Understanding the factors that regulate population dynamics is crucial for conserving imperiled species. Bull trout (Salvelinus confluentus), a piscivorous salmonid and one of North America's most threatened cold-water species, has declined significantly due to habitat loss, overfishing, invasive species, and climate change. While recovery efforts have primarily targeted these threats, the role of prey availability in influencing bull trout population dynamics under multiple stressors remains poorly understood. Using a stage-based integrated population model, we quantified the effects of non-native prey availability (kokanee; Oncorhynchus nerka), angling pressure, climatic variation, and density-dependent processes on bull trout population dynamics in Lake Koocanusa, a transboundary reservoir and river system (United States and Canada), over a 40-year period (1980–2023). Our results show that bull trout populations are regulated by density-dependent processes, including over-compensation in sub-adult recruitment and reduced adult survival at high densities. Increased kokanee biomass and restricted harvest significantly enhanced bull trout survival and abundance, whereas reduced water availability had a limited negative effect on sub-adult production. Model simulations indicate that as kokanee biomass availability increases, the number of bull trout that can be sustainably harvested also increases. In fact, a modest annual fishery (300 individuals) can be sustained, especially under moderate to high kokanee biomass conditions. These results underscore the importance of prey availability, including non-native species, in supporting bull trout populations. Effective management of threatened apex fish predators like bull trout requires addressing the complex interplay between environmental threats, prey dynamics, and density-dependent mechanisms across all life stages.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.70103","usgsCitation":"Cochrane, M., Cline, T., Schmidt, T.S., Dunnigan, J., Warnock, W., and Muhlfeld, C.C., 2025, Non-native prey availability and over-compensatory density dependence drive population dynamics of a native fish predator: Ecological Applications, v. 35, no. 7, e70103, 16 p., https://doi.org/10.1002/eap.70103.","productDescription":"e70103, 16 p.","ipdsId":"IP-173240","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":496925,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/eap.70103","text":"Publisher Index Page"},{"id":496789,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"British Columbia, Montana","otherGeospatial":"Lake Koocanusa","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -115.41674082695792,\n 49.37701492800039\n ],\n [\n -115.41674082695792,\n 48.769300021930604\n ],\n [\n -115.08255833560938,\n 48.769300021930604\n ],\n [\n -115.08255833560938,\n 49.37701492800039\n ],\n [\n -115.41674082695792,\n 49.37701492800039\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"35","issue":"7","noUsgsAuthors":false,"publicationDate":"2025-10-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Cochrane, Madaline","contributorId":362831,"corporation":false,"usgs":false,"family":"Cochrane","given":"Madaline","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":950747,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cline, Timothy","contributorId":339987,"corporation":false,"usgs":false,"family":"Cline","given":"Timothy","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":950748,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schmidt, Travis S. 0000-0003-1400-0637 tschmidt@usgs.gov","orcid":"https://orcid.org/0000-0003-1400-0637","contributorId":221742,"corporation":false,"usgs":true,"family":"Schmidt","given":"Travis","email":"tschmidt@usgs.gov","middleInitial":"S.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"preferred":true,"id":950749,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dunnigan, James","contributorId":279960,"corporation":false,"usgs":false,"family":"Dunnigan","given":"James","affiliations":[{"id":48633,"text":"MT FWP","active":true,"usgs":false}],"preferred":false,"id":950750,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Warnock, Will","contributorId":362833,"corporation":false,"usgs":false,"family":"Warnock","given":"Will","affiliations":[{"id":83135,"text":"British Columbia Ministry of Water, Land, and Resource Stewardship","active":true,"usgs":false}],"preferred":false,"id":950751,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Muhlfeld, Clint C. 0000-0002-4599-4059 cmuhlfeld@usgs.gov","orcid":"https://orcid.org/0000-0002-4599-4059","contributorId":924,"corporation":false,"usgs":true,"family":"Muhlfeld","given":"Clint","email":"cmuhlfeld@usgs.gov","middleInitial":"C.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":950752,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70273503,"text":"70273503 - 2025 - Near real-time indicators of burn severity in the western U.S. from active fire tracking","interactions":[],"lastModifiedDate":"2026-01-20T15:25:21.631459","indexId":"70273503","displayToPublicDate":"2025-10-07T08:18:27","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1636,"text":"Fire Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Near real-time indicators of burn severity in the western U.S. from active fire tracking","docAbstract":"Background
Timely information on wildfire burn severity is critical to assess and mitigate potential post-fire impacts on soils, vegetation, and hillslope stability. Tracking individual fire spread and intensity using satellite active fire data provides a pathway to near real-time (NRT) information. Here, we generated a large database (n = 2177) of wildfire events in the western United States (U.S.) between 2012 and 2021 using active fire detections from the Visible Infrared Imaging Radiometer Suite (VIIRS) sensor on the Suomi National Polar-orbiting Partnership (SNPP) satellite and the Fire Events Data Suite (FEDS) algorithm to track large fire growth every 12 h. We integrated fire tracking data with final fire perimeters and burn severity data from the Monitoring Trends in Burn Severity (MTBS) program to evaluate the relationship between burn severity and fire behavior metrics derived from the fire tracking approach, including the rate of fire spread and average fire radiative power (FRP) of fire detections for each 12-h growth increment.
Results
When stratified by vegetation type, FRP and rate of spread metrics were positively correlated with classified burn severity for each 12-h growth increment, highlighting the potential to rapidly identify areas of high and low severity burning. In forests, integrated measures of FRP over the fire lifetime captured persistent flaming and smoldering that compensated for initial differences between AM (01:30) and PM (13:30) fire detections. Predictive modeling of these relationships based on multiple fire behavior indicators and vegetation type from the LANDFIRE program yielded an accuracy of 78% for the separation of unburned/low and moderate/high burn severity classes.
Conclusions
These results demonstrate the ability to capture within-fire differences in burn severity using NRT indicators from fire tracking to assist with emergency management and disaster preparedness for post-fire hazards, such as landslides, debris flows, or changes in stream flow and water quality. As VIIRS data are available within minutes of each satellite overpass in the U.S., rapid estimates of burn severity based on fire tracking can be made days or weeks before a large wildfire is fully contained.
","language":"English","publisher":"Springer Nature","doi":"10.1186/s42408-025-00407-x","usgsCitation":"Orland, E., McCabe, T., Chen, Y., Scholten, R.C., Becker, Z., Loehman, R.A., Randerson, J.T., Coffield, S.R., Liu, T., Shiklomanov, A.N., Nelson, K., Peterson, B., Follette-Cook, M.B., and Morton, D.C., 2025, Near real-time indicators of burn severity in the western U.S. from active fire tracking: Fire Ecology, v. 21, 55, 18 p., https://doi.org/10.1186/s42408-025-00407-x.","productDescription":"55, 18 p.","ipdsId":"IP-170216","costCenters":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"links":[{"id":498919,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s42408-025-00407-x","text":"Publisher Index Page"},{"id":498774,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"western United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -124.28023348660705,\n 49.14849222332691\n ],\n [\n -124.28023348660705,\n 31.366087454025504\n ],\n [\n -101.57330654663889,\n 31.366087454025504\n ],\n [\n -101.57330654663889,\n 49.14849222332691\n ],\n [\n -124.28023348660705,\n 49.14849222332691\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"21","noUsgsAuthors":false,"publicationDate":"2025-10-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Orland, Elijah","contributorId":238845,"corporation":false,"usgs":false,"family":"Orland","given":"Elijah","email":"","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":954031,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCabe, Tempest","contributorId":365275,"corporation":false,"usgs":false,"family":"McCabe","given":"Tempest","affiliations":[{"id":7049,"text":"NASA Goddard Space Flight Center","active":true,"usgs":false}],"preferred":false,"id":954032,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chen, Yang","contributorId":192429,"corporation":false,"usgs":false,"family":"Chen","given":"Yang","email":"","affiliations":[],"preferred":false,"id":954033,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Scholten, Rebecca C. 0000-0002-0144-0572","orcid":"https://orcid.org/0000-0002-0144-0572","contributorId":365276,"corporation":false,"usgs":false,"family":"Scholten","given":"Rebecca","middleInitial":"C.","affiliations":[{"id":87119,"text":"Univ California Irvine","active":true,"usgs":false}],"preferred":false,"id":954034,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Becker, Zeb 0009-0008-1003-5529","orcid":"https://orcid.org/0009-0008-1003-5529","contributorId":365277,"corporation":false,"usgs":false,"family":"Becker","given":"Zeb","affiliations":[{"id":87120,"text":"NASA Goddard Space Flight Center/Univ Maryland","active":true,"usgs":false}],"preferred":false,"id":954035,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Loehman, Rachel A. 0000-0001-7680-1865 rloehman@usgs.gov","orcid":"https://orcid.org/0000-0001-7680-1865","contributorId":187605,"corporation":false,"usgs":true,"family":"Loehman","given":"Rachel","email":"rloehman@usgs.gov","middleInitial":"A.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"preferred":false,"id":954036,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Randerson, James T. 0000-0001-6559-7387","orcid":"https://orcid.org/0000-0001-6559-7387","contributorId":365278,"corporation":false,"usgs":false,"family":"Randerson","given":"James","middleInitial":"T.","affiliations":[{"id":87119,"text":"Univ California Irvine","active":true,"usgs":false}],"preferred":false,"id":954037,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Coffield, Shane R. 0000-0002-0550-5126","orcid":"https://orcid.org/0000-0002-0550-5126","contributorId":365279,"corporation":false,"usgs":false,"family":"Coffield","given":"Shane","middleInitial":"R.","affiliations":[{"id":7049,"text":"NASA Goddard Space Flight Center","active":true,"usgs":false}],"preferred":false,"id":954038,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Liu, Tianjia 0000-0003-3129-0154","orcid":"https://orcid.org/0000-0003-3129-0154","contributorId":365280,"corporation":false,"usgs":false,"family":"Liu","given":"Tianjia","affiliations":[{"id":52230,"text":"University of British Columbia, Vancouver, BC, Canada","active":true,"usgs":false}],"preferred":false,"id":954039,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Shiklomanov, Alexey N. 0000-0003-4022-5979","orcid":"https://orcid.org/0000-0003-4022-5979","contributorId":245541,"corporation":false,"usgs":false,"family":"Shiklomanov","given":"Alexey","email":"","middleInitial":"N.","affiliations":[{"id":49218,"text":"Boston University Department of Earth and Environment","active":true,"usgs":false}],"preferred":false,"id":954040,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Nelson, Kurtis 0000-0003-4911-4511 knelson@usgs.gov","orcid":"https://orcid.org/0000-0003-4911-4511","contributorId":3602,"corporation":false,"usgs":true,"family":"Nelson","given":"Kurtis","email":"knelson@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":954041,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Peterson, Birgit 0000-0002-4356-1540 bpeterson@usgs.gov","orcid":"https://orcid.org/0000-0002-4356-1540","contributorId":192353,"corporation":false,"usgs":true,"family":"Peterson","given":"Birgit","email":"bpeterson@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":954042,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Follette-Cook, Melanie B. 