We present the modeling results of the thermal lightcurve of asteroid (3) Juno at the wavelength of λ = 1.3 mm measured by the Atacama Large Millimeter-submillimeter Array. A thermophysical model together with a radiative transfer model suggests a thermal inertia of 13 ± 10 [J m−2 K−1 s−0.5], an equivalent emissivity of 0.8 ± 0.1, a loss tangent of 0.4 ± 0.3, and an index of refraction 1.8 ± 0.3. Based on previous laboratory measurements, the modeled index of refraction suggests a regolith porosity of about 45%. However, thermal inertia models using the material parameters of ordinary chondrite indicate a grain size of ∼10 μm and require a high porosity of ∼90% to explain the low thermal inertia. In order to explain such a contradiction, we postulate that some repulsive mechanism might be in effect to reduce the contact of grains and therefore the thermal inertia. The loss tangent of Juno’s regolith corrected for the modeled thermal skin depth is in the order of 0.5, much higher than that of the lunar regolith and indicating an electrical skin depth of L = 0.1–1.4 mm that is within the thermal skin depth. The shape of the rotational lightcurve of Juno in the millimeter wavelengths is dominated by its irregular shape, but rotational variations in the thermal and/or dielectric properties cannot be ruled out. Our results demonstrate that millimeter-wavelength observations of asteroids provide an extra dimension of constraints to the porosity and grain size of asteroid regolith compared to the thermal infrared observations.
","language":"English","publisher":"IOP Science","doi":"10.3847/PSJ/ae468f","usgsCitation":"Li, J., Titus, T.N., Moullet, A., and Hsieh, H.H., 2026, Thermal and dielectric properties of Juno’s regolith at one millimeter wavelength: Planetary Science Journal, v. 7, no. 3, 71, 12 p., https://doi.org/10.3847/PSJ/ae468f.","productDescription":"71, 12 p.","ipdsId":"IP-156204","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":503447,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3847/psj/ae468f","text":"Publisher Index Page"},{"id":503339,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"asteroid (3) Juno","volume":"7","issue":"3","noUsgsAuthors":false,"publicationDate":"2026-03-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Li, J-Y","contributorId":370357,"corporation":false,"usgs":false,"family":"Li","given":"J-Y","affiliations":[{"id":24584,"text":"PSI","active":true,"usgs":false}],"preferred":false,"id":960196,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Titus, Timothy N. 0000-0003-0700-4875 ttitus@usgs.gov","orcid":"https://orcid.org/0000-0003-0700-4875","contributorId":146,"corporation":false,"usgs":true,"family":"Titus","given":"Timothy","email":"ttitus@usgs.gov","middleInitial":"N.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":960197,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Moullet, Arielle","contributorId":224979,"corporation":false,"usgs":false,"family":"Moullet","given":"Arielle","email":"","affiliations":[{"id":41014,"text":"SOFIA/USRA, Moffett Field, CA","active":true,"usgs":false}],"preferred":false,"id":960198,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hsieh, Henry H.","contributorId":224980,"corporation":false,"usgs":false,"family":"Hsieh","given":"Henry","email":"","middleInitial":"H.","affiliations":[{"id":13179,"text":"Planetary Science Institute","active":true,"usgs":false}],"preferred":false,"id":960199,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70276314,"text":"70276314 - 2026 - Status of round goby invasion fronts in New York and Quebec: Implications for Lake Champlain","interactions":[],"lastModifiedDate":"2026-05-28T14:21:32.534574","indexId":"70276314","displayToPublicDate":"2026-03-25T09:17:24","publicationYear":"2026","noYear":false,"publicationType":{"id":27,"text":"Preprint"},"publicationSubtype":{"id":32,"text":"Preprint"},"seriesTitle":{"id":19846,"text":"BioRxiv","active":true,"publicationSubtype":{"id":32}},"title":"Status of round goby invasion fronts in New York and Quebec: Implications for Lake Champlain","docAbstract":"Invasive round goby Neogobius melanostomus have advanced eastward through the state of New York and provinces of Ontario and Quebec over the past two decades and are approaching Lake Champlain, one of the largest lakes in North America. This manuscript describes international efforts to monitor round goby populations during 2021–2025 on (a) the southern approach to Lake Champlain via the Hudson River and Champlain Canal, and (b) the northern approach to Lake Champlain via the Saint Lawrence River and Richelieu River. Monitoring utilized environmental DNA (eDNA), backpack electrofishing, beach seining, benthic trawling, and viral hemorrhagic septicemia virus (VHSV) testing. In the Champlain Canal, round goby were captured as far north as the downstream side of the C1 dam (97 kilometers [km] from Lake Champlain) while eDNA detections occurred as far north as the upstream side of the C2 dam (90 km from Lake Champlain). In the Richelieu River, round goby were captured as far south as Saint-Marc-sur-Richelieu (82 km from Lake Champlain) while the southern-most eDNA detections occurred near the Canadian side of the international border (4 km from Lake Champlain). Water temperature influenced habitat usage of round goby in the Champlain Canal, with catch rates in near-shore areas declining at < 10 °C. All VHSV test results were non-detections at the mouth of the Richelieu River, while one positive and two inconclusive results occurred along the Champlain Canal. Together, these data have informed multiple mitigation measures and have implications for management of aquatic invasive species across North America.
","language":"English","publisher":"BioRxiv","doi":"10.64898/2026.03.23.712452","usgsCitation":"George, S.D., Diebboll, H., Pearson, S., Goldsmit, J., Drouin, A., Vachon, N., Côté, G., Daudelin, S., Bartron, M.L., Modley, M., Littrell, K., Getchell, R.G., Fiorentino, R., Sadekoski, T., Finkelstein, J., Darling, M., Parent, G., and Atkins, L., 2026, Status of round goby invasion fronts in New York and Quebec: Implications for Lake Champlain: BioRxiv, preprint posted March 25, 2026, https://doi.org/10.64898/2026.03.23.712452.","productDescription":"26 p.","ipdsId":"IP-187768","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":504816,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.64898/2026.03.23.712452","text":"External 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Steven","contributorId":303228,"corporation":false,"usgs":false,"family":"Pearson","given":"Steven","email":"","affiliations":[{"id":13678,"text":"New York State Department of Environmental Conservation","active":true,"usgs":false}],"preferred":false,"id":962062,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Goldsmit, Jesica","contributorId":371577,"corporation":false,"usgs":false,"family":"Goldsmit","given":"Jesica","affiliations":[{"id":88179,"text":"Ministère de l’Environnement, de la Lutte contre les changements climatiques, de la Faune et des Parcs, Direction principale de l’expertise sur la faune aquatique","active":true,"usgs":false}],"preferred":false,"id":962063,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Drouin, Annick","contributorId":371578,"corporation":false,"usgs":false,"family":"Drouin","given":"Annick","affiliations":[{"id":88179,"text":"Ministère de l’Environnement, de la Lutte contre les changements climatiques, de la Faune et des Parcs, Direction principale de l’expertise sur la faune aquatique","active":true,"usgs":false}],"preferred":false,"id":962064,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Vachon, Nathalie","contributorId":371580,"corporation":false,"usgs":false,"family":"Vachon","given":"Nathalie","affiliations":[{"id":88180,"text":"Ministère de l’Environnement, de la Lutte contre les changements climatiques, de la Faune et des Parcs, Direction de la gestion de la faune de l’Estrie, de Montréal, de la Montérégie et de Laval","active":true,"usgs":false}],"preferred":false,"id":962066,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Côté, Guillaume","contributorId":371579,"corporation":false,"usgs":false,"family":"Côté","given":"Guillaume","affiliations":[{"id":88179,"text":"Ministère de l’Environnement, de la Lutte contre les changements climatiques, de la Faune et des Parcs, Direction principale de l’expertise sur la faune aquatique","active":true,"usgs":false}],"preferred":false,"id":962065,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Daudelin, Siena","contributorId":371581,"corporation":false,"usgs":false,"family":"Daudelin","given":"Siena","affiliations":[{"id":88181,"text":"Parks Canada, Quebec Waterways","active":true,"usgs":false}],"preferred":false,"id":962067,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Bartron, Meredith L.","contributorId":149109,"corporation":false,"usgs":false,"family":"Bartron","given":"Meredith","email":"","middleInitial":"L.","affiliations":[{"id":6678,"text":"U.S. Fish and Wildlife Service, Alaska Maritime National Wildlife Refuge","active":true,"usgs":false},{"id":26874,"text":"USFWS, Lamar, PA","active":true,"usgs":false}],"preferred":false,"id":962068,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Modley, Meg","contributorId":371582,"corporation":false,"usgs":false,"family":"Modley","given":"Meg","affiliations":[{"id":88182,"text":"Lake Champlain Basin Program/New England Interstate Water Pollution Control Commission","active":true,"usgs":false}],"preferred":false,"id":962069,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Littrell, Kate","contributorId":371583,"corporation":false,"usgs":false,"family":"Littrell","given":"Kate","affiliations":[{"id":88183,"text":"New York Power Authority, Environmental, Health & Safety","active":true,"usgs":false}],"preferred":false,"id":962070,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Getchell, Rodman G.","contributorId":201129,"corporation":false,"usgs":false,"family":"Getchell","given":"Rodman","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":962071,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Fiorentino, Rob","contributorId":371585,"corporation":false,"usgs":false,"family":"Fiorentino","given":"Rob","affiliations":[{"id":88184,"text":"New York State Department of Environmental Conservation, Bureau of Fisheries, Region 5","active":true,"usgs":false}],"preferred":false,"id":962072,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Sadekoski, Thomas R. 0009-0006-0450-6385","orcid":"https://orcid.org/0009-0006-0450-6385","contributorId":349875,"corporation":false,"usgs":true,"family":"Sadekoski","given":"Thomas R.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":962073,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Finkelstein, Jason S. 0000-0002-7496-7236","orcid":"https://orcid.org/0000-0002-7496-7236","contributorId":202452,"corporation":false,"usgs":true,"family":"Finkelstein","given":"Jason S.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":962074,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Darling, Michael J. 0009-0008-5733-3005","orcid":"https://orcid.org/0009-0008-5733-3005","contributorId":332525,"corporation":false,"usgs":true,"family":"Darling","given":"Michael J.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":962075,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Parent, Geneviève","contributorId":371587,"corporation":false,"usgs":false,"family":"Parent","given":"Geneviève","affiliations":[{"id":88187,"text":"Fisheries and Oceans Canada, Maurice Lamontagne Institute","active":true,"usgs":false}],"preferred":false,"id":962076,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Atkins, Lauren M.","contributorId":291382,"corporation":false,"usgs":false,"family":"Atkins","given":"Lauren M.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":962077,"contributorType":{"id":1,"text":"Authors"},"rank":18}]}} ,{"id":70274756,"text":"70274756 - 2026 - Mangrove ecosystems: Importance, threats and opportunities for restoration","interactions":[],"lastModifiedDate":"2026-04-08T15:26:45.625033","indexId":"70274756","displayToPublicDate":"2026-03-25T08:20:32","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Mangrove ecosystems: Importance, threats and opportunities for restoration","docAbstract":"Mangroves are crucial for biodiversity conservation, coastal protection, and supporting local livelihoods. Mangroves may also protect coasts from storms and rising sea levels and can play a major role in climate mitigation. Threats to their health include activities such as infrastructural development, urban encroachment, aquaculture and crop farming, and oil and gas exploration. We review the threats and opportunities for the restoration of mangrove ecosystems on the coasts of Africa, which are highly impacted by oil spills. The most important challenge for mangrove restoration identified in this review is the restoration of appropriate hydrologic and salinity regimes prior to natural recruitment or the active planting of propagules.
