The global use of antidepressants has steadily increased, raising concern to aquatic ecosystems due to the incomplete removal during wastewater treatment. Tricyclic antidepressants (TCAs) act on the neuronal system by inhibiting the reuptake of serotonin and norepinephrine. However, despite visual function being heavily dependent on the neuronal system, a knowledge gap remains regarding the ocular toxicity of TCAs. To bridge this knowledge gap, zebrafish (Danio rerio) embryos were exposed to sublethal test concentrations of amitriptyline (AMI, 0.3 to 300 μg/L nominal, 2.04 to 234 μg/L measured) and nortriptyline (NOR, 0.03 to 300 μg/L nominal, >0.107 to 20.7 μg/L measured), with the lowest test concentrations being environmentally relevant. Visual function was assessed with the optokinetic response assay, eye structure development was assessed histologically, and gene expression changes were analysed via transcriptomic profiling. Larval zebrafish (120 h post fertilization (hpf)) exposed to 4.99 and 234 μg/L of AMI exhibited a 26 % and 86 % decrease in the number of eye saccades respectively, with zebrafish exposed to 20.7 μg/L of NOR exhibiting a 65 % decrease. Histological analysis indicated a significant increase of the retinal pigment epithelium thickness after exposure to 234 μg/L of AMI and 20.7 μg/L of NOR. Transcriptomic analysis resulted in 1207 and 2742 differentially expressed genes across both AMI and NOR treatment groups respectively, including genes involved in vision, synaptic signaling, and neuronal development. These findings demonstrate that sublethal concentrations of AMI and NOR affect early life stage zebrafish visual development, which may be sensitive endpoint that could be incorporated into ecological risk assessments.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.cbpc.2025.110363","usgsCitation":"Jafari, M., Magnuson, J.T., Essfeld, F., Eilebrecht, S., Brotzmann, K., and Pampanin, D.M., 2025, Amitriptyline and nortriptyline induce ocular toxicity in early life stage zebrafish (Danio rerio) : Comparative Biochemistry and Physiology Part C: Toxicology & Pharmacology, v. 299, 110363, 11 p., https://doi.org/10.1016/j.cbpc.2025.110363.","productDescription":"110363, 11 p.","ipdsId":"IP-177174","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":496419,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.cbpc.2025.110363","text":"Publisher Index Page"},{"id":496400,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"299","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Jafari, Marwin","contributorId":361975,"corporation":false,"usgs":false,"family":"Jafari","given":"Marwin","affiliations":[{"id":79410,"text":"University of Stavanger, Norway","active":true,"usgs":false}],"preferred":false,"id":949763,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":949764,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Essfeld, Fabian","contributorId":361977,"corporation":false,"usgs":false,"family":"Essfeld","given":"Fabian","affiliations":[{"id":86408,"text":"Fraunhofer Institute for Molecular Biology and Applied Ecology IME, Germany","active":true,"usgs":false}],"preferred":false,"id":949765,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Eilebrecht, Sebastian","contributorId":361978,"corporation":false,"usgs":false,"family":"Eilebrecht","given":"Sebastian","affiliations":[{"id":86408,"text":"Fraunhofer Institute for Molecular Biology and Applied Ecology IME, Germany","active":true,"usgs":false}],"preferred":false,"id":949766,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brotzmann, Katharina","contributorId":361979,"corporation":false,"usgs":false,"family":"Brotzmann","given":"Katharina","affiliations":[{"id":51631,"text":"University of Heidelberg, Germany","active":true,"usgs":false}],"preferred":false,"id":949767,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Pampanin, Daniela M.","contributorId":361980,"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":949768,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70271717,"text":"sir20255089 - 2025 - Characterization of suspended sediment flux and streamflow trends in the Fountain Creek watershed, Colorado, 1998 through 2022","interactions":[],"lastModifiedDate":"2026-02-03T15:32:37.227386","indexId":"sir20255089","displayToPublicDate":"2025-09-22T16:30:00","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-5089","displayTitle":"Characterization of Suspended Sediment Flux and Streamflow Trends in the Fountain Creek Watershed, Colorado, 1998 Through 2022","title":"Characterization of suspended sediment flux and streamflow trends in the Fountain Creek watershed, Colorado, 1998 through 2022","docAbstract":"The U.S. Geological Survey evaluated long-term suspended sediment flux and streamflow datasets for temporal trends (monotonic and step trends) at 10 streamgage sites within the Fountain Creek watershed in central Colorado using the Mann-Kendall test (monotonic trend) and the Wilcoxon signed-rank test (step trend). Data were collected in cooperation with Colorado Springs Stormwater Enterprise. In this study, 10 sites with long-term suspended sediment records were evaluated during their operational periods, which ranged from 1998 through 2022. To assess how stream behavior might relate to shifts in suspended sediment transport, the Richards-Baker flashiness index, a measure of flashiness, was evaluated for each site. The Richards-Baker flashiness index was calculated for the same months as streamflow and suspended sediment (April through September) using all available streamflow data for a given site. Additionally, cumulative double-mass curves were developed to define temporal variation in the relation between streamflow and suspended sediment loads. This was completed by assessing differences in slopes before and after an observed break in the double-mass curve plots.
Five streamgage sites showed statistically significant (p<0.05) negative trends for suspended sediment flux, and nonsignificant decreases were indicated at the other five sites. The statistically significant negative trends are distributed across the watershed and include smaller tributaries and the main stem of Fountain Creek closer to its confluence with the Arkansas River. Such a broad distribution of negative trends is most likely an indication of improved water quality in the watershed with regards to suspended sediment. Assessing causes for the decreases in suspended sediment loads is beyond the scope of this report; however, spatially distributed bank erosion control projects, stormflow retention projects in the watershed, and changes in climate and storm patterns could be some of the potential drivers of the suspended sediment load trends in this watershed. The flashiness of the streamflow was assessed and can be dismissed on the basis of this study as a potential driver of trends in suspended sediment flux because the magnitude of changes was found to be negligible at all sites.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/sir20255089","collaboration":"Prepared in cooperation with Colorado Springs Stormwater Enterprise","usgsCitation":"Downhour, M.S., Hennessy, E.K., and Bern, C.R., 2025, Characterization of suspended sediment flux and streamflow trends in the Fountain Creek watershed, Colorado, 1998 through 2022 (ver. 1.1, December 2025): U.S. Geological Survey Scientific Investigations Report 2025–5089, 30 p., https://doi.org/10.3133/sir20255089.","productDescription":"Report: v, 30 p.; Data Release: Database","onlineOnly":"N","ipdsId":"IP-168198","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":498354,"rank":9,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255089/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2025-5089"},{"id":498313,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118883.htm","linkFileType":{"id":5,"text":"html"}},{"id":498183,"rank":7,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5089/sir20255089.xml"},{"id":498182,"rank":6,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5089/images"},{"id":498156,"rank":5,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2025/5089/versionHist.txt","size":"8.00 KB","linkFileType":{"id":2,"text":"txt"},"description":"SIR 2025-5089 version history"},{"id":495823,"rank":4,"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":495822,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P94UW017","text":"USGS data release","linkHelpText":"Suspended Sediment Data and Loads in the Fountain Creek Watershed, Colorado (ver 2.0, June 2025)"},{"id":495821,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5089/sir20255089.pdf","text":"Report","size":"4.74 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5089"},{"id":495820,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5089/coverthb2.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Fountain Creek watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -105.5,\n 39.5\n ],\n [\n -105.5,\n 38\n ],\n [\n -104,\n 38\n ],\n [\n -104,\n 39.5\n ],\n [\n -105.5,\n 39.5\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","edition":"Version 1.0: September 22, 2025; Version 1.1: December 30, 2025","contact":"Director, Colorado Water Science Center
U.S. Geological Survey
Box 25046, Mail Stop 415
Denver, CO 80225
Supporting the overarching goal to evaluate critical minerals nationwide, the mine waste characterization effort in the U.S. Geological Survey (USGS) Earth Mapping Resources Initiative has created a series of protocols to standardize sampling carried out under this effort by the participating State geological surveys and their cooperators. The protocols are based on published, reviewed methods that can be deployed in the field. The protocols include (1) collecting and processing composite samples of mine and mill waste, including tailings, waste rock, gangue, heap leach piles, ore stockpiles, slag, or other mineralized and processed materials and (2) collecting and preserving water samples from perpetual or long-term mine water sources. The protocols also specify information to document on field sheets and detail the collection of geospatial data. The analytical methods used by the USGS and USGS contract laboratories are described in this report, including the data delivery pathway for USGS-derived data.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/sir20255068","programNote":"Mineral Resources Program","usgsCitation":"Campbell, K.M., Seal, R.R., Piatak, N.M., Azain, J.S., Morrison, J.M., White, S.J., Manning, A.H., Walton-Day, K., Holloway, J.M., and Wang, B., 2025, Earth Mapping Resources Initiative protocols—Sampling hard-rock mine waste and perpetual mine water sources: U.S. Geological Survey Scientific Investigations Report 2025–5068, 22 p., https://doi.org/10.3133/sir20255068.","productDescription":"Report: viii, 22 p.; Appendix","onlineOnly":"Y","ipdsId":"IP-171986","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":495812,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2025/5068/sir20255068_Supplemental_AppendixFile.pdf","text":"Example Field Sheets","size":"172 KB","linkFileType":{"id":1,"text":"pdf"},"description":"Appendix for SIR 2025-5068","linkHelpText":"Example Earth MRI Mine Waste Characterization Field Sheets"},{"id":496041,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255068/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2025-5068"},{"id":495811,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5068/sir20255068.pdf","text":"Report","size":"1.76 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5068"},{"id":495810,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5068/coverthb.jpg"},{"id":495877,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5068/images"},{"id":495878,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5068/sir20255068.xml"}],"contact":"Director, Geology, Geophysics, and Geochemistry Science Center
U.S. Geological Survey
Box 25046, Mail Stop 973
Denver, CO 80225
Chinook salmon (Oncorhynchus tshawytscha) and Pacific lamprey (Entosphenus tridentatus) are native, anadromous fish species in the Siletz River Basin, western Oregon, that face many threats to their survival in freshwater and the ocean. The Confederated Tribes of Siletz Indians of Oregon seek to mitigate freshwater threats to Chinook salmon and Pacific lamprey, where possible, with habitat conservation and restoration efforts. This study was conducted to assist the Confederated Tribes of Siletz Indians of Oregon in documenting and understanding the hydrogeomorphic processes shaping present-day habitat conditions and assessing future habitat implications for Chinook salmon and Pacific lamprey along the main-stem Siletz River. As such, this study focused on understanding geomorphic processes and patterns of channel change, including lateral and vertical adjustments in channel position and changes in bed-material sediment (sands, gravels, and cobbles that mantle the channel bed), which collectively determine overall patterns of channel morphology and fluvial habitats. Objective One was to evaluate lateral changes in channel position, vertical changes in bed elevation, and longitudinal patterns in bed-material particle size along the Siletz River using detailed channel maps developed from aerial photographs collected from 1939 to 2016, long-term records of stage and discharge collected by the U.S. Geological Survey (USGS) near the City of Siletz, and sediment particle size data. Objective Two was to assess hydraulic conditions using one- and two-dimensional hydraulic models and transport capacity of bed-material sediment using bedload transport models and sediment particle size data for a range of discharge conditions. Objective Three was to identify potential burrowing habitat for lamprey larvae (PBH) along the Siletz River network and provide insights in local factors influencing PBH along the main-stem Siletz River. The overall findings are synthesized to describe habitat implications for Chinook salmon and Pacific lamprey under present-day and future conditions.