0000-0002-5648-584X","orcid":"https://orcid.org/0000-0002-5648-584X","contributorId":365282,"corporation":false,"usgs":false,"family":"Follette-Cook","given":"Melanie","middleInitial":"B.","affiliations":[{"id":7049,"text":"NASA Goddard Space Flight Center","active":true,"usgs":false}],"preferred":false,"id":954043,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Morton, Douglas C.","contributorId":225139,"corporation":false,"usgs":false,"family":"Morton","given":"Douglas","email":"","middleInitial":"C.","affiliations":[{"id":7049,"text":"NASA Goddard Space Flight Center","active":true,"usgs":false}],"preferred":false,"id":954044,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}} ,{"id":70272665,"text":"70272665 - 2025 - Host responses and viral traits interact to shape the impacts of climate warming on highly pathogenic avian influenza in migratory waterfowl","interactions":[],"lastModifiedDate":"2025-12-03T16:42:49.612362","indexId":"70272665","displayToPublicDate":"2025-10-06T10:36:55","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":22986,"text":"PLOS Computational Biology.","active":true,"publicationSubtype":{"id":10}},"title":"Host responses and viral traits interact to shape the impacts of climate warming on highly pathogenic avian influenza in migratory waterfowl","docAbstract":"Emerging infectious diseases pose threats to wildlife populations, as exemplified by recent outbreaks of avian influenza viruses in wild birds. Climate change can affect infection dynamics in wildlife through direct effects on pathogens (e.g., environmental decay rates) and changes to host ecology, including shifting migration patterns. Here, we adapt an existing mechanistic model that couples migration and infection to study how traits of highly pathogenic avian influenza (HPAI) viruses contribute to HPAI outcomes in migratory waterfowl, then apply this model to explore potential impacts of climate change on HPAI dynamics. We find that the simulated impacts of HPAI on the host population under baseline climate conditions varied from no impact to 100% mortality, depending on viral traits. In most cases, traits related to transmission (i.e., contact rates, shedding rates) were more important for HPAI establishment probability, infection prevalence, and mortality than were other viral traits (e.g., environmental temperature sensitivity, cross-protective immunity). We then simulated the effects of climate change (i.e., altered temperature regimes) on HPAI dynamics both via viral environmental decay and via changes in bird migration phenology. In these simulations, we found that a 9-day advancement in spring migration timing increased the duration of HPAI outbreaks by increasing time birds spent at their breeding grounds, leading to higher mortality and fewer infections. In contrast, increased viral decay in warmer years had a smaller, but opposite impact. These patterns depended on the primary transmission mode of HPAI (i.e., direct vs. environmental) and its sensitivity to environmental temperatures. Together, these results suggest that climate change is likely to increase the impacts of HPAI on waterfowl populations if HPAI relies strongly on direct transmission and birds advance their spring migration. Further integrating host-viral co-evolution and other climatic changes (e.g., salinity, humidity) could provide more precise predictions of how HPAI dynamics could change in the future.
","language":"English","publisher":"PLoS","doi":"10.1371/journal.pcbi.1013451","usgsCitation":"Teitelbaum, C.S., Casazza, M.L., Overton, C.T., Matchett, E., and Prosser, D.J., 2025, Host responses and viral traits interact to shape the impacts of climate warming on highly pathogenic avian influenza in migratory waterfowl: PLOS Computational Biology., v. 21, no. 10, e1013451, 22 p., https://doi.org/10.1371/journal.pcbi.1013451.","productDescription":"e1013451, 22 p.","ipdsId":"IP-157531","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":497119,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pcbi.1013451","text":"Publisher Index Page"},{"id":497015,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska, California, Oregon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -148.20078647084972,\n 61.26021297898512\n ],\n [\n -149.09364902779188,\n 62.66876277882301\n ],\n [\n -162.90133171617495,\n 63.7331238783043\n ],\n [\n -166.54926553897377,\n 61.85068028365225\n ],\n [\n -164.23587380154524,\n 59.41592981040935\n ],\n [\n -158.791073273557,\n 57.922862761320914\n ],\n [\n -148.20078647084972,\n 61.26021297898512\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -120.22676646003569,\n 44.192344518790605\n ],\n [\n -124.083446948291,\n 44.192344518790605\n ],\n [\n -124.083446948291,\n 36\n ],\n [\n -120.22676646003569,\n 36\n ],\n [\n -120.22676646003569,\n 44.192344518790605\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"21","issue":"10","noUsgsAuthors":false,"publicationDate":"2025-10-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Teitelbaum, Claire Stewart 0000-0001-5646-3184","orcid":"https://orcid.org/0000-0001-5646-3184","contributorId":295336,"corporation":false,"usgs":true,"family":"Teitelbaum","given":"Claire","email":"","middleInitial":"Stewart","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":951267,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Casazza, Michael L. 0000-0002-5636-735X mike_casazza@usgs.gov","orcid":"https://orcid.org/0000-0002-5636-735X","contributorId":2091,"corporation":false,"usgs":true,"family":"Casazza","given":"Michael","email":"mike_casazza@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":951268,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Overton, Cory T. 0000-0002-5060-7447 coverton@usgs.gov","orcid":"https://orcid.org/0000-0002-5060-7447","contributorId":3262,"corporation":false,"usgs":true,"family":"Overton","given":"Cory","email":"coverton@usgs.gov","middleInitial":"T.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":951269,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Matchett, Elliott 0000-0001-5095-2884 ematchett@usgs.gov","orcid":"https://orcid.org/0000-0001-5095-2884","contributorId":5541,"corporation":false,"usgs":true,"family":"Matchett","given":"Elliott","email":"ematchett@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":951270,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Prosser, Diann J. 0000-0002-5251-1799","orcid":"https://orcid.org/0000-0002-5251-1799","contributorId":221167,"corporation":false,"usgs":true,"family":"Prosser","given":"Diann","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":951271,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70274600,"text":"70274600 - 2025 - Ambient field seismology in critical zone hydrological sciences","interactions":[],"lastModifiedDate":"2026-04-01T15:12:52.682494","indexId":"70274600","displayToPublicDate":"2025-10-06T10:07:37","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":23777,"text":"Comptes Rendus. Géoscience","active":true,"publicationSubtype":{"id":10}},"title":"Ambient field seismology in critical zone hydrological sciences","docAbstract":"Passive ambient noise monitoring is an emerging tool in environmental seismology, leveraging the ambient seismic field to assess temporal variations in shallow subsurface properties. This review focuses on the potential and challenges of using scattered coda waves from noise correlation functions to monitor critical zone dynamics. The sensitivity of seismic velocities to various environmental factors, including precipitation, snowmelt, atmospheric pressure, and groundwater fluctuations, underscores the method’s versatility. While coda waves excel in detecting subtle changes due to their scattered nature, ballistic waves provide higher spatial resolution, albeit with challenges in source stability. Advances in seismic sensing, including distributed acoustic sensing and low-cost geophone networks, have enabled high-resolution monitoring of hydrological processes, subsurface deformation, and seismic hazards. Integrating seismic data with hydrological models provides insights into water storage, pore pressure changes, and soil moisture dynamics. However, limitations in spatial resolution, calibration with ground truth data, and coupled effects between environmental factors remain key challenges. This review emphasizes the importance of interdisciplinary approaches in refining methodologies, enhancing sensor deployments, and addressing data gaps. Passive seismic monitoring offers opportunities to understand critical zone processes and their broader impacts on seismic hazards and environmental sustainability.
","language":"English","publisher":"Academie des Sciences, Institut de France","doi":"10.5802/crgeos.310","usgsCitation":"Denolle, M.A., Shi, Q., Clements, T., Viens, L., Rodriguez-Tribaldos, V., and Cotton, F., 2025, Ambient field seismology in critical zone hydrological sciences: Comptes Rendus. Géoscience, v. 357, p. 425-451, https://doi.org/10.5802/crgeos.310.","productDescription":"27 p.","startPage":"425","endPage":"451","ipdsId":"IP-181097","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":502104,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5802/crgeos.310","text":"Publisher Index Page"},{"id":501930,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"357","noUsgsAuthors":false,"publicationDate":"2025-10-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Denolle, Marine A.","contributorId":345689,"corporation":false,"usgs":false,"family":"Denolle","given":"Marine","email":"","middleInitial":"A.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":958469,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shi, Qibin","contributorId":369115,"corporation":false,"usgs":false,"family":"Shi","given":"Qibin","affiliations":[{"id":49969,"text":"Department of Earth and Space Sciences, University of Washington, Seattle, WA, USA","active":true,"usgs":false}],"preferred":false,"id":958470,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Clements, Timothy Hugh 0000-0001-6632-1796","orcid":"https://orcid.org/0000-0001-6632-1796","contributorId":350753,"corporation":false,"usgs":true,"family":"Clements","given":"Timothy Hugh","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":958471,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Viens, Loic","contributorId":362345,"corporation":false,"usgs":false,"family":"Viens","given":"Loic","affiliations":[{"id":48588,"text":"Los Alamos National Lab","active":true,"usgs":false}],"preferred":false,"id":958472,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rodriguez-Tribaldos, Veronica","contributorId":369117,"corporation":false,"usgs":false,"family":"Rodriguez-Tribaldos","given":"Veronica","affiliations":[{"id":87725,"text":"GFZ Helmholtz Centre for Geosciences, Telegrafenberg 14473 Potsdam, Germany","active":true,"usgs":false}],"preferred":false,"id":958473,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cotton, Fabrice","contributorId":264167,"corporation":false,"usgs":false,"family":"Cotton","given":"Fabrice","email":"","affiliations":[],"preferred":false,"id":958474,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70272060,"text":"70272060 - 2025 - Diel and spatial variability in cyanobacterial composition, gene abundance, and toxin concentration: A pilot study","interactions":[],"lastModifiedDate":"2025-11-14T16:31:39.166686","indexId":"70272060","displayToPublicDate":"2025-10-06T09:26:11","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"Diel and spatial variability in cyanobacterial composition, gene abundance, and toxin concentration: A pilot study","docAbstract":"We designed a pilot field study to assess relations between sunlight, cyanobacteria, and cyanotoxins. In 2021, we collected day (07:00 h, 10:00 h, 13:00 h, 16:00 h) and night samples (19:00 h, 22:00 h, 01:00 h, 04:00 h) at two locations in Kabetogama Lake, MN, USA. One sample set was collected from the lakeward end of a boat dock and the other on the nearby shoreline. Cyanobacterial phylogenetic eDNA differences over 24 h (pseudo F = 2.0938, p = 0.127) were not significant. Copies of anatoxin (anaC) and microcystin (mcyE) synthetase genes varied significantly over the sampling times at the dock (Friedman Χ2 = 15.01, df = 7, p = 0.036; Friedman Χ2 = 19.22, df = 7, p = 0.008) and the shoreline (Friedman Χ2 = 19.33, df = 7, p = 0.007; Friedman Χ2 = 20.56, df = 7, p = 0.005), with the highest anaC counts occurring during the night for both sites. Additionally, the highest total and dissolved microcystin concentrations occurred at night. Despite the proximity of the sampling locations, cyanobacterial phylogenetic eDNA results indicate that the variability between sites (pseudo-F = 27.547, p = 0.001) were greater than temporal differences over 24 h (pseudo F = 2.0938, p = 0.127). Understanding the effect of diel and spatial variability may help researchers and resource managers make informed decisions about sampling and potential exposure.
