The communities in Indian Wells Valley (IWV), in the northern Mojave Desert in California, rely on groundwater for domestic and agricultural use. Mountain front recharge from the surrounding Sierra Nevada is the main source of natural recharge to the valley. Increased urbanization, agricultural development, and groundwater pumping during recent decades put IWV in a state of critical overdraft. The U.S. Geological Survey Basin Characterization Model, version 8 (BCMv8) was used to evaluate historical and future climate and hydrologic conditions in IWV. The BCMv8 estimated natural recharge in IWV at 10.7 million cubic meters (Mm3) per year for the period from 1981 to 2010. Future patterns of water balance variables using three future climate scenarios, hot- wet, hot-dry, and warm-moderately wet, were calculated for mid-century (2040–69) and end-of-century (2070–99) periods. Results for both wet models projected an increase in recharge in both periods, whereas the hot-dry model projected a decrease in recharge in both periods. All models reported a large increase in seasonal variability in recharge, indicating more future availability and frequent occurrences of drought years. All climate scenarios projected an increase in climatic water deficit in both periods. These increases in irrigation demand and variability of water supply highlight the importance of strategic management planning for the sustainability of water resources in IWV.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20265114","collaboration":"Prepared in cooperation with Kern County, California","programNote":"Water Availability and Use Science Program","usgsCitation":"Saleh, D., Flint, L., and Stern, M., 2026, Assessing natural recharge in Indian Wells Valley, California—A Basin Characterization Model case study (ver. 1.1, March 2026): U.S. Geological Survey Scientific Investigations Report 2026–5114, 34 p., https://doi.org/10.3133/sir20265114.","productDescription":"vi, 34 p.","numberOfPages":"34","onlineOnly":"Y","ipdsId":"IP-104255","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":501283,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_119214.htm","linkFileType":{"id":5,"text":"html"}},{"id":501282,"rank":6,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2026/5114/versionHist.txt","linkFileType":{"id":2,"text":"txt"},"description":"SIR 2026-5114 Version History"},{"id":501281,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2026/5114/images"},{"id":501278,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2026/5114/sir20265114.pdf","text":"Report","size":"4.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2026-5114 PDF"},{"id":501279,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20265114/full","linkFileType":{"id":5,"text":"html"},"description":"SIR 2026-5114 HTML"},{"id":501280,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2026/5114/sir20265114.XML","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2026-5114 XML"},{"id":500366,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2026/5114/coverthb2.jpg"}],"country":"United States","state":"California","otherGeospatial":"Indian Wells Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -118.5,\n 36.5\n ],\n [\n -118.5,\n 35\n ],\n [\n -117,\n 35\n ],\n [\n -117,\n 36.5\n ],\n [\n -118.5,\n 36.5\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","edition":"Version 1.0: February 18, 2026; Version 1.1: March 18, 2026","contact":"Director, California Water Science Center
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Monitoring suspended-sediment concentration (SSC) is essential to better understand how sediment transport could adversely affect water availability for human communities and ecosystems. Aquatic remote sensing methods are increasingly utilized to estimate SSC and turbidity in rivers; however, an evaluation of their quantitative performance is limited. This study evaluates the performance of three multispectral sensors, which vary in resolution and ease of deployment, to estimate turbidity in the Colorado River: the Multispectral Instrument (MSI) on board the European Space Agency’s Sentinel-2 satellite, an industrial-grade 10-band dual camera system mounted on a cable car, and a consumer-grade 6-band dual camera system positioned on the riverbank. We use multivariate linear regression to compare in situ turbidity measurements with concurrent spectral reflectance data from each sensor. Models for all three sensors selected similar spectral information and resulted in mean errors <35% in predicting turbidity. A cross-sensor comparison showed that little accuracy is lost when applying models developed for satellite-based systems to ground-based systems, and vice versa. Transferability of satellite-based models to ground-based systems could support continuous water-quality monitoring between satellite overpasses and avoid issues associated with cloud interference. Conversely, continuously operating ground-based systems could be used to rapidly establish datasets and models for application in satellite imagery, thus accelerating remote sensing applications. The encouraging performance of the consumer-grade system indicates that SSC could be monitored for low cost.
","language":"English","publisher":"MDPI","doi":"10.3390/rs18040638","usgsCitation":"Day, N.K., King, T.V., and Mosbrucker, A.R., 2026, A comparison of non-contact methods for measuring turbidity in the Colorado River: Remote Sensing, v. 18, no. 4, 638, 26 p., https://doi.org/10.3390/rs18040638.","productDescription":"638, 26 p.","ipdsId":"IP-177709","costCenters":[{"id":157,"text":"Cascades Volcano Observatory","active":false,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":500256,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs18040638","text":"Publisher Index Page"},{"id":500184,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","city":"Cameo","otherGeospatial":"Colorado River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -108.22,\n 39.26\n ],\n [\n -108.5833,\n 39.26\n ],\n [\n -108.5833,\n 39\n ],\n [\n -108.22,\n 39\n ],\n [\n -108.22,\n 39.26\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"18","issue":"4","noUsgsAuthors":false,"publicationDate":"2026-02-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Day, Natalie K. 0000-0002-8768-5705","orcid":"https://orcid.org/0000-0002-8768-5705","contributorId":207302,"corporation":false,"usgs":true,"family":"Day","given":"Natalie","middleInitial":"K.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":955899,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"King, Tyler V. 0000-0002-5785-3077","orcid":"https://orcid.org/0000-0002-5785-3077","contributorId":292424,"corporation":false,"usgs":true,"family":"King","given":"Tyler","middleInitial":"V.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":955900,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mosbrucker, Adam R. 0000-0003-0298-0324 amosbrucker@usgs.gov","orcid":"https://orcid.org/0000-0003-0298-0324","contributorId":4968,"corporation":false,"usgs":true,"family":"Mosbrucker","given":"Adam","email":"amosbrucker@usgs.gov","middleInitial":"R.","affiliations":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":955901,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70273925,"text":"sir20255113 - 2026 - Treatability study to evaluate bioremediation of trichloroethene at Site K, former Twin Cities Army Ammunition Plant, Arden Hills, Minnesota, 2020–22","interactions":[],"lastModifiedDate":"2026-02-20T18:18:35.530487","indexId":"sir20255113","displayToPublicDate":"2026-02-18T08:45:00","publicationYear":"2026","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-5113","displayTitle":"Treatability Study to Evaluate Bioremediation of Trichloroethene at Site K, Former Twin Cities Army Ammunition Plant, Arden Hills, Minnesota, 2020–22","title":"Treatability study to evaluate bioremediation of trichloroethene at Site K, former Twin Cities Army Ammunition Plant, Arden Hills, Minnesota, 2020–22","docAbstract":"Chlorinated solvents, including trichloroethene (TCE) and other chlorinated volatile organic compounds (cVOCs), are widespread contaminants that can be treated by bioremediation approaches that enhance anaerobic reductive dechlorination. Reductive dechlorination can be enhanced either through the addition of an electron donor (biostimulation) or the addition of a known dechlorinating culture (bioaugmentation) along with an electron donor. Although bioremediation has been applied at many TCE- contaminated groundwater sites, application in source zones at sites where residual dense nonaqueous phase liquid (DNAPL) is present is more limited. In this study, laboratory and field treatability tests were completed to evaluate the potential application of anaerobic bioremediation for a shallow groundwater plume containing TCE in a perched alluvial aquifer at Site K, former Twin Cities Army Ammunition Plant, Arden Hills, Minnesota, which was on the National Priorities List as the New Brighton/Arden Hills Superfund site until 2019. In addition to the presence of residual DNAPL at the site, temporal variability in groundwater flow directions and input of oxygenated recharge were possible complicating factors for the application of enhanced anaerobic biodegradation in the shallow plume. The Site K plume extends beneath the footprint of Building 103, which was demolished in 2006, and soil excavations to a maximum depth of 6 feet (ft) below ground surface in 2014 were known to leave some deeper contaminated soil in place in the TCE source area. Groundwater treatment at the site, formalized as part of the 1997 Record of Decision, has been in operation since 1986 and consists of an extraction trench at the downgradient edge of the plume to collect groundwater, which is then pumped to an on- site air stripper. Groundwater concentrations in the plume have been relatively stable since treatment began, indicating a continued source of TCE in the aquifer. The desire for a destructive remedy that would enhance the removal of cVOCs in the aquifer at Site K and shorten the remediation timeframe led the U.S. Army to request that the U.S. Geological Survey conduct a groundwater treatability study to assess bioremediation. This report describes the U.S. Geological Survey bioremediation treatability study conducted during 2020–22, including pre- design site characterization to assist in formulating the bioremediation approach, laboratory experiments to support the design of the field pilot test, and implementation and 1-year performance monitoring results for the pilot test.
Pre- design site characterization included the collection of soil cores for cVOC analysis and lithologic descriptions and the re- installment of three wells to obtain hydrologic measurements and initial groundwater chemistry. Relatively flat head gradients were measured at the site, and substantial decreases in water- level elevations occurred from spring to summer (May–July 2021). Continuous water- level monitoring indicated a rapid response to precipitation. Groundwater flow velocities were consistently less than 0.5 foot per day, and the pilot bioremediation test was therefore designed with short lateral distances (about 5 ft) between injection and individual monitoring points. Soil analyses confirmed that high volatile organic compound contamination was left in place in the source area. The highest concentrations were near or in clay at the base of the perched aquifer. Concentrations of cVOCs measured in the replaced wells were consistent with historical data and had a maximum TCE concentration of 57,700 micrograms per liter (μg/L), indicative of nearby residual DNAPL based on the general rule of observed concentrations exceeding 1 percent of solubility. The primary TCE daughter product detected was 1,2- cis- dichloroethene (cisDCE), which indicated limited reductive dechlorination in the plume. Groundwater in both the source and downgradient areas was relatively reducing during the pre- design characterization, particularly in the source area where methane concentrations greater than 400 μg/L were measured.
Initial laboratory tests conducted using native aquifer microorganisms from the three replacement wells showed that anaerobic TCE biodegradation rates were low when biostimulated with the addition of sodium lactate as an electron donor, also known as a carbon donor, and resulted in the production of only cisDCE. Addition of a known dechlorinating culture, WBC- 2, however, resulted in rapid biodegradation and production of ethene, verifying complete reductive dechlorination of TCE. Microcosms constructed with aquifer soil collected from the site were used to evaluate other electron donors besides lactate to support reductive dechlorination by WBC- 2, including corn syrup as an alternative fast- release compound and whey, soy- based vegetable oil, and 3- D Microemulsion (Regenesis, San Clemente, California) as slow-release compounds. First- order rate constants for total organic chlorine removal in these WBC- 2 amended microcosms were greatest with either lactate or vegetable oil as the donor, ranging between 0.061 and 0.047 per day or corresponding half- lives of 11–15 days. Testing of commercial products in other WBC- 2- bioaugmented microcosms led to selection for the field pilot test of an emulsified vegetable oil product that also contained some sodium lactate as a fast- release donor. Delaying the addition of WBC- 2 relative to the donor in the microcosms resulted in the most rapid overall biodegradation rates.
The selected design for the pilot test utilized three separate test plots, each about 30-ft wide and 60-ft long: plots GS1 and GS2 in the source area of the plume and plot GS3 in the downgradient area of the plume near the excavation trench. Each test plot had one injection well, one monitoring well upgradient from the injection point, and 12 surrounding monitoring wells in a grid to capture variable groundwater flow directions. Donor injections, which included a bromide tracer, were completed in October 2021, immediately following baseline sampling, and the WBC- 2 culture was injected about 40 days later, between November 30 and December 2, 2021. Performance monitoring conducted until December 2022 included hydrologic measurements and analyses of cVOCs, redox- sensitive constituents, dissolved organic carbon, bromide, volatile fatty acids, compound- specific carbon isotopes, and microbial communities.
The biogeochemical data collected during the pilot tests in the three treatment plots showed that enhanced, complete reductive dechlorination of cVOCs in the groundwater was achieved in the GS1 and GS3 plots. In contrast, evidence of distribution of the injected amendments and subsequent biodegradation was limited in GS2, which was in an area of more heterogeneous soil lithology and low water table elevations. The molar composition of volatile organic compounds in the GS1 and GS3 plots was dominated by ethene in wells that were reached by the injected amendments by the end of the monitoring period. In the GS1 and GS3 plots, similar patterns were observed of cVOC concentrations decreasing to near detection levels, or below, at some wells sampled in July and October 2022, whereas ethene became dominant and indicated sustained complete reductive dechlorination. Baseline cVOC concentrations were more than a factor of 10 higher in the groundwater in the GS1 plot than in GS3, but no apparent inhibition of complete dechlorination occurred. As expected from the initial pre- design site data and the laboratory experiments, enhanced dissolution of residual DNAPL coupled to biodegradation was evident in the GS1 plot, where a marked increase in dichloroethene (DCE) above the initial baseline and upgradient TCE and DCE concentrations occurred. DCE concentrations subsequently declined where DNAPL dissolution was evident, concurrent with production of vinyl chloride and then predominantly ethene. Thus, overall biodegradation rates outpaced the DNAPL dissolution and desorption and DCE production in the source area. This success in complete degradation to predominantly ethene was achieved even in areas where the DCE concentrations reached a maximum of about 30,000 μg/L. Compound specific isotope analysis of carbon in TCE, cisDCE, trans- 1,2- dichloroethene, and vinyl chloride was conducted to provide another line of evidence of the occurrence and extent of anaerobic biodegradation. Along a flow path in each plot that was affected by the injected amendments, carbon isotopes in the TCE and daughter cVOCs in the groundwater became isotopically heavier, indicating biodegradation.
