Satellite-based remote sensing and uncrewed aerial imagery play increasingly important roles in the mapping of wildlife populations and wildlife habitat, but the availability of imagery has been limited in remote areas. At the same time, ecotourism is a rapidly growing industry and can yield a vast catalog of photographs that could be harnessed for monitoring purposes, but the inherently ad-hoc and unstructured nature of these images make them difficult to use. To help address this, a subfield of computer vision known as phototourism has been developed to leverage a diverse collection of unstructured photographs to reconstruct a georeferenced three-dimensional scene capturing the environment at that location. Here we demonstrate the use of phototourism in an application involving Antarctic penguins, sentinel species whose dynamics are closely tracked as a measure of ecosystem functioning, and introduce a semi-automated pipeline for aligning and registering ground photographs using a digital elevation model (DEM) and satellite imagery. We employ the Segment Anything Model (SAM) for the interactive identification and segmentation of penguin colonies in these photographs. By creating a textured 3D mesh from the DEM and satellite imagery, we estimate camera poses to align ground photographs with the mesh and register the segmented penguin colony area to the mesh, achieving a detailed representation of the colony. Our approach has demonstrated promising performance, though challenges persist due to variations in image quality and the dynamic nature of natural landscapes. Nevertheless, our method offers a straightforward and effective tool for the georegistration of ad-hoc photographs in natural landscapes, with additional applications such as monitoring glacial retreat.
","language":"English","publisher":"PLoS","doi":"10.1371/journal.pone.0311038","usgsCitation":"Wu, H., Flynn, C., Hall, C., Che-Castaldo, C., Samaras, D., Schwaller, M., and Lynch, H., 2024, Penguin colony georegistration using camera pose estimation and phototourism: PLoS ONE, v. 19, no. 10, e0311038, 18 p., https://doi.org/10.1371/journal.pone.0311038.","productDescription":"e0311038, 18 p.","ipdsId":"IP-160209","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":466795,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0311038","text":"Publisher Index Page"},{"id":465996,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"19","issue":"10","noUsgsAuthors":false,"publicationDate":"2024-10-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Wu, Haoyu","contributorId":347903,"corporation":false,"usgs":false,"family":"Wu","given":"Haoyu","affiliations":[{"id":36488,"text":"Stony Brook University","active":true,"usgs":false}],"preferred":false,"id":922740,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Flynn, Clare","contributorId":347904,"corporation":false,"usgs":false,"family":"Flynn","given":"Clare","affiliations":[{"id":36488,"text":"Stony Brook University","active":true,"usgs":false}],"preferred":false,"id":922741,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hall, Carole","contributorId":347905,"corporation":false,"usgs":false,"family":"Hall","given":"Carole","affiliations":[{"id":36488,"text":"Stony Brook University","active":true,"usgs":false}],"preferred":false,"id":922742,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Che-Castaldo, Christian Joseph 0000-0002-7670-2178","orcid":"https://orcid.org/0000-0002-7670-2178","contributorId":347906,"corporation":false,"usgs":true,"family":"Che-Castaldo","given":"Christian Joseph","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":922743,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Samaras, Dimitris","contributorId":347907,"corporation":false,"usgs":false,"family":"Samaras","given":"Dimitris","affiliations":[{"id":36488,"text":"Stony Brook University","active":true,"usgs":false}],"preferred":false,"id":922744,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schwaller, Mathew","contributorId":347909,"corporation":false,"usgs":false,"family":"Schwaller","given":"Mathew","affiliations":[{"id":36488,"text":"Stony Brook University","active":true,"usgs":false}],"preferred":false,"id":922745,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lynch, Heather J.","contributorId":347911,"corporation":false,"usgs":false,"family":"Lynch","given":"Heather J.","affiliations":[{"id":36488,"text":"Stony Brook University","active":true,"usgs":false}],"preferred":false,"id":922746,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70261121,"text":"70261121 - 2024 - Examining inter-regional and intra-seasonal differences in wintering waterfowl landscape associations among Pacific and Atlantic