Starting on 3 May 2018, a series of eruptive fissures opened in Kīlauea Volcano’s lower East Rift Zone (LERZ). Over the course of the next 3 months, intense degassing accompanied lava effusion from these fissures. Here, we report on ground-based observations of the gas emissions associated with Kīlauea’s 2018 eruption. Visual observations combined with radiative transfer modeling show that ultraviolet light could not efficiently penetrate the gas and aerosol plume in the LERZ, complicating SO2 measurements by differential optical absorption spectroscopy (DOAS). By applying a statistical method that integrates a radiative transfer model with the DOAS retrievals, we were able to calculate sulfur dioxide (SO2) emission rates along with estimates of their uncertainty. We find that sustained SO2 emissions were highest in June and early July, when approximately 200 kt SO2 were emitted daily. At the 68% confidence interval, we estimate that 7.1–13.6 Mt SO2 were released from the LERZ during the entire May to September eruptive episode. Scaling our results with in situ measurements of plume composition, we calculate that 11–21 Mt H2O and 1.5–2.8 Mt CO2 were also emitted. The gas and aerosol emissions caused hazardous conditions in areas proximal to the active vents, but plume dispersion modeling shows that the eruption also significantly impacted air quality hundreds of kilometers downwind. Combined with petrologic studies of the erupted lavas, our measurements indicate that 1.1–2.3 km3 dense-rock equivalent of lava were erupted from the LERZ, which is approximately twice the concomitant collapse volume of the volcano’s summit.
","language":"English","publisher":"Springer","doi":"10.1007/s00445-020-01390-8","usgsCitation":"Kern, C., Lerner, A., Elias, T., Nadeau, P.A., Holland, L., Kelly, P.J., Werner, C., Clor, L., and Cappos, M., 2020, Quantifying gas emissions associated with the 2018 rift eruption of Kīlauea Volcano using ground-based DOAS measurements: Bulletin of Volcanology, v. 82, 55, 24 p., https://doi.org/10.1007/s00445-020-01390-8.","productDescription":"55, 24 p.","ipdsId":"IP-115197","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":436927,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9LXBJF3","text":"USGS data release","linkHelpText":"Differential Optical Absorption Spectroscopy data acquired during the 2018 rift eruption of Kilauea Volcano"},{"id":376424,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Kīlauea Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.3082275390625,\n 19.379170499941292\n ],\n [\n -155.2333831787109,\n 19.379170499941292\n ],\n [\n -155.2333831787109,\n 19.449111649832837\n ],\n [\n -155.3082275390625,\n 19.449111649832837\n ],\n [\n -155.3082275390625,\n 19.379170499941292\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"82","noUsgsAuthors":false,"publicationDate":"2020-06-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Kern, Christoph 0000-0002-8920-5701 ckern@usgs.gov","orcid":"https://orcid.org/0000-0002-8920-5701","contributorId":3387,"corporation":false,"usgs":true,"family":"Kern","given":"Christoph","email":"ckern@usgs.gov","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science 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Texas","docAbstract":"The lower Eagle Ford Group (LEFG) is one of the most productive continuous hydrocarbon plays in the United States but few associated produced waters data and minimal interpretation have been published. This effort focuses on results from compositional and isotopic data from 39 produced water samples collected from horizontal wells producing from the LEFG in south central Texas. The depth of the LEFG increases by approximately 1 km across the study area, from northwest (2.9 km) to southeast (3.9 km). Associated increases in calculated reservoir temperature (125-165 C), development of reservoir over-pressuring (400-800 bars total pressure), and increased thermal maturity (heavy oil to gas condensate) also occur along this trend. Produced water salinity starts at nearly 100 g/L in the shallowest samples and decreases linearly with depth to <35 g/L. Comparison of Br/Cl and ⁸⁷Sr/⁸⁶Sr data between LEFG produced waters and the Louann salt, suggests that halite recycling is the mechanism behind salinity greater than seawater. Decreasing salinity with depth and thermal maturity in the Gulf Coast Basin have previously been shown to be a result of release of inter-layer water during smectite to illite conversion. The produced water samples show increasing 18O and decreasing 2H with depth, which is attributed temperature-dependent isotope fractionation of O and H exchange between seawater and clays and calcite with increasing temperature. Multiple sources of data indicate that the waters in the LEFG are not connate, but rather entered the unit prior to smectite-illite conversion. Presence of allochthonous water in many major tight oil and shale gas plays in the U.S., including the LEFG, suggests there is unknown mechanism allowing for water advection into low permeability reservoirs.","language":"English","publisher":"Elsevier","doi":"10.1016/j.chemgeo.2020.119754","collaboration":"None","usgsCitation":"Engle, M.A., Doolan, C.A., Pitman, J., Varonka, M., Chenault, J., Orem, W.H., McMahon, P.B., and Jubb, A., 2020, Origin and geochemistry of formation waters from the lower Eagle Ford Group, Gulf Coast Basin, south central Texas: Chemical Geology, v. 550, 119754, 12 p., https://doi.org/10.1016/j.chemgeo.2020.119754.","productDescription":"119754, 12 p.","ipdsId":"IP-117920","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science 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resources","interactions":[],"lastModifiedDate":"2020-06-16T14:09:59.229883","indexId":"sir20185104","displayToPublicDate":"2020-06-16T09:20:00","publicationYear":"2020","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":"2018-5104","displayTitle":"Conceptual Framework and Approach for Conducting a Geoenvironmental Assessment of Undiscovered Uranium Resources","title":"Conceptual framework and approach for conducting a geoenvironmental assessment of undiscovered uranium resources","docAbstract":"This report presents a novel conceptual framework and approach for conducting a geologically based environmental assessment, or geoenvironmental assessment, of undiscovered uranium resources within an area likely to contain uranium deposits. The framework is based on a source-to-receptor model that prioritizes the most likely contaminant sources, contaminant pathways, and affected environmental media for three common uranium extraction methods—open pit or underground mining with milling and in situ recovery (ISR). Data on regional geology, hydrology, and climate, as well as historical uranium mining and milling records are used to estimate the probable amounts of waste rock, tailings, wastewater, surface land disturbance, and subsurface aquifer disturbance for likely mining methods. Constituents of concern that might take the form of leachates, dust, radon, and sediments formed by chemical and physical weathering are also identified in the geoenvironmental assessment. Finally, areas where constituents of concern are likely to occur and persist in air, land, surface water, and groundwater are indicated by the potential for dispersion of dust by wind, accumulation of radon because of air stagnation, dispersion of sediments and wastewater by runoff, and infiltration of wastewater or leachates with consideration of the likely mobility of contaminants in surface water and groundwater. The geoenvironmental assessment output can be summarized in the following primary products: (1) a descriptive geoenvironmental model; (2) maps and statistics of variables that indicate the potential for constituents of concern to occur and persist in air, land, surface water, and groundwater within a tract that is geologically permissive for the occurrence of uranium; and (3) tables providing estimated or indicated quantities of waste rock, tailings, wastewater, dust, and radon emissions that could be associated with undiscovered uranium resources, if extracted, for each permissive tract. The uranium geoenvironmental assessment could help natural resource managers to prioritize and (or) identify (1) important potential contaminant pathways, (2) management practices required depending on the types of constituents that could be of concern, (3) areas for response in the event of accidental release, and (4) future directions for study. Furthermore, indicators of rock and water volumes potentially associated with an undiscovered uranium deposit may be evaluated to make quantitative comparisons of water required for uranium production or potential waste products generated during uranium extraction from areas permissive for uranium resource occurrence throughout the United States.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185104","usgsCitation":"Gallegos, T.J., Walton-Day, K., and Seal, R.R., II, 2020, Conceptual framework and approach for conducting a geoenvironmental assessment of undiscovered uranium resources: U.S. Geological Survey Scientific Investigations Report 2018–5104, 28 p., https://doi.org/10.3133/sir20185104.","productDescription":"vi, 28 p.","numberOfPages":"28","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-070792","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science 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Science Center
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
Acid deposition has declined across eastern North America and northern Europe due to reduced emissions of sulfur and nitrogen oxides. Ecosystem recovery has been slow with limited improvement in surface water chemistry. Delayed recovery has encouraged acid-neutralization strategies to accelerate recovery of impaired biological communities. Lime application has been shown to increase pH and dissolved organic carbon (DOC), which could also drive increased mobilization of mercury (Hg) to surface waters. A four-year study was conducted within Honnedaga Lake’s watershed in the Adirondack region of New York to compare the effects of watershed and direct channel lime additions on Hg in stream water and macroinvertebrates. All treatments sharply increased stream pH and DOC concentrations, but large differences in the duration of impacts were apparent. The watershed treatment resulted in multi-year increases in concentrations and loads of total Hg (150%; 390%), DOC (190%; 350%) and nutrients, whereas total Hg and DOC increased for short periods (72–96 h) after channel treatments. No response of Hg in macroinvertebrates was evident following the watershed treatment, but a potential short-term and spatially constrained increase occurred after the channel treatment. Our observations indicate that both treatment approaches mobilize Hg, but that direct channel liming mobilizes considerably less than watershed liming over any period longer than a few days. During the final study year, increased methyl Hg concentrations were observed across reference and treated streams, which may reflect an extended dry period, highlighting that climate variation may also affect Hg dynamics.
