Ponds are an important source of greenhouse gases (GHGs) to the atmosphere, yet evaluating their role in global biogeochemical cycling is currently hampered by limitations in quantifying their global distribution. Existing satellite-derived estimates of lake distributions have difficulty identifying small lakes (5–10 ha) and ponds (<5 ha) due to limitations in satellite resolution and challenges extracting individual small waterbodies from low-albedo surfaces, vegetated water, and lotic water systems including rivers and streams. In this study, we developed generalizable pond mapping strategies based on their spatial-temporal-spectral characteristics to fully exploit accessible medium-resolution optical and synthetic aperture radar (SAR) time series to identify ponds. Our novel approach entails: (1) making full use of ponds' characteristics from an object-based perspective; (2) extracting pond objects using seeds of prominent water pixels defined by the SAR VH signal; (3) constructing training samples of ponds with high representativeness; and (4) improving inter-class discrimination by combining features from optical and SAR data. We designed a novel Optical-SAR Pond Object Mapper (OptiSAR-POM) to achieve an improved estimate of pond size distribution by incorporating mapping strategies into the object-based image analysis framework. We generated landscape objects through an elaborate water-focused segmentation approach, which adaptively aligned the segmentation parameters with the size and distribution patterns of ponds to identify small waterbodies and increase inter-class variability. We further introduced an interactive learning process to construct random forests for object-based classification, which incorporated adaptive empirical thresholds to identify potential pond objects and select representative training samples of varying sizes. We tested the OptiSAR-POM framework using Sentinel-1/2 time series at three county-level study sites and three supplementary watershed-level study sites in the United States and China. Our approach yielded high overall accuracy (>95 %) for all sites and highlighted the ability of Sentinel-1/2 imagery to accurately detect small ponds (0.1–1 ha) across diverse landscapes. The average producer's accuracy for small ponds at county-level sites improved by ∼45 % compared to that of all other products with a 10-m or higher spatial resolution, addressing the absence of such information in existing regional and global datasets. The generated county-level pond maps revealed the numerical dominance of ponds in lentic waters, their substantial area contribution in human-impacted regions, and the relevance of studying biogeochemical processes in smaller waterbodies.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2024.114484","usgsCitation":"Liu, D., Zhu, X., Holgerson, M., Bansal, S., and Xu, X., 2024, Inventorying ponds through novel size-adaptive object mapping using Sentinel-1/2 time series: Remote Sensing of Environment, v. 315, 114484, 21 p., https://doi.org/10.1016/j.rse.2024.114484.","productDescription":"114484, 21 p.","ipdsId":"IP-167730","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":490911,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"315","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Liu, Denghong","contributorId":357052,"corporation":false,"usgs":false,"family":"Liu","given":"Denghong","affiliations":[{"id":37969,"text":"Hong Kong Polytechnic University","active":true,"usgs":false}],"preferred":false,"id":940631,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zhu, Xioalin","contributorId":357055,"corporation":false,"usgs":false,"family":"Zhu","given":"Xioalin","affiliations":[{"id":37969,"text":"Hong Kong Polytechnic University","active":true,"usgs":false}],"preferred":false,"id":940632,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Holgerson, Meredith","contributorId":218790,"corporation":false,"usgs":false,"family":"Holgerson","given":"Meredith","affiliations":[{"id":6929,"text":"Portland State University","active":true,"usgs":false}],"preferred":false,"id":940633,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bansal, Sheel 0000-0003-1233-1707 sbansal@usgs.gov","orcid":"https://orcid.org/0000-0003-1233-1707","contributorId":167295,"corporation":false,"usgs":true,"family":"Bansal","given":"Sheel","email":"sbansal@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":940634,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Xu, Xiangtao","contributorId":348758,"corporation":false,"usgs":false,"family":"Xu","given":"Xiangtao","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":940635,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70259581,"text":"fs20243029 - 2024 - Developments in African industrial minerals for renewable energy","interactions":[],"lastModifiedDate":"2024-10-30T21:16:35.700196","indexId":"fs20243029","displayToPublicDate":"2024-10-29T13:20:00","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2024-3029","displayTitle":"Developments in African Industrial Minerals for Renewable Energy","title":"Developments in African industrial minerals for renewable energy","docAbstract":"Africa is emerging as a leading source for minerals used in the manufacture of batteries for electric vehicles and in other renewable energy applications. New graphite, lithium, and rare-earth mines have or could be opened in African countries from 2017 through 2026.
Estimates of production capacities for graphite, lithium, and rare-earth mines for 2023 and beyond are based upon supply-side assumptions, such as announced plans for new capacity construction and bankable feasibility studies, as well as projected trends that could affect current producing facilities in 2023 and planned new facilities projected to come online by 2026. Forward-looking information, including estimates of future production capacities, graphite flake distributions, and timing of the start of operations, are subject to risk factors and uncertainties that could cause actual events or results to differ significantly from expected outcomes. Projects listed in this report are presented as an indication of industry plans and are not a U.S. Geological Survey (USGS) prediction of what will take place. Only projects with planned startup dates are included in this report; ther graphite, lithium, and rare-earth projects in Africa without startup dates were known to be in various stages of development but are not included in this fact sheet.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20243029","usgsCitation":"Yager, T., 2024, Developments in African industrial minerals for renewable energy: U.S. Geological Survey Fact Sheet 2024–3029, 6 p., https://doi.org/10.3133/fs20243029","productDescription":"6 p.","numberOfPages":"6","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-153789","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":463121,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/fs20243029/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"FS 2024-3029 HTML"},{"id":463122,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2024/3029/fs20243029.XML","description":"FS 2024-3029 XML"},{"id":463123,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2024/3029/images"},{"id":462885,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2024/3029/coverthb2.jpg"},{"id":462886,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2024/3029/fs20243029.pdf","text":"Report","size":"1.03 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2024-3029 PDF"}],"otherGeospatial":"Africa","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -23.381408491331456,\n 38.850454189324125\n ],\n [\n -23.381408491331456,\n -38.520184226294504\n ],\n [\n 53.96234150866863,\n -38.520184226294504\n ],\n [\n 53.96234150866863,\n 38.850454189324125\n ],\n [\n -23.381408491331456,\n 38.850454189324125\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"National Minerals Information Center
U.S. Geological Survey
988 National Center
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The U.S. Geological Survey is working with Federal land management agencies to develop a series of science syntheses to support environmental effects analyses that agencies conduct to comply with the National Environmental Policy Act (NEPA). This report synthesizes science information about the potential effects of noise from oil and gas development on North American raptors, songbirds, and other small avian species. We conducted a structured search of published scientific literature to find information about noise levels produced during oil and gas development, methods for analyzing sound propagation, the effects of noise on avian species, and measures to reduce noise emissions. We follow the organization first established in U.S. Geological Survey Scientific Investigations Report 2023-5114, in which the report sections align with standard elements of NEPA analyses. We found that oil and gas development is a common source of human-caused noise on public lands and includes noise sources such as heavy construction and drilling machinery, long-term production machinery, truck traffic, and aircraft. Common techniques for predicting potential noise include field data collection using a sound level meter, inference from previously published data, and sound propagation modeling. The effects of human-caused noise on songbirds are well researched, whereas, among raptors, only owl species have been well-studied in relation to noise. Several studies have established that noise can reduce owl hunting success because many owl species are heavily reliant on hearing prey when hunting. The effects of noise on songbirds depend on several factors. Typically, birds that rely on vocal communication for mating, predator detection, and spatial orientation, and that are less able to adjust the frequencies of their vocalizations, are more vulnerable to behavioral changes and decreased fitness in noisy areas. Techniques suggested in the literature for reducing noise emissions include artificial sound barriers, seasonal and daily timing restrictions, traffic control measures, and siting infrastructure to take advantage of natural sound barriers. Public land managers can use this report by incorporating it by reference in NEPA documentation, as supplemental information, or as a general reference to find literature or identify gaps in the literature about the effects of noise from oil and gas development on raptors and songbirds.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245087","programNote":"Prepared in cooperation with the Bureau of Land Management and the U.S. Fish and Wildlife Service","usgsCitation":"Maxwell, L.M., Rutherford, T.K., Kleist, N.J., Teige, E.C., Lehrter, R.J., Gilbert, M.A., Wood, D.J.A., Johnston, A.N., Tull, J.C., Haby, T.S., and Carter, S.K., 2024, Effects of noise from oil and gas development on raptors and songbirds—A science synthesis to inform National Environmental Policy Act analyses: U.S. Geological Survey Scientific Investigations Report 2024–5087, 66 p., https://doi.org/10.3133/sir20245087.","productDescription":"xi, 99 p.","onlineOnly":"Y","ipdsId":"IP-154746","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":463505,"rank":8,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20245087/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2024-5087"},{"id":463364,"rank":7,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2024/5087/sir20245087.xml"},{"id":463363,"rank":6,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2024/5087/images"},{"id":463212,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20235132","text":"Effects of Culverts on Habitat Connectivity in Streams—A Science Synthesis to Inform National Environmental Policy Act Analyses"},{"id":463211,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20235114","text":"Effects of Noise from Oil and Gas Development on Ungulates and Small Mammals—A Science Synthesis to Inform National Environmental Policy Act Analyses"},{"id":463210,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/fs20243028","text":"Structured Science Syntheses to Inform Decision Making on Federal Public Lands"},{"id":463209,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5087/sir20245087.pdf","text":"Report","size":"3.12 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2024-5087"},{"id":463208,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5087/coverthb.jpg"},{"id":497884,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117742.htm","linkFileType":{"id":5,"text":"html"}}],"contact":"Director, Fort Collins Science Center
U.S. Geological Survey
2150 Centre Ave., Bldg. C
Fort Collins, CO 80526-8118
