No abstract available.
","conferenceTitle":"SEG/IMAGE '24 the International Meeting for Applied Geoscience & Energy","conferenceDate":"August 26-29, 2024","conferenceLocation":"Houston, TX","language":"English","publisher":"AAPG","usgsCitation":"Weihermann, J., Li, Y., and McCafferty, A.E., 2024, Airborne gamma-ray spectrometry inversion signatures of Hicks Dome area, SEG/IMAGE '24 the International Meeting for Applied Geoscience & Energy, Houston, TX, August 26-29, 2024, 4 p.","productDescription":"4 p.","ipdsId":"IP-164021","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":434775,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois","otherGeospatial":"Hicks Dome","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -88.5,\n 37.75\n ],\n [\n -88.5,\n 37.45\n ],\n [\n -88.15,\n 37.45\n ],\n [\n -88.15,\n 37.75\n ],\n [\n -88.5,\n 37.75\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Weihermann, Jessica","contributorId":335668,"corporation":false,"usgs":false,"family":"Weihermann","given":"Jessica","email":"","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":899106,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Li, Yaoguo","contributorId":335669,"corporation":false,"usgs":false,"family":"Li","given":"Yaoguo","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":899107,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McCafferty, Anne E. 0000-0001-5574-9201 anne@usgs.gov","orcid":"https://orcid.org/0000-0001-5574-9201","contributorId":1120,"corporation":false,"usgs":true,"family":"McCafferty","given":"Anne","email":"anne@usgs.gov","middleInitial":"E.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":899108,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70273467,"text":"70273467 - 2024 - 6PPD & 6PPD-quinone","interactions":[],"lastModifiedDate":"2026-01-15T16:38:21.618003","indexId":"70273467","displayToPublicDate":"2024-09-01T08:35:48","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":3,"text":"Organization Series"},"title":"6PPD & 6PPD-quinone","docAbstract":"No abstract available.
","language":"English","publisher":"Interstate Technology & Regulatory Council","usgsCitation":"Interstate Technology & Regulatory Council, Grant, K., Williams, T., Brauner, S., Zambrana, J., Nancarrow, C., Garland, M., McCue, D., Smith, R., Lane, R.F., Bristol, M.R., and Reinis, S., 2024, 6PPD & 6PPD-quinone.","ipdsId":"IP-185072","costCenters":[{"id":84311,"text":"Central Plains Water Science Center","active":true,"usgs":true}],"links":[{"id":498654,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":498629,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://6ppd.itrcweb.org/about-itrc/"}],"noUsgsAuthors":false,"publicationDate":"2024-09-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Interstate Technology & Regulatory Council","contributorId":365170,"corporation":true,"usgs":false,"organization":"Interstate Technology & Regulatory Council","id":953861,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grant, Kelly","contributorId":365171,"corporation":false,"usgs":false,"family":"Grant","given":"Kelly","affiliations":[],"preferred":false,"id":953862,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Williams, Tanya","contributorId":365172,"corporation":false,"usgs":false,"family":"Williams","given":"Tanya","affiliations":[],"preferred":false,"id":953863,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brauner, Steven","contributorId":365173,"corporation":false,"usgs":false,"family":"Brauner","given":"Steven","affiliations":[],"preferred":false,"id":953864,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zambrana, Jose","contributorId":365174,"corporation":false,"usgs":false,"family":"Zambrana","given":"Jose","affiliations":[],"preferred":false,"id":953865,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nancarrow, Christine","contributorId":365175,"corporation":false,"usgs":false,"family":"Nancarrow","given":"Christine","affiliations":[],"preferred":false,"id":953866,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Garland, Michael","contributorId":365176,"corporation":false,"usgs":false,"family":"Garland","given":"Michael","affiliations":[],"preferred":false,"id":953867,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"McCue, Dana","contributorId":365177,"corporation":false,"usgs":false,"family":"McCue","given":"Dana","affiliations":[],"preferred":false,"id":953868,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Smith, Rhea","contributorId":365178,"corporation":false,"usgs":false,"family":"Smith","given":"Rhea","affiliations":[],"preferred":false,"id":953869,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Lane, Rachael F. 0000-0001-9202-0612","orcid":"https://orcid.org/0000-0001-9202-0612","contributorId":222471,"corporation":false,"usgs":true,"family":"Lane","given":"Rachael","email":"","middleInitial":"F.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":953843,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Bristol, Madison Rose","contributorId":365179,"corporation":false,"usgs":false,"family":"Bristol","given":"Madison","middleInitial":"Rose","affiliations":[],"preferred":false,"id":953870,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Reinis, Sigrida","contributorId":365180,"corporation":false,"usgs":false,"family":"Reinis","given":"Sigrida","affiliations":[],"preferred":false,"id":953871,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70266810,"text":"70266810 - 2024 - Seasonal movements between mainstem and tributaries may facilitate the persistence of Roundtail Chub and Flannelmouth Sucker within an altered stream system","interactions":[],"lastModifiedDate":"2025-05-13T16:03:51.297459","indexId":"70266810","displayToPublicDate":"2024-09-01T00:00:00","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":12982,"text":"Transaction of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Seasonal movements between mainstem and tributaries may facilitate the persistence of Roundtail Chub and Flannelmouth Sucker within an altered stream system","docAbstract":"Objective
Movement enables animals to complete their life history by responding to changing environmental conditions. Linking movement behaviors to life history characteristics can allow more targeted management applications for declining native fish populations. We identified seasonal movement patterns of Roundtail Chub Gila robusta and Flannelmouth Sucker Catostomus latipinnis, two understudied species that currently occupy only a portion of their historical range within the Colorado River Basin.
Methods
We coupled Passive Integrated Transponder tag antenna systems with multi-state capture-recapture models to quantify juvenile and adult movement between mainstem and tributary habitat within the Blacks Fork subbasin of southwest Wyoming, U.S.A. during 2019–2021. We also evaluated how flow and temperature may cue the timing of seasonal movements.
Result
Adults from both species made spring spawning movements to reach upstream tributary habitat, though adult Flannelmouth Sucker movements were more common and longer. Roundtail Chub primarily moved into the Hams Fork while Flannelmouth Sucker primarily moved into Muddy Creek, an intermittent tributary that was also identified as important for juvenile rearing. Juvenile movements occurred primarily during the fall months, with distance traveled comparable between species. Temperature and flow influenced the timing of spring spawning movements in adult Flannelmouth Sucker, with low flow potentially limiting access to preferred spawning habitat.
Conclusion
Identified movements likely contribute to Roundtail Chub and Flannelmouth Sucker persistence within this highly altered stream system and ultimately provide insights for management and recovery strategies to prevent further population declines.
","language":"English","publisher":"Wiley","doi":"10.1002/tafs.10489","usgsCitation":"Magruder, A., Barrile, G., Siddons, S.F., Walrath, J.D., and Walters, A.W., 2024, Seasonal movements between mainstem and tributaries may facilitate the persistence of Roundtail Chub and Flannelmouth Sucker within an altered stream system: Transaction of the American Fisheries Society, v. 153, no. 5, p. 644-659, https://doi.org/10.1002/tafs.10489.","productDescription":"16 p.","startPage":"644","endPage":"659","ipdsId":"IP-152541","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":497999,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/tafs.10489","text":"Publisher Index Page"},{"id":485828,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Blacks Fork subbasin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -109.78521909444135,\n 41.60984642142259\n ],\n [\n -109.78521909444135,\n 41.45062453005164\n ],\n [\n -109.43506299346544,\n 41.45062453005164\n ],\n [\n -109.43506299346544,\n 41.60984642142259\n ],\n [\n -109.78521909444135,\n 41.60984642142259\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"153","issue":"5","noUsgsAuthors":false,"publicationDate":"2024-08-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Magruder, Alissa C.","contributorId":355068,"corporation":false,"usgs":false,"family":"Magruder","given":"Alissa C.","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":936822,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barrile, Gabriel M.","contributorId":288734,"corporation":false,"usgs":false,"family":"Barrile","given":"Gabriel M.","affiliations":[{"id":40829,"text":"uwy","active":true,"usgs":false}],"preferred":false,"id":936823,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Siddons, Stephen F.","contributorId":172276,"corporation":false,"usgs":false,"family":"Siddons","given":"Stephen","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":936824,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Walrath, John D.","contributorId":204718,"corporation":false,"usgs":false,"family":"Walrath","given":"John","email":"","middleInitial":"D.","affiliations":[{"id":36596,"text":"Wyoming Game and Fish Department","active":true,"usgs":false}],"preferred":false,"id":936968,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Walters, Annika W. 0000-0002-8638-6682 awalters@usgs.gov","orcid":"https://orcid.org/0000-0002-8638-6682","contributorId":4190,"corporation":false,"usgs":true,"family":"Walters","given":"Annika","email":"awalters@usgs.gov","middleInitial":"W.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":936825,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70266781,"text":"70266781 - 2024 - An invasive predator substantially alters energy flux without changing food web functional state or stability","interactions":[],"lastModifiedDate":"2025-05-14T13:19:21.365534","indexId":"70266781","displayToPublicDate":"2024-09-01T00:00:00","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":862,"text":"Aquatic Conservation: Marine and Freshwater Ecosystems","active":true,"publicationSubtype":{"id":10}},"title":"An invasive predator substantially alters energy flux without changing food web functional state or stability","docAbstract":"Understanding how invasive species affect the stability and function of ecosystems is critical for conserving ecosystems. Here, we quantified the effect of an actively suppressed invasive species on the Yellowstone Lake, U.S.A. ecosystem using a food-web energetics approach. 2. We compared energy flux, functional state, and stability of four food web states: a pre-invasion network, and three post-invasion networks undergoing active invasive species suppression: initial invasion; expansion; decline. 3. Invasion caused > 25% change (±) in energy flux for most consumers, and total flux increased twofold post-invasion. Flux to the species of conservation concern, Yellowstone cutthroat trout (Oncorhynchus virginalis bouvieri), was 2.8-times less post-invasion vs pre-invasion while invasive lake trout (Salvelinus namaycush) flux was up to 17.3-times higher compared to the initial invasion network. The dominant functional state and food web stability did not change post-invasion, likely due to introduction of a generalist predator and the stabilizing effect of suppression. 4. Lake trout invasion in Yellowstone Lake caused large changes to energy flux, shifting dominant fluxes away from the species of conservation concern, despite not changing functional state or stability. We demonstrate that changes in energy flux may signal invasions in ecosystems, but functional state or stability may not necessarily reflect the magnitude of invasion influences. 5. Implications for conservation: For invaded fish communities, a better understanding of how the invasive species controls the food web beyond just the direct influence on prey results can be achieved by investigating energy flux, functional state, and food-web stability. Furthermore, evaluating the effect of suppression beyond the invasive species can demonstrate the far-reaching value of suppression management actions for conservation.