","language":"English","publisher":"Springer Nature","doi":"10.1007/s10646-020-02224-1","usgsCitation":"Millard, G., Riva-Murray, K., Burns, D., Montesdeoca, M.S., and Driscoll, C., 2020, The impact of lime additions on mercury dynamics in stream chemistry and macroinvertebrates: A comparison of watershed and direct stream addition management strategies: Ecotoxicology, v. 29, p. 1627-1643, https://doi.org/10.1007/s10646-020-02224-1.","productDescription":"17 p.","startPage":"1627","endPage":"1643","ipdsId":"IP-109979","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":436928,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9C17PA0","text":"USGS data release","linkHelpText":"Methylmercury and associated data in macroinvertebrates from tributaries of Honnedaga Lake and from the Middle Branch Black River in New York."},{"id":378508,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Honnedaga Lake watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.89448547363281,\n 43.469864270218416\n ],\n [\n -74.74754333496092,\n 43.469864270218416\n ],\n [\n -74.74754333496092,\n 43.56496912804994\n ],\n [\n -74.89448547363281,\n 43.56496912804994\n ],\n [\n -74.89448547363281,\n 43.469864270218416\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"29","noUsgsAuthors":false,"publicationDate":"2020-06-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Millard, Geoffrey D.","contributorId":240873,"corporation":false,"usgs":false,"family":"Millard","given":"Geoffrey D.","affiliations":[{"id":5082,"text":"Syracuse University","active":true,"usgs":false}],"preferred":false,"id":799038,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Riva-Murray, Karen 0000-0001-6683-2238 krmurray@usgs.gov","orcid":"https://orcid.org/0000-0001-6683-2238","contributorId":168876,"corporation":false,"usgs":true,"family":"Riva-Murray","given":"Karen","email":"krmurray@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":799039,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Burns, Douglas A. 0000-0001-6516-2869","orcid":"https://orcid.org/0000-0001-6516-2869","contributorId":202943,"corporation":false,"usgs":true,"family":"Burns","given":"Douglas A.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":799041,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Montesdeoca, Mario S.","contributorId":240877,"corporation":false,"usgs":false,"family":"Montesdeoca","given":"Mario","email":"","middleInitial":"S.","affiliations":[{"id":5082,"text":"Syracuse University","active":true,"usgs":false}],"preferred":false,"id":799042,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Driscoll, Charles T.","contributorId":240874,"corporation":false,"usgs":false,"family":"Driscoll","given":"Charles T.","affiliations":[{"id":5082,"text":"Syracuse University","active":true,"usgs":false}],"preferred":false,"id":799040,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70208302,"text":"sim3441 - 2020 - Selected geologic maps of the Kodiak batholith and other Paleocene intrusive rocks, Kodiak Island, Alaska","interactions":[],"lastModifiedDate":"2020-06-12T16:10:02.495395","indexId":"sim3441","displayToPublicDate":"2020-06-12T07:52:07","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3441","displayTitle":"Selected Geologic Maps of the Kodiak Batholith and Other Paleocene Intrusive Rocks, Kodiak Island, Alaska","title":"Selected geologic maps of the Kodiak batholith and other Paleocene intrusive rocks, Kodiak Island, Alaska","docAbstract":"Kodiak Island in southern Alaska is one of the premier examples globally for the study of forearc magmatism. This location contains two Paleocene intrusive belts that formed due to the subduction of a migrating spreading ridge and slab-window: the Kodiak batholith and the trenchward magmatic belt. These magmatic rocks are part of the Sanak-Baranof belt, which extends for greater than 2,100 km along the southern Alaskan margin and vary in age from 61 to 50 Ma west to east.
Trenchward-belt rocks, with an 40Ar/39Ar age of 60.2±0.9 Ma, intrude into the Paleocene Ghost Rocks Formation and are composed of granitoids, basaltic dikes, and small gabbroic plutons that lie along or southward of the Kalsin Bay Fault. Such intrusions were emplaced at shallow levels and have abundant evidence of incomplete intermingling of basaltic and granitic magmas. These textures indicate trenchward-belt intrusions that froze before complete assimilation, leaving behind features such as abundant locally stoped blocks, gabbroic pods within granitic intrusions, and microstructural evidence such as strongly embayed olivine and pyroxene phenocrysts in granitoid bodies.
The Kodiak batholith and satellite intrusions extend for over 110 km along the axis of Kodiak Island and vary in width from 2 to 6 km. These intrude into the Late Cretaceous Kodiak Formation. U-Pb ages on zircon from the intrusions range from 59.2±0.2 Ma in the southwest to 58.4±0.2 Ma near its northwest tip. We interpret these ages as tracking the location of a migrating triple junction and associated slab-window. The batholith is composed of granite and granodiorite, with lesser amounts of tonalite and diorite. The center of the Kodiak batholith contains high-inclusion zones with abundant residual host rock fragments that were carried up from 5–10 km below current exposure levels. These high-inclusion zones contain biotite aggregates, pure quartz clots, and large xenocrysts of sillimanite, kyanite, andalusite, and garnet. This is a higher-pressure mineral assemblage than exists in the batholith metamorphic aureole. Gravity observations and modeling are consistent with the high-inclusion zones extending downward for 5–10 km. The Kodiak batholith results from a migrating triple junction and slab-window that led to high degrees of partial melting within the Kodiak accretionary prism.
Director,
Alaska Science Center
U.S. Geological Survey
4210 University Drive
Anchorage, Alaska 99508
Global assessments predict the impact of sea-level rise on salt marshes with present-day levels of sediment supply from rivers and the coastal ocean. However, these assessments do not consider that variations in marsh extent and the related reconfiguration of intertidal area affect local sediment dynamics, ultimately controlling the fate of the marshes themselves. We conducted a meta-analysis of six bays along the United States East Coast to show that a reduction in the current salt marsh area decreases the sediment availability in estuarine systems through changes in regional-scale hydrodynamics. This positive feedback between marsh disappearance and the ability of coastal bays to retain sediments reduces the trapping capacity of the whole tidal system and jeopardizes the survival of the remaining marshes. We show that on marsh platforms, the sediment deposition per unit area decreases exponentially with marsh loss. Marsh erosion enlarges tidal prism values and enhances the tendency toward ebb dominance, thus decreasing the overall sediment availability of the system. Our findings highlight that marsh deterioration reduces the sediment stock in back-barrier basins and therefore compromises the resilience of salt marshes.
Groundwater-level conditions, generalized groundwater potentiometric surfaces, and generalized flow directions at the decommissioned Naval Air Warfare Center in West Trenton, New Jersey, were evaluated for calendar year 2018. Groundwater levels measured continuously in five on-site wells and one nearby off-site well were plotted as hydrographs for January 1, 2018, through December 31, 2018. Groundwater levels measured in 110 wells on June 18, 2018, were contoured as generalized potentiometric surfaces on maps and sections. Generalized groundwater-flow directions inferred from the June 2018 data are shown in the maps and sections.
Groundwater levels in six monitoring wells fluctuated in response to seasonal changes, precipitation, and pumping from “pump-and-treat” (P&T) wells. Record high precipitation totals in November, combined with a shutdown of three P&T wells in November, resulted in annual high water levels in late November for five of the six wells monitored. Annual high groundwater levels that occur during the fall are uncharacteristic of the typical timing of annual high water levels, which usually occur in the spring following low evapotranspiration during the winter months, compared to annual low water levels, which usually occur in fall because of high evapotranspiration during the summer months. The annual high water levels occurred following a 3-day precipitation event totaling 3.50 inches from November 24-26, which also caused the largest 1-day water-level increase for five of the six wells in 2018.
The groundwater-level contour maps and sections include generalized flow directions. Given the heterogeneity of the site’s fractured rock aquifers, contours and associated groundwater-flow directions shown on the maps and sections should be considered as broad conceptualizations. A nearly vertical fault striking southwest to northeast separates the northwestern part of the site underlain by the Lockatong Formation from the southeastern part, which is underlain by the Stockton Formation. In the Lockatong Formation, general groundwater-flow directions were toward P&T wells. The P&T wells limited the flow of groundwater in the Lockatong Formation from the site into the adjacent areas and contained most groundwater contamination within the site. A groundwater divide bisected the site; groundwater in the western part generally flowed to P&T wells 8BR, 15BR, 20BR, 29BR, 56BR, 91BR, and BRP-2, and groundwater in the eastern part generally flowed to P&T well 48BR. A groundwater divide also was present in the Stockton Formation. Groundwater west of the divide in the Stockton Formation generally flowed toward P&T well 22BR, and groundwater east of the divide generally flowed south and southeast, away from the site. Saprolite and fill from land surface to depths of 25 feet below land surface exhibit similar properties to those of porous media, and water levels in surficial wells were contoured using a porous media aquifer approach. Water levels in these surficial wells indicate that groundwater in the saprolite and fill flowed predominantly toward Gold Run and, to a lesser extent, the West Ditch spring that drains to Gold Run. In addition, some shallow groundwater was captured by the cone of depression in the fractured bedrock and was attributed to P&T well 48BR.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201016","collaboration":"Prepared in cooperation with the U.S. Navy","usgsCitation":"Fiore, A.R., and Lacombe, P.J., 2020, Groundwater levels and generalized potentiometric surfaces, former Naval Air Warfare Center, West Trenton, New Jersey, 2018: U.S. Geological Survey Open-File Report 2020–1016, 28 p., https://doi.org/10.3133/ofr20201016.","productDescription":"Report: v, 28 p.; Data Release","numberOfPages":"28","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-104199","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":375290,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1016/ofr20201016.pdf","text":"Report","size":"10.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1016"},{"id":375285,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1016/coverthb.jpg"},{"id":375288,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P98N1GWV","text":"USGS data release","linkHelpText":"Reported groundwater levels and groundwater pump-and-treat withdrawals, former Naval Air Warfare Center, West Trenton, New Jersey, 2018"}],"country":"United States","state":"New Jersey","city":"West Trenton","otherGeospatial":"Former Naval Air Warfare Center","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.81613278388977,\n 40.26694411855267\n ],\n [\n -74.80834364891052,\n 40.26694411855267\n ],\n [\n -74.80834364891052,\n 40.27319835024231\n ],\n [\n -74.81613278388977,\n 40.27319835024231\n ],\n [\n -74.81613278388977,\n 40.26694411855267\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New Jersey Water Science Center
U.S. Geological Survey
3450 Princeton Pike, Suite 110
Lawrenceville, NJ 08648
Snake fungal disease (SFD), or ophidiomycosis, is caused by the fungus Ophidiomyces ophiodiicola (Allender et al. 2015; Lorch et al. 2015). SFD is widespread across wild populations in the eastern United States (Lorch et al. 2016) and is known to infect more than 30 species of snake in North America and Europe (Lorch et al. 2016; Franklinos et al. 2017). No known phylogenetic or ecological patterns have been observed in susceptibility among snake taxa, and it is presumed that all species are likely susceptible (Burbrink et al. 2017).