flyways","interactions":[{"subject":{"id":70261121,"text":"70261121 - 2024 - Examining inter-regional and intra-seasonal differences in wintering waterfowl landscape associations among Pacific and Atlantic flyways","indexId":"70261121","publicationYear":"2024","noYear":false,"title":"Examining inter-regional and intra-seasonal differences in wintering waterfowl landscape associations among Pacific and Atlantic flyways"},"predicate":"SUPERSEDED_BY","object":{"id":70261880,"text":"70261880 - 2025 - Examining inter-regional and intra-seasonal differences in wintering waterfowl landscape associations among Pacific and Atlantic flyways","indexId":"70261880","publicationYear":"2025","noYear":false,"title":"Examining inter-regional and intra-seasonal differences in wintering waterfowl landscape associations among Pacific and Atlantic flyways"},"id":1}],"supersededBy":{"id":70261880,"text":"70261880 - 2025 - Examining inter-regional and intra-seasonal differences in wintering waterfowl landscape associations among Pacific and Atlantic flyways","indexId":"70261880","publicationYear":"2025","noYear":false,"title":"Examining inter-regional and intra-seasonal differences in wintering waterfowl landscape associations among Pacific and Atlantic flyways"},"lastModifiedDate":"2025-01-27T17:18:30.964189","indexId":"70261121","displayToPublicDate":"2024-10-30T08:30:41","publicationYear":"2024","noYear":false,"publicationType":{"id":27,"text":"Preprint"},"publicationSubtype":{"id":32,"text":"Preprint"},"seriesTitle":{"id":19836,"text":"Authorea","active":true,"publicationSubtype":{"id":32}},"title":"Examining inter-regional and intra-seasonal differences in wintering waterfowl landscape associations among Pacific and Atlantic flyways","docAbstract":"The Central Valley of California (CVC) and Mid-Atlantic (MA) in the U.S. are both critical sites for nationwide food security (California Poultry Federation 2016, Prosser et al. 2017), and many waterfowl species annually, especially during the winter, providing feeding and roosting locations for a variety of species. Mapping waterfowl distributions, using NEXRAD, may aid in the adaptive management of important waterfowl habitat and allow various government agencies to better understand the interface between wild and domestic birds and commercial agricultural practices. We used 9 years (2014–2023) of data from the US NEXRAD network to model winter waterfowl relative abundance in the CVC and MA as a function of weather, temporal period, environmental conditions, and landcover characteristics using Boosted Regression Tree modelling. We were able to quantify the variability in effect size of 28 different covariates across space and time within two geographic regions which are critical to nationwide waterfowl management and host a high density of nationally important commercial agriculture. In general, weather, geographic (distance to features), and landcover condition (wetness index) predictors had the strongest relative effect on predicting wintering waterfowl relative abundance in both regions, while effects of land cover composition were more regionally and temporally specific. Increased daily mean temperature was a major predictor of increasing relative waterfowl abundance in both regions throughout the winter. Increasing precipitation had differing effects within regions, increasing relative waterfowl abundance in the MA, while decreasing in general within the CVC. Increasing relative waterfowl abundance in the CVC are strongly tied to the flooding of the landscape and rice availability, whereas waterfowl in the MA, where water is less limiting, are generally governed by waste grain availability and emergent wetland on the landscape. Waterfowl relative abundance in the MA was generally higher nearer to the Atlantic coast and lakes, while in the CVC they were higher nearer to lakes. Our findings promote a better understanding of spatial associations of waterfowl to landscape features and may aid in conservation and biosecurity management protocols.","language":"English","publisher":"Authorea","doi":"10.22541/au.173030440.00154170/v1","usgsCitation":"Hardy, M., Williams, C.K., Ladman, B.S., Pitesky, M.E., Overton, C.T., Casazza, M.L., Matchett, E., Prosser, D.J., and Buler, J.J., 2024, Examining inter-regional and intra-seasonal differences in wintering waterfowl landscape associations among Pacific and Atlantic flyways: Authorea, https://doi.org/10.22541/au.173030440.00154170/v1.","productDescription":"51 p.","ipdsId":"IP-172616","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":466797,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.22541/au.173030440.00154170/v1","text":"External