","language":"English","publisher":"Wiley","doi":"10.1002/aqc.4240","usgsCitation":"Glassic, H.C., Junker, J., Guy, C.S., Tronstad, L., Briggs, M., Albertson, L., Lujan, D., Brenden, T., Walsworth, T., and Koel, T., 2024, An invasive predator substantially alters energy flux without changing food web functional state or stability: Aquatic Conservation: Marine and Freshwater Ecosystems, v. 34, no. 9, e4240, 13 p., https://doi.org/10.1002/aqc.4240.","productDescription":"e4240, 13 p.","ipdsId":"IP-142967","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":490119,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/aqc.4240","text":"Publisher Index Page"},{"id":485825,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Yellowstone Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -110.60879514397,\n 44.60338974481584\n ],\n [\n -110.60879514397,\n 44.274195813940025\n ],\n [\n -110.14554498797068,\n 44.274195813940025\n ],\n [\n -110.14554498797068,\n 44.60338974481584\n ],\n [\n -110.60879514397,\n 44.60338974481584\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"34","issue":"9","noUsgsAuthors":false,"publicationDate":"2024-09-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Glassic, Hayley Corrine 0000-0001-6839-1026","orcid":"https://orcid.org/0000-0001-6839-1026","contributorId":305858,"corporation":false,"usgs":true,"family":"Glassic","given":"Hayley","email":"","middleInitial":"Corrine","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":936761,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Junker, James R.","contributorId":355003,"corporation":false,"usgs":false,"family":"Junker","given":"James R.","affiliations":[{"id":16203,"text":"Michigan Technological university","active":true,"usgs":false}],"preferred":false,"id":936762,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Guy, Christopher S. 0000-0002-9936-4781 cguy@usgs.gov","orcid":"https://orcid.org/0000-0002-9936-4781","contributorId":2876,"corporation":false,"usgs":true,"family":"Guy","given":"Christopher","email":"cguy@usgs.gov","middleInitial":"S.","affiliations":[{"id":438,"text":"National Research Program - 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2024 - Revised timing of rapid exhumation in the West Qinling: Implications for geodynamics of Oligocene-Miocene Tibetan plateau outward expansion","interactions":[],"lastModifiedDate":"2025-05-13T15:58:30.230601","indexId":"70266857","displayToPublicDate":"2024-08-31T10:50:41","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1427,"text":"Earth and Planetary Science Letters","active":true,"publicationSubtype":{"id":10}},"title":"Revised timing of rapid exhumation in the West Qinling: Implications for geodynamics of Oligocene-Miocene Tibetan plateau outward expansion","docAbstract":"Two contrasting age models for initial mountain building in the northeastern (NE) Tibetan Plateau (Paleocene-early Eocene versus late Oligocene-early Miocene) have led to the debate on how the deformed continental lithosphere absorbs plate convergence in general. The initial compressional deformation in the West Qinling (WQL) of the NE Tibetan Plateau figures prominently in this ongoing debate. Here, apatite (U-Th)/He (AHe) thermochronology combined with geomorphological analysis are used to refine the onset of compressional deformation in the WQL. New AHe ages from two vertical transects and an updated reconstruction of an obliquely-tilted erosion surface document the accelerated exhumation in the northern WQL at 23-22 Ma, interpreted as the onset of north-vergent thrusting. The AHe results, together with sedimentary records in the intermontane and foreland basins, suggest that the entire WQL began experiencing compressional deformation in the late Oligocene-early Miocene. When integrated with previous studies, our findings show that the northern plateau boundary has not remained stationary since the collision, but has instead experienced ∼750 km of outward expansion during the late Oligocene to middle Miocene. This phase of rapid plateau growth is coeval with the ∼30–50 % reduction of the India-Eurasia convergence rate, which suggests that the increased gravitational potential energy of orogenic belts played a key role in plate motion changes.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.epsl.2024.118966","usgsCitation":"Li, C., Zheng, D., Yu, J., Lease, R.O., Wang, Y., Pang, J., Wang, Y., Hao, Y., and Xu, Y., 2024, Revised timing of rapid exhumation in the West Qinling: Implications for geodynamics of Oligocene-Miocene Tibetan plateau outward expansion: Earth and Planetary Science Letters, v. 646, 118966, 9 p., https://doi.org/10.1016/j.epsl.2024.118966.","productDescription":"118966, 9 p.","ipdsId":"IP-165148","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":485826,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"China","otherGeospatial":"Tibetan plateau","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 101.5,\n 36\n ],\n [\n 101.5,\n 35\n ],\n [\n 104,\n 35\n ],\n [\n 104,\n 36\n ],\n [\n 101.5,\n 36\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"646","noUsgsAuthors":false,"publicationDate":"2024-08-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Li, Chaopeng","contributorId":355149,"corporation":false,"usgs":false,"family":"Li","given":"Chaopeng","affiliations":[{"id":84718,"text":"Institute of Geology, China Earthquake Administration","active":true,"usgs":false}],"preferred":false,"id":936937,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zheng, Dewen","contributorId":355150,"corporation":false,"usgs":false,"family":"Zheng","given":"Dewen","affiliations":[{"id":84718,"text":"Institute of Geology, China Earthquake Administration","active":true,"usgs":false}],"preferred":false,"id":936938,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yu, Jingxing","contributorId":355151,"corporation":false,"usgs":false,"family":"Yu","given":"Jingxing","affiliations":[{"id":84718,"text":"Institute of Geology, China Earthquake Administration","active":true,"usgs":false}],"preferred":false,"id":936939,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lease, Richard O. 0000-0003-2582-8966 rlease@usgs.gov","orcid":"https://orcid.org/0000-0003-2582-8966","contributorId":5098,"corporation":false,"usgs":true,"family":"Lease","given":"Richard","email":"rlease@usgs.gov","middleInitial":"O.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":936940,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wang, Yizhou","contributorId":355152,"corporation":false,"usgs":false,"family":"Wang","given":"Yizhou","affiliations":[{"id":84718,"text":"Institute of Geology, China Earthquake Administration","active":true,"usgs":false}],"preferred":false,"id":936941,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Pang, Jianzhang","contributorId":355153,"corporation":false,"usgs":false,"family":"Pang","given":"Jianzhang","affiliations":[{"id":84718,"text":"Institute of Geology, China Earthquake Administration","active":true,"usgs":false}],"preferred":false,"id":936942,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wang, Ying","contributorId":355154,"corporation":false,"usgs":false,"family":"Wang","given":"Ying","affiliations":[{"id":84718,"text":"Institute of Geology, China Earthquake Administration","active":true,"usgs":false}],"preferred":false,"id":936943,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hao, Yuqi","contributorId":355155,"corporation":false,"usgs":false,"family":"Hao","given":"Yuqi","affiliations":[{"id":84718,"text":"Institute of Geology, China Earthquake Administration","active":true,"usgs":false}],"preferred":false,"id":936944,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Xu, Yigang","contributorId":355156,"corporation":false,"usgs":false,"family":"Xu","given":"Yigang","affiliations":[{"id":84719,"text":"Guangzhou Institute of Geochemistry, Chinese Academy of Science","active":true,"usgs":false}],"preferred":false,"id":936945,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70258074,"text":"70258074 - 2024 - RegionGrow3D: A deterministic analysis for characterizing discrete three-dimensional landslide source areas on a regional scale","interactions":[],"lastModifiedDate":"2024-09-03T11:45:12.570817","indexId":"70258074","displayToPublicDate":"2024-08-31T06:43:19","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5739,"text":"Journal of Geophysical Research: Earth Surface","onlineIssn":"2169-9011","active":true,"publicationSubtype":{"id":10}},"title":"RegionGrow3D: A deterministic analysis for characterizing discrete three-dimensional landslide source areas on a regional scale","docAbstract":"Regional-scale characterization of shallow landslide hazards is important for reducing their destructive impact on society. These hazards are commonly characterized by (a) their location and likelihood using susceptibility maps, (b) landslide size and frequency using geomorphic scaling laws, and (c) the magnitude of disturbance required to cause landslides using initiation thresholds. Typically, this is accomplished through the use of inventories documenting the locations and triggering conditions of previous landslides. In the absence of comprehensive landslide inventories, physics-based slope stability models can be used to estimate landslide initiation potential and provide plausible distributions of landslide characteristics for a range of environmental and forcing conditions. However, these models are sometimes limited in their ability to capture key mechanisms tied to discrete three-dimensional (3D) landslide mechanics while possessing the computational efficiency required for broad-scale application. In this study, the RegionGrow3D (RG3D) model is developed to broadly simulate the area, volume, and location of landslides on a regional scale (≥1,000 km2) using 3D, limit-equilibrium (LE)-based slope stability modeling. Furthermore, RG3D is incorporated into a susceptibility framework that quantifies landsliding uncertainty using a distribution of soil shear strengths and their associated probabilities, back-calculated from inventoried landslides using 3D LE-based landslide forensics. This framework is used to evaluate the influence of uncertainty tied to shear strength, rainfall scenarios, and antecedent soil moisture on potential landsliding and rainfall thresholds over a large region of the Oregon Coast Range, USA.