Enhanced biodegradation rates calculated from the field tests in GS1 and GS3 showed half- lives of 36.9–75.3 days for DCE degradation and 9.48–38.5 days for ethene production. Notably, these ethene production rates calculated from the field tests are consistent with the results of WBC- 2- bioaugmented microcosms amended with either lactate or vegetable oil, which had half- lives for total organic chlorine removal that ranged from 11 to 15 days. These rates indicated rapid enhanced biodegradation, which is promising for application of a full- scale bioremediation remedy. Ultimately, however, the mass of residual or sorbed TCE in the aquifer that remains accessible for dissolution and biodegradation would likely control the time required for a full- scale bioremediation effort to achieve performance goals for TCE and cisDCE specified in the Record of Decision for Site K.
The field pilot tests showed that the relatively low hydraulic head gradients and temporal changes in groundwater flow directions in the shallow aquifer would add complexity to a full- scale bioremediation effort. The radius of influence (ROI) at GS1 and GS3 (16.3 ft and 12.7 ft, respectively) were close to the design ROI of 15 ft. The estimated ROI at GS2 was about four times the design ROI, but may be less reliable at this location owing to groundwater flow direction. In addition, the low temperatures following WBC- 2 injection in late November to early December 2021, in combination with the low hydraulic head gradients, were probably major factors in the delay observed before the onset of enhanced biodegradation following injection of the culture. Additional test injections could be beneficial to optimize the timing of donor and culture injections with the variable temperatures and hydraulic head in the shallow aquifer.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255113","collaboration":"Prepared in cooperation with U.S. Army Environmental Command","usgsCitation":"Lorah, M.M., Majcher, E.H., Mumford, A.C., Foss, E.P., Needham, T.P., Psoras, A.W., Livdahl, C.T., Trost, J.J., Berg, A.M., Polite, B.F., Akob, D.M., and Cozzarelli, I.M., 2026, Treatability study to evaluate bioremediation of trichloroethene at Site K, former Twin Cities Army Ammunition Plant, Arden Hills, Minnesota, 2020–22: U.S. Geological Survey Scientific Investigations Report 2025–5113, 88 p., https://doi.org/10.3133/sir20255113.","productDescription":"Report: xii, 88 p.; Data Release","numberOfPages":"88","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-175852","costCenters":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"links":[{"id":500361,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_119213.htm","linkFileType":{"id":5,"text":"html"}},{"id":500106,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13QTBR7","text":"USGS data release","linkHelpText":"Former Twin Cities Army Ammunition Site K treatability test data including various field measurements, laboratory tests and degradation constituents in the bioremediation of trichloroethylene and dichloroethylene, Arden Hills, Minnesota 2020–2022"},{"id":500104,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5113/sir20255113.XML","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2025-5113 XML"},{"id":500103,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255113/full","linkFileType":{"id":5,"text":"html"},"description":"SIR 2025-5113 HTML"},{"id":500102,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5113/sir20255113.pdf","size":"6.92 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5113 PDF"},{"id":500101,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5113/coverthb.jpg"},{"id":500105,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5113/images/"}],"country":"United States","state":"Minnesota","county":"Ramsey County","city":"Arden Hills","otherGeospatial":"Site K, former Twin Cities Army Ammunition Plant","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -93.17794646411902,\n 45.1090420800339\n ],\n [\n -93.17794646411902,\n 45.08000250215488\n ],\n [\n -93.14480906199879,\n 45.08000250215488\n ],\n [\n -93.14480906199879,\n 45.1090420800339\n ],\n [\n -93.17794646411902,\n 45.1090420800339\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Maryland-Delaware-D.C. Water Science Center
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5522 Research Park Drive
Catonsville, MD 21228
The Puyallup River drains a 990 square mile watershed in western Washington, with headwaters on the glacier-covered flanks of Mount Rainier. Major tributaries include the White, Carbon, and Mowich Rivers. In the levee-confined reaches of the lower watershed, loss of flood conveyance due to sand and gravel deposition has been a chronic issue. Over much of the 20th century, flood conveyance was maintained through sediment removal, but this practice ended in the late 1990s. Flood hazard management activities since the 1990s have primarily involved levee removal or setback projects. Assessments of 1984-2009 repeat cross sections suggested that sediment deposition rates were particularly high in reaches with recent levee setbacks. However, there have been no assessments of recent deposition rates since the 2009 surveys. There are also concerns that intensifying flood hydrology or increased sediment delivery from Mount Rainier may exacerbate deposition. However, assessment of those risks has been hindered by limited understanding of watershed-scale sediment delivery and routing, particularly for coarse sand and gravel.
The U.S. Geological Survey, in cooperation with Pierce County, initiated this study to improve understanding of sediment deposition in the lower Puyallup River watershed. This work is primarily based on differencing of multiple aerial lidar datasets collected during 2002–2022, supplemented by early 1990 photogrammetric elevation datasets, geomorphic assessments of streamgage data, historical topographic surveys from 1907, and previously collected sediment transport measurements. Analyses cover the Puyallup, Carbon, and Mowich Rivers, but do not include the White River.
During 2004–2020, repeat aerial lidar indicates that 1.3 ± 0.3 million yd3 of sediment accumulated in the lower 20 valley miles (VMs) of the Puyallup River, averaging 80,000 ± 20,000 cubic yards per year (yd3/yr). Deposition was observed during both 2004–11 and 2011–20 lidar differencing intervals. This continued a long-term depositional trend that extends back to at least 1977. From 2004 to 2011, deposition rates along the Soldiers Home levee setback reach, the only setback project downstream of VM 20 completed prior to 2011, were approximately four times higher than in adjacent unmodified reaches. From 2011 to 2020, two additional setback projects were completed; volumetric deposition rates over all three setback reaches were similar to adjacent unmodified reaches, suggesting elevated setback deposition in the 2004–11 interval may have been influenced by an extreme flood in November 2006. These levee setback projects increased the local cross-sectional area of the floodway, used as a rough proxy for relative flood conveyance, by 50 to 200 percent above 2004 conditions. If deposition continued at recent rates, cross-sectional area over the levee setback reaches would be reduced back to 2004 values by 2050-90.
Deposition also occurred over the lower six VMs of the Carbon River during 2004–20, though volumes (0.15 ± 0.09 million yd3) were an order of magnitude lower than along the Puyallup River. Relatively lower deposition rates in the Carbon River are most likely the combined result of modestly lower incoming sediment loads, modestly steeper channel slope, and the additional sediment transport capacity provided by two large non-glacial tributaries that enter the Carbon River near VM 5.
Upstream of the depositional reaches described above, 2002–22 sediment storage trends along the Puyallup, Carbon, and Mowich Rivers were predominately negative (net erosion) up to the Mount Rainier National Park boundary. Net erosion was the result of bank and bluff erosion exceeding deposition across wetted channel and bare gravel areas, as opposed to uniform vertical downcutting. Net erosion along these river valleys delivered 3.4 ± 0.6 million yd3 to the river system, equivalent to 190,000 ± 35,000 yd3/yr. Most of that volume was supplied by erosion of relatively low (4–10 ft) surfaces along the Puyallup and Mowich Rivers and tall (300 ft) glacial bluffs along the lower Carbon River. Substantial aggradation from 1984 to 2009 reported by Czuba and others (2010) along reaches of the Puyallup River (VM 19–22) where levee confinement has recently been removed was most likely an artifact of methodologic bias.
The Puyallup, Mowich, and Carbon Rivers drain five distinct glaciated watersheds on the flanks of Mount Rainier, four of which were assessed in this study. All four watersheds were impacted by an extreme November 2006 rainstorm. Between 2002 and 2008, debris flows occurred in all four headwater areas, collectively eroding at least 2.1 million yd3 of sediment. These debris flows formed distinct deposits one to two miles downstream of source areas, depositing 30-50 percent of the material eroded upstream. From 2008 to 2022, no headwater debris flows were observed and overall rates of geomorphic change in the headwaters were low. Rivers eroded into debris flow deposits emplaced over the 2002–08 interval, but re-deposited equivalent volumes of material within a half mile downstream.
Stage-discharge relations at five streamgages on upland rivers draining Mount Rainier show either net channel incision or dynamic variability with no long-term trend over the past 60–100 years. Observations of pervasive river valley erosion and stable or incising trends at long-term streamgages in the upper watershed do not support prior claims of widespread and accelerating aggradation of upland rivers draining Mount Rainier.
Erosion and deposition volumes estimated in this report were combined with sediment transport estimates from limited suspended sediment and bedload measurements, estimates of sub-glacial erosion rates, and sediment delivery from non-glacial tributaries to construct watershed-scale sediment budgets for the Puyallup River watershed. During 2004–20, the estimated sediment load entering the depositional lowlands was well balanced by estimated inputs from, in order of relative magnitude, subglacial erosion (33–60 percent of total sediment load), erosion along the major river valleys (25–45 percent), erosion in recently deglaciated headwater areas (7–17 percent) and non-glacial tributaries (3–9 percent). These results are specific to the study period and represent total sediment loads, most of which is fine material carried in suspension. The relative sourcing of sand and gravel may be different than implied by this sediment budget.
Downstream of VM 12, comparison of 1907 and 2009 channel surveys show net lowering of the channel thalweg of 4–12 ft. A long-term gage near VM 22 shows lowering of 4–5 ft through the 1960s. Lowering at both locations was inferred to be a channel response to the substantial straightening, and so steepening, of the river during major phases of levee construction through the early and mid-20th century.
Application of a simple empirical bedload-discharge power-law relation to an ensemble of model-estimated daily mean discharge records in the lower Puyallup River between 1977 and 2100 projects that annual bedload transport capacity in the lower Puyallup River will increase by 20–60 percent by the middle of the 21st century. Actual changes in bedload transport and deposition rates will depend on concurrent changes in sediment supply and local hydraulics governing deposition.
This report presents several key conclusions. First, the persistence and spatial patterns of sand and gravel deposition along the lower Puyallup River support prior claims that deposition is fundamentally caused by decreases in channel slope moving downstream. Given this underlying cause and the abundance of sand and gravel available to be transported downstream, deposition is likely to continue for the foreseeable future. Second, despite continued sediment deposition, recent levee setback projects in the lower Puyallup River will likely provide several decades of flood conveyance benefits relative to a no-action alternative. Third, while the rivers linking Mount Rainier to the Puget Sound lowlands have often been discussed as conduits that either pass or accumulate sediment from Mount Rainier, observations from 2002–22 show these river valleys acting as substantial sediment sources, delivering three times more sediment than recently deglaciated headwater areas on Mount Rainier. While the persistence and underlying cause of recent river valley erosion remain unknown, sediment storage dynamics along these river valleys are likely to be a major control on sand and gravel delivery to the lower watershed.
Little is understood of lake browning (due to increased dissolved organic carbon; DOC) in large lakes such as the Laurentian Great Lakes. Lake browning can alter whole lake ecosystems, including decreasing exposure to damaging ultraviolet radiation (UV-B) which is strongly and selectively attenuated by DOC more so than photosynthetically active radiation (PAR). We compared the changes in UV-B and PAR transparency to DOC data collected during the ice-free seasons from 62 nearshore sites in four of the five Great Lakes from 2002 to 2022 using linear mixed effects regression models based on backwards selected Bayesian information criteria. Regionally, DOC significantly increased from 2002 to 2022 by 0.5% per year on average. DOC strongly and inversely explained the variability of UV-B and PAR transparencies, as did seasons and offshore influence on these habitats. We provide regional evidence of lake browning within the nearshore habitats of the Great Lakes as a strong contrast to the well-documented increased offshore water transparency associated with the spread of invasive dreissenid mussels.
