Digital flood-inundation maps for a 131.8-mile reach of the Current River and a 44.6-mile reach of the Jacks Fork River, in southeast Missouri, were created by the U.S. Geological Survey (USGS) in cooperation with the Ozark Foothills Regional Planning Commission and the South Central Ozark Council of Governments. The maps also encompass the 134 miles of the Current and Jacks Fork Rivers within the Ozark National Scenic Riverways, which is the first national park area to protect a river system. The flood-inundation maps, which can be accessed through the USGS Flood Inundation Mapping Program website at https://water.usgs.gov/osw/flood_inundation/, depict estimates of the areal extent and depth of flooding corresponding to selected water levels (hereafter referred to as “stages”) at eight reference USGS streamgages—five on the Current River (USGS station numbers 07064440, 07064533, 07066510, 07067000, and 07068000) and three on the Jacks Fork River (USGS station numbers 07065200, 07065495, and 07066000). Near-real-time stages at these streamgages may be obtained from the USGS National Water Information System at https://doi.org/10.5066/F7P55KJN or the National Weather Service National Water Prediction Service at http://water.noaa.gov/, which also forecasts flood hydrographs at four of these sites (USGS station numbers 07067000, 07068000, 07065495, and 07066000).
Flood profiles were computed for seven of the eight map reaches by means of two-dimensional hydraulic models and the remaining reach by a one-dimensional hydraulic model. The models were calibrated by using stage-streamflow relations or streamflow measurements at the USGS streamgages and from high-flow stage measurements from water-level loggers distributed throughout the reaches.
The hydraulic models were used to compute water-surface profiles for flood stages at 1-foot intervals referenced to the streamgage datums. The profile stages ranged from the National Weather Service “action stage” or near bankfull, to a stage exceeding the highest recorded water level at each streamgage. The simulated water-surface profiles were then combined with a digital elevation model (derived from light detection and ranging data having a nonvegetated vertical accuracy of a maximum 10-centimeter root mean square error) to delineate the area flooded at each water level and the associated water depths.
The availability of these maps, along with information regarding current stage from the USGS streamgage and forecasted high-flow stages from the National Weather Service, will provide emergency management personnel, resource managers, and residents with information that is critical for flood-response activities such as evacuations and road closures, as well as for postflood recovery efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/sir20255092","collaboration":"South Central Ozark Council of Governments, Ozark Foothills Regional Planning Commission","usgsCitation":"Heimann, D.C., High, J.L., Atkinson, A.A., and Rydlund, P.H., Jr., 2025, Flood-inundation maps of the Current and Jacks Fork Rivers including the Ozark National Scenic Riverways, southeast Missouri, 2023: U.S. Geological Survey Scientific Investigations Report 2025–5092, 29 p., https://doi.org/10.3133/sir20255092.","productDescription":"Report: viii, 29 p.; Data Release; Dataset","numberOfPages":"42","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-135288","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":497780,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118892.htm"},{"id":495817,"rank":7,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"- USGS water data for the Nation"},{"id":495816,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P90H2UQY","text":"USGS data release","linkHelpText":"Hydraulic models and geospatial products associated with flood-inundation mapping of the Current and Jacks Fork Rivers including the Ozark National Scenic Riverways, Southeast Missouri, 2022–25"},{"id":495815,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5092/images"},{"id":495813,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255092/full","linkFileType":{"id":5,"text":"html"},"description":"SIR 2025-5092 HTML"},{"id":495809,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5092/sir20255092.pdf","text":"Report","size":"17 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5092"},{"id":495808,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5092/coverthb.jpg"},{"id":495814,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5092/sir20255092.XML","description":"SIR 2025-5092 XML"}],"country":"United States","state":"Missouri","otherGeospatial":"Current River, Jacks Fork River, Ozark National Scenic Riverways","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -91.75,\n 37.5\n ],\n [\n -91.75,\n 36.5\n ],\n [\n -90.75,\n 36.5\n ],\n [\n -90.75,\n 37.5\n ],\n [\n -91.75,\n 37.5\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
1400 Independence Road
Rolla, MO 65401
The U.S. Geological Survey created flood-inundation maps that make up a 131.8-mile reach of the Current River, a 44.6-mile reach of the Jacks Fork River, including 134 miles of the Ozark National Scenic Riverways in southeast Missouri. The flood-inundation maps show estimates of the extent and depth of flooding corresponding to selected water levels at eight reference U.S. Geological Survey streamgages—five on the Current River (U.S. Geological Survey station numbers 07064440, 07064533, 07066510, 07067000, and 07068000) and three on the Jacks Fork River (U.S. Geological Survey station numbers 07065200, 07065495, and 07066000).
","publicationDate":"2025-09-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Heimann, David C. 0000-0003-0450-2545 dheimann@usgs.gov","orcid":"https://orcid.org/0000-0003-0450-2545","contributorId":3822,"corporation":false,"usgs":true,"family":"Heimann","given":"David","email":"dheimann@usgs.gov","middleInitial":"C.","affiliations":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":949167,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"High, Jason L. 0009-0009-1031-1439","orcid":"https://orcid.org/0009-0009-1031-1439","contributorId":361676,"corporation":false,"usgs":true,"family":"High","given":"Jason","middleInitial":"L.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":949168,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Atkinson, Allison A. 0009-0001-7572-0729 aatkinson@usgs.gov","orcid":"https://orcid.org/0009-0001-7572-0729","contributorId":330979,"corporation":false,"usgs":true,"family":"Atkinson","given":"Allison","email":"aatkinson@usgs.gov","middleInitial":"A.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":949169,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rydlund, Paul H. Jr. 0000-0001-9461-9944 prydlund@usgs.gov","orcid":"https://orcid.org/0000-0001-9461-9944","contributorId":3840,"corporation":false,"usgs":true,"family":"Rydlund","given":"Paul","suffix":"Jr.","email":"prydlund@usgs.gov","middleInitial":"H.","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":949170,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70271736,"text":"cir1561 - 2025 - ShakeAlert®—Communication, education, outreach and technical engagement strategic vision","interactions":[],"lastModifiedDate":"2026-02-03T15:33:50.766743","indexId":"cir1561","displayToPublicDate":"2025-09-23T12:00:00","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":307,"text":"Circular","code":"CIR","onlineIssn":"2330-5703","printIssn":"1067-084X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1561","displayTitle":"ShakeAlert®—Communication, Education, Outreach and Technical Engagement Strategic Vision","title":"ShakeAlert®—Communication, education, outreach and technical engagement strategic vision","docAbstract":"In 2006, the U.S. Geological Survey (USGS) began directly supporting ShakeAlert® research and in 2012 the ShakeAlert demonstration system began testing (Given and others, 2018). The ShakeAlert earthquake early warning (EEW) system is a partnership between the U.S. Geological Survey (USGS) and the three West Coast States (Washington, Oregon, and California) served by the ShakeAlert System, which is part of the larger Advanced National Seismic System (ANSS). With more than 143 million people exposed to potentially damaging shaking in the United States (Jaiswal and others, 2015), earthquakes are a national hazard. Most of our Nation’s earthquake risk is concentrated in the highly populated areas on the active plate tectonic boundaries on the West Coast of the conterminous United States. ShakeAlert is the first public alert system in the United States to provide rapid mass notification of earthquake detection, potentially offering seconds of warning before strong shaking arrives. A few seconds may not seem like much time, but the information in ShakeAlert Messages can be used to trigger automated actions that can prevent injury or death, reduce immediate damage, and speed recovery from earthquakes.
