n ],\n [\n -122.99866255593334,\n 47.85189851108484\n ],\n [\n -122.15172890362373,\n 47.372708828726616\n ],\n [\n -121.78371606660804,\n 48.067954942351975\n ],\n [\n -122.3911893112707,\n 48.27472068018639\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","edition":"Online First","noUsgsAuthors":false,"publicationDate":"2025-12-11","publicationStatus":"PW","contributors":{"authors":[{"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":952040,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":952041,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":952042,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":952043,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70273097,"text":"70273097 - 2025 - Offsetting the noise: A framework for applying phenological offset corrections in remotely sensed burn severity assessments","interactions":[],"lastModifiedDate":"2025-12-15T15:28:32.541172","indexId":"70273097","displayToPublicDate":"2025-12-11T09:23:58","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2083,"text":"International Journal of Wildland Fire","active":true,"publicationSubtype":{"id":10}},"title":"Offsetting the noise: A framework for applying phenological offset corrections in remotely sensed burn severity assessments","docAbstract":"Phenological correction of pre- and post-fire imagery is used to improve remotely sensed burn severity evaluations. Unburned offset values standardize greenness between image pairs; however, efficacy across diverse scenarios remains underexplored.
We evaluated the impact of phenological offset correction methods to support analyst decision-making across fire-prone environments.
We generated burn severity spectral index values for a dataset of Composite Burn Index (CBI) field plots across the conterminous US. The effectiveness of offset corrections was tested across image selection techniques, spectral indices, offset generation methods and burn perimeter sources. We assessed the influence of offset corrections on the modeled relationship with CBI, agreement between burn severity thresholds and potential bias.
Applying offset corrections consistently improved the modeled relationship with CBI by addressing extreme outlier severity values. However, automated offset corrections had the potential to introduce bias, systematically lowering severity values and reducing correspondence with observed burn severity categories.
Offset corrections offer benefits but also present trade-offs to accurately representing remotely sensed burn severity.
The utility of offset corrections depends on the environment, methods and scale of analysis. We propose a decision-tree framework for analysts to consider when employing offset corrections given their study scope.
","language":"English","publisher":"CSIRO","doi":"10.1071/WF25066","usgsCitation":"Menick, C., Vanderhoof, M.K., Picotte, J., Reiner, A.L., and Chastain, R.A., 2025, Offsetting the noise: A framework for applying phenological offset corrections in remotely sensed burn severity assessments: International Journal of Wildland Fire, v. 34, no. 12, WF25066, 20 p., https://doi.org/10.1071/WF25066.","productDescription":"WF25066, 20 p.","ipdsId":"IP-176164","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":497520,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"conterminous United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"geometry\": {\n \"type\": \"MultiPolygon\",\n \"coordinates\": [\n [\n [\n [\n -94.81758,\n 49.38905\n ],\n [\n -94.64,\n 48.84\n 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mvanderhoof@usgs.gov","orcid":"https://orcid.org/0000-0002-0101-5533","contributorId":168395,"corporation":false,"usgs":true,"family":"Vanderhoof","given":"Melanie","email":"mvanderhoof@usgs.gov","middleInitial":"K.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":952310,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Picotte, Joshua J. 0000-0002-4021-4623","orcid":"https://orcid.org/0000-0002-4021-4623","contributorId":202800,"corporation":false,"usgs":true,"family":"Picotte","given":"Joshua J.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":952311,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Reiner, Alicia L.","contributorId":364195,"corporation":false,"usgs":false,"family":"Reiner","given":"Alicia","middleInitial":"L.","affiliations":[{"id":36400,"text":"US Forest Service","active":true,"usgs":false}],"preferred":false,"id":952312,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chastain, Robert A.","contributorId":364196,"corporation":false,"usgs":false,"family":"Chastain","given":"Robert","middleInitial":"A.","affiliations":[{"id":36400,"text":"US Forest Service","active":true,"usgs":false}],"preferred":false,"id":952313,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70273089,"text":"70273089 - 2025 - Similar population dynamics before and after a chytridiomycosis outbreak in a tropical riparian amphibian species","interactions":[],"lastModifiedDate":"2025-12-15T15:09:22.284775","indexId":"70273089","displayToPublicDate":"2025-12-11T09:01:28","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":"Similar population dynamics before and after a chytridiomycosis outbreak in a tropical riparian amphibian species","docAbstract":"Emerging infectious diseases can cause rapid, widespread host mortality, and the lack of demographic data before and after pathogen emergence complicates understanding mechanisms of host persistence. This challenge is further compounded by environmental conditions that influence host behavior, while driving pathogen growth and virulence. These interactions create complex disease outcomes that hinder predictions of when and how hosts endure pathogen outbreaks. Here, we analyzed 10 years of capture-mark-recapture data (2000–2014) spanning wet and dry seasons for male Espadarana prosoblepon in El Copé, Panama, encompassing a period before (2000–2004) and after (2010–2014) a Batrachochytrium dendrobatidis (Bd) outbreak using Jolly-Seber models. We found that post-Bd male E. prosoblepon population size (range in mean population size among primary periods = 136–225 individuals) was similar to pre-Bd population size (range in mean population size among primary periods = 201–242 individuals). Pre-Bd, average monthly survival probability in the wet season was 0.93 (95% credible interval [CI] = 0.90–0.96). Post-Bd, uninfected individuals had survival probability higher in the wet season (mean = 0.97; [95% CI = 0.95–0.98]) than the dry season (mean = 0.90 [95% CI = 0.84–0.94]), while survival probability for infected individuals decreased as a function of Bd infection intensity. Pre-Bd, mean monthly per-capita entry probability was 0.07 (95% CI = 0.05–0.10), and post-Bd, mean monthly per-capita entry probability was 0.06 (95% CI = 0.00–0.10). Lastly, infection probability during the wet season was lower (mean = 0.04 [95% CI = 0.03–0.05]) than the dry season (mean = 0.10 [95% CI = 0.05–0.15]), and recovery probability during the wet season was lower (mean = 0.19 [95% CI = 0.11–0.28]) than the dry season (mean = 0.54 [95% CI = 0.20–0.88]). Our findings suggest that survival probabilities of uninfected individuals, as well as per-capita entry probabilities, are similar pre- and post-Bd, leading to a stable and similar sized pre-Bd population. These results contribute to understanding disease dynamics and tropical amphibian ecology.
