Water users in Elbert County, Colorado, rely on groundwater from bedrock aquifers in the Denver Basin aquifer system (upper Dawson, lower Dawson, Denver, Arapahoe, and Laramie-Fox Hills aquifers) for approximately half of their water uses. Withdrawals from the bedrocks aquifers have increased to meet the water use needs of expanding regional population growth and development. The U.S. Geological Survey, in cooperation with the Elbert County Board of County Commissioners, began a study in 2015 to monitor groundwater levels within Elbert County. The primary purpose of this report is to present a summary of groundwater levels measured during the study period (2015–23) and present results from statistical analyses of changes in groundwater-level elevations through time.
Discrete groundwater levels were measured at 36 wells within Elbert County. Seven of those wells contained equipment to make and record continuous groundwater-level measurements at hourly intervals. All aquifers, except the lower Dawson aquifer, had only declining groundwater-level elevations in discrete measurements for wells with statistically significant trends. Of the eight statistically significant trends in the lower Dawson aquifer, two wells indicated increasing groundwater-level elevation from discrete measurements. The groundwater-level elevation trend medians in the upper Dawson, lower Dawson, Denver, Arapahoe, and Laramie-Fox Hills aquifers were −0.23, −0.66, −0.64, −0.39, and −0.63 feet per year, respectively, for discrete groundwater-level elevation measurements. Trends in continuous groundwater-level elevations were in agreement with statistically significant trends in discrete groundwater-level elevations for all wells. The groundwater-level elevation trend medians in this study, compared to the overall trends in a 2015−2018 study, both indicated declining groundwater-level elevations except in the upper Dawson aquifer, where the trend direction was opposite, a positive trend from 2015 to 2018 and a negative trend (declining groundwater elevations) from 2015 to 2023. The change in trends within the upper Dawson aquifer may be affected by differences in the study period and the trend analysis applied. Trends during the 2015–23 study period were compared to departures from the median 2015 groundwater-level elevation for each site in each aquifer. In general, the departures from the 2015 median supported trends observed at each site and correlated spatially with greater departures near the western border of Elbert County. Additionally, 30-year precipitation data showing wet and dry periods were overlaid with the departure from the 2015 median to assess groundwater-level patterns in wells in the five aquifers. Departures from the 2015 median groundwater-level elevations appeared greatest during the dry period between 2020 and 2023. Potentiometric-surface maps of the upper and lower Dawson aquifers created from static April 2023 groundwater elevations indicated groundwater-flow direction is generally from the south to the north. Results of this study could be used to guide additional groundwater monitoring in Elbert County and could aid in long-term planning of water resources.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/sir20265115","collaboration":"Prepared in cooperation with the Elbert County Board of County Commissioners","usgsCitation":"Palko, K.M., Russell, C.A., and Pieseski, N.J., 2026, Groundwater-level elevations in the bedrock aquifers of the Denver Basin aquifer system, Elbert County, Colorado, 2015–23: U.S. Geological Survey Scientific Investigations Report 2026–5115, 41 p., https://doi.org/10.3133/sir20265115.","productDescription":"Report: vii, 41 p.; Database","onlineOnly":"Y","ipdsId":"IP-162981","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":499285,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2026/5115/sir20265115.xml"},{"id":499284,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2026/5115/images"},{"id":499210,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2026/5115/coverthb.jpg"},{"id":499211,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2026/5115/sir20265115.pdf","text":"Report","size":"13.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2026-5115"},{"id":499212,"rank":3,"type":{"id":9,"text":"Database"},"url":"https://doi.org/10.5066/F7P55KJN","linkHelpText":"USGS Water Data for the Nation: U.S. Geological Survey National Water Information System database"},{"id":499446,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20265115/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2026-5115"},{"id":499601,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_119172.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Colorado","county":"Elbert County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-103.7126,39.5649],[-103.713,39.4761],[-103.7135,39.3876],[-103.7138,39.3011],[-103.7136,39.2136],[-103.7145,39.1265],[-103.7211,39.1266],[-103.722,39.0401],[-103.7201,38.9503],[-103.7186,38.8655],[-103.8315,38.867],[-103.9414,38.8666],[-104.0549,38.8666],[-104.0544,38.9528],[-104.0538,39.0407],[-104.0521,39.1264],[-104.166,39.1277],[-104.2733,39.1278],[-104.3854,39.1284],[-104.4958,39.1298],[-104.6072,39.1307],[-104.6642,39.1308],[-104.6638,39.2165],[-104.664,39.3026],[-104.663,39.3892],[-104.6626,39.4762],[-104.6627,39.5665],[-104.6054,39.5663],[-104.5374,39.5655],[-104.4927,39.5636],[-104.4891,39.5636],[-104.4742,39.5629],[-104.3841,39.5627],[-104.3763,39.5631],[-104.2695,39.5639],[-104.2647,39.5638],[-104.1602,39.5646],[-104.1543,39.565],[-104.0468,39.5652],[-104.0427,39.5651],[-103.9305,39.5646],[-103.9293,39.5646],[-103.8189,39.5646],[-103.8129,39.5649],[-103.7126,39.5649]]]},\"properties\":{\"name\":\"Elbert\",\"state\":\"CO\"}}]}","contact":"Director, Colorado Water Science Center
U.S. Geological Survey
Box 25046, Mail Stop 415
Denver, CO 80225
The frequent detection of pharmaceuticals and personal care products (PPCPs) in the environment raises concern for aquatic systems. Carbamazepine (CBZ), an antiepileptic drug, is among the most detected PPCP globally, with concentrations in surface water exceeding those that induce toxicity to aquatic organisms. Non-targeted transcriptomic profiling was conducted in zebrafish (Danio rerio) larvae exposed to 0, 1, 5, 10, or 50 μg/L CBZ from 2 h post fertilization (hpf) through hatching, and then sampled at 48, 72, or 144 hpf. Transcriptomic profiles were annotated and characterized with in silico bioinformatic software to assess top enriched pathways and identify targets of environmentally relevant concentrations of CBZ and anchor molecular effects to higher levels of biological organization. Based on this analysis, CBZ was predicted to impair visual perception and sensory system development. The number of eye saccades, determined with a visually mediated behavioral assay, optokinetic response, was significantly reduced in 144 hpf larvae exposed to concentrations as low as 1 μg/L CBZ. These results indicate that environmentally relevant concentrations of CBZ may target and impact processes involved in visual function in fish.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.envres.2026.123862","usgsCitation":"Magnuson, J.T., Puglis, H.J., Leet, J., Moody, A.H., Mariz, C.F., Edwards, T.M., and Pampanin, D.M., 2026, Effects of carbamazepine to visual function in early life stage fish: Environmental Research, v. 294, 123862, 8 p., https://doi.org/10.1016/j.envres.2026.123862.","productDescription":"123862, 8 p.","ipdsId":"IP-177152","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":502103,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envres.2026.123862","text":"Publisher Index Page"},{"id":501929,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"294","noUsgsAuthors":false,"publicationDate":"2026-01-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Magnuson, Jason Tyler 0000-0001-6841-8014","orcid":"https://orcid.org/0000-0001-6841-8014","contributorId":329838,"corporation":false,"usgs":true,"family":"Magnuson","given":"Jason","email":"","middleInitial":"Tyler","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":958239,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Puglis, Holly J. 0000-0002-3090-6597 hpuglis@usgs.gov","orcid":"https://orcid.org/0000-0002-3090-6597","contributorId":4686,"corporation":false,"usgs":true,"family":"Puglis","given":"Holly","email":"hpuglis@usgs.gov","middleInitial":"J.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":958240,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Leet, Jessica K.","contributorId":345949,"corporation":false,"usgs":false,"family":"Leet","given":"Jessica K.","affiliations":[{"id":78382,"text":"formerly Columbia Environmental Research Center","active":true,"usgs":false}],"preferred":false,"id":958241,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Moody, Adam H. 0000-0001-6160-7920","orcid":"https://orcid.org/0000-0001-6160-7920","contributorId":302592,"corporation":false,"usgs":true,"family":"Moody","given":"Adam","email":"","middleInitial":"H.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":958242,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mariz, Célio Freire Jr.","contributorId":369002,"corporation":false,"usgs":false,"family":"Mariz","given":"Célio","suffix":"Jr.","middleInitial":"Freire","affiliations":[{"id":87696,"text":"Cidade Universitária, Brazil","active":true,"usgs":false}],"preferred":false,"id":958243,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Edwards, Thea M. 0000-0002-6176-2872","orcid":"https://orcid.org/0000-0002-6176-2872","contributorId":241635,"corporation":false,"usgs":true,"family":"Edwards","given":"Thea","email":"","middleInitial":"M.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":958244,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pampanin, Daniela M.","contributorId":369003,"corporation":false,"usgs":false,"family":"Pampanin","given":"Daniela","middleInitial":"M.","affiliations":[{"id":79410,"text":"University of Stavanger, Norway","active":true,"usgs":false}],"preferred":false,"id":958245,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70274233,"text":"70274233 - 2026 - Harvest of long-tailed ducks from an important hunting location on Lake Michigan","interactions":[],"lastModifiedDate":"2026-03-17T19:04:12.850311","indexId":"70274233","displayToPublicDate":"2026-01-27T13:56:25","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Harvest of long-tailed ducks from an important hunting location on Lake Michigan","docAbstract":"Annual waterfowl harvest in North America is estimated through a collaborative and strategic process, with federal harvest surveys the primary method of estimation. Sea duck hunters participating in federal harvest surveys represent a small proportion of the overall waterfowl hunting population, limiting the utility of harvest estimates for sea ducks. The long-tailed duck (Clangula hyemalis) is one such species. To partially address the paucity of long-tailed duck harvest survey information, we conducted in-person hunter surveys from 1 November through 4 December 2016 at a boat launch in Two Rivers, Wisconsin, USA (Lake Michigan), an important area for long-tailed duck harvest within the state. Hunters were present on 15 of 21 survey days, and we surveyed occupants of 62 individual hunting boats on 127 occasions. Long-tailed ducks were the most common (97%) of the 1,431 sea ducks reported harvested by hunters. Hunter harvest of long-tailed ducks averaged 3.8 (95% CI = 3.4, 4.1; range = 0–6) long-tailed ducks/hunter/day. We used count models to evaluate the effects of environmental variables on hunter participation and harvest of long-tailed ducks. Wave height was the most influential predictor variable for hunter participation; an information criterion-based best model (wave height + temperature) indicated that hunter participation decreased by 91.9% (95% CI = 79.3–97.1%) for each 1-m increase in wave height. Long-tailed duck harvest was positively associated with air temperature; the relationship indicated a 9.5% (95% CI = 6.2–12.9%) increase in long-tailed duck harvest with each degree increase in temperature. Our results contribute to the understanding of waterfowl hunter participation, hunter preferences, and harvest on Lake Michigan and can inform managers as they assess regulatory frameworks for sea duck hunting.