Repository"},{"id":466796,"rank":2,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.22541/au.173030440.00154170/v1","text":"External Repository"},{"id":464459,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hardy, Matthew J.","contributorId":343392,"corporation":false,"usgs":false,"family":"Hardy","given":"Matthew J.","affiliations":[{"id":13359,"text":"University of Delaware","active":true,"usgs":false}],"preferred":false,"id":919360,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Williams, Christopher K.","contributorId":202263,"corporation":false,"usgs":false,"family":"Williams","given":"Christopher","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":919361,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ladman, Brian S.","contributorId":337102,"corporation":false,"usgs":false,"family":"Ladman","given":"Brian","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":919362,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pitesky, Maurice E.","contributorId":176920,"corporation":false,"usgs":false,"family":"Pitesky","given":"Maurice","email":"","middleInitial":"E.","affiliations":[{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":919363,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Overton, Cory T. 0000-0002-5060-7447 coverton@usgs.gov","orcid":"https://orcid.org/0000-0002-5060-7447","contributorId":3262,"corporation":false,"usgs":true,"family":"Overton","given":"Cory","email":"coverton@usgs.gov","middleInitial":"T.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":919364,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Casazza, Michael L. 0000-0002-5636-735X mike_casazza@usgs.gov","orcid":"https://orcid.org/0000-0002-5636-735X","contributorId":2091,"corporation":false,"usgs":true,"family":"Casazza","given":"Michael","email":"mike_casazza@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":919365,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Matchett, Elliott 0000-0001-5095-2884 ematchett@usgs.gov","orcid":"https://orcid.org/0000-0001-5095-2884","contributorId":5541,"corporation":false,"usgs":true,"family":"Matchett","given":"Elliott","email":"ematchett@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":919366,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Prosser, Diann J. 0000-0002-5251-1799","orcid":"https://orcid.org/0000-0002-5251-1799","contributorId":221167,"corporation":false,"usgs":true,"family":"Prosser","given":"Diann","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":919367,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Buler, Jeffrey J.","contributorId":194648,"corporation":false,"usgs":false,"family":"Buler","given":"Jeffrey","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":919368,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70260933,"text":"70260933 - 2024 - Identifying and filling critical knowledge gaps can optimize financial viability of blue carbon projects in tidal wetlands","interactions":[],"lastModifiedDate":"2024-11-15T14:33:52.68755","indexId":"70260933","displayToPublicDate":"2024-10-30T08:26:46","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5738,"text":"Frontiers in Environmental Science","active":true,"publicationSubtype":{"id":10}},"title":"Identifying and filling critical knowledge gaps can optimize financial viability of blue carbon projects in tidal wetlands","docAbstract":"One of the world’s largest “blue carbon” ecosystems, Louisiana’s tidal wetlands on the US Gulf of Mexico coast, is rapidly being lost. Louisiana’s strong legal, regulatory, and monitoring framework, developed for one of the world’s largest tidal wetland systems, provides an opportunity for a programmatic approach to blue carbon accreditation to support restoration of these ecologically and economically important tidal wetlands. Louisiana’s coastal wetlands span ∼1.4 million ha and accumulate 5.5–7.3 Tg yr−1 of blue carbon (organic carbon), ∼6%–8% of tidal marsh blue carbon accumulation globally. Louisiana has a favorable governance framework to advance blue carbon accreditation, due to centralized restoration planning, long term coastal monitoring, and strong legal and regulatory frameworks around carbon. Additional restoration efforts, planned through Louisiana’s Coastal Master Plan, over 50 years are projected to create, or avoid loss of, up to 81,000 ha of wetland. Current restoration funding, primarily from Deepwater Horizon oil spill settlements, will be fully committed by the early 2030s and additional funding sources are required. Existing accreditation methodologies have not been successfully applied to coastal Louisiana’s ecosystem restoration approaches or herbaceous tidal wetland types. Achieving financial viability for accreditation