Managed aquifer recharge is a widespread practice for storing water in the subsurface as groundwater. At a managed aquifer recharge facility in southern Arizona, groundwater-level and repeat microgravity data were collected to monitor aquifer response. These data were used to inform parameter identification for an unsaturated-zone flow model used to simulate the recharge process. The facility, the Southeast Houghton Artificial Recharge Project (SHARP), consists of 3 surface basins (about 27,600 square meters [6.8 acres] total surface area) where recycled water is distributed in recharge cycles lasting several months, with dry periods in between. During the study period, December 2020–December 2022, Tucson Water (the City of Tucson’s water utility) reported 6.56×106 cubic meters of water (5,320 acre-feet) recharged.
Monitoring included groundwater-level observations at 3 monitoring wells and repeat microgravity measurements at as many as 22 locations (some stations were destroyed between surveys). Six gravity surveys were carried out using absolute- and relative-gravity meters. Large gravity increases, more than 250 microgals, were observed during the first repeat survey, 3.5 months after the start of recharge, but only in the immediate vicinity of the recharge basins. Data show that water moved downward to the water table, and storage changes in the unsaturated zone away from the facility were likely minimal. Gravity decreased at stations more than 1 kilometer from the facility, consistent with regional groundwater-level changes. Groundwater-level increases in wells adjacent to the recharge basins began 2 months after the second repeat gravity survey, and 5.5 months after recharge began.
Unsaturated-zone flow modeling was carried out using software that simulates water movement and parameter estimation. Model calibration was carried out by minimizing an objective function calculated from the differences between simulated and observed groundwater levels, and between simulated and observed repeat microgravity data. Including repeat microgravity data in the objective function reduced the uncertainty in estimated parameter values for saturated hydraulic conductivity and saturated water content. Modeling indicated that the unsaturated zone between the recharge basins and the water table does not become saturated even after 685 days of simulated infiltration. This gradual wetting may account for increasing infiltration rates over time, as hydraulic conductivity increases with increasing water content. Unsaturated-zone water content decreased rapidly between recharge cycles. Model-simulated groundwater mounding extended about 1 kilometer from the center of SHARP after the 685-day period following the onset of recharge.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255017","collaboration":"Prepared in cooperation with Tucson Water","programNote":"Water Availability and Use Program","usgsCitation":"Wildermuth, L.M., Kennedy, J.R., and Conrad, J.L., 2025, Groundwater response to managed aquifer recharge at the Southeast Houghton Artificial Recharge Project in Tucson, Arizona: U.S. Geological Survey Scientific Investigations\nReport 2025–5017, 38 p., https://doi.org/10.3133/sir20255017.","productDescription":"Report: v, 38 p.; Data Release","numberOfPages":"38","onlineOnly":"Y","ipdsId":"IP-152298","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":497795,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118986.htm"},{"id":495375,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9E19SSK","text":"USGS data release","description":"Landrum, M.T., 2021, Repeat microgravity data from South Houghton Area Recharge Project, Tucson, Arizona, 2020-2022 (ver. 2.0, August 2024): U.S. Geological Survey data release, https://doi.org/10.5066/P9E19SSK.","linkHelpText":"Repeat microgravity data from South Houghton Area Recharge Project, Tucson, Arizona, 2020-2022 (ver. 2.0, August 2024)"},{"id":495371,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5017/sir20255017.pdf","text":"Report","size":"35 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5017 PDF"},{"id":495370,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5017/coverthb.jpg"},{"id":495372,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255017/full","linkFileType":{"id":5,"text":"html"},"description":"SIR 2025-5017 HTML"},{"id":495374,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5017/images"},{"id":495373,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5017/sir20255017.XML","description":"SIR 2025-5017 XML"}],"country":"United States","state":"Arizona","city":"Tucson","otherGeospatial":"Southeast Houghton Artificial Recharge Project","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -110.758333,\n 32.159722\n ],\n [\n -110.758333,\n 32.141667\n ],\n [\n -110.791667,\n 32.141667\n ],\n [\n -110.791667,\n 32.159722\n ],\n [\n -110.758333,\n 32.159722\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director,
Arizona Water Science Center
U.S. Geological Survey
520 N. Park Avenue
Tucson, AZ 85719
Despite their ubiquity and importance as freshwater habitat, small headwater streams are under-monitored by existing stream gage networks. To address this gap, we describe a low-cost, non-contact, and low-effort method that enables organizations to monitor relative streamflow dynamics in small headwater streams. The method uses a camera to capture repeat images of the stream from a fixed position. A person then annotates pairs of images, in each case indicating which image has more apparent streamflow or indicating equal flow if no difference is discernible. A deep learning modeling framework called streamflow rank estimation (SRE) is then trained on the annotated image pairs and applied to rank all images from highest to lowest apparent streamflow. From this result a relative hydrograph can be derived. We found that our modeled relative hydrograph dynamics matched the observed hydrograph dynamics well for 11 cameras at 8 streamflow sites in western Massachusetts. Higher performance was observed during the annotation period (median Kendall's Tau rank correlation of 0.75, with a range of 0.6–0.83) than after it (median Kendall's Tau of 0.59, with range 0.34–0.74). We found that annotation performance was generally consistent across the 11 camera sites and 2 individual annotators and was positively correlated with streamflow variability at a site. A scaling simulation determined that model performance improvements were limited after 1000 annotation pairs. Our model's estimates of relative flow, while not equivalent to absolute flow, may still be useful for many applications, such as ecological modeling and calculating event-based hydrological statistics (e.g., the number of out-of-bank floods). We anticipate that this method will be a valuable tool to extend existing stream monitoring networks and provide new insights on dynamic headwater systems.
","language":"English","publisher":"European Geosciences Union","doi":"10.5194/hess-29-6445-2025","usgsCitation":"Goodling, P.J., Fair, J.H., Gupta, A., Walker, J.D., Dubreuil, T., Hayden, M.J., and Letcher, B., 2025, Technical note: A low-cost approach to monitoring relative streamflow dynamics in small headwater streams using time lapse imagery and a deep learning model: Hydrology and Earth System Sciences, v. 29, no. 22, p. 6445-6460, https://doi.org/10.5194/hess-29-6445-2025.","productDescription":"16 p.","startPage":"6445","endPage":"6460","ipdsId":"IP-179122","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":496753,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/hess-29-6445-2025","text":"Publisher Index Page"},{"id":496681,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Massachusetts","otherGeospatial":"western Massachusetts","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -72.82742857720734,\n 42.73921316092924\n ],\n [\n -72.82742857720734,\n 42.42241182456118\n ],\n [\n -72.32535093532236,\n 42.42241182456118\n ],\n [\n -72.32535093532236,\n 42.73921316092924\n ],\n [\n -72.82742857720734,\n 42.73921316092924\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"29","issue":"22","noUsgsAuthors":false,"publicationDate":"2025-11-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Goodling, Phillip J. 0000-0001-5715-8579","orcid":"https://orcid.org/0000-0001-5715-8579","contributorId":239738,"corporation":false,"usgs":true,"family":"Goodling","given":"Phillip","email":"","middleInitial":"J.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":950550,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fair, Jennifer H. 0000-0002-9902-1893","orcid":"https://orcid.org/0000-0002-9902-1893","contributorId":245941,"corporation":false,"usgs":true,"family":"Fair","given":"Jennifer","middleInitial":"H.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":950551,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gupta, Amrita 0000-0003-2643-5865","orcid":"https://orcid.org/0000-0003-2643-5865","contributorId":264600,"corporation":false,"usgs":false,"family":"Gupta","given":"Amrita","email":"","affiliations":[{"id":54512,"text":"Georgia Institute of Techniology","active":true,"usgs":false}],"preferred":false,"id":950552,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Walker, Jeffrey D. 0000-0003-1923-6550","orcid":"https://orcid.org/0000-0003-1923-6550","contributorId":244114,"corporation":false,"usgs":false,"family":"Walker","given":"Jeffrey","middleInitial":"D.","affiliations":[{"id":48839,"text":"Walker Environmental Research LLC","active":true,"usgs":false}],"preferred":false,"id":950553,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dubreuil, Todd 0000-0003-0189-4336","orcid":"https://orcid.org/0000-0003-0189-4336","contributorId":217872,"corporation":false,"usgs":true,"family":"Dubreuil","given":"Todd","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":950554,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hayden, Michael J. 0000-0002-9010-6831","orcid":"https://orcid.org/0000-0002-9010-6831","contributorId":291388,"corporation":false,"usgs":true,"family":"Hayden","given":"Michael","middleInitial":"J.","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":950555,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Letcher, Benjamin H. 0000-0003-0191-5678","orcid":"https://orcid.org/0000-0003-0191-5678","contributorId":315442,"corporation":false,"usgs":true,"family":"Letcher","given":"Benjamin H.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":950556,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70272456,"text":"70272456 - 2025 - Aridity reduces lag times between aquatic and terrestrial dry-down among watersheds and across years in the northwest US","interactions":[],"lastModifiedDate":"2025-11-21T18:28:47.238214","indexId":"70272456","displayToPublicDate":"2025-11-18T12:22:05","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Aridity reduces lag times between aquatic and terrestrial dry-down among watersheds and across years in the northwest US","docAbstract":"Landscapes encompass both aquatic and terrestrial ecosystems that experience the same climate but may respond to climate in divergent ways. For example, the time lag between seasonal dry-down of terrestrial soil moisture and decline in streamflow has important implications for species and ecosystem processes across the aquatic–terrestrial interface. How these lags between aquatic and terrestrial hydrology vary with climate and spatial location within watersheds remains largely unexplored. Here, we examine seasonal patterns of aquatic–terrestrial dry-down across seven watersheds in the northwestern USA, spanning a wide range of aridity. We compared daily streamflow data from USGS gages at watershed outlets with simulated daily soil moisture (1979–2020) from multiple locations within each watershed. In all watersheds, annual dry cycles progressed sequentially through the following features: evapotranspiration, precipitation, shallow soil moisture, deep soil moisture, and finally streamflow. Seasonal streamflow minima lagged behind soil moisture minima for shorter durations in more arid watersheds and drier years. Within watersheds, lag times varied spatially due to interactions between elevation and aridity, with short lags in low-elevation soils near streams in arid watersheds and longer lags in less arid watersheds. Collectively, these results indicate shorter lags between seasonal aquatic and terrestrial dry periods in drier watersheds and years, and show that these tighter linkages are spatially aggregated in drier watersheds. The co-occurrence of seasonally dry conditions in both aquatic and terrestrial systems under increasing aridification is likely to intensify stressors on ecosystems and services. Recognizing these patterns may be critical for predicting ecosystem vulnerabilities and informing adaptation strategies to mitigate the impacts of seasonally dry conditions.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.70413","usgsCitation":"Butterfield, B.J., Schlaepfer, D.R., Al-Chokhachy, R., Dunham, J., Groom, J.D., Muhlfeld, C.C., Torgersen, C.E., and Bradford, J., 2025, Aridity reduces lag times between aquatic and terrestrial dry-down among watersheds and across years in the northwest US: Ecosphere, v. 16, no. 11, e70413, 14 p., https://doi.org/10.1002/ecs2.70413.","productDescription":"e70413, 14 p.","ipdsId":"IP-176106","costCenters":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":49226,"text":"Northwest Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":496924,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.70413","text":"Publisher Index Page"},{"id":496783,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana, Oregon, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -119.53311834886665,\n 48.954786193006896\n ],\n [\n -119.53311834886665,\n 42.09524314878942\n ],\n [\n -108.45919024142043,\n 42.09524314878942\n ],\n [\n -108.45919024142043,\n 48.954786193006896\n ],\n [\n -119.53311834886665,\n 48.954786193006896\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"16","issue":"11","noUsgsAuthors":false,"publicationDate":"2025-11-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Butterfield, Bradley J.","contributorId":362927,"corporation":false,"usgs":false,"family":"Butterfield","given":"Bradley","middleInitial":"J.","affiliations":[{"id":86572,"text":"Department of Biological Sciences, Northern Arizona University, Flagstaff, AZ 86011","active":true,"usgs":false}],"preferred":false,"id":950818,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schlaepfer, Daniel Rodolphe 0000-0001-9973-2065","orcid":"https://orcid.org/0000-0001-9973-2065","contributorId":225569,"corporation":false,"usgs":true,"family":"Schlaepfer","given":"Daniel","email":"","middleInitial":"Rodolphe","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":950819,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Al-Chokhachy, Robert 0000-0002-2136-5098","orcid":"https://orcid.org/0000-0002-2136-5098","contributorId":211560,"corporation":false,"usgs":true,"family":"Al-Chokhachy","given":"Robert","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":950820,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dunham, Jason 0000-0002-6268-0633","orcid":"https://orcid.org/0000-0002-6268-0633","contributorId":220078,"corporation":false,"usgs":true,"family":"Dunham","given":"Jason","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":950821,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Groom, Jeremiah D.","contributorId":362928,"corporation":false,"usgs":false,"family":"Groom","given":"Jeremiah","middleInitial":"D.","affiliations":[{"id":86575,"text":"Groom Analytics LLC, 1975 SE Crystal Lake Dr., Unit 173, Corvallis, OR 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Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":950824,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Bradford, John B. 0000-0001-9257-6303","orcid":"https://orcid.org/0000-0001-9257-6303","contributorId":219257,"corporation":false,"usgs":true,"family":"Bradford","given":"John B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":950825,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70271480,"text":"sir20255055 - 2025 - An inset groundwater-flow model to evaluate the effects of layering configuration on model calibration and assess managed aquifer recharge near Shellmound, Mississippi","interactions":[],"lastModifiedDate":"2026-02-03T16:31:45.919091","indexId":"sir20255055","displayToPublicDate":"2025-11-18T12:06:15","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-5055","displayTitle":"An Inset Groundwater-Flow Model to Evaluate the Effects of Layering Configuration on Model Calibration and Assess Managed Aquifer Recharge near Shellmound, Mississippi","title":"An inset groundwater-flow model to evaluate the effects of layering configuration on model calibration and assess managed aquifer recharge near Shellmound, Mississippi","docAbstract":"The U.S. Geological Survey has developed a high-resolution inset groundwater-flow model in the Mississippi Delta as part of an interdisciplinary collaboration coordinated by the Mississippi Alluvial Plain project to provide a tool that stakeholders can use to support water-resource management decisions. Groundwater withdrawals from the Mississippi River Valley alluvial (MRVA) aquifer have been vital to support agricultural production in the region, but substantial groundwater-level declines near Shellmound, Mississippi, have caused concerns for long-term sustainability of the aquifer. To better understand the subsurface and try to mitigate the long-term groundwater-level declines, stakeholders have undertaken actions including a Groundwater Transfer and Injection Pilot (GTIP) project using a riverbank filtration-based managed aquifer recharge approach. The pilot project consisted of extracting groundwater near the Tallahatchie River and reinjecting it into the aquifer 3 kilometers west where water levels have substantially declined. A high-resolution airborne electromagnetic (AEM) survey was also completed to collect electrical resistivity data to support the GTIP project and the development of the groundwater model.