","language":"English","publisher":"MDPI","doi":"10.3390/w18070787","usgsCitation":"Ohimain, E.I., Turner, R.E., and Middleton, B.A., 2026, Mangrove ecosystems: Importance, threats and opportunities for restoration: Water, v. 18, no. 7, 787, 13 p., https://doi.org/10.3390/w18070787.","productDescription":"787, 13 p.","ipdsId":"IP-186012","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":502484,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w18070787","text":"Publisher Index Page"},{"id":502276,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"18","issue":"7","noUsgsAuthors":false,"publicationDate":"2026-03-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Ohimain, Elijah I. 0000-0002-5491-6271","orcid":"https://orcid.org/0000-0002-5491-6271","contributorId":369427,"corporation":false,"usgs":false,"family":"Ohimain","given":"Elijah","middleInitial":"I.","affiliations":[{"id":87767,"text":"Niger Delta University, Wilberforce Island, Bayelsa State, Nigeria","active":true,"usgs":false}],"preferred":false,"id":958941,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Turner, Robert Eugene 0000-0002-1368-4160","orcid":"https://orcid.org/0000-0002-1368-4160","contributorId":369428,"corporation":false,"usgs":false,"family":"Turner","given":"Robert","middleInitial":"Eugene","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":958942,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Middleton, Beth A. 0000-0002-1220-2326","orcid":"https://orcid.org/0000-0002-1220-2326","contributorId":216869,"corporation":false,"usgs":true,"family":"Middleton","given":"Beth","middleInitial":"A.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":958943,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70275343,"text":"70275343 - 2026 - Tag retention, growth, condition, and survival of externally marked Yellow Perch","interactions":[],"lastModifiedDate":"2026-04-30T15:05:45.427802","indexId":"70275343","displayToPublicDate":"2026-03-25T08:00:41","publicationYear":"2026","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":"Tag retention, growth, condition, and survival of externally marked Yellow Perch","docAbstract":"Objective:
Determining the movement and survival of Yellow Perch Perca flavescens that inhabit Lake Erie is a priority management concern, yet contemporary understanding of their cross-jurisdictional movements and exploitation is lacking. To support future movement and survival studies, we evaluated the retention rates, condition, growth, and survival associated with four external tagging methods.
Methods: One-hundred hatchery- reared Yellow Perch (188–257 mm) were tagged and held in recirculating aquaculture systems over a 168- d period. We tested four external tag types, including loop tags, ring tags, streamer tags, and T- bar anchor tags, and quantified tag retention rates, as well as tagging effects on condition, growth, and survival.
Results: T- bar anchor and loop tags had 100% retention, whereas ring (54%) and streamer (0%) retention was poor. The condition and growth of fish were not affected by any of the tagging methods; however, the loop tags caused abrasive wounds near the tagging site that could lead to secondary infection and latent effects on survival. We found no evidence that tagging resulted in mortality.
Conclusion: External T- bar tags were the most efficient to apply and provided a marking option that was highly visible, had high retention, and had no effects on condition, growth, or survival in Yellow Perch over the 168- d study period.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/najfmt/vqag011","usgsCitation":"Dufour, M.R., Guzzo, F., Keeler, K., and Vandergoot, C.S., 2026, Tag retention, growth, condition, and survival of externally marked Yellow Perch: North American Journal of Fisheries Management, v. 46, no. 2, p. 551-563, https://doi.org/10.1093/najfmt/vqag011.","productDescription":"13 p.","startPage":"551","endPage":"563","ipdsId":"IP-177348","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":503789,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/najfmt/vqag011","text":"Publisher Index Page"},{"id":503675,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"46","issue":"2","noUsgsAuthors":false,"publicationDate":"2026-03-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Dufour, Mark Richard 0000-0001-6930-7666","orcid":"https://orcid.org/0000-0001-6930-7666","contributorId":291450,"corporation":false,"usgs":true,"family":"Dufour","given":"Mark","email":"","middleInitial":"Richard","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":960649,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Guzzo, Francesco 0000-0003-2374-0514","orcid":"https://orcid.org/0000-0003-2374-0514","contributorId":351294,"corporation":false,"usgs":true,"family":"Guzzo","given":"Francesco","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":960650,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Keeler, Kevin 0000-0002-8118-0060","orcid":"https://orcid.org/0000-0002-8118-0060","contributorId":203484,"corporation":false,"usgs":true,"family":"Keeler","given":"Kevin","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":960651,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vandergoot, Christopher S.","contributorId":351529,"corporation":false,"usgs":false,"family":"Vandergoot","given":"Christopher","middleInitial":"S.","affiliations":[{"id":84005,"text":"Michigan State University/GLATOS","active":true,"usgs":false}],"preferred":false,"id":960652,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70274695,"text":"70274695 - 2026 - Advances and applications of Unoccupied Aerial Systems (UAS) research in landscape ecology","interactions":[],"lastModifiedDate":"2026-04-06T14:55:21.789264","indexId":"70274695","displayToPublicDate":"2026-03-25T07:49:34","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2602,"text":"Landscape Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Advances and applications of Unoccupied Aerial Systems (UAS) research in landscape ecology","docAbstract":"Landscape ecologists have long depended on satellite and aerial remote sensing to address questions about landscape pattern and process, structure, and change (Foody 2023). Unoccupied aerial systems/vehicles (UAS/UAV, a.k.a. drones) technology is becoming an increasingly popular research tool in environmental sciences allowing scientists to generate low-cost, high-quality, and high-resolution imagery on demand that can be tailored to specific research questions. While satellite data are of a fixed resolution and temporal interval, UAS offer researchers control and flexibility to design studies and collect data at resolutions and scales that provide ecologically relevant information at finer spatial resolutions (e.g., < 30 cm) than what is currently available from satellite platforms (typically > 3m), thus helping capture objects such as individual plant canopies, micro-topography, and individual animals. Unlike satellites with fixed orbits, UAS can be deployed at more optimal temporal frequencies for ecological monitoring.
We organized the special collection “Advances and Applications of Unoccupied Aerial Systems (UAS) Research in Landscape Ecology” to showcase the many ways that UAS tools and technologies are currently applied to advance landscape ecological research. When we announced the collection in 2023, only 11 papers published in the journal Landscape Ecology used UAS data, which was a notably small number compared to many other general ecology, environmental science and remote sensing journals. In an attempt to understand why UAS were not more widely used in landscape ecology and provide possible solutions, we published a review article (Villarreal et al. 2025) that identified the challenges, knowledge gaps, and obstacles for the adoption of UAS technologies in landscape ecology research. The main issues we identified include: (1) an abundance of UAS methods papers in the existing literature, with comparatively few studies demonstrating how UAS can be applied to address ecological questions; (2) a perceived scale mismatch between the geographic extent of UAS data collection (local) compared to larger study areas (landscapes) and a need to design robust scaling approaches to connect fine-scale UAS data with broader ecological patterns; and (3) a need for improved integration of UAS data with other commonly used remote sensing datasets including historical high resolution aerial imagery. Additionally, researchers new to UAS remote sensing may be discouraged or overwhelmed by the general lack of scientific consensus and standardized protocols for typical tasks such as data collection, vegetation classification, and change detection, as well as restrictive and/or confusing policy, regulatory, and legal issues surrounding UAS operations (Villarreal et al. 2025).
","language":"English","publisher":"Springer Nature","doi":"10.1007/s10980-026-02331-0","usgsCitation":"Villarreal, M.L., Bishop, T.B., Sankey, T.T., and Smith, W.K., 2026, Advances and applications of Unoccupied Aerial Systems (UAS) research in landscape ecology: Landscape Ecology, v. 41, 65, 8 p., https://doi.org/10.1007/s10980-026-02331-0.","productDescription":"65, 8 p.","ipdsId":"IP-185152","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":502473,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10980-026-02331-0","text":"Publisher Index Page"},{"id":502205,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"41","noUsgsAuthors":false,"publicationDate":"2026-03-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Villarreal, Miguel L. 0000-0003-0720-1422 mvillarreal@usgs.gov","orcid":"https://orcid.org/0000-0003-0720-1422","contributorId":214980,"corporation":false,"usgs":true,"family":"Villarreal","given":"Miguel","email":"mvillarreal@usgs.gov","middleInitial":"L.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":958718,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bishop, Tara B.","contributorId":369273,"corporation":false,"usgs":false,"family":"Bishop","given":"Tara","middleInitial":"B.","affiliations":[{"id":40367,"text":"Utah Valley University","active":true,"usgs":false}],"preferred":false,"id":958719,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sankey, Temuulen Ts.","contributorId":369274,"corporation":false,"usgs":false,"family":"Sankey","given":"Temuulen","middleInitial":"Ts.","affiliations":[{"id":12698,"text":"Northern Arizona University","active":true,"usgs":false}],"preferred":false,"id":958720,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, William K.","contributorId":369275,"corporation":false,"usgs":false,"family":"Smith","given":"William","middleInitial":"K.","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":958721,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70274285,"text":"dr1218 - 2026 - Distribution and abundance of Least Bell’s Vireos (Vireo bellii pusillus) and Southwestern Willow Flycatchers (Empidonax traillii extimus) at the Mojave River Dam, San Bernardino County, California—2025 Data Summary","interactions":[],"lastModifiedDate":"2026-03-25T15:16:39.33281","indexId":"dr1218","displayToPublicDate":"2026-03-25T07:00:00","publicationYear":"2026","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":9318,"text":"Data Report","code":"DR","onlineIssn":"2771-9448","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1218","displayTitle":"Distribution and Abundance of Least Bell’s Vireos (Vireo bellii pusillus) and Southwestern Willow Flycatchers (Empidonax traillii extimus) at the Mojave River Dam, San Bernardino County, California—2025 Data Summary","title":"Distribution and abundance of Least Bell’s Vireos (Vireo bellii pusillus) and Southwestern Willow Flycatchers (Empidonax traillii extimus) at the Mojave River Dam, San Bernardino County, California—2025 Data Summary","docAbstract":"We surveyed for Least Bell’s Vireos (Vireo bellii pusillus; vireo) and Southwestern Willow Flycatchers (Empidonax traillii extimus; flycatcher) at the Mojave River Dam study area near Hesperia, California, in 2025. Four vireo surveys were completed between April 23 and June 26, 2025, and three flycatcher surveys were completed between May 16 and June 26, 2025.