We present 230Th-238U crystallization ages and trace element compositions for zircons spanning the late Pleistocene to Holocene rhyolite eruptive record at South Sister volcano in the central Oregon Cascade Range. Most zircon ages are between 100 and 20 ka, with very few in secular equilibrium (>350 ka). The weighted mean of zircon ages for the two oldest South Sister rhyolites, 31.5 ± 2.1 and 39.1 ± 2.4 ka, are significantly younger than the associated 40Ar/39Ar ages, 47.4 ± 9.7 and 51.4 ± 9.7 ka. We propose that these 40Ar/39Ar dates, performed on plagioclase separates, are compromised by a subtle amount of excess Ar and therefore the younger weighted mean zircon ages yield more reliable eruption ages. These results imply that the interval of rhyolite eruption at South Sister during the late Pleistocene was both shorter and more productive than previously thought and that eruption at South Sister initiated after Middle Sister. Compositionally, zircons from the Pleistocene rhyolites are broadly similar and show down-temperature zircon and plagioclase crystallization trends. However, we argue that destabilized amphibole and titanite in a common mush also exert leverage on the Pleistocene zircon trace element compositions. Divergence in the Eu/Eu* ratio between the Pleistocene and Holocene lavas implies chemically distinct magma reservoirs originating from the Pleistocene rhyolite eruptive sequence and the Holocene eruptive sequence. This work suggests a higher flux of rhyolite volcanism than previously thought and characterizes magmatic storage distinctions between the Pleistocene and Holocene rhyolites, aiding in the assessment of future eruptive hazards at South Sister volcano.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2024GC011680","usgsCitation":"Dechert, A.E., Andersen, N.L., Dufek, J., and Jilly-Rehak, C.E., 2024, Zircon constraints on the eruptive sequence and magma evolution of rhyolites at South Sister volcano, Oregon: Geochemistry, Geophysics, Geosystems, v. 25, no. 8, e2024GC011680, 16 p., https://doi.org/10.1029/2024GC011680.","productDescription":"e2024GC011680, 16 p.","ipdsId":"IP-166341","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":466802,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2024gc011680","text":"Publisher Index Page"},{"id":463333,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"South Sister Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.4687761419247,\n 44.8843098669841\n ],\n [\n -122.4687761419247,\n 43.77976481541276\n ],\n [\n -120.91024228397475,\n 43.77976481541276\n ],\n [\n -120.91024228397475,\n 44.8843098669841\n ],\n [\n -122.4687761419247,\n 44.8843098669841\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"25","issue":"8","noUsgsAuthors":false,"publicationDate":"2024-08-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Dechert, Annika E.","contributorId":345692,"corporation":false,"usgs":false,"family":"Dechert","given":"Annika","email":"","middleInitial":"E.","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":917269,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Andersen, Nathan Lee 0000-0002-4152-4914","orcid":"https://orcid.org/0000-0002-4152-4914","contributorId":345693,"corporation":false,"usgs":true,"family":"Andersen","given":"Nathan","email":"","middleInitial":"Lee","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":917270,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dufek, Josef","contributorId":194001,"corporation":false,"usgs":false,"family":"Dufek","given":"Josef","email":"","affiliations":[],"preferred":false,"id":917271,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jilly-Rehak, Christine E.","contributorId":344651,"corporation":false,"usgs":false,"family":"Jilly-Rehak","given":"Christine","email":"","middleInitial":"E.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":917272,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70260828,"text":"70260828 - 2024 - Adaptable plasmonic membrane sensors for fast and reliable detection of trace low micrometer microplastics in lake water","interactions":[],"lastModifiedDate":"2024-11-12T15:09:09.782218","indexId":"70260828","displayToPublicDate":"2024-10-29T09:05:58","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5925,"text":"Environmental Science and Technology","active":true,"publicationSubtype":{"id":10}},"title":"Adaptable plasmonic membrane sensors for fast and reliable detection of trace low micrometer microplastics in lake water","docAbstract":"In freshwater environments, low-micrometer microplastics (LMMPs) have captured significant attention due to their prevalence and toxicity. Yet, rapid detection of LMMPs (1–10 μm) at the single-particle level within complex freshwater matrices remains a hurdle. We developed an adaptable plasmonic membrane sensor for fast detection of individual LMMPs in eutrophic lake waters. The plasmonic membrane sensor functions both as a membrane filter and as a sensor for LMMP collection and analysis. Among the four types of membrane sensors, polycarbonate track-etch (PCTE) membrane sensors exhibit superior imaging quality for LMMPs due to their flat and homogeneous surfaces. Besides the significantly improved imaging contrast and reduced background interferences, the Raman intensity of LMMPs is enhanced by 48% ± 25% on PCTE membrane sensors compared to unmodified membranes. The increased Raman intensities of a chemical probe with an increasing gold layer thickness and a decreasing membrane pore size suggest a surface-enhanced Raman scattering effect from the membrane sensors. The membrane sensors achieve a detection limit of 1 μg/L and an ultrafast scanning time of 0.01 s for individual LMMPs across natural eutrophic lake water. The developed membrane sensors offer an adaptable tool for the swift and reliable detection of individual LMMPs in complex environmental matrices.
","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.est.4c06503","usgsCitation":"Wu, Z., Janssen, S., Tate, M., Wei, H., and Qin, M., 2024, Adaptable plasmonic membrane sensors for fast and reliable detection of trace low micrometer microplastics in lake water: Environmental Science and Technology, v. 58, no. 45, p. 20172-20180, https://doi.org/10.1021/acs.est.4c06503.","productDescription":"9 p.","startPage":"20172","endPage":"20180","ipdsId":"IP-171215","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":466803,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1021/acs.est.4c06503","text":"Publisher Index Page"},{"id":463868,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"58","issue":"45","noUsgsAuthors":false,"publicationDate":"2024-10-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Wu, Ziyan","contributorId":346132,"corporation":false,"usgs":false,"family":"Wu","given":"Ziyan","email":"","affiliations":[{"id":16925,"text":"University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":918229,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Janssen, Sarah E. 0000-0003-4432-3154","orcid":"https://orcid.org/0000-0003-4432-3154","contributorId":210991,"corporation":false,"usgs":true,"family":"Janssen","given":"Sarah E.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":918230,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tate, Michael T. 0000-0003-1525-1219 mttate@usgs.gov","orcid":"https://orcid.org/0000-0003-1525-1219","contributorId":3144,"corporation":false,"usgs":true,"family":"Tate","given":"Michael T.","email":"mttate@usgs.gov","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":918231,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wei, Hoaran","contributorId":346133,"corporation":false,"usgs":false,"family":"Wei","given":"Hoaran","email":"","affiliations":[{"id":16925,"text":"University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":918232,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Qin, Mohan","contributorId":346134,"corporation":false,"usgs":false,"family":"Qin","given":"Mohan","email":"","affiliations":[{"id":16925,"text":"University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":918233,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70260429,"text":"70260429 - 2024 - Dynamics, monitoring and forecasting of tephra in the atmosphere","interactions":[],"lastModifiedDate":"2024-11-01T13:54:00.975813","indexId":"70260429","displayToPublicDate":"2024-10-29T08:52:42","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3283,"text":"Reviews of Geophysics","active":true,"publicationSubtype":{"id":10}},"title":"Dynamics, monitoring and forecasting of tephra in the atmosphere","docAbstract":"Explosive volcanic eruptions inject hot mixtures of solid particles (tephra) and gasses into the atmosphere. Entraining ambient air, these mixtures can form plumes rising tens of kilometers until they spread laterally, forming umbrella clouds. While the largest clasts tend to settle in proximity to the volcano, the smallest fragments, commonly referred to as ash (≤2 mm in diameter), can be transported over long distances, forming volcanic clouds. Tephra plumes and clouds pose significant hazards to human society, affecting infrastructure, and human health through deposition on the ground or airborne suspension at low altitudes. Additionally, volcanic clouds are a threat to aviation, during both high-risk actions such as take-off and landing and at standard cruising altitudes. The ability to monitor and forecast tephra plumes and clouds is fundamental to mitigate the hazard associated with explosive eruptions. To that end, various monitoring techniques, ranging from ground-based instruments to sensors on-board satellites, and forecasting strategies, based on running numerical models to track the position of volcanic clouds, are efficiently employed. However, some limitations still exist, mainly due to the high unpredictability and variability of explosive eruptions, as well as the multiphase and complex nature of volcanic plumes. In the next decades, advances in monitoring and computational capabilities are expected to address these limitations and significantly improve the mitigation of the risk associated with tephra plumes and clouds.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2023RG000808","usgsCitation":"Pardini, F., Barsotti, S., Bonadonna, C., de’ Michieli Vitturi, M., Folch, A., Mastin, L.G., Osores, S., and Prata, A.T., 2024, Dynamics, monitoring and forecasting of tephra in the atmosphere: Reviews of Geophysics, v. 62, e2023RG000808, 68 p., https://doi.org/10.1029/2023RG000808.","productDescription":"e2023RG000808, 68 p.","ipdsId":"IP-160162","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":466804,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2023rg000808","text":"Publisher Index Page"},{"id":463533,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"62","noUsgsAuthors":false,"publicationDate":"2024-10-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Pardini, Federica","contributorId":345831,"corporation":false,"usgs":false,"family":"Pardini","given":"Federica","email":"","affiliations":[{"id":82720,"text":"Istituto Nazionale di Geofisica e Vulcanologia (INGV), Sezione di Pisa, Pisa, Italy","active":true,"usgs":false}],"preferred":false,"id":917656,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barsotti, Sara","contributorId":199711,"corporation":false,"usgs":false,"family":"Barsotti","given":"Sara","email":"","affiliations":[],"preferred":false,"id":917657,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bonadonna, Contanza 0000-0002-2368-2193","orcid":"https://orcid.org/0000-0002-2368-2193","contributorId":339895,"corporation":false,"usgs":false,"family":"Bonadonna","given":"Contanza","email":"","affiliations":[{"id":62805,"text":"Université de Genève","active":true,"usgs":false}],"preferred":false,"id":917658,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"de’ Michieli Vitturi, Mattia","contributorId":199708,"corporation":false,"usgs":false,"family":"de’ Michieli Vitturi","given":"Mattia","email":"","affiliations":[],"preferred":false,"id":917659,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Folch, Arnau","contributorId":199712,"corporation":false,"usgs":false,"family":"Folch","given":"Arnau","email":"","affiliations":[],"preferred":false,"id":917660,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mastin, Larry G. 0000-0002-4795-1992","orcid":"https://orcid.org/0000-0002-4795-1992","contributorId":265985,"corporation":false,"usgs":true,"family":"Mastin","given":"Larry","email":"","middleInitial":"G.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":917661,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Osores, Soledad 0009-0002-3352-9245","orcid":"https://orcid.org/0009-0002-3352-9245","contributorId":345832,"corporation":false,"usgs":false,"family":"Osores","given":"Soledad","email":"","affiliations":[{"id":82723,"text":"Servicio Meteorológico Nacional, Buenos Aires, Argentina","active":true,"usgs":false}],"preferred":false,"id":917662,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Prata, Andrew T. 0000-0001-9115-1143","orcid":"https://orcid.org/0000-0001-9115-1143","contributorId":345833,"corporation":false,"usgs":false,"family":"Prata","given":"Andrew","email":"","middleInitial":"T.","affiliations":[{"id":40928,"text":"Oxford University","active":true,"usgs":false}],"preferred":false,"id":917663,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70264867,"text":"70264867 - 2024 - Evaluating the impact of uncertainty in ground motion forecasts for post-earthquake impact modeling applications","interactions":[],"lastModifiedDate":"2025-03-26T15:38:39.371491","indexId":"70264867","displayToPublicDate":"2024-10-29T08:30:48","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7565,"text":"Earthquake Spectra Journal","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating the impact of uncertainty in ground motion forecasts for post-earthquake impact modeling applications","docAbstract":"The US Geological Survey’s (USGS) ShakeMap system provides a rapid characterization of strong ground shaking in areas directly affected by an earthquake. This study focuses on studying the aggregate effects of macroseismic shaking estimates from ShakeMap, expressed in terms of modified Mercalli intensity (MMI), when accounting for the uncertainty in forecasted ground motions. We use a Monte Carlo approach to generate numerous spatially correlated realizations of ground motions by utilizing a combination of circulant embedding and kriging techniques for efficiently handling the correlations. We then assessed the aggregate effects of shaking by looking at bin counts across these realizations. We demonstrate that the aggregate shaking regarding the mean macroseismic intensity estimates (from the ShakeMap output) is a biased representation of the aggregate shaking when shaking uncertainty is included. Incorporating shaking uncertainty can help to improve various downstream earthquake impact applications, such as the USGS Prompt Assessment of Global Earthquakes for Response (PAGER) overall earthquake fatality distribution or estimates of shaking-induced ground failure impacts from consequential earthquakes.
