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":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.
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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":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","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":70273513,"text":"70273513 - 2025 - Case study of deep learning image segmentation for the purposes of rapid 2D petrographic analysis in volcanic rocks","interactions":[],"lastModifiedDate":"2026-01-22T14:31:14.015253","indexId":"70273513","displayToPublicDate":"2025-10-05T07:43:15","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7593,"text":"Volcanica","active":true,"publicationSubtype":{"id":10}},"title":"Case study of deep learning image segmentation for the purposes of rapid 2D petrographic analysis in volcanic rocks","docAbstract":"Automation using deep learning methods is a useful alternative to manual methods of petrographic segmentation, but often requires user familiarity with coding and/or algorithms. We examine the DragonflyTM program's deep learning tools for application by users with a variety of skill levels as a method for petrographic image segmentation. An image processing methodology, bimodal image stacking, was created for low-input-data, high-efficacy training of models which can then be applied to varied samples. Using backscatter electron images we show that the resulting model segmentations agree with manual segmentation total and modal crystallinity values within 5%, and calculated plagioclase crystal size distribution (CSD) values within 2σ, despite limitations in discriminating mafic phases. Model creation and training takes <24 hours, 1–3 hours of which are supervised, and the resultant model can then be applied to new uncharacterized samples in <15 minutes per image. This allows for non-experts to create and utilize deep learning models to segment images of variable brightness and texture, at low user-time cost and resulting in size and shape data which are within uncertainty of manual segmentation. While some limitations are noted (for example, sieve-textured phases may need manual correction, and different minerals with similar BSE intensity may not be resolved as separate phases), this methodology can be utilized for general application of models to wide ranges of volcanic crystalline and bubble textures, and to create a library of models for rapid petrological analysis during volcanic eruptions.
","language":"English","publisher":"OJS/PKP","doi":"10.30909/vol/gsfc1696","usgsCitation":"Halverson, B.A., Loewen, M.W., Dietterich, H., and Whittington, A., 2025, Case study of deep learning image segmentation for the purposes of rapid 2D petrographic analysis in volcanic rocks: Volcanica, v. 8, no. 2, p. 427-443, https://doi.org/10.30909/vol/gsfc1696.","productDescription":"17 p.","startPage":"427","endPage":"443","ipdsId":"IP-168707","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":498931,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.30909/vol/gsfc1696","text":"Publisher Index Page"},{"id":498793,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Bogoslof Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -169.2081935551017,\n 55.01025512098417\n ],\n [\n -169.2081935551017,\n 53.07434331835552\n ],\n [\n -165.56066240589334,\n 53.07434331835552\n ],\n [\n -165.56066240589334,\n 55.01025512098417\n ],\n [\n -169.2081935551017,\n 55.01025512098417\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"8","issue":"2","noUsgsAuthors":false,"publicationDate":"2025-10-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Halverson, Brenna A. 0009-0009-7766-7384","orcid":"https://orcid.org/0009-0009-7766-7384","contributorId":365304,"corporation":false,"usgs":false,"family":"Halverson","given":"Brenna","middleInitial":"A.","affiliations":[{"id":87127,"text":"University of Texas San Antonio","active":true,"usgs":false}],"preferred":false,"id":954099,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Loewen, Matthew W. 0000-0002-5621-285X","orcid":"https://orcid.org/0000-0002-5621-285X","contributorId":213321,"corporation":false,"usgs":true,"family":"Loewen","given":"Matthew","email":"","middleInitial":"W.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":954100,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dietterich, Hannah R. 0000-0001-7898-4343","orcid":"https://orcid.org/0000-0001-7898-4343","contributorId":212771,"corporation":false,"usgs":true,"family":"Dietterich","given":"Hannah R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":954101,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Whittington, Alan 0000-0003-2477-3043","orcid":"https://orcid.org/0000-0003-2477-3043","contributorId":365305,"corporation":false,"usgs":false,"family":"Whittington","given":"Alan","affiliations":[{"id":87127,"text":"University of Texas San Antonio","active":true,"usgs":false}],"preferred":false,"id":954102,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70272967,"text":"70272967 - 2025 - UAS and high-resolution satellite imagery improve the accuracy of cheatgrass detection across an invaded Yellowstone landscape","interactions":[],"lastModifiedDate":"2025-12-11T14:57:10.87794","indexId":"70272967","displayToPublicDate":"2025-10-03T07:48:38","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2602,"text":"Landscape Ecology","active":true,"publicationSubtype":{"id":10}},"title":"UAS and high-resolution satellite imagery improve the accuracy of cheatgrass detection across an invaded Yellowstone landscape","docAbstract":"Context
Cheatgrass (Bromus tectorum L.) is a problem across the western United States, where it outcompetes and replaces native grass species, alters habitats, and increases the risk of wildfires. Cheatgrass greens up earlier in the growing season compared to native grasses, making it classifiable with multi-temporal and multi-spectral remote sensing.
Objectives
We mapped cheatgrass at different scales in the Greater Yellowstone Ecosystem using 10-m Sentinel-2 imagery, 3-m PlanetScope, and 10-cm Uncrewed Aerial Systems (UAS) imagery. We compared these maps to field-collected data to address 1) variation in seasonal phenological signals of native and cheatgrass patches, 2) the influence of scale on detectability and map accuracy across our study area.
Results
Model accuracy to predict cheatgrass presence increased with imagery resolution and ranged from 83% using 10-m Sentinel-2 to 94% with the integration of PlanetScope and UAS imagery. While there was spatial agreement across models, the fusion of UAS data with satellite sources allowed the detection of small cheatgrass with more precision. Our novel use of NExR and dNExR (a redness and differenced redness index) data in the classification of cheatgrass capitalizes on the senescence of cheatgrass during peak summer periods where cloud free imagery is more prevalent.
Conclusions
Our satellite and UAS-based models of cheatgrass prediction compare the fusion of very high resolution imagery and phenological time differencing to identify infested areas. Tradeoffs between accuracy and expense lead to important questions for management applications.