Results of Objective One, an evaluation of changes in channel position and bed elevations and longitudinal patterns in bed-material particle size along the Siletz River, include the following
Results of Objective Two, an evaluation of hydraulic and bedload transport conditions along the Siletz River, include the following
Results of Objective Three, an analysis of PBH for lamprey larvae, include the following
Together, these results suggest that most of the Siletz River between Wildcat Creek and the City of Siletz has had only modest vertical and lateral change between the 1930s and 2010s because of the bedrock in and along the main channel and the river’s relatively high transport capacity relative to bed-material sediment supply. However, localized sections of the Siletz River where the active channel widens, particularly at channel bends, exhibited some change in channel planform and the locations and area of gravel bars. In the future, moderate increases in autumn-winter discharge may not result in substantial changes in coarse gravel bars along the Siletz River but may result in selective transport of finer bed-material sediment (gravel, sands, and silts) that provide spawning habitats for Chinook salmon and Pacific lamprey and burrowing habitats for lamprey larvae. Assuming no substantial changes in bed-material sediment supply, increased bedload transport capacity may cause frequent entrainment of lamprey larvae that are burrowed in coarse sand deposits, suspension and downstream transport of salmon eggs incubating in gravels, and reductions in the areas of spawning gravels for Chinook salmon and Pacific lamprey. Exact implications of current and future discharge conditions for these species along the Siletz River depends on many factors, including sediment supply, local hydraulics, and the timing of flood events relative to fish life stages.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255063","collaboration":"Prepared in cooperation with the Confederated Tribes of Siletz Indians of Oregon","usgsCitation":"Jones, K.L., Keith, M.K., Harden, T.M., White, J.S., van de Wetering, S., and Dunham, J.B., 2025, Assessment of\nchannel morphology, hydraulics, and bedload transport along the Siletz River, western Oregon: U.S. Geological Survey\nScientific Investigations Report 2025–5063, 95 p., https://doi.org/10.3133/sir20255063.","productDescription":"Report: xii, 95 p.; 5 Data Releases","onlineOnly":"Y","ipdsId":"IP-127308","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":496021,"rank":11,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118884.htm","linkFileType":{"id":5,"text":"html"}},{"id":495760,"rank":10,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5063/sir20255063.XML"},{"id":495758,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1489NN8","text":"USGS data release","description":"USGS data release","linkHelpText":"One- and two-dimensional hydraulic models for the Siletz River, Oregon"},{"id":495757,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1N35MQN","text":"USGS data release","description":"USGS data release","linkHelpText":"Water surface elevation data from the Siletz River, 2017–18"},{"id":495751,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5063/coverthb.jpg"},{"id":495752,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5063/sir20255063.pdf","text":"Report","size":"28.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5063"},{"id":495753,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255063/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2025-5063"},{"id":495754,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9AWWRA0","text":"USGS data release","description":"USGS data release","linkHelpText":"Active channel mapping for the Siletz River, Oregon, 1939 to 2016"},{"id":495755,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P96ZXPP","text":"USGS data release","description":"USGS data release","linkHelpText":"Surficial and subsurface grain-size data for the Siletz River, Oregon, 2017–18"},{"id":495756,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9TIADK3","text":"USGS data release","description":"USGS data release","linkHelpText":"Modeled bedload transport capacity for the Siletz River, Oregon"},{"id":495759,"rank":9,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5063/images"}],"country":"United States","state":"Oregon","otherGeospatial":"Siletz River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -124.1,\n 45\n ],\n [\n -124.1,\n 44.333\n ],\n [\n -123.5,\n 44.333\n ],\n [\n -123.5,\n 45\n ],\n [\n -124.1,\n 45\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Oregon Water Science Center
U.S. Geological Survey
601 SW 2nd Avenue, Suite 1950
Portland, OR 97204
The Upper Mississippi River Restoration (UMRR) program, a broad partnership of State and Federal agencies administered by the U.S. Army Corps of Engineers, integrates ecosystem monitoring, research, and modeling to rehabilitate habitat and evaluate ecosystem trends over time in the Upper Mississippi River System. Hydrologic data are integral to the UMRR program because they are used in scientific research, decision-making, and restoration project planning. However, a lack of quantitative hydrologic data representing potential future conditions limits the ability to complete informative research on how future conditions may affect river ecology, achieve management goals, and design restoration projects for 50-year horizons.
The U.S. Geological Survey and the U.S. Army Corps of Engineers led a series of workshops with UMRR partners to (1) prioritize needs for understanding future hydrology, (2) discuss appropriate datasets that could address these needs, and (3) develop a plan for acquiring and distributing a hydrologic dataset of potential future conditions. Agency priorities for understanding future hydrology were broad, spanning ecologic, geomorphic, resource management, and engineering disciplines, and were identified for a range of spatial (project site, navigation pool, reach, system) and temporal (daily, seasonal, annual) scales. The LOcalized Constructed Analogs-Variable Infiltration Capacity-mizuRoute hydrologic data products were identified as a potential source of off-the-shelf data to meet UMRR priority needs but warranted a robust quantitative evaluation. The final meeting in the series scoped a proposal to evaluate the LOcalized Constructed Analogs-Variable Infiltration Capacity-mizuRoute hydrologic data products for use in UMRR applications, including contingencies if the data were determined to be unreliable.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20251050","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Van Appledorn, M., and Sawyer, L., 2025, Upper Mississippi River Restoration future hydrology meeting series: U.S. Geological Survey Open-File Report 2025–1050, 93 p., https://doi.org/10.3133/ofr20251050.","productDescription":"vii, 93 p.","numberOfPages":"106","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-144284","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":495840,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2025/1050/coverthb.jpg"},{"id":495844,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20251050/full"},{"id":495843,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2025/1050/images/"},{"id":495842,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2025/1050/ofr20251050.XML"},{"id":495841,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2025/1050/ofr20251050.pdf","text":"Report","size":"4.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2025-1050"}],"country":"United States","state":"Illinois, Iowa, Minnesota, Missouri, Wisconsin","otherGeospatial":"Upper Mississippi River system","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -89.2103238355043,\n 37.043422473537504\n ],\n [\n -87.69596012242188,\n 41.69069025518516\n ],\n [\n -89.11501122546446,\n 44.87351523241463\n ],\n [\n -89.14678376857329,\n 46.12049934311611\n ],\n [\n -92.37672035941334,\n 46.134727618766064\n ],\n [\n -94.31468231391703,\n 47.910742701911886\n ],\n [\n -96.86686171848238,\n 47.08812323847167\n ],\n [\n -94.08172387608387,\n 40.82297944373079\n ],\n [\n -89.40096330837447,\n 37.051916822243555\n ],\n [\n -89.2103238355043,\n 37.043422473537504\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Upper Midwest Environmental Sciences Center
U.S. Geological Survey
2630 Fanta Reed Road
La Crosse, Wisconsin 54603
A series of workshops was held so participants from several agencies could work together to prioritize needs for understanding future hydrologic scenarios, discuss appropriate datasets that could address these needs, and develop a plan for acquiring and distributing a hydrologic dataset representing potential future conditions. Agency priorities for understanding future hydrology spanned ecologic, geomorphic, resource management, and engineering disciplines and were identified for a range of spatial (project site, navigation pool, reach, system) and temporal (daily, seasonal, annual) scales. Participants described desired characteristics of a hydrologic dataset of potential future conditions that could meet agency priority needs and developed a workflow to evaluate a readily available data product.
","publicationDate":"2025-09-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Van Appledorn, Molly 0000-0002-8029-0014","orcid":"https://orcid.org/0000-0002-8029-0014","contributorId":205785,"corporation":false,"usgs":true,"family":"Van Appledorn","given":"Molly","email":"","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":949216,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sawyer, Lucie","contributorId":345904,"corporation":false,"usgs":false,"family":"Sawyer","given":"Lucie","email":"","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":949217,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70272029,"text":"70272029 - 2025 - A regional model comparison between MODPATH and MT3D of groundwater travel time distributions","interactions":[],"lastModifiedDate":"2025-12-01T16:48:27.452347","indexId":"70272029","displayToPublicDate":"2025-09-22T10:56:36","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3825,"text":"Groundwater","active":true,"publicationSubtype":{"id":10}},"title":"A regional model comparison between MODPATH and MT3D of groundwater travel time distributions","docAbstract":"Groundwater quality changes in wells and streams lag behind changes to land use due to groundwater travel times. Two contaminant transport methods were compared to assess differences in their simulated travel time distributions (TTDs) to streams and wells in the Wisconsin Central Sands. MODPATH simulates advective groundwater flow with particle tracking, while MT3D simulates age-mass using a finite difference solution without dispersion to allow for direct comparison of the two methods. MODPATH appropriately simulates groundwater TTDs from the water table to surface discharge but is subject to inaccuracies at weak-sink well cells due to the flow-model grid discretization and imprecise location of well discharge within well cells. MT3D better represents weak-sink well cells since it removes mass in proportion to the prescribed pumping rate, although travel time within well cells is neglected. Conversely, MT3D's treatment of surface water boundary cells is not as accurate as MODPATH because mass should be removed from the water table rather than the full cell volume. MT3D simulations of TTDs can also be confounded by the instantaneous vertical distribution of mass introduced throughout recharge cells instead of at the water table, which initiates mass along deeper flow paths. We evaluated 9 MODPATH and 13 MT3D implementations, generating differences in median travel times of up to 18 years. Both methods have strengths and weaknesses, with MT3D better representing weak-sink well cell behavior and MODPATH better representing surficial recharge and discharge. The effect of these characteristics on simulated TTDs, along with ideas for ameliorating method weaknesses, is discussed.