The information product issued by the ShakeAlert system is called a ShakeAlert Message and is one of the information products and tools of the ANSS. The ShakeAlert System includes the USGS component, plus the pathways by which ShakeAlert-powered products and (or) services are delivered to end users. Alerts can be delivered to cell phones or be used to trigger automated systems to protect equipment, facilities, and infrastructure, such as slowing or stopping a train. ShakeAlert-powered automated actions can include fire house doors that can be opened to prevent jamming, heavy equipment (for example, trains, elevators, and cranes) that can be automatically stopped or parked in safe positions, and pipeline valves that can be closed to prevent surges and spills. A few seconds of warning also may be sufficient for people to take protective actions, such as drop, cover, and hold on or modified protective actions for a broad range of populations. Advance training may increase the benefit of a speedy response to an alert.
Outreach and education about EEW may raise awareness of the overall earthquake threat and how people can best react when they receive an alert or feel shaking. ShakeAlert communication, education, outreach, and technical engagement (CEO&TE) efforts are highly collaborative and essential for the success of the ShakeAlert System. This strategic vision informs how the vast ShakeAlert CEO&TE Community operates and works together. The CEO&TE Community delineates a strategic framework that is intended to set the path for a long-term, sustainable approach to CEO&TE through three focus areas and five priorities.
The enumeration of the five priorities listed below does not suggest priority ranking.
This strategic vision is a tangible outcome of collaboration among many stakeholders beginning in July 2016. Since then, the work of the ShakeAlert CEO&TE Community has grown into an international effort. The USGS has developed, tested, and implemented a broad spectrum of communication, education, and outreach tools and resources—all of which recognize that seconds matter when it comes to safety and mitigating harm from earthquake hazards. The CEO&TE social science research effort has provided invaluable insights into the ShakeAlert System’s human interface. USGS-licensed technical partners develop, test, and implement real-world applications using ShakeAlert Messages.
The success of ShakeAlert CEO&TE efforts is predicated on robust collaboration across numerous agencies, organizations, and groups. As such, this strategic vision outlines a “partnership model” that delineates roles and responsibilities to ensure alignment with focus areas and priorities. The partnership model includes the CEO&TE lead agency (USGS); its principal partners (State agencies and university partners); its implementation partners (for example, technical partners who build systems to deliver ShakeAlert-powered products and (or) services [focus area one]), earthquake education partners who work to increase public preparedness for seismic events (focus area two); and other organizations that work together to enhance the adoption and effectiveness of the ShakeAlert System. These partners collaborate and convene through a variety of working groups and forums, which are also described in this strategic vision and align with focus area three (internal engagement). The CEO&TE Community collaboratively developed its operating principles and a consensus-based, decision-making strategic framework to guide its collective work. Performance metrics are used to continually measure success. Ultimately, the USGS and ShakeAlert CEO&TE Community are advancing the ShakeAlert System that as of the publication of this strategic vision to “provide earthquake early warning for all” serves more than 50 million people.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1561","usgsCitation":"de Groot, R.M., McBride, S.K., Vinci, M.J., Lotto, G.C., Anderson, M.L., Sumy, D.F., and Terbush, B., 2025, ShakeAlert—Communication, education, outreach, and technical engagement strategic vision: U.S. Geological Survey\nCircular 1561, 32 p., https://doi.org/10.3133/cir1561.","productDescription":"vi, 32 p.","numberOfPages":"32","onlineOnly":"Y","ipdsId":"IP-159575","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":495882,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/circ/1561/coverthb.jpg"},{"id":495886,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/circ/1561/images"},{"id":495885,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/circ/1561/cir1561.XML","linkFileType":{"id":8,"text":"xml"},"description":"CIR 1561 XML"},{"id":495884,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/cir1561/full","linkFileType":{"id":5,"text":"html"},"description":"CIR 1561 HTML"},{"id":495883,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1561/cir1561.pdf","text":"Report","size":"4.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"CIR 1561 PDF"}],"contact":"Earthquake Science Center-Pasadena Field Office
U.S. Geological Survey
525 South Wilson Ave.
Pasadena, CA 91106-3212
Digital flood-inundation maps for a 3.1-mile reach of Río de la Plata in and near Comerío, Puerto Rico, were created by the U.S. Geological Survey (USGS). Water-surface profiles were computed for the stream reach by using a one-dimensional steady-state step-backwater model. The model was calibrated to the current (2025) stage-streamflow relation (rating curve 11.0) for the USGS streamgage 50043800, Río de la Plata at Comerío, Puerto Rico. The resulting hydraulic model was then used to compute 16 water-surface profiles for water levels (flood stages) ranging from 10.00 to 40.00 feet at the streamgage and ranging from “action stage” to above “major flood stage” as reported by the National Weather Service. The 40.00-foot stage was selected because it exceeds the peak stage of 34.86 ft recorded during Hurricane Maria at the USGS streamgage 50043800, Río de Plata at Comerío, Puerto Rico. The simulated water-surface profiles were then used in combination with a digital elevation model derived from light detection and ranging data to map the inundated areas associated with each flood profile.