We detected two territorial male vireos, both of which were paired, and one transient vireo. No juvenile vireos were observed during surveys. Vireos were reported in two habitat types: riparian scrub dominated by narrowleaf willow (Salix exigua) or mule fat (Baccharis salicifolia) and willow-cottonwood dominated by red or arroyo willow (Salix laevigata or lasiolepis). One transient willow flycatcher of unknown subspecies was observed in willow-cottonwood habitat dominated by Fremont cottonwood (Populus fremontii).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/dr1218","programNote":"Ecosystems Mission Area–Species Management Research Program","usgsCitation":"Howell, S.L., and Kus, B.E., 2026, Distribution and abundance of Least Bell’s Vireos (Vireo bellii pusillus) and Southwestern Willow Flycatchers (Empidonax traillii extimus) at the Mojave River Dam, San Bernardino County, California—2025 data summary: U.S. Geological Survey Data Report 1218, 8 p., https://doi.org/10.3133/dr1218.","productDescription":"vi, 8 p.","numberOfPages":"8","onlineOnly":"Y","ipdsId":"IP-182721","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":501431,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/dr/1218/images"},{"id":501430,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/dr/1218/dr1218.XML","linkFileType":{"id":8,"text":"xml"},"description":"DR 1218 XML"},{"id":501429,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/dr1218/full","linkFileType":{"id":5,"text":"html"},"description":"DR 1218 HTML"},{"id":501428,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/dr/1218/dr1218.pdf","text":"Report","size":"5.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DR 1218 PDF"},{"id":501427,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/dr/1218/coverthb.jpg"}],"country":"United States","state":"California","county":"San Bernardino County","otherGeospatial":"Mojave River Dam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.22193446568201,\n 34.372629231592285\n ],\n [\n -117.26951127201511,\n 34.372629231592285\n ],\n [\n -117.26951127201511,\n 34.32314904481471\n ],\n [\n -117.22193446568201,\n 34.32314904481471\n ],\n [\n -117.22193446568201,\n 34.372629231592285\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
Migration is thought to be costly such that challenges faced during migration likely affect how birds migrate through direct selection on migratory behavior. Survival throughout the annual cycle and conditions that affect the survival costs of migration are therefore critical to our understanding of the causes and consequences of migration. Estimating daily survival throughout the annual cycle of migratory birds has only recently become possible. We used over a decade of GPS tracking data from 186 migratory Buteo lagopus to quantify causes of mortality as well as demographic, seasonal, and spatial variation in daily survival and how survival consequences of migration changed during an outbreak of highly pathogenic avian influenza virus. The cost of migration via direct mortality varied between avian influenza and baseline study periods. Surprisingly, mortality risk during typical spring migrations was lower than in all other seasons, but mortality risk during the avian influenza outbreak was higher during both spring and fall migrations. Additionally, we found increased mortality risk in females during the avian influenza outbreak but no sex differences during baseline periods. Hence, the relative cost of migration was altered by the virus. During baseline periods, mortality risk was highest during late fall migration and winter, coinciding with increased anthropogenic-related mortalities at lower latitudes. However, the number of deaths caused by avian influenza (n = 11) in a single year equaled the total number of deaths caused by anthropogenic-related factors (n = 11; primarily collision trauma and persecution) across all 12 study years. Overall, our study highlights how added stressors such as disease outbreaks and anthropogenic factors may exacerbate existing seasonal constraints by directly increasing mortality risk.
","language":"English","publisher":"Nordic Society Oikos","doi":"10.1002/jav.03616","usgsCitation":"Paprocki, N., Kidd, J., and Conway, C.J., 2026, Cost of migration increased during an outbreak of highly pathogenic avian influenza virus: Journal of Avian Biology, v. 2026, no. 2, e03616, 12 p., https://doi.org/10.1002/jav.03616.","productDescription":"e03616, 12 p.","ipdsId":"IP-184143","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":504189,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jav.03616","text":"Publisher Index Page"},{"id":503963,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -119.13235830742079,\n 34.051610219206324\n ],\n [\n -83.4075671325163,\n 31.97455989703157\n ],\n [\n -71.9618053244041,\n 36.378884780518845\n ],\n [\n -51.3279583202131,\n 47.102405825196826\n ],\n [\n -60.61639235445597,\n 69.08251642248632\n ],\n [\n -73.58348120720501,\n 75.6012254722263\n ],\n [\n -120.1573204427736,\n 80.22448058582967\n ],\n [\n -129.667008135693,\n 72.00987949294188\n ],\n [\n -169.6334732525069,\n 70.88068700335253\n ],\n [\n -168.86366811171357,\n 64.89630104169692\n ],\n [\n -167.77200080735236,\n 58.0662938080217\n ],\n [\n -170.9953070876699,\n 51.60858982544414\n ],\n [\n -148.62255894047334,\n 57.914290721992955\n ],\n [\n -135.08449775745427,\n 54.553326998846785\n ],\n [\n -127.18224152452092,\n 47.7217058670808\n ],\n [\n -125.96834641135626,\n 39.66868629978072\n ],\n [\n -119.13235830742079,\n 34.051610219206324\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"2026","issue":"2","noUsgsAuthors":false,"publicationDate":"2026-03-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Paprocki, Neil","contributorId":355054,"corporation":false,"usgs":false,"family":"Paprocki","given":"Neil","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":960906,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kidd, Jeff W","contributorId":243473,"corporation":false,"usgs":false,"family":"Kidd","given":"Jeff W","affiliations":[],"preferred":false,"id":960907,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Conway, Courtney J. 0000-0003-0492-2953 cconway@usgs.gov","orcid":"https://orcid.org/0000-0003-0492-2953","contributorId":2951,"corporation":false,"usgs":true,"family":"Conway","given":"Courtney","email":"cconway@usgs.gov","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":960908,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70275379,"text":"70275379 - 2026 - Changes in spatial distribution and abundance together determine potential for population persistence for greater sage-grouse","interactions":[],"lastModifiedDate":"2026-05-01T15:09:06.584","indexId":"70275379","displayToPublicDate":"2026-03-24T09:58:47","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1399,"text":"Diversity and Distributions","active":true,"publicationSubtype":{"id":10}},"title":"Changes in spatial distribution and abundance together determine potential for population persistence for greater sage-grouse","docAbstract":"Population ecologists often focus on changes in the distribution and abundance of wildlife species, which are useful for trend analyses and status assessments. However, rarely are these responses evaluated simultaneously for a single species, despite their unique contributions to fully assess a species' viability. For example, focusing solely on total abundance can mask important losses in overall distribution within a metapopulation structure that may contribute to long-term population instability that results from the extirpation of small peripheral populations.
Bi-State region of Nevada and California, USA.
We simultaneously evaluated changes in population abundance and distribution for greater sage-grouse (hereafter sage-grouse; Centrocercus urophasianus) within the Bi-State Distinct Population Segment (DPS), a genetically distinct and isolated population straddling the border of Nevada and California. We combined population counts, demographic data, and information on space use from marked individuals to evaluate changes in population distribution and abundance over three time periods that corresponded to the three most recent population nadirs (1995–2019, 2002–2019 and 2008–2019).
The Bi-State DPS exhibited evidence of ~1.2%–2.5% declines annually, over the short/medium-term (1995–2019; λ^ = 0.987, 95% CRI: 0.970–0.999), short-term (2002–2019; λ^ = 0.975, 95% CRI: 0.963–0.985) and recent-term (2008–2019; λ^ = 0.988, 95% CRI: 0.973–1.001). Since 1995, the spatial distribution of sage-grouse abundance in the Bi-State DPS shifted amongst subpopulations, with peripheral subpopulations suffering the largest declines.
Gains in abundance and distribution amongst expanding subpopulations did not offset losses in the remaining subpopulations, with a net loss in occupied distribution of 156 km2 since 1995. Reductions in spatial distribution could have implications for metapopulation persistence as peripheral populations become more vulnerable to stochastic events, which would not have been apparent from the evaluation of overall metapopulation abundance on its own.