","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.70182","usgsCitation":"Fara, L., Beatty, W.S., Gray, B.R., Kenow, K.P., and Eichholz, M.W., 2026, Harvest of long-tailed ducks from an important hunting location on Lake Michigan: Journal of Wildlife Management, v. 90, no. 3, e70182, https://doi.org/10.1002/jwmg.70182.","productDescription":"e70182","ipdsId":"IP-171382","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":501227,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","city":"Two Rivers","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -87.58814421174469,\n 44.16475294219143\n ],\n [\n -87.58814421174469,\n 44.13885420061274\n ],\n [\n -87.55382762153202,\n 44.13885420061274\n ],\n [\n -87.55382762153202,\n 44.16475294219143\n ],\n [\n -87.58814421174469,\n 44.16475294219143\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"90","issue":"3","noUsgsAuthors":false,"publicationDate":"2026-01-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Fara, Luke J.","contributorId":194768,"corporation":false,"usgs":false,"family":"Fara","given":"Luke J.","affiliations":[],"preferred":false,"id":957104,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Beatty, William S. 0000-0003-0013-3113 wbeatty@usgs.gov","orcid":"https://orcid.org/0000-0003-0013-3113","contributorId":173946,"corporation":false,"usgs":true,"family":"Beatty","given":"William","email":"wbeatty@usgs.gov","middleInitial":"S.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":957105,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gray, Brian R. 0000-0001-7682-9550 brgray@usgs.gov","orcid":"https://orcid.org/0000-0001-7682-9550","contributorId":2615,"corporation":false,"usgs":true,"family":"Gray","given":"Brian","email":"brgray@usgs.gov","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":957106,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kenow, Kevin P. 0000-0002-3062-5197 kkenow@usgs.gov","orcid":"https://orcid.org/0000-0002-3062-5197","contributorId":3339,"corporation":false,"usgs":true,"family":"Kenow","given":"Kevin","email":"kkenow@usgs.gov","middleInitial":"P.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":957107,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Eichholz, Michael W.","contributorId":171365,"corporation":false,"usgs":false,"family":"Eichholz","given":"Michael","email":"","middleInitial":"W.","affiliations":[{"id":26877,"text":"Southern Illinois University, Carbondale, IL","active":true,"usgs":false}],"preferred":false,"id":957108,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70273752,"text":"ofr20251024 - 2026 - Vegetation cover and composition in environments surrounding uranium mines in the Grand Canyon ecosystem, Northern Arizona","interactions":[],"lastModifiedDate":"2026-02-05T21:59:59.663994","indexId":"ofr20251024","displayToPublicDate":"2026-01-27T11:56:00","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":"2025-1024","displayTitle":"Vegetation Cover and Composition in Environments Surrounding Uranium Mines in the Grand Canyon Ecosystem, Northern Arizona","title":"Vegetation cover and composition in environments surrounding uranium mines in the Grand Canyon ecosystem, Northern Arizona","docAbstract":"Mining uranium from breccia-pipe deposits in the greater Grand Canyon region has occurred since the mid-1900s. However, possible ecosystem contamination with harmful levels of radionuclides may have occurred due to mining activities in the 21st century. In response, a 20-year Federal moratorium on new mining claims in the Grand Canyon watershed was initiated in 2012, to allow time to evaluate the potential effects of uranium exploration and mining on human health, wildlife, and water resources. This moratorium, nor the 2023 designation of the “Baaj Nwaavjo I’tah Kukveni–Ancestral Footprints of the Grand Canyon National Monument,” precludes operation or development of mining claims predating 2012.
Vegetation is a core ecosystem component that may be affected by uranium mining (for instance, through uptake and storage of radionuclides from the air or soil) or may act as a vector of exposure to wildlife, livestock, and humans (for instance, via their consumption of contaminated plant tissues). To provide baseline information about the plant communities associated with uranium mines in the Grand Canyon region, the U.S. Geological Survey surveyed an approximately 200-meter-wide buffer surrounding four breccia-pipe deposits, each in a unique stage of mine development, and at one reference area (a livestock water tank) that underwent ground disturbance but contains no mineral deposits. We sectioned the buffer zones into 0.65–4.52 hectare plots, within which we (1) inventoried all plant species, (2) measured percent cover of plant species, plant functional groups, and ground surface types (dark cyanobacteria, lichen, moss, bedrock, rock, embedded litter, duff, plant bases, and bare soil) using line-point intercept, and (3) measured length and frequency of gaps between perennial plant canopies using canopy gap intercept. We found that plant composition at the mines and the reference area differed from one another but were all characteristic of expected regional vegetation patterns. We provide this data summary as potential baseline information for future research and management efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20251024","collaboration":"Prepared in cooperation with the Bureau of Land Management and U.S. Forest Service","usgsCitation":"Mann, R.K., Duniway, M.C., and Hinck, J.E., 2026, Vegetation cover and composition in environments surrounding uranium mines in the Grand Canyon ecosystem, Northern Arizona: U.S. Geological Survey Open-File Report 2025–1024, 44 p., https://doi.org/10.3133/ofr20251024.","productDescription":"Report: vii, 44 p.; Data Release","numberOfPages":"44","onlineOnly":"Y","ipdsId":"IP-100773","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":499605,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_119200.htm","linkFileType":{"id":5,"text":"html"}},{"id":499095,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P912U706","text":"USGS data release","description":"Mann, R.K., and Duniway, M.C., 2020, Vegetation cover and composition data in environments surrounding uranium mines in the Grand Canyon ecosystem, USA: U.S. Geological Survey data release, https://doi.org/10.5066/P912U706","linkHelpText":"Vegetation cover and composition data in environments surrounding uranium mines in the Grand Canyon ecosystem, USA"},{"id":499094,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2025/1024/images"},{"id":499091,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2025/1024/ofr20251024.pdf","text":"Report","size":"10 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2025-1024 PDF"},{"id":499090,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2025/1024/coverthb.jpg"},{"id":499092,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20251024/full","linkFileType":{"id":5,"text":"html"},"description":"OFR 2025-1024 HTML"},{"id":499093,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2025/1024/ofr20251024.XML","linkFileType":{"id":8,"text":"xml"},"description":"OFR 2025-1024 XML"}],"country":"United States","state":"Arizona","otherGeospatial":"Grand Canyon region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -113.1667,\n 36.667\n ],\n [\n -113.1667,\n 35.667\n ],\n [\n -111.667,\n 35.667\n ],\n [\n -111.667,\n 36.667\n ],\n [\n -113.1667,\n 36.667\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Southwest Biological Science Center
U.S. Geological Survey
2255 N. Gemini Drive
Flagstaff, AZ 86001
Winter body condition is an important driver of survival, reproductive output, and overall population health in waterfowl. Diving duck species use distinct habitats, exploit unique resources, and can collectively provide an integrated index of winter habitat quality. The San Francisco Bay (SFB) is the largest estuary on the west coast of North America, serving as critical wintering habitat for diving ducks in the Pacific Flyway. To evaluate the body condition of diving ducks after multiple decades of tidal habitat restoration in SFB, we compared structurally corrected measurements (annual and decadal) of total carcass lipid among canvasback (Aythya valisineria), greater scaup (Aythya marila), lesser scaup (Aythya affinis), and ruddy duck (Oxyura jamaicensis). We found greater and lesser scaup gained lipid reserves within the estuary prior to spring migration; however, canvasback and ruddy duck lipid levels declined throughout the winter and into the spring. Lipid loss over the wintering period could indicate a reduction in foraging resource availability, dietary shifts, or metabolic changes. These deficiencies could have negative cross-seasonal implications, as these species must accumulate resources outside of their wintering areas to fuel migration and reproduction. Lipid levels were elevated in lesser scaup collected in 2017-2019 compared to 1998-2000, while we found no decadal differences in lipid levels for canvasback or greater scaup. Our findings suggest tidal restoration in SFB, among other factors, may benefit some diving duck species.
","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.70157","usgsCitation":"Hill, M.A., De La Cruz, S.E., Hall, L.A., Moskal, S.M., Takekawa, J.Y., and Eadie, J.M., 2026, Seasonal and decadal changes in winter body condition of four sympatric diving ducks: Journal of Wildlife Management, v. 90, no. 3, e70157, 18 p., https://doi.org/10.1002/jwmg.70157.","productDescription":"e70157, 18 p.","ipdsId":"IP-170624","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":500191,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":500259,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jwmg.70157","text":"Publisher Index Page"}],"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 -122.80199851025367,\n 38.22193702588538\n ],\n [\n -122.80199851025367,\n 37.4299942839268\n ],\n [\n -121.7624093609558,\n 37.4299942839268\n ],\n [\n -121.7624093609558,\n 38.22193702588538\n ],\n [\n -122.80199851025367,\n 38.22193702588538\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"90","issue":"3","noUsgsAuthors":false,"publicationDate":"2026-01-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Hill, Mason A. 0000-0001-9549-475X","orcid":"https://orcid.org/0000-0001-9549-475X","contributorId":295337,"corporation":false,"usgs":true,"family":"Hill","given":"Mason","email":"","middleInitial":"A.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":955884,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"De La Cruz, Susan E.W. 0000-0001-6315-0864","orcid":"https://orcid.org/0000-0001-6315-0864","contributorId":202774,"corporation":false,"usgs":true,"family":"De La Cruz","given":"Susan","email":"","middleInitial":"E.W.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":955885,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hall, Laurie Anne 0000-0001-5822-649X","orcid":"https://orcid.org/0000-0001-5822-649X","contributorId":243313,"corporation":false,"usgs":true,"family":"Hall","given":"Laurie","email":"","middleInitial":"Anne","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":955886,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Moskal, Stacy M. 0000-0001-7627-5316","orcid":"https://orcid.org/0000-0001-7627-5316","contributorId":342631,"corporation":false,"usgs":true,"family":"Moskal","given":"Stacy","middleInitial":"M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":955887,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Takekawa, John Y.","contributorId":366424,"corporation":false,"usgs":false,"family":"Takekawa","given":"John","middleInitial":"Y.","affiliations":[{"id":37814,"text":"Former USGS","active":true,"usgs":false}],"preferred":false,"id":955888,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Eadie, John M.","contributorId":366425,"corporation":false,"usgs":false,"family":"Eadie","given":"John","middleInitial":"M.","affiliations":[{"id":12711,"text":"UC Davis","active":true,"usgs":false}],"preferred":false,"id":955889,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70274093,"text":"70274093 - 2026 - Decadal trends and occurrence of geogenic constituents and mixtures in groundwater across the continental United States","interactions":[],"lastModifiedDate":"2026-02-25T15:55:07.891197","indexId":"70274093","displayToPublicDate":"2026-01-27T08:35:55","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":23306,"text":"Environmental Science and Technology - Water","active":true,"publicationSubtype":{"id":10}},"title":"Decadal trends and occurrence of geogenic constituents and mixtures in groundwater across the continental United States","docAbstract":"Worldwide, about 50% of the population is served by groundwater-sourced drinking water. Numerous groundwater quality assessments have found that geogenic constituents are among the most common contaminants in drinking-water aquifers. Documenting changing groundwater quality is a crucial aspect of water availability assessments. We assess trends and occurrence of geogenic constituent concentrations in groundwater across the continental United States using 3 decades of data from the U.S. Geological Survey’s National Water Quality Network. Thousands of groundwater wells were grouped into agricultural, urban, or domestic supply network types. Although most networks and constituents had no statistically significant change in concentration, many had increasing concentration trends, elevated concentrations, or both. Lithium, sodium, radium, sulfate, and uranium had increasing trends in more than 10% of the study networks. Urban and domestic well networks had increasing lithium and sodium trends more often than agricultural networks. Manganese most commonly increased in domestic well networks; uranium more commonly increased in agricultural and urban networks. Elevated concentration mixtures were widespread, and mixture complexities appeared to increase over time. Our results indicate that more than 2.3 million domestic-well users may be affected by elevated concentrations of one or more geogenic constituents.","language":"English","publisher":"American Chemical Society","doi":"10.1021/acsestwater.5c00756","usgsCitation":"Erickson, M.L., Elliott, S.M., Musgrove, M., Hinman, E., Sleckman, M.J., Stackpoole, S.M., Lindsey, B.D., 2026, Decadal trends and occurrence of geogenic constituents and mixtures in groundwater across the continental United States: Environmental Science and Technology - Water, v. 6, no. 2, p. 664-678, https://doi.org/10.1021/acsestwater.5c00756.","productDescription":"15 p.","startPage":"664","endPage":"678","ipdsId":"IP-168374","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":500624,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1021/acsestwater.5c00756","text":"Publisher Index 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merickso@usgs.gov","orcid":"https://orcid.org/0000-0002-1117-2866","contributorId":206446,"corporation":false,"usgs":true,"family":"Erickson","given":"Melinda","email":"merickso@usgs.gov","middleInitial":"L.