The flood-inundation maps and the supporting hydraulic model produced by this study can be used by emergency managers and local officials to assess flood mitigation strategies and to define flood hazard areas to help protect life and property, to coordinate flood response activities such as evacuations and road closures, and to aid post-flood recovery efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255094","usgsCitation":"Ostheimer, C.J., and Torres-Garcia, L.M., 2025, Flood-inundation maps for Río de la Plata in and near Comerío, Puerto Rico, 2025: U.S. Geological Survey Scientific Investigations Report 2025–5094, 15 p., https://doi.org/10.3133/sir20255094.","productDescription":"Report: vii, 15 p.; Data Release","numberOfPages":"15","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-176013","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":495789,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13UOGOZ","text":"USGS data release","linkHelpText":"Geospatial data sets and hydraulic model for Río de la Plata in and Near Comerío, Puerto Rico"},{"id":495788,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5094/images/"},{"id":495787,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5094/sir20255094.XML","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2025-5082 XML"},{"id":495786,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255094/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2025-5082 HTML"},{"id":495785,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5094/sir20255094.pdf","text":"Report","size":"6.45 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5082 PDF"},{"id":495780,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5094/coverthb.jpg"},{"id":497779,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118885.htm"}],"country":"United States","city":"Comerio","otherGeospatial":"Puerto Rico, Rio de la Plata","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -66.19365607546672,\n 18.268637648344637\n ],\n [\n -66.20264706241515,\n 18.27758838215894\n ],\n [\n -66.21903386120783,\n 18.274972061568477\n ],\n [\n -66.229184975504,\n 18.262991563440394\n ],\n [\n -66.22758980040052,\n 18.254728669228726\n ],\n [\n -66.24151132857823,\n 18.254590950995066\n ],\n [\n -66.24484669470401,\n 18.250734796117897\n ],\n [\n -66.26891933717856,\n 18.244950403338635\n ],\n [\n -66.26993444860818,\n 18.217403035734378\n ],\n [\n -66.26239381153299,\n 18.185167128209628\n ],\n [\n -66.25673819071034,\n 18.183238292382484\n ],\n [\n -66.2425266306957,\n 18.193984391766037\n ],\n [\n -66.24528193314764,\n 18.183789390509304\n ],\n [\n -66.22352954536923,\n 18.175247173917384\n ],\n [\n -66.20975303311035,\n 18.174696048809224\n ],\n [\n -66.2051125237173,\n 18.197290750643944\n ],\n [\n -66.18263505634692,\n 18.202112411579463\n ],\n [\n -66.16936609980282,\n 18.216851668012367\n ],\n [\n -66.16943860776185,\n 18.22635645849499\n ],\n [\n -66.17494917440196,\n 18.230488705183646\n ],\n [\n -66.17799450869079,\n 18.246878681547642\n ],\n [\n -66.19365607546672,\n 18.268637648344637\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Ohio-Kentucky-Indiana Water Science Center
U.S. Geological Survey
6460 Busch Blvd, Suite 100
Columbus, OH 43229-1737
Since their first use in the mid-1980s, external passive integrated transponder (PIT) tags have facilitated innovative investigations into multiple biological traits of animals. For native freshwater mussels, PIT tags are frequently used in capture-mark-recapture applications because they allow repeated, noninvasive sampling, are easy to apply, have high retention rates, and have negligible short-term effects on growth and survival. Because of these traits, resource managers and scientists are using PIT-tagged animals to estimate survival and movement of mussels associated with restoration efforts. However, consistency is limited in how PIT tags are affixed, monitored, and reported. Thus, our objectives were to (1) share our collective experiences in PIT tagging mussels across three case studies in small, medium, and large rivers and (2) propose guidelines for tagging and reporting data from PIT tag studies with native freshwater mussels to facilitate comparisons across future studies. The number of studies that have marked mussels with PIT tags has increased over the past 10 years. The ability to detect mussels using PIT tags has substantially advanced research in three areas of mussel ecology: (1) estimating vital rates (e.g., growth and survival), (2) tracking movements and behaviors of captively propagated, wild, and translocated individuals, and (3) improving our understanding of life history traits, such as reproductive timing. Each case study offers insights on tagging methods, tag loss, tag retention, and monitoring frequency across multiple species that range in conservation status from common to rare. We conclude with best-practice guidelines for placing PIT tags on freshwater mussels and a list of variables that could be reported in future studies to facilitate cross-system comparisons.