The inset groundwater-flow model was developed to (1) integrate the AEM data into the optimal layering configuration of the MRVA aquifer that the available observation data can support through calibration, and (2) assess the potential effect of the GTIP project on the groundwater levels. The AEM data were processed into three different layering configurations leading to the development of model A (18 layers), model B (16 layers), and model C (8 layers), all at a 100- x 100-meter cell spatial resolution using the U.S. Geological Survey modular finite-difference flow model 6 code with Newton-Raphson formulation. The model development process integrated recent advances in modeling, such as the incorporation of AEM data, the use of outputs from the soil-water-balance (SWB) model, and the Aquaculture and Irrigation Water-Use Model, and was facilitated by robust automation using the open-source python packages Modflow-setup and SFRmaker. Using Parameter Estimation ++ Iterative Ensemble Smoother, the three numerical groundwater-flow models (models A, B, and C) were calibrated against a set of observations, which included aquifer groundwater levels, streamflows, stream stage, and aquifer transmissivity. Results indicate that the detailed representation of MRVA aquifer layers in model A produced the best calibrated model by history matching, and the integration of data representing surficial connectivity played a key role in improving groundwater recharge and enhancing the ability of the model to match groundwater levels in the cone of depression. A forecast model simulated the managed aquifer recharge approach, and the results indicated that, given average irrigation and recharge conditions (2010–15), the GTIP project has the potential to induce groundwater-level increases of as much as 3 meters around the injection site, but a sustained increase would require repetition in subsequent years of water transfer at 2022 rates or above.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255055","collaboration":"Prepared in cooperation with U.S. Department of Agriculture Agricultural Research Service and the Mississippi Department of Environmental Quality","programNote":"Water Availability and Use Science Program","usgsCitation":"Guira, M., Traylor, J.P., Leaf, A.T., and Weisser, A.R., 2025, An inset groundwater-flow model to evaluate the effects of layering configuration on model calibration and assess managed aquifer recharge near Shellmound, Mississippi: U.S. Geological Survey Scientific Investigations Report 2025–5055, 134 p., https://doi.org/10.3133/sir20255055.","productDescription":"Report: ix, 134 p.; 3 Figures: 11.00 x 8.50 inches; Data Release; Dataset","numberOfPages":"148","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-154357","costCenters":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":84311,"text":"Central Plains Water Science Center","active":true,"usgs":true}],"links":[{"id":497793,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118974.htm"},{"id":495719,"rank":8,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/sir/2025/5055/downloads/","text":"Layered figures","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"Downloadable layered PDF files for figures 11, 12, and 13"},{"id":495626,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13DWA86","text":"USGS data release","linkHelpText":"Inset models used to evaluate the effects of layering configuration on model calibration from 1900 to 2018, and assess managed aquifer recharge near Shellmound, Mississippi, from 2019 to 2050"},{"id":495670,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255055/full"},{"id":495623,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5055/sir20255055.XML"},{"id":495622,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5055/sir20255055.pdf","text":"Report","size":"40 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5055"},{"id":495625,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"- USGS water data for the Nation"},{"id":495624,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5055/images/"},{"id":495621,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5055/coverthb.jpg"}],"country":"United States","state":"Mississippi","city":"Shellmound","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -90.55,\n 33.8\n ],\n [\n -90.55,\n 33.5\n ],\n [\n -90.1667,\n 33.5\n ],\n [\n -90.1667,\n 33.8\n ],\n [\n -90.55,\n 33.8\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Nebraska Water Science Center
U.S. Geological Survey
5231 South 19th Street
Lincoln, NE 68512
Western California is home to a variety of volcanic rocks. The locations, ages, and chemical compositions of these volcanic rocks help tell part of the fascinating story of California’s plate tectonic evolution over the past 40 million years. These volcanic rocks are a product of multiple tectonic processes, including subduction of divergent and transform plate boundaries beneath continental North America, opening of a slab window, creation and migration of a tectonic triple junction, and the birth and growth of the San Andreas Fault. This fact sheet explains these tectonic processes and discusses their role in shaping the volcanic history of western California over the past 40 million years. By studying the volcanic rock record in western California, geologists are able to piece together how regional volcanism and plate tectonics are linked in space and time. Recognizing this linkage helps scientists to understand possible future volcanism in the region, potential hazards associated with this volcanism, and the impacts these hazards may have on population and infrastructure. The U.S. Geological Survey California Volcano Observatory (CalVO) closely monitors the parts of western California with the greatest potential for volcanism.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20253013","usgsCitation":"Burgess, S., 2025, Plate tectonics and volcanism in western California: U.S. Geological Survey Fact Sheet 2025–3013, 4 p., https://doi.org/10.3133/fs20253013.","productDescription":"4 p.","numberOfPages":"4","onlineOnly":"N","ipdsId":"IP-163622","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":496594,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2025/3013/fs20253013.pdf","text":"Report","size":"4.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2025-3013 PDF"},{"id":496593,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2025/3013/coverthb.jpg"},{"id":497792,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118954.htm"}],"country":"United States","state":"California","otherGeospatial":"western California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.38733351762187,\n 32.59868901288149\n ],\n [\n -115.3421680410813,\n 32.7504065185027\n ],\n [\n -115.38672450471125,\n 33.9524552673855\n ],\n [\n -121.21290250910971,\n 39.35530704524879\n ],\n [\n -122.17585532159484,\n 40.55715736870522\n ],\n [\n -124.73655671441642,\n 40.36293527192478\n ],\n [\n -122.6851834364515,\n 36.66622910881948\n ],\n [\n -120.14136480939621,\n 32.588636683227534\n ],\n [\n -117.38733351762187,\n 32.59868901288149\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"California Volcano Observatory
Volcano Science Center
U.S. Geological Survey
350 North Akron Road
Moffett Field, CA 94035
Email: askCVO@usgs.gov
In 2021–22, clade 2.3.4.4b highly pathogenic avian influenza (HPAI) viruses were introduced by wild birds into North America, leading to geographically widespread disease. In response to HPAI outbreaks throughout late 2021 and early 2022, we recorded observations of sick and dead birds, estimated abundance of carcasses, collected swab and sera samples to detect viruses, and monitored bird nesting on the Yukon-Kuskokwim Delta region of Alaska to document potential effects of disease. Thirty-six reports of sick and dead birds were registered across the region. Nineteen carcasses were opportunistically collected for diagnostic testing, of which 12 were confirmed to be infected with clade 2.3.4.4b HPAI viruses. Carcass abundance estimates from line-distance sampling provided evidence that the most common species of dead birds from the western Yukon-Kuskokwim Delta region were Cackling Goose (Branta hutchinsii minima), Glaucous Gull (Larus hyperboreus), and Black Brant (Branta bernicla nigricans). Only one paired cloacal and oropharyngeal swab sample from a Northern Pintail (Anas acuta) tested positive for clade 2.3.4.4b HPAI virus, out of 464 live-captured duck and goose samples. Of 195 sera samples from waterfowl screened for antibodies reactive to influenza A viruses, antibodies were found in 41–98% of samples collected from Emperor Goose (Anser canagicus), Cackling Goose, Black Brant, and Spectacled Eider (Somateria fischeri). In addition, 15–98% of the same sera samples were reactive to a clade 2.3.4.4b H5 antigen. Fewer Black Brant and Emperor Goose nests were found on long-term study plots during 2022 than in previous years. Collectively, we found that HPAI viruses affected at least seven species of wild birds inhabiting the region during 2022. The full scope of impacts of HPAI at this location during 2022 is unknown, but our data indicate that acute effects to avian population health on the Yukon-Kuskokwim Delta region were likely modest.