","language":"English","publisher":"Springer Nature","doi":"10.1007/s10980-025-02200-2","usgsCitation":"Kreitler, J.R., Von Nonn, J.W., Munson, S.M., Zaideman, A.C., Bekedam, S.T., Rodman, A., and Villarreal, M., 2025, UAS and high-resolution satellite imagery improve the accuracy of cheatgrass detection across an invaded Yellowstone landscape: Landscape Ecology, v. 40, 189, 17 p., https://doi.org/10.1007/s10980-025-02200-2.","productDescription":"189, 17 p.","ipdsId":"IP-171263","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":497380,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10980-025-02200-2","text":"Publisher Index Page"},{"id":497321,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","city":"Gardiner","otherGeospatial":"northern gate to Yellowstone National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -110.74822627648368,\n 45.036818856935014\n ],\n [\n -110.74822627648368,\n 44.9980588003821\n ],\n [\n -110.6517700780241,\n 44.9980588003821\n ],\n [\n -110.6517700780241,\n 45.036818856935014\n ],\n [\n -110.74822627648368,\n 45.036818856935014\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"40","noUsgsAuthors":false,"publicationDate":"2025-10-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Kreitler, Jason R. 0000-0002-0243-5281 jkreitler@usgs.gov","orcid":"https://orcid.org/0000-0002-0243-5281","contributorId":4050,"corporation":false,"usgs":true,"family":"Kreitler","given":"Jason","email":"jkreitler@usgs.gov","middleInitial":"R.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":951916,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Von Nonn, Joshua W. 0009-0003-7251-7308","orcid":"https://orcid.org/0009-0003-7251-7308","contributorId":332293,"corporation":false,"usgs":true,"family":"Von Nonn","given":"Joshua","email":"","middleInitial":"W.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":951917,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Munson, Seth M. 0000-0002-2736-6374 smunson@usgs.gov","orcid":"https://orcid.org/0000-0002-2736-6374","contributorId":220026,"corporation":false,"usgs":true,"family":"Munson","given":"Seth","email":"smunson@usgs.gov","middleInitial":"M.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":951918,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zaideman, Alex C.","contributorId":363745,"corporation":false,"usgs":false,"family":"Zaideman","given":"Alex","middleInitial":"C.","affiliations":[{"id":13367,"text":"National Parks Service","active":true,"usgs":false}],"preferred":false,"id":951919,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bekedam, Steven T.","contributorId":363746,"corporation":false,"usgs":false,"family":"Bekedam","given":"Steven","middleInitial":"T.","affiliations":[{"id":13367,"text":"National Parks Service","active":true,"usgs":false}],"preferred":false,"id":951920,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rodman, Ann","contributorId":150932,"corporation":false,"usgs":false,"family":"Rodman","given":"Ann","affiliations":[{"id":6924,"text":"National Park Service, Upper Columbia Basin Network","active":true,"usgs":false}],"preferred":false,"id":951921,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Villarreal, Miguel L. 0000-0003-0720-1422 mvillarreal@usgs.gov","orcid":"https://orcid.org/0000-0003-0720-1422","contributorId":214980,"corporation":false,"usgs":true,"family":"Villarreal","given":"Miguel","email":"mvillarreal@usgs.gov","middleInitial":"L.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":951922,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70274009,"text":"70274009 - 2025 - Mechanisms influencing thermal refuges and territory occupancy by collared pikas during summer and winter","interactions":[],"lastModifiedDate":"2026-02-23T17:34:57.783598","indexId":"70274009","displayToPublicDate":"2025-10-02T10:29:41","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":899,"text":"Arctic, Antarctic, and Alpine Research","active":true,"publicationSubtype":{"id":10}},"title":"Mechanisms influencing thermal refuges and territory occupancy by collared pikas during summer and winter","docAbstract":"Collared pikas (Ochotona collaris) are cold adapted alpine lagomorphs of western Canada and Alaska, USA, that are vulnerable to direct and indirect effects of climate change. However, how and to what extent such changes influence persistence for this species is not well understood, particularly at fine spatial scales. Our goal was to evaluate how microclimate and microhabitat characteristics influence occupancy of collared pikas. We quantified thermal conditions during both summer and winter to test hypotheses about potential drivers of pika persistence. We recorded den occupancy and territory characteristics, including in situ measurements of den microclimate, across three study areas with contrasting climate gradients in southcentral and interior Alaska during 2017–2022. We examined changes in pika den occurrence by estimating annual colonization and extinction rates with a Bayesian dynamic occurrence model with forage availability, rock size, and multiple den temperature metrics as the explanatory variables. Our top model indicated that daily maximum temperature during both summer and winter best predicted den persistence and larger rocks had a moderating effect on warm summer den temperatures. This information helps to advance understanding about the mechanistic links between climate and population persistence for small mammal species under a rapidly changing arctic climate.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/15230430.2025.2502161","usgsCitation":"Harrison, L.A., Christie, K.S., Brandt, C., Falcy, M.R., Gilbert, S.L., Rachlow, J.L., 2025, Mechanisms influencing thermal refuges and territory occupancy by collared pikas during summer and winter: Arctic, Antarctic, and Alpine Research, v. 57, no. 1, 2502161, 17 p., https://doi.org/10.1080/15230430.2025.2502161.","productDescription":"2502161, 17 p.","ipdsId":"IP-179160","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":500594,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/15230430.2025.2502161","text":"Publisher Index Page"},{"id":500431,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -155.45653673679158,\n 62.833897716435274\n ],\n [\n -154.87402485631074,\n 60.0726821448782\n ],\n [\n -149.37753560622093,\n 60.9339172578167\n ],\n [\n -141.32845624709518,\n 59.98407037941388\n ],\n [\n -140.91038491440708,\n 62.78570300568498\n ],\n [\n -148.1580130001717,\n 64.18918315969188\n ],\n [\n -155.45653673679158,\n 62.833897716435274\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"57","issue":"1","noUsgsAuthors":false,"publicationDate":"2025-10-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Harrison, Lillian A.","contributorId":366637,"corporation":false,"usgs":false,"family":"Harrison","given":"Lillian","middleInitial":"A.","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":956114,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Christie, Katherine S.","contributorId":366638,"corporation":false,"usgs":false,"family":"Christie","given":"Katherine","middleInitial":"S.","affiliations":[{"id":7058,"text":"Alaska Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":956115,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brandt, Collette","contributorId":366639,"corporation":false,"usgs":false,"family":"Brandt","given":"Collette","affiliations":[{"id":87498,"text":"Joint Base Elmendorf-Richardson","active":true,"usgs":false}],"preferred":false,"id":956116,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Falcy, Matthew Richard 0000-0002-3332-2239","orcid":"https://orcid.org/0000-0002-3332-2239","contributorId":288500,"corporation":false,"usgs":true,"family":"Falcy","given":"Matthew","email":"","middleInitial":"Richard","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":956117,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gilbert, Sophie L.","contributorId":366640,"corporation":false,"usgs":false,"family":"Gilbert","given":"Sophie","middleInitial":"L.","affiliations":[{"id":87499,"text":"Vibrant Planet PBC","active":true,"usgs":false}],"preferred":false,"id":956118,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rachlow, Janet L.","contributorId":366641,"corporation":false,"usgs":false,"family":"Rachlow","given":"Janet","middleInitial":"L.","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":956119,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70274252,"text":"70274252 - 2025 - Thirty years of the U.S. National Land Cover Database: Impacts and future direction","interactions":[],"lastModifiedDate":"2026-03-19T20:00:20.373012","indexId":"70274252","displayToPublicDate":"2025-10-01T14:33:46","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5987,"text":"Photogrammetric Engineering & Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Thirty years of the U.S. National Land Cover Database: Impacts and future direction","docAbstract":"The National Land Cover Database (NLCD), developed through the Multi-Resolution Land Characteristics Consortium, was initiated 30 years ago and has continually provided critical, Landsat-based landcover and land-change information for the United States. Originally launched to address the lack of national-scale, moderate-resolution land-cover data, NLCD has evolved from the pioneering 1992 dataset into a comprehensive, annually updated product suite. Key innovations include the introduction of impervious surface mapping, forest canopy mapping, standardized Landsat mosaics, national-scale accuracy assessments, continual evolution of deep learning and artificial intelligence methodologies, and a transition toward operational, change-focused monitoring. The NLCD has become an essential resource for scientific research, land management, and policy development, with extensive adoption across federal, state, and local agencies; academia; and the private sector. The NLCD data underpin a wide array of applications, including biodiversity conservation, urban planning, hydrology, human health studies, and natural hazard assessment. As new global and high-resolution commercial land-cover products emerge, the NLCD continues to distinguish itself through its temporal depth, federal backing, and thematic consistency. Moving forward, the NLCD will maintain its niche as the leading, moderate-resolution, long-term land-cover and land-change dataset for the United States, ensuring continued support for broad national applications while complementing higher-resolution and global-mapping efforts.
","language":"English","publisher":"Ingenta","doi":"10.14358/PERS.25-00121R2","usgsCitation":"Sohl, T.L., Jin, S., Dewitz, J., Wickham, J., Brown, J.F., Stehman, S., Herold, N., Schleeweis, K., Tollerud, H.J., and Deering, C., 2025, Thirty years of the U.S. National Land Cover Database: Impacts and future direction: Photogrammetric Engineering & Remote Sensing, v. 91, no. 10, p. 647-659, https://doi.org/10.14358/PERS.25-00121R2.","productDescription":"13 p.","startPage":"647","endPage":"659","ipdsId":"IP-180474","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":501337,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"91","issue":"10","noUsgsAuthors":false,"publicationDate":"2025-10-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Sohl, Terry L. 0000-0002-9771-4231 sohl@usgs.gov","orcid":"https://orcid.org/0000-0002-9771-4231","contributorId":648,"corporation":false,"usgs":true,"family":"Sohl","given":"Terry","email":"sohl@usgs.gov","middleInitial":"L.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":957183,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jin, Suming 0000-0001-9919-8077 sjin@usgs.gov","orcid":"https://orcid.org/0000-0001-9919-8077","contributorId":4397,"corporation":false,"usgs":true,"family":"Jin","given":"Suming","email":"sjin@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":957184,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dewitz, Jon 0000-0002-0458-212X","orcid":"https://orcid.org/0000-0002-0458-212X","contributorId":222454,"corporation":false,"usgs":true,"family":"Dewitz","given":"Jon","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":957185,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wickham, James","contributorId":140259,"corporation":false,"usgs":false,"family":"Wickham","given":"James","affiliations":[{"id":12657,"text":"EPA NEIC","active":true,"usgs":false}],"preferred":false,"id":957186,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brown, Jesslyn F. 0000-0002-9976-1998 jfbrown@usgs.gov","orcid":"https://orcid.org/0000-0002-9976-1998","contributorId":176609,"corporation":false,"usgs":true,"family":"Brown","given":"Jesslyn","email":"jfbrown@usgs.gov","middleInitial":"F.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":957187,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stehman, Stephen","contributorId":39747,"corporation":false,"usgs":true,"family":"Stehman","given":"Stephen","affiliations":[],"preferred":false,"id":957188,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Herold, Nathaniel","contributorId":140258,"corporation":false,"usgs":false,"family":"Herold","given":"Nathaniel","email":"","affiliations":[{"id":12641,"text":"NOAA NMFS","active":true,"usgs":false}],"preferred":false,"id":957189,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Schleeweis, Karen","contributorId":169308,"corporation":false,"usgs":false,"family":"Schleeweis","given":"Karen","email":"","affiliations":[{"id":6679,"text":"US Forest Service, Rocky Mountain Research Station","active":true,"usgs":false}],"preferred":false,"id":957190,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Tollerud, Heather J. 0000-0001-9507-4456","orcid":"https://orcid.org/0000-0001-9507-4456","contributorId":210820,"corporation":false,"usgs":true,"family":"Tollerud","given":"Heather","email":"","middleInitial":"J.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":957191,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Deering, Carol 0000-0003-3565-6264 cdeering@usgs.gov","orcid":"https://orcid.org/0000-0003-3565-6264","contributorId":3001,"corporation":false,"usgs":true,"family":"Deering","given":"Carol","email":"cdeering@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":957192,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70273490,"text":"70273490 - 2025 - Update to a management-focused population viability analysis for North Atlantic right whales","interactions":[],"lastModifiedDate":"2026-01-20T16:12:22.264469","indexId":"70273490","displayToPublicDate":"2025-10-01T10:01:58","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":5134,"text":"NOAA Technical Memorandum","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"NMFS-NE-337","title":"Update to a management-focused population viability analysis for North Atlantic right whales","docAbstract":"We provide an update to the recently published population viability analysis for North Atlantic right whales (Eubalaena glacialis). The update includes improvements to the reproduction modeling and also shares additional context given evidence of reduced mortality indicated by recent population monitoring. Projections from the analysis are used to quantify simulated population sizes across 100 years and resulting quasi-extinction probabilities (falling below 50 mature females that have proven ability to reproduce) to compare hypothetical scenarios related to management of threats and changing environmental conditions. Under a status quo scenario reflecting conditions of 2019, prior to the enactment of new regulations by the U.S. and Canada, the North Atlantic right whale population would be expected to continue to fall, with a median decline of 88 percent (95% projection interval, –98 percent to –45 percent change) and a probability of falling below 50 proven females (i.e., quasi-extinction) of 0.988 at 100 years. In hypothetical scenarios that fully remove each of the three primary threats to right whales one at a time, removal of the entanglement threat alone reduces the probability of falling below 50 proven females in 100 years to 0.070; removal of the vessel strike threat alone reduces it to 0.522; and a return to historical prey abundance patterns (pre-2010), but with both human-related threats still in place, reduces it to 0.524. Although additional baseline scenarios were explored to examine the potential effects of recent regulations, we found that the most up-to-date mortality rates (2020–2022) are similar to those simulated under a 70% reduction in severe entanglement injury compared to rates estimated during 2013–2019. If management measures implemented in the U.S. and Canada continue to reduce mortality, the estimated probability of falling below 50 proven females in 100 years is 0.234. Our model continues to provide a tool for assessing North Atlantic right whale recovery.