","language":"English","publisher":"Freshwater Mollusk Conservation Society","doi":"10.31931/fmbc-d-25-00002","usgsCitation":"Tiemann, J.S., Ashton, M.J., Douglass, S.A., Stodola, A.P., Vinsel, R.M., and Newton, T.J., 2025, Pit tag application in native freshwater mussels: Case studies across small, medium, and large rivers: Freshwater Mollusk Biology and Conservation, v. 28, no. 2, p. 71-82, https://doi.org/10.31931/fmbc-d-25-00002.","productDescription":"12 p.","startPage":"71","endPage":"82","ipdsId":"IP-167177","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":496334,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.31931/fmbc-d-25-00002","text":"Publisher Index Page"},{"id":496271,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"28","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Tiemann, Jeremy S.","contributorId":361870,"corporation":false,"usgs":false,"family":"Tiemann","given":"Jeremy","middleInitial":"S.","affiliations":[{"id":36894,"text":"Illinois Natural History Survey","active":true,"usgs":false}],"preferred":false,"id":949599,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ashton, Matthew J.","contributorId":361871,"corporation":false,"usgs":false,"family":"Ashton","given":"Matthew","middleInitial":"J.","affiliations":[{"id":33964,"text":"Maryland Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":949600,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Douglass, Sarah A.","contributorId":361872,"corporation":false,"usgs":false,"family":"Douglass","given":"Sarah","middleInitial":"A.","affiliations":[{"id":36894,"text":"Illinois Natural History Survey","active":true,"usgs":false}],"preferred":false,"id":949601,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stodola, Alison P.","contributorId":361873,"corporation":false,"usgs":false,"family":"Stodola","given":"Alison","middleInitial":"P.","affiliations":[{"id":36894,"text":"Illinois Natural History Survey","active":true,"usgs":false}],"preferred":false,"id":949602,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Vinsel, Rachel M.","contributorId":361875,"corporation":false,"usgs":false,"family":"Vinsel","given":"Rachel","middleInitial":"M.","affiliations":[{"id":36894,"text":"Illinois Natural History Survey","active":true,"usgs":false}],"preferred":false,"id":949603,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Newton, Teresa J. 0000-0001-9351-5852","orcid":"https://orcid.org/0000-0001-9351-5852","contributorId":361878,"corporation":false,"usgs":false,"family":"Newton","given":"Teresa","middleInitial":"J.","affiliations":[{"id":85472,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":false}],"preferred":false,"id":949604,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70274058,"text":"70274058 - 2025 - Breeder turnover creates allelic variation in groups of gray wolves","interactions":[],"lastModifiedDate":"2026-02-23T16:53:42.236719","indexId":"70274058","displayToPublicDate":"2025-09-23T10:44:27","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1890,"text":"Heredity","active":true,"publicationSubtype":{"id":10}},"title":"Breeder turnover creates allelic variation in groups of gray wolves","docAbstract":"Genetic diversity is an important driver affecting the health of wildlife populations. In cooperatively breeding species, human impacts and breeder turnover can affect genetic diversity in groups. We generally do not have strong inferences about how the genetic composition of a group changes through time as individuals are lost (e.g., die, emigrate) or adopted (e.g., immigrate). I wanted to know how breeder turnover, group size, and harvest affected the fluctuation of unique alleles in groups of gray wolves (Canis lupus) in Idaho, USA, during 2008–2020. Turnover of breeding males was strongly associated with allelic change in groups. Turnover of breeding females also had a strong association with allelic change in groups, but was not the most supported model. Harvest was strongly correlated with breeding female turnover but not breeding male turnover. Outside of breeding female turnover, harvest generally had little effect on allelic change in groups. Groups rarely adopted new individuals unless there was a breeding vacancy. I show that over time groups gain and lose alleles in roughly equal proportions, but there are episodic changes to alleles in groups as a function of breeding male turnover. These findings have implications for how we define and evaluate group persistence and breeder lineages in cooperative breeders. Such definitions have important implications for studying the evolution and maintenance of cooperative breeding. It may be beneficial to define characteristics and vital rates of groups based, at least in part, on their underlying genetics when such information can be obtained.
","language":"English","doi":"10.1038/s41437-025-00788-4","usgsCitation":"Ausband, D.E., 2025, Breeder turnover creates allelic variation in groups of gray wolves: Heredity, v. 134, p. 577-583, https://doi.org/10.1038/s41437-025-00788-4.","productDescription":"7 p.","startPage":"577","endPage":"583","ipdsId":"IP-172832","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":500588,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41437-025-00788-4","text":"Publisher Index Page"},{"id":500422,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","volume":"134","noUsgsAuthors":false,"publicationDate":"2025-09-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Ausband, David Edward 0000-0001-9204-9837","orcid":"https://orcid.org/0000-0001-9204-9837","contributorId":275329,"corporation":false,"usgs":true,"family":"Ausband","given":"David","email":"","middleInitial":"Edward","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":956322,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70271918,"text":"70271918 - 2025 - Fluid inclusion constraints on the geometry of the magmatic plumbing system beneath Mauna Loa – Part 2: Xenoliths","interactions":[],"lastModifiedDate":"2025-09-25T13:17:30.283112","indexId":"70271918","displayToPublicDate":"2025-09-23T10:25:47","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1109,"text":"Bulletin of Volcanology","active":true,"publicationSubtype":{"id":10}},"title":"Fluid inclusion constraints on the geometry of the magmatic plumbing system beneath Mauna Loa – Part 2: Xenoliths","docAbstract":"Mauna Loa volcano erupts crystal-poor material at its summit and more crystal-rich material on its rift zones. Some of the more olivine-rich lava flows contain xenoliths with diverse mineralogy, including cumulate harzburgites with high-Mg# orthopyroxenes and high-Fo olivines (both > 84). Previous experimental work and thermodynamic modelling has proposed that high-Mg# orthopyroxenes only crystallize from Mauna Loa melts at high pressures (> 6 kbar, > 20 km), leading to suggestions that there is a region of sub-Moho magma storage at Mauna Loa in addition to the geophysically imaged magma reservoir at 2–5 km depth below the summit. We use melt and fluid inclusion barometry combined with thermodynamic models to further investigate this suggestion. Fluid inclusion data from harzburgites and dunitic xenoliths yield storage depths remarkably similar to those found in non-xenolithic crystals from lavas and tephras, with a clear peak at ~ 2–3 km (below the summit). Depths from melt inclusions in these xenoliths overlap with fluid inclusion pressures, ruling out the possibility of fluid inclusion re-equilibration during a period of stalling in a shallower reservoir. We examine five different thermodynamic models and find that the minimum pressure of olivine-orthopyroxene co-saturation varies by ~ 4 kbar (~ 12 km). These models also fail to predict that orthopyroxene is stable in ~ 15–80% of compositionally relevant experimental charges which grew orthopyroxene. Overall, this shows that phase stability modelling is an unreliable method of determining magma storage depth at Mauna Loa. We suggest that model discrepancies reflect a lack of experimental constraints on orthopyroxene stability at > 1200 ℃ and 0.01–5 kbar. Based on the presence of large oikocrystic orthopyroxenes completely enclosing rounded olivine chadacrysts, we suggest that these harzburgitic xenoliths formed through the reaction of intruding melts with olivine mush piles within the Mauna Loa edifice at ~ 3 km depth below the summit, with no need for a deeper storage reservoir. The predominance of pre-eruptive shallow storage means that there is more chance of detecting reservoir destabilization with geophysical monitoring techniques compared to a scenario where melts are supplied from sub-Moho reservoirs.