","language":"English","publisher":"Wiley","doi":"10.1111/gwat.70024","usgsCitation":"Baker, E.A., Juckem, P., Feinstein, D.T., and Hart, D., 2025, A regional model comparison between MODPATH and MT3D of groundwater travel time distributions: Groundwater, v. 63, no. 6, p. 861-873, https://doi.org/10.1111/gwat.70024.","productDescription":"13 p.","startPage":"861","endPage":"873","ipdsId":"IP-174512","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":496428,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/gwat.70024","text":"Publisher Index Page"},{"id":496413,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Central Sands study area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -89.76677243303999,\n 44.62588647709572\n ],\n [\n -89.76677243303999,\n 43.759169553502744\n ],\n [\n -88.89566146882221,\n 43.759169553502744\n ],\n [\n -88.89566146882221,\n 44.62588647709572\n ],\n [\n -89.76677243303999,\n 44.62588647709572\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"63","issue":"6","noUsgsAuthors":false,"publicationDate":"2025-09-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Baker, Emily A. 0000-0003-3443-5419","orcid":"https://orcid.org/0000-0003-3443-5419","contributorId":361983,"corporation":false,"usgs":false,"family":"Baker","given":"Emily","middleInitial":"A.","affiliations":[{"id":86409,"text":"Hamilton College, Wisconsin Geological and Natural History Survey","active":true,"usgs":false}],"preferred":false,"id":949772,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Juckem, Paul 0000-0002-3613-1761 pfjuckem@usgs.gov","orcid":"https://orcid.org/0000-0002-3613-1761","contributorId":214445,"corporation":false,"usgs":true,"family":"Juckem","given":"Paul","email":"pfjuckem@usgs.gov","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":949773,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Feinstein, Daniel T. 0000-0003-1151-2530","orcid":"https://orcid.org/0000-0003-1151-2530","contributorId":361984,"corporation":false,"usgs":false,"family":"Feinstein","given":"Daniel","middleInitial":"T.","affiliations":[{"id":40828,"text":"University of Wisconsin - Milwaukee","active":true,"usgs":false}],"preferred":false,"id":949774,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hart, David J. 0000-0001-8027-480X","orcid":"https://orcid.org/0000-0001-8027-480X","contributorId":292693,"corporation":false,"usgs":false,"family":"Hart","given":"David J.","affiliations":[{"id":39043,"text":"Wisconsin Geological and Natural History Survey","active":true,"usgs":false}],"preferred":false,"id":949775,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70272007,"text":"70272007 - 2025 - Persistence of a declining anuran species across its distribution","interactions":[],"lastModifiedDate":"2025-09-30T15:04:08.866478","indexId":"70272007","displayToPublicDate":"2025-09-22T07:50:48","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Persistence of a declining anuran species across its distribution","docAbstract":"Information on a species’ population dynamics, such as changes in abundance and distribution, can be used to identify declining populations and initiate conservation efforts and protections. For the Ornate Chorus Frog (Pseudacris ornata), anecdotal observations of local extirpation and population declines have been noted, but trends in its range-wide population status are generally unknown. We used 2227 verified records of Ornate Chorus Frog presence from across the species’ distribution, grouped into 407 populations, and a modified Cormack-Jolly-Seber survival analysis to estimate the probability that historical Ornate Chorus Frog populations persist in the year 2024. Our results suggested that > 36% of historical Ornate Chorus Frog populations are possibly extirpated (probability of persistence < 0.5) and that 33% of populations had a probability of persistence > 0.9. Many of these extant populations occurred in northwestern Florida, southeastern Alabama, and southern Georgia, USA. The probability of persistence was positively influenced by habitat suitability and mean winter precipitation and negatively influenced by urban imperviousness. Ornate Chorus Frogs in protected areas had a higher average probability of persistence compared to populations that were not in protected areas. Our study fills a knowledge gap by identifying regions where Ornate Chorus Frog populations are likely thriving and regions where they may be extinct.
","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0332991","usgsCitation":"Koen, E.L., Ellington, E.H., Barichivich, W.J., Kochman, H., Enge, K.M., and Walls, S.E., 2025, Persistence of a declining anuran species across its distribution: PLoS ONE, v. 20, no. 9, e0332991, 19 p., https://doi.org/10.1371/journal.pone.0332991.","productDescription":"e0332991, 19 p.","ipdsId":"IP-174507","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":496326,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0332991","text":"Publisher Index Page"},{"id":496261,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alabama, Florida, Georgia, Louisiana, Mississippi, North Carolina, South Carolina","otherGeospatial":"southeastern United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -91.71784743874963,\n 31.75977874337856\n ],\n [\n -91.41887328015432,\n 30.0038991640329\n ],\n [\n -81.31625954563552,\n 29.20277624190848\n ],\n [\n -76.06558770828089,\n 36.35992621029155\n ],\n [\n -78.31479749126278,\n 36.381895038050445\n ],\n [\n -79.79602141182846,\n 34.412235399163784\n ],\n [\n -83.52645511537602,\n 32.46454458803602\n ],\n [\n -86.36151154434091,\n 32.65274179593238\n ],\n [\n -88.57486167831063,\n 31.21366512354828\n ],\n [\n -91.71784743874963,\n 31.75977874337856\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"20","issue":"9","noUsgsAuthors":false,"publicationDate":"2025-09-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Koen, Erin L. 0000-0001-9481-7692","orcid":"https://orcid.org/0000-0001-9481-7692","contributorId":330539,"corporation":false,"usgs":false,"family":"Koen","given":"Erin","email":"","middleInitial":"L.","affiliations":[{"id":78927,"text":"Cherokee Nation Systems Solutions","active":true,"usgs":false}],"preferred":false,"id":949695,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ellington, Edward Hance","contributorId":361948,"corporation":false,"usgs":false,"family":"Ellington","given":"Edward","middleInitial":"Hance","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":949696,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barichivich, William J. 0000-0003-1103-6861","orcid":"https://orcid.org/0000-0003-1103-6861","contributorId":216371,"corporation":false,"usgs":true,"family":"Barichivich","given":"William","middleInitial":"J.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":949697,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kochman, Howard","contributorId":347042,"corporation":false,"usgs":false,"family":"Kochman","given":"Howard","affiliations":[{"id":12545,"text":"USGS retired","active":true,"usgs":false}],"preferred":false,"id":949698,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Enge, Kevin M.","contributorId":361950,"corporation":false,"usgs":false,"family":"Enge","given":"Kevin","middleInitial":"M.","affiliations":[{"id":12556,"text":"Florida Fish and Wildlife Conservation Commission","active":true,"usgs":false}],"preferred":false,"id":949699,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Walls, Susan E. 0000-0001-7391-9155","orcid":"https://orcid.org/0000-0001-7391-9155","contributorId":209862,"corporation":false,"usgs":true,"family":"Walls","given":"Susan","middleInitial":"E.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":949700,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70271928,"text":"70271928 - 2025 - Bears avoid residential neighborhoods in response to the experimental reduction of anthropogenic attractants","interactions":[],"lastModifiedDate":"2025-09-24T14:52:24.787526","indexId":"70271928","displayToPublicDate":"2025-09-22T07:45:27","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3910,"text":"Frontiers in Ecology and Evolution","onlineIssn":"2296-701X","active":true,"publicationSubtype":{"id":10}},"title":"Bears avoid residential neighborhoods in response to the experimental reduction of anthropogenic attractants","docAbstract":"Introduction: Urbanization is an extreme form of land use alteration, with human development driving changes in the distribution of resources available to wildlife. Some large carnivores have learned to exploit anthropogenic food resources in urban development, resulting in human-carnivore conflict that can have detrimental impacts to people and carnivores, as exemplified by American black bears. Management agencies commonly promote the use of bear-resistant garbage containers for reducing conflicts, but little is known about the actual behavioral responses of bears to this intervention.
Methods: To understand whether black bears alter their behavior in response to changes in residential waste management, we investigated patterns of bear behavior in Durango, Colorado, where anthropogenic attractants were experimentally manipulated. Using location data from collared black bears, we modeled resource selection and movement in response to areas that had received bear-resistant garbage containers compared to those that did not.
Results: Bears avoided residential areas where garbage availability had been reduced, and this avoidance response increased over subsequent years, potentially suggesting that bears were learning from the management intervention. Bear movement rates, however, were not notably affected by the garbage reduction.
