In 1921, the U.S. Geological Survey (USGS) established a streamgage on the Colorado River at Lees Ferry, Arizona, to monitor the river’s flow and level as it enters Grand Canyon. The following year, the seven States encompassing the Colorado River Basin (Arizona, California, Colorado, Nevada, New Mexico, Utah, and Wyoming) negotiated the 1922 Colorado River Compact to regulate distribution of the river’s waters between them. The compact divided the basin into two regions—the Upper Basin and the Lower Basin—and established the dividing point between them about one mile downstream from Lees Ferry, just below the confluence of the Colorado and Paria Rivers.
The Colorado River at Lees Ferry streamgage (USGS station 09380000) is one of the most important streamgages in the United States because it is used to measure how much water passes from the Upper Basin to the Lower Basin through Glen Canyon Dam. The dam, constructed between 1956 and 1966, generates hydropower and stores water in Lake Powell reservoir, which is used to provide Upper and Lower Basin states with the water allotted to them by the compact. Lower Basin states depend on releases from the dam to receive their allotments. The Lees Ferry streamgage, located less than 16 miles downstream from Glen Canyon Dam, produces publicly available, real-time water data that allows the Colorado River’s streamflow below the dam to be monitored.
Most years, the Colorado River runs dry before reaching its historical terminus at the Gulf of California in Mexico, so measuring and monitoring the river at Lees Ferry is critical for the Lower Basin ecosystems, agricultural resources, and municipal industries that rely on the river’s every drop. Additionally, Grand Canyon river guides and recreationalists depend on water level data from the Lees Ferry streamgage to determine when to run rapids and camp on sandbars. Streamflow and water-quality data collected at Lees Ferry are also important for monitoring the health of the Colorado River’s aquatic life because some species, including fish and macroinvertebrates, require certain water conditions to survive, reproduce, and spawn.
The Arizona Water Science Center is responsible for maintaining and collecting water data from the Lees Ferry streamgage. The Arizona Water Science Center is a branch of the USGS dedicated to providing high quality, impartial water data to resource managers and the public for their use in understanding and managing critical water resources in Arizona and the Southwest.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20263002","usgsCitation":"Cooney, K., 2026, Arizona Water Science Center activities at Lees Ferry, Arizona: U.S. Geological Survey Fact Sheet 2026–3002, 4 p., https://doi.org/10.3133/fs20263002.","productDescription":"4 p.","numberOfPages":"4","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-168012","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":505175,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_119483.htm","linkFileType":{"id":5,"text":"html"}},{"id":504982,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2026/3002/fs20263002.XML","linkFileType":{"id":8,"text":"xml"},"description":"FS 2026–3002 XML"},{"id":504981,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/fs20263002/full","linkFileType":{"id":5,"text":"html"},"description":"FS 2026–3002 HTML"},{"id":504983,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2026/3002/images"},{"id":504980,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2026/3002/fs20263002.pdf","text":"Report","size":"4.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2026–3002 PDF"},{"id":504979,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2026/3002/coverthb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Colorado River, Lees Ferry","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.37564572779584,\n 36.99849467623304\n ],\n [\n -111.65910481382933,\n 36.99849467623304\n ],\n [\n -111.65910481382933,\n 36.827943533328465\n ],\n [\n -111.37564572779584,\n 36.827943533328465\n ],\n [\n -111.37564572779584,\n 36.99849467623304\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Arizona Water Science Center
U.S. Geological Survey
520 N. Park Avenue, Suite 221
Tucson, AZ 85719
The U.S. Geological Survey monitors a suite of intertidal black abalone (Haliotis cracherodii) sites at San Nicolas Island, California, in cooperation with the U.S. Navy, which owns the island. The nine rocky intertidal sites were established in 1980 to study the potential effect of translocated sea otters on the intertidal black abalone population at the island. The sites were monitored from 1981 to 1997, typically annually or biennially. Monitoring resumed in 2001 and has been completed annually thereafter. Since 2018, the work has been carried out by the U.S. Geological Survey Western Ecological Research Center. The study sites became particularly important, from a management perspective, after a virulent disease decimated black abalone populations throughout southern California beginning in the mid-1980s. The disease, withering syndrome (Candidatus Xenohaliotis californiensis), was first observed on San Nicolas Island in 1992 and over the next few years, withering syndrome reduced the black abalone population on San Nicolas Island by more than 99 percent. In 2009, the black abalone subsequently was listed as endangered under the Endangered Species Act.
The subject of this report is the 2023 survey of the sites and the status of the measured population in comparison to long-term patterns (based on data collected since 1981) at San Nicolas Island. Between the years 2000 and 2023, the total monitored black abalone population at the island has grown from roughly 200 to more than 2,500 abalone following disease-related decline. Since it was first consistently measured in 2005, the average distance between adjacent black abalone has decreased substantially from approximately 50 centimeters to less than 15 centimeters, indicating that abalone are sufficiently close together at several of the sites to reproduce successfully. The total abalone count in 2023 was 2,570, which was 19.2 percent higher than in 2022 and the highest count since 1993. All nine sites had higher counts in 2023 than in the previous year. Over 25 percent of the black abalone counted in 2023 were classified as recruits, defined as having a shell length of 3 centimeters or less.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20261015","collaboration":"Prepared in cooperation with the U.S. Navy","programNote":"Ecosystems Mission Area—Species Management Research Program","usgsCitation":"Kenner, M.C., and Yee, J.L., 2026, Black abalone surveys at Naval Base Ventura County, San Nicolas Island, California—2023 annual report: U.S. Geological Survey Open- File Report 2026–1015, 39 p., https://doi.org/10.3133/ofr20261015.","productDescription":"viii, 39 p","numberOfPages":"39","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-166956","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":504926,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2026/1015/ofr20261015.pdf","text":"Report","size":"10.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2026-1015 PDF"},{"id":504929,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2026/1015/images"},{"id":504928,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2026/1015/ofr20261015.XML","description":"OFR 2026-1015 XML"},{"id":504927,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20261015/full","linkFileType":{"id":5,"text":"html"},"description":"OFR 2026-1015 HTML"},{"id":504925,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2026/1015/coverthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Naval Base Ventura County, San Nicolas Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.58614016989262,\n 33.29639489260616\n ],\n [\n -119.41438488619465,\n 33.29639489260616\n ],\n [\n -119.41438488619465,\n 33.201948055912865\n ],\n [\n -119.58614016989262,\n 33.201948055912865\n ],\n [\n -119.58614016989262,\n 33.29639489260616\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
The 2023 monitoring of black abalone at San Nicolas Island shows strong signs of population recovery following the severe declines caused by withering syndrome in the 1990s. The island-wide summed count from the study sites reached 2,570 individuals—the highest since 1993—and increased nearly 20 percent from 2022, with higher numbers recorded at all nine study sites. Recruitment was particularly strong, with over a quarter of individuals classified as young abalone, and densities and spacing between individuals indicate increasing likelihood of successful reproduction. Although one historically important transect at Site 8 continues to show reduced numbers of larger adults despite high recruitment, the overall population trend across the island remains positive. Continued monitoring is important to track long-term recovery, habitat conditions, and potential risks.
","publicationDate":"2026-06-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Kenner, Michael C. 0000-0003-4659-461X","orcid":"https://orcid.org/0000-0003-4659-461X","contributorId":208151,"corporation":false,"usgs":true,"family":"Kenner","given":"Michael","email":"","middleInitial":"C.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":962194,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yee, Julie L. 0000-0003-1782-157X julie_yee@usgs.gov","orcid":"https://orcid.org/0000-0003-1782-157X","contributorId":3246,"corporation":false,"usgs":true,"family":"Yee","given":"Julie","email":"julie_yee@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":962195,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70276287,"text":"sir20255018B - 2026 - Summaries of goals, actions, and information needs by management entity","interactions":[],"lastModifiedDate":"2026-06-03T16:05:30.771038","indexId":"sir20255018B","displayToPublicDate":"2026-06-02T16:30:00","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":"2025-5018","chapter":"B","displayTitle":"Summaries of Goals, Actions, and Information Needs by Management Entity","title":"Summaries of goals, actions, and information needs by management entity","docAbstract":"The grasslands in the North Central region are managed by a diverse group of Federal, State, and Tribal agencies; nongovernmental organizations; partnerships; and private landowners. This chapter highlights these various grassland management entities, provides background information on their mission and organizational structure, and describes some of their key grassland management activities, including the way in which each entity engages private landowners in grassland management. Each section also describes emerging challenges and opportunities and high-level information needs. The review and synthesis of grassland management-related documents identified specific information needs, which are listed in an appendix to provide additional detail for anyone looking to collaborate with grassland management entities on shared interests in grassland management or research.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255018B","collaboration":"Prepared in cooperation with the University of Colorado Boulder","programNote":"Climate Adaptation Science Centers","usgsCitation":"Miller Hesed, C.D., and Yocum, H.M., eds., 2026, Summaries of goals, actions, and information needs by management entity, chap. B of Grassland management priorities for the North Central region: U.S. Geological Survey Scientific Investigations Report 2025–5018–B, 151 p., https://doi.org/10.3133/sir20255018B.","productDescription":"Report: xviii, 151 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-154862","costCenters":[{"id":477,"text":"North Central Climate Science Center","active":true,"usgs":true}],"links":[{"id":504886,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20255018A","text":"SIR 2025-5018-A","linkHelpText":"Background, Methods, Goals, Challenges, Opportunities, and Information Needs"},{"id":504714,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5018/B/coverthb.jpg"},{"id":504715,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5018/B/sir20255018-B.pdf","text":"Report","size":"61.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5018-B"},{"id":504716,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9PCQHA2","text":"USGS data release","description":"SIR 2025-5018-B data release","linkHelpText":"Broadly Shared Information Needs Among Grassland Managers in the North Central Region"}],"contact":"Regional Administrator, North Central Climate Adaptation Science Center
U.S. Geological Survey
University of Colorado - Boulder
Sustainability, Energy and Environment Community
4001 Discovery Dr., Suite 348
Boulder, CO 80303