","language":"English","publisher":"Springer","doi":"10.1007/s00445-025-01869-2","usgsCitation":"Wieser, P.E., Gleeson, M., Rangel, B., DeVitre, C., Bearden, A.T., Lynn, K.J., Antoshechkina, P., Gaffney, A., and Monteleone, B., 2025, Fluid inclusion constraints on the geometry of the magmatic plumbing system beneath Mauna Loa – Part 2: Xenoliths: Bulletin of Volcanology, v. 87, 86, 24 p., https://doi.org/10.1007/s00445-025-01869-2.","productDescription":"86, 24 p.","ipdsId":"IP-176666","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":496156,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s00445-025-01869-2","text":"Publisher Index Page"},{"id":496014,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Mauna Loa","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -155.33750669977726,\n 19.719087637337836\n ],\n [\n -155.9431663120125,\n 19.719087637337836\n ],\n [\n -155.9431663120125,\n 18.997816607636395\n ],\n [\n -155.33750669977726,\n 18.997816607636395\n ],\n [\n -155.33750669977726,\n 19.719087637337836\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"87","noUsgsAuthors":false,"publicationDate":"2025-09-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Wieser, Penny E. 0000-0002-1070-8323","orcid":"https://orcid.org/0000-0002-1070-8323","contributorId":272601,"corporation":false,"usgs":false,"family":"Wieser","given":"Penny","email":"","middleInitial":"E.","affiliations":[{"id":27136,"text":"University of Cambridge","active":true,"usgs":false}],"preferred":false,"id":949375,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gleeson, Matthew","contributorId":346331,"corporation":false,"usgs":false,"family":"Gleeson","given":"Matthew","email":"","affiliations":[{"id":36942,"text":"University of California, Berkeley","active":true,"usgs":false}],"preferred":false,"id":949376,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rangel, Berenise","contributorId":346222,"corporation":false,"usgs":false,"family":"Rangel","given":"Berenise","email":"","affiliations":[{"id":13243,"text":"University of California Berkeley","active":true,"usgs":false}],"preferred":false,"id":949377,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"DeVitre, Charlotte","contributorId":346229,"corporation":false,"usgs":false,"family":"DeVitre","given":"Charlotte","email":"","affiliations":[{"id":13243,"text":"University of California Berkeley","active":true,"usgs":false}],"preferred":false,"id":949378,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bearden, Alexander T.","contributorId":361751,"corporation":false,"usgs":false,"family":"Bearden","given":"Alexander","middleInitial":"T.","affiliations":[{"id":36942,"text":"University of California, Berkeley","active":true,"usgs":false}],"preferred":false,"id":949379,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lynn, Kendra J. 0000-0001-7886-4376","orcid":"https://orcid.org/0000-0001-7886-4376","contributorId":290327,"corporation":false,"usgs":true,"family":"Lynn","given":"Kendra","email":"","middleInitial":"J.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":949380,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Antoshechkina, Paula 0000-0002-3358-5186","orcid":"https://orcid.org/0000-0002-3358-5186","contributorId":272605,"corporation":false,"usgs":false,"family":"Antoshechkina","given":"Paula","email":"","affiliations":[{"id":7218,"text":"California Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":949381,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Gaffney, Amy","contributorId":361752,"corporation":false,"usgs":false,"family":"Gaffney","given":"Amy","affiliations":[{"id":13621,"text":"Lawrence Livermore National Laboratory","active":true,"usgs":false}],"preferred":false,"id":949382,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Monteleone, Brian","contributorId":361754,"corporation":false,"usgs":false,"family":"Monteleone","given":"Brian","affiliations":[{"id":36711,"text":"Woods Hole Oceanographic Institution","active":true,"usgs":false}],"preferred":false,"id":949383,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70271943,"text":"70271943 - 2025 - A simple predictive model for salt marsh internal deterioration under sea-level rise and sediment deficits: Application to Chesapeake Bay","interactions":[],"lastModifiedDate":"2025-09-25T14:37:46.76289","indexId":"70271943","displayToPublicDate":"2025-09-23T09:32:17","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1584,"text":"Estuaries and Coasts","active":true,"publicationSubtype":{"id":10}},"title":"A simple predictive model for salt marsh internal deterioration under sea-level rise and sediment deficits: Application to Chesapeake Bay","docAbstract":"Salt marshes are dynamic biogeomorphic systems reliant on autochthonous and allochthonous input to maintain their three-dimensional configuration. Sea-level rise, subsidence, and sediment deficits can lead to submergence, open-water expansion, and ultimately loss of the vegetated marsh plain and associated ecosystem services. Widely used management-focused models focus on vegetation zonation in response to sea level but neglect sediment transport processes and geomorphic change. Process-based research models attempt to represent complex physical and biogeomorphic interactions but operate on spatiotemporal scales that are not directly transferable to restoration or management. Here we bridge these two paradigms and present a novel geomorphic model (UBMorph) based on the sediment-based lifespan concept that accounts for sea-level rise and open-water expansion to predict changes in salt marsh area in Chesapeake Bay. Model parameters such as surface accretion rate and elevation-to-areal loss fraction are selected using a separate, fully coupled biogeomorphic model (MarshMorpho2D) and the predicted lifespan is then compared with high marsh coverage from a zonation model (SLAMM). Across all of Chesapeake Bay, UBMorph estimates an overall loss of 404 km2 (37%) of vegetated marsh area under a dynamic 3–12 mm/y sea-level rise scenario (between 2010 and 2110). We then demonstrate a management-focused application of UBMorph and SLAMM used in tandem, for developing both a marsh condition and restoration model of the Chesapeake Bay portion of Maryland. The restoration model, which includes hydrologic intervention and sediment placement actions, indicates that ~ 400 km2 of marsh require either no intervention or low effort hydrologic intervention presently, whereas if no action is taken, over 700 km2 will require high effort intervention by 2070. This synthesis of research models with management-focused decision models demonstrates a tangible advance in bridging the gap between process-based research and restoration needs.
