Studies of naturally occurring subsurface carbon dioxide (CO2) accumulations can provide useful information for potential CO2 injection projects; however, the microbial communities and formation water geochemistry of most reservoirs are understudied. Formation water and microbial biomass were sampled at four CO2-rich reservoir sites: two within Bravo Dome, a commercial CO2 field in New Mexico; one northwest of Bravo Dome in Colorado (Oakdale Field); and one southwest of Bravo Dome in New Mexico (Rafter “K” Ranch). Aside from the Rafter “K” Ranch site, minor differences were observed in the geochemistry of formation water collected from these sites compared to historical data. No organisms were significantly associated with Oakdale Field compared to the other three sites, nor were any hydrogeochemical or gas geochemical parameters (for example, CO2 concentration) found to have significant associations with the microbial ecology of these four sites. Microorganisms from these sites were metabolically diverse and had the potential to (1) generate methane, (2) produce corrosive hydrogen sulfide (H2S), and (3) rapidly biofoul and (or) clog pore spaces by shifting microbial communities with changes in salinity or nutrient supply. This study demonstrates that high concentrations of CO2 in subsurface reservoirs apparently have not imparted a distinct geochemical or microbiological signature on the associated formation waters and that the microorganisms in these reservoirs are metabolically diverse and could adapt to geochemical changes in the subsurface.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205037","usgsCitation":"Shelton, J.L., Andrews, R.S., Akob, D.M., DeVera, C.A., Mumford, A.C., Engle, M., Plampin, M.R., and Brennan, S.T., 2020, Compositional analysis of formation water geochemistry and microbiology of commercial and carbon dioxide-rich wells in the southwestern United States: U.S. Geological Survey Scientific Investigations Report 2020–5037, 26 p., https://doi.org/10.3133/sir20205037.","productDescription":"viii, 26 p.","numberOfPages":"38","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-098514","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":374365,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5037/sir20205037.pdf","text":"Report","size":"1.90 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5037"},{"id":374364,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5037/coverthb.jpg"}],"country":"United States","state":"Colorado, New Mexico, Texas, Oklahoma","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -107.16064453125,\n 34.07086232376631\n ],\n [\n -102.919921875,\n 34.07086232376631\n ],\n [\n -102.919921875,\n 37.43997405227057\n ],\n [\n -107.16064453125,\n 37.43997405227057\n ],\n [\n -107.16064453125,\n 34.07086232376631\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Eastern Energy Resources Science Center
U.S. Geological Survey
12201 Sunrise Valley Drive
956 National Center
Reston, VA 20192
The National Petroleum Reserve in Alaska (NPR-A) encompasses more than 9.5 million hectares of federally managed land on the Arctic Coastal Plain of northern Alaska, where it supports a diversity of wildlife, including millions of migratory birds. Within the NPR-A, Teshekpuk Lake and the surrounding area provide important habitat for migratory birds, including large numbers of waterfowl and shorebirds that use the area for breeding and molting. This area has been designated by the Bureau of Land Management as the Teshekpuk Lake Special Area (TLSA) and is estimated to host 22 percent of the entire Pacific black brant (Branta bernicla nigricans) population as it undergoes flightless wing molt. Additionally, numerous other waterfowl species use the area for breeding and molting, including greater white-fronted geese (Anser albifrons), snow geese (Chen caerulescens), Canada geese (Branta hutchinsii), and tundra swans (Cygnus columbianus). A data-derived procedure was developed to define important habitats based on recent distributions of molting birds. That procedure was used to identify areas that could be prioritized for exclusion from oil and gas development within a pre-defined “Goose Molting Area” in the TLSA. This analysis was requested by the Bureau of Land Management to provide information for the development of alternative scenarios for an updated NPR-A, Integrated Activity Plan/Environmental Impact Statement. Habitat selections were based on the population densities of Pacific black brant and Canada geese and pre-defined thresholds for the minimum fraction of the population contained within selected areas. Selections were based on long-term records of population density combined with global-positioning system data to reveal small-scale patterns of habitat use. The highest population density of the Pacific black brant was found along the Beaufort Sea coast on the eastern edge of the study area, whereas Canada geese were somewhat more widely distributed. Depending on the selection criteria and width of protective buffers placed around selected habitat units, 52–85 percent of the Goose Molting Area was identified as high-priority habitat. The effectiveness of this approach to habitat protection assumes that buffers around selected habitat units are wide enough to provide adequate protection from disturbance related to oil and gas development. This assumption remained a key source of uncertainty that could be addressed through additional study of disturbance effects on molting waterfowl.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201034","collaboration":"Prepared in cooperation with the Bureau of Land Management","usgsCitation":"Flint, P.L., Patil, V., Shults, B., and Thompson, S.J., 2020, Prioritizing habitats based on abundance and distribution of molting waterfowl in the Teshekpuk Lake Special Area of the National Petroleum Reserve, Alaska: U.S. Geological Survey Open-File Report 2020-1034, 16 p., https://doi.org/10.3133/ofr20201034.","productDescription":"Report: iv, 16 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-115467","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":374468,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ZGNRTB","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Habitat selection scenarios for molting waterfowl in the Goose Molting Area of the Teshekpuk Lake Special Area, for NPR-A Integrated Activity Plan/Environmental Impact Statement (2020)"},{"id":374466,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1034/coverthb.jpg"},{"id":374467,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1034/ofr20201034.pdf","text":"Report","size":"3.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1034"}],"country":"United States","state":"Alaska","otherGeospatial":"National Petroleum Reserve","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -154.59411621093747,\n 70.23346027955571\n ],\n [\n -151.7816162109375,\n 70.23346027955571\n ],\n [\n -151.6717529296875,\n 70.52306573985297\n ],\n [\n -152.0892333984375,\n 70.8248355501024\n ],\n [\n -153.0670166015625,\n 70.95790503334285\n ],\n [\n -154.59411621093747,\n 70.86448996613296\n ],\n [\n -154.59411621093747,\n 70.23346027955571\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Alaska Science Center
U.S. Geological Survey
4210 University Drive
Anchorage, Alaska 99508
Since their inception over 20 years ago, the maximum considered earthquake ground motion maps in U.S. building codes have capped probabilistic values with deterministic ground motions from characteristic earthquakes on known active faults. This practice has increasingly been called into question both because of spatially non-uniform risk levels that are produced (risk being higher mainly in coastal California) and practical difficulties in defining characteristic earthquakes from recent earthquake rupture forecast models. We describe two proposals developed to enable phase-out of deterministic caps. One approach modestly increases collapse risk targets nationwide based on recent information on return periods of characteristic earthquakes on major central and eastern U.S. seismic sources; adoption of this approach would remove the perceived need for caps in California. The second approach uses geographically varying collapse risk targets, being higher near the highly active faults in California and unchanged elsewhere. Neither approach was adopted for the 2020 National Earthquake Hazards Reduction Program recommended seismic Provisions for new building structures, but they are described in a Part 3 document to accompany the Provisions and Commentary.
Snake Creek flows east from the southern Snake Range in Nevada over complex lithology before leaving Great Basin National Park. The river travels over a section of karst limestone where some surface water naturally recharges the groundwater flow system. In 1961 a water diversion pipeline was constructed by downstream water users to transport surface water through the groundwater recharge zone to reduce potential water losses. The diversion pipeline dewaters a 5-km reach for most of the year by transporting water past the recharge zone then returning it to the channel downstream. Snake Creek was incorporated into the newly established Great Basin National Park in 1986, and today park managers and visitors are concerned that the diversion has destabilized Snake Creek’s riparian ecosystem in this arid region where it has high ecological value. The objectives of this study were to 1) document riparian cottonwood forest conditions in the pipeline-dewatered (DW) reach, 2) evaluate Snake Creek water availability and whether it can support a healthy riparian ecosystem, and 3) determine if dewatering has shifted the fluvial system into an unnatural and poorly functioning state.
We pursued these ecohydrological study objectives in 11 research investigations of Snake Creek’s DW reach and nearby reference reaches. The research investigations analyzed: 1) riparian forest condition, tree age, growth, and death; 2) tree ring chronologies through time and space; 3) hydroclimatic drivers of tree growth; 4) stable carbon isotopes extracted from tree rings; 5) cottonwood ecophysiology related to water transport and water stress; 6) historical aerial photography; 7) stand-level riparian forest production; 8) groundwater availability as related to surface water and plant rooting zones; 9) near-surface geophysics using electrical resistivity imaging; 10) channel and valley geomorphology; and 11) in-channel wood jams caused by fallen trees. Integrating these diverse research topics provided a full perspective of historical and modern conditions along Snake Creek.
We found that modern hydrological conditions in Snake Creek’s DW reach could not maintain the drought-sensitive ecosystem. The riparian cottonwoods (Populus angustifolia and P. angustifolia x P. trichocarpa) have experienced significant dieback. Tree mortality was 2.4 times higher in the DW reach than in reference reaches, and surviving trees supported only 60% of the live canopy compared to trees in reference reaches. Changes in the DW reach forest began in the 1960s and became more severe during the last two decades. Stable carbon isotope ratios and branch dieback analyses both demonstrated initial forest adjustments related to water stress beginning in the early 1960s. Tree ring width chronologies indicated two periods of growth decline in the DW relative to control reaches. The first decline in the 1960s represented an immediate adjustment to the modified flow regime, and the second decline in the 2000s demonstrated reduced resilience to atmospheric drought. Aerial photos and stand-level forest production calculations indicated that substantial riparian forest decline occurred in the 1990s–2010s in the DW reach compared to reference reaches. Stable carbon isotope ratios and leaf water potentials revealed that trees in the DW reach experienced greater drought stress than those in reference reaches. Monitoring wells and electrical resistivity surveys both showed riparian water tables to be largely supported by in-channel surface water flow, indicating that the flow diversion removed water that recharges alluvial groundwater and sustains riparian plants. Areas of widespread tree mortality in the DW reach also corresponded to a larger and more unstable channel with a high instream wood load from fallen trees. Modern conditions of Snake Creek in the DW reach robustly suggest that dewatering the river and its associated riparian corridor adversely affected the riparian ecosystem. The degraded condition is likely to persist and intensify unless water is returned to the channel. As we documented during the wet 1980s and the scientific literature suggest, a partial recovery of the riparian ecosystem is likely possible with restored flows.