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":956509,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Elliott, Sarah M. 0000-0002-1414-3024 selliott@usgs.gov","orcid":"https://orcid.org/0000-0002-1414-3024","contributorId":1472,"corporation":false,"usgs":true,"family":"Elliott","given":"Sarah","email":"selliott@usgs.gov","middleInitial":"M.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":956510,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Musgrove, MaryLynn 0000-0003-1607-3864","orcid":"https://orcid.org/0000-0003-1607-3864","contributorId":223710,"corporation":false,"usgs":true,"family":"Musgrove","given":"MaryLynn","email":"","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":956511,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hinman, Elise Danica 0000-0001-5396-1583","orcid":"https://orcid.org/0000-0001-5396-1583","contributorId":356291,"corporation":false,"usgs":true,"family":"Hinman","given":"Elise Danica","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":956512,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sleckman, Margaux Jeanne 0000-0002-1843-6932","orcid":"https://orcid.org/0000-0002-1843-6932","contributorId":295257,"corporation":false,"usgs":true,"family":"Sleckman","given":"Margaux","email":"","middleInitial":"Jeanne","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":956513,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stackpoole, Sarah M. 0000-0002-5876-4922","orcid":"https://orcid.org/0000-0002-5876-4922","contributorId":211238,"corporation":false,"usgs":true,"family":"Stackpoole","given":"Sarah","email":"","middleInitial":"M.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":956514,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lindsey, Bruce D. 0000-0002-7180-4319 blindsey@usgs.gov","orcid":"https://orcid.org/0000-0002-7180-4319","contributorId":206667,"corporation":false,"usgs":true,"family":"Lindsey","given":"Bruce","email":"blindsey@usgs.gov","middleInitial":"D.","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":956515,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70273696,"text":"fs20253058 - 2026 - Recent scientific contributions by the U.S. Geological Survey in the San Francisco Bay and Sacramento–San Joaquin Delta Estuary","interactions":[],"lastModifiedDate":"2026-02-05T20:36:48.843992","indexId":"fs20253058","displayToPublicDate":"2026-01-26T08:50:40","publicationYear":"2026","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-3058","displayTitle":"Recent Scientific Contributions by the U.S. Geological Survey in the San Francisco Bay and Sacramento–San Joaquin Delta Estuary","title":"Recent scientific contributions by the U.S. Geological Survey in the San Francisco Bay and Sacramento–San Joaquin Delta Estuary","docAbstract":"The San Francisco Bay and Sacramento–San Joaquin Delta Estuary (hereafter, Bay-Delta) is the largest estuary on the West Coast of the United States. The Bay- Delta covers more than 1,600 square miles and drains a watershed of more than 75,000 square miles, which is greater than 40 percent of California. The region surrounding the Bay- Delta is home to about 10 million people, and its habitats (fig. 1) support more than 800 plant and animal species. The waterways of the Bay- Delta are the central hub of California’s extensive freshwater delivery system, supplying water to more than 27 million Californians and 4 million acres of farmland in the Central Valley.
The U.S. Geological Survey (USGS) is the primary science agency of the U.S. Department of the Interior, providing a broad range of Earth, water, biological, and mapping data and expertise to inform natural resource management across the country. This fact sheet focuses on research conducted by the USGS in the Bay- Delta region, mostly within the past 5 years. The fact sheet is organized across five major themes: water flow and water quality, fish and wildlife, wetland restoration, invasive species, and hazards. In each of these areas, the USGS works closely with Federal, State, and local agencies; academia; and non- governmental organizations to provide objective, evidence-based science. The data and knowledge gained from USGS research and monitoring are publicly available and are routinely used by agencies, including the U.S. Bureau of Reclamation, U.S. Army Corps of Engineers, U.S. Fish and Wildlife Service, California Department of Water Resources, California Department of Fish and Wildlife, California State Water Resources Control Board, Delta Stewardship Council, and many additional organizations and stakeholders to inform management of the Bay- Delta region and its resources.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20253058","usgsCitation":"Drexler, J.Z., and Weltzin, J.F., 2026, Recent scientific contributions by the U.S. Geological Survey in the San Francisco Bay and Sacramento–San Joaquin Delta Estuary: U.S. Geological Survey Fact Sheet 2025–3058, 6 p., https://doi.org/10.3133/fs20253058.","productDescription":"6 p.","numberOfPages":"6","onlineOnly":"Y","ipdsId":"IP-177659","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":498957,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2025/3058/coverthb.jpg"},{"id":498952,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2025/3058/fs20253058.pdf","text":"Report","size":"14.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2025-3058 PDF"},{"id":498953,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/fs20253058/full","linkFileType":{"id":5,"text":"html"},"description":"FS 2025-3058 HTML"},{"id":498954,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2025/3058/fs20253058.XML","linkFileType":{"id":8,"text":"xml"},"description":"FS 2025-3058 XML"},{"id":499139,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_119170.htm","linkFileType":{"id":5,"text":"html"}},{"id":498955,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2025/3058/images"}],"country":"United States","state":"California","otherGeospatial":"Sacramento–San Joaquin Delta Estuary, San Francisco Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.02008172785412,\n 38.8200776149005\n ],\n [\n -122.56776314124848,\n 38.8200776149005\n ],\n [\n -122.56776314124848,\n 37.19924956798722\n ],\n [\n -121.02008172785412,\n 37.19924956798722\n ],\n [\n -121.02008172785412,\n 38.8200776149005\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
The U.S. Geological Survey (USGS) is the primary science agency of the U.S. Department of the Interior. In the San Francisco Bay and Sacramento–San Joaquin Delta Estuary (Bay-Delta) of California, the USGS plays a unique role in providing scientific leadership because of its broad research and monitoring capabilities, innovative methodologies for data collection and analysis, and dedication to objective and credible science. This fact sheet provides a summary of recent USGS projects across the Bay-Delta organized under five major research themes: water flow and water quality, fish and wildlife, wetland restoration, invasive species, and hazards. A key component of USGS research is close collaboration with State and Federal partners, academia, and non-governmental organizations to accomplish its goals. The research and partnerships described in this fact sheet are critical to the management of the complex natural resource issues across the Bay-Delta region of California.
","publicationDate":"2026-01-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Drexler, Judith Z. 0000-0002-0127-3866 jdrexler@usgs.gov","orcid":"https://orcid.org/0000-0002-0127-3866","contributorId":167492,"corporation":false,"usgs":true,"family":"Drexler","given":"Judith","email":"jdrexler@usgs.gov","middleInitial":"Z.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":954311,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Weltzin, Jake 0000-0001-8641-6645","orcid":"https://orcid.org/0000-0001-8641-6645","contributorId":365438,"corporation":false,"usgs":false,"family":"Weltzin","given":"Jake","affiliations":[{"id":87138,"text":"formerly Senior Science Advisor, EMA, USGS, now retired.","active":true,"usgs":false}],"preferred":false,"id":954312,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70273775,"text":"70273775 - 2026 - Multi-year cut-to-drown management limits Phragmites australis growth, belowground resources, and rhizome viability in Great Lakes wetlands","interactions":[],"lastModifiedDate":"2026-03-23T14:45:51.612152","indexId":"70273775","displayToPublicDate":"2026-01-26T07:49:55","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Multi-year cut-to-drown management limits Phragmites australis growth, belowground resources, and rhizome viability in Great Lakes wetlands","title":"Multi-year cut-to-drown management limits Phragmites australis growth, belowground resources, and rhizome viability in Great Lakes wetlands","docAbstract":"The distribution and abundance of Phragmites in the Great Lakes coastal zone has expanded in part due to its unique ventilation physiology and its ability to take advantage of changes in lake levels over the past several decades. During an extended period of low lake levels in the early 2000s, Phragmites expanded into vast shallow water areas as lake bottoms were exposed. Many of those populations were able to persist when lake levels rose several years later. Here, we investigate a management strategy, known as cut-to-drown, that takes advantage of elevated water levels to effectively control Phragmites by cutting stems underwater, thereby drowning the plant and depleting its stored resources. We tested the impacts of cut timing and frequency on the effectiveness of the cut-to-drown strategy through a multi-year manipulative field study. After two seasons of treatments, we found a 92–99 % reduction in stem density, depending on cut timing. Carbohydrate reserves in rhizomes declined 75–92 %, such that rhizome viability was reduced by 73–100 %, depending on cut timing. We found that cutting continuously (every 2–3 weeks) throughout two growing seasons was the most effective way to implement cut-to-drown but provide evidence that less frequent cutting could produce similar results. Our study provides important evidence to inform best management practices for cut-to-drown. Particularly as lake level fluctuations become more frequent and extreme in the future, cut-to-drown could serve as a useful tool for limiting Phragmites’ ability to persist in high water environments.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2025.102736","usgsCitation":"Bickford, W.A., Schaefer, K.A., Widin, S.L., and Kowalski, K., 2026, Multi-year cut-to-drown management limits Phragmites australis growth, belowground resources, and rhizome viability in Great Lakes wetlands: Journal of Great Lakes Research, v. 52, no. 2, 102736, 10 p., https://doi.org/10.1016/j.jglr.2025.102736.","productDescription":"102736, 10 p.","ipdsId":"IP-179652","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":499164,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":499322,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jglr.2025.102736","text":"Publisher Index Page"}],"country":"United States","state":"Michigan, Ohio","otherGeospatial":"Lake Erie, Lake Huron","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -84.09644325245834,\n 44.503344381110054\n ],\n [\n -84.09644325245834,\n 41.28305521847017\n ],\n [\n -81.75470105903604,\n 41.28305521847017\n ],\n [\n -81.75470105903604,\n 44.503344381110054\n ],\n [\n -84.09644325245834,\n 44.503344381110054\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"52","issue":"2","noUsgsAuthors":false,"publicationDate":"2026-01-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Bickford, Wesley A. 0000-0001-7612-1325 wbickford@usgs.gov","orcid":"https://orcid.org/0000-0001-7612-1325","contributorId":5687,"corporation":false,"usgs":true,"family":"Bickford","given":"Wesley","email":"wbickford@usgs.gov","middleInitial":"A.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":954747,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schaefer, Kaira A. 0000-0002-6793-6095","orcid":"https://orcid.org/0000-0002-6793-6095","contributorId":359280,"corporation":false,"usgs":false,"family":"Schaefer","given":"Kaira","middleInitial":"A.","affiliations":[{"id":37387,"text":"University of Michigan","active":true,"usgs":false}],"preferred":false,"id":954748,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Widin, Spenser L. 0000-0002-6470-4061","orcid":"https://orcid.org/0000-0002-6470-4061","contributorId":303341,"corporation":false,"usgs":true,"family":"Widin","given":"Spenser","email":"","middleInitial":"L.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":954749,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kowalski, Kurt P. 0000-0002-8424-4701 kkowalski@usgs.gov","orcid":"https://orcid.org/0000-0002-8424-4701","contributorId":3768,"corporation":false,"usgs":true,"family":"Kowalski","given":"Kurt P.","email":"kkowalski@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":954750,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70273873,"text":"70273873 - 2026 - Teach me how to pycap: A high-capacity well decision support tool using analytical solutions in Python","interactions":[],"lastModifiedDate":"2026-03-23T14:50:21.582142","indexId":"70273873","displayToPublicDate":"2026-01-25T09:06:08","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3825,"text":"Groundwater","active":true,"publicationSubtype":{"id":10}},"title":"Teach me how to pycap: A high-capacity well decision support tool using analytical solutions in Python","docAbstract":"Regulatory agencies in humid temperate environments rely on timely evaluations of streamflow depletion and drawdown to protect aquatic ecosystems and existing water users. Numerical models offer detailed insights, but their complexity and time demands often preclude their practical use in rapid decision-making. We present pycap-dss, an open-source Python package that implements a suite of analytical solutions for estimating streamflow depletion and drawdown. The tool supports superposition of multiple wells and time-varying pumping, enabling cumulative impact assessments in situations with multiple wells and streams. The software is modular and extensible, allowing users to interchange solutions or add new analytical methods. A YAML-based configuration supports batch processing of multiple wells, and an optional AnalysisProject class facilitates integration with regulatory workflows. Rigorous unit and regression testing ensures computational reliability, and continuous integration supports ongoing development. We demonstrate deterministic examples of drawdown where multiple solutions are readily compared and streamflow depletion with multiple wells in the Central Sands region of Wisconsin. We also show the value of Monte Carlo analyses of streamflow depletion in the same Central Sands example, leveraging computational efficiency to evaluate the uncertainty of individual and cumulative streamflow depletion calculations from over 200 high-capacity wells.