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As the southernmost volcano in the Cascade Range and designated a very-high-threat volcano by the U.S. Geological Survey, the Lassen Volcanic Center (LVC) requires consistent monitoring to assess potential volcanic hazards. In 2014, the California Volcano Observatory established a gas geochemical monitoring program at LVC to provide baseline data to evaluate future changes.</p>
Results demonstrate consistent spatial patterns in bulk gas chemistry that support a two-circulation-cell hydrothermal model previously established for LVC. Gas samples from circulation cell 1 thermal areas have higher helium isotope ratios (6.59–7.50 times the air value) than those from circulation cell 2 (5.86–6.52 times the air value), indicating a stronger magmatic signature. The Sulphur Works and Pilot Pinnacle thermal areas within circulation cell 1 consistently emit gases with the highest magmatic helium contents, suggesting gas at these areas best represents conditions in the underlying volcanic system. A slight decrease in helium isotope values since 1974 may indicate progressive dilution of magmatic helium-3 (3He) by radiogenic helium-4 (4He) in the absence of recent magma intrusion. Carbon isotope compositions of carbon dioxide across all thermal areas are relatively uniform (−9.7–−7.3 per mil), falling within the range observed at other Cascade Range volcanoes. Based on gas geochemical characteristics and site accessibility, the Sulphur Works and Pilot Pinnacle thermal areas represent optimal targets for continued monitoring of the LVC magmatic-hydrothermal system. This study includes the most comprehensive helium isotope dataset collected at LVC currently available and establishes critical baseline data for future volcanic monitoring efforts.</p>
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20251056","usgsCitation":"Bergfeld, D., Lewicki, J.L., Peek, S.E., and Hunt, A.G., 2025, Gas chemistry and isotope data for volcano monitoring at the Lassen Volcanic Center, Lassen Volcanic National Park: U.S. Geological Survey Open-File Report 2025–1056, 23 p., https://doi.org/10.3133/ofr20251056.","productDescription":"Report: ix, 23 p.","numberOfPages":"23","onlineOnly":"Y","ipdsId":"IP-177202","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":497154,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20251056/full","linkFileType":{"id":5,"text":"html"},"description":"OFR 2025-1056 HTML"},{"id":497157,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9W29CON","text":"USGS data release","linkHelpText":"Chemical and isotopic compositions of gases from volcanic and geothermal areas in California"},{"id":497156,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2025/1056/images"},{"id":497155,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2025/1056/ofr20251056.XML","description":"OFR 2025-1056 XML"},{"id":497153,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2025/1056/ofr20251056.pdf","text":"Report","size":"2.58 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2025-1056 PDF"},{"id":497152,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2025/1056/coverthb2.jpg"}],"contact":"Director, Volcano Science Center
U.S. Geological Survey
1300 SE Cardinal Court Bldg. 10
Vancouver, WA 98683
Avian malaria is an existential threat to a majority of native Hawaiian forest birds. Climate change is facilitating the spread of malaria to historically disease-free areas, and despite the risk of native Hawaiian forest bird extinctions from malaria outbreaks, no comprehensive disease management plans exist for forest bird conservation areas. Hakalau Forest National Wildlife Refuge, Hawai‘i, supports a thriving bird community in a historically disease-free area that is now vulnerable to malaria incursion. Drawing on the expertise of land managers and research scientists, we developed an approach that could be used to proactively address the risk of expanding malaria into the Refuge. The plan lays out a multi-level approach that includes options for monitoring and management actions depending on defined threat levels: Vigilant, High Alert, Disease Outbreak, and Crisis levels. Initial Vigilant and High Alert levels monitor bird populations, climate conditions, and mosquito occurrence for signs of possible disease outbreaks, with higher levels shifting toward more direct management responses. While specific actions will change as new tools become available, the proactive approach can help Refuge managers better respond to changing malaria levels in the future and provide a model for managing disease here in Hawai‘i and elsewhere.
","language":"English","publisher":"Society for Conservation Biology","doi":"10.1111/csp2.70191","usgsCitation":"Paxton, E.H., Naboa, E., Agorastos, N.R., Ball, D.L., Fortini, L., Cady, T., Camp, R.J., Hart, P.J., Kaye, S., Kendall, S.J., LaPointe, D.A., Lopez, R.D., McClure, K.M., and Navine, A.K., 2025, Getting ahead of the crises: Developing an avian malaria disease management plan for Hawaiian forest birds: Conservation Science and Practice, v. 8, no. 2, e70191, 15 p., https://doi.org/10.1111/csp2.70191.","productDescription":"e70191, 15 p.","ipdsId":"IP-172770","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":502053,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/csp2.70191","text":"Publisher Index Page"},{"id":501957,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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Learning","active":true,"usgs":false}],"preferred":false,"id":952511,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Boyle, Lindsey J. 0009-0007-8825-5700","orcid":"https://orcid.org/0009-0007-8825-5700","contributorId":334493,"corporation":false,"usgs":true,"family":"Boyle","given":"Lindsey","middleInitial":"J.","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":952512,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Maloney, Kelly O. 0000-0003-2304-0745 kmaloney@usgs.gov","orcid":"https://orcid.org/0000-0003-2304-0745","contributorId":4636,"corporation":false,"usgs":true,"family":"Maloney","given":"Kelly","email":"kmaloney@usgs.gov","middleInitial":"O.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":952513,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schmid, Matthias","contributorId":236855,"corporation":false,"usgs":false,"family":"Schmid","given":"Matthias","affiliations":[{"id":47552,"text":"University of Bonn, Germany","active":true,"usgs":false}],"preferred":false,"id":952514,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70273055,"text":"70273055 - 2025 - Longer exposure to warm water increases subsequent thermal tolerance of brook trout in cold water: Acclimation timing and physiology","interactions":[],"lastModifiedDate":"2025-12-15T14:14:31.875055","indexId":"70273055","displayToPublicDate":"2025-12-10T09:34:00","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3919,"text":"Conservation Physiology","onlineIssn":"2051-1434","active":true,"publicationSubtype":{"id":10}},"title":"Longer exposure to warm water increases subsequent thermal tolerance of brook trout in cold water: Acclimation timing and physiology","docAbstract":"Climate change has resulted in increased incidence and variability of warming episodes in cold-water streams that support salmonids. The capacity to acclimate to warm temperatures may allow cold-water fish to persist in spite of changing thermal regimes, but accurately predicting fish performance under fluctuating stream temperatures also requires understanding re-acclimation to cool water, which is less well understood. We tested how thermal acclimation to warm temperatures and re-acclimation to cool water affected thermal tolerance and physiological endpoints in juvenile brook trout (Salvelinus fontinalis). We show that an initial thermal exposure (22°C, ΔT = 7°C) of 3, 7 and 14 days (but not 1 day) improved critical thermal maximum (CTmax) after a 14-day re-acclimation to cooler temperatures (15°C). Fish growth during the re-acclimation period decreased with increasing duration of initial thermal exposure (22°C). Physiological parameters associated with thermal acclimation (cortisol, glucose, haematocrit and haemoglobin) were lower at 15°C re-acclimation temperature than at the initial thermal treatment (22°C) and in some cases, lower than the 15°C control. Muscle HSP70 protein increased early (1 day) as part of the warm acclimation process and remained elevated at lower levels for up to 14 days. During re-acclimation to 15°C, HSP70 decreased relative to initial measures at 22°C. Fish exposed to the longest thermal treatment (22°C for 14 days) maintained elevated CTmax after 30 days of re-acclimation to 15°C without observed differences in the measured physiological endpoints but returned to control levels after 42 days at 15°C. This work shows that high-temperature acclimation effects in brook trout are retained for up to 30 days following re-acclimation to cool temperatures, and that isolated warming events may be expected to temporarily enhance thermal tolerance in subsequent thermal challenges.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/conphys/coaf082","usgsCitation":"Regish, A.M., O’Donnell, M., Letcher, B., Lambert, T., Hall, D.J., and McCormick, S.D., 2025, Longer exposure to warm water increases subsequent thermal tolerance of brook trout in cold water: Acclimation timing and physiology: Conservation Physiology, v. 13, no. 1, coaf082, 21 p., https://doi.org/10.1093/conphys/coaf082.","productDescription":"coaf082, 21 p.","ipdsId":"IP-176771","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":497702,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/conphys/coaf082","text":"Publisher Index Page"},{"id":497470,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","issue":"1","noUsgsAuthors":false,"publicationDate":"2025-12-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Regish, Amy M. 0000-0003-4747-4265","orcid":"https://orcid.org/0000-0003-4747-4265","contributorId":265360,"corporation":false,"usgs":true,"family":"Regish","given":"Amy","email":"","middleInitial":"M.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":952180,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"O’Donnell, Matthew 0000-0002-9089-2377 mjodonnell@usgs.gov","orcid":"https://orcid.org/0000-0002-9089-2377","contributorId":167315,"corporation":false,"usgs":true,"family":"O’Donnell","given":"Matthew","email":"mjodonnell@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":952181,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Letcher, Benjamin 0000-0003-0191-5678","orcid":"https://orcid.org/0000-0003-0191-5678","contributorId":242666,"corporation":false,"usgs":true,"family":"Letcher","given":"Benjamin","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":952182,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lambert, Timothy 0000-0002-9309-7782","orcid":"https://orcid.org/0000-0002-9309-7782","contributorId":364028,"corporation":false,"usgs":true,"family":"Lambert","given":"Timothy","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":952183,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hall, Daniel J. 0000-0003-2490-1535","orcid":"https://orcid.org/0000-0003-2490-1535","contributorId":244103,"corporation":false,"usgs":true,"family":"Hall","given":"Daniel","email":"","middleInitial":"J.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":952184,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McCormick, Stephen D. 0000-0003-0621-6200","orcid":"https://orcid.org/0000-0003-0621-6200","contributorId":364030,"corporation":false,"usgs":false,"family":"McCormick","given":"Stephen","middleInitial":"D.","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":952185,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70273989,"text":"70273989 - 2025 - Aggregating three sources of long-term trends of swallows and martins to identify priority conservation areas in the Great Lakes region","interactions":[],"lastModifiedDate":"2026-02-23T18:26:44.109374","indexId":"70273989","displayToPublicDate":"2025-12-10T09:21:40","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2163,"text":"Journal of Applied Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Aggregating three sources of long-term trends of swallows and martins to identify priority conservation areas in the Great Lakes region","docAbstract":"1. Long-term monitoring of bird populations across scales is important in evaluating conservation targets and creating effective conservation strategies. For nearly six decades, the Breeding Bird Survey (BBS) has served as the primary broad-scaled source of relative abundance trends of swallows and martins in North America. Recently, however, it has become possible to obtain breeding population trends using semi-structured eBird community science data. Moreover, weather surveil-lance radar data of swallow and martin roosting populations yield a third complementary source of trend information.