","language":"English","publisher":"NOAA","doi":"10.25923/0xdp-8s42","usgsCitation":"Linden, D., Runge, M., Hostetler, J.A., Borggaard, D., Garrison, L., Knowlton, A., Lesage, V., Williams, R., and Pace III, R., 2025, Update to a management-focused population viability analysis for North Atlantic right whales: NOAA Technical Memorandum NMFS-NE-337, 29 p., https://doi.org/10.25923/0xdp-8s42.","productDescription":"29 p.","ipdsId":"IP-181288","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":498779,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2025-10-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Linden, Daniel","contributorId":199671,"corporation":false,"usgs":false,"family":"Linden","given":"Daniel","affiliations":[],"preferred":false,"id":953918,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Runge, Michael C. 0000-0002-8081-536X mrunge@usgs.gov","orcid":"https://orcid.org/0000-0002-8081-536X","contributorId":214737,"corporation":false,"usgs":true,"family":"Runge","given":"Michael","email":"mrunge@usgs.gov","middleInitial":"C.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":953919,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hostetler, J. A. 0000-0003-3669-1758","orcid":"https://orcid.org/0000-0003-3669-1758","contributorId":11319,"corporation":false,"usgs":true,"family":"Hostetler","given":"J.","middleInitial":"A.","affiliations":[],"preferred":true,"id":953920,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Borggaard, Diane","contributorId":244380,"corporation":false,"usgs":false,"family":"Borggaard","given":"Diane","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":953921,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Garrison, Lance","contributorId":244391,"corporation":false,"usgs":false,"family":"Garrison","given":"Lance","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":953922,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Knowlton, Amy R.","contributorId":352046,"corporation":false,"usgs":false,"family":"Knowlton","given":"Amy R.","affiliations":[{"id":37373,"text":"New England Aquarium","active":true,"usgs":false}],"preferred":false,"id":953923,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lesage, Véronique","contributorId":352276,"corporation":false,"usgs":false,"family":"Lesage","given":"Véronique","affiliations":[{"id":13677,"text":"Fisheries and Oceans Canada","active":true,"usgs":false}],"preferred":false,"id":953924,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Williams, Robert A. 0000-0002-2973-8493","orcid":"https://orcid.org/0000-0002-2973-8493","contributorId":203802,"corporation":false,"usgs":false,"family":"Williams","given":"Robert A.","affiliations":[{"id":36721,"text":"USGS-Emeritus","active":true,"usgs":false}],"preferred":false,"id":953925,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Pace III, Richard","contributorId":365205,"corporation":false,"usgs":false,"family":"Pace III","given":"Richard","affiliations":[{"id":38698,"text":"NOAA Fisheries","active":true,"usgs":false}],"preferred":false,"id":953926,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70272617,"text":"70272617 - 2025 - Combining scanning electron microscopy, X-ray diffraction, and X-ray fluorescence to characterize shear zones at the Pogo gold deposit, Alaska","interactions":[],"lastModifiedDate":"2025-11-25T14:13:35.991175","indexId":"70272617","displayToPublicDate":"2025-10-01T09:44:09","publicationYear":"2025","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Combining scanning electron microscopy, X-ray diffraction, and X-ray fluorescence to characterize shear zones at the Pogo gold deposit, Alaska","docAbstract":"This study employs a multi-method analytical approach to characterize the mineralogical, geochemical, and textural properties of fault rocks from the Pogo gold mine in the Yukon-Tanana Upland, central Alaska. Specifically, we examine cataclasites, to document the structural and geochemical evolution of shear zones and their associations with gold mineralization. \nTo investigate the shear zone, we integrate portable X-ray fluorescence (pXRF), scanning electron microscopy-based automated mineralogy (SEM-AM), X-ray diffraction (XRD), and high-resolution micro-X-ray fluorescence (micro-XRF) mapping. These methods collectively provide insights into bulk and trace element chemistry, mineralogical composition, and deformation-related textures across multiple scales. Handheld pXRF enables rapid geochemical screening, guiding SEM-AM and XRD analyses to ensure consistent mineralogical interpretation. X-ray diffraction identifies and quantifies crystalline phases, while SEM-AM produces high-resolution mineral maps, revealing mineral abundances, grain-scale textures, and gold associations. Micro-XRF mapping further refines our understanding by showing visual trace element distributions at sub-millimetre resolution.\nBy integrating these techniques, we improve our understanding of the nature and geochemistry of Pogo shear zones, their role in gold mineralization, and support metallurgical processing strategies. This approach enhances exploration models and resource characterization for structurally complex gold deposits.","conferenceTitle":"18th SGA Biennial Meeting","conferenceDate":"August 3-7, 2025","conferenceLocation":"Golden, CO","language":"English","publisher":"Society for Geology Applied to Mineral Deposits (SGA)","usgsCitation":"Pfaff, K.I., Kasprowicz, F., Caine, J., Benzel, W., and Lowers, H.A., 2025, Combining scanning electron microscopy, X-ray diffraction, and X-ray fluorescence to characterize shear zones at the Pogo gold deposit, Alaska, 18th SGA Biennial Meeting, v. 3, Golden, CO, August 3-7, 2025, p. 1157-1160.","productDescription":"4 p.","startPage":"1157","endPage":"1160","ipdsId":"IP-176764","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":496856,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://www.e-sga.org/publications/conference-proceedings"},{"id":496827,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","volume":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Pfaff, Katharina I. 0000-0002-6605-2722","orcid":"https://orcid.org/0000-0002-6605-2722","contributorId":362430,"corporation":false,"usgs":true,"family":"Pfaff","given":"Katharina","middleInitial":"I.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":950951,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kasprowicz, Filip","contributorId":363040,"corporation":false,"usgs":false,"family":"Kasprowicz","given":"Filip","affiliations":[{"id":86594,"text":"Center to Advance the Science of Exploration to Reclamation in Mining, Department of Geology and Geological Engineering, Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":950952,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Caine, Jonathan Saul 0000-0002-7269-6989 jscaine@usgs.gov","orcid":"https://orcid.org/0000-0002-7269-6989","contributorId":199295,"corporation":false,"usgs":true,"family":"Caine","given":"Jonathan Saul","email":"jscaine@usgs.gov","affiliations":[],"preferred":true,"id":950953,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Benzel, William 0000-0002-4085-1876 wbenzel@usgs.gov","orcid":"https://orcid.org/0000-0002-4085-1876","contributorId":3594,"corporation":false,"usgs":true,"family":"Benzel","given":"William","email":"wbenzel@usgs.gov","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":950954,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lowers, Heather A. 0000-0001-5360-9264 hlowers@usgs.gov","orcid":"https://orcid.org/0000-0001-5360-9264","contributorId":191307,"corporation":false,"usgs":true,"family":"Lowers","given":"Heather","email":"hlowers@usgs.gov","middleInitial":"A.