","language":"English","publisher":"Springer","doi":"10.1007/s12237-025-01618-w","usgsCitation":"Ganju, N., Ackerman, K., Defne, Z., Mariotti, G., Curson, D., Posnik, Z., Carr, J., and Grand, J., 2025, A simple predictive model for salt marsh internal deterioration under sea-level rise and sediment deficits: Application to Chesapeake Bay: Estuaries and Coasts, v. 48, 178, 19 p., https://doi.org/10.1007/s12237-025-01618-w.","productDescription":"178, 19 p.","ipdsId":"IP-177384","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":496166,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s12237-025-01618-w","text":"Publisher Index Page"},{"id":496080,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland, Virginia","otherGeospatial":"Chesapeake Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -75.56007683480865,\n 39.662435478342644\n ],\n [\n -77.02265802866081,\n 39.662435478342644\n ],\n [\n -77.02265802866081,\n 36.851268885158845\n ],\n [\n -75.56007683480865,\n 36.851268885158845\n ],\n [\n -75.56007683480865,\n 39.662435478342644\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"48","noUsgsAuthors":false,"publicationDate":"2025-09-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Ganju, Neil K. 0000-0002-1096-0465","orcid":"https://orcid.org/0000-0002-1096-0465","contributorId":202878,"corporation":false,"usgs":true,"family":"Ganju","given":"Neil K.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":949455,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ackerman, Kate 0000-0003-3925-721X","orcid":"https://orcid.org/0000-0003-3925-721X","contributorId":293631,"corporation":false,"usgs":true,"family":"Ackerman","given":"Kate","email":"","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":949456,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Defne, Zafer 0000-0003-4544-4310 zdefne@usgs.gov","orcid":"https://orcid.org/0000-0003-4544-4310","contributorId":5520,"corporation":false,"usgs":true,"family":"Defne","given":"Zafer","email":"zdefne@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":949457,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mariotti, Giulio","contributorId":207541,"corporation":false,"usgs":false,"family":"Mariotti","given":"Giulio","email":"","affiliations":[{"id":37557,"text":"Louisiana State University, Baton Rouge LA","active":true,"usgs":false}],"preferred":false,"id":949458,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Curson, David","contributorId":361793,"corporation":false,"usgs":false,"family":"Curson","given":"David","affiliations":[{"id":86352,"text":"Audubon Mid-Atlantic","active":true,"usgs":false}],"preferred":false,"id":949459,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Posnik, Zachary","contributorId":361794,"corporation":false,"usgs":false,"family":"Posnik","given":"Zachary","affiliations":[{"id":27800,"text":"National Audubon Society","active":true,"usgs":false}],"preferred":false,"id":949460,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Carr, Joel 0000-0002-9164-4156 jcarr@usgs.gov","orcid":"https://orcid.org/0000-0002-9164-4156","contributorId":220098,"corporation":false,"usgs":true,"family":"Carr","given":"Joel","email":"jcarr@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":949461,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Grand, Joanna","contributorId":291964,"corporation":false,"usgs":false,"family":"Grand","given":"Joanna","email":"","affiliations":[{"id":27800,"text":"National Audubon Society","active":true,"usgs":false}],"preferred":false,"id":949462,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70271936,"text":"70271936 - 2025 - River-to-lake transitional areas contribute disproportionately to in-lake nutrient loading","interactions":[],"lastModifiedDate":"2025-09-25T14:31:08.098564","indexId":"70271936","displayToPublicDate":"2025-09-23T09:22:46","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":22676,"text":"Ocean-Land-Atmosphere Research","active":true,"publicationSubtype":{"id":10}},"title":"River-to-lake transitional areas contribute disproportionately to in-lake nutrient loading","docAbstract":"River-to-lake transitional areas are biogeochemically active sections of the aquatic continuum that are often understudied compared to their adjoining environments. Internal nutrient loading from river-to-lake transitional areas may be a considerable source of nutrients to lakes and if overlooked disconnect upstream management initiatives from in-lake improvements. To contextualize internal nutrient loading by river-to-lake sediments, we conducted sediment core incubations and nutrient assays at 3 time points over a field season from a major contributing tributary of Lake Erie. Using statistical and spatial interpolation models, we upscaled internal nitrogen and phosphorus loading rates across the highly impaired mouth of the Maumee River, which drains into the western basin of Lake Erie. We found that internal nutrient dynamics in this river-to-lake transitional area were regulated by spatial differences in the physical composition and nutrient and organic matter contents of sediments. The Maumee river-to-lake transitional area was largely a source of phosphorus and ammonium nitrogen and a sink of nitrate nitrogen through high denitrification rates. Yet, we observed substantial temporal variation whereby internal nutrient loading was greatest in late summer coinciding with near-zero denitrification. Sediments at this time could contribute an additional ~17% more soluble reactive phosphorus and ~3% more total kjeldahl nitrogen in the bioavailable ammonium nitrogen fraction relative to the daily external nutrient load. High internal nutrient loading rates compared to more offshore areas in western Lake Erie suggest that this degraded river-to-lake transitional area has a disproportional biogeochemical significance and a high potential to contribute to nearshore water quality issues.