","language":"English","publisher":"Wildlife Disease Association","doi":"10.7589/JWD-D-24-00199","usgsCitation":"Daniels, B., Osnas, E.E., Boldenow, M., Gerlach, R., Ahlstrom, C., Coburn, S., Brook, M.J., Brubaker, M., Fischer, J., Koons, D.N., Matz, A., Murphy, M., Rizzolo, D., Scott, L.C., Sinnett, D.R., Thompson, J.M., Lenoch, J., Kim Torchetti, M., Stallknecht, D., Poulson, R., and Ramey, A.M., 2025, Observational, virological, and serological data provide insights into an outbreak of highly pathogenic avian influenza among wild birds on the Yukon-Kuskokwim Delta, Alaska in 2022: Journal of Wildlife Diseases, v. 61, no. 4, p. 1010-1027, https://doi.org/10.7589/JWD-D-24-00199.","productDescription":"18 p.","startPage":"1010","endPage":"1027","ipdsId":"IP-171898","costCenters":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":496752,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index 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Wisconsin-Stevens Point","active":true,"usgs":false}],"preferred":false,"id":950513,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Lenoch, Juliana","contributorId":347254,"corporation":false,"usgs":false,"family":"Lenoch","given":"Juliana","email":"","affiliations":[{"id":83108,"text":"WS National Wildlife Disease Program, U.S. Department of Agriculture, Fort Collins, CO 80521, USA","active":true,"usgs":false}],"preferred":false,"id":950514,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Kim Torchetti, Mia","contributorId":139355,"corporation":false,"usgs":false,"family":"Kim Torchetti","given":"Mia","email":"","affiliations":[{"id":12747,"text":"USDA APHIS VS National Veterinary Services Laboratories, Ames, IA","active":true,"usgs":false}],"preferred":false,"id":950515,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Stallknecht, David E.","contributorId":225107,"corporation":false,"usgs":false,"family":"Stallknecht","given":"David E.","affiliations":[{"id":36701,"text":"Southeastern Cooperative Wildlife Disease Study, Department of Population Health, College of Veterinary Medicine, University of Georgia","active":true,"usgs":false}],"preferred":false,"id":950516,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Poulson, Rebecca L.","contributorId":198807,"corporation":false,"usgs":false,"family":"Poulson","given":"Rebecca L.","affiliations":[{"id":7125,"text":"Southeastern Cooperative Wildlife Disease Study, College of Veterinary Medicine, University of Georgia, Athens, GA 30602, USA.","active":true,"usgs":false}],"preferred":false,"id":950517,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Ramey, Andrew M. 0000-0002-3601-8400 aramey@usgs.gov","orcid":"https://orcid.org/0000-0002-3601-8400","contributorId":1872,"corporation":false,"usgs":true,"family":"Ramey","given":"Andrew","email":"aramey@usgs.gov","middleInitial":"M.","affiliations":[{"id":117,"text":"Alaska Science Center 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Glacial Maximum limits our ability to assess (1) the drivers of ice-sheet change, and (2) the performance of ice-sheet models that are benchmarked against the paleo-record of GrIS change. Here, we provide new in situ 10Be surface exposure chronologies of ice-sheet margin retreat from the outer Scoresby Sund and Storstrømmen Glacier regions in eastern and northeastern Greenland, respectively. Ice retreated from Rathbone Island, east of Scoresby Sund, by ∼ 14.1 ka, recording some of the earliest documentations of terrestrial deglaciation in Greenland. The mouth of Scoresby Sund deglaciated by ∼ 13.2 ka, and retreated at an average rate of ∼ 43 m yr−1 between 13.2 and 9.7 ka. Storstrømmen Glacier retreated from the outer coast to within ∼ 3 km of the modern ice margin between ∼ 12.7 and 8.6 ka at an average rate of ∼ 28 m yr−1. Retreat then slowed or reached a stillstand as ice retreated ∼ 3 km between ∼ 8.6 ka to the modern ice margin at ∼ 8.0 ka. These retreat rates are consistent with late glacial and Holocene estimates for marine-terminating outlet glaciers across East Greenland, and comparable to modern retreat rates observed at the largest ice streams in northeastern, and northwestern Greenland.
","language":"English","publisher":"European Geosciences Union","doi":"10.5194/cp-21-2263-2025","usgsCitation":"Anderson, J.T., Young, N.E., Balter-Kennedy, A., Prince, K., Walcott-George, C.K., Graham, B.L., Charton, J., Briner, J.P., and Shaefer, J.M., 2025, East Greenland Ice Sheet retreat history from Scoresby Sund and Storstrømmen Glacier during the last deglaciation: Climate of the Past, v. 21, no. 11, p. 2263-2281, https://doi.org/10.5194/cp-21-2263-2025.","productDescription":"19 p.","startPage":"2263","endPage":"2281","ipdsId":"IP-178844","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":496745,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/cp-21-2263-2025","text":"Publisher Index Page"},{"id":496637,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Greenland","otherGeospatial":"Scoresby Sund, Storstrømmen Glacier","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -47.161725727082626,\n 84.57071318603391\n ],\n [\n -47.161725727082626,\n 66.73876185091967\n ],\n [\n -27.30980297025164,\n 64.59666796479314\n ],\n [\n 2.0505995222399918,\n 81.78653428489469\n ],\n [\n -47.161725727082626,\n 84.57071318603391\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"21","issue":"11","noUsgsAuthors":false,"publicationDate":"2025-11-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Anderson, Jacob T. 0000-0002-4329-4200","orcid":"https://orcid.org/0000-0002-4329-4200","contributorId":362365,"corporation":false,"usgs":false,"family":"Anderson","given":"Jacob","middleInitial":"T.","affiliations":[{"id":17701,"text":"Lamont-Doherty Earth Observatory","active":true,"usgs":false}],"preferred":false,"id":950381,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Young, Nicolas E.","contributorId":362367,"corporation":false,"usgs":false,"family":"Young","given":"Nicolas","middleInitial":"E.","affiliations":[{"id":17701,"text":"Lamont-Doherty Earth Observatory","active":true,"usgs":false}],"preferred":false,"id":950382,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Balter-Kennedy, Allie 0000-0002-7828-7174","orcid":"https://orcid.org/0000-0002-7828-7174","contributorId":362369,"corporation":false,"usgs":false,"family":"Balter-Kennedy","given":"Allie","affiliations":[{"id":17701,"text":"Lamont-Doherty Earth Observatory","active":true,"usgs":false}],"preferred":false,"id":950383,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Prince, Karlee 0000-0003-4843-9322","orcid":"https://orcid.org/0000-0003-4843-9322","contributorId":362371,"corporation":false,"usgs":false,"family":"Prince","given":"Karlee","affiliations":[{"id":37334,"text":"University at Buffalo","active":true,"usgs":false}],"preferred":false,"id":950384,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Walcott-George, Caleb K. 0000-0003-4754-9466","orcid":"https://orcid.org/0000-0003-4754-9466","contributorId":362373,"corporation":false,"usgs":false,"family":"Walcott-George","given":"Caleb","middleInitial":"K.","affiliations":[{"id":37334,"text":"University at Buffalo","active":true,"usgs":false}],"preferred":false,"id":950385,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Graham, Brandon L. 0000-0002-7197-0413","orcid":"https://orcid.org/0000-0002-7197-0413","contributorId":340458,"corporation":false,"usgs":true,"family":"Graham","given":"Brandon","middleInitial":"L.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":950386,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Charton, Joanna","contributorId":362375,"corporation":false,"usgs":false,"family":"Charton","given":"Joanna","affiliations":[{"id":17701,"text":"Lamont-Doherty Earth Observatory","active":true,"usgs":false}],"preferred":false,"id":950387,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Briner, Jason P.","contributorId":362377,"corporation":false,"usgs":false,"family":"Briner","given":"Jason","middleInitial":"P.","affiliations":[{"id":37334,"text":"University at Buffalo","active":true,"usgs":false}],"preferred":false,"id":950388,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Shaefer, Joerg M.","contributorId":362379,"corporation":false,"usgs":false,"family":"Shaefer","given":"Joerg","middleInitial":"M.","affiliations":[{"id":17701,"text":"Lamont-Doherty Earth Observatory","active":true,"usgs":false}],"preferred":false,"id":950389,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70272215,"text":"70272215 - 2025 - Cryptic life history diversity supports endangered species recovery in an ultra-urbanized landscape","interactions":[],"lastModifiedDate":"2025-11-19T15:31:57.22913","indexId":"70272215","displayToPublicDate":"2025-11-18T08:28:18","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"Cryptic life history diversity supports endangered species recovery in an ultra-urbanized landscape","docAbstract":"Urban landscapes are often overlooked in conservation planning, allowing human activities to take precedence in ecosystem management. However, even heavily modified environments can support diverse species profiles, but continued expansion of the human footprint could transform these biodiversity hotspots into ecological traps that serve as hidden catalysts for demographic declines. In the backdrop of one of the world’s most urbanized landscapes-New York City, USA—is a federally endangered population of shortnose sturgeon (Acipenser brevirostrum) that has been quietly recovering for several decades despite many demographic threats. Here, we identify a unique behavioral phenotype of shortnose sturgeon that occupies habitats in New York Harbor in late spring and fall, likely using the area to optimize bioenergetic processes. As this study highlights, urbanized environments can be a nexus for cryptic phenotypic diversity which, if overlooked, can disrupt eco-evolutionary processes and contribute to population and species loss.
","language":"English","publisher":"Springer Nature","doi":"10.1038/s41598-025-24360-6","usgsCitation":"White, S.L., Higgs, A., and Fox, D., 2025, Cryptic life history diversity supports endangered species recovery in an ultra-urbanized landscape: Scientific Reports, v. 15, 40634, 8 p., https://doi.org/10.1038/s41598-025-24360-6.","productDescription":"40634, 8 p.","ipdsId":"IP-178198","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":496744,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-025-24360-6","text":"Publisher Index Page"},{"id":496636,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","city":"New York City","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -74.09993061657431,\n 40.736082719013496\n ],\n [\n -74.09993061657431,\n 40.588831128093005\n ],\n [\n -73.96403648299037,\n 40.588831128093005\n ],\n [\n -73.96403648299037,\n 40.736082719013496\n ],\n [\n -74.09993061657431,\n 40.736082719013496\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"15","noUsgsAuthors":false,"publicationDate":"2025-11-18","publicationStatus":"PW","contributors":{"authors":[{"text":"White, Shannon L. 0000-0003-4687-6596","orcid":"https://orcid.org/0000-0003-4687-6596","contributorId":263424,"corporation":false,"usgs":true,"family":"White","given":"Shannon","email":"","middleInitial":"L.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":950464,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Higgs, Amanda","contributorId":225402,"corporation":false,"usgs":false,"family":"Higgs","given":"Amanda","affiliations":[{"id":13678,"text":"New York State Department of Environmental Conservation","active":true,"usgs":false}],"preferred":false,"id":950465,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fox, Dewayne","contributorId":340954,"corporation":false,"usgs":false,"family":"Fox","given":"Dewayne","affiliations":[{"id":37219,"text":"Delaware State University","active":true,"usgs":false}],"preferred":false,"id":950466,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70275004,"text":"70275004 - 2025 - Systematics of three Amazonian antwren groups (Aves: Passeriformes: Thamnophilidae: Myrmotherula and Isleria)","interactions":[],"lastModifiedDate":"2026-04-10T15:25:25.342956","indexId":"70275004","displayToPublicDate":"2025-11-18T08:15:44","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3814,"text":"Zootaxa","onlineIssn":"1175-5334","printIssn":"1175-5326","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Systematics of three Amazonian antwren groups (Aves: Passeriformes: Thamnophilidae: Myrmotherula and Isleria)","title":"Systematics of three Amazonian antwren groups (Aves: Passeriformes: Thamnophilidae: Myrmotherula and Isleria)","docAbstract":"Working within the framework of a companion phylogenetic analysis, we reexamined species limits within three lineages of antwrens (two species and one species complex) widely distributed across the Amazon Basin. Diagnostic differences in vocal and plumage characters provided the basis for the following taxonomic revisions. Myrmotherula longipennis is found to comprise three species: (1) M. longipennis (sensu stricto), which is confined to the region north of the Amazon; (2) M. garbei, which is elevated from subspecies status and includes the subspecies zimmeri; and (3) M. paraensis, which is also elevated from subspecies status and includes subspecies transitiva and ochrogyna. Myrmotherula menetriesii also comprises three species: (1) M. menetriesii (sensu stricto), which occurs in the southwest quadrant of Amazonia and includes the subspecies berlepschi; (2) M. cinereiventris, which is elevated from subspecies status and includes the subspecies pallida; and (3) M. omissa, which is monotypic and is also elevated from subspecies status. We maintain two species in the Isleria complex, I. guttata and I. hauxwelli. Isleria guttata remains monotypic, but the subspecies of I. hauxwelli are revised. Isleria h. hellmayri is preserved as currently defined, but I. h. suffusa is synonymized with the nominate form, the geographic range of which is restricted to western Amazonia. A fourth subspecies, I. h. clarior, is resurrected; this subspecies occupies the major part of the range previously assigned to I. h. hauxwelli.