Discussion: Our findings highlight the importance of reducing the availability of anthropogenic attractants for changing bear behavior and reducing risk of urban human-bear conflict, and that these responses can strengthen over time as bears learn from the management intervention.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/fevo.2025.1657106","usgsCitation":"Venumière-Lefebvre, C.C., Johnson, H.E., Breck, S.W., Alldredge, M.W., and Crooks, K.R., 2025, Bears avoid residential neighborhoods in response to the experimental reduction of anthropogenic attractants: Frontiers in Ecology and Evolution, v. 13, 1657106, 16 p., https://doi.org/10.3389/fevo.2025.1657106.","productDescription":"1657106, 16 p.","ipdsId":"IP-180355","costCenters":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":496150,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fevo.2025.1657106","text":"Publisher Index Page"},{"id":496001,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","city":"Durango","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -108.03713489993451,\n 37.40217470571062\n ],\n [\n -108.03713489993451,\n 37.19518187022882\n ],\n [\n -107.73739324514958,\n 37.19518187022882\n ],\n [\n -107.73739324514958,\n 37.40217470571062\n ],\n [\n -108.03713489993451,\n 37.40217470571062\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"13","noUsgsAuthors":false,"publicationDate":"2025-09-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Venumière-Lefebvre, Cassandre C.","contributorId":361762,"corporation":false,"usgs":false,"family":"Venumière-Lefebvre","given":"Cassandre","middleInitial":"C.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":949407,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Heather E. 0000-0001-5392-7676 hejohnson@usgs.gov","orcid":"https://orcid.org/0000-0001-5392-7676","contributorId":205919,"corporation":false,"usgs":true,"family":"Johnson","given":"Heather","email":"hejohnson@usgs.gov","middleInitial":"E.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":949408,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Breck, Stewart W.","contributorId":361764,"corporation":false,"usgs":false,"family":"Breck","given":"Stewart","middleInitial":"W.","affiliations":[{"id":36589,"text":"USDA","active":true,"usgs":false}],"preferred":false,"id":949409,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Alldredge, Mathew W.","contributorId":361766,"corporation":false,"usgs":false,"family":"Alldredge","given":"Mathew","middleInitial":"W.","affiliations":[{"id":39887,"text":"Colorado Parks and Wildlife","active":true,"usgs":false}],"preferred":false,"id":949410,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Crooks, Kevin R.","contributorId":361768,"corporation":false,"usgs":false,"family":"Crooks","given":"Kevin","middleInitial":"R.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":949411,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70271737,"text":"70271737 - 2025 - Apicomplexan and non-metazoan microeukaryotes in the thermosensitive reef-building coral Acropora hyacinthus shift in abundance throughout an extreme coral bleaching event","interactions":[],"lastModifiedDate":"2025-09-23T14:40:41.565808","indexId":"70271737","displayToPublicDate":"2025-09-21T09:34:49","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3912,"text":"Frontiers in Marine Science","onlineIssn":"2296-7745","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Apicomplexan and non-metazoan microeukaryotes in the thermosensitive reef-building coral Acropora hyacinthus shift in abundance throughout an extreme coral bleaching event","title":"Apicomplexan and non-metazoan microeukaryotes in the thermosensitive reef-building coral Acropora hyacinthus shift in abundance throughout an extreme coral bleaching event","docAbstract":"Coral reefs play vital roles in global marine systems and are currently facing increased threats of bleaching. Coral bleaching is heavily influenced by the host-associated microeukaryote community – most notably the dinoflagellate family Symbiodiniaceae. The apicomplexan family Corallicolidae, is the second most abundant member of the microeukaryote community, yet their role in coral health is largely unknown. To explore the role that this apicomplexan and the greater non-metazoan microeukaryotic community play in coral health, samples of a thermally sensitive scleractinian coral, Acropora hyacinthus, were collected over the course of a severe coral bleaching event and its aftermath. Through 18S rRNA gene sequencing analysis, we found that taxa within the family Corallicolidae were relatively enriched in corals during, and immediately after, the severe bleaching event as compared to before or one year after. Although utilizing 18S rRNA gene sequencing methods is not the standard for Symbiodiniaceae community profiling, we were able to observe symbiont shuffling among the Symbiodiniaceae communities, as the dominant algal symbiont shifted from the genus Cladocopium to the genus Symbiodinium following the bleaching event. Furthermore, the non-metazoan microeukaryote community displayed a general shift towards a state of dysbiosis; evidenced by substantial changes in both microeukaryote community composition and dispersion. These results offer insight into the dynamics of apicomplexans throughout the course of an increasingly common global coral reef stressor.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/fmars.2025.1626071","usgsCitation":"Peterson, A., Patton, S., Schmeltzer, E.R., Grupstra, C., Howe-Kerr, L., Klinges, J.G., Maher, R., Messyasz, A., Seabrook, S., Thurber, A., Correa, A., and Vega Thurber, R., 2025, Apicomplexan and non-metazoan microeukaryotes in the thermosensitive reef-building coral Acropora hyacinthus shift in abundance throughout an extreme coral bleaching event: Frontiers in Marine Science, v. 12, 1626071, 15 p., https://doi.org/10.3389/fmars.2025.1626071.","productDescription":"1626071, 15 p.","ipdsId":"IP-180885","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":496144,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fmars.2025.1626071","text":"Publisher Index Page"},{"id":495897,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"French Polynesia","otherGeospatial":"Mo’orea","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -149.94261835394644,\n -17.463455039196617\n ],\n [\n -149.94261835394644,\n -17.612716041327616\n ],\n [\n -149.73838596029304,\n -17.612716041327616\n ],\n [\n -149.73838596029304,\n -17.463455039196617\n ],\n [\n -149.94261835394644,\n -17.463455039196617\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"12","noUsgsAuthors":false,"publicationDate":"2025-09-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Peterson, Athena","contributorId":361686,"corporation":false,"usgs":false,"family":"Peterson","given":"Athena","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":949231,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Patton, Sunni","contributorId":361687,"corporation":false,"usgs":false,"family":"Patton","given":"Sunni","affiliations":[{"id":86323,"text":"Oregon State University; University of California;","active":true,"usgs":false}],"preferred":false,"id":949232,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schmeltzer, Emily Rose 0000-0002-5390-4308","orcid":"https://orcid.org/0000-0002-5390-4308","contributorId":361688,"corporation":false,"usgs":true,"family":"Schmeltzer","given":"Emily","middleInitial":"Rose","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":949233,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Grupstra, Carsten","contributorId":361689,"corporation":false,"usgs":false,"family":"Grupstra","given":"Carsten","affiliations":[{"id":86324,"text":"Rice University; Boston University; Florida Atlantic University","active":true,"usgs":false}],"preferred":false,"id":949234,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Howe-Kerr, Lauren","contributorId":361690,"corporation":false,"usgs":false,"family":"Howe-Kerr","given":"Lauren","affiliations":[{"id":86325,"text":"Rice University; Minderoo Foundation","active":true,"usgs":false}],"preferred":false,"id":949235,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Klinges, J. 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When singing rates are tied to breeding stage, the rate at which birds are available for detection by surveyors can also show seasonal patterns that may shift with spring phenology. As the timing of peak bird availability changes over years, monitoring programs that do not account for changing availability could incorrectly conclude that there is a change in population size. We used a 20-yr point-count dataset to test for relationships between bird availability and spring vegetation phenology for 27 species in boreal Alaska. Nine of 22 migratory species showed a significant effect of day of spring (DOS) on availability, usually with availability declining over the survey window (late spring and early summer). In contrast, 3 of 5 resident species showed availability increasing over the survey window. We then conducted a simulation study to evaluate how changing spring phenology could affect estimates of population trend under a static survey window. We found that including DOS in the model as a covariate of availability prevented bias in the trend estimates and did not reduce precision. However, when the model ignored the effect of DOS on availability, population trend estimates were often significantly biased when spring phenology was advancing. Our study adds to previous evidence that bird availability is often related to spring phenology, and demonstrates that failing to account for seasonal changes in availability could result in the spurious estimation of a population trend when spring phenology changes over time. In some cases, the bias could be large enough to change species status assessments under IUCN Red List Criteria. Monitoring programs for birds and other taxa with seasonally varying availability could avoid bias by simply measuring and modeling the relationship between DOS and availability.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/ornithapp/duaf052","usgsCitation":"Weiser, E.L., Johnson, J., Matsuoka, S.M., and Handel, C.M., 2025, Accounting for seasonal patterns in bird availability prevents biased population trend estimates with advancing spring phenology: Ornithological Applications, v. 127, no. 4, p. 1-11, https://doi.org/10.1093/ornithapp/duaf052.","productDescription":"11 p.","startPage":"1","endPage":"11","ipdsId":"IP-178417","costCenters":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":496081,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","volume":"127","issue":"4","noUsgsAuthors":false,"publicationDate":"2025-09-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Weiser, Emily L. 0000-0003-1598-659X","orcid":"https://orcid.org/0000-0003-1598-659X","contributorId":213770,"corporation":false,"usgs":true,"family":"Weiser","given":"Emily","email":"","middleInitial":"L.","affiliations":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"preferred":true,"id":949463,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, James","contributorId":173063,"corporation":false,"usgs":false,"family":"Johnson","given":"James","email":"","affiliations":[],"preferred":false,"id":949464,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Matsuoka, Steven M. 0000-0001-6415-1885 smatsuoka@usgs.gov","orcid":"https://orcid.org/0000-0001-6415-1885","contributorId":184173,"corporation":false,"usgs":true,"family":"Matsuoka","given":"Steven","email":"smatsuoka@usgs.gov","middleInitial":"M.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":949465,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Handel, Colleen M. 0000-0002-0267-7408 cmhandel@usgs.gov","orcid":"https://orcid.org/0000-0002-0267-7408","contributorId":3067,"corporation":false,"usgs":true,"family":"Handel","given":"Colleen","email":"cmhandel@usgs.gov","middleInitial":"M.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":949466,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70274071,"text":"70274071 - 2025 - Beyond the mangroves: A global synthesis of tidal forested wetland types, drivers and future information opportunities","interactions":[],"lastModifiedDate":"2026-02-23T15:34:30.951807","indexId":"70274071","displayToPublicDate":"2025-09-20T09:23:24","publicationYear":"2025","noYear":false,"publicationType":{"id":27,"text":"Preprint"},"publicationSubtype":{"id":32,"text":"Preprint"},"title":"Beyond the mangroves: A global synthesis of tidal forested wetland types, drivers and future information opportunities","docAbstract":"There is increasing awareness of the global diversity of tidal forested wetlands (TFWs) and their significance in the provision of ecosystem services. These ecosystems, including mangrove forests, tidal freshwater forested wetlands, supratidal forests and transitional forests together span multiple climatic zones, geomorphic settings, and inundation and salinity regimes. We utilise case studies across five continents to demonstrate the state of knowledge among TFWs. Intertidal mangroves are the best-defined of the TFWs thanks to decades of research on their geomorphology, hydrology and ecology across their broad distribution. Non-mangrove forest settings, however, demonstrate more diverse hydrological, biochemical and vegetation conditions. In many cases, non-mangrove forests are situated at upper intertidal or supratidal elevations, where surface waters and groundwater are subject to interactions between tides freshwater inputs. Salinity datasets show variations ranging from tidal freshwater forested wetlands and ‘low-salinity mangroves’ to mesohaline or marine salinities, often with high temporal variability. While the floristic composition of non-mangrove forests vary among biogeographic regions, locally dominant TFW species are commonly distributed beyond the tidal niche into non-tidal wetland and upland forests. This presents challenges for traditional remote sensing approaches to ecosystem mapping, which are mostly lacking for non-mangrove forests. Geomorphic approaches and developments in machine learning offer opportunities to address this.