","language":"English","publisher":"Society for the Study of Amphibians and Reptiles","usgsCitation":"Glorioso, B., Bartoszek, I.A., and Lorch, J.M., 2020, Low-level detection of SFD-causing Ophidiomyces on Burmese Pythons in southwest Florida, with confirmation of the pathogen on co-occurring native snakes: Herpetological Review, v. 51, no. 2, p. 245-247.","productDescription":"3 p.","startPage":"245","endPage":"247","ipdsId":"IP-113676","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":375468,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":375438,"type":{"id":15,"text":"Index Page"},"url":"https://ssarherps.org/herpetological-review-pdfs/"}],"country":"United States","state":"Florida","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.6171875,\n 24.986058021167594\n ],\n [\n -80.4638671875,\n 24.986058021167594\n ],\n [\n -80.4638671875,\n 27.352252938063845\n ],\n [\n -82.6171875,\n 27.352252938063845\n ],\n [\n -82.6171875,\n 24.986058021167594\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"51","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Glorioso, Brad 0000-0002-5400-7414","orcid":"https://orcid.org/0000-0002-5400-7414","contributorId":204397,"corporation":false,"usgs":true,"family":"Glorioso","given":"Brad","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":790540,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bartoszek, Ian A.","contributorId":138954,"corporation":false,"usgs":false,"family":"Bartoszek","given":"Ian","email":"","middleInitial":"A.","affiliations":[{"id":12592,"text":"Conservancy of Southwest Florida, Naples, FL","active":true,"usgs":false}],"preferred":false,"id":790541,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lorch, Jeffrey M. 0000-0003-2239-1252 jlorch@usgs.gov","orcid":"https://orcid.org/0000-0003-2239-1252","contributorId":5565,"corporation":false,"usgs":true,"family":"Lorch","given":"Jeffrey","email":"jlorch@usgs.gov","middleInitial":"M.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":790542,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70211707,"text":"70211707 - 2020 - Repeatable source, path, and site effects from the 2019 Ridgecrest M7.1 earthquake sequence","interactions":[],"lastModifiedDate":"2020-08-07T13:28:29.468565","indexId":"70211707","displayToPublicDate":"2020-06-09T08:24:46","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Repeatable source, path, and site effects from the 2019 Ridgecrest M7.1 earthquake sequence","docAbstract":"We use a large instrumental dataset from the 2019 Ridgecrest earthquake sequence (Rekoske et al., 2019, 2020) to examine repeatable source‐, path‐, and site‐specific ground motions. A mixed‐effects analysis is used to partition total residuals relative to the Boore et al. (2014; hereafter, BSSA14) ground‐motion model. We calculate the Arias intensity stress drop for the earthquakes and find strong correlation with our event terms, indicating that they are consistent with source processes. We look for physically meaningful trends in the partitioned residuals and test the ability of BSSA14 to capture the behavior we observe in the data.
We find that BSSA14 is a good match to the median observations for
Structured decision making is a systematic, transparent process for improving the quality of complex decisions by identifying measurable management objectives and feasible management actions; predicting the potential consequences of management actions relative to the stated objectives; and selecting a course of action that maximizes the total benefit achieved and balances tradeoffs among objectives. The U.S. Geological Survey, in cooperation with the U.S. Fish and Wildlife Service, applied an existing, regional framework for structured decision making to develop a prototype tool for optimizing tidal marsh management decisions at the Cape May and Supawna Meadows National Wildlife Refuges in New Jersey. Refuge biologists, refuge managers, and research scientists identified multiple potential management actions to improve the ecological integrity of 13 marsh management units within the refuges and estimated the outcomes of each action in terms of performance metrics associated with each management objective. Value functions previously developed at the regional level were used to transform metric scores to a common utility scale, and utilities were summed to produce a single score representing the total management benefit that would be accrued from each potential management action. Constrained optimization was used to identify the set of management actions, one per marsh management unit, that would maximize total management benefits at different cost constraints at the refuge scale. Results indicated that, for the objectives and actions considered here, total management benefits may increase consistently up to approximately $785,000, but that further expenditures may yield diminishing return on investment. Management actions in optimal portfolios at total costs less than $785,000 included applying sediment to the marsh surface (thin layer deposition) in seven marsh management units, controlling the invasive reed Phragmites australis in four marsh management units, remediating hydrologic alterations in two marsh management units, and planting native vegetation in one marsh management unit. The management benefits were derived from expected improvements in the capacity for marsh elevation to keep pace with sea-level rise, increases in numbers of spiders (as an indicator of trophic health) and tidal marsh obligate birds, and increased cover of native vegetation. The prototype presented here provides a framework for decision making at the Cape May and Supawna Meadows National Wildlife Refuges that can be updated as new data and information become available. Insights from this process may also be useful to inform future habitat management planning at the refuges.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201055","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Neckles, H.A., Lyons, J.E., Nagel, J.L., Adamowicz, S.C., Mikula, T., Braudis, B., and Hanlon, H., 2020, Optimization of tidal marsh management at the Cape May and Supawna Meadows National Wildlife Refuges, New Jersey, through use of structured decision making: U.S. Geological Survey Open-File Report 2020–1055, 41 p., https://doi.org/10.3133/ofr20201055.","productDescription":"vii, 41 p.","numberOfPages":"41","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-101980","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":375304,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1055/ofr20201055.pdf","text":"Report","size":"3.36 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1055"},{"id":375303,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1055/coverthb.jpg"}],"country":"United States","state":"New Jersey","otherGeospatial":"Cape May, Supawna Meadows National Wildlife Refuges","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.377197265625,\n 39.690280594818034\n ],\n [\n -75.1025390625,\n 39.95185892663005\n ],\n [\n -75.41015624999999,\n 39.9602803542957\n ],\n [\n -75.618896484375,\n 39.58029027440865\n ],\n [\n -75.3662109375,\n 39.2407625100131\n ],\n [\n -75.0146484375,\n 38.788345355085625\n ],\n [\n -74.42138671875,\n 39.07037913108751\n ],\n [\n -74.410400390625,\n 39.605688178320804\n ],\n [\n -74.77294921875,\n 39.36827914916014\n ],\n [\n -75.16845703124999,\n 39.40224434029275\n ],\n [\n -75.377197265625,\n 39.690280594818034\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Eastern Ecological Science Center
U.S. Geological Survey
12100 Beech Forest Road
Laurel, MD 20708–4039
The novel β-coronavirus, SARS-CoV-2, may pose a threat to North American bat populations if bats are exposed to the virus through interaction with humans, if the virus can subsequently infect bats and be transmitted among them, and if the virus causes morbidity or mortality in bats. Further, if SARS-CoV-2 became established in bat populations, it could possibly serve as a source for new infection in humans, domesticated animals, or other wild animals. Wildlife management agencies in the United States are concerned about these potential risks and have begun to issue guidance regarding work that brings humans into contact with bats, but decision making is difficult because of the high degree of uncertainty about many of the relevant processes that could lead to virus transmission and establishment. The risk assessment described in this report was undertaken to provide management agencies with an understanding of the likelihood that the various steps in the causal pathways would lead to SARS-CoV-2 infection of North American bats from people. This assessment focused on the active season for bats in the temperate zone of North America (April 15 through November 15), and used Myotis lucifugus (little brown bats) as a surrogate species. At the time of this work (April 2020), no empirical data about the effects of SARS-CoV-2 on North American bats were available, so a formal process of expert judgment was used to elicit estimates of the underlying parameters. Twelve experts in bat ecology, epidemiology, virology, and wildlife disease from the United States, United Kingdom, and Australia participated in the elicitation. A Monte Carlo simulation model was used to integrate the parameter estimates elicited from the experts and to predict the likelihood of exposure and infection in bats through a series of transmission pathways, with particular attention to capturing uncertainty in the predictions.