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":950955,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"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":70272134,"text":"70272134 - 2025 - Disentangling the historical impacts of warming and fishing on exploited freshwater fish populations","interactions":[],"lastModifiedDate":"2025-11-17T14:48:38.067774","indexId":"70272134","displayToPublicDate":"2025-10-01T07:44:21","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5010,"text":"Science Advances","active":true,"publicationSubtype":{"id":10}},"title":"Disentangling the historical impacts of warming and fishing on exploited freshwater fish populations","docAbstract":"Worldwide, exploited fish populations are increasingly affected by the combined effects of warming and fishing. Disentangling the relative effects of these factors is challenging yet crucial for designing management strategies. We used a temperature-dependent population dynamics model to assess the impacts of lake warming and fishing on 521 freshwater fish populations in the Midwestern United States—a transitional zone between cold- and warmwater species. Overall, most warmwater species (65% of populations) exhibited increases in productivity from warming, while slightly more than half of the cool-/cold-water species (53% of populations) experienced reduced productivity. Populations closer to their carrying capacity showed greater resilience to warming. For the majority of populations (92%), fishing had a more pronounced effect on population dynamics than warming during the time period examined. Therefore, while warming is likely to increasingly threaten many fish populations, effective local fishery management remains a key lever to mitigate these impacts.
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2025 - Long Term Resource Monitoring procedures—Aquatic vegetation monitoring","interactions":[],"lastModifiedDate":"2026-02-03T16:24:07.215237","indexId":"tm2A22","displayToPublicDate":"2025-09-30T14:48:28","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2-A22","displayTitle":"Long Term Resource Monitoring Procedures—Aquatic Vegetation Monitoring","title":"Long Term Resource Monitoring procedures—Aquatic vegetation monitoring","docAbstract":"This standard operating procedure (SOP) manual describes the collection of standardized, long-term data for aquatic vegetation communities in selected study pools of the Upper Mississippi River System in the United States. The primary intent of the data collection is to assess the status and trends that aid in understanding the unique river ecosystem and to guide large-scale ecological restoration of the river and its biological communities, like aquatic plants and their dependent wildlife. This SOP is an update to the version published in 2000 and reflects modifications to sample sizes and additions of new data collection procedures. All long-term monitoring programs and their SOPs must be adapted to changing conditions and be improved through learning, and this SOP clarifies procedures and adds new elements since the initial SOP was written more than 25 years ago. The SOP is intended for multiple audiences, including vegetation specialists through the Upper Mississippi River Restoration Program, data analysts using the publicly available data generated through this SOP, and natural resource managers and restoration practitioners who need data and science to guide some decisions. This SOP may be transferable and adaptable to other ecosystems when the aquatic plant community is the focus.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm2A22","collaboration":"Prepared in cooperation with the Long Term Resource Monitoring element of the Upper Mississippi River Restoration Program, U.S. Army Corps of Engineers, U.S. Fish and Wildlife Service, Iowa Department of Natural Resources, Minnesota Department of Natural Resources, and Wisconsin Department of Natural Resources","usgsCitation":"Larson, D.M., Lund, E., Carhart, A.M., Fopma, S., and Szura, S., 2025, Long Term Resource Monitoring procedures—Aquatic vegetation monitoring: U.S. Geological Survey Techniques and Methods, book 2, chap. A22, 40 p., https://doi.org/10.3133/tm2A22.","productDescription":"Report: vi, 40 p.; 2 Linked Figures","numberOfPages":"50","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-167317","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":496282,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/02/a22/tm2A22.pdf","text":"Report","size":"4.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"TM 2-A22"},{"id":496281,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/02/a22/coverthb2.jpg"},{"id":496283,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/tm/02/a22/tm2A22.XML"},{"id":496284,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/tm/02/a22/images/"},{"id":496286,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/tm2A22/full"},{"id":496285,"rank":5,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/tm/02/a22/downloads/","text":"Printable versions of figures 2.1 and 7.1"}],"country":"United States","state":"Illinois, Iowa, Minnesota, Missouri, Wisconsin","otherGeospatial":"Illinois River, Upper Mississippi River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -91.82084396790316,\n 44.04246451932946\n ],\n [\n -91.50791848601513,\n 38.40902936668505\n ],\n [\n -89.8837153943196,\n 38.45968306709577\n ],\n [\n -89.16595397141731,\n 41.89729975230259\n ],\n [\n -90.33908638801539,\n 43.40513483806296\n ],\n [\n -91.27142102824394,\n 43.92243866259706\n ],\n [\n -91.82084396790316,\n 44.04246451932946\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Upper Midwest Environmental Sciences Center
U.S. Geological Survey
2630 Fanta Reed Road
La Crosse, Wisconsin 54603
The Upper Mississippi River Restoration Program’s Long Term Resource Monitoring element made updates to the standardized operating procedure manual for collecting standardized data for aquatic vegetation in the Upper Mississippi River System. This updated manual helps users collect data more effectively. The information from the monitoring surveys is used to assess the status and trends of aquatic plants, and helps restoration managers to engineer habitat conditions for this unique river ecosystem.