This systematic literature review critically examines 162 articles on harmful algal bloom (HAB) modeling in riverine systems to uncover persistent gaps, redefine critical challenges, and propose trackable opportunities to advance future modeling efforts. Articles largely focused on site-specific applications (93%) across more than 80 rivers worldwide. Most modeled systems were large, eutrophic rivers with flow modifications or obstructions. Geographic clustering of modeled systems was pronounced, with South Korea accounting for 26% of articles, followed by Europe (25%), United States (21%), and China (12%). Modeling approaches were led by process-based models (59%), though use of data-driven models (37%) increased over time, reflecting advances in computing and monitoring technology. Modeling endpoints varied widely across the articles with many focused on gross measures of algal abundance and fewer representing more refined endpoints like algal toxins or community composition. Furthermore, inconsistent units and taxonomic resolution hindered comparability between models. Datasets used for model development and calibration typically spanned 5 years, with weekly to monthly sampling at 1–10 sites, though durations and site counts were positively skewed. Quantitative metrics of model skill were often absent and included a diverse set of metrics when reported. Across all models, nutrients, light availability, streamflow, algal physiological processes, and water temperature emerged as key predictors, though algal processes were rarely incorporated in data-driven models. Scenario analyses primarily were conducted with process-based models and addressed flow management, whereas forecasting applications were less common and typically used data-driven models. After almost 50 years of riverine HAB modeling, persistent challenges include underrepresentation of benthic habitats, neglect of side-channel and backwater influences, insufficient documentation of river features, and weak linkages between modeled endpoints and potential harms. Addressing these gaps through reporting of contextual information, models from other aquatic settings, benchmark datasets, and community-driven tools could advance riverine HAB modeling towards increased transferability and ultimately operational forecasts.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.watres.2026.126240","usgsCitation":"Murphy, J.C., Gorney, R.M., Lucas, L.V., Zwart, J.A., and Graham, J.L., 2026, Fifty years of riverine harmful algal bloom modeling: A global synthesis of approaches, challenges, and opportunities: Water Research, v. 303, 126240, 17 p., https://doi.org/10.1016/j.watres.2026.126240.","productDescription":"126240, 17 p.","ipdsId":"IP-183599","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":505494,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.watres.2026.126240","text":"Publisher Index Page"},{"id":505269,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"303","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Murphy, Jennifer C. 0000-0002-0881-0919 jmurphy@usgs.gov","orcid":"https://orcid.org/0000-0002-0881-0919","contributorId":4281,"corporation":false,"usgs":true,"family":"Murphy","given":"Jennifer","email":"jmurphy@usgs.gov","middleInitial":"C.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":962742,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gorney, Rebecca M. 0000-0003-4406-261X","orcid":"https://orcid.org/0000-0003-4406-261X","contributorId":317259,"corporation":false,"usgs":true,"family":"Gorney","given":"Rebecca","middleInitial":"M.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":962743,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lucas, Lisa V. 0000-0001-7797-5517 llucas@usgs.gov","orcid":"https://orcid.org/0000-0001-7797-5517","contributorId":260498,"corporation":false,"usgs":true,"family":"Lucas","given":"Lisa","email":"llucas@usgs.gov","middleInitial":"V.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":962744,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zwart, Jacob Aaron 0000-0002-3870-405X","orcid":"https://orcid.org/0000-0002-3870-405X","contributorId":237809,"corporation":false,"usgs":true,"family":"Zwart","given":"Jacob","email":"","middleInitial":"Aaron","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":962745,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Graham, Jennifer L. 0000-0002-6420-9335 jlgraham@usgs.gov","orcid":"https://orcid.org/0000-0002-6420-9335","contributorId":202923,"corporation":false,"usgs":true,"family":"Graham","given":"Jennifer","email":"jlgraham@usgs.gov","middleInitial":"L.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":962746,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70276451,"text":"70276451 - 2026 - Trends in subdaily to daily rainfall in Florida, 1990–2022","interactions":[],"lastModifiedDate":"2026-06-05T14:20:31.360639","indexId":"70276451","displayToPublicDate":"2026-06-01T09:17:40","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2344,"text":"Journal of Hydrometeorology","active":true,"publicationSubtype":{"id":10}},"title":"Trends in subdaily to daily rainfall in Florida, 1990–2022","docAbstract":"Changing rainfall patterns and intensifying rainfall extremes affect urban infrastructure and can increase flash-flood risk. Understanding how climate change has altered rainfall can support state and local agencies as they adapt and build resiliency. In this study, rainfall data from 23 weather stations in Florida were used to examine temporal and spatial trends over the period 1990–2022. Subdaily to daily rainfall events of durations 1, 2, 3, 6, 12, and 24 h were examined. A variety of statistical methods were applied to examine annual and seasonal trends, including quantile regression, extreme value analysis, run theory using the Mann–Kendall test, Sen–Theil slope, and Poisson and negative binomial tests, and threshold exceedance rates using generalized additive models. Using subdaily rainfall data posed challenges, including equipment failures, limited documentation of the quality assurance and control process, and potential measurement interferences. Results indicated that over 1990–2022, there was a decrease in hourly rainfall extremes but an increase at moderate quantiles. Overall, the number of rainfall events increased, particularly at shorter durations, but the mean total rainfall per event decreased. Additionally, the annual number of daily rainfall extremes showed more decreases than increases.
","language":"English","publisher":"American Meteorological Society","doi":"10.1175/JHM-D-25-0112.1","usgsCitation":"Haider, S., Irizarry-Ortiz, M.M., Obeysekera, J.T., Maran, A.C., Solaiman, T., and Johnston, B.D., 2026, Trends in subdaily to daily rainfall in Florida, 1990–2022: Journal of Hydrometeorology, v. 27, no. 6, p. 847-865, https://doi.org/10.1175/JHM-D-25-0112.1.","productDescription":"19 p.","startPage":"847","endPage":"865","ipdsId":"IP-175860","costCenters":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"links":[{"id":505091,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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0000-0002-7038-1668","orcid":"https://orcid.org/0000-0002-7038-1668","contributorId":371820,"corporation":false,"usgs":false,"family":"Obeysekera","given":"Jayantha","middleInitial":"T.","affiliations":[{"id":7017,"text":"Florida International University","active":true,"usgs":false}],"preferred":false,"id":962410,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Maran, Ana C.","contributorId":371821,"corporation":false,"usgs":false,"family":"Maran","given":"Ana","middleInitial":"C.","affiliations":[{"id":7036,"text":"South Florida Water Management District","active":true,"usgs":false}],"preferred":false,"id":962411,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Solaiman, Tarana","contributorId":371822,"corporation":false,"usgs":false,"family":"Solaiman","given":"Tarana","affiliations":[{"id":7036,"text":"South Florida Water Management 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We developed a transferable workflow to evaluate geothermal district systems that pair ground heat exchangers with seasonal underground thermal energy storage. Using standardized hourly loads for seven commercial buildings and a uniform cost framework, we simulated ten U.S. cities with a physics-based ground heat exchanger model, subsurface storage simulations, and economic assessment to isolate the roles of climate and hydrogeology. In cooling-dominated cities, underground thermal energy storage supplied the majority of annual cooling, cutting electricity use and summer peaks substantially while achieving levelized costs comparable to or below conventional chiller-boiler plants. In cooler climates, the storage share shrunk, required borefield size and costs rose, and levelized cost of energy increased nearly linearly with declining underground thermal energy storage fraction, indicating storage fraction as the primary economic lever. Sensitivity analysis showed capital risk dominated by borefield drilling and surface heating, ventilation, and air-conditioning and piping, with underground thermal energy storage costs secondary. This workflow provides a transparent foundation for site-specific design and screening of next-generation geothermal district energy systems.
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tomography","interactions":[],"lastModifiedDate":"2026-06-11T14:11:59.66026","indexId":"70276609","displayToPublicDate":"2026-05-29T09:06:00","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":18010,"text":"JGR Machine Learning and Computation","active":true,"publicationSubtype":{"id":10}},"title":"Localization of spatiotemporally heterogeneous subsurface flows using autoencoder-based deep learning framework for time-lapse self-potential tomography","docAbstract":"Self-potential (SP) monitoring has emerged as a valuable method for characterizing subsurface hydrogeological features and processes due to its sensitivity to fluid-induced electrokinetic effects. Despite advancements in SP inversion, challenges remain in imaging groundwater dynamics from SP activities due to complex hydrological settings and transient noise. In this study, a deep learning autoencoder (AE)-based framework is proposed for the spatiotemporal localization of subsurface fluid movement from time-lapse SP tomography. Temporal segments of time-lapse numerical inversions were first derived from long-term SP monitoring conducted from a floodplain site in Oak Ridge, Tennessee, known for active hyporheic exchange. Subsequently, AE models based on vision transformer (ViT), convolutional long short-term memory (ConvLSTM), convolutional neural network, and temporal convolutional network were individually trained and compared on the SP tomography segments for reconstruction performance. Finally, the reconstruction error over time serves as an anomaly score to identify moments of active SP variation, whereas spatial distributions of errors within these moments are analyzed to image and localize regions associated with anomalous subsurface fluid movement. The results demonstrate that ConvLSTM- and ViT-AE are most capable for the localization task with contrasting error distributions and consistent delineation of anomalies. Applying the method to both SP arrays parallel and perpendicular to the stream produced consistent anomaly zones near a fault or karst feature, validating the robustness and generalization of the approach. These results demonstrate the potential of the proposed framework as a scalable and interpretable tool for spatiotemporal analysis of subsurface flow dynamics in complex hydrogeological systems.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2025JH001208","usgsCitation":"Yin, H., Ikard, S., Rucker, D.F., Brooks, S.C., Dai, Z., Soltanian, M.R., and Carroll, K.C., 2026, Localization of spatiotemporally heterogeneous subsurface flows using autoencoder-based deep learning framework for time-lapse self-potential tomography: JGR Machine Learning and Computation, v. 3, no. 3, e2025JH001208, 18 p., https://doi.org/10.1029/2025JH001208.","productDescription":"e2025JH001208, 18 p.","ipdsId":"IP-181872","costCenters":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":505499,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2025jh001208","text":"Publisher Index Page"},{"id":505401,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Tennessee","city":"Oak Ridge","otherGeospatial":"East Fork Poplar Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.23833522694086,\n 36.016061123798806\n ],\n [\n -84.39831073419363,\n 36.016061123798806\n ],\n [\n -84.39831073419363,\n 35.94029924736503\n ],\n [\n -84.23833522694086,\n 35.94029924736503\n ],\n [\n -84.23833522694086,\n 36.016061123798806\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"3","issue":"3","noUsgsAuthors":false,"publicationDate":"2026-05-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Yin, Huichao 0000-0001-6172-5580","orcid":"https://orcid.org/0000-0001-6172-5580","contributorId":366938,"corporation":false,"usgs":false,"family":"Yin","given":"Huichao","affiliations":[{"id":12628,"text":"New Mexico State University","active":true,"usgs":false}],"preferred":false,"id":962818,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ikard, Scott 0000-0002-8304-4935","orcid":"https://orcid.org/0000-0002-8304-4935","contributorId":201775,"corporation":false,"usgs":true,"family":"Ikard","given":"Scott","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":962819,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rucker, Dale F. 0000-0002-8930-2747","orcid":"https://orcid.org/0000-0002-8930-2747","contributorId":294463,"corporation":false,"usgs":false,"family":"Rucker","given":"Dale","email":"","middleInitial":"F.","affiliations":[{"id":63573,"text":"hydroGEOPHYSICS, Inc.","active":true,"usgs":false}],"preferred":false,"id":962820,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brooks, Scott C. 0000-0002-8437-9788","orcid":"https://orcid.org/0000-0002-8437-9788","contributorId":294464,"corporation":false,"usgs":false,"family":"Brooks","given":"Scott","email":"","middleInitial":"C.","affiliations":[{"id":37070,"text":"Oak Ridge National Laboratory","active":true,"usgs":false}],"preferred":false,"id":962821,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dai, Zhenxue 0000-0002-0805-7621","orcid":"https://orcid.org/0000-0002-0805-7621","contributorId":366941,"corporation":false,"usgs":false,"family":"Dai","given":"Zhenxue","affiliations":[{"id":87510,"text":"Jilin University","active":true,"usgs":false}],"preferred":false,"id":962822,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Soltanian, Mohamad Reza 0000-0002-5126-0668","orcid":"https://orcid.org/0000-0002-5126-0668","contributorId":372147,"corporation":false,"usgs":false,"family":"Soltanian","given":"Mohamad","middleInitial":"Reza","affiliations":[{"id":7159,"text":"University of Cincinnati","active":true,"usgs":false}],"preferred":false,"id":962823,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Carroll, Kenneth C. 0000-0003-2097-9589","orcid":"https://orcid.org/0000-0003-2097-9589","contributorId":247827,"corporation":false,"usgs":false,"family":"Carroll","given":"Kenneth","email":"","middleInitial":"C.","affiliations":[{"id":12628,"text":"New Mexico State University","active":true,"usgs":false}],"preferred":false,"id":962824,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70276608,"text":"70276608 - 2026 - Improving offshore 3D splay fault geometries and slip histories using seismic data reprocessing and structural modeling","interactions":[],"lastModifiedDate":"2026-06-11T13:57:08.223012","indexId":"70276608","displayToPublicDate":"2026-05-29T08:54:29","publicationYear":"2026","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":3,"text":"Organization Series"},"seriesTitle":{"id":23312,"text":"Final Report","active":true,"publicationSubtype":{"id":3}},"title":"Improving offshore 3D splay fault geometries and slip histories using seismic data reprocessing and structural modeling","docAbstract":"The goal of this project as written in the CRESCENT seed grant proposal was as follows: 1) reprocess selected profiles along strike from 45° to 48°N from the CASIE21 crustal-scale seismic data to obtain higher-resolution and higher-quality imaging of the uppermost 1-2 km of the accretionary wedge; 2) convert high-resolution USGS sparker seismic data from the time to depth domain to constrain near-surface fault geometries; 3) use kinematic modeling in the MOVE software to derive individual fault slip rates and per-event-displacements; and 4) work with the CFM group to create updated 3D models of identified faults based on the new data sources.