2. Using results from these three approaches, we propose a novel method of spatially combining estimates of percent change per year into a probability of directional agreement and/or disagreement that describes (1) the direction of the trend within a given region, (2) the amount of evidence associated with the estimate and (3) how much uncertainty surrounds it. We focus our efforts on an area of high Hirundinidae concentration in the North American Great Lakes region and predict trends from 2012 to 2022.
3. We found a high probability of agreement between all three sources about ob-served declines in swallow and martin trends in the region surrounding Lake Ontario and to the west of Lake Michigan. Focusing future research on these regions could improve our understanding of these declines and help build more targeted conservation initiatives.
4. Synthesis and applications. Our data integration methodology allows managers to identify regions that accumulate evidence of concerning trends across multiple wildlife monitoring schemes. These regions can thus be prioritized in conservation and management efforts. This approach can be generalized to other sources of long-term monitoring data of different species, at different stages of their annual cycle, in any geographic location.
","language":"English","publisher":"British Ecological Society","doi":"10.1111/1365-2664.70240","usgsCitation":"Belotti, M.C., Gerber, B., Zhao, W., Deng, Y., Simons, V.F., Perez, G., Kelly, J.F., Maji, S., Sheldon, D., Horton, K.G., 2025, Aggregating three sources of long-term trends of swallows and martins to identify priority conservation areas in the Great Lakes region: Journal of Applied Ecology, v. 63, no. 1, e70240, 16 p., https://doi.org/10.1111/1365-2664.70240.","productDescription":"e70240, 16 p.","ipdsId":"IP-176317","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":500445,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Great Lakes region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -94.7469287891596,\n 49.770041918152145\n ],\n [\n -91.3406258908565,\n 39.093578860754576\n ],\n [\n -86.19849947054858,\n 38.676567065124914\n ],\n [\n -76.98546258102999,\n 40.24007814743808\n ],\n [\n -75.14006120556701,\n 43.54111207792414\n ],\n [\n -76.98546258102999,\n 49.770041918152145\n ],\n [\n -94.7469287891596,\n 49.770041918152145\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"63","issue":"1","noUsgsAuthors":false,"publicationDate":"2025-12-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Belotti, Maria C.T.D.","contributorId":366510,"corporation":false,"usgs":false,"family":"Belotti","given":"Maria","middleInitial":"C.T.D.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":956010,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gerber, Brian Daniel 0000-0001-9285-9784","orcid":"https://orcid.org/0000-0001-9285-9784","contributorId":354265,"corporation":false,"usgs":true,"family":"Gerber","given":"Brian Daniel","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":956011,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zhao, Wenlong","contributorId":366511,"corporation":false,"usgs":false,"family":"Zhao","given":"Wenlong","affiliations":[{"id":34616,"text":"University of Massachusetts Amherst","active":true,"usgs":false}],"preferred":false,"id":956012,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Deng, Yuting","contributorId":366512,"corporation":false,"usgs":false,"family":"Deng","given":"Yuting","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":956013,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Simons, Victoria F.","contributorId":366513,"corporation":false,"usgs":false,"family":"Simons","given":"Victoria","middleInitial":"F.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":956014,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Perez, Gustavo","contributorId":366514,"corporation":false,"usgs":false,"family":"Perez","given":"Gustavo","affiliations":[{"id":34616,"text":"University of Massachusetts Amherst","active":true,"usgs":false}],"preferred":false,"id":956015,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kelly, Jeffrey F.","contributorId":366515,"corporation":false,"usgs":false,"family":"Kelly","given":"Jeffrey","middleInitial":"F.","affiliations":[{"id":7062,"text":"University of Oklahoma","active":true,"usgs":false}],"preferred":false,"id":956016,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Maji, Subhransu","contributorId":366516,"corporation":false,"usgs":false,"family":"Maji","given":"Subhransu","affiliations":[{"id":34616,"text":"University of Massachusetts Amherst","active":true,"usgs":false}],"preferred":false,"id":956017,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Sheldon, Daniel","contributorId":274685,"corporation":false,"usgs":false,"family":"Sheldon","given":"Daniel","email":"","affiliations":[],"preferred":false,"id":956018,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Horton, Kyle G.","contributorId":366517,"corporation":false,"usgs":false,"family":"Horton","given":"Kyle","middleInitial":"G.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":956019,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70273672,"text":"70273672 - 2025 - Viral outbreak dynamics and evolution in wildlife at the interface with humans","interactions":[],"lastModifiedDate":"2026-01-22T15:22:27.732462","indexId":"70273672","displayToPublicDate":"2025-12-10T08:15:16","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1028,"text":"Biology Letters","active":true,"publicationSubtype":{"id":10}},"title":"Viral outbreak dynamics and evolution in wildlife at the interface with humans","docAbstract":"In this study, we used a multi-faceted approach to understand patterns of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission and persistence in a wild white-tailed deer (Odocoileus virginianus) population. Serology data indicated transmission of SARS-CoV-2 and persistence during the seven-month sampling period. Traditional disease modelling based on deer-to-deer transmission indicated relatively low prevalence with an R0 of 1.9 and recovery period of 7 days; however, individual-based modelling informed by GPS tracked-movement data captured a potential transmission event. Phylogenetic analyses revealed a recurring pattern of divergent groups of deer-derived sequences with human-derived sequences falling close to each deer-derived cluster. Further, human-derived sequences were frequently sampled months prior to the deer-derived sequences, indicating repeated human to deer spillover. Using multiple types of data as well as both fine and broad scale analyses, we have characterized a pattern of localized outbreaks of SARS-CoV-2 within white-tailed deer populations that are likely recurring due to frequent spillover events. Our results suggest that while deer-to-deer transmission occurs over small spatiotemporal scales, SARS-CoV-2 persistence over longer periods and across larger regions is likely driven by repeated spillover from human populations.