of these restoration and wetland types will require expanded application of existing blue carbon crediting methodologies. It will also require expanded approaches for predicting the future landscape without restoration, such as numerical modeling, to be validated. Additional methodologies (and/or standards) would have many common elements with those currently available but may be beneficial, depending on the goals and needs of both the state of Louisiana and potential purchasers of Louisiana tidal wetland carbon credits. This study identified twenty targeted needs that will address data and knowledge gaps to maximize financial viability of blue carbon accreditation for Louisiana’s tidal wetlands. Knowledge needs were identified in five categories: legislative and policy, accreditation methodologies and standards, soil carbon flux, methane flux, and lateral carbon flux. Due to the large spatial scale and diversity of tidal wetlands, it is expected that progress in coastal Louisiana has high potential to be generalized to similar wetland ecosystems across the northern Gulf of Mexico and globally.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/fenvs.2024.1421850","usgsCitation":"Carruthers, T.J., Jones, S.B., Terrell, M.K., Scheibly, J.F., Player, B.J., Black, V.A., Ehrenwerth, J.R., Biber, P.D., Connolly, R.M., Crooks, S., Curole, J.P., Darnell, K.M., Dausman, A., DeJong, A.L., Doyle, S.M., Esposito, C.R., Friess, D., Fourqurean, J.W., Georgiou, I.Y., Grimsditch, G.D., He, S., Hillmann, E.R., Holm, G.O., Howard, J., Jung, H., Jupiter, S.D., Kiskaddon, E.P., Krauss, K., Lavery, P.S., Liu, B., Lovelock, C.E., Mack, S.K., Macreadie, P.I., McGlathery, K.J., Megonigal, J.P., Roberts, B.J., Settelmyer, S., Staver, L.W., Stevens, H.J., Sutton-Grier, A.E., Villa, J.A., White, J.R., and Waycott, M., 2024, Identifying and filling critical knowledge gaps can optimize financial viability of blue carbon projects in tidal wetlands: Frontiers in Environmental Science, v. 12, 1421850, 16 p., https://doi.org/10.3389/fenvs.2024.1421850.","productDescription":"1421850, 16 p.","ipdsId":"IP-165324","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":466798,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fenvs.2024.1421850","text":"Publisher Index Page"},{"id":464119,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -89.5798883414875,\n 30.183721520956823\n ],\n [\n -90.26254794159267,\n 30.659495947506798\n ],\n [\n -93.68519744349099,\n 30.159467726997462\n ],\n [\n -93.87222747091712,\n 29.82740239017822\n ],\n [\n -93.84417296680317,\n 29.62437970908134\n ],\n [\n -91.99257569528429,\n 29.372062504492533\n ],\n [\n -90.7114200074153,\n 28.898303996821014\n ],\n [\n -89.27128879623413,\n 28.832787010801255\n ],\n [\n -88.80371372766903,\n 29.168124063185203\n ],\n [\n -88.71955021532717,\n 29.851737484600278\n ],\n [\n -88.74760471944114,\n 30.127120053251076\n ],\n [\n -89.5798883414875,\n 30.183721520956823\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"12","noUsgsAuthors":false,"publicationDate":"2024-10-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Carruthers, Tim J.B.","contributorId":346277,"corporation":false,"usgs":false,"family":"Carruthers","given":"Tim","email":"","middleInitial":"J.B.","affiliations":[{"id":82811,"text":"The Water Institute, Baton Rouge, Louisiana, USA","active":true,"usgs":false}],"preferred":false,"id":918567,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jones, S. 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Indices of benthic macroinvertebrate integrity have declined in urban areas across the Chesapeake Bay watershed (CBW), and more information is needed about whether these declines may be due to elevated conductivity. A predictive SC model for the CBW was developed using monitoring data from the National Water Quality Portal. Predictor variables representing SC sources were compiled for nontidal reaches across the CBW. Random forests modeling was conducted to predict SC at four time periods (1999–2001, 2004–2006, 2009–2011, and 2014–2016), which were then compared to a national data set of background SC to quantify departures from background SC. Carbonate geology, impervious cover, forest cover, and snow depth were the most important variables for predicting SC. Observations and modeled results showed snow depth amplified the effect of impervious cover on SC. Elevated SC was predicted in two-thirds of reaches in the CBW, and these elevated conditions persisted over time in many areas. These results can be used in stressor identification assessments to prioritize future monitoring and to determine where management activities could be implemented to reduce salinization.