","language":"English","publisher":"AAAS","doi":"10.34133/olar.0109","usgsCitation":"Pearce, N.J., Larson, J.H., Kreiling, R.M., Evans, M.A., Bailey, S., Gierke, K., Bartsch, L., Xenopoulos, M.A., and Frost, P.C., 2025, River-to-lake transitional areas contribute disproportionately to in-lake nutrient loading: Ocean-Land-Atmosphere Research, v. 4, 0109, 14 p., https://doi.org/10.34133/olar.0109.","productDescription":"0109, 14 p.","ipdsId":"IP-150298","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":496165,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.34133/olar.0109","text":"Publisher Index Page"},{"id":496079,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Ohio","city":"Toledo","otherGeospatial":"Maumee River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -83.38205515826293,\n 41.76996302990986\n ],\n [\n -83.84330521317538,\n 41.76996302990986\n ],\n [\n -83.84330521317538,\n 41.398023594519884\n ],\n [\n -83.38205515826293,\n 41.398023594519884\n ],\n [\n -83.38205515826293,\n 41.76996302990986\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"4","noUsgsAuthors":false,"publicationDate":"2025-09-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Pearce, Nolan J.T. 0000-0001-6600-5275","orcid":"https://orcid.org/0000-0001-6600-5275","contributorId":268195,"corporation":false,"usgs":false,"family":"Pearce","given":"Nolan","email":"","middleInitial":"J.T.","affiliations":[{"id":36679,"text":"Trent University","active":true,"usgs":false}],"preferred":false,"id":949440,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Larson, James H. 0000-0002-6414-9758 jhlarson@usgs.gov","orcid":"https://orcid.org/0000-0002-6414-9758","contributorId":4250,"corporation":false,"usgs":true,"family":"Larson","given":"James","email":"jhlarson@usgs.gov","middleInitial":"H.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":949441,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kreiling, Rebecca M. 0000-0002-9295-4156","orcid":"https://orcid.org/0000-0002-9295-4156","contributorId":202193,"corporation":false,"usgs":true,"family":"Kreiling","given":"Rebecca","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":949442,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Evans, Mary Anne 0000-0002-1627-7210 maevans@usgs.gov","orcid":"https://orcid.org/0000-0002-1627-7210","contributorId":149358,"corporation":false,"usgs":true,"family":"Evans","given":"Mary","email":"maevans@usgs.gov","middleInitial":"Anne","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":949443,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bailey, Sean 0000-0003-0361-7914 sbailey@usgs.gov","orcid":"https://orcid.org/0000-0003-0361-7914","contributorId":198515,"corporation":false,"usgs":true,"family":"Bailey","given":"Sean","email":"sbailey@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":949444,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gierke, Kenna J. 0000-0002-8358-7825","orcid":"https://orcid.org/0000-0002-8358-7825","contributorId":342009,"corporation":false,"usgs":false,"family":"Gierke","given":"Kenna J.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":false,"id":949445,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bartsch, Lynn 0000-0002-1483-4845","orcid":"https://orcid.org/0000-0002-1483-4845","contributorId":361779,"corporation":false,"usgs":false,"family":"Bartsch","given":"Lynn","affiliations":[{"id":85472,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":false}],"preferred":false,"id":949446,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Xenopoulos, Marguerite A. 0000-0003-2307-948X","orcid":"https://orcid.org/0000-0003-2307-948X","contributorId":361780,"corporation":false,"usgs":false,"family":"Xenopoulos","given":"Marguerite","middleInitial":"A.","affiliations":[{"id":36679,"text":"Trent University","active":true,"usgs":false}],"preferred":false,"id":949447,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Frost, Paul C. 0000-0002-8267-1726","orcid":"https://orcid.org/0000-0002-8267-1726","contributorId":361782,"corporation":false,"usgs":false,"family":"Frost","given":"Paul","middleInitial":"C.","affiliations":[{"id":36679,"text":"Trent University","active":true,"usgs":false}],"preferred":false,"id":949448,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70274008,"text":"70274008 - 2025 - Integrated species distribution model using historical data shows decline in a common semi-aquatic mammal","interactions":[],"lastModifiedDate":"2026-02-23T15:59:43.189031","indexId":"70274008","displayToPublicDate":"2025-09-23T08:54:13","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":774,"text":"Animal Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Integrated species distribution model using historical data shows decline in a common semi-aquatic mammal","docAbstract":"Effective conservation requires an understanding of drivers of a species' distribution as well as long-term changes in their distribution. In recent decades, advances in data collection and analysis have allowed researchers to integrate a wide range of information to model species distributions, particularly by allowing presence-only data and detection-nondetection data to be formally combined in integrated species distribution models (ISDMs). However, these models are rarely used to investigate long-term trends, which are important in evaluating a species' status. Here, we use historical presence-only data of river otters (Lontra canadensis; 366 latrine locations from 1999 to 2007 and 105 locations of road-killed individuals recorded from 1999 to 2020) and 919 detection-nondetection surveys from 230 sites between 2021 and 2023 to understand the current distribution of river otters in Rhode Island, USA, as well as the changes in river otter distribution over the past two decades. We found that river otters were strongly associated with key habitat features such as streams and water, positively associated with urban areas, and tolerant of some contaminants, such as lead. Furthermore, despite uncertainties in historical river otter occurrence, we found clear supporting evidence that river otter intensity of use had declined from 1999 to 2023. This decline occurred despite being protected from harvest and in contrast to range expansions in other parts of the northeastern USA throughout the second half of the 20th century. Our results suggest the utility of this approach to detect declines in species for which historical data are available and a need for better understanding the cause of river otter declines. Where monitoring consists of opportunistically collected data, species conservation could benefit by continuing to collect these data as well as introducing designed surveys, as this would allow better integration of data types, improving trend estimation and reducing the amount of (typically more expensive) designed surveys needed.
","language":"English","publisher":"Zoological Society of London","doi":"10.1111/acv.70036","usgsCitation":"Crockett, J.G., Brown, C.B., Gerber, B., 2025, Integrated species distribution model using historical data shows decline in a common semi-aquatic mammal: Animal Conservation, 15 p., https://doi.org/10.1111/acv.70036.","productDescription":"15 p.","ipdsId":"IP-178855","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":500623,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/acv.70036","text":"Publisher Index Page"},{"id":500410,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Rhode Island","otherGeospatial":"Blackstone River, Block Island Sound, Narragansett 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0000-0001-9285-9784","orcid":"https://orcid.org/0000-0001-9285-9784","contributorId":354265,"corporation":false,"usgs":true,"family":"Gerber","given":"Brian Daniel","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":956113,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70272026,"text":"70272026 - 2025 - Amitriptyline and nortriptyline induce ocular toxicity in early life stage zebrafish (Danio rerio) ","interactions":[],"lastModifiedDate":"2025-11-13T15:10:44.848184","indexId":"70272026","displayToPublicDate":"2025-09-23T08:06:59","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":18327,"text":"Comparative Biochemistry and Physiology Part C: Toxicology & Pharmacology","active":true,"publicationSubtype":{"id":10}},"title":"Amitriptyline and nortriptyline induce ocular toxicity in early life stage zebrafish (Danio rerio) ","docAbstract":"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":382,"text":"Michigan Water Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","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. Grace","contributorId":361691,"corporation":false,"usgs":false,"family":"Klinges","given":"J.","middleInitial":"Grace","affiliations":[{"id":6607,"text":"Arizona State University","active":true,"usgs":false}],"preferred":false,"id":949236,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Maher, Rebecca","contributorId":361692,"corporation":false,"usgs":false,"family":"Maher","given":"Rebecca","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":949237,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Messyasz, Adrianna","contributorId":361693,"corporation":false,"usgs":false,"family":"Messyasz","given":"Adrianna","affiliations":[{"id":12727,"text":"Rutgers University","active":true,"usgs":false}],"preferred":false,"id":949238,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Seabrook, Sarah","contributorId":361694,"corporation":false,"usgs":false,"family":"Seabrook","given":"Sarah","affiliations":[{"id":86326,"text":"National Institute of Water and Atmospheric Research; Victoria University of Wellington","active":true,"usgs":false}],"preferred":false,"id":949239,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Thurber, Andrew","contributorId":169159,"corporation":false,"usgs":false,"family":"Thurber","given":"Andrew","affiliations":[{"id":25426,"text":"OSU","active":true,"usgs":false}],"preferred":false,"id":949240,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Correa, Adrienne","contributorId":361695,"corporation":false,"usgs":false,"family":"Correa","given":"Adrienne","affiliations":[{"id":86327,"text":"Rice University; University of California","active":true,"usgs":false}],"preferred":false,"id":949241,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Vega Thurber, Rebecca","contributorId":361696,"corporation":false,"usgs":false,"family":"Vega Thurber","given":"Rebecca","affiliations":[{"id":86328,"text":"Oregon State University; University of California","active":true,"usgs":false}],"preferred":false,"id":949242,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70271944,"text":"70271944 - 2025 - Accounting for seasonal patterns in bird availability prevents biased population trend estimates with advancing spring phenology","interactions":[],"lastModifiedDate":"2026-02-09T15:59:54.888313","indexId":"70271944","displayToPublicDate":"2025-09-20T09:42:37","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9101,"text":"Ornithological Applications","printIssn":"0010-5422","active":true,"publicationSubtype":{"id":10}},"title":"Accounting for seasonal patterns in bird availability prevents biased population trend estimates with advancing spring phenology","docAbstract":"Advancing spring phenology has been observed around the world, including changes in the timing of breeding of birds. 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.