","language":"English","publisher":"Magnolia","doi":"10.11646/zootaxa.5722.1.2","usgsCitation":"Isler, M.L., Chesser, R., Stryjewski, K.F., and Whitney, B.M., 2025, Systematics of three Amazonian antwren groups (Aves: Passeriformes: Thamnophilidae: Myrmotherula and Isleria): Zootaxa, v. 5722, no. 1, p. 45-78, https://doi.org/10.11646/zootaxa.5722.1.2.","productDescription":"34 p.","startPage":"45","endPage":"78","ipdsId":"IP-153882","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":502991,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"text":"External Repository"},{"id":502695,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Amazon Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -73.00954838629755,\n 2.3519259569629014\n ],\n [\n -78.06774683472436,\n -2.255572439661208\n ],\n [\n -79.56707854677558,\n -4.880278929701795\n ],\n [\n -74.76003992828132,\n -8.775821288672432\n ],\n [\n -63.303829327664644,\n -16.80700744301342\n ],\n [\n -50.4273365032854,\n -10.681599115018031\n ],\n [\n -48.65068329492766,\n 1.0163951683207557\n ],\n [\n -57.09083498655092,\n 5.704635857356543\n ],\n [\n -73.00954838629755,\n 2.3519259569629014\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"5722","issue":"1","noUsgsAuthors":false,"publicationDate":"2025-11-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Isler, Morton L","contributorId":369792,"corporation":false,"usgs":false,"family":"Isler","given":"Morton","middleInitial":"L","affiliations":[{"id":36606,"text":"Smithsonian Institution","active":true,"usgs":false}],"preferred":false,"id":959181,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chesser, R. Terry 0000-0003-4389-7092","orcid":"https://orcid.org/0000-0003-4389-7092","contributorId":87669,"corporation":false,"usgs":true,"family":"Chesser","given":"R. Terry","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":959182,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stryjewski, Katherine F.","contributorId":369794,"corporation":false,"usgs":false,"family":"Stryjewski","given":"Katherine","middleInitial":"F.","affiliations":[],"preferred":false,"id":959183,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Whitney, Bret M","contributorId":369795,"corporation":false,"usgs":false,"family":"Whitney","given":"Bret","middleInitial":"M","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":959184,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70274548,"text":"70274548 - 2025 - Population genetics of the endangered narrowly endemic Island Marble butterfly (Euchloe ausonides insulanus)","interactions":[],"lastModifiedDate":"2026-04-02T13:57:15.166442","indexId":"70274548","displayToPublicDate":"2025-11-18T00:00:00","publicationYear":"2025","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":"Population genetics of the endangered narrowly endemic Island Marble butterfly (Euchloe ausonides insulanus)","title":"Population genetics of the endangered narrowly endemic Island Marble butterfly (Euchloe ausonides insulanus)","docAbstract":"The Island Marble butterfly (Euchloe ausonides insulanus) is an endangered species endemic to the San Juan Islands off the coast of Washington State, United States, and British Columbia, Canada. The species was thought to be extinct for ~ 90 years before it was rediscovered at American Camp, San Juan Island National Historical Park in 1998. Here, we report the results of the first population genetic analyses for insulanus, using DNA collected non-invasively from individuals in the last known stronghold for the species. We used DNA extracted from meconium, larval exuviae, and natural mortalities to generate and test thirteen new microsatellite markers to estimate genetic diversity, population structure, and kinship. We assembled and annotated mitochondrial genomes, which were used alongside museum specimens of insulanus collected ~ 100 years ago from Vancouver Island, and other members of the E. ausonides species complex, to infer the evolutionary history of the species. The results indicated that insulanus experiences low heterozygosity, a small effective population size (Ne), and low allelic diversity. High levels of inbreeding were found in some individuals, but inbreeding was uneven across the population. No population structure or partitioning of genetic variation by host plant was detected. The mitogenomes of extant insulanus were all identical and modern samples showed a loss of allelic diversity compared to insulanus from museums. Extant insulanus formed a clade with museum specimens and we identified multiple putatively diagnostic alleles to differentiate insulanus from other subspecies. Based on these results, we outline considerations for species management and genetic monitoring.
","language":"English","publisher":"Springer Nature","doi":"10.1007/s10592-025-01737-8","usgsCitation":"Jones, K., Aunins, A.W., Young, C., Johnson, R.L., and Morrison, C.L., 2025, Population genetics of the endangered narrowly endemic Island Marble butterfly (Euchloe ausonides insulanus): Conservation Genetics, v. 27, 5, https://doi.org/10.1007/s10592-025-01737-8.","productDescription":"5","ipdsId":"IP-177244","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":501970,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"British Columbia, Washington","otherGeospatial":"San Juan Islands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -123.1794965908473,\n 48.762742021779246\n ],\n [\n -123.1794965908473,\n 48.384126042901784\n ],\n [\n -122.67085884048696,\n 48.384126042901784\n ],\n [\n -122.67085884048696,\n 48.762742021779246\n ],\n [\n -123.1794965908473,\n 48.762742021779246\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"27","noUsgsAuthors":false,"publicationDate":"2025-11-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Jones, Kara Suzanne 0000-0002-8168-0815","orcid":"https://orcid.org/0000-0002-8168-0815","contributorId":331477,"corporation":false,"usgs":true,"family":"Jones","given":"Kara Suzanne","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":958246,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aunins, Aaron W. 0000-0001-5240-1453 aaunins@usgs.gov","orcid":"https://orcid.org/0000-0001-5240-1453","contributorId":5863,"corporation":false,"usgs":true,"family":"Aunins","given":"Aaron","email":"aaunins@usgs.gov","middleInitial":"W.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":958247,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Young, Colleen Callahan 0000-0002-9858-4897","orcid":"https://orcid.org/0000-0002-9858-4897","contributorId":344669,"corporation":false,"usgs":true,"family":"Young","given":"Colleen Callahan","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":958248,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Johnson, Robin L. 0000-0003-4314-3792 rjohnson1@usgs.gov","orcid":"https://orcid.org/0000-0003-4314-3792","contributorId":224717,"corporation":false,"usgs":true,"family":"Johnson","given":"Robin","email":"rjohnson1@usgs.gov","middleInitial":"L.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":958249,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Morrison, Cheryl L. 0000-0001-9425-691X","orcid":"https://orcid.org/0000-0001-9425-691X","contributorId":239844,"corporation":false,"usgs":true,"family":"Morrison","given":"Cheryl","middleInitial":"L.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":958250,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70272147,"text":"fs20253042 - 2025 - Preserving and increasing water resources—Natural infrastructure in dryland streams in Baja California Sur, Mexico","interactions":[],"lastModifiedDate":"2026-02-03T16:30:25.529535","indexId":"fs20253042","displayToPublicDate":"2025-11-17T12:20:32","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-3042","displayTitle":"Preserving and Increasing Water Resources—Natural Infrastructure in Dryland Streams in Baja California Sur, Mexico","title":"Preserving and increasing water resources—Natural infrastructure in dryland streams in Baja California Sur, Mexico","docAbstract":"The Los Planes watershed of Baja California Sur, Mexico, and its underlying aquifer are experiencing groundwater decline owing to low average annual rainfall (28.1 centimeters per year) and rising water demand from population growth and agricultural activities. This decline in water availability can lead to desertification—a process that changes arable land to desert by degrading soil and vegetation—and can pose serious challenges to livelihoods that depend on the land.
To address these issues, a ranch in the Los Planes watershed has installed many natural infrastructures in dryland streams (NIDS) in channels for soil and water conservation. In 2022, the U.S. Geological Survey (USGS) began working with regional researchers and land managers to investigate the effects of NIDS on natural biological, geochemical, and physical processes and determine the efficacy of NIDS for water augmentation in the Los Planes watershed. The USGS also worked with local academic institutions and nonprofit organizations to create public educational opportunities focused on the area’s hydrogeology. These and other collaborative efforts with the U.S. Water Partnership and Innovaciones Alumbra aim at enhancing water resources in the Baja California Sur region and promoting water security and safeguarding community well-being.
La cuenca de Los Planes, ubicada en Baja California Sur, México, y su acuífero subyacente, están sufriendo una disminución de las aguas subterráneas debido a la baja precipitación media anual (28.1 centímetros por año) y la alta demanda de agua por parte de una población creciente y la actividad agrícola. Esta disminución de la disponibilidad de agua puede conducir a la desertificación—un proceso que por medio de la degradación del suelo y la vegetación convierte a la tierra cultivable en desierto—representando un serio desafío para los medios de vida de las personas.
Para abordar estos problemas, un rancho en la cuenca de Los Planes ha instalado numerosas obras de Infraestructura Natural en Arroyos de Tierras Áridas (INATS) para conservación del suelo y del agua. En 2022, el Servicio Geológico de los Estados Unidos (USGS, por sus siglas en inglés) comenzó a trabajar con investigadores regionales y gestores de tierras para estudiar los efectos de INATS en los procesos biológicos, geoquímicos y físicos, y determinar su eficacia en el aumento de los recursos hídricos en la cuenca de Los Planes. El USGS se ha asociado con instituciones académicas y organizaciones locales sin fines de lucro para crear oportunidades educativas públicas centradas en la hidrogeología de la zona. Estos y otros esfuerzos colaborativos con la Asociación del Agua de Estados Unidos (U.S. Water Partnership) e Innovaciones Alumbra, tienen como objetivo mejorar el uso de los recursos hídricos en la región de Baja California Sur, promover la seguridad hídrica y proteger el bienestar de la comunidad.
","language":"English, Spanish","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20253042","usgsCitation":"Anides Morales, A., Norman, L.M., and Mack, T.J., 2025, Preserving and increasing water resources—Natural infrastructure in dryland streams in Baja California Sur, Mexico: U.S. Geological Survey Fact Sheet 2025–3042, 4 p., https://doi.org/10.3133/fs20253042.","productDescription":"4 p.","numberOfPages":"4","onlineOnly":"N","ipdsId":"IP-167963","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":496556,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2025/3042/fs20253042.pdf","text":"Report (English)","size":"1.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2025-3042 PDF (English)"},{"id":496555,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2025/3042/coverthb.jpg"},{"id":496557,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2025/3042/fs20253042_spanish.pdf","text":"Report (Español)","size":"1.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2025-3042 PDF (Spanish)"}],"country":"Mexico","state":"Baja California Sur","otherGeospatial":"Los Planes watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -110.61060380724068,\n 24.369517436874077\n ],\n [\n -110.61060380724068,\n 22.79088429619047\n ],\n [\n -109.36626743882256,\n 22.79088429619047\n ],\n [\n -109.36626743882256,\n 24.369517436874077\n ],\n [\n -110.61060380724068,\n 24.369517436874077\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Western Geographic Science Center
U.S. Geological Survey
350 N. Akron Rd.
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Rangelands are extensive ecosystems, providing important ecosystem services while undergoing continuous change. As a result, improved monitoring technologies can help better characterize vegetation change. Satellite remote sensing has proven effective in this regard, tracking vegetation dynamics at broad and fine scales. We leveraged the spatial, spectral, and temporal resolution of Sentinel-2 satellites to estimate fractional cover and canopy gap across rangelands of the western United States. We produced annual, 10 m spatial resolution estimates of fractional cover and canopy gap size class for years 2018 to 2024. Fractional cover estimates include that of common plant functional types (annual forb and grass, bareground, littler, perennial forb and grass, shrub, tree) and select genera (including invasive annual grass species, pinyon-juniper species, and sagebrush species); canopy gap size classes include gap sizes 25 to 50, 51 to 100, 101 to 200, and greater than 200 cm. We make these data available as Cloud Optimized GeoTIFFs, organized as 75×75 km tiles covering the 17 western states of the United States.