","language":"English","publisher":"The Royal Society Publishing","doi":"10.1098/rsbl.2025.0540","usgsCitation":"Giglio, R.M., Westmoreland, A., Wilber, M.Q., WIlson-Henjum, G., Chan, A.N., Gardner, B., Horpiencharoen, W., Gagne, R.B., Corondi, A., Baker, A., Combs, M., Chandler, J., Manlove, K., Pepin, K.M., and Walter, W., 2025, Viral outbreak dynamics and evolution in wildlife at the interface with humans: Biology Letters, v. 21, no. 12, 20250540, 7 p., https://doi.org/10.1098/rsbl.2025.0540.","productDescription":"20250540, 7 p.","ipdsId":"IP-182184","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":498936,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1098/rsbl.2025.0540","text":"Publisher Index Page"},{"id":498836,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Pennsylvania","county":"Clearfield 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These decisions involve altering the timing and magnitude of water releases from dams and reservoirs, which can affect habitats for economically important and Federally and State-listed endangered fish species, water deliveries for agriculture or municipalities, and water quality. In this report, we describe the results of a rapid structured decision-making process used to assist management agencies in evaluating tradeoffs while gathering input from cooperating agencies, rightsholders, or interested parties (hereafter participants) through facilitated workshops in spring 2025. Consideration of alternative water management actions was initiated by the continued decline of Hypomesus transpacificus (delta smelt) populations and the issuance of a new biological opinion for the CVP and SWP long-term operations on the effects on delta smelt and other Endangered Species Act-listed species in November 2024. An Executive Order was also issued in January 2025, directing the Bureau of Reclamation to maximize water deliveries. Participants, led by the U.S. Geological Survey and cooperating agencies, identified 8 fundamental values (hereafter objectives) and 11 alternative water management scenarios (or “alternative management actions” based on the PrOACT model). Using multicriteria decision analysis, we evaluated performance (or “consequences” based on a consequence table analysis) and analyzed tradeoffs of alternative water management actions to the fundamental objectives. We ranked the alternative water management actions based on four participants’ objective weights and composite utility scores calculated using a linear value function. The three highest ranking alternative water management actions had the poorest performance for delta smelt but performed best for CVP and SWP water exports and objectives related to coldwater pool operations for salmonids. An optimum strategy that could prevent the extinction of delta smelt was not determined for this study. However, insights gained from our rapid decision analysis suggested nonflow scenarios could benefit the delta smelt population, including in drier years, and could be considered to avoid curtailment of water exports.
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U.S. Geological Survey
2255 N. Gemini Drive
Flagstaff, AZ 86001
Decisions on how to store and distribute water in California’s Central Valley are made considering the use of water resources by people, fish and wildlife, and the effects on water quality. Water is stored behind dams throughout the Central Valley for later release into rivers and canals for distribution to meet different water needs. Declining water availability and increasing human demands for water over recent decades have made these decisions increasingly difficult, especially because different uses of water resources often conflict. This report summarizes a facilitated decision-making process, led by the U.S. Geological Survey, involving water, fish, wildlife managers, and those that have an interest in how water is used (interest holders) in the Central Valley. This process provides information for water managers to consider when deciding how to distribute water resources to meet the needs for endangered Hypomesus transpacificus (delta smelt), different runs of Oncorhynchus tshawytscha (Chinook salmon), and Oncorhynchus mykiss (Central Valley steelhead), while maximizing water deliveries for human use and maintaining water quality standards.
","publicationDate":"2025-12-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Healy, Brian D. 0000-0002-4402-638X","orcid":"https://orcid.org/0000-0002-4402-638X","contributorId":304257,"corporation":false,"usgs":true,"family":"Healy","given":"Brian","middleInitial":"D.","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":951768,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Phillis, Corey C. 0000-0002-8940-3441","orcid":"https://orcid.org/0000-0002-8940-3441","contributorId":344284,"corporation":false,"usgs":false,"family":"Phillis","given":"Corey","middleInitial":"C.","affiliations":[{"id":82325,"text":"The Metropolitan Water District of Southern California","active":true,"usgs":false}],"preferred":false,"id":951769,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mahardja, Brian 0000-0003-0695-3745","orcid":"https://orcid.org/0000-0003-0695-3745","contributorId":288940,"corporation":false,"usgs":false,"family":"Mahardja","given":"Brian","affiliations":[{"id":7183,"text":"U.S. Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":951770,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Koizumi, Cameron","contributorId":363551,"corporation":false,"usgs":false,"family":"Koizumi","given":"Cameron","affiliations":[{"id":86721,"text":"US Bureau of Reclamation, Bay-Delta Office, Sacramento, California","active":true,"usgs":false}],"preferred":false,"id":951771,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pien, Catarina","contributorId":297193,"corporation":false,"usgs":false,"family":"Pien","given":"Catarina","email":"","affiliations":[{"id":37342,"text":"California Department of Water Resources","active":true,"usgs":false}],"preferred":false,"id":951772,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Parker, Nancy","contributorId":363552,"corporation":false,"usgs":false,"family":"Parker","given":"Nancy","affiliations":[{"id":86721,"text":"US Bureau of Reclamation, Bay-Delta Office, Sacramento, California","active":true,"usgs":false}],"preferred":false,"id":951773,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Conrad, J. Louise","contributorId":363553,"corporation":false,"usgs":false,"family":"Conrad","given":"J.","middleInitial":"Louise","affiliations":[{"id":86722,"text":"California Department of Water Resources, Sacramento, California","active":true,"usgs":false}],"preferred":false,"id":951774,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ekstrom, Julie","contributorId":363554,"corporation":false,"usgs":false,"family":"Ekstrom","given":"Julie","affiliations":[{"id":86722,"text":"California Department of Water Resources, Sacramento, California","active":true,"usgs":false}],"preferred":false,"id":951775,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Leimbach, Julie","contributorId":363555,"corporation":false,"usgs":false,"family":"Leimbach","given":"Julie","affiliations":[{"id":86723,"text":"Kearns & West, Sacramento, California","active":true,"usgs":false}],"preferred":false,"id":951776,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Silberblatt, Rafael","contributorId":363556,"corporation":false,"usgs":false,"family":"Silberblatt","given":"Rafael","affiliations":[{"id":86723,"text":"Kearns & West, Sacramento, California","active":true,"usgs":false}],"preferred":false,"id":951777,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Fischer, Tom","contributorId":363557,"corporation":false,"usgs":false,"family":"Fischer","given":"Tom","affiliations":[{"id":86723,"text":"Kearns & West, Sacramento, California","active":true,"usgs":false}],"preferred":false,"id":951778,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Ehlo, Chase","contributorId":145448,"corporation":false,"usgs":false,"family":"Ehlo","given":"Chase","affiliations":[],"preferred":false,"id":951779,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70272019,"text":"gip263 - 2025 - USGS—An Unparalleled Scientific Asset","interactions":[],"lastModifiedDate":"2026-03-05T18:22:22.613234","indexId":"gip263","displayToPublicDate":"2025-12-09T16:10:00","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":315,"text":"General Information Product","code":"GIP","onlineIssn":"2332-354X","printIssn":"2332-3531","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"263","displayTitle":"USGS: An Unparalleled Scientific Asset","title":"USGS—An Unparalleled Scientific Asset","docAbstract":"The U.S. Geological Survey (USGS) delivers information critical to powering our economy, managing our natural resources, and keeping Americans safe and healthy.1
$21B
Geologic maps save users an estimated 15% in annual costs: a value of between $14B and $21B.
$25.6B
in annual value to users of imagery from Landsat satellites, which were codeveloped by NASA and the USGS and operated through their lifespans by the USGS.
$13.5B
in annual benefits is generated by the USGS's 3D Elevation Program.
44%
USGS-identified undiscovered geothermal energy is equal to 44% of current U.S. electricity generation.
29.4B
barrels of oil and 391.6 trillion cubic feet of gas in recoverable resources are available on U.S. public lands based on USGS assessments.
$424B
in recent wildland fire damages highlight the need for USGS fire science, which supports efforts to protect communities and reduce risk.