","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2024-0407","usgsCitation":"Berry, N., Bunnell, D.B., Fisher, T., Overholt, E., Mette, E., Howell, T., and Williamson, C.E., 2026, Decreased water transparency of nearshore Laurentian Great Lakes habitats is driven by increased dissolved organic carbon.: Canadian Journal of Fisheries and Aquatic Sciences, v. 83, p. 1-9, https://doi.org/10.1139/cjfas-2024-0407.","productDescription":"9 p.","startPage":"1","endPage":"9","ipdsId":"IP-170502","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":500258,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1139/cjfas-2024-0407","text":"Publisher Index Page"},{"id":500189,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Great Lakes","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -88.84751857840234,\n 49.471311017762645\n ],\n [\n -92.81669615927237,\n 46.920316633964475\n ],\n [\n -91.56012545582533,\n 46.18295137477036\n ],\n [\n -87.0507208161673,\n 46.41933841908485\n ],\n [\n -88.74219710454639,\n 43.914354385501326\n ],\n [\n -87.95935986459418,\n 41.59912997740622\n ],\n [\n -83.9720223229704,\n 41.37139907143079\n ],\n [\n -81.15069356336562,\n 40.86644441718417\n ],\n [\n -78.58068940433992,\n 42.033414801353516\n ],\n [\n -75.56437638284248,\n 43.19976943418763\n ],\n [\n -76.07811679933005,\n 44.5165607788128\n ],\n [\n -79.06374555874787,\n 44.2536538155133\n ],\n [\n -79.2312465353583,\n 46.384270370895024\n ],\n [\n -83.12440166219844,\n 46.77820657483097\n ],\n [\n -84.46202674663817,\n 48.73561539687698\n ],\n [\n -88.84751857840234,\n 49.471311017762645\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"83","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Berry, Nicole Lynn 0000-0002-7889-197X","orcid":"https://orcid.org/0000-0002-7889-197X","contributorId":347450,"corporation":false,"usgs":true,"family":"Berry","given":"Nicole Lynn","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":955877,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bunnell, David B. 0000-0003-3521-7747","orcid":"https://orcid.org/0000-0003-3521-7747","contributorId":216540,"corporation":false,"usgs":true,"family":"Bunnell","given":"David","middleInitial":"B.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":955878,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fisher, Thomas J. 0000-0001-5885-7646","orcid":"https://orcid.org/0000-0001-5885-7646","contributorId":347464,"corporation":false,"usgs":false,"family":"Fisher","given":"Thomas J.","affiliations":[{"id":16608,"text":"Miami University","active":true,"usgs":false}],"preferred":false,"id":955879,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Overholt, Erin P. 0000-0001-9078-7086","orcid":"https://orcid.org/0000-0001-9078-7086","contributorId":347452,"corporation":false,"usgs":false,"family":"Overholt","given":"Erin P.","affiliations":[{"id":16608,"text":"Miami University","active":true,"usgs":false}],"preferred":false,"id":955880,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mette, Elizabeth M. 0009-0007-9622-1260","orcid":"https://orcid.org/0009-0007-9622-1260","contributorId":347466,"corporation":false,"usgs":false,"family":"Mette","given":"Elizabeth M.","affiliations":[{"id":16608,"text":"Miami University","active":true,"usgs":false}],"preferred":false,"id":955881,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Howell, Todd","contributorId":294685,"corporation":false,"usgs":false,"family":"Howell","given":"Todd","affiliations":[{"id":63627,"text":"Ontario Ministry of Environment and Climate Change","active":true,"usgs":false}],"preferred":false,"id":955882,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Williamson, Craig E. 0000-0001-7350-1912","orcid":"https://orcid.org/0000-0001-7350-1912","contributorId":347472,"corporation":false,"usgs":false,"family":"Williamson","given":"Craig","middleInitial":"E.","affiliations":[{"id":16608,"text":"Miami University","active":true,"usgs":false}],"preferred":false,"id":955883,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70274031,"text":"70274031 - 2026 - Action in uncertainty: Data-driven decisions that acknowledge emotional responses and transcendental connections","interactions":[],"lastModifiedDate":"2026-02-20T15:05:09.255266","indexId":"70274031","displayToPublicDate":"2026-02-18T07:59:00","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":23303,"text":"ESA Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"Action in uncertainty: Data-driven decisions that acknowledge emotional responses and transcendental connections","docAbstract":"The increasing uncertainty with global change often stifles action and results in calls for more data before moving beyond status quo environmental decisions (Mahapatra & Ratha 2017; Ripple et al. 2017; Montefalcone et al. 2025). Advancing science and collecting more data is crucial; however, science alone (i.e., “western” or “positivist” science, as described in Fuller, 2001; Reid et al. 2020) may be insufficient to reduce uncertainty to a comfortable level for decision making. Therefore, increasing personal and collective capacity to make proactive decisions may require decision makers to recognize that their own understanding of the world, and therefore interpretation of scientific data, is influenced by all Four Realms of human perception: Physical, Mental, Emotional, and Transcendental (Wolf 2017; Dukes et al. 2021; Clifford et al. 2022).\nIn the ESA Special Session, Action in Uncertainty, we introduced four questions to help participants increase cognitive awareness of how all Four Realms may affect their understanding in uncertain environmental decision contexts:\n\n1. Physical: How do I observe uncertainty through the five senses (feel, see, hear, taste, smell)?\nThe physical realm is what people observe, including ecological data observations and\nexperimentation.\n\n2. Mental: How do I think about uncertainty using logic, reason, and language-based\nunderstanding? The mental realm is how people think about the world, including scientific\ntheory, modeling, and decision frameworks.\n\n3. Emotional: How do I feel in uncertainty? The emotional realm is a person’s subjective emotional state, such as fear, curiosity, defensiveness, and awe.\n\n4. Transcendental: How do I connect to something greater than myself in uncertainty? The\ntranscendental realm includes people’s sense of purpose, responsibility for others, or moral\ncode.","language":"English","publisher":"Ecological Society of America","doi":"10.1002/bes2.70071","usgsCitation":"Ward, N.K., Guilbeau, K.G., Sesser, A.L., Lynch, A.J., 2026, Action in uncertainty: Data-driven decisions that acknowledge emotional responses and transcendental connections: ESA Bulletin, e70071, 10 p., https://doi.org/10.1002/bes2.70071.","productDescription":"e70071, 10 p.","ipdsId":"IP-183744","costCenters":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":500826,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/bes2.70071","text":"Publisher Index Page"},{"id":500338,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"edition":"Online First","noUsgsAuthors":false,"publicationDate":"2026-02-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Ward, Nicole K.","contributorId":366783,"corporation":false,"usgs":false,"family":"Ward","given":"Nicole","middleInitial":"K.","affiliations":[{"id":34923,"text":"Minnesota DNR","active":true,"usgs":false}],"preferred":false,"id":956220,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Guilbeau, Kelly G.","contributorId":366784,"corporation":false,"usgs":false,"family":"Guilbeau","given":"Kelly","middleInitial":"G.","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":956221,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sesser, Amanda L.","contributorId":366785,"corporation":false,"usgs":false,"family":"Sesser","given":"Amanda","middleInitial":"L.","affiliations":[{"id":62402,"text":"Prescott College","active":true,"usgs":false}],"preferred":false,"id":956222,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lynch, Abigail J. 0000-0001-8449-8392","orcid":"https://orcid.org/0000-0001-8449-8392","contributorId":207361,"corporation":false,"usgs":true,"family":"Lynch","given":"Abigail","middleInitial":"J.","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":956223,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70273963,"text":"70273963 - 2026 - Rising atmospheric CO2 reduces nitrogen availability in boreal forests","interactions":[],"lastModifiedDate":"2026-02-23T14:14:56.466551","indexId":"70273963","displayToPublicDate":"2026-02-18T07:44:06","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2840,"text":"Nature","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Rising atmospheric CO2 reduces nitrogen availability in boreal forests","title":"Rising atmospheric CO2 reduces nitrogen availability in boreal forests","docAbstract":"Anthropogenic nitrogen (N) pollution has been emphasized as a cause of eutrophication globally. However, several recent datasets have suggested widespread oligotrophication may be occurring in some ecosystems, which is suggested to be a response to rising atmospheric carbon dioxide (eCO2). Plant δ15N chronologies have served as primary evidence for oligotrophication, however, there has been wide disagreement whether eCO2 or temporal changes in N deposition explain these patterns. We constructed δ15N tree ring chronologies across Sweden’s 23.5 million hectare productive forest area from the 1950s to 2010s. The study area spans a 1500 km latitudinal distance where N deposition varies four-fold, but where eCO2 is spatially uniform. Our data revealed negative δ15N chronologies throughout Sweden, including forests in the far north where atmospheric N deposition rates are very low. Linear mixed effects models showed that eCO2 was by far the strongest predictor of δ15N values, whereas N deposition variables, temperature, and forest basal area had much lower explanatory power. Our results clarify debates on the interpretation of previous δ15N chronologies, and provide clear evidence that eCO2 is causing oligotrophication in boreal forests, which has implications for predicting their future role as sinks in the global carbon cycle.
","language":"English","publisher":"Springer Nature","doi":"10.1038/s41586-025-10039-5","usgsCitation":"Bassett, K.R., Hupperts, S.F., Jämtgård, S., Östlund, L., Fridman, J., Perakis, S.S., and Gundale, M.J., 2026, Rising atmospheric CO2 intensifies nitrogen limitation in boreal forests: Nature, no. 650, p. 629-635, https://doi.org/10.1038/s41586-025-10039-5.","productDescription":"7 p.","startPage":"629","endPage":"635","ipdsId":"IP-173383","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":500187,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":500257,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41586-025-10039-5","text":"Publisher Index Page"}],"country":"Sweden","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 14.63346302221828,\n 66.95808924222021\n ],\n [\n 11.816628950923374,\n 62.8816235388625\n ],\n [\n 10.714598292419112,\n 55.39166409191142\n ],\n [\n 12.399827072155716,\n 54.583535462334794\n ],\n [\n 15.194165810541499,\n 55.5418316669677\n ],\n [\n 18.56862330588048,\n 56.05323191584169\n ],\n [\n 20.49382747838886,\n 62.91560998030781\n ],\n [\n 24.239407941016225,\n 65.83107952726502\n ],\n [\n 23.93671762466677,\n 67.79623029566048\n ],\n [\n 20.84193122924367,\n 68.85442260744358\n ],\n [\n 17.380981641240524,\n 68.36281881641594\n ],\n [\n 14.63346302221828,\n 66.95808924222021\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","issue":"650","noUsgsAuthors":false,"publicationDate":"2026-02-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Bassett, Kelley R.","contributorId":366455,"corporation":false,"usgs":false,"family":"Bassett","given":"Kelley","middleInitial":"R.","affiliations":[{"id":12666,"text":"Swedish University of Agricultural Sciences","active":true,"usgs":false}],"preferred":false,"id":955928,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hupperts, Stefan F.","contributorId":366456,"corporation":false,"usgs":false,"family":"Hupperts","given":"Stefan","middleInitial":"F.","affiliations":[{"id":12666,"text":"Swedish University of Agricultural Sciences","active":true,"usgs":false}],"preferred":false,"id":955929,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jämtgård, Sandra","contributorId":366457,"corporation":false,"usgs":false,"family":"Jämtgård","given":"Sandra","affiliations":[{"id":12666,"text":"Swedish University of Agricultural Sciences","active":true,"usgs":false}],"preferred":false,"id":955930,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Östlund, Lars","contributorId":366458,"corporation":false,"usgs":false,"family":"Östlund","given":"Lars","affiliations":[{"id":12666,"text":"Swedish University of Agricultural Sciences","active":true,"usgs":false}],"preferred":false,"id":955931,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fridman, Jonas","contributorId":366459,"corporation":false,"usgs":false,"family":"Fridman","given":"Jonas","affiliations":[{"id":12666,"text":"Swedish University of Agricultural Sciences","active":true,"usgs":false}],"preferred":false,"id":955932,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Perakis, Steven S. 0000-0003-0703-9314 sperakis@usgs.gov","orcid":"https://orcid.org/0000-0003-0703-9314","contributorId":145528,"corporation":false,"usgs":true,"family":"Perakis","given":"Steven","email":"sperakis@usgs.gov","middleInitial":"S.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":955933,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gundale, Michael J.","contributorId":299675,"corporation":false,"usgs":false,"family":"Gundale","given":"Michael","middleInitial":"J.","affiliations":[{"id":64928,"text":"SLU","active":true,"usgs":false}],"preferred":false,"id":955934,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70274186,"text":"70274186 - 2026 - A targeted approach for mapping groundwater discharge to surface water and fish thermal refuge in four Lake Ontario tributaries","interactions":[],"lastModifiedDate":"2026-03-09T15:01:06.104632","indexId":"70274186","displayToPublicDate":"2026-02-17T15:04:37","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7176,"text":"Hydrologic Processes","active":true,"publicationSubtype":{"id":10}},"title":"A targeted approach for mapping groundwater discharge to surface water and fish thermal refuge in four Lake Ontario tributaries","docAbstract":"The duration, magnitude, and frequency of heatwaves are predicted to increase in the coming decades, a combination that can reduce the survival of many fish species. Across the world, there is broad interest in identifying thermal refuge for heat-intolerant fish species and exploring opportunities to enhance or protect these areas. Because deeper groundwater maintains a relatively constant temperature, groundwater-influenced areas along streams can provide cool-water refuge for fish during periods of extreme heat. A targeted approach was developed for identifying existing cold-water zones and areas of substantial groundwater discharge in four high priority Lake Ontario tributaries. Our approach included: (1) predicting where groundwater discharge is most likely with a simple geospatial model and (2) using model predictions to select field sites for intensive high-resolution study, including ground-based mapping of groundwater features (springs, seeps, tributaries) as well as drone-based optical and thermal infrared surveys. Results from field sites were used to both verify model performance and map different types and aerial extents of thermal anomalies. Geospatial modelling successfully predicted regions of widespread groundwater upwelling, later verified and mapped by field and drone surveys. Comparison of model and field survey results further highlighted specific geospatial layers, such as soil/bedrock types and topographic wetness index, as being particularly useful for predicting groundwater influence on streams in the study area. In addition, a comparison of geospatial model results with a model of fish abundances along the studied streams showed significant positive correlations for many heat-intolerant fish species over a wide geographic area. The approach developed in this study can be applied to other watersheds to highlight areas of probable groundwater discharge and could be used by fishery and water resource managers to support cold-water fish habitat management decision-making and resource conservation.