At this stage, we have begun the reprocessing of the CASIE21 seismic reflection data (Carbotte et al., 2023). The time-migration reprocessing of the CASIE21 dataset has improved imaging of the near-surface structure by incorporating usable frequencies up to ~220 Hz, in contrast to the ~50 Hz maximum usable content in the currently available pre-stack depth migrated (PSDM) profiles (Fig. 1C). An example of the image quality gained through reprocessing is shown in Fig. 1, where the dominant wavelength of each reflector is reduced to ~10 m (Fig. 1B) from ~20 m in the existing PSDM product (Fig. 1A). The reprocessing work is still currently in progress. While the imaging in the shallow section has been much improved, reprocessing below the first multiple is still needed to create a seamless image from the plate boundary to the surface.
","language":"English","publisher":"Cascadia Region Earthquake Science Center","doi":"10.5281/zenodo.20512959","usgsCitation":"Ledeczi, A.M., Miller, N.C., Tobin, H.J., and Condit, C.B., 2026, Improving offshore 3D splay fault geometries and slip histories using seismic data reprocessing and structural modeling: Final Report, 5 p., https://doi.org/10.5281/zenodo.20512959.","productDescription":"5 p.","ipdsId":"IP-190306","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":505393,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ledeczi, Anna M.","contributorId":372144,"corporation":false,"usgs":false,"family":"Ledeczi","given":"Anna","middleInitial":"M.","affiliations":[{"id":88268,"text":"Department of Earth & Space Sciences, University of Washington, Seattle","active":true,"usgs":false}],"preferred":false,"id":962814,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Miller, Nathaniel C. 0000-0003-3271-2929 ncmiller@usgs.gov","orcid":"https://orcid.org/0000-0003-3271-2929","contributorId":174592,"corporation":false,"usgs":true,"family":"Miller","given":"Nathaniel","email":"ncmiller@usgs.gov","middleInitial":"C.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":962815,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tobin, Harold J.","contributorId":372145,"corporation":false,"usgs":false,"family":"Tobin","given":"Harold","middleInitial":"J.","affiliations":[{"id":88268,"text":"Department of Earth & Space Sciences, University of Washington, Seattle","active":true,"usgs":false}],"preferred":false,"id":962816,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Condit, Cailey B.","contributorId":372146,"corporation":false,"usgs":false,"family":"Condit","given":"Cailey","middleInitial":"B.","affiliations":[{"id":88268,"text":"Department of Earth & Space Sciences, University of Washington, Seattle","active":true,"usgs":false}],"preferred":false,"id":962817,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70276343,"text":"70276343 - 2026 - Co-occurrence of pesticides and pharmaceuticals and personal care products (PPCPs) across Zostera marina (common eelgrass) communities","interactions":[],"lastModifiedDate":"2026-06-01T13:56:29.395433","indexId":"70276343","displayToPublicDate":"2026-05-29T08:51:15","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2676,"text":"Marine Pollution Bulletin","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Co-occurrence of pesticides and pharmaceuticals and personal care products (PPCPs) across Zostera marina (common eelgrass) communities","title":"Co-occurrence of pesticides and pharmaceuticals and personal care products (PPCPs) across Zostera marina (common eelgrass) communities","docAbstract":"Anthropogenic pressures are driving changes in eelgrass communities, which are altering baseline conditions in estuarine environments. Field detections have validated the transport of land-sourced pollutants to aquatic systems; however, studies rarely sample concurrently for pesticides, and pharmaceuticals and personal care products (PPCPs) across environmental compartments. Moreover, studies on contaminant uptake by eelgrass and associated species are even more limited. In collaboration with the Confederated Tribes of the Coos, Lower Umpqua and Siuslaw Indians (CTCLUSI), this study collected samples of water, eelgrass, clams, and sediment at sites of Tribal significance in Southern Oregon to test for organic contaminants (i.e., herbicides and pharmaceuticals). Paired sampling was conducted for analysis by the CTCLUSI in tandem with the United States Geological Survey (USGS) in order for the Tribe to develop analytical standards for future sampling efforts. Ten pesticides and eight pharmaceuticals were detected across the four sites, with the highest number of overall detections (27) at the Florence Marina site. The insecticide bifenthrin was most frequently detected across all media (0.012–1.565 μg/g organic carbon in sediment, 2.7–30 ng/g in organismal tissue) and the anti-diabetic agent metformin was the most detected PPCP in clam tissues (1.33–3.78 ng/g). Pesticides and PPCPs were observed to co-occur in eelgrass habitats, with numerous pesticide detections across media types. These findings demonstrate numerous routes of exposure for estuarine organisms which could be addressed with pharmaceutical disposal strategies or pesticide use restrictions near these habitats.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.marpolbul.2026.119908","usgsCitation":"Tissot, A.G., Niessner, J.C., Granek, E.F., Brown, K., and Hladik, M.L., 2026, Co-occurrence of pesticides and pharmaceuticals and personal care products (PPCPs) across Zostera marina (common eelgrass) communities: Marine Pollution Bulletin, v. 231, 119908, 14 p., https://doi.org/10.1016/j.marpolbul.2026.119908.","productDescription":"119908, 14 p.","ipdsId":"IP-179711","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":504904,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Coos Bay estuary, Siuslaw River estuary","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.24478795433298,\n 43.43457841847609\n ],\n [\n -124.3973913382971,\n 43.43457841847609\n ],\n [\n -124.3973913382971,\n 43.2765459832344\n ],\n [\n -124.24478795433298,\n 43.2765459832344\n ],\n [\n -124.24478795433298,\n 43.43457841847609\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.1162674030572,\n 43.99953029917708\n ],\n [\n -124.0308931847648,\n 43.99953029917708\n ],\n [\n -124.0308931847648,\n 43.95215009258666\n ],\n [\n -124.1162674030572,\n 43.95215009258666\n ],\n [\n -124.1162674030572,\n 43.99953029917708\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"231","noUsgsAuthors":false,"publicationDate":"2026-05-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Tissot, Alexandra G.","contributorId":371617,"corporation":false,"usgs":false,"family":"Tissot","given":"Alexandra","middleInitial":"G.","affiliations":[{"id":6929,"text":"Portland State University","active":true,"usgs":false}],"preferred":false,"id":962173,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Niessner, Janet C.","contributorId":371618,"corporation":false,"usgs":false,"family":"Niessner","given":"Janet","middleInitial":"C.","affiliations":[{"id":88193,"text":"Confederated Tribes of the Coos, Lower Umpqua, and Siuslaw Indians","active":true,"usgs":false}],"preferred":false,"id":962174,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Granek, Elise F.","contributorId":371619,"corporation":false,"usgs":false,"family":"Granek","given":"Elise","middleInitial":"F.","affiliations":[{"id":6929,"text":"Portland State University","active":true,"usgs":false}],"preferred":false,"id":962175,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brown, Kimberly","contributorId":371620,"corporation":false,"usgs":false,"family":"Brown","given":"Kimberly","affiliations":[{"id":6929,"text":"Portland State University","active":true,"usgs":false}],"preferred":false,"id":962176,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hladik, Michelle L. 0000-0002-0891-2712","orcid":"https://orcid.org/0000-0002-0891-2712","contributorId":221229,"corporation":false,"usgs":true,"family":"Hladik","given":"Michelle","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":962177,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70276268,"text":"ofr20261017 - 2026 - Range-wide relative abundance of the Appalachian grizzled skipper (Pyrgus centaureae wyandot) in the Eastern United States","interactions":[],"lastModifiedDate":"2026-05-29T13:09:53.489973","indexId":"ofr20261017","displayToPublicDate":"2026-05-28T10:15:05","publicationYear":"2026","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2026-1017","displayTitle":"Range-Wide Relative Abundance of the Appalachian Grizzled Skipper (Pyrgus centaureae wyandot) in the Eastern United States","title":"Range-wide relative abundance of the Appalachian grizzled skipper (Pyrgus centaureae wyandot) in the Eastern United States","docAbstract":"The U.S. Fish and Wildlife Service has designated the Pyrgus centaureae wyandot (Appalachian Grizzled Skipper [AGS]) to be at-risk, based on its declining populations and the lack of information on its status. The objective of this study was to complete range-wide surveys to locate extant AGS colonies and to quantify the number of AGS observed at each location. From 2021–24, 284 surveys were done in 25 unique (that is, distinct) counties in 8 States in the Eastern United States — Maryland, Michigan, New York, North Carolina, Ohio, Pennsylvania, Virginia, and West Virginia. We found AGS in only two counties: Alleghany County, Virginia, and Greenbrier County, West Virginia. AGS were observed 180 times in these two counties. Our results can inform U.S. Fish and Wildlife decisions about where and how future AGS conservation efforts can be implemented.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20261017","collaboration":"Maryland Department of Natural Resources; Michigan State University Extension; New Jersey Department of Environmental Protection; New York Natural Heritage Program; North Carolina Department of Natural and Cultural Resources; Ohio Department of Natural Resources; Western Pennsylvania Conservancy; U.S. Fish and Wildlife Service; Virginia Department of Conservation and Recreation; West Virginia Division of Natural Resources","usgsCitation":"Vyas, N.B., Selfridge, J., Cuthrell, D., Somes, R., White, E., Ratcliffe, J., Lynch, J., Hamon, L., Wyza, E., Leppo, B., Woods, P., Tur, A., Drummey, D., Nolan, K., Orcutt, E., Rapp, A., Card, L., Goldner, J., and Olcott, S., 2026, Range-wide relative abundance of the Appalachian grizzled skipper (Pyrgus centaureae wyandot) in the Eastern United States: U.S. Geological Survey Open-File Report 2026–1017, 57 p., 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U.S. Geological Survey
12100 Beech Forest Rd., Ste 4039
Laurel, MD 20708-4039
Prescribed fire is a common approach to reduce fuels and mitigate fire hazards. The accumulation of live and dead fuels following initial treatment means that repeated application of prescribed fire could be used to maintain this benefit. However, the effect of repeated prescribed fires is not well documented in many dry coniferous forests in the western United States. Here, we present observations of changes in live trees and surface fuels following two prescribed fires in dry coniferous forests in national parks of California.