","language":"English","publisher":"National Groundwater Association","doi":"10.1111/gwat.70046","usgsCitation":"Fienen, M., Pruitt, A., and Reeves, H.W., 2026, Teach me how to pycap: A high-capacity well decision support tool using analytical solutions in Python: Groundwater, v. 64, no. 2, p. 223-234, https://doi.org/10.1111/gwat.70046.","productDescription":"12 p.","startPage":"223","endPage":"234","ipdsId":"IP-183720","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":499748,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":499946,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/gwat.70046","text":"Publisher Index Page"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Tomorrow River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -89.67725263192825,\n 44.6879674210181\n ],\n [\n -89.67725263192825,\n 44.15565808301017\n ],\n [\n -89.16563204911922,\n 44.15565808301017\n ],\n [\n -89.16563204911922,\n 44.6879674210181\n ],\n [\n -89.67725263192825,\n 44.6879674210181\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"64","issue":"2","noUsgsAuthors":false,"publicationDate":"2026-01-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Fienen, Michael N. 0000-0002-7756-4651","orcid":"https://orcid.org/0000-0002-7756-4651","contributorId":245632,"corporation":false,"usgs":true,"family":"Fienen","given":"Michael N.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":955343,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pruitt, Aaron","contributorId":214451,"corporation":false,"usgs":false,"family":"Pruitt","given":"Aaron","affiliations":[],"preferred":false,"id":955344,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reeves, Howard W. 0000-0001-8057-2081 hwreeves@usgs.gov","orcid":"https://orcid.org/0000-0001-8057-2081","contributorId":2307,"corporation":false,"usgs":true,"family":"Reeves","given":"Howard","email":"hwreeves@usgs.gov","middleInitial":"W.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":955345,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70273779,"text":"70273779 - 2026 - Prioritizing resource protection and understanding potential susceptibility of springs to surficial changes in a low-temperature geothermal system","interactions":[],"lastModifiedDate":"2026-01-29T14:54:24.411943","indexId":"70273779","displayToPublicDate":"2026-01-24T08:46:07","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1828,"text":"Geothermics","active":true,"publicationSubtype":{"id":10}},"title":"Prioritizing resource protection and understanding potential susceptibility of springs to surficial changes in a low-temperature geothermal system","docAbstract":"Geothermal systems are vulnerable to changes in water budget and composition, requiring science-based management. This study uses a dataset of spring water temperatures, time series of groundwater residence time tracers (tritium and carbon-14), and stable isotopes of water to understand geothermal flow in a low-temperature geothermal system in north west Colorado, United States (Steamboat Springs). The geothermal system is bisected by the Yampa River, necessitating a stream mass balance approach to quantify total discharge. Time series analysis of water temperature data provides a ranked list of features more susceptible to surficial changes, which is corroborated using time series of tritium which indicate spatially distinct patterns of mixing between modern and pre-modern groundwater. All springs contain a portion of pre-modern groundwater that is thousands to tens of thousands of years old, a period coinciding with melting of extensive Pleistocene glaciers that was likely one of the recharge sources to the geothermal system. Stream mass balance indicates that greater than 80% of the total geothermal discharge is derived from diffuse or small springs, highlighting the extensive nature of the geothermal outflow zone and the association with local geologic structures. This study provides baseline data to support management of the Steamboat Springs geothermal system and indicates the utility of these approaches in developing science-based geothermal management.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.geothermics.2026.103615","usgsCitation":"Newman, C.P., and Pepin, J.D., 2026, Prioritizing resource protection and understanding potential susceptibility of springs to surficial changes in a low-temperature geothermal system: Geothermics, v. 136, 103615, 14 p., https://doi.org/10.1016/j.geothermics.2026.103615.","productDescription":"103615, 14 p.","ipdsId":"IP-180997","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":499294,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.geothermics.2026.103615","text":"Publisher Index Page"},{"id":499224,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","city":"Steamboat Springs","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -106.87961681380281,\n 40.567\n ],\n [\n -106.87961681380281,\n 40.45\n ],\n [\n -106.68,\n 40.45\n ],\n [\n -106.68,\n 40.567\n ],\n [\n -106.87961681380281,\n 40.567\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"136","noUsgsAuthors":false,"publicationDate":"2026-01-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Newman, Connor P. 0000-0002-6978-3440","orcid":"https://orcid.org/0000-0002-6978-3440","contributorId":222596,"corporation":false,"usgs":true,"family":"Newman","given":"Connor","email":"","middleInitial":"P.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":954760,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pepin, Jeff D. 0000-0002-7410-9979","orcid":"https://orcid.org/0000-0002-7410-9979","contributorId":222161,"corporation":false,"usgs":true,"family":"Pepin","given":"Jeff","email":"","middleInitial":"D.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":954761,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70274166,"text":"70274166 - 2026 - A catalogue of Do's and Don'ts in the modeling of environmental systems","interactions":[],"lastModifiedDate":"2026-03-03T15:08:37.444188","indexId":"70274166","displayToPublicDate":"2026-01-24T08:01:33","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1551,"text":"Environmental Modelling and Software","active":true,"publicationSubtype":{"id":10}},"title":"A catalogue of Do's and Don'ts in the modeling of environmental systems","docAbstract":"Modeling plays a vital role in understanding and managing complex environmental systems, but its credibility and quality depend heavily on a comprehensive set of defensible model activities and practices, especially when the system of interest is plagued with uncertainties and conflicting stakeholder perspectives. This paper proposes a catalogue of Do's and Don'ts to guide modelers in addressing the many pertinent considerations through the whole modeling cycle. This practical tool provides advice on approaching modeling effectively through adhering to good modeling practice. It emphasizes model choices that align with the model purpose and context, and the justification and documentation of modeling decisions and assumptions. Managing uncertainty is a core consideration. The identification, assessment and reporting of these uncertainties is important across the entire modeling process, which spans problem framing, technical design, implementation and application phases. Such good practices are critical for transparency and reliability of the modeling.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.envsoft.2026.106893","usgsCitation":"Sun, X., Jakeman, A.J., Hamilton, S.H., Grimm, V., Hunt, R.J., El Sawah, S., Wang, H., Croke, B., and Chen, M., 2026, A catalogue of Do's and Don'ts in the modeling of environmental systems: Environmental Modelling and Software, v. 198, 106893, 13 p., https://doi.org/10.1016/j.envsoft.2026.106893.","productDescription":"106893, 13 p.","ipdsId":"IP-176780","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":500725,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"198","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Sun, Xifu","contributorId":367094,"corporation":false,"usgs":false,"family":"Sun","given":"Xifu","affiliations":[{"id":27305,"text":"Australia National University","active":true,"usgs":false}],"preferred":false,"id":956745,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jakeman, Anthony J. 0000-0001-5282-2215","orcid":"https://orcid.org/0000-0001-5282-2215","contributorId":173848,"corporation":false,"usgs":false,"family":"Jakeman","given":"Anthony","email":"","middleInitial":"J.","affiliations":[{"id":17939,"text":"The Australian National University","active":true,"usgs":false}],"preferred":false,"id":956746,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hamilton, Serena H","contributorId":248834,"corporation":false,"usgs":false,"family":"Hamilton","given":"Serena","email":"","middleInitial":"H","affiliations":[{"id":50035,"text":"School of Science, Edith Cowan University, Joondalup, WA, Australia","active":true,"usgs":false}],"preferred":false,"id":956772,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Grimm, Volker","contributorId":224014,"corporation":false,"usgs":false,"family":"Grimm","given":"Volker","affiliations":[{"id":26949,"text":"Helmholtz Centre for Environmental Research, Germany","active":true,"usgs":false}],"preferred":false,"id":956773,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hunt, Randall J. 0000-0001-6465-9304 rjhunt@usgs.gov","orcid":"https://orcid.org/0000-0001-6465-9304","contributorId":214444,"corporation":false,"usgs":true,"family":"Hunt","given":"Randall","email":"rjhunt@usgs.gov","middleInitial":"J.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":956748,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"El Sawah, Sondoss","contributorId":367096,"corporation":false,"usgs":false,"family":"El Sawah","given":"Sondoss","affiliations":[{"id":87548,"text":"University of New South Wales Canberra","active":true,"usgs":false}],"preferred":false,"id":956749,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wang, Hsiao-Hsuan","contributorId":349683,"corporation":false,"usgs":false,"family":"Wang","given":"Hsiao-Hsuan","affiliations":[{"id":6747,"text":"Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":956750,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Croke, Barry 0000-0001-9216-1554","orcid":"https://orcid.org/0000-0001-9216-1554","contributorId":248856,"corporation":false,"usgs":false,"family":"Croke","given":"Barry","email":"","affiliations":[{"id":27305,"text":"Australia National University","active":true,"usgs":false}],"preferred":false,"id":956747,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Chen, Min","contributorId":330043,"corporation":false,"usgs":false,"family":"Chen","given":"Min","affiliations":[{"id":78773,"text":"University of Wisconsin-Madison, Wisconsin, USA","active":true,"usgs":false}],"preferred":false,"id":956751,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70274536,"text":"70274536 - 2026 - Extreme Potomac floods at Washington D.C. during the past 500 years","interactions":[],"lastModifiedDate":"2026-03-31T15:13:33.863387","indexId":"70274536","displayToPublicDate":"2026-01-23T10:08:43","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Extreme Potomac floods at Washington D.C. during the past 500 years","docAbstract":"Washington D.C. faces one of the highest 100-year flood risks of any major city along the U.S. East Coast. In addition to storm-surge inundation during hurricanes and nor'easters, water-level observations for Washington are strongly skewed by major floods on the Potomac River. Using geologic and historic records we find new evidence for ice-jam flooding at Georgetown during the Little Ice Age, as recently as 1784, that was up to ∼2x the magnitude of the largest events of the past hundred years (1936, 1942). Over the 19th century (a) human modifications to the Potomac estuary as well as (b) increasingly heavy rainfall and (c) land-clearance in the watershed may have contributed to increasingly frequent large floods at Washington. Early surveys of the U.S. Capitol Building and other local landmarks also suggest sea level on the Potomac estuary at Washington has risen by upwards of 0.7 m (2.2 ft) since the 1790s.