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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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0000-0002-1307-4784","orcid":"https://orcid.org/0000-0002-1307-4784","contributorId":331334,"corporation":false,"usgs":true,"family":"Chamberlin","given":"Catherine","email":"","middleInitial":"A.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":949547,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lombard, Melissa A. 0000-0001-5924-6556 mlombard@usgs.gov","orcid":"https://orcid.org/0000-0001-5924-6556","contributorId":198254,"corporation":false,"usgs":true,"family":"Lombard","given":"Melissa","email":"mlombard@usgs.gov","middleInitial":"A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":949548,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Diehl, Timothy H. 0000-0001-9691-2212 thdiehl@usgs.gov","orcid":"https://orcid.org/0000-0001-9691-2212","contributorId":546,"corporation":false,"usgs":true,"family":"Diehl","given":"Timothy","email":"thdiehl@usgs.gov","middleInitial":"H.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true}],"preferred":true,"id":949549,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Galanter, Amy E. 0000-0002-2960-0136","orcid":"https://orcid.org/0000-0002-2960-0136","contributorId":219038,"corporation":false,"usgs":true,"family":"Galanter","given":"Amy","email":"","middleInitial":"E.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":949550,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Gorman Sanisaca, Lillian E. 0000-0003-1711-3864","orcid":"https://orcid.org/0000-0003-1711-3864","contributorId":210381,"corporation":false,"usgs":true,"family":"Gorman Sanisaca","given":"Lillian","middleInitial":"E.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":949551,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Stewart, Jana S. 0000-0002-8121-1373","orcid":"https://orcid.org/0000-0002-8121-1373","contributorId":211037,"corporation":false,"usgs":true,"family":"Stewart","given":"Jana","middleInitial":"S.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":949552,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70271484,"text":"sir20255079 - 2025 - Microbial source tracking in Cedar and Crane Creeks near Curtice, Ohio, 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.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255079","collaboration":"Prepared in cooperation with the Ohio Environmental Protection Agency","usgsCitation":"Kephart, C.M., and Lynch, L.D., 2025, Microbial source tracking in Cedar and Crane Creeks near Curtice, Ohio, 2021: U.S. Geological Survey Scientific Investigations Report 2025–5079, 15 p., https://doi.org/10.3133/sir20255079.","productDescription":"Report: vii, 15 p.; 2 Dataset: Project Site","numberOfPages":"15","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-161982","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":495806,"rank":8,"type":{"id":18,"text":"Project Site"},"url":"https://www.usgs.gov/labs/ohio-water-microbiology-laboratory","text":"Ohio Water Microbiology Laboratory"},{"id":495702,"rank":7,"type":{"id":28,"text":"Dataset"},"url":"https://api.waterdata.usgs.gov/samples-data/results/fullbio?mimeType=text%2Fcsv&monitoringLocationIdentifier=USGS-413609083223700&monitoringLocationIdentifier=USGS-413627083212700&monitoringLocationIdentifier=USGS-413642083234700&monitoringLocationIdentifier=USGS-413644083201700&monitoringLocationIdentifier=USGS-413644083201701&monitoringLocationIdentifier=USGS-413657083223700&monitoringLocationIdentifier=USGS-413704083214700&monitoringLocationIdentifier=USGS-413705083194800&monitoringLocationIdentifier=USGS-413705083220200&monitoringLocationIdentifier=USGS-413719083190700&monitoringLocationIdentifier=USGS-413727083210300&monitoringLocationIdentifier=USGS-413736083195300","text":"USGS National Water Information System database","linkFileType":{"id":7,"text":"csv"},"linkHelpText":"- Data for all 12 monitoring locations"},{"id":495701,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"- USGS water data for the Nation"},{"id":495700,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5079/images/"},{"id":495699,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5079/sir20255079.XML","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2025-5079 XML"},{"id":495698,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255079/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2025-5079 HTML"},{"id":495697,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5079/sir20255079.pdf","text":"Report","size":"2.11 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5079 PDF"},{"id":495696,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5079/coverthb.jpg"}],"country":"United States","state":"Ohio","city":"Curtice","otherGeospatial":"Cedar and Crane Creeks","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -83.4,\n 41.65\n ],\n [\n -83.4,\n 41.567\n ],\n [\n -83.3167,\n 41.567\n ],\n [\n -83.3167,\n 41.65\n ],\n [\n -83.4,\n 41.65\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Ohio-Kentucky-Indiana Water Science Center
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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":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":456,"text":"National Wildlife Health Center","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":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","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