Climate change is exacerbating shoreline erosion and flooding, posing significant risks to coastal communities. Although traditional coastal defenses such as seawalls, dykes, and breakwaters offer protection from these hazards, their high environmental and economic costs are driving interest in cost-competitive nature-based solutions. Coral reef restoration is a nature-based solution that may be particularly apt to mitigate tropical coastal flooding and shoreline erosion while providing benefits to local tourism, fisheries, and nature. However, the novelty of this field requires studies demonstrating the benefits of reefs for coastal protection. While the flood protection benefits of reefs have been well-documented, their effects on shoreline erosion are comparatively less understood. Here, we investigate the effects of coral reefs on shoreline erosion by comparing tropical beach responses at short and long timescales, as well as identifying important reef structural features influencing coastal erosion rates. Our analyses leveraged two key datasets created in this study: the first derived from a literature review on short-term shoreline erosion due to storm events, and another compiling >80 years of long-term erosion rates, bathymetry, habitat, and wave energy for the Hawaiian Islands of Kauaʻi, Oʻahu, and Maui. Our analyses reveal three key findings regarding the effects of reefs on shoreline erosion. Firstly, we find evidence for the role of reefs in mitigating shoreline erosion during storm events, with coral reef-protected beaches experiencing 97 % less beach volume loss than unprotected beaches. Secondly, a linear regression analysis demonstrates that coral reef structure and wave energy are important predictors of long-term shoreline erosion rates, explaining 34 % of the variation across the Hawaiian Islands. Consistent with prior research, we find beaches protected by coral reefs with shallow reef crests, wide reef flats, calmer offshore conditions, and positioned farther from the shore exhibit lower erosion rates than others. Finally, when comparing historical erosion rates of protected and unprotected beaches in Hawai'i, we find a seemingly incongruous pattern where coral reef-protected beaches eroded up to 2x faster than beaches without reefs. While the cause of the enhanced erosion is yet to be fully understood, a combination of coral reef structural degradation and sea-level rise is likely shifting the equilibrium profiles of reef-protected beaches inshore. These results emphasize the role of coral reefs in reducing coastal erosion during storm events while revealing contrasting erosion patterns over long timescales. Future studies would ideally broaden the scope to include various regions, utilize advanced sediment transport models, and undertake field experiments to deepen our understanding of coral reef-coupled shoreline dynamics.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.nbsj.2024.100174","usgsCitation":"Bitterwolf, S., Reguero, B., Storlazzi, C.D., and Beck, M.W., 2024, Shifting sands: The influence of coral reefs on shoreline erosion from short-term storm protection to long-term disequilibrium: Nature-Based Solutions, v. 6, no. 6, 100174, 8 p., https://doi.org/10.1016/j.nbsj.2024.100174.","productDescription":"100174, 8 p.","ipdsId":"IP-167854","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":466942,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.nbsj.2024.100174","text":"Publisher Index Page"},{"id":433437,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","issue":"6","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bitterwolf, Stephan","contributorId":245650,"corporation":false,"usgs":false,"family":"Bitterwolf","given":"Stephan","email":"","affiliations":[{"id":17620,"text":"UCSC","active":true,"usgs":false}],"preferred":false,"id":912035,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reguero, Borja","contributorId":264485,"corporation":false,"usgs":false,"family":"Reguero","given":"Borja","affiliations":[{"id":6949,"text":"University of California, Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":912036,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Storlazzi, Curt D. 0000-0001-8057-4490","orcid":"https://orcid.org/0000-0001-8057-4490","contributorId":213610,"corporation":false,"usgs":true,"family":"Storlazzi","given":"Curt","middleInitial":"D.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":912037,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Beck, Michael W.","contributorId":259298,"corporation":false,"usgs":false,"family":"Beck","given":"Michael","email":"","middleInitial":"W.","affiliations":[{"id":6949,"text":"University of California, Santa Cruz","active":true,"usgs":false}],"preferred":true,"id":912038,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70257629,"text":"ofr20231053 - 2024 - Learning from a high-severity fire event—Conditions following the 2018 Carr Fire at Whiskeytown National Recreation Area","interactions":[],"lastModifiedDate":"2026-01-28T17:31:19.551324","indexId":"ofr20231053","displayToPublicDate":"2024-08-30T12:45:57","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-1053","displayTitle":"Learning from a High-Severity Fire Event: Conditions Following the 2018 Carr Fire at Whiskeytown National Recreation Area","title":"Learning from a high-severity fire event—Conditions following the 2018 Carr Fire at Whiskeytown National Recreation Area","docAbstract":"The 2018 Carr Fire burned more than 90 percent of Whiskeytown National Recreation Area, with much of the park burning at high severity. California yellow pine and mixed conifer forests are not well adapted to large, high-severity fires, and forest recovery after these events may be problematic. Large, high-severity fire patches pose difficulties for recruitment with interiors that are long distances from potential seed trees and may develop fuel structures that can promote further high-severity fire. This report details patterns of forest structure derived from field plots measured 2–3 years after the Carr Fire, providing a characterization of immediate fire effects. We coupled these observations with remotely sensed information, including data collected from unoccupied aircraft system surveys. The remotely sensed data were used to depict erosion after the Carr Fire as well as to create a high-resolution land cover classification map, a debris flow risk map and hazard assessment, and a post-fire canopy vegetation loss map. Results indicated high levels of tree mortality after the Carr Fire, including high-value old growth forest stands, supporting remotely sensed assessments of fire severity. The high-resolution tree mortality model also aligned well with other remotely sensed estimates of immediate burn severity. Results of the land cover classification illustrated the high percentage of dead vegetation remaining in the understory and canopy 8 months post-fire. Changes in vegetation height identified areas with canopy vegetation loss from 1- to 8-months post-fire. Pairing the post-fire debris accumulation with debris flow probabilities may identify high-risk debris flow areas. The results of this study will help inform future decisions concerning wildland fire and vegetation management strategies at Whiskeytown National Recreation Area and are broadly relevant for management in the aftermath of large, high-severity fires in mixed, dry coniferous forests in the western United States.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231053","collaboration":"Prepared in cooperation with the National Park Service","programNote":"Ecosystems Mission Area—Land Change Science Program","usgsCitation":"van Mantgem, P.J., Wright, M.C., Thorne, K.M., Beckmann, J., Buffington, K., Rankin, L.L., Colley, A., and Engber, E.A., 2024, Learning from a high-severity fire event—Conditions following the 2018 Carr Fire at Whiskeytown National Recreation Area: U.S. Geological Survey Open-File Report 2023–1053, 52 p., https://doi.org/10.3133/ofr20231053.","productDescription":"Report: viii, 52 p.; 2 Data Releases","numberOfPages":"52","onlineOnly":"Y","ipdsId":"IP-145882","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":499189,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117307.htm","linkFileType":{"id":5,"text":"html"}},{"id":432970,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231053/full"},{"id":432965,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P97Y21L1","text":"USGS Data Release","description":"Wright, M.C., Engber, E., and van Mantgem, P.J., 2024, Forest conditions following the 2018 Carr Fire at Whiskeytown National Recreation Area: U.S. Geological Survey data release, available at https://doi.org/10.5066/P97Y21L1.","linkHelpText":"Forest conditions following the 2018 Carr Fire at Whiskeytown National Recreation Area"},{"id":432964,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9GS9V1J","text":"USGS Data Release","description":"Thorne, K.M., Freeman, C.M., and Rankin, L.L., 2024, UAS imagery at Whiskeytown National Recreation Area in 2018 and 2019 following the Carr Fire: U.S. Geological Survey data release, available at https://doi.org/10.5066/P9GS9V1J.","linkHelpText":"UAS imagery at Whiskeytown National Recreation Area in 2018 and 2019 following the Carr Fire"},{"id":432969,"rank":6,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1053/images"},{"id":432968,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1053/ofr20231053.xml"},{"id":432967,"rank":4,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1053/ofr20231053.pdf","text":"Report","size":"16 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":432966,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1053/covrthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Whiskeytown National Recreation Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.82661214645721,\n 40.425804364692084\n ],\n [\n -122.42999478567339,\n 40.425804364692084\n ],\n [\n -122.42999478567339,\n 40.713227651132485\n ],\n [\n -122.82661214645721,\n 40.713227651132485\n ],\n [\n -122.82661214645721,\n 40.425804364692084\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