USGS earthquake, volcano, landslide, and coastal hazard monitoring and information save lives and minimize costs; for example, $2.8M can be saved because of USGS enhanced information about a Mauna Loa eruption.
$4.5B
is the estimated cost of annual flooding. Through a network of over 11,885 streamgages, the USGS supports public safety and enables forecasts, early warning systems, and management actions that protect lives and property.
$3.1B
The USGS identified a $3.1B risk to the American economy if China restricts gallium imports. This is one example underscoring the importance of the USGS mapping critical minerals, investigating supply chains, and producing the Nation’s critical minerals list.
$21B
in estimated annual costs results from invasive species. The USGS’s invasive species research informs approaches used to reduce their effects on agriculture, water infrastructure, disease transmission, fisheries, and outdoor recreation.
USGS innovations support early warnings for harmful algal blooms—over $2M in yearly benefits are provided to Kansas alone.
$45B
USGS science informs the management of big game (such as deer and elk). The big-game hunting industry contributes $45B to the U.S. economy.
$4.1T
Mineral commodities are necessary for the $4.1T in value added to the GDP by major industries that consume processed mineral materials and employ 1 million workers. Because of this, USGS data on mineral supply, demand, and trade are highly valued.
45,000 metric tons
Rare earths power the growing technology economy, including cell phones, electric vehicles, and medical devices. For over 70 years, USGS work has supported the discovery of rare earth resources in California’s Mountain Pass area, which produced 45,000 metric tons of rare earth concentrates in 2024—over 11% of the global supply.
$70.2B
USGS science informs early warning systems and management strategies to mitigate disease outbreaks in agriculture—critical research on highly pathogenic avian influenza, for example, helps safeguard the $70B value in poultry and egg production.
$11.8B
USGS groundwater tools are vital for agriculture; for example, in the Mississippi Alluvial Plain, 65% of farming relies on groundwater to support its $11.8B annual industry.
1Values throughout are given in billions (B), millions (M), and trillions (T) of U.S. dollars. GDP is “Gross Domestic Product.” Percentages are shown as %.
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Understanding predator–prey relationships is fundamental to our knowledge of the stability and resilience of ecological systems. These dynamics are shaped by both ecological factors, like interaction strength, and anthropogenic factors, like harvest intensity, which can have large-scale implications for community structure. However, few studies have focused on the combined impact of these effects and their contribution to phenomena like prey release within two-species frameworks. In this study, we investigate the interactive impact of interaction strength and harvest pressure on two trophic levels in a predator–prey system using a mathematical modeling approach. Our results reveal that interaction strength plays a crucial role in shaping population dynamics, with high interaction strength leading to a predator-dominated system and low interaction strength enabling coexistence between species. The addition of predator harvest into the system reveals complex and counterintuitive behavior not seen in unharvested systems, likely due to the destabilizing impacts of harvest at some interaction strengths. Specifically, the inclusion of harvest on the predator can induce a range of behaviors, such as prey release and predator decline, that alter the equilibrium abundance of both predator and prey populations. Interestingly, predator–prey systems with intermediate to high interaction strengths achieve maximum total abundance with low harvest levels rather than in scenarios with no harvest pressure, as prey populations benefit greatly from reduced predation mortality associated with predator harvest. We gain insights into the complex interplay between predator–prey interactions and human activities in shaping community composition and abundances across trophic levels. This study provides potential mechanisms that may explain the observed variation in numerical prey release in trophically complex systems in which predators and prey are both extracted, like coral reef fisheries. Results highlight the need for resource management to consider the wide range of factors that shape ecosystem dynamics to develop effective strategies that safeguard the long-term health of complex ecosystems and the human communities that they support.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.70449","usgsCitation":"Rahnke, S.A., Winter. Kawika B., Raz, L., McManus, L.C., 2025, Interaction strength and harvest intensity mediate predator–prey dynamics on coral reefs: Ecosphere, v. 16, no. 12, e70449, 15 p., https://doi.org/10.1002/ecs2.70449.","productDescription":"e70449, 15 p.","ipdsId":"IP-168169","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":500593,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.70449","text":"Publisher Index Page"},{"id":500430,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"16","issue":"12","noUsgsAuthors":false,"publicationDate":"2025-12-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Rahnke, Sophia A.","contributorId":366825,"corporation":false,"usgs":false,"family":"Rahnke","given":"Sophia","middleInitial":"A.","affiliations":[{"id":64253,"text":"University of Hawaiʻi at Mānoa","active":true,"usgs":false}],"preferred":false,"id":956278,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Winter. Kawika B.","contributorId":366826,"corporation":false,"usgs":false,"family":"Winter. Kawika B.","affiliations":[{"id":64253,"text":"University of Hawaiʻi at Mānoa","active":true,"usgs":false}],"preferred":false,"id":956279,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Raz, Lillian Joy Tuttle 0000-0002-5009-8080","orcid":"https://orcid.org/0000-0002-5009-8080","contributorId":354940,"corporation":false,"usgs":true,"family":"Raz","given":"Lillian Joy Tuttle","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":956280,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McManus, Lisa C.","contributorId":366827,"corporation":false,"usgs":false,"family":"McManus","given":"Lisa","middleInitial":"C.","affiliations":[{"id":64253,"text":"University of Hawaiʻi at Mānoa","active":true,"usgs":false}],"preferred":false,"id":956281,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70273281,"text":"70273281 - 2025 - Spatial connections between the timing of hydroclimatic extremes","interactions":[],"lastModifiedDate":"2025-12-30T17:01:25.636767","indexId":"70273281","displayToPublicDate":"2025-12-09T10:59:12","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":17124,"text":"Nature Water","active":true,"publicationSubtype":{"id":10}},"title":"Spatial connections between the timing of hydroclimatic extremes","docAbstract":"No abstract available.
","language":"English","publisher":"Nature","doi":"10.1038/s44221-025-00536-2","usgsCitation":"Archfield, S., 2025, Spatial connections between the timing of hydroclimatic extremes: Nature Water, v. 3, p. 1352-1353, https://doi.org/10.1038/s44221-025-00536-2.","productDescription":"2 p.","startPage":"1352","endPage":"1353","ipdsId":"IP-182869","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":498157,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"3","noUsgsAuthors":false,"publicationDate":"2025-12-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Archfield, Stacey 0000-0002-9011-3871 sarch@usgs.gov","orcid":"https://orcid.org/0000-0002-9011-3871","contributorId":214835,"corporation":false,"usgs":true,"family":"Archfield","given":"Stacey","email":"sarch@usgs.gov","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":953017,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70272813,"text":"70272813 - 2025 - Memory and jamming in fault zone sediments","interactions":[],"lastModifiedDate":"2025-12-10T16:13:50.433265","indexId":"70272813","displayToPublicDate":"2025-12-09T10:07:15","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":8956,"text":"Communications Earth & Environment","active":true,"publicationSubtype":{"id":10}},"title":"Memory and jamming in fault zone sediments","docAbstract":"Many subsurface processes involve transitions in granular material states, from arrested to creeping to flowing. Experiments and frameworks for idealized systems reveal that granular fabrics develop during shearing, co-evolve with applied stress, and govern such transitions. We use microtomography to test whether fabrics at two San Andreas fault sites reflect slip history and whether idealized frameworks extend to nature. Near-surface sediments within the fault zone transition between deformation patterns over the seismic cycle, including bulk/localized grain re-arrangements, individual grain fracturing, and localized zones of fracturing. Aseismic and co-seismic shearing produce distinct preferred grain orientations. Co-seismic fabrics can be preserved after centuries of aseismic strain, aseismic fabrics may be overprinted, and grain size and coordination number influence the fabrics. Idealized frameworks, namely anisotropic critical state theory, frictional jamming, and material memory, can explain our observations, and fault zone sediments likely undergo cycles of memory creation and erasure that influence rigidity spatiotemporally.