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Inorganic (37), organic (435) and microbial (3) constituents were assessed in 12 surface water sites from the Pryor Creek (n = 2), Bighorn River (n = 2) and Little Bighorn River (n = 8) valleys. Twenty-six organics, 33 inorganics and Escherichia coli were detected. Despite relatively low concentrations in surface waters within the Crow Reservation, mixture toxicity indicated prevalent chronic ecological effects and human-health secondary contact (recreation) effects at multiple sites. Further, to address Tribal concerns over the prevalence and corresponding risks of per- and polyfluoroalkyl substances (PFAS), we sampled water, sediment, biofilms and fish at a limited number of locations in the Little Bighorn River. Results indicated that PFAS were prevalent in fish tissues, including whole blood and filets, and to a lesser extent in biofilms, despite few detections in water and sediment samples. This is the first attempt to document environmental PFAS contamination within the reservation and the potential human-health concerns for the general population from consumption of recreational/subsistence fish. Overall, this effort provided preliminary information on the contaminant mixtures present and their potential health implications, which can support the protection of community health and culturally meaningful resources across the Crow Reservation.
","language":"English","publisher":"Royal Society of Chemistry","doi":"10.1039/d5em00565e","usgsCitation":"Smalling, K., Bradley, P., Romanok, K., Doyle, J.T., Eggers, M.J., Martin, C., Barnhart, E.P., Binette, P., Castro, E.M., Chavez, M., Ewing, S.A., Gordon, S.E., Fields, M.W., Gray, J.L., Groshong, A.M., Hwang, C., Kanagy, L.K., LaFrance, J.W., Loftin, K., Long, C.M., McCleskey, R., Meppelink, S.M., Richards, C.L., Schreiner, M., Shikany, J.I., and Tesfamariam, M., 2026, Per- and polyfluoroalkyl substances (PFAS) and other contaminants of concern in tribal waters of Montana: Environmental Science: Processes & Impacts, v. 28, p. 579-597, https://doi.org/10.1039/d5em00565e.","productDescription":"19 p.; Data Release","startPage":"579","endPage":"597","ipdsId":"IP-176501","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":499612,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index 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Chronic exposure is linked with multiple health outcomes, and risk can change sharply over short distances and with well depth. Coarse maps or sparse sampling often miss exceedances. Most existing models operate at ∼1 km resolution and use groundwater chemistry or detailed geologic logs, which limits their use in undersampled areas where improved guidance is most needed. We overcome these limitations by developing a machine learning model for Minnesota, USA, that predicts As exposure risk using only surficial variables from remote sensing and global data sets. Variables related to surface water hydrology and geomorphology are selected based on mechanistic links that control redox conditions and As mobilization. Local training was essential, and surficial geology variables that are more sensitive to local conditions were needed to maximize model accuracy. The resulting complete model was sufficiently sensitive to generate accurate and detailed risk maps and depth profiles of As concentrations above the 10 μg/L maximum contaminant level. Accuracy depended on local training data density. We identified a training data density of 0.07 wells/km2 as a practical target for stable county-level performance. Maps of exceedance probabilities highlight priority areas for testing that are particularly important in rural communities that have received less sampling. These results support public health action by guiding where to install wells and where to test them, how much new sampling is needed, and where treatment outreach is most urgent.
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We investigated the links among the environment, animal movement, and infectious disease dynamics in waterfowl, which are among the primary wildlife hosts of avian influenza viruses. By combining telemetry data on 4606 individuals from 26 waterfowl species with data on land cover, weather, and vegetation, we found that waterfowl moved less in areas of higher land cover heterogeneity and higher human population density. Moreover, predicted waterfowl movement distances were weakly but positively correlated with distances between detections of H5N1 highly pathogenic avian influenza in wild waterfowl, suggesting that environmental conditions might contribute to the spread of this disease via their effects on bird movements. By considering wildlife movements alongside other drivers of infectious disease dynamics, such as livestock production and human mobility, we move closer to predicting outbreaks and informing interventions.
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- Mountain goat declines in a protected, interior, native population","interactions":[],"lastModifiedDate":"2026-01-28T15:42:30.936097","indexId":"70273773","displayToPublicDate":"2026-01-22T09:37:07","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Mountain goat declines in a protected, interior, native population","docAbstract":"A shifting climate poses threats to alpine-adapted species including mountain goats. We used long-term (12 years) citizen science monitoring data and Bayesian N-mixture modeling to estimate population trends and drivers of population metrics among mountain goats in Glacier National Park (GNP). Median goats per site (n = 37 sites) declined by 45% (95% credible interval [CRI] = 32%, 57%) from 77.8 (95% CRI = 64.4, 95.1) in 2008 to 42.3 (95% CRI = 34.3, 52.2) in 2019, with consistent declines from 2008 until 2015, when the number of estimated goats stabilized. The decline exceeds IUCN criteria for classifying a population as vulnerable, >30% declines over only two generations. Across years, relatively few goats occupied northwestern GNP. Goat numbers declined the most at northeastern sites, trended toward decline in most southern sites, and increased at only two west-central sites. The proportion of permanent snow and glaciers, the presence of natural mineral licks, and habituation strongly increased the initial abundance of goats in the area. Weather variables had the greatest influence on population growth rates, particularly precipitation between May 15 and June 15 of the previous summer, the neonatal period. Lower growth occurred with less snow water equivalent and lower mean winter temperature, early summer temperature, and early summer precipitation. Projected reductions of permanent snow, increasing spring and summer temperatures, and insufficient and variable spring precipitation raise concerns for the future of native goats in this region. Our analyses reveal ways to improve detection rates of goats during surveys, which is important for optimizing the precision of estimates and the power to detect future trends. Detection increased with goat habituation, retention of observers with experience, use of binoculars, and conducting surveys at lower temperatures and earlier dates. Improving detection will be particularly important given the lower number of goats currently observed in the park. Research to estimate park-wide population size, evaluate genetic structure and diversity, assess changing habitat, human recreation levels and forage, and forward-project climate effects on persistence will be crucial to understanding the context of these results and conserving this iconic, metapopulation at the southern edge of the distribution of native mountain goats.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.70465","usgsCitation":"Graves, T., Janousek, W.M., Yarnall, M., and Belt, J., 2026, Mountain goat declines in a protected, interior, native population: Ecosphere, v. 17, no. 1, e70465, 17 p., https://doi.org/10.1002/ecs2.70465.","productDescription":"e70465, 17 p.","ipdsId":"IP-128275","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":499325,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.70465","text":"Publisher Index Page"},{"id":499544,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P91GTUL3","text":"USGS data release","linkHelpText":"Mountain goats (Oreamnos americanus) in Glacier National Park, Montana, USA, and Waterton Lakes National Park, Alberta, Canada, 2008-2023"},{"id":499170,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","otherGeospatial":"Glacier National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -113.60080650878787,\n 48.99458864720981\n ],\n [\n -114.48645916591128,\n 49.005131748927084\n ],\n [\n -114.0989861284199,\n 48.45748119419969\n ],\n [\n -113.89364327444952,\n 48.479975245922134\n ],\n [\n -113.55795234795937,\n 48.2165274365571\n ],\n [\n -113.33118241357474,\n 48.30924537874591\n ],\n [\n -113.2169046513653,\n 48.412463176207496\n ],\n [\n -113.40439160499024,\n 48.70318915560594\n ],\n [\n -113.41331955516296,\n 48.74677172670576\n ],\n [\n -113.46867284623328,\n 48.78796372490032\n ],\n [\n -113.59723532871878,\n 48.93362924512738\n ],\n [\n -113.60080650878787,\n 48.99458864720981\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"17","issue":"1","noUsgsAuthors":false,"publicationDate":"2026-01-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Graves, Tabitha A. 0000-0001-5145-2400","orcid":"https://orcid.org/0000-0001-5145-2400","contributorId":202084,"corporation":false,"usgs":true,"family":"Graves","given":"Tabitha A.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":954736,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Janousek, William Michael 0000-0003-3978-1775","orcid":"https://orcid.org/0000-0003-3978-1775","contributorId":237980,"corporation":false,"usgs":true,"family":"Janousek","given":"William","email":"","middleInitial":"Michael","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":954737,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yarnall, Michael","contributorId":300614,"corporation":false,"usgs":false,"family":"Yarnall","given":"Michael","email":"","affiliations":[{"id":38050,"text":"Contractor","active":true,"usgs":false}],"preferred":false,"id":954738,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Belt, Jami","contributorId":177314,"corporation":false,"usgs":false,"family":"Belt","given":"Jami","affiliations":[],"preferred":false,"id":954739,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70273701,"text":"70273701 - 2026 - Miocene evolution of the Humboldt Current","interactions":[],"lastModifiedDate":"2026-01-23T15:12:43.427537","indexId":"70273701","displayToPublicDate":"2026-01-22T09:04:07","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2996,"text":"Palaeogeography, Palaeoclimatology, Palaeoecology","printIssn":"0031-0182","active":true,"publicationSubtype":{"id":10}},"title":"Miocene evolution of the Humboldt Current","docAbstract":"Diatom records from the East Pisco Basin (EPB) of southern Peru and offshore Ocean Drilling Program (ODP) Hole 682 A reveal stepwise increases in the primary productivity of the Humboldt Current during the middle and late Miocene. Although diatoms are present back through the late middle Eocene, successively enhanced diatom production occurs during the Miocene in four steps. The first step between 14.2 and 13.8 Ma marks the onset of diatom deposition in the Pisco-0 sequence. A second step at ∼12.9 Ma coincides with a major drop in global sea level during which diatom deposition ceased in the EPB but continued in ODP 682 A as well as in Chile, Ecuador, and Colombia. Beginning at 10.4 to 10.0 Ma, a major increase in diatom sedimentation rates in both the EPB and in ODP 682 A signals an abrupt intensification of the Humboldt Current productivity, which may be related to the closure of the Central American Seaway to deeper water circulation. A fourth step coincides with the transgressive deposition of the diatom-rich Pisco-2 sequence at 8.4 Ma and is enhanced by the onset of the global Late Miocene Biogenic Bloom (8.0–4.5 Ma). Between 7 and 6 Ma, common subtropical diatoms in ODP 682 A contrast with high diatom deposition rates in the EPB, suggesting variable El Niño-La Niña conditions. During this time, fossil vegetation evidence from southern Peru supports the presence of seasonal periods of enhanced rainfall typical of El Niño conditions. The Miocene trend of increasing sea mammal diversity in the EPB parallels these steps, further supporting stepwise enhancement of primary productivity in the Humboldt Current during the Miocene.