Extraordinary floods surged down the Yellowstone River and its tributaries in northwestern Wyoming and south-central Montana on June 13–15, 2022. During the flood, U.S. Geological Survey staff worked to maintain real-time data from streamgages by making field measurements of streamflow and repairing damaged equipment while communicating the latest streamflow information with the public and with local, State, and Federal agencies. After the flood, staff surveyed high-water marks, computed peak streamflow at streamgages unreachable during the flood, and updated flood-frequency estimates for streamgages in the Upper Yellowstone River Basin. Streamflows were the highest on record at 17 streamgages in the Upper Yellowstone River Basin. River stages were highest on record at most of those streamgages. The flood-related data and analyses are summarized in this fact sheet.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20243035","collaboration":"Prepared in cooperation with the Montana Department of Natural Resources and Conservation and the Federal Emergency Management Agency","usgsCitation":"Chase, K.J., Dutton, D., Hamilton, W.B., Siefken, S.A., Vander Voort, C., and Whiteman, A., 2024, June 2022 floods in the Upper Yellowstone River Basin: U.S. Geological Survey Fact Sheet 2024–3035, 6 p., https://doi.org/10.3133/fs20243035.","productDescription":"6 p.","numberOfPages":"6","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-164447","costCenters":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"links":[{"id":433365,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/fs20243035/full"},{"id":433364,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2024/3035/images/"},{"id":433363,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2024/3035/fs20243035.XML"},{"id":433362,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2024/3035/fs20243035.pdf","text":"Report","size":"5.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2024–3035"},{"id":492687,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117264.htm","linkFileType":{"id":5,"text":"html"}},{"id":433361,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2024/3035/coverthb.jpg"}],"country":"United States","state":"Idaho, Montana, Wyoming","otherGeospatial":"Upper Yellowstone River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -111.3465081870854,\n 45.25268386886597\n ],\n [\n -111.3465081870854,\n 43.44596974043597\n ],\n [\n -108.70978943708536,\n 43.44596974043597\n ],\n [\n -108.70978943708536,\n 45.25268386886597\n ],\n [\n -111.3465081870854,\n 45.25268386886597\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Wyoming-Montana Water Science Center
U.S. Geological Survey
3162 Bozeman Avenue
Helena, MT 59601
National parks and preserves in the South Atlantic-Gulf Region contain valuable coastal habitats such as tidal wetlands and mangrove forests, as well as irreplaceable historic buildings and archeological sites located in low-lying areas. These natural and cultural resources are vulnerable to accelerated sea-level rise and escalating high tide flooding events. Through a Natural Resources Preservation Program-funded project during 2021–23, the U.S. Geological Survey, in collaboration with the National Park Service, estimated the probability of inundation at Biscayne National Park, Florida, and several other parks under various sea-level rise scenarios and contemporary high tide flooding thresholds. The maps produced for this effort can be used to assess potential habitat change and explore how infrastructure and cultural resources within the park may be exposed to future flooding-related hazards.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20243024","collaboration":"Prepared in collaboration with the National Park Service","usgsCitation":"Thurman, H.R., Enwright, N.M., Osland, M.J., Passeri, D.L., Day, R.H., Simons, B.M., Danielson, J.J., and Cushing, W.M., 2024, Projected sea-level rise and high tide flooding at Biscayne National Park, Florida: U.S. Geological Survey Fact Sheet 2024–3024, 6 p., https://doi.org/10.3133/fs20243024.","productDescription":"Report: 6 p.; Data Release","numberOfPages":"6","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-156837","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":499123,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117263.htm","linkFileType":{"id":5,"text":"html"}},{"id":462374,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/fs20243008","text":"USGS Fact Sheet 2024-3008","linkHelpText":"- Projected Sea-Level Rise and High Tide Flooding at Timucuan Ecological and Historic Preserve, Florida"},{"id":433350,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9FM6V0T","text":"USGS Data Release","linkHelpText":"Sea-level rise and high tide flooding inundation probability and depth statistics at Biscayne National Park, Florida"},{"id":433349,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2024/3024/fs20243024.pdf","text":"Report","size":"16 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2024–3024"},{"id":462377,"rank":7,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/fs20243022","text":"USGS Fact Sheet 2024-3022","linkHelpText":"- Projected Sea-Level Rise and High Tide Flooding at Big Cypress National Preserve, Florida"},{"id":462376,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/fs20243021","text":"USGS Fact Sheet 2024-3021","linkHelpText":"- Projected Sea-Level Rise and High Tide Flooding at San Juan National Historic Site, Puerto Rico"},{"id":462375,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/fs20243016","text":"USGS Fact Sheet 2024-3016","linkHelpText":"- Projected Sea-Level Rise and High Tide Flooding at De Soto National Memorial, Florida"},{"id":462378,"rank":8,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/fs20243023","text":"USGS Fact Sheet 2024-3023","linkHelpText":"- Projected Sea-Level Rise and High Tide Flooding at Dry Tortugas National Park, Florida"},{"id":433348,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2024/3024/coverthb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Biscayne National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -80.02512700796882,\n 25.761290873328747\n ],\n [\n -80.20652874795097,\n 25.746219053334585\n ],\n [\n -80.3416151500655,\n 25.65233220546078\n ],\n [\n -80.44196504877935,\n 25.166577096317894\n ],\n [\n -80.38664395077035,\n 25.123482598415634\n ],\n [\n -80.29015366354582,\n 25.224784951621928\n ],\n [\n -80.02512700796882,\n 25.761290873328747\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Wetland and Aquatic Research Center
U.S. Geological Survey
700 Cajundome Blvd.
Lafayette, LA 70506–3152
Contact Us- USGS Publications Warehouse
","tableOfContents":"The Shinnecock Indian Nation on Long Island, New York, faces challenges of shoreline retreat, saltwater intrusion, and flooding of the Tribal lands under changing climate and rising sea level. However, understanding of the dynamics of tidal circulation and waves and their impacts on the Shinnecock Indian Nation’s shoreline remains limited. This numerical study employs the integrated modeling capabilities of the hydrodynamic model Delft3D-FLOW and the spectral-wave model Simulating WAves Nearshore (SWAN) to investigate the circulation and wave dynamics along the shoreline of Shinnecock Indian Nation. The results of the 1-year long simulation indicate the majority of wind waves approach the Shinnecock Nation shorelines at normal wave angles, with yearly averaged offshore wave height of around 0.2 meter, maximum wave height reaching 0.65 meter, and yearly averaged offshore wave power of approximately 50 watts per meter. Boulders, acting as natural barriers, have been placed along the shoreline to reduce erosive wave forcing. Simulation results indicate the boulders to the north end effectively attenuate wave energy and reduce annual wave power, while the boulders near the two tidal ponds adjacent to the Tribal cemetery only have a slight influence on wave energy. There are large spatial variabilities in wave attenuation and current velocity reduction by the boulders. The model framework developed in this study can be utilized for the optimal design of nature-based solutions, guiding decisions on the placement of living shoreline structures and determining their optimal size. This study further identifies data and knowledge gaps as well as future research opportunities that can enhance the performance of numerical models and contribute to the scientific understanding of coastal processes and facilitate the optimal design of hybrid living shorelines in the future to achieve the maximum protective efficacy. This research can help to inform strategies for safeguarding vulnerable coastal communities and promoting resilience and sustainability of shoreline along the Shinnecock Indian Nation.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20241050","issn":"2331-1258","collaboration":"Prepared in collaboration with Northeastern University","usgsCitation":"Zhu, L., Wang, H., Chen, Q., Capurso, W., and Noll, M., 2024, Numerical modeling of circulation and wave dynamics along the shoreline of Shinnecock Indian Nation in Long Island, New York: U.S. Geological Survey Open-File Report 2024–1050, 32 p., https://doi.org/10.3133/ofr20241050.","productDescription":"Report: viii, 32 p.; Data Release","numberOfPages":"44","onlineOnly":"Y","ipdsId":"IP-163925","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":434899,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20241050/full","linkFileType":{"id":5,"text":"html"},"description":"OFR 2024-1050 HTML"},{"id":433221,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9OG0AAO","text":"USGS Data Release","linkHelpText":"Three-dimensional point cloud data collected with a scanning total station on the western shoreline of the Shinnecock Nation Tribal lands, Suffolk County, New York, 2022"},{"id":433217,"rank":2,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2024/1050/images"},{"id":433215,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2024/1050/coverthb.jpg"},{"id":433218,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2024/1050/ofr20241050.pdf","size":"3.53 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2024-1050"},{"id":433219,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2024/1050/ofr20241050.XML","linkFileType":{"id":8,"text":"xml"},"description":"OFR 2024-1050 XML"},{"id":499260,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117308.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"New York","otherGeospatial":"Shinnecock Indian Nation relative to Shinnecock Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -72.53273633004311,\n 40.90389205501435\n ],\n [\n -72.53273633004311,\n 40.82631366731101\n ],\n [\n -72.40468479043905,\n 40.82631366731101\n ],\n [\n -72.40468479043905,\n 40.90389205501435\n ],\n [\n -72.53273633004311,\n 40.90389205501435\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Wetland and Aquatic Research Center
U.S. Geological Survey
700 Cajundome Blvd.
Lafayette, LA 70506–3152
Contact Us- USGS Publications Warehouse
","tableOfContents":"No abstract available.