","language":"English","publisher":"Nature","doi":"10.1038/s43247-025-02952-4","usgsCitation":"Dasent, J., Wright, V., Scharer, K., Manga, M., and Kilburn, R., 2025, Memory and jamming in fault zone sediments: Communications Earth & Environment, v. 6, 998, 10 p., https://doi.org/10.1038/s43247-025-02952-4.","productDescription":"998, 10 p.","ipdsId":"IP-182362","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":497375,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s43247-025-02952-4","text":"Publisher Index Page"},{"id":497303,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Pallett Creek site","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.87041303515583,\n 34.45802677473017\n ],\n [\n -117.90497693113608,\n 34.45802677473017\n ],\n [\n -117.90497693113608,\n 34.43566682109183\n ],\n [\n -117.87041303515583,\n 34.43566682109183\n ],\n [\n -117.87041303515583,\n 34.45802677473017\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"6","noUsgsAuthors":false,"publicationDate":"2025-12-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Dasent, Jhardel","contributorId":363593,"corporation":false,"usgs":false,"family":"Dasent","given":"Jhardel","affiliations":[{"id":37799,"text":"SCRIPPS","active":true,"usgs":false}],"preferred":false,"id":951866,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wright, Vashan","contributorId":363595,"corporation":false,"usgs":false,"family":"Wright","given":"Vashan","affiliations":[],"preferred":false,"id":951867,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Scharer, Katherine M. 0000-0003-2811-2496","orcid":"https://orcid.org/0000-0003-2811-2496","contributorId":217361,"corporation":false,"usgs":true,"family":"Scharer","given":"Katherine M.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":951868,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Manga, Michael","contributorId":199572,"corporation":false,"usgs":false,"family":"Manga","given":"Michael","affiliations":[],"preferred":false,"id":951869,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kilburn, Richard","contributorId":363597,"corporation":false,"usgs":false,"family":"Kilburn","given":"Richard","affiliations":[{"id":37799,"text":"SCRIPPS","active":true,"usgs":false}],"preferred":false,"id":951870,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70272699,"text":"sir20255086 - 2025 - Conceptual and numerical groundwater flow model of the Iowa River alluvial aquifer near Tama County, Iowa, 1980 through 2022","interactions":[],"lastModifiedDate":"2026-02-03T16:48:21.047788","indexId":"sir20255086","displayToPublicDate":"2025-12-08T13:13:22","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":"2025-5086","displayTitle":"Conceptual and Numerical Groundwater Flow Model of the Iowa River Alluvial Aquifer near Tama County, Iowa, 1980 through 2022","title":"Conceptual and numerical groundwater flow model of the Iowa River alluvial aquifer near Tama County, Iowa, 1980 through 2022","docAbstract":"The Iowa River alluvial aquifer is an important source of water on the Meskwaki Settlement in Tama County, Iowa, which is land owned by the Sac & Fox Tribe of the Mississippi in Iowa (commonly known as the Meskwaki Nation). The U.S. Geological Survey constructed a groundwater flow model, including a conceptual and numerical model, of the Iowa River alluvial aquifer and underlying hydrogeologic units near the Meskwaki Settlement in Tama County, Iowa, for the period of January 1980–August 2022 to estimate the fraction of water pumped from the Iowa River alluvial aquifer by Meskwaki Settlement wells that is derived from streamflow depletion in the Iowa River and its tributaries. Streamflow depletion is a reduction in streamflow caused by groundwater pumping and includes the interception by groundwater production wells of water that otherwise would have been discharged to streams (called “captured groundwater discharge”) and induced infiltration of streamflow to the production wells. Calibrated model runs were performed with no simulated pumping and simulated pumping only at Meskwaki Settlement wells, and the change in simulated flow rates between the groundwater system and streams for the two model runs represents the amount of streamflow depletion in the Iowa River and tributary streams resulting from pumping at the Meskwaki Settlement wells. Streamflow depletion in the Iowa River and its tributaries as a percentage of simulated pumping at the Meskwaki Settlement wells was calculated by dividing this difference by the total simulated pumping rate for the Meskwaki Settlement wells. The model results demonstrate that the mean monthly streamflow depletion, including induced infiltration and captured discharge, in the Iowa River and its tributary streams as a percentage of mean monthly pumping at the Meskwaki Settlement wells was 97.4 percent and ranged from 65.4 to 112 percent. Of the total streamflow depletion, mean monthly induced recharge was 20.9 percent and ranged from 4.9 to 37.2 percent. Mean monthly captured discharge was 76.5 percent and ranged from 57.1 to 97.1 percent. These results indicate that most of the water pumped from the Meskwaki Settlement wells is the result of streamflow depletion, in the form of both induced infiltration and captured discharge.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255086","collaboration":"Prepared in cooperation with the Sac & Fox Tribe of the Mississippi in Iowa","usgsCitation":"Goldstein, K.M.F., and Davis, K.W., 2025, Conceptual and numerical groundwater flow model of the Iowa River alluvial aquifer near Tama County, Iowa, 1980 through 2022: U.S. Geological Survey Scientific Investigations Report 2025–5086, 55 p., https://doi.org/10.3133/sir20255086.","productDescription":"Report: viii, 55 p.; Data Release; Dataset","numberOfPages":"68","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-154245","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":497068,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5086/coverthb.jpg"},{"id":497069,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5086/sir20255086.pdf","text":"Report","size":"20.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5086"},{"id":497070,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5086/sir20255086.XML"},{"id":497071,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5086/images/"},{"id":497074,"rank":7,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"- USGS water data for the Nation"},{"id":497073,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1CPXXGM","text":"USGS data release","linkHelpText":"MODFLOW 6 groundwater flow model for the Iowa River alluvial aquifer near Tama, Iowa, 1980 through 2022"},{"id":497072,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255086/full"},{"id":497812,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_119054.htm"}],"country":"United States","state":"Iowa","county":"Tama County","otherGeospatial":"Iowa River alluvial aquifer","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -92.86911713753273,\n 42.130588756475845\n ],\n [\n -92.86911713753273,\n 41.830673568326176\n ],\n [\n -92.25633472266213,\n 41.830673568326176\n ],\n [\n -92.25633472266213,\n 42.130588756475845\n ],\n [\n -92.86911713753273,\n 42.130588756475845\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
400 South Clinton Street, Suite 269
Iowa City, IA 52240
Miami-Dade County is part of a densely populated urban corridor in southeastern Florida. The Biscayne aquifer serves as Miami-Dade County’s primary drinking water source and is characterized by highly permeable karstic limestone and carbonate sand. The aquifer’s coastal location and permeable nature make it susceptible to saltwater intrusion. Monitoring the current inland extent and the rate of movement of the saltwater front in the aquifer can inform management strategies for conserving the long-term sustainability of the county’s water supply. In the 1950s, the U.S. Geological Survey published a map of the inland extent of saltwater intrusion in the Biscayne aquifer and has continued to update this map to monitor changes over time, with the most recent update published in 2018. An updated map has been created showing the approximate inland extent of saltwater intrusion in the Biscayne aquifer in eastern Miami-Dade County in 2022, with the 2018 extent shown for comparison. The inland extent of saltwater intrusion was mapped through the interpretation of borehole electromagnetic induction logs and measurements of chloride and specific conductance in groundwater samples. The location of the saltwater interface at the base of the Biscayne aquifer was represented by the 1,000-milligram-per-liter isochlor. This report describes changes in the location of the saltwater interface from 2018 to 2022. By 2022, the saltwater interface had moved farther inland in both the northern and southern parts of the county, advancing by as much as 0.3 kilometer in the north and up to 0.8 kilometer in the Model Land Area to the south. However, it remained relatively unchanged from its 2018 position in the east-central part of the county.