The lack of consolidated information regarding the response of wild bird species to infection with avian influenza virus (AIV) is a challenge to both conservation managers and researchers alike, with related sectors also impacted, such as public health and commercial poultry. Using two independent searches, we reviewed published literature for studies describing wild bird species experimentally infected with avian influenza to assess host species’ relative susceptibility to AIVs. Additionally, we summarize broad-scale parameters for elements such as shedding duration and minimum infectious dose that can be used in transmission modelling efforts. Our synthesis shows that waterfowl (i.e. Anatidae) compose the vast majority of published AIV pathobiology studies, whereas gulls and passerines are less represented in research despite evidence that they also are susceptible and contribute to highly pathogenic avian influenza disease dynamics. This study represents the first comprehensive effort to compile available literature regarding the pathobiology of AIVs in all wild birds in over a decade. This database can now serve as a tool to all researchers, providing generalized estimates of pathobiology parameters for a variety of wild avian families and an opportunity to critically examine and assess what is known and identify where further insight is needed.
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
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":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 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","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins 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.
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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":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.
Objective: Native inland trout conservation efforts rely on physical barriers to exclude nonnative salmonids from target habitats. We used genetic techniques to evaluate a series of natural waterfalls for their potential to serve as barriers to prevent nonnative salmonids from entering a proposed reintroduction area for federally threatened Greenback Cutthroat Trout Oncorhynchus virginalis stomias.
Methods: Genetic samples were collected from nonnative Brook Trout Salvelinus fontinalis at 11 sampling reaches above and below natural waterfalls (height: ~1–3 m under base flow conditions) along a 33-km segment of Colorado's upper Cache la Poudre River near the outflow of the proposed reintroduction area. To evaluate whether upstream movement of Brook Trout is restricted by any of these waterfalls, we characterized longitudinal trends in genetic diversity along the river corridor and examined patterns of genetic differentiation and population structure in relation to waterfall locations using a panel of microsatellites.
Result: We found no evidence that the waterfalls served as complete movement barriers for nonnative Brook Trout based on genetic clustering analyses, estimates of population differentiation, and longitudinal genetic patterns. Our multilocus assessment did not identify alleles restricted to downstream reaches, and the river segment was genetically homogenized.
Conclusion: Our evaluation suggests that the existing waterfalls do not fully prevent upstream movement by nonnative Brook Trout, and thus barrier modification would be needed to establish an isolated Greenback Cutthroat Trout population in the proposed wilderness area.
","language":"English","publisher":"American Fisheries Society","doi":"10.1002/nafm.11033","usgsCitation":"Stack, T., Fairchild, M.P., Geiger, R., Oyler-McCance, S.J., Fike, J., Kennedy, C.M., Winkelman, D.L., and Kanno, Y., 2024, A genetic assessment of natural barriers for isolating a habitat network proposed for Greenback Cutthroat Trout reintroduction: Journal of Fisheries Management, v. 44, no. 5, p. 1062-1072, https://doi.org/10.1002/nafm.11033.","productDescription":"11 p.","startPage":"1062","endPage":"1072","ipdsId":"IP-164760","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":466818,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/nafm.11033","text":"Publisher Index Page"},{"id":464426,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Cache la Poudre River, Rocky Mountain National Park. 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A dense geodetic network recorded the Mw 7.1 Ridgecrest earthquake, including 16 Global Navigation Satellite System (GNSS) stations and 3 borehole strainmeters (BSM). The sub-nanostrain precision and sub-second sampling rate of BSMs bridges a gap between conventional seismologic and geodetic methods, exemplified by atypical postseismic shear strain reversals observed at nearfield (<2 km) station B921 that remain unexplained. We jointly invert GNSS displacements and BSM strains for coseismic and postseismic slip spanning hours to months over 7 independent periods. Cosiesmically, our model resolves the largest slip magnitudes of up to 6.6 m on the mainshock rupture plane, with similar patterns to other inferred slip distributions. The foreshock fault appears to slip coincidently with mainshock, revealing potential asperities activated during the preceding Mw 6.4 event. Postseismically, the best-fitting models adhere to mechanical rate-and-state expectations of logarithmically decaying slip adjacent to the coseismic rupture terminus, and where deep rheologic conditions favor creep. Most spatial variation occurs in the early postseismic timeframe (<1–2 weeks), with evidence for regional rheologic control and static stress dependence. Triggered creep on the neighboring Garlock Fault unexpectedly persists for >178 days—further highlighting the importance of fault networks in postseismic stress redistribution, critical to assessing future hazard.