","language":"English","publisher":"National Park Service","usgsCitation":"Schook, D.M., Cooper, D.J., Friedman, J.M., Rice, S.E., Hoover, J.D., and Thaxton, R.D., 2020, Effects of flow diversion on Snake Creek and its riparian cottonwood forest, Great Basin National Park: Natural Resource Report NPS/GRBA/NRR-2020/2104, xv, 159 p.","productDescription":"xv, 159 p.","ipdsId":"IP-114048","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":377493,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":377489,"type":{"id":15,"text":"Index Page"},"url":"https://irma.nps.gov/DataStore/DownloadFile/637892"}],"country":"United States","state":"Nevada","otherGeospatial":"Great Basin National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.3951416015625,\n 38.66406704456943\n ],\n [\n -114.114990234375,\n 38.66406704456943\n ],\n [\n -114.114990234375,\n 39.08956785484934\n ],\n [\n -114.3951416015625,\n 39.08956785484934\n ],\n [\n -114.3951416015625,\n 38.66406704456943\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Schook, Derek M.","contributorId":178325,"corporation":false,"usgs":false,"family":"Schook","given":"Derek","email":"","middleInitial":"M.","affiliations":[{"id":13539,"text":"Department of Geosciences, Colorado State University, Fort Collins, Colorado","active":true,"usgs":false}],"preferred":false,"id":796163,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cooper, David J.","contributorId":53309,"corporation":false,"usgs":true,"family":"Cooper","given":"David","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":796164,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Friedman, Jonathan M. 0000-0002-1329-0663 friedmanj@usgs.gov","orcid":"https://orcid.org/0000-0002-1329-0663","contributorId":2473,"corporation":false,"usgs":true,"family":"Friedman","given":"Jonathan","email":"friedmanj@usgs.gov","middleInitial":"M.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":796165,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rice, Steven E.","contributorId":238179,"corporation":false,"usgs":false,"family":"Rice","given":"Steven","email":"","middleInitial":"E.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":796166,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hoover, Jamie D.","contributorId":238180,"corporation":false,"usgs":false,"family":"Hoover","given":"Jamie","email":"","middleInitial":"D.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":796167,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Thaxton, Richard D.","contributorId":238181,"corporation":false,"usgs":false,"family":"Thaxton","given":"Richard","email":"","middleInitial":"D.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":796168,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70219907,"text":"70219907 - 2020 - Fisheries research and monitoring activities of the Lake Erie Biological Station, 2019","interactions":[],"lastModifiedDate":"2021-04-16T13:31:57.728158","indexId":"70219907","displayToPublicDate":"2020-04-30T08:29:44","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"seriesTitle":{"id":8434,"text":"Lake Erie Biological Station Annual Report","active":true,"publicationSubtype":{"id":4}},"title":"Fisheries research and monitoring activities of the Lake Erie Biological Station, 2019","docAbstract":"A comprehensive understanding of fish populations and their interactions is the cornerstone of modern fishery management and the basis for Fish Community Goals and Objectives for Lake Erie (Ryan et al. 2003). This report is responsive to U.S. Geological Survey (USGS) obligations via Memorandum of Understanding (MOU) with the Great Lakes Council of Lake Committees (CLC) to provide scientific information in support of fishery management. Goals for the USGS Great Lakes Deepwater Fish Assessment and Ecological Studies in 2019 were to monitor long-term changes in the fish community and population dynamics of key fishes of interest to management agencies. Specific to Lake Erie, expectations of this agreement were sustained investigations of native percids, forage (prey) fish populations, and Lake Trout.
Our 2019 deepwater program operations began in April and concluded in December, and utilized trawl, gillnet, hydroacoustic, lower trophic sampling, and telemetry methods. This work resulted in 88 bottom trawls covering 65 ha of lake-bottom and catching 24,140 fish totaling 3,622 kg during three separate trawl surveys in the West and Central basins of Lake Erie. Overnight gillnet sets (n=44) for cold water species were performed at 42 unique locations in the West and East basins of Lake Erie. A total of 8.0 km of gillnet was deployed during these surveys, which caught 286 fish, 114 of which were native coldwater species: Lake Trout, Burbot, and Lake Whitefish. USGS hydroacoustic surveys in 2019 produced 240 km of transects, and lower trophic sampling provided data from zooplankton samples (n=21) and water quality profiles (n=21) to populate a database maintained by the Ontario Ministry of Natural Resources and Forestry (OMNRF), Ohio Division of Natural Resources (ODNR), Michigan Division of Natural Resources (MDNR), Pennsylvania Fish and Boat Commission (PFBC), and New York State Department of Environmental Conservation (NYSDEC). USGS also assisted CLC member agencies with deployment and maintenance of the Great Lakes Acoustic Telemetry Observation System (GLATOS) throughout all three Lake Erie sub-basins, supporting multiple coordinated telemetry investigations.
In 2019, Lake Trout investigations included annual gill net surveys and acoustic telemetry of spawning migration and habitat use in coordination with OMNRF, NYSDEC, and PFBC. Results from Lake Trout investigations were reported in the Coldwater Task Group annual report to the Great Lakes Fishery Commission (GLFC) and the CLC (Coldwater Task Group 2020). Likewise, interagency forage fish assessments conducted with hydroacoustics were summarized and reported in the Forage Task Group annual report (Forage Task Group 2020).
This report presents biomass-based summaries of fish communities in western Lake Erie derived from USGS bottom trawl surveys conducted from 2013 to 2019 during June and September. The survey design provided temporal and spatial coverage that did not exist in the historic interagency trawl database, and thus complemented the August ODNR-OMNRF effort to reinforce stock assessments with more robust data. Analyses herein evaluated trends in: total biomass, abundance of dominant predator and forage species, non-native species composition, biodiversity and community structure. Data from this effort can be explored interactively online (https://lebs.shinyapps.io/western-basin/), and are accessible for download (https://doi.org/10.5066/P9LL6YOR, Keretz et al. 2020). Annual survey data are added to these sources as the data become available.
","language":"English","publisher":"Great Lakes Fishery Commission","usgsCitation":"Keretz, K.R., Kocovsky, P., Kraus, R., and Schmitt, J., 2020, Fisheries research and monitoring activities of the Lake Erie Biological Station, 2019: Lake Erie Biological Station Annual Report, 12 p.","productDescription":"12 p.","ipdsId":"IP-116726","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":385156,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":385155,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.glfc.org/lake-erie-committee.php"}],"country":"Canada, United States","otherGeospatial":"Lake Erie","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.4796142578125,\n 41.701627343789205\n ],\n [\n -83.056640625,\n 41.58668835697237\n ],\n [\n -82.9742431640625,\n 41.52091689636249\n ],\n [\n -83.0401611328125,\n 41.422134246213616\n ],\n [\n -82.9083251953125,\n 41.40153558289846\n ],\n [\n -82.79296874999999,\n 41.463311976686235\n ],\n [\n -82.4908447265625,\n 41.380930388318\n ],\n [\n -81.990966796875,\n 41.50446357504803\n ],\n [\n -81.7108154296875,\n 41.48800607185427\n ],\n [\n -81.3372802734375,\n 41.72623044860004\n ],\n [\n -80.48583984375,\n 41.983994270935625\n ],\n [\n -79.46411132812499,\n 42.407234661551875\n ],\n [\n -79.200439453125,\n 42.54093947168063\n ],\n [\n -78.848876953125,\n 42.79943131987838\n ],\n [\n -78.9202880859375,\n 42.879989517714826\n ],\n [\n -79.332275390625,\n 42.871938424448466\n ],\n [\n -79.4696044921875,\n 42.871938424448466\n ],\n [\n -79.7222900390625,\n 42.84375132629021\n ],\n [\n -80.22766113281249,\n 42.783307077249624\n ],\n [\n -80.46936035156249,\n 42.577354839557856\n ],\n [\n -80.85937499999999,\n 42.65012181368022\n ],\n [\n -81.30432128906249,\n 42.66628070564928\n ],\n [\n -81.5185546875,\n 42.5733097370664\n ],\n [\n -81.8096923828125,\n 42.382894009614034\n ],\n [\n -81.9140625,\n 42.285437007491545\n ],\n [\n -81.9305419921875,\n 42.256983603767466\n ],\n [\n -82.02392578125,\n 42.256983603767466\n ],\n [\n -82.430419921875,\n 42.11859868281563\n ],\n [\n -82.50732421875,\n 42.004407212963585\n ],\n [\n -82.5238037109375,\n 41.92271616673922\n ],\n [\n -82.60620117187499,\n 42.02481360781777\n ],\n [\n -82.72705078125,\n 42.02889410108475\n ],\n [\n -82.9248046875,\n 41.98807738309159\n ],\n [\n -83.045654296875,\n 42.049292638686836\n ],\n [\n -83.12805175781249,\n 42.1104489601222\n ],\n [\n -83.155517578125,\n 42.15118709351198\n ],\n [\n -83.22143554687499,\n 42.05337156043361\n ],\n [\n -83.177490234375,\n 42.004407212963585\n ],\n [\n -83.25439453125,\n 41.95540515378059\n ],\n [\n -83.4356689453125,\n 41.828642001860544\n ],\n [\n -83.4906005859375,\n 41.72623044860004\n ],\n [\n -83.4796142578125,\n 41.701627343789205\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Keretz, Kevin R. 0000-0002-4808-8350 kkeretz@usgs.gov","orcid":"https://orcid.org/0000-0002-4808-8350","contributorId":5859,"corporation":false,"usgs":true,"family":"Keretz","given":"Kevin","email":"kkeretz@usgs.gov","middleInitial":"R.","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false},{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":814367,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kocovsky, Patrick 0000-0003-4325-4265 pkocovsky@usgs.gov","orcid":"https://orcid.org/0000-0003-4325-4265","contributorId":150837,"corporation":false,"usgs":true,"family":"Kocovsky","given":"Patrick","email":"pkocovsky@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":814370,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kraus, Richard 0000-0003-4494-1841","orcid":"https://orcid.org/0000-0003-4494-1841","contributorId":216548,"corporation":false,"usgs":true,"family":"Kraus","given":"Richard","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":814368,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schmitt, Joseph 0000-0002-8354-4067","orcid":"https://orcid.org/0000-0002-8354-4067","contributorId":221020,"corporation":false,"usgs":true,"family":"Schmitt","given":"Joseph","email":"","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":814369,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70209818,"text":"70209818 - 2020 - Green turtle mitochondrial microsatellites indicate finer-scale natal homing to isolated islands than to continental nesting sites","interactions":[],"lastModifiedDate":"2020-06-12T17:45:25.808564","indexId":"70209818","displayToPublicDate":"2020-04-29T12:40:14","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2636,"text":"MEPS","active":true,"publicationSubtype":{"id":10}},"title":"Green turtle mitochondrial microsatellites indicate finer-scale natal homing to isolated islands than to continental nesting sites","docAbstract":"In highly mobile philopatric species, defining the scale of natal homing is fundamental to characterizing population dynamics and effectively managing distinct populations. Genetic tools have provided evidence of regional natal philopatry in marine turtles, but extensive sharing of maternally inherited mitochondrial control region (CR) haplotypes within regions (<500 km) often impedes identification of population boundaries. Previous CR-based analyses of Florida (USA) green turtle Chelonia mydas nesting sites detected at least 2 populations, but the ubiquity of haplotype CM-A3.1 among southern rookeries decreased the power to detect differentiation. We reassessed population structure by sequencing the mitochondrial microsatellite (short tandem repeat, mtSTR) in 786 samples from 11 nesting sites spanning 700 km from Canaveral National Seashore through Dry Tortugas National Park. The mtSTR marker subdivided CM-A3.1 into 12 haplotypes that were structured among rookeries, demonstrating independent female recruitment into the Dry Tortugas and Marquesas Keys nesting populations. Combined haplotypes provided support for recognition of at least 4 management units in Florida: (1) central eastern Florida, (2) southeastern Florida, (3) Key West National Wildlife Refuge, and (4) Dry Tortugas National Park. Recapture data indicated female nesting dispersal between islands <15 km apart, but haplotype frequencies demonstrated discrete natal homing to island groups separated by 70 km. These isolated insular rookeries may be more vulnerable to climate change-mediated nesting habitat instability than those along continental coasts and should be monitored more consistently to characterize population status. Broader application of the mtSTR markers holds great promise in improving resolution of stock structure and migratory connectivity for green turtles globally.