","language":"English","publisher":"BioRxiv","doi":"10.1101/2025.03.13.643073","usgsCitation":"Allred, B.W., McCord, S.E., Assal, T.J., Bestelmeyer, B.T., Boyd, C.S., Brooks, A.C., Cady, S.M., Duniway, M.C., Fuhlendorf, S.D., Green, S.A., Harrison, G.R., Jensen, E.R., Kachergis, E.J., Knight, A.C., Mattilio, C.M., Mealor, B.A., Naugle, D.E., O’Leary, D., Olsoy, P.J., Peirce, E.S., Reinhardt, J.R., Shriver, R.K., Smith, J.T., Tack, J.D., Tanner, A.M., Tanner, E.P., Twidwell, D., Webb, N.P., and Morford, S.L., 2025, Sentinel-2 based estimates of rangeland fractional cover and canopy gap class for the western United States: BioRxiv, https://doi.org/10.1101/2025.03.13.643073.","productDescription":"29 p.","ipdsId":"IP-183344","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":496923,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1101/2025.03.13.643073","text":"External Repository"},{"id":496781,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Allred, Brady W.","contributorId":362901,"corporation":false,"usgs":false,"family":"Allred","given":"Brady","middleInitial":"W.","affiliations":[{"id":86556,"text":"Numerical Terradynamic Simulation Group, University of Montana, Missoula, MT, USA","active":true,"usgs":false}],"preferred":false,"id":950786,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCord, Sarah E.","contributorId":362902,"corporation":false,"usgs":false,"family":"McCord","given":"Sarah","middleInitial":"E.","affiliations":[{"id":86557,"text":"Jornada Experimental Range, USDA Agricultural Research Service, Las Cruces, NM, USA","active":true,"usgs":false}],"preferred":false,"id":950787,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Assal, Timothy J.","contributorId":362903,"corporation":false,"usgs":false,"family":"Assal","given":"Timothy","middleInitial":"J.","affiliations":[{"id":86559,"text":"Bureau of Land Management, National Operations Center, Denver, CO, USA","active":true,"usgs":false}],"preferred":false,"id":950788,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bestelmeyer, Brandon T.","contributorId":362904,"corporation":false,"usgs":false,"family":"Bestelmeyer","given":"Brandon","middleInitial":"T.","affiliations":[{"id":86557,"text":"Jornada Experimental Range, USDA Agricultural Research Service, Las Cruces, NM, USA","active":true,"usgs":false}],"preferred":false,"id":950789,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Boyd, Chad S.","contributorId":362905,"corporation":false,"usgs":false,"family":"Boyd","given":"Chad","middleInitial":"S.","affiliations":[{"id":86561,"text":"Eastern Oregon Agricultural Research Center, USDA Agricultural Research Service, Burns, OR, USA","active":true,"usgs":false}],"preferred":false,"id":950790,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brooks, Alexander C.","contributorId":362906,"corporation":false,"usgs":false,"family":"Brooks","given":"Alexander","middleInitial":"C.","affiliations":[{"id":82671,"text":"Desert Research Institute, Reno, NV, USA","active":true,"usgs":false}],"preferred":false,"id":950791,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cady, Samantha M.","contributorId":362907,"corporation":false,"usgs":false,"family":"Cady","given":"Samantha","middleInitial":"M.","affiliations":[{"id":86562,"text":"Department of Agronomy and Horticulture, University of Nebraska–Lincoln, Lincoln, NE, USA","active":true,"usgs":false}],"preferred":false,"id":950792,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Duniway, Michael C. 0000-0002-9643-2785 mduniway@usgs.gov","orcid":"https://orcid.org/0000-0002-9643-2785","contributorId":219284,"corporation":false,"usgs":true,"family":"Duniway","given":"Michael","email":"mduniway@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":950793,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Fuhlendorf, Samuel D.","contributorId":362908,"corporation":false,"usgs":false,"family":"Fuhlendorf","given":"Samuel","middleInitial":"D.","affiliations":[{"id":86563,"text":"Natural Resource Ecology and Management, Oklahoma State University, Stillwater, OK, USA","active":true,"usgs":false}],"preferred":false,"id":950794,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Green, Shane A.","contributorId":362909,"corporation":false,"usgs":false,"family":"Green","given":"Shane","middleInitial":"A.","affiliations":[{"id":86564,"text":"USDA Natural Resources Conservation Service, Central National Technology Support Center, Ft. Worth, TX, USA","active":true,"usgs":false}],"preferred":false,"id":950795,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Harrison, Georgia R.","contributorId":362910,"corporation":false,"usgs":false,"family":"Harrison","given":"Georgia","middleInitial":"R.","affiliations":[{"id":86557,"text":"Jornada Experimental Range, USDA Agricultural Research Service, Las Cruces, NM, USA","active":true,"usgs":false}],"preferred":false,"id":950796,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Jensen, Eric R.","contributorId":362911,"corporation":false,"usgs":false,"family":"Jensen","given":"Eric","middleInitial":"R.","affiliations":[{"id":82671,"text":"Desert Research Institute, Reno, NV, USA","active":true,"usgs":false}],"preferred":false,"id":950797,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Kachergis, Emily J.","contributorId":362912,"corporation":false,"usgs":false,"family":"Kachergis","given":"Emily","middleInitial":"J.","affiliations":[{"id":86559,"text":"Bureau of Land Management, National Operations Center, Denver, CO, USA","active":true,"usgs":false}],"preferred":false,"id":950798,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Knight, Anna C. 0000-0002-9455-2855","orcid":"https://orcid.org/0000-0002-9455-2855","contributorId":255113,"corporation":false,"usgs":true,"family":"Knight","given":"Anna","email":"","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":950799,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Mattilio, Chloe M.","contributorId":362913,"corporation":false,"usgs":false,"family":"Mattilio","given":"Chloe","middleInitial":"M.","affiliations":[{"id":86565,"text":"University of Wyoming Sheridan Research and Extension Center, Institute for Managing Annual Grasses Invading Natural Ecosystems, Sheridan, WY, USA","active":true,"usgs":false}],"preferred":false,"id":950800,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Mealor, Brian A.","contributorId":362914,"corporation":false,"usgs":false,"family":"Mealor","given":"Brian","middleInitial":"A.","affiliations":[{"id":86565,"text":"University of Wyoming Sheridan Research and Extension Center, Institute for Managing Annual Grasses Invading Natural Ecosystems, Sheridan, WY, USA","active":true,"usgs":false}],"preferred":false,"id":950801,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Naugle, David E.","contributorId":362915,"corporation":false,"usgs":false,"family":"Naugle","given":"David","middleInitial":"E.","affiliations":[{"id":86566,"text":"W.A. Franke College of Forestry and Conservation, University of Montana, Missoula, MT, USA","active":true,"usgs":false}],"preferred":false,"id":950802,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"O’Leary, Dylan","contributorId":362916,"corporation":false,"usgs":false,"family":"O’Leary","given":"Dylan","affiliations":[{"id":86567,"text":"Institute for Natural Resources, Oregon State University, Corvallis, OR, USA","active":true,"usgs":false}],"preferred":false,"id":950803,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Olsoy, Peter J.","contributorId":362917,"corporation":false,"usgs":false,"family":"Olsoy","given":"Peter","middleInitial":"J.","affiliations":[{"id":86561,"text":"Eastern Oregon Agricultural Research Center, USDA Agricultural Research Service, Burns, OR, USA","active":true,"usgs":false}],"preferred":false,"id":950804,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Peirce, Erika S.","contributorId":362918,"corporation":false,"usgs":false,"family":"Peirce","given":"Erika","middleInitial":"S.","affiliations":[{"id":86568,"text":"Rangeland Resources and Systems Research Unit, USDA Agricultural Research Service, Fort Collins, CO, USA","active":true,"usgs":false}],"preferred":false,"id":950805,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Reinhardt, Jason R.","contributorId":362919,"corporation":false,"usgs":false,"family":"Reinhardt","given":"Jason","middleInitial":"R.","affiliations":[{"id":86569,"text":"USDA Forest Service, Rocky Mountain Research Station, Moscow, ID, USA","active":true,"usgs":false}],"preferred":false,"id":950806,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Shriver, Robert K.","contributorId":362920,"corporation":false,"usgs":false,"family":"Shriver","given":"Robert","middleInitial":"K.","affiliations":[{"id":52928,"text":"Department of Natural Resources and Environmental Science, University of Nevada, Reno, NV, USA","active":true,"usgs":false}],"preferred":false,"id":950807,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Smith, Joseph T.","contributorId":362921,"corporation":false,"usgs":false,"family":"Smith","given":"Joseph","middleInitial":"T.","affiliations":[{"id":86556,"text":"Numerical Terradynamic Simulation Group, University of Montana, Missoula, MT, USA","active":true,"usgs":false}],"preferred":false,"id":950808,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Tack, Jason D.","contributorId":362922,"corporation":false,"usgs":false,"family":"Tack","given":"Jason","middleInitial":"D.","affiliations":[{"id":86570,"text":"US Fish and Wildlife Service, Habitat and Population Evaluation Team, Missoula, MT, USA","active":true,"usgs":false}],"preferred":false,"id":950809,"contributorType":{"id":1,"text":"Authors"},"rank":24},{"text":"Tanner, Ashley M.","contributorId":362923,"corporation":false,"usgs":false,"family":"Tanner","given":"Ashley","middleInitial":"M.","affiliations":[{"id":86571,"text":"Caesar Kleberg Wildlife Research Institute, Texas A&M University-Kingsville, Kingsville, TX, USA","active":true,"usgs":false}],"preferred":false,"id":950810,"contributorType":{"id":1,"text":"Authors"},"rank":25},{"text":"Tanner, Evan P.","contributorId":362924,"corporation":false,"usgs":false,"family":"Tanner","given":"Evan","middleInitial":"P.","affiliations":[{"id":86571,"text":"Caesar Kleberg Wildlife Research Institute, Texas A&M University-Kingsville, Kingsville, TX, USA","active":true,"usgs":false}],"preferred":false,"id":950811,"contributorType":{"id":1,"text":"Authors"},"rank":26},{"text":"Twidwell, Dirac","contributorId":341491,"corporation":false,"usgs":false,"family":"Twidwell","given":"Dirac","affiliations":[{"id":16610,"text":"University of Nebraska-Lincoln","active":true,"usgs":false}],"preferred":false,"id":950812,"contributorType":{"id":1,"text":"Authors"},"rank":27},{"text":"Webb, Nicholas P.","contributorId":362925,"corporation":false,"usgs":false,"family":"Webb","given":"Nicholas","middleInitial":"P.","affiliations":[{"id":86557,"text":"Jornada Experimental Range, USDA Agricultural Research Service, Las Cruces, NM, USA","active":true,"usgs":false}],"preferred":false,"id":950813,"contributorType":{"id":1,"text":"Authors"},"rank":28},{"text":"Morford, Scott L.","contributorId":362926,"corporation":false,"usgs":false,"family":"Morford","given":"Scott","middleInitial":"L.","affiliations":[{"id":86556,"text":"Numerical Terradynamic Simulation Group, University of Montana, Missoula, MT, USA","active":true,"usgs":false}],"preferred":false,"id":950814,"contributorType":{"id":1,"text":"Authors"},"rank":29}]}} ,{"id":70272677,"text":"70272677 - 2025 - Carbon and nitrogen isotopes of different native fish tissues from the Santa Ana River, California","interactions":[],"lastModifiedDate":"2026-01-22T16:37:13.840737","indexId":"70272677","displayToPublicDate":"2025-11-17T09:31:28","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Carbon and nitrogen isotopes of different native fish tissues from the Santa Ana River, California","docAbstract":"Stable isotopes are commonly used to understand the role of fishes in aquatic food webs. However, variability in species- and tissue-specific isotopic values can affect the inference that is drawn from a stable isotope study. We evaluated differences in stable isotopes of carbon (δ13C) and nitrogen (δ15N) among three tissue types (white muscle, caudal fin rays, and eye lenses) for Santa Ana Sucker Pantosteus santaanae and Arroyo Chub Gila orcuttii to inform the design of a stable isotope study in the Santa Ana River, an urban river that is located in southern California.
We used multivariate analyses to test for differences in the stable isotopes of carbon (δ13C) and nitrogen (δ15N) among the three tissue types that were collected from Santa Ana Sucker and Arroyo Chub. We also summarized the variability in isotopic values that was recorded over time in fish eye lenses and interpreted this variability in reference to the spatial patterns in isotopic values that have been previously reported throughout the Santa Ana River.
We found that fin ray tissue and white muscle tissue were not significantly different for either isotope or fish species. Fish eye lenses were significantly higher in δ13C than muscle tissue, and eye lenses were significantly higher in δ15N than fin ray tissue for both fishes. We also found a greater range in δ13C and δ15N across eye lens layers for Santa Ana Sucker (δ13C = 2.01 ± 0.96‰, δ15N = 4.93 ± 4.18‰) than for Arroyo Chub (δ13C = 0.96 ± 0.65‰, δ15N = 4.63 ± 1.45‰).