","language":"English","publisher":"Sage Publishing","doi":"10.1177/87552930241283201","usgsCitation":"Engler, D.T., Jaiswal, K.S., and Ganesh, M., 2024, Evaluating the impact of uncertainty in ground motion forecasts for post-earthquake impact modeling applications: Earthquake Spectra Journal, v. 41, no. 1, p. 524-546, https://doi.org/10.1177/87552930241283201.","productDescription":"23 p.","startPage":"524","endPage":"546","ipdsId":"IP-160589","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":483880,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"41","issue":"1","noUsgsAuthors":false,"publicationDate":"2024-10-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Engler, Davis T. 0000-0002-7133-3545","orcid":"https://orcid.org/0000-0002-7133-3545","contributorId":265962,"corporation":false,"usgs":true,"family":"Engler","given":"Davis","email":"","middleInitial":"T.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":932100,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jaiswal, Kishor S. 0000-0002-5803-8007 kjaiswal@usgs.gov","orcid":"https://orcid.org/0000-0002-5803-8007","contributorId":149796,"corporation":false,"usgs":true,"family":"Jaiswal","given":"Kishor","email":"kjaiswal@usgs.gov","middleInitial":"S.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":932101,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ganesh, Mahadevan 0000-0002-7792-4119","orcid":"https://orcid.org/0000-0002-7792-4119","contributorId":352717,"corporation":false,"usgs":false,"family":"Ganesh","given":"Mahadevan","affiliations":[{"id":84292,"text":"Professor, Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":932102,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70260375,"text":"70260375 - 2024 - Population structure of Desmophyllum pertusum found along the United States eastern continental margin","interactions":[],"lastModifiedDate":"2024-11-01T14:13:20.307568","indexId":"70260375","displayToPublicDate":"2024-10-29T08:29:55","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":958,"text":"BMC Research Notes","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Population structure of Desmophyllum pertusum found along the United States eastern continental margin","title":"Population structure of Desmophyllum pertusum found along the United States eastern continental margin","docAbstract":"The connectivity and genetic structuring of populations throughout a region influence a species’ resilience and probability of recovery from anthropogenic impacts. By gaining a comprehensive understanding of population connectivity, more effective management can be prioritized. To assess the connectivity and population genetic structure of a common cold-water coral species, Desmophyllum pertusum (Lophelia pertusa), we performed Restriction-site Associated DNA Sequencing (RADseq) on individuals from nine sites ranging from submarine canyons off New England to the southeastern coast of the United States (SEUS) and the Gulf of Mexico (GOM). Fifty-seven individuals and 3,180 single-nucleotide polymorphisms (SNPs) were used to assess genetic differentiation.
High connectivity exists among populations along the SEUS, yet these populations were differentiated from those to the north off New England and in Norfolk Canyon along the North Atlantic coast of the United States, as well as those in the GOM. Interestingly, Norfolk Canyon, located just north of North Carolina, and GOM populations exhibited low levels of genetic differentiation, corroborating previous microsatellite analyses and signifying gene flow between these populations. Increasing sample sizes from existing populations and including additional sampling sites over a larger geographic range would help define potential source populations and reveal fine-scale connectivity patterns among D. pertusum populations.
","language":"English","publisher":"Springer Nature","doi":"10.1186/s13104-024-06977-4","usgsCitation":"Weinnig, A.M., Aunins, A.W., Salamone, V.J., Quattrini, A., Nizinski, M.S., and Morrison, C., 2024, Population structure of Desmophyllum pertusum found along the United States eastern continental margin: BMC Research Notes, v. 17, no. 1, 326, 7 p., https://doi.org/10.1186/s13104-024-06977-4.","productDescription":"326, 7 p.","ipdsId":"IP-157145","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":466805,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s13104-024-06977-4","text":"Publisher Index Page"},{"id":463535,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Unites States","otherGeospatial":"Atlantic coastal margin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -85.71142930127395,\n 28.923532210772052\n ],\n [\n -87.20770794927337,\n 29.778273658658676\n ],\n [\n -88.12002541768051,\n 29.69258193898787\n ],\n [\n -89.23879681191622,\n 28.44134714528691\n ],\n [\n -86.44254662826377,\n 27.912389547448754\n ],\n [\n -85.71142930127395,\n 28.923532210772052\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -64.9239384814065,\n 42.20254040148441\n ],\n [\n -67.63438293096546,\n 43.58902192305143\n ],\n [\n -69.21544486232233,\n 42.68212319523596\n ],\n [\n -69.57393034494278,\n 40.17025194363276\n ],\n [\n -73.58827669330255,\n 38.91808684375454\n ],\n [\n -74.60625646365936,\n 36.588016013722694\n ],\n [\n -75.5834673460983,\n 34.46068678372583\n ],\n [\n -79.47920624257769,\n 31.99090849493018\n ],\n [\n -80.4000384261637,\n 31.00478268172816\n ],\n [\n -79.478750607929,\n 26.481859079129094\n ],\n [\n -63.15489504288122,\n 42.1372460985159\n ],\n [\n -64.9239384814065,\n 42.20254040148441\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"17","issue":"1","noUsgsAuthors":false,"publicationDate":"2024-10-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Weinnig, Alexis Marie 0000-0001-8858-4837","orcid":"https://orcid.org/0000-0001-8858-4837","contributorId":331476,"corporation":false,"usgs":true,"family":"Weinnig","given":"Alexis","email":"","middleInitial":"Marie","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":917476,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aunins, Aaron 0000-0001-5240-1453 aaunins@usgs.gov","orcid":"https://orcid.org/0000-0001-5240-1453","contributorId":5863,"corporation":false,"usgs":true,"family":"Aunins","given":"Aaron","email":"aaunins@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":917477,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Salamone, Veronica J. 0000-0002-6274-6401","orcid":"https://orcid.org/0000-0002-6274-6401","contributorId":293174,"corporation":false,"usgs":true,"family":"Salamone","given":"Veronica","email":"","middleInitial":"J.","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":917478,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Quattrini, Andrea M.","contributorId":333886,"corporation":false,"usgs":false,"family":"Quattrini","given":"Andrea M.","affiliations":[{"id":80003,"text":"Department of Invertebrate Zoology, Smithsonian Institution, Washington DC, United States of America","active":true,"usgs":false}],"preferred":false,"id":917479,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nizinski, Martha S.","contributorId":174770,"corporation":false,"usgs":false,"family":"Nizinski","given":"Martha","email":"","middleInitial":"S.","affiliations":[{"id":27510,"text":"NMFS National Systematics Laboratory, Smithsonian Institution","active":true,"usgs":false}],"preferred":false,"id":917480,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Morrison, Cheryl 0000-0001-9425-691X cmorrison@usgs.gov","orcid":"https://orcid.org/0000-0001-9425-691X","contributorId":202644,"corporation":false,"usgs":true,"family":"Morrison","given":"Cheryl","email":"cmorrison@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":917481,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70267297,"text":"70267297 - 2024 - The influence of grazing on the spatiotemporal activity patterns of a primary sage-grouse nest predator","interactions":[],"lastModifiedDate":"2025-05-20T16:19:44.225742","indexId":"70267297","displayToPublicDate":"2024-10-29T00:00:00","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3228,"text":"Rangeland Ecology and Management","onlineIssn":"1551-5028","printIssn":"1550-7424","active":true,"publicationSubtype":{"id":10}},"title":"The influence of grazing on the spatiotemporal activity patterns of a primary sage-grouse nest predator","docAbstract":"Perturbations in ecological processes can occur when wildlife alter their spatiotemporal activity patterns to avoid human activities that they perceive as a risk. Such perturbations can have cascading effects throughout wildlife communities. For greater sage-grouse (Centrocercus urophasianus; hereafter sage-grouse), nest predation plays an important role in population dynamics. Domestic cattle (Bos taurus) grazing has been hypothesized to increase nest predation by reducing grass height, and therefore reducing nest concealment, which may facilitate nest detection by predators. Grass height is lower on grazed pastures, but sage-grouse nest success appears similar on pastures grazed at varying intensities in several recent studies. Any reductions in nest concealment caused by grazing could potentially be offset by a localized response of one or more nest predators to the presence of cattle (i.e., the cattle avoidance hypothesis). A reduction in nest predator density or relative use within pastures could explain similar patterns of nest success on pastures grazed at varying intensities. Also, wildlife can potentially partition themselves temporally to avoid risks associated with human activities. For example, a shift in diel activity patterns by nest predators in response to cattle could result in predators being active during portions of the day when they are less efficient at locating sage-grouse nests. Thus, the effects of grazing could be offset by a temporal avoidance of cattle by predators. We deployed motion sensor cameras across six pastures to evaluate whether coyotes (Canis latrans; a primary sage-grouse nest predator) altered spatiotemporal activity patterns in response to cattle. We found that the probability of detecting coyotes had a positive relationship with cattle detections at camera sites (β = 0.22; 95% CI = 0.14,0.30). We also found that coyotes did not shift their diel activity patterns in response to cattle being in the pastures. Thus, in our system, similar sage-grouse nest success among pastures with different grazing intensities cannot be explained by the cattle avoidance hypothesis, at least for coyotes.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.rama.2024.08.012","usgsCitation":"Helmstetter, N., Conway, C.J., Roberts, S., Makela, P., and Waits, L., 2024, The influence of grazing on the spatiotemporal activity patterns of a primary sage-grouse nest predator: Rangeland Ecology and Management, v. 98, p. 316-323, https://doi.org/10.1016/j.rama.2024.08.012.","productDescription":"8 p.","startPage":"316","endPage":"323","ipdsId":"IP-158843","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":486230,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"Big Butte, Pahsimeroi Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -114.07468470534926,\n 44.658252472114754\n ],\n [\n -114.07468470534926,\n 43.66884810770594\n ],\n [\n -112.78891524952729,\n 43.66884810770594\n ],\n [\n -112.78891524952729,\n 44.658252472114754\n ],\n [\n -114.07468470534926,\n 44.658252472114754\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"98","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Helmstetter, Nolan A.","contributorId":355566,"corporation":false,"usgs":false,"family":"Helmstetter","given":"Nolan A.","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":937659,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conway, Courtney J. 0000-0003-0492-2953 cconway@usgs.gov","orcid":"https://orcid.org/0000-0003-0492-2953","contributorId":2951,"corporation":false,"usgs":true,"family":"Conway","given":"Courtney","email":"cconway@usgs.gov","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":937660,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Roberts, Shane","contributorId":355567,"corporation":false,"usgs":false,"family":"Roberts","given":"Shane","affiliations":[{"id":36224,"text":"Idaho Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":937661,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Makela, Paul D.","contributorId":355569,"corporation":false,"usgs":false,"family":"Makela","given":"Paul D.","affiliations":[{"id":84780,"text":"United States Department of Interior","active":true,"usgs":false}],"preferred":false,"id":937663,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Waits, Lisette P.","contributorId":355568,"corporation":false,"usgs":false,"family":"Waits","given":"Lisette P.","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":937662,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70260112,"text":"70260112 - 2024 - The projected exposure and response of a natural barrier island system to climate-driven coastal hazards","interactions":[],"lastModifiedDate":"2024-10-30T21:25:08.166742","indexId":"70260112","displayToPublicDate":"2024-10-28T10:09:48","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"The projected exposure and response of a natural barrier island system to climate-driven coastal hazards","docAbstract":"Accelerating sea level rise (SLR) and changing storm patterns will increasingly expose barrier islands to coastal hazards, including flooding, erosion, and rising groundwater tables. We assess the exposure of Cape Lookout National Seashore, a barrier island system in North Carolina (USA), to projected SLR and storm hazards over the twenty-first century. We estimate that with 0.5 m of SLR, 47% of current subaerial barrier island area would be flooded daily, and the 1-year return period storm would flood 74%. For 20-year return period storms, over 85% is projected to be flooded for any SLR. The modelled groundwater table is already shallow (< 2 m deep), and while projected to shoal to the land surface with SLR, marine flooding is projected to overtake areas with emergent groundwater. Projected shoreline retreat reaches an average of 178 m with 1 m of SLR and no interventions, which is over 60% of the current island width at narrower locations. Compounding these hazards is subsidence, with one-third of the study area currently lowering at > 2 mm/yr. Our results demonstrate the difficulty of managing natural barrier systems such as those managed by federal park systems tasked with maintaining natural ecosystems and protecting cultural resources.