Director, Caribbean-Florida Water Science Center
U.S. Geological Survey
7595 SW 33d St.
Davie, FL 33314
Contact Us- USGS Publications Warehouse
","tableOfContents":"The U.S. Geological Survey is developing nationally consistent water-use modeling approaches to replace previous methods relying on locally specific reported and estimated data. These national assessments require datasets that incorporate water withdrawal variability across the United States and over long periods. However, source data often have unclear definitions, missing or varied units, differing temporal resolutions, varied data quality, and inconsistent formats, which hinder automation and require individualized processing. The public-supply datasets described in this paper were used in machine learning models to estimate annual and monthly public-supply water use for 2000–2020 for the conterminous United States (CONUS) and in a model to estimate public-supply deliveries. Public-supply withdrawal data were acquired for the CONUS and the District of Columbia; however, 11 states had annual data for only 1 year, and 10 states had no monthly data. Annual withdrawal data were acquired for 81% of public-supply water service areas, and monthly withdrawal data were acquired for 47% for at least 1 year from 2000 to 2020. These datasets and methods provide the most comprehensive collection of reported public-supply withdrawals to date and can be used by water-use managers, the scientific community, and the broader public. The extensive data processing described herein can be applicable to datasets representing other categories of water use.
","language":"English","publisher":"Wiley","doi":"10.1111/1752-1688.70054","usgsCitation":"Luukkonen, C.L., Alzraiee, A.H., Herbert, D.M., Niswonger, R.G., Larsen, J., Buchwald, C.A., Houston, N., Dieter, C., Miller, L.D., and Stewart, J.S., 2025, Harmonization of a water withdrawal dataset for the conterminous United States: JAWRA Journal of the American Water Resources Association, v. 61, no. 6, e70054, 13 p., https://doi.org/10.1111/1752-1688.70054.","productDescription":"e70054, 13 p.","ipdsId":"IP-157002","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":498676,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1752-1688.70054","text":"Publisher Index Page"},{"id":498511,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"conterminous United States","geographicExtents":"{\n 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,{"id":70273138,"text":"70273138 - 2025 - Rice cultivation supports growth and survival of a threatened semi-aquatic reptile","interactions":[],"lastModifiedDate":"2025-12-16T16:18:00.57795","indexId":"70273138","displayToPublicDate":"2025-12-08T10:06:54","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Rice cultivation supports growth and survival of a threatened semi-aquatic reptile","docAbstract":"Integration of agroecosystems and other working landscapes with protected lands and waters is critical to the conservation of Earth's biodiversity. Rice agroecosystems support many species by providing aquatic habitat where natural wetlands have been altered or drained. In regions with long dry seasons, rice fields and associated irrigation canals provide essential habitat for wetland-dependent species. We quantified the spatial scale and magnitude of the effect of rice growing on the growth and survival of the giant gartersnake (Thamnophis gigas), a threatened species that persists primarily in areas of rice agriculture in the Central Valley of California, USA. We used structural causal models to identify drought condition as a key confounder to adjust for when estimating the total effect of rice growing on demographic rates. We analyzed capture-mark-recapture data from 19 populations of giant gartersnakes with an integrated growth–survival model and used distance-weighted covariates to account for the decline in influence of rice with increasing distance from our study sites. We found strong support for a positive effect of rice grown within 1.9 km of a canal on giant gartersnake growth. There was also support for a positive effect of rice on giant gartersnake survival, although the spatial scale extended out to 5 km or more. Our results demonstrate how active rice growing benefits giant gartersnakes inhabiting irrigation canals and demonstrate an approach for studying landscape effects on wildlife in agroecosystems.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.70139","usgsCitation":"Rose, J.P., Nguyen, A.M., Jordan, A., Macias, D., Schoenig, E.J., Napolitano, G., Kim, R., Ersan, J.S., Fulton, A.M., and Halstead, B., 2025, Rice cultivation supports growth and survival of a threatened semi-aquatic reptile: Ecological Applications, v. 35, no. 8, e70139, 15 p., https://doi.org/10.1002/eap.70139.","productDescription":"e70139, 15 p.","ipdsId":"IP-172102","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":497730,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/eap.70139","text":"Publisher Index Page"},{"id":497649,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1JHAWVT","text":"USGS data release","linkHelpText":"Growth and Capture Mark Recapture Data from Giant Gartersnakes (Thamnophis gigas) in Rice Irrigation Canals 2018 to 2023 (ver. 2.0, July 2025)"},{"id":497576,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.17302271960432,\n 39.79287563400288\n ],\n [\n -122.17302271960432,\n 38.80561121822487\n ],\n [\n -121.10358373344488,\n 38.80561121822487\n ],\n [\n -121.10358373344488,\n 39.79287563400288\n ],\n [\n -122.17302271960432,\n 39.79287563400288\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"35","issue":"8","noUsgsAuthors":false,"publicationDate":"2025-12-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Rose, Jonathan P. 0000-0003-0874-9166 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S.M.","contributorId":364269,"corporation":false,"usgs":false,"family":"Ersan","given":"Julia","middleInitial":"S.M.","affiliations":[{"id":37814,"text":"Former USGS","active":true,"usgs":false}],"preferred":false,"id":952425,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Fulton, Alexandria M.","contributorId":364271,"corporation":false,"usgs":false,"family":"Fulton","given":"Alexandria","middleInitial":"M.","affiliations":[{"id":86778,"text":"Fish Program WADFW (former USGS)","active":true,"usgs":false}],"preferred":false,"id":952426,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Halstead, Brian J. 0000-0002-5535-6528 bhalstead@usgs.gov","orcid":"https://orcid.org/0000-0002-5535-6528","contributorId":215986,"corporation":false,"usgs":true,"family":"Halstead","given":"Brian","email":"bhalstead@usgs.gov","middleInitial":"J.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":952427,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70273028,"text":"70273028 - 2025 - Seasonal movements of nonnative White Catfish in the Penobscot River estuary","interactions":[],"lastModifiedDate":"2026-01-22T16:41:17.477908","indexId":"70273028","displayToPublicDate":"2025-12-08T10:04:34","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Seasonal movements of nonnative White Catfish in the Penobscot River estuary","docAbstract":"White Catfish Ameiurus catus has been introduced to coastal watersheds across the United States. In the Penobscot River, Maine, this species has become increasingly common in upstream habitats that have been made accessible by recent dam removals. We characterized the movements of White Catfish to understand the temporal variation in their movement patterns and contextualize these findings within the recent changes in watershed connectivity.
We captured and tagged 10 adult White Catfish (mean fork length = 271 mm) with acoustic transmitters in the lower Penobscot River in July 2022. The movements of the tagged fish were monitored through April 2023 with a large network of stationary receivers.
The tagged catfish were detected up to 6 km upstream and 31 km downstream from the release site. The total distance that was traveled by individuals ranged from 0 to 154 km during the study. Fall and spring movements were associated with changes in river flow and water temperature, but fish were relatively stationary from December through March, when at least five individuals were assumed to have overwintered in lower river tributaries.
Our results show that individual White Catfish may move considerable distances within large river systems and that these movements are potentially facilitated by changing river conditions. Collectively, this study fills a long-standing knowledge gap about the movement ecology of this species, adds context to help explain a recent increase in observations within their introduced range, and shows how changes in river conditions may be used to predict when and where these fish will move within a tidal system.