Our results indicate that fin rays may be a viable nonlethal alternative to white muscle tissue for use in a stable isotope study of native fish of the Santa Ana River. Additionally, eye lenses could provide a chemical history of fishes within the river, but species-specific correction factors may be needed if stable isotope values for eye lenses are to be compared with more conventional tissue types (e.g., white muscle).
The use of Uncrewed Aerial Systems (UASs) for remote sensing applications has increased significantly in recent years due to their low cost, operational flexibility, and rapid advancements in sensor technologies. In many cases, UAS platforms are considered viable alternatives to conventional satellite and crewed airborne platforms, offering very high spatial, spectral, and temporal resolution data. However, the radiometric quality of UAS-acquired data has not received equivalent attention, particularly with respect to absolute calibration. In this study, we (1) evaluate the absolute radiometric performance of two commonly used UAS sensors: the Headwall Nano-Hyperspec hyperspectral sensor and the MicaSense RedEdge-MX Dual Camera multispectral system; (2) assess the effectiveness of the Empirical Line Method (ELM) in improving the radiometric accuracy of reflectance products generated by these sensors; and (3) investigate the influence of calibration target characteristics—including size, material type, reflectance intensity, and quantity—on the performance of ELM for UAS data. A field campaign was conducted jointly by the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center and the USGS National Uncrewed Systems Office (NUSO) from 15 to 18 July 2023, at the USGS EROS Ground Validation Radiometer (GVR) site in Sioux Falls, South Dakota, USA, over a 160 m × 160 m vegetated area. Absolute calibration accuracy was evaluated by comparing UAS sensor-derived reflectance to in situ measurements of the site. Results indicate that the Headwall Nano-Hyperspec and MicaSense sensors underestimated reflectance by approximately 0.05 and 0.015 reflectance units, respectively. While the MicaSense sensor demonstrated better inherent radiometric accuracy, it exhibited saturation over bright targets due to limitations in its automatic gain and exposure settings. Application of the ELM using just two calibration targets reduced discrepancies to within 0.005 reflectance units. Reflectance products generated using various target materials—such as felt, melamine, or commercially available validation targets—showed comparable agreement with in situ measurements when used with the Nano-Hyperspec sensor. Furthermore, increasing the number of calibration targets beyond two did not yield measurable improvements in calibration accuracy. At a flight altitude of 200 ft above ground level (AGL), a target size of 0.6 m × 0.6 m or larger was sufficient to provide pure pixels for ELM implementation, whereas smaller targets (e.g., 0.3 m × 0.3 m) posed challenges in isolating pure pixels. Overall, the standard manufacturer-recommended calibration procedures were insufficient for achieving high radiometric accuracy with the tested sensors, which may restrict their applicability in scenarios requiring greater accuracy and precision. The use of the ELM significantly improved data quality, enhancing the reliability and applicability of UAS-based remote sensing in contexts requiring high precision and accuracy.
","language":"English","publisher":"MDPI","doi":"10.3390/rs17223738","usgsCitation":"Shrestha, M., Scholl, V.M., Sampath, A., Irwin, J., Kropuenske, T., Adams, J., Burgess, M.A., and Brady, L.R., 2025, Absolute radiometric calibration evaluation of Uncrewed Aerial System (UAS) Headwall and MicaSense sensors and improving data quality using the Empirical Line Method: Remote Sensing, v. 17, no. 22, 3738, 29 p., https://doi.org/10.3390/rs17223738.","productDescription":"3738, 29 p.","ipdsId":"IP-178436","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":497081,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs17223738","text":"Publisher Index Page"},{"id":496979,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"17","issue":"22","noUsgsAuthors":false,"publicationDate":"2025-11-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Shrestha, Mahesh 0000-0002-8368-6399 mshrestha@contractor.usgs.gov","orcid":"https://orcid.org/0000-0002-8368-6399","contributorId":259303,"corporation":false,"usgs":false,"family":"Shrestha","given":"Mahesh","email":"mshrestha@contractor.usgs.gov","affiliations":[{"id":54490,"text":"KBR, Inc., under contract to USGS","active":true,"usgs":false}],"preferred":true,"id":951160,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Scholl, Victoria Mary 0000-0002-2085-1449","orcid":"https://orcid.org/0000-0002-2085-1449","contributorId":295713,"corporation":false,"usgs":true,"family":"Scholl","given":"Victoria","email":"","middleInitial":"Mary","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":951161,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sampath, Aparajithan 0000-0002-6922-4913","orcid":"https://orcid.org/0000-0002-6922-4913","contributorId":222486,"corporation":false,"usgs":false,"family":"Sampath","given":"Aparajithan","affiliations":[{"id":54490,"text":"KBR, Inc., under contract to USGS","active":true,"usgs":false}],"preferred":false,"id":951162,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Irwin, Jeffrey 0000-0001-5828-0787 jrirwin@usgs.gov","orcid":"https://orcid.org/0000-0001-5828-0787","contributorId":222485,"corporation":false,"usgs":true,"family":"Irwin","given":"Jeffrey","email":"jrirwin@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":951163,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kropuenske, Travis 0000-0002-3269-4225","orcid":"https://orcid.org/0000-0002-3269-4225","contributorId":331816,"corporation":false,"usgs":false,"family":"Kropuenske","given":"Travis","email":"","affiliations":[{"id":53079,"text":"KBR, contractor to U.S. Geological Survey","active":true,"usgs":false}],"preferred":false,"id":951164,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Adams, Josip 0000-0001-8470-4141","orcid":"https://orcid.org/0000-0001-8470-4141","contributorId":217936,"corporation":false,"usgs":true,"family":"Adams","given":"Josip","email":"","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":5078,"text":"Southwest Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":951165,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Burgess, Matthew Alexander 0000-0003-3487-4972 mburgess@usgs.gov","orcid":"https://orcid.org/0000-0003-3487-4972","contributorId":225090,"corporation":false,"usgs":true,"family":"Burgess","given":"Matthew","email":"mburgess@usgs.gov","middleInitial":"Alexander","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":951166,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Brady, Lance R","contributorId":363145,"corporation":false,"usgs":false,"family":"Brady","given":"Lance","middleInitial":"R","affiliations":[{"id":86626,"text":"BLM (former USGS employee)","active":true,"usgs":false}],"preferred":false,"id":951167,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70272104,"text":"ofr20251046 - 2025 - Modeling floods, sediment entrainment, and downstream debris flows from hypothetical breaches of the blockage at Spirit Lake, Washington","interactions":[],"lastModifiedDate":"2026-02-03T16:29:30.731045","indexId":"ofr20251046","displayToPublicDate":"2025-11-17T07:48:44","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-1046","displayTitle":"Modeling Floods, Sediment Entrainment, and Downstream Debris Flows from Hypothetical Breaches of the Blockage at Spirit Lake, Washington","title":"Modeling floods, sediment entrainment, and downstream debris flows from hypothetical breaches of the blockage at Spirit Lake, Washington","docAbstract":"This report describes a modeling investigation by the U.S. Geological Survey (USGS) of hazards in the Toutle and Cowlitz River valleys posed by hypothetical outburst floods from Spirit Lake, Washington. A massive debris avalanche resulting from the collapse of Mount St. Helens’ north flank during the May 18, 1980, eruption blocked Spirit Lake’s natural outlet into the North Fork Toutle River. Lacking a natural outlet, subsequent runoff in the Spirit Lake watershed contributed to a rising lake level, elevating the potential for debris-dam breaching or catastrophic failure. The influence of highly erodible bed sediment in the upper North Fork Toutle River on downstream flood and debris-flow dynamics and extent is assessed in this study. Simulations of clear-water (non-erosive) outburst floods were used as a baseline and compared to erosive flows that entrain large volumes of material and transition into debris flows along their flow path, revealing the influence of entrainment on hazard extent. Clear-water floods were modeled with the shallow water equations. Erosive flows were modeled with a two-phase granular fluid model that accommodates mobilization and incorporation of sediment from the bed into the overlying flow and resultant changes in flow rheology across a wide range of solid concentrations, from dilute suspensions to dense-granular debris flows. Entrainment of bed material was found to substantially increase the total flow volume (total volume of transported water and sediment is approximately 150 percent of the water volume for non-erosive flows). Erosive flows are shown to exhibit higher flow-front speeds and faster downstream arrival times than non-erosive flows, consistent with volume amplification effects near the actively mobilizing flow front. However, the larger total volume of transported material does not necessarily lead to an enhancement of total volume throughput (cumulative discharge) or inundation extent (total affected area) for all locations along the entire flow path; while entrainment leads to the displacement of a larger volume of material overall, much of this dislocated material (water and sediment) deposits upstream from the distal extent of the flows. These results are consistent with energetic considerations of initial potential energy and granular shear resistance.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20251046","usgsCitation":"George, D.L., and Cannon, C.M., 2025, Modeling floods, sediment entrainment, and downstream debris flows from hypothetical breaches of the blockage at Spirit Lake, Washington: U.S. Geological Survey Open-File Report 2025–1046, 37 p., https://doi.org/10.3133/ofr20251046.","productDescription":"Report: ix, 37 p.; Data Release","numberOfPages":"37","onlineOnly":"Y","ipdsId":"IP-154709","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":496509,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P139AC3R","text":"USGS data release","description":"George, D.L., and Cannon, C.M., 2025, Simulated floods, sediment entrainment, and debris-flow inundation in the Toutle and Cowlitz River valleys resulting from hypothetical dam breaches of Spirit Lake, Washington: U.S. Geological Survey data release, https://doi.org/10.5066/P139AC3R.","linkHelpText":"Simulated floods, sediment entrainment, and debris-flow inundation in the Toutle and Cowlitz River valleys resulting from hypothetical dam breaches of Spirit Lake, Washington"},{"id":496505,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2025/1046/ofr20251046.pdf","text":"Report","size":"26.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2025-1046 PDF"},{"id":496504,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2025/1046/coverthb.jpg"},{"id":497791,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118953.htm"},{"id":496508,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2025/1046/images"},{"id":496507,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2025/1046/ofr20251046.XML","linkFileType":{"id":8,"text":"xml"},"description":"OFR 2025-1046 XML"},{"id":496506,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20251046/full","linkFileType":{"id":5,"text":"html"},"description":"OFR 2025-1046 HTML"}],"country":"United States","state":"Washington","otherGeospatial":"Spirit Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.133333,\n 46.2833\n ],\n [\n -122.2,\n 46.2833\n ],\n [\n -122.2,\n 46.25\n ],\n [\n -122.133333,\n 46.25\n ],\n [\n -122.133333,\n 46.2833\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"David A. Johnston Cascades Volcano Observatory
U.S. Geological Survey
1300 SE Cardinal Court
Building 10, Suite 100
Vancouver, WA 98683
Email: askCVO@usgs.gov
","tableOfContents":"This study presents a quantitative PCR (qPCR) assay for the detection of the endangered diamond darter Crystallaria cincotta from environmental DNA (eDNA) in water samples. The assay design is based on an alignment of mitochondrial cytochrome b DNA sequences from 58 individuals representing 25 percid species. Leveraging genetic differences, a species-specific qPCR assay was designed, incorporating alocked nucleic acid (LNA)-enriched probe and a secondary blocking probe to enhance specificity. The assay targets a 93-base pair fragment that includes a diagnostic single nucleotide polymorphism in the probe region; combined with multiple primer mismatches, this provides specificity for distinguishing C. cincotta from other sympatric percid species. Specificity was validated by testing genomic DNA from 16 percid species and synthetic templates, confirming no cross-reactivity. Performance metrics, including the standard curve, qPCR efficiency, limit of detection, and limit of quantification, are reported. The qPCR assay exhibited sufficient sensitivity to detect C. cincotta eDNA in environmental water samples collected from occupied riverine habitats. This study illustrates the effectiveness of LNA-enriched and blocking probes in developing species-specific qPCR assays for eDNA applications, demonstrating their utility in accurately distinguishing closely related species within diverse fish communities.