","language":"English","publisher":"Earth ArXiv","doi":"10.31223/X59Q6Q","usgsCitation":"Maher, S., Glasgow, M.E., Cochran, E.S., and Peng, Z., 2024, Distinguishing natural sources from anthropogenic noise in seismic data: EarthArXiv, https://doi.org/10.31223/X59Q6Q.","productDescription":"18 p.","ipdsId":"IP-167863","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":439185,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.31223/x59q6q","text":"External Repository"},{"id":434829,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Maher, Sean","contributorId":265979,"corporation":false,"usgs":false,"family":"Maher","given":"Sean","affiliations":[{"id":54850,"text":"Department of Earth Science and Earth Research Institute, University of California, Santa Barbara, Santa Barbara, CA, USA","active":true,"usgs":false}],"preferred":false,"id":913230,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Glasgow, Margaret Elizabeth 0000-0001-5637-5918","orcid":"https://orcid.org/0000-0001-5637-5918","contributorId":340268,"corporation":false,"usgs":true,"family":"Glasgow","given":"Margaret","email":"","middleInitial":"Elizabeth","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":913231,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cochran, Elizabeth S. 0000-0003-2485-4484 ecochran@usgs.gov","orcid":"https://orcid.org/0000-0003-2485-4484","contributorId":2025,"corporation":false,"usgs":true,"family":"Cochran","given":"Elizabeth","email":"ecochran@usgs.gov","middleInitial":"S.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":913232,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Peng, Zhigang","contributorId":199689,"corporation":false,"usgs":false,"family":"Peng","given":"Zhigang","email":"","affiliations":[],"preferred":false,"id":913233,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70257769,"text":"sir20235104 - 2024 - Estimated reductions in phosphorus loads from removal of leaf litter in the Lake Champlain drainage area, Vermont","interactions":[],"lastModifiedDate":"2026-01-30T18:20:39.416851","indexId":"sir20235104","displayToPublicDate":"2024-08-30T09:00:00","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":"2023-5104","displayTitle":"Estimated Reductions in Phosphorus Loads From Removal of Leaf Litter in the Lake Champlain Drainage Area, Vermont","title":"Estimated reductions in phosphorus loads from removal of leaf litter in the Lake Champlain drainage area, Vermont","docAbstract":"Excess nutrient loading and other factors are driving eutrophication and other negative effects on water-quality conditions in Lake Champlain and other receiving waters in Vermont. Two common best management practices were evaluated to determine how these practices can be optimized by targeting maintenance and operation to align better with seasonally driven needs, specifically to help municipalities remove a greater proportion of seasonal leaves and organic debris, reduce nutrient loading, and achieve water-quality goals.
To characterize solid materials typically removed by the municipal BMPs of catch-basin (CB) cleaning and street cleaning (SC), subsamples of CB and SC materials were collected each month from nine participating municipalities in central and northwestern Vermont between September 2017 and November 2018. Monthly and seasonal composites of CB and SC samples were created from the subsamples of available materials from all municipalities. Samples were analyzed for concentrations of total organic carbon, total Kjeldahl nitrogen, and total phosphorus (P), and separated into three particle-size fractions. Distribution of particle-size fractions was similar between CB and SC as both practices generally collect the coarser fraction of solid materials (greater than 125 micrometers in diameter). In the fall, however, the range of the coarser fraction of materials increased. This is attributed to the ability of SC to collect leaves and other light organic materials that commonly pass through a CB system designed to trap heavier materials.
Total organic carbon, total Kjeldahl nitrogen, and total P concentrations were highest in the catch-basin samples in the fall of 2017, and concentrations in the SC samples were highest in the fall of 2018. The collection of fewer samples in 2017 may account for some of the variability between fall 2017 and fall 2018 results. A subset of SC samples collected from piles representing specific street-cleaning routes in September and November 2018 were also analyzed. Materials collected in November were dominated by leaves, and the concentrations of the analyzed species of carbon, nitrogen, and phosphorus in some samples were more than double those in samples collected on the same street-cleaning routes in September.
The Vermont Department of Environmental Conservation and the University of Vermont developed estimates of load-reduction credits for CB and SC practices based on a policy developed by the Wisconsin Department of Natural Resources that determined the potential for credits associated with leaf-removal activities. This process also considered BMPs that were initiated during the U.S. Environmental Protection Agency’s Lake Champlain Basin Total Maximum Daily Load monitoring period (2000 to 2009) and adapted the Wisconsin Department of Natural Resources policies to apply to existing SC routes in the cooperating Vermont municipalities that possessed at least 17 percent tree cover. This exercise demonstrated that applying the Wisconsin Department of Natural Resources policy to existing street-cleaning routes possessing 17 percent or more tree cover would result in reductions in total P loads up to 65 percent of mandated target reductions, and about a 25 percent reduction on average.
Continuous simulations of stormwater runoff volume, and of loads of suspended sediments and total P, also were created for Englesby Brook Basin, an urbanized basin in Burlington and South Burlington that drains to Lake Champlain. Although the basin is more developed than the average of the nine cooperating municipalities, streamflow and P loading data collected by the U.S. Geological Survey were available to evaluate model performance. Simulations based on a year of average climatic conditions projected potential small reductions in total P of 0.08 to 0.10 percent as a result of CB cleaning and SC practices. Simulated weekly SC practices, however, reduced street-solid loads by as much as 7 percent. When the proportion of total P seen in fall SC materials collected in Vermont was applied to these simulated street-solid loads, estimated reductions of total P were about 29 percent. The combination of analytical results, estimated load-reduction credits, and simulated reductions indicate that targeted increases of SC activities to reduce leaf loading in the fall have the potential to reduce loading to receiving waters and could help regulated communities meet their water-quality goals.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235104","collaboration":"Prepared in cooperation with the Chittenden County Regional Planning Committee, the City of South Burlington, and the Vermont Department of Environmental Conservation","usgsCitation":"Sorenson, J.R., Pease, J.M., Foote, J.K., Chalmers, A.T., Ainley, D.H., and Williams, C.J., 2024, Estimated reductions in phosphorus loads from removal of leaf litter in the Lake Champlain drainage area, Vermont: U.S. Geological Survey Scientific Investigations Report 2023–5104, 46 p., https://doi.org/10.3133/sir20235104.","productDescription":"Report: viii, 46 p.; Data Release","numberOfPages":"46","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-121578","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":433177,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9A44LIX","text":"USGS data release","linkHelpText":"Data supporting phosphorus load-reduction estimates from leaf-litter removal in central and northwestern Vermont"},{"id":499382,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117265.htm","linkFileType":{"id":5,"text":"html"}},{"id":433176,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5104/sir20235104.XML","description":"SIR 2023-5104 XML"},{"id":433174,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235104/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2023-5104 HTML"},{"id":433173,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5104/sir20235104.pdf","text":"Report","size":"9.40 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5104 PDF"},{"id":433164,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5104/coverthb.jpg"},{"id":433175,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5104/images/"}],"country":"United States","state":"Vermont","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -73.3,\n 44.875\n ],\n [\n -73.3,\n 44.15\n ],\n [\n -72.5,\n 44.15\n ],\n [\n -72.5,\n 44.875\n ],\n [\n -73.3,\n 44.875\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
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The U.S. Geological Survey hosted a Mississippi River Science Forum with Federal agencies; Tribal, State, and local governments located in States that border the Mississippi River; academia; and other interested stakeholders. The purpose of the forum was to share current (2023) science; identify data gaps and areas of concern; and to prioritize next steps needed to advance the goals of improving water quality, restoring habitat and natural systems, improving navigation, eliminating aquatic invasive species, and building local resilience to natural disasters along the Mississippi River. The forum was a directive for the U.S. Geological Survey in the Consolidated Appropriations Act of 2022 (Public Law 117—103, 136 Stat. 49).
Participants and stakeholders that attended the Mississippi River Science Forum indicated the following.