","language":"English","publisher":"Inter-Research Science Press","doi":"10.3354/meps13348","usgsCitation":"Shamblin, B.M., Hart, K., Martin, K.J., Ceriani, S.A., Bagley, D.A., Mansfield, K.L., Ehrhart, L.M., and Nairn, C.J., 2020, Green turtle mitochondrial microsatellites indicate finer-scale natal homing to isolated islands than to continental nesting sites: MEPS, v. 643, p. 159-171, https://doi.org/10.3354/meps13348.","productDescription":"13 p.","startPage":"159","endPage":"171","ipdsId":"IP-112808","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":375563,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Dry Tortugas National Park, Key West National Wildlife Refuge, Marquesas Keys","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.10333251953125,\n 24.35960758535081\n ],\n [\n -82.64190673828125,\n 24.35960758535081\n ],\n [\n -82.64190673828125,\n 24.79670834894575\n ],\n [\n -83.10333251953125,\n 24.79670834894575\n ],\n [\n -83.10333251953125,\n 24.35960758535081\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.9415283203125,\n 24.171813716251364\n ],\n [\n -80.04638671875,\n 24.171813716251364\n ],\n [\n -80.04638671875,\n 26.377106813670053\n ],\n [\n -81.9415283203125,\n 26.377106813670053\n ],\n [\n -81.9415283203125,\n 24.171813716251364\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.28759765625,\n 24.404636766948936\n ],\n [\n -81.93603515625,\n 24.404636766948936\n ],\n [\n -81.93603515625,\n 24.65076163520743\n ],\n [\n -82.28759765625,\n 24.65076163520743\n ],\n [\n -82.28759765625,\n 24.404636766948936\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"643","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Shamblin, Brian M.","contributorId":138897,"corporation":false,"usgs":false,"family":"Shamblin","given":"Brian","email":"","middleInitial":"M.","affiliations":[{"id":12573,"text":"Daniel B. Warnell School of Forestry and Natural Resource, Athens Georiga","active":true,"usgs":false}],"preferred":false,"id":788149,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hart, Kristen 0000-0002-5257-7974","orcid":"https://orcid.org/0000-0002-5257-7974","contributorId":214952,"corporation":false,"usgs":true,"family":"Hart","given":"Kristen","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":788150,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Martin, Kelly J.","contributorId":168557,"corporation":false,"usgs":false,"family":"Martin","given":"Kelly","email":"","middleInitial":"J.","affiliations":[{"id":25334,"text":"Loggerhead Marinelife Center, 14200 U.S. Highway 1, Juno Beach, Florida, 33408, USA","active":true,"usgs":false}],"preferred":false,"id":788151,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ceriani, Simona A.","contributorId":224398,"corporation":false,"usgs":false,"family":"Ceriani","given":"Simona","email":"","middleInitial":"A.","affiliations":[{"id":40873,"text":"Florida Fish and Wildlife Research Institute, Florida Fish and Wildlife Conservation Commission","active":true,"usgs":false}],"preferred":false,"id":788152,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bagley, Dean A.","contributorId":138898,"corporation":false,"usgs":false,"family":"Bagley","given":"Dean","email":"","middleInitial":"A.","affiliations":[{"id":12574,"text":"Department of Biology , University of Central Florida, Orlando, Florida","active":true,"usgs":false}],"preferred":false,"id":788153,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mansfield, Katherine L.","contributorId":138887,"corporation":false,"usgs":false,"family":"Mansfield","given":"Katherine","email":"","middleInitial":"L.","affiliations":[{"id":12564,"text":"Department of Biology, University of Central Florida","active":true,"usgs":false}],"preferred":false,"id":788154,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ehrhart, Llewellyn M.","contributorId":138899,"corporation":false,"usgs":false,"family":"Ehrhart","given":"Llewellyn","email":"","middleInitial":"M.","affiliations":[{"id":12574,"text":"Department of Biology , University of Central Florida, Orlando, Florida","active":true,"usgs":false}],"preferred":false,"id":788155,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Nairn, Campbell J.","contributorId":138908,"corporation":false,"usgs":false,"family":"Nairn","given":"Campbell","email":"","middleInitial":"J.","affiliations":[{"id":12573,"text":"Daniel B. Warnell School of Forestry and Natural Resource, Athens Georiga","active":true,"usgs":false}],"preferred":false,"id":788156,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70206310,"text":"sim2932C - 2020 - Geologic map of the southern flank of Mauna Loa Volcano, Island of Hawai‘i, Hawaii","interactions":[],"lastModifiedDate":"2024-05-23T22:03:38.745463","indexId":"sim2932C","displayToPublicDate":"2020-04-28T11:59:26","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":"2932","chapter":"C","displayTitle":"Geologic Map of the Southern Flank of Mauna Loa Volcano, Island of Hawai‘i, Hawaii","title":"Geologic map of the southern flank of Mauna Loa Volcano, Island of Hawai‘i, Hawaii","docAbstract":"On the Island of Hawaiʻi, Mauna Loa, the largest volcano on Earth, has erupted 33 times since written descriptions became available in 1832. Some eruptions began with only brief seismic unrest, whereas others followed several months to a year of increased seismicity. Once underway, its eruptions can produce lava flows that may reach the sea in less than 24 hours, severing roads and utilities. In terms of eruption frequency, pre-eruption warning, and rapid flow emplacement, Mauna Loa has great volcanic-hazard potential for the Island of Hawai‘i. Volcanic hazards on Mauna Loa may be anticipated, and risk substantially mitigated, by documenting the past activity to refine our knowledge of the hazards and by alerting the public and local government officials of our findings and their implications for hazards assessments and risk.
Although most Mauna Loa eruptions begin in the summit area at 12,000 feet (ft) elevation, the Southwest Rift Zone (SWRZ) was the source of at least 10 flank eruptions since 1843. The SWRZ extends from the summit towards Kalae (South Point) at sea level. The lowermost part of this rift zone, marked by Pu‘uʻoke‘oke‘o to the north at 6,874 ft elevation and extending to the sea, makes up the lower SWRZ. The community of Hawaiian Ocean View Estates, with a population of about 2,500, is the largest in the region. The subdivision is built entirely on flows erupted from southern Mauna Loa, and some source vents are located within the subdivision. Approximately 25 percent of the subdivision is within Hazard Zone 1.
From east to west, the map covers the area from Punalu‘u to Miloli‘i and, from north to south, extends from north of Pu‘uʻoke‘oke‘o to Kalae (South Point). The map encompasses 1,163 square kilometers of the southwest flank of Mauna Loa, from 7,325 ft elevation to sea level. It shows the distribution of eruptive units (flows), which are separated into 16 age groups, ranging from more than 100,000 years before present to A.D. 1950.
Lava erupted from the SWRZ typically flows to the west, east, or south (depending upon vent location relative to the rift crest) and generally produces narrow flow lobes. Both morphologic lava flow types—‘a‘ā and pāhoehoe—are present. In general, the northern part of the mapped area is dominated by flows from the middle SWRZ, whereas the southern part contains flows from the lower SWRZ and includes areas adjacent to, and downslope of, the rift zone. The exceptions are flows that originated from the upper SWRZ in the northeastern part of the Punaluu quadrangle.