","language":"English","publisher":"Earth ArXiv","doi":"10.31223/X5ZF2B","usgsCitation":"Kelleway, J.J., Noe, G.E., Krauss, K., Brophy, L., Conner, W.H., Duberstein, J.A., Friess, D.A., Gedan, K., White, E., Adame, M.F., Adams, J.B., Carvalho, R.C., Freddie, A., Ikenna, I.N., Ocasio, E.R., Owers, C.J., Sasmito, S., Swales, A., Stewart-Sinclair, P., Ward, R.D., Zabarte-Maeztu, I., 2025, Beyond the mangroves: A global synthesis of tidal forested wetland types, drivers and future information opportunities, preprint posted September 20, 2025, https://doi.org/10.31223/X5ZF2B.","productDescription":"85 p.","ipdsId":"IP-185904","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":500404,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2025-09-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Kelleway, J. 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Overall, TE water withdrawal and consumption trends declined across CONUS by 14,335 and 278 million liters/day, respectively. Decreasing water withdrawal and consumption trends for TE plants are driven largely by switching from coal-fired plants to other generation technologies. TE plant cooling system technology has also changed, with large declining trends for TE plants using once-through cooling systems and small increasing consumption trends for TE plants using recirculating tower cooling systems. Fifteen hydrologic regions have decreasing trends in withdrawals and consumption. The largest decreases are for coal-fired plants using once-through freshwater cooling systems in the Great Lakes and Ohio hydrologic regions. Natural gas combined cycle plants with recirculating tower cooling systems have increased water consumption trends across most of the CONUS hydrologic regions. Some TE plants with recirculating tower or once-through cooling systems withdraw water volumes that on average are close to or exceed average simulated streamflows. Most of these situations occur in the central and eastern U.S., potentially leading to water availability issues among competing water needs, ecosystem impacts from thermal pollution, and power generation constraints.
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2021","interactions":[],"lastModifiedDate":"2026-02-03T15:29:46.906418","indexId":"sir20255079","displayToPublicDate":"2025-09-19T12:25:00","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-5079","displayTitle":"Microbial Source Tracking in Cedar and Crane Creeks Near Curtice, Ohio, 2021","title":"Microbial source tracking in Cedar and Crane Creeks near Curtice, Ohio, 2021","docAbstract":"Elevated concentrations of Escherichia coli (E. coli) bacteria and signs of sewage lead to impairment of Cedar and Crane Creeks near the town of Curtice, Ohio. In 2021, the U.S. Geological Survey, in cooperation with Ohio Environmental Protection Agency, collected samples and analyzed them for concentrations of E. coli and microbial source tracking (MST) markers to help characterize the locations and sources of fecal contamination and better inform potential remediation strategies. The study included a total of 118 samples collected at 12 sites (6 on Cedar Creek and 6 on Crane Creek) from May to September 2021 during wet and dry weather conditions.
All samples were analyzed for E. coli concentrations, and human and canine-associated MST markers. A subset of samples was analyzed for MST markers associated with swine, ruminant, cattle, horse, waterfowl, and poultry. Human-origin fecal contamination was found at all sites sampled in this study and concentrations of the human-associated MST marker HF183/BacR287 were significantly correlated with E. coli concentrations. The HF183/BacR287 marker was detected in 114 of 118 samples and the detection frequency in samples at each site ranged from 90 to 100 percent. E. coli concentrations exceeded the Ohio Environmental Protection Agency’s regulatory statistical threshold (410 most probable number of E. coli per 100 milliliters) in 91 percent of samples.
These findings verified that Cedar and Crane Creeks are impaired by bacteria, and the HF183/BacR287 marker results support that human-origin fecal contamination is the dominant contributor to that impairment. The canine-associated MST marker BacCan was also prevalent in collected samples (detected in 112 of 118 samples); however, BacCan can also be detected in human waste, so it is not feasible to ascertain whether canine feces is a source of contamination in these watersheds.
Human fecal contamination was nearly uniform among sites, but the Martin Williston Road ditch effluent site along Crane Creek had a significantly higher median HF183/BacR287 concentration than the other Crane Creek sites. Results indicate that the Martin Williston Road ditch is a potential source of human-origin fecal contamination to Crane Creek. There is likely additional human fecal contamination upstream from the study area.
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6460 Busch Blvd, Suite 100
Columbus, OH 43229
Emerging infectious diseases and biological invasions pose increasing threats to public and ecosystems health. Proactive measures—such as prevention and surveillance taken before initial detection of the pathogen or species—are essential to ensure minimal spread prior to first detection. We developed an optimization model to determine where, when, and how much effort should be allocated to prevention versus surveillance. The model accounts for imperfect detection, system dynamics, spatial heterogeneity in risk and costs and is scalable to large landscapes. We found that the most cost-effective strategy is to maintain the prevention and surveillance efforts at stable equilibrium for the majority of the time, with deviations occurring only initially to steer the system toward the equilibrium. The equilibrium effort is jointly determined by the introduction risk, management costs, and total budget. Application of this model to chronic wasting disease in New York State suggests that the optimal strategy could reduce the cumulative disease cases before initial detection by an average of 22% compared to current practice. The optimal surveillance strategy could detect the disease on average over 8 mo earlier than the current strategy.
","language":"English","publisher":"National Academy of Sciences","doi":"10.1073/pnas.2507202122","usgsCitation":"Wang, J., Hanley, B.J., Thompson, N.E., Gong, Y., Walsh, D.P., Gonzalez-Crespo, C., Huang, Y., Booth, J.G., Caudell, J.N., Miller, L.A., Schuler, K.L., 2025, Strategic planning of prevention and surveillance for emerging diseases and invasive species: PNAS, v. 122, no. 39, e2507202122, 9 p., https://doi.org/10.1073/pnas.2507202122.","productDescription":"e2507202122, 9 p.","ipdsId":"IP-177913","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":500578,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/12501194","text":"External Repository"},{"id":500349,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"122","issue":"39","noUsgsAuthors":false,"publicationDate":"2025-09-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Wang, Jue","contributorId":211355,"corporation":false,"usgs":false,"family":"Wang","given":"Jue","email":"","affiliations":[],"preferred":false,"id":956087,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hanley, Brenda J.","contributorId":366605,"corporation":false,"usgs":false,"family":"Hanley","given":"Brenda","middleInitial":"J.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":956088,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thompson, Noelle E.","contributorId":366606,"corporation":false,"usgs":false,"family":"Thompson","given":"Noelle","middleInitial":"E.","affiliations":[{"id":36225,"text":"Western Association of Fish and Wildlife Agencies","active":true,"usgs":false}],"preferred":false,"id":956089,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gong, Yu","contributorId":366607,"corporation":false,"usgs":false,"family":"Gong","given":"Yu","affiliations":[{"id":34006,"text":"Queen’s University","active":true,"usgs":false}],"preferred":false,"id":956090,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Walsh, Daniel P. 0000-0002-7772-2445","orcid":"https://orcid.org/0000-0002-7772-2445","contributorId":219539,"corporation":false,"usgs":true,"family":"Walsh","given":"Daniel","email":"","middleInitial":"P.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":956091,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gonzalez-Crespo, Carlos","contributorId":366611,"corporation":false,"usgs":false,"family":"Gonzalez-Crespo","given":"Carlos","affiliations":[{"id":35327,"text":"University of California – Davis","active":true,"usgs":false}],"preferred":false,"id":956092,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Huang, Yitong","contributorId":366612,"corporation":false,"usgs":false,"family":"Huang","given":"Yitong","affiliations":[{"id":35327,"text":"University of California – Davis","active":true,"usgs":false}],"preferred":false,"id":956093,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Booth, James G.","contributorId":366613,"corporation":false,"usgs":false,"family":"Booth","given":"James","middleInitial":"G.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":956094,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Caudell, Joe N.","contributorId":366614,"corporation":false,"usgs":false,"family":"Caudell","given":"Joe","middleInitial":"N.","affiliations":[{"id":55448,"text":"Indiana Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":956095,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Miller, Landon A.","contributorId":366615,"corporation":false,"usgs":false,"family":"Miller","given":"Landon","middleInitial":"A.","affiliations":[{"id":13678,"text":"New York State Department of Environmental Conservation","active":true,"usgs":false}],"preferred":false,"id":956096,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Schuler, Krysten L.","contributorId":366616,"corporation":false,"usgs":false,"family":"Schuler","given":"Krysten","middleInitial":"L.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":956097,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70274037,"text":"70274037 - 2025 - Ice Age biogeography corresponds with current climate vulnerability of freshwater fishes","interactions":[],"lastModifiedDate":"2026-02-23T17:00:47.816108","indexId":"70274037","displayToPublicDate":"2025-09-19T09:53:05","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1696,"text":"Freshwater Biology","active":true,"publicationSubtype":{"id":10}},"title":"Ice Age biogeography corresponds with current climate vulnerability of freshwater fishes","docAbstract":"1. Both local environmental factors and historical biogeography shape ecological communities, but determining which historical biogeographical patterns correspond with contemporary climate vulnerability is an underused conservation method. The historical colonization patterns of freshwater fishes following the Pleistocene (“Ice Age”) glaciations offers an ideal model for comparing historical biogeography and climate-change vulnerability.