Several plumes of dissolved, chlorinated solvents, including trichloroethylene, have been identified in a sole-source aquifer near the former Northrop Grumman Bethpage Facility and Naval Weapons Industrial Reserve Plant sites in southeastern Nassau County, New York. Past investigations have documented that the groundwater contamination originated from this industrial area and now extends to the south, in the direction of groundwater flow. The intermixed plumes are commonly referred to as the “Navy Grumman groundwater plume.” Detailed groundwater-flow modeling was needed for the New York State Department of Environmental Conservation (NYSDEC) to evaluate design options necessary for the construction, operation, optimization, maintenance, and monitoring of a groundwater extraction and treatment cleanup plan selected in a December 2019 Amended Record of Decision by the NYSDEC to comprehensively address these plumes.
Consequently, the NYSDEC began a cooperative study with the U.S. Geological Survey in 2020 to better understand the local hydrogeologic framework using two independent approaches to characterize aquifer heterogeneity and update an existing regional groundwater-flow model to provide transient boundary conditions for new inset groundwater-flow models of the plume area. We developed these detailed inset models for the two independent aquifer characterizations using history-matching techniques coupled with a novel approach to risk-based management optimization of the remedial design. We also used the updated regional model to assess this optimized groundwater extraction and treatment design for potential saltwater intrusion.
The ensembles of parameters resulting from history matching provided a platform with which to evaluate capture by water-supply and remedial wells using particle-tracking techniques. Using the ensemble to select a risk stance, we performed multiobjective optimization to identify various configurations of remedial pumping that are consistent with external constraints and that favor potentially competing objectives. Multiple solutions provide tradeoffs that NYSDEC can consider. In general, pumping redistribution may help to prevent further contamination migration downgradient. These and other study results are intended to support decisions for the remedial design focused on the local area encompassing the full extent of the Navy Grumman groundwater plume.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245086","collaboration":"Prepared in cooperation with New York State Department of Environmental Conservation","usgsCitation":"Fienen, M.N., Corson-Dosch, N., Stumm, F., Misut, P.E., Jahn, K., Troyer, J., Schubert, C.E., Walter, D.A., Finkelstein, J.S., Monti, J., Jr., St. Germain, D.J., Williams, J.H., and Woda, J.C., 2024, Analysis of factors affecting plume remediation in a sole-source aquifer system, southeastern Nassau County, New York: U.S. Geological Survey Scientific Investigations Report 2024–5086, 92 p., https://doi.org/10.3133/sir20245086.","productDescription":"Report: xii, 92 p.; 1 Dataset; 2 Data Releases","numberOfPages":"108","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-154036","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":497881,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117734.htm","linkFileType":{"id":5,"text":"html"}},{"id":463155,"rank":8,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"- USGS water data for the Nation"},{"id":463151,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2024/5086/images/"},{"id":463149,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5086/sir20245086.pdf","text":"Report","size":"5.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2024–5086"},{"id":463154,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P907ORL5","text":"USGS data release","linkHelpText":"MODFLOW 6 model scenario used to simulate transient stresses, heads, and flows in the Regional Aquifer System of Long Island, New York, 2005–2019"},{"id":463153,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P92KSK8H","text":"USGS data release","linkHelpText":"MODFLOW 6 models for simulating groundwater flow and a proposed remediation system in the sole-source aquifer system in southeastern Nassau County, New York"},{"id":463152,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20245086/full"},{"id":463150,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2024/5086/sir20245086.XML"},{"id":463148,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5086/coverthb.jpg"}],"country":"United States","state":"New York","county":"Nassau County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -73.62544451515083,\n 40.792321377318615\n ],\n [\n -73.61512551909095,\n 40.6377132292763\n ],\n [\n -73.42724709826577,\n 40.649402810993905\n ],\n [\n -73.44912803403062,\n 40.79737601237295\n ],\n [\n -73.62544451515083,\n 40.792321377318615\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, New York Water Science Center