","language":"English","publisher":"Wiley","doi":"10.1002/hyp.70459","usgsCitation":"Woda, J., Terry, N., Kelley, D.J., Finkelstein, J., Gazoorian, C.L., and McKenna, J., 2026, A targeted approach for mapping groundwater discharge to surface water and fish thermal refuge in four Lake Ontario tributaries: Hydrologic Processes, v. 40, e70459, 16 p., https://doi.org/10.1002/hyp.70459.","productDescription":"e70459, 16 p.","ipdsId":"IP-176833","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":501102,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/hyp.70459","text":"Publisher Index Page"},{"id":500774,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"New York","otherGeospatial":"Lake Ontario","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -80.34397142741707,\n 44.03795020350384\n ],\n [\n -80.34397142741707,\n 42.83906785974037\n ],\n [\n -75.35823758327766,\n 42.83906785974037\n ],\n [\n -75.35823758327766,\n 44.03795020350384\n ],\n [\n -80.34397142741707,\n 44.03795020350384\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"40","noUsgsAuthors":false,"publicationDate":"2026-03-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Woda, Joshua 0000-0002-2932-8013","orcid":"https://orcid.org/0000-0002-2932-8013","contributorId":290172,"corporation":false,"usgs":true,"family":"Woda","given":"Joshua","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":956839,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Terry, Neil 0000-0002-3965-340X nterry@usgs.gov","orcid":"https://orcid.org/0000-0002-3965-340X","contributorId":192554,"corporation":false,"usgs":true,"family":"Terry","given":"Neil","email":"nterry@usgs.gov","affiliations":[{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":956840,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kelley, David J 0000-0002-0143-0956","orcid":"https://orcid.org/0000-0002-0143-0956","contributorId":367137,"corporation":false,"usgs":true,"family":"Kelley","given":"David","middleInitial":"J","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":956841,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Finkelstein, Jason S. 0000-0002-7496-7236","orcid":"https://orcid.org/0000-0002-7496-7236","contributorId":202452,"corporation":false,"usgs":true,"family":"Finkelstein","given":"Jason S.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":956842,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gazoorian, Christopher L. 0000-0002-5408-6212 cgazoori@usgs.gov","orcid":"https://orcid.org/0000-0002-5408-6212","contributorId":2929,"corporation":false,"usgs":true,"family":"Gazoorian","given":"Christopher","email":"cgazoori@usgs.gov","middleInitial":"L.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":956843,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McKenna, James E. Jr. 0000-0002-1428-7597 jemckenna@usgs.gov","orcid":"https://orcid.org/0000-0002-1428-7597","contributorId":190798,"corporation":false,"usgs":true,"family":"McKenna","given":"James E.","suffix":"Jr.","email":"jemckenna@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":956844,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70273863,"text":"ofr20261062 - 2026 - Preliminary bedrock geologic map of the Port Henry quadrangle, Essex County, New York, and Addison County, Vermont","interactions":[],"lastModifiedDate":"2026-02-20T18:15:51.013573","indexId":"ofr20261062","displayToPublicDate":"2026-02-17T13:05:00","publicationYear":"2026","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2026-1062","displayTitle":"Preliminary Bedrock Geologic Map of the Port Henry Quadrangle, Essex County, New York, and Addison County, Vermont","title":"Preliminary bedrock geologic map of the Port Henry quadrangle, Essex County, New York, and Addison County, Vermont","docAbstract":"The bedrock geology of the 7.5-minute Port Henry quadrangle consists of deformed and metamorphosed Mesoproterozoic gneisses of the Adirondack Highlands unconformably overlain by weakly deformed lower Paleozoic sedimentary rocks of the Champlain Valley. The Mesoproterozoic rocks occur on the eastern edge of the Adirondack Highlands and represent an extension of the Grenville Province of Laurentia. Mesoproterozoic paragneiss, marble, and amphibolite hosted the emplacement of an anorthosite-mangerite-charnockite-granite (AMCG) suite, now exposed mostly as orthogneiss, at approximately 1.18–1.15 Ga (giga-annum). In the Port Henry quadrangle, the AMCG metaigneous rocks (Yhg, Ygb, Yanw) intruded older, mostly metasedimentary rocks of the Grenville Complex during the middle to late Shawinigan orogeny (~1,160–1,150 Ma [mega-annum]). All rocks were subsequently metamorphosed to upper amphibolite to granulite facies conditions during the 1,080–1,050 Ma Ottawan orogeny. New mapping reveals four periods of deformation: (1) D1 produced rarely preserved isoclinal folds in the paragneiss and marble and predates AMCG magmatism. (2) Subsequent D2 deformation produced the dominant gneissic fabric preserved in the rock, recumbent folding, and deformed all the Proterozoic units in the map area. Syn- to late-D2 felsic magmatism resulted in the regionally extensive Lyon Mountain Granite Gneiss, which hosts numerous magnetite ore bodies. (3) Mylonitic extensional shear zones and core complex formation marked the beginning of D3 deformation. Protracted D3 deformation resulted in F3 upright folding, dome and basin formation, pegmatite intrusion, reactivation of the S2 foliation, partial melting, metamorphism, metasomatism, iron-ore remobilization, and intrusion of magnetite-bearing pegmatite both as layer-parallel sills and crosscutting dikes. (4) D4 created northeast- and northwest-trending local high-grade ductile shear zones and boudinage, northwest-trending regional kilometer (km)-wide ductile shear zones, and crosscutting granitic pegmatite dikes. The development of the late-stage regional shear zones (D4) was likely due to the continuation of extensional doming and uplift from upper amphibolite facies conditions at the end of the Ottawan orogeny. The majority of iron-ore deposits in the Port Henry and adjacent Witherbee quadrangles are in the hanging wall of these extensional shear zones. In the Port Henry quadrangle, the km-wide Cheney Mountain shear zone is the result of D4 deformation. Kilometer-scale lineaments readily observed in lidar data are Ediacaran mafic dikes and Phanerozoic brittle faults. The Paleozoic rocks are part of the Early Cambrian to Late Ordovician carbonate bank on the ancient margin of Laurentia. The approximately 1-km-thick Cambrian to Ordovician stratigraphy records a transition from synrift clastics to passive-margin peritidal carbonate buildups to gradually deeper-water subtidal- to shelf-carbonates during foreland basin development associated with the Taconic orogeny. The Paleozoic rocks are weakly folded and block faulted. Large areas of the Champlain Valley are covered by undifferentiated glacial deposits, some of which contain mapped landslides. The map also shows waste rock piles and tailings from historical mining operations.
This study was undertaken to improve our understanding of the bedrock geology in the Adirondack Highlands, establish a modern framework for 1:24,000-scale bedrock geologic mapping in the Adirondacks, provide a context for historical iron mines in the eastern Adirondacks, and update the stratigraphy of the Champlain Valley in New York and Vermont. This Open-File Report includes a bedrock geologic map; a description of map units; a correlation of map units; and a geographic information system database that includes bedrock geologic units, faults, outcrops, and structural geologic information.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20261062","collaboration":"Prepared in cooperation with the State of Vermont, Vermont Agency of Natural Resources, Vermont Geological Survey and the State of New York, Department of Education, New York Geological Survey","programNote":"National Cooperative Geologic Mapping Program","usgsCitation":"Valley, P.M., Parker, M., Walsh, G.J., Orndorff, R.C., Walton, M.S., Jr., and Crider, E.A., Jr., 2026, Preliminary bedrock geologic map of the Port Henry quadrangle, Essex County, New York, and Addison County, Vermont: U.S. Geological Survey Open-File Report 2026–1062, 1 sheet, scale 1:24,000, https://doi.org/10.3133/ofr20261062.","productDescription":"1 Sheet: 63.17 x 30.58 inches; Data Release","numberOfPages":"1","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-158945","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":500360,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_119212.htm","linkFileType":{"id":5,"text":"html"}},{"id":499704,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13HYFPM","text":"USGS data release","linkHelpText":"Database for the preliminary bedrock geologic map of the Port Henry quadrangle, Essex County, New York, and Addison County, Vermont"},{"id":499702,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2026/1062/coverthb4.jpg"},{"id":499703,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2026/1062/ofr20261062.pdf","text":"Sheet","size":"5.45 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2026-1062 PDF"}],"country":"United States","state":"New York, Vermont","county":"Addison County, Essex County","otherGeospatial":"Port Henry quadrangle","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -73.5,\n 44.125\n ],\n [\n -73.5,\n 44\n ],\n [\n -73.375,\n 44\n ],\n [\n -73.375,\n 44.125\n ],\n [\n -73.5,\n 44.125\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Florence Bascom Geoscience Center
U.S. Geological Survey
926A National Center
12201 Sunrise Valley Drive
Reston, VA 20192
Snow avalanches pose considerable hazards to people and infrastructure in alpine environments. Traditional avalanche monitoring relies on meteorological data and visual observations, which can be limited in scope and timeliness. Infrasound offers a promising complementary monitoring tool by detecting the low-frequency sound waves generated by avalanches. Here, we present infrasound and camera observations during a 50-day field campaign in the Hooker Valley of Aoraki/Mount Cook National Park, New Zealand. Our study detected seven avalanches with the cameras, whereas the infrasound system identified only one of these events, which was the largest and occurred under conditions that likely favoured infrasound propagation. The infrasound system recorded numerous other events not captured by the cameras, indicating the benefit of further investigation to determine their sources. These findings highlight the potential of infrasound technology for detecting avalanches and providing broad spatial coverage, capturing events in areas not monitored by cameras, while also showcasing limitations in infrasound capabilities. The limited detection of smaller avalanches underscores the opportunity for further research to enhance detection capabilities and understand environmental influences such as snow cover and wind noise. Overall, this study emphasises the utility of multidisciplinary monitoring techniques to improve avalanche detection in alpine environments.
","language":"English","publisher":"Wiley","doi":"10.1002/jgo2.70015","usgsCitation":"Watson, L., Miller, A., Anderson, J., Toney, L., Ardid, A., 2026, Detecting snow avalanche activity using infrasound: Hooker Valley, New Zealand: New Zealand Journal of Geology and Geophysics, v. 69, no. 1, e70015, 16 p., https://doi.org/10.1002/jgo2.70015.","productDescription":"e70015, 16 p.","ipdsId":"IP-175825","costCenters":[{"id":78941,"text":"Geologic Hazards Science Center - Landslides / Earthquake Geology","active":true,"usgs":true}],"links":[{"id":500586,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jgo2.70015","text":"Publisher Index Page"},{"id":500419,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"New Zealand","city":"Hooker Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 170.26486817242153,\n -43.599726450780764\n ],\n [\n 170.1412259579667,\n -43.599726450780764\n ],\n [\n 170.1412259579667,\n -43.721673594304434\n ],\n [\n 170.26486817242153,\n -43.721673594304434\n ],\n [\n 170.26486817242153,\n -43.599726450780764\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"69","issue":"1","noUsgsAuthors":false,"publicationDate":"2026-02-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Watson, Leighton 0000-0003-1127-3613","orcid":"https://orcid.org/0000-0003-1127-3613","contributorId":366966,"corporation":false,"usgs":false,"family":"Watson","given":"Leighton","affiliations":[{"id":87515,"text":"University of Canterbury, Christchurch, New Zealand","active":true,"usgs":false}],"preferred":false,"id":956439,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Miller, Aubrey","contributorId":355134,"corporation":false,"usgs":false,"family":"Miller","given":"Aubrey","affiliations":[{"id":7092,"text":"Florida State University","active":true,"usgs":false}],"preferred":false,"id":956440,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anderson, Jacob F. 0000-0001-6447-6778","orcid":"https://orcid.org/0000-0001-6447-6778","contributorId":268017,"corporation":false,"usgs":false,"family":"Anderson","given":"Jacob F.","affiliations":[{"id":16201,"text":"Boise State University","active":true,"usgs":false}],"preferred":false,"id":956441,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Toney, Liam 0000-0003-0167-9433","orcid":"https://orcid.org/0000-0003-0167-9433","contributorId":257264,"corporation":false,"usgs":true,"family":"Toney","given":"Liam","email":"","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":956442,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ardid, Alberto 0000-0001-8040-8193","orcid":"https://orcid.org/0000-0001-8040-8193","contributorId":366967,"corporation":false,"usgs":false,"family":"Ardid","given":"Alberto","affiliations":[{"id":87515,"text":"University of Canterbury, Christchurch, New Zealand","active":true,"usgs":false}],"preferred":false,"id":956443,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70273931,"text":"70273931 - 2026 - Genomics reveals extensive population structure and undescribed phylogenetic relationships in the Cascade torrent salamander (Rhyacotriton cascadae)","interactions":[],"lastModifiedDate":"2026-02-18T15:39:30.672299","indexId":"70273931","displayToPublicDate":"2026-02-17T09:31:36","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2193,"text":"Journal of Biogeography","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Genomics reveals extensive population structure and undescribed phylogenetic relationships in the Cascade torrent salamander (Rhyacotriton cascadae)","title":"Genomics reveals extensive population structure and undescribed phylogenetic relationships in the Cascade torrent salamander (Rhyacotriton cascadae)","docAbstract":"Aims of the study are to examine patterns of range-wide genetic differentiation and population structure in a headwater obligate salamander living in a geologically rich region, to identify genetically distinct populations and areas of gene flow between them.
Oregon and Washington in the Pacific Northwest, United States of America.