Given the current state of knowledge as expressed by the expert panel, the results of this assessment indicate that there is a non-negligible risk of transmission of SARS-CoV-2 from humans to bats. For example, if a research scientist were shedding SARS-CoV-2 virus while handling bats under the field protocols used in North America prior to the COVID-19 pandemic, the risk model indicates that 50 percent (uncertainty, 15–84 percent) of those bats could be exposed to virus, and 17 percent (uncertainty, 3–51 percent) could become infected. Use of personal protective equipment, especially a respirator, is expected to reduce the exposure risk. The expert panel estimated that exposure risk from research scientists could be reduced 94–96 percent (uncertainty, 86–99 percent) through proper use of appropriate N95 respirators (a type of mechanical filter worn over the nose and mouth), dedicated clothing (such as Tyvek coveralls), and gloves. Should any North American bats become infected with SARS-CoV-2, the expert panel estimated that there is an approximately 33-percent chance the virus could spread within a bat population.
This study, conducted by the U.S. Geological Survey in cooperation with the U.S. Fish and Wildlife Service, identified several critical uncertainties that could affect the estimate of risks associated with SARS-CoV-2 entering bat populations—notably, the underlying probability that a human would be shedding virus while working with bats, the likelihood of the virus replicating in bat tissue, and the likelihood of transmission of the virus within bat populations. Ongoing empirical work during May–October 2020 may shed light on these issues. Follow-up work is needed to better understand the probability of transmission of SARS-CoV-2 to bats from the general public; the manner in which the probabilities of exposure, infection, and transmission would differ during hibernation compared to the breeding season; and the likelihood of important effects, like morbidity and mortality in bats, the possibility of zoonosis from a North American bat reservoir, and effects of and on other wildlife.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201060","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Runge, M.C., Grant, E.H.C., Coleman, J.T.H., Reichard, J.D., Gibbs, S.E.J., Cryan, P.M., Olival, K.J., Walsh, D.P., Blehert, D.S., Hopkins, M.C., and Sleeman, J.M., 2020, Assessing the risks posed by SARS-CoV-2 in and via North American bats—Decision framing and rapid risk assessment: U.S. Geological Survey Open-File Report 2020–1060, 43 p., https://doi.org/10.3133/ofr20201060.","productDescription":"vi, 43 p.","numberOfPages":"43","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-118911","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":375248,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1060/ofr20201060.pdf","text":"Report","size":"4.54 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1060"},{"id":375199,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1060/coverthb.jpg"}],"country":"Canada, Mexico, United States","otherGeospatial":"North America","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.1640625,\n 13.581920900545844\n ],\n [\n -84.72656249999999,\n 19.973348786110602\n ],\n [\n -75.9375,\n 27.371767300523047\n ],\n [\n -55.8984375,\n 45.336701909968134\n ],\n [\n -48.8671875,\n 45.336701909968134\n ],\n [\n -65.0390625,\n 61.77312286453146\n ],\n [\n -58.71093750000001,\n 67.47492238478702\n ],\n [\n -84.375,\n 74.1160468394894\n ],\n [\n -125.5078125,\n 75.32002523220804\n ],\n [\n -135.703125,\n 70.95969716686398\n ],\n [\n -156.4453125,\n 71.52490903732816\n ],\n [\n -167.34375,\n 68.9110048456202\n ],\n [\n -168.046875,\n 61.60639637138628\n ],\n [\n -166.2890625,\n 53.12040528310657\n ],\n [\n -146.95312499999997,\n 57.326521225217064\n ],\n [\n -138.515625,\n 56.559482483762245\n ],\n [\n -131.484375,\n 48.922499263758255\n ],\n [\n -127.96875,\n 40.17887331434696\n ],\n [\n -116.01562499999999,\n 24.84656534821976\n ],\n [\n -98.7890625,\n 13.239945499286312\n ],\n [\n -93.1640625,\n 13.581920900545844\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Eastern Ecological Science Center
U.S. Geological Survey
12100 Beech Forest Road
Laurel, MD 20708
This paper outlines the development and demonstration of a new tool, TOUGH2–ChemPlugin (T2CPI) for predicting rock–water–CO2 interaction following injection of supercritical CO2 into a heterogeneous carbonate system. Specifically, modeling capabilities of TOUGH2, which examines multiphase flow and supercritical CO2 behavior, were combined with the geochemical modeling capabilities of The Geochemist’s Workbench® (GWB), using ChemPluginTM. ChemPlugin is a self-linking re-entrant software object that, when coupled to a transport simulator, retains the flow and transport capabilities of the simulator but enables incorporation of reactive chemistry via GWB. To test and assess the capabilities of T2CPI, results from T2CPI simulations were compared to those of TOUGHREACT, using the same carbonate reservoir parameters (based on the Dollar Bay Formation of the South Florida Basin). Overall, results of simulations from TOUGHREACT and T2CPI were very similar for nearly all evaluated parameters. Dissimilarities between the two programs included qualitative differences in how TOUGHREACT and T2CPI predicted calcite dissolution and the subsequent spatial pattern of the porosity gain caused by how each handles evaporation of water near the injection point. The TOUGHREACT program is a proven, widely used tool for evaluating CO2–brine–rock interaction following supercritical CO2 injection. The T2CPI tool offers similar capabilities and strengths of TOUGHREACT, with the ability to read in and use databases for a wide range of activity coefficient types. This program also has abilities to use a wide range of kinetic constraints, define those kinetic constraints with scripts or compiled libraries, account for colloidal transport, and/or account for a wide range of surface sorption models.
","language":"English","publisher":"AAPG","doi":"10.1306/eg.08061919003","collaboration":"None","usgsCitation":"Roberts-Ashby, T., Berger, P.M., Cunningham, J.A., Kumar, R., and Blondes, M., 2020, Modeling geologic sequestration of carbon dioxide in a deep saline carbonate reservoir with TOUGH2–ChemPlugin, a new tool for reactive transport modeling: Environmental Geosciences, v. 27, no. 2, p. 103-116, https://doi.org/10.1306/eg.08061919003.","productDescription":"14 p.","startPage":"103","endPage":"116","ipdsId":"IP-098127","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":375280,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Dollar Bay Formation","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.18298339843749,\n 24.297040469311558\n ],\n [\n -79.73876953125,\n 24.297040469311558\n ],\n [\n -79.73876953125,\n 27.81478637667891\n ],\n [\n -83.18298339843749,\n 27.81478637667891\n ],\n [\n -83.18298339843749,\n 24.297040469311558\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"27","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Roberts-Ashby, Tina L. 0000-0003-2940-1740","orcid":"https://orcid.org/0000-0003-2940-1740","contributorId":205925,"corporation":false,"usgs":true,"family":"Roberts-Ashby","given":"Tina L.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":785375,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Berger, Peter M.","contributorId":223538,"corporation":false,"usgs":false,"family":"Berger","given":"Peter","email":"","middleInitial":"M.","affiliations":[{"id":40735,"text":"Illionois State Geological Survey","active":true,"usgs":false}],"preferred":false,"id":785376,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cunningham, Jeffrey A.","contributorId":223539,"corporation":false,"usgs":false,"family":"Cunningham","given":"Jeffrey","email":"","middleInitial":"A.","affiliations":[{"id":40736,"text":"Dept of Civil and Environmental Engineering, University of South Florida","active":true,"usgs":false}],"preferred":false,"id":785377,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kumar, Ram","contributorId":223540,"corporation":false,"usgs":false,"family":"Kumar","given":"Ram","email":"","affiliations":[{"id":40737,"text":"Dept. of Chemical and Biomedical Engineering, Univ. of South Florida","active":true,"usgs":false}],"preferred":false,"id":790254,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Blondes, Madalyn S. 0000-0003-0320-0107 mblondes@usgs.gov","orcid":"https://orcid.org/0000-0003-0320-0107","contributorId":3598,"corporation":false,"usgs":true,"family":"Blondes","given":"Madalyn S.","email":"mblondes@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":785378,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70211253,"text":"70211253 - 2020 - Locality note for rubber boa","interactions":[],"lastModifiedDate":"2020-08-06T23:20:25.341027","indexId":"70211253","displayToPublicDate":"2020-06-01T18:19:03","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1898,"text":"Herpetological Review","active":true,"publicationSubtype":{"id":10}},"title":"Locality note for rubber boa","docAbstract":"CHARINA BOTTAE BOTTAE (N. Rubber Boa), USA: CALIFORNIA: Monterey Co.: Landels-Hill Big Creek Reserve, east side of Hwy. 1, 80 km (50 miles) south of Carmel, Calif., (36.0719055 N 121.5991555 W) 19 June, 2009; (36.0703611 N 121.5982222 W) 06 July 2009; (36.9516666 N 121.5991944 W) 27 July 2009. In chronological order, photo vouchers MVZObs:Herp:26, MVZObs:Herp:27, MVZObs:Herp:28. Verified by Mitchell Mulks, formerly of 84 Redondo Ave. Suisun City, Calif., Michelle Koo, Staff Curator, Biodiversity Informatics & GIS and Researcher, MVZ, U.C., Berkeley, Calif. New southern extension of the species in the Santa Lucia Range of Monterey Co. approximately 48 km. (30 miles) south of previous range extension south of Carmel in Bixby Canyon (Burger, L.W., Herpetologica, Vol. 8. Part 1. March 22, 1952), and approximately 4 km. (2.5 miles) south of MVZ #229876 found 20 miles north of Nacimiento Road, at approximate coordinates of 36.10033 N 121.62026 W.","language":"English","publisher":"Society for the Study of Amphibians and Reptiles","usgsCitation":"Tomoleoni, J.A., and Hoyer, R.F., 2020, Locality note for rubber boa: Herpetological Review, v. 51, no. 2, 1 p.","productDescription":"1 p.","ipdsId":"IP-113927","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":377146,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":377145,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://ssarherps.org/herpetological-review-pdfs/"}],"country":"United States","state":"California","county":"Monterey County","city":"Carmel","otherGeospatial":"Santa Lucia Range","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.89743041992189,\n 36.49556152992\n ],\n [\n -121.83151245117186,\n 36.49556152992\n ],\n [\n -121.83151245117186,\n 36.54908666159689\n ],\n [\n -121.89743041992189,\n 36.54908666159689\n ],\n [\n -121.89743041992189,\n 36.49556152992\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"51","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Tomoleoni, Joseph A. 0000-0001-6980-251X jtomoleoni@usgs.gov","orcid":"https://orcid.org/0000-0001-6980-251X","contributorId":167551,"corporation":false,"usgs":true,"family":"Tomoleoni","given":"Joseph","email":"jtomoleoni@usgs.gov","middleInitial":"A.