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.palaeo.2026.113558","usgsCitation":"Barron, J.A., DeVries, T.J., and Coenen, J.J., 2026, Miocene evolution of the Humboldt Current: Palaeogeography, Palaeoclimatology, Palaeoecology, v. 686, 113558, 12 p., https://doi.org/10.1016/j.palaeo.2026.113558.","productDescription":"113558, 12 p.","ipdsId":"IP-180806","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":498990,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Peru","otherGeospatial":"Humboldt Current","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -80.73639910834312,\n -7.6494563030919664\n ],\n [\n -80.73639910834312,\n -16.02780933667553\n ],\n [\n -73.96573832460824,\n -16.02780933667553\n ],\n [\n -73.96573832460824,\n -7.6494563030919664\n ],\n [\n -80.73639910834312,\n -7.6494563030919664\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"686","noUsgsAuthors":false,"publicationDate":"2026-01-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Barron, John A. 0000-0002-9309-1145 jbarron@usgs.gov","orcid":"https://orcid.org/0000-0002-9309-1145","contributorId":2222,"corporation":false,"usgs":true,"family":"Barron","given":"John","email":"jbarron@usgs.gov","middleInitial":"A.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":954343,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"DeVries, Thomas J.","contributorId":365487,"corporation":false,"usgs":false,"family":"DeVries","given":"Thomas","middleInitial":"J.","affiliations":[{"id":87141,"text":"Burke Museum, University of Washington","active":true,"usgs":false}],"preferred":false,"id":954344,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Coenen, Jason J.","contributorId":365488,"corporation":false,"usgs":false,"family":"Coenen","given":"Jason","middleInitial":"J.","affiliations":[{"id":16602,"text":"University of Nebraska, Lincoln","active":true,"usgs":false}],"preferred":false,"id":954345,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70273700,"text":"70273700 - 2026 - Compilation of a nationwide river image dataset for identifying river channels and river rapids via deep learning","interactions":[],"lastModifiedDate":"2026-01-26T14:20:22.073435","indexId":"70273700","displayToPublicDate":"2026-01-22T08:44:42","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Compilation of a nationwide river image dataset for identifying river channels and river rapids via deep learning","docAbstract":"Remote sensing enables large-scale, image-based assessments of river dynamics, offering new opportunities for hydrological monitoring. We present a publicly available dataset consisting of 281,024 satellite and aerial images of U.S. rivers, constructed using an Application Programming Interface (API) and the U.S. Geological Survey’s National Hydrography Dataset. The dataset includes images, primary keys, and ancillary geospatial information. We use a manually labeled subset of the images to train models for detecting rapids, defined as areas where high velocity and turbulence lead to a wavy, rough, or even broken water surface visible in the imagery. To demonstrate the utility of this dataset, we develop an image segmentation model to identify rivers within images. This model achieved a mean test intersection-over-union (\uD835\uDC3C\uD835\uDC5C\uD835\uDC48) of 0.57, with performance rising to an actual \uD835\uDC3C\uD835\uDC5C\uD835\uDC48 of 0.89 on the subset of predictions with high confidence (predicted \uD835\uDC3C\uD835\uDC5C\uD835\uDC48 > 0.9). Following this initial segmentation of river channels within the images, we trained several convolutional neural network (CNN) architectures to classify the presence or absence of rapids. Our selected model reached an accuracy and F1 score of 0.93, indicating strong performance for the classification of rapids that could support consistent, efficient inventory and monitoring of rapids. These data provide new resources for recreation planning, habitat assessment, and discharge estimation. Overall, the dataset and tools offer a foundation for scalable, automated identification of geomorphic features to support riverine science and resource management.
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,{"id":70273409,"text":"ofr20251057 - 2026 - Distribution, abundance, breeding activities, and habitat use of the Least Bell's Vireo at Marine Corps Base Camp Pendleton, California—2020–24 summary report","interactions":[],"lastModifiedDate":"2026-02-03T17:09:16.100992","indexId":"ofr20251057","displayToPublicDate":"2026-01-21T07:00:00","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":"2025-1057","displayTitle":"Distribution, Abundance, Breeding Activities, and Habitat Use of the Least Bell's Vireo at Marine Corps Base Camp Pendleton, California—2020–24 Summary Report","title":"Distribution, abundance, breeding activities, and habitat use of the Least Bell's Vireo at Marine Corps Base Camp Pendleton, California—2020–24 summary report","docAbstract":"The purpose of this report is to provide the Marine Corps with a summary of abundance, breeding activity, demography, and habitat use of endangered Least Bell’s Vireos (Vireo bellii pusillus) at Marine Corps Base Camp Pendleton, California (MCBCP or Base). The report presents results of vireo surveys and monitoring in 2024 and summarizes a subset of data collected from 2020 through 2024. Surveys for the Least Bell's Vireo were completed at MCBCP between April 4 and July 9, 2024. Core survey areas and a subset of non-core areas in drainages containing riparian habitat suitable for vireos were surveyed two to four times. We detected 542 territorial male vireos and 17 transient vireos in core survey areas. An additional 102 territorial male vireos and 2 transients were detected in non-core survey areas. Transient vireos were detected on 5 of the 10 drainages/sites surveyed (core and non-core areas). In core survey areas, 87 percent of vireo territories were on the four most populated drainages, with the Santa Margarita River containing 67 percent of all territories in core areas surveyed on Base. In core areas, 77 percent of male vireos were confirmed as paired; 76 percent of male vireos in non-core areas were confirmed as paired.
The number of documented Least Bell’s Vireo territories in core survey areas on MCBCP decreased 3 percent from 2023. In five core survey area drainages, the number of territories increased by at least two, and in two core survey area drainages, the Santa Margarita River and Las Flores Creek, the number of vireo territories decreased by at least nine between 2023 and 2024. The number of vireo territories at Marine Corps Air Station, Camp Pendleton did not change from 2023 to 2024. The proportion of surveys during which Brown-headed Cowbirds (Molothrus ater) were detected decreased to 0.03 from a peak of 0.45 in 2022. Cowbirds were detected in April and June in 2024.
Most core-area vireos (58 percent, including transients) used mixed willow (Salix spp.) riparian habitat. An additional 9 percent of birds occupied willow habitat co-dominated by Western sycamores (Platanus racemosa). Riparian scrub dominated by mule fat (Baccharis salicifolia), sandbar willow (S. exigua), or blue elderberry (Sambucus mexicana) was used by 33 percent of vireos. Habitat dominated by non-native vegetation was used by 1 percent of vireos.
Since 2020, the number of vireos detected in each of the non-core survey groups was greater than expected, based on the change in vireo numbers in core survey areas. Although, the number of vireo territories on Base decreased from 2020–24, from approximately 1,224 to approximately 960, the trend in vireo territory numbers on Base since 2005 has been positive.
In 2019, MCBCP began operating an artificial seep along the Santa Margarita River; then, in 2021, two additional artificial seeps became operational. The artificial seeps pumped water to the surface during daylight hours starting in mid-April and ending in August each year and were designed to increase the amount of surface water to enhance Southwestern Willow Flycatcher (Empidonax traillii extimus) breeding habitat. Although this enhancement was designed to benefit flycatchers, few flycatchers have inhabited MCBCP, including the seep areas, within the past several years; therefore, vireos were selected as a surrogate species to determine effects of the habitat enhancement. This report presents the fifth year of annual monitoring and analyses summarizing all 5 years of vireo and vegetation response to the artificial seeps.
In 2020, we established four study sites along the Santa Margarita River, two surrounding and extending downstream from existing and proposed seep pumps at the Old Treatment Ponds and along Pump Road and two Reference sites in similar habitat downstream from the Seep sites. Seep pumps began operating at the Old Treatment Ponds in 2020 and along Pump Road in 2021. In 2023, seep pumps at the Pump Road Seep site did not function, and we recategorized that study site as Intermediate. We sampled vegetation at Seep, Intermediate, and Reference sites to determine the effects of surface-water enhancement by seep pumps. In 2024, vegetation cover was highest near the ground and decreased with increasing height. Woody vegetation made up most of the cover at all height categories. We determined that Seep and Intermediate sites differed from each other in addition to differing from Reference sites, which likely is, in part, because seep-pump operation at the Intermediate site was inconsistent compared to the Seep site. Soil saturation in 2024 was high at the Intermediate site and was associated with high native herbaceous cover and low non-native herbaceous cover. Sites differed, with the Intermediate site having more upper canopy cover in general, the Seep site having more low woody cover, and the Reference sites having more mid-canopy non-native vegetation cover.
Soil saturation significantly increased from 2020 through 2024 at the Seep site and was significantly higher at Seep and Intermediate sites than at their paired Reference sites in all years. Soil saturation likely was increased by the supplemental surface water at the Seep site. However, soil saturation at the Intermediate site was not clearly associated with seep pumps but likely affected by soil saturation at the site before seep-pump installation and flooding from high precipitation. Canopy height increased at the Intermediate site from 2020 through 2024 and increased with increasing soil saturation at the Intermediate and Reference sites. The canopy at the Seep site was shorter than at the Intermediate and Reference sites and decreased from 2020 through 2024 because tall trees were damaged and killed by shothole borer beetles (Euwallacea spp.).
We used Redundancy Analysis to discover associations among vegetation types, plant species, and other environmental variables (soil saturation, site, precipitation, and seep operation, defined as the site and year seep pumps were operating). These associations explained less than 15 percent of the variability in the vegetation, with the remaining 85 percent of variation unexplained. Generally, as soil saturation increased, understory vegetation increased and non-native cover decreased in the mid-and upper canopy. Non-native herbaceous plant species decreased in wetter soil.