","language":"English","publisher":"Nature","doi":"10.1038/s41598-024-76749-4","usgsCitation":"Thomas, J.A., Barnard, P.L., Vitousek, S., Erikson, L.H., Parker, K.A., Nederhoff, K., Befus, K.M., and Shirzaei, M., 2024, The projected exposure and response of a natural barrier island system to climate-driven coastal hazards: Scientific Reports, v. 14, 25814, 16 p., https://doi.org/10.1038/s41598-024-76749-4.","productDescription":"25814, 16 p.","ipdsId":"IP-159766","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":466806,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-024-76749-4","text":"Publisher Index Page"},{"id":463350,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina","otherGeospatial":"Cape Lookout National Seashore","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -76.00044575785073,\n 35.04289907218657\n ],\n [\n -76.06277684124831,\n 35.10241453299423\n ],\n [\n -76.46792888333269,\n 34.74467160307489\n ],\n [\n -76.53025996672974,\n 34.6678097189927\n ],\n [\n -76.6705049043746,\n 34.7105195823093\n ],\n [\n -76.69128193217362,\n 34.637899706102985\n ],\n [\n -76.4939001680816,\n 34.55666100513659\n ],\n [\n -76.00044575785073,\n 35.04289907218657\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"14","noUsgsAuthors":false,"publicationDate":"2024-10-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Thomas, Jennifer Anne 0000-0002-8338-0146","orcid":"https://orcid.org/0000-0002-8338-0146","contributorId":297988,"corporation":false,"usgs":true,"family":"Thomas","given":"Jennifer","email":"","middleInitial":"Anne","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":917041,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barnard, Patrick L. 0000-0003-1414-6476 pbarnard@usgs.gov","orcid":"https://orcid.org/0000-0003-1414-6476","contributorId":140982,"corporation":false,"usgs":true,"family":"Barnard","given":"Patrick","email":"pbarnard@usgs.gov","middleInitial":"L.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":917042,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vitousek, Sean 0000-0002-3369-4673 svitousek@usgs.gov","orcid":"https://orcid.org/0000-0002-3369-4673","contributorId":149065,"corporation":false,"usgs":true,"family":"Vitousek","given":"Sean","email":"svitousek@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":917047,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Erikson, Li H. 0000-0002-8607-7695 lerikson@usgs.gov","orcid":"https://orcid.org/0000-0002-8607-7695","contributorId":149963,"corporation":false,"usgs":true,"family":"Erikson","given":"Li","email":"lerikson@usgs.gov","middleInitial":"H.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":917043,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Parker, Kai Alexander 0000-0002-0268-3891","orcid":"https://orcid.org/0000-0002-0268-3891","contributorId":292869,"corporation":false,"usgs":true,"family":"Parker","given":"Kai","email":"","middleInitial":"Alexander","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":917044,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nederhoff, Kees 0000-0003-0552-3428","orcid":"https://orcid.org/0000-0003-0552-3428","contributorId":334091,"corporation":false,"usgs":false,"family":"Nederhoff","given":"Kees","affiliations":[{"id":39963,"text":"Deltares-USA","active":true,"usgs":false}],"preferred":true,"id":917045,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Befus, Kevin M.","contributorId":242636,"corporation":false,"usgs":false,"family":"Befus","given":"Kevin","email":"","middleInitial":"M.","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":917046,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Shirzaei, Manoochehr 0000-0003-0086-3722","orcid":"https://orcid.org/0000-0003-0086-3722","contributorId":245637,"corporation":false,"usgs":false,"family":"Shirzaei","given":"Manoochehr","email":"","affiliations":[{"id":49242,"text":"Dept. of Geosciences, Virginia Tech Univ.","active":true,"usgs":false}],"preferred":false,"id":917048,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70263169,"text":"70263169 - 2024 - Multi-decadal trophic shifts in Lake Erie yellow perch Perca flavescens","interactions":[],"lastModifiedDate":"2025-01-30T16:14:56.157932","indexId":"70263169","displayToPublicDate":"2024-10-28T10:08:06","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Multi-decadal trophic shifts in Lake Erie yellow perch Perca flavescens","title":"Multi-decadal trophic shifts in Lake Erie yellow perch Perca flavescens","docAbstract":"In Lake Erie, yellow perch Perca flavescens support vast commercial and recreational fisheries, yet populations have recently declined. Using N = 5889 yellow perch stomachs collected from 1997 to 2021, we explored trends in the feeding ecology and trophic level of yellow perch with generalized additive models. Models revealed a significant decrease in yellow perch trophic level (−0.15 trophic levels in the last decade), and significant dietary shifts. Yellow perch have shifted away from feeding on piscine prey and round goby Neogobius melanostomus over the 25-year period, and now feed on invertebrates more frequently—including invasive waterfleas (Bythotrephes longimanus and Cercopagis pengoi) and chironomids. Dietary patterns appear to reflect broad ecological changes—invasive waterfleas have proliferated while populations of forage fish and round goby have declined. Furthermore, hypoxia events have increased in duration and severity, which may explain observed increases in chironomid consumption, which are hypoxia tolerant. This study demonstrates trophic adaptability in yellow perch, which have changed feeding behavior and trophic position in response to novel invaders and changing environmental conditions.