","language":"English","publisher":"Wiley","doi":"10.1111/ddi.70092","usgsCitation":"Milligan, M.C., Coates, P., Prochazka, B.G., Chenaille, M.P., O’Neil, S.T., Mathews, S.R., Small, J.R., Miller, K., and Abele, S., 2026, Changes in spatial distribution and abundance together determine potential for population persistence for greater sage-grouse: Diversity and Distributions, v. 32, no. 3, e70092, 15 p., https://doi.org/10.1111/ddi.70092.","productDescription":"e70092, 15 p.","ipdsId":"IP-158428","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":504165,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ddi.70092","text":"Publisher Index Page"},{"id":503890,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Nevada","volume":"32","issue":"3","noUsgsAuthors":false,"publicationDate":"2026-03-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Milligan, Megan C. 0000-0001-8466-7803","orcid":"https://orcid.org/0000-0001-8466-7803","contributorId":296042,"corporation":false,"usgs":true,"family":"Milligan","given":"Megan","email":"","middleInitial":"C.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":960785,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coates, Peter S. 0000-0003-2672-9994","orcid":"https://orcid.org/0000-0003-2672-9994","contributorId":352181,"corporation":false,"usgs":true,"family":"Coates","given":"Peter S.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":960786,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Prochazka, Brian G. 0000-0001-7270-5550 bprochazka@usgs.gov","orcid":"https://orcid.org/0000-0001-7270-5550","contributorId":210597,"corporation":false,"usgs":true,"family":"Prochazka","given":"Brian","email":"bprochazka@usgs.gov","middleInitial":"G.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":960787,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chenaille, Michael P. 0000-0003-3387-7899 mchenaille@usgs.gov","orcid":"https://orcid.org/0000-0003-3387-7899","contributorId":194661,"corporation":false,"usgs":true,"family":"Chenaille","given":"Michael","email":"mchenaille@usgs.gov","middleInitial":"P.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":960788,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"O’Neil, Shawn T. 0000-0002-0899-5220","orcid":"https://orcid.org/0000-0002-0899-5220","contributorId":206589,"corporation":false,"usgs":true,"family":"O’Neil","given":"Shawn","email":"","middleInitial":"T.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":960789,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mathews, Steven R.","contributorId":370798,"corporation":false,"usgs":false,"family":"Mathews","given":"Steven","middleInitial":"R.","affiliations":[{"id":37814,"text":"Former USGS","active":true,"usgs":false}],"preferred":false,"id":960790,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Small, Justin R.","contributorId":370799,"corporation":false,"usgs":false,"family":"Small","given":"Justin","middleInitial":"R.","affiliations":[{"id":85566,"text":"NDOW","active":true,"usgs":false}],"preferred":false,"id":960791,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Miller, Katherine","contributorId":259248,"corporation":false,"usgs":false,"family":"Miller","given":"Katherine","email":"","affiliations":[{"id":6952,"text":"California Department of Fish and Wildlife","active":true,"usgs":false}],"preferred":true,"id":960792,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Abele, Steve","contributorId":299010,"corporation":false,"usgs":false,"family":"Abele","given":"Steve","email":"","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":true,"id":960793,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70275539,"text":"70275539 - 2026 - Leveraging local species data, a global database, and an occupancy model to explore bee–plant interactions","interactions":[],"lastModifiedDate":"2026-05-04T17:06:17.889447","indexId":"70275539","displayToPublicDate":"2026-03-24T09:58:15","publicationYear":"2026","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":"Leveraging local species data, a global database, and an occupancy model to explore bee–plant interactions","docAbstract":"Global declines in bee populations are threatening the ecosystem services they provide, including pollination. Many bee–plant interactions are understudied, producing an incomplete understanding of resulting ecosystem-level vulnerabilities. The last decade has generated a wealth of opportunistic data originating from natural history collection records, published ecological datasets, and citizen/community science initiatives in online databases such as Global Biotic Interactions (GloBI). Here, we explore hypotheses related to bee–plant interactions and detection processes using the GloBI database, curated checklists of bee and flowering plant species, and an occupancy model. We hypothesized that larger, social bees would visit a larger number of plant species, while smaller, solitary bees would visit fewer. We also predicted that flowers with open, bowl-like shapes would attract a greater diversity of bee visitors compared to closed shapes. Further, we hypothesized that both floral and bee traits, such as bright colors and conspicuous patterns, would increase detectability, and that different data collection methods would vary in their ability to capture bee–plant interactions. Lastly, we hypothesized that the interaction network generated by the output of the occupancy model, which accounted for imperfect bee–plant detection, would yield more interactions, thereby increasing measures of evenness and decreasing nestedness and specialization, as compared to the network generated from recorded interaction data. We found that smaller bees exhibited higher probabilities of plant interactions than larger bees, but we did not find evidence that bee sociality influenced the probability of interacting with plants. We found that blue flowers and closed (not-bowl-shaped) flowers had higher probabilities of bee-plant interaction than other flower colors or bowl-shaped flowers, respectively. We also found that larger bee size, blue flowers, bowl shapes, and community science sources were associated with higher detection probabilities of bee–plant interactions. Lastly, the interaction network generated by the occupancy model output showed higher levels of evenness, nestedness, and connectance than the network generated by the GloBI data. Our study is among the first to utilize occupancy modeling to directly model species' interactions, leverage aggregated, open-source databases and expert checklists, and highlight the influence of detection and collection biases on our understanding of ecological interactions.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.70221","usgsCitation":"Lee, M.J., DiRenzo, G.V., Diao, C., and Seltmann, K.C., 2026, Leveraging local species data, a global database, and an occupancy model to explore bee–plant interactions: Ecological Applications, v. 36, no. 2, e70221, 20 p., https://doi.org/10.1002/eap.70221.","productDescription":"e70221, 20 p.","ipdsId":"IP-150867","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":504184,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/eap.70221","text":"Publisher Index Page"},{"id":503954,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Santa Cruz Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -119.93350233953383,\n 34.08271906479452\n ],\n [\n -119.93350233953383,\n 33.94903535628485\n ],\n [\n -119.51877742715749,\n 33.94903535628485\n ],\n [\n -119.51877742715749,\n 34.08271906479452\n ],\n [\n -119.93350233953383,\n 34.08271906479452\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"36","issue":"2","noUsgsAuthors":false,"publicationDate":"2026-03-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Lee, Michelle J.","contributorId":370972,"corporation":false,"usgs":false,"family":"Lee","given":"Michelle","middleInitial":"J.","affiliations":[{"id":16936,"text":"University of California Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":960832,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"DiRenzo, Graziella Vittoria 0000-0001-5264-4762","orcid":"https://orcid.org/0000-0001-5264-4762","contributorId":243404,"corporation":false,"usgs":true,"family":"DiRenzo","given":"Graziella","email":"","middleInitial":"Vittoria","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":960833,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Diao, Chengyi","contributorId":371081,"corporation":false,"usgs":false,"family":"Diao","given":"Chengyi","affiliations":[],"preferred":false,"id":960983,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Seltmann, Katja C.","contributorId":370974,"corporation":false,"usgs":false,"family":"Seltmann","given":"Katja","middleInitial":"C.","affiliations":[{"id":16936,"text":"University of California Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":960835,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70275221,"text":"70275221 - 2026 - Compact seismicity bursts have different characteristics from regional seismicity","interactions":[],"lastModifiedDate":"2026-04-23T14:29:24.443954","indexId":"70275221","displayToPublicDate":"2026-03-24T09:18:03","publicationYear":"2026","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":"Compact seismicity bursts have different characteristics from regional seismicity","docAbstract":"Earthquakes tend to cluster, developing into sequences driven by stress perturbations and transient fault-zone processes. Depending on the driving process, earthquake sequences show differing behaviors. This variability challenges our ability to observe or distinguish these driving processes in high resolution. Here we systematically identify seismicity bursts throughout southern California using new statistical methods and examine their causes with other independent geophysical observations. Seismicity bursts are defined as statistically significant seismicity rate anomalies. Our approach has the advantage of being data driven, depending on few earthquake occurrence assumptions. We find abundant seismicity bursts across southern California, most frequently occurring along the San Jacinto Fault and in the Salton Sea and Coso geothermal fields. These seismicity bursts are highly compact in space and time, often encompassed by a 5 km radius and have durations less than 10 hr. Many of the seismicity bursts have their largest earthquake near the beginning of the sequence, but the largest earthquake is usually not an obvious mainshock. We utilize a variety of independent geophysical data sets to analyze the characteristics of the seismicity bursts, finding that the seismicity bursts have low b-values, low spectral stress drops, and varied stress ratios compared to regional seismicity. These differences suggest that seismicity bursts are driven by transient processes acting frequently across fault networks.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2025JB032917","usgsCitation":"DeSalvio, N., Fan, W., Barbour, A.J., and Hardebeck, J.L., 2026, Compact seismicity bursts have different characteristics from regional seismicity: JGR Solid Earth, v. 131, no. 3, e2025JB032917, 22 p., https://doi.org/10.1029/2025JB032917.","productDescription":"e2025JB032917, 22 p.","ipdsId":"IP-179229","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":503338,"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 \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121,\n 37\n ],\n [\n -115,\n 37\n ],\n [\n -115,\n 32\n ],\n [\n -121,\n 32\n ],\n [\n -121,\n 37\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"131","issue":"3","noUsgsAuthors":false,"publicationDate":"2026-03-24","publicationStatus":"PW","contributors":{"authors":[{"text":"DeSalvio, Nicolas","contributorId":352016,"corporation":false,"usgs":false,"family":"DeSalvio","given":"Nicolas","affiliations":[{"id":25459,"text":"SIO","active":true,"usgs":false}],"preferred":false,"id":960165,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fan, Wenyuan","contributorId":174007,"corporation":false,"usgs":false,"family":"Fan","given":"Wenyuan","email":"","affiliations":[{"id":6728,"text":"Scripps Inst Oceanography","active":true,"usgs":false}],"preferred":false,"id":960166,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barbour, Andrew J. 0000-0002-6890-2452","orcid":"https://orcid.org/0000-0002-6890-2452","contributorId":215339,"corporation":false,"usgs":true,"family":"Barbour","given":"Andrew","middleInitial":"J.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":960167,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hardebeck, Jeanne L. 0000-0002-6737-7780","orcid":"https://orcid.org/0000-0002-6737-7780","contributorId":254964,"corporation":false,"usgs":true,"family":"Hardebeck","given":"Jeanne","email":"","middleInitial":"L.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":960168,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70276375,"text":"70276375 - 2026 - Tidal wetland soil carbon accumulation rates for coastal California","interactions":[],"lastModifiedDate":"2026-06-02T14:13:42.244843","indexId":"70276375","displayToPublicDate":"2026-03-24T09:09:05","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3907,"text":"Scientific Data","active":true,"publicationSubtype":{"id":10}},"title":"Tidal wetland soil carbon accumulation rates for coastal California","docAbstract":"Carbon stock and carbon accumulation rate data are vital to multiple aspects of tidal wetland conservation and restoration policy. In California, USA tidal soil data are rare outside of the San Francisco Bay and Sacramento Delta regions, despite the differing conditions experienced by the outer coastline. Here we provide carbon stocks and decadal-to-centennial-scale carbon accumulation rate calculations. This dataset presents 83 soil depth profiles from 15 sites, with 58 cores from 12 tidal wetland sites analyzed for carbon stock, mostly from the outer coastline of California. Mean organic matter content was 11%, and stocks estimated to 1 meter depth ranged from 15.4 to 44.7 kgC m−2. Organic matter content generally declined asymptotically with depth. Carbon accumulation rates ranged from 39.2 to 130.0 gC m−2 yr−1. Neither carbon stock nor carbon accumulation rates were notably different from global average values. Data at this level of reporting are vital for establishing restoration baselines, informing greenhouse gas mitigation planning, and projecting future ecosystem response to sea-level rise.