Changes in forest structure and accumulation of surface fuels were similar over time following initial-entry and second-entry fires. An exception was that repeated fires were associated with substantial reductions in stem density. There were smaller changes in live tree basal area and stem biomass.
Our results indicate that following initial-entry fires, subsequent burning maintained reductions in surface fuel loads without major inadvertent losses of live tree basal area and stem biomass, implying the survival of large trees.
","language":"English","publisher":"Springer Nature","doi":"10.1186/s42408-026-00479-3","usgsCitation":"van Mantgem, P., Wright, M.C., Farris, C.A., Engber, E., McClure, E., Caprio, A., and Keifer, M., 2026, Effects of repeat prescribed burning in dry coniferous forests in national parks of California: Fire Ecology, v. 22, 64, 12 p., https://doi.org/10.1186/s42408-026-00479-3.","productDescription":"64, 12 p.","ipdsId":"IP-156305","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":505044,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s42408-026-00479-3","text":"Publisher Index Page"},{"id":504947,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Lava Beds National Monument, Lassen Volcanic National Park, Sequoia and Kings Canyon National Parks, Whiskeytown National Recreation Area), Yosemite National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.1080277,\n 38.048227194156595\n ],\n [\n -118.79094941920485,\n 38.048227194156595\n ],\n [\n -118.79094941920485,\n 37.130674\n ],\n [\n -120.1080277,\n 37.130674\n ],\n [\n -120.1080277,\n 38.048227194156595\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.137383,\n 36.994117430423145\n ],\n [\n -117.90254915270303,\n 36.994117430423145\n ],\n [\n -117.90254915270303,\n 35.5594697\n ],\n [\n -119.137383,\n 35.5594697\n ],\n [\n -119.137383,\n 36.994117430423145\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.7300358,\n 41.918368292356064\n ],\n [\n -121.2641104817198,\n 41.918368292356064\n ],\n [\n -121.2641104817198,\n 41.4876012\n ],\n [\n -121.7300358,\n 41.4876012\n ],\n [\n -121.7300358,\n 41.918368292356064\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.70837683858048,\n 40.8929042\n ],\n [\n -120.585063,\n 40.8929042\n ],\n [\n -120.585063,\n 40.30526774036363\n ],\n [\n -121.70837683858048,\n 40.30526774036363\n ],\n [\n -121.70837683858048,\n 40.8929042\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.7170431,\n 40.6657101\n ],\n [\n -122.4776842,\n 40.6657101\n ],\n [\n -122.4776842,\n 40.5463867\n ],\n [\n -122.7170431,\n 40.5463867\n ],\n [\n -122.7170431,\n 40.6657101\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"22","noUsgsAuthors":false,"publicationDate":"2026-05-28","publicationStatus":"PW","contributors":{"authors":[{"text":"van Mantgem, Phillip J. 0000-0002-3068-9422","orcid":"https://orcid.org/0000-0002-3068-9422","contributorId":204320,"corporation":false,"usgs":true,"family":"van Mantgem","given":"Phillip J.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":962222,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wright, Micah C. 0000-0002-5324-1110","orcid":"https://orcid.org/0000-0002-5324-1110","contributorId":229071,"corporation":false,"usgs":true,"family":"Wright","given":"Micah","middleInitial":"C.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":962223,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Farris, Calvin A.","contributorId":292802,"corporation":false,"usgs":false,"family":"Farris","given":"Calvin","email":"","middleInitial":"A.","affiliations":[{"id":63015,"text":"National Park Service, Division of Fire and Aviation Management, P.O. Box 1713, Klamath Falls, OR 97601, USA","active":true,"usgs":false}],"preferred":false,"id":962224,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Engber, Eamon","contributorId":202777,"corporation":false,"usgs":false,"family":"Engber","given":"Eamon","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":962225,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McClure, Emma J. 0009-0007-1285-4977","orcid":"https://orcid.org/0009-0007-1285-4977","contributorId":352134,"corporation":false,"usgs":false,"family":"McClure","given":"Emma J.","affiliations":[{"id":84121,"text":"National Park Service, Redwood National and State Parks","active":true,"usgs":false}],"preferred":false,"id":962226,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Caprio, Anthony C.","contributorId":35863,"corporation":false,"usgs":false,"family":"Caprio","given":"Anthony C.","affiliations":[],"preferred":false,"id":962227,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Keifer, MaryBeth","contributorId":194887,"corporation":false,"usgs":false,"family":"Keifer","given":"MaryBeth","email":"","affiliations":[],"preferred":false,"id":962228,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70276457,"text":"70276457 - 2026 - Future water constraints on United States lithium mining under climate change","interactions":[],"lastModifiedDate":"2026-06-05T13:48:19.979755","indexId":"70276457","displayToPublicDate":"2026-05-28T08:43:26","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":8956,"text":"Communications Earth & Environment","active":true,"publicationSubtype":{"id":10}},"title":"Future water constraints on United States lithium mining under climate change","docAbstract":"Lithium is necessary for low-carbon technologies that combat climate change, but lithium extraction is water-intensive. Changes in temperature and precipitation arising from climate change are altering water distribution, which could further strain supplies for new mines and industry, farms, and households. Here we explored how climate change, water use, and mining siting could impact lithium mining in the United States. We analyzed whether there would be sufficient water available to support the single existing and 22 proposed U.S. lithium mines at mid-century under four socioeconomic-climate scenarios and five climate models. Though dependent on socioeconomic-climate scenario, climate model, and lithium deposit type, available water supply in most subbasins would likely be unable to support new mines’ water demands, or even non-mining water demands from other sectors. Water scarcity could hinder the ability of the United States to produce enough lithium to meet domestic demand thereby necessitating higher imports.
","language":"English","publisher":"Nature","doi":"10.1038/s43247-026-03643-4","usgsCitation":"Trost, J.N., Nassar, N.T., and Dunn, J.B., 2026, Future water constraints on United States lithium mining under climate change: Communications Earth & Environment, https://doi.org/10.1038/s43247-026-03643-4.","ipdsId":"IP-182933","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":505458,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s43247-026-03643-4","text":"Publisher Index Page"},{"id":505085,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"conterminous United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"geometry\": {\n \"type\": \"MultiPolygon\",\n \"coordinates\": [\n [\n [\n [\n -94.81758,\n 49.38905\n ],\n [\n 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nnassar@usgs.gov","orcid":"https://orcid.org/0000-0001-8758-9732","contributorId":197864,"corporation":false,"usgs":true,"family":"Nassar","given":"Nedal","email":"nnassar@usgs.gov","middleInitial":"T.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":962434,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dunn, Jennifer B. 0000-0002-2065-5106","orcid":"https://orcid.org/0000-0002-2065-5106","contributorId":371832,"corporation":false,"usgs":false,"family":"Dunn","given":"Jennifer","middleInitial":"B.","affiliations":[{"id":25254,"text":"Northwestern University","active":true,"usgs":false}],"preferred":false,"id":962435,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70276319,"text":"70276319 - 2026 - Geochemical, mineralogical, and isotopic evidence for multi-stage genesis of the Hicks Dome REE + Y-HFSE-fluorite deposit, Illinois, USA","interactions":[],"lastModifiedDate":"2026-05-28T14:13:31.247592","indexId":"70276319","displayToPublicDate":"2026-05-27T09:02:02","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2954,"text":"Ore Geology Reviews","active":true,"publicationSubtype":{"id":10}},"title":"Geochemical, mineralogical, and isotopic evidence for multi-stage genesis of the Hicks Dome REE + Y-HFSE-fluorite deposit, Illinois, USA","docAbstract":"Hicks Dome hosts breccias enriched in rare earth elements (REE), Y, Th, F, Ba, Ti, Nb, and Be, alongside spatially associated lamprophyre dikes (ca. 271 Ma). Hicks Dome is located within the Illinois–Kentucky Fluorspar District, which hosts fluorite, Pb–Zn, and barite resources. This study investigates the genetic relationships between Hicks Dome mineralization in breccias, alkaline magmatism, and Illinois–Kentucky Fluorspar District mineralization. Lamprophyre dikes are light REE–enriched with chondrite-normalized abundances decreasing from La to Lu. The Host Breccia exhibits middle and heavy REE–enriched patterns that mirror those of the principal REE–Th host minerals, including fluorapatite, xenotime, and thorite. Textural evidence suggests recrystallization of phosphates, sulfates, and Ti–Nb oxides in the Host Breccia. U–Pb geochronology constrains multiple mineralizing events, with ages of 277 ± 18 Ma from low-Th apatite interpreted as main-stage mineralization, and 121.6 ± 9.7 Ma from high-Th apatite indicating later overprinting. O–H–C stable isotope data provide evidence for multiple stages of fluid-rock interaction and fluid mixing: (1) early magmatic fluids dissolved limestone country rock, (2) mixing between magmatic fluids and basinal brines led to main-stage mineralization in the Host Breccia, and (3) late-stage mineralization occurred following mixing of meteoric water and basinal brine. These results indicate that heavy REEs, high field strength elements, and fluorine precipitated proximal to its alkaline magmatic source because of fluid–rock interactions and fluid mixing. Subsequent fluid mixing drove late-stage recrystallization and additional fluorite formation, a process that may be similar to mineralization in the Illinois-Kentucky Fluorspar District.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.oregeorev.2026.107328","usgsCitation":"McIntosh, J.A., Andersen, A.K., Bennett, M.M., Thompson, J.M., Johnson, C.A., Hofstra, A.H., and Nuelle, L., 2026, Geochemical, mineralogical, and isotopic evidence for multi-stage genesis of the Hicks Dome REE + Y-HFSE-fluorite deposit, Illinois, USA: Ore Geology Reviews, v. 194, 107328, 23 p., https://doi.org/10.1016/j.oregeorev.2026.107328.","productDescription":"107328, 23 p.","ipdsId":"IP-180590","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":504815,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.oregeorev.2026.107328","text":"Publisher Index Page"},{"id":504772,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois","otherGeospatial":"Hicks Dome","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.383333,\n 37.55\n ],\n [\n -88.3,\n 37.55\n ],\n [\n -88.3,\n 37.466667\n ],\n [\n -88.383333,\n 37.466667\n ],\n [\n -88.383333,\n 37.55\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"194","noUsgsAuthors":false,"publicationDate":"2026-05-27","publicationStatus":"PW","contributors":{"authors":[{"text":"McIntosh, Julia A. 0000-0003-2819-8664","orcid":"https://orcid.org/0000-0003-2819-8664","contributorId":331662,"corporation":false,"usgs":true,"family":"McIntosh","given":"Julia","email":"","middleInitial":"A.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":962098,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Andersen, Allen K. 0000-0002-6865-2561","orcid":"https://orcid.org/0000-0002-6865-2561","contributorId":217476,"corporation":false,"usgs":true,"family":"Andersen","given":"Allen","email":"","middleInitial":"K.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":962099,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bennett, Mitchell M. 0000-0001-9533-9557 mbennett@usgs.gov","orcid":"https://orcid.org/0000-0001-9533-9557","contributorId":199379,"corporation":false,"usgs":true,"family":"Bennett","given":"Mitchell","email":"mbennett@usgs.gov","middleInitial":"M.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":962100,"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":962101,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Johnson, Craig A. 0000-0002-1334-2996 cjohnso@usgs.gov","orcid":"https://orcid.org/0000-0002-1334-2996","contributorId":909,"corporation":false,"usgs":true,"family":"Johnson","given":"Craig","email":"cjohnso@usgs.gov","middleInitial":"A.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":962102,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hofstra, Albert H. 0000-0002-2450-1593 ahofstra@usgs.gov","orcid":"https://orcid.org/0000-0002-2450-1593","contributorId":1302,"corporation":false,"usgs":true,"family":"Hofstra","given":"Albert","email":"ahofstra@usgs.gov","middleInitial":"H.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":962103,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Nuelle, Laurence","contributorId":371609,"corporation":false,"usgs":false,"family":"Nuelle","given":"Laurence","affiliations":[{"id":88191,"text":"Hicks Dome LLC","active":true,"usgs":false}],"preferred":false,"id":962104,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70276326,"text":"70276326 - 2026 - Status and trends of pelagic and benthic prey fish populations in Lake Michigan, 2025","interactions":[],"lastModifiedDate":"2026-05-29T13:52:57.889658","indexId":"70276326","displayToPublicDate":"2026-05-27T08:46:24","publicationYear":"2026","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":3,"text":"Organization Series"},"title":"Status and trends of pelagic and benthic prey fish populations in Lake Michigan, 2025","docAbstract":"Fall bottom trawl (fall BT) and lakewide acoustic (AC) surveys are conducted annually to generate indices of pelagic and benthic prey fish densities in Lake Michigan. The fall BT survey has been conducted each fall since 1973 using 12-m trawls at depths ranging from 9 to 110 m at fixed locations distributed across seven transects; this survey estimates densities of seven prey fish species [i.e., Alewife (Alosa pseudoharengus), Bloater (Coregonus hoyi), Rainbow Smelt (Osmerus mordax), Deepwater Sculpin (Myoxocephalus thompsonii), Slimy Sculpin (Cottus cognatus), Round Goby (Neogobius melanostomus), Ninespine Stickleback (Pungitius pungitius)]. The AC survey has been conducted each late summer/early fall since 2004 (except 2020). The 2025 AC survey consisted of 26 transects [470 km total (292 miles)] covering bottom depths ranging from 5 to 259 m and 44 midwater trawl tows at 1.4 to 82.4 m fishing depth; this survey estimates densities of three prey fish species (i.e., Alewife, Bloater, and Rainbow Smelt). The data generated from these surveys are used to estimate various population parameters that are, in turn, used by state and tribal agencies in managing Lake Michigan fish stocks.