Contact HVO
Volcano Science Center, Hawaiian Volcano Observatory
U.S. Geological Survey
Context Since 2005, unconventional gas develop[1]ment has rapidly altered forests across the Marcellus[1]Utica shale basin in the central Appalachian region of the eastern United States, an area of high conservation value for biodiversity. Much is still unknown about ecological impacts of associated land cover change. Objectives Our goal was to identify threshold responses among bird species and habitat guilds to (1) overall forest loss and fragmentation in affected landscapes, and (2) distance from anthropogenic landscapes, and (2) distance from anthropogenic disturbance, both related and unrelated to shale gas. Methods We conducted 2589 bird surveys at 190 sites across this region, and quantified community[1]level and species-specific thresholds relating to forest cover and distance to anthropogenic disturbance, using Threshold Indicator Taxa Analysis (TITAN). Results Forest interior species decreased abruptly in abundance and frequency of occurrence above a threshold of 17.0% overall forest loss, while early successional and synanthropic species increased abruptly above 30.5–36.5% forest loss, respectively. Broad quantile intervals around responses to distance from anthropogenic disturbance suggest these were not sharp threshold responses, but more gradual or linear responses. Among forest interior species evaluated, 48.1% increased in abundance farther from shale gas development, while 55.6% of early successional and synanthropic species decreased. Conclusions We found evidence of avian threshold responses to overall forest loss and fragmentation in affected landscapes across the Marcellus-Utica shale region. Our results suggest that efforts to avoid shale gas development in regional core forests—particularly those still retaining C 83% forest cover—can reduce negative effects on area-sensitive, forest interior dependent species
","language":"English","publisher":"Springer","doi":"10.1007/s10980-020-01019-3","usgsCitation":"Farwell, L.S., Wood, P.B., Dettmers, R., and Brittingham, M.C., 2020, Threshold responses of songbirds to forest loss and fragmentation across the Marcellus-Utica shale gas region: Landscape Ecology, v. 35, no. 6, p. 1353-1370, https://doi.org/10.1007/s10980-020-01019-3.","productDescription":"18 p.","startPage":"1353","endPage":"1370","ipdsId":"IP-109328","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":395532,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland, New York, Ohio, Pennsylvania, West Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.77221679687499,\n 39.825413103424786\n ],\n [\n -76.409912109375,\n 40.97989806962013\n ],\n [\n -75.91552734375,\n 41.95949009892467\n ],\n [\n -74.959716796875,\n 42.8115217450979\n ],\n [\n -76.146240234375,\n 43.229195113965005\n ],\n [\n -78.02490234375,\n 43.13306116240612\n ],\n [\n -79.34326171875,\n 42.415346114253616\n ],\n [\n -81.331787109375,\n 41.713930073371294\n ],\n [\n -82.36450195312499,\n 41.32732632036622\n ],\n [\n -83.133544921875,\n 41.6154423246811\n ],\n [\n -83.924560546875,\n 41.623655390686395\n ],\n [\n -84.638671875,\n 41.541477666790286\n ],\n [\n -84.67163085937499,\n 38.89958342598271\n ],\n [\n -84.627685546875,\n 38.831149809348744\n ],\n [\n -83.70483398437499,\n 36.84446074079564\n ],\n [\n -81.463623046875,\n 37.39634613318923\n ],\n [\n -77.77221679687499,\n 39.825413103424786\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"35","issue":"6","noUsgsAuthors":false,"publicationDate":"2020-04-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Farwell, Laura S.","contributorId":274766,"corporation":false,"usgs":false,"family":"Farwell","given":"Laura","email":"","middleInitial":"S.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":833306,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wood, Petra B. 0000-0002-8575-1705 pbwood@usgs.gov","orcid":"https://orcid.org/0000-0002-8575-1705","contributorId":199090,"corporation":false,"usgs":true,"family":"Wood","given":"Petra","email":"pbwood@usgs.gov","middleInitial":"B.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":833305,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dettmers, Randy","contributorId":48534,"corporation":false,"usgs":true,"family":"Dettmers","given":"Randy","affiliations":[],"preferred":false,"id":833433,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brittingham, Margaret C.","contributorId":131143,"corporation":false,"usgs":false,"family":"Brittingham","given":"Margaret","email":"","middleInitial":"C.","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":833434,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70212525,"text":"70212525 - 2020 - Spatiotemporal seismic structure variations associated with the 2018 Kīlauea eruption based on temporary dense geophone arrays","interactions":[],"lastModifiedDate":"2020-08-19T14:15:31.661551","indexId":"70212525","displayToPublicDate":"2020-04-23T09:09:27","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Spatiotemporal seismic structure variations associated with the 2018 Kīlauea eruption based on temporary dense geophone arrays","docAbstract":"During the 2018 Kīlauea volcanic eruption, lava erupted from a series of new fissures in the lower East Rift Zone more than 30 km away from the summit through a dike intrusion. Between late May and early August, variations in the effusion rate at the persistent eruptive vent (Fissure 8) were observed following near‐daily summit caldera collapse events. Targeting the ongoing eruptive activity and the subsurface magma movement, we deployed a temporary dense seismic array. The observed time‐lapse changes in seismic velocity associated with the response of the summit collapse in three areas are presented in this study. The results show (1) clear spatially dependent co‐collapse velocity reductions across the newly‐intruded dike structure, (2) a gradual post‐collapse velocity increase near Fissure 8 correlated with the surge of magma supply, and (3) a gradual post‐collapse velocity increase on the summit likely associated with reservoir pressurization and crustal welding.","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2019GL086668","usgsCitation":"Wu, S., Lin, F., Farrell, J., Shiro, B., Karlstrom, L., Okubo, P.G., and Koper, K.D., 2020, Spatiotemporal seismic structure variations associated with the 2018 Kīlauea eruption based on temporary dense geophone arrays: Geophysical Research Letters, v. 47, no. 9, e2019GL086668, 10 p., https://doi.org/10.1029/2019GL086668.","productDescription":"e2019GL086668, 10 p.","ipdsId":"IP-112920","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":456971,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2019gl086668","text":"Publisher Index Page"},{"id":377647,"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 19.36427174188655\n ],\n [\n -155.19012451171875,\n 19.36427174188655\n ],\n [\n -155.19012451171875,\n 19.46141299683288\n ],\n [\n -155.33843994140625,\n 19.46141299683288\n ],\n [\n -155.33843994140625,\n 19.36427174188655\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"47","issue":"9","noUsgsAuthors":false,"publicationDate":"2020-05-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Wu, Sin-Mei","contributorId":175479,"corporation":false,"usgs":false,"family":"Wu","given":"Sin-Mei","email":"","affiliations":[{"id":13252,"text":"University of Utah","active":true,"usgs":false}],"preferred":false,"id":796689,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lin, Fan-Chi","contributorId":175478,"corporation":false,"usgs":false,"family":"Lin","given":"Fan-Chi","email":"","affiliations":[{"id":13252,"text":"University of Utah","active":true,"usgs":false}],"preferred":false,"id":796690,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Farrell, Jamie","contributorId":175477,"corporation":false,"usgs":false,"family":"Farrell","given":"Jamie","affiliations":[{"id":13252,"text":"University of Utah","active":true,"usgs":false}],"preferred":false,"id":796691,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":796692,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Karlstrom, Leif","contributorId":23048,"corporation":false,"usgs":false,"family":"Karlstrom","given":"Leif","affiliations":[],"preferred":false,"id":796693,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Okubo, Paul G. 0000-0002-0381-6051 pokubo@usgs.gov","orcid":"https://orcid.org/0000-0002-0381-6051","contributorId":2730,"corporation":false,"usgs":true,"family":"Okubo","given":"Paul","email":"pokubo@usgs.gov","middleInitial":"G.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":false,"id":796694,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Koper, Keith D.","contributorId":175489,"corporation":false,"usgs":false,"family":"Koper","given":"Keith","email":"","middleInitial":"D.","affiliations":[{"id":27579,"text":"Swiss Federal Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":796724,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70217223,"text":"70217223 - 2020 - The Missoula and Bonneville floods—A review of ice-age megafloods in the Columbia River basin","interactions":[],"lastModifiedDate":"2021-01-13T13:59:28.598323","indexId":"70217223","displayToPublicDate":"2020-04-22T07:51:58","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1431,"text":"Earth-Science Reviews","active":true,"publicationSubtype":{"id":10}},"title":"The Missoula and Bonneville floods—A review of ice-age megafloods in the Columbia River basin","docAbstract":"The Channeled Scabland of eastern Washington State, USA, brought megafloods to the scientific forefront. A 30,000-km2 landscape of coulees and cataracts carved into the region’s loess-covered basalt attests to overwhelming volumes of energetic water. The scarred landscape, garnished by huge boulder bars and far-travelled ice-rafted erratics, spurred J Harlen Bretz’s vigorously disputed flood hypothesis in the 1920s. First known as the Spokane flood, it was rebranded the Missoula flood once understood that the water came from glacial Lake Missoula, formed when the Purcell Trench lobe of the last-glacial Cordilleran ice sheet dammed the Clark Fork valley in northwestern Idaho with ice a kilometer thick. Bretz’s flood evidence in the once-remote Channeled Scabland, widely seen and elaborated by the 1950s, eventually swayed consensus for cataclysmic flooding. Missoula flood questions then turned to some that continue today: how many? when? how big? what routes? what processes?
The Missoula floods passed through eastern Washington by a multitude of valleys, coulees and scabland tracts, some contemporaneously, some sequentially. Which routings and their timing depended on the positions of various lobes of the multi-pronged Cordilleran ice sheet and the erosional development of the channels themselves. The first floods mostly followed the big bend of Columbia valley looping through north-central Washington. But the south-advancing Okanogan ice lobe soon blocked that path, forming long-lasting glacial Lake Columbia in the impounded Columbia valley. Missoula floods into this lake were diverted south out of the Columbia valley and into eastern Washington coulees and scabland tracts. At least four floods entered Moses Coulee, but then as the Okanogan lobe advanced over and blocked the head of that coulee, more eastern paths took the water, including Grand Coulee and the Telford-Crab-Creek and Cheney-Palouse scabland tracts. Flood routing also depended on the erosion of the coulees. At some point, headward erosion of upper Grand Coulee lowered the divide saddle between the west-running Columbia valley and the deep and wide Grand Coulee heading southwest. Still uncertain is when this happened and the consequences with respect to the stage and extent of glacial Lake Columbia and to flood access to the other, higher, flood routes. Downstream, all flood routes converged onto Pasco Basin, flowed through Wallula Gap and the Columbia River Gorge into the Pacific Ocean, following submarine canyons and depositing sediment layers on abyssal plains.
Stratigraphic studies indicate dozens—likely more than a hundred—separate Missoula floods during the last glacial period. Over the length of the flood route, backwater areas and depositional basins preserve multiple flood beds, many of which are separated by signs of time, including volcanic ash layers and soil development in subaerial environments; and varve-like beds and pelagic mud layers in lacustrine and marine settings. Evidence also comes from the glacial Lake Missoula basin, where stratigraphy indicates dozens of filling and emptying cycles. Varve counts in conjunction of radiocarbon dating and paleomagnetic secular variation show the repeated filling-and-release cycles of glacial Lake Missoula had intervals possibly as long as 100 years early in the lake’s history but diminished to just one or two years for the last few floods. This behavior accords with jökulhlaup-style floods released by subglacial drainage from a self-dumping ice-dammed lake. But not yet clear is whether such a mechanism applies to all the floods or if some emptied more cataclysmically as hypothesized by some.
Radiocarbon dating of sparse organic materials remains key to defining flood chronology but has been lately bolstered by analyses of terrestrial cosmogenic nuclides and optically stimulated luminescence. Varve counts and paleomagnetic secular variation studies help to define durations and intervals represented by sequences of flood beds. The ~16 ka Mount St. Helens Set S tephra is commonly interbedded within flood deposits, enabling correlation of deposits among sites. Tephra from the 13.7–13.4 ka eruption of Glacier Peak overlies all glacial Lake Missoula and Missoula flood deposits, defining an end time. Overall conclusions are that glacial Lake Missoula was extant and producing floods for at least 3–4 ky during 20–14 ka. At least ~75 floods preceded Mount St Helens Set S, followed by 30 or more after the tephra fall. Most floods entered glacial Lake Columbia, impounded by the Okanogan lobe, for 2–5 ky between about 18.5 and 15 ka. Glacial Lake Columbia outlived Lake Missoula by >200–400 yr but may have been born later since at least one flood came down the Columbia valley before the Okanogan ice lobe blocked the Columbia valley at 18.5–18 ka. The maximum extent of the Okanogan and Purcell Trench lobes, many Missoula floods, substantial erosion of upper Grand Coulee, and the widespread tephra falls from Mount St. Helens eruptions all happened about 17–15 ka. People, in the area since 16.6–15.3 ka, almost certainly witnessed the last of the Missoula floods and later large floods from other ice-dammed lakes in the Columbia River basin.