","language":"English","publisher":"Nature","doi":"10.1038/s41597-026-06935-8","usgsCitation":"Homquist, J.R., Brown, L.N., Fard, E., Ambrose, R.F., Hargan, K.E., Hammond, D.E., Kemnitz, N.J., Smol, J.P., Thorne, K., and MacDonald, G.M., 2026, Tidal wetland soil carbon accumulation rates for coastal California: Scientific Data, v. 13, 733, 11 p., https://doi.org/10.1038/s41597-026-06935-8.","productDescription":"733, 11 p.","ipdsId":"IP-183445","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":505045,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41597-026-06935-8","text":"Publisher Index Page"},{"id":504948,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"coastal California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.7794573,\n 32.5268953\n ],\n [\n -116.7328649,\n 32.6789082\n ],\n [\n -118.7177816,\n 34.6610454\n ],\n [\n -120.0530892,\n 34.8685771\n ],\n [\n -121.4244861,\n 36.6837564\n ],\n [\n -122.2906316,\n 38.4005445\n ],\n [\n -123.9507437,\n 40.463016\n ],\n [\n -123.8424571,\n 41.9561618\n ],\n [\n -124.6003344,\n 42.0098155\n ],\n [\n -124.7807813,\n 40.1051087\n ],\n [\n -123.8785465,\n 38.7391313\n ],\n [\n -122.5793283,\n 36.7126829\n ],\n [\n -120.8470374,\n 34.3338619\n ],\n [\n -119.8365343,\n 33.4952897\n ],\n [\n -117.7794573,\n 32.5268953\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"13","noUsgsAuthors":false,"publicationDate":"2026-03-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Homquist, James R.","contributorId":371661,"corporation":false,"usgs":false,"family":"Homquist","given":"James","middleInitial":"R.","affiliations":[{"id":13510,"text":"Smithsonian Environmental Research Center","active":true,"usgs":false}],"preferred":false,"id":962257,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brown, Lauren N.","contributorId":371662,"corporation":false,"usgs":false,"family":"Brown","given":"Lauren","middleInitial":"N.","affiliations":[{"id":13587,"text":"Bowling Green State University","active":true,"usgs":false}],"preferred":false,"id":962258,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fard, Elizabeth","contributorId":331463,"corporation":false,"usgs":false,"family":"Fard","given":"Elizabeth","email":"","affiliations":[{"id":13399,"text":"UCLA","active":true,"usgs":false}],"preferred":false,"id":962259,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ambrose, Richard F.","contributorId":371663,"corporation":false,"usgs":false,"family":"Ambrose","given":"Richard","middleInitial":"F.","affiliations":[{"id":13399,"text":"UCLA","active":true,"usgs":false}],"preferred":false,"id":962260,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hargan, Kathryn E.","contributorId":371664,"corporation":false,"usgs":false,"family":"Hargan","given":"Kathryn","middleInitial":"E.","affiliations":[{"id":26965,"text":"Memorial University of Newfoundland","active":true,"usgs":false}],"preferred":false,"id":962261,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hammond, Douglas E.","contributorId":371665,"corporation":false,"usgs":false,"family":"Hammond","given":"Douglas","middleInitial":"E.","affiliations":[{"id":13249,"text":"University of Southern California","active":true,"usgs":false}],"preferred":false,"id":962262,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kemnitz, Nathaniel J.","contributorId":371666,"corporation":false,"usgs":false,"family":"Kemnitz","given":"Nathaniel","middleInitial":"J.","affiliations":[{"id":88196,"text":"Fugro U.S.A. Marine","active":true,"usgs":false}],"preferred":false,"id":962263,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Smol, John P.","contributorId":371668,"corporation":false,"usgs":false,"family":"Smol","given":"John","middleInitial":"P.","affiliations":[{"id":34006,"text":"Queen’s University","active":true,"usgs":false}],"preferred":false,"id":962264,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Thorne, Karen 0000-0002-1381-0657","orcid":"https://orcid.org/0000-0002-1381-0657","contributorId":371671,"corporation":false,"usgs":false,"family":"Thorne","given":"Karen","affiliations":[{"id":7065,"text":"USGS emeritus","active":true,"usgs":false}],"preferred":false,"id":962265,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"MacDonald, Glen M.","contributorId":371673,"corporation":false,"usgs":false,"family":"MacDonald","given":"Glen","middleInitial":"M.","affiliations":[{"id":13399,"text":"UCLA","active":true,"usgs":false}],"preferred":false,"id":962266,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70274328,"text":"70274328 - 2026 - Rapid seismic and infrasound assessment of large landslides: A case study from Denali National Park and Preserve (Alaska)","interactions":[],"lastModifiedDate":"2026-03-26T20:12:07.266266","indexId":"70274328","displayToPublicDate":"2026-03-23T13:03:56","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5739,"text":"Journal of Geophysical Research: Earth Surface","onlineIssn":"2169-9011","active":true,"publicationSubtype":{"id":10}},"title":"Rapid seismic and infrasound assessment of large landslides: A case study from Denali National Park and Preserve (Alaska)","docAbstract":"Large, rapid landslides are a global hazard that can occur in remote, mountainous areas. Eyewitness reports of landslides and satellite imagery can often be limited or delayed, particularly during inclement weather. However, landslide-generated seismic and infrasound (low-frequency atmospheric sound) waves can be remotely detected in near real-time. This information can significantly expedite characterization and possible landslide response activities. Here, we highlight these capabilities using a > 4 million m³ ice–rock avalanche in Denali National Park and Preserve (Alaska). This event was detected via a landslide-specific seismic location and volume estimation algorithm deployed in Alaska, and — notably — by standard earthquake monitoring systems. Following rapid detection of this event, we combined its seismic and infrasound dataset with optical, synthetic aperture radar, and oblique aerial imagery, multitemporal digital elevation models, and a numerical flow model to reconstruct its failure timeline and dynamics. We apply array processing to infrasound signals traveling > 250 km and find that two precursory events occurred minutes prior to the main failure. We use long-period seismic signals to infer the force exerted by the landslide on the Earth and constrain the rheological parameters of our numerical flow simulation with this result and deposit morphology. The main failure produced a steeply-dipping impulsive initial downward force and reached speeds exceeding 60 m/s. This impulsive force generated relatively strong seismic body waves, which contributed to the earthquake system detection. This large, remote Alaska landslide underscores the key value of seismic and infrasound analysis for rapid landslide assessment and motivates efforts to further operationalize these approaches.","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2025JF008577","usgsCitation":"Toney, L., West, M., Karasözen, E., Capps, D.M., Collins, E.A., Allstadt, K.E., Pursley, J., McFarlin, H., Mangeney, A., Fee, D., Staley, D.M., Haney, M.M., Lyons, J.J., and Bellini, J., 2026, Rapid seismic and infrasound assessment of large landslides: A case study from Denali National Park and Preserve (Alaska): Journal of Geophysical Research: Earth Surface, v. 131, no. 3, e2025JF008577, 21 p., https://doi.org/10.1029/2025JF008577.","productDescription":"e2025JF008577, 21 p.","ipdsId":"IP-179322","costCenters":[{"id":78941,"text":"Geologic Hazards Science Center - Landslides / Earthquake Geology","active":true,"usgs":true}],"links":[{"id":502039,"rank":1,"type":{"id":40,"text":"Open 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Earthquake Center, University of Alaska-Fairbanks","active":true,"usgs":false}],"preferred":false,"id":957895,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Capps, Denny M","contributorId":222771,"corporation":false,"usgs":false,"family":"Capps","given":"Denny","email":"","middleInitial":"M","affiliations":[{"id":40598,"text":"Denali National Park, National Park Service","active":true,"usgs":false}],"preferred":false,"id":957896,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Collins, Elaine A. 0000-0002-5475-4022","orcid":"https://orcid.org/0000-0002-5475-4022","contributorId":270255,"corporation":false,"usgs":true,"family":"Collins","given":"Elaine","middleInitial":"A.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":957897,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Allstadt, Kate E. 0000-0003-4977-5248","orcid":"https://orcid.org/0000-0003-4977-5248","contributorId":138704,"corporation":false,"usgs":true,"family":"Allstadt","given":"Kate","email":"","middleInitial":"E.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":957898,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pursley, Jana 0000-0002-7472-9668","orcid":"https://orcid.org/0000-0002-7472-9668","contributorId":269689,"corporation":false,"usgs":true,"family":"Pursley","given":"Jana","email":"","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":957899,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"McFarlin, Heather","contributorId":367929,"corporation":false,"usgs":false,"family":"McFarlin","given":"Heather","affiliations":[{"id":87644,"text":"Alaska Earthquake Center, 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jlyons@usgs.gov","orcid":"https://orcid.org/0000-0001-5409-1698","contributorId":5394,"corporation":false,"usgs":true,"family":"Lyons","given":"John","email":"jlyons@usgs.gov","middleInitial":"J.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":957905,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Bellini, John 0000-0002-9635-8730","orcid":"https://orcid.org/0000-0002-9635-8730","contributorId":269687,"corporation":false,"usgs":true,"family":"Bellini","given":"John","email":"","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":957906,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}} ,{"id":70275614,"text":"70275614 - 2026 - Population trends of dabbling ducks wintering in the alluvial valleys of Arkansas and Mississippi","interactions":[],"lastModifiedDate":"2026-05-19T15:50:12.562622","indexId":"70275614","displayToPublicDate":"2026-03-23T09:41:43","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3766,"text":"Wildlife Biology","active":true,"publicationSubtype":{"id":10}},"title":"Population trends of dabbling ducks wintering in the alluvial valleys of Arkansas and Mississippi","docAbstract":"Population abundances, distributions, and compositions across a diversity of taxa are changing, partly as a consequence of human-induced global modifications. Although linking population fluctuations to anthropogenic-induced alterations can be challenging, it is increasingly clear that long-term monitoring is critical to understanding changing populations. For waterfowl, concerns over recent declines in breeding populations or possible redistribution from using traditional wintering grounds for some species support continued monitoring of regional populations. To further understand population trends on traditional wintering grounds, we examined abundance trends over time within the Mississippi and Arkansas portions of the Mississippi Alluvial Valley, using two sources of data: systematic aerial surveys and citizen science data. We found great annual variability in rates of population change (r ranging from −1.04 to 0.71) in five species of dabbling ducks. Despite this annual variation, green-winged teal Anas carolinensis, mallards Anas platyrhynchos, northern pintail Anas acuta, and northern shoveler Spatula clypeata showed no significant trends in population size over approximately 15 years in Mississippi and Arkansas, but gadwall Mareca strepera showed a 4% annual increase in the citizen science data for Mississippi. Despite substantial variation in annual abundance, the timing of peak abundance was remarkably consistent from year to year, with peaks typically occurring in January. Our results demonstrate that autumn–winter population numbers of dabbling ducks can be quite variable interannually, but they lack a consistent trend in the Mississippi Alluvial Valley during the past two decades. Going forward, investigation into how citizen science data could be leveraged to increase the precision of trends within this landscape might be of benefit, and sampling efforts could perhaps be added towards the latter portion of the wintering period. As populations continue to adjust in a changing world, maintaining monitoring surveys in regions important to waterfowl is an effective and important means of evaluating trends.