Tissue samples were collected in 2022 and 2023.
The Cascade torrent salamander Rhyacotriton cascadae.
Utilisation of a genome-wide single nucleotide polymorphism (SNP) dataset from across the species range to conduct a principal components analysis (PCA), Bayesian model of population structure, co-ancestry matrix, phylogenetic tree and estimate genetic diversity.
There are extensive levels of population structure within R. cascadae, including a previously unknown and highly differentiated clade. Structure is characterised by an island-like pattern wherein the species is comprised of six populations that function as independent demographic units, with gene flow largely constrained within populations.
Our findings reveal cryptic population structure within R. cascadae, identifying six distinct populations across the range. The northernmost population in the northwest of the species range in Washington is surprisingly highly divergent from the other five populations, and the divergence was not previously known to science. While major rivers act as phylogeographic boundaries between some populations, these boundaries appear to not always be complete.
","language":"English","publisher":"Wiley","doi":"10.1111/jbi.70167","collaboration":"Co-authors: Oregon State University, USFS","usgsCitation":"Cousins, C.D., Olson, D.H., Millward, L.S., Adams, M.J., Pearl, C., Rowe, J., and Garcia, T.S., 2026, Genomics reveals extensive population structure and undescribed phylogenetic relationships in the Cascade torrent salamander (Rhyacotriton cascadae): Journal of Biogeography, v. 53, no. 2, e70167, 15 p., https://doi.org/10.1111/jbi.70167.","productDescription":"e70167, 15 p.","ipdsId":"IP-182783","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":500142,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon, Washington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -123,\n 47.03638131106257\n ],\n [\n -123,\n 43.52402382935975\n ],\n [\n -121.5,\n 43.52402382935975\n ],\n [\n -121.5,\n 47.03638131106257\n ],\n [\n -123,\n 47.03638131106257\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"53","issue":"2","noUsgsAuthors":false,"publicationDate":"2026-02-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Cousins, Christopher D","contributorId":366385,"corporation":false,"usgs":false,"family":"Cousins","given":"Christopher","middleInitial":"D","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":955799,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Olson, Deanna H","contributorId":366386,"corporation":false,"usgs":false,"family":"Olson","given":"Deanna","middleInitial":"H","affiliations":[{"id":7134,"text":"USFS","active":true,"usgs":false}],"preferred":false,"id":955800,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Millward, Lindsay S","contributorId":366387,"corporation":false,"usgs":false,"family":"Millward","given":"Lindsay","middleInitial":"S","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":955801,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Adams, Michael J. 0000-0001-8844-042X","orcid":"https://orcid.org/0000-0001-8844-042X","contributorId":211916,"corporation":false,"usgs":true,"family":"Adams","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":955802,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pearl, Christopher 0000-0003-2943-7321 christopher_pearl@usgs.gov","orcid":"https://orcid.org/0000-0003-2943-7321","contributorId":172669,"corporation":false,"usgs":true,"family":"Pearl","given":"Christopher","email":"christopher_pearl@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":955803,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rowe, Jennifer 0000-0002-5253-2223 jrowe@usgs.gov","orcid":"https://orcid.org/0000-0002-5253-2223","contributorId":172670,"corporation":false,"usgs":true,"family":"Rowe","given":"Jennifer","email":"jrowe@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":955804,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Garcia, Tiffany S","contributorId":366394,"corporation":false,"usgs":false,"family":"Garcia","given":"Tiffany","middleInitial":"S","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":955805,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70273939,"text":"70273939 - 2026 - Characterizing operational signatures of reservoirs with the SWOT satellite by comparing natural lake and reservoir dynamics","interactions":[],"lastModifiedDate":"2026-02-18T15:12:53.887851","indexId":"70273939","displayToPublicDate":"2026-02-17T07:57:49","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1562,"text":"Environmental Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Characterizing operational signatures of reservoirs with the SWOT satellite by comparing natural lake and reservoir dynamics","docAbstract":"Due to a lack of management operations data, hydrological models may represent reservoirs as natural lakes, leading to poor discharge predictions in regulated basins. To parse seasonal operational signatures, we compare the dynamics of natural lake and reservoir systems across North America using Surface Water and Ocean Topography (SWOT) satellite observations and derived discharge estimates. Overall, reservoirs and their adjacent river reaches exhibit significantly greater variability (in standard deviation) than their natural counterparts across almost all SWOT observed (e.g. water surface elevation) and inferred (e.g. discharge) variables. Natural lakes show strong same-day correlations between inflow and outflow discharge (median Spearman R = 0.8), whereas 76% of reservoirs exhibit maximum correlation when outflow is lagged, suggesting operations buffer seasonal flow variability. Our findings indicate operations not only affect reservoir dynamics themselves but also have upstream and downstream consequences, which, when integrated into models, will offer more realistic hydrologic conditions.
","language":"English","publisher":"IOP Publishing","doi":"10.1088/1748-9326/ae436e","usgsCitation":"Riggs, R.M., Dickinson, J.E., Brinkerhoff, C.B., Sikder, M.S., Wang, J., Gao, H., and Allen, G.H., 2026, Characterizing operational signatures of reservoirs with the SWOT satellite by comparing natural lake and reservoir dynamics: Environmental Research Letters, v. 21, 044008, 11 p., https://doi.org/10.1088/1748-9326/ae436e.","productDescription":"044008, 11 p.","ipdsId":"IP-177052","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":500251,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/1748-9326/ae436e","text":"Publisher Index Page"},{"id":500137,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"North America","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -165.20917200792005,\n 72.32481180155446\n ],\n [\n -116.99838105786625,\n 14.863773568551608\n ],\n [\n -87.70978967120412,\n 18.449041713609518\n ],\n [\n 1.251170353917047,\n 74.7933097957411\n ],\n [\n -165.20917200792005,\n 72.32481180155446\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"21","noUsgsAuthors":false,"publicationDate":"2026-02-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Riggs, Ryan Matthew 0000-0001-6834-9469","orcid":"https://orcid.org/0000-0001-6834-9469","contributorId":359717,"corporation":false,"usgs":true,"family":"Riggs","given":"Ryan","middleInitial":"Matthew","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":955826,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dickinson, Jesse E. 0000-0002-0048-0839 jdickins@usgs.gov","orcid":"https://orcid.org/0000-0002-0048-0839","contributorId":152545,"corporation":false,"usgs":true,"family":"Dickinson","given":"Jesse","email":"jdickins@usgs.gov","middleInitial":"E.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":955827,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brinkerhoff, Craig B. 0000-0001-6701-4835","orcid":"https://orcid.org/0000-0001-6701-4835","contributorId":345546,"corporation":false,"usgs":false,"family":"Brinkerhoff","given":"Craig","middleInitial":"B.","affiliations":[{"id":37550,"text":"Yale University","active":true,"usgs":false}],"preferred":false,"id":955828,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sikder, Md. Safat 0000-0002-1910-1800","orcid":"https://orcid.org/0000-0002-1910-1800","contributorId":359718,"corporation":false,"usgs":false,"family":"Sikder","given":"Md.","middleInitial":"Safat","affiliations":[{"id":85904,"text":"Department of Geography and Geographic Information Science, University of Illinois Urbana-Champaign","active":true,"usgs":false}],"preferred":false,"id":955829,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wang, Jida","contributorId":333531,"corporation":false,"usgs":false,"family":"Wang","given":"Jida","email":"","affiliations":[{"id":79917,"text":"Department of Geography and Geospatial Sciences, Kansas State University, Manhattan, KS, USA.","active":true,"usgs":false}],"preferred":false,"id":955830,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gao, Huilin 0000-0001-7009-8005","orcid":"https://orcid.org/0000-0001-7009-8005","contributorId":359721,"corporation":false,"usgs":false,"family":"Gao","given":"Huilin","affiliations":[{"id":51860,"text":"Department of Civil Engineering, Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":955831,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Allen, George H. 0000-0001-8301-5301","orcid":"https://orcid.org/0000-0001-8301-5301","contributorId":225161,"corporation":false,"usgs":false,"family":"Allen","given":"George","middleInitial":"H.","affiliations":[{"id":41057,"text":"Department of Geography, Texas A&M University, College Station, TX, 77843","active":true,"usgs":false}],"preferred":false,"id":955832,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70274640,"text":"70274640 - 2026 - Environment, taxonomy, and socioeconomics predict non-imperilment in freshwater fishes","interactions":[],"lastModifiedDate":"2026-04-02T18:30:01.828215","indexId":"70274640","displayToPublicDate":"2026-02-16T11:24:32","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2842,"text":"Nature Communications","active":true,"publicationSubtype":{"id":10}},"title":"Environment, taxonomy, and socioeconomics predict non-imperilment in freshwater fishes","docAbstract":"Freshwater fishes are among the most threatened taxa, yet conservation assessments remain incomplete for many species. Freshwater fishes provide essential ecosystem services such as food security, recreational opportunities, and cultural significance. Despite heavy alterations to freshwater ecosystems, the reasons for species’ sensitivity and resistance to imperilment are unclear. To address this need, we develop a machine learning framework to predict global imperilment status for 10,631 freshwater fish species using a comprehensive set of environmental, socioeconomic, and intrinsic species-level predictors. Using updated IUCN Red List data, we train and validate Random Forest classifiers to distinguish imperiled (Vulnerable, Endangered, Critically Endangered) from non-imperiled species. We examine the relative influence of 52 variables derived from 12 global sources describing extrinsic environmental and socioeconomic factors and intrinsic species-specific characteristics. Our models achieve higher accuracy for non-imperiled species (90.1%) compared to imperiled species (81.8%), reflecting the greater heterogeneity of threats and conditions driving imperilment. Across models, key predictors include habitat variables, taxonomic order, hydrological characteristics, and disturbance indicators, underscoring the interplay between ecology, geography, and human pressures. This integrative, reproducible approach demonstrates the utility of machine learning for guiding proactive conservation and provides a scalable framework for global biodiversity risk assessment.
","language":"English","publisher":"Springer Nature","doi":"10.1038/s41467-025-68154-w","usgsCitation":"Murphy, C.A., Olivos, J.A., Arismendi, I., García-Berthou, E., Johnson, S.L., and Dunham, J., 2026, Environment, taxonomy, and socioeconomics predict non-imperilment in freshwater fishes: Nature Communications, v. 17, 1661, 11 p., https://doi.org/10.1038/s41467-025-68154-w.","productDescription":"1661, 11 p.","ipdsId":"IP-170109","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":502097,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41467-025-68154-w","text":"Publisher Index Page"},{"id":502030,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"17","noUsgsAuthors":false,"publicationDate":"2026-02-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Murphy, Christina Amy 0000-0002-3467-6610","orcid":"https://orcid.org/0000-0002-3467-6610","contributorId":335232,"corporation":false,"usgs":true,"family":"Murphy","given":"Christina","email":"","middleInitial":"Amy","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":958522,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Olivos, J. Andres","contributorId":369132,"corporation":false,"usgs":false,"family":"Olivos","given":"J.","middleInitial":"Andres","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":958523,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Arismendi, Ivan","contributorId":341108,"corporation":false,"usgs":false,"family":"Arismendi","given":"Ivan","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":958524,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"García-Berthou, Emili","contributorId":6293,"corporation":false,"usgs":false,"family":"García-Berthou","given":"Emili","affiliations":[],"preferred":false,"id":958525,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Johnson, Sherri L.","contributorId":369137,"corporation":false,"usgs":false,"family":"Johnson","given":"Sherri","middleInitial":"L.","affiliations":[{"id":36493,"text":"USDA Forest Service","active":true,"usgs":false}],"preferred":false,"id":958526,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"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":958527,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70273929,"text":"70273929 - 2026 - Assessment of antibiotic resistance genes in Caribbean corals, including those treated with amoxicillin","interactions":[],"lastModifiedDate":"2026-02-18T15:41:02.87743","indexId":"70273929","displayToPublicDate":"2026-02-16T08:34:48","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1338,"text":"Coral Reefs","active":true,"publicationSubtype":{"id":10}},"title":"Assessment of antibiotic resistance genes in Caribbean corals, including those treated with amoxicillin","docAbstract":"The decimation of reefs from stony coral tissue loss disease prompted the use of a topical amoxicillin treatment to prevent coral mortality. Application of this treatment led to concerns about unintentional impacts such as potential alteration of the coral microbiome and possible spread of antibiotic resistance. We used three different methodologies—microbial RNA sequencing, 16S rRNA amplicon surveys, and microbial qPCR array—to assess these concerns and to establish a baseline of antibiotic resistance genes (ARGs) in untreated coral microbes. We conducted microbial RNA sequencing on wild Montastraea cavernosa coral mucus samples collected before and 24 h after amoxicillin application. While diverse antibiotic resistance genes (ARGs) were expressed, no differences in ARG expression were detected after amoxicillin treatment. Additionally, there were no notable changes in the microbial communities between the before and after samples. In a separate experiment, a microbial qPCR array was used to assess differences in ARGs over longer timescales using cores from wild Colpophyllia natans, comparing never-treated corals with ones treated a single time seven months prior and with those treated multiple times seven months and more prior. No clinically relevant ARGs were detected across any samples. A small number of above-detection reads (4 in the never-treated corals, 2 in the once-treated corals, and 0 in the multi-treated corals) may indicate weak amplification of similar environmental (non-anthropogenic) ARGs in the corals. Results indicate that the localized topical application of amoxicillin to prevent mortality of SCTLD-affected corals does not: (1) significantly disrupt microbiomes, (2) increase ARG expression in adjacent tissues of these species within 24 h, nor (3) increase abundance of clinically relevant ARGs over a 7 month time period.