Quantitative flow analyses give peak discharge estimates and support understanding of erosional and depositional processes. The first flow assessments were simple cross-section calculations but recent assessments employ two-dimensional hydrodynamic models. The general finding is that emplacement of the maximum stage evidence requires about 20 million m3/s near the Lake Missoula outlet and about 5–15 million m3/s through Wallula Gap and downstream in the Columbia River Gorge. These hydraulic analyses raise still-unresolved questions regarding canyon erosion and possible additional water sources.
The large Pleistocene Bonneville flood entered the Columbia River system from the southeast from pluvial Lake Bonneville, the Pleistocene predecessor to Great Salt Lake in the eastern Great Basin. During the last glacial, the lake basin filled, covering >50,000 km2 with 10,400 km3 of water before reaching its maximum possible stage governed by Red Rock Pass, the lowest divide separating the basin from the Snake River basin to the north. The overtopping lake rapidly incised 108–125 m into the Red Rock Pass outlet, spilling half of its total lake volume. G.K. Gilbert described the essential sequence in the 1870s, but the flood was mostly forgotten until the late 1950s when Harold Malde linked the spectacular scabland topography and bouldery “melon gravel” on the Snake River Plain to the Lake Bonneville overflow. The Bonneville flood appears to have been a singular event at about 18 ka. No evidence of multiple or pre-last-glacial spillovers has yet been found. Its total volume was about twice that of a maximum Lake Missoula flood yet its peak discharge was ~1 million m3/s, less than a tenth of the largest Missoula floods. Its comparatively simple flow path and much steadier flow make the Bonneville flood ideal for new studies of erosional and depositional processes.
At least two floods seem to have passed down the Columbia valley after the last of the Missoula floods, including a large flood about ~14 ka likely from cataclysmic demise of the thinning Okanogan ice lobe dam impounding glacial Lake Columbia. Floods from earlier glacial ages left scant yet clear evidence in the Channeled Scabland and Columbia valley. But their source, timing, and magnitudes are little understood. Some deposits are paleomagnetically reversed, thus older than ~800 ka. Last-glacial floods and perhaps older ones affected the Snake River Plain, some likely sourced in lakes dammed by alpine glaciers in central Idaho.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.earscirev.2020.103181","usgsCitation":"O'Connor, J., Baker, V.R., Waitt, R.B., Smith, L.N., Cannon, C.M., George, D.L., and Denlinger, R.P., 2020, The Missoula and Bonneville floods—A review of ice-age megafloods in the Columbia River basin: Earth-Science Reviews, v. 208, 103181, 51 p., https://doi.org/10.1016/j.earscirev.2020.103181.","productDescription":"103181, 51 p.","ipdsId":"IP-117652","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":456992,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://archimer.ifremer.fr/doc/00624/73634/","text":"External Repository"},{"id":382128,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Oregon, Washington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.76171875,\n 45.73685954736049\n ],\n [\n -116.4111328125,\n 45.73685954736049\n ],\n [\n -116.4111328125,\n 48.31242790407178\n ],\n [\n -120.76171875,\n 48.31242790407178\n ],\n [\n -120.76171875,\n 45.73685954736049\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"208","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"O'Connor, Jim E. 0000-0002-7928-5883 oconnor@usgs.gov","orcid":"https://orcid.org/0000-0002-7928-5883","contributorId":140771,"corporation":false,"usgs":true,"family":"O'Connor","given":"Jim E.","email":"oconnor@usgs.gov","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":false,"id":808089,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baker, Victor R.","contributorId":201141,"corporation":false,"usgs":false,"family":"Baker","given":"Victor","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":808090,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Waitt, Richard B. 0000-0002-6392-5604 waitt@usgs.gov","orcid":"https://orcid.org/0000-0002-6392-5604","contributorId":2343,"corporation":false,"usgs":true,"family":"Waitt","given":"Richard","email":"waitt@usgs.gov","middleInitial":"B.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":808091,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, Larry N","contributorId":247679,"corporation":false,"usgs":false,"family":"Smith","given":"Larry","email":"","middleInitial":"N","affiliations":[{"id":49605,"text":"Montana Technological University","active":true,"usgs":false}],"preferred":false,"id":808092,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cannon, Charles M. 0000-0003-4136-2350 ccannon@usgs.gov","orcid":"https://orcid.org/0000-0003-4136-2350","contributorId":247680,"corporation":false,"usgs":true,"family":"Cannon","given":"Charles","email":"ccannon@usgs.gov","middleInitial":"M.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":808093,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"George, David L. 0000-0002-5726-0255 dgeorge@usgs.gov","orcid":"https://orcid.org/0000-0002-5726-0255","contributorId":3120,"corporation":false,"usgs":true,"family":"George","given":"David","email":"dgeorge@usgs.gov","middleInitial":"L.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":808094,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Denlinger, Roger P. 0000-0003-0930-0635 roger@usgs.gov","orcid":"https://orcid.org/0000-0003-0930-0635","contributorId":2679,"corporation":false,"usgs":true,"family":"Denlinger","given":"Roger","email":"roger@usgs.gov","middleInitial":"P.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":808095,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70209199,"text":"sim3455 - 2020 - Potentiometric surface and hydrologic conditions of the South Coast aquifer, Santa Isabel area, Puerto Rico, March–April, 2014","interactions":[],"lastModifiedDate":"2020-05-07T10:45:27.668534","indexId":"sim3455","displayToPublicDate":"2020-04-21T06:42:53","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":"3455","displayTitle":"Potentiometric Surface and Hydrologic Conditions of the South Coast Aquifer, Santa Isabel Area, Puerto Rico, March–April, 2014","title":"Potentiometric surface and hydrologic conditions of the South Coast aquifer, Santa Isabel area, Puerto Rico, March–April, 2014","docAbstract":"A potentiometric surface map of the South Coast aquifer near Santa Isabel, Puerto Rico, was created from data collected during a synoptic survey of groundwater levels at 55 wells from March 31 to April 17, 2014. Measured groundwater level values ranged from −22.8 to 185.4 feet above mean sea level. During the study period, cumulative rainfall of 0.65 inch was recorded in the study area. Measurements of instantaneous streamflow at 15 locations in streams and irrigation canals, and locations of irrigation ponds, provide additional information about the hydrologic setting. Results of the study indicate a cone of depression was present near the center and eastern parts of the Santa Isabel area of southern Puerto Rico, and a small, deeper cone of depression existed west of Santa Isabel and Rio Coamo. These cones of depression represent areas where the potentiometric surface was below mean sea level. The long-term persistence of such conditions could result in seawater intrusion and an increase in concentrations of total dissolved solids within the South Coast aquifer.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3455","collaboration":"Prepared in cooperation with the Puerto Rico Department of Natural and Environmental Resources","usgsCitation":"Ramos, F.A., and Santiago, A.A., 2020, Potentiometric surface and hydrologic conditions of the South Coast aquifer, Santa Isabel area, Puerto Rico, March–April, 2014: U.S. Geological Survey Scientific Investigations Map 3455, 4 p., 1 sheet, https://doi.org/10.3133/sim3455.","productDescription":"Pamphlet: vi, 4 p.; Sheet: 35.68 inches x 28.17 inches; Data Release","numberOfPages":"14","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-064406","costCenters":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"links":[{"id":374025,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7NS0STQ","text":"USGS data release","linkHelpText":"Data and shapefiles for the potentiometric surface of the South Coast aquifer and hydrologic conditions in the Santa Isabel area, Puerto Rico, March–April 2014"},{"id":374019,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3455/coverthb.jpg"},{"id":374021,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3455/sim3455.pdf","text":"Pamphlet","size":"350 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3455 Pamphlet"},{"id":374022,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3455/sim3455_sheet.pdf","text":"Sheet 1—","size":"4.07 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3455 Sheet","linkHelpText":"Potentiometric Surface and Hydrologic Conditions of the South Coast Aquifer, Santa Isabel Area, Puerto Rico, March–April, 2014"}],"country":"United States","state":"Puerto Rico","otherGeospatial":"Santa Isabel Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -66.4779281616211,\n 17.932682319509986\n ],\n [\n -66.29854202270508,\n 17.932682319509986\n ],\n [\n -66.29854202270508,\n 18.029995361346103\n ],\n [\n -66.4779281616211,\n 18.029995361346103\n ],\n [\n -66.4779281616211,\n 17.932682319509986\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Caribbean-Florida Water Science Center
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 33559
Vertical and horizontal components of GNSS displacements in the Long Valley Caldera and adjacent Sierra Nevada range show a clear correlation with hydrological trends at both multiyear and seasonal time scales. We observe a clear vertical and horizontal seasonal deformation pattern primarily attributable to the solid earth response to hydrological surface loading at large-to-regional (Sierra Nevada range) scales. Several GNSS sites, located at the eastern edge of the Sierra Nevada along the southwestern rim of Long Valley Caldera, also show significant horizontal deformation that cannot be explained by elastic deformation from surface loading. Due to the location of these sites and the strong correlation between their horizontal displacements and spring discharge, we hypothesize that this deformation reflects poroelastic processes related to snowmelt runoff water infiltrating into the Sierra Nevada slopes around Long Valley Caldera. Interestingly, this is also an area where water infiltrates to feed the local hydrothermal system, and where snowmelt-induced earthquake swarms have been recently detected.