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":793427,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hoyer, Richard F","contributorId":229515,"corporation":false,"usgs":false,"family":"Hoyer","given":"Richard","email":"","middleInitial":"F","affiliations":[{"id":41662,"text":"Corvallis, OR","active":true,"usgs":false}],"preferred":false,"id":793428,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70212741,"text":"70212741 - 2020 - Climate change projected to reduce prescribed burning opportunities in the south-eastern United States","interactions":[],"lastModifiedDate":"2020-09-24T16:03:00.806638","indexId":"70212741","displayToPublicDate":"2020-06-01T11:22:20","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2083,"text":"International Journal of Wildland Fire","active":true,"publicationSubtype":{"id":10}},"title":"Climate change projected to reduce prescribed burning opportunities in the south-eastern United States","docAbstract":"Prescribed burning is a critical tool for managing wildfire risks and meeting ecological objectives, but its safe and effective application requires that specific meteorological criteria (a ‘burn window’) are met. Here, we evaluate the potential impacts of projected climatic change on prescribed burning in the south-eastern United States by applying a set of burn window criteria that capture temperature, relative humidity and wind speed to projections from an ensemble of Global Climate Models under two greenhouse gas emission scenarios. Regionally, the percentage of suitable days for burning changes little during winter but decreases substantially in summer owing to rising temperatures by the end of the 21st century compared with historical conditions. Management implications of such changes for six representative land management units include seasonal shifts in burning opportunities from summer to cool-season months, but with considerable regional variation. We contend that the practical constraints of rising temperatures on prescribed fire activities represent a significant future challenge and show that even meeting basic burn criteria (as defined today) will become increasingly difficult over time, which speaks to the need for adaptive management strategies to prepare for such changes.
","language":"English","publisher":"CSIRO Publishing","doi":"10.1071/WF19198","usgsCitation":"Kupfer, J., Terando, A., Gao, P., Teske, C., and Hiers, J., 2020, Climate change projected to reduce prescribed burning opportunities in the south-eastern United States: International Journal of Wildland Fire, v. 29, no. 9, p. 764-778, https://doi.org/10.1071/WF19198.","productDescription":"15 p.","startPage":"764","endPage":"778","ipdsId":"IP-108251","costCenters":[{"id":40926,"text":"Southeast Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":456540,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1071/wf19198","text":"Publisher Index Page"},{"id":377937,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alabama, Arkansas, Florida, Georgia, kentucky, Louisiana, Mississippi, Missouri, North Carolina, Oklahoma, South Carolina, Tennessee, 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abundance have been documented in many species. However, in order to better predict species responses, managers are seeking to understand the mechanisms that are driving these changes, including any thresholds that might soon be crossed. Leveraging the research that has already been supported by the Northeast Climate Adaptation Science Center and its partners, this project used the latest modeling techniques combined with robust field data to examine the impact of specific climate variables, land use change, and species interactions on the future distribution and abundance of species of conservation concern. Moreover, this project documented biological thresholds related to climate variability and change for critical species in the Northeastern and Midwestern U.S. Specifically, our objectives were to identify the primary drivers (climate change vs. urban growth) of species distribution changes in the Northeast; examine the nature of species landscape capability change over time to identify potential thresholds; determine how changing temperatures and snowpack characteristics will drive species interactions; analyze the sensitivity of tree and bird responses to the magnitude, variability, periodicity, and seasonality of temperature and precipitation under climate change in the eastern U.S.; and identify how discrete climate triggers such as extreme events will correlate with known biological thresholds. Major outcomes included 1) refining the understanding of the mechanisms that drive projected changes in the distribution of vulnerable populations; and 2) improving how these results are conveyed to stakeholders by identifying understandable responses in the form of thresholds.","language":"English","publisher":"Northeast Climate Adaptation Science Center","usgsCitation":"DeLuca, W., Bonnot, T.W., Siren, A., Horton, R.M., Griffin, C.R., and Morelli, T.L., 2020, Examining the mechanisms of species responses to climate change: Are there biological thresholds?, 34 p.","productDescription":"34 p.","ipdsId":"IP-117230","costCenters":[{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":376907,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":376805,"type":{"id":15,"text":"Index Page"},"url":"https://cascprojects.org/#/project/4f8c648de4b0546c0c397b43/57b35c6de4b03bcb01039665"}],"country":"United States","state":"Connecticut, Delaware, Illinois, Indiana, Iowa, Kentucky, Maine, Maryland, Massachusetts, Michigan, Minnesota, Missouri, New Hampshire New Jersey, New York, Ohio, Pennsylvania, Rhode Island. 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K.","contributorId":236810,"corporation":false,"usgs":false,"family":"Siren","given":"Alexej P. K.","affiliations":[],"preferred":false,"id":794252,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Horton, Radley M.","contributorId":139267,"corporation":false,"usgs":false,"family":"Horton","given":"Radley","email":"","middleInitial":"M.","affiliations":[{"id":7171,"text":"Columbia University","active":true,"usgs":false}],"preferred":false,"id":794253,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Griffin, Curtice R.","contributorId":74634,"corporation":false,"usgs":true,"family":"Griffin","given":"Curtice","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":794254,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Morelli, Toni Lyn 0000-0001-5865-5294 tmorelli@usgs.gov","orcid":"https://orcid.org/0000-0001-5865-5294","contributorId":197458,"corporation":false,"usgs":true,"family":"Morelli","given":"Toni","email":"tmorelli@usgs.gov","middleInitial":"Lyn","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":794255,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70211588,"text":"70211588 - 2020 - Trends in oyster populations in the northeastern Gulf of Mexico: An assessment of river discharge and fishing effects over time and space","interactions":[],"lastModifiedDate":"2023-08-31T17:33:18.95725","indexId":"70211588","displayToPublicDate":"2020-05-30T08:03:31","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2680,"text":"Marine and Coastal Fisheries: Dynamics, Management, and Ecosystem Science","active":true,"publicationSubtype":{"id":10}},"title":"Trends in oyster populations in the northeastern Gulf of Mexico: An assessment of river discharge and fishing effects over time and space","docAbstract":"Within the Big Bend region of the northeastern Gulf of Mexico, one of the least developed coastlines in the continental USA, intertidal and subtidal populations of eastern oyster Crassostrea virginica (hereafter referred to as “oyster”) are a critical ecosystem and important economic constituent. We assessed trends in intertidal oyster populations, river discharge, and commercial fishing activity in the Suwannee River estuary within the Big Bend region using fisheries‐independent data from irregular monitoring efforts and publicly available environmental data. We used generalized linear models to evaluate counts of oysters from line‐transect surveys over time and space. We assessed model performance using simulation to understand potential bias and then evaluated whether these counts were related to freshwater inputs from the Suwannee River and commercial oyster fishing effort and landings at different time lags. We found that intertidal oyster counts have declined over time and that most of these declines are found in inshore intertidal oyster bars, which are becoming degraded. We also found a significant relationship between oyster counts and a 1‐year lag on mean daily Suwannee River discharge, but including commercial fishery trips or landings did not improve model fit. It is unclear whether declines in intertidal oyster bars are offset by formation of new oyster reefs elsewhere. These results quantify rapid declines in intertidal oyster reefs in a region of coastline with high conservation value that can be used to inform ongoing and proposed restoration projects in the region.","language":"English","publisher":"Wiley","doi":"10.1002/mcf2.10117","usgsCitation":"Moore, J.F., Pine, W.E., Frederick, P., Becker, S., Moreno, M., Dodrill, M., Boone, M., Sturmer, L., and Yurek, S., 2020, Trends in oyster populations in the northeastern Gulf of Mexico: An assessment of river discharge and fishing effects over time and space: Marine and Coastal Fisheries: Dynamics, Management, and Ecosystem Science, v. 12, no. 3, p. 