The Seep site was characterized by more understory and less canopy, contrasting with the Intermediate site, which was characterized by less understory and more higher canopy cover. The addition of surface water via seep pumps or precipitation was associated with more vegetation near the ground. Higher early winter precipitation was associated with taller canopy and more woody vegetation in the upper canopy. We also created a Redundancy Analysis model isolating the components of Southwestern Willow Flycatcher habitat, as identified by Howell and others (2018). In this model, increased soil saturation resulted in increased cover of stinging nettle (Urtica dioica) and black willow (Salix gooddingii) below 3 meters (m), total cover 3–6 m, and black willow above 6 m. Cover of poison hemlock (Conium maculatum) and stinging nettle below 3 m was higher at the Seep site and lower at the Intermediate site.
Vireo territory density among the Seep, Intermediate, and Reference sites was similar before the seep pumps were installed. However, vireo territory density at Seep and Intermediate sites combined was significantly higher than at Reference sites after the seep pumps were installed.
We banded and resighted color banded vireos as part of a long-term evaluation of vireo survival, site fidelity, between-year movement, and the effect of surface-water enhancement on vireo return rate and between-year movement. We banded 164 Least Bell's Vireo nestlings during the 2024 season.
In 2024, we resighted 31 Least Bell's Vireos on Base that had been banded before the 2024 breeding season, and we were able to identify 25 of them. Of the 25 that we could identify, 24 were banded on Base and 1 was originally banded on the San Luis Rey River. Adult birds of known age ranged from 1 to 9 years old.
Base-wide survival of vireos was affected by sex, age, and year. Males had significantly higher annual survival than females (60 percent versus 47 percent, respectively). Adults had higher annual survival than first-year vireos (61 percent versus 11 percent, respectively). The return rate of adult vireos to Seep, Intermediate, or Reference sites was not affected by the original banding site (Seep versus Intermediate versus Reference).
Most returning adult vireos, predominantly males, showed strong between-year site fidelity. Of the adults present in 2023, 92 percent (all males) returned in 2024 to within 100 m of their previous territory. The average between-year movement for returning adult vireos was 0.4±0.03 kilometers (km). The average movement of first-year vireos detected in 2024 that fledged from a known nest on MCBCP in 2023 was 2.4±3.1 km.
We monitored 47 Least Bell's Vireo pairs to evaluate the effects of surface-water enhancement on nest success and breeding productivity. Breeding productivity in 2024 was similar among Seep, Intermediate, and Reference sites (2.8, 3.0, and 3.0 young fledged per pair, respectively), and the percentage of pairs that fledged at least one young was not significantly different among sites (83, 91, and 96 percent, respectively). According to the best model, daily nest survival from 2020–24 was not related to site. Other measures of breeding productivity were also similar among Seep, Intermediate, and Reference site pairs.
Between 2020 and 2024, the number of vireo fledglings produced per pair increased with increasing native herbaceous cover under 3 m and decreasing cover of all herbaceous vegetation under 5 m and was not affected by precipitation, site, or seep operation. The number of vireo fledglings produced per egg was lower at the Seep and Intermediate sites than at the Reference sites and increased with decreasing late winter precipitation, cover of poison hemlock, black mustard, non-native vegetation above 2 m, and all vegetation over 2 m. Vireo pairs at Seep and Intermediate sites were less likely to fledge young than vireo pairs at Reference sites. All vireo pairs were more likely to fledge young with less cover of poison hemlock and more cover of poison oak.
From 2020 through 2024, vireos placed their nests in 24 plant species. The most used plants in all years were willows, mostly red (S. laevigata), or arroyo (S. lasiolepis). The fate of a vireo nest (whether it successfully fledged young or not) was not affected by placement in native or non-native vegetation, by site, or by year, but nests were more likely to be successful if they were placed in woody plants than in herbaceous plants. Successful nests were placed higher in the host plant and farther from the outer edge of the nest clump than unsuccessful nests.
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The Cook County Precipitation Network is a set of 25 precipitation gages established within Cook County, Illinois, on approximately a 5- to 7-mile square grid and used by the U.S. Army Corps of Engineers to help account for diversions of water from Lake Michigan to the State of Illinois. The transition from the precipitation gage network operated by the Illinois State Water Survey to the precipitation gage network operated by the U.S. Geological Survey (USGS) was compared for periods of overlapping data. This transition took place from May through September during the 2019 water year. The USGS was able to establish replacement precipitation gages at 17 of the 25 sites by the conclusion of the overlapping operational period.
The double-mass curve method was used to compare the two networks by creating a graph of the cumulated data collected by the Illinois State Water Survey and the comparable data collected by the USGS. Breaks in the double-mass curve method are caused by a change in the relation between variables. The eight sites that were installed following the overlapping period have a gap in the recorded data; however, the slope of the line for each of the eight sites is nearly equivalent to the previous data. In general, the cumulated precipitation data from the two networks were similar. Three sites had greater than 8-percent difference in their cumulative data ratios, located at Cicero, Ping Tom Park at Chicago, and South Shore, Ill.
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Central Midwest Water Science Center
U.S. Geological Survey
405 North Goodwin
Urbana, IL 61801
The Cook County Precipitation Network includes 25 precipitation gages spread out across Cook County, Illinois. These gages help the U.S. Army Corps of Engineers track how much water is diverted from Lake Michigan into Illinois. In 2019, the responsibility for operating and maintaining these gages shifted from the Illinois State Water Survey to the U.S. Geological Survey. To evaluate the data consistency during the transition, the two organizations operated their networks at the same time for a few months (May to September 2019). During this period, the U.S. Geological Survey installed new gages at 17 of the 25 sites. The remaining 8 sites were installed later, resulting in data gaps for those sites. An analytical method called a double-mass curve was used to compare the data from both networks. Overall, the precipitation totals from both networks were very similar. However, three sites had cumulative data ratio differences greater than 8 percent.
","publicationDate":"2026-01-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Johnson, Kevin K. 0000-0003-2703-5994 johnsonk@usgs.gov","orcid":"https://orcid.org/0000-0003-2703-5994","contributorId":4220,"corporation":false,"usgs":true,"family":"Johnson","given":"Kevin","email":"johnsonk@usgs.gov","middleInitial":"K.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":953872,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70273942,"text":"70273942 - 2026 - Harmonization of aggregated freshwater biotic data to support continental and global assessment","interactions":[],"lastModifiedDate":"2026-02-19T14:32:03.770691","indexId":"70273942","displayToPublicDate":"2026-01-20T08:29:18","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":11111,"text":"PLOS Water","active":true,"publicationSubtype":{"id":10}},"title":"Harmonization of aggregated freshwater biotic data to support continental and global assessment","docAbstract":"Biodiversity loss and conservation are increasingly coming into focus in global policy fora, requiring information and assessments at wider spatial and temporal scales than previously considered. However, the monitoring framework required to support such data collection and assessment is lacking in many countries and is not harmonized across countries, hampering these efforts. Aggregation of existing freshwater data offers a solution to the problem of assessing status and trends of ecosystems and biodiversity at large spatial scales in the absence of nationally coordinated monitoring efforts. Analysis of aggregated data from different sources, collected using different protocols and with varying levels of metadata and supporting data, can be challenging and requires decisions regarding data comparability. In this paper, we identify the challenges inherent in harmonizing aggregated freshwater data for analysis, including general concerns related to research goals, spatial and temporal scale, sample selection, sampling effort, and site integrity. We also discuss the challenges related to measured parameters, sampled habitats, sample collection and processing methods, and data integrity for phytoplankton, benthic algae, macrophytes, zooplankton, benthic macroinvertebrates, fish, and supporting variables such as water and sediment chemistry. We provide a workflow to evaluate each of these challenges and make decisions about how best to work with the data. Finally, we review a case study from a large-scale analysis of freshwater data from the circumpolar Arctic region that exemplifies the encountered challenges and the chosen solutions. Through the description of the case study, we provide practical solutions to support aggregation and analysis of existing freshwater data. As global conversations about biodiversity status and trends continue, the demand for large-scale analyses of data from different sources will only grow. In the absence of globally harmonized monitoring, we are faced with the need to ensure comparability of data, making expert judgements where needed to support sound conclusions.
","language":"English","publisher":"PLOS","doi":"10.1371/journal.pwat.0000502","usgsCitation":"Lento, J., Laske, S.M., Culp, J.M., Goedkoop, W., Kahlert, M., Lau, D.C., Lavoie, I., Musetta-Lambert, J., Ólafsson, J.S., and Christoffersen, K.S., 2026, Harmonization of aggregated freshwater biotic data to support continental and global assessment: PLOS Water, v. 5, no. 1, e0000502, 27 p., https://doi.org/10.1371/journal.pwat.0000502.","productDescription":"e0000502, 27 p.","ipdsId":"IP-180104","costCenters":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"links":[{"id":500254,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pwat.0000502","text":"Publisher Index Page"},{"id":500141,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"5","issue":"1","noUsgsAuthors":false,"publicationDate":"2026-01-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Lento, Jennifer","contributorId":221451,"corporation":false,"usgs":false,"family":"Lento","given":"Jennifer","email":"","affiliations":[{"id":18889,"text":"University of New Brunswick","active":true,"usgs":false}],"preferred":false,"id":955855,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Laske, Sarah M. 0000-0002-6096-0420 slaske@usgs.gov","orcid":"https://orcid.org/0000-0002-6096-0420","contributorId":204872,"corporation":false,"usgs":true,"family":"Laske","given":"Sarah","email":"slaske@usgs.gov","middleInitial":"M.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"preferred":true,"id":955856,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Culp, Joseph M.","contributorId":366416,"corporation":false,"usgs":false,"family":"Culp","given":"Joseph","middleInitial":"M.","affiliations":[{"id":87479,"text":"Cold Regions Research Centre and Department of Biology, Wilfrid Laurier University","active":true,"usgs":false}],"preferred":false,"id":955857,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Goedkoop, Willem","contributorId":366417,"corporation":false,"usgs":false,"family":"Goedkoop","given":"Willem","affiliations":[{"id":87480,"text":"Swedish University of Agricultural Sciences, Department of Aquatic Sciences and Assessment","active":true,"usgs":false}],"preferred":false,"id":955858,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kahlert, Maria","contributorId":366418,"corporation":false,"usgs":false,"family":"Kahlert","given":"Maria","affiliations":[{"id":87480,"text":"Swedish University of Agricultural Sciences, Department of Aquatic Sciences and Assessment","active":true,"usgs":false}],"preferred":false,"id":955859,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lau, Danny C.P.","contributorId":366419,"corporation":false,"usgs":false,"family":"Lau","given":"Danny","middleInitial":"C.P.","affiliations":[{"id":87480,"text":"Swedish University of Agricultural Sciences, Department of Aquatic Sciences and Assessment","active":true,"usgs":false}],"preferred":false,"id":955860,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lavoie, Isabelle","contributorId":255561,"corporation":false,"usgs":false,"family":"Lavoie","given":"Isabelle","email":"","affiliations":[{"id":51586,"text":"Institut national de la recherche scientifique, Centre Eau Terre Environnement","active":true,"usgs":false}],"preferred":false,"id":955861,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Musetta-Lambert, Jordan","contributorId":366420,"corporation":false,"usgs":false,"family":"Musetta-Lambert","given":"Jordan","affiliations":[{"id":87481,"text":"Watershed Hydrology and Ecology Research Division, National Hydrology Research Centre, Environment and Climate Change Canada","active":true,"usgs":false}],"preferred":false,"id":955862,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Ólafsson, Jón S.","contributorId":366421,"corporation":false,"usgs":false,"family":"Ólafsson","given":"Jón","middleInitial":"S.","affiliations":[{"id":40381,"text":"Marine and Freshwater Research Institute, Iceland","active":true,"usgs":false}],"preferred":false,"id":955863,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Christoffersen, Kirsten S.","contributorId":366422,"corporation":false,"usgs":false,"family":"Christoffersen","given":"Kirsten","middleInitial":"S.","affiliations":[{"id":87482,"text":"Freshwater Biological Section, Department of Biology, University of Copenhagen","active":true,"usgs":false}],"preferred":false,"id":955864,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70273759,"text":"70273759 - 2026 - Recent range expansion and documentation of a reproductive population of northern snakehead Channa argus (Cantor, 1842) in the Saint Francis River Drainage, Missouri","interactions":[],"lastModifiedDate":"2026-03-16T14:12:37.829607","indexId":"70273759","displayToPublicDate":"2026-01-19T09:05:59","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":23282,"text":"Records of Biological Invasions","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Recent range expansion and documentation of a reproductive population of northern snakehead Channa argus (Cantor, 1842) in the Saint Francis River Drainage, Missouri","title":"Recent range expansion and documentation of a reproductive population of northern snakehead Channa argus (Cantor, 1842) in the Saint Francis River Drainage, Missouri","docAbstract":"Northern snakehead Channa argus (Cantor, 1842) is an aquatic invasive fish species in the United States with first documented occurrence in the wild in the 2000s. Management efforts to control their populations in the eastern United States are ongoing. In the Mississippi River basin, limited resources have been allocated to control its distribution, after initial detection and rapid response in Arkansas were unsuccessful. Northern snakehead distribution in the Mississippi River basin was limited to Arkansas and Mississippi until 2019 when a single northern snakehead was detected on the southern border of Missouri in the Saint Francis River drainage, the furthest northern detection. Described here are additional northern snakehead detections following public reports and subsequent monitoring in the Mingo basin of the Saint Francis River drainage, a historical braided channel and floodplain habitat of the Mississippi River with intermittently flooded bottomland hardwood forests and wetlands, and other consistent aquatic habitats. These increasing captures document the recent range expansion of northern snakehead. Most of the 11,300 ha Mingo basin consists of Mingo National Wildlife Refuge and Duck Creek Conservation Area; these areas are protected aquatic ecosystems possessing sensitive species and serve as a potential example of prioritized areas for northern snakehead control efforts. Additionally, we highlight the significance of these detections in the Mingo basin which is connected via the Castor River water-control structure to the Upper Mississippi River and may facilitate further range expansion.