This report highlights data gaps and areas of concern discussed during the forum, and it identifies needs to advance the goals of improving water quality, restoring habitat and natural systems, improving navigation, eliminating aquatic invasive species, and building local resilience to natural disasters with specific emphasis on data collection and measurement, and scientific investigation. The report also summarizes stakeholder input and feedback and outlines next steps identified by forum participants.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20241053","usgsCitation":"Nelson, J.C., Rebich, R.A., Jankowski, K., Edwards, T.M., Larson, J.H., Robertson, D.M., Sprague, L.A., Stackpoole, S.M., Summers, K.M., Cinotto, P.J., Rydlund, P.H., Churchill, C.J., Daniel, W.M., Mckenna, O.P., Middleton, B.A.,\nCarter, J., Hartley, S.B., Frey, J.W., and Warner, K.L., 2024, U.S. Geological Survey Mississippi River Science Forum—Summary of data and science needs and next steps: U.S. Geological Survey Open-File Report 2024–1053, 4 p.,\nhttps://doi.org/10.3133/ofr20241053.","productDescription":"iii, 4 p.","numberOfPages":"12","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-159348","costCenters":[{"id":82110,"text":"Midcontinent Regional Director's Office","active":true,"usgs":true}],"links":[{"id":433267,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20241053/full"},{"id":433266,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2024/1053/images/"},{"id":433265,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2024/1053/ofr20241053.XML"},{"id":433264,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2024/1053/ofr20241053.pdf","text":"Report","size":"1.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2024–1053"},{"id":433263,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2024/1053/coverthb.jpg"}],"otherGeospatial":"Mississippi River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.59374999999999,\n 30.14512718337613\n ],\n [\n -90.263671875,\n 31.12819929911196\n ],\n [\n -90.52734374999999,\n 33.063924198120645\n ],\n [\n -88.505859375,\n 35.460669951495305\n ],\n [\n -86.66015624999999,\n 35.10193405724606\n ],\n [\n -84.0234375,\n 35.31736632923788\n ],\n [\n -81.82617187499999,\n 36.73888412439431\n ],\n [\n -79.89257812499999,\n 37.996162679728116\n ],\n [\n -78.92578124999999,\n 39.70718665682654\n ],\n [\n -76.201171875,\n 42.032974332441405\n ],\n [\n -76.025390625,\n 42.87596410238256\n ],\n [\n -77.080078125,\n 42.87596410238256\n ],\n [\n -79.189453125,\n 41.31082388091818\n ],\n [\n -83.232421875,\n 40.38002840251183\n ],\n [\n -86.748046875,\n 41.178653972331674\n ],\n [\n -88.41796875,\n 41.376808565702355\n ],\n [\n -89.296875,\n 44.402391829093915\n ],\n [\n -90.17578124999999,\n 44.33956524809713\n ],\n [\n -89.384765625,\n 46.558860303117164\n ],\n [\n -92.900390625,\n 46.49839225859763\n ],\n [\n -93.955078125,\n 47.69497434186282\n ],\n [\n -96.767578125,\n 46.01222384063236\n ],\n [\n -103.18359375,\n 48.69096039092549\n ],\n [\n -109.86328125,\n 49.15296965617042\n ],\n [\n -112.06054687499999,\n 48.980216985374994\n ],\n [\n -112.763671875,\n 48.86471476180277\n ],\n [\n -112.412109375,\n 47.754097979680026\n ],\n [\n -111.97265625,\n 46.31658418182218\n ],\n [\n -112.32421875,\n 45.398449976304086\n ],\n [\n -113.5546875,\n 45.460130637921004\n ],\n [\n -111.796875,\n 44.08758502824516\n ],\n [\n -108.369140625,\n 42.16340342422401\n ],\n [\n -105.46875,\n 41.50857729743935\n ],\n [\n -105.29296874999999,\n 39.90973623453719\n ],\n [\n -105.8203125,\n 39.436192999314095\n ],\n [\n -105.29296874999999,\n 38.54816542304656\n ],\n [\n -104.58984375,\n 36.31512514748051\n ],\n [\n -105.1171875,\n 35.88905007936091\n ],\n [\n -105.29296874999999,\n 35.38904996691167\n ],\n [\n -103.095703125,\n 32.84267363195431\n ],\n [\n -99.931640625,\n 32.175612478499325\n ],\n [\n -95.625,\n 31.653381399664\n ],\n [\n -93.955078125,\n 31.052933985705163\n ],\n [\n -93.955078125,\n 29.458731185355344\n ],\n [\n -90.52734374999999,\n 28.459033019728043\n ],\n [\n -88.857421875,\n 28.536274512989916\n ],\n [\n -88.59374999999999,\n 30.14512718337613\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Midcontinent Regional Director’s Office
U.S. Geological Survey
1992 Folwell Avenue
St. Paul, MN 55108
One of the most significant features of the Northwest Atlantic, the Gulf Stream influences high magnitude environmental fluctuations in deep habitats across the South Atlantic Bight. Amid this variability, the Blake Plateau harbors extensive reefs formed by cold-water corals that were previously assumed to rely on narrow ranges of temperature, currents, and particulate supply. A benthic lander collected near-bed conditions at the Richardson Reef Complex, a cold-water reef dominated by the scleractinian Desmophyllum pertusum at 830 m within the path of the Gulf Stream. Specific behavior of the Gulf Stream resulted in recurring environmental patterns at depth. During offshore meanders, deep stream components intruded onto the reef and caused rapid (3.74°C per hour) temperature increases up to 10.8°C (> 5°C above the site mean) and increased chlorophyll. Within 2 d of peak temperatures, intrusions were replaced by strong, turbid upwelling currents that rapidly cooled the site to temperature minima (4.13°C). While considerable environmental variability from the Gulf Stream may otherwise implicate a thermally stressful setting for corals, high-temperature events were likely mitigated by their short duration (< 37.4 h) and physical coupling with enhanced organic material. This hypothesis was supported by high-density clustering of D. pertusum occurrences within 50 km around the Gulf Stream's position along the South Atlantic Bight. This suggests that cold-water corals experiencing environmental variability can be sustained by relationships between food supply, temperature, and currents that vary in strength along stochastic time scales, shedding further light on the niche of cold-water corals.
To assess changes in substrate conditions and the efficacy of artificially placed substrates at select sites on the Kootenai River near Bonners Ferry, Idaho, the U.S. Geological Survey, in cooperation with the Kootenai Tribe of Idaho, completed repeat bathymetric, velocimetric, and underwater videography surveys. Collectively, three project sites throughout the Kootenai River make up the Substrate Enhancement Pilot Project (SEPP), an effort intended to improve spawning and egg incubation viability at locations identified to be aquatic habitat limited for the endangered Kootenai River white sturgeon (Acipenser transmontanus). Following the placement of coarse substrates at each site, bathymetric, velocimetric, and underwater videography data were collected from 2012 to 2022 to assess the role of deposition and erosion on maintaining suitable white sturgeon spawning and incubation substrates. Minimal erosion and deposition occurred at all Substrate Enhancement Pilot Project sites, according to interannual and intra-annual net volumetric changes between bathymetric surveys. Depending on the timing of bathymetric surveys relative to the annual peak streamflow conditions, isolated locations of deposition or erosion were observed at each site and the potential for deposition or erosion was supported by measured mean depth-averaged velocities. This study concluded that variability of deposition and scour were common at each site throughout the monitoring period and may be attributed to fluctuations in streamflow. Repeat bathymetric, underwater videography, and velocity mapping surveys were used to verify the interstitial spaces and surfaces of substrates at each SEPP site remained free of fine sediments for intervals longer than a year but were susceptible to deposition between high streamflow events.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245070","collaboration":"Prepared in cooperation with the Kootenai Tribe of Idaho","usgsCitation":"Dudunake, T.J., 2024, Substrate Enhancement Pilot Project—Monitoring summary and evaluation, Kootenai River, Idaho, 2012–22 (ver. 1.1, March 6, 2025): U.S. Geological Survey Scientific Investigations Report 2024–5070, 18 p., https://doi.org/10.3133/sir20245070.","productDescription":"Report: vii, 18 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-150368","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":492698,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117304.htm","linkFileType":{"id":5,"text":"html"}},{"id":433328,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7ZC824R","text":"USGS data release","description":"USGS data release","linkHelpText":"Kootenai river substrate enhancement pilot projects near Bonners Ferry, ID (ver. 3.0, January 2023)"},{"id":433326,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5070/sir20245070.pdf","text":"Report","size":"12 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2024-5070"},{"id":433325,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5070/coverthb.jpg"},{"id":433330,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2024/5070/sir20245070.XML"},{"id":483010,"rank":7,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2024/5070/VersionHistory.txt","description":"Version History"},{"id":433329,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2024/5070/images"},{"id":433332,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20245070/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2024-5070"}],"country":"United States","state":"Idaho","otherGeospatial":"Kootenai River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -116.10215863331214,\n 48.646078728701696\n ],\n [\n -116.10215863331214,\n 48.83333398808213\n ],\n [\n -116.46984612347813,\n 48.83333398808213\n ],\n [\n -116.46984612347813,\n 48.646078728701696\n ],\n [\n -116.10215863331214,\n 48.646078728701696\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","edition":"Version 1.0: August 29, 2024; Version 1.1: March 6, 2025","contact":"Director, Idaho Water Science Center
U.S. Geological Survey
230 Collins Rd
Boise, Idaho 83702-4520
Paleoenvironmental data are essential for reconstructing environmental conditions in the distant past, and these reconstructions strongly depend on proxies and age–depth models. Proxies are indirect measurements that substitute for variables that cannot be directly measured, such as past precipitation. Conversely, an age–depth model is a tool that correlates the observed proxy with a specific moment in time. Bayesian age–depth modelling has proved to be a powerful method for estimating sediment ages and their associated uncertainties. However, there remains considerable potential for further integration into proxy analysis. In this paper, we explore a mathematical justification and a computational approach that integrates uncertainty at the age–depth level and propagates it to the proxy scale in the form of a posterior predictive distribution. This method mitigates potential biases and errors by removing the need to assign a single age to a given proxy measurement. It allows for quantifying the likelihood that proxy data values correspond to modelled ages, thus enabling the quantification of uncertainty in both the temporal and proxy value domains. The use of Bayesian statistics in proxy analysis represents a relatively recent advancement. We aim to mathematically justify incorporating the Markov chain Monte Carlo output from age–depth models into proxy analysis and to present a novel methodology for constructing environmental reconstructions using this approach.