","language":"English","publisher":"Nordic Society Oikos","doi":"10.1002/wlb3.01572","usgsCitation":"Boudreau, M.R., Havens, H., Leach, B., Naylor, L., Callicutt, J.T., Pearse, A.T., and Davis, J.B., 2026, Population trends of dabbling ducks wintering in the alluvial valleys of Arkansas and Mississippi: Wildlife Biology, v. 2026, no. 3, e01572, 13 p., https://doi.org/10.1002/wlb3.01572.","productDescription":"e01572, 13 p.","ipdsId":"IP-179403","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":504002,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":504201,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/wlb3.01572","text":"Publisher Index Page"}],"country":"United States","state":"Arkansas, Illinois, Kentucky, Louisiana, Mississippi, Missouri, Tennessee","otherGeospatial":"Mississippi Alluvial Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -91.81486038859579,\n 40.41852400825991\n ],\n [\n -91.81486038859579,\n 29.387847147895826\n ],\n [\n -89.06741949863552,\n 29.387847147895826\n ],\n [\n -89.06741949863552,\n 40.41852400825991\n ],\n [\n -91.81486038859579,\n 40.41852400825991\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"2026","issue":"3","noUsgsAuthors":false,"publicationDate":"2026-03-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Boudreau, Melanie R. 0000-0002-6280-5598","orcid":"https://orcid.org/0000-0002-6280-5598","contributorId":371124,"corporation":false,"usgs":false,"family":"Boudreau","given":"Melanie","middleInitial":"R.","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":961067,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Havens, Houston","contributorId":371125,"corporation":false,"usgs":false,"family":"Havens","given":"Houston","affiliations":[{"id":78821,"text":"Mississippi Department of Wildlife, Fisheries, and Parks","active":true,"usgs":false}],"preferred":false,"id":961068,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Leach, Brett","contributorId":356397,"corporation":false,"usgs":false,"family":"Leach","given":"Brett","affiliations":[{"id":12717,"text":"Louisiana Department of Wildlife and Fisheries","active":true,"usgs":false}],"preferred":false,"id":961069,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Naylor, Luke W.","contributorId":351070,"corporation":false,"usgs":false,"family":"Naylor","given":"Luke W.","affiliations":[{"id":37007,"text":"Arkansas Game and Fish Commission","active":true,"usgs":false}],"preferred":false,"id":961070,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Callicutt, James T.","contributorId":371126,"corporation":false,"usgs":false,"family":"Callicutt","given":"James","middleInitial":"T.","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":961071,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Pearse, Aaron T. 0000-0002-6137-1556 apearse@usgs.gov","orcid":"https://orcid.org/0000-0002-6137-1556","contributorId":1772,"corporation":false,"usgs":true,"family":"Pearse","given":"Aaron","email":"apearse@usgs.gov","middleInitial":"T.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":961072,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Davis, J. Brian 0000-0002-2598-3192","orcid":"https://orcid.org/0000-0002-2598-3192","contributorId":371127,"corporation":false,"usgs":false,"family":"Davis","given":"J.","middleInitial":"Brian","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":961073,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70274296,"text":"70274296 - 2026 - Decadal shifts in groundwater age detected by environmental tracers across California, USA","interactions":[],"lastModifiedDate":"2026-03-24T15:57:13.026731","indexId":"70274296","displayToPublicDate":"2026-03-23T08:53:06","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Decadal shifts in groundwater age detected by environmental tracers across California, USA","docAbstract":"Groundwater age offers important insight into recharge, storage, and contamination risk. Although models predict age changes can be driven by pumping and climate variability, direct observational evidence remains limited. Here, we analyzed paired environmental tracer suites (tritium, carbon-14, and tritiogenic helium-3) collected a decade apart from 268 wells across California to assess the prevalence of groundwater age transience. Travel-time distribution models and statistical tests indicated age transience at 29% of sites, occurring most often in agricultural regions, such as the San Joaquin Valley and Southern Coast Ranges, where large carbon-14 changes coincided with substantial nitrate and chloride shifts. Sites with tritiogenic helium-3 data showed more frequent age transience, underscoring the value of multi-tracer data sets. These results provide the first regional evidence of widespread groundwater age change and a method for detecting changing water balances with implications for groundwater sustainability and water quality.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2025GL119794","usgsCitation":"Jurgens, B.C., and Levy, Z.F., 2026, Decadal shifts in groundwater age detected by environmental tracers across California, USA: Geophysical Research Letters, v. 53, no. 6, e2025GL119794, 12 p., https://doi.org/10.1029/2025GL119794.","productDescription":"e2025GL119794, 12 p.","ipdsId":"IP-151777","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":501677,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2025gl119794","text":"Publisher Index Page"},{"id":501458,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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Spatial variations and connectivity in the sources and streambed storage of soft, fine-grained (silt and clay) sediment and related sediment-bound P (sed-P) were examined, from first-order ephemeral channels to a downstream water-monitoring station. Analysis included field inventories, a channel corridor sediment and sed-P budget applied to an extended channel network, and geochemical fingerprinting. Corridor inventories included mass wasting along valley sides, eroding streambanks, gullying along perennial and ephemeral channels, and streambed storage volumes in perennial reaches; each converted to masses. Erosion results estimate 7400 Mg/yr of fine-grained sediment, similar to the mean annual suspended sediment load of 5400 Mg/yr. Corridor erosion contributed 7200 kg/yr of sed-P, less than the mean annual particulate-P load of 10,000 kg/yr P. Soft sediment storage was 1400 Mg, with 1500 kg sed-P. Apportionment of soft sediment as streambank sourced was spatially variable, contributing ≥95 % in high order reaches with high storage and as little as 20 % in upstream reaches, where gully, crop, and forest provided the remainder. Two nearby tributaries showed similarity in the predominance of streambank-sourced material in stored soft sediment but differences in geomorphic setting affected its spatial distribution. The results of this study show the importance of including corridor erosion as a source of sediment and sed-P in agricultural basins, which can be helpful in decision-making regarding conservation practices.
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2026 - Quantitative microbial risk assessment with microbial source tracking for enteric pathogens in southwest Wisconsin private wells","interactions":[],"lastModifiedDate":"2026-03-24T16:36:58.393451","indexId":"70274259","displayToPublicDate":"2026-03-22T09:32:02","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2262,"text":"Journal of Environmental Quality","active":true,"publicationSubtype":{"id":10}},"title":"Quantitative microbial risk assessment with microbial source tracking for enteric pathogens in southwest Wisconsin private wells","docAbstract":"Private wells supply drinking water for many households, and their contamination by fecal microbes presents a risk of acute gastrointestinal illness (AGI). Risk is thought to vary by contaminating fecal source, but specific associations with fecal source are unknown for most private wells in the United States. This study characterizes AGI risk in Grant, Iowa, and Lafayette counties in southwestern Wisconsin. AGI risk was assessed for 10 viral, bacterial, and protozoan pathogens detected in private wells using quantitative microbial risk assessment. Exposure assessment was based on sampling 138 private wells in the study area, and risk was associated with fecal source by microbial source tracking (MST). Median Monte Carlo estimates indicated 4450 AGI cases/year in the study area associated with drinking water from contaminated private wells (95% confidence interval: 90–37,990). Most annual cases were associated with detection of human MST markers, including median estimates of 2550 associated with only human markers and 880 with human and livestock MST markers detected together. Note that 50 AGI cases/year were associated with detection of only livestock markers, and nearly 1000 cases were estimated to occur in the absence of detectable MST markers. This study characterizes AGI risk for households served by private wells in southwestern Wisconsin. It illustrates that human fecal sources can predominate risk associated with drinking water from private wells, even in a rural region characterized by substantial agricultural activity. MST can characterize the relationship between risk and fecal source; contributions of fecal sources to risk cannot be assumed from land use.","language":"English","publisher":"Wiley","doi":"10.1002/jeq2.70162","usgsCitation":"Burch, T., Stokdyk, J.P., Heffron, J., Opelt, S.A., and Firnstahl, A.D., 2026, Quantitative microbial risk assessment with microbial source tracking for enteric pathogens in southwest Wisconsin private wells: Journal of Environmental Quality, v. 55, no. 2, e70162, 14 p., https://doi.org/10.1002/jeq2.70162.","productDescription":"e70162, 14 p.","ipdsId":"IP-183588","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":501682,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jeq2.70162","text":"Publisher Index Page"},{"id":501473,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","otherGeospatial":"southwestern Wisconsin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -91.20734382695724,\n 43.496849558166275\n ],\n [\n -91.20734382695724,\n 42.51846762737475\n ],\n [\n -89.84773226925358,\n 42.51846762737475\n ],\n [\n -89.84773226925358,\n 43.496849558166275\n ],\n [\n -91.20734382695724,\n 43.496849558166275\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"55","issue":"2","noUsgsAuthors":false,"publicationDate":"2026-03-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Burch, Tucker R.","contributorId":195801,"corporation":false,"usgs":false,"family":"Burch","given":"Tucker R.","affiliations":[],"preferred":false,"id":957298,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stokdyk, Joel P. 0000-0003-2887-6277 jstokdyk@usgs.gov","orcid":"https://orcid.org/0000-0003-2887-6277","contributorId":193848,"corporation":false,"usgs":true,"family":"Stokdyk","given":"Joel","email":"jstokdyk@usgs.gov","middleInitial":"P.