","language":"English","publisher":"Springer Nature","doi":"10.1007/s12686-025-01407-4","usgsCitation":"Kinziger, A.P., Layne, C., and Welsh, S.A., 2025, Quantitative PCR detection of endangered diamond darter Crystallaria Cincotta in environmental DNA: Employing locked nucleic acids and blocking probe for specificity: Conservation Genetics Resources, v. 18, 2, 6 p., https://doi.org/10.1007/s12686-025-01407-4.","productDescription":"2, 6 p.","ipdsId":"IP-176804","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":497498,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"18","noUsgsAuthors":false,"publicationDate":"2025-11-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Kinziger, Andrew P.","contributorId":364132,"corporation":false,"usgs":false,"family":"Kinziger","given":"Andrew","middleInitial":"P.","affiliations":[{"id":86765,"text":"Aquatrace Genomics","active":true,"usgs":false}],"preferred":false,"id":952250,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Layne, Cameron M.","contributorId":349281,"corporation":false,"usgs":false,"family":"Layne","given":"Cameron M.","affiliations":[{"id":40299,"text":"West Virginia Division of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":952251,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Welsh, Stuart A. 0000-0003-0362-054X","orcid":"https://orcid.org/0000-0003-0362-054X","contributorId":217037,"corporation":false,"usgs":true,"family":"Welsh","given":"Stuart","email":"","middleInitial":"A.","affiliations":[{"id":642,"text":"West Virginia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":952252,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70272761,"text":"70272761 - 2025 - The Bird Banding Lab Is back online. Thank you for your patience","interactions":[],"lastModifiedDate":"2025-12-08T16:41:23.606136","indexId":"70272761","displayToPublicDate":"2025-11-15T10:39:03","publicationYear":"2025","noYear":false,"publicationType":{"id":25,"text":"Newsletter"},"publicationSubtype":{"id":30,"text":"Newsletter"},"seriesTitle":{"id":23092,"text":"Note to All Banders","active":true,"publicationSubtype":{"id":30}},"title":"The Bird Banding Lab Is back online. Thank you for your patience","docAbstract":"Note to All Banders was a special extra communication with more urgent information relevant to banders. This Note to All Banders was sent to U. S. bird banders on November 14, 2025, following the return of Bird Banding Lab staff after the 43-day furlough. This note includes information regarding staff resuming work and appreciate banders patience as staff works on the backlog resulting from lapsed operations.","language":"English","publisher":"U.S. Geological Survey","usgsCitation":"Celis-Murillo, A., 2025, The Bird Banding Lab Is back online. Thank you for your patience: Note to All Banders, 2 p,.","productDescription":"2 p,","ipdsId":"IP-183753","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":497203,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":497172,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.usgs.gov/media/files/note-banders-november-2025"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Celis-Murillo, Antonio 0000-0002-3371-6529","orcid":"https://orcid.org/0000-0002-3371-6529","contributorId":237851,"corporation":false,"usgs":true,"family":"Celis-Murillo","given":"Antonio","email":"","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":951626,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70272739,"text":"70272739 - 2025 - Understanding abundances and behaviors of shorebirds in coastal Louisiana","interactions":[],"lastModifiedDate":"2025-12-08T15:17:40.768553","indexId":"70272739","displayToPublicDate":"2025-11-15T09:08:38","publicationYear":"2025","noYear":false,"publicationType":{"id":27,"text":"Preprint"},"publicationSubtype":{"id":32,"text":"Preprint"},"seriesTitle":{"id":19846,"text":"BioRxiv","active":true,"publicationSubtype":{"id":32}},"title":"Understanding abundances and behaviors of shorebirds in coastal Louisiana","docAbstract":"Barrier islands provide resources and ecological services that are integral to economic and environmental interests, such as protection of coastal infrastructure and provision of wildlife habitat. Over time, barrier islands may become eroded and experience land loss, which can require management actions to restore island integrity. Barrier island restoration can create or modify habitats, which can impact the organisms depending on them. Our objective was to understand how the abundance and behaviors of a suite of shorebird species responded to restoration and habitat factors at two restored sites in coastal Louisiana (USA). For five focal species, we used abundance from the breeding and non-breeding seasons as well as breeding, foraging, and maintenance behaviors as response variables in boosted regression tree models to determine the importance of various geospatial and remotely sensed predictor variables related to restoration. Across sites and species, remotely sensed variables, particularly a brightness index, tended to be more important than restoration phases as predictors of bird abundance and behavior. Our results suggest that sediment composition, moisture, and vegetative cover are related to shorebird coastal habitat selection, although the direction and strength of relationships differ among these variables and our focal species. Tying these remote sensing metrics to restoration design and management actions can help land managers better understand factors that attract and benefit birds. Additional research can advance understanding in how remote sensing can be used to monitor the availability of functional habitats for shorebirds.
","language":"English","publisher":"BioRxiv","doi":"10.1101/2025.11.15.688530","usgsCitation":"Zenzal, T.J., Anderson, A.N., Enwright, N., Thurman, H.R., Cheney, W.C., LeBlanc, D., Dobbs, R.C., Geary, B., and Waddle, H., 2025, Understanding abundances and behaviors of shorebirds in coastal Louisiana: BioRxiv, https://doi.org/10.1101/2025.11.15.688530.","productDescription":"57 p.","ipdsId":"IP-160584","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":497396,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1101/2025.11.15.688530","text":"External Repository"},{"id":497186,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Zenzal, Theodore J. Jr. 0000-0001-7342-1373","orcid":"https://orcid.org/0000-0001-7342-1373","contributorId":224399,"corporation":false,"usgs":true,"family":"Zenzal","given":"Theodore","suffix":"Jr.","email":"","middleInitial":"J.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":951478,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, Amanda Nicole 0000-0003-3930-3896","orcid":"https://orcid.org/0000-0003-3930-3896","contributorId":224400,"corporation":false,"usgs":true,"family":"Anderson","given":"Amanda","email":"","middleInitial":"Nicole","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":951479,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Enwright, Nicholas 0000-0002-7887-3261","orcid":"https://orcid.org/0000-0002-7887-3261","contributorId":217771,"corporation":false,"usgs":true,"family":"Enwright","given":"Nicholas","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":951480,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thurman, Hana R.","contributorId":363355,"corporation":false,"usgs":false,"family":"Thurman","given":"Hana","middleInitial":"R.","affiliations":[{"id":64427,"text":"Cherokee Nation System Solutions","active":true,"usgs":false}],"preferred":false,"id":951481,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cheney, Wyatt C.","contributorId":363356,"corporation":false,"usgs":false,"family":"Cheney","given":"Wyatt","middleInitial":"C.","affiliations":[{"id":86667,"text":"Cheney Consulting","active":true,"usgs":false}],"preferred":false,"id":951482,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"LeBlanc, Delaina","contributorId":330122,"corporation":false,"usgs":false,"family":"LeBlanc","given":"Delaina","email":"","affiliations":[{"id":78819,"text":"Barataria-Terrebonne National Estuary","active":true,"usgs":false}],"preferred":false,"id":951483,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dobbs, Robert C.","contributorId":363357,"corporation":false,"usgs":false,"family":"Dobbs","given":"Robert","middleInitial":"C.","affiliations":[{"id":12717,"text":"Louisiana Department of Wildlife and Fisheries","active":true,"usgs":false}],"preferred":false,"id":951484,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Geary, Brock","contributorId":352310,"corporation":false,"usgs":false,"family":"Geary","given":"Brock","affiliations":[{"id":16979,"text":"University of Pennsylvania","active":true,"usgs":false}],"preferred":false,"id":951485,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Waddle, Hardin 0000-0003-1940-2133","orcid":"https://orcid.org/0000-0003-1940-2133","contributorId":222187,"corporation":false,"usgs":true,"family":"Waddle","given":"Hardin","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":951486,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70272577,"text":"70272577 - 2025 - Performance analysis of oil recovery and CO2 retention in a greenfield residual oil zone: CO2-EOR in Tall Cotton Field (Permian Basin, West Texas, USA)","interactions":[],"lastModifiedDate":"2025-11-24T16:11:13.736607","indexId":"70272577","displayToPublicDate":"2025-11-15T09:01:56","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":22979,"text":"Carbon Capture Science and Technology","active":true,"publicationSubtype":{"id":10}},"title":"Performance analysis of oil recovery and CO2 retention in a greenfield residual oil zone: CO2-EOR in Tall Cotton Field (Permian Basin, West Texas, USA)","docAbstract":"Residual oil zones (ROZs) can offer significant oil resources via enhanced oil recovery (EOR) as well as subsurface carbon dioxide (CO2) retention during injection. If injected CO2 is anthropogenic, the ROZs can offer a substantial geologic storage potential. The ROZs below the oil/water contact (OWC) of main pay zones (MPZ) in conventional reservoirs or brownfields, are more commonly developed for CO2 injection and oil production and reported in the literature. However, CO2-EOR in greenfield ROZs, reservoirs without a MPZ present, have rarely been developed for CO2-EOR operation. The Tall Cotton Field of West Texas, Permian Basin, which started production in 2015 (Phase 1) and expanded in 2017 (Phase 2) from the San Andres Limestone, is one of the first examples of greenfield ROZs developed for EOR by injecting CO2.
This paper analyses EOR and CO2 retention performance of Tall Cotton Field using allocated injection and production data from inverted 5-spot well patterns of Phase-1 and -2 developments. Production and injection data allocated to each of the 28 identified patterns (nine 20-acre patterns for Phase-1, three 20-acre and sixteen 10-acre patterns for Phase-2) were analyzed for historical and forecasted oil recovery using ratio-trend decline analysis, and for CO2 retention performance of the patterns. The allocated data were further used to calculate injected reservoir pore volume and void replacement ratios (VRR) for the analysis period. Quantitative results indicated that oil recovery factors of the 5-spot patterns varied between 4–10 %, and 5–30 % between the end of injection and the forecast periods, respectively. Storage of CO2, on the other hand, increased to a mean value of ∼7130 MMscf per pattern in Phase-1 and to a mean storage of 3700 MMscf per pattern in Phase-2 until the end of injection, followed by a decline after the end of injection and into the forecast period. Resulting CO2 utilization factors ∼6–50 Mscf/bbl were estimated at the end of injection. Overall, presented results suggested that developing greenfield ROZs for CO2-EOR can be as promising as brownfield ROZs and mature MPZs for EOR and underground storage of injected CO2. For Tall Cotton Field, results suggest that Phase-2 patterns generally outperformed Phase-1 for oil recovery factors, while Phase-1 performed better in CO2 retention performance metrics. This is the first study in the literature that reports a detailed CO2-EOR performance analysis of a greenfield ROZ in the Permian Basin, which can potentially allow for comparison with MPZs and brownfield ROZs.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ccst.2025.100544","usgsCitation":"Karacan, C.O., 2025, Performance analysis of oil recovery and CO2 retention in a greenfield residual oil zone: CO2-EOR in Tall Cotton Field (Permian Basin, West Texas, USA): Carbon Capture Science and Technology, v. 17, 100544, 14 p., https://doi.org/10.1016/j.ccst.2025.100544.","productDescription":"100544, 14 p.","ipdsId":"IP-179246","costCenters":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":496930,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ccst.2025.100544","text":"Publisher Index Page"},{"id":496830,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Texas","county":"Gaines County","otherGeospatial":"Tall Cotton Field","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -103.04678856680947,\n 33.3881629621319\n ],\n [\n -103.04678856680947,\n 31.601101499990648\n ],\n [\n -101.42024271710294,\n 31.601101499990648\n ],\n [\n -101.42024271710294,\n 33.3881629621319\n ],\n [\n -103.04678856680947,\n 33.3881629621319\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"17","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Karacan, C. Ozgen 0000-0002-0947-8241","orcid":"https://orcid.org/0000-0002-0947-8241","contributorId":201991,"corporation":false,"usgs":true,"family":"Karacan","given":"C.","email":"","middleInitial":"Ozgen","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":950843,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70271966,"text":"ofr20251037 - 2025 - Reconnaissance of potential alternate water supply sources for the City of Gary, West Virginia","interactions":[],"lastModifiedDate":"2026-02-03T16:28:45.074551","indexId":"ofr20251037","displayToPublicDate":"2025-11-14T14:55:00","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-1037","displayTitle":"Reconnaissance of Potential Alternate Water Supply Sources for the City of Gary, West Virginia","title":"Reconnaissance of potential alternate water supply sources for the City of Gary, West Virginia","docAbstract":"Seven potential sources of water, consisting of free-flowing discharge from abandoned coal mines at six locations and one abandoned flooded underground coal mine air shaft, were sampled for chemical analysis to assess the quality of the groundwater emanating from the seven mine sources. The six free-flowing mine discharge sources were also assessed for discharge by current-meter measurements on two separate occasions. The U.S. Geological Survey assessed these seven sources to provide information to the City of Gary, West Virginia (W. Va.), and the City of Gary’s consulting engineer with groundwater-quality and flow data to allow them to assess the seven sites as potential alternate sources of water for the City of Gary to augment its existing supply.