","language":"English","publisher":"Springer","doi":"10.1007/s13253-024-00647-5","usgsCitation":"Aquino-Lopez, M.A., Anderson, L., Sanchez-Cabeza, J., Ruiz-Fernandez, A.C., and Christen, J.A., 2024, Bayesian approaches to proxy uncertainty quantification in paleoecology: A mathematical justification and practical integration: Journal of Agricultural, Biological and Environmental Statistics, v. 31, p. 162-175, https://doi.org/10.1007/s13253-024-00647-5.","productDescription":"14 p.","startPage":"162","endPage":"175","ipdsId":"IP-153062","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":463766,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":466943,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://dx.doi.org/10.1007/s13253-024-00647-5","text":"Publisher Index Page"}],"volume":"31","noUsgsAuthors":false,"publicationDate":"2024-08-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Aquino-Lopez, Marco A.","contributorId":346064,"corporation":false,"usgs":false,"family":"Aquino-Lopez","given":"Marco","email":"","middleInitial":"A.","affiliations":[{"id":82759,"text":"Cabridge University, UK","active":true,"usgs":false}],"preferred":false,"id":917924,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, Lysanna 0000-0001-5650-9744 landerson@usgs.gov","orcid":"https://orcid.org/0000-0001-5650-9744","contributorId":5339,"corporation":false,"usgs":true,"family":"Anderson","given":"Lysanna","email":"landerson@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":917925,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sanchez-Cabeza, Joan-Albert","contributorId":346065,"corporation":false,"usgs":false,"family":"Sanchez-Cabeza","given":"Joan-Albert","email":"","affiliations":[{"id":82761,"text":"CIMAT","active":true,"usgs":false}],"preferred":false,"id":917926,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ruiz-Fernandez, Ana Carolina","contributorId":346066,"corporation":false,"usgs":false,"family":"Ruiz-Fernandez","given":"Ana","email":"","middleInitial":"Carolina","affiliations":[{"id":82761,"text":"CIMAT","active":true,"usgs":false}],"preferred":false,"id":917927,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Christen, J. Andres","contributorId":346067,"corporation":false,"usgs":false,"family":"Christen","given":"J.","email":"","middleInitial":"Andres","affiliations":[{"id":82761,"text":"CIMAT","active":true,"usgs":false}],"preferred":false,"id":917928,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70257885,"text":"70257885 - 2024 - Methane emissions associated with bald cypress knees across the Mississippi River Alluvial Valley","interactions":[],"lastModifiedDate":"2024-08-30T12:26:31.615205","indexId":"70257885","displayToPublicDate":"2024-08-29T07:24:59","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3750,"text":"Wetlands","onlineIssn":"1943-6246","printIssn":"0277-5212","active":true,"publicationSubtype":{"id":10}},"title":"Methane emissions associated with bald cypress knees across the Mississippi River Alluvial Valley","docAbstract":"In freshwater forested wetlands, bald cypress knees (Taxodium distichum (L.) Rich.) have the potential to emit large amounts of methane (CH4), but only a few studies have examined their greenhouse gas contribution. In this study, we measured CH4 fluxes associated with cypress knees across various climate and flooding gradients of the Mississippi River Alluvial Valley in southcentral United States. Greenhouse gases were measured using a portable gas analyzer with a custom-made chamber placed over the knees. We also conducted 3D lidar scans of knees using a smartphone to estimate the surface area and volume of knees. We investigated the following: (1) What parameters influence CH4 fluxes (i.e., knee height, distance to stream, temperature, relative humidity, water level, precipitation)? and (2) Which type of knee shape measurement (i.e., cone, frustrum, or lidar scan) provides the best fit to model data while maximizing measurement efficiency? We found that knee CH4 flux rates ranged from − 0.005 to 182 mmol m− 2 d− 1. There were positive correlations between CH4 fluxes, water levels, and temperature, and a negative correlation with knee height. Sites that had been dry for longer periods of time emitted less CH4 than sites where the soil remained saturated. The frustrum shape produced a knee volume estimate that was within 12% of lidar scans, whereas cone shapes underestimate knee dimensions (-100%). Further research of emissions and fluxes in cypress knees could fill knowledge gaps within the carbon cycle and could represent a major component of wetland CH4 budgets.
Coastal imaging systems have been developed to measure wave runup and total water level (TWL) at the shoreline, which is a key metric for assessing coastal flooding and erosion. However, extracting quantitative measurements from coastal images has typically been done through the laborious task of hand-digitization of wave runup timestacks. Timestacks are images created by sampling a cross-shore array of pixels from an image through time as waves propagate towards and run up a beach. We utilize over 7000 hand-digitized timestacks from six diverse locations to train and validate machine learning models to automate the process of TWL extraction. Using these data, we evaluate two deep learning model architectures for the task of runup detection. One is based on a fully convolutional architecture trained from scratch, and the other is a transformer-based architecture trained using transfer learning. The deep learning models provide a probability of each pixel being either wet or dry. When contoured at the 50% level (equal chance of being wet or dry), the deep learning models more accurately identified TWL maxima than minima at all sites. This resulted in accurate predictions of 2% exceedance runup, but under predictions of significant swash and over predictions of wave setup. Improved agreement with the complete TWL time series was obtained through post-processing by utilizing the wet/dry probability of each pixel to weight the contouring toward lower dryness probabilities for runup minima (maxima agreed well with observations without tuning). Overall, a transformer-based model using transfer learning provided the best agreement with wave runup statistics, including a) the 2% exceedance runup, b) significant swash, and c) wave setup at the shoreline. For a random subset of images, the model was found to be within the uncertainty range of hand-digitization. The relative success of the transfer learning model suggests that fine-tuning a large model has advantages compared to training a smaller model from scratch. Models provide per-pixel probabilistic estimates in less than 10 s per timestack on a single computational unit, versus the more than 5 min required for hand-digitization. The model is therefore well-suited for near real-time applications, allowing for the development of early warning systems for difficult to forecast events. Real-time wave runup and total water level observations can also be incorporated into coastal hazards forecasts for data assimilation and continual model validation and improvement.
The emergence of white-nose syndrome (WNS) in North America has resulted in mass mortalities of hibernating bats and total extirpation of local populations. The need to mitigate this disease has stirred a significant body of research to understand its pathogenesis. Pseudogymnoascus destructans, the causative agent of WNS, is a psychrophilic (cold-loving) fungus that resides within the class Leotiomycetes, which contains mainly plant pathogens and is unrelated to other consequential pathogens of animals. In this review, we revisit the unique biology of hibernating bats and P. destructans and provide an updated analysis of the stages and mechanisms of WNS progression. The extreme life history of hibernating bats, the psychrophilic nature of P. destructans, and its evolutionary distance from other well-characterized animal-infecting fungi translate into unique host–pathogen interactions, many of them yet to be discovered.