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":957299,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Heffron, Joe","contributorId":339799,"corporation":false,"usgs":false,"family":"Heffron","given":"Joe","email":"","affiliations":[],"preferred":false,"id":957300,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Opelt, Sarah A.","contributorId":300168,"corporation":false,"usgs":false,"family":"Opelt","given":"Sarah","middleInitial":"A.","affiliations":[],"preferred":false,"id":957301,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Firnstahl, Aaron D. 0000-0003-2686-7596 afirnstahl@usgs.gov","orcid":"https://orcid.org/0000-0003-2686-7596","contributorId":168296,"corporation":false,"usgs":true,"family":"Firnstahl","given":"Aaron","email":"afirnstahl@usgs.gov","middleInitial":"D.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":957302,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70274294,"text":"70274294 - 2026 - Net CO2 emissions from dry inland waters persist in the presence of vegetation","interactions":[],"lastModifiedDate":"2026-03-24T15:12:00.537","indexId":"70274294","displayToPublicDate":"2026-03-21T10:00:33","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1836,"text":"Global Biogeochemical Cycles","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Net CO2 emissions from dry inland waters persist in the presence of vegetation","title":"Net CO2 emissions from dry inland waters persist in the presence of vegetation","docAbstract":"Many inland waters are shrinking due to shifts in climate and water diversion for human uses. As they dry out, their exposed sediments emit large amounts of carbon dioxide (CO2) to the atmosphere. However, current global estimates of CO2 emissions from dry inland waters are derived exclusively from bare sediment dark-chamber measurements that do not account for the colonization of desiccated areas by vegetation. To understand the impact of vegetation on CO2 emissions from dry sediments, we analyzed 164 dry inland water bodies across five climatic regions and five inland water body types (lakes, ponds, reservoirs, streams and wetlands). On average, within vegetated zones, vegetation occupied 47 ± 35% in measured biomass quadrants. Light-induced decreases in instantaneous CO2 emissions in vegetated dry sediments were lower (mean ± SD = −3.7 ± 12.9 mmol CO2 m−2 hr−1) than increases during dark conditions (14.7 ± 20.1 mmol CO2 m−2 hr−1). Diel (24-hr) CO2 emissions from dry, vegetated sediments (mean ± SD = 100 ± 261 mmol CO2 m−2 d−1) were 25% lower than in bare sediments (133 ± 245 mmol CO2 m−2 d−1). These results indicate that vegetation can partially off-set sediment respiration, although the magnitude of this effect is insufficient to switch dry beds from net sources to net sinks of carbon.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2025GB008801","usgsCitation":"Sharma, K., Brothers, S., Bernal, S., Catalán, N., Keller, P., Koschorreck, M., Kosten, S., Leigh, C., von Schiller, D., Pastor, A., Larrañaga, A., Ari, A., Camacho-Santamans, A., Grinham, A., Lupon, A., Linkhorst, A., Elosegi, A., Obrador, B., Eyre, B.D., Trochine, C., Muniz, C.C., Feijoo, C., Duvert, C., Moreno-Ostos, E., Garcia, E.J., Oliveria, E.S., Cuassolo, F., Fernandez, H.R., Yeo, J., Oakes, J., Paranaíba, J.R., Pegg, J., Anselmo, J., Montes-Perez, J.J., van den Heuvel, L., Ran, L., Wilkinson, L.L., Gomez-Gener, L., Arroita, M., Shanafield, M., Gultemirian, M.L., Arce, M.I., Cobo, M., Sanchez-Montoya, M.M., Barros, N., Wells, N., Karakaya, N., Erturk Ari, P., Struik, Q., Aben, R., Rimas, R., Kumar, S., Bansal, S., Sarkar, S., Rodriguez-Gomez, S., Huang, T., Silverthorn, T., Datry, T., Diaz Villanueva, V., and Marce, R., 2026, Net CO2 emissions from dry inland waters persist in the presence of vegetation: Global Biogeochemical Cycles, v. 40, no. 3, e2025GB008801, 17 p., https://doi.org/10.1029/2025GB008801.","productDescription":"e2025GB008801, 17 p.","ipdsId":"IP-180179","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":501672,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2025gb008801","text":"Publisher Index Page"},{"id":501450,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"40","issue":"3","noUsgsAuthors":false,"publicationDate":"2026-03-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Sharma, K.","contributorId":367754,"corporation":false,"usgs":false,"family":"Sharma","given":"K.","affiliations":[],"preferred":false,"id":957646,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brothers, 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The sulfates range in composition from barite to celestine and locally occur with sparse sulfide minerals. We investigate the origin of sulfur enrichment and the occurrence of sulfur-bearing minerals in the Mountain Pass carbonatite with in-situ sulfur isotope and mineral chemistry. Barite cores with δ34S of 1 to 3‰ do not coexist with sulfides, whereas celestine rims with δ34S of > 3‰ are associated with sulfides with δ34S < -10‰. We propose a model in which sulfur-bearing sediments were subducted during episodes of plate convergence in the Mojave Province that preceded Mountain Pass magmatism. Metasomatism of the overlying mantle by melts derived from the subducted sediments generated an unusually carbon- and sulfur-rich source to yield carbonatite magmas. Sulfur from primary carbonatite magmas and ~ 1 to 7% sulfur from subducted sediment melts yielded a slightly enriched δ34S composition (relative to depleted mantle δ34S of -1‰) for early crystallizing barite. Celestine rims on magmatic barite cores formed at low, hydrothermal temperatures (< 350 °C) based on S isotope thermometry for equilibrium celestine-galena and celestine-pyrite pairs. The sparse sulfides in the carbonatite stock are not in equilibrium with the primary barite cores and therefore do not permit S isotope thermometry estimates of magmatic temperatures. The S/Se ratios of sulfide minerals (> 3,400) typically exceed primitive mantle values (S/Se of 3,340), also consistent with their derivation from hydrothermal fluids. Trace occurrences of sulfide and sulfate minerals in alkaline silicate stocks related to the carbonatite stock have similar δ34S compositions and yield similarly low formation temperatures, suggesting regionally extensive and chemically similar sulfur-bearing hydrothermal fluids that imparted lithologically diverse rocks with a consistent sulfur isotope fingerprint.
","language":"English","publisher":"Springer Nature","doi":"10.1007/s00126-026-01438-3","usgsCitation":"Benson, E.K., Watts, K., Pribil, M.J., Thompson, J.M., and Lowers, H.A., 2026, Insights into Mountain Pass carbonatite formation from in-situ sulfur isotopes and geochemistry of sulfate and sulfide minerals: Mineralium Deposita, 25 p., https://doi.org/10.1007/s00126-026-01438-3.","productDescription":"25 p.","ipdsId":"IP-179323","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":501676,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s00126-026-01438-3","text":"Publisher Index Page"},{"id":501457,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Nevada","otherGeospatial":"Mountain Pass","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -115.24550849872043,\n 35.963211671328224\n ],\n [\n -115.24550849872043,\n 34.54590209348751\n ],\n [\n -114.62637079295725,\n 34.54590209348751\n ],\n [\n -114.62637079295725,\n 35.963211671328224\n ],\n [\n -115.24550849872043,\n 35.963211671328224\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","edition":"Online First","noUsgsAuthors":false,"publicationDate":"2026-03-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Benson, Erin Kay 0000-0003-3166-6043","orcid":"https://orcid.org/0000-0003-3166-6043","contributorId":346098,"corporation":false,"usgs":true,"family":"Benson","given":"Erin","email":"","middleInitial":"Kay","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":957624,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Watts, Kathryn E. 0000-0002-6110-7499","orcid":"https://orcid.org/0000-0002-6110-7499","contributorId":204344,"corporation":false,"usgs":true,"family":"Watts","given":"Kathryn E.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":957625,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pribil, Michael J. 0000-0003-4859-8673 mpribil@usgs.gov","orcid":"https://orcid.org/0000-0003-4859-8673","contributorId":141158,"corporation":false,"usgs":true,"family":"Pribil","given":"Michael","email":"mpribil@usgs.gov","middleInitial":"J.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":957626,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thompson, Jay M. 0000-0003-3322-0870","orcid":"https://orcid.org/0000-0003-3322-0870","contributorId":329664,"corporation":false,"usgs":true,"family":"Thompson","given":"Jay","middleInitial":"M.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":957627,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lowers, Heather A. 0000-0001-5360-9264 hlowers@usgs.gov","orcid":"https://orcid.org/0000-0001-5360-9264","contributorId":191307,"corporation":false,"usgs":true,"family":"Lowers","given":"Heather","email":"hlowers@usgs.gov","middleInitial":"A.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":957628,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70274251,"text":"sir20265126 - 2026 - Estimation of impounded sediment volume in the Similkameen River upstream of Enloe Dam, Okanogan County, Washington","interactions":[],"lastModifiedDate":"2026-03-23T18:16:34.529968","indexId":"sir20265126","displayToPublicDate":"2026-03-20T12:25:00","publicationYear":"2026","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":"2026-5126","displayTitle":"Estimation of Impounded Sediment Volume in the Similkameen River upstream of Enloe Dam, Okanogan County, Washington","title":"Estimation of impounded sediment volume in the Similkameen River upstream of Enloe Dam, Okanogan County, Washington","docAbstract":"The Enloe Dam was built in 1920 for hydropower generation and impounds a steep-banked, narrow reach of the Similkameen River in north-central Washington. During the subsequent century, sediment from the Similkameen River watershed, which includes historical mining operations, accumulated within Enloe Dam’s impoundment. Enloe Dam ceased hydropower production in 1958 and is currently under consideration for removal, but there are concerns that the remobilization of sediments may have harmful impacts on downstream water quality. To complement previously published analyses of heavy metal concentrations within sediments and assess the total volume that may be transported following dam removal, this report presents estimates of the volume of sediment trapped behind Enloe Dam which was measured in 2020. The volume of sediment was estimated by comparing a bathymetric survey, collected using an acoustic Doppler continuous profiler, and a survey of the bedrock-sediment interface, collected using a continuous resistivity profiler.