For the AC survey, total biomass density of prey fish equaled 9.3 kg/ha, continuing a recent trend of index values above the long-term average of 5.4 kg/ha. For the fall BT, total biomass density of prey fish equaled 3.4 kg/ha, close to values observed since 2014 and well below historic numbers and those observed earlier in the 2000s. Over the period both surveys have been conducted (2004-2025), the total biomass density index had trended downward in the fall BT through the mid-2010s and appears to have stabilized at low values, while the AC survey biomass density index has remained relatively stable over the time series.
Mean biomass of yearling and older (YAO) Alewife was 4.3 kg/ha in the AC survey and 0.45 kg/ha in the fall BT. Since 2014, annual survey results suggest that the catchability of YAO Alewife for the fall BT is substantially lower than the AC survey. The 2025 AC survey YAO Alewife biomass density estimate was 57% higher than the average from 2004-2024. The Alewife population of Lake Michigan appears to be composed mostly of young fish and the proportion of age-4 and older Alewife was ~5% in both surveys. Age-0 Alewife numeric density from the AC survey was 259 fish/ha in 2025, lower than the long-term mean (487 fish/ha). Biomass density of large (≥120 mm) Bloater was 3.5 kg/ha in the AC survey and 1.9 kg/ha in the fall BT. The density of small (<120 mm) Bloater was 540 fish/ha in the AC survey, the second highest value in the time series. Meanwhile, small Bloater density estimated in the fall BT was only 6.1 fish/ha. Biomass density of large Rainbow Smelt (≥90 mm) was 0.69 kg/ha in the AC survey and 0.04 kg/ha in the fall BT survey. Numeric density of small (<90 mm) Rainbow Smelt was 541 fish/ha in the AC survey, the highest value in the time series, and 41 fish/ha in the fall BT. All four prey fish species indexed only by the fall BT had below-average biomass densities. Deepwater Sculpin biomass density was 0.21 kg/ha, which makes 15 of the past 16 years with biomass <1 kg/ha. Slimy Sculpin was estimated to be 0.03 kg/ha, an order of magnitude lower than the long-term average from the fall BT. Round Goby biomass density was 0.44 kg/ha and Ninespine Stickleback density was 0.20 kg/ha, the highest value since 2007.
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In response to the increased number of earthquakes in this region, rapid and accurate characterization of earthquake sources is necessary to understand the evolution of seismic activity and level of seismic hazard associated with these earthquakes. This study re-evaluates earthquake magnitudes, estimating moment magnitude (MW) for small earthquakes in the Delaware Basin using 1) moment-rate spectra derived from S-wave coda envelopes, and 2) a relative magnitude method that relies exclusively on the ratio of waveform amplitudes between highly correlated waveform pairs. The coda-envelope method produces accurate MW estimates for small earthquakes (M 1.5 – 3) that are consistent with independent, waveform modeled moment magnitudes for events with MW > 3. Using the relative amplitudes method to extend these MW magnitudes to many other events, we successfully provide relative moment magnitude (MW,rel) values for 81% of the Texas Seismological Network catalog in the Delaware Basin region, and 45% of the USGS Induced Seismicity Project’s catalog of events in southeast New Mexico. The adoption and integration of the calibrated MW,rel method with current magnitude estimation methods offers valuable insights into the relationships between local and moment magnitude and will contribute to improved characterization of widespread induced seismicity.
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Continuous water surface profiles of the Colorado River in Grand Canyon, a river influenced by two of the largest dams in the United States, have been measured infrequently. The water surface profile was first measured in 1923, 13 years before the completion of Hoover Dam, which impounded water into western Grand Canyon, and 40 years before the completion of Glen Canyon Dam, which affected streamflow and sediment supply for all of Grand Canyon. The water surface profile was next measured in 2000, 37 years after the completion of Glen Canyon Dam, although this profile did not include the segment affected by Hoover Dam. A continuous profile of riverbed elevations has never been published. Here, we present the first complete, coupled water surface and riverbed elevation profiles, collected in 2021 during a period of steady releases from Glen Canyon Dam. The profiles were constructed from positions and elevations measured by boat-based global navigation satellite systems and from bathymetry collected by multibeam sonar. Data collected by boat were supplemented by data from a photogrammetry-derived digital surface model that was created from concurrently collected aerial images. Independent measurements made by conventional total stations referenced to a common geodetic control network were used to evaluate accuracy of all measurements. The final water surface and riverbed elevation profiles improved the accuracy and precision reported for previous profiles. In this study, the mean absolute vertical accuracy of water surface elevations was 0.07 meter for 85 percent of river miles and 0.19 meter for 11 percent of river miles. For the remaining 4 percent of river miles, water surface elevations were interpolated between measured values. The profiles reported herein can be used for current assessment of Colorado River geomorphic conditions, quantification of changes in the river over time, and predictive modeling of river resources for potential future management scenarios.quantification of changes in the river over time, and predictive modeling of river resources for potential future management scenarios.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20265010","usgsCitation":"Sartain, S.L., Kaplinski, M.A., Kohl, K., Chapman, K.A., Bransky, N.D., Sankey, J.B., and Grams, P.E., 2026, Continuous and high-resolution longitudinal profiles of the water surface and riverbed elevation for 282 miles of the Colorado River from Lees Ferry to Pearce Ferry, Arizona, 2021: U.S. Geological Survey Scientific Investigations Report 2026–5010, 40 p., https://doi.org/10.3133/sir20265010.","productDescription":"Report: vii, 40 p.; Data Release","numberOfPages":"40","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-179784","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":504710,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_119446.htm","linkFileType":{"id":5,"text":"html"}},{"id":504453,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2026/5010/sir20265010.pdf","text":"Report","size":"6.81 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2026-5010 PDF"},{"id":504457,"rank":2,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20265010/full","linkFileType":{"id":5,"text":"html"},"description":"SIR 2026-5010 HTML"},{"id":504458,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2026/5010/sir20265010.XML","description":"SIR 2026-5010 XML"},{"id":504459,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2026/5010/images"},{"id":504460,"rank":5,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2026/5010/coverthb.jpg"},{"id":504461,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P135FNFM","text":"USGS data release","linkHelpText":"Continuous and high-resolution profiles of the water surface and riverbed elevation for 282 miles of the Colorado River from Lees Ferry to Pearce Ferry, AZ, 2021—Data"}],"country":"United States","state":"Arizona","otherGeospatial":"Colorado River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.415697136473,\n 36.90189262731032\n ],\n [\n -114.01161104871596,\n 36.90189262731032\n ],\n [\n -114.01161104871596,\n 35.51758910449131\n ],\n [\n -111.415697136473,\n 35.51758910449131\n ],\n [\n -111.415697136473,\n 36.90189262731032\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Southwest Biological Science Center
U.S. Geological Survey
2255 N. Gemini Drive
Flagstaff, AZ 86001
We measured the elevation of 282 miles of the water surface and riverbed of the Colorado River in Grand Canyon, from Lees Ferry, Arizona, to Pearce Ferry, Ariz. We collected water surface and riverbed elevations during a period of steady releases from Glen Canyon Dam in 2021. We used multiple, concurrent methods to measure the elevation of the water surface and assessed error for each measurement method to use the most accurate data possible in the final elevation profile. The final water surface profile is measured to the centimeter every river hundredth mile, with vertical uncertainty less than or equal to 0.07 meter for 85 percent of the river and less than or equal to 0.19 meter for the remainder of the river. We collected bathymetry of the river centerline everywhere possible, which did not include rapids and shallow areas. This study is the third measurement of a complete water surface profile; the first was collected in 1923, 40 years before Glen Canyon Dam was completed, and the second was collected in 2000, 37 years after Glen Canyon Dam was completed. A continuous riverbed profile had not been collected previously.