","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2023-0348","usgsCitation":"Schmitt, J., Gorman, A., Knight, C., Dufour, M.R., Roberts, J., and Hartman, T., 2024, Multi-decadal trophic shifts in Lake Erie yellow perch Perca flavescens: Canadian Journal of Fisheries and Aquatic Sciences, v. 81, no. 11, p. 1560-1580, https://doi.org/10.1139/cjfas-2023-0348.","productDescription":"21 p.","startPage":"1560","endPage":"1580","ipdsId":"IP-140880","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":489855,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1139/cjfas-2023-0348","text":"Publisher Index Page"},{"id":481508,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Lake Erie","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -80.56325919457086,\n 41.96883002032561\n ],\n [\n -80.71352325852209,\n 42.13778067147925\n ],\n [\n -81.1801985471471,\n 42.12256709658425\n ],\n [\n -82.40972750390958,\n 41.63184115572025\n ],\n [\n -82.53711113456517,\n 41.3996082733955\n ],\n [\n -82.45403485370326,\n 41.382988331945285\n ],\n [\n -82.0829607991845,\n 41.49923867953902\n ],\n [\n -81.86223827452686,\n 41.48020592339866\n ],\n [\n -81.73401076664092,\n 41.482825773508495\n ],\n [\n -81.3851200399411,\n 41.68976914941442\n ],\n [\n -80.56325919457086,\n 41.96883002032561\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"81","issue":"11","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Schmitt, Joseph 0000-0002-8354-4067","orcid":"https://orcid.org/0000-0002-8354-4067","contributorId":221020,"corporation":false,"usgs":true,"family":"Schmitt","given":"Joseph","email":"","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":925739,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gorman, Ann Marie","contributorId":350334,"corporation":false,"usgs":false,"family":"Gorman","given":"Ann Marie","affiliations":[],"preferred":false,"id":925740,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Knight, Carey","contributorId":214230,"corporation":false,"usgs":false,"family":"Knight","given":"Carey","affiliations":[{"id":16232,"text":"Ohio Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":925741,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dufour, Mark Richard 0000-0001-6930-7666","orcid":"https://orcid.org/0000-0001-6930-7666","contributorId":291450,"corporation":false,"usgs":true,"family":"Dufour","given":"Mark","email":"","middleInitial":"Richard","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":925742,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Roberts, James J. 0000-0002-4193-610X jroberts@usgs.gov","orcid":"https://orcid.org/0000-0002-4193-610X","contributorId":5453,"corporation":false,"usgs":true,"family":"Roberts","given":"James","email":"jroberts@usgs.gov","middleInitial":"J.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":925743,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hartman, Travis","contributorId":220316,"corporation":false,"usgs":false,"family":"Hartman","given":"Travis","email":"","affiliations":[{"id":37332,"text":"Ohio Department of Natural Resources, Division of Wildlife","active":true,"usgs":false}],"preferred":false,"id":925744,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70266311,"text":"70266311 - 2024 - Predator-specific mortality of sage-grouse nests based on predator DNA on eggshells","interactions":[],"lastModifiedDate":"2025-05-05T14:44:40.283853","indexId":"70266311","displayToPublicDate":"2024-10-28T09:41:24","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Predator-specific mortality of sage-grouse nests based on predator DNA on eggshells","docAbstract":"Greater sage-grouse (hereafter sage-grouse; Centrocercus urophasianus) populations have declined across their range. Increased nest predation as a result of anthropogenic land use is one mechanism proposed to explain these declines. However, sage-grouse contend with a diverse suite of nest predators that vary in functional traits (e.g., search tactics or hunting mode) and abundance. Consequently, generalizing about factors influencing nest fate is challenging. Identifying the explicit predator species responsible for nest predation events is, therefore, critical to understanding causal mechanisms linking land use to patterns of sage-grouse nest success. Cattle grazing is often assumed to adversely affect sage-grouse recruitment by reducing grass height (and hence cover), thereby facilitating nest detection by predators. However, recent evidence found little support for the hypothesized effect of grazing on nest fate at the pasture scale. Rather, nest success appears to be similar on pastures grazed at varying intensities. One possible explanation for the lack of observed effect involves a localized response by one or more nest predators. The presence of cattle may cause a temporary reduction in predator density and/or use within a pasture (the cattle avoidance hypothesis). The cattle avoidance hypothesis predicts a decreased probability of at least one sage-grouse nest predator predating sage-grouse nests in pastures with livestock relative to pastures without livestock present during the nesting season. To test the cattle avoidance hypothesis, we collected predator DNA from eggshells from predated nests and used genetic methods to identify the sage-grouse nest predator(s) responsible for the predation event. We evaluated the influence of habitat and grazing on predator-specific nest predation. We evaluated the efficacy of our genetic method by deploying artificial nests with trail cameras and compared the results of our genetic method to the species captured via trail camera. Our molecular methods identified at least one nest predator captured predating artificial nests via trail camera for 33 of 35 (94%) artificial nests. We detected nest predators via our molecular analysis at 76 of 114 (67%) predated sage-grouse nests. The primary predators detected at sage-grouse nests were coyotes (Canis latrans) and corvids (Corvidea). Grazing did not influence the probability of nest predation by either coyotes or corvids. Sagebrush canopy cover was negatively associated with the probability a coyote predated a nest, distance to water was positively associated with the probability a corvid predated a nest, and average minimum temperature was negatively associated with the probability that either a coyote or a corvid predated a nest. Our study provides a framework for implementing an effective, non-invasive method for identifying sage-grouse nest predators that can be used to better understand how management actions at local and regional scales may impact an important component of sage-grouse recruitment.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.70213","usgsCitation":"Helmstetter, N.A., Conway, C.J., Roberts, S., Adams, J., Makela, P., and Waits, L., 2024, Predator-specific mortality of sage-grouse nests based on predator DNA on eggshells: Ecology and Evolution, v. 14, no. 10, e70213, 19 p., https://doi.org/10.1002/ece3.70213.","productDescription":"e70213, 19 p.","ipdsId":"IP-166147","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":487947,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.70213","text":"Publisher Index Page"},{"id":485377,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -112.84878592693147,\n 44.720752546676636\n ],\n [\n -116.22953206733101,\n 44.720752546676636\n ],\n [\n -116.22953206733101,\n 41.995370325478774\n ],\n [\n -112.84878592693147,\n 41.995370325478774\n ],\n [\n -112.84878592693147,\n 44.720752546676636\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"14","issue":"10","noUsgsAuthors":false,"publicationDate":"2024-10-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Helmstetter, Nolan A.","contributorId":287004,"corporation":false,"usgs":false,"family":"Helmstetter","given":"Nolan","email":"","middleInitial":"A.","affiliations":[{"id":39599,"text":"ui","active":true,"usgs":false}],"preferred":false,"id":935533,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conway, Courtney J. 0000-0003-0492-2953 cconway@usgs.gov","orcid":"https://orcid.org/0000-0003-0492-2953","contributorId":2951,"corporation":false,"usgs":true,"family":"Conway","given":"Courtney","email":"cconway@usgs.gov","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":935534,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Roberts, Shane","contributorId":279606,"corporation":false,"usgs":false,"family":"Roberts","given":"Shane","affiliations":[{"id":56023,"text":"idfg","active":true,"usgs":false}],"preferred":false,"id":935535,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Adams, Jennifer R.","contributorId":341225,"corporation":false,"usgs":false,"family":"Adams","given":"Jennifer R.","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":935536,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Makela, Paul D.","contributorId":354380,"corporation":false,"usgs":false,"family":"Makela","given":"Paul D.","affiliations":[{"id":37086,"text":"U.S. Bureau of Land Management","active":true,"usgs":false}],"preferred":false,"id":935537,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Waits, Lisette P.","contributorId":338452,"corporation":false,"usgs":false,"family":"Waits","given":"Lisette P.","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":935538,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70260180,"text":"70260180 - 2024 - Tissue distribution and temporal and spatial assessment of per- and polyfluoroalkyl substances (PFAS) in smallmouth bass (Micropterus dolomieu) in the mid-Atlantic United States","interactions":[],"lastModifiedDate":"2024-10-30T13:35:44.534951","indexId":"70260180","displayToPublicDate":"2024-10-28T08:27:57","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1564,"text":"Environmental Science and Pollution Research","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Tissue distribution and temporal and spatial assessment of per- and polyfluoroalkyl substances (PFAS) in smallmouth bass (Per- and polyfluoroalkyl substances (PFAS) have become an environmental issue worldwide. A first step to assessing potential adverse effects on fish populations is to determine if concentrations of concern are present in a region and if so, in which watersheds. Hence, plasma from adult smallmouth bass Micropterus dolomieu collected at 10 sites within 4 river systems in the mid-Atlantic region of the United States, from 2014 to 2019, was analyzed for 13 PFAS. These analyses were directed at better understanding the presence and associations with land use attributes in an important sportfish. Four substances, PFOS, PFDA, PFUnA, and PFDoA, were detected in every plasma sample, with PFOS having the highest concentrations. Sites with mean plasma concentrations of PFOS below 100 ng/ml had the lowest percentage of developed landcover in the upstream catchments. Sites with moderate plasma concentrations (mean PFOS concentrations between 220 and 240 ng/ml) had low (< 7.0) percentages of developed land use but high (> 30) percentages of agricultural land use. Sites with mean plasma concentrations of PFOS > 350 ng/ml had the highest percentage of developed land use and the highest number PFAS facilities that included military installations and airports. Four of the sites were part of a long-term monitoring project, and PFAS concentrations of samples collected in spring 2017, 2018, and 2019 were compared. Significant annual differences in plasma concentrations were noted that may relate to sources and climatic factors. Samples were also collected at two sites for tissue (plasma, whole blood, liver, gonad, muscle) distribution analyses with an expanded analyte list of 28 PFAS. Relative tissue distributions were not consistent even within one species of similar ages. Although the long-chained legacy PFAS were generally detected more frequently and at higher concentrations, emerging compounds such as 6:2 FTS and GEN X were detected in a variety of tissues.