Climate change is expected to influence aquatic habitats and associated fish populations, yet we know little about the impact on recreational anglers. Our goal was to explore whether interannual fluctuations in waterbody surface area and other explanatory variables could be used as indicators of changes in angler fishing effort. Our approach leveraged a combination of remotely sensed waterbody surface area, environmental and fish population data, and onsite angler survey monitoring data for Devils Lake, North Dakota, USA during the open-water fishing period (May 1st to August 31st) for 9 years (1992–2021). The information was used to develop a dynamic waterbody size-angler effort model. Changes in waterbody surface area reliably predicted changes in angler effort (r2 = 0.60). Increases in waterbody surface area led to increases in angler effort, and decreases in waterbody surface area led to decreases in angler effort. Our findings show promise that remotely sensed fluctuations in waterbody surface area could be used as an indicator of interannual angler effort dynamics. Dynamic waterbody size-angler effort models could provide managers the ability to predict changes in angler effort via climate-related hydrological cycles that affect the size and distribution of waterbodies on the landscape.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.fishres.2024.107156","usgsCitation":"Maldonado, M., Mahmood, T., Coulter, D., Coulter, A., Chipps, S.R., Siller, M., Neal, M., Saha, A., and Kaemingk, M., 2024, Water-level changes impact angler effort in a large lake: Implications for climate change: Fisheries Research, v. 279, 107156, 5 p., https://doi.org/10.1016/j.fishres.2024.107156.","productDescription":"107156, 5 p.","ipdsId":"IP-160734","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":466947,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://dx.doi.org/10.1016/j.fishres.2024.107156","text":"Publisher Index Page"},{"id":466011,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Dakota","otherGeospatial":"Devils Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -99.36050675879237,\n 48.39597416139583\n ],\n [\n -99.36050675879237,\n 47.77201003721444\n ],\n [\n -98.24927832713699,\n 47.77201003721444\n ],\n [\n -98.24927832713699,\n 48.39597416139583\n ],\n [\n -99.36050675879237,\n 48.39597416139583\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"279","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Maldonado, Matthew L.","contributorId":347887,"corporation":false,"usgs":false,"family":"Maldonado","given":"Matthew L.","affiliations":[{"id":17628,"text":"University of North Dakota","active":true,"usgs":false}],"preferred":false,"id":922731,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mahmood, Taufique H.","contributorId":347888,"corporation":false,"usgs":false,"family":"Mahmood","given":"Taufique H.","affiliations":[{"id":17628,"text":"University of North Dakota","active":true,"usgs":false}],"preferred":false,"id":922732,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Coulter, David P.","contributorId":347889,"corporation":false,"usgs":false,"family":"Coulter","given":"David P.","affiliations":[{"id":5089,"text":"South Dakota State University","active":true,"usgs":false}],"preferred":false,"id":922733,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Coulter, Alison A.","contributorId":347890,"corporation":false,"usgs":false,"family":"Coulter","given":"Alison A.","affiliations":[{"id":5089,"text":"South Dakota State University","active":true,"usgs":false}],"preferred":false,"id":922734,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chipps, Steven R. 0000-0001-6511-7582 steve_chipps@usgs.gov","orcid":"https://orcid.org/0000-0001-6511-7582","contributorId":2243,"corporation":false,"usgs":true,"family":"Chipps","given":"Steven","email":"steve_chipps@usgs.gov","middleInitial":"R.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":922735,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Siller, Maddy K.","contributorId":347891,"corporation":false,"usgs":false,"family":"Siller","given":"Maddy K.","affiliations":[{"id":5089,"text":"South Dakota State University","active":true,"usgs":false}],"preferred":false,"id":922736,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Neal, Michaela L.","contributorId":347892,"corporation":false,"usgs":false,"family":"Neal","given":"Michaela L.","affiliations":[{"id":17628,"text":"University of North Dakota","active":true,"usgs":false}],"preferred":false,"id":922737,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Saha, Ayon","contributorId":347893,"corporation":false,"usgs":false,"family":"Saha","given":"Ayon","affiliations":[{"id":17628,"text":"University of North Dakota","active":true,"usgs":false}],"preferred":false,"id":922738,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kaemingk, Mark A.","contributorId":347895,"corporation":false,"usgs":false,"family":"Kaemingk","given":"Mark A.","affiliations":[{"id":17628,"text":"University of North Dakota","active":true,"usgs":false}],"preferred":false,"id":922739,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70256185,"text":"70256185 - 2024 - Supporting climate adaptation for rural Mekong River Basin communities in Thailand","interactions":[],"lastModifiedDate":"2024-08-28T15:09:21.686987","indexId":"70256185","displayToPublicDate":"2024-08-28T09:57:19","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2764,"text":"Mitigation and Adaptation Strategies for Global Change","active":true,"publicationSubtype":{"id":10}},"title":"Supporting climate adaptation for rural Mekong River Basin communities in Thailand","docAbstract":"Climate change impacts on large river basins, such as the Mekong River Basin (MRB), are complex due to shared governance and interconnected socioeconomic areas, making them highly vulnerable to change. The MRB, spanning six countries including Thailand, is crucial for the food and economic security of > 60 million people. However, in 2021, Thailand was ranked as the 9th highest risk country affected by climate change. To integrate climate adaptation in Thailand's MRB, we examined the effects of climate change on rapidly developing farmer and fisher communities in northeastern Thailand and explored feasible adaptation options. Using an interdisciplinary approach that included literature review, participatory action methods, and the resist-accept-direct (RAD) framework, we found that climate change is projected to increase temperatures, precipitation, extreme events, erosion, and water clarity, while decreasing heavy sediment transport. These changes negatively impact agriculture, fisheries, human health, and tourism. We identified several adaptation strategies across environmental, ecological, and human health categories to accommodate local needs, such as preventing habitat degradation (e.g., from dams and deforestation), providing fish refuge and passage, and supporting technical capacity. Community-driven adaptation planning and implementation are essential for supporting global sustainable development in a changing climate.
","language":"English","publisher":"Springer","doi":"10.1007/s11027-024-10154-0","usgsCitation":"Embke, H.S., Lynch, A., and Beard, 2024, Supporting climate adaptation for rural Mekong River Basin communities in Thailand: Mitigation and Adaptation Strategies for Global Change, v. 29, 67, 29 p., https://doi.org/10.1007/s11027-024-10154-0.","productDescription":"67, 29 p.","ipdsId":"IP-153560","costCenters":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true},{"id":65882,"text":"Midwest Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":433249,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Thailand","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 103.58713075502806,\n 18.415675046149772\n ],\n [\n 103.25074086691765,\n 18.334290245472285\n ],\n [\n 102.68316462566526,\n 17.813439961628113\n ],\n [\n 102.59999202106795,\n 17.84871117664857\n ],\n [\n 102.60900709222325,\n 17.95083485538415\n ],\n [\n 102.33917708734333,\n 18.048914557116312\n ],\n [\n 102.13127818612654,\n 18.217320023448924\n ],\n [\n 101.84223130367957,\n 18.12127146242109\n ],\n [\n 101.84381496679299,\n 17.360034521893695\n ],\n [\n 103.50389523271065,\n 17.326503169572362\n ],\n [\n 103.58713075502806,\n 18.415675046149772\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"29","noUsgsAuthors":false,"publicationDate":"2024-08-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Embke, Holly Susan 0000-0002-9897-7068","orcid":"https://orcid.org/0000-0002-9897-7068","contributorId":270754,"corporation":false,"usgs":true,"family":"Embke","given":"Holly","email":"","middleInitial":"Susan","affiliations":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":907028,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lynch, Abigail 0000-0001-8449-8392 ajlynch@usgs.gov","orcid":"https://orcid.org/0000-0001-8449-8392","contributorId":169460,"corporation":false,"usgs":true,"family":"Lynch","given":"Abigail","email":"ajlynch@usgs.gov","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":907029,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Beard, Jr. 0000-0003-2632-2350 dbeard@usgs.gov","orcid":"https://orcid.org/0000-0003-2632-2350","contributorId":169459,"corporation":false,"usgs":true,"family":"Beard","suffix":"Jr.","email":"dbeard@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":907030,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70260831,"text":"70260831 - 2024 - Hair mercury isotopes, a noninvasive biomarker for dietary methylmercury exposure and biological uptake","interactions":[],"lastModifiedDate":"2024-11-27T16:05:26.865603","indexId":"70260831","displayToPublicDate":"2024-08-28T09:51:02","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9161,"text":"Environmental Science: Processes & Impacts","active":true,"publicationSubtype":{"id":10}},"title":"Hair mercury isotopes, a noninvasive biomarker for dietary methylmercury exposure and biological uptake","docAbstract":"Background. Fish and rice are the main dietary sources of methylmercury (MeHg); however, rice does not contain the same beneficial nutrients as fish, and these differences can impact the observed health effects of MeHg. Hence, it is important to validate a biomarker, which can distinguish among dietary MeHg sources. Methods. Mercury (Hg) stable isotopes were analyzed in hair samples from peripartum mothers in China (n = 265). Associations between mass dependent fractionation (MDF) (δ202Hg) and mass independent fractionation (MIF) (Δ199Hg) (dependent variables) and dietary MeHg intake (independent variable) were investigated using multivariable regression models. Results. In adjusted models, hair Δ199Hg was positively correlated with serum omega-3 fatty acids (a biomarker for fish consumption) and negatively correlated with maternal rice MeHg intake, indicating MIF recorded in hair can be used to distinguish MeHg intake predominantly from fish versus rice. Conversely, in adjusted models, hair δ202Hg was not correlated with measures of dietary measures of MeHg intake. Instead, hair δ202Hg was strongly, negatively correlated with hair Hg, which explained 27–29% of the variability in hair δ202Hg. Conclusions. Our results indicated that hair Δ199Hg can be used to distinguish MeHg intake from fish versus rice. Results also suggested that lighter isotopes were preferentially accumulated in hair, potentially reflecting Hg binding to thiols (i.e., cysteine); however, more research is needed to elucidate this hypothesis. Broader impacts include 1) validation of a non-invasive biomarker to distinguish MeHg intake from rice versus fish, and 2) the potential to use Hg isotopes to investigate Hg binding in tissues.
","language":"English","publisher":"Royal Society of Chemistry","doi":"10.1039/D4EM00231H","usgsCitation":"Rothenburg, S.E., Korrick, S.A., Harrington, D., Thurston, S.W., Janssen, S., Tate, M., Nong, Y., Nong, H., Liu, J., Hong, C., and Ouyang, F., 2024, Hair mercury isotopes, a noninvasive biomarker for dietary methylmercury exposure and biological uptake: Environmental Science: Processes & Impacts, v. 26, p. 1975-1985, https://doi.org/10.1039/D4EM00231H.","productDescription":"11 p.","startPage":"1975","endPage":"1985","ipdsId":"IP-167813","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":497361,"rank":2,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC11560691/","text":"External Repository"},{"id":463874,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"26","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Rothenburg, Sarah E","contributorId":346139,"corporation":false,"usgs":false,"family":"Rothenburg","given":"Sarah","email":"","middleInitial":"E","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":918234,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Korrick, Susan A","contributorId":346141,"corporation":false,"usgs":false,"family":"Korrick","given":"Susan","email":"","middleInitial":"A","affiliations":[{"id":82779,"text":"Harvard T.H. 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Because of its unique ability to provide direct information on subsurface mass/density changes over time, gravimetry has important advantages over other volcano-monitoring techniques. As an example, if pre-eruptive magma accumulation occurs in voids, surface uplift or seismicity may not occur because the stress transmitted to the surrounding rock is not enough to induce fracturing or deformation; nevertheless, the addition of new mass would be associated with a gravity increase that may be measurable at the surface [1].
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