The study area spanned a 2.6-kilometer reach of the Similkameen River upstream from Enloe Dam. The volume of impounded sediment was calculated in 2020 by subtracting the elevation of the bedrock-sediment interface measured using the continuous resistivity profiler from a bathymetric surface measured by the acoustic Doppler current profiler. In 2020, the estimated volume of sediment impounded by Enloe Dam was 2.17±0.04 million cubic meters (Mm3) compared to 1.37 Mm3 measured in 1971. This equates to a deposition rate of approximately 16,300 cubic meters per year from 1971 to 2020. Continuous resistivity profiles revealed that bedrock within Enloe Dam’s impoundment was deepest (about 20 m) in the southern, downstream end of the profiles and shallowest (less than 5 m) in the northern upstream end of the profiles.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20265126","collaboration":"Prepared in cooperation with the Confederated Tribes of the Colville Reservation","usgsCitation":"Headman, A.O., Wilkerson, O.A., Curran, C.A., and Gendaszek, A.S., 2026, Estimation of impounded sediment volume in the Similkameen River upstream of Enloe Dam, Okanogan County, Washington: U.S. Geological Survey Scientific Investigations Report 2026–5126, 24 p., https://doi.org/10.3133/sir20265126.","productDescription":"Report: v, 24 p.; 2 Data Releases","numberOfPages":"24","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-144072","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":501399,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_119320.htm","linkFileType":{"id":5,"text":"html"}},{"id":501344,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P93NUBE8","text":"USGS data release","linkHelpText":"Continuous resistivity profiling (CRP) in the Similkameen River above Enloe Dam, Okanogan County, Washington"},{"id":501338,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2026/5126/coverthb.jpg"},{"id":501339,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2026/5126/sir20265126.pdf","size":"10 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2026-5126 PDF"},{"id":501343,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9VI2ZIX","text":"USGS data release","linkHelpText":"Sediment volume and bedrock of the Similkameen River above Enloe Dam near Oroville, Washington"},{"id":501340,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20265126/full","linkFileType":{"id":5,"text":"html"},"description":"SIR 2026-5126 HTML"},{"id":501341,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2026/5126/sir20265126.XML","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2026-5126 XML"},{"id":501342,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2026/5126/images/"}],"country":"United States","state":"Washington","county":"Okanogan County","otherGeospatial":"lower Similkameen River upstream from Enloe Dam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -119.52897239705791,\n 48.98921327416954\n ],\n [\n -119.52897239705791,\n 48.95605821757019\n ],\n [\n -119.49191341839283,\n 48.95605821757019\n ],\n [\n -119.49191341839283,\n 48.98921327416954\n ],\n [\n -119.52897239705791,\n 48.98921327416954\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Washington Water Science Center
U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402
Pervasive chemical weathering on stable cratons may form thick regoliths and elemental enrichment, but constraining the age of regolith formation is challenging. In this study we utilize multiple geochronological techniques on different minerals from the world-class Mount Weld rare earth element (REE) deposit, formed by lateritic weathering of a carbonatite, to constrain the age of formation and provide insight into landscape evolution. The oldest dates, ca. 100 to 38 Ma, are from Lu-Hf dating of churchite [HREE(PO4)·2(H2O)], a heavy REE phosphate mineral. Growth bands on individual minerals show a younging outwards. 40Ar/39Ar geochronology of cryptomelane [K(Mn4+,Mn2+)₈O₁₆] yielded dates from ca. 40 to 27 Ma. Similarly, (U-Th)/He geochronology of goethite [FeO(OH)] yielded dates ranging from ca. 45 to 19 Ma.
Integrating results into regional constraints, suggests 1) churchite formed by mineral saturation in a karst-like setting below the water table from ca. 100 to 40 Ma, 2) with minor uplift and erosion, cryptomelane and goethite formed at or near the water table between ca. 45 and 19 Ma, 3) after ca. 15 to 10 Ma chemical weathering within the profile had ended. Other studies document that the region experienced minimal uplift and a wet, warm climate from ca. 100 Ma to 15 Ma. These conditions and the high carbonate content of the carbonatite promote extensive chemical weathering, a deep weathering profile, and the preservation of the weathered section. This study highlights the use of multiple geochronological techniques utilizing different minerals to provide insight into how laterites form and to constrain the timing and history of the formation of this important mineral deposit.
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We present an assessment of water limitation, defined as the monthly balance (difference) between water supply (ws) and human consumptive water use (wc), for the conterminous United States (CONUS) during water years 2010–2020. We estimate that 26.7 million Americans, 8% of CONUS population, live in areas with chronic high or severe water limitation. Although ws greatly exceeds wc at the CONUS scale, water is limited locally or regionally due to spatial and temporal patterns in climate and wc. Our water limitation metric, the monthly supply and use index (SUI), peaked in 2012 during a widespread drought when 38% of the CONUS land area experienced elevated water stress. The central and Southwestern U.S. experienced the highest SUI due to the combination of low ws and high wc, especially for irrigation. Spatial overlays of SUI and fish habitat ranges, including those of conservation concern, revealed that several species had notable proportions of their habitat exposed to high or severe water limitation during spawning season over the modeled time period, especially the Arkansas River shiner. ws was calculated from two CONUS, physically-based, hydrologic models while wc was calculated from three CONUS models of water use for crop irrigation, thermoelectric power generation, and public supply. The ws and wc values were routed through a stream network and compared to calculate water limitation and SUI for human populations and fish species at the scale of 12-digit hydrologic unit codes. Evaluation of water availability at higher spatial and temporal resolution promotes more comprehensive analyses of the drivers of water availability and can be combined with complementary studies of water quality and water limiting thresholds to better understand the limitations on water availability.
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Accurate classification of streams as perennial or nonperennial is important for a variety of land and water resource management decisions. However, resource managers are challenged with how to reconcile different streamflow permanence information to determine if it is sufficient to avoid field verification, which can be prohibitively costly and time consuming. The study evaluates two datasets for the Pacific Northwest Region, U.S., the National Hydrography Dataset Plus High Resolution (NHDPlus HR) hydrographic classification and the PRObability of Streamflow PERmanence (PROSPER) model output, which differ in structure, output type, and temporal and spatial resolution. The framework includes a two-level evaluation that involves assessing agreement between the two datasets and evaluating the reliability of the two datasets. Summarized at a regional scale, the two datasets agree for 68% of flowlines with higher agreement for nonperennial streams. PROSPER nonperennial stream classifications may be considered generally reliable in arid regions relative to other ecoregions within the Pacific Northwest study area but less reliable for high elevation mountain regions and larger streams and rivers. More than 75% of NHDPlusHR classifications may be considered reliable when evaluating reliability based on approximate climate conditions associated with the year that the NHDPlus HR classification was assigned. The decision procedure is reproducible, flexible to varying criteria of end user applications, and is intended to help provide cost saving opportunities for land managers by providing information for more strategic field verification of streamflow class determination based on available yet imperfect data sources.
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2026 - Adaptive capacity of freshwater organisms in North America: Current understanding and future applications","interactions":[],"lastModifiedDate":"2026-03-24T14:51:37.697368","indexId":"70274282","displayToPublicDate":"2026-03-20T09:41:09","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":23620,"text":"Global Change Biology Communications","active":true,"publicationSubtype":{"id":10}},"title":"Adaptive capacity of freshwater organisms in North America: Current understanding and future applications","docAbstract":"Freshwater species are increasingly threatened by climate change, yet our ability to assess their vulnerability remains incomplete. Typically, climate change vulnerability assessments (CCVAs) evaluate three components: exposure, sensitivity, and adaptive capacity. Adaptive capacity, defined as the ability of a species to adjust to changing conditions, provides critical insight into how species may persist under future scenarios and can strengthen conservation planning by highlighting opportunities for resilience and targeted management strategies. Trait-based approaches offer a promising path for managers to operationalize adaptive capacity by identifying measurable biological and ecological traits that influence climate change response strategies. However, these insights are rarely integrated into broader vulnerability frameworks that support conservation decision making. We build on previous research to synthesize current understanding of adaptive capacity for three freshwater taxa in North America: fishes, mussels, and crayfishes. Our objectives were to: (1) assess the relevance of adaptive capacity factors for fishes, mussels, and crayfishes; (2) identify key opportunities and gaps in linking trait-based information into adaptive capacity assessments; and (3) illustrate how incorporating adaptive capacity can enhance management decisions for freshwater species under climate change. We used an expert workshop, literature review, and case studies to identify relevant adaptive capacity factors, assess available information, and evaluate inclusion in management contexts. We found that all three taxa had sufficient information to inform adaptive capacity assessments. In addition to existing adaptive capacity factors, we identified Morphology as an important yet underutilized cross-cutting diagnostic category when information was limited. By explicitly linking trait-based approaches with adaptive capacity frameworks, we offer practical guidance for improving climate adaptation strategies and prioritizing management actions for freshwater biodiversity under accelerating global change.
","language":"English","publisher":"Wiley","doi":"10.1002/gcb4.70009","usgsCitation":"Embke, H., Alofs, K., Bunnell, D., Caudill, C.M., Chu, C., Dunn, C.G., Fogelman, K., Gardner, S.T., Hook, T.O., Jackson, S.A., Keefer, M., Koenigbauer, S.T., LeDee, O.E., Ludsin, S., Lynch, A., Myers, B., Nyboer, E.A., Seaborn, T., Suski, C., Thurman, L., Walters, A.W., and Westhoff, J.T., 2026, Adaptive capacity of freshwater organisms in North America: Current understanding and future applications: Global Change Biology Communications, v. 1, no. 2, e70009, 21 p., https://doi.org/10.1002/gcb4.70009.","productDescription":"e70009, 21 p.","ipdsId":"IP-171922","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":65882,"text":"Midwest Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":501669,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/gcb4.70009","text":"Publisher Index Page"},{"id":501447,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"North America","volume":"1","issue":"2","noUsgsAuthors":false,"publicationDate":"2026-03-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Embke, Holly Susan 0000-0002-9897-7068","orcid":"https://orcid.org/0000-0002-9897-7068","contributorId":358337,"corporation":false,"usgs":true,"family":"Embke","given":"Holly Susan","affiliations":[{"id":65882,"text":"Midwest Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":957572,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Alofs, Karen 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Four vireo surveys were completed between April 16 and July 2, 2025, and three flycatcher surveys were completed between May 21 and July 2, 2025. We found 11 territorial male vireos, 4 of which were confirmed as paired, and 3 transient vireos. Of the 11 territorial vireos, 6 were detected along the Los Angeles River, 3 along Haskell Creek, and 2 along Bull Creek. Forty-three percent of vireos were detected in habitat characterized as mixed willow riparian, and most vireos were detected in habitat with greater than 50-percent native plant cover. No flycatchers were observed in the Sepulveda Dam project area in 2025.
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U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819