","language":"English","publisher":"Springer","doi":"10.1007/s11356-024-35097-6","usgsCitation":"Blazer, V., Walsh, H.L., Smith, C.R., Gordon, S.E., Keplinger, B.J., and Wertz, T., 2024, Tissue distribution and temporal and spatial assessment of per- and polyfluoroalkyl substances (PFAS) in smallmouth bass (Micropterus dolomieu) in the mid-Atlantic United States: Environmental Science and Pollution Research, v. p., no. 31, p. 59302-59319, https://doi.org/10.1007/s11356-024-35097-6.","productDescription":"18","startPage":"59302","endPage":"59319","ipdsId":"IP-164838","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":466808,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s11356-024-35097-6","text":"Publisher Index Page"},{"id":463428,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Delaware, 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viability is critical for successful long-term recovery of target ecosystems and species. However, often it is difficult to quantify conservation action efficacy because of the complex, dynamic nature of ecosystem processes and practical limitations associated with assessing target species’ population dynamics. Here, we present an analytical framework that allows for quantification of conservation action efficacy using greater sage-grouse (Centrocercus urophasianus; hereafter, sage-grouse) within the Bi-State Distinct Population Segment which borders Nevada and California. This framework utilizes web-based repositories of conservation efforts carried out in sagebrush ecosystems and readily fits within contemporary sagebrush conservation design strategies. We employed a state-space model within a Bayesian framework to estimate abundance (N) as inputs for a progressive change before-after-control-impact paired series (BACIPS) design. Count data from 57 leks (monitored between 2003–2021) coupled with 85 unique actions (initiated between 2012–2019) provided clear evidence that conservation actions increased population abundance, on average, by 4.4% annually across the study area, resulting in a 37.4% cumulative increase since 2012. Population gains varied by the type of conservation action and according to the number of lag years following its implementation.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.rama.2024.08.007","usgsCitation":"Coates, P.S., Prochazka, B.G., Webster, S.C., Weise, C.L., Aldridge, C., O’Donnell, M.S., Wiechman, L.A., Doherty, K., and Tull, J.C., 2024, Cooperative conservation actions improve sage-grouse population performance within the Bi-State Distinct Population Segment: Rangeland Ecology & Management, v. 97, no. 1, p. 135-145, https://doi.org/10.1016/j.rama.2024.08.007.","productDescription":"11 p.","startPage":"135","endPage":"145","ipdsId":"IP-146505","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":466809,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rama.2024.08.007","text":"Publisher Index Page"},{"id":464340,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Nevada","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -120.04744073936212,\n 39.58975622408602\n ],\n [\n -120.04744073936212,\n 37.73670490749031\n ],\n [\n -118.51467511686786,\n 37.73670490749031\n ],\n [\n -118.51467511686786,\n 39.58975622408602\n ],\n [\n -120.04744073936212,\n 39.58975622408602\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"97","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Coates, Peter S. 0000-0003-2672-9994 pcoates@usgs.gov","orcid":"https://orcid.org/0000-0003-2672-9994","contributorId":3263,"corporation":false,"usgs":true,"family":"Coates","given":"Peter","email":"pcoates@usgs.gov","middleInitial":"S.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":918999,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Prochazka, Brian G. 0000-0001-7270-5550 bprochazka@usgs.gov","orcid":"https://orcid.org/0000-0001-7270-5550","contributorId":174839,"corporation":false,"usgs":true,"family":"Prochazka","given":"Brian","email":"bprochazka@usgs.gov","middleInitial":"G.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":919000,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Webster, Sarah C. 0000-0003-4981-2010","orcid":"https://orcid.org/0000-0003-4981-2010","contributorId":302117,"corporation":false,"usgs":true,"family":"Webster","given":"Sarah","email":"","middleInitial":"C.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":919001,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Weise, Cali L.","contributorId":305785,"corporation":false,"usgs":false,"family":"Weise","given":"Cali","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":919002,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Aldridge, Cameron L. 0000-0003-3926-6941","orcid":"https://orcid.org/0000-0003-3926-6941","contributorId":213471,"corporation":false,"usgs":false,"family":"Aldridge","given":"Cameron L.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":919003,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"O’Donnell, Michael S. 0000-0002-3488-003X odonnellm@usgs.gov","orcid":"https://orcid.org/0000-0002-3488-003X","contributorId":140876,"corporation":false,"usgs":true,"family":"O’Donnell","given":"Michael","email":"odonnellm@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":919004,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wiechman, Lief A. 0000-0002-3804-4426","orcid":"https://orcid.org/0000-0002-3804-4426","contributorId":184047,"corporation":false,"usgs":true,"family":"Wiechman","given":"Lief","email":"","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":919005,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Doherty, Kevin E.","contributorId":177793,"corporation":false,"usgs":false,"family":"Doherty","given":"Kevin E.","affiliations":[],"preferred":false,"id":919006,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Tull, John C. 0000-0002-0680-008X","orcid":"https://orcid.org/0000-0002-0680-008X","contributorId":201650,"corporation":false,"usgs":false,"family":"Tull","given":"John","email":"","middleInitial":"C.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":919007,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70261313,"text":"70261313 - 2024 - Self-potential tomography preconditioned by particle swarm optimization— Application to monitoring hyporheic exchange in a bedrock river","interactions":[],"lastModifiedDate":"2024-12-06T14:15:01.195444","indexId":"70261313","displayToPublicDate":"2024-10-27T09:42:06","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Self-potential tomography preconditioned by particle swarm optimization— Application to monitoring hyporheic exchange in a bedrock river","docAbstract":"A self-potential (SP) data-inversion algorithm was developed and tested on an analytical model of electrical-potential profile data attributed to single and multiple polarized electrical sources. The developed algorithm was then validated by an application to SP-monitoring field data measured on the floodplain of East Fork Poplar Creek, Oak Ridge, Tennessee, to image electrical sources in areas conducive to preferential flow into the flood plain from the bedrock-lined riverbed. The algorithm combined stochastic source-localization by particle-swarm-optimization (PSO) of electrical sources characterized by simplified geometries with source tomography by regularized weighted least-squares minimization of a quadratic objective function. Prior information was incorporated by preconditioning the tomography algorithm by PSO results. Variable percentages of random noise were added to analytical-model data to evaluate the algorithm performance. Results indicated that true parameters of single-source models were inverted and approximated with small residual error, whereas inversion of analytical-model data representing multiple electrical sources accurately approximated the locations of the sources but miscalculated some parameters because of the non-uniqueness of the inverse-model solution. Source tomography applied to analytical model data during testing produced a spatially continuous parameter field that identified the locations of point-scale synthetic dipole sources of electrical current flow with varying degrees of accuracy depending on the prior information incorporated into the tomography. When applied to SP-monitoring field data, the algorithm imaged electrical sources within a known fault that intersects the bedrock riverbed and flood plain of East Fork Poplar Creek and depicted dynamic electrical conditions attributed to hyporheic exchange.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2024WR037549","usgsCitation":"Ikard, S., Carroll, K.C., Brooks, S.C., Rucker, D.F., Smith-Vega, G., and Elwes, A., 2024, Self-potential tomography preconditioned by particle swarm optimization— Application to monitoring hyporheic exchange in a bedrock river: Water Resources Research, v. 60, no. 10, e2024WR037549, 25 p., https://doi.org/10.1029/2024WR037549.","productDescription":"e2024WR037549, 25 p.","ipdsId":"IP-160252","costCenters":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":466810,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2024wr037549","text":"Publisher Index Page"},{"id":464806,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Tennessee","city":"Oak Ridge","otherGeospatial":"East Fork Poplar Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -84.23096147469687,\n 36.034094349042874\n ],\n [\n -84.40092348796415,\n 36.034094349042874\n ],\n [\n -84.40092348796415,\n 35.91942637548165\n ],\n [\n -84.23096147469687,\n 35.91942637548165\n ],\n [\n -84.23096147469687,\n 36.034094349042874\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"60","issue":"10","noUsgsAuthors":false,"publicationDate":"2024-10-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Ikard, Scott 0000-0002-8304-4935","orcid":"https://orcid.org/0000-0002-8304-4935","contributorId":201775,"corporation":false,"usgs":true,"family":"Ikard","given":"Scott","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":920340,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carroll, Kenneth C. 0000-0003-2097-9589","orcid":"https://orcid.org/0000-0003-2097-9589","contributorId":247827,"corporation":false,"usgs":false,"family":"Carroll","given":"Kenneth","email":"","middleInitial":"C.","affiliations":[{"id":12628,"text":"New Mexico State University","active":true,"usgs":false}],"preferred":false,"id":920341,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brooks, Scott C. 0000-0002-8437-9788","orcid":"https://orcid.org/0000-0002-8437-9788","contributorId":294464,"corporation":false,"usgs":false,"family":"Brooks","given":"Scott","email":"","middleInitial":"C.","affiliations":[{"id":37070,"text":"Oak Ridge National Laboratory","active":true,"usgs":false}],"preferred":false,"id":920343,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rucker, Dale F. 0000-0002-8930-2747","orcid":"https://orcid.org/0000-0002-8930-2747","contributorId":294463,"corporation":false,"usgs":false,"family":"Rucker","given":"Dale","email":"","middleInitial":"F.","affiliations":[{"id":63573,"text":"hydroGEOPHYSICS, Inc.","active":true,"usgs":false}],"preferred":false,"id":920342,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Smith-Vega, Gladisol 0009-0001-1597-7944","orcid":"https://orcid.org/0009-0001-1597-7944","contributorId":346951,"corporation":false,"usgs":false,"family":"Smith-Vega","given":"Gladisol","email":"","affiliations":[{"id":12628,"text":"New Mexico State University","active":true,"usgs":false}],"preferred":false,"id":920344,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Elwes, Aubrey 0009-0000-4058-8126","orcid":"https://orcid.org/0009-0000-4058-8126","contributorId":346952,"corporation":false,"usgs":false,"family":"Elwes","given":"Aubrey","email":"","affiliations":[{"id":12628,"text":"New Mexico State University","active":true,"usgs":false}],"preferred":false,"id":920345,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70260492,"text":"70260492 - 2024 - Handling effects on dispersal of PIT-tagged Flannelmouth Sucker","interactions":[],"lastModifiedDate":"2025-02-07T16:26:07.721487","indexId":"70260492","displayToPublicDate":"2024-10-26T10:35:57","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Handling effects on dispersal of PIT-tagged Flannelmouth Sucker","docAbstract":"Handling and tagging migrating fish might alter their behavior, limiting inference from mark–recapture studies. Posthandling flight of tributary spawning Flannelmouth Sucker Catostomus latipinnis was previously identified in Coal Creek in the upper Colorado River basin. Our objective was to determine if similar issues were present at McElmo Creek in the San Juan River basin.
We compared emigration timing of Flannelmouth Sucker that had been handled and tagged with passive integrated transponder tags during their tributary spawning run to individuals tagged in previous years and detected both entering and exiting the tributary. Linear mixed-effects models were used to examine intrinsic and extrinsic factors contributing to exit timing.
Sex and tagging year were associated with emigration timing, but handling did not result in posthandling flight from McElmo Creek. Females exited the tributary ~3 days before males, and larger fish emigrated earlier than smaller adults.
Differences in capture technique and timing, available spawning habitat, and fish motivation across river systems may contribute to differences in posthandling emigration of tributary spawning Flannelmouth Sucker.