","language":"English","publisher":"Springer Nature","doi":"10.1007/s00338-026-02832-z","usgsCitation":"Neely, K.L., Kellogg, C.A., Voelschow, J.J., Cauvin, A.R., Reed, S.A., Rubin, E., and Meyer, J.L., 2026, Assessment of antibiotic resistance genes in Caribbean corals, including those treated with amoxicillin: Coral Reefs, 14 p., https://doi.org/10.1007/s00338-026-02832-z.","productDescription":"14 p.","ipdsId":"IP-165548","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":500253,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s00338-026-02832-z","text":"Publisher Index Page"},{"id":500143,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Florida Keys National Marine Sanctuary","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -81.88542785512071,\n 25.86582460746976\n ],\n [\n -81.88542785512071,\n 24.727471962589036\n ],\n [\n -79.85775116113955,\n 24.727471962589036\n ],\n [\n -79.85775116113955,\n 25.86582460746976\n ],\n [\n -81.88542785512071,\n 25.86582460746976\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","edition":"Online First","noUsgsAuthors":false,"publicationDate":"2026-02-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Neely, Karen L.","contributorId":366376,"corporation":false,"usgs":false,"family":"Neely","given":"Karen","middleInitial":"L.","affiliations":[{"id":13165,"text":"Nova Southeastern University","active":true,"usgs":false}],"preferred":false,"id":955787,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kellogg, Christina A. 0000-0002-6492-9455 ckellogg@usgs.gov","orcid":"https://orcid.org/0000-0002-6492-9455","contributorId":391,"corporation":false,"usgs":true,"family":"Kellogg","given":"Christina","email":"ckellogg@usgs.gov","middleInitial":"A.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"preferred":true,"id":955788,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Voelschow, Julie Jenice 0000-0002-6605-9668","orcid":"https://orcid.org/0000-0002-6605-9668","contributorId":298433,"corporation":false,"usgs":true,"family":"Voelschow","given":"Julie","email":"","middleInitial":"Jenice","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":955789,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cauvin, Allison R.","contributorId":297877,"corporation":false,"usgs":false,"family":"Cauvin","given":"Allison","middleInitial":"R.","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":955790,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Reed, Sydney A.M.","contributorId":366378,"corporation":false,"usgs":false,"family":"Reed","given":"Sydney","middleInitial":"A.M.","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":955791,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rubin, Ewelina","contributorId":366380,"corporation":false,"usgs":false,"family":"Rubin","given":"Ewelina","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":955792,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Meyer, Julie L.","contributorId":366382,"corporation":false,"usgs":false,"family":"Meyer","given":"Julie","middleInitial":"L.","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":955793,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70274164,"text":"70274164 - 2026 - Breeding shorebird surveys in the Arctic National Wildlife Refuge, Alaska, suggest population declines over two decades for most species","interactions":[],"lastModifiedDate":"2026-03-03T14:41:55.420125","indexId":"70274164","displayToPublicDate":"2026-02-16T07:35:39","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9101,"text":"Ornithological Applications","printIssn":"0010-5422","active":true,"publicationSubtype":{"id":10}},"title":"Breeding shorebird surveys in the Arctic National Wildlife Refuge, Alaska, suggest population declines over two decades for most species","docAbstract":"Shorebird populations are declining globally but it generally remains unclear how those declines translate to changes at the regional scale. We conducted the first longitudinal surveys of breeding shorebirds in Alaska under the Program for Regional and International Shorebird Monitoring (PRISM), resurveying the Coastal Plain (1002 Area) of the Arctic National Wildlife Refuge (NWR) in 2019 and 2022 to compare with initial surveys conducted in 2002 and 2004. Our goals were to (1) estimate contemporary population sizes of breeding shorebirds across this 6,249 km2 area, and (2) assess population trends for the species detected in both survey periods. We estimated population sizes for 16 species, with a combined total of 135,178 (95% CI: 113,532–156,824) in 2019 and 2022—a decline of approximately 17% (90% CI: –34% to + 3%) from 2002 and 2004 when the same survey methods were used. Four species showed a statistically significant decrease (α = 0.10): Calidris alpina arcticola (Dunlin), Limnodromus scolopaceus (Long-billed Dowitcher), Phalaropus lobatus (Red-necked Phalarope), and P. fulicarius (Red Phalarope). Only C. melanotos (Pectoral Sandpiper) showed a significant increase. Overall, 5 of 10 species—and all species combined—had a > 90% probability of decline. Population changes for the polygamous species (i.e., Phalaropus sp. and C. melanotos), which show irruptive breeding and low breeding site fidelity, may reflect temporary immigration or emigration driven by annual environmental variation, rather than true population change. Nevertheless, the overall pattern of declines aligns with migration surveys outside the Arctic. These findings highlight the vulnerability of Arctic-breeding shorebirds to threats throughout their annual cycles and underscore the potential for sustained long-term monitoring in this rapidly changing region to inform effective, flyway-scale conservation strategies across the Western Hemisphere.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/ornithapp/duag022","usgsCitation":"Brown, S.C., Lyons, J., Saalfeld, S.T., Schulte, S., Latty, C.J., McGarvey, M., Kidd, L.R., Carr, K.L., and Lanctot, R.B., 2026, Breeding shorebird surveys in the Arctic National Wildlife Refuge, Alaska, suggest population declines over two decades for most species: Ornithological Applications, no. Online First, duag022, 31 p., https://doi.org/10.1093/ornithapp/duag022.","productDescription":"duag022, 31 p.","ipdsId":"IP-178597","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":500821,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/ornithapp/duag022","text":"Publisher Index Page"},{"id":500721,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Arctic National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -145.18568704946426,\n 68.80988789172946\n ],\n [\n -145.18568704946426,\n 68.30992788035755\n ],\n [\n -143.2945429606439,\n 68.30992788035755\n ],\n [\n -143.2945429606439,\n 68.80988789172946\n ],\n [\n -145.18568704946426,\n 68.80988789172946\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","issue":"Online First","noUsgsAuthors":false,"publicationDate":"2026-02-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Brown, Stephen C.","contributorId":367088,"corporation":false,"usgs":false,"family":"Brown","given":"Stephen","middleInitial":"C.","affiliations":[{"id":84665,"text":"Manomet Conservation Sciences","active":true,"usgs":false}],"preferred":false,"id":956736,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lyons, James E. 0000-0002-9810-8751","orcid":"https://orcid.org/0000-0002-9810-8751","contributorId":228916,"corporation":false,"usgs":true,"family":"Lyons","given":"James E.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":956737,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Saalfeld, Sarah T.","contributorId":367089,"corporation":false,"usgs":false,"family":"Saalfeld","given":"Sarah","middleInitial":"T.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":956738,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schulte, Shiloh","contributorId":354797,"corporation":false,"usgs":false,"family":"Schulte","given":"Shiloh","affiliations":[{"id":84665,"text":"Manomet Conservation Sciences","active":true,"usgs":false}],"preferred":false,"id":956739,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Latty, Christopher J.","contributorId":367090,"corporation":false,"usgs":false,"family":"Latty","given":"Christopher","middleInitial":"J.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":956740,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McGarvey, Metta","contributorId":332828,"corporation":false,"usgs":false,"family":"McGarvey","given":"Metta","email":"","affiliations":[{"id":79653,"text":"Manomet, Inc.","active":true,"usgs":false}],"preferred":false,"id":956741,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kidd, Lindall R.","contributorId":367091,"corporation":false,"usgs":false,"family":"Kidd","given":"Lindall","middleInitial":"R.","affiliations":[{"id":79655,"text":"BirdLife Australia","active":true,"usgs":false}],"preferred":false,"id":956742,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Carr, Kirsti L.K.","contributorId":367092,"corporation":false,"usgs":false,"family":"Carr","given":"Kirsti","middleInitial":"L.K.","affiliations":[{"id":12711,"text":"UC Davis","active":true,"usgs":false}],"preferred":false,"id":956743,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Lanctot, Richard B.","contributorId":367093,"corporation":false,"usgs":false,"family":"Lanctot","given":"Richard","middleInitial":"B.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":956744,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70274127,"text":"70274127 - 2026 - Revisiting chlorophyll a thresholds for San Francisco Bay: Insights from observations of phytoplankton molecular abundance","interactions":[],"lastModifiedDate":"2026-02-26T17:04:58.420993","indexId":"70274127","displayToPublicDate":"2026-02-14T09:59:26","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1878,"text":"Harmful Algae","active":true,"publicationSubtype":{"id":10}},"title":"Revisiting chlorophyll a thresholds for San Francisco Bay: Insights from observations of phytoplankton molecular abundance","docAbstract":"Harmful Algal Blooms (HABs) are a hazard for coastal environments worldwide; identifying screening thresholds of chlorophyll-a (chl-a) associated with increased risk of HABs is a management priority. Molecular surveillance of coastal phytoplankton and bivalve biotoxins could be used to link chl-a with HAB risk, but requires an understanding of whether the HAB risks increase uniformly as chl-a rises, or whether some taxa are disproportionately favored, and if these relationships vary by season. In this study, we present a novel use of molecular abundance data to investigate the scientific bases for estuarine chl-a thresholds protective against HABs. In San Francisco Bay (SFB), California, the relationship between molecular relative abundance (as measured by 18S metabarcoding) of nine different HAB taxa, absolute quantitative polymerase chain reaction (qPCR) abundance, and mussel toxin concentrations of a subset of the taxa were investigated for thresholds as a function of increasing chl-a. Our results show most HAB taxa did not increase in absolute or relative abundance during SFB’s spring bloom interval, when chl-a levels were highest (>10 µg/L) but the assemblage was dominated by non-harmful diatoms. However, several flagellated, mixotrophic taxa did increase above their molecular baseline in fall, and the combined probability of any HAB occurring above baseline was elevated when chl-a reached ∼4.6 µg/L in the fall. This work demonstrates the promise of molecular approaches in disentangling the seasonally complex interplay between stressors and phytoplankton/HAB community responses and has the potential to provide clearer, more cost-effective monitoring and mitigation strategies for managers.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.hal.2026.103086","usgsCitation":"Killam, D., Bouma-Gregson, K., Sutula, M., Kudela, R., Hagy, J., Anderson, S., and Senn, D., 2026, Revisiting chlorophyll a thresholds for San Francisco Bay: Insights from observations of phytoplankton molecular abundance: Harmful Algae, v. 154, 103086, 16 p., https://doi.org/10.1016/j.hal.2026.103086.","productDescription":"103086, 16 p.","ipdsId":"IP-180259","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":500614,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.hal.2026.103086","text":"Publisher Index Page"},{"id":500555,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.71825250199157,\n 38.24752479202505\n ],\n [\n -122.71825250199157,\n 37.383291571958864\n ],\n [\n -121.97685049909562,\n 37.383291571958864\n ],\n [\n -121.97685049909562,\n 38.24752479202505\n ],\n [\n -122.71825250199157,\n 38.24752479202505\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"154","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Killam, Daniel 0000-0001-7569-1828","orcid":"https://orcid.org/0000-0001-7569-1828","contributorId":364654,"corporation":false,"usgs":false,"family":"Killam","given":"Daniel","affiliations":[{"id":12703,"text":"San Francisco Estuary Institute","active":true,"usgs":false}],"preferred":false,"id":956609,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bouma-Gregson, Keith 0000-0002-0304-6034","orcid":"https://orcid.org/0000-0002-0304-6034","contributorId":311235,"corporation":false,"usgs":true,"family":"Bouma-Gregson","given":"Keith","email":"","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":956610,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sutula, Martha","contributorId":191008,"corporation":false,"usgs":false,"family":"Sutula","given":"Martha","email":"","affiliations":[],"preferred":false,"id":956611,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kudela, Raphael","contributorId":196461,"corporation":false,"usgs":false,"family":"Kudela","given":"Raphael","affiliations":[],"preferred":false,"id":956612,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hagy, James","contributorId":196462,"corporation":false,"usgs":false,"family":"Hagy","given":"James","affiliations":[],"preferred":false,"id":956613,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Anderson, Stephanie","contributorId":367032,"corporation":false,"usgs":false,"family":"Anderson","given":"Stephanie","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":956614,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Senn, David","contributorId":349909,"corporation":false,"usgs":false,"family":"Senn","given":"David","affiliations":[{"id":83533,"text":"San Francisco Estuary Institute, Richmond, CA, USA","active":true,"usgs":false}],"preferred":false,"id":956615,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70273914,"text":"sir20265124 - 2026 - Bathymetric and velocimetric surveys at highway bridges crossing the Missouri River near Kansas City, Missouri, August 8–9, 2023","interactions":[],"lastModifiedDate":"2026-02-23T14:47:38.348722","indexId":"sir20265124","displayToPublicDate":"2026-02-13T11:09:36","publicationYear":"2026","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2026-5124","displayTitle":"Bathymetric and Velocimetric Surveys at Highway Bridges Crossing the Missouri River near Kansas City, Missouri, August 8–9, 2023","title":"Bathymetric and velocimetric surveys at highway bridges crossing the Missouri River near Kansas City, Missouri, August 8–9, 2023","docAbstract":"Bathymetric and velocimetric data were collected by the U.S. Geological Survey, in cooperation with the Missouri Department of Transportation, near 8 bridge crossings of the Missouri River near Kansas City, Missouri, on August 8–9, 2023. A multibeam echosounder mapping system was used to obtain channel- bed elevations for river reaches that extended about 1,550 to 1,640 feet longitudinally and generally extended laterally across the active channel from bank to bank during low floodflow to nonflood conditions. These surveys provided the channel geometry and hydraulic conditions of the river at the time of the surveys and provided characteristics of scour holes, which may be useful in developing or verifying predictive guidelines or equations for computing potential scour depth. The data collected from the surveys may also be useful to the Missouri Department of Transportation as a record of low floodflow conditions in regards to the stability and integrity of the bridges with respect to bridge scour. Bathymetric data were collected around every in- channel pier. Scour holes were at most piers where bathymetry could be obtained, except for those piers on banks or surrounded by riprap. All the bridge sites in this study were surveyed and documented in previous studies.