2. We used current thermal niches and future stream-temperature projections to estimate the climate vulnerability of 29 Great Plains and Rocky Mountain fishes that we classified as either early or late colonists of the region in the wake of glacial retreat (~19,000 years ago).
3. Ninety-three percent of the most vulnerable species were amongst the earliest colonists of the region and we consider them “postglacial-pioneer species”. Median predicted site loss (number of historically occupied sites predicted to become too warm by end-of-century) was 0% for late colonizing species and 33% for early colonizing species.
4. We provide empirical evidence that postglacial-pioneer fishes are uniquely vulnerable to climate change, and we suggest this may apply to many taxa from formerly glaciated regions. More broadly, we demonstrate that evaluating the relationship between current species-environment patterns and historical biogeography may be a fruitful avenue for future climate change and conservation research.
","language":"English","publisher":"Wiley","doi":"10.1111/fwb.70098","usgsCitation":"Clancy, N.G., Budy, P.E., Walters, A.W., 2025, Ice Age biogeography corresponds with current climate vulnerability of freshwater fishes: Freshwater Biology, v. 70, no. 9, e70098, 11 p., https://doi.org/10.1111/fwb.70098.","productDescription":"e70098, 11 p.","ipdsId":"IP-160661","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":500423,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"North America","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -118.30686503555248,\n 65.96941120658738\n ],\n [\n -124.14315775412638,\n 45.060194959039514\n ],\n [\n -117.50546486911188,\n 33.44662341525755\n ],\n [\n -85.06334833163905,\n 30.623810459514957\n ],\n [\n -64.09085041980521,\n 45.76599507995419\n ],\n [\n -69.37510349475363,\n 64.53352486678543\n ],\n [\n -118.30686503555248,\n 65.96941120658738\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"70","issue":"9","noUsgsAuthors":false,"publicationDate":"2025-09-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Clancy, Niall G.","contributorId":366799,"corporation":false,"usgs":false,"family":"Clancy","given":"Niall","middleInitial":"G.","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":956244,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Budy, Phaedra E. 0000-0002-9918-1678 pbudy@usgs.gov","orcid":"https://orcid.org/0000-0002-9918-1678","contributorId":140028,"corporation":false,"usgs":true,"family":"Budy","given":"Phaedra","email":"pbudy@usgs.gov","middleInitial":"E.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":956245,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Walters, Annika W. 0000-0002-8638-6682 awalters@usgs.gov","orcid":"https://orcid.org/0000-0002-8638-6682","contributorId":4190,"corporation":false,"usgs":true,"family":"Walters","given":"Annika","email":"awalters@usgs.gov","middleInitial":"W.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":956246,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70271479,"text":"sir20255082 - 2025 - Methods for estimating selected low-flow statistics at gaged and ungaged stream sites in Massachusetts","interactions":[],"lastModifiedDate":"2026-02-03T15:29:05.375527","indexId":"sir20255082","displayToPublicDate":"2025-09-19T09:50:00","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-5082","displayTitle":"Methods for Estimating Selected Low-Flow Statistics at Gaged and Ungaged Stream Sites in Massachusetts","title":"Methods for estimating selected low-flow statistics at gaged and ungaged stream sites in Massachusetts","docAbstract":"The U.S. Geological Survey, in cooperation with the Massachusetts Department of Conservation and Recreation, Office of Water Resources, computed selected at-site streamflow statistics at U.S. Geological Survey streamgages in and near Massachusetts and developed regional regression equations for estimating selected streamflows at ungaged stream sites in Massachusetts. Two sets of regional regression equations were developed: (1) the “mainland” equations, for mainland Massachusetts excluding the area covered by the second set, and (2) the “southeastern” equations, for the Plymouth-Carver-Kingston-Duxbury aquifer area in southeastern Massachusetts and for Cape Cod. The regression equations and at-site statistics may be used by Federal, State, and local water managers in addressing water-resources issues relevant in Massachusetts.
Regional regression analyses for the mainland equations were developed to estimate the following 27 streamflow statistics: 99-, 98-, 95-, 90-, 85-, 80-, 75-, 70-, 60-, and 50-percent flow durations; monthly June, July, August, and September 90- and 50-percent flow durations; February, June, and August median of the monthly means; harmonic mean; and medians of the following annual low-flow frequency statistics: 7-day; 7-day, 2-year; 7-day, 10-year; 30-day, 2-year; and 30-day, 10-year. The analyses used 81 streamgages with minimal to no regulations in and near Massachusetts. The regression analyses determined that four basin characteristics—drainage area, combined hydrologic soils A and B, streamflow variability index, and annual mean temperature—were the only significant explanatory variables for the different mainland equations.
Regional regression equations were developed for the Plymouth-Carver-Kingston-Duxbury aquifer area in southeastern Massachusetts and Cape Cod, because surface-water drainage areas and groundwater contributing areas do not always coincide in this area of the State. The regression analyses to estimate 10 flow durations from the 99th to 50th percentiles used 18 streamflow sites with some occasional minor regulations—because there are few unregulated streams in southeastern Massachusetts. The analyses determined that groundwater contributing area and storage (combined water bodies and wetlands) were the only significant explanatory variables in the southeastern equations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255082","collaboration":"Prepared in cooperation with the Massachusetts Department of Conservation and Recreation, Office of Water Resources","usgsCitation":"Bent, G.C., Ahearn, E.A., and Fair, J.H., 2025, Methods for estimating selected low-flow statistics at gaged and ungaged stream sites in Massachusetts: U.S. Geological Survey Scientific Investigations Report 2025–5082, 76 p., https://doi.org/10.3133/sir20255082.","productDescription":"Report: ix, 76 p.; 3 Data Releases","numberOfPages":"76","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-164297","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":495617,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P142FWRJ","text":"USGS data release","linkHelpText":"MODPATH6 datasets using MODFLOW and SEAWAT input for development of 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\"}}]}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
The U.S. Geological Survey’s seismic velocity model for the Cascadia Subduction Zone provides P- and S-wave velocity (VP and VS, respectively) information from 40.2° to 50.0° N. latitude and −129.0° to −121.0° W. longitude, and is used to support a variety of research topics, including three-dimensional (3D) earthquake simulations and seismic hazard assessment in the Pacific Northwest. This report describes an update to the previous version (v) 1.6 of the 3D seismic velocity model for the Cascadia Subduction Zone. This new model (herein referred to as v1.7) contains more detailed near-surface structure for improved earthquake ground motion modeling. Updated features include the addition of a new shallow soil velocity model in the top few hundred meters and the option of adding user-specified topography. Although v1.6 of the Cascadia seismic velocity model has a minimum VS of 600 meters per second (m/s), the new model (v1.7) has a minimum VS of approximately 40 m/s. Overall, this update will allow for more accurate ground motion estimates from 3D simulations of scenario earthquakes in the Cascadia Subduction Zone region.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20251045","usgsCitation":"Wirth, E.A., Grant, A.R., Stone, I.P., Stephenson, W.J., and Frankel, A.D., 2025, Three-dimensional seismic velocity model for the Cascadia Subduction Zone with shallow soils and topography, version 1.7: U.S. Geological Survey Open-File Report 2025–1045, 18 p., https://doi.org/10.3133/ofr20251045.","productDescription":"Report: vi, 18 p.; Data Release","numberOfPages":"18","onlineOnly":"Y","ipdsId":"IP-161899","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":495639,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P14HJ3IC","text":"USGS data release","description":"Wirth, E.A., Grant, A.R., Stone, I.P., Stephenson, W.J., and Frankel, A.D., 2025, Data for A 3-D Seismic Velocity Model for Cascadia with Shallow Soils & Topography, Version 1.7: U.S. Geological Survey data release, https://doi.org/10.5066/P14HJ3IC","linkHelpText":"Data for A 3-D Seismic Velocity Model for Cascadia with Shallow Soils & Topography, Version 1.7"},{"id":495638,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2025/1045/images"},{"id":495637,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2025/1045/ofr20251045.XML","description":"OFR 2025-1045 XML"},{"id":495636,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20251045/full","linkFileType":{"id":5,"text":"html"},"description":"OFR 2025-1045 HTML"},{"id":495635,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2025/1045/ofr20251045.pdf","text":"Report","size":"4.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2025-1045 PDF"},{"id":495634,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2025/1045/coverthb.jpg"}],"country":"Canada, United States","state":"British Columbia, California, Oregon, Washington","otherGeospatial":"Cascadia Subduction Zone","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121,\n 50\n ],\n [\n -129,\n 50\n ],\n [\n -129,\n 40.2\n ],\n [\n -121,\n 40.2\n ],\n [\n -121,\n 50\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Earthquake Science Center