U.S. Geological Survey
425 Jordan Road
Troy, NY 12180–8349
Low-lying, tropical, coral-reef-lined coastlines are becoming increasingly vulnerable to wave-driven flooding due to population growth, coral reef degradation, and sea-level rise. Early-warning systems (EWSs) are needed to enable coastal authorities to issue timely alerts and coordinate preparedness and evacuation measures for their coastal communities. At longer timescales, risk management and adaptation planning require robust assessments of future flooding hazard considering uncertainties. However, due to diversity in reef morphologies and complex reef hydrodynamics compared to sandy shorelines, there have been no robust analytical solutions for wave runup to allow for the development of large-scale coastal wave-driven flooding EWSs and risk assessment frameworks for reef-lined coasts. To address the need for fast, robust predictions of runup that account for the natural variability in coral reef morphologies, we constructed the BEWARE-2 (Broad-range Estimator of Wave Attack in Reef Environments) meta-process modeling system. We developed this meta-process model using a training dataset of hydrodynamics and wave runup computed by the XBeach Non-Hydrostatic process-based hydrodynamic model for 440 combinations of water level, wave height, and wave period with 195 representative reef profiles that encompass the natural diversity in real-world fringing coral reef systems. Through this innovation, BEWARE-2 can be applied in a larger range of coastal settings than meta-models that rely on a parametric description of the coral reef geometry. In the validation stage, the BEWARE-2 modeling system produced runup results that had a relative root mean square error of 13% and relative bias of 5% relative to runup simulated by XBeach Non-Hydrostatic for a large range of oceanographic forcing conditions and for diverse reef morphologies (root mean square error and bias 0.63 and 0.26 m, respectively, relative to mean simulated wave runup of 4.85 m). Incorporating parametric modifications in the modeling system to account for variations in reef roughness and beach slope allows for systematic errors (relative bias) in BEWARE-2 predictions to be reduced by a factor of 1.5–6.5 for relatively coarse or smooth reefs and mild or steep beach slopes. This prediction provided by the BEWARE-2 modeling system is faster by 4–5 orders of magnitude than the full, process-based hydrodynamic model and could therefore be integrated into large-scale EWSs for tropical, reef-lined coasts and used for large-scale flood risk assessments.
","language":"English","publisher":"European Geosciences Union (EGU)","doi":"10.5194/nhess-24-3597-2024","usgsCitation":"McCall, R.T., Storlazzi, C.D., Roelvink, F., Pearson, S., de Goede, R., and Antolinez, J.A., 2024, Rapid simulation of wave runup on morphologically diverse, reef-lined coasts with the BEWARE-2 (Broad-range Estimator of Wave Attack in Reef Environments) meta-process model: Natural Hazards and Earth System Sciences, v. 24, p. 3597-3625, https://doi.org/10.5194/nhess-24-3597-2024.","productDescription":"29 p.","startPage":"3597","endPage":"3625","ipdsId":"IP-160501","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":466824,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/nhess-24-3597-2024","text":"Publisher Index Page"},{"id":463198,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"24","noUsgsAuthors":false,"publicationDate":"2024-10-24","publicationStatus":"PW","contributors":{"authors":[{"text":"McCall, Robert T.","contributorId":148986,"corporation":false,"usgs":false,"family":"McCall","given":"Robert","email":"","middleInitial":"T.","affiliations":[{"id":12474,"text":"Deltares, Netherlands","active":true,"usgs":false}],"preferred":false,"id":916722,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Storlazzi, Curt D. 0000-0001-8057-4490","orcid":"https://orcid.org/0000-0001-8057-4490","contributorId":213610,"corporation":false,"usgs":true,"family":"Storlazzi","given":"Curt","middleInitial":"D.