The average difference between the bathymetric surfaces ranged from 0.07 to 4.16 feet higher in 2023 than 2019, which indicates overall deposition between the survey dates, as might be expected based purely on streamflow at the time of the survey. However, the average difference between the bathymetric surfaces ranged from 1.44 feet higher to 1.88 feet lower in 2023 than 2015, which indicates a dynamic equilibrium of scour and deposition overall between those surveys, despite the lower flow conditions in 2023. Similarly, the average difference between the bathymetric surfaces ranged from 3.18 feet higher to 5.19 feet lower in 2023 than 2011, which indicates a relative equilibrium between scour and deposition overall, albeit the trend was toward scour as might be expected because of the substantial flood event in 2011.
Riprap blankets and alignment to flow had a substantial effect on the size of the scour hole for a given pier. Piers that were partially or fully surrounded by riprap blankets had scour holes that were substantially smaller (to nonexistent) compared to piers with no rock or riprap and effectively mitigated the scour holes historically observed at these piers. Several of the structures had piers that were skewed to primary approach flow. At most of the structures, the scour hole was deeper and longer on the side of the pier with impinging flow than the leeward side, with some amount of deposition on the leeward side, as typically observed at piers skewed to approach flow.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20265124","collaboration":"Prepared in cooperation with Missouri Department of Transportation","usgsCitation":"Huizinga, R.J., and Rivers, B.C., 2026, Bathymetric and velocimetric surveys at highway bridges crossing the Missouri River near Kansas City, Missouri, August 8–9, 2023: U.S. Geological Survey Scientific Investigations Report 2026–5124, 105 p., https://doi.org/10.3133/sir20265124.","productDescription":"Report: xi, 105 p.; Data Release; Dataset; 44 Oversize Map Figures: 17 x 11 inches","numberOfPages":"122","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-173988","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":500359,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_119211.htm","linkFileType":{"id":5,"text":"html"}},{"id":500080,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20265124/full"},{"id":500083,"rank":8,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2026/5124/images/"},{"id":500082,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1XUN9A8","text":"USGS data release","linkHelpText":"Bathymetry and velocity data from surveys at highway bridges crossing the Missouri River in Kansas City, Missouri, August 8–9, 2023"},{"id":500076,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2026/5124/coverthb.jpg"},{"id":500077,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2026/5124/sir20265124.pdf","text":"Report","size":"31 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2026-5124"},{"id":500078,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2026/5124/sir20265124.XML"},{"id":500079,"rank":4,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/sir/2026/5124/downloads/","text":"Oversize figures","linkFileType":{"id":1,"text":"pdf"}},{"id":500081,"rank":6,"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"}],"country":"United States","state":"Kansas, Missouri","city":"Kansas City","otherGeospatial":"Missouri River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.667,\n 39.2\n ],\n [\n -94.23,\n 39.2\n ],\n [\n -94.23,\n 39.07\n ],\n [\n -94.667,\n 39.07\n ],\n [\n -94.667,\n 39.2\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
1400 Independence Road
Rolla, MO 65401
Hydrologic models for the Wards Brook valley near Fryeburg, Maine were developed for historical (2016 – 2021) and hypothetical future conditions (2046 – 2065 and 2080 – 2099) to understand the effects of groundwater withdrawals for bottled water and municipal use on hydrologic conditions (stream base flows and groundwater levels). Analyses showed that the simulated base flows in Wards Brook were reduced because of pumping for both municipal water supplies and for water bottling, and about half of the total pumping impact on the base flows in Wards Brook was from the bottled water extraction. Simulated flows were greater than the minimum recommended streamflow of 2,180 cubic meters per day (400 gallons per minute) throughout the historical period. Simulated groundwater levels at two of three nearby ponds (Round Pond and Davis Pond) were minimally affected by pumping conditions, and effects were primarily from the municipal well closest to the ponds.
Several estimates of future projected recharge were used to understand the potential effects of groundwater withdrawals on hydrologic conditions under multiple hypothetical climate conditions. Annual projected recharge rates in the mid- and late-21st century from two climate scenarios (stabilized greenhouse-gas emissions and high greenhouse-gas emissions) were similar to rates for 2016 – 2021. However, monthly recharge patterns for the future periods shifted toward more recharge in the winter months (December, January, and February) and less recharge in April, May, and October relative to 2016 – 2021.
The lowest mean monthly base flows from the future emission scenarios all remain larger than the minimum recommended streamflow and indicate no long-term declines in flow relative to historical conditions. However, simulated base flows during hypothetical 3-year drought scenarios declined below minimum recommended streamflow during the summer months in the stabilized- and high-emission scenarios in the mid-21st century. Although water is generally plentiful in the Wards Brook valley, reduced pumping may be needed to maintain streamflows in Wards Brook under future climate conditions similar to modeled drought scenarios.
Constructed value of information (CVoI) is an expert elicitation decision-analytic tool used to prioritize sources of uncertainty based on their potential to improve decision outcomes if resolved. Despite increased application of CVoI, the robustness of CVoI prioritization of sources of uncertainty relative to differences in expert elicitation and scoring methods has not been evaluated. We engaged a group of species experts in a decision-analytic process to elicit uncertainties, framed as alternative hypotheses, about current population declines of the American kestrel (Falco sparverius) in the United States. Participants scored 13 hypotheses across 3 CVoI criteria, which are defined as constructed scales. Rather than experts selecting a single score per criterion, we used a likelihood point method to incorporate parametric uncertainty in the scoring process, in which experts were given 100 points to distribute across possible score categories within the criterion-specific constructed scale. Experts provided scores over 2 scoring rounds, with an opportunity to review and discuss initial scores between rounds. We used a Shannon entropy calculation to quantify how evenly participants allotted their points. We used simulation to evaluate the robustness of our prioritization results relative to a scoring method in which participants selected a single score category for each criterion. Participants often spread their points across 2 adjacent scores, reflecting parametric uncertainty. For one third of the hypothesis-scoring round combinations, the prioritization results differed in approximately 50% of simulations. The highest scoring hypotheses related to how the use of artificial versus natural nest cavities affects fecundity or survival, whether winter roosting sites are a limiting factor for population growth, and whether gamebird habitat management may benefit kestrel populations. Our CVoI prioritization framework can be used to develop collaborative research that is directly relevant to a management decision and is an advance in eliciting more representative expert beliefs.
","language":"English","publisher":"Society for Conservation Biology","doi":"10.1111/cobi.70227","usgsCitation":"Davis, K.P., Eaton, M.J., Bjerre, E.R., White, H.M., Boal, C.W., Herner-Thogmartin, J.H., Robinson, O., and Lawson, A.J., 2026, Constructed value of information with iterative scoring and parametric uncertainty to identify management-relevant research priorities for a declining raptor species: Conservation Biology, https://doi.org/10.1111/cobi.70227.","ipdsId":"IP-174796","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":502172,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"edition":"Online First","noUsgsAuthors":false,"publicationDate":"2026-02-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Davis, Kristin P.","contributorId":369136,"corporation":false,"usgs":false,"family":"Davis","given":"Kristin","middleInitial":"P.","affiliations":[{"id":12628,"text":"New Mexico State University","active":true,"usgs":false}],"preferred":false,"id":958514,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Eaton, Mitchell J. 0000-0001-7324-6333","orcid":"https://orcid.org/0000-0001-7324-6333","contributorId":213526,"corporation":false,"usgs":true,"family":"Eaton","given":"Mitchell","middleInitial":"J.","affiliations":[{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":958515,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bjerre, Emily R.","contributorId":369138,"corporation":false,"usgs":false,"family":"Bjerre","given":"Emily","middleInitial":"R.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":958516,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"White, Hillary M.","contributorId":369139,"corporation":false,"usgs":false,"family":"White","given":"Hillary","middleInitial":"M.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":958517,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Boal, Clint W. 0000-0001-6008-8911 cboal@usgs.gov","orcid":"https://orcid.org/0000-0001-6008-8911","contributorId":1909,"corporation":false,"usgs":true,"family":"Boal","given":"Clint","email":"cboal@usgs.gov","middleInitial":"W.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":958518,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Herner-Thogmartin, Jennifer H.","contributorId":369140,"corporation":false,"usgs":false,"family":"Herner-Thogmartin","given":"Jennifer","middleInitial":"H.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":958519,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Robinson, Orin J.","contributorId":288389,"corporation":false,"usgs":false,"family":"Robinson","given":"Orin J.","affiliations":[{"id":36682,"text":"Cornell Lab of Ornithology","active":true,"usgs":false}],"preferred":false,"id":958684,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lawson, Abigail Jean 0000-0002-2799-8750","orcid":"https://orcid.org/0000-0002-2799-8750","contributorId":276319,"corporation":false,"usgs":true,"family":"Lawson","given":"Abigail","email":"","middleInitial":"Jean","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":958521,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70274036,"text":"70274036 - 2026 - Habitat-based predictions of bridle shiner (Notropis bifrenatus) in the northeastern U.S.","interactions":[],"lastModifiedDate":"2026-02-23T18:10:39.262997","indexId":"70274036","displayToPublicDate":"2026-02-12T11:03:31","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Habitat-based predictions of bridle shiner (Notropis bifrenatus) in the northeastern U.S.","docAbstract":"We sought to assess bridle shiner (Notropis bifrenatus) habitat associations at local and regional scales across southern Maine and New Hampshire. We used local habitat data at 95 Maine sites to predict occupancy with classification and regression trees (CART). We then used ensemble species distribution models (SDMs) to model the historical (1898–2008) and current (2009–2022) ranges of the species. We used the BIOMOD platform to model the association between 35 environmental variables and bridle shiner presence during both time periods and at fine (pseudo-HUC14) and coarse (HUC12) spatial scales. We then calculated the change in predicted occupied drainages to estimate the change in the species' distribution at both scales. Within a site, bridle shiners were associated with submerged aquatic vegetation, organic substrate, and watermilfoil (Myriophyllum spp.). SDMs revealed an association with Appalachian (Hemlock-)Northern Hardwood Forest, sand substrate, and low-elevation terrain (at both spatial scales). Ensemble fine-scale SDMs suggest a substantial loss of historical bridle shiner habitat in both Maine (36% of drainages) and New Hampshire (16%), with comparable described losses (of 21% and 14%) at a coarse scale. Our local and regional models may be used to focus surveys on areas with high predicted habitat suitability or to inform habitat restoration efforts.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.72413","usgsCitation":"Katz, L.S., Coghlan, S.M., Carpenter, M.A., Kinnison, M.T., Zydlewski, J.D., 2026, Habitat-based predictions of bridle shiner (Notropis bifrenatus) in the northeastern U.S.: Ecology and Evolution, v. 16, no. 1, e72413, 19 p., https://doi.org/10.1002/ece3.72413.","productDescription":"e72413, 19 p.","ipdsId":"IP-158442","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":500597,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.72413","text":"Publisher Index Page"},{"id":500439,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maine, New Hampshire","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -69.25429976691849,\n 47.475434309112075\n ],\n [\n -71.47637622335257,\n 45.210844648573726\n ],\n [\n -72.2134392335759,\n 43.872712909182994\n ],\n [\n -72.54074189044374,\n 42.739662976646855\n ],\n [\n -71.15118191830072,\n 42.68091951244142\n ],\n [\n -69.70815322174685,\n 43.6220110458515\n ],\n [\n -66.83114905877525,\n 44.72524582330068\n ],\n [\n -67.67285260858687,\n 45.844248966240016\n ],\n [\n -67.78415740622219,\n 47.198837764366964\n ],\n [\n -68.11347172586534,\n 47.38520895041782\n ],\n [\n -69.25429976691849,\n 47.475434309112075\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"16","issue":"1","noUsgsAuthors":false,"publicationDate":"2026-01-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Katz, Lara S.","contributorId":366795,"corporation":false,"usgs":false,"family":"Katz","given":"Lara","middleInitial":"S.","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":956239,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coghlan, Stephen M. Jr.","contributorId":366796,"corporation":false,"usgs":false,"family":"Coghlan","given":"Stephen","suffix":"Jr.","middleInitial":"M.","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":956240,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Carpenter, Matthew A.","contributorId":366797,"corporation":false,"usgs":false,"family":"Carpenter","given":"Matthew","middleInitial":"A.","affiliations":[{"id":56597,"text":"New Hampshire Fish and Game Department","active":true,"usgs":false}],"preferred":false,"id":956241,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kinnison, Michael T.","contributorId":366798,"corporation":false,"usgs":false,"family":"Kinnison","given":"Michael","middleInitial":"T.","affiliations":[{"id":87507,"text":"Maine Center for Genetics in the Environment","active":true,"usgs":false}],"preferred":false,"id":956242,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zydlewski, Joseph D. 0000-0002-2255-2303 jzydlewski@usgs.gov","orcid":"https://orcid.org/0000-0002-2255-2303","contributorId":2004,"corporation":false,"usgs":true,"family":"Zydlewski","given":"Joseph","email":"jzydlewski@usgs.gov","middleInitial":"D.