","language":"English","publisher":"Regional Euro-Asian Biological Invasions Centre - REABIC","doi":"10.3391/bir.2026.15.1.17","usgsCitation":"Sterling, E.M., Bookout, T.A., Holmes, E., Baalman, N., Henderson, C., and Kroboth, P., 2026, Recent range expansion and documentation of a reproductive population of northern snakehead Channa argus (Cantor, 1842) in the Saint Francis River Drainage, Missouri: Records of Biological Invasions, v. 15, no. 1, p. 183-194, https://doi.org/10.3391/bir.2026.15.1.17.","productDescription":"12 p.","startPage":"183","endPage":"194","ipdsId":"IP-178255","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":501362,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3391/bir.2026.15.1.17","text":"Publisher Index Page"},{"id":501172,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Missouri","otherGeospatial":"Saint Francis River drainage","volume":"15","issue":"1","noUsgsAuthors":false,"publicationDate":"2026-01-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Sterling, Edward M.","contributorId":365674,"corporation":false,"usgs":false,"family":"Sterling","given":"Edward","middleInitial":"M.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":954593,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bookout, Taylor A.","contributorId":336867,"corporation":false,"usgs":false,"family":"Bookout","given":"Taylor","email":"","middleInitial":"A.","affiliations":[{"id":80890,"text":"Illinois Natural History Survey (INHS)","active":true,"usgs":false}],"preferred":false,"id":954594,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Holmes, Erin","contributorId":222739,"corporation":false,"usgs":false,"family":"Holmes","given":"Erin","email":"","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":954595,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Baalman, Neil","contributorId":365675,"corporation":false,"usgs":false,"family":"Baalman","given":"Neil","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":954596,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Henderson, Cody","contributorId":344002,"corporation":false,"usgs":false,"family":"Henderson","given":"Cody","email":"","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":957094,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kroboth, Patrick 0000-0002-9447-4818","orcid":"https://orcid.org/0000-0002-9447-4818","contributorId":216578,"corporation":false,"usgs":true,"family":"Kroboth","given":"Patrick","email":"","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":954597,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70274646,"text":"70274646 - 2026 - Compounding of 100-year coastal floods by rainfall in an urban environment","interactions":[],"lastModifiedDate":"2026-04-02T15:50:56.3047","indexId":"70274646","displayToPublicDate":"2026-01-16T10:46:09","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":"Compounding of 100-year coastal floods by rainfall in an urban environment","docAbstract":"Coastal and pluvial flooding are both becoming more prevalent and severe due to climate change and urbanization in floodplains. The co-occurrence of these flood drivers is generally assumed to exacerbate the resulting flood impacts, a result referred to as compound flooding. However, few observational or modeling studies have investigated the circumstances under which this occurs. Here, we study the impacts of these combined flood drivers and evaluate the implicit hypothesis of official flood maps, which is that rainfall has a negligible impact on the flood depth and flooded area due to a 100 year coastal flood. A coastal system model, configured to capture coastal and pluvial flood drivers, is used. We evaluate the flooding for different urban landform types, including coastal landfill (human-made land), convergent areas (topographic depressions) and other urban terrain, within a model domain covering the Jamaica Bay watershed of New York City. A scenario-based strategy is adopted with a 100 year coastal flood as a control simulation, to which we add a set of realistic scenarios of rainfall data from historical tropical cyclones. We also apply a joint probability analysis framework with historical data to evaluate the probability of these compound coastal-pluvial scenarios. Results reveal cases where the pluvial driver compounds the coastal flood through expansion of the flood zone, with a 17% chance of rainfall increasing the flood area by 6%–38%, and a 5% chance of an increase of 61%–73%. It is rare that floods are significantly deepened but when deepening occurs, it is more common for the convergent zone than for the coastal landfill. These findings quantitatively assess the potential of the pluvial driver to exacerbate flooding, which may influence emergency management strategies such as evacuation plans, shelter arrangements, and related preparedness measures.
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Understanding and ameliorating potential threats that reduce the likelihood of successful population establishment at recipient sites is a key component of successful translocation planning. We examined multiple potential threats, including pathogens, contaminants, and invasive species, as well as habitat suitability and food resources, to assess the feasibility of reintroducing threatened, stream-obligate foothill yellow-legged frogs, Rana boylii, to Pinnacles National Park. Foothill yellow-legged frogs were extirpated from this protected area more than half a century ago. Although invasive species, disease, contaminants, food resources, and water temperatures are unlikely to inhibit foothill yellow-legged frog population establishment, potential recipient streams at Pinnacles National Park had shorter hydroperiods and much higher canopy cover than reference streams with extant foothill yellow-legged frog populations. Although the exact cause of extirpation of foothill yellow-legged frogs from Pinnacles National Park is unknown, translocations of foothill yellow-legged frogs to the park are more likely to succeed if riparian canopy cover is reduced and stream hydroperiods increased to better match those at nearby populations. Thoroughly understanding the threats to and characteristics of potential recipient sites could improve the likelihood of success of translocation outcomes in natural areas.
","language":"English","publisher":"BioOne","doi":"10.3375/2162-4399-46.1.5","usgsCitation":"Macias, D., Kleeman, P.M., Hladik, M.L., Smalling, K., Johnson, P.G., Grear, D.A., Rose, J.P., and Halstead, B.J., 2026, Conducting feasibility assessments of potential conservation reintroductions: A case study with the imperiled foothill yellow-legged frog, Rana boylii: Natural Areas Journal, v. 46, no. 1, p. 31-43, https://doi.org/10.3375/2162-4399-46.1.5.","productDescription":"13 p.","startPage":"31","endPage":"43","ipdsId":"IP-177308","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true},{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":500647,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Pinnacles National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.28328712668666,\n 36.572411923460166\n ],\n [\n -121.28328712668666,\n 36.38981467953627\n ],\n [\n -121.0867615157555,\n 36.38981467953627\n ],\n [\n -121.0867615157555,\n 36.572411923460166\n ],\n [\n -121.28328712668666,\n 36.572411923460166\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"46","issue":"1","noUsgsAuthors":false,"publicationDate":"2026-01-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Macias, Daniel Antonio 0000-0002-4891-3656","orcid":"https://orcid.org/0000-0002-4891-3656","contributorId":349883,"corporation":false,"usgs":true,"family":"Macias","given":"Daniel Antonio","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":956674,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kleeman, Patrick M. 0000-0001-6567-3239 pkleeman@usgs.gov","orcid":"https://orcid.org/0000-0001-6567-3239","contributorId":3948,"corporation":false,"usgs":true,"family":"Kleeman","given":"Patrick","email":"pkleeman@usgs.gov","middleInitial":"M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":956675,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hladik, Michelle L. 0000-0002-0891-2712","orcid":"https://orcid.org/0000-0002-0891-2712","contributorId":221229,"corporation":false,"usgs":true,"family":"Hladik","given":"Michelle","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":956676,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smalling, Kelly 0000-0002-1214-4920","orcid":"https://orcid.org/0000-0002-1214-4920","contributorId":221234,"corporation":false,"usgs":true,"family":"Smalling","given":"Kelly","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":956677,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Johnson, Paul G.","contributorId":367069,"corporation":false,"usgs":false,"family":"Johnson","given":"Paul","middleInitial":"G.","affiliations":[{"id":36245,"text":"NPS","active":true,"usgs":false}],"preferred":false,"id":956678,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Grear, Daniel A. 0000-0002-5478-1549 dgrear@usgs.gov","orcid":"https://orcid.org/0000-0002-5478-1549","contributorId":189819,"corporation":false,"usgs":true,"family":"Grear","given":"Daniel","email":"dgrear@usgs.gov","middleInitial":"A.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":956679,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rose, Jonathan P. 0000-0003-0874-9166 jprose@usgs.gov","orcid":"https://orcid.org/0000-0003-0874-9166","contributorId":199339,"corporation":false,"usgs":true,"family":"Rose","given":"Jonathan","email":"jprose@usgs.gov","middleInitial":"P.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":956680,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Halstead, Brian J. 0000-0002-5535-6528 bhalstead@usgs.gov","orcid":"https://orcid.org/0000-0002-5535-6528","contributorId":215986,"corporation":false,"usgs":true,"family":"Halstead","given":"Brian","email":"bhalstead@usgs.gov","middleInitial":"J.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":956681,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ]}