","publicationDate":"2025-09-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Larson, Danelle M. 0000-0001-6349-6267","orcid":"https://orcid.org/0000-0001-6349-6267","contributorId":228838,"corporation":false,"usgs":true,"family":"Larson","given":"Danelle","email":"","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":949725,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lund, Eric","contributorId":221777,"corporation":false,"usgs":false,"family":"Lund","given":"Eric","affiliations":[{"id":6964,"text":"Minnesota Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":949726,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Carhart, Alicia M.","contributorId":361967,"corporation":false,"usgs":false,"family":"Carhart","given":"Alicia","middleInitial":"M.","affiliations":[{"id":6913,"text":"Wisconsin Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":949727,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fopma, Seth","contributorId":360281,"corporation":false,"usgs":false,"family":"Fopma","given":"Seth","affiliations":[{"id":24495,"text":"Iowa Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":949728,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Szura, Stephanie","contributorId":360278,"corporation":false,"usgs":false,"family":"Szura","given":"Stephanie","affiliations":[{"id":6964,"text":"Minnesota Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":949729,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70271982,"text":"sir20255031 - 2025 - User’s guide for the National Hydrography Dataset Plus High Resolution (NHDPlus HR)","interactions":[{"subject":{"id":70206120,"text":"ofr20191096 - 2019 - User's guide for the national hydrography dataset plus (NHDPlus) high resolution","indexId":"ofr20191096","publicationYear":"2019","noYear":false,"displayTitle":"User’s Guide for the National Hydrography Dataset Plus (NHDPlus) High Resolution","title":"User's guide for the national hydrography dataset plus (NHDPlus) high resolution"},"predicate":"SUPERSEDED_BY","object":{"id":70271982,"text":"sir20255031 - 2025 - User’s guide for the National Hydrography Dataset Plus High Resolution (NHDPlus HR)","indexId":"sir20255031","publicationYear":"2025","noYear":false,"title":"User’s guide for the National Hydrography Dataset Plus High Resolution (NHDPlus HR)"},"id":1}],"lastModifiedDate":"2026-02-03T16:23:33.096091","indexId":"sir20255031","displayToPublicDate":"2025-09-30T13:20:00","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":"2025-5031","displayTitle":"User’s Guide for the National Hydrography Dataset Plus High Resolution (NHDPlus HR)","title":"User’s guide for the National Hydrography Dataset Plus High Resolution (NHDPlus HR)","docAbstract":"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
Fostering a sense of classroom community in earth science classes supports students’ sense of belonging within the classroom and the broader scientific community, helping them build a sense of identity as a geoscientist. This study examines the effects of incorporating a 2-week, collaborative role-playing activity on sense of classroom community and science identity in an introductory hydrology class. Students assumed roles of residents, medical center representatives, government employees, and environmental activists to learn about flooding through a community-centered lens, focusing on a flood event in Harris County, Texas during Tropical Storm Allison. Pre-post-surveys were given immediately before and after the learning module to evaluate classroom community, science identity using Likert scales, and hydrologist identity using a pictorial scale. Qualitative analysis of a short-answer question in which students defined “hydrologist” provided context for quantitative identity data. Post-survey data on classroom community shows an increase in mean agreement as compared to the pre-survey. This increase was statistically significant for four classroom community statements. Paired science identity data show small effect size and no significant change, but pictorial identity as a hydrologist shows significant growth. Social aspects of the role-playing activity did not significantly alter student’s already high science identity but altered their conceptions of the social implications of hydrology and increased identity as hydrologists. The significant increase in classroom community has important implications for using role-playing as an active learning strategy to enhance student learning experience by creating a positive classroom climate and connecting hydrology concepts to community needs.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/10899995.2025.2565990","usgsCitation":"Plenge, M., Dolan, W., Tomlinson, A., Hutson, B., and Pavelsky, T., 2025, Impact of a place-based role-playing exercise on student sense of classroom community and science identity in a hydrology class: Journal of Geoscience Education, https://doi.org/10.1080/10899995.2025.2565990.","ipdsId":"IP-171850","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":498550,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"edition":"Online First","noUsgsAuthors":false,"publicationDate":"2025-09-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Plenge, Megan","contributorId":365013,"corporation":false,"usgs":false,"family":"Plenge","given":"Megan","affiliations":[{"id":27051,"text":"University of North Carolina at Chapel Hill","active":true,"usgs":false}],"preferred":false,"id":953582,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dolan, Wayana 0000-0001-8405-4302","orcid":"https://orcid.org/0000-0001-8405-4302","contributorId":354442,"corporation":false,"usgs":true,"family":"Dolan","given":"Wayana","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":953583,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tomlinson, Alexa","contributorId":365016,"corporation":false,"usgs":false,"family":"Tomlinson","given":"Alexa","affiliations":[{"id":27051,"text":"University of North Carolina at Chapel Hill","active":true,"usgs":false}],"preferred":false,"id":953584,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hutson, Bryant","contributorId":365018,"corporation":false,"usgs":false,"family":"Hutson","given":"Bryant","affiliations":[{"id":27051,"text":"University of North Carolina at Chapel Hill","active":true,"usgs":false}],"preferred":false,"id":953585,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pavelsky, Tamlin","contributorId":149629,"corporation":false,"usgs":false,"family":"Pavelsky","given":"Tamlin","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":953586,"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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of beaver dams and ponds on water quality in urban streams of the Tualatin River Basin, northwestern Oregon"},"predicate":"IS_PART_OF","object":{"id":70269440,"text":"sir20255039 - 2025 - Beavers in the Tualatin River Basin, northwestern Oregon","indexId":"sir20255039","publicationYear":"2025","noYear":false,"title":"Beavers in the Tualatin River Basin, northwestern Oregon"},"id":1}],"isPartOf":{"id":70269440,"text":"sir20255039 - 2025 - Beavers in the Tualatin River Basin, northwestern Oregon","indexId":"sir20255039","publicationYear":"2025","noYear":false,"title":"Beavers in the Tualatin River Basin, northwestern Oregon"},"lastModifiedDate":"2026-02-03T16:22:17.111248","indexId":"sir20255039D","displayToPublicDate":"2025-09-30T07:54:32","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations 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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