U.S. Geological Survey
350 N. Akron Rd.
Moffett Field, CA 94035
Earthquakes and their cascading consequences pose a significant threat to the people, environment, infrastructure, and economy of the U.S. Pacific Northwest. The Pacific Northwest is susceptible to three types of earthquakes: deep (intraslab) earthquakes, subduction zone (megathrust) earthquakes, and shallow crustal earthquakes. For each of these earthquake types, earth scientists can use a variety of methods to estimate the probability of occurrence for future events, which constrains seismic hazard and informs building codes. The timing of past earthquakes indicates that there is an 85-percent chance of a magnitude 6.5 or greater deep earthquake in the Puget Sound region; a 10-15-percent chance of an approximately magnitude 9 earthquake on the Cascadia Subduction Zone; and a 17-percent chance of a magnitude 6.5 or greater crustal fault earthquake in the Puget Sound region in the next 50 years. Individuals and communities can take simple steps to prepare for and reduce the impact of future earthquakes.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20253050","usgsCitation":"Wirth, E., Frankel, A., Sherrod, B., Grant, A., Dunham, A., Stone, I., and Grossman, J., 2025, Earthquake probabilities and hazards in the U.S. Pacific Northwest (ver. 1.1, September 30, 2025): U.S. Geological Survey Fact Sheet 2025–3050, 6 p., https://doi.org/10.3133/fs20253050.","productDescription":"6 p.","numberOfPages":"6","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-172377","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":495644,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2025/3050/fs20253050.pdf","text":"Report","size":"10 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2025-3050"},{"id":495647,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/fs20253050/full"},{"id":496244,"rank":7,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/fs/2025/3050/versionHist.txt","text":"Version History","size":"1 KB","linkFileType":{"id":2,"text":"txt"}},{"id":496024,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118878.htm","linkFileType":{"id":5,"text":"html"}},{"id":495646,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2025/3050/images/"},{"id":495645,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2025/3050/fs20253050.XML"},{"id":495643,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2025/3050/coverthb.jpg"}],"country":"United States","state":"California, Oregon, Washington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -131.42807526130667,\n 49.386193359384805\n ],\n [\n -131.42807526130667,\n 36.38535423200561\n ],\n [\n -119.71998032318022,\n 36.38535423200561\n ],\n [\n -119.71998032318022,\n 49.386193359384805\n ],\n [\n -131.42807526130667,\n 49.386193359384805\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","edition":"Version 1.0: September 19, 2025; Version 1.1: September 30, 2025","contact":"Earthquake Science Center, Seattle Field Office
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University of Washington, Department of Earth and Space Sciences
4000 15th Ave NE
Seattle, WA 98195
Earthquakes and their cascading consequences pose a significant threat to the people, environment, infrastructure, and economy of the U.S. Pacific Northwest. The timing of previous earthquakes helps estimate the likelihood of future events.
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This study applied a river catchment-scale approach to identify PFAS source zones and assess the relative importance of industrial PFAS sources in the River Mersey, UK – a post-industrial, densely populated catchment with diverse PFAS sources. Synoptic sampling and PFAS river load analysis identified key sub-catchments and river stretches contributing the majority of PFAS. Notably, the highest PFAS concentrations did not always correspond to the greatest loads. Most PFOS (64 %), PFOA (49 %), 6:2FTS (46 %) and PFHxS (56 %) were exported from the Upper Mersey sub-catchment, despite higher concentrations in northern sub-catchments, emphasising the importance of load-based monitoring. Mass balance analysis of loads highlighted substantial inputs from specific river stretches, notably the Lower Irwell (Bolton to Manchester City Centre), River Tame (Marple Bridge to Stockport), and Upper Mersey (Stockport to Urmston). While PFAS loads generally scaled with catchment area, yield (load per unit area) analysis identified disproportionately high exports from small headwater catchments, notably the upper River Roch (PFOA, PFHpA and PFHxA) and Glaze Brook (PFBS). Industrial sources in these sub-catchments (a waste management facility and landfills, respectively) were confirmed using gadolinium anomaly analysis and consented discharge records. More widely, gadolinium data suggested industrial discharges may contribute to PFAS occurrence at 62 % of our sample sites throughout the catchment. These findings demonstrate that spatial analysis of PFAS loads, rather than concentrations alone, is critical for identifying PFAS source areas. We present a scalable monitoring framework for PFAS source apportionment applied at the river catchment-scale that can be used by environmental managers to target and prioritise PFAS source areas for detailed monitoring and remediation.","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2025.180502","usgsCitation":"Byrne, P., Mayes, W.M., James, A.L., Comber, S., Biles, E., Riley, A.L., Verplanck, P., and Bradley, L., 2025, Spatially resolved source apportionment of per- and polyfluoroalkyl substances (PFAS) within a post-industrial river catchment: Science of the Total Environment, v. 1001, 180502, 12 p., https://doi.org/10.1016/j.scitotenv.2025.180502.","productDescription":"180502, 12 p.","ipdsId":"IP-180073","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":496352,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2025.180502","text":"Publisher Index Page"},{"id":495896,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United Kingdom","otherGeospatial":"River Mersey","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -2.4656527163469946,\n 53.60530248618926\n ],\n [\n -2.4656527163469946,\n 53.3355442876196\n ],\n [\n -1.966480261260216,\n 53.3355442876196\n ],\n [\n -1.966480261260216,\n 53.60530248618926\n ],\n [\n -2.4656527163469946,\n 53.60530248618926\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"1001","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Byrne, Patrick","contributorId":192845,"corporation":false,"usgs":false,"family":"Byrne","given":"Patrick","affiliations":[],"preferred":false,"id":949261,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mayes, William M.","contributorId":335073,"corporation":false,"usgs":false,"family":"Mayes","given":"William","email":"","middleInitial":"M.","affiliations":[{"id":40174,"text":"University of Hull","active":true,"usgs":false}],"preferred":false,"id":949262,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"James, Alun L.","contributorId":361704,"corporation":false,"usgs":false,"family":"James","given":"Alun","middleInitial":"L.","affiliations":[{"id":86333,"text":"Environment Agency UK","active":true,"usgs":false}],"preferred":false,"id":949263,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Comber, Sean","contributorId":335075,"corporation":false,"usgs":false,"family":"Comber","given":"Sean","email":"","affiliations":[{"id":80302,"text":"University of Plymouth,","active":true,"usgs":false}],"preferred":false,"id":949264,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Biles, Emma","contributorId":335077,"corporation":false,"usgs":false,"family":"Biles","given":"Emma","email":"","affiliations":[{"id":49583,"text":"Liverpool John Moores University","active":true,"usgs":false}],"preferred":false,"id":949265,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Riley, Alex L.","contributorId":361707,"corporation":false,"usgs":false,"family":"Riley","given":"Alex","middleInitial":"L.","affiliations":[{"id":40174,"text":"University of Hull","active":true,"usgs":false}],"preferred":false,"id":949266,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Verplanck, Philip L. 0000-0002-3653-6419","orcid":"https://orcid.org/0000-0002-3653-6419","contributorId":212813,"corporation":false,"usgs":true,"family":"Verplanck","given":"Philip","middleInitial":"L.","affiliations":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"preferred":true,"id":949267,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Bradley, Lee","contributorId":361708,"corporation":false,"usgs":false,"family":"Bradley","given":"Lee","affiliations":[{"id":86332,"text":"John Moores University","active":true,"usgs":false}],"preferred":false,"id":949268,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70271720,"text":"70271720 - 2025 - Machine learning generated streamflow drought forecasts for the Conterminous United States (CONUS): Developing and evaluating an operational tool to enhance sub-seasonal to seasonal streamflow drought early warning for gaged locations","interactions":[{"subject":{"id":70271720,"text":"70271720 - 2025 - Machine learning generated streamflow drought forecasts for the Conterminous United States (CONUS): Developing and evaluating an operational tool to enhance sub-seasonal to seasonal streamflow drought early warning for gaged locations","indexId":"70271720","publicationYear":"2025","noYear":false,"title":"Machine learning generated streamflow drought forecasts for the Conterminous United States (CONUS): Developing and evaluating an operational tool to enhance sub-seasonal to seasonal streamflow drought early warning for gaged locations"},"predicate":"SUPERSEDED_BY","object":{"id":70273497,"text":"70273497 - 2026 - Machine learning generated streamflow drought forecasts for the conterminous United States (CONUS): developing and evaluating an operational tool to enhance sub-seasonal to seasonal streamflow drought early warning for gaged locations","indexId":"70273497","publicationYear":"2026","noYear":false,"title":"Machine learning generated streamflow drought forecasts for the conterminous United States (CONUS): developing and evaluating an operational tool to enhance sub-seasonal to seasonal streamflow drought early warning for gaged locations"},"id":1}],"supersededBy":{"id":70273497,"text":"70273497 - 2026 - Machine learning generated streamflow drought forecasts for the conterminous United States (CONUS): developing and evaluating an operational tool to enhance sub-seasonal to seasonal streamflow drought early warning for gaged locations","indexId":"70273497","publicationYear":"2026","noYear":false,"title":"Machine learning generated streamflow drought forecasts for the conterminous United States (CONUS): developing and evaluating an operational tool to enhance sub-seasonal to seasonal streamflow drought early warning for gaged locations"},"lastModifiedDate":"2026-01-26T16:29:56.651322","indexId":"70271720","displayToPublicDate":"2025-09-19T09:20:12","publicationYear":"2025","noYear":false,"publicationType":{"id":27,"text":"Preprint"},"publicationSubtype":{"id":32,"text":"Preprint"},"seriesTitle":{"id":18346,"text":"EarthArXiv","active":true,"publicationSubtype":{"id":32}},"title":"Machine learning generated streamflow drought forecasts for the Conterminous United States (CONUS): Developing and evaluating an operational tool to enhance sub-seasonal to seasonal streamflow drought early warning for gaged locations","docAbstract":"Forecasts of streamflow drought, when streamflow declines below typical levels, are notably less available than for floods or meteorological drought, despite widespread impacts. To address this gap, we apply machine learning (ML) models to forecast streamflow drought 1-13 weeks into the future at > 3,000 streamgage locations across the conterminous United States (CONUS). We applied two ML methods (Long short-term memory (LSTM) neural networks; Light Gradient-Boosting Machine - LightGBM) and two benchmark model approaches (persistence; Autoregressive Integrated Moving Average - ARIMA) to predict weekly streamflow percentiles with independent models for each forecast horizon. To explore whether a training focus on dry weeks improved performance, both ML models were trained using all percentiles (LSTM-all, LightGBM-all) and only percentiles below 30% (LSTM<30, LightGBM<30). We evaluated model performance regionally and nationally for drought occurrence (the classification performance for a future date) and for drought onset/termination (performance identifying drought starts and ends). ML models generally performed worse than the persistence model for discrete classification (moderate, severe, extreme drought) of drought occurrence but exceeded the benchmark models for onset/termination. ML models outperformed benchmarks in predicting continuous streamflow percentiles below 30%. Occurrence performance was better for less intense droughts and shorter forecast horizons, with the ML models having predictive power at 1-4 week horizons for severe droughts (10th percentile threshold). All models struggled to forecast onset, though the best ML model was the LSTM<30 (sensitivity of 22%). Termination performance was greater, with the drought termination performance greatest for the LightGBM-all model. When estimating model uncertainty, the LSTM<30 model had the narrowest 90% percentile interval with closest to optimal capture. This work highlights the challenges and opportunities to further advance hydrological drought forecasting and supports an experimental operational streamflow drought assessment and forecast tool.