The bedrock geology of the Mount Ascutney 7.5- x 15-minute quadrangle consists of highly deformed and metamorphosed Mesoproterozoic through Devonian metasedimentary and meta-igneous rocks intruded by rocks of the Mesozoic White Mountain Igneous Suite. In the west, Mesoproterozoic gneisses of the Mount Holly Complex are the oldest rocks and form the northeastern flank of the Chester dome. The allochthonous Cambrian through Ordovician rocks include the Moretown and Cram Hill Formations and the North River Igneous Suite; these rocks structurally overlie the Chester dome along the Keyes Mountain thrust fault. Silurian and Devonian metasedimentary and metavolcanic rocks of the Connecticut Valley trough (CVT) unconformably overlie the pre-Silurian rocks. The easternmost extent of the CVT in New Hampshire is exposed in the Meriden antiform. Ordovician to Silurian and Devonian metasedimentary rocks of the Bronson Hill anticlinorium structurally overlie the CVT along the Monroe thrust fault. The oldest part of the Bronson Hill anticlinorium, called the Bronson Hill arc, consists of Ordovician metamorphosed volcanic, plutonic, and sedimentary rocks of the Ammonoosuc Volcanics, the Partridge Formation, and the Oliverian Plutonic Suite. The rocks of the Bronson Hill arc may be partly correlative with the pre-Silurian rocks above the Chester dome and are exposed in two fault-bounded structural belts (Cornish City and Claremont belts) and in the Sugar River dome. Collectively, these belts form the regional Orfordville anticlinorium, Hardscrabble synclinorium, and the western part of the broader Bronson Hill anticlinorium in western New Hampshire. Silurian to Devonian metasedimentary rocks of the Clough Quartzite, and Fitch and Littleton Formations unconformably overlie the rocks of the Bronson Hill arc. Devonian granitic and pegmatitic dikes and sills of the New Hampshire Plutonic Suite intruded previously deformed rocks. Post-tectonic Cretaceous plutonic and volcanic rocks of the Ascutney Mountain Intrusive Complex underlie Mount Ascutney. Because of the historically significant scientific research, and its prominence in the landscape, Mount Ascutney is commonly regarded as Vermont’s most famous volcano.
The bedrock geology was mapped to study the tectonic history of the area and to provide a framework for ongoing characterization of the bedrock of Vermont and New Hampshire. This Scientific Investigations Map of the Mount Ascutney 7.5- x 15-minute quadrangle consists of sheets 1 and 2 as well as a geographic information system (GIS) database that includes bedrock geologic units, faults, outcrops, structural geologic information, geochemistry, and photographs. Sheet 1 of the report includes a bedrock geologic map, a correlation of map units, and a description of map units. Sheet 2 includes a discussion of the geology, references, three cross sections from the geologic map on sheet 1, igneous rock geochemistry results of the main map units from the Mount Ascutney stock, a tectonic map showing major structural features, and a structural domain map showing the orientation and distribution of brittle features.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3440","collaboration":"Prepared in cooperation with the State of Vermont, Vermont Agency of Natural Resources, Vermont Geological Survey; State of New Hampshire, Department of Environmental Services, New Hampshire Geological Survey; and the National Park Service","usgsCitation":"Walsh, G.J., Valley, P.M., Thompson, P.J., Ratcliffe, N.M., Proctor, B.P., and Sicard, K.R., 2020, Bedrock geologic map of the Mount Ascutney 7.5- x 15-minute quadrangle, Windsor County, Vermont, and Sullivan County, New Hampshire (ver. 1.1, April 2020): U.S. Geological Survey Scientific Investigations Map 3440, 2 sheets, scale 1:24,000, https://doi.org/10.3133/sim3440.","productDescription":"2 Sheets: 61.00 x 40.81 inches and 57.00 x 40.50 inches; Read Me; Spatial Data; Metadata; Companion Files","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-090096","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":374082,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sim/3440/versionHist.txt","text":"Version History","size":"2.17 KB","linkFileType":{"id":2,"text":"txt"}},{"id":374079,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3440/coverthb4.jpg"},{"id":374081,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3440/sim3440_sheet2.pdf","text":"Sheet 2","size":"27.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":""},{"id":374080,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3440/sim3440_sheet1.pdf","text":"Sheet 1","size":"26.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3440"},{"id":374083,"rank":5,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sim/3440/sim3440_readme.txt","text":"Read Me","size":"13.1 KB","linkFileType":{"id":2,"text":"txt"}},{"id":374087,"rank":9,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sim/3440/sim3440_MountAscutney_openaccess.zip","text":"Open Access","size":"6.09 MB","linkFileType":{"id":6,"text":"zip"}},{"id":374086,"rank":8,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sim/3440/sim3440_MountAscutney_metadata.zip","text":"Metadata","size":"366 KB","linkFileType":{"id":6,"text":"zip"}},{"id":374085,"rank":7,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/sim/3440/sim3440_MountAscutney_database.zip","text":"Database","size":"6.58 MB","linkFileType":{"id":6,"text":"zip"}},{"id":374084,"rank":6,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sim/3440/sim3440_MountAscutney_basemap.zip","text":"Base Map","size":"43.7 MB","linkFileType":{"id":6,"text":"zip"}},{"id":374088,"rank":10,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sim/3440/sim3440_MountAscutney_photos.zip","text":"Photos","size":"577 MB","linkFileType":{"id":6,"text":"zip"}}],"country":"United States","state":"New Hampshire, Vermont","county":"Sullivan County, Windsor County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -72.5,\n 43.375\n ],\n [\n -72.25,\n 43.375\n ],\n [\n -72.25,\n 43.5\n ],\n [\n -72.5,\n 43.5\n ],\n [\n -72.5,\n 43.375\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"","edition":"Version 1.1: April 2020; Version 1.0: April 2020","contact":"Florence Bascom Geoscience Center
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Reston, VA 20192
Manganese (Mn) plays a critical role in river-water quality because Mn-oxides serve as sorption sites for contaminant metals. The aim of this study is to understand the seasonal cycling of Mn in an alpine streambed that experiences large spring snowmelt events and the potential responses to changes in snowmelt timing and magnitude. To address this goal, annual variations in river-water/groundwater interaction and Mn(aq) transport were measured and modeled in the bed of East River, Colorado, USA. In observations and numerical models, oxygenated river water containing dissolved organic carbon (DOC) mixes with groundwater rich in Mn(aq) in the streambed. The mixing depth increases during spring snowmelt when river discharge increases, leading to a greater DOC supply to the hyporheic zone and net respiration of Mn-oxides, despite an enhanced supply of oxygen. As groundwater upwelling resumes during the subsequent baseflow period, Mn(aq)-rich groundwater mixes with oxygenated river water, resulting in net accumulation of Mn-oxides until the bed freezes in winter. To explore potential responses of Mn transport to different climate-induced hydrological regimes, three hydrograph scenarios were numerically modeled (historic, low-snow, and storm) for the Rocky Mountain region. In a warming climate, Mn(aq) export to the river decreases, and Mn(aq) oxidation is favored in the upper streambed sediments over more of the year. One important implication is that the streambed may have an increased sorption capacity for metals over more of the year, leading to potential changes in river-water quality.
","language":"English","publisher":"Springer","doi":"10.1007/s10040-020-02146-6","usgsCitation":"Bryant, S., Sawyer, A., Briggs, M., Saup, C., Nelson, A.R., Wilkins, M.J., Christensen, J.R., and Williams, K.H., 2020, Seasonal manganese transport in the hyporheic zone of a snowmelt-dominated river (East River, Colorado): Hydrogeology Journal, v. 28, p. 1323-1341, https://doi.org/10.1007/s10040-020-02146-6.","productDescription":"19 p.","startPage":"1323","endPage":"1341","ipdsId":"IP-115069","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":385333,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"East River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.95238709449768,\n 38.92190699243362\n ],\n [\n -106.94936156272888,\n 38.92190699243362\n ],\n [\n -106.94936156272888,\n 38.923893566458055\n ],\n [\n -106.95238709449768,\n 38.923893566458055\n ],\n [\n -106.95238709449768,\n 38.92190699243362\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"28","noUsgsAuthors":false,"publicationDate":"2020-04-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Bryant, S.","contributorId":222764,"corporation":false,"usgs":false,"family":"Bryant","given":"S.","email":"","affiliations":[{"id":36630,"text":"Ohio State University","active":true,"usgs":false}],"preferred":false,"id":814777,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sawyer, A.","contributorId":222761,"corporation":false,"usgs":false,"family":"Sawyer","given":"A.","email":"","affiliations":[{"id":36630,"text":"Ohio State University","active":true,"usgs":false}],"preferred":false,"id":814778,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Briggs, Martin A. 0000-0003-3206-4132","orcid":"https://orcid.org/0000-0003-3206-4132","contributorId":257637,"corporation":false,"usgs":true,"family":"Briggs","given":"Martin A.","affiliations":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true}],"preferred":true,"id":814779,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Saup, C.","contributorId":222763,"corporation":false,"usgs":false,"family":"Saup","given":"C.","email":"","affiliations":[{"id":36630,"text":"Ohio State University","active":true,"usgs":false}],"preferred":false,"id":814780,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nelson, A. R","contributorId":193402,"corporation":false,"usgs":false,"family":"Nelson","given":"A.","email":"","middleInitial":"R","affiliations":[],"preferred":false,"id":814781,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wilkins, M. J.","contributorId":176779,"corporation":false,"usgs":false,"family":"Wilkins","given":"M.","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":814782,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Christensen, J. R.","contributorId":204686,"corporation":false,"usgs":false,"family":"Christensen","given":"J.","email":"","middleInitial":"R.","affiliations":[{"id":36974,"text":"U.S. Environmental Protection Agency, National Exposure Research Laboratory, Las Vegas, NV","active":true,"usgs":false}],"preferred":false,"id":814783,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Williams, K. H.","contributorId":176777,"corporation":false,"usgs":false,"family":"Williams","given":"K.","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":814784,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70208957,"text":"sim3451 - 2020 - Geologic map of the Homestake Reservoir 7.5′ quadrangle, Lake, Pitkin, and Eagle Counties, Colorado","interactions":[],"lastModifiedDate":"2020-04-30T13:51:00.671496","indexId":"sim3451","displayToPublicDate":"2020-04-17T11:50:00","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":"3451","title":"Geologic map of the Homestake Reservoir 7.5′ quadrangle, Lake, Pitkin, and Eagle Counties, Colorado","docAbstract":"The Homestake Reservoir 7.5' quadrangle lies at the northwestern end of the Upper Arkansas Valley, and headwaters of the Arkansas River, and the Roaring Fork, Fryingpan, and Eagle Rivers of the Colorado River system. The quadrangle lies within tectonic provinces of the 1.4 giga-annum (Ga) Picuris orogeny and includes the late Paleozoic Ancestral Rockies, Late Cretaceous-Paleocene Laramide orogeny, Oligocene-to-Miocene and Pliocene? volcanism, and Miocene to the present Rio Grande rift extensional tectonics. In the eastern half of the quadrangle, high-angle, east-dipping, Neogene normal faults displace Proterozoic rocks, and locally Miocene-to-Pliocene? volcanic rocks. Many quartz veins and hydrothermally altered zones are exposed along the eastern flank of the quadrangle, indicative of the multiple tectonic episodes the region has experienced. The main intent of the map is to unravel the structural complexity by partitioning the structures and volcanism within the appropriate geologic interval. This ultimately permits accurate identification of geomorphic features suitable for chronologies related to landscape evolution studies, seismic and other natural hazard identification, ground and surface water modeling, and paleoclimatic studies. Within the western half of the quadrangle, Mesoproterozoic and Paleoproterozoic igneous and metamorphic rocks of 1.4 Ga St. Kevin Granite and 1.8–1.7 Ga Biotite gneiss and schist, respectively, are uplifted along the generally east-dipping, high-angle Sawatch fault system. In the northwest portion of the quadrangle, strands of the Homestake shear zone have been mapped, dated and assigned to the 1.4 Ga Picuris orogeny of northern New Mexico. 