","language":"English","publisher":"American Fisheries Society","doi":"10.1002/nafm.11043","usgsCitation":"Bonjour, S.M., Gido, K., and McKinstry, M.C., 2024, Handling effects on dispersal of PIT-tagged Flannelmouth Sucker: North American Journal of Fisheries Management, v. 44, no. 5, p. 1111-1120, https://doi.org/10.1002/nafm.11043.","productDescription":"10 p.","startPage":"1111","endPage":"1120","ipdsId":"IP-164101","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":466811,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/nafm.11043","text":"Publisher Index Page"},{"id":463702,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, Utah","otherGeospatial":"McElmo Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -109.2051327142802,\n 37.21458135219234\n ],\n [\n -109.18545071833839,\n 37.2047842976106\n ],\n [\n -109.09360140394335,\n 37.24820822443989\n ],\n [\n -109.02389433498291,\n 37.315743074797766\n ],\n [\n -109.02225416865441,\n 37.33367692529539\n ],\n [\n -109.0489068714924,\n 37.33335089348972\n ],\n [\n -109.16412855606805,\n 37.24429130245919\n ],\n [\n -109.2051327142802,\n 37.21458135219234\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"44","issue":"5","noUsgsAuthors":false,"publicationDate":"2024-10-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Bonjour, Sophia Marie 0000-0003-3614-7023","orcid":"https://orcid.org/0000-0003-3614-7023","contributorId":335936,"corporation":false,"usgs":true,"family":"Bonjour","given":"Sophia","email":"","middleInitial":"Marie","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":917879,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gido, Keith B.","contributorId":341429,"corporation":false,"usgs":false,"family":"Gido","given":"Keith B.","affiliations":[{"id":12661,"text":"Kansas State University","active":true,"usgs":false}],"preferred":false,"id":917880,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McKinstry, Mark C.","contributorId":301155,"corporation":false,"usgs":false,"family":"McKinstry","given":"Mark","email":"","middleInitial":"C.","affiliations":[{"id":65322,"text":"Upper Colorado Regional Office","active":true,"usgs":false}],"preferred":false,"id":917881,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70261842,"text":"70261842 - 2024 - Imaging of seismic discontinuities using an adjoint method","interactions":[],"lastModifiedDate":"2024-12-30T15:44:38.161112","indexId":"70261842","displayToPublicDate":"2024-10-26T08:30:10","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1803,"text":"Geophysical Journal International","active":true,"publicationSubtype":{"id":10}},"title":"Imaging of seismic discontinuities using an adjoint method","docAbstract":"For imaging of seismic discontinuities at depth, reverse time migration (RTM) is a powerful method to apply to recordings of seismic events. It is especially powerful when an extensive receiver array, numerous seismic sources, or both, permit adequate reconstruction of incident and scattered wavefields at depth. Reconstructing either the incident or scattered wavefield at depth becomes less accurate when relatively few recordings of seismic events are available. Here we explore an inverse scattering approach to imaging discontinuities based on an adjoint method, employing sensitivity kernels (Frechet derivatives) that represent jumps in material properties across seismic-discontinuity surfaces. When combined with ray-based requirements on scattering geometry, it constitutes a powerful approach to determining the locations and amplitudes of the discontinuities, recovering only those properties that can be resolved by a spatially limited source and/or receiver distribution. This is illustrated by synthetic examples with local sources followed by a field example in a subduction zone setting","language":"English","publisher":"Oxford Academic","doi":"10.1093/gji/ggae377","usgsCitation":"Pollitz, F., and Langer, L., 2024, Imaging of seismic discontinuities using an adjoint method: Geophysical Journal International, v. 240, no. 1, p. 96-116, https://doi.org/10.1093/gji/ggae377.","productDescription":"21 p.","startPage":"96","endPage":"116","ipdsId":"IP-168143","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":466812,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/gji/ggae377","text":"Publisher Index Page"},{"id":465529,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Olympic Peninsula","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -124.04854303496683,\n 48.39880725647825\n ],\n [\n -124.04854303496683,\n 47.84371851145082\n ],\n [\n -122.34546521610972,\n 47.84371851145082\n ],\n [\n -122.34546521610972,\n 48.39880725647825\n ],\n [\n -124.04854303496683,\n 48.39880725647825\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"240","issue":"1","noUsgsAuthors":false,"publicationDate":"2024-10-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Pollitz, Frederick 0000-0002-4060-2706 fpollitz@usgs.gov","orcid":"https://orcid.org/0000-0002-4060-2706","contributorId":139578,"corporation":false,"usgs":true,"family":"Pollitz","given":"Frederick","email":"fpollitz@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":922000,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Langer, Leah","contributorId":347567,"corporation":false,"usgs":false,"family":"Langer","given":"Leah","affiliations":[{"id":34474,"text":"Tel Aviv University","active":true,"usgs":false}],"preferred":false,"id":922001,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70260185,"text":"70260185 - 2024 - Radiogenic strontium- and uranium-isotope tracers of water-rock interactions and hydrothermal flow in the Upper Geyser Basin, Yellowstone Plateau Volcanic Field, USA","interactions":[],"lastModifiedDate":"2024-10-30T12:08:08.229599","indexId":"70260185","displayToPublicDate":"2024-10-26T07:06:24","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":18959,"text":"Geochemistry Geophysics, Geosystems","active":true,"publicationSubtype":{"id":10}},"title":"Radiogenic strontium- and uranium-isotope tracers of water-rock interactions and hydrothermal flow in the Upper Geyser Basin, Yellowstone Plateau Volcanic Field, USA","docAbstract":"Natural radiogenic isotopes (primarily 87Sr/86Sr) from hot springs in the Upper Geyser Basin of the Yellowstone Plateau volcanic field and associated rocks were used to evaluate groundwater flow patterns, water-rock reactions, and the extent of mixing between various groundwater sources. Thermal waters have very low uranium concentrations and 234U/238U activity ratios near 1.0, which limit their utility as tracers in this reducing setting. Thermal waters have higher Sr concentrations (<22 ng/g) and a wide range of 87Sr/86Sr values that vary both temporally at individual discharge sites and between adjacent springs, indicating that conduits tap different subsurface reservoirs to varying degrees. Sr from local rhyolites have 87Sr/86Sr compositions that bound the range of values observed in groundwater throughout the basin. Non-boiling springs on the west flank of the basin discharge water with low 87Sr/86Sr consistent with flow through young volcanic rocks exposed at the surface. Boiling springs in the central basin have higher 87Sr/86Sr values reflecting interactions with older, more radiogenic volcanic rocks. Variability in upwelling thermal waters requires mixing with a low 87Sr/86Sr component derived from young lava or glacial sediments, or more likely, from deeper sources of hot groundwater circulating through buried Lava Creek Tuff having intermediate 87Sr/86Sr. Isotope data constrain basin-wide output of thermal water to 110–140 kg·s−1. Results underscore the utility of radiogenic Sr isotopes as valuable tracers of hydrothermal flow patterns and improve the understanding of temperature-dependent water-rock reactions in one of the largest continental hydrothermal systems on Earth.
Sustainable forestry typically involves integration of several economic and ecological objectives which, at times, may not be compatible with one another. Multi-objective prioritization via harvest scheduling programs can be used to elucidate these relationships and explore solutions. One such program is a spatially explicit harvest scheduler that adopts the Metropolis-Hastings algorithm to iteratively find management solutions to achieve multiple objectives (Habplan). Although this program has been used to address forest management scheduling and simulation-based tasks, its utility is constrained by time-intensive data preparation and challenges with incorporating spatial configuration objectives. To address these shortcomings, we introduce an open-source software package, HabplanR, streamlines data preparation, sets parameters, visualizes results, and assesses spatial components of ecological objectives. We developed four example objectives to incorporate into a multi-objective management problem: habitat quality indices for three species “types” (open, closed, and intermediate-canopy-associated species), and harvested pine pulpwood (revenue). We demonstrate the utility of this package to find management schedules that can accommodate potentially conflicting habitat needs of species, while achieving economic targets. We produced 100 software runs and prioritized individual objectives to select four management schedules for further comparisons. We compared outcome differences of the four schedules, including a spatial comparison of two high performing schedules. The software package makes costs and benefits of different schedules explicit and allows for consideration of the spatial configuration of management outcomes in decision-making.
","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0302640","usgsCitation":"Jones, M., Larsen-Gray, A., Prisley, S., Munro, H., and Hunter, E.A., 2024, A multi-objective approach for timber harvest scheduling to include management of at-risk species and spatial configuration objectives: PLoS ONE, v. 19, no. 10, e0302640, 21 p., https://doi.org/10.1371/journal.pone.0302640.","productDescription":"e0302640, 21 p.","ipdsId":"IP-160551","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":481054,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0302640","text":"Publisher Index Page"},{"id":480838,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"southeastern United States","volume":"19","issue":"10","noUsgsAuthors":false,"publicationDate":"2024-10-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Jones, Max D.","contributorId":348862,"corporation":false,"usgs":false,"family":"Jones","given":"Max D.","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":923838,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Larsen-Gray, Angela","contributorId":348864,"corporation":false,"usgs":false,"family":"Larsen-Gray","given":"Angela","affiliations":[{"id":38077,"text":"National Council for Air and Stream Improvement","active":true,"usgs":false}],"preferred":false,"id":923839,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Prisley, Stephen P.","contributorId":348867,"corporation":false,"usgs":false,"family":"Prisley","given":"Stephen P.","affiliations":[{"id":38077,"text":"National Council for Air and Stream Improvement","active":true,"usgs":false}],"preferred":false,"id":923840,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Munro, Holly L.","contributorId":348870,"corporation":false,"usgs":false,"family":"Munro","given":"Holly L.","affiliations":[{"id":38077,"text":"National Council for Air and Stream Improvement","active":true,"usgs":false}],"preferred":false,"id":923841,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hunter, Elizabeth Ann 0000-0003-4710-167X","orcid":"https://orcid.org/0000-0003-4710-167X","contributorId":288535,"corporation":false,"usgs":true,"family":"Hunter","given":"Elizabeth","email":"","middleInitial":"Ann","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":923842,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70260475,"text":"70260475 - 2024 - Benthic community metrics track hydrologically stressed mangrove systems","interactions":[],"lastModifiedDate":"2024-11-04T17:40:22.765316","indexId":"70260475","displayToPublicDate":"2024-10-25T11:33:28","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1398,"text":"Diversity","active":true,"publicationSubtype":{"id":10}},"title":"Benthic community metrics track hydrologically stressed mangrove systems","docAbstract":"Mangrove restoration efforts have increased in order to help combat their decline globally. While restoration efforts often focus on planting seedlings, underlying chronic issues, including disrupted hydrological regimes, can hinder restoration success. While improving hydrology may be more cost-effective and have higher success rates than planting seedlings alone, hydrological restoration success in this form is poorly understood. Restoration assessments can employ a functional equivalency approach, comparing restoration areas over time with natural, reference forests in order to quantify the relative effectiveness of different restoration approaches. Here, we employ the use of baseline community ecology metrics along with stable isotopes to track changes in the community and trophic structure and enable time estimates for establishing mangrove functional equivalency. We examined a mangrove system impacted by road construction and recently targeted for hydrological restoration within the Rookery Bay National Estuarine Research Reserve, Florida, USA. Samples were collected along a gradient of degradation, from a heavily degraded zone, with mostly dead trees, to a transition zone, with a high number of saplings, to a full canopy zone, with mature trees, and into a reference zone with dense, mature mangrove trees. The transition, full canopy, and reference zones were dominated by annelids, gastropods, isopods, and fiddler crabs. Diversity was lower in the dead zone; these taxa were enriched in 13C relative to those found in all the other zones, indicating a shift in the dominant carbon source from mangrove detritus (reference zone) to algae (dead zone). Community-wide isotope niche metrics also distinguished zones, likely reflecting dominant primary food resources (baseline organic matter) present. Our results suggest that stable isotope niche metrics provide a useful tool for tracking mangrove degradation gradients. These baseline data provide critical information on the ecosystem functioning in mangrove habitats following hydrological restoration.