For the six sites where discharge could be measured, discharge ranged from a minimum of 0.082 cubic feet per second (ft3/s) to a maximum of 3.685 ft3/s. Of the six sites measured, only two, Harmon Branch at Thorpe, W. Va. (USGS site 372201081303501) and the abandoned public-supply water wells near Havaco, W. Va. (USGS site 372358081344601), had discharge in excess of 1.00 ft3/s. Discharge from the abandoned public supply wells was 3.685 ft3/s on September 20, 2023, and 2.888 ft3/s on October 16, 2023, and discharge from Harmon Branch at Thorpe, W. Va., was 1.049 ft3/s on September 22, 2023, and 1.038 ft3/s on October 17, 2023. Discharge in the abandoned underground mine air shaft (USGS site 372224081340901) could not be assessed, but the air shaft drains an abandoned mine that likely contains water stored in approximately 1.7 square miles (mi2) of abandoned underground coal mines in the Pocahontas No. 3 coal seam, and possibly an additional 0.9 mi2 of leakage from the overlying Pocahontas No. 4 coal seam. Discharge for the six sites measured for the study was measured during a period between September 20 and October 18, 2023, and corresponded to the 12th to the 15th percentile of flow-duration statistics for the Tug Fork downstream of Elkhorn Creek at Welch, W. Va. streamgage (USGS site 03212750).
Water-quality data for the seven sites sampled overall were acceptable with respect to drinking water standards. Of the 203 constituents analyzed, only a few failed to meet applicable U.S. Environmental Protection Agency (EPA) drinking water standards. Iron exceeded the 300 micrograms per liter (μg/L) secondary maximum contaminant level (SMCL) at only 1 of the 7 sites (14.3 percent) sampled. Iron concentrations ranged from a minimum of less than (<) 5.00 μg/L to a maximum of 724 μg/L with a median concentration of 7.62 μg/L. Manganese exceeded the 50.0 μg/L SMCL at 2 of the 7 sites (28.6 percent) sampled. Manganese concentrations ranged from a minimum of 1.93 μg/L to a maximum of 271 μg/L with a median concentration of 4.03 μg/L. No sites sampled exceeded the arsenic maximum contaminant level (MCL) of 10 μg/L. Arsenic concentrations ranged from a minimum of <0.100 μg/L to a maximum of 2.35 μg/L with a median arsenic concentration of 0.200 μg/L. None of the seven sites sampled for selenium for this study exceeded the EPA MCL of 50.0 μg/L. Selenium concentrations ranged from a minimum of <0.050 μg/L to a maximum of 5.26 μg/L with a median concentration of 3.21 μg/L.
All seven sites were sampled for volatile organic compounds (VOCs), semivolatile organic compounds (SVOCs), and polychlorinated biphenyls (PCBs), but most had concentrations below the detection limit. Of the 10 PCB compounds analyzed for the seven sites sampled, none contained detectable concentrations of PCBs or Aroclor compounds. Of the 44 SVOCs analyzed at each of the seven sites sampled, only 1 SVOC, acenaphthene, was detected, at a concentration of 0.02 μg/L. Of the 96 VOCs analyzed, from each of the seven sites sampled, only two were found at detectable concentrations. Trichloromethane was detected only at 1 of the 7 (14.3 percent) sites sampled at a concentration of 0.027 μg/L, and benzene was detected at the same site and 3 additional sites (4 of the 7 sites or 57.1 percent of the sites sampled) at concentrations of 0.028, 0.029, 0.021, and 0.035 μg/L, but none exceeded the EPA MCL for benzene of 5.00 μg/L.
Total coliform bacteria are ubiquitous in the environment, and their presence only suggests the potential for contamination by near-surface processes. Escherichia coli (E. coli) bacteria are derived from either human or animal fecal material and can be an indicator of potential contamination by pathogenic bacteria or viruses. Total coliform bacteria were detected at all 7 sites sampled at concentrations ranging from 17.5 to greater than (>) 2,420 most probable number per 100 mL (MPN/100 mL) of sample, with a median total coliform concentration of 1,553 MPN/100 mL. Escherichia coli bacteria were detected at 4 of the 7 sites sampled at concentrations ranging from <1 to 11.9 MPN/100 mL, with a median E. coli concentration of 5.1 MPN/100 mL.
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1730 East Parham Road
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ringed seal whelping”","docAbstract":"The spring is a critical period when polar bears (Ursus maritimus Phipps, 1774) are thought to have peak access to seals and acquire the majority of their annual energy requirements during a period of hyperphagia. Pagano et al. (Pagano A.M., Atkinson S.N., and Archer L.C. 2025. Arctic Science.11:1-14. doi:10.1139/as-2024-0051) examined the intra-seasonal changes in body mass of 31 polar bears on the spring sea ice and found polar bears exhibited a feast or famine lifestyle. A lack of a relationship between changes in body mass and recapture date suggested that many bears had not entered their primary period of hyperphagia. Pilfold extended our discussion to conclude that our data show polar bear hyperphagia begins after the period of ringed seal (Pusa hispida Schreber, 1775) whelping, and discusses this in relation to previous work on the timing of polar bear seal kills. Here, we reassess whether our data provide information on the timing of polar bear hyperphagia. We find no relationships in our data to conclude when polar bear hyperphagia begins. 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","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/as-2025-0057","usgsCitation":"Pagano, A.M., Atkinson, S.N., and Archer, L.C., 2025, Reply to the discussion by Pilfold “Polar bear mass change confirms hyperphagia follows ringed seal whelping”: Arctic Science, v. 11, p. 1-3, https://doi.org/10.1139/as-2025-0057.","productDescription":"3 p.","startPage":"1","endPage":"3","ipdsId":"IP-181354","costCenters":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":496749,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1139/as-2025-0057","text":"Publisher Index Page"},{"id":496644,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Pagano, Anthony M. 0000-0003-2176-0909 apagano@usgs.gov","orcid":"https://orcid.org/0000-0003-2176-0909","contributorId":3884,"corporation":false,"usgs":true,"family":"Pagano","given":"Anthony","email":"apagano@usgs.gov","middleInitial":"M.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":950461,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Atkinson, Stephen N.","contributorId":362432,"corporation":false,"usgs":false,"family":"Atkinson","given":"Stephen","middleInitial":"N.","affiliations":[{"id":86523,"text":"26104 Melrose Road, Cooks Creek, MB R5M 0B9, Canada","active":true,"usgs":false}],"preferred":false,"id":950462,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Archer, Louise C.","contributorId":362433,"corporation":false,"usgs":false,"family":"Archer","given":"Louise","middleInitial":"C.","affiliations":[{"id":67687,"text":"University of Toronto Scarborough","active":true,"usgs":false}],"preferred":false,"id":950463,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70272102,"text":"fs20253045 - 2025 - Using monitoring and partnerships to provide management-relevant information about Chesapeake Bay rivers","interactions":[],"lastModifiedDate":"2026-02-03T16:27:44.999419","indexId":"fs20253045","displayToPublicDate":"2025-11-14T09:52:32","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-3045","displayTitle":"Using Monitoring and Partnerships to Provide Management-Relevant Information about Chesapeake Bay Rivers","title":"Using monitoring and partnerships to provide management-relevant information about Chesapeake Bay rivers","docAbstract":"The lands and waters of the Chesapeake Bay watershed provide more than $100 billion in economic benefits- an amount that is expected to increase by achieving the region’s clean-water goals. 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U.S. Geological Survey
1730 East Parham Road
Richmond, VA 23228
Massachusetts extends from the mountains of the Appalachian system in the west of the State to the sandy beaches and rocky shorelines of the Atlantic coast in the east. Inland topographic data support a wide range of important activities, including geologic mapping, transportation planning, forest and wildlife management, quantifying ecological services, water supply protection, commonwealth-wide infrastructure planning, local site planning, and flood-plain management. Nearshore bathymetry can be used to support coastal portions of the Commonwealth by addressing the combined threats of ocean warming, strong storm surge, and rising sea levels. The maintenance and (or) expansion of Massachusetts ports (for instance, Boston, New Bedford) and Cape Cod sediment management depends upon the accurate mapping of bathymetry and the frequent influx of sediment and redeposition. Critical applications that address the broad range of requirements depend on light detection and ranging (lidar) data that provide a highly detailed three-dimensional (3D) model of the Earth’s surface and aboveground features.
The 3D Elevation Program (3DEP) is managed by the U.S. Geological Survey (USGS) in partnership with Federal, State, Tribal, U.S. territorial, and local agencies to acquire consistent lidar coverage at quality level 2 or better to meet the many needs of the Nation and Massachusetts. The status of available and in-progress 3DEP baseline lidar data in Massachusetts is shown in figure 1. 3DEP baseline lidar data include quality level 2 or better, 1-meter or better digital elevation models, and lidar point clouds, and must meet the Lidar Base Specification version 1.2 (https://www.usgs.gov/3dep/lidarspec) or newer requirements. The National Enhanced Elevation Assessment identified user requirements and conservatively estimated that availability of lidar data would result in at least $1.23 million in new benefits annually to Massachusetts. The top 10 Massachusetts business uses for 3D elevation data, which are based on the estimated annual conservative benefits of 3DEP, are shown in table 2.
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\"}}]}","contact":"Director, National Geospatial Program
U.S. Geological Survey
12201 Sunrise Valley Drive, MS 511
Reston, VA 20192
Clade 2.3.4.4b Eurasian-origin H5N1 entered North America in late 2021 and spread across the continent. While studies have characterized the antibody response mounted by dabbling ducks following exposure, little data are available for diving ducks. This study sought to identify influenza A virus (IAV) infection and antibodies in Lesser and Greater Scaup captured in Maryland, Illinois, and Rhode Island. In Maryland, IAV seroprevalence increased from the 2021/2022 to 2022/2023 sampling season, with IAV antibody prevalence increasing for juvenile (38% to 80%) and adult (82% to 90%) Lesser Scaup. While adult Lesser Scaup sampled in Illinois in 2021/2022 had IAV antibody prevalence comparable to those sampled in Maryland (76% and 82%, respectively), they had higher antibody prevalence to both H5 (48% and 18%) and N1 (68% and 35%), potentially due to being sampled in March versus December and January. Our data suggest that Lesser Scaup had limited antibodies to highly pathogenic H5 IAV prior to the introduction of clade 2.3.4.4b H5N1 to North America, but relevant antibodies were widely observed in the months and year following. Our more limited data suggest similar trends may have occurred in Greater Scaup as well.
","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjm-2025-0176","usgsCitation":"Sullivan, J.D., Poulson, R., Olsen, G.H., Berlin, A., Cao, Z., Carter, D., Homyack, J., Kilburn, J., McWilliams, S.R., Osborn, J., Mezebish Quinn, T., Schley, H., Weegman, M.M., Williams, C., Stallknecht, D., and Prosser, D.J., 2025, Rapid increase in antibodies to influenza A virus H5 and N1 in Lesser Scaup (Aythya affinis) following the introduction of 2.3.4.4B H5N1 into North America: Canadian Journal of Microbiology, v. 71, p. 1-6, https://doi.org/10.1139/cjm-2025-0176.","productDescription":"6 p.","startPage":"1","endPage":"6","ipdsId":"IP-181219","costCenters":[{"id":50464,"text":"Eastern Ecological Science 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