Sediment bulk density (ρ-dry) and particle size are two important parameters for predicting sediment bed erosion. ρ-dry, however, is difficult to measure accurately. The units of ρdry have not been consistently reported in the literature, leading to confusion, particularly in the calculation of sediment budgets that typically require integrating mass-based and volumetric components. Relationships between ρdry and sediment composition have been developed for multiple regions and differ between systems. Developing a system-specific predictive model for ρdry can help fill data gaps and improve sediment budgets, model accuracy, and estimates of quantities of sediment needed for restoration. In this study, we investigate whether ρdry in San Francisco Estuary can be predicted from organic carbon content or percent of fines, which are more easily or frequently measured than ρdry. We compiled sediment properties from samples collected over the past decade throughout the intertidal and subtidal regions of San Francisco Bay and the Sacramento–San Joaquin Delta to examine this relationship. Sample composition ranged from 2.18 to 99.97% fines (particles < 0.0625 mm), ρ-dry ranged from 0.22 to 1.60 g cm-3, and organic carbon ranged from 0.06 to 7.98%. Regression analysis indicates that the percent of fines explains 93% of the variation of ρ-dry (p-value < 0.05, N = 81). The coefficient of determination decreased by ~1% when organic carbon was incorporated in the regression analysis. Comparison of this predictive ρ-dry model to four published models based on samples from other regions supports previous findings that the relationship between ρdry and grain size may vary by system. We also examined additional factors that may affect sediment erodibility, such as hydrographic and oceanographic conditions. Classification of sample sites as intertidal vs. subtidal or wavy vs. non-wavy each significantly explained the residuals from the ρdry model, and both intertidal and wavy conditions were associated with higher ρ-dry values.
","language":"English","publisher":"University of California Davis","doi":"10.15447/sfews.2025v23iss4art6","usgsCitation":"McGill, S., and Lacy, J.R., 2025, Predicting sediment bulk density for San Francisco Estuary: San Francisco Estuary and Watershed Science, v. 23, no. 4, 6, 21 p., https://doi.org/10.15447/sfews.2025v23iss4art6.","productDescription":"6, 21 p.","ipdsId":"IP-177286","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":498039,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.15447/sfews.2025v23iss4art6","text":"Publisher Index Page"},{"id":497767,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Estuary","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.5,\n 38.4\n ],\n [\n -122.8,\n 38.4\n ],\n [\n -122.8,\n 37.4\n ],\n [\n -121.5,\n 37.4\n ],\n [\n -121.5,\n 38.4\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"23","issue":"4","noUsgsAuthors":false,"publicationDate":"2025-12-08","publicationStatus":"PW","contributors":{"authors":[{"text":"McGill, Samantha C. 0000-0001-9320-8764","orcid":"https://orcid.org/0000-0001-9320-8764","contributorId":304095,"corporation":false,"usgs":true,"family":"McGill","given":"Samantha C.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":952710,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lacy, Jessica R. 0000-0002-2797-6172","orcid":"https://orcid.org/0000-0002-2797-6172","contributorId":201703,"corporation":false,"usgs":true,"family":"Lacy","given":"Jessica","email":"","middleInitial":"R.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":952711,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70273298,"text":"70273298 - 2025 - Causal analysis of fire regime drivers in California","interactions":[],"lastModifiedDate":"2026-01-05T14:54:53.160898","indexId":"70273298","displayToPublicDate":"2025-12-08T08:51:10","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2083,"text":"International Journal of Wildland Fire","active":true,"publicationSubtype":{"id":10}},"title":"Causal analysis of fire regime drivers in California","docAbstract":"Understanding the relative contribution of climate and human factors to wildfires is critical for managing risk across California’s diverse ecosystems, in the United States (US).
We propose a model that distinguishes between proximate and ultimate drivers of fire regimes and apply it to a century of fire and climate data to assess regional variation in causal mechanisms.
We analyzed fire statistics (1910–2021) alongside climate and weather data, stratifying the state by 10 ecoregions.
Northern forests had the strongest correlation with the proximate factor fuel aridity, ultimately due to climate. Fire rotation intervals exceeded 100 years, implicating woody fuel accumulation as an additional factor. Lightning ignitions occurred in decadal bursts, with dense strike events potentially overwhelming fire-fighting resources. Lower elevation/latitude foothill ecoregions experienced highest fire activity following wet winters and springs, implicating control by herbaceous fuel loads and a negative effect of global warming on future fires. Human ignitions dominate in these ecoregions, and population growth contributes to expansion of powerlines, a major ignition source.
While climate change may increase fire activity in forested ecoregions, its role is less pronounced in non-forested ecoregions, where human ignition sources are the dominant factor.
Different areas within ecoregions may require different management actions that reflect the specific proximate and ultimate factors at play.
","language":"English","publisher":"CSIRO","doi":"10.1071/WF25166","usgsCitation":"Keeley, J., and Syphard, A.D., 2025, Causal analysis of fire regime drivers in California: International Journal of Wildland Fire, v. 34, no. 12, WF25166, 27 p., https://doi.org/10.1071/WF25166.","productDescription":"WF25166, 27 p.","ipdsId":"IP-166632","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":498315,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"34","issue":"12","noUsgsAuthors":false,"publicationDate":"2025-10-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Keeley, Jon 0000-0002-4564-6521","orcid":"https://orcid.org/0000-0002-4564-6521","contributorId":216485,"corporation":false,"usgs":true,"family":"Keeley","given":"Jon","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":953272,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Syphard, Alexandra D.","contributorId":364829,"corporation":false,"usgs":false,"family":"Syphard","given":"Alexandra","middleInitial":"D.","affiliations":[{"id":38279,"text":"Conservation Biology Institute","active":true,"usgs":false}],"preferred":false,"id":953273,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70272700,"text":"sir20255091 - 2025 - Geochemical and hydrological investigations of historical data collected at the Lee Acres Landfill and Giant Bloomfield Refinery, New Mexico, 1985–2020","interactions":[],"lastModifiedDate":"2026-02-03T16:46:09.780586","indexId":"sir20255091","displayToPublicDate":"2025-12-08T06:36:04","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":"2025-5091","displayTitle":"Geochemical and Hydrological Investigations of Historical Data Collected at the Lee Acres Landfill and Giant Bloomfield Refinery, New Mexico, 1985–2020","title":"Geochemical and hydrological investigations of historical data collected at the Lee Acres Landfill and Giant Bloomfield Refinery, New Mexico, 1985–2020","docAbstract":"The Lee Acres Landfill and Giant Bloomfield Refinery are adjacent properties near the City of Farmington, New Mexico, each having undergone monitoring and remediation related to historical site activities. At the landfill, site cleanup has included the installation of a capillary barrier over former liquid waste lagoons and periodic monitoring of groundwater elevations and groundwater quality. At the refinery, remediation has focused on several petrochemical and crude oil release areas and included soil excavation, groundwater treatment, and regular monitoring of groundwater elevations and quality. Groundwater at both sites has higher concentrations of volatile organic compounds and trace metals than background aquifer concentrations. In 2022, the U.S. Geological Survey compiled the Lee Acres-Giant Bloomfield Refinery Database (LAGBRD), which contains publicly available groundwater-elevation data and organic and inorganic groundwater-quality data from both sites, spanning from 1985 to 2020. Data from the LAGBRD and precipitation data from other sources were used to better understand the cause of relatively high manganese concentrations observed in some groundwater wells at the site through comparison of groundwater chemistry to chemical end members, interpretation of spatial and temporal patterns in the groundwater chemistry, and interpretation of groundwater flow properties. In this study, elevated chloride concentrations in groundwater downgradient from the landfill have been attributed to landfill leachate based on the temporal and spatial variability of chloride concentrations and chloride-to-bromide ratios. Installation of a capillary barrier and surface-water runoff controls at the landfill in 2005 appears to have altered infiltration patterns at that site, resulting in a decrease in chloride at some wells but an increase in chloride and dissolved manganese at others. The timing and relation among groundwater elevation, chloride concentration, and manganese concentration suggest that leachate stored in the vadose zone provides a continued source of contamination to groundwater.
Director, New Mexico Water Science Center
U.S. Geological Survey
6700 Edith Blvd. NE
Albuquerque, NM 87113
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