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.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255039A","collaboration":"Prepared in cooperation with Clean Water Services","usgsCitation":"White, J.S., Smith, C.D., Jones, K.L., and Rounds, S.A., 2025, Stream network capacity to support beaver dams in the Tualatin River Basin, northwestern Oregon, chap. A 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–A, 20 p., https://doi.org/10.3133/sir20255039A.","productDescription":"Report: viii, 20 p.; 2 Data Releases","onlineOnly":"Y","ipdsId":"IP-102303","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":495854,"rank":7,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5039/a/sir20255039a.XML"},{"id":495853,"rank":6,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5039/a/images"},{"id":495852,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1SURYZ4","text":"USGS data release","description":"USGS data release","linkHelpText":"Stream network capacity to support beaver dams, Tualatin River Basin, northwest Oregon"},{"id":496245,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7PZ57QP","text":"USGS data release","description":"USGS data release","linkHelpText":"Beaver dam locations and beaver activity in the Tualatin Basin, Oregon"},{"id":495851,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255039a/full","linkFileType":{"id":5,"text":"html"},"description":"SIR 2025-5039-A"},{"id":495850,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5039/a/sir20255039a.pdf","size":"5.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5039-A"},{"id":495849,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5039/a/coverthb.jpg"}],"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
Growing interest in beaver-assisted restoration in the Tualatin River Basin of northwestern Oregon motivated a series of studies by the U.S. Geological Survey to assess the capacity of the stream network to support beaver dams and to evaluate the effects of beaver dams and ponds on urban streams. This multichapter volume describes the data collection from 2016–17 and the findings of these studies, which were done in partnership with Clean Water Services. Chapter A documents the locations of beaver dams in the Tualatin River Basin and how many beaver dams the stream network could support with existing and improved riparian vegetation. Beaver dam capacity was estimated by modifying existing tools to account for the low gradient of many streams in the Tualatin River Basin. Chapter B describes the effects of beaver dams and ponds on hydrologic and hydraulic responses of storm flows. Hydrologic and hydraulic responses for two urban stream reaches were compared with and without beaver dams and ponds and for a range of streamflow conditions using two-dimensional hydraulic models. Chapter C characterizes the effects of beaver dams and ponds on the transport and deposition of suspended sediment. Continuous turbidity, discrete suspended-sediment samples, and streamflow measurements collected during storms and base-flow periods were used to assess: (1) suspended-sediment loads upstream and downstream from two beaver-affected reaches, and (2) seasonal and longitudinal turbidity patterns. Chapter D describes the effects of beaver dams and ponds on longitudinal, spatial, and seasonal water-quality patterns. Continuous and synoptic water-quality data were collected along urban stream reaches, and net ecosystem production was calculated for two beaver-affected reaches. The findings of these studies illustrate that the effects of beaver dams and ponds on hydrology, hydraulics, suspended-sediment transport and deposition, and water quality are dependent on the characteristics of a stream reach (for example, channel gradient, groundwater exchange, and riparian vegetation) and the characteristics of beaver dams and ponds along that reach. This information can be used to consider the implications of beaver-assisted restoration in the Tualatin River Basin and the effects of beaver dams and ponds in urban streams.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255039","collaboration":"Prepared in cooperation with Clean Water Services","usgsCitation":"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, https://doi.org/10.3133/sir20255039.","productDescription":"Chapters A-D","onlineOnly":"Y","costCenters":[],"links":[{"id":496209,"rank":2,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://doi.org/10.3133/fs20253022","text":"Fact Sheet 2025-3022","description":"FS 2025-3022","linkHelpText":"- Beaver dams and their effects on urban streams in the Tualatin River Basin, northwestern Oregon"},{"id":496091,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5039/coverthb.jpg"}],"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
Between 1980 and 1986, the U.S. Geological Survey made a series of 1:2,000-scale topographic contour maps from aerial photographic surveys to monitor the eruption. These maps were made for operational purposes and were not intended for publication. Since then, advances in technology made it possible to digitize the original, highly detailed hardcopy maps and derive new digital data elevation models of the surface of the lava dome. These digital elevation models allow for the visualization of the progression of the eruption and reveal the rubbly, chaotic surface of the lava flows and dome. Additionally, these new data help fill gaps in the long-term record of topographic changes that have occurred at the volcano since the May 18, 1980, eruption.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/gip262","usgsCitation":"Bard, J.A., Friedle, C.M., Bartee, L., Dierker, B.C., Ganick, J.M., Gregory, N.M., Hill, K.R., Klug, J.G., Kruger, A., Mooney, D.T., Morrison, R.T., Rojas, I.I., Rollo, P., Stanton, S.A., Stewart, B., Stuhlmuller, B.E., Zyla, A.D., 2025, Rebuilding a volcano one lava flow at a time—Visualizing the lava dome-building eruption in the crater of Mount St. Helens, 1982–1986: U.S. Geological Survey General Information Product 262, https://doi.org/10.3133/gip262.","productDescription":"1 p.","onlineOnly":"N","ipdsId":"IP-180615","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":496232,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/gip/262/coverthb.jpg"},{"id":496233,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/gip/262/gip262.pdf","text":"Document","size":"33.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"GIP 262"},{"id":497787,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118911.htm"}],"country":"United States","state":"Washington","otherGeospatial":"Mount St. Helens","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.38015899040656,\n 46.32565684366381\n ],\n [\n -122.38015899040656,\n 46.080226964619754\n ],\n [\n -122.00665168620951,\n 46.080226964619754\n ],\n [\n -122.00665168620951,\n 46.32565684366381\n ],\n [\n -122.38015899040656,\n 46.32565684366381\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Center Director, Science Analytics and Synthesis Program
U.S. Geological Survey
P.O. Box 25046, Mail Stop 302
Denver, CO 80225