","publicationDate":"2026-05-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Sartain, Shannon L. 0000-0003-2395-6825","orcid":"https://orcid.org/0000-0003-2395-6825","contributorId":290222,"corporation":false,"usgs":true,"family":"Sartain","given":"Shannon","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":961627,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kaplinski, Matthew A. 0000-0001-6232-8325","orcid":"https://orcid.org/0000-0001-6232-8325","contributorId":333646,"corporation":false,"usgs":true,"family":"Kaplinski","given":"Matthew","email":"","middleInitial":"A.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":961628,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kohl, Keith 0000-0001-6812-0373","orcid":"https://orcid.org/0000-0001-6812-0373","contributorId":371349,"corporation":false,"usgs":false,"family":"Kohl","given":"Keith","affiliations":[{"id":88119,"text":"NOAA, National Geodetic Survey, Flagstaff, AZ","active":true,"usgs":false}],"preferred":false,"id":961629,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chapman, Katherine A. 0009-0009-1806-6474 kchapman@usgs.gov","orcid":"https://orcid.org/0009-0009-1806-6474","contributorId":345014,"corporation":false,"usgs":true,"family":"Chapman","given":"Katherine","email":"kchapman@usgs.gov","middleInitial":"A.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":961630,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bransky, Nathaniel D. 0000-0003-3113-7491","orcid":"https://orcid.org/0000-0003-3113-7491","contributorId":305709,"corporation":false,"usgs":true,"family":"Bransky","given":"Nathaniel","middleInitial":"D.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":961631,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sankey, Joel B. 0000-0003-3150-4992","orcid":"https://orcid.org/0000-0003-3150-4992","contributorId":261248,"corporation":false,"usgs":true,"family":"Sankey","given":"Joel B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":961632,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Grams, Paul E. 0000-0002-0873-0708","orcid":"https://orcid.org/0000-0002-0873-0708","contributorId":212943,"corporation":false,"usgs":true,"family":"Grams","given":"Paul","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":961633,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70276636,"text":"70276636 - 2026 - From start to stop: Simple methods for mapping susceptibility to landslide runout and debris-flow inundation","interactions":[],"lastModifiedDate":"2026-06-12T14:17:21.228806","indexId":"70276636","displayToPublicDate":"2026-05-26T09:00:54","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2604,"text":"Landslides","active":true,"publicationSubtype":{"id":10}},"title":"From start to stop: Simple methods for mapping susceptibility to landslide runout and debris-flow inundation","docAbstract":"Landslide runout and debris-flow inundation can disrupt areas well beyond their initial sources, causing widespread damage and extensive fatalities. Understanding where they start and how far they might travel is essential in many locations worldwide. However, most landslide susceptibility maps focus on initiation areas and fail to incorporate runout areas. Furthermore, hazards vary greatly with the degree of landslide mobility, and debris flows can grow as they travel beyond their initial source. Here, we use the USGS Grfin Tools software suite to map susceptible areas from start to stop in the Federated States of Micronesia where landslide and debris-flows runout onto gentle ground is a deadly threat. The DEM-based models in Grfin Tools use simple, empirical, and well-documented approaches that require minimal parameters and, thus, can be used in areas that lack detailed physical properties. We illustrate methods to estimate the required parameters using direct landslide observations, and we suggest alternate methods if direct observations are absent. Our simple parameter estimations in the Federated States of Micronesia successfully predict areas that match past landslide runout and debris-flow inundation, as well as zones with no inundation. In addition to creating preliminary regional assessments, Grfin Tools can be used for comparing multiple scenarios and/or identifying areas for further investigations.
","language":"English","publisher":"Springer","doi":"10.1007/s10346-026-02751-8","usgsCitation":"Reid, M.E., Cerovski-Darriau, C., Brien, D.L., Leb, I., and Cyr, A.J., 2026, From start to stop: Simple methods for mapping susceptibility to landslide runout and debris-flow inundation: Landslides, https://doi.org/10.1007/s10346-026-02751-8.","ipdsId":"IP-180986","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":505549,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Federated States of Micronesia","otherGeospatial":"Chuuk, Kosrae, Pohnpei","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 163.05349206922193,\n 5.386585845343674\n ],\n [\n 162.8882457651913,\n 5.386585845343674\n ],\n [\n 162.8882457651913,\n 5.249999335212365\n ],\n [\n 163.05349206922193,\n 5.249999335212365\n ],\n [\n 163.05349206922193,\n 5.386585845343674\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 158.10270329195367,\n 7.03005149396914\n ],\n [\n 158.38032341179485,\n 7.03005149396914\n ],\n [\n 158.38032341179485,\n 6.7620431146946345\n ],\n [\n 158.10270329195367,\n 6.7620431146946345\n ],\n [\n 158.10270329195367,\n 7.03005149396914\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 151.96242420771364,\n 7.49357812591748\n ],\n [\n 151.50337875009063,\n 7.49357812591748\n ],\n [\n 151.50337875009063,\n 7.22201647102294\n ],\n [\n 151.96242420771364,\n 7.22201647102294\n ],\n [\n 151.96242420771364,\n 7.49357812591748\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Online First","noUsgsAuthors":false,"publicationDate":"2026-05-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Reid, Mark E. 0000-0002-5595-1503 mreid@usgs.gov","orcid":"https://orcid.org/0000-0002-5595-1503","contributorId":1167,"corporation":false,"usgs":true,"family":"Reid","given":"Mark","email":"mreid@usgs.gov","middleInitial":"E.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":962918,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cerovski-Darriau, Corina 0000-0002-0543-0902","orcid":"https://orcid.org/0000-0002-0543-0902","contributorId":221159,"corporation":false,"usgs":true,"family":"Cerovski-Darriau","given":"Corina","email":"","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":962919,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brien, Dianne L. 0000-0003-3227-7963 dbrien@usgs.gov","orcid":"https://orcid.org/0000-0003-3227-7963","contributorId":229851,"corporation":false,"usgs":true,"family":"Brien","given":"Dianne","email":"dbrien@usgs.gov","middleInitial":"L.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":962920,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Leb, Isaac Henry 0009-0000-7643-6941","orcid":"https://orcid.org/0009-0000-7643-6941","contributorId":339798,"corporation":false,"usgs":true,"family":"Leb","given":"Isaac Henry","affiliations":[{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true}],"preferred":true,"id":962921,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cyr, Andrew J. 0000-0003-2293-5395 acyr@usgs.gov","orcid":"https://orcid.org/0000-0003-2293-5395","contributorId":3539,"corporation":false,"usgs":true,"family":"Cyr","given":"Andrew","email":"acyr@usgs.gov","middleInitial":"J.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":962922,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70276454,"text":"70276454 - 2026 - Streamflow and surface-water presence data availability across the conterminous United States: A review for headwater systems","interactions":[],"lastModifiedDate":"2026-06-05T13:55:33.458167","indexId":"70276454","displayToPublicDate":"2026-05-26T08:49:06","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Streamflow and surface-water presence data availability across the conterminous United States: A review for headwater systems","docAbstract":"Water is essential for life on Earth, supporting ecosystems, human health, and economic activities. Hydrology relies on observational data, and this paper discusses regional and national datasets for the conterminous United States (CONUS) publicly available as of 2023, focusing on headwaters, defined as first- and second-order streams at 1:24000 scale. It identifies 72 primary and secondary datasets and 11 repositories and argues how better integration and accessibility of hydrological data can improve research. The paper distinguishes between datasets where streamflow was the primary data collection objective and those where it was secondary. This distinction highlights opportunities to consider data from efforts peripheral to hydrology but is still useful for understanding hydrologic conditions. The analysis reveals that out of about 118 000 active and inactive stream observation sites, about 6.6% and 25% are located on first- and second-order streams, respectively. This indicates a substantial data gap for headwater systems, which account for over 77% of stream length in CONUS. Federal agencies manage 72% of hydrologic monitoring sites across all stream orders, but only 34% of these are in headwater systems. Academic institutions operate about 2% of sites, with almost half (48%) in headwater systems, focusing on ecosystem research. State agencies also operate about 2% of sites, primarily on larger systems, with 19% on headwaters. Additionally, 23% of sites are managed by multiple agencies. Spatial patterns further reveal pronounced disparities among physiographic regions. Eastern and coastal provinces show relatively dense monitoring, while central and western regions show sparse coverage. These gaps reflect historical priorities, logistical constraints, funding limitations, and the high cost of continuous instrumentation. To address biases in monitoring networks, data collection could be enhanced with low-cost monitoring, community science, and remote sensing technologies. This study also notes the benefits of long-term monitoring and prioritizing retention of streamgages with longer records.
","language":"English","publisher":"Wiley","doi":"10.1002/hyp.70572","usgsCitation":"Sando, R., Jaeger, K., Kelleher, C., Hammond, J., Christensen, J.R., Segura, C., Golden, H.E., Cheng, F.Y., Husic, A., Jones, C.N., Lane, C.R., Li, L., Mahoney, D.T., McMillan, H., Price, A.N., Seybold, E.C., Ward, A., Zimmer, M., and Pestana, S.J., 2026, Streamflow and surface-water presence data availability across the conterminous United States: A review for headwater systems: Hydrological Processes, v. 40, no. 5, e70572, 17 p., https://doi.org/10.1002/hyp.70572.","productDescription":"e70572, 17 p.","ipdsId":"IP-181989","costCenters":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"links":[{"id":505459,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/hyp.70572","text":"Publisher Index Page"},{"id":505086,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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Fungal litter mats, formed by agaric decomposer fungi, play a crucial role in stabilizing slopes, preventing erosion, and aiding nutrient cycling; however, little is known about how warming affects litter mat growth and function. We investigated two litter mat-forming fungi, Gymnopus johnstonii and Marasmius aff. crinis-equi, in warmed (+4°C above ambient) and control plots in the Luquillo Experimental Forest, Puerto Rico. Growth and time-to-leaf colonization were monitored over 6 weeks in spring (both species) and summer (G. johnstonii only). We hypothesized that warming would inhibit fungal mat growth and slow leaf colonization, particularly for G. johnstonii since it is drought sensitive. As expected, warming significantly reduced relative growth rates (RGR) in spring, though M. aff. crinis-equi showed slightly higher RGR than G. johnstonii. Leaf colonization was also delayed by 22% in warmed plots, with M. aff. crinis-equi colonizing leaves 4.3 times faster than G. johnstonii. There were significant seasonal differences in response to warming for G. johnstonii, with warming increasing RGR during the consistently wetter summer sampling period. Overall, warming led to significant inhibition of leaf colonization when conditions were dry, whereas there was a trend toward increased colonization in warm and wet conditions. Our findings suggest that warming, combined with drier conditions, is likely to suppress drought-sensitive fungal mat growth, reducing their ability to prevent nutrient and soil loss via erosion.