","language":"English","publisher":"Springer Nature","doi":"10.1038/s41598-025-18453-5","usgsCitation":"Christensen, V., Katona, L.R., LeDuc, J.F., Maki, R.P., Olds, H., Smith, J.C., and Trompeter, H., 2025, Diel and spatial variability in cyanobacterial composition, gene abundance, and toxin concentration: A pilot study: Scientific Reports, v. 15, 34734, 15 p., https://doi.org/10.1038/s41598-025-18453-5.","productDescription":"34734, 15 p.","ipdsId":"IP-159489","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":496713,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-025-18453-5","text":"Publisher Index Page"},{"id":496495,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota","otherGeospatial":"Kabetogama Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -92.88007417752388,\n 48.44937256738547\n ],\n [\n -92.88007417752388,\n 48.422380750562496\n ],\n [\n -92.82383108449349,\n 48.422380750562496\n ],\n [\n -92.82383108449349,\n 48.44937256738547\n ],\n [\n -92.88007417752388,\n 48.44937256738547\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"15","noUsgsAuthors":false,"publicationDate":"2025-10-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Christensen, Victoria 0000-0003-4166-7461","orcid":"https://orcid.org/0000-0003-4166-7461","contributorId":220548,"corporation":false,"usgs":true,"family":"Christensen","given":"Victoria","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":949945,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Katona, Leon R. 0000-0001-5323-1871","orcid":"https://orcid.org/0000-0001-5323-1871","contributorId":331458,"corporation":false,"usgs":true,"family":"Katona","given":"Leon","email":"","middleInitial":"R.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":949946,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"LeDuc, Jaime F.","contributorId":362078,"corporation":false,"usgs":false,"family":"LeDuc","given":"Jaime","middleInitial":"F.","affiliations":[{"id":86459,"text":"Surfrider Foundation","active":true,"usgs":false}],"preferred":false,"id":949947,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Maki, Ryan P.","contributorId":362079,"corporation":false,"usgs":false,"family":"Maki","given":"Ryan","middleInitial":"P.","affiliations":[{"id":36245,"text":"NPS","active":true,"usgs":false}],"preferred":false,"id":949948,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Olds, Hayley T. 0000-0002-6701-6459 htolds@usgs.gov","orcid":"https://orcid.org/0000-0002-6701-6459","contributorId":215837,"corporation":false,"usgs":true,"family":"Olds","given":"Hayley","email":"htolds@usgs.gov","middleInitial":"T.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":949949,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Smith, James C.","contributorId":362080,"corporation":false,"usgs":false,"family":"Smith","given":"James","middleInitial":"C.","affiliations":[{"id":36245,"text":"NPS","active":true,"usgs":false}],"preferred":false,"id":949950,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Trompeter, Hailey Elizabeth 0009-0007-6855-5642","orcid":"https://orcid.org/0009-0007-6855-5642","contributorId":358493,"corporation":false,"usgs":true,"family":"Trompeter","given":"Hailey Elizabeth","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":949951,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70272115,"text":"70272115 - 2025 - Modeling diverse environmental responses of reservoirs to floating photovoltaic systems","interactions":[],"lastModifiedDate":"2025-11-17T16:13:07.875496","indexId":"70272115","displayToPublicDate":"2025-10-06T09:06:52","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5362,"text":"Limnologica - Ecology and Management of Inland Waters","active":true,"publicationSubtype":{"id":10}},"title":"Modeling diverse environmental responses of reservoirs to floating photovoltaic systems","docAbstract":"Floating photovoltaic (FPV) systems are emerging as a promising strategy for large-scale clean energy production worldwide. However, by altering key physical drivers such as solar radiation and wind mixing, FPV installations may have also unintended consequences for lakes and reservoirs. Given the wide diversity of freshwater systems globally, understanding the consistency in direction and magnitude of environmental responses to FPV deployment is critical for informed regulatory oversight and sustainable energy development. Here, we used process-based models to simulate the effects of FPV coverage on 11 reservoirs across the United States. This is the first multi-reservoir analysis using a laterally averaged 2D process-based modeling framework to systematically evaluate FPV impacts across diverse climatic and morphometric contexts, enabling direct comparison of magnitude and direction of responses among systems. Specifically, we evaluated changes in (1) surface and outflow temperature, (2) thermocline depth, (3) water column stability, (4) dissolved oxygen concentrations, and (5) potential suitable habitat availability for warm- and cold-water fishes. We quantified changes in these response variables by an iterative approach that simulates increases in FPV coverage and compares them with reference conditions. We summarized responses for winter (January–February) and summer (July–August). As expected, our simulations show that increasing FPV coverage consistently cooled surface waters and altered thermal stratification patterns, but the magnitude and environmental implications of these changes varied among reservoirs. Notably, greater FPV coverage led to increased variability in habitat suitability for aquatic species, with some reservoirs exhibiting distinct and sometimes divergent responses. These findings underscore the importance of considering local environmental contexts when assessing FPV impacts. While large-scale FPV systems offer potential benefits for climate mitigation, their ecological effects, particularly on thermally sensitive biota, require careful site-specific evaluation to avoid unintended consequences to local freshwater biodiversity.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.limno.2025.126293","usgsCitation":"Bredeweg, E.M., Arismendi, I., Murphy, C.A., and Henkel, S.K., 2025, Modeling diverse environmental responses of reservoirs to floating photovoltaic systems: Limnologica - Ecology and Management of Inland Waters, v. 115, 126293, 11 p., https://doi.org/10.1016/j.limno.2025.126293.","productDescription":"126293, 11 p.","ipdsId":"IP-171829","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":496552,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas, Idaho, Ohio, Oregon, Tennessee, Washington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"geometry\": {\n \"type\": \"MultiPolygon\",\n \"coordinates\": [\n [\n [\n [\n -94.81758,\n 49.38905\n ],\n [\n -94.64,\n 48.84\n ],\n [\n -94.32914,\n 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University","active":true,"usgs":false}],"preferred":false,"id":950131,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Murphy, Christina Amy 0000-0002-3467-6610","orcid":"https://orcid.org/0000-0002-3467-6610","contributorId":335232,"corporation":false,"usgs":true,"family":"Murphy","given":"Christina","email":"","middleInitial":"Amy","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":950132,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Henkel, Sarah K.","contributorId":362167,"corporation":false,"usgs":false,"family":"Henkel","given":"Sarah","middleInitial":"K.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":950133,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70272206,"text":"70272206 - 2025 - Submarine groundwater discharge creates cold‐water refugia that can mitigate exposure of heat stress in nearshore corals","interactions":[],"lastModifiedDate":"2025-11-19T15:22:46.012205","indexId":"70272206","displayToPublicDate":"2025-10-06T08:18:38","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}},"title":"Submarine groundwater discharge creates cold‐water refugia that can mitigate exposure of heat stress in nearshore corals","docAbstract":"Coral reef mortality around the world is accelerating due to human activities and rising sea temperatures that cause bleaching, which is expected to become more frequent. Our ability to predict which corals will be most resilient, however, remains limited due to insufficient information characterizing nearshore temperature and habitat conditions. In this study, we examine how submarine groundwater discharge (SGD) reduces nearshore water temperatures and exposure of corals to heat stress, complementing the understanding that SGD can adversely affect coral when it contains elevated nutrient concentrations. Data from fixed nearshore sensors and vertical depth profiles along ~100 km of the western shoreline of the Island of Hawai’i from 2003 to 2014 demonstrate that submarine groundwater discharge (SGD) can reduce nearshore water temperatures by 1 °C–5°C and create estuarine-like conditions with salinities as low as 20 PSU, where the prevalent coral species, Pocillopora meandrina, Porites lobata, and Montipora capitata, thrive. Time-series temperature records reveal that exposure to high ambient ocean temperatures, which are known to initiate bleaching events, are reduced up to 5%–46% of the time. Coral health surveys indicated coral bleaching in response to moderately high annual temperatures in 2010 and 2011, with more colonies affected farther from cold, SGD-fed waters. Synthesis of these results, along with coral response data following the more extreme marine heat wave of 2014–2015, demonstrates lower coral loss and greater coral recovery near groundwater seeps, particularly those with higher flux and influence on reducing nearshore water temperatures. Our results demonstrate that SGD may therefore provide a beneficial ecosystem service and enhance coral reef resilience, particularly where human-related nutrient additions to groundwater can be mitigated. The implications of our findings are relevant across tropical coasts where groundwater inputs can be substantial, such as the Caribbean and Indo-Pacific, and contribute to improving our understanding of coral sensitivity to gradients in temperature and nutrient stress. Improved management of groundwater resources could thus be vital to local–regional strategies for mitigating future heat stress.