10Be and 26Al cosmogenic nuclide ages of the youngest glacial deposits indicate a last glacial maximum age of about 22–21 kilo-annum (ka) and complete deglaciation by about 14 kilo-annum, supported by chronologic studies in adjacent drainages. The Turquoise Lake impounding lateral and terminal moraine complex was deposited during late Pleistocene glacial maximum ~22–21 ka. No late Pleistocene tectonic activity is apparent within the quadrangle.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/sim3451","collaboration":"","usgsCitation":"Ruleman, C.A., Frothingham, M.G., Brandt, T.R., Shaw, C.A., Caffee, M.W., Brugger, K.A., and Goehring, B.M., 2020, Geologic map of the Homestake Reservoir 7.5' quadrangle, Lake, Pitkin, and Eagle Counties, Colorado: U.S. Geological Survey Scientific Investigations Map 3451, scale 1:24,000, https://doi.org/10.3133/sim3451.","productDescription":"3 Sheets: 54.00 x 48.50 inches; Read Me; Data Release","onlineOnly":"Y","ipdsId":"IP-088811","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":373759,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3451/coverthb.jpg"},{"id":373763,"rank":5,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sim/3451/sim3451_ReadMe.txt","text":" Read Me","size":"8.0 kB","linkFileType":{"id":2,"text":"txt"},"description":"SIM 3451 read me"},{"id":373762,"rank":4,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3451/sim3451_georeferenced.pdf","text":"Geologic Map of the Homestake Reservoir 7.5' Quadrangle, Eagle, Lake, and Pitkin Counties, Colorado","size":"165 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3451 georeferenced","linkHelpText":"(interactive georeferenced map with the shaded relief and topographic base layers)"},{"id":373764,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ON6QBE","text":"USGS data release","linkHelpText":"Data release for Geologic Map of the Homestake Reservoir 7.5' quadrangle, Lake, Pitkin, and Eagle Counties, Colorado"},{"id":373760,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3451/sim3451.pdf","text":"Geologic Map of the Homestake Reservoir 7.5' Quadrangle, Eagle, Lake, and Pitkin Counties, Colorado","size":"72.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3451 print quality","linkHelpText":"(print quality)"},{"id":373761,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3451/sim3451_hillshade_base.pdf","text":"Geologic Map of the Homestake Reservoir 7.5' Quadrangle, Eagle, Lake, and Pitkin Counties, Colorado","size":"54.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3451 hillshade base","linkHelpText":"(map with the shaded relief base)"}],"country":"United States","state":"Colorado","county":"Eagle County, Lake County, Pitkin County","otherGeospatial":"Homestake Reservoir","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.5,\n 39.375\n ],\n [\n -106.375,\n 39.375\n ],\n [\n -106.375,\n 39.25\n ],\n [\n -106.5,\n 39.25\n ],\n [\n -106.5,\n 39.375\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Geosciences and Environmental Change Science Center
U.S. Geological Survey
Box 25046, MS-980
Denver, CO 80225-0046
The amounts of trace metals and metalloids that have been introduced into aquatic ecosystems due to anthropogenic activities have increased in recent decades. Some of these elements like mercury are easily transferred from one trophic level to another and can accumulate to toxic quantities in organisms at the top of aquatic food webs. For this reason, seabirds like the Eastern brown pelican (Pelecanus occidentalis carolinensis) are susceptible to heavy metal and metalloid toxicity and may warrant periodic monitoring. Mercury, cadmium, copper, arsenic and selenium were measured in the feathers of adult brown pelicans and chicks in several breeding colonies (Shamrock Island, Chester Island, Marker 52 Island, North Deer Island, Raccoon Island, Felicity Island, Gaillard Island, Audubon Island, and Ten Palms Island) in the Northern Gulf of Mexico. Overall, most chicks and adults examined had mercury levels in feathers that were below the concentration range in which birds show symptoms of mercury toxicity. However, chicks in the Audubon Island and Ten Palms Island colonies displayed mercury levels that were 3 times higher than values observed in 5 other colonies. In addition, several adults and chicks displayed selenium concentrations that are above what is considered safe for birds. Cadmium quantities in feathers were below levels that trigger toxicity in birds. Similarly, arsenic measurements were at quantities below the average of what has been reported for birds living in contaminated sites. Finally, we identify pelican breeding colonies that may warrant monitoring due to elevated levels of contaminants.
","language":"English","publisher":"Springer","doi":"10.1007/s10661-020-8237-y","usgsCitation":"Ndu, U., Lamb, J., Janssen, S., Rossi, R., Satgé, Y., and Jodice, P.G., 2020, Mercury, cadmium, copper, arsenic, and selenium measurements in the feathers of adult eastern brown pelicans (Pelecanus occidentalis carolinensis) and chicks in multiple breeding grounds in the northern Gulf of Mexico: Environmental Monitoring and Assessment, v. 192, 286, 9 p., https://doi.org/10.1007/s10661-020-8237-y.","productDescription":"286, 9 p.","ipdsId":"IP-113634","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":396027,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alabama, Florida, Louisiana,Texas","otherGeospatial":"Audubon Island, Chester Island, Felicity Island, Gaillard Island, Marker 52 Island, North Deer Island, Racoon Island,, Shamrock Island,Ten Palms Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -99.49218749999999,\n 23.483400654325642\n ],\n [\n -84.814453125,\n 23.483400654325642\n ],\n [\n -84.814453125,\n 30.675715404167743\n ],\n [\n -99.49218749999999,\n 30.675715404167743\n ],\n [\n -99.49218749999999,\n 23.483400654325642\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"192","noUsgsAuthors":false,"publicationDate":"2020-04-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Ndu, U.","contributorId":279402,"corporation":false,"usgs":false,"family":"Ndu","given":"U.","email":"","affiliations":[{"id":6747,"text":"Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":834926,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lamb, J. S.","contributorId":270975,"corporation":false,"usgs":false,"family":"Lamb","given":"J. S.","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":834927,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Janssen, Sarah E. 0000-0003-4432-3154","orcid":"https://orcid.org/0000-0003-4432-3154","contributorId":210991,"corporation":false,"usgs":true,"family":"Janssen","given":"Sarah E.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":834928,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rossi, R.","contributorId":279403,"corporation":false,"usgs":false,"family":"Rossi","given":"R.","email":"","affiliations":[{"id":57254,"text":"Texas A & M Unversity","active":true,"usgs":false}],"preferred":false,"id":834929,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Satgé, Y. G.","contributorId":265430,"corporation":false,"usgs":false,"family":"Satgé","given":"Y. G.","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":834930,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jodice, Patrick G.R. 0000-0001-8716-120X","orcid":"https://orcid.org/0000-0001-8716-120X","contributorId":219852,"corporation":false,"usgs":true,"family":"Jodice","given":"Patrick","middleInitial":"G.R.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":834931,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70218846,"text":"70218846 - 2020 - Fluorescence spectroscopy of ancient sedimentary organic matter via confocal laser scanning microscopy (CLSM)","interactions":[],"lastModifiedDate":"2021-03-17T11:55:19.545882","indexId":"70218846","displayToPublicDate":"2020-04-15T06:49:02","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2033,"text":"International Journal of Coal Geology","active":true,"publicationSubtype":{"id":10}},"title":"Fluorescence spectroscopy of ancient sedimentary organic matter via confocal laser scanning microscopy (CLSM)","docAbstract":"Fluorescence spectroscopy via confocal laser scanning microscopy (CLSM) was used to analyze ancient sedimentary organic matter, including Tasmanites microfossils in Devonian shale and Gloecapsomorpha prisca (G. prisca) in Ordovician kukersite from North American basins. We examined fluorescence emission as a function of excitation laser wavelength, sample orientation, and with respect to location within individual organic entities and in transects across bedded organic matter. Results from spectral scans of the same field of view in Tasmanites with different laser lines showed progressive red-shift in emission maxima with longer excitation wavelengths. This result indicates steady-state Tasmanites fluorescence emission is an overlapping combination of emission from multiple fluorophore functions. Stokes shift decreased with increasing excitation wavelength, further suggesting the presence of multiple fluorophore functions with different S1 → S0 transition energies. This observation also indicates that at longer excitation wavelengths, less absorbed light energy is dissipated via collisional transfer than at shorter excitation wavelengths and may suggest fewer polar functions are preferentially absorbing. Confirming earlier results, emission spectra observed from high fluorescence intensity regions (fold apices) in individual Tasmanites are blue-shifted relative to emission from other locations in the same microfossil. We suggest high intensity emission is from photoselective alignment of polarized excitation with the fluorophore absorption and emission transition moment. The blue shift observed in regions of high intensity emission may be due to relative absence or realignment of polar species, e.g., bridging ether or ester functions, although variations in O abundance could not be confirmed with preliminary time-of-flight secondary ion mass spectrometry (TOF-SIMS) analysis. Tasmanites occurring in consolidated sediments are flattened from original spherical morphology and, in optical microscopy, this burial deformation results in generally parallel extinction (strain-influenced) and positive elongation. The deformation also induces fluorescence anisotropy observed as variations in emission wavelength when individual Tasmanites are measured from their long axis parallel to bedding, whereas this effect is absent in bedding-normal view. Transects from G. prisca-rich source layers into adjacent reservoir layers show decrease in fluorescence intensity and spectral red-shift (increase in full-width half-maximum with increasing red portion of the half-width). These results may suggest an increase in fluorescence quenching across the source-to-reservoir transition zone, consistent with an increase in aromaticity following petroleum expulsion and migration. These observations are supported by increasing reflectance values measured across similar micro-scale transects. Our results highlight the applicability of CLSM as a broad and under-utilized approach for the characterization of sedimentary organic matter and are discussed with perspective toward petroleum processes and thermal indices research.