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":916723,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Roelvink, Floortje","contributorId":258290,"corporation":false,"usgs":false,"family":"Roelvink","given":"Floortje","email":"","affiliations":[{"id":36257,"text":"Deltares","active":true,"usgs":false}],"preferred":false,"id":916724,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pearson, Stuart 0000-0002-3986-4469","orcid":"https://orcid.org/0000-0002-3986-4469","contributorId":245646,"corporation":false,"usgs":false,"family":"Pearson","given":"Stuart","email":"","affiliations":[{"id":49245,"text":"Delft University of Technology; Deltares","active":true,"usgs":false}],"preferred":false,"id":916725,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"de Goede, Roel","contributorId":345473,"corporation":false,"usgs":false,"family":"de Goede","given":"Roel","email":"","affiliations":[{"id":36257,"text":"Deltares","active":true,"usgs":false}],"preferred":false,"id":916726,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Antolinez, Jose A.A.","contributorId":177510,"corporation":false,"usgs":false,"family":"Antolinez","given":"Jose","email":"","middleInitial":"A.A.","affiliations":[],"preferred":false,"id":916727,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70260109,"text":"70260109 - 2024 - Predictions of groundwater PFAS occurrence at drinking water supply depths in the United States","interactions":[],"lastModifiedDate":"2024-11-27T15:53:46.572812","indexId":"70260109","displayToPublicDate":"2024-10-24T09:02:46","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3338,"text":"Science","active":true,"publicationSubtype":{"id":10}},"title":"Predictions of groundwater PFAS occurrence at drinking water supply depths in the United States","docAbstract":"Per- and polyfluoroalkyl substances (PFAS), known colloquially as “forever chemicals”, have been associated with adverse human health effects and have contaminated drinking water supplies across the United States owing to their long-term and widespread use. People in the United States may unknowingly be drinking water that contains PFAS because of a lack of systematic analysis, particularly in domestic water supplies. We present an extreme gradient boosting model for predicting the occurrence of PFAS in groundwater at the depths of drinking water supply for the conterminous United States. Our model results indicate that 71 to 95 million people in the conterminous United States potentially rely on groundwater with detectable concentrations of PFAS for their drinking-water supplies prior to any treatment.
","language":"English","publisher":"Science","doi":"10.1126/science.ado6638","usgsCitation":"Tokranov, A.K., Ransom, K.M., Bexfield, L.M., Lindsey, B.D., Watson, E., Dupuy, D., Stackelberg, P.E., Fram, M.S., Voss, S., Kingsbury, J.A., Jurgens, B., Smalling, K., and Bradley, P., 2024, Predictions of groundwater PFAS occurrence at drinking water supply depths in the United States: Science, v. 386, no. 6723, p. 748-755, https://doi.org/10.1126/science.ado6638.","productDescription":"8 p.","startPage":"748","endPage":"755","ipdsId":"IP-157604","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf 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across barnacle life stages and indirect effects of the Pacific Marine Heatwave","docAbstract":"Barnacles are a foundation species in intertidal habitats. During the Pacific Marine Heatwave (PMH), intertidal barnacle cover increased in the northern Gulf of Alaska (GoA); however, the role of pelagic larval supply in this increase was unknown. Using long-term monitoring data on intertidal benthic (percent cover) and pelagic larval populations (nauplii and cyprid concentrations), we examined potential environmental drivers (temperature, chlorophyll-a, mixed layer depth) of larval concentration and whether including larval concentration at regional and annual scales improved intertidal barnacle percent cover models in two study regions in the GoA. In both regions, larval concentrations were slightly higher following the PMH. Percent cover models were improved by including cyprid concentrations (but not nauplii), and the effect strength varied by site and tidal elevation. This indicates that larval concentration contributes as a bottom–up driver of benthic barnacle abundance. There is little evidence of a direct effect of the PMH on either life stage. Instead, our results may illustrate the positive feedback between life stages, where higher adult benthic abundance increased larval concentrations, which then supplied more new recruits to the benthos. As heatwaves continue to occur, integrating various data types can provide insights into factors influencing both benthic and pelagic communities.
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