","language":"English","publisher":"Frontiers","doi":"10.3389/fmars.2025.1621298","usgsCitation":"Grossman, E.E., Oberle, F.K., and Storlazzi, C.D., 2025, Submarine groundwater discharge creates cold‐water refugia that can mitigate exposure of heat stress in nearshore corals: Frontiers in Marine Science, v. 12, 1621298, 18 p., https://doi.org/10.3389/fmars.2025.1621298.","productDescription":"1621298, 18 p.","ipdsId":"IP-171287","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":496742,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fmars.2025.1621298","text":"Publisher Index Page"},{"id":496634,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -156.2635053313267,\n 20.047841438604692\n ],\n [\n -156.2635053313267,\n 19.356827231562278\n ],\n [\n -155.7474414544975,\n 19.356827231562278\n ],\n [\n -155.7474414544975,\n 20.047841438604692\n ],\n [\n -156.2635053313267,\n 20.047841438604692\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"12","noUsgsAuthors":false,"publicationDate":"2025-10-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Grossman, Eric E. 0000-0003-0269-6307 egrossman@usgs.gov","orcid":"https://orcid.org/0000-0003-0269-6307","contributorId":196610,"corporation":false,"usgs":true,"family":"Grossman","given":"Eric","email":"egrossman@usgs.gov","middleInitial":"E.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":950443,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Oberle, Ferdinand K.J. 0000-0001-8871-3619","orcid":"https://orcid.org/0000-0001-8871-3619","contributorId":214402,"corporation":false,"usgs":true,"family":"Oberle","given":"Ferdinand","middleInitial":"K.J.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":950444,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Storlazzi, Curt D. 0000-0001-8057-4490","orcid":"https://orcid.org/0000-0001-8057-4490","contributorId":213610,"corporation":false,"usgs":true,"family":"Storlazzi","given":"Curt","middleInitial":"D.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":950445,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70273139,"text":"70273139 - 2025 - Assessing flood water infiltration and storage in a restored floodplain","interactions":[],"lastModifiedDate":"2025-12-16T15:30:48.761523","indexId":"70273139","displayToPublicDate":"2025-10-05T09:20:35","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":23098,"text":"Hydological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Assessing flood water infiltration and storage in a restored floodplain","docAbstract":"In urban areas, floodplain restoration is gaining prominence as a strategy for restoring the natural functions of floodplain ecosystems and reducing flood risk. This has spurred research into potential interactions between floodwaters, the hyporheic zone, and the floodplain aquifer. An urban restored stream in Wisconsin, USA, was used as a case study to examine four methods to estimate floodplain infiltration and storage during overbank floods. We characterised flood-related infiltration over a 4-year period from 2018 through 2021 by simultaneously and continuously measuring groundwater levels and vertical temperature profiles with stream water levels linked to high-resolution flood inundation maps. High-resolution topographic data helped to quantify surface floodplain storage and the unsaturated soil volume relative to flood stage. Infiltration estimates from the simple methods align well with those from the more complex methods; however, the complex methods provide additional insights about the factors influencing infiltration. Results from all methods indicate that the volume of water that vertically infiltrates during floods is likely small relative to the total volume of the flood, with 0.08%–0.52% of flood water infiltrating into the floodplain, on average. Spatially variable vertical hydraulic gradients, driven by flood depth, groundwater level, and permeability, imply heterogeneous patterns of infiltration across the floodplain. Gradients favourable for infiltration typically occurred during the onset of flooding but, over the study period, were mostly (98% of the time) favourable for groundwater discharge to the channel (non-flood periods). These findings highlight the importance of considering surface-groundwater dynamics, floodplain soils, and unsaturated floodplain volume in defining the benefits of floodplain infiltration for flood attenuation.
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To better understand potential streamflow trends over time, the U.S. Geological Survey completed a study comparing low flows at continuous- and partial-record streamgages in New Jersey between a historical period (1950–79) and a current period (1990–2019). Fourteen statistics (one median for each of the twelve monthly minimum 1-day flows, minimum 7-day average streamflow with a 10-year recurrence interval, and median of the daily mean flows for the month of September) were calculated to evaluate how streamflow conditions may differ between the two time periods. Percent change was also calculated to better understand the magnitude of difference between the periods at individual streamgages. A Paired Wilcoxon Signed-Rank Test was implemented to test for a change in distribution between the two time periods for each statistic of interest. 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U.S. Geological Survey
3450 Princeton Pike, Suite 110
Lawrenceville, NJ 08648
No abstract available.
","language":"English","publisher":"North American Lake Management Society","usgsCitation":"Lane, R.F., Greer, J.B., Gordon, S.E., Williams, B., and Smalling, K., 2025, Treading water: How 6PPD-quinone makes it to our local water bodies & what it means for sensitive fish species: Lakeline Magazine, v. 45, no. 3, p. 6-10.","productDescription":"5 p.","startPage":"6","endPage":"10","ipdsId":"IP-183051","costCenters":[{"id":84311,"text":"Central Plains Water Science Center","active":true,"usgs":true}],"links":[{"id":497000,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":496805,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.nalms.org/lakeline-magazine/"}],"volume":"45","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lane, Rachael F. 0000-0001-9202-0612","orcid":"https://orcid.org/0000-0001-9202-0612","contributorId":222471,"corporation":false,"usgs":true,"family":"Lane","given":"Rachael","email":"","middleInitial":"F.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":950838,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Greer, Justin Blaine 0000-0001-6660-9976","orcid":"https://orcid.org/0000-0001-6660-9976","contributorId":265183,"corporation":false,"usgs":true,"family":"Greer","given":"Justin","email":"","middleInitial":"Blaine","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":950839,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gordon, Stephanie E. 0000-0002-6292-2612 sgordon@usgs.gov","orcid":"https://orcid.org/0000-0002-6292-2612","contributorId":200931,"corporation":false,"usgs":true,"family":"Gordon","given":"Stephanie","email":"sgordon@usgs.gov","middleInitial":"E.","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":950840,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Williams, Brianna 0000-0003-3389-8251","orcid":"https://orcid.org/0000-0003-3389-8251","contributorId":204714,"corporation":false,"usgs":true,"family":"Williams","given":"Brianna","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":950841,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Smalling, Kelly 0000-0002-1214-4920","orcid":"https://orcid.org/0000-0002-1214-4920","contributorId":221234,"corporation":false,"usgs":true,"family":"Smalling","given":"Kelly","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":950842,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70272610,"text":"70272610 - 2025 - Spatiotemporal overlap of mallards with poultry farms is associated with greater risk of avian influenza wild bird spillover events","interactions":[],"lastModifiedDate":"2025-11-24T16:13:28.896732","indexId":"70272610","displayToPublicDate":"2025-10-01T10:07:34","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Spatiotemporal overlap of mallards with poultry farms is associated with greater risk of avian influenza wild bird spillover events","docAbstract":"Animal movement influences local transmission and geographic spread of pathogens. Waterfowl are known reservoirs of pathogens, including H5 goose/Guangdong lineage (H5 GsGd) highly pathogenic avian influenza (HPAI). This HPAI virus lineage causes high rates of morbidity and mortality in domestic poultry and many wild bird species. Mallards (Anas platyrhynchos) are a generalist waterfowl species whose habitat largely overlaps with many other waterfowl and are considered effective spillover vectors of HPAI. To investigate the potential contribution of waterfowl to HPAI spillover, we used mallards as a proxy and measured the spatiotemporal overlap of 183 GPS-tagged mallards during 2021–2022 with respect to confirmed wild bird spillover events in United States (U.S.) poultry farms. Additionally, we estimated the probability of HPAI spillover events as a function of mallard overlap and poultry farm type. We found infrequent overlap instances between mallards and poultry farms; however, several of these overlap instances lasted > 5 days and up to 19 days. Population-level overlap with poultry farms was greatest during pre-breeding migration, followed by the breeding season. The probability of HPAI spillover was predicted to be greatest for commercial turkey farms, followed by backyard poultry farms. Importantly, farms overlapped by mallards were more than twice as likely to experience a spillover (i.e., increased risk probability), even in the absence of known mallard infection status at the time of overlap. These findings suggest that mallards (and/or other waterfowl) may be important contributors to HPAI spillover into poultry farms and that additional biosecurity measures may be needed. Because few instances of overlap occurred between mallards and farms with reported spillover events, tagged mallards are likely a proxy for other untagged waterfowl. Further studies of wild waterfowl interactions with poultry farms could improve understanding of how landscape characteristics influence spatial overlap, potentially informing which premises may require enhanced biosecurity measures.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.72221","usgsCitation":"Cullen, J.A., Masto, N.M., Sullivan, J.D., Highway, C., Patyk, K.A., McCool, M., Torchetti, M.K., Lantz, K., Poulson, R., Carter, D., Feddersen, J., Cohen, B.S., and Prosser, D.J., 2025, Spatiotemporal overlap of mallards with poultry farms is associated with greater risk of avian influenza wild bird spillover events: Ecology and Evolution, v. 15, no. 10, e72221, 14 p., https://doi.org/10.1002/ece3.72221.","productDescription":"e72221, 14 p.","ipdsId":"IP-171232","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":496932,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.72221","text":"Publisher Index Page"},{"id":496831,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Tennessee","otherGeospatial":"northwest Tennessee","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -88.28286191440344,\n 36.49028636519512\n ],\n [\n -90.12564166360227,\n 36.49028636519512\n ],\n [\n -90.12564166360227,\n 35.224526094303684\n ],\n [\n -88.28286191440344,\n 35.224526094303684\n ],\n [\n -88.28286191440344,\n 36.49028636519512\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"15","issue":"10","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Cullen, Joshua Alexander 0000-0002-8226-9198","orcid":"https://orcid.org/0000-0002-8226-9198","contributorId":363009,"corporation":false,"usgs":true,"family":"Cullen","given":"Joshua","middleInitial":"Alexander","affiliations":[{"id":50464,"text":"Eastern Ecological Science 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Cory","contributorId":316652,"corporation":false,"usgs":false,"family":"Highway","given":"Cory","affiliations":[{"id":68664,"text":"Tennessee Technical University","active":true,"usgs":false}],"preferred":false,"id":950913,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Patyk, Kelly A.","contributorId":139696,"corporation":false,"usgs":false,"family":"Patyk","given":"Kelly","email":"","middleInitial":"A.","affiliations":[{"id":6622,"text":"US Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":950914,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McCool, Mary-Jane","contributorId":347273,"corporation":false,"usgs":false,"family":"McCool","given":"Mary-Jane","email":"","affiliations":[{"id":36658,"text":"U.S. Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":950915,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Torchetti, Mia 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USA.","active":true,"usgs":false}],"preferred":false,"id":950918,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Carter, Deborah","contributorId":213914,"corporation":false,"usgs":false,"family":"Carter","given":"Deborah","affiliations":[{"id":38928,"text":"University of Georgia Southeastern Cooperative Wildlife Disease Study","active":true,"usgs":false}],"preferred":false,"id":950919,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Feddersen, Jamie","contributorId":329381,"corporation":false,"usgs":false,"family":"Feddersen","given":"Jamie","email":"","affiliations":[{"id":13408,"text":"Tennessee Wildlife Resources Agency","active":true,"usgs":false}],"preferred":false,"id":950920,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Cohen, Bradley S.","contributorId":171513,"corporation":false,"usgs":false,"family":"Cohen","given":"Bradley","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":950921,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Prosser, Diann J. 0000-0002-5251-1799","orcid":"https://orcid.org/0000-0002-5251-1799","contributorId":221167,"corporation":false,"usgs":true,"family":"Prosser","given":"Diann","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":950922,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70272235,"text":"70272235 - 2025 - A systematic literature review of forecasting and predictive models of harmful algal blooms in flowing waters","interactions":[],"lastModifiedDate":"2025-11-19T15:10:27.951072","indexId":"70272235","displayToPublicDate":"2025-10-01T09:02:45","publicationYear":"2025","noYear":false,"publicationType":{"id":27,"text":"Preprint"},"publicationSubtype":{"id":32,"text":"Preprint"},"seriesTitle":{"id":19846,"text":"BioRxiv","active":true,"publicationSubtype":{"id":32}},"title":"A systematic literature review of forecasting and predictive models of harmful algal blooms in flowing waters","docAbstract":"Occurrences of harmful algal blooms (HABs) in rivers challenge the belief that rivers are not susceptible to HABs because of their short residence times and fluctuating hydrology. Here we present a systematic literature review of predictive and forecasting models for HABs in flowing waters, including rivers, flowing in-stream reservoirs (e.g., run-of-river reservoirs and lock-and-dam systems) and tidal or estuarine systems with riverine processes. The review aimed to understand current and historical modeling approaches for predicting and forecasting river HABs, without restricting to specific taxa, such as cyanobacteria, or modeling endpoints. The review included 162 articles published over nearly 50 years, covering more than 80 rivers worldwide. Eutrophic, non-wadable rivers with in-stream obstruction were commonly modeled, though diverse environmental characteristics were reported. Most articles used algal biomass or chlorophyll as modeling endpoints, with a quarter using novel or unique endpoints. Algal toxins motivated model development in 23% of the articles, however just 5% used algal toxins as an endpoint. Only 6% of the articles modeled benthic HABs; the rest focused on pelagic HABs. There was no standard model used for modeling river HABs. Process-based models were more common (59%) than data-driven approaches (37%), with model formulations ranging from simple to complex, which contrasts with a lake-focused literature review of HAB models that found data-driven models were more common. Models in river settings shared similar input variables as those previously identified for lakes, such as water temperature, nutrients, and light availability. However, streamflow and other transport metrics took prominence in river models compared to lake models. Algal cell physiology (such as growth, predation, and motility) was routinely included as input data or as mathematical formulations in process-based models and these processes were frequently identified as an important predictor by the articles’ authors. Conversely, data-driven models rarely included these processes, instead using predictors related to environmental conditions, such as nutrients, water quality, water temperature, and streamflow. These important proxy predictors have apparent success with modeling overall algal biomass (irrespective of taxa) whereas other factors, such as those related to algal physiology and other biological processes, are likely responsible for more subtle shifts in community composition. These differences highlight the influence of data availability, especially for processes that are difficult, time-consuming, or expensive to measure, on model development and model outcomes, raising questions about the selection of modeling inputs and endpoints. Challenges to advancing river HAB modeling include the lack of site-specific model inputs representing key processes (e.g., photosynthetic parameters and predation rates), overlooked riverine environments like the benthos and side/back-channel areas, lack of information on environmental settings, and poorly reported model performance metrics. This review emphasizes opportunities for advancing river HAB modeling by learning from well-honed estuarine models, supporting current forecasting and operationalization efforts, and developing common datasets for river HAB model development and evaluation.
","language":"English","publisher":"BioRxiv","doi":"10.1101/2025.09.29.679270","usgsCitation":"Murphy, J.C., Gorney, R.M., Lucas, L., Zwart, J.A., and Graham, J.L., 2025, A systematic literature review of forecasting and predictive models of harmful algal blooms in flowing waters: BioRxiv, https://doi.org/10.1101/2025.09.29.679270.","productDescription":"52 p.","ipdsId":"IP-179513","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":496741,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1101/2025.09.29.679270","text":"External Repository"},{"id":496628,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Murphy, Jennifer C. 0000-0002-0881-0919 jmurphy@usgs.gov","orcid":"https://orcid.org/0000-0002-0881-0919","contributorId":4281,"corporation":false,"usgs":true,"family":"Murphy","given":"Jennifer","email":"jmurphy@usgs.gov","middleInitial":"C.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":950534,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gorney, Rebecca Michelle 0000-0003-4406-261X","orcid":"https://orcid.org/0000-0003-4406-261X","contributorId":317259,"corporation":false,"usgs":true,"family":"Gorney","given":"Rebecca","email":"","middleInitial":"Michelle","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":950535,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lucas, Lisa 0000-0001-7797-5517 llucas@usgs.gov","orcid":"https://orcid.org/0000-0001-7797-5517","contributorId":260498,"corporation":false,"usgs":true,"family":"Lucas","given":"Lisa","email":"llucas@usgs.gov","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":950536,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zwart, Jacob Aaron 0000-0002-3870-405X","orcid":"https://orcid.org/0000-0002-3870-405X","contributorId":237809,"corporation":false,"usgs":true,"family":"Zwart","given":"Jacob","email":"","middleInitial":"Aaron","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":950537,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Graham, Jennifer L. 0000-0002-6420-9335 jlgraham@usgs.gov","orcid":"https://orcid.org/0000-0002-6420-9335","contributorId":202923,"corporation":false,"usgs":true,"family":"Graham","given":"Jennifer","email":"jlgraham@usgs.gov","middleInitial":"L.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":950538,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70273492,"text":"70273492 - 2025 - Testicular neoplasms and other abnormalities in common carp Cyprinus carpio from the Lower Colorado River, United States","interactions":[],"lastModifiedDate":"2026-01-21T14:41:25.091826","indexId":"70273492","displayToPublicDate":"2025-10-01T09:01:02","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5762,"text":"Animals","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Testicular neoplasms and other abnormalities in common carp Cyprinus carpio from the Lower Colorado River, United States","title":"Testicular neoplasms and other abnormalities in common carp Cyprinus carpio from the Lower Colorado River, United States","docAbstract":"Abnormalities were observed in the testes of common carp Cyprinus carpio collected from Willow Beach, Arizona, USA, a site on the lower Colorado River, downstream of Lake Mead and Hoover Dam. Testicular tissue collected from this site in 2003 exhibited numerous large, pigmented macrophage aggregates (MAs) and a novel, previously undescribed hypertrophy and proliferation of putative Sertoli cells. In testes samples collected in 2007, numerous testicular MA, testicular oocytes, and proliferations of Sertoli cells were observed. Three carp collected in 2007 also had raised nodules within the testes, and, microscopically, seminoma, spermatogenic seminoma, and mixed stromal cell–germ cell neoplasms were diagnosed. Several risk factors for these adverse effects were identified. Carp collected at this site in 2003 ranged in age from 35 to 54 years and had the oldest mean age of the thirteen sites sampled within the Colorado River basin. This site also has an unusual thermal regime when compared to other sites studied in Lake Mead and upstream sites, in that temperatures varied little over the seasons (amplitude around 1.5 °C) and barely reached 15 °C. Additionally, carp from this site had the highest total polychlorinated biphenyl (PCB) body burden. Hence, advanced age, low water temperature, and exposure to PCBs and other environmental contaminants may contribute to the observed abnormalities, highlighting the complex environmental factors initiating pre-neoplastic and neoplastic changes in wild carp.
","language":"English","publisher":"MDPI","doi":"10.3390/ani15192887","usgsCitation":"Blazer, V., Goodbred, S.L., Walsh, H.L., Wichman, D., Johnson, D., and Patino, R., 2025, Testicular neoplasms and other abnormalities in common carp Cyprinus carpio from the Lower Colorado River, United States: Animals, v. 15, no. 19, 2887, 15 p., https://doi.org/10.3390/ani15192887.","productDescription":"2887, 15 p.","ipdsId":"IP-180041","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":498926,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/ani15192887","text":"Publisher Index Page"},{"id":498778,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Willow Beach","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -114.69161558714228,\n 35.89140842150485\n ],\n [\n -114.69161558714228,\n 35.8623130396342\n ],\n [\n -114.64784912081029,\n 35.8623130396342\n ],\n [\n -114.64784912081029,\n 35.89140842150485\n ],\n [\n -114.69161558714228,\n 35.89140842150485\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"15","issue":"19","noUsgsAuthors":false,"publicationDate":"2025-10-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Blazer, Vicki S. 0000-0001-6647-9614","orcid":"https://orcid.org/0000-0001-6647-9614","contributorId":349694,"corporation":false,"usgs":true,"family":"Blazer","given":"Vicki S.","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":953927,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Goodbred, Steven L.","contributorId":365206,"corporation":false,"usgs":false,"family":"Goodbred","given":"Steven","middleInitial":"L.","affiliations":[{"id":87075,"text":"USGS CWSC (retired)","active":true,"usgs":false}],"preferred":false,"id":953928,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Walsh, Heather L. 0000-0001-6392-4604 hwalsh@usgs.gov","orcid":"https://orcid.org/0000-0001-6392-4604","contributorId":4696,"corporation":false,"usgs":true,"family":"Walsh","given":"Heather","email":"hwalsh@usgs.gov","middleInitial":"L.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":953929,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wichman, Dylan","contributorId":365207,"corporation":false,"usgs":false,"family":"Wichman","given":"Dylan","affiliations":[{"id":87076,"text":"USGS EESC","active":true,"usgs":false}],"preferred":false,"id":953930,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Johnson, Darren 0000-0002-0502-6045","orcid":"https://orcid.org/0000-0002-0502-6045","contributorId":203921,"corporation":false,"usgs":true,"family":"Johnson","given":"Darren","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":953931,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Patino, Renaldo 0000-0002-4831-8400","orcid":"https://orcid.org/0000-0002-4831-8400","contributorId":353646,"corporation":false,"usgs":false,"family":"Patino","given":"Renaldo","affiliations":[{"id":12701,"text":"US Geological Survey","active":true,"usgs":false}],"preferred":false,"id":953932,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70272045,"text":"70272045 - 2025 - Water temperature analysis of the North Branch Au Sable River, Michigan, and implications to salmonid populations","interactions":[],"lastModifiedDate":"2025-11-14T15:00:58.935639","indexId":"70272045","displayToPublicDate":"2025-10-01T08:46:21","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"seriesTitle":{"id":19873,"text":"Fisheries Report","active":true,"publicationSubtype":{"id":2}},"seriesNumber":"47","title":"Water temperature analysis of the North Branch Au Sable River, Michigan, and implications to salmonid populations","docAbstract":"Ambient stream water temperatures affect salmonid movement and survival with fish actively seeking thermal refugia from warming waters. This study sought to investigate the potential role of water temperature in the perceived decline in native Brook Trout Salvelinus fontinalis and non-native Brown Trout Salmo trutta populations in the North Branch Au Sable River by fishers and reported to resource managers in 2018 and 2019. Water temperature was analyzed at nine stations within the North Branch Au Sable River in 2021 and 2022. A total of 61,390 temperature observations were collected with 58.0% exceeding the optimal growth threshold for Brook Trout of 16°C; 37.9% exceeding the movement threshold for Brook Trout of 18°C; 3.4% exceeding the upper limit for positive growth for Brook Trout of 23.4°C; and 28.6% exceeding the optimal growth threshold for Brown Trout of 19°C. The maximum daily water temperatures recorded for each year were 27.58°C in 2021 and 26.89°C in 2022. The availability of cold water thermal refugia is critical to the viability of native Brook Trout populations in the North Branch Au Sable River and its tributaries. Efforts should be taken to increase ambient stream water temperature monitoring year-round and to determine the size, frequency, and availability of thermal refugia within the watershed to increase the likelihood of a system resilient to the impacts of a warming climate.