191-204, https://doi.org/10.1002/mcf2.10117.","productDescription":"14 p.","startPage":"191","endPage":"204","ipdsId":"IP-114295","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":456589,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/mcf2.10117","text":"Publisher Index Page"},{"id":377005,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.51943969726561,\n 28.9913248161703\n ],\n [\n -82.67898559570311,\n 28.9913248161703\n ],\n [\n -82.67898559570311,\n 29.684473609006847\n ],\n [\n -83.51943969726561,\n 29.684473609006847\n ],\n [\n -83.51943969726561,\n 28.9913248161703\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"12","issue":"3","noUsgsAuthors":false,"publicationDate":"2020-05-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Moore, J. F","contributorId":236929,"corporation":false,"usgs":false,"family":"Moore","given":"J.","email":"","middleInitial":"F","affiliations":[{"id":47565,"text":"Department of Wildlife Ecology and Conservation, 110 Newins-Ziegler Hall, University of Florida, Gainesville, FL 32611","active":true,"usgs":false}],"preferred":false,"id":794727,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pine, W. E","contributorId":236930,"corporation":false,"usgs":false,"family":"Pine","given":"W.","email":"","middleInitial":"E","affiliations":[{"id":47565,"text":"Department of Wildlife Ecology and Conservation, 110 Newins-Ziegler Hall, University of Florida, Gainesville, FL 32611","active":true,"usgs":false}],"preferred":false,"id":794728,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Frederick, P. C","contributorId":236931,"corporation":false,"usgs":false,"family":"Frederick","given":"P. C","affiliations":[{"id":47565,"text":"Department of Wildlife Ecology and Conservation, 110 Newins-Ziegler Hall, University of Florida, Gainesville, FL 32611","active":true,"usgs":false}],"preferred":false,"id":794729,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Becker, Sarah","contributorId":210890,"corporation":false,"usgs":false,"family":"Becker","given":"Sarah","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":794730,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Moreno, Marcos","contributorId":195527,"corporation":false,"usgs":false,"family":"Moreno","given":"Marcos","email":"","affiliations":[],"preferred":false,"id":794731,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dodrill, Michael J. 0000-0002-7038-7170","orcid":"https://orcid.org/0000-0002-7038-7170","contributorId":206439,"corporation":false,"usgs":true,"family":"Dodrill","given":"Michael","middleInitial":"J.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":794732,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Boone, Matthew","contributorId":202724,"corporation":false,"usgs":false,"family":"Boone","given":"Matthew","affiliations":[{"id":13359,"text":"University of Delaware","active":true,"usgs":false}],"preferred":false,"id":794733,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sturmer, L","contributorId":236932,"corporation":false,"usgs":false,"family":"Sturmer","given":"L","email":"","affiliations":[{"id":47566,"text":"University of Florida Extension, Senatore George Kirkpatrick Marine Lab, 11350 SW 153rd Court, Cedar Key, FL 32625","active":true,"usgs":false}],"preferred":false,"id":794734,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Yurek, Simeon 0000-0002-6209-7915","orcid":"https://orcid.org/0000-0002-6209-7915","contributorId":216733,"corporation":false,"usgs":true,"family":"Yurek","given":"Simeon","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":794735,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70211682,"text":"70211682 - 2020 - Between the supercontinents: Mesoproterozoic Deer Trail Group, an intermediate age unit between the Mesoproterozoic Belt–Purcell Supergroup and the Neoproterozoic Windermere Supergroup in northeastern Washington, USA","interactions":[],"lastModifiedDate":"2020-12-29T21:24:38.461894","indexId":"70211682","displayToPublicDate":"2020-05-27T17:47:51","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1168,"text":"Canadian Journal of Earth Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Between the supercontinents: Mesoproterozoic Deer Trail Group, an intermediate age unit between the Mesoproterozoic Belt–Purcell Supergroup and the Neoproterozoic Windermere Supergroup in northeastern Washington, USA","docAbstract":"Mesoproterozoic and Neoproterozoic basins in western North America record the evolving position of the Laurentian craton within two supercontinents during their growth and dismemberment: Columbia (Nuna) and Rodinia. The western-most exposures of the Columbia rift-related Belt–Purcell Supergroup are preserved in northeastern Washington, structurally overlain by the Deer Trail Group and depositionally overlying the Neoproterozoic Windermere Supergroup. It has been disputed whether the Deer Trail Group is correlative with the Belt–Purcell Supergroup, or younger. To help resolve the uncertain correlation of these units and their bearing on supercontinent evolution, we characterized the detrital zircon age populations of units from the Deer Trail Group, the Windermere Supergroup, and the Belt–Purcell Supergroup in northeastern Washington. These data show that the western part of the Columbia supercontinent (now located in Australia and eastern Antarctica) remained attached to western Laurentia and continued to supply 1600–1500 Ma detrital zircon grains to the Belt–Purcell Supergroup until after ca. 1391 Ma. The Deer Trail Group is younger than the Belt–Purcell strata, with the basal unit younger than ca. 1362 Ma and a middle unit younger than ca. 1300 Ma. The Deer Trail Group has a pre-Grenville-age provenance from the southwestern USA and possibly east Antarctica. The Buffalo Hump Formation is younger than the Deer Trail Group, with Grenville-age (ca. 1112 Ma) detrital zircon grains and a detrital zircon signature like that of the overlying Neoproterozoic Windermere Supergroup. We interpret the Deer Trail Group to have been deposited during the rift-demise of supercontinent Columbia and before the Grenville-age assembly of the supercontinent Rodinia.
","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjes-2019-0188","usgsCitation":"Box, S.E., Pritchard, C.J., Stephens, T.S., and O’Sullivan, P.B., 2020, Between the supercontinents: Mesoproterozoic Deer Trail Group, an intermediate age unit between the Mesoproterozoic Belt–Purcell Supergroup and the Neoproterozoic Windermere Supergroup in northeastern Washington, USA: Canadian Journal of Earth Sciences, v. 57, no. 12, p. 1411-1427, https://doi.org/10.1139/cjes-2019-0188.","productDescription":"17 p.","startPage":"1411","endPage":"1427","ipdsId":"IP-112626","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":500791,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/1807/101706","text":"External Repository"},{"id":377140,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","city":"Chewelah","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.81188964843751,\n 47.89056441663247\n ],\n [\n -117.04833984375001,\n 47.89056441663247\n ],\n [\n -117.04833984375001,\n 48.669198799260045\n ],\n [\n -117.81188964843751,\n 48.669198799260045\n ],\n [\n -117.81188964843751,\n 47.89056441663247\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"57","issue":"12","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Box, Stephen E. 0000-0002-5268-8375 sbox@usgs.gov","orcid":"https://orcid.org/0000-0002-5268-8375","contributorId":1843,"corporation":false,"usgs":true,"family":"Box","given":"Stephen","email":"sbox@usgs.gov","middleInitial":"E.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":795048,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pritchard, Chad J. 0000-0002-4608-7776","orcid":"https://orcid.org/0000-0002-4608-7776","contributorId":237042,"corporation":false,"usgs":false,"family":"Pritchard","given":"Chad","email":"","middleInitial":"J.","affiliations":[{"id":47590,"text":"Eastern Washington University, Dept. of Geology","active":true,"usgs":false}],"preferred":false,"id":795049,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stephens, Travis S.","contributorId":237044,"corporation":false,"usgs":false,"family":"Stephens","given":"Travis","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":795050,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"O’Sullivan, Paul B.","contributorId":193544,"corporation":false,"usgs":false,"family":"O’Sullivan","given":"Paul","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":795051,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70222338,"text":"70222338 - 2020 - Challenges in quantifying air-water carbon dioxide flux using estuarine water quality data: Case study for Chesapeake Bay","interactions":[],"lastModifiedDate":"2021-07-22T15:12:18.885038","indexId":"70222338","displayToPublicDate":"2020-05-27T10:10:47","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7159,"text":"JGR Oceans","active":true,"publicationSubtype":{"id":10}},"title":"Challenges in quantifying air-water carbon dioxide flux using estuarine water quality data: Case study for Chesapeake Bay","docAbstract":"Estuaries play an uncertain but potentially important role in the global carbon cycle via CO2 outgassing. The uncertainty mainly stems from the paucity of studies that document the full spatial and temporal variability of estuarine surface water partial pressure of carbon dioxide ( pCO2). Here, we explore the potential of utilizing the abundance of pH data from historical water quality monitoring programs to fill the data void via a case study of the mainstem Chesapeake Bay (eastern United States). We calculate pCO2 and the air-water CO2 flux at monthly resolution from 1998 to 2018 from tidal fresh to polyhaline waters, paying special attention to the error estimation. The biggest error is due to the pH measurement error, and errors due to the gas transfer velocity, temporal sampling, the alkalinity mixing model, and the organic alkalinity estimation are 72%, 27%, 15%, and 5%, respectively, of the error due to pH. Seasonal, interannual, and spatial variability in the air-water flux and surface pCO2 is high, and a correlation analysis with oxygen reveals that this variability is driven largely by biological processes. Averaged over 1998–2018, the mainstem bay is a weak net source of CO2 to the atmosphere of 1.2 (1.1, 1.4) mol m−2 yr−1 (best estimate and 95% confidence interval). Our findings suggest that the abundance of historical pH measurements in estuaries around the globe should be mined in order to constrain the large spatial and temporal variability of the CO2 exchange between estuaries and the atmosphere.