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sampling activities in the U.S. Geological Survey national networks","interactions":[],"lastModifiedDate":"2026-02-03T15:26:53.6234","indexId":"gip260","displayToPublicDate":"2025-09-19T08:39:57","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":315,"text":"General Information Product","code":"GIP","onlineIssn":"2332-354X","printIssn":"2332-3531","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"260","displayTitle":"PFAS Sampling Activities in the U.S. Geological Survey National Networks","title":"PFAS sampling activities in the U.S. Geological Survey national networks","docAbstract":"Per- and polyfluoroalkyl substances (PFAS), frequently called “forever chemicals,” are used for a wide variety of industrial purposes and are often found in common household and industrial items such as firefighting foams, non-stick cookware, and water-resistant materials. The contamination of water, air, and soil by PFAS is a national and global issue due to their widespread occurrence in multiple applications and resistance to biodegradation and other traditional treatment processes. Research indicates that many PFAS can be emitted to the atmosphere and transported and deposited long distances from the source.
The U.S. Geological Survey (USGS) Water Resources Mission Area received funding to implement a national-scale sampling effort to assess PFAS occurrence. To follow agency directives, the National Water Quality Network (NWQN) added PFAS sample monitoring for both surface water and groundwater, and also added PFAS monitoring to selected sites in the National Atmospheric Deposition Program (NADP).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/gip260","usgsCitation":"Riskin, M.L., Lindsey, B.D., and McCammon, R.C., 2025, PFAS sampling activities in the U.S. Geological Survey national networks: U.S. Geological Survey General Information Product 260, https://doi.org/10.3133/gip260.","productDescription":"1 p.","onlineOnly":"Y","ipdsId":"IP-169424","costCenters":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"links":[{"id":495819,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/gip/260/gip260.pdf","text":"Report","size":"901 KB","linkFileType":{"id":1,"text":"pdf"},"description":"GIP 260"},{"id":495818,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/gip/260/coverthb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"geometry\": {\n \"type\": 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Observing Systems Division
Water Mission Area
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
Aerial photography and satellite imagery can be used to characterize landscape change over time and help to understand how these changes are related to climate and hydrology. Publicly available optical imagery from sources such as the United States National Agricultural Imagery Program (NAIP) is particularly valuable in this context due to its high temporal and spatial resolution. However, the exact time an image was acquired is often unknown, which complicates, if not precludes, linking images with other types of high temporal resolution data, such as streamflow records. In this letter, we propose a ‘sundial method’ to infer image acquisition time from shadow orientation. This approach involves measuring the direction of a shadow on the image and using solar geometry calculated for the known image date and location to infer the former sun position. Time estimates for 16 Worldview satellite and six NAIP aerial images based on 407 independent measurements of shadow orientation demonstrate the sundial method had an error of 2.1 ± 3.4 min, indicating that image acquisition times can be inferred with a high degree of accuracy and precision. Sensitivity analyses confirm the robustness of the method across different object types, shadow lengths, and solar zenith angles, while also providing practical guidelines regarding the number of measurements required and errors associated with uncertainty in the image date.
","language":"English","publisher":"Wiley","doi":"10.1002/esp.70157","usgsCitation":"Bae, I., Legleiter, C.J., and Yager, E., 2025, Sundial: A method for inferring image acquisition time from shadow orientation: Earth Surface Processes and Landforms, v. 50, no. 12, e70157, 10 p., https://doi.org/10.1002/esp.70157.","productDescription":"e70157, 10 p.","ipdsId":"IP-173049","costCenters":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"links":[{"id":495797,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"50","issue":"12","noUsgsAuthors":false,"publicationDate":"2025-09-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Bae, Inhyeok 0000-0003-3942-4110","orcid":"https://orcid.org/0000-0003-3942-4110","contributorId":347541,"corporation":false,"usgs":false,"family":"Bae","given":"Inhyeok","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":949025,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Legleiter, Carl J. 0000-0003-0940-8013 cjl@usgs.gov","orcid":"https://orcid.org/0000-0003-0940-8013","contributorId":169002,"corporation":false,"usgs":true,"family":"Legleiter","given":"Carl","email":"cjl@usgs.gov","middleInitial":"J.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":949024,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yager, Elowyn 0000-0002-3382-2356","orcid":"https://orcid.org/0000-0002-3382-2356","contributorId":347542,"corporation":false,"usgs":false,"family":"Yager","given":"Elowyn","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":949026,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70271707,"text":"70271707 - 2025 - Scenario projections of COVID-19 burden in the US, 2024-2025","interactions":[],"lastModifiedDate":"2025-09-19T14:41:41.794225","indexId":"70271707","displayToPublicDate":"2025-09-18T09:33:49","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":20081,"text":"JAMA Network Open","active":true,"publicationSubtype":{"id":10}},"title":"Scenario projections of COVID-19 burden in the US, 2024-2025","docAbstract":"Importance COVID-19 remains a disease with high burden in the US, prompting continued debate about optimal targets for annual vaccination.
Objective To project COVID-19 burden in the US for April 2024 to April 2025 under 6 scenarios of immune escape (20% and 50% per year) and levels of vaccine recommendation (no recommendation, vaccination for individuals at high risk only, vaccination for all eligible groups) and to assess the potential benefit of vaccine recommendations in reducing disease burden.
Design, Setting, and Participants For this decision analytical model, the US Scenario Modeling Hub, a collaborative modeling effort, convened 9 teams to provide scenario projections of US COVID-19 hospitalizations and deaths for April 2024 to April 2025, under 6 scenarios combining levels of immune escape and possible vaccine recommendations.
Exposure Annually reformulated vaccines were assumed to be 75% effective against hospitalization for variants circulating on June 15, 2024, and available on September 1, 2024. Age- and state-specific coverage was assumed to be as reported in September 2023 to April 2024.
Main Outcomes and Measures Ensemble estimates were made for weekly COVID-19 hospitalizations and deaths. Projections are presented for relative and absolute prevented hospitalizations and deaths averted due to vaccination over the April 2024 to April 2025 period.
Results For the US population (332 million, with an estimated 58 million aged ≥65 years), COVID-19 was expected to cause 814 000 (95% projection interval [PI], 400 000-1.2 million) hospitalizations and 54 000 (95% PI, 17 000-98 000) deaths for April 2024 to April 2025, comparable in magnitude to the prior year. Vaccination of high-risk groups only was projected to reduce hospitalizations (compared to no vaccination recommendation) by 76 000 (95% CI, 34 000-118 000) and deaths by 7000 (95% CI, 3000-11 000) across both immune escape scenarios. Compared with vaccinating high-risk groups only, a universal vaccine recommendation was projected to provide direct and indirect benefits, further preventing 11 000 hospitalizations and 1000 deaths in those aged 65 years and older.
Conclusions and Relevance In this decision analytical modeling study of COVID-19 burden in the US in 2024 to 2025, ensemble projections suggested that although vaccinating high-risk groups had substantial benefits in reducing disease burden, maintaining the vaccine recommendation for all individuals had the potential to save thousands more lives. Despite divergence of projections from observed disease trends in 2024 to 2025—possibly driven by variant emergence patterns and immune escape—averted COVID-19 burden due to vaccination was robust across immune escape scenarios, emphasizing the substantial benefit of broader vaccine availability for all individuals.
","language":"English","publisher":"JAMA","doi":"10.1001/jamanetworkopen.2025.32469","usgsCitation":"Loo, S.L., Jung, S., Contamin, L., Howerton, E., Bents, S., Hochheiser, H., Runge, M., Smith, C.P., Carcelén, E., Yan, K., Lemaitre, J.C., Przykucki, E., McKee, C., Sato, K., Hill, A., Chinazzi, M., Davis, J.T., Bay, C., Vespignani, A., Chen, S., Paul, R., Janies, D., Thill, J., Moore, S., Perkins, T.A., Srivastava, A., Aawar, M.A., Bi, K., Bandekar, S.R., Bouchnita, A., Fox, S., Meyers, L.A., Porebski, P., Venkatramanan, S., Lewis, B., Chen, J., Marathe, M., Ben-Nun, M., Turtle, J., Riley, P., Shea, K., Viboud, C., Lessler, J., and Truelove, S., 2025, Scenario projections of COVID-19 burden in the US, 2024-2025: JAMA Network Open, v. 8, no. 9, e2532469, 12 p., https://doi.org/10.1001/jamanetworkopen.2025.32469.","productDescription":"e2532469, 12 p.","ipdsId":"IP-180247","costCenters":[{"id":50464,"text":"Eastern Ecological Science 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density that inform conservation and management practices for imperiled species. As a result, evaluating the performance of different survey methods across a range of conditions that may be encountered in the field can increase understanding of the time and effort that may be required to ensure that survey results are sufficiently accurate and reliable for conservation goals. We used a spatially explicit agent-based model to simulate four commonly used freshwater mussel field survey methodologies: simple random sampling (SRS), transect random sampling (TRS), adaptive cluster sampling (ACS), and qualitative timed searches (QTS) to investigate the influence of sampling method, spatial distribution, and mussel density on the performance (i.e., accuracy, precision, and detection rate) of survey techniques. Our analysis suggests that mussel density, spatial distribution, and sampling effort influence sampling accuracy, precision, and species detection for all sampling methods. QTS produces highly variable catch-per-unit-effort (CPUE) metrics when mussels are dense and/or clustered, indicating the technique may be unreliable as a proxy for density. Quantitative methods like SRS and TRS may be well-suited for estimating population characteristics, but a high level of effort may be needed to obtain reasonable accuracy when mussels occur at low densities. ACS may be more efficient for mussels at low densities, but it can be challenging to plan for the level of effort required to complete an ACS protocol. Designing an ecological survey requires careful consideration of research objectives and available resources. Future research may consider the performance of qualitative and quantitative surveys in combination as a means of overcoming some of the practical challenges of applying individual survey methods.
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