","language":"English","publisher":"State of Michigan, Department of Natural Resources","usgsCitation":"Watson, N.M., Hayes, D.B., and Godby, N., 2025, Water temperature analysis of the North Branch Au Sable River, Michigan, and implications to salmonid populations: Fisheries Report 47, 27 p.","productDescription":"27 p.","ipdsId":"IP-170450","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":496475,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":496441,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://iffr.mlasolutions.com/"}],"country":"United States","state":"Michigan","otherGeospatial":"North Branch Au Sable River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -84.81284035831224,\n 45.1\n ],\n [\n -84.81284035831224,\n 44.25\n ],\n [\n -83.28405994697454,\n 44.25\n ],\n [\n -83.28405994697454,\n 45.1\n ],\n [\n -84.81284035831224,\n 45.1\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Watson, Nicole M. 0000-0002-9424-7615 nwatson@usgs.gov","orcid":"https://orcid.org/0000-0002-9424-7615","contributorId":5853,"corporation":false,"usgs":true,"family":"Watson","given":"Nicole","email":"nwatson@usgs.gov","middleInitial":"M.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":949839,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hayes, Daniel B. 0000-0002-8132-4749","orcid":"https://orcid.org/0000-0002-8132-4749","contributorId":362025,"corporation":false,"usgs":false,"family":"Hayes","given":"Daniel","middleInitial":"B.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":949840,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Godby, Neal","contributorId":102295,"corporation":false,"usgs":true,"family":"Godby","given":"Neal","affiliations":[],"preferred":false,"id":949841,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70272015,"text":"sir20255080 - 2025 - Potentiometric surface maps and groundwater-level hydrographs for confined aquifers of the New Jersey Coastal Plain, 2018","interactions":[],"lastModifiedDate":"2026-02-03T16:24:50.121719","indexId":"sir20255080","displayToPublicDate":"2025-09-30T16:45:00","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":"2025-5080","displayTitle":"Potentiometric Surface Maps and Groundwater-Level Hydrographs for Confined Aquifers of the New Jersey Coastal Plain, 2018","title":"Potentiometric surface maps and groundwater-level hydrographs for confined aquifers of the New Jersey Coastal Plain, 2018","docAbstract":"The U.S. Geological Survey, in cooperation with the New Jersey Department of Environmental Protection (NJDEP), prepared potentiometric surface maps for 10 confined aquifers of the New Jersey Coastal Plain physiographic province based on water-level measurements collected during late 2018 and early 2019 from 951 wells in New Jersey and parts of Pennsylvania and Delaware. Maps were prepared for the confined Cohansey aquifer, Rio Grande water-bearing zone, Atlantic City 800-foot sand, Piney Point aquifer, Vincentown aquifer, Wenonah-Mount Laurel aquifer, Englishtown aquifer system, and the upper, middle, and lower aquifers of the Potomac-Raritan-Magothy aquifer system.
Potentiometric surface maps indicate regional cones of depression in the following aquifers and the counties in which they are centered: Atlantic City 800-foot sand in Atlantic County, the Piney Point aquifer in Cumberland County, the Wenonah-Mount Laurel aquifer and Englishtown aquifer system in Monmouth and Ocean Counties, the Wenonah-Mount Laurel aquifer in Camden and Gloucester County, the upper aquifer of the Potomac-Raritan-Magothy aquifer system in Ocean County, and the upper, middle, and lower aquifers of the Potomac-Raritan-Magothy aquifer system in Camden County. Cones of depression with smaller areal extents were in the confined Cohansey aquifer, the Rio Grande water-bearing zone, the Atlantic City 800-foot sand centered in Cape May County, the Piney Point aquifer centered in Ocean County, the Wenonah-Mount Laurel aquifer in Salem and Burlington Counties, the Englishtown aquifer system in Camden County, the upper aquifer of the Potomac-Raritan-Magothy aquifer system in Monmouth County, and the middle aquifer of the Potomac-Raritan-Magothy aquifer system in Monmouth, Ocean, and Salem Counties. No cone of depression was interpreted in the Vincentown aquifer.
Long-term hydrographs are presented for 75 wells spanning each of the 10 confined aquifers, and contain a mix of discrete water-level measurements and daily mean water levels based on continuously recorded 15-minute data. Changes of water levels during 2014–19, as indicated by the hydrographs, were compared with those of previous periods to assess any departures from historical data. During 2014–19, water levels were stable and fluctuated within similar ranges as previous periods in the following aquifers and locations: all wells in the confined Cohansey aquifer, the Rio Grande water-bearing zone, the Vincentown aquifer, the Englishtown aquifer system, the Piney Point aquifer wells in Burlington and Ocean Counties, six of eight wells in the Wenonah-Mount Laurel aquifer, all wells in the upper and lower aquifers of the Potomac-Raritan-Magothy aquifer system outside NJDEP Critical Areas, and all wells in the middle aquifer of the Potomac-Raritan-Magothy aquifer system except those within NJDEP Critical Area II. Increasing water levels in 2014–19, ongoing since historical periods, were indicated in the following aquifers and locations: Atlantic County wells in the Piney Point aquifer, all wells in the upper and lower aquifers of the Potomac-Raritan-Magothy aquifer system outside NJDEP Critical Areas, and all wells in the middle aquifer of the Potomac-Raritan-Magothy aquifer system within NJDEP Critical Area II. Water levels in the Atlantic City 800-foot sand also increased during 2014–19 in wells in Atlantic County and northern Cape May County closer to the center of the cone of depression in that aquifer, which is a response unique to this period and absent from previous periods. During 2013–19, continued decreasing water levels, ongoing since previous periods, were indicated by hydrographs of Atlantic City 800-foot sand wells in southern Cape May County, Piney Point aquifer wells in Cumberland County where the regional cone of depression is located, and two wells in the Wenonah-Mount Laurel aquifer—070478, which in 2014–19 departed from previous periods, and 330020, which continued a gradual decrease throughout its period of record.
","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255080","collaboration":"Prepared in cooperation with the New Jersey Department of Environmental Protection","usgsCitation":"Fiore, A.R., Cauller, S.J., and Brown, E.J., 2025, Potentiometric surface maps and groundwater-level hydrographs for confined aquifers of the New Jersey Coastal Plain, 2018: U.S. Geological Survey Scientific Investigations Report 2025–5080, 37 p., 9 pls., https://doi.org/10.3133/sir20255080.","productDescription":"Report: viii, 37 p.; 9 Plates: 19.50 x 26.50 inches; Data Release","numberOfPages":"37","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-158226","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":496280,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9AT8Z9B","text":"USGS data release","linkHelpText":"Geospatial data representing wells open to, and 2018 potentiometric surface contours of, the confined aquifers of the New Jersey Coastal Plain"},{"id":496298,"rank":7,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2025/5080/sir20255080_plates.pdf","text":"Plates 1–9","size":"69.4 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":496277,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255080/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2025-5080 HTML"},{"id":496276,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5080/sir20255080.pdf","text":"Report","size":"5.31 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5080 PDF"},{"id":496279,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5080/images/"},{"id":496275,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5080/coverthb.jpg"},{"id":496278,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5080/sir20255080.XML","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2025-5080 XML"},{"id":497788,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118951.htm"}],"country":"United States","state":"New Jersey","otherGeospatial":"Coastal Plain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -73.86248123191035,\n 40.48417444667285\n ],\n [\n -74.37454480427728,\n 40.52176772292319\n ],\n [\n -74.76300682469329,\n 40.185368171011504\n ],\n [\n -75.09849675141594,\n 39.98542938463885\n ],\n [\n -75.2574130324954,\n 39.85000334106027\n ],\n [\n -75.46223846144186,\n 39.77133356243843\n ],\n [\n -75.58230854047962,\n 39.61100346658509\n ],\n [\n -75.5363993926121,\n 39.43666527993781\n ],\n [\n -74.85835659334042,\n 38.83679593629347\n ],\n [\n -74.02846045881562,\n 39.676267414234104\n ],\n [\n -73.86248123191035,\n 40.48417444667285\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, New Jersey Water Science Center
U.S. Geological Survey
3450 Princeton Pike, Suite 110
Lawrenceville, New Jersey 08648
The National Hydrography Dataset Plus High Resolution (NHDPlus HR) is a scalable hydrologic geospatial fabric or framework, built from (1) the High Resolution (1:24,000-scale or better) National Hydrography Dataset (NHD), (2) nationally complete Watershed Boundary Dataset (WBD), and (3) 1/3-arc-second 3D Elevation Program (3DEP) digital elevation model (DEM) data (at a 10-meter ground spacing; or 5-meter 3DEP DEM in Alaska only). The NHDPlus HR provides a modeling and assessment framework at a local 1:24,000 scale, while nesting seamlessly into the national context.