Komatiitic volcanic rocks are important hosts of Ni sulfide mineralization and record early Earth evolution; however, those in the well-studied Archean Wyoming Province have received little attention. Here, we elucidate the timing and petrogenesis of the Bradley Peak komatiitic volcanic rocks using field and textural observations, geochronology, and geochemistry. Detrital and igneous zircon U-Pb ages for two samples from previously undated units support published age determinations, placing the eruption age at 2.72 Ga. Stratigraphy of the volcanic flows was mapped and 36 samples including cumulates, greenschists, and spinifex-textured rocks were collected. Whole-rock geochemistry was used to classify the spinifex-textured samples as Al-undepleted komatiitic basalts (11–17 wt% MgO). Platinum-group element concentrations (n = 25) are like those in global Al-undepleted komatiitic basalts, and PGE/Ti ratios do not indicate the volcanic flows likely host sulfide mineralization. Initial εNd values of −0.5 to +4.7 (n = 16), indicate that these lavas were derived from a depleted mantle source and have negligible evolved crust contamination. The primary magma to the komatiitic basalt flows is estimated to have had 19 wt% MgO and be derived from ∼15 to 25 % mantle partial melting at 3–4 GPa. Trace element chemistry and thermodynamic modeling suggest the primary melt assimilated local banded iron formation. Although the Bradley Peak komatiitic basalts do not contain positive evidence of magmatic sulfide deposits, depleted Au in the flows suggests they could be source rocks for nearby orogenic gold deposits.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.precamres.2025.107929","usgsCitation":"Zieman, L.J., Jenkins, M., and Poletti, J.E., 2025, Petrogenesis and mineralization potential of spinifex komatiitic basalts in the Bradley Peak greenstone terrane, Wyoming Province: Precambrian Research, v. 430, 107929, 16 p., https://doi.org/10.1016/j.precamres.2025.107929.","productDescription":"107929, 16 p.","ipdsId":"IP-180102","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":496332,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.precamres.2025.107929","text":"Publisher Index Page"},{"id":496269,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Bradley Peak greenstone terrane","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -107.0833,\n 42.25\n ],\n [\n -107.0833,\n 42.125\n ],\n [\n -106.9167,\n 42.125\n ],\n [\n -106.9167,\n 42.25\n ],\n [\n -107.0833,\n 42.25\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"430","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Zieman, Lisa Joanne 0000-0002-0065-2565","orcid":"https://orcid.org/0000-0002-0065-2565","contributorId":345932,"corporation":false,"usgs":true,"family":"Zieman","given":"Lisa","email":"","middleInitial":"Joanne","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":949679,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jenkins, Michael 0000-0002-4261-409X mjenkins@usgs.gov","orcid":"https://orcid.org/0000-0002-4261-409X","contributorId":172433,"corporation":false,"usgs":true,"family":"Jenkins","given":"Michael","email":"mjenkins@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":949680,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Poletti, Jacob Evan 0000-0002-3091-1249","orcid":"https://orcid.org/0000-0002-3091-1249","contributorId":345933,"corporation":false,"usgs":true,"family":"Poletti","given":"Jacob","email":"","middleInitial":"Evan","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":949681,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70272068,"text":"70272068 - 2025 - Hot stops, cool looks: Aesthetic solutions for thermal comfort at transit stops","interactions":[],"lastModifiedDate":"2025-11-14T16:55:04.367089","indexId":"70272068","displayToPublicDate":"2025-09-27T09:51:56","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5408,"text":"Urban Climate","active":true,"publicationSubtype":{"id":10}},"title":"Hot stops, cool looks: Aesthetic solutions for thermal comfort at transit stops","docAbstract":"Increased urban heat intensifies thermal discomfort, particularly in critical public spaces such as transit stops. This study investigated the predictors of transit users' thermal perceptions in Denver, Colorado—a semi-arid city. Sixty bus stops spanning a gradient of land cover compositions were selected for study. Micrometeorological data, including thermal comfort indices, were collected alongside survey responses from 77 users at 31 unique stops. Survey responses captured thermal sensation votes (TSV) and thermal comfort votes (TCV) as well as aesthetic preference votes (APV) of bus stop structure. Ordinal forest analysis revealed that for both TSV and TCV, aesthetic preferences and thermal comfort indices were the most influential predictors of transit user thermal perception. Multiple ordered logistic regression further demonstrated that, for TSV, higher APV was associated with lower odds of rating a thermal environment as hot (OR = 0.664, p < 0.002) while increased Physiological Equivalent Temperature (PET) raised these odds (OR = 1.101, p < 0.006). An interaction analysis demonstrated that APV significantly moderated the effect of PET on TCV (interaction OR = 1.040, p < 0.041), suggesting that aesthetic preferences are significantly correlated with an alleviation of thermal discomfort under high heat stress. Bivariate analyses further indicated that bus stops with greater tree canopy cover (OR = 1.032, p < 0.025) and higher visible vegetation view factors (OR = 10.350, p < 0.022) were more likely to be rated as aesthetically pleasing. These findings underscore the importance of aesthetic preferences in transit stop planning for urban heat resiliency.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.uclim.2025.102606","usgsCitation":"Steinharter, L., Ibsen, P.C., Lam, T.Y., Nesbit, L., Park, K., and McHale, M., 2025, Hot stops, cool looks: Aesthetic solutions for thermal comfort at transit stops: Urban Climate, v. 64, 102606, 25 p., https://doi.org/10.1016/j.uclim.2025.102606.","productDescription":"102606, 25 p.","ipdsId":"IP-174250","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":496501,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","city":"Denver","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -105.1863006041697,\n 39.98477049655375\n ],\n [\n -105.1863006041697,\n 39.448378011936086\n ],\n [\n -104.68565284554944,\n 39.448378011936086\n ],\n [\n -104.68565284554944,\n 39.98477049655375\n ],\n [\n -105.1863006041697,\n 39.98477049655375\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"64","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Steinharter, Logan","contributorId":362081,"corporation":false,"usgs":false,"family":"Steinharter","given":"Logan","affiliations":[{"id":36972,"text":"University of British Columbia","active":true,"usgs":false}],"preferred":false,"id":949970,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ibsen, Peter Christian 0000-0002-3436-9100","orcid":"https://orcid.org/0000-0002-3436-9100","contributorId":260735,"corporation":false,"usgs":true,"family":"Ibsen","given":"Peter","email":"","middleInitial":"Christian","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":949971,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lam, Tzeng Yih","contributorId":362084,"corporation":false,"usgs":false,"family":"Lam","given":"Tzeng","middleInitial":"Yih","affiliations":[{"id":36972,"text":"University of British Columbia","active":true,"usgs":false}],"preferred":false,"id":949972,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nesbit, Lorien","contributorId":362087,"corporation":false,"usgs":false,"family":"Nesbit","given":"Lorien","affiliations":[{"id":36972,"text":"University of British Columbia","active":true,"usgs":false}],"preferred":false,"id":949973,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Park, Keunhyun","contributorId":224296,"corporation":false,"usgs":false,"family":"Park","given":"Keunhyun","email":"","affiliations":[{"id":40852,"text":"Utah State University, Department of Landscape Architecture and Environmental Planning","active":true,"usgs":false}],"preferred":false,"id":949974,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McHale, Melissa R.","contributorId":362090,"corporation":false,"usgs":false,"family":"McHale","given":"Melissa","middleInitial":"R.","affiliations":[{"id":36972,"text":"University of British Columbia","active":true,"usgs":false}],"preferred":false,"id":949975,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ]}