","language":"English","publisher":"MDPI","doi":"10.3390/d16110659","usgsCitation":"Demopoulos, A., Bourque, J., McClain Counts, J., Cormier, N., and Krauss, K., 2024, Benthic community metrics track hydrologically stressed mangrove systems: Diversity, v. 16, no. 11, 659, 27 p., https://doi.org/10.3390/d16110659.","productDescription":"659, 27 p.","ipdsId":"IP-170195","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":466814,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/d16110659","text":"Publisher Index Page"},{"id":463599,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -81.69167,\n 25.95\n ],\n [\n -81.69167,\n 25.9\n ],\n [\n -81.64167,\n 25.9\n ],\n [\n -81.64167,\n 25.95\n ],\n [\n -81.69167,\n 25.95\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"16","issue":"11","noUsgsAuthors":false,"publicationDate":"2024-10-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Demopoulos, Amanda 0000-0003-2096-4694","orcid":"https://orcid.org/0000-0003-2096-4694","contributorId":222192,"corporation":false,"usgs":true,"family":"Demopoulos","given":"Amanda","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":917772,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bourque, Jill 0000-0003-3809-2601","orcid":"https://orcid.org/0000-0003-3809-2601","contributorId":222184,"corporation":false,"usgs":true,"family":"Bourque","given":"Jill","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":917773,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McClain Counts, Jennifer 0000-0002-3383-5472","orcid":"https://orcid.org/0000-0002-3383-5472","contributorId":215718,"corporation":false,"usgs":true,"family":"McClain Counts","given":"Jennifer","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":917774,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cormier, Nicole 0000-0003-2453-9900","orcid":"https://orcid.org/0000-0003-2453-9900","contributorId":214726,"corporation":false,"usgs":false,"family":"Cormier","given":"Nicole","affiliations":[{"id":16788,"text":"Macquarie University","active":true,"usgs":false}],"preferred":false,"id":917775,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Krauss, Ken 0000-0003-2195-0729","orcid":"https://orcid.org/0000-0003-2195-0729","contributorId":218325,"corporation":false,"usgs":true,"family":"Krauss","given":"Ken","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":917776,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70261155,"text":"70261155 - 2024 - The geometry of fault reactivation and uplift along the central part of the Maacama fault zone, northern California Coast Ranges (USA)","interactions":[],"lastModifiedDate":"2024-11-26T16:40:13.642828","indexId":"70261155","displayToPublicDate":"2024-10-25T10:35:06","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1820,"text":"Geosphere","active":true,"publicationSubtype":{"id":10}},"title":"The geometry of fault reactivation and uplift along the central part of the Maacama fault zone, northern California Coast Ranges (USA)","docAbstract":"Fault reactivation of bedrock structures in active fault zones influences stress state and earthquake rupture phenomena through the introduction of weak slip surfaces that impact fault zone geometry and width. Yet, geometric relationships between modern faults and older reactivated faults are difficult to quantify in rocks that have experienced multiple deformation episodes. We used new geologic mapping, geomorphic tools, and structural modeling to quantify rock uplift and subsurface fault geometry of the central part of the Maacama Fault Zone near Ukiah, California, USA, and the surrounding area. Results suggest that the northern Mayacamas Mountains are in a tectonically driven disequilibrium, with differential rock uplift focused on the western side of the range. Steeply east-dipping fault surfaces and splays characterize the geometry of the Maacama Fault Zone. We mapped two newly identified faults to the east of the main Maacama Fault, the Cow Mountain–Mill Creek Fault, and Willow Creek Fault, which align with a moderately east-dipping cluster of microseismicity between 4–10 km depth beneath the Mayacamas Mountains. Static stress modeling on the Maacama Fault Zone and newly identified faults to the east quantify slip tendency values of 0.5–0.4, which suggests that the faults are moderately to poorly suited for slip in the modern stress field and may be weak. We infer that modern uplift is driven by oblique reverse, up-to-the-east, dip-slip motion on the reactivated Cenozoic Cow Mountain–Mill Creek and Willow Creek Faults as material is advected through a restraining bend on the Maacama Fault. This study shows that reactivated bedrock faults increase the fault zone width and introduce fault surfaces that contribute a component of vertical deformation and uplift in major strike-slip fault zones. Deformation is accommodated on an interconnected network of new and reactivated faults that delineate a complex seismic hazard.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES02750.1","usgsCitation":"Melosh, B.L., McLaughlin, R., and Ohlin, H., 2024, The geometry of fault reactivation and uplift along the central part of the Maacama fault zone, northern California Coast Ranges (USA): Geosphere, v. 20, no. 6, p. 1511-1532, https://doi.org/10.1130/GES02750.1.","productDescription":"22 p.","startPage":"1511","endPage":"1532","ipdsId":"IP-154371","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":466815,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges02750.1","text":"Publisher Index Page"},{"id":464534,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Maacama Fault Zone, Northern California Coast Ranges","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -123.45015959177604,\n 39.45109183492838\n ],\n [\n -123.45015959177604,\n 38.81847294177288\n ],\n [\n -122.91075258047664,\n 38.81847294177288\n ],\n [\n -122.91075258047664,\n 39.45109183492838\n ],\n [\n -123.45015959177604,\n 39.45109183492838\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"20","issue":"6","noUsgsAuthors":false,"publicationDate":"2024-10-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Melosh, Benjamin L. 0000-0002-8017-7193","orcid":"https://orcid.org/0000-0002-8017-7193","contributorId":217215,"corporation":false,"usgs":true,"family":"Melosh","given":"Benjamin","email":"","middleInitial":"L.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":919456,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McLaughlin, Robert J. 0000-0002-4390-2288","orcid":"https://orcid.org/0000-0002-4390-2288","contributorId":211450,"corporation":false,"usgs":true,"family":"McLaughlin","given":"Robert J.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":919457,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ohlin, Henry","contributorId":346525,"corporation":false,"usgs":false,"family":"Ohlin","given":"Henry","affiliations":[{"id":36466,"text":"Consulting Geologist","active":true,"usgs":false}],"preferred":false,"id":919458,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70259674,"text":"sir20245082 - 2024 - Use of a numerical groundwater-flow model and projected climate scenarios to simulate the effects of future climate conditions on base flow for reach 1 of the Washita River alluvial aquifer and Foss Reservoir storage, western Oklahoma","interactions":[],"lastModifiedDate":"2025-12-22T20:17:19.51282","indexId":"sir20245082","displayToPublicDate":"2024-10-25T10:23:33","publicationYear":"2024","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":"2024-5082","displayTitle":"Use of a Numerical Groundwater-Flow Model and Projected Climate Scenarios To Simulate the Effects of Future Climate Conditions on Base Flow for Reach 1 of the Washita River Alluvial Aquifer and Foss Reservoir Storage, Western Oklahoma","title":"Use of a numerical groundwater-flow model and projected climate scenarios to simulate the effects of future climate conditions on base flow for reach 1 of the Washita River alluvial aquifer and Foss Reservoir storage, western Oklahoma","docAbstract":"To better understand the relation between climate variability and future groundwater resources in reach 1 of the Washita River alluvial aquifer and Foss Reservoir in western Oklahoma, the U.S. Geological Survey, in cooperation with the Bureau of Reclamation, used a previously published numerical groundwater-flow model and climate-model data to investigate changes in base flow and reservoir storage by evaluating three scenarios. The three projected climate scenarios were (1) a central-tendency scenario, (2) a warmer/drier scenario, and (3) a less-warm/wetter scenario. To estimate future base flow and groundwater availability in western Oklahoma, specifically in reach 1 of the Washita River alluvial aquifer, downscaled climate-model data from 231 Coupled Model Intercomparison Project phase 5 (CMIP5) projections coupled with a previously published numerical groundwater-flow model were used to compare the effects of different climate scenarios on the aquifer. Changes in base flow and groundwater-level elevations during a 30-year baseline scenario (1985–2014) and the three 30-year projected climate scenarios (2050–79) under central-tendency, warmer/drier, and less-warm/wetter climatic conditions were assessed by using the calibrated model. In the simulations, the amount of base flow and reservoir storage declined in the central-tendency and warmer/drier scenarios compared to the amount of base flow and reservoir storage under historical climatic conditions (baseline scenario). Mean annual change in reservoir storage decreased from the baseline scenario the most in the warmer/drier scenario, followed by the central-tendency scenario, but increased in the less-warm/wetter scenario compared to the baseline scenario. At the end of the simulation period (2079), the largest magnitude differences in groundwater-level elevations in all three projected climate scenarios relative to the baseline scenario occurred upstream from Foss Reservoir. Results from incorporating downscaled climate projections into localized numerical groundwater-flow models can highlight potential future changes in and implications for groundwater resources and availability.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245082","issn":"2328-0328","collaboration":"Prepared in cooperation with Bureau of Reclamation","usgsCitation":"Labriola, L.G., Ellis, J.H., Gangopadhyay, S., Kirstetter, P.E., and Hong, Y., 2024, Use of a numerical groundwater-flow model and projected climate scenarios to simulate the effects of future climate conditions on base flow for reach 1 of the Washita River alluvial aquifer and Foss Reservoir storage, western Oklahoma: U.S. Geological Survey Scientific Investigations Report 2024–5082, 20 p., https://doi.org/10.3133/sir20245082.","productDescription":"Report: viii, 20 p.; 2 Datasets, Data Release","numberOfPages":"32","onlineOnly":"Y","ipdsId":"IP-140254","costCenters":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":497883,"rank":10,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117736.htm","linkFileType":{"id":5,"text":"html"}},{"id":463125,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20245082/full","description":"SIR 2024-5082 HTML"},{"id":463003,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2024/5082/images"},{"id":463001,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5082/coverthb.jpg"},{"id":463000,"rank":1,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2024/5082/images"},{"id":463006,"rank":9,"type":{"id":28,"text":"Dataset"},"url":"https://waterdata.usgs.gov/ok/nwis/","text":"USGS Water Data for Oklahoma","linkHelpText":"- USGS NWIS water data for Oklahoma"},{"id":463066,"rank":8,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS Water Data for the Nation","linkHelpText":"- USGS NWIS database"},{"id":463005,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9XFE87Q","text":"USGS Data Release","linkHelpText":"- MODFLOW-NWT model data used to simulate base flow and groundwater availability under different future climatic conditions for reach 1 of the Washita River alluvial aquifer and Foss Reservoir, western Oklahoma"},{"id":463124,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2024/5082/sir20245082.XML","description":"SIR 2024-5082 XML"},{"id":463002,"rank":4,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5082/sir20245082.pdf","size":"1.86 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2024-5082"}],"country":"United States","state":"Oklahoma","otherGeospatial":"Washita River alluvial aquifer and Foss Reservoir storage","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -99.99793544098728,\n 35.9\n ],\n [\n -99.99793544098728,\n 35.458335525604184\n ],\n [\n -98.75,\n 35.458335525604184\n ],\n [\n -98.75,\n 35.9\n ],\n [\n -99.99793544098728,\n 35.9\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Oklahoma-Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, TX 78754–4501
Contact Us- USGS Publications Warehouse
","tableOfContents":"Premature mortality of adult female Chinook Salmon Oncorhynchus tshawytscha is a major barrier to population recovery. The Willamette River basin, Oregon, typifies the problems that are faced by fishery managers in the Pacific Northwest (USA). Adult salmon are trapped and transported upstream of dams to access historical spawning grounds, but annual rates of prespawn mortality (PSM) are high (often >40%) and may limit the recovery of natural populations. The purpose of this study was to identify potential factors related to PSM of female Chinook Salmon that are outplanted above dams and incorporate them into a modeling framework to facilitate adaptive management of outplanting operations.
We evaluated PSM in Fall Creek of the Willamette River basin prior to transport facility improvements in summer and fall of 2010–2017 and postimprovement during 2020–2021. We estimated PSM and conducted exploratory analyses to identify possible nontransport sources of stress that may contribute to the observed high PSM rates. Candidate factors included long‐term elevated temperature exposure, elevated temperature exposure below the trap, total number of outplanted fish, and monthly human disturbance of outplanted fish. We then developed and fit three models, each representing a hypothesis of a factor influencing PSM, incorporated them into a single alternative decision model, and conducted sensitivity analyses.
Prespawn mortality averaged 0.66 (ranging from 0.37 to 0.94) over the study period. According to the simulation results, the top two management actions were to exclude human activities—swimming and fishing—from Fall Creek in July and August.
Expected PSM rates were predicted to be 0.38 when human activity was excluded in July and 0.37 for August. Sensitivity analyses indicated that the most influential decision model component was the choice of the alternative model.