NHDPlus HR is modeled after the highly successful NHDPlus version 2 (NHDPlusV2). Like NHDPlusV2, the NHDPlus HR includes data for a nationally seamless network of stream reaches, elevation-based catchment areas, flow surfaces, and value-added attributes that enhance stream-network navigation, analysis, and data display. However, NHDPlus HR provides much greater spatial detail than NHDPlusV2, while NHDPlusV2 is, at present, more complete in its attribution of additions, removals, and diversions, as well as stream connectivity. This user’s guide is intended to provide necessary information and guidance in the use of NHDPlus HR data.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255031","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency","programNote":"National Geospatial Program","usgsCitation":"Moore, R.B., McKay, L.D., Rea, A.H., Bondelid, T.R., Price, C.V., Dewald, T.G., and Hayes, L., 2025, User’s guide for the National Hydrography Dataset Plus High Resolution (NHDPlus HR): U.S. Geological Survey Scientific Investigations Report 2025–5031, 78 p., https://doi.org/10.3133/sir20255031. [Supersedes USGS Open-File Report 2019–1096.]","productDescription":"Report: xiii, 78 p.; 2 Data Releases; Project Site","numberOfPages":"78","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-150034","costCenters":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":496237,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5031/sir20255031.XML","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2025-5031 XML"},{"id":496238,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5031/images"},{"id":496239,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9WFOBQI","text":"USGS data release","linkHelpText":"USGS National Hydrography Dataset Plus High Resolution National Release 1 FileGDB"},{"id":496240,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://apps.nationalmap.gov/downloader/#/","text":"USGS data release","linkHelpText":"The National Map downloader (ver. 2.0)"},{"id":496273,"rank":8,"type":{"id":18,"text":"Project Site"},"url":"https://www.usgs.gov/national-hydrography/nhdplus-high-resolution","text":"NHDPlus High Resolution"},{"id":496236,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255031/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2025-5031 HTML"},{"id":496235,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5031/sir20255031.pdf","text":"Report","size":"9.55 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5031 PDF"},{"id":496234,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5031/coverthb.jpg"}],"contact":"Director, National Geospatial Program
Core Science Systems
U.S. Geological Survey
12201 Sunrise Valley Drive, MS 511
Reston, VA 20192
Sulfate is often touted as containing atmospheric oxygen whose isotopic signature can constrain redox, environmental conditions, and biological activity. Yet, the amount and isotopic fractionation associated with air-O2 incorporation during sulfate formation is still debated, making its verification difficult. In this study, we identify a distinct, microbially dominated environment with the potential to preserve maximum signals of air-O2 in sulfate. We report triple-oxygen isotope data for sulfate produced from pyrite oxidation in microbial and abiotic experiments, and from natural dissolved sulfate from the Rio Tinto, Spain, an acid mine drainage site. The oxygen isotope systematics of sulfate in these environments define a unique kinetic isotope effect associated with initial stage pyrite oxidation by Acidithiobacillus ferrooxidans that preserves >80 % oxygen from air-O2 in sulfate. Unlike experiments, which evolve toward water-oxygen dominated sulfate on short time scales, Rio Tinto, Spain hosts a microbe rich environment with distinct geochemistry that maintains high O2-oxygen in sulfate. Therefore, in addition to containing isotopic records from water and air, sulfates can also contain a biosignature that is promising for understanding conditions on Mars and early Earth.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.epsl.2025.119639","usgsCitation":"Kohl, I., Killingsworth, B.A., Zeigler, K., Young, E.D., and Coleman, M., 2025, Triple-oxygen isotopic evidence of prolonged direct bioleaching of pyrite with O2: Earth and Planetary Science Letters, v. 671, 119639, 10 p., https://doi.org/10.1016/j.epsl.2025.119639.","productDescription":"119639, 10 p.","ipdsId":"IP-172630","costCenters":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":496423,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.epsl.2025.119639","text":"Publisher Index Page"},{"id":496406,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Spain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -9.191561095536457,\n 43.45843865321959\n ],\n [\n -9.220384524245844,\n 41.937249586462514\n ],\n [\n -6.67459696121594,\n 41.76753344172553\n ],\n [\n -7.593667945421032,\n 37.4320694758983\n ],\n [\n -3.984102384259529,\n 35.59998830658435\n ],\n [\n 0.4092648847614413,\n 38.01073133574759\n ],\n [\n 3.171479154976481,\n 42.5594331414778\n ],\n [\n -7.946415250293342,\n 43.84479559131496\n ],\n [\n -9.191561095536457,\n 43.45843865321959\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"671","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kohl, Issaku","contributorId":361971,"corporation":false,"usgs":false,"family":"Kohl","given":"Issaku","affiliations":[{"id":13252,"text":"University of Utah","active":true,"usgs":false}],"preferred":false,"id":949747,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Killingsworth, Bryan Alan 0000-0001-6067-8604","orcid":"https://orcid.org/0000-0001-6067-8604","contributorId":270978,"corporation":false,"usgs":true,"family":"Killingsworth","given":"Bryan","email":"","middleInitial":"Alan","affiliations":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"preferred":true,"id":949748,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zeigler, Karen","contributorId":361972,"corporation":false,"usgs":false,"family":"Zeigler","given":"Karen","affiliations":[{"id":36307,"text":"University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":949749,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Young, Edward D.","contributorId":362021,"corporation":false,"usgs":false,"family":"Young","given":"Edward","middleInitial":"D.","affiliations":[{"id":12763,"text":"University of California, Los Angeles","active":true,"usgs":false}],"preferred":false,"id":949828,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Coleman, Max","contributorId":361973,"corporation":false,"usgs":false,"family":"Coleman","given":"Max","affiliations":[{"id":33580,"text":"NASA-JPL","active":true,"usgs":false}],"preferred":false,"id":949751,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70272027,"text":"70272027 - 2025 - Estimated ultimate recovery (EUR) Prediction for Eagle Ford Shale using integrated datasets and artificial neural networks","interactions":[],"lastModifiedDate":"2025-11-13T15:56:49.946165","indexId":"70272027","displayToPublicDate":"2025-09-30T08:51:52","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":10757,"text":"Energies","active":true,"publicationSubtype":{"id":10}},"title":"Estimated ultimate recovery (EUR) Prediction for Eagle Ford Shale using integrated datasets and artificial neural networks","docAbstract":"The estimated ultimate recovery (EUR) is an important parameter for forecasting oil and gas production and informing decisions regarding field development strategies. In this study, we combined site-specific geologic, completion, and operational parameters with the predictive capabilities of machine learning (ML) models to predict EURs of the wells for the Eagle Ford Marl Continuous Oil Assessment Unit. We developed an extensive dataset of wells that have produced from the lower and upper Eagle Ford Shale intervals and reduced the model complexity using principal component analysis. We tested the ML models and estimated the sensitivities of ML-predicted EURs to changes in the values of different input variables. The results of applying the optimized ML model to the Eagle Ford suggest that the approach developed in this study could be promising. The ML estimates of the EURs fit the DCA-based values with an R2 ~ 0.9 and a mean absolute error of ~36 × 103 bbl. In the lower Eagle Ford Shale, the EUR estimates were found to be most sensitive to changes in porosity, net thickness of the interval, clay volume, and the API gravity of the oil; and that in the upper Eagle Ford Shale they were most sensitive to changes in the total organic carbon and water saturation, which suggests that it could be important to consider these parameters in assessing these intervals or close analogs.
","language":"English","publisher":"MDPI","doi":"10.3390/en18195216","usgsCitation":"Karacan, C.O., Anderson, S.T., and Cahan, S., 2025, Estimated ultimate recovery (EUR) Prediction for Eagle Ford Shale using integrated datasets and artificial neural networks: Energies, v. 18, no. 19, 5216, 21 p., https://doi.org/10.3390/en18195216.","productDescription":"5216, 21 p.","ipdsId":"IP-164247","costCenters":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":496420,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/en18195216","text":"Publisher Index Page"},{"id":496401,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico, United States","state":"Louisiana, Mississippi, Texas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -99.39816695432742,\n 30.86268720310727\n ],\n [\n -99.39816695432742,\n 27.387197803061596\n ],\n [\n -89.04028077792094,\n 27.387197803061596\n ],\n [\n -89.04028077792094,\n 30.86268720310727\n ],\n [\n -99.39816695432742,\n 30.86268720310727\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"18","issue":"19","noUsgsAuthors":false,"publicationDate":"2025-09-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Karacan, C. Ozgen 0000-0002-0947-8241","orcid":"https://orcid.org/0000-0002-0947-8241","contributorId":201991,"corporation":false,"usgs":true,"family":"Karacan","given":"C.","email":"","middleInitial":"Ozgen","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":949769,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, Steven T. 0000-0003-3481-3424 sanderson@usgs.gov","orcid":"https://orcid.org/0000-0003-3481-3424","contributorId":2532,"corporation":false,"usgs":true,"family":"Anderson","given":"Steven","email":"sanderson@usgs.gov","middleInitial":"T.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":949770,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cahan, Steven M. 0000-0002-4776-3668","orcid":"https://orcid.org/0000-0002-4776-3668","contributorId":205929,"corporation":false,"usgs":true,"family":"Cahan","given":"Steven M.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":949771,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70272111,"text":"70272111 - 2025 - Unique thermal mixing patterns in Lake Ontario revealed by novel year-round observations of thermal stratification","interactions":[],"lastModifiedDate":"2025-12-01T16:52:39.768257","indexId":"70272111","displayToPublicDate":"2025-09-30T08:32:43","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2620,"text":"Limnology and Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"Unique thermal mixing patterns in Lake Ontario revealed by novel year-round observations of thermal stratification","docAbstract":"Year-round records of thermal stratification in the Great Lakes are rare, and there are few observations of thermal stratification during winter. In this paper, we analyze temperature data from 13 temperature logger chains and from over 130 benthic acoustic receivers that were deployed across Lake Ontario for 2 yr. The timing and duration of the fall overturn correlate with the local average water depth, and shallow sites (< 50 m depth) overturn up to a month before deep sites (> 100 m depths). Likewise, in spring, the shallow sites warm faster. Lake Ontario has partial ice cover, so wind-driven mixing stirs the water column throughout winter, and inverse thermal stratification is largely absent. The depth-averaged winter water temperatures vary between 0°C and 4°C, with the coldest temperatures (near 0.1°C) found in the shallow Kingston basin and warmest temperatures (near 4°C) at sites near the 244 m deep Rochester Basin. Lake Ontario appears to be a warm monomictic lake, rather than having a dimictic mixing pattern as previously described—there is no sustained ice cover or inverse stratification that inhibits vertical mixing in winter. Winter is a poorly understood season for many aquatic processes, including fish bioenergetics, fish distribution, biochemical processes, invertebrate distribution, and production. Moreover, the lack of knowledge of winter has hampered the use of correct initial conditions for running large lake hydrodynamic models.