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2019JC015610","usgsCitation":"Herrmann, M., Najjar, R.G., Da, F., Friedman, J.R., Friedrichs, M.A., Goldberger, S., Menendez, A., Shadwick, E.H., Stets, E.G., and St-Laurent, P., 2020, Challenges in quantifying air-water carbon dioxide flux using estuarine water quality data: Case study for Chesapeake Bay: JGR Oceans, v. 125, no. 7, e2019JC015610, 19 p., https://doi.org/10.1029/2019JC015610.","productDescription":"e2019JC015610, 19 p.","ipdsId":"IP-119043","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":456632,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1029/2019jc015610","text":"External Repository"},{"id":387386,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland, Virginia","otherGeospatial":"Chesapeake Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.11328125,\n 36.96744946416934\n ],\n [\n -75.970458984375,\n 37.501010429493284\n ],\n [\n -75.65185546874999,\n 37.90953361677018\n ],\n [\n -75.82763671875,\n 37.96152331396614\n ],\n [\n -75.816650390625,\n 38.07404145941957\n ],\n [\n -76.278076171875,\n 38.40194908237822\n ],\n [\n -76.168212890625,\n 38.8225909761771\n ],\n [\n -76.256103515625,\n 39.104488809440475\n ],\n [\n -76.1572265625,\n 39.29179704377487\n ],\n [\n -75.9375,\n 39.50404070558415\n ],\n [\n -75.9814453125,\n 39.57182223734374\n ],\n [\n -76.11328125,\n 39.53793974517628\n ],\n [\n -76.168212890625,\n 39.39375459224348\n ],\n [\n -76.3330078125,\n 39.36827914916014\n ],\n [\n -76.519775390625,\n 39.18117526158749\n ],\n [\n -76.5966796875,\n 38.805470223177466\n ],\n [\n -76.431884765625,\n 38.35888785866677\n ],\n [\n -76.35498046875,\n 38.07404145941957\n ],\n [\n -76.35498046875,\n 37.65773212628272\n ],\n [\n -76.453857421875,\n 37.33522435930639\n ],\n [\n -76.409912109375,\n 37.09900294387622\n ],\n [\n -76.11328125,\n 36.96744946416934\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"125","issue":"7","noUsgsAuthors":false,"publicationDate":"2020-07-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Herrmann, Maria","contributorId":198519,"corporation":false,"usgs":false,"family":"Herrmann","given":"Maria","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":819664,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Najjar, Raymond G. 0000-0002-3770-2300","orcid":"https://orcid.org/0000-0002-3770-2300","contributorId":261280,"corporation":false,"usgs":false,"family":"Najjar","given":"Raymond","email":"","middleInitial":"G.","affiliations":[{"id":6738,"text":"The Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":819665,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Da, Fei 0000-0002-5330-5962","orcid":"https://orcid.org/0000-0002-5330-5962","contributorId":261282,"corporation":false,"usgs":false,"family":"Da","given":"Fei","email":"","affiliations":[{"id":40564,"text":"Virginia Institute of Marine Science, William & Mary","active":true,"usgs":false}],"preferred":false,"id":819666,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Friedman, Jaclyn R. 0000-0001-8120-2541","orcid":"https://orcid.org/0000-0001-8120-2541","contributorId":222587,"corporation":false,"usgs":false,"family":"Friedman","given":"Jaclyn","email":"","middleInitial":"R.","affiliations":[{"id":40564,"text":"Virginia Institute of Marine Science, William & Mary","active":true,"usgs":false}],"preferred":false,"id":819668,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Friedrichs, Marjorie A. M. 0000-0003-2828-7595","orcid":"https://orcid.org/0000-0003-2828-7595","contributorId":222588,"corporation":false,"usgs":false,"family":"Friedrichs","given":"Marjorie","email":"","middleInitial":"A. M.","affiliations":[{"id":40564,"text":"Virginia Institute of Marine Science, William & Mary","active":true,"usgs":false}],"preferred":false,"id":819669,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Goldberger, Sreece","contributorId":261284,"corporation":false,"usgs":false,"family":"Goldberger","given":"Sreece","email":"","affiliations":[{"id":6738,"text":"The Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":819667,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Menendez, Alana","contributorId":261286,"corporation":false,"usgs":false,"family":"Menendez","given":"Alana","email":"","affiliations":[{"id":38178,"text":"City College of New York","active":true,"usgs":false}],"preferred":false,"id":819670,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Shadwick, Elizabeth H. 0000-0003-4008-3333","orcid":"https://orcid.org/0000-0003-4008-3333","contributorId":222589,"corporation":false,"usgs":false,"family":"Shadwick","given":"Elizabeth","email":"","middleInitial":"H.","affiliations":[{"id":36909,"text":"CSIRO","active":true,"usgs":false}],"preferred":false,"id":819671,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Stets, Edward G. 0000-0001-5375-0196 estets@usgs.gov","orcid":"https://orcid.org/0000-0001-5375-0196","contributorId":194490,"corporation":false,"usgs":true,"family":"Stets","given":"Edward","email":"estets@usgs.gov","middleInitial":"G.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":819672,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"St-Laurent, Pierre 0000-0002-1700-9509","orcid":"https://orcid.org/0000-0002-1700-9509","contributorId":261288,"corporation":false,"usgs":false,"family":"St-Laurent","given":"Pierre","email":"","affiliations":[{"id":40564,"text":"Virginia Institute of Marine Science, William & Mary","active":true,"usgs":false}],"preferred":false,"id":819673,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70210218,"text":"70210218 - 2020 - Seismic velocity variations associated with the 2018 lower East Rift Zone eruption of Kīlauea, Hawaiʻi","interactions":[],"lastModifiedDate":"2020-05-21T12:35:22.76059","indexId":"70210218","displayToPublicDate":"2020-05-20T07:31:12","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1109,"text":"Bulletin of Volcanology","active":true,"publicationSubtype":{"id":10}},"title":"Seismic velocity variations associated with the 2018 lower East Rift Zone eruption of Kīlauea, Hawaiʻi","docAbstract":"The 2018 lower East Rift Zone eruption of Kīlauea (Hawai‘i) marked a dramatic change in the volcano’s 35-year-long rift zone eruption. The collapse of the middle East Rift Zone vent Pu‘u ‘Ō‘ō was followed by one of the volcano’s most voluminous eruptions in 500 years. Over the course of this 3-month eruption, the draining of summit-stored magma led to near-daily collapses of a portion of the caldera and ultimately up to 500 m of summit subsidence. While deformation data indicated that the summit and middle East Rift Zone were inflating for the previous several years, why Pu‘u ‘Ō‘ō collapsed and what initiated down-rift dike propagation remains unclear. Using ambient noise seismic interferometry, we show that a Ml5.3 decollement earthquake beneath Kīlauea’s south flank in June 2017 induced a coseismic decrease of up to 0.30% in seismic velocity throughout the volcano. This velocity decrease may have been caused by dynamic stress–induced shallow crustal fracture, i.e., weakening to dilatant crack growth, and was greatest near Pu‘u ‘Ō‘ō. Additionally, we verify a pre-eruptive increase in seismic velocity, consistent with increasing pressurization in the volcano’s shallow summit magma reservoir. This velocity increase occurred coincident with the first in a series of lower-crustal earthquake swarms, 6 days before a 2-month period of rapid summit and middle East Rift Zone inflation. The increase in up-rift magma-static pressure, combined with the pre-existing weakness from the June 2017 earthquake, may have facilitated down-rift dike propagation and the devastating 2018 eruption.","language":"English","publisher":"Springer","doi":"10.1007/s00445-020-01380-w","usgsCitation":"Flinders, A.F., Caudron, C., Johanson, I.A., Taira, T., Shiro, B., and Haney, M.M., 2020, Seismic velocity variations associated with the 2018 lower East Rift Zone eruption of Kīlauea, Hawaiʻi: Bulletin of Volcanology, v. 82, 47, 13 p., https://doi.org/10.1007/s00445-020-01380-w.","productDescription":"47, 13 p.","ipdsId":"IP-107347","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":456690,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s00445-020-01380-w","text":"Publisher Index Page"},{"id":374979,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Kīlauea volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.33843994140625,\n 19.303367019780318\n ],\n [\n -155.16815185546875,\n 19.303367019780318\n ],\n [\n -155.16815185546875,\n 19.460765580777778\n ],\n [\n -155.33843994140625,\n 19.460765580777778\n ],\n [\n -155.33843994140625,\n 19.303367019780318\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"82","noUsgsAuthors":false,"publicationDate":"2020-08-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Flinders, Ashton F. 0000-0003-2483-4635 aflinders@usgs.gov","orcid":"https://orcid.org/0000-0003-2483-4635","contributorId":196960,"corporation":false,"usgs":true,"family":"Flinders","given":"Ashton","email":"aflinders@usgs.gov","middleInitial":"F.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":153,"text":"California Volcano Observatory","active":false,"usgs":true}],"preferred":false,"id":789582,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Caudron, Corentin 0000-0002-3748-0007","orcid":"https://orcid.org/0000-0002-3748-0007","contributorId":224799,"corporation":false,"usgs":false,"family":"Caudron","given":"Corentin","email":"","affiliations":[{"id":40942,"text":"Université Grenoble Alpes, Université Savoie, ISTerre, Grenoble, France","active":true,"usgs":false}],"preferred":false,"id":789583,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johanson, Ingrid A. 0000-0002-6049-2225","orcid":"https://orcid.org/0000-0002-6049-2225","contributorId":215613,"corporation":false,"usgs":true,"family":"Johanson","given":"Ingrid","email":"","middleInitial":"A.