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Projected warming and more frequent hurricanes in these ecosystems may alter soil CH4 sink strength, as warmer and wetter soils enhance methanogenesis activity. We measured soil CH4 and CO2 efflux during the calendar summer months of 2023 and 2024 alongside continuous records of soil moisture, soil and air temperature, and precipitation in an in–situ warming experiment (TRACE) located in a lowland tropical forest in Puerto Rico, six to seven years after Hurricanes Irma and Maria (2017). The realized warming (∼1.95°C) enhanced soil respiration only in summer 2023 (p < 0.05), but net soil CH4 uptake was invariant in both campaigns (p > 0.05). Instead, sampling day and between–plot variability explained soil CH4 dynamics much more than treatment contrasts. Importantly, CH4 uptake was consistently coupled to CO2 efflux, suggesting tight linkages between methanotrophic and heterotrophic activities. Between treatments, CH4 and CO2 responses to soil temperature variation were less sensitive in warmed plots, which may suggest weak metabolic upregulation under elevated temperatures. Together, these findings indicate that lowland tropical soils remain CH4 sink even under warming and years after hurricane disturbance, with CH4 dynamics driven more by spatial and temporal variability than experimental warming. Long–term, high–resolution monitoring integrating soil biogeochemistry and microbial processes will be critical to determine whether the observed net CH4 uptake signal represents a sustainable or transient response under continued warming and disturbance.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.agrformet.2026.111225","usgsCitation":"Larocca Conte, G., Zuvela, L., Cruz-Perez, R., Barreto-Vélez, T., Becerra-Santillan, N., Campbell, S.F., Chu, H.P., Dam, T., Grullón-Penkova, I.F., Kleit, M., Ortiz-Iglesias, D.A., Rubio-Lebrón, L.C., Cavaleri, M.A., Reed, S., Sihi, D., Wood, T.E., and O'Connell, C.S., 2026, Lowland tropical forests remain a methane sink under warming and long-term hurricane disturbance recovery: Agricultural and Forest Meteorology, v. 386, 111225, 19 p., https://doi.org/10.1016/j.agrformet.2026.111225.","productDescription":"111225, 19 p.","ipdsId":"IP-188749","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":505051,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.agrformet.2026.111225","text":"Publisher Index Page"},{"id":504960,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Puerto Rico, Sabana Field Research Station","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -65.66450414218644,\n 18.4096612\n ],\n [\n -65.8397851,\n 18.4096612\n ],\n [\n -65.8397851,\n 18.3\n ],\n [\n -65.66450414218644,\n 18.3\n ],\n [\n -65.66450414218644,\n 18.4096612\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"386","noUsgsAuthors":false,"publicationDate":"2026-05-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Larocca Conte, Gabriele","contributorId":371740,"corporation":false,"usgs":false,"family":"Larocca Conte","given":"Gabriele","affiliations":[{"id":88199,"text":"Department of Biology, Schmid College of Science and Technology, Chapman University, 1 University Dr, Orange, CA 92866, USA","active":true,"usgs":false}],"preferred":false,"id":962296,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zuvela, Lucia","contributorId":371741,"corporation":false,"usgs":false,"family":"Zuvela","given":"Lucia","affiliations":[{"id":88200,"text":"Department of Environmental Studies, Macalester College, 1600 Grand Ave, St Paul, MN 55105, United States of America","active":true,"usgs":false}],"preferred":false,"id":962297,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cruz-Perez, Rachel","contributorId":371742,"corporation":false,"usgs":false,"family":"Cruz-Perez","given":"Rachel","affiliations":[{"id":88201,"text":"Department of Ecosystem Science and Management, Penn State, 201 Old Main, University Park, PA 16802, United States of America","active":true,"usgs":false}],"preferred":false,"id":962298,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barreto-Vélez, Tatiana","contributorId":371743,"corporation":false,"usgs":false,"family":"Barreto-Vélez","given":"Tatiana","affiliations":[{"id":88204,"text":"U.S.D.A. 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Plant Sciences Initiative, North Carolina State University, Raleigh, NC 27695, United States of America","active":true,"usgs":false}],"preferred":false,"id":962310,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Wood, Tana E.","contributorId":197805,"corporation":false,"usgs":false,"family":"Wood","given":"Tana","middleInitial":"E.","affiliations":[],"preferred":false,"id":962320,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"O'Connell, Christine S.","contributorId":371758,"corporation":false,"usgs":false,"family":"O'Connell","given":"Christine","middleInitial":"S.","affiliations":[{"id":88216,"text":"Department of Environmental Studies, Macalester College, St. Paul, MN, USA; Biology Program, Chapman University, Orange, CA, USA","active":true,"usgs":false}],"preferred":false,"id":962321,"contributorType":{"id":1,"text":"Authors"},"rank":17}]}} ,{"id":70276574,"text":"70276574 - 2026 - Putting weight to work: A review and examples of weight-based indicators in freshwater fish stock assessment","interactions":[],"lastModifiedDate":"2026-06-09T16:17:19.51464","indexId":"70276574","displayToPublicDate":"2026-05-23T09:14:14","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":"Putting weight to work: A review and examples of weight-based indicators in freshwater fish stock assessment","docAbstract":"Despite being a direct measure of biomass and central to fisheries management, weight-based metrics remain underutilized in freshwater fish stock assessment. Here, we present a concise review of the application of weight in evaluating freshwater fish populations. We examine the historical use of weighing, assess how weight is applied across subdisciplines of freshwater fish science, contrast weight- and length-based approaches, and identify biases in their application. We then synthesize weight-based metrics, indices, and models within four broad categories—population and community weight structure; condition, growth, and efficiency; reproductive potential and production; and yield and exploitation dynamics—highlighting approaches that inform fish ecology, population and community dynamics, and vital rates. We conclude by identifying key opportunities and methodological innovations needed to expand the effective use of weight-based metrics in freshwater fish conservation and management.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/najfmt/vqag021","usgsCitation":"Miranda, L.E., Angulo-Valencia, M.A., and Fraser, C.E., 2026, Putting weight to work: A review and examples of weight-based indicators in freshwater fish stock assessment: North American Journal of Fisheries Management, vqag021, 27 p., https://doi.org/10.1093/najfmt/vqag021.","productDescription":"vqag021, 27 p.","ipdsId":"IP-184202","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":505242,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"edition":"Online First","noUsgsAuthors":false,"publicationDate":"2026-05-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Miranda, Leandro E. 0000-0002-2138-7924 smiranda@usgs.gov","orcid":"https://orcid.org/0000-0002-2138-7924","contributorId":531,"corporation":false,"usgs":true,"family":"Miranda","given":"Leandro","email":"smiranda@usgs.gov","middleInitial":"E.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":962704,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Angulo-Valencia, Mirtha A.","contributorId":372064,"corporation":false,"usgs":false,"family":"Angulo-Valencia","given":"Mirtha","middleInitial":"A.","affiliations":[{"id":88247,"text":"Department of Wildlife and Fisheries, Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":962705,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fraser, Camren E.","contributorId":372065,"corporation":false,"usgs":false,"family":"Fraser","given":"Camren","middleInitial":"E.","affiliations":[{"id":88247,"text":"Department of Wildlife and Fisheries, Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":962706,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70276560,"text":"70276560 - 2026 - Colonization of southern flying squirrels (Glaucomys volans) to urban Nebraska: Range expansion or human assisted translocation?","interactions":[],"lastModifiedDate":"2026-06-09T16:34:45.607344","indexId":"70276560","displayToPublicDate":"2026-05-22T09:30:03","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1324,"text":"Conservation Genetics","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Colonization of southern flying squirrels (Glaucomys volans) to urban Nebraska: Range expansion or human assisted translocation?","title":"Colonization of southern flying squirrels (Glaucomys volans) to urban Nebraska: Range expansion or human assisted translocation?","docAbstract":"Southern flying squirrels (Glaucomys volans; Linnaeus 1758) were first observed in Lincoln, Nebraska, in 2018, 80 km north of their described range. Given that southern flying squirrels are a species of concern within Nebraska, determining the origin of this new population (natural expansion or pet-trade) garnered interest from state biologists. Further, the recent colonization of Lincoln by southern flying squirrels presents a unique opportunity to investigate the genetic implications of a founding event on a small arboreal mammal. The Lincoln population had genetic characteristics suggestive of a single-event colonization with fewer rare alleles and lower genetic diversity than potential source populations and a high genetic variation between populations. Sample size and absence of other geographically close populations in our data set make it difficult to ascertain the origin of the Lincoln population. Based on shared co-ancestry and membership assignment clustering algorithms, the Lincoln population had greater genetic associations with an individual sampled from the native south-eastern Nebraska population relative to other studied locations, suggesting that Lincoln was colonized by a native population.
","language":"English","publisher":"Springer Nature","doi":"10.1007/s10592-026-01792-9","usgsCitation":"Wettschreck, J., Wilson, J.A., Wilson, R.E., May, A., Cary, M., Huebschman, J., and Sonsthagen, S.A., 2026, Colonization of southern flying squirrels (Glaucomys volans) to urban Nebraska: Range expansion or human assisted translocation?: Conservation Genetics, v. 27, 66, 7 p., https://doi.org/10.1007/s10592-026-01792-9.","productDescription":"66, 7 p.","ipdsId":"IP-183335","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":505482,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10592-026-01792-9","text":"Publisher Index Page"},{"id":505245,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nebraska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -104.09447930516654,\n 43.04276398641218\n ],\n [\n -96.3813287,\n 42.8383542\n ],\n [\n -95.40026609068622,\n 39.874800683508454\n ],\n [\n -101.8845684,\n 40.0186153\n ],\n [\n -102.0418976,\n 41.0314411\n ],\n [\n -104.1030619,\n 41.0174538\n ],\n [\n -104.09447930516654,\n 43.04276398641218\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"27","noUsgsAuthors":false,"publicationDate":"2026-05-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Wettschreck, Jennifer","contributorId":372023,"corporation":false,"usgs":false,"family":"Wettschreck","given":"Jennifer","affiliations":[{"id":16944,"text":"University of Nebraska-Omaha","active":true,"usgs":false}],"preferred":false,"id":962667,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wilson, James A.","contributorId":372024,"corporation":false,"usgs":false,"family":"Wilson","given":"James","middleInitial":"A.","affiliations":[{"id":16944,"text":"University of Nebraska-Omaha","active":true,"usgs":false}],"preferred":false,"id":962668,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wilson, Robert E.","contributorId":372025,"corporation":false,"usgs":false,"family":"Wilson","given":"Robert","middleInitial":"E.","affiliations":[{"id":16610,"text":"University of Nebraska-Lincoln","active":true,"usgs":false}],"preferred":false,"id":962669,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"May, Abby","contributorId":372026,"corporation":false,"usgs":false,"family":"May","given":"Abby","affiliations":[{"id":16610,"text":"University of Nebraska-Lincoln","active":true,"usgs":false}],"preferred":false,"id":962670,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cary, Megan","contributorId":372027,"corporation":false,"usgs":false,"family":"Cary","given":"Megan","affiliations":[{"id":16610,"text":"University of Nebraska-Lincoln","active":true,"usgs":false}],"preferred":false,"id":962671,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Huebschman, Jeffrey","contributorId":372028,"corporation":false,"usgs":false,"family":"Huebschman","given":"Jeffrey","affiliations":[{"id":16610,"text":"University of Nebraska-Lincoln","active":true,"usgs":false}],"preferred":false,"id":962672,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sonsthagen, Sarah A. 0000-0001-6215-5874","orcid":"https://orcid.org/0000-0001-6215-5874","contributorId":353767,"corporation":false,"usgs":true,"family":"Sonsthagen","given":"Sarah","middleInitial":"A.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":962673,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70276280,"text":"70276280 - 2026 - Biochar modulates the dynamics of legacy nutrients in enhancing soil health and crop productivity","interactions":[],"lastModifiedDate":"2026-05-26T14:24:39.646272","indexId":"70276280","displayToPublicDate":"2026-05-22T09:17:54","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2596,"text":"Land","active":true,"publicationSubtype":{"id":10}},"title":"Biochar modulates the dynamics of legacy nutrients in enhancing soil health and crop productivity","docAbstract":"Most major crops in agricultural soils exhibit relatively low nutrient use efficiency for nitrogen (N), phosphorus (P), and potassium (K), often necessitating supplemental nutrient inputs to achieve sustainable yields. Furthermore, the increasing use of biowastes such as compost, manure, and biosolids, which frequently have nutrient ratios that do not match crop requirements, has contributed to excessive nutrient inputs and subsequent accumulation in soils. This situation has been further exacerbated by intensive farming practices involving multiple cropping cycles per season. Overuse of nutrients causes them to accumulate in the soil, creating a legacy nutrient pool. The application of biochar as soil amendment is considered a potential strategy to control legacy nutrients dynamics. The current review inspects the possible value of biochar in modulating legacy nutrient reserves in the soil, thereby increasing the bioavailability of nutrients and improving crop yield. This review discusses the search scope and synthesis approaches for the bibliometric methodological component through rigorous screening process (Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA)), focusing on journal articles published in last 20 years that specifically address legacy nutrient management. The significance of the economic and environmental effects of legacy nutrients and the insufficient knowledge of how biochar application influences nutrient dynamics in soil highlight the necessity for additional research to address current gaps.