","language":"English","publisher":"Wiley","doi":"10.1002/lno.70215","usgsCitation":"Wells, M., Johnson, T.B., Robinson, R., Midwood, J., Shi, Y., Larocque, S., Eddie, A., O’Malley, B., Morton, K., Gorsky, D., and Tufts, B., 2025, Unique thermal mixing patterns in Lake Ontario revealed by novel year-round observations of thermal stratification: Limnology and Oceanography, v. 70, no. 11, p. 3401-3416, https://doi.org/10.1002/lno.70215.","productDescription":"16 p.","startPage":"3401","endPage":"3416","ipdsId":"IP-172993","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":496724,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/lno.70215","text":"Publisher Index Page"},{"id":496547,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Lake Ontario","geographicExtents":"{\n \"type\": 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B.","contributorId":127336,"corporation":false,"usgs":false,"family":"Johnson","given":"Tim","email":"","middleInitial":"B.","affiliations":[{"id":6780,"text":"Ontario Ministry of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":950106,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Robinson, Rylie","contributorId":362147,"corporation":false,"usgs":false,"family":"Robinson","given":"Rylie","affiliations":[{"id":6780,"text":"Ontario Ministry of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":950107,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Midwood, Jon","contributorId":353235,"corporation":false,"usgs":false,"family":"Midwood","given":"Jon","affiliations":[{"id":52613,"text":"DFO","active":true,"usgs":false}],"preferred":false,"id":950108,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Shi, 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Service","active":true,"usgs":false}],"preferred":false,"id":950113,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Tufts, Bruce","contributorId":256637,"corporation":false,"usgs":false,"family":"Tufts","given":"Bruce","email":"","affiliations":[{"id":36943,"text":"Queens University","active":true,"usgs":false}],"preferred":false,"id":950114,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70271935,"text":"fs20253022 - 2025 - Beaver dams and their effects on urban streams in the Tualatin River Basin, northwestern Oregon","interactions":[],"lastModifiedDate":"2026-02-03T16:22:51.589121","indexId":"fs20253022","displayToPublicDate":"2025-09-30T07:55:41","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact 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inundation, suspended-sediment transport and deposition, and water quality along two urban stream reaches (Fanno Creek at Greenway Park and Bronson Creek between Kaiser and Saltzman Roads). This fact sheet summarizes the results of these studies and implications for beaver-assisted restoration in the Tualatin River Basin.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20253022","usgsCitation":"Jones, K.L., Smith, C.D., White, J.S., Rounds, S.A., Doyle, M.C., and Leahy, E.K., Beaver dams and their effects on urban streams in the Tualatin River Basin, northwestern Oregon: U.S. Geological Survey Fact Sheet 2025–3022, 6 p., https://doi.org/10.3133/fs20253022","productDescription":"6 p.","onlineOnly":"Y","ipdsId":"IP-138686","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":496063,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2025/3022/fs20253022.XML"},{"id":496061,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2025/3022/coverthb.jpg"},{"id":496062,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2025/3022/fs20253022.pdf","text":"Report","size":"1.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2025-3022"},{"id":496206,"rank":4,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://doi.org/10.3133/sir20255039","text":"SIR 2025-5039","description":"SIR 2025-5039","linkHelpText":"- Beavers in the Tualatin River Basin, Northwestern Oregon"}],"country":"United States","state":"Oregon","otherGeospatial":"Tualatin River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -123.5,\n 45.75\n ],\n [\n -123.5,\n 45.375\n ],\n [\n -122.5,\n 45.375\n ],\n [\n -122.5,\n 45.75\n ],\n [\n -123.5,\n 45.75\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Oregon Water Science Center
601 SW 2nd Ave., Suite 1950
Portland, Oregon 97204
American beavers (Castor canadensis) are native to the Pacific Northwest, and their populations have increased in many locations after being nearly removed by historical trapping. Beaver dams have well-documented effects on water quality in forested streams, but their effects on water quality in urban streams have not been well characterized. The study documented the water-quality effects of beaver dams and beaver activity in selected urban streams of the Tualatin River Basin in northwestern Oregon. Variations in water quality upstream, downstream, and within ponded areas behind beaver dams were quantified with continuous measurements of water temperature, specific conductance, dissolved oxygen, and pH from May 2016 to November 2017 in two intensively monitored reaches of urban streams (Fanno and Bronson Creeks). Five other urban stream reaches were monitored upstream and downstream from beaver ponds using water-temperature sensors to document water-temperature changes in additional beaver-affected reaches. Spatial water-quality variations within a beaver pond along Fanno Creek were characterized in more detail on four hot summer afternoons with numerous measurements of temperature and dissolved oxygen. Results from the study were used to document and derive insights from measured patterns in the water-quality data, such as the following:
Director, Oregon Water Science Center
U.S. Geological Survey
601 SW 2nd Avenue, Suite 1950
Portland, Oregon 97204
This study investigated the effects of natural beaver dams and ponds on sediment transport and deposition in two urban beaver-affected reaches in the Tualatin River Basin, northwestern Oregon. Data were collected during 2016–17 from Fanno Creek at Greenway Park (between SW Hall Boulevard and SW Pearson Court) and Bronson Creek (between NW Laidlaw Road and NW Kaiser Road); each study reach contained multiple beaver dams. Continuous turbidity, discrete suspended-sediment samples, and streamflow measurements were collected during storms and baseflow periods to calculate suspended-sediment loads (SSLs) and to compare differences in SSLs upstream and downstream from the two beaver-affected reaches. Turbidity was measured continuously upstream, within, and downstream from these reaches to evaluate seasonal and longitudinal turbidity patterns and fluctuations. The volume and mass of sediment deposited in a large pond along the Fanno Creek study reach were also estimated. Study results include:
Director, Oregon Water Science Center
U.S. Geological Survey
601 SW 2nd Avenue, Suite 1950
Portland, Oregon 97204
American beaver (Castor canadensis) dams fundamentally alter stream hydraulics and hydrology by temporarily impounding water in stream channels. Water managers are interested in how this impoundment translates to changes in hydrograph dynamics, particularly regarding the magnitude and duration of high flows, the temporary storage of storm water, and the range and spatial distribution of water depths and velocities. High-resolution two-dimensional hydraulic models were developed to compare hydraulic responses to storm events in two 1-kilometer long, relatively small (less than 5-meter-wide channel), urban stream reaches in the Tualatin River Basin (northwestern Oregon) with and without beaver dams. Results from modeling unsteady storm events show that: (1) beaver dams generally attenuate (temporarily impound) more water during storm events than an undammed reach, (2) the timing and dynamics of this attenuation are complicated and thus do not always result in a reduction of peak flows, and (3) the influence of beaver dams on stream hydraulics diminishes as the magnitude of flow events increase. Local geomorphic conditions, specifically the presence of off-channel features, affect the extent to which dams alter hydrograph dynamics. Although the magnitudes of peak flows are not substantially affected by the beaver dams considered in this study, results show that beaver dams temporarily impound a considerable amount of water throughout the duration of storms, which slows water conveyance to downstream reaches. Steady-state streamflow simulations at several streamflow magnitudes were also used to assess how beaver dams affect stream depths, velocities, and inundated areas, which are important factors affecting aquatic habitats. Results show that beaver dams result in a more hydraulically diverse stream, with substantially more inundated area, lower velocities, and greater depths than corresponding undammed scenarios. However, these differences diminish as streamflows increase and the channels overflow their banks and become hydraulically connected to adjacent floodplains. Together, these results confirm that beaver dams can fundamentally change urban stream channel hydraulics, but the influence of these dams is bounded by local geomorphic controls and is diminished at large streamflows.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255039B","collaboration":"Prepared in cooperation with Clean Water Services","usgsCitation":"White, J.S., Jones, K.L., and Rounds, S.A., 2025, Effects of beaver dams and ponds on hydrologic and hydraulic responses of storm flows in urban streams of the Tualatin River Basin, northwestern Oregon, chap. B of Jones, K.L., and Smith, C.D., eds., Beavers in the Tualatin River Basin, northwestern Oregon: U.S. Geological Survey Scientific Investigations Report 2025–5039–B, 38 p., https://doi.org/10.3133/sir20255039B.","productDescription":"Report: viii, 38 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-164816","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":495978,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5039/b/sir20255039b.pdf","text":"Report","size":"6.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5039-B"},{"id":495981,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5039/b/images","text":"USGS data release","description":"USGS data release"},{"id":495982,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5039/b/sir20255039b.XML"},{"id":495977,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5039/b/coverthb.jpg"},{"id":495980,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1VZGC3Z","text":"USGS data release","description":"USGS data release","linkHelpText":"Hydraulic models of two beaver affected reaches in the Tualatin Basin, Oregon"},{"id":495979,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255039b/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2025-5039-B"}],"country":"United States","state":"Oregon","otherGeospatial":"Tualatin River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -123.5,\n 45.75\n ],\n [\n -123.5,\n 45.375\n ],\n [\n -122.5,\n 45.375\n ],\n [\n -122.5,\n 45.75\n ],\n [\n -123.5,\n 45.75\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, Oregon 97204
Beaver dams can help streams connect to their floodplains. These floodplain connections can expand the range of available aquatic habitats and aid in the restoration of stream and floodplain function and processes. American beavers (Castor canadensis) occupy a wide variety of aquatic habitats; however, their ability to build dams, the agent of stream and floodplain change, is constrained in large part by three physical variables—local vegetation, topography, and hydrology.
These three physical variables are combined in the Beaver Restoration Assessment Tool (BRAT), a geographic information system-based utility that uses a Fuzzy Inference System (FIS) to estimate the capacity of each reach within a stream network to support beaver dams. In this study, version 1.0 of BRAT was adapted and applied to the entire perennial stream network of Tualatin River Basin in northwestern Oregon. Beaver-dam locations in the Tualatin River Basin were compiled to (1) define the distribution of dams in the basin during 2013–16 and (2) provide necessary data for calibrating and validating BRAT predictions. BRAT was calibrated to the current known distribution of dams, as compiled in the inventory. The input FIS equations of the original BRAT model were adjusted to account for local topographic conditions; specifically, the low gradient of many streams in the basin, although subsequent updates to BRAT may obviate the need for these changes.
Results from this modified BRAT model reasonably simulated the dam inventory. Results show that beavers can currently build the greatest density of dams, defined as number of dams per kilometer of stream, in the higher-gradient forested streams of the basin, whereas they can build the fewest number of dams per kilometer in urban streams along the lower-gradient valley floor. Estimated dam density was generally 5-15 dams per kilometer (km) for forested streams and 2-4 dams/km for urban streams. Improving riparian vegetation along urban streams may allow beavers to build on average four additional dams per kilometer compared to current conditions. Results from this study may help inform local stream and stormwater management by (1) identifying stream reaches with the most potential to support beaver dams, (2) determining the likely factors limiting potential for dam building, and (3) identifying potential areas where dam building may affect human infrastructure.
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U.S. Geological Survey
601 SW 2nd Avenue, Suite 1950
Portland, Oregon 97204