As atmospheric dust deposition continues to increase across the southwestern United States, it has the potential to alter ecosystem productivity and structure by delivering nutrients, base cations, and pollutants to remote mountain sites. Due to the sparse distribution of dust monitoring sites, open questions remain about the spatial and temporal variability of dust fluxes and composition across mountainous terrain. We present a 1 year (November 2017 to November 2018) record of seasonal dust fluxes and composition from an elevation transect across the Colorado Front Range extending from the urban plains to the remote alpine. At all nine sites, dust was enriched in the essential nutrient phosphorus and the metals copper, zinc, lead, and cadmium, elements that are enriched in dust deposited at sites across the Rocky Mountain West. We observed a seasonal pattern in dust composition, with the highest concentrations of zinc and cadmium during the summer, when back trajectory modeling suggested a greater contribution of dust from local urban and agricultural regions to the east of the collection sites. During the summer, there was also a trend of higher dust fluxes at lower elevations; dust fluxes ranged from 18.9 ± 0.1 g m−2 yr−1 on the plains to 5.9 ± 0.2 g m−2 yr−1 in the alpine. Our results suggest that urban and agricultural land east of the Colorado Front Range is an important source of nutrients and pollutants to all elevations of the mountain range.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2019JF005436","usgsCitation":"Heindel, R.C., Putman, A.L., Murphy, S.F., Repert, D.A., and Hinckley, E.S., 2020, Atmospheric dust deposition varies by season and elevation in the Colorado Front Range, USA: Journal of Geophysical Research: Earth Surface, v. 125, no. 5, e2019JF005436, 18 p., https://doi.org/10.1029/2019JF005436.","productDescription":"e2019JF005436, 18 p.","ipdsId":"IP-117827","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":375411,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Colorado Front Range","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.578369140625,\n 39.65645604812829\n ],\n [\n -104.5458984375,\n 39.65645604812829\n ],\n [\n -104.5458984375,\n 40.463666324587685\n ],\n [\n -106.578369140625,\n 40.463666324587685\n ],\n [\n -106.578369140625,\n 39.65645604812829\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"125","issue":"5","noUsgsAuthors":false,"publicationDate":"2020-05-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Heindel, Ruth C. 0000-0001-6292-2076","orcid":"https://orcid.org/0000-0001-6292-2076","contributorId":225133,"corporation":false,"usgs":false,"family":"Heindel","given":"Ruth","email":"","middleInitial":"C.","affiliations":[{"id":36621,"text":"University of Colorado","active":true,"usgs":false}],"preferred":false,"id":790482,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Putman, Annie L. 0000-0002-9424-1707","orcid":"https://orcid.org/0000-0002-9424-1707","contributorId":225134,"corporation":false,"usgs":true,"family":"Putman","given":"Annie","email":"","middleInitial":"L.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":790483,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Murphy, Sheila F. 0000-0002-5481-3635 sfmurphy@usgs.gov","orcid":"https://orcid.org/0000-0002-5481-3635","contributorId":1854,"corporation":false,"usgs":true,"family":"Murphy","given":"Sheila","email":"sfmurphy@usgs.gov","middleInitial":"F.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":790484,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Repert, Deborah A. 0000-0001-7284-1456 darepert@usgs.gov","orcid":"https://orcid.org/0000-0001-7284-1456","contributorId":2578,"corporation":false,"usgs":true,"family":"Repert","given":"Deborah","email":"darepert@usgs.gov","middleInitial":"A.","affiliations":[{"id":38175,"text":"Toxics Substances Hydrology Program","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true}],"preferred":true,"id":790485,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hinckley, Eve-Lyn S.","contributorId":181894,"corporation":false,"usgs":false,"family":"Hinckley","given":"Eve-Lyn","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":790486,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70206370,"text":"ofr20191115 - 2020 - A decision framework to analyze tide-gate options for restoration of the Herring River Estuary, Massachusetts","interactions":[],"lastModifiedDate":"2024-03-04T19:21:20.997009","indexId":"ofr20191115","displayToPublicDate":"2020-04-10T09:00:00","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":"2019-1115","displayTitle":"A Decision Framework to Analyze Tide-Gate Options for Restoration of the Herring River Estuary, Massachusetts","title":"A decision framework to analyze tide-gate options for restoration of the Herring River Estuary, Massachusetts","docAbstract":"The collective set of decisions involved with the restoration of degraded wetlands is often more complex than considering only ecological responses and outcomes. Restoration is commonly driven by a complex interaction of social, economic, and ecological factors representing the mandate of resource stewards and the values of stakeholders. The authors worked with the Herring River Restoration Committee (HRRC) to develop a decision framework to understand the implications of complex tradeoffs and to guide decision making for the restoration of the 1,100-acre Herring River estuary within Cape Cod National Seashore, which has been restricted from tidal influence for more than 100 years. The HRRC represents decision maker and stakeholder interests in the restoration process. For a 25-year planning horizon, decisions involve the rate at which newly constructed water-control structures allow tidal exchange, and the timing and location of implementing numerous secondary management options. Decisions affect multiple stakeholders, including residents of two adjacent towns who value the watershed for numerous benefits and whose economy relies on seasonal activities and aquaculture. System response to management decisions is characterized by a high degree of uncertainty and risk with positive and negative outcomes possible. Decision policies will affect biophysical (for example, sediment transport, discharge of fecal coliform bacteria) and ecological (for example, vegetation response, fish passage, effects on shellfish) processes, as well as socioeconomic interests (for example, effects on property, viewscapes, recreation). The framework provides a structured approach for evaluating tradeoffs among multiple objectives (ecological and social) while appropriately characterizing relevant uncertainties and accounting for levels of risk tolerances and the values of decision makers and stakeholders. Consequences of tide-gate management options are predicted using a range of methods from quantitative physical process models to elicited expert judgement. The decision framework is presented, and the software developed to implement the tradeoff analysis is introduced. The results from an initial prototype analysis using a software application developed for analyses of tradeoffs and of sensitivity of the decision to risk and uncertainty are presented. The next step is to use the decision-support application to analyze options using improved predictions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191115","collaboration":"Prepared in cooperation with National Park Service and U.S. Fish and Wildlife Service","usgsCitation":"Smith, D.R., Eaton, M.J., Gannon, J.J., Smith, T.P., Derleth, E.L., Katz, J., Bosma, K.F., and Leduc, E., 2020, A decision framework to analyze tide-gate options for restoration of the Herring River Estuary, Massachusetts: U.S. Geological Survey Open-File Report 2019–1115, 42 p., https://doi.org/10.3133/ofr20191115.","productDescription":"viii, 42 p.","numberOfPages":"54","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-101813","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":373779,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1115/ofr20191115.pdf","text":"Report","size":"3.52 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1115"},{"id":373778,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1115/coverthb.jpg"}],"country":"United States","state":"Massachusetts","otherGeospatial":"Herring River Estuary","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -70.07286071777344,\n 41.92961289444422\n ],\n [\n -70.02462387084961,\n 41.92961289444422\n ],\n [\n -70.02462387084961,\n 41.96357478222518\n ],\n [\n -70.07286071777344,\n 41.96357478222518\n ],\n [\n -70.07286071777344,\n 41.92961289444422\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Eastern Ecological Science Center
U.S. Geological Survey
11649 Leetown Road
Kearneysville, WV 25430
Groundwater in eastern Abu Dhabi in the United Arab Emirates is an important resource that is widely used for irrigation and domestic supplies in rural areas. The U.S. Geological Survey and the Environment Agency—Abu Dhabi cooperated on an investigation to integrate existing hydrogeologic information and to answer questions about regional groundwater resources in Abu Dhabi by developing a numerical groundwater flow model based on MODFLOW–2005 software. The groundwater flow model developed in this investigation provides an improved understanding of groundwater conditions in the eastern region of the Emirate of Abu Dhabi. The flow model simulates steady-state predevelopment conditions from before the rapid growth of modern pumping in the 1980s and was calibrated with 1,342 groundwater-level observations by use of automated and manual calibration techniques. The calibrated model provides good accuracy, with a mean error of 0.50 meters and a standard error of 5.92 meters for simulated groundwater levels. The results of the regional water budget simulation show that gap recharge, which is groundwater inflow through mountain-front gap alluvium, is the greatest source of water to the aquifer. In the base simulation scenario, gap recharge represents 80 percent of total inflow (119,470 of 149,403 cubic meters per day) and the greatest outflow from the aquifer is from evapotranspiration (93 percent of total outflow). Model scenario and sensitivity results reveal a need for data that more thoroughly and more accurately describe aquifer hydraulic conductivity, inflow to the aquifer from the Oman Mountains, and recharge from precipitation on the piedmont. Additional long-term aquifer pumping test observations would improve understanding of aquifer hydraulic conductivity, which would also improve model accuracy. Future studies can modify the model to understand the effect of land-use change and water use on groundwater supplies and simulate more complex groundwater flow conditions in a predictive mode.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185158","collaboration":"Prepared in cooperation with the Environment Agency—Abu Dhabi","usgsCitation":"Eggleston, J.R., Mack, T.J., Imes, J.L., Kress, W., Woodward, D.W., and Bright, D.J., 2020, Hydrogeologic framework and simulation of predevelopment groundwater flow, eastern Abu Dhabi Emirate, United Arab Emirates: U.S. Geological Survey Scientific Investigations Report 2018–5158, 48 p., https://doi.org/10.3133/sir20185158.","productDescription":"Report: viii, 48 p.; Data Release","numberOfPages":"60","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-088658","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":373295,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5158/coverthb.jpg"},{"id":373296,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5158/sir20185158.pdf","text":"Report","size":"6.17 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5158"},{"id":373297,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ZWZISB","text":"USGS data release","description":"USGS data release","linkHelpText":"MODFLOW-2005 Groundwater Flow Model to Simulate Predevelopment Groundwater Flow in the Eastern Abu Dhabi Emirate, United Arab Emirates"}],"country":"United Arab Emirates","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[51.57952,24.2455],[51.75744,24.29407],[51.79439,24.01983],[52.57708,24.17744],[53.40401,24.15132],[54.008,24.12176],[54.69302,24.79789],[55.43902,25.43915],[56.07082,26.05546],[56.26104,25.71461],[56.39685,24.92473],[55.88623,24.92083],[55.80412,24.2696],[55.98121,24.13054],[55.52863,23.9336],[55.52584,23.52487],[55.23449,23.11099],[55.20834,22.70833],[55.0068,22.49695],[52.00073,23.00115],[51.61771,24.01422],[51.57952,24.2455]]]},\"properties\":{\"name\":\"United Arab Emirates\"}}]}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532