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":789584,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Taira, Taka’aki 0000-0002-6170-797X","orcid":"https://orcid.org/0000-0002-6170-797X","contributorId":222985,"corporation":false,"usgs":false,"family":"Taira","given":"Taka’aki","email":"","affiliations":[{"id":36942,"text":"University of California, Berkeley","active":true,"usgs":false}],"preferred":false,"id":789585,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Shiro, Brian 0000-0001-8756-288X","orcid":"https://orcid.org/0000-0001-8756-288X","contributorId":204040,"corporation":false,"usgs":true,"family":"Shiro","given":"Brian","email":"","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":789586,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Haney, Matthew M. 0000-0003-3317-7884 mhaney@usgs.gov","orcid":"https://orcid.org/0000-0003-3317-7884","contributorId":172948,"corporation":false,"usgs":true,"family":"Haney","given":"Matthew","email":"mhaney@usgs.gov","middleInitial":"M.","affiliations":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":789587,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70212673,"text":"70212673 - 2020 - Late Quaternary slip rates on the Sierra Madre fault zone and paleoseismic evidence on the size and frequency of past ruptures","interactions":[],"lastModifiedDate":"2020-08-25T16:21:14.208563","indexId":"70212673","displayToPublicDate":"2020-05-18T11:12:03","publicationYear":"2020","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"1","title":"Late Quaternary slip rates on the Sierra Madre fault zone and paleoseismic evidence on the size and frequency of past ruptures","docAbstract":"The Sierra Madre fault zone is a south-vergent, active reverse fault that accommodates shortening between basins on the northern margin of the Los Angeles region and the San Gabriel Mountains. The preservation of late Quaternary alluvial fill and fan surfaces in the hanging wall of the fault provides evidence of long-term uplift. Surface rupture from the 1971 Mw 6.6 San Fernando earthquake and evidence of large prehistoric displacements from trenching investigations emphasize the ongoing hazard posed by the fault system to the region. This one-day field trip visits some of the key locations near Pasadena and San Fernando, California, where slip rates have been determined from cosmogenic and luminescence dating of abandoned surfaces dating to 50–70, ca. 30, and ca. 12 ka and surface offsets measured from lidar and pre-development topographic maps. Another stop is the site of a paleoseismic trench, which provided key evidence on the timing and displacement of past ruptures on the fault. In combination, results from these field investigations converge on a slip rate for the eastern ~100 km of the fault zone of 1–2 mm/yr, which matches or exceeds the rates for other reverse faults in southern California. This rate, in combination with trenching data that show no evidence of post–mid Holocene ruptures along the central and eastern portions of the fault, indicate the fault zone poses a significant seismic hazard to the region.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"From the islands to the mountains: A 2020 view of geologic excursions in Southern California","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Geological Society of America","doi":"10.1130/2020.0059(01)","usgsCitation":"Burgette, R., Scharer, K., and Lindvall, S., 2020, Late Quaternary slip rates on the Sierra Madre fault zone and paleoseismic evidence on the size and frequency of past ruptures, chap. 1 of From the islands to the mountains: A 2020 view of geologic excursions in Southern California, v. 59, p. 1-20, https://doi.org/10.1130/2020.0059(01).","productDescription":"20 p.","startPage":"1","endPage":"20","ipdsId":"IP-116598","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":377832,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sierra Madre fault zone","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.21289062499999,\n 33.829356907739296\n ],\n [\n -115.62561035156249,\n 33.829356907739296\n ],\n [\n -115.62561035156249,\n 34.74161249883172\n ],\n [\n -118.21289062499999,\n 34.74161249883172\n ],\n [\n -118.21289062499999,\n 33.829356907739296\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"59","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Burgette, Reed J.","contributorId":175465,"corporation":false,"usgs":false,"family":"Burgette","given":"Reed J.","affiliations":[{"id":49682,"text":"Dept of Geolgical Sciences, New Mexico State University","active":true,"usgs":false}],"preferred":false,"id":797257,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Scharer, Katherine M. 0000-0003-2811-2496","orcid":"https://orcid.org/0000-0003-2811-2496","contributorId":217361,"corporation":false,"usgs":true,"family":"Scharer","given":"Katherine M.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":797258,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lindvall, Scott","contributorId":224667,"corporation":false,"usgs":false,"family":"Lindvall","given":"Scott","affiliations":[{"id":40908,"text":"Lettis Consultants International","active":true,"usgs":false}],"preferred":false,"id":797259,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70210016,"text":"ofr20201041 - 2020 - U.S. Geological Survey 2018 Kīlauea Volcano eruption response in Hawai'i—After-action review","interactions":[],"lastModifiedDate":"2020-06-08T21:58:33.431965","indexId":"ofr20201041","displayToPublicDate":"2020-05-14T12:39:16","publicationYear":"2020","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":"2020-1041","displayTitle":"U.S. Geological Survey 2018 Kīlauea Volcano Eruption Response in Hawai'i—After-Action Review","title":"U.S. Geological Survey 2018 Kīlauea Volcano eruption response in Hawai'i—After-action review","docAbstract":"The 2018 Kīlauea Volcano eruption lasted 107 days, and now ranks as the most destructive event at Kilauea since 1790, and as one of the most costly volcanic disasters in U.S. history. Multiple simultaneous hazard events unfolded, including sustained seismic activity leading to collapse at the summit of Halema'uma'u crater and severe damage to the HVO facility, with additional eruption of lava in the Kīlauea Lower East Rift Zone that progressively grew to a total of 24 fissure openings. In response to the complex and uncertain nature of the eruption, U.S. Geological Survey (USGS) team activities tended to coalesce around several interrelated core functional areas: science operations, emergency management and administration, and external communications. Upon cessation of the eruption, the USGS Hazard Response Executive Committee charged the Alaska Regional Office to lead an After-Action Review team, which focused on two basic questions: (1) what went well, and why?; and (2) what can be improved, and how? The purpose of the After-Action Review is to identify priorities for programmatic or policy improvements that the USGS can feasibly implement to advance strategic preparation for future disasters, and thereby reduce public vulnerabilities. Specifically, the review is intended to help USGS respond even better to the next eruption in Hawai'i or elsewhere by advancing any of the following goals:
Regional Director, Alaska
U.S. Geological Survey
4210 University Drive
Anchorage, Alaska 99508-4560
The addition of surface water from the San Juan-Chama Drinking Water Project to the Albuquerque water supply and the reduction in per capita water use has led to decreased groundwater withdrawals. This decrease in withdrawals has resulted in rising groundwater levels since 2008 in portions of the aquifer underlying Albuquerque. The wells used to assess the Kirtland Air Force Base Bulk Fuels Facility (KAFB BFF) ethylene dibromide (EDB) groundwater contamination were installed with well screens that crossed the water table in order to monitor and sample groundwater within the EDB plume. While replacement wells have been installed, an understanding of the water-table response to decreases in regional groundwater withdrawals is required to evaluate the monitoring well network. Water-table elevation maps of the aquifer underlying the Albuquerque metropolitan area east of the Rio Grande for 2008 and 2016 and a map of the change in elevations in this 8-year period provide an improved understanding of the water-table elevations and the changes that are occurring.
The water-table elevation contours for both 2008 and 2016 show that groundwater generally flows from the Rio Grande and from the mountain-front recharge in the southeast toward the center of the study area, a major groundwater pumping center. The water-table elevation increased in most of the study area from 2008 to 2016. The area of greatest increase in the water-table elevation covers most of the northeastern part of the study area, where there has historically been pumping-related drawdown and subsequent groundwater-level rises in the production zone of the Santa Fe Group aquifer system.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201036","collaboration":"Prepared in cooperation with Air Force Civil Engineer Center","usgsCitation":"Flickinger, A.K., and Mitchell, A.C., 2020, Water-table elevation maps for 2008 and 2016 and water-table elevation changes in the aquifer system underlying eastern Albuquerque, New Mexico: U.S. Geological Survey Open-File Report 2020–1036, 9 p., https://doi.org/10.3133/ofr20201036.","productDescription":"Report: vi, 9 p.; Data Release; Interactive Map","numberOfPages":"20","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-111755 ","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":374556,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://usgs.maps.arcgis.com/home/item.html?id=3b038837dfe347daa8691931182788f5","text":"Interactive map of the study area"},{"id":374553,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1036/coverthb.jpg"},{"id":374554,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1036/ofr20201036.pdf","text":"Report","size":"2.16 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020–1036"},{"id":374555,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9OHR8Z2","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Water-tables elevations and other well construction data for 2008 and 2016 in eastern Albuquerque, New Mexico"}],"country":"United States","state":"New Mexico","city":"Albuquerque","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.6607666015625,\n 34.836349990763864\n ],\n [\n -105.9521484375,\n 34.836349990763864\n ],\n [\n -105.9521484375,\n 35.27701633139884\n ],\n [\n -106.6607666015625,\n 35.27701633139884\n ],\n [\n -106.6607666015625,\n 34.836349990763864\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New Mexico Water Science Center
U.S. Geological Survey
6700 Edith Blvd. NE
Albuquerque, NM 87113