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":956243,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70273895,"text":"70273895 - 2026 - Inference of pattern-based geological CO2 sequestration and oil recovery potential in a commingled main pay and residual oil zone CO2-EOR flood","interactions":[],"lastModifiedDate":"2026-02-13T18:54:27.652376","indexId":"70273895","displayToPublicDate":"2026-02-12T09:51:46","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":16689,"text":"Geoenergy Science and Engineering","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Inference of pattern-based geological CO2 sequestration and oil recovery potential in a commingled main pay and residual oil zone CO2-EOR flood","title":"Inference of pattern-based geological CO2 sequestration and oil recovery potential in a commingled main pay and residual oil zone CO2-EOR flood","docAbstract":"Translocation is implemented worldwide as a conservation strategy for rare and endangered plant species, yet the factors that influence long-term success remain poorly understood. Remnant wild populations are often used as indicators to model habitat preference and select translocation sites, but such populations may be refugia from past biological or anthropogenic stressors and represent sub-optimal habitat conditions for focal taxa. To test assumptions about habitat preferences of rare species, we conducted a four-year experimental translocation of the Critically Endangered Hawaiian tree, ‘ohe mauka, Polyscias bisattenuata (Araliaceae), planting 3,700 saplings across eleven sites spanning diverse environmental conditions both within and beyond the species’ extant range. We measured seventeen predictor variables at the site and individual plant level in categories of climate, surrounding vegetation, soil chemistry, and genetic provenance. We used linear mixed effects models to assess relative effects of predictors on translocated plant survival, growth, and vigor. The factors which influenced plant performance shifted across ontogeny. The height of surrounding vegetation showed an initial negative relationship with two-year survival, but later showed a positive relationship with four-year growth. Four-year growth demonstrated a strong positive relationship with site annual mean temperature. Successful translocation sites were lower in elevation and warmer in temperature than conditions represented by remnant wild populations. Results demonstrate that basing translocation sites solely on limited extant wild occurrences can lead to suboptimal restoration practices, and experimental outplanting across broad conditions may help identify rare species' contemporary habitat preferences.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2025.111686","usgsCitation":"Douglas, J., Bai, M., Fortini, L., Yelenik, S.G., and Rønsted, N., 2026, Experimental translocation of a rare Hawaiian tree reveals disparity between remnant and potential habitat: Biological Conservation, v. 316, 111686, 14 p., https://doi.org/10.1016/j.biocon.2025.111686.","productDescription":"111686, 14 p.","ipdsId":"IP-172753","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":502101,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.biocon.2025.111686","text":"Publisher Index Page"},{"id":501926,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Kauai","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -159.43528948717787,\n 21.8600584707048\n ],\n [\n -159.31225642523046,\n 21.965179026209356\n ],\n [\n -159.27950254999953,\n 22.154674352412997\n ],\n [\n -159.3644769358584,\n 22.23581128374363\n ],\n [\n -159.5848810137864,\n 22.234993140593716\n ],\n [\n -159.77333377581635,\n 22.129242159745644\n ],\n [\n -159.80262962648277,\n 22.035753318333562\n ],\n [\n -159.7796155454661,\n 21.971740161149867\n ],\n [\n -159.6025771119729,\n 21.87649287101374\n ],\n [\n -159.43528948717787,\n 21.8600584707048\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"316","noUsgsAuthors":false,"publicationDate":"2026-02-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Douglas, Julia","contributorId":368953,"corporation":false,"usgs":false,"family":"Douglas","given":"Julia","affiliations":[{"id":40951,"text":"University of Hawai‘i - Mānoa","active":true,"usgs":false}],"preferred":false,"id":958166,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bai, Mingzhou","contributorId":368954,"corporation":false,"usgs":false,"family":"Bai","given":"Mingzhou","affiliations":[{"id":50046,"text":"Technical University of Denmark","active":true,"usgs":false}],"preferred":false,"id":958167,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fortini, Lucas Berio 0000-0002-5781-7295","orcid":"https://orcid.org/0000-0002-5781-7295","contributorId":236984,"corporation":false,"usgs":true,"family":"Fortini","given":"Lucas Berio","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":958168,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Yelenik, Stephanie G. 0000-0002-9011-0769","orcid":"https://orcid.org/0000-0002-9011-0769","contributorId":256836,"corporation":false,"usgs":false,"family":"Yelenik","given":"Stephanie","email":"","middleInitial":"G.","affiliations":[{"id":51875,"text":"formerly U.S. Geological Survey; currently Rocky Mountain Research Station, U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":958169,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rønsted, Nina","contributorId":368955,"corporation":false,"usgs":false,"family":"Rønsted","given":"Nina","affiliations":[{"id":87681,"text":"National Tropical Botanical Garden","active":true,"usgs":false}],"preferred":false,"id":958170,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70274650,"text":"70274650 - 2026 - Intraspecific contact among white-tailed deer: A literature review and chronic wasting disease case study","interactions":[],"lastModifiedDate":"2026-04-02T16:47:01.123474","indexId":"70274650","displayToPublicDate":"2026-02-12T09:38:04","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Intraspecific contact among white-tailed deer: A literature review and chronic wasting disease case study","docAbstract":"White-tailed deer (Odocoileus virginianus) are a valuable game mammal in the eastern United States necessitating detailed understanding of disease transmission. We conducted a literature review on intraspecific contact (i.e., interactions wherein disease transmission may occur) among deer. From 69 studies, we identified five themes underlying research on intraspecific deer contact: physical touch, social groups, spatial overlap, association rates, and social networks. Visual observations determined physical touch to be infrequent (< 2 touches/h) and indicated deer social groups were dependent on spatial dynamics of parturition and dispersal; most females remained with matriarchal family groups while males dispersed and formed bachelor groups. Assessed using global positioning system (GPS) monitoring, spatial overlap and association rates (i.e., instances of deer in close spatial–temporal proximity) were higher in correspondence to within-group social dynamics, and between-group scores were correspondingly low. Social network analyses indicated between-group transmission may be driven by socially dominant males, often termed super-spreaders (i.e., hosts infecting disproportionately high numbers of healthy individuals). We investigated these themes via a case study of deer infected with chronic wasting disease (CWD) in southcentral Pennsylvania, United States. We assessed spatial overlap and association rates using GPS monitoring data from 180 deer. Our results supported findings in the literature, showing strong correlations among spatial overlap, association rates, and correlated movements. Further, CWD-infected deer exhibited similar association rates to deer in which CWD was not detected. Our literature review and case study indicate direct transmission of CWD and other diseases is likely greatest within social groups following seasonal behavioral dynamics and that between-group transmission is likely driven by males via dispersal and mating interactions. Our results may be used to inform population management models with future work focused on high resolution spatial assessments of transmission in localized areas.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.73040","usgsCitation":"Wehr, N.H., Bondo, K.J., Rosenberry, C.S., Stainbrook, D., Wallingford, B.D., and Walter, W., 2026, Intraspecific contact among white-tailed deer: A literature review and chronic wasting disease case study: Ecology and Evolution, v. 16, no. 2, e73040, 20 p., https://doi.org/10.1002/ece3.73040.","productDescription":"e73040, 20 p.","ipdsId":"IP-182245","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":502090,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.73040","text":"Publisher Index Page"},{"id":502014,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Pennsylvania","otherGeospatial":"southcentral Pennsylvania","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -78.32215898198577,\n 40.430818578170204\n ],\n [\n -78.32215898198577,\n 39.73578816878745\n ],\n [\n -77.0741919959731,\n 39.73578816878745\n ],\n [\n -77.0741919959731,\n 40.430818578170204\n ],\n [\n -78.32215898198577,\n 40.430818578170204\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"16","issue":"2","noUsgsAuthors":false,"publicationDate":"2026-02-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Wehr, Nathaniel H.","contributorId":369169,"corporation":false,"usgs":false,"family":"Wehr","given":"Nathaniel","middleInitial":"H.","affiliations":[{"id":6738,"text":"The Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":958559,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bondo, Kristin J.","contributorId":369170,"corporation":false,"usgs":false,"family":"Bondo","given":"Kristin","middleInitial":"J.","affiliations":[{"id":6738,"text":"The Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":958560,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rosenberry, Christopher S.","contributorId":369171,"corporation":false,"usgs":false,"family":"Rosenberry","given":"Christopher","middleInitial":"S.","affiliations":[{"id":12891,"text":"Pennsylvania Game Commission","active":true,"usgs":false}],"preferred":false,"id":958561,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stainbrook, David","contributorId":272188,"corporation":false,"usgs":false,"family":"Stainbrook","given":"David","affiliations":[{"id":36985,"text":"Penn State University","active":true,"usgs":false}],"preferred":false,"id":958562,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wallingford, Bret D.","contributorId":369173,"corporation":false,"usgs":false,"family":"Wallingford","given":"Bret","middleInitial":"D.","affiliations":[{"id":12891,"text":"Pennsylvania Game Commission","active":true,"usgs":false}],"preferred":false,"id":958563,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Walter, W. David 0000-0003-3068-1073","orcid":"https://orcid.org/0000-0003-3068-1073","contributorId":219540,"corporation":false,"usgs":true,"family":"Walter","given":"W. David","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":958564,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70274182,"text":"70274182 - 2026 - Multiple-well monitoring site adjacent to the Midway- Sunset and Buena Vista Oil Fields, Kern County, California","interactions":[],"lastModifiedDate":"2026-03-05T15:22:54.30645","indexId":"70274182","displayToPublicDate":"2026-02-12T09:15:08","publicationYear":"2026","noYear":false,"publicationType":{"id":27,"text":"Preprint"},"publicationSubtype":{"id":32,"text":"Preprint"},"seriesTitle":{"id":18346,"text":"EarthArXiv","active":true,"publicationSubtype":{"id":32}},"title":"Multiple-well monitoring site adjacent to the Midway- Sunset and Buena Vista Oil Fields, Kern County, California","docAbstract":"Groundwater quality in and around oil fields in the Southern San Joaquin Valley is of interest to many California residents that rely heavily on groundwater for domestic, commercial, and agricultural use. To help assess the effects of historical oil-field activities and natural geologic sources on groundwater near the southwest margins of the Kern County Groundwater Subbasin, a multiple-well monitoring site was installed near the administrative boundary between the Midway-Sunset and Buena Vista Oil Fields in Kern County, California. The installation of the Midway-Sunset Buena Vista multiple-well monitoring site (MSBV) supports regional analysis of the relations of oil and gas sources to groundwater quality by providing information about the geology, hydrology, geophysical properties, and water quality of the alluvial and upper Tulare aquifers in areas where groundwater data were limited. Data collected from the site included drill cuttings, whole core samples, sidewall core samples, mud-gas analysis, borehole geophysical logs, depth to water measurements, and water quality samples. Whole cores were scanned using dual energy computed tomography. Subsamples of selected cores were analyzed for density, porosity, specific retention, and bulk minerology. Thin sections of the subsamples were prepared, photographed, and examined. Two samples were analyzed using scanning electron microscope technology to examine the microporosity of diatomite laden sediment. Instrumentation installed in the wells collect hourly depth to water measurements.
Analysis of the data show there is 355 feet of alluvium overlying the Tulare Formation at the well site. The contact between the two formations is an aquitard resulting in a perched aquifer in the alluvium and unconfined aquifer in the Tulare Formation. The alluvium is more heterogenous and finer grained than the Tulare Formation resulting in markedly higher porosity in the alluvium compared to the Tulare Formation. Higher specific retention observed in the alluvium is attributed to the finer grained sediment and greater abundance of reworked diatomite (as represented by opal-CT [cristobalite-tridymite]) compared to the Tulare Formation. Total dissolved solids (TDS) approached or exceeded 10,000 milligrams per liter (mg/L) in the alluvium from approximately 176 to 242 feet below land surface and at the top of the Amnicola clay at approximately 670 feet below land surface within the Tulare Formation. Elevated TDS, chloride, and boron concentrations in the alluvium and on top of the Amnicola clay likely reflect groundwater that is mixed with oil-field water. Water chemistry and modern-aged groundwater in the alluvial monitoring well (MSBV #3) are consistent with the oil-field water in the alluvium being derived from documented historical surface disposal of oil-field water upslope (northwest) of the site. Water chemistry and pre-modern groundwater age in the deeper Tulare monitoring well (MSBV #1) on top of the Amnicola clay are consistent with oil-field fluids derived from upslope natural geologic sources or old oil wells that leak in the subsurface. Shallow groundwater in the Tulare (MSBV #2) is not affected by mixing with oil-field sources.