","language":"English","publisher":"MDPI","doi":"10.3390/land15060896","usgsCitation":"Kumar, M., Bolan, S., Kumar, R., Gupta, J., Chen, D., Wu, H., Stackpoole, S.M., Chandel, N., Mukherjee, S., Chandra Garg, M., Mayilswami, S., Siddique, K.H., and Bolan, N., 2026, Biochar modulates the dynamics of legacy nutrients in enhancing soil health and crop productivity: Land, v. 15, no. 6, 896, 38 p., https://doi.org/10.3390/land15060896.","productDescription":"896, 38 p.","ipdsId":"IP-178871","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":504809,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/land15060896","text":"Publisher Index Page"},{"id":504694,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"15","issue":"6","noUsgsAuthors":false,"publicationDate":"2026-05-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Kumar, Manish 0000-0002-1444-5508","orcid":"https://orcid.org/0000-0002-1444-5508","contributorId":371510,"corporation":false,"usgs":false,"family":"Kumar","given":"Manish","affiliations":[{"id":88165,"text":"Amity Institute of Environmental Sciences (AIES), Amity University Uttar Pradesh (AUUP), Noida, India","active":true,"usgs":false}],"preferred":false,"id":961932,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bolan, Shiv","contributorId":371511,"corporation":false,"usgs":false,"family":"Bolan","given":"Shiv","affiliations":[{"id":88166,"text":"UWA School of Agriculture and Environment, The University of Western Australia, Perth, Western Australia 6009, Australia","active":true,"usgs":false}],"preferred":false,"id":961933,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kumar, Rakesh 0000-0001-7264-5682","orcid":"https://orcid.org/0000-0001-7264-5682","contributorId":371512,"corporation":false,"usgs":false,"family":"Kumar","given":"Rakesh","affiliations":[{"id":88167,"text":"Department of Biosystems Engineering, Auburn University, Auburn, Alabama, USA","active":true,"usgs":false}],"preferred":false,"id":961934,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gupta, Juhi","contributorId":371513,"corporation":false,"usgs":false,"family":"Gupta","given":"Juhi","affiliations":[{"id":88165,"text":"Amity Institute of Environmental Sciences (AIES), Amity University Uttar Pradesh (AUUP), Noida, India","active":true,"usgs":false}],"preferred":false,"id":961935,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chen, Dingjiang","contributorId":371514,"corporation":false,"usgs":false,"family":"Chen","given":"Dingjiang","affiliations":[{"id":88168,"text":"College of Environmental & Resource Sciences, Zhejiang University, Hangzhou 310058, China","active":true,"usgs":false}],"preferred":false,"id":961936,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wu, Hao","contributorId":254382,"corporation":false,"usgs":false,"family":"Wu","given":"Hao","email":"","affiliations":[{"id":25550,"text":"Virginia Polytechnic Institute and State University","active":true,"usgs":false}],"preferred":false,"id":961937,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Stackpoole, Sarah M. 0000-0002-5876-4922","orcid":"https://orcid.org/0000-0002-5876-4922","contributorId":211238,"corporation":false,"usgs":true,"family":"Stackpoole","given":"Sarah","email":"","middleInitial":"M.","affiliations":[{"id":37277,"text":"WMA - 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2026 - Tracking toxins: A pilot investigation of cyanotoxins in north-central Tennessee’s surface waters and wells","interactions":[],"lastModifiedDate":"2026-05-26T14:02:41.487505","indexId":"70276275","displayToPublicDate":"2026-05-22T08:56:58","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":21640,"text":"Toxins","active":true,"publicationSubtype":{"id":10}},"title":"Tracking toxins: A pilot investigation of cyanotoxins in north-central Tennessee’s surface waters and wells","docAbstract":"Cyanobacterial toxins (cyanotoxins) threaten aquatic ecosystems and human health, yet the factors influencing their production and distribution in freshwater remain unclear. In north-central Tennessee, nutrient-rich runoff from agricultural and urban areas, combined with a karst landscape that supports drinking and recreational water use, heightens the need to understand cyanotoxin behavior. To examine cyanotoxin patterns, the U.S. Geological Survey and the Tennessee Department of Environment and Conservation monitored 18 sites, including two wells under the influence of surface water, every two weeks from September 2022 to November 2024. At least one cyanotoxin was detected at all sites, with the highest concentrations in deep reservoirs and lower levels in shallow systems. Most detections occurred during summer and fall, aligning with high temperatures and rapid-onset drought. Statistical analysis indicated that increased specific conductivity and pH raised the likelihood of detecting total microcystin, likely resulting from drought conditions and nutrient-laden runoff. Additionally, dissolved microcystin showed an inverse relationship with Cumberland River water levels, and principal component analysis showed that Secchi depth, chlorophyll a, pH, temperature, and conductivity explained most water quality variability. These results help increase understanding of cyanotoxin distribution and associated water quality conditions during detections to guide future freshwater cyanotoxin monitoring studies.
","language":"English","publisher":"MDPI","doi":"10.3390/toxins18060239","usgsCitation":"Hill, K., Jaegge, A., Moore, D.M., and Byl, T.D., 2026, Tracking toxins: A pilot investigation of cyanotoxins in north-central Tennessee’s surface waters and wells: Toxins, v. 18, no. 6, 239, 27 p., https://doi.org/10.3390/toxins18060239.","productDescription":"239, 27 p.","ipdsId":"IP-176988","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":504806,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/toxins18060239","text":"Publisher Index Page"},{"id":504691,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Tennessee","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.2198843,\n 36.3818454\n ],\n [\n -86.7499179,\n 36.3854487\n ],\n [\n -86.2620481,\n 36.3782418\n ],\n [\n -86.25309635196582,\n 35.83582592918192\n ],\n [\n -87.22212220072319,\n 35.83582592918192\n ],\n [\n -87.2198843,\n 36.3818454\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"18","issue":"6","noUsgsAuthors":false,"publicationDate":"2026-05-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Hill, Kristi Lynn 0000-0003-2771-0849","orcid":"https://orcid.org/0000-0003-2771-0849","contributorId":296396,"corporation":false,"usgs":true,"family":"Hill","given":"Kristi Lynn","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":961924,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jaegge, Andrea 0000-0002-4414-2620","orcid":"https://orcid.org/0000-0002-4414-2620","contributorId":371504,"corporation":false,"usgs":false,"family":"Jaegge","given":"Andrea","affiliations":[{"id":81602,"text":"Tennessee Department of Environment and Conservation","active":true,"usgs":false}],"preferred":false,"id":961925,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Moore, Devin M.","contributorId":371505,"corporation":false,"usgs":false,"family":"Moore","given":"Devin","middleInitial":"M.","affiliations":[{"id":13370,"text":"Tennessee State University","active":true,"usgs":false}],"preferred":false,"id":961926,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Byl, Thomas D. 0000-0001-6907-9149 tdbyl@usgs.gov","orcid":"https://orcid.org/0000-0001-6907-9149","contributorId":583,"corporation":false,"usgs":true,"family":"Byl","given":"Thomas","email":"tdbyl@usgs.gov","middleInitial":"D.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":961927,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70276302,"text":"70276302 - 2026 - Waves, watersheds, and sediment in a coral reef embayment: Towards parsimonious models of accumulation and composition","interactions":[],"lastModifiedDate":"2026-05-27T14:03:54.905785","indexId":"70276302","displayToPublicDate":"2026-05-22T08:55:10","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1587,"text":"Estuarine, Coastal and Shelf Science","active":true,"publicationSubtype":{"id":10}},"title":"Waves, watersheds, and sediment in a coral reef embayment: Towards parsimonious models of accumulation and composition","docAbstract":"High sedimentation rates can damage coral reef ecosystems. Sedimentation rates are controlled by both sediment loads from watersheds and resuspension by waves and associated circulation patterns, but the outcomes are system specific and difficult to predict. The percent terrigenous (non-organic and non-carbonaceous) material in sediment is also often used as an indicator of watershed influence, but its dynamics are poorly understood. Sediment accumulation rates, particle size, and percent terrigenous were monitored quasi-monthly for one year (March 2014-April 2015) at nine sites in a coral reef-fringed embayment in American Samoa, where an aggregate quarry had increased sediment loads to the coast but mitigation reduced loads during the monitored period. Gross and net sediment accumulation rates were measured using sediment traps and SedPods (pods), respectively. Gross accumulation rates exceeded thresholds for impacts on coral health during at least one collection period at most sites, with more exceedances on the northern reef where water residence times and sediment availability are higher and corals show signs of sediment stress. Percent terrigenous of coarse sediment was higher in the traps and pods compared with the surrounding benthic sediment, indicating that some of the terrigenous sediment was advected through the bay without accumulating on the reef. The 95th percentile of hourly wave energy density (E95) taken from a global wave model (WaveWatch 3) was the best predictor of gross accumulation rates of both total and carbonate sediment in a log-log regression at most (n = 6) sites (R2 range 0.72-0.92), indicating a strong role of resuspension of benthic sediment. Gross accumulation rates of terrigenous sediment were not correlated with E95 and only correlated with SSY at the site nearest the stream mouth, indicating that most terrigenous sediment was not from resuspended benthic material but rather from a consistent watershed source. Percent terrigenous decreased with increasing wave energy due to high accumulation rates of carbonates during periods of high wave energy. Detection of the impact of sediment mitigation at the quarry on sediment accumulation was complicated by low wave energy in the period following mitigation. The use of gross accumulation rates and percent terrigenous as indicators of the magnitude and sources of sediment accumulation over time needs to account for wave-induced resuspension, which can be modelled with a simple power function using inputs from a global wave model.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecss.2026.109952","usgsCitation":"Biggs, T., Messina, A., and Storlazzi, C.D., 2026, Waves, watersheds, and sediment in a coral reef embayment: Towards parsimonious models of accumulation and composition: Estuarine, Coastal and Shelf Science, no. 339, 109952, 16 p., https://doi.org/10.1016/j.ecss.2026.109952.","productDescription":"109952, 16 p.","ipdsId":"IP-176787","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":504811,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecss.2026.109952","text":"Publisher Index Page"},{"id":504731,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"American Samoa, Faga'alu Bay, Tutuila Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -170.686,\n -14.286\n ],\n [\n -170.674,\n -14.286\n ],\n [\n -170.674,\n -14.296\n ],\n [\n -170.686,\n -14.296\n ],\n [\n -170.686,\n -14.286\n ]\n ]\n ]\n }\n }\n ]\n}","issue":"339","noUsgsAuthors":false,"publicationDate":"2026-05-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Biggs, Trent","contributorId":208268,"corporation":false,"usgs":false,"family":"Biggs","given":"Trent","affiliations":[],"preferred":false,"id":962036,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Messina, Alex","contributorId":174670,"corporation":false,"usgs":false,"family":"Messina","given":"Alex","email":"","affiliations":[],"preferred":false,"id":962037,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Storlazzi, Curt D. 0000-0001-8057-4490","orcid":"https://orcid.org/0000-0001-8057-4490","contributorId":213610,"corporation":false,"usgs":true,"family":"Storlazzi","given":"Curt","middleInitial":"D.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":962038,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ]}